Water quality analysis of the Rapur area, Andhra Pradesh, South India using multivariate techniques

NASA Astrophysics Data System (ADS)

Nagaraju, A.; Sreedhar, Y.; Thejaswi, A.; Sayadi, Mohammad Hossein

2017-10-01

The groundwater samples from Rapur area were collected from different sites to evaluate the major ion chemistry. The large number of data can lead to difficulties in the integration, interpretation, and representation of the results. Two multivariate statistical methods, hierarchical cluster analysis (HCA) and factor analysis (FA), were applied to evaluate their usefulness to classify and identify geochemical processes controlling groundwater geochemistry. Four statistically significant clusters were obtained from 30 sampling stations. This has resulted two important clusters viz., cluster 1 (pH, Si, CO3, Mg, SO4, Ca, K, HCO3, alkalinity, Na, Na + K, Cl, and hardness) and cluster 2 (EC and TDS) which are released to the study area from different sources. The application of different multivariate statistical techniques, such as principal component analysis (PCA), assists in the interpretation of complex data matrices for a better understanding of water quality of a study area. From PCA, it is clear that the first factor (factor 1), accounted for 36.2% of the total variance, was high positive loading in EC, Mg, Cl, TDS, and hardness. Based on the PCA scores, four significant cluster groups of sampling locations were detected on the basis of similarity of their water quality.

Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.

PubMed

Rennard, Stephen I; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K; Vestbo, Jørgen; Miller, Bruce E; Bakke, Per; Celli, Bartolomé; Calverley, Peter M A; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D; Lomas, David A; MacNee, William; Wouters, Emiel F M; Yates, Julie C; Coca, Ignacio; Agustí, Alvar

2015-03-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

Grouping of Bulgarian wines according to grape variety by using statistical methods

NASA Astrophysics Data System (ADS)

Milev, M.; Nikolova, Kr.; Ivanova, Ir.; Minkova, St.; Evtimov, T.; Krustev, St.

2017-12-01

68 different types of Bulgarian wines were studied in accordance with 9 optical parameters as follows: color parameters in XYZ and SIE Lab color systems, lightness, Hue angle, chroma, fluorescence intensity and emission wavelength. The main objective of this research is using hierarchical cluster analysis to evaluate the similarity and the distance between examined different types of Bulgarian wines and their grouping based on physical parameters. We have found that wines are grouped in clusters on the base of the degree of identity between them. There are two main clusters each one with two subclusters. The first one contains white wines and Sira, the second contains red wines and rose. The results from cluster analysis are presented graphically by a dendrogram. The other statistical technique used is factor analysis performed by the Method of Principal Components (PCA). The aim is to reduce the large number of variables to a few factors by grouping the correlated variables into one factor and subdividing the noncorrelated variables into different factors. Moreover the factor analysis provided the possibility to determine the parameters with the greatest influence over the distribution of samples in different clusters. In our study after the rotation of the factors with Varimax method the parameters were combined into two factors, which explain about 80 % of the total variation. The first one explains the 61.49% and correlates with color characteristics, the second one explains 18.34% from the variation and correlates with the parameters connected with fluorescence spectroscopy.

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

PubMed

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

2013-01-01

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

Common factor analysis versus principal component analysis: choice for symptom cluster research.

PubMed

Kim, Hee-Ju

2008-03-01

The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences from the two methods. CFA analyzes only the reliable common variance of data, while PCA analyzes all the variance of data. An underlying hypothetical process or construct is involved in CFA but not in PCA. PCA tends to increase factor loadings especially in a study with a small number of variables and/or low estimated communality. Thus, PCA is not appropriate for examining the structure of data. If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research), CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

Subtypes of female juvenile offenders: a cluster analysis of the Millon Adolescent Clinical Inventory.

PubMed

Stefurak, Tres; Calhoun, Georgia B

2007-01-01

The current study sought to explore subtypes of adolescents within a sample of female juvenile offenders. Using the Millon Adolescent Clinical Inventory with 101 female juvenile offenders, a two-step cluster analysis was performed beginning with a Ward's method hierarchical cluster analysis followed by a K-Means iterative partitioning cluster analysis. The results suggest an optimal three-cluster solution, with cluster profiles leading to the following group labels: Externalizing Problems, Depressed/Interpersonally Ambivalent, and Anxious Prosocial. Analysis along the factors of age, race, offense typology and offense chronicity were conducted to further understand the nature of found clusters. Only the effect for race was significant with the Anxious Prosocial and Depressed Intepersonally Ambivalent clusters appearing disproportionately comprised of African American girls. To establish external validity, clusters were compared across scales of the Behavioral Assessment System for Children - Self Report of Personality, and corroborative distinctions between clusters were found here.

An assessment of fatigue in patients with postural orthostatic tachycardia syndrome.

PubMed

Wise, Shelby; Ross, Amanda; Brown, Abigail; Evans, Meredyth; Jason, Leonard

2017-05-01

Individuals with postural orthostatic tachycardia syndrome share many symptoms with those who have chronic fatigue syndrome; one of which is severe fatigue. Previous literature found that those with chronic fatigue syndrome experience many forms of fatigue. The goal of this study was to investigate whether individuals with postural orthostatic tachycardia syndrome also experience multidimensional fatigue and whether these individuals can be clustered into subgroups based on the types of fatigue they endorse. A convenience sample of 138 participants (aged 14-29) with postural orthostatic tachycardia syndrome completed questionnaires that assessed fatigue, brain fog symptom severity, activities that improve brain fog, and brain fog-related disability. An exploratory factor analysis was conducted on the Fatigue Types Questionnaire, and a three-factor solution was produced. Factor scores were then used to cluster the patients into groups using a TwoStep cluster analysis. This resulted in two clusters, a high severity group and a low severity group. The clusters were then compared on a number of items related to symptom expression. Individuals within the more severe cluster had significantly more brain fog at the beginning and end of the survey when compared to cluster two. Those in the more severe cluster also described more activity impairment as well as more frequent, more severe, and more debilitation from postural orthostatic tachycardia syndrome and brain fog. The findings of the factor analysis suggest that patients with postural orthostatic tachycardia syndrome experience fatigue as a multidimensional construct and they also can be subgrouped based on symptom severity.

Prevalence and risk factors for scrub typhus in South India.

PubMed

Trowbridge, Paul; P, Divya; Premkumar, Prasanna S; Varghese, George M

2017-05-01

To determine the prevalence and risk factors of scrub typhus in Tamil Nadu, South India. We performed a clustered seroprevalence study of the areas around Vellore. All participants completed a risk factor survey, with seropositive and seronegative participants acting as cases and controls, respectively, in a risk factor analysis. After univariate analysis, variables found to be significant underwent multivariate analysis. Of 721 people participating in this study, 31.8% tested seropositive. By univariate analysis, after accounting for clustering, having a house that was clustered with other houses, having a fewer rooms in a house, having fewer people living in a household, defecating outside, female sex, age >60 years, shorter height, lower weight, smaller body mass index and smaller mid-upper arm circumference were found to be significantly associated with seropositivity. After multivariate regression modelling, living in a house clustered with other houses, female sex and age >60 years were significantly associated with scrub typhus exposure. Overall, scrub typhus is much more common than previously thought. Previously described individual environmental and habitual risk factors seem to have less importance in South India, perhaps because of the overall scrub typhus-conducive nature of the environment in this region. © 2017 John Wiley & Sons Ltd.

CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

PubMed Central

Peterson, Leif E

2002-01-01

CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

The contribution of psychological factors to recovery after mild traumatic brain injury: is cluster analysis a useful approach?

PubMed

Snell, Deborah L; Surgenor, Lois J; Hay-Smith, E Jean C; Williman, Jonathan; Siegert, Richard J

2015-01-01

Outcomes after mild traumatic brain injury (MTBI) vary, with slow or incomplete recovery for a significant minority. This study examines whether groups of cases with shared psychological factors but with different injury outcomes could be identified using cluster analysis. This is a prospective observational study following 147 adults presenting to a hospital-based emergency department or concussion services in Christchurch, New Zealand. This study examined associations between baseline demographic, clinical, psychological variables (distress, injury beliefs and symptom burden) and outcome 6 months later. A two-step approach to cluster analysis was applied (Ward's method to identify clusters, K-means to refine results). Three meaningful clusters emerged (high-adapters, medium-adapters, low-adapters). Baseline cluster-group membership was significantly associated with outcomes over time. High-adapters appeared recovered by 6-weeks and medium-adapters revealed improvements by 6-months. The low-adapters continued to endorse many symptoms, negative recovery expectations and distress, being significantly at risk for poor outcome more than 6-months after injury (OR (good outcome) = 0.12; CI = 0.03-0.53; p < 0.01). Cluster analysis supported the notion that groups could be identified early post-injury based on psychological factors, with group membership associated with differing outcomes over time. Implications for clinical care providers regarding therapy targets and cases that may benefit from different intensities of intervention are discussed.

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

PubMed

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

2015-01-01

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

Risk profiles for weight gain among postmenopausal women: A classification and regression tree analysis approach

USDA-ARS?s Scientific Manuscript database

Risk factors for obesity and weight gain are typically evaluated individually while "adjusting for" the influence of other confounding factors, and few studies, if any, have created risk profiles by clustering risk factors. We identified subgroups of postmenopausal women homogeneous in their cluster...

Usage of K-cluster and factor analysis for grouping and evaluation the quality of olive oil in accordance with physico-chemical parameters

NASA Astrophysics Data System (ADS)

Milev, M.; Nikolova, Kr.; Ivanova, Ir.; Dobreva, M.

2015-11-01

25 olive oils were studied- different in origin and ways of extraction, in accordance with 17 physico-chemical parameters as follows: color parameters - a and b, light, fluorescence peaks, pigments - chlorophyll and β-carotene, fatty-acid content. The goals of the current study were: Conducting correlation analysis to find the inner relation between the studied indices; By applying factor analysis with the help of the method of Principal Components (PCA), to reduce the great number of variables into a few factors, which are of main importance for distinguishing the different types of olive oil;Using K-means cluster to compare and group the tested types olive oils based on their similarity. The inner relation between the studied indices was found by applying correlation analysis. A factor analysis using PCA was applied on the basis of the found correlation matrix. Thus the number of the studied indices was reduced to 4 factors, which explained 79.3% from the entire variation. The first one unified the color parameters, β-carotene and the related with oxidative products fluorescence peak - about 520 nm. The second one was determined mainly by the chlorophyll content and related to it fluorescence peak - about 670 nm. The third and the fourth factors were determined by the fatty-acid content of the samples. The third one unified the fatty-acids, which give us the opportunity to distinguish olive oil from the other plant oils - oleic, linoleic and stearin acids. The fourth factor included fatty-acids with relatively much lower content in the studied samples. It is enquired the number of clusters to be determined preliminary in order to apply the K-Cluster analysis. The variant K = 3 was worked out because the types of the olive oil were three. The first cluster unified all salad and pomace olive oils, the second unified the samples of extra virgin oilstaken as controls from producers, which were bought from the trade network. The third cluster unified samples from pomace and extra virgin oils, which distinguish one from another in accordance with their parameters from the natural olive oils, because of presence of plant oils impurities.

Cardiometabolic Risk Clustering in Spinal Cord Injury: Results of Exploratory Factor Analysis

PubMed Central

2013-01-01

Background: Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. Objective: The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. Methods: One hundred twenty-one subjects (mean 37 ± 12 years; range, 18–73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). Results: The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3–factor model in persons with paraplegia (65.4% variance) and a 4–factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Conclusions: Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism. PMID:23960702

Consanguinity and family clustering of male factor infertility in Lebanon.

PubMed

Inhorn, Marcia C; Kobeissi, Loulou; Nassar, Zaher; Lakkis, Da'ad; Fakih, Michael H

2009-04-01

To investigate the influence of consanguineous marriage on male factor infertility in Lebanon, where rates of consanguineous marriage remain high (29.6% among Muslims, 16.5% among Christians). Clinic-based, case-control study, using reproductive history, risk factor interview, and laboratory-based semen analysis. Two IVF clinics in Beirut, Lebanon, during an 8-month period (January-August 2003). One hundred twenty infertile male patients and 100 fertile male controls, distinguished by semen analysis and reproductive history. None. Standard clinical semen analysis. The rates of consanguineous marriage were relatively high among the study sample. Patients (46%) were more likely than controls (37%) to report first-degree (parental) and second-degree (grandparental) consanguinity. The study demonstrated a clear pattern of family clustering of male factor infertility, with patients significantly more likely than controls to report infertility among close male relatives (odds ratio = 2.58). Men with azoospermia and severe oligospermia showed high rates of both consanguinity (50%) and family clustering (41%). Consanguineous marriage is a socially supported institution throughout the Muslim world, yet its relationship to infertility is poorly understood. This study demonstrated a significant association between consanguinity and family clustering of male factor infertility cases, suggesting a strong genetic component.

Application of Factor Analysis on the Financial Ratios of Indian Cement Industry and Validation of the Results by Cluster Analysis

NASA Astrophysics Data System (ADS)

De, Anupam; Bandyopadhyay, Gautam; Chakraborty, B. N.

2010-10-01

Financial ratio analysis is an important and commonly used tool in analyzing financial health of a firm. Quite a large number of financial ratios, which can be categorized in different groups, are used for this analysis. However, to reduce number of ratios to be used for financial analysis and regrouping them into different groups on basis of empirical evidence, Factor Analysis technique is being used successfully by different researches during the last three decades. In this study Factor Analysis has been applied over audited financial data of Indian cement companies for a period of 10 years. The sample companies are listed on the Stock Exchange India (BSE and NSE). Factor Analysis, conducted over 44 variables (financial ratios) grouped in 7 categories, resulted in 11 underlying categories (factors). Each factor is named in an appropriate manner considering the factor loads and constituent variables (ratios). Representative ratios are identified for each such factor. To validate the results of Factor Analysis and to reach final conclusion regarding the representative ratios, Cluster Analysis had been performed.

Transcription factor clusters regulate genes in eukaryotic cells

PubMed Central

Hedlund, Erik G; Friemann, Rosmarie; Hohmann, Stefan

2017-01-01

Transcription is regulated through binding factors to gene promoters to activate or repress expression, however, the mechanisms by which factors find targets remain unclear. Using single-molecule fluorescence microscopy, we determined in vivo stoichiometry and spatiotemporal dynamics of a GFP tagged repressor, Mig1, from a paradigm signaling pathway of Saccharomyces cerevisiae. We find the repressor operates in clusters, which upon extracellular signal detection, translocate from the cytoplasm, bind to nuclear targets and turnover. Simulations of Mig1 configuration within a 3D yeast genome model combined with a promoter-specific, fluorescent translation reporter confirmed clusters are the functional unit of gene regulation. In vitro and structural analysis on reconstituted Mig1 suggests that clusters are stabilized by depletion forces between intrinsically disordered sequences. We observed similar clusters of a co-regulatory activator from a different pathway, supporting a generalized cluster model for transcription factors that reduces promoter search times through intersegment transfer while stabilizing gene expression. PMID:28841133

A survey of scientific literacy to provide a foundation for designing science communication in Japan.

PubMed

Kawamoto, Shishin; Nakayama, Minoru; Saijo, Miki

2013-08-01

There are various definitions and survey methods for scientific literacy. Taking into consideration the contemporary significance of scientific literacy, we have defined it with an emphasis on its social aspects. To acquire the insights needed to design a form of science communication that will enhance the scientific literacy of each individual, we conducted a large-scale random survey within Japan of individuals older than 18 years, using a printed questionnaire. The data thus acquired were analyzed using factor analysis and cluster analysis to create a 3-factor/4-cluster model of people's interest and attitude toward science, technology and society and their resulting tendencies. Differences were found among the four clusters in terms of the three factors: scientific factor, social factor, and science-appreciating factor. We propose a plan for designing a form of science communication that is appropriate to this current status of scientific literacy in Japan.

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.

Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life.

PubMed

Dong, Skye T; Costa, Daniel S J; Butow, Phyllis N; Lovell, Melanie R; Agar, Meera; Velikova, Galina; Teckle, Paulos; Tong, Allison; Tebbutt, Niall C; Clarke, Stephen J; van der Hoek, Kim; King, Madeleine T; Fayers, Peter M

2016-01-01

Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Cluster subgroups based on overall pressure pain sensitivity and psychosocial factors in chronic musculoskeletal pain: Differences in clinical outcomes.

PubMed

Almeida, Suzana C; George, Steven Z; Leite, Raquel D V; Oliveira, Anamaria S; Chaves, Thais C

2018-05-17

We aimed to empirically derive psychosocial and pain sensitivity subgroups using cluster analysis within a sample of individuals with chronic musculoskeletal pain (CMP) and to investigate derived subgroups for differences in pain and disability outcomes. Eighty female participants with CMP answered psychosocial and disability scales and were assessed for pressure pain sensitivity. A cluster analysis was used to derive subgroups, and analysis of variance (ANOVA) was used to investigate differences between subgroups. Psychosocial factors (kinesiophobia, pain catastrophizing, anxiety, and depression) and overall pressure pain threshold (PPT) were entered into the cluster analysis. Three subgroups were empirically derived: cluster 1 (high pain sensitivity and high psychosocial distress; n = 12) characterized by low overall PPT and high psychosocial scores; cluster 2 (high pain sensitivity and intermediate psychosocial distress; n = 39) characterized by low overall PPT and intermediate psychosocial scores; and cluster 3 (low pain sensitivity and low psychosocial distress; n = 29) characterized by high overall PPT and low psychosocial scores compared to the other subgroups. Cluster 1 showed higher values for mean pain intensity (F (2,77)  = 10.58, p < 0.001) compared with cluster 3, and cluster 1 showed higher values for disability (F (2,77)  = 3.81, p = 0.03) compared with both clusters 2 and 3. Only cluster 1 was distinct from cluster 3 according to both pain and disability outcomes. Pain catastrophizing, depression, and anxiety were the psychosocial variables that best differentiated the subgroups. Overall, these results call attention to the importance of considering pain sensitivity and psychosocial variables to obtain a more comprehensive characterization of CMP patients' subtypes.

Subscales to the Taylor Manifest Anxiety Scale in Three Chronically Ill Populations.

ERIC Educational Resources Information Center

Moore, Peter N.; And Others

1984-01-01

Examines factors of anxiety in the Taylor Manifest Anxiety Scale in 150 asthma, tuberculosis, and chronic pain patients. Key cluster analysis revealed five clusters: restlessness, embarrassment, sensitivity, physiological anxiety, and self-confidence. Embarrassment is fairly dependent on the other factors. (JAC)

On-Line Pattern Analysis and Recognition System. OLPARS VI. Software Reference Manual,

DTIC Science & Technology

1982-06-18

Discriminant Analysis Data Transformation, Feature Extraction, Feature Evaluation Cluster Analysis, Classification Computer Software 20Z. ABSTRACT... cluster /scatter cut-off value, (2) change the one-space bin factor, (3) change from long prompts to short prompts or vice versa, (4) change the...value, a cluster plot is displayed, otherwise a scatter plot is shown. if option 1 is selected, the program requests that a new value be input

Prevalence and risk factors of seizure clusters in adult patients with epilepsy.

PubMed

Chen, Baibing; Choi, Hyunmi; Hirsch, Lawrence J; Katz, Austen; Legge, Alexander; Wong, Rebecca A; Jiang, Alfred; Kato, Kenneth; Buchsbaum, Richard; Detyniecki, Kamil

2017-07-01

In the current study, we explored the prevalence of physician-confirmed seizure clusters. We also investigated potential clinical factors associated with the occurrence of seizure clusters overall and by epilepsy type. We reviewed medical records of 4116 adult (≥16years old) outpatients with epilepsy at our centers for documentation of seizure clusters. Variables including patient demographics, epilepsy details, medical and psychiatric history, AED history, and epilepsy risk factors were then tested against history of seizure clusters. Patients were then divided into focal epilepsy, idiopathic generalized epilepsy (IGE), or symptomatic generalized epilepsy (SGE), and the same analysis was run. Overall, seizure clusters were independently associated with earlier age of seizure onset, symptomatic generalized epilepsy (SGE), central nervous system (CNS) infection, cortical dysplasia, status epilepticus, absence of 1-year seizure freedom, and having failed 2 or more AEDs (P<0.0026). Patients with SGE (27.1%) were more likely to develop seizure clusters than patients with focal epilepsy (16.3%) and IGE (7.4%; all P<0.001). Analysis by epilepsy type showed that absence of 1-year seizure freedom since starting treatment at one of our centers was associated with seizure clustering in patients across all 3 epilepsy types. In patients with SGE, clusters were associated with perinatal/congenital brain injury. In patients with focal epilepsy, clusters were associated with younger age of seizure onset, complex partial seizures, cortical dysplasia, status epilepticus, CNS infection, and having failed 2 or more AEDs. In patients with IGE, clusters were associated with presence of an aura. Only 43.5% of patients with seizure clusters were prescribed rescue medications. Patients with intractable epilepsy are at a higher risk of developing seizure clusters. Factors such as having SGE, CNS infection, cortical dysplasia, status epilepticus or an early seizure onset, can also independently increase one's chance of having seizure clusters. Copyright © 2017. Published by Elsevier B.V.

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).

Factors influencing the quality of life of haemodialysis patients according to symptom cluster.

PubMed

Shim, Hye Yeung; Cho, Mi-Kyoung

2018-05-01

To identify the characteristics in each symptom cluster and factors influencing the quality of life of haemodialysis patients in Korea according to cluster. Despite developments in renal replacement therapy, haemodialysis still restricts the activities of daily living due to pain and impairs physical functioning induced by the disease and its complications. Descriptive survey. Two hundred and thirty dialysis patients aged >18 years. They completed self-administered questionnaires of Dialysis Symptom Index and Kidney Disease Quality of Life instrument-Short Form 1.3. To determine the optimal number of clusters, the collected data were analysed using polytomous variable latent class analysis in R software (poLCA) to estimate the latent class models and the latent class regression models for polytomous outcome variables. Differences in characteristics, symptoms and QOL according to the symptom cluster of haemodialysis patients were analysed using the independent t test and chi-square test. The factors influencing the QOL according to symptom cluster were identified using hierarchical multiple regression analysis. Physical and emotional symptoms were significantly more severe, and the QOL was significantly worse in Cluster 1 than in Cluster 2. The factors influencing the QOL were spouse, job, insurance type and physical and emotional symptoms in Cluster 1, with these variables having an explanatory power of 60.9%. Physical and emotional symptoms were the only influencing factors in Cluster 2, and they had an explanatory power of 37.4%. Mitigating the symptoms experienced by haemodialysis patients and improving their QOL require educational and therapeutic symptom management interventions that are tailored according to the characteristics and symptoms in each cluster. The findings of this study are expected to lead to practical guidelines for addressing the symptoms experienced by haemodialysis patients, and they provide basic information for developing nursing interventions to manage these symptoms and improve the QOL of these patients. © 2017 John Wiley & Sons Ltd.

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

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.

Using BMDP and SPSS for a Q factor analysis.

PubMed

Tanner, B A; Koning, S M

1980-12-01

While Euclidean distances and Q factor analysis may sometimes be preferred to correlation coefficients and cluster analysis for developing a typology, commercially available software does not always facilitate their use. Commands are provided for using BMDP and SPSS in a Q factor analysis with Euclidean distances.

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-07-01

In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed yielding an explict cluster attribution for each particle, improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

A comparison of hierarchical cluster analysis and league table rankings as methods for analysis and presentation of district health system performance data in Uganda.

PubMed

Tashobya, Christine K; Dubourg, Dominique; Ssengooba, Freddie; Speybroeck, Niko; Macq, Jean; Criel, Bart

2016-03-01

In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards' method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences. © The Author 2015. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

A comparison of hierarchical cluster analysis and league table rankings as methods for analysis and presentation of district health system performance data in Uganda†

PubMed Central

Tashobya, Christine K; Dubourg, Dominique; Ssengooba, Freddie; Speybroeck, Niko; Macq, Jean; Criel, Bart

2016-01-01

In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards’ method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences. PMID:26024882

[High risk groups in health behavior defined by clustering of smoking, alcohol, and exercise habits: National Heath and Nutrition Examination Survey].

PubMed

Kang, Kiwon; Sung, Joohon; Kim, Chang Yup

2010-01-01

We investigated the clustering of selected lifestyle factors (cigarette smoking, heavy alcohol consumption, lack of physical exercise) and identified the population characteristics associated with increasing lifestyle risks. Data on lifestyle risk factors, sociodemographic characteristics, and history of chronic diseases were obtained from 7,694 individuals >/=20 years of age who participated in the 2005 Korea National Health and Nutrition Examination Survey (KNHANES). Clustering of lifestyle risks involved the observed prevalence of multiple risks and those expected from marginal exposure prevalence of the three selected risk factors. Prevalence odds ratio was adopted as a measurement of clustering. Multiple correspondence analysis, Kendall tau correlation, Man-Whitney analysis, and ordinal logistic regression analysis were conducted to identify variables increasing lifestyle risks. In both men and women, increased lifestyle risks were associated with clustering of: (1) cigarette smoking and excessive alcohol consumption, and (2) smoking, excessive alcohol consumption, and lack of physical exercise. Patterns of clustering for physical exercise were different from those for cigarette smoking and alcohol consumption. The increased unhealthy clustering was found among men 20-64 years of age with mild or moderate stress, and among women 35-49 years of age who were never-married, with mild stress, and increased body mass index (>30 kg/m(2)). Addressing a lack of physical exercise considering individual characteristics including gender, age, employment activity, and stress levels should be a focus of health promotion efforts.

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

PubMed Central

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

2007-01-01

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

A Comprehensive Careers Cluster Curriculum Model. Health Occupations Cluster Curriculum Project and Health-Care Aide Curriculum Project.

ERIC Educational Resources Information Center

Bortz, Richard F.

To prepare learning materials for health careers programs at the secondary level, the developmental phase of two curriculum projects--the Health Occupations Cluster Curriculum Project and Health-Care Aide Curriculum Project--utilized a model which incorporated a key factor analysis technique. Entitled "A Comprehensive Careers Cluster Curriculum…

Do Sexually Oriented Massage Parlors Cluster in Specific Neighborhoods? A Spatial Analysis of Indoor Sex Work in Los Angeles and Orange Counties, California.

PubMed

Chin, John J; Kim, Anna J; Takahashi, Lois; Wiebe, Douglas J

2015-01-01

Social determinants of health may be substantially affected by spatial factors, which together may explain the persistence of health inequities. Clustering of possible sources of negative health and social outcomes points to a spatial focus for future interventions. We analyzed the spatial clustering of sex work businesses in Southern California to examine where and why they cluster. We explored economic and legal factors as possible explanations of clustering. We manually coded data from a website used by paying members to post reviews of female massage parlor workers. We identified clusters of sexually oriented massage parlor businesses using spatial autocorrelation tests. We conducted spatial regression using census tract data to identify predictors of clustering. A total of 889 venues were identified. Clusters of tracts having higher-than-expected numbers of sexually oriented massage parlors ("hot spots") were located outside downtowns. These hot spots were characterized by a higher proportion of adult males, a higher proportion of households below the federal poverty level, and a smaller average household size. Sexually oriented massage parlors in Los Angeles and Orange counties cluster in particular neighborhoods. More research is needed to ascertain the causal factors of such clusters and how interventions can be designed to leverage these spatial factors.

Identifying Patient Attitudinal Clusters Associated with Asthma Control: The European REALISE Survey.

PubMed

van der Molen, Thys; Fletcher, Monica; Price, David

Asthma is a highly heterogeneous disease that can be classified into different clinical phenotypes, and treatment may be tailored accordingly. However, factors beyond purely clinical traits, such as patient attitudes and behaviors, can also have a marked impact on treatment outcomes. The objective of this study was to further analyze data from the REcognise Asthma and LInk to Symptoms and Experience (REALISE) Europe survey, to identify distinct patient groups sharing common attitudes toward asthma and its management. Factor analysis of respondent data (N = 7,930) from the REALISE Europe survey consolidated the 34 attitudinal variables provided by the study population into a set of 8 summary factors. Cluster analyses were used to identify patient clusters that showed similar attitudes and behaviors toward each of the 8 summary factors. Five distinct patient clusters were identified and named according to the key characteristics comprising that cluster: "Confident and self-managing," "Confident and accepting of their asthma," "Confident but dependent on others," "Concerned but confident in their health care professional (HCP)," and "Not confident in themselves or their HCP." Clusters showed clear variability in attributes such as degree of confidence in managing their asthma, use of reliever and preventer medication, and level of asthma control. The 5 patient clusters identified in this analysis displayed distinctly different personal attitudes that would require different approaches in the consultation room certainly for asthma but probably also for other chronic diseases. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Population changes in residential clusters in Japan.

PubMed

Sekiguchi, Takuya; Tamura, Kohei; Masuda, Naoki

2018-01-01

Population dynamics in urban and rural areas are different. Understanding factors that contribute to local population changes has various socioeconomic and political implications. In the present study, we use population census data in Japan to examine contributors to the population growth of residential clusters between years 2005 and 2010. The data set covers the entirety of Japan and has a high spatial resolution of 500 × 500 m2, enabling us to examine population dynamics in various parts of the country (urban and rural) using statistical analysis. We found that, in addition to the area, population density, and age, the shape of the cluster and the spatial distribution of inhabitants within the cluster are significantly related to the population growth rate of a residential cluster. Specifically, the population tends to grow if the cluster is "round" shaped (given the area) and the population is concentrated near the center rather than periphery of the cluster. Combination of the present results and analysis framework with other factors that have been omitted in the present study, such as migration, terrain, and transportation infrastructure, will be fruitful.

Spatial cluster for clustering the influence factor of birth and death child in Bogor Regency, West Java

NASA Astrophysics Data System (ADS)

Bekti, Rokhana Dwi; Rachmawati, Ro'fah

2014-03-01

The number of birth and death child is the benchmarks to determine and monitor the health and welfare in Indonesia. It can be used to identify groups of people who have a high mortality risk. Identifying group is important to compare the characteristics of human that have high and low risk. These characteristics can be seen from the factors that influenced it. Furthermore, there are factors which influence of birth and death child, such us economic, health facility, education, and others. The influence factors of every individual are different, but there are similarities some individuals which live close together or in the close locations. It means there was spatial effect. To identify group in this research, clustering is done by spatial cluster method, which is view to considering the influence of the location or the relationship between locations. One of spatial cluster method is Spatial 'K'luster Analysis by Tree Edge Removal (SKATER). The research was conducted in Bogor Regency, West Java. The goal was to get a cluster of districts based on the factors that influence birth and death child. SKATER build four number of cluster respectively consists of 26, 7, 2, and 5 districts. SKATER has good performance for clustering which include spatial effect. If it compare by other cluster method, Kmeans has good performance by MANOVA test.

Alternative Sigma Factor Over-Expression Enables Heterologous Expression of a Type II Polyketide Biosynthetic Pathway in Escherichia coli

PubMed Central

Stevens, David Cole; Conway, Kyle R.; Pearce, Nelson; Villegas-Peñaranda, Luis Roberto; Garza, Anthony G.; Boddy, Christopher N.

2013-01-01

Background Heterologous expression of bacterial biosynthetic gene clusters is currently an indispensable tool for characterizing biosynthetic pathways. Development of an effective, general heterologous expression system that can be applied to bioprospecting from metagenomic DNA will enable the discovery of a wealth of new natural products. Methodology We have developed a new Escherichia coli-based heterologous expression system for polyketide biosynthetic gene clusters. We have demonstrated the over-expression of the alternative sigma factor σ54 directly and positively regulates heterologous expression of the oxytetracycline biosynthetic gene cluster in E. coli. Bioinformatics analysis indicates that σ54 promoters are present in nearly 70% of polyketide and non-ribosomal peptide biosynthetic pathways. Conclusions We have demonstrated a new mechanism for heterologous expression of the oxytetracycline polyketide biosynthetic pathway, where high-level pleiotropic sigma factors from the heterologous host directly and positively regulate transcription of the non-native biosynthetic gene cluster. Our bioinformatics analysis is consistent with the hypothesis that heterologous expression mediated by the alternative sigma factor σ54 may be a viable method for the production of additional polyketide products. PMID:23724102

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

Groundwater flow and hydrogeochemical evolution in the Jianghan Plain, central China

NASA Astrophysics Data System (ADS)

Gan, Yiqun; Zhao, Ke; Deng, Yamin; Liang, Xing; Ma, Teng; Wang, Yanxin

2018-05-01

Hydrogeochemical analysis and multivariate statistics were applied to identify flow patterns and major processes controlling the hydrogeochemistry of groundwater in the Jianghan Plain, which is located in central Yangtze River Basin (central China) and characterized by intensive surface-water/groundwater interaction. Although HCO3-Ca-(Mg) type water predominated in the study area, the 457 (21 surface water and 436 groundwater) samples were effectively classified into five clusters by hierarchical cluster analysis. The hydrochemical variations among these clusters were governed by three factors from factor analysis. Major components (e.g., Ca, Mg and HCO3) in surface water and groundwater originated from carbonate and silicate weathering (factor 1). Redox conditions (factor 2) influenced the geogenic Fe and As contamination in shallow confined groundwater. Anthropogenic activities (factor 3) primarily caused high levels of Cl and SO4 in surface water and phreatic groundwater. Furthermore, the factor score 1 of samples in the shallow confined aquifer gradually increased along the flow paths. This study demonstrates that enhanced information on hydrochemistry in complex groundwater flow systems, by multivariate statistical methods, improves the understanding of groundwater flow and hydrogeochemical evolution due to natural and anthropogenic impacts.

Comparison of cluster-based and source-attribution methods for estimating transmission risk using large HIV sequence databases.

PubMed

Le Vu, Stéphane; Ratmann, Oliver; Delpech, Valerie; Brown, Alison E; Gill, O Noel; Tostevin, Anna; Fraser, Christophe; Volz, Erik M

2018-06-01

Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission. A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors. We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

How Teachers Use and Manage Their Blogs? A Cluster Analysis of Teachers' Blogs in Taiwan

ERIC Educational Resources Information Center

Liu, Eric Zhi-Feng; Hou, Huei-Tse

2013-01-01

The development of Web 2.0 has ushered in a new set of web-based tools, including blogs. This study focused on how teachers use and manage their blogs. A sample of 165 teachers' blogs in Taiwan was analyzed by factor analysis, cluster analysis and qualitative content analysis. First, the teachers' blogs were analyzed according to six criteria…

White Matter Tract Integrity in Alzheimer's Disease vs. Late Onset Bipolar Disorder and Its Correlation with Systemic Inflammation and Oxidative Stress Biomarkers.

PubMed

Besga, Ariadna; Chyzhyk, Darya; Gonzalez-Ortega, Itxaso; Echeveste, Jon; Graña-Lecuona, Marina; Graña, Manuel; Gonzalez-Pinto, Ana

2017-01-01

Background: Late Onset Bipolar Disorder (LOBD) is the development of Bipolar Disorder (BD) at an age above 50 years old. It is often difficult to differentiate from other aging dementias, such as Alzheimer's Disease (AD), because they share cognitive and behavioral impairment symptoms. Objectives: We look for WM tract voxel clusters showing significant differences when comparing of AD vs. LOBD, and its correlations with systemic blood plasma biomarkers (inflammatory, neurotrophic factors, and oxidative stress). Materials: A sample of healthy controls (HC) ( n = 19), AD patients ( n = 35), and LOBD patients ( n = 24) was recruited at the Alava University Hospital. Blood plasma samples were obtained at recruitment time and analyzed to extract the inflammatory, oxidative stress, and neurotrophic factors. Several modalities of MRI were acquired for each subject, Methods: Fractional anisotropy (FA) coefficients are obtained from diffusion weighted imaging (DWI). Tract based spatial statistics (TBSS) finds FA skeleton clusters of WM tract voxels showing significant differences for all possible contrasts between HC, AD, and LOBD. An ANOVA F -test over all contrasts is carried out. Results of F -test are used to mask TBSS detected clusters for the AD > LOBD and LOBD > AD contrast to select the image clusters used for correlation analysis. Finally, Pearson's correlation coefficients between FA values at cluster sites and systemic blood plasma biomarker values are computed. Results: The TBSS contrasts with by ANOVA F -test has identified strongly significant clusters in the forceps minor, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and cingulum gyrus. The correlation analysis of these tract clusters found strong negative correlation of AD with the nerve growth factor (NGF) and brain derived neurotrophic factor (BDNF) blood biomarkers. Negative correlation of AD and positive correlation of LOBD with inflammation biomarker IL6 was also found. Conclusion: TBSS voxel clusters tract atlas localizations are consistent with greater behavioral impairment and mood disorders in LOBD than in AD. Correlation analysis confirms that neurotrophic factors (i.e., NGF, BDNF) play a great role in AD while are absent in LOBD pathophysiology. Also, correlation results of IL1 and IL6 suggest stronger inflammatory effects in LOBD than in AD.

Do Sexually Oriented Massage Parlors Cluster in Specific Neighborhoods? A Spatial Analysis of Indoor Sex Work in Los Angeles and Orange Counties, California

PubMed Central

Kim, Anna J.; Takahashi, Lois; Wiebe, Douglas J.

2015-01-01

Objective Social determinants of health may be substantially affected by spatial factors, which together may explain the persistence of health inequities. Clustering of possible sources of negative health and social outcomes points to a spatial focus for future interventions. We analyzed the spatial clustering of sex work businesses in Southern California to examine where and why they cluster. We explored economic and legal factors as possible explanations of clustering. Methods We manually coded data from a website used by paying members to post reviews of female massage parlor workers. We identified clusters of sexually oriented massage parlor businesses using spatial autocorrelation tests. We conducted spatial regression using census tract data to identify predictors of clustering. Results A total of 889 venues were identified. Clusters of tracts having higher-than-expected numbers of sexually oriented massage parlors (“hot spots”) were located outside downtowns. These hot spots were characterized by a higher proportion of adult males, a higher proportion of households below the federal poverty level, and a smaller average household size. Conclusion Sexually oriented massage parlors in Los Angeles and Orange counties cluster in particular neighborhoods. More research is needed to ascertain the causal factors of such clusters and how interventions can be designed to leverage these spatial factors. PMID:26327731

Knowledge, attitudes towards and acceptability of genetic modification in Germany.

PubMed

Christoph, Inken B; Bruhn, Maike; Roosen, Jutta

2008-07-01

Genetic modification remains a controversial issue. The aim of this study is to analyse the attitudes towards genetic modification, the knowledge about it and its acceptability in different application areas among German consumers. Results are based on a survey from spring 2005. An exploratory factor analysis is conducted to identify the attitudes towards genetic modification. The identified factors are used in a cluster analysis that identified a cluster of supporters, of opponents and a group of indifferent consumers. Respondents' knowledge of genetics and biotechnology differs among the found clusters without revealing a clear relationship between knowledge and support of genetic modification. The acceptability of genetic modification varies by application area and cluster, and genetically modified non-food products are more widely accepted than food products. The perception of personal health risks has high explanatory power for attitudes and acceptability.

Clustering of risk factors for noncommunicable diseases in Brazilian adolescents: prevalence and correlates.

PubMed

Cureau, Felipe Vogt; Duarte, Paola; dos Santos, Daniela Lopes; Reichert, Felipe Fossati

2014-07-01

Few studies have investigated the prevalence and correlates of risk factors for noncommunicable diseases among Brazilian adolescents. We evaluated the clustering of risk factors and their associations with sociodemographic variables. We used a cross-sectional study carried out in 2011 comprising 1132 students aged 14-19 years from Santa Maria, Brazil. The cluster index was created as the sum of the risk factors. For the correlates analysis, a multinomial logistic regression was used. Furthermore, the observed/expected ratio was calculated. Prevalence of individual risk factors studied was as follows: 85.8% unhealthy diets, 53.5% physical inactivity, 31.3% elevated blood pressure, 23.9% overweight, 22.3% excessive drinking alcohol, and 8.6% smoking. Only 2.8% of the adolescents did not present any risk factor, while 21.7%, 40.9%, 23.1%, and 11.5% presented 1, 2, 3, and 4 or more risk factors, respectively. The most prevalent combination was between unhealthy diets and physical inactivity (observed/expected ratio =1.32; 95% CI: 1.16-1.49). Clustering of risk factors was directly associated with age and inversely associated with socioeconomic status. Clustering of risk factors for noncommunicable diseases is high in Brazilian adolescents. Preventive strategies are more likely to be successful if focusing on multiple risk factors, instead of a single one.

Typology of schizotypy in non-clinical young adults: Psychopathological and personality disorder traits correlates.

PubMed

Raynal, Patrick; Goutaudier, Nelly; Nidetch, Victoria; Chabrol, Henri

2016-12-30

Few typological studies address schizotypy in young adults. Schizotypal traits were assessed on 466 college students using the Schizotypal Personality Questionnaire-Brief (SPQ-B). Other measures evaluated personality traits previously associated with schizotypy (borderline, obsessionnal, and autistic traits), psychopathological symptoms (suicidal ideations, depressive and obsessive-compulsive symptoms) and psychosocial functioning. A factor analysis was first performed on SPQ-B results, leading to four factors: negative schizotypy, positive schizotypy, social anxiety, and reference ideas. Based on these factors, a cluster analysis was conducted, which yielded four clearly distinct groups characterized by "Low" (non schizotypy), "High schizotypy" (mixed positive and negative), "Positive schizotypy", and "Social impairment". Regarding personality disorder traits and psychopathological symptoms, the "High schizotypy" cluster scored higher than the "Positive" and the "Social impairment" groups, which scored higher than the "Low" cluster. The "Positive" group had higher levels of interpersonal relationships than in the "High" and the "Social impairment" clusters, suggesting that positive schizotypy was associated to benefits such as perceived social relationships. Nevertheless the "Positive" cluster was also linked to high levels of personality disorder traits and psychopathological symptoms, and to low academic achievement, at levels similar those observed in the "Social impairment" cluster, confirming an unhealthy side to positive schizotypy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Profile Analysis of the Woodcock-Johnson III Tests of Cognitive Abilities with Gifted Students.

ERIC Educational Resources Information Center

Rizza, Mary G.; McIntosh, David E.; McCunn, Alice

2001-01-01

The Cattell-Horn-Carroll (CHC) factor clusters of the Woodcock-Johnson III Tests of Cognitive Abilities (WJ III COG) were studied with a group of gifted and nongifted individuals. Results found both groups display similar patterns of performance across the CHC factor clusters. Discusses clinical and educational considerations when using the WJ III…

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

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-11-01

In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

The Awareness and Educational Status on Oral Health of Elite Athletes: A Cross-Sectional Study with Cluster Analysis

ERIC Educational Resources Information Center

Ozgur, Bahar Odabas

2016-01-01

In this cross-sectional survey, this study aimed to determine the factors associated with oral health of elite athletes and to determine the clustering tendency of the variables by dendrogram, and to determine the relationship between predefined clusters and see how these clusters can converge. A total of 97 elite (that is, top-level performing)…

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

Psychological Factors Predict Local and Referred Experimental Muscle Pain: A Cluster Analysis in Healthy Adults

PubMed Central

Lee, Jennifer E.; Watson, David; Frey-Law, Laura A.

2012-01-01

Background Recent studies suggest an underlying three- or four-factor structure explains the conceptual overlap and distinctiveness of several negative emotionality and pain-related constructs. However, the validity of these latent factors for predicting pain has not been examined. Methods A cohort of 189 (99F; 90M) healthy volunteers completed eight self-report negative emotionality and pain-related measures (Eysenck Personality Questionnaire-Revised; Positive and Negative Affect Schedule; State-Trait Anxiety Inventory; Pain Catastrophizing Scale; Fear of Pain Questionnaire; Somatosensory Amplification Scale; Anxiety Sensitivity Index; Whiteley Index). Using principal axis factoring, three primary latent factors were extracted: General Distress; Catastrophic Thinking; and Pain-Related Fear. Using these factors, individuals clustered into three subgroups of high, moderate, and low negative emotionality responses. Experimental pain was induced via intramuscular acidic infusion into the anterior tibialis muscle, producing local (infusion site) and/or referred (anterior ankle) pain and hyperalgesia. Results Pain outcomes differed between clusters (multivariate analysis of variance and multinomial regression), with individuals in the highest negative emotionality cluster reporting the greatest local pain (p = 0.05), mechanical hyperalgesia (pressure pain thresholds; p = 0.009) and greater odds (2.21 OR) of experiencing referred pain compared to the lowest negative emotionality cluster. Conclusion Our results provide support for three latent psychological factors explaining the majority of the variance between several pain-related psychological measures, and that individuals in the high negative emotionality subgroup are at increased risk for (1) acute local muscle pain; (2) local hyperalgesia; and (3) referred pain using a standardized nociceptive input. PMID:23165778

A cluster analysis on road traffic accidents using genetic algorithms

NASA Astrophysics Data System (ADS)

Saharan, Sabariah; Baragona, Roberto

2017-04-01

The analysis of traffic road accidents is increasingly important because of the accidents cost and public road safety. The availability or large data sets makes the study of factors that affect the frequency and severity accidents are viable. However, the data are often highly unbalanced and overlapped. We deal with the data set of the road traffic accidents recorded in Christchurch, New Zealand, from 2000-2009 with a total of 26440 accidents. The data is in a binary set and there are 50 factors road traffic accidents with four level of severity. We used genetic algorithm for the analysis because we are in the presence of a large unbalanced data set and standard clustering like k-means algorithm may not be suitable for the task. The genetic algorithm based on clustering for unknown K, (GCUK) has been used to identify the factors associated with accidents of different levels of severity. The results provided us with an interesting insight into the relationship between factors and accidents severity level and suggest that the two main factors that contributes to fatal accidents are "Speed greater than 60 km h" and "Did not see other people until it was too late". A comparison with the k-means algorithm and the independent component analysis is performed to validate the results.

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

PubMed Central

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

2017-01-01

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

Electrical Load Profile Analysis Using Clustering Techniques

NASA Astrophysics Data System (ADS)

Damayanti, R.; Abdullah, A. G.; Purnama, W.; Nandiyanto, A. B. D.

2017-03-01

Data mining is one of the data processing techniques to collect information from a set of stored data. Every day the consumption of electricity load is recorded by Electrical Company, usually at intervals of 15 or 30 minutes. This paper uses a clustering technique, which is one of data mining techniques to analyse the electrical load profiles during 2014. The three methods of clustering techniques were compared, namely K-Means (KM), Fuzzy C-Means (FCM), and K-Means Harmonics (KHM). The result shows that KHM is the most appropriate method to classify the electrical load profile. The optimum number of clusters is determined using the Davies-Bouldin Index. By grouping the load profile, the demand of variation analysis and estimation of energy loss from the group of load profile with similar pattern can be done. From the group of electric load profile, it can be known cluster load factor and a range of cluster loss factor that can help to find the range of values of coefficients for the estimated loss of energy without performing load flow studies.

Human factors analysis of workstation design: Earth Radiation Budget Satellite Mission Operations Room

NASA Technical Reports Server (NTRS)

Stewart, L. J.; Murphy, E. D.; Mitchell, C. M.

1982-01-01

A human factors analysis addressed three related yet distinct issues within the area of workstation design for the Earth Radiation Budget Satellite (ERBS) mission operation room (MOR). The first issue, physical layout of the MOR, received the most intensive effort. It involved the positioning of clusters of equipment within the physical dimensions of the ERBS MOR. The second issue for analysis was comprised of several environmental concerns, such as lighting, furniture, and heating and ventilation systems. The third issue was component arrangement, involving the physical arrangement of individual components within clusters of consoles, e.g., a communications panel.

Korean immigrants' knowledge of heart attack symptoms and risk factors.

PubMed

Hwang, Seon Y; Ryan, Catherine J; Zerwic, Julie Johnson

2008-02-01

This study assessed the knowledge of heart attack symptoms and risk factors in a convenience sample of Korean immigrants. A total of 116 Korean immigrants in a Midwestern metropolitan area were recruited through Korean churches and markets. Knowledge was assessed using both open-ended questions and a structured questionnaire. Latent class cluster analysis and Chi-square tests were used to analyze the data. About 76% of the sample had at least one self-reported risk factor for cardiovascular disease. Using an open-ended question, the majority of subjects could only identify one symptom. In the structured questionnaire, subjects identified a mean of 5 out of 10 heart attack symptoms and a mean of 5 out of 9 heart attack risk factors. Latent class cluster analysis showed that subjects clustered into two groups for both risk factors and symptoms: a high knowledge group and a low knowledge group. Subjects who clustered into the risk factor low knowledge group (48%) were more likely than the risk factor high knowledge group to be older than 65 years, to have lower education, to not know to use 911 when a heart attack occurred, and to not have a family history of heart attack. Korean immigrants' knowledge of heart attack symptoms and risk factors was variable, ranging from high to very low. Education should be focused on those at highest risk for a heart attack, which includes the elderly and those with risk factors.

Symptom clusters and related factors in bladder cancer patients three months after radical cystectomy.

PubMed

Ren, Hongyan; Tang, Ping; Zhao, Qinghua; Ren, Guosheng

2017-08-23

To identify symptom distress and clusters in patients 3 months after radical cystectomy and to explore their potential predictors. A cross-sectional design was used to investigate 99 bladder cancer patients 3 months after radical cystectomy. Data were collected by demographic and disease characteristic questionnaires, the symptom experience scale of the M.D. Anderson symptom inventory, two additional symptoms specific to radical cystectomy, and the functional assessment of cancer therapy questionnaire. A factor analysis, stepwise regression, and correlation analysis were applied. Three symptom clusters were identified: fatigue-malaise, gastrointestinal, and psycho-urinary. Age, complication severity, albumin post-surgery (negative), orthotropic neobladder reconstruction, adjuvant chemotherapy and American Society of Anesthesiologists (ASA) scores were significant predictors of fatigue-malaise. Adjuvant chemotherapy, orthotropic neobladder reconstruction, female gender, ASA scores and albumin (negative) were significant predictors of gastrointestinal symptoms. Being unmarried, having a higher educational level and complication severity were significant predictors of psycho-urinary symptoms. The correlations between clusters and for each cluster with quality of life were significant, with the highest correlation observed between the psycho-urinary cluster and quality of life. Bladder cancer patients experience concurrent symptoms that appear to cluster and are significantly correlated with quality of life. Moreover, symptom clusters may be predicted by certain demographic and clinical characteristics.

[On measuring of factors influencing the complex need for cultural entertainments of the inhabitants in geriatric nursing homes (3rd information) (author's transl)].

PubMed

Kuhlmey, J; Lautsch, E

1980-01-01

In our 2. information on the investigation of the need for cultural entertainments of inhabitants in geriatric nursing homes we tested the influence of the factors age, sex, kind of work and during of stay in the geriatric nursing home singly and successively for each single indicator of this complex need. In this 3. information the influence of this four factors was investigated in these contradictory dependency on the indicators under synchronous consideration of their contradictory dependency. The contradictory dependency of the factors was presented by typisation (cluster analysis). As a result of the cluster analysis same classes arose--similar disposed inhabitants belong to same classes. The average coinage in this classes was obtained and differences were analysed by statistical methods multidimensional analysis of variance and analysis of discriminance).

Dimensions of temperament: an analysis.

PubMed

Lorr, M; Stefic, E C

1976-01-01

The TDOT recast into a single stimulus format was administered to 150 college Ss. A factor analysis of the items followed by an analysis of item clusters that define each factor indicated the presence of 14 dimensions. Of the 10 bipolar scales of the TDOT, 3 were confirmed as independent dimensions, and 5 were confirmed in part or split into unipolar factors.

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

Risk Profiles for Injurious Falls in People Over 60: A Population-Based Cohort Study

PubMed Central

Ek, Stina; Rizzuto, Debora; Fratiglioni, Laura; Johnell, Kristina; Xu, Weili

2018-01-01

Abstract Background Although falls in older adults are related to multiple risk factors, these factors have commonly been studied individually. We aimed to identify risk profiles for injurious falls in older adults by detecting clusters of established risk factors and quantifying their impact on fall risk. Methods Participants were 2,566 people, aged 60 years and older, from the population-based Swedish National Study on Aging and Care in Kungsholmen. Injurious falls was defined as hospitalization for or receipt of outpatient care because a fall. Cluster analysis was used to identify aggregation of possible risk factors including chronic diseases, fall-risk increasing drugs (FRIDs), physical and cognitive impairments, and lifestyle-related factors. Associations between the clusters and injurious falls over 3, 5, and 10 years were estimated using flexible parametric survival models. Results Five clusters were identified including: a “healthy”, a “well-functioning with multimorbidity”, a “well-functioning, with multimorbidity and high FRID consumption”, a “physically and cognitively impaired”, and a “disabled” cluster. The risk of injurious falls for all groups was significantly higher than for the first cluster of healthy individuals in the reference category. Hazard ratios (95% confidence intervals) ranged from 1.71 (1.02–2.66) for the second cluster to 12.67 (7.38–21.75) for the last cluster over 3 years of follow-up. The highest risk was observed in the last two clusters with high burden of physical and cognitive impairments. Conclusion Risk factors for injurious fall tend to aggregate, representing different levels of risk for falls. Our findings can be useful to tailor and prioritize clinical and public health interventions. PMID:28605455

Exploring syndrome differentiation using non-negative matrix factorization and cluster analysis in patients with atopic dermatitis.

PubMed

Yun, Younghee; Jung, Wonmo; Kim, Hyunho; Jang, Bo-Hyoung; Kim, Min-Hee; Noh, Jiseong; Ko, Seong-Gyu; Choi, Inhwa

2017-08-01

Syndrome differentiation (SD) results in a diagnostic conclusion based on a cluster of concurrent symptoms and signs, including pulse form and tongue color. In Korea, there is a strong interest in the standardization of Traditional Medicine (TM). In order to standardize TM treatment, standardization of SD should be given priority. The aim of this study was to explore the SD, or symptom clusters, of patients with atopic dermatitis (AD) using non-negative factorization methods and k-means clustering analysis. We screened 80 patients and enrolled 73 eligible patients. One TM dermatologist evaluated the symptoms/signs using an existing clinical dataset from patients with AD. This dataset was designed to collect 15 dermatologic and 18 systemic symptoms/signs associated with AD. Non-negative matrix factorization was used to decompose the original data into a matrix with three features and a weight matrix. The point of intersection of the three coordinates from each patient was placed in three-dimensional space. With five clusters, the silhouette score reached 0.484, and this was the best silhouette score obtained from two to nine clusters. Patients were clustered according to the varying severity of concurrent symptoms/signs. Through the distribution of the null hypothesis generated by 10,000 permutation tests, we found significant cluster-specific symptoms/signs from the confidence intervals in the upper and lower 2.5% of the distribution. Patients in each cluster showed differences in symptoms/signs and severity. In a clinical situation, SD and treatment are based on the practitioners' observations and clinical experience. SD, identified through informatics, can contribute to development of standardized, objective, and consistent SD for each disease. Copyright © 2017. Published by Elsevier Ltd.

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

Exploring the application of latent class cluster analysis for investigating pedestrian crash injury severities in Switzerland.

PubMed

Sasidharan, Lekshmi; Wu, Kun-Feng; Menendez, Monica

2015-12-01

One of the major challenges in traffic safety analyses is the heterogeneous nature of safety data, due to the sundry factors involved in it. This heterogeneity often leads to difficulties in interpreting results and conclusions due to unrevealed relationships. Understanding the underlying relationship between injury severities and influential factors is critical for the selection of appropriate safety countermeasures. A method commonly employed to address systematic heterogeneity is to focus on any subgroup of data based on the research purpose. However, this need not ensure homogeneity in the data. In this paper, latent class cluster analysis is applied to identify homogenous subgroups for a specific crash type-pedestrian crashes. The manuscript employs data from police reported pedestrian (2009-2012) crashes in Switzerland. The analyses demonstrate that dividing pedestrian severity data into seven clusters helps in reducing the systematic heterogeneity of the data and to understand the hidden relationships between crash severity levels and socio-demographic, environmental, vehicle, temporal, traffic factors, and main reason for the crash. The pedestrian crash injury severity models were developed for the whole data and individual clusters, and were compared using receiver operating characteristics curve, for which results favored clustering. Overall, the study suggests that latent class clustered regression approach is suitable for reducing heterogeneity and revealing important hidden relationships in traffic safety analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2015-01-01

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

Health in police officers: Role of risk factor clusters and police divisions.

PubMed

Habersaat, Stephanie A; Geiger, Ashley M; Abdellaoui, Sid; Wolf, Jutta M

2015-10-01

Law enforcement is a stressful occupation associated with significant health problems. To date, most studies have focused on one specific factor or one domain of risk factors (e.g., organizational, personal). However, it is more likely that specific combinations of risk factors are differentially health relevant and further, depend on the area of police work. A self-selected group of officers from the criminal, community, and emergency division (N = 84) of a Swiss state police department answered questionnaires assessing personal and organizational risk factors as well as mental and physical health indicators. In general, few differences were observed across divisions in terms of risk factors or health indicators. Cluster analysis of all risk factors established a high-risk and a low-risk cluster with significant links to all mental health outcomes. Risk cluster-by-division interactions revealed that, in the high-risk cluster, Emergency officers reported fewer physical symptoms, while community officers reported more posttraumatic stress symptoms. Criminal officers in the high-risk cluster tended to perceived more stress. Finally, perceived stress did not mediate the relationship between risk clusters and posttraumatic stress symptoms. In summary, our results support the notion that police officers are a heterogeneous population in terms of processes linking risk factors and health indicators. This heterogeneity thereby appeared to be more dependent on personal factors and individuals' perception of their own work conditions than division-specific work environments. Our findings further suggest that stress-reduction interventions that do not target job-relevant sources of stress may only show limited effectiveness in reducing health risks associated with police work. Copyright © 2015 Elsevier Ltd. All rights reserved.

Health in police officers: Role of risk factor clusters and police divisions

PubMed Central

Habersaat, Stephanie A.; Geiger, Ashley M.; Abdellaoui, Sid; Wolf, Jutta M.

2015-01-01

Objective Law enforcement is a stressful occupation associated with significant health problems. To date, most studies have focused on one specific factor or one domain of risk factors (e.g., organizational, personal). However, it is more likely that specific combinations of risk factors are differentially health relevant and further, depend on the area of police work. Methods A self-selected group of officers from the criminal, community, and emergency division (N = 84) of a Swiss state police department answered questionnaires assessing personal and organizational risk factors as well as mental and physical health indicators. Results In general, few differences were observed across divisions in terms of risk factors or health indicators. Cluster analysis of all risk factors established a high-risk and a low-risk cluster with significant links to all mental health outcomes. Risk cluster-by-division interactions revealed that, in the high-risk cluster, Emergency officers reported fewer physical symptoms, while community officers reported more posttraumatic stress symptoms. Criminal officers in the high-risk cluster tended to perceived more stress. Finally, perceived stress did not mediate the relationship between risk clusters and posttraumatic stress symptoms. Conclusion In summary, our results support the notion that police officers are a heterogeneous population in terms of processes linking risk factors and health indicators. This heterogeneity thereby appeared to be more dependent on personal factors and individuals' perception of their own work conditions than division-specific work environments. Our findings further suggest that stress-reduction interventions that do not target job-relevant sources of stress may only show limited effectiveness in reducing health risks associated with police work. PMID:26364008

The Network Structure of Human Personality According to the NEO-PI-R: Matching Network Community Structure to Factor Structure

PubMed Central

Goekoop, Rutger; Goekoop, Jaap G.; Scholte, H. Steven

2012-01-01

Introduction Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. Aim To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). Methods 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. Results At facet level, NCS showed a best match (96.2%) with a ‘confirmatory’ 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with ‘confirmatory’ 5-FS and ‘exploratory’ 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. Conclusion We present the first optimized network graph of personality traits according to the NEO-PI-R: a ‘Personality Web’. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network. PMID:23284713

The network structure of human personality according to the NEO-PI-R: matching network community structure to factor structure.

PubMed

Goekoop, Rutger; Goekoop, Jaap G; Scholte, H Steven

2012-01-01

Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. At facet level, NCS showed a best match (96.2%) with a 'confirmatory' 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with 'confirmatory' 5-FS and 'exploratory' 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. We present the first optimized network graph of personality traits according to the NEO-PI-R: a 'Personality Web'. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network.

A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002

USGS Publications Warehouse

Saman, D.M.; Cole, H.P.; Odoi, A.; Myers, M.L.; Carey, D.I.; Westneat, S.C.

2012-01-01

Background: Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns. Methods: A spatial statistical analysis using Kulldorff's spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns. Results: The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55) and 10 counties in eastern Kentucky (RR = 1.97). Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002) and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001). Conclusions: This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions) with the intention of reducing tractor overturns in the highest risk counties in Kentucky. ?? 2012 Saman et al.

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

PubMed

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

2016-12-30

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

Conceptions of Memorizing and Understanding in Learning, and Self-Efficacy Held by University Biology Majors

NASA Astrophysics Data System (ADS)

Lin, Tzu-Chiang; Liang, Jyh-Chong; Tsai, Chin-Chung

2015-02-01

This study aims to explore Taiwanese university students' conceptions of learning biology as memorizing or as understanding, and their self-efficacy. To this end, two questionnaires were utilized to survey 293 Taiwanese university students with biology-related majors. A questionnaire for measuring students' conceptions of memorizing and understanding was validated through an exploratory factor analysis of participants' responses. As for the questionnaire regarding the students' biology learning self-efficacy (BLSE), an exploratory factor analysis revealed a total of four factors including higher-order cognitive skills (BLSE-HC), everyday application (BLSE-EA), science communication (BLSE-SC), and practical works (BLSE-PW). The results of the cluster analysis according to the participants' conceptions of learning biology indicated that students in the two major clusters either viewed learning biology as understanding or possessed mixed-conceptions of memorizing and understanding. The students in the third cluster mainly focused on memorizing in their learning while the students in the fourth cluster showed less agreement with both conceptions of memorizing and understanding. This study further revealed that the conception of learning as understanding was positively associated with the BLSE of university students with biology-related majors. However, the conception of learning as memorizing may foster students' BLSE only when such a notion co-exists with the conception of learning with understanding.

Detecting Outliers in Factor Analysis Using the Forward Search Algorithm

ERIC Educational Resources Information Center

Mavridis, Dimitris; Moustaki, Irini

2008-01-01

In this article we extend and implement the forward search algorithm for identifying atypical subjects/observations in factor analysis models. The forward search has been mainly developed for detecting aberrant observations in regression models (Atkinson, 1994) and in multivariate methods such as cluster and discriminant analysis (Atkinson, Riani,…

Customized recommendations for production management clusters of North American automatic milking systems.

PubMed

Tremblay, Marlène; Hess, Justin P; Christenson, Brock M; McIntyre, Kolby K; Smink, Ben; van der Kamp, Arjen J; de Jong, Lisanne G; Döpfer, Dörte

2016-07-01

Automatic milking systems (AMS) are implemented in a variety of situations and environments. Consequently, there is a need to characterize individual farming practices and regional challenges to streamline management advice and objectives for producers. Benchmarking is often used in the dairy industry to compare farms by computing percentile ranks of the production values of groups of farms. Grouping for conventional benchmarking is commonly limited to the use of a few factors such as farms' geographic region or breed of cattle. We hypothesized that herds' production data and management information could be clustered in a meaningful way using cluster analysis and that this clustering approach would yield better peer groups of farms than benchmarking methods based on criteria such as country, region, breed, or breed and region. By applying mixed latent-class model-based cluster analysis to 529 North American AMS dairy farms with respect to 18 significant risk factors, 6 clusters were identified. Each cluster (i.e., peer group) represented unique management styles, challenges, and production patterns. When compared with peer groups based on criteria similar to the conventional benchmarking standards, the 6 clusters better predicted milk produced (kilograms) per robot per day. Each cluster represented a unique management and production pattern that requires specialized advice. For example, cluster 1 farms were those that recently installed AMS robots, whereas cluster 3 farms (the most northern farms) fed high amounts of concentrates through the robot to compensate for low-energy feed in the bunk. In addition to general recommendations for farms within a cluster, individual farms can generate their own specific goals by comparing themselves to farms within their cluster. This is very comparable to benchmarking but adds the specific characteristics of the peer group, resulting in better farm management advice. The improvement that cluster analysis allows for is characterized by the multivariable approach and the fact that comparisons between production units can be accomplished within a cluster and between clusters as a choice. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Farm, household, and farmer characteristics associated with changes in management practices and technology adoption among dairy smallholders.

PubMed

Martínez-García, Carlos Galdino; Ugoretz, Sarah Janes; Arriaga-Jordán, Carlos Manuel; Wattiaux, Michel André

2015-02-01

This study explored whether technology adoption and changes in management practices were associated with farm structure, household, and farmer characteristics and to identify processes that may foster productivity and sustainability of small-scale dairy farming in the central highlands of Mexico. Factor analysis of survey data from 44 smallholders identified three factors-related to farm size, farmer's engagement, and household structure-that explained 70 % of cumulative variance. The subsequent hierarchical cluster analysis yielded three clusters. Cluster 1 included the most senior farmers with fewest years of education but greatest years of experience. Cluster 2 included farmers who reported access to extension, cooperative services, and more management changes. Cluster 2 obtained 25 and 35 % more milk than farmers in clusters 1 and 3, respectively. Cluster 3 included the youngest farmers, with most years of education and greatest availability of family labor. Access to a network and membership in a community of peers appeared as important contributors to success. Smallholders gravitated towards easy to implement technologies that have immediate benefits. Nonusers of high investment technologies found them unaffordable because of cost, insufficient farm size, and lack of knowledge or reliable electricity. Multivariate analysis may be a useful tool in planning extension activities and organizing channels of communication to effectively target farmers with varying needs, constraints, and motivations for change and in identifying farmers who may exemplify models of change for others who manage farms that are structurally similar but performing at a lower level.

Identifying and Assessing Interesting Subgroups in a Heterogeneous Population.

PubMed

Lee, Woojoo; Alexeyenko, Andrey; Pernemalm, Maria; Guegan, Justine; Dessen, Philippe; Lazar, Vladimir; Lehtiö, Janne; Pawitan, Yudi

2015-01-01

Biological heterogeneity is common in many diseases and it is often the reason for therapeutic failures. Thus, there is great interest in classifying a disease into subtypes that have clinical significance in terms of prognosis or therapy response. One of the most popular methods to uncover unrecognized subtypes is cluster analysis. However, classical clustering methods such as k-means clustering or hierarchical clustering are not guaranteed to produce clinically interesting subtypes. This could be because the main statistical variability--the basis of cluster generation--is dominated by genes not associated with the clinical phenotype of interest. Furthermore, a strong prognostic factor might be relevant for a certain subgroup but not for the whole population; thus an analysis of the whole sample may not reveal this prognostic factor. To address these problems we investigate methods to identify and assess clinically interesting subgroups in a heterogeneous population. The identification step uses a clustering algorithm and to assess significance we use a false discovery rate- (FDR-) based measure. Under the heterogeneity condition the standard FDR estimate is shown to overestimate the true FDR value, but this is remedied by an improved FDR estimation procedure. As illustrations, two real data examples from gene expression studies of lung cancer are provided.

The Influence of the Host Plant Is the Major Ecological Determinant of the Presence of Nitrogen-Fixing Root Nodule Symbiont Cluster II Frankia Species in Soil

PubMed Central

Battenberg, Kai; Wren, Jannah A.; Hillman, Janell; Edwards, Joseph; Huang, Liujing

2016-01-01

ABSTRACT The actinobacterial genus Frankia establishes nitrogen-fixing root nodule symbioses with specific hosts within the nitrogen-fixing plant clade. Of four genetically distinct subgroups of Frankia, cluster I, II, and III strains are capable of forming effective nitrogen-fixing symbiotic associations, while cluster IV strains generally do not. Cluster II Frankia strains have rarely been detected in soil devoid of host plants, unlike cluster I or III strains, suggesting a stronger association with their host. To investigate the degree of host influence, we characterized the cluster II Frankia strain distribution in rhizosphere soil in three locations in northern California. The presence/absence of cluster II Frankia strains at a given site correlated significantly with the presence/absence of host plants on the site, as determined by glutamine synthetase (glnA) gene sequence analysis, and by microbiome analysis (16S rRNA gene) of a subset of host/nonhost rhizosphere soils. However, the distribution of cluster II Frankia strains was not significantly affected by other potential determinants such as host-plant species, geographical location, climate, soil pH, or soil type. Rhizosphere soil microbiome analysis showed that cluster II Frankia strains occupied only a minute fraction of the microbiome even in the host-plant-present site and further revealed no statistically significant difference in the α-diversity or in the microbiome composition between the host-plant-present or -absent sites. Taken together, these data suggest that host plants provide a factor that is specific for cluster II Frankia strains, not a general growth-promoting factor. Further, the factor accumulates or is transported at the site level, i.e., beyond the host rhizosphere. IMPORTANCE Biological nitrogen fixation is a bacterial process that accounts for a major fraction of net new nitrogen input in terrestrial ecosystems. Transfer of fixed nitrogen to plant biomass is especially efficient via root nodule symbioses, which represent evolutionarily and ecologically specialized mutualistic associations. Frankia spp. (Actinobacteria), especially cluster II Frankia spp., have an extremely broad host range, yet comparatively little is known about the soil ecology of these organisms in relation to the host plants and their rhizosphere microbiomes. This study reveals a strong influence of the host plant on soil distribution of cluster II Frankia spp. PMID:27795313

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.

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.

The effect of cognitive appraisal for stressors on the oral health-related QOL of dry mouth patients.

PubMed

Matsuoka, Hirofumi; Chiba, Itsuo; Sakano, Yuji; Saito, Ichiro; Abiko, Yoshihiro

2014-01-01

Dry mouth is very common symptom, and psychological factors have an influence on this symptom. Although the influence of emotional factor related to patients with oral dryness has been examined in previous studies, the cognitive factors have not been examined thus far. The purpose of this study was to examine the influence of cognitive factors on patients with oral dryness. The participants were 106 patients complaining of oral dryness. They were required to complete a questionnaire measuring subjective oral dryness, oral-related QOL, cognition for stressors, and mood state. Correlational analyses revealed that OHIP-14 is significantly related to oral dryness, appraisal for effect, appraisal for threat, and commitment. These correlations were maintained even after controlling for the influence of depression and anxiety. Using oral dryness, appraisal for effect, appraisal for threat, and commitment, cluster analysis was done and three clusters (cluster-1, severe oral dryness; cluster-2, positive cognitive style: cluster-3, negative cognitive style) were extracted. The results of ANOVA showed that the group with severe oral dryness (cluster-1) had a significantly higher score on OHIP-14 than the other two groups. There was no significant difference between the groups with positive (cluster-2) and negative (cluster-3) cognitive style. Although the group of patients with positive cognitive style complained of more severe oral dryness than the group with negative cognitive style, no significant difference was observed between these two groups in OHIP-14. These results indicate that cognitive factors would be a useful therapeutic target for the improvement of the oral-related QOL of patients with oral dryness.

Tobacco, Marijuana, and Alcohol Use in University Students: A Cluster Analysis

PubMed Central

Primack, Brian A.; Kim, Kevin H.; Shensa, Ariel; Sidani, Jaime E.; Barnett, Tracey E.; Switzer, Galen E.

2012-01-01

Objective Segmentation of populations may facilitate development of targeted substance abuse prevention programs. We aimed to partition a national sample of university students according to profiles based on substance use. Participants We used 2008–2009 data from the National College Health Assessment from the American College Health Association. Our sample consisted of 111,245 individuals from 158 institutions. Method We partitioned the sample using cluster analysis according to current substance use behaviors. We examined the association of cluster membership with individual and institutional characteristics. Results Cluster analysis yielded six distinct clusters. Three individual factors—gender, year in school, and fraternity/sorority membership—were the most strongly associated with cluster membership. Conclusions In a large sample of university students, we were able to identify six distinct patterns of substance abuse. It may be valuable to target specific populations of college-aged substance users based on individual factors. However, comprehensive intervention will require a multifaceted approach. PMID:22686360

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

PubMed

Spanos, Thomas; Ene, Antoaneta; Simeonova, Pavlina

2015-01-01

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

Copy number gain at 8q12.1-q22.1 is associated with a malignant tumor phenotype in salivary gland myoepitheliomas.

PubMed

Vékony, Hedy; Röser, Kerstin; Löning, Thomas; Ylstra, Bauke; Meijer, Gerrit A; van Wieringen, Wessel N; van de Wiel, Mark A; Carvalho, Beatriz; Kok, Klaas; Leemans, C René; van der Waal, Isaäc; Bloemena, Elisabeth

2009-02-01

Salivary gland myoepithelial tumors are relatively uncommon tumors with an unpredictable clinical course. More knowledge about their genetic profiles is necessary to identify novel predictors of disease. In this study, we subjected 27 primary tumors (15 myoepitheliomas and 12 myoepithelial carcinomas) to genome-wide microarray-based comparative genomic hybridization (array CGH). We set out to delineate known chromosomal aberrations in more detail and to unravel chromosomal differences between benign myoepitheliomas and myoepithelial carcinomas. Patterns of DNA copy number aberrations were analyzed by unsupervised hierarchical cluster analysis. Both benign and malignant tumors revealed a limited amount of chromosomal alterations (median of 5 and 7.5, respectively). In both tumor groups, high frequency gains (> or =20%) were found mainly at loci of growth factors and growth factor receptors (e.g., PDGF, FGF(R)s, and EGFR). In myoepitheliomas, high frequency losses (> or =20%) were detected at regions of proto-cadherins. Cluster analysis of the array CGH data identified three clusters. Differential copy numbers on chromosome arm 8q and chromosome 17 set the clusters apart. Cluster 1 contained a mixture of the two phenotypes (n = 10), cluster 2 included mostly benign tumors (n = 10), and cluster 3 only contained carcinomas (n = 7). Supervised analysis between malignant and benign tumors revealed a 36 Mbp-region at 8q being more frequently gained in malignant tumors (P = 0.007, FDR = 0.05). This is the first study investigating genomic differences between benign and malignant myoepithelial tumors of the salivary glands at a genomic level. Both unsupervised and supervised analysis of the genomic profiles revealed chromosome arm 8q to be involved in the malignant phenotype of salivary gland myoepitheliomas.

Coping Patterns of African American Adolescents: A Confirmatory Factor Analysis and Cluster Analysis of the Children's Coping Strategies Checklist

ERIC Educational Resources Information Center

Gaylord-Harden, Noni K.; Gipson, Polly; Mance, GiShawn; Grant, Kathryn E.

2008-01-01

The current study examined patterns of coping strategies in a sample of 497 low-income urban African American adolescents (mean age = 12.61 years). Results of confirmatory factor analysis indicated that the 4-factor structure of the Children's Coping Strategies Checklist (T. S. Ayers, I. N. Sandler, S. G. West, & M. W. Roosa, 1996) was not…

Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010.

PubMed

Jentsch, Franziska; Allen, Jennifer; Fuchs, Judith; von der Lippe, Elena

2017-04-04

Modifiable health risk factors (MHRFs) significantly affect morbidity and mortality rates and frequently occur in specific combinations or risk clusters. Using five MHRFs (smoking, high-risk alcohol consumption, physical inactivity, low intake of fruits and vegetables, and obesity) this study investigates the extent to which risk clusters are observed in a representative sample of women aged 65 and older in Germany. Additionally, the structural composition of the clusters is systematically compared with data and findings from other countries. A pooled data set of Germany's representative cross-sectional surveys GEDA09 and GEDA10 was used. The cohort comprised 4,617 women aged 65 and older. Specific risk clusters based on five MHRFs are identified, using hierarchical cluster analysis. The MHRFs were defined as current smoking (daily or occasionally), risk alcohol consumption (according to the Alcohol Use Disorders Identification Test, a sum score of 4 or more points), physical inactivity (less active than 5 days per week for at least 30 min and lack of sports-related activity in the last three months), low intake of fruits and vegetables (less than one serving of fruits and one of vegetables per day), and obesity (a body mass index equal to or greater than 30). A total of 4,292 cases with full information on these factors are included in the cluster analysis. Extended analyses were also performed to include the number of chronic diseases by age and socioeconomic status of group members. A total of seven risk clusters were identified. In a comparison with data from international studies, the seven risk clusters were found to be stable with a high degree of structural equivalency. Evidence of the stability of risk clusters across various study populations provides a useful starting point for long-term targeted health interventions. The structural clusters provide information through which various MHRFs can be evaluated simultaneously.

Identification of the Main Regulator Responsible for Synthesis of the Typical Yellow Pigment Produced by Trichoderma reesei

PubMed Central

Derntl, Christian; Rassinger, Alice; Srebotnik, Ewald; Mach, Robert L.

2016-01-01

ABSTRACT The industrially used ascomycete Trichoderma reesei secretes a typical yellow pigment during cultivation, while other Trichoderma species do not. A comparative genomic analysis suggested that a putative secondary metabolism cluster, containing two polyketide-synthase encoding genes, is responsible for the yellow pigment synthesis. This cluster is conserved in a set of rather distantly related fungi, including Acremonium chrysogenum and Penicillium chrysogenum. In an attempt to silence the cluster in T. reesei, two genes of the cluster encoding transcription factors were individually deleted. For a complete genetic proof-of-function, the genes were reinserted into the genomes of the respective deletion strains. The deletion of the first transcription factor (termed yellow pigment regulator 1 [Ypr1]) resulted in the full abolishment of the yellow pigment formation and the expression of most genes of this cluster. A comparative high-pressure liquid chromatography (HPLC) analysis of supernatants of the ypr1 deletion and its parent strain suggested the presence of several yellow compounds in T. reesei that are all derived from the same cluster. A subsequent gas chromatography/mass spectrometry analysis strongly indicated the presence of sorbicillin in the major HPLC peak. The presence of the second transcription factor, termed yellow pigment regulator 2 (Ypr2), reduces the yellow pigment formation and the expression of most cluster genes, including the gene encoding the activator Ypr1. IMPORTANCE Trichoderma reesei is used for industry-scale production of carbohydrate-active enzymes. During growth, it secretes a typical yellow pigment. This is not favorable for industrial enzyme production because it makes the downstream process more complicated and thus increases operating costs. In this study, we demonstrate which regulators influence the synthesis of the yellow pigment. Based on these data, we also provide indication as to which genes are under the control of these regulators and are finally responsible for the biosynthesis of the yellow pigment. These genes are organized in a cluster that is also found in other industrially relevant fungi, such as the two antibiotic producers Penicillium chrysogenum and Acremonium chrysogenum. The targeted manipulation of a secondary metabolism cluster is an important option for any biotechnologically applied microorganism. PMID:27520818

Classification of municipal occupations.

PubMed

Ilmarinen, J; Suurnäkki, T; Nygård, C H; Landau, K

1991-01-01

Eighty-eight job titles were analyzed with the "ergonomic job analysis procedure" [Arbeitswissenschaftliche Erhebungsverfahren zur Tätigkeits-analyse abbreviated (AET) in German]. The objective was to classify the wide range of municipal jobs into homogeneous groups according to job demand and to provide better possibilities to study the relationships between work and health among the aging municipal working population. Altogether 216 items were classified. First, a hierarchical cluster analysis was made, and a dendrogram of the analyzed job titles was drawn. Second, a profile analysis was done in which the single items were grouped into 39 sum items, and a graphic profile was drawn. Finally, the stress factors were listed and drawn in ranking order. The cluster analysis formed 13 groups. Groups exposed to the highest stress factor level were kitchen supervisors, dentists, and physicians. More than 10 stress factors (greater than 50% of the maximum) were found in nursing, administration, installation, transport, and technical supervision.

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

PubMed

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

2015-03-15

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

Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering.

PubMed

He, Zhaoshui; Xie, Shengli; Zdunek, Rafal; Zhou, Guoxu; Cichocki, Andrzej

2011-12-01

Nonnegative matrix factorization (NMF) is an unsupervised learning method useful in various applications including image processing and semantic analysis of documents. This paper focuses on symmetric NMF (SNMF), which is a special case of NMF decomposition. Three parallel multiplicative update algorithms using level 3 basic linear algebra subprograms directly are developed for this problem. First, by minimizing the Euclidean distance, a multiplicative update algorithm is proposed, and its convergence under mild conditions is proved. Based on it, we further propose another two fast parallel methods: α-SNMF and β -SNMF algorithms. All of them are easy to implement. These algorithms are applied to probabilistic clustering. We demonstrate their effectiveness for facial image clustering, document categorization, and pattern clustering in gene expression.

Influence of diet, menstruation and genetic factors on iron status: a cross-sectional study in Spanish women of childbearing age.

PubMed

Blanco-Rojo, Ruth; Toxqui, Laura; López-Parra, Ana M; Baeza-Richer, Carlos; Pérez-Granados, Ana M; Arroyo-Pardo, Eduardo; Vaquero, M Pilar

2014-03-06

The aim of this study was to investigate the combined influence of diet, menstruation and genetic factors on iron status in Spanish menstruating women (n = 142). Dietary intake was assessed by a 72-h detailed dietary report and menstrual blood loss by a questionnaire, to determine a Menstrual Blood Loss Coefficient (MBLC). Five selected SNPs were genotyped: rs3811647, rs1799852 (Tf gene); rs1375515 (CACNA2D3 gene); and rs1800562 and rs1799945 (HFE gene, mutations C282Y and H63D, respectively). Iron biomarkers were determined and cluster analysis was performed. Differences among clusters in dietary intake, menstrual blood loss parameters and genotype frequencies distribution were studied. A categorical regression was performed to identify factors associated with cluster belonging. Three clusters were identified: women with poor iron status close to developing iron deficiency anemia (Cluster 1, n = 26); women with mild iron deficiency (Cluster 2, n = 59) and women with normal iron status (Cluster 3, n = 57). Three independent factors, red meat consumption, MBLC and mutation C282Y, were included in the model that better explained cluster belonging (R2 = 0.142, p < 0.001). In conclusion, the combination of high red meat consumption, low menstrual blood loss and the HFE C282Y mutation may protect from iron deficiency in women of childbearing age. These findings could be useful to implement adequate strategies to prevent iron deficiency anemia.

Recurrent-neural-network-based Boolean factor analysis and its application to word clustering.

PubMed

Frolov, Alexander A; Husek, Dusan; Polyakov, Pavel Yu

2009-07-01

The objective of this paper is to introduce a neural-network-based algorithm for word clustering as an extension of the neural-network-based Boolean factor analysis algorithm (Frolov , 2007). It is shown that this extended algorithm supports even the more complex model of signals that are supposed to be related to textual documents. It is hypothesized that every topic in textual data is characterized by a set of words which coherently appear in documents dedicated to a given topic. The appearance of each word in a document is coded by the activity of a particular neuron. In accordance with the Hebbian learning rule implemented in the network, sets of coherently appearing words (treated as factors) create tightly connected groups of neurons, hence, revealing them as attractors of the network dynamics. The found factors are eliminated from the network memory by the Hebbian unlearning rule facilitating the search of other factors. Topics related to the found sets of words can be identified based on the words' semantics. To make the method complete, a special technique based on a Bayesian procedure has been developed for the following purposes: first, to provide a complete description of factors in terms of component probability, and second, to enhance the accuracy of classification of signals to determine whether it contains the factor. Since it is assumed that every word may possibly contribute to several topics, the proposed method might be related to the method of fuzzy clustering. In this paper, we show that the results of Boolean factor analysis and fuzzy clustering are not contradictory, but complementary. To demonstrate the capabilities of this attempt, the method is applied to two types of textual data on neural networks in two different languages. The obtained topics and corresponding words are at a good level of agreement despite the fact that identical topics in Russian and English conferences contain different sets of keywords.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010.

PubMed

Zulu, Leo C; Kalipeni, Ezekiel; Johannes, Eliza

2014-05-23

Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi's estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across 'sub-epidemics' while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV "hotspots" clustered among eleven southern districts/cities while a "coldspot" captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010

PubMed Central

2014-01-01

Background Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi’s estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Methods Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Results Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across ‘sub-epidemics’ while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV “hotspots” clustered among eleven southern districts/cities while a “coldspot” captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Conclusions Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale. PMID:24886573

Cluster Analysis of Adolescent Blogs

ERIC Educational Resources Information Center

Liu, Eric Zhi-Feng; Lin, Chun-Hung; Chen, Feng-Yi; Peng, Ping-Chuan

2012-01-01

Emerging web applications and networking systems such as blogs have become popular, and they offer unique opportunities and environments for learners, especially for adolescent learners. This study attempts to explore the writing styles and genres used by adolescents in their blogs by employing content, factor, and cluster analyses. Factor…

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

Transcriptomic analysis of neuregulin-1 regulated genes following ischemic stroke by computational identification of promoter binding sites: A role for the ETS-1 transcription factor.

PubMed

Surles-Zeigler, Monique C; Li, Yonggang; Distel, Timothy J; Omotayo, Hakeem; Ge, Shaokui; Ford, Byron D

2018-01-01

Ischemic stroke is a major cause of mortality in the United States. We previously showed that neuregulin-1 (NRG1) was neuroprotective in rat models of ischemic stroke. We used gene expression profiling to understand the early cellular and molecular mechanisms of NRG1's effects after the induction of ischemia. Ischemic stroke was induced by middle cerebral artery occlusion (MCAO). Rats were allocated to 3 groups: (1) control, (2) MCAO and (3) MCAO + NRG1. Cortical brain tissues were collected three hours following MCAO and NRG1 treatment and subjected to microarray analysis. Data and statistical analyses were performed using R/Bioconductor platform alongside Genesis, Ingenuity Pathway Analysis and Enrichr software packages. There were 2693 genes differentially regulated following ischemia and NRG1 treatment. These genes were organized by expression patterns into clusters using a K-means clustering algorithm. We further analyzed genes in clusters where ischemia altered gene expression, which was reversed by NRG1 (clusters 4 and 10). NRG1, IRS1, OPA3, and POU6F1 were central linking (node) genes in cluster 4. Conserved Transcription Factor Binding Site Finder (CONFAC) identified ETS-1 as a potential transcriptional regulator of NRG1 suppressed genes following ischemia. A transcription factor activity array showed that ETS-1 activity was increased 2-fold, 3 hours following ischemia and this activity was attenuated by NRG1. These findings reveal key early transcriptional mechanisms associated with neuroprotection by NRG1 in the ischemic penumbra.

A time-series approach for clustering farms based on slaughterhouse health aberration data.

PubMed

Hulsegge, B; de Greef, K H

2018-05-01

A large amount of data is collected routinely in meat inspection in pig slaughterhouses. A time series clustering approach is presented and applied that groups farms based on similar statistical characteristics of meat inspection data over time. A three step characteristic-based clustering approach was used from the idea that the data contain more info than the incidence figures. A stratified subset containing 511,645 pigs was derived as a study set from 3.5 years of meat inspection data. The monthly averages of incidence of pleuritis and of pneumonia of 44 Dutch farms (delivering 5149 batches to 2 pig slaughterhouses) were subjected to 1) derivation of farm level data characteristics 2) factor analysis and 3) clustering into groups of farms. The characteristic-based clustering was able to cluster farms for both lung aberrations. Three groups of data characteristics were informative, describing incidence, time pattern and degree of autocorrelation. The consistency of clustering similar farms was confirmed by repetition of the analysis in a larger dataset. The robustness of the clustering was tested on a substantially extended dataset. This confirmed the earlier results, three data distribution aspects make up the majority of distinction between groups of farms and in these groups (clusters) the majority of the farms was allocated comparable to the earlier allocation (75% and 62% for pleuritis and pneumonia, respectively). The difference between pleuritis and pneumonia in their seasonal dependency was confirmed, supporting the biological relevance of the clustering. Comparison of the identified clusters of statistically comparable farms can be used to detect farm level risk factors causing the health aberrations beyond comparison on disease incidence and trend alone. Copyright © 2018 Elsevier B.V. All rights reserved.

Cosmology with the largest galaxy cluster surveys: going beyond Fisher matrix forecasts

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

Khedekar, Satej; Majumdar, Subhabrata, E-mail: satej@mpa-garching.mpg.de, E-mail: subha@tifr.res.in

2013-02-01

We make the first detailed MCMC likelihood study of cosmological constraints that are expected from some of the largest, ongoing and proposed, cluster surveys in different wave-bands and compare the estimates to the prevalent Fisher matrix forecasts. Mock catalogs of cluster counts expected from the surveys — eROSITA, WFXT, RCS2, DES and Planck, along with a mock dataset of follow-up mass calibrations are analyzed for this purpose. A fair agreement between MCMC and Fisher results is found only in the case of minimal models. However, for many cases, the marginalized constraints obtained from Fisher and MCMC methods can differ bymore » factors of 30-100%. The discrepancy can be alarmingly large for a time dependent dark energy equation of state, w(a); the Fisher methods are seen to under-estimate the constraints by as much as a factor of 4-5. Typically, Fisher estimates become more and more inappropriate as we move away from ΛCDM, to a constant-w dark energy to varying-w dark energy cosmologies. Fisher analysis, also, predicts incorrect parameter degeneracies. There are noticeable offsets in the likelihood contours obtained from Fisher methods that is caused due to an asymmetry in the posterior likelihood distribution as seen through a MCMC analysis. From the point of mass-calibration uncertainties, a high value of unknown scatter about the mean mass-observable relation, and its redshift dependence, is seen to have large degeneracies with the cosmological parameters σ{sub 8} and w(a) and can degrade the cosmological constraints considerably. We find that the addition of mass-calibrated cluster datasets can improve dark energy and σ{sub 8} constraints by factors of 2-3 from what can be obtained from CMB+SNe+BAO only . Finally, we show that a joint analysis of datasets of two (or more) different cluster surveys would significantly tighten cosmological constraints from using clusters only. Since, details of future cluster surveys are still being planned, we emphasize that optimal survey design must be done using MCMC analysis rather than Fisher forecasting.« less

Identifying and Assessing Interesting Subgroups in a Heterogeneous Population

PubMed Central

Lee, Woojoo; Alexeyenko, Andrey; Pernemalm, Maria; Guegan, Justine; Dessen, Philippe; Lazar, Vladimir; Lehtiö, Janne; Pawitan, Yudi

2015-01-01

Biological heterogeneity is common in many diseases and it is often the reason for therapeutic failures. Thus, there is great interest in classifying a disease into subtypes that have clinical significance in terms of prognosis or therapy response. One of the most popular methods to uncover unrecognized subtypes is cluster analysis. However, classical clustering methods such as k-means clustering or hierarchical clustering are not guaranteed to produce clinically interesting subtypes. This could be because the main statistical variability—the basis of cluster generation—is dominated by genes not associated with the clinical phenotype of interest. Furthermore, a strong prognostic factor might be relevant for a certain subgroup but not for the whole population; thus an analysis of the whole sample may not reveal this prognostic factor. To address these problems we investigate methods to identify and assess clinically interesting subgroups in a heterogeneous population. The identification step uses a clustering algorithm and to assess significance we use a false discovery rate- (FDR-) based measure. Under the heterogeneity condition the standard FDR estimate is shown to overestimate the true FDR value, but this is remedied by an improved FDR estimation procedure. As illustrations, two real data examples from gene expression studies of lung cancer are provided. PMID:26339613

A Cluster Analysis Typology of Suicide in the United States Air Force

DTIC Science & Technology

2011-08-01

theorists such as Sigmund Freud , Edwin Shneidman and other suicidologists. Typologies: Psychoanalytic. In contrast to Durkheim’s theory and its emphasis...on societal factors, many early psychological explanations of suicide were rooted in Sigmund Freud’s psychodynamic theory. Freud wrote of two...The basic writings of Sigmund Freud (pp. 35-178). New York: Random House. Garson, G. D. (2009). Cluster analysis. Retrieved November, 1, 2009 from

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

Phylodynamic Analysis Reveals CRF01_AE Dissemination between Japan and Neighboring Asian Countries and the Role of Intravenous Drug Use in Transmission

PubMed Central

Shiino, Teiichiro; Hattori, Junko; Yokomaku, Yoshiyuki; Iwatani, Yasumasa; Sugiura, Wataru

2014-01-01

Background One major circulating HIV-1 subtype in Southeast Asian countries is CRF01_AE, but little is known about its epidemiology in Japan. We conducted a molecular phylodynamic study of patients newly diagnosed with CRF01_AE from 2003 to 2010. Methods Plasma samples from patients registered in Japanese Drug Resistance HIV-1 Surveillance Network were analyzed for protease-reverse transcriptase sequences; all sequences undergo subtyping and phylogenetic analysis using distance-matrix-based, maximum likelihood and Bayesian coalescent Markov Chain Monte Carlo (MCMC) phylogenetic inferences. Transmission clusters were identified using interior branch test and depth-first searches for sub-tree partitions. Times of most recent common ancestor (tMRCAs) of significant clusters were estimated using Bayesian MCMC analysis. Results Among 3618 patient registered in our network, 243 were infected with CRF01_AE. The majority of individuals with CRF01_AE were Japanese, predominantly male, and reported heterosexual contact as their risk factor. We found 5 large clusters with ≥5 members and 25 small clusters consisting of pairs of individuals with highly related CRF01_AE strains. The earliest cluster showed a tMRCA of 1996, and consisted of individuals with their known risk as heterosexual contacts. The other four large clusters showed later tMRCAs between 2000 and 2002 with members including intravenous drug users (IVDU) and non-Japanese, but not men who have sex with men (MSM). In contrast, small clusters included a high frequency of individuals reporting MSM risk factors. Phylogenetic analysis also showed that some individuals infected with HIV strains spread in East and South-eastern Asian countries. Conclusions Introduction of CRF01_AE viruses into Japan is estimated to have occurred in the 1990s. CFR01_AE spread via heterosexual behavior, then among persons connected with non-Japanese, IVDU, and MSM. Phylogenetic analysis demonstrated that some viral variants are largely restricted to Japan, while others have a broad geographic distribution. PMID:25025900

The effect of cognitive appraisal for stressors on the oral health-related QOL of dry mouth patients

PubMed Central

2014-01-01

Background Dry mouth is very common symptom, and psychological factors have an influence on this symptom. Although the influence of emotional factor related to patients with oral dryness has been examined in previous studies, the cognitive factors have not been examined thus far. Objective The purpose of this study was to examine the influence of cognitive factors on patients with oral dryness. Methods The participants were 106 patients complaining of oral dryness. They were required to complete a questionnaire measuring subjective oral dryness, oral-related QOL, cognition for stressors, and mood state. Results Correlational analyses revealed that OHIP-14 is significantly related to oral dryness, appraisal for effect, appraisal for threat, and commitment. These correlations were maintained even after controlling for the influence of depression and anxiety. Using oral dryness, appraisal for effect, appraisal for threat, and commitment, cluster analysis was done and three clusters (cluster-1, severe oral dryness; cluster-2, positive cognitive style: cluster-3, negative cognitive style) were extracted. The results of ANOVA showed that the group with severe oral dryness (cluster-1) had a significantly higher score on OHIP-14 than the other two groups. There was no significant difference between the groups with positive (cluster-2) and negative (cluster-3) cognitive style. Conclusion Although the group of patients with positive cognitive style complained of more severe oral dryness than the group with negative cognitive style, no significant difference was observed between these two groups in OHIP-14. These results indicate that cognitive factors would be a useful therapeutic target for the improvement of the oral-related QOL of patients with oral dryness. PMID:26019720

Sputum neutrophil counts are associated with more severe asthma phenotypes using cluster analysis.

PubMed

Moore, Wendy C; Hastie, Annette T; Li, Xingnan; Li, Huashi; Busse, William W; Jarjour, Nizar N; Wenzel, Sally E; Peters, Stephen P; Meyers, Deborah A; Bleecker, Eugene R

2014-06-01

Clinical cluster analysis from the Severe Asthma Research Program (SARP) identified 5 asthma subphenotypes that represent the severity spectrum of early-onset allergic asthma, late-onset severe asthma, and severe asthma with chronic obstructive pulmonary disease characteristics. Analysis of induced sputum from a subset of SARP subjects showed 4 sputum inflammatory cellular patterns. Subjects with concurrent increases in eosinophil (≥2%) and neutrophil (≥40%) percentages had characteristics of very severe asthma. To better understand interactions between inflammation and clinical subphenotypes, we integrated inflammatory cellular measures and clinical variables in a new cluster analysis. Participants in SARP who underwent sputum induction at 3 clinical sites were included in this analysis (n = 423). Fifteen variables, including clinical characteristics and blood and sputum inflammatory cell assessments, were selected using factor analysis for unsupervised cluster analysis. Four phenotypic clusters were identified. Cluster A (n = 132) and B (n = 127) subjects had mild-to-moderate early-onset allergic asthma with paucigranulocytic or eosinophilic sputum inflammatory cell patterns. In contrast, these inflammatory patterns were present in only 7% of cluster C (n = 117) and D (n = 47) subjects who had moderate-to-severe asthma with frequent health care use despite treatment with high doses of inhaled or oral corticosteroids and, in cluster D, reduced lung function. The majority of these subjects (>83%) had sputum neutrophilia either alone or with concurrent sputum eosinophilia. Baseline lung function and sputum neutrophil percentages were the most important variables determining cluster assignment. This multivariate approach identified 4 asthma subphenotypes representing the severity spectrum from mild-to-moderate allergic asthma with minimal or eosinophil-predominant sputum inflammation to moderate-to-severe asthma with neutrophil-predominant or mixed granulocytic inflammation. Published by Mosby, Inc.

Sputum neutrophils are associated with more severe asthma phenotypes using cluster analysis

PubMed Central

Moore, Wendy C.; Hastie, Annette T.; Li, Xingnan; Li, Huashi; Busse, William W.; Jarjour, Nizar N.; Wenzel, Sally E.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

2013-01-01

Background Clinical cluster analysis from the Severe Asthma Research Program (SARP) identified five asthma subphenotypes that represent the severity spectrum of early onset allergic asthma, late onset severe asthma and severe asthma with COPD characteristics. Analysis of induced sputum from a subset of SARP subjects showed four sputum inflammatory cellular patterns. Subjects with concurrent increases in eosinophils (≥2%) and neutrophils (≥40%) had characteristics of very severe asthma. Objective To better understand interactions between inflammation and clinical subphenotypes we integrated inflammatory cellular measures and clinical variables in a new cluster analysis. Methods Participants in SARP at three clinical sites who underwent sputum induction were included in this analysis (n=423). Fifteen variables including clinical characteristics and blood and sputum inflammatory cell assessments were selected by factor analysis for unsupervised cluster analysis. Results Four phenotypic clusters were identified. Cluster A (n=132) and B (n=127) subjects had mild-moderate early onset allergic asthma with paucigranulocytic or eosinophilic sputum inflammatory cell patterns. In contrast, these inflammatory patterns were present in only 7% of Cluster C (n=117) and D (n=47) subjects who had moderate-severe asthma with frequent health care utilization despite treatment with high doses of inhaled or oral corticosteroids, and in Cluster D, reduced lung function. The majority these subjects (>83%) had sputum neutrophilia either alone or with concurrent sputum eosinophilia. Baseline lung function and sputum neutrophils were the most important variables determining cluster assignment. Conclusion This multivariate approach identified four asthma subphenotypes representing the severity spectrum from mild-moderate allergic asthma with minimal or eosinophilic predominant sputum inflammation to moderate-severe asthma with neutrophilic predominant or mixed granulocytic inflammation. PMID:24332216

Factor Analysis for Clustered Observations.

ERIC Educational Resources Information Center

Longford, N. T.; Muthen, B. O.

1992-01-01

A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)

A CLIPS expert system for clinical flow cytometry data analysis

NASA Technical Reports Server (NTRS)

Salzman, G. C.; Duque, R. E.; Braylan, R. C.; Stewart, C. C.

1990-01-01

An expert system is being developed using CLIPS to assist clinicians in the analysis of multivariate flow cytometry data from cancer patients. Cluster analysis is used to find subpopulations representing various cell types in multiple datasets each consisting of four to five measurements on each of 5000 cells. CLIPS facts are derived from results of the clustering. CLIPS rules are based on the expertise of Drs. Stewart, Duque, and Braylan. The rules incorporate certainty factors based on case histories.

Stalking: developing an empirical typology to classify stalkers.

PubMed

Del Ben, Kevin; Fremouw, W

2002-01-01

Stalking has received a great deal of attention from the media and its harmful effects on victims have been well documented. Stalking is also more common than previously thought, leading researchers to classify stalkers into groups in an attempt to predict future behavior. Previous research has grouped stalkers based on theoretical models rather than trying to empirically examine stalking behaviors along with other factors such as motivation, type of relationship, and attachment style in determining a typology of stalkers. Female college students (N = 108) who had experienced stalking behaviors responded to questions regarding their perceptions of those behaviors. First, these victim perceptions were factor analyzed. Then, cluster analysis grouped those factors to produce a four-cluster typology of stalkers. Cluster 1 (Harmless) appeared to reflect a more casual, less jealous pattern of behavior. Cluster 2 (Low Threat) appeared the least likely to become physically violent or threatening, or to engage in illegal behaviors. Cluster 3 (Violent Criminal) appeared to be the most likely to engage in physically threatening and illegal behaviors. Cluster 4 (High Threat) was characterized by a more serious type of relationship and may attempt to be more restrictive of their partner when first meeting them.

Alleviating Comprehension Problems in Movies. Working Paper.

ERIC Educational Resources Information Center

Tatsuki, Donna

This paper describes the various barriers to comprehension that learners may encounter when viewing feature films in a second language. Two clusters of interfacing factors that may contribute to comprehension hot spots emerged from a quantitative analysis of problems noted in student logbooks. One cluster had a strong acoustic basis, whereas the…

Cluster analysis and subgrouping to investigate inter-individual variability to non-invasive brain stimulation: a systematic review.

PubMed

Pellegrini, Michael; Zoghi, Maryam; Jaberzadeh, Shapour

2018-01-12

Cluster analysis and other subgrouping techniques have risen in popularity in recent years in non-invasive brain stimulation research in the attempt to investigate the issue of inter-individual variability - the issue of why some individuals respond, as traditionally expected, to non-invasive brain stimulation protocols and others do not. Cluster analysis and subgrouping techniques have been used to categorise individuals, based on their response patterns, as responder or non-responders. There is, however, a lack of consensus and consistency on the most appropriate technique to use. This systematic review aimed to provide a systematic summary of the cluster analysis and subgrouping techniques used to date and suggest recommendations moving forward. Twenty studies were included that utilised subgrouping techniques, while seven of these additionally utilised cluster analysis techniques. The results of this systematic review appear to indicate that statistical cluster analysis techniques are effective in identifying subgroups of individuals based on response patterns to non-invasive brain stimulation. This systematic review also reports a lack of consensus amongst researchers on the most effective subgrouping technique and the criteria used to determine whether an individual is categorised as a responder or a non-responder. This systematic review provides a step-by-step guide to carrying out statistical cluster analyses and subgrouping techniques to provide a framework for analysis when developing further insights into the contributing factors of inter-individual variability in response to non-invasive brain stimulation.

Exploring the musical taste of expert listeners: musicology students reveal tendency toward omnivorous taste

PubMed Central

Elvers, Paul; Omigie, Diana; Fuhrmann, Wolfgang; Fischinger, Timo

2015-01-01

Musicology students are engaged with music on an academic level and usually have an extensive musical background. They have a considerable knowledge of music history and theory and listening to music may be regarded as one of their primary occupations. Taken together, these factors qualify them as ≫expert listeners≪, who may be expected to exhibit a specific profile of musical taste: interest in a broad range of musical styles combined with a greater appreciation of ≫sophisticated≪ styles. The current study examined the musical taste of musicology students as compared to a control student group. Participants (n = 1003) completed an online survey regarding the frequency with which they listened to 22 musical styles. A factor analysis revealed six underlying dimensions of musical taste. A hierarchical cluster analysis then grouped all participants, regardless of their status, according to their similarity on these dimensions. The employed exploratory approach was expected to reveal potential differences between musicology students and controls. A three-cluster solution was obtained. Comparisons of the clusters in terms of musical taste revealed differences in the listening frequency and variety of appreciated music styles: the first cluster (51% musicology students/27% controls) showed the greatest musical engagement across all dimensions although with a tendency toward ≫sophisticated≪ musical styles. The second cluster (36% musicology students/46% controls) exhibited an interest in ≫conventional≪ music, while the third cluster (13% musicology students/27% controls) showed a strong liking of rock music. The results provide some support for the notion of specific tendencies in the musical taste of musicology students and the contribution of familiarity and knowledge toward musical omnivorousness. Further differences between the clusters in terms of social, personality, and sociodemographic factors are discussed. PMID:26347702

Exploring the musical taste of expert listeners: musicology students reveal tendency toward omnivorous taste.

PubMed

Elvers, Paul; Omigie, Diana; Fuhrmann, Wolfgang; Fischinger, Timo

2015-01-01

Musicology students are engaged with music on an academic level and usually have an extensive musical background. They have a considerable knowledge of music history and theory and listening to music may be regarded as one of their primary occupations. Taken together, these factors qualify them as ≫expert listeners≪, who may be expected to exhibit a specific profile of musical taste: interest in a broad range of musical styles combined with a greater appreciation of ≫sophisticated≪ styles. The current study examined the musical taste of musicology students as compared to a control student group. Participants (n = 1003) completed an online survey regarding the frequency with which they listened to 22 musical styles. A factor analysis revealed six underlying dimensions of musical taste. A hierarchical cluster analysis then grouped all participants, regardless of their status, according to their similarity on these dimensions. The employed exploratory approach was expected to reveal potential differences between musicology students and controls. A three-cluster solution was obtained. Comparisons of the clusters in terms of musical taste revealed differences in the listening frequency and variety of appreciated music styles: the first cluster (51% musicology students/27% controls) showed the greatest musical engagement across all dimensions although with a tendency toward ≫sophisticated≪ musical styles. The second cluster (36% musicology students/46% controls) exhibited an interest in ≫conventional≪ music, while the third cluster (13% musicology students/27% controls) showed a strong liking of rock music. The results provide some support for the notion of specific tendencies in the musical taste of musicology students and the contribution of familiarity and knowledge toward musical omnivorousness. Further differences between the clusters in terms of social, personality, and sociodemographic factors are discussed.

Time-dependent risks of cancer clustering among couples: a nationwide population-based cohort study in Taiwan.

PubMed

Wang, Jong-Yi; Liang, Yia-Wen; Yeh, Chun-Chen; Liu, Chiu-Shong; Wang, Chen-Yu

2018-02-21

Spousal clustering of cancer warrants attention. Whether the common environment or high-age vulnerability determines cancer clustering is unclear. The risk of clustering in couples versus non-couples is undetermined. The time to cancer clustering after the first cancer diagnosis is yet to be reported. This study investigated cancer clustering over time among couples by using nationwide data. A cohort of 5643 married couples in the 2002-2013 Taiwan National Health Insurance Research Database was identified and randomly matched with 5643 non-couple pairs through dual propensity score matching. Factors associated with clustering (both spouses with tumours) were analysed by using the Cox proportional hazard model. Propensity-matched analysis revealed that the risk of clustering of all tumours among couples (13.70%) was significantly higher than that among non-couples (11.84%) (OR=1.182, 95% CI 1.058 to 1.321, P=0.0031). The median time to clustering of all tumours and of malignant tumours was 2.92 and 2.32 years, respectively. Risk characteristics associated with clustering included high age and comorbidity. Shared environmental factors among spouses might be linked to a high incidence of cancer clustering. Cancer incidence in one spouse may signal cancer vulnerability in the other spouse. Promoting family-oriented cancer care in vulnerable families and preventing shared lifestyle risk factors for cancer are suggested. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

[Prognostic differences of phenotypes in pT1-2N0 invasive breast cancer: a large cohort study with cluster analysis].

PubMed

Wang, Z; Wang, W H; Wang, S L; Jin, J; Song, Y W; Liu, Y P; Ren, H; Fang, H; Tang, Y; Chen, B; Qi, S N; Lu, N N; Li, N; Tang, Y; Liu, X F; Yu, Z H; Li, Y X

2016-06-23

To find phenotypic subgroups of patients with pT1-2N0 invasive breast cancer by means of cluster analysis and estimate the prognosis and clinicopathological features of these subgroups. From 1999 to 2013, 4979 patients with pT1-2N0 invasive breast cancer were recruited for hierarchical clustering analysis. Age (≤40, 41-70, 70+ years), size of primary tumor, pathological type, grade of differentiation, microvascular invasion, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER-2) were chosen as distance metric between patients. Hierarchical cluster analysis was performed using Ward's method. Cophenetic correlation coefficient (CPCC) and Spearman correlation coefficient were used to validate clustering structures. The CPCC was 0.603. The Spearman correlation coefficient was 0.617 (P<0.001), which indicated a good fit of hierarchy to the data. A twelve-cluster model seemed to best illustrate our patient cohort. Patients in cluster 5, 9 and 12 had best prognosis and were characterized by age >40 years, smaller primary tumor, lower histologic grade, positive ER and PR status, and mainly negative HER-2. Patients in the cluster 1 and 11 had the worst prognosis, The cluster 1 was characterized by a larger tumor, higher grade and negative ER and PR status, while the cluster 11 was characterized by positive microvascular invasion. Patients in other 7 clusters had a moderate prognosis, and patients in each cluster had distinctive clinicopathological features and recurrent patterns. This study identified distinctive clinicopathologic phenotypes in a large cohort of patients with pT1-2N0 breast cancer through hierarchical clustering and revealed different prognosis. This integrative model may help physicians to make more personalized decisions regarding adjuvant therapy.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis.

PubMed

Flores, X; Comas, J; Roda, I R; Jiménez, L; Gernaey, K V

2007-01-01

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

Factors influencing epibenthic assemblages in the Minho Estuary (NW Iberian Peninsula).

PubMed

Costa-Dias, Sérgia; Freitas, Vânia; Sousa, Ronaldo; Antunes, Carlos

2010-01-01

The epibenthic community of the Minho Estuary was studied during the summer of 2006. Diversity was generally low and a total of 14 fish and five crustacean taxa were identified. Multivariate analysis revealed two site clusters (A and B). Water conductivity and percentage of fine sand were the abiotic variables that most contributed to the spatial distinction between clusters. The species contributing the most to the average similarity within Cluster A were Crangon crangon and Pomatoschistus microps, while in Cluster B was Atyaephyra desmarestii. Possible factors responsible for the low diversity of the epibenthic community in Minho Estuary were the low macrozoobenthic abundance and diversity, and the high abiotic oscillations between tides (mainly salinity) acting on the ecosystem. Copyright 2010 Elsevier Ltd. All rights reserved.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis.

PubMed

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-11-22

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7-15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: "Average refraction", "Acceleration" and the combination of "Myopia stabilization" and "Late onset of refraction progress". In regression models, younger children with more severe myopia were associated with larger "Acceleration". The risk factors of "Acceleration" included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with "Stabilization", and increased outdoor time was related to "Late onset of refraction progress". We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis

PubMed Central

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-01-01

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7–15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: “Average refraction”, “Acceleration” and the combination of “Myopia stabilization” and “Late onset of refraction progress”. In regression models, younger children with more severe myopia were associated with larger “Acceleration”. The risk factors of “Acceleration” included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with “Stabilization”, and increased outdoor time was related to “Late onset of refraction progress”. We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression. PMID:27874105

Investigating the effects of climate variations on bacillary dysentery incidence in northeast China using ridge regression and hierarchical cluster analysis

PubMed Central

Huang, Desheng; Guan, Peng; Guo, Junqiao; Wang, Ping; Zhou, Baosen

2008-01-01

Background The effects of climate variations on bacillary dysentery incidence have gained more recent concern. However, the multi-collinearity among meteorological factors affects the accuracy of correlation with bacillary dysentery incidence. Methods As a remedy, a modified method to combine ridge regression and hierarchical cluster analysis was proposed for investigating the effects of climate variations on bacillary dysentery incidence in northeast China. Results All weather indicators, temperatures, precipitation, evaporation and relative humidity have shown positive correlation with the monthly incidence of bacillary dysentery, while air pressure had a negative correlation with the incidence. Ridge regression and hierarchical cluster analysis showed that during 1987–1996, relative humidity, temperatures and air pressure affected the transmission of the bacillary dysentery. During this period, all meteorological factors were divided into three categories. Relative humidity and precipitation belonged to one class, temperature indexes and evaporation belonged to another class, and air pressure was the third class. Conclusion Meteorological factors have affected the transmission of bacillary dysentery in northeast China. Bacillary dysentery prevention and control would benefit from by giving more consideration to local climate variations. PMID:18816415

The doctor and the patient--how is a clinical encounter perceived?

PubMed

Adams, Robert; Price, Kay; Tucker, Graeme; Nguyen, Anh-Minh; Wilson, David

2012-01-01

To examine the population distribution of different types of relationships between people with chronic conditions and their doctors that influence decisions being made from a shared-decision making perspective. A survey questionnaire based on recurring themes about the doctor/patient relationship identified from qualitative in-depth interviews with people with chronic conditions and doctors was administered to a national population sample (n=999) of people with chronic conditions. Three factors explained the doctor/patient relationship. Factor 1 identified a positive partnership characteristic of involvement and shared decision-making; Factor 2 doctor-controlled relationship; Factor 3 relationship with negative dimensions. Cluster analysis identified four population groups. Cluster 1 doctor is in control (9.7% of the population); Cluster 2 ambivalent (27.6%); Cluster 3 positive long-term relationship (58.6%); Cluster 4 unhappy relationship (4.4%). The proportion of 18-34 year olds is significantly higher than expected in Cluster 4. The proportion of 65+ year olds is significantly higher than expected in Cluster 1, and significantly lower than expected in Cluster 4. This study adds to shared decision-making literature in that it shows in a representative sample of people with chronic illnesses how their perceptions of their experiences of the doctor-patient relationship are distributed across the population. Consideration needs to be given as to whether it is better to help doctors to alter their styles of interactions to suit the preferences of different patients or if it is feasible to match patients with doctors by style of decision-making and patient preference. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Analyzing Protein Clusters on the Plasma Membrane: Application of Spatial Statistical Analysis Methods on Super-Resolution Microscopy Images.

PubMed

Paparelli, Laura; Corthout, Nikky; Pavie, Benjamin; Annaert, Wim; Munck, Sebastian

2016-01-01

The spatial distribution of proteins within the cell affects their capability to interact with other molecules and directly influences cellular processes and signaling. At the plasma membrane, multiple factors drive protein compartmentalization into specialized functional domains, leading to the formation of clusters in which intermolecule interactions are facilitated. Therefore, quantifying protein distributions is a necessity for understanding their regulation and function. The recent advent of super-resolution microscopy has opened up the possibility of imaging protein distributions at the nanometer scale. In parallel, new spatial analysis methods have been developed to quantify distribution patterns in super-resolution images. In this chapter, we provide an overview of super-resolution microscopy and summarize the factors influencing protein arrangements on the plasma membrane. Finally, we highlight methods for analyzing clusterization of plasma membrane proteins, including examples of their applications.

Using concept mapping in the development of the EU-PAD framework (EUropean-Physical Activity Determinants across the life course): a DEDIPAC-study.

PubMed

Condello, Giancarlo; Ling, Fiona Chun Man; Bianco, Antonino; Chastin, Sebastien; Cardon, Greet; Ciarapica, Donatella; Conte, Daniele; Cortis, Cristina; De Craemer, Marieke; Di Blasio, Andrea; Gjaka, Masar; Hansen, Sylvia; Holdsworth, Michelle; Iacoviello, Licia; Izzicupo, Pascal; Jaeschke, Lina; Leone, Liliana; Manoni, Livia; Menescardi, Cristina; Migliaccio, Silvia; Nazare, Julie-Anne; Perchoux, Camille; Pesce, Caterina; Pierik, Frank; Pischon, Tobias; Polito, Angela; Puggina, Anna; Sannella, Alessandra; Schlicht, Wolfgang; Schulz, Holger; Simon, Chantal; Steinbrecher, Astrid; MacDonncha, Ciaran; Capranica, Laura

2016-11-09

A large proportion of European children, adults and older adults do not engage in sufficient physical activity (PA). Understanding individual and contextual factors associated with PA behaviours is essential for the identification and implementation of effective preventative environments, policies, and programmes that can promote an active lifestyle across life course and can potentially improve health. The current paper intends to provide 1) a multi-disciplinary, Pan-European and life course view of key determinants of PA behaviours and 2) a proposal of how these factors may cluster. After gathering a list of 183 potential PA behaviours-associated factors and a consensus meeting to unify/consolidate terminology, a concept mapping software was used to collate European experts' views of 106 identified factors for youth (<19 years), adults (19-64 years), and older adults (≥65 years). The analysis evaluated common trends in the clustering of factors and the ratings of the distinct factors' expected modifiability and population-level impact on PA behaviours across the life course. Priority for research was also assessed for each cluster. The concept mapping resulted in six distinct clusters, broadly merged in two themes: 1) the 'Person', which included clusters 'Intra-Personal Context and Wellbeing' and 'Family and Social Economic Status' (42 % of all factors) and 2) the 'Society', which included the remaining four clusters 'Policy and Provision', 'Cultural Context and Media', 'Social Support and Modelling', and 'Supportive Environment' (58 % of all factors). Overall, 25 factors were rated as the most impactful on PA behaviours across the life course and being the most modifiable. They were mostly situated in the 'Intra-Personal Context and Wellbeing' cluster. Furthermore, 16 of them were rated as top priority for research. The current framework provides a preliminary overview of factors which may account for PA behaviour across the life course and are most relevant to the European community. These insights could potentially be a foundation for future Pan-European research on how these factors might interact with each other, and assist policy makers to identify appropriate interventions to maximize PA behaviours and thus the health of European citizens.

Factor analysis and cluster analysis applied to assess the water quality of middle and lower Han River in Central China

NASA Astrophysics Data System (ADS)

Kuo, Yi-Ming; Liu, Wen-Wen

2015-04-01

The Han River basin is one of the most important industrial and grain production bases in the central China. A lot of factories and towns have been established along the river where large farmlands are located nearby. In the last few decades the water quality of the Han River, specifically in middle and lower reaches, has gradually declined. The agricultural nonpoint pollution and municipal and industrial point pollution significantly degrade the water quality of the Han River. Factor analysis can be applied to reduce the dimensionality of a data set consisting of a large number of inter-related variables. Cluster analysis can classify the samples according to their similar characters. In this study, factor analysis is used to identify major pollution indicators, and cluster analysis is employed to classify the samples based on the sample locations and hydrochemical variables. Water samples were collected from 12 sample sites collected from Xiangyang City (middle Han River) to Wuhan City (lower Han River). Correlations among 25 hydrochemical variables are statistically examined. The important pollutants are determined by factor analysis. A three-factor model is determined and explains over 85% of the total river water quality variation. Factor 1, including SS, Chl-a, TN and TP, can be considered as the nonpoint source pollution. Factor 2, including Cl-, Br-, SO42-, Ca2+, Mg2+, K+, Fe2+ and PO43-, can be treated as the industrial pollutant pollution. Factor 3, including F- and NO3-, reflects the influence of the groundwater or self-purification capability of the river water. The various land uses along the Han River correlate well with the pollution types. In addition, the result showed that the water quality of Han River deteriorated gradually from middle to lower Han River. Some tributaries have been seriously polluted and significantly influence the mainstream water quality of the Han River. Finally, the result showed that the nonpoint pollution and the point pollution both significantly influence water quality in the middle and lower Han River. This study provides an effective method for watershed management and pollution control in Han River.

Parkinson's Disease Subtypes in the Oxford Parkinson Disease Centre (OPDC) Discovery Cohort.

PubMed

Lawton, Michael; Baig, Fahd; Rolinski, Michal; Ruffman, Claudio; Nithi, Kannan; May, Margaret T; Ben-Shlomo, Yoav; Hu, Michele T M

2015-01-01

Within Parkinson's there is a spectrum of clinical features at presentation which may represent sub-types of the disease. However there is no widely accepted consensus of how best to group patients. Use a data-driven approach to unravel any heterogeneity in the Parkinson's phenotype in a well-characterised, population-based incidence cohort. 769 consecutive patients, with mean disease duration of 1.3 years, were assessed using a broad range of motor, cognitive and non-motor metrics. Multiple imputation was carried out using the chained equations approach to deal with missing data. We used an exploratory and then a confirmatory factor analysis to determine suitable domains to include within our cluster analysis. K-means cluster analysis of the factor scores and all the variables not loading into a factor was used to determine phenotypic subgroups. Our factor analysis found three important factors that were characterised by: psychological well-being features; non-tremor motor features, such as posture and rigidity; and cognitive features. Our subsequent five cluster model identified groups characterised by (1) mild motor and non-motor disease (25.4%), (2) poor posture and cognition (23.3%), (3) severe tremor (20.8%), (4) poor psychological well-being, RBD and sleep (18.9%), and (5) severe motor and non-motor disease with poor psychological well-being (11.7%). Our approach identified several Parkinson's phenotypic sub-groups driven by largely dopaminergic-resistant features (RBD, impaired cognition and posture, poor psychological well-being) that, in addition to dopaminergic-responsive motor features may be important for studying the aetiology, progression, and medication response of early Parkinson's.

Reliability and Validity of "Parents' Evaluation of Responsible Behaviors of 5-6 Year Old Children" Scale

ERIC Educational Resources Information Center

Polat, Ozgul; Dagal, Asude B.

2013-01-01

This study is aimed at developing a scale (Parents' Evaluation of Responsible Behaviors of 5-6 Year Old Children) for measuring parents' evaluation of their 5-6 year-old children's responsible behaviors. The construct validity of the scale was tested by Factor Analysis. Factor analysis determined that the scale can be clustered under 10 factors.…

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

Research on the relationship between the elements and pharmacological activities in velvet antler using factor analysis and cluster analysis

NASA Astrophysics Data System (ADS)

Zhou, Libing

2017-04-01

Velvet antler has certain effect on improving the body's immune cells and the regulation of immune system function, nervous system, anti-stress, anti-aging and osteoporosis. It has medicinal applications to treat a wide range of diseases such as tissue wound healing, anti-tumor, cardiovascular disease, et al. Therefore, the research on the relationship between pharmacological activities and elements in velvet antler is of great significance. The objective of this study was to comprehensively evaluate 15 kinds of elements in different varieties of velvet antlers and study on the relationship between the elements and traditional Chinese medicine efficacy for the human. The factor analysis and the factor cluster analysis methods were used to analyze the data of elements in the sika velvet antler, cervus elaphus linnaeus, flower horse hybrid velvet antler, apiti (elk) velvet antler, male reindeer velvet antler and find out the relationship between 15 kinds of elements including Ca, P, Mg, Na, K, Fe, Cu, Mn, Al, Ba, Co, Sr, Cr, Zn and Ni. Combining with MATLAB2010 and SPSS software, the chemometrics methods were made on the relationship between the elements in velvet antler and the pharmacological activities. The first commonality factor F1 had greater load on the indexes of Ca, P, Mg, Co, Sr and Ni, and the second commonality factor F2 had greater load on the indexes of K, Mn, Zn and Cr, and the third commonality factor F3 had greater load on the indexes of Na, Cu and Ba, and the fourth commonality factor F4 had greater load on the indexes of Fe and Al. 15 kinds of elements in velvet antler in the order were elk velvet antler>flower horse hybrid velvet antler>cervus elaphus linnaeus>sika velvet antler>male reindeer velvet antler. Based on the factor analysis and the factor cluster analysis, a model for evaluating traditional Chinese medicine quality was constructed. These studies provide the scientific base and theoretical foundation for the future large-scale rational relation development of velvet antler resources as well as the relationship between the elements and traditional Chinese medicine efficacy for the human.

[Styles of interpersonal conflict in patients with panic disorder, alcoholism, rheumatoid arthritis and healthy controls: a cluster analysis study].

PubMed

Eher, R; Windhaber, J; Rau, H; Schmitt, M; Kellner, E

2000-05-01

Conflict and conflict resolution in intimate relationships are not only among the most important factors influencing relationship satisfaction but are also seen in association with clinical symptoms. Styles of conflict will be assessed in patients suffering from panic disorder with and without agoraphobia, in alcoholics and in patients suffering from rheumatoid arthritis. 176 patients and healthy controls filled out the Styles of Conflict Inventory and questionnaires concerning severity of clinical symptoms. A cluster analysis revealed 5 types of conflict management. Healthy controls showed predominantely assertive and constructive styles, patients with panic disorder showed high levels of cognitive and/or behavioral aggression. Alcoholics showed high levels of repressed aggression, and patients with rheumatoid arthritis often did not exhibit any aggression during conflict. 5 Clusters of conflict pattern have been identified by cluster analysis. Each patient group showed considerable different patterns of conflict management.

Clustering of haemostatic variables and the effect of high cashew and walnut diets on these variables in metabolic syndrome patients.

PubMed

Pieters, Marlien; Oosthuizen, Welma; Jerling, Johann C; Loots, Du Toit; Mukuddem-Petersen, Janine; Hanekom, Susanna M

2005-09-01

We investigated the effect of a high walnut and cashew diet on haemostatic variables in people with the metabolic syndrome. Factor analysis was used to determine how the haemostatic variables cluster with other components of the metabolic syndrome and multiple regression to determine possible predictors. This randomized, control, parallel, controlled-feeding trial included 68 subjects who complied with the Third National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol criteria. After a 3-week run-in following the control diet, subjects were divided into three groups receiving either walnuts or cashews (20 energy%) or a control diet for 8 weeks. The nut intervention had no significant effect on von Willebrand factor antigen, fibrinogen, factor VII coagulant activity, plasminogen activator inhibitor 1 activity, tissue plasminogen activator activity or thrombin activatable fibrinolysis inhibitor. Statistically, fibrinogen clustered with the body-mass-correlates and acute phase response factors, and factor VII coagulant activity clustered with high-density lipoprotein cholesterol (HDL-C). Tissue plasminogen activator activity, plasminogen activator inhibitor 1 activity and von Willebrand factor antigen clustered into a separate endothelial function factor. HDL-C and markers of obesity were the strongest predictors of the haemostatic variables. We conclude that high walnut and cashew diets did not influence haemostatic factors in this group of metabolic syndrome subjects. The HDL-C increase and weight loss may be the main focus of dietary intervention for the metabolic syndrome. Furthermore, diet composition may have only limited effects if weight loss is not achieved.

Cluster headache and the hypocretin receptor 2 reconsidered: a genetic association study and meta-analysis.

PubMed

Weller, Claudia M; Wilbrink, Leopoldine A; Houwing-Duistermaat, Jeanine J; Koelewijn, Stephany C; Vijfhuizen, Lisanne S; Haan, Joost; Ferrari, Michel D; Terwindt, Gisela M; van den Maagdenberg, Arn M J M; de Vries, Boukje

2015-08-01

Cluster headache is a severe neurological disorder with a complex genetic background. A missense single nucleotide polymorphism (rs2653349; p.Ile308Val) in the HCRTR2 gene that encodes the hypocretin receptor 2 is the only genetic factor that is reported to be associated with cluster headache in different studies. However, as there are conflicting results between studies, we re-evaluated its role in cluster headache. We performed a genetic association analysis for rs2653349 in our large Leiden University Cluster headache Analysis (LUCA) program study population. Systematic selection of the literature yielded three additional studies comprising five study populations, which were included in our meta-analysis. Data were extracted according to predefined criteria. A total of 575 cluster headache patients from our LUCA study and 874 controls were genotyped for HCRTR2 SNP rs2653349 but no significant association with cluster headache was found (odds ratio 0.91 (95% confidence intervals 0.75-1.10), p = 0.319). In contrast, the meta-analysis that included in total 1167 cluster headache cases and 1618 controls from the six study populations, which were part of four different studies, showed association of the single nucleotide polymorphism with cluster headache (random effect odds ratio 0.69 (95% confidence intervals 0.53-0.90), p = 0.006). The association became weaker, as the odds ratio increased to 0.80, when the meta-analysis was repeated without the initial single South European study with the largest effect size. Although we did not find evidence for association of rs2653349 in our LUCA study, which is the largest investigated study population thus far, our meta-analysis provides genetic evidence for a role of HCRTR2 in cluster headache. Regardless, we feel that the association should be interpreted with caution as meta-analyses with individual populations that have limited power have diminished validity. © International Headache Society 2014.

Attitudes of Greek Drivers with Focus on Mobile Phone Use While Driving.

PubMed

Yannis, George; Theofilatos, Athanasios; Marinou, Paraskevi

2015-01-01

This article investigates the attitudes and behavior of Greek drivers with specific focus on mobile phone use while driving. The research is based on the data of the pan-European SARTRE 4 survey, which was conducted on a representative sample of Greek drivers in 2011. Analysis of the drivers' behavior was carried out by the statistical methods of factor and cluster analysis. According to the results of factor analysis, Greek drivers' responses in the selected questions were summarized into 4 factors, describing road behavior and accident involvement probability as well as their views on issues concerning other drivers' road behaviors, fatigued driving, enforcement of road safety, and mobile phone use while driving. The results of cluster analysis indicated 5 different groups of Greek drivers--the moderate, the optimistic, the conservative, the risky, and the reasonably cautious--and the characteristics of each group where identified. These results may be useful for the appropriate design of targeted road safety campaigns and other countermeasures.

System-wide analysis of the transcriptional network of human myelomonocytic leukemia cells predicts attractor structure and phorbol-ester-induced differentiation and dedifferentiation transitions

NASA Astrophysics Data System (ADS)

Sakata, Katsumi; Ohyanagi, Hajime; Sato, Shinji; Nobori, Hiroya; Hayashi, Akiko; Ishii, Hideshi; Daub, Carsten O.; Kawai, Jun; Suzuki, Harukazu; Saito, Toshiyuki

2015-02-01

We present a system-wide transcriptional network structure that controls cell types in the context of expression pattern transitions that correspond to cell type transitions. Co-expression based analyses uncovered a system-wide, ladder-like transcription factor cluster structure composed of nearly 1,600 transcription factors in a human transcriptional network. Computer simulations based on a transcriptional regulatory model deduced from the system-wide, ladder-like transcription factor cluster structure reproduced expression pattern transitions when human THP-1 myelomonocytic leukaemia cells cease proliferation and differentiate under phorbol myristate acetate stimulation. The behaviour of MYC, a reprogramming Yamanaka factor that was suggested to be essential for induced pluripotent stem cells during dedifferentiation, could be interpreted based on the transcriptional regulation predicted by the system-wide, ladder-like transcription factor cluster structure. This study introduces a novel system-wide structure to transcriptional networks that provides new insights into network topology.

Transcriptional regulation of gene expression clusters in motor neurons following spinal cord injury.

PubMed

Ryge, Jesper; Winther, Ole; Wienecke, Jacob; Sandelin, Albin; Westerdahl, Ann-Charlotte; Hultborn, Hans; Kiehn, Ole

2010-06-09

Spinal cord injury leads to neurological dysfunctions affecting the motor, sensory as well as the autonomic systems. Increased excitability of motor neurons has been implicated in injury-induced spasticity, where the reappearance of self-sustained plateau potentials in the absence of modulatory inputs from the brain correlates with the development of spasticity. Here we examine the dynamic transcriptional response of motor neurons to spinal cord injury as it evolves over time to unravel common gene expression patterns and their underlying regulatory mechanisms. For this we use a rat-tail-model with complete spinal cord transection causing injury-induced spasticity, where gene expression profiles are obtained from labeled motor neurons extracted with laser microdissection 0, 2, 7, 21 and 60 days post injury. Consensus clustering identifies 12 gene clusters with distinct time expression profiles. Analysis of these gene clusters identifies early immunological/inflammatory and late developmental responses as well as a regulation of genes relating to neuron excitability that support the development of motor neuron hyper-excitability and the reappearance of plateau potentials in the late phase of the injury response. Transcription factor motif analysis identifies differentially expressed transcription factors involved in the regulation of each gene cluster, shaping the expression of the identified biological processes and their associated genes underlying the changes in motor neuron excitability. This analysis provides important clues to the underlying mechanisms of transcriptional regulation responsible for the increased excitability observed in motor neurons in the late chronic phase of spinal cord injury suggesting alternative targets for treatment of spinal cord injury. Several transcription factors were identified as potential regulators of gene clusters containing elements related to motor neuron hyper-excitability, the manipulation of which potentially could be used to alter the transcriptional response to prevent the motor neurons from entering a state of hyper-excitability.

Transcriptional regulation of gene expression clusters in motor neurons following spinal cord injury

PubMed Central

2010-01-01

Background Spinal cord injury leads to neurological dysfunctions affecting the motor, sensory as well as the autonomic systems. Increased excitability of motor neurons has been implicated in injury-induced spasticity, where the reappearance of self-sustained plateau potentials in the absence of modulatory inputs from the brain correlates with the development of spasticity. Results Here we examine the dynamic transcriptional response of motor neurons to spinal cord injury as it evolves over time to unravel common gene expression patterns and their underlying regulatory mechanisms. For this we use a rat-tail-model with complete spinal cord transection causing injury-induced spasticity, where gene expression profiles are obtained from labeled motor neurons extracted with laser microdissection 0, 2, 7, 21 and 60 days post injury. Consensus clustering identifies 12 gene clusters with distinct time expression profiles. Analysis of these gene clusters identifies early immunological/inflammatory and late developmental responses as well as a regulation of genes relating to neuron excitability that support the development of motor neuron hyper-excitability and the reappearance of plateau potentials in the late phase of the injury response. Transcription factor motif analysis identifies differentially expressed transcription factors involved in the regulation of each gene cluster, shaping the expression of the identified biological processes and their associated genes underlying the changes in motor neuron excitability. Conclusions This analysis provides important clues to the underlying mechanisms of transcriptional regulation responsible for the increased excitability observed in motor neurons in the late chronic phase of spinal cord injury suggesting alternative targets for treatment of spinal cord injury. Several transcription factors were identified as potential regulators of gene clusters containing elements related to motor neuron hyper-excitability, the manipulation of which potentially could be used to alter the transcriptional response to prevent the motor neurons from entering a state of hyper-excitability. PMID:20534130

Socioeconomic status (SES) and childhood acute myeloid leukemia (AML) mortality risk: Analysis of SEER data.

PubMed

Knoble, Naomi B; Alderfer, Melissa A; Hossain, Md Jobayer

2016-10-01

Socioeconomic status (SES) is a complex construct of multiple indicators, known to impact cancer outcomes, but has not been adequately examined among pediatric AML patients. This study aimed to identify the patterns of co-occurrence of multiple community-level SES indicators and to explore associations between various patterns of these indicators and pediatric AML mortality risk. A nationally representative US sample of 3651 pediatric AML patients, aged 0-19 years at diagnosis was drawn from 17 Surveillance, Epidemiology, and End Results (SEER) database registries created between 1973 and 2012. Factor analysis, cluster analysis, stratified univariable and multivariable Cox proportional hazards models were used. Four SES factors accounting for 87% of the variance in SES indicators were identified: F1) economic/educational disadvantage, less immigration; F2) immigration-related features (foreign-born, language-isolation, crowding), less mobility; F3) housing instability; and, F4) absence of moving. F1 and F3 showed elevated risk of mortality, adjusted hazards ratios (aHR) (95% CI): 1.07(1.02-1.12) and 1.05(1.00-1.10), respectively. Seven SES-defined cluster groups were identified. Cluster 1 (low economic/educational disadvantage, few immigration-related features, and residential-stability) showed the minimum risk of mortality. Compared to Cluster 1, Cluster 3 (high economic/educational disadvantage, high-mobility) and Cluster 6 (moderately-high economic/educational disadvantages, housing-instability and immigration-related features) exhibited substantially greater risk of mortality, aHR(95% CI)=1.19(1.0-1.4) and 1.23 (1.1-1.5), respectively. Factors of correlated SES-indicators and their pattern-based groups demonstrated differential risks in the pediatric AML mortality indicating the need of special public-health attention in areas with economic-educational disadvantages, housing-instability and immigration-related features. Copyright © 2016 Elsevier Ltd. All rights reserved.

Behavioral Health Risk Profiles of Undergraduate University Students in England, Wales, and Northern Ireland: A Cluster Analysis.

PubMed

El Ansari, Walid; Ssewanyana, Derrick; Stock, Christiane

2018-01-01

Limited research has explored clustering of lifestyle behavioral risk factors (BRFs) among university students. This study aimed to explore clustering of BRFs, composition of clusters, and the association of the clusters with self-rated health and perceived academic performance. We assessed (BRFs), namely tobacco smoking, physical inactivity, alcohol consumption, illicit drug use, unhealthy nutrition, and inadequate sleep, using a self-administered general Student Health Survey among 3,706 undergraduates at seven UK universities. A two-step cluster analysis generated: Cluster 1 (the high physically active and health conscious) with very high health awareness/consciousness, good nutrition, and physical activity (PA), and relatively low alcohol, tobacco, and other drug (ATOD) use. Cluster 2 (the abstinent) had very low ATOD use, high health awareness, good nutrition, and medium high PA. Cluster 3 (the moderately health conscious) included the highest regard for healthy eating, second highest fruit/vegetable consumption, and moderately high ATOD use. Cluster 4 (the risk taking) showed the highest ATOD use, were the least health conscious, least fruit consuming, and attached the least importance on eating healthy. Compared to the healthy cluster (Cluster 1), students in other clusters had lower self-rated health, and particularly, students in the risk taking cluster (Cluster 4) reported lower academic performance. These associations were stronger for men than for women. Of the four clusters, Cluster 4 had the youngest students. Our results suggested that prevention among university students should address multiple BRFs simultaneously, with particular focus on the younger students.

See Change: Cosmology Analysis Update for the Supernova Cosmology Project High-z Cluster Supernova Survey

NASA Astrophysics Data System (ADS)

Hayden, Brian; Aldering, Gregory; Amanullah, Rahman; Barbary, Kyle; Bohringer, Hans; Boone, Kyle Robert; Brodwin, Mark; Cunha, Carlos; Currie, Miles; Deustua, Susana; Dixon, Samantha; Eisenhardt, Peter; Fassbender, Rene; Fruchter, Andrew; Gladders, Michael; Gonzalez, Anthony; Goobar, Ariel; Hildebrandt, Hendrik; Hilton, Matt; Hoekstra, Henk; Hook, Isobel; Huang, Xiaosheng; Huterer, Dragan; Jee, Myungkook James; Kim, Alex; Kowalski, Marek; Lidman, Chris; Linder, Eric; Luther, Kyle; Meyers, Joshua; Muzzin, Adam; Nordin, Jakob; Pain, Reynald; Perlmutter, Saul; Richard, Johan; Rosati, Piero; Rozo, Eduardo; Rubin, David; Ruiz-Lapuente, Pilar; Rykoff, Eli; Santos, Joana; Myers Saunders, Clare; Sofiatti, Caroline; Spadafora, Anthony L.; Stanford, Spencer; Stern, Daniel; Suzuki, Nao; Webb, Tracy; Wechsler, Risa; Williams, Steven; Willis, Jon; Wilson, Gillian; Yen, Mike

2018-01-01

The Supernova Cosmology Project has finished executing a large (174 orbits, cycles 22-23) Hubble Space Telescope program, which has measured ~30 type Ia Supernovae above z~1 in the highest-redshift, most massive galaxy clusters known to date. We present the status of the ongoing blinded cosmology analysis, demonstrating substantial improvement to the uncertainty on the Dark Energy density above z~1. Our extensive HST and ground-based campaign has already produced unique results; we have confirmed several of the highest redshift cluster members known to date, confirmed the redshift of one of the most massive galaxy clusters expected across the entire sky, and characterized one of the most extreme starburst environments yet known in a z~1.7 cluster. We have also discovered a lensed SN Ia at z=2.22 magnified by a factor of ~2.8, which is the highest spectroscopic redshift SN Ia currently known.

Impact of the Choice of Normalization Method on Molecular Cancer Class Discovery Using Nonnegative Matrix Factorization.

PubMed

Yang, Haixuan; Seoighe, Cathal

2016-01-01

Nonnegative Matrix Factorization (NMF) has proved to be an effective method for unsupervised clustering analysis of gene expression data. By the nonnegativity constraint, NMF provides a decomposition of the data matrix into two matrices that have been used for clustering analysis. However, the decomposition is not unique. This allows different clustering results to be obtained, resulting in different interpretations of the decomposition. To alleviate this problem, some existing methods directly enforce uniqueness to some extent by adding regularization terms in the NMF objective function. Alternatively, various normalization methods have been applied to the factor matrices; however, the effects of the choice of normalization have not been carefully investigated. Here we investigate the performance of NMF for the task of cancer class discovery, under a wide range of normalization choices. After extensive evaluations, we observe that the maximum norm showed the best performance, although the maximum norm has not previously been used for NMF. Matlab codes are freely available from: http://maths.nuigalway.ie/~haixuanyang/pNMF/pNMF.htm.

Identifying clusters of falls-related hospital admissions to inform population targets for prioritising falls prevention programmes

PubMed Central

Finch, Caroline F; Stephan, Karen; Shee, Anna Wong; Hill, Keith; Haines, Terry P; Clemson, Lindy; Day, Lesley

2015-01-01

Background There has been limited research investigating the relationship between injurious falls and hospital resource use. The aims of this study were to identify clusters of community-dwelling older people in the general population who are at increased risk of being admitted to hospital following a fall and how those clusters differed in their use of hospital resources. Methods Analysis of routinely collected hospital admissions data relating to 45 374 fall-related admissions in Victorian community-dwelling older adults aged ≥65 years that occurred during 2008/2009 to 2010/2011. Fall-related admission episodes were identified based on being admitted from a private residence to hospital with a principal diagnosis of injury (International Classification of Diseases (ICD)-10-AM codes S00 to T75) and having a first external cause of a fall (ICD-10-AM codes W00 to W19). A cluster analysis was performed to identify homogeneous groups using demographic details of patients and information on the presence of comorbidities. Hospital length of stay (LOS) was compared across clusters using competing risks regression. Results Clusters based on area of residence, demographic factors (age, gender, marital status, country of birth) and the presence of comorbidities were identified. Clusters representing hospitalised fallers with comorbidities were associated with longer LOS compared with other cluster groups. Clusters delineated by demographic factors were also associated with increased LOS. Conclusions All patients with comorbidity, and older women without comorbidities, stay in hospital longer following a fall and hence consume a disproportionate share of hospital resources. These findings have important implications for the targeting of falls prevention interventions for community-dwelling older people. PMID:25618735

Cluster analysis to estimate the risk of preeclampsia in the high-risk Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study.

PubMed

Villa, Pia M; Marttinen, Pekka; Gillberg, Jussi; Lokki, A Inkeri; Majander, Kerttu; Ordén, Maija-Riitta; Taipale, Pekka; Pesonen, Anukatriina; Räikkönen, Katri; Hämäläinen, Esa; Kajantie, Eero; Laivuori, Hannele

2017-01-01

Preeclampsia is divided into early-onset (delivery before 34 weeks of gestation) and late-onset (delivery at or after 34 weeks) subtypes, which may rise from different etiopathogenic backgrounds. Early-onset disease is associated with placental dysfunction. Late-onset disease develops predominantly due to metabolic disturbances, obesity, diabetes, lipid dysfunction, and inflammation, which affect endothelial function. Our aim was to use cluster analysis to investigate clinical factors predicting the onset and severity of preeclampsia in a cohort of women with known clinical risk factors. We recruited 903 pregnant women with risk factors for preeclampsia at gestational weeks 12+0-13+6. Each individual outcome diagnosis was independently verified from medical records. We applied a Bayesian clustering algorithm to classify the study participants to clusters based on their particular risk factor combination. For each cluster, we computed the risk ratio of each disease outcome, relative to the risk in the general population. The risk of preeclampsia increased exponentially with respect to the number of risk factors. Our analysis revealed 25 number of clusters. Preeclampsia in a previous pregnancy (n = 138) increased the risk of preeclampsia 8.1 fold (95% confidence interval (CI) 5.7-11.2) compared to a general population of pregnant women. Having a small for gestational age infant (n = 57) in a previous pregnancy increased the risk of early-onset preeclampsia 17.5 fold (95%CI 2.1-60.5). Cluster of those two risk factors together (n = 21) increased the risk of severe preeclampsia to 23.8-fold (95%CI 5.1-60.6), intermediate onset (delivery between 34+0-36+6 weeks of gestation) to 25.1-fold (95%CI 3.1-79.9) and preterm preeclampsia (delivery before 37+0 weeks of gestation) to 16.4-fold (95%CI 2.0-52.4). Body mass index over 30 kg/m2 (n = 228) as a sole risk factor increased the risk of preeclampsia to 2.1-fold (95%CI 1.1-3.6). Together with preeclampsia in an earlier pregnancy the risk increased to 11.4 (95%CI 4.5-20.9). Chronic hypertension (n = 60) increased the risk of preeclampsia 5.3-fold (95%CI 2.4-9.8), of severe preeclampsia 22.2-fold (95%CI 9.9-41.0), and risk of early-onset preeclampsia 16.7-fold (95%CI 2.0-57.6). If a woman had chronic hypertension combined with obesity, gestational diabetes and earlier preeclampsia, the risk of term preeclampsia increased 4.8-fold (95%CI 0.1-21.7). Women with type 1 diabetes mellitus had a high risk of all subgroups of preeclampsia. The risk of preeclampsia increases exponentially with respect to the number of risk factors. Early-onset preeclampsia and severe preeclampsia have different risk profile from term preeclampsia.

Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health

PubMed Central

Fogel, Paul; Gaston-Mathé, Yann; Hawkins, Douglas; Fogel, Fajwel; Luta, George; Young, S. Stanley

2016-01-01

Often data can be represented as a matrix, e.g., observations as rows and variables as columns, or as a doubly classified contingency table. Researchers may be interested in clustering the observations, the variables, or both. If the data is non-negative, then Non-negative Matrix Factorization (NMF) can be used to perform the clustering. By its nature, NMF-based clustering is focused on the large values. If the data is normalized by subtracting the row/column means, it becomes of mixed signs and the original NMF cannot be used. Our idea is to split and then concatenate the positive and negative parts of the matrix, after taking the absolute value of the negative elements. NMF applied to the concatenated data, which we call PosNegNMF, offers the advantages of the original NMF approach, while giving equal weight to large and small values. We use two public health datasets to illustrate the new method and compare it with alternative clustering methods, such as K-means and clustering methods based on the Singular Value Decomposition (SVD) or Principal Component Analysis (PCA). With the exception of situations where a reasonably accurate factorization can be achieved using the first SVD component, we recommend that the epidemiologists and environmental scientists use the new method to obtain clusters with improved quality and interpretability. PMID:27213413

Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health.

PubMed

Fogel, Paul; Gaston-Mathé, Yann; Hawkins, Douglas; Fogel, Fajwel; Luta, George; Young, S Stanley

2016-05-18

Often data can be represented as a matrix, e.g., observations as rows and variables as columns, or as a doubly classified contingency table. Researchers may be interested in clustering the observations, the variables, or both. If the data is non-negative, then Non-negative Matrix Factorization (NMF) can be used to perform the clustering. By its nature, NMF-based clustering is focused on the large values. If the data is normalized by subtracting the row/column means, it becomes of mixed signs and the original NMF cannot be used. Our idea is to split and then concatenate the positive and negative parts of the matrix, after taking the absolute value of the negative elements. NMF applied to the concatenated data, which we call PosNegNMF, offers the advantages of the original NMF approach, while giving equal weight to large and small values. We use two public health datasets to illustrate the new method and compare it with alternative clustering methods, such as K-means and clustering methods based on the Singular Value Decomposition (SVD) or Principal Component Analysis (PCA). With the exception of situations where a reasonably accurate factorization can be achieved using the first SVD component, we recommend that the epidemiologists and environmental scientists use the new method to obtain clusters with improved quality and interpretability.

Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.

PubMed

Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A; Kardia, Sharon L R; Allison, Matthew; Diez Roux, Ana V

2016-11-01

There has been an increased interest in identifying gene-environment interaction (G × E) in the context of multiple environmental exposures. Most G × E studies analyze one exposure at a time, but we are exposed to multiple exposures in reality. Efficient analysis strategies for complex G × E with multiple environmental factors in a single model are still lacking. Using the data from the Multiethnic Study of Atherosclerosis, we illustrate a two-step approach for modeling G × E with multiple environmental factors. First, we utilize common clustering and classification strategies (e.g., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. Second, we illustrate the use of an additive main effects and multiplicative interaction model, instead of the conventional saturated interaction model using product terms of factors, to study G × E with the data-driven exposure subgroups defined in the first step. We demonstrate useful analytical approaches to translate multiple environmental exposures into one summary class. These tools not only allow researchers to consider several environmental exposures in G × E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead of examining effect modification for each exposure in isolation.

Bulk tank milk prevalence and production losses, spatial analysis, and predictive risk mapping of Ostertagia ostertagi infections in Mexican cattle herds.

PubMed

Villa-Mancera, Abel; Pastelín-Rojas, César; Olivares-Pérez, Jaime; Córdova-Izquierdo, Alejandro; Reynoso-Palomar, Alejandro

2018-05-01

This study investigated the prevalence, production losses, spatial clustering, and predictive risk mapping in different climate zones in five states of Mexico. The bulk tank milk samples obtained between January and April 2015 were analyzed for antibodies against Ostertagia ostertagi using the Svanovir ELISA. A total of 1204 farm owners or managers answered the questionnaire. The overall herd prevalence and mean optical density ratio (ODR) of parasite were 61.96% and 0.55, respectively. Overall, the production loss was approximately 0.542 kg of milk per parasited cow per day (mean ODR = 0.92, 142 farms, 11.79%). The spatial disease cluster analysis using SatScan software indicated that two high-risk clusters were observed. In the multivariable analysis, three models were tested for potential association with the ELISA results supported by climatic, environmental, and management factors. The final logistic regression model based on both climatic/environmental and management variables included the factors rainfall, elevation, land surface temperature (LST) day, and parasite control program that were significantly associated with an increased risk of infection. Geostatistical kriging was applied to generate a risk map for the presence of parasite in dairy cattle herds in Mexico. The results indicate that climatic and meteorological factors had a higher potential impact on the spatial distribution of O. ostertagi than the management factors.

The Brazilian version of the three-factor eating questionnaire-R21: psychometric evaluation and scoring pattern.

PubMed

de Medeiros, Anna Cecília Queiroz; Yamamoto, Maria Emilia; Pedrosa, Lucia Fatima Campos; Hutz, Claudio Simon

2017-03-01

This study aimed to evaluate the psychometric properties and scoring pattern of the Brazilian version of the three-factor eating questionnaire-r21 (TFEQ-R21). Data were collected from 410 undergraduate students. Confirmatory factor analysis was conducted to examine the factor structure of the TFEQ-R21. Convergent and discriminant validity also was assessed. Cluster analysis was performed to investigate scoring patterns. In assessing the quality setting, the model was considered satisfactory (χ 2 /gl = 2.24, CFI = 0.97, TLI = 0.96, RMSEA = 0.05). The instrument was also considered appropriate in relation to the discriminant and convergent validity. There was a positive correlation between body mass index and the dimensions of cognitive restraint (r s  = 0.449, p < 0.001) and emotional eating (r s  = 0.112, p = 0.023). Using cluster analysis three respondent profiles were identified. The profile "A" was associated with appropriate weight, the "B" was characterized by high scores in cognitive restraint dimension, and the cluster "C" focused individuals who had higher scores on the uncontrolled eating and emotional eating dimensions. The Brazilian version of TFEQ-R21 has adequate psychometric properties, and the identified response profiles offer a promising prospect for its use in clinical practice, in weight loss interventions.

Space-time analysis of Down syndrome: results consistent with transient pre-disposing contagious agent.

PubMed

McNally, Richard J Q; Rankin, Judith; Shirley, Mark D F; Rushton, Stephen P; Pless-Mulloli, Tanja

2008-10-01

Whilst maternal age is an established risk factor for Patau syndrome (trisomy 13), Edwards syndrome (trisomy 18) and Down syndrome (trisomy 21), the aetiology and contribution of genetic and environmental factors remains unclear. We analysed for space-time clustering using high quality fully population-based data from a geographically defined region. The study included all cases of Patau, Edwards and Down syndrome, delivered during 1985-2003 and resident in the former Northern Region of England, including terminations of pregnancy for fetal anomaly. We applied the K-function test for space-time clustering with fixed thresholds of close in space and time using residential addresses at time of delivery. The Knox test was used to indicate the range over which the clustering effect occurred. Tests were repeated using nearest neighbour (NN) thresholds to adjust for variable population density. The study analysed 116 cases of Patau syndrome, 240 cases of Edwards syndrome and 1084 cases of Down syndrome. There was evidence of space-time clustering for Down syndrome (fixed threshold of close in space: P = 0.01, NN threshold: P = 0.02), but little or no clustering for Patau (P = 0.57, P = 0.19) or Edwards (P = 0.37, P = 0.06) syndromes. Clustering of Down syndrome was associated with cases from more densely populated areas and evidence of clustering persisted when cases were restricted to maternal age <40 years. The highly novel space-time clustering for Down syndrome suggests an aetiological role for transient environmental factors, such as infections.

Spatial distribution and ecological risk assessment of heavy metal on surface sediment in west part of Java Sea

NASA Astrophysics Data System (ADS)

Effendi, Hefni; Wardiatno, Yusli; Kawaroe, Mujizat; Mursalin; Fauzia Lestari, Dea

2017-01-01

The surface sediments were identified from west part of Java Sea to evaluate spatial distribution and ecological risk potential of heavy metals (Hg, As, Cd, Cr, Cu, Pb, Zn and Ni). The samples were taken from surface sediment (<0.5 m) in 26 m up to 80 m water depth with Eikman grab. The average material composition on sediment samples were clay (9.86%), sand (8.57%) and mud sand (81.57%). The analysis showed that Pb (11.2%), Cd (49.7%), and Ni (59.5%) exceeded of Probably Effect Level (PEL). Base on ecological risk analysis, {{Cd }}≤ft( {E_r^i:300.64} \\right) and {{Cr }}≤ft( {E_r^i:0.02} \\right) were categorized to high risk and low risk criteria. The ecological risk potential sequences of this study were Cd>Hg>Pb>Ni>Cu>As>Zn>Cr. Furthermore, the result of multivariate statistical analysis shows that correlation among heavy metals (As/Ni, Cd/Ni, and Cu/Zn) and heavy metals with Risk Index (Cd/Ri and Ni/Ri) had positive correlation in significance level p<0.05. Total variance of analysis factor was 80.04% and developed into 3 factors (eigenvalues >1). On the cluster analysis, Cd, Ni, Pb were identified as fairly high contaminations level (cluster 1), Hg as moderate contamination level (cluster 2) and Cu, Zn, Cr with lower contamination level (cluster 3).

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.

Socioeconomic Status (SES) and Childhood Acute Myeloid Leukemia (AML) Mortality

PubMed Central

Knoble, Naomi B.; Alderfer, Melissa A.; Hossain, Md Jobayer

2016-01-01

Socioeconomic status (SES) is a complex construct of multiple indicators, known to impact cancer outcomes, but has not been adequately examined among pediatric AML patients. This study aimed to identify the patterns of co-occurrence of multiple community-level SES indicators and to explore associations between various patterns of these indicators and pediatric AML mortality risk. A nationally representative US sample of 3,651 pediatric AML patients, aged 0–19 years at diagnosis was drawn from 17 Surveillance, Epidemiology, and End Results (SEER) database registries created between 1973 and 2012. Factor analysis, cluster analysis, stratified univariable and multivariable Cox proportional hazards models were used. Four SES factors accounting for 87% of the variance in SES indicators were identified: F1) economic/educational disadvantage, less immigration; F2) immigration-related features (foreign-born, language-isolation, crowding), less mobility F3) housing instability; and, F4) absence of moving. F1 and F3 showed elevated risk of mortality, adjusted hazards ratios (aHR) (95% CI): 1.07(1.02–1.12) and 1.05(1.00–1.10), respectively. Seven SES-defined cluster groups were identified. Cluster 1: (low economic/educational disadvantage, few immigration-related features, and residential-stability) showed the minimum risk of mortality. Compared to Cluster 1, Cluster 3: (high economic/educational disadvantage, high-mobility) and Cluster 6: (moderately-high economic/educational disadvantages, housing-instability and immigration-related features) exhibited substantially greater risk of mortality, aHR(95% CI) = 1.19(1.0–1.4) and 1.23 (1.1–1.5), respectively. Factors of correlated SES-indicators and their pattern-based groups demonstrated differential risks in the pediatric AML mortality indicating the need of special public-health attention in areas with economic-educational disadvantages, housing-instability and immigration-related features. PMID:27543948

Clusters and Factors Associated with Complementary Basic Education in Tanzania Mainland

ERIC Educational Resources Information Center

Edwin, Paul; Amina, Msengwa S.; Godwin, Naimani M.

2017-01-01

Complimentary Basic Education in Tanzania (COBET) is a community-based programme initiated in 1999 to provide formal education system opportunity to over aged children or children above school age. The COBET program was analyzed using secondary data collected from 21 regions from 2008 to 2012. Cluster analysis was applied to classify the 21…

Russian consumers' motives for food choice.

PubMed

Honkanen, Pirjo; Frewer, Lynn

2009-04-01

Knowledge about food choice motives which have potential to influence consumer consumption decisions is important when designing food and health policies, as well as marketing strategies. Russian consumers' food choice motives were studied in a survey (1081 respondents across four cities), with the purpose of identifying consumer segments based on these motives. These segments were then profiled using consumption, attitudinal and demographic variables. Face-to-face interviews were used to sample the data, which were analysed with two-step cluster analysis (SPSS). Three clusters emerged, representing 21.5%, 45.8% and 32.7% of the sample. The clusters were similar in terms of the order of motivations, but differed in motivational level. Sensory factors and availability were the most important motives for food choice in all three clusters, followed by price. This may reflect the turbulence which Russia has recently experienced politically and economically. Cluster profiles differed in relation to socio-demographic factors, consumption patterns and attitudes towards health and healthy food.

Multivariate Analysis of Remains of Molluscan Foods Consumed by Latest Pleistocene and Holocene Humans in Nerja Cave, Málaga, Spain

NASA Astrophysics Data System (ADS)

Serrano, Francisco; Guerra-Merchán, Antonio; Lozano-Francisco, Carmen; Vera-Peláez, José Luis

1997-09-01

Nerja Cave is a karstic cavity used by humans from Late Paleolithic to post-Chalcolithic times. Remains of molluscan foods in the uppermost Pleistocene and Holocene sediments were studied with cluster analysis and principal components analysis, in both Qand Rmodes. The results from cluster analysis distinguished interval groups mainly in accordance with chronology and distinguished assemblages of species mainly according to habitat. Significant changes in the shellfish diet through time were revealed. In the Late Magdalenian, most molluscs consumed consisted of pulmonate gastropods and species from sandy sea bottoms. The Epipaleolithic diet was more varied and included species from rocky shorelines. From the Neolithic onward most molluscs consumed were from rocky shorelines. From the principal components analysis in Qmode, the first factor reflected mainly changes in the predominant capture environment, probably because of major paleogeographic changes. The second factor may reflect selective capture along rocky coastlines during certain times. The third factor correlated well with the sea-surface temperature curve in the western Mediterranean (Alboran Sea) during the late Quaternary.

Economic and Demographic Factors Impacting Placement of Students with Autism

ERIC Educational Resources Information Center

Kurth, Jennifer A.; Mastergeorge, Ann M.; Paschall, Katherine

2016-01-01

Educational placement of students with autism is often associated with child factors, such as IQ and communication skills. However, variability in placement patterns across states suggests that other factors are at play. This study used hierarchical cluster analysis techniques to identify demographic, economic, and educational covariates…

Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

ERIC Educational Resources Information Center

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

2011-01-01

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

Graph analysis of cell clusters forming vascular networks

NASA Astrophysics Data System (ADS)

Alves, A. P.; Mesquita, O. N.; Gómez-Gardeñes, J.; Agero, U.

2018-03-01

This manuscript describes the experimental observation of vasculogenesis in chick embryos by means of network analysis. The formation of the vascular network was observed in the area opaca of embryos from 40 to 55 h of development. In the area opaca endothelial cell clusters self-organize as a primitive and approximately regular network of capillaries. The process was observed by bright-field microscopy in control embryos and in embryos treated with Bevacizumab (Avastin), an antibody that inhibits the signalling of the vascular endothelial growth factor (VEGF). The sequence of images of the vascular growth were thresholded, and used to quantify the forming network in control and Avastin-treated embryos. This characterization is made by measuring vessels density, number of cell clusters and the largest cluster density. From the original images, the topology of the vascular network was extracted and characterized by means of the usual network metrics such as: the degree distribution, average clustering coefficient, average short path length and assortativity, among others. This analysis allows to monitor how the largest connected cluster of the vascular network evolves in time and provides with quantitative evidence of the disruptive effects that Avastin has on the tree structure of vascular networks.

Gender-related dimensions of childhood adversities in the general population.

PubMed

Coêlho, Bruno M; Santana, Geilson L; Viana, Maria C; Andrade, Laura H; Wang, Yuan-Pang

2018-06-11

Childhood adversities (CAs) comprise a group of negative experiences individuals may suffer in their lifetimes. The goal of the present study was to investigate the cluster discrimination of CAs through psychometric determination of the common attributes of such experiences for men and women. Parental mental illness, substance misuse, criminality, death, divorce, other parental loss, family violence, physical abuse, sexual abuse, neglect, physical illness, and economic adversity were assessed in a general-population sample (n=5,037). Exploratory and confirmatory factor analysis determined gender-related dimensions of CA. The contribution of each individual adversity was explored through Rasch analysis. Adversities were reported by 53.6% of the sample. A three-factor model of CA dimensions fit the data better for men, and a two-factor model for women. For both genders, the dimension of family maladjustment - encompassing physical abuse, neglect, parental mental disorders, and family violence - was the core cluster of CAs. Women endorsed more CAs than men. Rasch analysis found that sexual abuse, physical illness, parental criminal behavior, parental divorce, and economic adversity were difficult to report in face-to-face interviews. CAs embrace sensitive personal information, clustering of which differed by gender. Acknowledging CAs may have an impact on medical and psychiatric outcomes in adulthood.

Understanding the motives for food choice in Western Balkan Countries.

PubMed

Milošević, Jasna; Žeželj, Iris; Gorton, Matthew; Barjolle, Dominique

2012-02-01

Substantial empirical evidence exists regarding the importance of different factors underlying food choice in Western Europe. However, research results on eating habits and food choice in the Western Balkan Countries (WBCs) remain scarce. A Food Choice Questionnaire (FCQ), an instrument that measures the reported importance of nine factors underlying food choice, was administered to a representative sample of 3085 adult respondents in six WBCs. The most important factors reported are sensory appeal, purchase convenience, and health and natural content; the least important are ethical concern and familiarity. The ranking of food choice motives across WBCs was strikingly similar. Factor analysis revealed eight factors compared to nine in the original FCQ model: health and natural content scales loaded onto one factor as did familiarity and ethical concern; the convenience scale items generated two factors, one related to purchase convenience and the other to preparation convenience. Groups of consumers with similar motivational profiles were identified using cluster analysis. Each cluster has distinct food purchasing behavior and socio-economic characteristics, for which appropriate public health communication messages can be drawn. Copyright © 2011 Elsevier Ltd. All rights reserved.

Nationwide analysis on the impact of socioeconomic land use factors and incidence of urothelial carcinoma.

PubMed

Brandt, Maximilian P; Gust, Kilian M; Mani, Jens; Vallo, Stefan; Höfner, Thomas; Borgmann, Hendrik; Tsaur, Igor; Thomas, Christian; Haferkamp, Axel; Herrmann, Eva; Bartsch, Georg

2018-02-01

Incidence rates for urothelial carcinoma (UC) have been reported to differ between countries within the European Union (EU). Besides occupational exposure to chemicals, other substances such as tobacco and nitrite in groundwater have been identified as risk factors for UC. We investigated if regional differences in UC incidence rates are associated with agricultural, industrial and residential land use. Newly diagnosed cases of UC between 2003 and 2010 were included. Information within 364 administrative districts of Germany from 2004 for land use factors were obtained and calculated as a proportion of the total area of the respective administrative district and as a smoothed proportion. Furthermore, information on smoking habits was included in our analysis. Kulldorff spatial clustering was used to detect different clusters. A negative binomial model was used to test the spatial association between UC incidence as a ratio of observed versus expected incidence rates, land use and smoking habits. We identified 437,847,834 person years with 171,086 cases of UC. Cluster analysis revealed areas with higher incidence of UC than others (p=0.0002). Multivariate analysis including significant pairwise interactions showed that the environmental factors were independently associated with UC (p<0.001). The RR was 1.066 (95% CI 1.052-1.080), 1.066 (95% CI 1.042-1.089) and 1.067 (95% CI 1.045-1.093) for agricultural, industrial and residential areas, respectively, and 0.996 (95% CI 0.869-0.999) for the proportion of never smokers. This study displays regional differences in incidence of UC in Germany. Additionally, results suggest that socioeconomic factors based on agricultural, industrial and residential land use may be associated with UC incidence rates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characterizing cognitive heterogeneity on the schizophrenia-bipolar disorder spectrum.

PubMed

Van Rheenen, T E; Lewandowski, K E; Tan, E J; Ospina, L H; Ongur, D; Neill, E; Gurvich, C; Pantelis, C; Malhotra, A K; Rossell, S L; Burdick, K E

2017-07-01

Current group-average analysis suggests quantitative but not qualitative cognitive differences between schizophrenia (SZ) and bipolar disorder (BD). There is increasing recognition that cognitive within-group heterogeneity exists in both disorders, but it remains unclear as to whether between-group comparisons of performance in cognitive subgroups emerging from within each of these nosological categories uphold group-average findings. We addressed this by identifying cognitive subgroups in large samples of SZ and BD patients independently, and comparing their cognitive profiles. The utility of a cross-diagnostic clustering approach to understanding cognitive heterogeneity in these patients was also explored. Hierarchical clustering analyses were conducted using cognitive data from 1541 participants (SZ n = 564, BD n = 402, healthy control n = 575). Three qualitatively and quantitatively similar clusters emerged within each clinical group: a severely impaired cluster, a mild-moderately impaired cluster and a relatively intact cognitive cluster. A cross-diagnostic clustering solution also resulted in three subgroups and was superior in reducing cognitive heterogeneity compared with disorder clustering independently. Quantitative SZ-BD cognitive differences commonly seen using group averages did not hold when cognitive heterogeneity was factored into our sample. Members of each corresponding subgroup, irrespective of diagnosis, might be manifesting the outcome of differences in shared cognitive risk factors.

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

NASA Astrophysics Data System (ADS)

Gulgundi, Mohammad Shahid; Shetty, Amba

2018-03-01

Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water.

Gender differences in climacteric symptoms and associated factors in Korean men and women.

PubMed

Yeom, Hyun-E

2018-06-01

Both men and women may experience multifaceted symptoms that are part of natural aging throughout the climacteric period. This study compared the prevalence and severity of climacteric symptoms between genders and identified the underlying clusters of climacteric symptoms and associated factors in midlife men and women. A cross-sectional study was done with 254 middle-aged Korean men (n = 129, M = 50.4) and women (n = 125, M = 49.5). Data were collected by self-administered surveys and analyzed using t-tests, chi-square tests, exploratory factor analysis, and regression analysis. Significant gender differences in overall climacteric symptoms were not detected except for muscle weakness, weight gain, and hot flashes. Climacteric symptoms were clustered as physical, vasomotor-genital, psychological, and metabolic dimensions, with the physical dimension being the most explanatory cluster. A significant gender effect was found only in the metabolic dimension after adjusting for the relevant covariates, and regular eating was significantly associated with all symptom clusters. This study offers evidence that most climacteric symptoms are shared by both men and women and emphasizes the importance of healthier lifestyles in the climacteric transition period. The findings highlight the critical need for integrated assessments of the multifactorial symptoms and of modifying poor lifestyles in both genders throughout the climacteric transition period. Copyright © 2018 Elsevier Inc. All rights reserved.

Sleep, Dietary, and Exercise Behavioral Clusters among Truck Drivers with Obesity: Implications for Interventions

PubMed Central

Olson, Ryan; Thompson, Sharon V.; Wipfli, Brad; Hanson, Ginger; Elliot, Diane L.; Anger, W. Kent; Bodner, Todd; Hammer, Leslie B.; Hohn, Elliot; Perrin, Nancy A.

2015-01-01

Objective Our objectives were to describe a sample of truck drivers, identify clusters of drivers with similar patterns in behaviors affecting energy balance (sleep, diet, and exercise), and test for cluster differences in health and psychosocial factors. Methods Participants’ (n=452, BMI M=37.2, 86.4% male) self-reported behaviors were dichotomized prior to hierarchical cluster analysis, which identified groups with similar behavior co-variation. Cluster differences were tested with generalized estimating equations. Results Five behavioral clusters were identified that differed significantly in age, smoking status, diabetes prevalence, lost work days, stress, and social support, but not in BMI. Cluster 2, characterized by the best sleep quality, had significantly lower lost workdays and stress than other clusters. Conclusions Weight management interventions for drivers should explicitly address sleep, and may be maximally effective after establishing socially supportive work environments that reduce stress exposures. PMID:26949883

Sleep, Dietary, and Exercise Behavioral Clusters Among Truck Drivers With Obesity: Implications for Interventions.

PubMed

Olson, Ryan; Thompson, Sharon V; Wipfli, Brad; Hanson, Ginger; Elliot, Diane L; Anger, W Kent; Bodner, Todd; Hammer, Leslie B; Hohn, Elliot; Perrin, Nancy A

2016-03-01

The objectives of the study were to describe a sample of truck drivers, identify clusters of drivers with similar patterns in behaviors affecting energy balance (sleep, diet, and exercise), and test for cluster differences in health safety, and psychosocial factors. Participants' (n = 452, body mass index M = 37.2, 86.4% male) self-reported behaviors were dichotomized prior to hierarchical cluster analysis, which identified groups with similar behavior covariation. Cluster differences were tested with generalized estimating equations. Five behavioral clusters were identified that differed significantly in age, smoking status, diabetes prevalence, lost work days, stress, and social support, but not in body mass index. Cluster 2, characterized by the best sleep quality, had significantly lower lost workdays and stress than other clusters. Weight management interventions for drivers should explicitly address sleep, and may be maximally effective after establishing socially supportive work environments that reduce stress exposures.

Molecular Fingerprinting of Mycobacterium tuberculosis and Risk Factors for Tuberculosis Transmission in Paris, France, and Surrounding Area

PubMed Central

Gutiérrez, M. C.; Vincent, V.; Aubert, D.; Bizet, J.; Gaillot, O.; Lebrun, L.; Le Pendeven, C.; Le Pennec, M. P.; Mathieu, D.; Offredo, C.; Pangon, B.; Pierre-Audigier, C.

1998-01-01

Forty-three percent of the tuberculosis cases reported in France are from the Ile de France region. The incidence of tuberculosis in this region is 33 cases per 100,000 inhabitants, twice the national average. A restriction fragment length polymorphism (RFLP) analysis was performed with clinical isolates of Mycobacterium tuberculosis isolated during 1995 in 10 hospitals in Paris and surrounding areas to detect tuberculosis transmission and define the factors associated with clustering in this population. The molecular markers used were the insertion sequence IS6110 and the direct repeat (DR) sequence. Social, demographic, and clinical data were collected from the patients’ medical files. Ten patients with isolates with a single copy of IS6110 were excluded from further analysis. Twenty-four patients with false-positive cultures due to laboratory contamination (based on RFLP analysis with IS6110 and examination of patient data) were also excluded. The study was then conducted with 272 strains isolated from 272 patients. Further fingerprinting was performed by using the DR element with strains with patterns by RFLP analysis with IS6110 that differed by one band only and strains with identical patterns by RFLP analysis with IS6110 and with low numbers of copies of IS6110. The combined use of both markers identified unique patterns for 177 strains and clustered 95 (35.7%) strains in 26 groups, each containing isolates from 2 to 12 patients. The clustering was strongly associated with homelessness and the male sex. It was not associated with age, birth in a foreign country, human immunodeficiency virus positivity, or residence in hostels or prison. Isolates from homeless people were often included in large clusters, and homeless people could be the source of tuberculosis transmission for more than 50% of the clustered patients. These results suggest that homeless people play a key role in the spread of M. tuberculosis in the community and that poor socioeconomic conditions are the main risk factors associated with active tuberculosis transmission. PMID:9466764

Clusters of Behaviors and Beliefs Predicting Adolescent Depression: Implications for Prevention

PubMed Central

Paunesku, David; Ellis, Justin; Fogel, Joshua; Kuwabara, Sachiko A; Gollan, Jackie; Gladstone, Tracy; Reinecke, Mark; Van Voorhees, Benjamin W.

2009-01-01

OBJECTIVE Risk factors for various disorders are known to cluster. However, the factor structure for behaviors and beliefs predicting depressive disorder in adolescents is not known. Knowledge of this structure can facilitate prevention planning. METHODS We used the National Longitudinal Study of Adolescent Health (AddHealth) data set to conduct an exploratory factor analysis to identify clusters of behaviors/experiences predicting the onset of major depressive disorder (MDD) at 1-year follow-up (N=4,791). RESULTS Four factors were identified: family/interpersonal relations, self-emancipation, avoidant problem solving/low self-worth, and religious activity. Strong family/interpersonal relations were the most significantly protective against depression at one year follow-up. Avoidant problem solving/low self-worth was not predictive of MDD on its own, but significantly amplified the risks associated with delinquency. CONCLUSION Depression prevention interventions should consider giving family relationships a more central role in their efforts. Programs teaching problem solving skills may be most appropriate for reducing MDD risk in delinquent youth. PMID:20502621

Identifying contextual influences of community reintegration among injured servicemembers.

PubMed

Hawkins, Brent L; McGuire, Francis A; Britt, Thomas W; Linder, Sandra M

2015-01-01

Research suggests that community reintegration (CR) after injury and rehabilitation is difficult for many injured servicemembers. However, little is known about the influence of the contextual factors, both personal and environmental, that influence CR. Framed within the International Classification of Functioning, Disability and Health and Social Cognitive Theory, the quantitative portion of a larger mixed-methods study of 51 injured, community-dwelling servicemembers compared the relative contribution of contextual factors between groups of servicemembers with different levels of CR. Cluster analysis indicated three groups of servicemembers showing low, moderate, and high levels of CR. Statistical analyses identified contextual factors (e.g., personal and environmental factors) that significantly discriminated between CR clusters. Multivariate analysis of variance and discriminant analysis indicated significant contributions of general self-efficacy, services and assistance barriers, physical and structural barriers, attitudes and support barriers, perceived level of disability and/or handicap, work and school barriers, and policy barriers on CR scores. Overall, analyses indicated that injured servicemembers with lower CR scores had lower general self-efficacy scores, reported more difficulty with environmental barriers, and reported their injuries as more disabling.

Evolutionary analysis of groundwater flow: Application of multivariate statistical analysis to hydrochemical data in the Densu Basin, Ghana

NASA Astrophysics Data System (ADS)

Yidana, Sandow Mark; Bawoyobie, Patrick; Sakyi, Patrick; Fynn, Obed Fiifi

2018-02-01

An evolutionary trend has been postulated through the analysis of hydrochemical data of a crystalline rock aquifer system in the Densu Basin, Southern Ghana. Hydrochemcial data from 63 groundwater samples, taken from two main groundwater outlets (Boreholes and hand dug wells) were used to postulate an evolutionary theory for the basin. Sequential factor and hierarchical cluster analysis were used to disintegrate the data into three factors and five clusters (spatial associations). These were used to characterize the controls on groundwater hydrochemistry and its evolution in the terrain. The dissolution of soluble salts and cation exchange processes are the dominant processes controlling groundwater hydrochemistry in the terrain. The trend of evolution of this set of processes follows the pattern of groundwater flow predicted by a calibrated transient groundwater model in the area. The data suggest that anthropogenic activities represent the second most important process in the hydrochemistry. Silicate mineral weathering is the third most important set of processes. Groundwater associations resulting from Q-mode hierarchical cluster analysis indicate an evolutionary pattern consistent with the general groundwater flow pattern in the basin. These key findings are at variance with results of previous investigations and indicate that when carefully done, groundwater hydrochemical data can be very useful for conceptualizing groundwater flow in basins.

A symptom level examination of the relationship between Cluster B personality disorders and patterns of criminality and violence in women.

PubMed

Warren, Janet I; South, Susan C

2009-01-01

The psychometric properties and structure of the Cluster B Personality Disorder criteria (Antisocial, Borderline, Histrionic, and Narcissistic) are examined in a sample of 261 female inmates using a self-report screen followed by a full diagnostic interview. The results of the structural analyses in this sample demonstrated good internal consistency and convergence, but poor discriminant validity between disorders. An exploratory factor analysis found that the structure of these disorders was best accounted for by a four-factor solution that paralleled the Diagnostic and Statistical Manual (DSM-IV-TR; APA, 2000) classification scheme with some significant and notable exceptions. Using the factor scores generated from the factor analysis, the personality profiles of the women were compared with several behavioral indices, including instant offense, institutional infractions, and self-report violence and victimization within the prison. Of particular importance was the consistent relationship observed between narcissistic personality traits and threatening and violent behavior within the prison combined with the impulsive but less malignant presentation of antisocial personality traits among this sample of women. Results are discussed as they inform our understanding of the structural integrity of the four Cluster B diagnostic categories and the relationship of these personality disorders to different types of criminality and violence.

A baseline record of trace elements concentration along the beach placer mining areas of Kanyakumari coast, South India.

PubMed

Simon Peter, T; Chandrasekar, N; John Wilson, J S; Selvakumar, S; Krishnakumar, S; Magesh, N S

2017-06-15

Trace element concentration in the beach placer mining areas of Kanyakumari coast, South India was assessed. Sewage and contaminated sediments from mining sites has contaminated the surface sediments. Enrichment factor indicates moderately severe enrichment for Pb, minor enrichment for Mn, Zn, Ni, Fe and no enrichment for Cr and Cu. The Igeo values show higher concentration of Pb ranging in the scale of 3-4, which shows strong contamination due to high anthropogenic activity such as mining and terrestrial influences into the coastal regions. Correlation coefficient shows that most of the elements are associated with each other except Ni and Pb. Factor analysis reveals that Mn, Zn, Fe, Cr, Pb and Cu are having a significant loading and it indicates that these elements are mainly derived from similar origin. The cluster analysis clearly indicated that the mining areas are grouped under cluster 2 and non-mining areas are clustered under group 1. Copyright © 2017 Elsevier Ltd. All rights reserved.

Classifying At-Risk High School Youth: The Influence of Exposure to Community Violence and Protective Factors on Academic and Health Outcomes

ERIC Educational Resources Information Center

Solberg, V. Scott H.; Carlstom, Aaron H.; Howard, Kimberly A. S.; Jones, Janice E.

2007-01-01

Using cluster analysis, 789 predominately Latino and African American high school youth were classified into varying academic at-risk profiles using self-reported levels of academic confidence, motivation to attend school, perceived family support, connections with teachers and peers, and exposure to violence. Six clusters emerged, 5 of which were…

The acceptability among young Hindus and Muslims of actively ending the lives of newborns with genetic defects.

PubMed

Kamble, Shanmukh; Ahmed, Ramadan; Sorum, Paul Clay; Mullet, Etienne

2014-03-01

To explore the views in non-Western cultures about ending the lives of damaged newborns. 254 university students from India and 150 from Kuwait rated the acceptability of ending the lives of newborns with genetic defects in 54 vignettes consisting of all combinations of four factors: gestational age (term or 7 months); severity of genetic defect (trisomy 21 alone, trisomy 21 with serious morphological abnormalities or trisomy 13 with impending death); the parents' attitude about prolonging care (unknown, in favour or opposed); and the procedure used (withholding treatment, withdrawing it or injecting a lethal substance). Four clusters were identified by cluster analysis and subjected to analysis of variance. Cluster I, labelled 'Never Acceptable', included 4% of the Indians and 59% of the Kuwaitis. Cluster II, 'No Firm Opinion', had little variation in rating from one scenario to the next; it included 38% of the Indians and 18% of the Kuwaitis. In Cluster III, 'Parents' Attitude+Severity+Procedure', all three factors affected the ratings; it was composed of 18% of the Indians and 16% of the Kuwaitis. Cluster IV was called 'Severity+Parents' Attitude' because these had the strongest impact; it was composed of 40% of the Indians and 7% of the Kuwaitis. In accordance with the teachings of Islam versus Hinduism, Kuwaiti students were more likely to oppose ending a newborn's life under all conditions, Indian students more likely to favour it and to judge its acceptability in light of the different circumstances.

Autism spectrum disorder in Down syndrome: cluster analysis of Aberrant Behaviour Checklist data supports diagnosis.

PubMed

Ji, N Y; Capone, G T; Kaufmann, W E

2011-11-01

The diagnostic validity of autism spectrum disorder (ASD) based on Diagnostic and Statistical Manual of Mental Disorders (DSM) has been challenged in Down syndrome (DS), because of the high prevalence of cognitive impairments in this population. Therefore, we attempted to validate DSM-based diagnoses via an unbiased categorisation of participants with a DSM-independent behavioural instrument. Based on scores on the Aberrant Behaviour Checklist - Community, we performed sequential factor (four DS-relevant factors: Autism-Like Behaviour, Disruptive Behaviour, Hyperactivity, Self-Injury) and cluster analyses on a 293-participant paediatric DS clinic cohort. The four resulting clusters were compared with DSM-delineated groups: DS + ASD, DS + None (no DSM diagnosis), DS + DBD (disruptive behaviour disorder) and DS + SMD (stereotypic movement disorder), the latter two as comparison groups. Two clusters were identified with DS + ASD: Cluster 1 (35.1%) with higher disruptive behaviour and Cluster 4 (48.2%) with more severe autistic behaviour and higher percentage of late onset ASD. The majority of participants in DS + None (71.9%) and DS + DBD (87.5%) were classified into Cluster 2 and 3, respectively, while participants in DS + SMD were relatively evenly distributed throughout the four clusters. Our unbiased, DSM-independent analyses, using a rating scale specifically designed for individuals with severe intellectual disability, demonstrated that DSM-based criteria of ASD are applicable to DS individuals despite their cognitive impairments. Two DS + ASD clusters were identified and supported the existence of at least two subtypes of ASD in DS, which deserve further characterisation. Despite the prominence of stereotypic behaviour in DS, the SMD diagnosis was not identified by cluster analysis, suggesting that high-level stereotypy is distributed throughout DS. Further supporting DSM diagnoses, typically behaving DS participants were easily distinguished as a group from those with maladaptive behaviours. © 2011 The Authors. Journal of Intellectual Disability Research © 2011 Blackwell Publishing Ltd.

A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark

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

Gittens, Alex; Kottalam, Jey; Yang, Jiyan

We investigate the performance and scalability of the randomized CX low-rank matrix factorization and demonstrate its applicability through the analysis of a 1TB mass spectrometry imaging (MSI) dataset, using Apache Spark on an Amazon EC2 cluster, a Cray XC40 system, and an experimental Cray cluster. We implemented this factorization both as a parallelized C implementation with hand-tuned optimizations and in Scala using the Apache Spark high-level cluster computing framework. We obtained consistent performance across the three platforms: using Spark we were able to process the 1TB size dataset in under 30 minutes with 960 cores on all systems, with themore » fastest times obtained on the experimental Cray cluster. In comparison, the C implementation was 21X faster on the Amazon EC2 system, due to careful cache optimizations, bandwidth-friendly access of matrices and vector computation using SIMD units. We report these results and their implications on the hardware and software issues arising in supporting data-centric workloads in parallel and distributed environments.« less

Role of Hydrophobic Clusters and Long-Range Contact Networks in the Folding of (α/β)8 Barrel Proteins

PubMed Central

Selvaraj, S.; Gromiha, M. Michael

2003-01-01

Analysis on the three dimensional structures of (α/β)8 barrel proteins provides ample light to understand the factors that are responsible for directing and maintaining their common fold. In this work, the hydrophobically enriched clusters are identified in 92% of the considered (α/β)8 barrel proteins. The residue segments with hydrophobic clusters have high thermal stability. Further, these clusters are formed and stabilized through long-range interactions. Specifically, a network of long-range contacts connects adjacent β-strands of the (α/β)8 barrel domain and the hydrophobic clusters. The implications of hydrophobic clusters and long-range networks in providing a feasible common mechanism for the folding of (α/β)8 barrel proteins are proposed. PMID:12609894

A pyrosequencing assay for the quantitative methylation analysis of the PCDHB gene cluster, the major factor in neuroblastoma methylator phenotype.

PubMed

Banelli, Barbara; Brigati, Claudio; Di Vinci, Angela; Casciano, Ida; Forlani, Alessandra; Borzì, Luana; Allemanni, Giorgio; Romani, Massimo

2012-03-01

Epigenetic alterations are hallmarks of cancer and powerful biomarkers, whose clinical utilization is made difficult by the absence of standardization and of common methods of data interpretation. The coordinate methylation of many loci in cancer is defined as 'CpG island methylator phenotype' (CIMP) and identifies clinically distinct groups of patients. In neuroblastoma (NB), CIMP is defined by a methylation signature, which includes different loci, but its predictive power on outcome is entirely recapitulated by the PCDHB cluster only. We have developed a robust and cost-effective pyrosequencing-based assay that could facilitate the clinical application of CIMP in NB. This assay permits the unbiased simultaneous amplification and sequencing of 17 out of 19 genes of the PCDHB cluster for quantitative methylation analysis, taking into account all the sequence variations. As some of these variations were at CpG doublets, we bypassed the data interpretation conducted by the methylation analysis software to assign the corrected methylation value at these sites. The final result of the assay is the mean methylation level of 17 gene fragments in the protocadherin B cluster (PCDHB) cluster. We have utilized this assay to compare the methylation levels of the PCDHB cluster between high-risk and very low-risk NB patients, confirming the predictive value of CIMP. Our results demonstrate that the pyrosequencing-based assay herein described is a powerful instrument for the analysis of this gene cluster that may simplify the data comparison between different laboratories and, in perspective, could facilitate its clinical application. Furthermore, our results demonstrate that, in principle, pyrosequencing can be efficiently utilized for the methylation analysis of gene clusters with high internal homologies.

Somatosensory nociceptive characteristics differentiate subgroups in people with chronic low back pain: a cluster analysis.

PubMed

Rabey, Martin; Slater, Helen; OʼSullivan, Peter; Beales, Darren; Smith, Anne

2015-10-01

The objectives of this study were to explore the existence of subgroups in a cohort with chronic low back pain (n = 294) based on the results of multimodal sensory testing and profile subgroups on demographic, psychological, lifestyle, and general health factors. Bedside (2-point discrimination, brush, vibration and pinprick perception, temporal summation on repeated monofilament stimulation) and laboratory (mechanical detection threshold, pressure, heat and cold pain thresholds, conditioned pain modulation) sensory testing were examined at wrist and lumbar sites. Data were entered into principal component analysis, and 5 component scores were entered into latent class analysis. Three clusters, with different sensory characteristics, were derived. Cluster 1 (31.9%) was characterised by average to high temperature and pressure pain sensitivity. Cluster 2 (52.0%) was characterised by average to high pressure pain sensitivity. Cluster 3 (16.0%) was characterised by low temperature and pressure pain sensitivity. Temporal summation occurred significantly more frequently in cluster 1. Subgroups were profiled on pain intensity, disability, depression, anxiety, stress, life events, fear avoidance, catastrophizing, perception of the low back region, comorbidities, body mass index, multiple pain sites, sleep, and activity levels. Clusters 1 and 2 had a significantly greater proportion of female participants and higher depression and sleep disturbance scores than cluster 3. The proportion of participants undertaking <300 minutes per week of moderate activity was significantly greater in cluster 1 than in clusters 2 and 3. Low back pain, therefore, does not appear to be homogeneous. Pain mechanisms relating to presentations of each subgroup were postulated. Future research may investigate prognoses and interventions tailored towards these subgroups.

Anthropogenic Enrichment of Heavy Metals in Urban Dust and Possible Corresponding Sources

NASA Astrophysics Data System (ADS)

van Laaten, Neele; Merten, Dirk; Pirrung, Michael

2017-04-01

Atmospheric dust (particulate matter, PM) is regarded as a crucial factor for human health and a major environmental problem in densely populated areas. Due to anthropogenic processes like traffic, waste incineration and industry increased amounts of PM can be detected in those areas. To reduce the amounts detailed knowledge on both the composition of PM and the source contribution in a target area is needed. The latter has, to our knowledge, rarely been regarded in central Europe. Within this study, spider webs from various locations in the city of Jena (Germany), that act as natural trappers of PM, were analyzed for the contents of 27 trace elements using aqua regia digestion followed by ICP-OES and ICP-MS determinations. Aerosol-crust enrichment factors were calculated for selected elements and both a cluster analysis and a factor analysis were executed to identify sources of PM. High values for the enrichment factors clearly show an anthropogenic influence. In addition, the cluster analysis leads to a grouping of the sampling points mainly depending on the kind and volume of traffic at the corresponding locations. Five different possible sources of PM can be found by the factor analysis: Soil erosion (41% of variance), abrasion of rails (16%), tyre and break wear (16%), charcoal combustion (8%) and oil combustion (7%).

Input frequency and lexical variability in phonological development: a survival analysis of word-initial cluster production.

PubMed

Ota, Mitsuhiko; Green, Sam J

2013-06-01

Although it has been often hypothesized that children learn to produce new sound patterns first in frequently heard words, the available evidence in support of this claim is inconclusive. To re-examine this question, we conducted a survival analysis of word-initial consonant clusters produced by three children in the Providence Corpus (0 ; 11-4 ; 0). The analysis took account of several lexical factors in addition to lexical input frequency, including the age of first production, production frequency, neighborhood density and number of phonemes. The results showed that lexical input frequency was a significant predictor of the age at which the accuracy level of cluster production in each word first reached 80%. The magnitude of the frequency effect differed across cluster types. Our findings indicate that some of the between-word variance found in the development of sound production can indeed be attributed to the frequency of words in the child's ambient language.

Rome Foundation-Asian working team report: Asian functional gastrointestinal disorder symptom clusters.

PubMed

Siah, Kewin Tien Ho; Gong, Xiaorong; Yang, Xi Jessie; Whitehead, William E; Chen, Minhu; Hou, Xiaohua; Pratap, Nitesh; Ghoshal, Uday C; Syam, Ari F; Abdullah, Murdani; Choi, Myung-Gyu; Bak, Young-Tae; Lu, Ching-Liang; Gonlachanvit, Sutep; Boon, Chua Seng; Fang, Fan; Cheong, Pui Kuan; Wu, Justin C Y; Gwee, Kok-Ann

2018-06-01

Functional gastrointestinal disorders (FGIDs) are diagnosed by the presence of a characteristic set of symptoms. However, the current criteria-based diagnostic approach is to some extent subjective and largely derived from observations in English-speaking Western patients. We aimed to identify latent symptom clusters in Asian patients with FGID. 1805 consecutive unselected patients with FGID who presented for primary or secondary care to 11 centres across Asia completed a cultural and linguistic adaptation of the Rome III Diagnostic Questionnaire that was translated to the local languages. Principal components factor analysis with varimax rotation was used to identify symptom clusters. Nine symptom clusters were identified, consisting of two oesophageal factors (F6: globus, odynophagia and dysphagia; F9: chest pain and heartburn), two gastroduodenal factors (F5: bloating, fullness, belching and flatulence; F8 regurgitation, nausea and vomiting), three bowel factors (F2: abdominal pain and diarrhoea; F3: meal-related bowel symptoms; F7: upper abdominal pain and constipation) and two anorectal factors (F1: anorectal pain and constipation; F4: diarrhoea, urgency and incontinence). We found that the broad categorisation used both in clinical practice and in the Rome system, that is, broad anatomical divisions, and certain diagnoses with long historical records, that is, IBS with diarrhoea, and chronic constipation, are still valid in our Asian societies. In addition, we found a bowel symptom cluster with meal trigger and a gas cluster that suggests a different emphasis in our populations. Future studies to compare a non-Asian cohort and to match to putative pathophysiology will help to verify our findings. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Factors associated with the growing-finishing performances of swine herds: an exploratory study on serological and herd level indicators.

PubMed

Fablet, C; Rose, N; Grasland, B; Robert, N; Lewandowski, E; Gosselin, M

2018-01-01

Growing and finishing performances of pigs strongly influence farm efficiency and profitability. The performances of the pigs rely on the herd health status and also on several non-infectious factors. Many recommendations for the improvement of the technical performances of a herd are based on the results of studies assessing the effect of one or a limited number of infections or environmental factors. Few studies investigated jointly the influence of both type of factors on swine herd performances. This work aimed at identifying infectious and non-infectious factors associated with the growing and finishing performances of 41 French swine herds. Two groups of herds were identified using a clustering analysis: a cluster of 24 herds with the highest technical performance values (mean average daily gain = 781.1 g/day +/- 26.3; mean feed conversion ratio = 2.5 kg/kg +/- 0.1; mean mortality rate = 4.1% +/- 0.9; and mean carcass slaughter weight = 121.2 kg +/- 5.2) and a cluster of 17 herds with the lowest performance values (mean average daily gain =715.8 g/day +/- 26.5; mean feed conversion ratio = 2.6 kg/kg +/- 0.1; mean mortality rate = 6.8% +/- 2.0; and mean carcass slaughter weight = 117.7 kg +/- 3.6). Multiple correspondence analysis was used to identify factors associated with the level of technical performance. Infection with the porcine reproductive and respiratory syndrome virus and the porcine circovirus type 2 were infectious factors associated with the cluster having the lowest performance values. This cluster also featured farrow-to-finish type herds, a short interval between successive batches of pigs (≤3 weeks) and mixing of pigs from different batches in the growing or/and finishing steps. Inconsistency between nursery and fattening building management was another factor associated with the low-performance cluster. The odds of a herd showing low growing-finishing performance was significantly increased when infected by PRRS virus in the growing-finishing steps (OR = 8.8, 95% confidence interval [95% CI]: 1.8-41.7) and belonging to a farrow-to-finish type herd (OR = 5.1, 95% CI = 1.1-23.8). Herd management and viral infections significantly influenced the performance levels of the swine herds included in this study.

Cluster analysis to estimate the risk of preeclampsia in the high-risk Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study

PubMed Central

Marttinen, Pekka; Gillberg, Jussi; Lokki, A. Inkeri; Majander, Kerttu; Ordén, Maija-Riitta; Taipale, Pekka; Pesonen, Anukatriina; Räikkönen, Katri; Hämäläinen, Esa; Kajantie, Eero; Laivuori, Hannele

2017-01-01

Objectives Preeclampsia is divided into early-onset (delivery before 34 weeks of gestation) and late-onset (delivery at or after 34 weeks) subtypes, which may rise from different etiopathogenic backgrounds. Early-onset disease is associated with placental dysfunction. Late-onset disease develops predominantly due to metabolic disturbances, obesity, diabetes, lipid dysfunction, and inflammation, which affect endothelial function. Our aim was to use cluster analysis to investigate clinical factors predicting the onset and severity of preeclampsia in a cohort of women with known clinical risk factors. Methods We recruited 903 pregnant women with risk factors for preeclampsia at gestational weeks 12+0–13+6. Each individual outcome diagnosis was independently verified from medical records. We applied a Bayesian clustering algorithm to classify the study participants to clusters based on their particular risk factor combination. For each cluster, we computed the risk ratio of each disease outcome, relative to the risk in the general population. Results The risk of preeclampsia increased exponentially with respect to the number of risk factors. Our analysis revealed 25 number of clusters. Preeclampsia in a previous pregnancy (n = 138) increased the risk of preeclampsia 8.1 fold (95% confidence interval (CI) 5.7–11.2) compared to a general population of pregnant women. Having a small for gestational age infant (n = 57) in a previous pregnancy increased the risk of early-onset preeclampsia 17.5 fold (95%CI 2.1–60.5). Cluster of those two risk factors together (n = 21) increased the risk of severe preeclampsia to 23.8-fold (95%CI 5.1–60.6), intermediate onset (delivery between 34+0–36+6 weeks of gestation) to 25.1-fold (95%CI 3.1–79.9) and preterm preeclampsia (delivery before 37+0 weeks of gestation) to 16.4-fold (95%CI 2.0–52.4). Body mass index over 30 kg/m2 (n = 228) as a sole risk factor increased the risk of preeclampsia to 2.1-fold (95%CI 1.1–3.6). Together with preeclampsia in an earlier pregnancy the risk increased to 11.4 (95%CI 4.5–20.9). Chronic hypertension (n = 60) increased the risk of preeclampsia 5.3-fold (95%CI 2.4–9.8), of severe preeclampsia 22.2-fold (95%CI 9.9–41.0), and risk of early-onset preeclampsia 16.7-fold (95%CI 2.0–57.6). If a woman had chronic hypertension combined with obesity, gestational diabetes and earlier preeclampsia, the risk of term preeclampsia increased 4.8-fold (95%CI 0.1–21.7). Women with type 1 diabetes mellitus had a high risk of all subgroups of preeclampsia. Conclusion The risk of preeclampsia increases exponentially with respect to the number of risk factors. Early-onset preeclampsia and severe preeclampsia have different risk profile from term preeclampsia. PMID:28350823

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

RSAT 2015: Regulatory Sequence Analysis Tools

PubMed Central

Medina-Rivera, Alejandra; Defrance, Matthieu; Sand, Olivier; Herrmann, Carl; Castro-Mondragon, Jaime A.; Delerce, Jeremy; Jaeger, Sébastien; Blanchet, Christophe; Vincens, Pierre; Caron, Christophe; Staines, Daniel M.; Contreras-Moreira, Bruno; Artufel, Marie; Charbonnier-Khamvongsa, Lucie; Hernandez, Céline; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

2015-01-01

RSAT (Regulatory Sequence Analysis Tools) is a modular software suite for the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, appropriate to genome-wide data sets like ChIP-seq, (ii) transcription factor binding motif analysis (quality assessment, comparisons and clustering), (iii) comparative genomics and (iv) analysis of regulatory variations. Nine new programs have been added to the 43 described in the 2011 NAR Web Software Issue, including a tool to extract sequences from a list of coordinates (fetch-sequences from UCSC), novel programs dedicated to the analysis of regulatory variants from GWAS or population genomics (retrieve-variation-seq and variation-scan), a program to cluster motifs and visualize the similarities as trees (matrix-clustering). To deal with the drastic increase of sequenced genomes, RSAT public sites have been reorganized into taxon-specific servers. The suite is well-documented with tutorials and published protocols. The software suite is available through Web sites, SOAP/WSDL Web services, virtual machines and stand-alone programs at http://www.rsat.eu/. PMID:25904632

Coastal Benthic Boundary Layer Special Research Program. Program Direction and Workshop Recommendations

DTIC Science & Technology

1992-08-01

Faas, " Analysis of the relationship between acoustic reflectivity and sediment porosity," Geophysics 3 4, 546-553 (1969). M. A. Foda , J. Y.-H. Chang...properties, together with in situ measured mechanical, acoustic and electrical properties, should be subjected to factor analysis . Natural clusters could...properties. The mechanical 1 properties and remotely sensed properties are a matrix of information that can be subjected to factor analysis . One can

Spatiotemporal Analysis of the Malaria Epidemic in Mainland China, 2004-2014.

PubMed

Huang, Qiang; Hu, Lin; Liao, Qi-Bin; Xia, Jing; Wang, Qian-Ru; Peng, Hong-Juan

2017-08-01

The purpose of this study is to characterize spatiotemporal heterogeneities in malaria distribution at a provincial level and investigate the association between malaria incidence and climate factors from 2004 to 2014 in China to inform current malaria control efforts. National malaria incidence peaked (4.6/100,000) in 2006 and decreased to a very low level (0.21/100,000) in 2014, and the proportion of imported cases increased from 16.2% in 2004 to 98.2% in 2014. Statistical analyses of global and local spatial autocorrelations and purely spatial scan statistics revealed that malaria was localized in Hainan, Anhui, and Yunnan during 2004-2009 and then gradually shifted and clustered in Yunnan after 2010. Purely temporal clusters shortened to less than 5 months during 2012-2014. The two most likely clusters detected using spatiotemporal analysis occurred in Anhui between July 2005 and November 2007 and Yunnan between January 2010 and June 2012. Correlation coefficients for the association between malaria incidence and climate factors sharply decreased after 2010, and there were zero-month lag effects for climate factors during 2010-2014. Overall, the spatiotemporal distribution of malaria in China changed from relatively scattered (2004-2009) to relatively clustered (2010-2014). As the proportion of imported cases increased, the effect of climate factors on malaria incidence has gradually become weaker since 2011. Therefore, new warning systems should be applied to monitor resurgence and outbreaks of malaria in mainland China, and quarantine at borders should be reinforced to control the increasingly trend of imported malaria cases.

Gene expression factor analysis to differentiate pathways linked to fibromyalgia, chronic fatigue syndrome, and depression in a diverse patient sample

PubMed Central

Iacob, Eli; Light, Alan R.; Donaldson, Gary W.; Okifuji, Akiko; Hughen, Ronald W.; White, Andrea T.; Light, Kathleen C.

2015-01-01

Objective To determine if independent candidate genes can be grouped into meaningful biological factors and if these factors are associated with the diagnosis of chronic fatigue syndrome (CFS) and fibromyalgia (FMS) while controlling for co-morbid depression, sex, and age. Methods We included leukocyte mRNA gene expression from a total of 261 individuals including healthy controls (n=61), patients with FMS only (n=15), CFS only (n=33), co-morbid CFS and FMS (n=79), and medication-resistant (n=42) or medication-responsive (n=31) depression. We used Exploratory Factor Analysis (EFA) on 34 candidate genes to determine factor scores and regression analysis to examine if these factors were associated with specific diagnoses. Results EFA resulted in four independent factors with minimal overlap of genes between factors explaining 51% of the variance. We labeled these factors by function as: 1) Purinergic and cellular modulators; 2) Neuronal growth and immune function; 3) Nociception and stress mediators; 4) Energy and mitochondrial function. Regression analysis predicting these biological factors using FMS, CFS, depression severity, age, and sex revealed that greater expression in Factors 1 and 3 was positively associated with CFS and negatively associated with depression severity (QIDS score), but not associated with FMS. Conclusion Expression of candidate genes can be grouped into meaningful clusters, and CFS and depression are associated with the same 2 clusters but in opposite directions when controlling for co-morbid FMS. Given high co-morbid disease and interrelationships between biomarkers, EFA may help determine patient subgroups in this population based on gene expression. PMID:26097208

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).

Spatial clustering and risk factors of malaria infections in Bata district, Equatorial Guinea.

PubMed

Gómez-Barroso, Diana; García-Carrasco, Emely; Herrador, Zaida; Ncogo, Policarpo; Romay-Barja, María; Ondo Mangue, Martín Eka; Nseng, Gloria; Riloha, Matilde; Santana, Maria Angeles; Valladares, Basilio; Aparicio, Pilar; Benito, Agustín

2017-04-12

The transmission of malaria is intense in the majority of the countries of sub-Saharan Africa, particularly in those that are located along the Equatorial strip. The present study aimed to describe the current distribution of malaria prevalence among children and its environment-related factors as well as to detect malaria spatial clusters in the district of Bata, in Equatorial Guinea. From June to August 2013 a representative cross-sectional survey using a multistage, stratified, cluster-selected sample was carried out of children in urban and rural areas of Bata District. All children were tested for malaria using rapid diagnostic tests (RDTs). Results were linked to each household by global position system data. Two cluster analysis methods were used: hot spot analysis using the Getis-Ord Gi statistic, and the SaTScan™ spatial statistic estimates, based on the assumption of a Poisson distribution to detect spatial clusters. In addition, univariate associations and Poisson regression model were used to explore the association between malaria prevalence at household level with different environmental factors. A total of 1416 children aged 2 months to 15 years living in 417 households were included in this study. Malaria prevalence by RDTs was 47.53%, being highest in the age group 6-15 years (63.24%, p < 0.001). Those children living in rural areas were there malaria risk is greater (65.81%) (p < 0.001). Malaria prevalence was higher in those houses located <1 km from a river and <3 km to a forest (IRR: 1.31; 95% CI 1.13-1.51 and IRR: 1.44; 95% CI 1.25-1.66, respectively). Poisson regression analysis also showed a decrease in malaria prevalence with altitude (IRR: 0.73; 95% CI 0.62-0.86). A significant cluster inland of the district, in rural areas has been found. This study reveals a high prevalence of RDT-based malaria among children in Bata district. Those households situated in inland rural areas, near to a river, a green area and/or at low altitude were a risk factor for malaria. Spatial tools can help policy makers to promote new recommendations for malaria control.

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

PubMed

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

2017-09-01

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

Symptom clusters and quality of life among patients with advanced heart failure

PubMed Central

Yu, Doris SF; Chan, Helen YL; Leung, Doris YP; Hui, Elsie; Sit, Janet WH

2016-01-01

Objectives To identify symptom clusters among patients with advanced heart failure (HF) and the independent relationships with their quality of life (QoL). Methods This is the secondary data analysis of a cross-sectional study which interviewed 119 patients with advanced HF in the geriatric unit of a regional hospital in Hong Kong. The symptom profile and QoL were assessed by using the Edmonton Symptom Assessment Scale (ESAS) and the McGill QoL Questionnaire. Exploratory factor analysis was used to identify the symptom clusters. Hierarchical regression analysis was used to examine the independent relationships with their QoL, after adjusting the effects of age, gender, and comorbidities. Results The patients were at an advanced age (82.9 ± 6.5 years). Three distinct symptom clusters were identified: they were the distress cluster (including shortness of breath, anxiety, and depression), the decondition cluster (fatigue, drowsiness, nausea, and reduced appetite), and the discomfort cluster (pain, and sense of generalized discomfort). These three symptom clusters accounted for 63.25% of variance of the patients' symptom experience. The small to moderate correlations between these symptom clusters indicated that they were rather independent of one another. After adjusting the age, gender and comorbidities, the distress (β = −0.635, P < 0.001), the decondition (β = −0.148, P = 0.01), and the discomfort (β = −0.258, P < 0.001) symptom clusters independently predicted their QoL. Conclusions This study identified the distinctive symptom clusters among patients with advanced HF. The results shed light on the need to develop palliative care interventions for optimizing the symptom control for this life-limiting disease. PMID:27403150

Breast cancer and symptom clusters during radiotherapy.

PubMed

Matthews, Ellyn E; Schmiege, Sarah J; Cook, Paul F; Sousa, Karen H

2012-01-01

Symptom clusters assessment shifts the clinical focus from a specific symptom to the patient's experience as a whole. Few studies have examined breast cancer symptom clusters during treatment, and fewer studies have addressed symptom clusters during radiation therapy (RT). The theoretical underpinning of this study is the Symptoms Experience Model. Research is needed to identify antecedents and consequences of cancer-related symptom clusters. The present study was intended to determine the clustering of symptoms during RT in women with breast cancer and significant correlations among the symptoms, individual characteristics, and mood. A secondary data analysis from a descriptive correlational study of 93 women at weeks 3 to 7 of RT from centers in the mid-Atlantic region of the United States, Symptom Distress Scale, the subscales of the Positive and Negative Affect Scale, Life Orientation Test, and Self-transcendence Scale were completed. Confirmatory factor analysis revealed symptoms grouped into 3 distinct clusters: pain-insomnia-fatigue, cognitive disturbance-outlook, and gastrointestinal. The pain-insomnia-fatigue and cognitive disturbance-outlook clusters were associated with individual characteristics, optimism, self-transcendence, and positive and negative mood. The gastrointestinal cluster correlated significantly only with positive mood. This study provides insight into symptoms that group together and the relationship of symptom clusters to antecedents and mood. These findings underscore the need to define and standardize the measurement of symptom clusters and understand variability in concurrent symptoms. Attention to symptom clusters shifts the clinical focus from a specific symptom to the patient's experience as a whole and helps identify the most effective interventions.

Analysis of local bond-orientational order for liquid gallium at ambient pressure: Two types of cluster structures.

PubMed

Chen, Lin-Yuan; Tang, Ping-Han; Wu, Ten-Ming

2016-07-14

In terms of the local bond-orientational order (LBOO) parameters, a cluster approach to analyze local structures of simple liquids was developed. In this approach, a cluster is defined as a combination of neighboring seeds having at least nb local-orientational bonds and their nearest neighbors, and a cluster ensemble is a collection of clusters with a specified nb and number of seeds ns. This cluster analysis was applied to investigate the microscopic structures of liquid Ga at ambient pressure (AP). The liquid structures studied were generated through ab initio molecular dynamics simulations. By scrutinizing the static structure factors (SSFs) of cluster ensembles with different combinations of nb and ns, we found that liquid Ga at AP contained two types of cluster structures, one characterized by sixfold orientational symmetry and the other showing fourfold orientational symmetry. The SSFs of cluster structures with sixfold orientational symmetry were akin to the SSF of a hard-sphere fluid. On the contrary, the SSFs of cluster structures showing fourfold orientational symmetry behaved similarly as the anomalous SSF of liquid Ga at AP, which is well known for exhibiting a high-q shoulder. The local structures of a highly LBOO cluster whose SSF displayed a high-q shoulder were found to be more similar to the structure of β-Ga than those of other solid phases of Ga. More generally, the cluster structures showing fourfold orientational symmetry have an inclination to resemble more to β-Ga.

A weak lensing analysis of the PLCK G100.2-30.4 cluster

NASA Astrophysics Data System (ADS)

Radovich, M.; Formicola, I.; Meneghetti, M.; Bartalucci, I.; Bourdin, H.; Mazzotta, P.; Moscardini, L.; Ettori, S.; Arnaud, M.; Pratt, G. W.; Aghanim, N.; Dahle, H.; Douspis, M.; Pointecouteau, E.; Grado, A.

2015-07-01

We present a mass estimate of the Planck-discovered cluster PLCK G100.2-30.4, derived from a weak lensing analysis of deep Subaru griz images. We perform a careful selection of the background galaxies using the multi-band imaging data, and undertake the weak lensing analysis on the deep (1 h) r -band image. The shape measurement is based on the Kaiser-Squires-Broadhurst algorithm; we adopt the PSFex software to model the point spread function (PSF) across the field and correct for this in the shape measurement. The weak lensing analysis is validated through extensive image simulations. We compare the resulting weak lensing mass profile and total mass estimate to those obtained from our re-analysis of XMM-Newton observations, derived under the hypothesis of hydrostatic equilibrium. The total integrated mass profiles agree remarkably well, within 1σ across their common radial range. A mass M500 ~ 7 × 1014M⊙ is derived for the cluster from our weak lensing analysis. Comparing this value to that obtained from our reanalysis of XMM-Newton data, we obtain a bias factor of (1-b) = 0.8 ± 0.1. This is compatible within 1σ with the value of (1-b) obtained in Planck 2015 from the calibration of the bias factor using newly available weak lensing reconstructed masses. Based on data collected at Subaru Telescope (University of Tokyo).

Effects of additional data on Bayesian clustering.

PubMed

Yamazaki, Keisuke

2017-10-01

Hierarchical probabilistic models, such as mixture models, are used for cluster analysis. These models have two types of variables: observable and latent. In cluster analysis, the latent variable is estimated, and it is expected that additional information will improve the accuracy of the estimation of the latent variable. Many proposed learning methods are able to use additional data; these include semi-supervised learning and transfer learning. However, from a statistical point of view, a complex probabilistic model that encompasses both the initial and additional data might be less accurate due to having a higher-dimensional parameter. The present paper presents a theoretical analysis of the accuracy of such a model and clarifies which factor has the greatest effect on its accuracy, the advantages of obtaining additional data, and the disadvantages of increasing the complexity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Water-Soluble Phosphine-Protected Au₁₁ Clusters: Synthesis, Electronic Structure, and Chiral Phase Transfer in a Synergistic Fashion.

PubMed

Yao, Hiroshi; Iwatsu, Mana

2016-04-05

Synthesis of atomically precise, water-soluble phosphine-protected gold clusters is still currently limited probably due to a stability issue. We here present the synthesis, magic-number isolation, and exploration of the electronic structures as well as the asymmetric conversion of triphenylphosphine monosulfonate (TPPS)-protected gold clusters. Electrospray ionization mass spectrometry and elemental analysis result in the primary formation of Au11(TPPS)9Cl undecagold cluster compound. Magnetic circular dichroism (MCD) spectroscopy clarifies that extremely weak transitions are present in the low-energy region unresolved in the UV-vis absorption, which can be due to the Faraday B-terms based on the magnetically allowed transitions in the cluster. Asymmetric conversion without changing the nuclearity is remarkable by the chiral phase transfer in a synergistic fashion, which yields a rather small anisotropy factor (g-factor) of at most (2.5-7.0) × 10(-5). Quantum chemical calculations for model undecagold cluster compounds are then used to evaluate the optical and chiroptical responses induced by the chiral phase transfer. On this basis, we find that the Au core distortion is ignorable, and the chiral ion-pairing causes a slight increase in the CD response of the Au11 cluster.

MIXOR: a computer program for mixed-effects ordinal regression analysis.

PubMed

Hedeker, D; Gibbons, R D

1996-03-01

MIXOR provides maximum marginal likelihood estimates for mixed-effects ordinal probit, logistic, and complementary log-log regression models. These models can be used for analysis of dichotomous and ordinal outcomes from either a clustered or longitudinal design. For clustered data, the mixed-effects model assumes that data within clusters are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from clustering of the data. Similarly, for longitudinal data, the mixed-effects approach can allow for individual-varying intercepts and slopes across time, and can estimate the degree to which these time-related effects vary in the population of individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated, along with the effects of model covariates. Examples illustrating usage and features of MIXOR are provided.

Fundamental movement skills and motivational factors influencing engagement in physical activity.

PubMed

Kalaja, Sami; Jaakkola, Timo; Liukkonen, Jarmo; Watt, Anthony

2010-08-01

To assess whether subgroups based on children's fundamental movement skills, perceived competence, and self-determined motivation toward physical education vary with current self-reported physical activity, a sample of 316 Finnish Grade 7 students completed fundamental movement skills measures and self-report questionnaires assessing perceived competence, self-determined motivation toward physical education, and current physical activity. Cluster analysis indicated a three-cluster structure: "Low motivation/low skills profile," "High skills/low motivation profile," and "High skills/high motivation profile." Analysis of variance indicated that students in the third cluster engaged in significantly more physical activity than students of clusters one and two. These results provide support for previous claims regarding the importance of the relationship of fundamental movement skills with continuing engagement in physical activity. High fundamental movement skills, however, may represent only one element in maintaining adolescents' engagement in physical activity.

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

PubMed

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

2017-09-01

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

Race, deprivation, and immigrant isolation: The spatial demography of air-toxic clusters in the continental United States.

PubMed

Liévanos, Raoul S

2015-11-01

This article contributes to environmental inequality outcomes research on the spatial and demographic factors associated with cumulative air-toxic health risks at multiple geographic scales across the United States. It employs a rigorous spatial cluster analysis of census tract-level 2005 estimated lifetime cancer risk (LCR) of ambient air-toxic emissions from stationary (e.g., facility) and mobile (e.g., vehicular) sources to locate spatial clusters of air-toxic LCR risk in the continental United States. It then tests intersectional environmental inequality hypotheses on the predictors of tract presence in air-toxic LCR clusters with tract-level principal component factor measures of economic deprivation by race and immigrant status. Logistic regression analyses show that net of controls, isolated Latino immigrant-economic deprivation is the strongest positive demographic predictor of tract presence in air-toxic LCR clusters, followed by black-economic deprivation and isolated Asian/Pacific Islander immigrant-economic deprivation. Findings suggest scholarly and practical implications for future research, advocacy, and policy. Copyright © 2015 Elsevier Inc. All rights reserved.

Refractory black carbon at the Whistler Peak High Elevation Research Site - Measurements and simulations

NASA Astrophysics Data System (ADS)

Hanna, Sarah J.; Xu, Jun-Wei; Schroder, Jason C.; Wang, Qiaoqiao; McMeeking, Gavin R.; Hayden, Katherine; Leaitch, W. Richard; Macdonald, AnneMarie; von Salzen, Knut; Martin, Randall V.; Bertram, Allan K.

2018-05-01

Measurements of black carbon at remote and high altitude locations provide an important constraint for models. Here we present six months of refractory black carbon (rBC) data collected in July-August of 2009, June-July of 2010, and April-May of 2012 using a single particle soot photometer (SP2) at the remote Whistler High Elevation Research Site in the Coast Mountains of British Columbia (50.06°N, 122.96°W, 2182 m a.m.s.l). In order to reduce regional boundary layer influences, only measurements collected during the night (2000-0800 PST) were considered. Times impacted by local biomass burning were removed from the data set, as were periods of in-cloud sampling. Back trajectories and back trajectory cluster analysis were used to classify the sampled air masses as Southern Pacific, Northern Pacific, Western Pacific/Asian, or Northern Canadian in origin. The largest rBC mass median diameter (182 nm) was seen for air masses in the Southern Pacific cluster, and the smallest (156 nm) was seen for air masses in the Western Pacific/Asian cluster. Considering all the clusters, the median mass concentration of rBC was 25.0 ± 7.6 ng/m3-STP. The Northern Pacific, Southern Pacific, Western Pacific/Asian, and Northern Canada clusters had median mass concentrations of 25.0 ± 7.6, 21.3 ± 6.9, 25.0 ± 7.9, and 40.6 ± 12.9 ng/m3-STP, respectively. We compared these measurements with simulations from the global chemical transport model GEOS-Chem. The default GEOS-Chem simulations overestimated the median rBC mass concentrations for the different clusters by a factor of 1.2-2.2. The largest difference was observed for the Northern Pacific cluster (factor of 2.2) and the smallest difference was observed for the Northern Canada cluster (factor of 1.2). A sensitivity simulation that excluded Vancouver emissions still overestimated the median rBC mass concentrations for the different clusters by a factor of 1.1-2.0. After implementation of a revised wet scavenging scheme, the simulations overestimated the median rBC mass concentrations for the different clusters by a factor of 1.0-2.0.

Suicide Clusters: A Review of Risk Factors and Mechanisms

ERIC Educational Resources Information Center

Haw, Camilla; Hawton, Keith; Niedzwiedz, Claire; Platt, Steve

2013-01-01

Suicide clusters, although uncommon, cause great concern in the communities in which they occur. We searched the world literature on suicide clusters and describe the risk factors and proposed psychological mechanisms underlying the spatio-temporal clustering of suicides (point clusters). Potential risk factors include male gender, being an…

Complete Genome Sequence and Comparative Analysis of the Fish Pathogen Lactococcus garvieae

PubMed Central

Oshima, Kenshiro; Yoshizaki, Mariko; Kawanishi, Michiko; Nakaya, Kohei; Suzuki, Takehito; Miyauchi, Eiji; Ishii, Yasuo; Tanabe, Soichi; Murakami, Masaru; Hattori, Masahira

2011-01-01

Lactococcus garvieae causes fatal haemorrhagic septicaemia in fish such as yellowtail. The comparative analysis of genomes of a virulent strain Lg2 and a non-virulent strain ATCC 49156 of L. garvieae revealed that the two strains shared a high degree of sequence identity, but Lg2 had a 16.5-kb capsule gene cluster that is absent in ATCC 49156. The capsule gene cluster was composed of 15 genes, of which eight genes are highly conserved with those in exopolysaccharide biosynthesis gene cluster often found in Lactococcus lactis strains. Sequence analysis of the capsule gene cluster in the less virulent strain L. garvieae Lg2-S, Lg2-derived strain, showed that two conserved genes were disrupted by a single base pair deletion, respectively. These results strongly suggest that the capsule is crucial for virulence of Lg2. The capsule gene cluster of Lg2 may be a genomic island from several features such as the presence of insertion sequences flanked on both ends, different GC content from the chromosomal average, integration into the locus syntenic to other lactococcal genome sequences, and distribution in human gut microbiomes. The analysis also predicted other potential virulence factors such as haemolysin. The present study provides new insights into understanding of the virulence mechanisms of L. garvieae in fish. PMID:21829716

Defining syndromes using cattle meat inspection data for syndromic surveillance purposes: a statistical approach with the 2005-2010 data from ten French slaughterhouses.

PubMed

Dupuy, Céline; Morignat, Eric; Maugey, Xavier; Vinard, Jean-Luc; Hendrikx, Pascal; Ducrot, Christian; Calavas, Didier; Gay, Emilie

2013-04-30

The slaughterhouse is a central processing point for food animals and thus a source of both demographic data (age, breed, sex) and health-related data (reason for condemnation and condemned portions) that are not available through other sources. Using these data for syndromic surveillance is therefore tempting. However many possible reasons for condemnation and condemned portions exist, making the definition of relevant syndromes challenging.The objective of this study was to determine a typology of cattle with at least one portion of the carcass condemned in order to define syndromes. Multiple factor analysis (MFA) in combination with clustering methods was performed using both health-related data and demographic data. Analyses were performed on 381,186 cattle with at least one portion of the carcass condemned among the 1,937,917 cattle slaughtered in ten French abattoirs. Results of the MFA and clustering methods led to 12 clusters considered as stable according to year of slaughter and slaughterhouse. One cluster was specific to a disease of public health importance (cysticercosis). Two clusters were linked to the slaughtering process (fecal contamination of heart or lungs and deterioration lesions). Two clusters respectively characterized by chronic liver lesions and chronic peritonitis could be linked to diseases of economic importance to farmers. Three clusters could be linked respectively to reticulo-pericarditis, fatty liver syndrome and farmer's lung syndrome, which are related to both diseases of economic importance to farmers and herd management issues. Three clusters respectively characterized by arthritis, myopathy and Dark Firm Dry (DFD) meat could notably be linked to animal welfare issues. Finally, one cluster, characterized by bronchopneumonia, could be linked to both animal health and herd management issues. The statistical approach of combining multiple factor analysis with cluster analysis showed its relevance for the detection of syndromes using available large and complex slaughterhouse data. The advantages of this statistical approach are to i) define groups of reasons for condemnation based on meat inspection data, ii) help grouping reasons for condemnation among a list of various possible reasons for condemnation for which a consensus among experts could be difficult to reach, iii) assign each animal to a single syndrome which allows the detection of changes in trends of syndromes to detect unusual patterns in known diseases and emergence of new diseases.

A geographic analysis of individual and environmental risk factors for hypospadias births

PubMed Central

Winston, Jennifer J; Meyer, Robert E; Emch, Michael E

2014-01-01

Background Hypospadias is a relatively common birth defect affecting the male urinary tract. We explored the etiology of hypospadias by examining its spatial distribution in North Carolina and the spatial clustering of residuals from individual and environmental risk factors. Methods We used data collected by the North Carolina Birth Defects Monitoring Program from 2003-2005 to estimate local Moran's I statistics to identify geographic clustering of overall and severe hypospadias, using 995 overall cases and 16,013 controls. We conducted logistic regression and local Moran's I statistics on standardized residuals to consider the contribution of individual variables (maternal age, maternal race/ethnicity, maternal education, smoking, parity, and diabetes) and environmental variables (block group land cover) to this clustering. Results Local Moran's I statistics indicated significant clustering of overall and severe hypospadias in eastern central North Carolina. Spatial clustering of hypospadias persisted when controlling for individual factors, but diminished somewhat when controlling for environmental factors. In adjusted models, maternal residence in a block group with more than 5% crop cover was associated with overall hypospadias (OR = 1.22; 95% CI = 1.04 – 1.43); that is living in a block group with greater than 5% crop cover was associated with a 22% increase in the odds of having a baby with hypospadias. Land cover was not associated with severe hypospadias. Conclusions This study illustrates the potential contribution of mapping in generating hypotheses about disease etiology. Results suggest that environmental factors including proximity to agriculture may play some role in the spatial distribution of hypospadias. PMID:25196538

Analyzing the Role of Community and Individual Factors in Food Insecurity: Identifying Diverse Barriers Across Clustered Community Members.

PubMed

Jablonski, Becca B R; McFadden, Dawn Thilmany; Colpaart, Ashley

2016-10-01

This paper uses the results from a community food security assessment survey of 684 residents and three focus groups in Pueblo County, Colorado to examine the question: what community and individual factors contribute to or alleviate food insecurity, and are these factors consistent throughout a sub-county population. Importantly, we use a technique called cluster analysis to endogenously determine the key factors pertinent to food access and fruit and vegetable consumption. Our results show significant heterogeneity among sub-population clusters in terms of the community and individual factors that would make it easier to get access to fruits and vegetables. We find two distinct clusters of food insecure populations: the first was significantly less likely to identify increased access to fruits and vegetables proximate to where they live or work as a way to improve their household's healthy food consumption despite being significantly less likely to utilize a personal vehicle to get to the store; the second group did not report significant challenges with access, rather with affordability. We conclude that though interventions focused on improving the local food retail environment may be important for some subsamples of the food insecure population, it is unclear that proximity to a store with healthy food will support enhanced food security for all. We recommend that future research recognizes that determinants of food insecurity may vary within county or zip code level regions, and that multiple interventions that target sub-population clusters may elicit better improvements in access to and consumption of fruits and vegetables.

The use of multicomponent statistical analysis in hydrogeological environmental research.

PubMed

Lambrakis, Nicolaos; Antonakos, Andreas; Panagopoulos, George

2004-04-01

The present article examines the possibilities of investigating NO(3)(-) spread in aquifers by applying multicomponent statistical methods (factor, cluster and discriminant analysis) on hydrogeological, hydrochemical, and environmental parameters. A 4-R-Mode factor model determined from the analysis showed its useful role in investigating hydrogeological parameters affecting NO(3)(-) concentration, such as its dilution by upcoming groundwater of the recharge areas. The relationship between NO(3)(-) concentration and agricultural activities can be determined sufficiently by the first factor which relies on NO(3)(-) and SO(4)(2-) of the same origin-that of agricultural fertilizers. The other three factors of R-Mode analysis are not connected directly to the NO(3)(-) problem. They do however, by extracting the role of the unsaturated zone, show an interesting relationship between organic matter content, thickness and saturated hydraulic conductivity. The application of Hirerarchical Cluster Analysis, based on all possible combinations of classification method, showed two main groups of samples. The first group comprises samples from the edges and the second from the central part of the study area. By the application of Discriminant Analysis it was shown that NO(3)(-) and SO(4)(2-) ions are the most significant variables in the discriminant function. Therefore, the first group is considered to comprise all samples from areas not influenced by fertilizers lying on the edges of contaminating activities such as crop cultivation, while the second comprises all the other samples.

Health and disease phenotyping in old age using a cluster network analysis.

PubMed

Valenzuela, Jesus Felix; Monterola, Christopher; Tong, Victor Joo Chuan; Ng, Tze Pin; Larbi, Anis

2017-11-15

Human ageing is a complex trait that involves the synergistic action of numerous biological processes that interact to form a complex network. Here we performed a network analysis to examine the interrelationships between physiological and psychological functions, disease, disability, quality of life, lifestyle and behavioural risk factors for ageing in a cohort of 3,270 subjects aged ≥55 years. We considered associations between numerical and categorical descriptors using effect-size measures for each variable pair and identified clusters of variables from the resulting pairwise effect-size network and minimum spanning tree. We show, by way of a correspondence analysis between the two sets of clusters, that they correspond to coarse-grained and fine-grained structure of the network relationships. The clusters obtained from the minimum spanning tree mapped to various conceptual domains and corresponded to physiological and syndromic states. Hierarchical ordering of these clusters identified six common themes based on interactions with physiological systems and common underlying substrates of age-associated morbidity and disease chronicity, functional disability, and quality of life. These findings provide a starting point for indepth analyses of ageing that incorporate immunologic, metabolomic and proteomic biomarkers, and ultimately offer low-level-based typologies of healthy and unhealthy ageing.

Clusters of midlife women by physical activity and their racial/ethnic differences.

PubMed

Im, Eun-Ok; Ko, Young; Chee, Eunice; Chee, Wonshik; Mao, Jun James

2017-04-01

The purpose of this study was to identify clusters of midlife women by physical activity and to determine racial/ethnic differences in physical activities in each cluster. This was a secondary analysis of the data from 542 women (157 non-Hispanic [NH] Whites, 127 Hispanics, 135 NH African Americans, and 123 NH Asian) in a larger Internet study on midlife women's attitudes toward physical activity. The instruments included the Barriers to Health Activities Scale, the Physical Activity Assessment Inventory, the Questions on Attitudes toward Physical Activity, Subjective Norm, Perceived Behavioral Control, and Behavioral Intention, and the Kaiser Physical Activity Survey. The data were analyzed using hierarchical cluster analyses, analysis of variance, and multinominal logistic analyses. A three-cluster solution was adopted: cluster 1 (high active living and sports/exercise activity group; 48%), cluster 2 (high household/caregiving and occupational activity group; 27%), and cluster 3 (low active living and sports/exercise activity group; 26%). There were significant racial/ethnic differences in occupational activities of clusters 1 and 3 (all P < 0.01). Compared with cluster 1, cluster 2 tended to have lower family income, less access to health care, higher unemployment, higher perceived barriers scores, and lower social influences scores (all P < 0.01). Compared with cluster 1, cluster 3 tended to have greater obesity, less access to health care, higher perceived barriers scores, more negative attitudes toward physical activity, and lower self-efficacy scores (all P < 0.01). Midlife women's unique patterns of physical activity and their associated factors need to be considered in future intervention development.

Identification of chronic rhinosinusitis phenotypes using cluster analysis.

PubMed

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

2015-05-01

Current clinical classifications of chronic rhinosinusitis (CRS) have been largely defined based upon preconceived notions of factors thought to be important, such as polyp or eosinophil status. Unfortunately, these classification systems have little correlation with symptom severity or treatment outcomes. Unsupervised clustering can be used to identify phenotypic subgroups of CRS patients, describe clinical differences in these clusters and define simple algorithms for classification. A multi-institutional, prospective study of 382 patients with CRS who had failed initial medical therapy completed the Sino-Nasal Outcome Test (SNOT-22), Rhinosinusitis Disability Index (RSDI), Medical Outcomes Study Short Form-12 (SF-12), Pittsburgh Sleep Quality Index (PSQI), and Patient Health Questionnaire (PHQ-2). Objective measures of CRS severity included Brief Smell Identification Test (B-SIT), CT, and endoscopy scoring. All variables were reduced and unsupervised hierarchical clustering was performed. After clusters were defined, variations in medication usage were analyzed. Discriminant analysis was performed to develop a simplified, clinically useful algorithm for clustering. Clustering was largely determined by age, severity of patient reported outcome measures, depression, and fibromyalgia. CT and endoscopy varied somewhat among clusters. Traditional clinical measures, including polyp/atopic status, prior surgery, B-SIT and asthma, did not vary among clusters. A simplified algorithm based upon productivity loss, SNOT-22 score, and age predicted clustering with 89% accuracy. Medication usage among clusters did vary significantly. A simplified algorithm based upon hierarchical clustering is able to classify CRS patients and predict medication usage. Further studies are warranted to determine if such clustering predicts treatment outcomes. © 2015 ARS-AAOA, LLC.

Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.

PubMed

McParland, D; Phillips, C M; Brennan, L; Roche, H M; Gormley, I C

2017-12-10

The LIPGENE-SU.VI.MAX study, like many others, recorded high-dimensional continuous phenotypic data and categorical genotypic data. LIPGENE-SU.VI.MAX focuses on the need to account for both phenotypic and genetic factors when studying the metabolic syndrome (MetS), a complex disorder that can lead to higher risk of type 2 diabetes and cardiovascular disease. Interest lies in clustering the LIPGENE-SU.VI.MAX participants into homogeneous groups or sub-phenotypes, by jointly considering their phenotypic and genotypic data, and in determining which variables are discriminatory. A novel latent variable model that elegantly accommodates high dimensional, mixed data is developed to cluster LIPGENE-SU.VI.MAX participants using a Bayesian finite mixture model. A computationally efficient variable selection algorithm is incorporated, estimation is via a Gibbs sampling algorithm and an approximate BIC-MCMC criterion is developed to select the optimal model. Two clusters or sub-phenotypes ('healthy' and 'at risk') are uncovered. A small subset of variables is deemed discriminatory, which notably includes phenotypic and genotypic variables, highlighting the need to jointly consider both factors. Further, 7 years after the LIPGENE-SU.VI.MAX data were collected, participants underwent further analysis to diagnose presence or absence of the MetS. The two uncovered sub-phenotypes strongly correspond to the 7-year follow-up disease classification, highlighting the role of phenotypic and genotypic factors in the MetS and emphasising the potential utility of the clustering approach in early screening. Additionally, the ability of the proposed approach to define the uncertainty in sub-phenotype membership at the participant level is synonymous with the concepts of precision medicine and nutrition. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Image Patch Analysis of Sunspots and Active Regions

NASA Astrophysics Data System (ADS)

Moon, K.; Delouille, V.; Hero, A.

2017-12-01

The flare productivity of an active region has been observed to be related to its spatial complexity. Separating active regions that are quiet from potentially eruptive ones is a key issue in space weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature does not use all of the information present in the observations. In our work, we present an image patch analysis for characterizing sunspots and active regions. We first propose fine-scale quantitative descriptors for an active region's complexity such as intrinsic dimension, and we relate them to the Mount Wilson classification. Second, we introduce a new clustering of active regions that is based on the local geometry observed in Line of Sight magnetogram and continuum images. To obtain this local geometry, we use a reduced-dimension representation of an active region that is obtained by factoring the corresponding data matrix comprised of local image patches using the singular value decomposition. The resulting factorizations of active regions can be compared via the definition of appropriate metrics on the factors. The distances obtained from these metrics are then used to cluster the active regions. Results. We find that these metrics result in natural clusterings of active regions. The clusterings are related to large scale descriptors of an active region such as its size, its local magnetic field distribution, and its complexity as measured by the Mount Wilson classification scheme. We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the R-value.

Assessment of stem cell differentiation based on genome-wide expression profiles.

PubMed

Godoy, Patricio; Schmidt-Heck, Wolfgang; Hellwig, Birte; Nell, Patrick; Feuerborn, David; Rahnenführer, Jörg; Kattler, Kathrin; Walter, Jörn; Blüthgen, Nils; Hengstler, Jan G

2018-07-05

In recent years, protocols have been established to differentiate stem and precursor cells into more mature cell types. However, progress in this field has been hampered by difficulties to assess the differentiation status of stem cell-derived cells in an unbiased manner. Here, we present an analysis pipeline based on published data and methods to quantify the degree of differentiation and to identify transcriptional control factors explaining differences from the intended target cells or tissues. The pipeline requires RNA-Seq or gene array data of the stem cell starting population, derived 'mature' cells and primary target cells or tissue. It consists of a principal component analysis to represent global expression changes and to identify possible problems of the dataset that require special attention, such as: batch effects; clustering techniques to identify gene groups with similar features; over-representation analysis to characterize biological motifs and transcriptional control factors of the identified gene clusters; and metagenes as well as gene regulatory networks for quantitative cell-type assessment and identification of influential transcription factors. Possibilities and limitations of the analysis pipeline are illustrated using the example of human embryonic stem cell and human induced pluripotent cells to generate 'hepatocyte-like cells'. The pipeline quantifies the degree of incomplete differentiation as well as remaining stemness and identifies unwanted features, such as colon- and fibroblast-associated gene clusters that are absent in real hepatocytes but typically induced by currently available differentiation protocols. Finally, transcription factors responsible for incomplete and unwanted differentiation are identified. The proposed method is widely applicable and allows an unbiased and quantitative assessment of stem cell-derived cells.This article is part of the theme issue 'Designer human tissue: coming to a lab near you'. © 2018 The Author(s).

Cluster analysis identifies three urodynamic patterns in patients with orthotopic neobladder reconstruction.

PubMed

Kim, Kwang Hyun; Yoon, Hyun Suk; Song, Wan; Choo, Hee Jung; Yoon, Hana; Chung, Woo Sik; Sim, Bong Suk; Lee, Dong Hyeon

2017-01-01

To classify patients with orthotopic neobladder based on urodynamic parameters using cluster analysis and to characterize the voiding function of each group. From January 2012 to November 2015, 142 patients with bladder cancer underwent radical cystectomy and Studer neobladder reconstruction at our institute. Of the 142 patients, 103 with complete urodynamic data and information on urinary functional outcomes were included in this study. K-means clustering was performed with urodynamic parameters which included maximal cystometric capacity, residual volume, maximal flow rate, compliance, and detrusor pressure at maximum flow rate. Three groups emerged by cluster analysis. Urodynamic parameters and urinary function outcomes were compared between three groups. Group 1 (n = 44) had ideal urodynamic parameters with a mean maximal bladder capacity of 513.3 ml and mean residual urine volume of 33.1 ml. Group 2 (n = 42) was characterized by small bladder capacity with low compliance. Patients in group 2 had higher rates of daytime incontinence and nighttime incontinence than patients in group 1. Group 3 (n = 17) was characterized by large residual urine volume with high compliance. When we examined gender differences in urodynamics and functional outcomes, residual urine volume and the rate of daytime incontinence were only marginally significant. However, females were significantly more likely to belong to group 2 or 3 (P = 0.003). In multivariate analysis to identify factors associated with group 1 which has the most ideal urodynamic pattern, age (OR 0.95, P = 0.017) and male gender (OR 7.57, P = 0.003) were identified as significant factors. While patients with ileal neobladder present with various voiding symptoms, three urodynamic patterns were identified by cluster analysis. Approximately half of patients had ideal urodynamic parameters. The other two groups were characterized by large residual urine and small capacity bladder with low compliance. Young age and male gender appear to have a favorable impact on urodynamic and voiding outcomes in patients undergoing orthotopic neobladder reconstruction.

Career paths in physicians' postgraduate training - an eight-year follow-up study.

PubMed

Buddeberg-Fischer, Barbara; Stamm, Martina; Klaghofer, Richard

2010-10-06

To date, there are hardly any studies on the choice of career path in medical school graduates. The present study aimed to investigate what career paths can be identified in the course of postgraduate training of physicians; what factors have an influence on the choice of a career path; and in what way the career paths are correlated with career-related factors as well as with work-life balance aspirations. The data reported originates from five questionnaire surveys of the prospective SwissMedCareer Study, beginning in 2001 (T1, last year of medical school). The study sample consisted of 358 physicians (197 females, 55%; 161 males, 45%) participating at each assessment from T2 (2003, first year of residency) to T5 (2009, seventh year of residency), answering the question: What career do you aspire to have? Furthermore, personal characteristics, chosen specialty, career motivation, mentoring experience, work-life balance as well as workload, career success and career satisfaction were assessed. Career paths were analysed with cluster analysis, and differences between clusters analysed with multivariate methods. The cluster analysis revealed four career clusters which discriminated distinctly between each other: (1) career in practice, (2) hospital career, (3) academic career, and (4) changing career goal. From T3 (third year of residency) to T5, respondents in Cluster 1-3 were rather stable in terms of their career path aspirations, while those assigned to Cluster 4 showed a high fluctuation in their career plans. Physicians in Cluster 1 showed high values in extraprofessional concerns and often consider part-time work. Cluster 2 and 3 were characterised by high instrumentality, intrinsic and extrinsic career motivation, career orientation and high career success. No cluster differences were seen in career satisfaction. In Cluster 1 and 4, females were overrepresented. Trainees should be supported to stay on the career path that best suits his/her personal and professional profile. Attention should be paid to the subgroup of physicians in Cluster 4 switching from one to another career goal in the course of their postgraduate training.

Workplace cluster of Bell’s palsy in Lima, Peru

PubMed Central

2014-01-01

Background We report on a workplace cluster of Bell’s palsy that occurred within a four-month period in 2011 among employees of a three-story office building in Lima, Peru and our investigation to determine the etiology and associated risk factors. Findings An outbreak investigation was conducted to identify possible common infectious or environmental exposures and included patient interviews, reviews of medical records, an epidemiologic survey, serological analysis for IgM and IgG antibodies to putative Bell’s palsy-inducing pathogens, and an environmental exposure assessment of the office building. Three cases of Bell’s palsy were reported among 65 at-risk employees, attack rate 4.6%. Although two patients had underlying risk factors, there was no clear association or common identifiable risk factor among all cases. Serologic analysis showed no evidence of recent infections, and air and water sample measures of all known chemical or neurotoxins were below maximum allowable concentrations for exposure. Conclusions An infection spread among workplace employees could not be excluded as a potential cause of this cluster; however, it was unlikely a pathogen commonly associated with individual cases of Bell’s palsy. Although a specific etiology was not identified among all cases, we believe this methodology will aid future outbreak investigations of Bell’s palsy and a better understanding of its etiology. While environmental assessments may be useful in their ability to ascertain the cause of clusters of Bell’s palsy, future investigations should prioritize focus on common infectious etiology. PMID:24885256

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.

Neural activity in relation to empirically derived personality syndromes in depression using a psychodynamic fMRI paradigm

PubMed Central

Taubner, Svenja; Wiswede, Daniel; Kessler, Henrik

2013-01-01

Objective: The heterogeneity between patients with depression cannot be captured adequately with existing descriptive systems of diagnosis and neurobiological models of depression. Furthermore, considering the highly individual nature of depression, the application of general stimuli in past research efforts may not capture the essence of the disorder. This study aims to identify subtypes of depression by using empirically derived personality syndromes, and to explore neural correlates of the derived personality syndromes. Materials and Methods: In the present exploratory study, an individually tailored and psychodynamically based functional magnetic resonance imaging paradigm using dysfunctional relationship patterns was presented to 20 chronically depressed patients. Results from the Shedler–Westen Assessment Procedure (SWAP-200) were analyzed by Q-factor analysis to identify clinically relevant subgroups of depression and related brain activation. Results: The principle component analysis of SWAP-200 items from all 20 patients lead to a two-factor solution: “Depressive Personality” and “Emotional-Hostile-Externalizing Personality.” Both factors were used in a whole-brain correlational analysis but only the second factor yielded significant positive correlations in four regions: a large cluster in the right orbitofrontal cortex (OFC), the left ventral striatum, a small cluster in the left temporal pole, and another small cluster in the right middle frontal gyrus. Discussion: The degree to which patients with depression score high on the factor “Emotional-Hostile-Externalizing Personality” correlated with relatively higher activity in three key areas involved in emotion processing, evaluation of reward/punishment, negative cognitions, depressive pathology, and social knowledge (OFC, ventral striatum, temporal pole). Results may contribute to an alternative description of neural correlates of depression showing differential brain activation dependent on the extent of specific personality syndromes in depression. PMID:24363644

Clustering of obesity and dental caries with lifestyle factors among Danish adolescents.

PubMed

Cinar, Ayse Basak; Christensen, Lisa Boge; Hede, Borge

2011-01-01

To assess any clustering between obesity, dental health, and lifestyle factors (dietary patterns, physical activity, smoking, and alcohol consumption) among adolescents. A cluster sample of 15-year-old Danish adolescents (DA) from eight municipalities was selected. Self-reported questionnaires for adolescents and their mothers to assess body-mass index (BMI), socioeconomic and lifestyle factors, and clinical examinations to examine adolescents' dental status (DMFT) were used. Descriptive statistics, chi-square tests, and factor analysis were applied. The mean DMFT was 2.03 and mean BMI was 21.30 among DA.Of the whole sample, 62% experienced caries (DMFT > 0) and 16% were classified as obese. No association appeared between obesity and DMFT (p > 0.05). Most adolescents were likely to have breakfast every day (76%), but their daily consumption of fruit was lower (38%). More than half of adolescents reported having physical exercise (66%) and no alcohol consumption (57%). Smokers were more likely to consume alcohol (80%) but less likely to exercise (44%) than nonsmokers (alcohol consumption, 55%; exercise, 68%), (P < 0.05). Principal component analysis revealed that DMFT and obesity were interrelated in DA. In line with earlier studies, obesity and dental caries share common lifestyle factors among adolescents, regardless of nationality and different health-care systems. Thus, it seems that dental health is a global health concern. There is a need for collaboration between dental and general health-care providers to manage both obesity and dental caries in adolescents by using a holistic approach.

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

PubMed Central

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

2014-01-01

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

Air Pollution, Climate, and Heart Disease

MedlinePlus

... CJ , Ezzati M , AlMazroa MA , Memish ZA . A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet . 2012 ; 380 : 2224 – 2260 . OpenUrl CrossRef ...

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

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

USGS Publications Warehouse

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

2002-01-01

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

UFVA, A Combined Linear and Nonlinear Factor Analysis Program Package for Chemical Data Evaluation.

DTIC Science & Technology

1980-11-01

that one cluster consists of the monoterpenes and Isoprene; the second is of the sesquiterpenes. Compound 8 (Caryophyllene) should therefore belong to...two clusters very clearly (Fig. 6). Figure 6 The very similar fragmentation pattern of Isoprene and the monoterpenes is reflected by their close...13 of another set of 13 terpene components. These are Isoprene, four monoterpenes (Myrcene, Menthol, Camphene, Umbellulone), four sesquiterpenes

Using multivariate techniques to assess the effects of urbanization on surface water quality: a case study in the Liangjiang New Area, China.

PubMed

Luo, Kun; Hu, Xuebin; He, Qiang; Wu, Zhengsong; Cheng, Hao; Hu, Zhenlong; Mazumder, Asit

2017-04-01

Rapid urbanization in China has been causing dramatic deterioration in the water quality of rivers and threatening aquatic ecosystem health. In this paper, multivariate techniques, such as factor analysis (FA) and cluster analysis (CA), were applied to analyze the water quality datasets for 19 rivers in Liangjiang New Area (LJNA), China, collected in April (dry season) and September (wet season) of 2014 and 2015. In most sampling rivers, total phosphorus, total nitrogen, and fecal coliform exceeded the Class V guideline (GB3838-2002), which could thereby threaten the water quality in Yangtze and Jialing Rivers. FA clearly identified the five groups of water quality variables, which explain majority of the experimental data. Nutritious pollution, seasonal changes, and construction activities were three key factors influencing rivers' water quality in LJNA. CA grouped 19 sampling sites into two clusters, which located at sub-catchments with high- and low-level urbanization, respectively. One-way ANOVA showed the nutrients (total phosphorus, soluble reactive phosphorus, total nitrogen, ammonium nitrogen, and nitrite), fecal coliform, and conductivity in cluster 1 were significantly greater than in cluster 2. Thus, catchment urbanization degraded rivers' water quality in Liangjiang New Area. Identifying effective buffer zones at riparian scale to weaken the negative impacts of catchment urbanization was recommended.

Use of Latent Profile Analysis in Studies of Gifted Students

ERIC Educational Resources Information Center

Mammadov, Sakhavat; Ward, Thomas J.; Cross, Jennifer Riedl; Cross, Tracy L.

2016-01-01

To date, in gifted education and related fields various conventional factor analytic and clustering techniques have been used extensively for investigation of the underlying structure of data. Latent profile analysis is a relatively new method in the field. In this article, we provide an introduction to latent profile analysis for gifted education…

Systematic, multiparametric analysis of Mycobacterium tuberculosis intracellular infection offers insight into coordinated virulence.

PubMed

Barczak, Amy K; Avraham, Roi; Singh, Shantanu; Luo, Samantha S; Zhang, Wei Ran; Bray, Mark-Anthony; Hinman, Amelia E; Thompson, Matthew; Nietupski, Raymond M; Golas, Aaron; Montgomery, Paul; Fitzgerald, Michael; Smith, Roger S; White, Dylan W; Tischler, Anna D; Carpenter, Anne E; Hung, Deborah T

2017-05-01

A key to the pathogenic success of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, is the capacity to survive within host macrophages. Although several factors required for this survival have been identified, a comprehensive knowledge of such factors and how they work together to manipulate the host environment to benefit bacterial survival are not well understood. To systematically identify Mtb factors required for intracellular growth, we screened an arrayed, non-redundant Mtb transposon mutant library by high-content imaging to characterize the mutant-macrophage interaction. Based on a combination of imaging features, we identified mutants impaired for intracellular survival. We then characterized the phenotype of infection with each mutant by profiling the induced macrophage cytokine response. Taking a systems-level approach to understanding the biology of identified mutants, we performed a multiparametric analysis combining pathogen and host phenotypes to predict functional relationships between mutants based on clustering. Strikingly, mutants defective in two well-known virulence factors, the ESX-1 protein secretion system and the virulence lipid phthiocerol dimycocerosate (PDIM), clustered together. Building upon the shared phenotype of loss of the macrophage type I interferon (IFN) response to infection, we found that PDIM production and export are required for coordinated secretion of ESX-1-substrates, for phagosomal permeabilization, and for downstream induction of the type I IFN response. Multiparametric clustering also identified two novel genes that are required for PDIM production and induction of the type I IFN response. Thus, multiparametric analysis combining host and pathogen infection phenotypes can be used to identify novel functional relationships between genes that play a role in infection.

Geographic Variation and Factors Associated with Female Genital Mutilation among Reproductive Age Women in Ethiopia: A National Population Based Survey

PubMed Central

Setegn, Tesfaye; Lakew, Yihunie; Deribe, Kebede

2016-01-01

Background Female genital mutilation (FGM) is a common traditional practice in developing nations including Ethiopia. It poses complex and serious long-term health risks for women and girls and can lead to death. In Ethiopia, the geographic distribution and factors associated with FGM practices are poorly understood. Therefore, we assessed the spatial distribution and factors associated with FGM among reproductive age women in the country. Method We used population based national representative surveys. Data from two (2000 and 2005) Ethiopian demographic and health surveys (EDHS) were used in this analysis. Briefly, EDHS used a stratified, two-stage cluster sampling design. A total of 15,367 (from EDHS 2000) and 14,070 (from EDHS 2005) women of reproductive age (15–49 years) were included in the analysis. Three outcome variables were used (prevalence of FGM among women, prevalence of FGM among daughters and support for the continuation of FGM). The data were weighted and descriptive statistics (percentage change), bivariate and multivariable logistic regression analyses were carried out. Multicollinearity of variables was assessed using variance inflation factors (VIF) with a reference value of 10 before interpreting the final output. The geographic variation and clustering of weighted FGM prevalence were analyzed and visualized on maps using ArcGIS. Z-scores were used to assess the statistical difference of geographic clustering of FGM prevalence spots. Result The trend of FGM weighted prevalence has been decreasing. Being wealthy, Muslim and in higher age categories are associated with increased odds of FGM among women. Similarly, daughters from Muslim women have increased odds of experiencing FGM. Women in the higher age categories have increased odds of having daughters who experience FGM. The odds of FGM among daughters decrease with increased maternal education. Mass media exposure, being wealthy and higher paternal and maternal education are associated with decreased odds of women’s support of FGM continuation. FGM prevalence and geographic clustering showed variation across regions in Ethiopia. Conclusion Individual, economic, socio-demographic, religious and cultural factors played major roles in the existing practice and continuation of FGM. The significant geographic clustering of FGM was observed across regions in Ethiopia. Therefore, targeted and integrated interventions involving religious leaders in high FGM prevalence spot clusters and addressing the socio-economic and geographic inequalities are recommended to eliminate FGM. PMID:26741488

Geographic Variation and Factors Associated with Female Genital Mutilation among Reproductive Age Women in Ethiopia: A National Population Based Survey.

PubMed

Setegn, Tesfaye; Lakew, Yihunie; Deribe, Kebede

2016-01-01

Female genital mutilation (FGM) is a common traditional practice in developing nations including Ethiopia. It poses complex and serious long-term health risks for women and girls and can lead to death. In Ethiopia, the geographic distribution and factors associated with FGM practices are poorly understood. Therefore, we assessed the spatial distribution and factors associated with FGM among reproductive age women in the country. We used population based national representative surveys. Data from two (2000 and 2005) Ethiopian demographic and health surveys (EDHS) were used in this analysis. Briefly, EDHS used a stratified, two-stage cluster sampling design. A total of 15,367 (from EDHS 2000) and 14,070 (from EDHS 2005) women of reproductive age (15-49 years) were included in the analysis. Three outcome variables were used (prevalence of FGM among women, prevalence of FGM among daughters and support for the continuation of FGM). The data were weighted and descriptive statistics (percentage change), bivariate and multivariable logistic regression analyses were carried out. Multicollinearity of variables was assessed using variance inflation factors (VIF) with a reference value of 10 before interpreting the final output. The geographic variation and clustering of weighted FGM prevalence were analyzed and visualized on maps using ArcGIS. Z-scores were used to assess the statistical difference of geographic clustering of FGM prevalence spots. The trend of FGM weighted prevalence has been decreasing. Being wealthy, Muslim and in higher age categories are associated with increased odds of FGM among women. Similarly, daughters from Muslim women have increased odds of experiencing FGM. Women in the higher age categories have increased odds of having daughters who experience FGM. The odds of FGM among daughters decrease with increased maternal education. Mass media exposure, being wealthy and higher paternal and maternal education are associated with decreased odds of women's support of FGM continuation. FGM prevalence and geographic clustering showed variation across regions in Ethiopia. Individual, economic, socio-demographic, religious and cultural factors played major roles in the existing practice and continuation of FGM. The significant geographic clustering of FGM was observed across regions in Ethiopia. Therefore, targeted and integrated interventions involving religious leaders in high FGM prevalence spot clusters and addressing the socio-economic and geographic inequalities are recommended to eliminate FGM.

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.

Ligand combination strategy for the preparation of novel low-dimensional and open-framework metal cluster materials

NASA Astrophysics Data System (ADS)

Anokhina, Ekaterina V.

Low-dimensional and open-framework materials containing transition metals have a wide range of applications in redox catalysis, solid-state batteries, and electronic and magnetic devices. This dissertation reports on research carried out with the goal to develop a strategy for the preparation of low-dimensional and open-framework materials using octahedral metal clusters as building blocks. Our approach takes its roots from crystal engineering principles where the desired framework topologies are achieved through building block design. The key idea of this work is to induce directional bonding preferences in the cluster units using a combination of ligands with a large difference in charge density. This investigation led to the preparation and characterization of a new family of niobium oxychloride cluster compounds with original structure types exhibiting 1ow-dimensional or open-framework character. Most of these materials have framework topologies unprecedented in compounds containing octahedral clusters. Comparative analysis of their structural features indicates that the novel cluster connectivity patterns in these systems are the result of complex interplay between the effects of anisotropic ligand arrangement in the cluster unit and optimization of ligand-counterion electrostatic interactions. The important role played by these factors sets niobium oxychloride systems apart from cluster compounds with one ligand type or statistical ligand distribution where the main structure-determining factor is the total number of ligands. These results provide a blueprint for expanding the ligand combination strategy to other transition metal cluster systems and for the future rational design of cluster-based materials.

[Methods of a posteriori identification of food patterns in Brazilian children: a systematic review].

PubMed

Carvalho, Carolina Abreu de; Fonsêca, Poliana Cristina de Almeida; Nobre, Luciana Neri; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2016-01-01

The objective of this study is to provide guidance for identifying dietary patterns using the a posteriori approach, and analyze the methodological aspects of the studies conducted in Brazil that identified the dietary patterns of children. Articles were selected from the Latin American and Caribbean Literature on Health Sciences, Scientific Electronic Library Online and Pubmed databases. The key words were: Dietary pattern; Food pattern; Principal Components Analysis; Factor analysis; Cluster analysis; Reduced rank regression. We included studies that identified dietary patterns of children using the a posteriori approach. Seven studies published between 2007 and 2014 were selected, six of which were cross-sectional and one cohort, Five studies used the food frequency questionnaire for dietary assessment; one used a 24-hour dietary recall and the other a food list. The method of exploratory approach used in most publications was principal components factor analysis, followed by cluster analysis. The sample size of the studies ranged from 232 to 4231, the values of the Kaiser-Meyer-Olkin test from 0.524 to 0.873, and Cronbach's alpha from 0.51 to 0.69. Few Brazilian studies identified dietary patterns of children using the a posteriori approach and principal components factor analysis was the technique most used.

Extracting Galaxy Cluster Gas Inhomogeneity from X-Ray Surface Brightness: A Statistical Approach and Application to Abell 3667

NASA Astrophysics Data System (ADS)

Kawahara, Hajime; Reese, Erik D.; Kitayama, Tetsu; Sasaki, Shin; Suto, Yasushi

2008-11-01

Our previous analysis indicates that small-scale fluctuations in the intracluster medium (ICM) from cosmological hydrodynamic simulations follow the lognormal probability density function. In order to test the lognormal nature of the ICM directly against X-ray observations of galaxy clusters, we develop a method of extracting statistical information about the three-dimensional properties of the fluctuations from the two-dimensional X-ray surface brightness. We first create a set of synthetic clusters with lognormal fluctuations around their mean profile given by spherical isothermal β-models, later considering polytropic temperature profiles as well. Performing mock observations of these synthetic clusters, we find that the resulting X-ray surface brightness fluctuations also follow the lognormal distribution fairly well. Systematic analysis of the synthetic clusters provides an empirical relation between the three-dimensional density fluctuations and the two-dimensional X-ray surface brightness. We analyze Chandra observations of the galaxy cluster Abell 3667, and find that its X-ray surface brightness fluctuations follow the lognormal distribution. While the lognormal model was originally motivated by cosmological hydrodynamic simulations, this is the first observational confirmation of the lognormal signature in a real cluster. Finally we check the synthetic cluster results against clusters from cosmological hydrodynamic simulations. As a result of the complex structure exhibited by simulated clusters, the empirical relation between the two- and three-dimensional fluctuation properties calibrated with synthetic clusters when applied to simulated clusters shows large scatter. Nevertheless we are able to reproduce the true value of the fluctuation amplitude of simulated clusters within a factor of 2 from their two-dimensional X-ray surface brightness alone. Our current methodology combined with existing observational data is useful in describing and inferring the statistical properties of the three-dimensional inhomogeneity in galaxy clusters.

Applying spatial analysis tools in public health: an example using SaTScan to detect geographic targets for colorectal cancer screening interventions.

PubMed

Sherman, Recinda L; Henry, Kevin A; Tannenbaum, Stacey L; Feaster, Daniel J; Kobetz, Erin; Lee, David J

2014-03-20

Epidemiologists are gradually incorporating spatial analysis into health-related research as geocoded cases of disease become widely available and health-focused geospatial computer applications are developed. One health-focused application of spatial analysis is cluster detection. Using cluster detection to identify geographic areas with high-risk populations and then screening those populations for disease can improve cancer control. SaTScan is a free cluster-detection software application used by epidemiologists around the world to describe spatial clusters of infectious and chronic disease, as well as disease vectors and risk factors. The objectives of this article are to describe how spatial analysis can be used in cancer control to detect geographic areas in need of colorectal cancer screening intervention, identify issues commonly encountered by SaTScan users, detail how to select the appropriate methods for using SaTScan, and explain how method selection can affect results. As an example, we used various methods to detect areas in Florida where the population is at high risk for late-stage diagnosis of colorectal cancer. We found that much of our analysis was underpowered and that no single method detected all clusters of statistical or public health significance. However, all methods detected 1 area as high risk; this area is potentially a priority area for a screening intervention. Cluster detection can be incorporated into routine public health operations, but the challenge is to identify areas in which the burden of disease can be alleviated through public health intervention. Reliance on SaTScan's default settings does not always produce pertinent results.

Patterns and predictors of clustered risky health behaviors among adult survivors of childhood cancer: A report from the Childhood Cancer Survivor Study.

PubMed

Lown, E Anne; Hijiya, Nobuko; Zhang, Nan; Srivastava, Deo Kumar; Leisenring, Wendy M; Nathan, Paul C; Castellino, Sharon M; Devine, Katie A; Dilley, Kimberley; Krull, Kevin R; Oeffinger, Kevin C; Hudson, Melissa M; Armstrong, Gregory T; Robison, Leslie L; Ness, Kirsten K

2016-09-01

Health complications related to childhood cancer may be influenced by risky health behaviors (RHBs), particularly when RHBs co-occur. To the authors' knowledge, only limited information is available describing how RHBs cluster among survivors of childhood cancer and their siblings and the risk factors for co-occurring RHBs. Latent class analysis was used to identify RHB clusters using longitudinal survey data regarding smoking, alcohol use, and physical activity from adult survivors (4184 survivors) and siblings (1598 siblings) in the Childhood Cancer Survivor Study. Generalized logistic regression was used to evaluate associations between demographic characteristics, treatment exposures, psychological distress, health conditions, and cluster membership. Three RHB clusters were identified: a low-risk cluster, an insufficiently active cluster, and a high-risk cluster (tobacco and risky alcohol use and insufficient activity). Compared with siblings, survivors were more likely to be in the insufficiently active cluster (adjusted odds ratio [ORadj ], 1.17; 95% confidence interval [95% CI], 1.06-1.27) and were less likely to be in the high-risk cluster (ORadj , 0.79; 95% CI, 0.69-0.88). Risk factors for membership in the high-risk cluster included psychological distress (ORadj , 2.76; 95% CI, 1.98-3.86), low educational attainment (ORadj , 7.49; 95% CI, 5.15-10.88), income <$20,000 (ORadj , 2.62; 95% CI, 1.93-3.57), being divorced/separated or widowed (ORadj , 1.36; 95% CI, 1.03-1.79), and limb amputation (ORadj , 1.52; 95% CI, 1.03-2.24). Risk factors for the insufficiently active cluster included chronic health conditions, psychological distress, low education or income, being obese or overweight, female sex, nonwhite race/ethnicity, single marital status, cranial radiation, and cisplatin exposure. RHBs co-occur in survivors of childhood cancer and their siblings. Economic and educational disadvantages and psychological distress should be considered in screening and interventions to reduce RHBs. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2747-2756. © 2016 American Cancer Society. © 2016 American Cancer Society.

Spatial Analysis of China Province-level Perinatal Mortality

PubMed Central

XIANG, Kun; SONG, Deyong

2016-01-01

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

Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey.

PubMed

Tsui, Sharon; Denison, Julie A; Kennedy, Caitlin E; Chang, Larry W; Koole, Olivier; Torpey, Kwasi; Van Praag, Eric; Farley, Jason; Ford, Nathan; Stuart, Leine; Wabwire-Mangen, Fred

2017-12-06

Organization of HIV care and treatment services, including clinic staffing and services, may shape clinical and financial outcomes, yet there has been little attempt to describe different models of HIV care in sub-Saharan Africa (SSA). Information about the relative benefits and drawbacks of different models could inform the scale-up of antiretroviral therapy (ART) and associated services in resource-limited settings (RLS), especially in light of expanded client populations with country adoption of WHO's test and treat recommendation. We characterized task-shifting/task-sharing practices in 19 diverse ART clinics in Tanzania, Uganda, and Zambia and used cluster analysis to identify unique models of service provision. We ran descriptive statistics to explore how the clusters varied by environmental factors and programmatic characteristics. Finally, we employed the Delphi Method to make systematic use of expert opinions to ensure that the cluster variables were meaningful in the context of actual task-shifting of ART services in SSA. The cluster analysis identified three task-shifting/task-sharing models. The main differences across models were the availability of medical doctors, the scope of clinical responsibility assigned to nurses, and the use of lay health care workers. Patterns of healthcare staffing in HIV service delivery were associated with different environmental factors (e.g., health facility levels, urban vs. rural settings) and programme characteristics (e.g., community ART distribution or integrated tuberculosis treatment on-site). Understanding the relative advantages and disadvantages of different models of care can help national programmes adapt to increased client load, select optimal adherence strategies within decentralized models of care, and identify differentiated models of care for clients to meet the growing needs of long-term ART patients who require more complicated treatment management.

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Dynamic multifactor clustering of financial networks

NASA Astrophysics Data System (ADS)

Ross, Gordon J.

2014-02-01

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

Impact of human activity and natural processes on groundwater arsenic in an urbanized area (South China) using multivariate statistical techniques.

PubMed

Huang, Guanxing; Chen, Zongyu; Liu, Fan; Sun, Jichao; Wang, Jincui

2014-11-01

Anthropogenic factors resulted from the urbanization may affect the groundwater As in urbanized areas. Groundwater samples from the Guangzhou city (South China) were collected for As and other parameter analysis, in order to assess the impact of urbanization and natural processes on As distribution in aquifers. Nearly 25.5 % of groundwater samples were above the WHO drinking water standard for As, and the As concentrations in the granular aquifer (GA) were generally far higher than that in the fractured bedrock aquifer (FBA). Samples were classified into four clusters by using hierarchical cluster analysis. Cluster 1 is mainly located in the FBA and controlled by natural processes. Anthropogenic pollution resulted from the urbanization is responsible for high As concentrations identified in cluster 2. Clusters 3 and 4 are mainly located in the GA and controlled by both natural processes and anthropogenic factors. Three main mechanisms control the source and mobilization of groundwater As in the study area. Firstly, the interaction of water and calcareous rocks appears to be responsible for As release in the FBA. Secondly, reduction of Fe/Mn oxyhydroxides and decomposition of organic matter are probably responsible for high As concentrations in the GA. Thirdly, during the process of urbanization, the infiltration of wastewater/leachate with a high As content is likely to be the main source for groundwater As, while NO3 (-) contamination diminishes groundwater As.

The association between Polycystic Ovary Syndrome (PCOS) and metabolic syndrome: a statistical modelling approach.

PubMed

Ranasinha, S; Joham, A E; Norman, R J; Shaw, J E; Zoungas, S; Boyle, J; Moran, L; Teede, H J

2015-12-01

Polycystic ovary syndrome (PCOS) affects 12-21% of women. Women with PCOS exhibit clustering of metabolic features. We applied rigorous statistical methods to further understand the interplay between PCOS and metabolic features including insulin resistance, obesity and androgen status. Retrospective cross-sectional analysis. Women with PCOS attending reproductive endocrine clinics in South Australia for the treatment of PCOS (n = 172). Women without PCOS (controls) in the same Australian region (n = 335) from the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), a national population-based study (age- and BMI-matched within one standard deviation of the PCOS cohort). The factor structure for metabolic syndrome for women with PCOS and control groups was examined, specifically, the contribution of individual factors to metabolic syndrome and the association of hyperandrogenism with other metabolic factors. Women with PCOS demonstrated clustering of metabolic features that was not observed in the control group. Metabolic syndrome in the PCOS cohort was strongly represented by obesity (standardized factor loading = 0·95, P < 0·001) and insulin resistance factors (loading = 0·92, P < 0·001) and moderately by blood pressure (loading = 0·62, P < 0·001) and lipid factors (loading = 0·67, P = 0·002). On further analysis, the insulin resistance factor strongly correlated with the obesity (r = 0·70, P < 0·001) and lipid factors (r = 0·68, P < 0·001) and moderately with the blood pressure factor (loading = 0·43, P = 0·002). The hyperandrogenism factor was moderately correlated with the insulin resistance factor (r = 0·38, P < 0·003), but did not correlate with any other metabolic factors. PCOS women are more likely to display metabolic clustering in comparison with age- and BMI-matched control women. Obesity and insulin resistance, but not androgens, are independently and most strongly associated with metabolic syndrome in PCOS. © 2015 John Wiley & Sons Ltd.

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

PubMed Central

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

2010-01-01

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

Clustering of samples and variables with mixed-type data

PubMed Central

Edelmann, Dominic; Kopp-Schneider, Annette

2017-01-01

Analysis of data measured on different scales is a relevant challenge. Biomedical studies often focus on high-throughput datasets of, e.g., quantitative measurements. However, the need for integration of other features possibly measured on different scales, e.g. clinical or cytogenetic factors, becomes increasingly important. The analysis results (e.g. a selection of relevant genes) are then visualized, while adding further information, like clinical factors, on top. However, a more integrative approach is desirable, where all available data are analyzed jointly, and where also in the visualization different data sources are combined in a more natural way. Here we specifically target integrative visualization and present a heatmap-style graphic display. To this end, we develop and explore methods for clustering mixed-type data, with special focus on clustering variables. Clustering of variables does not receive as much attention in the literature as does clustering of samples. We extend the variables clustering methodology by two new approaches, one based on the combination of different association measures and the other on distance correlation. With simulation studies we evaluate and compare different clustering strategies. Applying specific methods for mixed-type data proves to be comparable and in many cases beneficial as compared to standard approaches applied to corresponding quantitative or binarized data. Our two novel approaches for mixed-type variables show similar or better performance than the existing methods ClustOfVar and bias-corrected mutual information. Further, in contrast to ClustOfVar, our methods provide dissimilarity matrices, which is an advantage, especially for the purpose of visualization. Real data examples aim to give an impression of various kinds of potential applications for the integrative heatmap and other graphical displays based on dissimilarity matrices. We demonstrate that the presented integrative heatmap provides more information than common data displays about the relationship among variables and samples. The described clustering and visualization methods are implemented in our R package CluMix available from https://cran.r-project.org/web/packages/CluMix. PMID:29182671

A Study on Regional Frequency Analysis using Artificial Neural Network - the Sumjin River Basin

NASA Astrophysics Data System (ADS)

Jeong, C.; Ahn, J.; Ahn, H.; Heo, J. H.

2017-12-01

Regional frequency analysis means to make up for shortcomings in the at-site frequency analysis which is about a lack of sample size through the regional concept. Regional rainfall quantile depends on the identification of hydrologically homogeneous regions, hence the regional classification based on hydrological homogeneous assumption is very important. For regional clustering about rainfall, multidimensional variables and factors related geographical features and meteorological figure are considered such as mean annual precipitation, number of days with precipitation in a year and average maximum daily precipitation in a month. Self-Organizing Feature Map method which is one of the artificial neural network algorithm in the unsupervised learning techniques solves N-dimensional and nonlinear problems and be shown results simply as a data visualization technique. In this study, for the Sumjin river basin in South Korea, cluster analysis was performed based on SOM method using high-dimensional geographical features and meteorological factor as input data. then, for the results, in order to evaluate the homogeneity of regions, the L-moment based discordancy and heterogeneity measures were used. Rainfall quantiles were estimated as the index flood method which is one of regional rainfall frequency analysis. Clustering analysis using SOM method and the consequential variation in rainfall quantile were analyzed. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

The effect of the morphology of supported subnanometer Pt clusters on the first and key step of CO 2 photoreduction [Morphology effect of supported subnanometer Pt clusters on first and key step of CO 2 photoreduction

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

Yang, Chi -Ta; Wood, Brandon C.; Bhethanabotla, Venkat R.

2015-09-04

In this study, using density functional theory calculations, we investigate the influence of size-dependent cluster morphology on the synergistic catalytic properties of anatase TiO 2(101) surfaces decorated with subnanometer Pt clusters. Focusing on the formation of the key precursor in the CO 2 photoreduction reaction (bent CO 2 –), we find that flatter (2D-like) Pt clusters that “wet” the TiO 2 surface offer significantly less benefit than 3D-like Pt clusters. We attribute the differences to three factors. First, the 3D clusters provide a greater number of accessible Pt–TiO 2 interfacial sites with geometries that can aid CO 2 bond bendingmore » and charge transfer processes. Second, binding competition among each Pt–CO 2 bonding interaction mitigates maximum orbital overlaps, leading to insufficient CO 2 binding. Third and also most interestingly, the 3D clusters tend to possess higher structural fluxionality than the flatter clusters, which is shown to correlate positively with CO2 binding strength. The preferred morphology adopted by the clusters depends on several factors, including the cluster size and the presence of oxygen vacancies on the TiO 2 surface; this suggests a strategy for optimizing the synergistic effect between Pt clusters and TiO 2 surfaces for CO 2 photocatalysis. Clusters of ~6–8 atoms should provide the largest benefit, since they retain the desired 3D morphology, yet are small enough to exhibit high structural fluxionality. Electronic structure analysis provides additional insight into the electronic motivations for the enhanced binding of CO 2 on TiO 2-supported 3D Pt clusters, as well as suppressed binding on flattened, 2D-like clusters.« less

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

PubMed

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

2018-04-27

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

Chill, Be Cool Man: African American Men, Identity, Coping, and Aggressive Ideation

PubMed Central

Thomas, Alvin; Hammond, Wizdom Powell; Kohn-Wood, Laura P.

2016-01-01

Aggression is an important correlate of violence, depression, coping, and suicide among emerging young African American males. Yet most researchers treat aggression deterministically, fail to address cultural factors, or consider the potential for individual characteristics to exert an intersectional influence on this psychosocial outcome. Addressing this gap, we consider the moderating effect of coping on the relationship between masculine and racial identity and aggressive ideation among African American males (N = 128) drawn from 2 large Midwestern universities. Using the phenomenological variant of ecological systems theory and person-centered methodology as a guide, hierarchical cluster analysis grouped participants into profile groups based on their responses to both a measure of racial identity and a measure of masculine identity. Results from the cluster analysis revealed 3 distinct identity clusters: Identity Ambivalent, Identity Appraising, and Identity Consolidated. Although these cluster groups did not differ with regard to coping, significant differences were observed between cluster groups in relation to aggressive ideation. Further, a full model with identity profile clusters, coping, and aggressive ideation indicates that cluster membership significantly moderates the relationship between coping and aggressive ideation. The implications of these data for intersecting identities of African American men, and the association of identity and outcomes related to risk for mental health and violence, are discussed. PMID:25090145

Chill, be cool man: African American men, identity, coping, and aggressive ideation.

PubMed

Thomas, Alvin; Hammond, Wizdom Powell; Kohn-Wood, Laura P

2015-07-01

Aggression is an important correlate of violence, depression, coping, and suicide among emerging young African American males. Yet most researchers treat aggression deterministically, fail to address cultural factors, or consider the potential for individual characteristics to exert an intersectional influence on this psychosocial outcome. Addressing this gap, we consider the moderating effect of coping on the relationship between masculine and racial identity and aggressive ideation among African American males (N = 128) drawn from 2 large Midwestern universities. Using the phenomenological variant of ecological systems theory and person-centered methodology as a guide, hierarchical cluster analysis grouped participants into profile groups based on their responses to both a measure of racial identity and a measure of masculine identity. Results from the cluster analysis revealed 3 distinct identity clusters: Identity Ambivalent, Identity Appraising, and Identity Consolidated. Although these cluster groups did not differ with regard to coping, significant differences were observed between cluster groups in relation to aggressive ideation. Further, a full model with identity profile clusters, coping, and aggressive ideation indicates that cluster membership significantly moderates the relationship between coping and aggressive ideation. The implications of these data for intersecting identities of African American men, and the association of identity and outcomes related to risk for mental health and violence, are discussed. (c) 2015 APA, all rights reserved).

Principal components derived from CSF inflammatory profiles predict outcome in survivors after severe traumatic brain injury.

PubMed

Kumar, Raj G; Rubin, Jonathan E; Berger, Rachel P; Kochanek, Patrick M; Wagner, Amy K

2016-03-01

Studies have characterized absolute levels of multiple inflammatory markers as significant risk factors for poor outcomes after traumatic brain injury (TBI). However, inflammatory marker concentrations are highly inter-related, and production of one may result in the production or regulation of another. Therefore, a more comprehensive characterization of the inflammatory response post-TBI should consider relative levels of markers in the inflammatory pathway. We used principal component analysis (PCA) as a dimension-reduction technique to characterize the sets of markers that contribute independently to variability in cerebrospinal (CSF) inflammatory profiles after TBI. Using PCA results, we defined groups (or clusters) of individuals (n=111) with similar patterns of acute CSF inflammation that were then evaluated in the context of outcome and other relevant CSF and serum biomarkers collected days 0-3 and 4-5 post-injury. We identified four significant principal components (PC1-PC4) for CSF inflammation from days 0-3, and PC1 accounted for the greatest (31%) percentage of variance. PC1 was characterized by relatively higher CSF sICAM-1, sFAS, IL-10, IL-6, sVCAM-1, IL-5, and IL-8 levels. Cluster analysis then defined two distinct clusters, such that individuals in cluster 1 had highly positive PC1 scores and relatively higher levels of CSF cortisol, progesterone, estradiol, testosterone, brain derived neurotrophic factor (BDNF), and S100b; this group also had higher serum cortisol and lower serum BDNF. Multinomial logistic regression analyses showed that individuals in cluster 1 had a 10.9 times increased likelihood of GOS scores of 2/3 vs. 4/5 at 6 months compared to cluster 2, after controlling for covariates. Cluster group did not discriminate between mortality compared to GOS scores of 4/5 after controlling for age and other covariates. Cluster groupings also did not discriminate mortality or 12 month outcomes in multivariate models. PCA and cluster analysis establish that a subset of CSF inflammatory markers measured in days 0-3 post-TBI may distinguish individuals with poor 6-month outcome, and future studies should prospectively validate these findings. PCA of inflammatory mediators after TBI could aid in prognostication and in identifying patient subgroups for therapeutic interventions. Copyright © 2015 Elsevier Inc. All rights reserved.

RSAT 2015: Regulatory Sequence Analysis Tools.

PubMed

Medina-Rivera, Alejandra; Defrance, Matthieu; Sand, Olivier; Herrmann, Carl; Castro-Mondragon, Jaime A; Delerce, Jeremy; Jaeger, Sébastien; Blanchet, Christophe; Vincens, Pierre; Caron, Christophe; Staines, Daniel M; Contreras-Moreira, Bruno; Artufel, Marie; Charbonnier-Khamvongsa, Lucie; Hernandez, Céline; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

2015-07-01

RSAT (Regulatory Sequence Analysis Tools) is a modular software suite for the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, appropriate to genome-wide data sets like ChIP-seq, (ii) transcription factor binding motif analysis (quality assessment, comparisons and clustering), (iii) comparative genomics and (iv) analysis of regulatory variations. Nine new programs have been added to the 43 described in the 2011 NAR Web Software Issue, including a tool to extract sequences from a list of coordinates (fetch-sequences from UCSC), novel programs dedicated to the analysis of regulatory variants from GWAS or population genomics (retrieve-variation-seq and variation-scan), a program to cluster motifs and visualize the similarities as trees (matrix-clustering). To deal with the drastic increase of sequenced genomes, RSAT public sites have been reorganized into taxon-specific servers. The suite is well-documented with tutorials and published protocols. The software suite is available through Web sites, SOAP/WSDL Web services, virtual machines and stand-alone programs at http://www.rsat.eu/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

A study on phenomenology of Dhat syndrome in men in a general medical setting

PubMed Central

Prakash, Sathya; Sharan, Pratap; Sood, Mamta

2016-01-01

Background: “Dhat syndrome” is believed to be a culture-bound syndrome of the Indian subcontinent. Although many studies have been performed, many have methodological limitations and there is a lack of agreement in many areas. Aims: The aim is to study the phenomenology of “Dhat syndrome” in men and to explore the possibility of subtypes within this entity. Settings and Design: It is a cross-sectional descriptive study conducted at a sex and marriage counseling clinic of a tertiary care teaching hospital in Northern India. Materials and Methods: An operational definition and assessment instrument for “Dhat syndrome” was developed after taking all concerned stakeholders into account and review of literature. It was applied on 100 patients along with socio-demographic profile, Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, Mini International Neuropsychiatric Interview, and Postgraduate Institute Neuroticism Scale. Statistical Analysis: For statistical analysis, descriptive statistics, group comparisons, and Pearson's product moment correlations were carried out. Factor analysis and cluster analysis were done to determine the factor structure and subtypes of “Dhat syndrome.” Results: A diagnostic and assessment instrument for “Dhat syndrome” has been developed and the phenomenology in 100 patients has been described. Both the health beliefs scale and associated symptoms scale demonstrated a three-factor structure. The patients with “Dhat syndrome” could be categorized into three clusters based on severity. Conclusions: There appears to be a significant agreement among various stakeholders on the phenomenology of “Dhat syndrome” although some differences exist. “Dhat syndrome” could be subtyped into three clusters based on severity. PMID:27385844

Classification of Support Needs for Elderly Outpatients with Diabetes Who Live Alone.

PubMed

Miyawaki, Yoshiko; Shimizu, Yasuko; Seto, Natsuko

2016-02-01

To investigate the support needs of elderly patients with diabetes and to classify elderly patients with diabetes living alone on the basis of support needs. Support needs were derived from a literature review of relevant journals and interviews of outpatients as well as expert nurses in the field of diabetes to prepare a 45-item questionnaire. Each item was analyzed on a 4-point Likert scale. The study included 634 elderly patients with diabetes who were recruited from 3 hospitals in Japan. Exploratory factor analysis was performed to determine the underlying structure of support needs, followed by hierarchical cluster analysis to clarify the characteristics of patients living alone (n=104) who had common support needs. Exploratory factor analysis suggested a 5-factor solution with 23 items: (1) hope for class and gatherings, (2) hope for personal advice including emergency response, (3) supportlessness and hopelessness, (4) barriers to food preparation, (5) hope of safe medical therapy. The hierarchical cluster analysis of subjects yielded 7 clusters, including a no special-support needs group, a collective support group, a self-care support group, a personal-support focus group, a life-support group, a food-preparation support group and a healthcare-environment support group. The support needs of elderly patients with diabetes who live alone can be divided into 2 categories: life and self-care support. Implementation of these categories in outpatient-management programs in which contact time with patients is limited is important in the overall management of elderly patients with diabetes who are living alone. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2016-03-21

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

Sunyaev-Zel'dovich Effect and X-ray Scaling Relations from Weak-Lensing Mass Calibration of 32 SPT Selected Galaxy Clusters

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

Dietrich, J.P.; et al.

Uncertainty in the mass-observable scaling relations is currently the limiting factor for galaxy cluster based cosmology. Weak gravitational lensing can provide a direct mass calibration and reduce the mass uncertainty. We present new ground-based weak lensing observations of 19 South Pole Telescope (SPT) selected clusters and combine them with previously reported space-based observations of 13 galaxy clusters to constrain the cluster mass scaling relations with the Sunyaev-Zel'dovich effect (SZE), the cluster gas massmore » $$M_\\mathrm{gas}$$, and $$Y_\\mathrm{X}$$, the product of $$M_\\mathrm{gas}$$ and X-ray temperature. We extend a previously used framework for the analysis of scaling relations and cosmological constraints obtained from SPT-selected clusters to make use of weak lensing information. We introduce a new approach to estimate the effective average redshift distribution of background galaxies and quantify a number of systematic errors affecting the weak lensing modelling. These errors include a calibration of the bias incurred by fitting a Navarro-Frenk-White profile to the reduced shear using $N$-body simulations. We blind the analysis to avoid confirmation bias. We are able to limit the systematic uncertainties to 6.4% in cluster mass (68% confidence). Our constraints on the mass-X-ray observable scaling relations parameters are consistent with those obtained by earlier studies, and our constraints for the mass-SZE scaling relation are consistent with the the simulation-based prior used in the most recent SPT-SZ cosmology analysis. We can now replace the external mass calibration priors used in previous SPT-SZ cosmology studies with a direct, internal calibration obtained on the same clusters.« less

Using data mining to segment healthcare markets from patients' preference perspectives.

PubMed

Liu, Sandra S; Chen, Jie

2009-01-01

This paper aims to provide an example of how to use data mining techniques to identify patient segments regarding preferences for healthcare attributes and their demographic characteristics. Data were derived from a number of individuals who received in-patient care at a health network in 2006. Data mining and conventional hierarchical clustering with average linkage and Pearson correlation procedures are employed and compared to show how each procedure best determines segmentation variables. Data mining tools identified three differentiable segments by means of cluster analysis. These three clusters have significantly different demographic profiles. The study reveals, when compared with traditional statistical methods, that data mining provides an efficient and effective tool for market segmentation. When there are numerous cluster variables involved, researchers and practitioners need to incorporate factor analysis for reducing variables to clearly and meaningfully understand clusters. Interests and applications in data mining are increasing in many businesses. However, this technology is seldom applied to healthcare customer experience management. The paper shows that efficient and effective application of data mining methods can aid the understanding of patient healthcare preferences.

Geographic Clustering of Cardiometabolic Risk Factors in Metropolitan Centres in France and Australia

PubMed Central

Paquet, Catherine; Chaix, Basile; Howard, Natasha J.; Coffee, Neil T.; Adams, Robert J.; Taylor, Anne W.; Thomas, Frédérique; Daniel, Mark

2016-01-01

Understanding how health outcomes are spatially distributed represents a first step in investigating the scale and nature of environmental influences on health and has important implications for statistical power and analytic efficiency. Using Australian and French cohort data, this study aimed to describe and compare the extent of geographic variation, and the implications for analytic efficiency, across geographic units, countries and a range of cardiometabolic parameters (Body Mass Index (BMI) waist circumference, blood pressure, resting heart rate, triglycerides, cholesterol, glucose, HbA1c). Geographic clustering was assessed using Intra-Class Correlation (ICC) coefficients in biomedical cohorts from Adelaide (Australia, n = 3893) and Paris (France, n = 6430) for eight geographic administrative units. The median ICC was 0.01 suggesting 1% of risk factor variance attributable to variation between geographic units. Clustering differed by cardiometabolic parameters, administrative units and countries and was greatest for BMI and resting heart rate in the French sample, HbA1c in the Australian sample, and for smaller geographic units. Analytic inefficiency due to clustering was greatest for geographic units in which participants were nested in fewer, larger geographic units. Differences observed in geographic clustering across risk factors have implications for choice of geographic unit in sampling and analysis, and highlight potential cross-country differences in the distribution, or role, of environmental features related to cardiometabolic health. PMID:27213423

Candidatus Frankia Datiscae Dg1, the Actinobacterial Microsymbiont of Datisca glomerata, Expresses the Canonical nod Genes nodABC in Symbiosis with Its Host Plant

PubMed Central

Persson, Tomas; Battenberg, Kai; Demina, Irina V.; Vigil-Stenman, Theoden; Vanden Heuvel, Brian; Pujic, Petar; Facciotti, Marc T.; Wilbanks, Elizabeth G.; O'Brien, Anna; Fournier, Pascale; Cruz Hernandez, Maria Antonia; Mendoza Herrera, Alberto; Médigue, Claudine; Normand, Philippe; Pawlowski, Katharina; Berry, Alison M.

2015-01-01

Frankia strains are nitrogen-fixing soil actinobacteria that can form root symbioses with actinorhizal plants. Phylogenetically, symbiotic frankiae can be divided into three clusters, and this division also corresponds to host specificity groups. The strains of cluster II which form symbioses with actinorhizal Rosales and Cucurbitales, thus displaying a broad host range, show suprisingly low genetic diversity and to date can not be cultured. The genome of the first representative of this cluster, Candidatus Frankia datiscae Dg1 (Dg1), a microsymbiont of Datisca glomerata, was recently sequenced. A phylogenetic analysis of 50 different housekeeping genes of Dg1 and three published Frankia genomes showed that cluster II is basal among the symbiotic Frankia clusters. Detailed analysis showed that nodules of D. glomerata, independent of the origin of the inoculum, contain several closely related cluster II Frankia operational taxonomic units. Actinorhizal plants and legumes both belong to the nitrogen-fixing plant clade, and bacterial signaling in both groups involves the common symbiotic pathway also used by arbuscular mycorrhizal fungi. However, so far, no molecules resembling rhizobial Nod factors could be isolated from Frankia cultures. Alone among Frankia genomes available to date, the genome of Dg1 contains the canonical nod genes nodA, nodB and nodC known from rhizobia, and these genes are arranged in two operons which are expressed in D. glomerata nodules. Furthermore, Frankia Dg1 nodC was able to partially complement a Rhizobium leguminosarum A34 nodC::Tn5 mutant. Phylogenetic analysis showed that Dg1 Nod proteins are positioned at the root of both α- and β-rhizobial NodABC proteins. NodA-like acyl transferases were found across the phylum Actinobacteria, but among Proteobacteria only in nodulators. Taken together, our evidence indicates an Actinobacterial origin of rhizobial Nod factors. PMID:26020781

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

Fascioliasis risk factors and space-time clusters in domestic ruminants in Bangladesh.

PubMed

Rahman, A K M Anisur; Islam, S K Shaheenur; Talukder, Md Hasanuzzaman; Hassan, Md Kumrul; Dhand, Navneet K; Ward, Michael P

2017-05-08

A retrospective observational study was conducted to identify fascioliasis hotspots, clusters, potential risk factors and to map fascioliasis risk in domestic ruminants in Bangladesh. Cases of fascioliasis in cattle, buffalo, sheep and goats from all districts in Bangladesh between 2011 and 2013 were identified via secondary surveillance data from the Department of Livestock Services' Epidemiology Unit. From each case report, date of report, species affected and district data were extracted. The total number of domestic ruminants in each district was used to calculate fascioliasis cases per ten thousand animals at risk per district, and this was used for cluster and hotspot analysis. Clustering was assessed with Moran's spatial autocorrelation statistic, hotspots with the local indicator of spatial association (LISA) statistic and space-time clusters with the scan statistic (Poisson model). The association between district fascioliasis prevalence and climate (temperature, precipitation), elevation, land cover and water bodies was investigated using a spatial regression model. A total of 1,723,971 cases of fascioliasis were reported in the three-year study period in cattle (1,164,560), goats (424,314), buffalo (88,924) and sheep (46,173). A total of nine hotspots were identified; one of these persisted in each of the three years. Only two local clusters were found. Five space-time clusters located within 22 districts were also identified. Annual risk maps of fascioliasis cases correlated with the hotspots and clusters detected. Cultivated and managed (P < 0.001) and artificial surface (P = 0.04) land cover areas, and elevation (P = 0.003) were positively and negatively associated with fascioliasis in Bangladesh, respectively. Results indicate that due to land use characteristics some areas of Bangladesh are at greater risk of fascioliasis. The potential risk factors, hot spots and clusters identified in this study can be used to guide science-based treatment and control decisions for fascioliasis in Bangladesh and in other similar geo-climatic zones throughout the world.

[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

PubMed

Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

2011-11-01

To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P < 0.0001) based on testing by the Lagrangemultiplier. Therefore, the over-dispersion dispersed data using a modified Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

The X-ray cluster survey with eRosita: forecasts for cosmology, cluster physics and primordial non-Gaussianity

NASA Astrophysics Data System (ADS)

Pillepich, Annalisa; Porciani, Cristiano; Reiprich, Thomas H.

2012-05-01

Starting in late 2013, the eRosita telescope will survey the X-ray sky with unprecedented sensitivity. Assuming a detection limit of 50 photons in the (0.5-2.0) keV energy band with a typical exposure time of 1.6 ks, we predict that eRosita will detect ˜9.3 × 104 clusters of galaxies more massive than 5 × 1013 h-1 M⊙, with the currently planned all-sky survey. Their median redshift will be z≃ 0.35. We perform a Fisher-matrix analysis to forecast the constraining power of ? on the Λ cold dark matter (ΛCDM) cosmology and, simultaneously, on the X-ray scaling relations for galaxy clusters. Special attention is devoted to the possibility of detecting primordial non-Gaussianity. We consider two experimental probes: the number counts and the angular clustering of a photon-count limited sample of clusters. We discuss how the cluster sample should be split to optimize the analysis and we show that redshift information of the individual clusters is vital to break the strong degeneracies among the model parameters. For example, performing a 'tomographic' analysis based on photometric-redshift estimates and combining one- and two-point statistics will give marginal 1σ errors of Δσ8≃ 0.036 and ΔΩm≃ 0.012 without priors, and improve the current estimates on the slope of the luminosity-mass relation by a factor of 3. Regarding primordial non-Gaussianity, ? clusters alone will give ΔfNL≃ 9, 36 and 144 for the local, orthogonal and equilateral model, respectively. Measuring redshifts with spectroscopic accuracy would further tighten the constraints by nearly 40 per cent (barring fNL which displays smaller improvements). Finally, combining ? data with the analysis of temperature anisotropies in the cosmic microwave background by the Planck satellite should give sensational constraints on both the cosmology and the properties of the intracluster medium.

Cluster analysis: a new approach for identification of underlying risk factors for coronary artery disease in essential hypertensive patients.

PubMed

Guo, Qi; Lu, Xiaoni; Gao, Ya; Zhang, Jingjing; Yan, Bin; Su, Dan; Song, Anqi; Zhao, Xi; Wang, Gang

2017-03-07

Grading of essential hypertension according to blood pressure (BP) level may not adequately reflect clinical heterogeneity of hypertensive patients. This study was carried out to explore clinical phenotypes in essential hypertensive patients using cluster analysis. This study recruited 513 hypertensive patients and evaluated BP variations with ambulatory blood pressure monitoring. Four distinct hypertension groups were identified using cluster analysis: (1) younger male smokers with relatively high BP had the most severe carotid plaque thickness but no coronary artery disease (CAD); (2) older women with relatively low diastolic BP had more diabetes; (3) non-smokers with a low systolic BP level had neither diabetes nor CAD; (4) hypertensive patients with BP reverse dipping were most likely to have CAD but had least severe carotid plaque thickness. In binary logistic analysis, reverse dipping was significantly associated with prevalence of CAD. Cluster analysis was shown to be a feasible approach for investigating the heterogeneity of essential hypertension in clinical studies. BP reverse dipping might be valuable for prediction of CAD in hypertensive patients when compared with carotid plaque thickness. However, large-scale prospective trials with more information of plaque morphology are necessary to further compare the predicative power between BP dipping pattern and carotid plaque.

Cluster analysis: a new approach for identification of underlying risk factors for coronary artery disease in essential hypertensive patients

PubMed Central

Guo, Qi; Lu, Xiaoni; Gao, Ya; Zhang, Jingjing; Yan, Bin; Su, Dan; Song, Anqi; Zhao, Xi; Wang, Gang

2017-01-01

Grading of essential hypertension according to blood pressure (BP) level may not adequately reflect clinical heterogeneity of hypertensive patients. This study was carried out to explore clinical phenotypes in essential hypertensive patients using cluster analysis. This study recruited 513 hypertensive patients and evaluated BP variations with ambulatory blood pressure monitoring. Four distinct hypertension groups were identified using cluster analysis: (1) younger male smokers with relatively high BP had the most severe carotid plaque thickness but no coronary artery disease (CAD); (2) older women with relatively low diastolic BP had more diabetes; (3) non-smokers with a low systolic BP level had neither diabetes nor CAD; (4) hypertensive patients with BP reverse dipping were most likely to have CAD but had least severe carotid plaque thickness. In binary logistic analysis, reverse dipping was significantly associated with prevalence of CAD. Cluster analysis was shown to be a feasible approach for investigating the heterogeneity of essential hypertension in clinical studies. BP reverse dipping might be valuable for prediction of CAD in hypertensive patients when compared with carotid plaque thickness. However, large-scale prospective trials with more information of plaque morphology are necessary to further compare the predicative power between BP dipping pattern and carotid plaque. PMID:28266630

A West Virginia case study: does erosion differ between streambanks clustered by the bank assessment of nonpoint source consequences of sediment (BANCS) model parameters?

Treesearch

Abby L. McQueen; Nicolas P. Zegre; Danny L. Welsch

2013-01-01

The integration of factors and processes responsible for streambank erosion is complex. To explore the influence of physical variables on streambank erosion, parameters for the bank assessment of nonpoint source consequences of sediment (BANCS) model were collected on a 1-km reach of Horseshoe Run in Tucker County, West Virginia. Cluster analysis was used to establish...

A study on phenomenology of Dhat syndrome in men in a general medical setting.

PubMed

Prakash, Sathya; Sharan, Pratap; Sood, Mamta

2016-01-01

"Dhat syndrome" is believed to be a culture-bound syndrome of the Indian subcontinent. Although many studies have been performed, many have methodological limitations and there is a lack of agreement in many areas. The aim is to study the phenomenology of "Dhat syndrome" in men and to explore the possibility of subtypes within this entity. It is a cross-sectional descriptive study conducted at a sex and marriage counseling clinic of a tertiary care teaching hospital in Northern India. An operational definition and assessment instrument for "Dhat syndrome" was developed after taking all concerned stakeholders into account and review of literature. It was applied on 100 patients along with socio-demographic profile, Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, Mini International Neuropsychiatric Interview, and Postgraduate Institute Neuroticism Scale. For statistical analysis, descriptive statistics, group comparisons, and Pearson's product moment correlations were carried out. Factor analysis and cluster analysis were done to determine the factor structure and subtypes of "Dhat syndrome." A diagnostic and assessment instrument for "Dhat syndrome" has been developed and the phenomenology in 100 patients has been described. Both the health beliefs scale and associated symptoms scale demonstrated a three-factor structure. The patients with "Dhat syndrome" could be categorized into three clusters based on severity. There appears to be a significant agreement among various stakeholders on the phenomenology of "Dhat syndrome" although some differences exist. "Dhat syndrome" could be subtyped into three clusters based on severity.

Robust continuous clustering

PubMed Central

Shah, Sohil Atul

2017-01-01

Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank. PMID:28851838

Spatial analysis of under-5 mortality and potential risk factors in the Basse Health and Demographic Surveillance System, the Gambia.

PubMed

Quattrochi, John; Jasseh, Momodou; Mackenzie, Grant; Castro, Marcia C

2015-07-01

To describe the spatial pattern in under-5 mortality rates in the Basse Health and Demographic Surveillance System (BHDSS) and to test for associations between under-5 deaths and biodemographic and socio-economic risk factors. Using data on child survival from 2007 to 2011 in the BHDSS, we mapped under-5 mortality by km(2) . We tested for spatial clustering of high or low death rates using Kulldorff's spatial scan statistic. Associations between child death and a variety of biodemographic and socio-economic factors were assessed with Cox proportional hazards models, and deviance residuals from the best-fitting model were tested for spatial clustering. The overall death rate among children under 5 was 0.0195 deaths per child-year. We found two spatial clusters of high death rates and one spatial cluster of low death rates; children in the two high clusters died at a rate of 0.0264 and 0.0292 deaths per child-year, while in the low cluster, the rate was 0.0144 deaths per child-year. We also found that children born to Fula mothers experienced, on average, a higher hazard of death, whereas children born in the households in the upper two quintiles of asset ownership experienced, on average, a lower hazard of death. After accounting for the spatial distribution of biodemographic and socio-economic characteristics, we found no residual spatial pattern in child mortality risk. This study demonstrates that significant inequality in under-5 death rates can occur within a relatively small area (1100 km(2) ). Risks of under-5 mortality were associated with mother's ethnicity and household wealth. If high mortality clusters persist, then equity concerns may require additional public health efforts in those areas. © 2015 John Wiley & Sons Ltd.

Configural Scoring of Simulator Sickness, Cybersickness and Space Adaptation Syndrome: Similarities and Differences?

NASA Technical Reports Server (NTRS)

Kennedy, Robert S.; Drexler, Julie M.; Compton, Daniel E.; Stanney, Kay M.; Lanham, Susan; Harm, Deborah L.

2001-01-01

From a survey of ten U.S. Navy flight simulators a large number (N > 1,600 exposures) of self-reports of motion sickness symptomatology were obtained. Using these data, scoring algorithms were derived, which permit examination of groups of individuals that can be scored either for 1) their total sickness experience in a particular device; or, 2) according to three separable symptom clusters which emerged from a Factor Analysis. Scores from this total score are found to be proportional to other global motion sickness symptom checklist scores with which they correlate (r = 0.82). The factors that surfaced from the analysis include clusters of symptoms referable as nausea, oculomotor disturbances, and disorientation (N, 0, and D). The factor scores may have utility in differentiating the source of symptoms in different devices. The present chapter describes our experience with the use of both of these types of scores and illustrates their use with examples from flight simulators, space sickness and virtual environments.

Assessing the hydrogeochemical processes affecting groundwater pollution in arid areas using an integration of geochemical equilibrium and multivariate statistical techniques.

PubMed

El Alfy, Mohamed; Lashin, Aref; Abdalla, Fathy; Al-Bassam, Abdulaziz

2017-10-01

Rapid economic expansion poses serious problems for groundwater resources in arid areas, which typically have high rates of groundwater depletion. In this study, integration of hydrochemical investigations involving chemical and statistical analyses are conducted to assess the factors controlling hydrochemistry and potential pollution in an arid region. Fifty-four groundwater samples were collected from the Dhurma aquifer in Saudi Arabia, and twenty-one physicochemical variables were examined for each sample. Spatial patterns of salinity and nitrate were mapped using fitted variograms. The nitrate spatial distribution shows that nitrate pollution is a persistent problem affecting a wide area of the aquifer. The hydrochemical investigations and cluster analysis reveal four significant clusters of groundwater zones. Five main factors were extracted, which explain >77% of the total data variance. These factors indicated that the chemical characteristics of the groundwater were influenced by rock-water interactions and anthropogenic factors. The identified clusters and factors were validated with hydrochemical investigations. The geogenic factors include the dissolution of various minerals (calcite, aragonite, gypsum, anhydrite, halite and fluorite) and ion exchange processes. The anthropogenic factors include the impact of irrigation return flows and the application of potassium, nitrate, and phosphate fertilizers. Over time, these anthropogenic factors will most likely contribute to further declines in groundwater quality. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multivariate analysis of selected metals in tannery effluents and related soil.

PubMed

Tariq, Saadia R; Shah, Munir H; Shaheen, N; Khalique, A; Manzoor, S; Jaffar, M

2005-06-30

Effluent and relevant soil samples from 38 tanning units housed in Kasur, Pakistan, were obtained for metal analysis by flame atomic absorption spectrophotometric method. The levels of 12 metals, Na, Ca, K, Mg, Fe, Mn, Cr, Co, Cd, Ni, Pb and Zn were determined in the two media. The data were evaluated towards metal distribution and metal-to-metal correlations. The study evidenced enhanced levels of Cr (391, 16.7 mg/L) and Na (25,519, 9369 mg/L) in tannery effluents and relevant soil samples, respectively. The effluent versus soil trace metal content relationship confirmed that the effluent Cr was strongly correlated with soil Cr. For metal source identification the techniques of principal component analysis, and cluster analysis were applied. The principal component analysis yielded two factors for effluents: factor 1 (49.6% variance) showed significant loading for Ca, Fe, Mn, Cr, Cd, Ni, Pb and Zn, referring to a tanning related source for these metals, and factor 2 (12.6% variance) with higher loadings of Na, K, Mg and Co, was associated with the processes during the skin/hide treatment. Similarly, two factors with a cumulative variance of 34.8% were obtained for soil samples: factor 1 manifested the contribution from Mg, Mn, Co, Cd, Ni and Pb, which though soil-based is basically effluent-derived, while factor 2 was found associated with Na, K, Ca, Cr and Zn which referred to a tannery-based source. The dendograms obtained from cluster analysis, also support the observed results. The study exhibits a gross pollution of soils with Cr at levels far exceeding the stipulated safe limit laid down for tannery effluents.

Cluster folding analysis of 20Ne+16O elastic transfer

NASA Astrophysics Data System (ADS)

Hamada, Sh.; Keeley, N.; Kemper, K. W.; Rusek, K.

2018-05-01

The available experimental data for the 20Ne+16O system in the energy range where the effect of α -cluster transfer is well observed are reanalyzed using the cluster folding model. The cluster folding potential, which includes both real and imaginary terms, reproduces the data at forward angles and the inclusion of the 16O(20Ne,16O)20Ne elastic transfer process provides a satisfactory description of the backward angles. The spectroscopic factor for the 20Ne→16O+α overlap was extracted and compared with other values from the literature. The present results suggest that the (20Ne,16O ) reaction might be an alternative means of exploring the α -particle structure of nuclei.

Symptom clusters in patients with nasopharyngeal carcinoma during radiotherapy.

PubMed

Xiao, Wenli; Chan, Carmen W H; Fan, Yuying; Leung, Doris Y P; Xia, Weixiong; He, Yan; Tang, Linquan

2017-06-01

Despite the improvement in radiotherapy (RT) technology, patients with nasopharyngeal carcinoma (NPC) still suffer from numerous distressing symptoms simultaneously during RT. The purpose of the study was to investigate the symptom clusters experienced by NPC patients during RT. First-treated Chinese NPC patients (n = 130) undergoing late-period RT (from week 4 till the end) were recruited for this cross-sectional study. They completed a sociodemographic and clinical data questionnaire, the Chinese version of the M. D. Anderson Symptom Inventory - Head and Neck Module (MDASI-HN-C) and the Chinese version of the Functional Assessment of Cancer Therapy - Head and Neck Scale (FACT-H&N-C). Principal axis factor analysis with oblimin rotation, independent t-test, one-way analysis of variance (ANOVA) and Pearson product-moment correlation were used to analyze the data. Four symptom clusters were identified, and labelled general, gastrointestinal, nutrition impact and social interaction impact. Of these 4 types, the nutrition impact symptom cluster was the most severe. Statistically positive correlations were found between severity of all 4 symptom clusters and symptom interference, as well as weight loss. Statistically negative correlations were detected between the cluster severity and the QOL total score and 3 out of 5 subscale scores. The four clusters identified reveal the symptom patterns experienced by NPC patients during RT. Future intervention studies on managing these symptom clusters are warranted, especially for the nutrition impact symptom cluster. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluating WAIS-IV structure through a different psychometric lens: structural causal model discovery as an alternative to confirmatory factor analysis.

PubMed

van Dijk, Marjolein J A M; Claassen, Tom; Suwartono, Christiany; van der Veld, William M; van der Heijden, Paul T; Hendriks, Marc P H

Since the publication of the WAIS-IV in the U.S. in 2008, efforts have been made to explore the structural validity by applying factor analysis to various samples. This study aims to achieve a more fine-grained understanding of the structure of the Dutch language version of the WAIS-IV (WAIS-IV-NL) by applying an alternative analysis based on causal modeling in addition to confirmatory factor analysis (CFA). The Bayesian Constraint-based Causal Discovery (BCCD) algorithm learns underlying network structures directly from data and assesses more complex structures than is possible with factor analysis. WAIS-IV-NL profiles of two clinical samples of 202 patients (i.e. patients with temporal lobe epilepsy and a mixed psychiatric outpatient group) were analyzed and contrasted with a matched control group (N = 202) selected from the Dutch standardization sample of the WAIS-IV-NL to investigate internal structure by means of CFA and BCCD. With CFA, the four-factor structure as proposed by Wechsler demonstrates acceptable fit in all three subsamples. However, BCCD revealed three consistent clusters (verbal comprehension, visual processing, and processing speed) in all three subsamples. The combination of Arithmetic and Digit Span as a coherent working memory factor could not be verified, and Matrix Reasoning appeared to be isolated. With BCCD, some discrepancies from the proposed four-factor structure are exemplified. Furthermore, these results fit CHC theory of intelligence more clearly. Consistent clustering patterns indicate these results are robust. The structural causal discovery approach may be helpful in better interpreting existing tests, the development of new tests, and aid in diagnostic instruments.

Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study.

PubMed

Meghani, Salimah H; Knafl, George J

2017-02-10

To identify unique clusters of patients based on their concerns in using analgesia for cancer pain and predictors of the cluster membership. This was a 3-mo prospective observational study ( n = 207). Patients were included if they were adults (≥ 18 years), diagnosed with solid tumors or multiple myelomas, and had at least one prescription of around-the-clock pain medication for cancer or cancer-treatment-related pain. Patients were recruited from two outpatient medical oncology clinics within a large health system in Philadelphia. A choice-based conjoint (CBC) analysis experiment was used to elicit analgesic treatment preferences (utilities). Patients employed trade-offs based on five analgesic attributes (percent relief from analgesics, type of analgesic, type of side-effects, severity of side-effects, out of pocket cost). Patients were clustered based on CBC utilities using novel adaptive statistical methods. Multiple logistic regression was used to identify predictors of cluster membership. The analyses found 4 unique clusters: Most patients made trade-offs based on the expectation of pain relief (cluster 1, 41%). For a subset, the main underlying concern was type of analgesic prescribed, i.e ., opioid vs non-opioid (cluster 2, 11%) and type of analgesic side effects (cluster 4, 21%), respectively. About one in four made trade-offs based on multiple concerns simultaneously including pain relief, type of side effects, and severity of side effects (cluster 3, 28%). In multivariable analysis, to identify predictors of cluster membership, clinical and socioeconomic factors (education, health literacy, income, social support) rather than analgesic attitudes and beliefs were found important; only the belief, i.e ., pain medications can mask changes in health or keep you from knowing what is going on in your body was found significant in predicting two of the four clusters [cluster 1 (-); cluster 4 (+)]. Most patients appear to be driven by a single salient concern in using analgesia for cancer pain. Addressing these concerns, perhaps through real time clinical assessments, may improve patients' analgesic adherence patterns and cancer pain outcomes.

Spatio-Temporal Dynamics of Asymptomatic Malaria: Bridging the Gap Between Annual Malaria Resurgences in a Sahelian Environment.

PubMed

Coulibaly, Drissa; Travassos, Mark A; Tolo, Youssouf; Laurens, Matthew B; Kone, Abdoulaye K; Traore, Karim; Sissoko, Mody; Niangaly, Amadou; Diarra, Issa; Daou, Modibo; Guindo, Boureima; Rebaudet, Stanislas; Kouriba, Bourema; Dessay, Nadine; Piarroux, Renaud; Plowe, Christopher V; Doumbo, Ogobara K; Thera, Mahamadou A; Gaudart, Jean

2017-12-01

In areas of seasonal malaria transmission, the incidence rate of malaria infection is presumed to be near zero at the end of the dry season. Asymptomatic individuals may constitute a major parasite reservoir during this time. We conducted a longitudinal analysis of the spatio-temporal distribution of clinical malaria and asymptomatic parasitemia over time in a Malian town to highlight these malaria transmission dynamics. For a cohort of 300 rural children followed over 2009-2014, periodicity and phase shift between malaria and rainfall were determined by spectral analysis. Spatial risk clusters of clinical episodes or carriage were identified. A nested-case-control study was conducted to assess the parasite carriage factors. Malaria infection persisted over the entire year with seasonal peaks. High transmission periods began 2-3 months after the rains began. A cluster with a low risk of clinical malaria in the town center persisted in high and low transmission periods. Throughout 2009-2014, cluster locations did not vary from year to year. Asymptomatic and gametocyte carriage were persistent, even during low transmission periods. For high transmission periods, the ratio of asymptomatic to clinical cases was approximately 0.5, but was five times higher during low transmission periods. Clinical episodes at previous high transmission periods were a protective factor for asymptomatic carriage, but carrying parasites without symptoms at a previous high transmission period was a risk factor for asymptomatic carriage. Stable malaria transmission was associated with sustained asymptomatic carriage during dry seasons. Control strategies should target persistent low-level parasitemia clusters to interrupt transmission.

Micro-epidemiology and spatial heterogeneity of P. vivax parasitaemia in riverine communities of the Peruvian Amazon: A multilevel analysis.

PubMed

Carrasco-Escobar, Gabriel; Gamboa, Dionicia; Castro, Marcia C; Bangdiwala, Shrikant I; Rodriguez, Hugo; Contreras-Mancilla, Juan; Alava, Freddy; Speybroeck, Niko; Lescano, Andres G; Vinetz, Joseph M; Rosas-Aguirre, Angel; Llanos-Cuentas, Alejandro

2017-08-14

Malaria has steadily increased in the Peruvian Amazon over the last five years. This study aimed to determine the parasite prevalence and micro-geographical heterogeneity of Plasmodium vivax parasitaemia in communities of the Peruvian Amazon. Four cross-sectional active case detection surveys were conducted between May and July 2015 in four riverine communities in Mazan district. Analysis of 2785 samples of 820 individuals nested within 154 households for Plasmodium parasitaemia was carried out using light microscopy and qPCR. The spatio-temporal distribution of Plasmodium parasitaemia, dominated by P. vivax, was shown to cluster at both household and community levels. Of enrolled individuals, 47% had at least one P. vivax parasitaemia and 10% P. falciparum, by qPCR, both of which were predominantly sub-microscopic and asymptomatic. Spatial analysis detected significant clustering in three communities. Our findings showed that communities at small-to-moderate spatial scales differed in P. vivax parasite prevalence, and multilevel Poisson regression models showed that such differences were influenced by factors such as age, education, and location of households within high-risk clusters, as well as factors linked to a local micro-geographic context, such as travel and occupation. Complex transmission patterns were found to be related to human mobility among communities in the same micro-basin.

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

PubMed

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

2016-01-01

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

A Cross-Cultural Comparison of Symptom Reporting and Symptom Clusters in Heart Failure.

PubMed

Park, Jumin; Johantgen, Mary E

2017-07-01

An understanding of symptoms in heart failure (HF) among different cultural groups has become increasingly important. The purpose of this study was to compare symptom reporting and symptom clusters in HF patients between a Western (the United States) and an Eastern Asian sample (China and Taiwan). A secondary analysis of a cross-sectional observational study was conducted. The data were obtained from a matched HF patient sample from the United States and China/Taiwan ( N = 240 in each). Eight selective items related to HF symptoms from the Minnesota Living with Heart Failure Questionnaire were analyzed. Compared with the U.S. sample, HF patients from China/Taiwan reported a lower level of symptom distress. Analysis of two different regional groups did not result in the same number of clusters using latent class approach: the United States (four classes) and China/Taiwan (three classes). The study demonstrated that symptom reporting and identification of symptom clusters might be influenced by cultural factors.

An application of bioassessment metrics and multivariate techniques to evaluate central Nebraska streams

USGS Publications Warehouse

Frenzel, S.A.

1996-01-01

Ninety-one stream sites in central Nebraska were classified into four clusters on the basis of a cluster analysis (TWINSPAN) of macroinvertebrate data. Rapid bioassessment protocol scores for macroinvertebrate species were significantly different among sites grouped by teh first division into two clusters. This division may have distinguished sites on the basis of water-quality imparement. Individual metrics that differed between clusters of sites were the Hilsenhoff Biotic Index, the number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa, and the ratio of individuals in EPT to Chironomidae taxa. Canonical correspondence analysis of 57 of 91 sites showed that stream width, site altitude, latitude, soil permeability, water temperature, and mean annual precipitation were the most important environmental variables describing variance in the species-environment relation. Stream width and soil permeability reflected streamflow characteristics of a site, whereas site altitude and latitude were factors related to general climatic conditions. Mean annual precipitation related to both streamflow and climatic conditions.

Clustering gene expression data based on predicted differential effects of GV interaction.

PubMed

Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

Optimization of the Ion Source-Mass Spectrometry Parameters in Non-Steroidal Anti-Inflammatory and Analgesic Pharmaceuticals Analysis by a Design of Experiments Approach

NASA Astrophysics Data System (ADS)

Paíga, Paula; Silva, Luís M. S.; Delerue-Matos, Cristina

2016-10-01

The flow rates of drying and nebulizing gas, heat block and desolvation line temperatures and interface voltage are potential electrospray ionization parameters as they may enhance sensitivity of the mass spectrometer. The conditions that give higher sensitivity of 13 pharmaceuticals were explored. First, Plackett-Burman design was implemented to screen significant factors, and it was concluded that interface voltage and nebulizing gas flow were the only factors that influence the intensity signal for all pharmaceuticals. This fractionated factorial design was projected to set a full 22 factorial design with center points. The lack-of-fit test proved to be significant. Then, a central composite face-centered design was conducted. Finally, a stepwise multiple linear regression and subsequently an optimization problem solving were carried out. Two main drug clusters were found concerning the signal intensities of all runs of the augmented factorial design. p-Aminophenol, salicylic acid, and nimesulide constitute one cluster as a result of showing much higher sensitivity than the remaining drugs. The other cluster is more homogeneous with some sub-clusters comprising one pharmaceutical and its respective metabolite. It was observed that instrumental signal increased when both significant factors increased with maximum signal occurring when both codified factors are set at level +1. It was also found that, for most of the pharmaceuticals, interface voltage influences the intensity of the instrument more than the nebulizing gas flowrate. The only exceptions refer to nimesulide where the relative importance of the factors is reversed and still salicylic acid where both factors equally influence the instrumental signal.

Recent TB transmission, clustering and predictors of large clusters in London, 2010–2012: results from first 3 years of universal MIRU-VNTR strain typing

PubMed Central

Hamblion, Esther L; Le Menach, Arnaud; Anderson, Laura F; Lalor, Maeve K; Brown, Tim; Abubakar, Ibrahim; Anderson, Charlotte; Maguire, Helen; Anderson, Sarah R

2016-01-01

Background The incidence of TB has doubled in the last 20 years in London. A better understanding of risk groups for recent transmission is required to effectively target interventions. We investigated the molecular epidemiological characteristics of TB cases to estimate the proportion of cases due to recent transmission, and identify predictors for belonging to a cluster. Methods The study population included all culture-positive TB cases in London residents, notified between January 2010 and December 2012, strain typed using 24-loci multiple interspersed repetitive units-variable number tandem repeats. Multivariable logistic regression analysis was performed to assess the risk factors for clustering using sociodemographic and clinical characteristics of cases and for cluster size based on the characteristics of the first two cases. Results There were 10 147 cases of which 5728 (57%) were culture confirmed and 4790 isolates (84%) were typed. 2194 (46%) were clustered in 570 clusters, and the estimated proportion attributable to recent transmission was 34%. Clustered cases were more likely to be UK born, have pulmonary TB, a previous diagnosis, a history of substance abuse or alcohol abuse and imprisonment, be of white, Indian, black-African or Caribbean ethnicity. The time between notification of the first two cases was more likely to be <90 days in large clusters. Conclusions Up to a third of TB cases in London may be due to recent transmission. Resources should be directed to the timely investigation of clusters involving cases with risk factors, particularly those with a short period between the first two cases, to interrupt onward transmission of TB. PMID:27417280

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.

Risk factors associated with occurrence of African swine fever outbreaks in smallholder pig farms in four districts along the Uganda-Kenya border.

PubMed

Nantima, Noelina; Ocaido, Michael; Ouma, Emily; Davies, Jocelyn; Dione, Michel; Okoth, Edward; Mugisha, Anthony; Bishop, Richard

2015-03-01

A cross-sectional survey was carried out to assess risk factors associated with occurrence of African swine fever (ASF) outbreaks in smallholder pig farms in four districts along Kenya-Uganda border. Information was collected by administering questionnaires to 642 randomly selected pig households in the study area. The study showed that the major risk factors that influenced ASF occurrence were purchase of pigs in the previous year (p < 0.000) and feeding of pigs with swill (p < 0.024). By employing cluster analysis, three clusters of pig production types were identified based on production characteristics that were found to differ significantly between districts. The most vulnerable cluster to ASF was households with the highest reported number of ASF outbreaks and composed of those that practiced free range at least some of the time. The majority of the households in this cluster were from Busia district in Uganda. On the other hand, the least vulnerable cluster to ASF composed of households that had the least number of pig purchases, minimal swill feeding, and less treatment for internal and external parasites. The largest proportion of households in this cluster was from Busia district Kenya. The study recommended the need to sensitize farmers to adopt proper biosecurity practices such as total confinement of pigs, treatment of swill, isolation of newly purchased pigs for at least 2 weeks, and provision of incentives for farmers to report suspected outbreaks to authorities and rapid confirmation of outbreaks.

Defining syndromes using cattle meat inspection data for syndromic surveillance purposes: a statistical approach with the 2005–2010 data from ten French slaughterhouses

PubMed Central

2013-01-01

Background The slaughterhouse is a central processing point for food animals and thus a source of both demographic data (age, breed, sex) and health-related data (reason for condemnation and condemned portions) that are not available through other sources. Using these data for syndromic surveillance is therefore tempting. However many possible reasons for condemnation and condemned portions exist, making the definition of relevant syndromes challenging. The objective of this study was to determine a typology of cattle with at least one portion of the carcass condemned in order to define syndromes. Multiple factor analysis (MFA) in combination with clustering methods was performed using both health-related data and demographic data. Results Analyses were performed on 381,186 cattle with at least one portion of the carcass condemned among the 1,937,917 cattle slaughtered in ten French abattoirs. Results of the MFA and clustering methods led to 12 clusters considered as stable according to year of slaughter and slaughterhouse. One cluster was specific to a disease of public health importance (cysticercosis). Two clusters were linked to the slaughtering process (fecal contamination of heart or lungs and deterioration lesions). Two clusters respectively characterized by chronic liver lesions and chronic peritonitis could be linked to diseases of economic importance to farmers. Three clusters could be linked respectively to reticulo-pericarditis, fatty liver syndrome and farmer’s lung syndrome, which are related to both diseases of economic importance to farmers and herd management issues. Three clusters respectively characterized by arthritis, myopathy and Dark Firm Dry (DFD) meat could notably be linked to animal welfare issues. Finally, one cluster, characterized by bronchopneumonia, could be linked to both animal health and herd management issues. Conclusion The statistical approach of combining multiple factor analysis with cluster analysis showed its relevance for the detection of syndromes using available large and complex slaughterhouse data. The advantages of this statistical approach are to i) define groups of reasons for condemnation based on meat inspection data, ii) help grouping reasons for condemnation among a list of various possible reasons for condemnation for which a consensus among experts could be difficult to reach, iii) assign each animal to a single syndrome which allows the detection of changes in trends of syndromes to detect unusual patterns in known diseases and emergence of new diseases. PMID:23628140

Spatio-Temporal Analysis of Smear-Positive Tuberculosis in the Sidama Zone, Southern Ethiopia

PubMed Central

Dangisso, Mesay Hailu; Datiko, Daniel Gemechu; Lindtjørn, Bernt

2015-01-01

Background Tuberculosis (TB) is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs). However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia. Methods A retrospective space–time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district) to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB). Scan statistics, Global Moran’s I, and Getis and Ordi (Gi*) statistics were all used to help analyze the spatial distribution and clusters of the disease across settings. Results A total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p<0.001), with 12,155 observed and 8,668 expected cases. The Gi* statistic also identified the clusters in the same areas, and the spatial clusters showed stability in most areas in each year during the study period. The space-time analysis also detected the most likely cluster in 193 kebeles in the same eight districts (RR= 1.92, p<0.001), with 7,584 observed and 4,738 expected cases in 2003-2012. Conclusion The study found variations in CNRs and significant spatio-temporal clusters of smear-positive PTB in the Sidama Zone. The findings can be used to guide TB control programs to devise effective TB control strategies for the geographic areas characterized by the highest CNRs. Further studies are required to understand the factors associated with clustering based on individual level locations and investigation of cases. PMID:26030162

The Outer Limits of Galaxy Clusters: Observations to the Virial Radius with Suzaku, XMM,and Chandra

NASA Technical Reports Server (NTRS)

Miller, Eric D.; Bautz, Marshall; George, Jithin; Mushotzky, Richard; Davis, David; Henry, J. Patrick

2012-01-01

The outskirts of galaxy clusters, near the virial radius, remain relatively unexplored territory and yet are vital to our understanding of cluster growth, structure, and mass. In this presentation, we show the first results from a program to constrain the sate of the outer intra-cluster medium (ICM) in a large sample of galaxy clusters, exploiting the strengths of three complementary X-ray observatories: Suzaku (low, stable background), XMM-Newton (high sensitivity),and Chandra (good spatial resolution). By carefully combining observations from the cluster core to beyond r200, we are able to identify and reduce systematic uncertainties that would impede our spatial and spectral analysis using a single telescope. Our sample comprises nine clusters at z is approximately 0.1-0.2 fully covered in azimuth to beyond r200, and our analysis indicates that the ICM is not in hydrostatic equilibrium in the cluster outskirts, where we see clear azimuthal variations in temperature and surface brightness. In one of the clusters, we are able to measure the diffuse X-ray emission well beyond r200, and we find that the entropy profile and the gas fraction are consistent with expectations from theory and numerical simulations. These results stand in contrast to recent studies which point to gas clumping in the outskirts; the extent to which differences of cluster environment or instrumental effects factor in this difference remains unclear. From a broader perspective, this project will produce a sizeable fiducial data set for detailed comparison with high-resolution numerical simulations.

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

USGS Publications Warehouse

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

2002-01-01

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

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

PubMed Central

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

1986-01-01

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

Accident patterns for construction-related workers: a cluster analysis

NASA Astrophysics Data System (ADS)

Liao, Chia-Wen; Tyan, Yaw-Yauan

2012-01-01

The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

Accident patterns for construction-related workers: a cluster analysis

NASA Astrophysics Data System (ADS)

Liao, Chia-Wen; Tyan, Yaw-Yauan

2011-12-01

The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

Body Mass Index, Waist Circumference, and the Clustering of Cardiometabolic Risk Factors in Early Childhood.

PubMed

Anderson, Laura N; Lebovic, Gerald; Hamilton, Jill; Hanley, Anthony J; McCrindle, Brian W; Maguire, Jonathon L; Parkin, Patricia C; Birken, Catherine S

2016-03-01

Obesity has its origins in early childhood; however, there is limited evidence of the association between anthropometric indicators and cardiometabolic risk factors in young children. Our aim was to evaluate the associations between body mass index (BMI) and waist circumference (WC) in relation to cardiometabolic risk factors and to explore the clustering of these factors. A cross-sectional study was conducted in children aged 1-5 years through TARGet Kids! (n = 2917). Logistic regression was used to evaluate associations between BMI and WC z-scores and individual traditional and possible non-traditional cardiometabolic risk factors. The underlying clustering of these measures was evaluated using principal components analysis (PCA). Child obesity (BMI z-score >2) was associated with high (>90th percentile) leptin [odds ratio (OR) 8.15, 95% confidence interval (CI) 4.56, 14.58] and insulin (OR = 1.76; 95% CI 1.05, 2.94). WC z-score >1 was associated with high insulin (OR 1.59, 95% CI 1.11, 2.28), leptin (OR 5.48, 95% CI 3.48, 8.63) and 25-hydroxyvitamin D < 75 nmol/L (OR 1.39, 95% CI 1.08, 1.79). BMI and WC were not associated with other traditional cardiometabolic risk factors, including non-High Density Lipoprotein (HDL) cholesterol, and glucose. Among children 3-5 years (n = 1035) the PCA of traditional risk factors identified three components: adiposity/blood pressure, metabolic, and lipids. The inclusion of non-traditional risk factors identified four additional components but contributed minimally to the total variation explained. Anthropometric indicators are associated with selected cardiometabolic risk factors in early childhood, although the clustering of risk factors suggests that adiposity is only one distinct component of cardiometabolic risk. The measurement of other risk factors beyond BMI and WC may be important in defining cardiometabolic risk in early childhood. © 2015 John Wiley & Sons Ltd.

Genetic analysis of fibroblast growth factor signaling in the Drosophila eye.

PubMed

Mukherjee, T; Choi, I; Banerjee, Utpal

2012-01-01

The development of eyes in Drosophila involves intricate epithelial reorganization events for accurate positioning of cells and proper formation and organization of ommatidial clusters. We demonstrate that Branchless (Bnl), the fibroblast growth factor ligand, regulates restructuring events in the eye disc primordium from as early as the emergence of clusters from a morphogenetic front to the cellular movements during pupal eye development. Breathless (Btl) functions as the fibroblast growth factor receptor to mediate Bnl signal, and together they regulate expression of DE-cadherin, Crumbs, and Actin. In addition, in the eye Bnl regulates the temporal onset and extent of retinal basal glial cell migration by activating Btl in the glia. We hypothesized that the Bnl functions in the eye are Hedgehog dependent and represent novel aspects of Bnl signaling not explored previously.

Using preoperative unsupervised cluster analysis of chronic rhinosinusitis to inform patient decision and endoscopic sinus surgery outcome.

PubMed

Adnane, Choaib; Adouly, Taoufik; Khallouk, Amine; Rouadi, Sami; Abada, Redallah; Roubal, Mohamed; Mahtar, Mohamed

2017-02-01

The purpose of this study is to use unsupervised cluster methodology to identify phenotype and mucosal eosinophilia endotype subgroups of patients with medical refractory chronic rhinosinusitis (CRS), and evaluate the difference in quality of life (QOL) outcomes after endoscopic sinus surgery (ESS) between these clusters for better surgical case selection. A prospective cohort study included 131 patients with medical refractory CRS who elected ESS. The Sino-Nasal Outcome Test (SNOT-22) was used to evaluate QOL before and 12 months after surgery. Unsupervised two-step clustering method was performed. One hundred and thirteen subjects were retained in this study: 46 patients with CRS without nasal polyps and 67 patients with nasal polyps. Nasal polyps, gender, mucosal eosinophilia profile, and prior sinus surgery were the most discriminating factors in the generated clusters. Three clusters were identified. A significant clinical improvement was observed in all clusters 12 months after surgery with a reduction of SNOT-22 scores. There was a significant difference in QOL outcomes between clusters; cluster 1 had the worst QOL improvement after FESS in comparison with the other clusters 2 and 3. All patients in cluster 1 presented CRSwNP with the highest mucosal eosinophilia endotype. Clustering method is able to classify CRS phenotypes and endotypes with different associated surgical outcomes.

Altitude as a risk factor for the development of hypospadias. Geographical cluster distribution analysis in South America.

PubMed

Fernández, Nicolas; Lorenzo, Armando; Bägli, Darius; Zarante, Ignacio

2016-10-01

Hypospadias is the most common congenital anomaly affecting the genitals. It has been established as a multifactorial disease with increasing prevalence. Many risk factors have been identified such as prematurity, birth weight, mother's age, and exposure to endocrine disruptors. In recent decades multiple authors using surveillance systems have described an increase in prevalence of hypospadias, but most of the published literature comes from developed countries in Europe and North America and few of the published studies have involved cluster analysis. Few large-scale studies have been performed addressing the effect of altitude and other geographical aspects on the development of hypospadias. Acknowledging this limitation, we present novel results of a multinational spatial scan statistical analysis over a 30-year period in South America and an altitude analysis of hypospadias distribution on a continent level. A retrospective review was performed of the Latin American collaborative study of congenital malformations (ECLAMC). A total of 4,020,384 newborns was surveyed between 1982 and December 2011 in all participating centers. We selected all patients with hypospadias. All degrees of clinical severity were included in the analysis. Each participating center was geographically identified with its coordinates and altitude above sea level. A spatial scan statistical analysis was performed using Kulldorf's methodology and a prevalence trend analysis over time in centers below and above 2000 m. During the study period we found 159 hospitals in six different countries (Colombia, Bolivia, Brazil, Argentina, Chile, and Uruguay) with 4,537 cases of hypospadias and a global prevalence rate of 11.3/10,000 newborns. Trend analysis showed that centers below 2000 m had an increasing trend with an average of 10/10,000 newborns as opposed to those centers above 2000 m that showed a reducing trend with an average prevalence of 7.8 (p = 0.1246). We identified clusters with significant increases of prevalence in five centers along the coast at an average altitude of 219.8 m above sea level (p > 0.0000). Reduction in prevalence was found in clusters located in two centers on the Andes mountains. Altitude of 2,000 m was associated with hypospadias (Figure), with an OR 0.59 (0.5-0.69). There are ethnic arguments to support our results supported by protective polymorphism distribution in high lands. Altitude above 2,000 m is suggested to have a protective effect for hypospadias. Specific clusters have been identified with increased risk for hypospadias. Environmental risk factors in these areas need to be further studied given the association seen between altitude and the distribution of more severe cases. Copyright © 2016 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

Sensory factors affecting female consumers' acceptability of nail polish.

PubMed

Sun, C; Koppel, K; Adhikari, K

2015-12-01

The objectives of this study were to determine what sensory factors impact consumers' acceptability of nail polishes, to explore how these sensory factors impact consumers' acceptability of nail polishes, to investigate whether there are any consumer segments according to their overall acceptability on different nail polishes and to scrutinize how the consumer segments are related to the sensory factors. Ninety-eight females participated in a nail polish consumer study at Kansas State University. Eight commercial products belonging to four categories - regular (REG), gel (GEL), flake (FLK) and water-based (WAT) - were evaluated. Each nail polish sample was evaluated twice by each participant in two different tasks - a task devoted to applying and evaluating the product and a task devoted to observing the appearance and evaluating the product. Pearson's correlation analysis, analysis of variance (ANOVA), external preference mapping, cluster analysis and internal preference mapping were applied for data analysis. Participants' scores of overall liking of the nail polishes were similar in the application task and in the observation task. In general, participants liked the REG and GEL product samples more than the FLK and WAT samples. Among all the sensory attributes, appearance attributes were the major factors that affected participants' overall liking. Aroma seemed to be a minor factor to participants' overall liking. Some sensory attributes, such as runny, shininess, opacity, spreadability, smoothness, coverage and wet appearance, were found to drive participants' overall acceptability positively, whereas others such as pinhole, fatty-edges, blister, brushlines, pearl-like, flake-protrusion, glittery and initial-drag impacted participants' overall acceptability negatively. Four clusters of participants were identified according to their overall liking scores from both the application task and the observation task. Participants' acceptability, based on different sensory attributes, could help a nail polish manufacturer modify or improve their nail polish formulas. Nail polish manufacturers could use the consumer cluster information to improve their marketing strategies for specific categories of their products and to target their advertising on particular consumer groups. © 2015 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006

PubMed Central

2009-01-01

Background Spatial analytical techniques and models are often used in epidemiology to identify spatial anomalies (hotspots) in disease regions. These analytical approaches can be used to not only identify the location of such hotspots, but also their spatial patterns. Methods In this study, we utilize spatial autocorrelation methodologies, including Global Moran's I and Local Getis-Ord statistics, to describe and map spatial clusters, and areas in which these are situated, for the 20 leading causes of death in Taiwan. In addition, we use the fit to a logistic regression model to test the characteristics of similarity and dissimilarity by gender. Results Gender is compared in efforts to formulate the common spatial risk. The mean found by local spatial autocorrelation analysis is utilized to identify spatial cluster patterns. There is naturally great interest in discovering the relationship between the leading causes of death and well-documented spatial risk factors. For example, in Taiwan, we found the geographical distribution of clusters where there is a prevalence of tuberculosis to closely correspond to the location of aboriginal townships. Conclusions Cluster mapping helps to clarify issues such as the spatial aspects of both internal and external correlations for leading health care events. This is of great aid in assessing spatial risk factors, which in turn facilitates the planning of the most advantageous types of health care policies and implementation of effective health care services. PMID:20003460

Variable number of tandem repeats and pulsed-field gel electrophoresis cluster analysis of enterohemorrhagic Escherichia coli serovar O157 strains.

PubMed

Yokoyama, Eiji; Uchimura, Masako

2007-11-01

Ninety-five enterohemorrhagic Escherichia coli serovar O157 strains, including 30 strains isolated from 13 intrafamily outbreaks and 14 strains isolated from 3 mass outbreaks, were studied by pulsed-field gel electrophoresis (PFGE) and variable number of tandem repeats (VNTR) typing, and the resulting data were subjected to cluster analysis. Cluster analysis of the VNTR typing data revealed that 57 (60.0%) of 95 strains, including all epidemiologically linked strains, formed clusters with at least 95% similarity. Cluster analysis of the PFGE patterns revealed that 67 (70.5%) of 95 strains, including all but 1 of the epidemiologically linked strains, formed clusters with 90% similarity. The number of epidemiologically unlinked strains forming clusters was significantly less by VNTR cluster analysis than by PFGE cluster analysis. The congruence value between PFGE and VNTR cluster analysis was low and did not show an obvious correlation. With two-step cluster analysis, the number of clustered epidemiologically unlinked strains by PFGE cluster analysis that were divided by subsequent VNTR cluster analysis was significantly higher than the number by VNTR cluster analysis that were divided by subsequent PFGE cluster analysis. These results indicate that VNTR cluster analysis is more efficient than PFGE cluster analysis as an epidemiological tool to trace the transmission of enterohemorrhagic E. coli O157.

An improved optimization algorithm and Bayes factor termination criterion for sequential projection pursuit

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

Webb-Robertson, Bobbie-Jo M.; Jarman, Kristin H.; Harvey, Scott D.

2005-05-28

A fundamental problem in analysis of highly multivariate spectral or chromatographic data is reduction of dimensionality. Principal components analysis (PCA), concerned with explaining the variance-covariance structure of the data, is a commonly used approach to dimension reduction. Recently an attractive alternative to PCA, sequential projection pursuit (SPP), has been introduced. Designed to elicit clustering tendencies in the data, SPP may be more appropriate when performing clustering or classification analysis. However, the existing genetic algorithm (GA) implementation of SPP has two shortcomings, computation time and inability to determine the number of factors necessary to explain the majority of the structure inmore » the data. We address both these shortcomings. First, we introduce a new SPP algorithm, a random scan sampling algorithm (RSSA), that significantly reduces computation time. We compare the computational burden of the RSS and GA implementation for SPP on a dataset containing Raman spectra of twelve organic compounds. Second, we propose a Bayes factor criterion, BFC, as an effective measure for selecting the number of factors needed to explain the majority of the structure in the data. We compare SPP to PCA on two datasets varying in type, size, and difficulty; in both cases SPP achieves a higher accuracy with a lower number of latent variables.« less

Functional analysis of a biosynthetic cluster essential for production of 4-formylaminooxyvinylglycine, a germination-arrest factor from Pseudomonas fluorescens WH6

USDA-ARS?s Scientific Manuscript database

Rhizosphere-associated Pseudomonas fluorescens WH6 produces the germination-arrest factor, 4-formylaminooxyvinylglycine (FVG). FVG has previously been shown to both arrest the germination of weedy grasses and to inhibit the growth of the bacterial plant pathogen Erwinia amylovora. Very little is kno...

Posttraumatic Stress Disorder Symptom Structure in Injured Children: Functional Impairment and Depression Symptoms in a Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Kassam-Adams, Nancy; Marsac, Meghan L.; Cirilli, Carla

2010-01-01

Objective: To examine the factor structure of posttraumatic stress disorder (PTSD) symptoms in children and adolescents who have experienced an acute single-incident trauma, associations between PTSD symptom clusters and functional impairment, and the specificity of PTSD symptoms in relation to depression and general distress. Method: Examined…

A Test for Cluster Bias: Detecting Violations of Measurement Invariance across Clusters in Multilevel Data

ERIC Educational Resources Information Center

Jak, Suzanne; Oort, Frans J.; Dolan, Conor V.

2013-01-01

We present a test for cluster bias, which can be used to detect violations of measurement invariance across clusters in 2-level data. We show how measurement invariance assumptions across clusters imply measurement invariance across levels in a 2-level factor model. Cluster bias is investigated by testing whether the within-level factor loadings…

Community pharmacy customer segmentation based on factors influencing their selection of pharmacy and over-the-counter medicines.

PubMed

Kevrekidis, Dimitrios Phaedon; Minarikova, Daniela; Markos, Angelos; Malovecka, Ivona; Minarik, Peter

2018-01-01

Within the competitive pharmacy market environment, community pharmacies are required to develop efficient marketing strategies based on contemporary information about consumer behavior in order to attract clients and develop customer loyalty. This study aimed to investigate the consumers' preferences concerning the selection of pharmacy and over-the-counter (OTC) medicines, and to identify customer segments in relation to these preferences. A cross-sectional study was conducted between February and March 2016 on a convenient quota sample of 300 participants recruited in the metropolitan area of Thessaloniki, Greece. The main instrument used for data collection was a structured questionnaire with close-ended, multiple choice questions. To identify customer segments, Two-Step cluster analysis was conducted. Three distinct pharmacy customer clusters emerged. Customers of the largest cluster (49%; 'convenience customers') were mostly younger consumers. They gave moderate to positive ratings to factors affecting the selection of pharmacy and OTCs; convenience, and previous experience and the pharmacist's opinion, received the highest ratings. Customers of the second cluster (35%; 'loyal customers') were mainly retired; most of them reported visiting a single pharmacy. They gave high ratings to all factors that influence pharmacy selection, especially the pharmacy's staff, and factors influencing the purchase of OTCs, particularly previous experience and the pharmacist's opinion. Customers of the smallest cluster (16%; 'convenience and price-sensitive customers') were mainly retired or unemployed with low to moderate education, and low personal income. They gave the lowest ratings to most of the examined factors; convenience among factors influencing pharmacy selection, whereas previous experience, the pharmacist's opinion and product price among those affecting the purchase of OTCs, received the highest ratings. The community pharmacy market comprised of distinct customer segments that varied in the consumer preferences concerning the selection of pharmacy and OTCs, the evaluation of pharmaceutical services and products, and demographic characteristics.

Relationship between Oral Malodor and the Global Composition of Indigenous Bacterial Populations in Saliva ▿

PubMed Central

Takeshita, Toru; Suzuki, Nao; Nakano, Yoshio; Shimazaki, Yoshihiro; Yoneda, Masahiro; Hirofuji, Takao; Yamashita, Yoshihisa

2010-01-01

Oral malodor develops mostly from the metabolic activities of indigenous bacterial populations within the oral cavity, but whether healthy or oral malodor-related patterns of the global bacterial composition exist remains unclear. In this study, the bacterial compositions in the saliva of 240 subjects complaining of oral malodor were divided into groups based on terminal-restriction fragment length polymorphism (T-RFLP) profiles using hierarchical cluster analysis, and the patterns of the microbial community composition of those exhibiting higher and lower malodor were explored. Four types of bacterial community compositions were detected (clusters I, II, III, and IV). Two parameters for measuring oral malodor intensity (the concentration of volatile sulfur compounds in mouth air and the organoleptic score) were noticeably lower in cluster I than in the other clusters. Using multivariate analysis, the differences in the levels of oral malodor were significant after adjustment for potential confounding factors such as total bacterial count, mean periodontal pocket depth, and tongue coating score (P < 0.001). Among the four clusters with different proportions of indigenous members, the T-RFLP profiles of cluster I were implicated as the bacterial populations with higher proportions of Streptococcus, Granulicatella, Rothia, and Treponema species than those of the other clusters. These results clearly correlate the global composition of indigenous bacterial populations with the severity of oral malodor. PMID:20228112

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.

The Internet and Services Marketing--The Case of Danish Retail Banking.

ERIC Educational Resources Information Center

Mols, Niels Peter

2000-01-01

Examines various aspects of the motives, perceptions, and expectations connected with the introduction of Internet banking in Danish retail banking. Responses from questionnaires and results from a factor analysis and a hierarchical cluster analysis indicate a belief that Internet banking will become more important in the future. (Author/LRW)

Acknowledging Different Needs: Developing a Taxonomy of Welfare Leavers.

ERIC Educational Resources Information Center

Julnes, George; Hayashi, Kentaro; Anderson, Steven

2001-01-01

Used cluster analysis of survey data for 506 respondents to create a taxonomy of welfare leavers in Illinois based on their self-reported well-being after leaving welfare. Used classification tree analysis to identify factors associated with different types of leavers. Findings highlight the existence of many marginally successful leavers who…

Patterns of Self-care in Adults With Heart Failure and Their Associations With Sociodemographic and Clinical Characteristics, Quality of Life, and Hospitalizations: A Cluster Analysis.

PubMed

Vellone, Ercole; Fida, Roberta; Ghezzi, Valerio; D'Agostino, Fabio; Biagioli, Valentina; Paturzo, Marco; Strömberg, Anna; Alvaro, Rosaria; Jaarsma, Tiny

Self-care is important in heart failure (HF) treatment, but patients may have difficulties and be inconsistent in its performance. Inconsistencies in self-care behaviors may mirror patterns of self-care in HF patients that are worth identifying to provide interventions tailored to patients. The aims of this study are to identify clusters of HF patients in relation to self-care behaviors and to examine and compare the profile of each HF patient cluster considering the patient's sociodemographics, clinical variables, quality of life, and hospitalizations. This was a secondary analysis of data from a cross-sectional study in which we enrolled 1192 HF patients across Italy. A cluster analysis was used to identify clusters of patients based on the European Heart Failure Self-care Behaviour Scale factor scores. Analysis of variance and χ test were used to examine the characteristics of each cluster. Patients were 72.4 years old on average, and 58% were men. Four clusters of patients were identified: (1) high consistent adherence with high consulting behaviors, characterized by younger patients, with higher formal education and higher income, less clinically compromised, with the best physical and mental quality of life (QOL) and lowest hospitalization rates; (2) low consistent adherence with low consulting behaviors, characterized mainly by male patients, with lower formal education and lowest income, more clinically compromised, and worse mental QOL; (3) inconsistent adherence with low consulting behaviors, characterized by patients who were less likely to have a caregiver, with the longest illness duration, the highest number of prescribed medications, and the best mental QOL; (4) and inconsistent adherence with high consulting behaviors, characterized by patients who were mostly female, with lower formal education, worst cognitive impairment, worst physical and mental QOL, and higher hospitalization rates. The 4 clusters identified in this study and their associated characteristics could be used to tailor interventions aimed at improving self-care behaviors in HF patients.

Patient clusters in acute, work-related back pain based on patterns of disability risk factors.

PubMed

Shaw, William S; Pransky, Glenn; Patterson, William; Linton, Steven J; Winters, Thomas

2007-02-01

To identify subgroups of patients with work-related back pain based on disability risk factors. Patients with work-related back pain (N = 528) completed a 16-item questionnaire of potential disability risk factors before their initial medical evaluation. Outcomes of pain, functional limitation, and work disability were assessed 1 and 3 months later. A K-Means cluster analysis of 5 disability risk factors (pain, depressed mood, fear avoidant beliefs, work inflexibility, and poor expectations for recovery) resulted in 4 sub-groups: low risk (n = 182); emotional distress (n = 103); severe pain/fear avoidant (n = 102); and concerns about job accommodation (n = 141). Pain and disability outcomes at follow-up were superior in the low-risk group and poorest in the severe pain/fear avoidant group. Patients with acute back pain can be discriminated into subgroups depending on whether disability is related to pain beliefs, emotional distress, or workplace concerns.

Assessment of sediment quality in the Mediterranean Sea-Boughrara lagoon exchange areas (southeastern Tunisia): GIS approach-based chemometric methods.

PubMed

Kharroubi, Adel; Gargouri, Dorra; Baati, Houda; Azri, Chafai

2012-06-01

Concentrations of selected heavy metals (Cd, Pb, Zn, Cu, Mn, and Fe) in surface sediments from 66 sites in both northern and eastern Mediterranean Sea-Boughrara lagoon exchange areas (southeastern Tunisia) were studied in order to understand current metal contamination due to the urbanization and economic development of nearby several coastal regions of the Gulf of Gabès. Multiple approaches were applied for the sediment quality assessment. These approaches were based on GIS coupled with chemometric methods (enrichment factors, geoaccumulation index, principal component analysis, and cluster analysis). Enrichment factors and principal component analysis revealed two distinct groups of metals. The first group corresponded to Fe and Mn derived from natural sources, and the second group contained Cd, Pb, Zn, and Cu originated from man-made sources. For these latter metals, cluster analysis showed two distinct distributions in the selected areas. They were attributed to temporal and spatial variations of contaminant sources input. The geoaccumulation index (I (geo)) values explained that only Cd, Pb, and Cu can be considered as moderate to extreme pollutants in the studied sediments.

The Role of Inflammation in the Pain, Fatigue, and Sleep Disturbance Symptom Cluster in Advanced Cancer.

PubMed

Kwekkeboom, Kristine L; Tostrud, Lauren; Costanzo, Erin; Coe, Christopher L; Serlin, Ronald C; Ward, Sandra E; Zhang, Yingzi

2018-05-01

Symptom researchers have proposed a model of inflammatory cytokine activity and dysregulation in cancer to explain co-occurring symptoms including pain, fatigue, and sleep disturbance. We tested the hypothesis that psychological stress accentuates inflammation and that stress and inflammation contribute to one's experience of the pain, fatigue, and sleep disturbance symptom cluster (symptom cluster severity, symptom cluster distress) and its impact (symptom cluster interference with daily life, quality of life). We used baseline data from a symptom cluster management trial. Adult participants (N = 158) receiving chemotherapy for advanced cancer reported pain, fatigue, and sleep disturbance on enrollment. Before intervention, participants completed measures of demographics, perceived stress, symptom cluster severity, symptom cluster distress, symptom cluster interference with daily life, and quality of life and provided a blood sample for four inflammatory biomarkers (interleukin-1β, interleukin-6, tumor necrosis factor-α, and C-reactive protein). Stress was not directly related to any inflammatory biomarker. Stress and tumor necrosis factor-α were positively related to symptom cluster distress, although not symptom cluster severity. Tumor necrosis factor-α was indirectly related to symptom cluster interference with daily life, through its effect on symptom cluster distress. Stress was positively associated with symptom cluster interference with daily life and inversely with quality of life. Stress also had indirect effects on symptom cluster interference with daily life, through its effect on symptom cluster distress. The proposed inflammatory model of symptoms was partially supported. Investigators should test interventions that target stress as a contributing factor in co-occurring pain, fatigue, and sleep disturbance and explore other factors that may influence inflammatory biomarker levels within the context of an advanced cancer diagnosis and treatment. Copyright © 2018 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Source Evaluation and Trace Metal Contamination in Benthic Sediments from Equatorial Ecosystems Using Multivariate Statistical Techniques

PubMed Central

Benson, Nsikak U.; Asuquo, Francis E.; Williams, Akan B.; Essien, Joseph P.; Ekong, Cyril I.; Akpabio, Otobong; Olajire, Abaas A.

2016-01-01

Trace metals (Cd, Cr, Cu, Ni and Pb) concentrations in benthic sediments were analyzed through multi-step fractionation scheme to assess the levels and sources of contamination in estuarine, riverine and freshwater ecosystems in Niger Delta (Nigeria). The degree of contamination was assessed using the individual contamination factors (ICF) and global contamination factor (GCF). Multivariate statistical approaches including principal component analysis (PCA), cluster analysis and correlation test were employed to evaluate the interrelationships and associated sources of contamination. The spatial distribution of metal concentrations followed the pattern Pb>Cu>Cr>Cd>Ni. Ecological risk index by ICF showed significant potential mobility and bioavailability for Cu, Cu and Ni. The ICF contamination trend in the benthic sediments at all studied sites was Cu>Cr>Ni>Cd>Pb. The principal component and agglomerative clustering analyses indicate that trace metals contamination in the ecosystems was influenced by multiple pollution sources. PMID:27257934

Quantum chemical calculations in the structural analysis of phloretin

NASA Astrophysics Data System (ADS)

Gómez-Zavaglia, Andrea

2009-07-01

In this work, a conformational search on the molecule of phloretin [2',4',6'-Trihydroxy-3-(4-hydroxyphenyl)-propiophenone] has been performed. The molecule of phloretin has eight dihedral angles, four of them taking part in the carbon backbone and the other four, related with the orientation of the hydroxyl groups. A systematic search involving a random variation of the dihedral angles has been used to generate input structures for the quantum chemical calculations. Calculations at the DFT(B3LYP)/6-311++G(d,p) level of theory permitted the identification of 58 local minima belonging to the C 1 symmetry point group. The molecular structures of the conformers have been analyzed using hierarchical cluster analysis. This method allowed us to group conformers according to their similarities, and thus, to correlate the conformers' stability with structural parameters. The dendrogram obtained from the hierarchical cluster analysis depicted two main clusters. Cluster I included all the conformers with relative energies lower than 25 kJ mol -1 and cluster II, the remaining conformers. The possibility of forming intramolecular hydrogen bonds resulted the main factor contributing for the stability. Accordingly, all conformers depicting intramolecular H-bonds belong to cluster I. These conformations are clearly favored when the carbon backbone is as planar as possible. The values of the νC dbnd O and νOH vibrational modes were compared among all the conformers of phloretin. The redshifts associated with intramolecular H-bonds were correlated with the H-bonds distances and energies.

Identification of Reliable Components in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS): a Data-Driven Approach across Metabolic Processes.

PubMed

Motegi, Hiromi; Tsuboi, Yuuri; Saga, Ayako; Kagami, Tomoko; Inoue, Maki; Toki, Hideaki; Minowa, Osamu; Noda, Tetsuo; Kikuchi, Jun

2015-11-04

There is an increasing need to use multivariate statistical methods for understanding biological functions, identifying the mechanisms of diseases, and exploring biomarkers. In addition to classical analyses such as hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis, various multivariate strategies, including independent component analysis, non-negative matrix factorization, and multivariate curve resolution, have recently been proposed. However, determining the number of components is problematic. Despite the proposal of several different methods, no satisfactory approach has yet been reported. To resolve this problem, we implemented a new idea: classifying a component as "reliable" or "unreliable" based on the reproducibility of its appearance, regardless of the number of components in the calculation. Using the clustering method for classification, we applied this idea to multivariate curve resolution-alternating least squares (MCR-ALS). Comparisons between conventional and modified methods applied to proton nuclear magnetic resonance ((1)H-NMR) spectral datasets derived from known standard mixtures and biological mixtures (urine and feces of mice) revealed that more plausible results are obtained by the modified method. In particular, clusters containing little information were detected with reliability. This strategy, named "cluster-aided MCR-ALS," will facilitate the attainment of more reliable results in the metabolomics datasets.

Local and regional components of aerosol in a heavily trafficked street canyon in central London derived from PMF and cluster analysis of single-particle ATOFMS spectra.

PubMed

Giorio, Chiara; Tapparo, Andrea; Dall'Osto, Manuel; Beddows, David C S; Esser-Gietl, Johanna K; Healy, Robert M; Harrison, Roy M

2015-03-17

Positive matrix factorization (PMF) has been applied to single particle ATOFMS spectra collected on a six lane heavily trafficked road in central London (Marylebone Road), which well represents an urban street canyon. PMF analysis successfully extracted 11 factors from mass spectra of about 700,000 particles as a complement to information on particle types (from K-means cluster analysis). The factors were associated with specific sources and represent the contribution of different traffic related components (i.e., lubricating oils, fresh elemental carbon, organonitrogen and aromatic compounds), secondary aerosol locally produced (i.e., nitrate, oxidized organic aerosol and oxidized organonitrogen compounds), urban background together with regional transport (aged elemental carbon and ammonium) and fresh sea spray. An important result from this study is the evidence that rapid chemical processes occur in the street canyon with production of secondary particles from road traffic emissions. These locally generated particles, together with aging processes, dramatically affected aerosol composition producing internally mixed particles. These processes may become important with stagnant air conditions and in countries where gasoline vehicles are predominant and need to be considered when quantifying the impact of traffic emissions.

Inflammatory Mediator Profiles Differ in Sepsis Patients With and Without Bacteremia.

PubMed

Mosevoll, Knut Anders; Skrede, Steinar; Markussen, Dagfinn Lunde; Fanebust, Hans Rune; Flaatten, Hans Kristian; Aßmus, Jörg; Reikvam, Håkon; Bruserud, Øystein

2018-01-01

Systemic levels of cytokines are altered during infection and sepsis. This prospective observational study aimed to investigate whether plasma levels of multiple inflammatory mediators differed between sepsis patients with and those without bacteremia during the initial phase of hospitalization. A total of 80 sepsis patients with proven bacterial infection and no immunosuppression were included in the study. Plasma samples were collected within 24 h of hospitalization, and Luminex ® analysis was performed on 35 mediators: 16 cytokines, six growth factors, four adhesion molecules, and nine matrix metalloproteases (MMPs)/tissue inhibitors of metalloproteinases (TIMPs). Forty-two patients (52.5%) and 38 (47.5%) patients showed positive and negative blood cultures, respectively. There were significant differences in plasma levels of six soluble mediators between the two "bacteremia" and "non-bacteremia" groups, using Mann-Whitney U test ( p  < 0.0014): tumor necrosis factor alpha (TNFα), CCL4, E-selectin, vascular cell adhesion molecule-1 (VCAM-1), intracellular adhesion molecule-1 (ICAM-1), and TIMP-1. Ten soluble mediators also significantly differed in plasma levels between the two groups, with p -values ranging between 0.05 and 0.0014: interleukin (IL)-1ra, IL-10, CCL2, CCL5, CXCL8, CXCL11, hepatocyte growth factor, MMP-8, TIMP-2, and TIMP-4. VCAM-1 showed the most robust results using univariate and multivariate logistic regression. Using unsupervised hierarchical clustering, we found that TNFα, CCL4, E-selectin, VCAM-1, ICAM-1, and TIMP-1 could be used to discriminate between patients with and those without bacteremia. Patients with bacteremia were mainly clustered in two separate groups (two upper clusters, 41/42, 98%), with higher levels of the mediators. One (2%) patient with bacteremia was clustered in the lower cluster, which compromised most of the patients without bacteremia (23/38, 61%) (χ 2 test, p  < 0.0001). Our study showed that analysis of the plasma inflammatory mediator profile could represent a potential strategy for early identification of patients with bacteremia.

Pathways to Late-Life Suicidal Behavior: Cluster Analysis and Predictive Validation of Suicidal Behavior in a Sample of Older Adults With Major Depression.

PubMed

Szanto, Katalin; Galfalvy, Hanga; Vanyukov, Polina M; Keilp, John G; Dombrovski, Alexandre Y

Clinical heterogeneity is a key challenge to understanding suicidal risk, as different pathways to suicidal behavior are likely to exist. We aimed to identify such pathways by uncovering latent classes of late-life depression cases and relating them to prior and future suicidal behavior. Data were collected from June 2010 to September 2015. In this longitudinal study we examined distinct associations of clinical and cognitive/decision-making factors with suicidal behavior in 194 older (50+ years) nondemented, depressed patients; 57 nonpsychiatric healthy controls provided benchmark data. The DSM-IV was used to establish diagnostic criteria. We identified multivariate patterns of risk factors, defining clusters based on personality traits, perceived social support, cognitive performance, and decision-making in an analysis blinded to participants' history of suicidal behavior. We validated these clusters using past and prospective suicidal ideation and behavior. Of 5 clusters identified, 3 were associated with high risk for suicidal behavior: (1) cognitive deficits, dysfunctional personality, low social support, high willingness to delay future rewards, and overrepresentation of high-lethality attempters; (2) high-personality pathology (ie, low self-esteem), minimal or no cognitive deficits, and overrepresentation of low-lethality attempters and ideators; (3) cognitive deficits, inability to delay future rewards, and similar distribution of high- and low-lethality attempters. There were significant between-cluster differences in number (P < .001) and lethality (P = .002) of past suicide attempts and in the likelihood of future suicide attempts (P = .010, 30 attempts by 22 patients, 2 fatal) and emergency psychiatric hospitalizations to prevent suicide (P = .005, 31 participants). Three pathways to suicidal behavior in older patients were found, marked by (1) very high levels of cognitive and dispositional risk factors suggesting a dementia prodrome, (2) dysfunctional personality traits, and (3) impulsive decision-making and cognitive deficits. © Copyright 2018 Physicians Postgraduate Press, Inc.

Mindfulness-Based Stress Reduction in Post-treatment Breast Cancer Patients: Immediate and Sustained Effects Across Multiple Symptom Clusters.

PubMed

Reich, Richard R; Lengacher, Cecile A; Alinat, Carissa B; Kip, Kevin E; Paterson, Carly; Ramesar, Sophia; Han, Heather S; Ismail-Khan, Roohi; Johnson-Mallard, Versie; Moscoso, Manolete; Budhrani-Shani, Pinky; Shivers, Steve; Cox, Charles E; Goodman, Matthew; Park, Jong

2017-01-01

Breast cancer survivors (BCS) face adverse physical and psychological symptoms, often co-occurring. Biologic and psychological factors may link symptoms within clusters, distinguishable by prevalence and/or severity. Few studies have examined the effects of behavioral interventions or treatment of symptom clusters. The aim of this study was to identify symptom clusters among post-treatment BCS and determine symptom cluster improvement following the Mindfulness-Based Stress Reduction for Breast Cancer (MBSR(BC)) program. Three hundred twenty-two Stage 0-III post-treatment BCS were randomly assigned to either a six-week MBSR(BC) program or usual care. Psychological (depression, anxiety, stress, and fear of recurrence), physical (fatigue, pain, sleep, and drowsiness), and cognitive symptoms and quality of life were assessed at baseline, six, and 12 weeks, along with demographic and clinical history data at baseline. A three-step analytic process included the error-accounting models of factor analysis and structural equation modeling. Four symptom clusters emerged at baseline: pain, psychological, fatigue, and cognitive. From baseline to six weeks, the model demonstrated evidence of MBSR(BC) effectiveness in both the psychological (anxiety, depression, perceived stress and QOL, emotional well-being) (P = 0.007) and fatigue (fatigue, sleep, and drowsiness) (P < 0.001) clusters. Results between six and 12 weeks showed sustained effects, but further improvement was not observed. Our results provide clinical effectiveness evidence that MBSR(BC) works to improve symptom clusters, particularly for psychological and fatigue symptom clusters, with the greatest improvement occurring during the six-week program with sustained effects for several weeks after MBSR(BC) training. Name and URL of Registry: ClinicalTrials.gov. Registration number: NCT01177124. Copyright © 2016. Published by Elsevier Inc.

An Empirically Derived Taxonomy of Factors Affecting Physicians' Willingness to Disclose Medical Errors

PubMed Central

Kaldjian, Lauris C; Jones, Elizabeth W; Rosenthal, Gary E; Tripp-Reimer, Toni; Hillis, Stephen L

2006-01-01

BACKGROUND Physician disclosure of medical errors to institutions, patients, and colleagues is important for patient safety, patient care, and professional education. However, the variables that may facilitate or impede disclosure are diverse and lack conceptual organization. OBJECTIVE To develop an empirically derived, comprehensive taxonomy of factors that affects voluntary disclosure of errors by physicians. DESIGN A mixed-methods study using qualitative data collection (structured literature search and exploratory focus groups), quantitative data transformation (sorting and hierarchical cluster analysis), and validation procedures (confirmatory focus groups and expert review). RESULTS Full-text review of 316 articles identified 91 impeding or facilitating factors affecting physicians' willingness to disclose errors. Exploratory focus groups identified an additional 27 factors. Sorting and hierarchical cluster analysis organized factors into 8 domains. Confirmatory focus groups and expert review relocated 6 factors, removed 2 factors, and modified 4 domain names. The final taxonomy contained 4 domains of facilitating factors (responsibility to patient, responsibility to self, responsibility to profession, responsibility to community), and 4 domains of impeding factors (attitudinal barriers, uncertainties, helplessness, fears and anxieties). CONCLUSIONS A taxonomy of facilitating and impeding factors provides a conceptual framework for a complex field of variables that affects physicians' willingness to disclose errors to institutions, patients, and colleagues. This taxonomy can be used to guide the design of studies to measure the impact of different factors on disclosure, to assist in the design of error-reporting systems, and to inform educational interventions to promote the disclosure of errors to patients. PMID:16918739

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.

Identifying Two Groups of Entitled Individuals: Cluster Analysis Reveals Emotional Stability and Self-Esteem Distinction.

PubMed

Crowe, Michael L; LoPilato, Alexander C; Campbell, W Keith; Miller, Joshua D

2016-12-01

The present study hypothesized that there exist two distinct groups of entitled individuals: grandiose-entitled, and vulnerable-entitled. Self-report scores of entitlement were collected for 916 individuals using an online platform. Model-based cluster analyses were conducted on the individuals with scores one standard deviation above mean (n = 159) using the five-factor model dimensions as clustering variables. The results support the existence of two groups of entitled individuals categorized as emotionally stable and emotionally vulnerable. The emotionally stable cluster reported emotional stability, high self-esteem, more positive affect, and antisocial behavior. The emotionally vulnerable cluster reported low self-esteem and high levels of neuroticism, disinhibition, conventionality, psychopathy, negative affect, childhood abuse, intrusive parenting, and attachment difficulties. Compared to the control group, both clusters reported being more antagonistic, extraverted, Machiavellian, and narcissistic. These results suggest important differences are missed when simply examining the linear relationships between entitlement and various aspects of its nomological network.

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

PubMed

Leech, Rebecca M; McNaughton, Sarah A; Timperio, Anna

2014-01-22

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.

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

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

EPA Pesticide Factsheets

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

Prognostic factors and outcome in anorexia nervosa: a follow-up study.

PubMed

Errichiello, Luca; Iodice, Davide; Bruzzese, Dario; Gherghi, Marco; Senatore, Ignazio

2016-03-01

Anorexia nervosa is an eating disorder characterized by food restriction, irrational fear of gaining weight and consequent weight loss. High mortality rates have been reported, mostly due to suicide and malnutrition. Good outcomes largely vary between 18 and 42%. We aimed to assess outcome and prognostic factors of a large group of patients with anorexia nervosa. Moreover we aimed to identify clusters of prognostic factors related to specific outcomes. We retrospectively reviewed data of 100 patients diagnosed with anorexia nervosa previously hospitalized in a tertiary level structure. Then we performed follow-up structured telephone interviews. We identified four dead patients, while 34% were clinically recovered. In univariate analysis, short duration of inpatient treatment (p = 0.003), short duration of disorder (p = 0.001), early age at first inpatient treatment (p = 0.025) and preserved insight (p = 0.029) were significantly associated with clinical recovery at follow-up. In multiple logistic regression analysis, duration of first inpatient treatment, duration of disorder and preserved insight maintained their association with outcome. Moreover multiple correspondence analysis and cluster analysis allowed to identify different typologies of patients with specific features. Notably, group 1 was characterized by two or more inpatient treatments, BMI ≤ 14, absence of insight, history of long-term inpatient treatments, first inpatient treatment ≥30 days. While group 4 was characterized by preserved insight, BMI ≥ 16, first inpatient treatment ≤14 days, no more than one inpatient treatment, no psychotropic drugs intake, duration of illness ≤4 years. We confirmed the association between short duration of inpatient treatment, short duration of disorder, early age at first inpatient treatment, preserved insight and clinical recovery. We also differentiated patients with anorexia nervosa in well-defined outcome groups according to specific clusters of prognostic factors. Our study might help clinicians to evaluate prognosis of patients with anorexia nervosa.

Density-cluster NMA: A new protein decomposition technique for coarse-grained normal mode analysis.

PubMed

Demerdash, Omar N A; Mitchell, Julie C

2012-07-01

Normal mode analysis has emerged as a useful technique for investigating protein motions on long time scales. This is largely due to the advent of coarse-graining techniques, particularly Hooke's Law-based potentials and the rotational-translational blocking (RTB) method for reducing the size of the force-constant matrix, the Hessian. Here we present a new method for domain decomposition for use in RTB that is based on hierarchical clustering of atomic density gradients, which we call Density-Cluster RTB (DCRTB). The method reduces the number of degrees of freedom by 85-90% compared with the standard blocking approaches. We compared the normal modes from DCRTB against standard RTB using 1-4 residues in sequence in a single block, with good agreement between the two methods. We also show that Density-Cluster RTB and standard RTB perform well in capturing the experimentally determined direction of conformational change. Significantly, we report superior correlation of DCRTB with B-factors compared with 1-4 residue per block RTB. Finally, we show significant reduction in computational cost for Density-Cluster RTB that is nearly 100-fold for many examples. Copyright © 2012 Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

Zhang, Tianzhen; Wang, Xiumei; Gao, Xinbo

2018-04-01

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

Clustering of risk factors and the risk of incident cardiovascular disease in Asian and Caucasian populations: results from the Asia Pacific Cohort Studies Collaboration

PubMed Central

Peters, Sanne A E; Wang, Xin; Lam, Tai-Hing; Kim, Hyeon Chang; Ho, Suzanne; Ninomiya, Toshiharu; Knuiman, Matthew; Vaartjes, Ilonca; Bots, Michael L; Woodward, Mark

2018-01-01

Objective To assess the relationship between risk factor clusters and cardiovascular disease (CVD) incidence in Asian and Caucasian populations and to estimate the burden of CVD attributable to each cluster. Setting Asia Pacific Cohort Studies Collaboration. Participants Individual participant data from 34 population-based cohorts, involving 314 024 participants without a history of CVD at baseline. Outcome measures Clusters were 11 possible combinations of four individual risk factors (current smoking, overweight, blood pressure (BP) and total cholesterol). Cox regression models were used to obtain adjusted HRs and 95% CIs for CVD associated with individual risk factors and risk factor clusters. Population-attributable fractions (PAFs) were calculated. Results During a mean follow-up of 7 years, 6203 CVD events were recorded. The ranking of HRs and PAFs was similar for Australia and New Zealand (ANZ) and Asia; clusters including BP consistently showed the highest HRs and PAFs. The BP–smoking cluster had the highest HR for people with two risk factors: 4.13 (3.56 to 4.80) for Asia and 3.07 (2.23 to 4.23) for ANZ. Corresponding PAFs were 24% and 11%, respectively. For individuals with three risk factors, the BP–smoking–cholesterol cluster had the highest HR (4.67 (3.92 to 5.57) for Asia and 3.49 (2.69 to 4.53) for ANZ). Corresponding PAFs were 13% and 10%. Conclusions Risk factor clusters act similarly on CVD risk in Asian and Caucasian populations. Clusters including elevated BP were associated with the highest excess risk of CVD. PMID:29511013

Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text

PubMed Central

Xin, Yu; Hochberg, Ephraim; Joshi, Rohit; Uzuner, Ozlem; Szolovits, Peter

2015-01-01

Objective Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxes. Moreover, training data for these automated approaches at often sparsely annotated at best. The authors target unsupervised learning for modeling clinical narrative text, aiming at improving both accuracy and interpretability. Methods The authors introduce a novel framework named subgraph augmented non-negative tensor factorization (SANTF). In addition to relying on atomic features (e.g., words in clinical narrative text), SANTF automatically mines higher-order features (e.g., relations of lymphoid cells expressing antigens) from clinical narrative text by converting sentences into a graph representation and identifying important subgraphs. The authors compose a tensor using patients, higher-order features, and atomic features as its respective modes. We then apply non-negative tensor factorization to cluster patients, and simultaneously identify latent groups of higher-order features that link to patient clusters, as in clinical guidelines where a panel of immunophenotypic features and laboratory results are used to specify diagnostic criteria. Results and Conclusion SANTF demonstrated over 10% improvement in averaged F-measure on patient clustering compared to widely used non-negative matrix factorization (NMF) and k-means clustering methods. Multiple baselines were established by modeling patient data using patient-by-features matrices with different feature configurations and then performing NMF or k-means to cluster patients. Feature analysis identified latent groups of higher-order features that lead to medical insights. We also found that the latent groups of atomic features help to better correlate the latent groups of higher-order features. PMID:25862765

Subspace K-means clustering.

PubMed

Timmerman, Marieke E; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla

2013-12-01

To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the existing related clustering methods, including deterministic, stochastic, and unsupervised learning approaches. To evaluate subspace K-means, we performed a comparative simulation study, in which we manipulated the overlap of subspaces, the between-cluster variance, and the error variance. The study shows that the subspace K-means algorithm is sensitive to local minima but that the problem can be reasonably dealt with by using partitions of various cluster procedures as a starting point for the algorithm. Subspace K-means performs very well in recovering the true clustering across all conditions considered and appears to be superior to its competitor methods: K-means, reduced K-means, factorial K-means, mixtures of factor analyzers (MFA), and MCLUST. The best competitor method, MFA, showed a performance similar to that of subspace K-means in easy conditions but deteriorated in more difficult ones. Using data from a study on parental behavior, we show that subspace K-means analysis provides a rich insight into the cluster characteristics, in terms of both the relative positions of the clusters (via the centroids) and the shape of the clusters (via the within-cluster residuals).

Fibrinogen and associated risk factors in a high-risk population: urban Indigenous Australians, the DRUID Study.

PubMed

Maple-Brown, Louise J; Cunningham, Joan; Nandi, Nirjhar; Hodge, Allison; O'Dea, Kerin

2010-10-29

Epidemiological evidence suggests that fibrinogen and CRP are associated with coronary heart disease risk. High CRP in Indigenous Australians has been reported in previous studies including our 'Diabetes and Related diseases in Urban Indigenous population in Darwin region' (DRUID) Study. We studied levels of fibrinogen and its cross-sectional relationship with traditional and non-traditional cardiovascular risk factors in an urban Indigenous Australian cohort. Fibrinogen data were available from 287 males and 628 females (aged ≥ 15 years) from the DRUID study. Analysis was performed for associations with the following risk factors: diabetes, HbA1c, age, BMI, waist circumference, waist-hip ratio, total cholesterol, triglyceride, HDL cholesterol, C-reactive protein, homocysteine, blood pressure, heart rate, urine ACR, smoking status, alcohol abstinence. Fibrinogen generally increased with age in both genders; levels by age group were higher than those previously reported in other populations, including Native Americans. Fibrinogen was higher in those with than without diabetes (4.24 vs 3.56 g/L, p < 0.001). After adjusting for age and sex, the following were significantly associated with fibrinogen: BMI, waist, waist-hip ratio, systolic blood pressure, heart rate, fasting triglycerides, HDL cholesterol, HbA1c, CRP, ACR and alcohol abstinence. On multivariate regression (age and sex-adjusted) CRP and HbA1c were significant independent predictors of fibrinogen, explaining 27% of its variance; CRP alone explained 25% of fibrinogen variance. On factor analysis, both CRP and fibrinogen clustered with obesity in women (this factor explained 20% of variance); but in men, CRP clustered with obesity (factor explained 18% of variance) whilst fibrinogen clustered with HbA1c and urine ACR (factor explained 13% of variance). Fibrinogen is associated with traditional and non-traditional cardiovascular risk factors in this urban Indigenous cohort and may be a useful biomarker of CVD in this high-risk population. The apparent different associations of fibrinogen with cardiovascular disease risk markers in men and women should be explored further.

Geographic clustering of elevated blood heavy metal levels in pregnant women.

PubMed

King, Katherine E; Darrah, Thomas H; Money, Eric; Meentemeyer, Ross; Maguire, Rachel L; Nye, Monica D; Michener, Lloyd; Murtha, Amy P; Jirtle, Randy; Murphy, Susan K; Mendez, Michelle A; Robarge, Wayne; Vengosh, Avner; Hoyo, Cathrine

2015-10-09

Cadmium (Cd), lead (Pb), mercury (Hg), and arsenic (As) exposure is ubiquitous and has been associated with higher risk of growth restriction and cardiometabolic and neurodevelopmental disorders. However, cost-efficient strategies to identify at-risk populations and potential sources of exposure to inform mitigation efforts are limited. The objective of this study was to describe the spatial distribution and identify factors associated with Cd, Pb, Hg, and As concentrations in peripheral blood of pregnant women. Heavy metals were measured in whole peripheral blood of 310 pregnant women obtained at gestational age ~12 weeks. Prenatal residential addresses were geocoded and geospatial analysis (Getis-Ord Gi* statistics) was used to determine if elevated blood concentrations were geographically clustered. Logistic regression models were used to identify factors associated with elevated blood metal levels and cluster membership. Geospatial clusters for Cd and Pb were identified with high confidence (p-value for Gi* statistic <0.01). The Cd and Pb clusters comprised 10.5 and 9.2 % of Durham County residents, respectively. Medians and interquartile ranges of blood concentrations (μg/dL) for all participants were Cd 0.02 (0.01-0.04), Hg 0.03 (0.01-0.07), Pb 0.34 (0.16-0.83), and As 0.04 (0.04-0.05). In the Cd cluster, medians and interquartile ranges of blood concentrations (μg/dL) were Cd 0.06 (0.02-0.16), Hg 0.02 (0.00-0.05), Pb 0.54 (0.23-1.23), and As 0.05 (0.04-0.05). In the Pb cluster, medians and interquartile ranges of blood concentrations (μg/dL) were Cd 0.03 (0.02-0.15), Hg 0.01 (0.01-0.05), Pb 0.39 (0.24-0.74), and As 0.04 (0.04-0.05). Co-exposure with Pb and Cd was also clustered, the p-values for the Gi* statistic for Pb and Cd was <0.01. Cluster membership was associated with lower education levels and higher pre-pregnancy BMI. Our data support that elevated blood concentrations of Cd and Pb are spatially clustered in this urban environment compared to the surrounding areas. Spatial analysis of metals concentrations in peripheral blood or urine obtained routinely during prenatal care can be useful in surveillance of heavy metal exposure.

Optimization of the Ion Source-Mass Spectrometry Parameters in Non-Steroidal Anti-Inflammatory and Analgesic Pharmaceuticals Analysis by a Design of Experiments Approach.

PubMed

Paíga, Paula; Silva, Luís M S; Delerue-Matos, Cristina

2016-10-01

The flow rates of drying and nebulizing gas, heat block and desolvation line temperatures and interface voltage are potential electrospray ionization parameters as they may enhance sensitivity of the mass spectrometer. The conditions that give higher sensitivity of 13 pharmaceuticals were explored. First, Plackett-Burman design was implemented to screen significant factors, and it was concluded that interface voltage and nebulizing gas flow were the only factors that influence the intensity signal for all pharmaceuticals. This fractionated factorial design was projected to set a full 2(2) factorial design with center points. The lack-of-fit test proved to be significant. Then, a central composite face-centered design was conducted. Finally, a stepwise multiple linear regression and subsequently an optimization problem solving were carried out. Two main drug clusters were found concerning the signal intensities of all runs of the augmented factorial design. p-Aminophenol, salicylic acid, and nimesulide constitute one cluster as a result of showing much higher sensitivity than the remaining drugs. The other cluster is more homogeneous with some sub-clusters comprising one pharmaceutical and its respective metabolite. It was observed that instrumental signal increased when both significant factors increased with maximum signal occurring when both codified factors are set at level +1. It was also found that, for most of the pharmaceuticals, interface voltage influences the intensity of the instrument more than the nebulizing gas flowrate. The only exceptions refer to nimesulide where the relative importance of the factors is reversed and still salicylic acid where both factors equally influence the instrumental signal. Graphical Abstract ᅟ.

Integrative analysis of signaling pathways and diseases associated with the miR-106b/25 cluster and their function study in berberine-induced multiple myeloma cells.

PubMed

Gu, Chunming; Li, Tianfu; Yin, Zhao; Chen, Shengting; Fei, Jia; Shen, Jianping; Zhang, Yuan

2017-05-01

Berberine (BBR), a traditional Chinese herbal medicine compound, has emerged as a novel class of anti-tumor agent. Our previous microRNA (miRNA) microarray demonstrated that miR-106b/25 was significantly down-regulated in BBR-treated multiple myeloma (MM) cells. Here, systematic integration showed that miR-106b/25 cluster is involved in multiple cancer-related signaling pathways and tumorigenesis. MiREnvironment database revealed that multiple environmental factors (drug, ionizing radiation, hypoxia) affected the miR-106b/25 cluster expression. By targeting the seed region in the miRNA, tiny anti-mir106b/25 cluster (t-anti-mir106b/25 cluster) significantly induced suppression in cell viability and colony formation. Western blot validated that t-anti-miR-106b/25 cluster effectively inhibited the expression of P38 MAPK and phospho-P38 MAPK in MM cells. These findings indicated the miR-106b/25 cluster functioned as oncogene and might provide a novel molecular insight into MM.

Radio emission in the directions of cD and related galaxies in poor clusters. III. VLA observations at 20 cm

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

Burns, J.O.; White, R.A.; Hough, D.H.

1981-01-01

VLA radio maps and optical identifications of a sample of sources in the directions of 21 Yerkes poor cluster fields are presented. The majority of the cluster radio sources are associated with the dominant D or cD galaxies (approx.70%). Our analysis of dominant galaxies in rich and poor clusters indicates that these giant galaxies are much more often radio emitters (approx.25% of cD's are radio active in the poor clusters), have steeper radio spectra, and have simpler radio morphologies (i.e., double or other linear structure) than other less bright ellipticals. A strong continuum of radio properties in cD galaxies ismore » seen from rich to poor clusters. We speculate that the location of these dominant galaxies at the cluster centers (i.e., at the bottom of a deep, isolated gravitational potential well) is the crucial factor in explaining their multifrequency activity. We briefly discuss galaxy cannibalism and gas infall models as fueling mechanisms for the observed radio and x-ray emission.« less

Radio emission in the directions of cD and related galaxies in poor clusters. III - VLA observations at 20 cm

NASA Technical Reports Server (NTRS)

Burns, J. O.; White, R. A.; Hough, D. H.

1981-01-01

VLA radio maps and optical identifications of a sample of sources in the directions of 21 Yerkes poor cluster fields are presented. The majority of the cluster radio sources are associated with the dominant D or cD galaxies (approximately 70 percent). Our analysis of dominant galaxies in rich and poor clusters indicates that these giant galaxies are much more often radio emitters (approximately 25 percent of cD's are radio active in the poor clusters), have steeper radio spectra, and have simpler radio morphologies (i.e., double or other linear structure) than other less bright ellipticals. A strong continuum of radio properties in cD galaxies is seen from rich to poor clusters. It is speculated that the location of these dominant galaxies at the cluster centers (i.e., at the bottom of a deep, isolated gravitational potential well) is the crucial factor in explaining their multifrequency activity. Galaxy cannibalism and gas infall models as fueling mechanisms for the observed radio and X-ray emission are discussed

Is the non-isothermal double β-model incompatible with no time evolution of galaxy cluster gas mass fraction?

NASA Astrophysics Data System (ADS)

Holanda, R. F. L.

2018-05-01

In this paper, we propose a new method to obtain the depletion factor γ(z), the ratio by which the measured baryon fraction in galaxy clusters is depleted with respect to the universal mean. We use exclusively galaxy cluster data, namely, X-ray gas mass fraction (fgas) and angular diameter distance measurements from Sunyaev-Zel'dovich effect plus X-ray observations. The galaxy clusters are the same in both data set and the non-isothermal spherical double β-model was used to describe their electron density and temperature profiles. In order to compare our results with those from recent cosmological hydrodynamical simulations, we suppose a possible time evolution for γ(z), such as, γ(z) =γ0(1 +γ1 z) . As main conclusions we found that: the γ0 value is in full agreement with the simulations. On the other hand, although the γ1 value found in our analysis is compatible with γ1 = 0 within 2σ c.l., our results show a non-negligible time evolution for the depletion factor, unlike the results of the simulations. However, we also put constraints on γ(z) by using the fgas measurements and angular diameter distances obtained from the flat ΛCDM model (Planck results) and from a sample of galaxy clusters described by an elliptical profile. For these cases no significant time evolution for γ(z) was found. Then, if a constant depletion factor is an inherent characteristic of these structures, our results show that the spherical double β-model used to describe the galaxy clusters considered does not affect the quality of their fgas measurements.

Mapping the Dark Matter Distribution of the Merging Galaxy Cluster Abell 115

NASA Astrophysics Data System (ADS)

Kim, Mincheol; Jee, Myungkook James; Forman, William; Golovich, Nathan; van Weeren, Reinout

2018-01-01

The colliding galaxy cluster Abell 115 shows a number of clear merging features including radio relics, double X-ray peaks, and offsets between the cluster member galaxies and the X-ray distributions. In order to constrain the merging scenario of this complex system, it is critical to know where the dark matter is. We present a high-fidelity weak-lensing analysis of the system using a state-of-the-art method that robustly models the detailed PSF variations. Our mass reconstruction reveals two distinct mass peaks. Through a careful bootstrapping analysis, we demonstrate that the positions of these two mass peaks are highly consistent with those of the cluster galaxies, although the comparison with the X-ray emission shows that the mass peaks lead the X-ray peaks. We obtain the first weak-lensing mass of each subcluster by simultaneously fitting two NFW profiles, as well as the total mass of the system. Interestingly, the total mass is a few factors lower than the published dynamical mass based on velocity dispersion. This large mass discrepancy may be attributed to a significant disruption of the cluster galaxy orbits due to the violent merger. Our preliminary analysis indicates that the two subclusters might have experienced a first off-axis collision a few Gyrs ago and might be now returning for a second collision.

Proposed shade guide for human facial skin and lip: a pilot study.

PubMed

Wee, Alvin G; Beatty, Mark W; Gozalo-Diaz, David J; Kim-Pusateri, Seungyee; Marx, David B

2013-08-01

Currently, no commercially available facial shade guide exists in the United States for the fabrication of facial prostheses. The purpose of this study was to measure facial skin and lip color in a human population sample stratified by age, gender, and race. Clustering analysis was used to determine optimal color coordinates for a proposed facial shade guide. Participants (n=119) were recruited from 4 racial/ethnic groups, 5 age groups, and both genders. Reflectance measurements of participants' noses and lower lips were made by using a spectroradiometer and xenon arc lamp with a 45/0 optical configuration. Repeated measures ANOVA (α=.05), to identify skin and lip color differences, resulting from race, age, gender, and location, and a hierarchical clustering analysis, to identify clusters of skin colors) were used. Significant contributors to L*a*b* facial color were race and facial location (P<.01). b* affected all factors (P<.05). Age affected only b* (P<.001), while gender affected only L* (P<.05) and b* (P<.05). Analyses identified 5 clusters of skin color. The study showed that skin color caused by age and gender primarily occurred within the yellow-blue axis. A significant lightness difference between gender groups was also found. Clustering analysis identified 5 distinct skin shade tabs. Copyright © 2013 The Editorial Council of the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

Phenotypes of comorbidity in OSAS patients: combining categorical principal component analysis with cluster analysis.

PubMed

Vavougios, George D; George D, George; Pastaka, Chaido; Zarogiannis, Sotirios G; Gourgoulianis, Konstantinos I

2016-02-01

Phenotyping obstructive sleep apnea syndrome's comorbidity has been attempted for the first time only recently. The aim of our study was to determine phenotypes of comorbidity in obstructive sleep apnea syndrome patients employing a data-driven approach. Data from 1472 consecutive patient records were recovered from our hospital's database. Categorical principal component analysis and two-step clustering were employed to detect distinct clusters in the data. Univariate comparisons between clusters included one-way analysis of variance with Bonferroni correction and chi-square tests. Predictors of pairwise cluster membership were determined via a binary logistic regression model. The analyses revealed six distinct clusters: A, 'healthy, reporting sleeping related symptoms'; B, 'mild obstructive sleep apnea syndrome without significant comorbidities'; C1: 'moderate obstructive sleep apnea syndrome, obesity, without significant comorbidities'; C2: 'moderate obstructive sleep apnea syndrome with severe comorbidity, obesity and the exclusive inclusion of stroke'; D1: 'severe obstructive sleep apnea syndrome and obesity without comorbidity and a 33.8% prevalence of hypertension'; and D2: 'severe obstructive sleep apnea syndrome with severe comorbidities, along with the highest Epworth Sleepiness Scale score and highest body mass index'. Clusters differed significantly in apnea-hypopnea index, oxygen desaturation index; arousal index; age, body mass index, minimum oxygen saturation and daytime oxygen saturation (one-way analysis of variance P < 0.0001). Binary logistic regression indicated that older age, greater body mass index, lower daytime oxygen saturation and hypertension were associated independently with an increased risk of belonging in a comorbid cluster. Six distinct phenotypes of obstructive sleep apnea syndrome and its comorbidities were identified. Mapping the heterogeneity of the obstructive sleep apnea syndrome may help the early identification of at-risk groups. Finally, determining predictors of comorbidity for the moderate and severe strata of these phenotypes implies a need to take these factors into account when considering obstructive sleep apnea syndrome treatment options. © 2015 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.

Radiomics of CT Features May Be Nonreproducible and Redundant: Influence of CT Acquisition Parameters.

PubMed

Berenguer, Roberto; Pastor-Juan, María Del Rosario; Canales-Vázquez, Jesús; Castro-García, Miguel; Villas, María Victoria; Legorburo, Francisco Mansilla; Sabater, Sebastià

2018-04-24

Purpose To identify the reproducible and nonredundant radiomics features (RFs) for computed tomography (CT). Materials and Methods Two phantoms were used to test RF reproducibility by using test-retest analysis, by changing the CT acquisition parameters (hereafter, intra-CT analysis), and by comparing five different scanners with the same CT parameters (hereafter, inter-CT analysis). Reproducible RFs were selected by using the concordance correlation coefficient (as a measure of the agreement between variables) and the coefficient of variation (defined as the ratio of the standard deviation to the mean). Redundant features were grouped by using hierarchical cluster analysis. Results A total of 177 RFs including intensity, shape, and texture features were evaluated. The test-retest analysis showed that 91% (161 of 177) of the RFs were reproducible according to concordance correlation coefficient. Reproducibility of intra-CT RFs, based on coefficient of variation, ranged from 89.3% (151 of 177) to 43.1% (76 of 177) where the pitch factor and the reconstruction kernel were modified, respectively. Reproducibility of inter-CT RFs, based on coefficient of variation, also showed large material differences, from 85.3% (151 of 177; wood) to only 15.8% (28 of 177; polyurethane). Ten clusters were identified after the hierarchical cluster analysis and one RF per cluster was chosen as representative. Conclusion Many RFs were redundant and nonreproducible. If all the CT parameters are fixed except field of view, tube voltage, and milliamperage, then the information provided by the analyzed RFs can be summarized in only 10 RFs (each representing a cluster) because of redundancy. © RSNA, 2018 Online supplemental material is available for this article.

Spatio-Temporal Trends and Risk Factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China

PubMed Central

Bao, Changjun; Hu, Jianli; Liu, Wendong; Liang, Qi; Wu, Ying; Norris, Jessie; Peng, Zhihang; Yu, Rongbin; Shen, Hongbing; Chen, Feng

2014-01-01

Objective This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission. Methods County-level incidence rates were obtained for analysis using geographic information system (GIS) tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA) model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions. Results The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR = 11674.74, P<0.001). The time series model was established as ARIMA (1, 12, 0), which predicted well for cases from August to December, 2011. Highways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR = 3.64) and not having access to a safe water source (OR = 2.04) as the main causes of Shigella in Jiangsu Province. Conclusion Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time. PMID:24416167

Research on the method of information system risk state estimation based on clustering particle filter

NASA Astrophysics Data System (ADS)

Cui, Jia; Hong, Bei; Jiang, Xuepeng; Chen, Qinghua

2017-05-01

With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

Low-income women's reproductive weight patterns empirically based clusters of prepregnant, gestational, and postpartum weights.

PubMed

Walker, Lorraine O

2009-01-01

Women have varying weight responses to pregnancy and the postpartum period. The purpose of this study was to derive sub-groups of women based on differing reproductive weight clusters; to validate clusters by reference to adequacy of gestational weight gain (GWG) and postpartum incremental weight shifts; and to examine associations between clusters and demographic, behavioral, and psychosocial variables. A cluster analysis was conducted of a multi-ethnic/racial sample of low-income women (n = 247). Clusters were derived from three weight variables: prepregnant body mass index, GWG, and postpartum retained weight. Five clusters were derived: Cluster 1, normal weight-high prenatal gain-average retain; cluster 2, normal weight-low prenatal gain-zero retain; cluster 3, high normal weight-high prenatal gain-high retain; cluster 4, obese-low prenatal gain-average retain; and cluster 5, overweight-very high prenatal gain-very high retain. Clusters differed with regard to postpartum weight shifts (p < .001), with clusters 3, 4, and 5, mostly gaining weight between 6 weeks and 12 months postpartum, whereas clusters 1 and 2 were losing weight. Clusters were also associated with race/ethnicity (p < .01), breastfeeding immediately postdelivery (p < .01), smoking at 12 months (p < .05), and reaching weight goals at 6 and 12 months (p < .001), but not depressive symptoms, fat intake habits, or physical activity. In a five-cluster solution, postpartum weight shifts, ethnicity, and initial breastfeeding were among factors associated with clusters. Monitoring of weight and appropriate intervention beyond the 6 weeks after birth is needed for low-income women in high normal weight, overweight, and obese clusters.

Myeloid Clusters Are Associated with a Pro-Metastatic Environment and Poor Prognosis in Smoking-Related Early Stage Non-Small Cell Lung Cancer

PubMed Central

Zhang, Wang; Pal, Sumanta K.; Liu, Xueli; Yang, Chunmei; Allahabadi, Sachin; Bhanji, Shaira; Figlin, Robert A.; Yu, Hua; Reckamp, Karen L.

2013-01-01

Background This study aimed to understand the role of myeloid cell clusters in uninvolved regional lymph nodes from early stage non-small cell lung cancer patients. Methods Uninvolved regional lymph node sections from 67 patients with stage I–III resected non-small cell lung cancer were immunostained to detect myeloid clusters, STAT3 activity and occult metastasis. Anthracosis intensity, myeloid cluster infiltration associated with anthracosis and pSTAT3 level were scored and correlated with patient survival. Multivariate Cox regression analysis was performed with prognostic variables. Human macrophages were used for in vitro nicotine treatment. Results CD68+ myeloid clusters associated with anthracosis and with an immunosuppressive and metastasis-promoting phenotype and elevated overall STAT3 activity were observed in uninvolved lymph nodes. In patients with a smoking history, myeloid cluster score significantly correlated with anthracosis intensity and pSTAT3 level (P<0.01). Nicotine activated STAT3 in macrophages in long-term culture. CD68+ myeloid clusters correlated and colocalized with occult metastasis. Myeloid cluster score was an independent prognostic factor (P = 0.049) and was associated with survival by Kaplan-Maier estimate in patients with a history of smoking (P = 0.055). The combination of myeloid cluster score with either lymph node stage or pSTAT3 level defined two populations with a significant difference in survival (P = 0.024 and P = 0.004, respectively). Conclusions Myeloid clusters facilitate a pro-metastatic microenvironment in uninvolved regional lymph nodes and associate with occult metastasis in early stage non-small cell lung cancer. Myeloid cluster score is an independent prognostic factor for survival in patients with a history of smoking, and may present a novel method to inform therapy choices in the adjuvant setting. Further validation studies are warranted. PMID:23717691

Effects of cluster location and cluster distribution on performance on the traveling salesman problem.

PubMed

MacGregor, James N

2015-10-01

Research on human performance in solving traveling salesman problems typically uses point sets as stimuli, and most models have proposed a processing stage at which stimulus dots are clustered. However, few empirical studies have investigated the effects of clustering on performance. In one recent study, researchers compared the effects of clustered, random, and regular stimuli, and concluded that clustering facilitates performance (Dry, Preiss, & Wagemans, 2012). Another study suggested that these results may have been influenced by the location rather than the degree of clustering (MacGregor, 2013). Two experiments are reported that mark an attempt to disentangle these factors. The first experiment tested several combinations of degree of clustering and cluster location, and revealed mixed evidence that clustering influences performance. In a second experiment, both factors were varied independently, showing that they interact. The results are discussed in terms of the importance of clustering effects, in particular, and perceptual factors, in general, during performance of the traveling salesman problem.

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.

Factor Analysis of Key Success Indicators in Curriculum Quality Assurance Operation for Bachelor's Degree in Physical Education

ERIC Educational Resources Information Center

Sukdee, Thitipong; Tornee, Songpol; Kraipetch, Chanita

2017-01-01

The purpose of this study was to analyze the factors of key success indicators in curriculum quality assurance operation for bachelor's degree in Physical Education. The 576 subjects were selected using cluster sampling from curriculum lecturers, staffs, and lecturers at the Academy of Physical Education Curriculum. The instrument was a related…

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

PubMed

Troche, Joshua; Crutch, Sebastian; Reilly, Jamie

2014-01-01

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

Genetic Analysis of Fibroblast Growth Factor Signaling in the Drosophila Eye

PubMed Central

Mukherjee, T.; Choi, I.; Banerjee, Utpal

2012-01-01

The development of eyes in Drosophila involves intricate epithelial reorganization events for accurate positioning of cells and proper formation and organization of ommatidial clusters. We demonstrate that Branchless (Bnl), the fibroblast growth factor ligand, regulates restructuring events in the eye disc primordium from as early as the emergence of clusters from a morphogenetic front to the cellular movements during pupal eye development. Breathless (Btl) functions as the fibroblast growth factor receptor to mediate Bnl signal, and together they regulate expression of DE-cadherin, Crumbs, and Actin. In addition, in the eye Bnl regulates the temporal onset and extent of retinal basal glial cell migration by activating Btl in the glia. We hypothesized that the Bnl functions in the eye are Hedgehog dependent and represent novel aspects of Bnl signaling not explored previously. PMID:22384378

Neuropsychiatric symptom clusters and functional disability in cognitively-impaired-not-demented individuals.

PubMed

Peters, Kevin R; Rockwood, Kenneth; Black, Sandra E; Hogan, David B; Gauthier, Serge G; Loy-English, Inge; Hsiung, Ging-Yuek R; Jacova, Claudia; Kertesz, Andrew; Feldman, Howard H

2008-02-01

Previous research has shown that cognitively-impaired-not-demented (CIND) individuals with at least one neuropsychiatric symptom (NPS) have more functional disability than individuals without any NPSs. The objectives of the present study were to determine whether there are consistent clusters of NPS in CIND individuals and whether certain NPS clusters are more strongly associated with measures of functional disability than other NPS clusters in this population. This was a cross-sectional baseline study of NPS using the Neuropsychiatric Inventory (NPI) in a national clinic-based observational cohort study (the Canadian Cohort Study of Cognitive Impairment and Related Dementias study). The present investigation focuses on a subset of CIND subjects (73%) whose informant endorsed the presence of at least one NPI item. A hierarchical cluster analysis identified two NPS clusters. One consisted of mood factors (i.e., depression, anxiety, apathy, irritability, and problems with sleep) and the other cluster captured frontal symptoms (i.e., aberrant motor behavior, disinhibition, agitation, and problems with appetite). NPSs grouped within the mood cluster were more common than the frontal cluster (95% of subjects had at least one NPS within the mood cluster versus 53% in the frontal cluster). However, the frontal cluster was more strongly associated with functional disability measures even after controlling for cognitive status (i.e., the Mini-Mental State Exam) and the mood cluster score. The frontal cluster of NPSs was more strongly associated with functional disability than the mood cluster.

Analysis of soluble factors in conditioned media derived from primary cultures of cirrhotic liver of biliary atresia.

PubMed

Yamazaki, Taisuke; Wakai, Mariko; Enosawa, Shin; Tokiwa, Takayoshi

2017-06-01

Biliary atresia (BA) is a rare and serious liver disease in newborn infants. Previously, we reported that non-parenchymal cell (NPC) fractions from cirrhotic liver of BA may contain hepatic stem/progenitor cells in primary culture of NPC fractions. In this study, NPC fractions were subjected to primary or passage culture and found that clusters of hepatocyte-like cells appear even without adding hepatocyte growth factor (HGF) to the culture medium, but not in their passage culture used as a control. Based on these findings, conditioned media (CMs) were collected and soluble factors in the CMs were analyzed in order to elucidate the mechanism of the appearance of hepatocyte-like cells or their clusters. A large amount of active HGF consisting of α and β chains was detected in CMs derived from primary culture, but not in CMs from passage culture, as determined by western blot analysis, bone morphogenetic protein (BMP)-4, oncostatin M (OSM), and transforming growth factor (TGF)-β1 were not detected in any of the CMs. The number of hepatocyte-like cells in primary culture tended to decrease following treatment with the HGF receptor c-Met inhibitor, SU11274 in a dose-dependent manner. Furthermore, the clusters of hepatocyte-like cells tended to increase in size and number when freshly isolated NPC fractions were cultured in the presence of 10% of CMs collected after 3-4 wk of primary culture. In conclusion, these findings indicate that CMs derived from primary culture of NPC fractions of BA liver contain a large amount of active HGF, which may activate hepatic stem/progenitor cells and promote the appearance of hepatocyte-like cells or their clusters through HGF/c-Met signaling. The present study would lead to cell therapy using the patient's own cells for the treatment of BA.

Assessing PTSD in the military: Validation of a scale distributed to Danish soldiers after deployment since 1998.

PubMed

Karstoft, Karen-Inge; Andersen, Søren B; Nielsen, Anni B S

2017-06-01

Since 1998, soldiers deployed to war zones with the Danish Defense (≈31,000) have been invited to fill out a questionnaire on post-mission reactions. This provides a unique data source for studying the psychological toll of war. Here, we validate a measure of PTSD-symptoms from the questionnaire. Soldiers from two cohorts deployed to Afghanistan with the International Security Assistance Force (ISAF) in 2009 (ISAF7, N = 334) and 2013 (ISAF15, N = 278) filled out a standard questionnaire (Psychological Reactions following International Missions, PRIM) concerning a range of post-deployment reactions including symptoms of PTSD (PRIM-PTSD). They also filled out a validated measure of PTSD-symptoms in DSM-IV, the PTSD-checklist (PCL). We tested reliability of PRIM-PTSD by estimating Cronbach's alpha, and tested validity by correlating items, clusters, and overall scale with corresponding items in the PCL. Furthermore, we conducted two confirmatory factor analytic models to test the factor structure of PRIM-PTSD, and tested measurement invariance of the selected model. Finally, we established a screening and a clinical cutoff score by application of ROC analysis. We found high internal consistency of the PRIM-PTSD (Cronbach's alpha = 0.88; both cohorts), strong item-item (0.48-0.83), item-cluster (0.43-0.72), cluster-cluster (0.71-0.82) and full-scale (0.86-0.88) correlations between PRIM-PTSD and PCL. The factor analyses showed adequate fit of a one-factor model, which was also found to display strong measurement invariance across cohorts. ROC curve analysis established cutoff scores for screening (sensitivity = 1, specificity = 0.93) and clinical use (sensitivity = 0.71, specificity = 0.98). In conclusion, we find that PRIM-PTSD is a valid measure for assessing PTSD-symptoms in Danish soldiers following deployment. © 2017 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Endohedral gallide cluster superconductors and superconductivity in ReGa5.

PubMed

Xie, Weiwei; Luo, Huixia; Phelan, Brendan F; Klimczuk, Tomasz; Cevallos, Francois Alexandre; Cava, Robert Joseph

2015-12-22

We present transition metal-embedded (T@Gan) endohedral Ga-clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2Ga9 are all previously known superconductors. The well-known exotic superconductor PuCoGa5 and related phases are also members of this endohedral gallide cluster family. We show that electron-deficient compounds like Mo8Ga41 prefer architectures with vertex-sharing gallium clusters, whereas electron-rich compounds, like PdGa5, prefer edge-sharing cluster architectures. The superconducting transition temperatures are highest for the electron-poor, corner-sharing architectures. Based on this analysis, the previously unknown endohedral cluster compound ReGa5 is postulated to exist at an intermediate electron count and a mix of corner sharing and edge sharing cluster architectures. The empirical prediction is shown to be correct and leads to the discovery of superconductivity in ReGa5. The Fermi levels for endohedral gallide cluster compounds are located in deep pseudogaps in the electronic densities of states, an important factor in determining their chemical stability, while at the same time limiting their superconducting transition temperatures.

Hierarchical and Complex System Entropy Clustering Analysis Based Validation for Traditional Chinese Medicine Syndrome Patterns of Chronic Atrophic Gastritis.

PubMed

Zhang, Yin; Liu, Yue; Li, Yannan; Zhao, Xia; Zhuo, Lin; Zhou, Ajian; Zhang, Li; Su, Zeqi; Chen, Cen; Du, Shiyu; Liu, Daming; Ding, Xia

2018-03-22

Chronic atrophic gastritis (CAG) is the precancerous stage of gastric carcinoma. Traditional Chinese Medicine (TCM) has been widely used in treating CAG. This study aimed to reveal core pathogenesis of CAG by validating the TCM syndrome patterns and provide evidence for optimization of treatment strategies. This is a cross-sectional study conducted in 4 hospitals in China. Hierarchical clustering analysis (HCA) and complex system entropy clustering analysis (CSECA) were performed, respectively, to achieve syndrome pattern validation. Based on HCA, 15 common factors were assigned to 6 syndrome patterns: liver depression and spleen deficiency and blood stasis in the stomach collateral, internal harassment of phlegm-heat and blood stasis in the stomach collateral, phlegm-turbidity internal obstruction, spleen yang deficiency, internal harassment of phlegm-heat and spleen deficiency, and spleen qi deficiency. By CSECA, 22 common factors were assigned to 7 syndrome patterns: qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency. Combination of qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency may play a crucial role in CAG pathogenesis. In accord with this, treatment strategies by TCM herbal prescriptions should be targeted to regulating qi, activating blood, resolving turbidity, clearing heat, removing toxin, nourishing yin, and warming yang. Further explorations are needed to verify and expand the current conclusions.

Users' perception as a tool to improve urban beach planning and management.

PubMed

Cervantes, Omar; Espejel, Ileana; Arellano, Evarista; Delhumeau, Sheila

2008-08-01

Four beaches that share physiographic characteristics (sandy, wide, and long) but differ in socioeconomic and cultural terms (three are located in northwestern Mexico and one in California, USA) were evaluated by beach users. Surveys (565) composed of 36 questions were handed out to beach users on weekends and holidays in 2005. The 25 questions that revealed the most information were selected by factor analysis and classified by cluster analysis. Beach users' preferences were assigned a value by comparing the present survey results with the characteristics of an "ideal" recreational urban beach. Cluster analysis separated three groups of questions: (a) services and infrastructure, (b) recreational activities, and (c) beach conditions. Cluster linkage distance (r=0.82, r=0.78, r=0.67) was used as a weight and multiplied by the value of beach descriptive factors. Mazatlán and Oceanside obtained the highest values because there are enough infrastructure and services; on the contrary, Ensenada and Rosarito were rated medium and low because infrastructure and services are lacking. The presently proposed method can contribute to improving current beach evaluations because the final score represents the beach users' evaluation of the quality of the beach. The weight considered in the present study marks the beach users' preferences among the studied beaches. Adding this weight to beach evaluation will contribute to more specific beach planning in which users' perception is considered.

Users' Perception as a Tool to Improve Urban Beach Planning and Management

NASA Astrophysics Data System (ADS)

Cervantes, Omar; Espejel, Ileana; Arellano, Evarista; Delhumeau, Sheila

2008-08-01

Four beaches that share physiographic characteristics (sandy, wide, and long) but differ in socioeconomic and cultural terms (three are located in northwestern Mexico and one in California, USA) were evaluated by beach users. Surveys (565) composed of 36 questions were handed out to beach users on weekends and holidays in 2005. The 25 questions that revealed the most information were selected by factor analysis and classified by cluster analysis. Beach users’ preferences were assigned a value by comparing the present survey results with the characteristics of an “ideal” recreational urban beach. Cluster analysis separated three groups of questions: (a) services and infrastructure, (b) recreational activities, and (c) beach conditions. Cluster linkage distance ( r = 0.82, r = 0.78, r = 0.67) was used as a weight and multiplied by the value of beach descriptive factors. Mazatlán and Oceanside obtained the highest values because there are enough infrastructure and services; on the contrary, Ensenada and Rosarito were rated medium and low because infrastructure and services are lacking. The presently proposed method can contribute to improving current beach evaluations because the final score represents the beach users’ evaluation of the quality of the beach. The weight considered in the present study marks the beach users’ preferences among the studied beaches. Adding this weight to beach evaluation will contribute to more specific beach planning in which users’ perception is considered.

An empirical evaluation of the structure of DSM-IV personality disorders in a nationally representative sample: results of confirmatory factor analysis in the National Epidemiologic Survey on Alcohol and Related Conditions Waves 1 and 2.

PubMed

Cox, Brian J; Clara, Ian P; Worobec, Lydia M; Grant, Bridget F

2012-12-01

Individual personality disorders (PD) are grouped into three clusters in the DSM-IV (A, B, and C). There is very little empirical evidence available concerning the validity of this model in the general population. The current study included all 10 of the DSM-IV PD assessed in Wave 1 and Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Confirmatory factor analysis was used to evaluate three plausible models of the structure of Axis II personality disorders (the current hierarchical DSM-IV three-factor model in which individual PD are believed to load on their assigned clusters, which in turn load onto a single Axis II factor; a general single-factor model; and three independent factors). Each of these models was tested in both the total and also separately for gender. The higher order DSM-IV model demonstrated good fit to the data on a number of goodness-of-fit indices. The results for this model were very similar across genders. A model of PD based on the current DSM-IV hierarchical conceptualization of a higher order classification scheme received strong empirical support through confirmatory factor analysis using a number of goodness-of-fit indices in a nationally representative sample. Other models involving broad, higher order personality domains such as neuroticism in relation to personality disorders have yet to be tested in epidemiologic surveys and represent an important avenue for future research.

Food Purchase Decision-Making Typologies of Women with Non-Insulin-Dependent Diabetes Mellitus.

ERIC Educational Resources Information Center

Miller, Carla; Warland, Rex; Achterberg, Cheryl

1997-01-01

Food selection is a key factor in the nutritional management of diabetes. Criteria that influence point-of-purchase decision making in women with non-insulin-dependent diabetes mellitus were identified. Four types of shoppers were distinguished from interviews; cluster analysis was used to confirm the analysis. Usefulness in patient education is…

Market segmentation and analysis of Japan's residential post and beam construction market.

Treesearch

Joseph A. Roos; Ivan L. Eastin; Hisaaki Matsuguma

2005-01-01

A mail survey of Japanese post and beam builders was conducted to measure their level of ethnocentrism, market orientation, risk aversion, and price consciousness. The data were analyzed utilizing factor and cluster analysis. The results showed that Japanese post and beam builders can be divided into three distinct market segments: open to import...

The human RHOX gene cluster: target genes and functional analysis of gene variants in infertile men.

PubMed

Borgmann, Jennifer; Tüttelmann, Frank; Dworniczak, Bernd; Röpke, Albrecht; Song, Hye-Won; Kliesch, Sabine; Wilkinson, Miles F; Laurentino, Sandra; Gromoll, Jörg

2016-11-15

The X-linked reproductive homeobox (RHOX) gene cluster encodes transcription factors preferentially expressed in reproductive tissues. This gene cluster has important roles in male fertility based on phenotypic defects of Rhox-mutant mice and the finding that aberrant RHOX promoter methylation is strongly associated with abnormal human sperm parameters. However, little is known about the molecular mechanism of RHOX function in humans. Using gene expression profiling, we identified genes regulated by members of the human RHOX gene cluster. Some genes were uniquely regulated by RHOXF1 or RHOXF2/2B, while others were regulated by both of these transcription factors. Several of these regulated genes encode proteins involved in processes relevant to spermatogenesis; e.g. stress protection and cell survival. One of the target genes of RHOXF2/2B is RHOXF1, suggesting cross-regulation to enhance transcriptional responses. The potential role of RHOX in human infertility was addressed by sequencing all RHOX exons in a group of 250 patients with severe oligozoospermia. This revealed two mutations in RHOXF1 (c.515G > A and c.522C > T) and four in RHOXF2/2B (-73C > G, c.202G > A, c.411C > T and c.679G > A), of which only one (c.202G > A) was found in a control group of men with normal sperm concentration. Functional analysis demonstrated that c.202G > A and c.679G > A significantly impaired the ability of RHOXF2/2B to regulate downstream genes. Molecular modelling suggested that these mutations alter RHOXF2/F2B protein conformation. By combining clinical data with in vitro functional analysis, we demonstrate how the X-linked RHOX gene cluster may function in normal human spermatogenesis and we provide evidence that it is impaired in human male fertility.

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

PubMed

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

2012-04-18

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

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

PubMed

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

2007-01-01

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

Transcriptional profiles of Arabidopsis stomataless mutants reveal developmental and physiological features of life in the absence of stomata

PubMed Central

de Marcos, Alberto; Triviño, Magdalena; Pérez-Bueno, María Luisa; Ballesteros, Isabel; Barón, Matilde; Mena, Montaña; Fenoll, Carmen

2015-01-01

Loss of function of the positive stomata development regulators SPCH or MUTE in Arabidopsis thaliana renders stomataless plants; spch-3 and mute-3 mutants are extreme dwarfs, but produce cotyledons and tiny leaves, providing a system to interrogate plant life in the absence of stomata. To this end, we compared their cotyledon transcriptomes with that of wild-type plants. K-means clustering of differentially expressed genes generated four clusters: clusters 1 and 2 grouped genes commonly regulated in the mutants, while clusters 3 and 4 contained genes distinctively regulated in mute-3. Classification in functional categories and metabolic pathways of genes in clusters 1 and 2 suggested that both mutants had depressed secondary, nitrogen and sulfur metabolisms, while only a few photosynthesis-related genes were down-regulated. In situ quenching analysis of chlorophyll fluorescence revealed limited inhibition of photosynthesis. This and other fluorescence measurements matched the mutant transcriptomic features. Differential transcriptomes of both mutants were enriched in growth-related genes, including known stomata development regulators, which paralleled their epidermal phenotypes. Analysis of cluster 3 was not informative for developmental aspects of mute-3. Cluster 4 comprised genes differentially up−regulated in mute−3, 35% of which were direct targets for SPCH and may relate to the unique cell types of mute−3. A screen of T-DNA insertion lines in genes differentially expressed in the mutants identified a gene putatively involved in stomata development. A collection of lines for conditional overexpression of transcription factors differentially expressed in the mutants rendered distinct epidermal phenotypes, suggesting that these proteins may be novel stomatal development regulators. Thus, our transcriptome analysis represents a useful source of new genes for the study of stomata development and for characterizing physiology and growth in the absence of stomata. PMID:26157447

[Health status, use of health services and reported morbidity: application of correspondence analysis].

PubMed

Espinàs, J A; Riba, M D; Borràs, J M; Sánchez, V

1995-01-01

The study of the relationship between self-reported morbidity, health status and health care utilization presents methodological problems due to the variety of illnesses and medical conditions that one individual may report. In this article, correspondence analysis was use to analyse these relationships. Data from the Spanish National Health Survey pertaining to the region of Catalonia was studied. Statistical analysis included multi-way correspondence analysis (MCA) followed by cluster analysis. The first factor extracted is defined by self-assessed health perception; the second, by limitation of activities, and the third is related to self-reported morbidity caused by chronic and acute health problems. Fourth and fifth factors, capture residual variability and missing values. Acute problems are more related to perception of poor health while chronic problems are related to perception of fair health. Also, it may be possible to distinguish self-reported morbidity due to relapses of chronic diseases from true acute health problems. Cluster analysis classified individuals into four groups: 1) healthy people; 2) people who assess their health as being poor and those with acute health problems; 3) people with chronic health problems, limited activity and a perception of fair health; and 4) missing values. Correspondence analysis is a useful tool when analyzing qualitative variables like those in a health survey.

Low Birth Weight as a Predictor of Cardiovascular Risk Factors in Childhood and Adolescence? The PEP Family Heart Study

PubMed Central

Haas, Gerda-Maria; Liepold, Evelyn; Schwandt, Peter

2015-01-01

Background: Low birth weight is considered a risk factor for cardiovascular disease (CVD) in later life. Because data in children and adolescents are sparse and controversial, we assessed the association of birth weight with CVD risk factors in German youths. Methods: We categorized 843 urban children and adolescents aged 3-18 years by quintiles of birth weight and measured nine traditional risk factors in terms of body mass index (BMI), waist circumference (WC), systolic (SBP) and diastolic (DBP) blood pressure, total cholesterol (TC), LDL-C, HDL-C, Non HDL-C and triglycerides (TG). SPSS 21 was used for statistical analysis. Results: Mean values and prevalence of nine anthropometric and lipid risk variables were equally distributed over the five birth weight groups. Though risk factors clustered between 3.0 kg and 4.0 kg of birth weight in both genders we found only one significant correlation of birth weight with TG for males and females and another one for HDL-C in males. The strongest clustering of significant regression coefficients occurred in the 2nd birth weight quintile for SBP (ß 0.018), TC (ß -0.050), LDL-C (ß -0.039), non LDL-C (ß -0.049) and log TG (ß -0.001) in males and females. Conclusions: Overall we did not find significant associations between birth weight and nine traditional cardiovascular risk factors in children and adolescents. However, the 2nd quintile of birth weight might suggest clustering of risk factors. PMID:26900435

Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search.

PubMed

Mena, Carlos; Sepúlveda, Cesar; Fuentes, Eduardo; Ormazábal, Yony; Palomo, Iván

2018-05-07

Cardiovascular diseases (CVDs) are the primary cause of death and disability in de world, and the detection of populations at risk as well as localization of vulnerable areas is essential for adequate epidemiological management. Techniques developed for spatial analysis, among them geographical information systems and spatial statistics, such as cluster detection and spatial correlation, are useful for the study of the distribution of the CVDs. These techniques, enabling recognition of events at different geographical levels of study (e.g., rural, deprived neighbourhoods, etc.), make it possible to relate CVDs to factors present in the immediate environment. The systemic literature presented here shows that this group of diseases is clustered with regard to incidence, mortality and hospitalization as well as obesity, smoking, increased glycated haemoglobin levels, hypertension physical activity and age. In addition, acquired variables such as income, residency (rural or urban) and education, contribute to CVD clustering. Both local cluster detection and spatial regression techniques give statistical weight to the findings providing valuable information that can influence response mechanisms in the health services by indicating locations in need of intervention and assignment of available resources.

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

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

[The users of centers for AIDS information and prevention in the Comunidad Valenciana, Spain: a study based on cluster analysis].

PubMed

González Aracil, J; Ruiz Pérez, I; Aviñó Rico, M J; Hernández Aguado, I

1999-01-01

To measure the usefulness of multiple correspondence analysis (MCA) and cluster analysis applied to the epidemiological research of HIV infection. The specific are to explore the relationships between the different variables that characterize the users of the AIDS Information and Prevention Center (CIPS) and to identify clusters of characteristics which in terms of the attendance to these centers, could be considered similar. The clinical history the CIPS in the Valencian region in Spain was used as data source. The target population target were intravenous drug users (IDUSs) attending these centers between 1987 and 1994 (n = 6211). Information about socio-demographic and HIV type I infection-related variables (drug use and sexual behaviour) was collected by means of a semistructured questionnaire. A MCA was carried out to obtain a group of quantitative factors that were used in a cluster analysis. A 44.8% HIV type I prevalence was found. Five factors were detected by MCA that explain 51.14% of the total variability, of which sex, age and the usual sexual partner were the variables best explained. Cluster analysis allowed to describe 5 different subgroups of CIPS users according to their socio-demographics characteristics, risk behaviours and serologic status. It is necessary to highlight the categories 1 and 2, which collect the serologic status and the most relevant characteristics of HIV infection. Category I contains users with a negative serology and characterized by being mainly single adolescent men, with a low educational level; they stated that they have no steady sexual partner, do not share syringes and have been intravenous drug users between 3 and 10 years. They mainly come from the city of Alicante. Category 2 contains mainly people that are HIV positive and older. They also share syringes and have been intravenous drug users for a longer time; they have a higher education level and most of them come from the city of Valencia. The proposed method of analysis was able to characterise the CIPS users, identifying those socio-demographic variables and risk behaviours that are more related to the serologic status. The applicability of these techniques to epidemiologic studies of HIV type I infection is discussed.

Factors associated with recently transmitted Mycobacterium tuberculosis strain MS0006 in Hinds County, Mississippi.

PubMed

Temple, Brian; Kwara, Awewura; Sunesara, Imran; Mena, Leandro; Dobbs, Thomas; Henderson, Harold; Holcomb, Mike; Webb, Risa

2011-12-01

The objective of this study was to investigate risk factors associated with tuberculosis (TB) transmission that was caused by Mycobacterium tuberculosis strain MS0006 from 2004 to 2009 in Hinds County, Mississippi. DNA fingerprinting using spoligotyping, mycobacterial interspersed repetitive unit, and IS6110-based restriction fragment length polymorphism of culture-confirmed cases of TB was performed. Clinical and demographic factors associated with strain MS0006 were analyzed by univariate and multivariate analysis. Of the 144 cases of TB diagnosed during the study period, 117 were culture positive with fingerprints available. There were 48 different strains, of which 6 clustered strains were distributed among 74 patients. The MS0006 strain accounted for 46.2% of all culture-confirmed cases. Risk factors for having the MS0006 strain in a univariate analysis included homelessness, HIV co-infection, sputum smear negativity, tuberculin skin test negativity, and noninjectable drug use. Multivariate analysis identified homelessness (odds ratio 7.88, 95% confidence interval 2.90-21.35) and African American race (odds ratio 5.80, 95% confidence interval 1.37-24.55) as independent predictors of having TB caused by the MS0006 strain of M. tuberculosis. Our findings suggest that a majority of recently transmitted TB in the studied county was caused by the MS0006 strain. African American race and homelessness were significant risk factors for inclusion in the cluster. Molecular epidemiology techniques continue to provide in-depth analysis of disease transmission and play a vital role in effective contact tracing and interruption of ongoing transmission.

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.

Emergence of sporadic non-clustered cases of hospital-associated listeriosis among immunocompromised adults in southern Taiwan from 1992 to 2013: effect of precipitating immunosuppressive agents.

PubMed

Lee, Chun-Yuan; Tsai, Hung-Chin; Kunin, Calvin M; Lee, Susan Shin-Jung; Wu, Kuan-Sheng; Chen, Yao-Shen

2014-03-19

Sporadic non-clustered hospital-associated listeriosis is an emerging infectious disease in immunocompromised hosts. The current study was designed to determine the impact of long-term and precipitating immunosuppressive agents and underlying diseases on triggering the expression of the disease, and to compare the clinical features and outcome of hospital-associated and community-associated listeriosis. We reviewed the medical records of all patients with Listeria monocytogenes isolated from sterile body sites at a large medical center in southern Taiwan during 1992-2013. Non-clustered cases were defined as those unrelated to any other in time or place. Multivariable regression analysis was used to determine factors associated with prognosis. Thirty-five non-clustered cases of listeriosis were identified. Twelve (34.2%) were hospital-associated, and 23 (65.7%) were community-associated. The 60-day mortality was significantly greater in hospital-associated than in community-associated cases (66.7% vs. 17.4%, p = 0.007). Significantly more hospital-associated than community-associated cases were treated with a precipitating immunosuppressive agent within 4 weeks prior to onset of listeriosis (91.7% vs. 4.3%, respectively p < 0.001). The median period from the start of precipitating immunosuppressive treatment to the onset of listeriosis-related symptoms was 12 days (range, 4-27 days) in 11 of the 12 hospital-associated cases. In the multivariable analysis, APACHE II score >21 (p = 0.04) and receipt of precipitating immunosuppressive therapy (p = 0.02) were independent risk factors for 60-day mortality. Sporadic non-clustered hospital-associated listeriosis needs to be considered in the differential diagnosis of sepsis in immunocompromised patients, particularly in those treated with new or increased doses of immunosuppressive agents.

Minor digestive symptoms and their impact in the general population: a cluster analysis approach.

PubMed

L'Heureux-Bouron, Diane; Legrain-Raspaud, Sophie; Carruthers, Helen R; Whorwell, P J

2018-01-01

The classification and treatment of patients who do not meet the criteria for a functional gastrointestinal (GI) disorder has not been well established. This study aimed to record the prevalence of minor digestive symptoms (MDSs) in the general population attempting to divide them into symptom clusters as well as trying to assess their impact and the way sufferers cope with them. Following face-to-face interviews, a web-based, self-administered questionnaire was designed to capture a range of GI sensations using 34 questions and 12 images depicting abdominal symptoms. A randomly selected sample of 1515 women and 409 men representing the general population in France was studied. Cluster analysis was used to identify groups of respondents with naturally co-occurring symptoms. Data were also collected on other factors such as exacerbating and relieving strategies. MDSs were reported at least every 2 months in 66.5% of women and 47.7% of men. A total of 11 symptom clusters were identified: constipation-like, flatulence, abdominal pressure, abdominal swelling, acid reflux, diarrhoea-like, intestinal heaviness, intestinal pain, gurgling, burning and gastric pain. Despite being minor, these problems had a major impact on vitality and self-image as well as emotional, social and physical well-being. Respondents considered lifestyle, food and disordered function as the main factors responsible for MDSs. Physical measures and dietary modification were the most frequent strategies adopted to obtain relief. MDSs are common and improved methods of recognition are needed so that better management strategies can be developed for individuals with these symptoms. The definition of symptom clusters may offer one way of achieving this goal.

Analysis of Changes in Recent Tuberculosis Transmission Patterns after a Sharp Increase in Immigration▿

PubMed Central

Iñigo, Jesús; García de Viedma, Darío; Arce, Araceli; Palenque, Elia; Alonso Rodríguez, Noelia; Rodríguez, Elena; Ruiz Serrano, María Jesús; Andrés, Sandra; Bouza, Emilio; Chaves, Fernando

2007-01-01

We conducted a population-based molecular epidemiological study of tuberculosis (TB) in Madrid, Spain (2002 to 2004), to define transmission patterns and factors associated with clustering. We particularly focused on examining how the increase in TB cases among immigrants in recent years (2.8% in 1997 to 1999 to 36.2% during the current study) was modifying transmission patterns. Mycobacterium tuberculosis isolates obtained from patients living in nine districts of Madrid (1,459,232 inhabitants) were genotyped. The TB case rate among foreign-born people was three to four times that of Spanish-born people, and the median time from arrival to the onset of treatment was 22.4 months. During the study period, 227 (36.3%) patients were grouped in 64 clusters, and 115 (50.7%) of them were in 21 clusters with mixed Spanish-born and foreign-born patients. Three of the 21 mixed clusters accounted for 21.1% of clustered patients. Twenty-two of 38 (57.9%) immigrants in mixed clusters were infected with TB strains that had already been identified in the native population in 1997 to 1999, including the three most prevalent strains. Factors identified as independent predictors of clustering were homelessness (odds ratio [OR], 2.3; 95% confidence interval [95% CI], 1.2 to 4.5; P = 0.011) and to be born in Spain (OR, 1.8; 95% CI, 1.2 to 2.6; P = 0.002). The results indicated that (i) TB transmission was higher in Spanish-born people, associated mainly with homelessness, (ii) that foreign-born people were much less likely to be clustered, suggesting a higher percentage of infection before arriving in Spain, and (iii) that an extensive transmission between Spanish- and foreign-born populations, caused mainly by autochthonous strains, was taking place in Madrid. PMID:17108076

Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant.

PubMed

Zamani, Abbas Ali; Yaftian, Mohammad Reza; Parizanganeh, Abdolhossein

2012-12-17

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area.

Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant

PubMed Central

2012-01-01

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area. PMID:23369182

Nature of Bonding in Bowl-Like B36 Cluster Revisited: Concentric (6π+18π) Double Aromaticity and Reason for the Preference of a Hexagonal Hole in a Central Location.

PubMed

Li, Rui; You, Xue-Rui; Wang, Kang; Zhai, Hua-Jin

2018-05-04

The bowl-shaped C 6v B 36 cluster with a central hexagon hole is considered an ideal molecular model for low-dimensional boron-based nanosystems. Owing to the electron deficiency of boron, chemical bonding in the B 36 cluster is intriguing, complicated, and has remained elusive despite a couple of papers in the literature. Herein, a bonding analysis is given through canonical molecular orbitals (CMOs) and adaptive natural density partitioning (AdNDP), further aided by natural bond orbital (NBO) analysis and orbital composition calculations. The concerted computational data establish the idea of concentric double π aromaticity for the B 36 cluster, with inner 6π and outer 18π electron counting, which both conform to the (4n+2) Hückel rule. The updated bonding picture differs from existing knowledge of the system. A refined bonding model is also proposed for coronene, of which the B 36 cluster is an inorganic analogue. It is further shown that concentric double π aromaticity in the B 36 cluster is retained and spatially fixed, irrespective of the migration of the hexagonal hole; the latter process changes the system energetically. The hexagonal hole is a destabilizing factor for σ/π CMOs. The central hexagon hole affects substantially fewer CMOs, thus making the bowl-shaped C 6v B 36 cluster the global minimum. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prevalence and clustering of soil-transmitted helminth infections in a tribal area in southern India.

PubMed

Kaliappan, Saravanakumar Puthupalayam; George, Santosh; Francis, Mark Rohit; Kattula, Deepthi; Sarkar, Rajiv; Minz, Shantidani; Mohan, Venkata Raghava; George, Kuryan; Roy, Sheela; Ajjampur, Sitara Swarna Rao; Muliyil, Jayaprakash; Kang, Gagandeep

2013-12-01

To estimate the prevalence, spatial patterns and clustering in the distribution of soil-transmitted helminth (STH) infections, and factors associated with hookworm infections in a tribal population in Tamil Nadu, India. Cross-sectional study with one-stage cluster sampling of 22 clusters. Demographic and risk factor data and stool samples for microscopic ova/cysts examination were collected from 1237 participants. Geographical information systems mapping assessed spatial patterns of infection. The overall prevalence of STH was 39% (95% CI 36%–42%), with hookworm 38% (95% CI 35–41%) and Ascaris lumbricoides 1.5% (95% CI 0.8–2.2%). No Trichuris trichiura infection was detected. People involved in farming had higher odds of hookworm infection (1.68, 95% CI 1.31–2.17, P < 0.001). In the multiple logistic regression, adults (2.31, 95% CI 1.80–2.96, P < 0.001), people with pet cats (1.55, 95% CI 1.10–2.18, P = 0.011) and people who did not wash their hands with soap after defecation (1.84, 95% CI 1.27–2.67, P = 0.001) had higher odds of hookworm infection, but gender and poor usage of foot wear did not significantly increase risk. Cluster analysis, based on design effect calculation, did not show any clustering of cases among the study population; however, spatial scan statistic detected a significant cluster for hookworm infections in one village. Multiple approaches including health education, improving the existing sanitary practices and regular preventive chemotherapy are needed to control the burden of STH in similar endemic areas.

Analysis of long-term water quality for effective river health monitoring in peri-urban landscapes--a case study of the Hawkesbury-Nepean river system in NSW, Australia.

PubMed

Pinto, U; Maheshwari, B L; Ollerton, R L

2013-06-01

The Hawkesbury-Nepean River (HNR) system in South-Eastern Australia is the main source of water supply for the Sydney Metropolitan area and is one of the more complex river systems due to the influence of urbanisation and other activities in the peri-urban landscape through which it flows. The long-term monitoring of river water quality is likely to suffer from data gaps due to funding cuts, changes in priority and related reasons. Nevertheless, we need to assess river health based on the available information. In this study, we demonstrated how the Factor Analysis (FA), Hierarchical Agglomerative Cluster Analysis (HACA) and Trend Analysis (TA) can be applied to evaluate long-term historic data sets. Six water quality parameters, viz., temperature, chlorophyll-a, dissolved oxygen, oxides of nitrogen, suspended solids and reactive silicates, measured at weekly intervals between 1985 and 2008 at 12 monitoring stations located along the 300 km length of the HNR system were evaluated to understand the human and natural influences on the river system in a peri-urban landscape. The application of FA extracted three latent factors which explained more than 70 % of the total variance of the data and related to the 'bio-geographical', 'natural' and 'nutrient pollutant' dimensions of the HNR system. The bio-geographical and nutrient pollution factors more likely related to the direct influence of changes and activities of peri-urban natures and accounted for approximately 50 % of variability in water quality. The application of HACA indicated two major clusters representing clean and polluted zones of the river. On the spatial scale, one cluster was represented by the upper and lower sections of the river (clean zone) and accounted for approximately 158 km of the river. The other cluster was represented by the middle section (polluted zone) with a length of approximately 98 km. Trend Analysis indicated how the point sources influence river water quality on spatio-temporal scales, taking into account the various effects of nutrient and other pollutant loads from sewerage effluents, agriculture and other point and non-point sources along the river and major tributaries of the HNR. Over the past 26 years, water temperature has significantly increased while suspended solids have significantly decreased (p < 0.05). The analysis of water quality data through FA, HACA and TA helped to characterise the key sections and cluster the key water quality variables of the HNR system. The insights gained from this study have the potential to improve the effectiveness of river health-monitoring programs in terms of cost, time and effort, particularly in a peri-urban context.

Barrios, ghettos, and residential racial composition: Examining the racial makeup of neighborhood profiles and their relationship to self-rated health.

PubMed

Booth, Jaime M; Teixeira, Samantha; Zuberi, Anita; Wallace, John M

2018-01-01

Racial/ethnic disparities in self-rated health persist and according to the social determinants of health framework, may be partially explained by residential context. The relationship between neighborhood factors and self-rated health has been examined in isolation but a more holistic approach is needed to understand how these factors may cluster together and how these neighborhood typologies relate to health. To address this gap, we conducted a latent profile analysis using data from the Chicago Community Adult Health Study (CCAHS; N = 2969 respondents in 342 neighborhood clusters) to identify neighborhood profiles, examined differences in neighborhood characteristics among the identified typologies and tested their relationship to self-rated health. Results indicated four distinct classes of neighborhoods that vary significantly on most neighborhood-level social determinants of health and can be defined by racial/ethnic composition and class. Residents in Hispanic, majority black disadvantaged, and majority black non-poor neighborhoods all had significantly poorer self-rated health when compared to majority white neighborhoods. The difference between black non-poor and white neighborhoods in self-rated health was not significant when controlling for individual race/ethnicity. The results indicate that neighborhood factors do cluster by race and class of the neighborhood and that this clustering is related to poorer self-rated health. Copyright © 2017. Published by Elsevier Inc.

Multilocus sequence analysis of Anaplasma phagocytophilum reveals three distinct lineages with different host ranges in clinically ill French cattle.

PubMed

Chastagner, Amélie; Dugat, Thibaud; Vourc'h, Gwenaël; Verheyden, Hélène; Legrand, Loïc; Bachy, Véronique; Chabanne, Luc; Joncour, Guy; Maillard, Renaud; Boulouis, Henri-Jean; Haddad, Nadia; Bailly, Xavier; Leblond, Agnès

2014-12-09

Molecular epidemiology represents a powerful approach to elucidate the complex epidemiological cycles of multi-host pathogens, such as Anaplasma phagocytophilum. A. phagocytophilum is a tick-borne bacterium that affects a wide range of wild and domesticated animals. Here, we characterized its genetic diversity in populations of French cattle; we then compared the observed genotypes with those found in horses, dogs, and roe deer to determine whether genotypes of A. phagocytophilum are shared among different hosts. We sampled 120 domesticated animals (104 cattle, 13 horses, and 3 dogs) and 40 wild animals (roe deer) and used multilocus sequence analysis on nine loci (ankA, msp4, groESL, typA, pled, gyrA, recG, polA, and an intergenic region) to characterize the genotypes of A. phagocytophilum present. Phylogenic analysis revealed three genetic clusters of bacterial variants in domesticated animals. The two principal clusters included 98% of the bacterial genotypes found in cattle, which were only distantly related to those in roe deer. One cluster comprised only cattle genotypes, while the second contained genotypes from cattle, horses, and dogs. The third contained all roe deer genotypes and three cattle genotypes. Geographical factors could not explain this clustering pattern. These results suggest that roe deer do not contribute to the spread of A. phagocytophilum in cattle in France. Further studies should explore if these different clusters are associated with differing disease severity in domesticated hosts. Additionally, it remains to be seen if the three clusters of A. phagocytophilum genotypes in cattle correspond to distinct epidemiological cycles, potentially involving different reservoir hosts.

Population clustering based on copy number variations detected from next generation sequencing data.

PubMed

Duan, Junbo; Zhang, Ji-Gang; Wan, Mingxi; Deng, Hong-Wen; Wang, Yu-Ping

2014-08-01

Copy number variations (CNVs) can be used as significant bio-markers and next generation sequencing (NGS) provides a high resolution detection of these CNVs. But how to extract features from CNVs and further apply them to genomic studies such as population clustering have become a big challenge. In this paper, we propose a novel method for population clustering based on CNVs from NGS. First, CNVs are extracted from each sample to form a feature matrix. Then, this feature matrix is decomposed into the source matrix and weight matrix with non-negative matrix factorization (NMF). The source matrix consists of common CNVs that are shared by all the samples from the same group, and the weight matrix indicates the corresponding level of CNVs from each sample. Therefore, using NMF of CNVs one can differentiate samples from different ethnic groups, i.e. population clustering. To validate the approach, we applied it to the analysis of both simulation data and two real data set from the 1000 Genomes Project. The results on simulation data demonstrate that the proposed method can recover the true common CNVs with high quality. The results on the first real data analysis show that the proposed method can cluster two family trio with different ancestries into two ethnic groups and the results on the second real data analysis show that the proposed method can be applied to the whole-genome with large sample size consisting of multiple groups. Both results demonstrate the potential of the proposed method for population clustering.

Social and Behavioral Risk Marker Clustering Associated with Biological Risk Factors for Coronary Heart Disease: NHANES 2001–2004

PubMed Central

Everage, Nicholas J.; Linkletter, Crystal D.; Gjelsvik, Annie; McGarvey, Stephen T.; Loucks, Eric B.

2014-01-01

Background. Social and behavioral risk markers (e.g., physical activity, diet, smoking, and socioeconomic position) cluster; however, little is known whether clustering is associated with coronary heart disease (CHD) risk. Objectives were to determine if sociobehavioral clustering is associated with biological CHD risk factors (total cholesterol, HDL cholesterol, systolic blood pressure, body mass index, waist circumference, and diabetes) and whether associations are independent of individual clustering components. Methods. Participants included 4,305 males and 4,673 females aged ≥20 years from NHANES 2001–2004. Sociobehavioral Risk Marker Index (SRI) included a summary score of physical activity, fruit/vegetable consumption, smoking, and educational attainment. Regression analyses evaluated associations of SRI with aforementioned biological CHD risk factors. Receiver operator curve analyses assessed independent predictive ability of SRI. Results. Healthful clustering (SRI = 0) was associated with improved biological CHD risk factor levels in 5 of 6 risk factors in females and 2 of 6 risk factors in males. Adding SRI to models containing age, race, and individual SRI components did not improve C-statistics. Conclusions. Findings suggest that healthful sociobehavioral risk marker clustering is associated with favorable CHD risk factor levels, particularly in females. These findings should inform social ecological interventions that consider health impacts of addressing social and behavioral risk factors. PMID:24719858

Globular Cluster Abundances from High-Resolution Integrated-Light Spectra. I. 47 Tuc

NASA Astrophysics Data System (ADS)

McWilliam, Andrew; Bernstein, Rebecca A.

2008-09-01

We describe the detailed chemical abundance analysis of a high-resolution (R ~ 35,000), integrated-light (IL), spectrum of the core of the Galactic globular cluster 47 Tuc, obtained using the du Pont echelle at Las Campanas. We develop an abundance analysis strategy that can be applied to spatial unresolved extragalactic clusters. We have computed abundances for Na, Mg, Al, Si, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Y, Zr, Ba, La, Nd, and Eu. For an analysis with the known color-magnitude diagram (CMD) for 47 Tuc we obtain a mean [Fe/H] value of -0.75 +/- 0.026 +/- 0.045 dex (random and systematic error), in good agreement with the mean of five recent high-resolution abundance studies, at -0.70 dex. Typical random errors on our mean [X/Fe] ratios are 0.07-0.10 dex, similar to studies of individual stars in 47 Tuc. Na and Al appear enhanced, perhaps due to proton burning in the most luminous cluster stars. Our IL abundance analysis with an unknown CMD employed theoretical Teramo isochrones; however, we apply zero-point abundance corrections to account for the factor of 3 underprediction of stars at the AGB bump luminosity. While line diagnostics alone provide only mild constraints on the cluster age (ruling out ages younger than ~2 Gyr), when theoretical IL B - V colors are combined with metallicity derived from the Fe I lines, the age is constrained to 10-15 Gyr and we obtain [ Fe/H ] = - 0.70 +/- 0.021 +/- 0.052 dex. We find that Fe I line diagnostics may also be used to constrain the horizontal-branch morphology of an unresolved cluster. Lastly, our spectrum synthesis of 5.4 million TiO lines indicates that the 7300-7600 Å TiO window should be useful for estimating the effect of M giants on the IL abundances, and important for clusters more metal-rich than 47 Tuc.

Menstrual experiences and beliefs: a multicountry study of relationships with fertility and fertility regulating methods.

PubMed

Severy, L J; Thapa, S; Askew, I; Glor, J

1993-01-01

Knowledge is needed about what women generally experience (behavior and beliefs about sexual, personal, social, and dietary factors) during menstruation as baseline data. Data were obtained from a WHO non nationally representative sample of 5322 parous women from 14 cultural groups between 1973 to 1980 and a subsample of 500 women with detailed daily diaries from 10 countries (Egypt, India, Indonesia, jamaica, Korea, Mexico, Pakistan, Philippines, UK, and Yugoslavia). This study identified and analyzed 1) critical variables through principal component analysis and varimax rotation, 2) clusters of types of women with particular menstrual experiences and particular beliefs, and 3) the relationship between demographic variables and the 2 resultant cluster and the relationship between beliefs and experiences. Factor analysis resulted in the identification of 6 factors and 13 variables which accounted for more than 65% of the variance: amount of bleeding, activity during the last menstrual period, mood during last menstrual period, discomfort during last menstrual period, predictability, and blood characteristics (smell and color). Beliefs that explained more than 53% of the estimated variance were bathing behavior during menstruation, fertility and femininity issues, interpretations and implications of menstruation, and beliefs about not washing hair or body during menstruation. Alpha estimates of reliability for the belief ranged from .33 to .73, and for behavior the range was .40 to .59. The cluster analysis of type of persons identified 3 groups of women: type I (26.4%) who experienced low blood loss the first day and had a long duration of bleeding; type II (52.3%) who had a short duration of bleeding; and type III (21.2%) who had the heaviest bleeding and longest duration of bleeding. The cluster analysis of women's belief types indicated 9 profiles. For instance, Type 2 women tended to believe that menstruation is dirty but prefer more blood loss. Belief Profiles 3, 4, 5, 8, and 9 are consistently represented and profiles 1, 2, 6, and 7 show wide variability. 7 demographic factors were found to be significantly related to belief clusters: country of residence, religion, literacy, age, work environment, social status, and rural vs. urban area. There was evidence, for instance, that type 2 women were overrepresented in the use of modern methods, and that Belief Profile 1, which represents 10.23% of the sample, showed 17.86% using modern methods. The findings show that Belief Profile 1 persons who disagreed with many items were the most likely to use modern methods and have smaller family sizes. Beliefs, which reflect socialization according to demographic variables, appear to affect choice of methods and family size.

Phenotypes of sleeplessness: stressing the need for psychodiagnostics in the assessment of insomnia.

PubMed

van de Laar, Merijn; Leufkens, Tim; Bakker, Bart; Pevernagie, Dirk; Overeem, Sebastiaan

2017-09-01

Insomnia is a too general term for various subtypes that might have different etiologies and therefore require different types of treatment. In this explorative study we used cluster analysis to distinguish different phenotypes in 218 patients with insomnia, taking into account several factors including sleep variables and characteristics related to personality and psychiatric comorbidity. Three clusters emerged from the analysis. The 'moderate insomnia with low psychopathology'-cluster was characterized by relatively normal personality traits, as well as normal levels of anxiety and depressive symptoms in the presence of moderate insomnia severity. The 'severe insomnia with moderate psychopathology'-cluster showed relatively high scores on the Insomnia Severity Index and scores on the sleep log that were indicative for severe insomnia. Anxiety and depressive symptoms were slightly above the cut-off and they were characterized by below average self-sufficiency and less goal-directed behavior. The 'early onset insomnia with high psychopathology'-cluster showed a much younger age and earlier insomnia onset than the other two groups. Anxiety and depressive symptoms were well above the cut-off score and the group consisted of a higher percentage of subjects with comorbid psychiatric disorders. This cluster showed a 'typical psychiatric' personality profile. Our findings stress the need for psychodiagnostic procedures next to a sleep-related diagnostic approach, especially in the younger insomnia patients. Specific treatment suggestions are given based on the three phenotypes.

Para-hydrogen and helium cluster size distributions in free jet expansions based on Smoluchowski theory with kernel scaling.

PubMed

Kornilov, Oleg; Toennies, J Peter

2015-02-21

The size distribution of para-H2 (pH2) clusters produced in free jet expansions at a source temperature of T0 = 29.5 K and pressures of P0 = 0.9-1.96 bars is reported and analyzed according to a cluster growth model based on the Smoluchowski theory with kernel scaling. Good overall agreement is found between the measured and predicted, Nk = A k(a) e(-bk), shape of the distribution. The fit yields values for A and b for values of a derived from simple collision models. The small remaining deviations between measured abundances and theory imply a (pH2)k magic number cluster of k = 13 as has been observed previously by Raman spectroscopy. The predicted linear dependence of b(-(a+1)) on source gas pressure was verified and used to determine the value of the basic effective agglomeration reaction rate constant. A comparison of the corresponding effective growth cross sections σ11 with results from a similar analysis of He cluster size distributions indicates that the latter are much larger by a factor 6-10. An analysis of the three body recombination rates, the geometric sizes and the fact that the He clusters are liquid independent of their size can explain the larger cross sections found for He.

GENETIC AND ENVIRONMENTAL CONTRIBUTIONS TO THE CO-OCCURRENCE OF DEPRESSIVE PERSONALITY DISORDER AND DSM-IV PERSONALITY DISORDERS

PubMed Central

Ørstavik, Ragnhild E.; Kendler, Kenneth S.; Røysamb, Espen; Czajkowski, Nikolai; Tambs, Kristian; Reichborn-Kjennerud, Ted

2012-01-01

One of the main controversies with regard to depressive personality disorder (DPD) concerns the co-occurrence with the established DSM-IV personality disorders (PDs). The main aim of this study was to examine to what extent DPD and the DSM-IV PDs share genetic and environmental risk factors, using multivariate twin modeling. The DSM-IV Structured Interview for Personality was applied to 2,794 young adult twins. Paranoid PD from Cluster A, borderline PD from Cluster B, and all three PDs from Cluster C were independently and significantly associated with DPD in multiple regression analysis. The genetic correlations between DPD and the other PDs were strong (.53–.83), while the environmental correlations were moderate (.36–.40). Close to 50% of the total variance in DPD was disorder specific. However, only 5% was due to disorder-specific genetic factors, indicating that a substantial part of the genetic vulnerability to DPD also increases the vulnerability to other PDs. PMID:22686231

Genetic and environmental contributions to the co-occurrence of depressive personality disorder and DSM-IV personality disorders.

PubMed

Ørstavik, Ragnhild E; Kendler, Kenneth S; Røysamb, Espen; Czajkowski, Nikolai; Tambs, Kristian; Reichborn-Kjennerud, Ted

2012-06-01

One of the main controversies with regard to depressive personality disorder (DPD) concerns the co-occurrence with the established DSM-IV personality disorders (PDs). The main aim of this study was to examine to what extent DPD and the DSM-IV PDs share genetic and environmental risk factors, using multivariate twin modeling. The DSM-IV Structured Interview for Personality was applied to 2,794 young adult twins. Paranoid PD from Cluster A, borderline PD from Cluster B, and all three PDs from Cluster C were independently and significantly associated with DPD in multiple regression analysis. The genetic correlations between DPD and the other PDs were strong (.53-.83), while the environmental correlations were moderate (.36-.40). Close to 50% of the total variance in DPD was disorder specific. However, only 5% was due to disorder-specific genetic factors, indicating that a substantial part of the genetic vulnerability to DPD also increases the vulnerability to other PDs.

Cluster analysis of cognitive performance in elderly and demented subjects.

PubMed

Giaquinto, S; Nolfe, G; Calvani, M

1985-06-01

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

Influence of Average Income on Epidemics of Seasonal Influenza.

PubMed

Seike, Issei; Saito, Norihiro; Saito, Satoshi; Itoga, Masamichi; Kayaba, Hiroyuki

2016-11-22

Understanding the local factors influencing the transmission of communicable diseases is important to minimize social damage. The aim of this study was to investigate local factors influencing seasonal influenza epidemics in Aomori prefecture consisting of 6 regions, i.e., Seihoku, Chunan, and Tosei on the west side, and Sanpachi, Kamikita, and Shimokita on the east side. Four indices (epidemic onset, duration, scale, and steepness of epidemic curves) were defined, and their correlations with regional characteristics and meteorological factors were investigated. Data for influenza seasons from 2006-2007 to 2014-2015 were collected. The 2009-2010 season was excluded because of the pandemic of A (H1N1)pdm09. Average income was strongly correlated with epidemic onset, duration, and scale. The ratio of children aged ≤5 years to the total population was strongly correlated with epidemic duration and scale. Low temperature in January showed moderate correlation with epidemic duration and scale. Cluster analysis showed that 2 isolated regions, Seihoku and Chunan, belonged to the same cluster in the 4 indices of epidemic curves, and other 2 relatively urbanized regions formed another cluster in 3 of the 4 indices. This study highlights important local factors that influence seasonal influenza epidemics and may help in implementation of preventive measures.

Resolution of the apparent discrepancy between the number of massive subhaloes in Abell 2744 and ΛCDM

NASA Astrophysics Data System (ADS)

Mao, Tian-Xiang; Wang, Jie; Frenk, Carlos S.; Gao, Liang; Li, Ran; Wang, Qiao; Cao, Xiaoyue; Li, Ming

2018-07-01

Schwinn et al. have recently compared the abundance and distribution of massive substructures identified in a gravitational lensing analysis of Abell 2744 by Jauzac et al. and N-body simulation, and found no cluster in Lambda cold dark matter (ΛCDM) simulation that is similar to Abell 2744. Schwinn et al. identified the measured projected aperture masses with the actual masses associated with subhaloes in the Millenium XXL N-body simulation. We have used the high-resolution Phoenix cluster simulations to show that such an identification is incorrect: the aperture mass is dominated by mass in the body of the cluster that happens to be projected along the line of sight to the subhalo. This enhancement varies from factors of a few to factors of more than 100, particularly for subhaloes projected near the centre of the cluster. We calculate aperture masses for subhaloes in our simulation and compare them to the measurements for Abell 2744. We find that the data for Abell 2744 are in excellent agreement with the matched predictions from ΛCDM. We provide further predictions for aperture mass functions of subhaloes in idealized surveys with varying mass detection thresholds.

MicroRNA miR-23a cluster promotes osteocyte differentiation by regulating TGF-β signalling in osteoblasts

PubMed Central

Zeng, Huan-Chang; Bae, Yangjin; Dawson, Brian C.; Chen, Yuqing; Bertin, Terry; Munivez, Elda; Campeau, Philippe M.; Tao, Jianning; Chen, Rui; Lee, Brendan H.

2017-01-01

Osteocytes are the terminally differentiated cell type of the osteoblastic lineage and have important functions in skeletal homeostasis. Although the transcriptional regulation of osteoblast differentiation has been well characterized, the factors that regulate differentiation of osteocytes from mature osteoblasts are poorly understood. Here we show that miR-23a∼27a∼24-2 (miR-23a cluster) promotes osteocyte differentiation. Osteoblast-specific miR-23a cluster gain-of-function mice have low bone mass associated with decreased osteoblast but increased osteocyte numbers. By contrast, loss-of-function transgenic mice overexpressing microRNA decoys for either miR-23a or miR-27a, but not miR24-2, show decreased osteocyte numbers. Moreover, RNA-sequencing analysis shows altered transforming growth factor-β (TGF-β) signalling. Prdm16, a negative regulator of the TGF-β pathway, is directly repressed by miR-27a with concomitant alteration of sclerostin expression, and pharmacological inhibition of TGF-β rescues the phenotypes observed in the gain-of-function transgenic mice. Taken together, the miR-23a cluster regulates osteocyte differentiation by modulating the TGF-β signalling pathway through targeting of Prdm16. PMID:28397831

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

PubMed

Sharabi, Adi; Levi, Uzi; Margalit, Malka

2012-01-01

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

A new approach to hierarchical data analysis: Targeted maximum likelihood estimation for the causal effect of a cluster-level exposure.

PubMed

Balzer, Laura B; Zheng, Wenjing; van der Laan, Mark J; Petersen, Maya L

2018-01-01

We often seek to estimate the impact of an exposure naturally occurring or randomly assigned at the cluster-level. For example, the literature on neighborhood determinants of health continues to grow. Likewise, community randomized trials are applied to learn about real-world implementation, sustainability, and population effects of interventions with proven individual-level efficacy. In these settings, individual-level outcomes are correlated due to shared cluster-level factors, including the exposure, as well as social or biological interactions between individuals. To flexibly and efficiently estimate the effect of a cluster-level exposure, we present two targeted maximum likelihood estimators (TMLEs). The first TMLE is developed under a non-parametric causal model, which allows for arbitrary interactions between individuals within a cluster. These interactions include direct transmission of the outcome (i.e. contagion) and influence of one individual's covariates on another's outcome (i.e. covariate interference). The second TMLE is developed under a causal sub-model assuming the cluster-level and individual-specific covariates are sufficient to control for confounding. Simulations compare the alternative estimators and illustrate the potential gains from pairing individual-level risk factors and outcomes during estimation, while avoiding unwarranted assumptions. Our results suggest that estimation under the sub-model can result in bias and misleading inference in an observational setting. Incorporating working assumptions during estimation is more robust than assuming they hold in the underlying causal model. We illustrate our approach with an application to HIV prevention and treatment.

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Horizontal transfer of a large and highly toxic secondary metabolic gene cluster between fungi.

PubMed

Slot, Jason C; Rokas, Antonis

2011-01-25

Genes involved in intermediary and secondary metabolism in fungi are frequently physically linked or clustered. For example, in Aspergillus nidulans the entire pathway for the production of sterigmatocystin (ST), a highly toxic secondary metabolite and a precursor to the aflatoxins (AF), is located in a ∼54 kb, 23 gene cluster. We discovered that a complete ST gene cluster in Podospora anserina was horizontally transferred from Aspergillus. Phylogenetic analysis shows that most Podospora cluster genes are adjacent to or nested within Aspergillus cluster genes, although the two genera belong to different taxonomic classes. Furthermore, the Podospora cluster is highly conserved in content, sequence, and microsynteny with the Aspergillus ST/AF clusters and its intergenic regions contain 14 putative binding sites for AflR, the transcription factor required for activation of the ST/AF biosynthetic genes. Examination of ∼52,000 Podospora expressed sequence tags identified transcripts for 14 genes in the cluster, with several expressed at multiple life cycle stages. The presence of putative AflR-binding sites and the expression evidence for several cluster genes, coupled with the recent independent discovery of ST production in Podospora [1], suggest that this HGT event probably resulted in a functional cluster. Given the abundance of metabolic gene clusters in fungi, our finding that one of the largest known metabolic gene clusters moved intact between species suggests that such transfers might have significantly contributed to fungal metabolic diversity. PAPERFLICK: Copyright © 2011 Elsevier Ltd. All rights reserved.

[The relationship of empathic-affective responses toward others' positive affect with prosocial behaviors and aggressive behaviors].

PubMed

Sakurai, Shigeo; Hayama, Daichi; Suzuki, Takashi; Kurazumi, Tomoe; Hagiwara, Toshihiko; Suzuki, Miyuki; Ohuchi, Akiko; Chizuko, Oikawa

2011-06-01

The purposes of this study were to develop and validate the Empathic-Affective Response Scale, and to examine the relationship of empathic-affective responses with prosocial behaviors and aggressive behaviors. Undergraduate students (N = 443) participated in a questionnaire study. The results of factor analysis indicated that empathic-affective responses involved three factors: (a) sharing and good feeling toward others' positive affect, (b) sharing of negative affect and (c) sympathy toward others' negative affect. Correlations with other empathy-related scales and internal consistency suggested that this scale has satisfactory validity and reliability. Cluster analysis revealed that participants were clustered into four groups: high-empathic group, low-empathic group, insufficient positive affective response group and insufficient negative affective response group. Additional analysis showed the frequency of prosocial behaviors in high-empathic group was highest in all groups. On the other hand, the frequency of aggressive behaviors in both insufficient positive affective response group and low-empathic group were higher than others' groups. The results indicated that empathic-affective responses toward positive affect are also very important to predict prosocial behaviors and aggressive behaviors.

Breakfast patterns and their likelihood of increased risk of overweight/obesity and risk factors for metabolic syndrome in adults 19+ years: National Health and Nutrition Examination Survey 2001-2008

USDA-ARS?s Scientific Manuscript database

Little is known about the relationship of specific types of breakfast consumed and the risk of overweight/obesity or risk factors for metabolic syndrome. Cluster analysis using National Health and Nutrition Examination Survey 2001-2008 data identified 12 breakfast clusters—including no breakfast, in...

Analysis of routine traffic count stations to optimize locations and frequency : final report.

DOT National Transportation Integrated Search

1981-06-01

This report describes a grouping of statewide permanent and key traffic counters on the basis of their geographic variations in traffic flow. Several factors were considered including the distance between clusters and urban versus rural areas. : Traf...

Cluster preformation law for heavy and superheavy nuclei

NASA Astrophysics Data System (ADS)

Wei, K.; Zhang, H. F.

2017-08-01

The concept of cluster radioactivity has been extended to allow emitted particles with ZC>28 for superheavy nuclei by nuclear theory [Poenaru et al., Phys. Rev. Lett. 107, 062503 (2011), 10.1103/PhysRevLett.107.062503]. The preformation and emission mechanics of heavy-ion particles must be examined again before the fascinating radioactivity is observed for superheavy nuclei in laboratory. We extract the cluster preformation factor for heavy and superheavy nuclei within a preformed cluster model, in which the decay constant is the product of the preformation factor, assault frequency, and penetration probability. The calculated results show that the cluster penetration probability for superheavy nuclei is larger than that for actinide elements. The preformation factor depends on the nuclear structures of the emitted cluster and mother nucleus, and the well-known cluster preformation law S (AC) =S (α) (AC-1 )/3 [Blendowske and Walliser, Phys. Rev. Lett. 61, 1930 (1988), 10.1103/PhysRevLett.61.1930] will break down when the mass number of the emitted cluster Ac>28 , and new preformation formulas are proposed to estimate the preformation factor for heavy and superheavy nuclei.

Variability of O3 and NO2 profile shapes during DISCOVER-AQ: Implications for satellite observations and comparisons to model-simulated profiles

NASA Astrophysics Data System (ADS)

Flynn, Clare Marie; Pickering, Kenneth E.; Crawford, James H.; Weinheimer, Andrew J.; Diskin, Glenn; Thornhill, K. Lee; Loughner, Christopher; Lee, Pius; Strode, Sarah A.

2016-12-01

To investigate the variability of in situ profile shapes under a variety of meteorological and pollution conditions, results are presented of an agglomerative hierarchical cluster analysis of the in situ O3 and NO2 profiles for each of the four campaigns of the NASA DISCOVER-AQ mission. Understanding the observed profile variability for these trace gases is useful for understanding the accuracy of the assumed profile shapes used in satellite retrieval algorithms as well as for understanding the correlation between satellite column observations and surface concentrations. The four campaigns of the DISCOVER-AQ mission took place in Maryland during July 2011, the San Joaquin Valley of California during January-February 2013, the Houston, Texas, metropolitan region during September 2013, and the Denver-Front Range region of Colorado during July-August 2014. Several distinct profile clusters emerged for the California, Texas, and Colorado campaigns for O3, indicating significant variability of O3 profile shapes, while the Maryland campaign presented only one distinct O3 cluster. In contrast, very few distinct profile clusters emerged for NO2 during any campaign for this particular clustering technique, indicating the NO2 profile behavior was relatively uniform throughout each campaign. However, changes in NO2 profile shape were evident as the boundary layer evolved through the day, but they were apparently not significant enough to yield more clusters. The degree of vertical mixing (as indicated by temperature lapse rate) associated with each cluster exerted an important influence on the shapes of the median cluster profiles for O3, as well as impacted the correlations between the associated column and surface data for each cluster for O3. The correlation analyses suggest satellites may have the best chance to relate to surface O3 under the conditions encountered during the Maryland campaign Clusters 1 and 2, which include deep, convective boundary layers and few interruptions to this connection from complex meteorology, chemical environments, or orography. The regional CMAQ model captured the shape factors for O3, and moderately well captured the NO2 shape factors, for the conditions associated with the Maryland campaign, suggesting that a regional air quality model may adequately specify a priori profile shapes for remote sensing retrievals. CMAQ shape factor profiles were not as well represented for the other regions.

Risk factors for pulmonary cavitation in tuberculosis patients from China.

PubMed

Zhang, Liqun; Pang, Yu; Yu, Xia; Wang, Yufeng; Lu, Jie; Gao, Mengqiu; Huang, Hairong; Zhao, Yanlin

2016-10-12

Pulmonary cavitation is one of the most frequently observed clinical characteristics in tuberculosis (TB). The objective of this study was to investigate the potential risk factors associated with cavitary TB in China. A total of 385 smear-positive patients were enrolled in the study, including 192 (49.9%) patients with cavitation as determined by radiographic findings. Statistical analysis revealed that the distribution of patients with diabetes in the cavitary group was significantly higher than that in the non-cavitary group (adjusted odds ratio (OR) (95% confidence interval (CI)):12.08 (5.75-25.35), P<0.001). Similarly, we also found that the proportion of individuals with multidrug-resistant TB in the cavitary group was also higher than that in the non-cavitary group (adjusted OR (95% CI): 2.48 (1.52-4.07), P<0.001). Of the 385 Mycobacterium tuberculosis strains, 330 strains (85.7%) were classified as the Beijing genotype, which included 260 strains that belonged to the modern Beijing sublineage and 70 to the ancient Beijing sublineage. In addition, there were 80 and 31 strains belonging to large and small clusters, respectively. Statistical analysis revealed that cavitary disease was observed more frequently among the large clusters than the small clusters (P=0.037). In conclusion, our findings demonstrate that diabetes and multidrug resistance are risk factors associated with cavitary TB. In addition, there was no significant difference in the cavitary presentation between patients infected with the Beijing genotype strains and those infected with the non-Beijing genotype strains.

[From "deadly quartet" to "metabolic syndrome". An analysis of its clinical relevance].

PubMed

Vancheri, Federico; Burgio, Antonio; Dovico, Rossana

2007-03-01

The metabolic syndrome denotes a clustering of specific risk factors for both cardiovascular disease and type 2 diabetes, whose underlying pathophysiology is believed to include insulin resistance. It has been widely reported that the syndrome is a simple clinical tool to identify people at high long term risk of cardiovascular disease and diabetes. However, its clinical importance is under debate. There are substantial uncertainties about the clinical definition of the syndrome, as to whether the risk factors clustering indicates a single unifying disorder, whether the risk conferred by the condition as a whole is higher risk than its individual components, and whether its predictive value of future cardiovascular events or diabetes is greater than established predicting models such as the Framingham Risk Score and the Diabetes Risk Score. We undertook an extensive review of the literature. Our analysis indicates that current definitions of the syndrome are incomplete or ambiguous, more than one pathophysiological process underlies the syndrome, although the combination of insulin resistance and hyperinsulinemia are related to most cases; the risk associated with the syndrome is no greater than that explained by the presence of its components, and the syndrome is less effective in predicting the future development of cardiovascular events and diabetes than established predicting models. Although the syndrome has some importance in understanding the pathophysiology of cardiovascular and diabetes risk factors clustering, its use as a clinical syndrome is not justified by current data.

Low Back Pain Subgroups using Fear-Avoidance Model Measures: Results of a Cluster Analysis

PubMed Central

Beneciuk, Jason M.; Robinson, Michael E.; George, Steven Z.

2012-01-01

Objectives The purpose of this secondary analysis was to test the hypothesis that an empirically derived psychological subgrouping scheme based on multiple Fear-Avoidance Model (FAM) constructs would provide additional capabilities for clinical outcomes in comparison to a single FAM construct. Methods Patients (n = 108) with acute or sub-acute low back pain (LBP) enrolled in a clinical trial comparing behavioral physical therapy interventions to classification based physical therapy completed baseline questionnaires for pain catastrophizing (PCS), fear-avoidance beliefs (FABQ-PA, FABQ-W), and patient-specific fear (FDAQ). Clinical outcomes were pain intensity and disability measured at baseline, 4-weeks, and 6-months. A hierarchical agglomerative cluster analysis was used to create distinct cluster profiles among FAM measures and discriminant analysis was used to interpret clusters. Changes in clinical outcomes were investigated with repeated measures ANOVA and differences in results based on cluster membership were compared to FABQ-PA subgrouping used in the original trial. Results Three distinct FAM subgroups (Low Risk, High Specific Fear, and High Fear & Catastrophizing) emerged from cluster analysis. Subgroups differed on baseline pain and disability (p’s<.01) with the High Fear & Catastrophizing subgroup associated with greater pain than the Low Risk subgroup (p<.01) and the greatest disability (p’s<.05). Subgroup × time interactions were detected for both pain and disability (p’s<.05) with the High Fear & Catastrophizing subgroup reporting greater changes in pain and disability than other subgroups (p’s<.05). In contrast, FABQ-PA subgroups used in the original trial were not associated with interactions for clinical outcomes. Discussion These data suggest that subgrouping based on multiple FAM measures may provide additional information on clinical outcomes in comparison to determining subgroup status by FABQ-PA alone. Subgrouping methods for patients with LBP should include multiple psychological factors to further explore if patients can be matched with appropriate interventions. PMID:22510537

Who are the obese? A cluster analysis exploring subgroups of the obese.

PubMed

Green, M A; Strong, M; Razak, F; Subramanian, S V; Relton, C; Bissell, P

2016-06-01

Body mass index (BMI) can be used to group individuals in terms of their height and weight as obese. However, such a distinction fails to account for the variation within this group across other factors such as health, demographic and behavioural characteristics. The study aims to examine the existence of subgroups of obese individuals. Data were taken from the Yorkshire Health Study (2010-12) including information on demographic, health and behavioural characteristics. Individuals with a BMI of ≥30 were included. A two-step cluster analysis was used to define groups of individuals who shared common characteristics. The cluster analysis found six distinct groups of individuals whose BMI was ≥30. These subgroups were heavy drinking males, young healthy females; the affluent and healthy elderly; the physically sick but happy elderly; the unhappy and anxious middle aged and a cluster with the poorest health. It is important to account for the important heterogeneity within individuals who are obese. Interventions introduced by clinicians and policymakers should not target obese individuals as a whole but tailor strategies depending upon the subgroups that individuals belong to. © The Author 2015. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

EPA Pesticide Factsheets

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

Cluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations

NASA Astrophysics Data System (ADS)

Gligor, M.; Ausloos, M.

2007-05-01

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

Students' Changing Attitudes and Aspirations Towards Physics During Secondary School

NASA Astrophysics Data System (ADS)

Sheldrake, Richard; Mujtaba, Tamjid; Reiss, Michael J.

2017-11-01

Many countries desire more students to study science subjects, although relatively few students decide to study non-compulsory physics at upper-secondary school and at university. To gain insight into students' intentions to study non-compulsory physics, a longitudinal sample (covering 2258 students across 88 secondary schools in England) was surveyed in year 8 (age 12/13) and again in year 10 (age 14/15). Predictive modelling highlighted that perceived advice, perceived utility of physics, interest in physics, self-concept beliefs (students' subjective beliefs of their current abilities and performance) and home support specifically orientated to physics were key predictors of students' intentions. Latent-transition analysis via Markov models revealed clusters of students, given these factors at years 8 and 10. Students' intentions varied across the clusters, and at year 10 even varied when accounting for the students' underlying attitudes and beliefs, highlighting that considering clusters offered additional explanatory power and insight. Regardless of whether three-cluster, four-cluster, or five-cluster models were considered, the majority of students remained in the same cluster over time; for those who transitioned clusters, more students changed clusters reflecting an increase in attitudes than changed clusters reflecting a decrease. Students in the cluster with the most positive attitudes were most likely to remain within that cluster, while students in clusters with less positive attitudes were more likely to change clusters. Overall, the cluster profiles highlighted that students' attitudes and beliefs may be more closely related than previously assumed, but that changes in their attitudes and beliefs were indeed possible.

Clonal Clusters and Virulence Factors of Group C and G Streptococcus Causing Severe Infections, Manitoba, Canada, 2012-2014.

PubMed

Lother, Sylvain A; Demczuk, Walter; Martin, Irene; Mulvey, Michael; Dufault, Brenden; Lagacé-Wiens, Philippe; Keynan, Yoav

2017-07-01

The incidence of group C and G Streptococcus (GCGS) bacteremia, which is associated with severe disease and death, is increasing. We characterized clinical features, outcomes, and genetic determinants of GCGS bacteremia for 89 patients in Winnipeg, Manitoba, Canada, who had GCGS bacteremia during 2012-2014. Of the 89 patients, 51% had bacteremia from skin and soft tissue, 70% had severe disease features, and 20% died. Whole-genome sequencing analysis was performed on isolates derived from 89 blood samples and 33 respiratory sample controls: 5 closely related genetic lineages were identified as being more likely to cause invasive disease than non-clade isolates (83% vs. 57%, p = 0.002). Virulence factors cbp, fbp, speG, sicG, gfbA, and bca clustered clonally into these clades. A clonal distribution of virulence factors may account for severe and fatal cases of bacteremia caused by invasive GCGS.

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

PubMed

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

2016-06-01

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

Effect of Clustering Algorithm on Establishing Markov State Model for Molecular Dynamics Simulations.

PubMed

Li, Yan; Dong, Zigang

2016-06-27

Recently, the Markov state model has been applied for kinetic analysis of molecular dynamics simulations. However, discretization of the conformational space remains a primary challenge in model building, and it is not clear how the space decomposition by distinct clustering strategies exerts influence on the model output. In this work, different clustering algorithms are employed to partition the conformational space sampled in opening and closing of fatty acid binding protein 4 as well as inactivation and activation of the epidermal growth factor receptor. Various classifications are achieved, and Markov models are set up accordingly. On the basis of the models, the total net flux and transition rate are calculated between two distinct states. Our results indicate that geometric and kinetic clustering perform equally well. The construction and outcome of Markov models are heavily dependent on the data traits. Compared to other methods, a combination of Bayesian and hierarchical clustering is feasible in identification of metastable states.

Individual and couple-level risk factors for hepatitis C infection among heterosexual drug users: a multilevel dyadic analysis.

PubMed

McMahon, James M; Pouget, Enrique R; Tortu, Stephanie

2007-06-01

Hepatitis C virus (HCV) is the most common bloodborne pathogen in the United States and is a leading cause of liver-related morbidity and mortality. Although it is known that HCV is most commonly transmitted among injection drug users, the role of sexual transmission in the spread of HCV remains controversial because of inconsistent findings across studies involving heterosexual couples. A novel multilevel modeling technique designed to overcome the limitations of previous research was performed to assess multiple risk factors for HCV while partitioning the source of risk at the individual and couple level. The analysis was performed on risk exposure and HCV screening data obtained from 265 drug-using couples in East Harlem, New York City. In multivariable analysis, significant individual risk factors for HCV included a history of injection drug use, tattooing, and older age. At the couple level, HCV infection tended to cluster within couples, and this interdependence was accounted for by couples' drug-injection behavior. Individual and couple-level sexual behavior was not associated with HCV infection. Our results are consistent with prior research indicating that sexual contact plays little role in HCV transmission. Rather, couples' injection behavior appears to account for the clustering of HCV within heterosexual dyads.

A study and meta-analysis of lay attributions of cures for overcoming specific psychological problems.

PubMed

Furnham, A; Hayward, R

1997-09-01

Lay beliefs about the importance of 24 different contributors to overcoming 4 disorders that constitute primarily cognitive deficits were studied. A meta-analysis of previous programmatic studies in the area was performed so that 22 different psychological problems could be compared. In the present study, 107 participants completed a questionnaire indicating how effective 24 factors were in overcoming 4 specific problems: dyslexia, fear of flying, amnesia, and learning difficulties. Factor analysis revealed almost identical clusters (inner control, social consequences, understanding, receiving help, and fate) for each problem. The perceived relevance of those factors differed significantly between problems. Some individual difference factors (sex and religion) were found to predict certain factor attributions for specific disorders. A meta-analysis of the 5 studies in this series yielded a 6-factor structure comparable to those of the individual studies and provided results indicating the benefits and limitations of this kind of investigation. The clinical relevance of studying attributions for cure is considered.

Electrostatic effects on clustering and ion dynamics in ionomer melts

NASA Astrophysics Data System (ADS)

Ma, Boran; Nguyen, Trung; Pryamitsyn, Victor; Olvera de La Cruz, Monica

An understanding of the relationships between ionomer chain morphology, dynamics and counter-ion mobility is a key factor in the design of ion conducting membranes for battery applications. In this study, we investigate the influence of electrostatic coupling between randomly charged copolymers (ionomers) and counter ions on the structural and dynamic features of a model system of ionomer melts. Using coarse-grained molecular dynamics (CGMD) simulations, we found that variations in electrostatic coupling strength (Γ) remarkably affect the formation of ion-counter ion clusters, ion mobility, and polymer dynamics for a range of charged monomer fractions. Specifically, an increase in Γ leads to larger ionic cluster sizes and reduced polymer and ion mobility. Analysis of the distribution of the radius of gyration of the clusters further reveals that the fractal dimension of the ion clusters is nearly independent from Γ for all the cases studied. Finally, at sufficiently high values of Γ, we observed arrested heterogeneous ions mobility, which is correlated with an increase in ion cluster size. These findings provide insight into the role of electrostatics in governing the nanostructures formed by ionomers.

Genetic approaches of the Fe-S cluster biogenesis process in bacteria: Historical account, methodological aspects and future challenges.

PubMed

Py, Béatrice; Barras, Frédéric

2015-06-01

Since their discovery in the 50's, Fe-S cluster proteins have attracted much attention from chemists, biophysicists and biochemists. However, in the 80's they were joined by geneticists who helped to realize that in vivo maturation of Fe-S cluster bound proteins required assistance of a large number of factors defining complex multi-step pathways. The question of how clusters are formed and distributed in vivo has since been the focus of much effort. Here we review how genetics in discovering genes and investigating processes as they unfold in vivo has provoked seminal advances toward our understanding of Fe-S cluster biogenesis. The power and limitations of genetic approaches are discussed. As a final comment, we argue how the marriage of classic strategies and new high-throughput technologies should allow genetics of Fe-S cluster biology to be even more insightful in the future. This article is part of a Special Issue entitled: Fe/S proteins: Analysis, structure, function, biogenesis and diseases. Copyright © 2015 Elsevier B.V. All rights reserved.

Clustering of modifiable biobehavioral risk factors for chronic disease in US adults: a latent class analysis.

PubMed

Leventhal, Adam M; Huh, Jimi; Dunton, Genevieve F

2014-11-01

Examining the co-occurrence patterns of modifiable biobehavioral risk factors for deadly chronic diseases (e.g. cancer, cardiovascular disease, diabetes) can elucidate the etiology of risk factors and guide disease-prevention programming. The aims of this study were to (1) identify latent classes based on the clustering of five key biobehavioral risk factors among US adults who reported at least one risk factor and (2) explore the demographic correlates of the identified latent classes. Participants were respondents of the National Epidemiologic Survey of Alcohol and Related Conditions (2004-2005) with at least one of the following disease risk factors in the past year (N = 22,789), which were also the latent class indicators: (1) alcohol abuse/dependence, (2) drug abuse/dependence, (3) nicotine dependence, (4) obesity, and (5) physical inactivity. Housing sample units were selected to match the US National Census in location and demographic characteristics, with young adults oversampled. Participants were administered surveys by trained interviewers. Five latent classes were yielded: 'obese, active non-substance abusers' (23%); 'nicotine-dependent, active, and non-obese' (19%); 'active, non-obese alcohol abusers' (6%); 'inactive, non-substance abusers' (50%); and 'active, polysubstance abusers' (3.7%). Four classes were characterized by a 100% likelihood of having one risk factor coupled with a low or moderate likelihood of having the other four risk factors. The five classes exhibited unique demographic profiles. Risk factors may cluster together in a non-monotonic fashion, with the majority of the at-risk population of US adults expected to have a high likelihood of endorsing only one of these five risk factors. © Royal Society for Public Health 2013.

Headache cessation by an educational intervention in grammar schools: a cluster randomized trial.

PubMed

Albers, L; Heinen, F; Landgraf, M; Straube, A; Blum, B; Filippopulos, F; Lehmann, S; Mansmann, U; Berger, U; Akboga, Y; von Kries, R

2015-02-01

Headache is a common health problem in adolescents. There are a number of risk factors for headache in adolescents that are amenable to intervention. The aim of the study was to assess the effectiveness of a low-level headache prevention programme in the classroom setting to prevent these risk factors. In all, 1674 students in 8th-10th grade at 12 grammar schools in greater Munich, Germany, were cluster randomized into intervention and control groups. A standardized 60-min prevention lesson focusing on preventable risk factors for headache (physical inactivity, coffee consumption, alcohol consumption and smoking) and providing instructions on stress management and neck and shoulder muscle relaxation exercises was given in a classroom setting. Seven months later, students were reassessed. The main outcome parameter was headache cessation. Logistic regression models with random effects for cluster and adjustment for baseline risk factors were calculated. Nine hundred students (intervention group N = 450, control group N = 450) with headache at baseline and complete data for headache and confounders were included in the analysis. Headache cessation was observed in 9.78% of the control group compared with 16.22% in the intervention group (number needed to treat = 16). Accounting for cluster effects and confounders, the probability of headache cessation in the intervention group was 1.77 (95% confidence interval = [1.08; 2.90]) higher than in the control group. The effect was most pronounced in adolescents with tension-type headache: odds ratio = 2.11 (95% confidence interval = [1.15; 3.80]). Our study demonstrates the effectiveness of a one-time, classroom-based headache prevention programme. © 2014 EAN.

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.

A Hierarchical Framework for State-Space Matrix Inference and Clustering.

PubMed

Zuo, Chandler; Chen, Kailei; Hewitt, Kyle J; Bresnick, Emery H; Keleş, Sündüz

2016-09-01

In recent years, a large number of genomic and epigenomic studies have been focusing on the integrative analysis of multiple experimental datasets measured over a large number of observational units. The objectives of such studies include not only inferring a hidden state of activity for each unit over individual experiments, but also detecting highly associated clusters of units based on their inferred states. Although there are a number of methods tailored for specific datasets, there is currently no state-of-the-art modeling framework for this general class of problems. In this paper, we develop the MBASIC ( M atrix B ased A nalysis for S tate-space I nference and C lustering) framework. MBASIC consists of two parts: state-space mapping and state-space clustering. In state-space mapping, it maps observations onto a finite state-space, representing the activation states of units across conditions. In state-space clustering, MBASIC incorporates a finite mixture model to cluster the units based on their inferred state-space profiles across all conditions. Both the state-space mapping and clustering can be simultaneously estimated through an Expectation-Maximization algorithm. MBASIC flexibly adapts to a large number of parametric distributions for the observed data, as well as the heterogeneity in replicate experiments. It allows for imposing structural assumptions on each cluster, and enables model selection using information criterion. In our data-driven simulation studies, MBASIC showed significant accuracy in recovering both the underlying state-space variables and clustering structures. We applied MBASIC to two genome research problems using large numbers of datasets from the ENCODE project. The first application grouped genes based on transcription factor occupancy profiles of their promoter regions in two different cell types. The second application focused on identifying groups of loci that are similar to a GATA2 binding site that is functional at its endogenous locus by utilizing transcription factor occupancy data and illustrated applicability of MBASIC in a wide variety of problems. In both studies, MBASIC showed higher levels of raw data fidelity than analyzing these data with a two-step approach using ENCODE results on transcription factor occupancy data.

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis

PubMed Central

2013-01-01

Background Given the serious threats posed to terrestrial ecosystems by industrial contamination, environmental monitoring is a standard procedure used for assessing the current status of an environment or trends in environmental parameters. Measurement of metal concentrations at different trophic levels followed by their statistical analysis using exploratory multivariate methods can provide meaningful information on the status of environmental quality. In this context, the present paper proposes a novel chemometric approach to standard statistical methods by combining the Block clustering with Partial least square (PLS) analysis to investigate the accumulation patterns of metals in anthropized terrestrial ecosystems. The present study focused on copper, zinc, manganese, iron, cobalt, cadmium, nickel, and lead transfer along a soil-plant-snai food chain, and the hepatopancreas of the Roman snail (Helix pomatia) was used as a biological end-point of metal accumulation. Results Block clustering deliniates between the areas exposed to industrial and vehicular contamination. The toxic metals have similar distributions in the nettle leaves and snail hepatopancreas. PLS analysis showed that (1) zinc and copper concentrations at the lower trophic levels are the most important latent factors that contribute to metal accumulation in land snails; (2) cadmium and lead are the main determinants of pollution pattern in areas exposed to industrial contamination; (3) at the sites located near roads lead is the most threatfull metal for terrestrial ecosystems. Conclusion There were three major benefits by applying block clustering with PLS for processing the obtained data: firstly, it helped in grouping sites depending on the type of contamination. Secondly, it was valuable for identifying the latent factors that contribute the most to metal accumulation in land snails. Finally, it optimized the number and type of data that are best for monitoring the status of metallic contamination in terrestrial ecosystems exposed to different kinds of anthropic polution. PMID:23987502

Lifestyle and accidents among young drivers.

PubMed

Gregersen, N P; Berg, H Y

1994-06-01

This study covers the lifestyle component of the problems related to young drivers' accident risk. The purpose of the study is to measure the relationship between lifestyle and accident risk, and to identify specific high-risk and low-risk groups. Lifestyle is measured through a questionnaire, where 20-year-olds describe themselves and how often they deal with a large number of different activities, like sports, music, movies, reading, cars and driving, political engagement, etc. They also report their involvement in traffic accidents. With a principal component analysis followed by a cluster analysis, lifestyle profiles are defined. These profiles are finally correlated to accidents, which makes it possible to define high-risk and low-risk groups. The cluster analysis defined 15 clusters including four high-risk groups with an average overrisk of 150% and two low-risk groups with an average underrisk of 75%. The results are discussed from two perspectives. The first is the importance of theoretical understanding of the contribution of lifestyle factors to young drivers' high accident risk. The second is how the findings could be used in practical road safety measures, like education, campaigns, etc.

Precision growth index using the clustering of cosmic structures and growth data

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

Pouri, Athina; Basilakos, Spyros; Plionis, Manolis, E-mail: athpouri@phys.uoa.gr, E-mail: svasil@academyofathens.gr, E-mail: mplionis@physics.auth.gr

2014-08-01

We use the clustering properties of Luminous Red Galaxies (LRGs) and the growth rate data provided by the various galaxy surveys in order to constrain the growth index γ) of the linear matter fluctuations. We perform a standard χ{sup 2}-minimization procedure between theoretical expectations and data, followed by a joint likelihood analysis and we find a value of γ=0.56± 0.05, perfectly consistent with the expectations of the ΛCDM model, and Ω{sub m0} =0.29± 0.01, in very good agreement with the latest Planck results. Our analysis provides significantly more stringent growth index constraints with respect to previous studies, as indicated by the fact thatmore » the corresponding uncertainty is only ∼ 0.09 γ. Finally, allowing γ to vary with redshift in two manners (Taylor expansion around z=0, and Taylor expansion around the scale factor), we find that the combined statistical analysis between our clustering and literature growth data alleviates the degeneracy and obtain more stringent constraints with respect to other recent studies.« less

Integrated Analysis of Dysregulated miRNA-gene Expression in HMGA2-silenced Retinoblastoma Cells

PubMed Central

Venkatesan, Nalini; Deepa, PR; Vasudevan, Madavan; Khetan, Vikas; Reddy, Ashwin M; Krishnakumar, Subramanian

2014-01-01

Retinoblastoma (RB) is a primary childhood eye cancer. HMGA2 shows promise as a molecule for targeted therapy. The involvement of miRNAs in genome-level molecular dys-regulation in HMGA2-silenced RB cells is poorly understood. Through miRNA expression microarray profiling, and an integrated array analysis of the HMGA2-silenced RB cells, the dysregulated miRNAs and the miRNA-target relationships were modelled. Loop network analysis revealed a regulatory association between the transcription factor (SOX5) and the deregulated miRNAs (miR-29a, miR-9*, miR-9-3). Silencing of HMGA2 deregulated the vital oncomirs (miR-7, miR-331, miR-26a, miR-221, miR-17~92 and miR-106b∼25) in RB cells. From this list, the role of the miR-106b∼25 cluster was examined further for its expression in primary RB tumor tissues (n = 20). The regulatory targets of miR-106b∼25 cluster namely p21 (cyclin-dependent kinase inhibitor) and BIM (pro-apoptotic gene) were elevated, and apoptotic cell death was observed, in RB tumor cells treated with the specific antagomirs of the miR-106b∼25 cluster. Thus, suppression of miR-106b∼25 cluster controls RB tumor growth. Taken together, HMGA2 mediated anti-tumor effect present in RB is, in part, mediated through the miR-106b∼25 cluster. PMID:25232279

Using factor analysis to identify neuromuscular synergies during treadmill walking

NASA Technical Reports Server (NTRS)

Merkle, L. A.; Layne, C. S.; Bloomberg, J. J.; Zhang, J. J.

1998-01-01

Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.

The peculiar velocities of rich clusters in the hot and cold dark matter scenarios

NASA Technical Reports Server (NTRS)

Rhee, George F.; West, Michael J.; Villumsen, Jens V.

1993-01-01

We present the results of a study of the peculiar velocities of rich clusters of galaxies. The peculiar motion of rich clusters in various cosmological scenarios is of interest for a number of reasons. Observationally, one can measure the peculiar motion of clusters to greater distances than galaxies because cluster peculiar motions can be determined to greater accuracy. One can also test the slope of distance indicator relations using clusters to see if galaxy properties vary with environment. We have used N-body simulations to measure the amplitude and rms cluster peculiar velocity as a function of bias parameter in the hot and cold dark matter scenarios. In addition to measuring the mean and rms peculiar velocity of clusters in the two models, we determined whether the peculiar velocity vector of a given cluster is well aligned with the gravity vector due to all the particles in the simulation and the gravity vector due to the particles present only in the clusters. We have investigated the peculiar velocities of rich clusters of galaxies in the cold dark matter and hot dark matter galaxy formation scenarios. We have derived peculiar velocities and associated errors for the scenarios using four values of the bias parameter ranging from b = 1 to b = 2.5. The growth of the mean peculiar velocity with scale factor has been determined and compared to that predicted by linear theory. In addition, we have compared the orientation of force and velocity in these simulations to see if a program such as that proposed by Bertschinger and Dekel (1989) for elliptical galaxy peculiar motions can be applied to clusters. The method they describe enables one to recover the density field from large scale redshift distance samples. The method makes it possible to do this when only radial velocities are known by assuming that the velocity field is curl free. Our analysis suggests that this program if applied to clusters is only realizable for models with a low value of the bias parameter, i.e., models in which the peculiar velocities of clusters are large enough that the errors do not render the analysis impracticable.

Linking Strengths: Identifying and Exploring Protective Factor Clusters in Academically Resilient Low-Socioeconomic Urban Students of Color

ERIC Educational Resources Information Center

Morales, Erik E.

2010-01-01

Based on data from qualitative interviews with 50 high-achieving low-socioeconomic students of color, two "clusters" of important and symbiotic protective factors are identified and explored. Each cluster consists of a series of interrelated protective factors identified by the participants as crucial to their statistically exceptional academic…

Endohedral gallide cluster superconductors and superconductivity in ReGa5

PubMed Central

Xie, Weiwei; Luo, Huixia; Phelan, Brendan F.; Klimczuk, Tomasz; Cevallos, Francois Alexandre; Cava, Robert Joseph

2015-01-01

We present transition metal-embedded (T@Gan) endohedral Ga-clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2Ga9 are all previously known superconductors. The well-known exotic superconductor PuCoGa5 and related phases are also members of this endohedral gallide cluster family. We show that electron-deficient compounds like Mo8Ga41 prefer architectures with vertex-sharing gallium clusters, whereas electron-rich compounds, like PdGa5, prefer edge-sharing cluster architectures. The superconducting transition temperatures are highest for the electron-poor, corner-sharing architectures. Based on this analysis, the previously unknown endohedral cluster compound ReGa5 is postulated to exist at an intermediate electron count and a mix of corner sharing and edge sharing cluster architectures. The empirical prediction is shown to be correct and leads to the discovery of superconductivity in ReGa5. The Fermi levels for endohedral gallide cluster compounds are located in deep pseudogaps in the electronic densities of states, an important factor in determining their chemical stability, while at the same time limiting their superconducting transition temperatures. PMID:26644566

Molecular analysis of hepatitis A virus strains obtained from patients with acute hepatitis A in Mongolia, 2004-2013.

PubMed

Tsatsralt-Od, Bira; Baasanjav, Nachin; Nyamkhuu, Dulmaa; Ohnishi, Hiroshi; Takahashi, Masaharu; Kobayashi, Tominari; Nagashima, Shigeo; Nishizawa, Tsutomu; Okamoto, Hiroaki

2016-04-01

Despite the high endemicity of hepatitis A virus (HAV) in Mongolia, the genetic information on those HAV strains is limited. Serum samples obtained from 935 patients with acute hepatitis in Ulaanbaatar, Mongolia during 2004-2013 were tested for the presence of HAV RNA using reverse transcription-PCR with primers targeting the VP1-2B region (481 nucleotides, primer sequences at both ends excluded). Overall, 180 patients (19.3%) had detectable HAV RNA. These 180 isolates shared 94.6-100% identity and formed four phylogenetic clusters within subgenotype IA. One or three representative HAV isolates from each cluster exhibited 2.6-3.9% difference between clusters over the entire genome. Cluster 1 accounted for 65.0% of the total, followed by Cluster 2 (30.6%), Cluster 3 (3.3%), and Cluster 4 (1.1%). Clusters 1 and 2 were predominant throughout the observation period, whereas Cluster 3 was undetectable in 2009 and 2013 and Cluster 4 became undetectable after 2009. The Mongolian HAV isolates were closest to those of Chinese or Japanese origin (97.7-98.5% identities over the entire genome), suggesting the evolution from a common ancestor with those circulating in China and Japan. Further molecular epidemiological analyses of HAV infection are necessary to investigate the factors underlying the spread of HAV and to implement appropriate prevention measures in Mongolia. © 2015 Wiley Periodicals, Inc.

Biochemical characterization and phylogenetic analysis based on 16S rRNA sequences for V-factor dependent members of Pasteurellaceae derived from laboratory rats.

PubMed

Hayashimoto, Nobuhito; Ueno, Masami; Tkakura, Akira; Itoh, Toshio

2007-06-01

Phylogenetic analysis based on 16S rRNA sequences with sequence data of some bacterial species of Pasteurellaceae related to rodents deposited in GenBank was performed along with biochemical characterization for the 20 strains of V-factor dependent members of Pasteurellaceae derived from laboratory rats to obtain basic information and to investigate the taxonomic positions. The results of biochemical tests for all strains were identical except for three tests, the ornithine decarboxylase test, and fermentation tests of D(+) mannose and D(+) xylose. The biochemical properties of 8 of 20 strains that showed negative results for the fermentation test of D(+) xylose agreed with those of Haemophilus parainfluenzae complex. By phylogenetic analysis, the strains were divided into two clusters that agreed with the results of the fermentation test of xylose (group I: negative reaction for xylose, group II: positive reaction for xylose). The clusters were independent of other bacterial species of Pasteurellaceae tested. The sequences of the strains in group I showed 99.7-99.8% similarity and the strains in group II showed 99.3-99.7% similarity. None of the strains in group I had a close relation with Haemophilus parainfluenzae by phylogenetic analysis, although they showed the same biochemical properties. In conclusion, the strains had characteristic biochemical properties and formed two independent groups within the "rodent cluster" of Pasteurellaceae that differed in the results of the fermentation test of xylose. Therefore, they seemed to be hitherto undescribed taxa in Pasteurellaceae.

GC-MS analyses and chemometric processing to discriminate the local and long-distance sources of PAHs associated to atmospheric PM2.5.

PubMed

Masiol, Mauro; Centanni, Elena; Squizzato, Stefania; Hofer, Angelika; Pecorari, Eliana; Rampazzo, Giancarlo; Pavoni, Bruno

2012-09-01

This study presents a procedure to differentiate the local and remote sources of particulate-bound polycyclic aromatic hydrocarbons (PAHs). Data were collected during an extended PM(2.5) sampling campaign (2009-2010) carried out for 1 year in Venice-Mestre, Italy, at three stations with different emissive scenarios: urban, industrial, and semirural background. Diagnostic ratios and factor analysis were initially applied to point out the most probable sources. In a second step, the areal distribution of the identified sources was studied by applying the discriminant analysis on factor scores. Third, samples collected in days with similar atmospheric circulation patterns were grouped using a cluster analysis on wind data. Local contributions to PM(2.5) and PAHs were then assessed by interpreting cluster results with chemical data. Results evidenced that significantly lower levels of PM(2.5) and PAHs were found when faster winds changed air masses, whereas in presence of scarce ventilation, locally emitted pollutants were trapped and concentrations increased. This way, an estimation of pollutant loads due to local sources can be derived from data collected in days with similar wind patterns. Long-range contributions were detected by a cluster analysis on the air mass back-trajectories. Results revealed that PM(2.5) concentrations were relatively high when air masses had passed over the Po Valley. However, external sources do not significantly contribute to the PAHs load. The proposed procedure can be applied to other environments with minor modifications, and the obtained information can be useful to design local and national air pollution control strategies.

Patterns of Food Parenting Practices and Children's Intake of Energy-Dense Snack Foods.

PubMed

Gevers, Dorus W M; Kremers, Stef P J; de Vries, Nanne K; van Assema, Patricia

2015-05-27

Most previous studies of parental influences on children's diets included just a single or a few types of food parenting practices, while parents actually employ multiple types of practices. Our objective was to investigate the clustering of parents regarding food parenting practices and to characterize the clusters in terms of background characteristics and children's intake of energy-dense snack foods. A sample of Dutch parents of children aged 4-12 was recruited by a research agency to fill out an online questionnaire. A hierarchical cluster analysis (n = 888) was performed, followed by k-means clustering. ANOVAs, ANCOVAs and chi-square tests were used to investigate associations between cluster membership, parental and child background characteristics, as well as children's intake of energy-dense snack foods. Four distinct patterns were discovered: "high covert control and rewarding", "low covert control and non-rewarding", "high involvement and supportive" and "low involvement and indulgent". The "high involvement and supportive" cluster was found to be most favorable in terms of children's intake. Several background factors characterized cluster membership. This study expands the current knowledge about parental influences on children's diets. Interventions should focus on increasing parental involvement in food parenting.

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.

Genetic Variation of Beet Armyworm (Lepidoptera: Noctuidae) Populations Detected Using Microsatellite Markers in Iran.

PubMed

Golikhajeh, Neshat; Naseri, Bahram; Razmjou, Jabraeil; Hosseini, Reza; Aghbolaghi, Marzieh Asadi

2018-05-28

In order to understand the population genetic diversity and structure of Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), a serious pest of sugar beet in Iran and the world, we genotyped 133 individuals from seven regions in Iran using four microsatellite loci. Significant difference was seen between the observed and expected heterozygosity in all loci. A lower observed heterozygosity than expected heterozygosity indicated a low heterozygosity in these populations. The value of F showed a high genetic differentiation, so that the mean of Fst was 0.21. Molecular analysis variance showed significant differences within and among populations with group variance accounted for 71 and 21%, respectively. No correlation was found between pair-wise Fst and geographic distance by Mantel test. Bayesian clustering analysis grouped all regions to two clusters. These data suggested that a combination of different factors, such as geographic distance, environmental condition, and physiological behavior in addition to genetic factors, could play an important role in forming variation within and between S. exigua populations.

A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Takuma, Takehisa; Masugi, Masao

2009-03-01

This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.

Symptom clusters and treatment time delay in Korean patients with ST-elevation myocardial infarction on admission.

PubMed

Kim, Hee-Sook; Eun, Sang Jun; Hwang, Jin Yong; Lee, Kun-Sei; Cho, Sung-Il

2018-05-01

Most patients with acute myocardial infarction (AMI) experience more than one symptom at onset. Although symptoms are an important early indicator, patients and physicians may have difficulty interpreting symptoms and detecting AMI at an early stage. This study aimed to identify symptom clusters among Korean patients with ST-elevation myocardial infarction (STEMI), to examine the relationship between symptom clusters and patient-related variables, and to investigate the influence of symptom clusters on treatment time delay (decision time [DT], onset-to-balloon time [OTB]). This was a prospective multicenter study with a descriptive design that used face-to-face interviews. A total of 342 patients with STEMI were included in this study. To identify symptom clusters, two-step cluster analysis was performed using SPSS software. Multinomial logistic regression to explore factors related to each cluster and multiple logistic regression to determine the effect of symptom clusters on treatment time delay were conducted. Three symptom clusters were identified: cluster 1 (classic MI; characterized by chest pain); cluster 2 (stress symptoms; sweating and chest pain); and cluster 3 (multiple symptoms; dizziness, sweating, chest pain, weakness, and dyspnea). Compared with patients in clusters 2 and 3, those in cluster 1 were more likely to have diabetes or prior MI. Patients in clusters 2 and 3, who predominantly showed other symptoms in addition to chest pain, had a significantly shorter DT and OTB than those in cluster 1. In conclusion, to decrease treatment time delay, it seems important that patients and clinicians recognize symptom clusters, rather than relying on chest pain alone. Further research is necessary to translate our findings into clinical practice and to improve patient education and public education campaigns.

A framework for graph-based synthesis, analysis, and visualization of HPC cluster job data.

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

Mayo, Jackson R.; Kegelmeyer, W. Philip, Jr.; Wong, Matthew H.

The monitoring and system analysis of high performance computing (HPC) clusters is of increasing importance to the HPC community. Analysis of HPC job data can be used to characterize system usage and diagnose and examine failure modes and their effects. This analysis is not straightforward, however, due to the complex relationships that exist between jobs. These relationships are based on a number of factors, including shared compute nodes between jobs, proximity of jobs in time, etc. Graph-based techniques represent an approach that is particularly well suited to this problem, and provide an effective technique for discovering important relationships in jobmore » queuing and execution data. The efficacy of these techniques is rooted in the use of a semantic graph as a knowledge representation tool. In a semantic graph job data, represented in a combination of numerical and textual forms, can be flexibly processed into edges, with corresponding weights, expressing relationships between jobs, nodes, users, and other relevant entities. This graph-based representation permits formal manipulation by a number of analysis algorithms. This report presents a methodology and software implementation that leverages semantic graph-based techniques for the system-level monitoring and analysis of HPC clusters based on job queuing and execution data. Ontology development and graph synthesis is discussed with respect to the domain of HPC job data. The framework developed automates the synthesis of graphs from a database of job information. It also provides a front end, enabling visualization of the synthesized graphs. Additionally, an analysis engine is incorporated that provides performance analysis, graph-based clustering, and failure prediction capabilities for HPC systems.« less

Search for a gamma-ray line feature from a group of nearby galaxy clusters with Fermi LAT Pass 8 data

NASA Astrophysics Data System (ADS)

Liang, Yun-Feng; Shen, Zhao-Qiang; Li, Xiang; Fan, Yi-Zhong; Huang, Xiaoyuan; Lei, Shi-Jun; Feng, Lei; Liang, En-Wei; Chang, Jin

2016-05-01

Galaxy clusters are the largest gravitationally bound objects in the Universe and may be suitable targets for indirect dark matter searches. With 85 months of Fermi LAT Pass 8 publicly available data, we analyze the gamma-ray emission in the direction of 16 nearby galaxy clusters with an unbinned likelihood analysis. No statistically or globally significant γ -ray line feature is identified and a tentative line signal may present at ˜43 GeV . The 95% confidence level upper limits on the velocity-averaged cross section of dark matter particles annihilating into double γ rays (i.e., ⟨σ v ⟩χχ →γ γ) are derived. Unless very optimistic boost factors of dark matter annihilation in these galaxy clusters have been assumed, such constraints are much weaker than the bounds set by the Galactic γ -ray data.

Clustering Tree-structured Data on Manifold

PubMed Central

Lu, Na; Miao, Hongyu

2016-01-01

Tree-structured data usually contain both topological and geometrical information, and are necessarily considered on manifold instead of Euclidean space for appropriate data parameterization and analysis. In this study, we propose a novel tree-structured data parameterization, called Topology-Attribute matrix (T-A matrix), so the data clustering task can be conducted on matrix manifold. We incorporate the structure constraints embedded in data into the non-negative matrix factorization method to determine meta-trees from the T-A matrix, and the signature vector of each single tree can then be extracted by meta-tree decomposition. The meta-tree space turns out to be a cone space, in which we explore the distance metric and implement the clustering algorithm based on the concepts like Fréchet mean. Finally, the T-A matrix based clustering (TAMBAC) framework is evaluated and compared using both simulated data and real retinal images to illus trate its efficiency and accuracy. PMID:26660696

A hybrid clustering approach for multivariate time series - A case study applied to failure analysis in a gas turbine.

PubMed

Fontes, Cristiano Hora; Budman, Hector

2017-11-01

A clustering problem involving multivariate time series (MTS) requires the selection of similarity metrics. This paper shows the limitations of the PCA similarity factor (SPCA) as a single metric in nonlinear problems where there are differences in magnitude of the same process variables due to expected changes in operation conditions. A novel method for clustering MTS based on a combination between SPCA and the average-based Euclidean distance (AED) within a fuzzy clustering approach is proposed. Case studies involving either simulated or real industrial data collected from a large scale gas turbine are used to illustrate that the hybrid approach enhances the ability to recognize normal and fault operating patterns. This paper also proposes an oversampling procedure to create synthetic multivariate time series that can be useful in commonly occurring situations involving unbalanced data sets. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Canine parvovirus in Australia: the role of socio-economic factors in disease clusters.

PubMed

Brady, S; Norris, J M; Kelman, M; Ward, M P

2012-08-01

To identify clusters of canine parvoviral related disease occurring in Australia during 2010 and investigate the role of socio-economic factors contributing to these clusters, reported cases of canine parvovirus were extracted from an on-line disease surveillance system. Reported residential postcode was used to locate cases, and clusters were identified using a scan statistic. Cases included in clusters were compared to those not included in such clusters with respect to human socioeconomic factors (postcode area relative socioeconomic disadvantage, economic resources, education and occupation) and dog factors (neuter status, breed, age, gender, vaccination status). During 2010, there were 1187 cases of canine parvovirus reported. Nineteen significant (P<0.05) disease clusters were identified, most commonly located in New South Wales. Eleven (58%) clusters occurred between April and July, and the average cluster length was 5.7 days. All clusters occurred in postcodes with a significantly (P<0.05) greater level of relative socioeconomic disadvantage and a lower rank in education and occupation, and it was noted that clustered cases were less likely to have been neutered (P=0.004). No significant difference (P>0.05) was found between cases reported from cluster postcodes and those not within clusters for dog age, gender, breed or vaccination status (although the latter needs to be interpreted with caution, since vaccination was absent in most of the cases). Further research is required to investigate the apparent association between indicators of poor socioeconomic status and clusters of reported canine parvovirus diseases; however these initial findings may be useful for developing geographically- and temporally-targeted prevention and disease control programs. Copyright © 2012 Elsevier Ltd. All rights reserved.

General and Specific Effects on Cattell-Horn-Carroll Broad Ability Composites: Analysis of the Woodcock-Johnson III Normative Update Cattell-Horn-Carroll Factor Clusters across Development

ERIC Educational Resources Information Center

Floyd, Randy G.; McGrew, Kevin S.; Barry, Amberly; Rafael, Fawziya; Rogers, Joshua

2009-01-01

Many school psychologists focus their interpretation on composite scores from intelligence test batteries designed to measure the broad abilities from the Cattell-Horn-Carroll theory. The purpose of this study was to investigate the general factor loadings and specificity of the broad ability composite scores from one such intelligence test…

Calibrating the Planck cluster mass scale with cluster velocity dispersions

NASA Astrophysics Data System (ADS)

Amodeo, S.; Mei, S.; Stanford, S. A.; Bartlett, J. G.; Lawrence, C. L.; Chary, R. R.; Shim, H.; Marleau, F.; Stern, D.

2017-12-01

The potential of galaxy clusters as cosmological probes critically depends on the capability to obtain accurate estimates of their mass. This will be a key measurement for the next generation of cosmological surveys, such as Euclid. The discrepancy between the cosmological parameters determined from anisotropies in the cosmic microwave background and those derived from cluster abundance measurements from the Planck satellite calls for careful evaluation of systematic biases in cluster mass estimates. For this purpose, it is crucial to use independent techniques, like analysis of the thermal emission of the intracluster medium (ICM), observed either in the X-rays or through the Sunyaev-Zeldovich (SZ) effect, dynamics of member galaxies or gravitational lensing. We discuss possible bias in the Planck SZ mass proxy, which is based on X-ray observations. Using optical spectroscopy from the Gemini Multi-Object Spectrograph of 17 Planck-selected clusters, we present new estimates of the cluster mass based on the velocity dispersion of the member galaxies and independently of the ICM properties. We show how the difference between the velocity dispersion of galaxy and dark matter particles in simulations is the primary factor limiting interpretation of dynamical cluster mass measurements at this time, and we give the first observational constraints on the velocity bias.

Real-time observation of formation and relaxation dynamics of NH4 in (CH3OH)m(NH3)n clusters.

PubMed

Yamada, Yuji; Nishino, Yoko; Fujihara, Akimasa; Ishikawa, Haruki; Fuke, Kiyokazu

2009-03-26

The formation and relaxation dynamics of NH4(CH3OH)m(NH3)n clusters produced by photolysis of ammonia-methanol mixed clusters has been observed by a time-resolved pump-probe method with femtosecond pulse lasers. From the detailed analysis of the time evolutions of the protonated cluster ions, NH4(+)(CH3OH)m(NH3)n, the kinetic model has been constructed, which consists of sequential three-step reaction: ultrafast hydrogen-atom transfer producing the radical pair (NH4-NH2)*, the relaxation process of radical-pair clusters, and dissociation of the solvated NH4 clusters. The initial hydrogen transfer hardly occurs between ammonia and methanol, implying the unfavorable formation of radical pair, (CH3OH2-NH2)*. The remarkable dependence of the time constants in each step on the number and composition of solvents has been explained by the following factors: hydrogen delocalization within the clusters, the internal conversion of the excited-state radical pair, and the stabilization of NH4 by solvation. The dependence of the time profiles on the probe wavelength is attributed to the different ionization efficiency of the NH4(CH3OH)m(NH3)n clusters.

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

PubMed Central

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons. PMID:27698666

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites.

PubMed

Irizarry, Kristopher J L; Bryden, Randall L

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus . Our results provide insight into pigment phenotypes in pythons.

Planck 2015 results. XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

NASA Astrophysics Data System (ADS)

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

2016-09-01

We present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing of background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. Improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.

Planck 2015 results: XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

DOE PAGES

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

2016-09-20

In this work, we present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing ofmore » background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. In conclusion, improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.« less

Planck 2015 results: XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

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

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

In this work, we present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing ofmore » background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. In conclusion, improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.« less

Networking between community health programs: a case study outlining the effectiveness, barriers and enablers

PubMed Central

2012-01-01

Background In India, since the 1990s, there has been a burgeoning of NGOs involved in providing primary health care. This has resulted in a complex NGO-Government interface which is difficult for lone NGOs to navigate. The Uttarakhand Cluster, India, links such small community health programs together to build NGO capacity, increase visibility and better link to the government schemes and the formal healthcare system. This research, undertaken between 1998 and 2011, aims to examine barriers and facilitators to such linking, or clustering, and the effectiveness of this clustering approach. Methods Interviews, indicator surveys and participant observation were used to document the process and explore the enablers, the barriers and the effectiveness of networks improving community health. Results The analysis revealed that when activating, framing, mobilising and synthesizing the Uttarakhand Cluster, key brokers and network players were important in bridging between organisations. The ties (or relationships) that held the cluster together included homophily around common faith, common friendships and geographical location and common mission. Self interest whereby members sought funds, visibility, credibility, increased capacity and access to trainings was also a commonly identified motivating factor for networking. Barriers to network synthesizing included lack of funding, poor communication, limited time and lack of human resources. Risk aversion and mistrust remained significant barriers to overcome for such a network. Conclusions In conclusion, specific enabling factors allowed the clustering approach to be effective at increasing access to resources, creating collaborative opportunities and increasing visibility, credibility and confidence of the cluster members. These findings add to knowledge regarding social network formation and collaboration, and such knowledge will assist in the conceptualisation, formation and success of potential health networks in India and other developing world countries. PMID:22812627

Determination of clusters and factors associated with dengue dispersion during the first epidemic related to Dengue virus serotype 4 in Vitória, Brazil

PubMed Central

Herbinger, Karl-Heinz; Cerutti Junior, Crispim; Malta Romano, Camila; de Souza Areias Cabidelle, Aline; Fröschl, Günter

2017-01-01

Dengue occurrence is partially influenced by the immune status of the population. Consequently, the introduction of a new Dengue virus serotype can trigger explosive epidemics in susceptible populations. The determination of clusters in this scenario can help to identify hotspots and understand the disease dispersion regardless of the influence of the population herd immunity. The present study evaluated the pattern and factors associated with dengue dispersion during the first epidemic related to Dengue virus serotype 4 in Vitória, Espírito Santo state, Brazil. Data on 18,861 dengue cases reported in Vitória from September 2012 to June 2013 were included in the study. The analysis of spatial variation in temporal trend was performed to detect clusters that were compared by their respective relative risk, house index, population density, and income in an ecological study. Overall, 11 clusters were detected. The time trend increase of dengue incidence in the overall study population was 636%. The five clusters that showed a lower time trend increase than the overall population presented a higher incidence in the beginning of the epidemic and, compared to the six clusters with higher time trend increase, they presented higher relative risk for their inhabitants to acquire dengue infection (P-value = 0.02) and a lower income (P-value <0.01). House index and population density did not differ between the clusters. Early increase of dengue incidence and higher relative risk for acquiring dengue infection were favored in low-income areas. Preventive actions and improvement of infrastructure in low-income areas should be prioritized in order to diminish the magnitude of dengue dispersion after the introduction of a new serotype. PMID:28388694

Networking between community health programs: a case study outlining the effectiveness, barriers and enablers.

PubMed

Grills, Nathan J; Robinson, Priscilla; Phillip, Maneesh

2012-07-19

In India, since the 1990s, there has been a burgeoning of NGOs involved in providing primary health care. This has resulted in a complex NGO-Government interface which is difficult for lone NGOs to navigate. The Uttarakhand Cluster, India, links such small community health programs together to build NGO capacity, increase visibility and better link to the government schemes and the formal healthcare system. This research, undertaken between 1998 and 2011, aims to examine barriers and facilitators to such linking, or clustering, and the effectiveness of this clustering approach. Interviews, indicator surveys and participant observation were used to document the process and explore the enablers, the barriers and the effectiveness of networks improving community health. The analysis revealed that when activating, framing, mobilising and synthesizing the Uttarakhand Cluster, key brokers and network players were important in bridging between organisations. The ties (or relationships) that held the cluster together included homophily around common faith, common friendships and geographical location and common mission. Self interest whereby members sought funds, visibility, credibility, increased capacity and access to trainings was also a commonly identified motivating factor for networking. Barriers to network synthesizing included lack of funding, poor communication, limited time and lack of human resources. Risk aversion and mistrust remained significant barriers to overcome for such a network. In conclusion, specific enabling factors allowed the clustering approach to be effective at increasing access to resources, creating collaborative opportunities and increasing visibility, credibility and confidence of the cluster members. These findings add to knowledge regarding social network formation and collaboration, and such knowledge will assist in the conceptualisation, formation and success of potential health networks in India and other developing world countries.

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

PubMed

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

2011-04-17

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

Using Cluster Analysis to Examine Husband-Wife Decision Making

ERIC Educational Resources Information Center

Bonds-Raacke, Jennifer M.

2006-01-01

Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

Exploration of the psychometric characteristics of the Liebowitz Social Anxiety Scale in a Spanish adolescent sample.

PubMed

Zubeidat, Ihab; Salinas, José María; Sierra, Juan Carlos

2008-01-01

Social phobia is an excessive concern about scrutiny by other people in situations the person considers embarrassing or humiliating. The purpose of this study is to explore the factor structure, reliability, and validity of the social fear and social avoidance subscales of the Liebowitz Social Anxiety Scale (LSAS) and to analyze the score distribution of both subscales. To this end, we assessed a sample of 1,012 Spanish adolescents attending school. The results of a first-order factor analysis indicate the existence of a dominant factor in both subscales of the LSAS--as well as three other less relevant factors--and explain most of the variance of the subscales. The internal consistency of the first factor was quite high in both subscales. The LSAS and its two subscales showed adequate theoretical validity with different variables related to social interaction. Finally, the different scores obtained in both subscales make it possible to group adolescents into three clusters with different characteristics. A study of the sociodemographic variables of the components of the clusters showed a significant relation only with sex. 2007 Wiley-Liss, Inc.

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).

Confirmation of Nosocomial Transmission of Hepatitis C Virus by Phylogenetic Analysis of the NS5-B Region

PubMed Central

Norder, Heléne; Bergström, Åsa; Uhnoo, Ingrid; Aldén, Jöran; Weiss, Lars; Czajkowski, Jan; Magnius, Lars

1998-01-01

Four hepatitis C virus transmission chains at three dialysis units were disclosed by limited sequencing; three of these were disclosed by analysis of the NS5-B region of the genome. Dialysis on the same shift as that during which infected patients were dialyzed was the common factor for seven patients in two chains. Two nurses exposed to needle sticks and their sources of infection constituted two other chains. The strains of three chains belonged to subtype 1a and formed clusters with an intrachain variability of 0 to 6 nucleotides compared to 8 to 37 nucleotides for unrelated strains within this subtype. The clusters were supported by bootstrap values ranging from 89 to 100%. PMID:9738071

Did factory girls make bad mothers? Women's labor market experience, motherhood, and children's mortality risks in the past.

PubMed

Janssens, Angélique; Pelzer, Ben

2012-01-01

Prior research has suggested that the quality of maternal care given to infants and small children plays an important role in the strong clustering of children's deaths. In this article, we investigate the quality of maternal care provided by those women who most nineteenth-century social commentators declared would never make good housewives or mothers: the young girls and women working in textile mills. We carried out this examination using an analysis of children's mortality risks in two textile cities in The Netherlands between roughly 1900 and 1930. Our analysis suggests that these children's clustered mortality risks cannot have resulted from either their mothers' labor market experience or biological or genetic factors.

A psychometric investigation of the hypersexual disorder screening inventory among highly sexually active gay and bisexual men: an item response theory analysis.

PubMed

Parsons, Jeffrey T; Rendina, H Jonathon; Ventuneac, Ana; Cook, Karon F; Grov, Christian; Mustanski, Brian

2013-12-01

The Hypersexual Disorder Screening Inventory (HDSI) was designed as an instrument for the screening of hypersexuality by the American Psychiatric Association's taskforce for the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. Our study sought to conduct a psychometric analysis of the HDSI, including an investigation of its underlying structure and reliability utilizing item response theory (IRT) modeling, and an examination of its polythetic scoring criteria in comparison to a standard dimensionally based cutoff score. We examined a diverse group of 202 highly sexually active gay and bisexual men in New York City. We conducted psychometric analyses of the HDSI, including both confirmatory factor analysis of its structure and IRT analysis of the item and scale reliabilities. We utilized the HDSI. The HDSI adequately fit a single-factor solution, although there was evidence that two of the items may measure a second factor that taps into sex as a form of coping. The scale showed evidence of strong reliability across much of the continuum of hypersexuality, and results suggested that, in addition to the proposed polythetic scoring criteria, a cutoff score of 20 on the severity index might be used for preliminary classification of HD. The HDSI was found to be highly reliable, and results suggested that a unidimensional, quantitative conception of hypersexuality with a clinically relevant cutoff score may be more appropriate than a qualitative syndrome comprised of multiple distinct clusters of problems. However, we also found preliminary evidence that three clusters of symptoms may constitute an HD syndrome as opposed to the two clusters initially proposed. Future research is needed to determine which of these issues are characteristic of the hypersexuality and HD constructs themselves and which are more likely to be methodological artifacts of the HDSI. © 2013 International Society for Sexual Medicine.

Neutrino masses, scale-dependent growth, and redshift-space distortions

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

Hernández, Oscar F., E-mail: oscarh@physics.mcgill.ca

2017-06-01

Massive neutrinos leave a unique signature in the large scale clustering of matter. We investigate the wavenumber dependence of the growth factor arising from neutrino masses and use a Fisher analysis to determine the aspects of a galaxy survey needed to measure this scale dependence.

Multidimensional Structure of the Hypomanic Personality Scale

ERIC Educational Resources Information Center

Schalet, Benjamin D.; Durbin, C. Emily; Revelle, William

2011-01-01

The structure of the Hypomanic Personality Scale was explored in a sample of young adults (N = 884); resulting structures were validated on subsamples with measures of personality traits, internalizing symptoms, and externalizing behaviors. Hierarchical cluster analysis and estimates of general factor saturation suggested the presence of a weak…

Understanding clusters of risk factors across different environmental and social contexts for the prediction of injuries among Canadian youth.

PubMed

Russell, K; Davison, C; King, N; Pike, I; Pickett, W

2016-05-01

Among Canadian youth, injury is the most common reason for presentation to the emergency department. Youth who commonly engage in multiple risk-taking behaviours are at greater risk for injury, but is it unknown if this phenomenon is more pronounced in different contexts. We aimed to study relationships between risk-taking behaviours and injury, and variations in such relationships between different environmental and social contexts, among youth in Canada. Risk-taking behaviour and injury outcome data were collected from grade 9 to 10 students using the 2009-2010 (Cycle 6) of the Health Behaviour in School-Aged Children Survey (n=10,429). Principal components analysis was used to identify clusters of risk-taking behaviours. Within each identified cluster, the degree of risk-taking was categorized into quartiles from lowest to highest engagement in the behaviours. Risk ratios with 95% confidence intervals were calculated to determine the association between the risk of any injury and the degree of risk-taking behaviour specific to the cluster. Clusters were then examined across home, school, neighbourhood and sport contexts. Four clusters of risk-taking behaviour were identified which were labelled as "gateway substance use", "hard drugs and weapons", "overt risk-taking", and "physical activity". Each cluster was related to injury occurrence in a graded fashion. Clusters of risk behaviour were most strongly associated with injuries sustained in neighbourhood settings, and expectedly, increasing physical activity behaviours were associated with increased risk of sport injuries and injuries occurring at school. This study furthers understanding of clustered risk-taking phenomena that put youth at increasing levels of injury risk. Higher risks for injury and associated gradients were observed in less structured contexts such as neighbourhoods. In contrast, clustered physical activity behaviours were most related to school injury or sport injury and were more likely to be sustained in a supervised context. Understanding the clustered and cumulative nature of risk-behaviours, and how these vary by environmental and social context, helps to explain potential mechanisms of injury as well as modifiable factors that may be important avenues for intervention. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Clusters of Midlife Women by Physical Activity and Their Racial/Ethnic Differences

PubMed Central

Im, Eun-Ok; Ko, Young; Chee, Eunice; Chee, Wonshik; Mao, Jun James

2016-01-01

Objective The purpose of this study was to identify clusters of midlife women by physical activity and to determine racial/ethnic differences in physical activities in each cluster. Methods This was a secondary analysis of the data from 542 women (157 Non-Hispanic [NH] Whites, 127 Hispanics, 135 NH African Americans, and 123 NH Asian) in a larger Internet study on midlife women’s attitudes toward physical activity. The instruments included the Barriers to Health Activities Scale, the Physical Activity Assessment Inventory, the Questions on Attitudes toward Physical Activity, Subjective Norm, Perceived Behavioral Control, and Behavioral Intention, and the Kaiser Physical Activity Survey. The data were analyzed using hierarchical cluster analyses, ANOVA, and multinominal logistic analyses. Results A three cluster solution was adopted: Cluster 1 (high active living and sports/exercise activity group; 48%), Cluster 2 (high household/caregiving and occupational activity group; 27%), and Cluster 3 (low active living and sports/exercise activity group; 26%). There were significant racial/ethnic differences in occupational activities of Clusters 1 and 3 (all p<.01). Compared with Cluster 1, Cluster 2 tended to have lower family income, less access to health care, higher unemployment, higher perceived barriers scores, and lower social influences scores (all p<.01). Compared with Cluster 1, Cluster 3 tended to have greater obesity, less access to health care, higher perceived barriers scores, more negative attutides toward physical activity, and lower self-efficacy scores (all p<.01). Conclusions Midlife women’s unique patterns of physical activity and their associated factors need to be considered in future intervention development. PMID:27846052

The link between parental allergy and offspring allergic and nonallergic rhinitis.

PubMed

Westman, M; Kull, I; Lind, T; Melén, E; Stjärne, P; Toskala, E; Wickman, M; Bergström, A

2013-12-01

Parental allergy-related disease increases the risk for rhinitis, but it remains unknown how different phenotypes of parental allergy affect this risk. The aim of this study was to investigate how parental hay fever, asthma, and eczema affect the risk of allergic rhinitis (AR) and nonallergic rhinitis (NAR) at 8 years of age. Information on 2413 children from a population-based birth cohort was used combining questionnaire data and IgE to inhalant allergens. Logistic regression was used to estimate the association between parental allergy-related disease and AR and NAR. In addition, cluster analysis was used to search for latent phenotypes of heredity likely to be associated with AR and NAR. At age 8 years, 13.8% of the children had AR, while 6.4% had NAR. Parental isolated hay fever increased the odds of AR (OR 2.2, 95% CI 1.6-3.2), whereas isolated asthma or eczema did not. The odds of NAR increased when one parent had two or more allergy-related diseases. In the cluster analysis, the highest proportion of AR, 37.5%, was seen in a cluster where both parents had hay fever and pollen allergy and that of NAR, 11.0%, in a cluster where one parent had hay fever, pollen allergy, and eczema. Parental allergy-related disease may be an important risk factor for NAR as well as AR, and the risk is comparable for maternal and paternal allergy. Parental hay fever seems to be the dominating hereditary risk factor for AR. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Transforming Graph Data for Statistical Relational Learning

DTIC Science & Technology

2012-10-01

Jordan, 2003), PLSA (Hofmann, 1999), ? Classification via RMN (Taskar et al., 2003) or SVM (Hasan, Chaoji, Salem , & Zaki, 2006) ? Hierarchical...dimensionality reduction methods such as Principal 407 Rossi, McDowell, Aha, & Neville Component Analysis (PCA), Principal Factor Analysis ( PFA ), and...clustering algorithm. Journal of the Royal Statistical Society. Series C, Applied statistics, 28, 100–108. Hasan, M. A., Chaoji, V., Salem , S., & Zaki, M

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

Exploration and validation of clusters of physically abused children.

PubMed

Sabourin Ward, Caryn; Haskett, Mary E

2008-05-01

Cluster analysis was used to enhance understanding of heterogeneity in social adjustment of physically abused children. Ninety-eight physically abused children (ages 5-10) were clustered on the basis of social adjustment, as measured by observed behavior with peers on the school playground and by teacher reports of social behavior. Seventy-seven matched nonabused children served as a comparison sample. Clusters were validated on the basis of observed parental sensitivity, parents' self-reported disciplinary tactics, and children's social information processing operations (i.e., generation of solutions to peer relationship problems and attributions of peer intentions in social situations). Three subgroups of physically abused children emerged from the cluster analysis; clusters were labeled Socially Well Adjusted, Hanging in There, and Social Difficulties. Examination of cluster differences on risk and protective factors provided substantial evidence in support of the external validity of the three-cluster solution. Specifically, clusters differed significantly in attributions of peer intent and in parenting (i.e., sensitivity and harshness of parenting). Clusters also differed in the ways in which they were similar to, or different from, the comparison group of nonabused children. Results supported the contention that there were clinically relevant subgroups of physically abused children with potentially unique treatment needs. Findings also pointed to the relevance of social information processing operations and parenting context in understanding diversity among physically abused children. Pending replication, findings provide support for the importance of considering unique treatment of needs among physically abused children. A singular approach to intervention is unlikely to be effective for these children. For example, some physically abused children might need a more intensive focus on development of prosocial skills in relationships with peers while the prosocial skills of other abused children will be developmentally appropriate. In contrast, most physically abused children might benefit from training in social problem-solving skills. Findings also point to the importance of promoting positive parenting practices in addition to reducing harsh discipline of physically abusive parents.

Genome-wide organization and expression profiling of the NAC transcription factor family in potato (Solanum tuberosum L.).

PubMed

Singh, Anil Kumar; Sharma, Vishal; Pal, Awadhesh Kumar; Acharya, Vishal; Ahuja, Paramvir Singh

2013-08-01

NAC [no apical meristem (NAM), Arabidopsis thaliana transcription activation factor [ATAF1/2] and cup-shaped cotyledon (CUC2)] proteins belong to one of the largest plant-specific transcription factor (TF) families and play important roles in plant development processes, response to biotic and abiotic cues and hormone signalling. Our genome-wide analysis identified 110 StNAC genes in potato encoding for 136 proteins, including 14 membrane-bound TFs. The physical map positions of StNAC genes on 12 potato chromosomes were non-random, and 40 genes were found to be distributed in 16 clusters. The StNAC proteins were phylogenetically clustered into 12 subgroups. Phylogenetic analysis of StNACs along with their Arabidopsis and rice counterparts divided these proteins into 18 subgroups. Our comparative analysis has also identified 36 putative TNAC proteins, which appear to be restricted to Solanaceae family. In silico expression analysis, using Illumina RNA-seq transcriptome data, revealed tissue-specific, biotic, abiotic stress and hormone-responsive expression profile of StNAC genes. Several StNAC genes, including StNAC072 and StNAC101that are orthologs of known stress-responsive Arabidopsis RESPONSIVE TO DEHYDRATION 26 (RD26) were identified as highly abiotic stress responsive. Quantitative real-time polymerase chain reaction analysis largely corroborated the expression profile of StNAC genes as revealed by the RNA-seq data. Taken together, this analysis indicates towards putative functions of several StNAC TFs, which will provide blue-print for their functional characterization and utilization in potato improvement.

Cohort study on clustering of lifestyle risk factors and understanding its association with stress on health and wellbeing among school teachers in Malaysia (CLUSTer)--a study protocol.

PubMed

Moy, Foong Ming; Hoe, Victor Chee Wai; Hairi, Noran Naqiah; Buckley, Brian; Wark, Petra A; Koh, David; Bueno-de-Mesquita, H Bas; Bulgiba, Awang M

2014-06-17

The study on Clustering of Lifestyle risk factors and Understanding its association with Stress on health and wellbeing among school Teachers in Malaysia (CLUSTer) is a prospective cohort study which aims to extensively study teachers in Malaysia with respect to clustering of lifestyle risk factors and stress, and subsequently, to follow-up the population for important health outcomes. This study is being conducted in six states within Peninsular Malaysia. From each state, schools from each district are randomly selected and invited to participate in the study. Once the schools agree to participate, all teachers who fulfilled the inclusion criteria are invited to participate. Data collection includes a questionnaire survey and health assessment. Information collected in the questionnaire includes socio-demographic characteristics, participants' medical history and family history of chronic diseases, teaching characteristics and burden, questions on smoking, alcohol consumption and physical activities (IPAQ); a food frequency questionnaire, the job content questionnaire (JCQ); depression, anxiety and stress scale (DASS21); health related quality of life (SF12-V2); Voice Handicap Index 10 on voice disorder, questions on chronic pain, sleep duration and obstetric history for female participants. Following blood drawn for predefined clinical tests, additional blood and urine specimens are collected and stored for future analysis. Active follow up of exposure and health outcomes will be carried out every two years via telephone or face to face contact. Data collection started in March 2013 and as of the end of March 2014 has been completed for four states: Kuala Lumpur, Selangor, Melaka and Penang. Approximately 6580 participants have been recruited. The first round of data collection and blood sampling is expected to be completed by the end of 2014 with an expected 10,000 participants recruited. Our study will provide a good basis for exploring the clustering of lifestyle risk factors and stress and its association with major chronic medical conditions such as obesity, hypertension, impaired glucose tolerance, diabetes mellitus, coronary heart diseases, kidney failure and cancers among teachers.

Cohort study on clustering of lifestyle risk factors and understanding its association with stress on health and wellbeing among school teachers in Malaysia (CLUSTer) – a study protocol

PubMed Central

2014-01-01

Background The study on Clustering of Lifestyle risk factors and Understanding its association with Stress on health and wellbeing among school Teachers in Malaysia (CLUSTer) is a prospective cohort study which aims to extensively study teachers in Malaysia with respect to clustering of lifestyle risk factors and stress, and subsequently, to follow-up the population for important health outcomes. Method/design This study is being conducted in six states within Peninsular Malaysia. From each state, schools from each district are randomly selected and invited to participate in the study. Once the schools agree to participate, all teachers who fulfilled the inclusion criteria are invited to participate. Data collection includes a questionnaire survey and health assessment. Information collected in the questionnaire includes socio-demographic characteristics, participants’ medical history and family history of chronic diseases, teaching characteristics and burden, questions on smoking, alcohol consumption and physical activities (IPAQ); a food frequency questionnaire, the job content questionnaire (JCQ); depression, anxiety and stress scale (DASS21); health related quality of life (SF12-V2); Voice Handicap Index 10 on voice disorder, questions on chronic pain, sleep duration and obstetric history for female participants. Following blood drawn for predefined clinical tests, additional blood and urine specimens are collected and stored for future analysis. Active follow up of exposure and health outcomes will be carried out every two years via telephone or face to face contact. Data collection started in March 2013 and as of the end of March 2014 has been completed for four states: Kuala Lumpur, Selangor, Melaka and Penang. Approximately 6580 participants have been recruited. The first round of data collection and blood sampling is expected to be completed by the end of 2014 with an expected 10,000 participants recruited. Discussion Our study will provide a good basis for exploring the clustering of lifestyle risk factors and stress and its association with major chronic medical conditions such as obesity, hypertension, impaired glucose tolerance, diabetes mellitus, coronary heart diseases, kidney failure and cancers among teachers. PMID:24938383

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

DOE PAGES

Vasylkivska, Veronika S.; Huerta, Nicolas J.

2017-06-24

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