The clustering evolution of distant red galaxies in the GOODS-MUSIC sample

NASA Astrophysics Data System (ADS)

Grazian, A.; Fontana, A.; Moscardini, L.; Salimbeni, S.; Menci, N.; Giallongo, E.; de Santis, C.; Gallozzi, S.; Nonino, M.; Cristiani, S.; Vanzella, E.

2006-07-01

Aims.We study the clustering properties of Distant Red Galaxies (DRGs) to test whether they are the progenitors of local massive galaxies. Methods.We use the GOODS-MUSIC sample, a catalog of ~3000 Ks-selected galaxies based on VLT and HST observation of the GOODS-South field with extended multi-wavelength coverage (from 0.3 to 8~μm) and accurate estimates of the photometric redshifts to select 179 DRGs with J-Ks≥ 1.3 in an area of 135 sq. arcmin.Results.We first show that the J-Ks≥ 1.3 criterion selects a rather heterogeneous sample of galaxies, going from the targeted high-redshift luminous evolved systems, to a significant fraction of lower redshift (1

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

PubMed Central

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

2009-01-01

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

[Design of the National Surveillance of Nutritional Indicators (MONIN), Peru 2007-2010].

PubMed

Campos-Sánchez, Miguel; Ricaldi-Sueldo, Rita; Miranda-Cuadros, Marianella

2011-06-01

To describe the design and methods of the national surveillance of nutritional indicators (MONIN) 2007-2010, carried out by INS/CENAN. MONIN was designed as a continuous (repeated cross-sectional) survey, with stratified multi-stage random sampling, considering the universe as all under five children and pregnant women residing in Peru, divided into 5 geographical strata and 6 trimesters (randomly permuted weeks, about 78% of the time between November 19, 2007 and April 2, 2010). The total sample was 3,827 children in 361 completed clusters. The dropout rate was 8.4% in clusters, 1.8% in houses, and 13.2% in households. Dropout was also 4.2, 13.3, 21.2, 55% and 29% in anthropometry, hemoglobin, food intake, retinol and ioduria measurements, respectively. The MONIN design is feasible and useful for the estimation of indicators of childhood malnutrition.

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

PubMed

Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

An adaptive two-stage sequential design for sampling rare and clustered populations

USGS Publications Warehouse

Brown, J.A.; Salehi, M.M.; Moradi, M.; Bell, G.; Smith, D.R.

2008-01-01

How to design an efficient large-area survey continues to be an interesting question for ecologists. In sampling large areas, as is common in environmental studies, adaptive sampling can be efficient because it ensures survey effort is targeted to subareas of high interest. In two-stage sampling, higher density primary sample units are usually of more interest than lower density primary units when populations are rare and clustered. Two-stage sequential sampling has been suggested as a method for allocating second stage sample effort among primary units. Here, we suggest a modification: adaptive two-stage sequential sampling. In this method, the adaptive part of the allocation process means the design is more flexible in how much extra effort can be directed to higher-abundance primary units. We discuss how best to design an adaptive two-stage sequential sample. ?? 2008 The Society of Population Ecology and Springer.

Optimized scheme in coal-fired boiler combustion based on information entropy and modified K-prototypes algorithm

NASA Astrophysics Data System (ADS)

Gu, Hui; Zhu, Hongxia; Cui, Yanfeng; Si, Fengqi; Xue, Rui; Xi, Han; Zhang, Jiayu

2018-06-01

An integrated combustion optimization scheme is proposed for the combined considering the restriction in coal-fired boiler combustion efficiency and outlet NOx emissions. Continuous attribute discretization and reduction techniques are handled as optimization preparation by E-Cluster and C_RED methods, in which the segmentation numbers don't need to be provided in advance and can be continuously adapted with data characters. In order to obtain results of multi-objections with clustering method for mixed data, a modified K-prototypes algorithm is then proposed. This algorithm can be divided into two stages as K-prototypes algorithm for clustering number self-adaptation and clustering for multi-objective optimization, respectively. Field tests were carried out at a 660 MW coal-fired boiler to provide real data as a case study for controllable attribute discretization and reduction in boiler system and obtaining optimization parameters considering [ maxηb, minyNOx ] multi-objective rule.

A method for automatic grain segmentation of multi-angle cross-polarized microscopic images of sandstone

NASA Astrophysics Data System (ADS)

Jiang, Feng; Gu, Qing; Hao, Huizhen; Li, Na; Wang, Bingqian; Hu, Xiumian

2018-06-01

Automatic grain segmentation of sandstone is to partition mineral grains into separate regions in the thin section, which is the first step for computer aided mineral identification and sandstone classification. The sandstone microscopic images contain a large number of mixed mineral grains where differences among adjacent grains, i.e., quartz, feldspar and lithic grains, are usually ambiguous, which make grain segmentation difficult. In this paper, we take advantage of multi-angle cross-polarized microscopic images and propose a method for grain segmentation with high accuracy. The method consists of two stages, in the first stage, we enhance the SLIC (Simple Linear Iterative Clustering) algorithm, named MSLIC, to make use of multi-angle images and segment the images as boundary adherent superpixels. In the second stage, we propose the region merging technique which combines the coarse merging and fine merging algorithms. The coarse merging merges the adjacent superpixels with less evident boundaries, and the fine merging merges the ambiguous superpixels using the spatial enhanced fuzzy clustering. Experiments are designed on 9 sets of multi-angle cross-polarized images taken from the three major types of sandstones. The results demonstrate both the effectiveness and potential of the proposed method, comparing to the available segmentation methods.

Variable Circumstellar Disks of “Classical” Be Stars

NASA Astrophysics Data System (ADS)

Gerhartz, Cody; Bjorkman, K. S.; Wisniewski, J. P.

2013-06-01

Circumstellar disks are common among many stars, all spectral types, and at different stages of their lifetimes. Among the near-main sequence “Classical” Be stars, there is growing evidence that these disks can form, dissipate, and reform, on timescales that are differ from case to case. We present data for a subset of cases where observations have been obtained throughout the different phases of the disk cycle. Using data obtained with the SpeX instrument at the NASA IRTF, we examine the IR spectral line variability of these stars to better understand the timescales and the physical mechanisms involved. The primary focus in this study are the V/R variations that are observed in the sample. The second stage of our project is to examine a sample of star clusters known to contain Be stars, with the goal to develop a more statistically significant sample of variable circumstellar disk systems. With a robust multi-epoch study we can determine whether these Be stars exhibit disk-loss or disk-renewal phases. The larger sample will enable a better understanding of the prevalence of these disk events.

Thermodynamics and Kinetics of Prenucleation Clusters, Classical and Non-Classical Nucleation.

PubMed

Zahn, Dirk

2015-07-20

Recent observations of prenucleation species and multi-stage crystal nucleation processes challenge the long-established view on the thermodynamics of crystal formation. Here, we review and generalize extensions to classical nucleation theory. Going beyond the conventional implementation as has been used for more than a century now, nucleation inhibitors, precursor clusters and non-classical nucleation processes are rationalized as well by analogous concepts based on competing interface and bulk energy terms. This is illustrated by recent examples of species formed prior to/instead of crystal nucleation and multi-step nucleation processes. Much of the discussed insights were obtained from molecular simulation using advanced sampling techniques, briefly summarized herein for both nucleation-controlled and diffusion-controlled aggregate formation. © 2015 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Estimating regression coefficients from clustered samples: Sampling errors and optimum sample allocation

NASA Technical Reports Server (NTRS)

Kalton, G.

1983-01-01

A number of surveys were conducted to study the relationship between the level of aircraft or traffic noise exposure experienced by people living in a particular area and their annoyance with it. These surveys generally employ a clustered sample design which affects the precision of the survey estimates. Regression analysis of annoyance on noise measures and other variables is often an important component of the survey analysis. Formulae are presented for estimating the standard errors of regression coefficients and ratio of regression coefficients that are applicable with a two- or three-stage clustered sample design. Using a simple cost function, they also determine the optimum allocation of the sample across the stages of the sample design for the estimation of a regression coefficient.

Multi-species attributes as the condition for adaptive sampling of rare species using two-stage sequential sampling with an auxiliary variable

USGS Publications Warehouse

Panahbehagh, B.; Smith, D.R.; Salehi, M.M.; Hornbach, D.J.; Brown, D.J.; Chan, F.; Marinova, D.; Anderssen, R.S.

2011-01-01

Assessing populations of rare species is challenging because of the large effort required to locate patches of occupied habitat and achieve precise estimates of density and abundance. The presence of a rare species has been shown to be correlated with presence or abundance of more common species. Thus, ecological community richness or abundance can be used to inform sampling of rare species. Adaptive sampling designs have been developed specifically for rare and clustered populations and have been applied to a wide range of rare species. However, adaptive sampling can be logistically challenging, in part, because variation in final sample size introduces uncertainty in survey planning. Two-stage sequential sampling (TSS), a recently developed design, allows for adaptive sampling, but avoids edge units and has an upper bound on final sample size. In this paper we present an extension of two-stage sequential sampling that incorporates an auxiliary variable (TSSAV), such as community attributes, as the condition for adaptive sampling. We develop a set of simulations to approximate sampling of endangered freshwater mussels to evaluate the performance of the TSSAV design. The performance measures that we are interested in are efficiency and probability of sampling a unit occupied by the rare species. Efficiency measures the precision of population estimate from the TSSAV design relative to a standard design, such as simple random sampling (SRS). The simulations indicate that the density and distribution of the auxiliary population is the most important determinant of the performance of the TSSAV design. Of the design factors, such as sample size, the fraction of the primary units sampled was most important. For the best scenarios, the odds of sampling the rare species was approximately 1.5 times higher for TSSAV compared to SRS and efficiency was as high as 2 (i.e., variance from TSSAV was half that of SRS). We have found that design performance, especially for adaptive designs, is often case-specific. Efficiency of adaptive designs is especially sensitive to spatial distribution. We recommend that simulations tailored to the application of interest are highly useful for evaluating designs in preparation for sampling rare and clustered populations.

Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

PubMed

Wu, Dingming; Wang, Dongfang; Zhang, Michael Q; Gu, Jin

2015-12-01

One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data. In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types. LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/ .

Role of competition between polarity sites in establishing a unique front

PubMed Central

Wu, Chi-Fang; Chiou, Jian-Geng; Minakova, Maria; Woods, Benjamin; Tsygankov, Denis; Zyla, Trevin R; Savage, Natasha S; Elston, Timothy C; Lew, Daniel J

2015-01-01

Polarity establishment in many cells is thought to occur via positive feedback that reinforces even tiny asymmetries in polarity protein distribution. Cdc42 and related GTPases are activated and accumulate in a patch of the cortex that defines the front of the cell. Positive feedback enables spontaneous polarization triggered by stochastic fluctuations, but as such fluctuations can occur at multiple locations, how do cells ensure that they make only one front? In polarizing cells of the model yeast Saccharomyces cerevisiae, positive feedback can trigger growth of several Cdc42 clusters at the same time, but this multi-cluster stage rapidly evolves to a single-cluster state, which then promotes bud emergence. By manipulating polarity protein dynamics, we show that resolution of multi-cluster intermediates occurs through a greedy competition between clusters to recruit and retain polarity proteins from a shared intracellular pool. DOI: http://dx.doi.org/10.7554/eLife.11611.001 PMID:26523396

A two-stage cluster sampling method using gridded population data, a GIS, and Google Earth(TM) imagery in a population-based mortality survey in Iraq.

PubMed

Galway, Lp; Bell, Nathaniel; Sae, Al Shatari; Hagopian, Amy; Burnham, Gilbert; Flaxman, Abraham; Weiss, Wiliam M; Rajaratnam, Julie; Takaro, Tim K

2012-04-27

Mortality estimates can measure and monitor the impacts of conflict on a population, guide humanitarian efforts, and help to better understand the public health impacts of conflict. Vital statistics registration and surveillance systems are rarely functional in conflict settings, posing a challenge of estimating mortality using retrospective population-based surveys. We present a two-stage cluster sampling method for application in population-based mortality surveys. The sampling method utilizes gridded population data and a geographic information system (GIS) to select clusters in the first sampling stage and Google Earth TM imagery and sampling grids to select households in the second sampling stage. The sampling method is implemented in a household mortality study in Iraq in 2011. Factors affecting feasibility and methodological quality are described. Sampling is a challenge in retrospective population-based mortality studies and alternatives that improve on the conventional approaches are needed. The sampling strategy presented here was designed to generate a representative sample of the Iraqi population while reducing the potential for bias and considering the context specific challenges of the study setting. This sampling strategy, or variations on it, are adaptable and should be considered and tested in other conflict settings.

A two-stage cluster sampling method using gridded population data, a GIS, and Google EarthTM imagery in a population-based mortality survey in Iraq

PubMed Central

2012-01-01

Background Mortality estimates can measure and monitor the impacts of conflict on a population, guide humanitarian efforts, and help to better understand the public health impacts of conflict. Vital statistics registration and surveillance systems are rarely functional in conflict settings, posing a challenge of estimating mortality using retrospective population-based surveys. Results We present a two-stage cluster sampling method for application in population-based mortality surveys. The sampling method utilizes gridded population data and a geographic information system (GIS) to select clusters in the first sampling stage and Google Earth TM imagery and sampling grids to select households in the second sampling stage. The sampling method is implemented in a household mortality study in Iraq in 2011. Factors affecting feasibility and methodological quality are described. Conclusion Sampling is a challenge in retrospective population-based mortality studies and alternatives that improve on the conventional approaches are needed. The sampling strategy presented here was designed to generate a representative sample of the Iraqi population while reducing the potential for bias and considering the context specific challenges of the study setting. This sampling strategy, or variations on it, are adaptable and should be considered and tested in other conflict settings. PMID:22540266

Study of shallow junction formation by boron-containing cluster ion implantation of silicon and two-stage annealing

NASA Astrophysics Data System (ADS)

Lu, Xin-Ming

Shallow junction formation made by low energy ion implantation and rapid thermal annealing is facing a major challenge for ULSI (ultra large scale integration) as the line width decreases down to the sub micrometer region. The issues include low beam current, the channeling effect in low energy ion implantation and TED (transient enhanced diffusion) during annealing after ion implantation. In this work, boron containing small cluster ions, such as GeB, SiB and SiB2, was generated by using the SNICS (source of negative ion by cesium sputtering) ion source to implant into Si substrates to form shallow junctions. The use of boron containing cluster ions effectively reduces the boron energy while keeping the energy of the cluster ion beam at a high level. At the same time, it reduces the channeling effect due to amorphization by co-implanted heavy atoms like Ge and Si. Cluster ions have been used to produce 0.65--2keV boron for low energy ion implantation. Two stage annealing, which is a combination of low temperature (550°C) preannealing and high temperature annealing (1000°C), was carried out to anneal the Si sample implanted by GeB, SiBn clusters. The key concept of two-step annealing, that is, the separation of crystal regrowth, point defects removal with dopant activation from dopant diffusion, is discussed in detail. The advantages of the two stage annealing include better lattice structure, better dopant activation and retarded boron diffusion. The junction depth of the two stage annealed GeB sample was only half that of the one-step annealed sample, indicating that TED was suppressed by two stage annealing. Junction depths as small as 30 nm have been achieved by two stage annealing of sample implanted with 5 x 10-4/cm2 of 5 keV GeB at 1000°C for 1 second. The samples were evaluated by SIMS (secondary ion mass spectrometry) profiling, TEM (transmission electron microscopy) and RBS (Rutherford Backscattering Spectrometry)/channeling. Cluster ion implantation in combination with two-step annealing is effective in fabricating ultra-shallow junctions.

Variable Circumstellar Disks of “Classical” Be Stars, Part 2

NASA Astrophysics Data System (ADS)

Gerhartz, Cody; Davidson, J. W.; Bjorkman, K. S.; Wisniewski, J. P.

2014-01-01

Circumstellar disks are common among many stars, all spectral types, and at different stages of their lifetimes. Among the near-main sequence “Classical” Be stars, there is growing evidence that these disks can form, dissipate, and reform, on timescales that are differ from case to case. We present data for a subset of cases where observations have been obtained throughout the different phases of the disk cycle. Using data obtained with the SpeX instrument at the NASA IRTF, we examine the IR spectral line variability of these stars to better understand the timescales and the physical mechanisms involved. The primary focus in this study are the V/R variations that are observed in the sample. A complete run of all double-peaked velocity profiles in the sample is now complete. The second stage of our project is to examine a sample of star clusters known to contain Be stars, with the goal to develop a more statistically significant sample of variable circumstellar disk systems. With a robust multi-epoch study we can determine whether these Be stars exhibit disk-loss or disk-renewal phases. The larger sample will enable an understanding of the prevalence of these disk events.

Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?

PubMed

Kent, Peter; Stochkendahl, Mette Jensen; Christensen, Henrik Wulff; Kongsted, Alice

2015-01-01

Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role participation, psychological factors, biomarkers and imaging. However, such 'whole person' research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may improve the clinical interpretability of derived subgroups and reduce sample size requirements. This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it.

Cortical atrophy patterns in early Parkinson's disease patients using hierarchical cluster analysis.

PubMed

Uribe, Carme; Segura, Barbara; Baggio, Hugo Cesar; Abos, Alexandra; Garcia-Diaz, Anna Isabel; Campabadal, Anna; Marti, Maria Jose; Valldeoriola, Francesc; Compta, Yaroslau; Tolosa, Eduard; Junque, Carme

2018-05-01

Cortical brain atrophy detectable with MRI in non-demented advanced Parkinson's disease (PD) is well characterized, but its presence in early disease stages is still under debate. We aimed to investigate cortical atrophy patterns in a large sample of early untreated PD patients using a hypothesis-free data-driven approach. Seventy-seven de novo PD patients and 50 controls from the Parkinson's Progression Marker Initiative database with T1-weighted images in a 3-tesla Siemens scanner were included in this study. Mean cortical thickness was extracted from 360 cortical areas defined by the Human Connectome Project Multi-Modal Parcellation version 1.0, and a hierarchical cluster analysis was performed using Ward's linkage method. A general linear model with cortical thickness data was then used to compare clustering groups using FreeSurfer software. We identified two patterns of cortical atrophy. Compared with controls, patients grouped in pattern 1 (n = 33) were characterized by cortical thinning in bilateral orbitofrontal, anterior cingulate, and lateral and medial anterior temporal gyri. Patients in pattern 2 (n = 44) showed cortical thinning in bilateral occipital gyrus, cuneus, superior parietal gyrus, and left postcentral gyrus, and they showed neuropsychological impairment in memory and other cognitive domains. Even in the early stages of PD, there is evidence of cortical brain atrophy. Neuroimaging clustering analysis is able to detect two subgroups of cortical thinning, one with mainly anterior atrophy, and the other with posterior predominance and worse cognitive performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Variable Circumstellar Disks of Classical Be Stars in Clusters

NASA Astrophysics Data System (ADS)

Gerhartz, C.; Bjorkman, K. S.; Bjorkman, J. E.; Wisniewski, J. P.

2016-11-01

Circumstellar disks are common among many stars, at most spectral types, and at different stages of their lifetimes. Among the near-main-sequence classical Be stars, there is growing evidence that these disks form, dissipate, and reform on timescales that differ from star to star. Using data obtained with the Large Monolithic Imager (LMI) at the Lowell Observatory Discovery Channel Telescope (DCT), along with additional complementary data obtained at the University of Toledo Ritter Observatory (RO), we have begun a long-term monitoring project of a well-studied set of galactic star clusters that are known to contain Be stars. Our goal is to develop a statistically significant sample of variable circumstellar disk systems over multiple timescales. With a robust multi-epoch study we can determine the relative fraction of Be stars that exhibit disk-loss or disk-renewal phases, and investigate the range of timescales over which these events occur. A larger sample will improve our understanding of the prevalence and nature of the disk variability, and may provide insight about underlying physical mechanisms.

Estimating accuracy of land-cover composition from two-stage cluster sampling

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Fattorini, L.; Wade, T.D.; Baffetta, F.; Smith, J.H.

2009-01-01

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias. ?? 2009 Elsevier Inc.

Online Low-Rank Representation Learning for Joint Multi-subspace Recovery and Clustering.

PubMed

Li, Bo; Liu, Risheng; Cao, Junjie; Zhang, Jie; Lai, Yu-Kun; Liua, Xiuping

2017-10-06

Benefiting from global rank constraints, the lowrank representation (LRR) method has been shown to be an effective solution to subspace learning. However, the global mechanism also means that the LRR model is not suitable for handling large-scale data or dynamic data. For large-scale data, the LRR method suffers from high time complexity, and for dynamic data, it has to recompute a complex rank minimization for the entire data set whenever new samples are dynamically added, making it prohibitively expensive. Existing attempts to online LRR either take a stochastic approach or build the representation purely based on a small sample set and treat new input as out-of-sample data. The former often requires multiple runs for good performance and thus takes longer time to run, and the latter formulates online LRR as an out-ofsample classification problem and is less robust to noise. In this paper, a novel online low-rank representation subspace learning method is proposed for both large-scale and dynamic data. The proposed algorithm is composed of two stages: static learning and dynamic updating. In the first stage, the subspace structure is learned from a small number of data samples. In the second stage, the intrinsic principal components of the entire data set are computed incrementally by utilizing the learned subspace structure, and the low-rank representation matrix can also be incrementally solved by an efficient online singular value decomposition (SVD) algorithm. The time complexity is reduced dramatically for large-scale data, and repeated computation is avoided for dynamic problems. We further perform theoretical analysis comparing the proposed online algorithm with the batch LRR method. Finally, experimental results on typical tasks of subspace recovery and subspace clustering show that the proposed algorithm performs comparably or better than batch methods including the batch LRR, and significantly outperforms state-of-the-art online methods.

Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color Imaging

PubMed Central

Doi, Ryoichi; Arif, Chusnul

2014-01-01

Red-green-blue (RGB) channels of RGB digital photographs were loaded with luminosity-adjusted R, G, and completely white grayscale images, respectively (RGwhtB method), or R, G, and R + G (RGB yellow) grayscale images, respectively (RGrgbyB method), to adjust the brightness of the entire area of multi-temporally acquired color digital photographs of a rice canopy. From the RGwhtB or RGrgbyB pseudocolor image, cyan, magenta, CMYK yellow, black, L*, a*, and b* grayscale images were prepared. Using these grayscale images and R, G, and RGB yellow grayscale images, the luminosity-adjusted pixels of the canopy photographs were statistically clustered. With the RGrgbyB and the RGwhtB methods, seven and five major color clusters were given, respectively. The RGrgbyB method showed clear differences among three rice growth stages, and the vegetative stage was further divided into two substages. The RGwhtB method could not clearly discriminate between the second vegetative and midseason stages. The relative advantages of the RGrgbyB method were attributed to the R, G, B, magenta, yellow, L*, and a* grayscale images that contained richer information to show the colorimetrical differences among objects than those of the RGwhtB method. The comparison of rice canopy colors at different time points was enabled by the pseudocolor imaging method. PMID:25302325

Poor Prognosis Indicated by Venous Circulating Tumor Cell Clusters in Early-Stage Lung Cancers.

PubMed

Murlidhar, Vasudha; Reddy, Rishindra M; Fouladdel, Shamileh; Zhao, Lili; Ishikawa, Martin K; Grabauskiene, Svetlana; Zhang, Zhuo; Lin, Jules; Chang, Andrew C; Carrott, Philip; Lynch, William R; Orringer, Mark B; Kumar-Sinha, Chandan; Palanisamy, Nallasivam; Beer, David G; Wicha, Max S; Ramnath, Nithya; Azizi, Ebrahim; Nagrath, Sunitha

2017-09-15

Early detection of metastasis can be aided by circulating tumor cells (CTC), which also show potential to predict early relapse. Because of the limited CTC numbers in peripheral blood in early stages, we investigated CTCs in pulmonary vein blood accessed during surgical resection of tumors. Pulmonary vein (PV) and peripheral vein (Pe) blood specimens from patients with lung cancer were drawn during the perioperative period and assessed for CTC burden using a microfluidic device. From 108 blood samples analyzed from 36 patients, PV had significantly higher number of CTCs compared with preoperative Pe ( P < 0.0001) and intraoperative Pe ( P < 0.001) blood. CTC clusters with large number of CTCs were observed in 50% of patients, with PV often revealing larger clusters. Long-term surveillance indicated that presence of clusters in preoperative Pe blood predicted a trend toward poor prognosis. Gene expression analysis by RT-qPCR revealed enrichment of p53 signaling and extracellular matrix involvement in PV and Pe samples. Ki67 expression was detected in 62.5% of PV samples and 59.2% of Pe samples, with the majority (72.7%) of patients positive for Ki67 expression in PV having single CTCs as opposed to clusters. Gene ontology analysis revealed enrichment of cell migration and immune-related pathways in CTC clusters, suggesting survival advantage of clusters in circulation. Clusters display characteristics of therapeutic resistance, indicating the aggressive nature of these cells. Thus, CTCs isolated from early stages of lung cancer are predictive of poor prognosis and can be interrogated to determine biomarkers predictive of recurrence. Cancer Res; 77(18); 5194-206. ©2017 AACR . ©2017 American Association for Cancer Research.

ICM: a web server for integrated clustering of multi-dimensional biomedical data.

PubMed

He, Song; He, Haochen; Xu, Wenjian; Huang, Xin; Jiang, Shuai; Li, Fei; He, Fuchu; Bo, Xiaochen

2016-07-08

Large-scale efforts for parallel acquisition of multi-omics profiling continue to generate extensive amounts of multi-dimensional biomedical data. Thus, integrated clustering of multiple types of omics data is essential for developing individual-based treatments and precision medicine. However, while rapid progress has been made, methods for integrated clustering are lacking an intuitive web interface that facilitates the biomedical researchers without sufficient programming skills. Here, we present a web tool, named Integrated Clustering of Multi-dimensional biomedical data (ICM), that provides an interface from which to fuse, cluster and visualize multi-dimensional biomedical data and knowledge. With ICM, users can explore the heterogeneity of a disease or a biological process by identifying subgroups of patients. The results obtained can then be interactively modified by using an intuitive user interface. Researchers can also exchange the results from ICM with collaborators via a web link containing a Project ID number that will directly pull up the analysis results being shared. ICM also support incremental clustering that allows users to add new sample data into the data of a previous study to obtain a clustering result. Currently, the ICM web server is available with no login requirement and at no cost at http://biotech.bmi.ac.cn/icm/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Early stages of carbonate mineralization revealed from molecular simulations: Implications for biomineral formation

NASA Astrophysics Data System (ADS)

Wallace, A. F.; DeYoreo, J.; Banfield, J. F.

2011-12-01

The carbonate mineral constituents of many biomineralized products, formed both in and ex vivo, grow by a multi-stage crystallization process that involves the nucleation and structural reorganization of transient amorphous phases. The existence of transient phases and cluster species has significant implications for carbonate nucleation and growth in natural and engineered environments, both modern and ancient. The structure of these intermediate phases remains elusive, as does the nature of the disorder to order transition, however, these process details may strongly influence the interpretation of elemental and isotopic climate proxy data obtained from authigenic and biogenic carbonates. While molecular simulations have been applied to certain aspects of crystal growth, studies of metal carbonate nucleation are strongly inhibited by the presence of kinetic traps that prevent adequate sampling of the potential landscape upon which the growing clusters reside within timescales accessible by simulation. This research addresses this challenge by marrying the recent Kawska-Zahn (KZ) approach to simulation of crystal nucleation and growth from solution with replica-exchange molecular dynamics (REMD) techniques. REMD has been used previously to enhance sampling of protein conformations that occupy energy wells that are separated by sizable thermodynamic and kinetic barriers, and is used here to probe the initial formation and onset of order within hydrated calcium and iron carbonate cluster species during nucleation. Results to date suggest that growing clusters initiate as short linear ion chains that evolve into two- and three-dimensional structures with continued growth. The planar structures exhibit an obvious 2d lattice, while establishment of a 3d lattice is hindered by incomplete ion desolvation. The formation of a dehydrated core consisting of a single carbonate ion is observed when the clusters are ~0.75 nm. At the same size a distorted, but discernible calcite-type lattice is also apparent. Continued growth results in expansion of the dehydrated core, however, complete desolvation and incorporation of cations into the growing carbonate phase is not achieved until the cluster grows to ~1.2 nm. Exploration of the system free energy along the crystallization path reveals "special" cluster sizes that correlate with ion desolvation milestones. The formation of these species comprise critical bottlenecks on the energy landscape and for the establishment of order within the growing clusters.

The Size Distribution Of Cluster Galaxies

NASA Astrophysics Data System (ADS)

Kuchner, U.; Ziegler, B.; Bamford, S.; Verdugo, M.; Haeussler, B.

2017-06-01

We establish a sample of 560 spectroscopically confirmed cluster members of MACS J1206.2- 0847 at z = 0.45 and utilize multi-wavelength and multi-component Sersic profile fitting to provide luminosities and sizes for the key structural components bulge and disk. While the difference between field and cluster galaxy properties are mostly due to a preference for cluster members to be early-type (quiescent, bulge-dominated), we see evidence for an outer disk fading and a sharp rise in the number of red disks with smaller effective radii at the tidally active cluster region around R200. Even though red disks are already virialized according to their velocity distribution, they are clearly not part of the old population found in the innermost region; they represent an important population of transitional objects in clusters.

Relationship between happiness and tobacco smoking among high school students.

PubMed

Ataeiasl, Maryam; Sarbakhsh, Parvin; Dadashzadeh, Hossein; Augner, Christoph; Anbarlouei, Masoumeh; Mohammadpoorasl, Asghar

2018-01-01

Recent research has described negative relationship between happiness and habitual smoking among adolescents. No study of this relationship has been conducted among Iranian adolescents. The aim of the present study was to characterize the relationship between happiness and cigarette or hookah smoking among a sample of high school students. A sample of 1,161 10th-grade students in Tabriz (northwest Iran) was selected by multi-stage proportional cluster sampling. Participants completed a self-administered multiple-choice questionnaire including information on cigarette smoking, hookah smoking, happiness score, substance abuse, self-injury, general risk-taking behavior, attitudes towards smoking, socioeconomic information, and demographic characteristics. An ordinal logistic regression model was used for data analysis. It was found that 5.9 and 5.0% of students were regular cigarette smokers and regular hookah smokers, respectively. After controlling for potential confounders, higher happiness scores were found to protect students against more advanced stages of cigarette smoking (odds ratio [OR], 0.98; 95% confidence interval [CI], 0.97 to 0.99; p=0.013). However, no significant relationship was found between happiness scores and hookah smoking status (OR, 1.01; 95% CI, 0.97 to 1.02; p=0.523). Happiness scores were associated with less advanced stages of habitual cigarette smoking among high school students. Our findings underscore the necessity of conducting longitudinal or interventional studies aiming to determine the effects of enhancing happiness on preventing the transition through the stages of cigarette and hookah smoking.

Young globular clusters in NGC 1316

NASA Astrophysics Data System (ADS)

Sesto, Leandro A.; Faifer, Favio R.; Smith Castelli, Analía V.; Forte, Juan C.; Escudero, Carlos G.

2018-05-01

We present multi-object spectroscopy of the inner zone of the globular cluster (GC) system associated with the intermediate-age merger remnant NGC 1316. Using the multi-object mode of the GMOS camera, we obtained spectra for 35 GCs. We find pieces of evidence that the innermost GCs of NGC 1316 rotate almost perpendicular to the stellar component of the galaxy. In a second stage, we determined ages, metallicities and α-element abundances for each GC present in the sample, through the measurement of different Lick/IDS indices and their comparison with simple stellar population models. We confirmed the existence of multiple GC populations associated with NGC 1316, where the presence of a dominant subpopulation of very young GCs, with an average age of 2.1 Gyr, metallicities between -0.5 < [Z/H] < 0.5 dex and α-element abundances in the range -0.2 < [α/Fe] < 0.3 dex, stands out. Several objects in our sample present subsolar values of [α/Fe] and a large spread of [Z/H] and ages. Some of these objects could actually be stripped nuclei, possibly accreted during minor merger events. Finally, the results have been analyzed with the aim of describing the different episodes of star formation and thus provide a more complete picture about the evolutionary history of the galaxy. We conclude that these pieces of evidence could indicate that this galaxy has cannibalized one or more gas-rich galaxies, where the last fusion event occurred about 2 Gyr ago.

Sampling Methods in Cardiovascular Nursing Research: An Overview.

PubMed

Kandola, Damanpreet; Banner, Davina; O'Keefe-McCarthy, Sheila; Jassal, Debbie

2014-01-01

Cardiovascular nursing research covers a wide array of topics from health services to psychosocial patient experiences. The selection of specific participant samples is an important part of the research design and process. The sampling strategy employed is of utmost importance to ensure that a representative sample of participants is chosen. There are two main categories of sampling methods: probability and non-probability. Probability sampling is the random selection of elements from the population, where each element of the population has an equal and independent chance of being included in the sample. There are five main types of probability sampling including simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. Non-probability sampling methods are those in which elements are chosen through non-random methods for inclusion into the research study and include convenience sampling, purposive sampling, and snowball sampling. Each approach offers distinct advantages and disadvantages and must be considered critically. In this research column, we provide an introduction to these key sampling techniques and draw on examples from the cardiovascular research. Understanding the differences in sampling techniques may aid nurses in effective appraisal of research literature and provide a reference pointfor nurses who engage in cardiovascular research.

Two-stage sequential sampling: A neighborhood-free adaptive sampling procedure

USGS Publications Warehouse

Salehi, M.; Smith, D.R.

2005-01-01

Designing an efficient sampling scheme for a rare and clustered population is a challenging area of research. Adaptive cluster sampling, which has been shown to be viable for such a population, is based on sampling a neighborhood of units around a unit that meets a specified condition. However, the edge units produced by sampling neighborhoods have proven to limit the efficiency and applicability of adaptive cluster sampling. We propose a sampling design that is adaptive in the sense that the final sample depends on observed values, but it avoids the use of neighborhoods and the sampling of edge units. Unbiased estimators of population total and its variance are derived using Murthy's estimator. The modified two-stage sampling design is easy to implement and can be applied to a wider range of populations than adaptive cluster sampling. We evaluate the proposed sampling design by simulating sampling of two real biological populations and an artificial population for which the variable of interest took the value either 0 or 1 (e.g., indicating presence and absence of a rare event). We show that the proposed sampling design is more efficient than conventional sampling in nearly all cases. The approach used to derive estimators (Murthy's estimator) opens the door for unbiased estimators to be found for similar sequential sampling designs. ?? 2005 American Statistical Association and the International Biometric Society.

Evaluation for Bearing Wear States Based on Online Oil Multi-Parameters Monitoring

PubMed Central

Hu, Hai-Feng

2018-01-01

As bearings are critical components of a mechanical system, it is important to characterize their wear states and evaluate health conditions. In this paper, a novel approach for analyzing the relationship between online oil multi-parameter monitoring samples and bearing wear states has been proposed based on an improved gray k-means clustering model (G-KCM). First, an online monitoring system with multiple sensors for bearings is established, obtaining oil multi-parameter data and vibration signals for bearings through the whole lifetime. Secondly, a gray correlation degree distance matrix is generated using a gray correlation model (GCM) to express the relationship of oil monitoring samples at different times and then a KCM is applied to cluster the matrix. Analysis and experimental results show that there is an obvious correspondence that state changing coincides basically in time between the lubricants’ multi-parameters and the bearings’ wear states. It also has shown that online oil samples with multi-parameters have early wear failure prediction ability for bearings superior to vibration signals. It is expected to realize online oil monitoring and evaluation for bearing health condition and to provide a novel approach for early identification of bearing-related failure modes. PMID:29621175

Evaluation for Bearing Wear States Based on Online Oil Multi-Parameters Monitoring.

PubMed

Wang, Si-Yuan; Yang, Ding-Xin; Hu, Hai-Feng

2018-04-05

As bearings are critical components of a mechanical system, it is important to characterize their wear states and evaluate health conditions. In this paper, a novel approach for analyzing the relationship between online oil multi-parameter monitoring samples and bearing wear states has been proposed based on an improved gray k-means clustering model (G-KCM). First, an online monitoring system with multiple sensors for bearings is established, obtaining oil multi-parameter data and vibration signals for bearings through the whole lifetime. Secondly, a gray correlation degree distance matrix is generated using a gray correlation model (GCM) to express the relationship of oil monitoring samples at different times and then a KCM is applied to cluster the matrix. Analysis and experimental results show that there is an obvious correspondence that state changing coincides basically in time between the lubricants' multi-parameters and the bearings' wear states. It also has shown that online oil samples with multi-parameters have early wear failure prediction ability for bearings superior to vibration signals. It is expected to realize online oil monitoring and evaluation for bearing health condition and to provide a novel approach for early identification of bearing-related failure modes.

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks.

PubMed

Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

2018-04-26

With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results indicated that our proposed method outperforms the existing baseline methods and was able to achieve good performance in habitat suitability prediction.

The Australian longitudinal study on male health sampling design and survey weighting: implications for analysis and interpretation of clustered data.

PubMed

Spittal, Matthew J; Carlin, John B; Currier, Dianne; Downes, Marnie; English, Dallas R; Gordon, Ian; Pirkis, Jane; Gurrin, Lyle

2016-10-31

The Australian Longitudinal Study on Male Health (Ten to Men) used a complex sampling scheme to identify potential participants for the baseline survey. This raises important questions about when and how to adjust for the sampling design when analyzing data from the baseline survey. We describe the sampling scheme used in Ten to Men focusing on four important elements: stratification, multi-stage sampling, clustering and sample weights. We discuss how these elements fit together when using baseline data to estimate a population parameter (e.g., population mean or prevalence) or to estimate the association between an exposure and an outcome (e.g., an odds ratio). We illustrate this with examples using a continuous outcome (weight in kilograms) and a binary outcome (smoking status). Estimates of a population mean or disease prevalence using Ten to Men baseline data are influenced by the extent to which the sampling design is addressed in an analysis. Estimates of mean weight and smoking prevalence are larger in unweighted analyses than weighted analyses (e.g., mean = 83.9 kg vs. 81.4 kg; prevalence = 18.0 % vs. 16.7 %, for unweighted and weighted analyses respectively) and the standard error of the mean is 1.03 times larger in an analysis that acknowledges the hierarchical (clustered) structure of the data compared with one that does not. For smoking prevalence, the corresponding standard error is 1.07 times larger. Measures of association (mean group differences, odds ratios) are generally similar in unweighted or weighted analyses and whether or not adjustment is made for clustering. The extent to which the Ten to Men sampling design is accounted for in any analysis of the baseline data will depend on the research question. When the goals of the analysis are to estimate the prevalence of a disease or risk factor in the population or the magnitude of a population-level exposure-outcome association, our advice is to adopt an analysis that respects the sampling design.

Determinants of customers' intention to participate in a Korean restaurant health promotion program: an application of the theory of planned behavior.

PubMed

Hong, Kyungeui; Gittelsohn, Joel; Joung, Hyojee

2010-06-01

The purpose of this study was to investigate the effects of personal characteristics and theory of planned behavior (TPB) constructs on the intention to participate in a restaurant health promotion program. In total, 830 adults residing in Seoul were sampled by a multi-stage cluster and random sampling design. Data were collected from a structured self-administered questionnaire, which covered variables concerning demographics, health status and TPB constructs including attitude, subjective norm and perceived behavioral control. A path analysis combining personal characteristics and TPB constructs was used to investigate determinants of the customers' intention. Positive and negative attitudes, subjective norms and perceived behavioral control directly affected the intention to participate. Demographics and health status both directly and indirectly affected the intention to participate. This study identifies personal characteristics and TPB constructs that are important to planning and implementing a restaurant health promotion program.

A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets

DOE PAGES

Klein, M.; Mohr, J. J.; Desai, S.; ...

2017-11-14

We describe a multi-component matched filter cluster confirmation tool (MCMF) designed for the study of large X-ray source catalogs produced by the upcoming X-ray all-sky survey mission eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts $0.05

A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets

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

Klein, M.; Mohr, J. J.; Desai, S.

We describe a multi-component matched filter cluster confirmation tool (MCMF) designed for the study of large X-ray source catalogs produced by the upcoming X-ray all-sky survey mission eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts $0.05

Variations in the prevalence of antibody to brucella infection in cattle by farm, area and district in Kenya.

PubMed Central

Kadohira, M.; McDermott, J. J.; Shoukri, M. M.; Kyule, M. N.

1997-01-01

Variations in the sero-prevalence of antibody to brucella infection by cow, farm and area factors were investigated for three contrasting districts in Kenya: Samburu, an arid and pastoral area: Kiambu, a tropical highland area; and Kilifi, a typical tropical coastal area. Cattle were selected by a two-stage cluster sampling procedure and visited once between August 1991 and 1992. Schall's algorithm, a statistical model suitable for multi-level analysis was used. Using this model, older age, free grazing and large herd size (> or = 31) were associated with higher seroprevalence. Also, significant farm-to-farm, area-to-area and district-to-district variations were estimated. The patterns of high risk districts and areas seen were consistent with known animal husbandry and movement risk factors, but the larger than expected farm-to-farm variation within high risk areas and districts could not be explained. Thus, a multi-level method provided additional information beyond conventional analyses of sero-prevalence data. PMID:9042033

The impact of sharing arrangement institution on beef cattle breeding performance in Kupang District, East Nusa Tenggara Province, Indonesia

NASA Astrophysics Data System (ADS)

Nono, O. H.; Natawidjaja, R.; Arief, B.; Suryadi, D.; Kapa, M. M. J.

2018-02-01

The aim of this study was to analyse the impact of sharing arrangement systems to performance of beef cattle breeding. This research was conducted in Kupang Regency - East Nusa Tenggara Province, Indonesia. The study used multi stage cluster random sampling method to determine the sample area and respondents. The sample areas consisted of 2 sub-districts and 6 villages, while the total respondents were 117 people comprised 74 Participant Farmers (PF) of sharing arrangement systems (SAS) and 43 non-participant farmers (NPF). 23 investors were selected for the survey. The result of the study indicated that the performance of NPF in terms of revenue, net profit, and return on investment (ROI) was better than PF respondents. The value of ROI was between 16.69-32.23 %. This indicated that utilization of farm asset was not optimum yet. It was found that farm efficiency was 1.73 which indicated that SAS does not increase farm productivity.

The three-zone composite productivity model for a multi-fractured horizontal shale gas well

NASA Astrophysics Data System (ADS)

Qi, Qian; Zhu, Weiyao

2018-02-01

Due to the nano-micro pore structures and the massive multi-stage multi-cluster hydraulic fracturing in shale gas reservoirs, the multi-scale seepage flows are much more complicated than in most other conventional reservoirs, and are crucial for the economic development of shale gas. In this study, a new multi-scale non-linear flow model was established and simplified, based on different diffusion and slip correction coefficients. Due to the fact that different flow laws existed between the fracture network and matrix zone, a three-zone composite model was proposed. Then, according to the conformal transformation combined with the law of equivalent percolation resistance, the productivity equation of a horizontal fractured well, with consideration given to diffusion, slip, desorption, and absorption, was built. Also, an analytic solution was derived, and the interference of the multi-cluster fractures was analyzed. The results indicated that the diffusion of the shale gas was mainly in the transition and Fick diffusion regions. The matrix permeability was found to be influenced by slippage and diffusion, which was determined by the pore pressure and diameter according to the Knudsen number. It was determined that, with the increased half-lengths of the fracture clusters, flow conductivity of the fractures, and permeability of the fracture network, the productivity of the fractured well also increased. Meanwhile, with the increased number of fractures, the distance between the fractures decreased, and the productivity slowly increased due to the mutual interfere of the fractures.

Multilevel Analysis of Trachomatous Trichiasis and Corneal Opacity in Nigeria: The Role of Environmental and Climatic Risk Factors on the Distribution of Disease.

PubMed

Smith, Jennifer L; Sivasubramaniam, Selvaraj; Rabiu, Mansur M; Kyari, Fatima; Solomon, Anthony W; Gilbert, Clare

2015-01-01

The distribution of trachoma in Nigeria is spatially heterogeneous, with large-scale trends observed across the country and more local variation within areas. Relative contributions of individual and cluster-level risk factors to the geographic distribution of disease remain largely unknown. The primary aim of this analysis is to assess the relationship between climatic factors and trachomatous trichiasis (TT) and/or corneal opacity (CO) due to trachoma in Nigeria, while accounting for the effects of individual risk factors and spatial correlation. In addition, we explore the relative importance of variation in the risk of trichiasis and/or corneal opacity (TT/CO) at different levels. Data from the 2007 National Blindness and Visual Impairment Survey were used for this analysis, which included a nationally representative sample of adults aged 40 years and above. Complete data were available from 304 clusters selected using a multi-stage stratified cluster-random sampling strategy. All participants (13,543 individuals) were interviewed and examined by an ophthalmologist for the presence or absence of TT and CO. In addition to field-collected data, remotely sensed climatic data were extracted for each cluster and used to fit Bayesian hierarchical logistic models to disease outcome. The risk of TT/CO was associated with factors at both the individual and cluster levels, with approximately 14% of the total variation attributed to the cluster level. Beyond established individual risk factors (age, gender and occupation), there was strong evidence that environmental/climatic factors at the cluster-level (lower precipitation, higher land surface temperature, higher mean annual temperature and rural classification) were also associated with a greater risk of TT/CO. This study establishes the importance of large-scale risk factors in the geographical distribution of TT/CO in Nigeria, supporting anecdotal evidence that environmental conditions are associated with increased risk in this context and highlighting their potential use in improving estimates of disease burden at large scales.

Grouping methods for estimating the prevalences of rare traits from complex survey data that preserve confidentiality of respondents.

PubMed

Hyun, Noorie; Gastwirth, Joseph L; Graubard, Barry I

2018-03-26

Originally, 2-stage group testing was developed for efficiently screening individuals for a disease. In response to the HIV/AIDS epidemic, 1-stage group testing was adopted for estimating prevalences of a single or multiple traits from testing groups of size q, so individuals were not tested. This paper extends the methodology of 1-stage group testing to surveys with sample weighted complex multistage-cluster designs. Sample weighted-generalized estimating equations are used to estimate the prevalences of categorical traits while accounting for the error rates inherent in the tests. Two difficulties arise when using group testing in complex samples: (1) How does one weight the results of the test on each group as the sample weights will differ among observations in the same group. Furthermore, if the sample weights are related to positivity of the diagnostic test, then group-level weighting is needed to reduce bias in the prevalence estimation; (2) How does one form groups that will allow accurate estimation of the standard errors of prevalence estimates under multistage-cluster sampling allowing for intracluster correlation of the test results. We study 5 different grouping methods to address the weighting and cluster sampling aspects of complex designed samples. Finite sample properties of the estimators of prevalences, variances, and confidence interval coverage for these grouping methods are studied using simulations. National Health and Nutrition Examination Survey data are used to illustrate the methods. Copyright © 2018 John Wiley & Sons, Ltd.

The Role of School Culture and Basic Psychological Needs on Iranian Adolescents' Academic Alienation: A Multi-Level Examination

ERIC Educational Resources Information Center

Mahmoudi, Hojjat; Brown, Monica R.; Amani Saribagloo, Javad; Dadashzadeh, Shiva

2018-01-01

This aim of this current research was a multi-level analysis of the relationship between school culture, basic psychological needs, and adolescents' academic alienation. One thousand twenty-nine (N = 1,029) high school students from Qom City were randomly selected through a multi-phase cluster sampling method and answered questions regarding…

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap.

PubMed

Zhou, Hanzhi; Elliott, Michael R; Raghunathan, Trivellore E

2016-06-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in "Delta-V," a key crash severity measure.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap

PubMed Central

Zhou, Hanzhi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in “Delta-V,” a key crash severity measure. PMID:29226161

NanoRocks: A Long-Term Microgravity Experiment to Stydy Planet Formation and Planetary Ring Particles

NASA Astrophysics Data System (ADS)

Brisset, J.; Colwell, J. E.; Dove, A.; Maukonen, D.; Brown, N.; Lai, K.; Hoover, B.

2015-12-01

We report on the results of the NanoRocks experiment on the International Space Station (ISS), which simulates collisions that occur in protoplanetary disks and planetary ring systems. A critical stage of the process of early planet formation is the growth of solid bodies from mm-sized chondrules and aggregates to km-sized planetesimals. To characterize the collision behavior of dust in protoplanetary conditions, experimental data is required, working hand in hand with models and numerical simulations. In addition, the collisional evolution of planetary rings takes place in the same collisional regime. The objective of the NanoRocks experiment is to study low-energy collisions of mm-sized particles of different shapes and materials. An aluminum tray (~8x8x2cm) divided into eight sample cells holding different types of particles gets shaken every 60 s providing particles with initial velocities of a few cm/s. In September 2014, NanoRocks reached ISS and 220 video files, each covering one shaking cycle, have already been downloaded from Station. The data analysis is focused on the dynamical evolution of the multi-particle systems and on the formation of cluster. We track the particles down to mean relative velocities less than 1 mm/s where we observe cluster formation. The mean velocity evolution after each shaking event allows for a determination of the mean coefficient of restitution for each particle set. These values can be used as input into protoplanetary disk and planetary rings simulations. In addition, the cluster analysis allows for a determination of the mean final cluster size and the average particle velocity of clustering onset. The size and shape of these particle clumps is crucial to understand the first stages of planet formation inside protoplanetary disks as well as many a feature of Saturn's rings. We report on the results from the ensemble of these collision experiments and discuss applications to planetesimal formation and planetary ring evolution.

Data processing 1: Advancements in machine analysis of multispectral data

NASA Technical Reports Server (NTRS)

Swain, P. H.

1972-01-01

Multispectral data processing procedures are outlined beginning with the data display process used to accomplish data editing and proceeding through clustering, feature selection criterion for error probability estimation, and sample clustering and sample classification. The effective utilization of large quantities of remote sensing data by formulating a three stage sampling model for evaluation of crop acreage estimates represents an improvement in determining the cost benefit relationship associated with remote sensing technology.

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments

PubMed Central

2013-01-01

Background Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. Results To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations. The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. Conclusions We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs. PMID:24160725

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

PubMed

Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello

2013-10-26

Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

ULTRA-DEEP GEMINI NEAR-INFRARED OBSERVATIONS OF THE BULGE GLOBULAR CLUSTER NGC 6624

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

Saracino, S.; Dalessandro, E.; Ferraro, F. R.

2016-11-20

We used ultra-deep J and K {sub s} images secured with the near-infrared (NIR) GSAOI camera assisted by the multi-conjugate adaptive optics system GeMS at the GEMINI South Telescope in Chile, to obtain a ( K {sub s} , J - K {sub s} ) color–magnitude diagram (CMD) for the bulge globular cluster NGC 6624. We obtained the deepest and most accurate NIR CMD from the ground for this cluster, by reaching K {sub s} ∼ 21.5, approximately 8 mag below the horizontal branch level. The entire extension of the Main Sequence (MS) is nicely sampled and at K {submore » s} ∼ 20 we detected the so-called MS “knee” in a purely NIR CMD. By taking advantage of the exquisite quality of the data, we estimated the absolute age of NGC 6624 ( t {sub age} = 12.0 ± 0.5 Gyr), which turns out to be in good agreement with previous studies in the literature. We also analyzed the luminosity and mass functions of MS stars down to M ∼ 0.45 M{sub ⊙}, finding evidence of a significant increase of low-mass stars at increasing distances from the cluster center. This is a clear signature of mass segregation, confirming that NGC 6624 is in an advanced stage of dynamical evolution.« less

Sipa1l1 is an early biomarker of liver fibrosis in CCl4-treated rats

PubMed Central

Marfà, Santiago; Morales-Ruiz, Manuel; Oró, Denise; Ribera, Jordi; Fernández-Varo, Guillermo; Jiménez, Wladimiro

2016-01-01

ABSTRACT At present, several procedures are used for staging liver fibrosis. However, these methods may involve clinical complications and/or present diagnostic uncertainty mainly in the early stages of the disease. Thus, this study was designed to unveil new non-invasive biomarkers of liver fibrosis in an in vivo model of fibrosis/cirrhosis induction by CCl4 inhalation by using a label-free quantitative LC-MS/MS approach. We analyzed 94 serum samples from adult Wistar rats with different degrees of liver fibrosis and 36 control rats. Firstly, serum samples from 18 CCl4-treated rats were clustered into three different groups according to the severity of hepatic and the serum proteome was characterized by label-free LC-MS/MS. Furthermore, three different pooled serum samples obtained from 16 control Wistar rats were also analyzed. Based on the proteomic data obtained, we performed a multivariate analysis which displayed three main cell signaling pathways altered in fibrosis. In cirrhosis, more biological imbalances were detected as well as multi-organ alterations. In addition, hemopexin and signal-induced proliferation-associated 1 like 1 (SIPA1L1) were selected as potential serum markers of liver fibrogenesis among all the analyzed proteins. The results were validated by ELISA in an independent group of 76 fibrotic/cirrhotic rats and 20 controls which confirmed SIPA1L1 as a potential non-invasive biomarker of liver fibrosis. In particular, SIPA1L1 showed a clear diminution in serum samples from fibrotic/cirrhotic rats and a great accuracy at identifying early fibrotic stages. In conclusion, the proteomic analysis of serum samples from CCl4-treated rats has enabled the identification of SIPA1L1 as a non-invasive marker of early liver fibrosis. PMID:27230648

Mutation Clusters from Cancer Exome.

PubMed

Kakushadze, Zura; Yu, Willie

2017-08-15

We apply our statistically deterministic machine learning/clustering algorithm *K-means (recently developed in https://ssrn.com/abstract=2908286) to 10,656 published exome samples for 32 cancer types. A majority of cancer types exhibit a mutation clustering structure. Our results are in-sample stable. They are also out-of-sample stable when applied to 1389 published genome samples across 14 cancer types. In contrast, we find in- and out-of-sample instabilities in cancer signatures extracted from exome samples via nonnegative matrix factorization (NMF), a computationally-costly and non-deterministic method. Extracting stable mutation structures from exome data could have important implications for speed and cost, which are critical for early-stage cancer diagnostics, such as novel blood-test methods currently in development.

Mutation Clusters from Cancer Exome

PubMed Central

Kakushadze, Zura; Yu, Willie

2017-01-01

We apply our statistically deterministic machine learning/clustering algorithm *K-means (recently developed in https://ssrn.com/abstract=2908286) to 10,656 published exome samples for 32 cancer types. A majority of cancer types exhibit a mutation clustering structure. Our results are in-sample stable. They are also out-of-sample stable when applied to 1389 published genome samples across 14 cancer types. In contrast, we find in- and out-of-sample instabilities in cancer signatures extracted from exome samples via nonnegative matrix factorization (NMF), a computationally-costly and non-deterministic method. Extracting stable mutation structures from exome data could have important implications for speed and cost, which are critical for early-stage cancer diagnostics, such as novel blood-test methods currently in development. PMID:28809811

Multi-Target State Extraction for the SMC-PHD Filter

PubMed Central

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-01-01

The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been demonstrated to be a favorable method for multi-target tracking. However, the time-varying target states need to be extracted from the particle approximation of the posterior PHD, which is difficult to implement due to the unknown relations between the large amount of particles and the PHD peaks representing potential target locations. To address this problem, a novel multi-target state extraction algorithm is proposed in this paper. By exploiting the information of measurements and particle likelihoods in the filtering stage, we propose a validation mechanism which aims at selecting effective measurements and particles corresponding to detected targets. Subsequently, the state estimates of the detected and undetected targets are performed separately: the former are obtained from the particle clusters directed by effective measurements, while the latter are obtained from the particles corresponding to undetected targets via clustering method. Simulation results demonstrate that the proposed method yields better estimation accuracy and reliability compared to existing methods. PMID:27322274

[Update on pubertal development among primary school students in Shanghai, 2014].

PubMed

Chen, Y; Zhang, Y T; Chen, C; Jiang, Y R; Song, Y J; Liu, S J; Jiang, F

2016-11-06

Objective: To investigate the current prevalence of pubertal development in healthy Shanghai schoolchildren. Methods: This study was a cross-sectional investigation focused on current pubertal development conducted in healthy Shanghai schoolchildren by multi-stage cluster sampling. The sample included 17 571 children in grades 1-5 investigated in June 2014. The data were weighted by inverse probability weighting (IPW) to make them more representative. At examination, stages of breast and pubic hair development were rated according to the Tanner method. Testicular volume was determined. Data on menarche and spermatorrhea were collected by the status quo method. The rates of precocious puberty, breast, and pubic hair development of Tanner stage ≥Ⅱ in girls aged 6-7 years, menarche in girls aged 6-9 years, and testicular volume ≥4 ml and pubic hair development of Tanner stage ≥Ⅱ in boys aged 6-8 years were calculated. All the data were weighted by IPW. Results: After data processing, 16 197 children's data were analyzed. In girls aged 6-7 years, 17.2% and 2.5% showed evidence of breast and pubic hair development at Tanner stage ≥Ⅱ, respectively. In girls aged 6-9 years, 0.3% had experienced menarche. Schoolgirls' rate of menarche was 4.7%. In girls aged 6-7 years, 19.0% were diagnosed with precocious puberty according to the classic criteria. In boys aged 6-8 years, 1.7% had testicular volume ≥4 ml, and 0.6% showed evidence of pubic hair development at Tanner stage ≥Ⅱ. Schoolboys' incidence rate of spermatorrhea was 0.1%. In boys aged 6-8 years, 2.3% were diagnosed with precocious puberty according to the classic criteria. All the numbers above were weighted. Conclusion: Proper education on adolescence and sex is essential for Shanghai schoolchildren.

Extending cluster Lot Quality Assurance Sampling designs for surveillance programs

PubMed Central

Hund, Lauren; Pagano, Marcello

2014-01-01

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance based on the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible non-parametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. PMID:24633656

Extending cluster lot quality assurance sampling designs for surveillance programs.

PubMed

Hund, Lauren; Pagano, Marcello

2014-07-20

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance on the basis of the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible nonparametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. Copyright © 2014 John Wiley & Sons, Ltd.

Mid-course multi-target tracking using continuous representation

NASA Technical Reports Server (NTRS)

Zak, Michail; Toomarian, Nikzad

1991-01-01

The thrust of this paper is to present a new approach to multi-target tracking for the mid-course stage of the Strategic Defense Initiative (SDI). This approach is based upon a continuum representation of a cluster of flying objects. We assume that the velocities of the flying objects can be embedded into a smooth velocity field. This assumption is based upon the impossibility of encounters in a high density cluster between the flying objects. Therefore, the problem is reduced to an identification of a moving continuum based upon consecutive time frame observations. In contradistinction to the previous approaches, here each target is considered as a center of a small continuous neighborhood subjected to a local-affine transformation, and therefore, the target trajectories do not mix. Obviously, their mixture in plane of sensor view is apparent. The approach is illustrated by an example.

Integrated cluster- and case-based surveillance for detecting stage III zoonotic pathogens: an example of Nipah virus surveillance in Bangladesh.

PubMed

Naser, A M; Hossain, M J; Sazzad, H M S; Homaira, N; Gurley, E S; Podder, G; Afroj, S; Banu, S; Rollin, P E; Daszak, P; Ahmed, B-N; Rahman, M; Luby, S P

2015-07-01

This paper explores the utility of cluster- and case-based surveillance established in government hospitals in Bangladesh to detect Nipah virus, a stage III zoonotic pathogen. Physicians listed meningo-encephalitis cases in the 10 surveillance hospitals and identified a cluster when ⩾2 cases who lived within 30 min walking distance of one another developed symptoms within 3 weeks of each other. Physicians collected blood samples from the clustered cases. As part of case-based surveillance, blood was collected from all listed meningo-encephalitis cases in three hospitals during the Nipah season (January-March). An investigation team visited clustered cases' communities to collect epidemiological information and blood from the living cases. We tested serum using Nipah-specific IgM ELISA. Up to September 2011, in 5887 listed cases, we identified 62 clusters comprising 176 encephalitis cases. We collected blood from 127 of these cases. In 10 clusters, we identified a total of 62 Nipah cases: 18 laboratory-confirmed and 34 probable. We identified person-to-person transmission of Nipah virus in four clusters. From case-based surveillance, we identified 23 (4%) Nipah cases. Faced with thousands of encephalitis cases, integrated cluster surveillance allows targeted deployment of investigative resources to detect outbreaks by stage III zoonotic pathogens in resource-limited settings.

Non-small cell lung cancer detection using microRNA expression profiling of bronchoalveolar lavage fluid and sputum.

PubMed

Kim, Julian O; Gazala, Sayf; Razzak, Rene; Guo, Linghong; Ghosh, Sunita; Roa, Wilson H; Bédard, Eric L R

2015-04-01

To assess if miRNA expression profiling of bronchoalveolar lavage (BAL) fluid and sputum could be used to detect early-stage non-small cell lung cancer (NSCLC). Hierarchical cluster analysis was performed on the expression levels of 5 miRNAs (miR-21, miR-143, miR-155, miR-210, and miR-372) which were quantified using RNA reverse transcription and quantitative real-time polymerase chain reaction in sputum and BAL samples from NSCLC cases and cancer-free controls. Cluster analysis of the miRNA expression levels in BAL samples from 21 NSCLC cases and sputum samples from 10 cancer-free controls yielded a diagnostic sensitivity of 85.7% and specificity of 100%. Cluster analysis of sputum samples from the same patients yielded a diagnostic sensitivity of 67.8% and specificity of 90%. miRNA expression profiling of sputum and BAL fluids represent a potential means to detect early-stage NSCLC. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Clustering of temperamental and cognitive risk factors for anxiety in a college sample of late adolescents.

PubMed

Viana, Andres G; Gratz, Kim L; Bierman, Karen L

2013-01-01

Temperamental vulnerabilities (e.g., behavioral inhibition, anxiety sensitivity) and cognitive biases (e.g., interpretive and judgment biases) may exacerbate feelings of stress and anxiety, particularly among late adolescents during the early years of college. The goal of the present study was to apply person-centered analyses to explore possible heterogeneity in the patterns of these four risk factors in late adolescence, and to examine associations with several anxiety outcomes (i.e., worry, anxiety symptoms, and trait anxiety). Cluster analyses in a college sample of 855 late adolescents revealed a Low-Risk group, along with four reliable clusters with distinct profiles of risk factors and anxiety outcomes (Inhibited, Sensitive, Cognitively-Biased, and Multi-Risk). Of the risk profiles, Multi-Risk youth experienced the highest levels of anxiety outcomes, whereas Inhibited youth experienced the lowest levels of anxiety outcomes. Sensitive and Cognitively-Biased youth experienced comparable levels of anxiety-related outcomes, despite different constellations of risk factors. Implications for interventions and future research are discussed.

Amplified Fragment Length Polymorphism Fingerprinting of Pseudomonas Strains from a Poultry Processing Plant

PubMed Central

Geornaras, Ifigenia; Kunene, Nokuthula F.; von Holy, Alexander; Hastings, John W.

1999-01-01

Molecular typing has been used previously to identify and trace dissemination of pathogenic and spoilage bacteria associated with food processing. Amplified fragment length polymorphism (AFLP) is a novel DNA fingerprinting technique which is considered highly reproducible and has high discriminatory power. This technique was used to fingerprint 88 Pseudomonas fluorescens and Pseudomonas putida strains that were previously isolated from plate counts of carcasses at six processing stages and various equipment surfaces and environmental sources of a poultry abattoir. Clustering of the AFLP patterns revealed a high level of diversity among the strains. Six clusters (clusters I through VI) were delineated at an arbitrary Dice coefficient level of 0.65; clusters III (31 strains) and IV (28 strains) were the largest clusters. More than one-half (52.3%) of the strains obtained from carcass samples, which may have represented the resident carcass population, grouped together in cluster III. By contrast, 43.2% of the strains from most of the equipment surfaces and environmental sources grouped together in cluster IV. In most cases, the clusters in which carcass strains from processing stages grouped corresponded to the clusters in which strains from the associated equipment surfaces and/or environmental sources were found. This provided evidence that there was cross-contamination between carcasses and the abattoir environment at the DNA level. The AFLP data also showed that strains were being disseminated from the beginning to the end of the poultry processing operation, since many strains associated with carcasses at the packaging stage were members of the same clusters as strains obtained from carcasses after the defeathering stage. PMID:10473382

Amplified fragment length polymorphism fingerprinting of Pseudomonas strains from a poultry processing plant.

PubMed

Geornaras, I; Kunene, N F; von Holy, A; Hastings, J W

1999-09-01

Molecular typing has been used previously to identify and trace dissemination of pathogenic and spoilage bacteria associated with food processing. Amplified fragment length polymorphism (AFLP) is a novel DNA fingerprinting technique which is considered highly reproducible and has high discriminatory power. This technique was used to fingerprint 88 Pseudomonas fluorescens and Pseudomonas putida strains that were previously isolated from plate counts of carcasses at six processing stages and various equipment surfaces and environmental sources of a poultry abattoir. Clustering of the AFLP patterns revealed a high level of diversity among the strains. Six clusters (clusters I through VI) were delineated at an arbitrary Dice coefficient level of 0.65; clusters III (31 strains) and IV (28 strains) were the largest clusters. More than one-half (52.3%) of the strains obtained from carcass samples, which may have represented the resident carcass population, grouped together in cluster III. By contrast, 43.2% of the strains from most of the equipment surfaces and environmental sources grouped together in cluster IV. In most cases, the clusters in which carcass strains from processing stages grouped corresponded to the clusters in which strains from the associated equipment surfaces and/or environmental sources were found. This provided evidence that there was cross-contamination between carcasses and the abattoir environment at the DNA level. The AFLP data also showed that strains were being disseminated from the beginning to the end of the poultry processing operation, since many strains associated with carcasses at the packaging stage were members of the same clusters as strains obtained from carcasses after the defeathering stage.

A particle swarm optimized kernel-based clustering method for crop mapping from multi-temporal polarimetric L-band SAR observations

NASA Astrophysics Data System (ADS)

Tamiminia, Haifa; Homayouni, Saeid; McNairn, Heather; Safari, Abdoreza

2017-06-01

Polarimetric Synthetic Aperture Radar (PolSAR) data, thanks to their specific characteristics such as high resolution, weather and daylight independence, have become a valuable source of information for environment monitoring and management. The discrimination capability of observations acquired by these sensors can be used for land cover classification and mapping. The aim of this paper is to propose an optimized kernel-based C-means clustering algorithm for agriculture crop mapping from multi-temporal PolSAR data. Firstly, several polarimetric features are extracted from preprocessed data. These features are linear polarization intensities, and several statistical and physical based decompositions such as Cloude-Pottier, Freeman-Durden and Yamaguchi techniques. Then, the kernelized version of hard and fuzzy C-means clustering algorithms are applied to these polarimetric features in order to identify crop types. The kernel function, unlike the conventional partitioning clustering algorithms, simplifies the non-spherical and non-linearly patterns of data structure, to be clustered easily. In addition, in order to enhance the results, Particle Swarm Optimization (PSO) algorithm is used to tune the kernel parameters, cluster centers and to optimize features selection. The efficiency of this method was evaluated by using multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Manitoba, Canada, during June and July in 2012. The results demonstrate more accurate crop maps using the proposed method when compared to the classical approaches, (e.g. 12% improvement in general). In addition, when the optimization technique is used, greater improvement is observed in crop classification, e.g. 5% in overall. Furthermore, a strong relationship between Freeman-Durden volume scattering component, which is related to canopy structure, and phenological growth stages is observed.

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2017-06-06

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)

PubMed Central

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-01-01

Background Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. Methods We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. Application We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. Conclusion This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy. PMID:17543100

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR).

PubMed

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-06-01

Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy.

Galaxy clustering dependence on the [O II] emission line luminosity in the local Universe

NASA Astrophysics Data System (ADS)

Favole, Ginevra; Rodríguez-Torres, Sergio A.; Comparat, Johan; Prada, Francisco; Guo, Hong; Klypin, Anatoly; Montero-Dorta, Antonio D.

2017-11-01

We study the galaxy clustering dependence on the [O II] emission line luminosity in the SDSS DR7 Main galaxy sample at mean redshift z ∼ 0.1. We select volume-limited samples of galaxies with different [O II] luminosity thresholds and measure their projected, monopole and quadrupole two-point correlation functions. We model these observations using the 1 h-1 Gpc MultiDark-Planck cosmological simulation and generate light cones with the SUrvey GenerAtoR algorithm. To interpret our results, we adopt a modified (Sub)Halo Abundance Matching scheme, accounting for the stellar mass incompleteness of the emission line galaxies. The satellite fraction constitutes an extra parameter in this model and allows to optimize the clustering fit on both small and intermediate scales (i.e. rp ≲ 30 h-1 Mpc), with no need of any velocity bias correction. We find that, in the local Universe, the [O II] luminosity correlates with all the clustering statistics explored and with the galaxy bias. This latter quantity correlates more strongly with the SDSS r-band magnitude than [O II] luminosity. In conclusion, we propose a straightforward method to produce reliable clustering models, entirely built on the simulation products, which provides robust predictions of the typical ELG host halo masses and satellite fraction values. The SDSS galaxy data, MultiDark mock catalogues and clustering results are made publicly available.

Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research was to combine machine-learning (ML) algorithms with traditional regression techniques by utilising self-reported medical symptoms to identify and describe clusters of individuals with increased rates of depression from a large cross-sectional community based population epidemiological study. A multi-staged methodology utilising ML and traditional statistical techniques was performed using the community based population National Health and Nutrition Examination Study (2009-2010) (N = 3,922). A Self-organised Mapping (SOM) ML algorithm, combined with hierarchical clustering, was performed to create participant clusters based on 68 medical symptoms. Binary logistic regression, controlling for sociodemographic confounders, was used to then identify the key clusters of participants with higher levels of depression (PHQ-9≥10, n = 377). Finally, a Multiple Additive Regression Tree boosted ML algorithm was run to identify the important medical symptoms for each key cluster within 17 broad categories: heart, liver, thyroid, respiratory, diabetes, arthritis, fractures and osteoporosis, skeletal pain, blood pressure, blood transfusion, cholesterol, vision, hearing, psoriasis, weight, bowels and urinary. Five clusters of participants, based on medical symptoms, were identified to have significantly increased rates of depression compared to the cluster with the lowest rate: odds ratios ranged from 2.24 (95% CI 1.56, 3.24) to 6.33 (95% CI 1.67, 24.02). The ML boosted regression algorithm identified three key medical condition categories as being significantly more common in these clusters: bowel, pain and urinary symptoms. Bowel-related symptoms was found to dominate the relative importance of symptoms within the five key clusters. This methodology shows promise for the identification of conditions in general populations and supports the current focus on the potential importance of bowel symptoms and the gut in mental health research.

The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

NASA Astrophysics Data System (ADS)

Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

2018-04-01

Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

The Atacama Cosmology Telescope: Physical Properties and Purity of a Galaxy Cluster Sample Selected Via the Sunyaev-Zel'Dovich Effect

NASA Technical Reports Server (NTRS)

Menanteau, Felipe; Gonzalez, Jorge; Juin, Jean-Baptiste; Marriage, Tobias; Reese, Erik D.; Acquaviva, Viviana; Aguirre, Paula; Appel, John Willam; Baker, Andrew J.; Barrientos, L. Felipe;

Methodology of a nationwide cross-sectional survey of prevalence and epidemiological patterns of hepatitis A, B and C infection in Brazil.

PubMed

Ximenes, Ricardo Arraes de Alencar; Pereira, Leila Maria Beltrão; Martelli, Celina Maria Turchi; Merchán-Hamann, Edgar; Stein, Airton Tetelbom; Figueiredo, Gerusa Maria; Braga, Maria Cynthia; Montarroyos, Ulisses Ramos; Brasil, Leila Melo; Turchi, Marília Dalva; Fonseca, José Carlos Ferraz da; Lima, Maria Luiza Carvalho de; Alencar, Luis Cláudio Arraes de; Costa, Marcelo; Coral, Gabriela; Moreira, Regina Celia; Cardoso, Maria Regina Alves

2010-09-01

A population-based survey to provide information on the prevalence of hepatitis viral infection and the pattern of risk factors was carried out in the urban population of all Brazilian state capitals and the Federal District, between 2005 and 2009. This paper describes the design and methodology of the study which involved a population aged 5 to 19 for hepatitis A and 10 to 69 for hepatitis B and C. Interviews and blood samples were obtained through household visits. The sample was selected using stratified multi-stage cluster sampling and was drawn with equal probability from each domain of study (region and age-group). Nationwide, 19,280 households and ~31,000 residents were selected. The study is large enough to detect prevalence of viral infection around 0.1% and risk factor assessments within each region. The methodology seems to be a viable way of differentiating between distinct epidemiological patterns of hepatitis A, B and C. These data will be of value for the evaluation of vaccination policies and for the design of control program strategies.

Globular Cluster Star Classification: Application to M13

NASA Astrophysics Data System (ADS)

Caimmi, R.

2013-06-01

Starting from recent determination of Fe, O, Na abundances on a restricted sample (N=67) of halo and thick disk stars, a natural and well motivated selection criterion is defined for the classification globular cluster stars. An application is performed to M13 using a sample (N=113) for which Fe, O, Na abundances have been recently inferred from observations. A comparison is made between the current and earlier M13 star classifications. Both O and Na empirical differential abundance distributions are determined for each class and for the whole sample (with the addition of Fe in the last case) and compared with their theoretical counterparts due to cosmic scatter obeying a Gaussian distribution whose parameters are inferred from related subsamples. The occurrence of an agreement between the empirical and theoretical distributions is interpreted as absence of significant chemical evolution and vice versa. The procedure is repeated with regard to four additional classes depending on whether oxygen and sodium abundance is above (stage CE) or below (stage AF) a selected threshold. Both O and Na empirical differential abundance distributions, related to the whole sample, exhibit a linear fit for the AF and CE stage. Within the errors, the oxygen slope for the CE stage is equal and of opposite sign with respect to the sodium slope for AF stage, while the contrary holds when dealing with the oxygen slope for the AF stage with respect to the sodium slope for the CE stage. In the light of simple models of chemical evolution applied to M13, oxygen depletion appears to be mainly turned into sodium enrichment for [O/H]≥-1.35 and [Na/H]≤-1.45, while one or more largely preferred channels occur for [O/H]<-1.35 and [Na/H]>-1.45. In addition, the primordial to the current M13 mass ratio can be inferred from the true sodium yield in units of the sodium solar abundance. Though the above results are mainly qualitative due to large (∓.5 dex) uncertainties in abundance determination, still the exhibited trend is expected to be real. The proposed classification of globular cluster stars may be extended in a twofold manner, namely to: (i) elements other than Na and Fe and (ii) globular clusters other than M13.

XMM-Subaru:Complete High Precision Study of Galaxy Clusters for Modern Cosmology

NASA Astrophysics Data System (ADS)

Zhang, Yu-Ying

2011-10-01

We request 382 ks data for 12 clusters to complete our survey of a volume-limited sample of 55 clusters. We investigated the existing data, which hints a mass dependent bias in the X-ray to weak lensing mass ratios for disturbed ones. X-ray mass proxies, e.g., Yx, show low scatter, but the best fits, particularly the slopes, of the mass-observable relations may be biased due to this mass dependence. Our program will quantify any mass/radial dependent bias based on three independent probes (X-ray/lensing/velocity dispersion) for such a volume-limited sample, and deliver definitive constraints on systematics for upcoming cluster cosmology surveys. The dataset will be a major asset for programs aiming to measure dark energy and programs adding a multi-wavelength focus to studies of cluster physics.

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.

A two-stage method for microcalcification cluster segmentation in mammography by deformable models

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

Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.

Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods aremore » applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST{sub cluster}, average of minimum distance—AMINDIST{sub cluster}) and the area overlap measure (AOM{sub cluster}). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross-validation methodology. A previously developed B-spline active rays segmentation method was also considered for comparison purposes. Results: Interobserver and intraobserver segmentation agreements (median and [25%, 75%] quartile range) were substantial with respect to the distance metrics HDIST{sub cluster} (2.3 [1.8, 2.9] and 2.5 [2.1, 3.2] pixels) and AMINDIST{sub cluster} (0.8 [0.6, 1.0] and 1.0 [0.8, 1.2] pixels), while moderate with respect to AOM{sub cluster} (0.64 [0.55, 0.71] and 0.59 [0.52, 0.66]). The proposed segmentation method outperformed (0.80 ± 0.04) statistically significantly (Mann-Whitney U-test, p < 0.05) the B-spline active rays segmentation method (0.69 ± 0.04), suggesting the significance of the proposed semiautomated method. Conclusions: Results indicate a reliable semiautomated segmentation method for MC clusters offered by deformable models, which could be utilized in MC cluster quantitative image analysis.« less

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks

PubMed Central

Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

2018-01-01

Simple Summary The understanding of the spatio-temporal distribution of the species habitats would facilitate wildlife resource management and conservation efforts. Existing methods have poor performance due to the limited availability of training samples. More recently, location-aware sensors have been widely used to track animal movements. The aim of the study was to generate suitability maps of bar-head geese using movement data coupled with environmental parameters, such as remote sensing images and temperature data. Therefore, we modified a deep convolutional neural network for the multi-scale inputs. The results indicate that the proposed method can identify the areas with the dense goose species around Qinghai Lake. In addition, this approach might also be interesting for implementation in other species with different niche factors or in areas where biological survey data are scarce. Abstract With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results indicated that our proposed method outperforms the existing baseline methods and was able to achieve good performance in habitat suitability prediction. PMID:29701686

Adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization

NASA Astrophysics Data System (ADS)

Zhang, Tianzhen; Wang, Xiumei; Gao, Xinbo

2018-04-01

Nowadays, several datasets are demonstrated by multi-view, which usually include shared and complementary information. Multi-view clustering methods integrate the information of multi-view to obtain better clustering results. Nonnegative matrix factorization has become an essential and popular tool in clustering methods because of its interpretation. However, existing nonnegative matrix factorization based multi-view clustering algorithms do not consider the disagreement between views and neglects the fact that different views will have different contributions to the data distribution. In this paper, we propose a new multi-view clustering method, named adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization. The proposed algorithm can obtain the parts-based representation of multi-view data by nonnegative matrix factorization. Then, pairwise co-regularization is used to measure the disagreement between views. There is only one parameter to auto learning the weight values according to the contribution of each view to data distribution. Experimental results show that the proposed algorithm outperforms several state-of-the-arts algorithms for multi-view clustering.

Image quality guided approach for adaptive modelling of biometric intra-class variations

NASA Astrophysics Data System (ADS)

Abboud, Ali J.; Jassim, Sabah A.

2010-04-01

The high intra-class variability of acquired biometric data can be attributed to several factors such as quality of acquisition sensor (e.g. thermal), environmental (e.g. lighting), behavioural (e.g. change face pose). Such large fuzziness of biometric data can cause a big difference between an acquired and stored biometric data that will eventually lead to reduced performance. Many systems store multiple templates in order to account for such variations in the biometric data during enrolment stage. The number and typicality of these templates are the most important factors that affect system performance than other factors. In this paper, a novel offline approach is proposed for systematic modelling of intra-class variability and typicality in biometric data by regularly selecting new templates from a set of available biometric images. Our proposed technique is a two stage algorithm whereby in the first stage image samples are clustered in terms of their image quality profile vectors, rather than their biometric feature vectors, and in the second stage a per cluster template is selected from a small number of samples in each clusters to create an ultimate template sets. These experiments have been conducted on five face image databases and their results will demonstrate the effectiveness of proposed quality guided approach.

Evaluation of intensified behaviour change communication strategies in an artemisinin resistance setting.

PubMed

Canavati, Sara E; de Beyl, Celine Zegers; Ly, Po; Shafique, Muhammad; Boukheng, Thavrin; Rang, Chandary; Whittaker, Maxine Anne; Roca-Feltrer, Arantxa; Sintasath, David

2016-04-30

In Cambodia, behaviour change communication (BCC) represents an integral component of malaria efforts aimed at fighting artemisinin resistant parasites and achieving elimination. The multi-pronged BCC interventions include interpersonal communication through village health volunteers (VHVs) and village malaria workers (VMWs), broadcasting malaria prevention, diagnosis and treatment messages via TV, radio and mobile broadcasting units (MBUs), distributing information education and communication (IEC) materials and introducing mobile malaria workers (MMWs) in endemic villages. This was a cross sectional household survey using a stratified multi-stage cluster sampling approach, conducted in December 2012. A stratified multi-stage cluster sampling approach was used; 30 villages were selected (15 in each stratum) and a total of 774 households were interviewed. This survey aimed to assess the potential added effect of 'intense' BCC interventions in three Western provinces. Conducted 2 years after start of these efforts, 'non-intense' BCC (niBBC) interventions (e.g., radio or TV) were compared to "intense" BCC (iBBC) implemented through a set of interpersonal communication strategies such as VMWs, VHVs, mobile broadcasting units and listener viewer clubs. In both groups, the knowledge of the mode of malaria transmission was high (96.9 vs 97.2 %; p = 0.83), as well as of fever as a symptom (91.5 vs 93.5 %; p = 0.38). Knowledge of local risk factors, such as staying in the forest (39.7 vs 30.7 %; p = 0.17) or the farm (7.1 vs 5.1 %; p = 0.40) was low in both groups. Few respondents in either group knew that they must get tested if they suspected malaria (0.3 vs 0.1; p = 0.69). However, iBBC increased the discussions about malaria in the family (51.7 vs 35.8 %; p = 0.002) and reported prompt access to treatment in case of fever (77.1 vs 59.4 %; p < 0.01). The use of iBCC supported positive improvements in both attitudes and behaviours among the population with regard to malaria compared to mass media (niBCC) only. The significantly increase in people seeking treatment for fever in iBCC villages supports Objective Five of the Strategic Plan in the Cambodia Malaria Elimination Action Framework (2016-2020). Therefore, this study provides evidence for the planning and implementation of future BCC interventions to achieve the elimination of artemisinin resistant Plasmodium falciparum malaria.

The Open Cluster Chemical Abundances and Mapping (OCCAM) Survey: Current Status

NASA Astrophysics Data System (ADS)

Frinchaboy, Peter; O'Connell, Julia; Donor, John; Cunha, Katia; Thompson, Benjamin; Melendez, Matthew; Shetrone, Matthew; Zasowski, Gail; Majewski, Steven R.; APOGEE TEAM

2018-01-01

The Open Cluster Chemical Analysis and Mapping (OCCAM) survey aims to produce a comprehensive, uniform, infrared-based data set forhundreds of open clusters, and constrain key Galactic dynamical and chemical parameters using the SDSS/APOGEE survey and follow-up from the McDonald Observatory Otto Struve 2.1-m telescope and Sandiford Cass Echelle Spectrograph (R ~ 60,000). We report on multi-element radial abundance gradients obtained from a sample of over 30 disk open clusters. The APOGEE chemical abundances were derived automatically by the ASPCAP pipeline and these are part of the SDSS IV Data Release 14, optical follow-up were analyzed using equivalent width analysis and spectral synthesis. We present the current open cluster sample that spans a significant range in age allowing exploration of the evolution of the Galactic abundance gradients. This work is supported by an NSF AAG grants AST-1311835 & AST-1715662.

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

PubMed

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

2015-06-15

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

Subaru Weak-Lensing Survey II: Multi-Object Spectroscopy and Cluster Masses

NASA Astrophysics Data System (ADS)

Hamana, Takashi; Miyazaki, Satoshi; Kashikawa, Nobunari; Ellis, Richard S.; Massey, Richard J.; Refregier, Alexandre; Taylor, James E.

2009-08-01

We present the first results of a multi-object spectroscopic campaign to follow up cluster candidates located via weak lensing. Our main goals are to search for spatial concentrations of galaxies that are plausible optical counterparts of the weak-lensing signals, and to determine the cluster redshifts from those of member galaxies. Around each of 36 targeted cluster candidates, we obtained 15-32 galaxy redshifts. For 28 of these targets, we confirmed a secure cluster identification, with more than five spectroscopic galaxies within a velocity of ±3000km s-1. This includes three cases where two clusters at different redshifts are projected along the same line-of-sight. In 6 of the 8 unconfirmed targets, we found multiple small galaxy concentrations at different redshifts, each containing at least three spectroscopic galaxies. The weak-lensing signal around those systems was thus probably created by the projection of groups or small clusters along the same line-of-sight. In both of the remaining two targets, a single small galaxy concentration was found. In some candidate super-cluster systems, we found additional evidence of filaments connecting the main density peak to an additional nearby structure. For a subsample of our most cleanly measured clusters, we investigated the statistical relation between their weak-lensing mass (MNFW, σSIS) and the velocity dispersion of their member galaxies (σv), comparing our sample with optically and X-ray selected samples from the literature. Our lensing-selected clusters are consistent with σv = σSIS, with a similar scatter to that of optically and X-ray selected clusters. We also derived an empirical relation between the cluster mass and the galaxy velocity dispersion, M200E(z) = 11.0 × 1014 × (σv/1000km s-1)3.0 h-1 Modot, which is in reasonable agreement with predictions of N-body simulations in the Λ CDM cosmology.

Hierarchical Cluster Analysis of Three-Dimensional Reconstructions of Unbiased Sampled Microglia Shows not Continuous Morphological Changes from Stage 1 to 2 after Multiple Dengue Infections in Callithrix penicillata

PubMed Central

Diniz, Daniel G.; Silva, Geane O.; Naves, Thaís B.; Fernandes, Taiany N.; Araújo, Sanderson C.; Diniz, José A. P.; de Farias, Luis H. S.; Sosthenes, Marcia C. K.; Diniz, Cristovam G.; Anthony, Daniel C.; da Costa Vasconcelos, Pedro F.; Picanço Diniz, Cristovam W.

2016-01-01

It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous. PMID:27047345

Hierarchical Cluster Analysis of Three-Dimensional Reconstructions of Unbiased Sampled Microglia Shows not Continuous Morphological Changes from Stage 1 to 2 after Multiple Dengue Infections in Callithrix penicillata.

PubMed

Diniz, Daniel G; Silva, Geane O; Naves, Thaís B; Fernandes, Taiany N; Araújo, Sanderson C; Diniz, José A P; de Farias, Luis H S; Sosthenes, Marcia C K; Diniz, Cristovam G; Anthony, Daniel C; da Costa Vasconcelos, Pedro F; Picanço Diniz, Cristovam W

2016-01-01

It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous.

Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

USGS Publications Warehouse

Smith, D.R.; Rogala, J.T.; Gray, B.R.; Zigler, S.J.; Newton, T.J.

2011-01-01

Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

Merging history of three bimodal clusters

NASA Astrophysics Data System (ADS)

Maurogordato, S.; Sauvageot, J. L.; Bourdin, H.; Cappi, A.; Benoist, C.; Ferrari, C.; Mars, G.; Houairi, K.

2011-01-01

We present a combined X-ray and optical analysis of three bimodal galaxy clusters selected as merging candidates at z ~ 0.1. These targets are part of MUSIC (MUlti-Wavelength Sample of Interacting Clusters), which is a general project designed to study the physics of merging clusters by means of multi-wavelength observations. Observations include spectro-imaging with XMM-Newton EPIC camera, multi-object spectroscopy (260 new redshifts), and wide-field imaging at the ESO 3.6 m and 2.2 m telescopes. We build a global picture of these clusters using X-ray luminosity and temperature maps together with galaxy density and velocity distributions. Idealized numerical simulations were used to constrain the merging scenario for each system. We show that A2933 is very likely an equal-mass advanced pre-merger ~200 Myr before the core collapse, while A2440 and A2384 are post-merger systems (~450 Myr and ~1.5 Gyr after core collapse, respectively). In the case of A2384, we detect a spectacular filament of galaxies and gas spreading over more than 1 h-1 Mpc, which we infer to have been stripped during the previous collision. The analysis of the MUSIC sample allows us to outline some general properties of merging clusters: a strong luminosity segregation of galaxies in recent post-mergers; the existence of preferential axes - corresponding to the merging directions - along which the BCGs and structures on various scales are aligned; the concomitance, in most major merger cases, of secondary merging or accretion events, with groups infalling onto the main cluster, and in some cases the evidence of previous merging episodes in one of the main components. These results are in good agreement with the hierarchical scenario of structure formation, in which clusters are expected to form by successive merging events, and matter is accreted along large-scale filaments. Based on data obtained with the European Southern Observatory, Chile (programs 072.A-0595, 075.A-0264, and 079.A-0425).Tables 5-7 are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/525/A79

a Snapshot Survey of X-Ray Selected Central Cluster Galaxies

NASA Astrophysics Data System (ADS)

Edge, Alastair

1999-07-01

Central cluster galaxies are the most massive stellar systems known and have been used as standard candles for many decades. Only recently have central cluster galaxies been recognised to exhibit a wide variety of small scale {<100 pc} features that can only be reliably detected with HST resolution. The most intriguing of these are dust lanes which have been detected in many central cluster galaxies. Dust is not expected to survive long in the hostile cluster environment unless shielded by the ISM of a disk galaxy or very dense clouds of cold gas. WFPC2 snapshot images of a representative subset of the central cluster galaxies from an X-ray selected cluster sample would provide important constraints on the formation and evolution of dust in cluster cores that cannot be obtained from ground-based observations. In addition, these images will allow the AGN component, the frequency of multiple nuclei, and the amount of massive-star formation in central cluster galaxies to be ass es sed. The proposed HST observatio ns would also provide high-resolution images of previously unresolved gravitational arcs in the most massive clusters in our sample resulting in constraints on the shape of the gravitational potential of these systems. This project will complement our extensive multi-frequency work on this sample that includes optical spectroscopy and photometry, VLA and X-ray images for the majority of the 210 targets.

Knowledge and practices related to plague in an endemic area of Uganda.

PubMed

Kugeler, Kiersten J; Apangu, Titus; Forrester, Joseph D; Griffith, Kevin S; Candini, Gordian; Abaru, Janet; Okoth, Jimmy F; Apio, Harriet; Ezama, Geoffrey; Okello, Robert; Brett, Meghan; Mead, Paul

2017-11-01

Plague is a virulent zoonosis reported most commonly from Sub-Saharan Africa. Early treatment with antibiotics is important to prevent mortality. Understanding knowledge gaps and common behaviors informs the development of educational efforts to reduce plague mortality. A multi-stage cluster-sampled survey of 420 households was conducted in the plague-endemic West Nile region of Uganda to assess knowledge of symptoms and causes of plague and health care-seeking practices. Most (84%) respondents were able to correctly describe plague symptoms; approximately 75% linked plague with fleas and dead rats. Most respondents indicated that they would seek health care at a clinic for possible plague; however plague-like symptoms were reportedly common, and in practice, persons sought care for those symptoms at a health clinic infrequently. Persons in the plague-endemic region of Uganda have a high level of understanding of plague, yet topics for targeted educational messages are apparent. Published by Elsevier Ltd.

The association of urbanisation with the prevalence of dental caries among schoolchildren in Nigeria new capital territory.

PubMed

el-Nadeef, M A; Adegbembo, A O; Honkala, E

1998-02-01

The aim of this study was to examine the association of urbanisation and social class with dental caries. A multi-stage stratified cluster sampling technique was used to select schoolchildren (n = 915). Clinical examination was carried out in daylight according to WHO criteria. The distribution of the subjects between strata was: 315 (urban); 303 (semi-urban) and 297 (rural). The mean age of subjects in each strata was 11.4 years. The mean number of decayed teeth (DT) in the respective strata were 27 per cent; 24 per cent; and 12 per cent. Urban children and semi-urban had higher risk for caries than their rural reference group. Urbanisation had no significant effect on the caries prevalence when social class was controlled except among subjects from the low social class in semi-urban areas. The development of satellite towns around big cities do have implications for planning oral health services.

Kinematic Clues to OB Field Star Origins: Radial Velocities, Runaways, and Binaries

NASA Astrophysics Data System (ADS)

Januszewski, Helen; Castro, Norberto; Oey, Sally; Becker, Juliette; Kratter, Kaitlin M.; Mateo, Mario; Simón-Díaz, Sergio; Bjorkman, Jon E.; Bjorkman, Karen; Sigut, Aaron; Smullen, Rachel; M2FS Team

2018-01-01

Field OB stars are a crucial probe of star formation in extreme conditions. Properties of massive stars formed in relative isolation can distinguish between competing star formation theories, while the statistics of runaway stars allow an indirect test of the densest conditions in clusters. To address these questions, we have obtained multi-epoch, spectroscopic observations for a spatially complete sample of 48 OB field stars in the SMC Wing with the IMACS and M2FS multi-object spectrographs at the Magellan Telescopes. The observations span 3-6 epochs per star, with sampling frequency ranging from one day to about one year. From these spectra, we have calculated the radial velocities (RVs) and, in particular, the systemic velocities for binaries. Thus, we present the intrinsic RV distribution largely uncontaminated by binary motions. We estimate the runaway frequency, corresponding to the high velocity stars in our sample, and we also constrain the binary frequency. The binary frequency and fitted orbital parameters also place important constraints on star formation theories, as these properties drive the process of runaway ejection in clusters, and we discuss these properties as derived from our sample. This unique kinematic analysis of a high mass field star population thus provides a new look at the processes governing formation and interaction of stars in environments at extreme densities, from isolation to dense clusters.

Optical Tweezers for Sample Fixing in Micro-Diffraction Experiments

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

Amenitsch, H.; Rappolt, M.; Sartori, B.

2007-01-19

In order to manipulate, characterize and measure the micro-diffraction of individual structural elements down to single phospholipid liposomes we have been using optical tweezers (OT) combined with an imaging microscope. We were able to install the OT system at the microfocus beamline ID13 at the ESRF and trap clusters of about 50 multi-lamellar liposomes (< 10 {mu}m large cluster). Further we have performed a scanning diffraction experiment with a 1 micrometer beam to demonstrate the fixing capabilities and to confirm the size of the liposome cluster by X-ray diffraction.

Intra-class correlation estimates for assessment of vitamin A intake in children.

PubMed

Agarwal, Girdhar G; Awasthi, Shally; Walter, Stephen D

2005-03-01

In many community-based surveys, multi-level sampling is inherent in the design. In the design of these studies, especially to calculate the appropriate sample size, investigators need good estimates of intra-class correlation coefficient (ICC), along with the cluster size, to adjust for variation inflation due to clustering at each level. The present study used data on the assessment of clinical vitamin A deficiency and intake of vitamin A-rich food in children in a district in India. For the survey, 16 households were sampled from 200 villages nested within eight randomly-selected blocks of the district. ICCs and components of variances were estimated from a three-level hierarchical random effects analysis of variance model. Estimates of ICCs and variance components were obtained at village and block levels. Between-cluster variation was evident at each level of clustering. In these estimates, ICCs were inversely related to cluster size, but the design effect could be substantial for large clusters. At the block level, most ICC estimates were below 0.07. At the village level, many ICC estimates ranged from 0.014 to 0.45. These estimates may provide useful information for the design of epidemiological studies in which the sampled (or allocated) units range in size from households to large administrative zones.

X-Ray Properties of Lensing-Selected Clusters

NASA Astrophysics Data System (ADS)

Paterno-Mahler, Rachel; Sharon, Keren; Bayliss, Matthew; McDonald, Michael; Gladders, Michael; Johnson, Traci; Dahle, Hakon; Rigby, Jane R.; Whitaker, Katherine E.; Florian, Michael; Wuyts, Eva

2017-08-01

I will present preliminary results from the Michigan Swift X-ray observations of clusters from the Sloan Giant Arcs Survey (SGAS). These clusters were lensing selected based on the presence of a giant arc visible from SDSS. I will characterize the morphology of the intracluster medium (ICM) of the clusters in the sample, and discuss the offset between the X-ray centroid, the mass centroid as determined by strong lensing analysis, and the BCG position. I will also present early-stage work on the scaling relation between the lensing mass and the X-ray luminosity.

Combining evidence from multiple electronic health care databases: performances of one-stage and two-stage meta-analysis in matched case-control studies.

PubMed

La Gamba, Fabiola; Corrao, Giovanni; Romio, Silvana; Sturkenboom, Miriam; Trifirò, Gianluca; Schink, Tania; de Ridder, Maria

2017-10-01

Clustering of patients in databases is usually ignored in one-stage meta-analysis of multi-database studies using matched case-control data. The aim of this study was to compare bias and efficiency of such a one-stage meta-analysis with a two-stage meta-analysis. First, we compared the approaches by generating matched case-control data under 5 simulated scenarios, built by varying: (1) the exposure-outcome association; (2) its variability among databases; (3) the confounding strength of one covariate on this association; (4) its variability; and (5) the (heterogeneous) confounding strength of two covariates. Second, we made the same comparison using empirical data from the ARITMO project, a multiple database study investigating the risk of ventricular arrhythmia following the use of medications with arrhythmogenic potential. In our study, we specifically investigated the effect of current use of promethazine. Bias increased for one-stage meta-analysis with increasing (1) between-database variance of exposure effect and (2) heterogeneous confounding generated by two covariates. The efficiency of one-stage meta-analysis was slightly lower than that of two-stage meta-analysis for the majority of investigated scenarios. Based on ARITMO data, there were no evident differences between one-stage (OR = 1.50, CI = [1.08; 2.08]) and two-stage (OR = 1.55, CI = [1.12; 2.16]) approaches. When the effect of interest is heterogeneous, a one-stage meta-analysis ignoring clustering gives biased estimates. Two-stage meta-analysis generates estimates at least as accurate and precise as one-stage meta-analysis. However, in a study using small databases and rare exposures and/or outcomes, a correct one-stage meta-analysis becomes essential. Copyright © 2017 John Wiley & Sons, Ltd.

Computational Plume Modeling of COnceptual ARES Vehicle Stage Tests

NASA Technical Reports Server (NTRS)

Allgood, Daniel C.; Ahuja, Vineet

2007-01-01

The plume-induced environment of a conceptual ARES V vehicle stage test at the NASA Stennis Space Center (NASA-SSC) was modeled using computational fluid dynamics (CFD). A full-scale multi-element grid was generated for the NASA-SSC B-2 test stand with the ARES V stage being located in a proposed off-center forward position. The plume produced by the ARES V main power plant (cluster of five RS-68 LOX/LH2 engines) was simulated using a multi-element flow solver - CRUNCH. The primary objective of this work was to obtain a fundamental understanding of the ARES V plume and its impingement characteristics on the B-2 flame-deflector. The location, size and shape of the impingement region were quantified along with the un-cooled deflector wall pressures, temperatures and incident heating rates. Issues with the proposed tests were identified and several of these addressed using the CFD methodology. The final results of this modeling effort will provide useful data and boundary conditions in upcoming engineering studies that are directed towards determining the required facility modifications for ensuring safe and reliable stage testing in support of the Constellation Program.

Automatic Clustering Using Multi-objective Particle Swarm and Simulated Annealing

PubMed Central

Abubaker, Ahmad; Baharum, Adam; Alrefaei, Mahmoud

2015-01-01

This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, “MOPSOSA”. The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO) and the Multi-Objective Simulated Annealing (MOSA). Three cluster validity indices were optimized simultaneously to establish the suitable number of clusters and the appropriate clustering for a dataset. The first cluster validity index is centred on Euclidean distance, the second on the point symmetry distance, and the last cluster validity index is based on short distance. A number of algorithms have been compared with the MOPSOSA algorithm in resolving clustering problems by determining the actual number of clusters and optimal clustering. Computational experiments were carried out to study fourteen artificial and five real life datasets. PMID:26132309

Estimation of winter wheat canopy nitrogen density at different growth stages based on Multi-LUT approach

NASA Astrophysics Data System (ADS)

Li, Zhenhai; Li, Na; Li, Zhenhong; Wang, Jianwen; Liu, Chang

2017-10-01

Rapid real-time monitoring of wheat nitrogen (N) status is crucial for precision N management during wheat growth. In this study, Multi Lookup Table (Multi-LUT) approach based on the N-PROSAIL model parameters setting at different growth stages was constructed to estimating canopy N density (CND) in winter wheat. The results showed that the estimated CND was in line with with measured CND, with the determination coefficient (R2) and the corresponding root mean square error (RMSE) values of 0.80 and 1.16 g m-2, respectively. Time-consuming of one sample estimation was only 6 ms under the test machine with CPU configuration of Intel(R) Core(TM) i5-2430 @2.40GHz quad-core. These results confirmed the potential of using Multi-LUT approach for CND retrieval in winter wheat at different growth stages and under variables climatic conditions.

Algorithms for Large-Scale Astronomical Problems

DTIC Science & Technology

2013-08-01

implemented as a succession of Hadoop MapReduce jobs and sequential programs written in Java . The sampling and splitting stages are implemented as...one MapReduce job, the partitioning and clustering phases make up another job. The merging stage is implemented as a stand-alone Java program. The...Merging. The merging stage is implemented as a sequential Java program that reads the files with the shell information, which were generated by

VizieR Online Data Catalog: LAMOST survey of star clusters in M31. II. (Chen+, 2016)

NASA Astrophysics Data System (ADS)

Chen, B.; Liu, X.; Xiang, M.; Yuan, H.; Huang, Y.; Shi, J.; Fan, Z.; Huo, Z.; Wang, C.; Ren, J.; Tian, Z.; Zhang, H.; Liu, G.; Cao, Z.; Zhang, Y.; Hou, Y.; Wang, Y.

2016-09-01

We select a sample of 306 massive star clusters observed with the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) in the vicinity fields of M31 and M33. Massive clusters in our sample are all selected from the catalog presented in Paper I (Chen et al. 2015, Cat. J/other/RAA/15.1392), including five newly discovered clusters selected with the SDSS photometry, three newly confirmed, and 298 previously known clusters from Revised Bologna Catalogue (RBC; Galleti et al. 2012, Cat. V/143; http://www.bo.astro.it/M31/). Since then another two objects, B341 and B207, have also been observed with LAMOST, and they are included in the current analysis. The current sample does not include those listed in Paper I but is selected from Johnson et al. 2012 (Cat. J/ApJ/752/95) since most of them are young but not so massive. All objects are observed with LAMOST between 2011 September and 2014 June. Table1 lists the name, position, and radial velocity of all sample clusters analyzed in the current work. The LAMOST spectra cover the wavelength range 3700-9000Å at a resolving power of R~1800. Details about the observations and data reduction can be found in Paper I. The median signal-to-noise ratio (S/N) per pixel at 4750 and 7450Å of spectra of all clusters in the current sample are, respectively, 14 and 37. Essentially all spectra have S/N(4750Å)>5 except for the spectra of 18 clusters. The latter have S/N(7540Å)>10. Peacock et al. 2010 (Cat. J/MNRAS/402/803) retrieved images of M31 star clusters and candidates from the SDSS archive and extracted ugriz aperture photometric magnitudes from those objects using the SExtractor. They present a catalog containing homogeneous ugriz photometry of 572 star clusters and 373 candidates. Among them, 299 clusters are in our sample. (2 data files).

Application of the theory of reasoned action to promoting breakfast consumption.

PubMed

Hosseini, Zahra; Gharlipour Gharghani, Zabihollah; Mansoori, Anahita; Aghamolaei, Teamur; Mohammadi Nasrabadi, Maryam

2015-01-01

Breakfast is the most important daily meal, but neglected more than other meals by children and adolescents. The aim of this study was to evaluate the effectiveness of an educational intervention, based on the Theory of Reasoned Action (TRA) to increase breakfast consumption among school children in Bandar Abbas, Iran. In this quasi experimental study which was conducted in 2012, 88 students of four secondary schools in Bandar Abbas, south of Iran, were enrolled. Multi-stage cluster sampling was performed with random allocation of interventional and control groups. The study tool was a questionnaire which was filled by the students before and two months after the educational intervention. For data analysis, statistical tests including paired-samples t-test, independent samples t-test, Wilcoxon test, and Mann-Whitney test were used through SPSS v.18 software. The result of the study showed that application of TRA significantly increased scores of behavior of breakfast consumption (p<0.01). After the intervention, a significant increase was revealed in all nutrition intakes, except for fat and sugar (p<0.01). The findings support application of the TRA in improving the intention and behavior of breakfast consumption. Applying this theory for designing interventions to increase breakfast eating is recommended.

Multi-Scale/Multi-Functional Probabilistic Composite Fatigue

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A multi-level (multi-scale/multi-functional) evaluation is demonstrated by applying it to three different sample problems. These problems include the probabilistic evaluation of a space shuttle main engine blade, an engine rotor and an aircraft wing. The results demonstrate that the blade will fail at the highest probability path, the engine two-stage rotor will fail by fracture at the rim and the aircraft wing will fail at 109 fatigue cycles with a probability of 0.9967.

The SAMI Galaxy Survey: the cluster redshift survey, target selection and cluster properties

NASA Astrophysics Data System (ADS)

Owers, M. S.; Allen, J. T.; Baldry, I.; Bryant, J. J.; Cecil, G. N.; Cortese, L.; Croom, S. M.; Driver, S. P.; Fogarty, L. M. R.; Green, A. W.; Helmich, E.; de Jong, J. T. A.; Kuijken, K.; Mahajan, S.; McFarland, J.; Pracy, M. B.; Robotham, A. G. S.; Sikkema, G.; Sweet, S.; Taylor, E. N.; Verdoes Kleijn, G.; Bauer, A. E.; Bland-Hawthorn, J.; Brough, S.; Colless, M.; Couch, W. J.; Davies, R. L.; Drinkwater, M. J.; Goodwin, M.; Hopkins, A. M.; Konstantopoulos, I. S.; Foster, C.; Lawrence, J. S.; Lorente, N. P. F.; Medling, A. M.; Metcalfe, N.; Richards, S. N.; van de Sande, J.; Scott, N.; Shanks, T.; Sharp, R.; Thomas, A. D.; Tonini, C.

2017-06-01

We describe the selection of galaxies targeted in eight low-redshift clusters (APMCC0917, A168, A4038, EDCC442, A3880, A2399, A119 and A85; 0.029 < z < 0.058) as part of the Sydney-AAO Multi-Object Integral field spectrograph Galaxy Survey (SAMI-GS). We have conducted a redshift survey of these clusters using the AAOmega multi-object spectrograph on the 3.9-m Anglo-Australian Telescope. The redshift survey is used to determine cluster membership and to characterize the dynamical properties of the clusters. In combination with existing data, the survey resulted in 21 257 reliable redshift measurements and 2899 confirmed cluster member galaxies. Our redshift catalogue has a high spectroscopic completeness (˜94 per cent) for rpetro ≤ 19.4 and cluster-centric distances R < 2R200. We use the confirmed cluster member positions and redshifts to determine cluster velocity dispersion, R200, virial and caustic masses, as well as cluster structure. The clusters have virial masses 14.25 ≤ log(M200/M⊙) ≤ 15.19. The cluster sample exhibits a range of dynamical states, from relatively relaxed-appearing systems, to clusters with strong indications of merger-related substructure. Aperture- and point spread function matched photometry are derived from Sloan Digital Sky Survey and VLT Survey Telescope/ATLAS imaging and used to estimate stellar masses. These estimates, in combination with the redshifts, are used to define the input target catalogue for the cluster portion of the SAMI-GS. The primary SAMI-GS cluster targets have R

Stages of change in adults who have failed an online hearing screening.

PubMed

Laplante-Lévesque, Ariane; Brännström, K Jonas; Ingo, Elisabeth; Andersson, Gerhard; Lunner, Thomas

2015-01-01

Hearing screening has been proposed to promote help-seeking and rehabilitation in adults with hearing impairment. However, some longitudinal studies point to low help-seeking and subsequent rehabilitation after a failed hearing screening (positive screening result). Some barriers to help-seeking and rehabilitation could be intrinsic to the profiles and needs of people who have failed a hearing screening. Theories of health behavior change could help to understand this population. One of these theories is the transtheoretical (stages-of-change) model of health behavior change, which describes profiles and needs of people facing behavior changes such as seeking help and taking up rehabilitation. According to this model, people go through distinct stages toward health behavior change: precontemplation, contemplation, action, and finally, maintenance. The present study describes the psychometric properties (construct validity) of the stages of change in adults who have failed an online hearing screening. Stages of change were measured with the University of Rhode Island Change Assessment (URICA). Principal component analysis is presented, along with cluster analysis. Internal consistency was investigated. Finally, relationships between URICA scores and speech-in-noise recognition threshold, self-reported hearing disability, and self-reported duration of hearing disability are presented. In total, 224 adults who had failed a Swedish online hearing screening test (measure of speech-in-noise recognition) completed further questionnaires online, including the URICA. A principal component analysis identified the stages of precontemplation, contemplation, and action, plus an additional stage, termed preparation (between contemplation and action). According to the URICA, half (50%) of the participants were in the preparation stage of change. The contemplation stage was represented by 38% of participants, while 9% were in the precontemplation stage. Finally, the action stage was represented by approximately 3% of the participants. Cluster analysis identified four stages-of-change clusters: they were named decision making (44% of sample), participation (28% of sample), indecision (16% of sample), and reluctance (12% of sample). The construct validity of the model was good. Participants who reported a more advanced stage of change had significantly greater self-reported hearing disability. However, participants who reported a more advanced stage of change did not have a significantly worse speech-in-noise recognition threshold or reported a significantly longer duration of hearing impairment. The additional stage this study uncovered, and which other studies have also uncovered, preparation, highlights the need for adequate guidance for adults who are yet to seek help for their hearing. The fact that very few people were in the action stage (approximately 3% of the sample) signals that screening alone is unlikely to be enough to improve help-seeking and rehabilitation rates. As expected, people in the later stages of change reported significantly greater hearing disability. The lack of significant relationships between stages-of-change measures and speech-in-noise recognition threshold and self-reported duration of hearing disability highlights the complex interplay between impairment, disability, and behaviors in adults who have failed an online hearing screening and who are yet to seek help.

A Lagrangian analysis of cold cloud clusters and their life cycles with satellite observations

PubMed Central

Esmaili, Rebekah Bradley; Tian, Yudong; Vila, Daniel Alejandro; Kim, Kyu-Myong

2018-01-01

Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi-coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Niño. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics. PMID:29744257

Simple Epidemiological Dynamics Explain Phylogenetic Clustering of HIV from Patients with Recent Infection

PubMed Central

Volz, Erik M.; Koopman, James S.; Ward, Melissa J.; Brown, Andrew Leigh; Frost, Simon D. W.

2012-01-01

Phylogenies of highly genetically variable viruses such as HIV-1 are potentially informative of epidemiological dynamics. Several studies have demonstrated the presence of clusters of highly related HIV-1 sequences, particularly among recently HIV-infected individuals, which have been used to argue for a high transmission rate during acute infection. Using a large set of HIV-1 subtype B pol sequences collected from men who have sex with men, we demonstrate that virus from recent infections tend to be phylogenetically clustered at a greater rate than virus from patients with chronic infection (‘excess clustering’) and also tend to cluster with other recent HIV infections rather than chronic, established infections (‘excess co-clustering’), consistent with previous reports. To determine the role that a higher infectivity during acute infection may play in excess clustering and co-clustering, we developed a simple model of HIV infection that incorporates an early period of intensified transmission, and explicitly considers the dynamics of phylogenetic clusters alongside the dynamics of acute and chronic infected cases. We explored the potential for clustering statistics to be used for inference of acute stage transmission rates and found that no single statistic explains very much variance in parameters controlling acute stage transmission rates. We demonstrate that high transmission rates during the acute stage is not the main cause of excess clustering of virus from patients with early/acute infection compared to chronic infection, which may simply reflect the shorter time since transmission in acute infection. Higher transmission during acute infection can result in excess co-clustering of sequences, while the extent of clustering observed is most sensitive to the fraction of infections sampled. PMID:22761556

A Lagrangian analysis of cold cloud clusters and their life cycles with satellite observations.

PubMed

Esmaili, Rebekah Bradley; Tian, Yudong; Vila, Daniel Alejandro; Kim, Kyu-Myong

2016-10-16

Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi-coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Niño. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics.

A Lagrangian Analysis of Cold Cloud Clusters and Their Life Cycles With Satellite Observations

NASA Technical Reports Server (NTRS)

Esmaili, Rebekah Bradley; Tian, Yudong; Vila, Daniel Alejandro; Kim, Kyu-Myong

2016-01-01

Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Nino. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics.

VizieR Online Data Catalog: 44 SZ-selected galaxy clusters ACT observations (Sifon+, 2016)

NASA Astrophysics Data System (ADS)

Sifon, C.; Battaglia, N.; Hasselfield, M.; Menanteau, F.; Barrientos, L. F.; Bond, J. R.; Crichton, D.; Devlin, M. J.; Dunner, R.; Hilton, M.; Hincks, A. D.; Hlozek, R.; Huffenberger, K. M.; Hughes, J. P.; Infante, L.; Kosowsky, A.; Marsden, D.; Marriage, T. A.; Moodley, K.; Niemack, M. D.; Page, L. A.; Spergel, D. N.; Staggs, S. T.; Trac, H.; Wollack, E. J.

2017-11-01

ACT is a 6-metre off-axis Gregorian telescope located at an altitude of 5200um in the Atacama desert in Chile, designed to observe the CMB at arcminute resolution. Galaxy clusters were detected in the 148GHz band by matched-filtering the maps with the pressure profile suggested by Arnaud et al. (2010A&A...517A..92A), fit to X-ray selected local (z<0.2) clusters, with varying cluster sizes,θ500, from 1.18 to 27-arcmin. Because of the complete overlap of ACT equatorial observations with Sloan Digital Sky Survey Data Release 8 (SDSS DR8; Aihara et al., 2011ApJS..193...29A) imaging, all cluster candidates were assessed with optical data (Menanteau et al., 2013ApJ...765...67M). We observed 20 clusters from the equatorial sample with the Gemini Multi-Object Spectrograph (GMOS) on the Gemini-South telescope, split in semesters 2011B (ObsID:GS-2011B-C-1, PI:Barrientos/Menanteau) and 2012A (ObsID:GS-2012A-C-1, PI:Menanteau), prioritizing clusters in the cosmological sample at 0.3

Vascular endothelial growth factor and nitric oxide synthase expression in human tooth germ development.

PubMed

Mastrangelo, F; Sberna, M T; Tettamanti, L; Cantatore, G; Tagliabue, A; Gherlone, E

2016-01-01

Vascular Endothelia Growth Factor (VEGF) and Nitric Oxide Synthase (NOS) expression, were evaluated in human tooth germs at two different stages of embryogenesis, to clarify the role of angiogenesis during tooth tissue differentiation and growth. Seventy-two third molar germ specimens were selected during oral surgery. Thirty-six were in the early stage and 36 in the later stage of tooth development. The samples were evaluated with Semi-quantitative Reverse Transcription-Polymerase chain Reaction analyses (RT-PcR), Western blot analysis (WB) and immunohistochemical analysis. Western blot and immunohistochemical analysis showed a VEGF and NOS 1-2-3 positive reaction in all samples analysed. VEGF high positive decrease reaction was observed in stellate reticulum cells, ameloblast and odontoblast clusters in early stage compared to later stage of tooth germ development. Comparable VEGF expression was observed in endothelial cells of early and advanced stage growth. NOS1 and NOS3 expressions showed a high increased value in stellate reticulum cells, and ameloblast and odontoblast clusters in advanced stage compared to early stage of development. The absence or only moderate positive reaction of NOS2 was detected in all the different tissues. Positive NOS2 expression showed in advanced stage of tissue development compared to early stage. The action of VEGF and NOS molecules are important mediators of angiogenesis during dental tissue development. VEGF high positive expression in stellate reticulum cells in the early stage of tooth development compared to the later stage and the other cell types, suggests a critical role of the stellate reticulum during dental embryo-morphogenesis.

Automatic sleep staging using multi-dimensional feature extraction and multi-kernel fuzzy support vector machine.

PubMed

Zhang, Yanjun; Zhang, Xiangmin; Liu, Wenhui; Luo, Yuxi; Yu, Enjia; Zou, Keju; Liu, Xiaoliang

2014-01-01

This paper employed the clinical Polysomnographic (PSG) data, mainly including all-night Electroencephalogram (EEG), Electrooculogram (EOG) and Electromyogram (EMG) signals of subjects, and adopted the American Academy of Sleep Medicine (AASM) clinical staging manual as standards to realize automatic sleep staging. Authors extracted eighteen different features of EEG, EOG and EMG in time domains and frequency domains to construct the vectors according to the existing literatures as well as clinical experience. By adopting sleep samples self-learning, the linear combination of weights and parameters of multiple kernels of the fuzzy support vector machine (FSVM) were learned and the multi-kernel FSVM (MK-FSVM) was constructed. The overall agreement between the experts' scores and the results presented was 82.53%. Compared with previous results, the accuracy of N1 was improved to some extent while the accuracies of other stages were approximate, which well reflected the sleep structure. The staging algorithm proposed in this paper is transparent, and worth further investigation.

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.

The evolution of the Y-M scaling relation in MUSIC clusters

NASA Astrophysics Data System (ADS)

Sembolini, F.; Yepes, G.; De Petris, M.; Gottlöber, S.; Lamagna, L.; Comis, B.

2013-04-01

This work describes the baryon content and Sunyaev-Zeld'ovich properties of the MUSIC (Marenostrum-MultiDark SImulations of galaxy clusters) dataset and their evolution with redshift and aperture radius. The MUSIC dataset is one of the largest samples of hydrodynamically simulated galaxy clusters (more than 2000 objects, including more than 500 clusters). We show that when the effects of cooling and stellar feedbacks are properly taken into account, the gas fraction of the MUSIC clusters consistently agrees with recent observational results. Moreover, the gas fraction has a net dependence with the total mass of the cluster and increases slightly with redshift at high overdensities. The study of the Y-M relation confirms the consistence of the self-similar model, showing no evolution with redshift at low overdensities.

[Violence and post-traumatic stress disorder in childhood].

PubMed

Ximenes, Liana Furtado; de Oliveira, Raquel de Vasconcelos Carvalhães; de Assis, Simone Gonçalves

2009-01-01

This study presents the prevalence of symptoms of Posttraumatic Stress Disorder (PTSD) in 500 schoolchildren (6-13 years old) in São Gonçalo, Rio de Janeiro. It also investigates the association between PTSD, violence and other adverse events in the lives of these children. The multi-stage cluster sampling strategy involved three selection stages. Parents were interviewed about their children's behavior. The instrument used to screen symptoms of PTSD was the Child Behavior Checklist-Posttraumatic Stress Disorder Scale (CBCL-PTSD). Conflict Tactics Scales (CTS) were applied to evaluate family violence and other scales to investigate the socioeconomic profile, familiar relationship, characteristics and adverse events in the lives of the children. Multivariate analysis was performed using a hierarchical model with a significance level of 5%. The prevalence of clinical symptoms of PTSD was of 6.5%. The multivariate analysis suggested an explanation model of PTSD characterized by 18 variables, such as the child's characteristics; specific life events; family violence; and other family factors. The results reveal that it is necessary to work with the child in particularly difficult moments of his/her life in order to prevent or minimize the impact of adverse events on their mental and social functioning.

A random cluster survey and a convenience sample give comparable estimates of immunity to vaccine preventable diseases in children of school age in Victoria, Australia.

PubMed

Kelly, Heath; Riddell, Michaela A; Gidding, Heather F; Nolan, Terry; Gilbert, Gwendolyn L

2002-08-19

We compared estimates of the age-specific population immunity to measles, mumps, rubella, hepatitis B and varicella zoster viruses in Victorian school children obtained by a national sero-survey, using a convenience sample of residual sera from diagnostic laboratories throughout Australia, with those from a three-stage random cluster survey. When grouped according to school age (primary or secondary school) there was no significant difference in the estimates of immunity to measles, mumps, hepatitis B or varicella. Compared with the convenience sample, the random cluster survey estimated higher immunity to rubella in samples from both primary (98.7% versus 93.6%, P = 0.002) and secondary school students (98.4% versus 93.2%, P = 0.03). Despite some limitations, this study suggests that the collection of a convenience sample of sera from diagnostic laboratories is an appropriate sampling strategy to provide population immunity data that will inform Australia's current and future immunisation policies. Copyright 2002 Elsevier Science Ltd.

Are Epiphytic Microbial Communities in the Carposphere of Ripening Grape Clusters (Vitis vinifera L.) Different between Conventional, Organic, and Biodynamic Grapes?

PubMed

Kecskeméti, Elizabeth; Berkelmann-Löhnertz, Beate; Reineke, Annette

2016-01-01

Using barcoded pyrosequencing fungal and bacterial communities associated with grape berry clusters (Vitis vinifera L.) obtained from conventional, organic and biodynamic vineyard plots were investigated in two subsequent years at different stages during berry ripening. The four most abundant operational taxonomic units (OTUs) based on fungal ITS data were Botrytis cinerea, Cladosporium spp., Aureobasidium pullulans and Alternaria alternata which represented 57% and 47% of the total reads in 2010 and 2011, respectively. Members of the genera Sphingomonas, Gluconobacter, Pseudomonas, Erwinia, and Massilia constituted 67% of the total number of bacterial 16S DNA reads in 2010 samples and 78% in 2011 samples. Viticultural management system had no significant effect on abundance of fungi or bacteria in both years and at all three sampling dates. Exceptions were A. alternata and Pseudomonas spp. which were more abundant in the carposphere of conventional compared to biodynamic berries, as well as Sphingomonas spp. which was significantly less abundant on conventional compared to organic berries at an early ripening stage in 2011. In general, there were no significant differences in fungal and bacterial diversity indices or richness evident between management systems. No distinct fungal or bacterial communities were associated with the different maturation stages or management systems, respectively. An exception was the last stage of berry maturation in 2011, where the Simpson diversity index was significantly higher for fungal communities on biodynamic compared to conventional grapes. Our study highlights the existence of complex and dynamic microbial communities in the grape cluster carposphere including both phytopathogenic and potentially antagonistic microorganisms that can have a significant impact on grape production. Such knowledge is particularly relevant for development, selection and application of effective control measures against economically important pathogens present in the grape carposphere.

Are Epiphytic Microbial Communities in the Carposphere of Ripening Grape Clusters (Vitis vinifera L.) Different between Conventional, Organic, and Biodynamic Grapes?

PubMed Central

Kecskeméti, Elizabeth; Berkelmann-Löhnertz, Beate; Reineke, Annette

2016-01-01

Using barcoded pyrosequencing fungal and bacterial communities associated with grape berry clusters (Vitis vinifera L.) obtained from conventional, organic and biodynamic vineyard plots were investigated in two subsequent years at different stages during berry ripening. The four most abundant operational taxonomic units (OTUs) based on fungal ITS data were Botrytis cinerea, Cladosporium spp., Aureobasidium pullulans and Alternaria alternata which represented 57% and 47% of the total reads in 2010 and 2011, respectively. Members of the genera Sphingomonas, Gluconobacter, Pseudomonas, Erwinia, and Massilia constituted 67% of the total number of bacterial 16S DNA reads in 2010 samples and 78% in 2011 samples. Viticultural management system had no significant effect on abundance of fungi or bacteria in both years and at all three sampling dates. Exceptions were A. alternata and Pseudomonas spp. which were more abundant in the carposphere of conventional compared to biodynamic berries, as well as Sphingomonas spp. which was significantly less abundant on conventional compared to organic berries at an early ripening stage in 2011. In general, there were no significant differences in fungal and bacterial diversity indices or richness evident between management systems. No distinct fungal or bacterial communities were associated with the different maturation stages or management systems, respectively. An exception was the last stage of berry maturation in 2011, where the Simpson diversity index was significantly higher for fungal communities on biodynamic compared to conventional grapes. Our study highlights the existence of complex and dynamic microbial communities in the grape cluster carposphere including both phytopathogenic and potentially antagonistic microorganisms that can have a significant impact on grape production. Such knowledge is particularly relevant for development, selection and application of effective control measures against economically important pathogens present in the grape carposphere. PMID:27500633

Adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique algorithm for tackling binary imbalanced datasets in biomedical data classification.

PubMed

Li, Jinyan; Fong, Simon; Sung, Yunsick; Cho, Kyungeun; Wong, Raymond; Wong, Kelvin K L

2016-01-01

An imbalanced dataset is defined as a training dataset that has imbalanced proportions of data in both interesting and uninteresting classes. Often in biomedical applications, samples from the stimulating class are rare in a population, such as medical anomalies, positive clinical tests, and particular diseases. Although the target samples in the primitive dataset are small in number, the induction of a classification model over such training data leads to poor prediction performance due to insufficient training from the minority class. In this paper, we use a novel class-balancing method named adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique (ASCB_DmSMOTE) to solve this imbalanced dataset problem, which is common in biomedical applications. The proposed method combines under-sampling and over-sampling into a swarm optimisation algorithm. It adaptively selects suitable parameters for the rebalancing algorithm to find the best solution. Compared with the other versions of the SMOTE algorithm, significant improvements, which include higher accuracy and credibility, are observed with ASCB_DmSMOTE. Our proposed method tactfully combines two rebalancing techniques together. It reasonably re-allocates the majority class in the details and dynamically optimises the two parameters of SMOTE to synthesise a reasonable scale of minority class for each clustered sub-imbalanced dataset. The proposed methods ultimately overcome other conventional methods and attains higher credibility with even greater accuracy of the classification model.

Influence of exposure differences on city-to-city heterogeneity ...

EPA Pesticide Factsheets

Multi-city population-based epidemiological studies have observed heterogeneity between city-specific fine particulate matter (PM2.5)-mortality effect estimates. These studies typically use ambient monitoring data as a surrogate for exposure leading to potential exposure misclassification. The level of exposure misclassification can differ by city affecting the observed health effect estimate. The objective of this analysis is to evaluate whether previously developed residential infiltration-based city clusters can explain city-to-city heterogeneity in PM2.5 mortality risk estimates. In a prior paper 94 cities were clustered based on residential infiltration factors (e.g. home age/size, prevalence of air conditioning (AC)), resulting in 5 clusters. For this analysis, the association between PM2.5 and all-cause mortality was first determined in 77 cities across the United States for 2001–2005. Next, a second stage analysis was conducted evaluating the influence of cluster assignment on heterogeneity in the risk estimates. Associations between a 2-day (lag 0–1 days) moving average of PM2.5 concentrations and non-accidental mortality were determined for each city. Estimated effects ranged from −3.2 to 5.1% with a pooled estimate of 0.33% (95% CI: 0.13, 0.53) increase in mortality per 10 μg/m3 increase in PM2.5. The second stage analysis determined that cluster assignment was marginally significant in explaining the city-to-city heterogeneity. The health effe

[Study on correction of data bias caused by different missing mechanisms in survey of medical expenditure among students enrolling in Urban Resident Basic Medical Insurance].

PubMed

Zhang, Haixia; Zhao, Junkang; Gu, Caijiao; Cui, Yan; Rong, Huiying; Meng, Fanlong; Wang, Tong

2015-05-01

The study of the medical expenditure and its influencing factors among the students enrolling in Urban Resident Basic Medical Insurance (URBMI) in Taiyuan indicated that non response bias and selection bias coexist in dependent variable of the survey data. Unlike previous studies only focused on one missing mechanism, a two-stage method to deal with two missing mechanisms simultaneously was suggested in this study, combining multiple imputation with sample selection model. A total of 1 190 questionnaires were returned by the students (or their parents) selected in child care settings, schools and universities in Taiyuan by stratified cluster random sampling in 2012. In the returned questionnaires, 2.52% existed not missing at random (NMAR) of dependent variable and 7.14% existed missing at random (MAR) of dependent variable. First, multiple imputation was conducted for MAR by using completed data, then sample selection model was used to correct NMAR in multiple imputation, and a multi influencing factor analysis model was established. Based on 1 000 times resampling, the best scheme of filling the random missing values is the predictive mean matching (PMM) method under the missing proportion. With this optimal scheme, a two stage survey was conducted. Finally, it was found that the influencing factors on annual medical expenditure among the students enrolling in URBMI in Taiyuan included population group, annual household gross income, affordability of medical insurance expenditure, chronic disease, seeking medical care in hospital, seeking medical care in community health center or private clinic, hospitalization, hospitalization canceled due to certain reason, self medication and acceptable proportion of self-paid medical expenditure. The two-stage method combining multiple imputation with sample selection model can deal with non response bias and selection bias effectively in dependent variable of the survey data.

Multi-stage Mass Spectrometry of Poly(vinyl pyrrolidone) and Its Vinyl Succinimide Copolymer Formed upon Exposure to Sodium Hypochlorite

PubMed Central

Fouquet, Thierry; Torimura, Masaki; Sato, Hiroaki

2016-01-01

The degradation routes of poly(vinyl pyrrolidone) (PVP) exposed to sodium hypochlorite (bleach) have been previously investigated using chemical analyses such as infrared spectroscopy. So far, no reports have proposed mass spectrometry (MS) as an alternative tool despite its capability to provide molecular and structural information using its single stage electrospray (ESI) or matrix assisted laser desorption ionization (MALDI) and multi stage (MSn) configurations, respectively. The present study thus reports on the characterization of PVP after its exposure to bleach by high resolution MALDI spiralTOF-MS and Kendrick mass defect analysis providing clues as to the formation of a vinyl pyrrolidone/vinyl succinimide copolymeric degradation product. A thorough investigation of the fragmentation pathways of PVP adducted with sodium and proton allows one main route to be described—namely the release of the pyrrolidone pendant group in a charge remote and charge driven mechanism, respectively. Extrapolating this fragmentation pathway, the oxidation of vinyl pyrrolidone into vinyl succinimide hypothesized from the single stage MS is validated by the detection of an alternative succinimide neutral loss in lieu of the pyrrolidone release in the ESI-MSn spectra of the aged PVP sample. It constitutes an example of application of multi-stage mass spectrometry for the characterization of the degradation of polymeric samples at a molecular level. PMID:27800293

High energy neutrinos and gamma-ray emission from supernovae in compact star clusters

NASA Astrophysics Data System (ADS)

Bykov, A. M.; Ellison, D. C.; Gladilin, P. E.; Osipov, S. M.

2017-01-01

Compact clusters of young massive stars are observed in the Milky Way and in starburst galaxies. The compact clusters with multiple powerful winds of young massive stars and supernova shocks are favorable sites for high-energy particle acceleration. We argue that expanding young supernova (SN) shells in compact stellar clusters can be very efficient PeV CR accelerators. At a stage when a supernova shock is colliding with collective fast winds from massive stars in a compact cluster the Fermi mechanism allows particle acceleration to energies well above the standard limits of diffusive shock acceleration in an isolated SNR. The energy spectrum of protons in such an accelerator is a hard power-law with a broad spectral upturn above TeV before a break at multi-PeV energies, providing a large energy flux in the high-energy end of the spectrum. The acceleration stage in the colliding shock flow lasts for a few hundred years after the supernova explosion producing high-energy CRs that escape the accelerator and diffuse through the ambient matter producing γ-rays and neutrinos in inelastic nuclear collisions. In starburst galaxies a sizeable fraction of core collapse supernovae is expected to occur in compact star clusters and therefore their high energy gamma-ray and neutrino spectra in the PeV energy regime may differ strongly from that of our Galaxy. To test the model with individual sources we briefly discuss the recent H.E.S.S. detections of gamma-rays from two potential candidate sources, Westerlund 1 and HESS J1806-204 in the Milky Way. We argue that this model of compact star clusters, with typical parameters, could produce a neutrino flux sufficient to explain a fraction of the recently detected IceCube South Pole Observatory neutrinos.

Application of ion-induced nucleation mass spectrometry in the analysis of trace gases evolved from a polyimide film during the thermal curing stages

NASA Technical Reports Server (NTRS)

Smith, A. C.

1982-01-01

Trace gases evolved from a polyimide film during its thermal curing stages have been studied using ion-induced nucleation mass spectrometry. The technique involved exposing the test gas sample to a low energy beta source and recording the masses of the ion-induced molecular clusters formed in the reaction chamber. On the basis of the experimentally observed molecular cluster spectra, it has been concluded that the dominant trace component had a molecular weight of 87 atomic mass units. This component has been identified as a molecule of dimethylacetamide (DMAC) which had been used as a solvent in the preparation of the test polyimide specimen. This identification has been further confirmed by comparing the spectra of the test gas sample and the DMAC calibration sample obtained with a conventional mass spectrometer. The advantages of the ion-induced nucleation mass spectrometer versus the conventional mass spectrometer are discussed.

Applying the Hájek Approach in Formula-Based Variance Estimation. Research Report. ETS RR-17-24

ERIC Educational Resources Information Center

Qian, Jiahe

2017-01-01

The variance formula derived for a two-stage sampling design without replacement employs the joint inclusion probabilities in the first-stage selection of clusters. One of the difficulties encountered in data analysis is the lack of information about such joint inclusion probabilities. One way to solve this issue is by applying Hájek's…

Long-lasting insecticide-treated house screens and targeted treatment of productive breeding-sites for dengue vector control in Acapulco, Mexico

PubMed Central

Che-Mendoza, Azael; Guillermo-May, Guillermo; Herrera-Bojórquez, Josué; Barrera-Pérez, Mario; Dzul-Manzanilla, Felipe; Gutierrez-Castro, Cipriano; Arredondo-Jiménez, Juan I.; Sánchez-Tejeda, Gustavo; Vazquez-Prokopec, Gonzalo; Ranson, Hilary; Lenhart, Audrey; Sommerfeld, Johannes; McCall, Philip J.; Kroeger, Axel; Manrique-Saide, Pablo

2015-01-01

Background Long-lasting insecticidal net screens (LLIS) fitted to domestic windows and doors in combination with targeted treatment (TT) of the most productive Aedes aegypti breeding sites were evaluated for their impact on dengue vector indices in a cluster-randomised trial in Mexico between 2011 and 2013. Methods Sequentially over 2 years, LLIS and TT were deployed in 10 treatment clusters (100 houses/cluster) and followed up over 24 months. Cross-sectional surveys quantified infestations of adult mosquitoes, immature stages at baseline (pre-intervention) and in four post-intervention samples at 6-monthly intervals. Identical surveys were carried out in 10 control clusters that received no treatment. Results LLIS clusters had significantly lower infestations compared to control clusters at 5 and 12 months after installation, as measured by adult (male and female) and pupal-based vector indices. After addition of TT to the intervention houses in intervention clusters, indices remained significantly lower in the treated clusters until 18 (immature and adult stage indices) and 24 months (adult indices only) post-intervention. Conclusions These safe, simple affordable vector control tools were well-accepted by study participants and are potentially suitable in many regions at risk from dengue worldwide. PMID:25604761

Planck 2015 results. XXVII. The second Planck catalogue of Sunyaev-Zeldovich sources

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Barrena, R.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Battye, R.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bikmaev, I.; Böhringer, H.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bucher, M.; Burenin, R.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Carvalho, P.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Chon, G.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Dahle, H.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Eisenhardt, P. R. M.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fergusson, J.; Feroz, F.; Ferragamo, A.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Génova-Santos, R. T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Grainge, K. J. B.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Hempel, A.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jin, T.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Khamitov, I.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mak, D. S. Y.; Mandolesi, N.; Mangilli, A.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; Mazzotta, P.; McGehee, P.; Mei, S.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nastasi, A.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Olamaie, M.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrott, Y. C.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reach, W. T.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rozo, E.; Rubiño-Martín, J. A.; Rumsey, C.; Rusholme, B.; Rykoff, E. S.; Sandri, M.; Santos, D.; Saunders, R. D. E.; Savelainen, M.; Savini, G.; Schammel, M. P.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Shimwell, T. W.; Spencer, L. D.; Stanford, S. A.; Stern, D.; Stolyarov, V.; Stompor, R.; Streblyanska, A.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tramonte, D.; Tristram, M.; Tucci, M.; Tuovinen, J.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; White, S. D. M.; Wright, E. L.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present the all-sky Planck catalogue of Sunyaev-Zeldovich (SZ) sources detected from the 29 month full-mission data. The catalogue (PSZ2) is the largest SZ-selected sample of galaxy clusters yet produced and the deepest systematic all-sky surveyof galaxy clusters. It contains 1653 detections, of which 1203 are confirmed clusters with identified counterparts in external data sets, and is the first SZ-selected cluster survey containing >103 confirmed clusters. We present a detailed analysis of the survey selection function in terms of its completeness and statistical reliability, placing a lower limit of 83% on the purity. Using simulations, we find that the estimates of the SZ strength parameter Y5R500are robust to pressure-profile variation and beam systematics, but accurate conversion to Y500 requires the use of prior information on the cluster extent. We describe the multi-wavelength search for counterparts in ancillary data, which makes use of radio, microwave, infra-red, optical, and X-ray data sets, and which places emphasis on the robustness of the counterpart match. We discuss the physical properties of the new sample and identify a population of low-redshift X-ray under-luminous clusters revealed by SZ selection. These objects appear in optical and SZ surveys with consistent properties for their mass, but are almost absent from ROSAT X-ray selected samples.

Planck 2015 results: XXVII. The second Planck catalogue of Sunyaev-Zeldovich sources

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-09-20

Here, we present the all-sky Planck catalogue of Sunyaev-Zeldovich (SZ) sources detected from the 29 month full-mission data. The catalogue (PSZ2) is the largest SZ-selected sample of galaxy clusters yet produced and the deepest systematic all-sky surveyof galaxy clusters. It contains 1653 detections, of which 1203 are confirmed clusters with identified counterparts in external data sets, and is the first SZ-selected cluster survey containing >103 confirmed clusters. We present a detailed analysis of the survey selection function in terms of its completeness and statistical reliability, placing a lower limit of 83% on the purity. Using simulations, we find that themore » estimates of the SZ strength parameter Y5R500are robust to pressure-profile variation and beam systematics, but accurate conversion to Y500 requires the use of prior information on the cluster extent. We describe the multi-wavelength search for counterparts in ancillary data, which makes use of radio, microwave, infra-red, optical, and X-ray data sets, and which places emphasis on the robustness of the counterpart match. We discuss the physical properties of the new sample and identify a population of low-redshift X-ray under-luminous clusters revealed by SZ selection. These objects appear in optical and SZ surveys with consistent properties for their mass, but are almost absent from ROSAT X-ray selected samples.« less

An Australian Version of the Neighborhood Environment Walkability Scale: Validity Evidence

ERIC Educational Resources Information Center

Cerin, Ester; Leslie, Eva; Owen, Neville; Bauman, Adrian

2008-01-01

This study examined validity evidence for the Australian version of the Neighborhood Environment Walkability Scale (NEWS-AU). A stratified two-stage cluster sampling design was used to recruit 2,650 adults from Adelaide (Australia). The sample was drawn from residential addresses within eight high-walkable and eight low-walkable suburbs matched…

Beyond Low-Rank Representations: Orthogonal clustering basis reconstruction with optimized graph structure for multi-view spectral clustering.

PubMed

Wang, Yang; Wu, Lin

2018-07-01

Low-Rank Representation (LRR) is arguably one of the most powerful paradigms for Multi-view spectral clustering, which elegantly encodes the multi-view local graph/manifold structures into an intrinsic low-rank self-expressive data similarity embedded in high-dimensional space, to yield a better graph partition than their single-view counterparts. In this paper we revisit it with a fundamentally different perspective by discovering LRR as essentially a latent clustered orthogonal projection based representation winged with an optimized local graph structure for spectral clustering; each column of the representation is fundamentally a cluster basis orthogonal to others to indicate its members, which intuitively projects the view-specific feature representation to be the one spanned by all orthogonal basis to characterize the cluster structures. Upon this finding, we propose our technique with the following: (1) We decompose LRR into latent clustered orthogonal representation via low-rank matrix factorization, to encode the more flexible cluster structures than LRR over primal data objects; (2) We convert the problem of LRR into that of simultaneously learning orthogonal clustered representation and optimized local graph structure for each view; (3) The learned orthogonal clustered representations and local graph structures enjoy the same magnitude for multi-view, so that the ideal multi-view consensus can be readily achieved. The experiments over multi-view datasets validate its superiority, especially over recent state-of-the-art LRR models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mechanism for Collective Cell Alignment in Myxococcus xanthus Bacteria

PubMed Central

Balagam, Rajesh; Igoshin, Oleg A.

2015-01-01

Myxococcus xanthus cells self-organize into aligned groups, clusters, at various stages of their lifecycle. Formation of these clusters is crucial for the complex dynamic multi-cellular behavior of these bacteria. However, the mechanism underlying the cell alignment and clustering is not fully understood. Motivated by studies of clustering in self-propelled rods, we hypothesized that M. xanthus cells can align and form clusters through pure mechanical interactions among cells and between cells and substrate. We test this hypothesis using an agent-based simulation framework in which each agent is based on the biophysical model of an individual M. xanthus cell. We show that model agents, under realistic cell flexibility values, can align and form cell clusters but only when periodic reversals of cell directions are suppressed. However, by extending our model to introduce the observed ability of cells to deposit and follow slime trails, we show that effective trail-following leads to clusters in reversing cells. Furthermore, we conclude that mechanical cell alignment combined with slime-trail-following is sufficient to explain the distinct clustering behaviors observed for wild-type and non-reversing M. xanthus mutants in recent experiments. Our results are robust to variation in model parameters, match the experimentally observed trends and can be applied to understand surface motility patterns of other bacterial species. PMID:26308508

Zodiacal Exoplanets in Time: Searching for Young Stars in K2

NASA Astrophysics Data System (ADS)

Morris, Nathan Ryan; Mann, Andrew; Rizzuto, Aaron

2018-01-01

Observations of planetary systems around young stars provide insight into the early stages of planetary system formation. Nearby young open clusters such as the Hyades, Pleiades, and Praesepe provide important benchmarks for the properties of stellar systems in general. These clusters are all known to be less than 1 Gyr old, making them ideal targets for a survey of young planetary systems. Few transiting planets have been detected around clusters stars, however, so this alone is too small of a sample. K2, the revived Kepler mission, has provided a vast number of light curves for young stars in clusters and elsewhere in the K2 field. This provides us with the opportunity to extend the sample of young systems to field stars while calibrating with cluster stars. We compute rotational periods from starspot patterns for ~36,000 K2 targets and use gyrochronological relationships derived from cluster stars to determine their ages. From there, we have begun searching for planets around young stars outside the clusters with the ultimate goal of shedding light on how planets and planetary systems evolve in their early, most formative years.

Accelerating three-dimensional FDTD calculations on GPU clusters for electromagnetic field simulation.

PubMed

Nagaoka, Tomoaki; Watanabe, Soichi

2012-01-01

Electromagnetic simulation with anatomically realistic computational human model using the finite-difference time domain (FDTD) method has recently been performed in a number of fields in biomedical engineering. To improve the method's calculation speed and realize large-scale computing with the computational human model, we adapt three-dimensional FDTD code to a multi-GPU cluster environment with Compute Unified Device Architecture and Message Passing Interface. Our multi-GPU cluster system consists of three nodes. The seven GPU boards (NVIDIA Tesla C2070) are mounted on each node. We examined the performance of the FDTD calculation on multi-GPU cluster environment. We confirmed that the FDTD calculation on the multi-GPU clusters is faster than that on a multi-GPU (a single workstation), and we also found that the GPU cluster system calculate faster than a vector supercomputer. In addition, our GPU cluster system allowed us to perform the large-scale FDTD calculation because were able to use GPU memory of over 100 GB.

Toward a modular multi-material nanoparticle synthesis and assembly strategy via bionanocombinatorics: bifunctional peptides for linking Au and Ag nanomaterials

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

Briggs, Beverly D.; Palafox-Hernandez, J. Pablo; Li, Yue

Materials-binding peptides represent a unique avenue towards controlling the shape and size of nanoparticles (NPs) grown under aqueous conditions. Here, employing a bionanocombinatorics approach, two such materials-binding peptides were linked at either end of a photoswitchable spacer, forming a multi-domain materials-binding molecule to control the in situ synthesis and organization of Ag and Au NPs under ambient conditions. These multi-domain molecules retained the peptides’ ability to nucleate, grow, and stabilize Ag and Au NPs in aqueous media. Disordered co-assemblies of the two nanomaterials were observed by TEM imaging of dried samples after sequential growth of the two metals, and showedmore » a clustering behavior that was not observed without both metals and the linker molecules. While TEM evidence indicated the formation of AuNP/AgNP assemblies upon drying, SAXS analysis indicated that no extended assemblies existed in solution, suggesting that sample drying plays an important role in facilitating NP clustering. Molecular simulations and experimental data revealed tunable materials-binding based upon the isomerization state of the photoswitchable unit and metal employed. This work is a first step in generating externally actuated biomolecules with specific material-binding properties that could be used as the building blocks to achieve multi-material switchable NP assemblies.« less

MIKiS: The Multi-instrument Kinematic Survey of Galactic Globular Clusters. I. Velocity Dispersion Profiles and Rotation Signals of 11 Globular Clusters

NASA Astrophysics Data System (ADS)

Ferraro, F. R.; Mucciarelli, A.; Lanzoni, B.; Pallanca, C.; Lapenna, E.; Origlia, L.; Dalessandro, E.; Valenti, E.; Beccari, G.; Bellazzini, M.; Vesperini, E.; Varri, A.; Sollima, A.

2018-06-01

We present the first results of the Multi-Instrument Kinematic Survey of Galactic Globular Clusters (GGCs), a project aimed at exploring the internal kinematics of a representative sample of GGCs from the radial velocity of individual stars, covering the entire radial extension of each system. This is achieved by exploiting the formidable combination of multi-object and integral field unit spectroscopic facilities of the ESO Very Large Telescope. As a first step, here we discuss the results obtained for 11 clusters from high and medium resolution spectra acquired through a combination of FLAMES and KMOS observations. We provide the first kinematical characterization of NGC 1261 and NGC 6496. In all the surveyed systems, the velocity dispersion profile declines at increasing radii, in agreement with the expectation from the King model that best fits the density/luminosity profile. In the majority of the surveyed systems, we find evidence of rotation within a few half-mass radii from the center. These results are in general overall agreement with the predictions of recent theoretical studies, suggesting that the detected signals could be the relic of significant internal rotation set at the epoch of the cluster’s formation. Based on FLAMES and KMOS observations performed at the European Southern Observatory as part of the Large Programme 193.D-0232 (PI: Ferraro).

[Principal component analysis and cluster analysis of inorganic elements in sea cucumber Apostichopus japonicus].

PubMed

Liu, Xiao-Fang; Xue, Chang-Hu; Wang, Yu-Ming; Li, Zhao-Jie; Xue, Yong; Xu, Jie

2011-11-01

The present study is to investigate the feasibility of multi-elements analysis in determination of the geographical origin of sea cucumber Apostichopus japonicus, and to make choice of the effective tracers in sea cucumber Apostichopus japonicus geographical origin assessment. The content of the elements such as Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Hg and Pb in sea cucumber Apostichopus japonicus samples from seven places of geographical origin were determined by means of ICP-MS. The results were used for the development of elements database. Cluster analysis(CA) and principal component analysis (PCA) were applied to differentiate the sea cucumber Apostichopus japonicus geographical origin. Three principal components which accounted for over 89% of the total variance were extracted from the standardized data. The results of Q-type cluster analysis showed that the 26 samples could be clustered reasonably into five groups, the classification results were significantly associated with the marine distribution of the sea cucumber Apostichopus japonicus samples. The CA and PCA were the effective methods for elements analysis of sea cucumber Apostichopus japonicus samples. The content of the mineral elements in sea cucumber Apostichopus japonicus samples was good chemical descriptors for differentiating their geographical origins.

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

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

Cluster galaxy dynamics and the effects of large-scale environment

NASA Astrophysics Data System (ADS)

White, Martin; Cohn, J. D.; Smit, Renske

2010-11-01

Advances in observational capabilities have ushered in a new era of multi-wavelength, multi-physics probes of galaxy clusters and ambitious surveys are compiling large samples of cluster candidates selected in different ways. We use a high-resolution N-body simulation to study how the influence of large-scale structure in and around clusters causes correlated signals in different physical probes and discuss some implications this has for multi-physics probes of clusters (e.g. richness, lensing, Compton distortion and velocity dispersion). We pay particular attention to velocity dispersions, matching galaxies to subhaloes which are explicitly tracked in the simulation. We find that not only do haloes persist as subhaloes when they fall into a larger host, but groups of subhaloes retain their identity for long periods within larger host haloes. The highly anisotropic nature of infall into massive clusters, and their triaxiality, translates into an anisotropic velocity ellipsoid: line-of-sight galaxy velocity dispersions for any individual halo show large variance depending on viewing angle. The orientation of the velocity ellipsoid is correlated with the large-scale structure, and thus velocity outliers correlate with outliers caused by projection in other probes. We quantify this orientation uncertainty and give illustrative examples. Such a large variance suggests that velocity dispersion estimators will work better in an ensemble sense than for any individual cluster, which may inform strategies for obtaining redshifts of cluster members. We similarly find that the ability of substructure indicators to find kinematic substructures is highly viewing angle dependent. While groups of subhaloes which merge with a larger host halo can retain their identity for many Gyr, they are only sporadically picked up by substructure indicators. We discuss the effects of correlated scatter on scaling relations estimated through stacking, both analytically and in the simulations, showing that the strong correlation of measures with mass and the large scatter in mass at fixed observable mitigate line-of-sight projections.

Joint fMRI analysis and subject clustering using sparse dictionary learning

NASA Astrophysics Data System (ADS)

Kim, Seung-Jun; Dontaraju, Krishna K.

2017-08-01

Multi-subject fMRI data analysis methods based on sparse dictionary learning are proposed. In addition to identifying the component spatial maps by exploiting the sparsity of the maps, clusters of the subjects are learned by postulating that the fMRI volumes admit a subspace clustering structure. Furthermore, in order to tune the associated hyper-parameters systematically, a cross-validation strategy is developed based on entry-wise sampling of the fMRI dataset. Efficient algorithms for solving the proposed constrained dictionary learning formulations are developed. Numerical tests performed on synthetic fMRI data show promising results and provides insights into the proposed technique.

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.

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

NASA Astrophysics Data System (ADS)

Li, Hui; Yu, Jun-Ling; Yu, Le-An; Sun, Jie

2014-05-01

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting.

SPT-GMOS: A GEMINI/GMOS-SOUTH SPECTROSCOPIC SURVEY OF GALAXY CLUSTERS IN THE SPT-SZ SURVEY

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

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.

We present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg{sup 2} of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goal ofmore » these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W , of [O ii] λλ 3727, 3729 and H- δ , and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m {sup ⋆}). Finally, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ∼20% of the full SPT-SZ sample.« less

SPT-GMOS: A Gemini/GMOS-South Spectroscopic survey of galaxy clusters in the SPT-SZ survey

DOE PAGES

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.; ...

2016-11-01

Here, we present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg 2 of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goalmore » of these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W, of [O II] λλ3727, 3729 and H-δ, and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m*). Lastly, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ~20% of the full SPT-SZ sample.« less

SPT-GMOS: A Gemini/GMOS-South Spectroscopic survey of galaxy clusters in the SPT-SZ survey

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

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.

Here, we present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg 2 of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goalmore » of these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W, of [O II] λλ3727, 3729 and H-δ, and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m*). Lastly, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ~20% of the full SPT-SZ sample.« less

SPT-GMOS: A Gemini/GMOS-South Spectroscopic Survey of Galaxy Clusters in the SPT-SZ Survey

NASA Astrophysics Data System (ADS)

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.; Allen, S. W.; Applegate, D. E.; Ashby, M. L. N.; Bautz, M.; Benson, B. A.; Bleem, L. E.; Bocquet, S.; Brodwin, M.; Capasso, R.; Carlstrom, J. E.; Chang, C. L.; Chiu, I.; Cho, H.-M.; Clocchiatti, A.; Crawford, T. M.; Crites, A. T.; de Haan, T.; Desai, S.; Dietrich, J. P.; Dobbs, M. A.; Doucouliagos, A. N.; Foley, R. J.; Forman, W. R.; Garmire, G. P.; George, E. M.; Gladders, M. D.; Gonzalez, A. H.; Gupta, N.; Halverson, N. W.; Hlavacek-Larrondo, J.; Hoekstra, H.; Holder, G. P.; Holzapfel, W. L.; Hou, Z.; Hrubes, J. D.; Huang, N.; Jones, C.; Keisler, R.; Knox, L.; Lee, A. T.; Leitch, E. M.; von der Linden, A.; Luong-Van, D.; Mantz, A.; Marrone, D. P.; McDonald, M.; McMahon, J. J.; Meyer, S. S.; Mocanu, L. M.; Mohr, J. J.; Murray, S. S.; Padin, S.; Pryke, C.; Rapetti, D.; Reichardt, C. L.; Rest, A.; Ruhl, J. E.; Saliwanchik, B. R.; Saro, A.; Sayre, J. T.; Schaffer, K. K.; Schrabback, T.; Shirokoff, E.; Song, J.; Spieler, H. G.; Stalder, B.; Stanford, S. A.; Staniszewski, Z.; Stark, A. A.; Story, K. T.; Vanderlinde, K.; Vieira, J. D.; Vikhlinin, A.; Williamson, R.; Zenteno, A.

2016-11-01

We present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg2 of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goal of these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W, of [O II] λλ3727, 3729 and H-δ, and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m⋆). Finally, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ∼20% of the full SPT-SZ sample.

Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

PubMed Central

Dunne, Philip D.; Alderdice, Matthew; O'Reilly, Paul G.; Roddy, Aideen C.; McCorry, Amy M. B.; Richman, Susan; Maughan, Tim; McDade, Simon S.; Johnston, Patrick G.; Longley, Daniel B.; Kay, Elaine; McArt, Darragh G.; Lawler, Mark

2017-01-01

Stromal-derived intratumoural heterogeneity (ITH) has been shown to undermine molecular stratification of patients into appropriate prognostic/predictive subgroups. Here, using several clinically relevant colorectal cancer (CRC) gene expression signatures, we assessed the susceptibility of these signatures to the confounding effects of ITH using gene expression microarray data obtained from multiple tumour regions of a cohort of 24 patients, including central tumour, the tumour invasive front and lymph node metastasis. Sample clustering alongside correlative assessment revealed variation in the ability of each signature to cluster samples according to patient-of-origin rather than region-of-origin within the multi-region dataset. Signatures focused on cancer-cell intrinsic gene expression were found to produce more clinically useful, patient-centred classifiers, as exemplified by the CRC intrinsic signature (CRIS), which robustly clustered samples by patient-of-origin rather than region-of-origin. These findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of stromal-derived ITH. PMID:28561046

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

PubMed Central

2010-01-01

Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters. PMID:21034451

Clustered lot quality assurance sampling: a pragmatic tool for timely assessment of vaccination coverage.

PubMed

Greenland, K; Rondy, M; Chevez, A; Sadozai, N; Gasasira, A; Abanida, E A; Pate, M A; Ronveaux, O; Okayasu, H; Pedalino, B; Pezzoli, L

2011-07-01

To evaluate oral poliovirus vaccine (OPV) coverage of the November 2009 round in five Northern Nigeria states with ongoing wild poliovirus transmission using clustered lot quality assurance sampling (CLQAS). We selected four local government areas in each pre-selected state and sampled six clusters of 10 children in each Local Government Area, defined as the lot area. We used three decision thresholds to classify OPV coverage: 75-90%, 55-70% and 35-50%. A full lot was completed, but we also assessed in retrospect the potential time-saving benefits of stopping sampling when a lot had been classified. We accepted two local government areas (LGAs) with vaccination coverage above 75%. Of the remaining 18 rejected LGAs, 11 also failed to reach 70% coverage, of which four also failed to reach 50%. The average time taken to complete a lot was 10 h. By stopping sampling when a decision was reached, we could have classified lots in 5.3, 7.7 and 7.3 h on average at the 90%, 70% and 50% coverage targets, respectively. Clustered lot quality assurance sampling was feasible and useful to estimate OPV coverage in Northern Nigeria. The multi-threshold approach provided useful information on the variation of IPD vaccination coverage. CLQAS is a very timely tool, allowing corrective actions to be directly taken in insufficiently covered areas. © 2011 Blackwell Publishing Ltd.

CLUMP-3D: Testing ΛCDM with Galaxy Cluster Shapes

NASA Astrophysics Data System (ADS)

Sereno, Mauro; Umetsu, Keiichi; Ettori, Stefano; Sayers, Jack; Chiu, I.-Non; Meneghetti, Massimo; Vega-Ferrero, Jesús; Zitrin, Adi

2018-06-01

The ΛCDM model of structure formation makes strong predictions on the concentration and shape of dark matter (DM) halos, which are determined by mass accretion processes. Comparison between predicted shapes and observations provides a geometric test of the ΛCDM model. Accurate and precise measurements needs a full three-dimensional (3D) analysis of the cluster mass distribution. We accomplish this with a multi-probe 3D analysis of the X-ray regular Cluster Lensing and Supernova survey with Hubble (CLASH) clusters combining strong and weak lensing, X-ray photometry and spectroscopy, and the Sunyaev–Zel’dovich effect (SZe). The cluster shapes and concentrations are consistent with ΛCDM predictions. The CLASH clusters are randomly oriented, as expected given the sample selection criteria. Shapes agree with numerical results for DM-only halos, which hints at baryonic physics being less effective in making halos rounder.

Relationship of Academic, Physical and Social Self-Concepts of Students with Their Academic Achievement

ERIC Educational Resources Information Center

Zahra, Asma-Tuz; Arif, Manzoor H.; Yousuf, Muhammad Imran

2010-01-01

This study investigated relationship between self-concept and academic achievement of bachelor degree students. Female students at bachelor were considered the target population. A sample of 1500 students was selected by using two stage cluster sampling technique. An amended form of Self-Descriptive Questionnaire developed by Marsh (1985) was used…

SOMFlow: Guided Exploratory Cluster Analysis with Self-Organizing Maps and Analytic Provenance.

PubMed

Sacha, Dominik; Kraus, Matthias; Bernard, Jurgen; Behrisch, Michael; Schreck, Tobias; Asano, Yuki; Keim, Daniel A

2018-01-01

Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arriving at useful clusterings often requires several rounds of user interactions to fine-tune the data preprocessing and algorithms. We present a multi-stage Visual Analytics (VA) approach for iterative cluster refinement together with an implementation (SOMFlow) that uses Self-Organizing Maps (SOM) to analyze time series data. It supports exploration by offering the analyst a visual platform to analyze intermediate results, adapt the underlying computations, iteratively partition the data, and to reflect previous analytical activities. The history of previous decisions is explicitly visualized within a flow graph, allowing to compare earlier cluster refinements and to explore relations. We further leverage quality and interestingness measures to guide the analyst in the discovery of useful patterns, relations, and data partitions. We conducted two pair analytics experiments together with a subject matter expert in speech intonation research to demonstrate that the approach is effective for interactive data analysis, supporting enhanced understanding of clustering results as well as the interactive process itself.

The Effect of Crop Insurance on Technical Efficiency of Wheat Farmers in Kermanshah Province: A Corrected Ordinary Least Square Approach

NASA Astrophysics Data System (ADS)

Agahi, Hossein; Zarafshani, Kiumars; Behjat, Amir-Mohsen

The purpose of this study was to describe the effect of crop insurance on agricultural production among dry wheat farmers in Kermanshah province. The population of this study consisted of dry wheat farmers. Data used in this study was collected using stratified multi-stage cluster sampling method and face to face interview with 251 farmers in three different climate regions: tropical, temperate and cold during 2003-2004 crop years. The procedures used for determining farmers' technical efficiency was Corrected Ordinary Least Square (COLS). Findings revealed that crop insurance has positive effect on temperate and tropical regions. However, the production difference between insured and uninsured farmers in cold region was non-significant. It is therefore concluded that technical efficiency of agricultural production in Kermanshah province is a function of crop insurance as well as other variables such as crop management practices, personal characteristics and fair distribution of agricultural inputs.

Patterns of marriage and reproductive practices: is there any relationship?

PubMed

Vedadhir, Abouali; Taghizadeh, Ziba; Behmanesh, Fereshteh; Ebadi, Abbas; Pourreza, Abulghasem; Abbasi-Shavazi, Mohammad Jalal

2017-04-01

Today, a transition from traditional to modern marriages can be observed in many countries. This shift in patterns of marriage has evidently affected childbearing and reproductive practices. This study aimed to examine the relationship between patterns of marriage and reproductive practices in Iran. Hence, 880 married women, aged 15-49 years old, living in the North of Iran were selected using a multi-stage cluster sampling strategy and their patterns of marriage and reproductive practices were cross sectionally studied. The results revealed that there were no significant differences in the reproductive practices by three main patterns of marriage in Babol, Iran. The study also indicated that there were no significant differences in reproductive practices in three patterns of marriage after controlling for socio-economic variables. It seems that apart from the patterns of marriage, other influencing factors are the determinants of fertility in women, and the policy-makers of Iran need to pay attention to these determinants before making any decisions in this area.

Estimation of late twentieth century land-cover change in California

USGS Publications Warehouse

Sleeter, Benjamin M.; Wilson, Tamara S.; Soulard, Christopher E.; Liu, Jinxun

2011-01-01

We present the first comprehensive multi-temporal analysis of land-cover change for California across its major ecological regions and primary land-cover types. Recently completed satellite-based estimates of land-cover and land-use change information for large portions of the United States allow for consistent measurement and comparison across heterogeneous landscapes. Landsat data were employed within a pure-panel stratified one-stage cluster sample to estimate and characterize land-cover change for 1973–2000. Results indicate anthropogenic and natural disturbances, such as forest cutting and fire, were the dominant changes, followed by large fluctuations between agriculture and rangelands. Contrary to common perception, agriculture remained relatively stable over the 27-year period with an estimated loss of 1.0% of agricultural land. The largest net declines occurred in the grasslands/shrubs class at 5,131 km2 and forest class at 4,722 km2. Developed lands increased by 37.6%, composing an estimated 4.2% of the state’s land cover by 2000.

Multiscale synchrony behaviors of paired financial time series by 3D multi-continuum percolation

NASA Astrophysics Data System (ADS)

Wang, M.; Wang, J.; Wang, B. T.

2018-02-01

Multiscale synchrony behaviors and nonlinear dynamics of paired financial time series are investigated, in an attempt to study the cross correlation relationships between two stock markets. A random stock price model is developed by a new system called three-dimensional (3D) multi-continuum percolation system, which is utilized to imitate the formation mechanism of price dynamics and explain the nonlinear behaviors found in financial time series. We assume that the price fluctuations are caused by the spread of investment information. The cluster of 3D multi-continuum percolation represents the cluster of investors who share the same investment attitude. In this paper, we focus on the paired return series, the paired volatility series, and the paired intrinsic mode functions which are decomposed by empirical mode decomposition. A new cross recurrence quantification analysis is put forward, combining with multiscale cross-sample entropy, to investigate the multiscale synchrony of these paired series from the proposed model. The corresponding research is also carried out for two China stock markets as comparison.

Application of the theory of reasoned action to promoting breakfast consumption

PubMed Central

Hosseini, Zahra; Gharlipour Gharghani, Zabihollah; Mansoori, Anahita; Aghamolaei, Teamur; Mohammadi Nasrabadi, Maryam

2015-01-01

Background: Breakfast is the most important daily meal, but neglected more than other meals by children and adolescents. The aim of this study was to evaluate the effectiveness of an educational intervention, based on the Theory of Reasoned Action (TRA) to increase breakfast consumption among school children in Bandar Abbas, Iran. Methods: In this quasi experimental study which was conducted in 2012, 88 students of four secondary schools in Bandar Abbas, south of Iran, were enrolled. Multi-stage cluster sampling was performed with random allocation of interventional and control groups. The study tool was a questionnaire which was filled by the students before and two months after the educational intervention. For data analysis, statistical tests including paired-samples t-test, independent samples t-test, Wilcoxon test, and Mann-Whitney test were used through SPSS v.18 software. Results: The result of the study showed that application of TRA significantly increased scores of behavior of breakfast consumption (p<0.01). After the intervention, a significant increase was revealed in all nutrition intakes, except for fat and sugar (p<0.01). Conclusion: The findings support application of the TRA in improving the intention and behavior of breakfast consumption. Applying this theory for designing interventions to increase breakfast eating is recommended. PMID:26913252

Identifying Factors Associated with Risk Assessment Competencies of Public Health Emergency Responders.

PubMed

Hao, Jiejing; Ren, Jiaojiao; Wu, Qunhong; Hao, Yanhua; Sun, Hong; Ning, Ning; Ding, Ding

2017-06-04

This study aimed to better understand the current situation of risk assessment and identify the factors associated with competence of emergency responders in public health risk assessment. The participants were selected by a multi-stage, stratified cluster sampling method in Heilongjiang Centers for Disease Control and Prevention (CDC). The questionnaires that measured their perceptions on risk assessment competences were administered through the face-to-face survey. A final sample of 1889 staff was obtained. Of this sample, 78.6% of respondents rated their own risk assessment competences as "relatively low", contrasting with 21.4% rated as "relatively high". Most of the respondents (62.7%) did not participate in any risk assessment work. Only 13.7% and 42.7% of respondents reported participating in risk assessment training and were familiar with risk assessment tools. There existed statistical significance between risk assessment-related characteristics of respondents and their self-rated competences scores. Financial support from the government and administrative attention were regarded as the important factors contributing to risk assessment competences of CDC responders. Higher attention should be given to risk assessment training and enhancing the availability of surveillance data. Continuous efforts should be made to remove the financial and technical obstacles to improve the competences of risk assessment for public health emergency responders.

Identifying Factors Associated with Risk Assessment Competencies of Public Health Emergency Responders

PubMed Central

Hao, Jiejing; Ren, Jiaojiao; Wu, Qunhong; Hao, Yanhua; Sun, Hong; Ning, Ning; Ding, Ding

2017-01-01

This study aimed to better understand the current situation of risk assessment and identify the factors associated with competence of emergency responders in public health risk assessment. The participants were selected by a multi-stage, stratified cluster sampling method in Heilongjiang Centers for Disease Control and Prevention (CDC). The questionnaires that measured their perceptions on risk assessment competences were administered through the face-to-face survey. A final sample of 1889 staff was obtained. Of this sample, 78.6% of respondents rated their own risk assessment competences as “relatively low”, contrasting with 21.4% rated as “relatively high”. Most of the respondents (62.7%) did not participate in any risk assessment work. Only 13.7% and 42.7% of respondents reported participating in risk assessment training and were familiar with risk assessment tools. There existed statistical significance between risk assessment-related characteristics of respondents and their self-rated competences scores. Financial support from the government and administrative attention were regarded as the important factors contributing to risk assessment competences of CDC responders. Higher attention should be given to risk assessment training and enhancing the availability of surveillance data. Continuous efforts should be made to remove the financial and technical obstacles to improve the competences of risk assessment for public health emergency responders. PMID:28587226

S-CNN: Subcategory-aware convolutional networks for object detection.

PubMed

Chen, Tao; Lu, Shijian; Fan, Jiayuan

2017-09-26

The marriage between the deep convolutional neural network (CNN) and region proposals has made breakthroughs for object detection in recent years. While the discriminative object features are learned via a deep CNN for classification, the large intra-class variation and deformation still limit the performance of the CNN based object detection. We propose a subcategory-aware CNN (S-CNN) to solve the object intra-class variation problem. In the proposed technique, the training samples are first grouped into multiple subcategories automatically through a novel instance sharing maximum margin clustering process. A multi-component Aggregated Channel Feature (ACF) detector is then trained to produce more latent training samples, where each ACF component corresponds to one clustered subcategory. The produced latent samples together with their subcategory labels are further fed into a CNN classifier to filter out false proposals for object detection. An iterative learning algorithm is designed for the joint optimization of image subcategorization, multi-component ACF detector, and subcategory-aware CNN classifier. Experiments on INRIA Person dataset, Pascal VOC 2007 dataset and MS COCO dataset show that the proposed technique clearly outperforms the state-of-the-art methods for generic object detection.

Earth Science Data Fusion with Event Building Approach

NASA Technical Reports Server (NTRS)

Lukashin, C.; Bartle, Ar.; Callaway, E.; Gyurjyan, V.; Mancilla, S.; Oyarzun, R.; Vakhnin, A.

2015-01-01

Objectives of the NASA Information And Data System (NAIADS) project are to develop a prototype of a conceptually new middleware framework to modernize and significantly improve efficiency of the Earth Science data fusion, big data processing and analytics. The key components of the NAIADS include: Service Oriented Architecture (SOA) multi-lingual framework, multi-sensor coincident data Predictor, fast into-memory data Staging, multi-sensor data-Event Builder, complete data-Event streaming (a work flow with minimized IO), on-line data processing control and analytics services. The NAIADS project is leveraging CLARA framework, developed in Jefferson Lab, and integrated with the ZeroMQ messaging library. The science services are prototyped and incorporated into the system. Merging the SCIAMACHY Level-1 observations and MODIS/Terra Level-2 (Clouds and Aerosols) data products, and ECMWF re- analysis will be used for NAIADS demonstration and performance tests in compute Cloud and Cluster environments.

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Chen, Yuan L.; Miller, Robert A.

2003-01-01

Advanced oxide thermal barrier coatings have been developed by incorporating multi-component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma-sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), electron energy-loss spectroscopy (EELS) and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia- yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging from 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Chen, Yuan L.; Miller, Robert A.

1990-01-01

Advanced oxide thermal barrier coatings have been developed by incorporating multi- component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma- sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia-yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging fiom 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

An Exemplar-Based Multi-View Domain Generalization Framework for Visual Recognition.

PubMed

Niu, Li; Li, Wen; Xu, Dong; Cai, Jianfei

2018-02-01

In this paper, we propose a new exemplar-based multi-view domain generalization (EMVDG) framework for visual recognition by learning robust classifier that are able to generalize well to arbitrary target domain based on the training samples with multiple types of features (i.e., multi-view features). In this framework, we aim to address two issues simultaneously. First, the distribution of training samples (i.e., the source domain) is often considerably different from that of testing samples (i.e., the target domain), so the performance of the classifiers learnt on the source domain may drop significantly on the target domain. Moreover, the testing data are often unseen during the training procedure. Second, when the training data are associated with multi-view features, the recognition performance can be further improved by exploiting the relation among multiple types of features. To address the first issue, considering that it has been shown that fusing multiple SVM classifiers can enhance the domain generalization ability, we build our EMVDG framework upon exemplar SVMs (ESVMs), in which a set of ESVM classifiers are learnt with each one trained based on one positive training sample and all the negative training samples. When the source domain contains multiple latent domains, the learnt ESVM classifiers are expected to be grouped into multiple clusters. To address the second issue, we propose two approaches under the EMVDG framework based on the consensus principle and the complementary principle, respectively. Specifically, we propose an EMVDG_CO method by adding a co-regularizer to enforce the cluster structures of ESVM classifiers on different views to be consistent based on the consensus principle. Inspired by multiple kernel learning, we also propose another EMVDG_MK method by fusing the ESVM classifiers from different views based on the complementary principle. In addition, we further extend our EMVDG framework to exemplar-based multi-view domain adaptation (EMVDA) framework when the unlabeled target domain data are available during the training procedure. The effectiveness of our EMVDG and EMVDA frameworks for visual recognition is clearly demonstrated by comprehensive experiments on three benchmark data sets.

Small Launch Vehicle Design Approaches: Clustered Cores Compared with Multi-Stage Inline Concepts

NASA Technical Reports Server (NTRS)

Waters, Eric D.; Beers, Benjamin; Esther, Elizabeth; Philips, Alan; Threet, Grady E., Jr.

2013-01-01

In an effort to better define small launch vehicle design options two approaches were investigated from the small launch vehicle trade space. The primary focus was to evaluate a clustered common core design against a purpose built inline vehicle. Both designs focused on liquid oxygen (LOX) and rocket propellant grade kerosene (RP-1) stages with the terminal stage later evaluated as a LOX/methane (CH4) stage. A series of performance optimization runs were done in order to minimize gross liftoff weight (GLOW) including alternative thrust levels, delivery altitude for payload, vehicle length to diameter ratio, alternative engine feed systems, re-evaluation of mass growth allowances, passive versus active guidance systems, and rail and tower launch methods. Additionally manufacturability, cost, and operations also play a large role in the benefits and detriments for each design. Presented here is the Advanced Concepts Office's Earth to Orbit Launch Team methodology and high level discussion of the performance trades and trends of both small launch vehicle solutions along with design philosophies that shaped both concepts. Without putting forth a decree stating one approach is better than the other; this discussion is meant to educate the community at large and let the reader determine which architecture is truly the most economical; since each path has such a unique set of limitations and potential payoffs.

Temporal variation of aftershocks by means of multifractal characterization of their inter-event time and cluster analysis

NASA Astrophysics Data System (ADS)

Figueroa-Soto, A.; Zuñiga, R.; Marquez-Ramirez, V.; Monterrubio-Velasco, M.

2017-12-01

. The inter-event time characteristics of seismic aftershock sequences can provide important information to discern stages in the aftershock generation process. In order to investigate whether separate dynamic stages can be identified, (1) aftershock series after selected earthquake mainshocks, which took place at similar tectonic regimes were analyzed. To this end we selected two well-defined aftershock sequences from New Zealand and one aftershock sequence for Mexico, we (2) analyzed the fractal behavior of the logarithm of inter-event times (also called waiting times) of aftershocks by means of Holdeŕs exponent, and (3) their magnitude and spatial location based on a methodology proposed by Zaliapin and Ben Zion [2011] which accounts for the clustering properties of the sequence. In general, more than two coherent process stages can be identified following the main rupture, evidencing a type of "cascade" process which precludes implying a single generalized power law even though the temporal rate and average fractal character appear to be unique (as in a single Omorís p value). We found that aftershock processes indeed show multi-fractal characteristics, which may be related to different stages in the process of diffusion, as seen in the temporary-spatial distribution of aftershocks. Our method provides a way of defining the onset of the return to seismic background activity and the end of the main aftershock sequence.

Probing the non-thermal emission in Abell 2146 and the Perseus cluster with the JVLA

NASA Astrophysics Data System (ADS)

Gendron-Marsolais, Marie-Lou; Hlavacek-Larrondo, Julie; van Weeren, Reinout; Clarke, Tracy; Intema, Huib; Russell, Helen; Edge, Alastair; Fabian, Andy; Olamaie, Malak; Rumsey, Clare; King, Lindsay; McNamara, Brian; Fecteau-Beaucage, David; Hogan, Michael; Mezcua, Mar; Taylor, Gregory; Blundell, Katherine; Sanders, Jeremy

2018-01-01

Jets created from accretion onto supermassive black holes release relativistic particles on large distances. These strongly affect the intracluster medium when located in the center of a brightest cluster galaxy. The hierarchical merging of subclusters and groups, from which cluster originate, also generates perturbations into the intracluster medium through shocks and turbulence, constituting a potential source of reacceleration for these particles. I will present deep multi-configuration low radio frequency observations from the Karl G. Jansky Very Large Array of two unique clusters, probing the non-thermal emission from the old particle population of the AGN outflows.Recently awarded of 550 hours of Chandra observations, Abell 2146 is one of the rare clusters undergoing a spectacular merger in the plane of the sky. Our recent deep multi-configuration JVLA 1.4 GHz observations have revealed the presence of a structure extending to 850 kpc in size, consisting of one component associated with the upstream shock and classified as a radio relic, and one associated with the subcluster core, consistent with a radio halo bounded by the bow shock. Theses structures have some of the lowest radio powers detected thus far in any cluster. The flux measurements of the halo, its morphology and measurements of the dynamical state of the cluster suggest that the halo was recently created (~ 0.3 Gyr after core passage). This makes A2146 extremely interesting to study, allowing us to probe the complete evolutionary stages of halos.I will also present results on 230-470 MHz JVLA observations of the Perseus cluster. Our observations of this nearby relaxed cool core cluster have revealed a multitude of new structures associated with the mini-halo, extending to hundreds of kpc in size. Its irregular morphology seems to be have been influenced both by the AGN activity and by the sloshing motion of the cluster’ gas. In addition, it has a filamentary structure similar to that seen in radio relics found in merging clusters.These results both illustrate the high-quality images that can be obtained with the new JVLA at low radio-frequencies.

Long-lasting insecticide-treated house screens and targeted treatment of productive breeding-sites for dengue vector control in Acapulco, Mexico.

PubMed

Che-Mendoza, Azael; Guillermo-May, Guillermo; Herrera-Bojórquez, Josué; Barrera-Pérez, Mario; Dzul-Manzanilla, Felipe; Gutierrez-Castro, Cipriano; Arredondo-Jiménez, Juan I; Sánchez-Tejeda, Gustavo; Vazquez-Prokopec, Gonzalo; Ranson, Hilary; Lenhart, Audrey; Sommerfeld, Johannes; McCall, Philip J; Kroeger, Axel; Manrique-Saide, Pablo

2015-02-01

Long-lasting insecticidal net screens (LLIS) fitted to domestic windows and doors in combination with targeted treatment (TT) of the most productive Aedes aegypti breeding sites were evaluated for their impact on dengue vector indices in a cluster-randomised trial in Mexico between 2011 and 2013. Sequentially over 2 years, LLIS and TT were deployed in 10 treatment clusters (100 houses/cluster) and followed up over 24 months. Cross-sectional surveys quantified infestations of adult mosquitoes, immature stages at baseline (pre-intervention) and in four post-intervention samples at 6-monthly intervals. Identical surveys were carried out in 10 control clusters that received no treatment. LLIS clusters had significantly lower infestations compared to control clusters at 5 and 12 months after installation, as measured by adult (male and female) and pupal-based vector indices. After addition of TT to the intervention houses in intervention clusters, indices remained significantly lower in the treated clusters until 18 (immature and adult stage indices) and 24 months (adult indices only) post-intervention. These safe, simple affordable vector control tools were well-accepted by study participants and are potentially suitable in many regions at risk from dengue worldwide. © The author 2015. The World Health Organization has granted Oxford University Press permission for the reproduction of this article.

Scalable multi-sample single-cell data analysis by Partition-Assisted Clustering and Multiple Alignments of Networks

PubMed Central

Samusik, Nikolay; Wang, Xiaowei; Guan, Leying; Nolan, Garry P.

2017-01-01

Mass cytometry (CyTOF) has greatly expanded the capability of cytometry. It is now easy to generate multiple CyTOF samples in a single study, with each sample containing single-cell measurement on 50 markers for more than hundreds of thousands of cells. Current methods do not adequately address the issues concerning combining multiple samples for subpopulation discovery, and these issues can be quickly and dramatically amplified with increasing number of samples. To overcome this limitation, we developed Partition-Assisted Clustering and Multiple Alignments of Networks (PAC-MAN) for the fast automatic identification of cell populations in CyTOF data closely matching that of expert manual-discovery, and for alignments between subpopulations across samples to define dataset-level cellular states. PAC-MAN is computationally efficient, allowing the management of very large CyTOF datasets, which are increasingly common in clinical studies and cancer studies that monitor various tissue samples for each subject. PMID:29281633

From Solidification Processing to Microstructure to Mechanical Properties: A Multi-scale X-ray Study of an Al-Cu Alloy Sample

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

Tourret, D.; Mertens, J. C. E.; Lieberman, E.

We follow an Al-12 at. pct Cu alloy sample from the liquid state to mechanical failure, using in situ X-ray radiography during directional solidification and tensile testing, as well as three-dimensional computed tomography of the microstructure before and after mechanical testing. The solidification processing stage is simulated with a multi-scale dendritic needle network model, and the micromechanical behavior of the solidified microstructure is simulated using voxelized tomography data and an elasto-viscoplastic fast Fourier transform model. This study demonstrates the feasibility of direct in situ monitoring of a metal alloy microstructure from the liquid processing stage up to its mechanical failure,more » supported by quantitative simulations of microstructure formation and its mechanical behavior.« less

From Solidification Processing to Microstructure to Mechanical Properties: A Multi-scale X-ray Study of an Al-Cu Alloy Sample

DOE PAGES

Tourret, D.; Mertens, J. C. E.; Lieberman, E.; ...

2017-09-13

We follow an Al-12 at. pct Cu alloy sample from the liquid state to mechanical failure, using in situ X-ray radiography during directional solidification and tensile testing, as well as three-dimensional computed tomography of the microstructure before and after mechanical testing. The solidification processing stage is simulated with a multi-scale dendritic needle network model, and the micromechanical behavior of the solidified microstructure is simulated using voxelized tomography data and an elasto-viscoplastic fast Fourier transform model. This study demonstrates the feasibility of direct in situ monitoring of a metal alloy microstructure from the liquid processing stage up to its mechanical failure,more » supported by quantitative simulations of microstructure formation and its mechanical behavior.« less

From Solidification Processing to Microstructure to Mechanical Properties: A Multi-scale X-ray Study of an Al-Cu Alloy Sample

NASA Astrophysics Data System (ADS)

Tourret, D.; Mertens, J. C. E.; Lieberman, E.; Imhoff, S. D.; Gibbs, J. W.; Henderson, K.; Fezzaa, K.; Deriy, A. L.; Sun, T.; Lebensohn, R. A.; Patterson, B. M.; Clarke, A. J.

2017-11-01

We follow an Al-12 at. pct Cu alloy sample from the liquid state to mechanical failure, using in situ X-ray radiography during directional solidification and tensile testing, as well as three-dimensional computed tomography of the microstructure before and after mechanical testing. The solidification processing stage is simulated with a multi-scale dendritic needle network model, and the micromechanical behavior of the solidified microstructure is simulated using voxelized tomography data and an elasto-viscoplastic fast Fourier transform model. This study demonstrates the feasibility of direct in situ monitoring of a metal alloy microstructure from the liquid processing stage up to its mechanical failure, supported by quantitative simulations of microstructure formation and its mechanical behavior.

WINGS-SPE Spectroscopy in the WIde-field Nearby Galaxy-cluster Survey

NASA Astrophysics Data System (ADS)

Cava, A.; Bettoni, D.; Poggianti, B. M.; Couch, W. J.; Moles, M.; Varela, J.; Biviano, A.; D'Onofrio, M.; Dressler, A.; Fasano, G.; Fritz, J.; Kjærgaard, P.; Ramella, M.; Valentinuzzi, T.

2009-03-01

Aims: We present the results from a comprehensive spectroscopic survey of the WINGS (WIde-field Nearby Galaxy-cluster Survey) clusters, a program called WINGS-SPE. The WINGS-SPE sample consists of 48 clusters, 22 of which are in the southern sky and 26 in the north. The main goals of this spectroscopic survey are: (1) to study the dynamics and kinematics of the WINGS clusters and their constituent galaxies, (2) to explore the link between the spectral properties and the morphological evolution in different density environments and across a wide range of cluster X-ray luminosities and optical properties. Methods: Using multi-object fiber-fed spectrographs, we observed our sample of WINGS cluster galaxies at an intermediate resolution of 6-9 Å and, using a cross-correlation technique, we measured redshifts with a mean accuracy of ~45 km s-1. Results: We present redshift measurements for 6137 galaxies and their first analyses. Details of the spectroscopic observations are reported. The WINGS-SPE has ~30% overlap with previously published data sets, allowing us both to perform a complete comparison with the literature and to extend the catalogs. Conclusions: Using our redshifts, we calculate the velocity dispersion for all the clusters in the WINGS-SPE sample. We almost triple the number of member galaxies known in each cluster with respect to previous works. We also investigate the X-ray luminosity vs. velocity dispersion relation for our WINGS-SPE clusters, and find it to be consistent with the form Lx ∝ σ_v^4. Table 4, containing the complete redshift catalog, is only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/495/707

Factors Affecting Jordanian School Adolescents' Experience of Being Bullied.

PubMed

Shaheen, Abeer M; Hammad, Sawsan; Haourani, Eman M; Nassar, Omayyah S

The purpose of this study was to identify the Jordanian school adolescents' experience of being bullied, and to examine its association with selected socio-demographic variables. This cross sectional descriptive study used multi-stages cluster sampling technique to recruit a sample of in-school adolescents in Jordan (N=436). The Personal Experiences Checklist was used to measure the experience of bullying. Descriptive statistics and parametric tests were used in the analysis. Relational-verbal bullying was the most common form of bullying while cyber bullying was the least common type. Male adolescents experienced bullying more than females. In addition, adolescents belonging to low-income families experienced bullying more than those from moderate-income families. Finally, being bullied was negatively correlated with academic performance of students. This study indicated that risk factors for bullying are multifaceted which necessitate the development of prevention and intervention strategies to combat bullying taking into consideration these factors. Schools should introduce environmental changes to discourage bullying and establish a policy with specific guidelines of what constitutes bullying behavior and expected disciplinary procedures. Staff training on information about the definition of bullying, current trends, and the effects of bullying is also recommended. Copyright © 2017 Elsevier Inc. All rights reserved.

A multi-populations multi-strategies differential evolution algorithm for structural optimization of metal nanoclusters

NASA Astrophysics Data System (ADS)

Fan, Tian-E.; Shao, Gui-Fang; Ji, Qing-Shuang; Zheng, Ji-Wen; Liu, Tun-dong; Wen, Yu-Hua

2016-11-01

Theoretically, the determination of the structure of a cluster is to search the global minimum on its potential energy surface. The global minimization problem is often nondeterministic-polynomial-time (NP) hard and the number of local minima grows exponentially with the cluster size. In this article, a multi-populations multi-strategies differential evolution algorithm has been proposed to search the globally stable structure of Fe and Cr nanoclusters. The algorithm combines a multi-populations differential evolution with an elite pool scheme to keep the diversity of the solutions and avoid prematurely trapping into local optima. Moreover, multi-strategies such as growing method in initialization and three differential strategies in mutation are introduced to improve the convergence speed and lower the computational cost. The accuracy and effectiveness of our algorithm have been verified by comparing the results of Fe clusters with Cambridge Cluster Database. Meanwhile, the performance of our algorithm has been analyzed by comparing the convergence rate and energy evaluations with the classical DE algorithm. The multi-populations, multi-strategies mutation and growing method in initialization in our algorithm have been considered respectively. Furthermore, the structural growth pattern of Cr clusters has been predicted by this algorithm. The results show that the lowest-energy structure of Cr clusters contains many icosahedra, and the number of the icosahedral rings rises with increasing size.

Ram-air sample collection device for a chemical warfare agent sensor

DOEpatents

Megerle, Clifford A.; Adkins, Douglas R.; Frye-Mason, Gregory C.

2002-01-01

In a surface acoustic wave sensor mounted within a body, the sensor having a surface acoustic wave array detector and a micro-fabricated sample preconcentrator exposed on a surface of the body, an apparatus for collecting air for the sensor, comprising a housing operatively arranged to mount atop the body, the housing including a multi-stage channel having an inlet and an outlet, the channel having a first stage having a first height and width proximate the inlet, a second stage having a second lower height and width proximate the micro-fabricated sample preconcentrator, a third stage having a still lower third height and width proximate the surface acoustic wave array detector, and a fourth stage having a fourth height and width proximate the outlet, where the fourth height and width are substantially the same as the first height and width.

From Sample to Multi-Omics Conclusions in under 48 Hours

PubMed Central

Navas-Molina, Jose A.; Hyde, Embriette R.; Vázquez-Baeza, Yoshiki; Humphrey, Greg; Gaffney, James; Minich, Jeremiah J.; Melnik, Alexey V.; Herschend, Jakob; DeReus, Jeff; Durant, Austin; Dutton, Rachel J.; Khosroheidari, Mahdieh; Green, Clifford; da Silva, Ricardo; Dorrestein, Pieter C.; Knight, Rob

2016-01-01

ABSTRACT Multi-omics methods have greatly advanced our understanding of the biological organism and its microbial associates. However, they are not routinely used in clinical or industrial applications, due to the length of time required to generate and analyze omics data. Here, we applied a novel integrated omics pipeline for the analysis of human and environmental samples in under 48 h. Human subjects that ferment their own foods provided swab samples from skin, feces, oral cavity, fermented foods, and household surfaces to assess the impact of home food fermentation on their microbial and chemical ecology. These samples were analyzed with 16S rRNA gene sequencing, inferred gene function profiles, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics through the Qiita, PICRUSt, and GNPS pipelines, respectively. The human sample microbiomes clustered with the corresponding sample types in the American Gut Project (http://www.americangut.org), and the fermented food samples produced a separate cluster. The microbial communities of the household surfaces were primarily sourced from the fermented foods, and their consumption was associated with increased gut microbial diversity. Untargeted metabolomics revealed that human skin and fermented food samples had separate chemical ecologies and that stool was more similar to fermented foods than to other sample types. Metabolites from the fermented foods, including plant products such as procyanidin and pheophytin, were present in the skin and stool samples of the individuals consuming the foods. Some food metabolites were modified during digestion, and others were detected in stool intact. This study represents a first-of-its-kind analysis of multi-omics data that achieved time intervals matching those of classic microbiological culturing. IMPORTANCE Polymicrobial infections are difficult to diagnose due to the challenge in comprehensively cultivating the microbes present. Omics methods, such as 16S rRNA sequencing, metagenomics, and metabolomics, can provide a more complete picture of a microbial community and its metabolite production, without the biases and selectivity of microbial culture. However, these advanced methods have not been applied to clinical or industrial microbiology or other areas where complex microbial dysbioses require immediate intervention. The reason for this is the length of time required to generate and analyze omics data. Here, we describe the development and application of a pipeline for multi-omics data analysis in time frames matching those of the culture-based approaches often used for these applications. This study applied multi-omics methods effectively in clinically relevant time frames and sets a precedent toward their implementation in clinical medicine and industrial microbiology. PMID:27822524

ATCA observations of the MACS-Planck Radio Halo Cluster Project. II. Radio observations of an intermediate redshift cluster sample

NASA Astrophysics Data System (ADS)

Martinez Aviles, G.; Johnston-Hollitt, M.; Ferrari, C.; Venturi, T.; Democles, J.; Dallacasa, D.; Cassano, R.; Brunetti, G.; Giacintucci, S.; Pratt, G. W.; Arnaud, M.; Aghanim, N.; Brown, S.; Douspis, M.; Hurier, J.; Intema, H. T.; Langer, M.; Macario, G.; Pointecouteau, E.

2018-04-01

Aim. A fraction of galaxy clusters host diffuse radio sources whose origins are investigated through multi-wavelength studies of cluster samples. We investigate the presence of diffuse radio emission in a sample of seven galaxy clusters in the largely unexplored intermediate redshift range (0.3 < z < 0.44). Methods: In search of diffuse emission, deep radio imaging of the clusters are presented from wide band (1.1-3.1 GHz), full resolution ( 5 arcsec) observations with the Australia Telescope Compact Array (ATCA). The visibilities were also imaged at lower resolution after point source modelling and subtraction and after a taper was applied to achieve better sensitivity to low surface brightness diffuse radio emission. In case of non-detection of diffuse sources, we set upper limits for the radio power of injected diffuse radio sources in the field of our observations. Furthermore, we discuss the dynamical state of the observed clusters based on an X-ray morphological analysis with XMM-Newton. Results: We detect a giant radio halo in PSZ2 G284.97-23.69 (z = 0.39) and a possible diffuse source in the nearly relaxed cluster PSZ2 G262.73-40.92 (z = 0.421). Our sample contains three highly disturbed massive clusters without clear traces of diffuse emission at the observed frequencies. We were able to inject modelled radio haloes with low values of total flux density to set upper detection limits; however, with our high-frequency observations we cannot exclude the presence of RH in these systems because of the sensitivity of our observations in combination with the high z of the observed clusters. The reduced images are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/611/A94

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

NASA Technical Reports Server (NTRS)

Naesset, Erik; Gobakken, Terje; Bollandsas, Ole Martin; Gregoire, Timothy G.; Nelson, Ross; Stahl, Goeran

2013-01-01

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Membership determination of open clusters based on a spectral clustering method

NASA Astrophysics Data System (ADS)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

The Observations of Redshift Evolution in Large Scale Environments (ORELSE) Survey

NASA Astrophysics Data System (ADS)

Squires, Gordon K.; Lubin, L. M.; Gal, R. R.

2007-05-01

We present the motivation, design, and latest results from the Observations of Redshift Evolution in Large Scale Environments (ORELSE) Survey, a systematic search for structure on scales greater than 10 Mpc around 20 known galaxy clusters at z > 0.6. When complete, the survey will cover nearly 5 square degrees, all targeted at high-density regions, making it complementary and comparable to field surveys such as DEEP2, GOODS, and COSMOS. For the survey, we are using the Large Format Camera on the Palomar 5-m and SuPRIME-Cam on the Subaru 8-m to obtain optical/near-infrared imaging of an approximately 30 arcmin region around previously studied high-redshift clusters. Colors are used to identify likely member galaxies which are targeted for follow-up spectroscopy with the DEep Imaging Multi-Object Spectrograph on the Keck 10-m. This technique has been used to identify successfully the Cl 1604 supercluster at z = 0.9, a large scale structure containing at least eight clusters (Gal & Lubin 2004; Gal, Lubin & Squires 2005). We present the most recent structures to be photometrically and spectroscopically confirmed through this program, discuss the properties of the member galaxies as a function of environment, and describe our planned multi-wavelength (radio, mid-IR, and X-ray) observations of these systems. The goal of this survey is to identify and examine a statistical sample of large scale structures during an active period in the assembly history of the most massive clusters. With such a sample, we can begin to constrain large scale cluster dynamics and determine the effect of the larger environment on galaxy evolution.

A cluster analytic study of the Wechsler Intelligence Test for Children-IV in children referred for psychoeducational assessment due to persistent academic difficulties.

PubMed

Hale, Corinne R; Casey, Joseph E; Ricciardi, Philip W R

2014-02-01

Wechsler Intelligence Test for Children-IV core subtest scores of 472 children were cluster analyzed to determine if reliable and valid subgroups would emerge. Three subgroups were identified. Clusters were reliable across different stages of the analysis as well as across algorithms and samples. With respect to external validity, the Globally Low cluster differed from the other two clusters on Wechsler Individual Achievement Test-II Word Reading, Numerical Operations, and Spelling subtests, whereas the latter two clusters did not differ from one another. The clusters derived have been identified in studies using previous WISC editions. Clusters characterized by poor performance on subtests historically associated with the VIQ (i.e., VCI + WMI) and PIQ (i.e., POI + PSI) did not emerge, nor did a cluster characterized by low scores on PRI subtests. Picture Concepts represented the highest subtest score in every cluster, failing to vary in a predictable manner with the other PRI subtests.

Axial tomography in 3D live cell microscopy

NASA Astrophysics Data System (ADS)

Richter, Verena; Bruns, Sarah; Bruns, Thomas; Piper, Mathis; Weber, Petra; Wagner, Michael; Cremer, Christoph; Schneckenburger, Herbert

2017-07-01

A miniaturized setup for sample rotation on a microscope stage has been developed, combined with light sheet, confocal or structured illumination microscopy and applied to living cells as well as to small organisms. This setup permits axial tomography with improved visualization of single cells or small cell clusters as well as an enhanced effective 3D resolution upon sample rotation.

Large Scale Structures in the GOODS-SOUTH Field up to z~2.5

NASA Astrophysics Data System (ADS)

Trevese, D.; Castellano, M.; Salimbeni, S.; Pentericci, L.; Fiore, F.

2009-05-01

We apply a density evaluation technique based on photometric redshifts, developed by our group, to estimate galaxy space density on the deep (z450~26) multi-wavelength GOODS-MUSIC catalogue. We find several groups and clusters in the redshift range 0.4-2.5. We present here an outline of the X-ray properties of our cluster sample as computed from the Chandra 2Ms data. A group at z = 0.96 could be associated to an extended X-ray source, while two clusters with masses of few times 1014Msolar have upper limits on their X-ray emission significantly lower than expected from their optical properties.

Molecular diversity of seed-borne Fusarium species associated with maize in India

USDA-ARS?s Scientific Manuscript database

A total of 62 Fusarium isolates were recovered from 106 maize seeds sampled across 13 states in India, 90% of which were identified as F. verticillioides. Our study included (1) species confirmation through PCR assay using the tef-1a gene, (2) a fumonisin cluster genotype assay using developed multi...

Spectroscopic Confirmation of Five Galaxy Clusters at z > 1.25 in the 2500 deg^2 SPT-SZ Survey

NASA Astrophysics Data System (ADS)

Khullar, Gourav; Bleem, Lindsey; Bayliss, Matthew; Gladders, Michael; South Pole Telescope (SPT) Collaboration

2018-06-01

We present spectroscopic confirmation of 5 galaxy clusters at 1.25 < z < 1.5, discovered in the 2500 deg2 South Pole Telescope Sunyaev-Zel’dovich (SPT-SZ) survey. These clusters, taken from a nearly redshift-independent mass-limited sample of clusters, have multi-wavelength follow-up imaging data from the X-ray to the near-IR, and currently form the most homogenous massive high-redshift cluster sample in existence. We briefly describe the analysis pipeline used on the low S/N spectra of these faint galaxies, and describing the multiple techniques used to extract robust redshifts from a combination of absorption-line (Ca II H&K doublet - λλ3934,3968Å) and emission-line ([OII] λλ3727,3729Å) spectral features. We present several ensemble analyses of cluster member galaxies that demonstrate the reliability of the measured redshifts. We also identify modest [OII] emission and pronounced CN and Hδ absorption in a composite stacked spectrum of 28 low S/N passive galaxy spectra with redshifts derived primarily from Ca II H&K features. This work increases the number of spectroscopically-confirmed SPT-SZ galaxy clusters at z > 1.25 from 2 to 7, further demonstrating the efficacy of SZ selection for the highest redshift massive clusters, and enabling further detailed study of these confirmed systems.

Immune Centroids Over-Sampling Method for Multi-Class Classification

DTIC Science & Technology

2015-05-22

recognize to specific antigens . The response of a receptor to an antigen can activate its hosting B-cell. Activated B-cell then proliferates and...modifying N.K. Jerne’s theory. The theory states that in a pre-existing group of lympho- cytes ( specifically B cells), a specific antigen only...the clusters of each small class, which have high data density, called global immune centroids over-sampling (denoted as Global-IC). Specifically

Implementation of hybrid clustering based on partitioning around medoids algorithm and divisive analysis on human Papillomavirus DNA

NASA Astrophysics Data System (ADS)

Arimbi, Mentari Dian; Bustamam, Alhadi; Lestari, Dian

2017-03-01

Data clustering can be executed through partition or hierarchical method for many types of data including DNA sequences. Both clustering methods can be combined by processing partition algorithm in the first level and hierarchical in the second level, called hybrid clustering. In the partition phase some popular methods such as PAM, K-means, or Fuzzy c-means methods could be applied. In this study we selected partitioning around medoids (PAM) in our partition stage. Furthermore, following the partition algorithm, in hierarchical stage we applied divisive analysis algorithm (DIANA) in order to have more specific clusters and sub clusters structures. The number of main clusters is determined using Davies Bouldin Index (DBI) value. We choose the optimal number of clusters if the results minimize the DBI value. In this work, we conduct the clustering on 1252 HPV DNA sequences data from GenBank. The characteristic extraction is initially performed, followed by normalizing and genetic distance calculation using Euclidean distance. In our implementation, we used the hybrid PAM and DIANA using the R open source programming tool. In our results, we obtained 3 main clusters with average DBI value is 0.979, using PAM in the first stage. After executing DIANA in the second stage, we obtained 4 sub clusters for Cluster-1, 9 sub clusters for Cluster-2 and 2 sub clusters in Cluster-3, with the BDI value 0.972, 0.771, and 0.768 for each main cluster respectively. Since the second stage produce lower DBI value compare to the DBI value in the first stage, we conclude that this hybrid approach can improve the accuracy of our clustering results.

Aggregates and Superaggregates of Soot with Four Distinct Fractal Morphologies

NASA Technical Reports Server (NTRS)

Sorensen, C. M.; Kim, W.; Fry, D.; Chakrabarti, A.

2004-01-01

Soot formed in laminar diffusion flames of heavily sooting fuels evolves through four distinct growth stages which give rise to four distinct aggregate fractal morphologies. These results were inferred from large and small angle static light scattering from the flames, microphotography of the flames, and analysis of soot sampled from the flames. The growth stages occur approximately over four successive orders of magnitude in aggregate size. Comparison to computer simulations suggests that these four growth stages involve either diffusion limited cluster aggregation or percolation in either three or two dimensions.

Multi-water-bag models of ion temperature gradient instability in cylindrical geometry

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

Coulette, David; Besse, Nicolas

2013-05-15

Ion temperature gradient instabilities play a major role in the understanding of anomalous transport in core fusion plasmas. In the considered cylindrical geometry, ion dynamics is described using a drift-kinetic multi-water-bag model for the parallel velocity dependency of the ion distribution function. In a first stage, global linear stability analysis is performed. From the obtained normal modes, parametric dependencies of the main spectral characteristics of the instability are then examined. Comparison of the multi-water-bag results with a reference continuous Maxwellian case allows us to evaluate the effects of discrete parallel velocity sampling induced by the Multi-Water-Bag model. Differences between themore » global model and local models considered in previous works are discussed. Using results from linear, quasilinear, and nonlinear numerical simulations, an analysis of the first stage saturation dynamics of the instability is proposed, where the divergence between the three models is examined.« less

Health-risk behaviour in Croatia.

PubMed

Bécue-Bertaut, Mónica; Kern, Josipa; Hernández-Maldonado, Maria-Luisa; Juresa, Vesna; Vuletic, Silvije

2008-02-01

To identify the health-risk behaviour of various homogeneous clusters of individuals. The study was conducted in 13 of the 20 Croatian counties and in Zagreb, the Croatian capital. In the first stage, general practices were selected in each county. The second-stage sample was created by drawing a random subsample of 10% of the patients registered at each selected general practice. The sample was divided into seven homogenous clusters using statistical methodology, combining multiple factor analysis with a hybrid clustering method. Seven homogeneous clusters were identified, three composed of males and four composed of females, based on statistically significant differences between selected characteristics (P<0.001). Although, in general, self-assessed health declined with age, significant variations were observed within specific age intervals. Higher levels of self-assessed health were associated with higher levels of education and/or socio-economic status. Many individuals, especially females, who self-reported poor health were heavy consumers of sleeping pills. Males and females reported different health-risk behaviours related to lifestyle, diet and use of the healthcare system. Heavy alcohol and tobacco use, unhealthy diet, risky physical activity and non-use of the healthcare system influenced self-assessed health in males. Females were slightly less satisfied with their health than males of the same age and educational level. Even highly educated females who took preventive healthcare tests and ate a healthy diet reported a less satisfactory self-assessed level of health than expected. Sociodemographic characteristics, life style, self-assessed health and use of the healthcare system were used in the identification of seven homogeneous population clusters. A comprehensive analysis of these clusters suggests health-related prevention and intervention efforts geared towards specific populations.

Spectral Discrimination of the Invasive Plant Spartina alterniflora at Multiple Phenological Stages in a Saltmarsh Wetland

PubMed Central

Ouyang, Zu-Tao; Gao, Yu; Xie, Xiao; Guo, Hai-Qiang; Zhang, Ting-Ting; Zhao, Bin

2013-01-01

Spartina alterniflora has widely invaded the saltmarshes of the Yangtze River Estuary and brought negative effects to the ecosystem. Remote sensing technique has recently been used to monitor its distribution, but the similar morphology and canopy structure among S. alterniflora and its neighbor species make it difficult even with high-resolution images. Nevertheless, these species have divergence on phenological stages throughout the year, which cause distinguishing spectral characteristics among them and provide opportunities for discrimination. The field spectra of the S. alterniflora community as well as its major victims, native Phragmites australis and Scirpus mariqueter, were measured in 2009 and 2010 at multi-phenological stages in the Yangtze River Estuary, aiming to find the most appropriate periods for mapping S. alterniflora. Collected spectral data were analyzed separately for every stage firstly by re-sampling reflectance curves into continued 5-nm-wide hyper-spectral bands and then by re-sampling into broad multi-spectral bands – the same as the band ranges of the TM sensor, as well as calculating commonly used vegetation indices. The results showed that differences among saltmarsh communities’ spectral characteristics were affected by their phenological stages. The germination and early vegetative growth stage and the flowering stage were probably the best timings to identify S. alterniflora. Vegetation indices like NDVI, ANVI, VNVI, and RVI are likely to enhance spectral separability and also make it possible to discriminate S. alterniflora at its withering stage. PMID:23826265

High-throughput screening of chemical effects on ...

EPA Pesticide Factsheets

Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2,060 chemical samples on steroidogenesis via HPLC-MS/MS quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a three stage screening strategy. The first stage established the maximum tolerated concentration (MTC; >70% viability) per sample. The second stage quantified changes in hormone levels at the MTC while the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were pre-stimulated with 10 µM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2,060 chemical samples evaluated, 524 samples were selected for six-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17β-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into five distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A d

High-throughput screening of chemical effects on steroidogenesis using H295R human adrenocortical carcinoma cells

EPA Pesticide Factsheets

Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2060 chemical samples on steroidogenesis via high-performance liquid chromatography followed by tandem mass spectrometry quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a 3 stage screening strategy. The first stage established the maximum tolerated concentration (MTC; ? 70% viability) per sample. The second stage quantified changes in hormone levels at the MTC whereas the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were prestimulated with 10 00b5M forskolin for 48??h to induce steroidogenesis followed by chemical treatment for 48??h. Of the 2060 chemical samples evaluated, 524 samples were selected for 6-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 1703b2-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into 5 distinct profiles generally representing putative mec

A History of H I Stripping in Virgo: A Phase-space View of VIVA Galaxies

NASA Astrophysics Data System (ADS)

Yoon, Hyein; Chung, Aeree; Smith, Rory; Jaffé, Yara L.

2017-04-01

We investigate the orbital histories of Virgo galaxies at various stages of H I gas stripping. In particular, we compare the location of galaxies with different H I morphology in phase space. This method is a great tool for tracing the gas stripping histories of galaxies as they fall into the cluster. Most galaxies at the early stage of H I stripping are found in the first infall region of Virgo, while galaxies undergoing active H I stripping mostly appear to be falling in or moving out near the cluster core for the first time. Galaxies with severely stripped, yet symmetric, H I disks are found in one of two locations. Some are deep inside the cluster, but others are found in the cluster outskirts with low orbital velocities. We suggest that the latter group of galaxies belong to a “backsplash” population. These present the clearest candidates for backsplashed galaxies observationally identified to date. We further investigate the distribution of a large sample of H I-detected galaxies toward Virgo in phase space, confirming that most galaxies are stripped of their gas as they settle into the gravitational potential of the cluster. In addition, we discuss the impact of tidal interactions between galaxies and group preprocessing on the H I properties of the cluster galaxies, and link the associated star formation evolution to the stripping sequence of cluster galaxies.

CHEERS: The chemical evolution RGS sample

NASA Astrophysics Data System (ADS)

de Plaa, J.; Kaastra, J. S.; Werner, N.; Pinto, C.; Kosec, P.; Zhang, Y.-Y.; Mernier, F.; Lovisari, L.; Akamatsu, H.; Schellenberger, G.; Hofmann, F.; Reiprich, T. H.; Finoguenov, A.; Ahoranta, J.; Sanders, J. S.; Fabian, A. C.; Pols, O.; Simionescu, A.; Vink, J.; Böhringer, H.

2017-11-01

Context. The chemical yields of supernovae and the metal enrichment of the intra-cluster medium (ICM) are not well understood. The hot gas in clusters of galaxies has been enriched with metals originating from billions of supernovae and provides a fair sample of large-scale metal enrichment in the Universe. High-resolution X-ray spectra of clusters of galaxies provide a unique way of measuring abundances in the hot intracluster medium (ICM). The abundance measurements can provide constraints on the supernova explosion mechanism and the initial-mass function of the stellar population. This paper introduces the CHEmical Enrichment RGS Sample (CHEERS), which is a sample of 44 bright local giant ellipticals, groups, and clusters of galaxies observed with XMM-Newton. Aims: The CHEERS project aims to provide the most accurate set of cluster abundances measured in X-rays using this sample. This paper focuses specifically on the abundance measurements of O and Fe using the reflection grating spectrometer (RGS) on board XMM-Newton. We aim to thoroughly discuss the cluster to cluster abundance variations and the robustness of the measurements. Methods: We have selected the CHEERS sample such that the oxygen abundance in each cluster is detected at a level of at least 5σ in the RGS. The dispersive nature of the RGS limits the sample to clusters with sharp surface brightness peaks. The deep exposures and the size of the sample allow us to quantify the intrinsic scatter and the systematic uncertainties in the abundances using spectral modeling techniques. Results: We report the oxygen and iron abundances as measured with RGS in the core regions of all 44 clusters in the sample. We do not find a significant trend of O/Fe as a function of cluster temperature, but we do find an intrinsic scatter in the O and Fe abundances from cluster to cluster. The level of systematic uncertainties in the O/Fe ratio is estimated to be around 20-30%, while the systematic uncertainties in the absolute O and Fe abundances can be as high as 50% in extreme cases. Thanks to the high statistics of the observations, we were able to identify and correct a systematic bias in the oxygen abundance determination that was due to an inaccuracy in the spectral model. Conclusions: The lack of dependence of O/Fe on temperature suggests that the enrichment of the ICM does not depend on cluster mass and that most of the enrichment likely took place before the ICM was formed. We find that the observed scatter in the O/Fe ratio is due to a combination of intrinsic scatter in the source and systematic uncertainties in the spectral fitting, which we are unable to separate. The astrophysical source of intrinsic scatter could be due to differences in active galactic nucleus activity and ongoing star formation in the brightest cluster galaxy. The systematic scatter is due to uncertainties in the spatial line broadening, absorption column, multi-temperature structure, and the thermal plasma models.

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.

PubMed

Lajnef, Tarek; Chaibi, Sahbi; Ruby, Perrine; Aguera, Pierre-Emmanuel; Eichenlaub, Jean-Baptiste; Samet, Mounir; Kachouri, Abdennaceur; Jerbi, Karim

2015-07-30

Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are promising, there is need for improvement, especially given the time-consuming and tedious nature of visual sleep scoring. Here we propose a sleep staging framework that consists of a multi-class support vector machine (SVM) classification based on a decision tree approach. The performance of the method was evaluated using polysomnographic data from 15 subjects (electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) recordings). The decision tree, or dendrogram, was obtained using a hierarchical clustering technique and a wide range of time and frequency-domain features were extracted. Feature selection was carried out using forward sequential selection and classification was evaluated using k-fold cross-validation. The dendrogram-based SVM (DSVM) achieved mean specificity, sensitivity and overall accuracy of 0.92, 0.74 and 0.88 respectively, compared to expert visual scoring. Restricting DSVM classification to data where both experts' scoring was consistent (76.73% of the data) led to a mean specificity, sensitivity and overall accuracy of 0.94, 0.82 and 0.92 respectively. The DSVM framework outperforms classification with more standard multi-class "one-against-all" SVM and linear-discriminant analysis. The promising results of the proposed methodology suggest that it may be a valuable alternative to existing automatic methods and that it could accelerate visual scoring by providing a robust starting hypnogram that can be further fine-tuned by expert inspection. Copyright © 2015 Elsevier B.V. All rights reserved.

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

PubMed Central

2013-01-01

Background There is a rising public and political demand for prospective cancer cluster monitoring. But there is little empirical evidence on the performance of established cluster detection tests under conditions of small and heterogeneous sample sizes and varying spatial scales, such as are the case for most existing population-based cancer registries. Therefore this simulation study aims to evaluate different cluster detection methods, implemented in the open soure environment R, in their ability to identify clusters of lung cancer using real-life data from an epidemiological cancer registry in Germany. Methods Risk surfaces were constructed with two different spatial cluster types, representing a relative risk of RR = 2.0 or of RR = 4.0, in relation to the overall background incidence of lung cancer, separately for men and women. Lung cancer cases were sampled from this risk surface as geocodes using an inhomogeneous Poisson process. The realisations of the cancer cases were analysed within small spatial (census tracts, N = 1983) and within aggregated large spatial scales (communities, N = 78). Subsequently, they were submitted to the cluster detection methods. The test accuracy for cluster location was determined in terms of detection rates (DR), false-positive (FP) rates and positive predictive values. The Bayesian smoothing models were evaluated using ROC curves. Results With moderate risk increase (RR = 2.0), local cluster tests showed better DR (for both spatial aggregation scales > 0.90) and lower FP rates (both < 0.05) than the Bayesian smoothing methods. When the cluster RR was raised four-fold, the local cluster tests showed better DR with lower FPs only for the small spatial scale. At a large spatial scale, the Bayesian smoothing methods, especially those implementing a spatial neighbourhood, showed a substantially lower FP rate than the cluster tests. However, the risk increases at this scale were mostly diluted by data aggregation. Conclusion High resolution spatial scales seem more appropriate as data base for cancer cluster testing and monitoring than the commonly used aggregated scales. We suggest the development of a two-stage approach that combines methods with high detection rates as a first-line screening with methods of higher predictive ability at the second stage. PMID:24314148

MYCN-non-amplified metastatic neuroblastoma with good prognosis and spontaneous regression: a molecular portrait of stage 4S.

PubMed

Bénard, Jean; Raguénez, Gilda; Kauffmann, Audrey; Valent, Alexander; Ripoche, Hugues; Joulin, Virginie; Job, Bastien; Danglot, Gisèle; Cantais, Sabrina; Robert, Thomas; Terrier-Lacombe, Marie-José; Chassevent, Agnès; Koscielny, Serge; Fischer, Matthias; Berthold, Frank; Lipinski, Marc; Tursz, Thomas; Dessen, Philippe; Lazar, Vladimir; Valteau-Couanet, Dominique

2008-10-01

Stage 4 neuroblastoma (NB) are heterogeneous regarding their clinical presentations and behavior. Indeed infants (stage 4S and non-stage 4S of age <365days at diagnosis) show regression contrasting with progression in children (>365days). Our study aimed at: (i) identifying age-based genomic and gene expression profiles of stage 4 NB supporting this clinical stratification; and (ii) finding a stage 4S NB signature. Differential genome and transcriptome analyses of a learning set of MYCN-non amplified stage 4 NB tumors at diagnosis (n=29 tumors including 12 stage 4S) were performed using 1Mb BAC microarrays and Agilent 22K probes oligo-microarrays. mRNA chips data following filtering yielded informative genes before supervised hierarchical clustering to identify relationship among tumor samples. After confirmation by quantitative RT-PCR, a stage 4S NB's gene cluster was obtained and submitted to a validation set (n=22 tumors). Genomic abnormalities of infant's tumors (whole chromosomes gains or loss) differ radically from that of children (intra-chromosomal rearrangements) but could not discriminate infants with 4S from those without this presentation. In contrast, differential gene expression by looking at both individual genes and whole biological pathways leads to a molecular stage 4S NB portrait which provides new biological clues about this fascinating entity.

Effect of W self-implantation and He plasma exposure on early-stage defect and bubble formation in tungsten

NASA Astrophysics Data System (ADS)

Thompson, M.; Drummond, D.; Sullivan, J.; Elliman, R.; Kluth, P.; Kirby, N.; Riley, D.; Corr, C. S.

2018-06-01

To determine the effect of pre-existing defects on helium-vacancy cluster nucleation and growth, tungsten samples were self-implanted with 1 MeV tungsten ions at varying fluences to induce radiation damage, then subsequently exposed to helium plasma in the MAGPIE linear plasma device. Positron annihilation lifetime spectroscopy was performed both immediately after self-implantation, and again after plasma exposure. After self-implantation vacancies clusters were not observed near the sample surface (<30 nm). At greater depths (30–150 nm) vacancy clusters formed, and were found to increase in size with increasing W-ion fluence. After helium plasma exposure in the MAGPIE linear plasma device at ~300 K with a fluence of 1023 He-m‑2, deep (30–150 nm) vacancy clusters showed similar positron lifetimes, while shallow (<30 nm) clusters were not observed. The intensity of positron lifetime signals fell for most samples after plasma exposure, indicating that defects were filling with helium. The absence of shallow clusters indicates that helium requires pre-existing defects in order to drive vacancy cluster growth at 300 K. Further samples that had not been pre-damaged with W-ions were also exposed to helium plasma in MAGPIE across fluences from 1  ×  1022 to 1.2  ×  1024 He-m‑2. Samples exposed to fluences up to 1  ×  1023 He-m‑2 showed no signs of damage. Fluences of 5  ×  1023 He-m‑2 and higher showed significant helium-cluster formation within the first 30 nm, with positron lifetimes in the vicinity 0.5–0.6 ns. The sample temperature was significantly higher for these higher fluence exposures (~400 K) due to plasma heating. This higher temperature likely enhanced bubble formation by significantly increasing the rate interstitial helium clusters generate vacancies, which is we suspect is the rate-limiting step for helium-vacancy cluster/bubble nucleation in the absence of pre-existing defects.

Absorption spectroscopy and multi-angle scattering measurements in the visible spectral range for the geographic classification of Italian exravirgin olive oils

NASA Astrophysics Data System (ADS)

Mignani, Anna G.; Ciaccheri, Leonardo; Cimato, Antonio; Sani, Graziano; Smith, Peter R.

2004-03-01

Absorption spectroscopy and multi-angle scattering measurements in the visible spectral range are innovately used to analyze samples of extra virgin olive oils coming from selected areas of Tuscany, a famous Italian region for the production of extra virgin olive oil. The measured spectra are processed by means of the Principal Component Analysis method, so as to create a 3D map capable of clustering the Tuscan oils within the wider area of Italian extra virgin olive oils.

Effects of PREPARE, a Multi-component, School-Based HIV and Intimate Partner Violence (IPV) Prevention Programme on Adolescent Sexual Risk Behaviour and IPV: Cluster Randomised Controlled Trial.

PubMed

Mathews, Catherine; Eggers, Sander M; Townsend, Loraine; Aarø, Leif E; de Vries, Petrus J; Mason-Jones, Amanda J; De Koker, Petra; McClinton Appollis, Tracy; Mtshizana, Yolisa; Koech, Joy; Wubs, Annegreet; De Vries, Hein

2016-09-01

Young South Africans, especially women, are at high risk of HIV. We evaluated the effects of PREPARE, a multi-component, school-based HIV prevention intervention to delay sexual debut, increase condom use and decrease intimate partner violence (IPV) among young adolescents. We conducted a cluster RCT among Grade eights in 42 high schools. The intervention comprised education sessions, a school health service and a school sexual violence prevention programme. Participants completed questionnaires at baseline, 6 and 12 months. Regression was undertaken to provide ORs or coefficients adjusted for clustering. Of 6244 sampled adolescents, 55.3 % participated. At 12 months there were no differences between intervention and control arms in sexual risk behaviours. Participants in the intervention arm were less likely to report IPV victimisation (35.1 vs. 40.9 %; OR 0.77, 95 % CI 0.61-0.99; t(40) = 2.14) suggesting the intervention shaped intimate partnerships into safer ones, potentially lowering the risk for HIV.

Types of Bullying in the Senior High Schools in Ghana

ERIC Educational Resources Information Center

Antiri, Kwasi Otopa

2016-01-01

The main objective of the study was to examine the types of bullying that were taking place in the senior high schools in Ghana. A multi-stage sampling procedure, comprising purposive, simple random and snowball sampling technique, was used in the selection of the sample. A total of 354 respondents were drawn six schools in Ashanti, Central and…

Characterization of high explosive particles using cluster secondary ion mass spectrometry.

PubMed

Gillen, Greg; Mahoney, Christine; Wight, Scott; Lareau, Richard

2006-01-01

The use of secondary ion mass spectrometry (SIMS) for the detection and spatially resolved analysis of individual high explosive particles is described. A C(8) (-) carbon cluster primary ion beam was used in a commercial SIMS instrument to analyze samples of high explosives dispersed as particles on silicon substrates. In comparison with monatomic primary ion bombardment, the carbon cluster primary ion beam was found to greatly enhance characteristic secondary ion signals from the explosive compounds while causing minimal beam-induced degradation. The resistance of these compounds to degradation under ion bombardment allows explosive particles to be analyzed under high primary ion dose bombardment (dynamic SIMS) conditions, facilitating the rapid acquisition of spatially resolved molecular information. The use of cluster SIMS combined with computer control of the sample stage position allows for the automated identification and counting of explosive particle distributions on silicon surfaces. This will be useful for characterizing the efficiency of transfer of particulates in trace explosive detection portal collectors and/or swipes utilized for ion mobility spectrometry applications.

Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

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

Liu, Z.; Bessa, M. A.; Liu, W.K.

A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical andmore » concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about 43,000 is achieved by using the SCA method, as opposed to FE2, enabling the solution of an otherwise computationally intractable problem. The second example uses a crystal plasticity constitutive law and computes the fatigue potency of extrinsic microscale features such as voids. This shows that local stress and strain are capture sufficiently well by SCA. This model has been incorporated in a process-structure-properties prediction framework for process design in additive manufacturing.« less

Low-Dead-Volume Inlet for Vacuum Chamber

NASA Technical Reports Server (NTRS)

Naylor, Guy; Arkin, C.

2010-01-01

Gas introduction from near-ambient pressures to high vacuum traditionally is accomplished either by multi-stage differential pumping that allows for very rapid response, or by a capillary method that allows for a simple, single-stage introduction, but which often has a delayed response. Another means to introduce the gas sample is to use the multi-stage design with only a single stage. This is accomplished by using a very small conductance limit. The problem with this method is that a small conductance limit will amplify issues associated with dead -volume. As a result, a high -vacuum gas inlet was developed with low dead -volume, allowing the use of a very low conductance limit interface. Gas flows through the ConFlat flange at a relatively high flow rate at orders of magnitude greater than through the conductance limit. The small flow goes through a conductance limit that is a double-sided ConFlat.

Low-Dead-Volume Inlet for Vacuum Chamber

NASA Technical Reports Server (NTRS)

Naylor, Guy; Arkin, C.

2011-01-01

Gas introduction from near-ambient pressures to high vacuum traditionally is accomplished either by multi-stage differential pumping that allows for very rapid response, or by a capillary method that allows for a simple, single-stage introduction, but which often has a delayed response. Another means to introduce the gas sample is to use the multi-stage design with only a single stage. This is accomplished by using a very small conductance limit. The problem with this method is that a small conductance limit will amplify issues associated with dead-volume. As a result, a high-vacuum gas inlet was developed with low dead-volume, allowing the use of a very low conductance limit interface. Gas flows through the ConFlat flange at a relatively high flow rate at orders of magnitude greater than through the conductance limit. The small flow goes through a conductance limit that is a double-sided ConFlat.

Cluster analysis and its application to healthcare claims data: a study of end-stage renal disease patients who initiated hemodialysis.

PubMed

Liao, Minlei; Li, Yunfeng; Kianifard, Farid; Obi, Engels; Arcona, Stephen

2016-03-02

Cluster analysis (CA) is a frequently used applied statistical technique that helps to reveal hidden structures and "clusters" found in large data sets. However, this method has not been widely used in large healthcare claims databases where the distribution of expenditure data is commonly severely skewed. The purpose of this study was to identify cost change patterns of patients with end-stage renal disease (ESRD) who initiated hemodialysis (HD) by applying different clustering methods. A retrospective, cross-sectional, observational study was conducted using the Truven Health MarketScan® Research Databases. Patients aged ≥18 years with ≥2 ESRD diagnoses who initiated HD between 2008 and 2010 were included. The K-means CA method and hierarchical CA with various linkage methods were applied to all-cause costs within baseline (12-months pre-HD) and follow-up periods (12-months post-HD) to identify clusters. Demographic, clinical, and cost information was extracted from both periods, and then examined by cluster. A total of 18,380 patients were identified. Meaningful all-cause cost clusters were generated using K-means CA and hierarchical CA with either flexible beta or Ward's methods. Based on cluster sample sizes and change of cost patterns, the K-means CA method and 4 clusters were selected: Cluster 1: Average to High (n = 113); Cluster 2: Very High to High (n = 89); Cluster 3: Average to Average (n = 16,624); or Cluster 4: Increasing Costs, High at Both Points (n = 1554). Median cost changes in the 12-month pre-HD and post-HD periods increased from $185,070 to $884,605 for Cluster 1 (Average to High), decreased from $910,930 to $157,997 for Cluster 2 (Very High to High), were relatively stable and remained low from $15,168 to $13,026 for Cluster 3 (Average to Average), and increased from $57,909 to $193,140 for Cluster 4 (Increasing Costs, High at Both Points). Relatively stable costs after starting HD were associated with more stable scores on comorbidity index scores from the pre-and post-HD periods, while increasing costs were associated with more sharply increasing comorbidity scores. The K-means CA method appeared to be the most appropriate in healthcare claims data with highly skewed cost information when taking into account both change of cost patterns and sample size in the smallest cluster.

Network module detection: Affinity search technique with the multi-node topological overlap measure

PubMed Central

Li, Ai; Horvath, Steve

2009-01-01

Background Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. Findings We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Conclusion Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: PMID:19619323

Network module detection: Affinity search technique with the multi-node topological overlap measure.

PubMed

Li, Ai; Horvath, Steve

2009-07-20

Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

A multi-wavelength census of star formation activity in the young embedded cluster around Serpens/G3-G6

NASA Astrophysics Data System (ADS)

Djupvik, A. A.; André, Ph.; Bontemps, S.; Motte, F.; Olofsson, G.; Gålfalk, M.; Florén, H.-G.

2006-11-01

Aims.The aim of this paper is to characterise the star formation activity in the poorly studied embedded cluster Serpens/G3-G6, located ~45 arcmin (3 pc) to the south of the Serpens Cloud Core, and to determine the luminosity and mass functions of its population of Young Stellar Objects (YSOs). Methods: .Multi-wavelength broadband photometry was obtained to sample the near and mid-IR spectral energy distributions to separate YSOs from field stars and classify the YSO evolutionary stage. ISOCAM mapping in the two filters LW2 (5-8.5 μm) and LW3 (12-18 μm) of a 19 arcmin × 16 arcmin field was combined with JHKS data from 2MASS, KS data from Arnica/NOT, and L arcmin data from SIRCA/NOT. Continuum emission at 1.3 mm (IRAM) and 3.6 cm (VLA) was mapped to study the cloud structure and the coldest/youngest sources. Deep narrow band imaging at the 2.12 μm S(1) line of H2 from NOTCam/NOT was obtained to search for signs of bipolar outflows. Results: .We have strong evidence for a stellar population of 31 Class II sources, 5 flat-spectrum sources, 5 Class I sources, and two Class 0 sources. Our method does not sample the Class III sources. The cloud is composed of two main dense clumps aligned along a ridge over ~0.5 pc plus a starless core coinciding with absorption features seen in the ISOCAM maps. We find two S-shaped bipolar collimated flows embedded in the NE clump, and propose the two driving sources to be a Class 0 candidate (MMS3) and a double Class I (MMS2). For the Class II population we find a best age of ~2 Myr and compatibility with recent Initial Mass Functions (IMFs) by comparing the observed Class II luminosity function (LF), which is complete to 0.08 L⊙, to various model LFs with different star formation scenarios and input IMFs.

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

PubMed

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for personalized cancer therapy.

The need of adequate information to achieve total compliance of mass drug administration in Pekalongan

NASA Astrophysics Data System (ADS)

Ginandjar, Praba; Saraswati, Lintang Dian; Taufik, Opik; Nurjazuli; Widjanarko, Bagoes

2017-02-01

World Health Organization (WHO) initiated The Global Program to Eliminate Lymphatic Filariasis (LF) through mass drug administration (MDA). Pekalongan started MDA in 2011. Yet the LF prevalence in 2015 remained exceed the threshold (1%). This study aimed to describe the inhibiting factors related to the compliance of MDA in community level. This was a rapid survey with cross sectional approach. A two-stages random sampling was used in this study. In the first stage, 25 clusters were randomly selected from 27 villages with proportionate to population size (PPS) methods (C-Survey). In the second stage, 10 subjects were randomly selected from each cluster. Subject consisted of 250 respondents from 25 selected clusters. Variables consisted of MDA coverage, practice of taking medication during MDA, enabling and inhibiting factors to MDA in community level. The results showed most respondents had poor knowledge on filariasis, which influence awareness of the disease. Health-illness perception, did not receive the drugs, lactation, side effect, and size of the drugs were dominant factors of non-compliance to MDA. MDA information and community empowerment were needed to improve MDA coverage. Further study to explore the appropriate model of socialization will support the success of MDA program

Development of Effective Teacher Program: Teamwork Building Program for Thailand's Municipal Schools

ERIC Educational Resources Information Center

Chantathai, Pimpka; Tesaputa, Kowat; Somprach, Kanokorn

2015-01-01

This research is aimed to formulate the effective teacher teamwork program in municipal schools in Thailand. Primary survey on current situation and problem was conducted to develop the plan to suggest potential programs. Samples were randomly selected from municipal schools by using multi-stage sampling method in order to investigate their…

The Impact of Education on Rural Women's Participation in Political and Economic Activities

ERIC Educational Resources Information Center

Bishaw, Alemayehu

2014-01-01

This study endeavored to investigate the impact of education on rural women's participation in political and economic activities. Six hundred rural women and 12 gender Activists were selected for this study from three Zones of Amhara Region, Ethiopia using multi-stage random sampling technique and purposeful sampling techniques respectively.…

Enhancing Argumentative Writing Skill through Contextual Teaching and Learning

ERIC Educational Resources Information Center

Hasani, Aceng

2016-01-01

This study aims to describe the influence of contextual learning model and critical thinking ability toward argumentative writing skill on university students. The population of the research was 147 university students, and 52 university students were used as sample with multi stage sampling. The results of the research indicate that; group of…

Acculturation Stress, Drinking, and Intimate Partner Violence among Hispanic Couples in the U.S

ERIC Educational Resources Information Center

Caetano, Raul; Ramisetty-Mikler, Suhasini; Caetano Vaeth, Patrice A.; Harris, T. Robert

2007-01-01

This article examines the cross-sectional association between acculturation, acculturation stress, drinking, and intimate partner violence (IPV) among Hispanic couples in the U.S. The data being analyzed come from a multi-cluster random household sample of couples interviewed as part of the second wave of a 5-year national longitudinal study. The…

PRIMUS: Galaxy clustering as a function of luminosity and color at 0.2 < z < 1

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

Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.

2014-04-01

We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(r{sub p} , π) and w{sub p} (r{sub p} ), using volume-limited samples constructed from a parent sample of over ∼130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg{sup 2} of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1more » Mpc h {sup –1} < r{sub p} < 1 Mpc h {sup –1}) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b {sub gal} ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ∼ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that 'cosmic variance' can be a significant source of uncertainty for high-redshift clustering measurements.« less

PRIMUS: Galaxy Clustering as a Function of Luminosity and Color at 0.2 < z < 1

NASA Astrophysics Data System (ADS)

Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.; Moustakas, John; Aird, James; Blanton, Michael R.; Bray, Aaron D.; Cool, Richard J.; Eisenstein, Daniel J.; Mendez, Alexander J.; Wong, Kenneth C.; Zhu, Guangtun

2014-04-01

We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(rp , π) and wp (rp ), using volume-limited samples constructed from a parent sample of over ~130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg2 of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1 Mpc h -1 < rp < 1 Mpc h -1) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b gal ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ~ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that "cosmic variance" can be a significant source of uncertainty for high-redshift clustering measurements.

Communication: An efficient approach to compute state-specific nuclear gradients for a generic state-averaged multi-configuration self consistent field wavefunction.

PubMed

Granovsky, Alexander A

2015-12-21

We present a new, very efficient semi-numerical approach for the computation of state-specific nuclear gradients of a generic state-averaged multi-configuration self consistent field wavefunction. Our approach eliminates the costly coupled-perturbed multi-configuration Hartree-Fock step as well as the associated integral transformation stage. The details of the implementation within the Firefly quantum chemistry package are discussed and several sample applications are given. The new approach is routinely applicable to geometry optimization of molecular systems with 1000+ basis functions using a standalone multi-core workstation.

Communication: An efficient approach to compute state-specific nuclear gradients for a generic state-averaged multi-configuration self consistent field wavefunction

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

Granovsky, Alexander A., E-mail: alex.granovsky@gmail.com

We present a new, very efficient semi-numerical approach for the computation of state-specific nuclear gradients of a generic state-averaged multi-configuration self consistent field wavefunction. Our approach eliminates the costly coupled-perturbed multi-configuration Hartree-Fock step as well as the associated integral transformation stage. The details of the implementation within the Firefly quantum chemistry package are discussed and several sample applications are given. The new approach is routinely applicable to geometry optimization of molecular systems with 1000+ basis functions using a standalone multi-core workstation.

Awareness of cervical cancer risk factors and symptoms: cross-sectional community survey in post-conflict northern Uganda.

PubMed

Mwaka, Amos D; Orach, Christopher G; Were, Edward M; Lyratzopoulos, Georgios; Wabinga, Henry; Roland, Martin

2016-08-01

Lack of awareness of risk factors and symptoms for cancer may lead to late diagnosis and poor prognosis. We assessed community awareness about cervical cancer risk factors and symptoms and perceptions about prevention and cure of cervical cancer in order to contribute data to inform interventions to improve cervical cancer survival. Cross-sectional population-based survey. We conducted this study in Gulu, a post-conflict district in Uganda in 2012. The sample included 448 persons aged 18 years and above, selected through a multi-stage stratified cluster sampling process. We collected data using a pretested structured questionnaire. Logistic regressions were used to determine magnitudes of associations between socio-demographic and outcome variables. Most participants (444/448) had heard about cervical cancer. Known risk factors including multiple sexual partners, human papillomavirus infection, and early onset of sexual activity, were recognized by 88%, 82%, and 78% of respondents respectively. 63% of participants believed that prolonged use of family planning pills and injections caused cervical cancer. The majority of participants recognized symptoms of cervical cancer including inter-menstrual bleeding (85%), post-menopausal bleeding (84%), and offensive vaginal discharge (83%). 70% of participants believed that cervical cancer is preventable and 92% believed that it could be cured if diagnosed at an early stage. Recognition of cervical cancer risk factors and symptoms was high among study participants. Targeted interventions including increasing availability of HPV vaccination, population-based cervical screening and diagnostic services can translate high awareness into actual benefits. © 2015 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

Cluster mass profile reconstruction with size and flux magnification on the HST STAGES survey.

PubMed

Duncan, Christopher A J; Heymans, Catherine; Heavens, Alan F; Joachimi, Benjamin

2016-03-21

We present the first measurement of individual cluster mass estimates using weak lensing size and flux magnification. Using data from the HST STAGES (Space Telescope A901/902 Galaxy Evolution Survey) survey of the A901/902 supercluster we detect the four known groups in the supercluster at high significance using magnification alone. We discuss the application of a fully Bayesian inference analysis, and investigate a broad range of potential systematics in the application of the method. We compare our results to a previous weak lensing shear analysis of the same field finding the recovered signal-to-noise of our magnification-only analysis to range from 45 to 110 per cent of the signal-to-noise in the shear-only analysis. On a case-by-case basis we find consistent magnification and shear constraints on cluster virial radius, and finding that for the full sample, magnification constraints to be a factor 0.77 ± 0.18 lower than the shear measurements.

Molecular epidemiological characteristics of Salmonella enterica serovars Enteritidis, Typhimurium and Livingstone strains isolated in a Tunisian university hospital.

PubMed

Ktari, Sonia; Ksibi, Boutheina; Gharsallah, Houda; Mnif, Basma; Maalej, Sonda; Rhimi, Fouzia; Hammami, Adnene

2016-03-01

Enteritidis, Typhimurium and Livingstone are the main Salmonella enterica serovars recovered in Tunisia. Here, we aimed to assess the genetic diversity of fifty-seven Salmonella enterica strains from different sampling periods, origins and settings using pulsed-field gel electrophoresis (PFGE), multi-locus sequence typing (MLST) and multi-locus variable-number tandem repeat analysis (MLVA). Salmonella Enteritidis, isolated from human and food sources from two regions in Sfax in 2007, were grouped into one cluster using PFGE. However, using MLVA these strains were divided into two clusters. Salmonella Typhimurium strains, recovered in 2012 and represent sporadic cases of human clinical isolates, were included in one PFGE cluster. Nevertheless, the MLVA technique, divided Salmonella Typhimurium isolates into six clusters with diversity index reaching (DI = 0.757). For Salmonella Livingstone which was responsible of two nosocomial outbreaks during 2000-2003, the PFGE and MLVA methods showed that these strains were genetically closely related. Salmonella Enteritidis and Salmonella Livingstone populations showed a single ST lineage ST11 and ST543 respectively. For Salmonella Typhimurium, two MLST sequence types ST19 and ST328 were defined. Salmonella Enteritidis and Salmonella Typhimurium strains were clearly differentiated by MLVA which was not the case using PFGE. © 2015 APMIS. Published by John Wiley & Sons Ltd.

Possible pathways used to predict different stages of lung adenocarcinoma.

PubMed

Chen, Xiaodong; Duan, Qiongyu; Xuan, Ying; Sun, Yunan; Wu, Rong

2017-04-01

We aimed to find some specific pathways that can be used to predict the stage of lung adenocarcinoma.RNA-Seq expression profile data and clinical data of lung adenocarcinoma (stage I [37], stage II 161], stage III [75], and stage IV [45]) were obtained from the TCGA dataset. The differentially expressed genes were merged, correlation coefficient matrix between genes was constructed with correlation analysis, and unsupervised clustering was carried out with hierarchical clustering method. The specific coexpression network in every stage was constructed with cytoscape software. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed with KOBAS database and Fisher exact test. Euclidean distance algorithm was used to calculate total deviation score. The diagnostic model was constructed with SVM algorithm.Eighteen specific genes were obtained by getting intersection of 4 group differentially expressed genes. Ten significantly enriched pathways were obtained. In the distribution map of 10 pathways score in different groups, degrees that sample groups deviated from the normal level were as follows: stage I < stage II < stage III < stage IV. The pathway score of 4 stages exhibited linear change in some pathways, and the score of 1 or 2 stages were significantly different from the rest stages in some pathways. There was significant difference between dead and alive for these pathways except thyroid hormone signaling pathway.Those 10 pathways are associated with the development of lung adenocarcinoma and may be able to predict different stages of it. Furthermore, these pathways except thyroid hormone signaling pathway may be able to predict the prognosis.

Structure and thermodynamics of a mixture of patchy and spherical colloids: A multi-body association theory with complete reference fluid information

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

Bansal, Artee; Asthagiri, D.; Cox, Kenneth R.

A mixture of solvent particles with short-range, directional interactions and solute particles with short-range, isotropic interactions that can bond multiple times is of fundamental interest in understanding liquids and colloidal mixtures. Because of multi-body correlations, predicting the structure and thermodynamics of such systems remains a challenge. Earlier Marshall and Chapman [J. Chem. Phys. 139, 104904 (2013)] developed a theory wherein association effects due to interactions multiply the partition function for clustering of particles in a reference hard-sphere system. The multi-body effects are incorporated in the clustering process, which in their work was obtained in the absence of the bulk medium.more » The bulk solvent effects were then modeled approximately within a second order perturbation approach. However, their approach is inadequate at high densities and for large association strengths. Based on the idea that the clustering of solvent in a defined coordination volume around the solute is related to occupancy statistics in that defined coordination volume, we develop an approach to incorporate the complete information about hard-sphere clustering in a bulk solvent at the density of interest. The occupancy probabilities are obtained from enhanced sampling simulations but we also develop a concise parametric form to model these probabilities using the quasichemical theory of solutions. We show that incorporating the complete reference information results in an approach that can predict the bonding state and thermodynamics of the colloidal solute for a wide range of system conditions.« less

Small Angle Neutron Scattering (SANS) Studies on the Structural Evolution of Pyromellitamide Self-assembled Gels

DOE PAGES

Scott, Jamieson; Tong, Katie; William, Hamilton; ...

2014-10-31

The kinetics of aggregation of two pyromellitamide gelators; tetrabutyl- (C4) and tetrahexylpyromellitamide (C6), in deuterated cyclohexane has been investigated by small angle neutron scattering (SANS) for up to six days. The purpose of this study was to improve our understanding of how self-assembled gels are formed. Short-term (< 3 hour) time scales revealed multiple phases with the data for the tetrabutylpyromellitamide C4 indicating one dimensional stacking and aggregation corresponding to a multi-fiber braided cluster arrangement that is about 35 Å in diameter. The corresponding tetrahexylpyromellitamide C6 data suggests that the C6 also forms one-dimensional stacks but that these aggregate tomore » a thicker multi-fiber braided cluster that have a diameter of 61.8 Å. Over a longer period of time, the radius, persistence length and contour length all continue to increase in 6 days after cooling. This data suggests that structural changes in self-assembled gels occur over a period exceeding several days and that fairly subtle changes in the structure (e.g. tail-length) can influence the packing of molecules in self-assembled gels on the single-to-few fiber bundle stage.« less

Small Angle Neutron Scattering (SANS) Studies on the Structural Evolution of Pyromellitamide Self-assembled Gels

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

Scott, Jamieson; Tong, Katie; William, Hamilton

The kinetics of aggregation of two pyromellitamide gelators; tetrabutyl- (C4) and tetrahexylpyromellitamide (C6), in deuterated cyclohexane has been investigated by small angle neutron scattering (SANS) for up to six days. The purpose of this study was to improve our understanding of how self-assembled gels are formed. Short-term (< 3 hour) time scales revealed multiple phases with the data for the tetrabutylpyromellitamide C4 indicating one dimensional stacking and aggregation corresponding to a multi-fiber braided cluster arrangement that is about 35 Å in diameter. The corresponding tetrahexylpyromellitamide C6 data suggests that the C6 also forms one-dimensional stacks but that these aggregate tomore » a thicker multi-fiber braided cluster that have a diameter of 61.8 Å. Over a longer period of time, the radius, persistence length and contour length all continue to increase in 6 days after cooling. This data suggests that structural changes in self-assembled gels occur over a period exceeding several days and that fairly subtle changes in the structure (e.g. tail-length) can influence the packing of molecules in self-assembled gels on the single-to-few fiber bundle stage.« less

Blastodinium spp. infect copepods in the ultra-oligotrophic marine waters of the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Alves-de-Souza, C.; Cornet, C.; Nowaczyk, A.; Gasparini, S.; Skovgaard, A.; Guillou, L.

2011-08-01

Blastodinium are chloroplast-containing dinoflagellates which infect a wide range of copepods. They develop inside the gut of their host, where they produce successive generations of sporocytes that are eventually expelled through the anus of the copepod. Here, we report on copepod infections in the oligotrophic to ultra-oligotrophic waters of the Mediterranean Sea sampled during the BOUM cruise. Based on a DNA-stain screening of gut contents, 16 % of copepods were possibly infected in samples from the Eastern Mediterranean infected, with up to 51 % of Corycaeidae, 33 % of Calanoida, but less than 2 % of Oithonidae and Oncaeidae. Parasites were classified into distinct morphotypes, with some tentatively assigned to species B. mangini, B. contortum, and B. cf. spinulosum. Based upon the SSU rDNA gene sequence analyses of 15 individuals, the genus Blastodinium was found to be polyphyletic, containing at least three independent clusters. The first cluster grouped all sequences retrieved from parasites of Corycaeidae and Oncaeidae during this study, and included sequences of Blastodinium mangini (the "mangini" cluster). Sequences from cells infecting Calanoida belonged to two different clusters, one including B. contortum (the "contortum" cluster), and the other uniting all B. spinulosum-like morphotypes (the "spinulosum" cluster). Cluster-specific oligonucleotidic probes were designed and tested by fluorescence in situ hybridization (FISH) in order to assess the distribution of dinospores, the Blastodinium dispersal and infecting stage. Probe-positive cells were all small thecate dinoflagellates, with lengths ranging from 7 to 18 μm. Maximal abundances of Blastodinium dinospores were detected at the Deep Chlorophyll Maximum (DCM) or slightly below. This was in contrast to distributions of autotrophic pico- and nanoplankton, microplanktonic dinoflagellates, and nauplii which showed maximal concentrations above the DCM. The distinct distribution of dinospores and nauplii argues against infection during the naupliar stage. Dinospores, described as autotrophic in the literature, may escape the severe nutrient limitation of ultra-oligotrophic ecosystems by living inside copepods.

Blastodinium spp. infect copepods in the ultra-oligotrophic marine waters of the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Alves-de-Souza, C.; Cornet, C.; Nowaczyk, A.; Gasparini, S.; Skovgaard, A.; Guillou, L.

2011-03-01

Blastodinium are chloroplast-containing dinoflagellates which infect a wide range of copepods. They develop inside the gut of their host, where they produce successive generations of sporocytes that are eventually expelled through the anus of the copepod. Here, we report on copepod infections in the oligotrophic to ultra-oligotrophic waters of the Mediterranean Sea sampled during the BOUM cruise. Based on a DNA-stain screening of gut contents, 16% of copepods were possibly infected in samples from the Eastern Mediterranean, with up to 51% of Corycaeidae, 33% of Calanoida, but less than 2% of Oithonidae and Oncaeidae. Parasites were classified into distinct morphotypes, with some tentatively assigned to species B. mangini, B. contortum, and B. cf. spinulosum. Based upon the SSU rDNA gene sequence analyses of 15 individuals, the genus Blastodinium was found to be polyphyletic, containing at least three independent clusters. The first cluster grouped all sequences retrieved from parasites of Corycaeidae and Oncaeidae during this study, and included sequences of Blastodinium mangini (the "mangini" cluster). Sequences from cells infecting Calanoida belonged to two different clusters, one including B. contortum (the "contortum" cluster), and the other uniting all B. spinulosum-like morphotypes (the "spinulosum" cluster). Cluster-specific oligonucleotidic probes were designed and tested by FISH in order to assess the distribution of dinospores, the Blastodinium dispersal and infecting stage. Probe-positive cells were all small thecate dinoflagellates, with lengths ranging from 7 to 18 μm. Maximal abundances of Blastodinium dinospores were detected at the Deep Chlorophyll Maximum (DCM) or slightly below. This was in contrast to distributions of autotrophic pico- and nanoplankton, microplanktonic dinoflagellates, and nauplii which showed maximal concentrations above the DCM. The distinct distributions of dinospores and nauplii argues against infection during the naupliar stage. Blastodinium, described as autotrophic in the literature, may escape the severe nutrient limitation of ultra-oligotrophic ecosystems by living inside copepods.

THE CLUSTER LENSING AND SUPERNOVA SURVEY WITH HUBBLE: AN OVERVIEW

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

Postman, Marc; Coe, Dan; Bradley, Larry

2012-04-01

The Cluster Lensing And Supernova survey with Hubble (CLASH) is a 524-orbit Multi-Cycle Treasury Program to use the gravitational lensing properties of 25 galaxy clusters to accurately constrain their mass distributions. The survey, described in detail in this paper, will definitively establish the degree of concentration of dark matter in the cluster cores, a key prediction of structure formation models. The CLASH cluster sample is larger and less biased than current samples of space-based imaging studies of clusters to similar depth, as we have minimized lensing-based selection that favors systems with overly dense cores. Specifically, 20 CLASH clusters are solelymore » X-ray selected. The X-ray-selected clusters are massive (kT > 5 keV) and, in most cases, dynamically relaxed. Five additional clusters are included for their lensing strength ({theta}{sub Ein} > 35'' at z{sub s} = 2) to optimize the likelihood of finding highly magnified high-z (z > 7) galaxies. A total of 16 broadband filters, spanning the near-UV to near-IR, are employed for each 20-orbit campaign on each cluster. These data are used to measure precise ({sigma}{sub z} {approx} 0.02(1 + z)) photometric redshifts for newly discovered arcs. Observations of each cluster are spread over eight epochs to enable a search for Type Ia supernovae at z > 1 to improve constraints on the time dependence of the dark energy equation of state and the evolution of supernovae. We present newly re-derived X-ray luminosities, temperatures, and Fe abundances for the CLASH clusters as well as a representative source list for MACS1149.6+2223 (z 0.544).« less

Exploring the Web : The Active Galaxy Population in the ORELSE Survey

NASA Astrophysics Data System (ADS)

Lubin, Lori

What are the physical processes that trigger starburst and nuclear activity in galaxies and drive galaxy evolution? Studies aimed at understanding this complex issue have largely focused on the cores of galaxy clusters or on field surveys, leaving underexplored intermediate-density regimes where rapid evolution occurs. As a result, we are conducting the ORELSE survey, a search for structure on scales > 10 Mpc around 18 clusters at 0.6 < z < 1.3. The survey covers 5 sq. deg., all targeted at high-density regions, making it comparable to field surveys such as DEEP2 and COSMOS. ORELSE is unmatched, with no other cluster survey having comparable breadth, depth, precision, and multi-band coverage. As such, ORELSE overcomes critical problems with previous high-redshift studies, including cosmic variance, restricted environmental ranges, sparse cluster samples, inconsistent star formation rate measures, and limited spectroscopy. From its initial spectral and photometric components, ORELSE already contains wellmeasured properties such as redshift, color, stellar mass, and star formation rate for a statistical sample of 7000 field+cluster galaxies. Because X-ray and mid-IR observations are crucial for a complete census of the active galaxy population, we propose to use the wealth of archival Chandra, Spitzer, and Herschel data in the ORELSE fields to map AGN and starburst galaxies over large scales. When complete, our sample will exceed by more than an order of magnitude the current samples of spectroscopically-confirmed active galaxies in high-redshift clusters and their environs. Combined with our numerical simulations plus galaxy formation models, we will provide a robust census of the active galaxy population in intermediate and high-density environments at z = 1, constrain the physical processes (e.g., merging, intracluster gas interactions, AGN feedback) responsible for triggering/quenching starburst and nuclear activity, and estimate their associated timescales.

Bad seeds produce bad crops: a single stage-process of prostate tumor invasion

PubMed Central

Man, Yan-gao; Gardner, William A.

2008-01-01

It is a commonly held belief that prostate carcinogenesis is a multi-stage process and that tumor invasion is triggered by the overproduction of proteolytic enzymes. This belief is consistent with data from cell cultures and animal models, whereas is hard to interpret several critical facts, including the presence of cancer in “healthy” young men and cancer DNA phenotype in morphologically normal prostate tissues. These facts argue that alternative pathways may exist for prostate tumor invasion in some cases. Since degradation of the basal cell layer is the most distinct sign of invasion, our recent studies have attempted to identify pre-invasive lesions with focal basal cell layer alterations. Our studies revealed that about 30% of prostate cancer patients harbored normal appearing duct or acinar clusters with a high frequency of focal basal cell layer disruptions. These focally disrupted basal cell layers had significantly reduced cell proliferation and tumor suppressor expression, whereas significantly elevated degeneration, apoptosis, and infiltration of immunoreactive cells. In sharp contrast, associated epithelial cell had significantly elevated proliferation, expression of malignancy-signature markers, and physical continuity with invasive lesions. Based on these and other findings, we have proposed that these normal appearing duct or acinar clusters are derived from monoclonal proliferation of genetically damaged stem cells and could progress directly to invasion through two pathways: 1) clonal in situ transformation (CIST) and 2) multi-potential progenitor mediated “budding” (MPMB). These pathways may contribute to early onset of prostate cancer at young ages, and to clinically more aggressive prostate tumors. PMID:18725981

Modeling of Aerosols in Post-Combustor Flow Path and Sampling System

NASA Technical Reports Server (NTRS)

Wey, Thomas; Liu, Nan-Suey

2006-01-01

The development and application of a multi-dimensional capability for modeling and simulation of aviation-sourced particle emissions and their precursors are elucidated. Current focus is on the role of the flow and thermal environments. The cases investigated include a film cooled turbine blade, the first-stage of a high-pressure turbine, the sampling probes, the sampling lines, and a pressure reduction chamber.

Predictors of adolescents' mental health problems in Saudi Arabia: findings from the Jeeluna® national study.

PubMed

Abou Abbas, Oraynab; AlBuhairan, Fadia

2017-01-01

Depression and anxiety among adolescents require further attention as they have profound harmful implications on several aspects of adolescents' wellbeing and can be associated with life threatening risk behaviors such as suicide. To examine the underlying risk factors for feeling so sad or hopeless and for feeling worried among adolescents in Saudi Arabia. Data from Jeeluna ® national survey was used. A cross-sectional, multi-stage, stratified, cluster random sampling technique was applied among a sample of students aged 10-19 years attending intermediate and secondary schools in Saudi Arabia. A self-administered questionnaire assessing several domains, including feeling so sad or hopeless and worried, was used to collect data. Logistic regression models were fitted to determine the different factors associated with mental health. A sample of 12,121 students was included in this study. Feeling so sad or hopeless and feeling worried were significantly more prevalent among females and older adolescents ( p  < 0.0001). The results showed that poor relationship with parents, negative body image, and chronic illness to be significantly associated with feeling so sad or hopeless and worried. Symptoms suggestive of mental health problems among adolescents in Saudi Arabia are prevalent and deserve special attention. Adopting effective strategies, including regular screening and intervention programs are highly needed to better address, detect, and control early signs of these problems.

Estimating Accuracy of Land-Cover Composition From Two-Stage Clustering Sampling

EPA Science Inventory

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), ...

SciSpark's SRDD : A Scientific Resilient Distributed Dataset for Multidimensional Data

NASA Astrophysics Data System (ADS)

Palamuttam, R. S.; Wilson, B. D.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; McGibbney, L. J.; Ramirez, P.

2015-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We have developed SciSpark, a robust Big Data framework, that extends ApacheTM Spark for scaling scientific computations. Apache Spark improves the map-reduce implementation in ApacheTM Hadoop for parallel computing on a cluster, by emphasizing in-memory computation, "spilling" to disk only as needed, and relying on lazy evaluation. Central to Spark is the Resilient Distributed Dataset (RDD), an in-memory distributed data structure that extends the functional paradigm provided by the Scala programming language. However, RDDs are ideal for tabular or unstructured data, and not for highly dimensional data. The SciSpark project introduces the Scientific Resilient Distributed Dataset (sRDD), a distributed-computing array structure which supports iterative scientific algorithms for multidimensional data. SciSpark processes data stored in NetCDF and HDF files by partitioning them across time or space and distributing the partitions among a cluster of compute nodes. We show usability and extensibility of SciSpark by implementing distributed algorithms for geospatial operations on large collections of multi-dimensional grids. In particular we address the problem of scaling an automated method for finding Mesoscale Convective Complexes. SciSpark provides a tensor interface to support the pluggability of different matrix libraries. We evaluate performance of the various matrix libraries in distributed pipelines, such as Nd4jTM and BreezeTM. We detail the architecture and design of SciSpark, our efforts to integrate climate science algorithms, parallel ingest and partitioning (sharding) of A-Train satellite observations from model grids. These solutions are encompassed in SciSpark, an open-source software framework for distributed computing on scientific data.

Binge drinking as a risk factor for violence among secondary school students in a nationally representative sample in Puerto Rico.

PubMed

Reyes-Pulliza, Juan Carlos; Rodríguez-Figueroa, Linnette; Moscoso-Álvarez, Margarita R; Colón, Héctor; Cotto-Negrón, Coral; Rivera, Laura; Irizarry-Pérez, Marisela

2015-03-01

The objective of this study was to determine the association between binge drinking and violence in a representative sample of secondary-school students in Puerto Rico. Consulta Juvenil VII (a biennial survey of school-aged youths in Puerto Rico) has a representative sample of adolescent students in Puerto Rico. A multi-stage stratified cluster sampling design was used. The sampling frame of Consulta Juvenil VII includes all the public and private schools registered with the Department of Education and the Council of General Education in Puerto Rico. The study utilizes a self-administered questionnaire that was translated and adapted from the "Student Survey of Risk and Protective Factors and Prevalence of Alcohol, Tobacco, and Other Drug Use". "Binge drinking" was defined as having 5 or more alcoholic drinks in a row during the 30 days preceding the survey. Almost 20% of the sample members reported that at least 1 instance of binge drinking had taken place during the 2 weeks prior to the survey (17.7%). After controlling for gender, age, school level, the type of system, and the parents' educational levels, the odds of a given binge drinker reporting violent behaviors were 5 times greater than the odds among non-binge drinkers (OR: 5.6; 95% CI: 4.7-6.7). The study shows an association between binge drinking and violence in Puerto Rican adolescents, indicating that Hispanic youths who abuse alcohol may be at increased risk of violence. These findings suggest that violence prevention programs should be integrated with substance use prevention programs. [PR Health

Differentially co-expressed interacting protein pairs discriminate samples under distinct stages of HIV type 1 infection.

PubMed

Yoon, Dukyong; Kim, Hyosil; Suh-Kim, Haeyoung; Park, Rae Woong; Lee, KiYoung

2011-01-01

Microarray analyses based on differentially expressed genes (DEGs) have been widely used to distinguish samples across different cellular conditions. However, studies based on DEGs have not been able to clearly determine significant differences between samples of pathophysiologically similar HIV-1 stages, e.g., between acute and chronic progressive (or AIDS) or between uninfected and clinically latent stages. We here suggest a novel approach to allow such discrimination based on stage-specific genetic features of HIV-1 infection. Our approach is based on co-expression changes of genes known to interact. The method can identify a genetic signature for a single sample as contrasted with existing protein-protein-based analyses with correlational designs. Our approach distinguishes each sample using differentially co-expressed interacting protein pairs (DEPs) based on co-expression scores of individual interacting pairs within a sample. The co-expression score has positive value if two genes in a sample are simultaneously up-regulated or down-regulated. And the score has higher absolute value if expression-changing ratios are similar between the two genes. We compared characteristics of DEPs with that of DEGs by evaluating their usefulness in separation of HIV-1 stage. And we identified DEP-based network-modules and their gene-ontology enrichment to find out the HIV-1 stage-specific gene signature. Based on the DEP approach, we observed clear separation among samples from distinct HIV-1 stages using clustering and principal component analyses. Moreover, the discrimination power of DEPs on the samples (70-100% accuracy) was much higher than that of DEGs (35-45%) using several well-known classifiers. DEP-based network analysis also revealed the HIV-1 stage-specific network modules; the main biological processes were related to "translation," "RNA splicing," "mRNA, RNA, and nucleic acid transport," and "DNA metabolism." Through the HIV-1 stage-related modules, changing stage-specific patterns of protein interactions could be observed. DEP-based method discriminated the HIV-1 infection stages clearly, and revealed a HIV-1 stage-specific gene signature. The proposed DEP-based method might complement existing DEG-based approaches in various microarray expression analyses.

Pulsed depressed collector

DOEpatents

Kemp, Mark A

2015-11-03

A high power RF device has an electron beam cavity, a modulator, and a circuit for feed-forward energy recovery from a multi-stage depressed collector to the modulator. The electron beam cavity include a cathode, an anode, and the multi-stage depressed collector, and the modulator is configured to provide pulses to the cathode. Voltages of the electrode stages of the multi-stage depressed collector are allowed to float as determined by fixed impedances seen by the electrode stages. The energy recovery circuit includes a storage capacitor that dynamically biases potentials of the electrode stages of the multi-stage depressed collector and provides recovered energy from the electrode stages of the multi-stage depressed collector to the modulator. The circuit may also include a step-down transformer, where the electrode stages of the multi-stage depressed collector are electrically connected to separate taps on the step-down transformer.

A History of H i Stripping in Virgo: A Phase-space View of VIVA Galaxies

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

Yoon, Hyein; Chung, Aeree; Smith, Rory

We investigate the orbital histories of Virgo galaxies at various stages of H i gas stripping. In particular, we compare the location of galaxies with different H i morphology in phase space. This method is a great tool for tracing the gas stripping histories of galaxies as they fall into the cluster. Most galaxies at the early stage of H i stripping are found in the first infall region of Virgo, while galaxies undergoing active H i stripping mostly appear to be falling in or moving out near the cluster core for the first time. Galaxies with severely stripped, yetmore » symmetric, H i disks are found in one of two locations. Some are deep inside the cluster, but others are found in the cluster outskirts with low orbital velocities. We suggest that the latter group of galaxies belong to a “backsplash” population. These present the clearest candidates for backsplashed galaxies observationally identified to date. We further investigate the distribution of a large sample of H i-detected galaxies toward Virgo in phase space, confirming that most galaxies are stripped of their gas as they settle into the gravitational potential of the cluster. In addition, we discuss the impact of tidal interactions between galaxies and group preprocessing on the H i properties of the cluster galaxies, and link the associated star formation evolution to the stripping sequence of cluster galaxies.« less

Structural evolution in the crystallization of rapid cooling silver melt

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

Tian, Z.A., E-mail: ze.tian@gmail.com; Laboratory for Simulation and Modelling of Particulate Systems School of Materials Science and Engineering, University of New South Wales, Sydney, NSW 2052; Dong, K.J.

2015-03-15

The structural evolution in a rapid cooling process of silver melt has been investigated at different scales by adopting several analysis methods. The results testify Ostwald’s rule of stages and Frank conjecture upon icosahedron with many specific details. In particular, the cluster-scale analysis by a recent developed method called LSCA (the Largest Standard Cluster Analysis) clarified the complex structural evolution occurred in crystallization: different kinds of local clusters (such as ico-like (ico is the abbreviation of icosahedron), ico-bcc like (bcc, body-centred cubic), bcc, bcc-like structures) in turn have their maximal numbers as temperature decreases. And in a rather wide temperaturemore » range the icosahedral short-range order (ISRO) demonstrates a saturated stage (where the amount of ico-like structures keeps stable) that breeds metastable bcc clusters. As the precursor of crystallization, after reaching the maximal number bcc clusters finally decrease, resulting in the final solid being a mixture mainly composed of fcc/hcp (face-centred cubic and hexagonal-closed packed) clusters and to a less degree, bcc clusters. This detailed geometric picture for crystallization of liquid metal is believed to be useful to improve the fundamental understanding of liquid–solid phase transition. - Highlights: • A comprehensive structural analysis is conducted focusing on crystallization. • The involved atoms in our analysis are more than 90% for all samples concerned. • A series of distinct intermediate states are found in crystallization of silver melt. • A novelty icosahedron-saturated state breeds the metastable bcc state.« less

Design and simulation study of the immunization Data Quality Audit (DQA).

PubMed

Woodard, Stacy; Archer, Linda; Zell, Elizabeth; Ronveaux, Olivier; Birmingham, Maureen

2007-08-01

The goal of the Data Quality Audit (DQA) is to assess whether the Global Alliance for Vaccines and Immunization-funded countries are adequately reporting the number of diphtheria-tetanus-pertussis immunizations given, on which the "shares" are awarded. Given that this sampling design is a modified two-stage cluster sample (modified because a stratified, rather than a simple, random sample of health facilities is obtained from the selected clusters); the formula for the calculation of the standard error for the estimate is unknown. An approximated standard error has been proposed, and the first goal of this simulation is to assess the accuracy of the standard error. Results from the simulations based on hypothetical populations were found not to be representative of the actual DQAs that were conducted. Additional simulations were then conducted on the actual DQA data to better access the precision of the DQ with both the original and the increased sample sizes.

CUDA programs for the GPU computing of the Swendsen-Wang multi-cluster spin flip algorithm: 2D and 3D Ising, Potts, and XY models

NASA Astrophysics Data System (ADS)

Komura, Yukihiro; Okabe, Yutaka

2014-03-01

We present sample CUDA programs for the GPU computing of the Swendsen-Wang multi-cluster spin flip algorithm. We deal with the classical spin models; the Ising model, the q-state Potts model, and the classical XY model. As for the lattice, both the 2D (square) lattice and the 3D (simple cubic) lattice are treated. We already reported the idea of the GPU implementation for 2D models (Komura and Okabe, 2012). We here explain the details of sample programs, and discuss the performance of the present GPU implementation for the 3D Ising and XY models. We also show the calculated results of the moment ratio for these models, and discuss phase transitions. Catalogue identifier: AERM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERM_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 5632 No. of bytes in distributed program, including test data, etc.: 14688 Distribution format: tar.gz Programming language: C, CUDA. Computer: System with an NVIDIA CUDA enabled GPU. Operating system: System with an NVIDIA CUDA enabled GPU. Classification: 23. External routines: NVIDIA CUDA Toolkit 3.0 or newer Nature of problem: Monte Carlo simulation of classical spin systems. Ising, q-state Potts model, and the classical XY model are treated for both two-dimensional and three-dimensional lattices. Solution method: GPU-based Swendsen-Wang multi-cluster spin flip Monte Carlo method. The CUDA implementation for the cluster-labeling is based on the work by Hawick et al. [1] and that by Kalentev et al. [2]. Restrictions: The system size is limited depending on the memory of a GPU. Running time: For the parameters used in the sample programs, it takes about a minute for each program. Of course, it depends on the system size, the number of Monte Carlo steps, etc. References: [1] K.A. Hawick, A. Leist, and D. P. Playne, Parallel Computing 36 (2010) 655-678 [2] O. Kalentev, A. Rai, S. Kemnitzb, and R. Schneider, J. Parallel Distrib. Comput. 71 (2011) 615-620

Dynamics, Chemical Abundances, and ages of Globular Clusters in the Virgo Cluster of Galaxies

NASA Astrophysics Data System (ADS)

Guhathakurta, Puragra; NGVS Collaboration

2018-01-01

We present a study of the dynamics, metallicities, and ages of globular clusters (GCs) in the Next Generation Virgo cluster Survey (NGVS), a deep, multi-band (u, g, r, i, z, and Ks), wide-field (104 deg2) imaging survey carried out using the 3.6-m Canada-France-Hawaii Telescope and MegaCam imager. GC candidates were selected from the NGVS survey using photometric and image morphology criteria and these were followed up with deep, medium-resolution, multi-object spectroscopy using the Keck II 10-m telescope and DEIMOS spectrograph. The primary spectroscopic targets were candidate GC satellites of dwarf elliptical (dE) and ultra-diffuse galaxies (UDGs) in the Virgo cluster. While many objects were confirmed as GC satellites of Virgo dEs and UDGs, many turned out to be non-satellites based on their radial velocity and/or positional mismatch any identifiable Virgo cluster galaxy. We have used a combination of spectral characteristics (e.g., presence of absorption vs. emission lines), new Gaussian mixture modeling of radial velocity and sky position data, and a new extreme deconvolution analysis of ugrizKs photometry and image morphology, to classify all the objects in our sample into: (1) GC satellites of dE galaxies, (2) GC satellites of UDGs, (3) intra-cluster GCs (ICGCs) in the Virgo cluster, (4) GCs in the outer halo of the central cluster galaxy M87, (5) foreground Milky Way stars, and (6) distant background galaxies. We use these data to study the dynamics and dark matter content of dE and UDGs in the Virgo cluster, place important constraints on the nature of dE nuclei, and study the origin of ICGCs versus GCs in the remote M87 halo.We are grateful for financial support from the NSF and NASA/STScI.

Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

PubMed Central

Xu, Rui; Zhen, Zonglei; Liu, Jia

2010-01-01

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081

Socio-Economic Background and Access to Internet as Correlates of Students' Achievement in Agricultural Science

ERIC Educational Resources Information Center

Adegoke, Sunday Paul; Osokoya, Modupe M.

2015-01-01

This study investigated access to internet and socio-economic background as correlates of students' achievement in Agricultural Science among selected Senior Secondary Schools Two Students in Ogbomoso South and North Local Government Areas. The study adopted multi-stage sampling technique. Simple random sampling was used to select 30 students from…

A sequential-move game for enhancing safety and security cooperation within chemical clusters.

PubMed

Pavlova, Yulia; Reniers, Genserik

2011-02-15

The present paper provides a game theoretic analysis of strategic cooperation on safety and security among chemical companies within a chemical industrial cluster. We suggest a two-stage sequential move game between adjacent chemical plants and the so-called Multi-Plant Council (MPC). The MPC is considered in the game as a leader player who makes the first move, and the individual chemical companies are the followers. The MPC's objective is to achieve full cooperation among players through establishing a subsidy system at minimum expense. The rest of the players rationally react to the subsidies proposed by the MPC and play Nash equilibrium. We show that such a case of conflict between safety and security, and social cooperation, belongs to the 'coordination with assurance' class of games, and we explore the role of cluster governance (fulfilled by the MPC) in achieving a full cooperative outcome in domino effects prevention negotiations. The paper proposes an algorithm that can be used by the MPC to develop the subsidy system. Furthermore, a stepwise plan to improve cross-company safety and security management in a chemical industrial cluster is suggested and an illustrative example is provided. Copyright © 2010 Elsevier B.V. All rights reserved.

Intraclass Correlations for Three-Level Multi-Site Cluster-Randomized Trials of Science Achievement

ERIC Educational Resources Information Center

Westine, Carl D.

2015-01-01

A cluster-randomized trial (CRT) relies on random assignment of intact clusters to treatment conditions, such as classrooms or schools (Raudenbush & Bryk, 2002). One specific type of CRT, a multi-site CRT (MSCRT), is commonly employed in educational research and evaluation studies (Spybrook & Raudenbush, 2009; Spybrook, 2014; Bloom,…

Multi-exemplar affinity propagation.

PubMed

Wang, Chang-Dong; Lai, Jian-Huang; Suen, Ching Y; Zhu, Jun-Yong

2013-09-01

The affinity propagation (AP) clustering algorithm has received much attention in the past few years. AP is appealing because it is efficient, insensitive to initialization, and it produces clusters at a lower error rate than other exemplar-based methods. However, its single-exemplar model becomes inadequate when applied to model multisubclasses in some situations such as scene analysis and character recognition. To remedy this deficiency, we have extended the single-exemplar model to a multi-exemplar one to create a new multi-exemplar affinity propagation (MEAP) algorithm. This new model automatically determines the number of exemplars in each cluster associated with a super exemplar to approximate the subclasses in the category. Solving the model is NP-hard and we tackle it with the max-sum belief propagation to produce neighborhood maximum clusters, with no need to specify beforehand the number of clusters, multi-exemplars, and superexemplars. Also, utilizing the sparsity in the data, we are able to reduce substantially the computational time and storage. Experimental studies have shown MEAP's significant improvements over other algorithms on unsupervised image categorization and the clustering of handwritten digits.

Research of seafloor topographic analyses for a staged mineral exploration

NASA Astrophysics Data System (ADS)

Ikeda, M.; Kadoshima, K.; Koizumi, Y.; Yamakawa, T.; Asakawa, E.; Sumi, T.; Kose, M.

2016-12-01

J-MARES (Research and Development Partnership for Next Generation Technology of Marine Resources Survey, JAPAN) has been designing a low-cost and high-efficiency exploration system for seafloor hydrothermal massive sulfide (SMS) deposits in "Cross-ministerial Strategic Innovation Promotion Program (SIP)" granted by the Cabinet Office, Government of Japan since 2014. We proposed the multi-stage approach, which is designed from the regional scaled to the detail scaled survey stages through semi-detail scaled, focusing a prospective area by seafloor topographic analyses. We applied this method to the area of more than 100km x 100km around Okinawa Trough, including some well-known mineralized deposits. In the regional scale survey, we assume survey areas are more than 100 km x 100km. Then the spatial resolution of topography data should be bigger than 100m. The 500 m resolution data which is interpolated into 250 m resolution was used for extracting depression and performing principal component analysis (PCA) by the wavelength obtained from frequency analysis. As the result, we have successfully extracted the areas having the topographic features quite similar to well-known mineralized deposits. In the semi-local survey stage, we use the topography data obtained by bathymetric survey using multi-narrow beam echo-sounder. The 30m-resolution data was used for extracting depression, relative-large mounds, hills, lineaments as fault, and also for performing frequency analysis. As the result, wavelength as principal component constituting in the target area was extracted by PCA of wavelength obtained from frequency analysis. Therefore, color image was composited by using the second principal component (PC2) to the forth principal component (PC4) in which the continuity of specific wavelength was observed, and consistent with extracted lineaments. In addition, well-known mineralized deposits were discriminated in the same clusters by using clustering from PC2 to PC4.We applied the results described above to a new area, and successfully extract the quite similar area in vicinity to one of the well-known mineralized deposits. So we are going to verify the extracted areas by using geophysical methods, such as vertical cable seismic and time-domain EM survey, developed in this SIP project.

Sustainability of evidence-based healthcare: research agenda, methodological advances, and infrastructure support.

PubMed

Proctor, Enola; Luke, Douglas; Calhoun, Annaliese; McMillen, Curtis; Brownson, Ross; McCrary, Stacey; Padek, Margaret

2015-06-11

Little is known about how well or under what conditions health innovations are sustained and their gains maintained once they are put into practice. Implementation science typically focuses on uptake by early adopters of one healthcare innovation at a time. The later-stage challenges of scaling up and sustaining evidence-supported interventions receive too little attention. This project identifies the challenges associated with sustainability research and generates recommendations for accelerating and strengthening this work. A multi-method, multi-stage approach, was used: (1) identifying and recruiting experts in sustainability as participants, (2) conducting research on sustainability using concept mapping, (3) action planning during an intensive working conference of sustainability experts to expand the concept mapping quantitative results, and (4) consolidating results into a set of recommendations for research, methodological advances, and infrastructure building to advance understanding of sustainability. Participants comprised researchers, funders, and leaders in health, mental health, and public health with shared interest in the sustainability of evidence-based health care. Prompted to identify important issues for sustainability research, participants generated 91 distinct statements, for which a concept mapping process produced 11 conceptually distinct clusters. During the conference, participants built upon the concept mapping clusters to generate recommendations for sustainability research. The recommendations fell into three domains: (1) pursue high priority research questions as a unified agenda on sustainability; (2) advance methods for sustainability research; (3) advance infrastructure to support sustainability research. Implementation science needs to pursue later-stage translation research questions required for population impact. Priorities include conceptual consistency and operational clarity for measuring sustainability, developing evidence about the value of sustaining interventions over time, identifying correlates of sustainability along with strategies for sustaining evidence-supported interventions, advancing the theoretical base and research designs for sustainability research, and advancing the workforce capacity, research culture, and funding mechanisms for this important work.

Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

USGS Publications Warehouse

Sethi, Suresh; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick R.; Fuller, Angela K.; Hare, Matthew P.

2016-01-01

Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

Inspection logistics planning for multi-stage production systems with applications to semiconductor fabrication lines

NASA Astrophysics Data System (ADS)

Chen, Kyle Dakai

Since the market for semiconductor products has become more lucrative and competitive, research into improving yields for semiconductor fabrication lines has lately received a tremendous amount of attention. One of the most critical tasks in achieving such yield improvements is to plan the in-line inspection sampling efficiently so that any potential yield problems can be detected early and eliminated quickly. We formulate a multi-stage inspection planning model based on configurations in actual semiconductor fabrication lines, specifically taking into account both the capacity constraint and the congestion effects at the inspection station. We propose a new mixed First-Come-First-Serve (FCFS) and Last-Come-First-Serve (LCFS) discipline for serving the inspection samples to expedite the detection of potential yield problems. Employing this mixed FCFS and LCFS discipline, we derive approximate expressions for the queueing delays in yield problem detection time and develop near-optimal algorithms to obtain the inspection logistics planning policies. We also investigate the queueing performance with this mixed type of service discipline under different assumptions and configurations. In addition, we conduct numerical tests and generate managerial insights based on input data from actual semiconductor fabrication lines. To the best of our knowledge, this research is novel in developing, for the first time in the literature, near-optimal results for inspection logistics planning in multi-stage production systems with congestion effects explicitly considered.

Stochastic Multi-Commodity Facility Location Based on a New Scenario Generation Technique

NASA Astrophysics Data System (ADS)

Mahootchi, M.; Fattahi, M.; Khakbazan, E.

2011-11-01

This paper extends two models for stochastic multi-commodity facility location problem. The problem is formulated as two-stage stochastic programming. As a main point of this study, a new algorithm is applied to efficiently generate scenarios for uncertain correlated customers' demands. This algorithm uses Latin Hypercube Sampling (LHS) and a scenario reduction approach. The relation between customer satisfaction level and cost are considered in model I. The risk measure using Conditional Value-at-Risk (CVaR) is embedded into the optimization model II. Here, the structure of the network contains three facility layers including plants, distribution centers, and retailers. The first stage decisions are the number, locations, and the capacity of distribution centers. In the second stage, the decisions are the amount of productions, the volume of transportation between plants and customers.

Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

PubMed Central

Liu, Wenfen

2017-01-01

Constrained spectral clustering (CSC) method can greatly improve the clustering accuracy with the incorporation of constraint information into spectral clustering and thus has been paid academic attention widely. In this paper, we propose a fast CSC algorithm via encoding landmark-based graph construction into a new CSC model and applying random sampling to decrease the data size after spectral embedding. Compared with the original model, the new algorithm has the similar results with the increase of its model size asymptotically; compared with the most efficient CSC algorithm known, the new algorithm runs faster and has a wider range of suitable data sets. Meanwhile, a scalable semisupervised cluster ensemble algorithm is also proposed via the combination of our fast CSC algorithm and dimensionality reduction with random projection in the process of spectral ensemble clustering. We demonstrate by presenting theoretical analysis and empirical results that the new cluster ensemble algorithm has advantages in terms of efficiency and effectiveness. Furthermore, the approximate preservation of random projection in clustering accuracy proved in the stage of consensus clustering is also suitable for the weighted k-means clustering and thus gives the theoretical guarantee to this special kind of k-means clustering where each point has its corresponding weight. PMID:29312447

[Cigarette consumer price and affordability in China: results from 2015 China adult survey].

PubMed

Wang, L L; Yang, Y; Nan, Y; Tu, M W; Wang, J J; Jiang, Y

2017-01-10

Objective: To analyze the change of cigarette consumption price, and understand the cigarette affordability in China. Methods: A total of 16 800 households were selected through multi-stage stratified cluster sampling. Then IPAQ was used to randomly select one family member to conduct the survey. Questionnaire from Global Tobacco Surveillance System with added country-specific questions was used. Results: Up to 50 % of current smokers would buy 20 cigarettes with price of 9.9 yuan (RMB) or less, and 25 % of current smokers would not buy 20 cigarettes with price exceed 5.5 yuan (RMB). Only 10 % would buy 20 cigarettes with price over 19.9 yuan (RMB). The calculated median monthly expenditure for cigarettes was 181.4 yuan (RMB). From 2010 to 2015, the proportion of annual expenditure for cigarettes in disposable income per capita declined from 10.5 % to 8.8 % in urban area and from 21.1 % to 17.3 % in rural area. Conclusion: During 2010-2015, the purchasing power of Chinese smokers increased in both urban area and rural area due to the decrease of cigarette consumption price.

[Influences of life event and coping style on left-behind middle school student mental health in a three-gorge area county].

PubMed

Wu, Rui; Li, Jianqiao; Liu, Qin; Wang, Hong

2014-07-01

To study the effects of life event and coping style on left-behind middle school student mental health. 1405 left-behind middle school students were selected by multi-stage cluster random sampling method and investigated with Middle School Student Mental Health Scale (MSSMHS), Multidimensional Life Events Rating Questionnaire for Middle School Students (MLERQ) and Trait Coping Style Questionnaire (TCSQ). The mental health detection rate of left-behind middle school students was 26.33%. Life event have significant influence on mental health (F = 447.624, P = 0.000). The main effect for negative coping style on mental health was significant (F = 263.669, P = 0.000). Positive coping style have effect on mental health but the main effect was not significant (F = 2.436, P = 0.119). The interaction effect of life event and negative coping style was significant (F = 23.173, P = 0.000). Life event and coping style has a certain effect on left-behind middle school student mental health, but its mechanism is complicated and still uncertain.

Analysis on leisure patterns of the pre-elderly adults.

PubMed

Cho, Gun-Sang; Yi, Eun-Surk

2013-01-01

The purpose of study is to analyze how leisure activities affect the near elders' preparation for successful and productive aging. To achieve the purpose of the study, this study was conducted in 2012 and the data was collected by using multi-stage stratified cluster random sampling method in the great city area (6 places), metropolitan area (7 places), medium-sized urban area (6 places), and rural area (6 places). Out of the total number of 1,000 copies of questionnaire distributed to pre-elders (Baby-boomers from 55 yr to 64 yr), 978 were collected and used for data analysis. According to the result, the more time, frequency and intensity in leisure and recreational participation, the higher the satisfaction level and the happiness level in their life. It means that leisure and recreational activities play an important role for their life. In other words, for pre-elders, leisure activities can be regarded as the important element for preparation of their old age. Therefore, the leisure and recreation for pre-elderly adults should not be recognized as a tool for improving the economic productivity but for reinforcing the recovery resilience.

Sexual violence as a risk factor for family planning-related outcomes among young Burundian women.

PubMed

Elouard, Yajna; Weiss, Carine; Martin-Hilber, Adriane; Merten, Sonja

2018-01-01

The study aimed to examine associations between experience of sexual violence and family planning-related outcomes. A multi-stage cluster survey was conducted among a representative sample of 744 young women aged 15-24 in eight provinces in Burundi. The prevalence of young women who reported having ever been physically forced to have sexual intercourse was 26.1%. Young women who had experienced sexual violence (ever) were 2.5 times more likely not to have used any modern contraceptives in the 12 months preceding the survey. They were also 2.3 times more likely to report that their last pregnancy was unplanned. Higher odds of not being able to negotiate contraceptive use with their partners were only reported by young women having experienced sexual violence in the 12 months prior to the survey when adjusted for confounders. Sexual violence was found to be significantly associated with contraceptive negotiation and use as well as unplanned pregnancy. Weak perceived ability to negotiate contraceptive use highlights gender inequalities leaving young women vulnerable to unprotected sex and thus unplanned pregnancies.

Metabolic syndrome: a common problem among office workers.

PubMed

Alavi, S S; Makarem, J; Mehrdad, R; Abbasi, M

2015-01-01

Metabolic syndrome (MSx) is associated with several health problems. Workers are an important part of any organization. To determine the prevalence of MSx and related variables among office workers. This cross-sectional study evaluated 1488 office workers in Qom province, Central Iran, by using a multi-stage cluster sampling. Diagnosis of MSx was based on blood HDL-cholesterol, triglyceride, and fasting blood sugar (FBS) levels and waist circumference, and blood pressure. The overall prevalence of MSx was 35.9% (95% CI 33.5% to 38.3%), higher in men (37.2%) than in women (20.6%), and increased with age. The most common laboratory findings of MSx were hypertriglyceridemia (45.9%) and low HDL-cholesterol level (45.5%). Office workers with MSx had a significantly (p<0.001) higher body mass index than those without MSx. Lack of regular leisure time physical activity (p=0.003), and low intake of fruits (p=0.02) were associated with MSx. The prevalence of MSx was very high among office workers. Workplace health improvement programs through identifying and preventing MSx are necessary for improvement of staff's health.

Quality of Life, Motor Ability, and Weight Status among School-aged Children of Tehran.

PubMed

Khodaverdi, F; Bahram, A; Jafarabadi, M Asghari

2012-01-01

This study aimed to investigate the relationship between health Related quality of life (HRQOL), motor ability and weight status in children. Two hundred forty children ages 9-11 yr who were selected via multi stage cluster sampling design from primary schools in the Shahre Qods at Tehran, Iran in 2007. HRQOL was assessed by the pediatric quality of life inventory (PedsQL). Motor abilities were determined by a Basic Motor Ability Test (BMAT). Body mass index was calculated to determine weight status. Psychosocial, physical, and total health related qualities of life (all P< 0.05) were significantly lowered for obese when compared to normal weight participants. In contrast, the mean scores for each HRQOL domain in motor ability category were not significant. No significant interaction was apparent when examining HRQOL scores, BMAT variables and weight status. Regardless of motor ability levels, reducing body weight among children is a potential avenue for promoting improved HRQOL. Over weight boys reported significantly worse school performance than over weight girls, suggesting the importance in considering such dimensions in programs aimed at further understanding obesity in children.

Clustering of longitudinal data by using an extended baseline: A new method for treatment efficacy clustering in longitudinal data.

PubMed

Schramm, Catherine; Vial, Céline; Bachoud-Lévi, Anne-Catherine; Katsahian, Sandrine

2018-01-01

Heterogeneity in treatment efficacy is a major concern in clinical trials. Clustering may help to identify the treatment responders and the non-responders. In the context of longitudinal cluster analyses, sample size and variability of the times of measurements are the main issues with the current methods. Here, we propose a new two-step method for the Clustering of Longitudinal data by using an Extended Baseline. The first step relies on a piecewise linear mixed model for repeated measurements with a treatment-time interaction. The second step clusters the random predictions and considers several parametric (model-based) and non-parametric (partitioning, ascendant hierarchical clustering) algorithms. A simulation study compares all options of the clustering of longitudinal data by using an extended baseline method with the latent-class mixed model. The clustering of longitudinal data by using an extended baseline method with the two model-based algorithms was the more robust model. The clustering of longitudinal data by using an extended baseline method with all the non-parametric algorithms failed when there were unequal variances of treatment effect between clusters or when the subgroups had unbalanced sample sizes. The latent-class mixed model failed when the between-patients slope variability is high. Two real data sets on neurodegenerative disease and on obesity illustrate the clustering of longitudinal data by using an extended baseline method and show how clustering may help to identify the marker(s) of the treatment response. The application of the clustering of longitudinal data by using an extended baseline method in exploratory analysis as the first stage before setting up stratified designs can provide a better estimation of treatment effect in future clinical trials.

Identification of a New Susceptibility Locus for Systemic Lupus Erythematosus on Chromosome 12 in Individuals of European Ancestry

PubMed Central

Demirci, F. Yesim; Wang, Xingbin; Kelly, Jennifer A.; Morris, David L.; Barmada, M. Michael; Feingold, Eleanor; Kao, Amy H.; Sivils, Kathy L.; Bernatsky, Sasha; Pineau, Christian; Clarke, Ann; Ramsey-Goldman, Rosalind; Vyse, Timothy J.; Gaffney, Patrick M.; Manzi, Susan; Kamboh, M. Ilyas

2016-01-01

Objective Genome-wide association studies (GWASs) in individuals of European ancestry identified a number of systemic lupus erythematosus (SLE) susceptibility loci using earlier versions of high-density genotyping platforms. Follow-up studies on suggestive GWAS regions using larger samples and more markers identified additional SLE loci in European-descent subjects. Here we report the results of a multi-stage study that we performed to identify novel SLE loci. Methods In Stage 1, we conducted a new GWAS of SLE in a North American case-control sample of European ancestry (n=1,166) genotyped on Affymetrix Genome-Wide Human SNP Array 6.0. In Stage 2, we further investigated top new suggestive GWAS hits by in silico evaluation and meta-analysis using an additional dataset of European-descent subjects (>2,500 individuals), followed by replication of top meta-analysis findings in another dataset of European-descent subjects (>10,000 individuals) in Stage 3. Results As expected, our GWAS revealed most significant associations at the major histocompatibility complex locus (6p21), which easily surpassed genome-wide significance threshold (P<5×10−8). Several other SLE signals/loci previously implicated in Caucasians and/or Asians were also supported in Stage 1 discovery sample and strongest signals were observed at 2q32/STAT4 (P=3.6×10−7) and at 8p23/BLK (P=8.1×10−6). Stage 2 meta-analyses identified a new genome-wide significant SLE locus at 12q12 (meta P=3.1×10−8), which was replicated in Stage 3. Conclusion Our multi-stage study identified and replicated a new SLE locus that warrants further follow-up in additional studies. Publicly available databases suggest that this new SLE signal falls within a functionally relevant genomic region and near biologically important genes. PMID:26316170

Active epilepsy prevalence, the treatment gap, and treatment gap risk profile in eastern China: A population-based study.

PubMed

Ding, Xiaoyan; Zheng, Yang; Guo, Yi; Shen, Chunhong; Wang, Shan; Chen, Feng; Yan, Shengqiang; Ding, Meiping

2018-01-01

We measured the prevalence of active epilepsy and investigated the treatment gap and treatment gap risk profile in eastern China. This was a cross-sectional population-based survey conducted in Zhejiang, China, from October 2013 to March 2014. A total 54,976 people were selected using multi-stage cluster sampling. A two-stage questionnaire-based process was used to identify patients with active epilepsy and to record their demographic, socioeconomic, and epilepsy-related features. Logistic regression analysis was used to analyze risk factors of the treatment gap in eastern China, as adjusted for age and sex. We interviewed 50,035 people; 118 had active epilepsy (2.4‰), among which the treatment gap was 58.5%. In multivariate analysis, failure to receive appropriate antiepileptic treatment was associated with higher seizure frequency of 12-23 times per year (adjusted odds ratio=6.874; 95% confidence interval [CI]=2.372-19.918), >24 times per year (adjusted odds ratio=19.623; 95% CI=4.999-77.024), and a lack of health insurance (adjusted odds ratio=7.284; 95% CI=1.321-40.154). Eastern China has relatively lower prevalence of active epilepsy and smaller treatment gap. Interventions aimed at reducing seizure frequency, improving the health insurance system should be investigated as potential targets to further bridge the treatment gap. Copyright © 2017 Elsevier Inc. All rights reserved.

Novel microfabrication stage allowing for one-photon and multi-photon light assisted molecular immobilization and for multi-photon microscope

NASA Astrophysics Data System (ADS)

Gonçalves, Odete; Snider, Scott; Zadoyan, Ruben; Nguyen, Quoc-Thang; Vorum, Henrik; Petersen, Steffen B.; Neves-Petersen, Maria Teresa

2017-02-01

Light Assisted Molecular Immobilization (LAMI) results in spatially oriented and localized covalent coupling of biomolecules onto thiol reactive surfaces. LAMI is possible due to the conserved spatial proximity between aromatic residues and disulfide bridges in proteins. When aromatic residues are excited with UV light (275-295nm), disulphide bridges are disrupted and the formed thiol groups covalently bind to surfaces. Immobilization hereby reported is achieved in a microfabrication stage coupled to a fs-laser, through one- or multi-photon excitation. The fundamental 840nm output is tripled to 280nm and focused onto the sample, leading to one-photon excitation and molecular immobilization. The sample rests on a xyz-stage with micrometer step resolution and is illuminated according to a pattern uploaded to the software controlling the stage and the shutter. Molecules are immobilized according to such pattern, with micrometer spatial resolution. Spatial masks inserted in the light path lead to light diffraction patterns used to immobilize biomolecules with submicrometer spatial resolution. Light diffraction patterns are imaged by an inbuilt microscope. Two-photon microscopy and imaging of the fluorescent microbeads is shown. Immobilization of proteins, e.g. C-reactive protein, and of an engineered molecular beacon has been successfully achieved. The beacon was coupled to a peptide containing a disulfide bridge neighboring a tryptophan residue, being this way possible to immobilize the beacon on a surface using one-photon LAMI. This technology is being implemented in the creation of point-of-care biosensors aiming at the detection of cancer and cardiovascular disease markers.

Optical and structural characterization of Ge clusters embedded in ZrO2

NASA Astrophysics Data System (ADS)

Agocs, E.; Zolnai, Z.; Rossall, A. K.; van den Berg, J. A.; Fodor, B.; Lehninger, D.; Khomenkova, L.; Ponomaryov, S.; Gudymenko, O.; Yukhymchuk, V.; Kalas, B.; Heitmann, J.; Petrik, P.

2017-11-01

The change of optical and structural properties of Ge nanoclusters in ZrO2 matrix have been investigated by spectroscopic ellipsometry versus annealing temperatures. Radio-frequency top-down magnetron sputtering approach was used to produce the samples of different types, i.e. single-layers of pure Ge, pure ZrO2 and Ge-rich-ZrO2 as well as multi-layers stacked of 40 periods of 5-nm-Ge-rich-ZrO2 layers alternated by 5-nm-ZrO2 ones. Germanium nanoclusters in ZrO2 host were formed by rapid-thermal annealing at 600-800 °C during 30 s in nitrogen atmosphere. Reference optical properties for pure ZrO2 and pure Ge have been extracted using single-layer samples. As-deposited multi-layer structures can be perfectly modeled using the effective medium theory. However, annealed multi-layers demonstrated a significant diffusion of elements that was confirmed by medium energy ion scattering measurements. This fact prevents fitting of such annealed structure either by homogeneous or by periodic multi-layer models.

Multi-wavelength HPLC fingerprints from complex substances: An exploratory chemometrics study of the Cassia seed example.

PubMed

Ni, Yongnian; Lai, Yanhua; Brandes, Sarina; Kokot, Serge

2009-08-11

Multi-wavelength fingerprints of Cassia seed, a traditional Chinese medicine (TCM), were collected by high-performance liquid chromatography (HPLC) at two wavelengths with the use of diode array detection. The two data sets of chromatograms were combined by the data fusion-based method. This data set of fingerprints was compared separately with the two data sets collected at each of the two wavelengths. It was demonstrated with the use of principal component analysis (PCA), that multi-wavelength fingerprints provided a much improved representation of the differences in the samples. Thereafter, the multi-wavelength fingerprint data set was submitted for classification to a suite of chemometrics methods viz. fuzzy clustering (FC), SIMCA and the rank ordering MCDM PROMETHEE and GAIA. Each method highlighted different properties of the data matrix according to the fingerprints from different types of Cassia seeds. In general, the PROMETHEE and GAIA MCDM methods provided the most comprehensive information for matching and discrimination of the fingerprints, and appeared to be best suited for quality assurance purposes for these and similar types of sample.

Ultra-deep GEMINI Near-infrared Observations of the Bulge Globular Cluster NGC 6624.

NASA Astrophysics Data System (ADS)

Saracino, S.; Dalessandro, E.; Ferraro, F. R.; Geisler, D.; Mauro, F.; Lanzoni, B.; Origlia, L.; Miocchi, P.; Cohen, R. E.; Villanova, S.; Moni Bidin, C.

2016-11-01

We used ultra-deep J and K s images secured with the near-infrared (NIR) GSAOI camera assisted by the multi-conjugate adaptive optics system GeMS at the GEMINI South Telescope in Chile, to obtain a (K s , J - K s ) color-magnitude diagram (CMD) for the bulge globular cluster NGC 6624. We obtained the deepest and most accurate NIR CMD from the ground for this cluster, by reaching K s ˜ 21.5, approximately 8 mag below the horizontal branch level. The entire extension of the Main Sequence (MS) is nicely sampled and at K s ˜ 20 we detected the so-called MS “knee” in a purely NIR CMD. By taking advantage of the exquisite quality of the data, we estimated the absolute age of NGC 6624 (t age = 12.0 ± 0.5 Gyr), which turns out to be in good agreement with previous studies in the literature. We also analyzed the luminosity and mass functions of MS stars down to M ˜ 0.45 M⊙, finding evidence of a significant increase of low-mass stars at increasing distances from the cluster center. This is a clear signature of mass segregation, confirming that NGC 6624 is in an advanced stage of dynamical evolution. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência, Tecnologia e Inovação (Brazil) and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina). Based on observations gathered with ESO-VISTA telescope (program ID 179.B-2002).

A formal concept analysis approach to consensus clustering of multi-experiment expression data

PubMed Central

2014-01-01

Background Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis and integration of multiple datasets are expected to yield more reliable and robust results since they are based on a larger number of samples and the effects of the individual study-specific biases are diminished. This is supported by recent studies suggesting that important biological signals are often preserved or enhanced by multiple experiments. An approach to combining data from different experiments is the aggregation of their clusterings into a consensus or representative clustering solution which increases the confidence in the common features of all the datasets and reveals the important differences among them. Results We propose a novel generic consensus clustering technique that applies Formal Concept Analysis (FCA) approach for the consolidation and analysis of clustering solutions derived from several microarray datasets. These datasets are initially divided into groups of related experiments with respect to a predefined criterion. Subsequently, a consensus clustering algorithm is applied to each group resulting in a clustering solution per group. These solutions are pooled together and further analysed by employing FCA which allows extracting valuable insights from the data and generating a gene partition over all the experiments. In order to validate the FCA-enhanced approach two consensus clustering algorithms are adapted to incorporate the FCA analysis. Their performance is evaluated on gene expression data from multi-experiment study examining the global cell-cycle control of fission yeast. The FCA results derived from both methods demonstrate that, although both algorithms optimize different clustering characteristics, FCA is able to overcome and diminish these differences and preserve some relevant biological signals. Conclusions The proposed FCA-enhanced consensus clustering technique is a general approach to the combination of clustering algorithms with FCA for deriving clustering solutions from multiple gene expression matrices. The experimental results presented herein demonstrate that it is a robust data integration technique able to produce good quality clustering solution that is representative for the whole set of expression matrices. PMID:24885407

No sign (yet) of intergalactic globular clusters in the Local Group

NASA Astrophysics Data System (ADS)

Mackey, A. D.; Beasley, M. A.; Leaman, R.

2016-07-01

We present Gemini Multi-Object Spectrograph (GMOS) imaging of 12 candidate intergalactic globular clusters (IGCs) in the Local Group, identified in a recent survey of the Sloan Digital Sky Survey (SDSS) footprint by di Tullio Zinn & Zinn. Our image quality is sufficiently high, at ˜0.4-0.7 arcsec, that we are able to unambiguously classify all 12 targets as distant galaxies. To reinforce this conclusion we use GMOS images of globular clusters in the M31 halo, taken under very similar conditions, to show that any genuine clusters in the putative IGC sample would be straightforward to distinguish. Based on the stated sensitivity of the di Tullio Zinn & Zinn search algorithm, we conclude that there cannot be a significant number of IGCs with MV ≤ -6 lying unseen in the SDSS area if their properties mirror those of globular clusters in the outskirts of M31 - even a population of 4 would have only a ≈1 per cent chance of non-detection.

Genome-wide expressions in autologous eutopic and ectopic endometrium of fertile women with endometriosis.

PubMed

Khan, Meraj A; Sengupta, Jayasree; Mittal, Suneeta; Ghosh, Debabrata

2012-09-24

In order to obtain a lead of the pathophysiology of endometriosis, genome-wide expressional analyses of eutopic and ectopic endometrium have earlier been reported, however, the effects of stages of severity and phases of menstrual cycle on expressional profiles have not been examined. The effect of genetic heterogeneity and fertility history on transcriptional activity was also not considered. In the present study, a genome-wide expression analysis of autologous, paired eutopic and ectopic endometrial samples obtained from fertile women (n=18) suffering from moderate (stage 3; n=8) or severe (stage 4; n=10) ovarian endometriosis during proliferative (n=13) and secretory (n=5) phases of menstrual cycle was performed. Individual pure RNA samples were subjected to Agilent's Whole Human Genome 44K microarray experiments. Microarray data were validated (P<0.01) by estimating transcript copy numbers by performing real time RT-PCR of seven (7) arbitrarily selected genes in all samples. The data obtained were subjected to differential expression (DE) and differential co-expression (DC) analyses followed by networks and enrichment analysis, and gene set enrichment analysis (GSEA). The reproducibility of prediction based on GSEA implementation of DC results was assessed by examining the relative expressions of twenty eight (28) selected genes in RNA samples obtained from fresh pool of eutopic and ectopic samples from confirmed ovarian endometriosis patients with stages 3 and 4 (n=4/each) during proliferative and secretory (n=4/each) phases. Higher clustering effect of pairing (cluster distance, cd=0.1) in samples from same individuals on expressional arrays among eutopic and ectopic samples was observed as compared to that of clinical stages of severity (cd=0.5) and phases of menstrual cycle (cd=0.6). Post hoc analysis revealed anomaly in the expressional profiles of several genes associated with immunological, neuracrine and endocrine functions and gynecological cancers however with no overt oncogenic potential in endometriotic tissue. Dys-regulation of three (CLOCK, ESR1, and MYC) major transcription factors appeared to be significant causative factors in the pathogenesis of ovarian endometriosis. A novel cohort of twenty-eight (28) genes representing potential marker for ovarian endometriosis in fertile women was discovered. Dysfunctional expression of immuno-neuro-endocrine behaviour in endometrium appeared critical to endometriosis. Although no overt oncogenic potential was evident, several genes associated with gynecological cancers were observed to be high in the expressional profiles in endometriotic tissue.

Family clustering of secondary chronic kidney disease with hypertension or diabetes mellitus. A case-control study.

PubMed

de Almeida, Fernando Antonio; Ciambelli, Giuliano Serafino; Bertoco, André Luz; Jurado, Marcelo Mai; Siqueira, Guilherme Vasconcelos; Bernardo, Eder Augusto; Pavan, Maria Valeria; Gianini, Reinaldo José

2015-02-01

In Brazil hypertension and type 2 diabetes mellitus are responsible for 60% of cases of end-stage renal disease in renal replacement therapy. In the United States studies have identified family clustering of chronic kidney disease, predominantly in African-Americans. A single Brazilian study observed family clustering among patients with chronic kidney disease when compared with hospitalized patients with normal renal function. This article aims to assess whether there is family clustering of chronic kidney disease in relatives of individuals in renal replacement therapy caused by hypertension and/or diabetes mellitus. A case-control study with 336 patients in renal replacement therapy with diabetes mellitus or hypertension for at least 5 years (cases) and a control matched sample group of individuals with hypertension or diabetes mellitus and normal renal function (n = 389). Individuals in renal replacement therapy (cases) had a ratio of 2.35 (95% CI 1.42-3.89, p < 0.001) versus the control group in having relatives with chronic renal disease, irrespective of race or causative illness. There is family clustering of chronic kidney disease in the sample studied, and this predisposition is irrespective of race and underlying disease (hypertension or diabetes mellitus).

The improvement and simulation for LEACH clustering routing protocol

NASA Astrophysics Data System (ADS)

Ji, Ai-guo; Zhao, Jun-xiang

2017-01-01

An energy-balanced unequal multi-hop clustering routing protocol LEACH-EUMC is proposed in this paper. The candidate cluster head nodes are elected firstly, then they compete to be formal cluster head nodes by adding energy and distance factors, finally the date are transferred to sink through multi-hop. The results of simulation show that the improved algorithm is better than LEACH in network lifetime, energy consumption and the amount of data transmission.

Self-similarity of temperature profiles in distant galaxy clusters: the quest for a universal law

NASA Astrophysics Data System (ADS)

Baldi, A.; Ettori, S.; Molendi, S.; Gastaldello, F.

2012-09-01

Context. We present the XMM-Newton temperature profiles of 12 bright (LX > 4 × 1044 erg s-1) clusters of galaxies at 0.4 < z < 0.9, having an average temperature in the range 5 ≲ kT ≲ 11 keV. Aims: The main goal of this paper is to study for the first time the temperature profiles of a sample of high-redshift clusters, to investigate their properties, and to define a universal law to describe the temperature radial profiles in galaxy clusters as a function of both cosmic time and their state of relaxation. Methods: We performed a spatially resolved spectral analysis, using Cash statistics, to measure the temperature in the intracluster medium at different radii. Results: We extracted temperature profiles for the clusters in our sample, finding that all profiles are declining toward larger radii. The normalized temperature profiles (normalized by the mean temperature T500) are found to be generally self-similar. The sample was subdivided into five cool-core (CC) and seven non cool-core (NCC) clusters by introducing a pseudo-entropy ratio σ = (TIN/TOUT) × (EMIN/EMOUT)-1/3 and defining the objects with σ < 0.6 as CC clusters and those with σ ≥ 0.6 as NCC clusters. The profiles of CC and NCC clusters differ mainly in the central regions, with the latter exhibiting a slightly flatter central profile. A significant dependence of the temperature profiles on the pseudo-entropy ratio σ is detected by fitting a function of r and σ, showing an indication that the outer part of the profiles becomes steeper for higher values of σ (i.e. transitioning toward the NCC clusters). No significant evidence of redshift evolution could be found within the redshift range sampled by our clusters (0.4 < z < 0.9). A comparison of our high-z sample with intermediate clusters at 0.1 < z < 0.3 showed how the CC and NCC cluster temperature profiles have experienced some sort of evolution. This can happen because higher z clusters are at a less advanced stage of their formation and did not have enough time to create a relaxed structure, which is characterized by a central temperature dip in CC clusters and by flatter profiles in NCC clusters. Conclusions: This is the first time that a systematic study of the temperature profiles of galaxy clusters at z > 0.4 has been attempted. We were able to define the closest possible relation to a universal law for the temperature profiles of galaxy clusters at 0.1 < z < 0.9, showing a dependence on both the relaxation state of the clusters and the redshift. Appendix A is only available in electronic form at http://www.aanda.org

A Database of Young Star Clusters for Five Hundred Galaxies

NASA Astrophysics Data System (ADS)

Evans, Jessica; Whitmore, B. C.; Lindsay, K.; Chandar, R.; Larsen, S.

2009-01-01

The study of young massive stellar clusters has faced a series of observational challenges, such as the use of inconsistent data sets and low number statistics. To rectify these shortcomings, this project will use the source lists developed as part of the Hubble Legacy Archive to obtain a large, uniform database of super star clusters in nearby star-forming galaxies in order to address two fundamental astronomical questions: 1) To what degree is the cluster luminosity (and mass) function of star clusters universal? 2) What fraction of super star clusters are "missing" in optical studies (i.e., are hidden by dust)? The archive's recent data release (Data Release 2 - September, 2008) will help us achieve the large sample necessary (N 50 galaxies for multi-wavelength, N 500 galaxies for ACS F814W). The uniform data set will comprise of ACS, WFPC2, and NICMOS data, with DAOphot used for object detection. This database will also support comparisons with new Monte-Carlo simulations that have independently been developed in the past few years, and will be used to test the Whitmore, Chandar, Fall (2007) framework designed to understand the demographics of star clusters in all star forming galaxies. The catalogs will increase the number of galaxies with measured mass and luminosity functions by an order of magnitude, and will provide a powerful new tool for comparative studies, both ours and the community's. The poster will describe our preliminary investigation for the first 30 galaxies in the sample.

A multi purpose source chamber at the PLEIADES beamline at SOLEIL for spectroscopic studies of isolated species: cold molecules, clusters, and nanoparticles.

PubMed

Lindblad, Andreas; Söderström, Johan; Nicolas, Christophe; Robert, Emmanuel; Miron, Catalin

2013-11-01

This paper describes the philosophy and design goals regarding the construction of a versatile sample environment: a source capable of producing beams of atoms, molecules, clusters, and nanoparticles in view of studying their interaction with short wavelength (vacuum ultraviolet and x-ray) synchrotron radiation. In the design, specific care has been taken of (a) the use standard components, (b) ensuring modularity, i.e., that swiftly switching between different experimental configurations was possible. To demonstrate the efficiency of the design, proof-of-principle experiments have been conducted by recording x-ray absorption and photoelectron spectra from isolated nanoparticles (SiO2) and free mixed clusters (Ar/Xe). The results from those experiments are showcased and briefly discussed.

The method of parallel-hierarchical transformation for rapid recognition of dynamic images using GPGPU technology

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Yarovyi, Andrii; Kokriatskaya, Nataliya; Nakonechna, Svitlana; Abramenko, Ludmila; Ławicki, Tomasz; Popiel, Piotr; Yesmakhanova, Laura

2016-09-01

The paper presents a method of parallel-hierarchical transformations for rapid recognition of dynamic images using GPU technology. Direct parallel-hierarchical transformations based on cluster CPU-and GPU-oriented hardware platform. Mathematic models of training of the parallel hierarchical (PH) network for the transformation are developed, as well as a training method of the PH network for recognition of dynamic images. This research is most topical for problems on organizing high-performance computations of super large arrays of information designed to implement multi-stage sensing and processing as well as compaction and recognition of data in the informational structures and computer devices. This method has such advantages as high performance through the use of recent advances in parallelization, possibility to work with images of ultra dimension, ease of scaling in case of changing the number of nodes in the cluster, auto scan of local network to detect compute nodes.

Duration of Sleep and ADHD Tendency among Adolescents in China

ERIC Educational Resources Information Center

Lam, Lawrence T.; Yang, L.

2008-01-01

Objective: This study investigates the association between duration of sleep and ADHD tendency among adolescents. Method: This population-based health survey uses a two-stage random cluster sampling design. Participants ages 13 to 17 are recruited from the total population of adolescents attending high school in one city of China. Duration of…

Factors Influencing Entrepreneurial Intentions of Chinese Secondary School Students: An Empirical Study

ERIC Educational Resources Information Center

Xu, Xiaozhou; Ni, Hao; Ye, Yinghua

2016-01-01

The ideal stage to learn about and foster positive attitudes toward entrepreneurship is believed to be during childhood and adolescence. However, most entrepreneurial studies examine college rather than secondary school students (SSS). Based on a modified theory of planned behavior (TPB), this study used stratified cluster sampling and a…

Adaptive functioning and its associated factors among girl children residing in slum areas of Bhubaneswar, India.

PubMed

Panigrahi, Ansuman; Das, Sai C; Sahoo, Prabhudarsan

2018-01-01

Adaptive functioning develops throughout early childhood, and its limitation is a reflection that the child has developmental or emotional problems or even mental retardation. Little is known about the adaptive functioning or developmental status of slum children. The present cross-sectional study was undertaken during the year 2014 to assess the status of adaptive functioning among girl children aged between 3 and 9 years residing in slum areas of Bhubaneswar and to explore the factors associated with poor adaptive functioning. Stratified multi-stage cluster random sampling technique was used to select the study population; 256 mother-child pairs from 256 households in selected slum areas were studied. Demographic information was collected, and adaptive functioning was assessed using the modified Vineland Social Maturity Scale. Univariate and multivariate analyses was carried out using Statistical Package for Social Sciences (SPSS) version 21. One-fifth (54, 21%) of the girls sampled had poor adaptive functioning, and 44 (17%) had poor cognitive functioning. Multivariate analysis revealed that the age of the child, parents' education, presence of stunting in children and attending school/early childhood centre were strong predictors of adaptive functioning in slum children. One-fifth of girls from slums are developmentally vulnerable; parental education, stunting and early childhood education or exposure to schooling are modifiable factors influencing children's adaptive functioning. Health, education and welfare sectors need to be aware of this so that a multi-pronged approach can be planned to properly address this issue in one of the most disadvantaged sections of the society. © 2017 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Determinants of neonatal mortality in rural and urban Nigeria: Evidence from a population-based national survey.

PubMed

Adewuyi, Emmanuel O; Zhao, Yun

2017-02-01

Significant reduction in the global burden of neonatal mortality was achieved through the millennium development goals. In Nigeria, however, only a marginal reduction was realized. This study assesses the rural-urban differences in neonatal mortality rate (NMR) and the associated risk factors in Nigeria. The dataset from the 2013 Nigeria demographic and health survey (NDHS), disaggregated by rural-urban residence (n = 20 449 and 9935, respectively), was explored using univariate, bivariate, and multivariable analysis. Complex samples analysis was applied to adjust for the unequal selection probabilities due to the multi-stage cluster sampling method used in the 2013 NDHS. The adjusted relationship between the outcome and predictor variables was assessed on multi-level logistic regression analysis. NMR for rural and urban populations was 36 and 28 deaths per 1000 live births, respectively. Risk factors in urban residence were lack of electricity access (adjusted OR [AOR], 1.555; 95%CI: 1.089-2.220), small birth size (as a proxy for low birthweight; AOR, 3.048; 95%CI: 2.047-4.537), and male gender (AOR, 1.666; 95%CI: 1.215-2.284). Risk factors in rural residence were small birth size (a proxy for low birthweight; AOR, 2.118; 95%CI: 1.600-2.804), and birth interval <2 years (AOR, 2.149; 95%CI: 1.760-2.624). Cesarean delivery was a risk factor both in rural (AOR, 5.038; 95%CI: 2.617-9.700) and urban Nigeria (AOR, 2.632; 95%CI: 1.543-4.489). Determinants of neonatal mortality were different in rural and urban Nigeria, and rural neonates had greater risk of mortality than their urban counterparts. © 2016 Japan Pediatric Society.

A researcher's review of adherence to forensic examination principles in homicide cases in Poland.

PubMed

Juszka, K; Juszka, K

The purpose of this paper is to verify adherence to forensic examination principles in homicide cases by analyzing the results of the author's own study of 90 court and prosecution cases from the period 2000-2010. The analyzed cases were sampled using the so-called multi-stage cluster sampling method, commonly used in social sciences in Poland. The cases were held in 17 organizational judiciary and prosecution units reporting to the Court of Appeal in Krakow and Appellate Prosecutor's Office in Krakow, respectively. The research tool was a questionnaire containing 40 relevant guidelines, covering both qualitative and quantitative features. In the 90 analyzed cases, a total of 251 forensic examination reports were prepared, including 110 site examination reports, 20 separate corpse examination reports, 29 personal examination reports and 92 object examination reports. The research aspects of forensic examinations will be analyzed from the perspective of adherence to the principles of conducting the same. As regards postulates de lege ferenda with respect to the implementation of forensic examination principles one should emphasize the need for using the appropriate form of description of corpse examination; the need for a more responsible attitude towards sealing off crime scenes and for recording information on sealing-off procedures in the examination report; the need for clear distinction of examination stages in drafting the examination report; the need for a detailed analysis of the examination carried out at its final stage at all times; the need for using professional vocabulary in all descriptions of examination activities in each case and the need for regular monitoring (by the person in charge of examination) also with regard to the tactical requirement to sign each sheet of the examination report. The tactical and procedural development of forensic examination principles, taking into account also the postulates de lege ferenda presented herein, will contribute to further development of forensic examination studies and will thus make examination a more common practice in criminal procedures.

River Induced Wellbore Flow Dynamics in Long-Screen Wells and their Impact on Aqueous Sampling Results

NASA Astrophysics Data System (ADS)

Vermeul, V.; McKinley, J. P.; Newcomer, D.; Fritz, B. G.; Mackley, R.; Zachara, J. M.

2010-12-01

Previously published field investigations and modeling studies have demonstrated the potential for sample bias associated with vertical wellbore flow in conventional monitoring wells constructed with long-screened intervals. In this study, simultaneous measurement of 1) wellbore flow using an electromagnetic borehole flowmeter (EBF), 2) depth discrete hydraulic head, and 3) aqueous uranium concentrations were used to quantify wellbore flow and assess the associated impacts on measured aqueous concentrations. Monitoring results demonstrate the utility of continuous (i.e., hourly measurements for ~ one month) ambient wellbore flow monitoring and show that relatively large wellbore flows (up to 4 LPM) can be induced by aquifer hydrodynamics associated with a fluctuating river boundary located approximately 250 m from the test well. The observed vertical wellbore flows were strongly correlated with fluctuations in river stage, alternating between upward and downward flow throughout the monitoring period in response to changes in river stage. Continuous monitoring of ambient wellbore flows using an EBF system allowed these effects to be evaluated in concert with continuously monitored river stage elevations (hourly) and aqueous uranium concentrations (daily) in a long-screen well and an adjacent multi-level well cluster. This study demonstrates that when contaminant concentrations within the aquifer vary significantly over the depth interval interrogated, river-induced vertical wellbore flow can result in variations in measured concentration that nearly encompass the full range of variation in aquifer contaminant concentration with depth. In addition, observed variability in aqueous concentrations measured during active tracer transport experiments provided additional evidence of wellbore flow impacts and showed that the magnitude and direction of wellbore flow varied spatially across the wellfield. An approach to mitigate these effects based on increasing hydraulic resistance within the wellbore was evaluated. This research is part of the ERSP Hanford IFRC at Pacific Northwest National Laboratory.

RCSLenS: The Red Cluster Sequence Lensing Survey

NASA Astrophysics Data System (ADS)

Hildebrandt, H.; Choi, A.; Heymans, C.; Blake, C.; Erben, T.; Miller, L.; Nakajima, R.; van Waerbeke, L.; Viola, M.; Buddendiek, A.; Harnois-Déraps, J.; Hojjati, A.; Joachimi, B.; Joudaki, S.; Kitching, T. D.; Wolf, C.; Gwyn, S.; Johnson, N.; Kuijken, K.; Sheikhbahaee, Z.; Tudorica, A.; Yee, H. K. C.

2016-11-01

We present the Red Cluster Sequence Lensing Survey (RCSLenS), an application of the methods developed for the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS) to the ˜785 deg2, multi-band imaging data of the Red-sequence Cluster Survey 2. This project represents the largest public, sub-arcsecond seeing, multi-band survey to date that is suited for weak gravitational lensing measurements. With a careful assessment of systematic errors in shape measurements and photometric redshifts, we extend the use of this data set to allow cross-correlation analyses between weak lensing observables and other data sets. We describe the imaging data, the data reduction, masking, multi-colour photometry, photometric redshifts, shape measurements, tests for systematic errors, and a blinding scheme to allow for more objective measurements. In total, we analyse 761 pointings with r-band coverage, which constitutes our lensing sample. Residual large-scale B-mode systematics prevent the use of this shear catalogue for cosmic shear science. The effective number density of lensing sources over an unmasked area of 571.7 deg2 and down to a magnitude limit of r ˜ 24.5 is 8.1 galaxies per arcmin2 (weighted: 5.5 arcmin-2) distributed over 14 patches on the sky. Photometric redshifts based on four-band griz data are available for 513 pointings covering an unmasked area of 383.5 deg2. We present weak lensing mass reconstructions of some example clusters as well as the full survey representing the largest areas that have been mapped in this way. All our data products are publicly available through Canadian Astronomy Data Centre at http://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/en/community/rcslens/query.html in a format very similar to the CFHTLenS data release.

Time-Resolved Surveys of Stellar Clusters

NASA Astrophysics Data System (ADS)

Eyer, Laurent; Eggenberger, Patrick; Greco, Claudia; Saesen, Sophie; Anderson, Richard I.; Mowlavi, Nami

We describe the information that can be gained when a survey is done multi-epoch, and its particular impact in open cluster research. We first explain the irreplaceable information that multi-epoch observations are giving within astrometry, photometry and spectroscopy. Then we give three examples of results on open clusters from multi-epoch surveys, namely, the distance to the Pleiades, the angular momentum evolution of low mass stars and asteroseismology. Finally we mention several very large surveys, which are ongoing or planned for the future, Gaia, JASMINE, LSST, and VVV.

Relationship Level of Individual Value Perceptions and Competence Beliefs of Classroom Teachers

ERIC Educational Resources Information Center

Kop, Yasar; Tasdan, Murat; Alibeyoglu, Aytekin

2017-01-01

The main aim of this study is to reveal classroom teachers' personal value perceptions and the level of their efficiencies. The quantitative research method was used in the research. The target population of the research consisted of 335 classroom teachers in Kars. Multi stage sampling model was selected in order to determine the sampling in the…

Teachers' Methodologies and Sources of Information on HIV/AIDS for Students with Visual Impairments in Selected Residential and Integrated Schools in Ghana

ERIC Educational Resources Information Center

Hayford, Samuel K.; Ocansey, Frederick

2017-01-01

This study reports part of a national survey on sources of information, education and communication materials on HIV/AIDS available to students with visual impairments in residential, segregated, and integrated schools in Ghana. A multi-staged stratified random sampling procedure and a purposive and simple random sampling approach, where…

A 6-gene signature identifies four molecular subgroups of neuroblastoma

PubMed Central

2011-01-01

Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p < 0.05, Fisher's exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics. PMID:21492432

Relaxation channels of multi-photon excited xenon clusters

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

Serdobintsev, P. Yu.; Melnikov, A. S.; Department of Physics, St. Petersburg State University, Saint Petersburg 198904

2015-09-21

The relaxation processes of the xenon clusters subjected to multi-photon excitation by laser radiation with quantum energies significantly lower than the thresholds of excitation of atoms and ionization of clusters were studied. Results obtained by means of the photoelectron spectroscopy method showed that desorption processes of excited atoms play a significant role in the decay of two-photon excited xenon clusters. A number of excited states of xenon atoms formed during this process were discovered and identified.

Using Open Clusters to Trace the Local Milky Way Rotation Curve and Velocity Field

NASA Astrophysics Data System (ADS)

Frinchaboy, Peter M.; Majewski, S. R.

2006-12-01

Establishing the rotation curve of the Milky Way is one of the fundamental contributions needed to understand the Galaxy and its mass distribution. We have undertaken a systematic spectroscopic survey of open star clusters which can serve as tracers of Galactic disk dynamics. We report on our initial sample of 67 clusters for which the Hydra multi-fiber spectrographs on the WIYN and Blanco telescopes have delivered 1-2 km/s radial velocities (RVs) of many dozens of stars in the fields of each cluster, which are used to derive cluster membership and bulk cluster kinematics when combined with Tycho-2 proper motions. The clusters selected for study have a broad spatial distribution in order to be sensitive to the disk velocity field in all Galactic quadrants and across a Galactocentric radius range as much as 3.0 kpc from the solar circle. Through analysis of the cluster sample, we find (1) the rotation velocity of the LSR is 221 (+2,-4) km/s, (2) the local rotation curve is declining with radius having a slope of -9.0 km/s/kpc, (3) we find (using R_0 = 8.5 kpc) the following Galactic parameters: A = 17.0 km/s/kpc and B = -8.9 km/s/kpc, which yields a Galaxy mass within of 1.5 R_0 of M = 0.9 ± 0.2 x 10^11 solar masses and a M/L of 5.9 in solar units. We also explore the distribution of the local velocity field and find evidence for non-circular motion due to the sprial arms.

Effects of rare earth doping on multi-core iron oxide nanoparticles properties

NASA Astrophysics Data System (ADS)

Petran, Anca; Radu, Teodora; Borodi, Gheorghe; Nan, Alexandrina; Suciu, Maria; Turcu, Rodica

2018-01-01

New multi-core iron oxide magnetic nanoparticles doped with rare earth metals (Gd, Eu) were obtained by a one step synthesis procedure using a solvothermal method for potential biomedical applications. The obtained clusters were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), energy-dispersive X-ray microanalysis (EDX), X-ray photoelectron spectroscopy (XPS) and magnetization measurements. They possess high colloidal stability, a saturation magnetization of up to 52 emu/g, and nearly spherical shape. The presence of rare earth ions in the obtained samples was confirmed by EDX and XPS. XRD analysis proved the homogeneous distribution of the trivalent rare earth ions in the inverse-spinel structure of magnetite and the increase of crystal strain upon doping the samples. XPS study reveals the valence state and the cation distribution on the octahedral and tetrahedral sites of the analysed samples. The observed shift of the XPS valence band spectra maximum in the direction of higher binding energies after rare earth doping, as well as theoretical valence band calculations prove the presence of Gd and Eu ions in octahedral sites. The blood protein adsorption ability of the obtained samples surface, the most important factor of the interaction between biomaterials and body fluids, was assessed by interaction with bovine serum albumin (BSA). The rare earth doped clusters surface show higher afinity for binding BSA. In vitro cytotoxicity test results for the studied samples showed no cytotoxicity in low and medium doses, establishing a potential perspective for rare earth doped MNC to facilitate multiple therapies in a single formulation for cancer theranostics.

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

NASA Technical Reports Server (NTRS)

Tomberlin, T. J.

1985-01-01

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Monitoring Powdery Mildew of Winter Wheat by Using Moderate Resolution Multi-Temporal Satellite Imagery

PubMed Central

Zhang, Jingcheng; Pu, Ruiliang; Yuan, Lin; Wang, Jihua; Huang, Wenjiang; Yang, Guijun

2014-01-01

Powdery mildew is one of the most serious diseases that have a significant impact on the production of winter wheat. As an effective alternative to traditional sampling methods, remote sensing can be a useful tool in disease detection. This study attempted to use multi-temporal moderate resolution satellite-based data of surface reflectances in blue (B), green (G), red (R) and near infrared (NIR) bands from HJ-CCD (CCD sensor on Huanjing satellite) to monitor disease at a regional scale. In a suburban area in Beijing, China, an extensive field campaign for disease intensity survey was conducted at key growth stages of winter wheat in 2010. Meanwhile, corresponding time series of HJ-CCD images were acquired over the study area. In this study, a number of single-stage and multi-stage spectral features, which were sensitive to powdery mildew, were selected by using an independent t-test. With the selected spectral features, four advanced methods: mahalanobis distance, maximum likelihood classifier, partial least square regression and mixture tuned matched filtering were tested and evaluated for their performances in disease mapping. The experimental results showed that all four algorithms could generate disease maps with a generally correct distribution pattern of powdery mildew at the grain filling stage (Zadoks 72). However, by comparing these disease maps with ground survey data (validation samples), all of the four algorithms also produced a variable degree of error in estimating the disease occurrence and severity. Further, we found that the integration of MTMF and PLSR algorithms could result in a significant accuracy improvement of identifying and determining the disease intensity (overall accuracy of 72% increased to 78% and kappa coefficient of 0.49 increased to 0.59). The experimental results also demonstrated that the multi-temporal satellite images have a great potential in crop diseases mapping at a regional scale. PMID:24691435

Monitoring powdery mildew of winter wheat by using moderate resolution multi-temporal satellite imagery.

PubMed

Zhang, Jingcheng; Pu, Ruiliang; Yuan, Lin; Wang, Jihua; Huang, Wenjiang; Yang, Guijun

2014-01-01

Powdery mildew is one of the most serious diseases that have a significant impact on the production of winter wheat. As an effective alternative to traditional sampling methods, remote sensing can be a useful tool in disease detection. This study attempted to use multi-temporal moderate resolution satellite-based data of surface reflectances in blue (B), green (G), red (R) and near infrared (NIR) bands from HJ-CCD (CCD sensor on Huanjing satellite) to monitor disease at a regional scale. In a suburban area in Beijing, China, an extensive field campaign for disease intensity survey was conducted at key growth stages of winter wheat in 2010. Meanwhile, corresponding time series of HJ-CCD images were acquired over the study area. In this study, a number of single-stage and multi-stage spectral features, which were sensitive to powdery mildew, were selected by using an independent t-test. With the selected spectral features, four advanced methods: mahalanobis distance, maximum likelihood classifier, partial least square regression and mixture tuned matched filtering were tested and evaluated for their performances in disease mapping. The experimental results showed that all four algorithms could generate disease maps with a generally correct distribution pattern of powdery mildew at the grain filling stage (Zadoks 72). However, by comparing these disease maps with ground survey data (validation samples), all of the four algorithms also produced a variable degree of error in estimating the disease occurrence and severity. Further, we found that the integration of MTMF and PLSR algorithms could result in a significant accuracy improvement of identifying and determining the disease intensity (overall accuracy of 72% increased to 78% and kappa coefficient of 0.49 increased to 0.59). The experimental results also demonstrated that the multi-temporal satellite images have a great potential in crop diseases mapping at a regional scale.

Big Bangs in Galaxy Clusters: Using X-ray Temperature Maps to Trace Merger Histories in Clusters with Radio Halos/Relics

NASA Astrophysics Data System (ADS)

Burns, Jack O.; Datta, Abhirup; Hallman, Eric J.

2016-06-01

Galaxy clusters are assembled through large and small mergers which are the most energetic events ("bangs") since the Big Bang. Cluster mergers "stir" the intracluster medium (ICM) creating shocks and turbulence which are illuminated by ~Mpc-sized radio features called relics and halos. These shocks heat the ICM and are detected in x-rays via thermal emission. Disturbed morphologies in x-ray surface brightness and temperatures are direct evidence for cluster mergers. In the radio, relics (in the outskirts of the clusters) and halos (located near the cluster core) are also clear signposts of recent mergers. Our recent ENZO cosmological simulations suggest that around a merger event, radio emission peaks very sharply (and briefly) while the x-ray emission rises and decays slowly. Hence, a sample of galaxy clusters that shows both luminous x-ray emission and radio relics/halos are good candidates for very recent mergers. We are in the early stages of analyzing a unique sample of 48 galaxy clusters with (i) known radio relics and/or halos and (ii) significant archival x-ray observations (>50 ksec) from Chandra and/or XMM. We have developed a new x-ray data analysis pipeline, implemented on parallel processor supercomputers, to create x-ray surface brightness, high fidelity temperature, and pressure maps of these clusters in order to study merging activity. The temperature maps are made using three different map-making techniques: Weighted Voronoi Tessellation, Adaptive Circular Binning, and Contour Binning. In this talk, we will show preliminary results for several clusters, including Abell 2744 and the Bullet cluster. This work is supported by NASA ADAP grant NNX15AE17G.

A versatile rotary-stage high frequency probe station for studying magnetic films and devices

NASA Astrophysics Data System (ADS)

He, Shikun; Meng, Zhaoliang; Huang, Lisen; Yap, Lee Koon; Zhou, Tiejun; Panagopoulos, Christos

2016-07-01

We present a rotary-stage microwave probe station suitable for magnetic films and spintronic devices. Two stages, one for field rotation from parallel to perpendicular to the sample plane (out-of-plane) and the other intended for field rotation within the sample plane (in-plane) have been designed. The sample probes and micro-positioners are rotated simultaneously with the stages, which allows the field orientation to cover θ from 0∘ to 90∘ and φ from 0∘ to 360∘. θ and φ being the angle between the direction of current flow and field in a out-of-plane and an in-plane rotation, respectively. The operation frequency is up to 40 GHz and the magnetic field up to 1 T. The sample holder vision system and probe assembly are compactly designed for the probes to land on a wafer with diameter up to 3 cm. Using homemade multi-pin probes and commercially available high frequency probes, several applications including 4-probe DC measurements, the determination of domain wall velocity, and spin transfer torque ferromagnetic resonance are demonstrated.

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

Properties of young massive clusters obtained with different massive-star evolutionary models

NASA Astrophysics Data System (ADS)

Wofford, Aida; Charlot, Stéphane

We undertake a comprehensive comparative test of seven widely-used spectral synthesis models using multi-band HST photometry of a sample of eight YMCs in two galaxies. We provide a first quantitative estimate of the accuracies and uncertainties of new models, show the good progress of models in fitting high-quality observations, and highlight the need of further comprehensive comparative tests.

Prevalence of COPD in 6 Urban Clusters in Argentina: The EPOC.AR Study.

PubMed

Echazarreta, Andrés L; Arias, Sergio J; Del Olmo, Ricardo; Giugno, Eduardo R; Colodenco, Federico D; Arce, Santiago C; Bossio, Juan C; Armando, Gustavo; Soriano, Joan B

2018-05-01

The prevalence of chronic obstructive pulmonary disease (COPD) has not been studied in Argentina. To determine the prevalence and relevant clinical characteristics of COPD in a representative sample. We performed a cross-sectional study in a population of adults aged ≥ 40 years randomly selected by cluster sampling in 6 urban locations. Subjects answered a structured survey and performed pre- and post-bronchodilator spirometry (PBD). COPD was defined as FEV 1 /FVC ratio < 0.7 predicted value. The total prevalence was estimated for each cluster with its 95% confidence interval (CI). Of 4,599 surveys and 3,999 spirometries, 3,469 were considered of adequate quality (86.8%) for our study. The prevalence of COPD was 14.5% (CI: 13.4-15.7). The distribution of COPD cases according to FEV1 (GOLD 2017) was stage 1: 38% (CI: 34-43); stage 2: 52% (CI: 47-56); stage 3: 10% (CI: 7-13); and stage 4: 1% (CI: 0-2), and according to the refined ABCD (GOLD 2017) assessment: A: 52% (CI: 47-56); B: 43% (CI: 39-48); C: 1% (CI: 0-2); D: 4% (CI: 2-6). The rate of underdiagnosis was 77.4% (CI 73.7-81.1%) and diagnostic error 60.7% (CI 55.1-66.3%). A significant association was found between COPD and age (OR 3.77 in individuals 50-59 years of age and 19.23 in those > 80 years), male gender (OR 1.62; CI 1.31-2), smoking (OR 1.95; CI 1.49-2.54), low socioeconomic status (OR 1.33; CI 1.02-1.73), and previous tuberculosis (OR 3.3; CI 1.43-7.62). We estimate that more than 2.3 million Argentineans have COPD, with high rates of underdiagnosis and diagnostic error. Copyright © 2017 SEPAR. Publicado por Elsevier España, S.L.U. All rights reserved.

Mismatch of Posttraumatic Stress Disorder (PTSD) Symptoms and DSM-IV Symptom Clusters in a Cancer Sample: Exploratory Factor Analysis of the PTSD Checklist-Civilian Version

PubMed Central

Shelby, Rebecca A.; Golden-Kreutz, Deanna M.; Andersen, Barbara L.

2007-01-01

The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV; American Psychiatric Association, 1994a) conceptualization of posttraumatic stress disorder (PTSD) includes three symptom clusters: reexperiencing, avoidance/numbing, and arousal. The PTSD Checklist-Civilian Version (PCL-C) corresponds to the DSM-IV PTSD symptoms. In the current study, we conducted exploratory factor analysis (EFA) of the PCL-C with two aims: (a) to examine whether the PCL-C evidenced the three-factor solution implied by the DSM-IV symptom clusters, and (b) to identify a factor solution for the PCL-C in a cancer sample. Women (N = 148) with Stage II or III breast cancer completed the PCL-C after completion of cancer treatment. We extracted two-, three-, four-, and five-factor solutions using EFA. Our data did not support the DSM-IV PTSD symptom clusters. Instead, EFA identified a four-factor solution including reexperiencing, avoidance, numbing, and arousal factors. Four symptom items, which may be confounded with illness and cancer treatment-related symptoms, exhibited poor factor loadings. Using these symptom items in cancer samples may lead to overdiagnosis of PTSD and inflated rates of PTSD symptoms. PMID:16281232

Multilevel Hierarchical Kernel Spectral Clustering for Real-Life Large Scale Complex Networks

PubMed Central

Mall, Raghvendra; Langone, Rocco; Suykens, Johan A. K.

2014-01-01

Kernel spectral clustering corresponds to a weighted kernel principal component analysis problem in a constrained optimization framework. The primal formulation leads to an eigen-decomposition of a centered Laplacian matrix at the dual level. The dual formulation allows to build a model on a representative subgraph of the large scale network in the training phase and the model parameters are estimated in the validation stage. The KSC model has a powerful out-of-sample extension property which allows cluster affiliation for the unseen nodes of the big data network. In this paper we exploit the structure of the projections in the eigenspace during the validation stage to automatically determine a set of increasing distance thresholds. We use these distance thresholds in the test phase to obtain multiple levels of hierarchy for the large scale network. The hierarchical structure in the network is determined in a bottom-up fashion. We empirically showcase that real-world networks have multilevel hierarchical organization which cannot be detected efficiently by several state-of-the-art large scale hierarchical community detection techniques like the Louvain, OSLOM and Infomap methods. We show that a major advantage of our proposed approach is the ability to locate good quality clusters at both the finer and coarser levels of hierarchy using internal cluster quality metrics on 7 real-life networks. PMID:24949877

Multi-stage decoding of multi-level modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

Storage assignment optimization in a multi-tier shuttle warehousing system

NASA Astrophysics Data System (ADS)

Wang, Yanyan; Mou, Shandong; Wu, Yaohua

2016-03-01

The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem(TSP), which has been widely applied in the conventional automated storage and retrieval system(AS/RS). However, the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems(MSWS) because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP. In this study, a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period (SWP) and lift idle period (LIP) during transaction cycle time. A mean arrival time difference matrix for pairwise stock keeping units(SKUs) is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation. The decomposition method is applied to analyze the interactions among outbound task time, SWP, and LIP. The ant colony clustering algorithm is designed to determine storage partitions using clustering items. In addition, goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane. This combination is derived based on the analysis results of the queuing network model and on three basic principles. The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry. The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.

Supramolecular clusters between carbohydrates and concave pyridines. Detection in the gas phase by resonance-enhanced multi-photon ionization reflectron time-of-flight mass spectrometer.

PubMed

Liebig, Timo; Lüning, Ulrich; Grotemeyer, Jürgen

2006-01-01

For the first time the formation of supramolecular clusters between concave pyridines and different carbohydrates could be observed in the gas phase. The different clusters have been investigated by means of laser desorption into a supersonic beam followed by resonant multi photon excitation yielding mass spectra with high intensity of the different cluster. These preliminary results open a way for the investigations of the hydrogen bonds in these compounds.

The expression of Mirc1/Mir17-92 cluster in sputum samples correlates with pulmonary exacerbations in cystic fibrosis patients.

PubMed

Krause, Kathrin; Kopp, Benjamin T; Tazi, Mia F; Caution, Kyle; Hamilton, Kaitlin; Badr, Asmaa; Shrestha, Chandra; Tumin, Dmitry; Hayes, Don; Robledo-Avila, Frank; Hall-Stoodley, Luanne; Klamer, Brett G; Zhang, Xiaoli; Partida-Sanchez, Santiago; Parinandi, Narasimham L; Kirkby, Stephen E; Dakhlallah, Duaa; McCoy, Karen S; Cormet-Boyaka, Estelle; Amer, Amal O

2018-07-01

Cystic fibrosis (CF) is a multi-organ disorder characterized by chronic sino-pulmonary infections and inflammation. Many patients with CF suffer from repeated pulmonary exacerbations that are predictors of worsened long-term morbidity and mortality. There are no reliable markers that associate with the onset or progression of an exacerbation or pulmonary deterioration. Previously, we found that the Mirc1/Mir17-92a cluster which is comprised of 6 microRNAs (Mirs) is highly expressed in CF mice and negatively regulates autophagy which in turn improves CF transmembrane conductance regulator (CFTR) function. Therefore, here we sought to examine the expression of individual Mirs within the Mirc1/Mir17-92 cluster in human cells and biological fluids and determine their role as biomarkers of pulmonary exacerbations and response to treatment. Mirc1/Mir17-92 cluster expression was measured in human CF and non-CF plasma, blood-derived neutrophils, and sputum samples. Values were correlated with pulmonary function, exacerbations and use of CFTR modulators. Mirc1/Mir17-92 cluster expression was not significantly elevated in CF neutrophils nor plasma when compared to the non-CF cohort. Cluster expression in CF sputum was significantly higher than its expression in plasma. Elevated CF sputum Mirc1/Mir17-92 cluster expression positively correlated with pulmonary exacerbations and negatively correlated with lung function. Patients with CF undergoing treatment with the CFTR modulator Ivacaftor/Lumacaftor did not demonstrate significant change in the expression Mirc1/Mir17-92 cluster after six months of treatment. Mirc1/Mir17-92 cluster expression is a promising biomarker of respiratory status in patients with CF including pulmonary exacerbation. Published by Elsevier B.V.

Multidimensional Normalization to Minimize Plate Effects of Suspension Bead Array Data.

PubMed

Hong, Mun-Gwan; Lee, Woojoo; Nilsson, Peter; Pawitan, Yudi; Schwenk, Jochen M

2016-10-07

Enhanced by the growing number of biobanks, biomarker studies can now be performed with reasonable statistical power by using large sets of samples. Antibody-based proteomics by means of suspension bead arrays offers one attractive approach to analyze serum, plasma, or CSF samples for such studies in microtiter plates. To expand measurements beyond single batches, with either 96 or 384 samples per plate, suitable normalization methods are required to minimize the variation between plates. Here we propose two normalization approaches utilizing MA coordinates. The multidimensional MA (multi-MA) and MA-loess both consider all samples of a microtiter plate per suspension bead array assay and thus do not require any external reference samples. We demonstrate the performance of the two MA normalization methods with data obtained from the analysis of 384 samples including both serum and plasma. Samples were randomized across 96-well sample plates, processed, and analyzed in assay plates, respectively. Using principal component analysis (PCA), we could show that plate-wise clusters found in the first two components were eliminated by multi-MA normalization as compared with other normalization methods. Furthermore, we studied the correlation profiles between random pairs of antibodies and found that both MA normalization methods substantially reduced the inflated correlation introduced by plate effects. Normalization approaches using multi-MA and MA-loess minimized batch effects arising from the analysis of several assay plates with antibody suspension bead arrays. In a simulated biomarker study, multi-MA restored associations lost due to plate effects. Our normalization approaches, which are available as R package MDimNormn, could also be useful in studies using other types of high-throughput assay data.

Intention to Quit Smoking and Associated Factors in Smokers Newly Diagnosed with Pulmonary Tuberculosis.

PubMed

Aryanpur, Mahshid; Masjedi, Mohammad Reza; Mortaz, Esmaeil; Hosseini, Mostafa; Jamaati, Hmidreza; Tabarsi, Payam; Soori, Hamid; Heydari, Gholam Reza; Kazempour-Dizaji, Mehdi; Emami, Habib; Mozafarian, Alireza

2016-01-01

Several studies have shown that smoking, as a modifiable risk factor, can affect tuberculosis (TB) in different aspects such as enhancing development of TB infection, activation of latent TB and its related mortality. Since willingness to quit smoking is a critical stage, which may lead to quit attempts, being aware of smokers' intention to quit and the related predictors can provide considerable advantages. In this cross-sectional study, subjects were recruited via a multi-stage cluster sampling method. Sampling was performed during 2012-2014 among pulmonary TB (PTB) patients referred to health centers in Tehran implementing the directly observed treatment short course (DOTS) strategy and a TB referral center. Data analysis was conducted using SPSS version 22 and the factors influencing quit intention were assessed using bivariate regression and multiple logistic regression models. In this study 1,127 newly diagnosed PTB patients were studied; from which 284 patients (22%) were current smokers. When diagnosed with TB, 59 (23.8%) smokers quit smoking. Among the remaining 189 (76.2%) patients who continued smoking, 52.4% had intention to quit. In the final multiple logistic regression model, living in urban areas (OR=8.81, P=0.003), having an office job (OR= 7.34, P=0.001), being single (OR=4.89, P=0.016) and a one unit increase in the motivation degree (OR=2.60, P<0.001) were found to increase the intention to quit smoking. The study found that PTB patients who continued smoking had remarkable intention to quit. Thus, it is recommended that smoking cessation interventions should be started at the time of TB diagnosis. Understanding the associated factors can guide the consultants to predict patients' intention to quit and select the most proper management to facilitate smoking cessation for each patient.

Clustered Multi-Task Learning for Automatic Radar Target Recognition

PubMed Central

Li, Cong; Bao, Weimin; Xu, Luping; Zhang, Hua

2017-01-01

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. PMID:28953267

The three-dimensional Multi-Block Advanced Grid Generation System (3DMAGGS)

NASA Technical Reports Server (NTRS)

Alter, Stephen J.; Weilmuenster, Kenneth J.

1993-01-01

As the size and complexity of three dimensional volume grids increases, there is a growing need for fast and efficient 3D volumetric elliptic grid solvers. Present day solvers are limited by computational speed and do not have all the capabilities such as interior volume grid clustering control, viscous grid clustering at the wall of a configuration, truncation error limiters, and convergence optimization residing in one code. A new volume grid generator, 3DMAGGS (Three-Dimensional Multi-Block Advanced Grid Generation System), which is based on the 3DGRAPE code, has evolved to meet these needs. This is a manual for the usage of 3DMAGGS and contains five sections, including the motivations and usage, a GRIDGEN interface, a grid quality analysis tool, a sample case for verifying correct operation of the code, and a comparison to both 3DGRAPE and GRIDGEN3D. Since it was derived from 3DGRAPE, this technical memorandum should be used in conjunction with the 3DGRAPE manual (NASA TM-102224).

Which nets are being used: factors associated with mosquito net use in Amhara, Oromia and Southern Nations, Nationalities and Peoples' Regions of Ethiopia.

PubMed

Ngondi, Jeremiah M; Graves, Patricia M; Gebre, Teshome; Mosher, Aryc W; Shargie, Estifanos B; Emerson, Paul M; Richards, Frank O

2011-04-17

There has been recent large scale-up of malaria control interventions in Ethiopia where transmission is unstable. While household ownership of long-lasting insecticidal nets (LLIN) has increased greatly, there are concerns about inadequate net use. This study aimed to investigate factors associated with net use at two time points, before and after mass distribution of nets. Two cross sectional surveys were carried out in 2006 and 2007 in Amhara, Oromia and SNNP regions. The latter was a sub-sample of the national Malaria Indicator Survey (MIS 3R). Each survey wave used multi-stage cluster random sampling with 25 households per cluster (224 clusters with 5,730 households in Baseline 2006 and 245 clusters with 5,910 households in MIS 3R 2007). Net ownership was assessed by visual inspection while net utilization was reported as use of the net the previous night. This net level analysis was restricted to households owning at least one net of any type. Logistic regression models of association between net use and explanatory variables including net type, age, condition, cost and other household characteristics were undertaken using generalized linear latent and mixed models (GLLAMM). A total of 3,784 nets in 2,430 households were included in the baseline 2006 analysis while the MIS 3R 2007 analysis comprised 5,413 nets in 3,328 households. The proportion of nets used the previous night decreased from 85.1% to 56.0% between baseline 2006 and MIS 3R 2007, respectively. Factors independently associated with increased proportion of nets used were: LLIN net type (at baseline 2006); indoor residual spraying (at MIS 3R 2007); and increasing wealth index at both surveys. At both baseline 2006 and MIS 3R 2007, reduced proportion of nets used was independently associated with increasing net age, increasing damage of nets, increasing household net density, and increasing altitude (>2,000 m). This study identified modifiable factors affecting use of nets that were consistent across both surveys. While net replacement remains important, the findings suggest that: more education about use and care of nets; making nets more resistant to damage; and encouraging net mending are likely to maximize the huge investment in scale up of net ownership by ensuring they are used. Without this step, the widespread benefits of LLIN cannot be realized.

Enhancing local health department disaster response capacity with rapid community needs assessments: validation of a computerized program for binary attribute cluster sampling.

PubMed

Groenewold, Matthew R

2006-01-01

Local health departments are among the first agencies to respond to disasters or other mass emergencies. However, they often lack the ability to handle large-scale events. Plans including locally developed and deployed tools may enhance local response. Simplified cluster sampling methods can be useful in assessing community needs after a sudden-onset, short duration event. Using an adaptation of the methodology used by the World Health Organization Expanded Programme on Immunization (EPI), a Microsoft Access-based application for two-stage cluster sampling of residential addresses in Louisville/Jefferson County Metro, Kentucky was developed. The sampling frame was derived from geographically referenced data on residential addresses and political districts available through the Louisville/Jefferson County Information Consortium (LOJIC). The program randomly selected 30 clusters, defined as election precincts, from within the area of interest, and then, randomly selected 10 residential addresses from each cluster. The program, called the Rapid Assessment Tools Package (RATP), was tested in terms of accuracy and precision using data on a dichotomous characteristic of residential addresses available from the local tax assessor database. A series of 30 samples were produced and analyzed with respect to their precision and accuracy in estimating the prevalence of the study attribute. Point estimates with 95% confidence intervals were calculated by determining the proportion of the study attribute values in each of the samples and compared with the population proportion. To estimate the design effect, corresponding simple random samples of 300 addresses were taken after each of the 30 cluster samples. The sample proportion fell within +/-10 absolute percentage points of the true proportion in 80% of the samples. In 93.3% of the samples, the point estimate fell within +/-12.5%, and 96.7% fell within +/-15%. All of the point estimates fell within +/-20% of the true proportion. Estimates of the design effect ranged from 0.926 to 1.436 (mean = 1.157, median = 1.170) for the 30 samples. Although prospective evaluation of its performance in field trials or a real emergency is required to confirm its utility, this study suggests that the RATP, a locally designed and deployed tool, may provide population-based estimates of community needs or the extent of event-related consequences that are precise enough to serve as the basis for the initial post-event decisions regarding relief efforts.

Helium segregation on surfaces of plasma-exposed tungsten

DOE PAGES

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; ...

2016-01-21

Here we report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He-n (1 <= n <= 7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides themore » thermodynamic driving force for surface segregation. Elastic interaction force induces drift fluxes of these mobile Hen clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters' drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. Moreover, these near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.« less

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.

Toward the 21st Century: Preparing Proactive Visionary Transformational Leaders for Building Learning Communities through Multi-Technology. Leadership I Formative Evaluation of Cluster 54.

ERIC Educational Resources Information Center

Groff, Warren H.

This paper presents a description and formative evaluation of National (Multi-Tech) Cluster III, Nova University's third technology-intensive doctoral program in Child and Youth Studies (CYS) in which formal instruction occurs in clusters, or groups of professionals in different geographic locations who are connected via electronic communications…

Multi-Object Spectroscopy with MUSE

NASA Astrophysics Data System (ADS)

Kelz, A.; Kamann, S.; Urrutia, T.; Weilbacher, P.; Bacon, R.

2016-10-01

Since 2014, MUSE, the Multi-Unit Spectroscopic Explorer, is in operation at the ESO-VLT. It combines a superb spatial sampling with a large wavelength coverage. By design, MUSE is an integral-field instrument, but its field-of-view and large multiplex make it a powerful tool for multi-object spectroscopy too. Every data-cube consists of 90,000 image-sliced spectra and 3700 monochromatic images. In autumn 2014, the observing programs with MUSE have commenced, with targets ranging from distant galaxies in the Hubble Deep Field to local stellar populations, star formation regions and globular clusters. This paper provides a brief summary of the key features of the MUSE instrument and its complex data reduction software. Some selected examples are given, how multi-object spectroscopy for hundreds of continuum and emission-line objects can be obtained in wide, deep and crowded fields with MUSE, without the classical need for any target pre-selection.

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

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

PubMed

Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

2015-01-01

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

Development of design technique for vacuum insulation in large size multi-aperture multi-grid accelerator for nuclear fusion.

PubMed

Kojima, A; Hanada, M; Tobari, H; Nishikiori, R; Hiratsuka, J; Kashiwagi, M; Umeda, N; Yoshida, M; Ichikawa, M; Watanabe, K; Yamano, Y; Grisham, L R

2016-02-01

Design techniques for the vacuum insulation have been developed in order to realize a reliable voltage holding capability of multi-aperture multi-grid (MAMuG) accelerators for fusion application. In this method, the nested multi-stage configuration of the MAMuG accelerator can be uniquely designed to satisfy the target voltage within given boundary conditions. The evaluation of the voltage holding capabilities of each acceleration stages was based on the previous experimental results about the area effect and the multi-aperture effect. Since the multi-grid effect was found to be the extension of the area effect by the total facing area this time, the total voltage holding capability of the multi-stage can be estimated from that per single stage by assuming the stage with the highest electric field, the total facing area, and the total apertures. By applying these consideration, the analysis on the 3-stage MAMuG accelerator for JT-60SA agreed well with the past gap-scan experiments with an accuracy of less than 10% variation, which demonstrated the high reliability to design MAMuG accelerators and also multi-stage high voltage bushings.

Development of design technique for vacuum insulation in large size multi-aperture multi-grid accelerator for nuclear fusion

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

Kojima, A., E-mail: kojima.atsushi@jaea.go.jp; Hanada, M.; Tobari, H.

Design techniques for the vacuum insulation have been developed in order to realize a reliable voltage holding capability of multi-aperture multi-grid (MAMuG) accelerators for fusion application. In this method, the nested multi-stage configuration of the MAMuG accelerator can be uniquely designed to satisfy the target voltage within given boundary conditions. The evaluation of the voltage holding capabilities of each acceleration stages was based on the previous experimental results about the area effect and the multi-aperture effect. Since the multi-grid effect was found to be the extension of the area effect by the total facing area this time, the total voltagemore » holding capability of the multi-stage can be estimated from that per single stage by assuming the stage with the highest electric field, the total facing area, and the total apertures. By applying these consideration, the analysis on the 3-stage MAMuG accelerator for JT-60SA agreed well with the past gap-scan experiments with an accuracy of less than 10% variation, which demonstrated the high reliability to design MAMuG accelerators and also multi-stage high voltage bushings.« less

Pressure ulcer multidisciplinary teams via telemedicine: a pragmatic cluster randomized stepped wedge trial in long term care.

PubMed

Stern, Anita; Mitsakakis, Nicholas; Paulden, Mike; Alibhai, Shabbir; Wong, Josephine; Tomlinson, George; Brooker, Ann-Sylvia; Krahn, Murray; Zwarenstein, Merrick

2014-02-24

The study was conducted to determine the clinical and cost effectiveness of enhanced multi-disciplinary teams (EMDTs) vs. 'usual care' for the treatment of pressure ulcers in long term care (LTC) facilities in Ontario, Canada We conducted a multi-method study: a pragmatic cluster randomized stepped-wedge trial, ethnographic observation and in-depth interviews, and an economic evaluation. Long term care facilities (clusters) were randomly allocated to start dates of the intervention. An advance practice nurse (APN) with expertise in skin and wound care visited intervention facilities to educate staff on pressure ulcer prevention and treatment, supported by an off-site hospital based expert multi-disciplinary wound care team via email, telephone, or video link as needed. The primary outcome was rate of reduction in pressure ulcer surface area (cm2/day) measured on before and after standard photographs by an assessor blinded to facility allocation. Secondary outcomes were time to healing, probability of healing, pressure ulcer incidence, pressure ulcer prevalence, wound pain, hospitalization, emergency department visits, utility, and cost. 12 of 15 eligible LTC facilities were randomly selected to participate and randomized to start date of the intervention following the stepped wedge design. 137 residents with a total of 259 pressure ulcers (stage 2 or greater) were recruited over the 17 month study period. No statistically significant differences were found between control and intervention periods on any of the primary or secondary outcomes. The economic evaluation demonstrated a mean reduction in direct care costs of $650 per resident compared to 'usual care'. The qualitative study suggested that onsite support by APN wound specialists was welcomed, and is responsible for reduced costs through discontinuation of expensive non evidence based treatments. Insufficient allocation of nursing home staff time to wound care may explain the lack of impact on healing. Enhanced multi-disciplinary wound care teams were cost effective, with most benefit through cost reduction initiated by APNs, but did not improve the treatment of pressure ulcers in nursing homes. Policy makers should consider the potential yield of strengthening evidence based primary care within LTC facilities, through outreach by APNs. ClinicalTrials.gov identifier NCT01232764.

Low-income women's reproductive weight patterns empirically based clusters of prepregnant, gestational, and postpartum weights.

PubMed

Walker, Lorraine O

2009-01-01

Women have varying weight responses to pregnancy and the postpartum period. The purpose of this study was to derive sub-groups of women based on differing reproductive weight clusters; to validate clusters by reference to adequacy of gestational weight gain (GWG) and postpartum incremental weight shifts; and to examine associations between clusters and demographic, behavioral, and psychosocial variables. A cluster analysis was conducted of a multi-ethnic/racial sample of low-income women (n = 247). Clusters were derived from three weight variables: prepregnant body mass index, GWG, and postpartum retained weight. Five clusters were derived: Cluster 1, normal weight-high prenatal gain-average retain; cluster 2, normal weight-low prenatal gain-zero retain; cluster 3, high normal weight-high prenatal gain-high retain; cluster 4, obese-low prenatal gain-average retain; and cluster 5, overweight-very high prenatal gain-very high retain. Clusters differed with regard to postpartum weight shifts (p < .001), with clusters 3, 4, and 5, mostly gaining weight between 6 weeks and 12 months postpartum, whereas clusters 1 and 2 were losing weight. Clusters were also associated with race/ethnicity (p < .01), breastfeeding immediately postdelivery (p < .01), smoking at 12 months (p < .05), and reaching weight goals at 6 and 12 months (p < .001), but not depressive symptoms, fat intake habits, or physical activity. In a five-cluster solution, postpartum weight shifts, ethnicity, and initial breastfeeding were among factors associated with clusters. Monitoring of weight and appropriate intervention beyond the 6 weeks after birth is needed for low-income women in high normal weight, overweight, and obese clusters.

An Association between Bullying Behaviors and Alcohol Use among Middle School Students

ERIC Educational Resources Information Center

Peleg-Oren, Neta; Cardenas, Gabriel A.; Comerford, Mary; Galea, Sandro

2012-01-01

Although a high prevalence of bullying behaviors among adolescents has been documented, little is known about the association between bullying behaviors and alcohol use among perpetrators or victims. This study used data from a representative two-stage cluster random sample of 44, 532 middle school adolescents in Florida. We found a high…

MOCASSIN-prot: a multi-objective clustering approach for protein similarity networks.

PubMed

Keel, Brittney N; Deng, Bo; Moriyama, Etsuko N

2018-04-15

Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure. The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families. MOCASSIN-prot, implemented in Perl and Matlab, is freely available at http://bioinfolab.unl.edu/emlab/MOCASSINprot. emoriyama2@unl.edu. Supplementary data are available at Bioinformatics online.

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.

A Profile of Puerto Rican Health in the United States: Data from the Hispanic Health and Nutrition Examination Survey 1982-84.

ERIC Educational Resources Information Center

Munoz, Eric; And Others

The health conditions and health status of Hispanic Americans will assume increased importance as their population increases. The goal of this book of charts is to present data from the Hispanic Health and Nutrition Examination Survey (HHANES) on Puerto Ricans. The Puerto Rican HHANES sampling procedure is a multi-stage probability sample of…

Student Assessment of Quality of Access at the National Open University of Nigeria (NOUN)

ERIC Educational Resources Information Center

Inegbedion, Juliet O.; Adu, Folorunso I.; Ofulue, Christine Y.

2016-01-01

This paper presents a study conducted by Inegbedion, Adu and Ofulue from the National Open University of Nigeria. The study focused on the quality of access (admission and registration) at NOUN from a student perspective. A survey design was used for the study while a multi-stage sampling technique was used to select the sample size. All the…

A Gender Based Study on Job Satisfaction among Higher Secondary School Heads in Khyber Pakhtunkhwa, (Pakistan)

ERIC Educational Resources Information Center

Mumtaz, Safina; Suleman, Qaiser; Ahmad, Zubair

2016-01-01

The purpose of the study was to analyze and compare the job satisfaction with twenty dimensions of male and female higher secondary school heads in Khyber Pakhtunkhwa. A total of 108 higher secondary school heads were selected from eleven districts as sample through multi-stage sampling technique in which 66 were male and 42 were female. The study…

Dual-mode nested search method for categorical uncertain multi-objective optimization

NASA Astrophysics Data System (ADS)

Tang, Long; Wang, Hu

2016-10-01

Categorical multi-objective optimization is an important issue involved in many matching design problems. Non-numerical variables and their uncertainty are the major challenges of such optimizations. Therefore, this article proposes a dual-mode nested search (DMNS) method. In the outer layer, kriging metamodels are established using standard regular simplex mapping (SRSM) from categorical candidates to numerical values. Assisted by the metamodels, a k-cluster-based intelligent sampling strategy is developed to search Pareto frontier points. The inner layer uses an interval number method to model the uncertainty of categorical candidates. To improve the efficiency, a multi-feature convergent optimization via most-promising-area stochastic search (MFCOMPASS) is proposed to determine the bounds of objectives. Finally, typical numerical examples are employed to demonstrate the effectiveness of the proposed DMNS method.

NCSTRL+: Adding Multi-Discipline and Multi-Genre Support to the Dienst Protocol Using Clusters and Buckets

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.; Zubair, Mohammad

1998-01-01

We describe NCSTRL+, a unified, canonical digital library for scientific and technical information (STI). NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible digital library (DL) that provides access to over 100 university departments and laboratories. NCSTRL+ implements two new technologies: cluster functionality and publishing buckets. We have extended Dienst, the protocol underlying NCSTRL, to provide the ability to cluster independent collections into a logically centralized digital library based upon subject category classification, type of organization, and genres of material. The bucket construct provides a mechanism for publishing and managing logically linked entities with multiple data forms as a single object. The NCSTRL+ prototype DL contains the holdings of NCSTRL and the NASA Technical Report Server (NTRS). The prototype demonstrates the feasibility of publishing into a multi-cluster DL, searching across clusters, and storing and presenting buckets of information.

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

NASA Astrophysics Data System (ADS)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

Users matter : multi-agent systems model of high performance computing cluster users.

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

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less

Geographical classification of Epimedium based on HPLC fingerprint analysis combined with multi-ingredients quantitative analysis.

PubMed

Xu, Ning; Zhou, Guofu; Li, Xiaojuan; Lu, Heng; Meng, Fanyun; Zhai, Huaqiang

2017-05-01

A reliable and comprehensive method for identifying the origin and assessing the quality of Epimedium has been developed. The method is based on analysis of HPLC fingerprints, combined with similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) and multi-ingredient quantitative analysis. Nineteen batches of Epimedium, collected from different areas in the western regions of China, were used to establish the fingerprints and 18 peaks were selected for the analysis. Similarity analysis, HCA and PCA all classified the 19 areas into three groups. Simultaneous quantification of the five major bioactive ingredients in the Epimedium samples was also carried out to confirm the consistency of the quality tests. These methods were successfully used to identify the geographical origin of the Epimedium samples and to evaluate their quality. Copyright © 2016 John Wiley & Sons, Ltd.

A multi purpose source chamber at the PLEIADES beamline at SOLEIL for spectroscopic studies of isolated species: Cold molecules, clusters, and nanoparticles

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

Lindblad, Andreas; Söderström, Johan; Nicolas, Christophe

2013-11-15

This paper describes the philosophy and design goals regarding the construction of a versatile sample environment: a source capable of producing beams of atoms, molecules, clusters, and nanoparticles in view of studying their interaction with short wavelength (vacuum ultraviolet and x-ray) synchrotron radiation. In the design, specific care has been taken of (a) the use standard components, (b) ensuring modularity, i.e., that swiftly switching between different experimental configurations was possible. To demonstrate the efficiency of the design, proof-of-principle experiments have been conducted by recording x-ray absorption and photoelectron spectra from isolated nanoparticles (SiO{sub 2}) and free mixed clusters (Ar/Xe). Themore » results from those experiments are showcased and briefly discussed.« less

Separation of Platinum from Palladium and Iridium in Iron Meteorites and Accurate High-Precision Determination of Platinum Isotopes by Multi-Collector ICP-MS.

PubMed

Hunt, Alison C; Ek, Mattias; Schönbächler, Maria

2017-12-01

This study presents a new measurement procedure for the isolation of Pt from iron meteorite samples. The method also allows for the separation of Pd from the same sample aliquot. The separation entails a two-stage anion-exchange procedure. In the first stage, Pt and Pd are separated from each other and from major matrix constituents including Fe and Ni. In the second stage, Ir is reduced with ascorbic acid and eluted from the column before Pt collection. Platinum yields for the total procedure were typically 50-70%. After purification, high-precision Pt isotope determinations were performed by multi-collector ICP-MS. The precision of the new method was assessed using the IIAB iron meteorite North Chile. Replicate analyses of multiple digestions of this material yielded an intermediate precision for the measurement results of 0.73 for ε 192 Pt, 0.15 for ε 194 Pt and 0.09 for ε 196 Pt (2 standard deviations). The NIST SRM 3140 Pt solution reference material was passed through the measurement procedure and yielded an isotopic composition that is identical to the unprocessed Pt reference material. This indicates that the new technique is unbiased within the limit of the estimated uncertainties. Data for three iron meteorites support that Pt isotope variations in these samples are due to exposure to galactic cosmic rays in space.

Factorial versus multi-arm multi-stage designs for clinical trials with multiple treatments.

PubMed

Jaki, Thomas; Vasileiou, Despina

2017-02-20

When several treatments are available for evaluation in a clinical trial, different design options are available. We compare multi-arm multi-stage with factorial designs, and in particular, we will consider a 2 × 2 factorial design, where groups of patients will either take treatments A, B, both or neither. We investigate the performance and characteristics of both types of designs under different scenarios and compare them using both theory and simulations. For the factorial designs, we construct appropriate test statistics to test the hypothesis of no treatment effect against the control group with overall control of the type I error. We study the effect of the choice of the allocation ratios on the critical value and sample size requirements for a target power. We also study how the possibility of an interaction between the two treatments A and B affects type I and type II errors when testing for significance of each of the treatment effects. We present both simulation results and a case study on an osteoarthritis clinical trial. We discover that in an optimal factorial design in terms of minimising the associated critical value, the corresponding allocation ratios differ substantially to those of a balanced design. We also find evidence of potentially big losses in power in factorial designs for moderate deviations from the study design assumptions and little gain compared with multi-arm multi-stage designs when the assumptions hold. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks.

PubMed

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X

2015-12-26

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks

PubMed Central

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X.

2015-01-01

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols. PMID:26712764

Galaxy cluster luminosities and colours, and their dependence on cluster mass and merger state

NASA Astrophysics Data System (ADS)

Mulroy, Sarah L.; McGee, Sean L.; Gillman, Steven; Smith, Graham P.; Haines, Chris P.; Démoclès, Jessica; Okabe, Nobuhiro; Egami, Eiichi

2017-12-01

We study a sample of 19 galaxy clusters in the redshift range 0.15 < z < 0.30 with highly complete spectroscopic membership catalogues (to K < K*(z) + 1.5) from the Arizona Cluster Redshift Survey, individual weak-lensing masses and near-infrared data from the Local Cluster Substructure Survey, and optical photometry from the Sloan Digital Sky Survey. We fit the scaling relations between total cluster luminosity in each of six bandpasses (grizJK) and cluster mass, finding cluster luminosity to be a promising mass proxy with low intrinsic scatter σln L|M of only ∼10-20 per cent for all relations. At fixed overdensity radius, the intercept increases with wavelength, consistent with an old stellar population. The scatter and slope are consistent across all wavelengths, suggesting that cluster colour is not a function of mass. Comparing colour with indicators of the level of disturbance in the cluster, we find a narrower variety in the cluster colours of 'disturbed' clusters than of 'undisturbed' clusters. This trend is more pronounced with indicators sensitive to the initial stages of a cluster merger, e.g. the Dressler Schectman statistic. We interpret this as possible evidence that the total cluster star formation rate is 'standardized' in mergers, perhaps through a process such as a system-wide shock in the intracluster medium.

Dysfunctional tubular endoplasmic reticulum constitutes a pathological feature of Alzheimer's disease.

PubMed

Sharoar, M G; Shi, Q; Ge, Y; He, W; Hu, X; Perry, G; Zhu, X; Yan, R

2016-09-01

Pathological features in Alzheimer's brains include mitochondrial dysfunction and dystrophic neurites (DNs) in areas surrounding amyloid plaques. Using a mouse model that overexpresses reticulon 3 (RTN3) and spontaneously develops age-dependent hippocampal DNs, here we report that DNs contain both RTN3 and REEPs, topologically similar proteins that can shape tubular endoplasmic reticulum (ER). Importantly, ultrastructural examinations of such DNs revealed gradual accumulation of tubular ER in axonal termini, and such abnormal tubular ER inclusion is found in areas surrounding amyloid plaques in biopsy samples from Alzheimer's disease (AD) brains. Functionally, abnormally clustered tubular ER induces enhanced mitochondrial fission in the early stages of DN formation and eventual mitochondrial degeneration at later stages. Furthermore, such DNs are abrogated when RTN3 is ablated in aging and AD mouse models. Hence, abnormally clustered tubular ER can be pathogenic in brain regions: disrupting mitochondrial integrity, inducing DNs formation and impairing cognitive function in AD and aging brains.

Quality of life and visual function in Nigeria: findings from the National Survey of Blindness and Visual Impairment.

PubMed

Tran, Hang My; Mahdi, Abdull M; Sivasubramaniam, Selvaraj; Gudlavalleti, Murthy V S; Gilbert, Clare E; Shah, Shaheen P; Ezelum, C C; Abubakar, Tafida; Bankole, Olufunmilayo O

2011-12-01

To assess associations of visual function (VF) and quality of life (QOL) by visual acuity (VA), causes of blindness and types of cataract procedures in Nigeria. Multi-stage stratified cluster random sampling was used to identify a nationally representative sample of persons aged ≥ 40 years. VF/QOL questionnaires were administered to participants with VA <6/60 in one or both eyes and/or Mehra-Minassian cataract grade 2B or 3 in one or both eyes and a random sample of those with bilateral VA ≥ 6/12. VF/QOL questionnaires were administered to 2076 participants. Spearman's rank correlation showed a strong correlation between decreasing VA and VF/QOL scores (p<0.0001) with greatest impact on social (p<0.0001) and mobility-related activities (p<0.0001). People who were blind due to glaucoma had lower VF and QOL scores than those who were blind due to cataract. Mean VF and QOL scores were lower after couching compared with conventional cataract surgery (mean VF score=51.0 vs 63.0 and mean QOL score=71.3 vs 79.3). Finally, VF and QOL scores were lower among populations with specific characteristics. Populations with the following characteristics should be targeted to improve VF and QOL: people who are blind, older people, women, manual labourers, people living in rural areas, those living in the northern geopolitical zones, those practising Islamic and Traditionalism faith, those not currently married and those who have undergone couching.

Emotional Intelligence and Depressive Symptoms as Predictors of Happiness Among Adolescents.

PubMed

Abdollahi, Abbas; Abu Talib, Mansor; Motalebi, Seyedeh Ameneh

2015-12-01

Given that happiness is an important construct to enable adolescents to cope better with difficulties and stress of life, it is necessary to advance our knowledge about the possible etiology of happiness in adolescents. The present study sought to investigate the relationships of emotional intelligence, depressive symptoms, and happiness in a sample of male students in Tehran, Iran. This cross-sectional study was conducted on a sample of high school students in Tehran in 2012. The participants comprised of 188 male students (aged 16 to 19 years old) selected by multi-stage cluster sampling method. For gathering the data, the students filled out assessing emotions scale, Beck depression inventory-II, and Oxford happiness inventory. Data analysis was carried out using descriptive and analytical statistics in statistical package for social sciences (SPSS) software. The findings showed that a significant positive association existed between high ability of emotional intelligence and happiness (P < 0.01). Conversely, the low ability of emotional intelligence was associated with unhappiness (P < 0.01), there was a positive association between non-depression symptoms and happiness (P < 0.05), and severe depressive symptoms were positively associated with unhappiness (P < 0.01). High ability of emotional intelligence (P < 0.01) and non-depression symptoms (P < 0.05) were the strongest predictors of happiness. These findings reinforced the importance of emotional intelligence as a facilitating factor for happiness in adolescences. In addition, the findings suggested that depression symptoms may be harmful for happiness in adolescents.

The impact of environmental and demographic factors on nursing job satisfaction.

PubMed

Rahnavard, Farnaz; Sadati, Ahmad Kalateh; Hemmati, Sorror; Ebrahimzade, Najmeh; Sarikhani, Yaser; Heydari, Seyed Taghi; Lankarani, Kamran Bagheri

2018-04-01

This study aims to evaluate all aspects of job satisfaction in registered nurses working in different hospitals in Shiraz, Iran. This cross-sectional study was performed during February to August 2015 in Shiraz, Iran. It comprised of 371 registered nurses working in government and private hospitals using multi-stage cluster sampling. Job satisfaction was evaluated using 5 items of the Job Descriptive Index (JDI) consisting of 63 questions developed by Smith, Kendall, and Hulin (1969). Statistical tests including independent sample t test and one-way analysis of variance (ANOVA) were used in order to identify the relation between job satisfaction, and demographic features and work environment. Data were analyzed by SPSS version 15.0, using descriptive statistics, independent-samples t-test, and ANOVA. Our findings showed no relationship between demographic variables and job satisfaction. However, a significant association was observed between environmental aspects such as work rotation (fixed versus rotating) nurse's status (staff vs. supervisors), type of hospitals (governmental vs. private) and work (p<0.01), promotion (p<0.02) and pay (p<0.01) items respectively; however, type of hospital was deemed exempt regarding promotion. Also regarding the number of shifts per week, nurses with more than eight shifts present a lower mean score of satisfaction about pay significantly (p=0.03). The results concerning younger nurses have different types of satisfaction based on several environmental factors. Nurses' policy makers must pay more attention to nurses' satisfaction and focus on reducing the various inequalities.

Metabolic syndrome among 13 year old adolescents: prevalence and risk factors.

PubMed

Fadzlina, A A; Harun, Fatimah; Nurul Haniza, M Y; Al Sadat, Nabilla; Murray, Liam; Cantwell, Marie M; Su, Tin Tin; Majid, Hazreen Abdul; Jalaludin, Muhammad Yazid

2014-01-01

Obesity and metabolic syndrome is prevalent among Malaysian adolescents and has been associated with certain behavioural factors such as duration of sleep, screen time and physical activity. The aim of the study is to report the prevalence of overweight/obesity, metabolic syndrome and its risk factors among adolescents. A multi-staged cluster sampling method was used to select participants from urban and rural schools in Selangor, Perak and Wilayah Persekutuan Kuala Lumpur. Participants underwent anthropometric measurement and physical examination including blood pressure measurement. Blood samples were taken for fasting glucose and lipids and participants answered a self-administered questionnaire. Overweight and obesity was defined using the extrapolated adult body mass index (BMI) cut-offs of >25 kg/m2 and >30 kg/m2, according to the International Obesity Task Force (IOTF) criteria. Metabolic syndrome was defined based on International Diabetes Federation (IDF) 2007 criteria. Data were collected from 1361 participants. After excluding incomplete data and missing values for the variables, we analysed a sample of 1014 participants. Prevalence of overweight and obesity in this population was 25.4% (N = 258). The prevalence of metabolic syndrome was 2.6% in the population and 10% among the overweight and obese adolescents. Participants who slept between 7 and 9 hours a day has a lower risk of developing metabolic syndrome OR 0.38(0.15-0.94). Our results provide the prevalence of metabolic syndrome in Malaysian adolescents. Adequate sleep between 7 and 9 hours per day reduces the risk of developing metabolic syndrome.

A false sense of security? Can tiered approach be trusted to accurately classify immunogenicity samples?

PubMed

Jaki, Thomas; Allacher, Peter; Horling, Frank

2016-09-05

Detecting and characterizing of anti-drug antibodies (ADA) against a protein therapeutic are crucially important to monitor the unwanted immune response. Usually a multi-tiered approach that initially rapidly screens for positive samples that are subsequently confirmed in a separate assay is employed for testing of patient samples for ADA activity. In this manuscript we evaluate the ability of different methods used to classify subject with screening and competition based confirmatory assays. We find that for the overall performance of the multi-stage process the method used for confirmation is most important where a t-test is best when differences are moderate to large. Moreover we find that, when differences between positive and negative samples are not sufficiently large, using a competition based confirmation step does yield poor classification of positive samples. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Clustering redshift distributions for the Dark Energy Survey

NASA Astrophysics Data System (ADS)

Helsby, Jennifer

Accurate determination of photometric redshifts and their errors is critical for large scale structure and weak lensing studies for constraining cosmology from deep, wide imaging surveys. Current photometric redshift methods suffer from bias and scatter due to incomplete training sets. Exploiting the clustering between a sample of galaxies for which we have spectroscopic redshifts and a sample of galaxies for which the redshifts are unknown can allow us to reconstruct the true redshift distribution of the unknown sample. Here we use this method in both simulations and early data from the Dark Energy Survey (DES) to determine the true redshift distributions of galaxies in photometric redshift bins. We find that cross-correlating with the spectroscopic samples currently used for training provides a useful test of photometric redshifts and provides reliable estimates of the true redshift distribution in a photometric redshift bin. We discuss the use of the cross-correlation method in validating template- or learning-based approaches to redshift estimation and its future use in Stage IV surveys.

The environmental management problem of Pohorje, Slovenia: A new group approach within ANP - SWOT framework.

PubMed

Grošelj, Petra; Zadnik Stirn, Lidija

2015-09-15

Environmental management problems can be dealt with by combining participatory methods, which make it possible to include various stakeholders in a decision-making process, and multi-criteria methods, which offer a formal model for structuring and solving a problem. This paper proposes a three-phase decision making approach based on the analytic network process and SWOT (strengths, weaknesses, opportunities and threats) analysis. The approach enables inclusion of various stakeholders or groups of stakeholders in particular stages of decision making. The structure of the proposed approach is composed of a network consisting of an objective cluster, a cluster of strategic goals, a cluster of SWOT factors and a cluster of alternatives. The application of the suggested approach is applied to a management problem of Pohorje, a mountainous area in Slovenia. Stakeholders from sectors that are important for Pohorje (forestry, agriculture, tourism and nature protection agencies) who can offer a wide range of expert knowledge were included in the decision-making process. The results identify the alternative of "sustainable development" as the most appropriate for development of Pohorje. The application in the paper offers an example of employing the new approach to an environmental management problem. This can also be applied to decision-making problems in various other fields. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Evolution of the Cluster X-ray Scaling Relations in the Wide Angle ROSAT Pointed Survey Sample at 0.6 < z < 1.0

NASA Technical Reports Server (NTRS)

Maughan, B. J.; Jones, L. R.; Ebeling, H.; Scharf, C.

2006-01-01

The X-ray properties of a sample of 11 high-redshift (0.6 < z < 1 .O) clusters observed with Chardm and/or XMM-Newton are used to investigate the evolution of the cluster scaling relations. The observed evolution in the normalization of the L-T, M-T, M(sub 2)-T and M-L relations is consistent with simple self-similar predictions, in which the properties of clusters reflect the properties of the Universe at their redshift of observation. Under the assumption that the model of self-similar evolution is correct and that the local systems formed via a single spherical collapse, the high-redshift L-T relation is consistent with the high-z clusters having virialized at a significantly higher redshift than the local systems. The data are also consistent with the more realistic scenario of clusters forming via the continuous accretion of material. The slope of the L-T relation at high redshift (B = 3.32 +/- 0.37) is consistent with the local relation, and significantly steeper than the self-similar prediction of B = 2. This suggests that the same non-gravitational processes are responsible for steepening the local and high-z relations, possibly occurring universally at z is approximately greater than 1 or in the early stages of the cluster formation, prior to their observation. The properties of the intracluster medium at high redshift are found to be similar to those in the local Universe. The mean surface-brightness profile slope for the sample is Beta = 0.66 +/- 0.05, the mean gas mass fractions within R(sub 2500(z)) and R(200(z)) are 0.069 +/- 0.012 and 0.11 +/- 0.02, respectively, and the mean metallicity of the sample is 0.28 +/- 0.11 Z(sub solar).

Multi-Sample Cluster Analysis Using Akaike’s Information Criterion.

DTIC Science & Technology

1982-12-20

of Likelihood Criteria for I)fferent Hypotheses," in P. A. Krishnaiah (Ed.), Multivariate Analysis-Il, New York: Academic Press. [5] Fisher, R. A...Methods of Simultaneous Inference in MANOVA," in P. R. Krishnaiah (Ed.), rultivariate Analysis-Il, New York: Academic Press. [8) Kendall, M. G. (1966...1982), Applied Multivariate Statisti- cal-Analysis, Englewood Cliffs: Prentice-Mall, Inc. [1U] Krishnaiah , P. R. (1969), "Simultaneous Test

What Works in Gifted Education Mathematics Study: Impact of Pre-Differentiated and Enriched Curricula on General Education Teachers and Their Students. Research Monograph Series. RM13242

ERIC Educational Resources Information Center

Gubbins, E. Jean; McCoach, D. Betsy; Foreman, Jennifer L.; Gilson, Cindy M.; Bruce-Davis, Micah N.; Rubenstein, Lisa DaVia; Savino, Jennifer; Rambo, Karen; Waterman, Craig

2013-01-01

The present study seeks to determine how exposure to pre-differentiated and enriched curricula incorporating educative curriculum materials affects students' achievement as well as teacher and administrator responses to the intervention. A 2-year multi-site cluster randomized control trial study recruited a national sample of 4,530 grade 3…

Cancer genetics and reproduction.

PubMed

Hanson, Helen; Hodgson, Shirley

2010-02-01

Cancers of the reproductive organs (i.e., ovaries, uterus and testes), like other cancers, occur as a result of a multi-stage interaction of genetic and environmental factors. A small proportion of cancers of the reproductive organs occur as part of a recognised cancer syndrome, as a result of inheritance of mutations in highly penetrant cancer susceptibility genes (e.g., BRCA1, BRCA2, MLH1 or MSH2). Recognition of individuals and families with inherited cancer predisposition syndromes and individuals at high risk due to familial cancer clustering is fundamentally important for the management and treatment of the current cancer and for future prevention of further cancers for the individual and their extended family.

Inhomogeneity compensation for MR brain image segmentation using a multi-stage FCM-based approach.

PubMed

Szilágyi, László; Szilágyi, Sándor M; Dávid, László; Benyó, Zoltán

2008-01-01

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms. This paper proposes a multiple stage fuzzy c-means (FCM) based algorithm for the estimation and compensation of the slowly varying additive or multiplicative noise, supported by a pre-filtering technique for Gaussian and impulse noise elimination. The slowly varying behavior of the bias or gain field is assured by a smoothening filter that performs a context dependent averaging, based on a morphological criterion. The experiments using 2-D synthetic phantoms and real MR images show, that the proposed method provides accurate segmentation. The produced segmentation and fuzzy membership values can serve as excellent support for 3-D registration and segmentation techniques.

Object Manifold Alignment for Multi-Temporal High Resolution Remote Sensing Images Classification

NASA Astrophysics Data System (ADS)

Gao, G.; Zhang, M.; Gu, Y.

2017-05-01

Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, "pepper and salt" appears and classification results will be effected when the pixelwise classification algorithms are applied to high-resolution satellite images, in which the spatial relationship among the pixels is ignored. For classifying the multi-temporal high resolution images with limited labelled samples, spectral drift and "pepper and salt" problem, an object-based manifold alignment method is proposed. Firstly, multi-temporal multispectral images are cut to superpixels by simple linear iterative clustering (SLIC) respectively. Secondly, some features obtained from superpixels are formed as vector. Thirdly, a majority voting manifold alignment method aiming at solving high resolution problem is proposed and mapping the vector data to alignment space. At last, all the data in the alignment space are classified by using KNN method. Multi-temporal images from different areas or the same area are both considered in this paper. In the experiments, 2 groups of multi-temporal HR images collected by China GF1 and GF2 satellites are used for performance evaluation. Experimental results indicate that the proposed method not only has significantly outperforms than traditional domain adaptation methods in classification accuracy, but also effectively overcome the problem of "pepper and salt".

CLASH: A census of magnified star-forming galaxies at z ∼ 6-8

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

Bradley, L. D.; Coe, D.; Postman, M.

2014-09-01

We utilize 16 band Hubble Space Telescope (HST) observations of 18 lensing clusters obtained as part of the Cluster Lensing And Supernova survey with Hubble (CLASH) Multi-Cycle Treasury program to search for z ∼ 6-8 galaxies. We report the discovery of 204, 45, and 13 Lyman-break galaxy candidates at z ∼ 6, z ∼ 7, and z ∼ 8, respectively, identified from purely photometric redshift selections. This large sample, representing nearly an order of magnitude increase in the number of magnified star-forming galaxies at z ∼ 6-8 presented to date, is unique in that we have observations in four WFC3/UVISmore » UV, seven ACS/WFC optical, and all five WFC3/IR broadband filters, which enable very accurate photometric redshift selections. We construct detailed lensing models for 17 of the 18 clusters to estimate object magnifications and to identify two new multiply lensed z ≳ 6 candidates. The median magnifications over the 17 clusters are 4, 4, and 5 for the z ∼ 6, z ∼ 7, and z ∼ 8 samples, respectively, over an average area of 4.5 arcmin{sup 2} per cluster. We compare our observed number counts with expectations based on convolving 'blank' field UV luminosity functions through our cluster lens models and find rough agreement down to ∼27 mag, where we begin to suffer significant incompleteness. In all three redshift bins, we find a higher number density at brighter observed magnitudes than the field predictions, empirically demonstrating for the first time the enhanced efficiency of lensing clusters over field surveys. Our number counts also are in general agreement with the lensed expectations from the cluster models, especially at z ∼ 6, where we have the best statistics.« less

SciSpark: Highly Interactive and Scalable Model Evaluation and Climate Metrics

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Mattmann, C. A.; Waliser, D. E.; Kim, J.; Loikith, P.; Lee, H.; McGibbney, L. J.; Whitehall, K. D.

2014-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We are developing a lightning fast Big Data technology called SciSpark based on ApacheTM Spark. Spark implements the map-reduce paradigm for parallel computing on a cluster, but emphasizes in-memory computation, "spilling" to disk only as needed, and so outperforms the disk-based ApacheTM Hadoop by 100x in memory and by 10x on disk, and makes iterative algorithms feasible. SciSpark will enable scalable model evaluation by executing large-scale comparisons of A-Train satellite observations to model grids on a cluster of 100 to 1000 compute nodes. This 2nd generation capability for NASA's Regional Climate Model Evaluation System (RCMES) will compute simple climate metrics at interactive speeds, and extend to quite sophisticated iterative algorithms such as machine-learning (ML) based clustering of temperature PDFs, and even graph-based algorithms for searching for Mesocale Convective Complexes. The goals of SciSpark are to: (1) Decrease the time to compute comparison statistics and plots from minutes to seconds; (2) Allow for interactive exploration of time-series properties over seasons and years; (3) Decrease the time for satellite data ingestion into RCMES to hours; (4) Allow for Level-2 comparisons with higher-order statistics or PDF's in minutes to hours; and (5) Move RCMES into a near real time decision-making platform. We will report on: the architecture and design of SciSpark, our efforts to integrate climate science algorithms in Python and Scala, parallel ingest and partitioning (sharding) of A-Train satellite observations from HDF files and model grids from netCDF files, first parallel runs to compute comparison statistics and PDF's, and first metrics quantifying parallel speedups and memory & disk usage.

Cross-scale analysis of cluster correspondence using different operational neighborhoods

NASA Astrophysics Data System (ADS)

Lu, Yongmei; Thill, Jean-Claude

2008-09-01

Cluster correspondence analysis examines the spatial autocorrelation of multi-location events at the local scale. This paper argues that patterns of cluster correspondence are highly sensitive to the definition of operational neighborhoods that form the spatial units of analysis. A subset of multi-location events is examined for cluster correspondence if they are associated with the same operational neighborhood. This paper discusses the construction of operational neighborhoods for cluster correspondence analysis based on the spatial properties of the underlying zoning system and the scales at which the zones are aggregated into neighborhoods. Impacts of this construction on the degree of cluster correspondence are also analyzed. Empirical analyses of cluster correspondence between paired vehicle theft and recovery locations are conducted on different zoning methods and across a series of geographic scales and the dynamics of cluster correspondence patterns are discussed.

High-Throughput Screening of Chemical Effects on Steroidogenesis Using H295R Human Adrenocortical Carcinoma Cells.

PubMed

Karmaus, Agnes L; Toole, Colleen M; Filer, Dayne L; Lewis, Kenneth C; Martin, Matthew T

2016-04-01

Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2060 chemical samples on steroidogenesis via high-performance liquid chromatography followed by tandem mass spectrometry quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a 3 stage screening strategy. The first stage established the maximum tolerated concentration (MTC; ≥ 70% viability) per sample. The second stage quantified changes in hormone levels at the MTC whereas the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were prestimulated with 10 µM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2060 chemical samples evaluated, 524 samples were selected for 6-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17β-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into 5 distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A distinct pattern was observed between imidazole and triazole fungicides suggesting potentially distinct mechanisms of action. From a chemical testing and prioritization perspective, this assay platform provides a robust model for high-throughput screening of chemicals for effects on steroidogenesis. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology.

High-Throughput Screening of Chemical Effects on Steroidogenesis Using H295R Human Adrenocortical Carcinoma Cells

PubMed Central

Toole, Colleen M.; Filer, Dayne L.; Lewis, Kenneth C.; Martin, Matthew T.

2016-01-01

Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2060 chemical samples on steroidogenesis via high-performance liquid chromatography followed by tandem mass spectrometry quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a 3 stage screening strategy. The first stage established the maximum tolerated concentration (MTC; ≥ 70% viability) per sample. The second stage quantified changes in hormone levels at the MTC whereas the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were prestimulated with 10 µM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2060 chemical samples evaluated, 524 samples were selected for 6-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17β-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into 5 distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A distinct pattern was observed between imidazole and triazole fungicides suggesting potentially distinct mechanisms of action. From a chemical testing and prioritization perspective, this assay platform provides a robust model for high-throughput screening of chemicals for effects on steroidogenesis. PMID:26781511

Automated flow cytometric analysis across large numbers of samples and cell types.

PubMed

Chen, Xiaoyi; Hasan, Milena; Libri, Valentina; Urrutia, Alejandra; Beitz, Benoît; Rouilly, Vincent; Duffy, Darragh; Patin, Étienne; Chalmond, Bernard; Rogge, Lars; Quintana-Murci, Lluis; Albert, Matthew L; Schwikowski, Benno

2015-04-01

Multi-parametric flow cytometry is a key technology for characterization of immune cell phenotypes. However, robust high-dimensional post-analytic strategies for automated data analysis in large numbers of donors are still lacking. Here, we report a computational pipeline, called FlowGM, which minimizes operator input, is insensitive to compensation settings, and can be adapted to different analytic panels. A Gaussian Mixture Model (GMM)-based approach was utilized for initial clustering, with the number of clusters determined using Bayesian Information Criterion. Meta-clustering in a reference donor permitted automated identification of 24 cell types across four panels. Cluster labels were integrated into FCS files, thus permitting comparisons to manual gating. Cell numbers and coefficient of variation (CV) were similar between FlowGM and conventional gating for lymphocyte populations, but notably FlowGM provided improved discrimination of "hard-to-gate" monocyte and dendritic cell (DC) subsets. FlowGM thus provides rapid high-dimensional analysis of cell phenotypes and is amenable to cohort studies. Copyright © 2015. Published by Elsevier Inc.

Design of a Phase III cluster randomized trial to assess the efficacy and safety of a malaria transmission blocking vaccine.

PubMed

Delrieu, Isabelle; Leboulleux, Didier; Ivinson, Karen; Gessner, Bradford D

2015-03-24

Vaccines interrupting Plasmodium falciparum malaria transmission targeting sexual, sporogonic, or mosquito-stage antigens (SSM-VIMT) are currently under development to reduce malaria transmission. An international group of malaria experts was established to evaluate the feasibility and optimal design of a Phase III cluster randomized trial (CRT) that could support regulatory review and approval of an SSM-VIMT. The consensus design is a CRT with a sentinel population randomly selected from defined inner and buffer zones in each cluster, a cluster size sufficient to assess true vaccine efficacy in the inner zone, and inclusion of ongoing assessment of vaccine impact stratified by distance of residence from the cluster edge. Trials should be conducted first in areas of moderate transmission, where SSM-VIMT impact should be greatest. Sample size estimates suggest that such a trial is feasible, and within the range of previously supported trials of malaria interventions, although substantial issues to implementation exist. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao

1991-01-01

Various types of multistage decoding for multilevel block modulation codes, in which the decoding of a component code at each stage can be either soft decision or hard decision, maximum likelihood or bounded distance are discussed. Error performance for codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. It was found that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. It was found that the difference in performance between the suboptimum multi-stage soft decision maximum likelihood decoding of a modulation code and the single stage optimum decoding of the overall code is very small, only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Helium segregation on surfaces of plasma-exposed tungsten

NASA Astrophysics Data System (ADS)

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; Hammond, Karl D.; Wirth, Brian D.

2016-02-01

We report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He n (1  ⩽  n  ⩽  7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides the thermodynamic driving force for surface segregation. This elastic interaction force induces drift fluxes of these mobile He n clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters’ drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. These near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

PubMed Central

Borri, Marco; Schmidt, Maria A.; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M.; Partridge, Mike; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Katie L.; Leach, Martin O.

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

Building Multi-Discipline, Multi-Format Digital Libraries Using Clusters and Buckets. Degree rewarded by Old Dominion Univ. on Aug. 1997

NASA Technical Reports Server (NTRS)

Nelson, Michael L.

1997-01-01

Our objective was to study the feasibility of extending the Dienst protocol to enable a multi-discipline, multi-format digital library. We implemented two new technologies: cluster functionality and publishing buckets. We have designed a possible implementation of clusters and buckets, and have prototyped some aspects of the resultant digital library. Currently, digital libraries are segregated by the disciplines they serve (computer science, aeronautics, etc.), and by the format of their holdings (reports, software, datasets, etc.). NCSTRL+ is a multi-discipline, multi-format digital library (DL) prototype created to explore the feasibility of the design and implementation issues involved with created a unified, canonical scientific and technical information (STI) DL. NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible DL that provides access to over 80 university departments and laboratories. We have extended the Dienst protocol (version 4.1.8), the protocol underlying NCSTRL, to provide the ability to cluster independent collections into a logically centralized DL based upon subject category classification, type of organization, and genre of material. The concept of buckets provides a mechanism for publishing and managing logically linked entities with multiple data formats.

The Kormendy relation of galaxies in the Frontier Fields clusters: Abell S1063 and MACS J1149.5+2223

NASA Astrophysics Data System (ADS)

Tortorelli, Luca; Mercurio, Amata; Paolillo, Maurizio; Rosati, Piero; Gargiulo, Adriana; Gobat, Raphael; Balestra, Italo; Caminha, G. B.; Annunziatella, Marianna; Grillo, Claudio; Lombardi, Marco; Nonino, Mario; Rettura, Alessandro; Sartoris, Barbara; Strazzullo, Veronica

2018-06-01

We analyse the Kormendy relations (KRs) of the two Frontier Fields clusters, Abell S1063, at z = 0.348, and MACS J1149.5+2223, at z = 0.542, exploiting very deep Hubble Space Telescope photometry and Very Large Telescope (VLT)/Multi Unit Spectroscopic Explorer (MUSE) integral field spectroscopy. With this novel data set, we are able to investigate how the KR parameters depend on the cluster galaxy sample selection and how this affects studies of galaxy evolution based on the KR. We define and compare four different galaxy samples according to (a) Sérsic indices: early-type (`ETG'), (b) visual inspection: `ellipticals', (c) colours: `red', (d) spectral properties: `passive'. The classification is performed for a complete sample of galaxies with mF814W ≤ 22.5 ABmag (M* ≳ 1010.0 M⊙). To derive robust galaxy structural parameters, we use two methods: (1) an iterative estimate of structural parameters using images of increasing size, in order to deal with closely separated galaxies and (2) different background estimations, to deal with the intracluster light contamination. The comparison between the KRs obtained from the different samples suggests that the sample selection could affect the estimate of the best-fitting KR parameters. The KR built with ETGs is fully consistent with the one obtained for ellipticals and passive. On the other hand, the KR slope built on the red sample is only marginally consistent with those obtained with the other samples. We also release the photometric catalogue with structural parameters for the galaxies included in the present analysis.

Differences in Flower Transcriptome between Grapevine Clones Are Related to Their Cluster Compactness, Fruitfulness, and Berry Size

PubMed Central

Grimplet, Jérôme; Tello, Javier; Laguna, Natalia; Ibáñez, Javier

2017-01-01

Grapevine cluster compactness has a clear impact on fruit quality and health status, as clusters with greater compactness are more susceptible to pests and diseases and ripen more asynchronously. Different parameters related to inflorescence and cluster architecture (length, width, branching, etc.), fruitfulness (number of berries, number of seeds) and berry size (length, width) contribute to the final level of compactness. From a collection of 501 clones of cultivar Garnacha Tinta, two compact and two loose clones with stable differences for cluster compactness-related traits were selected and phenotyped. Key organs and developmental stages were selected for sampling and transcriptomic analyses. Comparison of global gene expression patterns in flowers at the end of bloom allowed identification of potential gene networks with a role in determining the final berry number, berry size and ultimately cluster compactness. A large portion of the differentially expressed genes were found in networks related to cell division (carbohydrates uptake, cell wall metabolism, cell cycle, nucleic acids metabolism, cell division, DNA repair). Their greater expression level in flowers of compact clones indicated that the number of berries and the berry size at ripening appear related to the rate of cell replication in flowers during the early growth stages after pollination. In addition, fluctuations in auxin and gibberellin signaling and transport related gene expression support that they play a central role in fruit set and impact berry number and size. Other hormones, such as ethylene and jasmonate may differentially regulate indirect effects, such as defense mechanisms activation or polyphenols production. This is the first transcriptomic based analysis focused on the discovery of the underlying gene networks involved in grapevine traits of grapevine cluster compactness, berry number and berry size. PMID:28496449

Differences in Flower Transcriptome between Grapevine Clones Are Related to Their Cluster Compactness, Fruitfulness, and Berry Size.

PubMed

Grimplet, Jérôme; Tello, Javier; Laguna, Natalia; Ibáñez, Javier

2017-01-01

Grapevine cluster compactness has a clear impact on fruit quality and health status, as clusters with greater compactness are more susceptible to pests and diseases and ripen more asynchronously. Different parameters related to inflorescence and cluster architecture (length, width, branching, etc.), fruitfulness (number of berries, number of seeds) and berry size (length, width) contribute to the final level of compactness. From a collection of 501 clones of cultivar Garnacha Tinta, two compact and two loose clones with stable differences for cluster compactness-related traits were selected and phenotyped. Key organs and developmental stages were selected for sampling and transcriptomic analyses. Comparison of global gene expression patterns in flowers at the end of bloom allowed identification of potential gene networks with a role in determining the final berry number, berry size and ultimately cluster compactness. A large portion of the differentially expressed genes were found in networks related to cell division (carbohydrates uptake, cell wall metabolism, cell cycle, nucleic acids metabolism, cell division, DNA repair). Their greater expression level in flowers of compact clones indicated that the number of berries and the berry size at ripening appear related to the rate of cell replication in flowers during the early growth stages after pollination. In addition, fluctuations in auxin and gibberellin signaling and transport related gene expression support that they play a central role in fruit set and impact berry number and size. Other hormones, such as ethylene and jasmonate may differentially regulate indirect effects, such as defense mechanisms activation or polyphenols production. This is the first transcriptomic based analysis focused on the discovery of the underlying gene networks involved in grapevine traits of grapevine cluster compactness, berry number and berry size.

Novel histopathologic feature identified through image analysis augments stage II colorectal cancer clinical reporting

PubMed Central

Caie, Peter D.; Zhou, Ying; Turnbull, Arran K.; Oniscu, Anca; Harrison, David J.

2016-01-01

A number of candidate histopathologic factors show promise in identifying stage II colorectal cancer (CRC) patients at a high risk of disease-specific death, however they can suffer from low reproducibility and none have replaced classical pathologic staging. We developed an image analysis algorithm which standardized the quantification of specific histopathologic features and exported a multi-parametric feature-set captured without bias. The image analysis algorithm was executed across a training set (n = 50) and the resultant big data was distilled through decision tree modelling to identify the most informative parameters to sub-categorize stage II CRC patients. The most significant, and novel, parameter identified was the ‘sum area of poorly differentiated clusters’ (AreaPDC). This feature was validated across a second cohort of stage II CRC patients (n = 134) (HR = 4; 95% CI, 1.5– 11). Finally, the AreaPDC was integrated with the significant features within the clinical pathology report, pT stage and differentiation, into a novel prognostic index (HR = 7.5; 95% CI, 3–18.5) which improved upon current clinical staging (HR = 4.26; 95% CI, 1.7– 10.3). The identification of poorly differentiated clusters as being highly significant in disease progression presents evidence to suggest that these features could be the source of novel targets to decrease the risk of disease specific death. PMID:27322148

Global, Multi-Objective Trajectory Optimization With Parametric Spreading

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob A.; Phillips, Sean M.; Hughes, Kyle M.

2017-01-01

Mission design problems are often characterized by multiple, competing trajectory optimization objectives. Recent multi-objective trajectory optimization formulations enable generation of globally-optimal, Pareto solutions via a multi-objective genetic algorithm. A byproduct of these formulations is that clustering in design space can occur in evolving the population towards the Pareto front. This clustering can be a drawback, however, if parametric evaluations of design variables are desired. This effort addresses clustering by incorporating operators that encourage a uniform spread over specified design variables while maintaining Pareto front representation. The algorithm is demonstrated on a Neptune orbiter mission, and enhanced multidimensional visualization strategies are presented.

Clustering of Multi-Temporal Fully Polarimetric L-Band SAR Data for Agricultural Land Cover Mapping

NASA Astrophysics Data System (ADS)

Tamiminia, H.; Homayouni, S.; Safari, A.

2015-12-01

Recently, the unique capabilities of Polarimetric Synthetic Aperture Radar (PolSAR) sensors make them an important and efficient tool for natural resources and environmental applications, such as land cover and crop classification. The aim of this paper is to classify multi-temporal full polarimetric SAR data using kernel-based fuzzy C-means clustering method, over an agricultural region. This method starts with transforming input data into the higher dimensional space using kernel functions and then clustering them in the feature space. Feature space, due to its inherent properties, has the ability to take in account the nonlinear and complex nature of polarimetric data. Several SAR polarimetric features extracted using target decomposition algorithms. Features from Cloude-Pottier, Freeman-Durden and Yamaguchi algorithms used as inputs for the clustering. This method was applied to multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Canada, during June and July in 2012. The results demonstrate the efficiency of this approach with respect to the classical methods. In addition, using multi-temporal data in the clustering process helped to investigate the phenological cycle of plants and significantly improved the performance of agricultural land cover mapping.

Investigating the health profile of patients with end-stage renal failure receiving peritoneal dialysis: a cluster analysis.

PubMed

Chan, M F; Wong, Frances K Y; Chow, Susan K Y

2010-03-01

To determine whether the patients with end stage renal failure can be differentiated into several subtypes based on five main variables. There is a lack of interventional research linking to clinical outcomes among the patients with end stage renal failure in Hong Kong and with no clear evidence of differences in terms of their clinical/health outcomes and characteristics. A cross-sectional survey. Data were collected using a structured questionnaire. One hundred and fifty-three patients with end stage renal failure were recruited during 2007 at three renal centres in Hong Kong. Five main variables were employed: predisposing characteristic, enabling resources, quality of life, symptom control and self-care adherence. A cluster analysis yielded two clusters. Each cluster represented a different profile of patients with end stage renal failure. Cluster A consisted of 49.7% (n = 76) and Cluster B consisted of 50.3% (n = 77) of the patients. Cluster A patients, more of whom were women, were older, less educated, had higher quality of life scores, a better adherence rate and more had received nursing care supports than patients in Cluster B. We have identified two groupings of patients with end stage renal failure who were experiencing unique health profile. Nursing support services may have an effect on patient health outcomes but only on a group of patients whose profile is similar to the patients in Cluster A and not for patients in Cluster B. A clear profile may help health care professional make appropriate strategies to target a specific group of patients to improve patient outcomes. The identification of risk for future health-care use could enable better targeting of interventional strategies in these groups. The results of this study might provide health care professionals with a model to design specified interventions to improve life quality for each profile group.

Estimation of Nationwide Vaccination Coverage and Comparison of Interview and Telephone Survey Methodology for Estimating Vaccination Status

PubMed Central

Park, Boyoung; Lee, Yeon-Kyeng; Cho, Lisa Y.; Go, Un Yeong; Yang, Jae Jeong; Ma, Seung Hyun; Choi, Bo-Youl; Lee, Moo-Sik; Lee, Jin-Seok; Choi, Eun Hwa; Lee, Hoan Jong

2011-01-01

This study compared interview and telephone surveys to select the better method for regularly estimating nationwide vaccination coverage rates in Korea. Interview surveys using multi-stage cluster sampling and telephone surveys using stratified random sampling were conducted. Nationwide coverage rates were estimated in subjects with vaccination cards in the interview survey. The interview survey relative to the telephone survey showed a higher response rate, lower missing rate, higher validity and a less difference in vaccination coverage rates between card owners and non-owners. Primary vaccination coverage rate was greater than 90% except for the fourth dose of DTaP (diphtheria/tetanus/pertussis), the third dose of polio, and the third dose of Japanese B encephalitis (JBE). The DTaP4: Polio3: MMR1 fully vaccination rate was 62.0% and BCG1:HepB3:DTaP4:Polio3:MMR1 was 59.5%. For age-appropriate vaccination, the coverage rate was 50%-80%. We concluded that the interview survey was better than the telephone survey. These results can be applied to countries with incomplete registry and decreasing rates of landline telephone coverage due to increased cell phone usage and countries. Among mandatory vaccines, efforts to increase vaccination rate for the fourth dose of DTaP, the third dose of polio, JBE and regular vaccinations at recommended periods should be conducted in Korea. PMID:21655054

Assessments of Ebola knowledge, attitudes and practices in Forécariah, Guinea and Kambia, Sierra Leone, July–August 2015

PubMed Central

Bunnell, Rebecca; Robinson, Susan; Jalloh, Mohammad B.; Barry, Alpha Mamoudou; Corker, Jamaica; Sengeh, Paul; VanSteelandt, Amanda; Li, Wenshu; Dafae, Foday; Diallo, Alpha Ahmadou; Martel, Lise D.; Hersey, Sara; Marston, Barbara; Morgan, Oliver; Redd, John T.

2017-01-01

The border region of Forécariah (Guinea) and Kambia (Sierra Leone) was of immense interest to the West Africa Ebola response. Cross-sectional household surveys with multi-stage cluster sampling procedure were used to collect random samples from Kambia (n = 635) in July 2015 and Forécariah (n = 502) in August 2015 to assess public knowledge, attitudes and practices related to Ebola. Knowledge of the disease was high in both places, and handwashing with soap and water was the most widespread prevention practice. Acceptance of safe alternatives to traditional burials was significantly lower in Forécariah compared with Kambia. In both locations, there was a minority who held discriminatory attitudes towards survivors. Radio was the predominant source of information in both locations, but those from Kambia were more likely to have received Ebola information from community sources (mosques/churches, community meetings or health workers) compared with those in Forécariah. These findings contextualize the utility of Ebola health messaging during the epidemic and suggest the importance of continued partnership with community leaders, including religious leaders, as a prominent part of future public health protection. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’. PMID:28396475

Assessments of Ebola knowledge, attitudes and practices in Forécariah, Guinea and Kambia, Sierra Leone, July-August 2015.

PubMed

Jalloh, Mohamed F; Bunnell, Rebecca; Robinson, Susan; Jalloh, Mohammad B; Barry, Alpha Mamoudou; Corker, Jamaica; Sengeh, Paul; VanSteelandt, Amanda; Li, Wenshu; Dafae, Foday; Diallo, Alpha Ahmadou; Martel, Lise D; Hersey, Sara; Marston, Barbara; Morgan, Oliver; Redd, John T

2017-05-26

The border region of Forécariah (Guinea) and Kambia (Sierra Leone) was of immense interest to the West Africa Ebola response. Cross-sectional household surveys with multi-stage cluster sampling procedure were used to collect random samples from Kambia ( n = 635) in July 2015 and Forécariah ( n = 502) in August 2015 to assess public knowledge, attitudes and practices related to Ebola. Knowledge of the disease was high in both places, and handwashing with soap and water was the most widespread prevention practice. Acceptance of safe alternatives to traditional burials was significantly lower in Forécariah compared with Kambia. In both locations, there was a minority who held discriminatory attitudes towards survivors. Radio was the predominant source of information in both locations, but those from Kambia were more likely to have received Ebola information from community sources (mosques/churches, community meetings or health workers) compared with those in Forécariah. These findings contextualize the utility of Ebola health messaging during the epidemic and suggest the importance of continued partnership with community leaders, including religious leaders, as a prominent part of future public health protection.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'. © 2017 The Author(s).

Prescribing Patterns in Outpatient Clinics of Township Hospitals in China: A Comparative Study before and after the 2009 Health System Reform.

PubMed

Ding, Ding; Pan, Qingxia; Shan, Linghan; Liu, Chaojie; Gao, Lijun; Hao, Yanhua; Song, Jian; Ning, Ning; Cui, Yu; Li, Ye; Qi, Xinye; Liang, Chao; Wu, Qunhong; Liu, Guoxiang

2016-07-05

China introduced a series of health reforms in 2009, including a national essential medicines policy and a medical insurance system for primary care institutions. This study aimed to determine the changing prescribing patterns associated with those reforms in township hospitals. A multi-stage stratified random cluster sampling method was adopted to identify 29 township hospitals from six counties in three provinces. A total of 2899 prescriptions were collected from the participating township hospitals using a systematic random sampling strategy. Seven prescribing indicators were calculated and compared between 2008 and 2013, assessing use of medicines (antibiotics and adrenal corticosteroids) and polypharmacy, administration route of medicines (injections), and affordability of medicines. Significant changes in prescribing patterns were found. The average number of medicines and costs per-prescription dropped by about 50%. The percentage of prescriptions requiring antibiotics declined from 54% to 38%. The percentage of prescriptions requiring adrenal corticosteroid declined from 14% to 4%. The percentage of prescriptions requiring injections declined from 54% to 25%. Despite similar changing patterns, significant regional differences were observed. Significant changes in prescribing patterns are evident in township hospitals in China. Overprescription of antibiotics, injections and adrenal corticosteroids has been reduced. However, salient regional disparities still exist. Further studies are needed to determine potential shifts in the risk of the inappropriate use of medicines from primary care settings to metropolitan hospitals.

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

Treesearch

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

2015-01-01

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

Establishing the Baseline Height and Weight Status of New Hampshire Head Start Children, 2007-2008

ERIC Educational Resources Information Center

Blaney, David D.; Flynn, Regina T.; Martin, Nancy R.; Anderson, Ludmila

2010-01-01

We report on a standardized survey of height and weight status of children attending the New Hampshire Head Start Program during the 2007-2008 school year. Baseline prevalence estimates of overweight and obesity are needed for obesity prevention activities and intervention. We selected a random one-stage cluster sample and screened 629 children…

Biometric templates selection and update using quality measures

NASA Astrophysics Data System (ADS)

Abboud, Ali J.; Jassim, Sabah A.

2012-06-01

To deal with severe variation in recording conditions, most biometric systems acquire multiple biometric samples, at the enrolment stage, for the same person and then extract their individual biometric feature vectors and store them in the gallery in the form of biometric template(s), labelled with the person's identity. The number of samples/templates and the choice of the most appropriate templates influence the performance of the system. The desired biometric template(s) selection technique must aim to control the run time and storage requirements while improving the recognition accuracy of the biometric system. This paper is devoted to elaborating on and discussing a new two stages approach for biometric templates selection and update. This approach uses a quality-based clustering, followed by a special criterion for the selection of an ultimate set of biometric templates from the various clusters. This approach is developed to select adaptively a specific number of templates for each individual. The number of biometric templates depends mainly on the performance of each individual (i.e. gallery size should be optimised to meet the needs of each target individual). These experiments have been conducted on two face image databases and their results will demonstrate the effectiveness of proposed quality-guided approach.

A versatile rotary-stage high frequency probe station for studying magnetic films and devices

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

He, Shikun; Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371; Meng, Zhaoliang

We present a rotary-stage microwave probe station suitable for magnetic films and spintronic devices. Two stages, one for field rotation from parallel to perpendicular to the sample plane (out-of-plane) and the other intended for field rotation within the sample plane (in-plane) have been designed. The sample probes and micro-positioners are rotated simultaneously with the stages, which allows the field orientation to cover θ from 0{sup ∘} to 90{sup ∘} and φ from 0{sup ∘} to 360{sup ∘}. θ and φ being the angle between the direction of current flow and field in a out-of-plane and an in-plane rotation, respectively. Themore » operation frequency is up to 40 GHz and the magnetic field up to 1 T. The sample holder vision system and probe assembly are compactly designed for the probes to land on a wafer with diameter up to 3 cm. Using homemade multi-pin probes and commercially available high frequency probes, several applications including 4-probe DC measurements, the determination of domain wall velocity, and spin transfer torque ferromagnetic resonance are demonstrated.« less

Novel product ions of 2-aminoanilide and benzimidazole Ag(I) complexes using electrospray ionization with multi-stage tandem mass spectrometry.

PubMed

Johnson, Byron S; Burinsky, David J; Burova, Svetlana A; Davis, Roman; Fitzgerald, Russ N; Matsuoka, Richard T

2012-05-15

The 2-aminoaniline scaffold is of significant value to the pharmaceutical industry and is embedded in a number of pharmacophores including 2-aminoanilides and benzimidazoles. A novel application of coordination ion spray mass spectrometry (CIS-MS) for interrogating the silver ion (Ag(+)) complexes of a homologous series of these compounds using multi-stage tandem mass spectrometry is described. Unlike the ubiquitous alkali metal ion complexes, Ag(+) complexes of 2-aminoanilides and benzimidazoles were found to yield [M - H](+) ions in significant abundance via gas-phase elimination of the metal hydride (AgH) resulting in unique product ion cascades. Sample introduction was by liquid chromatography with mass spectrometry analysis performed on a hybrid linear ion trap/orbitrap instrument capable of high-resolution measurements. Rigorous structural characterization by multi-stage tandem mass spectrometry using [M +  H](+), [M - H](-) and [M - H](+) precursor ions derived from ESI and CIS experiments was performed for the homologous series of 2-aminoanilide and benzimidazole compounds. A full tabular comparison of structural information resulting from these product ion cascades was produced. Multi-stage tandem mass spectrometry of [M - H](+) ions resulting from Ag(+) complexes of 2-aminoanilides and benzimidazoles in CIS-MS experiments produced unique product ion cascades that exhibited complementary structural information to that obtained from tandem mass spectrometry of [M  +  H](+) and [M - H](-) ions by electrospray ionization (ESI). These observations may be broadly applicable to other compounds that are observed to form Ag(+) complexes and eliminate AgH. Copyright © 2012 John Wiley & Sons, Ltd.

HST Grism Confirmation of 16 Structures at 1.4 < z < 2.8 from the Clusters Around Radio-Loud AGN (CARLA) Survey

NASA Astrophysics Data System (ADS)

Noirot, Gaël; Stern, Daniel; Mei, Simona; Wylezalek, Dominika; Cooke, Elizabeth A.; De Breuck, Carlos; Galametz, Audrey; Hatch, Nina A.; Vernet, Joël; Brodwin, Mark; Eisenhardt, Peter; Gonzalez, Anthony H.; Jarvis, Matt; Rettura, Alessandro; Seymour, Nick; Stanford, S. A.

2018-05-01

We report spectroscopic results from our 40-orbit Hubble Space Telescope slitless grism spectroscopy program observing the 20 densest Clusters Around Radio-Loud AGN (CARLA) candidate galaxy clusters at 1.4 < z < 2.8. These candidate rich structures, among the richest and most distant known, were identified on the basis of [3.6]–[4.5] color from a 408 hr multi-cycle Spitzer program targeting 420 distant radio-loud AGN. We report the spectroscopic confirmation of 16 distant structures at 1.4 < z < 2.8 associated with the targeted powerful high-redshift radio-loud AGN. We also report the serendipitous discovery and spectroscopic confirmation of seven additional structures at 0.87 < z < 2.12 not associated with the targeted radio-loud AGN. We find that 1010–1011 M ⊙ member galaxies of our confirmed CARLA structures form significantly fewer stars than their field counterparts at all redshifts within 1.4 ≤ z ≤ 2. We also observe higher star-forming activity in the structure cores up to z = 2, finding similar trends as cluster surveys at slightly lower redshifts (1.0 < z < 1.5). By design, our efficient strategy of obtaining just two grism orbits per field only obtains spectroscopic confirmation of emission line galaxies. Deeper spectroscopy will be required to study the population of evolved, massive galaxies in these (forming) clusters. Lacking multi-band coverage of the fields, we adopt a very conservative approach of calling all confirmations “structures,” although we note that a number of features are consistent with some of them being bona fide galaxy clusters. Together this survey represents a unique and large homogenous sample of spectroscopically confirmed structures at high redshifts, potentially more than doubling the census of confirmed, massive clusters at z > 1.4.

Three gravitationally lensed supernovae behind clash galaxy clusters

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

Patel, Brandon; McCully, Curtis; Jha, Saurabh W.

2014-05-01

We report observations of three gravitationally lensed supernovae (SNe) in the Cluster Lensing And Supernova survey with Hubble (CLASH) Multi-Cycle Treasury program. These objects, SN CLO12Car (z = 1.28), SN CLN12Did (z = 0.85), and SN CLA11Tib (z = 1.14), are located behind three different clusters, MACSJ1720.2+3536 (z = 0.391), RXJ1532.9+3021 (z = 0.345), and A383 (z = 0.187), respectively. Each SN was detected in Hubble Space Telescope optical and infrared images. Based on photometric classification, we find that SNe CLO12Car and CLN12Did are likely to be Type Ia supernovae (SNe Ia), while the classification of SN CLA11Tib is inconclusive.more » Using multi-color light-curve fits to determine a standardized SN Ia luminosity distance, we infer that SN CLO12Car was ∼1.0 ± 0.2 mag brighter than field SNe Ia at a similar redshift and ascribe this to gravitational lens magnification. Similarly, SN CLN12Did is ∼0.2 ± 0.2 mag brighter than field SNe Ia. We derive independent estimates of the predicted magnification from CLASH strong+weak-lensing maps of the clusters (in magnitude units, 2.5 log{sub 10}μ): 0.83 ± 0.16 mag for SN CLO12Car, 0.28 ± 0.08 mag for SN CLN12Did, and 0.43 ± 0.11 mag for SN CLA11Tib. The two SNe Ia provide a new test of the cluster lens model predictions: we find that the magnifications based on the SN Ia brightness and those predicted by the lens maps are consistent. Our results herald the promise of future observations of samples of cluster-lensed SNe Ia (from the ground or space) to help illuminate the dark-matter distribution in clusters of galaxies, through the direct determination of absolute magnifications.« less

Three Gravitationally Lensed Supernovae Behind Clash Galaxy Clusters

NASA Technical Reports Server (NTRS)

Patel, Brandon; McCully, Curtis; Jha, Saurbh W.; Rodney, Steven A.; Jones, David O.; Graur, Or; Merten, Julian; Zitrin, Adi; Riess, Adam G.; Matheson, Thomas;

A highly efficient multi-core algorithm for clustering extremely large datasets

PubMed Central

2010-01-01

Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer. PMID:20370922

Non-thermal emission and dynamical state of massive galaxy clusters from CLASH sample

NASA Astrophysics Data System (ADS)

Pandey-Pommier, M.; Richard, J.; Combes, F.; Edge, A.; Guiderdoni, B.; Narasimha, D.; Bagchi, J.; Jacob, J.

2016-12-01

Massive galaxy clusters are the most violent large scale structures undergoing merger events in the Universe. Based upon their morphological properties in X-rays, they are classified as un-relaxed and relaxed clusters and often host (a fraction of them) different types of non-thermal radio emitting components, viz., 'haloes', 'mini-haloes', 'relics' and 'phoenix' within their Intra Cluster Medium (ICM). The radio haloes show steep (α = -1.2) and ultra steep (α < -1.5) spectral properties at low radio frequencies, giving important insights on the merger (pre or post) state of the cluster. Ultra steep spectrum radio halo emissions are rare and expected to be the dominating population to be discovered via LOFAR and SKA in the future. Further, the distribution of matter (morphological information), alignment of hot X-ray emitting gas from the ICM with the total mass (dark + baryonic matter) and the bright cluster galaxy (BCG) is generally used to study the dynamical state of the cluster. We present here a multi wavelength study on 14 massive clusters from the CLASH survey and show the correlation between the state of their merger in X-ray and spectral properties (1.4 GHz - 150 MHz) at radio wavelengths. Using the optical data we also discuss about the gas-mass alignment, in order to understand the interplay between dark and baryonic matter in massive galaxy clusters.

Size-guided multi-seed heuristic method for geometry optimization of clusters: Application to benzene clusters.

PubMed

Takeuchi, Hiroshi

2018-05-08

Since searching for the global minimum on the potential energy surface of a cluster is very difficult, many geometry optimization methods have been proposed, in which initial geometries are randomly generated and subsequently improved with different algorithms. In this study, a size-guided multi-seed heuristic method is developed and applied to benzene clusters. It produces initial configurations of the cluster with n molecules from the lowest-energy configurations of the cluster with n - 1 molecules (seeds). The initial geometries are further optimized with the geometrical perturbations previously used for molecular clusters. These steps are repeated until the size n satisfies a predefined one. The method locates putative global minima of benzene clusters with up to 65 molecules. The performance of the method is discussed using the computational cost, rates to locate the global minima, and energies of initial geometries. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Fractal Clustering and Knowledge-driven Validation Assessment for Gene Expression Profiling.

PubMed

Wang, Lu-Yong; Balasubramanian, Ammaiappan; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

DNA microarray experiments generate a substantial amount of information about the global gene expression. Gene expression profiles can be represented as points in multi-dimensional space. It is essential to identify relevant groups of genes in biomedical research. Clustering is helpful in pattern recognition in gene expression profiles. A number of clustering techniques have been introduced. However, these traditional methods mainly utilize shape-based assumption or some distance metric to cluster the points in multi-dimension linear Euclidean space. Their results shows poor consistence with the functional annotation of genes in previous validation study. From a novel different perspective, we propose fractal clustering method to cluster genes using intrinsic (fractal) dimension from modern geometry. This method clusters points in such a way that points in the same clusters are more self-affine among themselves than to the points in other clusters. We assess this method using annotation-based validation assessment for gene clusters. It shows that this method is superior in identifying functional related gene groups than other traditional methods.

Planck intermediate results: XXXVI. Optical identification and redshifts of Planck SZ sources with telescopes at the Canary Islands observatories

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-02-09

In this paper, we present the results of approximately three years of observations of Planck Sunyaev-Zeldovich (SZ) sources with telescopes at the Canary Islands observatories as part of the general optical follow-up programme undertaken by the Planck Collaboration. In total, 78 SZ sources are discussed. Deep-imaging observations were obtained for most of these sources; spectroscopic observations in either in long-slit or multi-object modes were obtained for many. We effectively used 37.5 clear nights. We found optical counterparts for 73 of the 78 candidates. This sample includes 53 spectroscopic redshift determinations, 20 of them obtained with a multi-object spectroscopic mode. Finally,more » the sample contains new redshifts for 27 Planck clusters that were not included in the first Planck SZ source catalogue (PSZ1).« less

Predicting cognitive function of the Malaysian elderly: a structural equation modelling approach.

PubMed

Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah; Shahar, Suzana

2018-01-01

The aim of this study was to identify the predictors of elderly's cognitive function based on biopsychosocial and cognitive reserve perspectives. The study included 2322 community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, biomarkers, psychosocial status, disability, and cognitive function. A biopsychosocial model of cognitive function was developed to test variables' predictive power on cognitive function. Statistical analyses were performed using SPSS (version 15.0) in conjunction with Analysis of Moment Structures Graphics (AMOS 7.0). The estimated theoretical model fitted the data well. Psychosocial stress and metabolic syndrome (MetS) negatively predicted cognitive function and psychosocial stress appeared as a main predictor. Socio-demographic characteristics, except gender, also had significant effects on cognitive function. However, disability failed to predict cognitive function. Several factors together may predict cognitive function in the Malaysian elderly population, and the variance accounted for it is large enough to be considered substantial. Key factor associated with the elderly's cognitive function seems to be psychosocial well-being. Thus, psychosocial well-being should be included in the elderly assessment, apart from medical conditions, both in clinical and community setting.

Moderating effect of intrinsic religiosity on the relationship between depression and cognitive function among community-dwelling older adults.

PubMed

Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah

2018-04-01

Research has found that depression in later life is associated with cognitive impairment. Thus, the mechanism to reduce the effect of depression on cognitive function is warranted. In this paper, we intend to examine whether intrinsic religiosity mediates the association between depression and cognitive function. The study included 2322 nationally representative community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, cognitive function, depression and intrinsic religiosity. A four-step moderated hierarchical regression analysis was employed to test the moderating effect. Statistical analyses were performed using SPSS (version 15.0). Bivariate analyses showed that both depression and intrinsic religiosity had significant relationships with cognitive function. In addition, four-step moderated hierarchical regression analysis revealed that the intrinsic religiosity moderated the association between depression and cognitive function, after controlling for selected socio-demographic characteristics. Intrinsic religiosity might reduce the negative effect of depression on cognitive function. Professionals who are working with depressed older adults should seek ways to improve their intrinsic religiosity as one of the strategies to prevent cognitive impairment.

Analysis on leisure patterns of the pre-elderly adults

PubMed Central

Cho, Gun-Sang; Yi, Eun-Surk

2013-01-01

The purpose of study is to analyze how leisure activities affect the near elders’ preparation for successful and productive aging. To achieve the purpose of the study, this study was conducted in 2012 and the data was collected by using multi-stage stratified cluster random sampling method in the great city area (6 places), metropolitan area (7 places), medium-sized urban area (6 places), and rural area (6 places). Out of the total number of 1,000 copies of questionnaire distributed to pre-elders (Baby-boomers from 55 yr to 64 yr), 978 were collected and used for data analysis. According to the result, the more time, frequency and intensity in leisure and recreational participation, the higher the satisfaction level and the happiness level in their life. It means that leisure and recreational activities play an important role for their life. In other words, for pre-elders, leisure activities can be regarded as the important element for preparation of their old age. Therefore, the leisure and recreation for pre-elderly adults should not be recognized as a tool for improving the economic productivity but for reinforcing the recovery resilience. PMID:24278898

Seroprevalence of antibodies to measles and rubella eight months after a vaccination campaign in the southeast of Iran.

PubMed

Izadi, Shahrokh; Zahraei, Seyed Mohsen; Mokhtari-Azad, Talat

2018-02-08

Eight months after the mass immunization campaign of November 2015 against measles and rubella in the southeast of Iran, in order to evaluate the sero-immunity level of the people living in the mentioned region, a serosurvey study was performed. Using a multi-stage probability proportional to size cluster sampling, the sera of 1,056 participants, ranging from 15 months to 20 years old, were tested for measles and rubella IgG antibodies in the National Reference Laboratory at Tehran University of Medical Sciences, Tehran, Iran. The seroprevalence rates of antibodies against measles and rubella in the age groups below 16 years were respectively 98.4 and 93.2%. In the age group of 16 to 20 years, who was not the target of the mass immunization campaign, the said rates were respectively 91.7% and 87.4%. The herd immunity of the age groups below 16 years, who were the target of the campaign, is favourably high and reassuring both for measles and for rubella. Campaigns of supplementary vaccination play a substantial role for filling the gaps in the herd immunity.

Quality of Life, Motor Ability, and Weight Status among School-aged Children of Tehran

PubMed Central

Khodaverdi, F; Bahram, A; Jafarabadi, M Asghari

2012-01-01

Background: This study aimed to investigate the relationship between health Related quality of life (HRQOL), motor ability and weight status in children. Methods: Two hundred forty children ages 9–11 yr who were selected via multi stage cluster sampling design from primary schools in the Shahre Qods at Tehran, Iran in 2007. HRQOL was assessed by the pediatric quality of life inventory (PedsQL). Motor abilities were determined by a Basic Motor Ability Test (BMAT). Body mass index was calculated to determine weight status. Results: Psychosocial, physical, and total health related qualities of life (all P< 0.05) were significantly lowered for obese when compared to normal weight participants. In contrast, the mean scores for each HRQOL domain in motor ability category were not significant. No significant interaction was apparent when examining HRQOL scores, BMAT variables and weight status. Conclusion: Regardless of motor ability levels, reducing body weight among children is a potential avenue for promoting improved HRQOL. Over weight boys reported significantly worse school performance than over weight girls, suggesting the importance in considering such dimensions in programs aimed at further understanding obesity in children. PMID:23113200

Cervical cancer screening among Lebanese women.

PubMed

Bou-Orm, I R; Sakr, R E; Adib, S M

2018-02-01

Cervical cancer is a very common malignancy amongst women worldwide. Pap smear is an effective and inexpensive screening test in asymptomatic women. The aim of this paper was to assess the prevalence of Pap smear screening for cervical cancer among Lebanese women and to determine associated sociodemographic and psychosocial characteristics. This national survey included 2255 women, selected by multi-stage random cluster sampling across Lebanon. A questionnaire about practices and perceptions related to cervical cancer screening was developed based on the "Health Belief Model". The weighted national prevalence of "ever-use" of the Pap smear for screening purposes was 35%. Most important determinants of screening behavior were: residence within Greater Beirut, higher socio-economic status and educational attainment, marriage status, presence of a health coverage, awareness of Pap smear usefulness, knowing someone who had already done it, and a balance between perceived benefits and perceived barriers to Pap smear screening. Regular information campaigns regarding the availability and effectiveness of the test should be devised, targeting in priority the sexually vulnerable women in Lebanon. Moreover, healthcare providers should be encouraged to discuss with their patients the opportunity of obtaining a Pap smear. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Experimental light scattering by small particles: system design and calibration

NASA Astrophysics Data System (ADS)

Maconi, Göran; Kassamakov, Ivan; Penttilä, Antti; Gritsevich, Maria; Hæggström, Edward; Muinonen, Karri

2017-06-01

We describe a setup for precise multi-angular measurements of light scattered by mm- to μm-sized samples. We present a calibration procedure that ensures accurate measurements. Calibration is done using a spherical sample (d = 5 mm, n = 1.517) fixed on a static holder. The ultimate goal of the project is to allow accurate multi-wavelength measurements (the full Mueller matrix) of single-particle samples which are levitated ultrasonically. The system comprises a tunable multimode Argon-krypton laser, with 12 wavelengths ranging from 465 to 676 nm, a linear polarizer, a reference photomultiplier tube (PMT) monitoring beam intensity, and several PMT:s mounted radially towards the sample at an adjustable radius. The current 150 mm radius allows measuring all azimuthal angles except for ±4° around the backward scattering direction. The measurement angle is controlled by a motor-driven rotational stage with an accuracy of 15'.

Analyses of advanced concepts in multi-stage gyro-amplifiers and startup in high power gyro-oscillators

NASA Astrophysics Data System (ADS)

Sinitsyn, Oleksandr V.

Gyrotrons are well recognized sources of high-power coherent electromagnetic radiation. The power that gyrotrons can radiate in the millimeter- and submillimeter-wavelength regions exceeds the power of classical microwave tubes by many orders of magnitude. In this work, the author considers some problems related to the operation of gyro-devices and methods of their solution. In particular, the self-excitation conditions for parasitic backward waves and effect of distributed losses on the small-signal gain of gyro-TWTs are analyzed. The corresponding small-signal theory describing two-stage gyro-traveling-wave tubes (gyro-TWTs) with the first stage having distributed losses is presented. The theory is illustrated by using it for the description of operation of a Ka-band gyro-TWT designed at the Naval Research Laboratory. Also, the results of nonlinear studies of this tube are presented and compared with the ones obtained by the use of MAGY, a multi-frequency, self-consistent code developed at the University of Maryland. An attempt to build a large signal theory of gyro-TWTs with tapered geometry and magnetic field profile is made and first results are obtained for a 250 GHz gyro-TWT. A comparative small-signal analysis of conventional four-cavity and three-stage clustered-cavity gyroklystrons is performed. The corresponding point-gap models for these devices are presented. The efficiency, gain, bandwidth and gain-bandwidth product are analyzed for each scheme. Advantages of the clustered-cavity over the conventional design are discussed. The startup scenarios in high-power gyrotrons and the most important physical effects associated with them are considered. The work presents the results of startup simulations for a 140 GHz, MW-class gyrotron developed by Communications and Power Industries (CPI) for electron-cyclotron resonance heating (ECRH) and current drive experiments on the "Wendelstein 7-X" stellarator plasma. Also presented are the results for a 110 GHz, 1.5 MW gyrotron currently being developed at CPI. The simulations are carried out for six competing modes and with the effects of electron velocity spread and voltage depression taken into account. Also, the slow stage of the startup in long-pulse gyrotrons is analyzed and attention is paid to the effects of ion compensation of the beam space charge, frequency deviation due to the cavity wall heating and beam current decrease due to cathode cooling. These effects are modeled with a simple nonlinear theory and the code MAGY.

Beam-hardening correction by a surface fitting and phase classification by a least square support vector machine approach for tomography images of geological samples

NASA Astrophysics Data System (ADS)

Khan, F.; Enzmann, F.; Kersten, M.

2015-12-01

In X-ray computed microtomography (μXCT) image processing is the most important operation prior to image analysis. Such processing mainly involves artefact reduction and image segmentation. We propose a new two-stage post-reconstruction procedure of an image of a geological rock core obtained by polychromatic cone-beam μXCT technology. In the first stage, the beam-hardening (BH) is removed applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. The final BH-corrected image is extracted from the residual data, or the difference between the surface elevation values and the original grey-scale values. For the second stage, we propose using a least square support vector machine (a non-linear classifier algorithm) to segment the BH-corrected data as a pixel-based multi-classification task. A combination of the two approaches was used to classify a complex multi-mineral rock sample. The Matlab code for this approach is provided in the Appendix. A minor drawback is that the proposed segmentation algorithm may become computationally demanding in the case of a high dimensional training data set.

Multi-stage versus single-stage inflation and deflation cycle for alternating low pressure air mattresses to prevent pressure ulcers in hospitalised patients: a randomised-controlled clinical trial.

PubMed

Demarré, L; Beeckman, D; Vanderwee, K; Defloor, T; Grypdonck, M; Verhaeghe, S

2012-04-01

The duration and the amount of pressure and shear must be reduced in order to minimize the risk of pressure ulcer development. Alternating low pressure air mattresses with multi-stage inflation and deflation cycle of the air cells have been developed to relieve pressure by sequentially inflating and deflating the air cells. Evidence about the effectiveness of this type of mattress in clinical practice is lacking. This study aimed to compare the effectiveness of an alternating low pressure air mattress that has a standard single-stage inflation and deflation cycle of the air cells with an alternating low pressure air mattress with multi-stage inflation and deflation cycle of the air cells. A randomised controlled trial was performed in a convenience sample of 25 wards in five hospitals in Belgium. In total, 610 patients were included and randomly assigned to the experimental group (n=298) or the control group (n=312). In the experimental group, patients were allocated to an alternating low pressure air mattress with multi-stage inflation and deflation cycle of the air cells. In the control group, patients were allocated to an alternating low pressure air mattress with a standard single-stage inflation and deflation cycle of the air cells. The outcome was defined as cumulative pressure ulcer incidence (Grade II-IV). An intention-to-treat analysis was performed. There was no significant difference in cumulative pressure ulcer incidence (Grade II-IV) between both groups (Exp.=5.7%, Contr.=5.8%, p=0.97). When patients developed a pressure ulcer, the median time was 5.0 days in the experimental group (IQR=3.0-8.5) and 8.0 days in the control group (IQR=3.0-8.5) (Mann-Whitney U-test=113, p=0.182). The probability to remain pressure ulcer free during the observation period in this trial did not differ significantly between the experimental group and the control group (log-rank χ(2)=0.013, df=1, p=0.911). An alternating low pressure air mattress with multi-stage inflation and deflation of the air cells does not result in a significantly lower pressure ulcer incidence compared to an alternating low pressure air mattress with a standard single-stage inflation and deflation cycle of the air cells. Both alternating mattress types are equally effective to prevent pressure ulcer development. © 2011 Elsevier Ltd. All rights reserved.

Prevalence and factors related to dental caries among pre-school children of Saddar town, Karachi, Pakistan: a cross-sectional study.

PubMed

Dawani, Narendar; Nisar, Nighat; Khan, Nazeer; Syed, Shahbano; Tanweer, Navara

2012-12-27

Dental caries is highly prevalent and a significant public health problem among children throughout the world. Epidemiological data regarding prevalence of dental caries amongst Pakistani pre-school children is very limited. The objective of this study is to determine the frequency of dental caries among pre-school children of Saddar Town, Karachi, Pakistan and the factors related to caries. A cross-sectional study of 1000 preschool children was conducted in Saddar town, Karachi. Two-stage cluster sampling was used to select the sample. At first stage, eight clusters were selected randomly from total 11 clusters. In second stage, from the eight selected clusters, preschools were identified and children between 3- to 6-years age group were assessed for dental caries. Caries prevalence was 51% with a mean dmft score being 2.08 (±2.97) of which decayed teeth constituted 1.95. The mean dmft of males was 2.3 (±3.08) and of females was 1.90 (±2.90). The mean dmft of 3, 4, 5 and 6-year olds was 1.65, 2.11, 2.16 and 3.11 respectively. A significant association was found between dental caries and following variables: age group of 4-years (p-value < 0.029, RR = 1.248, 95% Bias corrected CI 0.029-0.437) and 5-years (p-value < 0.009, RR = 1.545, 95% Bias corrected CI 0.047-0.739), presence of dental plaque (p-value < 0.003, RR = 0.744, 95% Bias corrected CI (-0.433)-(-0.169)), poor oral hygiene (p-value < 0.000, RR = 0.661, 95% Bias corrected CI (-0.532)-(-0.284)), as well as consumption of non-sweetened milk (p-value < 0.049, RR = 1.232, 95% Bias corrected CI 0.061-0.367). Half of the preschoolers had dental caries coupled with a high prevalence of unmet dental treatment needs. Association between caries experience and age of child, consumption of non-sweetened milk, dental plaque and poor oral hygiene had been established.

Risk factors of pre-eclampsia/eclampsia and its adverse outcomes in low- and middle-income countries: a WHO secondary analysis.

PubMed

Bilano, Ver Luanni; Ota, Erika; Ganchimeg, Togoobaatar; Mori, Rintaro; Souza, João Paulo

2014-01-01

Pre-eclampsia has an immense adverse impact on maternal and perinatal health especially in low- and middle-income settings. We aimed to estimate the associations between pre-eclampsia/eclampsia and its risk factors, and adverse maternal and perinatal outcomes. We performed a secondary analysis of the WHO Global Survey on Maternal and Perinatal Health. The survey was a multi-country, facility-based cross-sectional study. A global sample consisting of 24 countries from three regions and 373 health facilities was obtained via a stratified multi-stage cluster sampling design. Maternal and offspring data were extracted from records using standardized questionnaires. Multi-level logistic regression modelling was conducted with random effects at the individual, facility and country levels. Data for 276,388 mothers and their infants was analysed. The prevalence of pre-eclampsia/eclampsia in the study population was 10,754 (4%). At the individual level, sociodemographic characteristics of maternal age ≥30 years and low educational attainment were significantly associated with higher risk of pre-eclampsia/eclampsia. As for clinical and obstetric variables, high body mass index (BMI), nulliparity (AOR: 2.04; 95%CI 1.92-2.16), absence of antenatal care (AOR: 1.41; 95%CI 1.26-1.57), chronic hypertension (AOR: 7.75; 95%CI 6.77-8.87), gestational diabetes (AOR: 2.00; 95%CI 1.63-2.45), cardiac or renal disease (AOR: 2.38; 95%CI 1.86-3.05), pyelonephritis or urinary tract infection (AOR: 1.13; 95%CI 1.03-1.24) and severe anemia (AOR: 2.98; 95%CI 2.47-3.61) were found to be significant risk factors, while having >8 visits of antenatal care was protective (AOR: 0.90; 95%CI 0.83-0.98). Pre-eclampsia/eclampsia was found to be a significant risk factor for maternal death, perinatal death, preterm birth and low birthweight. Chronic hypertension, obesity and severe anemia were the highest risk factors of preeclampsia/eclampsia. Implementation of effective interventions prioritizing risk factors, provision of quality health services during pre-pregnancy and during pregnancy for joint efforts in the areas of maternal health are recommended.

Transcriptome and gene expression analysis during flower blooming in Rosa chinensis 'Pallida'.

PubMed

Yan, Huijun; Zhang, Hao; Chen, Min; Jian, Hongying; Baudino, Sylvie; Caissard, Jean-Claude; Bendahmane, Mohammed; Li, Shubin; Zhang, Ting; Zhou, Ningning; Qiu, Xianqin; Wang, Qigang; Tang, Kaixue

2014-04-25

Rosa chinensis 'Pallida' (Rosa L.) is one of the most important ancient rose cultivars originating from China. It contributed the 'tea scent' trait to modern roses. However, little information is available on the gene regulatory networks involved in scent biosynthesis and metabolism in Rosa. In this study, the transcriptome of R. chinensis 'Pallida' petals at different developmental stages, from flower buds to senescent flowers, was investigated using Illumina sequencing technology. De novo assembly generated 89,614 clusters with an average length of 428bp. Based on sequence similarity search with known proteins, 62.9% of total clusters were annotated. Out of these annotated transcripts, 25,705 and 37,159 sequences were assigned to gene ontology and clusters of orthologous groups, respectively. The dataset provides information on transcripts putatively associated with known scent metabolic pathways. Digital gene expression (DGE) was obtained using RNA samples from flower bud, open flower and senescent flower stages. Comparative DGE and quantitative real time PCR permitted the identification of five transcripts encoding proteins putatively associated with scent biosynthesis in roses. The study provides a foundation for scent-related gene discovery in roses. Copyright © 2014. Published by Elsevier B.V.

The Clustering of Lifestyle Behaviours in New Zealand and their Relationship with Optimal Wellbeing.

PubMed

Prendergast, Kate B; Mackay, Lisa M; Schofield, Grant M

2016-10-01

The purpose of this research was to determine (1) associations between multiple lifestyle behaviours and optimal wellbeing and (2) the extent to which five lifestyle behaviours-sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake-cluster in a national sample. A national sample of New Zealand adults participated in a web-based wellbeing survey. Five lifestyle behaviours-sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake-were dichotomised into healthy (meets recommendations) and unhealthy (does not meet recommendations) categories. Optimal wellbeing was calculated using a multi-dimensional flourishing scale, and binary logistic regression analysis was used to calculate the relationship between multiple healthy behaviours and optimal wellbeing. Clustering was examined by comparing the observed and expected prevalence rates (O/E) of healthy and unhealthy two-, three-, four-, and five-behaviour combinations. Data from 9425 participants show those engaging in four to five healthy behaviours (23 %) were 4.7 (95 % confidence interval (CI) 3.8-5.7) times more likely to achieve optimal wellbeing compared to those engaging in zero to one healthy behaviour (21 %). Clustering was observed for healthy (5 %, O/E 2.0, 95 % CI 1.8-2.2) and unhealthy (5 %, O/E 2.1, 95 % CI 1.9-2.3) five-behaviour combinations and for four- and three-behaviour combinations. At the two-behaviour level, healthy fruit and vegetable intake clustered with all behaviours, except sleep which did not cluster with any behaviour. Multiple lifestyle behaviours were positively associated with optimal wellbeing. The results show lifestyle behaviours cluster, providing support for multiple behaviour lifestyle-based interventions for optimising wellbeing.

Kelvin-Helmholtz Instability: Lessons Learned and Ways Forward

NASA Astrophysics Data System (ADS)

Masson, A.; Nykyri, K.

2018-06-01

The Kelvin-Helmholtz instability (KHI) is a ubiquitous phenomenon across the Universe, observed from 500 m deep in the oceans on Earth to the Orion molecular cloud. Over the past two decades, several space missions have enabled a leap forward in our understanding of this phenomenon at the Earth's magnetopause. Key results obtained by these missions are first presented, with a special emphasis on Cluster and THEMIS. In particular, as an ideal instability, the KHI was not expected to produce mass transport. Simulations, later confirmed by spacecraft observations, indicate that plasma transport in Kelvin-Helmholtz (KH) vortices can arise during non-linear stage of its development via secondary process. In addition to plasma transport, spacecraft observations have revealed that KHI can also lead to significant ion heating due to enhanced ion-scale wave activity driven by the KHI. Finally, we describe what are the upcoming observational opportunities in 2018-2020, thanks to a unique constellation of multi-spacecraft missions including: MMS, Cluster, THEMIS, Van Allen Probes and Swarm.

Perturbative universal state-selective correction for state-specific multi-reference coupled cluster methods

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

Brabec, Jiri; Banik, Subrata; Kowalski, Karol

2016-10-28

The implementation details of the universal state-selective (USS) multi-reference coupled cluster (MRCC) formalism with singles and doubles (USS(2)) are discussed on the example of several benchmark systems. We demonstrate that the USS(2) formalism is capable of improving accuracies of state specific multi-reference coupled-cluster (MRCC) methods based on the Brillouin-Wigner and Mukherjee’s sufficiency conditions. Additionally, it is shown that the USS(2) approach significantly alleviates problems associated with the lack of invariance of MRCC theories upon the rotation of active orbitals. We also discuss the perturbative USS(2) formulations that significantly reduce numerical overhead of the full USS(2) method.

CASP10-BCL::Fold efficiently samples topologies of large proteins.

PubMed

Heinze, Sten; Putnam, Daniel K; Fischer, Axel W; Kohlmann, Tim; Weiner, Brian E; Meiler, Jens

2015-03-01

During CASP10 in summer 2012, we tested BCL::Fold for prediction of free modeling (FM) and template-based modeling (TBM) targets. BCL::Fold assembles the tertiary structure of a protein from predicted secondary structure elements (SSEs) omitting more flexible loop regions early on. This approach enables the sampling of conformational space for larger proteins with more complex topologies. In preparation of CASP11, we analyzed the quality of CASP10 models throughout the prediction pipeline to understand BCL::Fold's ability to sample the native topology, identify native-like models by scoring and/or clustering approaches, and our ability to add loop regions and side chains to initial SSE-only models. The standout observation is that BCL::Fold sampled topologies with a GDT_TS score > 33% for 12 of 18 and with a topology score > 0.8 for 11 of 18 test cases de novo. Despite the sampling success of BCL::Fold, significant challenges still exist in clustering and loop generation stages of the pipeline. The clustering approach employed for model selection often failed to identify the most native-like assembly of SSEs for further refinement and submission. It was also observed that for some β-strand proteins model refinement failed as β-strands were not properly aligned to form hydrogen bonds removing otherwise accurate models from the pool. Further, BCL::Fold samples frequently non-natural topologies that require loop regions to pass through the center of the protein. © 2015 Wiley Periodicals, Inc.

Admixture in Humans of Two Divergent Plasmodium knowlesi Populations Associated with Different Macaque Host Species

PubMed Central

Divis, Paul C. S.; Singh, Balbir; Anderios, Fread; Hisam, Shamilah; Matusop, Asmad; Kocken, Clemens H.; Assefa, Samuel A.; Duffy, Craig W.; Conway, David J.

2015-01-01

Human malaria parasite species were originally acquired from other primate hosts and subsequently became endemic, then spread throughout large parts of the world. A major zoonosis is now occurring with Plasmodium knowlesi from macaques in Southeast Asia, with a recent acceleration in numbers of reported cases particularly in Malaysia. To investigate the parasite population genetics, we developed sensitive and species-specific microsatellite genotyping protocols and applied these to analysis of samples from 10 sites covering a range of >1,600 km within which most cases have occurred. Genotypic analyses of 599 P. knowlesi infections (552 in humans and 47 in wild macaques) at 10 highly polymorphic loci provide radical new insights on the emergence. Parasites from sympatric long-tailed macaques (Macaca fascicularis) and pig-tailed macaques (M. nemestrina) were very highly differentiated (FST = 0.22, and K-means clustering confirmed two host-associated subpopulations). Approximately two thirds of human P. knowlesi infections were of the long-tailed macaque type (Cluster 1), and one third were of the pig-tailed-macaque type (Cluster 2), with relative proportions varying across the different sites. Among the samples from humans, there was significant indication of genetic isolation by geographical distance overall and within Cluster 1 alone. Across the different sites, the level of multi-locus linkage disequilibrium correlated with the degree of local admixture of the two different clusters. The widespread occurrence of both types of P. knowlesi in humans enhances the potential for parasite adaptation in this zoonotic system. PMID:26020959

Efficiency of static core turn-off in a system-on-a-chip with variation

DOEpatents

Cher, Chen-Yong; Coteus, Paul W; Gara, Alan; Kursun, Eren; Paulsen, David P; Schuelke, Brian A; Sheets, II, John E; Tian, Shurong

2013-10-29

A processor-implemented method for improving efficiency of a static core turn-off in a multi-core processor with variation, the method comprising: conducting via a simulation a turn-off analysis of the multi-core processor at the multi-core processor's design stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's design stage includes a first output corresponding to a first multi-core processor core to turn off; conducting a turn-off analysis of the multi-core processor at the multi-core processor's testing stage, wherein the turn-off analysis of the multi-core processor at the multi-core processor's testing stage includes a second output corresponding to a second multi-core processor core to turn off; comparing the first output and the second output to determine if the first output is referring to the same core to turn off as the second output; outputting a third output corresponding to the first multi-core processor core if the first output and the second output are both referring to the same core to turn off.

Myeloid Clusters Are Associated with a Pro-Metastatic Environment and Poor Prognosis in Smoking-Related Early Stage Non-Small Cell Lung Cancer

PubMed Central

Zhang, Wang; Pal, Sumanta K.; Liu, Xueli; Yang, Chunmei; Allahabadi, Sachin; Bhanji, Shaira; Figlin, Robert A.; Yu, Hua; Reckamp, Karen L.

2013-01-01

Background This study aimed to understand the role of myeloid cell clusters in uninvolved regional lymph nodes from early stage non-small cell lung cancer patients. Methods Uninvolved regional lymph node sections from 67 patients with stage I–III resected non-small cell lung cancer were immunostained to detect myeloid clusters, STAT3 activity and occult metastasis. Anthracosis intensity, myeloid cluster infiltration associated with anthracosis and pSTAT3 level were scored and correlated with patient survival. Multivariate Cox regression analysis was performed with prognostic variables. Human macrophages were used for in vitro nicotine treatment. Results CD68+ myeloid clusters associated with anthracosis and with an immunosuppressive and metastasis-promoting phenotype and elevated overall STAT3 activity were observed in uninvolved lymph nodes. In patients with a smoking history, myeloid cluster score significantly correlated with anthracosis intensity and pSTAT3 level (P<0.01). Nicotine activated STAT3 in macrophages in long-term culture. CD68+ myeloid clusters correlated and colocalized with occult metastasis. Myeloid cluster score was an independent prognostic factor (P = 0.049) and was associated with survival by Kaplan-Maier estimate in patients with a history of smoking (P = 0.055). The combination of myeloid cluster score with either lymph node stage or pSTAT3 level defined two populations with a significant difference in survival (P = 0.024 and P = 0.004, respectively). Conclusions Myeloid clusters facilitate a pro-metastatic microenvironment in uninvolved regional lymph nodes and associate with occult metastasis in early stage non-small cell lung cancer. Myeloid cluster score is an independent prognostic factor for survival in patients with a history of smoking, and may present a novel method to inform therapy choices in the adjuvant setting. Further validation studies are warranted. PMID:23717691

Prevalence and clustering of soil-transmitted helminth infections in a tribal area in southern India.

PubMed

Kaliappan, Saravanakumar Puthupalayam; George, Santosh; Francis, Mark Rohit; Kattula, Deepthi; Sarkar, Rajiv; Minz, Shantidani; Mohan, Venkata Raghava; George, Kuryan; Roy, Sheela; Ajjampur, Sitara Swarna Rao; Muliyil, Jayaprakash; Kang, Gagandeep

2013-12-01

To estimate the prevalence, spatial patterns and clustering in the distribution of soil-transmitted helminth (STH) infections, and factors associated with hookworm infections in a tribal population in Tamil Nadu, India. Cross-sectional study with one-stage cluster sampling of 22 clusters. Demographic and risk factor data and stool samples for microscopic ova/cysts examination were collected from 1237 participants. Geographical information systems mapping assessed spatial patterns of infection. The overall prevalence of STH was 39% (95% CI 36%–42%), with hookworm 38% (95% CI 35–41%) and Ascaris lumbricoides 1.5% (95% CI 0.8–2.2%). No Trichuris trichiura infection was detected. People involved in farming had higher odds of hookworm infection (1.68, 95% CI 1.31–2.17, P < 0.001). In the multiple logistic regression, adults (2.31, 95% CI 1.80–2.96, P < 0.001), people with pet cats (1.55, 95% CI 1.10–2.18, P = 0.011) and people who did not wash their hands with soap after defecation (1.84, 95% CI 1.27–2.67, P = 0.001) had higher odds of hookworm infection, but gender and poor usage of foot wear did not significantly increase risk. Cluster analysis, based on design effect calculation, did not show any clustering of cases among the study population; however, spatial scan statistic detected a significant cluster for hookworm infections in one village. Multiple approaches including health education, improving the existing sanitary practices and regular preventive chemotherapy are needed to control the burden of STH in similar endemic areas.

Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use.

PubMed

Babbin, Steven F; Velicer, Wayne F; Paiva, Andrea L; Brick, Leslie Ann D; Redding, Colleen A

2015-01-01

Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N=4059) and alcohol (N=3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions. Copyright © 2014. Published by Elsevier Ltd.

Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use

PubMed Central

Babbin, Steven F.; Velicer, Wayne F.; Paiva, Andrea L.; Brick, Leslie Ann D.; Redding, Colleen A.

2015-01-01

Introduction Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Methods Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N= 4059) and alcohol (N= 3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Results Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Conclusions Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions. PMID:25222849

Multi-agent grid system Agent-GRID with dynamic load balancing of cluster nodes

NASA Astrophysics Data System (ADS)

Satymbekov, M. N.; Pak, I. T.; Naizabayeva, L.; Nurzhanov, Ch. A.

2017-12-01

In this study the work presents the system designed for automated load balancing of the contributor by analysing the load of compute nodes and the subsequent migration of virtual machines from loaded nodes to less loaded ones. This system increases the performance of cluster nodes and helps in the timely processing of data. A grid system balances the work of cluster nodes the relevance of the system is the award of multi-agent balancing for the solution of such problems.

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

Noble, A. G.; McDonald, M.; Muzzin, A.

We present ALMA CO (2–1) detections in 11 gas-rich cluster galaxies at z ∼ 1.6, constituting the largest sample of molecular gas measurements in z > 1.5 clusters to date. The observations span three galaxy clusters, derived from the Spitzer Adaptation of the Red-sequence Cluster Survey. We augment the >5 σ detections of the CO (2–1) fluxes with multi-band photometry, yielding stellar masses and infrared-derived star formation rates, to place some of the first constraints on molecular gas properties in z ∼ 1.6 cluster environments. We measure sizable gas reservoirs of 0.5–2 × 10{sup 11} M {sub ☉} in thesemore » objects, with high gas fractions ( f {sub gas}) and long depletion timescales ( τ ), averaging 62% and 1.4 Gyr, respectively. We compare our cluster galaxies to the scaling relations of the coeval field, in the context of how gas fractions and depletion timescales vary with respect to the star-forming main sequence. We find that our cluster galaxies lie systematically off the field scaling relations at z = 1.6 toward enhanced gas fractions, at a level of ∼4 σ , but have consistent depletion timescales. Exploiting CO detections in lower-redshift clusters from the literature, we investigate the evolution of the gas fraction in cluster galaxies, finding it to mimic the strong rise with redshift in the field. We emphasize the utility of detecting abundant gas-rich galaxies in high-redshift clusters, deeming them as crucial laboratories for future statistical studies.« less

Molecular characterization of Shiga-toxigenic Escherichia coli isolated from diverse sources from India by multi-locus variable number tandem repeat analysis (MLVA).

PubMed

Kumar, A; Taneja, N; Sharma, R K; Sharma, H; Ramamurthy, T; Sharma, M

2014-12-01

In a first study from India, a diverse collection of 140 environmental and clinical non-O157 Shiga-toxigenic Escherichia coli strains from a large geographical area in north India was typed by multi-locus variable number tandem repeat analysis (MLVA). The distribution of major virulence genes stx1, stx2 and eae was found to be 78%, 70% and 10%, respectively; 15 isolates were enterohaemorrhagic E. coli (stx1 +/stx2 + and eae +). By MLVA analysis, 44 different alleles were obtained. Dendrogram analysis revealed 104 different genotypes and 19 MLVA-type complexes divided into two main lineages, i.e. mutton and animal stool. Human isolates presented a statistically significant greater odds ratio for clustering with mutton samples compared to animal stool isolates. Five human isolates clustered with animal stool strains suggesting that some of the human infections may be from cattle, perhaps through milk, contact or the environment. Further epidemiological studies are required to explore these sources in context with occurrence of human cases.

A Multi-Discipline, Multi-Genre Digital Library for Research and Education

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.

2004-01-01

We describe NCSTRL+, a unified, canonical digital library for educational and scientific and technical information (STI). NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible digital library (DL) that provides access to over 100 university departments and laboratories. NCSTRL+ implements two new technologies: cluster functionality and publishing "buckets". We have extended the Dienst protocol, the protocol underlying NCSTRL, to provide the ability to "cluster" independent collections into a logically centralized digital library based upon subject category classification, type of organization, and genres of material. The concept of "buckets" provides a mechanism for publishing and managing logically linked entities with multiple data formats. The NCSTRL+ prototype DL contains the holdings of NCSTRL and the NASA Technical Report Server (NTRS). The prototype demonstrates the feasibility of publishing into a multi-cluster DL, searching across clusters, and storing and presenting buckets of information.

Holistic and consumer-centric assessment of beer: A multi-measurement approach.

PubMed

Jaeger, Sara R; Cardello, Armand V; Chheang, Sok L; Beresford, Michelle K; Hedderley, Duncan I; Pineau, Benedicte

2017-09-01

Despite occupying a cornerstone position in consumer research and innovation, product liking/disliking provides only partial insight into consumer behaviour. By adopting a consumer-centric perspective and drawing on additional factors that underpin food-related consumer behaviour, a more complete product understanding is gained. The present research showcases this approach in a study with New Zealand beer (incl. pilsner, lager and ale categories). Implementation of a multi-variate approach with 128 regular beer drinkers provided assessments pertaining to liking and sensory novelty/complexity, situational appropriateness of consumption, as well as attitudes/perceptions and emotional associations. The 9 samples grouped into two clusters, where 4 of the beers were similar in being perceived as having less complex flavours, being appropriate for many uses and evoking stronger emotional associations of "relaxed/calm." The 4 beers were perceived as "easy to drink", and were, on average, most liked. One of the samples in this cluster was lighter in alcohol (2.5% ABV), but not inferior to beers with 4-5% ABV. The 5 beers in the second cluster were, on average, less liked and were associated with more negative emotions, e.g. "unhappy, "jittery", and "tense". Additional insights were gained from segmentation which identified two groups of consumers, named 'Lager Lovers' and 'Ale Aficionados'. Beers 1-4 were positively perceived by 'Lager Lovers' but less so by 'Ale Aficionados', and vice versa. The study was conducted under central location test conditions compatible with testing protocols often used in product research. The study protocol can be amended to include few/many consumer-centric measures and extended to product testing where packaging, brand, and other extrinsic information is available to consumers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inorganic material profiling using Arn+ cluster: Can we achieve high quality profiles?

NASA Astrophysics Data System (ADS)

Conard, T.; Fleischmann, C.; Havelund, R.; Franquet, A.; Poleunis, C.; Delcorte, A.; Vandervorst, W.

2018-06-01

Retrieving molecular information by sputtering of organic systems has been concretized in the last years due to the introduction of sputtering by large gas clusters which drastically eliminated the compound degradation during the analysis and has led to strong improvements in depth resolution. Rapidly however, a limitation was observed for heterogeneous systems where inorganic layers or structures needed to be profiled concurrently. As opposed to organic material, erosion of the inorganic layer appears very difficult and prone to many artefacts. To shed some light on these problems we investigated a simple system consisting of aluminum delta layer(s) buried in a silicon matrix in order to define the most favorable beam conditions for practical analysis. We show that counterintuitive to the small energy/atom used and unlike monoatomic ion sputtering, the information depth obtained with large cluster ions is typically very large (∼10 nm) and that this can be caused both by a large roughness development at early stages of the sputtering process and by a large mixing zone. As a consequence, a large deformation of the Al intensity profile is observed. Using sample rotation during profiling significantly improves the depth resolution while sample temperature has no significant effect. The determining parameter for high depth resolution still remains the total energy of the cluster instead of the energy per atom in the cluster.

Homogeneity tests of clustered diagnostic markers with applications to the BioCycle Study

PubMed Central

Tang, Liansheng Larry; Liu, Aiyi; Schisterman, Enrique F.; Zhou, Xiao-Hua; Liu, Catherine Chun-ling

2014-01-01

Diagnostic trials often require the use of a homogeneity test among several markers. Such a test may be necessary to determine the power both during the design phase and in the initial analysis stage. However, no formal method is available for the power and sample size calculation when the number of markers is greater than two and marker measurements are clustered in subjects. This article presents two procedures for testing the accuracy among clustered diagnostic markers. The first procedure is a test of homogeneity among continuous markers based on a global null hypothesis of the same accuracy. The result under the alternative provides the explicit distribution for the power and sample size calculation. The second procedure is a simultaneous pairwise comparison test based on weighted areas under the receiver operating characteristic curves. This test is particularly useful if a global difference among markers is found by the homogeneity test. We apply our procedures to the BioCycle Study designed to assess and compare the accuracy of hormone and oxidative stress markers in distinguishing women with ovulatory menstrual cycles from those without. PMID:22733707

Behavioural Problems of Juvenile Street Hawkers in Uyo Metropolis, Nigeria

ERIC Educational Resources Information Center

Udoh, Nsisong A.; Joseph, Eme U.

2012-01-01

The study sought the opinions of Faculty of Education Students of University of Uyo on the behavioural problems of juvenile street hawkers in Uyo metropolis. Five research hypotheses were formulated to guide the study. This cross-sectional survey employed multi-stage random sampling technique in selecting 200 regular undergraduate students in the…

Illuminating the star clusters and satellite galaxies with multi-scale baryonic simulations

NASA Astrophysics Data System (ADS)

Maji, Moupiya; Zhu, Qirong; Li, Yuexing; Marinacci, Federico; Charlton, Jane; Hernquist, Lars; Knebe, Alexander

2018-01-01

Over the past decade, advances in computational architecture have made it possible for the first time to investigate some of the fundamental questions around the formation, evolution and assembly of the building blocks of the universe; star clusters and galaxies. In this talk, I will focus on two major questions: What is the origin of the observed universal lognormal mass function in globular clusters? What is the statistical distribution of the properties of satellite planes in a large sample of satellite systems?Observations of globular clusters show that they have universal lognormal mass functions with a characteristic peak at 2X105 MSun, although the origin of this peaked distribution is unclear. We investigate the formation of star clusters in interacting galaxies using baryonic simulations and found that massive clusters preferentially form in extremely high pressure gas clouds which reside in highly shocked regions produced by galaxy interactions. These massive clusters have quasi-lognormal initial mass functions with a peak around ~106MSun which may survive dynamical evolution and slowly evolve into the universal lognormal profiles observed today.The classical Milky Way (MW) satellites are observed to be distributed in a highly-flattened plane, called Disk of Satellites (DoS). However the significance, coherence and origin of DoS is highly debated. To understand this, we first analyze all MW satellites and find that a small sample size can artificially produce a highly anisotropic spatial distribution and a strong clustering of their angular momentum. Comparing a baryonic simulation of a MW-sized galaxy with its N-body counterpart we find that an anisotropic DoS can originate from baryonic processes. Furthermore, we explore the statistical distribution of DoS properties by analyzing 2591 satellite systems in the cosmological hydrodynamic simulation Illustris. We find that the DoS becomes more isotropic with increasing sample sizes and most (~90%) satellite systems have no clear coherent rotation. Their overall evolution indicate that the DoS may be part of large scale filamentary structure. Our results show that baryonic processes may be the key to solve many long standing theoretical problems.

Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space.

PubMed

Jacob, Benjamin J; Krapp, Fiorella; Ponce, Mario; Gottuzzo, Eduardo; Griffith, Daniel A; Novak, Robert J

2010-05-01

Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multi-drug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDRTB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e., the Moran's coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centers, using a 10 m2 grid-based algorithm. Geographical information system (GIS)-gridded measurements of each health center were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDR-TB covariates. Pearson's correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS(R) module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centers and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran's coefficient into uncorrelated, orthogonal map pattern components revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations.

Formation and evolution of oxygen-vacancy clusters in lead and tin doped silicon

NASA Astrophysics Data System (ADS)

Londos, C. A.; Aliprantis, D.; Sgourou, E. N.; Chroneos, A.; Pochet, P.

2012-06-01

Infrared spectroscopy (IR) measurements were used to investigate the effect of lead (Pb), tin (Sn), and (Pb, Sn) codoping on electron radiation-induced defects in silicon (Si). The study was mainly focused on oxygen-vacancy (VOn) clusters and in particular their formation and evolution upon annealing. It was determined that Pb causes a larger reduction in the production of the VO defect than Sn. In (Pb, Sn) co-doped Si isochronal anneals revealed that the evolution of VO increases substantially at ˜170 °C. This is attributed to the release of V from the SnV pair. Interestingly, in the corresponding evolution curves of VO in the Sn- and the Pb-doped samples, this inverse annealing stage is also present for the former while it is not present for the latter. This is attributed to the formation of PbV pairs that do not dissociate below 280 °C. The partial capture of V by Sn in co-doped samples is rationalized through the higher compressive local strain around Pb atoms that leads to a retardation of vacancy diffusion. The conversion of VO to the VO2 defect is substantially reduced in the Pb-doped sample. The evolution curves of VO and VO2 clusters in the isovalent doped Si samples hint the production of VO2 from other mechanisms (i.e., besides VO + Oi → VO2). For larger VOn clusters (n = 3,4), the signals are very weak in the Pb-doped sample, whereas for n ≥ 5, they are not present in the spectra. Conversely, bands related with the VO5 and VOnCs defects are present in the spectra of the Sn-doped and (Pb, Sn) codoped Si.

Estimating the concrete compressive strength using hard clustering and fuzzy clustering based regression techniques.

PubMed

Nagwani, Naresh Kumar; Deo, Shirish V

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm.

Estimating the Concrete Compressive Strength Using Hard Clustering and Fuzzy Clustering Based Regression Techniques

PubMed Central

Nagwani, Naresh Kumar; Deo, Shirish V.

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm. PMID:25374939

Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

PubMed

Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

2015-11-01

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

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

Liu, Hui; Song, Yongduan; Xue, Fangzheng

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than themore » SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.« less

Persistent Topology and Metastable State in Conformational Dynamics

PubMed Central

Chang, Huang-Wei; Bacallado, Sergio; Pande, Vijay S.; Carlsson, Gunnar E.

2013-01-01

The large amount of molecular dynamics simulation data produced by modern computational models brings big opportunities and challenges to researchers. Clustering algorithms play an important role in understanding biomolecular kinetics from the simulation data, especially under the Markov state model framework. However, the ruggedness of the free energy landscape in a biomolecular system makes common clustering algorithms very sensitive to perturbations of the data. Here, we introduce a data-exploratory tool which provides an overview of the clustering structure under different parameters. The proposed Multi-Persistent Clustering analysis combines insights from recent studies on the dynamics of systems with dominant metastable states with the concept of multi-dimensional persistence in computational topology. We propose to explore the clustering structure of the data based on its persistence on scale and density. The analysis provides a systematic way to discover clusters that are robust to perturbations of the data. The dominant states of the system can be chosen with confidence. For the clusters on the borderline, the user can choose to do more simulation or make a decision based on their structural characteristics. Furthermore, our multi-resolution analysis gives users information about the relative potential of the clusters and their hierarchical relationship. The effectiveness of the proposed method is illustrated in three biomolecules: alanine dipeptide, Villin headpiece, and the FiP35 WW domain. PMID:23565139

Spring frost vulnerability of sweet cherries under controlled conditions

NASA Astrophysics Data System (ADS)

Matzneller, Philipp; Götz, Klaus-P.; Chmielewski, Frank-M.

2016-01-01

Spring frost is a significant production hazard in nearly all temperate fruit-growing regions. Sweet cherries are among the first fruit varieties starting their development in spring and therefore highly susceptible to late frost. Temperatures at which injuries are likely to occur are widely published, but their origin and determination methods are not well documented. In this study, a standardized method was used to investigate critical frost temperatures for the sweet cherry cultivar `Summit' under controlled conditions. Twigs were sampled at four development stages ("side green," "green tip," "open cluster," "full bloom") and subjected to three frost temperatures (-2.5, -5.0, -10.0 °C). The main advantage of this method, compared to other approaches, was that the exposition period and the time interval required to reach the target temperature were always constant (2 h). Furthermore, then, the twigs were placed in a climate chamber until full bloom, before the examination of the flowers and not further developed buds started. For the first two sampling stages (side green, green tip), the number of buds found in open cluster, "first white," and full bloom at the evaluation date decreased with the strength of the frost treatment. The flower organs showed different levels of cold hardiness and became more vulnerable in more advanced development stages. In this paper, we developed four empirical functions which allow calculating possible frost damages on sweet cherry buds or flowers at the investigated development stages. These equations can help farmers to estimate possible frost damages on cherry buds due to frost events. However, it is necessary to validate the critical temperatures obtained in laboratory with some field observations.

Spring frost vulnerability of sweet cherries under controlled conditions.

PubMed

Matzneller, Philipp; Götz, Klaus-P; Chmielewski, Frank-M

2016-01-01

Spring frost is a significant production hazard in nearly all temperate fruit-growing regions. Sweet cherries are among the first fruit varieties starting their development in spring and therefore highly susceptible to late frost. Temperatures at which injuries are likely to occur are widely published, but their origin and determination methods are not well documented. In this study, a standardized method was used to investigate critical frost temperatures for the sweet cherry cultivar 'Summit' under controlled conditions. Twigs were sampled at four development stages ("side green," "green tip," "open cluster," "full bloom") and subjected to three frost temperatures (-2.5, -5.0, -10.0 °C). The main advantage of this method, compared to other approaches, was that the exposition period and the time interval required to reach the target temperature were always constant (2 h). Furthermore, then, the twigs were placed in a climate chamber until full bloom, before the examination of the flowers and not further developed buds started. For the first two sampling stages (side green, green tip), the number of buds found in open cluster, "first white," and full bloom at the evaluation date decreased with the strength of the frost treatment. The flower organs showed different levels of cold hardiness and became more vulnerable in more advanced development stages. In this paper, we developed four empirical functions which allow calculating possible frost damages on sweet cherry buds or flowers at the investigated development stages. These equations can help farmers to estimate possible frost damages on cherry buds due to frost events. However, it is necessary to validate the critical temperatures obtained in laboratory with some field observations.

Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

NASA Astrophysics Data System (ADS)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

Multi-Sample Cluster Analysis Using Akaike’s Information Criterion.

DTIC Science & Technology

1982-12-20

Intervals. For more details on these test procedures refer to Gabriel [7J, Krishnaiah (CIlUj, [11]), Srivastava [16), and others. -3- As noted in Consul...723. (4] Consul, P. C. (1969), "The Exact Distributions of Likelihood Criteria for Different Hypotheses," in P. R. Krishnaiah (Ed.), Multivariate...1178. [7] Gabriel, K. R. (1969), "A Comparison of Some lethods of Simultaneous Inference in MANOVA," in P. R. Krishnaiah (Ed.), Multivariate Analysis-lI

Multi-focus image fusion and robust encryption algorithm based on compressive sensing

NASA Astrophysics Data System (ADS)

Xiao, Di; Wang, Lan; Xiang, Tao; Wang, Yong

2017-06-01

Multi-focus image fusion schemes have been studied in recent years. However, little work has been done in multi-focus image transmission security. This paper proposes a scheme that can reduce data transmission volume and resist various attacks. First, multi-focus image fusion based on wavelet decomposition can generate complete scene images and optimize the perception of the human eye. The fused images are sparsely represented with DCT and sampled with structurally random matrix (SRM), which reduces the data volume and realizes the initial encryption. Then the obtained measurements are further encrypted to resist noise and crop attack through combining permutation and diffusion stages. At the receiver, the cipher images can be jointly decrypted and reconstructed. Simulation results demonstrate the security and robustness of the proposed scheme.

Stream Clustering of Growing Objects

NASA Astrophysics Data System (ADS)

Siddiqui, Zaigham Faraz; Spiliopoulou, Myra

We study incremental clustering of objects that grow and accumulate over time. The objects come from a multi-table stream e.g. streams of Customer and Transaction. As the Transactions stream accumulates, the Customers’ profiles grow. First, we use an incremental propositionalisation to convert the multi-table stream into a single-table stream upon which we apply clustering. For this purpose, we develop an online version of K-Means algorithm that can handle these swelling objects and any new objects that arrive. The algorithm also monitors the quality of the model and performs re-clustering when it deteriorates. We evaluate our method on the PKDD Challenge 1999 dataset.

Effects of female bovine plasma collected at different days of the estrous cycle on epididymal spermatozoa motility.

PubMed

Nait Mouloud, M; Ouennoughi, F; Yaiche, L; Kaidi, R; Iguer-Ouada, M

2017-03-15

The aim of this study was to assess the effects of female bovine plasma collected at different days of the reproductive cycle on epididymal spermatozoa motility and to test hypothesis that the subpopulations pattern of motile spermatozoa is affected by this treatment. Blood plasma samples were collected from five Holstein Friesian cows at different stages of the estrous cycle (days 0, 5, 10, 12 and 18), one pregnant cow and one adult bull and were diluted 1:9 (V/V) with normal saline. Female charcoal-treated plasma, Bull plasma and saline were used as controls. Semen samples were obtained from cauda epididymidis through retrograde flushing and diluted in saline to approximately 60 × 106 sperm/ml. The extended semen was diluted 1:2 (V/V) with tested media and motility was evaluated at 15 min and then every hour for 6 h using a computer-assisted semen analysis. Multivariate clustering procedure was applied to identify and quantify specific subpopulations within the semen samples. The statistical analysis clustered all the motile spermatozoa into three separate subpopulations with defined patterns of movement: Subpopulation 1 poorly motile and non-progressive spermatozoa (39.3%), subpopulation 2 including the fastest and the most vigorous spermatozoa (46.4%) and subpopulation 3 represented by slow, non-vigorous but linear spermatozoa (14.3%). Initially, sperm samples supplemented with female, male or female charcoal-treated plasma stimulated equally total motility and spermatozoa belonging to subpopulation 2 regardless of the estrous cycle stage. After 1-h incubation, the motility of these both categories of spermatozoa (total motile and those assigned to subpopulation 2) is enhanced and maintained more in day 12, 18 and pregnant cow plasma than in female plasma from earlier stage of the estrous cycle (day 0, 5 and 10), male plasma and female-charcoal treated plasma. In conclusion, the overall results showed that female plasma stimulated significantly sperm motility, especially at the late stage of the estrous cycle. Additionally, to the diverse compounds contained in blood plasma, progesterone may play a key role in such motility activation. Copyright © 2016 Elsevier Inc. All rights reserved.

Adaptive fuzzy leader clustering of complex data sets in pattern recognition

NASA Technical Reports Server (NTRS)

Newton, Scott C.; Pemmaraju, Surya; Mitra, Sunanda

1992-01-01

A modular, unsupervised neural network architecture for clustering and classification of complex data sets is presented. The adaptive fuzzy leader clustering (AFLC) architecture is a hybrid neural-fuzzy system that learns on-line in a stable and efficient manner. The initial classification is performed in two stages: a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from fuzzy C-means system equations for the centroids and the membership values. The AFLC algorithm is applied to the Anderson Iris data and laser-luminescent fingerprint image data. It is concluded that the AFLC algorithm successfully classifies features extracted from real data, discrete or continuous.

Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes.

PubMed

King, Paula; Pham, Long K; Waltz, Shannon; Sphar, Dan; Yamamoto, Robert T; Conrad, Douglas; Taplitz, Randy; Torriani, Francesca; Forsyth, R Allyn

2016-01-01

We describe the sampling of sixty-three uncultured hospital air samples collected over a six-month period and analysis using shotgun metagenomic sequencing. Our primary goals were to determine the longitudinal metagenomic variability of this environment, identify and characterize genomes of potential pathogens and determine whether they are atypical to the hospital airborne metagenome. Air samples were collected from eight locations which included patient wards, the main lobby and outside. The resulting DNA libraries produced 972 million sequences representing 51 gigabases. Hierarchical clustering of samples by the most abundant 50 microbial orders generated three major nodes which primarily clustered by type of location. Because the indoor locations were longitudinally consistent, episodic relative increases in microbial genomic signatures related to the opportunistic pathogens Aspergillus, Penicillium and Stenotrophomonas were identified as outliers at specific locations. Further analysis of microbial reads specific for Stenotrophomonas maltophilia indicated homology to a sequenced multi-drug resistant clinical strain and we observed broad sequence coverage of resistance genes. We demonstrate that a shotgun metagenomic sequencing approach can be used to characterize the resistance determinants of pathogen genomes that are uncharacteristic for an otherwise consistent hospital air microbial metagenomic profile.

The Cluster Environment of Two High-mass Protostars

NASA Astrophysics Data System (ADS)

Montes, Virginie; Hofner, Peter

2017-06-01

Characterizing the environment and stellar population in which high-mass stars form is an important step to decide between the main massive star formation theories. In the monolithic collapse model, the mass of the core will determine the final stellar mass (e.g., McKee & Tan 2003). In contrast, in the competitive accretion model (e.g., Bonnell & Bate 2006), the mass of the high-mass star is related to the properties of the cluster. As dynamical processes substantially affect the appearance of a cluster, we study early stages of high-mass star formation. These regions often show extended emission from hot dust at infrared wavelengths, which can cause difficulties to define the cluster. We use a multi-wavelength technique to study nearby high-mass star clusters, based on X-ray observations with the Chandra X-Ray Telescope, in conjunction with infrared data and VLA data. The technique relies on the fact that YSOs are particularly bright in X-ray and that contamination is relatively small. X-ray observations allow us to determine the cluster size. The cluster membership and YSOs classification is established using infrared identification of the X-ray sources, and color-color and color-magnitude diagrams.In this talk, I will present our findings on the cluster study of two high-mass star forming regions: IRAS 20126+4104 and IRAS 16562-3959. While most massive stars appear to be formed in rich a cluster environment, those two sources are candidates for the formation of massive stars in a relatively poor cluster. In contrast to what was found in previous studies (Qiu et al. 2008), the dominant B0-type protostar in IRAS 20126+4104 is associated with a small cluster of low-mass stars. I will also show our current work on IRAS 16562-3959, which contains one of the most luminous O-type protostars in the Galaxy. In the vicinity of this particularly interesting region there is a multitude of small clusters, for which I will present how their stellar population differ from the high-mass star-forming cluster IRAS 16562-3959.

IN-SYNC. VII. Evidence for a Decreasing Spectroscopic Binary Fraction (from 1 to 100 Myr) within the IN-SYNC Sample

NASA Astrophysics Data System (ADS)

Jaehnig, Karl; Bird, Jonathan C.; Stassun, Keivan G.; Da Rio, Nicola; Tan, Jonathan C.; Cotaar, Michiel; Somers, Garrett

2017-12-01

We study the occurrence of spectroscopic binaries in young star-forming regions using the INfrared Spectroscopy of Young Nebulous Clusters (IN-SYNC) survey, carried out in SDSS-III with the APOGEE spectrograph. Multi-epoch observations of thousands of low-mass stars in Orion A, NGC 2264, NGC 1333, IC 348, and the Pleiades have been carried out, yielding H-band spectra with a nominal resolution of R = 22,500 for sources with H < 12 mag. Radial velocity precisions of ˜0.3 {km} {{{s}}}-1 were achieved, which we use to identify radial velocity variations indicative of undetected companions. We use Monte Carlo simulations to assess the types of spectroscopic binaries to which we are sensitive, finding sensitivity to binaries with orbital periods ≲ {10}3.5 days, for stars with 2500 {{K}}≤slant {T}{eff}≤slant 6000 {{K}} and v \\sin i < 100 {km} {{{s}}}-1. Using Bayesian inference, we find evidence for a decline in the spectroscopic binary fraction, by a factor of 3-4, from the age of our pre-main-sequence (PMS) sample to the Pleiades age . The significance of this decline is weakened if spot-induced radial-velocity jitter is strong in the sample, and is only marginally significant when comparing any one of the PMS clusters against the Pleiades. However, the same decline in both sense and magnitude is found for each of the five PMS clusters, and the decline reaches a statistical significance of greater than 95% confidence when considering the PMS clusters jointly. Our results suggest that dynamical processes disrupt the widest spectroscopic binaries ({P}{orb}≈ {10}3{--}{10}4 days) as clusters age, indicating that this occurs early in the stars’ evolution, while they still reside within their nascent clusters.

OT2_eegami_6: SPIRE Snapshot Survey II: Using SPT/CODEX Massive Clusters as Powerful Gravitational Lenses

NASA Astrophysics Data System (ADS)

Egami, E.

2011-09-01

On the extragalactic side, one of the most remarkable results coming out of Herschel is the discovery of extremely bright (>100 mJy in the SPIRE bands) gravitationally lensed galaxies. The great sensitivity and mapping speed of SPIRE have enabled us to find these rare extraordinary objects. What is truly exciting about these bright lensed galaxies is that they enable a variety of detailed multi-wavelength follow-up observations, shedding new light on the physical properties of these high-redshift sources. In this regard, our OT1 program, "SPIRE Snapshot Survey of Massive Galaxy Clusters" turned out to be a great success. After imaging ~50 galaxies out of 279 in the program, we have already found two spectacularly bright lensed galaxies, one of which is at a redshift of 4.69. This type of cluster-lensed sources are not only bright but also spatially stretched over a large scale, so ALMA (or NOEMA in the north) is likely to be able to study them at the level of individual GMCs. Such studies will open up a new frontier in the study of high-redshift galaxies. Here, we propose to extend this highly efficient and effective survey of gravitationally lensed galaxies to another 353 clusters carefully chosen from the SPT and CODEX cluster samples. These samples contain newly discovered high-redshift (z>0.3) massive (>3-4e14 Msun) clusters, which can be used as powerful gravitational lenses to magnify sources at high redshift. With the OT1 and OT2 surveys together, we expect to find ~20 highly magnified SPIRE sources with exceptional brightnesses (assuming a discovery rate of ~1/30). Such a unique sample of extraordinary objects will enable a variety of follow-up sciences, and will therefore remain as a great legacy of the Herschel mission for years to come.

Remote sensing imagery classification using multi-objective gravitational search algorithm

NASA Astrophysics Data System (ADS)

Zhang, Aizhu; Sun, Genyun; Wang, Zhenjie

2016-10-01

Simultaneous optimization of different validity measures can capture different data characteristics of remote sensing imagery (RSI) and thereby achieving high quality classification results. In this paper, two conflicting cluster validity indices, the Xie-Beni (XB) index and the fuzzy C-means (FCM) (Jm) measure, are integrated with a diversity-enhanced and memory-based multi-objective gravitational search algorithm (DMMOGSA) to present a novel multi-objective optimization based RSI classification method. In this method, the Gabor filter method is firstly implemented to extract texture features of RSI. Then, the texture features are syncretized with the spectral features to construct the spatial-spectral feature space/set of the RSI. Afterwards, cluster of the spectral-spatial feature set is carried out on the basis of the proposed method. To be specific, cluster centers are randomly generated initially. After that, the cluster centers are updated and optimized adaptively by employing the DMMOGSA. Accordingly, a set of non-dominated cluster centers are obtained. Therefore, numbers of image classification results of RSI are produced and users can pick up the most promising one according to their problem requirements. To quantitatively and qualitatively validate the effectiveness of the proposed method, the proposed classification method was applied to classifier two aerial high-resolution remote sensing imageries. The obtained classification results are compared with that produced by two single cluster validity index based and two state-of-the-art multi-objective optimization algorithms based classification results. Comparison results show that the proposed method can achieve more accurate RSI classification.

Spitzer Clusters

NASA Astrophysics Data System (ADS)

Krick, Kessica

This proposal is a specific response to the strategic goal of NASA's research program to "discover how the universe works and explore how the universe evolved into its present form." Towards this goal, we propose to mine the Spitzer archive for all observations of galaxy groups and clusters for the purpose of studying galaxy evolution in clusters, contamination rates for Sunyaev Zeldovich cluster surveys, and to provide a database of Spitzer observed clusters to the broader community. Funding from this proposal will go towards two years of support for a Postdoc to do this work. After searching the Spitzer Heritage Archive, we have found 194 unique galaxy groups and clusters that have data from both the Infrared array camera (IRAC; Fazio et al. 2004) at 3.6 - 8 microns and the multiband imaging photometer for Spitzer (MIPS; Rieke et al. 2004) at 24microns. This large sample will add value beyond the individual datasets because it will be a larger sample of IR clusters than ever before and will have sufficient diversity in mass, redshift, and dynamical state to allow us to differentiate amongst the effects of these cluster properties. An infrared sample is important because it is unaffected by dust extinction while at the same time is an excellent measure of both stellar mass (IRAC wavelengths) and star formation rate (MIPS wavelengths). Additionally, IRAC can be used to differentiate star forming galaxies (SFG) from active galactic nuclei (AGN), due to their different spectral shapes in this wavelength regime. Specifically, we intend to identify SFG and AGN in galaxy groups and clusters. Groups and clusters differ from the field because the galaxy densities are higher, there is a large potential well due mainly to the mass of the dark matter, and there is hot X-ray gas (the intracluster medium; ICM). We will examine the impact of these differences in environment on galaxy formation by comparing cluster properties of AGN and SFG to those in the field. Also, we will examine the effect that evolutions of cluster redshift and dynamical state have on SFG and AGN in groups and clusters. In addition to environment, we will study the timescales of chemical enrichment of the ICM, using the SFG and AGN as tracers of processes that can transport metals outside of galaxies. Cosmological parameters can be measured based on observing galaxy clusters as signposts of the growth of structure in the universe. The best way to select a redshift independent sample is to use the SZ effect with mm observations to detect a shift in the cosmic microwave background spectrum as those photons scatter off hot gas in clusters. However, such mm observations are contaminated by the emission of SFG and AGN. We intend to characterize the magnitude of this effect on SZ surveys by understanding the frequency, radial distribution, and redshift distribution of these galaxies in clusters. Lastly, a compiled cluster catalog of all Spitzer observed clusters would be useful to the broader astronomical community. We plan to incorporate ancillary multi-wavelength data, where available, and to both publish our catalog in journals, and work with NED to make the catalog easily accessible in an efficient manner by the community.

An Examination of the Multi-Faceted Motivation System in Healthy Young Adults.

PubMed

Da Silva, Susana; Apatsidou, Areti; Saperia, Sarah; Siddiqui, Ishraq; Jeffay, Eliyas; Voineskos, Aristotle N; Daskalakis, Zafiris J; Remington, Gary; Zakzanis, Konstantine K; Foussias, George

2018-01-01

Background: Amotivation is a prevalent symptom in schizophrenia (SZ) and depression (MDD), and is linked to poor functional outcomes in affected individuals. Conceptualizations of motivation have outlined a multi-faceted construct comprised of reward responsiveness, reward expectancy, reward valuation, effort valuation, and action selection/preference-based decision making. To date, findings from studies utilizing variable-centered approaches to examining isolated facets of motivation in SZ and MDD have been inconsistent. Thus, the present study adopted a person-centered approach, and comprehensively examined the reward system in a non-clinical sample in an attempt to explore potential subtypes of motivation impairments, while minimizing the effects of illness-related confounds. Methods: Ninety-six healthy undergraduate students were evaluated for amotivation, schizotypal traits, depressive symptoms, and cognition, and administered objective computerized tasks to measure the different facets of motivation. Cluster analysis was performed to explore subgroups of individuals based on similar motivation task performance. Additionally, correlational analyses were conducted in order to examine inter-relationships between motivation facets, and relations between clinical measures and facets of motivation. Results: Cluster analysis identified two subgroups of individuals with differential motivation performance profiles. Correlational analyses revealed that reward responsiveness was associated with amotivation, depressive symptoms, and negative schizotypy. Further, significant inter-correlations were found between reward responsiveness and reward expectancy, as well as between reward valuation and effort valuation. Conclusions: Our results mark important steps forward in understanding motivation in a non-clinical sample, and guide future dimensional and comprehensive analyses of the multi-faceted reward system. It remains to be seen whether these patterns of results will be similar in clinical populations such as SZ and MDD.

An Examination of the Multi-Faceted Motivation System in Healthy Young Adults

PubMed Central

Da Silva, Susana; Apatsidou, Areti; Saperia, Sarah; Siddiqui, Ishraq; Jeffay, Eliyas; Voineskos, Aristotle N.; Daskalakis, Zafiris J.; Remington, Gary; Zakzanis, Konstantine K.; Foussias, George

2018-01-01

Background: Amotivation is a prevalent symptom in schizophrenia (SZ) and depression (MDD), and is linked to poor functional outcomes in affected individuals. Conceptualizations of motivation have outlined a multi-faceted construct comprised of reward responsiveness, reward expectancy, reward valuation, effort valuation, and action selection/preference-based decision making. To date, findings from studies utilizing variable-centered approaches to examining isolated facets of motivation in SZ and MDD have been inconsistent. Thus, the present study adopted a person-centered approach, and comprehensively examined the reward system in a non-clinical sample in an attempt to explore potential subtypes of motivation impairments, while minimizing the effects of illness-related confounds. Methods: Ninety-six healthy undergraduate students were evaluated for amotivation, schizotypal traits, depressive symptoms, and cognition, and administered objective computerized tasks to measure the different facets of motivation. Cluster analysis was performed to explore subgroups of individuals based on similar motivation task performance. Additionally, correlational analyses were conducted in order to examine inter-relationships between motivation facets, and relations between clinical measures and facets of motivation. Results: Cluster analysis identified two subgroups of individuals with differential motivation performance profiles. Correlational analyses revealed that reward responsiveness was associated with amotivation, depressive symptoms, and negative schizotypy. Further, significant inter-correlations were found between reward responsiveness and reward expectancy, as well as between reward valuation and effort valuation. Conclusions: Our results mark important steps forward in understanding motivation in a non-clinical sample, and guide future dimensional and comprehensive analyses of the multi-faceted reward system. It remains to be seen whether these patterns of results will be similar in clinical populations such as SZ and MDD.

Dynamic clustering scheme based on the coordination of management and control in multi-layer and multi-region intelligent optical network

NASA Astrophysics Data System (ADS)

Niu, Xiaoliang; Yuan, Fen; Huang, Shanguo; Guo, Bingli; Gu, Wanyi

2011-12-01

A Dynamic clustering scheme based on coordination of management and control is proposed to reduce network congestion rate and improve the blocking performance of hierarchical routing in Multi-layer and Multi-region intelligent optical network. Its implement relies on mobile agent (MA) technology, which has the advantages of efficiency, flexibility, functional and scalability. The paper's major contribution is to adjust dynamically domain when the performance of working network isn't in ideal status. And the incorporation of centralized NMS and distributed MA control technology migrate computing process to control plane node which releases the burden of NMS and improves process efficiently. Experiments are conducted on Multi-layer and multi-region Simulation Platform for Optical Network (MSPON) to assess the performance of the scheme.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

PubMed

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-09-25

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

PubMed Central

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-01-01

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

Multiplexed immunofluorescence delineates proteomic cancer cell states associated with metabolism

PubMed Central

Sood, Anup; Miller, Alexandra M.; Brogi, Edi; Sui, Yunxia; Armenia, Joshua; McDonough, Elizabeth; Santamaria-Pang, Alberto; Stamper, Aleksandra; Campos, Carl; Pang, Zhengyu; Li, Qing; Port, Elisa; Graeber, Thomas G.; Schultz, Nikolaus; Ginty, Fiona; Larson, Steven M.

2016-01-01

The phenotypic diversity of cancer results from genetic and nongenetic factors. Most studies of cancer heterogeneity have focused on DNA alterations, as technologies for proteomic measurements in clinical specimen are currently less advanced. Here, we used a multiplexed immunofluorescence staining platform to measure the expression of 27 proteins at the single-cell level in formalin-fixed and paraffin-embedded samples from treatment-naive stage II/III human breast cancer. Unsupervised clustering of protein expression data from 638,577 tumor cells in 26 breast cancers identified 8 clusters of protein coexpression. In about one-third of breast cancers, over 95% of all neoplastic cells expressed a single protein coexpression cluster. The remaining tumors harbored tumor cells representing multiple protein coexpression clusters, either in a regional distribution or intermingled throughout the tumor. Tumor uptake of the radiotracer 18F-fluorodeoxyglucose was associated with protein expression clusters characterized by hormone receptor loss, PTEN alteration, and HER2 gene amplification. Our study demonstrates an approach to generate cellular heterogeneity metrics in routinely collected solid tumor specimens and integrate them with in vivo cancer phenotypes. PMID:27182557

A Technique of Two-Stage Clustering Applied to Environmental and Civil Engineering and Related Methods of Citation Analysis.

ERIC Educational Resources Information Center

Miyamoto, S.; Nakayama, K.

1983-01-01

A method of two-stage clustering of literature based on citation frequency is applied to 5,065 articles from 57 journals in environmental and civil engineering. Results of related methods of citation analysis (hierarchical graph, clustering of journals, multidimensional scaling) applied to same set of articles are compared. Ten references are…

NOA: A Scalable Multi-Parent Clustering Hierarchy for WSNs

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

Cree, Johnathan V.; Delgado-Frias, Jose; Hughes, Michael A.

2012-08-10

NOA is a multi-parent, N-tiered, hierarchical clustering algorithm that provides a scalable, robust and reliable solution to autonomous configuration of large-scale wireless sensor networks. The novel clustering hierarchy's inherent benefits can be utilized by in-network data processing techniques to provide equally robust, reliable and scalable in-network data processing solutions capable of reducing the amount of data sent to sinks. Utilizing a multi-parent framework, NOA reduces the cost of network setup when compared to hierarchical beaconing solutions by removing the expense of r-hop broadcasting (r is the radius of the cluster) needed to build the network and instead passes network topologymore » information among shared children. NOA2, a two-parent clustering hierarchy solution, and NOA3, the three-parent variant, saw up to an 83% and 72% reduction in overhead, respectively, when compared to performing one round of a one-parent hierarchical beaconing, as well as 92% and 88% less overhead when compared to one round of two- and three-parent hierarchical beaconing hierarchy.« less

Development and evaluation of a multi-locus sequence typing scheme for Mycoplasma synoviae.

PubMed

Dijkman, R; Feberwee, A; Landman, W J M

2016-08-01

Reproducible molecular Mycoplasma synoviae typing techniques with sufficient discriminatory power may help to expand knowledge on its epidemiology and contribute to the improvement of control and eradication programmes of this mycoplasma species. The present study describes the development and validation of a novel multi-locus sequence typing (MLST) scheme for M. synoviae. Thirteen M. synoviae isolates originating from different poultry categories, farms and lesions, were subjected to whole genome sequencing. Their sequences were compared to that of M. synoviae reference strain MS53. A high number of single nucleotide polymorphisms (SNPs) indicating considerable genetic diversity were identified. SNPs were present in over 40 putative target genes for MLST of which five target genes were selected (nanA, uvrA, lepA, ruvB and ugpA) for the MLST scheme. This scheme was evaluated analysing 209 M. synoviae samples from different countries, categories of poultry, farms and lesions. Eleven clonal clusters and 76 different sequence types (STs) were obtained. Clustering occurred following geographical origin, supporting the hypothesis of regional population evolution. M. synoviae samples obtained from epidemiologically linked outbreaks often harboured the same ST. In contrast, multiple M. synoviae lineages were found in samples originating from swollen joints or oviducts from hens that produce eggs with eggshell apex abnormalities indicating that further research is needed to identify the genetic factors of M. synoviae that may explain its variations in tissue tropism and disease inducing potential. Furthermore, MLST proved to have a higher discriminatory power compared to variable lipoprotein and haemagglutinin A typing, which generated 50 different genotypes on the same database.

Population Structure of Hispanics in the United States: The Multi-Ethnic Study of Atherosclerosis

PubMed Central

Manichaikul, Ani; Palmas, Walter; Rodriguez, Carlos J.; Peralta, Carmen A.; Divers, Jasmin; Guo, Xiuqing; Chen, Wei-Min; Wong, Quenna; Williams, Kayleen; Kerr, Kathleen F.; Taylor, Kent D.; Tsai, Michael Y.; Goodarzi, Mark O.; Sale, Michèle M.; Diez-Roux, Ana V.; Rich, Stephen S.; Rotter, Jerome I.; Mychaleckyj, Josyf C.

2012-01-01

Using ∼60,000 SNPs selected for minimal linkage disequilibrium, we perform population structure analysis of 1,374 unrelated Hispanic individuals from the Multi-Ethnic Study of Atherosclerosis (MESA), with self-identification corresponding to Central America (n = 93), Cuba (n = 50), the Dominican Republic (n = 203), Mexico (n = 708), Puerto Rico (n = 192), and South America (n = 111). By projection of principal components (PCs) of ancestry to samples from the HapMap phase III and the Human Genome Diversity Panel (HGDP), we show the first two PCs quantify the Caucasian, African, and Native American origins, while the third and fourth PCs bring out an axis that aligns with known South-to-North geographic location of HGDP Native American samples and further separates MESA Mexican versus Central/South American samples along the same axis. Using k-means clustering computed from the first four PCs, we define four subgroups of the MESA Hispanic cohort that show close agreement with self-identification, labeling the clusters as primarily Dominican/Cuban, Mexican, Central/South American, and Puerto Rican. To demonstrate our recommendations for genetic analysis in the MESA Hispanic cohort, we present pooled and stratified association analysis of triglycerides for selected SNPs in the LPL and TRIB1 gene regions, previously reported in GWAS of triglycerides in Caucasians but as yet unconfirmed in Hispanic populations. We report statistically significant evidence for genetic association in both genes, and we further demonstrate the importance of considering population substructure and genetic heterogeneity in genetic association studies performed in the United States Hispanic population. PMID:22511882

Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

PubMed

Fukunishi, Yoshifumi; Mikami, Yoshiaki; Nakamura, Haruki

2005-09-01

We developed a new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix. The receptors were classified by a cluster analysis based on calculations of the distance between receptor pockets. A set of low homologous receptors that bind a similar compound could be classified into one cluster. Based on this line of reasoning, we proposed a new in silico screening method. According to this method, compounds in a database were docked to multiple targets. The new docking score was a slightly modified version of the multiple active site correction (MASC) score. Receptors that were at a set distance from the target receptor were not included in the analysis, and the modified MASC scores were calculated for the selected receptors. The choice of the receptors is important to achieve a good screening result, and our clustering of receptors is useful to this purpose. This method was applied to the analysis of a set of 132 receptors and 132 compounds, and the results demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling, using a receptor-ligand docking program, Sievgene, which was newly developed with a good docking performance yielding 50.8% of the reconstructed complexes at a distance of less than 2 A RMSD.

Facies Modeling Using 3D Pre-Stack Simultaneous Seismic Inversion and Multi-Attribute Probability Neural Network Transform in the Wattenberg Field, Colorado

NASA Astrophysics Data System (ADS)

Harryandi, Sheila

The Niobrara/Codell unconventional tight reservoir play at Wattenberg Field, Colorado has potentially two billion barrels of oil equivalent requiring hundreds of wells to access this resource. The Reservoir Characterization Project (RCP), in conjunction with Anadarko Petroleum Corporation (APC), began reservoir characterization research to determine how to increase reservoir recovery while maximizing operational efficiency. Past research results indicate that targeting the highest rock quality within the reservoir section for hydraulic fracturing is optimal for improving horizontal well stimulation through multi-stage hydraulic fracturing. The reservoir is highly heterogeneous, consisting of alternating chalks and marls. Modeling the facies within the reservoir is very important to be able to capture the heterogeneity at the well-bore scale; this heterogeneity is then upscaled from the borehole scale to the seismic scale to distribute the heterogeneity in the inter-well space. I performed facies clustering analysis to create several facies defining the reservoir interval in the RCP Wattenberg Field study area. Each facies can be expressed in terms of a range of rock property values from wells obtained by cluster analysis. I used the facies classification from the wells to guide the pre-stack seismic inversion and multi-attribute transform. The seismic data extended the facies information and rock quality information from the wells. By obtaining this information from the 3D facies model, I generated a facies volume capturing the reservoir heterogeneity throughout a ten square mile study-area within the field area. Recommendations are made based on the facies modeling, which include the location for future hydraulic fracturing/re-fracturing treatments to improve recovery from the reservoir, and potential deeper intervals for future exploration drilling targets.

Exploring the IMF of star clusters: a joint SLUG and LEGUS effort

NASA Astrophysics Data System (ADS)

Ashworth, G.; Fumagalli, M.; Krumholz, M. R.; Adamo, A.; Calzetti, D.; Chandar, R.; Cignoni, M.; Dale, D.; Elmegreen, B. G.; Gallagher, J. S., III; Gouliermis, D. A.; Grasha, K.; Grebel, E. K.; Johnson, K. E.; Lee, J.; Tosi, M.; Wofford, A.

2017-08-01

We present the implementation of a Bayesian formalism within the Stochastically Lighting Up Galaxies (slug) stellar population synthesis code, which is designed to investigate variations in the initial mass function (IMF) of star clusters. By comparing observed cluster photometry to large libraries of clusters simulated with a continuously varying IMF, our formalism yields the posterior probability distribution function (PDF) of the cluster mass, age and extinction, jointly with the parameters describing the IMF. We apply this formalism to a sample of star clusters from the nearby galaxy NGC 628, for which broad-band photometry in five filters is available as part of the Legacy ExtraGalactic UV Survey (LEGUS). After allowing the upper-end slope of the IMF (α3) to vary, we recover PDFs for the mass, age and extinction that are broadly consistent with what is found when assuming an invariant Kroupa IMF. However, the posterior PDF for α3 is very broad due to a strong degeneracy with the cluster mass, and it is found to be sensitive to the choice of priors, particularly on the cluster mass. We find only a modest improvement in the constraining power of α3 when adding Hα photometry from the companion Hα-LEGUS survey. Conversely, Hα photometry significantly improves the age determination, reducing the frequency of multi-modal PDFs. With the aid of mock clusters, we quantify the degeneracy between physical parameters, showing how constraints on the cluster mass that are independent of photometry can be used to pin down the IMF properties of star clusters.

ALMA Observations of Gas-rich Galaxies in z ˜ 1.6 Galaxy Clusters: Evidence for Higher Gas Fractions in High-density Environments

NASA Astrophysics Data System (ADS)

Noble, A. G.; McDonald, M.; Muzzin, A.; Nantais, J.; Rudnick, G.; van Kampen, E.; Webb, T. M. A.; Wilson, G.; Yee, H. K. C.; Boone, K.; Cooper, M. C.; DeGroot, A.; Delahaye, A.; Demarco, R.; Foltz, R.; Hayden, B.; Lidman, C.; Manilla-Robles, A.; Perlmutter, S.

2017-06-01

We present ALMA CO (2-1) detections in 11 gas-rich cluster galaxies at z ˜ 1.6, constituting the largest sample of molecular gas measurements in z > 1.5 clusters to date. The observations span three galaxy clusters, derived from the Spitzer Adaptation of the Red-sequence Cluster Survey. We augment the >5σ detections of the CO (2-1) fluxes with multi-band photometry, yielding stellar masses and infrared-derived star formation rates, to place some of the first constraints on molecular gas properties in z ˜ 1.6 cluster environments. We measure sizable gas reservoirs of 0.5-2 × 1011 M ⊙ in these objects, with high gas fractions (f gas) and long depletion timescales (τ), averaging 62% and 1.4 Gyr, respectively. We compare our cluster galaxies to the scaling relations of the coeval field, in the context of how gas fractions and depletion timescales vary with respect to the star-forming main sequence. We find that our cluster galaxies lie systematically off the field scaling relations at z = 1.6 toward enhanced gas fractions, at a level of ˜4σ, but have consistent depletion timescales. Exploiting CO detections in lower-redshift clusters from the literature, we investigate the evolution of the gas fraction in cluster galaxies, finding it to mimic the strong rise with redshift in the field. We emphasize the utility of detecting abundant gas-rich galaxies in high-redshift clusters, deeming them as crucial laboratories for future statistical studies.

Optimising cluster survey design for planning schistosomiasis preventive chemotherapy.

PubMed

Knowles, Sarah C L; Sturrock, Hugh J W; Turner, Hugo; Whitton, Jane M; Gower, Charlotte M; Jemu, Samuel; Phillips, Anna E; Meite, Aboulaye; Thomas, Brent; Kollie, Karsor; Thomas, Catherine; Rebollo, Maria P; Styles, Ben; Clements, Michelle; Fenwick, Alan; Harrison, Wendy E; Fleming, Fiona M

2017-05-01

The cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and converting this into treatment decisions has not been thoroughly evaluated. We used baseline schistosomiasis mapping surveys from three countries (Malawi, Côte d'Ivoire and Liberia) to generate spatially realistic gold standard datasets, against which we tested alternative two-stage cluster survey designs. We assessed how sampling different numbers of schools per district (2-20) and children per school (10-50) influences the accuracy of prevalence estimates and treatment class assignment, and we compared survey cost-efficiency using data from Malawi. Due to the focal nature of schistosomiasis, up to 53% simulated surveys involving 2-5 schools per district failed to detect schistosomiasis in low endemicity areas (1-10% prevalence). Increasing the number of schools surveyed per district improved treatment class assignment far more than increasing the number of children sampled per school. For Malawi, surveys of 15 schools per district and 20-30 children per school reliably detected endemic schistosomiasis and maximised cost-efficiency. In sensitivity analyses where treatment costs and the country considered were varied, optimal survey size was remarkably consistent, with cost-efficiency maximised at 15-20 schools per district. Among two-stage cluster surveys for schistosomiasis, our simulations indicated that surveying 15-20 schools per district and 20-30 children per school optimised cost-efficiency and minimised the risk of under-treatment, with surveys involving more schools of greater cost-efficiency as treatment costs rose.

Survey methods for assessing land cover map accuracy

USGS Publications Warehouse

Nusser, S.M.; Klaas, E.E.

2003-01-01

The increasing availability of digital photographic materials has fueled efforts by agencies and organizations to generate land cover maps for states, regions, and the United States as a whole. Regardless of the information sources and classification methods used, land cover maps are subject to numerous sources of error. In order to understand the quality of the information contained in these maps, it is desirable to generate statistically valid estimates of accuracy rates describing misclassification errors. We explored a full sample survey framework for creating accuracy assessment study designs that balance statistical and operational considerations in relation to study objectives for a regional assessment of GAP land cover maps. We focused not only on appropriate sample designs and estimation approaches, but on aspects of the data collection process, such as gaining cooperation of land owners and using pixel clusters as an observation unit. The approach was tested in a pilot study to assess the accuracy of Iowa GAP land cover maps. A stratified two-stage cluster sampling design addressed sample size requirements for land covers and the need for geographic spread while minimizing operational effort. Recruitment methods used for private land owners yielded high response rates, minimizing a source of nonresponse error. Collecting data for a 9-pixel cluster centered on the sampled pixel was simple to implement, and provided better information on rarer vegetation classes as well as substantial gains in precision relative to observing data at a single-pixel.

Galaxy evolution in merging clusters: The passive core of the "Train Wreck" cluster of galaxies, A 520

NASA Astrophysics Data System (ADS)

Deshev, Boris; Finoguenov, Alexis; Verdugo, Miguel; Ziegler, Bodo; Park, Changbom; Hwang, Ho Seong; Haines, Christopher; Kamphuis, Peter; Tamm, Antti; Einasto, Maret; Hwang, Narae; Park, Byeong-Gon

2017-11-01

Aims: The mergers of galaxy clusters are the most energetic events in the Universe after the Big Bang. With the increased availability of multi-object spectroscopy and X-ray data, an ever increasing fraction of local clusters are recognised as exhibiting signs of recent or past merging events on various scales. Our goal is to probe how these mergers affect the evolution and content of their member galaxies. We specifically aim to answer the following questions: is the quenching of star formation in merging clusters enhanced when compared with relaxed clusters? Is the quenching preceded by a (short-lived) burst of star formation? Methods: We obtained optical spectroscopy of >400 galaxies in the field of the merging cluster Abell 520. We combine these observations with archival data to obtain a comprehensive picture of the state of star formation in the members of this merging cluster. Finally, we compare these observations with a control sample of ten non-merging clusters at the same redshift from The Arizona Cluster Redshift Survey (ACReS). We split the member galaxies into passive, star forming or recently quenched depending on their spectra. Results: The core of the merger shows a decreased fraction of star forming galaxies compared to clusters in the non-merging sample. This region, dominated by passive galaxies, is extended along the axis of the merger. We find evidence of rapid quenching of the galaxies during the core passage with no signs of a star burst on the time scales of the merger (≲0.4 Gyr). Additionally, we report the tentative discovery of an infalling group along the main filament feeding the merger, currently at 2.5 Mpc from the merger centre. This group contains a high fraction of star forming galaxies as well as approximately two thirds of all the recently quenched galaxies in our survey. The reduced spectra are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/607/A131

Characterization of Hatay honeys according to their multi-element analysis using ICP-OES combined with chemometrics.

PubMed

Yücel, Yasin; Sultanoğlu, Pınar

2013-09-01

Chemical characterisation has been carried out on 45 honey samples collected from Hatay region of Turkey. The concentrations of 17 elements were determined by inductively coupled plasma optical emission spectrometry (ICP-OES). Ca, K, Mg and Na were the most abundant elements, with mean contents of 219.38, 446.93, 49.06 and 95.91 mg kg(-1) respectively. The trace element mean contents ranged between 0.03 and 15.07 mg kg(-1). Chemometric methods such as principal component analysis (PCA) and cluster analysis (CA) techniques were applied to classify honey according to mineral content. The first most important principal component (PC) was strongly associated with the value of Al, B, Cd and Co. CA showed eight clusters corresponding to the eight botanical origins of honey. PCA explained 75.69% of the variance with the first six PC variables. Chemometric analysis of the analytical data allowed the accurate classification of the honey samples according to origin. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mass calibration and cosmological analysis of the SPT-SZ galaxy cluster sample using velocity dispersion σ v and x-ray Y X measurements

DOE PAGES

Bocquet, S.; Saro, A.; Mohr, J. J.; ...

2015-01-30

Here, we present a velocity-dispersion-based mass calibration of the South Pole Telescope Sunyaev-Zel'dovich effect survey (SPT-SZ) galaxy cluster sample. Using a homogeneously selected sample of 100 cluster candidates from 720 deg 2 of the survey along with 63 velocity dispersion (σ v) and 16 X-ray Y X measurements of sample clusters, we simultaneously calibrate the mass-observable relation and constrain cosmological parameters. Our method accounts for cluster selection, cosmological sensitivity, and uncertainties in the mass calibrators. The calibrations using σ v and Y X are consistent at the 0.6σ level, with the σ v calibration preferring ~16% higher masses. We usemore » the full SPTCL data set (SZ clusters+σ v+Y X) to measure σ 8(Ωm/0.27) 0.3 = 0.809 ± 0.036 within a flat ΛCDM model. The SPT cluster abundance is lower than preferred by either the WMAP9 or Planck+WMAP9 polarization (WP) data, but assuming that the sum of the neutrino masses is m ν = 0.06 eV, we find the data sets to be consistent at the 1.0σ level for WMAP9 and 1.5σ for Planck+WP. Allowing for larger Σm ν further reconciles the results. When we combine the SPTCL and Planck+WP data sets with information from baryon acoustic oscillations and Type Ia supernovae, the preferred cluster masses are 1.9σ higher than the Y X calibration and 0.8σ higher than the σ v calibration. Given the scale of these shifts (~44% and ~23% in mass, respectively), we execute a goodness-of-fit test; it reveals no tension, indicating that the best-fit model provides an adequate description of the data. Using the multi-probe data set, we measure Ω m = 0.299 ± 0.009 and σ8 = 0.829 ± 0.011. Within a νCDM model we find Σm ν = 0.148 ± 0.081 eV. We present a consistency test of the cosmic growth rate using SPT clusters. Allowing both the growth index γ and the dark energy equation-of-state parameter w to vary, we find γ = 0.73 ± 0.28 and w = –1.007 ± 0.065, demonstrating that the eΣxpansion and the growth histories are consistent with a ΛCDM universe (γ = 0.55; w = –1).« less

Mass Calibration and Cosmological Analysis of the SPT-SZ Galaxy Cluster Sample Using Velocity Dispersion σ v and X-Ray Y X Measurements

NASA Astrophysics Data System (ADS)

Bocquet, S.; Saro, A.; Mohr, J. J.; Aird, K. A.; Ashby, M. L. N.; Bautz, M.; Bayliss, M.; Bazin, G.; Benson, B. A.; Bleem, L. E.; Brodwin, M.; Carlstrom, J. E.; Chang, C. L.; Chiu, I.; Cho, H. M.; Clocchiatti, A.; Crawford, T. M.; Crites, A. T.; Desai, S.; de Haan, T.; Dietrich, J. P.; Dobbs, M. A.; Foley, R. J.; Forman, W. R.; Gangkofner, D.; George, E. M.; Gladders, M. D.; Gonzalez, A. H.; Halverson, N. W.; Hennig, C.; Hlavacek-Larrondo, J.; Holder, G. P.; Holzapfel, W. L.; Hrubes, J. D.; Jones, C.; Keisler, R.; Knox, L.; Lee, A. T.; Leitch, E. M.; Liu, J.; Lueker, M.; Luong-Van, D.; Marrone, D. P.; McDonald, M.; McMahon, J. J.; Meyer, S. S.; Mocanu, L.; Murray, S. S.; Padin, S.; Pryke, C.; Reichardt, C. L.; Rest, A.; Ruel, J.; Ruhl, J. E.; Saliwanchik, B. R.; Sayre, J. T.; Schaffer, K. K.; Shirokoff, E.; Spieler, H. G.; Stalder, B.; Stanford, S. A.; Staniszewski, Z.; Stark, A. A.; Story, K.; Stubbs, C. W.; Vanderlinde, K.; Vieira, J. D.; Vikhlinin, A.; Williamson, R.; Zahn, O.; Zenteno, A.

2015-02-01

We present a velocity-dispersion-based mass calibration of the South Pole Telescope Sunyaev-Zel'dovich effect survey (SPT-SZ) galaxy cluster sample. Using a homogeneously selected sample of 100 cluster candidates from 720 deg2 of the survey along with 63 velocity dispersion (σ v ) and 16 X-ray Y X measurements of sample clusters, we simultaneously calibrate the mass-observable relation and constrain cosmological parameters. Our method accounts for cluster selection, cosmological sensitivity, and uncertainties in the mass calibrators. The calibrations using σ v and Y X are consistent at the 0.6σ level, with the σ v calibration preferring ~16% higher masses. We use the full SPTCL data set (SZ clusters+σ v +Y X) to measure σ8(Ωm/0.27)0.3 = 0.809 ± 0.036 within a flat ΛCDM model. The SPT cluster abundance is lower than preferred by either the WMAP9 or Planck+WMAP9 polarization (WP) data, but assuming that the sum of the neutrino masses is ∑m ν = 0.06 eV, we find the data sets to be consistent at the 1.0σ level for WMAP9 and 1.5σ for Planck+WP. Allowing for larger ∑m ν further reconciles the results. When we combine the SPTCL and Planck+WP data sets with information from baryon acoustic oscillations and Type Ia supernovae, the preferred cluster masses are 1.9σ higher than the Y X calibration and 0.8σ higher than the σ v calibration. Given the scale of these shifts (~44% and ~23% in mass, respectively), we execute a goodness-of-fit test; it reveals no tension, indicating that the best-fit model provides an adequate description of the data. Using the multi-probe data set, we measure Ωm = 0.299 ± 0.009 and σ8 = 0.829 ± 0.011. Within a νCDM model we find ∑m ν = 0.148 ± 0.081 eV. We present a consistency test of the cosmic growth rate using SPT clusters. Allowing both the growth index γ and the dark energy equation-of-state parameter w to vary, we find γ = 0.73 ± 0.28 and w = -1.007 ± 0.065, demonstrating that the expansion and the growth histories are consistent with a ΛCDM universe (γ = 0.55; w = -1).

Multi-stage internal gear/turbine fuel pump

DOEpatents

Maier, Eugen; Raney, Michael Raymond

2004-07-06

A multi-stage internal gear/turbine fuel pump for a vehicle includes a housing having an inlet and an outlet and a motor disposed in the housing. The multi-stage internal gear/turbine fuel pump also includes a shaft extending axially and disposed in the housing. The multi-stage internal gear/turbine fuel pump further includes a plurality of pumping modules disposed axially along the shaft. One of the pumping modules is a turbine pumping module and another of the pumping modules is a gerotor pumping module for rotation by the motor to pump fuel from the inlet to the outlet.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Patterns of workplace supervisor support desired by abused women.

PubMed

Perrin, Nancy A; Yragui, Nanette L; Hanson, Ginger C; Glass, Nancy

2011-07-01

The purpose of this study was to understand differences in patterns of supervisor support desired by female victims of intimate partner violence (IPV) and to examine whether the pattern of support desired at work is reflective of a woman's stage of change in the abusive relationship, IPV-related work interference, and IPV-related job reprimands or job loss. We conducted interviews in Spanish or English with adult women working in low-income jobs who had been physically or sexually abused by an intimate partner/ ex-partner in the past year ( N = 133). Cluster analysis revealed three distinct clusters that form a hierarchy of type of support wanted: those who desired limited support; those who desired confidential, time-off, and emotional support; and those who desired support in wide variety of ways from their supervisor. The clusters appeared to reflect stages of behavior change in an abusive relationship. Specifically, the limited-support cluster may represent an early precontemplation stage, with women reporting the least interference with work. The support-in-every-way cluster may represent later stages of change, in which women are breaking away from the abusive partner and report the greatest interference with work. Women in the confidential-, time-off-, and emotional-support cluster are in a transition stage in which they are considering change and are exploring options in their abusive relationship. Understanding the hierarchy of the type of support desired, and its relationship to stages of change in the abusive relationship and work interference, may provide a strong foundation for developing appropriate and effective workplace interventions to guide supervisors in providing support to women experiencing IPV.

The Sampling Design of the China Family Panel Studies (CFPS)

PubMed Central

Xie, Yu; Lu, Ping

2018-01-01

The China Family Panel Studies (CFPS) is an on-going, nearly nationwide, comprehensive, longitudinal social survey that is intended to serve research needs on a large variety of social phenomena in contemporary China. In this paper, we describe the sampling design of the CFPS sample for its 2010 baseline survey and methods for constructing weights to adjust for sampling design and survey nonresponses. Specifically, the CFPS used a multi-stage probability strategy to reduce operation costs and implicit stratification to increase efficiency. Respondents were oversampled in five provinces or administrative equivalents for regional comparisons. We provide operation details for both sampling and weights construction. PMID:29854418

Sleep stages identification in patients with sleep disorder using k-means clustering

NASA Astrophysics Data System (ADS)

Fadhlullah, M. U.; Resahya, A.; Nugraha, D. F.; Yulita, I. N.

2018-05-01

Data mining is a computational intelligence discipline where a large dataset processed using a certain method to look for patterns within the large dataset. This pattern then used for real time application or to develop some certain knowledge. This is a valuable tool to solve a complex problem, discover new knowledge, data analysis and decision making. To be able to get the pattern that lies inside the large dataset, clustering method is used to get the pattern. Clustering is basically grouping data that looks similar so a certain pattern can be seen in the large data set. Clustering itself has several algorithms to group the data into the corresponding cluster. This research used data from patients who suffer sleep disorders and aims to help people in the medical world to reduce the time required to classify the sleep stages from a patient who suffers from sleep disorders. This study used K-Means algorithm and silhouette evaluation to find out that 3 clusters are the optimal cluster for this dataset which means can be divided to 3 sleep stages.

Receptor clustering affects signal transduction at the membrane level in the reaction-limited regime

NASA Astrophysics Data System (ADS)

Caré, Bertrand R.; Soula, Hédi A.

2013-01-01

Many types of membrane receptors are found to be organized as clusters on the cell surface. We investigate the potential effect of such receptor clustering on the intracellular signal transduction stage. We consider a canonical pathway with a membrane receptor (R) activating a membrane-bound intracellular relay protein (G). We use Monte Carlo simulations to recreate biochemical reactions using different receptor spatial distributions and explore the dynamics of the signal transduction. Results show that activation of G by R is severely impaired by R clustering, leading to an apparent blunted biological effect compared to control. Paradoxically, this clustering decreases the half maximal effective dose (ED50) of the transduction stage, increasing the apparent affinity. We study an example of inter-receptor interaction in order to account for possible compensatory effects of clustering and observe the parameter range in which such interactions slightly counterbalance the loss of activation of G. The membrane receptors’ spatial distribution affects the internal stages of signal amplification, suggesting a functional role for membrane domains and receptor clustering independently of proximity-induced receptor-receptor interactions.

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: modelling the clustering and halo occupation distribution of BOSS CMASS galaxies in the Final Data Release

NASA Astrophysics Data System (ADS)

Rodríguez-Torres, Sergio A.; Chuang, Chia-Hsun; Prada, Francisco; Guo, Hong; Klypin, Anatoly; Behroozi, Peter; Hahn, Chang Hoon; Comparat, Johan; Yepes, Gustavo; Montero-Dorta, Antonio D.; Brownstein, Joel R.; Maraston, Claudia; McBride, Cameron K.; Tinker, Jeremy; Gottlöber, Stefan; Favole, Ginevra; Shu, Yiping; Kitaura, Francisco-Shu; Bolton, Adam; Scoccimarro, Román; Samushia, Lado; Schlegel, David; Schneider, Donald P.; Thomas, Daniel

2016-08-01

We present a study of the clustering and halo occupation distribution of Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxies in the redshift range 0.43 < z < 0.7 drawn from the Final SDSS-III Data Release. We compare the BOSS results with the predictions of a halo abundance matching (HAM) clustering model that assigns galaxies to dark matter haloes selected from the large BigMultiDark N-body simulation of a flat Λ cold dark matter Planck cosmology. We compare the observational data with the simulated ones on a light cone constructed from 20 subsequent outputs of the simulation. Observational effects such as incompleteness, geometry, veto masks and fibre collisions are included in the model, which reproduces within 1σ errors the observed monopole of the two-point correlation function at all relevant scales: from the smallest scales, 0.5 h-1 Mpc, up to scales beyond the baryon acoustic oscillation feature. This model also agrees remarkably well with the BOSS galaxy power spectrum (up to k ˜ 1 h Mpc-1), and the three-point correlation function. The quadrupole of the correlation function presents some tensions with observations. We discuss possible causes that can explain this disagreement, including target selection effects. Overall, the standard HAM model describes remarkably well the clustering statistics of the CMASS sample. We compare the stellar-to-halo mass relation for the CMASS sample measured using weak lensing in the Canada-France-Hawaii Telescope Stripe 82 Survey with the prediction of our clustering model, and find a good agreement within 1σ. The BigMD-BOSS light cone including properties of BOSS galaxies and halo properties is made publicly available.

A comprehensive comparative test of seven widely used spectral synthesis models against multi-band photometry of young massive-star clusters

NASA Astrophysics Data System (ADS)

Wofford, A.; Charlot, S.; Bruzual, G.; Eldridge, J. J.; Calzetti, D.; Adamo, A.; Cignoni, M.; de Mink, S. E.; Gouliermis, D. A.; Grasha, K.; Grebel, E. K.; Lee, J. C.; Östlin, G.; Smith, L. J.; Ubeda, L.; Zackrisson, E.

2016-04-01

We test the predictions of spectral synthesis models based on seven different massive-star prescriptions against Legacy ExtraGalactic UV Survey (LEGUS) observations of eight young massive clusters in two local galaxies, NGC 1566 and NGC 5253, chosen because predictions of all seven models are available at the published galactic metallicities. The high angular resolution, extensive cluster inventory, and full near-ultraviolet to near-infrared photometric coverage make the LEGUS data set excellent for this study. We account for both stellar and nebular emission in the models and try two different prescriptions for attenuation by dust. From Bayesian fits of model libraries to the observations, we find remarkably low dispersion in the median E(B - V) (˜0.03 mag), stellar masses (˜104 M⊙), and ages (˜1 Myr) derived for individual clusters using different models, although maximum discrepancies in these quantities can reach 0.09 mag and factors of 2.8 and 2.5, respectively. This is for ranges in median properties of 0.05-0.54 mag, 1.8-10 × 104 M⊙, and 1.6-40 Myr spanned by the clusters in our sample. In terms of best fit, the observations are slightly better reproduced by models with interacting binaries and least well reproduced by models with single rotating stars. Our study provides a first quantitative estimate of the accuracies and uncertainties of the most recent spectral synthesis models of young stellar populations, demonstrates the good progress of models in fitting high-quality observations, and highlights the needs for a larger cluster sample and more extensive tests of the model parameter space.

Cloud computing and validation of expandable in silico livers.

PubMed

Ropella, Glen E P; Hunt, C Anthony

2010-12-03

In Silico Livers (ISLs) are works in progress. They are used to challenge multilevel, multi-attribute, mechanistic hypotheses about the hepatic disposition of xenobiotics coupled with hepatic responses. To enhance ISL-to-liver mappings, we added discrete time metabolism, biliary elimination, and bolus dosing features to a previously validated ISL and initiated re-validated experiments that required scaling experiments to use more simulated lobules than previously, more than could be achieved using the local cluster technology. Rather than dramatically increasing the size of our local cluster we undertook the re-validation experiments using the Amazon EC2 cloud platform. So doing required demonstrating the efficacy of scaling a simulation to use more cluster nodes and assessing the scientific equivalence of local cluster validation experiments with those executed using the cloud platform. The local cluster technology was duplicated in the Amazon EC2 cloud platform. Synthetic modeling protocols were followed to identify a successful parameterization. Experiment sample sizes (number of simulated lobules) on both platforms were 49, 70, 84, and 152 (cloud only). Experimental indistinguishability was demonstrated for ISL outflow profiles of diltiazem using both platforms for experiments consisting of 84 or more samples. The process was analogous to demonstration of results equivalency from two different wet-labs. The results provide additional evidence that disposition simulations using ISLs can cover the behavior space of liver experiments in distinct experimental contexts (there is in silico-to-wet-lab phenotype similarity). The scientific value of experimenting with multiscale biomedical models has been limited to research groups with access to computer clusters. The availability of cloud technology coupled with the evidence of scientific equivalency has lowered the barrier and will greatly facilitate model sharing as well as provide straightforward tools for scaling simulations to encompass greater detail with no extra investment in hardware.

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

Breast Self Examination Practice among Female Students of Tertiary Institutions

ERIC Educational Resources Information Center

Agbonifoh, Julia Adesua

2016-01-01

Against the background of the dangers posed by breast cancer world-wide, and the importance of its early detection and therefore breast self examination (BSE), this study investigated the practice of BSE among female students in tertiary institutions in Edo state. A sample of 723 participants selected through a combination of multi-stage,…

Causal Factors Influencing Adversity Quotient of Twelfth Grade and Third-Year Vocational Students

ERIC Educational Resources Information Center

Pangma, Rachapoom; Tayraukham, Sombat; Nuangchalerm, Prasart

2009-01-01

Problem statement: The aim of this research was to study the causal factors influencing students' adversity between twelfth grade and third-year vocational students in Sisaket province, Thailand. Six hundred and seventy two of twelfth grade and 376 third-year vocational students were selected by multi-stage random sampling techniques. Approach:…

Texas School Survey of Substance Abuse: Grades 7-12. 1992.

ERIC Educational Resources Information Center

Liu, Liang Y.; Fredlund, Eric V.

The 1992 Texas School Survey results for secondary students are based on data collected from a sample of 73,073 students in grades 7 through 12. Students were randomly selected from school districts throughout the state using a multi-stage probability design. The procedure ensured that students living in metropolitan and rural areas of Texas are…

Teacher Use of Data to Guide Instructional Practice in Elementary Schools

ERIC Educational Resources Information Center

Burrows, Debra C.

2011-01-01

This descriptive study focused on the degree to which data-driven decision making as envisioned by the NCLB legislation was actually occurring in the elementary schools studied. A multi-stage random sample of six Pennsylvania school districts out of 19 located within the service area of Pennsylvania Intermediate Unit #17, one of 29 regional…

A Chondrule from the Mokoia (CV3) Chondrite with Anomalously Low 26Mg*: Evidence for a Multi-Stage History-

NASA Astrophysics Data System (ADS)

Claydon, J. L.; Elliott, T.; Coath, C. D.; Chen, H. W.; Taylor, C. A.; Russell, S. S.

2015-07-01

MC-ICP-MS measurements of Mg isotopes in chondrule MOK13B reveal that it may have formed from low-Al/Mg material that underwent chemical fractionation to increase Al/Mg after decay of 26-Al, or it may sample a region with anomalous Al or Mg isotopes.

How to Classify the Diversity of Seventh Grade Students' Mathematical Process Skills: An Application of Latent Profile Analysis

ERIC Educational Resources Information Center

Kaosa-ard, Chanapat; Erawan, Waraporn; Damrongpanit, Suntonrapot; Suksawang, Poonpong

2015-01-01

The researcher applied latent profile analysis to study the difference of the students' mathematical process skill. These skills are problem solving skills, reasoning skills, communication and presentation skills, connection knowledge skills, and creativity skills. Samples were 2,485 seventh-grade students obtained from Multi-stage Random…

Do Human-Figure Drawings of Children and Adolescents Mirror Their Cognitive Style and Self-Esteem?

ERIC Educational Resources Information Center

Dey, Anindita; Ghosh, Paromita

2016-01-01

The investigation probed relationships among human-figure drawing, field-dependent-independent cognitive style and self-esteem of 10-15 year olds. It also attempted to predict human-figure drawing scores of participants based on their field-dependence-independence and self-esteem. Area, stratified and multi-stage random sampling were used to…