The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review

PubMed Central

2014-01-01

Diet, physical activity (PA) and sedentary behavior are important, yet modifiable, determinants of obesity. Recent research into the clustering of these behaviors suggests that children and adolescents have multiple obesogenic risk factors. This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis (CA) and latent class analysis (LCA), to identify clustering patterns of diet, PA and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity. A literature search of electronic databases was undertaken to identify studies which have used data-driven methodologies to investigate the clustering of diet, PA and sedentary behavior among children and adolescents aged 5–18 years old. Eighteen studies (62% of potential studies) were identified that met the inclusion criteria, of which eight examined the clustering of PA and sedentary behavior and eight examined diet, PA and sedentary behavior. Studies were mostly cross-sectional and conducted in older children and adolescents (≥9 years). Findings from the review suggest that obesogenic cluster patterns are complex with a mixed PA/sedentary behavior cluster observed most frequently, but healthy and unhealthy patterning of all three behaviors was also reported. Cluster membership was found to differ according to age, gender and socio-economic status (SES). The tendency for older children/adolescents, particularly females, to comprise clusters defined by low PA was the most robust finding. Findings to support an association between obesogenic cluster patterns and overweight and obesity were inconclusive, with longitudinal research in this area limited. Diet, PA and sedentary behavior cluster together in complex ways that are not well understood. Further research, particularly in younger children, is needed to understand how cluster membership differs according to socio-demographic profile. Longitudinal research is also essential to establish how different cluster patterns track over time and their influence on the development of overweight and obesity. PMID:24450617

A tale of two anomalies: Depletion, dispersion, and the connection between the stellar lithium spread and inflated radii on the pre-main sequence

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

Somers, Garrett; Pinsonneault, Marc H., E-mail: somers@astronomy.ohio-state.edu, E-mail: pinsono@astronomy.ohio-state.edu

2014-07-20

We investigate lithium depletion in standard stellar models (SSMs) and main sequence (MS) open clusters, and explore the origin of the Li dispersion in young, cool stars of equal mass, age, and composition. We first demonstrate that SSMs accurately predict the Li abundances of solar analogs at the zero-age main sequence (ZAMS) within theoretical uncertainties. We then measure the rate of MS Li depletion by removing the [Fe/H]-dependent ZAMS Li pattern from three well-studied clusters, and comparing the detrended data. MS depletion is found to be mass-dependent, in the sense of more depletion at low mass. A dispersion in Limore » abundance at fixed T{sub eff} is nearly universal, and sets in by ∼200 Myr. We discuss mass and age dispersion trends, and the pattern is mixed. We argue that metallicity impacts the ZAMS Li pattern, in agreement with theoretical expectations but contrary to the findings of some previous studies, and suggest Li as a test of cluster metallicity. Finally, we argue that a radius dispersion in stars of fixed mass and age, during the epoch of pre-MS Li destruction, is responsible for the spread in Li abundances and the correlation between rotation and Li in young cool stars, most well known in the Pleiades. We calculate stellar models, inflated to match observed radius anomalies in magnetically active systems, and the resulting range of Li abundances reproduces the observed patterns of young clusters. We discuss ramifications for pre-MS evolutionary tracks and age measurements of young clusters, and suggest an observational test.« less

Delay-induced cluster patterns in coupled Cayley tree networks

NASA Astrophysics Data System (ADS)

Singh, A.; Jalan, S.

2013-07-01

We study effects of delay in diffusively coupled logistic maps on the Cayley tree networks. We find that smaller coupling values exhibit sensitiveness to value of delay, and lead to different cluster patterns of self-organized and driven types. Whereas larger coupling strengths exhibit robustness against change in delay values, and lead to stable driven clusters comprising nodes from last generation of the Cayley tree. Furthermore, introduction of delay exhibits suppression as well as enhancement of synchronization depending upon coupling strength values. To the end we discuss the importance of results to understand conflicts and cooperations observed in family business.

Extreme weather events and environmental contamination are associated with case-clusters of melioidosis in the Northern Territory of Australia.

PubMed

Cheng, Allen C; Jacups, Susan P; Gal, Daniel; Mayo, Mark; Currie, Bart J

2006-04-01

Melioidosis, the infection due to the environmental organism Burkholderia pseudomallei, is endemic to northern Australia and South East Asia. It is associated with exposure to mud and pooled surface water, but environmental determinants of this disease are poorly understood. We defined case-clusters in northern Australia, determined their contribution to the observed rate of melioidosis, and explored clinical features and associated environmental factors. Using geographical information systems data, we examined clustering of melioidosis cases in time and geographical space in the Top End of the Northern Territory of Australia between 1990 and 2002 using a scan statistic. DNA macrorestriction analysis, resolved by pulsed field gel electrophoresis, was performed on isolates from patients. We defined five case-clusters involving 27 patients that occurred within 7-28 days and/or a radius of 100-300 km. Clustered cases were associated with extreme weather events or environmental contamination; no difference in the clinical pattern of disease was noted from other patients not involved in clusters. Isolates from patients linked to environmental contamination were caused by isolates with similar DNA macrorestriction patterns, but isolates from patients linked to severe weather events had more diverse DNA macrorestriction patterns. Case-clusters of melioidosis where isolates exhibit diverse DNA macrorestriction patterns in our region are linked to extreme weather events and outbreaks where isolates are predominantly of the same DNA macrorestriction pattern are linked with contamination of an environmental source.

Effects of small-scale clustering of flowers on pollinator foraging behaviour and flower visitation rate.

PubMed

Akter, Asma; Biella, Paolo; Klecka, Jan

2017-01-01

Plants often grow in clusters of various sizes and have a variable number of flowers per inflorescence. This small-scale spatial clustering affects insect foraging strategies and plant reproductive success. In our study, we aimed to determine how visitation rate and foraging behaviour of pollinators depend on the number of flowers per plant and on the size of clusters of multiple plants using Dracocephalum moldavica (Lamiaceae) as a target species. We measured flower visitation rate by observations of insects visiting single plants and clusters of plants with different numbers of flowers. Detailed data on foraging behaviour within clusters of different sizes were gathered for honeybees, Apis mellifera, the most abundant visitor of Dracocephalum in the experiments. We found that the total number of flower visitors increased with the increasing number of flowers on individual plants and in larger clusters, but less then proportionally. Although individual honeybees visited more flowers in larger clusters, they visited a smaller proportion of flowers, as has been previously observed. Consequently, visitation rate per flower and unit time peaked in clusters with an intermediate number of flowers. These patterns do not conform to expectations based on optimal foraging theory and the ideal free distribution model. We attribute this discrepancy to incomplete information about the distribution of resources. Detailed observations and video recordings of individual honeybees also showed that the number of flowers had no effect on handling time of flowers by honeybees. We evaluated the implications of these patterns for insect foraging biology and plant reproduction.

Effects of small-scale clustering of flowers on pollinator foraging behaviour and flower visitation rate

PubMed Central

2017-01-01

Plants often grow in clusters of various sizes and have a variable number of flowers per inflorescence. This small-scale spatial clustering affects insect foraging strategies and plant reproductive success. In our study, we aimed to determine how visitation rate and foraging behaviour of pollinators depend on the number of flowers per plant and on the size of clusters of multiple plants using Dracocephalum moldavica (Lamiaceae) as a target species. We measured flower visitation rate by observations of insects visiting single plants and clusters of plants with different numbers of flowers. Detailed data on foraging behaviour within clusters of different sizes were gathered for honeybees, Apis mellifera, the most abundant visitor of Dracocephalum in the experiments. We found that the total number of flower visitors increased with the increasing number of flowers on individual plants and in larger clusters, but less then proportionally. Although individual honeybees visited more flowers in larger clusters, they visited a smaller proportion of flowers, as has been previously observed. Consequently, visitation rate per flower and unit time peaked in clusters with an intermediate number of flowers. These patterns do not conform to expectations based on optimal foraging theory and the ideal free distribution model. We attribute this discrepancy to incomplete information about the distribution of resources. Detailed observations and video recordings of individual honeybees also showed that the number of flowers had no effect on handling time of flowers by honeybees. We evaluated the implications of these patterns for insect foraging biology and plant reproduction. PMID:29136042

A comparison of heuristic and model-based clustering methods for dietary pattern analysis.

PubMed

Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia

2016-02-01

Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.

Patterned biofilm formation reveals a mechanism for structural heterogeneity in bacterial biofilms.

PubMed

Gu, Huan; Hou, Shuyu; Yongyat, Chanokpon; De Tore, Suzanne; Ren, Dacheng

2013-09-03

Bacterial biofilms are ubiquitous and are the major cause of chronic infections in humans and persistent biofouling in industry. Despite the significance of bacterial biofilms, the mechanism of biofilm formation and associated drug tolerance is still not fully understood. A major challenge in biofilm research is the intrinsic heterogeneity in the biofilm structure, which leads to temporal and spatial variation in cell density and gene expression. To understand and control such structural heterogeneity, surfaces with patterned functional alkanthiols were used in this study to obtain Escherichia coli cell clusters with systematically varied cluster size and distance between clusters. The results from quantitative imaging analysis revealed an interesting phenomenon in which multicellular connections can be formed between cell clusters depending on the size of interacting clusters and the distance between them. In addition, significant differences in patterned biofilm formation were observed between wild-type E. coli RP437 and some of its isogenic mutants, indicating that certain cellular and genetic factors are involved in interactions among cell clusters. In particular, autoinducer-2-mediated quorum sensing was found to be important. Collectively, these results provide missing information that links cell-to-cell signaling and interaction among cell clusters to the structural organization of bacterial biofilms.

Geomorphological analysis of boulders and polygons on Martian periglacial patterned ground terrains

NASA Astrophysics Data System (ADS)

Orloff, Travis C.

Images from the High Resolution Imaging Science Experiment Camera onboard the Mars Reconnaisance Orbiter show the surface in higher detail than previously capable. I look at a landscape on Mars called permafrost patterned ground which covers ˜10 million square kilometers of the surface at high latitudes (>50°). Using the new high resolution images available we objectively characterize permafrost patterned ground terrains as an alternative to observational surveys which while detailed suffer from subjective bias. I take two dimensional Fourier transforms of individual images of Martian permafrost patterned ground to find the scale most representative of the terrain. This scale acts as a proxy for the size of the polygons themselves. Then I look at the distribution of spectral scales in the northern hemisphere between 50-70° and find correlations to previous studies and with the extent of ground ice in the surface. The high resolution images also show boulders clustering with respect to the underlying pattern. I make the first detailed observations of these clustered boulders and use crater counting to place constraints on the time it takes for boulders to cluster. Finally, I present a potential mechanism for the process that clusters the boulders that takes the specifics of the Martian environment to account. Boulders lying on the surface get trapped in seasonal CO2 frost while ice in the near surface contracts in the winter. The CO2 frost sublimates in spring/summer allowing the boulders to move when the near surface ice expands in summer. Repeated iterations lead to boulders that cluster in the polygon edges. Using a thermal model of the subsurface with Mars conditions and an elastic model of a polygon I show boulders could move as much as ˜0.1mm per year in the present day.

Five task clusters that enable efficient and effective digitization of biological collections

PubMed Central

Nelson, Gil; Paul, Deborah; Riccardi, Gregory; Mast, Austin R.

2012-01-01

Abstract This paper describes and illustrates five major clusters of related tasks (herein referred to as task clusters) that are common to efficient and effective practices in the digitization of biological specimen data and media. Examples of these clusters come from the observation of diverse digitization processes. The staff of iDigBio (The U.S. National Science Foundation’s National Resource for Advancing Digitization of Biological Collections) visited active biological and paleontological collections digitization programs for the purpose of documenting and assessing current digitization practices and tools. These observations identified five task clusters that comprise the digitization process leading up to data publication: (1) pre-digitization curation and staging, (2) specimen image capture, (3) specimen image processing, (4) electronic data capture, and (5) georeferencing locality descriptions. While not all institutions are completing each of these task clusters for each specimen, these clusters describe a composite picture of digitization of biological and paleontological specimens across the programs that were observed. We describe these clusters, three workflow patterns that dominate the implemention of these clusters, and offer a set of workflow recommendations for digitization programs. PMID:22859876

Positive feedback can lead to dynamic nanometer-scale clustering on cell membranes

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

Wehrens, Martijn; Rein ten Wolde, Pieter; Mugler, Andrew, E-mail: amugler@purdue.edu

2014-11-28

Clustering of molecules on biological membranes is a widely observed phenomenon. A key example is the clustering of the oncoprotein Ras, which is known to be important for signal transduction in mammalian cells. Yet, the mechanism by which Ras clusters form and are maintained remains unclear. Recently, it has been discovered that activated Ras promotes further Ras activation. Here we show using particle-based simulation that this positive feedback is sufficient to produce persistent clusters of active Ras molecules at the nanometer scale via a dynamic nucleation mechanism. Furthermore, we find that our cluster statistics are consistent with experimental observations ofmore » the Ras system. Interestingly, we show that our model does not support a Turing regime of macroscopic reaction-diffusion patterning, and therefore that the clustering we observe is a purely stochastic effect, arising from the coupling of positive feedback with the discrete nature of individual molecules. These results underscore the importance of stochastic and dynamic properties of reaction diffusion systems for biological behavior.« less

Kinematic gait patterns in healthy runners: A hierarchical cluster analysis.

PubMed

Phinyomark, Angkoon; Osis, Sean; Hettinga, Blayne A; Ferber, Reed

2015-11-05

Previous studies have demonstrated distinct clusters of gait patterns in both healthy and pathological groups, suggesting that different movement strategies may be represented. However, these studies have used discrete time point variables and usually focused on only one specific joint and plane of motion. Therefore, the first purpose of this study was to determine if running gait patterns for healthy subjects could be classified into homogeneous subgroups using three-dimensional kinematic data from the ankle, knee, and hip joints. The second purpose was to identify differences in joint kinematics between these groups. The third purpose was to investigate the practical implications of clustering healthy subjects by comparing these kinematics with runners experiencing patellofemoral pain (PFP). A principal component analysis (PCA) was used to reduce the dimensionality of the entire gait waveform data and then a hierarchical cluster analysis (HCA) determined group sets of similar gait patterns and homogeneous clusters. The results show two distinct running gait patterns were found with the main between-group differences occurring in frontal and sagittal plane knee angles (P<0.001), independent of age, height, weight, and running speed. When these two groups were compared to PFP runners, one cluster exhibited greater while the other exhibited reduced peak knee abduction angles (P<0.05). The variability observed in running patterns across this sample could be the result of different gait strategies. These results suggest care must be taken when selecting samples of subjects in order to investigate the pathomechanics of injured runners. Copyright © 2015 Elsevier Ltd. All rights reserved.

Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

PubMed Central

Hallac, David; Vare, Sagar; Boyd, Stephen; Leskovec, Jure

2018-01-01

Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. PMID:29770257

Spatial location influences vocal interactions in bullfrog choruses

PubMed Central

Bates, Mary E.; Cropp, Brett F.; Gonchar, Marina; Knowles, Jeffrey; Simmons, James A.; Simmons, Andrea Megela

2010-01-01

A multiple sensor array was employed to identify the spatial locations of all vocalizing male bullfrogs (Rana catesbeiana) in five natural choruses. Patterns of vocal activity collected with this array were compared with computer simulations of chorus activity. Bullfrogs were not randomly spaced within choruses, but tended to cluster into closely spaced groups of two to five vocalizing males. There were nonrandom, differing patterns of vocal interactions within clusters of closely spaced males and between different clusters. Bullfrogs located within the same cluster tended to overlap or alternate call notes with two or more other males in that cluster. These near-simultaneous calling bouts produced advertisement calls with more pronounced amplitude modulation than occurred in nonoverlapping notes or calls. Bullfrogs located in different clusters more often alternated entire calls or overlapped only small segments of their calls. They also tended to respond sequentially to calls of their farther neighbors compared to their nearer neighbors. Results of computational analyses showed that the observed patterns of vocal interactions were significantly different than expected based on random activity. The use of a multiple sensor array provides a richer view of the dynamics of choruses than available based on single microphone techniques. PMID:20370047

p-capture reaction cycles in rotating massive stars and their impact on elemental abundances in globular cluster stars: A case study of O, Na and Al

NASA Astrophysics Data System (ADS)

Mahanta, Upakul; Goswami, Aruna; Duorah, Hiralal; Duorah, Kalpana

2017-08-01

Elemental abundance patterns of globular cluster stars can provide important clues for understanding cluster formation and early chemical evolution. The origin of the abundance patterns, however, still remains poorly understood. We have studied the impact of p-capture reaction cycles on the abundances of oxygen, sodium and aluminium considering nuclear reaction cycles of carbon-nitrogen-oxygen-fluorine, neon-sodium and magnesium-aluminium in massive stars in stellar conditions of temperature range 2×107 to 10×107 K and typical density of 102 gm cc-1. We have estimated abundances of oxygen, sodium and aluminium with respect to Fe, which are then assumed to be ejected from those stars because of rotation reaching a critical limit. These ejected abundances of elements are then compared with their counterparts that have been observed in some metal-poor evolved stars, mainly giants and red giants, of globular clusters M3, M4, M13 and NGC 6752. We observe an excellent agreement with [O/Fe] between the estimated and observed abundance values for globular clusters M3 and M4 with a correlation coefficient above 0.9 and a strong linear correlation for the remaining two clusters with a correlation coefficient above 0.7. The estimated [Na/Fe] is found to have a correlation coefficient above 0.7, thus implying a strong correlation for all four globular clusters. As far as [Al/Fe] is concerned, it also shows a strong correlation between the estimated abundance and the observed abundance for globular clusters M13 and NGC 6752, since here also the correlation coefficient is above 0.7 whereas for globular cluster M4 there is a moderate correlation found with a correlation coefficient above 0.6. Possible sources of these discrepancies are discussed.

Using hierarchical cluster models to systematically identify groups of jobs with similar occupational questionnaire response patterns to assist rule-based expert exposure assessment in population-based studies.

PubMed

Friesen, Melissa C; Shortreed, Susan M; Wheeler, David C; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S; Baris, Dalsu; Karagas, Margaret R; Schwenn, Molly; Johnson, Alison; Armenti, Karla R; Silverman, Debra T; Yu, Kai

2015-05-01

Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m(-3) respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters' homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job's estimate and the mean estimate for all jobs within the cluster. Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2014.

Coulomb Fission in Multiply-Charged Ammonia Clusters: Accurate Measurements of the Rayleigh Instability Limit from Fragmentation Patterns.

PubMed

Harris, Christopher; Stace, Anthony J

2018-03-15

A series of experiments have been undertaken on the fragmentation of multiply charged ammonia clusters, (NH 3 ) n z+ , where z ≤ 8 and n ≤ 850, to establish Rayleigh instability limits, whereby clusters at certain critical sizes become unstable due to Coulomb repulsion between the resident charges. Experimental results on size-selected clusters are found to be in excellent agreement with theoretical predictions of Rayleigh instability limits at all values of the charge. Electrostatic theory has been used to help identify fragmentation patterns on the assumption that the clusters separate into two dielectric spheres, and the predicted Coulomb repulsion energies used to establish pathways and the sizes of cluster fragments. The results show that fragmentation is very asymmetric in terms of both the numbers of molecules involved and the amount of charge each fragment accommodates. For clusters carrying a charge ≤+4, the results show that fragmentation proceeds via the loss of small, singly charged clusters. When clusters carry a charge of +5 or more, the experimental observations suggest a marked switch in behavior. Although the laboratory measurements equate to fragmentation via the loss of a large dication cluster, electrostatic theory supports an interpretation that involves the sequential loss of two smaller, singly charged clusters possibly accompanied by the extensive evaporation of neutral molecules. It is suggested that this change in fragmentation pattern is driven by the channelling of Coulomb repulsion energy into intermolecular modes within these larger clusters. Overall, the results appear to support the ion evaporation model that is frequently used to interpret electrospray experiments.

HIV transmission patterns among The Netherlands, Suriname, and The Netherlands Antilles: a molecular epidemiological study.

PubMed

Kramer, Merlijn A; Cornelissen, Marion; Paraskevis, Dimitrios; Prins, Maria; Coutinho, Roel A; van Sighem, Ard I; Sabajo, Lesley; Duits, Ashley J; Winkel, Cai N; Prins, Jan M; van der Ende, Marchina E; Kauffmann, Robert H; Op de Coul, Eline L

2011-02-01

We aimed to study patterns of HIV transmission among Suriname, The Netherlands Antilles, and The Netherlands. Fragments of env, gag, and pol genes of 55 HIV-infected Surinamese, Antillean, and Dutch heterosexuals living in The Netherlands and 72 HIV-infected heterosexuals living in Suriname and the Antilles were amplified and sequenced. We included 145 pol sequences of HIV-infected Surinamese, Antillean, and Dutch heterosexuals living in The Netherlands from an observational cohort. All sequences were phylogenetically analyzed by neighbor-joining. Additionally, HIV-1 mobility among ethnic groups was estimated. A phylogenetic tree of all pol sequences showed two Surinamese and three Antillean clusters of related strains, but no clustering between ethnic groups. Clusters included sequences of individuals living in Suriname and the Antilles as well as those who have migrated to The Netherlands. Similar clustering patterns were observed in env and gag. Analysis of HIV mobility among ethnic groups showed significantly lower migration between groups than expected under the hypothesis of panmixis, apart from higher HIV migration between Antilleans in The Netherlands and all other groups. Our study shows that HIV transmission mainly occurs within the ethnic group. This suggests that cultural factors could have a larger impact on HIV mobility than geographic distance.

Spatial and temporal patterns in preterm birth in the United States.

PubMed

Byrnes, John; Mahoney, Richard; Quaintance, Cele; Gould, Jeffrey B; Carmichael, Suzan; Shaw, Gary M; Showen, Amy; Phibbs, Ciaran; Stevenson, David K; Wise, Paul H

2015-06-01

Despite years of research, the etiologies of preterm birth remain unclear. In order to help generate new research hypotheses, this study explored spatial and temporal patterns of preterm birth in a large, total-population dataset. Data on 145 million US births in 3,000 counties from the Natality Files of the National Center for Health Statistics for 1971-2011 were examined. State trends in early (<34 wk) and late (34-36 wk) preterm birth rates were compared. K-means cluster analyses were conducted to identify gestational age distribution patterns for all US counties over time. A weak association was observed between state trends in <34 wk birth rates and the initial absolute <34 wk birth rate. Significant associations were observed between trends in <34 wk and 34-36 wk birth rates and between white and African American <34 wk births. Periodicity was observed in county-level trends in <34 wk birth rates. Cluster analyses identified periods of significant heterogeneity and homogeneity in gestational age distributional trends for US counties. The observed geographic and temporal patterns suggest periodicity and complex, shared influences among preterm birth rates in the United States. These patterns could provide insight into promising hypotheses for further research.

Using Hierarchical Cluster Models to Systematically Identify Groups of Jobs With Similar Occupational Questionnaire Response Patterns to Assist Rule-Based Expert Exposure Assessment in Population-Based Studies

PubMed Central

Friesen, Melissa C.; Shortreed, Susan M.; Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Armenti, Karla R.; Silverman, Debra T.; Yu, Kai

2015-01-01

Objectives: Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Methods: Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m−3 respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters’ homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job’s estimate and the mean estimate for all jobs within the cluster. Results: Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. Conclusions: This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. PMID:25477475

Patterns of breast cancer mortality trends in Europe.

PubMed

Amaro, Joana; Severo, Milton; Vilela, Sofia; Fonseca, Sérgio; Fontes, Filipa; La Vecchia, Carlo; Lunet, Nuno

2013-06-01

To identify patterns of variation in breast cancer mortality in Europe (1980-2010), using a model-based approach. Mortality data were obtained from the World Health Organization database and mixed models were used to describe the time trends in the age-standardized mortality rates (ASMR). Model-based clustering was used to identify clusters of countries with homogeneous variation in ASMR. Three patterns were identified. Patterns 1 and 2 are characterized by stable or slightly increasing trends in ASMR in the first half of the period analysed, and a clear decline is observed thereafter; in pattern 1 the median of the ASMR is higher, and the highest rates were achieved sooner. Pattern 3 is characterised by a rapid increase in mortality until 1999, declining slowly thereafter. This study provides a general model for the description and interpretation of the variation in breast cancer mortality in Europe, based in three main patterns. Copyright © 2013 Elsevier Ltd. All rights reserved.

Time fluctuation analysis of forest fire sequences

NASA Astrophysics Data System (ADS)

Vega Orozco, Carmen D.; Kanevski, Mikhaïl; Tonini, Marj; Golay, Jean; Pereira, Mário J. G.

2013-04-01

Forest fires are complex events involving both space and time fluctuations. Understanding of their dynamics and pattern distribution is of great importance in order to improve the resource allocation and support fire management actions at local and global levels. This study aims at characterizing the temporal fluctuations of forest fire sequences observed in Portugal, which is the country that holds the largest wildfire land dataset in Europe. This research applies several exploratory data analysis measures to 302,000 forest fires occurred from 1980 to 2007. The applied clustering measures are: Morisita clustering index, fractal and multifractal dimensions (box-counting), Ripley's K-function, Allan Factor, and variography. These algorithms enable a global time structural analysis describing the degree of clustering of a point pattern and defining whether the observed events occur randomly, in clusters or in a regular pattern. The considered methods are of general importance and can be used for other spatio-temporal events (i.e. crime, epidemiology, biodiversity, geomarketing, etc.). An important contribution of this research deals with the analysis and estimation of local measures of clustering that helps understanding their temporal structure. Each measure is described and executed for the raw data (forest fires geo-database) and results are compared to reference patterns generated under the null hypothesis of randomness (Poisson processes) embedded in the same time period of the raw data. This comparison enables estimating the degree of the deviation of the real data from a Poisson process. Generalizations to functional measures of these clustering methods, taking into account the phenomena, were also applied and adapted to detect time dependences in a measured variable (i.e. burned area). The time clustering of the raw data is compared several times with the Poisson processes at different thresholds of the measured function. Then, the clustering measure value depends on the threshold which helps to understand the time pattern of the studied events. Our findings detected the presence of overdensity of events in particular time periods and showed that the forest fire sequences in Portugal can be considered as a multifractal process with a degree of time-clustering of the events. Key words: time sequences, Morisita index, fractals, multifractals, box-counting, Ripley's K-function, Allan Factor, variography, forest fires, point process. Acknowledgements This work was partly supported by the SNFS Project No. 200021-140658, "Analysis and Modelling of Space-Time Patterns in Complex Regions". References - Kanevski M. (Editor). 2008. Advanced Mapping of Environmental Data: Geostatistics, Machine Learning and Bayesian Maximum Entropy. London / Hoboken: iSTE / Wiley. - Telesca L. and Pereira M.G. 2010. Time-clustering investigation of fire temporal fluctuations in Portugal, Nat. Hazards Earth Syst. Sci., vol. 10(4): 661-666. - Vega Orozco C., Tonini M., Conedera M., Kanevski M. (2012) Cluster recognition in spatial-temporal sequences: the case of forest fires, Geoinformatica, vol. 16(4): 653-673.

Globular cluster chemistry in fast-rotating dwarf stars belonging to intermediate-age open clusters

NASA Astrophysics Data System (ADS)

Pancino, Elena

2018-06-01

The peculiar chemistry observed in multiple populations of Galactic globular clusters is not generally found in other systems such as dwarf galaxies and open clusters, and no model can currently fully explain it. Exploring the boundaries of the multiple-population phenomenon and the variation of its extent in the space of cluster mass, age, metallicity, and compactness has proven to be a fruitful line of investigation. In the framework of a larger project to search for multiple populations in open clusters that is based on literature and survey data, I found peculiar chemical abundance patterns in a sample of intermediate-age open clusters with publicly available data. More specifically, fast-rotating dwarf stars (v sin i ≥ 50 km s-1) that belong to four clusters (Pleiades, Ursa Major, Come Berenices, and Hyades) display a bimodality in either [Na/Fe] or [O/Fe], or both, with the low-Na and high-O peak more populated than the high-Na and low-O peak. Additionally, two clusters show a Na-O anti-correlation in the fast-rotating stars, and one cluster shows a large [Mg/Fe] variation in stars with high [Na/Fe], reaching the extreme Mg depletion observed in NGC 2808. Even considering that the sample sizes are small, these patterns call for attention in the light of a possible connection with the multiple population phenomenon of globular clusters. The specific chemistry observed in these fast-rotating dwarf stars is thought to be produced by a complex interplay of different diffusion and mixing mechanisms, such as rotational mixing and mass loss, which in turn are influenced by metallicity, binarity, mass, age, variability, and so on. However, with the sample in hand, it was not possible to identify which stellar parameters cause the observed Na and O bimodality and Na-O anti-correlation. This suggests that other stellar properties might be important in addition to stellar rotation. Stellar binarity might influence the rotational properties and enhance rotational mixing and mass loss of stars in a dense environment like that of clusters (especially globulars). In conclusion, rotation and binarity appear as a promising research avenue for better understanding multiple stellar populations in globular clusters; this is certainly worth exploring further.

Are clusters of dietary patterns and cluster membership stable over time? Results of a longitudinal cluster analysis study.

PubMed

Walthouwer, Michel Jean Louis; Oenema, Anke; Soetens, Katja; Lechner, Lilian; de Vries, Hein

2014-11-01

Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition. This study had a longitudinal design with online measurements at baseline (N=483) and 6 months follow-up (N=379). Dietary intake was assessed with a validated food frequency questionnaire. A hierarchical cluster analysis was performed, followed by a K-means cluster analysis. Multinomial logistic regression analyses were conducted to identify the sociodemographic predictors of cluster membership and cluster transition. At baseline and follow-up, a comparable three-cluster solution was derived, distinguishing a healthy, moderately healthy, and unhealthy dietary pattern. Male and lower educated participants were significantly more likely to have a less healthy dietary pattern. Further, 251 (66.2%) participants remained in the same cluster, 45 (11.9%) participants changed to an unhealthier cluster, and 83 (21.9%) participants shifted to a healthier cluster. Men and people living alone were significantly more likely to shift toward a less healthy dietary pattern. Distinctive clusters of dietary patterns can be derived. Yet, cluster membership is unstable and only few sociodemographic factors were associated with cluster membership and cluster transition. These findings imply that clusters based on dietary intake may not be suitable as a basis for nutrition education interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Microbial community pattern detection in human body habitats via ensemble clustering framework.

PubMed

Yang, Peng; Su, Xiaoquan; Ou-Yang, Le; Chua, Hon-Nian; Li, Xiao-Li; Ning, Kang

2014-01-01

The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. Recent studies on healthy human microbiome focus on particular body habitats, assuming that microbiome develop similar structural patterns to perform similar ecosystem function under same environmental conditions. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively. To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural pattern. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender. In summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. The clustering results indicate that structure of human microbiome is varied systematically across body habitats and host genders. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome.

Microbial community pattern detection in human body habitats via ensemble clustering framework

PubMed Central

2014-01-01

Background The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. Recent studies on healthy human microbiome focus on particular body habitats, assuming that microbiome develop similar structural patterns to perform similar ecosystem function under same environmental conditions. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively. Results To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural pattern. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender. Conclusions In summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. The clustering results indicate that structure of human microbiome is varied systematically across body habitats and host genders. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome. PMID:25521415

Determination of Arctic sea ice variability modes on interannual timescales via nonhierarchical clustering

NASA Astrophysics Data System (ADS)

Fučkar, Neven-Stjepan; Guemas, Virginie; Massonnet, François; Doblas-Reyes, Francisco

2015-04-01

Over the modern observational era, the northern hemisphere sea ice concentration, age and thickness have experienced a sharp long-term decline superimposed with strong internal variability. Hence, there is a crucial need to identify robust patterns of Arctic sea ice variability on interannual timescales and disentangle them from the long-term trend in noisy datasets. The principal component analysis (PCA) is a versatile and broadly used method for the study of climate variability. However, the PCA has several limiting aspects because it assumes that all modes of variability have symmetry between positive and negative phases, and suppresses nonlinearities by using a linear covariance matrix. Clustering methods offer an alternative set of dimension reduction tools that are more robust and capable of taking into account possible nonlinear characteristics of a climate field. Cluster analysis aggregates data into groups or clusters based on their distance, to simultaneously minimize the distance between data points in a given cluster and maximize the distance between the centers of the clusters. We extract modes of Arctic interannual sea-ice variability with nonhierarchical K-means cluster analysis and investigate the mechanisms leading to these modes. Our focus is on the sea ice thickness (SIT) as the base variable for clustering because SIT holds most of the climate memory for variability and predictability on interannual timescales. We primarily use global reconstructions of sea ice fields with a state-of-the-art ocean-sea-ice model, but we also verify the robustness of determined clusters in other Arctic sea ice datasets. Applied cluster analysis over the 1958-2013 period shows that the optimal number of detrended SIT clusters is K=3. Determined SIT cluster patterns and their time series of occurrence are rather similar between different seasons and months. Two opposite thermodynamic modes are characterized with prevailing negative or positive SIT anomalies over the Arctic basin. The intermediate mode, with negative anomalies centered on the East Siberian shelf and positive anomalies along the North American side of the basin, has predominately dynamic characteristics. The associated sea ice concentration (SIC) clusters vary more between different seasons and months, but the SIC patterns are physically framed by the SIT cluster patterns.

How Escherichia coli lands and forms cell clusters on a surface: a new role of surface topography

PubMed Central

Gu, Huan; Chen, Aaron; Song, Xinran; Brasch, Megan E.; Henderson, James H.; Ren, Dacheng

2016-01-01

Bacterial response to surface topography during biofilm formation was studied using 5 μm tall line patterns of poly (dimethylsiloxane) (PDMS). Escherichia coli cells attached on top of protruding line patterns were found to align more perpendicularly to the orientation of line patterns when the pattern narrowed. Consistently, cell cluster formation per unit area on 5 μm wide line patterns was reduced by 14-fold compared to flat PDMS. Contrasting the reduced colony formation, cells attached on narrow patterns were longer and had higher transcriptional activities, suggesting that such unfavorable topography may present a stress to attached cells. Results of mutant studies indicate that flagellar motility is involved in the observed preference in cell orientation on narrow patterns, which was corroborated by the changes in cell rotation pattern before settling on different surface topographies. These findings led to a set of new design principles for creating antifouling topographies, which was validated using 10 μm tall hexagonal patterns. PMID:27412365

An approach to online network monitoring using clustered patterns

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

Kim, Jinoh; Sim, Alex; Suh, Sang C.

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less

An approach to online network monitoring using clustered patterns

DOE PAGES

Kim, Jinoh; Sim, Alex; Suh, Sang C.; ...

2017-03-13

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less

Suicide methods in children and adolescents.

PubMed

Kõlves, Kairi; de Leo, Diego

2017-02-01

There are notable differences in suicide methods between countries. The aim of this paper is to analyse and describe suicide methods in children and adolescents aged 10-19 years in different countries/territories worldwide. Suicide data by ICD-10 X codes were obtained from the WHO Mortality Database and population data from the World Bank. In total, 101 countries or territories, have data at least for 5 years in 2000-2009. Cluster analysis by suicide methods was performed for countries/territories with at least 10 suicide cases separately by gender (74 for males and 71 for females) in 2000-2009. The most frequent suicide method was hanging, followed by poisoning by pesticides for females and firearms for males. Cluster analyses of similarities in the country/territory level suicide method patterns by gender identified four clusters for both gender. Hanging and poisoning by pesticides defined the clusters of countries/territories by their suicide patterns in youth for both genders. In addition, a mixed method and a jumping from height cluster were identified for females and two mixed method clusters for males. A number of geographical similarities were observed. Overall, the patterns of suicide methods in children and adolescents reflect lethality, availability and acceptability of suicide means similarly to country specific patterns of all ages. Means restriction has very good potential in preventing youth suicides in different countries. It is also crucial to consider cognitive availability influenced by sensationalised media reporting and/or provision of technical details about specific methods.

Explaining ecological clusters of maternal depression in South Western Sydney.

PubMed

Eastwood ED, John; Kemp, Lynn; Jalaludin, Bin

2014-01-24

The aim of the qualitative study reported here was to: 1) explain the observed clustering of postnatal depressive symptoms in South Western Sydney; and 2) identify group-level mechanisms that would add to our understanding of the social determinants of maternal depression. Critical realism provided the methodological underpinning for the study. The setting was four local government areas in South Western Sydney, Australia. Child and Family practitioners and mothers in naturally occurring mothers groups were interviewed. Using an open coding approach to maximise emergence of patterns and relationships we have identified seven theoretical concepts that might explain the observed spatial clustering of maternal depression. The theoretical concepts identified were: Community-level social networks; Social Capital and Social Cohesion; "Depressed community"; Access to services at the group level; Ethnic segregation and diversity; Supportive social policy; and Big business. We postulate that these regional structural, economic, social and cultural mechanisms partially explain the pattern of maternal depression observed in families and communities within South Western Sydney. We further observe that powerful global economic and political forces are having an impact on the local situation. The challenge for policy and practice is to support mothers and their families within this adverse regional and global-economic context.

Multiwavelength Studies of Young OB Associations

NASA Astrophysics Data System (ADS)

Feigelson, Eric D.

We discuss how contemporary multiwavelength observations of young OB-dominated clusters address long-standing astrophysical questions: Do clusters form rapidly or slowly with an age spread? When do clusters expand and disperse to constitute the field star population? Do rich clusters form by amalgamation of smaller subclusters? What is the pattern and duration of cluster formation in massive star forming regions (MSFRs)? Past observational difficulties in obtaining good stellar censuses of MSFRs have been alleviated in recent studies that combine X-ray and infrared surveys to obtain rich, though still incomplete, censuses of young stars in MSFRs. We describe here one of these efforts, the MYStIX project, that produced a catalog of 31,784 probable members of 20 MSFRs. We find that age spread within clusters is real in the sense that the stars in the core formed after the cluster halo. This is consistent with some recent astrophysical models involving merging star-forming filaments. Cluster expansion is seen in the ensemble of (sub)clusters, and older dispersing populations are found across MSFRs. Long-lived, asynchronous star formation is pervasive across MSFRs.

Dietary patterns by cluster analysis in pregnant women: relationship with nutrient intakes and dietary patterns in 7-year-old offspring.

PubMed

Freitas-Vilela, Ana Amélia; Smith, Andrew D A C; Kac, Gilberto; Pearson, Rebecca M; Heron, Jon; Emond, Alan; Hibbeln, Joseph R; Castro, Maria Beatriz Trindade; Emmett, Pauline M

2017-04-01

Little is known about how dietary patterns of mothers and their children track over time. The objectives of this study are to obtain dietary patterns in pregnancy using cluster analysis, to examine women's mean nutrient intakes in each cluster and to compare the dietary patterns of mothers to those of their children. Pregnant women (n = 12 195) from the Avon Longitudinal Study of Parents and Children reported their frequency of consumption of 47 foods and food groups. These data were used to obtain dietary patterns during pregnancy by cluster analysis. The absolute and energy-adjusted nutrient intakes were compared between clusters. Women's dietary patterns were compared with previously derived clusters of their children at 7 years of age. Multinomial logistic regression was performed to evaluate relationships comparing maternal and offspring clusters. Three maternal clusters were identified: 'fruit and vegetables', 'meat and potatoes' and 'white bread and coffee'. After energy adjustment women in the 'fruit and vegetables' cluster had the highest mean nutrient intakes. Mothers in the 'fruit and vegetables' cluster were more likely than mothers in 'meat and potatoes' (adjusted odds ratio [OR]: 2.00; 95% Confidence Interval [CI]: 1.69-2.36) or 'white bread and coffee' (OR: 2.18; 95% CI: 1.87-2.53) clusters to have children in a 'plant-based' cluster. However the majority of children were in clusters unrelated to their mother dietary pattern. Three distinct dietary patterns were obtained in pregnancy; the 'fruit and vegetables' pattern being the most nutrient dense. Mothers' dietary patterns were associated with but did not dominate offspring dietary patterns. © 2016 The Authors. Maternal & Child Nutrition published by John Wiley & Sons Ltd.

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

PubMed

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

2015-01-01

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

On the determination of age and mass functions of stars in young open star clusters from the analysis of their luminosity functions

NASA Astrophysics Data System (ADS)

Piskunov, A. E.; Belikov, A. N.; Kharchenko, N. V.; Sagar, R.; Subramaniam, A.

2004-04-01

We construct the observed luminosity functions of the remote young open clusters NGC 2383, 2384, 4103, 4755, 7510 and Hogg 15 from CCD observations of them. The observed LFs are corrected for field star contamination determined with the help of a Galactic star count model. In the case of Hogg 15 and NGC 2383 we also consider the additional contamination from neighbouring clusters NGC 4609 and 2384, respectively. These corrections provide a realistic pattern of cluster LF in the vicinity of the main-sequence (MS) turn-on point and at fainter magnitudes reveal the so-called H-feature arising as a result of the transition of the pre-MS phase to the MS, which is dependent on the cluster age. The theoretical LFs are constructed representing a cluster population model with continuous star formation for a short time-scale and a power-law initial mass function (IMF), and these are fitted to the observed LF. As a result, we are able to determine for each cluster a set of parameters describing the cluster population (the age, duration of star formation, IMF slope and percentage of field star contamination). It is found that in spite of the non-monotonic behaviour of observed LFs, cluster IMFs can be described as power-law functions with slopes similar to Salpeter's value. The present main-sequence turn-on cluster ages are several times lower than those derived from the fitting of theoretical isochrones to the turn-off region of the upper main sequences.

Title: Chimeras in small, globally coupled networks: Experiments and stability analysis

NASA Astrophysics Data System (ADS)

Hart, Joseph D.; Bansal, Kanika; Murphy, Thomas E.; Roy, Rajarshi

Since the initial observation of chimera states, there has been much discussion of the conditions under which these states emerge. The emphasis thus far has mainly been to analyze large networks of coupled oscillators; however, recent studies have begun to focus on the opposite limit: what is the smallest system of coupled oscillators in which chimeras can exist? We experimentally observe chimeras and other partially synchronous patterns in a network of four globally-coupled chaotic opto-electronic oscillators. By examining the equations of motion, we demonstrate that symmetries in the network topology allow a variety of synchronous states to exist, including cluster synchronous states and a chimera state. Using the group theoretical approach recently developed for analyzing cluster synchronization, we show how to derive the variational equations for these synchronous patterns and calculate their linear stability. The stability analysis gives good agreement with our experimental results. Both experiments and simulations suggest that these chimera states often appear in regions of multistability between global, cluster, and desynchronized states.

Pattern of comorbidity among anxious and odd personality disorders: the case of obsessive-compulsive personality disorder.

PubMed

Rossi, A; Marinangeli, M G; Butti, G; Kalyvoka, A; Petruzzi, C

2000-09-01

The aim of this study was to examine the pattern of comorbidity among obsessive-compulsive personality disorder (OCPD) and other personality disorders (PDs) in a sample of 400 psychiatric inpatients. PDs were assessed using the Semistructured Clinical Interview for DSM-III-R Personality Disorders (SCID-II). Odds ratios (ORs) were calculated to determine significant comorbidity among OCPD and other axis II disorders. The most elevated odds ratios were found for the cooccurrence of OCPD with cluster A PDs (the "odd" PDs, or paranoid and schizoid PDs). These results are consistent with those of previous studies showing a higher cooccurrence of OCPD with cluster A than with cluster C ("anxious") PDs. In light of these observations, issues associated with the nosologic status of OCPD within the Diagnostic and Statistical Manual of Mental Disorders clustering system remain unsettled.

Links between patterns of racial socialization and discrimination experiences and psychological adjustment: a cluster analysis.

PubMed

Ajayi, Alex A; Syed, Moin

2014-10-01

This study used a person-oriented analytic approach to identify meaningful patterns of barriers-focused racial socialization and perceived racial discrimination experiences in a sample of 295 late adolescents. Using cluster analysis, three distinct groups were identified: Low Barrier Socialization-Low Discrimination, High Barrier Socialization-Low Discrimination, and High Barrier Socialization-High Discrimination clusters. These groups were substantively unique in terms of the frequency of racial socialization messages about bias preparation and out-group mistrust its members received and their actual perceived discrimination experiences. Further, individuals in the High Barrier Socialization-High Discrimination cluster reported significantly higher depressive symptoms than those in the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. However, no differences in adjustment were observed between the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. Overall, the findings highlight important individual differences in how young people of color experience their race and how these differences have significant implications on psychological adjustment. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Ozone trends and their relationship to characteristic weather patterns.

PubMed

Austin, Elena; Zanobetti, Antonella; Coull, Brent; Schwartz, Joel; Gold, Diane R; Koutrakis, Petros

2015-01-01

Local trends in ozone concentration may differ by meteorological conditions. Furthermore, the trends occurring at the extremes of the Ozone distribution are often not reported even though these may be very different than the trend observed at the mean or median and they may be more relevant to health outcomes. Classify days of observation over a 16-year period into broad categories that capture salient daily local weather characteristics. Determine the rate of change in mean and median O3 concentrations within these different categories to assess how concentration trends are impacted by daily weather. Further examine if trends vary for observations in the extremes of the O3 distribution. We used k-means clustering to categorize days of observation based on the maximum daily temperature, standard deviation of daily temperature, mean daily ground level wind speed, mean daily water vapor pressure and mean daily sea-level barometric pressure. The five cluster solution was determined to be the appropriate one based on cluster diagnostics and cluster interpretability. Trends in cluster frequency and pollution trends within clusters were modeled using Poisson regression with penalized splines as well as quantile regression. There were five characteristic groupings identified. The frequency of days with large standard deviations in hourly temperature decreased over the observation period, whereas the frequency of warmer days with smaller deviations in temperature increased. O3 trends were significantly different within the different weather groupings. Furthermore, the rate of O3 change for the 95th percentile and 5th percentile was significantly different than the rate of change of the median for several of the weather categories.We found that O3 trends vary between different characteristic local weather patterns. O3 trends were significantly different between the different weather groupings suggesting an important interaction between changes in prevailing weather conditions and O3 concentration.

The Common Prescription Patterns Based on the Hierarchical Clustering of Herb-Pairs Efficacies

PubMed Central

2016-01-01

Prescription patterns are rules or regularities used to generate, recognize, or judge a prescription. Most of existing studies focused on the specific prescription patterns for diverse diseases or syndromes, while little attention was paid to the common patterns, which reflect the global view of the regularities of prescriptions. In this paper, we designed a method CPPM to find the common prescription patterns. The CPPM is based on the hierarchical clustering of herb-pair efficacies (HPEs). Firstly, HPEs were hierarchically clustered; secondly, the individual herbs are labeled by the HPEC (the clusters of HPEs); and then the prescription patterns were extracted from the combinations of HPEC; finally the common patterns are recognized statistically. The results showed that HPEs have hierarchical clustering structure. When the clustering level is 2 and the HPEs were classified into two clusters, the common prescription patterns are obvious. Among 332 candidate prescriptions, 319 prescriptions follow the common patterns. The description of the patterns is that if a prescription contains the herbs of the cluster (C 1), it is very likely to have other herbs of another cluster (C 2); while a prescription has the herbs of C 2, it may have no herbs of C 1. Finally, we discussed that the common patterns are mathematically coincident with the Blood-Qi theory. PMID:27190534

Dietary Patterns of Women Are Associated with Incident Abdominal Obesity but Not Metabolic Syndrome123

PubMed Central

Kimokoti, Ruth W.; Gona, Philimon; Zhu, Lei; Newby, P. K.; Millen, Barbara E.; Brown, Lisa S.; D’Agostino, Ralph B.; Fung, Teresa T.

2012-01-01

Data on the relationship between empirical dietary patterns and metabolic syndrome (MetS) and its components in prospective study designs are limited. In addition, demographic and lifestyle determinants of MetS may modify the association between dietary patterns and the syndrome. We prospectively examined the relationship between empirically derived patterns and MetS and MetS components among 1146 women in the Framingham Offspring/Spouse cohort. They were aged 25–77 y with BMI ≥18.5 kg/m2 and free of cardiovascular disease, diabetes, cancer, and MetS at baseline, and followed for a mean of 7 y. Five dietary patterns, Heart Healthier, Lighter Eating, Wine and Moderate Eating, Higher Fat, and Empty Calorie, were previously identified using cluster analysis from food intake collected using a FFQ. After adjusting for potential confounders, we observed lower odds for abdominal obesity for Higher Fat [OR = 0.48 (95% CI: 0.25, 0.91)] and Wine and Moderate Eating clusters [OR = 0.28 (95% CI: 0.11, 0.72)] compared with the Empty Calorie cluster. Additional adjustment for BMI somewhat attenuated these OR [Higher Fat OR = 0.52 (95% CI: 0.27, 1.00); Wine and Moderate Eating OR = 0.34 (95% CI: 0.13, 0.89)]. None of the clusters was associated with MetS or other MetS components. Baseline smoking status and age did not modify the relation between dietary patterns and MetS. The Higher Fat and Wine and Moderate Eating patterns showed an inverse association with abdominal obesity; certain foods might be targeted in these habitual patterns to achieve optimal dietary patterns for MetS prevention. PMID:22833658

Cluster signal-to-noise analysis for evaluation of the information content in an image.

PubMed

Weerawanich, Warangkana; Shimizu, Mayumi; Takeshita, Yohei; Okamura, Kazutoshi; Yoshida, Shoko; Yoshiura, Kazunori

2018-01-01

(1) To develop an observer-free method of analysing image quality related to the observer performance in the detection task and (2) to analyse observer behaviour patterns in the detection of small mass changes in cone-beam CT images. 13 observers detected holes in a Teflon phantom in cone-beam CT images. Using the same images, we developed a new method, cluster signal-to-noise analysis, to detect the holes by applying various cut-off values using ImageJ and reconstructing cluster signal-to-noise curves. We then evaluated the correlation between cluster signal-to-noise analysis and the observer performance test. We measured the background noise in each image to evaluate the relationship with false positive rates (FPRs) of the observers. Correlations between mean FPRs and intra- and interobserver variations were also evaluated. Moreover, we calculated true positive rates (TPRs) and accuracies from background noise and evaluated their correlations with TPRs from observers. Cluster signal-to-noise curves were derived in cluster signal-to-noise analysis. They yield the detection of signals (true holes) related to noise (false holes). This method correlated highly with the observer performance test (R 2 = 0.9296). In noisy images, increasing background noise resulted in higher FPRs and larger intra- and interobserver variations. TPRs and accuracies calculated from background noise had high correlation with actual TPRs from observers; R 2 was 0.9244 and 0.9338, respectively. Cluster signal-to-noise analysis can simulate the detection performance of observers and thus replace the observer performance test in the evaluation of image quality. Erroneous decision-making increased with increasing background noise.

Clustering of four major lifestyle risk factors among Korean adults with metabolic syndrome.

PubMed

Ha, Shin; Choi, Hui Ran; Lee, Yo Han

2017-01-01

The purpose of this study was to investigate the clustering pattern of four major lifestyle risk factors-smoking, heavy drinking, poor diet, and physical inactivity-among people with metabolic syndrome in South Korea. There were 2,469 adults with metabolic syndrome aged 30 years or older available with the 5th Korean National Health and Nutrition Examination Survey dataset. We calculated the ratio of the observed to expected (O/E) prevalence for the 16 different combinations and the prevalence odds ratios (POR) of four lifestyle risk factors. The four lifestyle risk factors tended to cluster in specific multiple combinations. Smoking and heavy drinking was clustered (POR: 1.86 for male, 4.46 for female), heavy drinking and poor diet were clustered (POR: 1.38 for male, 1.74 for female), and smoking and physical inactivity were also clustered (POR: 1.48 for male). Those who were male, younger, low-educated and living alone were much more likely to have a higher number of lifestyle risk factors. Some helpful implications can be drawn from the knowledge on clustering pattern of lifestyle risk factors for more effective intervention program targeting metabolic syndrome.

Conjunction of anti-parallel and component reconnection at the dayside MP: Cluster and Double Star coordinated observation on 6 April 2004

NASA Astrophysics Data System (ADS)

Wang, J.; Pu, Z. Y.; Fu, S. Y.; Wang, X. G.; Xiao, C. J.; Dunlop, M. W.; Wei, Y.; Bogdanova, Y. V.; Zong, Q. G.; Xie, L.

2011-05-01

Previous theoretical and simulation studies have suggested that the anti-parallel and component reconnection can occur simultaneously on the dayside magnetopause. Certain observations have also been reported to support global conjunct pattern of magnetic reconnection. Here, we show direct evidence for the conjunction of anti-parallel and component MR using coordinated observations of Double Star TC-1 and Cluster under the same IMF condition on 6 April, 2004. The global MR X-line configuration constructed is in good agreement with the “S-shape” model.

Spatial Temporal Sowing Pattern of Rapeseed-Mustard Crop in India Using Multi-Date IRS Awifs Data

NASA Astrophysics Data System (ADS)

Rajak, D. R.; Patel, H. A.; Chaudhari, K. N.; Patel, N. K.; Panigrahy, S.; Parihar, J. S.

2011-08-01

This paper highlights the results on spatial pattern of sowing of rapeseed/mustard in four major states in India using multidate Advanced Wide Field Sensor (AWiFS) data for 2010-11 crop season. Geo-referenced, calibrated AWiFS data acquired during October 2010 to February 2011 were used to generate the Normalised Difference Vegetation Index (NDVI) image sets. Iterative Self-Organizing Data Analysis Technique (ISODATA) based clustering of the multi date NDVI dataset for mustard crop pixels was performed. The clusters were segregated to spectral emergence classes using a spectral profile matching approach with reference to ground truth data. The sowing dates were derived from the spectral emergence data using a lag period based on field observation. Analysis showed the sowing pattern in the study states is spread over around 60 days from mid October to mid December. Three distinct clusters of sowing pattern were observed. The major one (around 40%) is sown between mid October and first week of November. Around 25% area is sown from last week of November to mid December. The other 35% area is sown in between these two periods. Analysis of temperature, a key weather variable influencing the growth of this crop, showed that the crop sowing in northern Rajasthan and Haryana is delayed by about one month to avoid the frost damage during reproductive phase. In the parts of Gujarat, southern parts of Rajasthan and Madhya Pradesh (MP), an early sowing in the second fortnight of October was observed, mainly to avoid higher mean temperatures during the month of March.

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

Infrared detection of (H 2O) 20 isomers of exceptional stability: A drop-like and a face-sharing pentagonal prism cluster

DOE PAGES

Pradzynski, Christoph C.; Dierking, Christoph W.; Zurheide, Florian; ...

2014-09-01

Water clusters containing fully coordinated water molecules are model systems that mimic the local environment of the condensed phase. Present knowledge about the water cluster size regime in which the transition from the allsurface to the fully solvated water molecules occurs is mainly based on theoretical predictions in lieu of the absence of precisely size resolved experimental measurements. Here, we report size and isomer selective infrared (IR) spectra of (H 2O) 20 clusters tagged with a sodium atom by employing IR excitation modulated photoionization spectroscopy. The observed absorption patterns in the OH stretching ”fingerprint” region are consistent with the theoreticallymore » predicted spectra of two structurally distinct isomers: A drop-like cluster with a fully coordinated (interior) water and an edge-sharing pentagonal prism cluster in which all atoms are on the surface. The observed isomers show exceptional stability and are predicted to be nearly isoenergetic.« less

Spatial patterns in vegetation fires in the Indian region.

PubMed

Vadrevu, Krishna Prasad; Badarinath, K V S; Anuradha, Eaturu

2008-12-01

In this study, we used fire count datasets derived from Along Track Scanning Radiometer (ATSR) satellite to characterize spatial patterns in fire occurrences across highly diverse geographical, vegetation and topographic gradients in the Indian region. For characterizing the spatial patterns of fire occurrences, observed fire point patterns were tested against the hypothesis of a complete spatial random (CSR) pattern using three different techniques, the quadrat analysis, nearest neighbor analysis and Ripley's K function. Hierarchical nearest neighboring technique was used to depict the 'hotspots' of fire incidents. Of the different states, highest fire counts were recorded in Madhya Pradesh (14.77%) followed by Gujarat (10.86%), Maharastra (9.92%), Mizoram (7.66%), Jharkhand (6.41%), etc. With respect to the vegetation categories, highest number of fires were recorded in agricultural regions (40.26%) followed by tropical moist deciduous vegetation (12.72), dry deciduous vegetation (11.40%), abandoned slash and burn secondary forests (9.04%), tropical montane forests (8.07%) followed by others. Analysis of fire counts based on elevation and slope range suggested that maximum number of fires occurred in low and medium elevation types and in very low to low-slope categories. Results from three different spatial techniques for spatial pattern suggested clustered pattern in fire events compared to CSR. Most importantly, results from Ripley's K statistic suggested that fire events are highly clustered at a lag-distance of 125 miles. Hierarchical nearest neighboring clustering technique identified significant clusters of fire 'hotspots' in different states in northeast and central India. The implications of these results in fire management and mitigation were discussed. Also, this study highlights the potential of spatial point pattern statistics in environmental monitoring and assessment studies with special reference to fire events in the Indian region.

Explaining ecological clusters of maternal depression in South Western Sydney

PubMed Central

2014-01-01

Background The aim of the qualitative study reported here was to: 1) explain the observed clustering of postnatal depressive symptoms in South Western Sydney; and 2) identify group-level mechanisms that would add to our understanding of the social determinants of maternal depression. Methods Critical realism provided the methodological underpinning for the study. The setting was four local government areas in South Western Sydney, Australia. Child and Family practitioners and mothers in naturally occurring mothers groups were interviewed. Results Using an open coding approach to maximise emergence of patterns and relationships we have identified seven theoretical concepts that might explain the observed spatial clustering of maternal depression. The theoretical concepts identified were: Community-level social networks; Social Capital and Social Cohesion; "Depressed community"; Access to services at the group level; Ethnic segregation and diversity; Supportive social policy; and Big business. Conclusions We postulate that these regional structural, economic, social and cultural mechanisms partially explain the pattern of maternal depression observed in families and communities within South Western Sydney. We further observe that powerful global economic and political forces are having an impact on the local situation. The challenge for policy and practice is to support mothers and their families within this adverse regional and global-economic context. PMID:24460690

Structural transition of (InSb)n clusters at n = 6-10

NASA Astrophysics Data System (ADS)

Lu, Qi Liang; Luo, Qi Quan; Huang, Shou Guo; Li, Yi De

2016-10-01

An optimization strategy combining global semi-empirical quantum mechanical search with all-electron density functional theory was adopted to determine the lowest energy structure of (InSb)n clusters with n = 6-10. A new structural growth pattern of the clusters was observed. The lowest energy structures of (InSb)6 and (InSb)8 were different from that of previously reported results. Competition existed between core-shell and cage-like structures of (InSb)8. The structural transition of (InSb)n clusters occurred at size n = 8-9. For (InSb)9 and (InSb)10 clusters, core-shell structure were more energetically favorable than the cage. The corresponding electronic properties were investigated.

Mechanism of cell alignment in groups of Myxococcus xanthus bacteria

NASA Astrophysics Data System (ADS)

Balgam, Rajesh; Igoshin, Oleg

2015-03-01

Myxococcus xanthus is a model for studying self-organization in bacteria. These flexible cylindrical bacteria move along. In groups, M. xanthus cells align themselves into dynamic cell clusters but the mechanism underlying their formation is unknown. It has been shown that steric interactions can cause alignment in self-propelled hard rods but it is not clear how flexibility and reversals affect the alignment and cluster formation. We have investigated cell alignment process using our biophysical model of M. xanthus cell in an agent-based simulation framework under realistic cell flexibility values. We observed that flexible model cells can form aligned cell clusters when reversals are suppressed but these clusters disappeared when reversals frequency becomes similar to the observed value. However, M. xanthus cells follow slime (polysaccharide gel like material) trails left by other cells and we show that implementing this into our model rescues cell clustering for reversing cells. Our results show that slime following along with periodic cell reversals act as positive feedback to reinforce existing slime trails and recruit more cells. Furthermore, we have observed that mechanical cell alignment combined with slime following is sufficient to explain the distinct clustering patterns of reversing and non-reversing cells as observed in recent experiments. This work is supported by NSF MCB 0845919 and 1411780.

Inferred vs Realized Patterns of Gene Flow: An Analysis of Population Structure in the Andros Island Rock Iguana

PubMed Central

Colosimo, Giuliano; Knapp, Charles R.; Wallace, Lisa E.; Welch, Mark E.

2014-01-01

Ecological data, the primary source of information on patterns and rates of migration, can be integrated with genetic data to more accurately describe the realized connectivity between geographically isolated demes. In this paper we implement this approach and discuss its implications for managing populations of the endangered Andros Island Rock Iguana, Cyclura cychlura cychlura. This iguana is endemic to Andros, a highly fragmented landmass of large islands and smaller cays. Field observations suggest that geographically isolated demes were panmictic due to high, inferred rates of gene flow. We expand on these observations using 16 polymorphic microsatellites to investigate the genetic structure and rates of gene flow from 188 Andros Iguanas collected across 23 island sites. Bayesian clustering of specimens assigned individuals to three distinct genotypic clusters. An analysis of molecular variance (AMOVA) indicates that allele frequency differences are responsible for a significant portion of the genetic variance across the three defined clusters (Fst =  0.117, p0.01). These clusters are associated with larger islands and satellite cays isolated by broad water channels with strong currents. These findings imply that broad water channels present greater obstacles to gene flow than was inferred from field observation alone. Additionally, rates of gene flow were indirectly estimated using BAYESASS 3.0. The proportion of individuals originating from within each identified cluster varied from 94.5 to 98.7%, providing further support for local isolation. Our assessment reveals a major disparity between inferred and realized gene flow. We discuss our results in a conservation perspective for species inhabiting highly fragmented landscapes. PMID:25229344

Associations of Streptococcus suis Serotype 2 Ribotype Profiles with Clinical Disease and Antimicrobial Resistance

PubMed Central

Rasmussen, S. R.; Aarestrup, F. M.; Jensen, N. E.; Jorsal, S. E.

1999-01-01

A total of 122 Streptococcus suis serotype 2 strains were characterized thoroughly by comparing clinical and pathological observations, ribotype profiles, and antimicrobial resistance. Twenty-one different ribotype profiles were found and compared by cluster analysis, resulting in the identification of three ribotype clusters. A total of 58% of all strains investigated were of two ribotypes belonging to different ribotype clusters. A remarkable relationship existed between the observed ribotype profiles and the clinical-pathological observations because strains of one of the two dominant ribotypes were almost exclusively isolated from pigs with meningitis, while strains of the other dominant ribotype were never associated with meningitis. This second ribotype was isolated only from pigs with pneumonia, endocarditis, pericarditis, or septicemia. Cluster analysis revealed that strains belonging to the same ribotype cluster as one of the dominant ribotypes came from pigs that showed clinical signs similar to those of pigs infected with strains with the respective dominant ribotype profiles. Furthermore, strains belonging to different ribotype clusters had totally different patterns of resistance to antibiotics because strains isolated from pigs with meningitis were resistant to sulfamethazoxazole and strains isolated from pigs with pneumonia, endocarditis, pericarditis, or septicemia were resistant to tetracycline. PMID:9889228

Atypical Mg-poor Milky Way Field Stars with Globular Cluster Second-generation-like Chemical Patterns

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

Fernández-Trincado, J. G.; Geisler, D.; Tang, B.

We report the peculiar chemical abundance patterns of 11 atypical Milky Way (MW) field red giant stars observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE). These atypical giants exhibit strong Al and N enhancements accompanied by C and Mg depletions, strikingly similar to those observed in the so-called second-generation (SG) stars of globular clusters (GCs). Remarkably, we find low Mg abundances ([Mg/Fe] < 0.0) together with strong Al and N overabundances in the majority (5/7) of the metal-rich ([Fe/H] ≳ −1.0) sample stars, which is at odds with actual observations of SG stars in Galactic GCs of similarmore » metallicities. This chemical pattern is unique and unprecedented among MW stars, posing urgent questions about its origin. These atypical stars could be former SG stars of dissolved GCs formed with intrinsically lower abundances of Mg and enriched Al (subsequently self-polluted by massive AGB stars) or the result of exotic binary systems. We speculate that the stars Mg-deficiency as well as the orbital properties suggest that they could have an extragalactic origin. This discovery should guide future dedicated spectroscopic searches of atypical stellar chemical patterns in our Galaxy, a fundamental step forward to understanding the Galactic formation and evolution.« less

Atypical Mg-poor Milky Way Field Stars with Globular Cluster Second-generation-like Chemical Patterns

NASA Astrophysics Data System (ADS)

Fernández-Trincado, J. G.; Zamora, O.; García-Hernández, D. A.; Souto, Diogo; Dell'Agli, F.; Schiavon, R. P.; Geisler, D.; Tang, B.; Villanova, S.; Hasselquist, Sten; Mennickent, R. E.; Cunha, Katia; Shetrone, M.; Allende Prieto, Carlos; Vieira, K.; Zasowski, G.; Sobeck, J.; Hayes, C. R.; Majewski, S. R.; Placco, V. M.; Beers, T. C.; Schleicher, D. R. G.; Robin, A. C.; Mészáros, Sz.; Masseron, T.; García Pérez, Ana E.; Anders, F.; Meza, A.; Alves-Brito, A.; Carrera, R.; Minniti, D.; Lane, R. R.; Fernández-Alvar, E.; Moreno, E.; Pichardo, B.; Pérez-Villegas, A.; Schultheis, M.; Roman-Lopes, A.; Fuentes, C. E.; Nitschelm, C.; Harding, P.; Bizyaev, D.; Pan, K.; Oravetz, D.; Simmons, A.; Ivans, Inese I.; Blanco-Cuaresma, S.; Hernández, J.; Alonso-García, J.; Valenzuela, O.; Chanamé, J.

2017-09-01

We report the peculiar chemical abundance patterns of 11 atypical Milky Way (MW) field red giant stars observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE). These atypical giants exhibit strong Al and N enhancements accompanied by C and Mg depletions, strikingly similar to those observed in the so-called second-generation (SG) stars of globular clusters (GCs). Remarkably, we find low Mg abundances ([Mg/Fe] < 0.0) together with strong Al and N overabundances in the majority (5/7) of the metal-rich ([Fe/H] ≳ -1.0) sample stars, which is at odds with actual observations of SG stars in Galactic GCs of similar metallicities. This chemical pattern is unique and unprecedented among MW stars, posing urgent questions about its origin. These atypical stars could be former SG stars of dissolved GCs formed with intrinsically lower abundances of Mg and enriched Al (subsequently self-polluted by massive AGB stars) or the result of exotic binary systems. We speculate that the stars Mg-deficiency as well as the orbital properties suggest that they could have an extragalactic origin. This discovery should guide future dedicated spectroscopic searches of atypical stellar chemical patterns in our Galaxy, a fundamental step forward to understanding the Galactic formation and evolution.

Evaluating controls on fluvial sand-body clustering in the Ferris Formation (Cretaceous/Paleogene, Wyoming, USA)

NASA Astrophysics Data System (ADS)

Hajek, E. A.; Heller, P.

2009-12-01

A primary goal of sedimentary geologists is to interpret past tectonic, climatic, and eustatic conditions from the stratigraphic record. Stratigraphic changes in alluvial-basin fills are routinely interpreted as the result of past tectonic movements or changes in climate or sea level. Recent physical and numerical models have shown that sedimentary systems can exhibit self-organization on basin-filling time scales, suggesting that structured stratigraphic patterns can form spontaneously rather than as the result of changing boundary conditions. The Ferris Formation (Upper Cretaceous/Paleogene, Hanna Basin, Wyoming) exhibits stratigraphic organization where clusters of closely-spaced channel deposits are separated from other clusters by intervals dominated by overbank material. In order to evaluate the role of basinal controls on deposition and ascertain the potential for self-organization in this ancient deposit, the spatial patterns of key channel properties (including sand-body dimensions, paleoflow depth, maximum clast size, paleocurrent direction, and sediment provenance) are analyzed. Overall the study area lacks strong trends sand-body properties through the stratigraphic succession and in cluster groups. Consequently there is no indication that the stratigraphic pattern observed in the Ferris Formation was driven by systematic changes in climate or tectonics.

Which modifiable health risk behaviours are related? A systematic review of the clustering of Smoking, Nutrition, Alcohol and Physical activity ('SNAP') health risk factors.

PubMed

Noble, Natasha; Paul, Christine; Turon, Heidi; Oldmeadow, Christopher

2015-12-01

There is a growing body of literature examining the clustering of health risk behaviours, but little consensus about which risk factors can be expected to cluster for which sub groups of people. This systematic review aimed to examine the international literature on the clustering of smoking, poor nutrition, excess alcohol and physical inactivity (SNAP) health behaviours among adults, including associated socio-demographic variables. A literature search was conducted in May 2014. Studies examining at least two SNAP risk factors, and using a cluster or factor analysis technique, or comparing observed to expected prevalence of risk factor combinations, were included. Fifty-six relevant studies were identified. A majority of studies (81%) reported a 'healthy' cluster characterised by the absence of any SNAP risk factors. More than half of the studies reported a clustering of alcohol with smoking, and half reported clustering of all four SNAP risk factors. The methodological quality of included studies was generally weak to moderate. Males and those with greater social disadvantage showed riskier patterns of behaviours; younger age was less clearly associated with riskier behaviours. Clustering patterns reported here reinforce the need for health promotion interventions to target multiple behaviours, and for such efforts to be specifically designed and accessible for males and those who are socially disadvantaged. Copyright © 2015 Elsevier Inc. All rights reserved.

Clustering of risk factors for cardiometabolic diseases in low-income, female adolescents.

PubMed

Melo, Elza M F S de; Azevedo, George D; Silva, João B da; Lemos, Telma M A M; Maranhão, Técia M O; Freitas, Ana K M S O; Spyrides, Maria H; Costa, Eduardo C

2016-02-16

To assess the prevalence and clustering patterns of cardiometabolic risk factors among low-income, female adolescents. Cross-sectional study involving 196 students of public schools (11-19 years old). The following risk factors were considered in the analysis: excess weight, central obesity, dyslipidemia, high blood pressure, and high fasting glucose. The ratio between observed and expected prevalence and its confidence interval were used to identify clustering of risk factors that exceeded expected prevalence in the population. The most prevalent risk factors were dyslipidemia (70.9%), and central obesity (39.8%), followed by excess weight (29.6%), and high blood pressure (12.8%). A total of 42.9% of adolescents had two or more risk factors, and 24% had three or more. Excess weight, central obesity, and dyslipidemia were common risk factors in the clustering patterns that showed higher-than-expected prevalence. Clustering of risk factors (≥ two factors) among the adolescents showed considerable prevalence, and there was a non-casual coexistence of excess weight, central obesity, and dyslipidemia (mainly low HDL-cholesterol).

Patterning of functional human astrocytes onto parylene-C/SiO2 substrates for the study of Ca2+ dynamics in astrocytic networks

NASA Astrophysics Data System (ADS)

Raos, B. J.; Simpson, M. C.; Doyle, C. S.; Murray, A. F.; Graham, E. S.; Unsworth, C. P.

2018-06-01

Objective. Recent literature suggests that astrocytes form organized functional networks and communicate through transient changes in cytosolic Ca2+. Traditional techniques to investigate network activity, such as pharmacological blocking or genetic knockout, are difficult to restrict to individual cells. The objective of this work is to develop cell-patterning techniques to physically manipulate astrocytic interactions to enable the study of Ca2+ in astrocytic networks. Approach. We investigate how an in vitro cell-patterning platform that utilizes geometric patterns of parylene-C on SiO2 can be used to physically isolate single astrocytes and small astrocytic networks. Main results. We report that single astrocytes are effectively isolated on 75  ×  75 µm square parylene nodes, whereas multi-cellular astrocytic networks are isolated on larger nodes, with the mean number of astrocytes per cluster increasing as a function of node size. Additionally, we report that astrocytes in small multi-cellular clusters exhibit spatio-temporal clustering of Ca2+ transients. Finally, we report that the frequency and regularity of Ca2+ transients was positively correlated with astrocyte connectivity. Significance. The significance of this work is to demonstrate how patterning hNT astrocytes replicates spatio-temporal clustering of Ca2+ signalling that is observed in vivo but not in dissociated in vitro cultures. We therefore highlight the importance of the structure of astrocytic networks in determining ensemble Ca2+ behaviour.

Space-time analysis of pneumonia hospitalisations in the Netherlands.

PubMed

Benincà, Elisa; van Boven, Michiel; Hagenaars, Thomas; van der Hoek, Wim

2017-01-01

Community acquired pneumonia is a major global public health problem. In the Netherlands there are 40,000-50,000 hospital admissions for pneumonia per year. In the large majority of these hospital admissions the etiologic agent is not determined and a real-time surveillance system is lacking. Localised and temporal increases in hospital admissions for pneumonia are therefore only detected retrospectively and the etiologic agents remain unknown. Here, we perform spatio-temporal analyses of pneumonia hospital admission data in the Netherlands. To this end, we scanned for spatial clusters on yearly and seasonal basis, and applied wavelet cluster analysis on the time series of five main regions. The pneumonia hospital admissions show strong clustering in space and time superimposed on a regular yearly cycle with high incidence in winter and low incidence in summer. Cluster analysis reveals a heterogeneous pattern, with most significant clusters occurring in the western, highly urbanised, and in the eastern, intensively farmed, part of the Netherlands. Quantitatively, the relative risk (RR) of the significant clusters for the age-standardised incidence varies from a minimum of 1.2 to a maximum of 2.2. We discuss possible underlying causes for the patterns observed, such as variations in air pollution.

Global Clusters as Laboratories for Stellar Evolution

NASA Technical Reports Server (NTRS)

Catelan, Marcio; Valcarce, Aldo A. R.; Sweigart, Allen V.

2010-01-01

Globular clusters have long been considered the closest approximation to a physicist's laboratory in astrophysics, and as such a near-ideal laboratory for (low-mass) stellar evolution, However, recent observations have cast a shadow on this long-standing paradigm, suggesting the presence of multiple populations with widely different abundance patterns, and - crucially - with widely different helium abundances as welL In this review we discuss which features of the Hertzsprung-Russell diagram may be used as helium abundance indicators, and present an overview of available constraints on the helium abundance in globular clusters,

Modest validity and fair reproducibility of dietary patterns derived by cluster analysis.

PubMed

Funtikova, Anna N; Benítez-Arciniega, Alejandra A; Fitó, Montserrat; Schröder, Helmut

2015-03-01

Cluster analysis is widely used to analyze dietary patterns. We aimed to analyze the validity and reproducibility of the dietary patterns defined by cluster analysis derived from a food frequency questionnaire (FFQ). We hypothesized that the dietary patterns derived by cluster analysis have fair to modest reproducibility and validity. Dietary data were collected from 107 individuals from population-based survey, by an FFQ at baseline (FFQ1) and after 1 year (FFQ2), and by twelve 24-hour dietary recalls (24-HDR). Repeatability and validity were measured by comparing clusters obtained by the FFQ1 and FFQ2 and by the FFQ2 and 24-HDR (reference method), respectively. Cluster analysis identified a "fruits & vegetables" and a "meat" pattern in each dietary data source. Cluster membership was concordant for 66.7% of participants in FFQ1 and FFQ2 (reproducibility), and for 67.0% in FFQ2 and 24-HDR (validity). Spearman correlation analysis showed reasonable reproducibility, especially in the "fruits & vegetables" pattern, and lower validity also especially in the "fruits & vegetables" pattern. κ statistic revealed a fair validity and reproducibility of clusters. Our findings indicate a reasonable reproducibility and fair to modest validity of dietary patterns derived by cluster analysis. Copyright © 2015 Elsevier Inc. All rights reserved.

From antinode clusters to node clusters: the concentration-dependent transition of floaters on a standing Faraday wave.

PubMed

Sanlı, Ceyda; Lohse, Detlef; van der Meer, Devaraj

2014-05-01

A hydrophilic floating sphere that is denser than water drifts to an amplitude maximum (antinode) of a surface standing wave. A few identical floaters therefore organize into antinode clusters. However, beyond a transitional value of the floater concentration ϕ, we observe that the same spheres spontaneously accumulate at the nodal lines, completely inverting the self-organized particle pattern on the wave. From a potential energy estimate we show (i) that at low ϕ antinode clusters are energetically favorable over nodal ones and (ii) how this situation reverses at high ϕ, in agreement with the experiment.

Chromatin organization and global regulation of Hox gene clusters

PubMed Central

Montavon, Thomas; Duboule, Denis

2013-01-01

During development, a properly coordinated expression of Hox genes, within their different genomic clusters is critical for patterning the body plans of many animals with a bilateral symmetry. The fascinating correspondence between the topological organization of Hox clusters and their transcriptional activation in space and time has served as a paradigm for understanding the relationships between genome structure and function. Here, we review some recent observations, which revealed highly dynamic changes in the structure of chromatin at Hox clusters, in parallel with their activation during embryonic development. We discuss the relevance of these findings for our understanding of large-scale gene regulation. PMID:23650639

Clinical Phenotype of Diabetic Peripheral Neuropathy and Relation to Symptom Patterns: Cluster and Factor Analysis in Patients with Type 2 Diabetes in Korea.

PubMed

Won, Jong Chul; Im, Yong-Jin; Lee, Ji-Hyun; Kim, Chong Hwa; Kwon, Hyuk Sang; Cha, Bong-Yun; Park, Tae Sun

2017-01-01

Patients with diabetic peripheral neuropathy (DPN) is the most common complication. However, patients are usually suffering from not only diverse sensory deficit but also neuropathy-related discomforts. The aim of this study is to identify distinct groups of patients with DPN with respect to its clinical impacts on symptom patterns and comorbidities. A hierarchical cluster analysis and factor analysis were performed to identify relevant subgroups of patients with DPN ( n = 1338) and symptom patterns. Patients with DPN were divided into three clusters: asymptomatic (cluster 1, n = 448, 33.5%), moderate symptoms with disturbed sleep (cluster 2, n = 562, 42.0%), and severe symptoms with decreased quality of life (cluster 3, n = 328, 24.5%). Patients in cluster 3, compared with clusters 1 and 2, were characterized by higher levels of HbA1c and more severe pain and physical impairments. Patients in cluster 2 had moderate pain levels but disturbed sleep patterns comparable to those in cluster 3. The frequency of symptoms on each item of MNSI by "painful" symptom pattern showed a similar distribution pattern with increasing intensities along the three clusters. Cluster and factor analysis endorsed the use of comprehensive and symptomatic subgrouping to individualize the evaluation of patients with DPN.

A TRAJECTORY-CLUSTERING CORRELATION METHODOLOGY FOR EXAMINING THE LONG-RANGE TRANSPORT OF AIR POLLUTANTS. (R825260)

EPA Science Inventory

We present a robust methodology for examining the relationship between synoptic-scale atmospheric transport patterns and pollutant concentration levels observed at a site. Our approach entails calculating a large number of back-trajectories from the observational site over a long...

Quantifying opening-mode fracture spatial organization in horizontal wellbore image logs, core and outcrop: Application to Upper Cretaceous Frontier Formation tight gas sandstones, USA

NASA Astrophysics Data System (ADS)

Li, J. Z.; Laubach, S. E.; Gale, J. F. W.; Marrett, R. A.

2018-03-01

The Upper Cretaceous Frontier Formation is a naturally fractured gas-producing sandstone in Wyoming. Regionally, random and statistically more clustered than random patterns exist in the same upper to lower shoreface depositional facies. East-west- and north-south-striking regional fractures sampled using image logs and cores from three horizontal wells exhibit clustered patterns, whereas data collected from east-west-striking fractures in outcrop have patterns that are indistinguishable from random. Image log data analyzed with the correlation count method shows clusters ∼35 m wide and spaced ∼50 to 90 m apart as well as clusters up to 12 m wide with periodic inter-cluster spacings. A hierarchy of cluster sizes exists; organization within clusters is likely fractal. These rocks have markedly different structural and burial histories, so regional differences in degree of clustering are unsurprising. Clustered patterns correspond to fractures having core quartz deposition contemporaneous with fracture opening, circumstances that some models suggest might affect spacing patterns by interfering with fracture growth. Our results show that quantifying and identifying patterns as statistically more or less clustered than random delineates differences in fracture patterns that are not otherwise apparent but that may influence gas and water production, and therefore may be economically important.

Organic-inorganic hybrid resists for EUVL

NASA Astrophysics Data System (ADS)

Singh, Vikram; Kalyani, Vishwanath; Satyanarayana, V. S. V.; Pradeep, Chullikkattil P.; Ghosh, Subrata; Sharma, Satinder; Gonsalves, Kenneth E.

2014-03-01

Herein, we describe preliminary results on organic-inorganic hybrid photoresists, capable of showing line patterns up to 16 nm under e-beam exposure studies, prepared by incorporating polyoxometalates (POMs) clusters into organic photoresist materials. Various Mo and W based clusters such as (TBA)2[Mo6O19], (TBA)5(H)[P2V3W15O62] and (TBA)4[P2Mo18O61] (where TBA = tetrabutyl ammonium counter ion) have been incorporated into PMMA matrix by mixing POM solutions and standard PMMA polymer in anisole (MW ~ 95000, MicroChem) in 1:33 w/v ratio. E-beam exposure followed by development with MIBK solutions showed that these new organic-inorganic hybrid photoresists show good line patterns upto 16 nm, which were not observed in the case of control experiments done on pure PMMA polymer resist. The observed enhancement of resist properties in the case of hybrid resists could possibly be due to a combination of features imparted to the resist by the POM clusters such as increased sensitivity, etch resistance and thermal stability.

Different Patterns of the Urban Heat Island Intensity from Cluster Analysis

NASA Astrophysics Data System (ADS)

Silva, F. B.; Longo, K.

2014-12-01

This study analyzes the different variability patterns of the Urban Heat Island intensity (UHII) in the Metropolitan Area of Rio de Janeiro (MARJ), one of the largest urban agglomerations in Brazil. The UHII is defined as the difference in the surface air temperature between the urban/suburban and rural/vegetated areas. To choose one or more stations that represent those areas we used the technique of cluster analysis on the air temperature observations from 14 surface weather stations in the MARJ. The cluster analysis aims to classify objects based on their characteristics, gathering similar groups. The results show homogeneity patterns between air temperature observations, with 6 homogeneous groups being defined. Among those groups, one might be a natural choice for the representative urban area (Central station); one corresponds to suburban area (Afonsos station); and another group referred as rural area is compound of three stations (Ecologia, Santa Cruz and Xerém) that are located in vegetated regions. The arithmetic mean of temperature from the three rural stations is taken to represent the rural station temperature. The UHII is determined from these homogeneous groups. The first UHII is estimated from urban and rural temperature areas (Case 1), whilst the second UHII is obtained from suburban and rural temperature areas (Case 2). In Case 1, the maximum UHII occurs in two periods, one in the early morning and the other at night, while the minimum UHII occurs in the afternoon. In Case 2, the maximum UHII is observed during afternoon/night and the minimum during dawn/early morning. This study demonstrates that the stations choice reflects different UHII patterns, evidencing that distinct behaviors of this phenomenon can be identified.

Cluster observations of two separated cusp populations: double cusp or motion of the cusp?

NASA Astrophysics Data System (ADS)

Escoubet, C.-Philippe; Berchem, Jean; Trattner, Karlheinz; Pitout, Frederic; Richard, Robert; Taylor, Matt; Soucek, Jan; Grison, Benjamin; Laakso, Harri; Masson, Arnaud; Dunlop, Malcolm; Dandouras, Iannis; Reme, Henri; Fazakerley, Andrew; Daly, Patrick

2013-04-01

Modelling plasma entry in the polar cusp has been successful in reproducing ion dispersions observed in the cusp at low and mid-altitudes. The use of a realistic convection pattern allowed Wing et al. (2001) to predict double cusp signatures that were subsequently observed by the DMSP spacecraft. In this paper, we present a cusp crossing where two cusp populations are observed, separated by a gap around 1° ILAT wide. Cluster 1 (C1) and Cluster 2 (C2) observed these two cusp populations with a time delay of three minutes and about 15 and 42 minutes later, Cluster 4 (C4) and Cluster 3 (C3) observed, respectively, a single cusp population. A peculiarity of this event is the fact that the second cusp population seen on C1 and C2 was observed at the same time as the first cusp population on C4. This would tend to suggest that the two cusp populations were spatial features similar to the double cusp. Due to the nested crossing of C1 and C2 through the gap between the two cusp encounters, C2 being first to leave the cusp and last to re-enter it, these observations cannot be explained by two stable cusps with a gap of precipitation in between. On the other hand these observations are in agreement with a motion of the cusp first dawnward and then back duskward due to the effect of the IMF-By component.

Dynamical pattern formation in a low-concentration magnetorheological fluid under two orthogonal sinusoidal fields

NASA Astrophysics Data System (ADS)

Yépez, L. D.; Carrillo, J. L.; Donado, F.; Sausedo-Solorio, J. M.; Miranda-Romagnoli, P.

2016-06-01

The dynamical pattern formation of clusters of magnetic particles in a low-concentration magnetorheological fluid, under the influence of a superposition of two perpendicular sinusoidal fields, is studied experimentally. By varying the frequency and phase shift of the perpendicular fields, this configuration enables us to experimentally analyze a wide range of field configurations, including the case of a pure rotating field and the case of an oscillating unidirectional field. The fields are applied parallel to the horizontal plane where the fluid lies or in the vertical plane. For fields applied in the horizontal plane, we observed that, when the ratio of the frequencies increases, the average cluster size exhibits a kind of periodic resonances. When the phase shift between the fields is varied, the average chain length reaches maximal values for the cases of the rotating field and the unidirectional case. We analyze and discuss these results in terms of a weighted average of the time-dependent Mason number. In the case of a rotating field on the vertical plane, we also observe that the competition between the magnetic and the viscous forces determines the average cluster size. We show that this configuration generates a series of physically meaningful self-organization of clusters and transport phenomena.

Spatio-temporal cluster detection of chickenpox in Valencia, Spain in the period 2008-2012.

PubMed

Iftimi, Adina; Martínez-Ruiz, Francisco; Míguez Santiyán, Ana; Montes, Francisco

2015-05-18

Chickenpox is a highly contagious airborne disease caused by Varicella zoster, which affects nearly all non-immune children worldwide with an annual incidence estimated at 80-90 million cases. To analyze the spatiotemporal pattern of the chickenpox incidence in the city of Valencia, Spain two complementary statistical approaches were used. First, we evaluated the existence of clusters and spatio-temporal interaction; secondly, we used this information to find the locations of the spatio-temporal clusters via the space-time permutation model. The first method used detects any aggregation in our data but does not provide the spatial and temporal information. The second method gives the locations, areas and time-frame for the spatio-temporal clusters. An overall decreasing time trend, a pronounced 12-monthly periodicity and two complementary periods were observed. Several areas with high incidence, surrounding the center of the city were identified. The existence of aggregation in time and space was observed, and a number of spatio-temporal clusters were located.

The respective roles of polar/nonpolar binary patterns and amino acid composition in protein regular secondary structures explored exhaustively using hydrophobic cluster analysis.

PubMed

Rebehmed, Joseph; Quintus, Flavien; Mornon, Jean-Paul; Callebaut, Isabelle

2016-05-01

Several studies have highlighted the leading role of the sequence periodicity of polar and nonpolar amino acids (binary patterns) in the formation of regular secondary structures (RSS). However, these were based on the analysis of only a few simple cases, with no direct mean to correlate binary patterns with the limits of RSS. Here, HCA-derived hydrophobic clusters (HC) which are conditioned binary patterns whose positions fit well those of RSS, were considered. All the HC types, defined by unique binary patterns, which were commonly observed in three-dimensional (3D) structures of globular domains, were analyzed. The 180 HC types with preferences for either α-helices or β-strands distinctly contain basic binary units typical of these RSS. Therefore a general trend supporting the "binary pattern preference" assumption was observed. HC for which observed RSS are in disagreement with their expected behavior (discordant HC) were also examined. They were separated in HC types with moderate preferences for RSS, having "weak" binary patterns and versatile RSS and HC types with high preferences for RSS, having "strong" binary patterns and then displaying nonpolar amino acids at the protein surface. It was shown that in both cases, discordant HC could be distinguished from concordant ones by well-differentiated amino acid compositions. The obtained results could, thus, help to complement the currently available methods for the accurate prediction of secondary structures in proteins from the only information of a single amino acid sequence. This can be especially useful for characterizing orphan sequences and for assisting protein engineering and design. © 2016 Wiley Periodicals, Inc.

Spatial correlations, clustering and percolation-like transitions in homicide crimes

NASA Astrophysics Data System (ADS)

Alves, L. G. A.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2015-07-01

The spatial dynamics of criminal activities has been recently studied through statistical physics methods; however, models and results have been focusing on local scales (city level) and much less is known about these patterns at larger scales, e.g. at a country level. Here we report on a characterization of the spatial dynamics of the homicide crimes along the Brazilian territory using data from all cities (˜5000) in a period of more than thirty years. Our results show that the spatial correlation function in the per capita homicides decays exponentially with the distance between cities and that the characteristic correlation length displays an acute increasing trend in the latest years. We also investigate the formation of spatial clusters of cities via a percolation-like analysis, where clustering of cities and a phase-transition-like behavior describing the size of the largest cluster as a function of a homicide threshold are observed. This transition-like behavior presents evolutive features characterized by an increasing in the homicide threshold (where the transitions occur) and by a decreasing in the transition magnitudes (length of the jumps in the cluster size). We believe that our work sheds new light on the spatial patterns of criminal activities at large scales, which may contribute for better political decisions and resources allocation as well as opens new possibilities for modeling criminal activities by setting up fundamental empirical patterns at large scales.

Relatedness and nesting dispersion within breeding populations of greater white-fronted geese

USGS Publications Warehouse

Fowler, A.C.; Eadie, J.M.; Ely, Craig R.

2004-01-01

We studied patterns of relatedness and nesting dispersion in female Pacific Greater White-fronted Geese (Anser albifrons frontalis) in Alaska. Female Greater White-fronted Geese are thought to be strongly philopatric and are often observed nesting in close association with other females. Analysis of the distribution of nests on the Yukon-Kuskokwim Delta in 1998 indicated that nests were significantly clumped. We tested the hypothesis that females in the same nest cluster would be closely related using estimates of genetic relatedness based on six microsatellite DNA loci. There was no difference in the mean relatedness of females in the same cluster compared to females found in different clusters. However, relatedness among females was negatively correlated with distance between their nests, and geese nesting within 50 m of one another tended to be more closely related than those nesting farther apart. Randomization tests revealed that pairs of related individuals (R > 0.45) were more likely to occur in the same cluster when analyzed at the scale of the entire study site. However, the pattern did not hold when restricted to pairs found within 500 m of each other. Our results indicate that nest clusters are not composed primarily of closely related females, but Greater White-fronted Geese appear to be sufficiently philopatric to promote nonrandom patterns of relatedness at a local scale.

Clustering change patterns using Fourier transformation with time-course gene expression data.

PubMed

Kim, Jaehee

2011-01-01

To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a period of time because biologically related gene groups can share the same change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. This work is aimed at discovering gene groups with similar change patterns which share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. We applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns.

Modeling and clustering water demand patterns from real-world smart meter data

NASA Astrophysics Data System (ADS)

Cheifetz, Nicolas; Noumir, Zineb; Samé, Allou; Sandraz, Anne-Claire; Féliers, Cédric; Heim, Véronique

2017-08-01

Nowadays, drinking water utilities need an acute comprehension of the water demand on their distribution network, in order to efficiently operate the optimization of resources, manage billing and propose new customer services. With the emergence of smart grids, based on automated meter reading (AMR), a better understanding of the consumption modes is now accessible for smart cities with more granularities. In this context, this paper evaluates a novel methodology for identifying relevant usage profiles from the water consumption data produced by smart meters. The methodology is fully data-driven using the consumption time series which are seen as functions or curves observed with an hourly time step. First, a Fourier-based additive time series decomposition model is introduced to extract seasonal patterns from time series. These patterns are intended to represent the customer habits in terms of water consumption. Two functional clustering approaches are then used to classify the extracted seasonal patterns: the functional version of K-means, and the Fourier REgression Mixture (FReMix) model. The K-means approach produces a hard segmentation and K representative prototypes. On the other hand, the FReMix is a generative model and also produces K profiles as well as a soft segmentation based on the posterior probabilities. The proposed approach is applied to a smart grid deployed on the largest water distribution network (WDN) in France. The two clustering strategies are evaluated and compared. Finally, a realistic interpretation of the consumption habits is given for each cluster. The extensive experiments and the qualitative interpretation of the resulting clusters allow one to highlight the effectiveness of the proposed methodology.

Relating anomaly correlation to lead time: Clustering analysis of CFSv2 forecasts of summer precipitation in China

NASA Astrophysics Data System (ADS)

Zhao, Tongtiegang; Liu, Pan; Zhang, Yongyong; Ruan, Chengqing

2017-09-01

Global climate model (GCM) forecasts are an integral part of long-range hydroclimatic forecasting. We propose to use clustering to explore anomaly correlation, which indicates the performance of raw GCM forecasts, in the three-dimensional space of latitude, longitude, and initialization time. Focusing on a certain period of the year, correlations for forecasts initialized at different preceding periods form a vector. The vectors of anomaly correlation across different GCM grid cells are clustered to reveal how GCM forecasts perform as time progresses. Through the case study of Climate Forecast System Version 2 (CFSv2) forecasts of summer precipitation in China, we observe that the correlation at a certain cell oscillates with lead time and can become negative. The use of clustering reveals two meaningful patterns that characterize the relationship between anomaly correlation and lead time. For some grid cells in Central and Southwest China, CFSv2 forecasts exhibit positive correlations with observations and they tend to improve as time progresses. This result suggests that CFSv2 forecasts tend to capture the summer precipitation induced by the East Asian monsoon and the South Asian monsoon. It also indicates that CFSv2 forecasts can potentially be applied to improving hydrological forecasts in these regions. For some other cells, the correlations are generally close to zero at different lead times. This outcome implies that CFSv2 forecasts still have plenty of room for further improvement. The robustness of the patterns has been tested using both hierarchical clustering and k-means clustering and examined with the Silhouette score.

Clustering of Health Behaviors and Cardiorespiratory Fitness Among U.S. Adolescents.

PubMed

Hartz, Jacob; Yingling, Leah; Ayers, Colby; Adu-Brimpong, Joel; Rivers, Joshua; Ahuja, Chaarushi; Powell-Wiley, Tiffany M

2018-05-01

Decreased cardiorespiratory fitness (CRF) is associated with an increased risk of cardiovascular disease. However, little is known how the interaction of diet, physical activity (PA), and sedentary time (ST) affects CRF among adolescents. By using a nationally representative sample of U.S. adolescents, we used cluster analysis to investigate the interactions of these behaviors with CRF. We hypothesized that distinct clustering patterns exist and that less healthy clusters are associated with lower CRF. We used 2003-2004 National Health and Nutrition Examination Survey data for persons aged 12-19 years (N = 1,225). PA and ST were measured objectively by an accelerometer, and the American Heart Association Healthy Diet Score quantified diet quality. Maximal oxygen consumption (V˙O 2 ​max) was measured by submaximal treadmill exercise test. We performed cluster analysis to identify sex-specific clustering of diet, PA, and ST. Adjusting for accelerometer wear time, age, body mass index, race/ethnicity, and the poverty-to-income ratio, we performed sex-stratified linear regression analysis to evaluate the association of cluster with V˙O 2 ​max. Three clusters were identified for girls and boys. For girls, there was no difference across clusters for age (p = .1), weight (p = .3), and BMI (p = .5), and no relationship between clusters and V˙O 2 ​max. For boys, the youngest cluster (p < .01) had three healthy behaviors, weighed less, and was associated with a higher V˙O 2 ​max compared with the two older clusters. We observed clustering of diet, PA, and ST in U.S. adolescents. Specific patterns were associated with lower V˙O 2 ​max for boys, suggesting that our clusters may help identify adolescent boys most in need of interventions. Published by Elsevier Inc.

Cooperation in Harsh Environments and the Emergence of Spatial Patterns.

PubMed

Smaldino, Paul E

2013-11-01

This paper concerns the confluence of two important areas of research in mathematical biology: spatial pattern formation and cooperative dilemmas. Mechanisms through which social organisms form spatial patterns are not fully understood. Prior work connecting cooperation and pattern formation has often included unrealistic assumptions that shed doubt on the applicability of those models toward understanding real biological patterns. I investigated a more biologically realistic model of cooperation among social actors. The environment is harsh, so that interactions with cooperators are strictly needed to survive. Harshness is implemented via a constant energy deduction. I show that this model can generate spatial patterns similar to those seen in many naturally-occuring systems. Moreover, for each payoff matrix there is an associated critical value of the energy deduction that separates two distinct dynamical processes. In low-harshness environments, the growth of cooperator clusters is impeded by defectors, but these clusters gradually expand to form dense dendritic patterns. In very harsh environments, cooperators expand rapidly but defectors can subsequently make inroads to form reticulated patterns. The resulting web-like patterns are reminiscent of transportation networks observed in slime mold colonies and other biological systems.

Effects of daily management changes on behavioral patterns of a solitary female African elephant (Loxodonta africana) in a zoo.

PubMed

Koyama, Nao; Ueno, Yoshikazu; Eguchi, Yusuke; Uetake, Katsuji; Tanaka, Toshio

2012-07-01

This study investigated the effects of changes in daily management on behavior of a solitary female elephant in a zoo. The activity budget and space utilization of the subject and the management changes were recorded for 1 year after the conspecific male died. The observation days could be categorized into five clusters (C1-C5) by the characteristic behavioral pattern of each day. C1 had the highest percentage of resting of all clusters, and was observed after the loss of the conspecific and the beginning of use of the indoor exhibition room at night. C2, which had the highest percentage of stereotypy of any cluster, was observed after the beginning of habituation to the indoor exhibition room. Also, when the time schedule of management was changed irregularly, the subject frequently exhibited stereotypic pacing (C2, C4). The subject tended to rest when exhibiting lameness in the left hind limb (C3). In C5, activity reached a high level when she could utilize a familiar place under a stable management schedule. These results indicate that management changes affected the mental stability of an elephant in the early stage of social isolation. © 2012 The Authors. Animal Science Journal © 2012 Japanese Society of Animal Science.

Variation of gunshot injury patterns in mortality associated with human rights abuses and armed conflict: an exploratory study.

PubMed

Baraybar, Jose Pablo

2015-09-01

The analysis of the distribution of gunshot injuries in a sample of 777 sets of human remains of proven human rights abuse from Somaliland, the Balkans and Peru is compared to frequencies of injuries sustained by combatants in contemporary conflicts reported in the literature. Principal Component Analysis (PCA) reduced the data to three components accounting for 82.94% of the variance. The first component with 38.31% of variance shows segments Arms and thorax/abdomen to be positively correlated (0.887 and 0.662, respectively); the segment head/neck is strongly correlated (0.951) to the second component while the segment thorax/abdomen shows a low, negative correlation (-0.388). Finally in the third component only the legs are strongly correlated (0.991). Data was further subjected to a K-means cluster analysis to determine the likely groupings combining the four types of injuries. Each of the three clusters reproduced similar patterns observed in the PCA: Cluster 1 shows the prevalence of injuries to the thorax/abdomen and extremities in addition to injuries to the head/neck; Cluster 2 shows injuries to the head/neck and Cluster 3 injuries to the thorax/abdomen and a lower representation of the arms and legs. Most of the cases (70.5%), irrespective of geography and type of site (attack or detention), were grouped into Cluster 2. Such comparison shows that in human rights abuse, irrespective of their geography, gunshot injuries tend to follow a pattern favouring the head/neck and thorax/abdomen areas over the extremities, the reverse pattern observed in contemporary combat operations. In those settings gunshot wound trauma is the second cause of mortality/morbidity (after fragmenting ammunition) and its distribution concentrates on the extremities, thorax/abdomen and head; following the pattern of protective armour when it is used. Considering that human rights abuses are often presented as encounters between two armed groups in the context of counter-insurgency operations, a careful analysis of gunshot injury patterns could serve as an indicator that in fact murder, rather than combat, took place and the intention was to kill rather than to maim or render people unfit for battle. To compare the variation of gunshot injury patterns between mortality associated with human rights abuses and armed conflict in selected samples from different countries. Literature review and case analysis. Original statistical analysis of gunshot injuries on human remains (n=777) recovered from mass or clandestine graves associated with human rights abuses in countries in Somaliland, the Balkans and Peru (1983-1995) and literature review of mortality caused by armed conflicts. Mechanism of gunshot injury and wound distribution pattern in geographically diverse samples of human rights abuse. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

A visual analytics approach for pattern-recognition in patient-generated data.

PubMed

Feller, Daniel J; Burgermaster, Marissa; Levine, Matthew E; Smaldone, Arlene; Davidson, Patricia G; Albers, David J; Mamykina, Lena

2018-06-13

To develop and test a visual analytics tool to help clinicians identify systematic and clinically meaningful patterns in patient-generated data (PGD) while decreasing perceived information overload. Participatory design was used to develop Glucolyzer, an interactive tool featuring hierarchical clustering and a heatmap visualization to help registered dietitians (RDs) identify associative patterns between blood glucose levels and per-meal macronutrient composition for individuals with type 2 diabetes (T2DM). Ten RDs participated in a within-subjects experiment to compare Glucolyzer to a static logbook format. For each representation, participants had 25 minutes to examine 1 month of diabetes self-monitoring data captured by an individual with T2DM and identify clinically meaningful patterns. We compared the quality and accuracy of the observations generated using each representation. Participants generated 50% more observations when using Glucolyzer (98) than when using the logbook format (64) without any loss in accuracy (69% accuracy vs 62%, respectively, p = .17). Participants identified more observations that included ingredients other than carbohydrates using Glucolyzer (36% vs 16%, p = .027). Fewer RDs reported feelings of information overload using Glucolyzer compared to the logbook format. Study participants displayed variable acceptance of hierarchical clustering. Visual analytics have the potential to mitigate provider concerns about the volume of self-monitoring data. Glucolyzer helped dietitians identify meaningful patterns in self-monitoring data without incurring perceived information overload. Future studies should assess whether similar tools can support clinicians in personalizing behavioral interventions that improve patient outcomes.

Predicting stability limits for pure and doped dicationic noble gas clusters undergoing coulomb explosion: A parallel tempering based study.

PubMed

Ghorai, Sankar; Chaudhury, Pinaki

2018-05-30

We have used a replica exchange Monte-Carlo procedure, popularly known as Parallel Tempering, to study the problem of Coulomb explosion in homogeneous Ar and Xe dicationic clusters as well as mixed Ar-Xe dicationic clusters of varying sizes with different degrees of relative composition. All the clusters studied have two units of positive charges. The simulations reveal that in all the cases there is a cutoff size below which the clusters fragment. It is seen that for the case of pure Ar, the value is around 95 while that for Xe it is 55. For the mixed clusters with increasing Xe content, the cutoff limit for suppression of Coulomb explosion gradually decreases from 95 for a pure Ar to 55 for a pure Xe cluster. The hallmark of this study is this smooth progression. All the clusters are simulated using the reliable potential energy surface developed by Gay and Berne (Gay and Berne, Phys. Rev. Lett. 1982, 49, 194). For the hetero clusters, we have also discussed two different ways of charge distribution, that is one in which both positive charges are on two Xe atoms and the other where the two charges are at a Xe atom and at an Ar atom. The fragmentation patterns observed by us are such that single ionic ejections are the favored dissociating pattern. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

An Unexpected Detection of Bifurcated Blue Straggler Sequences in the Young Globular Cluster NGC 2173

NASA Astrophysics Data System (ADS)

Li, Chengyuan; Deng, Licai; de Grijs, Richard; Jiang, Dengkai; Xin, Yu

2018-03-01

The bifurcated patterns in the color–magnitude diagrams of blue straggler stars (BSSs) have attracted significant attention. This type of special (but rare) pattern of two distinct blue straggler sequences is commonly interpreted as evidence that cluster core-collapse-driven stellar collisions are an efficient formation mechanism. Here, we report the detection of a bifurcated blue straggler distribution in a young Large Magellanic Cloud cluster, NGC 2173. Because of the cluster’s low central stellar number density and its young age, dynamical analysis shows that stellar collisions alone cannot explain the observed BSSs. Therefore, binary evolution is instead the most viable explanation of the origin of these BSSs. However, the reason why binary evolution would render the color–magnitude distribution of BSSs bifurcated remains unclear. C. Li, L. Deng, and R. de Grijs jointly designed this project.

The biogeodynamics of microbial landscapes

NASA Astrophysics Data System (ADS)

Battin, T. J.; Hödl, I.; Bertuzzo, E.; Mari, L.; Suweis, S. S.; Rinaldo, A.

2011-12-01

Spatial configuration is fundamental in defining the structural and functional properties of biological systems. Biofilms, surface-attached and matrix-enclosed microorganisms, are a striking example of spatial organisation. Coupled biotic and abiotic processes shape the spatial organisation across scales of the landscapes formed by these benthic biofilms in streams and rivers. Experimenting with such biofilms in streams, we found that, depending on the streambed topography and the related hydrodynamic microenvironment, biofilm landscapes form increasingly diverging spatial patterns as they grow. Strikingly, however, cluster size distributions tend to converge even in contrasting hydrodynamic microenvironments. To reproduce the observed cluster size distributions we used a continuous, size-structured population model. The model accounts for the formation, growth, erosion and merging of biofilm clusters. Our results suggest not only that hydrodynamic forcing induce the diverging patterning of the microbial landscape, but also that microorganisms have developed strategies to equally exploit spatial resources independently of the physical structure of the microenvironment where they live.

A null model for microbial diversification

PubMed Central

Straub, Timothy J.

2017-01-01

Whether prokaryotes (Bacteria and Archaea) are naturally organized into phenotypically and genetically cohesive units comparable to animal or plant species remains contested, frustrating attempts to estimate how many such units there might be, or to identify the ecological roles they play. Analyses of gene sequences in various closely related prokaryotic groups reveal that sequence diversity is typically organized into distinct clusters, and processes such as periodic selection and extensive recombination are understood to be drivers of cluster formation (“speciation”). However, observed patterns are rarely compared with those obtainable with simple null models of diversification under stochastic lineage birth and death and random genetic drift. Via a combination of simulations and analyses of core and phylogenetic marker genes, we show that patterns of diversity for the genera Escherichia, Neisseria, and Borrelia are generally indistinguishable from patterns arising under a null model. We suggest that caution should thus be taken in interpreting observed clustering as a result of selective evolutionary forces. Unknown forces do, however, appear to play a role in Helicobacter pylori, and some individual genes in all groups fail to conform to the null model. Taken together, we recommend the presented birth−death model as a null hypothesis in prokaryotic speciation studies. It is only when the real data are statistically different from the expectations under the null model that some speciation process should be invoked. PMID:28630293

Sejong Open Cluster Survey (SOS). 0. Target Selection and Data Analysis

NASA Astrophysics Data System (ADS)

Sung, Hwankyung; Lim, Beomdu; Bessell, Michael S.; Kim, Jinyoung S.; Hur, Hyeonoh; Chun, Moo-Young; Park, Byeong-Gon

2013-06-01

Star clusters are superb astrophysical laboratories containing cospatial and coeval samples of stars with similar chemical composition. We initiate the Sejong Open cluster Survey (SOS) - a project dedicated to providing homogeneous photometry of a large number of open clusters in the SAAO Johnson-Cousins' UBVI system. To achieve our main goal, we pay much attention to the observation of standard stars in order to reproduce the SAAO standard system. Many of our targets are relatively small sparse clusters that escaped previous observations. As clusters are considered building blocks of the Galactic disk, their physical properties such as the initial mass function, the pattern of mass segregation, etc. give valuable information on the formation and evolution of the Galactic disk. The spatial distribution of young open clusters will be used to revise the local spiral arm structure of the Galaxy. In addition, the homogeneous data can also be used to test stellar evolutionary theory, especially concerning rare massive stars. In this paper we present the target selection criteria, the observational strategy for accurate photometry, and the adopted calibrations for data analysis such as color-color relations, zero-age main sequence relations, Sp - M_V relations, Sp - T_{eff} relations, Sp - color relations, and T_{eff} - BC relations. Finally we provide some data analysis such as the determination of the reddening law, the membership selection criteria, and distance determination.

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

PubMed

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

2016-09-01

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

Predictability of Sleep in Patients with Insomnia

PubMed Central

Vallières, Annie; Ivers, Hans; Beaulieu-Bonneau, Simon; Morin, Charles M.

2011-01-01

Study Objectives: To evaluate whether the night-to-night variability in insomnia follows specific predictable patterns and to characterize sleep patterns using objective sleep and clinical variables. Design: Prospective observational study. Setting: University-affiliated sleep disorders center. Participants: 146 participants suffering from chronic and primary insomnia. Measurements and Results: Daily sleep diaries were completed for an average of 48 days and self-reported questionnaires once. Three nights were spent in the sleep laboratory for polysomnographic (PSG) assessment. Sleep efficiency, sleep onset latency, wake after sleep onset, and total sleep time were derived from sleep diaries and PSG. Time-series diary data were used to compute conditional probabilities of having an insomnia night after 1, 2, or 3 consecutive insomnia night(s). Conditional probabilities were submitted to a k-means cluster analysis. A 3-cluster solution was retained. One cluster included 38 participants exhibiting an unpredictable insomnia pattern. Another included 30 participants with a low and decreasing probability to have an insomnia night. The last cluster included 49 participants exhibiting a high probability to have insomnia every night. Clusters differed on age, insomnia severity, and mental fatigue, and on subjective sleep variables, but not on PSG sleep variables. Conclusion: These findings replicate our previous study and provide additional evidence that unpredictability is a less prevalent feature of insomnia than suggested previously in the literature. The presence of the 3 clusters is discussed in term of sleep perception and sleep homeostasis dysregulation. Citation: Vallières A; Ivers H; Beaulieu-Bonneau S; Morin CM. Predictability of sleep in patients with insomnia. SLEEP 2011;34(5):609-617. PMID:21532954

Peeking Network States with Clustered Patterns

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

Kim, Jinoh; Sim, Alex

2015-10-20

Network traffic monitoring has long been a core element for effec- tive network management and security. However, it is still a chal- lenging task with a high degree of complexity for comprehensive analysis when considering multiple variables and ever-increasing traffic volumes to monitor. For example, one of the widely con- sidered approaches is to scrutinize probabilistic distributions, but it poses a scalability concern and multivariate analysis is not gen- erally supported due to the exponential increase of the complexity. In this work, we propose a novel method for network traffic moni- toring based on clustering, one of the powerful deep-learningmore » tech- niques. We show that the new approach enables us to recognize clustered results as patterns representing the network states, which can then be utilized to evaluate “similarity” of network states over time. In addition, we define a new quantitative measure for the similarity between two compared network states observed in dif- ferent time windows, as a supportive means for intuitive analysis. Finally, we demonstrate the clustering-based network monitoring with public traffic traces, and show that the proposed approach us- ing the clustering method has a great opportunity for feasible, cost- effective network monitoring.« less

Spatial patterns in electoral wards with high lymphoma incidence in Yorkshire health region.

PubMed Central

Barnes, N.; Cartwright, R. A.; O'Brien, C.; Roberts, B.; Richards, I. D.; Bird, C. C.

1987-01-01

The possibilities of clustering between those electoral wards which display higher than expected incidences of cases of the lymphomas occurring between 1978 and 1982 are examined. Clusters are defined as being those wards with cases in excess (at a probability of less than 10%) which are geographically adjacent to each other. A separate analysis extends the definition of cluster to include high incidence wards that are adjacent or separated by one other ward. The results indicate that many high incidence lymphoma wards do occur close together and when computer simulations are used to compute expected results, many of the observed results are shown to be highly improbable both in the overall number of clustering wards and in the largest number of wards comprising a 'cluster'. PMID:3663469

Suicide in the oldest old: an observational study and cluster analysis.

PubMed

Sinyor, Mark; Tan, Lynnette Pei Lin; Schaffer, Ayal; Gallagher, Damien; Shulman, Kenneth

2016-01-01

The older population are at a high risk for suicide. This study sought to learn more about the characteristics of suicide in the oldest-old and to use a cluster analysis to determine if oldest-old suicide victims assort into clinically meaningful subgroups. Data were collected from a coroner's chart review of suicide victims in Toronto from 1998 to 2011. We compared two age groups (65-79 year olds, n = 335, and 80+ year olds, n = 191) and then conducted a hierarchical agglomerative cluster analysis using Ward's method to identify distinct clusters in the 80+ group. The younger and older age groups differed according to marital status, living circumstances and pattern of stressors. The cluster analysis identified three distinct clusters in the 80+ group. Cluster 1 was the largest (n = 124) and included people who were either married or widowed who had significantly more depression and somewhat more medical health stressors. In contrast, cluster 2 (n = 50) comprised people who were almost all single and living alone with significantly less identified depression and slightly fewer medical health stressors. All members of cluster 3 (n = 17) lived in a retirement residence or nursing home, and this group had the highest rates of depression, dementia, other mental illness and past suicide attempts. This is the first study to use the cluster analysis technique to identify meaningful subgroups among suicide victims in the oldest-old. The results reveal different patterns of suicide in the older population that may be relevant for clinical care. Copyright © 2015 John Wiley & Sons, Ltd.

Exploring the relation between spatial configuration of buildings and remotely sensed temperatures

NASA Astrophysics Data System (ADS)

Myint, S. W.; Zheng, B.; Kaplan, S.; Huang, H.

2013-12-01

While the relationship between fractional cover of buildings and the UHI has been well studied, relationships of how spatial arrangements (e.g., clustered, dispersed) of buildings influence urban warming are not well understood. Since a diversity of spatial patterns can be observed under the same percentage of buildings cover, it is of great interest and importance to investigate the amount of variation in certain urban thermal feature such as surface temperature that is accounted for by the inclusion of spatial arrangement component. The various spatial arrangements of buildings cover can give rise to different urban thermal behaviors that may not be uncovered with the information of buildings fraction only, but can be captured to some extent using spatial analysis. The goal of this study is to examine how spatial arrangements of buildings influence and shape surface temperature in different urban settings. The study area selected is the Las-Vegas metropolitan area in Nevada, located in the Mojave Desert. An object-oriented approach was used to identify buildings using a Geoeye-1 image acquired on October 12, 2011. A spatial autocorrelation technique (i.e., Moran's I) that can measure spatial pattern (clustered, dispersed) was used to determine spatial configuration of buildings. A daytime temperature layer in degree Celsius, generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image, was integrated with Moran's I values of building cover and building fractions to achieve the goals set in the study. To avoid uncertainty and properly evaluate if spatial pattern of buildings has an impact on urban warming, the relation between Moran's I values and surface temperatures was observed at different levels according to their fractions (e.g., 0-0.1, 0.5-0.6, 0.9-1). There is a negative correlation exists between spatial pattern of buildings and surface temperatures implying that dispersed building arrangements elevate surface temperatures more severely than clustered buildings. This suggests that more clustered buildings have less impact on the urban heat island (UHI) effect. We conclude that having buildings as clustered as possible can be expected to protect the settlements from increased heat island effects, reduce pollution, and preserve the hydrological systems.

Spatial-temporal clustering of tornadoes

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Spatial-Temporal Clustering of Tornadoes

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Athletic groin pain (part 2): a prospective cohort study on the biomechanical evaluation of change of direction identifies three clusters of movement patterns

PubMed Central

Franklyn-Miller, A; Richter, C; King, E; Gore, S; Moran, K; Strike, S; Falvey, E C

2017-01-01

Background Athletic groin pain (AGP) is prevalent in sports involving repeated accelerations, decelerations, kicking and change-of-direction movements. Clinical and radiological examinations lack the ability to assess pathomechanics of AGP, but three-dimensional biomechanical movement analysis may be an important innovation. Aim The primary aim was to describe and analyse movements used by patients with AGP during a maximum effort change-of-direction task. The secondary aim was to determine if specific anatomical diagnoses were related to a distinct movement strategy. Methods 322 athletes with a current symptom of chronic AGP participated. Structured and standardised clinical assessments and radiological examinations were performed on all participants. Additionally, each participant performed multiple repetitions of a planned maximum effort change-of-direction task during which whole body kinematics were recorded. Kinematic and kinetic data were examined using continuous waveform analysis techniques in combination with a subgroup design that used gap statistic and hierarchical clustering. Results Three subgroups (clusters) were identified. Kinematic and kinetic measures of the clusters differed strongly in patterns observed in thorax, pelvis, hip, knee and ankle. Cluster 1 (40%) was characterised by increased ankle eversion, external rotation and knee internal rotation and greater knee work. Cluster 2 (15%) was characterised by increased hip flexion, pelvis contralateral drop, thorax tilt and increased hip work. Cluster 3 (45%) was characterised by high ankle dorsiflexion, thorax contralateral drop, ankle work and prolonged ground contact time. No correlation was observed between movement clusters and clinically palpated location of the participant's pain. Conclusions We identified three distinct movement strategies among athletes with long-standing groin pain during a maximum effort change-of-direction task These movement strategies were not related to clinical assessment findings but highlighted targets for rehabilitation in response to possible propagative mechanisms. Trial registration number NCT02437942, pre results. PMID:28209597

A uniform contribution of core-collapse and type Ia supernovae to the chemical enrichment pattern in the outskirts of the Virgo Cluster

DOE PAGES

Simionescu, A.; Werner, N.; Urban, O.; ...

2015-09-24

We present the first measurements of the abundances of α-elements (Mg, Si, and S) extending out beyond the virial radius of a cluster of galaxies. Our results, based on Suzaku Key Project observations of the Virgo Cluster, show that the chemical composition of the intracluster medium is consistent with being constant on large scales, with a flat distribution of the Si/Fe, S/Fe, and Mg/Fe ratios as a function of radius and azimuth out to 1.4 Mpc (1.3 r 200). Chemical enrichment of the intergalactic medium due solely to core-collapse supernovae (SNcc) is excluded with very high significance; instead, the measuredmore » metal abundance ratios are generally consistent with the solar value. The uniform metal abundance ratios observed today are likely the result of an early phase of enrichment and mixing, with both SNcc and SNe Ia contributing to the metal budget during the period of peak star formation activity at redshifts of 2–3. Furthermore, we estimate the ratio between the number of SNe Ia and the total number of supernovae enriching the intergalactic medium to be between 12% and 37%, broadly consistent with the metal abundance patterns in our own Galaxy or with the SN Ia contribution estimated for the cluster cores.« less

A UNIFORM CONTRIBUTION OF CORE-COLLAPSE AND TYPE Ia SUPERNOVAE TO THE CHEMICAL ENRICHMENT PATTERN IN THE OUTSKIRTS OF THE VIRGO CLUSTER

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

Simionescu, A.; Ichinohe, Y.; Werner, N.

2015-10-01

We present the first measurements of the abundances of α-elements (Mg, Si, and S) extending out beyond the virial radius of a cluster of galaxies. Our results, based on Suzaku Key Project observations of the Virgo Cluster, show that the chemical composition of the intracluster medium is consistent with being constant on large scales, with a flat distribution of the Si/Fe, S/Fe, and Mg/Fe ratios as a function of radius and azimuth out to 1.4 Mpc (1.3 r{sub 200}). Chemical enrichment of the intergalactic medium due solely to core-collapse supernovae (SNcc) is excluded with very high significance; instead, the measuredmore » metal abundance ratios are generally consistent with the solar value. The uniform metal abundance ratios observed today are likely the result of an early phase of enrichment and mixing, with both SNcc and SNe Ia contributing to the metal budget during the period of peak star formation activity at redshifts of 2–3. We estimate the ratio between the number of SNe Ia and the total number of supernovae enriching the intergalactic medium to be between 12% and 37%, broadly consistent with the metal abundance patterns in our own Galaxy or with the SN Ia contribution estimated for the cluster cores.« less

Spatial Hotspot Analysis of Acute Myocardial Infarction Events in an Urban Population: A Correlation Study of Health Problems and Industrial Installation

PubMed Central

NAMAYANDE, Motahareh Sadat; NEJADKOORKI, Farhad; NAMAYANDE, Seyedeh Mahdieh; DEHGHAN, Hamidreza

2016-01-01

Background: The current study’s objectives were to find any possible spatial patterns and hotspot of cardiovascular events and to perform a correlation study to find any possible relevance between cardiovascular disease (CVE) and location of industrial installation said above. Methods: We used the Acute Myocardial Infarction (AMI) hospital admission record in three main hospitals in Yazd, Yazd Province, Iran during 2013, because of CVDs and searched for possible correlation between industries as point-source pollutants and non-random distribution of AMI events. Results: MI incidence rate in Yazd was obtained 531 per 100,000 person-year among men, 458 per 100,000 person-year among women and 783/100,000 person-yr totally. We applied a GIS Hotspot analysis to determine feasible clusters and two sets of clusters were observed. Mean age of 56 AMI events occurred in the cluster cells was calculated as 62.21±14.75 yr. Age and sex as main confounders of AMI were evaluated in the cluster areas in comparison to other areas. We observed no significant difference regarding sex (59% in cluster cells versus 55% in total for men) and age (62.21±14.7 in cluster cells versus 63.28±13.98 in total for men). Conclusion: We found proximity of AMI events cluster to industries installations, and a steel industry, specifically. There could be an association between road-related pollutants and the observed sets of cluster due to the proximity exist between rather crowded highways nearby the events cluster. PMID:27057527

Atoll-scale patterns in coral reef community structure: Human signatures on Ulithi Atoll, Micronesia.

PubMed

Crane, Nicole L; Nelson, Peter; Abelson, Avigdor; Precoda, Kristin; Rulmal, John; Bernardi, Giacomo; Paddack, Michelle

2017-01-01

The dynamic relationship between reefs and the people who utilize them at a subsistence level is poorly understood. This paper characterizes atoll-scale patterns in shallow coral reef habitat and fish community structure, and correlates these with environmental characteristics and anthropogenic factors, critical to conservation efforts for the reefs and the people who depend on them. Hierarchical clustering analyses by site for benthic composition and fish community resulted in the same 3 major clusters: cluster 1-oceanic (close proximity to deep water) and uninhabited (low human impact); cluster 2-oceanic and inhabited (high human impact); and cluster 3-lagoonal (facing the inside of the lagoon) and inhabited (highest human impact). Distance from village, reef exposure to deep water and human population size had the greatest effect in predicting the fish and benthic community structure. Our study demonstrates a strong association between benthic and fish community structure and human use across the Ulithi Atoll (Yap State, Federated States of Micronesia) and confirms a pattern observed by local people that an 'opportunistic' scleractinian coral (Montipora sp.) is associated with more highly impacted reefs. Our findings suggest that small human populations (subsistence fishing) can nevertheless have considerable ecological impacts on reefs due, in part, to changes in fishing practices rather than overfishing per se, as well as larger global trends. Findings from this work can assist in building local capacity to manage reef resources across an atoll-wide scale, and illustrates the importance of anthropogenic impact even in small communities.

Atmospheric circulation feedback on west Asian dust and Indian monsoon rainfall

NASA Astrophysics Data System (ADS)

Kaskaoutis, Dimitris; Houssos, Elias; Gautam, Ritesh; Singh, Ramesh; Rashki, Alireza; Dumka, Umesh

2016-04-01

Classification of the atmospheric circulation patterns associated with high aerosol loading events over the Ganges valley, via the synergy of Factor and Cluster analysis techniques, has indicated six different synoptic weather patterns, two of which mostly occur during late pre-monsoon and monsoon seasons (May to September). The current study focuses on examining these two specific clusters that are associated with different mean sea level pressure (MSLP), geopotential height at 700 hPa (Z700) and wind fields that seem to affect the aerosol (mostly dust) emissions and precipitation distribution over the Indian sub-continent. Furthermore, the study reveals that enhanced aerosol presence over the Arabian Sea is positively associated with increased rainfall over the Indian landmass. The increased dust over the Arabian Sea and rainfall over India are associated with deepening of the northwestern Indian and Arabian lows that increase thermal convection and convergence of humid air masses into Indian landmass, resulting in larger monsoon precipitation. For this cluster, negative MSLP and Z700 anomalies are observed over the Arabian Peninsula that enhance the dust outflow from Arabia and, concurrently, the southwesterly air flow resulting in increase in monsoon precipitation over India. The daily precipitation over India is found to be positively correlated with the aerosol loading over the Arabian Sea for both weather clusters, thus verifying recent results from satellite observations and model simulations concerning the modulation of the Indian summer monsoon rainfall by the Arabian dust. The present work reveals that in addition to the radiative impacts of dust on modulating the monsoon rainfall, differing weather patterns favor changes in dust emissions, accumulation as well as rainfall distribution over south Asia.

Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition

PubMed Central

Cui, Zhiming; Zhao, Pengpeng

2014-01-01

A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity. PMID:24605045

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.

Double cusp encounter by Cluster: double cusp or motion of the cusp?

NASA Astrophysics Data System (ADS)

Escoubet, C. P.; Berchem, J.; Trattner, K. J.; Pitout, F.; Richard, R.; Taylor, M. G. G. T.; Soucek, J.; Grison, B.; Laakso, H.; Masson, A.; Dunlop, M.; Dandouras, I.; Reme, H.; Fazakerley, A.; Daly, P.

2013-04-01

Modelling plasma entry in the polar cusp has been successful in reproducing ion dispersions observed in the cusp at low and mid-altitudes. The use of a realistic convection pattern, when the IMF-By is large and stable, allowed Wing et al. (2001) to predict double cusp signatures that were subsequently observed by the DMSP spacecraft. In this paper we present a cusp crossing where two cusp populations are observed, separated by a gap around 1° Invariant Latitude (ILAT) wide. Cluster 1 (C1) and Cluster 2 (C2) observed these two cusp populations with a time delay of 3 min, and about 15 and 42 min later Cluster 4 (C4) and Cluster 3 (C3) observed, respectively, a single cusp population. A peculiarity of this event is the fact that the second cusp population seen on C1 and C2 was observed at the same time as the first cusp population on C4. This would tend to suggest that the two cusp populations had spatial features similar to the double cusp. Due to the nested crossing of C1 and C2 through the gap between the two cusp populations, C2 being first to leave the cusp and last to re-enter it, these observations are difficult to be explained by two distinct cusps with a gap in between. However, since we observe the cusp in a narrow area of local time post-noon, a second cusp may have been present in the pre-noon sector but could not be observed. On the other hand, these observations are in agreement with a motion of the cusp first dawnward and then back duskward due to the effect of the IMF-By component.

Recent variations in seasonality of temperature and precipitation in Canada, 1976-95

NASA Astrophysics Data System (ADS)

Whitfield, Paul H.; Bodtker, Karin; Cannon, Alex J.

2002-11-01

A previously reported analysis of rehabilitated monthly temperature and precipitation time series for several hundred stations across Canada showed generally spatially coherent patterns of variation between two decades (1976-85 and 1986-95). The present work expands that analysis to finer time scales and a greater number of stations. We demonstrate how the finer temporal resolution, at 5 day or 11 day intervals, increases the separation between clusters of recent variations in seasonal patterns of temperature and precipitation. We also expand the analysis by increasing the number of stations from only rehabilitated monthly data sets to rehabilitated daily sets, then to approximately 1500 daily observation stations. This increases the spatial density of data and allows a finer spatial resolution of patterns between the two decades. We also examine the success of clustering partial records, i.e. sites where the data record is incomplete. The intent of this study was to be consistent with previous work and explore how greater temporal and spatial detail in the climate data affects the resolution of patterns of recent climate variations. The variations we report for temperature and precipitation are taking place at different temporal and spatial scales. Further, the spatial patterns are much broader than local climate regions and ecozones, indicating that the differences observed may be the result of variations in atmospheric circulation.

Clustering of Dietary Patterns, Lifestyles, and Overweight among Spanish Children and Adolescents in the ANIBES Study

PubMed Central

Pérez-Rodrigo, Carmen; Gil, Ángel; González-Gross, Marcela; Ortega, Rosa M.; Serra-Majem, Lluis; Varela-Moreiras, Gregorio; Aranceta-Bartrina, Javier

2015-01-01

Weight gain has been associated with behaviors related to diet, sedentary lifestyle, and physical activity. We investigated dietary patterns and possible meaningful clustering of physical activity, sedentary behavior, and sleep time in Spanish children and adolescents and whether the identified clusters could be associated with overweight. Analysis was based on a subsample (n = 415) of the cross-sectional ANIBES study in Spain. We performed exploratory factor analysis and subsequent cluster analysis of dietary patterns, physical activity, sedentary behaviors, and sleep time. Logistic regression analysis was used to explore the association between the cluster solutions and overweight. Factor analysis identified four dietary patterns, one reflecting a profile closer to the traditional Mediterranean diet. Dietary patterns, physical activity behaviors, sedentary behaviors and sleep time on weekdays in Spanish children and adolescents clustered into two different groups. A low physical activity-poorer diet lifestyle pattern, which included a higher proportion of girls, and a high physical activity, low sedentary behavior, longer sleep duration, healthier diet lifestyle pattern. Although increased risk of being overweight was not significant, the Prevalence Ratios (PRs) for the low physical activity-poorer diet lifestyle pattern were >1 in children and in adolescents. The healthier lifestyle pattern included lower proportions of children and adolescents from low socioeconomic status backgrounds. PMID:26729155

Tests of Si(111)-7 × 7 structural models by comparison with transmission electron diffraction patterns

NASA Astrophysics Data System (ADS)

McRae, E. G.; Petroff, P. M.

1984-11-01

Several structural models of the Si(111)-7 × 7 surface are tested by comparing calculated and observed transmission electron diffraction (TED) patterns. The models comprise "adatom" models where the unit mesh contains 12 adatoms or atom clusters in a locally (2 × 2) arrangement, and "triangle-dimer" models where the unit mesh contains 9 dimers or pairs of dimers bordering a triangular subunit of the unit mesh. The distribution of diffraction intensity among fractional-order spots is calculated kinematically and compared with TED patterns observed by Petroff and Wilson and others. No agreement is found for adatom models. Good but not perfect agreement is found for one triangle-dimer model.

Meteor tracking via local pattern clustering in spatio-temporal domain

NASA Astrophysics Data System (ADS)

Kukal, Jaromír.; Klimt, Martin; Švihlík, Jan; Fliegel, Karel

2016-09-01

Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).

Selection of intracellular calcium patterns in a model with clustered Ca2+ release channels

NASA Astrophysics Data System (ADS)

Shuai, J. W.; Jung, P.

2003-03-01

A two-dimensional model is proposed for intracellular Ca2+ waves, which incorporates both the discrete nature of Ca2+ release sites in the endoplasmic reticulum membrane and the stochastic dynamics of the clustered inositol 1,4,5-triphosphate (IP3) receptors. Depending on the Ca2+ diffusion coefficient and concentration of IP3, various spontaneous Ca2+ patterns, such as calcium puffs, local waves, abortive waves, global oscillation, and tide waves, can be observed. We further investigate the speed of the global waves as a function of the IP3 concentration and the Ca2+ diffusion coefficient and under what conditions the spatially averaged Ca2+ response can be described by a simple set of ordinary differential equations.

Topological defect clustering and plastic deformation mechanisms in functionalized graphene

NASA Astrophysics Data System (ADS)

Nunes, Ricardo; Araujo, Joice; Chacham, Helio

2011-03-01

We present ab initio results suggesting that strain plays a central role in the clustering of topological defects in strained and functionalized graphene models. We apply strain onto the topological-defect graphene networks from our previous work, and obtain topological-defect clustering patterns which are in excellent agreement with recent observations in samples of reduced graphene oxide. In our models, the graphene layer, containing an initial concentration of isolated topological defects, is covered by hydrogen or hydroxyl groups. Our results also suggest a rich variety of plastic deformation mechanism in functionalized graphene systems. We acknowledge support from the Brazilian agencies: CNPq, Fapemig, and INCT-Materiais de Carbono.

Segmentation and clustering as complementary sources of information

NASA Astrophysics Data System (ADS)

Dale, Michael B.; Allison, Lloyd; Dale, Patricia E. R.

2007-03-01

This paper examines the effects of using a segmentation method to identify change-points or edges in vegetation. It identifies coherence (spatial or temporal) in place of unconstrained clustering. The segmentation method involves change-point detection along a sequence of observations so that each cluster formed is composed of adjacent samples; this is a form of constrained clustering. The protocol identifies one or more models, one for each section identified, and the quality of each is assessed using a minimum message length criterion, which provides a rational basis for selecting an appropriate model. Although the segmentation is less efficient than clustering, it does provide other information because it incorporates textural similarity as well as homogeneity. In addition it can be useful in determining various scales of variation that may apply to the data, providing a general method of small-scale pattern analysis.

High-resolution Spectroscopic Observations of Single Red Giants in Three Open Clusters: NGC 2360, NGC 3680, and NGC 5822

NASA Astrophysics Data System (ADS)

Peña Suárez, V. J.; Sales Silva, J. V.; Katime Santrich, O. J.; Drake, N. A.; Pereira, C. B.

2018-02-01

Single stars in open clusters with known distances are important targets in constraining the nucleosynthesis process since their ages and luminosities are also known. In this work, we analyze a sample of 29 single red giants of the open clusters NGC 2360, NGC 3680, and NGC 5822 using high-resolution spectroscopy. We obtained atmospheric parameters, abundances of the elements C, N, O, Na, Mg, Al, Ca, Si, Ti, Ni, Cr, Y, Zr, La, Ce, and Nd, as well as radial and rotational velocities. We employed the local thermodynamic equilibrium atmospheric models of Kurucz and the spectral analysis code MOOG. Rotational velocities and light-element abundances were derived using spectral synthesis. Based on our analysis of the single red giants in these three open clusters, we could compare, for the first time, their abundance pattern with that of the binary stars of the same clusters previously studied. Our results show that the abundances of both single and binary stars of the open clusters NGC 2360, NGC 3680, and NGC 5822 do not have significant differences. For the elements created by the s-process, we observed that the open clusters NGC 2360, NGC 3680, and NGC 5822 also follow the trend already raised in the literature that young clusters have higher s-process element abundances than older clusters. Finally, we observed that the three clusters of our sample exhibit a trend in the [Y/Mg]-age relation, which may indicate the ability of the [Y/Mg] ratio to be used as a clock for the giants. Based on the observations made with the 2.2 m telescope at the European Southern Observatory (La Silla, Chile) under an agreement with Observatório Nacional and under an agreement between Observatório Nacional and Max-Planck Institute für Astronomie.

Novel layered clustering-based approach for generating ensemble of classifiers.

PubMed

Rahman, Ashfaqur; Verma, Brijesh

2011-05-01

This paper introduces a novel concept for creating an ensemble of classifiers. The concept is based on generating an ensemble of classifiers through clustering of data at multiple layers. The ensemble classifier model generates a set of alternative clustering of a dataset at different layers by randomly initializing the clustering parameters and trains a set of base classifiers on the patterns at different clusters in different layers. A test pattern is classified by first finding the appropriate cluster at each layer and then using the corresponding base classifier. The decisions obtained at different layers are fused into a final verdict using majority voting. As the base classifiers are trained on overlapping patterns at different layers, the proposed approach achieves diversity among the individual classifiers. Identification of difficult-to-classify patterns through clustering as well as achievement of diversity through layering leads to better classification results as evidenced from the experimental results.

Beverage consumption patterns of Canadian adults aged 19 to 65 years.

PubMed

Nikpartow, Nooshin; Danyliw, Adrienne D; Whiting, Susan J; Lim, Hyun J; Vatanparast, Hassanali

2012-12-01

To investigate the beverage intake patterns of Canadian adults and explore characteristics of participants in different beverage clusters. Analyses of nationally representative data with cross-sectional complex stratified design. Canadian Community Health Survey, Cycle 2.2 (2004). A total of 14 277 participants aged 19-65 years, in whom dietary intake was assessed using a single 24 h recall, were included in the study. After determining total intake and the contribution of beverages to total energy intake among age/sex groups, cluster analysis (K-means method) was used to classify males and females into distinct clusters based on the dominant pattern of beverage intakes. To test differences across clusters, χ2 tests and 95 % confidence intervals of the mean intakes were used. Six beverage clusters in women and seven beverage clusters in men were identified. 'Sugar-sweetened' beverage clusters - regular soft drinks and fruit drinks - as well as a 'beer' cluster, appeared for both men and women. No 'milk' cluster appeared among women. The mean consumption of the dominant beverage in each cluster was higher among men than women. The 'soft drink' cluster in men had the lowest proportion of the higher levels of education, and in women the highest proportion of inactivity, compared with other beverage clusters. Patterns of beverage intake in Canadian women indicate high consumption of sugar-sweetened beverages particularly fruit drinks, low intake of milk and high intake of beer. These patterns in women have implications for poor bone health, risk of obesity and other morbidities.

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

PubMed

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

2018-01-01

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

Delineation of Stenotrophomonas maltophilia isolates from cystic fibrosis patients by fatty acid methyl ester profiles and matrix-assisted laser desorption/ionization time-of-flight mass spectra using hierarchical cluster analysis and principal component analysis.

PubMed

Vidigal, Pedrina Gonçalves; Mosel, Frank; Koehling, Hedda Luise; Mueller, Karl Dieter; Buer, Jan; Rath, Peter Michael; Steinmann, Joerg

2014-12-01

Stenotrophomonas maltophilia is an opportunist multidrug-resistant pathogen that causes a wide range of nosocomial infections. Various cystic fibrosis (CF) centres have reported an increasing prevalence of S. maltophilia colonization/infection among patients with this disease. The purpose of this study was to assess specific fingerprints of S. maltophilia isolates from CF patients (n = 71) by investigating fatty acid methyl esters (FAMEs) through gas chromatography (GC) and highly abundant proteins by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), and to compare them with isolates obtained from intensive care unit (ICU) patients (n = 20) and the environment (n = 11). Principal component analysis (PCA) of GC-FAME patterns did not reveal a clustering corresponding to distinct CF, ICU or environmental types. Based on the peak area index, it was observed that S. maltophilia isolates from CF patients produced significantly higher amounts of fatty acids in comparison with ICU patients and the environmental isolates. Hierarchical cluster analysis (HCA) based on the MALDI-TOF MS peak profiles of S. maltophilia revealed the presence of five large clusters, suggesting a high phenotypic diversity. Although HCA of MALDI-TOF mass spectra did not result in distinct clusters predominantly composed of CF isolates, PCA revealed the presence of a distinct cluster composed of S. maltophilia isolates from CF patients. Our data suggest that S. maltophilia colonizing CF patients tend to modify not only their fatty acid patterns but also their protein patterns as a response to adaptation in the unfavourable environment of the CF lung. © 2014 The Authors.

A view of the H-band light-element chemical patterns in globular clusters under the AGB self-enrichment scenario

NASA Astrophysics Data System (ADS)

Dell'Agli, F.; García-Hernández, D. A.; Ventura, P.; Mészáros, Sz; Masseron, T.; Fernández-Trincado, J. G.; Tang, B.; Shetrone, M.; Zamora, O.; Lucatello, S.

2018-04-01

We discuss the self-enrichment scenario by asymptotic giant branch (AGB) stars for the formation of multiple populations in globular clusters (GCs) by analysing data set of giant stars observed in nine Galactic GCs, covering a wide range of metallicities and for which the simultaneous measurements of C, N, O, Mg, Al, and Si are available. To this aim, we calculated six sets of AGB models, with the same chemical composition as the stars belonging to the first generation of each GC. We find that the AGB yields can reproduce the set of observations available, not only in terms of the degree of contamination shown by stars in each GC but, more important, also the observed trend with metallicity, which agrees well with the predictions from AGB evolution modelling. While further observational evidences are required to definitively fix the main actors in the pollution of the interstellar medium from which new generation of stars formed in GCs, the present results confirm that the gas ejected by stars of mass in the range 4 M_{⊙} ≤ M ≤ 8 M_{⊙} during the AGB phase share the same chemical patterns traced by stars in GCs.

Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers

PubMed Central

Jackson, Monica C; Huang, Lan; Luo, Jun; Hachey, Mark; Feuer, Eric

2009-01-01

Background The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated. Methods We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*pop; and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. Results For simulated data with outlier patterns, Tango's MEET, Moran's I and I*pop had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*pop (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. Conclusion SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*pop perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango's method should be used for global clustering evaluation instead of SaTScan. PMID:19822013

Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers.

PubMed

Jackson, Monica C; Huang, Lan; Luo, Jun; Hachey, Mark; Feuer, Eric

2009-10-12

The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated. We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*(pop); and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. For simulated data with outlier patterns, Tango's MEET, Moran's I and I*(pop) had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*(pop) (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*(pop) perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango's method should be used for global clustering evaluation instead of SaTScan.

Stable Chimeras and Independently Synchronizable Clusters

NASA Astrophysics Data System (ADS)

Cho, Young Sul; Nishikawa, Takashi; Motter, Adilson E.

2017-08-01

Cluster synchronization is a phenomenon in which a network self-organizes into a pattern of synchronized sets. It has been shown that diverse patterns of stable cluster synchronization can be captured by symmetries of the network. Here, we establish a theoretical basis to divide an arbitrary pattern of symmetry clusters into independently synchronizable cluster sets, in which the synchronization stability of the individual clusters in each set is decoupled from that in all the other sets. Using this framework, we suggest a new approach to find permanently stable chimera states by capturing two or more symmetry clusters—at least one stable and one unstable—that compose the entire fully symmetric network.

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.

Influence of hormonal control on LH pulsatility and secretion in women with classical congenital adrenal hyperplasia.

PubMed

Bachelot, Anne; Chakhtoura, Zeina; Plu-Bureau, Geneviève; Coudert, Mathieu; Coussieu, Christiane; Badachi, Yasmina; Dulon, Jérome; Charbit, Beny; Touraine, Philippe

2012-10-01

Women with classical congenital adrenal hyperplasia (CAH) exhibit reduced fertility due to several factors including anovulation. This has been attributed to a disturbed gonadotropic axis as in polycystic ovary syndrome (PCOS), but there is no precise evaluation. Our aim was to evaluate the gonadotropic axis and LH pulsatility patterns and to determine factor(s) that could account for the potential abnormality of LH pulsatility. Case/control study. Sixteen CAH women (11 with the salt-wasting form and five with the simple virilizing form), aged from 18 to 40 years, and 16 age-matched women, with regular menstrual cycles (28 ± 3 days), were included. LH pulse patterns over 6 h were determined in patients and controls. No differences were observed between patients and controls in terms of mean LH levels, LH pulse amplitude, or LH frequency. In CAH patients, LH pulsatility patterns were heterogeneous, leading us to perform a clustering analysis of LH data, resulting in a two-cluster partition. Patients in cluster 1 had similar LH pulsatility patterns to the controls. Patients in cluster 2 had: lower LH pulse amplitude and frequency and presented menstrual cycle disturbances more frequently; higher 17-OH progesterone, testosterone, progesterone, and androstenedione levels; and lower FSH levels. LH pulsatility may be normal in CAH women well controlled by hormonal treatment. Undertreatment is responsible for hypogonadotropic hypogonadism, with low LH pulse levels and frequency, but not PCOS. Suppression of progesterone and androgen concentrations during the follicular phase of the menstrual cycle should be a major objective in these patients.

Meteorology-induced variations in the spatial behavior of summer ozone pollution in Central California

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

Jin, Ling; Harley, Robert A.; Brown, Nancy J.

Cluster analysis was applied to daily 8 h ozone maxima modeled for a summer season to characterize meteorology-induced variations in the spatial distribution of ozone. Principal component analysis is employed to form a reduced dimension set to describe and interpret ozone spatial patterns. The first three principal components (PCs) capture {approx}85% of total variance, with PC1 describing a general spatial trend, and PC2 and PC3 each describing a spatial contrast. Six clusters were identified for California's San Joaquin Valley (SJV) with two low, three moderate, and one high-ozone cluster. The moderate ozone clusters are distinguished by elevated ozone levels inmore » different parts of the valley: northern, western, and eastern, respectively. The SJV ozone clusters have stronger coupling with the San Francisco Bay area (SFB) than with the Sacramento Valley (SV). Variations in ozone spatial distributions induced by anthropogenic emission changes are small relative to the overall variations in ozone amomalies observed for the whole summer. Ozone regimes identified here are mostly determined by the direct and indirect meteorological effects. Existing measurement sites are sufficiently representative to capture ozone spatial patterns in the SFB and SV, but the western side of the SJV is under-sampled.« less

Skill transfer, affordances and dexterity in different climbing environments.

PubMed

Seifert, L; Wattebled, L; L'hermette, M; Bideault, G; Herault, R; Davids, K

2013-12-01

This study explored how skills in one region of a perceptual-motor landscape of performance, created in part by previous experience in rock climbing, can shape those that emerge in another region (ice climbing). Ten novices in rock climbing and five intermediate rock climbers were observed climbing an icefall. Locations of right and left ice tools and crampons were videotaped from a frontal camera. Inter-individual variability of upper and lower limb couplings and types of action regarding icefall properties were assessed by cluster hierarchical analysis, distinguishing three clusters. Pelvis vertical displacement, duration and number of pelvis pauses were also analyzed. Experienced rock climbers were grouped in the same cluster and showed the highest range and variability of limb angular locations and coordination patterns, the highest vertical displacement and the shortest pelvis plateaux durations. Non-fluent climbers (clusters 2 and 3) showed low range and variability of limb angular locations and coordination patterns. In particular, climbers of cluster 3 exhibited the lowest vertical displacement, the longest plateaux durations and the greatest ratio between tool swinging and definitive anchorage. Our results exemplified the positive influence of skills in rock climbing on ice climbing performance, facilitated by the detection of affordances from environmental properties. Copyright © 2013 Elsevier B.V. All rights reserved.

Guasom Analysis Of The Alhambra Survey

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Patterns of Dysmorphic Features in Schizophrenia

PubMed Central

Scutt, L.E.; Chow, E.W.C.; Weksberg, R.; Honer, W.G.; Bassett, Anne S.

2011-01-01

Congenital dysmorphic features are prevalent in schizophrenia and may reflect underlying neurodevelopmental abnormalities. A cluster analysis approach delineating patterns of dysmorphic features has been used in genetics to classify individuals into more etiologically homogeneous subgroups. In the present study, this approach was applied to schizophrenia, using a sample with a suspected genetic syndrome as a testable model. Subjects (n = 159) with schizophrenia or schizoaffective disorder were ascertained from chronic patient populations (random, n=123) or referred with possible 22q11 deletion syndrome (referred, n = 36). All subjects were evaluated for presence or absence of 70 reliably assessed dysmorphic features, which were used in a three-step cluster analysis. The analysis produced four major clusters with different patterns of dysmorphic features. Significant between-cluster differences were found for rates of 37 dysmorphic features (P < 0.05), median number of dysmorphic features (P = 0.0001), and validating features not used in the cluster analysis: mild mental retardation (P = 0.001) and congenital heart defects (P = 0.002). Two clusters (1 and 4) appeared to represent more developmental subgroups of schizophrenia with elevated rates of dysmorphic features and validating features. Cluster 1 (n = 27) comprised mostly referred subjects. Cluster 4 (n= 18) had a different pattern of dysmorphic features; one subject had a mosaic Turner syndrome variant. Two other clusters had lower rates and patterns of features consistent with those found in previous studies of schizophrenia. Delineating patterns of dysmorphic features may help identify subgroups that could represent neurodevelopmental forms of schizophrenia with more homogeneous origins. PMID:11803519

Autonomic specificity of basic emotions: evidence from pattern classification and cluster analysis.

PubMed

Stephens, Chad L; Christie, Israel C; Friedman, Bruce H

2010-07-01

Autonomic nervous system (ANS) specificity of emotion remains controversial in contemporary emotion research, and has received mixed support over decades of investigation. This study was designed to replicate and extend psychophysiological research, which has used multivariate pattern classification analysis (PCA) in support of ANS specificity. Forty-nine undergraduates (27 women) listened to emotion-inducing music and viewed affective films while a montage of ANS variables, including heart rate variability indices, peripheral vascular activity, systolic time intervals, and electrodermal activity, were recorded. Evidence for ANS discrimination of emotion was found via PCA with 44.6% of overall observations correctly classified into the predicted emotion conditions, using ANS variables (z=16.05, p<.001). Cluster analysis of these data indicated a lack of distinct clusters, which suggests that ANS responses to the stimuli were nomothetic and stimulus-specific rather than idiosyncratic and individual-specific. Collectively these results further confirm and extend support for the notion that basic emotions have distinct ANS signatures. Copyright © 2010 Elsevier B.V. All rights reserved.

A global deltas typology of environmental stress and its relation to terrestrial hydrology

NASA Astrophysics Data System (ADS)

Tessler, Z. D.; Vorosmarty, C. J.; McDonald, K. C.; Schroeder, R.; Grossberg, M.; Gladkova, I.; Aizenman, H.

2013-12-01

River delta systems around the world are under varying degrees of environmental stress stemming from a variety of human impacts, both from upstream basin based activities and local impacts on the deltas themselves, as well as sea level rise. These stresses are known to affect rates of relative sea level rise by disrupting the delivery or deposition of sediment on the delta. We present a global database of several of these stresses, and investigate patterns of stress across delta systems. Several methods of aggregating the environmental stressors into an index score are also investigated. A statistical clustering analysis, which we refer to as a "global delta fingerprinting system", across the environmental stresses identifies systems under similar states of threat. Several deltas, including the Nile, are in unique clusters, while regional patterns are evident among deltas in Southeast Asia. These patterns are compared with observed surface inundation derived from SAR, NDVI from MODIS, river discharge estimates from the WBMplus numerical model, and ocean wave activity from WAVEWATCH III. Delta inundation sensitivity to river and coastal forcings are observed to vary with environmental stress and social indicators including population density and GDP.

Genetics and evolution of Yersinia pseudotuberculosis O-specific polysaccharides: a novel pattern of O-antigen diversity

PubMed Central

Kenyon, Johanna J.; Cunneen, Monica M.

2017-01-01

Abstract O-antigen polysaccharide is a major immunogenic feature of the lipopolysaccharide of Gram-negative bacteria, and most species produce a large variety of forms that differ substantially from one another. There are 18 known O-antigen forms in the Yersinia pseudotuberculosis complex, which are typical in being composed of multiple copies of a short oligosaccharide called an O unit. The O-antigen gene clusters are located between the hemH and gsk genes, and are atypical as 15 of them are closely related, each having one of five downstream gene modules for alternative main-chain synthesis, and one of seven upstream modules for alternative side-branch sugar synthesis. As a result, many of the genes are in more than one gene cluster. The gene order in each module is such that, in general, the earlier a gene product functions in O-unit synthesis, the closer the gene is to the 5΄ end for side-branch modules or the 3΄ end for main-chain modules. We propose a model whereby natural selection could generate the observed pattern in gene order, a pattern that has also been observed in other species. PMID:28364730

Partial bisulfite conversion for unique template sequencing

PubMed Central

Kumar, Vijay; Rosenbaum, Julie; Wang, Zihua; Forcier, Talitha; Ronemus, Michael; Wigler, Michael

2018-01-01

Abstract We introduce a new protocol, mutational sequencing or muSeq, which uses sodium bisulfite to randomly deaminate unmethylated cytosines at a fixed and tunable rate. The muSeq protocol marks each initial template molecule with a unique mutation signature that is present in every copy of the template, and in every fragmented copy of a copy. In the sequenced read data, this signature is observed as a unique pattern of C-to-T or G-to-A nucleotide conversions. Clustering reads with the same conversion pattern enables accurate count and long-range assembly of initial template molecules from short-read sequence data. We explore count and low-error sequencing by profiling 135 000 restriction fragments in a PstI representation, demonstrating that muSeq improves copy number inference and significantly reduces sporadic sequencer error. We explore long-range assembly in the context of cDNA, generating contiguous transcript clusters greater than 3,000 bp in length. The muSeq assemblies reveal transcriptional diversity not observable from short-read data alone. PMID:29161423

Pattern formation and collective effects in populations of magnetic microswimmers

NASA Astrophysics Data System (ADS)

Vach, Peter J.; Walker, Debora; Fischer, Peer; Fratzl, Peter; Faivre, Damien

2017-03-01

Self-propelled particles are one prototype of synthetic active matter used to understand complex biological processes, such as the coordination of movement in bacterial colonies or schools of fishes. Collective patterns such as clusters were observed for such systems, reproducing features of biological organization. However, one limitation of this model is that the synthetic assemblies are made of identical individuals. Here we introduce an active system based on magnetic particles at colloidal scales. We use identical but also randomly-shaped magnetic micropropellers and show that they exhibit dynamic and reversible pattern formation.

Managing distance and covariate information with point-based clustering.

PubMed

Whigham, Peter A; de Graaf, Brandon; Srivastava, Rashmi; Glue, Paul

2016-09-01

Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley's K and applied to the problem of clustering with deliberate self-harm (DSH), is presented. Point-based Monte-Carlo simulation of Ripley's K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years' emergency hospital presentations (n = 136) in a New Zealand town (population ~50,000). Study area was defined by residential (housing) land parcels representing a finite set of possible point addresses. Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley's K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for covariate measures that exhibit spatial clustering, such as deprivation, are crucial when assessing point-based clustering.

Stability-based validation of dietary patterns obtained by cluster analysis.

PubMed

Sauvageot, Nicolas; Schritz, Anna; Leite, Sonia; Alkerwi, Ala'a; Stranges, Saverio; Zannad, Faiez; Streel, Sylvie; Hoge, Axelle; Donneau, Anne-Françoise; Albert, Adelin; Guillaume, Michèle

2017-01-14

Cluster analysis is a data-driven method used to create clusters of individuals sharing similar dietary habits. However, this method requires specific choices from the user which have an influence on the results. Therefore, there is a need of an objective methodology helping researchers in their decisions during cluster analysis. The objective of this study was to use such a methodology based on stability of clustering solutions to select the most appropriate clustering method and number of clusters for describing dietary patterns in the NESCAV study (Nutrition, Environment and Cardiovascular Health), a large population-based cross-sectional study in the Greater Region (N = 2298). Clustering solutions were obtained with K-means, K-medians and Ward's method and a number of clusters varying from 2 to 6. Their stability was assessed with three indices: adjusted Rand index, Cramer's V and misclassification rate. The most stable solution was obtained with K-means method and a number of clusters equal to 3. The "Convenient" cluster characterized by the consumption of convenient foods was the most prevalent with 46% of the population having this dietary behaviour. In addition, a "Prudent" and a "Non-Prudent" patterns associated respectively with healthy and non-healthy dietary habits were adopted by 25% and 29% of the population. The "Convenient" and "Non-Prudent" clusters were associated with higher cardiovascular risk whereas the "Prudent" pattern was associated with a decreased cardiovascular risk. Associations with others factors showed that the choice of a specific dietary pattern is part of a wider lifestyle profile. This study is of interest for both researchers and public health professionals. From a methodological standpoint, we showed that using stability of clustering solutions could help researchers in their choices. From a public health perspective, this study showed the need of targeted health promotion campaigns describing the benefits of healthy dietary patterns.

Atoll-scale patterns in coral reef community structure: Human signatures on Ulithi Atoll, Micronesia

PubMed Central

Nelson, Peter; Abelson, Avigdor; Precoda, Kristin; Rulmal, John; Bernardi, Giacomo; Paddack, Michelle

2017-01-01

The dynamic relationship between reefs and the people who utilize them at a subsistence level is poorly understood. This paper characterizes atoll-scale patterns in shallow coral reef habitat and fish community structure, and correlates these with environmental characteristics and anthropogenic factors, critical to conservation efforts for the reefs and the people who depend on them. Hierarchical clustering analyses by site for benthic composition and fish community resulted in the same 3 major clusters: cluster 1–oceanic (close proximity to deep water) and uninhabited (low human impact); cluster 2–oceanic and inhabited (high human impact); and cluster 3–lagoonal (facing the inside of the lagoon) and inhabited (highest human impact). Distance from village, reef exposure to deep water and human population size had the greatest effect in predicting the fish and benthic community structure. Our study demonstrates a strong association between benthic and fish community structure and human use across the Ulithi Atoll (Yap State, Federated States of Micronesia) and confirms a pattern observed by local people that an ‘opportunistic’ scleractinian coral (Montipora sp.) is associated with more highly impacted reefs. Our findings suggest that small human populations (subsistence fishing) can nevertheless have considerable ecological impacts on reefs due, in part, to changes in fishing practices rather than overfishing per se, as well as larger global trends. Findings from this work can assist in building local capacity to manage reef resources across an atoll-wide scale, and illustrates the importance of anthropogenic impact even in small communities. PMID:28489903

On the non-Poissonian repetition pattern of FRB121102

NASA Astrophysics Data System (ADS)

Oppermann, Niels; Yu, Hao-Ran; Pen, Ue-Li

2018-04-01

The Fast Radio Burst FRB121102 has been observed to repeat in an irregular fashion. Using published timing data of the observed bursts, we show that Poissonian statistics are not a good description of this random process. As an alternative, we suggest to describe the intervals between bursts with a Weibull distribution with a shape parameter smaller than one, which allows for the clustered nature of the bursts. We quantify the amount of clustering using the parameters of the Weibull distribution and discuss the consequences that it has for the detection probabilities of future observations and for the optimization of observing strategies. Allowing for this generalization, we find a mean repetition rate of r=5.7^{+3.0}_{-2.0} per day and index k=0.34^{+0.06}_{-0.05} for a correlation function ξ(t) = (t/t0)k - 1.

Cluster analysis of multiple planetary flow regimes

NASA Technical Reports Server (NTRS)

Mo, Kingtse; Ghil, Michael

1987-01-01

A modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them. This method was applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data. The dynamical model is governed by the fully-nonlinear, equivalent-barotropic vorticity equation on the sphere. Clusters of point in the model's phase space are associated with either a few persistent or with many transient events. Two stationary clusters have patterns similar to unstable stationary model solutions, zonal, or blocked. Transient clusters of wave trains serve as way stations between the stationary ones. For the NH data, cluster analysis was performed in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters are found in the low-frequency band of more than 10 days, and transient clusters in the bandpass frequency window between 2.5 and 6 days. In the low-frequency band three pairs of clusters determine, respectively, EOFs 1, 2, and 3. They exhibit well-known regional features, such as blocking, the Pacific/North American (PNA) pattern and wave trains. Both model and low-pass data show strong bimodality. Clusters in the bandpass window show wave-train patterns in the two jet exit regions. They are related, as in the model, to transitions between stationary clusters.

Phylogeographic analysis of rabies viruses in the Philippines.

PubMed

Tohma, Kentaro; Saito, Mariko; Kamigaki, Taro; Tuason, Laarni T; Demetria, Catalino S; Orbina, Jun Ryan C; Manalo, Daria L; Miranda, Mary E; Noguchi, Akira; Inoue, Satoshi; Suzuki, Akira; Quiambao, Beatriz P; Oshitani, Hitoshi

2014-04-01

Rabies still remains a public health threat in the Philippines. A significant number of human rabies cases, about 200-300 cases annually, have been reported, and the country needs an effective strategy for rabies control. To develop an effective control strategy, it is important to understand the transmission patterns of the rabies viruses. We conducted phylogenetic analyses by considering the temporal and spatial evolution of rabies viruses to reveal the transmission dynamics in the Philippines. After evaluating the molecular clock and phylogeographic analysis, we estimated that the Philippine strains were introduced from China around the beginning of 20th century. Upon this introduction, the rabies viruses evolved within the Philippines to form three major clades, and there was no indication of introduction of other rabies viruses from any other country. However, within the Philippines, island-to-island migrations were observed. Since then, the rabies viruses have diffused and only evolved within each island group. The evolutionary pattern of these viruses was strongly shaped by geographical boundaries. The association index statistics demonstrated a strong spatial structure within the island group, indicating that the seas were a significant geographical barrier for viral dispersal. Strong spatial structure was also observed even at a regional level, and most of the viral migrations (79.7% of the total median number) in Luzon were observed between neighboring regions. Rabies viruses were genetically clustered at a regional level, and this strong spatial structure suggests a geographical clustering of transmission chains and the potential effectiveness of rabies control that targets geographical clustering. Dog vaccination campaigns have been conducted independently by local governments in the Philippines, but it could be more effective to implement a coordinated vaccination campaign among neighboring areas to eliminate geographically-clustered rabies transmission chains. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Micro-flock patterns and macro-clusters in chiral active Brownian disks

NASA Astrophysics Data System (ADS)

Levis, Demian; Liebchen, Benno

2018-02-01

Chiral active particles (or self-propelled circle swimmers) feature a rich collective behavior, comprising rotating macro-clusters and micro-flock patterns which consist of phase-synchronized rotating clusters with a characteristic self-limited size. These patterns emerge from the competition of alignment interactions and rotations suggesting that they might occur generically in many chiral active matter systems. However, although excluded volume interactions occur naturally among typical circle swimmers, it is not yet clear if macro-clusters and micro-flock patterns survive their presence. The present work shows that both types of pattern do survive but feature strongly enhance fluctuations regarding the size and shape of the individual clusters. Despite these fluctuations, we find that the average micro-flock size still follows the same characteristic scaling law as in the absence of excluded volume interactions, i.e. micro-flock sizes scale linearly with the single-swimmer radius.

Effect of dose and size on defect engineering in carbon cluster implanted silicon wafers

NASA Astrophysics Data System (ADS)

Okuyama, Ryosuke; Masada, Ayumi; Shigematsu, Satoshi; Kadono, Takeshi; Hirose, Ryo; Koga, Yoshihiro; Okuda, Hidehiko; Kurita, Kazunari

2018-01-01

Carbon-cluster-ion-implanted defects were investigated by high-resolution cross-sectional transmission electron microscopy toward achieving high-performance CMOS image sensors. We revealed that implantation damage formation in the silicon wafer bulk significantly differs between carbon-cluster and monomer ions after implantation. After epitaxial growth, small and large defects were observed in the implanted region of carbon clusters. The electron diffraction pattern of both small and large defects exhibits that from bulk crystalline silicon in the implanted region. On the one hand, we assumed that the silicon carbide structure was not formed in the implanted region, and small defects formed because of the complex of carbon and interstitial silicon. On the other hand, large defects were hypothesized to originate from the recrystallization of the amorphous layer formed by high-dose carbon-cluster implantation. These defects are considered to contribute to the powerful gettering capability required for high-performance CMOS image sensors.

Using cluster analysis to organize and explore regional GPS velocities

USGS Publications Warehouse

Simpson, Robert W.; Thatcher, Wayne; Savage, James C.

2012-01-01

Cluster analysis offers a simple visual exploratory tool for the initial investigation of regional Global Positioning System (GPS) velocity observations, which are providing increasingly precise mappings of actively deforming continental lithosphere. The deformation fields from dense regional GPS networks can often be concisely described in terms of relatively coherent blocks bounded by active faults, although the choice of blocks, their number and size, can be subjective and is often guided by the distribution of known faults. To illustrate our method, we apply cluster analysis to GPS velocities from the San Francisco Bay Region, California, to search for spatially coherent patterns of deformation, including evidence of block-like behavior. The clustering process identifies four robust groupings of velocities that we identify with four crustal blocks. Although the analysis uses no prior geologic information other than the GPS velocities, the cluster/block boundaries track three major faults, both locked and creeping.

Effects of landscape features on population genetic variation of a tropical stream fish, Stone lapping minnow, Garra cambodgiensis, in the upper Nan River drainage basin, northern Thailand.

PubMed

Jaisuk, Chaowalee; Senanan, Wansuk

2018-01-01

Spatial genetic variation of river-dwelling freshwater fishes is typically affected by the historical and contemporary river landscape as well as life-history traits. Tropical river and stream landscapes have endured extended geological change, shaping the existing pattern of genetic diversity, but were not directly affected by glaciation. Thus, spatial genetic variation of tropical fish populations should look very different from the pattern observed in temperate fish populations. These data are becoming important for designing appropriate management and conservation plans, as these aquatic systems are undergoing intense development and exploitation. This study evaluated the effects of landscape features on population genetic diversity of Garra cambodgiensis, a stream cyprinid , in eight tributary streams in the upper Nan River drainage basin ( n  = 30-100 individuals/location), Nan Province, Thailand. These populations are under intense fishing pressure from local communities. Based on 11 microsatellite loci, we detected moderate genetic diversity within eight population samples (average number of alleles per locus = 10.99 ± 3.00; allelic richness = 10.12 ± 2.44). Allelic richness within samples and stream order of the sampling location were negatively correlated ( P  < 0.05). We did not detect recent bottleneck events in these populations, but we did detect genetic divergence among populations (Global F ST = 0.022, P  < 0.01). The Bayesian clustering algorithms (TESS and STRUCTURE) suggested that four to five genetic clusters roughly coincide with sub-basins: (1) headwater streams/main stem of the Nan River, (2) a middle tributary, (3) a southeastern tributary and (4) a southwestern tributary. We observed positive correlation between geographic distance and linearized F ST ( P  < 0.05), and the genetic differentiation pattern can be moderately explained by the contemporary stream network (STREAMTREE analysis, R 2 = 0.75). The MEMGENE analysis suggested genetic division between northern (genetic clusters 1 and 2) and southern (clusters 3 and 4) sub-basins. We observed a high degree of genetic admixture in each location, highlighting the importance of natural flooding patterns and possible genetic impacts of supplementary stocking. Insights obtained from this research advance our knowledge of the complexity of a tropical stream system, and guide current conservation and restoration efforts for this species in Thailand.

Information processing architecture of functionally defined clusters in the macaque cortex.

PubMed

Shen, Kelly; Bezgin, Gleb; Hutchison, R Matthew; Gati, Joseph S; Menon, Ravi S; Everling, Stefan; McIntosh, Anthony R

2012-11-28

Computational and empirical neuroimaging studies have suggested that the anatomical connections between brain regions primarily constrain their functional interactions. Given that the large-scale organization of functional networks is determined by the temporal relationships between brain regions, the structural limitations may extend to the global characteristics of functional networks. Here, we explored the extent to which the functional network community structure is determined by the underlying anatomical architecture. We directly compared macaque (Macaca fascicularis) functional connectivity (FC) assessed using spontaneous blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) to directed anatomical connectivity derived from macaque axonal tract tracing studies. Consistent with previous reports, FC increased with increasing strength of anatomical connection, and FC was also present between regions that had no direct anatomical connection. We observed moderate similarity between the FC of each region and its anatomical connectivity. Notably, anatomical connectivity patterns, as described by structural motifs, were different within and across functional modules: partitioning of the functional network was supported by dense bidirectional anatomical connections within clusters and unidirectional connections between clusters. Together, our data directly demonstrate that the FC patterns observed in resting-state BOLD-fMRI are dictated by the underlying neuroanatomical architecture. Importantly, we show how this architecture contributes to the global organizational principles of both functional specialization and integration.

Asymmetric Top Rotors in Superfluid Para-Hydrogen Nano-Clusters

NASA Astrophysics Data System (ADS)

Zeng, Tao; Li, Hui; Roy, Pierre-Nicholas

2012-06-01

We present the first simulation study of bosonic clusters doped with an asymmetric top molecule. A variation of the path-integral Monte Carlo method is developed to study a para-water (pH_2O) impurity in para-hydrogen (pH_2) clusters. The growth pattern of the doped clusters is similar in nature to that of the pure clusters. The pH_2O molecule appears to rotate freely in the cluster due to its large rotational constants and the lack of adiabatic following. The presence of pH_2O substantially quenches the superfluid response of pH_2 with respect to the space fixed frame. We also study the behaviour of a sulphur dioxide (32S16O_2) dopant in the pH_2 clusters. For such a heavy rotor, the adiabatic following of the pH_2 molecules is established and the superfluid renormalization of the rotational constants is observed. The rotational structure of the SO_2-p(H_2)_N clusters' ro-vibrational spectra is predicted. The connection between the superfluid response respect to the external boundary rotation and the dopant rotation is discussed.

The split in the ancient cold front in the Perseus cluster

NASA Astrophysics Data System (ADS)

Walker, Stephen A.; ZuHone, John; Fabian, Andy; Sanders, Jeremy

2018-04-01

Sloshing cold fronts in clusters, produced as the dense cluster core moves around in the cluster potential in response to in-falling subgroups, provide a powerful probe of the physics of the intracluster medium and the magnetic fields permeating it1,2. These sharp discontinuities in density and temperature rise gradually outwards with age in a characteristic spiral pattern, embedding into the intracluster medium a record of the minor merging activity of clusters: the further from the cluster centre a cold front is, the older it is. Recently, it was discovered that these cold fronts can survive out to extremely large radii in the Perseus cluster3. Here, we report on high-spatial-resolution Chandra observations of the large-scale cold front in Perseus. We find that rather than broadening through diffusion, the cold front remains extremely sharp (consistent with abrupt jumps in density) and instead is split into two sharp edges. These results show that magnetic draping can suppress diffusion for vast periods of time—around 5 Gyr—even as the cold front expands out to nearly half the cluster virial radius.

Sensory Processing Subtypes in Autism: Association with Adaptive Behavior

ERIC Educational Resources Information Center

Lane, Alison E.; Young, Robyn L.; Baker, Amy E. Z.; Angley, Manya T.

2010-01-01

Children with autism are frequently observed to experience difficulties in sensory processing. This study examined specific patterns of sensory processing in 54 children with autistic disorder and their association with adaptive behavior. Model-based cluster analysis revealed three distinct sensory processing subtypes in autism. These subtypes…

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

Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

PubMed

Resche-Rigon, Matthieu; White, Ian R

2018-06-01

In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

Principles of proportional recovery after stroke generalize to neglect and aphasia.

PubMed

Marchi, N A; Ptak, R; Di Pietro, M; Schnider, A; Guggisberg, A G

2017-08-01

Motor recovery after stroke can be characterized into two different patterns. A majority of patients recover about 70% of initial impairment, whereas some patients with severe initial deficits show little or no improvement. Here, we investigated whether recovery from visuospatial neglect and aphasia is also separated into two different groups and whether similar proportions of recovery can be expected for the two cognitive functions. We assessed 35 patients with neglect and 14 patients with aphasia at 3 weeks and 3 months after stroke using standardized tests. Recovery patterns were classified with hierarchical clustering and the proportion of recovery was estimated from initial impairment using a linear regression analysis. Patients were reliably clustered into two different groups. For patients in the first cluster (n = 40), recovery followed a linear model where improvement was proportional to initial impairment and achieved 71% of maximal possible recovery for both cognitive deficits. Patients in the second cluster (n = 9) exhibited poor recovery (<25% of initial impairment). Our findings indicate that improvement from neglect or aphasia after stroke shows the same dichotomy and proportionality as observed in motor recovery. This is suggestive of common underlying principles of plasticity, which apply to motor and cognitive functions. © 2017 EAN.

Spatiotemporal patterns of severe fever with thrombocytopenia syndrome in China, 2011-2016.

PubMed

Sun, Jimin; Lu, Liang; Wu, Haixia; Yang, Jun; Liu, Keke; Liu, Qiyong

2018-05-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and the number of SFTS cases have increased year by year in China. However, spatiotemporal patterns and trends of SFTS are less clear up to date. In order to explore spatiotemporal patterns and predict SFTS incidences, we analyzed temporal trends of SFTS using autoregressive integrated moving average (ARIMA) model, spatial patterns, and spatiotemporal clusters of SFTS cases at the county level based on SFTS data in China during 2011-2016. We determined the optimal time series model was ARIMA (2, 0, 1) × (0, 0, 1) 12 which fitted the SFTS cases reasonably well during the training process and forecast process. In the spatial clustering analysis, the global autocorrelation suggested that SFTS cases were not of random distribution. Local spatial autocorrelation analysis of SFTS identified foci mainly concentrated in Hubei Province, Henan Province, Anhui Province, Shandong Province, Liaoning Province, and Zhejiang Province. A most likely cluster including 21 counties in Henan Province and Hubei Province was observed in the central region of China from April 2015 to August 2016. Our results will provide a sound evidence base for future prevention and control programs of SFTS such as allocation of the health resources, surveillance in high-risk regions, health education, improvement of diagnosis and so on. Copyright © 2018 Elsevier GmbH. All rights reserved.

Contemporary and historical evolutionary processes interact to shape patterns of within-lake phenotypic divergences in polyphenic pumpkinseed sunfish, Lepomis gibbosus.

PubMed

Weese, Dylan J; Ferguson, Moira M; Robinson, Beren W

2012-03-01

Historical and contemporary evolutionary processes can both contribute to patterns of phenotypic variation among populations of a species. Recent studies are revealing how interactions between historical and contemporary processes better explain observed patterns of phenotypic divergence than either process alone. Here, we investigate the roles of evolutionary history and adaptation to current environmental conditions in structuring phenotypic variation among polyphenic populations of sunfish inhabiting 12 postglacial lakes in eastern North America. The pumpkinseed sunfish polyphenism includes sympatric ecomorphs specialized for littoral or pelagic lake habitats. First, we use population genetic methods to test the evolutionary independence of within-lake phenotypic divergences of ecomorphs and to describe patterns of genetic structure among lake populations that clustered into three geographical groupings. We then used multivariate analysis of covariance (MANCOVA) to partition body shape variation (quantified with geometric morphometrics) among the effects of evolutionary history (reflecting phenotypic variation among genetic clusters), the shared phenotypic response of all populations to alternate habitats within lakes (reflecting adaptation to contemporary conditions), and unique phenotypic responses to habitats within lakes nested within genetic clusters. All effects had a significant influence on body form, but the effects of history and the interaction between history and contemporary habitat were larger than contemporary processes in structuring phenotypic variation. This highlights how divergence can be better understood against a known backdrop of evolutionary history.

Porosity and Variations in Microgravity Aerogel Nano-Structures. 2; New Laser Speckle Characterization Methods

NASA Technical Reports Server (NTRS)

Hunt, A. J.; Ayers, M. R.; Sibille, L.; Smith, D. D.

2001-01-01

The transition from sol to gel is a process that is critical to the properties of engineered nanomaterials, but one with few available techniques for observing the dynamic processes occurring during the evolution of the gel network. Specifically, the observation of various cluster aggregation models, such as diffusion-limited and reaction-limited cluster growth can be quite difficult. This can be rather important as the actual aggregation model can dramatically influence the mechanical properties of gels, and is significantly affected by the presence of convective flows, or their absence in microgravity. We have developed two new non-intrusive optical methods for observing the aggregation processes within gels in real time. These make use of the dynamic behavior of laser speckle patterns produced when an intense laser source is passed through a gelling sol. The first method is a simplified time-correlation measurement, where the speckle pattern is observed using a CCD camera and information on the movement of the scattering objects is readily apparent. This approach is extremely sensitive to minute variations in the flow field as the observed speckle pattern is a diffraction-based image, and is therefore sensitive to motions within the sol on the order of the wavelength of the probing light. Additionally, this method has proven useful in determining a precise time for the gel-point, an event often difficult to measure. Monitoring the evolution of contrast within the speckle field is another method that has proven useful for studying aeration. In this case, speckle contrast is dependent upon the size (correlation length) and number of scattering centers, increasing with increasing size, and decreasing with increasing numbers. The dynamic behavior of cluster growth in gels causes both of these to change simultaneously with time, the exact rate of which is determined by the specific aggregation model involved. Actual growth processes can now be observed, and the effects of varying gravity fields on the growth processes qualitatively described. Results on preliminary ground-based measurements have been obtained.

Patterns of adjustment among siblings exposed to intimate partner violence.

PubMed

Piotrowski, Caroline C

2011-02-01

This research explored and compared patterns of adjustment in siblings exposed to intimate partner violence. The quality of family relationships were investigated as potential mechanisms that accounted for heterogeneity in these patterns. Participants included 47 sibling pairs and their mothers recruited from the community. Mothers and children reported on child adjustment measures and the quality of family relationships. Five cluster patterns were identified for both younger and older siblings, replicating three identified in previous research: primarily internalizing symptoms, a combination of internalizing and externalizing symptoms, and an asymptomatic cluster. There was little overlap in cluster membership within families; most siblings differed in terms of their pattern of adjustment. The quality of family relationships varied significantly across clusters. Overall, asymptomatic siblings reported the most positive family relationships. Maternal warmth differed across clusters for both older and younger siblings, while maternal hostility varied across clusters for older but not younger siblings. The quality of sibling relationships also differed across clusters for older but not younger siblings. These findings underscore the importance of examining differential sibling experiences within violent families, and demonstrate the significance of family relationships as a mediating mechanism influencing heterogeneous child adjustment. PsycINFO Database Record (c) 2011 APA, all rights reserved.

Multimorbidity Patterns in Older Adults: An Approach to the Complex Interrelationships Among Chronic Diseases.

PubMed

Mino-León, Dolores; Reyes-Morales, Hortensia; Doubova, Svetlana V; Pérez-Cuevas, Ricardo; Giraldo-Rodríguez, Liliana; Agudelo-Botero, Marcela

2017-01-01

There is a growing need for evidence based answers to multimorbidity, especially in primary care settings. The aim was estimate the prevalence and patterns of multimorbidity in a Mexican population of public health institution users ≥60 years old. Observational and multicenter study was carried out in four family medicine units in Mexico City; included older men and women who attended at least one consultation with their family doctor during 2013. The most common diseases were grouped into 11 domains. The observed and expected rates, as well as the prevalence ratios, were calculated for the pairs of the more common domains. Logistic regression models were developed to estimate the magnitude of the association. Cluster and principal components analyses were performed to identify multimorbidity patterns. Half of all of the patients who were ≥60 years old and treated by a family doctor had multimorbidity. The most common disease domains were hypertensive and endocrine diseases. The highest prevalence of multimorbidity concerned the renal domain. The domain pairs with the strongest associations were endocrine + renal and hypertension + cardiac. The cluster and principal components analyses revealed five consistent patterns of multimorbidity. The domains grouped into five patterns could establish the framework for developing treatment guides, deepen the knowledge of multimorbidity, develop strategies to prevent it, decrease its burden, and align health services to the care needs that doctors face in daily practice. Copyright © 2017 IMSS. Published by Elsevier Inc. All rights reserved.

TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.

PubMed

Jung, Inuk; Jo, Kyuri; Kang, Hyejin; Ahn, Hongryul; Yu, Youngjae; Kim, Sun

2017-12-01

Identifying biologically meaningful gene expression patterns from time series gene expression data is important to understand the underlying biological mechanisms. To identify significantly perturbed gene sets between different phenotypes, analysis of time series transcriptome data requires consideration of time and sample dimensions. Thus, the analysis of such time series data seeks to search gene sets that exhibit similar or different expression patterns between two or more sample conditions, constituting the three-dimensional data, i.e. gene-time-condition. Computational complexity for analyzing such data is very high, compared to the already difficult NP-hard two dimensional biclustering algorithms. Because of this challenge, traditional time series clustering algorithms are designed to capture co-expressed genes with similar expression pattern in two sample conditions. We present a triclustering algorithm, TimesVector, specifically designed for clustering three-dimensional time series data to capture distinctively similar or different gene expression patterns between two or more sample conditions. TimesVector identifies clusters with distinctive expression patterns in three steps: (i) dimension reduction and clustering of time-condition concatenated vectors, (ii) post-processing clusters for detecting similar and distinct expression patterns and (iii) rescuing genes from unclassified clusters. Using four sets of time series gene expression data, generated by both microarray and high throughput sequencing platforms, we demonstrated that TimesVector successfully detected biologically meaningful clusters of high quality. TimesVector improved the clustering quality compared to existing triclustering tools and only TimesVector detected clusters with differential expression patterns across conditions successfully. The TimesVector software is available at http://biohealth.snu.ac.kr/software/TimesVector/. sunkim.bioinfo@snu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Fragmentation pathways of tungsten hexacarbonyl clusters upon electron ionization.

PubMed

Neustetter, M; Jabbour Al Maalouf, E; Limão-Vieira, P; Denifl, S

2016-08-07

Electron ionization of neat tungsten hexacarbonyl (W(CO)6) clusters has been investigated in a crossed electron-molecular beam experiment coupled with a mass spectrometer system. The molecule is used for nanofabrication processes through electron beam induced deposition and ion beam induced deposition techniques. Positive ion mass spectra of W(CO)6 clusters formed by electron ionization at 70 eV contain the ion series of the type W(CO)n (+) (0 ≤ n ≤ 6) and W2(CO)n (+) (0 ≤ n ≤ 12). In addition, a series of peaks are observed and have been assigned to WC(CO)n (+) (0 ≤ n ≤ 3) and W2C(CO)n (+) (0 ≤ n ≤ 10). A distinct change of relative fragment ion intensity can be observed for clusters compared to the single molecule. The characteristic fragmentation pattern obtained in the mass spectra can be explained by a sequential decay of the ionized organometallic, which is also supported by the study of the clusters when embedded in helium nanodroplets. In addition, appearance energies for the dissociative ionization channels for singly charged ions have been estimated from experimental ion efficiency curves.

Distinct collective states due to trade-off between attractive and repulsive couplings

NASA Astrophysics Data System (ADS)

Sathiyadevi, K.; Chandrasekar, V. K.; Senthilkumar, D. V.; Lakshmanan, M.

2018-03-01

We investigate the effect of repulsive coupling together with an attractive coupling in a network of nonlocally coupled oscillators. To understand the complex interaction between these two couplings we introduce a control parameter in the repulsive coupling which plays a crucial role in inducing distinct complex collective patterns. In particular, we show the emergence of various cluster chimera death states through a dynamically distinct transition route, namely the oscillatory cluster state and coherent oscillation death state as a function of the repulsive coupling in the presence of the attractive coupling. In the oscillatory cluster state, the oscillators in the network are grouped into two distinct dynamical states of homogeneous and inhomogeneous oscillatory states. Further, the network of coupled oscillators follow the same transition route in the entire coupling range. Depending upon distinct coupling ranges, the system displays different number of clusters in the death state and oscillatory state. We also observe that the number of coherent domains in the oscillatory cluster state exponentially decreases with increase in coupling range and obeys a power-law decay. Additionally, we show analytical stability for observed solitary state, synchronized state, and incoherent oscillation death state.

Spatial Patterns of Plasmodium falciparum Clinical Incidence, Asymptomatic Parasite Carriage and Anopheles Density in Two Villages in Mali

PubMed Central

Sissoko, Mahamadou S.; van den Hoogen, Lotus L.; Samake, Yacouba; Tapily, Amadou; Diarra, Adama Z.; Coulibaly, Maimouna; Bouare, Madama; Gaudart, Jean; Knight, Philip; Sauerwein, Robert W.; Takken, Willem; Bousema, Teun; Doumbo, Ogobara K.

2015-01-01

Heterogeneity in malaria exposure is most readily recognized in areas with low-transmission patterns. By comparison, little research has been done on spatial patterns in malaria exposure in high-endemic settings. We determined the spatial clustering of clinical malaria incidence, asymptomatic parasite carriage, and Anopheles density in two villages in Mali exposed to low- and mesoendemic-malaria transmission. In the two study areas that were < 1 km2 in size, we observed evidence for spatial clustering of Anopheles densities or malaria parasite carriage during the dry season. Anopheles density and malaria prevalence appeared associated in some of our detected hotspots. However, many households with high parasite prevalence or high Anopheles densities were located outside the identified hotspots. Our findings indicate that within small villages exposed to low- or mesoendemic-malaria transmission, spatial patterns in mosquito densities and parasite carriage are best detected in the dry season. Considering the high prevalence of parasite carriage outside detected hotspots, the suitability of the area for targeting control efforts to households or areas of more intense malaria transmission may be limited. PMID:26324728

Size dependent fragmentation of argon clusters in the soft x-ray ionization regime

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

Gisselbrecht, Mathieu; Lindgren, Andreas; Burmeister, Florian

Photofragmentation of argon clusters of average size ranging from 10 up to 1000 atoms is studied using soft x-ray radiation below the 2p threshold and multicoincidence mass spectroscopy technique. For small clusters (=10), ionization induces fast fragmentation with neutral emission imparting a large amount of energy. While the primary dissociation takes place on a picosecond time scale, the fragments undergo slow degradation in the spectrometer on a microsecond time scale. For larger clusters ({>=}100) we believe that we observe the fragmentation pattern of multiply charged species on a time-scale which lasts a few hundred nanoseconds. The reason for these slowermore » processes is the large number of neutral atoms which act as an efficient cooling bath where the excess energy ('heat') dissipates among all degrees of freedom. Further degradation of the photoionic cluster in spectrometer then takes place on the microsecond time scale, similar to small clusters.« less

Photochemical cleavage of metal--carbon nanocrystals and their reconstruction into met--cars clusters

NASA Astrophysics Data System (ADS)

Pilgrim, J. S.; Duncan, M. A.

1994-10-01

Titanium and zirconium metal--carbon clusters are produced by laser vaporization in a pulsed nozzle source and detected with time-of-flight mass spectrometry. In addition to the now-familiar "met-cars" stoichiometry (M8C12), larger magic number clusters are produced with near 1:1 metal--carbon ratios. The special stoichiometries observed correspond to face-centered cubic crystal fragments, with a strong preference for fragments with symmetrical x,y,z dimensions. Mass-selected photodissociation experiments are used to investigate the structural patterns and stabilities of these systems. Photodissociation of the larger "nanocrystal" clusters leads to cleavage along crystal planes, producing smaller crystals also having highly symmetric dimensions. Photoexcitation of all these crystallites, in particular the 3 × 3 × 3 species, also leads to surface reconstruction, forming the M8C12 met-cars cluster and/or the M8C13 cluster, the latter of which is assigned to a met--cars cage with an endohedral carbon atom.

Pattern formation in a model for mountain pine beetle dispersal: linking model predictions to data.

PubMed

Strohm, S; Tyson, R C; Powell, J A

2013-10-01

Pattern formation occurs in a wide range of biological systems. This pattern formation can occur in mathematical models because of diffusion-driven instability or due to the interaction between reaction, diffusion, and chemotaxis. In this paper, we investigate the spatial pattern formation of attack clusters in a system for Mountain Pine Beetle. The pattern formation (aggregation) of the Mountain Pine Beetle in order to attack susceptible trees is crucial for their survival and reproduction. We use a reaction-diffusion equation with chemotaxis to model the interaction between Mountain Pine Beetle, Mountain Pine Beetle pheromones, and susceptible trees. Mathematical analysis is utilized to discover the spacing in-between beetle attacks on the susceptible landscape. The model predictions are verified by analysing aerial detection survey data of Mountain Pine Beetle Attack from the Sawtooth National Recreation Area. We find that the distance between Mountain Pine Beetle attack clusters predicted by our model closely corresponds to the observed attack data in the Sawtooth National Recreation Area. These results clarify the spatial mechanisms controlling the transition from incipient to epidemic populations and may lead to control measures which protect forests from Mountain Pine Beetle outbreak.

Observations on Substance Abuse Theory.

ERIC Educational Resources Information Center

Shaffer, Howard J.

1986-01-01

Applies a philosophy of science perspective to substance abuse theory to clarify these theories in general and peer cluster theory in particular. Examines the natural history of an illicit drug from a macroscopic level of analysis to illuminate some of the social-psychological factors that influence drug use and abuse patterns. (Author/KS)

Fluorine Variations in the Globular Cluster NGC 6656 (M22): Implications for Internal Enrichment Timescales

NASA Astrophysics Data System (ADS)

D'Orazi, Valentina; Lucatello, Sara; Lugaro, Maria; Gratton, Raffaele G.; Angelou, George; Bragaglia, Angela; Carretta, Eugenio; Alves-Brito, Alan; Ivans, Inese I.; Masseron, Thomas; Mucciarelli, Alessio

2013-01-01

Observed chemical (anti)correlations in proton-capture elements among globular cluster stars are presently recognized as the signature of self-enrichment from now extinct, previous generations of stars. This defines the multiple population scenario. Since fluorine is also affected by proton captures, determining its abundance in globular clusters provides new and complementary clues regarding the nature of these previous generations and supplies strong observational constraints to the chemical enrichment timescales. In this paper, we present our results on near-infrared CRIRES spectroscopic observations of six cool giant stars in NGC 6656 (M22): the main objective is to derive the F content and its internal variation in this peculiar cluster, which exhibits significant changes in both light- and heavy-element abundances. Across our sample, we detected F variations beyond the measurement uncertainties and found that the F abundances are positively correlated with O and anticorrelated with Na, as expected according to the multiple population framework. Furthermore, our observations reveal an increase in the F content between the two different sub-groups, s-process rich and s-process poor, hosted within M22. The comparison with theoretical models suggests that asymptotic giant stars with masses between 4 and 5 M ⊙ are responsible for the observed chemical pattern, confirming evidence from previous works: the difference in age between the two sub-components in M22 must be not larger than a few hundred Myr. Based on observations taken with ESO telescopes under program 087.0319(A).

Clustering of multiple energy balance related behaviors is associated with body fat composition indicators in adolescents: Results from the HELENA and ELANA studies.

PubMed

Moreira, Naiara Ferraz; da Veiga, Gloria Valeria; Santaliestra-Pasías, Alba María; Androutsos, Odysseas; Cuenca-García, Magdalena; de Oliveira, Alessandra Silva Dias; Pereira, Rosangela Alves; de Moraes, Anelise Bezerra de Vasconcelos; Van den Bussche, Karen; Censi, Laura; González-Gross, Marcela; Cañada, David; Gottrand, Frederic; Kafatos, Anthony; Marcos, Ascensión; Widhalm, Kurt; Mólnar, Dénes; Moreno, Luis Alberto

2018-01-01

The objective of this study was to identify clustering patterns of four energy balance-related behaviors (EBRB): television (TV) watching, moderate and vigorous physical activity (MVPA), consumption of fruits and vegetables (F&V), and consumption of sugar-sweetened beverages (SSB), among European and Brazilian adolescents. EBRB associations with different body fat composition indicators were then evaluated. Participants included adolescents from eight European countries in the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescents) study (n = 2,057, 53.8% female; age: 12.5-17.5 years) and from the metropolitan region of Rio de Janeiro/Brazil in the ELANA study (the Adolescent Nutritional Assessment Longitudinal Study) (n = 968, 53.2% female; age: 13.5-19 years). EBRB data allowed for sex- and study-specific clusters. Associations were estimated by ANOVA and odds ratios. Five clustering patterns were identified. Four similar clusters were identified for each sex and study. Among boys, different cluster identified was characterized by high F&V consumption in the HELENA study and high TV watching and high MVPA time in the ELANA study. Among girls, the different clusters identified was characterized by high F&V consumption in both studies and, additionally, high SSB consumption in the ELANA study. Regression analysis showed that clusters characterized by high SSB consumption in European boys; high TV watching, and high TV watching plus high MVPA in Brazilian boys; and high MVPA, and high SSB and F&V consumption in Brazilian girls, were positively associated with different body fat composition indicators. Common clusters were observed in adolescents from Europe and Brazil, however, no cluster was identified as being completely healthy or unhealthy. Each cluster seems to impact on body composition indicators, depending on the group. Public health actions should aim to promote adequate practices of EBRB. Copyright © 2017. Published by Elsevier Ltd.

What Do the Hitomi Observations Tell Us About the Turbulent Velocities in the Perseus Cluster? Probing the Velocity Field with Mock Observations

NASA Astrophysics Data System (ADS)

ZuHone, J. A.; Miller, E. D.; Bulbul, E.; Zhuravleva, I.

2018-02-01

Hitomi made the first direct measurements of galaxy cluster gas motions in the Perseus cluster, which implied that its core is fairly “quiescent,” with velocities less than ∼200 km s‑1, despite the presence of an active galactic nucleus and sloshing cold fronts. Building on previous work, we use synthetic Hitomi/X-ray Spectrometer (SXS) observations of the hot plasma of a simulated cluster with sloshing gas motions and varying viscosity to analyze its velocity structure in a similar fashion. We find that sloshing motions can produce line shifts and widths similar to those measured by Hitomi. We find these measurements are unaffected by the value of the gas viscosity, since its effects are only manifested clearly on angular scales smaller than the SXS ∼1‧ PSF. The PSF biases the line shift of regions near the core as much as ∼40–50 km s‑1, so it is crucial to model this effect carefully. We also infer that if sloshing motions dominate the observed velocity gradient, Perseus must be observed from a line of sight that is somewhat inclined from the plane of these motions, but one that still allows the spiral pattern to be visible. Finally, we find that assuming isotropy of motions can underestimate the total velocity and kinetic energy of the core in our simulation by as much as ∼60%. However, the total kinetic energy in our simulated cluster core is still less than 10% of the thermal energy in the core, in agreement with the Hitomi observations.

TRMM-TMI Satellite Observed Soil Moisture and Vegetation Density (1998-2005) Show Strong Connection with El Nino in Eastern Australia

NASA Technical Reports Server (NTRS)

Liu, Yi; van Dijk, Albert I.J.M.; Owe, Manfred

2007-01-01

Spatiotemporal patterns in soil moisture and vegetation water content across mainland Australia were investigated from 1998 through 2005, using TRMMITMI passive microwave observations. The Empirical Orthogonal Function technique was used to extract dominant spatial and temporal patterns in retrieved estimates of moisture content for the top 1-cm of soil (theta) and vegetation moisture content (via optical depth tau). The dominant temporal theta and tau patterns were strongly correlated to El Nino/Southern Oscillation (ENSO) in spring (3 = 0.90), and to a progressively lesser extent autumn, summer and winter. The Indian Ocean Dipole (IOD) index also explained part of the variation in spring 8 and z. Cluster analysis suggested that the regions most affected by ENS0 are mainly located in eastern Australia. The results suggest that the drought conditions experienced in eastern Australia since 2000 an clearly expressed in these satellite observations have a strong connection with ENSO patterns.

Predawn plasma bubble cluster observed in Southeast Asia

NASA Astrophysics Data System (ADS)

Watthanasangmechai, Kornyanat; Yamamoto, Mamoru; Saito, Akinori; Tsunoda, Roland; Yokoyama, Tatsuhiro; Supnithi, Pornchai; Ishii, Mamoru; Yatini, Clara

2016-06-01

Predawn plasma bubble was detected as deep plasma depletion by GNU Radio Beacon Receiver (GRBR) network and in situ measurement onboard Defense Meteorological Satellite Program F15 (DMSPF15) satellite and was confirmed by sparse GPS network in Southeast Asia. In addition to the deep depletion, the GPS network revealed the coexisting submesoscale irregularities. A deep depletion is regarded as a primary bubble. Submesoscale irregularities are regarded as secondary bubbles. Primary bubble and secondary bubbles appeared together as a cluster with zonal wavelength of 50 km. An altitude of secondary bubbles happened to be lower than that of the primary bubble in the same cluster. The observed pattern of plasma bubble cluster is consistent with the simulation result of the recent high-resolution bubble (HIRB) model. This event is only a single event out of 76 satellite passes at nighttime during 3-25 March 2012 that significantly shows plasma depletion at plasma bubble wall. The inside structure of the primary bubble was clearly revealed from the in situ density data of DMSPF15 satellite and the ground-based GRBR total electron content.

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

Jian, Tian; Lopez, Gary V.; Wang, Lai-Sheng, E-mail: Lai-Sheng-Wang@brown.edu

We report the observation of a manganese-centered tubular boron cluster (MnB{sub 16}{sup −}), which is characterized by photoelectron spectroscopy and ab initio calculations. The relatively simple pattern of the photoelectron spectrum indicates the cluster to be highly symmetric. Ab initio calculations show that MnB{sub 16}{sup −} has a Mn-centered tubular structure with C{sub 4v} symmetry due to first-order Jahn-Teller effect, while neutral MnB{sub 16} reduces to C{sub 2v} symmetry due to second-order Jahn-Teller effect. In MnB{sub 16}{sup −}, two unpaired electrons are observed, one on the Mn 3d{sub z{sup 2}} orbital and another on the B{sub 16} tube, making itmore » an unusual biradical. Strong covalent bonding is found between the Mn 3d orbitals and the B{sub 16} tube, which helps to stabilize the tubular structure. The current result suggests that there may exist a whole class of metal-stabilized tubular boron clusters. These metal-doped boron clusters provide a new bonding modality for transition metals, as well as a new avenue to design boron-based nanomaterials.« less

High ozone levels in the northeast of Portugal: Analysis and characterization

NASA Astrophysics Data System (ADS)

Carvalho, A.; Monteiro, A.; Ribeiro, I.; Tchepel, O.; Miranda, A. I.; Borrego, C.; Saavedra, S.; Souto, J. A.; Casares, J. J.

2010-03-01

Each summer period extremely high ozone levels are registered at the rural background station of Lamas d'Olo, located in the Northeast of Portugal. In average, 30% of the total alert threshold registered in Portugal is detected at this site. The main purpose of this study is to characterize the atmospheric conditions that lead to the ozone-rich episodes at this site. Synoptic patterns anomalies and back trajectories cluster analysis were performed, for the period between 2004 and 2007, considering 76 days when ozone maximum hourly concentrations were above 200 μg m -3. The obtained atmospheric anomaly fields suggested that a positive temperature anomaly is visible above the Iberian Peninsula. A strong wind flow pattern from NE is observable in the North of Portugal and Galicia, in Spain. These two features may lead to an enhancement of the photochemical production and to the transport of pollutants from Spain to Portugal. In addition, the 3D mean back trajectories associated to the ozone episode days were analysed. A clustering method has been applied to the obtained back trajectories. Four main clusters of ozone-rich episodes were identified, with different frequencies of occurrence: north-westerly flows (11%); north-easterly flows (45%), southern flow (4%) and westerly flows (40%). Both analyses highlight the NE flow as a dominant pattern over the North of Portugal during summer. The analysis of the ozone concentrations for each selected cluster indicates that this northeast circulation pattern, together with the southern flow, are responsible for the highest ozone peak episodes. This also suggests that long-range transport of atmospheric pollutants is the main contributor to the ozone levels registered at Lamas d'Olo. This is also highlighted by the correlation of the ozone time-series with the meteorological parameters analysed in the frequency domain.

Graduation of fertility schedules: an analysis of fertility patterns in London in the 1980s and an application to fertility forecasts.

PubMed

Congdon, P

1990-08-01

London's average total fertility rate (TFR) stood at 1.75. Using a cluster analysis to compare the 1985-1987 fertility patterns of different boroughs of London, demographers learned that 5 natural groupings occurred. 4 boroughs in a central London cluster have the distinction of having a low TFR (1.38) and late fertility (average age of 29.58 years). The researchers attributed these occurrences to the high levels of employment and career attachment and low rates of marriage among women in this cluster. 2 inner city boroughs constituted the smallest cluster and had the largest TFR (2.37), mainly due to high numbers of births to the ethnic minorities. The largest cluster consisted of 12 boroughs located mainly along the periphery with 2 centrally located boroughs (TFR, 1.79). Some of the upper class outer boroughs characterized another cluster with a TFR of 1.61. Another cluster made up of inner and outer boroughs in east and southeast London had a ample proportion of manual worker (TFR, 2.04). Social class most likely accounted for the contrast in TFRs between the 2 aformentioned clusters. Demographers observed that cyclical fluctuation of fertility occurred as opposed to secular trends. Due to these fluctuations, demographers used autoregressive moving average forecast models to time series of the fertility variables in London since 1952. They also applied structural time series models which included regression variables and the influence of cyclical and/or trend behavior. The results showed that large cohorts and the increase in female economic activity caused a delay in the modal age of births and a reduction in the number of births.

Patterns of long-term and short-term responses in adult patients with attention-deficit/hyperactivity disorder in a completer cohort of 12 weeks or more with atomoxetine.

PubMed

Sobanski, E; Leppämäki, S; Bushe, C; Berggren, L; Casillas, M; Deberdt, W

2015-11-01

Atomoxetine is a well-established pharmacotherapy for adult ADHD. Long-term studies show incremental reductions in symptoms over time. However, clinical experience suggests that patients differ in their response patterns. From 13 Eli Lilly-sponsored studies, we pooled and analyzed data for adults with ADHD who completed atomoxetine treatment at long-term (24 weeks; n=1443) and/or short-term (12 weeks; n=2830) time-points, and had CAARS-Inv:SV total and CGI-S data up to or after these time-points and at Week 0 (i.e. at baseline, when patients first received atomoxetine). The goal was to identify and describe distinct trajectories of response to atomoxetine using hierarchical clustering methods and linear mixed modelling. Based on the homogeneity of changes in CAARS-Inv:SV total scores, 5 response clusters were identified for patients who completed long-term (24 weeks) treatment with atomoxetine, and 4 clusters were identified for patients who completed short-term (12 weeks) treatment. Four of the 5 long-term clusters (comprising 95% of completer patients) showed positive trajectories: 2 faster responding clusters (L1 and L2), and 2 more gradually responding clusters (L3 and L4). Responses (i.e.≥30% reduction in CAARS-Inv:SV total score, and CGI-S score≤3) were observed at 8 and 24 weeks in 80% and 95% of completers in Cluster L1, versus 5% and 48% in Cluster L4. While many adults with ADHD responded relatively rapidly to atomoxetine, others responded more gradually without a clear plateau at 24 weeks. Longer-term treatment may be associated with greater numbers of responders. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Social influences on health-related behaviour clustering during adulthood in two British birth cohort studies.

PubMed

Mawditt, Claire; Sacker, Amanda; Britton, Annie; Kelly, Yvonne; Cable, Noriko

2018-05-01

Building upon evidence linking socio-economic position (SEP) in childhood and adulthood with health-related behaviours (HRB) in adulthood, we examined how pre-adolescent SEP predicted membership of three HRB clusters: "Risky", "Moderate Smokers" and "Mainstream" (the latter pattern consisting of more beneficial HRBs), that were detected in our previous work. Data were taken from two British cohorts (born in 1958 and 1970) in pre-adolescence (age 11 and 10, respectively) and adulthood (age 33 and 34). SEP constructs in pre-adolescence and adulthood were derived through Confirmatory Factor Analysis. Conceptualised paths from pre-adolescent SEP to HRB cluster membership via adult SEP in our path models were tested for statistical significance separately by gender and cohort. Adult SEP mediated the path between pre-adolescent SEP and adult HRB clusters. More disadvantaged SEP in pre-adolescence predicted more disadvantaged SEP in adulthood which was associated with membership of the "Risky" and "Moderate Smokers" clusters compared to the "Mainstream" cluster. For example, large positive indirect effects between pre-adolescent SEP and adult HRB via adult SEP were present (coefficient 1958 Women = 0.39; 1970 Women = 0.36, 1958 Men = 0.51; 1970 Men = 0.39; p < 0.01) when comparing "Risky" and "Mainstream" cluster membership. Amongst men we found a small significant direct association (p < 0.001) between pre-adolescent SEP and HRB cluster membership. Our findings suggest that associations between adult SEP and HRBs are not likely to be pre-determined by earlier social circumstances, providing optimism for interventions relevant to reducing social gradients in HRBs. Observing consistent findings across the cohorts implies the social patterning of adult lifestyles may persist across time. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Phytoplankton community in lake Ebony, Pantai Indah Kapuk, North Jakarta

NASA Astrophysics Data System (ADS)

Pratiwi, NTM; Ayu, IP; Hariyadi, S.; Mulyawati, D.; Iswantari, A.

2018-05-01

Lake Ebony is an ornamental lake in coastal area of North Jakarta, located at 6°6’18”S- 6°6’35”S and 106°44’39’Έ-106°44’56’Έ. Phytoplankton community in Lake Ebony lives in high organic materials received from domestic waste. A spatio-temporal observation at five sites was carried out to understand the spatial distribution of phytoplankton at each group of time of observation and the succession of phytoplankton. Spatial analysis was carried out to map the distribution pattern of plankton,using ArcGIS 10.1 with IDW (Inverse Distance Weighted) interpolation method. Spatial clustering was determined by Canberra Index. The succession of phytoplankton was shown by graph of Frontier succession models, SDI (rate of succession), and SIMI. There were two clustered groups of site. Based on graph of Frontier succession, phytoplankton in Lake Ebony was at Stage 2 and 3 with the rate of succession ranged from 0.008 to 0.003, and value of SIMI ranged from 0.68 to 0.97. There was different spatial distribution pattern of phytoplankton in three groups of observation time, with low rate of succession.

Zodiacal Exoplanets in Time: Searching for Young Stars in K2

NASA Astrophysics Data System (ADS)

Morris, Nathan; Mann, Andrew W.

2017-06-01

Nearby young, open clusters such as the Hyades, Pleiades, and Praesepe provide an important reference point for the properties of stellar systems in general. In each cluster, all stars are of the same known age. As such, observations of planetary systems around these stars can be used to gain insight into the early stages of planetary system formation. K2, the revived Kepler mission, has provided a vast number of light curves for young stars in the and elsewhere in the K2 field. We aim to compute rotational periods from sunspot patterns for all K2 target stars and use gyrochronometric relationships derived from cluster stars to determine their ages. From there, we will search for planets around young stars outside the clusters with the ultimate goal of shedding light on how planets and planetary systems evolve with time.

DENBRAN: A basic program for a significance test for multivariate normality of clusters from branching patterns in dendrograms

NASA Astrophysics Data System (ADS)

Sneath, P. H. A.

A BASIC program is presented for significance tests to determine whether a dendrogram is derived from clustering of points that belong to a single multivariate normal distribution. The significance tests are based on statistics of the Kolmogorov—Smirnov type, obtained by comparing the observed cumulative graph of branch levels with a graph for the hypothesis of multivariate normality. The program also permits testing whether the dendrogram could be from a cluster of lower dimensionality due to character correlations. The program makes provision for three similarity coefficients, (1) Euclidean distances, (2) squared Euclidean distances, and (3) Simple Matching Coefficients, and for five cluster methods (1) WPGMA, (2) UPGMA, (3) Single Linkage (or Minimum Spanning Trees), (4) Complete Linkage, and (5) Ward's Increase in Sums of Squares. The program is entitled DENBRAN.

Analysis of Rainfall and PM2.5 Data Using Clustered Trajectory Analysis for National Park Sites in the Western U.S.

NASA Astrophysics Data System (ADS)

Solorzano, N. N.; Hafner, W.; Jaffe, D.

2005-12-01

We calculated daily kinematic back-trajectories using the NOAA-HYSPLIT model to analyze 7 years of PM2.5 data from National Park sites in the Western U.S. (Glacier N.P., Mount Rainier N.P., Sequoia N.P., Rocky Mountain N.P. and Denali N.P.) The back-trajectories were clustered using a k-means clustering algorithm to segregate the trajectories into 6 main transport patterns. We calculated trajectory clusters for 1, 5 and 10 days to represent short, medium and long-range flow patterns. Some trajectory types and clusters show marked seasonality. Generally faster flow patterns are more prevalent in winter and slower/stagnant patterns are more prevalent in summer. In addition, we found significant inter-annual variability that may be important for explaining variations in rainfall and/or pollutant concentrations. The 5 and 10-day analyses revealed that, for the 4 non-Alaskan sites, trajectories from Asia tend to be less frequent in the summer, compared to the rest of the year. The clusters of different duration show very different predictive power for rainfall and PM2.5. We found that the 1-day clusters are a better predictor for precipitation and PM2.5 concentrations, as compared to the 5 and 10-day clusters. At each of the sites, there is at least one cluster with an average PM2.5 concentration that is different than the average for the site, indicating distinctive transport patterns. The same is true for 5 and 10-day clusters. Interestingly, only one site, Mount Rainier N.P., shows seasonal differences in PM2.5 concentrations between the clusters that differ from the average.

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.

Globular Cluster Contributions to the Galactic Halo

NASA Astrophysics Data System (ADS)

Martell, Sarah; Grebel, Eva; Lai, David

2010-08-01

The goal of this project is to confirm chemically that globular clusters are the source of as much as half the population of the Galactic halo. Using moderate-resolution spectroscopy from the SEGUE survey, we have identified a previously unknown population of halo field giants with distinctly strong CN features. CN variations are typically only observed in globular clusters, so these stars are interpreted as immigrants to the halo that originally formed in globular clusters. In one night of Keck/HIRES time, we will obtain high-quality, high- resolution spectra for five such stars, and determine abundances of O, Na, Mg, Al, alpha, iron-peak and neutron-capture elements. With this information we can state clearly whether these unusual CN-strong halo stars carry the full abundance pattern seen in CN-strong globular cluster stars, with depleted C, O, and Mg and enhanced N, Na, and Al. This type of coarse ``chemical tagging'' will allow a clearer division of the Galactic halo into contributions from globular clusters and from dwarf galaxies, and will place constraints on theoretical models of globular cluster formation and evolution.

Spatial patterns of the congenital heart disease prevalence among 0- to 14-year-old children in Sichuan Basin, P. R China, from 2004 to 2009

PubMed Central

2014-01-01

Background Congenital heart disease (CHD) is the most common type of major birth defects in Sichuan, the most populous province in China. The detailed etiology of CHD is unknown but some environmental factors are suspected as the cause of this disease. However, the geographical variations in CHD prevalence would be highly valuable in providing a clue on the role of the environment in CHD etiology. Here, we investigate the spatial patterns and geographic differences in CHD prevalence among 0- to 14-year-old children, discuss the possible environmental risk factors that might be associated with CHD prevalence in Sichuan Basin from 2004 to 2009. Methods The hierarchical Bayesian model was used to estimate CHD prevalence at the township level. Spatial autocorrelation statistics were performed, and a hot-spot analysis with different distance thresholds was used to identify the spatial pattern of CHD prevalence. Distribution and clustering maps were drawn using geographic information system tools. Results CHD prevalence was significantly clustered in Sichuan Basin in different spatial scale. Typical hot/cold clusters were identified, and possible CHD causes were discussed. The association between selected hypothetical environmental factors of maternal exposure and CHD prevalence was evaluated. Conclusions The largest hot-spot clustering phenomena and the CHD prevalence clustering trend among 0- to 14-year-old children in the study area showed a plausibly close similarity with those observed in the Tuojiang River Basin. The high ecological risk of heavy metal(Cd, As, and Pb)sediments in the middle and lower streams of the Tuojiang River watershed and ammonia–nitrogen pollution may have contribution to the high prevalence of CHD in this area. PMID:24924350

Parity among interpretation methods of MLEE patterns and disparity among clustering methods in epidemiological typing of Candida albicans.

PubMed

Boriollo, Marcelo Fabiano Gomes; Rosa, Edvaldo Antonio Ribeiro; Gonçalves, Reginaldo Bruno; Höfling, José Francisco

2006-03-01

The typing of C. albicans by MLEE (multilocus enzyme electrophoresis) is dependent on the interpretation of enzyme electrophoretic patterns, and the study of the epidemiological relationships of these yeasts can be conducted by cluster analysis. Therefore, the aims of the present study were to first determine the discriminatory power of genetic interpretation (deduction of the allelic composition of diploid organisms) and numerical interpretation (mere determination of the presence and absence of bands) of MLEE patterns, and then to determine the concordance (Pearson product-moment correlation coefficient) and similarity (Jaccard similarity coefficient) of the groups of strains generated by three cluster analysis models, and the discriminatory power of such models as well [model A: genetic interpretation, genetic distance matrix of Nei (d(ij)) and UPGMA dendrogram; model B: genetic interpretation, Dice similarity matrix (S(D1)) and UPGMA dendrogram; model C: numerical interpretation, Dice similarity matrix (S(D2)) and UPGMA dendrogram]. MLEE was found to be a powerful and reliable tool for the typing of C. albicans due to its high discriminatory power (>0.9). Discriminatory power indicated that numerical interpretation is a method capable of discriminating a greater number of strains (47 versus 43 subtypes), but also pointed to model B as a method capable of providing a greater number of groups, suggesting its use for the typing of C. albicans by MLEE and cluster analysis. Very good agreement was only observed between the elements of the matrices S(D1) and S(D2), but a large majority of the groups generated in the three UPGMA dendrograms showed similarity S(J) between 4.8% and 75%, suggesting disparities in the conclusions obtained by the cluster assays.

A cluster pattern algorithm for the analysis of multiparametric cell assays.

PubMed

Kaufman, Menachem; Bloch, David; Zurgil, Naomi; Shafran, Yana; Deutsch, Mordechai

2005-09-01

The issue of multiparametric analysis of complex single cell assays of both static and flow cytometry (SC and FC, respectively) has become common in recent years. In such assays, the analysis of changes, applying common statistical parameters and tests, often fails to detect significant differences between the investigated samples. The cluster pattern similarity (CPS) measure between two sets of gated clusters is based on computing the difference between their density distribution functions' set points. The CPS was applied for the discrimination between two observations in a four-dimensional parameter space. The similarity coefficient (r) ranges between 0 (perfect similarity) to 1 (dissimilar). Three CPS validation tests were carried out: on the same stock samples of fluorescent beads, yielding very low r's (0, 0.066); and on two cell models: mitogenic stimulation of peripheral blood mononuclear cells (PBMC), and apoptosis induction in Jurkat T cell line by H2O2. In both latter cases, r indicated similarity (r < 0.23) within the same group, and dissimilarity (r > 0.48) otherwise. This classification and algorithm approach offers a measure of similarity between samples. It relies on the multidimensional pattern of the sample parameters. The algorithm compensates for environmental drifts in this apparatus and assay; it also may be applied to more than four dimensions.

Characterization of anticancer agents by their growth inhibitory activity and relationships to mechanism of action and structure.

PubMed

Keskin, O; Bahar, I; Jernigan, R L; Beutler, J A; Shoemaker, R H; Sausville, E A; Covell, D G

2000-04-01

An analysis of the growth inhibitory potency of 122 anticancer agents available from the National Cancer Institute anticancer drug screen is presented. Methods of singular value decomposition (SVD) were applied to determine the matrix of distances between all compounds. These SVD-derived dissimilarity distances were used to cluster compounds that exhibit similar tumor growth inhibitory activity patterns against 60 human cancer cell lines. Cluster analysis divides the 122 standard agents into 25 statistically distinct groups. The first eight groups include structurally diverse compounds with reactive functionalities that act as DNA-damaging agents while the remaining 17 groups include compounds that inhibit nucleic acid biosynthesis and mitosis. Examination of the average activity patterns across the 60 tumor cell lines reveals unique 'fingerprints' associated with each group. A diverse set of structural features are observed for compounds within these groups, with frequent occurrences of strong within-group structural similarities. Clustering of cell types by their response to the 122 anticancer agents divides the 60 cell types into 21 groups. The strongest within-panel groupings were found for the renal, leukemia and ovarian cell panels. These results contribute to the basis for comparisons between log(GI(50)) screening patterns of the 122 anticancer agents and additional tested compounds.

Spatial pattern recognition of seismic events in South West Colombia

NASA Astrophysics Data System (ADS)

Benítez, Hernán D.; Flórez, Juan F.; Duque, Diana P.; Benavides, Alberto; Lucía Baquero, Olga; Quintero, Jiber

2013-09-01

Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

Allergen Sensitization Pattern by Sex: A Cluster Analysis in Korea.

PubMed

Ohn, Jungyoon; Paik, Seung Hwan; Doh, Eun Jin; Park, Hyun-Sun; Yoon, Hyun-Sun; Cho, Soyun

2017-12-01

Allergens tend to sensitize simultaneously. Etiology of this phenomenon has been suggested to be allergen cross-reactivity or concurrent exposure. However, little is known about specific allergen sensitization patterns. To investigate the allergen sensitization characteristics according to gender. Multiple allergen simultaneous test (MAST) is widely used as a screening tool for detecting allergen sensitization in dermatologic clinics. We retrospectively reviewed the medical records of patients with MAST results between 2008 and 2014 in our Department of Dermatology. A cluster analysis was performed to elucidate the allergen-specific immunoglobulin (Ig)E cluster pattern. The results of MAST (39 allergen-specific IgEs) from 4,360 cases were analyzed. By cluster analysis, 39items were grouped into 8 clusters. Each cluster had characteristic features. When compared with female, the male group tended to be sensitized more frequently to all tested allergens, except for fungus allergens cluster. The cluster and comparative analysis results demonstrate that the allergen sensitization is clustered, manifesting allergen similarity or co-exposure. Only the fungus cluster allergens tend to sensitize female group more frequently than male group.

Dietary patterns, insulin sensitivity and inflammation in older adults

PubMed Central

Anderson, Amy L.; Harris, Tamara B.; Tylavsky, Frances A.; Perry, Sara E.; Houston, Denise K.; Lee, Jung Sun; Kanaya, Alka M.; Sahyoun, Nadine R.

2011-01-01

Background/Objectives Several studies have linked dietary patterns to insulin sensitivity and systemic inflammation, which affect risk of multiple chronic diseases. The purpose of this study was to investigate the dietary patterns of a cohort of older adults, and examine relationships of dietary patterns with markers of insulin sensitivity and systemic inflammation. Subjects/Methods The Health, Aging and Body Composition (Health ABC) Study is a prospective cohort study of 3075 older adults. In Health ABC, multiple indicators of glucose metabolism and systemic inflammation were assessed. Food intake was estimated with a modified Block food frequency questionnaire (FFQ). In this study, dietary patterns of 1751 participants with complete data were derived by cluster analysis. Results Six clusters were identified, including a ‘Healthy foods’ cluster, characterized by higher intake of lowfat dairy products, fruit, whole grains, poultry, fish and vegetables. In the main analysis, the ‘Healthy foods’ cluster had significantly lower fasting insulin and HOMA-IR than the ‘Breakfast cereal’ and ‘High-fat dairy products’ clusters, and lower fasting glucose than the ‘High-fat dairy products’ cluster (P ≤ 0.05). No differences were found in 2-hour glucose. With respect to inflammation, the ‘Healthy foods’ cluster had lower IL-6 than the ‘Sweets and desserts’ and ‘High-fat dairy products’ clusters, and no differences were seen in CRP or TNF-α. Conclusions A dietary pattern high in lowfat dairy products, fruit, whole grains, poultry, fish and vegetables may be associated with greater insulin sensitivity and lower systemic inflammation in older adults. PMID:21915138

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.

Properties of Ammonium Ion–Water Clusters: Analyses of Structure Evolution, Noncovalent Interactions, and Temperature and Humidity Effects

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

Pei, Shi-Tu; Jiang, Shuai; Liu, Yi-Rong

2015-03-03

Although ammonium ion–water clusters are abundant in the biosphere, some information regarding these clusters, such as their growth route, the influence of temperature and humidity, and the concentrations of various hydrated clusters, is lacking. In this study, theoretical calculations are performed on ammonium ion–water clusters. These theoretical calculations are focused on determining the following characteristics: (1) the pattern of cluster growth; (2) the percentages of clusters of the same size at different temperatures and humidities; (3) the distributions of different isomers for the same size clusters at different temperatures; (4) the relative strengths of the noncovalent interactions for clusters ofmore » different sizes. The results suggest that the dipole moment may be very significant for the ammonium ion–water system, and some new stable isomers were found. The nucleation of ammonium ions and water molecules is favorable at low temperatures; thus, the clusters observed at high altitudes might not be present at low altitudes. High humidity can contribute to the formation of large ammonium ion–water clusters, whereas the formation of small clusters may be favorable under low-humidity conditions. The potential energy surfaces (PES) of these different sized clusters are complicated and differ according to the distribution of isomers at different temperatures. Some similar structures are observed between NH4+(H2O)n and M(H2O)n (where M represents an alkali metal ion or water molecule); when n = 8, the clusters begin to form the closed-cage geometry. As the cluster size increases, these interactions become progressively weaker. The successive binding energy at the DF-MP2-F12/VDZ-F12 level is better than that at the PW91PW91/6-311++G(3df, 3pd) level and is consistent with the experimentally determined values.« less

Properties of ammonium ion-water clusters: analyses of structure evolution, noncovalent interactions, and temperature and humidity effects.

PubMed

Pei, Shi-Tu; Jiang, Shuai; Liu, Yi-Rong; Huang, Teng; Xu, Kang-Ming; Wen, Hui; Zhu, Yu-Peng; Huang, Wei

2015-03-26

Although ammonium ion-water clusters are abundant in the biosphere, some information regarding these clusters, such as their growth route, the influence of temperature and humidity, and the concentrations of various hydrated clusters, is lacking. In this study, theoretical calculations are performed on ammonium ion-water clusters. These theoretical calculations are focused on determining the following characteristics: (1) the pattern of cluster growth; (2) the percentages of clusters of the same size at different temperatures and humidities; (3) the distributions of different isomers for the same size clusters at different temperatures; (4) the relative strengths of the noncovalent interactions for clusters of different sizes. The results suggest that the dipole moment may be very significant for the ammonium ion-water system, and some new stable isomers were found. The nucleation of ammonium ions and water molecules is favorable at low temperatures; thus, the clusters observed at high altitudes might not be present at low altitudes. High humidity can contribute to the formation of large ammonium ion-water clusters, whereas the formation of small clusters may be favorable under low-humidity conditions. The potential energy surfaces (PES) of these different sized clusters are complicated and differ according to the distribution of isomers at different temperatures. Some similar structures are observed between NH4(+)(H2O)n and M(H2O)n (where M represents an alkali metal ion or water molecule); when n = 8, the clusters begin to form the closed-cage geometry. As the cluster size increases, these interactions become progressively weaker. The successive binding energy at the DF-MP2-F12/VDZ-F12 level is better than that at the PW91PW91/6-311++G(3df, 3pd) level and is consistent with the experimentally determined values.

Post-decomposition optimizations using pattern matching and rule-based clustering for multi-patterning technology

NASA Astrophysics Data System (ADS)

Wang, Lynn T.-N.; Madhavan, Sriram

2018-03-01

A pattern matching and rule-based polygon clustering methodology with DFM scoring is proposed to detect decomposition-induced manufacturability detractors and fix the layout designs prior to manufacturing. A pattern matcher scans the layout for pre-characterized patterns from a library. If a pattern were detected, rule-based clustering identifies the neighboring polygons that interact with those captured by the pattern. Then, DFM scores are computed for the possible layout fixes: the fix with the best score is applied. The proposed methodology was applied to two 20nm products with a chip area of 11 mm2 on the metal 2 layer. All the hotspots were resolved. The number of DFM spacing violations decreased by 7-15%.

Circadian desynchronization

PubMed Central

Granada, Adrián E.; Cambras, Trinitat; Díez-Noguera, Antoni; Herzel, Hanspeter

2011-01-01

The suprachiasmatic nucleus (SCN) coordinates via multiple outputs physiological and behavioural circadian rhythms. The SCN is composed of a heterogeneous network of coupled oscillators that entrain to the daily light–dark cycles. Outside the physiological entrainment range, rich locomotor patterns of desynchronized rhythms are observed. Previous studies interpreted these results as the output of different SCN neural subpopulations. We find, however, that even a single periodically driven oscillator can induce such complex desynchronized locomotor patterns. Using signal analysis, we show how the observed patterns can be consistently clustered into two generic oscillatory interaction groups: modulation and superposition. In seven of 17 rats undergoing forced desynchronization, we find a theoretically predicted third spectral component. Combining signal analysis with the theory of coupled oscillators, we provide a framework for the study of circadian desynchronization. PMID:22419981

Fluid synthesis and structure of a new polymorphic modification of boron nitride

NASA Astrophysics Data System (ADS)

Pokropivny, V. V.; Smolyar, A. S.; Ovsiannikova, L. I.; Pokropivny, A. V.; Kuts, V. A.; Lyashenko, V. I.; Nesterenko, Yu. V.

2013-04-01

A new previously unknown phase of boron nitride with a hardness of 0.41-0.63 GPa has been pre-pared by the supercritical fluid synthesis. The presence of a new phase is confirmed by the X-ray spectra and IR absorption spectra, where new reflections and bands are distinguished. The fundamental reflection of the X-ray diffraction pattern is d = 0.286-0.291 nm, and the characteristic band in the infrared absorption spectrum is observed at 704 cm-1. The X-ray diffraction pattern and the experimental and theoretical infrared absorption spectra show that a new synthesized boron nitride phase can be a cluster crystal (space group 211) with a simple cubic lattice. Cage clusters of a fullerene-like morphology B24N24 with point symmetry O are arranged in lattice sites.

Competitive aggregation dynamics using phase wave signals.

PubMed

Sakaguchi, Hidetsugu; Maeyama, Satomi

2014-10-21

Coupled equations of the phase equation and the equation of cell concentration n are proposed for competitive aggregation dynamics of slime mold in two dimensions. Phase waves are used as tactic signals of aggregation in this model. Several aggregation clusters are formed initially, and target patterns appear around the localized aggregation clusters. Owing to the competition among target patterns, the number of the localized aggregation clusters decreases, and finally one dominant localized pattern survives. If the phase equation is replaced with the complex Ginzburg-Landau equation, several spiral patterns appear, and n is localized near the center of the spiral patterns. After the competition among spiral patterns, one dominant spiral survives. Copyright © 2014 Elsevier Ltd. All rights reserved.

Vector nature of multi-soliton patterns in a passively mode-locked figure-eight fiber laser.

PubMed

Ning, Qiu-Yi; Liu, Hao; Zheng, Xu-Wu; Yu, Wei; Luo, Ai-Ping; Huang, Xu-Guang; Luo, Zhi-Chao; Xu, Wen-Cheng; Xu, Shan-Hui; Yang, Zhong-Min

2014-05-19

The vector nature of multi-soliton dynamic patterns was investigated in a passively mode-locked figure-eight fiber laser based on the nonlinear amplifying loop mirror (NALM). By properly adjusting the cavity parameters such as the pump power level and intra-cavity polarization controllers (PCs), in addition to the fundamental vector soliton, various vector multi-soliton regimes were observed, such as the random static distribution of vector multiple solitons, vector soliton cluster, vector soliton flow, and the state of vector multiple solitons occupying the whole cavity. Both the polarization-locked vector solitons (PLVSs) and the polarization-rotating vector solitons (PRVSs) were observed for fundamental soliton and each type of multi-soliton patterns. The obtained results further reveal the fundamental physics of multi-soliton patterns and demonstrate that the figure-eight fiber lasers are indeed a good platform for investigating the vector nature of different soliton types.

Predicting spiral wave patterns from cell properties in a model of biological self-organization.

PubMed

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Predicting spiral wave patterns from cell properties in a model of biological self-organization

NASA Astrophysics Data System (ADS)

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Adaptive nest clustering and density-dependent nest survival in dabbling ducks

USGS Publications Warehouse

Ringelman, Kevin M.; Eadie, John M.; Ackerman, Joshua T.

2014-01-01

Density-dependent population regulation is observed in many taxa, and understanding the mechanisms that generate density dependence is especially important for the conservation of heavily-managed species. In one such system, North American waterfowl, density dependence is often observed at continental scales, and nest predation has long been implicated as a key factor driving this pattern. However, despite extensive research on this topic, it remains unclear if and how nest density influences predation rates. Part of this confusion may have arisen because previous studies have studied density-dependent predation at relatively large spatial and temporal scales. Because the spatial distribution of nests changes throughout the season, which potentially influences predator behavior, nest survival may vary through time at relatively small spatial scales. As such, density-dependent nest predation might be more detectable at a spatially- and temporally-refined scale and this may provide new insights into nest site selection and predator foraging behavior. Here, we used three years of data on nest survival of two species of waterfowl, mallards and gadwall, to more fully explore the relationship between local nest clustering and nest survival. Throughout the season, we found that the distribution of nests was consistently clustered at small spatial scales (˜50–400 m), especially for mallard nests, and that this pattern was robust to yearly variation in nest density and the intensity of predation. We demonstrated further that local nest clustering had positive fitness consequences – nests with closer nearest neighbors were more likely to be successful, a result that is counter to the general assumption that nest predation rates increase with nest density.

Pattern Selection and Super-Patterns in Opinion Dynamics

NASA Astrophysics Data System (ADS)

Ben-Naim, Eli; Scheel, Arnd

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

The Problem of “Just for Fun”: Patterns of Use Situations among Active Club Drug Users

PubMed Central

Starks, Tyrel J.; Golub, Sarit; Kelly, Brian C.; Parsons, Jeffrey T.

2010-01-01

Existing research has demonstrated the significance of situational antecedents to substance use. The current study used a cluster analytic approach to identify groups of club drug users who report using substances in similar situations (assessed by the Inventory of Drug Taking Situations) with longitudinal data from 400 active drug users. A three-cluster solution emerged in baseline data and was replicated in 12-month follow-up data. Groups were identified as Situationally Restricted, Pleasure Driven, and Situationally Broad users. Group differences were observed on measures of mental health, attitudes towards substance use, amount of substance use, and rates of substance dependence. Cluster membership predicted substance dependence after controlling for past dependence, current use, and current depression/anxiety. PMID:20696530

Identification of atypical flight patterns

NASA Technical Reports Server (NTRS)

Statler, Irving C. (Inventor); Ferryman, Thomas A. (Inventor); Amidan, Brett G. (Inventor); Whitney, Paul D. (Inventor); White, Amanda M. (Inventor); Willse, Alan R. (Inventor); Cooley, Scott K. (Inventor); Jay, Joseph Griffith (Inventor); Lawrence, Robert E. (Inventor); Mosbrucker, Chris (Inventor)

2005-01-01

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis.

On the mechanochemical theory of biological pattern formation with application to vasculogenesis.

PubMed

Murray, James D

2003-02-01

We first describe the Murray-Oster mechanical theory of pattern formation, the biological basis of which is experimentally well documented. The model quantifies the interaction of cells and the extracellular matrix via the cell-generated forces. The model framework is described in quantitative detail. Vascular endothelial cells, when cultured on gelled basement membrane matrix, rapidly aggregate into clusters while deforming the matrix into a network of cord-like structures tessellating the planar culture. We apply the mechanical theory of pattern formation to this culture system and show that neither strain-biased anisotropic cell traction nor cell migration are necessary for pattern formation: isotropic, strain-stimulated cell traction is sufficient to form the observed patterns. Predictions from the model were confirmed experimentally.

Behavioral self-organization underlies the resilience of a coastal ecosystem.

PubMed

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R; Herman, Peter M J; van de Koppel, Johan

2017-07-25

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds ( Mytilus edulis ) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance.

Behavioral self-organization underlies the resilience of a coastal ecosystem

PubMed Central

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R.; Herman, Peter M. J.

2017-01-01

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds (Mytilus edulis) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance. PMID:28696313

Emergent patterns in interacting neuronal sub-populations

NASA Astrophysics Data System (ADS)

Kamal, Neeraj Kumar; Sinha, Sudeshna

2015-05-01

We investigate an ensemble of coupled model neurons, consisting of groups of varying sizes and intrinsic dynamics, ranging from periodic to chaotic, where the inter-group coupling interaction is effectively like a dynamic signal from a different sub-population. We observe that the minority group can significantly influence the majority group. For instance, when a small chaotic group is coupled to a large periodic group, the chaotic group de-synchronizes. However, counter-intuitively, when a small periodic group couples strongly to a large chaotic group, it leads to complete synchronization in the majority chaotic population, which also spikes at the frequency of the small periodic group. It then appears that the small group of periodic neurons can act like a pacemaker for the whole network. Further, we report the existence of varied clustering patterns, ranging from sets of synchronized clusters to anti-phase clusters, governed by the interplay of the relative sizes and dynamics of the sub-populations. So these results have relevance in understanding how a group can influence the synchrony of another group of dynamically different elements, reminiscent of event-related synchronization/de-synchronization in complex networks.

Spatial expression of Hox cluster genes in the ontogeny of a sea urchin

NASA Technical Reports Server (NTRS)

Arenas-Mena, C.; Cameron, A. R.; Davidson, E. H.

2000-01-01

The Hox cluster of the sea urchin Strongylocentrous purpuratus contains ten genes in a 500 kb span of the genome. Only two of these genes are expressed during embryogenesis, while all of eight genes tested are expressed during development of the adult body plan in the larval stage. We report the spatial expression during larval development of the five 'posterior' genes of the cluster: SpHox7, SpHox8, SpHox9/10, SpHox11/13a and SpHox11/13b. The five genes exhibit a dynamic, largely mesodermal program of expression. Only SpHox7 displays extensive expression within the pentameral rudiment itself. A spatially sequential and colinear arrangement of expression domains is found in the somatocoels, the paired posterior mesodermal structures that will become the adult perivisceral coeloms. No such sequential expression pattern is observed in endodermal, epidermal or neural tissues of either the larva or the presumptive juvenile sea urchin. The spatial expression patterns of the Hox genes illuminate the evolutionary process by which the pentameral echinoderm body plan emerged from a bilateral ancestor.

Merged or monolithic? Using machine-learning to reconstruct the dynamical history of simulated star clusters

NASA Astrophysics Data System (ADS)

Pasquato, Mario; Chung, Chul

2016-05-01

Context. Machine-learning (ML) solves problems by learning patterns from data with limited or no human guidance. In astronomy, ML is mainly applied to large observational datasets, e.g. for morphological galaxy classification. Aims: We apply ML to gravitational N-body simulations of star clusters that are either formed by merging two progenitors or evolved in isolation, planning to later identify globular clusters (GCs) that may have a history of merging from observational data. Methods: We create mock-observations from simulated GCs, from which we measure a set of parameters (also called features in the machine-learning field). After carrying out dimensionality reduction on the feature space, the resulting datapoints are fed in to various classification algorithms. Using repeated random subsampling validation, we check whether the groups identified by the algorithms correspond to the underlying physical distinction between mergers and monolithically evolved simulations. Results: The three algorithms we considered (C5.0 trees, k-nearest neighbour, and support-vector machines) all achieve a test misclassification rate of about 10% without parameter tuning, with support-vector machines slightly outperforming the others. The first principal component of feature space correlates with cluster concentration. If we exclude it from the regression, the performance of the algorithms is only slightly reduced.

How Much are Built Environments Changing, and Where?: Patterns of Change by Neighborhood Sociodemographic Characteristics across Seven U.S. Metropolitan Areas

PubMed Central

Hirsch, Jana A.; Grengs, Joe; Schulz, Amy; Adar, Sara D.; Rodriguez, Daniel A.; Brines, Shannon J.; Diez Roux, Ana V.

2016-01-01

Investments in neighborhood built environments could increase physical activity and overall health. Disproportionate distribution of these changes in advantaged neighborhoods could inflate health disparities. Little information exists on where changes are occurring. This paper aims to 1) identify changes in the built environment in neighborhoods and 2) investigate associations between high levels of change and sociodemographic characteristics. Using Geographic Information Systems, neighborhood land-use, local destinations (for walking, social engagement, and physical activity), and sociodemographics were characterized in 2000 and 2010 for seven U.S. cities. Linear and change on change models estimated associations of built environment changes with baseline (2000) and change (2010–2000) in sociodemographics. Spatial patterns were assessed using Global Moran’s I to measure overall clustering of change and Local Moran’s I to identify statistically significant clusters of high increases surrounded by high increases (HH). Sociodemographic characteristics were compared between HH cluster and other tracts using Analysis of Variance (ANOVA). We observed small land-use changes but increases in the destination types. Greater increases in destinations were associated with higher percentage non-Hispanic whites, percentage households with no vehicle, and median household income. Associations were present for both baseline sociodemographics and changes over time. Greater increases in destinations were associated with lower baseline percentage over 65 but higher increases in percentage over 65 between 2000 and 2010. Global Moran’s indicated changes were spatially clustered. HH cluster tracts started with a higher percentage non-Hispanic whites and higher percentage of households without vehicles. Between 2000 and 2010, HH cluster tracts experienced increases in percent non-Hispanic white, greater increases in median household income, and larger decreases in percent of households without a vehicle. Changes in the built environment are occurring in neighborhoods across a diverse set of U.S. metropolitan areas, but are patterned such that they may lead to increased health disparities over time. PMID:27701020

Genome-wide identification of novel expression signatures reveal distinct patterns and prevalence of binding motifs for p53, nuclear factor-κB and other signal transcription factors in head and neck squamous cell carcinoma

PubMed Central

Yan, Bin; Yang, Xinping; Lee, Tin-Lap; Friedman, Jay; Tang, Jun; Van Waes, Carter; Chen, Zhong

2007-01-01

Background Differentially expressed gene profiles have previously been observed among pathologically defined cancers by microarray technologies, including head and neck squamous cell carcinomas (HNSCCs). However, the molecular expression signatures and transcriptional regulatory controls that underlie the heterogeneity in HNSCCs are not well defined. Results Genome-wide cDNA microarray profiling of ten HNSCC cell lines revealed novel gene expression signatures that distinguished cancer cell subsets associated with p53 status. Three major clusters of over-expressed genes (A to C) were defined through hierarchical clustering, Gene Ontology, and statistical modeling. The promoters of genes in these clusters exhibited different patterns and prevalence of transcription factor binding sites for p53, nuclear factor-κB (NF-κB), activator protein (AP)-1, signal transducer and activator of transcription (STAT)3 and early growth response (EGR)1, as compared with the frequency in vertebrate promoters. Cluster A genes involved in chromatin structure and function exhibited enrichment for p53 and decreased AP-1 binding sites, whereas clusters B and C, containing cytokine and antiapoptotic genes, exhibited a significant increase in prevalence of NF-κB binding sites. An increase in STAT3 and EGR1 binding sites was distributed among the over-expressed clusters. Novel regulatory modules containing p53 or NF-κB concomitant with other transcription factor binding motifs were identified, and experimental data supported the predicted transcriptional regulation and binding activity. Conclusion The transcription factors p53, NF-κB, and AP-1 may be important determinants of the heterogeneous pattern of gene expression, whereas STAT3 and EGR1 may broadly enhance gene expression in HNSCCs. Defining these novel gene signatures and regulatory mechanisms will be important for establishing new molecular classifications and subtyping, which in turn will promote development of targeted therapeutics for HNSCC. PMID:17498291

Cluster: A New Application for Spatial Analysis of Pixelated Data for Epiphytotics.

PubMed

Nelson, Scot C; Corcoja, Iulian; Pethybridge, Sarah J

2017-12-01

Spatial analysis of epiphytotics is essential to develop and test hypotheses about pathogen ecology, disease dynamics, and to optimize plant disease management strategies. Data collection for spatial analysis requires substantial investment in time to depict patterns in various frames and hierarchies. We developed a new approach for spatial analysis of pixelated data in digital imagery and incorporated the method in a stand-alone desktop application called Cluster. The user isolates target entities (clusters) by designating up to 24 pixel colors as nontargets and moves a threshold slider to visualize the targets. The app calculates the percent area occupied by targeted pixels, identifies the centroids of targeted clusters, and computes the relative compass angle of orientation for each cluster. Users can deselect anomalous clusters manually and/or automatically by specifying a size threshold value to exclude smaller targets from the analysis. Up to 1,000 stochastic simulations randomly place the centroids of each cluster in ranked order of size (largest to smallest) within each matrix while preserving their calculated angles of orientation for the long axes. A two-tailed probability t test compares the mean inter-cluster distances for the observed versus the values derived from randomly simulated maps. This is the basis for statistical testing of the null hypothesis that the clusters are randomly distributed within the frame of interest. These frames can assume any shape, from natural (e.g., leaf) to arbitrary (e.g., a rectangular or polygonal field). Cluster summarizes normalized attributes of clusters, including pixel number, axis length, axis width, compass orientation, and the length/width ratio, available to the user as a downloadable spreadsheet. Each simulated map may be saved as an image and inspected. Provided examples demonstrate the utility of Cluster to analyze patterns at various spatial scales in plant pathology and ecology and highlight the limitations, trade-offs, and considerations for the sensitivities of variables and the biological interpretations of results. The Cluster app is available as a free download for Apple computers at iTunes, with a link to a user guide website.

Constructivism in Practice: an Exploratory Study of Teaching Patterns and Student Motivation in Physics Classrooms in Finland, Germany and Switzerland

NASA Astrophysics Data System (ADS)

Beerenwinkel, Anne; von Arx, Matthias

2017-04-01

For the last three decades, moderate constructivism has become an increasingly prominent perspective in science education. Researchers have defined characteristics of constructivist-oriented science classrooms, but the implementation of such science teaching in daily classroom practice seems difficult. Against this background, we conducted a sub-study within the tri-national research project Quality of Instruction in Physics (QuIP) analysing 60 videotaped physics classes involving a large sample of students ( N = 1192) from Finland, Germany and Switzerland in order to investigate the kinds of constructivist components and teaching patterns that can be found in regular classrooms without any intervention. We applied a newly developed coding scheme to capture constructivist facets of science teaching and conducted principal component and cluster analyses to explore which components and patterns were most prominent in the classes observed. Two underlying components were found, resulting in two scales—Structured Knowledge Acquisition and Fostering Autonomy—which describe key aspects of constructivist teaching. Only the first scale was rather well established in the lessons investigated. Classes were clustered based on these scales. The analysis of the different clusters suggested that teaching physics in a structured way combined with fostering students' autonomy contributes to students' motivation. However, our regression models indicated that content knowledge is a more important predictor for students' motivation, and there was no homogeneous pattern for all gender- and country-specific subgroups investigated. The results are discussed in light of recent discussions on the feasibility of constructivism in practice.

Analizing Student Biology Education Misconception And Scientific Argumentation Ability Using Diagnostic Question Clusters (Dqcs) Of Molecular Genetic Concept

NASA Astrophysics Data System (ADS)

Nurlaila, L.; Sriyati, S.; Riandi

2017-02-01

The purpose of this research is to describe the profile of misconceptions and scientific argumentation ability using Diagnostic Question Cluster (DQCs) of molecular genetics concept. This research use descriptive research method and biology education students as a research subject. The Instrument that used in this research are DQCs, sheets interviews, observations, and field notes. The DQCs tested by writing and oral that used to analyze misconceptions and scientific argumentation ability. Sheets interviews, observations and field notes, are used to analyze the possible factors causing misconceptions and scientific argumentation ability. The results showed that misconception of molecular genetics are: DNA (23.75%), genes (18.75%) of chromosomes (15%) and protein synthesis (5.5%). The pattern of the highest misconceptions owned Misconception-Understand Partial. The average scientific argumentation ability is 55% and still categorized warrant (W). The pattern of the scientific argumentation abilities formed is level 2 to level 2 that consists of the arguments in the form of a claim with a counter claim that accompanied by data, collateral (warrant) or support (backing) but does not contain a disclaimer (rebutal).

Partial bisulfite conversion for unique template sequencing.

PubMed

Kumar, Vijay; Rosenbaum, Julie; Wang, Zihua; Forcier, Talitha; Ronemus, Michael; Wigler, Michael; Levy, Dan

2018-01-25

We introduce a new protocol, mutational sequencing or muSeq, which uses sodium bisulfite to randomly deaminate unmethylated cytosines at a fixed and tunable rate. The muSeq protocol marks each initial template molecule with a unique mutation signature that is present in every copy of the template, and in every fragmented copy of a copy. In the sequenced read data, this signature is observed as a unique pattern of C-to-T or G-to-A nucleotide conversions. Clustering reads with the same conversion pattern enables accurate count and long-range assembly of initial template molecules from short-read sequence data. We explore count and low-error sequencing by profiling 135 000 restriction fragments in a PstI representation, demonstrating that muSeq improves copy number inference and significantly reduces sporadic sequencer error. We explore long-range assembly in the context of cDNA, generating contiguous transcript clusters greater than 3,000 bp in length. The muSeq assemblies reveal transcriptional diversity not observable from short-read data alone. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Effect of palladium doping on the stability and fragmentation patterns of cationic gold clusters

NASA Astrophysics Data System (ADS)

Ferrari, P.; Hussein, H. A.; Heard, C. J.; Vanbuel, J.; Johnston, R. L.; Lievens, P.; Janssens, E.

2018-05-01

We analyze in detail how the interplay between electronic structure and cluster geometry determines the stability and the fragmentation channels of single Pd-doped cationic Au clusters, PdA uN-1+ (N =2 -20 ). For this purpose, a combination of photofragmentation experiments and density functional theory calculations was employed. A remarkable agreement between the experiment and the calculations is obtained. Pd doping is found to modify the structure of the Au clusters, in particular altering the two-dimensional to three-dimensional transition size, with direct consequences on the stability of the clusters. Analysis of the electronic density of states of the clusters shows that depending on cluster size, Pd delocalizes one 4 d electron, giving an enhanced stability to PdA u6 + , or remains with all 4 d10 electrons localized, closing an electronic shell in PdA u9 + . Furthermore, it is observed that for most clusters, Au evaporation is the lowest-energy decay channel, although for some sizes Pd evaporation competes. In particular, PdA u7 + and PdA u9 + decay by Pd evaporation due to the high stability of the A u7 + and A u9 + fragmentation products.

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

PubMed

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

2009-12-01

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

From broadscale patterns to fine-scale processes: habitat structure influences genetic differentiation in the pitcher plant midge across multiple spatial scales.

PubMed

Rasic, Gordana; Keyghobadi, Nusha

2012-01-01

The spatial scale at which samples are collected and analysed influences the inferences that can be drawn from landscape genetic studies. We examined genetic structure and its landscape correlates in the pitcher plant midge, Metriocnemus knabi, an inhabitant of the purple pitcher plant, Sarracenia purpurea, across several spatial scales that are naturally delimited by the midge's habitat (leaf, plant, cluster of plants, bog and system of bogs). We analysed 11 microsatellite loci in 710 M. knabi larvae from two systems of bogs in Algonquin Provincial Park (Canada) and tested the hypotheses that variables related to habitat structure are associated with genetic differentiation in this midge. Up to 54% of variation in individual-based genetic distances at several scales was explained by broadscale landscape variables of bog size, pitcher plant density within bogs and connectivity of pitcher plant clusters. Our results indicate that oviposition behaviour of females at fine scales, as inferred from the spatial locations of full-sib larvae, and spatially limited gene flow at broad scales represent the important processes underlying observed genetic patterns in M. knabi. Broadscale landscape features (bog size and plant density) appear to influence oviposition behaviour of midges, which in turn influences the patterns of genetic differentiation observed at both fine and broad scales. Thus, we inferred linkages among genetic patterns, landscape patterns and ecological processes across spatial scales in M. knabi. Our results reinforce the value of exploring such links simultaneously across multiple spatial scales and landscapes when investigating genetic diversity within a species. © 2011 Blackwell Publishing Ltd.

Implementation of K-Means Clustering Method for Electronic Learning Model

NASA Astrophysics Data System (ADS)

Latipa Sari, Herlina; Suranti Mrs., Dewi; Natalia Zulita, Leni

2017-12-01

Teaching and Learning process at SMK Negeri 2 Bengkulu Tengah has applied e-learning system for teachers and students. The e-learning was based on the classification of normative, productive, and adaptive subjects. SMK Negeri 2 Bengkulu Tengah consisted of 394 students and 60 teachers with 16 subjects. The record of e-learning database was used in this research to observe students’ activity pattern in attending class. K-Means algorithm in this research was used to classify students’ learning activities using e-learning, so that it was obtained cluster of students’ activity and improvement of student’s ability. Implementation of K-Means Clustering method for electronic learning model at SMK Negeri 2 Bengkulu Tengah was conducted by observing 10 students’ activities, namely participation of students in the classroom, submit assignment, view assignment, add discussion, view discussion, add comment, download course materials, view article, view test, and submit test. In the e-learning model, the testing was conducted toward 10 students that yielded 2 clusters of membership data (C1 and C2). Cluster 1: with membership percentage of 70% and it consisted of 6 members, namely 1112438 Anggi Julian, 1112439 Anis Maulita, 1112441 Ardi Febriansyah, 1112452 Berlian Sinurat, 1112460 Dewi Anugrah Anwar and 1112467 Eka Tri Oktavia Sari. Cluster 2:with membership percentage of 30% and it consisted of 4 members, namely 1112463 Dosita Afriyani, 1112471 Erda Novita, 1112474 Eskardi and 1112477 Fachrur Rozi.

Identification of genetically diverse genotypes for photoperiod insensitivity in soybean using RAPD markers.

PubMed

Singh, R K; Bhatia, V S; Yadav, Sanjeev; Athale, Rashmi; Lakshmi, N; Guruprasad, K N; Chauhan, G S

2008-10-01

Most of the Indian soybean varieties were found to be highly sensitive to photoperiod, which limits their cultivation in only localized area. Identification of genetically diverse source of photoperiod insensitive would help to broaden the genetic base for this trait. Present study was undertaken with RAPD markers for genetic diversity estimation in 44 accessions of soybean differing in response to photoperiod sensitivity. The selected twenty-five RAPD primers produced a total of 199 amplicons, which generated 89.9 % polymorphism. The number of amplification products ranged from 2 to 13 for different primers. The polymorphism information content ranged from 0.0 for monomorphic loci to 0.5 with an average of 0.289. Genetic diversity between pairs of genotypes was 37.7% with a range of 3.9 to 71.6%. UPGMA cluster analysis placed all the accessions of soybean into four major clusters. No discernable geographical patterns were observed in clustering however; the smaller groups corresponded well with pedigree. Mantel's test (r = 0.915) indicates very good fit for clustering pattern. Two genotypes, MACS 330 and 111/2/1939 made a very divergent group from other accessions of soybean and highly photoperiod insensitive that may be potential source for broadening the genetic base of soybean for this trait.

Kin-Aggregations Explain Chaotic Genetic Patchiness, a Commonly Observed Genetic Pattern, in a Marine Fish.

PubMed

Selwyn, Jason D; Hogan, J Derek; Downey-Wall, Alan M; Gurski, Lauren M; Portnoy, David S; Heath, Daniel D

2016-01-01

The phenomenon of chaotic genetic patchiness is a pattern commonly seen in marine organisms, particularly those with demersal adults and pelagic larvae. This pattern is usually associated with sweepstakes recruitment and variable reproductive success. Here we investigate the biological underpinnings of this pattern in a species of marine goby Coryphopterus personatus. We find that populations of this species show tell-tale signs of chaotic genetic patchiness including: small, but significant, differences in genetic structure over short distances; a non-equilibrium or "chaotic" pattern of differentiation among locations in space; and within locus, within population deviations from the expectations of Hardy-Weinberg equilibrium (HWE). We show that despite having a pelagic larval stage, and a wide distribution across Caribbean coral reefs, this species forms groups of highly related individuals at small spatial scales (<10 metres). These spatially clustered family groups cause the observed deviations from HWE and local population differentiation, a finding that is rarely demonstrated, but could be more common than previously thought.

Large clusters of co-expressed genes in the Drosophila genome.

PubMed

Boutanaev, Alexander M; Kalmykova, Alla I; Shevelyov, Yuri Y; Nurminsky, Dmitry I

2002-12-12

Clustering of co-expressed, non-homologous genes on chromosomes implies their co-regulation. In lower eukaryotes, co-expressed genes are often found in pairs. Clustering of genes that share aspects of transcriptional regulation has also been reported in higher eukaryotes. To advance our understanding of the mode of coordinated gene regulation in multicellular organisms, we performed a genome-wide analysis of the chromosomal distribution of co-expressed genes in Drosophila. We identified a total of 1,661 testes-specific genes, one-third of which are clustered on chromosomes. The number of clusters of three or more genes is much higher than expected by chance. We observed a similar trend for genes upregulated in the embryo and in the adult head, although the expression pattern of individual genes cannot be predicted on the basis of chromosomal position alone. Our data suggest that the prevalent mechanism of transcriptional co-regulation in higher eukaryotes operates with extensive chromatin domains that comprise multiple genes.

Spatiotemporal earthquake clusters along the North Anatolian fault zone offshore Istanbul

USGS Publications Warehouse

Bulut, Fatih; Ellsworth, William L.; Bohnhoff, Marco; Aktar, Mustafa; Dresen, Georg

2011-01-01

We investigate earthquakes with similar waveforms in order to characterize spatiotemporal microseismicity clusters within the North Anatolian fault zone (NAFZ) in northwest Turkey along the transition between the 1999 ??zmit rupture zone and the Marmara Sea seismic gap. Earthquakes within distinct activity clusters are relocated with cross-correlation derived relative travel times using the double difference method. The spatiotemporal distribution of micro earthquakes within individual clusters is resolved with relative location accuracy comparable to or better than the source size. High-precision relative hypocenters define the geometry of individual fault patches, permitting a better understanding of fault kinematics and their role in local-scale seismotectonics along the region of interest. Temporal seismic sequences observed in the eastern Sea of Marmara region suggest progressive failure of mostly nonoverlapping areas on adjacent fault patches and systematic migration of microearthquakes within clusters during the progressive failure of neighboring fault patches. The temporal distributions of magnitudes as well as the number of events follow swarmlike behavior rather than a mainshock/aftershock pattern.

Large scale meteorological patterns and moisture sources during precipitation extremes over South Asia

NASA Astrophysics Data System (ADS)

Mehmood, S.; Ashfaq, M.; Evans, K. J.; Black, R. X.; Hsu, H. H.

2017-12-01

Extreme precipitation during summer season has shown an increasing trend across South Asia in recent decades, causing an exponential increase in weather related losses. Here we combine a cluster analyses technique (Agglomerative Hierarchical Clustering) with a Lagrangian based moisture analyses technique to investigate potential commonalities in the characteristics of the large scale meteorological patterns (LSMP) and moisture anomalies associated with the observed extreme precipitation events, and their representation in the Department of Energy model ACME. Using precipitation observations from the Indian Meteorological Department (IMD) and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE), and atmospheric variables from Era-Interim Reanalysis, we first identify LSMP both in upper and lower troposphere that are responsible for wide spread precipitation extreme events during 1980-2015 period. For each of the selected extreme event, we perform moisture source analyses to identify major evaporative sources that sustain anomalous moisture supply during the course of the event, with a particular focus on local terrestrial moisture recycling. Further, we perform similar analyses on two sets of five-member ensemble of ACME model (1-degree and ¼ degree) to investigate the ability of ACME model in simulating precipitation extremes associated with each of the LSMP patterns and associated anomalous moisture sourcing from each of the terrestrial and oceanic evaporative region. Comparison of low and high-resolution model configurations provides insight about the influence of horizontal grid spacing in the simulation of extreme precipitation and the governing mechanisms.

Is there an association between food patterns and life satisfaction among Norway's inhabitants ages 65 years and older?

PubMed

André, Beate; Canhão, Helena; Espnes, Geir A; Ferreira Rodrigues, Ana Maria; Gregorio, Maria João; Nguyen, Camilla; Sousa, Rute; Grønning, Kjersti

2017-03-01

The lack of information regarding older adults' health and lifestyles makes it difficult to design suitable interventions for people at risk of developing unhealth lifestyles. Therefore, there is a need to increase knowledge about older adults' food patterns and quality of life. Our aim was to determine associations among food patterns, anxiety, depression, and life satisfaction in Norwegian inhabitants ages 65+. The Nord-Trøndelag Health Study (The HUNT Study) is a large, population-based cohort study that includes data for 125 000 Norwegian participants. The cohort used for this study is wave three of the study, consisting of 11 619 participants age 65 and over. Cluster analysis was used to categorize the participants based on similarities in food consumption; two clusters were identified based on similarities regarding food consumption among participants. Significant differences between the clusters were found, as participants in the healthy food-patterns cluster had higher life satisfaction and lower anxiety and depression than those in the unhealthy food-patterns cluster. The associations among food patterns, anxiety, depression, and life satisfaction among older adults show the need for increased focus on interactions among food patterns, food consumption, and life satisfaction among the elderly in order to explore how society can influence these patterns. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

US Household Food Shopping Patterns: Dynamic Shifts since 2000 and Socioeconomic Predictors

PubMed Central

Stern, Dalia; Robinson, Whitney R; Ng, Shu Wen; Gordon-Larsen, Penny; Popkin, Barry M

2016-01-01

Under the assumption that differential food access might underlie nutritional disparities, programs and policies have focused on the need to build supermarkets in underserved areas, in an effort to improve dietary quality. However, there is limited evidence about which types of stores different income and race-ethnic households use. We used cross-sectional cluster analysis to derive shopping patterns from US households’ volume food purchases (Nielsen Homescan) by store from 2000–2012. Multinomial logistic regression identified household SES characteristics that were associated with shopping patterns in 2012. We found three shopping patterns: primary-grocery, primary-mass-merchandise, and combination cluster. In 2012, we found no income/race-ethnic differences for grocery cluster membership. However, low-income non-Hispanic blacks (vs. non-Hispanic whites) had a significantly lower probability of belonging to the mass-merchandise cluster. These varied shopping patterns must be considered in future policy initiatives. Further, it is important to continue studying the complex rationale for people’s food shopping patterns. PMID:26526241

Fragmentation pathways of tungsten hexacarbonyl clusters upon electron ionization

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

Neustetter, M.; Jabbour Al Maalouf, E.; Denifl, S., E-mail: Stephan.Denifl@uibk.ac.at, E-mail: plimaovieira@fct.unl.pt

2016-08-07

Electron ionization of neat tungsten hexacarbonyl (W(CO){sub 6}) clusters has been investigated in a crossed electron-molecular beam experiment coupled with a mass spectrometer system. The molecule is used for nanofabrication processes through electron beam induced deposition and ion beam induced deposition techniques. Positive ion mass spectra of W(CO){sub 6} clusters formed by electron ionization at 70 eV contain the ion series of the type W(CO){sub n}{sup +} (0 ≤ n ≤ 6) and W{sub 2}(CO){sub n}{sup +} (0 ≤ n ≤ 12). In addition, a series of peaks are observed and have been assigned to WC(CO){sub n}{sup +} (0 ≤more » n ≤ 3) and W{sub 2}C(CO){sub n}{sup +} (0 ≤ n ≤ 10). A distinct change of relative fragment ion intensity can be observed for clusters compared to the single molecule. The characteristic fragmentation pattern obtained in the mass spectra can be explained by a sequential decay of the ionized organometallic, which is also supported by the study of the clusters when embedded in helium nanodroplets. In addition, appearance energies for the dissociative ionization channels for singly charged ions have been estimated from experimental ion efficiency curves.« less

Prostate cancer incidence and tumor severity in Georgia: descriptive epidemiology, racial disparity, and geographic trends.

PubMed

Wagner, Sara E; Bauer, Sarah E; Bayakly, A Rana; Vena, John E

2013-01-01

Limited research has been conducted to describe the geographical clustering and distribution of prostate cancer (PrCA) incidence in Georgia (GA). This study describes and compares the temporal and geographic trends of PrCA incidence in GA with a specific focus on racial disparities. GA Comprehensive Cancer Registry PrCA incidence data were obtained for 1998-2008. Directly standardized age-adjusted PrCA incidence rates per 100,000 were analyzed by race, stage, grade, and county. County-level hotspots of PrCA incidence were analyzed with the Getis-Ord Gi* statistic in a geographic information system; a census tract-level cluster analysis was performed with a Discrete Poisson model and implemented in SaTScan(®) software. Significant (p < 0.05) hotspots of PrCA incidence were observed in nine southwestern counties and six centrally located counties among men of both races. Six significant (p < 0.1) clusters of PrCA incidence rates were detected for men of both races in north and northwest central Georgia. When stratified by race, clusters among white and black men were similar, although centroids were slightly shifted. Most notably, a large (122 km radius) cluster in northwest central Georgia was detected only in whites, and two smaller clusters (0-32 km radii) were detected in Southwest Georgia only in black men. Clusters of high-grade and late-stage tumors were identified primarily in the northern portion of the state among men of both races. This study revealed a pattern of higher incidence and more advanced disease in northern and northwest central Georgia, highlighting geographic patterns that need more research and investigation of possible environmental determinants.

Beverage consumption patterns at age 13–17 are associated with weight, height, and BMI at age 17

PubMed Central

Marshall, Teresa A.; Van Buren, John M.; Warren, John J.; Cavanaugh, Joseph E.; Levy, Steven M.

2017-01-01

Background Sugar-sweetened beverages (SSBs) have been associated with obesity in children and adults; however, associations between beverage patterns and obesity are not understood. Objective To describe beverage patterns during adolescence, and the associations between adolescent beverage patterns and age 17 anthropometric measures. Design Cross-sectional analyses of longitudinally-collected data. Participants/setting Participants in the longitudinal Iowa Fluoride Study having at least one beverage questionnaire completed between ages 13.0 and 14.0 years, having a second questionnaire completed between 16.0 and 17.0 years and attending an age 17 clinic exam for weight and height measurements (n=369). Exposure Beverages were collapsed into 4 categories {i.e., 100% juice, milk, water and other sugar-free beverages (water/SFB), and SSBs} for the purpose of clustering. Five beverage clusters were identified from standardized age 13–17 mean daily beverage intakes and named by the authors for the dominant beverage: juice, milk, water/SFB, neutral and SSB. Outcome Age 17 weight, height and BMI. Statistical analyses Ward’s method for clustering of beverage variables. One-way ANOVA and chi-square tests for bivariable associations. Gamma regression for associations of weight or BMI (outcomes) with beverage clusters and demographic variables. Linear regression for associations of height (outcome) with beverage clusters and demographic variables. Results Participants with family incomes < $60,000 trended shorter (1.5±0.8 cm; P=0.070) and were heavier (2.0±0.7 BMI units; P=0.002) than participants with family incomes ≥ 60,000/year. Adjusted mean weight, height and BMI estimates differed by beverage cluster membership. For example, on average, male and female members of the neutral cluster were 4.5 cm (P=0.010) and 4.2 (P=0.034) cm shorter, respectively, than members of the milk cluster. For members of the juice cluster, the mean BMI was lower than for members of the milk cluster (by 2.4 units), water/SFB cluster (3.5 units), neutral cluster (2.2 units) and SSB cluster (3.2 units) (all Ps<0.05). Conclusions Age 13–17 year beverage patterns were associated with age 17 anthropometric measures and BMI in this sample. Beverage patterns might be characteristic of overall food choices and dietary behaviors that influence growth. PMID:28259744

Acquisition of Japanese contracted sounds in L1 phonology

NASA Astrophysics Data System (ADS)

Tsurutani, Chiharu

2002-05-01

Japanese possesses a group of palatalized consonants, known to Japanese scholars as the contracted sounds, [CjV]. English learners of Japanese appear to treat them initially as consonant + glide clusters, where there is an equivalent [Cj] cluster in English, or otherwise tend to insert an epenthetic vowel [CVjV]. The acquisition of the Japanese contracted sounds by first language (L1) learners has not been widely studied compared with the consonant clusters in English with which they bear a close phonetic resemblance but have quite a different phonological status. This is a study to investigate the L1 acquisition process of the Japanese contracted sounds (a) in order to observe how the palatalization gesture is acquired in Japanese and (b) to investigate differences in the sound acquisition processes of first and second language (L2) learners: Japanese children compared with English learners. To do this, the productions of Japanese children ranging in age from 2.5 to 3.5 years were transcribed and the pattern of misproduction was observed.

Workload Characterization of a Leadership Class Storage Cluster

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

Kim, Youngjae; Gunasekaran, Raghul; Shipman, Galen M

2010-01-01

Understanding workload characteristics is critical for optimizing and improving the performance of current systems and software, and architecting new storage systems based on observed workload patterns. In this paper, we characterize the scientific workloads of the world s fastest HPC (High Performance Computing) storage cluster, Spider, at the Oak Ridge Leadership Computing Facility (OLCF). Spider provides an aggregate bandwidth of over 240 GB/s with over 10 petabytes of RAID 6 formatted capacity. OLCFs flagship petascale simulation platform, Jaguar, and other large HPC clusters, in total over 250 thousands compute cores, depend on Spider for their I/O needs. We characterize themore » system utilization, the demands of reads and writes, idle time, and the distribution of read requests to write requests for the storage system observed over a period of 6 months. From this study we develop synthesized workloads and we show that the read and write I/O bandwidth usage as well as the inter-arrival time of requests can be modeled as a Pareto distribution.« less

The structure of deposited metal clusters generated by laser evaporation

NASA Astrophysics Data System (ADS)

Faust, P.; Brandstättner, M.; Ding, A.

1991-09-01

Metal clusters have been produced using a laser evaporation source. A Nd-YAG laser beam focused onto a solid silver rod was used to evaporate the material, which was then cooled to form clusters with the help of a pulsed high pressure He beam. TOF mass spectra of these clusters reveal a strong occurrence of small and medium sized clusters ( n<100). Clusters were also deposited onto grid supported thin layers of carbon-films which were investigated by transmission electron microscopy. Very high resolution pictures of these grids were used to analyze the size distribution and the structure of the deposited clusters. The diffraction pattern caused by crystalline structure of the clusters reveals 3-and 5-fold symmetries as well as fcc bulk structure. This can be explained in terms of icosahedron and cuboctahedron type clusters deposited on the surface of the carbon layer. There is strong evidence that part of these cluster geometries had already been formed before the depostion process. The non-linear dependence of the cluster size and the cluster density on the generating conditions is discussed. Therefore the samples were observed in HREM in the stable DEEKO 100 microscope of the Fritz-Haber-Institut operating at 100 KV with the spherical aberration c S =0.5 mm. The quality of the pictures was improved by using the conditions of minimum phase contrast hollow cone illumination. This procedure led to a minimum of phase contrast artefacts. Among the well-crystallized particles were a great amount of five- and three-fold symmetries, icosahedra and cuboctahedra respectively. The largest clusters with five- and three-fold symmetries have been found with diameters of 7 nm; the smallest particles displaying the same undistorted symmetries were of about 2 mm. Even smaller ones with strong distortions could be observed although their classification is difficult. The quality of the images was improved by applying Fourier filtering techniques.

Patterns of evolution of MHC class II genes of crows (Corvus) suggest trans-species polymorphism

PubMed Central

Townsend, Andrea K.; Sepil, Irem; Nishiumi, Isao; Satta, Yoko

2015-01-01

A distinguishing characteristic of genes that code for the major histocompatibility complex (MHC) is that alleles often share more similarity between, rather than within species. There are two likely mechanisms that can explain this pattern: convergent evolution and trans-species polymorphism (TSP), in which ancient allelic lineages are maintained by balancing selection and retained by descendant species. Distinguishing between these two mechanisms has major implications in how we view adaptation of immune genes. In this study we analyzed exon 2 of the MHC class IIB in three passerine bird species in the genus Corvus: jungle crows (Corvus macrorhynchos japonensis) American crows (C. brachyrhynchos) and carrion crows (C. corone orientalis). Carrion crows and American crows are recently diverged, but allopatric, sister species, whereas carrion crows and jungle crows are more distantly related but sympatric species, and possibly share pathogens linked to MHC IIB polymorphisms. These patterns of evolutionary divergence and current geographic ranges enabled us to test for trans-species polymorphism and convergent evolution of the MHC IIB in crows. Phylogenetic reconstructions of MHC IIB sequences revealed several well supported interspecific clusters containing all three species, and there was no biased clustering of variants among the sympatric carrion crows and jungle crows. The topologies of phylogenetic trees constructed from putatively selected sites were remarkably different than those constructed from putatively neutral sites. In addition, trees constructed using non-synonymous substitutions from a continuous fragment of exon 2 had more, and generally more inclusive, supported interspecific MHC IIB variant clusters than those constructed from the same fragment using synonymous substitutions. These phylogenetic patterns suggest that recombination, especially gene conversion, has partially erased the signal of allelic ancestry in these species. While clustering of positively selected amino acids by supertyping revealed a single supertype shared by only jungle and carrion crows, a pattern consistent with convergence, the overall phylogenetic patterns we observed suggest that TSP, rather than convergence, explains the interspecific allelic similarity of MHC IIB genes in these species of crows. PMID:25802816

Neuropsychological phenotypes among men with and without HIV disease in the multicenter AIDS cohort study.

PubMed

Molsberry, Samantha A; Cheng, Yu; Kingsley, Lawrence; Jacobson, Lisa; Levine, Andrew J; Martin, Eileen; Miller, Eric N; Munro, Cynthia A; Ragin, Ann; Sacktor, Ned; Becker, James T

2018-05-11

Mild forms of HIV-associated neurocognitive disorder (HAND) remain prevalent in the combination anti-retroviral therapy (cART) era. This study's objective was to identify neuropsychological subgroups within the Multicenter AIDS Cohort Study (MACS) based on the participant-based latent structure of cognitive function and to identify factors associated with subgroups. The MACS is a four-site longitudinal study of the natural and treated history of HIV disease among gay and bisexual men. Using neuropsychological domain scores we used a cluster variable selection algorithm to identify the optimal subset of domains with cluster information. Latent profile analysis was applied using scores from identified domains. Exploratory and post-hoc analyses were conducted to identify factors associated with cluster membership and the drivers of the observed associations. Cluster variable selection identified all domains as containing cluster information except for Working Memory. A three-profile solution produced the best fit for the data. Profile 1 performed below average on all domains, Profile 2 performed average on executive functioning, motor, and speed and below average on learning and memory, Profile 3 performed at or above average across all domains. Several demographic, cognitive, and social factors were associated with profile membership; these associations were driven by differences between Profile 1 and the other profiles. There is an identifiable pattern of neuropsychological performance among MACS members determined by all domains except Working Memory. Neither HIV nor HIV-related biomarkers were related with cluster membership, consistent with other findings that cognitive performance patterns do not map directly onto HIV serostatus.

Dietary patterns and sarcopenia in an urban African American and White population in the United States.

PubMed

Fanelli Kuczmarski, Marie; Mason, Marc A; Beydoun, May A; Allegro, Deanne; Zonderman, Alan B; Evans, Michele K

2013-01-01

The primary objective of this cross-sectional study was to characterize dietary patterns of African Americans and Whites, 30 to 64 years, examined in the Healthy Aging in Neighborhoods of Diversity across the Life Span study. Other objectives of the study were to evaluate micronutrient adequacy of each pattern and to determine the association of diet with sarcopenia. Cluster analysis was used to determine patterns and mean adequacy ratio (MAR) to determine adequacy of 15 micronutrients. Ten clusters were identified: sandwich, sweet drink, pizza, poultry, frozen meal, dessert, alcoholic drink, bread, starchy vegetables, and pasta/rice dish. MAR ranged from 69 for the sweet drink cluster to 82 for the pasta/rice dish cluster. Sarcopenia was present in 6.4% of the sample, ranging from 1.5% in the poultry cluster to 14.1% in the alcoholic drink cluster. This study is the first to report an association between diet and sarcopenia in people younger than 65 years. The identification of presarcopenia has important implications for dietary interventions that might delay age-associated loss of lean mass.

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

PubMed

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

2015-02-01

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

Predictions of a population of cataclysmic variables in globular clusters

NASA Technical Reports Server (NTRS)

Di Stefano, R.; Rappaport, S.

1994-01-01

We have studied the number of cataclysmic variables (CVs) that should be active in globular clusters during the present epoch as a result of binary formation via two-body tidal capture. We predict the orbital period and luminosity distributions of CVs in globular clusters. The results arebased on Monte Carlo simulations combined with evolution calculations appropriate to each system formed during the lifetime of two specific globular clusters, omega Cen and 47 Tuc. From our study of these two clusters, which represent the range of core densities and states of mass segregation that are likely to be interesting, we extrapolate our results to the Galactic globlular cluster system. Although there is at present little direct observational evidence of CVs in globular clusters, we find that there should be a large number of active systems. We predict that there should be more than approximately 100 CVs in both 47 Tuc and omega Cen and several thousand in the Galactic globular cluster system. These numbers are based on two-body processes alone and represent a lower bound on the number of systems that may have been formed as a result of stellar interaction within globular clusters. The relation between these calculations and the paucity of optically detected CVs in globular clusters is discussed. Should future observations fail to find convincing evidence of a substantial population of cluster CVs, then the two-body tidal capture scenario is likely to be seriously constrained. Of the CVs we espect in 47 Tuc and omega Cen, approximately 45 and 20, respectively, should have accretion luminosities above 10(exp 33) ergs/s. If one utilizes a relation for converting accretion luminosity to hard X-ray luminosity that is based on observations of Galactic plane CVs, even these sources will not exhibit X-ray luminosities above 10(exp 33) ergs/s. While we cannot account directly for the most luminous subset of the low-luminosity globular cluster X-ray sources without assuming an evolutionary pattern that is different from that of the majority of CVs in the disk, we are able to account for all of the observed lower luminosity subset of these sources, many of which have been recently discovered through ROSAT observations. In order for our predicted integrated cluster X-ray luminosities to be consistent with observational upper limits, the relation between accretion and X-ray luminosities should be something like that inferred from the Galactic plane population of CVs. Our calculations predict a large number of systems with L(sub acc) is less than 10(exp 32) ergs/s. Although our calculations imply that globular clusters should have an enhancement of CVs relative to the number thought to be present in the Galactic disk, this enhancement is at most roughly an order of magnitude, not comparable to the factor of approximately 100 for low-mass X-ray binaries (LMXBs).

Reproductive pair correlations and the clustering of organisms.

PubMed

Young, W R; Roberts, A J; Stuhne, G

2001-07-19

Clustering of organisms can be a consequence of social behaviour, or of the response of individuals to chemical and physical cues. Environmental variability can also cause clustering: for example, marine turbulence transports plankton and produces chlorophyll concentration patterns in the upper ocean. Even in a homogeneous environment, nonlinear interactions between species can result in spontaneous pattern formation. Here we show that a population of independent, random-walking organisms ('brownian bugs'), reproducing by binary division and dying at constant rates, spontaneously aggregates. Using an individual-based model, we show that clusters form out of spatially homogeneous initial conditions without environmental variability, predator-prey interactions, kinesis or taxis. The clustering mechanism is reproductively driven-birth must always be adjacent to a living organism. This clustering can overwhelm diffusion and create non-poissonian correlations between pairs (parent and offspring) or organisms, leading to the emergence of patterns.

Lifestyle Patterns and Weight Status in Spanish Adults: The ANIBES Study.

PubMed

Pérez-Rodrigo, Carmen; Gianzo-Citores, Marta; Gil, Ángel; González-Gross, Marcela; Ortega, Rosa M; Serra-Majem, Lluis; Varela-Moreiras, Gregorio; Aranceta-Bartrina, Javier

2017-06-14

Limited knowledge is available on lifestyle patterns in Spanish adults. We investigated dietary patterns and possible meaningful clustering of physical activity, sedentary behavior, sleep time, and smoking in Spanish adults aged 18-64 years and their association with obesity. Analysis was based on a subsample ( n = 1617) of the cross-sectional ANIBES study in Spain. We performed exploratory factor analysis and subsequent cluster analysis of dietary patterns, physical activity, sedentary behaviors, sleep time, and smoking. Logistic regression analysis was used to explore the association between the cluster solutions and obesity. Factor analysis identified four dietary patterns, " Traditional DP ", " Mediterranean DP ", " Snack DP " and " Dairy-sweet DP ". Dietary patterns, physical activity behaviors, sedentary behaviors, sleep time, and smoking in Spanish adults aggregated into three different clusters of lifestyle patterns: " Mixed diet-physically active-low sedentary lifestyle pattern ", " Not poor diet-low physical activity-low sedentary lifestyle pattern " and " Poor diet-low physical activity-sedentary lifestyle pattern ". A higher proportion of people aged 18-30 years was classified into the " Poor diet-low physical activity-sedentary lifestyle pattern ". The prevalence odds ratio for obesity in men in the " Mixed diet-physically active-low sedentary lifestyle pattern " was significantly lower compared to those in the " Poor diet-low physical activity-sedentary lifestyle pattern ". Those behavior patterns are helpful to identify specific issues in population subgroups and inform intervention strategies. The findings in this study underline the importance of designing and implementing interventions that address multiple health risk practices, considering lifestyle patterns and associated determinants.

Evolution of Dengue Virus Type 3 Genotype III in Venezuela: Diversification, Rates and Population Dynamics

PubMed Central

2010-01-01

Background Dengue virus (DENV) is a member of the genus Flavivirus of the family Flaviviridae. DENV are comprised of four distinct serotypes (DENV-1 through DENV-4) and each serotype can be divided in different genotypes. Currently, there is a dramatic emergence of DENV-3 genotype III in Latin America. Nevertheless, we still have an incomplete understanding of the evolutionary forces underlying the evolution of this genotype in this region of the world. In order to gain insight into the degree of genetic variability, rates and patterns of evolution of this genotype in Venezuela and the South American region, phylogenetic analysis, based on a large number (n = 119) of envelope gene sequences from DENV-3 genotype III strains isolated in Venezuela from 2001 to 2008, were performed. Results Phylogenetic analysis revealed an in situ evolution of DENV-3 genotype III following its introduction in the Latin American region, where three different genetic clusters (A to C) can be observed among the DENV-3 genotype III strains circulating in this region. Bayesian coalescent inference analyses revealed an evolutionary rate of 8.48 × 10-4 substitutions/site/year (s/s/y) for strains of cluster A, composed entirely of strains isolated in Venezuela. Amino acid substitution at position 329 of domain III of the E protein (A→V) was found in almost all E proteins from Cluster A strains. Conclusions A significant evolutionary change between DENV-3 genotype III strains that circulated in the initial years of the introduction in the continent and strains isolated in the Latin American region in recent years was observed. The presence of DENV-3 genotype III strains belonging to different clusters was observed in Venezuela, revealing several introduction events into this country. The evolutionary rate found for Cluster A strains circulating in Venezuela is similar to the others previously established for this genotype in other regions of the world. This suggests a lack of correlation among DENV genotype III substitution rate and ecological pattern of virus spread. PMID:21087501

Statistics of voids in hierarchical universes

NASA Technical Reports Server (NTRS)

Fry, J. N.

1986-01-01

As one alternative to the N-point galaxy correlation function statistics, the distribution of holes or the probability that a volume of given size and shape be empty of galaxies can be considered. The probability of voids resulting from a variety of hierarchical patterns of clustering is considered, and these are compared with the results of numerical simulations and with observations. A scaling relation required by the hierarchical pattern of higher order correlation functions is seen to be obeyed in the simulations, and the numerical results show a clear difference between neutrino models and cold-particle models; voids are more likely in neutrino universes. Observational data do not yet distinguish but are close to being able to distinguish between models.

Patterns of Childhood Abuse and Neglect in a Representative German Population Sample

PubMed Central

Schilling, Christoph; Weidner, Kerstin; Brähler, Elmar; Glaesmer, Heide; Häuser, Winfried; Pöhlmann, Karin

2016-01-01

Background Different types of childhood maltreatment, like emotional abuse, emotional neglect, physical abuse, physical neglect and sexual abuse are interrelated because of their co-occurrence. Different patterns of childhood abuse and neglect are associated with the degree of severity of mental disorders in adulthood. The purpose of this study was (a) to identify different patterns of childhood maltreatment in a representative German community sample, (b) to replicate the patterns of childhood neglect and abuse recently found in a clinical German sample, (c) to examine whether participants reporting exposure to specific patterns of child maltreatment would report different levels of psychological distress, and (d) to compare the results of the typological approach and the results of a cumulative risk model based on our data set. Methods In a cross-sectional survey conducted in 2010, a representative random sample of 2504 German participants aged between 14 and 92 years completed the Childhood Trauma Questionnaire (CTQ). General anxiety and depression were assessed by standardized questionnaires (GAD-2, PHQ-2). Cluster analysis was conducted with the CTQ-subscales to identify different patterns of childhood maltreatment. Results Three different patterns of childhood abuse and neglect could be identified by cluster analysis. Cluster one showed low values on all CTQ-scales. Cluster two showed high values in emotional and physical neglect. Only cluster three showed high values in physical and sexual abuse. The three patterns of childhood maltreatment showed different degrees of depression (PHQ-2) and anxiety (GAD-2). Cluster one showed lowest levels of psychological distress, cluster three showed highest levels of mental distress. Conclusion The results show that different types of childhood maltreatment are interrelated and can be grouped into specific patterns of childhood abuse and neglect, which are associated with differing severity of psychological distress in adulthood. The results correspond to those recently found in a German clinical sample and support a typological approach in the research of maltreatment. While cumulative risk models focus on the number of maltreatment types, the typological approach takes the number as well as the severity of the maltreatment types into account. Thus, specific patterns of maltreatment can be examined with regard to specific long-term psychological consequences. PMID:27442446

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

PubMed

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

2014-01-01

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

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys

PubMed Central

Hund, Lauren; Bedrick, Edward J.; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis. PMID:26125967

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

PubMed

Hund, Lauren; Bedrick, Edward J; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

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

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

An updated survey of globular clusters in M 31. III. A spectroscopic metallicity scale for the Revised Bologna Catalog

NASA Astrophysics Data System (ADS)

Galleti, S.; Bellazzini, M.; Buzzoni, A.; Federici, L.; Fusi Pecci, F.

2009-12-01

Aims. We present a new homogeneous set of metallicity estimates based on Lick indices for the old globular clusters of the M 31 galaxy. The final aim is to add homogeneous spectroscopic metallicities to as many entries as possible of the Revised Bologna Catalog of M 31 clusters, by reporting Lick index measurements from any source (literature, new observations, etc.) on the same scale. Methods: New empirical relations of [Fe/H] as a function of [MgFe] and Mg2 indices are based on the well-studied galactic globular clusters, complemented with theoretical model predictions for -0.2≤ [Fe/H]≤ +0.5. Lick indices for M 31 clusters from various literature sources (225 clusters) and from new observations by our team (71 clusters) have been transformed into the Trager et al. system, yielding new metallicity estimates for 245 globular clusters of M 31. Results: Our values are in good agreement with recent estimates based on detailed spectral fitting and with those obtained from color magnitude diagrams of clusters imaged with the Hubble Space Telescope. The typical uncertainty on individual estimates is ≃±0.25 dex, as resulted from the comparison with metallicities derived from color magnitude diagrams of individual clusters. Conclusions: The metallicity distribution of M 31 globular cluster is briefly discussed and compared with that of the Milky Way. Simple parametric statistical tests suggest that the distribution is probably not unimodal. The strong correlation between metallicity and kinematics found in previous studies is confirmed. The most metal-rich GCs tend to be packed into the center of the system and to cluster tightly around the galactic rotation curve defined by the HI disk, while the velocity dispersion about the curve increases with decreasing metallicity. However, also the clusters with [Fe/H]<-1.0 display a clear rotation pattern, at odds with their Milky Way counterparts. Based on observations made at La Palma, at the Spanish Observatorio del Roque de los Muchachos of the IAC, with the William Herschel Telescope of the Isaac Newton Group and with the Italian Telescopio Nazionale Galileo (TNG) operated by the Fundación Galileo Galilei of INAF. Also based on observations made with the G.B. Cassini Telescope at Loiano (Italy), operated by the Osservatorio Astronomico di Bologna (INAF). Appendices are only available in electronic form at http://www.aanda.org

Combinatorial pattern discovery approach for the folding trajectory analysis of a beta-hairpin.

PubMed

Parida, Laxmi; Zhou, Ruhong

2005-06-01

The study of protein folding mechanisms continues to be one of the most challenging problems in computational biology. Currently, the protein folding mechanism is often characterized by calculating the free energy landscape versus various reaction coordinates, such as the fraction of native contacts, the radius of gyration, RMSD from the native structure, and so on. In this paper, we present a combinatorial pattern discovery approach toward understanding the global state changes during the folding process. This is a first step toward an unsupervised (and perhaps eventually automated) approach toward identification of global states. The approach is based on computing biclusters (or patterned clusters)-each cluster is a combination of various reaction coordinates, and its signature pattern facilitates the computation of the Z-score for the cluster. For this discovery process, we present an algorithm of time complexity c in RO((N + nm) log n), where N is the size of the output patterns and (n x m) is the size of the input with n time frames and m reaction coordinates. To date, this is the best time complexity for this problem. We next apply this to a beta-hairpin folding trajectory and demonstrate that this approach extracts crucial information about protein folding intermediate states and mechanism. We make three observations about the approach: (1) The method recovers states previously obtained by visually analyzing free energy surfaces. (2) It also succeeds in extracting meaningful patterns and structures that had been overlooked in previous works, which provides a better understanding of the folding mechanism of the beta-hairpin. These new patterns also interconnect various states in existing free energy surfaces versus different reaction coordinates. (3) The approach does not require calculating the free energy values, yet it offers an analysis comparable to, and sometimes better than, the methods that use free energy landscapes, thus validating the choice of reaction coordinates. (An abstract version of this work was presented at the 2005 Asia Pacific Bioinformatics Conference [1].).

a Three-Step Spatial-Temporal Clustering Method for Human Activity Pattern Analysis

NASA Astrophysics Data System (ADS)

Huang, W.; Li, S.; Xu, S.

2016-06-01

How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time) to four dimensions (space, time and semantics). More specifically, not only a location and time that people stay and spend are collected, but also what people "say" for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The results show that the approximate 55% spatiotemporal clusters distributed in different locations can be eventually grouped as the same type of clusters with consideration of semantic aspect.

Coherent tropical-subtropical Holocene see-saw moisture patterns in the Eastern Hemisphere monsoon systems

NASA Astrophysics Data System (ADS)

Wang, Yongbo; Bekeschus, Benjamin; Handorf, Dörthe; Liu, Xingqi; Dallmeyer, Anne; Herzschuh, Ulrike

2017-08-01

The concept of a Global Monsoon (GM) has been proposed based on modern precipitation observations, but its application over a wide range of temporal scales is still under debate. Here, we present a synthesis of 268 continental paleo-moisture records collected from monsoonal systems in the Eastern Hemisphere, including the East Asian Monsoon (EAsM), the Indian Monsoon (IM), the East African Monsoon (EAfM), and the Australian Monsoon (AuM) covering the last 18,000 years. The overall pattern of late Glacial to Holocene moisture change is consistent with those inferred from ice cores and marine records. With respect to the last 10,000 years (10 ka), i.e. a period that has high spatial coverage, a Fuzzy c-Means clustering analysis of the moisture index records together with ;Xie-Beni; index reveals four clusters of our data set. The paleoclimatic meaning of each cluster is interpreted considering the temporal evolution and spatial distribution patterns. The major trend in the tropical AuM, EAfM, and IM regions is a gradual decrease in moisture conditions since the early Holocene. Moisture changes in the EAsM regions show maximum index values between 8 and 6 ka. However, records located in nearby subtropical areas, i.e. in regions not influenced by the intertropical convergence zone, show an opposite trend compared to the tropical monsoon regions (AuM, EAfM and IM), i.e. a gradual increase. Analyses of modern meteorological data reveal the same spatial patterns as in the paleoclimate records such that, in times of overall monsoon strengthening, lower precipitation rates are observed in the nearby subtropical areas. We explain this pattern as the effect of a strong monsoon circulation suppressing air uplift in nearby subtropical areas, and hence hindering precipitation. By analogy to the modern system, this would mean that during the early Holocene strong monsoon period, the intensified ascending airflows within the monsoon domains led to relatively weaker ascending or even descending airflows in the adjacent subtropical regions, resulting in a precipitation deficit compared to the late Holocene. Our conceptual model therefore integrates regionally contrasting moisture changes into the Global Monsoon hypothesis.

Ultraviolet and infrared laser-induced fragmentation of free (CF{sub 3}I){sub n} clusters in a molecular beam and (CF{sub 3}I){sub n} clusters inside or on the surface of large (Xe){sub m} clusters

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

Apatin, V. M.; Lokhman, V. N.; Makarov, G. N., E-mail: gmakarov@isan.troitsk.ru

The fragmentation of free homogeneous (CF{sub 3}I){sub n} clusters in a molecular beam (n ≤ 45 is the average number of molecules in the cluster) and (CF{sub 3}I){sub n} clusters inside or on the surface of large (Xe){sub m} clusters (m ≥ 100 is the average number of atoms in the cluster) by ultraviolet and infrared laser radiations has been studied. These three types of (CF{sub 3}I){sub n} clusters are shown to have different stabilities with respect to fragmentation by both ultraviolet and infrared radiations and completely different dependences of the fragmentation probability on the energy of ultraviolet and infraredmore » radiations. When exposed to ultraviolet radiation, the free (CF{sub 3}I){sub n} clusters fragment at comparatively low fluences (Φ{sub UV} ≤ 0.15 J cm{sup −2}) and the weakest energy dependence of the fragmentation probability is observed for them. A stronger energy dependence of the fragmentation probability is observed for the (CF{sub 3}I){sub n} clusters localized inside (Xe){sub m} clusters, and the strongest dependence is observed for the (CF{sub 3}I){sub n} clusters located on the surface of (Xe){sub m} clusters. When the clusters are exposed to infrared radiation, the homogeneous (CF{sub 3}I){sub n} clusters efficiently fragment at low fluences (Φ{sub IR} ≤ 25 mJ cm{sup −2}), higher fluences (Φ{sub IR} ≈ 75 mJ cm{sup −2}) are needed for the fragmentation of the (CF{sub 3}I){sub n} localized inside (Xe){sub m} clusters, and even higher fluences (Φ{sub IR} ≈ 150 mJ cm{sup −2}) are needed for the fragmentation of the (CF{sub 3}I){sub n} clusters located on the surface of (Xe){sub m} clusters. It has been established that small (CF{sub 3}I){sub n} clusters located on the surface of (Xe){sub m} clusters do not fragment up to fluences Φ{sub IR} ≈ 250 mJ cm{sup −2}. The fragmentation efficiency of (CF{sub 3}I){sub n} clusters is shown to be the same (at the same fluence) when they are excited by both pulsed (τ{sub p} ≈ 150 ns) and continuous-wave infrared laser radiations. Possible causes of such a pattern of ultraviolet and infrared laser-induced fragmentation of these clusters are discussed.« less

G-protein coupled receptor expression patterns delineate medulloblastoma subgroups

PubMed Central

2013-01-01

Background Medulloblastoma is the most common malignant brain tumor in children. Genetic profiling has identified four principle tumor subgroups; each subgroup is characterized by different initiating mutations, genetic and clinical profiles, and prognoses. The two most well-defined subgroups are caused by overactive signaling in the WNT and SHH mitogenic pathways; less is understood about Groups 3 and 4 medulloblastoma. Identification of tumor subgroup using molecular classification is set to become an important component of medulloblastoma diagnosis and staging, and will likely guide therapeutic options. However, thus far, few druggable targets have emerged. G-protein coupled receptors (GPCRs) possess characteristics that make them ideal targets for molecular imaging and therapeutics; drugs targeting GPCRs account for 30-40% of all current pharmaceuticals. While expression patterns of many proteins in human medulloblastoma subgroups have been discerned, the expression pattern of GPCRs in medulloblastoma has not been investigated. We hypothesized that analysis of GPCR expression would identify clear subsets of medulloblastoma and suggest distinct GPCRs that might serve as molecular targets for both imaging and therapy. Results Our study found that medulloblastoma tumors fall into distinct clusters based solely on GPCR expression patterns. Normal cerebellum clustered separately from the tumor samples. Further, two of the tumor clusters correspond with high fidelity to the WNT and SHH subgroups of medulloblastoma. Distinct over-expressed GPCRs emerge; for example, LGR5 and GPR64 are significantly and uniquely over-expressed in the WNT subgroup of tumors, while PTGER4 is over-expressed in the SHH subgroup. Uniquely under-expressed GPCRs were also observed. Our key findings were independently validated using a large international dataset. Conclusions Our results identify GPCRs with potential to act as imaging and therapeutic targets. Elucidating tumorigenic pathways is a secondary benefit to identifying differential GPCR expression patterns in medulloblastoma tumors. PMID:24252460

Wavelet analysis of particle density functions in nucleus-nucleus interactions

NASA Astrophysics Data System (ADS)

Manna, S. K.; Haldar, P. K.; Mali, P.; Mukhopadhyay, A.; Singh, G.

A continuous wavelet analysis is performed for pattern recognition of the pseudorapidity density profile of singly charged particles produced in 16O+Ag/Br and 32S+Ag/Br interactions, each at an incident energy of 200 GeV per nucleon in the laboratory system. The experiments are compared with a model prediction based on the ultra-relativistic quantum molecular dynamics (UrQMD). To eliminate the contribution coming from known source(s) of particle cluster formation like Bose-Einstein correlation (BEC), the UrQMD output is modified by “an algorithm that mimics the BEC as an after burner.” We observe that for both interactions particle clusters are found at same pseudorapidity locations at all scales. However, the cluster locations in the 16O+Ag/Br interaction are different from those found in the 32S+Ag/Br interaction. Significant differences between experiments and simulations are revealed in the wavelet pseudorapidity spectra that can be interpreted as the preferred pseudorapidity values and/or scales of the pseudorapidity interval at which clusters of particles are formed. The observed discrepancy between experiment and corresponding simulation should therefore be interpreted in terms of some kind of nontrivial dynamics of multiparticle production.

Pattern selection and super-patterns in the bounded confidence model

DOE PAGES

Ben-Naim, E.; Scheel, A.

2015-10-26

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

Pattern selection and super-patterns in the bounded confidence model

NASA Astrophysics Data System (ADS)

Ben-Naim, E.; Scheel, A.

2015-10-01

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

Adenocarcinoma predominant pattern subtyping and nuclear grading in cytology: Is there a role in prognostication of advanced pulmonary adenocarcinomas?

PubMed

Nambirajan, A; Kaur, H; Jangra, K; Kaur, K; Madan, K; Mathur, S R; Iyer, V K; Jain, D

2018-04-01

Primary lung adenocarcinomas (ADs) show varied architectural patterns, and pattern-based subtyping of ADs is currently recommended due to prognostic implications. Predicting AD patterns on cytology is challenging; however, cytological nuclear features appear to correlate with histological grade and survival in early stage lung ADs. The feasibility and value of AD pattern prediction and nuclear grading on cytology in advanced lung ADs is not known. We aimed to predict patterns and analyse nuclear features on cytology and evaluate their role in prognostication. One-hundred patients of Stage III/IV lung AD with available matched cytology and histology samples were included. Cyto-patterns based on cell arrangement patterns (flat sheets vs three-dimensional clusters vs papillae) and cyto-nuclear score based on nuclear features (size, shape, contour), nucleoli (macronucleoli vs prominent vs inconspicuous), and nuclear chromatin were determined, and correlated with predominant histological-pattern observed on the matched small biopsy and outcome. Higher cyto-nuclear scores were observed with high-grade histo-patterns (solid, micropapillary and cribriform), while the predicted cyto-patterns did not correspond to the predominant pattern on histology in 77% cases. Highest cyto-histo agreement was observed for solid pattern (72%). High grade histo-patterns and cyto-nuclear scores > 3 showed a trend towards inferior survival (not significant). Nuclear grade scoring on cytology is simple to perform, and is predictive of high grade patterns. Its inclusion in routine reporting of cytology samples of lung ADs may be valuable. © 2018 John Wiley & Sons Ltd.

Do obesity-promoting food environments cluster around socially disadvantaged schools in Glasgow, Scotland?

PubMed

Ellaway, Anne; Macdonald, Laura; Lamb, Karen; Thornton, Lukar; Day, Peter; Pearce, Jamie

2012-11-01

Increase in the consumption of food and drinks outside the home by adolescents and young people and associations with rising levels of obesity is a significant concern worldwide and it has been suggested that the food environment around schools may be a contributory factor. As few studies have explored this issue in a UK setting, we examined whether different types of food outlets are clustered around public secondary schools in Glasgow, and whether this pattern differed by social disadvantage. We found evidence of clustering of food outlets around schools but a more complex picture in relation to deprivation was observed. Across all schools there were numerous opportunities for pupils to purchase energy dense foods locally and the implications for policy are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mapping similarities in temporal parking occupancy behavior based on city-wide parking meter data

NASA Astrophysics Data System (ADS)

Bock, Fabian; Xia, Karen; Sester, Monika

2018-05-01

The search for a parking space is a severe and stressful problem for drivers in many cities. The provision of maps with parking space occupancy information assists drivers in avoiding the most crowded roads at certain times. Since parking occupancy reveals a repetitive pattern per day and per week, typical parking occupancy patterns can be extracted from historical data. In this paper, we analyze city-wide parking meter data from Hannover, Germany, for a full year. We describe an approach of clustering these parking meters to reduce the complexity of this parking occupancy information and to reveal areas with similar parking behavior. The parking occupancy at every parking meter is derived from a timestamp of ticket payment and the validity period of the parking tickets. The similarity of the parking meters is computed as the mean-squared deviation of the average daily patterns in parking occupancy at the parking meters. Based on this similarity measure, a hierarchical clustering is applied. The number of clusters is determined with the Davies-Bouldin Index and the Silhouette Index. Results show that, after extensive data cleansing, the clustering leads to three clusters representing typical parking occupancy day patterns. Those clusters differ mainly in the hour of the maximum occupancy. In addition, the lo-cations of parking meter clusters, computed only based on temporal similarity, also show clear spatial distinctions from other clusters.

Multimorbidity patterns of and use of health services by Swedish 85-year-olds: an exploratory study

PubMed Central

2013-01-01

Background As life expectancy continues to rise, more elderly are reaching advanced ages (≥80 years). The increasing prevalence of multimorbidity places additional demands on health-care resources for the elderly. Previous studies noted the impact of multimorbidity on the use of health services, but the effects of multimorbidity patterns on health-service use have not been well studied, especially for very old people. This study determines patterns of multimorbidity associated with emergency-room visits and hospitalization in an 85-year-old population. Methods Health and living conditions were reported via postal questionnaire by 496 Linköping residents aged 85 years (189 men and 307 women). Diagnoses of morbidity were reviewed in patients’ case reports, and the local health-care register provided information on the use of health services. Hierarchical cluster analysis was applied to evaluate patterns of multimorbidity with gender stratification. Factors associated with emergency-room visits and hospitalization were analyzed using logistic regression models. Results Cluster analyses revealed five clusters: vascular, cardiopulmonary, cardiac (only for men), somatic–mental (only for men), mental disease (only for women), and three other clusters related to aging (one for men and two for women). Heart failure in men (OR = 2.4, 95% CI = 1–5.7) and women (OR = 3, 95% CI = 1.3–6.9) as a single morbidity explained more variance than morbidity clusters in models of emergency-room visits. Men's cardiac cluster (OR = 1.6; 95% CI = 1–2.7) and women's cardiopulmonary cluster (OR = 1.7, 95% CI = 1.2–2.4) were significantly associated with hospitalization. The combination of the cardiopulmonary cluster with the men’s cardiac cluster (OR = 1.6, 95% CI = 1–2.4) and one of the women’s aging clusters (OR = 0.5, 95% CI = 0.3–0.8) showed interaction effects on hospitalization. Conclusion In this 85-year-old population, patterns of cardiac and pulmonary conditions were better than a single morbidity in explaining hospitalization. Heart failure was superior to multimorbidity patterns in explaining emergency-room visits. A holistic approach to examining the patterns of multimorbidity and their relationships with the use of health services will contribute to both local health care policy and geriatric practice. PMID:24195643

Mycobacterial interspersed repetitive unit typing and mutational profile for multidrug-resistant and extensively drug-resistant tuberculosis surveillance in Portugal: a 3-year period overview.

PubMed

Silva, Carla; Perdigão, João; Jordão, Luísa; Portugal, Isabel

2014-12-01

Multidrug tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) cases constitute a serious health problem in Portugal, of which the majority of isolates belong to the Lisboa family and the Q1 cluster, highly related to the Lisboa family. Here we sought to investigate the molecular basis of resistant TB as well as to determine the prevalence of specific drug resistance mutations and their association with MDR-TB and/or XDR-TB. In total, 74 Mycobacterium tuberculosis clinical isolates collected in Lisbon Health Region were genotyped by 24-loci mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR), and the mutational profile associated with first- and second-line drug resistance was studied. Seven new mutations were found, whilst the remaining 28 mutations had been previously associated with drug resistance. None of the mutations was specifically associated with MDR-TB. The mutational patterns observed among isolates belonging to Lisboa3 and Q1 clusters were also observed in isolates with unique MIRU-VNTR patterns but closely related to these strains. Such data suggest that the genotyping technique employed discriminates isolates with the same mutational profile. To establish the most adequate genotyping technique, the discriminatory power of three different MIRU-VNTR sets was analysed. The 15-loci MIRU-VNTR set showed adequate discriminatory power, comparable with the 24-loci set, allowing clustering of 60% and 86% of the MDR-TB and XDR-TB isolates, respectively, the majority of which belonged to the Lisboa3 and Q1 clusters. From an epidemiological standpoint, this study suggests combined mutational and genotyping analysis as a valuable tool for drug resistance surveillance. Copyright © 2014 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

Classification of mechanisms, climatic context, areal scaling, and synchronization of floods: the hydroclimatology of floods in the Upper Paraná River basin, Brazil

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; AghaKouchak, Amir; Lall, Upmanu

2017-12-01

Floods are the main natural disaster in Brazil, causing substantial economic damage and loss of life. Studies suggest that some extreme floods result from a causal climate chain. Exceptional rain and floods are determined by large-scale anomalies and persistent patterns in the atmospheric and oceanic circulations, which influence the magnitude, extent, and duration of these extremes. Moreover, floods can result from different generating mechanisms. These factors contradict the assumptions of homogeneity, and often stationarity, in flood frequency analysis. Here we outline a methodological framework based on clustering using self-organizing maps (SOMs) that allows the linkage of large-scale processes to local-scale observations. The methodology is applied to flood data from several sites in the flood-prone Upper Paraná River basin (UPRB) in southern Brazil. The SOM clustering approach is employed to classify the 6-day rainfall field over the UPRB into four categories, which are then used to classify floods into four types based on the spatiotemporal dynamics of the rainfall field prior to the observed flood events. An analysis of the vertically integrated moisture fluxes, vorticity, and high-level atmospheric circulation revealed that these four clusters are related to known tropical and extratropical processes, including the South American low-level jet (SALLJ); extratropical cyclones; and the South Atlantic Convergence Zone (SACZ). Persistent anomalies in the sea surface temperature fields in the Pacific and Atlantic oceans are also found to be associated with these processes. Floods associated with each cluster present different patterns in terms of frequency, magnitude, spatial variability, scaling, and synchronization of events across the sites and subbasins. These insights suggest new directions for flood risk assessment, forecasting, and management.

THE ROLE OF THERMOHALINE MIXING IN INTERMEDIATE- AND LOW-METALLICITY GLOBULAR CLUSTERS

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

Angelou, George C.; Stancliffe, Richard J.; Church, Ross P.

It is now widely accepted that globular cluster red giant branch (RGB) stars owe their strange abundance patterns to a combination of pollution from progenitor stars and in situ extra mixing. In this hybrid theory a first generation of stars imprints abundance patterns into the gas from which a second generation forms. The hybrid theory suggests that extra mixing is operating in both populations and we use the variation of [C/Fe] with luminosity to examine how efficient this mixing is. We investigate the observed RGBs of M3, M13, M92, M15, and NGC 5466 as a means to test a theorymore » of thermohaline mixing. The second parameter pair M3 and M13 are of intermediate metallicity and our models are able to account for the evolution of carbon along the RGB in both clusters, although in order to fit the most carbon-depleted main-sequence stars in M13 we require a model whose initial [C/Fe] abundance leads to a carbon abundance lower than is observed. Furthermore, our results suggest that stars in M13 formed with some primary nitrogen (higher C+N+O than stars in M3). In the metal-poor regime only NGC 5466 can be tentatively explained by thermohaline mixing operating in multiple populations. We find thermohaline mixing unable to model the depletion of [C/Fe] with magnitude in M92 and M15. It appears as if extra mixing is occurring before the luminosity function bump in these clusters. To reconcile the data with the models would require first dredge-up to be deeper than found in extant models.« less

A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

US Household Food Shopping Patterns: Dynamic Shifts Since 2000 And Socioeconomic Predictors.

PubMed

Stern, Dalia; Robinson, Whitney R; Ng, Shu Wen; Gordon-Larsen, Penny; Popkin, Barry M

2015-11-01

Under the assumption that differential food access might underlie nutritional disparities, programs and policies have focused on the need to build supermarkets in underserved areas, in an effort to improve dietary quality. However, there is limited evidence about which types of stores are used by households of different income levels and differing races/ethnicities. We used cross-sectional cluster analysis to derive shopping patterns from US households' volume food purchases by store from 2000 to 2012. Multinomial logistic regression identified household socioeconomic characteristics that were associated with shopping patterns in 2012. We found three food shopping patterns or clusters: households that primarily shopped at grocery stores, households that primarily shopped at mass merchandisers, and a combination cluster in which households split their purchases among multiple store types. In 2012 we found no income or race/ethnicity differences for the cluster of households that primarily shopped at grocery stores. However, low-income non-Hispanic blacks (versus non-Hispanic whites) had a significantly lower probability of belonging to the mass merchandise cluster. These varied shopping patterns must be considered in future policy initiatives. Furthermore, it is important to continue studying the complex rationales for people's food shopping patterns. Project HOPE—The People-to-People Health Foundation, Inc.

Strong genetic differentiation in tropical seagrass Enhalus acoroides (Hydrocharitaceae) at the Indo-Malay Archipelago revealed by microsatellite DNA.

PubMed

Putra, I Nyoman Giri; Syamsuni, Yuliana Fitri; Subhan, Beginer; Pharmawati, Made; Madduppa, Hawis

2018-01-01

The Indo-Malay Archipelago is regarded as a barrier that separates organisms of the Indian and Pacific Oceans. Previous studies of marine biota from this region have found a variety of biogeographic barriers, seemingly dependent on taxon and methodology. Several hypotheses, such as emergence of the Sunda Shelf and recent physical oceanography, have been proposed to account for the genetic structuring of marine organisms in this region. Here, we used six microsatellite loci to infer genetic diversity, population differentiation and phylogeographic patterns of Enhalus acoroides across the Indo-Malay Archipelago. Heterozygosities were consistently high, and significant isolation-by-distance, consistent with restricted gene flow, was observed. Both a neighbour joining tree based on D A distance and Bayesian clustering revealed three major clusters of E. acoroides . Our results indicate that phylogeographic patterns of E. acoroides have possibly been influenced by glaciation and deglaciation during the Pleistocene. Recent physical oceanography such as the South Java Current and the Seasonally Reversing Current may also play a role in shaping the genetic patterns of E. acoroides .

Strong genetic differentiation in tropical seagrass Enhalus acoroides (Hydrocharitaceae) at the Indo-Malay Archipelago revealed by microsatellite DNA

PubMed Central

Putra, I Nyoman Giri; Syamsuni, Yuliana Fitri; Subhan, Beginer; Pharmawati, Made

2018-01-01

The Indo-Malay Archipelago is regarded as a barrier that separates organisms of the Indian and Pacific Oceans. Previous studies of marine biota from this region have found a variety of biogeographic barriers, seemingly dependent on taxon and methodology. Several hypotheses, such as emergence of the Sunda Shelf and recent physical oceanography, have been proposed to account for the genetic structuring of marine organisms in this region. Here, we used six microsatellite loci to infer genetic diversity, population differentiation and phylogeographic patterns of Enhalus acoroides across the Indo-Malay Archipelago. Heterozygosities were consistently high, and significant isolation-by-distance, consistent with restricted gene flow, was observed. Both a neighbour joining tree based on DA distance and Bayesian clustering revealed three major clusters of E. acoroides. Our results indicate that phylogeographic patterns of E. acoroides have possibly been influenced by glaciation and deglaciation during the Pleistocene. Recent physical oceanography such as the South Java Current and the Seasonally Reversing Current may also play a role in shaping the genetic patterns of E. acoroides. PMID:29576933

The Future of Wind Energy in California: Future Projections in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Wang, M.; Ullrich, P. A.; Millstein, D.; Collier, C.

2017-12-01

This study focuses on the wind energy characterization and future projection at five primary wind turbine sites in California. Historical (1980-2000) and mid-century (2030-2050) simulations were produced using the Variable-Resolution Community Earth System Model (VR-CESM) to analyze the trends and variations in wind energy under climate change. Datasets from Det Norske Veritas Germanischer Llyod (DNV GL), MERRA-2, CFSR, NARR, as well as surface observational data were used for model validation and comparison. Significant seasonal wind speed changes under RCP8.5 were detected from several wind farm sites. Large-scale patterns were then investigated to analyze the synoptic-scale impact on localized wind change. The agglomerative clustering method was applied to analyze and group different wind patterns. The associated meteorological background of each cluster was investigated to analyze the drivers of different wind patterns. This study improves the characterization of uncertainty around the magnitude and variability in space and time of California's wind resources in the near future, and also enhances understanding of the physical mechanisms related to the trends in wind resource variability.

Profiling children's emotion regulation behaviours.

PubMed

Callear, Angela; Harvey, Shane T; Bimler, David; Catto, Nicholas

2018-02-20

Callear, Harvey, and Bimler (2016, International Journal of Behavioral Development, 41, 456) organized children's emotion regulation behaviours into a coherent structure. However, further investigation is needed to identify core patterns of these emotion regulation behaviours. To identify clusters and prototypal constellations of emotion regulation behaviours, the 85 behavioural items comprising the Children's Emotion Regulation Inventory (ChERI) were ranked by 151 parents in order of applicability, using an ordinal sorting procedure (Method of Successive Sorts). Responses were aggregated in empirical scales, for classification of the cases using hierarchical and k-means clustering. The scales were based on nine key 'hotspots' of children's emotion regulation behaviours, interpreted as Outward Engagement, Inward or Somatic Focus, Disengagement, Disruptive, Impulsive/Labile, Social Connectedness/Compliance, Generating Closeness/Intimacy, Establishing Order and Generating Disorder. Five summary styles of children's emotion regulation emerged and are characterized on those scales. These hotspots and styles provide guidance to clinicians, parents, teachers, and other invested adults to assess and support children's emotional development. Statement of contribution What is already known on this subject? Measurements of children's emotion regulation predominantly focus on internal processes and/or isolated expressions of emotion regulation behaviours. Research detailing anger and anxiety emotion regulation styles exists (e.g., Carthy, Horesh, Apter, & Gross, 2010, Journal of Psychopathology and Behavioral Assessment, 32, 23; Zalewski, Lengua, Wilson, Trancik, & Bazinet, 2011, Journal of Experimental Child Psychology, 110, 141). Callear, Harvey, and Bimler (2016, International Journal of Behavioral Development, 41, 456) developed the Children's Emotion Regulation Inventory to identify children's observable emotion regulation strategies. What does this study add? Research does not investigate which clusters of children's emotion regulation behaviours are most commonly exhibited and nor does it investigate emotion regulation behavioural styles. Examines how children's emotion regulation behaviours co-occur. Identifies nine core clusters (groupings) of emotion regulation behaviours most commonly observed to be exhibited in children. Identifies five emotion regulation behavioural styles (common co-occurring patterns of emotion regulation behaviour clusters) in children. © 2018 The British Psychological Society.

Spatial ecology of refuge selection by an herbivore under risk of predation

USGS Publications Warehouse

Wilson, Tammy L.; Rayburn, Andrew P.; Edwards, Thomas C.

2012-01-01

Prey species use structures such as burrows to minimize predation risk. The spatial arrangement of these resources can have important implications for individual and population fitness. For example, there is evidence that clustered resources can benefit individuals by reducing predation risk and increasing foraging opportunity concurrently, which leads to higher population density. However, the scale of clustering that is important in these processes has been ignored during theoretical and empirical development of resource models. Ecological understanding of refuge exploitation by prey can be improved by spatial analysis of refuge use and availability that incorporates the effect of scale. We measured the spatial distribution of pygmy rabbit (Brachylagus idahoensis) refugia (burrows) through censuses in four 6-ha sites. Point pattern analyses were used to evaluate burrow selection by comparing the spatial distribution of used and available burrows. The presence of food resources and additional overstory cover resources was further examined using logistic regression. Burrows were spatially clustered at scales up to approximately 25 m, and then regularly spaced at distances beyond ~40 m. Pygmy rabbit exploitation of burrows did not match availability. Burrows used by pygmy rabbits were likely to be located in areas with high overall burrow density (resource clusters) and high overstory cover, which together minimized predation risk. However, in some cases we observed an interaction between either overstory cover (safety) or understory cover (forage) and burrow density. The interactions show that pygmy rabbits will use burrows in areas with low relative burrow density (high relative predation risk) if understory food resources are high. This points to a potential trade-off whereby rabbits must sacrifice some safety afforded by additional nearby burrows to obtain ample forage resources. Observed patterns of clustered burrows and non-random burrow use improve understanding of the importance of spatial distribution of refugia for burrowing herbivores. The analyses used allowed for the estimation of the spatial scale where subtle trade-offs between predation avoidance and foraging opportunity are likely to occur in a natural system.

On the missing second generation AGB stars in NGC 6752

NASA Astrophysics Data System (ADS)

Cassisi, Santi; Salaris, Maurizio; Pietrinferni, Adriano; Vink, Jorick S.; Monelli, Matteo

2014-11-01

In recent years the view of Galactic globular clusters as simple stellar populations has changed dramatically, it is now thought that basically all globular clusters host multiple stellar populations, each with its own chemical abundance pattern and colour-magnitude diagram sequence. Recent spectroscopic observations of asymptotic giant branch stars in the globular cluster NGC 6752 have disclosed a low [Na/Fe] abundance for the whole sample, suggesting that they are all first generation stars, and that all second generation stars fail to reach the AGB in this cluster. A scenario proposed to explain these observations invokes strong mass loss in second generation horizontal branch stars - all located at the hot side of the blue and extended horizontal branch of this cluster - possibly induced by the metal enhancement associated to radiative levitation. This enhanced mass loss would prevent second generation stars from reaching the asymptotic giant branch phase, thus explaining at the same time the low value of the ratio between horizontal branch and asymptotic giant branch stars (the R2 parameter) observed in NGC 6752. We have critically discussed this mass-loss scenario, finding that the required mass-loss rates are of the order of 10-9 M⊙ yr-1, significantly higher than current theoretical and empirical constraints. By making use of synthetic horizontal branch simulations, we demonstrate that our modelling correctly predicts the R2 parameter for NGC 6752, without the need to invoke very efficient mass loss during the core He-burning stage. As a test of our stellar models we show that we can reproduce the observed value of R2 for both M 3, a cluster of approximately the same metallicity and with a redder horizontal branch morphology, and M 13, a cluster with a horizontal branch very similar to NGC 6752. However, our simulations for the NGC 6752 horizontal branch predict however the presence of a significant fraction of second generation stars (about 50%) along the cluster asymptotic giant branch. We conclude that there is no simple explanation for the lack of second generation stars in the spectroscopically surveyed sample, although the interplay between mass loss (with low rates) and radiative levitation may play a role in explaining this puzzle.

Scaling Linguistic Characterization of Precipitation Variability

NASA Astrophysics Data System (ADS)

Primo, C.; Gutierrez, J. M.

2003-04-01

Rainfall variability is influenced by changes in the aggregation of daily rainfall. This problem is of great importance for hydrological, agricultural and ecological applications. Rainfall averages, or accumulations, are widely used as standard climatic parameters. However different aggregation schemes may lead to the same average or accumulated values. In this paper we present a fractal method to characterize different aggregation schemes. The method provides scaling exponents characterizing weekly or monthly rainfall patterns for a given station. To this aim, we establish an analogy with linguistic analysis, considering precipitation as a discrete variable (e.g., rain, no rain). Each weekly, or monthly, symbolic precipitation sequence of observed precipitation is then considered as a "word" (in this case, a binary word) which defines a specific weekly rainfall pattern. Thus, each site defines a "language" characterized by the words observed in that site during a period representative of the climatology. Then, the more variable the observed weekly precipitation sequences, the more complex the obtained language. To characterize these languages, we first applied the Zipf's method obtaining scaling histograms of rank ordered frequencies. However, to obtain significant exponents, the scaling must be maintained some orders of magnitude, requiring long sequences of daily precipitation which are not available at particular stations. Thus this analysis is not suitable for applications involving particular stations (such as regionalization). Then, we introduce an alternative fractal method applicable to data from local stations. The so-called Chaos-Game method uses Iterated Function Systems (IFS) for graphically representing rainfall languages, in a way that complex languages define complex graphical patterns. The box-counting dimension and the entropy of the resulting patterns are used as linguistic parameters to quantitatively characterize the complexity of the patterns. We illustrate the high climatological discrimination power of the linguistic parameters in the Iberian peninsula, when compared with other standard techniques (such as seasonal mean accumulated precipitation). As an example, standard and linguistic parameters are used as inputs for a clustering regionalization method, comparing the resulting clusters.

Storyline Visualizations of Eye Tracking of Movie Viewing

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

Balint, John T.; Arendt, Dustin L.; Blaha, Leslie M.

Storyline visualizations offer an approach that promises to capture the spatio-temporal characteristics of individual observers and simultaneously illustrate emerging group behaviors. We develop a visual analytics approach to parsing, aligning, and clustering fixation sequences from eye tracking data. Visualization of the results captures the similarities and differences across a group of observers performing a common task. We apply our storyline approach to visualize gaze patterns of people watching dynamic movie clips. Storylines mitigate some of the shortcomings of existent spatio-temporal visualization techniques and, importantly, continue to highlight individual observer behavioral dynamics.

Pattern-formation mechanisms in motility mutants of Myxococcus xanthus

PubMed Central

Starruß, Jörn; Peruani, Fernando; Jakovljevic, Vladimir; Søgaard-Andersen, Lotte; Deutsch, Andreas; Bär, Markus

2012-01-01

Formation of spatial patterns of cells is a recurring theme in biology and often depends on regulated cell motility. Motility of the rod-shaped cells of the bacterium Myxococcus xanthus depends on two motility machineries, type IV pili (giving rise to S-motility) and the gliding motility apparatus (giving rise to A-motility). Cell motility is regulated by occasional reversals. Moving M. xanthus cells can organize into spreading colonies or spore-filled fruiting bodies, depending on their nutritional status. To ultimately understand these two pattern-formation processes and the contributions by the two motility machineries, as well as the cell reversal machinery, we analyse spatial self-organization in three M. xanthus strains: (i) a mutant that moves unidirectionally without reversing by the A-motility system only, (ii) a unidirectional mutant that is also equipped with the S-motility system, and (iii) the wild-type that, in addition to the two motility systems, occasionally reverses its direction of movement. The mutant moving by means of the A-engine illustrates that collective motion in the form of large moving clusters can arise in gliding bacteria owing to steric interactions of the rod-shaped cells, without the need of invoking any biochemical signal regulation. The two-engine strain mutant reveals that the same phenomenon emerges when both motility systems are present, and as long as cells exhibit unidirectional motion only. From the study of these two strains, we conclude that unidirectional cell motion induces the formation of large moving clusters at low and intermediate densities, while it results in vortex formation at very high densities. These findings are consistent with what is known from self-propelled rod models, which strongly suggests that the combined effect of self-propulsion and volume exclusion interactions is the pattern-formation mechanism leading to the observed phenomena. On the other hand, we learn that when cells occasionally reverse their moving direction, as observed in the wild-type, cells form small but strongly elongated clusters and self-organize into a mesh-like structure at high enough densities. These results have been obtained from a careful analysis of the cluster statistics of ensembles of cells, and analysed in the light of a coagulation Smoluchowski equation with fragmentation. PMID:24312730

Application of Clustering Algorithms to Observed and Simulated Daily Precipitation over the Tropical and Southern Pacific Ocean

NASA Astrophysics Data System (ADS)

Pike, M.; Lintner, B. R.

2017-12-01

We apply two data organization methods, self-organizing maps (SOMs) and k-means clustering with linear unidimensional scaling (k-means+LUS), to identify and organize the spatial patterns inherent in daily austral summer (December-January-February or DJF) rainfall over the tropical and southern Pacific Ocean basins from Tropical Rainfall Measuring Mission (TRMM) satellite observations. For either a 2x2 SOM or k = 4 clustering of all available DJFs from 1998-2013, we find an El Niño/Southern Oscillation (ENSO) signature, with pairs of maps reflecting either El Niño or La Niña phase conditions. Within each of the ENSO-phase pairs, one map favors Intertropical Convergence Zone (ITCZ)-active conditions, in which precipitation is more intense over the ITCZ region compared to the South Pacific Convergence Zone (SPCZ) region, while the remaining one is SPCZ-active. The SPCZ-active maps show a spatial translation of the principal SPCZ diagonal consistent with the impacts of El Niño/Southern Oscillation (ENSO) or analogous low-frequency modes of variability on the SPCZ as shown in prior studies. Because of the dominant impact of ENSO, we further apply these methods separately on subsets of rainfall data for each ENSO phase. While the overall position of the SPCZ is sensitive to the phase of ENSO, within each phase, more- or less-steeply sloped SPCZ diagonals may occur. Thus, while the mean position of the SPCZ is largely controlled by ENSO phase, the distinct orientations of the SPCZ within the same ENSO phase point to higher-frequency modulation of SPCZ slope. To investigate the nature of these further, we construct composites of pressure-level winds and specific humidity from the Climate Forecast System Reanalysis (CFSR) associated with the rainfall patterns. For either SOM or kmeans-based composites, we find large-scale dynamics and moisture signatures that are consistent with the rainfall patterns and which we interpret in terms of previously described mechanisms of SPCZ variability. By progressively increasing the number of clusters, patterns reminiscent of Rossby wave propagation begin to emerge. To further investigate the connection to propagation, we examine upper air vorticity composites in relationship to the periodic enhancements of SPCZ precipitation which appear to be independent of ENSO.

Analysis of ambient SO 2 concentrations and winds in the complex surroundings of a thermal power plant

NASA Astrophysics Data System (ADS)

Mlakar, P.

2004-11-01

SO2 pollution is still a significant problem in Slovenia, especially around large thermal power plants (TPPs), like the one at Šoštanj. The Šoštanj TPP is the exclusive source of SO2 in the area and is therefore a perfect example for air pollution studies. In order to understand air pollution around the Šoštanj TPP in detail, some analyses of emissions and ambient concentrations of SO2 at six automated monitoring stations in the surroundings of the TPP were made. The data base from 1991 to 1993 was used when there were no desulfurisation plants in operation. Statistical analyses of the influence of the emissions from the three TPP stacks at different measuring points were made. The analyses prove that the smallest stack (100 m) mainly pollutes villages and towns near the TPP within a radius of a few kilometres. The medium stack's (150 m) influence is noticed at shorter as well as at longer distances up to more than ten kilometres. The highest stack (230 m) pollutes mainly at longer distances, where the plume reaches the higher hills. Detailed analyses of ambient SO2 concentrations were made. They show the temporal and spatial distribution of different classes of SO2 concentrations from very low to alarming values. These analyses show that pollution patterns at a particular station remain the same if observed on a yearly basis, but can vary very much if observed on a monthly basis, mainly because of different weather patterns. Therefore the winds in the basin (as the most important feature influencing air pollution dispersion) were further analysed in detail to find clusters of similar patterns. For cluster analysis of ground-level winds patterns in the basin around the Šoštanj Thermal Power Plant, the Kohonen neural network and Leaders' method were used. Furthermore, the dependence of ambient SO2 concentrations on the clusters obtained was analysed. The results proved that effective cluster analysis can be a useful tool for compressing a huge wind data base in order to find the correlation between winds and pollutant concentrations. The analyses made provide a better insight into air pollution over complex terrain.

Lymphohaematopoietic system cancer incidence in an urban area near a coke oven plant: an ecological investigation

PubMed Central

Parodi, S; Vercelli, M; Stella, A; Stagnaro, E; Valerio, F

2003-01-01

Aims: To evaluate the incidence risk of lymphohaematopoietic cancers for the 1986–94 period in Cornigliano, a district of Genoa (Italy), where a coke oven is located a few hundred metres from the residential area. Methods: The whole of Genoa and one of its 25 districts (Rivarolo) were selected as controls. The trend of risk around the coke oven was evaluated via Stone's method, while the geographic pattern of such risks across the Cornigliano district was evaluated by computing full Bayes estimates of standardised incidence ratio (FBE-SIR). Results: In males, elevated relative risks (RR) were observed for all lymphohaematopoietic cancers (RR 1.7 v Rivarolo and 1.6 v Genoa), for NHL (RR 2.4 v Rivarolo and 1.7 v Genoa), and for leukaemia (RR 2.4 v Rivarolo and 1.9 v Genoa). In females, statistically non-significant RR were observed. In males no excess of risk was found close to the coke oven. In females, a rising risk for NHL was observed approaching the plant, although statistical significance was not reached, while the risk for leukaemia was not evaluable due to the small number of cases. Analysis of the geographic pattern of risk suggested the presence of a cluster of NHL in both sexes in the eastern part of the district, where a foundry had been operational until the early 1980s. A cluster of leukaemia cases was observed in males in a northern part of the area, where no major sources of benzene seemed to be present. Conclusions: The estimated risks seem to be slightly or not at all related to the distance from the coke oven. The statistically significant higher risks observed in males for NHL and leukaemia, and the clusters of leukaemia in males and of NHL in both sexes deserve further investigations in order to trace the exposures associated with such risks. PMID:12598665

LITHIUM DEPLETION IS A STRONG TEST OF CORE-ENVELOPE RECOUPLING

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

Somers, Garrett; Pinsonneault, Marc H., E-mail: somers@astronomy.ohio-state.edu

2016-09-20

Rotational mixing is a prime candidate for explaining the gradual depletion of lithium from the photospheres of cool stars during the main sequence. However, previous mixing calculations have relied primarily on treatments of angular momentum transport in stellar interiors incompatible with solar and stellar data in the sense that they overestimate the internal differential rotation. Instead, recent studies suggest that stars are strongly differentially rotating at young ages but approach a solid body rotation during their lifetimes. We modify our rotating stellar evolution code to include an additional source of angular momentum transport, a necessary ingredient for explaining the openmore » cluster rotation pattern, and examine the consequences for mixing. We confirm that core-envelope recoupling with a ∼20 Myr timescale is required to explain the evolution of the mean rotation pattern along the main sequence, and demonstrate that it also provides a more accurate description of the Li depletion pattern seen in open clusters. Recoupling produces a characteristic pattern of efficient mixing at early ages and little mixing at late ages, thus predicting a flattening of Li depletion at a few Gyr, in agreement with the observed late-time evolution. Using Li abundances we argue that the timescale for core-envelope recoupling during the main sequence decreases sharply with increasing mass. We discuss the implications of this finding for stellar physics, including the viability of gravity waves and magnetic fields as agents of angular momentum transport. We also raise the possibility of intrinsic differences in initial conditions in star clusters using M67 as an example.« less

Microfluidic cell trap array for controlled positioning of single cells on adhesive micropatterns.

PubMed

Lin, Laiyi; Chu, Yeh-Shiu; Thiery, Jean Paul; Lim, Chwee Teck; Rodriguez, Isabel

2013-02-21

Adhesive micropattern arrays permit the continuous monitoring and systematic study of the behavior of spatially confined cells of well-defined shape and size in ordered configurations. This technique has contributed to defining mechanisms that control cell polarity and cell functions, including proliferation, apoptosis, differentiation and migration in two-dimensional cell culture systems. These micropattern studies often involve isolating a single cell on one adhesive protein micropattern using random seeding methods. Random seeding has been successful for isolated and, to a lesser degree, paired patterns, where two patterns are placed in close proximity. Using this method, we found that the probability of obtaining one cell per pattern decreases significantly as the number of micropatterns in a cluster increases, from 16% for paired micropatterns to 0.3% for clusters of 6 micropatterns. This work presents a simple yet effective platform based on a microfludic sieve-like trap array to exert precise control over the positioning of single cells on micropatterns. We observed a 4-fold improvement over random seeding in the efficiency of placing a pair of single cells on paired micropattern and a 40-fold improvement for 6-pattern clusters. The controlled nature of this platform can also allow the juxtaposition of two different cell populations through a simple modification in the trap arrangement. With excellent control of the identity, number and position of neighbouring cells, this cell-positioning platform provides a unique opportunity for the extension of two-dimensional micropattern studies beyond paired micropatterns to organizations containing many cells or different cell types.

Evaporation-driven clustering of microscale pillars and lamellae

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

Kim, Tae-Hong; Kim, Jungchul; Kim, Ho-Young, E-mail: hyk@snu.ac.kr

As a liquid film covering an array of micro- or nanoscale pillars or lamellae evaporates, its meniscus pulls the elastic patterns together because of capillary effects, leading to clustering of the slender microstructures. While this elastocapillary coalescence may imply various useful applications, it is detrimental to a semiconductor manufacturing process called the spin drying, where a liquid film rinses patterned wafers until drying. To understand the transient mechanism underlying such self-organization during and after liquid evaporation, we visualize the clustering dynamics of polymer micropatterns. Our visualization experiments reveal that the patterns clumped during liquid evaporation can be re-separated when completelymore » dried in some cases. This restoration behavior is explained by considering adhesion energy of the patterns as well as capillary forces, which leads to a regime map to predict whether permanent stiction would occur. This work does not only extend our understanding of micropattern stiction, but also suggests a novel path to control and prevent pattern clustering.« less

Quantitative estimation of time-variable earthquake hazard by using fuzzy set theory

NASA Astrophysics Data System (ADS)

Deyi, Feng; Ichikawa, M.

1989-11-01

In this paper, the various methods of fuzzy set theory, called fuzzy mathematics, have been applied to the quantitative estimation of the time-variable earthquake hazard. The results obtained consist of the following. (1) Quantitative estimation of the earthquake hazard on the basis of seismicity data. By using some methods of fuzzy mathematics, seismicity patterns before large earthquakes can be studied more clearly and more quantitatively, highly active periods in a given region and quiet periods of seismic activity before large earthquakes can be recognized, similarities in temporal variation of seismic activity and seismic gaps can be examined and, on the other hand, the time-variable earthquake hazard can be assessed directly on the basis of a series of statistical indices of seismicity. Two methods of fuzzy clustering analysis, the method of fuzzy similarity, and the direct method of fuzzy pattern recognition, have been studied is particular. One method of fuzzy clustering analysis is based on fuzzy netting, and another is based on the fuzzy equivalent relation. (2) Quantitative estimation of the earthquake hazard on the basis of observational data for different precursors. The direct method of fuzzy pattern recognition has been applied to research on earthquake precursors of different kinds. On the basis of the temporal and spatial characteristics of recognized precursors, earthquake hazards in different terms can be estimated. This paper mainly deals with medium-short-term precursors observed in Japan and China.

Beverage Consumption Patterns at Age 13 to 17 Years Are Associated with Weight, Height, and Body Mass Index at Age 17 Years.

PubMed

Marshall, Teresa A; Van Buren, John M; Warren, John J; Cavanaugh, Joseph E; Levy, Steven M

2017-05-01

Sugar-sweetened beverages (SSBs) have been associated with obesity in children and adults; however, associations between beverage patterns and obesity are not understood. Our aim was to describe beverage patterns during adolescence and associations between adolescent beverage patterns and anthropometric measures at age 17 years. We conducted a cross-sectional analyses of longitudinally collected data. Data from participants in the longitudinal Iowa Fluoride Study having at least one beverage questionnaire completed between ages 13.0 and 14.0 years, having a second questionnaire completed between 16.0 and 17.0 years, and attending clinic examination for weight and height measurements at age 17 years (n=369) were included. Beverages were collapsed into four categories (ie, 100% juice, milk, water and other sugar-free beverages, and SSBs) for the purpose of clustering. Five beverage clusters were identified from standardized age 13 to 17 years mean daily beverage intakes and named by the authors for the dominant beverage: juice, milk, water/sugar-free beverages, neutral, and SSB. Weight, height, and body mass index (BMI; calculated as kg/m 2 ) at age 17 years were analyzed. We used Ward's method for clustering of beverage variables, one-way analysis of variance and χ 2 tests for bivariable associations, and γ-regression for associations of weight or BMI (outcomes) with beverage clusters and demographic variables. Linear regression was used for associations of height (outcome) with beverage clusters and demographic variables. Participants with family incomes <$60,000 trended shorter (1.5±0.8 cm; P=0.070) and were heavier (2.0±0.7 BMI units; P=0.002) than participants with family incomes ≥$60,000/year. Adjusted mean weight, height, and BMI estimates differed by beverage cluster membership. For example, on average, male and female members of the neutral cluster were 4.5 cm (P=0.010) and 4.2 cm (P=0.034) shorter, respectively, than members of the milk cluster. For members of the juice cluster, mean BMI was lower than for members of the milk cluster (by 2.4 units), water/sugar-free beverage cluster (3.5 units), neutral cluster (2.2 units), and SSB cluster (3.2 units) (all P<0.05). Beverage patterns at ages 13 to 17 years were associated with anthropometric measures and BMI at age 17 years in this sample. Beverage patterns might be characteristic of overall food choices and dietary behaviors that influence growth. Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Method and system for data clustering for very large databases

NASA Technical Reports Server (NTRS)

Livny, Miron (Inventor); Zhang, Tian (Inventor); Ramakrishnan, Raghu (Inventor)

1998-01-01

Multi-dimensional data contained in very large databases is efficiently and accurately clustered to determine patterns therein and extract useful information from such patterns. Conventional computer processors may be used which have limited memory capacity and conventional operating speed, allowing massive data sets to be processed in a reasonable time and with reasonable computer resources. The clustering process is organized using a clustering feature tree structure wherein each clustering feature comprises the number of data points in the cluster, the linear sum of the data points in the cluster, and the square sum of the data points in the cluster. A dense region of data points is treated collectively as a single cluster, and points in sparsely occupied regions can be treated as outliers and removed from the clustering feature tree. The clustering can be carried out continuously with new data points being received and processed, and with the clustering feature tree being restructured as necessary to accommodate the information from the newly received data points.

Spectroscopic constraints on the form of the stellar cluster mass function

NASA Astrophysics Data System (ADS)

Bastian, N.; Konstantopoulos, I. S.; Trancho, G.; Weisz, D. R.; Larsen, S. S.; Fouesneau, M.; Kaschinski, C. B.; Gieles, M.

2012-05-01

This contribution addresses the question of whether the initial cluster mass function (ICMF) has a fundamental limit (or truncation) at high masses. The shape of the ICMF at high masses can be studied using the most massive young (<10 Myr) clusters, however this has proven difficult due to low-number statistics. In this contribution we use an alternative method based on the luminosities of the brightest clusters, combined with their ages. The advantages are that more clusters can be used and that the ICMF leaves a distinct pattern on the global relation between the cluster luminosity and median age within a population. If a truncation is present, a generic prediction (nearly independent of the cluster disruption law adopted) is that the median age of bright clusters should be younger than that of fainter clusters. In the case of an non-truncated ICMF, the median age should be independent of cluster luminosity. Here, we present optical spectroscopy of twelve young stellar clusters in the face-on spiral galaxy NGC 2997. The spectra are used to estimate the age of each cluster, and the brightness of the clusters is taken from the literature. The observations are compared with the model expectations of Larsen (2009, A&A, 494, 539) for various ICMF forms and both mass dependent and mass independent cluster disruption. While there exists some degeneracy between the truncation mass and the amount of mass independent disruption, the observations favour a truncated ICMF. For low or modest amounts of mass independent disruption, a truncation mass of 5-6 × 105 M⊙ is estimated, consistent with previous determinations. Additionally, we investigate possible truncations in the ICMF in the spiral galaxy M 83, the interacting Antennae galaxies, and the collection of spiral and dwarf galaxies present in Larsen (2009, A&A, 494, 539) based on photometric catalogues taken from the literature, and find that all catalogues are consistent with having a truncation in the cluster mass functions. However for the case of the Antennae, we find a truncation mass of a few × 106M⊙ , suggesting a dependence on the environment, as has been previously suggested.

Visual cluster analysis and pattern recognition methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

2001-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Distinct aggregation patterns and fluid porous phase in a 2D model for colloids with competitive interactions

NASA Astrophysics Data System (ADS)

Bordin, José Rafael

2018-04-01

In this paper we explore the self-assembly patterns in a two dimensional colloidal system using extensive Langevin Dynamics simulations. The pair potential proposed to model the competitive interaction have a short range length scale between first neighbors and a second characteristic length scale between third neighbors. We investigate how the temperature and colloidal density will affect the assembled morphologies. The potential shows aggregate patterns similar to observed in previous works, as clusters, stripes and porous phase. Nevertheless, we observe at high densities and temperatures a porous mesophase with a high mobility, which we name fluid porous phase, while at lower temperatures the porous structure is rigid. triangular packing was observed for the colloids and pores in both solid and fluid porous phases. Our results show that the porous structure is well defined for a large range of temperature and density, and that the fluid porous phase is a consequence of the competitive interaction and the random forces from the Langevin Dynamics.

Reviewing Sonority for Word-Final Sonorant+Obstruent Consonant Cluster Development in Turkish

ERIC Educational Resources Information Center

Topbas, Seyhun; Kopkalli-Yavuz, Handan

2008-01-01

The purpose of this study is to investigate the acquisition patterns of sonorant+obstruent coda clusters in Turkish to determine whether Turkish data support the prediction the Sonority Sequencing Principle (SSP) makes as to which consonant (i.e. C1 or C2) is more likely to be preserved in sonorant+obstruent clusters, and the error patterns of…

Complete characterization of the stability of cluster synchronization in complex dynamical networks.

PubMed

Sorrentino, Francesco; Pecora, Louis M; Hagerstrom, Aaron M; Murphy, Thomas E; Roy, Rajarshi

2016-04-01

Synchronization is an important and prevalent phenomenon in natural and engineered systems. In many dynamical networks, the coupling is balanced or adjusted to admit global synchronization, a condition called Laplacian coupling. Many networks exhibit incomplete synchronization, where two or more clusters of synchronization persist, and computational group theory has recently proved to be valuable in discovering these cluster states based on the topology of the network. In the important case of Laplacian coupling, additional synchronization patterns can exist that would not be predicted from the group theory analysis alone. Understanding how and when clusters form, merge, and persist is essential for understanding collective dynamics, synchronization, and failure mechanisms of complex networks such as electric power grids, distributed control networks, and autonomous swarming vehicles. We describe a method to find and analyze all of the possible cluster synchronization patterns in a Laplacian-coupled network, by applying methods of computational group theory to dynamically equivalent networks. We present a general technique to evaluate the stability of each of the dynamically valid cluster synchronization patterns. Our results are validated in an optoelectronic experiment on a five-node network that confirms the synchronization patterns predicted by the theory.

Group B Streptococcus Vaginal Carriage in Pregnant Women as Deciphered by Clustered Regularly Interspaced Short Palindromic Repeat Analysis.

PubMed

Beauruelle, Clemence; Pastuszka, Adeline; Mereghetti, Laurent; Lanotte, Philippe

2018-06-01

We evaluated the diversity of group B Streptococcus (GBS) vaginal carriage populations in pregnant women. For this purpose, we studied each isolate present in a primary culture of a vaginal swab using a new approach based on clustered regularly interspaced short palindromic repeats (CRISPR) locus analysis. To evaluate the CRISPR array composition rapidly, a restriction fragment length polymorphism (RFLP) analysis was performed. For each different pattern observed, the CRISPR array was sequenced and capsular typing and multilocus sequence typing (MLST) were performed. A total of 970 isolates from 10 women were analyzed by CRISPR-RFLP. Each woman carrying GBS isolates presented one to five specific "personal" patterns. Five women showed similar isolates with specific and unique restriction patterns, suggesting the carriage of a single GBS clone. Different patterns were observed among isolates from the other five women. For three of these, CRISPR locus sequencing highlighted low levels of internal modifications in the locus backbone, whereas there were high levels of modifications for the last two women, suggesting the carriage of two different clones. These two clones were closely related, having the same ancestral spacer(s), the same capsular type and, in one case, the same ST, but showed different antibiotic resistance patterns in pairs. Eight of 10 women were colonized by a single GBS clone, while two of them were colonized by two strains, leading to a risk of selection of more-virulent and/or more-resistant clones during antibiotic prophylaxis. This CRISPR analysis made it possible to separate isolates belonging to a single capsular type and sequence type, highlighting the greater discriminating power of this approach. Copyright © 2018 American Society for Microbiology.

Influence of atmospheric transport on ozone and trace- level toxic air contaminants over the northeastern United States

NASA Astrophysics Data System (ADS)

Brankov, Elvira

This thesis presents a methodology for examining the relationship between synoptic-scale atmospheric transport patterns and observed pollutant concentration levels. It involves calculating a large number of back-trajectories from the observational site and subjecting them to cluster analysis. The pollutant concentration data observed at that site are then segregated according to the back-trajectory clusters. If the pollutant observations extend over several seasons, it is important to filter out seasonal and long-term components from the time series data before pollutant cluster-segregation, because only the short-term component of the time series data is related to the synoptic-scale transport. Multiple comparison procedures are used to test for significant differences in the chemical composition of pollutant data associated with each cluster. This procedure is useful in indicating potential pollutant source regions and isolating meteorological regimes associated with pollutant transport from those regions. If many observational sites are available, the spatial and temporal scales of the pollution transport from a given direction can be extracted through the time-lagged inter- site correlation analysis of pollutant concentrations. The proposed methodology is applicable to any pollutant at any site if sufficiently abundant data set is available. This is illustrated through examination of five-year long time series data of ozone concentrations at several sites in the Northeast. The results provide evidence of ozone transport to these sites, revealing the characteristic spatial and temporal scales involved in the transport and identifying source regions for this pollutant. Problems related to statistical analyses of censored data are addressed in the second half of this thesis. Although censoring (reporting concentrations in a non-quantitative way) is typical for trace-level measurements, methods for statistical analysis, inference and interpretation of such data are complex and still under development. In this study, multiple comparison of censored data sets was required in order to examine the influence of synoptic- scale circulations on concentration levels of several trace-level toxic pollutants observed in the Northeast (e.g., As, Se, Mn, V, etc.). Since the traditional multiple comparison procedures are not readily applicable to such data sets, a Monte Carlo simulation study was performed to assess several nonparametric methods for multiple comparison of censored data sets. Application of an appropriate comparison procedure to clusters of toxic trace elements observed in the Northeast led to the identification of potential source regions and atmospheric patterns associated with the long-range transport of these pollutants. A method for comparison of proportions and elemental ratio calculations were used to confirm/clarify these inferences with a greater degree of confidence.

Maternal-child overweight/obesity and undernutrition in Kenya: a geographic analysis.

PubMed

Pawloski, Lisa R; Curtin, Kevin M; Gewa, Constance; Attaway, David

2012-11-01

The purpose of the study was to examine geographic relationships of nutritional status (BMI), including underweight, overweight and obesity, among Kenyan mothers and children. Spatial relationships were examined concerning BMI of the mothers and BMI-for-age percentiles of their children. These included spatial statistical measures of the clustering of segments of the population, in addition to inspection of co-location of significant clusters. Rural and urban areas of Kenya, including the cities of Nairobi and Mombasa, and the Kisumu region. Mother-child pairs from Demographic and Health Survey data including 1541 observations in 2003 and 1592 observations in 2009. These mother-child pairs were organized into 399 locational clusters. There is extremely strong evidence that high BMI values exhibit strong spatial clustering. There were co-locations of overweight mothers and overweight children only in the Nairobi region, while both underweight mothers and children tended to cluster in rural areas. In Mombasa clusters of overweight mothers were associated with normal-weight children, while in the Kisumu region clusters of overweight children were associated with normal-weight mothers. These findings show there is geographic variability as well as some defined patterns concerning the distribution of malnutrition among mothers and children in Kenya, and suggest the need for further geographic analyses concerning the potential factors which influence nutritional status in this population. In addition, the methods used in this research may be easily applied to other Demographic and Health Survey data in order to begin to understand the geographic determinants of health in low-income countries.

The effect of clustering on perceived quantity in humans (Homo sapiens) and in chicks (Gallus gallus).

PubMed

Bertamini, Marco; Guest, Martin; Vallortigara, Giorgio; Rugani, Rosa; Regolin, Lucia

2018-04-30

Animals can perceive the numerosity of sets of visual elements. Qualitative and quantitative similarities in different species suggest the existence of a shared system (approximate number system). Biases associated with sensory properties are informative about the underlying mechanisms. In humans, regular spacing increases perceived numerosity (regular-random numerosity illusion). This has led to a model that predicts numerosity based on occupancy (a measure that decreases when elements are close together). We used a procedure in which observers selected one of two stimuli and were given feedback with respect to whether the choice was correct. One configuration had 20 elements and the other 40, randomly placed inside a circular region. Participants had to discover the rule based on feedback. Because density and clustering covaried with numerosity, different dimensions could be used. After reaching a criterion, test trials presented two types of configurations with 30 elements. One type had a larger interelement distance than the other (high or low clustering). If observers had adopted a numerosity strategy, they would choose low clustering (if reinforced with 40) and high clustering (if reinforced with 20). A clustering or density strategy predicts the opposite. Human adults used a numerosity strategy. Chicks were tested using a similar procedure. There were two behavioral measures: first approach response and final circumnavigation (walking behind the screen). The prediction based on numerosity was confirmed by the first approach data. For chicks, one clear pattern from both responses was a preference for the configurations with higher clustering. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Patterning C. elegans: homeotic cluster genes, cell fates and cell migrations.

PubMed

Salser, S J; Kenyon, C

1994-05-01

Despite its simple body form, the nematode C. elegans expresses homeotic cluster genes similar to those of insects and vertebrates in the patterning of many cell types and tissues along the anteroposterior axis. In the ventral nerve cord, these genes program spatial patterns of cell death, fusion, division and neurotransmitter production; in migrating cells they regulate the direction and extent of movement. Nematode development permits an analysis at the cellular level of how homeotic cluster genes interact to specify cell fates, and how cell behavior can be regulated to assemble an organism.

Clustering eating habits: frequent consumption of different dietary patterns among the Italian general population in the association with obesity, physical activity, sociocultural characteristics and psychological factors.

PubMed

Denoth, Francesca; Scalese, Marco; Siciliano, Valeria; Di Renzo, Laura; De Lorenzo, Antonino; Molinaro, Sabrina

2016-06-01

(a) To identify clusters of eating patterns among the Italian population aged 15-64 years, focusing on typical Mediterranean diet (Med-diet) items consumption; (b) to examine the distribution of eating habits, as identified clusters, among age classes and genders; (c) evaluate the impact of: belonging to a specific eating cluster, level of physical activity (PA), sociocultural and psychological factors, as elements determining weight abnormalities. Data for this cross-sectional study were collected using self-reporting questionnaires administered to a sample of 33,127 subjects participating in the Italian population survey on alcohol and other drugs (IPSAD(®)2011). The cluster analysis was performed on a subsample (n = 5278 subjects) which provided information on eating habits, and adapted to identify categories of eating patterns. Stepwise multinomial regression analysis was performed to evaluate the associations between weight categories and eating clusters, adjusted for the following background variables: PA levels, sociocultural and psychological factors. Three clusters were identified: "Mediterranean-like", "Western-like" and "low fruit/vegetables". Frequent consumption of Med-diet patterns was more common among females and elderly. The relationship between overweight/obesity and male gender, educational level, PA, depression and eating disorders (p < 0.05) was confirmed. Belonging to a cluster other than "Mediterranean-like" was significantly associated with obesity. The low consumption of Med-diet patterns among youth, and the frequent association of sociocultural, psychological issues and inappropriate lifestyle with overweight/obesity, highlight the need for an interdisciplinary approach including market policies, to promote a wider awareness of the Mediterranean eating habit benefits in combination with an appropriate lifestyle.

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

Biogeographic distribution patterns and their correlates in the diverse frog fauna of the Atlantic Forest hotspot.

PubMed

Vasconcelos, Tiago S; Prado, Vitor H M; da Silva, Fernando R; Haddad, Célio F B

2014-01-01

Anurans are a highly diverse group in the Atlantic Forest hotspot (AF), yet distribution patterns and species richness gradients are not randomly distributed throughout the biome. Thus, we explore how anuran species are distributed in this complex and biodiverse hotspot, and hypothesize that this group can be distinguished by different cohesive regions. We used range maps of 497 species to obtain a presence/absence data grid, resolved to 50×50 km grain size, which was submitted to k-means clustering with v-fold cross-validation to determine the biogeographic regions. We also explored the extent to which current environmental variables, topography, and floristic structure of the AF are expected to identify the cluster patterns recognized by the k-means clustering. The biogeographic patterns found for amphibians are broadly congruent with ecoregions identified in the AF, but their edges, and sometimes the whole extent of some clusters, present much less resolved pattern compared to previous classification. We also identified that climate, topography, and vegetation structure of the AF explained a high percentage of variance of the cluster patterns identified, but the magnitude of the regression coefficients shifted regarding their importance in explaining the variance for each cluster. Specifically, we propose that the anuran fauna of the AF can be split into four biogeographic regions: a) less diverse and widely-ranged species that predominantly occur in the inland semideciduous forests; b) northern small-ranged species that presumably evolved within the Pleistocene forest refugia; c) highly diverse and small-ranged species from the southeastern Brazilian mountain chain and its adjacent semideciduous forest; and d) southern species from the Araucaria forest. Finally, the high congruence among the cluster patterns and previous eco-regions identified for the AF suggests that preserving the underlying habitat structure helps to preserve the historical and ecological signals that underlie the geographic distribution of AF anurans.

Coulomb fission in multiply charged molecular clusters: Experiment and theory

NASA Astrophysics Data System (ADS)

Harris, Christopher; Baptiste, Joshua; Lindgren, Eric B.; Besley, Elena; Stace, Anthony J.

2017-04-01

A series of three multiply charged molecular clusters, (C6H6)nz+ (benzene), (CH3CNnz) + (acetonitrile), and (C4H8O)nz+ (tetrahydrofuran), where the charge z is either 3 or 4, have been studied for the purpose of identifying the patterns of behaviour close to the charge instability limit. Experiments show that on a time scale of ˜10-4 s, ions close to the limit undergo Coulomb fission where the observed pathways exhibit considerable asymmetry in the sizes of the charged fragments and are all associated with kinetic (ejection) energies of between 1.4 and 2.2 eV. Accurate kinetic energies have been determined through a computer simulation of peak profiles recorded in the experiments and the results modelled using a theory formulated to describe how charged particles of dielectric materials interact with one another [E. Bichoutskaia et al., J. Chem. Phys. 133, 024105 (2010)]. The calculated electrostatic interaction energy between separating fragments gives an accurate account for the measured kinetic energies and also supports the conclusion that +4 ions fragment into +3 and +1 products as opposed to the alternative of two +2 fragments. This close match between the theory and experiment reinforces the assumption that a significant fraction of excess charge resides on the surfaces of the fragment ions. It is proposed that the high degree of asymmetry seen in the fragmentation patterns of the multiply charged clusters is due, in part, to limits imposed by the time window during which observations are made.

Asymmetric DNA methylation of CpG dyads is a feature of secondary DMRs associated with the Dlk1/Gtl2 imprinting cluster in mouse.

PubMed

Guntrum, Megan; Vlasova, Ekaterina; Davis, Tamara L

2017-01-01

Differential DNA methylation plays a critical role in the regulation of imprinted genes. The differentially methylated state of the imprinting control region is inherited via the gametes at fertilization, and is stably maintained in somatic cells throughout development, influencing the expression of genes across the imprinting cluster. In contrast, DNA methylation patterns are more labile at secondary differentially methylated regions which are established at imprinted loci during post-implantation development. To investigate the nature of these more variably methylated secondary differentially methylated regions, we adopted a hairpin linker bisulfite mutagenesis approach to examine CpG dyad methylation at differentially methylated regions associated with the murine Dlk1/Gtl2 imprinting cluster on both complementary strands. We observed homomethylation at greater than 90% of the methylated CpG dyads at the IG-DMR, which serves as the imprinting control element. In contrast, homomethylation was only observed at 67-78% of the methylated CpG dyads at the secondary differentially methylated regions; the remaining 22-33% of methylated CpG dyads exhibited hemimethylation. We propose that this high degree of hemimethylation could explain the variability in DNA methylation patterns at secondary differentially methylated regions associated with imprinted loci. We further suggest that the presence of 5-hydroxymethylation at secondary differentially methylated regions may result in hemimethylation and methylation variability as a result of passive and/or active demethylation mechanisms.

Visualization and minimization of clustering of micro-pillars and walls due to liquid film evaporation

NASA Astrophysics Data System (ADS)

Kim, Tae-Hong; Kim, Jungchul; Kim, Ho-Young

2013-11-01

The spin drying, in which a rinsing liquid deposited on a wafer is rapidly dried by wafer spinning, is an essential step in the semiconductor manufacturing process. While the liquid evaporates, its meniscus straddles neighboring submicron-size patterns such as pillars and walls. Then the capillary effects that pull the patterns together may lead to direct contact of the patterns, which is often referred to as pattern leaning. This poses a problem becoming more and more serious as the pattern size shrinks and the aspect ratio of the patterns increases. While the clustering behavior of high-aspect-ratio micro- and nanopillars was investigated before, a technical strategy to prevent such clustering has been pursed in industrial practices without being supported by the recently established theory of elastocapillarity. Here we visualize the clustering behavior of polymer micropatterns with the evaporation of liquid film while varying the sizes and temperature of the micropatterns. We find a critical role of substrate temperature in preventing the leaning of the patterns via changing the evaporation rate and behavior of the liquid film. Also, we construct a regime map that guides us to find a process condition to avoid pattern leaning in semiconductor manufacturing. This work was supported by the National Research Foundation of Korea (grant no. 2012-008023).

Hybridization and differential introgression associated with environmental shifts in a mistletoe species complex.

PubMed

Baena-Díaz, Fernanda; Ramírez-Barahona, Santiago; Ornelas, Juan Francisco

2018-04-03

Host specialization after host shifting is traditionally viewed as the pathway to speciation in parasitic plants. However, geographical and environmental changes can also influence parasite speciation, through hybridization processes. Here we investigated the impact of past climatic fluctuations, environment, and host shifts on the genetic structure and patterns of hybridization and gene flow between Psittacanthus calyculatus and P. schiedeanus, a Mesoamerican species complex. Using microsatellites (408 individuals), we document moderate genetic diversity but high genetic differentiation between widespread parental clusters, calyculatus in dry pine-oak forests and schiedeanus in cloud forests. Bayesian analyses identified a third cluster, with admixture between parental clusters in areas of xeric and tropical dry forests and high levels of migration rates following secondary contact. Coincidently host associations in these areas differ from those in areas of parental species, suggesting that past hybridization played a role in environmental and host shifts. Overall, the observed genetic and geographic patterns suggest that these Psittacanthus populations could have entered a distinct evolutionary pathway. The results provide evidence for highlights on the importance of the Pleistocene climate changes, habitat differences, and potential host shifts in the evolutionary history of Neotropical mistletoes.

Design of partially supervised classifiers for multispectral image data

NASA Technical Reports Server (NTRS)

Jeon, Byeungwoo; Landgrebe, David

1993-01-01

A partially supervised classification problem is addressed, especially when the class definition and corresponding training samples are provided a priori only for just one particular class. In practical applications of pattern classification techniques, a frequently observed characteristic is the heavy, often nearly impossible requirements on representative prior statistical class characteristics of all classes in a given data set. Considering the effort in both time and man-power required to have a well-defined, exhaustive list of classes with a corresponding representative set of training samples, this 'partially' supervised capability would be very desirable, assuming adequate classifier performance can be obtained. Two different classification algorithms are developed to achieve simplicity in classifier design by reducing the requirement of prior statistical information without sacrificing significant classifying capability. The first one is based on optimal significance testing, where the optimal acceptance probability is estimated directly from the data set. In the second approach, the partially supervised classification is considered as a problem of unsupervised clustering with initially one known cluster or class. A weighted unsupervised clustering procedure is developed to automatically define other classes and estimate their class statistics. The operational simplicity thus realized should make these partially supervised classification schemes very viable tools in pattern classification.

Molecular epidemiology of Escherichia coli O157:H7 strains by bacteriophage lambda restriction fragment length polymorphism analysis: application to a multistate foodborne outbreak and a day-care center cluster.

PubMed

Samadpour, M; Grimm, L M; Desai, B; Alfi, D; Ongerth, J E; Tarr, P I

1993-12-01

Genomic DNAs prepared from 168 isolates of Escherichia coli O157:H7 were analyzed for restriction fragment length polymorphisms on Southern blots probed with bacteriophage lambda DNA. The isolates analyzed included strains from a recent large multistate outbreak of E. coli O157:H7 infection associated with consumption of poorly cooked beef in restaurants, a day-care center cluster, and temporally and geographically unrelated isolates. E. coli O157:H7 isolates recovered from the incriminated meat and from 61 (96.8%) of 63 patients from Washington and Nevada possessed identical lambda restriction fragment length patterns. The lambda restriction fragment length polymorphisms observed in 11 (91.7%) of 12 day-care center patients were identical, but they differed from that of the strain associated with the multistate outbreak. E. coli O157:H7 from 42 patients temporally or geographically unrelated to either cluster of infection possessed unique and different lambda restriction fragment length patterns, except for paired isolates from three separate clusters of infection. These data demonstrate that the hybridization of DNA digests of E. coli O157:H7 with radiolabelled bacteriophage lambda DNA can be a useful, stable, and discriminatory epidemiologic tool for analyzing the linkage between strains of E. coli O157:H7.

Exploring spatial evolution of economic clusters: A case study of Beijing

NASA Astrophysics Data System (ADS)

Yang, Zhenshan; Sliuzas, Richard; Cai, Jianming; Ottens, Henk F. L.

2012-10-01

An identification of economic clusters and analysing their changing spatial patterns is important for understanding urban economic space dynamics. Previous studies, however, suffer from limitations as a consequence of using fixed geographically areas and not combining functional and spatial dynamics. The paper presents an approach, based on local spatial statistics and the case of Beijing to understand the spatial clustering of industries that are functionally interconnected by common or complementary patterns of demand or supply relations. Using register data of business establishments, it identifies economic clusters and analyses their pattern based on postcodes at different time slices during the period 1983-2002. The study shows how the advanced services occupy the urban centre and key sub centres. The Information and Communication Technology (ICT) cluster is mainly concentrated in the north part of the city and circles the urban centre, and the main manufacturing clusters are evolved in the key sub centers. This type of outcomes improves understanding of urban-economic dynamics, which can support spatial and economic planning.

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

1999-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Cardiovascular reactivity patterns and pathways to hypertension: a multivariate cluster analysis.

PubMed

Brindle, R C; Ginty, A T; Jones, A; Phillips, A C; Roseboom, T J; Carroll, D; Painter, R C; de Rooij, S R

2016-12-01

Substantial evidence links exaggerated mental stress induced blood pressure reactivity to future hypertension, but the results for heart rate reactivity are less clear. For this reason multivariate cluster analysis was carried out to examine the relationship between heart rate and blood pressure reactivity patterns and hypertension in a large prospective cohort (age range 55-60 years). Four clusters emerged with statistically different systolic and diastolic blood pressure and heart rate reactivity patterns. Cluster 1 was characterised by a relatively exaggerated blood pressure and heart rate response while the blood pressure and heart rate responses of cluster 2 were relatively modest and in line with the sample mean. Cluster 3 was characterised by blunted cardiovascular stress reactivity across all variables and cluster 4, by an exaggerated blood pressure response and modest heart rate response. Membership to cluster 4 conferred an increased risk of hypertension at 5-year follow-up (hazard ratio=2.98 (95% CI: 1.50-5.90), P<0.01) that survived adjustment for a host of potential confounding variables. These results suggest that the cardiac reactivity plays a potentially important role in the link between blood pressure reactivity and hypertension and support the use of multivariate approaches to stress psychophysiology.

Is Technology-Mediated Parental Monitoring Related to Adolescent Substance Use?

PubMed

Rudi, Jessie; Dworkin, Jodi

2018-01-03

Prevention researchers have identified parental monitoring leading to parental knowledge to be a protective factor against adolescent substance use. In today's digital society, parental monitoring can occur using technology-mediated communication methods, such as text messaging, email, and social networking sites. The current study aimed to identify patterns, or clusters, of in-person and technology-mediated monitoring behaviors, and examine differences between the patterns (clusters) in adolescent substance use. Cross-sectional survey data were collected from 289 parents of adolescents using Facebook and Amazon Mechanical Turk (MTurk). Cluster analyses were computed to identify patterns of in-person and technology-mediated monitoring behaviors, and chi-square analyses were computed to examine differences in substance use between the identified clusters. Three monitoring clusters were identified: a moderate in-person and moderate technology-mediated monitoring cluster (moderate-moderate), a high in-person and high technology-mediated monitoring cluster (high-high), and a high in-person and low technology-mediated monitoring cluster (high-low). Higher frequency of technology-mediated parental monitoring was not associated with lower levels of substance use. Results show that higher levels of technology-mediated parental monitoring may not be associated with adolescent substance use.

The Impact of Multilocus Variable-Number Tandem-Repeat Analysis on PulseNet Canada Escherichia coli O157:H7 Laboratory Surveillance and Outbreak Support, 2008-2012.

PubMed

Rumore, Jillian Leigh; Tschetter, Lorelee; Nadon, Celine

2016-05-01

The lack of pattern diversity among pulsed-field gel electrophoresis (PFGE) profiles for Escherichia coli O157:H7 in Canada does not consistently provide optimal discrimination, and therefore, differentiating temporally and/or geographically associated sporadic cases from potential outbreak cases can at times impede investigations. To address this limitation, DNA sequence-based methods such as multilocus variable-number tandem-repeat analysis (MLVA) have been explored. To assess the performance of MLVA as a supplemental method to PFGE from the Canadian perspective, a retrospective analysis of all E. coli O157:H7 isolated in Canada from January 2008 to December 2012 (inclusive) was conducted. A total of 2285 E. coli O157:H7 isolates and 63 clusters of cases (by PFGE) were selected for the study. Based on the qualitative analysis, the addition of MLVA improved the categorization of cases for 60% of clusters and no change was observed for ∼40% of clusters investigated. In such situations, MLVA serves to confirm PFGE results, but may not add further information per se. The findings of this study demonstrate that MLVA data, when used in combination with PFGE-based analyses, provide additional resolution to the detection of clusters lacking PFGE diversity as well as demonstrate good epidemiological concordance. In addition, MLVA is able to identify cluster-associated isolates with variant PFGE pattern combinations that may have been previously missed by PFGE alone. Optimal laboratory surveillance in Canada is achieved with the application of PFGE and MLVA in tandem for routine surveillance, cluster detection, and outbreak response.

Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

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

Zhang, Jianbao; Ma, Zhongjun, E-mail: mzj1234402@163.com; Chen, Guanrong

All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding ormore » deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.« less

Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

NASA Astrophysics Data System (ADS)

Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong

2014-06-01

All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.

Computational identification of developmental enhancers:conservation and function of transcription factor binding-site clustersin drosophila melanogaster and drosophila psedoobscura

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

Berman, Benjamin P.; Pfeiffer, Barret D.; Laverty, Todd R.

2004-08-06

The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene, and assayedmore » embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. Measuring conservation of sequence features closely linked to function--such as binding-site clustering--makes better use of comparative sequence data than commonly used methods that examine only sequence identity.« less

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.

Population substructure and space use of Foxe Basin polar bears.

PubMed

Sahanatien, Vicki; Peacock, Elizabeth; Derocher, Andrew E

2015-07-01

Climate change has been identified as a major driver of habitat change, particularly for sea ice-dependent species such as the polar bear (Ursus maritimus). Population structure and space use of polar bears have been challenging to quantify because of their circumpolar distribution and tendency to range over large areas. Knowledge of movement patterns, home range, and habitat is needed for conservation and management. This is the first study to examine the spatial ecology of polar bears in the Foxe Basin management unit of Nunavut, Canada. Foxe Basin is in the mid-Arctic, part of the seasonal sea ice ecoregion and it is being negatively affected by climate change. Our objectives were to examine intrapopulation spatial structure, to determine movement patterns, and to consider how polar bear movements may respond to changing sea ice habitat conditions. Hierarchical and fuzzy cluster analyses were used to assess intrapopulation spatial structure of geographic position system satellite-collared female polar bears. Seasonal and annual movement metrics (home range, movement rates, time on ice) and home-range fidelity (static and dynamic overlap) were compared to examine the influence of regional sea ice on movements. The polar bears were distributed in three spatial clusters, and there were differences in the movement metrics between clusters that may reflect sea ice habitat conditions. Within the clusters, bears moved independently of each other. Annual and seasonal home-range fidelity was observed, and the bears used two movement patterns: on-ice range residency and annual migration. We predict that home-range fidelity may decline as the spatial and temporal predictability of sea ice changes. These new findings also provide baseline information for managing and monitoring this polar bear population.

Genetic structure of the world's polar bear populations.

PubMed

Paetkau, D; Amstrup, S C; Born, E W; Calvert, W; Derocher, A E; Garner, G W; Messier, F; Stirling, I; Taylor, M K; Wiig, O; Strobeck, C

1999-10-01

We studied genetic structure in polar bear (Ursus maritimus) populations by typing a sample of 473 individuals spanning the species distribution at 16 highly variable microsatellite loci. No genetic discontinuities were found that would be consistent with evolutionarily significant periods of isolation between groups. Direct comparison of movement data and genetic data from the Canadian Arctic revealed a highly significant correlation. Genetic data generally supported existing population (management unit) designations, although there were two cases where genetic data failed to differentiate between pairs of populations previously resolved by movement data. A sharp contrast was found between the minimal genetic structure observed among populations surrounding the polar basin and the presence of several marked genetic discontinuities in the Canadian Arctic. The discontinuities in the Canadian Arctic caused the appearance of four genetic clusters of polar bear populations. These clusters vary in total estimated population size from 100 to over 10 000, and the smallest may merit a relatively conservative management strategy in consideration of its apparent isolation. We suggest that the observed pattern of genetic discontinuities has developed in response to differences in the seasonal distribution and pattern of sea ice habitat and the effects of these differences on the distribution and abundance of seals.

Genetic structure of the world's polar bear populations

USGS Publications Warehouse

Paetkau, David; Amstrup, Steven C.; Born, E.W.; Calvert, W.; Derocher, A.E.; Garner, G.W.; Messier, F.; Stirling, I.; Taylor, M.K.; Wiig, O.; Strobeck, C.

1999-01-01

We studied genetic structure in polar bear (Ursus maritimus) populations by typing a sample of 473 individuals spanning the species distribution at 16 highly variable microsatellite loci. No genetic discontinuities were found that would be consistent with evolutionarily significant periods of isolation between groups. Direct comparison of movement data and genetic data from the Canadian Arctic revealed a highly significant correlation. Genetic data generally supported existing population (management unit) designations, although there were two cases where genetic data failed to differentiate between pairs of populations previously resolved by movement data. A sharp contrast was found between the minimal genetic structure observed among populations surrounding the polar basin and the presence of several marked genetic discontinuities in the Canadian Arctic. The discontinuities in the Canadian Arctic caused the appearance of four genetic clusters of polar bear populations. These clusters vary in total estimated population size from 100 to over 10 000, and the smallest may merit a relatively conservative management strategy in consideration of its apparent isolation. We suggest that the observed pattern of genetic discontinuities has developed in response to differences in the seasonal distribution and pattern of sea ice habitat and the effects of these differences on the distribution and abundance of seals.

Dynamic Segmentation Of Behavior Patterns Based On Quantity Value Movement Using Fuzzy Subtractive Clustering Method

NASA Astrophysics Data System (ADS)

Sangadji, Iriansyah; Arvio, Yozika; Indrianto

2018-03-01

to understand by analyzing the pattern of changes in value movements that can dynamically vary over a given period with relative accuracy, an equipment is required based on the utilization of technical working principles or specific analytical method. This will affect the level of validity of the output that will occur from this system. Subtractive clustering is based on the density (potential) size of data points in a space (variable). The basic concept of subtractive clustering is to determine the regions in a variable that has high potential for the surrounding points. In this paper result is segmentation of behavior pattern based on quantity value movement. It shows the number of clusters is formed and that has many members.

A new concept to study the effect of climate change on different flood types

NASA Astrophysics Data System (ADS)

Nissen, Katrin; Nied, Manuela; Pardowitz, Tobias; Ulbrich, Uwe; Merz, Bruno

2014-05-01

Flooding is triggered by the interaction of various processes. Especially important are the hydrological conditions prior to the event (e.g. soil saturation, snow cover) and the meteorological conditions during flood development (e.g. rainfall, temperature). Depending on these (pre-) conditions different flood types may develop such as long-rain floods, short-rain floods, flash floods, snowmelt floods and rain-on-snow floods. A new concept taking these factors into account is introduced and applied to flooding in the Elbe River basin. During the period September 1957 to August 2002, 82 flood events are identified and classified according to their flood type. The hydrological and meteorological conditions at each day during the analysis period are detemined. In case of the hydrological conditions, a soil moisture pattern classification is carried out. Soil moisture is simulated with a rainfall-runoff model driven by atmospheric observations. Days of similar soil moisture patterns are identified by a principle component analysis and a subsequent cluster analysis on the leading principal components. The meteorological conditions are identified by applying a cluster analysis to the geopotential height, temperature and humidity fields of the ERA40 reanalysis data set using the SANDRA cluster algorithm. We are able to identify specific pattern combinations of hydrological pre-conditions and meteorological conditions which favour different flood types. Based on these results it is possible to analyse the effect of climate change on different flood types. As an example we show first results obtained using an ensemble of climate scenario simulations of ECHAM5 MPIOM model, taking only the changes in the meteorological conditions into account. According to the simulations, the frequency of the meteorological patterns favouring long-rain, short-rain and flash floods will not change significantly under future climate conditions. A significant increase is, however, predicted for the amount of precipitation associated with many of the relevant meteorological patterns. The increase varies between 12 and 67% depending on the weather pattern.

Population structure and migration pattern of a conifer pathogen, Grosmannia clavigera, as influenced by its symbiont, the mountain pine beetle.

PubMed

Tsui, Clement K M; Roe, Amanda D; El-Kassaby, Yousry A; Rice, Adrianne V; Alamouti, Sepideh M; Sperling, Felix A H; Cooke, Janice E K; Bohlmann, Jörg; Hamelin, Richard C

2012-01-01

We investigated the population structure of Grosmannia clavigera (Gc), a fungal symbiont of the mountain pine beetle (MPB) that plays a crucial role in the establishment and reproductive success of this pathogen. This insect-fungal complex has destroyed over 16 million ha of lodgepole pine forests in Canada, the largest MPB epidemic in recorded history. During this current epidemic, MPB has expanded its range beyond historically recorded boundaries, both northward and eastward, and has now reached the jack pine of Alberta, potentially threatening the Canadian boreal forest. To better understand the dynamics between the beetle and its fungal symbiont, we sampled 19 populations in western North America and genotyped individuals from these populations with eight microsatellite markers. The fungus displayed high haplotype diversity, with over 250 unique haplotypes observed in 335 single spore isolates. Linkage equilibria in 13 of the 19 populations suggested that the fungus reproduces sexually. Bayesian clustering and distance analyses identified four genetic clusters that corresponded to four major geographical regions, which suggested that the epidemic arose from multiple geographical sources. A genetic cluster north of the Rocky Mountains, where the MPB has recently become established, experienced a population bottleneck, probably as a result of the recent range expansion. The two genetic clusters located north and west of the Rocky Mountains contained many fungal isolates admixed from all populations, possibly due to the massive movement of MPB during the epidemic. The general agreement in north-south differentiation of MPB and G. clavigera populations points to the fungal pathogen's dependence on the movement of its insect vector. In addition, the patterns of diversity and the individual assignment tests of the fungal associate suggest that migration across the Rocky Mountains occurred via a northeastern corridor, in accordance with meteorological patterns and observation of MPB movement data. Our results highlight the potential of this pathogen for both expansion and sexual reproduction, and also identify some possible barriers to gene flow. Understanding the ecological and evolutionary dynamics of this fungus-beetle association is important for the modelling and prediction of MPB epidemics. © 2011 Crown in the right of Canada.

The faces of pain: a cluster analysis of individual differences in facial activity patterns of pain.

PubMed

Kunz, M; Lautenbacher, S

2014-07-01

There is general agreement that facial activity during pain conveys pain-specific information but is nevertheless characterized by substantial inter-individual differences. With the present study we aim to investigate whether these differences represent idiosyncratic variations or whether they can be clustered into distinct facial activity patterns. Facial actions during heat pain were assessed in two samples of pain-free individuals (n = 128; n = 112) and were later analysed using the Facial Action Coding System. Hierarchical cluster analyses were used to look for combinations of single facial actions in episodes of pain. The stability/replicability of facial activity patterns was determined across samples as well as across different basic social situations. Cluster analyses revealed four distinct activity patterns during pain, which stably occurred across samples and situations: (I) narrowed eyes with furrowed brows and wrinkled nose; (II) opened mouth with narrowed eyes; (III) raised eyebrows; and (IV) furrowed brows with narrowed eyes. In addition, a considerable number of participants were facially completely unresponsive during pain induction (stoic cluster). These activity patterns seem to be reaction stereotypies in the majority of individuals (in nearly two-thirds), whereas a minority displayed varying clusters across situations. These findings suggest that there is no uniform set of facial actions but instead there are at least four different facial activity patterns occurring during pain that are composed of different configurations of facial actions. Raising awareness about these different 'faces of pain' might hold the potential of improving the detection and, thereby, the communication of pain. © 2013 European Pain Federation - EFIC®

Application of Classification Methods for Forecasting Mid-Term Power Load Patterns

NASA Astrophysics Data System (ADS)

Piao, Minghao; Lee, Heon Gyu; Park, Jin Hyoung; Ryu, Keun Ho

Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in long duration load profiles. The proposed approach in this paper consists of three stages: (i) data preprocessing: noise or outlier is removed and the continuous attribute-valued features are transformed to discrete values, (ii) cluster analysis: k-means clustering is used to create load pattern classes and the representative load profiles for each class and (iii) classification: we evaluated several supervised learning methods in order to select a suitable prediction method. According to the proposed methodology, power load measured from AMR (automatic meter reading) system, as well as customer indexes, were used as inputs for clustering. The output of clustering was the classification of representative load profiles (or classes). In order to evaluate the result of forecasting load patterns, the several classification methods were applied on a set of high voltage customers of the Korea power system and derived class labels from clustering and other features are used as input to produce classifiers. Lastly, the result of our experiments was presented.

A pattern-mixture model approach for handling missing continuous outcome data in longitudinal cluster randomized trials.

PubMed

Fiero, Mallorie H; Hsu, Chiu-Hsieh; Bell, Melanie L

2017-11-20

We extend the pattern-mixture approach to handle missing continuous outcome data in longitudinal cluster randomized trials, which randomize groups of individuals to treatment arms, rather than the individuals themselves. Individuals who drop out at the same time point are grouped into the same dropout pattern. We approach extrapolation of the pattern-mixture model by applying multilevel multiple imputation, which imputes missing values while appropriately accounting for the hierarchical data structure found in cluster randomized trials. To assess parameters of interest under various missing data assumptions, imputed values are multiplied by a sensitivity parameter, k, which increases or decreases imputed values. Using simulated data, we show that estimates of parameters of interest can vary widely under differing missing data assumptions. We conduct a sensitivity analysis using real data from a cluster randomized trial by increasing k until the treatment effect inference changes. By performing a sensitivity analysis for missing data, researchers can assess whether certain missing data assumptions are reasonable for their cluster randomized trial. Copyright © 2017 John Wiley & Sons, Ltd.

Rotational spectroscopic study of carbonyl sulfide solvated with hydrogen molecules.

PubMed

Michaud, Julie M; Jäger, Wolfgang

2008-10-14

Rotational spectra of small-sized (H(2))(N)-OCS clusters with N = 2-7 were measured using a pulsed-jet Fourier transform microwave spectrometer. These include spectra of pure (para-H(2))(N)-OCS clusters, pure (ortho-H(2))(N)-OCS clusters, and mixed ortho-H(2) and para-H(2) containing clusters. The rotational lines of ortho-H(2) molecules containing clusters show proton spin-proton spin hyperfine structure, and the pattern evolves as the number of ortho-H(2) molecules in the cluster increases. Various isotopologues of the clusters were investigated, including those with O(13)CS, OC(33)S, OC(34)S, and O(13)C(34)S. Nuclear quadrupole hyperfine structures of rotational transitions were observed for (33)S (nuclear spin quantum number I = 3/2) containing isotopologues. The (33)S nuclear quadrupole coupling constants are compared to the corresponding constant of the OCS monomer and those of the He(N)-OCS clusters. The assignment of the number of solvating hydrogen molecules N is supported by the analyses of the proton spin-proton spin hyperfine structures of the mixed clusters, the dependence of line intensities on sample conditions (pressure and concentrations), and the agreement of the (para-H(2))(N)-OCS and (ortho-H(2))(N)-OCS rotational constants with those from a previous infrared study [J. Tang and A. R. W. McKellar, J. Chem. Phys. 121, 3087 (2004)].

Formation, Fragmentation, and Structures of YxOy(+) (x = 1, 2, y = 1 - 13) Clusters: Collision-Induced Dissociation Experiments and Density Functional Theory Calculations.

PubMed

Glodić, Pavle; Mihesan, Claudia; Klontzas, Emmanouel; Velegrakis, Michalis

2016-02-25

Yttrium oxide cluster cations have been experimentally and theoretically studied. We produced small, oxygen-rich yttrium oxide clusters, YxOy+ (x = 1, 2, y = 1–13), by mixing the laser-produced yttrium plasma with a molecular oxygen jet. Mass spectrometry measurements showed that the most stable clusters are those consisting of one yttrium and an odd number of oxygen atoms of the form YO(+)(2k+1) (k = 0–6). Additionally, we performed collision induced dissociation experiments, which indicated that the loss of pairs of oxygen atoms down to a YO+ core is the preferred fragmentation channel for all clusters investigated. Furthermore, we conduct DFT calculations and we obtained two types of low-energy structures: one containing an yttrium cation core and the other composed of YO+ core and O2 ligands, being in agreement with the observed fragmentation pattern. Finally, from the fragmentation studies, total collision cross sections are obtained and these are compared with geometrical cross sections of the calculated structures.

Dietary patterns in middle-aged Irish men and women defined by cluster analysis.

PubMed

Villegas, R; Salim, A; Collins, M M; Flynn, A; Perry, I J

2004-12-01

To identify and characterise dietary patterns in a middle-aged Irish population sample and study associations between these patterns, sociodemographic and anthropometric variables and major risk factors for cardiovascular disease. A cross-sectional study. A group of 1473 men and women were sampled from 17 general practice lists in the South of Ireland. A total of 1018 attended for screening, with a response rate of 69%. Participants completed a detailed health and lifestyle questionnaire and provided a fasting blood sample for glucose, lipids and homocysteine. Dietary intake was assessed using a standard food-frequency questionnaire adapted for use in the Irish population. The food-frequency questionnaire was a modification of that used in the UK arm of the European Prospective Investigation into Cancer study, which was based on that used in the US Nurses' Health Study. Dietary patterns were assessed primarily by K-means cluster analysis, following initial principal components analysis to identify the seeds. Three dietary patterns were identified. These clusters corresponded to a traditional Irish diet, a prudent diet and a diet characterised by high consumption of alcoholic drinks and convenience foods. Cluster 1 (Traditional Diet) had the highest intakes of saturated fat (SFA), monounsaturated fat (MUFA) and percentage of total energy from fat, and the lowest polyunsaturated fat (PUFA) intake and ratio of polyunsaturated to saturated fat (P:S). Cluster 2 (Prudent Diet) was characterised by significantly higher intakes of fibre, PUFA, P:S ratio and antioxidant vitamins (vitamins C and E), and lower intakes of total fat, MUFA, SFA and cholesterol. Cluster 3 (Alcohol & Convenience Foods) had the highest intakes of alcohol, protein, cholesterol, vitamin B(12), vitamin B(6), folate, iron, phosphorus, selenium and zinc, and the lowest intakes of PUFA, vitamin A and antioxidant vitamins (vitamins C and E). There were significant differences between clusters in gender distribution, smoking status, physical activity, body mass index, waist circumference and serum homocysteine concentrations. In this general population sample, cluster analysis methods yielded two major dietary patterns: prudent and traditional. The prudent dietary pattern is associated with other health-seeking behaviours. Study of dietary patterns will help elucidate links between diet and disease and contribute to the development of healthy eating guidelines for health promotion.

Modifiable lifestyle behavior patterns, sedentary time and physical activity contexts: a cluster analysis among middle school boys and girls in the SALTA study.

PubMed

Marques, Elisa A; Pizarro, Andreia N; Figueiredo, Pedro; Mota, Jorge; Santos, Maria P

2013-06-01

To analyze how modifiable health-related variables are clustered and associated with children's participation in play, active travel and structured exercise and sport among boys and girls. Data were collected from 9 middle-schools in Porto (Portugal) area. A total of 636 children in the 6th grade (340 girls and 296 boys) with a mean age of 11.64 years old participated in the study. Cluster analyses were used to identify patterns of lifestyle and healthy/unhealthy behaviors. Multinomial logistic regression analysis was used to estimate associations between cluster allocation, sedentary time and participation in three different physical activity (PA) contexts: play, active travel, and structured exercise/sport. Four distinct clusters were identified based on four lifestyle risk factors. The most disadvantaged cluster was characterized by high body mass index, low high-density lipoprotein cholesterol and cardiorespiratory fitness and a moderate level of moderate to vigorous PA. Everyday outdoor play (OR=1.85, 95%CI 0.318-0.915) and structured exercise/sport (OR=1.85, 95%CI 0.291-0.990) were associated with healthier lifestyle patterns. There were no significant associations between health patterns and sedentary time or travel mode. Outdoor play and sport/exercise participation seem more important than active travel from school in influencing children's healthy cluster profiles. Copyright © 2013 Elsevier Inc. All rights reserved.

Progressive colonization and restricted gene flow shape island-dependent population structure in Galápagos marine iguanas (Amblyrhynchus cristatus)

PubMed Central

2009-01-01

Background Marine iguanas (Amblyrhynchus cristatus) inhabit the coastlines of large and small islands throughout the Galápagos archipelago, providing a rich system to study the spatial and temporal factors influencing the phylogeographic distribution and population structure of a species. Here, we analyze the microevolution of marine iguanas using the complete mitochondrial control region (CR) as well as 13 microsatellite loci representing more than 1200 individuals from 13 islands. Results CR data show that marine iguanas occupy three general clades: one that is widely distributed across the northern archipelago, and likely spread from east to west by way of the South Equatorial current, a second that is found mostly on the older eastern and central islands, and a third that is limited to the younger northern and western islands. Generally, the CR haplotype distribution pattern supports the colonization of the archipelago from the older, eastern islands to the younger, western islands. However, there are also signatures of recurrent, historical gene flow between islands after population establishment. Bayesian cluster analysis of microsatellite genotypes indicates the existence of twenty distinct genetic clusters generally following a one-cluster-per-island pattern. However, two well-differentiated clusters were found on the easternmost island of San Cristóbal, while nine distinct and highly intermixed clusters were found on youngest, westernmost islands of Isabela and Fernandina. High mtDNA and microsatellite genetic diversity were observed for populations on Isabela and Fernandina that may be the result of a recent population expansion and founder events from multiple sources. Conclusions While a past genetic study based on pure FST analysis suggested that marine iguana populations display high levels of nuclear (but not mitochondrial) gene flow due to male-biased dispersal, the results of our sex-biased dispersal tests and the finding of strong genetic differentiation between islands do not support this view. Therefore, our study is a nice example of how recently developed analytical tools such as Bayesian clustering analysis and DNA sequence-based demographic analyses can overcome potential biases introduced by simply relying on FST estimates from markers with different inheritance patterns. PMID:20028547

Gear Shifting of Quadriceps during Isometric Knee Extension Disclosed Using Ultrasonography.

PubMed

Zhang, Shu; Huang, Weijian; Zeng, Yu; Shi, Wenxiu; Diao, Xianfen; Wei, Xiguang; Ling, Shan

2018-01-01

Ultrasonography has been widely employed to estimate the morphological changes of muscle during contraction. To further investigate the motion pattern of quadriceps during isometric knee extensions, we studied the relative motion pattern between femur and quadriceps under ultrasonography. An interesting observation is that although the force of isometric knee extension can be controlled to change almost linearly, femur in the simultaneously captured ultrasound video sequences has several different piecewise moving patterns. This phenomenon is like quadriceps having several forward gear ratios like a car starting from rest towards maximal voluntary contraction (MVC) and then returning to rest. Therefore, to verify this assumption, we captured several ultrasound video sequences of isometric knee extension and collected the torque/force signal simultaneously. Then we extract the shapes of femur from these ultrasound video sequences using video processing techniques and study the motion pattern both qualitatively and quantitatively. The phenomenon can be seen easier via a comparison between the torque signal and relative spatial distance between femur and quadriceps. Furthermore, we use cluster analysis techniques to study the process and the clustering results also provided preliminary support to the conclusion that, during both ramp increasing and decreasing phases, quadriceps contraction may have several forward gear ratios relative to femur.

Techniques for spatio-temporal analysis of vegetation fires in the topical belt of Africa

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

Brivio, P.A.; Ober, G.; Koffi, B.

1995-12-31

Biomass burning of forests and savannas is a phenomenon of continental or even global proportions, capable of causing large scale environmental changes. Satellite space observations, in particular from NOAA-AVHRR GAC data, are the only source of information allowing one to document burning patterns at regional and continental scale and over long periods of time. This paper presents some techniques, such as clustering and rose-diagram, useful in the spatial-temporal analysis of satellite derived fires maps to characterize the evolution of spatial patterns of vegetation fires at regional scale. An automatic clustering approach is presented which enables one to describe and parameterizemore » spatial distribution of fire patterns at different scales. The problem of geographical distribution of vegetation fires with respect to some location of interest, point or line, is also considered and presented. In particular rose-diagrams are used to relate fires patterns to some reference point, as experimental sites of tropospheric chemistry measurements. Different temporal data-sets in the tropical belt of Africa, covering both Northern and Southern Hemisphere dry seasons, using these techniques were analyzed and showed very promising results when compared with data from rain chemistry studies at different sampling sites in the equatorial forest.« less

Integrative analyses of conserved WNT clusters and their co-operative behaviour in human breast cancer

PubMed Central

Qurrat-ul-Ain; Seemab, Umair; Nawaz, Sulaman; Rashid, Sajid

2011-01-01

In human, WNT gene clusters are highly conserved at specie level and associated with carcinogenesis. Among them, WNT-10A and WNT-6 genes clustered in chromosome 2q35 are homologous to WNT-10B and WNT-1 located in chromosome 12q13, respectively. In an attempt to study co-regulation, the coordinated expression of these genes was monitored in human breast cancer tissues. As compared to normal tissue, both WNT-10A and WNT-10B genes exhibited lower expression while WNT-6 and WNT-1 showed increased expression in breast cancer tissues. The co-expression pattern was elaborated by detailed phylogenetic and syntenic analyses. Moreover, the intergenic and intragenic regions for these gene clusters were analyzed for studying the transcriptional regulation. In this context, adequate conserved binding sites for SOX and TCF family of transcriptional factors were observed. We propose that SOX9 and TCF4 may compete for binding at the promoters of WNT family genes thus regulating the disease phenotype. PMID:22355234

Clusters of cultures: diversity in meaning of family value and gender role items across Europe.

PubMed

van Vlimmeren, Eva; Moors, Guy B D; Gelissen, John P T M

2017-01-01

Survey data are often used to map cultural diversity by aggregating scores of attitude and value items across countries. However, this procedure only makes sense if the same concept is measured in all countries. In this study we argue that when (co)variances among sets of items are similar across countries, these countries share a common way of assigning meaning to the items. Clusters of cultures can then be observed by doing a cluster analysis on the (co)variance matrices of sets of related items. This study focuses on family values and gender role attitudes. We find four clusters of cultures that assign a distinct meaning to these items, especially in the case of gender roles. Some of these differences reflect response style behavior in the form of acquiescence. Adjusting for this style effect impacts on country comparisons hence demonstrating the usefulness of investigating the patterns of meaning given to sets of items prior to aggregating scores into cultural characteristics.

Breaking the power law: Multiscale simulations of self-ion irradiated tungsten

NASA Astrophysics Data System (ADS)

Jin, Miaomiao; Permann, Cody; Short, Michael P.

2018-06-01

The initial stage of radiation defect creation has often been shown to follow a power law distribution at short time scales, recently so with tungsten, following many self-organizing patterns found in nature. The evolution of this damage, however, is dominated by interactions between defect clusters, as the coalescence of smaller defects into clusters depends on the balance between transport, absorption, and emission to/from existing clusters. The long-time evolution of radiation-induced defects in tungsten is studied with cluster dynamics parameterized with lower length scale simulations, and is shown to deviate from a power law size distribution. The effects of parameters such as dose rate and total dose, as parameters affecting the strength of the driving force for defect evolution, are also analyzed. Excellent agreement is achieved with regards to an experimentally measured defect size distribution at 30 K. This study provides another satisfactory explanation for experimental observations in addition to that of primary radiation damage, which should be reconciled with additional validation data.

Patterns of victimization between and within peer clusters in a high school social network.

PubMed

Swartz, Kristin; Reyns, Bradford W; Wilcox, Pamela; Dunham, Jessica R

2012-01-01

This study presents a descriptive analysis of patterns of violent victimization between and within the various cohesive clusters of peers comprising a sample of more than 500 9th-12th grade students from one high school. Social network analysis techniques provide a visualization of the overall friendship network structure and allow for the examination of variation in victimization across the various peer clusters within the larger network. Social relationships among clusters with varying levels of victimization are also illustrated so as to provide a sense of possible spatial clustering or diffusion of victimization across proximal peer clusters. Additionally, to provide a sense of the sorts of peer clusters that support (or do not support) victimization, characteristics of clusters at both the high and low ends of the victimization scale are discussed. Finally, several of the peer clusters at both the high and low ends of the victimization continuum are "unpacked", allowing examination of within-network individual-level differences in victimization for these select clusters.

Fractal patterns formed by growth of radial viscous fingers*

NASA Astrophysics Data System (ADS)

Praud, Olivier

2004-03-01

We examine fractal patterns formed by the injection of air into oil in a thin (0.13 mm) layer contained between two cylindrical glass plates of 288 mm diameter (a Hele-Shaw cell) [1]. The resultant radially grown patterns are similar to those formed in Diffusion Limited Aggregation (DLA), but the relation between the continuum limit of DLA and continuum (Laplacian) growth remains an open question. Our viscous fingering patterns in the limit of very high pressure difference reach an asymptotic state in which they exhibit a fractal dimension of 1.70± 0.02, in good agreement with a calculation of the fractal dimension of a DLA cluster, 1.713± 0.003 [2]. The generalized dimensions are also computed and show that the observed pattern is self-similar with Dq = 1.70 for all q. Further, the probability density function of shielding angles suggests the existence of a critical angle close to 75 degrees. This result is in accord with numerical and analytical evidence of a critical angle in DLA [3]. Thus fractal viscous fingering patterns and Diffusion Limited Aggregation clusters have a similar geometrical structure. *Work conducted in collaboration with H.L. Swinney, M.G. Moore and Eran Sharon [1] E. Sharon, M. G. Moore, W. D. McCormick, and H. L. Swinney, Phys. Rev. Lett. 91, 205504 (2003). [2] B.Davidovitch et A. Levermann and I. Procaccia, Phys. Rev. E 62, 5919 (2000). [3] D. A. Kessler et al., Phys. Rev. E 57, 6913 (1998).

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, G.C.; Martinez, R.F.

1999-05-04

A method of clustering using a novel template to define a region of influence is disclosed. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques. 30 figs.

Patterns of Cluster Reduction in the Acquisition of #sC Onsets: Are Bilinguals Different from Monolinguals?

ERIC Educational Resources Information Center

Yavas, Mehmet

2011-01-01

This article is a comparative look at the cluster reduction patterns of English #sC onsets in three groups of children. Data from 40 monolingual, 40 Spanish-English bilingual and 40 Haitian Creole-English bilingual children were examined. While there were several similarities in the patterns exhibited by the three groups, there was a sharp…

Gait patterns in hemiplegic patients with equinus foot deformity.

PubMed

Manca, M; Ferraresi, G; Cosma, M; Cavazzuti, L; Morelli, M; Benedetti, M G

2014-01-01

Equinus deformity of the foot is a common feature of hemiplegia, which impairs the gait pattern of patients. The aim of the present study was to explore the role of ankle-foot deformity in gait impairment. A hierarchical cluster analysis was used to classify the gait patterns of 49 chronic hemiplegic patients with equinus deformity of the foot, based on temporal-distance parameters and joint kinematic measures obtained by an innovative protocol for motion assessment in the sagittal, frontal, and transverse planes, synthesized by parametrical analysis. Cluster analysis identified five subgroups of patients with homogenous levels of dysfunction during gait. Specific joint kinematic abnormalities were found, according to the speed of progression in each cluster. Patients with faster walking were those with less ankle-foot complex impairment or with reduced range of motion of ankle-foot complex, that is with a stiff ankle-foot complex. Slow walking was typical of patients with ankle-foot complex instability (i.e., larger motion in all the planes), severe equinus and hip internal rotation pattern, and patients with hip external rotation pattern. Clustering of gait patterns in these patients is helpful for a better understanding of dysfunction during gait and delivering more targeted treatment.

Acquisition of /s/-Clusters in Dutch-Speaking Children with Phonological Disorders

ERIC Educational Resources Information Center

Gerrits, Ellen

2010-01-01

This study investigated the acquisition of word initial s clusters of 3-5 year old Dutch children with phonological disorders. Within these clusters, sl was produced correctly most often, whereas sn and sx were the more difficult clusters. In cluster reductions, s+obstruent and sl clusters reduction patterns followed the Sonority Sequencing…

Differences in clinical characteristics and frequency of accompanying migraine features in episodic and chronic cluster headache.

PubMed

Gaul, C; Christmann, N; Schröder, D; Weber, R; Shanib, H; Diener, H C; Holle, D

2012-05-01

Data on clinical differences between episodic (eCH) and chronic cluster headache (cCH) and accompanying migraine features are limited. History and clinical features of 209 consecutive cluster headache patients (144 eCH, 65 cCH; male:female ratio 3.4 : 1) were obtained in a tertiary headache centre by face-to-face interviews. Relationship between occurrence of accompanying symptoms, pain intensity, comorbid migraine, and circannual and circadian rhythmicity was analysed. 99.5% of patients reported a minimum of one ipsilateral cranial autonomic symptom (CAS); 80% showed at least three CAS. A seasonal rhythmicity was observed in both eCH and cCH. A comorbid headache disorder occurred in 25%. No significant difference was detected between patients with comorbid migraine and without regarding occurrence of phonophobia, photophobia or nausea during cluster attacks. Patients with comorbid migraine reported allodynia significantly (p = 0.022) more often during cluster attacks than patients without comorbid migraine. Occurrence of CAS and attack frequency, as well as periodic patterns of attacks, are relatively uniform in eCH and cCH. Multiple CAS are not related to pain intensity. Allodynia during cluster attacks is a frequent symptom. The unexpectedly high rate of accompanying migrainous features during cluster attacks cannot be explained by comorbid migraine.

Unveiling hidden properties of young star clusters: differential reddening, star-formation spread, and binary fraction

NASA Astrophysics Data System (ADS)

Bonatto, C.; Lima, E. F.; Bica, E.

2012-04-01

Context. Usually, important parameters of young, low-mass star clusters are very difficult to obtain by means of photometry, especially when differential reddening and/or binaries occur in large amounts. Aims: We present a semi-analytical approach (ASAmin) that, when applied to the Hess diagram of a young star cluster, is able to retrieve the values of mass, age, star-formation spread, distance modulus, foreground and differential reddening, and binary fraction. Methods: The global optimisation method known as adaptive simulated annealing (ASA) is used to minimise the residuals between the observed and simulated Hess diagrams of a star cluster. The simulations are realistic and take the most relevant parameters of young clusters into account. Important features of the simulations are a normal (Gaussian) differential reddening distribution, a time-decreasing star-formation rate, the unresolved binaries, and the smearing effect produced by photometric uncertainties on Hess diagrams. Free parameters are cluster mass, age, distance modulus, star-formation spread, foreground and differential reddening, and binary fraction. Results: Tests with model clusters built with parameters spanning a broad range of values show that ASAmin retrieves the input values with a high precision for cluster mass, distance modulus, and foreground reddening, but they are somewhat lower for the remaining parameters. Given the statistical nature of the simulations, several runs should be performed to obtain significant convergence patterns. Specifically, we find that the retrieved (absolute minimum) parameters converge to mean values with a low dispersion as the Hess residuals decrease. When applied to actual young clusters, the retrieved parameters follow convergence patterns similar to the models. We show how the stochasticity associated with the early phases may affect the results, especially in low-mass clusters. This effect can be minimised by averaging out several twin clusters in the simulated Hess diagrams. Conclusions: Even for low-mass star clusters, ASAmin is sensitive to the values of cluster mass, age, distance modulus, star-formation spread, foreground and differential reddening, and to a lesser degree, binary fraction. Compared with simpler approaches, including binaries, a decaying star-formation rate, and a normally distributed differential reddening appears to yield more constrained parameters, especially the mass, age, and distance from the Sun. A robust determination of cluster parameters may have a positive impact on many fields. For instance, age, mass, and binary fraction are important for establishing the dynamical state of a cluster or for deriving a more precise star-formation rate in the Galaxy.

Elucidation of the Pattern of the Onset of Male Lower Urinary Tract Symptoms Using Cluster Analysis: Efficacy of Tamsulosin in Each Symptom Group.

PubMed

Aikawa, Ken; Kataoka, Masao; Ogawa, Soichiro; Akaihata, Hidenori; Sato, Yuichi; Yabe, Michihiro; Hata, Junya; Koguchi, Tomoyuki; Kojima, Yoshiyuki; Shiragasawa, Chihaya; Kobayashi, Toshimitsu; Yamaguchi, Osamu

2015-08-01

To present a new grouping of male patients with lower urinary tract symptoms (LUTS) based on symptom patterns and clarify whether the therapeutic effect of α1-blocker differs among the groups. We performed secondary analysis of anonymous data from 4815 patients enrolled in a postmarketing surveillance study of tamsulosin in Japan. Data on 7 International Prostate Symptom Score (IPSS) items at the initial visit were used in the cluster analysis. IPSS and quality of life (QOL) scores before and after tamsulosin treatment for 12 weeks were assessed in each cluster. Partial correlation coefficients were also obtained for IPSS and QOL scores based on changes before and after treatment. Five symptom groups were identified by cluster analysis of IPSS. On their symptom profile, each cluster was labeled as minimal type (cluster 1), multiple severe type (cluster 2), weak stream type (cluster 3), storage type (cluster 4), and voiding type (cluster 5). Prevalence and the mean symptom score were significantly improved in almost all symptoms in all clusters by tamsulosin treatment. Nocturia and weak stream had the strongest effect on QOL in clusters 1, 2, and 4 and clusters 3 and 5, respectively. The study clarified that 5 characteristic symptom patterns exist by cluster analysis of IPSS in male patients with LUTS. Tamsulosin improved various symptoms and QOL in each symptom group. The study reports many male patients with LUTS being satisfied with monotherapy using tamsulosin and suggests the usefulness of α1-blockers as a drug of first choice. Copyright © 2015 Elsevier Inc. All rights reserved.

Clustering of spontaneous recurrent seizures separated by long seizure-free periods: An extended video-EEG monitoring study of a pilocarpine mouse model.

PubMed

Lim, Jung-Ah; Moon, Jangsup; Kim, Tae-Joon; Jun, Jin-Sun; Park, Byeongsu; Byun, Jung-Ick; Sunwoo, Jun-Sang; Park, Kyung-Il; Lee, Soon-Tae; Jung, Keun-Hwa; Jung, Ki-Young; Kim, Manho; Jeon, Daejong; Chu, Kon; Lee, Sang Kun

2018-01-01

Seizure clustering is a common and significant phenomenon in patients with epilepsy. The clustering of spontaneous recurrent seizures (SRSs) in animal models of epilepsy, including mouse pilocarpine models, has been reported. However, most studies have analyzed seizures for a short duration after the induction of status epilepticus (SE). In this study, we investigated the detailed characteristics of seizure clustering in the chronic stage of a mouse pilocarpine-induced epilepsy model for an extended duration by continuous 24/7 video-EEG monitoring. A seizure cluster was defined as the occurrence of one or more seizures per day for at least three consecutive days and at least five seizures during the cluster period. We analyzed the cluster duration, seizure-free period, cluster interval, and numbers of seizures within and outside the seizure clusters. The video-EEG monitoring began 84.5±33.7 days after the induction of SE and continued for 53.7±20.4 days. Every mouse displayed seizure clusters, and 97.0% of the seizures occurred within a cluster period. The seizure clusters were followed by long seizure-free periods of 16.3±6.8 days, showing a cyclic pattern. The SRSs also occurred in a grouped pattern within a day. We demonstrate that almost all seizures occur in clusters with a cyclic pattern in the chronic stage of a mouse pilocarpine-induced epilepsy model. The seizure-free periods between clusters were long. These findings should be considered when performing in vivo studies using this animal model. Furthermore, this model might be appropriate for studying the unrevealed mechanism of ictogenesis.

Mining Co-Location Patterns with Clustering Items from Spatial Data Sets

NASA Astrophysics Data System (ADS)

Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.

2018-05-01

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.

Computational identification of developmental enhancers:conservation and function of transcription factor binding-site clustersin drosophila melanogaster and drosophila psedoobscura

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

Berman, Benjamin P.; Pfeiffer, Barret D.; Laverty, Todd R.

2004-08-06

Background The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. Results We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene,more » and assayed embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. Conclusions Measuring conservation of sequence features closely linked to function - such as binding-site clustering - makes better use of comparative sequence data than commonly used methods that examine only sequence identity.« less

Off-road truck-related accidents in U.S. mines

PubMed Central

Dindarloo, Saeid R.; Pollard, Jonisha P.; Siami-Irdemoosa, Elnaz

2016-01-01

Introduction Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. Methods A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Results Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5 years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. Conclusions The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Practical application Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. PMID:27620937

Off-road truck-related accidents in U.S. mines.

PubMed

Dindarloo, Saeid R; Pollard, Jonisha P; Siami-Irdemoosa, Elnaz

2016-09-01

Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

Changes in Cerebral Blood Flow during an Alteration in Glycemic State in a Large Non-human Primate (Papio hamadryas sp.).

PubMed

Kochunov, Peter; Wey, Hsiao-Ying; Fox, Peter T; Lancaster, Jack L; Davis, Michael D; Wang, Danny J J; Lin, Ai-Ling; Bastarrachea, Raul A; Andrade, Marcia C R; Mattern, Vicki; Frost, Patrice; Higgins, Paul B; Comuzzie, Anthony G; Voruganti, Venkata S

2017-01-01

Changes in cerebral blood flow (CBF) during a hyperglycemic challenge were mapped, using perfusion-weighted MRI, in a group of non-human primates. Seven female baboons were fasted for 16 h prior to 1-h imaging experiment, performed under general anesthesia, that consisted of a 20-min baseline, followed by a bolus infusion of glucose (500 mg/kg). CBF maps were collected every 7 s and blood glucose and insulin levels were sampled at regular intervals. Blood glucose levels rose from 51.3 ± 10.9 to 203.9 ± 38.9 mg/dL and declined to 133.4 ± 22.0 mg/dL, at the end of the experiment. Regional CBF changes consisted of four clusters: cerebral cortex, thalamus, hypothalamus, and mesencephalon. Increases in the hypothalamic blood flow occurred concurrently with the regulatory response to systemic glucose change, whereas CBF declined for other clusters. The return to baseline of hypothalamic blood flow was observed while CBF was still increasing in other brain regions. The spatial pattern of extra-hypothalamic CBF changes was correlated with the patterns of several cerebral networks including the default mode network. These findings suggest that hypothalamic blood flow response to systemic glucose levels can potentially be explained by regulatory activity. The response of extra-hypothalamic clusters followed a different time course and its spatial pattern resembled that of the default-mode network.

The Role of Deep Creep in the Timing of Large Earthquakes

NASA Astrophysics Data System (ADS)

Sammis, C. G.; Smith, S. W.

2012-12-01

The observed temporal clustering of the world's largest earthquakes has been largely discounted for two reasons: a) it is consistent with Poisson clustering, and b) no physical mechanism leading to such clustering has been proposed. This lack of a mechanism arises primarily because the static stress transfer mechanism, commonly used to explain aftershocks and the clustering of large events on localized fault networks, does not work at global distances. However, there is recent observational evidence that the surface waves from large earthquakes trigger non-volcanic tremor at the base of distant fault zones at global distances. Based on these observations, we develop a simple non-linear coupled oscillator model that shows how the triggering of such tremor can lead to the synchronization of large earthquakes on a global scale. A basic assumption of the model is that induced tremor is a proxy for deep creep that advances the seismic cycle of the fault. We support this hypothesis by demonstrating that the 2010 Maule Chile and the 2011 Fukushima Japan earthquakes, which have been shown to induce tremor on the Parkfield segment of the San Andreas Fault, also produce changes in off-fault seismicity that are spatially and temporally consistent with episodes of deep creep on the fault. The observed spatial pattern can be simulated using an Okada dislocation model for deep creep (below 20 km) on the fault plane in which the slip rate decreases from North to South consistent with surface creep measurements and deepens south of the "Parkfield asperity" as indicated by recent tremor locations. The model predicts the off-fault events should have reverse mechanism consistent with observed topography.

Intracluster age gradients in numerous young stellar clusters

NASA Astrophysics Data System (ADS)

Getman, K. V.; Feigelson, E. D.; Kuhn, M. A.; Bate, M. R.; Broos, P. S.; Garmire, G. P.

2018-05-01

The pace and pattern of star formation leading to rich young stellar clusters is quite uncertain. In this context, we analyse the spatial distribution of ages within 19 young (median t ≲ 3 Myr on the Siess et al. time-scale), morphologically simple, isolated, and relatively rich stellar clusters. Our analysis is based on young stellar object (YSO) samples from the Massive Young Star-Forming Complex Study in Infrared and X-ray and Star Formation in Nearby Clouds surveys, and a new estimator of pre-main sequence (PMS) stellar ages, AgeJX, derived from X-ray and near-infrared photometric data. Median cluster ages are computed within four annular subregions of the clusters. We confirm and extend the earlier result of Getman et al. (2014): 80 per cent of the clusters show age trends where stars in cluster cores are younger than in outer regions. Our cluster stacking analyses establish the existence of an age gradient to high statistical significance in several ways. Time-scales vary with the choice of PMS evolutionary model; the inferred median age gradient across the studied clusters ranges from 0.75 to 1.5 Myr pc-1. The empirical finding reported in the present study - late or continuing formation of stars in the cores of star clusters with older stars dispersed in the outer regions - has a strong foundation with other observational studies and with the astrophysical models like the global hierarchical collapse model of Vázquez-Semadeni et al.

Sudden appearance of sub-keV structured ions in the inner magnetosphere within one hour: drift simulation

NASA Astrophysics Data System (ADS)

Yamauchi, Masatoshi; Ebihara, Yusuke; Dandouras, Iannis; Nilsson, Hans

2014-05-01

Energy-latitude dispersed structured sub-keV ions in the inner magnetosphere drifts very slowly in the noon-to-afternoon sectors because the eastward corotation and the westward magnetic drift balances to each other there. However, majority of Cluster ion observation by the Cluster Ion Spectrometry (CIS) COmposition DIstribution Function (CODIF) instrument during 2001-2006 showed significant development or intensification (by more than factor of 3) within 1-2 h in that sector during the Cluster perigee traversals that quickly scans latitudinal structure at a fixed local time (Yamauchi et al., 2013). The frequent observations of significant inbound-outbound differences in the wedge-like dispersed ions by Cluster indicates either new injections or high eastward drift velocity even in the afternoon sector. To examine the former possibility, i.e., whether such sudden appearances in the dayside can be explained by the drift motion of ions that are formed during substorm-related injections, we numerically simulated two such examples, one at noon (8 September 2002) and the other in the afternoon (9 July 2001), based on the same ion drift simulation model that has successfully reproduced the ion pattern of an inbound-outbound symmetric event at 5 MLT observed by the Cluster CIS/CODIF instrument. The model uses backward phase-space mapping to a boundary at the nightside 8 Earth radii and forward numerical simulation using re-constructed distribution function at that boundary. For both examples, the ion drift model with finite duration (limited to 1-2 hours) of proton source in the nightside can explain the observed large inbound-outbound differences in the sub-keV proton population without any new sources. Ion drift motion is thus able to cause rapid changes of complicated ion populations, at remote places from the source long time after the substorm activities, although this result does not eliminate the possibility of having independent ionospheric sources. References: Yamauchi, M. et al.: Cluster observation of few-hour-scale evolution of structured plasma in the inner magnetosphere, Ann. Geophys., 31, 1569-1578, doi:10.5194/angeo-31-1569-2013, 2013.

Supra-galactic colour patterns in globular cluster systems

NASA Astrophysics Data System (ADS)

Forte, Juan C.

2017-07-01

An analysis of globular cluster systems associated with galaxies included in the Virgo and Fornax Hubble Space Telescope-Advanced Camera Surveys reveals distinct (g - z) colour modulation patterns. These features appear on composite samples of globular clusters and, most evidently, in galaxies with absolute magnitudes Mg in the range from -20.2 to -19.2. These colour modulations are also detectable on some samples of globular clusters in the central galaxies NGC 1399 and NGC 4486 (and confirmed on data sets obtained with different instruments and photometric systems), as well as in other bright galaxies in these clusters. After discarding field contamination, photometric errors and statistical effects, we conclude that these supra-galactic colour patterns are real and reflect some previously unknown characteristic. These features suggest that the globular cluster formation process was not entirely stochastic but included a fraction of clusters that formed in a rather synchronized fashion over large spatial scales, and in a tentative time lapse of about 1.5 Gy at redshifts z between 2 and 4. We speculate that the putative mechanism leading to that synchronism may be associated with large scale feedback effects connected with violent star-forming events and/or with supermassive black holes.

Fatality rate of pedestrians and fatal crash involvement rate of drivers in pedestrian crashes: a case study of Iran.

PubMed

Kashani, Ali Tavakoli; Besharati, Mohammad Mehdi

2017-06-01

The aim of this study was to uncover patterns of pedestrian crashes. In the first stage, 34,178 pedestrian-involved crashes occurred in Iran during a four-year period were grouped into homogeneous clusters using a clustering analysis. Next, some in-cluster and inter-cluster crash patterns were analysed. The clustering analysis yielded six pedestrian crash groups. Car/van/pickup crashes on rural roads as well as heavy vehicle crashes were found to be less frequent but more likely to be fatal compared to other crash clusters. In addition, after controlling for crash frequency in each cluster, it was found that the fatality rate of each pedestrian age group as well as the fatal crash involvement rate of each driver age group varies across the six clusters. Results of present study has some policy implications including, promoting pedestrian safety training sessions for heavy vehicle drivers, imposing limitations over elderly heavy vehicle drivers, reinforcing penalties toward under 19 drivers and motorcyclists. In addition, road safety campaigns in rural areas may be promoted to inform people about the higher fatality rate of pedestrians on rural roads. The crash patterns uncovered in this study might also be useful for prioritizing future pedestrian safety research areas.

Patterns of amino acid conservation in human and animal immunodeficiency viruses.

PubMed

Voitenko, Olga S; Dhroso, Andi; Feldmann, Anna; Korkin, Dmitry; Kalinina, Olga V

2016-09-01

Due to their high genomic variability, RNA viruses and retroviruses present a unique opportunity for detailed study of molecular evolution. Lentiviruses, with HIV being a notable example, are one of the best studied viral groups: hundreds of thousands of sequences are available together with experimentally resolved three-dimensional structures for most viral proteins. In this work, we use these data to study specific patterns of evolution of the viral proteins, and their relationship to protein interactions and immunogenicity. We propose a method for identification of two types of surface residues clusters with abnormal conservation: extremely conserved and extremely variable clusters. We identify them on the surface of proteins from HIV and other animal immunodeficiency viruses. Both types of clusters are overrepresented on the interaction interfaces of viral proteins with other proteins, nucleic acids or low molecular-weight ligands, both in the viral particle and between the virus and its host. In the immunodeficiency viruses, the interaction interfaces are not more conserved than the corresponding proteins on an average, and we show that extremely conserved clusters coincide with protein-protein interaction hotspots, predicted as the residues with the largest energetic contribution to the interaction. Extremely variable clusters have been identified here for the first time. In the HIV-1 envelope protein gp120, they overlap with known antigenic sites. These antigenic sites also contain many residues from extremely conserved clusters, hence representing a unique interacting interface enriched both in extremely conserved and in extremely variable clusters of residues. This observation may have important implication for antiretroviral vaccine development. A Python package is available at https://bioinf.mpi-inf.mpg.de/publications/viral-ppi-pred/ voitenko@mpi-inf.mpg.de or kalinina@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Necessary Sequencing Depth and Clustering Method to Obtain Relatively Stable Diversity Patterns in Studying Fish Gut Microbiota.

PubMed

Xiao, Fanshu; Yu, Yuhe; Li, Jinjin; Juneau, Philippe; Yan, Qingyun

2018-05-25

The 16S rRNA gene is one of the most commonly used molecular markers for estimating bacterial diversity during the past decades. However, there is no consistency about the sequencing depth (from thousand to millions of sequences per sample), and the clustering methods used to generate OTUs may also be different among studies. These inconsistent premises make effective comparisons among studies difficult or unreliable. This study aims to examine the necessary sequencing depth and clustering method that would be needed to ensure a stable diversity patterns for studying fish gut microbiota. A total number of 42 samples dataset of Siniperca chuatsi (carnivorous fish) gut microbiota were used to test how the sequencing depth and clustering may affect the alpha and beta diversity patterns of fish intestinal microbiota. Interestingly, we found that the sequencing depth (resampling 1000-11,000 per sample) and the clustering methods (UPARSE and UCLUST) did not bias the estimates of the diversity patterns during the fish development from larva to adult. Although we should acknowledge that a suitable sequencing depth may differ case by case, our finding indicates that a shallow sequencing such as 1000 sequences per sample may be also enough to reflect the general diversity patterns of fish gut microbiota. However, we have shown in the present study that strict pre-processing of the original sequences is required to ensure reliable results. This study provides evidences to help making a strong scientific choice of the sequencing depth and clustering method for future studies on fish gut microbiota patterns, but at the same time reducing as much as possible the costs related to the analysis.

Potential of SNP markers for the characterization of Brazilian cassava germplasm.

PubMed

de Oliveira, Eder Jorge; Ferreira, Cláudia Fortes; da Silva Santos, Vanderlei; de Jesus, Onildo Nunes; Oliveira, Gilmara Alvarenga Fachardo; da Silva, Maiane Suzarte

2014-06-01

High-throughput markers, such as SNPs, along with different methodologies were used to evaluate the applicability of the Bayesian approach and the multivariate analysis in structuring the genetic diversity in cassavas. The objective of the present work was to evaluate the diversity and genetic structure of the largest cassava germplasm bank in Brazil. Complementary methodological approaches such as discriminant analysis of principal components (DAPC), Bayesian analysis and molecular analysis of variance (AMOVA) were used to understand the structure and diversity of 1,280 accessions genotyped using 402 single nucleotide polymorphism markers. The genetic diversity (0.327) and the average observed heterozygosity (0.322) were high considering the bi-allelic markers. In terms of population, the presence of a complex genetic structure was observed indicating the formation of 30 clusters by DAPC and 34 clusters by Bayesian analysis. Both methodologies presented difficulties and controversies in terms of the allocation of some accessions to specific clusters. However, the clusters suggested by the DAPC analysis seemed to be more consistent for presenting higher probability of allocation of the accessions within the clusters. Prior information related to breeding patterns and geographic origins of the accessions were not sufficient for providing clear differentiation between the clusters according to the AMOVA analysis. In contrast, the F ST was maximized when considering the clusters suggested by the Bayesian and DAPC analyses. The high frequency of germplasm exchange between producers and the subsequent alteration of the name of the same material may be one of the causes of the low association between genetic diversity and geographic origin. The results of this study may benefit cassava germplasm conservation programs, and contribute to the maximization of genetic gains in breeding programs.

A Genetic Algorithm That Exchanges Neighboring Centers for Fuzzy c-Means Clustering

ERIC Educational Resources Information Center

Chahine, Firas Safwan

2012-01-01

Clustering algorithms are widely used in pattern recognition and data mining applications. Due to their computational efficiency, partitional clustering algorithms are better suited for applications with large datasets than hierarchical clustering algorithms. K-means is among the most popular partitional clustering algorithm, but has a major…

Reconstruction of sediment transport pathways in modern microtidal sand flat by multiple classification analysis

NASA Astrophysics Data System (ADS)

Yamashita, S.; Nakajo, T.; Naruse, H.

2009-12-01

In this study, we statistically classified the grain size distribution of the bottom surface sediment on a microtidal sand flat to analyze the depositional processes of the sediment. Multiple classification analysis revealed that two types of sediment populations exist in the bottom surface sediment. Then, we employed the sediment trend model developed by Gao and Collins (1992) for the estimation of sediment transport pathways. As a result, we found that statistical discrimination of the bottom surface sediment provides useful information for the sediment trend model while dealing with various types of sediment transport processes. The microtidal sand flat along the Kushida River estuary, Ise Bay, central Japan, was investigated, and 102 bottom surface sediment samples were obtained. Then, their grain size distribution patterns were measured by the settling tube method, and each grain size distribution parameter (mud and gravel contents, mean grain size, coefficient of variance (CV), skewness, kurtosis, 5, 25, 50, 75, and 95 percentile) was calculated. Here, CV is the normalized sorting value divided by the mean grain size. Two classical statistical methods—principal component analysis (PCA) and fuzzy cluster analysis—were applied. The results of PCA showed that the bottom surface sediment of the study area is mainly characterized by grain size (mean grain size and 5-95 percentile) and the CV value, indicating predominantly large absolute values of factor loadings in primal component (PC) 1. PC1 is interpreted as being indicative of the grain-size trend, in which a finer grain-size distribution indicates better size sorting. The frequency distribution of PC1 has a bimodal shape and suggests the existence of two types of sediment populations. Therefore, we applied fuzzy cluster analysis, the results of which revealed two groupings of the sediment (Cluster 1 and Cluster 2). Cluster 1 shows a lower value of PC1, indicating coarse and poorly sorted sediments. Cluster 1 sediments are distributed around the branched channel from Kushida River and show an expanding distribution from the river mouth toward the northeast direction. Cluster 2 shows a higher value of PC1, indicating fine and well-sorted sediments; this cluster is distributed in a distant area from the river mouth, including the offshore region. Therefore, Cluster 1 and Cluster 2 are interpreted as being deposited by fluvial and wave processes, respectively. Finally, on the basis of this distribution pattern, the sediment trend model was applied in areas dominated separately by fluvial and wave processes. Resultant sediment transport patterns showed good agreement with those obtained by field observations. The results of this study provide an important insight into the numerical models of sediment transport.

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

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

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Patterns of Physical and Relational Aggression in a School-Based Sample of Boys and Girls

ERIC Educational Resources Information Center

Crapanzano, Ann Marie; Frick, Paul J.; Terranova, Andrew M.

2010-01-01

The current study investigated the patterns of aggressive behavior displayed in a sample of 282 students in the 4th through 7th grades (M age = 11.28; SD = 1.82). Using cluster analyses, two distinct patterns of physical aggression emerged for both boys and girls with one aggressive cluster showing mild levels of reactive aggression and one group…

Segmentation and supercycles: A catalog of earthquake cycle complexities from the Sumatran Sunda Megathrust and other well-studied faults worldwide

NASA Astrophysics Data System (ADS)

Philibosian, B.; Meltzner, A. J.; Sieh, K.

2017-12-01

Understanding earthquake cycle processes is key to both seismic hazard and fault mechanics. A concept that has come into focus recently is that rupture segmentation and cyclicity can be complex, and that simple models of periodically repeating similar earthquakes are inadequate. The term "supercycle" has been used to describe repeating longer periods of strain accumulation that involve multiple fault ruptures. However, this term has become broadly applied, lumping together several distinct phenomena that likely have disparate underlying causes. Earthquake recurrence patterns have often been described as "clustered," but this term is also imprecise. It is necessary to develop a terminology framework that consistently and meaningfully describes all types of behavior that are observed. We divide earthquake cycle patterns into four major classes, each having different implications for seismic hazard and fault mechanics: 1) quasi-periodic similar ruptures, 2) temporally clustered similar ruptures, 3) temporally clustered complementary ruptures, also known as rupture cascades, in which neighboring fault patches fail sequentially, and 4) superimposed cycles in which neighboring fault patches have cycles with different recurrence intervals, but may occasionally rupture together. Rupture segmentation is classified as persistent, frequent, or transient depending on how reliably ruptures terminate in a given area. We discuss the paleoseismic and historical evidence currently available for each of these types of behavior on subduction zone megathrust faults worldwide. Due to the unique level of paleoseismic and paleogeodetic detail provided by the coral microatoll technique, the Sumatran Sunda megathrust provides one of the most complete records over multiple seismic cycles. Most subduction zones with sufficient data exhibit examples of persistent and frequent segmentation, with cycle patterns 1, 3, and 4 on different segments. Pattern 2 is generally confined to overlap zones between segments. This catalog of seismic cycle observations provides a basis for exploring and modeling root causes of rupture segmentation and cycle behavior. Researchers should expect to discover similar behavior styles on other megathrust faults and perhaps major crustal faults around the world.

Distribution of Spoligotyping Defined Genotypic Lineages among Drug-Resistant Mycobacterium tuberculosis Complex Clinical Isolates in Ankara, Turkey

PubMed Central

Kisa, Ozgul; Tarhan, Gulnur; Gunal, Selami; Albay, Ali; Durmaz, Riza; Saribas, Zeynep; Zozio, Thierry; Alp, Alpaslan; Ceyhan, Ismail; Tombak, Ahmet; Rastogi, Nalin

2012-01-01

Background Investigation of genetic heterogeneity and spoligotype-defined lineages of drug-resistant Mycobacterium tuberculosis clinical isolates collected during a three-year period in two university hospitals and National Tuberculosis Reference and Research Laboratory in Ankara, Turkey. Methods and Findings A total of 95 drug-resistant M. tuberculosis isolates collected from three different centers were included in this study. Susceptibility testing of the isolates to four major antituberculous drugs was performed using proportion method on Löwenstein–Jensen medium and BACTEC 460-TB system. All clinical isolates were typed by using spoligotyping and IS6110-restriction fragment length polymorphism (RFLP) methods. Seventy-three of the 95 (76.8%) drug resistant M. tuberculosis isolates were isoniazid-resistant, 45 (47.4%) were rifampicin-resistant, 32 (33.7%) were streptomycin-resistant and 31 (32.6%) were ethambutol-resistant. The proportion of multidrug-resistant isolates (MDR) was 42.1%. By using spoligotyping, 35 distinct patterns were observed; 75 clinical isolates were grouped in 15 clusters (clustering rate of 79%) and 20 isolates displayed unique patterns. Five of these 20 unique patterns corresponded to orphan patterns in the SITVIT2 database, while 4 shared types containing 8 isolates were newly created. The most prevalent M. tuberculosis lineages were: Haarlem (23/95, 24.2%), ill-defined T superfamily (22/95, 23.2%), the Turkey family (19/95, 20%; previously designated as LAM7-TUR), Beijing (6/95, 6.3%), and Latin-America & Mediterranean (LAM, 5/95 or 5.3%), followed by Manu (3/95, 3.2%) and S (1/95, 1%) lineages. Four of the six Beijing family isolates (66.7%) were MDR. A combination of IS6110-RFLP and spoligotyping reduced the clustering rate from 79% to 11.5% among the drug resistant isolates. Conclusions The results obtained showed that ill-defined T, Haarlem, the Turkey family (previously designated as LAM7-TUR family with high phylogeographical specifity for Turkey), Beijing and LAM were predominant lineages observed in almost 80% of the drug-Resistant M. tuberculosis complex clinical isolates in Ankara, Turkey. PMID:22279583

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

PubMed Central

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

2015-01-01

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

Winter precipitation forecast in the European and Mediterranean regions using cluster analysis

NASA Astrophysics Data System (ADS)

Molnos, S.

2017-12-01

The European and Mediterranean climates are sensitive to large-scale circulation of the atmosphere andocean making it difficult to forecast precipitation or temperature on seasonal time-scales. In addition, theMediterranean region has been identified as a hotspot for climate change and already today a drying in theMediterranean region is observed.Thus, it is critically important to predict seasonal droughts as early as possible such that water managersand stakeholders can mitigate impacts.We developed a novel cluster-based forecast method to empirically predict winter's precipitationanomalies in European and Mediterranean regions using precursors in autumn. This approach does notonly utilizes the amplitude but also the pattern of the precursors in generating the forecast.Using a toy model we show that it achieves a better forecast skill than more traditional regression models. Furthermore, we compare our algorithm with dynamic forecast models demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

Analysis of Spatial Pattern and Influencing Factors of E-Commerce

NASA Astrophysics Data System (ADS)

Zhang, Y.; Chen, J.; Zhang, S.

2017-09-01

This paper aims to study the relationship between e-commerce development and geographical characteristics using data of e-commerce, economy, Internet, express delivery and population from 2011 to 2015. Moran's I model and GWR model are applied to analyze the spatial pattern of E-commerce and its influencing factors. There is a growth trend of e-commerce from west to east, and it is obvious to see that e-commerce development has a space-time clustering, especially around the Yangtze River delta. The comprehensive factors caculated through PCA are described as fundamental social productivity, resident living standard and population sex structure. The first two factors have positive correlation with e-commerce, and the intensity of effect increases yearly. However, the influence of population sex structure on the E-commerce development is not significant. Our results suggest that the clustering of e-commerce has a downward trend and the impact of driving factors on e-commerce is observably distinct from year to year in space.

Formation rates, stability and reactivity of sulfuric acid - amine clusters predicted by computational chemistry

NASA Astrophysics Data System (ADS)

Kurtén, Theo; Ortega, Ismael; Kupiainen, Oona; Olenius, Tinja; Loukonen, Ville; Reiman, Heidi; McGrath, Matthew; Vehkamäki, Hanna

2013-04-01

Despite the importance of atmospheric particle formation for both climate and air quality, both experiments and non-empirical models using e.g. sulfuric acid, ammonia and water as condensing vapors have so far been unable to reproduce atmospheric observations using realistic trace gas concentrations. Recent experimental and theoretical evidence has shown that this mystery is likely resolved by amines. Combining first-principles evaporation rates for sulfuric acid - dimethylamine clusters with cluster kinetic modeling, we show that even sub-ppt concentrations of amines, together with atmospherically realistic concentrations of sulfuric acid, result in formation rates close to those observed in the atmosphere. Our simulated cluster formation rates are also close to, though somewhat larger than, those measured at the CLOUD experiment in CERN for both sulfuric acid - ammonia and sulfuric acid - dimethylamine systems. A sensitivity analysis indicates that the remaining discrepancy for the sulfuric acid - amine particle formation rates is likely caused by steric hindrances to cluster formation (due to alkyl groups of the amine molecules) rather than by significant errors in the evaporation rates. First-principles molecular dynamic and reaction kinetic modeling shed further light on the microscopic physics and chemistry of sulfuric acid - amine clusters. For example, while the number and type of hydrogen bonds in the clusters typically reach their equilibrium values on a picosecond timescale, and the overall bonding patterns predicted by traditional "static" quantum chemical calculations seem to be stable, the individual atoms participating in the hydrogen bonds continuously change at atmospherically realistic temperatures. From a chemical reactivity perspective, we have also discovered a surprising phenomenon: clustering with sulfuric acid molecules slightly increases the activation energy required for the abstraction of alkyl hydrogens from amine molecules. This implies that the oxidation rate of amines by OH and possibly other oxidants may be decreased by clustering, thus prolonging the chemical lifetime of amines in the air.

A pattern recognition approach to transistor array parameter variance

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Low work function, stable compound clusters and generation process

DOEpatents

Dinh, Long N.; Balooch, Mehdi; Schildbach, Marcus A.; Hamza, Alex V.; McLean, II, William

2000-01-01

Low work function, stable compound clusters are generated by co-evaporation of a solid semiconductor (i.e., Si) and alkali metal (i.e., Cs) elements in an oxygen environment. The compound clusters are easily patterned during deposition on substrate surfaces using a conventional photo-resist technique. The cluster size distribution is narrow, with a peak range of angstroms to nanometers depending on the oxygen pressure and the Si source temperature. Tests have shown that compound clusters when deposited on a carbon substrate contain the desired low work function property and are stable up to 600.degree. C. Using the patterned cluster containing plate as a cathode baseplate and a faceplate covered with phosphor as an anode, one can apply a positive bias to the faceplate to easily extract electrons and obtain illumination.

Where Wolves Kill Moose: The Influence of Prey Life History Dynamics on the Landscape Ecology of Predation

PubMed Central

Montgomery, Robert A.; Vucetich, John A.; Roloff, Gary J.; Bump, Joseph K.; Peterson, Rolf O.

2014-01-01

The landscape ecology of predation is well studied and known to be influenced by habitat heterogeneity. Little attention has been given to how the influence of habitat heterogeneity on the landscape ecology of predation might be modulated by life history dynamics of prey in mammalian systems. We demonstrate how life history dynamics of moose (Alces alces) contribute to landscape patterns in predation by wolves (Canis lupus) in Isle Royale National Park, Lake Superior, USA. We use pattern analysis and kernel density estimates of moose kill sites to demonstrate that moose in senescent condition and moose in prime condition tend to be wolf-killed in different regions of Isle Royale in winter. Predation on senescent moose was clustered in one kill zone in the northeast portion of the island, whereas predation on prime moose was clustered in 13 separate kill zones distributed throughout the full extent of the island. Moreover, the probability of kill occurrence for senescent moose, in comparison to prime moose, increased in high elevation habitat with patches of dense coniferous trees. These differences can be attributed, at least in part, to senescent moose being more vulnerable to predation and making different risk-sensitive habitat decisions than prime moose. Landscape patterns emerging from prey life history dynamics and habitat heterogeneity have been observed in the predation ecology of fish and insects, but this is the first mammalian system for which such observations have been made. PMID:24622241

Hierarchical random walks in trace fossils and the origin of optimal search behavior

PubMed Central

Sims, David W.; Reynolds, Andrew M.; Humphries, Nicolas E.; Southall, Emily J.; Wearmouth, Victoria J.; Metcalfe, Brett; Twitchett, Richard J.

2014-01-01

Efficient searching is crucial for timely location of food and other resources. Recent studies show that diverse living animals use a theoretically optimal scale-free random search for sparse resources known as a Lévy walk, but little is known of the origins and evolution of foraging behavior and the search strategies of extinct organisms. Here, using simulations of self-avoiding trace fossil trails, we show that randomly introduced strophotaxis (U-turns)—initiated by obstructions such as self-trail avoidance or innate cueing—leads to random looping patterns with clustering across increasing scales that is consistent with the presence of Lévy walks. This predicts that optimal Lévy searches may emerge from simple behaviors observed in fossil trails. We then analyzed fossilized trails of benthic marine organisms by using a novel path analysis technique and find the first evidence, to our knowledge, of Lévy-like search strategies in extinct animals. Our results show that simple search behaviors of extinct animals in heterogeneous environments give rise to hierarchically nested Brownian walk clusters that converge to optimal Lévy patterns. Primary productivity collapse and large-scale food scarcity characterizing mass extinctions evident in the fossil record may have triggered adaptation of optimal Lévy-like searches. The findings suggest that Lévy-like behavior has been used by foragers since at least the Eocene but may have a more ancient origin, which might explain recent widespread observations of such patterns among modern taxa. PMID:25024221

Dense Bicoid hubs accentuate binding along the morphogen gradient

PubMed Central

Mir, Mustafa; Reimer, Armando; Haines, Jenna E.; Li, Xiao-Yong; Stadler, Michael; Garcia, Hernan

2017-01-01

Morphogen gradients direct the spatial patterning of developing embryos; however, the mechanisms by which these gradients are interpreted remain elusive. Here we used lattice light-sheet microscopy to perform in vivo single-molecule imaging in early Drosophila melanogaster embryos of the transcription factor Bicoid that forms a gradient and initiates patterning along the anteroposterior axis. In contrast to canonical models, we observed that Bicoid binds to DNA with a rapid off rate throughout the embryo such that its average occupancy at target loci is on-rate-dependent. We further observed Bicoid forming transient “hubs” of locally high density that facilitate binding as factor levels drop, including in the posterior, where we observed Bicoid binding despite vanishingly low protein levels. We propose that localized modulation of transcription factor on rates via clustering provides a general mechanism to facilitate binding to low-affinity targets and that this may be a prevalent feature of other developmental transcription factors. PMID:28982761

Surface induced selective deposition of Dysprosium Polyoxometalate on HOPG surface studied by STM and STS

NASA Astrophysics Data System (ADS)

Costa Milan, David; Pinilla Cienfuegos, Elena; Cardona Serra, Salvador; Coronado Miralles, Eugenio; Untiedt Lecuona, Carlos

2013-03-01

Scanning Tunneling Microscope (STM) and scanning Tunnelling spectroscopy (STS) techniques have been used to study the Preyssler type Polyoxometalate K12[DyP5W30O110] molecules deposited on Highly Oriented Pyrolytic Graphite surface (HOPG). Chainlike arrangements of clusters containing two or three molecules, as well as different cluster sizes are observed. As many structural artifacts are present on the graphite surface, like Moiré patterns, that could look like the molecular deposits, we have studied their STS and size to ensure the presence of the POM molecules on the surface. This article shows the possibility of addressing POMs on a flat surface to obtain their electronic properties through STS.

Application of an automatic cloud tracking technique to Meteosat water vapor and infrared observations

NASA Technical Reports Server (NTRS)

Endlich, R. M.; Wolf, D. E.

1980-01-01

The automatic cloud tracking system was applied to METEOSAT 6.7 micrometers water vapor measurements to learn whether the system can track the motions of water vapor patterns. Data for the midlatitudes, subtropics, and tropics were selected from a sequence of METEOSAT pictures for 25 April 1978. Trackable features in the water vapor patterns were identified using a clustering technique and the features were tracked by two different methods. In flat (low contrast) water vapor fields, the automatic motion computations were not reliable, but in areas where the water vapor fields contained small scale structure (such as in the vicinity of active weather phenomena) the computations were successful. Cloud motions were computed using METEOSAT infrared observations (including tropical convective systems and midlatitude jet stream cirrus).

Emerging European winter precipitation pattern linked to atmospheric circulation changes over the North Atlantic region in recent decades

NASA Astrophysics Data System (ADS)

Ummenhofer, Caroline C.; Seo, Hyodae; Kwon, Young-Oh; Parfitt, Rhys; Brands, Swen; Joyce, Terrence M.

2017-08-01

Dominant European winter precipitation patterns over the past century, along with their associated extratropical North Atlantic circulation changes, are evaluated using cluster analysis. Contrary to the four regimes traditionally identified based on daily wintertime atmospheric circulation patterns, five distinct seasonal precipitation regimes are detected here. Recurrent precipitation patterns in each regime are linked to changes in atmospheric blocking, storm track, and sea surface temperatures across the North Atlantic region. Multidecadal variability in the frequency of the precipitation patterns reveals more (fewer) winters with wet conditions in northern (southern) Europe in recent decades and an emerging distinct pattern of enhanced wintertime precipitation over the northern British Isles. This pattern has become unusually common since the 1980s and is associated with changes in moisture transport and more frequent atmospheric river events. The observed precipitation changes post-1950 coincide with changes in storm track activity over the central/eastern North Atlantic toward the northern British Isles.

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.

Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species

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

Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna

Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated themore » identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.« less

Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species

DOE PAGES

Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna; ...

2015-04-09

Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated themore » identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.« less

Molecular Networking and Pattern-Based Genome Mining Improves discovery of biosynthetic gene clusters and their products from Salinispora species

PubMed Central

Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna; Sarkar, Anindita; Li, Jie; Ziemert, Nadine; Wang, Mingxun; Bandeira, Nuno; Moore, Bradley S.; Dorrestein, Pieter C.; Jensen, Paul R.

2015-01-01

Summary Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. Here we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated the identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. These efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches. PMID:25865308

Ambipolar SnOx thin-film transistors achieved at high sputtering power

NASA Astrophysics Data System (ADS)

Li, Yunpeng; Yang, Jia; Qu, Yunxiu; Zhang, Jiawei; Zhou, Li; Yang, Zaixing; Lin, Zhaojun; Wang, Qingpu; Song, Aimin; Xin, Qian

2018-04-01

SnO is the only oxide semiconductor to date that has exhibited ambipolar behavior in thin-film transistors (TFTs). In this work, ambipolar behavior was observed in SnOx TFTs fabricated at a high sputtering power of 200 W and post-annealed at 150-250 °C in ambient air. X-ray-diffraction patterns showed polycrystallisation of SnO and Sn in the annealed SnOx films. Scanning-electron-microscopy images revealed that microgrooves appeared after the films were annealed. Clusters subsequently segregated along the microgrooves, and our experiments suggest that they were most likely Sn clusters. Atomic force microscopy images indicate an abrupt increase in film roughness due to the cluster segregations. An important implication of this work is that excess Sn in the film, which has generally been thought to be detrimental to the film quality, may promote the ambipolar conduction when it is segregated from the film to enhance the stoichiometric balance.

Phylogenetic relationships of chrysanthemums in Korea based on novel SSR markers.

PubMed

Khaing, A A; Moe, K T; Hong, W J; Park, C S; Yeon, K H; Park, H S; Kim, D C; Choi, B J; Jung, J Y; Chae, S C; Lee, K M; Park, Y J

2013-11-07

Chrysanthemums are well known for their esthetic and medicinal values. Characterization of chrysanthemums is vital for their conservation and management as well as for understanding their genetic relationships. We found 12 simple sequence repeat markers (SSRs) of 100 designed primers to be polymorphic. These novel SSR markers were used to evaluate 95 accessions of chrysanthemums (3 indigenous and 92 cultivated accessions). Two hundred alleles were identified, with an average of 16.7 alleles per locus. KNUCRY-77 gave the highest polymorphic information content value (0.879), while KNUCRY-10 gave the lowest (0.218). Similar patterns of grouping were observed with a distance-based dendrogram developed using PowerMarker and model-based clustering with Structure. Three clusters with some admixtures were identified by model-based clustering. These newly developed SSR markers will be useful for further studies of chrysanthemums, such as taxonomy and marker-assisted selection breeding.

Transmission clustering among newly diagnosed HIV patients in Chicago, 2008 to 2011: using phylogenetics to expand knowledge of regional HIV transmission patterns

PubMed Central

Lubelchek, Ronald J.; Hoehnen, Sarah C.; Hotton, Anna L.; Kincaid, Stacey L.; Barker, David E.; French, Audrey L.

2014-01-01

Introduction HIV transmission cluster analyses can inform HIV prevention efforts. We describe the first such assessment for transmission clustering among HIV patients in Chicago. Methods We performed transmission cluster analyses using HIV pol sequences from newly diagnosed patients presenting to Chicago’s largest HIV clinic between 2008 and 2011. We compared sequences via progressive pairwise alignment, using neighbor joining to construct an un-rooted phylogenetic tree. We defined clusters as >2 sequences among which each sequence had at least one partner within a genetic distance of ≤ 1.5%. We used multivariable regression to examine factors associated with clustering and used geospatial analysis to assess geographic proximity of phylogenetically clustered patients. Results We compared sequences from 920 patients; median age 35 years; 75% male; 67% Black, 23% Hispanic; 8% had a Rapid Plasma Reagin (RPR) titer ≥ 1:16 concurrent with their HIV diagnosis. We had HIV transmission risk data for 54%; 43% identified as men who have sex with men (MSM). Phylogenetic analysis demonstrated 123 patients (13%) grouped into 26 clusters, the largest having 20 members. In multivariable regression, age < 25, Black race, MSM status, male gender, higher HIV viral load, and RPR ≥ 1:16 associated with clustering. We did not observe geographic grouping of genetically clustered patients. Discussion Our results demonstrate high rates of HIV transmission clustering, without local geographic foci, among young Black MSM in Chicago. Applied prospectively, phylogenetic analyses could guide prevention efforts and help break the cycle of transmission. PMID:25321182

Geometric Patterns for Neighboring Bases Near the Stacked State in Nucleic Acid Strands.

PubMed

Sedova, Ada; Banavali, Nilesh K

2017-03-14

Structural variation in base stacking has been analyzed frequently in isolated double helical contexts for nucleic acids, but not as often in nonhelical geometries or in complex biomolecular environments. In this study, conformations of two neighboring bases near their stacked state in any environment are comprehensively characterized for single-strand dinucleotide (SSD) nucleic acid crystal structure conformations. An ensemble clustering method is used to identify a reduced set of representative stacking geometries based on pairwise distances between select atoms in consecutive bases, with multiple separable conformational clusters obtained for categories divided by nucleic acid type (DNA/RNA), SSD sequence, stacking face orientation, and the presence or absence of a protein environment. For both DNA and RNA, SSD conformations are observed that are either close to the A-form, or close to the B-form, or intermediate between the two forms, or further away from either form, illustrating the local structural heterogeneity near the stacked state. Among this large variety of distinct conformations, several common stacking patterns are observed between DNA and RNA, and between nucleic acids in isolation or in complex with proteins, suggesting that these might be stable stacking orientations. Noncanonical face/face orientations of the two bases are also observed for neighboring bases in the same strand, but their frequency is much lower, with multiple SSD sequences across categories showing no occurrences of such unusual stacked conformations. The resulting reduced set of stacking geometries is directly useful for stacking-energy comparisons between empirical force fields, prediction of plausible localized variations in single-strand structures near their canonical states, and identification of analogous stacking patterns in newly solved nucleic acid containing structures.

Transcriptome-Wide Changes in Chlamydomonas reinhardtii Gene Expression Regulated by Carbon Dioxide and the CO2-Concentrating Mechanism Regulator CIA5/CCM1[W][OA

PubMed Central

Fang, Wei; Si, Yaqing; Douglass, Stephen; Casero, David; Merchant, Sabeeha S.; Pellegrini, Matteo; Ladunga, Istvan; Liu, Peng; Spalding, Martin H.

2012-01-01

We used RNA sequencing to query the Chlamydomonas reinhardtii transcriptome for regulation by CO2 and by the transcription regulator CIA5 (CCM1). Both CO2 and CIA5 are known to play roles in acclimation to low CO2 and in induction of an essential CO2-concentrating mechanism (CCM), but less is known about their interaction and impact on the whole transcriptome. Our comparison of the transcriptome of a wild type versus a cia5 mutant strain under three different CO2 conditions, high CO2 (5%), low CO2 (0.03 to 0.05%), and very low CO2 (<0.02%), provided an entry into global changes in the gene expression patterns occurring in response to the interaction between CO2 and CIA5. We observed a massive impact of CIA5 and CO2 on the transcriptome, affecting almost 25% of all Chlamydomonas genes, and we discovered an array of gene clusters with distinctive expression patterns that provide insight into the regulatory interaction between CIA5 and CO2. Several individual clusters respond primarily to either CIA5 or CO2, providing access to genes regulated by one factor but decoupled from the other. Three distinct clusters clearly associated with CCM-related genes may represent a rich source of candidates for new CCM components, including a small cluster of genes encoding putative inorganic carbon transporters. PMID:22634760

Three-dimensional visualization of cultural clusters in the 1878 yellow fever epidemic of New Orleans

PubMed Central

Curtis, Andrew J

2008-01-01

Background An epidemic may exhibit different spatial patterns with a change in geographic scale, with each scale having different conduits and impediments to disease spread. Mapping disease at each of these scales often reveals different cluster patterns. This paper will consider this change of geographic scale in an analysis of yellow fever deaths for New Orleans in 1878. Global clustering for the whole city, will be followed by a focus on the French Quarter, then clusters of that area, and finally street-level patterns of a single cluster. The three-dimensional visualization capabilities of a GIS will be used as part of a cluster creation process that incorporates physical buildings in calculating mortality-to-mortality distance. Including nativity of the deceased will also capture cultural connection. Results Twenty-two yellow fever clusters were identified for the French Quarter. These generally mirror the results of other global cluster and density surfaces created for the entire epidemic in New Orleans. However, the addition of building-distance, and disease specific time frame between deaths reveal that disease spread contains a cultural component. Same nativity mortality clusters emerge in a similar time frame irrespective of proximity. Italian nativity mortalities were far more densely grouped than any of the other cohorts. A final examination of mortalities for one of the nativity clusters reveals that further sub-division is present, and that this pattern would only be revealed at this scale (street level) of investigation. Conclusion Disease spread in an epidemic is complex resulting from a combination of geographic distance, geographic distance with specific connection to the built environment, disease-specific time frame between deaths, impediments such as herd immunity, and social or cultural connection. This research has shown that the importance of cultural connection may be more important than simple proximity, which in turn might mean traditional quarantine measures should be re-evaluated. PMID:18721469

Three-dimensional visualization of cultural clusters in the 1878 yellow fever epidemic of New Orleans.

PubMed

Curtis, Andrew J

2008-08-22

An epidemic may exhibit different spatial patterns with a change in geographic scale, with each scale having different conduits and impediments to disease spread. Mapping disease at each of these scales often reveals different cluster patterns. This paper will consider this change of geographic scale in an analysis of yellow fever deaths for New Orleans in 1878. Global clustering for the whole city, will be followed by a focus on the French Quarter, then clusters of that area, and finally street-level patterns of a single cluster. The three-dimensional visualization capabilities of a GIS will be used as part of a cluster creation process that incorporates physical buildings in calculating mortality-to-mortality distance. Including nativity of the deceased will also capture cultural connection. Twenty-two yellow fever clusters were identified for the French Quarter. These generally mirror the results of other global cluster and density surfaces created for the entire epidemic in New Orleans. However, the addition of building-distance, and disease specific time frame between deaths reveal that disease spread contains a cultural component. Same nativity mortality clusters emerge in a similar time frame irrespective of proximity. Italian nativity mortalities were far more densely grouped than any of the other cohorts. A final examination of mortalities for one of the nativity clusters reveals that further sub-division is present, and that this pattern would only be revealed at this scale (street level) of investigation. Disease spread in an epidemic is complex resulting from a combination of geographic distance, geographic distance with specific connection to the built environment, disease-specific time frame between deaths, impediments such as herd immunity, and social or cultural connection. This research has shown that the importance of cultural connection may be more important than simple proximity, which in turn might mean traditional quarantine measures should be re-evaluated.

Social Media Use and Depression and Anxiety Symptoms: A Cluster Analysis.

PubMed

Shensa, Ariel; Sidani, Jaime E; Dew, Mary Amanda; Escobar-Viera, César G; Primack, Brian A

2018-03-01

Individuals use social media with varying quantity, emotional, and behavioral at- tachment that may have differential associations with mental health outcomes. In this study, we sought to identify distinct patterns of social media use (SMU) and to assess associations between those patterns and depression and anxiety symptoms. In October 2014, a nationally-representative sample of 1730 US adults ages 19 to 32 completed an online survey. Cluster analysis was used to identify patterns of SMU. Depression and anxiety were measured using respective 4-item Patient-Reported Outcome Measurement Information System (PROMIS) scales. Multivariable logistic regression models were used to assess associations between clus- ter membership and depression and anxiety. Cluster analysis yielded a 5-cluster solu- tion. Participants were characterized as "Wired," "Connected," "Diffuse Dabblers," "Concentrated Dabblers," and "Unplugged." Membership in 2 clusters - "Wired" and "Connected" - increased the odds of elevated depression and anxiety symptoms (AOR = 2.7, 95% CI = 1.5-4.7; AOR = 3.7, 95% CI = 2.1-6.5, respectively, and AOR = 2.0, 95% CI = 1.3-3.2; AOR = 2.0, 95% CI = 1.3-3.1, respectively). SMU pattern characterization of a large population suggests 2 pat- terns are associated with risk for depression and anxiety. Developing educational interventions that address use patterns rather than single aspects of SMU (eg, quantity) would likely be useful.

[Clustering patterns of behavioral risk factors linked to chronic disease among young adults in two localities in Bogota, Colombia: importance of sex differences].

PubMed

Gómez Gutiérrez, Luis Fernando; Lucumí Cuesta, Diego Iván; Girón Vargas, Sandra Lorena; Espinosa García, Gladys

2004-01-01

The characterization of clustering behavioral risk factors may be used as a guideline for interventions aimed at preventing chronic diseases. This study determined the clustering patterns of some behavioral risk factors in young adults aged 18 to 29 years and established the factors associated with having two or more of them. Patterns of clustering by gender were established in four behavioral risk factors (low consumption of fruits and vegetables, physical inactivity in leisure time, current tobacco consumption and acute alcohol consumption), in 1465 young adults participants through a multistage probabilistic sample. Regression models identified the sociodemografic variables associated with having two or more of the aforementioned behavioral risk factors. Having one, 32.9% two and 17.7% three or four. Acute alcohol consumption was the risk factor most frequent in the combined risk factor patterns among males; physical inactivity during leisure time being the most frequent among females. Among the females, having two or more behavioral risk factors was linked to be separated or divorced, this having been linked to work having been the main activity over the past 30 days among males. The combinations of behavioral risk factors studied and the factors associated with clustering show different patterns among males and females. These findings stressed the need of designing interventions sensitive to gender differences.

Psychosocial Costs of Racism to Whites: Exploring Patterns through Cluster Analysis

ERIC Educational Resources Information Center

Spanierman, Lisa B.; Poteat, V. Paul; Beer, Amanda M.; Armstrong, Patrick Ian

2006-01-01

Participants (230 White college students) completed the Psychosocial Costs of Racism to Whites (PCRW) Scale. Using cluster analysis, we identified 5 distinct cluster groups on the basis of PCRW subscale scores: the unempathic and unaware cluster contained the lowest empathy scores; the insensitive and afraid cluster consisted of low empathy and…

RR Lyrae stars in and around NGC 6441: signatures of dissolving cluster stars

NASA Astrophysics Data System (ADS)

Kunder, Andrea

2018-06-01

Detailed elemental abundance patterns of metal-poor ([Fe/H]~ -1 dex) stars in the Galactic bulge indicate that a number of them are consistent with globular cluster (GC) stars and may be former members of dissolved GCs. This would indicate that a few per cent of the Galactic bulge was built up from destruction and/or evaporation of globular clusters. Here an attempt is made to identify such presumptive destroyed stars originating from the massive, inner Galaxy globular cluster NGC~6441 using its rich RR Lyrae variable star (RRL) population. We present radial velocities of forty RRLs centered on the globular cluster NGC~6441. All of the 13 RRLs observed within the cluster tidal radius have velocities consistent with cluster membership, with an average radial velocity of 24 +- 5~km/s and a star-to-star scatter of 11~km/s. This includes two new RRLs that were previously not associated with the cluster. Eight RRLs with radial velocities consistent with cluster membership but up to three time the distance from the tidal radius are also reported. These potential extra-tidal RRLs also have exceptionally long periods, which is a curious characteristic of the NGC~6441 RRL population that hosts RRLs with periods longer than seen anywhere else in the Milky Way. As expected of stripped cluster stars, most are inline with the cluster's orbit. Therefore, either the tidal radius of NGC~6441 is underestimated and/or we are seeing dissolving cluster stars stemming from NGC~6441 that are building up the old spheroidal bulge. Both the mean velocity of the cluster as well as the underlying field population is consistent with belonging to an old spheroidal bulge with low rotation and high velocity dispersion that formed before the bar.

Autoantibodies in pediatric systemic lupus erythematosus: ethnic grouping, cluster analysis, and clinical correlations.

PubMed

Jurencák, Roman; Fritzler, Marvin; Tyrrell, Pascal; Hiraki, Linda; Benseler, Susanne; Silverman, Earl

2009-02-01

(1) To evaluate the spectrum of serum autoantibodies in pediatric-onset systemic lupus erythematosus (pSLE) with a focus on ethnic differences; (2) using cluster analysis, to identify patients with similar autoantibody patterns and to determine their clinical associations. A single-center cohort study of all patients with newly diagnosed pSLE seen over an 8-year period was performed. Ethnicity, clinical, and serological data were prospectively collected from 156/169 patients (92%). The frequencies of 10 selected autoantibodies among ethnic groups were compared. Cluster analysis identified groups of patients with similar autoantibody profiles. Associations of these groups with clinical and laboratory features of pSLE were examined. Among our 5 ethnic groups, there were differences only in the prevalence of anti-U1RNP and anti-Sm antibodies, which occurred more frequently in non-Caucasian patients (p < 0.0001, p < 0.01, respectively). Cluster analysis revealed 3 autoantibody clusters. Cluster 1 consisted of anti-dsDNA antibodies. Cluster 2 consisted of anti-dsDNA, antichromatin, antiribosomal P, anti-U1RNP, anti-Sm, anti-Ro and anti-La autoantibody. Cluster 3 consisted of anti-dsDNA, anti-RNP, and anti-Sm autoantibody. The highest proportion of Caucasians was in cluster 1 (p < 0.05), which was characterized by a mild disease with infrequent major organ involvement compared to cluster 2, which had the highest frequency of nephritis, renal failure, serositis, and hemolytic anemia, or cluster 3, which was characterized by frequent neuropsychiatric disease and nephritis. We observed ethnic differences in autoantibody profiles in pSLE. Autoantibodies tended to cluster together and these clusters were associated with different clinical courses.

Use of Patterned CNT Arrays for Display Purposes

NASA Technical Reports Server (NTRS)

Delzeit, Lance D. (Inventor); Schipper, John F. (Inventor)

2009-01-01

Method and system for providing a dynamically reconfigurable display having nanometer-scale resolution, using a patterned array of multi-wall carbon nanotube (MWCNT) clusters. A diode, phosphor or other light source on each MWCNT cluster is independently activated, and different color light sources (e.g., red, green, blue, grey scale, infrared) can be mixed if desired. Resolution is estimated to be 40-100 nm, and reconfiguration time for each MWCNT cluster is no greater than one microsecond.

Recognizing patterns of visual field loss using unsupervised machine learning

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Cardiorespiratory instability in monitored step-down unit patients: using cluster analysis to identify patterns of change

PubMed Central

Clermont, Gilles; Chen, Lujie; Dubrawski, Artur W.; Ren, Dianxu; Hoffman, Leslie A.; Pinsky, Michael R.; Hravnak, Marilyn

2018-01-01

Cardiorespiratory instability (CRI) in monitored step-down unit (SDU) patients has a variety of etiologies, and likely manifests in patterns of vital signs (VS) changes. We explored use of clustering techniques to identify patterns in the initial CRI epoch (CRI1; first exceedances of VS beyond stability thresholds after SDU admission) of unstable patients, and inter-cluster differences in admission characteristics and outcomes. Continuous noninvasive monitoring of heart rate (HR), respiratory rate (RR), and pulse oximetry (SpO2) were sampled at 1/20 Hz. We identified CRI1 in 165 patients, employed hierarchical and k-means clustering, tested several clustering solutions, used 10-fold cross validation to establish the best solution and assessed inter-cluster differences in admission characteristics and outcomes. Three clusters (C) were derived: C1) normal/high HR and RR, normal SpO2 (n = 30); C2) normal HR and RR, low SpO2 (n = 103); and C3) low/normal HR, low RR and normal SpO2 (n = 32). Clusters were significantly different based on age (p < 0.001; older patients in C2), number of comorbidities (p = 0.008; more C2 patients had ≥ 2) and hospital length of stay (p = 0.006; C1 patients stayed longer). There were no between-cluster differences in SDU length of stay, or mortality. Three different clusters of VS presentations for CRI1 were identified. Clusters varied on age, number of comorbidities and hospital length of stay. Future study is needed to determine if there are common physiologic underpinnings of VS clusters which might inform clinical decision-making when CRI first manifests. PMID:28229353

Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis.

PubMed

Cohen, Mitchell J; Grossman, Adam D; Morabito, Diane; Knudson, M Margaret; Butte, Atul J; Manley, Geoffrey T

2010-01-01

Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome. Multivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality. We identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters. Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.

Stress Drop and Directivity Patterns Observed in Small-Magnitude (

NASA Astrophysics Data System (ADS)

Ruhl, C. J.; Hatch, R. L.; Abercrombie, R. E.; Smith, K.

2017-12-01

Recent improvements in seismic instrumentation and network coverage in the Reno, NV area have provided high-quality records of abundant microseismicity, including several swarms and clusters. Here, we discuss stress drop and directivity patterns of small-magnitude seismicity in the 2008 Mw4.9 Mogul earthquake swarm in Reno, NV and in the nearby region of an ML3.2 sequence near Virginia City, NV. In both sequences, double-difference relocated earthquakes cluster on multiple distinct structures consistent with focal mechanism and moment tensor fault plane solutions. Both sequences also show migration potentially related to fluid flow. We estimate corner frequency and stress drop using EGF-derived spectral ratios, convolving earthquake pairs (target*EGF) such that we preserve phase and recover source-time functions (STF) on a station-by-station basis. We then stack individual STFs per station for all EGF-target pairs per target earthquake, increasing the signal-to-noise of our results. By applying an azimuthal- and incidence-angle-dependent stretching factor to STFs in the time domain, we are able to invert for rupture directivity and velocity assuming both unilateral and bilateral rupture. Earthquakes in both sequences, some as low as ML2.1, show strong unilateral directivity consistent with independent fault plane solutions. We investigate and compare the relationship between rupture and migration directions on subfaults within each sequence. Average stress drops for both sequences are 4 MPa, but there is large variation in individual estimates for both sequences. Although this variation is not explained simply by any one parameter (e.g., depth), spatiotemporal variation in the Mogul swarm is distinct: coherent clusters of high and low stress drop earthquakes along the mainshock fault plane are seen, and high-stress-drop foreshocks correlate with an area of reduced aftershock productivity. These observations are best explained by a difference in rheology along the fault plane. The unprecedented detail achieved for these small magnitude earthquakes confirms that stress drop, when measured precisely, is a valuable observation of physically-meaningful fault zone properties and earthquake behavior.

A cluster analysis of patterns of objectively measured physical activity in Hong Kong.

PubMed

Lee, Paul H; Yu, Ying-Ying; McDowell, Ian; Leung, Gabriel M; Lam, T H

2013-08-01

The health benefits of exercise are clear. In targeting interventions it would be valuable to know whether characteristic patterns of physical activity (PA) are associated with particular population subgroups. The present study used cluster analysis to identify characteristic hourly PA patterns measured by accelerometer. Cross-sectional design. Objectively measured PA in Hong Kong adults. Four-day accelerometer data were collected during 2009 to 2011 for 1714 participants in Hong Kong (mean age 44?2 years, 45?9% male). Two clusters were identified, one more active than the other. The ‘active cluster’ (n 480) was characterized by a routine PA pattern on weekdays and a more active and varied pattern on weekends; the other, the ‘less active cluster’ (n 1234), by a consistently low PA pattern on both weekdays and weekends with little variation from day to day. Demographic, lifestyle, PA level and health characteristics of the two clusters were compared. They differed in age, sex, smoking, income and level of PA required at work. The odds of having any chronic health conditions was lower for the active group (adjusted OR50?62, 95% CI 0?46, 0?84) but the two groups did not differ in terms of specific chronic health conditions or obesity. Implications are drawn for targeting exercise promotion programmes at the population level.

Multiple Coordination Patterns in Infant and Adult Vocalizations

PubMed Central

Abney, Drew H.; Warlaumont, Anne S.; Oller, D. Kimbrough; Wallot, Sebastian; Kello, Christopher T.

2017-01-01

The study of vocal coordination between infants and adults has led to important insights into the development of social, cognitive, emotional and linguistic abilities. We used an automatic system to identify vocalizations produced by infants and adults over the course of the day for fifteen infants studied longitudinally during the first two years of life. We measured three different types of vocal coordination: coincidence-based, rate-based, and cluster-based. Coincidence-based and rate-based coordination are established measures in the developmental literature. Cluster-based coordination is new and measures the strength of matching in the degree to which vocalization events occur in hierarchically nested clusters. We investigated whether various coordination patterns differ as a function of vocalization type, whether different coordination patterns provide unique information about the dynamics of vocal interaction, and how the various coordination patterns each relate to infant age. All vocal coordination patterns displayed greater coordination for infant speech-related vocalizations, adults adapted the hierarchical clustering of their vocalizations to match that of infants, and each of the three coordination patterns had unique associations with infant age. Altogether, our results indicate that vocal coordination between infants and adults is multifaceted, suggesting a complex relationship between vocal coordination and the development of vocal communication. PMID:29375276

Patterns of dairy food intake, body composition and markers of metabolic health in Ireland: results from the National Adult Nutrition Survey.

PubMed

Feeney, E L; O'Sullivan, A; Nugent, A P; McNulty, B; Walton, J; Flynn, A; Gibney, E R

2017-02-20

Studies examining the association between dairy consumption and metabolic health have shown mixed results. This may be due, in part, to the use of different definitions of dairy, and to single types of dairy foods examined in isolation. The objective of the study was to examine associations between dairy food intake and metabolic health, identify patterns of dairy food consumption and determine whether dairy dietary patterns are associated with outcomes of metabolic health, in a cross-sectional survey. A 4-day food diary was used to assess food and beverage consumption, including dairy (defined as milk, cheese, yogurt, cream and butter) in free-living, healthy Irish adults aged 18-90 years (n=1500). Fasting blood samples (n=897) were collected, and anthropometric measurements taken. Differences in metabolic health markers across patterns and tertiles of dairy consumption were tested via analysis of covariance. Patterns of dairy food consumption, of different fat contents, were identified using cluster analysis. Higher (total) dairy was associated with lower body mass index, %body fat, waist circumference and waist-to-hip ratio (P<0.001), and lower systolic (P=0.02) and diastolic (P<0.001) blood pressure. Similar trends were observed when milk and yogurt intakes were considered separately. Higher cheese consumption was associated with higher C-peptide (P<0.001). Dietary pattern analysis identified three patterns (clusters) of dairy consumption; 'Whole milk', 'Reduced fat milks and yogurt' and 'Butter and cream'. The 'Reduced fat milks and yogurt' cluster had the highest scores on a Healthy Eating Index, and lower-fat and saturated fat intakes, but greater triglyceride levels (P=0.028) and total cholesterol (P=0.015). Overall, these results suggest that while milk and yogurt consumption is associated with a favourable body phenotype, the blood lipid profiles are less favourable when eaten as part of a low-fat high-carbohydrate dietary pattern. More research is needed to better understand this association. Overall, these results suggest that although milk and yogurt consumption is associated with a favourable body phenotype, the blood lipid profiles are less favourable when eaten as part of a low-fat high-carbohydrate dietary pattern. More research is needed to better understand this association.

Patterns of dairy food intake, body composition and markers of metabolic health in Ireland: results from the National Adult Nutrition Survey

PubMed Central

Feeney, E L; O'Sullivan, A; Nugent, A P; McNulty, B; Walton, J; Flynn, A; Gibney, E R

2017-01-01

Background: Studies examining the association between dairy consumption and metabolic health have shown mixed results. This may be due, in part, to the use of different definitions of dairy, and to single types of dairy foods examined in isolation. Objective: The objective of the study was to examine associations between dairy food intake and metabolic health, identify patterns of dairy food consumption and determine whether dairy dietary patterns are associated with outcomes of metabolic health, in a cross-sectional survey. Design: A 4-day food diary was used to assess food and beverage consumption, including dairy (defined as milk, cheese, yogurt, cream and butter) in free-living, healthy Irish adults aged 18–90 years (n=1500). Fasting blood samples (n=897) were collected, and anthropometric measurements taken. Differences in metabolic health markers across patterns and tertiles of dairy consumption were tested via analysis of covariance. Patterns of dairy food consumption, of different fat contents, were identified using cluster analysis. Results: Higher (total) dairy was associated with lower body mass index, %body fat, waist circumference and waist-to-hip ratio (P<0.001), and lower systolic (P=0.02) and diastolic (P<0.001) blood pressure. Similar trends were observed when milk and yogurt intakes were considered separately. Higher cheese consumption was associated with higher C-peptide (P<0.001). Dietary pattern analysis identified three patterns (clusters) of dairy consumption; 'Whole milk', 'Reduced fat milks and yogurt' and 'Butter and cream'. The 'Reduced fat milks and yogurt' cluster had the highest scores on a Healthy Eating Index, and lower-fat and saturated fat intakes, but greater triglyceride levels (P=0.028) and total cholesterol (P=0.015). conclusion: Overall, these results suggest that while milk and yogurt consumption is associated with a favourable body phenotype, the blood lipid profiles are less favourable when eaten as part of a low-fat high-carbohydrate dietary pattern. More research is needed to better understand this association. Conclusion: Overall, these results suggest that although milk and yogurt consumption is associated with a favourable body phenotype, the blood lipid profiles are less favourable when eaten as part of a low-fat high-carbohydrate dietary pattern. More research is needed to better understand this association. PMID:28218736

Analysis of a Spatial Point Pattern: Examining the Damage to Pavement and Pipes in Santa Clara Valley Resulting from the Loma Prieta Earthquake

USGS Publications Warehouse

Phelps, G.A.

2008-01-01

This report describes some simple spatial statistical methods to explore the relationships of scattered points to geologic or other features, represented by points, lines, or areas. It also describes statistical methods to search for linear trends and clustered patterns within the scattered point data. Scattered points are often contained within irregularly shaped study areas, necessitating the use of methods largely unexplored in the point pattern literature. The methods take advantage of the power of modern GIS toolkits to numerically approximate the null hypothesis of randomly located data within an irregular study area. Observed distributions can then be compared with the null distribution of a set of randomly located points. The methods are non-parametric and are applicable to irregularly shaped study areas. Patterns within the point data are examined by comparing the distribution of the orientation of the set of vectors defined by each pair of points within the data with the equivalent distribution for a random set of points within the study area. A simple model is proposed to describe linear or clustered structure within scattered data. A scattered data set of damage to pavement and pipes, recorded after the 1989 Loma Prieta earthquake, is used as an example to demonstrate the analytical techniques. The damage is found to be preferentially located nearer a set of mapped lineaments than randomly scattered damage, suggesting range-front faulting along the base of the Santa Cruz Mountains is related to both the earthquake damage and the mapped lineaments. The damage also exhibit two non-random patterns: a single cluster of damage centered in the town of Los Gatos, California, and a linear alignment of damage along the range front of the Santa Cruz Mountains, California. The linear alignment of damage is strongest between 45? and 50? northwest. This agrees well with the mean trend of the mapped lineaments, measured as 49? northwest.

Titanium embedded cage structure formation in Al{sub n}Ti{sup +} clusters and their interaction with Ar

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

Torres, M. B., E-mail: begonia@ubu.es; Vega, A.; Balbás, L. C.

2014-05-07

Recently, Ar physisorption was used as a structural probe for the location of the Ti dopant atom in aluminium cluster cations, Al{sub n}Ti{sup +} [Lang et al., J. Am. Soc. Mass Spectrom. 22, 1508 (2011)]. As an experiment result, the lack of Ar complexes for n > n{sub c} determines the cluster size for which the Ti atom is located inside of an Al cage. To elucidate the decisive factors for the formation of endohedrally Al{sub n}Ti{sup +}, experimentalists proposed detailed computational studies as indispensable. In this work, we investigated, using the density functional theory, the structural and electronic propertiesmore » of singly titanium doped cationic clusters, Al{sub n}Ti{sup +} (n = 16–21) as well as the adsorption of an Ar atom on them. The first endohedral doped cluster, with Ti encapsulated in a fcc-like cage skeleton, appears at n{sub c} = 21, which is the critical number consistent with the exohedral-endohedral transition experimentally observed. At this critical size the non-crystalline icosahedral growth pattern, related to the pure aluminium clusters, with the Ti atom in the surface, changes into a endohedral fcc-like pattern. The map of structural isomers, relative energy differences, second energy differences, and structural parameters were determined and analyzed. Moreover, we show the critical size depends on the net charge of the cluster, being different for the cationic clusters (n{sub c} = 21) and their neutral counterparts (n{sub c} = 20). For the Al {sub n} Ti {sup +} · Ar complexes, and for n < 21, the preferred Ar adsorption site is on top of the exohedral Ti atom, with adsorption energy in very good agreement with the experimental value. Instead, for n = 21, the Ar adsorption occurs on the top an Al atom with very low absorption energy. For all sizes the geometry of the Al{sub n}Ti{sup +} clusters keeps unaltered in the Ar-cluster complexes. This fact indicates that Ar adsorption does not influence the cluster structure, providing support to the experimental technique used. For n{sub c} = 21, the smallest size of endohedral Ti doped cationic clusters, the Ar binding energy decreases drastically, whereas the Ar-cluster distance increases substantially, point to Ar physisorption, as assumed by the experimentalists. Calculated Ar adsorption energies agree well with available experimental binding energies.« less

Identification of new participants in the rainbow trout (Oncorhynchus mykiss) oocyte maturation and ovulation processes using cDNA microarrays

PubMed Central

Bobe, Julien; Montfort, Jerôme; Nguyen, Thaovi; Fostier, Alexis

2006-01-01

Background The hormonal control of oocyte maturation and ovulation as well as the molecular mechanisms of nuclear maturation have been thoroughly studied in fish. In contrast, the other molecular events occurring in the ovary during post-vitellogenesis have received far less attention. Methods Nylon microarrays displaying 9152 rainbow trout cDNAs were hybridized using RNA samples originating from ovarian tissue collected during late vitellogenesis, post-vitellogenesis and oocyte maturation. Differentially expressed genes were identified using a statistical analysis. A supervised clustering analysis was performed using only differentially expressed genes in order to identify gene clusters exhibiting similar expression profiles. In addition, specific genes were selected and their preovulatory ovarian expression was analyzed using real-time PCR. Results From the statistical analysis, 310 differentially expressed genes were identified. Among those genes, 90 were up-regulated at the time of oocyte maturation while 220 exhibited an opposite pattern. After clustering analysis, 90 clones belonging to 3 gene clusters exhibiting the most remarkable expression patterns were kept for further analysis. Using real-time PCR analysis, we observed a strong up-regulation of ion and water transport genes such as aquaporin 4 (aqp4) and pendrin (slc26). In addition, a dramatic up-regulation of vasotocin (avt) gene was observed. Furthermore, angiotensin-converting-enzyme 2 (ace2), coagulation factor V (cf5), adam 22, and the chemokine cxcl14 genes exhibited a sharp up-regulation at the time of oocyte maturation. Finally, ovarian aromatase (cyp19a1) exhibited a dramatic down-regulation over the post-vitellogenic period while a down-regulation of Cytidine monophosphate-N-acetylneuraminic acid hydroxylase (cmah) was observed at the time of oocyte maturation. Conclusion We showed the over or under expression of more that 300 genes, most of them being previously unstudied or unknown in the fish preovulatory ovary. Our data confirmed the down-regulation of estrogen synthesis genes during the preovulatory period. In addition, the strong up-regulation of aqp4 and slc26 genes prior to ovulation suggests their participation in the oocyte hydration process occurring at that time. Furthermore, among the most up-regulated clones, several genes such as cxcl14, ace2, adam22, cf5 have pro-inflammatory, vasodilatory, proteolytics and coagulatory functions. The identity and expression patterns of those genes support the theory comparing ovulation to an inflammatory-like reaction. PMID:16872517

Unlearning of Mixed States in the Hopfield Model —Extensive Loading Case—

NASA Astrophysics Data System (ADS)

Hayashi, Kao; Hashimoto, Chinami; Kimoto, Tomoyuki; Uezu, Tatsuya

2018-05-01

We study the unlearning of mixed states in the Hopfield model for the extensive loading case. Firstly, we focus on case I, where several embedded patterns are correlated with each other, whereas the rest are uncorrelated. Secondly, we study case II, where patterns are divided into clusters in such a way that patterns in any cluster are correlated but those in two different clusters are not correlated. By using the replica method, we derive the saddle point equations for order parameters under the ansatz of replica symmetry. The same equations are also derived by self-consistent signal-to-noise analysis in case I. In both cases I and II, we find that when the correlation between patterns is large, the network loses its ability to retrieve the embedded patterns and, depending on the parameters, a confused memory, which is a mixed state and/or spin glass state, emerges. By unlearning the mixed state, the network acquires the ability to retrieve the embedded patterns again in some parameter regions. We find that to delete the mixed state and to retrieve the embedded patterns, the coefficient of unlearning should be chosen appropriately. We perform Markov chain Monte Carlo simulations and find that the simulation and theoretical results agree reasonably well, except for the spin glass solution in a parameter region due to the replica symmetry breaking. Furthermore, we find that the existence of many correlated clusters reduces the stabilities of both embedded patterns and mixed states.

Prospective associations between socio-economic status and dietary patterns in European children: the Identification and Prevention of Dietary- and Lifestyle-induced Health Effects in Children and Infants (IDEFICS) Study.

PubMed

Fernández-Alvira, Juan Miguel; Börnhorst, Claudia; Bammann, Karin; Gwozdz, Wencke; Krogh, Vittorio; Hebestreit, Antje; Barba, Gianvincenzo; Reisch, Lucia; Eiben, Gabriele; Iglesia, Iris; Veidebaum, Tomas; Kourides, Yannis A; Kovacs, Eva; Huybrechts, Inge; Pigeot, Iris; Moreno, Luis A

2015-02-14

Exploring changes in children's diet over time and the relationship between these changes and socio-economic status (SES) may help to understand the impact of social inequalities on dietary patterns. The aim of the present study was to describe dietary patterns by applying a cluster analysis to 9301 children participating in the baseline (2-9 years old) and follow-up (4-11 years old) surveys of the Identification and Prevention of Dietary- and Lifestyle-induced Health Effects in Children and Infants Study, and to describe the cluster memberships of these children over time and their association with SES. We applied the K-means clustering algorithm based on the similarities between the relative frequencies of consumption of forty-two food items. The following three consistent clusters were obtained at baseline and follow-up: processed (higher frequency of consumption of snacks and fast food); sweet (higher frequency of consumption of sweet foods and sweetened drinks); healthy (higher frequency of consumption of fruits, vegetables and wholemeal products). Children with higher-educated mothers and fathers and the highest household income were more likely to be allocated to the healthy cluster at baseline and follow-up and less likely to be allocated to the sweet cluster. Migrants were more likely to be allocated to the processed cluster at baseline and follow-up. Applying the cluster analysis to derive dietary patterns at the two time points allowed us to identify groups of children from a lower socio-economic background presenting persistently unhealthier dietary profiles. This finding reflects the need for healthy eating interventions specifically targeting children from lower socio-economic backgrounds.

Patterns of Health-Risk Behavior among Japanese High School Students.

ERIC Educational Resources Information Center

Takakura, Minoru; Nagayama, Tomoko; Sakihara, Seizo; Willcox, Craig

2001-01-01

Surveyed Japanese high school students' health risk behavior patterns, examining clustering and accumulation of health risk behaviors. Physical inactivity and alcohol use were the most common risk behaviors. Prevalence rates for most risk behaviors varied by demographic variables. Smoking, drinking, and sexual intercourse clustered among both…

Dietary Patterns Among Overweight and Obese African-American Women Living in the Rural South.

PubMed

Sterling, Samara; Judd, Suzanne; Bertrand, Brenda; Carson, Tiffany L; Chandler-Laney, Paula; Baskin, Monica L

2018-02-01

Obesity and chronic diseases disproportionately affect African-American women in the rural South (US) and may be influenced by adherence to a typical Southern-style diet. There is a need to examine dietary patterns of this population and to determine if consumption of nutritionally rich foods like nuts is associated with consumption of other nutritious foods. The objectives of this study were to identify (1) dietary patterns of overweight/obese African-American women in the rural South; (2) the role that nuts play in the diet; (3) and adherence to federal food group recommendations across dietary patterns. Secondary data analysis of two baseline 24-h dietary recalls was performed on 383 overweight/obese African-American women enrolled in a weight loss intervention in Alabama and Mississippi between 2011 and 2013. Cluster analysis identified dietary patterns. t tests and chi-square tests tested demographic and dietary differences across clusters. The proportion of women in each cluster who met federal recommendations for fruit, vegetable, nuts, added sugar, and sodium intake was calculated. Two dietary patterns were found. Nut intake frequency was higher in cluster 2 (P < .001), which was characterized by a higher intake frequency of fruits and vegetables, but high mean daily intake of added sugar (12.26 ± 7.67 tsp) and sodium (2800 ± 881 mg). Ninety-two percent of participants in this cluster consumed red/processed meats daily. Even among women in this population who consume a more plant-based dietary pattern containing nuts, there is still a need to decrease intake of added sugar, sodium, and red meat.

Distribution of shallow very low frequency earthquakes in the eastern Nankai trough influenced by a subducted oceanic ridge: Results from cluster analysis applied to ocean bottom seismographs

NASA Astrophysics Data System (ADS)

To, A.; Obana, K.; Araki, E.

2016-12-01

The activity of very low frequency earthquakes (VLFEs) in the shallow accretionary prism of the eastern Nankai trough has been observed frequently in the past. In this study, we investigated the distribution of VLFEs that occurred in October 2015, which were recorded by an array of broadband ocean bottom seismometers (BBOBSs) of DONET1 network. The size of the network is much wider (>80 km) compared to previous BBOBS networks that were used for close-in observations of VLFEs; therefore the new dataset provides a broader overview of the VLFE distribution of this region. We first located the detected events using conventional methods such as the envelope correlation method. However, the results seemed to be largely scattered due to noise and the effect of 3D structures that could not be properly handled. Then, we introduced hierarchal clustering analysis, based on measured travel time patterns among stations obtained for each event. The analyses enabled the assessment of relative locations among events. Finally, the locations of event-clusters were estimated, instead of individual events, so that the obtained locations seemed less scattered. The obtained results indicate that the VLFE distribution is strongly influenced by a subducted ridge (Park et al., 2003) that exists beneath the northeastern side of the DONET1 network. Though the VLFEs are distributed from an area near the outer ridge toward the trench axis in the region with a smooth plate boundary, they are clustered at a shallow depth near the outer ridge in the region of the rough plate boundary. The VLFEs are clustered on the landward side of the peak of the subducted ridge; this could be explained by an elevated pore pressure in the region caused by the low-permeability oceanic ridge that may clog the up-dip pathway of the fluid along the decollement zone. The along-strike variation of the stress state, inferred from the VLFE distribution, should be an important factor in assessing the strain release pattern and the regional variation of the tsunamigenic potential in the shallow plate boundary.

Two Distinct Patterns of Clostridium Difficile Diversity Across Europe Indicates Contrasting Routes of Spread.

PubMed

Eyre, David W; Davies, Kerrie A; Davis, Georgina; Fawley, Warren N; Dingle, Kate E; De Maio, Nicola; Karas, Andreas; Crook, Derrick W; Peto, Tim E A; Walker, A Sarah; Wilcox, Mark H

2018-04-06

Rates of Clostridium difficile infection vary widely across Europe, as do prevalent ribotypes. The extent of Europe-wide diversity within each ribotype is however unknown. Inpatient diarrhoeal faecal samples submitted on one day in summer and winter (2012-2013) to laboratories in 482 European hospitals were cultured for C. difficile, and isolates ribotyped; those from the 10 most prevalent ribotypes were Illumina whole-genome sequenced. Pairwise single nucleotide differences (SNPs) were obtained from recombination-corrected maximum-likelihood phylogenies. Within each ribotype, country-based sequence clustering was assessed using the ratio of the median SNPs between isolates within versus across different countries using permutation tests. Time-scaled Bayesian phylogenies where used to reconstruct the historic location of each lineage. Sequenced isolates (n=624) were from 19 countries. Five ribotypes had within-country clustering: ribotype-356, only in Italy; ribotype-018, predominantly in Italy; ribotype-176, with distinct Czech and German clades; ribotype-001/072, including distinct German, Slovakian, and Spanish clades; and ribotype-027, with multiple predominantly country-specific clades including in Hungary, Italy, Germany, Romania and Poland. By contrast, we found no within-country clustering for ribotypes 078, 015, 002, 014, and 020, consistent with a Europe-wide distribution. Fluoroquinolone-resistance was significantly more common in within-country clustered ribotypes (p=0.009). Fluoroquinolone-resistant isolates were also more tightly geographically clustered, median (IQR) 43 (0-213) miles between each isolate and the most closely genetically-related isolate vs. 421 (204-680) in non-resistant pairs (p<0.001). Two distinct patterns of C. difficile ribotype spread were observed, consistent with either predominantly healthcare-associated acquisition or Europe-wide dissemination via other routes/sources, e.g. the food chain.

Insights into quasar UV spectra using unsupervised clustering analysis

NASA Astrophysics Data System (ADS)

Tammour, A.; Gallagher, S. C.; Daley, M.; Richards, G. T.

2016-06-01

Machine learning techniques can provide powerful tools to detect patterns in multidimensional parameter space. We use K-means - a simple yet powerful unsupervised clustering algorithm which picks out structure in unlabelled data - to study a sample of quasar UV spectra from the Quasar Catalog of the 10th Data Release of the Sloan Digital Sky Survey (SDSS-DR10) of Paris et al. Detecting patterns in large data sets helps us gain insights into the physical conditions and processes giving rise to the observed properties of quasars. We use K-means to find clusters in the parameter space of the equivalent width (EW), the blue- and red-half-width at half-maximum (HWHM) of the Mg II 2800 Å line, the C IV 1549 Å line, and the C III] 1908 Å blend in samples of broad absorption line (BAL) and non-BAL quasars at redshift 1.6-2.1. Using this method, we successfully recover correlations well-known in the UV regime such as the anti-correlation between the EW and blueshift of the C IV emission line and the shape of the ionizing spectra energy distribution (SED) probed by the strength of He II and the Si III]/C III] ratio. We find this to be particularly evident when the properties of C III] are used to find the clusters, while those of Mg II proved to be less strongly correlated with the properties of the other lines in the spectra such as the width of C IV or the Si III]/C III] ratio. We conclude that unsupervised clustering methods (such as K-means) are powerful methods for finding `natural' binning boundaries in multidimensional data sets and discuss caveats and future work.

Cluster analysis of the organic peaks in bulk mass spectra obtained during the 2002 New England Air Quality Study with an Aerodyne aerosol mass spectrometer

NASA Astrophysics Data System (ADS)

Marcolli, C.; Canagaratna, M. R.; Worsnop, D. R.; Bahreini, R.; de Gouw, J. A.; Warneke, C.; Goldan, P. D.; Kuster, W. C.; Williams, E. J.; Lerner, B. M.; Roberts, J. M.; Meagher, J. F.; Fehsenfeld, F. C.; Marchewka, M. L.; Bertman, S. B.; Middlebrook, A. M.

2006-06-01

We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel Ronald H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter most probably originating from both, anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent as much as 5 µg/m3 organic aerosol mass - 17% of the total organic mass - that can be attributed to biogenic sources. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.

A new application of hierarchical cluster analysis to investigate organic peaks in bulk mass spectra obtained with an Aerodyne Aerosol Mass Spectrometer

NASA Astrophysics Data System (ADS)

Middlebrook, A. M.; Marcolli, C.; Canagaratna, M. R.; Worsnop, D. R.; Bahreini, R.; de Gouw, J. A.; Warneke, C.; Goldan, P. D.; Kuster, W. C.; Williams, E. J.; Lerner, B. M.; Roberts, J. M.; Meagher, J. F.; Fehsenfeld, F. C.; Marchewka, M. L.; Bertman, S. B.

2006-12-01

We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel Ronald H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter probably originating from both anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent on average 17% of the total organic mass that stems likely from biogenic sources during the ship's cruise. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.

Cluster Analysis of the Organic Peaks in Bulk Mass Spectra Obtained During the 2002 New England Air Quality Study with an Aerodyne Aerosol Mass Spectrometer

NASA Astrophysics Data System (ADS)

Marcolli, C.; Canagaratna, M. R.; Worsnop, D. R.; Bahreini, R.; de Gouw, J. A.; Warneke, C.; Goldan, P. D.; Kuster, W. C.; Williams, E. J.; Lerner, B. M.; Roberts, J. M.; Meagher, J. F.; Fehsenfeld, F. C.; Marchewka, M.; Bertman, S. B.; Middlebrook, A. M.

2006-12-01

We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel R. H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter probably originating from both anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent on average 17% of the total organic mass that stems likely from biogenic sources during the ship's cruise. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.

Spatial and Temporal Variation of Japanese encephalitis Disease and Detection of Disease Hotspots: a Case Study of Gorakhpur District, Uttar Pradesh, India

NASA Astrophysics Data System (ADS)

Verma, S.; Gupta, R. D.

2014-11-01

In recent times, Japanese Encephalitis (JE) has emerged as a serious public health problem. In India, JE outbreaks were recently reported in Uttar Pradesh, Gorakhpur. The present study presents an approach to use GIS for analyzing the reported cases of JE in the Gorakhpur district based on spatial analysis to bring out the spatial and temporal dynamics of the JE epidemic. The study investigates spatiotemporal pattern of the occurrence of disease and detection of the JE hotspot. Spatial patterns of the JE disease can provide an understanding of geographical changes. Geospatial distribution of the JE disease outbreak is being investigated since 2005 in this study. The JE incidence data for the years 2005 to 2010 is used. The data is then geo-coded at block level. Spatial analysis is used to evaluate autocorrelation in JE distribution and to test the cases that are clustered or dispersed in space. The Inverse Distance Weighting interpolation technique is used to predict the pattern of JE incidence distribution prevalent across the study area. Moran's I Index (Moran's I) statistics is used to evaluate autocorrelation in spatial distribution. The Getis-Ord Gi*(d) is used to identify the disease areas. The results represent spatial disease patterns from 2005 to 2010, depicting spatially clustered patterns with significant differences between the blocks. It is observed that the blocks on the built up areas reported higher incidences.

Academic Performance and Lifestyle Behaviors in Australian School Children: A Cluster Analysis.

PubMed

Dumuid, Dorothea; Olds, Timothy; Martín-Fernández, Josep-Antoni; Lewis, Lucy K; Cassidy, Leah; Maher, Carol

2017-12-01

Poor academic performance has been linked with particular lifestyle behaviors, such as unhealthy diet, short sleep duration, high screen time, and low physical activity. However, little is known about how lifestyle behavior patterns (or combinations of behaviors) contribute to children's academic performance. We aimed to compare academic performance across clusters of children with common lifestyle behavior patterns. We clustered participants (Australian children aged 9-11 years, n = 284) into four mutually exclusive groups of distinct lifestyle behavior patterns, using the following lifestyle behaviors as cluster inputs: light, moderate, and vigorous physical activity; sedentary behavior and sleep, derived from 24-hour accelerometry; self-reported screen time and diet. Differences in academic performance (measured by a nationally administered standardized test) were detected across the clusters, with scores being lowest in the Junk Food Screenies cluster (unhealthy diet/high screen time) and highest in the Sitters cluster (high nonscreen sedentary behavior/low physical activity). These findings suggest that reduction in screen time and an improved diet may contribute positively to academic performance. While children with high nonscreen sedentary time performed better academically in this study, they also accumulated low levels of physical activity. This warrants further investigation, given the known physical and mental benefits of physical activity.

Obesigenic families: parents’ physical activity and dietary intake patterns predict girls’ risk of overweight

PubMed Central

Davison, K Krahnstoever; Birch, L Lipps

2008-01-01

OBJECTIVE To determine whether obesigenic families can be identified based on mothers’ and fathers’ dietary and activity patterns. METHODS A total of 197 girls and their parents were assessed when girls were 5 y old; 192 families were reassessed when girls were 7 y old. Measures of parents’ physical activity and dietary intake were obtained and entered into a cluster analysis to assess whether distinct family clusters could be identified. Girls’ skinfold thickness and body mass index (BMI) were also assessed and were used to examine the predictive validity of the clusters. RESULTS Obesigenic and a non-obesigenic family clusters were identified. Mothers and fathers in the obesigenic cluster reported high levels of dietary intake and low levels of physical activity, while mothers and fathers in the non-obesigenic cluster reported low levels of dietary intake and high levels of activity. Girls from families in the obesigenic cluster had significantly higher BMI and skinfold thickness values at age 7 and showed significantly greater increases in BMI and skinfold thickness from ages 5 to 7 y than girls from non-obesigenic families; differences were reduced but not eliminated after controlling for parents’ BMI. CONCLUSIONS Obesigenic families, defined in terms of parents’ activity and dietary patterns, can be used predict children’s risk of obesity. PMID:12187395

Lifestyle Patterns and Weight Status in Spanish Adults: The ANIBES Study

PubMed Central

Pérez-Rodrigo, Carmen; Gianzo-Citores, Marta; Gil, Ángel; González-Gross, Marcela; Ortega, Rosa M.; Serra-Majem, Lluis; Varela-Moreiras, Gregorio; Aranceta-Bartrina, Javier

2017-01-01

Limited knowledge is available on lifestyle patterns in Spanish adults. We investigated dietary patterns and possible meaningful clustering of physical activity, sedentary behavior, sleep time, and smoking in Spanish adults aged 18–64 years and their association with obesity. Analysis was based on a subsample (n = 1617) of the cross-sectional ANIBES study in Spain. We performed exploratory factor analysis and subsequent cluster analysis of dietary patterns, physical activity, sedentary behaviors, sleep time, and smoking. Logistic regression analysis was used to explore the association between the cluster solutions and obesity. Factor analysis identified four dietary patterns, “Traditional DP”, “Mediterranean DP”, “Snack DP” and “Dairy-sweet DP”. Dietary patterns, physical activity behaviors, sedentary behaviors, sleep time, and smoking in Spanish adults aggregated into three different clusters of lifestyle patterns: “Mixed diet-physically active-low sedentary lifestyle pattern”, “Not poor diet-low physical activity-low sedentary lifestyle pattern” and “Poor diet-low physical activity-sedentary lifestyle pattern”. A higher proportion of people aged 18–30 years was classified into the “Poor diet-low physical activity-sedentary lifestyle pattern”. The prevalence odds ratio for obesity in men in the “Mixed diet-physically active-low sedentary lifestyle pattern” was significantly lower compared to those in the “Poor diet-low physical activity-sedentary lifestyle pattern”. Those behavior patterns are helpful to identify specific issues in population subgroups and inform intervention strategies. The findings in this study underline the importance of designing and implementing interventions that address multiple health risk practices, considering lifestyle patterns and associated determinants. PMID:28613259

The Geomorphology of Puget Sound Beaches

DTIC Science & Technology

2006-10-01

of longer-term climate variations it is referred to as a meteorological residual. An analysis of regional air pressure and water level observations...wave and tidal climate . For further details on the analy- sis rational and methods, see Finlayson (2006) The clustering analysis resulted in four profile...energy compared with incident waves on the Pacific Coast, and (2) the wave climate is tightly coupled with local wind patterns. The direction of

Statistical Evaluation of Voltage Variation of Power Distribution System with Clustered Home-Cogeneration Systems

NASA Astrophysics Data System (ADS)

Kato, Takeyoshi; Minagata, Atsushi; Suzuoki, Yasuo

This paper discusses the influence of mass installation of a home co-generation system (H-CGS) using a polymer electrolyte fuel cell (PEFC) on the voltage profile of power distribution system in residential area. The influence of H-CGS is compared with that of photovoltaic power generation systems (PV systems). The operation pattern of H-CGS is assumed based on the electricity and hot-water demand observed in 10 households for a year. The main results are as follows. With the clustered H-CGS, the voltage of each bus is higher by about 1-3% compared with the conventional system without any distributed generators. Because H-CGS tends to increase the output during the early evening, H-CGS contributes to recover the voltage drop during the early evening, resulting in smaller voltage variation of distribution system throughout a day. Because of small rated power output about 1kW, the influence on voltage profile by the clustered H-CGS is smaller than that by the clustered PV systems. The highest voltage during the day time is not so high as compared with the distribution system with the clustered PV systems, even if the reverse power flow from H-CGS is allowed.

Calculation of composition distribution of ultrafine ion-H2O-H2SO4 clusters using a modified binary ion nucleation theory

NASA Technical Reports Server (NTRS)

Singh, J. J.; Smith, A. S.; Chan, L. Y.; Yue, G. K.

1982-01-01

Thomson's ion nucleation theory was modified to include the effects of curvature dependence of the microscopic surface tension of field dependent, nonlinear, dielectric properties of the liquid; and of sulfuric acid hydrate formation in binary mixtures of water and sulfuric acid vapors. The modified theory leads to a broadening of the ion cluster spectrum, and shifts it towards larger numbers of H2O and H2SO4 molecules. Whether there is more shifting towards larger numbers of H2O or H2SO4 molecules depends on the relative humidity and relative acidity of the mixture. Usually, a broadening of the spectrum is accompanied by a lowering of the mean cluster intensity. For fixed values of relative humidity and relative acidity, a similar broadening pattern is observed when the temperature is lowered. These features of the modified theory illustrate that a trace of sulfuric acid can facilitate the formation of ultrafine, stable, prenucleation ion clusters as well as the growth of the prenucleation ion clusters towards the critical saddle point conditions, even with low values of relative humidity and relative acidity.

Influence of the Lower Jaw Position on the Running Pattern.

PubMed

Maurer, Christian; Stief, Felix; Jonas, Alexander; Kovac, Andrej; Groneberg, David Alexander; Meurer, Andrea; Ohlendorf, Daniela

2015-01-01

The effects of manipulated dental occlusion on body posture has been investigated quite often and discussed controversially in the literature. Far less attention has been paid to the influence of dental occlusion position on human movement. If human movement was analysed, it was mostly while walking and not while running. This study was therefore designed to identify the effect of lower jaw positions on running behaviour according to different dental occlusion positions. Twenty healthy young recreational runners (mean age = 33.9±5.8 years) participated in this study. Kinematic data were collected using an eight-camera Vicon motion capture system (VICON Motion Systems, Oxford, UK). Subjects were consecutively prepared with four different dental occlusion conditions in random order and performed five running trials per test condition on a level walkway with their preferred running shoes. Vector based pattern recognition methods, in particular cluster analysis and support vector machines (SVM) were used for movement pattern identification. Subjects exhibited unique movement patterns leading to 18 clusters for the 20 subjects. No overall classification of the splint condition could be observed. Within individual subjects different running patterns could be identified for the four splint conditions. The splint conditions lead to a more symmetrical running pattern than the control condition. The influence of an occlusal splint on running pattern can be confirmed in this study. Wearing a splint increases the symmetry of the running pattern. A more symmetrical running pattern might help to reduce the risk of injuries or help in performance. The change of the movement pattern between the neutral condition and any of the three splint conditions was significant within subjects but not across subjects. Therefore the dental splint has a measureable influence on the running pattern of subjects, however subjects individuality has to be considered when choosing the optimal splint condition for a specific subject.

Dietary patterns of rural older adults are associated with weight and nutritional status.

PubMed

Ledikwe, Jenny H; Smiciklas-Wright, Helen; Mitchell, Diane C; Miller, Carla K; Jensen, Gordon L

2004-04-01

To characterize dietary patterns of rural older adults and relate patterns to weight and nutritional status. Cross-sectional. Rural Pennsylvania. One hundred seventy-nine community-dwelling adults aged 66 to 87 years. A home visit was conducted to collect demographic, health behavior, and anthropometric data and a blood sample. Five 24-hour dietary recall were administered. Cluster analysis classified participants into dietary patterns using food subgroup servings. Chi-square, analysis of covariance, and logistic regression were used to assess differences across clusters. A low-nutrient-dense cluster (n=107), with higher intake of breads, sweet breads/desserts, dairy desserts, processed meats, eggs, and fats/oils, and a high-nutrient-dense cluster (n=72) with higher intake of cereals, dark green/yellow vegetables, other vegetables, citrus/melons/berries, fruit juices, other fruits, milks, poultry, fish, and beans, were identified. Those in the high-nutrient-dense cluster had lower energy intake; higher energy-adjusted intake of fiber, iron, zinc, folate, and vitamins B(6), B(12), and D; higher Healthy Eating Index scores; higher plasma vitamin B(12) levels; and a lower waist circumference. Those with a low-nutrient-dense dietary pattern were twice as likely to be obese, twice as likely to have low plasma vitamin B(12) levels, and three to 17 times more likely to have low nutrient intake. This study provides support for recommending a high-nutrient-dense dietary pattern for older adults. Behavioral interventions encouraging diets characterized by high-nutrient-dense foods may improve weight and nutritional status of older adults.

Spatiotemporal analysis of dengue fever in Nepal from 2010 to 2014.

PubMed

Acharya, Bipin Kumar; Cao, ChunXiang; Lakes, Tobia; Chen, Wei; Naeem, Shahid

2016-08-22

Due to recent emergence, dengue is becoming one of the major public health problems in Nepal. The numbers of reported dengue cases in general and the area with reported dengue cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of dengue have not been investigated yet. This study aims to fill this gap by analyzing spatiotemporal patterns based on monthly surveillance data aggregated at district. Dengue cases from 2010 to 2014 at district level were collected from the Nepal government's health and mapping agencies respectively. GeoDa software was used to map crude incidence, excess hazard and spatially smoothed incidence. Cluster analysis was performed in SaTScan software to explore spatiotemporal clusters of dengue during the above-mentioned time period. Spatiotemporal distribution of dengue fever in Nepal from 2010 to 2014 was mapped at district level in terms of crude incidence, excess risk and spatially smoothed incidence. Results show that the distribution of dengue fever was not random but clustered in space and time. Chitwan district was identified as the most likely cluster and Jhapa district was the first secondary cluster in both spatial and spatiotemporal scan. July to September of 2010 was identified as a significant temporal cluster. This study assessed and mapped for the first time the spatiotemporal pattern of dengue fever in Nepal. Two districts namely Chitwan and Jhapa were found highly affected by dengue fever. The current study also demonstrated the importance of geospatial approach in epidemiological research. The initial result on dengue patterns and risk of this study may assist institutions and policy makers to develop better preventive strategies.

pySAPC, a python package for sparse affinity propagation clustering: Application to odontogenesis whole genome time series gene-expression data.

PubMed

Cao, Huojun; Amendt, Brad A

2016-11-01

Developmental dental anomalies are common forms of congenital defects. The molecular mechanisms of dental anomalies are poorly understood. Systematic approaches such as clustering genes based on similar expression patterns could identify novel genes involved in dental anomalies and provide a framework for understanding molecular regulatory mechanisms of these genes during tooth development (odontogenesis). A python package (pySAPC) of sparse affinity propagation clustering algorithm for large datasets was developed. Whole genome pair-wise similarity was calculated based on expression pattern similarity based on 45 microarrays of several stages during odontogenesis. pySAPC identified 743 gene clusters based on expression pattern similarity during mouse tooth development. Three clusters are significantly enriched for genes associated with dental anomalies (with FDR <0.1). The three clusters of genes have distinct expression patterns during odontogenesis. Clustering genes based on similar expression profiles recovered several known regulatory relationships for genes involved in odontogenesis, as well as many novel genes that may be involved with the same genetic pathways as genes that have already been shown to contribute to dental defects. By using sparse similarity matrix, pySAPC use much less memory and CPU time compared with the original affinity propagation program that uses a full similarity matrix. This python package will be useful for many applications where dataset(s) are too large to use full similarity matrix. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016. Published by Elsevier B.V.

Characterizing Suicide in Toronto: An Observational Study and Cluster Analysis

PubMed Central

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

2014-01-01

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

Tuberculosis outbreaks predicted by characteristics of first patients in a DNA fingerprint cluster.

PubMed

Kik, Sandra V; Verver, Suzanne; van Soolingen, Dick; de Haas, Petra E W; Cobelens, Frank G; Kremer, Kristin; van Deutekom, Henk; Borgdorff, Martien W

2008-07-01

Some clusters of patients who have Mycobacterium tuberculosis isolates with identical DNA fingerprint patterns grow faster than others. It is unclear what predictors determine cluster growth. To assess whether the development of a tuberculosis (TB) outbreak can be predicted by the characteristics of its first two patients. Demographic and clinical data of all culture-confirmed patients with TB in the Netherlands from 1993 through 2004 were combined with DNA fingerprint data. Clusters were restricted to cluster episodes of 2 years to only detect newly arising clusters. Characteristics of the first two patients were compared between small (2-4 cases) and large (5 or more cases) cluster episodes. Of 5,454 clustered cases, 1,756 (32%) were part of a cluster episode of 2 years. Of 622 cluster episodes, 54 (9%) were large and 568 (91%) were small episodes. Independent predictors for large cluster episodes were as follows: less than 3 months' time between the diagnosis of the first two patients, one or both patients were young (<35 yr), both patients lived in an urban area, and both patients came from sub-Saharan Africa. In the Netherlands, patients in new cluster episodes should be screened for these risk factors. When the risk pattern applies, targeted interventions (e.g., intensified contact investigation) should be considered to prevent further cluster expansion.

Biased immunoglobulin light chain gene usage in the shark1

PubMed Central

Iacoangeli, Anna; Lui, Anita; Naik, Ushma; Ohta, Yuko; Flajnik, Martin; Hsu, Ellen

2015-01-01

This study of a large family of kappa light (L) chain clusters in nurse shark completes the characterization of its classical immunoglobulin (Ig) gene content (two heavy chain classes, mu and omega, and four L chain isotopes, kappa, lambda, sigma, and sigma-2). The shark kappa clusters are minigenes consisting of a simple VL-JL-CL array, where V to J recombination occurs over a ~500 bp interval, and functional clusters are widely separated by at least 100 kb. Six out of ca. 39 kappa clusters are pre-rearranged in the germline (GL-joined). Unlike the complex gene organization and multistep assembly process of Ig in mammals, each shark Ig rearrangement, somatic or in the germline, appears to be an independent event localized to the minigene. This study examined the expression of functional, non-productive, and sterile transcripts of the kappa clusters compared to the other three L chain isotypes. Kappa cluster usage was investigated in young sharks, and a skewed pattern of split gene expression was observed, one similar in functional and non-productive rearrangements. These results show that the individual activation of the spatially distant kappa clusters is non-random. Although both split and GL-joined kappa genes are expressed, the latter are prominent in young animals and wane with age. We speculate that, in the shark, the differential activation of the multiple isotypes can be advantageously used in receptor editing. PMID:26342033

Biased Immunoglobulin Light Chain Gene Usage in the Shark.

PubMed

Iacoangeli, Anna; Lui, Anita; Naik, Ushma; Ohta, Yuko; Flajnik, Martin; Hsu, Ellen

2015-10-15

This study of a large family of κ L chain clusters in nurse shark completes the characterization of its classical Ig gene content (two H chain isotypes, μ and ω, and four L chain isotypes, κ, λ, σ, and σ-2). The shark κ clusters are minigenes consisting of a simple VL-JL-CL array, where V to J recombination occurs over an ~500-bp interval, and functional clusters are widely separated by at least 100 kb. Six out of ~39 κ clusters are prerearranged in the germline (germline joined). Unlike the complex gene organization and multistep assembly process of Ig in mammals, each shark Ig rearrangement, somatic or in the germline, appears to be an independent event localized to the minigene. This study examined the expression of functional, nonproductive, and sterile transcripts of the κ clusters compared with the other three L chain isotypes. κ cluster usage was investigated in young sharks, and a skewed pattern of split gene expression was observed, one similar in functional and nonproductive rearrangements. These results show that the individual activation of the spatially distant κ clusters is nonrandom. Although both split and germline-joined κ genes are expressed, the latter are prominent in young animals and wane with age. We speculate that, in the shark, the differential activation of the multiple isotypes can be advantageously used in receptor editing. Copyright © 2015 by The American Association of Immunologists, Inc.

Rationalizing the role of structural motif and underlying electronic structure in the finite temperature behavior of atomic clusters

NASA Astrophysics Data System (ADS)

Susan, Anju; Joshi, Kavita

2014-04-01

Melting in finite size systems is an interesting but complex phenomenon. Many factors affect melting and owing to their interdependencies it is a challenging task to rationalize their roles in the phase transition. In this work, we demonstrate how structural motif of the ground state influences melting transition in small clusters. Here, we report a case with clusters of aluminum and gallium having same number of atoms, valence electrons, and similar structural motif of the ground state but drastically different melting temperatures. We have employed Born-Oppenheimer molecular dynamics to simulate the solid-like to liquid-like transition in these clusters. Our simulations have reproduced the experimental trends fairly well. Further, the detailed analysis of isomers has brought out the role of the ground state structure and underlying electronic structure in the finite temperature behavior of these clusters. For both clusters, isomers accessible before cluster melts have striking similarities and does have strong influence of the structural motif of the ground state. Further, the shape of the heat capacity curve is similar in both the cases but the transition is more spread over for Al36 which is consistent with the observed isomerization pattern. Our simulations also suggest a way to characterize transition region on the basis of accessibility of the ground state at a specific temperature.

Transfer of Timing Information from RGC to LGN Spike Trains

NASA Astrophysics Data System (ADS)

Teich, Malvin C.; Lowen, Steven B.; Saleh, Bahaa E. A.; Kaplan, Ehud

1998-03-01

We have studied the firing patterns of retinal ganglion cells (RGCs) and their target lateral geniculate nucleus (LGN) cells. We find that clusters of spikes in the RGC neural firing pattern appear at the LGN output essentially unchanged, while isolated RGC firing events are more likely to be eliminated; thus the LGN action-potential sequence is therefore not merely a randomly deleted version of the RGC spike train. Employing information-theoretic techniques we developed for point processes,(B. E. A. Saleh and M. C. Teich, Phys. Rev. Lett.) 58, 2656--2659 (1987). we are able to estimate the information efficiency of the LGN neuronal output --- the proportion of the variation in the LGN firing pattern that carries information about its associated RGC input. A suitably modified integrate-and-fire neural model reproduces both the enhanced clustering in the LGN data (which accounts for the increased coefficient of variation) and the measured value of information efficiency, as well as mimicking the results of other observed statistical measures. Reliable information transmission therefore coexists with fractal fluctuations, which appear in RGC and LGN firing patterns.(M. C. Teich, C. Heneghan, S. B. Lowen, T. Ozaki, and E. Kaplan, J. Opt. Soc. Am. A) 14, 529--546 (1997).

Health-Related Quality of Life and Lifestyle Behavior Clusters in School-Aged Children from 12 Countries.

PubMed

Dumuid, Dorothea; Olds, Timothy; Lewis, Lucy K; Martin-Fernández, Josep Antoni; Katzmarzyk, Peter T; Barreira, Tiago; Broyles, Stephanie T; Chaput, Jean-Philippe; Fogelholm, Mikael; Hu, Gang; Kuriyan, Rebecca; Kurpad, Anura; Lambert, Estelle V; Maia, José; Matsudo, Victor; Onywera, Vincent O; Sarmiento, Olga L; Standage, Martyn; Tremblay, Mark S; Tudor-Locke, Catrine; Zhao, Pei; Gillison, Fiona; Maher, Carol

2017-04-01

To evaluate the relationship between children's lifestyles and health-related quality of life and to explore whether this relationship varies among children from different world regions. This study used cross-sectional data from the International Study of Childhood Obesity, Lifestyle and the Environment. Children (9-11 years) were recruited from sites in 12 nations (n = 5759). Clustering input variables were 24-hour accelerometry and self-reported diet and screen time. Health-related quality of life was self-reported with KIDSCREEN-10. Cluster analyses (using compositional analysis techniques) were performed on a site-wise basis. Lifestyle behavior cluster characteristics were compared between sites. The relationship between cluster membership and health-related quality of life was assessed with the use of linear models. Lifestyle behavior clusters were similar across the 12 sites, with clusters commonly characterized by (1) high physical activity (actives); (2) high sedentary behavior (sitters); (3) high screen time/unhealthy eating pattern (junk-food screenies); and (4) low screen time/healthy eating pattern and moderate physical activity/sedentary behavior (all-rounders). Health-related quality of life was greatest in the all-rounders cluster. Children from different world regions clustered into groups of similar lifestyle behaviors. Cluster membership was related to differing health-related quality of life, with children from the all-rounders cluster consistently reporting greatest health-related quality of life at sites around the world. Findings support the importance of a healthy combination of lifestyle behaviors in childhood: low screen time, healthy eating pattern, and balanced daily activity behaviors (physical activity and sedentary behavior). ClinicalTrials.gov: NCT01722500. Copyright © 2016 Elsevier Inc. All rights reserved.

What if Reading is Easy but Unimportant? How Students’ Patterns of Affirming and Undermining Motivation for Reading Information Texts Predict Different Reading Outcomes

PubMed Central

Rosenzweig, Emily Q.; Wigfield, Allan

2016-01-01

Many affirming and undermining motivational constructs affect students as they read information texts, but few researchers have explored how these motivations are patterned within students. In this study we used cluster analysis to classify middle school students (n = 1,134) based on their patterns of self-efficacy, perceived difficulty, value, and devalue for reading school information texts. We then compared how the patterns predicted students’ language arts grades, science information text comprehension, and dedication to reading school information texts. We found and validated a four-cluster solution. One cluster included a pattern of high affirming and low undermining motivations, and another included low affirming and high undermining motivations. Students with these patterns earned the highest and lowest scores, respectively, on all outcomes. A third pattern showed high self-efficacy/low difficulty with low value/high devalue, and a fourth showed moderate levels of all four motivational constructs. Students with the high efficacy and devalue pattern showed high information text comprehension but relatively low dedication. Students with the moderate pattern showed high dedication but low initial information text comprehension. Students with these two patterns earned similar grades. We discuss the implications of our findings for motivation theories and for school instruction that involves information text reading. PMID:28496289

What if Reading is Easy but Unimportant? How Students' Patterns of Affirming and Undermining Motivation for Reading Information Texts Predict Different Reading Outcomes.

PubMed

Rosenzweig, Emily Q; Wigfield, Allan

2017-01-01

Many affirming and undermining motivational constructs affect students as they read information texts, but few researchers have explored how these motivations are patterned within students. In this study we used cluster analysis to classify middle school students (n = 1,134) based on their patterns of self-efficacy, perceived difficulty, value, and devalue for reading school information texts. We then compared how the patterns predicted students' language arts grades, science information text comprehension, and dedication to reading school information texts. We found and validated a four-cluster solution. One cluster included a pattern of high affirming and low undermining motivations, and another included low affirming and high undermining motivations. Students with these patterns earned the highest and lowest scores, respectively, on all outcomes. A third pattern showed high self-efficacy/low difficulty with low value/high devalue, and a fourth showed moderate levels of all four motivational constructs. Students with the high efficacy and devalue pattern showed high information text comprehension but relatively low dedication. Students with the moderate pattern showed high dedication but low initial information text comprehension. Students with these two patterns earned similar grades. We discuss the implications of our findings for motivation theories and for school instruction that involves information text reading.

Assessment of Overlap of Phylogenetic Transmission Clusters and Communities in Simple Sexual Contact Networks: Applications to HIV-1

PubMed Central

Villandre, Luc; Günthard, Huldrych F.; Kouyos, Roger; Stadler, Tanja

2016-01-01

Background Transmission patterns of sexually-transmitted infections (STIs) could relate to the structure of the underlying sexual contact network, whose features are therefore of interest to clinicians. Conventionally, we represent sexual contacts in a population with a graph, that can reveal the existence of communities. Phylogenetic methods help infer the history of an epidemic and incidentally, may help detecting communities. In particular, phylogenetic analyses of HIV-1 epidemics among men who have sex with men (MSM) have revealed the existence of large transmission clusters, possibly resulting from within-community transmissions. Past studies have explored the association between contact networks and phylogenies, including transmission clusters, producing conflicting conclusions about whether network features significantly affect observed transmission history. As far as we know however, none of them thoroughly investigated the role of communities, defined with respect to the network graph, in the observation of clusters. Methods The present study investigates, through simulations, community detection from phylogenies. We simulate a large number of epidemics over both unweighted and weighted, undirected random interconnected-islands networks, with islands corresponding to communities. We use weighting to modulate distance between islands. We translate each epidemic into a phylogeny, that lets us partition our samples of infected subjects into transmission clusters, based on several common definitions from the literature. We measure similarity between subjects’ island membership indices and transmission cluster membership indices with the adjusted Rand index. Results and Conclusion Analyses reveal modest mean correspondence between communities in graphs and phylogenetic transmission clusters. We conclude that common methods often have limited success in detecting contact network communities from phylogenies. The rarely-fulfilled requirement that network communities correspond to clades in the phylogeny is their main drawback. Understanding the link between transmission clusters and communities in sexual contact networks could help inform policymaking to curb HIV incidence in MSMs. PMID:26863322

Dietary patterns derived by hybrid clustering method in older people: association with cognition, mood, and self-rated health.

PubMed

Samieri, Cécilia; Jutand, Marthe-Aline; Féart, Catherine; Capuron, Lucile; Letenneur, Luc; Barberger-Gateau, Pascale

2008-09-01

Several nutritional factors, including dietary fatty acids, antioxidants, and folates, have been related to pathological brain aging. Dietary patterns that represent a combination of foods may better predict disease risk than single foods or nutrients. To identify dietary patterns by a mixed clustering method and to analyze their relationship with cognitive function, depressive symptoms, and self-rated health in older people. Cross-sectional population-based study. Subjects included 1,724 elderly community dwellers living in Bordeaux, France from 2001 to 2002. Cluster analysis, combining hybrid clustering, and research for stable groups during the k-means step on mean number of weekly servings of 20 predetermined food groups, separately in men and women. Five dietary clusters were identified in each sex. A "healthy" cluster characterized by higher consumption of fish in men (n=157; 24.3%) and fruits and vegetables in women (n=267; 24.8%) had significantly lower mean number of errors to Mini Mental State score after adjustment for socio-demographic variables (beta=-0.11; 95% confidence interval [CI], -0.22 to -0.004 in men; beta=-0.13; 95% CI, -0.22 to -0.04 in women). The same cluster was associated with borderline significance with lower depressive symptoms in women (beta=-0.16; 95% CI, -0.33 to 0.007). Men in the "pasta eaters" cluster (n=136; 21%) had higher depressive symptoms (beta=0.26; 95% CI, 0.06 to 0.46) and higher risk to report poor health (polytomous regression, odds ratio [OR]=1.91; 95% CI, 1.21 to 3.01) than the "healthy" cluster. Women in the "biscuits and snacking" cluster (n=162; 15%) had greater risk of poor perceived health (OR=1.69; 95% CI, 1.15 to 2.48) compared to "healthy" eaters. Additional adjustment for body mass index and medication use strengthened these associations. Sex-specific dietary patterns derived by hybrid clustering method are associated with fewer cognitive and depressive symptoms and better perceived health in older people.

Average correlation clustering algorithm (ACCA) for grouping of co-regulated genes with similar pattern of variation in their expression values.

PubMed

Bhattacharya, Anindya; De, Rajat K

2010-08-01

Distance based clustering algorithms can group genes that show similar expression values under multiple experimental conditions. They are unable to identify a group of genes that have similar pattern of variation in their expression values. Previously we developed an algorithm called divisive correlation clustering algorithm (DCCA) to tackle this situation, which is based on the concept of correlation clustering. But this algorithm may also fail for certain cases. In order to overcome these situations, we propose a new clustering algorithm, called average correlation clustering algorithm (ACCA), which is able to produce better clustering solution than that produced by some others. ACCA is able to find groups of genes having more common transcription factors and similar pattern of variation in their expression values. Moreover, ACCA is more efficient than DCCA with respect to the time of execution. Like DCCA, we use the concept of correlation clustering concept introduced by Bansal et al. ACCA uses the correlation matrix in such a way that all genes in a cluster have the highest average correlation values with the genes in that cluster. We have applied ACCA and some well-known conventional methods including DCCA to two artificial and nine gene expression datasets, and compared the performance of the algorithms. The clustering results of ACCA are found to be more significantly relevant to the biological annotations than those of the other methods. Analysis of the results show the superiority of ACCA over some others in determining a group of genes having more common transcription factors and with similar pattern of variation in their expression profiles. Availability of the software: The software has been developed using C and Visual Basic languages, and can be executed on the Microsoft Windows platforms. The software may be downloaded as a zip file from http://www.isical.ac.in/~rajat. Then it needs to be installed. Two word files (included in the zip file) need to be consulted before installation and execution of the software. Copyright 2010 Elsevier Inc. All rights reserved.

MOCCA code for star cluster simulation: comparison with optical observations using COCOA

NASA Astrophysics Data System (ADS)

Askar, Abbas; Giersz, Mirek; Pych, Wojciech; Olech, Arkadiusz; Hypki, Arkadiusz

2016-02-01

We introduce and present preliminary results from COCOA (Cluster simulatiOn Comparison with ObservAtions) code for a star cluster after 12 Gyr of evolution simulated using the MOCCA code. The COCOA code is being developed to quickly compare results of numerical simulations of star clusters with observational data. We use COCOA to obtain parameters of the projected cluster model. For comparison, a FITS file of the projected cluster was provided to observers so that they could use their observational methods and techniques to obtain cluster parameters. The results show that the similarity of cluster parameters obtained through numerical simulations and observations depends significantly on the quality of observational data and photometric accuracy.

Vortex with fourfold defect lines in a simple model of self-propelled particles

NASA Astrophysics Data System (ADS)

Seyed-Allaei, Hamid; Ejtehadi, Mohammad Reza

2016-03-01

We study the formation of a vortex with fourfold symmetry in a minimal model of self-propelled particles, confined inside a squared box, using computer simulations and also theoretical analysis. In addition to the vortex pattern, we observe five other regimes in the system: a homogeneous gaseous phase, band structures, moving clumps, moving clusters, and vibrating rings. All six regimes emerge from controlling the strength of noise and from the contribution of repulsion and alignment interactions. We study the shape of the vortex and its symmetry in detail. The pattern shows exponential defect lines where incoming and outgoing flows of particles collide. We show that alignment and repulsion interactions between particles are necessary to form such patterns. We derive hydrodynamical equations with an introduction of the "small deviation" technique to describe the vortex phase. The method is applicable to other systems as well. Finally, we compare the theory with the results of both computer simulations and an experiment using Quincke rotors. A good agreement between the three is observed.

Expression patterns of the aquaporin gene family during renal development: influence of genetic variability.

PubMed

Parreira, Kleber S; Debaix, Huguette; Cnops, Yvette; Geffers, Lars; Devuyst, Olivier

2009-08-01

High-throughput analyses have shown that aquaporins (AQPs) belong to a cluster of genes that are differentially expressed during kidney organogenesis. However, the spatiotemporal expression patterns of the AQP gene family during tubular maturation and the potential influence of genetic variation on these patterns and on water handling remain unknown. We investigated the expression patterns of all AQP isoforms in fetal (E13.5 to E18.5), postnatal (P1 to P28), and adult (9 weeks) kidneys of inbred (C57BL/6J) and outbred (CD-1) mice. Using quantitative polymerase chain reaction (PCR), we evidenced two mRNA patterns during tubular maturation in C57 mice. The AQPs 1-7-11 showed an early (from E14.5) and progressive increase to adult levels, similar to the mRNA pattern observed for proximal tubule markers (Megalin, NaPi-IIa, OAT1) and reflecting the continuous increase in renal cortical structures during development. By contrast, AQPs 2-3-4 showed a later (E15.5) and more abrupt increase, with transient postnatal overexpression. Most AQP genes were expressed earlier and/or stronger in maturing CD-1 kidneys. Furthermore, adult CD-1 kidneys expressed more AQP2 in the collecting ducts, which was reflected by a significant delay in excreting a water load. The expression patterns of proximal vs. distal AQPs and the earlier expression in the CD-1 strain were confirmed by immunoblotting and immunostaining. These data (1) substantiate the clustering of important genes during tubular maturation and (2) demonstrate that genetic variability influences the regulation of the AQP gene family during tubular maturation and water handling by the mature kidney.

Temporal and spatial mapping of hand, foot and mouth disease in Sarawak, Malaysia.

PubMed

Sham, Noraishah M; Krishnarajah, Isthrinayagy; Ibrahim, Noor Akma; Lye, Munn-Sann

2014-05-01

Hand, foot and mouth disease (HFMD) is endemic in Sarawak, Malaysia. In this study, a geographical information system (GIS) was used to investigate the relationship between the reported HFMD cases and the spatial patterns in 11 districts of Sarawak from 2006 to 2012. Within this 7-years period, the highest number of reported HFMD cases occurred in 2006, followed by 2012, 2008, 2009, 2007, 2010 and 2011, in descending order. However, while there was no significant distribution pattern or clustering in the first part of the study period (2006 to 2011) based on Moran's I statistic, spatial autocorrelation (P = 0.068) was observed in 2012.

Postural orientation and standing postural alignment in ambulant children with bilateral cerebral palsy.

PubMed

Domagalska-Szopa, Małgorzata; Szopa, Andrzej

2017-11-01

Standing postural alignment in children with cerebral palsy is usually altered by central postural control disorders. The primary aim of this study is to describe body alignment in a quiet standing position in ambulatory children with bilateral cerebral palsy compared with children with typical development. Fifty-eight children with bilateral cerebral palsy (aged 7-13years) and 45 age-matched children with typical development underwent a surface topography examination based on Moiré topography and were classified according to their sagittal postural profiles. The following eight grouping variables were extracted using a data reduction technique: angle of trunk inclination, pelvic tilt, and lordosis, the difference between kyphosis and lordosis, angle of vertebral lateral curvature, shoulder inclination, and shoulder and pelvic rotation. According to the cluster analysis results, 25% of the participants were classified into Cluster 1, 9% into Cluster 2, 49% in Cluster 3, and 17% in Cluster 4. Three different postural patterns emerged in accordance with the sagittal postural profiles in children with bilateral cerebral palsy and were defined as follows: 1) a lordotic postural pattern corresponding to forward-leaning posture; 2) a swayback postural pattern corresponding to backward-leaning posture; and 3) a balanced postural pattern corresponding to balanced posture. Copyright © 2017 Elsevier Ltd. All rights reserved.

Image-based quantification and mathematical modeling of spatial heterogeneity in ESC colonies.

PubMed

Herberg, Maria; Zerjatke, Thomas; de Back, Walter; Glauche, Ingmar; Roeder, Ingo

2015-06-01

Pluripotent embryonic stem cells (ESCs) have the potential to differentiate into cells of all three germ layers. This unique property has been extensively studied on the intracellular, transcriptional level. However, ESCs typically form clusters of cells with distinct size and shape, and establish spatial structures that are vital for the maintenance of pluripotency. Even though it is recognized that the cells' arrangement and local interactions play a role in fate decision processes, the relations between transcriptional and spatial patterns have not yet been studied. We present a systems biology approach which combines live-cell imaging, quantitative image analysis, and multiscale, mathematical modeling of ESC growth. In particular, we develop quantitative measures of the morphology and of the spatial clustering of ESCs with different expression levels and apply them to images of both in vitro and in silico cultures. Using the same measures, we are able to compare model scenarios with different assumptions on cell-cell adhesions and intercellular feedback mechanisms directly with experimental data. Applying our methodology to microscopy images of cultured ESCs, we demonstrate that the emerging colonies are highly variable regarding both morphological and spatial fluorescence patterns. Moreover, we can show that most ESC colonies contain only one cluster of cells with high self-renewing capacity. These cells are preferentially located in the interior of a colony structure. The integrated approach combining image analysis with mathematical modeling allows us to reveal potential transcription factor related cellular and intercellular mechanisms behind the emergence of observed patterns that cannot be derived from images directly. © 2015 International Society for Advancement of Cytometry.

SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering.

PubMed

Van den Eynden, Jimmy; Fierro, Ana Carolina; Verbeke, Lieven P C; Marchal, Kathleen

2015-04-23

With the advances in high throughput technologies, increasing amounts of cancer somatic mutation data are being generated and made available. Only a small number of (driver) mutations occur in driver genes and are responsible for carcinogenesis, while the majority of (passenger) mutations do not influence tumour biology. In this study, SomInaClust is introduced, a method that accurately identifies driver genes based on their mutation pattern across tumour samples and then classifies them into oncogenes or tumour suppressor genes respectively. SomInaClust starts from the observation that oncogenes mainly contain mutations that, due to positive selection, cluster at similar positions in a gene across patient samples, whereas tumour suppressor genes contain a high number of protein-truncating mutations throughout the entire gene length. The method was shown to prioritize driver genes in 9 different solid cancers. Furthermore it was found to be complementary to existing similar-purpose methods with the additional advantages that it has a higher sensitivity, also for rare mutations (occurring in less than 1% of all samples), and it accurately classifies candidate driver genes in putative oncogenes and tumour suppressor genes. Pathway enrichment analysis showed that the identified genes belong to known cancer signalling pathways, and that the distinction between oncogenes and tumour suppressor genes is biologically relevant. SomInaClust was shown to detect candidate driver genes based on somatic mutation patterns of inactivation and clustering and to distinguish oncogenes from tumour suppressor genes. The method could be used for the identification of new cancer genes or to filter mutation data for further data-integration purposes.

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

PubMed

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-05-21

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen's temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

Clustering of Synoptic Pattern over the Korean Peninsula from Meteorological Models

NASA Astrophysics Data System (ADS)

Kim, Jinah; Heo, Kiyoung; Choi, Jungwoon; Jung, Sanghoon

2017-04-01

Numerical modeling data on meteorological and ocean science is one of example of big geographic data sources. The properties of the data including the volume, variety, and dynamic aspects pose new challenges for geographic visualization, and visual geoanalytics using big data analysis using machine learning method. A combination of algorithmic and visual approaches that make sense of large volumes of various types of spatiotemporal data are required to gain knowledge about complex phenomena. In the East coast of Korea, it is suffering from property damages and human causalities due to abnormal high waves (swell-like high-height waves). It is known to be caused by local meteorological conditions on the East Sea of Korean Peninsula in previous research and they proposed three kinds of pressure patterns that generate abnormal high waves. However, they cannot describe all kinds of pressure patterns that generate abnormal high waves. In our study, we propose unsupervised machine learning method for pattern clustering and applied it to classify a pattern which has occurred abnormal high waves using numerical meteorological model's reanalysis data from 2000 to 2015 and past historical records of accidents by abnormal high waves. About 25,000 patterns of total spatial distribution of sea surface pressure are clustered into 30 patterns and they are classified into seasonal sea level pressure patterns based on meteorological characteristics of Korean peninsula. Moreover, in order to determine the representative patterns which occurs abnormal high waves, we classified it again using historical accidents cases among the winter season pressure patterns. In this work, we clustered synoptic pattern over the Korean Peninsula in meteorological modeling reanalysis data and we could understand a seasonal variation through identifying the occurrence of clustered synoptic pattern. For the future work, we have to identify the relationship of wave modeling data for better understanding of abnormal high waves and we will develop pattern decision system to predict abnormal high waves in advances. This research was a part of the project titled "Development of Korea Operational Oceanographic System (KOOS), Phase 2" and "Investigation of Large Swell Waves and Rip currents and Development of The Disaster Response System," funded by the Ministry of Oceans & Fisheries Korea (Grant PM59691 and PM59240).

Patterns of time use among low-income urban minority adolescents and associations with academic outcomes and problem behaviors.

PubMed

Wolf, Sharon; Aber, J Lawrence; Morris, Pamela A

2015-06-01

Time budgets represent key opportunities for developmental support and contribute to an understanding of achievement gaps and adjustment across populations of youth. This study assessed the connection between out-of-school time use patterns and academic performance outcomes, academic motivations and goals, and problem behaviors for 504 low-income urban African American and Latino adolescents (54% female; M = 16.6 years). Time use patterns were measured across eight activity types using cluster analysis. Four groups of adolescents were identified, based on their different profiles of time use: (1) Academic: those with most time in academic activities; (2) Social: those with most time in social activities; (3) Maintenance/work: those with most time in maintenance and work activities; and (4) TV/computer: those with most time in TV or computer activities. Time use patterns were meaningfully associated with variation in outcomes in this population. Adolescents in the Academic cluster had the highest levels of adjustment across all domains; adolescents in the Social cluster had the lowest academic performance and highest problem behaviors; and adolescents in the TV/computer cluster had the lowest levels of intrinsic motivation. Females were more likely to be in the Academic cluster, and less likely to be in the other three clusters compared to males. No differences by race or gender were found in assessing the relationship between time use and outcomes. The study's results indicate that time use patterns are meaningfully associated with within-group variation in adjustment for low-income minority adolescents, and that shared contexts may shape time use more than individual differences in race/ethnicity for this population.

Patterns of long-term care services use in a suburban municipality of Japan: a population-based study.

PubMed

Igarashi, Ayumi; Yamamoto-Mitani, Noriko; Yoshie, Satoru; Iijima, Katsuya

2017-05-01

Increasing service use under the long-term care insurance (LTCI) system in Japan requires a comprehensive understanding of how the services are actually used. This study aimed to identify patterns of LTCI service use and to examine the characteristics of the patterns. We analyzed data from a population of 4,339 older adults living in the community who were certified as "Needing Care" and were using at least one LTCI service in a suburban municipality of Japan. We identified six patterns of service use using cluster analysis based on the amount of fees for LTCI services and compared characteristics among the clusters. The clusters were: 1) light use of care services (n = 1,852); 2) day care-centered (n = 1,071); 3) day care with rehabilitation-centered (n = 616); 4) home help-centered (n = 365); 5) short-stay respite service-centered (n = 246); and 6) compound uses of visiting services (n = 189). "Home help-centered" and "short-stay respite service-centered" clusters used a large number of fees, whereas "compound uses of visiting services" clusters did not despite their severe conditions. The "day care-centered (with rehabilitation)" classification included few people who needed medical procedures, likely due to the lack of medical facilities in those agencies. The results show the impact of social and medical factors on LTCI service use, suggesting possible difficulties in the socialization of care. The clusters could be used as typical service use patterns, providing a framework for further studies, such as those evaluating the services' effects. Geriatr Gerontol Int 2017; 17: 753-759. © 2016 Japan Geriatrics Society.

Patterning in time and space: HoxB cluster gene expression in the developing chick embryo.

PubMed

Gouveia, Analuce; Marcelino, Hugo M; Gonçalves, Lisa; Palmeirim, Isabel; Andrade, Raquel P

2015-01-01

The developing embryo is a paradigmatic model to study molecular mechanisms of time control in Biology. Hox genes are key players in the specification of tissue identity during embryo development and their expression is under strict temporal regulation. However, the molecular mechanisms underlying timely Hox activation in the early embryo remain unknown. This is hindered by the lack of a rigorous temporal framework of sequential Hox expression within a single cluster. Herein, a thorough characterization of HoxB cluster gene expression was performed over time and space in the early chick embryo. Clear temporal collinearity of HoxB cluster gene expression activation was observed. Spatial collinearity of HoxB expression was evidenced in different stages of development and in multiple tissues. Using embryo explant cultures we showed that HoxB2 is cyclically expressed in the rostral presomitic mesoderm with the same periodicity as somite formation, suggesting a link between timely tissue specification and somite formation. We foresee that the molecular framework herein provided will facilitate experimental approaches aimed at identifying the regulatory mechanisms underlying Hox expression in Time and Space.

Patterning in time and space: HoxB cluster gene expression in the developing chick embryo

PubMed Central

Gouveia, Analuce; Marcelino, Hugo M; Gonçalves, Lisa; Palmeirim, Isabel; Andrade, Raquel P

2015-01-01

The developing embryo is a paradigmatic model to study molecular mechanisms of time control in Biology. Hox genes are key players in the specification of tissue identity during embryo development and their expression is under strict temporal regulation. However, the molecular mechanisms underlying timely Hox activation in the early embryo remain unknown. This is hindered by the lack of a rigorous temporal framework of sequential Hox expression within a single cluster. Herein, a thorough characterization of HoxB cluster gene expression was performed over time and space in the early chick embryo. Clear temporal collinearity of HoxB cluster gene expression activation was observed. Spatial collinearity of HoxB expression was evidenced in different stages of development and in multiple tissues. Using embryo explant cultures we showed that HoxB2 is cyclically expressed in the rostral presomitic mesoderm with the same periodicity as somite formation, suggesting a link between timely tissue specification and somite formation. We foresee that the molecular framework herein provided will facilitate experimental approaches aimed at identifying the regulatory mechanisms underlying Hox expression in Time and Space. PMID:25602523

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

Vasylkivska, Veronika S.; Huerta, Nicolas J.

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

Observing RAM Pressure Stripping and Morphological Transformation in the Coma Cluster

NASA Astrophysics Data System (ADS)

Gregg, Michael; West, Michael

2017-07-01

The two largest spirals in the Coma cluster, NGC4911 and NGC4921, are being vigorously ram-pressure stripped by the hot intracluster medium. Our HST ACS and WFC3 images have revealed galactic scale shock fronts, giant "Pillars of Creation", rivulets of dust, and spatially coherent star formation in these grand design spirals. We have now obtained HST WFC3 imaging of five additional large Coma spirals to search for and investigate the effects of ram pressure stripping across the wider cluster environment. The results are equally spectacular as the first two examples. The geometry of the interactions in some cases allows an estimation of the various time scales involved, including gas flows out of the disk leading to creation of the ICM, and the attendant triggered star formation in the galaxy disks. The global star formation patterns yield insights into the spatial and temporal ISM-ICM interactions driving cluster galaxy evolution and ultimately transforming morphologies from spiral to S0. These processes were much more common in the early Universe when the intergalactic and intracluster components were initially created from stripping and destruction of member galaxies.

Stress moderates the relationships between problem-gambling severity and specific psychopathologies.

PubMed

Ronzitti, Silvia; Kraus, Shane W; Hoff, Rani A; Potenza, Marc N

2018-01-01

The purpose of this study was to examine the extent to which stress moderated the relationships between problem-gambling severity and psychopathologies. We analyzed Wave-1 data from 41,869 participants of the National Epidemiologic Survey of Alcohol and Related Conditions (NESARC). Logistic regression showed that as compared to a non-gambling (NG) group, individuals at-risk gambling (ARG) and problem gambling (PPG) demonstrated higher odds of multiple Axis-I and Axis-II disorders in both high- and low-stress groups. Interactions odds ratios were statistically significant for stress moderating the relationships between at-risk gambling (versus non-gambling) and Any Axis-I and Any Axis-II disorder, with substance-use and Cluster-A and Cluster-B disorders contributing significantly. Some similar patterns were observed for pathological gambling (versus non-gambling), with stress moderating relationships with Cluster-B disorders. In all cases, a stronger relationship was observed between problem-gambling severity and psychopathology in the low-stress versus high-stress groups. The findings suggest that perceived stress accounts for some of the variance in the relationship between problem-gambling severity and specific forms of psychopathology, particularly with respect to lower intensity, subsyndromal levels of gambling. Findings suggest that stress may be particularly important to consider in the relationships between problem-gambling severity and substance use and Cluster-B disorders. Published by Elsevier B.V.

Custom-made foot orthoses: an analysis of prescription characteristics from an Australian commercial orthotic laboratory.

PubMed

Menz, Hylton B; Allan, Jamie J; Bonanno, Daniel R; Landorf, Karl B; Murley, George S

2017-01-01

Foot orthoses are widely used in the prevention and treatment of foot disorders. The aim of this study was to describe characteristics of custom-made foot orthosis prescriptions from a Australian podiatric orthotic laboratory. One thousand consecutive foot orthosis prescription forms were obtained from a commercial prescription foot orthosis laboratory located in Melbourne, Victoria, Australia (Footwork Podiatric Laboratory). Each item from the prescription form was documented in relation to orthosis type, cast correction, arch fill technique, cast modifications, shell material, shell modifications and cover material. Cluster analysis and discriminant function analysis were applied to identify patterns in the prescription data. Prescriptions were obtained from 178 clinical practices across Australia and Hong Kong, with patients ranging in age from 5 to 92 years. Three broad categories ('clusters') were observed that were indicative of increasing 'control' of rearfoot pronation. A combination of five variables (rearfoot cast correction, cover shape, orthosis type, forefoot cast correction and plantar fascial accommodation) was able to identify these clusters with an accuracy of 70%. Significant differences between clusters were observed in relation to age and sex of the patient and the geographic location of the prescribing clinician. Foot orthosis prescriptions are complex, but can be broadly classified into three categories. Selection of these prescription subtypes appears to be influenced by both patient factors (age and sex) and clinician factors (clinic location).

Segregation of face sensitive areas within the fusiform gyrus using global signal regression? A study on amygdala resting-state functional connectivity.

PubMed

Kruschwitz, Johann D; Meyer-Lindenberg, Andreas; Veer, Ilya M; Wackerhagen, Carolin; Erk, Susanne; Mohnke, Sebastian; Pöhland, Lydia; Haddad, Leila; Grimm, Oliver; Tost, Heike; Romanczuk-Seiferth, Nina; Heinz, Andreas; Walter, Martin; Walter, Henrik

2015-10-01

The application of global signal regression (GSR) to resting-state functional magnetic resonance imaging data and its usefulness is a widely discussed topic. In this article, we report an observation of segregated distribution of amygdala resting-state functional connectivity (rs-FC) within the fusiform gyrus (FFG) as an effect of GSR in a multi-center-sample of 276 healthy subjects. Specifically, we observed that amygdala rs-FC was distributed within the FFG as distinct anterior versus posterior clusters delineated by positive versus negative rs-FC polarity when GSR was performed. To characterize this effect in more detail, post hoc analyses revealed the following: first, direct overlays of task-functional magnetic resonance imaging derived face sensitive areas and clusters of positive versus negative amygdala rs-FC showed that the positive amygdala rs-FC cluster corresponded best with the fusiform face area, whereas the occipital face area corresponded to the negative amygdala rs-FC cluster. Second, as expected from a hierarchical face perception model, these amygdala rs-FC defined clusters showed differential rs-FC with other regions of the visual stream. Third, dynamic connectivity analyses revealed that these amygdala rs-FC defined clusters also differed in their rs-FC variance across time to the amygdala. Furthermore, subsample analyses of three independent research sites confirmed reliability of the effect of GSR, as revealed by similar patterns of distinct amygdala rs-FC polarity within the FFG. In this article, we discuss the potential of GSR to segregate face sensitive areas within the FFG and furthermore discuss how our results may relate to the functional organization of the face-perception circuit. © 2015 Wiley Periodicals, Inc.

Spatial and temporal statistical analysis of bycatch data: Patterns of sea turtle bycatch in the North Atlantic

USGS Publications Warehouse

Gardner, B.; Sullivan, P.J.; Morreale, S.J.; Epperly, S.P.

2008-01-01

Loggerhead (Caretta caretta) and leatherback (Dermochelys coriacea) sea turtle distributions and movements in offshore waters of the western North Atlantic are not well understood despite continued efforts to monitor, survey, and observe them. Loggerhead and leatherback sea turtles are listed as endangered by the World Conservation Union, and thus anthropogenic mortality of these species, including fishing, is of elevated interest. This study quantifies spatial and temporal patterns of sea turtle bycatch distributions to identify potential processes influencing their locations. A Ripley's K function analysis was employed on the NOAA Fisheries Atlantic Pelagic Longline Observer Program data to determine spatial, temporal, and spatio-temporal patterns of sea turtle bycatch distributions within the pattern of the pelagic fishery distribution. Results indicate that loggerhead and leatherback sea turtle catch distributions change seasonally, with patterns of spatial clustering appearing from July through October. The results from the space-time analysis indicate that sea turtle catch distributions are related on a relatively fine scale (30-200 km and 1-5 days). The use of spatial and temporal point pattern analysis, particularly K function analysis, is a novel way to examine bycatch data and can be used to inform fishing practices such that fishing could still occur while minimizing sea turtle bycatch. ?? 2008 NRC.

Assessing Genetic Structure in Common but Ecologically Distinct Carnivores: The Stone Marten and Red Fox.

PubMed

Basto, Mafalda P; Santos-Reis, Margarida; Simões, Luciana; Grilo, Clara; Cardoso, Luís; Cortes, Helder; Bruford, Michael W; Fernandes, Carlos

2016-01-01

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation.

Evidence of a Partitioned Dynamo Reversal Process from Paleomagnetic Recordings in Tahitian Lavas

NASA Astrophysics Data System (ADS)

Hoffman, K. A.; Mochizuki, N.

2012-12-01

Lavas erupted at the Society hotspot during the Matuyama-Brunhes (M-B) reversal record transitional field behavior containing two tight, subhorizontal paleodirectional groups that when averaged are antipodal at the 95% confidence level, and thus correlate to antipodal clustered virtual geomagnetic poles (VGPs). These observations--data obtained from two published records of the M-B transition from distinct sections of a succession of flows on Tahiti--are associated with a time when the strength of the axial dipole was significantly reduced. One cluster was recorded by lavas that were not erupted in succession, involving a directional rebound, suggesting that significant time had passed during this volcanic activity. Time spent during the formation of the antipodal cluster is unknown, yet it resides in the same location as VGP clusters from four other transitional events obtained from Society hotspot lavas. Calculated VGPs at the Society hotspot for both "polarities" of the 400-year averaged historic field--less the axial dipole term--are found in the cluster locations. These findings offer strong support for a two-tiered dynamo process in which nearly the entire axial dipole component undergoes both demise and regeneration quasi-independently from that of the remainder of the field--the proposed Shallow Core Generated (SCOR) field--the pattern of which being tied to long-held physical conditions of the lower-most mantle. Apart from polarity reversal, such fixed magnetic features along the core-mantle boundary would also significantly influence the long-term pattern of global paleosecular variation and likely impose strict site-dependent limits on the utility of the geocentric axial dipole (GAD) hypothesis.Clustered Matuyama-Brunhes transitional VGPs reported from the Punaruu Valley (in red), along with the VGP associated with each sign ("polarity") of the 400-year mean historic NAD-field (in yellow) calculated from model gulm1 for the site of the Society hotspot.

Assessing Genetic Structure in Common but Ecologically Distinct Carnivores: The Stone Marten and Red Fox

PubMed Central

Basto, Mafalda P.; Santos-Reis, Margarida; Simões, Luciana; Grilo, Clara; Cardoso, Luís; Cortes, Helder; Bruford, Michael W.; Fernandes, Carlos

2016-01-01

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation. PMID:26727497

The relationship between a low grain intake dietary pattern and impulsive behaviors in middle-aged Japanese people.

PubMed

Toyomaki, Atsuhito; Koga, Minori; Okada, Emiko; Nakai, Yukiei; Miyazaki, Akane; Tamakoshi, Akiko; Kiso, Yoshinobu; Kusumi, Ichiro

2017-01-01

Several studies indicate that dietary habits are associated with mental health. We are interested in identifying not a specific single nutrient/food group but the population preferring specific food combinations that can be related to mental health. Very few studies have examined relationships between dietary patterns and multifaceted mental states using cluster analysis. The purpose of this study was to investigate population-level dietary patterns associated with mental state using cluster analysis. We focused on depressive state, sleep quality, subjective well-being, and impulsive behaviors using rating scales. Two hundred and seventy-nine Japanese middle-aged people participated in the present study. Dietary pattern was estimated using a brief self-administered diet-history questionnaire (the BDHQ). We conducted K-means cluster analysis using thirteen BDHQ food groups: milk, meat, fish, egg, pulses, potatoes, green and yellow vegetables, other vegetables, mushrooms, seaweed, sweets, fruits, and grain. We identified three clusters characterized as "vegetable and fruit dominant," "grain dominant," and "low grain tendency" subgroups. The vegetable and fruit dominant group showed increases in several aspects of subjective well-being demonstrated by the SF-8. Differences in mean subject characteristics across clusters were tested using ANOVA. The low frequency intake of grain group showed higher impulsive behavior, demonstrated by BIS-11 deliberation and sum scores. The present study demonstrated that traditional Japanese dietary patterns, such as eating rice, can help with beneficial changes in mental health.

The relationship between a low grain intake dietary pattern and impulsive behaviors in middle-aged Japanese people

PubMed Central

Toyomaki, Atsuhito; Koga, Minori; Okada, Emiko; Nakai, Yukiei; Miyazaki, Akane; Tamakoshi, Akiko; Kiso, Yoshinobu; Kusumi, Ichiro

2017-01-01

Several studies indicate that dietary habits are associated with mental health. We are interested in identifying not a specific single nutrient/food group but the population preferring specific food combinations that can be related to mental health. Very few studies have examined relationships between dietary patterns and multifaceted mental states using cluster analysis. The purpose of this study was to investigate population-level dietary patterns associated with mental state using cluster analysis. We focused on depressive state, sleep quality, subjective well-being, and impulsive behaviors using rating scales. Two hundred and seventy-nine Japanese middle-aged people participated in the present study. Dietary pattern was estimated using a brief self-administered diet-history questionnaire (the BDHQ). We conducted K-means cluster analysis using thirteen BDHQ food groups: milk, meat, fish, egg, pulses, potatoes, green and yellow vegetables, other vegetables, mushrooms, seaweed, sweets, fruits, and grain. We identified three clusters characterized as “vegetable and fruit dominant,” “grain dominant,” and “low grain tendency” subgroups. The vegetable and fruit dominant group showed increases in several aspects of subjective well-being demonstrated by the SF-8. Differences in mean subject characteristics across clusters were tested using ANOVA. The low frequency intake of grain group showed higher impulsive behavior, demonstrated by BIS-11 deliberation and sum scores. The present study demonstrated that traditional Japanese dietary patterns, such as eating rice, can help with beneficial changes in mental health. PMID:28704469

Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

PubMed Central

Goovaerts, Pierre; Jacquez, Geoffrey M

2004-01-01

Background Complete Spatial Randomness (CSR) is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new methodology allows one to identify geographic pattern above and beyond background variation. The implementation of this approach in spatial statistical software will facilitate the detection of spatial disparities in mortality rates, establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. It will allow researchers to systematically evaluate how sensitive their results are to assumptions implicit under alternative null hypotheses. PMID:15272930

Distinct subtypes of behavioral-variant frontotemporal dementia based on patterns of network degeneration

PubMed Central

Ranasinghe, Kamalini G; Rankin, Katherine P; Pressman, Peter S; Perry, David C; Lobach, Iryna V; Seeley, William W; Coppola, Giovanni; Karydas, Anna M; Grinberg, Lea T; Shany-Ur, Tal; Lee, Suzee E; Rabinovici, Gil D; Rosen, Howard J; Gorno-Tempini, Maria Luisa; Boxer, Adam L; Miller, Zachary A; Chiong, Winston; DeMay, Mary; Kramer, Joel H; Possin, Katherine L; Sturm, Virginia E; Bettcher, Brianne M; Neylan, Michael; Zackey, Diana D; Nguyen, Lauren A; Ketelle, Robin; Block, Nikolas; Wu, Teresa Q; Dallich, Alison; Russek, Natanya; Caplan, Alyssa; Geschwind, Daniel H; Vossel, Keith A; Miller, Bruce L

2016-01-01

Importance Clearer delineation of the phenotypic heterogeneity within behavioral variant frontotemporal dementia (bvFTD) will help uncover underlying biological mechanisms, and will improve clinicians’ ability to predict disease course and design targeted management strategies. Objective To identify subtypes of bvFTD syndrome based on distinctive patterns of atrophy defined by selective vulnerability of specific functional networks targeted in bvFTD, using statistical classification approaches. Design, Setting and Participants In this retrospective observational study, 104 patients meeting the Frontotemporal Dementia Consortium consensus criteria for bvFTD were evaluated at the Memory and Aging Center of Department of Neurology at University of California, San Francisco. Patients underwent a multidisciplinary clinical evaluation, including clinical demographics, genetic testing, symptom evaluation, neurological exam, neuropsychological bedside testing, and socioemotional assessments. Ninety patients underwent structural Magnetic Resonance Imaging at their earliest evaluation at the memory clinic. From each patients’ structural imaging, the mean volumes of 18 regions of interest (ROI) comprising the functional networks specifically vulnerable in bvFTD, including the ‘salience network’ (SN), with key nodes in the frontoinsula and pregenual anterior cingulate, and the ‘semantic appraisal network’ (SAN) anchored in the anterior temporal lobe and subgenual cingulate, were estimated. Principal component and cluster analyses of ROI volumes were used to identify patient clusters with anatomically distinct atrophy patterns. Main Outcome Measures We evaluated brain morphology and other clinical features including presenting symptoms, neurologic exam signs, neuropsychological performance, rate of dementia progression, and socioemotional function in each patient cluster. Results We identified four subgroups of bvFTD patients with distinct anatomic patterns of network degeneration, including two separate salience network–predominant subgroups: frontal/temporal (SN-FT), and frontal (SN-F), and a semantic appraisal network–predominant group (SAN), and a subcortical–predominant group. Subgroups demonstrated distinct patterns of cognitive, socioemotional, and motor symptoms, as well as genetic compositions and estimated rates of disease progression. Conclusions Divergent patterns of vulnerability in specific functional network components make an important contribution to clinical heterogeneity of bvFTD. The data-driven anatomical classification identifies biologically meaningful phenotypes and provides a replicable approach to disambiguate the bvFTD syndrome. PMID:27429218

Patterns of houses and habitat loss from 1937 to 1999 in northern Wisconsin, USA.

PubMed

Gonzalez-Abraham, Charlotte E; Radeloff, Volker C; Hawbaker, Todd J; Hammer, Roger B; Stewart, Susan I; Clayton, Murray K

2007-10-01

Rural America is witnessing widespread housing development, which is to the detriment of the environment. It has been suggested to cluster houses so that their disturbance zones overlap and thus cause less habitat loss than is the case for dispersed development. Clustering houses makes intuitive sense, but few empirical studies have quantified the spatial pattern of houses in real landscapes, assessed changes in their patterns over time, and quantified the resulting habitat loss. We addressed three basic questions: (1) What are the spatial patterns of houses and how do they change over time; (2) How much habitat is lost due to houses, and how is this affected by spatial pattern of houses; and (3) What type of habitat is most affected by housing development. We mapped 27 419 houses from aerial photos for five time periods in 17 townships in northern Wisconsin and calculated the terrestrial land area remaining after buffering each house using 100- and 500-m disturbance zones. The number of houses increased by 353% between 1937 and 1999. Ripley's K test showed that houses were significantly clustered at all time periods and at all scales. Due to the clustering, the rate at which habitat was lost (176% and 55% for 100- and 500-m buffers, respectively) was substantially lower than housing growth rates, and most land area was undisturbed (95% and 61% for 100-m and 500-m buffers, respectively). Houses were strongly clustered within 100 m of lakes. Habitat loss was lowest in wetlands but reached up to 60% in deciduous forests. Our results are encouraging in that clustered development is common in northern Wisconsin, and habitat loss is thus limited. However, the concentration of development along lakeshores causes concern, because these may be critical habitats for many species. Conservation goals can only be met if policies promote clustered development and simultaneously steer development away from sensitive ecosystems.

Time-resolved x-ray imaging of a laser-induced nanoplasma and its neutral residuals

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

Fluckiger, L.; Rupp, D.; Adolph, M.

The evolution of individual, large gas-phase xenon clusters, turned into a nanoplasma by a high power infrared laser pulse, is tracked from femtoseconds up to nanoseconds after laser excitation via coherent diffractive imaging, using ultra-short soft x-ray free electron laser pulses. A decline of scattering signal at high detection angles with increasing time delay indicates a softening of the cluster surface. Here we demonstrate, for the first time a representative speckle pattern of a new stage of cluster expansion for xenon clusters after a nanosecond irradiation. The analysis of the measured average speckle size and the envelope of the intensitymore » distribution reveals a mean cluster size and length scale of internal density fluctuations. Furthermore, the measured diffraction patterns were reproduced by scattering simulations which assumed that the cluster expands with pronounced internal density fluctuations hundreds of picoseconds after excitation.« less

Time-resolved x-ray imaging of a laser-induced nanoplasma and its neutral residuals

DOE PAGES

Fluckiger, L.; Rupp, D.; Adolph, M.; ...

2016-04-13

The evolution of individual, large gas-phase xenon clusters, turned into a nanoplasma by a high power infrared laser pulse, is tracked from femtoseconds up to nanoseconds after laser excitation via coherent diffractive imaging, using ultra-short soft x-ray free electron laser pulses. A decline of scattering signal at high detection angles with increasing time delay indicates a softening of the cluster surface. Here we demonstrate, for the first time a representative speckle pattern of a new stage of cluster expansion for xenon clusters after a nanosecond irradiation. The analysis of the measured average speckle size and the envelope of the intensitymore » distribution reveals a mean cluster size and length scale of internal density fluctuations. Furthermore, the measured diffraction patterns were reproduced by scattering simulations which assumed that the cluster expands with pronounced internal density fluctuations hundreds of picoseconds after excitation.« less

Functional clustering of time series gene expression data by Granger causality

PubMed Central

2012-01-01

Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

Auroral E-region Plasma Irregularities and their Control by the Plasma Convection in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Forsythe, V. V.; Makarevich, R. A.

2016-12-01

Small-scale ionospheric plasma irregularities in the high-latitude E region and their control by F-region plasma convection are investigated using Super Dual Auroral Network (SuperDARN) observations at high southern latitudes over a 1-year period. Significant asymmetries are found in the velocity occurrence distribution due to the clustering of the high-velocity echoes of a particular velocity polarity. Statistical analysis of convection showed that some radars observe predominantly negative bias in the convection component within their short, E-region ranges, while others have a predominantly positive bias. A hypothesis that this bias is caused by asymmetric sectoring of the high-latitude plasma convection pattern is investigated. A new algorithm is developed that samples the plasma convection map and evaluates the convection pattern asymmetry along the particular latitude that corresponds to the radar location. It is demonstrated that the convection asymmetry has a particular seasonal and diurnal pattern, which is different for the polar and auroral radars. Possible causes for the observed convection pattern asymmetry are discussed. It is further proposed that the statistical occurrence of high-velocity E-region echoes generated by the Farley-Buneman instability (FBI) is highly sensitive to small changes in the convection pattern, which is consistent with the electric field threshold for the FBI onset being perhaps sharper and lower than previously thought.

[Spatial analysis of mortality from cardiovascular diseases in Madrid City, Spain].

PubMed

Gómez-Barroso, Diana; Prieto-Flores, María-Eugenia; Mellado San Gabino, Ana; Moreno Jiménez, Antonio

2015-01-01

Cardiovascular disease is the leading cause of death worldwide, but its spatial distribution is not homogeneous. The objective of this study is to analyze the spatial pattern of mortality from these diseases for men and women, in the populated urban area (AUP) of the municipality of Madrid, and to identify spatial aggregations. An ecological study was carried out by census tract, for men and women in 2010. Standardized Mortality Ratio (SMR), Relative Risk Smoothing (RRS) and Posterior Probability (PP) were calculated to consider the spatial pattern of the disease. To identify spatial clusters the Moran index (Moran I) and the Local Index of Spatial Autocorrelation (LISA) were used. The results were mapped. SMR higher than 1.1 was observed mainly in central areas among men and in peripheral areas among women. The PP that RRS was higher than 1 surpassed 0.8 in the center and in the periphery, in both men and women. Moran's I was 0.04 for men and 0.03 for women (p <0.05 in both cases). Sex differences were observed in the spatial distribution of mortality cases. RME RRS and PP maps showed a heterogeneous pattern in men, whereas in women a clearer pattern was detected, with a relatively higher risk in peripheral areas of the AUP. The LISA method showed similar patterns to those previously observed.

Cluster analysis of particulate matter (PM10) and black carbon (BC) concentrations

NASA Astrophysics Data System (ADS)

Žibert, Janez; Pražnikar, Jure

2012-09-01

The monitoring of air-pollution constituents like particulate matter (PM10) and black carbon (BC) can provide information about air quality and the dynamics of emissions. Air quality depends on natural and anthropogenic sources of emissions as well as the weather conditions. For a one-year period the diurnal concentrations of PM10 and BC in the Port of Koper were analysed by clustering days into similar groups according to the similarity of the BC and PM10 hourly derived day-profiles without any prior assumptions about working and non-working days, weather conditions or hot and cold seasons. The analysis was performed by using k-means clustering with the squared Euclidean distance as the similarity measure. The analysis showed that 10 clusters in the BC case produced 3 clusters with just one member day and 7 clusters that encompasses more than one day with similar BC profiles. Similar results were found in the PM10 case, where one cluster has a single-member day, while 7 clusters contain several member days. The clustering analysis revealed that the clusters with less pronounced bimodal patterns and low hourly and average daily concentrations for both types of measurements include the most days in the one-year analysis. A typical day profile of the BC measurements includes a bimodal pattern with morning and evening peaks, while the PM10 measurements reveal a less pronounced bimodality. There are also clusters with single-peak day-profiles. The BC data in such cases exhibit morning peaks, while the PM10 data consist of noon or afternoon single peaks. Single pronounced peaks can be explained by appropriate cluster wind speed profiles. The analysis also revealed some special day-profiles. The BC cluster with a high midnight peak at 30/04/2010 and the PM10 cluster with the highest observed concentration of PM10 at 01/05/2010 (208.0 μg m-3) coincide with 1 May, which is a national holiday in Slovenia and has very strong tradition of bonfire parties. The clustering of the diurnal concentration showed that various different day-profiles are presented in a cold period, while this is not the case for the hot season. Additional analysis of ship traffic and rain fall data showed that there is no statistically significant difference between the ship gross (bruto) registered tonnage (BRT) values in the case of BC and PM10 clusters, but that there is statistically significant differences between the rain fall in the BC and PM10 clusters. The wind-rose for clusters which included most days in the sampling period indicating that emitted PM10 and BC from Port of Koper were manly transported in the west direction over the sea and in the east direction, where there is in no populated area. Presented analysis showed that both BC and PM10 concentrations were driven by rain intensity and wind speed.

Hierarchical cluster analysis of progression patterns in open-angle glaucoma patients with medical treatment.

PubMed

Bae, Hyoung Won; Rho, Seungsoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

2014-04-29

To classify medically treated open-angle glaucoma (OAG) by the pattern of progression using hierarchical cluster analysis, and to determine OAG progression characteristics by comparing clusters. Ninety-five eyes of 95 OAG patients who received medical treatment, and who had undergone visual field (VF) testing at least once per year for 5 or more years. OAG was classified into subgroups using hierarchical cluster analysis based on the following five variables: baseline mean deviation (MD), baseline visual field index (VFI), MD slope, VFI slope, and Glaucoma Progression Analysis (GPA) printout. After that, other parameters were compared between clusters. Two clusters were made after a hierarchical cluster analysis. Cluster 1 showed -4.06 ± 2.43 dB baseline MD, 92.58% ± 6.27% baseline VFI, -0.28 ± 0.38 dB per year MD slope, -0.52% ± 0.81% per year VFI slope, and all "no progression" cases in GPA printout, whereas cluster 2 showed -8.68 ± 3.81 baseline MD, 77.54 ± 12.98 baseline VFI, -0.72 ± 0.55 MD slope, -2.22 ± 1.89 VFI slope, and seven "possible" and four "likely" progression cases in GPA printout. There were no significant differences in age, sex, mean IOP, central corneal thickness, and axial length between clusters. However, cluster 2 included more high-tension glaucoma patients and used a greater number of antiglaucoma eye drops significantly compared with cluster 1. Hierarchical cluster analysis of progression patterns divided OAG into slow and fast progression groups, evidenced by assessing the parameters of glaucomatous progression in VF testing. In the fast progression group, the prevalence of high-tension glaucoma was greater and the number of antiglaucoma medications administered was increased versus the slow progression group. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

MOCCA-SURVEY Database I: Is NGC 6535 a dark star cluster harbouring an IMBH?

NASA Astrophysics Data System (ADS)

Askar, Abbas; Bianchini, Paolo; de Vita, Ruggero; Giersz, Mirek; Hypki, Arkadiusz; Kamann, Sebastian

2017-01-01

We describe the dynamical evolution of a unique type of dark star cluster model in which the majority of the cluster mass at Hubble time is dominated by an intermediate-mass black hole (IMBH). We analysed results from about 2000 star cluster models (Survey Database I) simulated using the Monte Carlo code MOnte Carlo Cluster simulAtor and identified these dark star cluster models. Taking one of these models, we apply the method of simulating realistic `mock observations' by utilizing the Cluster simulatiOn Comparison with ObservAtions (COCOA) and Simulating Stellar Cluster Observation (SISCO) codes to obtain the photometric and kinematic observational properties of the dark star cluster model at 12 Gyr. We find that the perplexing Galactic globular cluster NGC 6535 closely matches the observational photometric and kinematic properties of the dark star cluster model presented in this paper. Based on our analysis and currently observed properties of NGC 6535, we suggest that this globular cluster could potentially harbour an IMBH. If it exists, the presence of this IMBH can be detected robustly with proposed kinematic observations of NGC 6535.

Two-Dimensional Animal-Like Fractals in Thin Films

NASA Astrophysics Data System (ADS)

Gao, Hong-jun; Xue, Zeng-quan; Wu, Quan-de; Pang, Shi-jin

1996-02-01

We present a few unique animal-like fractal patterns in ionized-cluster-beam deposited fullerene-tetracyanoquinodimethane thin films. The fractal patterns consisting of animal-like aggregates such as "fishes" and "quasi-seahorses" have been characterized by transmission electron microscopy. The results indicate that the small aggregates of the animal-like body are composed of many single crystals whose crystalline directions are generally different. The formation of the fractal patterns can be attributed to the cluster-diffusion-limited aggregation.

Clustering Of Left Ventricular Wall Motion Patterns

NASA Astrophysics Data System (ADS)

Bjelogrlic, Z.; Jakopin, J.; Gyergyek, L.

1982-11-01

A method for detection of wall regions with similar motion was presented. A model based on local direction information was used to measure the left ventricular wall motion from cineangiographic sequence. Three time functions were used to define segmental motion patterns: distance of a ventricular contour segment from the mean contour, the velocity of a segment and its acceleration. Motion patterns were clustered by the UPGMA algorithm and by an algorithm based on K-nearest neighboor classification rule.

An investigation on thermal patterns in Iran based on spatial autocorrelation

NASA Astrophysics Data System (ADS)

Fallah Ghalhari, Gholamabbas; Dadashi Roudbari, Abbasali

2018-02-01

The present study aimed at investigating temporal-spatial patterns and monthly patterns of temperature in Iran using new spatial statistical methods such as cluster and outlier analysis, and hotspot analysis. To do so, climatic parameters, monthly average temperature of 122 synoptic stations, were assessed. Statistical analysis showed that January with 120.75% had the most fluctuation among the studied months. Global Moran's Index revealed that yearly changes of temperature in Iran followed a strong spatially clustered pattern. Findings showed that the biggest thermal cluster pattern in Iran, 0.975388, occurred in May. Cluster and outlier analyses showed that thermal homogeneity in Iran decreases in cold months, while it increases in warm months. This is due to the radiation angle and synoptic systems which strongly influence thermal order in Iran. The elevations, however, have the most notable part proved by Geographically weighted regression model. Iran's thermal analysis through hotspot showed that hot thermal patterns (very hot, hot, and semi-hot) were dominant in the South, covering an area of 33.5% (about 552,145.3 km2). Regions such as mountain foot and low lands lack any significant spatial autocorrelation, 25.2% covering about 415,345.1 km2. The last is the cold thermal area (very cold, cold, and semi-cold) with about 25.2% covering about 552,145.3 km2 of the whole area of Iran.

Self-organization and positioning of bacterial protein clusters

NASA Astrophysics Data System (ADS)

Murray, Seán M.; Sourjik, Victor

2017-10-01

Many cellular processes require proteins to be precisely positioned within the cell. In some cases this can be attributed to passive mechanisms such as recruitment by other proteins in the cell or by exploiting the curvature of the membrane. However, in bacteria, active self-positioning is likely to play a role in multiple processes, including the positioning of the future site of cell division and cytoplasmic protein clusters. How can such dynamic clusters be formed and positioned? Here, we present a model for the self-organization and positioning of dynamic protein clusters into regularly repeating patterns based on a phase-locked Turing pattern. A single peak in the concentration is always positioned at the midpoint of the model cell, and two peaks are positioned at the midpoint of each half. Furthermore, domain growth results in peak splitting and pattern doubling. We argue that the model may explain the regular positioning of the highly conserved structural maintenance of chromosomes complexes on the bacterial nucleoid and that it provides an attractive mechanism for the self-positioning of dynamic protein clusters in other systems.

The observation of negative permittivity in stripe and bubble phases

NASA Astrophysics Data System (ADS)

Smet, Jurgen

The physics of itinerant two-dimensional electrons is by and large governed by repulsive Coulomb forces. However, cases exist where the interplay of attractive and repulsive interaction components may instigate spontaneous symmetry lowering and clustering of charges in geometric patterns such as bubbles and stripes, provided these interactions act on different length scales. The existence of these phases in higher Landau levels has so far been concluded from transport behavior. Here, we report surface acoustic wave experiments. They probe the permittivity at small wave vector. This technique offers true directionality, whereas in transport the current distribution is complex and strongly affected by the inhomogeneous density pattern. Outside the charge density wave regime, the measured permittivity is always positive. However, negative permittivity is observed in the bubble phase irrespective of the propagation direction. For the stripe phase the permittivity takes on both positive as well as negative values depending on the propagation direction. This confirms the stripe phase to be a strongly anisotropic medium. The observation of negative permittivity is considered an immediate consequence of the exchange related attractive interaction. It makes charge clustering favorable in higher Landau levels where the repulsive direct Coulomb interaction acts on a longer length scale and is responsible for a negative compressibility of the electronic system. This work has been carried out with B. Friess, K. von Klitzing (MPI-FKF), Y. Peng, F. von Oppen (FU Berlin), B. Rosenow (Uni Leipzig) and V. Umansky (Weizmann Institute of Science).

Interactive visual exploration and analysis of origin-destination data

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

The Snapshot Hubble U-band Cluster Survey (SHUCS). I. Survey Description and First Application to the Mixed Star Cluster Population of NGC 4041

NASA Astrophysics Data System (ADS)

Konstantopoulos, I. S.; Smith, L. J.; Adamo, A.; Silva-Villa, E.; Gallagher, J. S.; Bastian, N.; Ryon, J. E.; Westmoquette, M. S.; Zackrisson, E.; Larsen, S. S.; Weisz, D. R.; Charlton, J. C.

2013-05-01

We present the Snapshot Hubble U-band Cluster Survey (SHUCS), a project aimed at characterizing the star cluster populations of 10 nearby galaxies (d < 23 Mpc, half within ≈12 Mpc) through new F336W (U-band equivalent) imaging from Wide Field Camera 3, and archival BVI-equivalent data with the Hubble Space Telescope. Completing the UBVI baseline reduces the age-extinction degeneracy of optical colors, thus enabling the measurement of reliable ages and masses for the thousands of clusters covered by our survey. The sample consists chiefly of face-on spiral galaxies at low inclination, in various degrees of isolation (isolated, in group, merging), and includes two active galactic nucleus hosts. This first paper outlines the survey itself, the observational datasets, the analysis methods, and presents a proof-of-concept study of the large-scale properties and star cluster population of NGC 4041, a massive SAbc galaxy at a distance of ≈23 Mpc, and part of a small grouping of six giant members. We resolve two structural components with distinct stellar populations, a morphology more akin to merging and interacting systems. We also find strong evidence of a truncated, Schechter-type mass function, and a similarly segmented luminosity function. These results indicate that binning must erase much of the substructure present in the mass and luminosity functions, and might account for the conflicting reports on the intrinsic shape of these functions in the literature. We also note a tidal feature in the outskirts of the galaxy in Galaxy Evolution Explorer UV imaging, and follow it up with a comprehensive multi-wavelength study of NGC 4041 and its parent group. We deduce a minor merger as a likely cause of its segmented structure and the observed pattern of a radially decreasing star formation rate. We propose that combining the study of star cluster populations with broadband metrics is not only advantageous, but often easily achievable thorough archival datasets. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with program SNAP 12229.

Dietary Patterns Derived by Cluster Analysis are Associated with Cognitive Function among Korean Older Adults

PubMed Central

Kim, Jihye; Yu, Areum; Choi, Bo Youl; Nam, Jung Hyun; Kim, Mi Kyung; Oh, Dong Hoon; Yang, Yoon Jung

2015-01-01

The objective of this study was to investigate major dietary patterns among older Korean adults through cluster analysis and to determine an association between dietary patterns and cognitive function. This is a cross-sectional study. The data from the Korean Multi-Rural Communities Cohort Study was used. Participants included 765 participants aged 60 years and over. A quantitative food frequency questionnaire with 106 items was used to investigate dietary intake. The Korean version of the MMSE-KC (Mini-Mental Status Examination–Korean version) was used to assess cognitive function. Two major dietary patterns were identified using K-means cluster analysis. The “MFDF” dietary pattern indicated high consumption of Multigrain rice, Fish, Dairy products, Fruits and fruit juices, while the “WNC” dietary pattern referred to higher intakes of White rice, Noodles, and Coffee. Means of the total MMSE-KC and orientation score of the participants in the MFDF dietary pattern were higher than those of the WNC dietary pattern. Compared with the WNC dietary pattern, the MFDF dietary pattern showed a lower risk of cognitive impairment after adjusting for covariates (OR 0.64, 95% CI 0.44–0.94). The MFDF dietary pattern, with high consumption of multigrain rice, fish, dairy products, and fruits may be related to better cognition among Korean older adults. PMID:26035243

GEsture: an online hand-drawing tool for gene expression pattern search.

PubMed

Wang, Chunyan; Xu, Yiqing; Wang, Xuelin; Zhang, Li; Wei, Suyun; Ye, Qiaolin; Zhu, Youxiang; Yin, Hengfu; Nainwal, Manoj; Tanon-Reyes, Luis; Cheng, Feng; Yin, Tongming; Ye, Ning

2018-01-01

Gene expression profiling data provide useful information for the investigation of biological function and process. However, identifying a specific expression pattern from extensive time series gene expression data is not an easy task. Clustering, a popular method, is often used to classify similar expression genes, however, genes with a 'desirable' or 'user-defined' pattern cannot be efficiently detected by clustering methods. To address these limitations, we developed an online tool called GEsture. Users can draw, or graph a curve using a mouse instead of inputting abstract parameters of clustering methods. GEsture explores genes showing similar, opposite and time-delay expression patterns with a gene expression curve as input from time series datasets. We presented three examples that illustrate the capacity of GEsture in gene hunting while following users' requirements. GEsture also provides visualization tools (such as expression pattern figure, heat map and correlation network) to display the searching results. The result outputs may provide useful information for researchers to understand the targets, function and biological processes of the involved genes.

Spatial patterns and secular trends in human leishmaniasis incidence in Morocco between 2003 and 2013.

PubMed

Sadeq, Mina

2016-05-11

Few studies on spatial patterns or secular trends in human leishmanias have been conducted in Morocco. This study aimed to examine spatial patterns and trends associated with the human leishmaniasis incidence rate (HLIR) at the province/prefecture level between 2003 and 2013 in Morocco. Only the available published country data on the HLIR between 2003 and 2013, from the open access files of the Ministry of Health, were used. Secular trends were examined using Kendall's rank correlation. An exploratory spatial data analysis was also conducted to examine the spatial autocorrelation (Global Moran's I and local indicator of spatial association [LISA]), and spatial diffusion at the province/prefecture level. The influence of various covariates (poverty rate, vulnerability rate, population density, and urbanization) on the HLIR was tested via spatial regression (ordinary least squares regression). At the country level, no secular variation was observed. Poisson annual incidence rate estimates were 13 per 100 000 population (95 % CI = 12.9-13.1) for cutaneous leishmaniasis (CL) and 0.4 per 100 000 population (95 % CI = 0.4-0.5) for visceral leishmaniasis (VL). The available data on HLIR were based on combined CL and VL cases, however, as the CL cases totally outnumbered the VL ones, HLIR may be considered as CL incidence rate. At the provincial level, a secular increase in the incidence rate was observed in Al Hoceima (P = 0.008), Taounate (P = 0.04), Larache (P = 0.002), Tétouan (P = 0.0003), Khenifra (P = 0.008), Meknes (P = 0.03), and El Kelaa (P = 0.0007), whereas a secular decrease was observed only in the Chichaoua province (P = 0.006). Even though increased or decreased rate was evident in these provinces, none of them showed clustering of leishmaniasis incidence. Significant spatial clusters of high leishmaniasis incidence were located in the northeastern part of Morocco, while spatial clusters of low leishmaniasis incidence were seen in some northwestern and southern parts of Morocco; there was spatial randomness in the remaining parts of the country. Significant clustering was seen from 2005 to 2013, during which time the Errachidia province was a permanent 'hot spot'. Global Moran's I increased from 0.2844 (P = 0.006) in 2005 to 0.5886 (P = 0.001) in 2011, and decreased to 0.2491 (P = 0.004) in 2013. It was found that only poverty had an effect on the HLIR (P = 0.0003), contributing only 23 % to this (Adjusted R-squared = 0.226). Localities showing either secular increase in human leishmaniasis or significant clustering have been identified, which may guide decision-making as to where to appropriately allocate funding and implement control measures. Researchers are also urged to undertake further studies focusing on these localities.

Double cusp encounter by Cluster: double cusp or motion of the cusp?

NASA Astrophysics Data System (ADS)

Escoubet, C. P.; Berchem, J.; Trattner, K. J.; Pitout, F.; Richard, R. L.; Taylor, M. G.; Soucek, J.; Grison, B.; Laakso, H. E.; Masson, A.; Dunlop, M. W.; Dandouras, I. S.; Reme, H.; Fazakerley, A. N.; Daly, P. W.

2012-12-01

Modeling plasma entry in the polar cusp has been successful in reproducing ion dispersions observed in the cusp at low and mid-altitudes. The use of a realistic convection pattern allowed Wing et al. [2001] to model double cusp signatures that were observed by the DMSP spacecraft when the Interplanetary Magnetic Field (IMF) is southward but has a dominant By component (|IMF-By|>|IMF-Bz|). Under these conditions, reconnection between the IMF and the geomagnetic field is predicted to occur both at high latitudes and around the equatorial plane (or subsolar region). This multiple reconnection topology subsequently produces two different injections of plasma into the cusp, hence the observation of the so-called double cusp. However, the two cusps can be very close to each other and a detailed analysis of the dispersion of the precipitating ions is very often required to clearly identify them. We will present a cusp crossing where two cusps are observed, separated by 1° ILAT. Cluster 1 and 2 observed these two cusps within a few minute interval and about 10 and 50 min later, respectively, Cluster 4 and 3 observed a single cusp only. A peculiarity of this event was the fact that the second cusp seen on C1 and C2 was observed at the same time as the first cusp on C4. This would tend to suggest that the two dispersions are spatial features similar to the double cusp. However more detailed analysis of the characteristics of the cusps (ion dispersion, boundaries) and the IMF abrupt changes clearly showed that the double cusp was in fact a single cusp that had moved toward dawn and then back toward dusk following the changes in the IMF direction.

Characterizing the course of back pain after osteoporotic vertebral fracture: a hierarchical cluster analysis of a prospective cohort study.

PubMed

Toyoda, Hiromitsu; Takahashi, Shinji; Hoshino, Masatoshi; Takayama, Kazushi; Iseki, Kazumichi; Sasaoka, Ryuichi; Tsujio, Tadao; Yasuda, Hiroyuki; Sasaki, Takeharu; Kanematsu, Fumiaki; Kono, Hiroshi; Nakamura, Hiroaki

2017-09-23

This study demonstrated four distinct patterns in the course of back pain after osteoporotic vertebral fracture (OVF). Greater angular instability in the first 6 months after the baseline was one factor affecting back pain after OVF. Understanding the natural course of symptomatic acute OVF is important in deciding the optimal treatment strategy. We used latent class analysis to classify the course of back pain after OVF and identify the risk factors associated with persistent pain. This multicenter cohort study included 218 consecutive patients with ≤ 2-week-old OVFs who were enrolled at 11 institutions. Dynamic x-rays and back pain assessment with a visual analog scale (VAS) were obtained at enrollment and at 1-, 3-, and 6-month follow-ups. The VAS scores were used to characterize patient groups, using hierarchical cluster analysis. VAS for 128 patients was used for hierarchical cluster analysis. Analysis yielded four clusters representing different patterns of back pain progression. Cluster 1 patients (50.8%) had stable, mild pain. Cluster 2 patients (21.1%) started with moderate pain and progressed quickly to very low pain. Patients in cluster 3 (10.9%) had moderate pain that initially improved but worsened after 3 months. Cluster 4 patients (17.2%) had persistent severe pain. Patients in cluster 4 showed significant high baseline pain intensity, higher degree of angular instability, and higher number of previous OVFs, and tended to lack regular exercise. In contrast, patients in cluster 2 had significantly lower baseline VAS and less angular instability. We identified four distinct groups of OVF patients with different patterns of back pain progression. Understanding the course of back pain after OVF may help in its management and contribute to future treatment trials.

Exploring Spatial Patterns of Colorectal Cancer in Tehran City, Iran

PubMed

Mansori, Kamyar; Mosavi-Jarrahi, Alireza; Ganbary Motlagh, Ali; Solaymani-Dodaran, Masoud; Salehi, Masoud; Delavari, Alireza; Sanjari Moghaddam, Ali; Asadi-Lari, Mohsen

2018-04-27

Objectives: Colorectal cancer (CRC) may now be the second most common cancer in the world. The aim of this study was to determine whether clusters of high and low risk of CRC might exist at the neighborhood level in Tehran city. Methods: In this study, new cases of CRC provided from Cancer Registry Data of the Management Center of Ministry of Health and Medical Education of Iran in the period from March 2008 to March 2011 were analyzed. Raw standardized incidence rates (SIRs) were calculated for CRC in each neighborhood, along with ratios of observed to expected cases. The York and Mollie (BYM) spatial model was used for smoothing of the estimated raw SIRs. To discover clusters of high and low CRC incidence a purely spatial scan statistic was applied. Results: A total of 2,815 new cases of CRC were identified and after removal of duplicate cases, 2,491 were geocoded to neighborhoods. The locations with higher than expected incidence of CRC were northern and central districts of Tehran city. An observed to expected ratio of 2.57 (p<0.001) was found for districts of 2, 6 and 11, whereas, the lowest ratio of 0.23 (p<0.001) was apparent for northeast and south areas of the city, including district 4. Conclusions: This study showed that there is a significant spatial variation in patterns of incidence of CRC at the neighborhood level in Tehran city. Identification of such spatial patterns and assessment of underlying risk factors can provide valuable information for policymakers responsible for equitable distribution of healthcare resources. Creative Commons Attribution License

A Holarctic Biogeographical Analysis of the Collembola (Arthropoda, Hexapoda) Unravels Recent Post-Glacial Colonization Patterns

PubMed Central

Ávila-Jiménez, María Luisa; Coulson, Stephen James

2011-01-01

We aimed to describe the main Arctic biogeographical patterns of the Collembola, and analyze historical factors and current climatic regimes determining Arctic collembolan species distribution. Furthermore, we aimed to identify possible dispersal routes, colonization sources and glacial refugia for Arctic collembola. We implemented a Gaussian Mixture Clustering method on species distribution ranges and applied a distance- based parametric bootstrap test on presence-absence collembolan species distribution data. Additionally, multivariate analysis was performed considering species distributions, biodiversity, cluster distribution and environmental factors (temperature and precipitation). No clear relation was found between current climatic regimes and species distribution in the Arctic. Gaussian Mixture Clustering found common elements within Siberian areas, Atlantic areas, the Canadian Arctic, a mid-Siberian cluster and specific Beringian elements, following the same pattern previously described, using a variety of molecular methods, for Arctic plants. Species distribution hence indicate the influence of recent glacial history, as LGM glacial refugia (mid-Siberia, and Beringia) and major dispersal routes to high Arctic island groups can be identified. Endemic species are found in the high Arctic, but no specific biogeographical pattern can be clearly identified as a sign of high Arctic glacial refugia. Ocean currents patterns are suggested as being an important factor shaping the distribution of Arctic Collembola, which is consistent with Antarctic studies in collembolan biogeography. The clear relations between cluster distribution and geographical areas considering their recent glacial history, lack of relationship of species distribution with current climatic regimes, and consistency with previously described Arctic patterns in a series of organisms inferred using a variety of methods, suggest that historical phenomena shaping contemporary collembolan distribution can be inferred through biogeographical analysis. PMID:26467728