[Kriging analysis of vegetation index depression in peak cluster karst area].

PubMed

Yang, Qi-Yong; Jiang, Zhong-Cheng; Ma, Zu-Lu; Cao, Jian-Hua; Luo, Wei-Qun; Li, Wen-Jun; Duan, Xiao-Fang

2012-04-01

In order to master the spatial variability of the normal different vegetation index (NDVI) of the peak cluster karst area, taking into account the problem of the mountain shadow "missing" information of remote sensing images existing in the karst area, NDVI of the non-shaded area were extracted in Guohua Ecological Experimental Area, in Pingguo County, Guangxi applying image processing software, ENVI. The spatial variability of NDVI was analyzed applying geostatistical method, and the NDVI of the mountain shadow areas was predicted and validated. The results indicated that the NDVI of the study area showed strong spatial variability and spatial autocorrelation resulting from the impact of intrinsic factors, and the range was 300 m. The spatial distribution maps of the NDVI interpolated by Kriging interpolation method showed that the mean of NDVI was 0.196, apparently strip and block. The higher NDVI values distributed in the area where the slope was greater than 25 degrees of the peak cluster area, while the lower values distributed in the area such as foot of the peak cluster and depression, where slope was less than 25 degrees. Kriging method validation results show that interpolation has a very high prediction accuracy and could predict the NDVI of the shadow area, which provides a new idea and method for monitoring and evaluation of the karst rocky desertification.

Prediction models for clustered data: comparison of a random intercept and standard regression model

PubMed Central

2013-01-01

Background When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Methods Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. Results The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. Conclusion The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters. PMID:23414436

Prediction models for clustered data: comparison of a random intercept and standard regression model.

PubMed

Bouwmeester, Walter; Twisk, Jos W R; Kappen, Teus H; van Klei, Wilton A; Moons, Karel G M; Vergouwe, Yvonne

2013-02-15

When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters.

Sleep and chronobiology in cluster headache.

PubMed

Barloese, M; Lund, N; Petersen, A; Rasmussen, M; Jennum, P; Jensen, R

2015-10-01

Cluster headache (CH) is the headache disorder with the strongest chronobiological traits. The severe attacks of pain occur with diurnal and annual rhythmicity but the precise rhythm and involvement of potential zeitgebers is unknown. Patients complain of poor sleep quality yet this has never been studied. We investigated triggers, rhythms, sleep quality and chronotypes in CH. Patients and controls completed questionnaires and structured interviews composed of new and previously validated parts including the Pittsburgh Sleep Quality Index (PSQI) and Morningness-Eveningness Questionnaire (MEQ). Patients were characterized by a CH index, a unified measure of headache burden. A total of 275 CH patients and 145 matched controls were included. The most common trigger was sleep (80%) and a relationship between clusters and daylight was identified. Of the patients, 82.2% reported diurnal and 56% annual rhythmicity. Patients reported impaired sleep quality (PSQI) (p < 0.0001) and an inverse relationship between time passed since last attack and sleep quality was identified (p < 0.0001). The CH index was positively related to the PSQI (p < 0.0001). Diurnally, CH exhibits a relationship with night-time and annually with daylight hours. Patients' sleep quality is reduced compared with controls. Results suggest a complex relationship as sleep quality improves between clusters, but remains pathological. © International Headache Society 2015.

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

NASA Astrophysics Data System (ADS)

Bock, Fabian; Xia, Karen; Sester, Monika

2018-05-01

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

Method for exploratory cluster analysis and visualisation of single-trial ERP ensembles.

PubMed

Williams, N J; Nasuto, S J; Saddy, J D

2015-07-30

The validity of ensemble averaging on event-related potential (ERP) data has been questioned, due to its assumption that the ERP is identical across trials. Thus, there is a need for preliminary testing for cluster structure in the data. We propose a complete pipeline for the cluster analysis of ERP data. To increase the signal-to-noise (SNR) ratio of the raw single-trials, we used a denoising method based on Empirical Mode Decomposition (EMD). Next, we used a bootstrap-based method to determine the number of clusters, through a measure called the Stability Index (SI). We then used a clustering algorithm based on a Genetic Algorithm (GA) to define initial cluster centroids for subsequent k-means clustering. Finally, we visualised the clustering results through a scheme based on Principal Component Analysis (PCA). After validating the pipeline on simulated data, we tested it on data from two experiments - a P300 speller paradigm on a single subject and a language processing study on 25 subjects. Results revealed evidence for the existence of 6 clusters in one experimental condition from the language processing study. Further, a two-way chi-square test revealed an influence of subject on cluster membership. Our analysis operates on denoised single-trials, the number of clusters are determined in a principled manner and the results are presented through an intuitive visualisation. Given the cluster structure in some experimental conditions, we suggest application of cluster analysis as a preliminary step before ensemble averaging. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Tai, Lin-Ru; Chou, Chang-Wei; Lee, I-Fang

In this study, we used a multiple copy (EGFP){sub 3} reporter system to establish a numeric nuclear index system to assess the degree of nuclear import. The system was first validated by a FRAP assay, and then was applied to evaluate the essential and multifaceted nature of basic amino acid clusters during the nuclear import of ribosomal protein L7. The results indicate that the sequence context of the basic cluster determines the degree of nuclear import, and that the number of basic residues in the cluster is irrelevant; rather the position of the pertinent basic residues is crucial. Moreover, itmore » also found that the type of carrier protein used by basic cluster has a great impact on the degree of nuclear import. In case of L7, importin β2 or importin β3 are preferentially used by clusters with a high import efficiency, notwithstanding that other importins are also used by clusters with a weaker level of nuclear import. Such a preferential usage of multiple basic clusters and importins to gain nuclear entry would seem to be a common practice among ribosomal proteins in order to ensure their full participation in high rate ribosome synthesis. - Highlights: ► We introduce a numeric index system that represents the degree of nuclear import. ► The rate of nuclear import is dictated by the sequence context of the basic cluster. ► Importin β2 and β3 were mainly responsible for the N4 mediated nuclear import.« less

Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

PubMed Central

Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

2013-01-01

Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674

The improved physical activity index for measuring physical activity in EPIC Germany.

PubMed

Wientzek, Angelika; Vigl, Matthäus; Steindorf, Karen; Brühmann, Boris; Bergmann, Manuela M; Harttig, Ulrich; Katzke, Verena; Kaaks, Rudolf; Boeing, Heiner

2014-01-01

In the European Investigation into Cancer and Nutrition study (EPIC), physical activity (PA) has been indexed as a cross-tabulation between PA at work and recreational activity. As the proportion of non-working participants increases, other categorization strategies are needed. Therefore, our aim was to develop a valid PA index for this population, which will also be able to express PA continuously. In the German EPIC centers Potsdam and Heidelberg, a clustered sample of 3,766 participants was re-invited to the study center. 1,615 participants agreed to participate and 1,344 participants were finally included in this study. PA was measured by questionnaires on defined activities and a 7-day combined heart rate and acceleration sensor. In a training sample of 433 participants, the Improved Physical Activity Index (IPAI) was developed. Its performance was evaluated in a validation sample of 911 participants and compared with the Cambridge Index and the Total PA Index. The IPAI consists of items covering five areas including PA at work, sport, cycling, television viewing, and computer use. The correlations of the IPAI with accelerometer counts in the training and validation sample ranged r = 0.40-0.43 and with physical activity energy expenditure (PAEE) r = 0.33-0.40 and were higher than for the Cambridge Index and the Total PA Index previously applied in EPIC. In non-working participants the IPAI showed higher correlations than the Cambridge Index and the Total PA Index, with r = 0.34 for accelerometer counts and r = 0.29 for PAEE. In conclusion, we developed a valid physical activity index which is able to express PA continuously as well as to categorize participants according to their PA level. In populations with increasing rates of non-working people the performance of the IPAI is better than the established indices used in EPIC.

The Improved Physical Activity Index for Measuring Physical Activity in EPIC Germany

PubMed Central

Wientzek, Angelika; Vigl, Matthäus; Steindorf, Karen; Brühmann, Boris; Bergmann, Manuela M.; Harttig, Ulrich; Katzke, Verena; Kaaks, Rudolf; Boeing, Heiner

2014-01-01

In the European Investigation into Cancer and Nutrition study (EPIC), physical activity (PA) has been indexed as a cross-tabulation between PA at work and recreational activity. As the proportion of non-working participants increases, other categorization strategies are needed. Therefore, our aim was to develop a valid PA index for this population, which will also be able to express PA continuously. In the German EPIC centers Potsdam and Heidelberg, a clustered sample of 3,766 participants was re-invited to the study center. 1,615 participants agreed to participate and 1,344 participants were finally included in this study. PA was measured by questionnaires on defined activities and a 7-day combined heart rate and acceleration sensor. In a training sample of 433 participants, the Improved Physical Activity Index (IPAI) was developed. Its performance was evaluated in a validation sample of 911 participants and compared with the Cambridge Index and the Total PA Index. The IPAI consists of items covering five areas including PA at work, sport, cycling, television viewing, and computer use. The correlations of the IPAI with accelerometer counts in the training and validation sample ranged r = 0.40–0.43 and with physical activity energy expenditure (PAEE) r = 0.33–0.40 and were higher than for the Cambridge Index and the Total PA Index previously applied in EPIC. In non-working participants the IPAI showed higher correlations than the Cambridge Index and the Total PA Index, with r = 0.34 for accelerometer counts and r = 0.29 for PAEE. In conclusion, we developed a valid physical activity index which is able to express PA continuously as well as to categorize participants according to their PA level. In populations with increasing rates of non-working people the performance of the IPAI is better than the established indices used in EPIC. PMID:24642812

[Psychometric properties of the third version of family adaptability and cohesion evaluation scales (FACES-III): a study of peruvian adolescents].

PubMed

Bazo-Alvarez, Juan Carlos; Bazo-Alvarez, Oscar Alfredo; Aguila, Jeins; Peralta, Frank; Mormontoy, Wilfredo; Bennett, Ian M

2016-01-01

Our aim was to evaluate the psychometric properties of the FACES-III among Peruvian high school students. This is a psychometric cross-sectional study. A probabilistic sampling was applied, defined by three stages: stratum one (school), stratum two (grade) and cluster (section). The participants were 910 adolescent students of both sexes, between 11 and 18 years of age. The instrument was also the object of study: the Olson's FACES-III. The analysis included a review of the structure / construct validity of the measure by factor analysis and assessment of internal consistency (reliability). The real-cohesion scale had moderately high reliability (Ω=.85) while the real-flexibility scale had moderate reliability (Ω=.74). The reliability found for the ideal-cohesion was moderately high (Ω=.89) like for the scale of ideal-flexibility (Ω=.86). Construct validity was confirmed by the goodness of fit of a two factor model (cohesion and flexibility) with 10 items each [Adjusted goodness of fit index (AGFI) = 0.96; Expected Cross Validation Index (ECVI) = 0.87; Normed fit index (NFI) = 0.93; Goodness of fit index (GFI) = 0.97; Root mean square error of approximation (RMSEA) = 0.06]. FACES-III has sufficient reliability and validity to be used in Peruvian adolescents for the purpose of group or individual assessment.

Development of a Two-fluid Drag Law for Clustered Particles using Direct Numerical Simulation and Validation through Experiments

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

Gokaltun, Seckin; Munroe, Norman; Subramaniam, Shankar

2014-12-31

This study presents a new drag model, based on the cohesive inter-particle forces, implemented in the MFIX code. This new drag model combines an existing standard model in MFIX with a particle-based drag model based on a switching principle. Switches between the models in the computational domain occur where strong particle-to-particle cohesion potential is detected. Three versions of the new model were obtained by using one standard drag model in each version. Later, performance of each version was compared against available experimental data for a fluidized bed, published in the literature and used extensively by other researchers for validation purposes.more » In our analysis of the results, we first observed that standard models used in this research were incapable of producing closely matching results. Then, we showed for a simple case that a threshold is needed to be set on the solid volume fraction. This modification was applied to avoid non-physical results for the clustering predictions, when governing equation of the solid granular temperate was solved. Later, we used our hybrid technique and observed the capability of our approach in improving the numerical results significantly; however, improvement of the results depended on the threshold of the cohesive index, which was used in the switching procedure. Our results showed that small values of the threshold for the cohesive index could result in significant reduction of the computational error for all the versions of the proposed drag model. In addition, we redesigned an existing circulating fluidized bed (CFB) test facility in order to create validation cases for clustering regime of Geldart A type particles.« less

Pipelining Architecture of Indexing Using Agglomerative Clustering

NASA Astrophysics Data System (ADS)

Goyal, Deepika; Goyal, Deepti; Gupta, Parul

2010-11-01

The World Wide Web is an interlinked collection of billions of documents. Ironically the huge size of this collection has become an obstacle for information retrieval. To access the information from Internet, search engine is used. Search engine retrieve the pages from indexer. This paper introduce a novel pipelining technique for structuring the core index-building system that substantially reduces the index construction time and also clustering algorithm that aims at partitioning the set of documents into ordered clusters so that the documents within the same cluster are similar and are being assigned the closer document identifiers. After assigning to the clusters it creates the hierarchy of index so that searching is efficient. It will make the super cluster then mega cluster by itself. The pipeline architecture will create the index in such a way that it will be efficient in space and time saving manner. It will direct the search from higher level to lower level of index or higher level of clusters to lower level of cluster so that the user gets the possible match result in time saving manner. As one cluster is making by taking only two clusters so it search is limited to two clusters for lower level of index and so on. So it is efficient in time saving manner.

Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach

PubMed Central

Li, Zhao-Liang

2018-01-01

Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM*) approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval numbers and the spectral uncertainty. The classification results based on a hyperspectral dataset using the FCM, IT2FCM, and the proposed improved IT2FCM* algorithms show that the IT2FCM* method plays the best performance according to the clustering accuracy. In this paper, in order to validate and demonstrate the separability of the IT2FCM*, four type-I fuzzy validity indexes are employed, and a comparative analysis of these fuzzy validity indexes also applied in FCM and IT2FCM methods are made. These four indexes are also applied into different spatial and spectral resolution datasets to analyze the effects of spectral and spatial scaling factors on the separability of FCM, IT2FCM, and IT2FCM* methods. The results of these validity indexes from the hyperspectral datasets show that the improved IT2FCM* algorithm have the best values among these three algorithms in general. The results demonstrate that the IT2FCM* exhibits good performance in hyperspectral remote-sensing image classification because of its ability to handle hyperspectral uncertainty. PMID:29373548

Detection of the power lines in UAV remote sensed images using spectral-spatial methods.

PubMed

Bhola, Rishav; Krishna, Nandigam Hari; Ramesh, K N; Senthilnath, J; Anand, Gautham

2018-01-15

In this paper, detection of the power lines on images acquired by Unmanned Aerial Vehicle (UAV) based remote sensing is carried out using spectral-spatial methods. Spectral clustering was performed using Kmeans and Expectation Maximization (EM) algorithm to classify the pixels into the power lines and non-power lines. The spectral clustering methods used in this study are parametric in nature, to automate the number of clusters Davies-Bouldin index (DBI) is used. The UAV remote sensed image is clustered into the number of clusters determined by DBI. The k clustered image is merged into 2 clusters (power lines and non-power lines). Further, spatial segmentation was performed using morphological and geometric operations, to eliminate the non-power line regions. In this study, UAV images acquired at different altitudes and angles were analyzed to validate the robustness of the proposed method. It was observed that the EM with spatial segmentation (EM-Seg) performed better than the Kmeans with spatial segmentation (Kmeans-Seg) on most of the UAV images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dietary patterns and quality in West-African immigrants in Madrid

PubMed Central

Delisle, Hélène F; Vioque, Jesús; Gil, Augusta

2009-01-01

Background Eating patterns of immigrants deserve to be better documented because they may reflect the extent of acculturation and associated health risks. The study assessed dietary patterns and quality in Bubi immigrants (from Equatorial Guinea) using cluster analysis and comparing different diet quality indexes. Methods A random sample of 83 Bubi men and 130 women living in Madrid were studied. A 99-item food frequency questionnaire was administered, body weights and heights were self-reported and socio-demographic and health information was collected during interviews. Usual intakes were collapsed into 19 food groups. Cluster analysis of standardized food intakes per 1000 kcalories was performed. Dietary quality was appraised using the Alternative Mediterranean Diet Score, the Alternative Healthy Eating Index and scores of micronutrient adequacy and prevention based on WHO/FAO recommendations. Results Two dietary patterns were identified. The 'Healthier' pattern, so confirmed by two dietary quality indexes, featured a higher consumption of fish, fruits, vegetables, legumes, dairy products and bread while the 'Western' pattern included more processed meat, animal fat, and sweetened foods and drinks. One third of the subjects were in the 'Healthier' food cluster, with the same proportion of men and women. Age ≥ 30 and residence in Madrid ≥ 11 years were independently associated with the healthier diet. Consumption of traditional foods was unrelated to dietary pattern, however. Overall, Bubi diets were somewhat protective because of high intakes of fruits and vegetables and monounsaturated fat (olive oil), but not with respect to sugar, cholesterol, omega-3 fatty acids and fibre. Less than two thirds of subjects had adequate intakes of iron, calcium and folate in both dietary phenotypes. Body mass index, physical exercise, and self-reported health and cardiovascular disease condition showed no significant association with the dietary pattern. Conclusion Cluster analysis combined with dietary quality assessment facilitates the interpretation of dietary patterns, but choosing the appropriate quality indexes is a problem. A small number of such indexes should be standardized and validated for international use. In the group studied, younger subjects and more recent immigrants were more likely to have a 'Western' pattern and should be a priority target for nutrition communication. PMID:19166606

Application of hybrid clustering using parallel k-means algorithm and DIANA algorithm

NASA Astrophysics Data System (ADS)

Umam, Khoirul; Bustamam, Alhadi; Lestari, Dian

2017-03-01

DNA is one of the carrier of genetic information of living organisms. Encoding, sequencing, and clustering DNA sequences has become the key jobs and routine in the world of molecular biology, in particular on bioinformatics application. There are two type of clustering, hierarchical clustering and partitioning clustering. In this paper, we combined two type clustering i.e. K-Means (partitioning clustering) and DIANA (hierarchical clustering), therefore it called Hybrid clustering. Application of hybrid clustering using Parallel K-Means algorithm and DIANA algorithm used to clustering DNA sequences of Human Papillomavirus (HPV). The clustering process is started with Collecting DNA sequences of HPV are obtained from NCBI (National Centre for Biotechnology Information), then performing characteristics extraction of DNA sequences. The characteristics extraction result is store in a matrix form, then normalize this matrix using Min-Max normalization and calculate genetic distance using Euclidian Distance. Furthermore, the hybrid clustering is applied by using implementation of Parallel K-Means algorithm and DIANA algorithm. The aim of using Hybrid Clustering is to obtain better clusters result. For validating the resulted clusters, to get optimum number of clusters, we use Davies-Bouldin Index (DBI). In this study, the result of implementation of Parallel K-Means clustering is data clustered become 5 clusters with minimal IDB value is 0.8741, and Hybrid Clustering clustered data become 13 sub-clusters with minimal IDB values = 0.8216, 0.6845, 0.3331, 0.1994 and 0.3952. The IDB value of hybrid clustering less than IBD value of Parallel K-Means clustering only that perform at 1ts stage. Its means clustering using Hybrid Clustering have the better result to clustered DNA sequence of HPV than perform parallel K-Means Clustering only.

Using satellite fire detection to calibrate components of the fire weather index system in Malaysia and Indonesia.

PubMed

Dymond, Caren C; Field, Robert D; Roswintiarti, Orbita; Guswanto

2005-04-01

Vegetation fires have become an increasing problem in tropical environments as a consequence of socioeconomic pressures and subsequent land-use change. In response, fire management systems are being developed. This study set out to determine the relationships between two aspects of the fire problems in western Indonesia and Malaysia, and two components of the Canadian Forest Fire Weather Index System. The study resulted in a new method for calibrating components of fire danger rating systems based on satellite fire detection (hotspot) data. Once the climate was accounted for, a problematic number of fires were related to high levels of the Fine Fuel Moisture Code. The relationship between climate, Fine Fuel Moisture Code, and hotspot occurrence was used to calibrate Fire Occurrence Potential classes where low accounted for 3% of the fires from 1994 to 2000, moderate accounted for 25%, high 26%, and extreme 38%. Further problems arise when there are large clusters of fires burning that may consume valuable land or produce local smoke pollution. Once the climate was taken into account, the hotspot load (number and size of clusters of hotspots) was related to the Fire Weather Index. The relationship between climate, Fire Weather Index, and hotspot load was used to calibrate Fire Load Potential classes. Low Fire Load Potential conditions (75% of an average year) corresponded with 24% of the hotspot clusters, which had an average size of 30% of the largest cluster. In contrast, extreme Fire Load Potential conditions (1% of an average year) corresponded with 30% of the hotspot clusters, which had an average size of 58% of the maximum. Both Fire Occurrence Potential and Fire Load Potential calibrations were successfully validated with data from 2001. This study showed that when ground measurements are not available, fire statistics derived from satellite fire detection archives can be reliably used for calibration. More importantly, as a result of this work, Malaysia and Indonesia have two new sources of information to initiate fire prevention and suppression activities.

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.

Reliability and Validity of Athletes Disability Index Questionnaire.

PubMed

Noormohammadpour, Pardis; Hosseini Khezri, Alireza; Farahbakhsh, Farzin; Mansournia, Mohammad Ali; Smuck, Matthew; Kordi, Ramin

2018-03-01

The purpose of this study was to evaluate validity and reliability of a new proposed questionnaire for assessment of functional disability in athletes with low back pain (LBP). Validity and reliability study. Elite athletes participating in different fields of sports. Participants were 165 male and female athletes (between 12 and 50 years old) with LBP. Athlete Disability Index (ADI) Questionnaire which is developed by the authors for assessing LBP-related disability in athletes, Oswestry Disability Index (ODI), and the Roland-Morris Disability Questionnaire (RDQ). Self-reported responses were collected regarding LBP-related disability through ADI, ODI, and RDQ. The test-retest reliability was strong, and intraclass correlation value ranged between 0.74 and 0.94. The Cronbach alpha coefficient value of 0.91 (P < 0.001) demonstrated excellent internal consistency of the questionnaire. The correlation coefficient between ADI and ODI was r = 0.918 (P < 0.0001), between ADI and RDQ was r = 0.669 (P < 0.0001), and between ADI and visual analog scale was r = 0.626 (P < 0.001). According to ODI and RDQ, disability levels were mild in the large majority of subjects (91.5% and 86.0%, respectively). Alternatively, disability assessments by the ADI did not cluster at the mild level and ranged more broadly from mild to very high. The ADI is a reliable and valid instrument for assessing disability in athletes with LBP. Compared with the available LBP disability questionnaires used in the general population, ADI can more precisely stratify the disability levels of athletes due to LBP.

Algebraic approach to small-world network models

NASA Astrophysics Data System (ADS)

Rudolph-Lilith, Michelle; Muller, Lyle E.

2014-01-01

We introduce an analytic model for directed Watts-Strogatz small-world graphs and deduce an algebraic expression of its defining adjacency matrix. The latter is then used to calculate the small-world digraph's asymmetry index and clustering coefficient in an analytically exact fashion, valid nonasymptotically for all graph sizes. The proposed approach is general and can be applied to all algebraically well-defined graph-theoretical measures, thus allowing for an analytical investigation of finite-size small-world graphs.

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure.

PubMed

Zhang, Wen; Xiao, Fan; Li, Bin; Zhang, Siguang

2016-01-01

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods.

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure

PubMed Central

Xiao, Fan; Li, Bin; Zhang, Siguang

2016-01-01

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods. PMID:27579031

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

Obesigenic families: parents’ physical activity and dietary intake patterns predict girls’ risk of overweight

PubMed Central

Davison, K Krahnstoever; Birch, L Lipps

2008-01-01

OBJECTIVE To determine whether obesigenic families can be identified based on mothers’ and fathers’ dietary and activity patterns. METHODS A total of 197 girls and their parents were assessed when girls were 5 y old; 192 families were reassessed when girls were 7 y old. Measures of parents’ physical activity and dietary intake were obtained and entered into a cluster analysis to assess whether distinct family clusters could be identified. Girls’ skinfold thickness and body mass index (BMI) were also assessed and were used to examine the predictive validity of the clusters. RESULTS Obesigenic and a non-obesigenic family clusters were identified. Mothers and fathers in the obesigenic cluster reported high levels of dietary intake and low levels of physical activity, while mothers and fathers in the non-obesigenic cluster reported low levels of dietary intake and high levels of activity. Girls from families in the obesigenic cluster had significantly higher BMI and skinfold thickness values at age 7 and showed significantly greater increases in BMI and skinfold thickness from ages 5 to 7 y than girls from non-obesigenic families; differences were reduced but not eliminated after controlling for parents’ BMI. CONCLUSIONS Obesigenic families, defined in terms of parents’ activity and dietary patterns, can be used predict children’s risk of obesity. PMID:12187395

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

PubMed

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

2015-03-01

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

Clustering of financial time series with application to index and enhanced index tracking portfolio

NASA Astrophysics Data System (ADS)

Dose, Christian; Cincotti, Silvano

2005-09-01

A stochastic-optimization technique based on time series cluster analysis is described for index tracking and enhanced index tracking problems. Our methodology solves the problem in two steps, i.e., by first selecting a subset of stocks and then setting the weight of each stock as a result of an optimization process (asset allocation). Present formulation takes into account constraints on the number of stocks and on the fraction of capital invested in each of them, whilst not including transaction costs. Computational results based on clustering selection are compared to those of random techniques and show the importance of clustering in noise reduction and robust forecasting applications, in particular for enhanced index tracking.

Sexual behavioral abstine HIV/AIDS questionnaire: Validation study of an Iranian questionnaire.

PubMed

Najarkolaei, Fatemeh Rahmati; Niknami, Shamsaddin; Shokravi, Farkhondeh Amin; Tavafian, Sedigheh Sadat; Fesharaki, Mohammad Gholami; Jafari, Mohammad Reza

2014-01-01

This study was designed to assess the validity and reliability of the designed sexual, behavioral abstinence, and avoidance of high-risk situation questionnaire (SBAHAQ), with an aim to construct an appropriate development tool in the Iranian population. A descriptive-analytic study was conducted among female undergraduate students of Tehran University, who were selected through cluster random sampling. After reviewing the questionnaires and investigating face and content validity, internal consistency of the questionnaire was assessed by Cronbach's alpha. Explanatory and confirmatory factor analysis was conducted using SPSS and AMOS 16 Software, respectively. The sample consisted of 348 female university students with a mean age of 20.69 ± 1.63 years. The content validity ratio (CVR) coefficient was 0.85 and the reliability of each section of the questionnaire was as follows: Perceived benefit (PB; 0.87), behavioral intention (BI; 0.77), and self-efficacy (SE; 0.85) (Cronbach's alpha totally was 0.83). Explanatory factor analysis showed three factors, including SE, PB, and BI, with the total variance of 61% and Kaiser-Meyer-Olkin (KMO) index of 88%. These factors were also confirmed by confirmatory factor analysis [adjusted goodness of fitness index (AGFI) = 0.939, root mean square error of approximation (RMSEA) = 0.039]. This study showed the designed questionnaire provided adequate construct validity and reliability, and could be adequately used to measure sexual abstinence and avoidance of high-risk situations among female students.

cluML: A markup language for clustering and cluster validity assessment of microarray data.

PubMed

Bolshakova, Nadia; Cunningham, Pádraig

2005-01-01

cluML is a new markup language for microarray data clustering and cluster validity assessment. The XML-based format has been designed to address some of the limitations observed in traditional formats, such as inability to store multiple clustering (including biclustering) and validation results within a dataset. cluML is an effective tool to support biomedical knowledge representation in gene expression data analysis. Although cluML was developed for DNA microarray analysis applications, it can be effectively used for the representation of clustering and for the validation of other biomedical and physical data that has no limitations.

Characterizing tuberculosis genotype clusters along the United States-Mexico border.

PubMed

Baker, B J; Moonan, P K

2014-03-01

We examined the growth of tuberculosis (TB) genotype clusters during 2005-2010 in the United States, categorized by country of origin and ethnicity of the index case and geographic proximity to the US-Mexico border at the time of TB diagnosis. Nationwide, 38.9% of cases subsequent to Mexico-born index cases were US-born. Among clusters following US-born Hispanic and US-born non-Hispanic index cases, respectively 29.2% and 5.3% of subsequent cluster members were Mexico-born. In border areas, the majority of subsequent cases were Mexico-born following US-born Hispanic (56.4%) and US-born non-Hispanic (55.6%) index cases. These findings suggest that TB transmission commonly occurs between US-born and Mexico-born persons. Along the US-Mexico border, prioritizing TB genotype clusters following US-born index cases for investigation may prevent subsequent cases among both US-born and Mexico-born persons.

Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach.

PubMed

Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan

2018-08-01

Understanding precipitation on a regional basis is an important component of water resources planning and management. The present study outlines a methodology based on continuous wavelet transform (CWT) and multiscale entropy (CWME), combined with self-organizing map (SOM) and k-means clustering techniques, to measure and analyze the complexity of precipitation. Historical monthly precipitation data from 1960 to 2010 at 31 rain gauges across Iran were preprocessed by CWT. The multi-resolution CWT approach segregated the major features of the original precipitation series by unfolding the structure of the time series which was often ambiguous. The entropy concept was then applied to components obtained from CWT to measure dispersion, uncertainty, disorder, and diversification of subcomponents. Based on different validity indices, k-means clustering captured homogenous areas more accurately, and additional analysis was performed based on the outcome of this approach. The 31 rain gauges in this study were clustered into 6 groups, each one having a unique CWME pattern across different time scales. The results of clustering showed that hydrologic similarity (multiscale variation of precipitation) was not based on geographic contiguity. According to the pattern of entropy across the scales, each cluster was assigned an entropy signature that provided an estimation of the entropy pattern of precipitation data in each cluster. Based on the pattern of mean CWME for each cluster, a characteristic signature was assigned, which provided an estimation of the CWME of a cluster across scales of 1-2, 3-8, and 9-13 months relative to other stations. The validity of the homogeneous clusters demonstrated the usefulness of the proposed approach to regionalize precipitation. Further analysis based on wavelet coherence (WTC) was performed by selecting central rain gauges in each cluster and analyzing against temperature, wind, Multivariate ENSO index (MEI), and East Atlantic (EA) and North Atlantic Oscillation (NAO), indeces. The results revealed that all climatic features except NAO influenced precipitation in Iran during the 1960-2010 period. Copyright © 2018 Elsevier Inc. All rights reserved.

Mass functions for globular cluster main sequences based on CCD photometry and stellar models

NASA Astrophysics Data System (ADS)

McClure, Robert D.; Vandenberg, Don A.; Smith, Graeme H.; Fahlman, Gregory G.; Richer, Harvey B.; Hesser, James E.; Harris, William E.; Stetson, Peter B.; Bell, R. A.

1986-08-01

Main-sequence luminosity functions constructed from CCD observations of globular clusters reveal a strong trend in slope with metal abundance. Theoretical luminosity functions constructed from VandenBerg and Bell's (1985) isochrones have been fitted to the observations and reveal a trend between x, the power-law index of the mass function, and metal abundance. The most metal-poor clusters require an index of about x = 2.5, whereas the most metal-rich clusters exhibit an index of x of roughly -0.5. The luminosity functions for two sparse clusters, E3 and Pal 5, are distinct from those of the more massive clusters, in that they show a turndown which is possibly a result of mass loss or tidal disruption.

Role of isostaticity and load-bearing microstructure in the elasticity of yielded colloidal gels.

PubMed

Hsiao, Lilian C; Newman, Richmond S; Glotzer, Sharon C; Solomon, Michael J

2012-10-02

We report a simple correlation between microstructure and strain-dependent elasticity in colloidal gels by visualizing the evolution of cluster structure in high strain-rate flows. We control the initial gel microstructure by inducing different levels of isotropic depletion attraction between particles suspended in refractive index matched solvents. Contrary to previous ideas from mode coupling and micromechanical treatments, our studies show that bond breakage occurs mainly due to the erosion of rigid clusters that persist far beyond the yield strain. This rigidity contributes to gel elasticity even when the sample is fully fluidized; the origin of the elasticity is the slow Brownian relaxation of rigid, hydrodynamically interacting clusters. We find a power-law scaling of the elastic modulus with the stress-bearing volume fraction that is valid over a range of volume fractions and gelation conditions. These results provide a conceptual framework to quantitatively connect the flow-induced microstructure of soft materials to their nonlinear rheology.

Towards Tunable Consensus Clustering for Studying Functional Brain Connectivity During Affective Processing.

PubMed

Liu, Chao; Abu-Jamous, Basel; Brattico, Elvira; Nandi, Asoke K

2017-03-01

In the past decades, neuroimaging of humans has gained a position of status within neuroscience, and data-driven approaches and functional connectivity analyses of functional magnetic resonance imaging (fMRI) data are increasingly favored to depict the complex architecture of human brains. However, the reliability of these findings is jeopardized by too many analysis methods and sometimes too few samples used, which leads to discord among researchers. We propose a tunable consensus clustering paradigm that aims at overcoming the clustering methods selection problem as well as reliability issues in neuroimaging by means of first applying several analysis methods (three in this study) on multiple datasets and then integrating the clustering results. To validate the method, we applied it to a complex fMRI experiment involving affective processing of hundreds of music clips. We found that brain structures related to visual, reward, and auditory processing have intrinsic spatial patterns of coherent neuroactivity during affective processing. The comparisons between the results obtained from our method and those from each individual clustering algorithm demonstrate that our paradigm has notable advantages over traditional single clustering algorithms in being able to evidence robust connectivity patterns even with complex neuroimaging data involving a variety of stimuli and affective evaluations of them. The consensus clustering method is implemented in the R package "UNCLES" available on http://cran.r-project.org/web/packages/UNCLES/index.html .

Sexual behavioral abstine HIV/AIDS questionnaire: Validation study of an Iranian questionnaire

PubMed Central

Najarkolaei, Fatemeh Rahmati; Niknami, Shamsaddin; Shokravi, Farkhondeh Amin; Tavafian, Sedigheh Sadat; Fesharaki, Mohammad Gholami; Jafari, Mohammad Reza

2014-01-01

Background: This study was designed to assess the validity and reliability of the designed sexual, behavioral abstinence, and avoidance of high-risk situation questionnaire (SBAHAQ), with an aim to construct an appropriate development tool in the Iranian population. Materials and Methods: A descriptive–analytic study was conducted among female undergraduate students of Tehran University, who were selected through cluster random sampling. After reviewing the questionnaires and investigating face and content validity, internal consistency of the questionnaire was assessed by Cronbach's alpha. Explanatory and confirmatory factor analysis was conducted using SPSS and AMOS 16 Software, respectively. Results: The sample consisted of 348 female university students with a mean age of 20.69 ± 1.63 years. The content validity ratio (CVR) coefficient was 0.85 and the reliability of each section of the questionnaire was as follows: Perceived benefit (PB; 0.87), behavioral intention (BI; 0.77), and self-efficacy (SE; 0.85) (Cronbach's alpha totally was 0.83). Explanatory factor analysis showed three factors, including SE, PB, and BI, with the total variance of 61% and Kaiser–Meyer–Olkin (KMO) index of 88%. These factors were also confirmed by confirmatory factor analysis [adjusted goodness of fitness index (AGFI) = 0.939, root mean square error of approximation (RMSEA) = 0.039]. Conclusion: This study showed the designed questionnaire provided adequate construct validity and reliability, and could be adequately used to measure sexual abstinence and avoidance of high-risk situations among female students. PMID:24741650

A psychometric validation study of the Impulsive-Compulsive Behaviours Checklist: A transdiagnostic tool for addictive and compulsive behaviours.

PubMed

Guo, Karen; Youssef, George J; Dawson, Andrew; Parkes, Linden; Oostermeijer, Sanne; López-Solà, Clara; Lorenzetti, Valentina; Greenwood, Christopher; Fontenelle, Leonardo F; Yücel, Murat

2017-04-01

The occurrence of repetitive behaviours that are often harmful has been attributed to traits traditionally described as "impulsive" or "compulsive" e.g. substance dependence, excessive gambling, and hoarding. These behaviours are common and often co-occur in both the general population and psychiatric populations. The lack of measures to concurrently index a range of such behaviours led to the development of the Impulsive-Compulsive Behaviours (ICB) Checklist. This study aims to validate the ICB Checklist in a general community sample. Factor analyses revealed a two-factor structure, demonstrating good model fit in two independent samples. These were labelled Impulsive-Compulsions and Compulsive-Impulsions, comprising of classically compulsive and impulsive behaviours respectively. Reliability and construct validity were further confirmed using correlations with existing measures of impulsivity and compulsivity. Results suggest that the ICB Checklist is a valid and practical assessment that can be used to monitor behavioural clusters characterised by deficits in inhibition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Detection of major climatic and environmental predictors of liver fluke exposure risk in Ireland using spatial cluster analysis.

PubMed

Selemetas, Nikolaos; de Waal, Theo

2015-04-30

Fasciolosis caused by Fasciola hepatica (liver fluke) can cause significant economic and production losses in dairy cow farms. The aim of the current study was to identify important weather and environmental predictors of the exposure risk to liver fluke by detecting clusters of fasciolosis in Ireland. During autumn 2012, bulk-tank milk samples from 4365 dairy farms were collected throughout Ireland. Using an in-house antibody-detection ELISA, the analysis of BTM samples showed that 83% (n=3602) of dairy farms had been exposed to liver fluke. The Getis-Ord Gi* statistic identified 74 high-risk and 130 low-risk significant (P<0.01) clusters of fasciolosis. The low-risk clusters were mostly located in the southern regions of Ireland, whereas the high-risk clusters were mainly situated in the western part. Several climatic variables (monthly and seasonal mean rainfall and temperatures, total wet days and rain days) and environmental datasets (soil types, enhanced vegetation index and normalised difference vegetation index) were used to investigate dissimilarities in the exposure to liver fluke between clusters. Rainfall, total wet days and rain days, and soil type were the significant classes of climatic and environmental variables explaining the differences between significant clusters. A discriminant function analysis was used to predict the exposure risk to liver fluke using 80% of data for modelling and the remaining subset of 20% for post hoc model validation. The most significant predictors of the model risk function were total rainfall in August and September and total wet days. The risk model presented 100% sensitivity and 91% specificity and an accuracy of 95% correctly classified cases. A risk map of exposure to liver fluke was constructed with higher probability of exposure in western and north-western regions. The results of this study identified differences between clusters of fasciolosis in Ireland regarding climatic and environmental variables and detected significant predictors of the exposure risk to liver fluke. Copyright © 2015 Elsevier B.V. All rights reserved.

Emotional disorders: cluster 4 of the proposed meta-structure for DSM-V and ICD-11.

PubMed

Goldberg, D P; Krueger, R F; Andrews, G; Hobbs, M J

2009-12-01

The extant major psychiatric classifications DSM-IV, and ICD-10, are atheoretical and largely descriptive. Although this achieves good reliability, the validity of a medical diagnosis would be greatly enhanced by an understanding of risk factors and clinical manifestations. In an effort to group mental disorders on the basis of aetiology, five clusters have been proposed. This paper considers the validity of the fourth cluster, emotional disorders, within that proposal. We reviewed the literature in relation to 11 validating criteria proposed by a Study Group of the DSM-V Task Force, as applied to the cluster of emotional disorders. An emotional cluster of disorders identified using the 11 validators is feasible. Negative affectivity is the defining feature of the emotional cluster. Although there are differences between disorders in the remaining validating criteria, there are similarities that support the feasibility of an emotional cluster. Strong intra-cluster co-morbidity may reflect the action of common risk factors and also shared higher-order symptom dimensions in these emotional disorders. Emotional disorders meet many of the salient criteria proposed by the Study Group of the DSM-V Task Force to suggest a classification cluster.

A Cluster-Randomized Trial of Insecticide-Treated Curtains for Dengue Vector Control in Thailand

PubMed Central

Lenhart, Audrey; Trongtokit, Yuwadee; Alexander, Neal; Apiwathnasorn, Chamnarn; Satimai, Wichai; Vanlerberghe, Veerle; Van der Stuyft, Patrick; McCall, Philip J.

2013-01-01

The efficacy of insecticide-treated window curtains (ITCs) for dengue vector control was evaluated in Thailand in a cluster-randomized controlled trial. A total of 2,037 houses in 26 clusters was randomized to receive the intervention or act as control (no treatment). Entomological surveys measured Aedes infestations (Breteau index, house index, container index, and pupae per person index) and oviposition indices (mean numbers of eggs laid in oviposition traps) immediately before and after intervention, and at 3-month intervals over 12 months. There were no consistent statistically significant differences in entomological indices between intervention and control clusters, although oviposition indices were lower (P < 0.01) in ITC clusters during the wet season. It is possible that the open housing structures in the study reduced the likelihood of mosquitoes making contact with ITCs. ITCs deployed in a region where this house design is common may be unsuitable for dengue vector control. PMID:23166195

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.

Hierarchical clusters of phytoplankton variables in dammed water bodies

NASA Astrophysics Data System (ADS)

Silva, Eliana Costa e.; Lopes, Isabel Cristina; Correia, Aldina; Gonçalves, A. Manuela

2017-06-01

In this paper a dataset containing biological variables of the water column of several Portuguese reservoirs is analyzed. Hierarchical cluster analysis is used to obtain clusters of phytoplankton variables of the phylum Cyanophyta, with the objective of validating the classification of Portuguese reservoirs previewly presented in [1] which were divided into three clusters: (1) Interior Tagus and Aguieira; (2) Douro; and (3) Other rivers. Now three new clusters of Cyanophyta variables were found. Kruskal-Wallis and Mann-Whitney tests are used to compare the now obtained Cyanophyta clusters and the previous Reservoirs clusters, in order to validate the classification of the water quality of reservoirs. The amount of Cyanophyta algae present in the reservoirs from the three clusters is significantly different, which validates the previous classification.

[The appraisal of reliability and validity of subjective workload assessment technique and NASA-task load index].

PubMed

Xiao, Yuan-mei; Wang, Zhi-ming; Wang, Mian-zhen; Lan, Ya-jia

2005-06-01

To test the reliability and validity of two mental workload assessment scales, i.e. subjective workload assessment technique (SWAT) and NASA task load index (NASA-TLX). One thousand two hundred and sixty-eight mental workers were sampled from various kinds of occupations, such as scientific research, education, administration and medicine, etc, with randomized cluster sampling. The re-test reliability, split-half reliability, Cronbach's alpha coefficient and correlation coefficients between item score and total score were adopted to test the reliability. The test of validity included structure validity. The re-test reliability coefficients of these two scales and their items were ranged from 0.516 to 0.753 (P < 0.01), indicating the two scales had good re-test reliability; the split-half reliability of SWAT was 0.645, and its Cronbach's alpha coefficient was more than 0.80, all the correlation coefficients between its items score and total score were more than 0.70; as for NASA-TLX, both the split-half reliability and Cronbach's alpha coefficient were more than 0.80, the correlation coefficients between its items score and total score were all more than 0.60 (P < 0.01) except the item of performance. Both scales had good inner consistency. The Pearson correlation coefficient between the two scales was 0.492 (P < 0.01), implying the results of the two scales had good consistency. Factor analysis showed that the two scales had good structure validity. Both SWAT and NASA-TLX have good reliability and validity and may be used as a valid tool to assess mental workload in China after being revised properly.

Subject and Citation Indexing. Part I: The Clustering Structure of Composite Representations in the Cystic Fibrosis Document Collection. Part II: The Optimal, Cluster-Based Retrieval Performance of Composite Representations.

ERIC Educational Resources Information Center

Shaw, W. M., Jr.

1991-01-01

Two articles discuss the clustering of composite representations in the Cystic Fibrosis Document Collection from the National Library of Medicine's MEDLINE file. Clustering is evaluated as a function of the exhaustivity of composite representations based on Medical Subject Headings (MeSH) and citation indexes, and evaluation of retrieval…

Automated segmentation of white matter fiber bundles using diffusion tensor imaging data and a new density based clustering algorithm.

PubMed

Kamali, Tahereh; Stashuk, Daniel

2016-10-01

Robust and accurate segmentation of brain white matter (WM) fiber bundles assists in diagnosing and assessing progression or remission of neuropsychiatric diseases such as schizophrenia, autism and depression. Supervised segmentation methods are infeasible in most applications since generating gold standards is too costly. Hence, there is a growing interest in designing unsupervised methods. However, most conventional unsupervised methods require the number of clusters be known in advance which is not possible in most applications. The purpose of this study is to design an unsupervised segmentation algorithm for brain white matter fiber bundles which can automatically segment fiber bundles using intrinsic diffusion tensor imaging data information without considering any prior information or assumption about data distributions. Here, a new density based clustering algorithm called neighborhood distance entropy consistency (NDEC), is proposed which discovers natural clusters within data by simultaneously utilizing both local and global density information. The performance of NDEC is compared with other state of the art clustering algorithms including chameleon, spectral clustering, DBSCAN and k-means using Johns Hopkins University publicly available diffusion tensor imaging data. The performance of NDEC and other employed clustering algorithms were evaluated using dice ratio as an external evaluation criteria and density based clustering validation (DBCV) index as an internal evaluation metric. Across all employed clustering algorithms, NDEC obtained the highest average dice ratio (0.94) and DBCV value (0.71). NDEC can find clusters with arbitrary shapes and densities and consequently can be used for WM fiber bundle segmentation where there is no distinct boundary between various bundles. NDEC may also be used as an effective tool in other pattern recognition and medical diagnostic systems in which discovering natural clusters within data is a necessity. Copyright © 2016 Elsevier B.V. All rights reserved.

Pan-European comparison of candidate distributions for climatological drought indices, SPI and SPEI

NASA Astrophysics Data System (ADS)

Stagge, James; Tallaksen, Lena; Gudmundsson, Lukas; Van Loon, Anne; Stahl, Kerstin

2013-04-01

Drought indices are vital to objectively quantify and compare drought severity, duration, and extent across regions with varied climatic and hydrologic regimes. The Standardized Precipitation Index (SPI), a well-reviewed meterological drought index recommended by the WMO, and its more recent water balance variant, the Standardized Precipitation-Evapotranspiration Index (SPEI) both rely on selection of univariate probability distributions to normalize the index, allowing for comparisons across climates. The SPI, considered a universal meteorological drought index, measures anomalies in precipitation, whereas the SPEI measures anomalies in climatic water balance (precipitation minus potential evapotranspiration), a more comprehensive measure of water availability that incorporates temperature. Many reviewers recommend use of the gamma (Pearson Type III) distribution for SPI normalization, while developers of the SPEI recommend use of the three parameter log-logistic distribution, based on point observation validation. Before the SPEI can be implemented at the pan-European scale, it is necessary to further validate the index using a range of candidate distributions to determine sensitivity to distribution selection, identify recommended distributions, and highlight those instances where a given distribution may not be valid. This study rigorously compares a suite of candidate probability distributions using WATCH Forcing Data, a global, historical (1958-2001) climate dataset based on ERA40 reanalysis with 0.5 x 0.5 degree resolution and bias-correction based on CRU-TS2.1 observations. Using maximum likelihood estimation, alternative candidate distributions are fit for the SPI and SPEI across the range of European climate zones. When evaluated at this scale, the gamma distribution for the SPI results in negatively skewed values, exaggerating the index severity of extreme dry conditions, while decreasing the index severity of extreme high precipitation. This bias is particularly notable for shorter aggregation periods (1-6 months) during the summer months in southern Europe (below 45° latitude), and can partially be attributed to distribution fitting difficulties in semi-arid regions where monthly precipitation totals cluster near zero. By contrast, the SPEI has potential for avoiding this fitting difficulty because it is not bounded by zero. However, the recommended log-logistic distribution produces index values with less variation than the standard normal distribution. Among the alternative candidate distributions, the best fit distribution and the distribution parameters vary in space and time, suggesting regional commonalities within hydroclimatic regimes, as discussed further in the presentation.

[Foliage clumping index of main vegetation types in Daxing'an Mountains, Northeast China].

PubMed

Huang, Ting; Fan, Wen Yi; Mao, Xue Gang; Yu, Ying

2017-03-18

The foliage clumping index quantifies the cluster degree of the leaf spatial distribution under random canopy. It is of comparable importance for establishment of ecological models. MODIS BRDF model parameter products (MCD43A1 data) and land cover types (MCD12Q1 data) were used in this study to simulate the reflectivity of the hot spots and dark spots, and calculate the normalized difference between hotspot and darkspot (NDHD) based on the Ross-Li semi-empirical model. Least square method was then used to simulate the relationship between NDHD and the foliage clumping index and foliage clumping index products of 500-m resolution in August 2014 were retrieved. Measurements of the foliage clumping index in Daxing'an Mountains were conducted by using the TRAC (Tracing Radiation and Architecture of Canopies) sampling instrument for mo-del validation and analysis. Results showed that it was a feasible algorithm to retrieve clumping index from MCD43A1 product with the correlation of simulated data and the measured data of significance (R 2 =0.8879). The MODIS near infrared wave band was more sensitive than that on red band to foliage clumping index change. With the increase of the solar zenith angle, the clumping index retrieved by Ross-Li model had a linear increase (R 2 =0.9699), which indicated that the foliage clumping index related to the solar zenith angle.

Development and field validation of a regional, management-scale habitat model: A koala Phascolarctos cinereus case study.

PubMed

Law, Bradley; Caccamo, Gabriele; Roe, Paul; Truskinger, Anthony; Brassil, Traecey; Gonsalves, Leroy; McConville, Anna; Stanton, Matthew

2017-09-01

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional-scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently-collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2-km spatial filter and by modeling separately two subregions separated by the 500-m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground-truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows ( n  = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground-truth sites. Similarly, a site habitat quality index at ground-truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site-based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field-validated models of similar resolution would assist in guiding management of conservation-dependent species.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

NASA Astrophysics Data System (ADS)

Salimi, F.; Ristovski, Z.; Mazaheri, M.; Laiman, R.; Crilley, L. R.; He, C.; Clifford, S.; Morawska, L.

2014-06-01

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

NASA Astrophysics Data System (ADS)

Salimi, F.; Ristovski, Z.; Mazaheri, M.; Laiman, R.; Crilley, L. R.; He, C.; Clifford, S.; Morawska, L.

2014-11-01

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods that have been recently employed to analyse PNSD data; however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectrum to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Pain patients' experiences of validation and invalidation from physicians before and after multimodal pain rehabilitation: Associations with pain, negative affectivity, and treatment outcome.

PubMed

Edlund, Sara M; Wurm, Matilda; Holländare, Fredrik; Linton, Steven J; Fruzzetti, Alan E; Tillfors, Maria

2017-10-01

Validating and invalidating responses play an important role in communication with pain patients, for example regarding emotion regulation and adherence to treatment. However, it is unclear how patients' perceptions of validation and invalidation relate to patient characteristics and treatment outcome. The aim of this study was to investigate the occurrence of subgroups based on pain patients' perceptions of validation and invalidation from their physicians. The stability of these perceptions and differences between subgroups regarding pain, pain interference, negative affectivity and treatment outcome were also explored. A total of 108 pain patients answered questionnaires regarding perceived validation and invalidation, pain severity, pain interference, and negative affectivity before and after pain rehabilitation treatment. Two cluster analyses using perceived validation and invalidation were performed, one on pre-scores and one on post-scores. The stability of patient perceptions from pre- to post-treatment was investigated, and clusters were compared on pain severity, pain interference, and negative affectivity. Finally, the connection between perceived validation and invalidation and treatment outcome was explored. Three clusters emerged both before and after treatment: (1) low validation and heightened invalidation, (2) moderate validation and invalidation, and (3) high validation and low invalidation. Perceptions of validation and invalidation were generally stable over time, although there were individuals whose perceptions changed. When compared to the other two clusters, the low validation/heightened invalidation cluster displayed significantly higher levels of pain interference and negative affectivity post-treatment but not pre-treatment. The whole sample significantly improved on pain interference and depression, but treatment outcome was independent of cluster. Unexpectedly, differences between clusters on pain interference and negative affectivity were only found post-treatment. This appeared to be due to the pre- and post-heightened invalidation clusters not containing the same individuals. Therefore, additional analyses were conducted to investigate the individuals who changed clusters. Results showed that patients scoring high on negative affectivity ended up in the heightened invalidation cluster post-treatment. Taken together, most patients felt understood when communicating with their rehabilitation physician. However, a smaller group of patients experienced the opposite: low levels of validation and heightened levels of invalidation. This group stood out as more problematic, reporting greater pain interference and negative affectivity when compared to the other groups after treatment. Patient perceptions were typically stable over time, but some individuals changed cluster, and these movements seemed to be related to negative affectivity and pain interference. These results do not support a connection between perceived validation and invalidation from physicians (meeting the patients pre- and post-treatment) and treatment outcome. Overall, our results suggest that there is a connection between negative affectivity and pain interference in the patients, and perceived validation and invalidation from the physicians. In clinical practice, it is important to pay attention to comorbid psychological problems and level of pain interference, since these factors may negatively influence effective communication. A focus on decreasing invalidating responses and/or increasing validating responses might be particularly important for patients with high levels of psychological problems and pain interference. Copyright © 2017. Published by Elsevier B.V.

a Clustering-Based Approach for Evaluation of EO Image Indexing

NASA Astrophysics Data System (ADS)

Bahmanyar, R.; Rigoll, G.; Datcu, M.

2013-09-01

The volume of Earth Observation data is increasing immensely in order of several Terabytes a day. Therefore, to explore and investigate the content of this huge amount of data, developing more sophisticated Content-Based Information Retrieval (CBIR) systems are highly demanded. These systems should be able to not only discover unknown structures behind the data, but also provide relevant results to the users' queries. Since in any retrieval system the images are processed based on a discrete set of their features (i.e., feature descriptors), study and assessment of the structure of feature space, build by different feature descriptors, is of high importance. In this paper, we introduce a clustering-based approach to study the content of image collections. In our approach, we claim that using both internal and external evaluation of clusters for different feature descriptors, helps to understand the structure of feature space. Moreover, the semantic understanding of users about the images also can be assessed. To validate the performance of our approach, we used an annotated Synthetic Aperture Radar (SAR) image collection. Quantitative results besides the visualization of feature space demonstrate the applicability of our approach.

Diary Data Subjected to Cluster Analysis of Intake/Output/Void Habits with Resulting Clusters Compared by Continence Status, Age, Race

PubMed Central

Miller, Janis M; Guo, Ying; Rodseth, Sarah Becker

2011-01-01

Background Data that incorporate the full complexity of healthy beverage intake and voiding frequency do not exist; therefore, clinicians reviewing bladder habits or voiding diaries for continence care must rely on expert opinion recommendations. Objective To use data-driven cluster analyses to reduce complex voiding diary variables into discrete patterns or data cluster profiles, descriptively name the clusters, and perform validity testing. Method Participants were 352 community women who filled out a 3-day voiding diary. Six variables (void frequency during daytime hours, void frequency during nighttime hours, modal output, total output, total intake, and body mass index) were entered into cluster analyses. The clusters were analyzed for differences by continence status, age, race (Black women, n = 196 White women, n = 156), and for those who were incontinent, by leakage episode severity. Results Three clusters emerged, labeled descriptively as Conventional, Benchmark, and Superplus. The Conventional cluster (68% of the sample) demonstrated mean daily intake of 45 ±13 ounces; mean daily output of 37 ± 15 ounces, mean daily voids 5 ± 2 times, mean modal daytime output 10±0.5 ounces, and mean nighttime voids 1±1 times. The Superplus cluster (7% of the sample) showed double or triple these values across the 5 variables, and the Benchmark cluster (25%) showed values consistent with current popular recommendations on intake and output (e.g., meeting or exceeding the 8 × 8 fluid intake rule of thumb). The clusters differed significantly (p < .05) by age, race, amount of irritating beverages consumed, and incontinence status. Discussion Identification of three discrete clusters provides for a potential parsimonious but data-driven means of classifying individuals for additional epidemiological or clinical study. The clinical utility rests with potential for intervening to move an individual from a high risk to low risk cluster with regards to incontinence. PMID:21317828

Fractal Clustering and Knowledge-driven Validation Assessment for Gene Expression Profiling.

PubMed

Wang, Lu-Yong; Balasubramanian, Ammaiappan; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

DNA microarray experiments generate a substantial amount of information about the global gene expression. Gene expression profiles can be represented as points in multi-dimensional space. It is essential to identify relevant groups of genes in biomedical research. Clustering is helpful in pattern recognition in gene expression profiles. A number of clustering techniques have been introduced. However, these traditional methods mainly utilize shape-based assumption or some distance metric to cluster the points in multi-dimension linear Euclidean space. Their results shows poor consistence with the functional annotation of genes in previous validation study. From a novel different perspective, we propose fractal clustering method to cluster genes using intrinsic (fractal) dimension from modern geometry. This method clusters points in such a way that points in the same clusters are more self-affine among themselves than to the points in other clusters. We assess this method using annotation-based validation assessment for gene clusters. It shows that this method is superior in identifying functional related gene groups than other traditional methods.

Using an index of habitat patch proximity for landscape design

Treesearch

Eric J. Gustafson; George R. Parker

1994-01-01

A proximity index (PX) inspired by island biogeography theory is described which quantifies the spatial context of a habitat patch in relation to its neighbors. The index distinguishes sparse distributions of small habitat patches from clusters of large patches. An evaluation of the relationship between PX and variation in the spatial characteristics of clusters of...

Detecting grizzly bear use of ungulate carcasses using global positioning system telemetry and activity data

USGS Publications Warehouse

Ebinger, Michael R.; Haroldson, Mark A.; van Manen, Frank T.; Costello, Cecily M.; Bjornlie, Daniel D.; Thompson, Daniel J.; Gunther, Kerry A.; Fortin, Jennifer K.; Teisberg, Justin E.; Pils, Shannon R; White, P J; Cain, Steven L.; Cross, Paul C.

2016-01-01

Global positioning system (GPS) wildlife collars have revolutionized wildlife research. Studies of predation by free-ranging carnivores have particularly benefited from the application of location clustering algorithms to determine when and where predation events occur. These studies have changed our understanding of large carnivore behavior, but the gains have concentrated on obligate carnivores. Facultative carnivores, such as grizzly/brown bears (Ursus arctos), exhibit a variety of behaviors that can lead to the formation of GPS clusters. We combined clustering techniques with field site investigations of grizzly bear GPS locations (n = 732 site investigations; 2004–2011) to produce 174 GPS clusters where documented behavior was partitioned into five classes (large-biomass carcass, small-biomass carcass, old carcass, non-carcass activity, and resting). We used multinomial logistic regression to predict the probability of clusters belonging to each class. Two cross-validation methods—leaving out individual clusters, or leaving out individual bears—showed that correct prediction of bear visitation to large-biomass carcasses was 78–88%, whereas the false-positive rate was 18–24%. As a case study, we applied our predictive model to a GPS data set of 266 bear-years in the Greater Yellowstone Ecosystem (2002–2011) and examined trends in carcass visitation during fall hyperphagia (September–October). We identified 1997 spatial GPS clusters, of which 347 were predicted to be large-biomass carcasses. We used the clustered data to develop a carcass visitation index, which varied annually, but more than doubled during the study period. Our study demonstrates the effectiveness and utility of identifying GPS clusters associated with carcass visitation by a facultative carnivore.

Detecting grizzly bear use of ungulate carcasses using global positioning system telemetry and activity data.

PubMed

Ebinger, Michael R; Haroldson, Mark A; van Manen, Frank T; Costello, Cecily M; Bjornlie, Daniel D; Thompson, Daniel J; Gunther, Kerry A; Fortin, Jennifer K; Teisberg, Justin E; Pils, Shannon R; White, P J; Cain, Steven L; Cross, Paul C

2016-07-01

Global positioning system (GPS) wildlife collars have revolutionized wildlife research. Studies of predation by free-ranging carnivores have particularly benefited from the application of location clustering algorithms to determine when and where predation events occur. These studies have changed our understanding of large carnivore behavior, but the gains have concentrated on obligate carnivores. Facultative carnivores, such as grizzly/brown bears (Ursus arctos), exhibit a variety of behaviors that can lead to the formation of GPS clusters. We combined clustering techniques with field site investigations of grizzly bear GPS locations (n = 732 site investigations; 2004-2011) to produce 174 GPS clusters where documented behavior was partitioned into five classes (large-biomass carcass, small-biomass carcass, old carcass, non-carcass activity, and resting). We used multinomial logistic regression to predict the probability of clusters belonging to each class. Two cross-validation methods-leaving out individual clusters, or leaving out individual bears-showed that correct prediction of bear visitation to large-biomass carcasses was 78-88 %, whereas the false-positive rate was 18-24 %. As a case study, we applied our predictive model to a GPS data set of 266 bear-years in the Greater Yellowstone Ecosystem (2002-2011) and examined trends in carcass visitation during fall hyperphagia (September-October). We identified 1997 spatial GPS clusters, of which 347 were predicted to be large-biomass carcasses. We used the clustered data to develop a carcass visitation index, which varied annually, but more than doubled during the study period. Our study demonstrates the effectiveness and utility of identifying GPS clusters associated with carcass visitation by a facultative carnivore.

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.

The effect of UV irradiation on the refractive index modulation in photo-thermo-refractive glasses: Mechanisms and application

NASA Astrophysics Data System (ADS)

Chernakov, Dmitry I.; Sidorov, Alexander I.; Stolyarchuk, Maxim V.; Kozlova, Darya A.; Krykova, Victoria A.; Nikonorov, Nikolay V.

2018-02-01

It is shown experimentally that in photo-thermo-refractive glasses the transformation of charged silver subnanosized molecular clusters to neutral state by UV irradiation results in the increase of glass refractive index. The increment of the refractive index reaches Δn = 0.76·10-4. Computer simulation has shown that the polarizability of neutral molecular clusters is by 20-40% larger than of charged ones. The reason of this is the increase of electron density and volume of electron density surfaces during the transformation of molecular cluster to the neutral state. The transition molecular cluster from the ground state to the excited state also results in the increase of its polarizability.

Modeling of correlated data with informative cluster sizes: An evaluation of joint modeling and within-cluster resampling approaches.

PubMed

Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S

2017-08-01

Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.

The degree-related clustering coefficient and its application to link prediction

NASA Astrophysics Data System (ADS)

Liu, Yangyang; Zhao, Chengli; Wang, Xiaojie; Huang, Qiangjuan; Zhang, Xue; Yi, Dongyun

2016-07-01

Link prediction plays a significant role in explaining the evolution of networks. However it is still a challenging problem that has been addressed only with topological information in recent years. Based on the belief that network nodes with a great number of common neighbors are more likely to be connected, many similarity indices have achieved considerable accuracy and efficiency. Motivated by the natural assumption that the effect of missing links on the estimation of a node's clustering ability could be related to node degree, in this paper, we propose a degree-related clustering coefficient index to quantify the clustering ability of nodes. Unlike the classical clustering coefficient, our new coefficient is highly robust when the observed bias of links is considered. Furthermore, we propose a degree-related clustering ability path (DCP) index, which applies the proposed coefficient to the link prediction problem. Experiments on 12 real-world networks show that our proposed method is highly accurate and robust compared with four common-neighbor-based similarity indices (Common Neighbors(CN), Adamic-Adar(AA), Resource Allocation(RA), and Preferential Attachment(PA)), and the recently introduced clustering ability (CA) index.

Degradation of Perfluorinated Ether Lubricants on Pure Aluminum Surfaces: Semiempirical Quantum Chemical Modeling

NASA Technical Reports Server (NTRS)

Slaby, Scott M.; Ewing, David W.; Zehe, Michael J.

1997-01-01

The AM1 semiempirical quantum chemical method was used to model the interaction of perfluoroethers with aluminum surfaces. Perfluorodimethoxymethane and perfluorodimethyl ether were studied interacting with aluminum surfaces, which were modeled by a five-atom cluster and a nine-atom cluster. Interactions were studied for edge (high index) sites and top (low index) sites of the clusters. Both dissociative binding and nondissociative binding were found, with dissociative binding being stronger. The two different ethers bound and dissociated on the clusters in different ways: perfluorodimethoxymethane through its oxygen atoms, but perfluorodimethyl ether through its fluorine atoms. The acetal linkage of perfluorodimeth-oxymethane was the key structural feature of this molecule in its binding and dissociation on the aluminum surface models. The high-index sites of the clusters caused the dissociation of both ethers. These results are consistent with the experimental observation that perfluorinated ethers decompose in contact with sputtered aluminum surfaces.

Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region.

PubMed

Roux, Emmanuel; Gaborit, Pascal; Romaña, Christine A; Girod, Romain; Dessay, Nadine; Dusfour, Isabelle

2013-12-01

Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum. We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value < 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001). The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes.

Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region

PubMed Central

2013-01-01

Background Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum. Results We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value << 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001). Conclusions The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes. PMID:24289184

Competency Index. [Health Technology Cluster.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Center on Education and Training for Employment.

This competency index lists the competencies included in the 62 units of the Tech Prep Competency Profiles within the Health Technologies Cluster. The unit topics are as follows: employability skills; professionalism; teamwork; computer literacy; documentation; infection control and risk management; medical terminology; anatomy, physiology, and…

Quantification of Hepatorenal Index for Computer-Aided Fatty Liver Classification with Self-Organizing Map and Fuzzy Stretching from Ultrasonography.

PubMed

Kim, Kwang Baek; Kim, Chang Won

2015-01-01

Accurate measures of liver fat content are essential for investigating hepatic steatosis. For a noninvasive inexpensive ultrasonographic analysis, it is necessary to validate the quantitative assessment of liver fat content so that fully automated reliable computer-aided software can assist medical practitioners without any operator subjectivity. In this study, we attempt to quantify the hepatorenal index difference between the liver and the kidney with respect to the multiple severity status of hepatic steatosis. In order to do this, a series of carefully designed image processing techniques, including fuzzy stretching and edge tracking, are applied to extract regions of interest. Then, an unsupervised neural learning algorithm, the self-organizing map, is designed to establish characteristic clusters from the image, and the distribution of the hepatorenal index values with respect to the different levels of the fatty liver status is experimentally verified to estimate the differences in the distribution of the hepatorenal index. Such findings will be useful in building reliable computer-aided diagnostic software if combined with a good set of other characteristic feature sets and powerful machine learning classifiers in the future.

Quantification of Hepatorenal Index for Computer-Aided Fatty Liver Classification with Self-Organizing Map and Fuzzy Stretching from Ultrasonography

PubMed Central

Kim, Kwang Baek

2015-01-01

Accurate measures of liver fat content are essential for investigating hepatic steatosis. For a noninvasive inexpensive ultrasonographic analysis, it is necessary to validate the quantitative assessment of liver fat content so that fully automated reliable computer-aided software can assist medical practitioners without any operator subjectivity. In this study, we attempt to quantify the hepatorenal index difference between the liver and the kidney with respect to the multiple severity status of hepatic steatosis. In order to do this, a series of carefully designed image processing techniques, including fuzzy stretching and edge tracking, are applied to extract regions of interest. Then, an unsupervised neural learning algorithm, the self-organizing map, is designed to establish characteristic clusters from the image, and the distribution of the hepatorenal index values with respect to the different levels of the fatty liver status is experimentally verified to estimate the differences in the distribution of the hepatorenal index. Such findings will be useful in building reliable computer-aided diagnostic software if combined with a good set of other characteristic feature sets and powerful machine learning classifiers in the future. PMID:26247023

Use of multiple cluster analysis methods to explore the validity of a community outcomes concept map.

PubMed

Orsi, Rebecca

2017-02-01

Concept mapping is now a commonly-used technique for articulating and evaluating programmatic outcomes. However, research regarding validity of knowledge and outcomes produced with concept mapping is sparse. The current study describes quantitative validity analyses using a concept mapping dataset. We sought to increase the validity of concept mapping evaluation results by running multiple cluster analysis methods and then using several metrics to choose from among solutions. We present four different clustering methods based on analyses using the R statistical software package: partitioning around medoids (PAM), fuzzy analysis (FANNY), agglomerative nesting (AGNES) and divisive analysis (DIANA). We then used the Dunn and Davies-Bouldin indices to assist in choosing a valid cluster solution for a concept mapping outcomes evaluation. We conclude that the validity of the outcomes map is high, based on the analyses described. Finally, we discuss areas for further concept mapping methods research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Parent-reported social support for child's fruit and vegetable intake: validity of measures.

PubMed

Dave, Jayna M; Evans, Alexandra E; Condrasky, Marge D; Williams, Joel E

2012-01-01

To develop and validate measures of parental social support to increase their child's fruit and vegetable (FV) consumption. Cross-sectional study design. School and home. Two hundred three parents with at least 1 elementary school-aged child. Parents completed a questionnaire that included instrumental social support scale (ISSPS), emotional social support scale (ESSPS), household FV availability and accessibility index, and demographics. Exploratory factor analysis with promax rotation was conducted to obtain the psychometric properties of ISSPS and ESSPS. Internal consistency and test-retest reliabilities were also assessed. Factor analysis indicated a 4-factor model for ESSPS: positive encouragement, negative role modeling, discouragement, and an item cluster called reinforcement. Psychometric properties indicated that ISSPS performed best as independent single scales with α = .87. Internal consistency reliabilities were acceptable, and test-retest reliabilities ranged from low to acceptable. Correlations between scales, subscales, and item clusters were significant (P < .05). In addition, ISSPS and the positive encouragement subscale were significantly correlated with household FV availability. The ISSPS and ESSPS subscales demonstrated good internal consistency reliability and are suitable for impact assessment of an intervention designed to target parents to help their children eat more fruit and vegetables. Copyright © 2012 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Pupal productivity in rainy and dry seasons: findings from the impact survey of a randomised controlled trial of dengue prevention in Guerrero, Mexico.

PubMed

Jiménez-Alejo, Abel; Morales-Pérez, Arcadio; Nava-Aguilera, Elizabeth; Flores-Moreno, Miguel; Apreza-Aguilar, Sinahí; Carranza-Alcaraz, Wilhelm; Cortés-Guzmán, Antonio Juan; Fernández-Salas, Ildefonso; Ledogar, Robert J; Cockcroft, Anne; Andersson, Neil

2017-05-30

The follow-up survey of a cluster-randomised controlled trial of evidence-based community mobilisation for dengue control in Nicaragua and Mexico included entomological information from the 2012 rainy and dry seasons. We used data from the Mexican arm of the trial to assess the impact of the community action on pupal production of the dengue vector Aedes aegypti in both rainy and dry seasons. Trained field workers inspected household water containers in 90 clusters and collected any pupae or larvae present for entomological examination. We calculated indices of pupae per person and pupae per household, and traditional entomological indices of container index, household index and Breteau index, and compared these between rainy and dry seasons and between intervention and control clusters, using a cluster t-test to test significance of differences. In 11,933 houses in the rainy season, we inspected 40,323 containers and found 7070 Aedes aegypti pupae. In the dry season, we inspected 43,461 containers and counted 6552 pupae. All pupae and entomological indices were lower in the intervention clusters (IC) than in control clusters (CC) in both the rainy season (RS) and the dry season (DS): pupae per container 0.12 IC and 0.24 CC in RS, and 0.10 IC and 0.20 CC in DS; pupae per household 0.46 IC and 0.82 CC in RS, and 0.41 IC and 0.83 CC in DS; pupae per person 0.11 IC and 0.19 CC in RS, and 0.10 IC and 0.20 CC in DS; household index 16% IC and 21% CC in RS, and 12.1% IC and 17.9% CC in DS; container index 7.5% IC and 11.5% CC in RS, and 4.6% IC and 7.1% CC in DS; Breteau index 27% IC and 36% CC in RS, and 19% IC and 29% CC in DS. All differences between the intervention and control clusters were statistically significant, taking into account clustering. The trial intervention led to significant decreases in pupal and conventional entomological indices in both rainy and dry seasons. ISRCTN27581154 .

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.

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.

Objectifying Content Validity: Conducting a Content Validity Study in Social Work Research.

ERIC Educational Resources Information Center

Rubio, Doris McGartland; Berg-Weger, Marla; Tebb, Susan S.; Lee, E. Suzanne; Rauch, Shannon

2003-01-01

The purpose of this article is to demonstrate how to conduct a content validity study. Instructions on how to calculate a content validity index, factorial validity index, and an interrater reliability index and guide for interpreting these indices are included. Implications regarding the value of conducting a content validity study for…

Externalizing disorders: cluster 5 of the proposed meta-structure for DSM-V and ICD-11.

PubMed

Krueger, R F; South, S C

2009-12-01

The extant major psychiatric classifications DSM-IV and ICD-10 are purportedly atheoretical and largely descriptive. Although this achieves good reliability, the validity of a medical diagnosis is greatly enhanced by an understanding of the etiology. In an attempt to group mental disorders on the basis of etiology, five clusters have been proposed. We consider the validity of the fifth cluster, externalizing disorders, within this proposal. We reviewed the literature in relation to 11 validating criteria proposed by the Study Group of the DSM-V Task Force, in terms of the extent to which these criteria support the idea of a coherent externalizing spectrum of disorders. This cluster distinguishes itself by the central role of disinhibitory personality in mental disorders spread throughout sections of the current classifications, including substance dependence, antisocial personality disorder and conduct disorder. Shared biomarkers, co-morbidity and course offer additional evidence for a valid cluster of externalizing disorders. Externalizing disorders meet many of the salient criteria proposed by the Study Group of the DSM-V Task Force to suggest a classification cluster.

Approximate cluster analysis method and three-dimensional diagram of optical characteristics of lunar surface

NASA Astrophysics Data System (ADS)

Yevsyukov, N. N.

1985-09-01

An approximate isolation algorithm for the isolation of multidimensional clusters is developed and applied in the construction of a three-dimensional diagram of the optical characteristics of the lunar surface. The method is somewhat analogous to that of Koontz and Fukunaga (1972) and involves isolating two-dimensional clusters, adding a new characteristic, and linearizing, a cycle which is repeated a limited number of times. The lunar-surface parameters analyzed are the 620-nm albedo, the 620/380-nm color index, and the 950/620-nm index. The results are presented graphically; the reliability of the cluster-isolation process is discussed; and some correspondences between known lunar morphology and the cluster maps are indicated.

Logistics Enterprise Evaluation Model Based On Fuzzy Clustering Analysis

NASA Astrophysics Data System (ADS)

Fu, Pei-hua; Yin, Hong-bo

In this thesis, we introduced an evaluation model based on fuzzy cluster algorithm of logistics enterprises. First of all,we present the evaluation index system which contains basic information, management level, technical strength, transport capacity,informatization level, market competition and customer service. We decided the index weight according to the grades, and evaluated integrate ability of the logistics enterprises using fuzzy cluster analysis method. In this thesis, we introduced the system evaluation module and cluster analysis module in detail and described how we achieved these two modules. At last, we gave the result of the system.

Competency Index. [Business/Computer Technologies Cluster.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Center on Education and Training for Employment.

This index allows the user to scan the competencies under each title for the 28 subjects appropriate for use in a competency list for the 12 occupations within the business/computer technologies cluster. Titles of the 28 units are as follows: employability skills; professionalism; teamwork; professional and ethical standards; economic and business…

75 FR 40857 - Webinar About Advanced Defense Technologies RFP

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-14

... Defense Technologies RFP. Please visit http://www.sba.gov/clusters/index.html for more information. The RFP may be found on http://www.fedbizopps.gov . LOGISTICAL INFORMATION: The webinar will be held on Monday, July 19, 2010. For details, please visit http://www.sba.gov/clusters/index.html . SUPPLEMENTARY...

Tensor contraction engine: Abstraction and automated parallel implementation of configuration-interaction, coupled-cluster, and many-body perturbation theories

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

Hirata, So

2003-11-20

We develop a symbolic manipulation program and program generator (Tensor Contraction Engine or TCE) that automatically derives the working equations of a well-defined model of second-quantized many-electron theories and synthesizes efficient parallel computer programs on the basis of these equations. Provided an ansatz of a many-electron theory model, TCE performs valid contractions of creation and annihilation operators according to Wick's theorem, consolidates identical terms, and reduces the expressions into the form of multiple tensor contractions acted by permutation operators. Subsequently, it determines the binary contraction order for each multiple tensor contraction with the minimal operation and memory cost, factorizes commonmore » binary contractions (defines intermediate tensors), and identifies reusable intermediates. The resulting ordered list of binary tensor contractions, additions, and index permutations is translated into an optimized program that is combined with the NWChem and UTChem computational chemistry software packages. The programs synthesized by TCE take advantage of spin symmetry, Abelian point-group symmetry, and index permutation symmetry at every stage of calculations to minimize the number of arithmetic operations and storage requirement, adjust the peak local memory usage by index range tiling, and support parallel I/O interfaces and dynamic load balancing for parallel executions. We demonstrate the utility of TCE through automatic derivation and implementation of parallel programs for various models of configuration-interaction theory (CISD, CISDT, CISDTQ), many-body perturbation theory [MBPT(2), MBPT(3), MBPT(4)], and coupled-cluster theory (LCCD, CCD, LCCSD, CCSD, QCISD, CCSDT, and CCSDTQ).« less

Prediction, Detection, and Validation of Isotope Clusters in Mass Spectrometry Data

PubMed Central

Treutler, Hendrik; Neumann, Steffen

2016-01-01

Mass spectrometry is a key analytical platform for metabolomics. The precise quantification and identification of small molecules is a prerequisite for elucidating the metabolism and the detection, validation, and evaluation of isotope clusters in LC-MS data is important for this task. Here, we present an approach for the improved detection of isotope clusters using chemical prior knowledge and the validation of detected isotope clusters depending on the substance mass using database statistics. We find remarkable improvements regarding the number of detected isotope clusters and are able to predict the correct molecular formula in the top three ranks in 92% of the cases. We make our methodology freely available as part of the Bioconductor packages xcms version 1.50.0 and CAMERA version 1.30.0. PMID:27775610

Initial derivation of diagnostic clusters combining history elements and physical examination tests for symptomatic knee osteoarthritis.

PubMed

Décary, Simon; Feldman, Debbie; Frémont, Pierre; Pelletier, Jean-Pierre; Martel-Pelletier, Johanne; Fallaha, Michel; Pelletier, Bruno; Belzile, Sylvain; Sylvestre, Marie-Pierre; Vendittoli, Pascal-André; Desmeules, François

2018-05-21

The aim of the present study was to assess the validity of clusters combining history elements and physical examination tests to diagnose symptomatic knee osteoarthritis (SOA) compared with other knee disorders. This was a prospective diagnostic accuracy study, in which 279 consecutive patients consulting for a knee complaint were assessed. History elements and standardized physical examination tests were obtained independently by a physiotherapist and compared with an expert physician's composite diagnosis, including clinical examination and imaging. Recursive partitioning was used to develop diagnostic clusters for SOA. Diagnostic accuracy measures were calculated, including sensitivity, specificity, and positive and negative likelihood ratios (LR+/-), with associated 95% confidence intervals (CIs). A total of 129 patients had a diagnosis of SOA (46.2%). Most cases (76%) had combined tibiofemoral and patellofemoral knee OA and 63% had radiological Kellgren-Lawrence grades of 2 or 3. Different combinations of history elements and physical examination tests were used in clusters accurately to discriminate SOA from other knee disorders. These included age of patients, body mass index, presence of valgus/varus knee misalignment, palpable knee crepitus and limited passive knee extension. Two clusters to rule in SOA reached an LR+ of 13.6 (95% CI 6.5 to 28.4) and three clusters to rule out SOA reached an LR- of 0.11 (95% CI 0.06 to 0.20). Diagnostic clusters combining history elements and physical examination tests were able to support the differential diagnosis of SOA compared with various knee disorders without relying systematically on imaging. This could support primary care clinicians' role in the efficient management of these patients. Copyright © 2018 John Wiley & Sons, Ltd.

Body Composition Indices and Single and Clustered Cardiovascular Disease Risk Factors in Adolescents: Providing Clinical-Based Cut-Points.

PubMed

Gracia-Marco, Luis; Moreno, Luis A; Ruiz, Jonatan R; Ortega, Francisco B; de Moraes, Augusto César Ferreira; Gottrand, Frederic; Roccaldo, Romana; Marcos, Ascensión; Gómez-Martínez, Sonia; Dallongeville, Jean; Kafatos, Anthony; Molnar, Denes; Bueno, Gloria; de Henauw, Stefaan; Widhalm, Kurt; Wells, Jonathan C

2016-01-01

The aims of the present study in adolescents were 1) to examine how various body composition-screening tests relate to single and clustered cardiovascular disease (CVD) risk factors, 2) to examine how lean mass and body fatness (independently of each other) relate to clustered CVD risk factors, and 3) to calculate specific thresholds for body composition indices associated with an unhealthier clustered CVD risk. We measured 1089 European adolescents (46.7% boys, 12.5-17.49years) in 2006-2007. CVD risk factors included: systolic blood pressure, maximum oxygen uptake, homeostasis model assessment, C-reactive protein (n=748), total cholesterol/high density lipoprotein cholesterol and triglycerides. Body composition indices included: height, body mass index (BMI), lean mass, the sum of four skinfolds, central/peripheral skinfolds, waist circumference (WC), waist-to-height ratio (WHtR) and waist-to-hip ratio (WHR). Most body composition indices are associated with single CVD risk factors. The sum of four skinfolds, WHtR, BMI, WC and lean mass are strong and positively associated with clustered CVD risk. Interestingly, lean mass is positively associated with clustered CVD risk independently of body fatness in girls. Moderate and highly accurate thresholds for the sum of four skinfolds, WHtR, BMI, WC and lean mass are associated with an unhealthier clustered CVD risk (all AUC>0.773). In conclusion, our results support an association between most of the assessed body composition indices and single and clustered CVD risk factors. In addition, lean mass (independent of body fatness) is positively associated with clustered CVD risk in girls, which is a novel finding that helps to understand why an index such as BMI is a good index of CVD risk but a bad index of adiposity. Moderate to highly accurate thresholds for body composition indices associated with a healthier clustered CVD risk were found. Further studies with a longitudinal design are needed to confirm these findings. Copyright © 2015 Elsevier Inc. All rights reserved.

A knowledge-driven approach to cluster validity assessment.

PubMed

Bolshakova, Nadia; Azuaje, Francisco; Cunningham, Pádraig

2005-05-15

This paper presents an approach to assessing cluster validity based on similarity knowledge extracted from the Gene Ontology. The program is freely available for non-profit use on request from the authors.

Polarization of the Sunyaev-Zel'dovich effect: relativistic imprint of thermal and non-thermal plasma

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

Emritte, Mohammad Shehzad; Colafrancesco, Sergio; Marchegiani, Paolo, E-mail: Sergio.Colafrancesco@wits.ac.za, E-mail: emrittes@yahoo.com, E-mail: Paolo.Marchegiani@wits.ac.za

2016-07-01

Inverse Compton (IC) scattering of the anisotropic CMB fluctuations off cosmic electron plasmas generates a polarization of the associated Sunyaev-Zel'dovich (SZ) effect. The polarized SZ effect has important applications in cosmology and in astrophysics of galaxy clusters. However, this signal has been studied so far mostly in the non-relativistic regime which is valid only in the very low electron temperature limit for a thermal electron population and, as such, has limited astrophysical applications. Partial attempts to extend this calculation to the IC scattering of a thermal electron plasma in the relativistic regime have been done but these cannot be appliedmore » to a more general or mildly relativistic electron distribution. In this paper we derive a general form of the SZ effect polarization that is valid in the full relativistic approach for both thermal and non-thermal electron plasmas, as well as for a generic combination of various electron population which can be co-spatially distributed in the environments of galaxy clusters or radiogalaxy lobes. We derive the spectral shape of the Stokes parameters induced by the IC scattering of every CMB multipole for both thermal and non-thermal electron populations, focussing in particular on the CMB quadrupole and octupole that provide the largest detectable signals in cosmic structures (like galaxy clusters). We found that the CMB quadrupole induced Stoke parameter Q is always positive with a maximum amplitude at a frequency ≈ 216 GHz which increases non-linearly with increasing cluster temperature. On the contrary, the CMB octupole induced Q spectrum shows a cross-over frequency which depends on the cluster electron temperature in a linear way, while it shows a non-linear dependence on the minimum momentum p {sub 1} of a non-thermal power-law spectrum as well as a linear dependence on the power-law spectral index of the non-thermal electron population. We discuss some of the possibilities to disentangle the quadrupole-induced Q spectrum from the octupole-induced one which will allow to measure these important cosmological quantities through the SZ effect polarization at different cluster locations in the universe. We finally apply our model to the Bullet cluster and derive the visibility windows of the total, quandrupole-induced and octupole-induced Stoke parameter Q in the frequency ranges accessible to SKA, ALMA, MILLIMETRON and CORE++ experiments.« less

Food consumption, body mass index and risk for oral health in adolescents.

PubMed

Bica, Isabel; Cunha, Madalena; Reis, Margarida; Costa, José; Costa, Patricia; Bica, Alexandra

2014-11-01

The food intake has great influence on the oral health of adolescents, being relevant to analyze the type of food consumed by adolescents and their relationship with the DMFT index (decayed, missing and filled), the plaque index (PI) and the body mass index (BMI). Epidemiological study conducted in public schools of the 3rd cycle of basic education, central Portugal. The sociodemographic and dietary habits and frequency characterization was obtained through a self-administered questionnaire completed by adolescents and validated for the population under study. The DMFT index was evaluated according to WHO criteria, oral hygiene was evaluated based on the plaque index and BMI through weight and height in adolescents. Random sample by clusters (schools) with 661 adolescents, 84.1% female and 15.9% male. Adolescents with mean age 13.22 years (± 1.139). The mean DMFT was 2.23 (± 2.484), the prevalence of PI was 96.4%, and ≥ 5 BMI <85. Adolescents with a higher DMFT index consume more cariogenic foods (r=0.160; P=.000). Adolescents with a higher BMI consume less cariogenic foods (r=-0.1343; P=.001). The value of t reveals that the consumption of cariogenic foods explains 1.8% of the variance of the BMI and 2.6% DMFT. The cariogenic foods are presented as a risk factor for dental caries. The results suggest that it is important to develop up actions for health education. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

Primary prevention of childhood obesity through counselling sessions at Swedish child health centres: design, methods and baseline sample characteristics of the PRIMROSE cluster-randomised trial.

PubMed

Döring, Nora; Hansson, Lena M; Andersson, Elina Scheers; Bohman, Benjamin; Westin, Maria; Magnusson, Margaretha; Larsson, Christel; Sundblom, Elinor; Willmer, Mikaela; Blennow, Margareta; Heitmann, Berit L; Forsberg, Lars; Wallin, Sanna; Tynelius, Per; Ghaderi, Ata; Rasmussen, Finn

2014-04-09

Childhood obesity is a growing concern in Sweden. Children with overweight and obesity run a high risk of becoming obese as adults, and are likely to develop comorbidities. Despite the immense demand, there is still a lack of evidence-based comprehensive prevention programmes targeting pre-school children and their families in primary health care settings. The aims are to describe the design and methodology of the PRIMROSE cluster-randomised controlled trial, assess the relative validity of a food frequency questionnaire, and describe the baseline characteristics of the eligible young children and their mothers. The PRIMROSE trial targets first-time parents and their children at Swedish child health centres (CHC) in eight counties in Sweden. Randomisation is conducted at the CHC unit level. CHC nurses employed at the participating CHC received training in carrying out the intervention alongside their provision of regular services. The intervention programme, starting when the child is 8-9 months of age and ending at age 4, is based on social cognitive theory and employs motivational interviewing. Primary outcomes are children's body mass index and waist circumference at four years. Secondary outcomes are children's and mothers' eating habits (assessed by a food frequency questionnaire), and children's and mothers' physical activity (measured by accelerometer and a validated questionnaire), and mothers' body mass index and waist circumference. The on-going population-based PRIMROSE trial, which targets childhood obesity, is embedded in the regular national (routine) preventive child health services that are available free-of-charge to all young families in Sweden. Of the participants (n = 1369), 489 intervention and 550 control mothers (75.9%) responded to the validated physical activity and food frequency questionnaire at baseline (i.e., before the first intervention session, or, for children in the control group, before they reached 10 months of age). The food frequency questionnaire showed acceptable relative validity when compared with an 8-day food diary. We are not aware of any previous RCT, concerned with the primary prevention of childhood obesity through sessions at CHC that addresses healthy eating habits and physical activity in the context of a routine child health services programme. ISRCTN16991919.

Invasion percolation between two sites in two, three, and four dimensions

NASA Astrophysics Data System (ADS)

Lee, Sang Bub

2009-06-01

The mass distribution of invaded clusters in non-trapping invasion percolation between an injection site and an extraction site has been studied, in two, three, and four dimensions. This study is an extension of the recent study focused on two dimensions by Araújo et al. [A.D. Araújo, T.F. Vasconcelos, A.A. Moreira, L.S. Lucena, J.S. Andrade Jr., Phys. Rev. E 72 (2005) 041404] with respect to higher dimensions. The mass distribution exhibits a power-law behavior, P(m)∝m. It has been found that the index α for pe

Environmental clustering of lakes to evaluate performance of a macrophyte index of biotic integrity

USGS Publications Warehouse

Vondracek, Bruce C.; Vondracek, Bruce; Hatch, Lorin K.

2013-01-01

Proper classification of sites is critical for the use of biological indices that can distinguish between natural and human-induced variation in biological response. The macrophyte-based index of biotic integrity was developed to assess the condition of Minnesota lakes in relation to anthropogenic stressors, but macrophyte community composition varies naturally across the state. The goal of the study was to identify environmental characteristics that naturally influence macrophyte index response and establish a preliminary lake classification scheme for biological assessment (bioassessment). Using a comprehensive set of environmental variables, we identified similar groups of lakes by clustering using flexible beta classification. Variance partitioning analysis of IBI response indicated that evaluating similar lake clusters could improve the ability of the macrophyte index to identify community change to anthropogenic stressors, although lake groups did not fully account for the natural variation in macrophyte composition. Diagnostic capabilities of the index could be improved when evaluating lakes with similar environmental characteristics, suggesting the index has potential for accurate bioassessment provided comparable groups of lakes are evaluated.

A Granular Self-Organizing Map for Clustering and Gene Selection in Microarray Data.

PubMed

Ray, Shubhra Sankar; Ganivada, Avatharam; Pal, Sankar K

2016-09-01

A new granular self-organizing map (GSOM) is developed by integrating the concept of a fuzzy rough set with the SOM. While training the GSOM, the weights of a winning neuron and the neighborhood neurons are updated through a modified learning procedure. The neighborhood is newly defined using the fuzzy rough sets. The clusters (granules) evolved by the GSOM are presented to a decision table as its decision classes. Based on the decision table, a method of gene selection is developed. The effectiveness of the GSOM is shown in both clustering samples and developing an unsupervised fuzzy rough feature selection (UFRFS) method for gene selection in microarray data. While the superior results of the GSOM, as compared with the related clustering methods, are provided in terms of β -index, DB-index, Dunn-index, and fuzzy rough entropy, the genes selected by the UFRFS are not only better in terms of classification accuracy and a feature evaluation index, but also statistically more significant than the related unsupervised methods. The C-codes of the GSOM and UFRFS are available online at http://avatharamg.webs.com/software-code.

The method of approximate cluster analysis and the three-dimensional diagram of optical characteristics of the lunar surface

NASA Astrophysics Data System (ADS)

Evsyukov, N. N.

1984-12-01

An approximate isolation algorithm for the isolation of multidimensional clusters is developed and applied in the construction of a three-dimensional diagram of the optical characteristics of the lunar surface. The method is somewhat analogous to that of Koontz and Fukunaga (1972) and involves isolating two-dimensional clusters, adding a new characteristic, and linearizing, a cycle which is repeated a limited number of times. The lunar-surface parameters analyzed are the 620-nm albedo, the 620/380-nm color index, and the 950/620-nm index. The results are presented graphically; the reliability of the cluster-isolation process is discussed; and some correspondences between known lunar morphology and the cluster maps are indicated.

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

PubMed

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

Evaluation of Potential LSST Spatial Indexing Strategies

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

Nikolaev, S; Abdulla, G; Matzke, R

2006-10-13

The LSST requirement for producing alerts in near real-time, and the fact that generating an alert depends on knowing the history of light variations for a given sky position, both imply that the clustering information for all detections is available at any time during the survey. Therefore, any data structure describing clustering of detections in LSST needs to be continuously updated, even as new detections are arriving from the pipeline. We call this use case ''incremental clustering'', to reflect this continuous updating of clustering information. This document describes the evaluation results for several potential LSST incremental clustering strategies, using: (1)more » Neighbors table and zone optimization to store spatial clusters (a.k.a. Jim Grey's, or SDSS algorithm); (2) MySQL built-in R-tree implementation; (3) an external spatial index library which supports a query interface.« less

Clustering stock market companies via chaotic map synchronization

NASA Astrophysics Data System (ADS)

Basalto, N.; Bellotti, R.; De Carlo, F.; Facchi, P.; Pascazio, S.

2005-01-01

A pairwise clustering approach is applied to the analysis of the Dow Jones index companies, in order to identify similar temporal behavior of the traded stock prices. To this end, the chaotic map clustering algorithm is used, where a map is associated to each company and the correlation coefficients of the financial time series to the coupling strengths between maps. The simulation of a chaotic map dynamics gives rise to a natural partition of the data, as companies belonging to the same industrial branch are often grouped together. The identification of clusters of companies of a given stock market index can be exploited in the portfolio optimization strategies.

Principal Cluster Axes: A Projection Pursuit Index for the Preservation of Cluster Structures in the Presence of Data Reduction

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.; Henson, Robert

2012-01-01

A measure of "clusterability" serves as the basis of a new methodology designed to preserve cluster structure in a reduced dimensional space. Similar to principal component analysis, which finds the direction of maximal variance in multivariate space, principal cluster axes find the direction of maximum clusterability in multivariate space.…

Environmental Conditions in Low-Income Urban Housing: Clustering and Associations With Self-Reported Health

PubMed Central

Spengler, John D.; Harley, Amy E.; Stoddard, Anne; Yang, May; Alvarez-Reeves, Marty; Sorensen, Glorian

2014-01-01

Objectives. We explored prevalence and clustering of key environmental conditions in low-income housing and associations with self-reported health. Methods. The Health in Common Study, conducted between 2005 and 2009, recruited participants (n = 828) from 20 low-income housing developments in the Boston area. We interviewed 1 participant per household and conducted a brief inspection of the unit (apartment). We created binary indexes and a summed index for household exposures: mold, combustion by-products, secondhand smoke, chemicals, pests, and inadequate ventilation. We used multivariable logistic regression to examine the associations between each index and household characteristics and between each index and self-reported health. Results. Environmental problems were common; more than half of homes had 3 or more exposure-related problems (median summed index = 3). After adjustment for household-level demographics, we found clustering of problems in site (P < .01) for pests, combustion byproducts, mold, and ventilation. Higher summed index values were associated with higher adjusted odds of reporting fair–poor health (odds ratio = 2.7 for highest category; P < .008 for trend). Conclusions. We found evidence that indoor environmental conditions in multifamily housing cluster by site and that cumulative exposures may be associated with poor health. PMID:24028244

Validating the Farsi version of the Pregnancy Worries and Stress Questionnaire (PWSQ): An exploratory factor analysis.

PubMed

Navidpour, Fariba; Dolatian, Mahrokh; Shishehgar, Sara; Yaghmaei, Farideh; Majd, Hamid Alavi; Hashemi, Seyed Saeed

2016-10-01

Biological, environmental, inter- and intrapersonal changes during the antenatal period can result in anxiety and stress in pregnant women. It is pivotal to identify potential stressors and prevent their foetal and maternal consequences. The present study was conducted to validate and examine the factor structure of the Farsi version of the Pregnancy Worries and Stress Questionnaire (PWSQ). In 2015, 502 Iranian healthy pregnant women, referred to selected hospitals in Tehran for prenatal care at 8-39 weeks of pregnancy, were recruited through a randomized cluster sampling. The PWSQ was translated into Farsi, and its validity and reliability were examined using exploratory factor analysis by SPSS version 21. The content validity of items on the PWSQ was between 0.63-1. The content validity index for relevance, clarity and simplicity were 0.92, 0.98, and 0.98, respectively, with a mean of 0.94. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.863. Test-retest reliability showed high internal consistency (α=0.89; p<0.0001). The psychometric evaluation and exploratory factor analysis showed that the translated questionnaire is a valid and reliable tool to identify stress in Iranian pregnant women. Application of the questionnaire can facilitate the diagnosis of stress in pregnant women and assist health care providers in providing timely support and minimizing negative outcomes of stress and anxiety in pregnant women and their infants.

Analysis of Basis Weight Uniformity of Microfiber Nonwovens and Its Impact on Permeability and Filtration Properties

NASA Astrophysics Data System (ADS)

Amirnasr, Elham

It is widely recognized that nonwoven basis weight non-uniformity affects various properties of nonwovens. However, few studies can be found in this topic. The development of uniformity definition and measurement methods and the study of their impact on various web properties such as filtration properties and air permeability would be beneficial both in industrial applications and in academia. They can be utilized as a quality control tool and would provide insights about nonwoven behaviors that cannot be solely explained by average values. Therefore, for quantifying nonwoven web basis weight uniformity we purse to develop an optical analytical tool. The quadrant method and clustering analysis was utilized in an image analysis scheme to help define "uniformity" and its spatial variation. Implementing the quadrant method in an image analysis system allows the establishment of a uniformity index that can be used to quantify the degree of uniformity. Clustering analysis has also been modified and verified using uniform and random simulated images with known parameters. Number of clusters and cluster properties such as cluster size, member and density was determined. We also utilized this new measurement method to evaluate uniformity of nonwovens produced with different processes and investigated impacts of uniformity on filtration and permeability. The results of quadrant method shows that uniformity index computed from quadrant method demonstrate a good range for non-uniformity of nonwoven webs. Clustering analysis is also been applied on reference nonwoven with known visual uniformity. From clustering analysis results, cluster size is promising to be used as uniformity parameter. It is been shown that non-uniform nonwovens has provide lager cluster size than uniform nonwovens. It was been tried to find a relationship between web properties and uniformity index (as a web characteristic). To achieve this, filtration properties, air permeability, solidity and uniformity index of meltblown and spunbond samples was measured. Results for filtration test show some deviation between theoretical and experimental filtration efficiency by considering different types of fiber diameter. This deviation can occur due to variation in basis weight non-uniformity. So an appropriate theory is required to predict the variation of filtration efficiency with respect to non-uniformity of nonwoven filter media. And the results for air permeability test showed that uniformity index determined by quadrant method and measured properties have some relationship. In the other word, air permeability decreases as uniformity index on nonwoven web increase.

Flow Cytometry with Gold Nanoparticles and their Clusters as scattering Contrast Agents: FDTD Simulation of Light-Cell Interaction

PubMed Central

Tanev, Stoyan; Sun, Wenbo; Pond, James; Tuchin, Valery V.; Zharov, Vladimir P.

2010-01-01

The formulation of the Finite-Difference Time-Domain (FDTD) approach is presented in the framework of its potential applications to in vivo flow cytometry based on light scattering. The consideration is focused on comparison of light scattering by a single biological cell alone in controlled refractive index matching conditions and by cells labeled by gold nanoparticles. The optical schematics including phase contrast (OPCM) microscopy as a prospective modality for in vivo flow cytometry is also analyzed. The validation of the FDTD approach for the simulation of flow cytometry may open a new avenue in the development of advanced cytometric techniques based on scattering effects from nanoscale targets. PMID:19670359

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation.

PubMed

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-04-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67x3 (67 clusters of three observations) and a 33x6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67x3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis.

The Nature of Indexing: How Humans and Machines Analyze Messages and Texts for Retrieval. Part II: Machine Indexing, and the Allocation of Human versus Machine Effort.

ERIC Educational Resources Information Center

Anderson, James D.; Perez-Carballo, Jose

2001-01-01

Discussion of human intellectual indexing versus automatic indexing focuses on automatic indexing. Topics include keyword indexing; negative vocabulary control; counting words; comparative counting and weighting; stemming; words versus phrases; clustering; latent semantic indexing; citation indexes; bibliographic coupling; co-citation; relevance…

Feasibility of feature-based indexing, clustering, and search of clinical trials: A case study of breast cancer trials from ClinicalTrials.gov

PubMed Central

Boland, Mary Regina; Miotto, Riccardo; Gao, Junfeng; Weng, Chunhua

2013-01-01

Summary Background When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. Objectives This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. Methods We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. Results We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. Conclusions It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency. PMID:23666475

Transmission and Progression to Disease of Mycobacterium tuberculosis Phylogenetic Lineages in The Netherlands.

PubMed

Nebenzahl-Guimaraes, Hanna; Verhagen, Lilly M; Borgdorff, Martien W; van Soolingen, Dick

2015-10-01

The aim of this study was to determine if mycobacterial lineages affect infection risk, clustering, and disease progression among Mycobacterium tuberculosis cases in The Netherlands. Multivariate negative binomial regression models adjusted for patient-related factors and stratified by patient ethnicity were used to determine the association between phylogenetic lineages and infectivity (mean number of positive contacts around each patient) and clustering (as defined by number of secondary cases within 2 years after diagnosis of an index case sharing the same fingerprint) indices. An estimate of progression to disease by each risk factor was calculated as a bootstrapped risk ratio of the clustering index by the infectivity index. Compared to the Euro-American reference, Mycobacterium africanum showed significantly lower infectivity and clustering indices in the foreign-born population, while Mycobacterium bovis showed significantly lower infectivity and clustering indices in the native population. Significantly lower infectivity was also observed for the East African Indian lineage in the foreign-born population. Smear positivity was a significant risk factor for increased infectivity and increased clustering. Estimates of progression to disease were significantly associated with age, sputum-smear status, and behavioral risk factors, such as alcohol and intravenous drug abuse, but not with phylogenetic lineages. In conclusion, we found evidence of a bacteriological factor influencing indicators of a strain's transmissibility, namely, a decreased ability to infect and a lower clustering index in ancient phylogenetic lineages compared to their modern counterparts. Confirmation of these findings via follow-up studies using tuberculin skin test conversion data should have important implications on M. tuberculosis control efforts. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Feasibility of feature-based indexing, clustering, and search of clinical trials. A case study of breast cancer trials from ClinicalTrials.gov.

PubMed

Boland, M R; Miotto, R; Gao, J; Weng, C

2013-01-01

When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency.

[Development and validation of the Family Vulnerability Index to Disability and Dependence (FVI-DD)].

PubMed

Amendola, Fernanda; Alvarenga, Márcia Regina Martins; Latorre, Maria do Rosário Dias de Oliveira; Oliveira, Maria Amélia de Campos

2014-02-01

This exploratory, descriptive, cross-sectional, and quantitative study aimed to develop and validate an index of family vulnerability to disability and dependence (FVI-DD). This study was adapted from the Family Development Index, with the addition of social and health indicators of disability and dependence. The instrument was applied to 248 families in the city of Sao Paulo, followed by exploratory factor analysis. Factor validation was performed using the concurrent and discriminant validity of the Lawton scale and Katz Index. The descriptive level adopted for the study was p < 0.05. The final vulnerability index comprised 50 questions classified into seven factors contemplating social and health dimensions, and this index exhibited good internal consistency (Cronbach's alpha = 0.82). FVI-DD was validated using both the Lawton scale and Katz Index. We conclude that FVI-DD can accurately and reliably assess family vulnerability to disability and dependence.

CRAWview: for viewing splicing variation, gene families, and polymorphism in clusters of ESTs and full-length sequences.

PubMed

Chou, A; Burke, J

1999-05-01

DNA sequence clustering has become a valuable method in support of gene discovery and gene expression analysis. Our interest lies in leveraging the sequence diversity within clusters of expressed sequence tags (ESTs) to model gene structure for the study of gene variants that arise from, among other things, alternative mRNA splicing, polymorphism, and divergence after gene duplication, fusion, and translocation events. In previous work, CRAW was developed to discover gene variants from assembled clusters of ESTs. Most importantly, novel gene features (the differing units between gene variants, for example alternative exons, polymorphisms, transposable elements, etc.) that are specialized to tissue, disease, population, or developmental states can be identified when these tools collate DNA source information with gene variant discrimination. While the goal is complete automation of novel feature and gene variant detection, current methods are far from perfect and hence the development of effective tools for visualization and exploratory data analysis are of paramount importance in the process of sifting through candidate genes and validating targets. We present CRAWview, a Java based visualization extension to CRAW. Features that vary between gene forms are displayed using an automatically generated color coded index. The reporting format of CRAWview gives a brief, high level summary report to display overlap and divergence within clusters of sequences as well as the ability to 'drill down' and see detailed information concerning regions of interest. Additionally, the alignment viewing and editing capabilities of CRAWview make it possible to interactively correct frame-shifts and otherwise edit cluster assemblies. We have implemented CRAWview as a Java application across windows NT/95 and UNIX platforms. A beta version of CRAWview will be freely available to academic users from Pangea Systems (http://www.pangeasystems.com). Contact :

Assessment of the climatic potential for tourism in Iran through biometeorology clustering.

PubMed

Roshan, Gholamreza; Yousefi, Robabe; Błażejczyk, Krzysztof

2018-04-01

This study presents a spatiotemporal analysis of bioclimatic comfort conditions for Iran using mean daily meteorological data from 1995 to 2014, analyzed through Physiological Equivalent Temperature (PET) index and Universal Thermal Climate Index (UTCI) indices, and bioclimatic clustering. The results of this study demonstrate that due to the climate variability across Iran during the year, there is at any point in time a location with climatic condition suitable for tourism. Mean values demonstrate maxima in bioclimatic comfort indices for the country in late winter and spring and minima for summer. Seven statistically significant clusters in bioclimatic indices were identified. Comparing these with clustering performed on PET and UTCI, the maximum overlaps between the two indices. In the following, the outputs of this research showed that most appropriate bioclimatic clustering for Iran includes seven clusters. These clustering locations according to climatic suitability for tourism provide a valuable contribution to tourism management in the country, particularly through marketing destinations to maximize tourist flow.

Validation Study of a Gatekeeping Attitude Index for Social Work Education

ERIC Educational Resources Information Center

Tam, Dora M. Y.; Coleman, Heather

2011-01-01

This article reports on a study designed to validate the Gatekeeping Attitude Index, a 14-item Likert scaling index. The authors collected data from a convenience sample of social work field instructors (N = 188) with a response rate of 74.0%. Construct validation by exploratory factor analysis identified a 2-factor solution on the index after…

Strains of Mycobacterium tuberculosis transmitting infection in Brazilian households and those associated with community transmission of tuberculosis.

PubMed

Vinhas, Solange Alves; Jones-López, Edward C; Ribeiro Rodrigues, Rodrigo; Gaeddert, Mary; Peres, Renata Lyrio; Marques-Rodrigues, Patricia; de Aguiar, Paola Poloni Lobo; White, Laura Forsberg; Alland, David; Salgame, Padmini; Hom, David; Ellner, Jerrold J; Dietze, Reynaldo; Collins, Lauren F; Shashkina, Elena; Kreiswirth, Barry; Palaci, Moisés

2017-05-01

Molecular epidemiologic studies have shown that the dynamics of tuberculosis transmission varies geographically. We sought to determine which strains of Mycobacterium tuberculosis (MTB) were infecting household contacts (HHC), and which were causing clusters of tuberculosis (TB) disease in Vitoria-ES, Brazil. A total of 741 households contacts (445 TST +) and 139 index cases were characterized according to the proportion of contacts in each household that had a tuberculin skin test positive: low (LT) (≤40% TST+), high (HT) (≥70% TST+) and (40-70% TST+) intermediate (IT) transmission. IS6110-RFLP and spoligotyping analysis were performed only 139 MTB isolates from index cases and 841 community isolates. Clustering occurred in 45% of the entire study population. There was no statistically significant association between MTB household transmission category and clustering. Within the household study population, the proportion of clusters in HT and LT groups was similar (31% and 36%, respectively; p = 0.82). Among index cases isolates associated with households demonstrating TST conversion, the frequency of unique pattern genotypes was higher for index cases of the LT compared to HT households (p = 0.03). We concluded that clusters and lineages associated with MTB infection in HT households had no proclivity for increased transmission of TB in the community. Copyright © 2017 Elsevier Ltd. All rights reserved.

Subject Indexing and Citation Indexing--Part I: Clustering Structure in the Cystic Fibrosis Document Collection [and] Part II: An Evaluation and Comparison.

ERIC Educational Resources Information Center

Shaw, W. M., Jr.

1990-01-01

These two articles discuss clustering structure in the Cystic Fibrosis Document Collection, which is derived from the National Library of Medicine's MEDLINE file. The exhaustivity of four subject representations and two citation representations is examined, and descriptor-weight thresholds and similarity thresholds are used to compute…

The ALICE Software Release Validation cluster

NASA Astrophysics Data System (ADS)

Berzano, D.; Krzewicki, M.

2015-12-01

One of the most important steps of software lifecycle is Quality Assurance: this process comprehends both automatic tests and manual reviews, and all of them must pass successfully before the software is approved for production. Some tests, such as source code static analysis, are executed on a single dedicated service: in High Energy Physics, a full simulation and reconstruction chain on a distributed computing environment, backed with a sample “golden” dataset, is also necessary for the quality sign off. The ALICE experiment uses dedicated and virtualized computing infrastructures for the Release Validation in order not to taint the production environment (i.e. CVMFS and the Grid) with non-validated software and validation jobs: the ALICE Release Validation cluster is a disposable virtual cluster appliance based on CernVM and the Virtual Analysis Facility, capable of deploying on demand, and with a single command, a dedicated virtual HTCondor cluster with an automatically scalable number of virtual workers on any cloud supporting the standard EC2 interface. Input and output data are externally stored on EOS, and a dedicated CVMFS service is used to provide the software to be validated. We will show how the Release Validation Cluster deployment and disposal are completely transparent for the Release Manager, who simply triggers the validation from the ALICE build system's web interface. CernVM 3, based entirely on CVMFS, permits to boot any snapshot of the operating system in time: we will show how this allows us to certify each ALICE software release for an exact CernVM snapshot, addressing the problem of Long Term Data Preservation by ensuring a consistent environment for software execution and data reprocessing in the future.

Characterization of Patients Who Present With Insomnia: Is There Room for a Symptom Cluster-Based Approach?

PubMed Central

Crawford, Megan R.; Chirinos, Diana A.; Iurcotta, Toni; Edinger, Jack D.; Wyatt, James K.; Manber, Rachel; Ong, Jason C.

2017-01-01

Study Objectives: This study examined empirically derived symptom cluster profiles among patients who present with insomnia using clinical data and polysomnography. Methods: Latent profile analysis was used to identify symptom cluster profiles of 175 individuals (63% female) with insomnia disorder based on total scores on validated self-report instruments of daytime and nighttime symptoms (Insomnia Severity Index, Glasgow Sleep Effort Scale, Fatigue Severity Scale, Beliefs and Attitudes about Sleep, Epworth Sleepiness Scale, Pre-Sleep Arousal Scale), mean values from a 7-day sleep diary (sleep onset latency, wake after sleep onset, and sleep efficiency), and total sleep time derived from an in-laboratory PSG. Results: The best-fitting model had three symptom cluster profiles: “High Subjective Wakefulness” (HSW), “Mild Insomnia” (MI) and “Insomnia-Related Distress” (IRD). The HSW symptom cluster profile (26.3% of the sample) reported high wake after sleep onset, high sleep onset latency, and low sleep efficiency. Despite relatively comparable PSG-derived total sleep time, they reported greater levels of daytime sleepiness. The MI symptom cluster profile (45.1%) reported the least disturbance in the sleep diary and questionnaires and had the highest sleep efficiency. The IRD symptom cluster profile (28.6%) reported the highest mean scores on the insomnia-related distress measures (eg, sleep effort and arousal) and waking correlates (fatigue). Covariates associated with symptom cluster membership were older age for the HSW profile, greater obstructive sleep apnea severity for the MI profile, and, when adjusting for obstructive sleep apnea severity, being overweight/obese for the IRD profile. Conclusions: The heterogeneous nature of insomnia disorder is captured by this data-driven approach to identify symptom cluster profiles. The adaptation of a symptom cluster-based approach could guide tailored patient-centered management of patients presenting with insomnia, and enhance patient care. Citation: Crawford MR, Chirinos DA, Iurcotta T, Edinger JD, Wyatt JK, Manber R, Ong JC. Characterization of patients who present with insomnia: is there room for a symptom cluster-based approach? J Clin Sleep Med. 2017;13(7):911–921. PMID:28633722

Speaker Linking and Applications using Non-Parametric Hashing Methods

DTIC Science & Technology

2016-09-08

clustering method based on hashing—canopy- clustering . We apply this method to a large corpus of speaker recordings, demonstrate performance tradeoffs...and compare to other hash- ing methods. Index Terms: speaker recognition, clustering , hashing, locality sensitive hashing. 1. Introduction We assume...speaker in our corpus. Second, given a QBE method, how can we perform speaker clustering —each clustering should be a single speaker, and a cluster should

Psychosocial Clusters and their Associations with Well-Being and Health: An Empirical Strategy for Identifying Psychosocial Predictors Most Relevant to Racially/Ethnically Diverse Women’s Health

PubMed Central

Jabson, Jennifer M.; Bowen, Deborah; Weinberg, Janice; Kroenke, Candyce; Luo, Juhua; Messina, Catherine; Shumaker, Sally; Tindle, Hilary A.

2016-01-01

BACKGROUND Strategies for identifying the most relevant psychosocial predictors in studies of racial/ethnic minority women’s health are limited because they largely exclude cultural influences and they assume that psychosocial predictors are independent. This paper proposes and tests an empirical solution. METHODS Hierarchical cluster analysis, conducted with data from 140,652 Women’s Health Initiative participants, identified clusters among individual psychosocial predictors. Multivariable analyses tested associations between clusters and health outcomes. RESULTS A Social Cluster and a Stress Cluster were identified. The Social Cluster was positively associated with well-being and inversely associated with chronic disease index, and the Stress Cluster was inversely associated with well-being and positively associated with chronic disease index. As hypothesized, the magnitude of association between clusters and outcomes differed by race/ethnicity. CONCLUSIONS By identifying psychosocial clusters and their associations with health, we have taken an important step toward understanding how individual psychosocial predictors interrelate and how empirically formed Stress and Social clusters relate to health outcomes. This study has also demonstrated important insight about differences in associations between these psychosocial clusters and health among racial/ethnic minorities. These differences could signal the best pathways for intervention modification and tailoring. PMID:27279761

Mining the National Career Assessment Examination Result Using Clustering Algorithm

NASA Astrophysics Data System (ADS)

Pagudpud, M. V.; Palaoag, T. T.; Padirayon, L. M.

2018-03-01

Education is an essential process today which elicits authorities to discover and establish innovative strategies for educational improvement. This study applied data mining using clustering technique for knowledge extraction from the National Career Assessment Examination (NCAE) result in the Division of Quirino. The NCAE is an examination given to all grade 9 students in the Philippines to assess their aptitudes in the different domains. Clustering the students is helpful in identifying students’ learning considerations. With the use of the RapidMiner tool, clustering algorithms such as Density-Based Spatial Clustering of Applications with Noise (DBSCAN), k-means, k-medoid, expectation maximization clustering, and support vector clustering algorithms were analyzed. The silhouette indexes of the said clustering algorithms were compared, and the result showed that the k-means algorithm with k = 3 and silhouette index equal to 0.196 is the most appropriate clustering algorithm to group the students. Three groups were formed having 477 students in the determined group (cluster 0), 310 proficient students (cluster 1) and 396 developing students (cluster 2). The data mining technique used in this study is essential in extracting useful information from the NCAE result to better understand the abilities of students which in turn is a good basis for adopting teaching strategies.

Developing the Persian version of the homophone meaning generation test

PubMed Central

Ebrahimipour, Mona; Motamed, Mohammad Reza; Ashayeri, Hassan; Modarresi, Yahya; Kamali, Mohammad

2016-01-01

Background: Finding the right word is a necessity in communication, and its evaluation has always been a challenging clinical issue, suggesting the need for valid and reliable measurements. The Homophone Meaning Generation Test (HMGT) can measure the ability to switch between verbal concepts, which is required in word retrieval. The purpose of this study was to adapt and validate the Persian version of the HMGT. Methods: The first phase involved the adaptation of the HMGT to the Persian language. The second phase concerned the psychometric testing. The word-finding performance was assessed in 90 Persian-speaking healthy individuals (20-50 year old; 45 males and 45 females) through three naming tasks: Semantic Fluency, Phonemic Fluency, and Homophone Meaning Generation Test. The participants had no history of neurological or psychiatric diseases, alcohol abuse, severe depression, or history of speech, language, or learning problems. Results: The internal consistency coefficient was larger than 0.8 for all the items with a total Cronbach’s alpha of 0.80. Interrater and intrarater reliability were also excellent. The validity of all items was above 0.77, and the content validity index (0.99) was appropriate. The Persian HMGT had strong convergent validity with semantic and phonemic switching and adequate divergent validity with semantic and phonemic clustering. Conclusion: The Persian version of the Homophone Meaning Generation Test is an appropriate, valid, and reliable test to evaluate the ability to switch between verbal concepts in the assessment of word-finding performance. PMID:27390705

Developing the Persian version of the homophone meaning generation test.

PubMed

Ebrahimipour, Mona; Motamed, Mohammad Reza; Ashayeri, Hassan; Modarresi, Yahya; Kamali, Mohammad

2016-01-01

Finding the right word is a necessity in communication, and its evaluation has always been a challenging clinical issue, suggesting the need for valid and reliable measurements. The Homophone Meaning Generation Test (HMGT) can measure the ability to switch between verbal concepts, which is required in word retrieval. The purpose of this study was to adapt and validate the Persian version of the HMGT. The first phase involved the adaptation of the HMGT to the Persian language. The second phase concerned the psychometric testing. The word-finding performance was assessed in 90 Persian-speaking healthy individuals (20-50 year old; 45 males and 45 females) through three naming tasks: Semantic Fluency, Phonemic Fluency, and Homophone Meaning Generation Test. The participants had no history of neurological or psychiatric diseases, alcohol abuse, severe depression, or history of speech, language, or learning problems. The internal consistency coefficient was larger than 0.8 for all the items with a total Cronbach's alpha of 0.80. Interrater and intrarater reliability were also excellent. The validity of all items was above 0.77, and the content validity index (0.99) was appropriate. The Persian HMGT had strong convergent validity with semantic and phonemic switching and adequate divergent validity with semantic and phonemic clustering. The Persian version of the Homophone Meaning Generation Test is an appropriate, valid, and reliable test to evaluate the ability to switch between verbal concepts in the assessment of word-finding performance.

Neurocognitive disorders: cluster 1 of the proposed meta-structure for DSM-V and ICD-11.

PubMed

Sachdev, P; Andrews, G; Hobbs, M J; Sunderland, M; Anderson, T M

2009-12-01

In an effort to group mental disorders on the basis of aetiology, five clusters have been proposed. In this paper, we consider the validity of the first cluster, neurocognitive disorders, within this proposal. These disorders are categorized as 'Dementia, Delirium, and Amnestic and Other Cognitive Disorders' in DSM-IV and 'Organic, including Symptomatic Mental Disorders' in ICD-10. We reviewed the literature in relation to 11 validating criteria proposed by a Study Group of the DSM-V Task Force as applied to the cluster of neurocognitive disorders. 'Neurocognitive' replaces the previous terms 'cognitive' and 'organic' used in DSM-IV and ICD-10 respectively as the descriptor for disorders in this cluster. Although cognitive/organic problems are present in other disorders, this cluster distinguishes itself by the demonstrable neural substrate abnormalities and the salience of cognitive symptoms and deficits. Shared biomarkers, co-morbidity and course offer less persuasive evidence for a valid cluster of neurocognitive disorders. The occurrence of these disorders subsequent to normal brain development sets this cluster apart from neurodevelopmental disorders. The aetiology of the disorders is varied, but the neurobiological underpinnings are better understood than for mental disorders in any other cluster. Neurocognitive disorders meet some of the salient criteria proposed by the Study Group of the DSM-V Task Force to suggest a classification cluster. Further developments in the aetiopathogenesis of these disorders will enhance the clinical utility of this cluster.

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

PubMed

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

2014-02-01

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

A robust Multi-Band Water Index (MBWI) for automated extraction of surface water from Landsat 8 OLI imagery

NASA Astrophysics Data System (ADS)

Wang, Xiaobiao; Xie, Shunping; Zhang, Xueliang; Chen, Cheng; Guo, Hao; Du, Jinkang; Duan, Zheng

2018-06-01

Surface water is vital resources for terrestrial life, while the rapid development of urbanization results in diverse changes in sizes, amounts, and quality of surface water. To accurately extract surface water from remote sensing imagery is very important for water environment conservations and water resource management. In this study, a new Multi-Band Water Index (MBWI) for Landsat 8 Operational Land Imager (OLI) images is proposed by maximizing the spectral difference between water and non-water surfaces using pure pixels. Based on the MBWI map, the K-means cluster method is applied to automatically extract surface water. The performance of MBWI is validated and compared with six widely used water indices in 29 sites of China. Results show that our proposed MBWI performs best with the highest accuracy in 26 out of the 29 test sites. Compared with other water indices, the MBWI results in lower mean water total errors by a range of 9.31%-25.99%, and higher mean overall accuracies and kappa coefficients by 0.87%-3.73% and 0.06-0.18, respectively. It is also demonstrated for MBWI in terms of robustly discriminating surface water from confused backgrounds that are usually sources of surface water extraction errors, e.g., mountainous shadows and dark built-up areas. In addition, the new index is validated to be able to mitigate the seasonal and daily influences resulting from the variations of the solar condition. MBWI holds the potential to be a useful surface water extraction technology for water resource studies and applications.

A system for counting fetal and maternal red blood cells.

PubMed

Ge, Ji; Gong, Zheng; Chen, Jun; Liu, Jun; Nguyen, John; Yang, Zongyi; Wang, Chen; Sun, Yu

2014-12-01

The Kleihauer-Betke (KB) test is the standard method for quantitating fetal-maternal hemorrhage in maternal care. In hospitals, the KB test is performed by a certified technologist to count a minimum of 2000 fetal and maternal red blood cells (RBCs) on a blood smear. Manual counting suffers from inherent inconsistency and unreliability. This paper describes a system for automated counting and distinguishing fetal and maternal RBCs on clinical KB slides. A custom-adapted hardware platform is used for KB slide scanning and image capturing. Spatial-color pixel classification with spectral clustering is proposed to separate overlapping cells. Optimal clustering number and total cell number are obtained through maximizing cluster validity index. To accurately identify fetal RBCs from maternal RBCs, multiple features including cell size, roundness, gradient, and saturation difference between cell and whole slide are used in supervised learning to generate feature vectors, to tackle cell color, shape, and contrast variations across clinical KB slides. The results show that the automated system is capable of completing the counting of over 60,000 cells (versus ∼2000 by technologists) within 5 min (versus ∼15 min by technologists). The throughput is improved by approximately 90 times compared to manual reading by technologists. The counting results are highly accurate and correlate strongly with those from benchmarking flow cytometry measurement.

Item validity vs. item discrimination index: a redundancy?

NASA Astrophysics Data System (ADS)

Panjaitan, R. L.; Irawati, R.; Sujana, A.; Hanifah, N.; Djuanda, D.

2018-03-01

In several literatures about evaluation and test analysis, it is common to find that there are calculations of item validity as well as item discrimination index (D) with different formula for each. Meanwhile, other resources said that item discrimination index could be obtained by calculating the correlation between the testee’s score in a particular item and the testee’s score on the overall test, which is actually the same concept as item validity. Some research reports, especially undergraduate theses tend to include both item validity and item discrimination index in the instrument analysis. It seems that these concepts might overlap for both reflect the test quality on measuring the examinees’ ability. In this paper, examples of some results of data processing on item validity and item discrimination index were compared. It would be discussed whether item validity and item discrimination index can be represented by one of them only or it should be better to present both calculations for simple test analysis, especially in undergraduate theses where test analyses were included.

Trends of Educational Technology Research: More than a Decade of International Research in Six SSCI-Indexed Refereed Journals

ERIC Educational Resources Information Center

Hsu, Yu-Chang; Hung, Jui-Long; Ching, Yu-Hui

2013-01-01

This study applied text mining methods to examine the abstracts of 2,997 international research articles published between 2000 and 2010 by six journals included in the Social Science Citation Index in the field of Educational Technology (EDTECH). A total of 19 clusters of research areas were identified, and these clusters were further analyzed in…

Cross validation issues in multiobjective clustering

PubMed Central

Brusco, Michael J.; Steinley, Douglas

2018-01-01

The implementation of multiobjective programming methods in combinatorial data analysis is an emergent area of study with a variety of pragmatic applications in the behavioural sciences. Most notably, multiobjective programming provides a tool for analysts to model trade offs among competing criteria in clustering, seriation, and unidimensional scaling tasks. Although multiobjective programming has considerable promise, the technique can produce numerically appealing results that lack empirical validity. With this issue in mind, the purpose of this paper is to briefly review viable areas of application for multiobjective programming and, more importantly, to outline the importance of cross-validation when using this method in cluster analysis. PMID:19055857

Severity of illness index for surgical departments in a Cuban hospital: a revalidation study.

PubMed

Armas-Bencomo, Amadys; Tamargo-Barbeito, Teddy Osmin; Fuentes-Valdés, Edelberto; Jiménez-Paneque, Rosa Eugenia

2017-03-08

In the context of the evaluation of hospital services, the incorporation of severity indices allows an essential control variable for performance comparisons in time and space through risk adjustment. The severity index for surgical services was developed in 1999 and validated as a general index for surgical services. Sixteen years later the hospital context is different in many ways and a revalidation was considered necessary to guarantee its current usefulness. To evaluate the validity and reliability of the surgical services severity index to warrant its reasonable use under current conditions. A descriptive study was carried out in the General Surgery service of the "Hermanos Ameijeiras" Clinical Surgical Hospital of Havana, Cuba during the second half of 2010. We reviewed the medical records of 511 patients discharged from this service. Items were the same as the original index as were their weighted values. Conceptual or construct validity, criterion validity and inter-rater reliability as well as internal consistency of the proposed index were evaluated. Construct validity was expressed as a significant association between the value of the severity index for surgical services and discharge status. A significant association was also found, although weak, with length of hospital stay. Criterion validity was demonstrated through the correlations between the severity index for surgical services and other similar indices. Regarding criterion validity, the Horn index showed a correlation of 0.722 (95% CI: 0.677-0.761) with our index. With the POSSUM score, correlation was 0.454 (95% CI: 0.388-0.514) with mortality risk and 0.539 (95% CI: 0.462-0.607) with morbidity risk. Internal consistency yielded a standardized Cronbach's alpha of 0.8; inter-rater reliability resulted in a reliability coefficient of 0.98 for the quantitative index and a weighted global Kappa coefficient of 0.87 for the ordinal surgical index of severity for surgical services (IGQ). The validity and reliability of the proposed index was satisfactory in all aspects evaluated. The surgical services severity index may be used in the original context and is easily adaptable to other contexts as well.

Evidence based community mobilization for dengue prevention in Nicaragua and Mexico (Camino Verde, the Green Way): cluster randomized controlled trial

PubMed Central

Nava-Aguilera, Elizabeth; Arosteguí, Jorge; Morales-Perez, Arcadio; Suazo-Laguna, Harold; Legorreta-Soberanis, José; Hernandez-Alvarez, Carlos; Fernandez-Salas, Ildefonso; Paredes-Solís, Sergio; Balmaseda, Angel; Cortés-Guzmán, Antonio Juan; Serrano de los Santos, René; Coloma, Josefina; Ledogar, Robert J; Harris, Eva

2015-01-01

Objective To test whether community mobilization adds effectiveness to conventional dengue control. Design Pragmatic open label parallel group cluster randomized controlled trial. Those assessing the outcomes and analyzing the data were blinded to group assignment. Centralized computerized randomization after the baseline study allocated half the sites to intervention, stratified by country, evidence of recent dengue virus infection in children aged 3-9, and vector indices. Setting Random sample of communities in Managua, capital of Nicaragua, and three coastal regions in Guerrero State in the south of Mexico. Participants Residents in a random sample of census enumeration areas across both countries: 75 intervention and 75 control clusters (about 140 households each) were randomized and analyzed (60 clusters in Nicaragua and 90 in Mexico), including 85 182 residents in 18 838 households. Interventions A community mobilization protocol began with community discussion of baseline results. Each intervention cluster adapted the basic intervention—chemical-free prevention of mosquito reproduction—to its own circumstances. All clusters continued the government run dengue control program. Main outcome measures Primary outcomes per protocol were self reported cases of dengue, serological evidence of recent dengue virus infection, and conventional entomological indices (house index: households with larvae or pupae/households examined; container index: containers with larvae or pupae/containers examined; Breteau index: containers with larvae or pupae/households examined; and pupae per person: pupae found/number of residents). Per protocol secondary analysis examined the effect of Camino Verde in the context of temephos use. Results With cluster as the unit of analysis, serological evidence from intervention sites showed a lower risk of infection with dengue virus in children (relative risk reduction 29.5%, 95% confidence interval 3.8% to 55.3%), fewer reports of dengue illness (24.7%, 1.8% to 51.2%), fewer houses with larvae or pupae among houses visited (house index) (44.1%, 13.6% to 74.7%), fewer containers with larvae or pupae among containers examined (container index) (36.7%, 24.5% to 44.8%), fewer containers with larvae or pupae among houses visited (Breteau index) (35.1%, 16.7% to 55.5%), and fewer pupae per person (51.7%, 36.2% to 76.1%). The numbers needed to treat were 30 (95% confidence interval 20 to 59) for a lower risk of infection in children, 71 (48 to 143) for fewer reports of dengue illness, 17 (14 to 20) for the house index, 37 (35 to 67) for the container index, 10 (6 to 29) for the Breteau index, and 12 (7 to 31) for fewer pupae per person. Secondary per protocol analysis showed no serological evidence of a protective effect of temephos. Conclusions Evidence based community mobilization can add effectiveness to dengue vector control. Each site implementing the intervention in its own way has the advantage of local customization and strong community engagement. Trial registration ISRCTN27581154 PMID:26156323

Evidence based community mobilization for dengue prevention in Nicaragua and Mexico (Camino Verde, the Green Way): cluster randomized controlled trial.

PubMed

Andersson, Neil; Nava-Aguilera, Elizabeth; Arosteguí, Jorge; Morales-Perez, Arcadio; Suazo-Laguna, Harold; Legorreta-Soberanis, José; Hernandez-Alvarez, Carlos; Fernandez-Salas, Ildefonso; Paredes-Solís, Sergio; Balmaseda, Angel; Cortés-Guzmán, Antonio Juan; Serrano de Los Santos, René; Coloma, Josefina; Ledogar, Robert J; Harris, Eva

2015-07-08

To test whether community mobilization adds effectiveness to conventional dengue control. Pragmatic open label parallel group cluster randomized controlled trial. Those assessing the outcomes and analyzing the data were blinded to group assignment. Centralized computerized randomization after the baseline study allocated half the sites to intervention, stratified by country, evidence of recent dengue virus infection in children aged 3-9, and vector indices. Random sample of communities in Managua, capital of Nicaragua, and three coastal regions in Guerrero State in the south of Mexico. Residents in a random sample of census enumeration areas across both countries: 75 intervention and 75 control clusters (about 140 households each) were randomized and analyzed (60 clusters in Nicaragua and 90 in Mexico), including 85,182 residents in 18,838 households. A community mobilization protocol began with community discussion of baseline results. Each intervention cluster adapted the basic intervention-chemical-free prevention of mosquito reproduction-to its own circumstances. All clusters continued the government run dengue control program. Primary outcomes per protocol were self reported cases of dengue, serological evidence of recent dengue virus infection, and conventional entomological indices (house index: households with larvae or pupae/households examined; container index: containers with larvae or pupae/containers examined; Breteau index: containers with larvae or pupae/households examined; and pupae per person: pupae found/number of residents). Per protocol secondary analysis examined the effect of Camino Verde in the context of temephos use. With cluster as the unit of analysis, serological evidence from intervention sites showed a lower risk of infection with dengue virus in children (relative risk reduction 29.5%, 95% confidence interval 3.8% to 55.3%), fewer reports of dengue illness (24.7%, 1.8% to 51.2%), fewer houses with larvae or pupae among houses visited (house index) (44.1%, 13.6% to 74.7%), fewer containers with larvae or pupae among containers examined (container index) (36.7%, 24.5% to 44.8%), fewer containers with larvae or pupae among houses visited (Breteau index) (35.1%, 16.7% to 55.5%), and fewer pupae per person (51.7%, 36.2% to 76.1%). The numbers needed to treat were 30 (95% confidence interval 20 to 59) for a lower risk of infection in children, 71 (48 to 143) for fewer reports of dengue illness, 17 (14 to 20) for the house index, 37 (35 to 67) for the container index, 10 (6 to 29) for the Breteau index, and 12 (7 to 31) for fewer pupae per person. Secondary per protocol analysis showed no serological evidence of a protective effect of temephos. Evidence based community mobilization can add effectiveness to dengue vector control. Each site implementing the intervention in its own way has the advantage of local customization and strong community engagement. ISRCTN27581154. © Andersson et al 2015.

Cluster analysis of molecular simulation trajectories for systems where both conformation and orientation of the sampled states are important.

PubMed

Abramyan, Tigran M; Snyder, James A; Thyparambil, Aby A; Stuart, Steven J; Latour, Robert A

2016-08-05

Clustering methods have been widely used to group together similar conformational states from molecular simulations of biomolecules in solution. For applications such as the interaction of a protein with a surface, the orientation of the protein relative to the surface is also an important clustering parameter because of its potential effect on adsorbed-state bioactivity. This study presents cluster analysis methods that are specifically designed for systems where both molecular orientation and conformation are important, and the methods are demonstrated using test cases of adsorbed proteins for validation. Additionally, because cluster analysis can be a very subjective process, an objective procedure for identifying both the optimal number of clusters and the best clustering algorithm to be applied to analyze a given dataset is presented. The method is demonstrated for several agglomerative hierarchical clustering algorithms used in conjunction with three cluster validation techniques. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Integrating data from randomized controlled trials and observational studies to predict the response to pregabalin in patients with painful diabetic peripheral neuropathy.

PubMed

Alexander, Joe; Edwards, Roger A; Savoldelli, Alberto; Manca, Luigi; Grugni, Roberto; Emir, Birol; Whalen, Ed; Watt, Stephen; Brodsky, Marina; Parsons, Bruce

2017-07-20

More patient-specific medical care is expected as more is learned about variations in patient responses to medical treatments. Analytical tools enable insights by linking treatment responses from different types of studies, such as randomized controlled trials (RCTs) and observational studies. Given the importance of evidence from both types of studies, our goal was to integrate these types of data into a single predictive platform to help predict response to pregabalin in individual patients with painful diabetic peripheral neuropathy (pDPN). We utilized three pivotal RCTs of pregabalin (398 North American patients) and the largest observational study of pregabalin (3159 German patients). We implemented a hierarchical cluster analysis to identify patient clusters in the Observational Study to which RCT patients could be matched using the coarsened exact matching (CEM) technique, thereby creating a matched dataset. We then developed autoregressive moving average models (ARMAXs) to estimate weekly pain scores for pregabalin-treated patients in each cluster in the matched dataset using the maximum likelihood method. Finally, we validated ARMAX models using Observational Study patients who had not matched with RCT patients, using t tests between observed and predicted pain scores. Cluster analysis yielded six clusters (287-777 patients each) with the following clustering variables: gender, age, pDPN duration, body mass index, depression history, pregabalin monotherapy, prior gabapentin use, baseline pain score, and baseline sleep interference. CEM yielded 1528 unique patients in the matched dataset. The reduction in global imbalance scores for the clusters after adding the RCT patients (ranging from 6 to 63% depending on the cluster) demonstrated that the process reduced the bias of covariates in five of the six clusters. ARMAX models of pain score performed well (R 2 : 0.85-0.91; root mean square errors: 0.53-0.57). t tests did not show differences between observed and predicted pain scores in the 1955 patients who had not matched with RCT patients. The combination of cluster analyses, CEM, and ARMAX modeling enabled strong predictive capabilities with respect to pain scores. Integrating RCT and Observational Study data using CEM enabled effective use of Observational Study data to predict patient responses.

Examining Factor Structure and Validating the Persian Version of the Pregnancy's Worries and Stress Questionnaire for Pregnant Iranian Women.

PubMed

Navidpour, Fariba; Dolatian, Mahrokh; Yaghmaei, Farideh; Majd, Hamid Alavi; Hashemi, Seyed Saeed

2015-04-23

Pregnant women tend to experience anxiety and stress when faced with the changes to their biology, environment and personal relationships. The identification of these factors and the prevention of their side effects are vital for both mother and fetus. The present study was conducted to validate and to examine the factor structure of the Persian version of the Pregnancy's Worries and Stress Questionnaire. The 25-item PWSQ was first translated by specialists into Persian. The questionnaire's validity was determined using face, content, criterion and construct validity and reliability of questionnaire was examined using Cronbach's alpha. Confirmatory factor analysis was performed in AMOS and SPSS 21. Participants included healthy Iranian pregnant women (8-39 weeks) who refer to selected hospitals for prenatal care. Hospitals included private, social security and university hospitals and selected through the random cluster sampling method. The results of validity and reliability assessments of the questionnaire were acceptable. Cronbach's alpha calculated showed a high internal consistency of 0.89. The confirmatory factor analysis using the c2, CMIN/DF, IFI, CFI, NFI and NNFI indexes showed the 6-factor model to be the best fitted model for explaining the data. The questionnaire was translated into Persian to examine stress and worry specific to Iranian pregnant women. The psychometric results showed that the questionnaire is suitable for identifying Iranian pregnant women with pregnancy-related stress.

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation

PubMed Central

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-01-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67×3 (67 clusters of three observations) and a 33×6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67×3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis. PMID:20011037

The Spatial Distribution of the Young Stellar Clusters in the Star-forming Galaxy NGC 628

NASA Astrophysics Data System (ADS)

Grasha, K.; Calzetti, D.; Adamo, A.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Aloisi, A.; Bright, S. N.; Christian, C.; Cignoni, M.; Dale, D. A.; Dobbs, C.; Elmegreen, D. M.; Fumagalli, M.; Gallagher, J. S., III; Grebel, E. K.; Johnson, K. E.; Lee, J. C.; Messa, M.; Smith, L. J.; Ryon, J. E.; Thilker, D.; Ubeda, L.; Wofford, A.

2015-12-01

We present a study of the spatial distribution of the stellar cluster populations in the star-forming galaxy NGC 628. Using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey), we have identified 1392 potential young (≲ 100 Myr) stellar clusters within the galaxy using a combination of visual inspection and automatic selection. We investigate the clustering of these young stellar clusters and quantify the strength and change of clustering strength with scale using the two-point correlation function. We also investigate how image boundary conditions and dust lanes affect the observed clustering. The distribution of the clusters is well fit by a broken power law with negative exponent α. We recover a weighted mean index of α ∼ -0.8 for all spatial scales below the break at 3.″3 (158 pc at a distance of 9.9 Mpc) and an index of α ∼ -0.18 above 158 pc for the accumulation of all cluster types. The strength of the clustering increases with decreasing age and clusters older than 40 Myr lose their clustered structure very rapidly and tend to be randomly distributed in this galaxy, whereas the mass of the star cluster has little effect on the clustering strength. This is consistent with results from other studies that the morphological hierarchy in stellar clustering resembles the same hierarchy as the turbulent interstellar medium.

Association between elder abuse and poor sleep: A cross-sectional study among rural older Malaysians.

PubMed

Yunus, Raudah Mohd; Wazid, Syeda Wasfeea; Hairi, Noran N; Choo, Wan Yuen; Hairi, Farizah M; Sooryanarayana, Rajini; Ahmad, Sharifah N; Razak, Inayah A; Peramalah, Devi; Aziz, Suriyati A; Mohamad, Zaiton L; Mohamad, Rosmala; Ali, Zainudin M; Bulgiba, Awang

2017-01-01

To examine the association between elder abuse and poor sleep using a Malay validated version of Pittsburgh Sleep Quality Index (PSQI). This study was divided into two phases. Phase I tested the construct validity and reliability of the Malay version of PSQI. Phase II was a population-based, cross-sectional study with a multi-stage cluster sampling method. Home-based interviews were conducted by trained personnel using a structured questionnaire, to determine exposure and outcome. Kuala Pilah, a district in Negeri Sembilan which is one of the fourteen states in Malaysia. 1648 community-dwelling older Malaysians. The Malay version of PSQI had significant test re-test reliability with intra-class correlation coefficients of 0.62. Confirmatory factor analyses revealed that one factor PSQI scale with three components (subjective sleep quality, sleep latency, and sleep disturbances) was most suitable. Cronbach's Alpha was 0.60 and composite reliability was 0.63. PSQI scores were highest among neglect (4.11), followed by physical (4.10), psychological (3.96) and financial abuse (3.60). There was a dose-response relationship between clustering of abuse and PSQI scores; 3.41, 3.50 and 3.84 for "no abuse", "1 type of abuse" and "2 types or more". Generalized linear models revealed six variables as significant determinants of sleep quality-abuse, co-morbidities, self-rated health, income, social support and gait speed. Among abuse subtypes, only neglect was significantly associated with poor sleep. The Malay PSQI was valid and reliable. Abuse was significantly associated with poor sleep. As sleep is essential for health and is a good predictor for mortality among older adults, management of abuse victims should entail sleep assessment. Interventions or treatment modalities which focus on improving sleep quality among abuse victims should be designed.

cluster trials v. 1.0

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

Mitchell, John; Castillo, Andrew

2016-09-21

This software contains a set of python modules – input, search, cluster, analysis; these modules read input files containing spatial coordinates and associated attributes which can be used to perform nearest neighbor search (spatial indexing via kdtree), cluster analysis/identification, and calculation of spatial statistics for analysis.

MODEL-BASED CLUSTERING FOR CLASSIFICATION OF AQUATIC SYSTEMS AND DIAGNOSIS OF ECOLOGICAL STRESS

EPA Science Inventory

Clustering approaches were developed using the classification likelihood, the mixture likelihood, and also using a randomization approach with a model index. Using a clustering approach based on the mixture and classification likelihoods, we have developed an algorithm that...

Effect Sizes in Cluster-Randomized Designs

ERIC Educational Resources Information Center

Hedges, Larry V.

2007-01-01

Multisite research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Researchers would like to compute effect size indexes based on the standardized mean difference to compare the results of cluster-randomized studies (and corresponding quasi-experiments) with other studies and to…

Greenhouse tomato limited cluster production systems: crop management practices affect yield

NASA Technical Reports Server (NTRS)

Logendra, L. S.; Gianfagna, T. J.; Specca, D. R.; Janes, H. W.

2001-01-01

Limited-cluster production systems may be a useful strategy to increase crop production and profitability for the greenhouse tomato (Lycopersicon esculentum Mill). In this study, using an ebb-and-flood hydroponics system, we modified plant architecture and spacing and determined the effects on fruit yield and harvest index at two light levels. Single-cluster plants pruned to allow two leaves above the cluster had 25% higher fruit yields than did plants pruned directly above the cluster; this was due to an increase in fruit weight, not fruit number. Both fruit yield and harvest index were greater for all single-cluster plants at the higher light level because of increases in both fruit weight and fruit number. Fruit yield for two-cluster plants was 30% to 40% higher than for single-cluster plants, and there was little difference in the dates or length of the harvest period. Fruit yield for three-cluster plants was not significantly different from that of two-cluster plants; moreover, the harvest period was delayed by 5 days. Plant density (5.5, 7.4, 9.2 plants/m2) affected fruit yield/plant, but not fruit yield/unit area. Given the higher costs for materials and labor associated with higher plant densities, a two-cluster crop at 5.5 plants/m2 with two leaves above the cluster was the best of the production system strategies tested.

Identification and validation of asthma phenotypes in Chinese population using cluster analysis.

PubMed

Wang, Lei; Liang, Rui; Zhou, Ting; Zheng, Jing; Liang, Bing Miao; Zhang, Hong Ping; Luo, Feng Ming; Gibson, Peter G; Wang, Gang

2017-10-01

Asthma is a heterogeneous airway disease, so it is crucial to clearly identify clinical phenotypes to achieve better asthma management. To identify and prospectively validate asthma clusters in a Chinese population. Two hundred eighty-four patients were consecutively recruited and 18 sociodemographic and clinical variables were collected. Hierarchical cluster analysis was performed by the Ward method followed by k-means cluster analysis. Then, a prospective 12-month cohort study was used to validate the identified clusters. Five clusters were successfully identified. Clusters 1 (n = 71) and 3 (n = 81) were mild asthma phenotypes with slight airway obstruction and low exacerbation risk, but with a sex differential. Cluster 2 (n = 65) described an "allergic" phenotype, cluster 4 (n = 33) featured a "fixed airflow limitation" phenotype with smoking, and cluster 5 (n = 34) was a "low socioeconomic status" phenotype. Patients in clusters 2, 4, and 5 had distinctly lower socioeconomic status and more psychological symptoms. Cluster 2 had a significantly increased risk of exacerbations (risk ratio [RR] 1.13, 95% confidence interval [CI] 1.03-1.25), unplanned visits for asthma (RR 1.98, 95% CI 1.07-3.66), and emergency visits for asthma (RR 7.17, 95% CI 1.26-40.80). Cluster 4 had an increased risk of unplanned visits (RR 2.22, 95% CI 1.02-4.81), and cluster 5 had increased emergency visits (RR 12.72, 95% CI 1.95-69.78). Kaplan-Meier analysis confirmed that cluster grouping was predictive of time to the first asthma exacerbation, unplanned visit, emergency visit, and hospital admission (P < .0001 for all comparisons). We identified 3 clinical clusters as "allergic asthma," "fixed airflow limitation," and "low socioeconomic status" phenotypes that are at high risk of severe asthma exacerbations and that have management implications for clinical practice in developing countries. Copyright © 2017 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

NONLINEAR COLOR-METALLICITY RELATIONS OF GLOBULAR CLUSTERS. V. NONLINEAR ABSORPTION-LINE INDEX VERSUS METALLICITY RELATIONS AND BIMODAL INDEX DISTRIBUTIONS OF M31 GLOBULAR CLUSTERS

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

Kim, Sooyoung; Yoon, Suk-Jin; Chung, Chul

2013-05-10

Recent spectroscopy on the globular cluster (GC) system of M31 with unprecedented precision witnessed a clear bimodality in absorption-line index distributions of old GCs. Such division of extragalactic GCs, so far asserted mainly by photometric color bimodality, has been viewed as the presence of merely two distinct metallicity subgroups within individual galaxies and forms a critical backbone of various galaxy formation theories. Given that spectroscopy is a more detailed probe into stellar population than photometry, the discovery of index bimodality may point to the very existence of dual GC populations. However, here we show that the observed spectroscopic dichotomy ofmore » M31 GCs emerges due to the nonlinear nature of metallicity-to-index conversion and thus one does not necessarily have to invoke two separate GC subsystems. We take this as a close analogy to the recent view that metallicity-color nonlinearity is primarily responsible for observed GC color bimodality. We also demonstrate that the metallicity-sensitive magnesium line displays non-negligible metallicity-index nonlinearity and Balmer lines show rather strong nonlinearity. This gives rise to bimodal index distributions, which are routinely interpreted as bimodal metallicity distributions, not considering metallicity-index nonlinearity. Our findings give a new insight into the constitution of M31's GC system, which could change much of the current thought on the formation of GC systems and their host galaxies.« less

Improved infrared precipitation estimation approaches based on k-means clustering: Application to north Algeria using MSG-SEVIRI satellite data

NASA Astrophysics Data System (ADS)

Mokdad, Fatiha; Haddad, Boualem

2017-06-01

In this paper, two new infrared precipitation estimation approaches based on the concept of k-means clustering are first proposed, named the NAW-Kmeans and the GPI-Kmeans methods. Then, they are adapted to the southern Mediterranean basin, where the subtropical climate prevails. The infrared data (10.8 μm channel) acquired by MSG-SEVIRI sensor in winter and spring 2012 are used. Tests are carried out in eight areas distributed over northern Algeria: Sebra, El Bordj, Chlef, Blida, Bordj Menael, Sidi Aich, Beni Ourthilane, and Beni Aziz. The validation is performed by a comparison of the estimated rainfalls to rain gauges observations collected by the National Office of Meteorology in Dar El Beida (Algeria). Despite the complexity of the subtropical climate, the obtained results indicate that the NAW-Kmeans and the GPI-Kmeans approaches gave satisfactory results for the considered rain rates. Also, the proposed schemes lead to improvement in precipitation estimation performance when compared to the original algorithms NAW (Nagri, Adler, and Wetzel) and GPI (GOES Precipitation Index).

A Variable-Selection Heuristic for K-Means Clustering.

ERIC Educational Resources Information Center

Brusco, Michael J.; Cradit, J. Dennis

2001-01-01

Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

Effect Sizes in Three-Level Cluster-Randomized Experiments

ERIC Educational Resources Information Center

Hedges, Larry V.

2011-01-01

Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…

Validation of the content of the prevention protocol for early sepsis caused by Streptococcus agalactiaein newborns

PubMed Central

da Silva, Fabiana Alves; Vidal, Cláudia Fernanda de Lacerda; de Araújo, Ednaldo Cavalcante

2015-01-01

Abstract Objective: to validate the content of the prevention protocol for early sepsis caused by Streptococcus agalactiaein newborns. Method: a transversal, descriptive and methodological study, with a quantitative approach. The sample was composed of 15 judges, 8 obstetricians and 7 pediatricians. The validation occurred through the assessment of the content of the protocol by the judges that received the instrument for data collection - checklist - which contained 7 items that represent the requisites to be met by the protocol. The validation of the content was achieved by applying the Content Validity Index. Result: in the judging process, all the items that represented requirements considered by the protocol obtained concordance within the established level (Content Validity Index > 0.75). Of 7 items, 6 have obtained full concordance (Content Validity Index 1.0) and the feasibility item obtained a Content Validity Index of 0.93. The global assessment of the instruments obtained a Content Validity Index of 0.99. Conclusion: the validation of content that was done was an efficient tool for the adjustment of the protocol, according to the judgment of experienced professionals, which demonstrates the importance of conducting a previous validation of the instruments. It is expected that this study will serve as an incentive for the adoption of universal tracking by other institutions through validated protocols. PMID:26444165

Coronary heart disease index based on longitudinal electrocardiography

NASA Technical Reports Server (NTRS)

Townsend, J. C.; Cronin, J. P.

1977-01-01

A coronary heart disease index was developed from longitudinal ECG (LCG) tracings to serve as a cardiac health measure in studies of working and, essentially, asymptomatic populations, such as pilots and executives. For a given subject, the index consisted of a composite score based on the presence of LCG aberrations and weighted values previously assigned to them. The index was validated by correlating it with the known presence or absence of CHD as determined by a complete physical examination, including treadmill, resting ECG, and risk factor information. The validating sample consisted of 111 subjects drawn by a stratified-random procedure from 5000 available case histories. The CHD index was found to be significantly more valid as a sole indicator of CHD than the LCG without the use of the index. The index consistently produced higher validity coefficients in identifying CHD than did treadmill testing, resting ECG, or risk factor analysis.

Performance analysis of clustering techniques over microarray data: A case study

NASA Astrophysics Data System (ADS)

Dash, Rasmita; Misra, Bijan Bihari

2018-03-01

Handling big data is one of the major issues in the field of statistical data analysis. In such investigation cluster analysis plays a vital role to deal with the large scale data. There are many clustering techniques with different cluster analysis approach. But which approach suits a particular dataset is difficult to predict. To deal with this problem a grading approach is introduced over many clustering techniques to identify a stable technique. But the grading approach depends on the characteristic of dataset as well as on the validity indices. So a two stage grading approach is implemented. In this study the grading approach is implemented over five clustering techniques like hybrid swarm based clustering (HSC), k-means, partitioning around medoids (PAM), vector quantization (VQ) and agglomerative nesting (AGNES). The experimentation is conducted over five microarray datasets with seven validity indices. The finding of grading approach that a cluster technique is significant is also established by Nemenyi post-hoc hypothetical test.

Analysis of ground-motion simulation big data

NASA Astrophysics Data System (ADS)

Maeda, T.; Fujiwara, H.

2016-12-01

We developed a parallel distributed processing system which applies a big data analysis to the large-scale ground motion simulation data. The system uses ground-motion index values and earthquake scenario parameters as input. We used peak ground velocity value and velocity response spectra as the ground-motion index. The ground-motion index values are calculated from our simulation data. We used simulated long-period ground motion waveforms at about 80,000 meshes calculated by a three dimensional finite difference method based on 369 earthquake scenarios of a great earthquake in the Nankai Trough. These scenarios were constructed by considering the uncertainty of source model parameters such as source area, rupture starting point, asperity location, rupture velocity, fmax and slip function. We used these parameters as the earthquake scenario parameter. The system firstly carries out the clustering of the earthquake scenario in each mesh by the k-means method. The number of clusters is determined in advance using a hierarchical clustering by the Ward's method. The scenario clustering results are converted to the 1-D feature vector. The dimension of the feature vector is the number of scenario combination. If two scenarios belong to the same cluster the component of the feature vector is 1, and otherwise the component is 0. The feature vector shows a `response' of mesh to the assumed earthquake scenario group. Next, the system performs the clustering of the mesh by k-means method using the feature vector of each mesh previously obtained. Here the number of clusters is arbitrarily given. The clustering of scenarios and meshes are performed by parallel distributed processing with Hadoop and Spark, respectively. In this study, we divided the meshes into 20 clusters. The meshes in each cluster are geometrically concentrated. Thus this system can extract regions, in which the meshes have similar `response', as clusters. For each cluster, it is possible to determine particular scenario parameters which characterize the cluster. In other word, by utilizing this system, we can obtain critical scenario parameters of the ground-motion simulation for each evaluation point objectively. This research was supported by CREST, JST.

Accurate Grid-based Clustering Algorithm with Diagonal Grid Searching and Merging

NASA Astrophysics Data System (ADS)

Liu, Feng; Ye, Chengcheng; Zhu, Erzhou

2017-09-01

Due to the advent of big data, data mining technology has attracted more and more attentions. As an important data analysis method, grid clustering algorithm is fast but with relatively lower accuracy. This paper presents an improved clustering algorithm combined with grid and density parameters. The algorithm first divides the data space into the valid meshes and invalid meshes through grid parameters. Secondly, from the starting point located at the first point of the diagonal of the grids, the algorithm takes the direction of “horizontal right, vertical down” to merge the valid meshes. Furthermore, by the boundary grid processing, the invalid grids are searched and merged when the adjacent left, above, and diagonal-direction grids are all the valid ones. By doing this, the accuracy of clustering is improved. The experimental results have shown that the proposed algorithm is accuracy and relatively faster when compared with some popularly used algorithms.

Cancer Detection in Microarray Data Using a Modified Cat Swarm Optimization Clustering Approach

PubMed

M, Pandi; R, Balamurugan; N, Sadhasivam

2017-12-29

Objective: A better understanding of functional genomics can be obtained by extracting patterns hidden in gene expression data. This could have paramount implications for cancer diagnosis, gene treatments and other domains. Clustering may reveal natural structures and identify interesting patterns in underlying data. The main objective of this research was to derive a heuristic approach to detection of highly co-expressed genes related to cancer from gene expression data with minimum Mean Squared Error (MSE). Methods: A modified CSO algorithm using Harmony Search (MCSO-HS) for clustering cancer gene expression data was applied. Experiment results are analyzed using two cancer gene expression benchmark datasets, namely for leukaemia and for breast cancer. Result: The results indicated MCSO-HS to be better than HS and CSO, 13% and 9% with the leukaemia dataset. For breast cancer dataset improvement was by 22% and 17%, respectively, in terms of MSE. Conclusion: The results showed MCSO-HS to outperform HS and CSO with both benchmark datasets. To validate the clustering results, this work was tested with internal and external cluster validation indices. Also this work points to biological validation of clusters with gene ontology in terms of function, process and component. Creative Commons Attribution License

Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.

ERIC Educational Resources Information Center

Wang, James Z.; Du, Yanping

Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…

Cloud computing and validation of expandable in silico livers.

PubMed

Ropella, Glen E P; Hunt, C Anthony

2010-12-03

In Silico Livers (ISLs) are works in progress. They are used to challenge multilevel, multi-attribute, mechanistic hypotheses about the hepatic disposition of xenobiotics coupled with hepatic responses. To enhance ISL-to-liver mappings, we added discrete time metabolism, biliary elimination, and bolus dosing features to a previously validated ISL and initiated re-validated experiments that required scaling experiments to use more simulated lobules than previously, more than could be achieved using the local cluster technology. Rather than dramatically increasing the size of our local cluster we undertook the re-validation experiments using the Amazon EC2 cloud platform. So doing required demonstrating the efficacy of scaling a simulation to use more cluster nodes and assessing the scientific equivalence of local cluster validation experiments with those executed using the cloud platform. The local cluster technology was duplicated in the Amazon EC2 cloud platform. Synthetic modeling protocols were followed to identify a successful parameterization. Experiment sample sizes (number of simulated lobules) on both platforms were 49, 70, 84, and 152 (cloud only). Experimental indistinguishability was demonstrated for ISL outflow profiles of diltiazem using both platforms for experiments consisting of 84 or more samples. The process was analogous to demonstration of results equivalency from two different wet-labs. The results provide additional evidence that disposition simulations using ISLs can cover the behavior space of liver experiments in distinct experimental contexts (there is in silico-to-wet-lab phenotype similarity). The scientific value of experimenting with multiscale biomedical models has been limited to research groups with access to computer clusters. The availability of cloud technology coupled with the evidence of scientific equivalency has lowered the barrier and will greatly facilitate model sharing as well as provide straightforward tools for scaling simulations to encompass greater detail with no extra investment in hardware.

Cardiovascular Risk Factors in Cluster Headache.

PubMed

Lasaosa, S Santos; Diago, E Bellosta; Calzada, J Navarro; Benito, A Velázquez

2017-06-01

 Patients with cluster headache tend to have a dysregulation of systemic blood pressure such as increased blood pressure variability and decreased nocturnal dipping. This pattern of nocturnal nondipping is associated with end-organ damage and increased risk of cardiovascular disease.  To determine if cluster headache is associated with a higher risk of cardiovascular disease.  Cross-sectional study of 33 cluster headache patients without evidence of cardiovascular disease and 30 age- and gender-matched healthy controls. Ambulatory blood pressure monitoring was performed in all subjects. We evaluate anthropometric, hematologic, and structural parameters (carotid intima-media thickness and ankle-brachial index).  Of the 33 cluster headache patients, 16 (48.5%) were nondippers, a higher percentage than expected. Most of the cluster headache patients (69.7%) also presented a pathological ankle-brachial index. In terms of the carotid intima-media thickness values, 58.3% of the patients were in the 75th percentile, 25% were in the 90th percentile, and 20% were in the 95th percentile. In the control group, only five of the 30 subjects (16.7%) had a nondipper pattern ( P  =   0.004), with 4.54% in the 90th and 95th percentiles ( P  =   0.012 and 0.015).  Compared with healthy controls, patients with cluster headache presented a high incidence (48.5%) of nondipper pattern, pathological ankle-brachial index (69.7%), and intima-media thickness values above the 75th percentile. These findings support the hypothesis that patients with cluster headache present increased risk of cardiovascular disease. © 2016 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

The panchromatic Hubble Andromeda Treasury. V. Ages and masses of the year 1 stellar clusters

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

Fouesneau, Morgan; Johnson, L. Clifton; Weisz, Daniel R.

We present ages and masses for 601 star clusters in M31 from the analysis of the six filter integrated light measurements from near-ultraviolet to near-infrared wavelengths, made as part of the Panchromatic Hubble Andromeda Treasury (PHAT). We derive the ages and masses using a probabilistic technique, which accounts for the effects of stochastic sampling of the stellar initial mass function. Tests on synthetic data show that this method, in conjunction with the exquisite sensitivity of the PHAT observations and their broad wavelength baseline, provides robust age and mass recovery for clusters ranging from ∼10{sup 2} to 2 × 10{sup 6}more » M {sub ☉}. We find that the cluster age distribution is consistent with being uniform over the past 100 Myr, which suggests a weak effect of cluster disruption within M31. The age distribution of older (>100 Myr) clusters falls toward old ages, consistent with a power-law decline of index –1, likely from a combination of fading and disruption of the clusters. We find that the mass distribution of the whole sample can be well described by a single power law with a spectral index of –1.9 ± 0.1 over the range of 10{sup 3}-3 × 10{sup 5} M {sub ☉}. However, if we subdivide the sample by galactocentric radius, we find that the age distributions remain unchanged. However, the mass spectral index varies significantly, showing best-fit values between –2.2 and –1.8, with the shallower slope in the highest star formation intensity regions. We explore the robustness of our study to potential systematics and conclude that the cluster mass function may vary with respect to environment.« less

UBO Detector - A cluster-based, fully automated pipeline for extracting white matter hyperintensities.

PubMed

Jiang, Jiyang; Liu, Tao; Zhu, Wanlin; Koncz, Rebecca; Liu, Hao; Lee, Teresa; Sachdev, Perminder S; Wen, Wei

2018-07-01

We present 'UBO Detector', a cluster-based, fully automated pipeline for extracting and calculating variables for regions of white matter hyperintensities (WMH) (available for download at https://cheba.unsw.edu.au/group/neuroimaging-pipeline). It takes T1-weighted and fluid attenuated inversion recovery (FLAIR) scans as input, and SPM12 and FSL functions are utilised for pre-processing. The candidate clusters are then generated by FMRIB's Automated Segmentation Tool (FAST). A supervised machine learning algorithm, k-nearest neighbor (k-NN), is applied to determine whether the candidate clusters are WMH or non-WMH. UBO Detector generates both image and text (volumes and the number of WMH clusters) outputs for whole brain, periventricular, deep, and lobar WMH, as well as WMH in arterial territories. The computation time for each brain is approximately 15 min. We validated the performance of UBO Detector by showing a) high segmentation (similarity index (SI) = 0.848) and volumetric (intraclass correlation coefficient (ICC) = 0.985) agreement between the UBO Detector-derived and manually traced WMH; b) highly correlated (r 2  > 0.9) and a steady increase of WMH volumes over time; and c) significant associations of periventricular (t = 22.591, p < 0.001) and deep (t = 14.523, p < 0.001) WMH volumes generated by UBO Detector with Fazekas rating scores. With parallel computing enabled in UBO Detector, the processing can take advantage of multi-core CPU's that are commonly available on workstations. In conclusion, UBO Detector is a reliable, efficient and fully automated WMH segmentation pipeline. Copyright © 2018 Elsevier Inc. All rights reserved.

Combining evidence, biomedical literature and statistical dependence: new insights for functional annotation of gene sets

PubMed Central

Aubry, Marc; Monnier, Annabelle; Chicault, Celine; de Tayrac, Marie; Galibert, Marie-Dominique; Burgun, Anita; Mosser, Jean

2006-01-01

Background Large-scale genomic studies based on transcriptome technologies provide clusters of genes that need to be functionally annotated. The Gene Ontology (GO) implements a controlled vocabulary organised into three hierarchies: cellular components, molecular functions and biological processes. This terminology allows a coherent and consistent description of the knowledge about gene functions. The GO terms related to genes come primarily from semi-automatic annotations made by trained biologists (annotation based on evidence) or text-mining of the published scientific literature (literature profiling). Results We report an original functional annotation method based on a combination of evidence and literature that overcomes the weaknesses and the limitations of each approach. It relies on the Gene Ontology Annotation database (GOA Human) and the PubGene biomedical literature index. We support these annotations with statistically associated GO terms and retrieve associative relations across the three GO hierarchies to emphasise the major pathways involved by a gene cluster. Both annotation methods and associative relations were quantitatively evaluated with a reference set of 7397 genes and a multi-cluster study of 14 clusters. We also validated the biological appropriateness of our hybrid method with the annotation of a single gene (cdc2) and that of a down-regulated cluster of 37 genes identified by a transcriptome study of an in vitro enterocyte differentiation model (CaCo-2 cells). Conclusion The combination of both approaches is more informative than either separate approach: literature mining can enrich an annotation based only on evidence. Text-mining of the literature can also find valuable associated MEDLINE references that confirm the relevance of the annotation. Eventually, GO terms networks can be built with associative relations in order to highlight cooperative and competitive pathways and their connected molecular functions. PMID:16674810

Cluster analysis of novel isometric strength measures produces a valid and evidence-based classification structure for wheelchair track racing.

PubMed

Connick, Mark J; Beckman, Emma; Vanlandewijck, Yves; Malone, Laurie A; Blomqvist, Sven; Tweedy, Sean M

2017-11-25

The Para athletics wheelchair-racing classification system employs best practice to ensure that classes comprise athletes whose impairments cause a comparable degree of activity limitation. However, decision-making is largely subjective and scientific evidence which reduces this subjectivity is required. To evaluate whether isometric strength tests were valid for the purposes of classifying wheelchair racers and whether cluster analysis of the strength measures produced a valid classification structure. Thirty-two international level, male wheelchair racers from classes T51-54 completed six isometric strength tests evaluating elbow extensors, shoulder flexors, trunk flexors and forearm pronators and two wheelchair performance tests-Top-Speed (0-15 m) and Top-Speed (absolute). Strength tests significantly correlated with wheelchair performance were included in a cluster analysis and the validity of the resulting clusters was assessed. All six strength tests correlated with performance (r=0.54-0.88). Cluster analysis yielded four clusters with reasonable overall structure (mean silhouette coefficient=0.58) and large intercluster strength differences. Six athletes (19%) were allocated to clusters that did not align with their current class. While the mean wheelchair racing performance of the resulting clusters was unequivocally hierarchical, the mean performance of current classes was not, with no difference between current classes T53 and T54. Cluster analysis of isometric strength tests produced classes comprising athletes who experienced a similar degree of activity limitation. The strength tests reported can provide the basis for a new, more transparent, less subjective wheelchair racing classification system, pending replication of these findings in a larger, representative sample. This paper also provides guidance for development of evidence-based systems in other Para sports. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Community involvement in dengue vector control: cluster randomised trial.

PubMed

Vanlerberghe, V; Toledo, M E; Rodríguez, M; Gómez, D; Baly, A; Benítez, J R; Van der Stuyft, P

2010-01-01

To assess the effectiveness of an integrated community based environmental management strategy to control Aedes aegypti, the vector of dengue, compared with a routine strategy. Design Cluster randomised trial. Setting Guantanamo, Cuba. Participants 32 circumscriptions (around 2000 inhabitants each). Interventions The circumscriptions were randomly allocated to control clusters (n=16) comprising routine Aedes control programme (entomological surveillance, source reduction, selective adulticiding, and health education) and to intervention clusters (n=16) comprising the routine Aedes control programme combined with a community based environmental management approach. The primary outcome was levels of Aedes infestation: house index (number of houses positive for at least one container with immature stages of Ae aegypti per 100 inspected houses), Breteau index (number of containers positive for immature stages of Ae aegypti per 100 inspected houses), and the pupae per inhabitant statistic (number of Ae aegypti pupae per inhabitant). All clusters were subjected to the intended intervention; all completed the study protocol up to February 2006 and all were included in the analysis. At baseline the Aedes infestation levels were comparable between intervention and control clusters: house index 0.25% v 0.20%, pupae per inhabitant 0.44 x 10(-3) v 0.29 x 10(-3). At the end of the intervention these indices were significantly lower in the intervention clusters: rate ratio for house indices 0.49 (95% confidence interval 0.27 to 0.88) and rate ratio for pupae per inhabitant 0.27 (0.09 to 0.76). A community based environmental management embedded in a routine control programme was effective at reducing levels of Aedes infestation. Trial Registration Current Controlled Trials ISRCTN88405796.

Community involvement in dengue vector control: cluster randomised trial.

PubMed

Vanlerberghe, V; Toledo, M E; Rodríguez, M; Gomez, D; Baly, A; Benitez, J R; Van der Stuyft, P

2009-06-09

To assess the effectiveness of an integrated community based environmental management strategy to control Aedes aegypti, the vector of dengue, compared with a routine strategy. Cluster randomised trial. Guantanamo, Cuba. 32 circumscriptions (around 2000 inhabitants each). The circumscriptions were randomly allocated to control clusters (n=16) comprising routine Aedes control programme (entomological surveillance, source reduction, selective adulticiding, and health education) and to intervention clusters (n=16) comprising the routine Aedes control programme combined with a community based environmental management approach. The primary outcome was levels of Aedes infestation: house index (number of houses positive for at least one container with immature stages of Ae aegypti per 100 inspected houses), Breteau index (number of containers positive for immature stages of Ae aegypti per 100 inspected houses), and the pupae per inhabitant statistic (number of Ae aegypti pupae per inhabitant). All clusters were subjected to the intended intervention; all completed the study protocol up to February 2006 and all were included in the analysis. At baseline the Aedes infestation levels were comparable between intervention and control clusters: house index 0.25% v 0.20%, pupae per inhabitant 0.44x10(-3) v 0.29x10(-3). At the end of the intervention these indices were significantly lower in the intervention clusters: rate ratio for house indices 0.49 (95% confidence interval 0.27 to 0.88) and rate ratio for pupae per inhabitant 0.27 (0.09 to 0.76). A community based environmental management embedded in a routine control programme was effective at reducing levels of Aedes infestation. Current Controlled Trials ISRCTN88405796.

Link prediction with node clustering coefficient

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

2016-06-01

Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

An Empirical Taxonomy of Hospital Governing Board Roles

PubMed Central

Lee, Shoou-Yih D; Alexander, Jeffrey A; Wang, Virginia; Margolin, Frances S; Combes, John R

2008-01-01

Objective To develop a taxonomy of governing board roles in U.S. hospitals. Data Sources 2005 AHA Hospital Governance Survey, 2004 AHA Annual Survey of Hospitals, and Area Resource File. Study Design A governing board taxonomy was developed using cluster analysis. Results were validated and reviewed by industry experts. Differences in hospital and environmental characteristics across clusters were examined. Data Extraction Methods One-thousand three-hundred thirty-four hospitals with complete information on the study variables were included in the analysis. Principal Findings Five distinct clusters of hospital governing boards were identified. Statistical tests showed that the five clusters had high internal reliability and high internal validity. Statistically significant differences in hospital and environmental conditions were found among clusters. Conclusions The developed taxonomy provides policy makers, health care executives, and researchers a useful way to describe and understand hospital governing board roles. The taxonomy may also facilitate valid and systematic assessment of governance performance. Further, the taxonomy could be used as a framework for governing boards themselves to identify areas for improvement and direction for change. PMID:18355260

Simultaneous clustering of gene expression data with clinical chemistry and pathological evaluations reveals phenotypic prototypes

PubMed Central

Bushel, Pierre R; Wolfinger, Russell D; Gibson, Greg

2007-01-01

Background Commonly employed clustering methods for analysis of gene expression data do not directly incorporate phenotypic data about the samples. Furthermore, clustering of samples with known phenotypes is typically performed in an informal fashion. The inability of clustering algorithms to incorporate biological data in the grouping process can limit proper interpretation of the data and its underlying biology. Results We present a more formal approach, the modk-prototypes algorithm, for clustering biological samples based on simultaneously considering microarray gene expression data and classes of known phenotypic variables such as clinical chemistry evaluations and histopathologic observations. The strategy involves constructing an objective function with the sum of the squared Euclidean distances for numeric microarray and clinical chemistry data and simple matching for histopathology categorical values in order to measure dissimilarity of the samples. Separate weighting terms are used for microarray, clinical chemistry and histopathology measurements to control the influence of each data domain on the clustering of the samples. The dynamic validity index for numeric data was modified with a category utility measure for determining the number of clusters in the data sets. A cluster's prototype, formed from the mean of the values for numeric features and the mode of the categorical values of all the samples in the group, is representative of the phenotype of the cluster members. The approach is shown to work well with a simulated mixed data set and two real data examples containing numeric and categorical data types. One from a heart disease study and another from acetaminophen (an analgesic) exposure in rat liver that causes centrilobular necrosis. Conclusion The modk-prototypes algorithm partitioned the simulated data into clusters with samples in their respective class group and the heart disease samples into two groups (sick and buff denoting samples having pain type representative of angina and non-angina respectively) with an accuracy of 79%. This is on par with, or better than, the assignment accuracy of the heart disease samples by several well-known and successful clustering algorithms. Following modk-prototypes clustering of the acetaminophen-exposed samples, informative genes from the cluster prototypes were identified that are descriptive of, and phenotypically anchored to, levels of necrosis of the centrilobular region of the rat liver. The biological processes cell growth and/or maintenance, amine metabolism, and stress response were shown to discern between no and moderate levels of acetaminophen-induced centrilobular necrosis. The use of well-known and traditional measurements directly in the clustering provides some guarantee that the resulting clusters will be meaningfully interpretable. PMID:17408499

ValWorkBench: an open source Java library for cluster validation, with applications to microarray data analysis.

PubMed

Giancarlo, R; Scaturro, D; Utro, F

2015-02-01

The prediction of the number of clusters in a dataset, in particular microarrays, is a fundamental task in biological data analysis, usually performed via validation measures. Unfortunately, it has received very little attention and in fact there is a growing need for software tools/libraries dedicated to it. Here we present ValWorkBench, a software library consisting of eleven well known validation measures, together with novel heuristic approximations for some of them. The main objective of this paper is to provide the interested researcher with the full software documentation of an open source cluster validation platform having the main features of being easily extendible in a homogeneous way and of offering software components that can be readily re-used. Consequently, the focus of the presentation is on the architecture of the library, since it provides an essential map that can be used to access the full software documentation, which is available at the supplementary material website [1]. The mentioned main features of ValWorkBench are also discussed and exemplified, with emphasis on software abstraction design and re-usability. A comparison with existing cluster validation software libraries, mainly in terms of the mentioned features, is also offered. It suggests that ValWorkBench is a much needed contribution to the microarray software development/algorithm engineering community. For completeness, it is important to mention that previous accurate algorithmic experimental analysis of the relative merits of each of the implemented measures [19,23,25], carried out specifically on microarray data, gives useful insights on the effectiveness of ValWorkBench for cluster validation to researchers in the microarray community interested in its use for the mentioned task. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Iterative Stable Alignment and Clustering of 2D Transmission Electron Microscope Images

PubMed Central

Yang, Zhengfan; Fang, Jia; Chittuluru, Johnathan; Asturias, Francisco J.; Penczek, Pawel A.

2012-01-01

SUMMARY Identification of homogeneous subsets of images in a macromolecular electron microscopy (EM) image data set is a critical step in single-particle analysis. The task is handled by iterative algorithms, whose performance is compromised by the compounded limitations of image alignment and K-means clustering. Here we describe an approach, iterative stable alignment and clustering (ISAC) that, relying on a new clustering method and on the concepts of stability and reproducibility, can extract validated, homogeneous subsets of images. ISAC requires only a small number of simple parameters and, with minimal human intervention, can eliminate bias from two-dimensional image clustering and maximize the quality of group averages that can be used for ab initio three-dimensional structural determination and analysis of macromolecular conformational variability. Repeated testing of the stability and reproducibility of a solution within ISAC eliminates heterogeneous or incorrect classes and introduces critical validation to the process of EM image clustering. PMID:22325773

Using cluster ensemble and validation to identify subtypes of pervasive developmental disorders.

PubMed

Shen, Jess J; Lee, Phil-Hyoun; Holden, Jeanette J A; Shatkay, Hagit

2007-10-11

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior. Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.

Using Cluster Ensemble and Validation to Identify Subtypes of Pervasive Developmental Disorders

PubMed Central

Shen, Jess J.; Lee, Phil Hyoun; Holden, Jeanette J.A.; Shatkay, Hagit

2007-01-01

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior.1 Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes19. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.2 PMID:18693920

A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

NASA Technical Reports Server (NTRS)

Li, Zhenlong; Hu, Fei; Schnase, John L.; Duffy, Daniel Q.; Lee, Tsengdar; Bowen, Michael K.; Yang, Chaowei

2016-01-01

Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data

DOE PAGES

Hsu, David

2015-09-27

Clustering methods are often used to model energy consumption for two reasons. First, clustering is often used to process data and to improve the predictive accuracy of subsequent energy models. Second, stable clusters that are reproducible with respect to non-essential changes can be used to group, target, and interpret observed subjects. However, it is well known that clustering methods are highly sensitive to the choice of algorithms and variables. This can lead to misleading assessments of predictive accuracy and mis-interpretation of clusters in policymaking. This paper therefore introduces two methods to the modeling of energy consumption in buildings: clusterwise regression,more » also known as latent class regression, which integrates clustering and regression simultaneously; and cluster validation methods to measure stability. Using a large dataset of multifamily buildings in New York City, clusterwise regression is compared to common two-stage algorithms that use K-means and model-based clustering with linear regression. Predictive accuracy is evaluated using 20-fold cross validation, and the stability of the perturbed clusters is measured using the Jaccard coefficient. These results show that there seems to be an inherent tradeoff between prediction accuracy and cluster stability. This paper concludes by discussing which clustering methods may be appropriate for different analytical purposes.« less

Use of keyword hierarchies to interpret gene expression patterns.

PubMed

Masys, D R; Welsh, J B; Lynn Fink, J; Gribskov, M; Klacansky, I; Corbeil, J

2001-04-01

High-density microarray technology permits the quantitative and simultaneous monitoring of thousands of genes. The interpretation challenge is to extract relevant information from this large amount of data. A growing variety of statistical analysis approaches are available to identify clusters of genes that share common expression characteristics, but provide no information regarding the biological similarities of genes within clusters. The published literature provides a potential source of information to assist in interpretation of clustering results. We describe a data mining method that uses indexing terms ('keywords') from the published literature linked to specific genes to present a view of the conceptual similarity of genes within a cluster or group of interest. The method takes advantage of the hierarchical nature of Medical Subject Headings used to index citations in the MEDLINE database, and the registry numbers applied to enzymes.

Chinese Adaptation and Psychometric Properties of the Child Version of the Cognitive Emotion Regulation Questionnaire

PubMed Central

Liu, Wen; Chen, Liang; Blue, Philip R.

2016-01-01

This study aimed to validate a Chinese’s adaption of the Cognitive Emotion Regulation Questionnaire for children (CERQ-Ck). This self-report instrument evaluates nine cognitive emotion regulation strategies that can be used by children after experiencing a negative life event. The CERQ-Ck was evaluated in a sample of 1403 elementary students between the ages of 9 and 11 by using cluster sampling. All the item-correlation coefficients for CERQ-Ck were above 0.30. The internal consistencies of the nine factors suggested moderate reliability (0.66 to 0.73). Confirmatory factor analysis (CFA) indicated that the current version had the same structure as the original instrument (Tucker–Lewis index = 0.912, comparative fit index = 0.922, root mean square error of approximation = 0.032, standardized root mean square residual = 0.044). A second-order factor and a third-order factor structure were also found. Test–retest correlations (0.53 to 0.70, ps < 0.01) over a period of 1 month, which ranged from acceptable to moderately strong were obtained from a random and stratified subsample of elementary students (N = 76). In addition, we analyzed convergent validity in relation to CERQ-Ck and the Chinese version of the Children’s Depression Inventory model dimensions with a subsample of 1083 elementary students. Multiple-group CFA confirmed the measurement invariance for both the male and female groups (ΔCFI < 0.01, ΔRMSEA < 0.015). Overall, results indicate that CERQ-Ck has similar psychometric properties to the original instrument as well as with adequate reliability and validity to investigate the nine cognitive emotion regulation strategies during late childhood developmental periods. PMID:26925586

Chinese Adaptation and Psychometric Properties of the Child Version of the Cognitive Emotion Regulation Questionnaire.

PubMed

Liu, Wen; Chen, Liang; Blue, Philip R

2016-01-01

This study aimed to validate a Chinese's adaption of the Cognitive Emotion Regulation Questionnaire for children (CERQ-Ck). This self-report instrument evaluates nine cognitive emotion regulation strategies that can be used by children after experiencing a negative life event. The CERQ-Ck was evaluated in a sample of 1403 elementary students between the ages of 9 and 11 by using cluster sampling. All the item-correlation coefficients for CERQ-Ck were above 0.30. The internal consistencies of the nine factors suggested moderate reliability (0.66 to 0.73). Confirmatory factor analysis (CFA) indicated that the current version had the same structure as the original instrument (Tucker-Lewis index = 0.912, comparative fit index = 0.922, root mean square error of approximation = 0.032, standardized root mean square residual = 0.044). A second-order factor and a third-order factor structure were also found. Test-retest correlations (0.53 to 0.70, ps < 0.01) over a period of 1 month, which ranged from acceptable to moderately strong were obtained from a random and stratified subsample of elementary students (N = 76). In addition, we analyzed convergent validity in relation to CERQ-Ck and the Chinese version of the Children's Depression Inventory model dimensions with a subsample of 1083 elementary students. Multiple-group CFA confirmed the measurement invariance for both the male and female groups (ΔCFI < 0.01, ΔRMSEA < 0.015). Overall, results indicate that CERQ-Ck has similar psychometric properties to the original instrument as well as with adequate reliability and validity to investigate the nine cognitive emotion regulation strategies during late childhood developmental periods.

[Diversity of beta-proteobacterial ammonia-oxidizing bacteria and ammonia-oxidizing archaea in shrimp farm sediment].

PubMed

Gao, Lihai; Lin, Weitie

2011-01-01

In order to study the diversity of ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA) in shrimp farm sediment. Total microbial DNA was directly extracted from the shrimp farm sediment. The clone library of amoA genes were constructed with beta-Proteobacterial-AOB and AOA specific primers. The library was screened by PCR-restriction fragment length polymorphism (RFLP) analysis and clones with unique RFLP patterns were sequenced. Phylogenetic analyses of the amoA gene fragments showed that all AOB sequences from shrimp farm sediment were affiliated with Nitrosomonas (61.54%) or Nitrosomonas-like (38. 46%) species and grouped into Nitrosomonas communis cluster, Nitrosomonas sp. Nm148 cluster, Nitrosomonas oligotropha cluster. All AOA sequences belonged to the kingdom Crenarchaeote except that one Operational Taxa Unit (OTU) sequence was Unclassified-Archaea and fell within cluster S (soil origin). AOB and AOA species composition included 13 OTUs and 9 OTUs. The clone coverage of bacterial and archaeal amoA genes was 73.47% and 90.43%. The Shannon-Wiener index, Evenness index, Simpson index and Richness index of AOB were higher than those of AOA. These findings represent the first detailed examination of archaeal amoA diversity in shrimp farm sediment and demonstrate that diverse communities of Crenarchaeote capable of ammonia oxidation are present within shrimp farm sediment, where they may be actively involved in nitrification.

Structural evolutions and hereditary characteristics of icosahedral nano-clusters formed in Mg70Zn30 alloys during rapid solidification processes

NASA Astrophysics Data System (ADS)

Liang, Yong-Chao; Liu, Rang-Su; Xie, Quan; Tian, Ze-An; Mo, Yun-Fei; Zhang, Hai-Tao; Liu, Hai-Rong; Hou, Zhao-Yang; Zhou, Li-Li; Peng, Ping

2017-02-01

To investigate the structural evolution and hereditary mechanism of icosahedral nano-clusters formed during rapid solidification, a molecular dynamics (MD) simulation study has been performed for a system consisting of 107 atoms of liquid Mg70Zn30 alloy. Adopting Honeycutt-Anderson (HA) bond-type index method and cluster type index method (CTIM-3) to analyse the microstructures in the system it is found that for all the nano-clusters including 2~8 icosahedral clusters in the system, there are 62 kinds of geometrical structures, and those can be classified, by the configurations of the central atoms of basic clusters they contained, into four types: chain-like, triangle-tailed, quadrilateral-tailed and pyramidal-tailed. The evolution of icosahedral nano-clusters can be conducted by perfect heredity and replacement heredity, and the perfect heredity emerges when temperature is slightly less than Tm then increase rapidly and far exceeds the replacement heredity at Tg; while for the replacement heredity, there are three major modes: replaced by triangle (3-atoms), quadrangle (4-atoms) and pentagonal pyramid (6-atoms), rather than by single atom step by step during rapid solidification processes.

Reliability and validity of a combat exposure index for Vietnam era veterans.

PubMed

Janes, G R; Goldberg, J; Eisen, S A; True, W R

1991-01-01

The reliability and validity of a self-report measure of combat exposure are examined in a cohort of male-male twin pairs who served in the military during the Vietnam era. Test-retest reliability for a five-level ordinal index of combat exposure is assessed by use of 192 duplicate sets of responses. The chance-corrected proportion in agreement (as measured by the kappa coefficient) is .84. As a measure of criterion-related validity, the combat index is correlated with the award of combat-related military medals ascertained from the military records. The probability of receiving a Purple Heart, Bronze Star, Commendation Medal and Combat Infantry Badge is associated strongly with the combat exposure index. These results show that this simple index is a reliable and valid measure of combat exposure.

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.

An evaluation of nursing students' communication ability during practical clinical training.

PubMed

Xie, Jianfei; Ding, Siqing; Wang, Chunmei; Liu, Aizhong

2013-08-01

To investigate communication abilities and other influential factors on nursing students at the beginning of clinical practical session. A cluster sample of 312 nursing students from 22 nursing colleges or universities was recruited. Communication ability of these participants was evaluated by 4 questionnaires for demographic data, clinical communication behavior, treatment communication skills and interpersonal communication skills at the beginning of clinical practical session. The stability and accuracy of the questionnaires were established with an overall content validity index of 0.78, the Cronbach's Alpha index ranged from 0.872 to 0.951, and the letter index fluctuates from 0.85 to 0.89. Results demonstrated that 88.1% of the nursing students require extra training in clinical communication behavior, treatment communication skills, and interpersonal communication skills. The Pearson analysis revealed significantly positive correlations between communication abilities and the students' educational level, clinical training experience, living circumstances and number of siblings. Most nursing students need communication skill training. Multiple factors, including educational level, living circumstances, number of siblings, and training experience significantly affect nursing students' communication abilities. Our study suggested a need to widely establish a communication course or clinical communication training program to improve nursing students' communication skills. Copyright © 2012 Elsevier Ltd. All rights reserved.

Quantitative measurement and analysis for detection and treatment planning of developmental dysplasia of the hip

NASA Astrophysics Data System (ADS)

Liu, Xin; Lu, Hongbing; Chen, Hanyong; Zhao, Li; Shi, Zhengxing; Liang, Zhengrong

2009-02-01

Developmental dysplasia of the hip is a congenital hip joint malformation affecting the proximal femurs and acetabulum that are subluxatable, dislocatable, and dislocated. Conventionally, physicians made diagnoses and treatments only based on findings from two-dimensional (2D) images by manually calculating clinic parameters. However, anatomical complexity of the disease and the limitation of current standard procedures make accurate diagnosis quite difficultly. In this study, we developed a system that provides quantitative measurement of 3D clinical indexes based on computed tomography (CT) images. To extract bone structure from surrounding tissues more accurately, the system firstly segments the bone using a knowledge-based fuzzy clustering method, which is formulated by modifying the objective function of the standard fuzzy c-means algorithm with additive adaptation penalty. The second part of the system calculates automatically the clinical indexes, which are extended from 2D to 3D for accurate description of spatial relationship between femurs and acetabulum. To evaluate the system performance, experimental study based on 22 patients with unilateral or bilateral affected hip was performed. The results of 3D acetabulum index (AI) automatically provided by the system were validated by comparison with 2D results measured by surgeons manually. The correlation between the two results was found to be 0.622 (p<0.01).

Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach

NASA Astrophysics Data System (ADS)

Ulusoy, Tolga; Keskin, Mustafa; Shirvani, Ayoub; Deviren, Bayram; Kantar, Ersin; Çaǧrı Dönmez, Cem

2012-11-01

This study reports on topology of the top 40 UK companies that have been analysed for predictive verification of markets for the period 2006-2010, applying the concept of minimal spanning tree and hierarchical tree (HT) analysis. Construction of the minimal spanning tree (MST) and the hierarchical tree (HT) is confined to a brief description of the methodology and a definition of the correlation function between a pair of companies based on the London Stock Exchange (LSE) index in order to quantify synchronization between the companies. A derivation of hierarchical organization and the construction of minimal-spanning and hierarchical trees for the 2006-2008 and 2008-2010 periods have been used and the results validate the predictive verification of applied semantics. The trees are known as useful tools to perceive and detect the global structure, taxonomy and hierarchy in financial data. From these trees, two different clusters of companies in 2006 were detected. They also show three clusters in 2008 and two between 2008 and 2010, according to their proximity. The clusters match each other as regards their common production activities or their strong interrelationship. The key companies are generally given by major economic activities as expected. This work gives a comparative approach between MST and HT methods from statistical physics and information theory with analysis of financial markets that may give new valuable and useful information of the financial market dynamics.

Research on potential user identification model for electric energy substitution

NASA Astrophysics Data System (ADS)

Xia, Huaijian; Chen, Meiling; Lin, Haiying; Yang, Shuo; Miao, Bo; Zhu, Xinzhi

2018-01-01

The implementation of energy substitution plays an important role in promoting the development of energy conservation and emission reduction in china. Energy service management platform of alternative energy users based on the data in the enterprise production value, product output, coal and other energy consumption as a potential evaluation index, using principal component analysis model to simplify the formation of characteristic index, comprehensive index contains the original variables, and using fuzzy clustering model for the same industry user’s flexible classification. The comprehensive index number and user clustering classification based on constructed particle optimization neural network classification model based on the user, user can replace electric potential prediction. The results of an example show that the model can effectively predict the potential of users’ energy potential.

Validity and reliability of the Brazilian version of the Work Ability Index questionnaire.

PubMed

Martinez, Maria Carmen; Latorre, Maria do Rosário Dias de Oliveira; Fischer, Frida Marina

2009-06-01

To evaluate the validity and reliability of the Portuguese language version of a work ability index. Cross sectional survey of a sample of 475 workers from an electrical company in the state of Sao Paulo, Southeastern Brazil (spread across ten municipalities in the Campinas area), carried out in 2005. The following aspects of the Brazilian version of the Work Ability Index were evaluated: construct validity, using factorial exploratory analysis, and discriminant capacity, by comparing mean Work Ability Index scores in two groups with different absenteeism levels; criterion validity, by determining the correlation between self-reported health and Work Ability Index score; and reliability, using Cronbach's alpha to determine the internal consistency of the questionnaire. Factorial analysis indicated three factors in the work ability construct: issues pertaining to 'mental resources' (20.6% of the variance), self-perceived work ability (18.9% of the variance), and presence of diseases and health-related limitations (18.4% of the variance). The index was capable of discriminating workers according to levels of absenteeism, identifying a significantly lower (p<0.0001) mean score among subjects with high absenteeism (37.2 points) when compared to those with low absenteeism (42.3 points). Criterion validity analysis showed a correlation between the index and all dimensions of health status analyzed (p<0.0001). Reliability of the index was high, with a Cronbach's alpha of 0.72. The Brazilian version of the Work Ability Index showed satisfactory psychometric properties with respect to construct validity, thus constituting an appropriate option for evaluating work ability in both individual and population-based settings.

Effects of age and body mass index on breast characteristics: A cluster analysis.

PubMed

Coltman, Celeste E; Steele, Julie R; McGhee, Deirdre E

2018-05-24

Limited research has quantified variation in the characteristics of the breasts among women and determined how these breast characteristics are influenced by age and body mass. The aim of this study was to classify the breasts of women in the community into different categories based on comprehensive and objective measurements of the characteristics of their breasts and torsos, and to determine the effect of age and body mass index (BMI) on the prevalence of these breast categories. Four breast characteristic clusters were identified (X-Large, Very-ptotic & Splayed; Large, Ptotic & Splayed; Medium & Mildly-ptotic; and Small & Non-ptotic), with age and BMI shown to significantly affect the breast characteristic clusters. These results highlight the difference in breast characteristics exhibited among women and how these clusters are affected by age and BMI. The breast characteristic clusters identified in this study could be used as a basis for future bra designs and sizing systems in order to improve bra fit for women.

International Well-Being Index: The Austrian Version

ERIC Educational Resources Information Center

Renn, Daniela; Pfaffenberger, Nicole; Platter, Marion; Mitmansgruber, Horst; Cummins, Robert A.; Hofer, Stefan

2009-01-01

The International Well-being Index (IWI) measures both personal and national well-being. It comprises two subscales: the Personal Well-being Index (PWI) and the National Well-being Index (NWI). The aim of this paper is to test the psychometric properties (validity and reliability) of the translated scale in Austria. Convergent validity is assessed…

SYSTEMATIC REVIEW OF HEALTHY EATING INDEXES IN ADULTS AND ELDERLY: APPLICABILITY AND VALIDITY.

PubMed

Pinto de Souza Fernandes, Dalila; Queiroz Ribeiro, Andréia; Lopes Duarte, Maria Sônia; Castro Franceschini, Sylvia do Carmo

2015-08-01

The Healthy Eating Index (HEI) assesses a combination of different types of foods, nutrients and dietary components. It has been adapted in some countries, considering the local dietary habits. in this article, the Healthy Eating Indexes published to date were identified by means of a systematic review. Besides, issues relating to their validity, applicability and limitations were discussed. an electronic search was performed in the PUBMED, SCIENCE DIRECT, BVS and SciELO data base containing studies on the adaptation, review, update or validation of the HEI. The descriptors Healthy Eating Index, Index of Diet Quality, Quality of diet, Diet surveys were used, in different combinations. a total of 11 studies were described and critically analyzed. One of the studies dealt with the development of the index; six proposed adjustments; two assessed validity and reliability of the index, and the other two proposed revision and update. The Healthy Eating Indexes reveal the actual quality of the diet, but the absence of a methodological standard hinders the comparison of the results found in different populations. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Examining Factor Structure and Validating the Persian Version of the Pregnancy’s Worries and Stress Questionnaire for Pregnant Iranian Women

PubMed Central

Navidpour, Fariba; Dolatian, Mahrokh; Yaghmaei, Farideh; Majd, Hamid Alavi; Hashemi, Seyed Saeed

2015-01-01

Background and Objectives: Pregnant women tend to experience anxiety and stress when faced with the changes to their biology, environment and personal relationships. The identification of these factors and the prevention of their side effects are vital for both mother and fetus. The present study was conducted to validate and to examine the factor structure of the Persian version of the Pregnancy’s Worries and Stress Questionnaire. Materials and Methods: The 25-item PWSQ was first translated by specialists into Persian. The questionnaire’s validity was determined using face, content, criterion and construct validity and reliability of questionnaire was examined using Cronbach’s alpha. Confirmatory factor analysis was performed in AMOS and SPSS 21. Participants included healthy Iranian pregnant women (8-39 weeks) who refer to selected hospitals for prenatal care. Hospitals included private, social security and university hospitals and selected through the random cluster sampling method. Findings: The results of validity and reliability assessments of the questionnaire were acceptable. Cronbach’s alpha calculated showed a high internal consistency of 0.89. The confirmatory factor analysis using the χ2, CMIN/DF, IFI, CFI, NFI and NNFI indexes showed the 6-factor model to be the best fitted model for explaining the data. Conclusion: The questionnaire was translated into Persian to examine stress and worry specific to Iranian pregnant women. The psychometric results showed that the questionnaire is suitable for identifying Iranian pregnant women with pregnancy-related stress. PMID:26153186

Fine Scale Spatiotemporal Clustering of Dengue Virus Transmission in Children and Aedes aegypti in Rural Thai Villages

PubMed Central

Yoon, In-Kyu; Getis, Arthur; Aldstadt, Jared; Rothman, Alan L.; Tannitisupawong, Darunee; Koenraadt, Constantianus J. M.; Fansiri, Thanyalak; Jones, James W.; Morrison, Amy C.; Jarman, Richard G.; Nisalak, Ananda; Mammen, Mammen P.; Thammapalo, Suwich; Srikiatkhachorn, Anon; Green, Sharone; Libraty, Daniel H.; Gibbons, Robert V.; Endy, Timothy; Pimgate, Chusak; Scott, Thomas W.

2012-01-01

Background Based on spatiotemporal clustering of human dengue virus (DENV) infections, transmission is thought to occur at fine spatiotemporal scales by horizontal transfer of virus between humans and mosquito vectors. To define the dimensions of local transmission and quantify the factors that support it, we examined relationships between infected humans and Aedes aegypti in Thai villages. Methodology/Principal Findings Geographic cluster investigations of 100-meter radius were conducted around DENV-positive and DENV-negative febrile “index” cases (positive and negative clusters, respectively) from a longitudinal cohort study in rural Thailand. Child contacts and Ae. aegypti from cluster houses were assessed for DENV infection. Spatiotemporal, demographic, and entomological parameters were evaluated. In positive clusters, the DENV infection rate among child contacts was 35.3% in index houses, 29.9% in houses within 20 meters, and decreased with distance from the index house to 6.2% in houses 80–100 meters away (p<0.001). Significantly more Ae. aegypti were DENV-infectious (i.e., DENV-positive in head/thorax) in positive clusters (23/1755; 1.3%) than negative clusters (1/1548; 0.1%). In positive clusters, 8.2% of mosquitoes were DENV-infectious in index houses, 4.2% in other houses with DENV-infected children, and 0.4% in houses without infected children (p<0.001). The DENV infection rate in contacts was 47.4% in houses with infectious mosquitoes, 28.7% in other houses in the same cluster, and 10.8% in positive clusters without infectious mosquitoes (p<0.001). Ae. aegypti pupae and adult females were more numerous only in houses containing infectious mosquitoes. Conclusions/Significance Human and mosquito infections are positively associated at the level of individual houses and neighboring residences. Certain houses with high transmission risk contribute disproportionately to DENV spread to neighboring houses. Small groups of houses with elevated transmission risk are consistent with over-dispersion of transmission (i.e., at a given point in time, people/mosquitoes from a small portion of houses are responsible for the majority of transmission). PMID:22816001

Instrument validation process: a case study using the Paediatric Pain Knowledge and Attitudes Questionnaire.

PubMed

Peirce, Deborah; Brown, Janie; Corkish, Victoria; Lane, Marguerite; Wilson, Sally

2016-06-01

To compare two methods of calculating interrater agreement while determining content validity of the Paediatric Pain Knowledge and Attitudes Questionnaire for use with Australian nurses. Paediatric pain assessment and management documentation was found to be suboptimal revealing a need to assess paediatric nurses' knowledge and attitude to pain. The Paediatric Pain Knowledge and Attitudes Questionnaire was selected as it had been reported as valid and reliable in the United Kingdom with student nurses. The questionnaire required content validity determination prior to use in the Australian context. A two phase process of expert review. Ten paediatric nurses completed a relevancy rating of all 68 questionnaire items. In phase two, five pain experts reviewed the items of the questionnaire that scored an unacceptable item level content validity. Item and scale level content validity indices and intraclass correlation coefficients were calculated. In phase one, 31 items received an item level content validity index <0·78 and the scale level content validity index average was 0·80 which were below levels required for acceptable validity. The intraclass correlation coefficient was 0·47. In phase two, 10 items were amended and four items deleted. The revised questionnaire provided a scale level content validity index average >0·90 and an intraclass correlation coefficient of 0·94 demonstrating excellent agreement between raters therefore acceptable content validity. Equivalent outcomes were achieved using the content validity index and the intraclass correlation coefficient. To assess content validity the content validity index has the advantage of providing an item level score and is a simple calculation. The intraclass correlation coefficient requires statistical knowledge, or support, and has the advantage of accounting for the possibility of chance agreement. © 2016 John Wiley & Sons Ltd.

Flow cytometry with gold nanoparticles and their clusters as scattering contrast agents: FDTD simulation of light-cell interaction.

PubMed

Tanev, Stoyan; Sun, Wenbo; Pond, James; Tuchin, Valery V; Zharov, Vladimir P

2009-09-01

The formulation of the finite-difference time-domain (FDTD) approach is presented in the framework of its potential applications to in-vivo flow cytometry based on light scattering. The consideration is focused on comparison of light scattering by a single biological cell alone in controlled refractive-index matching conditions and by cells labeled by gold nanoparticles. The optical schematics including phase contrast (OPCM) microscopy as a prospective modality for in-vivo flow cytometry is also analyzed. The validation of the FDTD approach for the simulation of flow cytometry may open up a new avenue in the development of advanced cytometric techniques based on scattering effects from nanoscale targets. 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

PubMed Central

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods. Conclusions Appropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems. PMID:22643026

Incremental Criterion Validity of the WJ-III COG Clinical Clusters: Marginal Predictive Effects beyond the General Factor

ERIC Educational Resources Information Center

McGill, Ryan J.

2015-01-01

The current study examined the incremental validity of the clinical clusters from the Woodcock-Johnson III Tests of Cognitive Abilities (WJ-III COG) for predicting scores on the Woodcock-Johnson III Tests of Achievement (WJ-III ACH). All participants were children and adolescents (N = 4,722) drawn from the nationally representative WJ-III…

Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities. To propose a method that effectively segments brain tumor from MR images and to evaluate the performance of unsupervised optimal fuzzy clustering (UOFC) algorithm for segmentation of brain tumor from MR images. Segmentation is done by preprocessing the MR image to standardize intensity inhomogeneities followed by feature extraction, feature fusion and clustering. Different validation measures are used to evaluate the performance of the proposed method using different clustering algorithms. The proposed method using UOFC algorithm produces high sensitivity (96%) and low specificity (4%) compared to other clustering methods. Validation results clearly show that the proposed method with UOFC algorithm effectively segments brain tumor from MR images.

Correspondence between ion-cluster and bulk thermodynamics: on the validity of the cluster pair approximation

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

Vlcek, Lukas; Chialvo, Ariel; Simonson, J Michael

2013-01-01

Molecular models and experimental estimates based on the cluster pair approximation (CPA) provide inconsistent predictions of absolute single-ion hydration properties. To understand the origin of this discrepancy we used molecular simulations to study the transition between hydration of alkali metal and halide ions in small aqueous clusters and bulk water. The results demonstrate that the assumptions underlying the CPA are not generally valid as a result of a significant shift in the ion hydration free energies (~15 kJ/mol) and enthalpies (~47 kJ/mol) in the intermediate range of cluster sizes. When this effect is accounted for, the systematic differences between modelsmore » and experimental predictions disappear, and the value of absolute proton hydration enthalpy based on the CPA gets in closer agreement with other estimates.« less

A cluster-analytic approach towards multidimensional health-related behaviors in adolescents: the MoMo-Study

PubMed Central

2012-01-01

Background Although knowledge on single health-related behaviors and their association with health parameters is available, research on multiple health-related behaviors is needed to understand the interactions among these behaviors. The aims of the study were (a) to identify typical health-related behavior patterns in German adolescents focusing on physical activity, media use and dietary behavior; (b) to describe the socio-demographic correlates of the identified clusters and (c) to study their association with overweight. Methods Within the framework of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) and the “Motorik-Modul” (MoMo), 1,643 German adolescents (11–17 years) completed a questionnaire assessing the amount and type of weekly physical activity in sports clubs and during leisure time, weekly use of television, computer and console games and the frequency and amount of food consumption. From this data the three indices ‘physical activity’, ‘media use’ and ‘healthy nutrition’ were derived and included in a cluster analysis conducted with Ward’s Method and K-means analysis. Chi-square tests were performed to identify socio-demographic correlates of the clusters as well as their association with overweight. Results Four stable clusters representing typical health-related behavior patterns were identified: Cluster 1 (16.2%)—high scores in physical activity index and average scores in media use index and healthy nutrition index; cluster 2 (34.6%)—high healthy nutrition score and below average scores in the other two indices; cluster 3 (18.4%)—low physical activity score, low healthy nutrition score and very high media use score; cluster 4 (30.5%)—below average scores on all three indices. Boys were overrepresented in the clusters 1 and 3, and the relative number of adolescents with low socio-economic status as well as overweight was significantly higher than average in cluster 3. Conclusions Meaningful and stable clusters of health-related behavior were identified. These results confirm findings of another youth study hence supporting the assumption that these clusters represent typical behavior patterns of adolescents. These results are particularly relevant for the characterization of target groups for primary prevention of lifestyle diseases. PMID:23273134

Community involvement in dengue vector control: cluster randomised trial

PubMed Central

Toledo, M E; Rodríguez, M; Gomez, D; Baly, A; Benitez, J R; Van der Stuyft, P

2009-01-01

Objective To assess the effectiveness of an integrated community based environmental management strategy to control Aedes aegypti, the vector of dengue, compared with a routine strategy. Design Cluster randomised trial. Setting Guantanamo, Cuba. Participants 32 circumscriptions (around 2000 inhabitants each). Interventions The circumscriptions were randomly allocated to control clusters (n=16) comprising routine Aedes control programme (entomological surveillance, source reduction, selective adulticiding, and health education) and to intervention clusters (n=16) comprising the routine Aedes control programme combined with a community based environmental management approach. Main outcome measures The primary outcome was levels of Aedes infestation: house index (number of houses positive for at least one container with immature stages of Ae aegypti per 100 inspected houses), Breteau index (number of containers positive for immature stages of Ae aegypti per 100 inspected houses), and the pupae per inhabitant statistic (number of Ae aegypti pupae per inhabitant). Results All clusters were subjected to the intended intervention; all completed the study protocol up to February 2006 and all were included in the analysis. At baseline the Aedes infestation levels were comparable between intervention and control clusters: house index 0.25% v 0.20%, pupae per inhabitant 0.44×10−3 v 0.29×10−3. At the end of the intervention these indices were significantly lower in the intervention clusters: rate ratio for house indices 0.49 (95% confidence interval 0.27 to 0.88) and rate ratio for pupae per inhabitant 0.27 (0.09 to 0.76). Conclusion A community based environmental management embedded in a routine control programme was effective at reducing levels of Aedes infestation. Trial registration Current Controlled Trials ISRCTN88405796. PMID:19509031

Community-based control of Aedes aegypti by adoption of eco-health methods in Chennai City, India

PubMed Central

Arunachalam, Natarajan; Tyagi, Brij Kishore; Samuel, Miriam; Krishnamoorthi, R; Manavalan, R; Tewari, Satish Chandra; Ashokkumar, V; Kroeger, Axel; Sommerfeld, Johannes; Petzold, Max

2012-01-01

Background Dengue is highly endemic in Chennai city, South India, in spite of continuous vector control efforts. This intervention study was aimed at establishing the efficacy as well as the favouring and limiting factors relating to a community-based environmental intervention package to control the dengue vector Aedes aegypti. Methods A cluster randomized controlled trial was designed to measure the outcome of a new vector control package and process analysis; different data collection tools were used to determine the performance. Ten randomly selected intervention clusters (neighbourhoods with 100 houses each) were paired with ten control clusters on the basis of ecological/entomological indices and sociological parameters collected during baseline studies. In the intervention clusters, Aedes control was carried out using a community-based environmental management approach like provision of water container covers through community actors, clean-up campaigns, and dissemination of dengue information through schoolchildren. The main outcome measure was reduction in pupal indices (pupae per person index), used as a proxy measure of adult vectors, in the intervention clusters compared to the control clusters. Results At baseline, almost half the respondents did not know that dengue is serious but preventable, or that it is transmitted by mosquitoes. The stakeholder analysis showed that dengue vector control is carried out by vertically structured programmes of national, state, and local administrative bodies through fogging and larval control with temephos, without any involvement of community-based organizations, and that vector control efforts were conducted in an isolated and irregular way. The most productive container types for Aedes pupae were cement tanks, drums, and discarded containers. All ten intervention clusters with a total of 1000 houses and 4639 inhabitants received the intervention while the ten control clusters with a total of 1000 houses and 4439 inhabitants received only the routine government services and some of the information education and communication project materials. The follow-up studies showed that there was a substantial increase in dengue understanding in the intervention group with only minor knowledge changes in the control group. Community involvement and the partnership among stakeholders (particularly women’s self-help groups) worked well. After 10 months of intervention, the pupae per person index was significantly reduced to 0.004 pupae per person from 1.075 (P = 0.020) in the intervention clusters compared to control clusters. There were also significant reductions in the Stegomyia indices: the house index was reduced to 4.2%, the container index to 1.05%, and the Breteau index to 4.3 from the baseline values of 19.6, 8.91, and 30.8 in the intervention arm. Conclusion A community-based approach together with other stakeholders that promoted interventions to prevent dengue vector breeding led to a substantial reduction in dengue vector density. PMID:23318241

Community-based control of Aedes aegypti by adoption of eco-health methods in Chennai City, India.

PubMed

Arunachalam, Natarajan; Tyagi, Brij Kishore; Samuel, Miriam; Krishnamoorthi, R; Manavalan, R; Tewari, Satish Chandra; Ashokkumar, V; Kroeger, Axel; Sommerfeld, Johannes; Petzold, Max

2012-12-01

Dengue is highly endemic in Chennai city, South India, in spite of continuous vector control efforts. This intervention study was aimed at establishing the efficacy as well as the favouring and limiting factors relating to a community-based environmental intervention package to control the dengue vector Aedes aegypti. A cluster randomized controlled trial was designed to measure the outcome of a new vector control package and process analysis; different data collection tools were used to determine the performance. Ten randomly selected intervention clusters (neighbourhoods with 100 houses each) were paired with ten control clusters on the basis of ecological/entomological indices and sociological parameters collected during baseline studies. In the intervention clusters, Aedes control was carried out using a community-based environmental management approach like provision of water container covers through community actors, clean-up campaigns, and dissemination of dengue information through schoolchildren. The main outcome measure was reduction in pupal indices (pupae per person index), used as a proxy measure of adult vectors, in the intervention clusters compared to the control clusters. At baseline, almost half the respondents did not know that dengue is serious but preventable, or that it is transmitted by mosquitoes. The stakeholder analysis showed that dengue vector control is carried out by vertically structured programmes of national, state, and local administrative bodies through fogging and larval control with temephos, without any involvement of community-based organizations, and that vector control efforts were conducted in an isolated and irregular way. The most productive container types for Aedes pupae were cement tanks, drums, and discarded containers. All ten intervention clusters with a total of 1000 houses and 4639 inhabitants received the intervention while the ten control clusters with a total of 1000 houses and 4439 inhabitants received only the routine government services and some of the information education and communication project materials. The follow-up studies showed that there was a substantial increase in dengue understanding in the intervention group with only minor knowledge changes in the control group. Community involvement and the partnership among stakeholders (particularly women's self-help groups) worked well. After 10 months of intervention, the pupae per person index was significantly reduced to 0·004 pupae per person from 1·075 (P = 0·020) in the intervention clusters compared to control clusters. There were also significant reductions in the Stegomyia indices: the house index was reduced to 4·2%, the container index to 1·05%, and the Breteau index to 4·3 from the baseline values of 19·6, 8·91, and 30·8 in the intervention arm. A community-based approach together with other stakeholders that promoted interventions to prevent dengue vector breeding led to a substantial reduction in dengue vector density.

Clustering analysis of line indices for LAMOST spectra with AstroStat

NASA Astrophysics Data System (ADS)

Chen, Shu-Xin; Sun, Wei-Min; Yan, Qi

2018-06-01

The application of data mining in astronomical surveys, such as the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) survey, provides an effective approach to automatically analyze a large amount of complex survey data. Unsupervised clustering could help astronomers find the associations and outliers in a big data set. In this paper, we employ the k-means method to perform clustering for the line index of LAMOST spectra with the powerful software AstroStat. Implementing the line index approach for analyzing astronomical spectra is an effective way to extract spectral features for low resolution spectra, which can represent the main spectral characteristics of stars. A total of 144 340 line indices for A type stars is analyzed through calculating their intra and inter distances between pairs of stars. For intra distance, we use the definition of Mahalanobis distance to explore the degree of clustering for each class, while for outlier detection, we define a local outlier factor for each spectrum. AstroStat furnishes a set of visualization tools for illustrating the analysis results. Checking the spectra detected as outliers, we find that most of them are problematic data and only a few correspond to rare astronomical objects. We show two examples of these outliers, a spectrum with abnormal continuumand a spectrum with emission lines. Our work demonstrates that line index clustering is a good method for examining data quality and identifying rare objects.

75 FR 40856 - Federal Register Meeting Notice; Webinar About Regional Innovation Clusters RFP

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-14

... potential Offerors about the Regional Innovation Clusters RFP. For more information please go to http://www.sba.gov/clusters/index.html . The RFP may be found on http://www.fedbizopps.gov . Logistical Information: The webinar will be held on Thursday, July 15, 2010. For details, please visit http://www.sba.gov...

An Analytical Study on an Orthodontic Index: Index of Complexity, Outcome and Need (ICON)

PubMed Central

Torkan, Sepide; Pakshir, Hamid Reza; Fattahi, Hamid Reza; Oshagh, Morteza; Momeni Danaei, Shahla; Salehi, Parisa; Hedayati, Zohreh

2015-01-01

Statement of the Problem The validity of the Index of Complexity, Outcome and Need (ICON) which is an orthodontic index developed and introduced in 2000 should be studied in different ethnic groups. Purpose The aim of this study was to perform an analysis on the ICON and to verify whether this index is valid for assessing both the need and complexity of orthodontic treatment in Iran. Materials and Method Five orthodontists were asked to score pre-treatment diagnostic records of 100 patients with a uniform distribution of different types of malocclusions determined by Dental Health Component of the Index of Treatment Need. A calibrated examiner also assessed the need for orthodontic treatment and complexity of the cases based on the ICON index as well as the Index of Orthodontic Treatment Need (IOTN). 10 days later, 25% of the cases were re-scored by the panel of experts and the calibrated orthodontist. Results The weighted kappa revealed the inter-examiner reliability of the experts to be 0.63 and 0.51 for the need and complexity components, respectively. ROC curve was used to assess the validity of the index. A new cut-off point was adjusted at 35 in lieu of 43 as the suggested cut-off point. This cut-off point showed the highest level of sensitivity and specificity in our society for orthodontic treatment need (0.77 and 0.78, respectively), but it failed to define definite ranges for the complexity of treatment. Conclusion ICON is a valid index in assessing the need for treatment in Iran when the cut-off point is adjusted to 35. As for complexity of treatment, the index is not validated for our society. It seems that ICON is a well-suited substitute for the IOTN index. PMID:26331142

Radio Sources Toward Galaxy Clusters at 30 GHz

NASA Technical Reports Server (NTRS)

Coble, K.; Bonamente, M.; Carlstrom, J. E.; Dawson, K.; Hasler, N.; Holzapfel, W.; Joy, M.; LaRoque, S.; Marrone, D. P.; Reese, E. D.

2007-01-01

Extra-galactic radio sources are a significant contaminant in cosmic microwave background and Sunyaev-Zeldovich effect experiments. Deep interferometric observations with the BIMA and OVRO arrays are used to characterize the spatial, spectral, and flux distributions of radio sources toward massive galaxy clusters at 28.5 GHz. We compute counts of mJy source fluxes from 89 fields centered on known massive galaxy clusters and 8 non-cluster fields. We find that source counts in the inner regions of the cluster fields (within 0.5 arcmin of the cluster center) are a factor of 8.9 (+4.2 to -3.8) times higher than counts in the outer regions of the cluster fields (radius greater than 0.5 arcmin). Counts in the outer regions of the cluster fields are in turn a factor of 3.3 (+4.1 -1.8) greater than those in the noncluster fields. Counts in the non-cluster fields are consistent with extrapolations from the results of other surveys. We compute spectral indices of mJy sources in cluster fields between 1.4 and 28.5 GHz and find a mean spectral index of al[ja = 0.66 with an rms dispersion of 0.36, where flux S varies as upsilon(sup -alpha). The distribution is skewed, with a median spectral index of 0.72 and 25th and 75th percentiles of 0.51 and 0.92, respectively. This is steeper than the spectral indices of stronger field sources measured by other surveys.

Differences in Coping Styles among Persons with Spinal Cord Injury: A Cluster-Analytic Approach.

ERIC Educational Resources Information Center

Frank, Robert G.; And Others

1987-01-01

Identified and validated two subgroups in group of 53 persons with spinal cord injury by applying cluster-analytic procedures to subjects' self-reported coping and health locus of control belief scores. Cluster 1 coped less effectively and tended to be psychologically distressed; Cluster 2 subjects emphasized internal health attributions and…

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station

NASA Astrophysics Data System (ADS)

Moustris, Konstantinos; Tsiros, Ioannis X.; Tseliou, Areti; Nastos, Panagiotis

2018-04-01

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station.

PubMed

Moustris, Konstantinos; Tsiros, Ioannis X; Tseliou, Areti; Nastos, Panagiotis

2018-04-11

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

Psychometric Properties of the Heart Disease Knowledge Scale: Evidence from Item and Confirmatory Factor Analyses

PubMed Central

Lim, Bee Chiu; Kueh, Yee Cheng; Arifin, Wan Nor; Ng, Kok Huan

2016-01-01

Background Heart disease knowledge is an important concept for health education, yet there is lack of evidence on proper validated instruments used to measure levels of heart disease knowledge in the Malaysian context. Methods A cross-sectional, survey design was conducted to examine the psychometric properties of the adapted English version of the Heart Disease Knowledge Questionnaire (HDKQ). Using proportionate cluster sampling, 788 undergraduate students at Universiti Sains Malaysia, Malaysia, were recruited and completed the HDKQ. Item analysis and confirmatory factor analysis (CFA) were used for the psychometric evaluation. Construct validity of the measurement model was included. Results Most of the students were Malay (48%), female (71%), and from the field of science (51%). An acceptable range was obtained with respect to both the difficulty and discrimination indices in the item analysis results. The difficulty index ranged from 0.12–0.91 and a discrimination index of ≥ 0.20 were reported for the final retained 23 items. The final CFA model showed an adequate fit to the data, yielding a 23-item, one-factor model [weighted least squares mean and variance adjusted scaled chi-square difference = 1.22, degrees of freedom = 2, P-value = 0.544, the root mean square error of approximation = 0.03 (90% confidence interval = 0.03, 0.04); close-fit P-value = > 0.950]. Conclusion Adequate psychometric values were obtained for Malaysian undergraduate university students using the 23-item, one-factor model of the adapted HDKQ. PMID:27660543

Psychometric Properties of the Heart Disease Knowledge Scale: Evidence from Item and Confirmatory Factor Analyses.

PubMed

Lim, Bee Chiu; Kueh, Yee Cheng; Arifin, Wan Nor; Ng, Kok Huan

2016-07-01

Heart disease knowledge is an important concept for health education, yet there is lack of evidence on proper validated instruments used to measure levels of heart disease knowledge in the Malaysian context. A cross-sectional, survey design was conducted to examine the psychometric properties of the adapted English version of the Heart Disease Knowledge Questionnaire (HDKQ). Using proportionate cluster sampling, 788 undergraduate students at Universiti Sains Malaysia, Malaysia, were recruited and completed the HDKQ. Item analysis and confirmatory factor analysis (CFA) were used for the psychometric evaluation. Construct validity of the measurement model was included. Most of the students were Malay (48%), female (71%), and from the field of science (51%). An acceptable range was obtained with respect to both the difficulty and discrimination indices in the item analysis results. The difficulty index ranged from 0.12-0.91 and a discrimination index of ≥ 0.20 were reported for the final retained 23 items. The final CFA model showed an adequate fit to the data, yielding a 23-item, one-factor model [weighted least squares mean and variance adjusted scaled chi-square difference = 1.22, degrees of freedom = 2, P-value = 0.544, the root mean square error of approximation = 0.03 (90% confidence interval = 0.03, 0.04); close-fit P-value = > 0.950]. Adequate psychometric values were obtained for Malaysian undergraduate university students using the 23-item, one-factor model of the adapted HDKQ.

Person mobility in the design and analysis of cluster-randomized cohort prevention trials.

PubMed

Vuchinich, Sam; Flay, Brian R; Aber, Lawrence; Bickman, Leonard

2012-06-01

Person mobility is an inescapable fact of life for most cluster-randomized (e.g., schools, hospitals, clinic, cities, state) cohort prevention trials. Mobility rates are an important substantive consideration in estimating the effects of an intervention. In cluster-randomized trials, mobility rates are often correlated with ethnicity, poverty and other variables associated with disparity. This raises the possibility that estimated intervention effects may generalize to only the least mobile segments of a population and, thus, create a threat to external validity. Such mobility can also create threats to the internal validity of conclusions from randomized trials. Researchers must decide how to deal with persons who leave study clusters during a trial (dropouts), persons and clusters that do not comply with an assigned intervention, and persons who enter clusters during a trial (late entrants), in addition to the persons who remain for the duration of a trial (stayers). Statistical techniques alone cannot solve the key issues of internal and external validity raised by the phenomenon of person mobility. This commentary presents a systematic, Campbellian-type analysis of person mobility in cluster-randomized cohort prevention trials. It describes four approaches for dealing with dropouts, late entrants and stayers with respect to data collection, analysis and generalizability. The questions at issue are: 1) From whom should data be collected at each wave of data collection? 2) Which cases should be included in the analyses of an intervention effect? and 3) To what populations can trial results be generalized? The conclusions lead to recommendations for the design and analysis of future cluster-randomized cohort prevention trials.

Rosacea assessment by erythema index and principal component analysis segmentation maps

NASA Astrophysics Data System (ADS)

Kuzmina, Ilona; Rubins, Uldis; Saknite, Inga; Spigulis, Janis

2017-12-01

RGB images of rosacea were analyzed using segmentation maps of principal component analysis (PCA) and erythema index (EI). Areas of segmented clusters were compared to Clinician's Erythema Assessment (CEA) values given by two dermatologists. The results show that visible blood vessels are segmented more precisely on maps of the erythema index and the third principal component (PC3). In many cases, a distribution of clusters on EI and PC3 maps are very similar. Mean values of clusters' areas on these maps show a decrease of the area of blood vessels and erythema and an increase of lighter skin area after the therapy for the patients with diagnosis CEA = 2 on the first visit and CEA=1 on the second visit. This study shows that EI and PC3 maps are more useful than the maps of the first (PC1) and second (PC2) principal components for indicating vascular structures and erythema on the skin of rosacea patients and therapy monitoring.

WAIS-III index score profiles in the Canadian standardization sample.

PubMed

Lange, Rael T

2007-01-01

Representative index score profiles were examined in the Canadian standardization sample of the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III). The identification of profile patterns was based on the methodology proposed by Lange, Iverson, Senior, and Chelune (2002) that aims to maximize the influence of profile shape and minimize the influence of profile magnitude on the cluster solution. A two-step cluster analysis procedure was used (i.e., hierarchical and k-means analyses). Cluster analysis of the four index scores (i.e., Verbal Comprehension [VCI], Perceptual Organization [POI], Working Memory [WMI], Processing Speed [PSI]) identified six profiles in this sample. Profiles were differentiated by pattern of performance and were primarily characterized as (a) high VCI/POI, low WMI/PSI, (b) low VCI/POI, high WMI/PSI, (c) high PSI, (d) low PSI, (e) high VCI/WMI, low POI/PSI, and (f) low VCI, high POI. These profiles are potentially useful for determining whether a patient's WAIS-III performance is unusual in a normal population.

Cloud computing and validation of expandable in silico livers

PubMed Central

2010-01-01

Background In Silico Livers (ISLs) are works in progress. They are used to challenge multilevel, multi-attribute, mechanistic hypotheses about the hepatic disposition of xenobiotics coupled with hepatic responses. To enhance ISL-to-liver mappings, we added discrete time metabolism, biliary elimination, and bolus dosing features to a previously validated ISL and initiated re-validated experiments that required scaling experiments to use more simulated lobules than previously, more than could be achieved using the local cluster technology. Rather than dramatically increasing the size of our local cluster we undertook the re-validation experiments using the Amazon EC2 cloud platform. So doing required demonstrating the efficacy of scaling a simulation to use more cluster nodes and assessing the scientific equivalence of local cluster validation experiments with those executed using the cloud platform. Results The local cluster technology was duplicated in the Amazon EC2 cloud platform. Synthetic modeling protocols were followed to identify a successful parameterization. Experiment sample sizes (number of simulated lobules) on both platforms were 49, 70, 84, and 152 (cloud only). Experimental indistinguishability was demonstrated for ISL outflow profiles of diltiazem using both platforms for experiments consisting of 84 or more samples. The process was analogous to demonstration of results equivalency from two different wet-labs. Conclusions The results provide additional evidence that disposition simulations using ISLs can cover the behavior space of liver experiments in distinct experimental contexts (there is in silico-to-wet-lab phenotype similarity). The scientific value of experimenting with multiscale biomedical models has been limited to research groups with access to computer clusters. The availability of cloud technology coupled with the evidence of scientific equivalency has lowered the barrier and will greatly facilitate model sharing as well as provide straightforward tools for scaling simulations to encompass greater detail with no extra investment in hardware. PMID:21129207

Analysis of genetic association using hierarchical clustering and cluster validation indices.

PubMed

Pagnuco, Inti A; Pastore, Juan I; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia L

2017-10-01

It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, based on some criteria of similarity. This task is usually performed by clustering algorithms, where the genes are clustered into meaningful groups based on their expression values in a set of experiment. In this work, we propose a method to find sets of co-expressed genes, based on cluster validation indices as a measure of similarity for individual gene groups, and a combination of variants of hierarchical clustering to generate the candidate groups. We evaluated its ability to retrieve significant sets on simulated correlated and real genomics data, where the performance is measured based on its detection ability of co-regulated sets against a full search. Additionally, we analyzed the quality of the best ranked groups using an online bioinformatics tool that provides network information for the selected genes. Copyright © 2017 Elsevier Inc. All rights reserved.

Effects of Task Index Variations On Transfer of Training Criteria. Final Report.

ERIC Educational Resources Information Center

Mirabella, Angelo; Wheaton, George R.

The concluding series of a research program designed to validate a battery of task indexes for use in forecasting the effectiveness of training devices is described. Phase I collated 17 task indexes and applied them to sonar training devices, while in Phase II the 17 index battery was validated, using skill acquisition measures as criteria.…

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

PubMed

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

2015-01-01

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

The influence of environment on the properties of galaxies

NASA Astrophysics Data System (ADS)

Hashimoto, Yasuhiro

1999-11-01

I will present the result of the evaluation of the environmental influences on three important galactic properties; morphology, star formation rate, and interaction in the local universe. I have used a very large and homogeneous sample of 15749 galaxies drawn from the Las Campanas Redshift Survey (Shectman et al. 1996). This data set consists of galaxies inhabiting the entire range of galactic environments, from the sparsest field to the densest clusters, thus allowing me to study environmental variations without combing multiple data sets with inhomogeneous characteristics. Furthermore, I can also extend the research to a ``general'' environmental investigation by, for the first time, decoupling the very local environment, as characterized by local galaxy density, from the effects of larger-scale environments, such as membership in a cluster. The star formation rate is characterized by the strength of EW(OII), while the galactic morphology is characterized by the automatically-measured concentration index (e.g. Okamura, Kodaira, & Watanabe 1984), which is more closely related to the bulge-to-disk ratio of galaxies than Hubble type, and is therefore expected to behave more independently on star formation activity in a galaxy. On the other hand, the first systematic quantitative investigation of the environmental influence on the interaction of galaxies is made by using two automatically-determined objective measures; the asymmetry index and existence of companions. The principal conclusions of this work are: (1)The concentration of the galactic light profile (characterized by the concentration index) is predominantly correlated with the relatively small-scale environment which is characterized by the local galaxy density. (2)The star formation rate of galaxies (characterized by the EW(OII)) is correlated both with the small-scale environment (the local galaxy density) and the larger scale environment which is characterized by the cluster membership. For weakly star forming galaxies, the star formation rate is correlated both with the local galaxy density and rich cluster membership. It also shows a correlation with poor cluster membership. For strongly star forming galaxies, the star formation rate is correlated with the local density and the poor cluster membership. (3)Interacting galaxies (characterized by the asymmetry index and/or the existence of apparent companions) show no correlation with rich cluster membership, but show a fair to strong correlation with the poor cluster membership.

HIV-Risk Index: Development and Validation of a Brief Risk Index for Hispanic Young People.

PubMed

Ballester-Arnal, Rafael; Gil-Llario, María Dolores; Castro-Calvo, Jesús; Giménez-García, Cristina

2016-08-01

The prevalence of HIV risk behaviors among young people facilitates the spread of HIV, in particular regarding unsafe sex behavior, although this trend is different within this population. For this reason, identifying the riskier young population is required to prevent HIV infection. The main purpose of this study was to develop and validate a risk index to assess the different sexual HIV risk exposure among Hispanic Young people. For this purpose, 9861 Spanish young people were randomly distributed into two groups (derivation and validation group). According to the results, the factor analyses grouped the nine items of the HIV- risk index into two factors (factor 1, direct sexual risk indicators and factor 2, indirect sexual risk indicators) with an equal structure for men and women by a multi-group confirmatory factor analysis. The variance explained was 54.26 %. Moreover, the Cronbach's alpha coefficient revealed high internal reliability (α = .79) and the convergent validity supported its evidence based on different HIV risk indexes. Therefore, the HIV-risk index seem to be a rigorous and valid measure to estimate HIV risk exposure among young people.

Regionalization Study of Satellite based Hydrological Model (SHM) in Hydrologically Homogeneous River Basins of India

NASA Astrophysics Data System (ADS)

Kumari, Babita; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghvendra P.

2017-04-01

A new semi-distributed conceptual hydrological model, namely Satellite based Hydrological Model (SHM), has been developed under 'PRACRITI-2' program of Space Application Centre (SAC), Ahmedabad for sustainable water resources management of India by using data from Indian Remote Sensing satellites. Entire India is divided into 5km x 5km grid cells and properties at the center of the cells are assumed to represent the property of the cells. SHM contains five modules namely surface water, forest, snow, groundwater and routing. Two empirical equations (SCS-CN and Hargreaves) and water balance method have been used in the surface water module; the forest module is based on the calculations of water balancing & dynamics of subsurface. 2-D Boussinesq equation is used for groundwater modelling which is solved using implicit finite-difference. The routing module follows a distributed routing approach which requires flow path and network with the key point of travel time estimation. The aim of this study is to evaluate the performance of SHM using regionalization technique which also checks the usefulness of a model in data scarce condition or for ungauged basins. However, homogeneity analysis is pre-requisite to regionalization. Similarity index (Φ) and hierarchical agglomerative cluster analysis are adopted to test the homogeneity in terms of physical attributes of three basins namely Brahmani (39,033 km km^2)), Baitarani (10,982 km km^2)) and Kangsabati (9,660 km km^2)) with respect to Subarnarekha (29,196 km km^2)) basin. The results of both homogeneity analysis show that Brahmani basin is the most homogeneous with respect to Subarnarekha river basin in terms of physical characteristics (land use land cover classes, soiltype and elevation). The calibration and validation of model parameters of Brahmani basin is in progress which are to be transferred into the SHM set up of Subarnarekha basin and results are to be compared with the results of calibrated and validated parameter set up of SHM of Subarnarekha basin to test the applicability of SHM in hydrologically homogeneous regions of India. Keywords: SHM, regionalization, homogeneity, donor catchment, similarity index, cluster analysis

Development and Validation of the Work-Related Well-Being Index: Analysis of the Federal Employee Viewpoint Survey.

PubMed

Eaton, Jennifer L; Mohr, David C; Hodgson, Michael J; McPhaul, Kathleen M

2018-02-01

To describe development and validation of the work-related well-being (WRWB) index. Principal components analysis was performed using Federal Employee Viewpoint Survey (FEVS) data (N = 392,752) to extract variables representing worker well-being constructs. Confirmatory factor analysis was performed to verify factor structure. To validate the WRWB index, we used multiple regression analysis to examine relationships with burnout associated outcomes. Principal Components Analysis identified three positive psychology constructs: "Work Positivity", "Co-worker Relationships", and "Work Mastery". An 11 item index explaining 63.5% of variance was achieved. The structural equation model provided a very good fit to the data. Higher WRWB scores were positively associated with all three employee experience measures examined in regression models. The new WRWB index shows promise as a valid and widely accessible instrument to assess worker well-being.

Development and Validation of the Work-Related Well-Being Index: Analysis of the Federal Employee Viewpoint Survey (FEVS).

PubMed

Eaton, Jennifer L; Mohr, David C; Hodgson, Michael J; McPhaul, Kathleen M

2017-10-11

To describe development and validation of the Work-Related Well-Being (WRWB) Index. Principal Components Analysis was performed using Federal Employee Viewpoint Survey (FEVS) data (N = 392,752) to extract variables representing worker well-being constructs. Confirmatory factor analysis was performed to verify factor structure. To validate the WRWB index, we used multiple regression analysis to examine relationships with burnout associated outcomes. PCA identified three positive psychology constructs: "Work Positivity", "Co-worker Relationships", and "Work Mastery". An 11 item index explaining 63.5% of variance was achieved. The structural equation model provided a very good fit to the data. Higher WRWB scores were positively associated with all 3 employee experience measures examined in regression models. The new WRWB index shows promise as a valid and widely accessible instrument to assess worker well-being.

Validation of a quality-of-life instrument for patients with nonmelanoma skin cancer.

PubMed

Rhee, John S; Matthews, B Alex; Neuburg, Marcy; Logan, Brent R; Burzynski, Mary; Nattinger, Ann B

2006-01-01

To validate a disease-specific quality-of-life instrument--the Skin Cancer Index--intended to measure quality-of-life issues relevant to patients with nonmelanoma skin cancer. Internal reliability, convergent and divergent validity with existing scales, and factor analyses were performed in a cross-sectional study of 211 patients presenting with cervicofacial nonmelanoma skin cancer to a dermatologic surgery clinic. Factor analyses of the Skin Cancer Index confirmed a multidimensional scale with 3 distinct subscales-emotional, social, and appearance. Excellent internal validity of the 3 subscales was demonstrated. Substantial evidence was observed for convergent validity with the Dermatology Life Quality Index, Rosenberg Self-Esteem Scale, Lerman's Cancer Worry Scale, and Medical Outcomes Survey Short-Form 12 domains for vitality, emotion, social function, and mental health. These findings validate a new disease-specific quality-of-life instrument for patients with cervicofacial nonmelanoma skin cancer. Studies on the responsiveness of the Skin Cancer Index to clinical intervention are currently under way.

Looking for signs of Alzheimer's disease.

PubMed

Hodgson, Lynne Gershenson; Cutler, Stephen J

2003-01-01

This study examined the correlates of symptom-seeking behavior for Alzheimer's disease (AD) among middle-aged persons. Symptom seeking, the tendency to search for signs of disease, is one manifestation of an individual's concern about developing AD. The data were obtained from a survey of two subsamples of 40-60 year old adults: 1) 108 adult children with a living parent with a diagnosis of probable AD; and 2) 150 adults in a matched group with no parental history of AD. Bivariate and multivariate analyses were used to identify significant predictors of symptom seeking, which was measured by a composite index comprised of responses from three questions about checking for signs of AD, interpreting signs as symptoms of AD, and soliciting external validation for concerns. Four clusters of predictors were examined: memory assessment, AD experience, sociodemographics, and well-being. Within these clusters, the constellations of significant predictors varied by subsample, but the most robust predictors were aspects of subjective assessments of memory functioning and AD experience. An understanding of the correlates of symptom seeking for AD has implications for early detection of the disease as well as identifying populations under stress from excessive worry about their own future health.

[Application of the Children's Impact of Event Scale (Chinese Version) on a rapid assessment of posttraumatic stress disorder among children from the Wenchuan earthquake area].

PubMed

Zhao, Gao-feng; Zhang, Qiang; Pang, Yan; Ren, Zheng-jia; Peng, Dan; Jiang, Guo-guo; Liu, Shan-ming; Chen, Ying; Geng, Ting; Zhang, Shu-sen; Yang, Yan-chun; Deng, Hong

2009-11-01

To explore the reliability and validity of the Children's Impact of Event Scale (Chinese version, CRIES-13) and to determine the value and the optimal cutoff point of the score of CRIES-13 in screening posttraumatic stress disorder (PTSD), so as to provide evidence for PTSD prevention and identify children at risk in Wenchuan earthquake areas. A total of 253 children experienced the Wenchuan earthquake were tested through Stratified random cluster sampling. The authors examined CRIES-13's internal consistency, discriminative validity and predictive value of the cut-off. PTSD was assessed with the DSM-IV criteria. Area under the curve while sensitivity, specificity and Youden index were computed based on the receiver operating characteristic curve analysis. Optimal cutoff point was determined by the maximum of Youden index. 20.9% of the subjects were found to have met the DSM-IV criteria for PTSD 7 months after the Wenchuan earthquake accident. The Cronbach's coefficient of CRIES-13 was 0.903 and the mean inter-item correlation coefficients ranged from 0.283 to 0.689, the correlation coefficient of the three factors with the total scale scores ranged from 0.836 to 0.868 while the correlation coefficient among the three factors ranged from 0.568 to 0.718, PTSD cases indicated much higher scores than non-PTSD cases, the Youden index reached maximum value when the total score approached 18 in CRIES-13 with sensitivity and specificity as 81.1% and 76.5% respectively. Consistency check showed that there were no significant differences between the results of CRIES-13 score >/= 32 and clinical diagnosis (Kappa = 0.529) from the screening program. CRIES-13 appeared to be a reliable and valid measure for assessing the posttraumatic stress symptoms among children after the earthquake accident in the Wenchuan area. The CRIES-13 seemed to be a useful self-rating diagnostic instrument for survivors with PTSD symptoms as a clinical concern by using a 18 cut-off in total score. Consistency check showed that there was no significant difference between the screening result of CRIES-13 score >/= 32 and clinical diagnosis.

Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation.

PubMed

Du, Hai-Wen; Wang, Yong; Zhuang, Da-Fang; Jiang, Xiao-San

2017-08-07

The nest flea index of Meriones unguiculatus is a critical indicator for the prevention and control of plague, which can be used not only to detect the spatial and temporal distributions of Meriones unguiculatus, but also to reveal its cluster rule. This research detected the temporal and spatial distribution characteristics of the plague natural foci of Mongolian gerbils by body flea index from 2005 to 2014, in order to predict plague outbreaks. Global spatial autocorrelation was used to describe the entire spatial distribution pattern of the body flea index in the natural plague foci of typical Chinese Mongolian gerbils. Cluster and outlier analysis and hot spot analysis were also used to detect the intensity of clusters based on geographic information system methods. The quantity of M. unguiculatus nest fleas in the sentinel surveillance sites from 2005 to 2014 and host density data of the study area from 2005 to 2010 used in this study were provided by Chinese Center for Disease Control and Prevention. The epidemic focus regions of the Mongolian gerbils remain the same as the hot spot regions relating to the body flea index. High clustering areas possess a similar pattern as the distribution pattern of the body flea index indicating that the transmission risk of plague is relatively high. In terms of time series, the area of the epidemic focus gradually increased from 2005 to 2007, declined rapidly in 2008 and 2009, and then decreased slowly and began trending towards stability from 2009 to 2014. For the spatial change, the epidemic focus regions began moving northward from the southwest epidemic focus of the Mongolian gerbils from 2005 to 2007, and then moved from north to south in 2007 and 2008. The body flea index of Chinese gerbil foci reveals significant spatial and temporal aggregation characteristics through the employing of spatial autocorrelation. The diversity of temporary and spatial distribution is mainly affected by seasonal variation, the human activity and natural factors.

Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of Merit, Gap Statistics and Model Explorer.

PubMed

Giancarlo, Raffaele; Scaturro, Davide; Utro, Filippo

2008-10-29

Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analysis and Classification, in particular with regard to the prediction of the number of clusters in a dataset, usually established via internal validation measures. Despite the wealth of internal measures available in the literature, new ones have been recently proposed, some of them specifically for microarray data. We consider five such measures: Clest, Consensus (Consensus Clustering), FOM (Figure of Merit), Gap (Gap Statistics) and ME (Model Explorer), in addition to the classic WCSS (Within Cluster Sum-of-Squares) and KL (Krzanowski and Lai index). We perform extensive experiments on six benchmark microarray datasets, using both Hierarchical and K-means clustering algorithms, and we provide an analysis assessing both the intrinsic ability of a measure to predict the correct number of clusters in a dataset and its merit relative to the other measures. We pay particular attention both to precision and speed. Moreover, we also provide various fast approximation algorithms for the computation of Gap, FOM and WCSS. The main result is a hierarchy of those measures in terms of precision and speed, highlighting some of their merits and limitations not reported before in the literature. Based on our analysis, we draw several conclusions for the use of those internal measures on microarray data. We report the main ones. Consensus is by far the best performer in terms of predictive power and remarkably algorithm-independent. Unfortunately, on large datasets, it may be of no use because of its non-trivial computer time demand (weeks on a state of the art PC). FOM is the second best performer although, quite surprisingly, it may not be competitive in this scenario: it has essentially the same predictive power of WCSS but it is from 6 to 100 times slower in time, depending on the dataset. The approximation algorithms for the computation of FOM, Gap and WCSS perform very well, i.e., they are faster while still granting a very close approximation of FOM and WCSS. The approximation algorithm for the computation of Gap deserves to be singled-out since it has a predictive power far better than Gap, it is competitive with the other measures, but it is at least two order of magnitude faster in time with respect to Gap. Another important novel conclusion that can be drawn from our analysis is that all the measures we have considered show severe limitations on large datasets, either due to computational demand (Consensus, as already mentioned, Clest and Gap) or to lack of precision (all of the other measures, including their approximations). The software and datasets are available under the GNU GPL on the supplementary material web page.

Validating Clusters with the Lower Bound for Sum-of-Squares Error

ERIC Educational Resources Information Center

Steinley, Douglas

2007-01-01

Given that a minor condition holds (e.g., the number of variables is greater than the number of clusters), a nontrivial lower bound for the sum-of-squares error criterion in K-means clustering is derived. By calculating the lower bound for several different situations, a method is developed to determine the adequacy of cluster solution based on…

Classification of different degrees of adiposity in sedentary rats.

PubMed

Leopoldo, A S; Lima-Leopoldo, A P; Nascimento, A F; Luvizotto, R A M; Sugizaki, M M; Campos, D H S; da Silva, D C T; Padovani, C R; Cicogna, A C

2016-01-01

In experimental studies, several parameters, such as body weight, body mass index, adiposity index, and dual-energy X-ray absorptiometry, have commonly been used to demonstrate increased adiposity and investigate the mechanisms underlying obesity and sedentary lifestyles. However, these investigations have not classified the degree of adiposity nor defined adiposity categories for rats, such as normal, overweight, and obese. The aim of the study was to characterize the degree of adiposity in rats fed a high-fat diet using cluster analysis and to create adiposity intervals in an experimental model of obesity. Thirty-day-old male Wistar rats were fed a normal (n=41) or a high-fat (n=43) diet for 15 weeks. Obesity was defined based on the adiposity index; and the degree of adiposity was evaluated using cluster analysis. Cluster analysis allowed the rats to be classified into two groups (overweight and obese). The obese group displayed significantly higher total body fat and a higher adiposity index compared with those of the overweight group. No differences in systolic blood pressure or nonesterified fatty acid, glucose, total cholesterol, or triglyceride levels were observed between the obese and overweight groups. The adiposity index of the obese group was positively correlated with final body weight, total body fat, and leptin levels. Despite the classification of sedentary rats into overweight and obese groups, it was not possible to identify differences in the comorbidities between the two groups.

Nonlinear Color–Metallicity Relations of Globular Clusters. VII. Nonlinear Absorption-line Index versus Metallicity Relations and Bimodal Index Distributions of NGC 5128 Globular Clusters

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

Kim, Sooyoung; Yoon, Suk-Jin, E-mail: sjyoon0691@yonsei.ac.kr

Spectroscopy on the globular cluster (GC) system of NGC 5128 revealed bimodality in absorption-line index distributions of its old GCs. GC division is a widely observed and studied phenomenon whose interpretation has depicted host galaxy formation and evolution such that it harbors two distinct metallicity groups. Such a conventional view of GC bimodality has mainly been based on photometry. The recent GC photometric data, however, presented an alternative perspective in which the nonlinear metallicity-to-color transformation is responsible for color bimodality of GC systems. Here we apply the same line of analysis to the spectral indices and examine the absorption-line indexmore » versus metallicity relations for the NGC 5128 GC system. NGC 5128 GCs display nonlinearity in the metallicity-index planes, most prominently for the Balmer lines and by a non-negligible degree for the metallicity-sensitive magnesium line. We demonstrate that the observed spectroscopic division of NGC 5128 GCs can be caused by the nonlinear nature of the metallicity-to-index conversions and thus one does not need to resort to two separate GC subgroups. Our analysis incorporating this nonlinearity provides a new perspective on the structure of NGC 5128's GC system, and a further piece to the global picture of the formation of GC systems and their host galaxies.« less

Construct Meaning in Multilevel Settings

ERIC Educational Resources Information Center

Stapleton, Laura M.; Yang, Ji Seung; Hancock, Gregory R.

2016-01-01

We present types of constructs, individual- and cluster-level, and their confirmatory factor analytic validation models when data are from individuals nested within clusters. When a construct is theoretically individual level, spurious construct-irrelevant dependency in the data may appear to signal cluster-level dependency; in such cases,…

The MMPI-2 in sexual harassment and discrimination litigants.

PubMed

Long, Barbara; Rouse, Steven V; Nelsen, R Owen; Butcher, James N

2004-06-01

In order to understand patterns of respondents on validity and clinical scales, this study analyzed archival Minnesota Multiphasic Personality Inventory 2s (MMPI-2s) produced by 192 women and 14 men who initiated legal claims of ongoing emotional harm related to workplace sexual harassment and discrimination. The MMPI-2s were administered as a part of a comprehensive psychiatric forensic evaluation of the claimants' current psychological condition. All validity and clinical scale scores were manually entered into the computer, and codetype and cluster analyses were obtained. Among the women, 28% produced a "normal limits" profile, providing no MMPI-2 support for their claims of ongoing emotional distress. Cluster analysis of the validity scales of the remaining profiles produced four distinctive clusters of profiles representing different approaches to the test items. Copyright 2004 Wiley Periodicals, Inc.

Validation of the Interpersonal Reactivity Index in a Chinese Context

ERIC Educational Resources Information Center

Siu, Andrew M. H.; Shek, Daniel T. L.

2005-01-01

Objectives: Psychometric properties of the Chinese version of the Interpersonal Reactivity Index (C-IRI) for the assessment of empathy in Chinese people were examined. Method: The Interpersonal Reactivity Index (IRI) was translated to Chinese, and an expert panel reviewed its content validity and cultural relevance. The translated instrument…

Analysis of genetic association in Listeria and Diabetes using Hierarchical Clustering and Silhouette Index

NASA Astrophysics Data System (ADS)

Pagnuco, Inti A.; Pastore, Juan I.; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia L.

2016-04-01

It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, where significative groups of genes are defined based on some criteria. This task is usually performed by clustering algorithms, where the whole family of genes, or a subset of them, are clustered into meaningful groups based on their expression values in a set of experiment. In this work we used a methodology based on the Silhouette index as a measure of cluster quality for individual gene groups, and a combination of several variants of hierarchical clustering to generate the candidate groups, to obtain sets of co-expressed genes for two real data examples. We analyzed the quality of the best ranked groups, obtained by the algorithm, using an online bioinformatics tool that provides network information for the selected genes. Moreover, to verify the performance of the algorithm, considering the fact that it doesn’t find all possible subsets, we compared its results against a full search, to determine the amount of good co-regulated sets not detected.

An inventory of publications on electronic medical records revisited.

PubMed

Moorman, P W; Schuemie, M J; van der Lei, J

2009-01-01

In this short review we provide an update of our earlier inventories of publications indexed in MedLine with the MeSH term 'Medical Records Systems, Computerized'. We retrieved and analyzed all references to English articles published before January 1, 2008, and indexed in PubMed with the MeSH term 'Medical Records Systems, Computerized'. We retrieved a total of 11,924 publications, of which 3937 (33%) appeared in a journal with an impact factor. Since 2002 the number of yearly publications, and the number of journals in which those publications appeared, increased. A cluster analysis revealed three clusters: an organizational issues cluster, a technically oriented cluster and a cluster about order-entry and research. Although our previous inventory in 2003 suggested a constant yearly production of publications on electronic medical records since 1998, the current inventory shows another rise in production since 2002. In addition, many new journals and countries have shown interest during the last five years. In the last 15 years, interest in organizational issues remained fairly constant, order entry and research with systems gained attention, while interest in technical issues relatively decreased.

Breaking the indexing ambiguity in serial crystallography.

PubMed

Brehm, Wolfgang; Diederichs, Kay

2014-01-01

In serial crystallography, a very incomplete partial data set is obtained from each diffraction experiment (a `snapshot'). In some space groups, an indexing ambiguity exists which requires that the indexing mode of each snapshot needs to be established with respect to a reference data set. In the absence of such re-indexing information, crystallographers have thus far resorted to a straight merging of all snapshots, yielding a perfectly twinned data set of higher symmetry which is poorly suited for structure solution and refinement. Here, two algorithms have been designed for assembling complete data sets by clustering those snapshots that are indexed in the same way, and they have been tested using 15,445 snapshots from photosystem I [Chapman et al. (2011), Nature (London), 470, 73-77] and with noisy model data. The results of the clustering are unambiguous and enabled the construction of complete data sets in the correct space group P63 instead of (twinned) P6322 that researchers have been forced to use previously in such cases of indexing ambiguity. The algorithms thus extend the applicability and reach of serial crystallography.

Forecasting Jakarta composite index (IHSG) based on chen fuzzy time series and firefly clustering algorithm

NASA Astrophysics Data System (ADS)

Ningrum, R. W.; Surarso, B.; Farikhin; Safarudin, Y. M.

2018-03-01

This paper proposes the combination of Firefly Algorithm (FA) and Chen Fuzzy Time Series Forecasting. Most of the existing fuzzy forecasting methods based on fuzzy time series use the static length of intervals. Therefore, we apply an artificial intelligence, i.e., Firefly Algorithm (FA) to set non-stationary length of intervals for each cluster on Chen Method. The method is evaluated by applying on the Jakarta Composite Index (IHSG) and compare with classical Chen Fuzzy Time Series Forecasting. Its performance verified through simulation using Matlab.

A new casemix adjustment index for hospital mortality among patients with congestive heart failure.

PubMed

Polanczyk, C A; Rohde, L E; Philbin, E A; Di Salvo, T G

1998-10-01

Comparative analysis of hospital outcomes requires reliable adjustment for casemix. Although congestive heart failure is one of the most common indications for hospitalization, congestive heart failure casemix adjustment has not been widely studied. The purposes of this study were (1) to describe and validate a new congestive heart failure-specific casemix adjustment index to predict in-hospital mortality and (2) to compare its performance to the Charlson comorbidity index. Data from all 4,608 admissions to the Massachusetts General Hospital from January 1990 to July 1996 with a principal ICD-9-CM discharge diagnosis of congestive heart failure were evaluated. Massachusetts General Hospital patients were randomly divided in a derivation and a validation set. By logistic regression, odds ratios for in-hospital death were computed and weights were assigned to construct a new predictive index in the derivation set. The performance of the index was tested in an internal Massachusetts General Hospital validation set and in a non-Massachusetts General Hospital external validation set incorporating data from all 1995 New York state hospital discharges with a primary discharge diagnosis of congestive heart failure. Overall in-hospital mortality was 6.4%. Based on the new index, patients were assigned to six categories with incrementally increasing hospital mortality rates ranging from 0.5% to 31%. By logistic regression, "c" statistics of the congestive heart failure-specific index (0.83 and 0.78, derivation and validation set) were significantly superior to the Charlson index (0.66). Similar incrementally increasing hospital mortality rates were observed in the New York database with the congestive heart failure-specific index ("c" statistics 0.75). In an administrative database, this congestive heart failure-specific index may be a more adequate casemix adjustment tool to predict hospital mortality in patients hospitalized for congestive heart failure.

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.

Modulated Modularity Clustering as an Exploratory Tool for Functional Genomic Inference

PubMed Central

Stone, Eric A.; Ayroles, Julien F.

2009-01-01

In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC), seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity) that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation. PMID:19424432

MeSH key terms for validation and annotation of gene expression clusters

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

Rechtsteiner, A.; Rocha, L. M.

2004-01-01

Integration of different sources of information is a great challenge for the analysis of gene expression data, and for the field of Functional Genomics in general. As the availability of numerical data from high-throughput methods increases, so does the need for technologies that assist in the validation and evaluation of the biological significance of results extracted from these data. In mRNA assaying with microarrays, for example, numerical analysis often attempts to identify clusters of co-expressed genes. The important task to find the biological significance of the results and validate them has so far mostly fallen to the biological expert whomore » had to perform this task manually. One of the most promising avenues to develop automated and integrative technology for such tasks lies in the application of modern Information Retrieval (IR) and Knowledge Management (KM) algorithms to databases with biomedical publications and data. Examples of databases available for the field are bibliographic databases c ntaining scientific publications (e.g. MEDLINE/PUBMED), databases containing sequence data (e.g. GenBank) and databases of semantic annotations (e.g. the Gene Ontology Consortium and Medical Subject Headings (MeSH)). We present here an approach that uses the MeSH terms and their concept hierarchies to validate and obtain functional information for gene expression clusters. The controlled and hierarchical MeSH vocabulary is used by the National Library of Medicine (NLM) to index all the articles cited in MEDLINE. Such indexing with a controlled vocabulary eliminates some of the ambiguity due to polysemy (terms that have multiple meanings) and synonymy (multiple terms have similar meaning) that would be encountered if terms would be extracted directly from the articles due to differing article contexts or author preferences and background. Further, the hierarchical organization of the MeSH terms can illustrate the conceptuallfunctional relationships of genes associated with MeSH terms. MeSH terms can be associated with genes through co-occurrence of these in MEDLINE citations, i.e. the genes occur in titles or abstracts and the MeSH terms are assigned by experts. To identify MeSH terms associated with a group of genes we used the tool MESHGENE developed at the Information Dynamics Lab at HP Labs (http://www-idl.hpl.hp.com/meshgene/). When presented with a list of human genes, MESHGENE uses some sophisticated techniques to search for these gene symbols in the titles and abstracts of all MEDLINE citations. MeSH terms and the number of co-occurrences can be retrieved. Gene symbols that are aliases of each other are pooled from several databases. This addresses the problem of synonymy, the fact that several symbols can refer to the same gene. MESHGENE employs some sophisticated algorithms that disregards symbols that are likely to be acronyms for other concepts than a gene. This addresses the problem of polysemy, i.e. possible multiple meanings of a gene symbol. We applied our approach to gene expression data from herpes virus infected human fibroblast cells. The data contains 12 time-points, between 1/2 hrs and 48 hrs after infection. Singular Value Decomposition was used to identify the dominant modes of expression. 75% of the variance in the expression data was captured by the first two modes, the first exhibiting a monotonly increasing expression pattern and the second a more transient pattern. Projection of the gene expression vectors onto this first two modes identified 3 statistically significant clusters of co-expressed genes. 500 genes from cluster 1 and 300 genes from clusters 2 and 3 each were uploaded to MESHGENE and the MeSH terms and co-occurrence values were retrieved. MeSH terms were also obtained for 5 groups of randomly selected genes with similar numbers of genes. The log was taken of the co-occurrence values and for each MeSH term these log co-occurrence values were summed for each group over the genes in that group. A matrix with 8 columns for the 8 groups of genes and with 14,000 rows with the MeSH terms was obtained. To analyze this association matrix we used a Latent Semantic Analysis (LSA) approach. We applied SVD to this gene-group vs. MeSH term association matrix. The first 2 modes that capture most of the variation (and therefore most times also information) in the association matrix were highly associated with MeSH terms that occurred uniquely or disproportionally in the 3 gene clusters. MeSH terms highly associated with the 5 groups of randomly selected genes were associated with the lower modes. These modes seem to just capture 'noise' in the association matrix. This result by itself is of great interest for gene expression analysis. We were able to show that the 3 clusters of genes not only separated in 'expression space' but also in the MeSH term space with which they are associated through the literature.« less

Development and validation of a scoring index to predict the presence of lesions in capsule endoscopy in patients with suspected Crohn's disease of the small bowel: a Spanish multicenter study.

PubMed

Egea-Valenzuela, Juan; González Suárez, Begoña; Sierra Bernal, Cristian; Juanmartiñena Fernández, José Francisco; Luján-Sanchís, Marisol; San Juan Acosta, Mileidis; Martínez Andrés, Blanca; Pons Beltrán, Vicente; Sastre Lozano, Violeta; Carretero Ribón, Cristina; de Vera Almenar, Félix; Sánchez Cuenca, Joaquín; Alberca de Las Parras, Fernando; Rodríguez de Miguel, Cristina; Valle Muñoz, Julio; Férnandez-Urién Sainz, Ignacio; Torres González, Carolina; Borque Barrera, Pilar; Pérez-Cuadrado Robles, Enrique; Alonso Lázaro, Noelia; Martínez García, Pilar; Prieto de Frías, César; Carballo Álvarez, Fernando

2018-05-01

Capsule endoscopy (CE) is the first-line investigation in cases of suspected Crohn's disease (CD) of the small bowel, but the factors associated with a higher diagnostic yield remain unclear. Our aim is to develop and validate a scoring index to assess the risk of the patients in this setting on the basis of biomarkers. Data on fecal calprotectin, C-reactive protein, and other biomarkers from a population of 124 patients with suspected CD of the small bowel studied by CE and included in a PhD study were used to build a scoring index. This was first used on this population (internal validation process) and after that on a different set of patients from a multicenter study (external validation process). An index was designed in which every biomarker is assigned a score. Three risk groups have been established (low, intermediate, and high). In the internal validation analysis (124 individuals), patients had a 10, 46.5, and 81% probability of showing inflammatory lesions in CE in the low-risk, intermediate-risk, and high-risk groups, respectively. In the external validation analysis, including 410 patients from 12 Spanish hospitals, this probability was 15.8, 49.7, and 80.6% for the low-risk, intermediate-risk, and high-risk groups, respectively. Results from the internal validation process show that the scoring index is coherent, and results from the external validation process confirm its reliability. This index can be a useful tool for selecting patients before CE studies in cases of suspected CD of the small bowel.

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

PubMed Central

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

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

Revision of empirical electric field modeling in the inner magnetosphere using Cluster data

NASA Astrophysics Data System (ADS)

Matsui, H.; Torbert, R. B.; Spence, H. E.; Khotyaintsev, Yu. V.; Lindqvist, P.-A.

2013-07-01

Using Cluster data from the Electron Drift (EDI) and the Electric Field and Wave (EFW) instruments, we revise our empirically-based, inner-magnetospheric electric field (UNH-IMEF) model at 22.662 mV/m; Kp<1, 1≤Kp<2, 2≤Kp<3, 3≤Kp<4, 4≤Kp<5, and Kp≥4+. Patterns consist of one set of data and processing for smaller activities, and another for higher activities. As activity increases, the skewed potential contour related to the partial ring current appears on the nightside. With the revised analysis, we find that the skewed potential contours get clearer and potential contours get denser on the nightside and morningside. Since the fluctuating components are not negligible, standard deviations from the modeled values are included in the model. In this study, we perform validation of the derived model more extensively. We find experimentally that the skewed contours are located close to the last closed equipotential, consistent with previous theories. This gives physical context to our model and serves as one validation effort. As another validation effort, the derived results are compared with other models/measurements. From these comparisons, we conclude that our model has some clear advantages over the others.

Association between elder abuse and poor sleep: A cross-sectional study among rural older Malaysians

PubMed Central

Hairi, Noran N.; Choo, Wan Yuen; Hairi, Farizah M.; Sooryanarayana, Rajini; Ahmad, Sharifah N.; Razak, Inayah A.; Peramalah, Devi; Aziz, Suriyati A.; Mohamad, Zaiton L.; Mohamad, Rosmala; Ali, Zainudin M.; Awang Mahmud, Awang B.

2017-01-01

Objectives To examine the association between elder abuse and poor sleep using a Malay validated version of Pittsburgh Sleep Quality Index (PSQI). Design This study was divided into two phases. Phase I tested the construct validity and reliability of the Malay version of PSQI. Phase II was a population-based, cross-sectional study with a multi-stage cluster sampling method. Home-based interviews were conducted by trained personnel using a structured questionnaire, to determine exposure and outcome. Setting Kuala Pilah, a district in Negeri Sembilan which is one of the fourteen states in Malaysia. Participants 1648 community-dwelling older Malaysians. Results The Malay version of PSQI had significant test re-test reliability with intra-class correlation coefficients of 0.62. Confirmatory factor analyses revealed that one factor PSQI scale with three components (subjective sleep quality, sleep latency, and sleep disturbances) was most suitable. Cronbach’s Alpha was 0.60 and composite reliability was 0.63. PSQI scores were highest among neglect (4.11), followed by physical (4.10), psychological (3.96) and financial abuse (3.60). There was a dose-response relationship between clustering of abuse and PSQI scores; 3.41, 3.50 and 3.84 for “no abuse”, “1 type of abuse” and “2 types or more”. Generalized linear models revealed six variables as significant determinants of sleep quality–abuse, co-morbidities, self-rated health, income, social support and gait speed. Among abuse subtypes, only neglect was significantly associated with poor sleep. Conclusion The Malay PSQI was valid and reliable. Abuse was significantly associated with poor sleep. As sleep is essential for health and is a good predictor for mortality among older adults, management of abuse victims should entail sleep assessment. Interventions or treatment modalities which focus on improving sleep quality among abuse victims should be designed. PMID:28686603

Continental Scale Vegetation Structure Mapping Using Field Calibrated Landsat, ALOS Palsar And GLAS ICESat

NASA Astrophysics Data System (ADS)

Scarth, P.; Phinn, S. R.; Armston, J.; Lucas, R.

2015-12-01

Vertical plant profiles are important descriptors of canopy structure and are used to inform models of biomass, biodiversity and fire risk. In Australia, an approach has been developed to produce large area maps of vertical plant profiles by extrapolating waveform lidar estimates of vertical plant profiles from ICESat/GLAS using large area segmentation of ALOS PALSAR and Landsat satellite image products. The main assumption of this approach is that the vegetation height profiles are consistent across the segments defined from ALOS PALSAR and Landsat image products. More than 1500 field sites were used to develop an index of fractional cover using Landsat data. A time series of the green fraction was used to calculate the persistent green fraction continuously across the landscape. This was fused with ALOS PALSAR L-band Fine Beam Dual polarisation 25m data and used to segment the Australian landscapes. K-means clustering then grouped the segments with similar cover and backscatter into approximately 1000 clusters. Where GLAS-ICESat footprints intersected these clusters, canopy profiles were extracted and aggregated to produce a mean vertical vegetation profile for each cluster that was used to derive mean canopy and understorey height, depth and density. Due to the large number of returns, these retrievals are near continuous across the landscape, enabling them to be used for inventory and modelling applications. To validate this product, a radiative transfer model was adapted to map directional gap probability from airborne waveform lidar datasets to retrieve vertical plant profiles Comparison over several test sites show excellent agreement and work is underway to extend the analysis to improve national biomass mapping. The integration of the three datasets provide options for future operational monitoring of structure and AGB across large areas for quantifying carbon dynamics, structural change and biodiversity.

The Rorschach Perceptual-Thinking Index (PTI): An Examination of Reliability, Validity, and Diagnostic Efficiency

ERIC Educational Resources Information Center

Hilsenroth, Mark J.; Eudell-Simmons, Erin M.; DeFife, Jared A.; Charnas, Jocelyn W.

2007-01-01

This study investigates the reliability, validity, and diagnostic efficiency of the Rorschach Perceptual-Thinking Index (PTI) in relation to the accurate identification of psychotic disorder (PTD) patients. The PTI is a revision of the Rorschach Schizophrenia Index (SCZI), designed to achieve several criteria, including an increase in the…

Measuring cervical cancer risk: development and validation of the CARE Risky Sexual Behavior Index.

PubMed

Reiter, Paul L; Katz, Mira L; Ferketich, Amy K; Ruffin, Mack T; Paskett, Electra D

2009-12-01

To develop and validate a risky sexual behavior index specific to cervical cancer research. Sexual behavior data on 428 women from the Community Awareness Resources and Education (CARE) study were utilized. A weighting scheme for eight risky sexual behaviors was generated and validated in creating the CARE Risky Sexual Behavior Index. Cutpoints were then identified to classify women as having a low, medium, or high level of risky sexual behavior. Index scores ranged from 0 to 35, with women considered to have a low level of risky sexual behavior if their score was less than six (31.3% of sample), a medium level if their score was 6–10 (30.6%), or a high level if their score was 11 or greater (38.1%). A strong association was observed between the created categories and having a previous abnormal Pap smear test (p < 0.001). The CARE Risky Sexual Behavior Index provides a tool for measuring risky sexual behavior level for cervical cancer research. Future studies are needed to validate this index in varied populations and test its use in the clinical setting.

Clustering of adherence to personalised dietary recommendations and changes in healthy eating index within the Food4Me study.

PubMed

Livingstone, Katherine M; Celis-Morales, Carlos; Lara, Jose; Woolhead, Clara; O'Donovan, Clare B; Forster, Hannah; Marsaux, Cyril Fm; Macready, Anna L; Fallaize, Rosalind; Navas-Carretero, Santiago; San-Cristobal, Rodrigo; Kolossa, Silvia; Tsirigoti, Lydia; Lambrinou, Christina P; Moschonis, George; Surwiłło, Agnieszka; Drevon, Christian A; Manios, Yannis; Traczyk, Iwona; Gibney, Eileen R; Brennan, Lorraine; Walsh, Marianne C; Lovegrove, Julie A; Martinez, J Alfredo; Saris, Wim Hm; Daniel, Hannelore; Gibney, Mike; Mathers, John C

2016-12-01

To characterise clusters of individuals based on adherence to dietary recommendations and to determine whether changes in Healthy Eating Index (HEI) scores in response to a personalised nutrition (PN) intervention varied between clusters. Food4Me study participants were clustered according to whether their baseline dietary intakes met European dietary recommendations. Changes in HEI scores between baseline and month 6 were compared between clusters and stratified by whether individuals received generalised or PN advice. Pan-European, Internet-based, 6-month randomised controlled trial. Adults aged 18-79 years (n 1480). Individuals in cluster 1 (C1) met all recommended intakes except for red meat, those in cluster 2 (C2) met two recommendations, and those in cluster 3 (C3) and cluster 4 (C4) met one recommendation each. C1 had higher intakes of white fish, beans and lentils and low-fat dairy products and lower percentage energy intake from SFA (P<0·05). C2 consumed less chips and pizza and fried foods than C3 and C4 (P<0·05). C1 were lighter, had lower BMI and waist circumference than C3 and were more physically active than C4 (P<0·05). More individuals in C4 were smokers and wanted to lose weight than in C1 (P<0·05). Individuals who received PN advice in C4 reported greater improvements in HEI compared with C3 and C1 (P<0·05). The cluster where the fewest recommendations were met (C4) reported greater improvements in HEI following a 6-month trial of PN whereas there was no difference between clusters for those randomised to the Control, non-personalised dietary intervention.

Clustering of Multivariate Geostatistical Data

NASA Astrophysics Data System (ADS)

Fouedjio, Francky

2017-04-01

Multivariate data indexed by geographical coordinates have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations belonging to the same cluster have a certain degree of homogeneity while data locations in the different clusters have to be as different as possible. However, groups of data locations created through classical clustering techniques turn out to show poor spatial contiguity, a feature obviously inconvenient for many geoscience applications. In this work, we develop a clustering method that overcomes this problem by accounting the spatial dependence structure of data; thus reinforcing the spatial contiguity of resulting cluster. The capability of the proposed clustering method to provide spatially contiguous and meaningful clusters of data locations is assessed using both synthetic and real datasets. Keywords: clustering, geostatistics, spatial contiguity, spatial dependence.

Millon Clinical Multiaxial Inventory–III Subtypes of Opioid Dependence: Validity and Matching to Behavioral Therapies

PubMed Central

Ball, Samuel A.; Nich, Charla; Rounsaville, Bruce J.; Eagan, Dorothy; Carroll, Kathleen M.

2013-01-01

The concurrent and predictive validity of 2 different methods of Millon Clinical Multiaxial Inventory–III subtyping (protocol sorting, cluster analysis) was evaluated in 125 recently detoxified opioid-dependent outpatients in a 12-week randomized clinical trial. Participants received naltrexone and relapse prevention group counseling and were assigned to 1 of 3 intervention conditions: (a) no-incentive vouchers, (b) incentive vouchers alone, or (c) incentive vouchers plus relationship counseling. Affective disturbance was the most common Axis I protocol-sorted subtype (66%), antisocial–narcissistic was the most common Axis II subtype (46%), and cluster analysis suggested that a 2-cluster solution (high vs. low psychiatric severity) was optimal. Predictive validity analyses indicated less symptom improvement for the higher problem subtypes, and patient treatment matching analyses indicated that some subtypes had better outcomes in the no-incentive voucher conditions. PMID:15301655

Identification of Marker-Trait Associations for Lint Traits in Cotton

PubMed Central

Iqbal, Muhammad A.; Rahman, Mehboob-ur-

2017-01-01

Harvesting high quality lint, a long-awaited breeding goal—accomplished partly, can be achieved by identifying DNA markers which could be used for diagnosing cotton plants containing the desired traits. In the present studies, a total of 185 cotton genotypes exhibiting diversity for lint traits were selected from a set of 546 genotypes evaluated for fiber traits in 2009. These genotypes were extensively studied for three consecutive years (2011–2013) at three different locations. Significant genetic variations were found for average boll weight, ginning out turn (GOT), micronaire value, staple length, fiber bundle strength, and uniformity index. IR-NIBGE-3701 showed maximum GOT (43.63%). Clustering of genotypes using Ward's method was found more informative than that of the clusters generated by principal component analysis. A total of 382 SSRs were surveyed on 10 Gossypium hirsutum genotypes exhibiting contrasting fiber traits. Out of these, 95 polymorphic SSR primer pairs were then surveyed on 185 genotypes. The gene diversity averaged 0.191 and the polymorphic information content (PIC) averaged 0.175. Unweighted pair group method with arithmetic mean (UPGMA), principal coordinate analysis (PCoA), and STRUCTURE software grouped these genotypes into four major clusters each. Genetic distance within the clusters ranged from 0.0587 to 0.1030. A total of 47 (25.41%) genotypes exhibited shared ancestry. In total 6.8% (r2 ≥ 0.05) and 4.4% (r2 ≥ 0.1) of the marker pairs showed significant linkage disequilibrium (LD). A number of marker-trait associations (in total 75) including 13 for average boll weight, 18 for GOT percentage, eight for micronaire value, 18 for staple length, three for fiber bundle strength, and 15 for uniformity index were calculated. Out of these, MGHES-51 was associated with all the traits. Most of the marker-trait associations were novel while few validated the associations reported in the previous studies. High frequency of favorable alleles in cultivated varieties is possibly due to fixation of desirable alleles by domestication. These favorable alleles can be used in marker assisted breeding or for gene cloning using next generation sequencing tools. The present studies would set a stage for harvesting high quality lint without compromising the yield potential—ascertaining natural fiber security. PMID:28220132

Psychometric testing of the Caregiver Quality of Life Index-Cancer scale in an Iranian sample of family caregivers to newly diagnosed breast cancer women.

PubMed

Khanjari, Sedigheh; Oskouie, Fatemeh; Langius-Eklöf, Ann

2012-02-01

To translate and test the reliability and validity of the Persian version of the Caregiver Quality of Life Index-Cancer scale. Research across many countries has determined quality of life of cancer patients, but few attempts have been made to measure the quality of life of family caregivers of patients with breast cancer. The Caregiver Quality of Life Index-Cancer scale was developed for this purpose, but until now, it has not been translated into or tested in the Persian language. Methodological research design. After standard translation, the 35-item Caregiver Quality of Life Index-Cancer scale was administered to 166 Iranian family caregivers of patients with breast cancer. A confirmatory factor analysis was carried out using LISREL to test the scale's construct validity. Further, the internal consistency and convergent validity of the instrument were tested. For convergent validity, four instruments were used in the study: sense of coherence scale, spirituality perspective scale, health index and brief religious coping scale. The confirmatory factor analysis resulted in the same four-factor structure as the original, though, with somewhat different item loadings. The Persian version of the Caregiver Quality of Life Index-Cancer scales had satisfactory internal consistency (0·72-0·90). Tests of convergent validity showed that all hypotheses were confirmed. A hierarchical multiple regression analysis additionally confirmed the convergent validity between the total Caregiver Quality of Life Index-Cancer score and sense of coherence (β = 0·34), negative religious coping (β = -0·21), education (β = 0·24) and the more severe stage of breast cancer (β = 0·23), in total explaining 41% of the variance. The Persian version of the Caregiver Quality of Life Index-Cancer scale could be a reliable and valid measure in Iranian family caregivers of patients with breast cancer. The Persian version of the Caregiver Quality of Life Index-Cancer scale is simple to administer and will help nurses to identify the nursing needs of family caregivers. © 2011 Blackwell Publishing Ltd.

Spatial and temporal clustering of dengue virus transmission in Thai villages.

PubMed

Mammen, Mammen P; Pimgate, Chusak; Koenraadt, Constantianus J M; Rothman, Alan L; Aldstadt, Jared; Nisalak, Ananda; Jarman, Richard G; Jones, James W; Srikiatkhachorn, Anon; Ypil-Butac, Charity Ann; Getis, Arthur; Thammapalo, Suwich; Morrison, Amy C; Libraty, Daniel H; Green, Sharone; Scott, Thomas W

2008-11-04

Transmission of dengue viruses (DENV), the leading cause of arboviral disease worldwide, is known to vary through time and space, likely owing to a combination of factors related to the human host, virus, mosquito vector, and environment. An improved understanding of variation in transmission patterns is fundamental to conducting surveillance and implementing disease prevention strategies. To test the hypothesis that DENV transmission is spatially and temporally focal, we compared geographic and temporal characteristics within Thai villages where DENV are and are not being actively transmitted. Cluster investigations were conducted within 100 m of homes where febrile index children with (positive clusters) and without (negative clusters) acute dengue lived during two seasons of peak DENV transmission. Data on human infection and mosquito infection/density were examined to precisely (1) define the spatial and temporal dimensions of DENV transmission, (2) correlate these factors with variation in DENV transmission, and (3) determine the burden of inapparent and symptomatic infections. Among 556 village children enrolled as neighbors of 12 dengue-positive and 22 dengue-negative index cases, all 27 DENV infections (4.9% of enrollees) occurred in positive clusters (p < 0.01; attributable risk [AR] = 10.4 per 100; 95% confidence interval 1-19.8 per 100]. In positive clusters, 12.4% of enrollees became infected in a 15-d period and DENV infections were aggregated centrally near homes of index cases. As only 1 of 217 pairs of serologic specimens tested in positive clusters revealed a recent DENV infection that occurred prior to cluster initiation, we attribute the observed DENV transmission subsequent to cluster investigation to recent DENV transmission activity. Of the 1,022 female adult Ae. aegypti collected, all eight (0.8%) dengue-infected mosquitoes came from houses in positive clusters; none from control clusters or schools. Distinguishing features between positive and negative clusters were greater availability of piped water in negative clusters (p < 0.01) and greater number of Ae. aegypti pupae per person in positive clusters (p = 0.04). During primarily DENV-4 transmission seasons, the ratio of inapparent to symptomatic infections was nearly 1:1 among child enrollees. Study limitations included inability to sample all children and mosquitoes within each cluster and our reliance on serologic rather than virologic evidence of interval infections in enrollees given restrictions on the frequency of blood collections in children. Our data reveal the remarkably focal nature of DENV transmission within a hyperendemic rural area of Thailand. These data suggest that active school-based dengue case detection prompting local spraying could contain recent virus introductions and reduce the longitudinal risk of virus spread within rural areas. Our results should prompt future cluster studies to explore how host immune and behavioral aspects may impact DENV transmission and prevention strategies. Cluster methodology could serve as a useful research tool for investigation of other temporally and spatially clustered infectious diseases.

Spatial and Temporal Clustering of Dengue Virus Transmission in Thai Villages

PubMed Central

Mammen, Mammen P; Pimgate, Chusak; Koenraadt, Constantianus J. M; Rothman, Alan L; Aldstadt, Jared; Nisalak, Ananda; Jarman, Richard G; Jones, James W; Srikiatkhachorn, Anon; Ypil-Butac, Charity Ann; Getis, Arthur; Thammapalo, Suwich; Morrison, Amy C; Libraty, Daniel H; Green, Sharone; Scott, Thomas W

2008-01-01

Background Transmission of dengue viruses (DENV), the leading cause of arboviral disease worldwide, is known to vary through time and space, likely owing to a combination of factors related to the human host, virus, mosquito vector, and environment. An improved understanding of variation in transmission patterns is fundamental to conducting surveillance and implementing disease prevention strategies. To test the hypothesis that DENV transmission is spatially and temporally focal, we compared geographic and temporal characteristics within Thai villages where DENV are and are not being actively transmitted. Methods and Findings Cluster investigations were conducted within 100 m of homes where febrile index children with (positive clusters) and without (negative clusters) acute dengue lived during two seasons of peak DENV transmission. Data on human infection and mosquito infection/density were examined to precisely (1) define the spatial and temporal dimensions of DENV transmission, (2) correlate these factors with variation in DENV transmission, and (3) determine the burden of inapparent and symptomatic infections. Among 556 village children enrolled as neighbors of 12 dengue-positive and 22 dengue-negative index cases, all 27 DENV infections (4.9% of enrollees) occurred in positive clusters (p < 0.01; attributable risk [AR] = 10.4 per 100; 95% confidence interval 1–19.8 per 100]. In positive clusters, 12.4% of enrollees became infected in a 15-d period and DENV infections were aggregated centrally near homes of index cases. As only 1 of 217 pairs of serologic specimens tested in positive clusters revealed a recent DENV infection that occurred prior to cluster initiation, we attribute the observed DENV transmission subsequent to cluster investigation to recent DENV transmission activity. Of the 1,022 female adult Ae. aegypti collected, all eight (0.8%) dengue-infected mosquitoes came from houses in positive clusters; none from control clusters or schools. Distinguishing features between positive and negative clusters were greater availability of piped water in negative clusters (p < 0.01) and greater number of Ae. aegypti pupae per person in positive clusters (p = 0.04). During primarily DENV-4 transmission seasons, the ratio of inapparent to symptomatic infections was nearly 1:1 among child enrollees. Study limitations included inability to sample all children and mosquitoes within each cluster and our reliance on serologic rather than virologic evidence of interval infections in enrollees given restrictions on the frequency of blood collections in children. Conclusions Our data reveal the remarkably focal nature of DENV transmission within a hyperendemic rural area of Thailand. These data suggest that active school-based dengue case detection prompting local spraying could contain recent virus introductions and reduce the longitudinal risk of virus spread within rural areas. Our results should prompt future cluster studies to explore how host immune and behavioral aspects may impact DENV transmission and prevention strategies. Cluster methodology could serve as a useful research tool for investigation of other temporally and spatially clustered infectious diseases. PMID:18986209

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

NASA Astrophysics Data System (ADS)

Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

2013-12-01

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.

Hailstorm forecast from stability indexes in Southwestern France

NASA Astrophysics Data System (ADS)

Melcón, Pablo; Merino, Andrés; Sánchez, José Luis; Dessens, Jean; Gascón, Estíbaliz; Berthet, Claude; López, Laura; García-Ortega, Eduardo

2016-04-01

Forecasting hailstorms is a difficult task because of their small spatial and temporal scales. Over recent decades, stability indexes have been commonly used in operational forecasting to provide a simplified representation of different thermodynamic characteristics of the atmosphere, regarding the onset of convective events. However, they are estimated from vertical profiles obtained by radiosondes, which are usually available only twice a day and have limited spatial representativeness. Numerical models predictions can be used to overcome these drawbacks, providing vertical profiles with higher spatiotemporal resolution. The main objective of this study is to create a tool for hail prediction in the southwest of France, one of the European regions where hailstorms have a higher incidence. The Association Nationale d'Etude et de Lutte contre les Fleáux Atmosphériques (ANELFA) maintains there a dense hailpad network in continuous operation, which has created an extensive database of hail events, used in this study as ground truth. The new technique is aimed to classify the spatial distribution of different stability indexes on hail days. These indexes were calculated from vertical profiles at 1200 UTC provided by WRF numerical model, validated with radiosonde data from Bordeaux. Binary logistic regression is used to select those indexes that best represent thermodynamic conditions related to occurrence of hail in the zone. Then, they are combined in a single algorithm that surpassed the predictive power they have when used independently. Regression equation results in hail days are used in cluster analysis to identify different spatial patterns given by the probability algorithm. This new tool can be used in operational forecasting, in combination with synoptic and mesoscale techniques, to properly define hail probability and distribution. Acknowledgements The authors would like to thank the CEPA González Díez Foundation and the University of Leon for its financial support.

Exploration and Validation of Clusters of Physically Abused Children

ERIC Educational Resources Information Center

Ward, Caryn Sabourin; Haskett, Mary E.

2008-01-01

Objective: Cluster analysis was used to enhance understanding of heterogeneity in social adjustment of physically abused children. Method: 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…

Comparing the performance of biomedical clustering methods.

PubMed

Wiwie, Christian; Baumbach, Jan; Röttger, Richard

2015-11-01

Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future. This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide-ranging comparison we were able to develop a short guideline for biomedical clustering tasks. ClustEval allows biomedical researchers to pick the appropriate tool for their data type and allows method developers to compare their tool to the state of the art.

Classification of frailty using the Kihon checklist: A cluster analysis of older adults in urban areas.

PubMed

Kera, Takeshi; Kawai, Hisashi; Yoshida, Hideyo; Hirano, Hirohiko; Kojima, Motonaga; Fujiwara, Yoshinori; Ihara, Kazushige; Obuchi, Shuichi

2017-01-01

Frailty is an important predictor of the need for long-term care and hospitalization. Our aim was to categorize frailty in community-dwelling older adults. The present study was carried out in 2011-2013, and consisted of 1380 individuals over 65 years of age. Participants completed the Kihon checklist, which is widely used to assess frailty in Japan, and their physical, cognitive and social function was evaluated. Non-hierarchical cluster analysis was used to statistically categorize frailty. The optimum number of clusters was determined as the point at which the external reference values (instrumental activity of daily living score, grip power, 10-m walk time, body mass index, portable fall risk index, occlusal force and Mini-Mental State Examination score) differed. According to the Kihon checklist, 369 (26.7%) of the 1380 study participants were considered frail. When the cluster number was increased from two to six, the scores in each subdomain of the Kihon checklist significantly differed. The estimated minimum number of clusters was five, and each of the five cluster groups had distinct characteristics. The numbers of participants in cluster groups 1-5 were 105, 78, 62, 71 and 53, respectively. We identified five types of frailty in community-dwelling older adults in Japan: "experience of falling," "pre-frailty," "oral frailty," "housebound" and "severe frailty." Geriatr Gerontol Int 2017; 17: 69-77. © 2016 Japan Geriatrics Society.

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

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

Convalescing Cluster Configuration Using a Superlative Framework

PubMed Central

Sabitha, R.; Karthik, S.

2015-01-01

Competent data mining methods are vital to discover knowledge from databases which are built as a result of enormous growth of data. Various techniques of data mining are applied to obtain knowledge from these databases. Data clustering is one such descriptive data mining technique which guides in partitioning data objects into disjoint segments. K-means algorithm is a versatile algorithm among the various approaches used in data clustering. The algorithm and its diverse adaptation methods suffer certain problems in their performance. To overcome these issues a superlative algorithm has been proposed in this paper to perform data clustering. The specific feature of the proposed algorithm is discretizing the dataset, thereby improving the accuracy of clustering, and also adopting the binary search initialization method to generate cluster centroids. The generated centroids are fed as input to K-means approach which iteratively segments the data objects into respective clusters. The clustered results are measured for accuracy and validity. Experiments conducted by testing the approach on datasets from the UC Irvine Machine Learning Repository evidently show that the accuracy and validity measure is higher than the other two approaches, namely, simple K-means and Binary Search method. Thus, the proposed approach proves that discretization process will improve the efficacy of descriptive data mining tasks. PMID:26543895

Clustering of unhealthy food around German schools and its influence on dietary behavior in school children: a pilot study

PubMed Central

2013-01-01

Background The availability of fast foods, sweets, and other snacks in the living environment of children is assumed to contribute to an obesogenic environment. In particular, it is hypothesized that food retailers are spatially clustered around schools and that a higher availability of unhealthy foods leads to its higher consumption in children. Studies that support these relationships have primarily been conducted in the U.S. or Australia, but rarely in European communities. We used data of FFQ and 24-HDR of the IDEFICS study, as well as geographical data from one German study region to investigate (1) the clustering of food outlets around schools and (2) the influence of junk food availability on the food intake in school children. Methods We geocoded food outlets offering junk food (e.g. supermarkets, kiosks, and fast food restaurants). Spatial cluster analysis of food retailers around child-serving institutions was conducted using an inhomogeneous K-function to calculate global 95% confidence envelopes. Furthermore, a food retail index was implemented considering the kernel density of junk food supplies per service area, adjusted for residential density. We linked the food retail index to FFQ and 24-HDR data of 384 6- to 9-year-old school children in the study region and investigated the impact of the index on food intake, using multilevel regression models adjusted for sex, age, BMI, parent’s education and income, as well as adjusting for over- and underreporting of food intake. Results Comparing the 95% confidence envelopes to the observed K-function, we showed that food stores and fast food restaurants do not significantly cluster around schools. Apart from this result, the food retail index showed no effect on BMI (β=0.01,p=0.11) or food intake variables assessed by FFQ and 24-HDR. Conclusion In the built environment of the German study region, clustering of food retailers does not depend on the location of schools. Additionally, the results suggest that the consumption of junk food in young children is not influenced by spatial availability of unhealthy food. However, investigations should be replicated in other European communities to increase environmental variability. PMID:23714200

Modeling Classical Swine Fever Outbreak-Related Outcomes

PubMed Central

Yadav, Shankar; Olynk Widmar, Nicole J.; Weng, Hsin-Yi

2016-01-01

The study was carried out to estimate classical swine fever (CSF) outbreak-related outcomes, such as epidemic duration and number of infected, vaccinated, and depopulated premises, using defined most likely CSF outbreak scenarios. Risk metrics were established using empirical data to select the most likely CSF outbreak scenarios in Indiana. These scenarios were simulated using a stochastic between-premises disease spread model to estimate outbreak-related outcomes. A total of 19 single-site (i.e., with one index premises at the onset of an outbreak) and 15 multiple-site (i.e., with more than one index premises at the onset of an outbreak) outbreak scenarios of CSF were selected using the risk metrics. The number of index premises in the multiple-site outbreak scenarios ranged from 4 to 32. The multiple-site outbreak scenarios were further classified into clustered (N = 6) and non-clustered (N = 9) groups. The estimated median (5th, 95th percentiles) epidemic duration (days) was 224 (24, 343) in the single-site and was 190 (157, 251) and 210 (167, 302) in the clustered and non-clustered multiple-site outbreak scenarios, respectively. The median (5th, 95th percentiles) number of infected premises was 323 (0, 488) in the single-site outbreak scenarios and was 529 (395, 662) and 465 (295, 640) in the clustered and non-clustered multiple-site outbreak scenarios, respectively. Both the number and spatial distributions of the index premises affected the outcome estimates. The results also showed the importance of implementing vaccinations to accommodate depopulation in the CSF outbreak controls. The use of routinely collected surveillance data in the risk metrics and disease spread model allows end users to generate timely outbreak-related information based on the initial outbreak’s characteristics. Swine producers can use this information to make an informed decision on the management of swine operations and continuity of business, so that potential losses could be minimized during a CSF outbreak. Government authorities might use the information to make emergency preparedness plans for CSF outbreak control. PMID:26870741

Clustering of unhealthy food around German schools and its influence on dietary behavior in school children: a pilot study.

PubMed

Buck, Christoph; Börnhorst, Claudia; Pohlabeln, Hermann; Huybrechts, Inge; Pala, Valeria; Reisch, Lucia; Pigeot, Iris

2013-05-24

The availability of fast foods, sweets, and other snacks in the living environment of children is assumed to contribute to an obesogenic environment. In particular, it is hypothesized that food retailers are spatially clustered around schools and that a higher availability of unhealthy foods leads to its higher consumption in children. Studies that support these relationships have primarily been conducted in the U.S. or Australia, but rarely in European communities. We used data of FFQ and 24-HDR of the IDEFICS study, as well as geographical data from one German study region to investigate (1) the clustering of food outlets around schools and (2) the influence of junk food availability on the food intake in school children. We geocoded food outlets offering junk food (e.g. supermarkets, kiosks, and fast food restaurants). Spatial cluster analysis of food retailers around child-serving institutions was conducted using an inhomogeneous K-function to calculate global 95% confidence envelopes. Furthermore, a food retail index was implemented considering the kernel density of junk food supplies per service area, adjusted for residential density. We linked the food retail index to FFQ and 24-HDR data of 384 6- to 9-year-old school children in the study region and investigated the impact of the index on food intake, using multilevel regression models adjusted for sex, age, BMI, parent's education and income, as well as adjusting for over- and underreporting of food intake. Comparing the 95% confidence envelopes to the observed K-function, we showed that food stores and fast food restaurants do not significantly cluster around schools. Apart from this result, the food retail index showed no effect on BMI (β=0.01,p=0.11) or food intake variables assessed by FFQ and 24-HDR. In the built environment of the German study region, clustering of food retailers does not depend on the location of schools. Additionally, the results suggest that the consumption of junk food in young children is not influenced by spatial availability of unhealthy food. However, investigations should be replicated in other European communities to increase environmental variability.

Reliability and validity of the Korean version of the Short Musculoskeletal Function Assessment questionnaire for patients with musculoskeletal disorder.

PubMed

Jung, Kyoung-Sim; Jung, Jin-Hwa; In, Tae-Sung; Cho, Hwi-Young

2016-09-01

[Purpose] The purpose of this study was to establish the reliability and validity of the Short Musculoskeletal Function Assessment questionnaire, which was translated into Korean, for patients with musculoskeletal disorder. [Subjects and Methods] Fifty-five subjects (26 males and 29 females) with musculoskeletal diseases participated in the study. The Short Musculoskeletal Function Assessment questionnaire focuses on a limited range of physical functions and includes a dysfunction index and a bother index. Reliability was determined using the intraclass correlation coefficient, and validity was examined by correlating short musculoskeletal function assessment scores with the 36-item Short-Form Health Survey (SF-36) score. [Results] The reliability was 0.97 for the dysfunction index and 0.94 for the bother index. Validity was established by comparison with Korean version of the SF-36. [Conclusion] This study demonstrated that the Korean version of the Short Musculoskeletal Function Assessment questionnaire is a reliable and valid instrument for the assessment of musculoskeletal disorders.

VALIDITY OF HYDROSTATIC EQUILIBRIUM IN GALAXY CLUSTERS FROM COSMOLOGICAL HYDRODYNAMICAL SIMULATIONS

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

Suto, Daichi; Suto, Yasushi; Kawahara, Hajime

2013-04-10

We examine the validity of the hydrostatic equilibrium (HSE) assumption for galaxy clusters using one of the highest-resolution cosmological hydrodynamical simulations. We define and evaluate several effective mass terms corresponding to the Euler equations of gas dynamics, and quantify the degree of the validity of HSE in terms of the mass estimate. We find that the mass estimated under the HSE assumption (the HSE mass) deviates from the true mass by up to {approx}30%. This level of departure from HSE is consistent with the previous claims, but our physical interpretation is rather different. We demonstrate that the inertial term inmore » the Euler equations makes a negligible contribution to the total mass, and the overall gravity of the cluster is balanced by the thermal gas pressure gradient and the gas acceleration term. Indeed, the deviation from the HSE mass is well explained by the acceleration term at almost all radii. We also clarify the confusion of previous work due to the inappropriate application of the Jeans equations in considering the validity of HSE from the gas dynamics extracted from cosmological hydrodynamical simulations.« less

Impact of socioeconomic inequalities on geographic disparities in cancer incidence: comparison of methods for spatial disease mapping.

PubMed

Goungounga, Juste Aristide; Gaudart, Jean; Colonna, Marc; Giorgi, Roch

2016-10-12

The reliability of spatial statistics is often put into question because real spatial variations may not be found, especially in heterogeneous areas. Our objective was to compare empirically different cluster detection methods. We assessed their ability to find spatial clusters of cancer cases and evaluated the impact of the socioeconomic status (e.g., the Townsend index) on cancer incidence. Moran's I, the empirical Bayes index (EBI), and Potthoff-Whittinghill test were used to investigate the general clustering. The local cluster detection methods were: i) the spatial oblique decision tree (SpODT); ii) the spatial scan statistic of Kulldorff (SaTScan); and, iii) the hierarchical Bayesian spatial modeling (HBSM) in a univariate and multivariate setting. These methods were used with and without introducing the Townsend index of socioeconomic deprivation known to be related to the distribution of cancer incidence. Incidence data stemmed from the Cancer Registry of Isère and were limited to prostate, lung, colon-rectum, and bladder cancers diagnosed between 1999 and 2007 in men only. The study found a spatial heterogeneity (p < 0.01) and an autocorrelation for prostate (EBI = 0.02; p = 0.001), lung (EBI = 0.01; p = 0.019) and bladder (EBI = 0.007; p = 0.05) cancers. After introduction of the Townsend index, SaTScan failed in finding cancers clusters. This introduction changed the results obtained with the other methods. SpODT identified five spatial classes (p < 0.05): four in the Western and one in the Northern parts of the study area (standardized incidence ratios: 1.68, 1.39, 1.14, 1.12, and 1.16, respectively). In the univariate setting, the Bayesian smoothing method found the same clusters as the two other methods (RR >1.2). The multivariate HBSM found a spatial correlation between lung and bladder cancers (r = 0.6). In spatial analysis of cancer incidence, SpODT and HBSM may be used not only for cluster detection but also for searching for confounding or etiological factors in small areas. Moreover, the multivariate HBSM offers a flexible and meaningful modeling of spatial variations; it shows plausible previously unknown associations between various cancers.

Hierarchical Clustering on the Basis of Inter-Job Similarity as a Tool in Validity Generalization

ERIC Educational Resources Information Center

Mobley, William H.; Ramsay, Robert S.

1973-01-01

The present research was stimulated by three related problems frequently faced in validation research: viable procedures for combining similar jobs in order to assess the validity of various predictors, for assessing groups of jobs represented in previous validity studies, and for assessing the applicability of validity findings between units.…

Concurrent Validity of Wechsler Adult Intelligence Scales-Third Edition Index Score Short Forms in the Canadian Standardization Sample

ERIC Educational Resources Information Center

Lange, Rael T.; Iverson, Grant L.

2008-01-01

This study evaluated the concurrent validity of estimated Wechsler Adult Intelligence Scales-Third Edition (WAIS-III) index scores using various one- and two-subtest combinations. Participants were the Canadian WAIS-III standardization sample. Using all possible one- and two-subtest combinations, an estimated Verbal Comprehension Index (VCI), an…

The effectiveness of repeat lumbar transforaminal epidural steroid injections.

PubMed

Murthy, Naveen S; Geske, Jennifer R; Shelerud, Randy A; Wald, John T; Diehn, Felix E; Thielen, Kent R; Kaufmann, Timothy J; Morris, Jonathan M; Lehman, Vance T; Amrami, Kimberly K; Carter, Rickey E; Maus, Timothy P

2014-10-01

The aim of this study was to determine 1) if repeat lumbar transforaminal epidural steroid injections (TFESIs) resulted in recovery of pain relief, which has waned since an index injection, and 2) if cumulative benefit could be achieved by repeat injections within 3 months of the index injection. Retrospective observational study with statistical modeling of the response to repeat TFESI. Academic radiology practice. Two thousand eighty-seven single-level TFESIs were performed for radicular pain on 933 subjects. Subjects received repeat TFESIs >2 weeks and <1 year from the index injection. Hierarchical linear modeling was performed to evaluate changes in continuous and categorical pain relief outcomes after repeat TFESI. Subgroup analyses were performed on patients with <3 months duration of pain (acute pain), patients receiving repeat injections within 3 months (clustered injections), and in patients with both acute pain and clustered injections. Repeat TFESIs achieved pain relief in both continuous and categorical outcomes. Relative to the index injection, there was a minimal but statistically significant decrease in pain relief in modeled continuous outcome measures with subsequent injections. Acute pain patients recovered all prior benefit with a statistically significant cumulative benefit. Patients receiving clustered injections achieved statistically significant cumulative benefit, of greater magnitude in acute pain patients. Repeat TFESI may be performed for recurrence of radicular pain with the expectation of recovery of most or all previously achieved benefit; acute pain patients will likely recover all prior benefit. Repeat TFESIs within 3 months of the index injection can provide cumulative benefit. Wiley Periodicals, Inc.

Development and validation of an ICD-10-based disability predictive index for patients admitted to hospitals with trauma.

PubMed

Wada, Tomoki; Yasunaga, Hideo; Yamana, Hayato; Matsui, Hiroki; Fushimi, Kiyohide; Morimura, Naoto

2018-03-01

There was no established disability predictive measurement for patients with trauma that could be used in administrative claims databases. The aim of the present study was to develop and validate a diagnosis-based disability predictive index for severe physical disability at discharge using the International Classification of Diseases, 10th revision (ICD-10) coding. This retrospective observational study used the Diagnosis Procedure Combination database in Japan. Patients who were admitted to hospitals with trauma and discharged alive from 01 April 2010 to 31 March 2015 were included. Pediatric patients under 15 years old were excluded. Data for patients admitted to hospitals from 01 April 2010 to 31 March 2013 was used for development of a disability predictive index (derivation cohort), while data for patients admitted to hospitals from 01 April 2013 to 31 March 2015 was used for the internal validation (validation cohort). The outcome of interest was severe physical disability defined as the Barthel Index score of <60 at discharge. Trauma-related ICD-10 codes were categorized into 36 injury groups with reference to the categorization used in the Global Burden of Diseases study 2013. A multivariable logistic regression analysis was performed for the outcome using the injury groups and patient baseline characteristics including patient age, sex, and Charlson Comorbidity Index (CCI) score in the derivation cohort. A score corresponding to a regression coefficient was assigned to each injury group. The disability predictive index for each patient was defined as the sum of the scores. The predictive performance of the index was validated using the receiver operating characteristic curve analysis in the validation cohort. The derivation cohort included 1,475,158 patients, while the validation cohort included 939,659 patients. Of the 939,659 patients, 235,382 (25.0%) were discharged with severe physical disability. The c-statistics of the disability predictive index was 0.795 (95% confidence interval [CI] 0.794-0.795), while that of a model using the disability predictive index and patient baseline characteristics was 0.856 (95% CI 0.855-0.857). Severe physical disability at discharge may be well predicted with patient age, sex, CCI score, and the diagnosis-based disability predictive index in patients admitted to hospitals with trauma. Copyright © 2018 Elsevier Ltd. All rights reserved.

A cross-sectional study of the association of age, race and ethnicity, and body mass index with sex steroid hormone marker profiles among men in the National Health and Nutrition Examination Survey (NHANES III)

PubMed Central

Ritchey, Jamie; Karmaus, Wilfried; Sabo-Attwood, Tara; Steck, Susan E; Zhang, Hongmei

2012-01-01

Objectives Since sex hormone markers are metabolically linked, examining sex steroid hormones singly may account for inconsistent findings by age, race/ethnicity and body mass index (BMI) across studies. First, these markers were statistically combined into profiles to account for the metabolic relationship between markers. Then, the relationships between sex steroid hormone profiles and age, race/ethnicity and BMI were explored in multinomial logistic regression models. Design Cross-sectional survey. Setting The US Third National Health and Nutrition Examination Survey (NHANES III). Participants 1538 Men, >17 years. Primary outcome measure Sex hormone profiles. Results Cluster analysis was used to identify four statistically determined profiles with Blom-transformed T, E, sex hormone binding globulin (SHBG), and 3-α diol G. We used these four profiles with multinomial logistic regression models to examine differences by race/ethnicity, age and BMI. Mexican American men >50 years were associated with the profile that had lowest T, E and 3-α diol G levels compared to other profiles (p<0.05). Non-Hispanic Black, overweight (25–29.9 kg/m2) and obese (>30 kg/m2) men were most likely to be associated with the cluster with the lowest SHBG (p<0.05). Conclusion The associations of sex steroid hormone profiles by race/ethnicity are novel, while the findings by age and BMI groups are largely consistent with observations from single hormone studies. Future studies should validate these hormone profile groups and investigate these profiles in relation to chronic diseases and certain cancers. PMID:23043125

Application of 2D and 3D image technologies to characterise morphological attributes of grapevine clusters.

PubMed

Tello, Javier; Cubero, Sergio; Blasco, José; Tardaguila, Javier; Aleixos, Nuria; Ibáñez, Javier

2016-10-01

Grapevine cluster morphology influences the quality and commercial value of wine and table grapes. It is routinely evaluated by subjective and inaccurate methods that do not meet the requirements set by the food industry. Novel two-dimensional (2D) and three-dimensional (3D) machine vision technologies emerge as promising tools for its automatic and fast evaluation. The automatic evaluation of cluster length, width and elongation was successfully achieved by the analysis of 2D images, significant and strong correlations with the manual methods being found (r = 0.959, 0.861 and 0.852, respectively). The classification of clusters according to their shape can be achieved by evaluating their conicity in different sections of the cluster. The geometric reconstruction of the morphological volume of the cluster from 2D features worked better than the direct 3D laser scanning system, showing a high correlation (r = 0.956) with the manual approach (water displacement method). In addition, we constructed and validated a simple linear regression model for cluster compactness estimation. It showed a high predictive capacity for both the training and validation subsets of clusters (R(2)  = 84.5 and 71.1%, respectively). The methodologies proposed in this work provide continuous and accurate data for the fast and objective characterisation of cluster morphology. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

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

PubMed

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

2018-08-01

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

Development and validation of a Client Problem Profile and Index for drug treatment.

PubMed

Joe, George W; Simpson, D Dwayne; Greener, Jack M; Rowan-Szal, Grace A

2004-08-01

The development of the Client Problem Profile and Index are described, and initial concurrent and predictive validity data are presented for a sample of 547 patients in outpatient methadone treatment. Derived from the TCU Brief Intake for drug treatment admissions, the profile covers 14 problem areas related to drug use (particularly cocaine, heroin/opiate, marijuana, other illegal drugs, and multiple drug use), HIV risks, psychosocial-functioning, health, employment, and criminality. Analyses of predictive validity show the profile and its index (number of problem areas) were significantly related to therapeutic engagement, during-treatment performance, and posttreatment follow-up outcomes. Low moderate to high moderate effect sizes were observed in analyses of the index's discrimination.

[Relevance and validity of a new French composite index to measure poverty on a geographical level].

PubMed

Challier, B; Viel, J F

2001-02-01

A number of disease conditions are influenced by deprivation. Geographical measurement of deprivation can provide an independent contribution to individual measures by accounting for the social context. Such a geographical approach, based on deprivation indices, is classical in Great Britain but scarcely used in France. The objective of this work was to build and validate an index readily usable in French municipalities and cantons. Socioeconomic data (unemployment, occupations, housing specifications, income, etc.) were derived from the 1990 census of municipalities and cantons in the Doubs departement. A new index was built by principal components analysis on the municipality data. The validity of the new index was checked and tested for correlations with British deprivation indices. Principal components analysis on municipality data identified four components (explaining 76% of the variance). Only the first component (CP1 explaining 42% of the variance) was retained. Content validity (wide choice of potential deprivation items, correlation between items and CP1: 0.52 to 0.96) and construct validity (CP1 socially relevant; Cronbach's alpha=0.91; correlation between CP1 and three out of four British indices ranging from 0.73 to 0.88) were sufficient. Analysis on canton data supported that on municipality data. The validation of the new index being satisfactory, the user will have to make a choice. The new index, CP1, is closer to the local background and was derived from data from a French departement. It is therefore better adapted to more descriptive approaches such as health care planning. To examine the relationship between deprivation and health with a more etiological approach, the British indices (anteriority, international comparisons) would be more appropriate, but CP1, once validated in various health problem situations, should be most useful for French studies.

Equivalent damage validation by variable cluster analysis

NASA Astrophysics Data System (ADS)

Drago, Carlo; Ferlito, Rachele; Zucconi, Maria

2016-06-01

The main aim of this work is to perform a clustering analysis on the damage relieved in the old center of L'Aquila after the earthquake occurred on April 6, 2009 and to validate an Indicator of Equivalent Damage ED that summarizes the information reported on the AeDES card regarding the level of damage and their extension on the surface of the buildings. In particular we used a sample of 13442 masonry buildings located in an area characterized by a Macroseismic Intensity equal to 8 [1]. The aim is to ensure the coherence between the clusters and its hierarchy identified in the data of damage detected and in the data of the ED elaborated.

Validity analysis on merged and averaged data using within and between analysis: focus on effect of qualitative social capital on self-rated health.

PubMed

Shin, Sang Soo; Shin, Young-Jeon

2016-01-01

With an increasing number of studies highlighting regional social capital (SC) as a determinant of health, many studies are using multi-level analysis with merged and averaged scores of community residents' survey responses calculated from community SC data. Sufficient examination is required to validate if the merged and averaged data can represent the community. Therefore, this study analyzes the validity of the selected indicators and their applicability in multi-level analysis. Within and between analysis (WABA) was performed after creating community variables using merged and averaged data of community residents' responses from the 2013 Community Health Survey in Korea, using subjective self-rated health assessment as a dependent variable. Further analysis was performed following the model suggested by WABA result. Both E-test results (1) and WABA results (2) revealed that single-level analysis needs to be performed using qualitative SC variable with cluster mean centering. Through single-level multivariate regression analysis, qualitative SC with cluster mean centering showed positive effect on self-rated health (0.054, p<0.001), although there was no substantial difference in comparison to analysis using SC variables without cluster mean centering or multi-level analysis. As modification in qualitative SC was larger within the community than between communities, we validate that relational analysis of individual self-rated health can be performed within the group, using cluster mean centering. Other tests besides the WABA can be performed in the future to confirm the validity of using community variables and their applicability in multi-level analysis.

Major depressive disorder subtypes to predict long-term course

PubMed Central

van Loo, Hanna M.; Cai, Tianxi; Gruber, Michael J.; Li, Junlong; de Jonge, Peter; Petukhova, Maria; Rose, Sherri; Sampson, Nancy A.; Schoevers, Robert A.; Wardenaar, Klaas J.; Wilcox, Marsha A.; Al-Hamzawi, Ali Obaid; Andrade, Laura Helena; Bromet, Evelyn J.; Bunting, Brendan; Fayyad, John; Florescu, Silvia E.; Gureje, Oye; Hu, Chiyi; Huang, Yueqin; Levinson, Daphna; Medina-Mora, Maria Elena; Nakane, Yoshibumi; Posada-Villa, Jose; Scott, Kate M.; Xavier, Miguel; Zarkov, Zahari; Kessler, Ronald C.

2016-01-01

Background Variation in course of major depressive disorder (MDD) is not strongly predicted by existing subtype distinctions. A new subtyping approach is considered here. Methods Two data mining techniques, ensemble recursive partitioning and Lasso generalized linear models (GLMs) followed by k-means cluster analysis, are used to search for subtypes based on index episode symptoms predicting subsequent MDD course in the World Mental Health (WMH) Surveys. The WMH surveys are community surveys in 16 countries. Lifetime DSM-IV MDD was reported by 8,261 respondents. Retrospectively reported outcomes included measures of persistence (number of years with an episode; number of with an episode lasting most of the year) and severity (hospitalization for MDD; disability due to MDD). Results Recursive partitioning found significant clusters defined by the conjunctions of early onset, suicidality, and anxiety (irritability, panic, nervousness-worry-anxiety) during the index episode. GLMs found additional associations involving a number of individual symptoms. Predicted values of the four outcomes were strongly correlated. Cluster analysis of these predicted values found three clusters having consistently high, intermediate, or low predicted scores across all outcomes. The high-risk cluster (30.0% of respondents) accounted for 52.9-69.7% of high persistence and severity and was most strongly predicted by index episode severe dysphoria, suicidality, anxiety, and early onset. A total symptom count, in comparison, was not a significant predictor. Conclusions Despite being based on retrospective reports, results suggest that useful MDD subtyping distinctions can be made using data mining methods. Further studies are needed to test and expand these results with prospective data. PMID:24425049

Derivation and validation of a composite index of severity in chronic obstructive pulmonary disease: the DOSE Index.

PubMed

Jones, Rupert C; Donaldson, Gavin C; Chavannes, Niels H; Kida, Kozui; Dickson-Spillmann, Maria; Harding, Samantha; Wedzicha, Jadwiga A; Price, David; Hyland, Michael E

2009-12-15

Chronic obstructive pulmonary disease (COPD) is increasingly recognized as a multicomponent disease with systemic consequences and effects on quality of life. Single measures such as lung function provide a limited reflection of how the disease affects patients. Composite measures have the potential to account for many of the facets of COPD. To derive and validate a multicomponent assessment tool of COPD severity that is applicable to all patients and health care settings. The index was derived using data from 375 patients with COPD in primary care. Regression analysis led to a model explaining 48% of the variance in health status as measured by the Clinical COPD Questionnaire with four components: dyspnea (D), airflow obstruction (O), smoking status (S), and exacerbation frequency (E). The DOSE Index was validated in cross-sectional and longitudinal samples in various health care settings in Holland, Japan, and the United Kingdom. The DOSE Index correlated with health status in all data sets. A high DOSE Index score (> or = 4) was associated with a greater risk of hospital admission (odds ratio, 8.3 [4.1-17]) or respiratory failure (odds ratio, 7.8 [3.4-18.3]). The index predicted exacerbations in the subsequent year (P < or = 0.014). The DOSE Index is a simple, valid tool for assessing the severity of COPD. The index is related to a range of clinically important outcomes such as health care consumption and predicts future events.

ctsGE-clustering subgroups of expression data.

PubMed

Sharabi-Schwager, Michal; Or, Etti; Ophir, Ron

2017-07-01

A pre-requisite to clustering noisy data, such as gene-expression data, is the filtering step. As an alternative to this step, the ctsGE R-package applies a sorting step in which all of the data are divided into small groups. The groups are divided according to how the time points are related to the time-series median. Then clustering is performed separately on each group. Thus, the clustering is done in two steps. First, an expression index (i.e. a sequence of 1, -1 and 0) is defined and genes with the same index are grouped together, and then each group of genes is clustered by k-means to create subgroups. The ctsGE package also provides an interactive tool to visualize and explore the gene-expression patterns and their subclusters. ctsGE proposes a way of organizing and exploring expression data without eliminating valuable information. Freely available as part of the Bioconductor project at https://bioconductor.org/packages/ctsGE/ . ron@agri.gov.il. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The persistent clustering of adult body mass index by school attended in adolescence.

PubMed

Evans, Clare Rosenfeld; Lippert, Adam M; Subramanian, S V

2016-03-01

It is well known that adolescent body mass index (BMI) shows school-level clustering. We explore whether school-level clustering of BMI persists into adulthood. Multilevel models nesting young adults in schools they attended as adolescents are fit for 3 outcomes: adolescent BMI, self-report adult BMI and measured adult BMI. Sex-stratified and race/ethnicity-stratified (black, Hispanic, white, other) analyses were also conducted. School-level clustering (wave 1 intraclass correlation coefficient (ICC)=1.3%) persists over time (wave 4 ICC=2%), and results are comparable across stratified analyses of both sexes and all racial/ethnic groups (except for Hispanics when measured BMIs are used). Controlling for BMI in adolescence partially attenuates this effect. School-level clustering of BMI persists into young adulthood. Possible explanations include the salience of school environments in establishing behaviours and trajectories, the selection of adult social networks that resemble adolescent networks and reinforce previous behaviours, and characteristics of school catchment areas associated with BMI. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

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

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

2013-12-15

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme ismore » confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.« less

An improved bridge safety index for narrow bridges.

DOT National Transportation Integrated Search

1983-08-01

In this report, a new bridge safety index is developed based upon an extensive : statistical study of accident data on 78 bridges. A total of 655 accidents : were recorded at these bridges over the six-year period between 1974 and 1979. : Cluster ana...

Dietary patterns and the insulin resistance phenotype among non-diabetic adults

USDA-ARS?s Scientific Manuscript database

Background: Information on the relation between dietary patterns derived by cluster analysis and insulin resistance is scarce. Objective: To compare insulin resistance phenotypes, including waist circumference, body mass index, fasting and 2-hour post-challenge insulin, insulin sensitivity index (I...

Clustering and Profiling Students According to Their Interactions with an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Harley, Jason M.; Trevors, Gregory J.; Azevedo, Roger

2013-01-01

In this paper, we present the results obtained using a clustering algorithm (Expectation-Maximization) on data collected from 106 college students learning about the circulatory system with MetaTutor, an agent-based Intelligent Tutoring System (ITS) designed to foster self-regulated learning (SRL). The three extracted clusters were validated and…

Validity of body mass index as a measurement of adiposity in infancy

USDA-ARS?s Scientific Manuscript database

To assess the validity of body mass index (BMI) and age- and sex-standardized BMI z-score (BMIZ) as surrogates for adiposity (body fat percentage [BF%], fat mass, and fat mass index [kg/m2]) at 3 time points in infancy (1, 4, and 7 months) and to assess the extent to which the change in BMIZ represe...

The Cluster Sensitivity Index: A Basic Measure of Classification Robustness

ERIC Educational Resources Information Center

Hom, Willard C.

2010-01-01

Analysts of institutional performance have occasionally used a peer grouping approach in which they compared institutions only to other institutions with similar characteristics. Because analysts historically have used cluster analysis to define peer groups (i.e., the group of comparable institutions), the author proposes and demonstrates with…

Distinct ADHD Symptom Clusters Differentially Associated with Personality Traits

ERIC Educational Resources Information Center

McKinney, Ashley A.; Canu, Will H.; Schneider, H. G.

2013-01-01

Objective: ADHD has been linked to various constructs, yet there is a lack of focus on how its symptom clusters differentially associate with personality, which this study addresses. Method: The current study examines the relationship between impulsive and inattentive ADHD traits and personality, indexed by the Revised NEO Personality Inventory…

Earthquake clustering in modern seismicity and its relationship with strong historical earthquakes around Beijing, China

NASA Astrophysics Data System (ADS)

Wang, Jian; Main, Ian G.; Musson, Roger M. W.

2017-11-01

Beijing, China's capital city, is located in a typical intraplate seismic belt, with relatively high-quality instrumental catalogue data available since 1970. The Chinese historical earthquake catalogue contains six strong historical earthquakes of Ms ≥ 6 around Beijing, the earliest in 294 AD. This poses a significant potential hazard to one of the most densely populated and economically active parts of China. In some intraplate areas, persistent clusters of events associated with historical events can occur over centuries, for example, the ongoing sequence in the New Madrid zone of the eastern US. Here we will examine the evidence for such persistent clusters around Beijing. We introduce a metric known as the `seismic density index' that quantifies the degree of clustering of seismic energy release. For a given map location, this multi-dimensional index depends on the number of events, their magnitudes, and the distances to the locations of the surrounding population of earthquakes. We apply the index to modern instrumental catalogue data between 1970 and 2014, and identify six clear candidate zones. We then compare these locations to earthquake epicentre and seismic intensity data for the six largest historical earthquakes. Each candidate zone contains one of the six historical events, and the location of peak intensity is within 5 km or so of the reported epicentre in five of these cases. In one case—the great Ms 8 earthquake of 1679—the peak is closer to the area of strongest shaking (Intensity XI or more) than the reported epicentre. The present-day event rates are similar to those predicted by the modified Omori law but there is no evidence of ongoing decay in event rates. Accordingly, the index is more likely to be picking out the location of persistent weaknesses in the lithosphere. Our results imply zones of high seismic density index could be used in principle to indicate the location of unrecorded historical of palaeoseismic events, in China and elsewhere.

Trust index based fault tolerant multiple event localization algorithm for WSNs.

PubMed

Xu, Xianghua; Gao, Xueyong; Wan, Jian; Xiong, Naixue

2011-01-01

This paper investigates the use of wireless sensor networks for multiple event source localization using binary information from the sensor nodes. The events could continually emit signals whose strength is attenuated inversely proportional to the distance from the source. In this context, faults occur due to various reasons and are manifested when a node reports a wrong decision. In order to reduce the impact of node faults on the accuracy of multiple event localization, we introduce a trust index model to evaluate the fidelity of information which the nodes report and use in the event detection process, and propose the Trust Index based Subtract on Negative Add on Positive (TISNAP) localization algorithm, which reduces the impact of faulty nodes on the event localization by decreasing their trust index, to improve the accuracy of event localization and performance of fault tolerance for multiple event source localization. The algorithm includes three phases: first, the sink identifies the cluster nodes to determine the number of events occurred in the entire region by analyzing the binary data reported by all nodes; then, it constructs the likelihood matrix related to the cluster nodes and estimates the location of all events according to the alarmed status and trust index of the nodes around the cluster nodes. Finally, the sink updates the trust index of all nodes according to the fidelity of their information in the previous reporting cycle. The algorithm improves the accuracy of localization and performance of fault tolerance in multiple event source localization. The experiment results show that when the probability of node fault is close to 50%, the algorithm can still accurately determine the number of the events and have better accuracy of localization compared with other algorithms.

Trust Index Based Fault Tolerant Multiple Event Localization Algorithm for WSNs

PubMed Central

Xu, Xianghua; Gao, Xueyong; Wan, Jian; Xiong, Naixue

2011-01-01

This paper investigates the use of wireless sensor networks for multiple event source localization using binary information from the sensor nodes. The events could continually emit signals whose strength is attenuated inversely proportional to the distance from the source. In this context, faults occur due to various reasons and are manifested when a node reports a wrong decision. In order to reduce the impact of node faults on the accuracy of multiple event localization, we introduce a trust index model to evaluate the fidelity of information which the nodes report and use in the event detection process, and propose the Trust Index based Subtract on Negative Add on Positive (TISNAP) localization algorithm, which reduces the impact of faulty nodes on the event localization by decreasing their trust index, to improve the accuracy of event localization and performance of fault tolerance for multiple event source localization. The algorithm includes three phases: first, the sink identifies the cluster nodes to determine the number of events occurred in the entire region by analyzing the binary data reported by all nodes; then, it constructs the likelihood matrix related to the cluster nodes and estimates the location of all events according to the alarmed status and trust index of the nodes around the cluster nodes. Finally, the sink updates the trust index of all nodes according to the fidelity of their information in the previous reporting cycle. The algorithm improves the accuracy of localization and performance of fault tolerance in multiple event source localization. The experiment results show that when the probability of node fault is close to 50%, the algorithm can still accurately determine the number of the events and have better accuracy of localization compared with other algorithms. PMID:22163972

British isles lupus assessment group 2004 index is valid for assessment of disease activity in systemic lupus erythematosus

PubMed Central

Yee, Chee-Seng; Farewell, Vernon; Isenberg, David A; Rahman, Anisur; Teh, Lee-Suan; Griffiths, Bridget; Bruce, Ian N; Ahmad, Yasmeen; Prabu, Athiveeraramapandian; Akil, Mohammed; McHugh, Neil; D'Cruz, David; Khamashta, Munther A; Maddison, Peter; Gordon, Caroline

2007-01-01

Objective To determine the construct and criterion validity of the British Isles Lupus Assessment Group 2004 (BILAG-2004) index for assessing disease activity in systemic lupus erythematosus (SLE). Methods Patients with SLE were recruited into a multicenter cross-sectional study. Data on SLE disease activity (scores on the BILAG-2004 index, Classic BILAG index, and Systemic Lupus Erythematosus Disease Activity Index 2000 [SLEDAI-2K]), investigations, and therapy were collected. Overall BILAG-2004 and overall Classic BILAG scores were determined by the highest score achieved in any of the individual systems in the respective index. Erythrocyte sedimentation rates (ESRs), C3 levels, C4 levels, anti–double-stranded DNA (anti-dsDNA) levels, and SLEDAI-2K scores were used in the analysis of construct validity, and increase in therapy was used as the criterion for active disease in the analysis of criterion validity. Statistical analyses were performed using ordinal logistic regression for construct validity and logistic regression for criterion validity. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Results Of the 369 patients with SLE, 92.7% were women, 59.9% were white, 18.4% were Afro-Caribbean and 18.4% were South Asian. Their mean ± SD age was 41.6 ± 13.2 years and mean disease duration was 8.8 ± 7.7 years. More than 1 assessment was obtained on 88.6% of the patients, and a total of 1,510 assessments were obtained. Increasing overall scores on the BILAG-2004 index were associated with increasing ESRs, decreasing C3 levels, decreasing C4 levels, elevated anti-dsDNA levels, and increasing SLEDAI-2K scores (all P < 0.01). Increase in therapy was observed more frequently in patients with overall BILAG-2004 scores reflecting higher disease activity. Scores indicating active disease (overall BILAG-2004 scores of A and B) were significantly associated with increase in therapy (odds ratio [OR] 19.3, P < 0.01). The BILAG-2004 and Classic BILAG indices had comparable sensitivity, specificity, PPV, and NPV. Conclusion These findings show that the BILAG-2004 index has construct and criterion validity. PMID:18050213

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation.

PubMed

Saatchi, Mahdi; McClure, Mathew C; McKay, Stephanie D; Rolf, Megan M; Kim, JaeWoo; Decker, Jared E; Taxis, Tasia M; Chapple, Richard H; Ramey, Holly R; Northcutt, Sally L; Bauck, Stewart; Woodward, Brent; Dekkers, Jack C M; Fernando, Rohan L; Schnabel, Robert D; Garrick, Dorian J; Taylor, Jeremy F

2011-11-28

Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

PubMed Central

2011-01-01

Background Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Methods Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Results Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. Conclusions These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy. PMID:22122853

Evaluation of diagnostic tools that tertiary teachers can apply to profile their students' conceptions

NASA Astrophysics Data System (ADS)

Schultz, Madeleine; Lawrie, Gwendolyn A.; Bailey, Chantal H.; Bedford, Simon B.; Dargaville, Tim R.; O'Brien, Glennys; Tasker, Roy; Thompson, Christopher D.; Williams, Mark; Wright, Anthony H.

2017-03-01

A multi-institution collaborative team of Australian chemistry education researchers, teaching a total of over 3000 first year chemistry students annually, has explored a tool for diagnosing students' prior conceptions as they enter tertiary chemistry courses. Five core topics were selected and clusters of diagnostic items were assembled linking related concepts in each topic together. An ordered multiple choice assessment strategy was adopted to enable provision of formative feedback to students through combination of the specific distractors that they chose. Concept items were either sourced from existing research instruments or developed by the project team. The outcome is a diagnostic tool consisting of five topic clusters of five concept items that has been delivered in large introductory chemistry classes at five Australian institutions. Statistical analysis of data has enabled exploration of the composition and validity of the instrument including a comparison between delivery of the complete 25 item instrument with subsets of five items, clustered by topic. This analysis revealed that most items retained their validity when delivered in small clusters. Tensions between the assembly, validation and delivery of diagnostic instruments for the purposes of acquiring robust psychometric research data versus their pragmatic use are considered in this study.

Does cognitive performance map to categorical diagnoses of schizophrenia, schizoaffective disorder and bipolar disorder? A discriminant functions analysis.

PubMed

Van Rheenen, Tamsyn E; Bryce, Shayden; Tan, Eric J; Neill, Erica; Gurvich, Caroline; Louise, Stephanie; Rossell, Susan L

2016-03-01

Despite known overlaps in the pattern of cognitive impairments in individuals with bipolar disorder (BD), schizophrenia (SZ) and schizoaffective disorder (SZA), few studies have examined the extent to which cognitive performance validates traditional diagnostic boundaries in these groups. Individuals with SZ (n=49), schizoaffective disorder (n=33) and BD (n=35) completed a battery of cognitive tests measuring the domains of processing speed, immediate memory, semantic memory, learning, working memory, executive function and sustained attention. A discriminant functions analysis revealed a significant function comprising semantic memory, immediate memory and processing speed that maximally separated patients with SZ from those with BD. Initial classification scores on the basis of this function showed modest diagnostic accuracy, owing in part to the misclassification of SZA patients as having SZ. When SZA patients were removed from the model, a second cross-validated classifier yielded slightly improved diagnostic accuracy and a single function solution, of which semantic memory loaded most heavily. A cluster of non-executive cognitive processes appears to have some validity in mapping onto traditional nosological boundaries. However, since semantic memory performance was the primary driver of the discrimination between BD and SZ, it is possible that performance differences between the disorders in this cognitive domain in particular, index separate underlying aetiologies. Copyright © 2015 Elsevier B.V. All rights reserved.

A reliable DNA barcode reference library for the identification of the North European shelf fish fauna.

PubMed

Knebelsberger, Thomas; Landi, Monica; Neumann, Hermann; Kloppmann, Matthias; Sell, Anne F; Campbell, Patrick D; Laakmann, Silke; Raupach, Michael J; Carvalho, Gary R; Costa, Filipe O

2014-09-01

Valid fish species identification is an essential step both for fundamental science and fisheries management. The traditional identification is mainly based on external morphological diagnostic characters, leading to inconsistent results in many cases. Here, we provide a sequence reference library based on mitochondrial cytochrome c oxidase subunit I (COI) for a valid identification of 93 North Atlantic fish species originating from the North Sea and adjacent waters, including many commercially exploited species. Neighbour-joining analysis based on K2P genetic distances formed nonoverlapping clusters for all species with a ≥99% bootstrap support each. Identification was successful for 100% of the species as the minimum genetic distance to the nearest neighbour always exceeded the maximum intraspecific distance. A barcoding gap was apparent for the whole data set. Within-species distances ranged from 0 to 2.35%, while interspecific distances varied between 3.15 and 28.09%. Distances between congeners were on average 51-fold higher than those within species. The validation of the sequence library by applying BOLDs barcode index number (BIN) analysis tool and a ranking system demonstrated high taxonomic reliability of the DNA barcodes for 85% of the investigated fish species. Thus, the sequence library presented here can be confidently used as a benchmark for identification of at least two-thirds of the typical fish species recorded for the North Sea. © 2014 John Wiley & Sons Ltd.

Risk-Based Prioritization Method for the Classification of Groundwater Pollution from Hazardous Waste Landfills.

PubMed

Yang, Yu; Jiang, Yong-Hai; Lian, Xin-Ying; Xi, Bei-Dou; Ma, Zhi-Fei; Xu, Xiang-Jian; An, Da

2016-12-01

Hazardous waste landfill sites are a significant source of groundwater pollution. To ensure that these landfills with a significantly high risk of groundwater contamination are properly managed, a risk-based ranking method related to groundwater contamination is needed. In this research, a risk-based prioritization method for the classification of groundwater pollution from hazardous waste landfills was established. The method encompasses five phases, including risk pre-screening, indicator selection, characterization, classification and, lastly, validation. In the risk ranking index system employed here, 14 indicators involving hazardous waste landfills and migration in the vadose zone as well as aquifer were selected. The boundary of each indicator was determined by K-means cluster analysis and the weight of each indicator was calculated by principal component analysis. These methods were applied to 37 hazardous waste landfills in China. The result showed that the risk for groundwater contamination from hazardous waste landfills could be ranked into three classes from low to high risk. In all, 62.2 % of the hazardous waste landfill sites were classified in the low and medium risk classes. The process simulation method and standardized anomalies were used to validate the result of risk ranking; the results were consistent with the simulated results related to the characteristics of contamination. The risk ranking method was feasible, valid and can provide reference data related to risk management for groundwater contamination at hazardous waste landfill sites.

Supervised group Lasso with applications to microarray data analysis

PubMed Central

Ma, Shuangge; Song, Xiao; Huang, Jian

2007-01-01

Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods. PMID:17316436

Air Combat Training: Good Stick Index Validation. Final Report for Period 3 April 1978-1 April 1979.

ERIC Educational Resources Information Center

Moore, Samuel B.; And Others

A study was conducted to investigate and statistically validate a performance measuring system (the Good Stick Index) in the Tactical Air Command Combat Engagement Simulator I (TAC ACES I) Air Combat Maneuvering (ACM) training program. The study utilized a twelve-week sample of eighty-nine student pilots to statistically validate the Good Stick…

Adaptation and Validation of the Brazilian Version of the Hope Index

ERIC Educational Resources Information Center

Pacico, Juliana Cerentini; Zanon, Cristian; Bastianello, Micheline Roat; Reppold, Caroline Tozzi; Hutz, Claudio Simon

2013-01-01

The objective of this study was to adapt and gather validity evidence for a Brazilian sample version of the Hope Index and to verify if cultural differences would produce different results than those found in the United States. In this study, we present a set of analyses that together comprise a comprehensive validity argument for the use of a…

Clustering Heart Rate Dynamics Is Associated with β-Adrenergic Receptor Polymorphisms: Analysis by Information-Based Similarity Index

PubMed Central

Yang, Albert C.; Tsai, Shih-Jen; Hong, Chen-Jee; Wang, Cynthia; Chen, Tai-Jui; Liou, Ying-Jay; Peng, Chung-Kang

2011-01-01

Background Genetic polymorphisms in the gene encoding the β-adrenergic receptors (β-AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype–phenotype analysis to investigate the association between β-AR gene polymorphisms and heart rate dynamics. Methods A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6±10.8 years, range 19 to 63 years) were recruited and genotyped for three common β-AR polymorphisms: β1-AR Ser49Gly, β2-AR Arg16Gly and β2-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects. Results With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β2-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity. Conclusions We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms. Our results provide evidence that β2-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control. PMID:21573230

A computer-aided differential diagnosis between UIP and NSIP using automated assessment of the extent and distribution of regional disease patterns at HRCT: comparison with the radiologist's decision

NASA Astrophysics Data System (ADS)

Kim, Namkug; Seo, Joon Beom; Park, Sang Ok; Lee, Youngjoo; Lee, Jeongjin

2009-02-01

To evaluate the accuracy of computer aided differential diagnosis (CADD) between usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP) at HRCT in comparison with that of a radiologist's decision. A computerized classification for six local disease patterns (normal, NL; ground-glass opacity, GGO; reticular opacity, RO; honeycombing, HC; emphysema, EM; and consolidation, CON) using texture/shape analyses and a SVM classifier at HRCT was used for pixel-by-pixel labeling on the whole lung area. The mode filter was applied on the results to reduce noise. Area fraction (AF) of each pattern, directional probabilistic density function (pdf) (dPDF: mean, SD, skewness of pdf /3 directions: superior-inferior, anterior-posterior, central-peripheral), regional cluster distribution pattern (RCDP: number, mean, SD of clusters, mean, SD of centroid of clusters) were automatically evaluated. Spatially normalized left and right lungs were evaluated separately. Disease division index (DDI) on every combination of AFs and asymmetric index (AI) between left and right lung ((left-right)/left) were also evaluated. To assess the accuracy of the system, fifty-four HRCT data sets in patients with pathologically diagnosed UIP (n=26) and NSIP (n=28) were used. For a classification procedure, a CADD-SVM classifier with internal parameter optimization, and sequential forward floating feature selection (SFFS) were employed. The accuracy was assessed by a 5-folding cross validation with 20- times repetition. For comparison, two thoracic radiologists reviewed the whole HRCT images without clinical information and diagnose each case either as UIP or NSIP. The accuracies of radiologists' decision were 0.75 and 0.87, respectively. The accuracies of the CADD system using the features of AF, dPDF, AI of dPDF, RDP, AI of RDP, DDI were 0.70, 0.79, 0.77, 0.80, 0.78, 0.81, respectively. The accuracy of optimized CADD using all features after SFFS was 0.91. We developed the CADD system to differentiate between UIP and NSIP using automated assessment of the extent and distribution of regional disease patterns at HRCT.

An efficient 3D R-tree spatial index method for virtual geographic environments

NASA Astrophysics Data System (ADS)

Zhu, Qing; Gong, Jun; Zhang, Yeting

A three-dimensional (3D) spatial index is required for real time applications of integrated organization and management in virtual geographic environments of above ground, underground, indoor and outdoor objects. Being one of the most promising methods, the R-tree spatial index has been paid increasing attention in 3D geospatial database management. Since the existing R-tree methods are usually limited by their weakness of low efficiency, due to the critical overlap of sibling nodes and the uneven size of nodes, this paper introduces the k-means clustering method and employs the 3D overlap volume, 3D coverage volume and the minimum bounding box shape value of nodes as the integrative grouping criteria. A new spatial cluster grouping algorithm and R-tree insertion algorithm is then proposed. Experimental analysis on comparative performance of spatial indexing shows that by the new method the overlap of R-tree sibling nodes is minimized drastically and a balance in the volumes of the nodes is maintained.

[Reliability and validity of the Chinese version on Comprehensive Scores for Financial Toxicity based on the patient-reported outcome measures].

PubMed

Yu, H H; Bi, X; Liu, Y Y

2017-08-10

Objective: To evaluate the reliability and validity of the Chinese version on comprehensive scores for financial toxicity (COST), based on the patient-reported outcome measures. Methods: A total of 118 cancer patients were face-to-face interviewed by well-trained investigators. Cronbach's α and Pearson correlation coefficient were used to evaluate reliability. Content validity index (CVI) and exploratory factor analysis (EFA) were used to evaluate the content validity and construct validity, respectively. Results: The Cronbach's α coefficient appeared as 0.889 for the whole questionnaire, with the results of test-retest were between 0.77 and 0.98. Scale-content validity index (S-CVI) appeared as 0.82, with item-content validity index (I-CVI) between 0.83 and 1.00. Two components were extracted from the Exploratory factor analysis, with cumulative rate as 68.04% and loading>0.60 on every item. Conclusion: The Chinese version of COST scale showed high reliability and good validity, thus can be applied to assess the financial situation in cancer patients.

Internet Gamblers Differ on Social Variables: A Latent Class Analysis.

PubMed

Khazaal, Yasser; Chatton, Anne; Achab, Sophia; Monney, Gregoire; Thorens, Gabriel; Dufour, Magali; Zullino, Daniele; Rothen, Stephane

2017-09-01

Online gambling has gained popularity in the last decade, leading to an important shift in how consumers engage in gambling and in the factors related to problem gambling and prevention. Indebtedness and loneliness have previously been associated with problem gambling. The current study aimed to characterize online gamblers in relation to indebtedness, loneliness, and several in-game social behaviors. The data set was obtained from 584 Internet gamblers recruited online through gambling websites and forums. Of these gamblers, 372 participants completed all study assessments and were included in the analyses. Questionnaires included those on sociodemographics and social variables (indebtedness, loneliness, in-game social behaviors), as well as the Gambling Motives Questionnaire, Gambling Related Cognitions Scale, Internet Addiction Test, Problem Gambling Severity Index, Short Depression-Happiness Scale, and UPPS-P Impulsive Behavior Scale. Social variables were explored with a latent class model. The clusters obtained were compared for psychological measures and three clusters were found: lonely indebted gamblers (cluster 1: 6.5%), not lonely not indebted gamblers (cluster 2: 75.4%), and not lonely indebted gamblers (cluster 3: 18%). Participants in clusters 1 and 3 (particularly in cluster 1) were at higher risk of problem gambling than were those in cluster 2. The three groups differed on most assessed variables, including the Problem Gambling Severity Index, the Short Depression-Happiness Scale, and the UPPS-P subscales (except the sensation seeking subscore). Results highlight significant between-group differences, suggesting that Internet gamblers are not a homogeneous group. Specific intervention strategies could be implemented for groups at risk.

Performance Assessment of Kernel Density Clustering for Gene Expression Profile Data

PubMed Central

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

2003-01-01

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

Prioritizing subwatersheds for stormwater pollution to Wachusett Reservoir.

PubMed

Cho, Kyung Hwa; Park, Mi-Hyun

2013-02-01

The Wachusett Reservoir is a primary drinking water resource for the greater Boston, Massachusetts, area. With a drainage area of 280 km2, the watershed has been gradually urbanized with increased residential, commercial, industrial, and transportation land uses. Increased impervious surface area as a result of urbanization results in increased runoff volume and pollutant loads to the reservoir. This study estimated annual stormwater pollutant mass loads in the watershed to prioritize sub-basins and to identify areas susceptible to stormwater pollution. Catchment Prioritization Index (CPI) was calculated using annual stormwater pollutant mass loads, which were further used to identify clustered hotspots through application of the Getis-Ord Gi* statistic. Validation with observed data showed higher levels of fecal coliform bacteria loading from identified hotspots. This approach will be useful to prioritize sub-basins for future (1) development of stormwater monitoring strategies and (2) best management practices (BMPs) in the watershed.

Power-Law Template for IR Point Source Clustering

NASA Technical Reports Server (NTRS)

Addison, Graeme E.; Dunkley, Joanna; Hajian, Amir; Viero, Marco; Bond, J. Richard; Das, Sudeep; Devlin, Mark; Halpern, Mark; Hincks, Adam; Hlozek, Renee;

Neurodevelopmental disorders: cluster 2 of the proposed meta-structure for DSM-V and ICD-11.

PubMed

Andrews, G; Pine, D S; Hobbs, M J; Anderson, T M; Sunderland, M

2009-12-01

DSM-IV and ICD-10 are atheoretical and largely descriptive. Although this achieves good reliability, the validity of diagnoses can be increased by an understanding of risk factors and other clinical features. In an effort to group mental disorders on this basis, five clusters have been proposed. We now consider the second cluster, namely neurodevelopmental disorders. We reviewed the literature in relation to 11 validating criteria proposed by a DSM-V Task Force Study Group. This cluster reflects disorders of neurodevelopment rather than a 'childhood' disorders cluster. It comprises disorders subcategorized in DSM-IV and ICD-10 as Mental Retardation; Learning, Motor, and Communication Disorders; and Pervasive Developmental Disorders. Although these disorders seem to be heterogeneous, they share similarities on some risk and clinical factors. There is evidence of a neurodevelopmental genetic phenotype, the disorders have an early emerging and continuing course, and all have salient cognitive symptoms. Within-cluster co-morbidity also supports grouping these disorders together. Other childhood disorders currently listed in DSM-IV share similarities with the Externalizing and Emotional clusters. These include Conduct Disorder, Attention Deficit Hyperactivity Disorder and Separation Anxiety Disorder. The Tic, Eating/Feeding and Elimination disorders, and Selective Mutisms were allocated to the 'Not Yet Assigned' group. Neurodevelopmental disorders meet some of the salient criteria proposed by the American Psychiatric Association (APA) to suggest a classification cluster.

Validating clustering of molecular dynamics simulations using polymer models.

PubMed

Phillips, Joshua L; Colvin, Michael E; Newsam, Shawn

2011-11-14

Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.

Validating clustering of molecular dynamics simulations using polymer models

PubMed Central

2011-01-01

Background Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers. PMID:22082218

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

PubMed

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

2016-04-01

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

Unsupervised Learning and Pattern Recognition of Biological Data Structures with Density Functional Theory and Machine Learning.

PubMed

Chen, Chien-Chang; Juan, Hung-Hui; Tsai, Meng-Yuan; Lu, Henry Horng-Shing

2018-01-11

By introducing the methods of machine learning into the density functional theory, we made a detour for the construction of the most probable density function, which can be estimated by learning relevant features from the system of interest. Using the properties of universal functional, the vital core of density functional theory, the most probable cluster numbers and the corresponding cluster boundaries in a studying system can be simultaneously and automatically determined and the plausibility is erected on the Hohenberg-Kohn theorems. For the method validation and pragmatic applications, interdisciplinary problems from physical to biological systems were enumerated. The amalgamation of uncharged atomic clusters validated the unsupervised searching process of the cluster numbers and the corresponding cluster boundaries were exhibited likewise. High accurate clustering results of the Fisher's iris dataset showed the feasibility and the flexibility of the proposed scheme. Brain tumor detections from low-dimensional magnetic resonance imaging datasets and segmentations of high-dimensional neural network imageries in the Brainbow system were also used to inspect the method practicality. The experimental results exhibit the successful connection between the physical theory and the machine learning methods and will benefit the clinical diagnoses.

LACE+ index: extension of a validated index to predict early death or urgent readmission after hospital discharge using administrative data

PubMed Central

van Walraven, Carl; Wong, Jenna; Forster, Alan J

2012-01-01

Background Death or urgent readmission after hospital discharge is a common adverse event that can be used to compare outcomes of care between institutions. To accurately adjust for risk and to allow for interhospital comparisons of readmission rates, we used administrative data to derive and internally validate an extension of the LACE index, a previously validated index for 30-day death or urgent readmission. Methods We randomly selected 500 000 medical and surgical patients discharged to the community from any Ontario hospital between 1 April 2003 and 31 March 2009. We derived a logistic regression model on 250 000 randomly selected patients from this group and modified the final model into an index scoring system, the LACE+ index. We internally validated the LACE+ index using data from the remaining 250 000 patients and compared its performance with that of the original LACE index. Results Within 30 days of discharge to the community, 33 825 (6.8%) of the patients had died or had been urgently readmitted. In addition to the variables included in the LACE index (length of stay in hospital [L], acuity of admission [A], comorbidity [C] and emergency department utilization in the 6 months before admission [E]), the LACE+ index incorporated patient age and sex, teaching status of the discharge hospital, acute diagnoses and procedures performed during the index admission, number of days on alternative level of care during the index admission, and number of elective and urgent admissions to hospital in the year before the index admission. The LACE+ index was highly discriminative (C statistic 0.771, 95% confidence interval 0.767–0.775), was well calibrated across most of its range of scores and had a model performance that exceeded that of the LACE index. Interpretation The LACE+ index can be used to predict the risk of postdischarge death or urgent readmission on the basis of administrative data for the Ontario population. Its performance exceeds that of the LACE index, and it allows analysts to accurately estimate the risk of important postdischarge outcomes. PMID:23696773

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

Soffientini, Chiara Dolores, E-mail: chiaradolores.soffientini@polimi.it; Baselli, Giuseppe; De Bernardi, Elisabetta

Purpose: Quantitative {sup 18}F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level. Methods: An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previousmore » analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD). Results: The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was demonstrated. The inclusion of the spatial prior improved segmentation accuracy only for lesions surrounded by heterogeneous background: in the relevant simulation subset, the median VE significantly decreased from 13% to 7%. Results on clinical data were found in accordance with simulations, with absolute VE <7%, Dice >0.85, CE <0.30, and HD <0.81. Conclusions: The sole introduction of constraints based on background modeling outperformed standard GMM and the other tested algorithms. Insertion of a spatial prior improved the accuracy for realistic cases of objects in heterogeneous backgrounds. Moreover, robustness against initialization supports the applicability in a clinical setting. In conclusion, application-driven constraints can generally improve the capabilities of GMM and statistical clustering algorithms.« less

Patterns of Dysmorphic Features in Schizophrenia

PubMed Central

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

2011-01-01

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

Measurement issues in research on social support and health.

PubMed Central

Dean, K; Holst, E; Kreiner, S; Schoenborn, C; Wilson, R

1994-01-01

STUDY OBJECTIVE--The aims were: (1) to identify methodological problems that may explain the inconsistencies and contradictions in the research evidence on social support and health, and (2) to validate a frequently used measure of social support in order to determine whether or not it could be used in multivariate analyses of population data in research on social support and health. DESIGN AND METHODS--Secondary analysis of data collected in a cross sectional survey of a multistage cluster sample of the population of the United States, designed to study relationships in behavioural, social support and health variables. Statistical models based on item response theory and graph theory were used to validate the measure of social support to be used in subsequent analyses. PARTICIPANTS--Data on 1755 men and women aged 20 to 64 years were available for the scale validation. RESULTS--Massive evidence of item bias was found for all items of a group membership subscale. The most serious problems were found in relationship to an item measuring membership in work related groups. Using that item in the social network scale in multivariate analyses would distort findings on the statistical effects of education, employment status, and household income. Evidence of item bias was also found for a sociability subscale. When marital status was included to create what is called an intimate contacts subscale, the confounding grew worse. CONCLUSIONS--The composite measure of social network is not valid and would seriously distort the findings of analyses attempting to study relationships between the index and other variables. The findings show that valid measurement is a methodological issue that must be addressed in scientific research on population health. PMID:8189179

Newspaper coverage of suicide and initiation of suicide clusters in teenagers in the USA, 1988-96: a retrospective, population-based, case-control study.

PubMed

Gould, Madelyn S; Kleinman, Marjorie H; Lake, Alison M; Forman, Judith; Midle, Jennifer Bassett

2014-06-01

Public health and clinical efforts to prevent suicide clusters are seriously hampered by the unanswered question of why such outbreaks occur. We aimed to establish whether an environmental factor-newspaper reports of suicide-has a role in the emergence of suicide clusters. In this retrospective, population-based, case-control study, we identified suicide clusters in young people aged 13-20 years in the USA from 1988 to 1996 (preceding the advent of social media) using the time-space Scan statistic. For each cluster community, we selected two matched non-cluster control communities in which suicides of similarly aged youth occurred, from non-contiguous counties within the same state as the cluster. We examined newspapers within each cluster community for stories about suicide published in the days between the first and second suicides in the cluster. In non-cluster communities, we examined a matched length of time after the matched control suicide. We used a content-analysis procedure to code the characteristics of each story and compared newspaper stories about suicide published in case and control communities with mixed-effect regression analyses. We identified 53 suicide clusters, of which 48 were included in the media review. For one cluster we could identify only one appropriate control; therefore, 95 matched control communities were included. The mean number of news stories about suicidal individuals published after an index cluster suicide (7·42 [SD 10·02]) was significantly greater than the mean number of suicide stories published after a non-cluster suicide (5·14 [6.00]; p<0·0001). Several story characteristics, including front-page placement, headlines containing the word suicide or a description of the method used, and detailed descriptions of the suicidal individual and act, appeared more often in stories published after the index cluster suicides than after non-cluster suicides. Our identification of an association between newspaper reports about suicide (including specific story characteristics) and the initiation of teenage suicide clusters should provide an empirical basis to support efforts by mental health professionals, community officials, and the media to work together to identify and prevent the onset of suicide clusters. US National Institute of Mental Health and American Foundation for Suicide Prevention. Copyright © 2014 Elsevier Ltd. All rights reserved.

Reactivity Indexes of Fullerene and Bismullene Mixed Clusters: How the Intruders Modify the Properties.

PubMed

Martínez, Ana

2016-11-03

In this investigation, the feasibility of functionalizing fullerene and bismullene with Bi and C as intruders is theoretically explored. The systems analyzed are C 60-x Bi x (with x = 0-10, fullerene-like) and Bi 60-y C y (with y = 0-10, bismullene-like). Optimized geometries, reactivity indexes, and highest occupied molecular orbital to lowest unoccupied molecular orbital (HOMO-LUMO) gaps (for analyzing the potential application of these molecules as materials for solar cells) are reported. The most stable structures of bismullene-like systems have cage geometries. The most stable fullerene-like geometries resemble a cup with bismuth atoms at the edge of the bowl. The presence of intruders increases the electron acceptor power and decreases the electron donor power in most cases. HOMO-LUMO gaps indicate that bismullene-like clusters represent better candidates for building solar cells than fullerene-like clusters. This information could be useful for future experiments.

Pneumonic Plague Cluster, Uganda, 2004

PubMed Central

Asiki, Gershim; Anywaine, Zaccheus; Yockey, Brook; Schriefer, Martin E.; Aleti, Philliam; Ogen-Odoi, Asaph; Staples, J. Erin; Sexton, Christopher; Bearden, Scott W.; Kool, Jacob L.

2006-01-01

The public and clinicians have long-held beliefs that pneumonic plague is highly contagious; inappropriate alarm and panic have occurred during outbreaks. We investigated communicability in a naturally occurring pneumonic plague cluster. We defined a probable pneumonic plague case as an acute-onset respiratory illness with bloody sputum during December 2004 in Kango Subcounty, Uganda. A definite case was a probable case with laboratory evidence of Yersinia pestis infection. The cluster (1 definite and 3 probable cases) consisted of 2 concurrent index patient–caregiver pairs. Direct fluorescent antibody microscopy and polymerase chain reaction testing on the only surviving patient's sputum verified plague infection. Both index patients transmitted pneumonic plague to only 1 caregiver each, despite 23 additional untreated close contacts (attack rate 8%). Person-to-person transmission was compatible with transmission by respiratory droplets, rather than aerosols, and only a few close contacts, all within droplet range, became ill. PMID:16704785

A Cluster Analysis of Personality Style in Adults with ADHD

ERIC Educational Resources Information Center

Robin, Arthur L.; Tzelepis, Angela; Bedway, Marquita

2008-01-01

Objective: The purpose of this study was to use hierarchical linear cluster analysis to examine the normative personality styles of adults with ADHD. Method: A total of 311 adults with ADHD completed the Millon Index of Personality Styles, which consists of 24 scales assessing motivating aims, cognitive modes, and interpersonal behaviors. Results:…

The Star Schema Benchmark and Augmented Fact Table Indexing

NASA Astrophysics Data System (ADS)

O'Neil, Patrick; O'Neil, Elizabeth; Chen, Xuedong; Revilak, Stephen

We provide a benchmark measuring star schema queries retrieving data from a fact table with Where clause column restrictions on dimension tables. Clustering is crucial to performance with modern disk technology, since retrievals with filter factors down to 0.0005 are now performed most efficiently by sequential table search rather than by indexed access. DB2’s Multi-Dimensional Clustering (MDC) provides methods to "dice" the fact table along a number of orthogonal "dimensions", but only when these dimensions are columns in the fact table. The diced cells cluster fact rows on several of these "dimensions" at once so queries restricting several such columns can access crucially localized data, with much faster query response. Unfortunately, columns of dimension tables of a star schema are not usually represented in the fact table. In this paper, we show a simple way to adjoin physical copies of dimension columns to the fact table, dicing data to effectively cluster query retrieval, and explain how such dicing can be achieved on database products other than DB2. We provide benchmark measurements to show successful use of this methodology on three commercial database products.

Hirsch Index Value and Variability Related to General Surgery in a UK Deanery.

PubMed

Abdelrahman, Tarig; Brown, Josephine; Wheat, Jenny; Thomas, Charlotte; Lewis, Wyn

2016-01-01

The Hirsch Index (h-index) is often used to assess research impact, and on average a social science senior lecturer will have an h-index of 2.29, yet its validity within the context of UK General Surgery (GS) is unknown. The aim of this study was to calculate the h-indices of a cohort of GS consultants in a UK Deanery to assess its relative validity. Individual h-indices and total publication (TP) counts were obtained for GS consultants via the Scopus and Web of Science (WoS) Internet search engines. Assessment of construct validity and reliability of these 2 measures of the h-index was undertaken. All hospitals in a single UK National Health Service Deanery were included (14 general hospitals). All 136 GS consultants from the Deanery were included. Median h-index (Scopus) was 5 (0-52) and TP 15 (0-369), and strong correlation was found between h-index and TP (ρ = 0.932, p < 0.001), with the intraclass correlation between Scopus and WoS h-index also significant (intraclass correlation coefficient = 0.973 [95% CI: 0.962-0.981], p < 0.001). Academic GS consultants had higher h-indices than nonacademic University Hospital and District General Hospital consultants (Scopus 12 vs 7 vs 4 [p < 0.001] and WoS 10.5 vs 7 vs 4 [p < 0.001]). h-Index was >2.29 in 57.4% of consultants. No subspecialty differences were apparent in median h-indices (p = 0.792) and TP (p = 0.903). h-Index is a valid GS research productivity metric with over half of consultants performing at levels equivalent to social science Senior Lecturers. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Validity and reproducibility of HOMA-IR, 1/HOMA-IR, QUICKI and McAuley's indices in patients with hypertension and type II diabetes.

PubMed

Sarafidis, P A; Lasaridis, A N; Nilsson, P M; Pikilidou, M I; Stafilas, P C; Kanaki, A; Kazakos, K; Yovos, J; Bakris, G L

2007-09-01

The aim of this study was to evaluate the validity and reliability of homeostasis model assessment-insulin resistance (HOMA-IR) index, its reciprocal (1/HOMA-IR), quantitative insulin sensitivity check index (QUICKI) and McAuley's index in hypertensive diabetic patients. In 78 patients with hypertension and type II diabetes glucose, insulin and triglyceride levels were determined after a 12-h fast to calculate these indices, and insulin sensitivity (IS) was measured with the hyperinsulinemic euglycemic clamp technique. Two weeks later, subjects had again their glucose, insulin and triglycerides measured. Simple and multiple linear regression analysis were applied to assess the validity of these indices compared to clamp IS and coefficients of variation between the two visits were estimated to assess their reproducibility. HOMA-IR index was strongly and inversely correlated with the basic IS clamp index, the M-value (r=-0.572, P<0.001), M-value normalized with subjects' body weight or fat-free mass and every other clamp-derived index. 1/HOMA-IR and QUICKI indices were positively correlated with the M-value (r=0.342, P<0.05 and r=0.456, P<0.01, respectively) and the rest clamp indices. McAuley's index generally presented less strong correlations (r=0.317, P<0.05 with M-value). In multivariate analysis, HOMA-IR was the best fit of clamp-derived IS. Coefficients of variation between the two visits were 23.5% for HOMA-IR, 19.2% for 1/HOMA-IR, 7.8% for QUICKI and 15.1% for McAuley's index. In conclusion, HOMA-IR, 1/HOMA-IR and QUICKI are valid estimates of clamp-derived IS in patients with hypertension and type II diabetes, whereas the validity of McAuley's index needs further evaluation. QUICKI displayed better reproducibility than the other indices.

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.

Ant colony algorithm for clustering in portfolio optimization

NASA Astrophysics Data System (ADS)

Subekti, R.; Sari, E. R.; Kusumawati, R.

2018-03-01

This research aims to describe portfolio optimization using clustering methods with ant colony approach. Two stock portfolios of LQ45 Indonesia is proposed based on the cluster results obtained from ant colony optimization (ACO). The first portfolio consists of assets with ant colony displacement opportunities beyond the defined probability limits of the researcher, where the weight of each asset is determined by mean-variance method. The second portfolio consists of two assets with the assumption that each asset is a cluster formed from ACO. The first portfolio has a better performance compared to the second portfolio seen from the Sharpe index.

A multiple-feature and multiple-kernel scene segmentation algorithm for humanoid robot.

PubMed

Liu, Zhi; Xu, Shuqiong; Zhang, Yun; Chen, Chun Lung Philip

2014-11-01

This technical correspondence presents a multiple-feature and multiple-kernel support vector machine (MFMK-SVM) methodology to achieve a more reliable and robust segmentation performance for humanoid robot. The pixel wise intensity, gradient, and C1 SMF features are extracted via the local homogeneity model and Gabor filter, which would be used as inputs of MFMK-SVM model. It may provide multiple features of the samples for easier implementation and efficient computation of MFMK-SVM model. A new clustering method, which is called feature validity-interval type-2 fuzzy C-means (FV-IT2FCM) clustering algorithm, is proposed by integrating a type-2 fuzzy criterion in the clustering optimization process to improve the robustness and reliability of clustering results by the iterative optimization. Furthermore, the clustering validity is employed to select the training samples for the learning of the MFMK-SVM model. The MFMK-SVM scene segmentation method is able to fully take advantage of the multiple features of scene image and the ability of multiple kernels. Experiments on the BSDS dataset and real natural scene images demonstrate the superior performance of our proposed method.

Exploring relationships between Dairy Herd Improvement monitors of performance and the Transition Cow Index in Wisconsin dairy herds.

PubMed

Schultz, K K; Bennett, T B; Nordlund, K V; Döpfer, D; Cook, N B

2016-09-01

Transition cow management has been tracked via the Transition Cow Index (TCI; AgSource Cooperative Services, Verona, WI) since 2006. Transition Cow Index was developed to measure the difference between actual and predicted milk yield at first test day to evaluate the relative success of the transition period program. This project aimed to assess TCI in relation to all commonly used Dairy Herd Improvement (DHI) metrics available through AgSource Cooperative Services. Regression analysis was used to isolate variables that were relevant to TCI, and then principal components analysis and network analysis were used to determine the relative strength and relatedness among variables. Finally, cluster analysis was used to segregate herds based on similarity of relevant variables. The DHI data were obtained from 2,131 Wisconsin dairy herds with test-day mean ≥30 cows, which were tested ≥10 times throughout the 2014 calendar year. The original list of 940 DHI variables was reduced through expert-driven selection and regression analysis to 23 variables. The K-means cluster analysis produced 5 distinct clusters. Descriptive statistics were calculated for the 23 variables per cluster grouping. Using principal components analysis, cluster analysis, and network analysis, 4 parameters were isolated as most relevant to TCI; these were energy-corrected milk, 3 measures of intramammary infection (dry cow cure rate, linear somatic cell count score in primiparous cows, and new infection rate), peak ratio, and days in milk at peak milk production. These variables together with cow and newborn calf survival measures form a group of metrics that can be used to assist in the evaluation of overall transition period performance. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Predictors of fibromyalgia: a population-based twin cohort study.

PubMed

Markkula, Ritva A; Kalso, Eija A; Kaprio, Jaakko A

2016-01-15

Fibromyalgia (FM) is a pain syndrome, the mechanisms and predictors of which are still unclear. We have earlier validated a set of FM-symptom questions for detecting possible FM in an epidemiological survey and thereby identified a cluster with "possible FM". This study explores prospectively predictors for membership of that FM-symptom cluster. A population-based sample of 8343 subjects of the older Finnish Twin Cohort replied to health questionnaires in 1975, 1981, and 1990. Their answers to the set of FM-symptom questions in 1990 classified them in three latent classes (LC): LC1 with no or few symptoms, LC2 with some symptoms, and LC3 with many FM symptoms. We analysed putative predictors for these symptom classes using baseline (1975 and 1981) data on regional pain, headache, migraine, sleeping, body mass index (BMI), physical activity, smoking, and zygosity, adjusted for age, gender, and education. Those with a high likelihood of having fibromyalgia at baseline were excluded from the analysis. In the final multivariate regression model, regional pain, sleeping problems, and overweight were all predictors for membership in the class with many FM symptoms. The strongest non-genetic predictor was frequent headache (OR 8.6, CI 95% 3.8-19.2), followed by persistent back pain (OR 4.7, CI 95% 3.3-6.7) and persistent neck pain (OR 3.3, CI 95% 1.8-6.0). Regional pain, frequent headache, and persistent back or neck pain, sleeping problems, and overweight are predictors for having a cluster of symptoms consistent with fibromyalgia.

Internal validation of the prognostic index for spine metastasis (PRISM) for stratifying survival in patients treated with spinal stereotactic radiosurgery.

PubMed

Jensen, Garrett; Tang, Chad; Hess, Kenneth R; Bishop, Andrew J; Pan, Hubert Y; Li, Jing; Yang, James N; Tannir, Nizar M; Amini, Behrang; Tatsui, Claudio; Rhines, Laurence; Brown, Paul D; Ghia, Amol J

2017-01-01

We sought to validate the Prognostic Index for Spinal Metastases (PRISM), a scoring system that stratifies patients into subgroups by overall survival.Methods and materials: The PRISM was previously created from multivariate Cox regression with patients enrolled in prospective single institution trials of stereotactic spine radiosurgery (SSRS) for spinal metastasis. We assess model calibration and discrimination within a validation cohort of patients treated off-trial with SSRS for metastatic disease at the same institution. The training and validation cohorts consisted of 205 and 249 patients respectively. Similar survival trends were shown in the 4 PRISM. Survival was significantly different between PRISM subgroups (P<0.0001). C-index for the validation cohort was 0.68 after stratification into subgroups. We internally validated the PRISM with patients treated off-protocol, demonstrating that it can distinguish subgroups by survival, which will be useful for individualizing treatment of spinal metastases and stratifying patients for clinical trials.

Development and validation of a prognostic index for 4-year mortality in older adults.

PubMed

Lee, Sei J; Lindquist, Karla; Segal, Mark R; Covinsky, Kenneth E

2006-02-15

Both comorbid conditions and functional measures predict mortality in older adults, but few prognostic indexes combine both classes of predictors. Combining easily obtained measures into an accurate predictive model could be useful to clinicians advising patients, as well as policy makers and epidemiologists interested in risk adjustment. To develop and validate a prognostic index for 4-year mortality using information that can be obtained from patient report. Using the 1998 wave of the Health and Retirement Study (HRS), a population-based study of community-dwelling US adults older than 50 years, we developed the prognostic index from 11,701 individuals and validated the index with 8009. Individuals were asked about their demographic characteristics, whether they had specific diseases, and whether they had difficulty with a series of functional measures. We identified variables independently associated with mortality and weighted the variables to create a risk index. Death by December 31, 2002. The overall response rate was 81%. During the 4-year follow-up, there were 1361 deaths (12%) in the development cohort and 1072 deaths (13%) in the validation cohort. Twelve independent predictors of mortality were identified: 2 demographic variables (age: 60-64 years, 1 point; 65-69 years, 2 points; 70-74 years, 3 points; 75-79 years, 4 points; 80-84 years, 5 points, >85 years, 7 points and male sex, 2 points), 6 comorbid conditions (diabetes, 1 point; cancer, 2 points; lung disease, 2 points; heart failure, 2 points; current tobacco use, 2 points; and body mass index <25, 1 point), and difficulty with 4 functional variables (bathing, 2 points; walking several blocks, 2 points; managing money, 2 points, and pushing large objects, 1 point. Scores on the risk index were strongly associated with 4-year mortality in the validation cohort, with 0 to 5 points predicting a less than 4% risk, 6 to 9 points predicting a 15% risk, 10 to 13 points predicting a 42% risk, and 14 or more points predicting a 64% risk. The risk index showed excellent discrimination with a cstatistic of 0.84 in the development cohort and 0.82 in the validation cohort. This prognostic index, incorporating age, sex, self-reported comorbid conditions, and functional measures, accurately stratifies community-dwelling older adults into groups at varying risk of mortality.

Evaluation of the psychometric properties of the main meal quality index when applied in the UK population.

PubMed

Gorgulho, B M; Pot, G K; Marchioni, D M

2017-05-01

The aim of this study was to evaluate the validity and reliability of the Main Meal Quality Index when applied on the UK population. The indicator was developed to assess meal quality in different populations, and is composed of 10 components: fruit, vegetables (excluding potatoes), ratio of animal protein to total protein, fiber, carbohydrate, total fat, saturated fat, processed meat, sugary beverages and desserts, and energy density, resulting in a score range of 0-100 points. The performance of the indicator was measured using strategies for assessing content validity, construct validity, discriminant validity and reliability, including principal component analysis, linear regression models and Cronbach's alpha. The indicator presented good reliability. The Main Meal Quality Index has been shown to be valid for use as an instrument to evaluate, monitor and compare the quality of meals consumed by adults in the United Kingdom.

Dark Energy Survey Year 1 Results: Weak Lensing Mass Calibration of redMaPPer Galaxy Clusters

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

McClintock, T.; et al.

We constrain the mass--richness scaling relation of redMaPPer galaxy clusters identified in the Dark Energy Survey Year 1 data using weak gravitational lensing. We split clusters intomore » $$4\\times3$$ bins of richness $$\\lambda$$ and redshift $z$ for $$\\lambda\\geq20$$ and $$0.2 \\leq z \\leq 0.65$$ and measure the mean masses of these bins using their stacked weak lensing signal. By modeling the scaling relation as $$\\langle M_{\\rm 200m}|\\lambda,z\\rangle = M_0 (\\lambda/40)^F ((1+z)/1.35)^G$$, we constrain the normalization of the scaling relation at the 5.0 per cent level as $$M_0 = [3.081 \\pm 0.075 ({\\rm stat}) \\pm 0.133 ({\\rm sys})] \\cdot 10^{14}\\ {\\rm M}_\\odot$$ at $$\\lambda=40$$ and $z=0.35$. The richness scaling index is constrained to be $$F=1.356 \\pm 0.051\\ ({\\rm stat})\\pm 0.008\\ ({\\rm sys})$$ and the redshift scaling index $$G=-0.30\\pm 0.30\\ ({\\rm stat})\\pm 0.06\\ ({\\rm sys})$$. These are the tightest measurements of the normalization and richness scaling index made to date. We use a semi-analytic covariance matrix to characterize the statistical errors in the recovered weak lensing profiles. Our analysis accounts for the following sources of systematic error: shear and photometric redshift errors, cluster miscentering, cluster member dilution of the source sample, systematic uncertainties in the modeling of the halo--mass correlation function, halo triaxiality, and projection effects. We discuss prospects for reducing this systematic error budget, which dominates the uncertainty on $$M_0$$. Our result is in excellent agreement with, but has significantly smaller uncertainties than, previous measurements in the literature, and augurs well for the power of the DES cluster survey as a tool for precision cosmology and upcoming galaxy surveys such as LSST, Euclid and WFIRST.« less

Integrated K-band spectra of old and intermediate-age globular clusters in the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Lyubenova, M.; Kuntschner, H.; Rejkuba, M.; Silva, D. R.; Kissler-Patig, M.; Tacconi-Garman, L. E.; Larsen, S. S.

2010-02-01

Current stellar population models have arguably the largest uncertainties in the near-IR wavelength range, partly due to a lack of large and well calibrated empirical spectral libraries. In this paper we present a project whose aim it is to provide the first library of luminosity weighted integrated near-IR spectra of globular clusters to be used to test the current stellar population models and serve as calibrators for future ones. Our pilot study presents spatially integrated K-band spectra of three old (≥10 Gyr) and metal poor ([Fe/H] ~ -1.4), and three intermediate age (1-2 Gyr) and more metal rich ([Fe/H] ~ - 0.4) globular clusters in the LMC. We measured the line strengths of the Na I, Ca I and 12CO (2-0) absorption features. The Na I index decreases with increasing age and decreasing metallicity of the clusters. The DCO index, used to measure the 12CO (2-0) line strength, is significantly reduced by the presence of carbon-rich TP-AGB stars in the globular clusters with age ~1 Gyr. This is in contradiction to the predictions of the stellar population models of Maraston (2005, MNRAS, 362, 799). We find that this disagreement is due to the different CO absorption strength of carbon-rich Milky Way TP-AGB stars used in the models and the LMC carbon stars in our sample. For globular clusters with age ≥ 2 Gyr we find DCO index measurements consistent with the model predictions. Based on observation collected at the ESO Paranal La Silla Observatory, Chile, Prog. ID 078.B-0205.Spectra in FITS format are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/510/A19

A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method.

PubMed

Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol

2007-11-27

A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries.

A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method

PubMed Central

Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol

2007-01-01

Background A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Results Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Conclusion Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries. PMID:18047705

Why so GLUMM? Detecting depression clusters through graphing lifestyle-environs using machine-learning methods (GLUMM).

PubMed

Dipnall, J F; Pasco, J A; Berk, M; Williams, L J; Dodd, S; Jacka, F N; Meyer, D

2017-01-01

Key lifestyle-environ risk factors are operative for depression, but it is unclear how risk factors cluster. Machine-learning (ML) algorithms exist that learn, extract, identify and map underlying patterns to identify groupings of depressed individuals without constraints. The aim of this research was to use a large epidemiological study to identify and characterise depression clusters through "Graphing lifestyle-environs using machine-learning methods" (GLUMM). Two ML algorithms were implemented: unsupervised Self-organised mapping (SOM) to create GLUMM clusters and a supervised boosted regression algorithm to describe clusters. Ninety-six "lifestyle-environ" variables were used from the National health and nutrition examination study (2009-2010). Multivariate logistic regression validated clusters and controlled for possible sociodemographic confounders. The SOM identified two GLUMM cluster solutions. These solutions contained one dominant depressed cluster (GLUMM5-1, GLUMM7-1). Equal proportions of members in each cluster rated as highly depressed (17%). Alcohol consumption and demographics validated clusters. Boosted regression identified GLUMM5-1 as more informative than GLUMM7-1. Members were more likely to: have problems sleeping; unhealthy eating; ≤2 years in their home; an old home; perceive themselves underweight; exposed to work fumes; experienced sex at ≤14 years; not perform moderate recreational activities. A positive relationship between GLUMM5-1 (OR: 7.50, P<0.001) and GLUMM7-1 (OR: 7.88, P<0.001) with depression was found, with significant interactions with those married/living with partner (P=0.001). Using ML based GLUMM to form ordered depressive clusters from multitudinous lifestyle-environ variables enabled a deeper exploration of the heterogeneous data to uncover better understandings into relationships between the complex mental health factors. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Shared and Distinct Rupture Discriminants of Small and Large Intracranial Aneurysms.

PubMed

Varble, Nicole; Tutino, Vincent M; Yu, Jihnhee; Sonig, Ashish; Siddiqui, Adnan H; Davies, Jason M; Meng, Hui

2018-04-01

Many ruptured intracranial aneurysms (IAs) are small. Clinical presentations suggest that small and large IAs could have different phenotypes. It is unknown if small and large IAs have different characteristics that discriminate rupture. We analyzed morphological, hemodynamic, and clinical parameters of 413 retrospectively collected IAs (training cohort; 102 ruptured IAs). Hierarchal cluster analysis was performed to determine a size cutoff to dichotomize the IA population into small and large IAs. We applied multivariate logistic regression to build rupture discrimination models for small IAs, large IAs, and an aggregation of all IAs. We validated the ability of these 3 models to predict rupture status in a second, independently collected cohort of 129 IAs (testing cohort; 14 ruptured IAs). Hierarchal cluster analysis in the training cohort confirmed that small and large IAs are best separated at 5 mm based on morphological and hemodynamic features (area under the curve=0.81). For small IAs (<5 mm), the resulting rupture discrimination model included undulation index, oscillatory shear index, previous subarachnoid hemorrhage, and absence of multiple IAs (area under the curve=0.84; 95% confidence interval, 0.78-0.88), whereas for large IAs (≥5 mm), the model included undulation index, low wall shear stress, previous subarachnoid hemorrhage, and IA location (area under the curve=0.87; 95% confidence interval, 0.82-0.93). The model for the aggregated training cohort retained all the parameters in the size-dichotomized models. Results in the testing cohort showed that the size-dichotomized rupture discrimination model had higher sensitivity (64% versus 29%) and accuracy (77% versus 74%), marginally higher area under the curve (0.75; 95% confidence interval, 0.61-0.88 versus 0.67; 95% confidence interval, 0.52-0.82), and similar specificity (78% versus 80%) compared with the aggregate-based model. Small (<5 mm) and large (≥5 mm) IAs have different hemodynamic and clinical, but not morphological, rupture discriminants. Size-dichotomized rupture discrimination models performed better than the aggregate model. © 2018 American Heart Association, Inc.

Approximation algorithm for the problem of partitioning a sequence into clusters

NASA Astrophysics Data System (ADS)

Kel'manov, A. V.; Mikhailova, L. V.; Khamidullin, S. A.; Khandeev, V. I.

2017-08-01

We consider the problem of partitioning a finite sequence of Euclidean points into a given number of clusters (subsequences) using the criterion of the minimal sum (over all clusters) of intercluster sums of squared distances from the elements of the clusters to their centers. It is assumed that the center of one of the desired clusters is at the origin, while the center of each of the other clusters is unknown and determined as the mean value over all elements in this cluster. Additionally, the partition obeys two structural constraints on the indices of sequence elements contained in the clusters with unknown centers: (1) the concatenation of the indices of elements in these clusters is an increasing sequence, and (2) the difference between an index and the preceding one is bounded above and below by prescribed constants. It is shown that this problem is strongly NP-hard. A 2-approximation algorithm is constructed that is polynomial-time for a fixed number of clusters.

Clustering of color map pixels: an interactive approach

NASA Astrophysics Data System (ADS)

Moon, Yiu Sang; Luk, Franklin T.; Yuen, K. N.; Yeung, Hoi Wo

2003-12-01

The demand for digital maps continues to arise as mobile electronic devices become more popular nowadays. Instead of creating the entire map from void, we may convert a scanned paper map into a digital one. Color clustering is the very first step of the conversion process. Currently, most of the existing clustering algorithms are fully automatic. They are fast and efficient but may not work well in map conversion because of the numerous ambiguous issues associated with printed maps. Here we introduce two interactive approaches for color clustering on the map: color clustering with pre-calculated index colors (PCIC) and color clustering with pre-calculated color ranges (PCCR). We also introduce a memory model that could enhance and integrate different image processing techniques for fine-tuning the clustering results. Problems and examples of the algorithms are discussed in the paper.

An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States

USGS Publications Warehouse

Wendel, Jochen; Buttenfield, Barbara P.; Stanislawski, Larry V.

2016-01-01

Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification.

The Application of the Health Belief Model in Oral Health Education

PubMed Central

Solhi, M; Zadeh, D Shojaei; Seraj, B; Zadeh, S Faghih

2010-01-01

Background: The goal of this study was to determine the application of health belief model in oral health education for 12-year-old children and its effect on oral health behaviors and indexes. Methods: A quasi-experimental study was carried out on twelve-year-old girl students (n-291) in the first grade of secondary school, in the central district of Tehran, Iran. Research sample was selected by a multistage cluster sampling. The data was obtained by using a valid reliable questionnaire for measuring the perceptions, a checklist for observing the quality of brushing and dental flossing and health files and clinical observation. First, a descriptive study was applied to individual perceptions, oral behaviors, Oral Hygiene Index (OHI) and Decayed, Missing and Filled Teeth Index (DMFTI). Then an educational planning based on the results and Health Belief Model (HBM) was applied. The procedure was repeated after six months. Results: After education, based on HBM, all the oral health perceptions increased (P<.05). Correct brushing and flossing are influenced by increased perceptions. A low correlation between the reduction of DMFTI and increased perceived severity and increased perceived barriers are found (r= −0.28, r = 0.43 respectively). In addition, there was a limited correlation between OHI and increased perceived benefits (r = −0.26). Conclusion: Using health belief model in oral health education for increasing the likelihood of taking preventive oral health behaviors is applicable. PMID:23113044

Process Flow Features as a Host-Based Event Knowledge Representation

DTIC Science & Technology

2012-06-14

an executing process during a window of time called a process flow. Process flows are calculated from key process data structures extracted from...for Cluster 98. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.9. Davies- Boldin Dunn Index Sliding Window 5 on Windows 7...82 4.10. Davies- Boldin Dunn Index Sliding Window 10 on Windows 7 . 83 4.11. Davies- Boldin Dunn Index Sliding Window 20 on Windows 7 . 83 ix List of

Psychometric Properties of Korean Version of the Second Victim Experience and Support Tool (K-SVEST).

PubMed

Kim, Eun-Mi; Kim, Sun-Aee; Lee, Ju-Ry; Burlison, Jonathan D; Oh, Eui Geum

2018-02-13

"Second victims" are defined as healthcare professionals whose wellness is influenced by adverse clinical events. The Second Victim Experience and Support Tool (SVEST) was used to measure the second-victim experience and quality of support resources. Although the reliability and validity of the original SVEST have been validated, those for the Korean tool have not been validated. The aim of the study was to evaluate the psychometric properties of the Korean version of the SVEST. The study included 305 clinical nurses as participants. The SVEST was translated into Korean via back translation. Content validity was assessed by seven experts, and test-retest reliability was evaluated by 30 clinicians. Internal consistency and construct validity were assessed via confirmatory factor analysis. The analyses were performed using SPSS 23.0 and STATA 13.0 software. The content validity index value demonstrated validity; item- and scale-level content validity index values were both 0.95. Test-retest reliability and internal consistency reliability were satisfactory: the intraclass consistent coefficient was 0.71, and Cronbach α values ranged from 0.59 to 0.87. The CFA showed a significantly good fit for an eight-factor structure (χ = 578.21, df = 303, comparative fit index = 0.92, Tucker-Lewis index = 0.90, root mean square error of approximation = 0.05). The K-SVEST demonstrated good psychometric properties and adequate validity and reliability. The results showed that the Korean version of SVEST demonstrated the extent of second victimhood and support resources in Korean healthcare workers and could aid in the development of support programs and evaluation of their effectiveness.

Field-Aligned Current at Plasma Sheet Boundary Layers During Storm Time: Cluster Observation

NASA Astrophysics Data System (ADS)

Shi, J.; Cheng, Z.; Zhang, T.; Dunlop, M.; Liu, Z.

2007-05-01

The magnetic field data from the FGM instruments on board the four Cluster spacecrafts were used to study Field Aligned Current (FAC) at the Plasma Sheet Boundary Layers (PSBLs) with the so called "curlometer technique". We analyzed the date obtained in 2001 in the magnetotail and only two cases were found in the storm time. One (August 17, 2001) occurred from sudden commencement to main phase, and the other (October 1, 2001) lay in the main phase and recovery phase. The relationship between the FAC density and the AE index was studied and the results are shown as follows. (1) In the sudden commencement and the main phase the density of the FAC increases obviously, in the recovery phase the density of the FAC increases slightly. (2) From the sudden commencement to the initial stage of the main phase the FAC increases with decreasing AE index and decreases with increasing AE index. From the late stage of the main phase to initial stage of the recovery phase, the FAC increases with increasing AE index and decreases with decreasing AE index. In the late stage of the recovery phase the disturbance of the FAC is not so violent, so that the FAC varying with the AE index is not very obvious.

A Scalable Monitoring for the CMS Filter Farm Based on Elasticsearch

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

Andre, J.M.; et al.

2015-12-23

A flexible monitoring system has been designed for the CMS File-based Filter Farm making use of modern data mining and analytics components. All the metadata and monitoring information concerning data flow and execution of the HLT are generated locally in the form of small documents using the JSON encoding. These documents are indexed into a hierarchy of elasticsearch (es) clusters along with process and system log information. Elasticsearch is a search server based on Apache Lucene. It provides a distributed, multitenant-capable search and aggregation engine. Since es is schema-free, any new information can be added seamlessly and the unstructured informationmore » can be queried in non-predetermined ways. The leaf es clusters consist of the very same nodes that form the Filter Farm thus providing natural horizontal scaling. A separate central” es cluster is used to collect and index aggregated information. The fine-grained information, all the way to individual processes, remains available in the leaf clusters. The central es cluster provides quasi-real-time high-level monitoring information to any kind of client. Historical data can be retrieved to analyse past problems or correlate them with external information. We discuss the design and performance of this system in the context of the CMS DAQ commissioning for LHC Run 2.« less

Teachers' Perceptions of Fairness, Well-Being and Burnout: A Contribution to the Validation of the Organizational Justice Index by Hoy and Tarter

ERIC Educational Resources Information Center

Capone, Vincenza; Petrillo, Giovanna

2016-01-01

Purpose: The purpose of this paper is to contribute to the validation of the Organizational Justice Index (OJI) by Hoy and Tarter (2004), a self-report questionnaire for teachers' perceptions of fairness in the operation and administration of schools. Design/methodology/approach: In two studies the authors validated the Italian version of the OJI.…

Herth hope index: psychometric testing of the Chinese version.

PubMed

Chan, Keung Sum; Li, Ho Cheung William; Chan, Sally Wai-Chi; Lopez, Violeta

2012-09-01

This article is a report on psychometric testing of the Chinese version of the herth hope index. The availability of a valid and reliable instrument that accurately measures the level of hope in patients with heart failure is crucial before any hope-enhancing interventions can be appropriately planned and evaluated. There is no such instrument for Chinese people. A test-retest, within-subjects design was used. A purposive sample of 120 Hong Kong Chinese patients with heart failure between the ages of 60 and 80 years admitted to two medical wards was recruited during an 8-month period in 2009. Participants were asked to respond to the Chinese version of the herth hope index, Hamilton depression rating scale and Rosenberg's self-esteem scale. The internal consistency, content validity and construct validity and test-retest reliability of the Chinese version of the herth hope index were assessed. The newly translated scale demonstrated adequate internal consistency, good content validity and appropriate convergent and discriminant validity. Confirmatory factor analysis added further evidence of the construct validity of the scale. Results suggest that the newly translated scale can be used as a self-report assessment tool in assessing the level of hope in Hong Kong Chinese patients with heart failure. © 2011 Blackwell Publishing Ltd.

Strong evidences for a nonextensive behavior of the rotation period in open clusters

NASA Astrophysics Data System (ADS)

de Freitas, D. B.; Nepomuceno, M. M. F.; Soares, B. B.; Silva, J. R. P.

2014-11-01

Time-dependent nonextensivity in a stellar astrophysical scenario combines nonextensive entropic indices qK derived from the modified Kawaler's parametrization, and q, obtained from rotational velocity distribution. These q's are related through a heuristic single relation given by q≈ q0(1-Δ t/qK) , where t is the cluster age. In a nonextensive scenario, these indices are quantities that measure the degree of nonextensivity present in the system. Recent studies reveal that the index q is correlated to the formation rate of high-energy tails present in the distribution of rotation velocity. On the other hand, the index qK is determined by the stellar rotation-age relationship. This depends on the magnetic-field configuration through the expression qK=1+4aN/3 , where a and N denote the saturation level of the star magnetic field and its topology, respectively. In the present study, we show that the connection q-qK is also consistent with 548 rotation period data for single main-sequence stars in 11 open clusters aged less than 1 Gyr. The value of qK ˜ 2.5 from our unsaturated model shows that the mean magnetic-field topology of these stars is slightly more complex than a purely radial field. Our results also suggest that stellar rotational braking behavior affects the degree of anti-correlation between q and cluster age t. Finally, we suggest that stellar magnetic braking can be scaled by the entropic index q.

Effectiveness and feasibility of long-lasting insecticide-treated curtains and water container covers for dengue vector control in Colombia: a cluster randomised trial

PubMed Central

Quintero, Juliana; García-Betancourt, Tatiana; Cortés, Sebastian; García, Diana; Alcalá, Lucas; González-Uribe, Catalina; Brochero, Helena; Carrasquilla, Gabriel

2015-01-01

Background Long-lasting insecticide-treated net (LLIN) window and door curtains alone or in combination with LLIN water container covers were analysed regarding effectiveness in reducing dengue vector density, and feasibility of the intervention. Methods A cluster randomised trial was conducted in an urban area of Colombia comparing 10 randomly selected control and 10 intervention clusters. In control clusters, routine vector control activities were performed. The intervention delivered first, LLIN curtains (from July to August 2013) and secondly, water container covers (from October to March 2014). Cross-sectional entomological surveys were carried out at baseline (February 2013 to June 2013), 9 weeks after the first intervention (August to October 2013), and 4–6 weeks after the second intervention (March to April 2014). Results Curtains were installed in 922 households and water container covers in 303 households. The Breteau index (BI) fell from 14 to 6 in the intervention group and from 8 to 5 in the control group. The additional intervention with LLIN covers for water containers showed a significant reduction in pupae per person index (PPI) (p=0.01). In the intervention group, the PPI index showed a clear decline of 71% compared with 25% in the control group. Costs were high but options for cost savings were identified. Conclusions Short term impact evaluation indicates that the intervention package can reduce dengue vector density but sustained effect will depend on multiple factors. PMID:25604762

Social Exclusion Index-for Health Surveys (SEI-HS): a prospective nationwide study to extend and validate a multidimensional social exclusion questionnaire.

PubMed

van Bergen, Addi P L; Hoff, Stella J M; Schreurs, Hanneke; van Loon, Annelies; van Hemert, Albert M

2017-03-14

Social exclusion (SE) refers to the inability of certain groups or individuals to fully participate in society. SE is associated with socioeconomic inequalities in health, and its measurement in routine public health monitoring is considered key to designing effective health policies. In an earlier retrospective analysis we demonstrated that in all four major Dutch cities, SE could largely be measured with existing local public health monitoring data. The current prospective study is aimed at constructing and validating an extended national measure for SE that optimally employs available items. In 2012, a stratified general population sample of 258,928 Dutch adults completed a version of the Netherlands Public Health Monitor (PHM) questionnaire in which 9 items were added covering aspects of SE that were found to be missing in our previous research. Items were derived from the SCP social exclusion index, a well-constructed 15-item instrument developed by the Netherlands Institute for Social Research (SCP). The dataset was randomly divided into a development sample (N =129,464) and a validation sample (N = 129,464). Canonical correlation analysis was conducted in the development sample. The psychometric properties were studied and compared with those of the original SCP index. All analyses were then replicated in the validation sample. The analysis yielded a four dimensional index, the Social Exclusion Index for Health Surveys (SEI-HS), containing 8 SCP items and 9 PHM items. The four dimensions: "lack of social participation", "material deprivation", "lack of normative integration" and "inadequate access to basic social rights", were each measured with 3 to 6 items. The SEI-HS showed adequate internal consistency for both the general index and for two of four dimension scales. The internal structure and construct validity of the SEI-HS were satisfactory and similar to the original SCP index. Replication of the SEI-HS in the validation sample confirmed its generalisability. This study demonstrates that the SEI-HS offers epidemiologists and public health researchers a uniform, reliable, valid and efficient means of assessing social exclusion and its underlying dimensions. The study also provides valuable insights in how to develop embedded measures for public health surveillance.

Price Formation Based on Particle-Cluster Aggregation

NASA Astrophysics Data System (ADS)

Wang, Shijun; Zhang, Changshui

In the present work, we propose a microscopic model of financial markets based on particle-cluster aggregation on a two-dimensional small-world information network in order to simulate the dynamics of the stock markets. "Stylized facts" of the financial market time series, such as fat-tail distribution of returns, volatility clustering and multifractality, are observed in the model. The results of the model agree with empirical data taken from historical records of the daily closures of the NYSE composite index.

Application of Fuzzy c-Means and Joint-Feature-Clustering to Detect Redundancies of Image-Features in Drug Combinations Studies of Breast Cancer

NASA Astrophysics Data System (ADS)

Brandl, Miriam B.; Beck, Dominik; Pham, Tuan D.

2011-06-01

The high dimensionality of image-based dataset can be a drawback for classification accuracy. In this study, we propose the application of fuzzy c-means clustering, cluster validity indices and the notation of a joint-feature-clustering matrix to find redundancies of image-features. The introduced matrix indicates how frequently features are grouped in a mutual cluster. The resulting information can be used to find data-derived feature prototypes with a common biological meaning, reduce data storage as well as computation times and improve the classification accuracy.

Measuring the contribution of art therapy in multidisciplinary treatment of personality disorders: The construction of the Self‐expression and Emotion Regulation in Art Therapy Scale (SERATS)

PubMed Central

van Hooren, Susan; van der Veld, William M.; Hutschemaekers, Giel

2017-01-01

Abstract Despite the use of art therapy in clinical practice, its appreciation and reported beneficial results, no instruments are available to measure specific effects of art therapy among patients with personality disorders cluster B/C in multidisciplinary treatment. In the present study, we described the development and psychometric evaluation of the Self‐expression and Emotion Regulation in Art Therapy Scale (SERATS). Structural validity (exploratory and confirmatory factor analysis), reliability, construct validity and sensitivity to change were examined using two independent databases (n = 335; n = 34) of patients diagnosed with personality disorders cluster B/C. This resulted in a nine‐item effect scale with a single factor with a high internal reliability and high test–retest reliability; it demonstrated discriminant validity and sensitivity to change. In conclusion, the SERATS is brief and content‐valid and offers objective and reliable information on self‐expression and emotion regulation in art therapy among patients with personality disorders cluster B/C. Although more research on construct validity is needed, the SERATS is a promising tool to be applied as an effect scale and as a monitoring tool during art therapy treatment. © 2017 The Authors Personality and Mental Health Published by John Wiley & Sons Ltd PMID:28730717

Serial album validation for promotion of infant body weight control

PubMed Central

Saraiva, Nathalia Costa Gonzaga; Medeiros, Carla Campos Muniz; de Araujo, Thelma Leite

2018-01-01

ABSTRACT Objective: to validate the content and appearance of a serial album for children aged from 7 to 10 years addressing the topic of prevention and control of body weight. Method: methodological study with descriptive nature. The validation process was attended by 33 specialists in educational technologies and/or in excess of infantile weight. The agreement index of 80% was the minimum considered to guarantee the validation of the material. Results: most of the specialists had a doctoral degree and a graduate degree in nursing. Regarding content, illustrations, layout and relevance, all items were validated and 69.7% of the experts considered the album as great. The overall agreement validation index for the educational technology was 0.88. Only the script-sheet 3 did not reach the cutoff point of the content validation index. Changes were made to the material, such as title change, inclusion of the school context and insertion of nutritionist and physical educator in the story narrated in the album. Conclusion: the proposed serial album was considered valid by experts regarding content and appearance, suggesting that this technology has the potential to contribute in health education by promoting healthy weight in the age group of 7 to 10 years. PMID:29791665

Validation of nomograms for overall survival, cancer-specific survival, and recurrence in carcinoma of the major salivary glands.

PubMed

Hay, Ashley; Migliacci, Jocelyn; Zanoni, Daniella Karassawa; Patel, Snehal; Yu, Changhong; Kattan, Michael W; Ganly, Ian

2018-05-01

The purpose of this study was to investigate the performance of the Memorial Sloan Kettering Cancer Center salivary carcinoma nomograms predicting overall survival, cancer-specific survival, and recurrence with an external validation dataset. The validation dataset comprised 123 patients treated between 2010 and 2015 at our institution. They were evaluated by assessing discrimination (concordance index [C-index]) and calibration (plotting predicted vs actual probabilities for quintiles). The validation cohort (n = 123) showed some differences to the original cohort (n = 301). The validation cohort had less high-grade cancers (P = .006), less lymphovascular invasion (LVI; P < .001) and shorter follow-up of 19 months versus 45.6 months. Validation showed a C-index of 0.833 (95% confidence interval [CI] 0.758-0.908), 0.807 (95% CI 0.717-0.898), and 0.844 (95% CI 0.768-0.920) for overall survival, cancer-specific survival, and recurrence, respectively. The 3 salivary gland nomograms performed well using a contemporary validation dataset, despite limitations related to sample size, follow-up, and differences in clinical and pathology characteristics between the original and validation cohorts. © 2018 Wiley Periodicals, Inc.

Effects of Group Size and Lack of Sphericity on the Recovery of Clusters in K-means Cluster Analysis.

PubMed

Craen, Saskia de; Commandeur, Jacques J F; Frank, Laurence E; Heiser, Willem J

2006-06-01

K-means cluster analysis is known for its tendency to produce spherical and equally sized clusters. To assess the magnitude of these effects, a simulation study was conducted, in which populations were created with varying departures from sphericity and group sizes. An analysis of the recovery of clusters in the samples taken from these populations showed a significant effect of lack of sphericity and group size. This effect was, however, not as large as expected, with still a recovery index of more than 0.5 in the "worst case scenario." An interaction effect between the two data aspects was also found. The decreasing trend in the recovery of clusters for increasing departures from sphericity is different for equal and unequal group sizes.

Comparison between volatility return intervals of the S&P 500 index and two common models

NASA Astrophysics Data System (ADS)

Vodenska-Chitkushev, I.; Wang, F. Z.; Weber, P.; Yamasaki, K.; Havlin, S.; Stanley, H. E.

2008-01-01

We analyze the S&P 500 index data for the 13-year period, from January 1, 1984 to December 31, 1996, with one data point every 10 min. For this database, we study the distribution and clustering of volatility return intervals, which are defined as the time intervals between successive volatilities above a certain threshold q. We find that the long memory in the volatility leads to a clustering of above-median as well as below-median return intervals. In addition, it turns out that the short return intervals form larger clusters compared to the long return intervals. When comparing the empirical results to the ARMA-FIGARCH and fBm models for volatility, we find that the fBm model predicts scaling better than the ARMA-FIGARCH model, which is consistent with the argument that both ARMA-FIGARCH and fBm capture the long-term dependence in return intervals to a certain extent, but only fBm accounts for the scaling. We perform the Student's t-test to compare the empirical data with the shuffled records, ARMA-FIGARCH and fBm. We analyze separately the clusters of above-median return intervals and the clusters of below-median return intervals for different thresholds q. We find that the empirical data are statistically different from the shuffled data for all thresholds q. Our results also suggest that the ARMA-FIGARCH model is statistically different from the S&P 500 for intermediate q for both above-median and below-median clusters, while fBm is statistically different from S&P 500 for small and large q for above-median clusters and for small q for below-median clusters. Neither model can fully explain the entire regime of q studied.

Prediction of overall survival for metastatic pancreatic cancer: Development and validation of a prognostic nomogram with data from open clinical trial and real-world study.

PubMed

Hang, Junjie; Wu, Lixia; Zhu, Lina; Sun, Zhiqiang; Wang, Ge; Pan, Jingjing; Zheng, Suhua; Xu, Kequn; Du, Jiadi; Jiang, Hua

2018-06-01

It is necessary to develop prognostic tools of metastatic pancreatic cancer (MPC) for optimizing therapeutic strategies. Thus, we tried to develop and validate a prognostic nomogram of MPC. Data from 3 clinical trials (NCT00844649, NCT01124786, and NCT00574275) and 133 Chinese MPC patients were used for analysis. The former 2 trials were taken as the training cohort while NCT00574275 was used as the validation cohort. In addition, 133 MPC patients treated in China were taken as the testing cohort. Cox regression model was used to investigate prognostic factors in the training cohort. With these factors, we established a nomogram and verified it by Harrell's concordance index (C-index) and calibration plots. Furthermore, the nomogram was externally validated in the validation cohort and testing cohort. In the training cohort (n = 445), performance status, liver metastasis, Carbohydrate antigen 19-9 (CA19-9) log-value, absolute neutrophil count (ANC), and albumin were independent prognostic factors for overall survival (OS). A nomogram was established with these factors to predict OS and survival probabilities. The nomogram showed an acceptable discrimination ability (C-index: .683) and good calibration, and was further externally validated in the validation cohort (n = 273, C-index: .699) and testing cohort (n = 133, C-index: .653).The nomogram total points (NTP) had the potential to stratify patients into 3-risk groups with median OS of 11.7, 7.0 and 3.7 months (P < .001), respectively. In conclusion, the prognostic nomogram with NTP can predict OS for patients with MPC with considerable accuracy. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Validity, responsiveness, and minimal clinically important difference of EQ-5D-5L in stroke patients undergoing rehabilitation.

PubMed

Chen, Poyu; Lin, Keh-Chung; Liing, Rong-Jiuan; Wu, Ching-Yi; Chen, Chia-Ling; Chang, Ku-Chou

2016-06-01

To examine the criterion validity, responsiveness, and minimal clinically important difference (MCID) of the EuroQoL 5-Dimensions Questionnaire (EQ-5D-5L) and visual analog scale (EQ-VAS) in people receiving rehabilitation after stroke. The EQ-5D-5L, along with four criterion measures-the Medical Research Council scales for muscle strength, the Fugl-Meyer assessment, the functional independence measure, and the Stroke Impact Scale-was administered to 65 patients with stroke before and after 3- to 4-week therapy. Criterion validity was estimated using the Spearman correlation coefficient. Responsiveness was analyzed by the effect size, standardized response mean (SRM), and criterion responsiveness. The MCID was determined by anchor-based and distribution-based approaches. The percentage of patients exceeding the MCID was also reported. Concurrent validity of the EQ-Index was better compared with the EQ-VAS. The EQ-Index has better power for predicting the rehabilitation outcome in the activities of daily living than other motor-related outcome measures. The EQ-Index was moderately responsive to change (SRM = 0.63), whereas the EQ-VAS was only mildly responsive to change. The MCID estimation of the EQ-Index (the percentage of patients exceeding the MCID) was 0.10 (33.8 %) and 0.10 (33.8 %) based on the anchor-based and distribution-based approaches, respectively, and the estimation of EQ-VAS was 8.61 (41.5 %) and 10.82 (32.3 %). The EQ-Index has shown reasonable concurrent validity, limited predictive validity, and acceptable responsiveness for detecting the health-related quality of life in stroke patients undergoing rehabilitation, but not for EQ-VAS. Future research considering different recovery stages after stroke is warranted to validate these estimations.

Fuzzy Clustering Analysis in Environmental Impact Assessment--A Complement Tool to Environmental Quality Index.

ERIC Educational Resources Information Center

Kung, Hsiang-Te; And Others

1993-01-01

In spite of rapid progress achieved in the methodological research underlying environmental impact assessment (EIA), the problem of weighting various parameters has not yet been solved. This paper presents a new approach, fuzzy clustering analysis, which is illustrated with an EIA case study on Baoshan-Wusong District in Shanghai, China. (Author)

OMERACT-based fibromyalgia symptom subgroups: an exploratory cluster analysis.

PubMed

Vincent, Ann; Hoskin, Tanya L; Whipple, Mary O; Clauw, Daniel J; Barton, Debra L; Benzo, Roberto P; Williams, David A

2014-10-16

The aim of this study was to identify subsets of patients with fibromyalgia with similar symptom profiles using the Outcome Measures in Rheumatology (OMERACT) core symptom domains. Female patients with a diagnosis of fibromyalgia and currently meeting fibromyalgia research survey criteria completed the Brief Pain Inventory, the 30-item Profile of Mood States, the Medical Outcomes Sleep Scale, the Multidimensional Fatigue Inventory, the Multiple Ability Self-Report Questionnaire, the Fibromyalgia Impact Questionnaire-Revised (FIQ-R) and the Short Form-36 between 1 June 2011 and 31 October 2011. Hierarchical agglomerative clustering was used to identify subgroups of patients with similar symptom profiles. To validate the results from this sample, hierarchical agglomerative clustering was repeated in an external sample of female patients with fibromyalgia with similar inclusion criteria. A total of 581 females with a mean age of 55.1 (range, 20.1 to 90.2) years were included. A four-cluster solution best fit the data, and each clustering variable differed significantly (P <0.0001) among the four clusters. The four clusters divided the sample into severity levels: Cluster 1 reflects the lowest average levels across all symptoms, and cluster 4 reflects the highest average levels. Clusters 2 and 3 capture moderate symptoms levels. Clusters 2 and 3 differed mainly in profiles of anxiety and depression, with Cluster 2 having lower levels of depression and anxiety than Cluster 3, despite higher levels of pain. The results of the cluster analysis of the external sample (n = 478) looked very similar to those found in the original cluster analysis, except for a slight difference in sleep problems. This was despite having patients in the validation sample who were significantly younger (P <0.0001) and had more severe symptoms (higher FIQ-R total scores (P = 0.0004)). In our study, we incorporated core OMERACT symptom domains, which allowed for clustering based on a comprehensive symptom profile. Although our exploratory cluster solution needs confirmation in a longitudinal study, this approach could provide a rationale to support the study of individualized clinical evaluation and intervention.

Longitudinal changes in physical activity, sedentary behavior and body mass index in adolescence: Migrations towards different weight cluster.

PubMed

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

2017-01-01

This study examined longitudinal changes in physical activity, sedentary behavior and body mass index in adolescents, specifically their migrations towards a different weight cluster. A cohort of 755 adolescents participated in a three-year study. A clustering Self-Organized Maps Analysis was performed to visualize changes in subjects' characteristics between the first and second assessment, and how adolescents were grouped. Also a classification tree was used to identify the behavioral characteristics of the groups that changed their weight cluster. Results indicated that boys were more active and less sedentary than girls. Boys were especially keen to technological-based activities while girls preferred social-based activities. A moderate competing effect between sedentary behaviors and physical activities was observed, especially in girls. Overweight and obesity were negatively associated with physical activity, although a small group of overweight/obese adolescents showed a positive relationship with vigorous physical activity. Cluster migrations indicated that 22.66% of adolescents changed their weight cluster to a lower category and none of them moved in the opposite direction. The behavioral characteristics of these adolescents did not support the hypothesis that the change to a lower weight cluster was a consequence of an increase in time devoted to physical activity or a decrease in time spent on sedentary behavior. Physical activity and sedentary behavior does not exert a substantial effect on overweight and obesity. Therefore, there are other ways of changing to a lower-weight status in adolescents apart from those in which physical activity and sedentary behavior are involved.

Longitudinal changes in physical activity, sedentary behavior and body mass index in adolescence: Migrations towards different weight cluster

PubMed Central

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

2017-01-01

This study examined longitudinal changes in physical activity, sedentary behavior and body mass index in adolescents, specifically their migrations towards a different weight cluster. A cohort of 755 adolescents participated in a three-year study. A clustering Self-Organized Maps Analysis was performed to visualize changes in subjects’ characteristics between the first and second assessment, and how adolescents were grouped. Also a classification tree was used to identify the behavioral characteristics of the groups that changed their weight cluster. Results indicated that boys were more active and less sedentary than girls. Boys were especially keen to technological-based activities while girls preferred social-based activities. A moderate competing effect between sedentary behaviors and physical activities was observed, especially in girls. Overweight and obesity were negatively associated with physical activity, although a small group of overweight/obese adolescents showed a positive relationship with vigorous physical activity. Cluster migrations indicated that 22.66% of adolescents changed their weight cluster to a lower category and none of them moved in the opposite direction. The behavioral characteristics of these adolescents did not support the hypothesis that the change to a lower weight cluster was a consequence of an increase in time devoted to physical activity or a decrease in time spent on sedentary behavior. Physical activity and sedentary behavior does not exert a substantial effect on overweight and obesity. Therefore, there are other ways of changing to a lower-weight status in adolescents apart from those in which physical activity and sedentary behavior are involved. PMID:28636644

Power-Law Template for Infrared Point-Source Clustering

NASA Technical Reports Server (NTRS)

Addison, Graeme E; Dunkley, Joanna; Hajian, Amir; Viero, Marco; Bond, J. Richard; Das, Sudeep; Devlin, Mark J.; Halpern, Mark; Hincks, Adam D; Hlozek, Renee;

Accurate prediction of secondary metabolite gene clusters in filamentous fungi.

PubMed

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

2013-01-02

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

Features of dissociation differentially predict antidepressant response to ketamine in treatment-resistant depression.

PubMed

Niciu, Mark J; Shovestul, Bridget J; Jaso, Brittany A; Farmer, Cristan; Luckenbaugh, David A; Brutsche, Nancy E; Park, Lawrence T; Ballard, Elizabeth D; Zarate, Carlos A

2018-05-01

Ketamine induces rapid and robust antidepressant effects, and many patients also describe dissociation, which is associated with antidepressant response. This follow-up study investigated whether antidepressant efficacy is uniquely related to dissociative symptom clusters. Treatment-resistant patients with major depressive disorder (MDD) or bipolar disorder (BD) (n = 126) drawn from three studies received a single subanesthetic (0.5 mg/kg) ketamine infusion. Dissociative effects were measured using the Clinician-Administered Dissociative States Scale (CADSS). Antidepressant response was measured using the 17-item Hamilton Depression Rating Scale (HAM-D). A confirmatory factor analysis established the validity of CADSS subscales (derealization, depersonalization, amnesia), and a general linear model with repeated measures was fitted to test whether subscale scores were associated with antidepressant response. Factor validity was supported, with a root mean square error of approximation of .06, a comparative fit index of .97, and a Tucker-Lewis index of .96. Across all studies and timepoints, the depersonalization subscale was positively related to HAM-D percent change. A significant effect of derealization on HAM-D percent change was observed at one timepoint (Day 7) in one study. The amnesia subscale was unrelated to HAM-D percent change. Possible inadequate blinding; combined MDD/BD datasets might have underrepresented ketamine's antidepressant efficacy; the possibility of Type I errors in secondary analyses. From a psychometric perspective, researchers may elect to administer only the CADSS depersonalization subscale, given that it was most closely related to antidepressant response. From a neurobiological perspective, mechanistic similarities may exist between ketamine-induced depersonalization and antidepressant response, although off-target effects cannot be excluded. Published by Elsevier B.V.

Can a deprivation index be used legitimately over both urban and rural areas?

PubMed Central

2014-01-01

Background Although widely used, area-based deprivation indices remain sensitive to urban–rural differences as such indices are usually standardised around typical urban values. There is, therefore, a need to determine to what extent available deprivation indices can be used legitimately over both urban and rural areas. Methods This study was carried out in Brittany, France, a relatively affluent region that contains deep rural areas. Among the 1,736 residential census block groups (IRIS) composing the Brittany region, 1,005 (57.9%) are rural. Four deprivation indices were calculated: two scores (Carstairs and Townsend) developed in the UK and two more recent French measures (Havard and Rey). Two standardisation levels were considered: all of the IRIS and only the urban IRIS of the region. Internal validity (Kappa coefficients and entropy values) and external validity (relationship with colorectal cancer screening [CCS] attendance) were investigated. Results Regardless of the deprivation measure used, wealthy areas are mostly clustered in the West and at the outskirts of major towns. Carstairs and Rey scores stand out by all evaluation criteria, capturing both urban and rural deprivation. High levels of agreements were found across standardisation levels (κ = 0.96). The distributions of deprivation scores were balanced across urban and rural areas, and high Shannon entropy values were observed in the capital city (≥0.93). Similar and significant negative trends were observed between CCS attendance and both deprivation indices, independent of the degree of urbanisation. Conclusions These results provide support, despite potential sociological objections, for the use of a compromise index that would facilitate comparisons and interpretations across urban and rural locations in public health research. PMID:24929662

Validation of the Combined Comorbidity Index of Charlson and Elixhauser to Predict 30-Day Mortality Across ICD-9 and ICD-10.

PubMed

Simard, Marc; Sirois, Caroline; Candas, Bernard

2018-05-01

To validate and compare performance of an International Classification of Diseases, tenth revision (ICD-10) version of a combined comorbidity index merging conditions of Charlson and Elixhauser measures against individual measures in the prediction of 30-day mortality. To select a weight derivation method providing optimal performance across ICD-9 and ICD-10 coding systems. Using 2 adult population-based cohorts of patients with hospital admissions in ICD-9 (2005, n=337,367) and ICD-10 (2011, n=348,820), we validated a combined comorbidity index by predicting 30-day mortality with logistic regression. To appreciate performance of the Combined index and both individual measures, factors impacting indices performance such as population characteristics and weight derivation methods were accounted for. We applied 3 scoring methods (Van Walraven, Schneeweiss, and Charlson) and determined which provides best predictive values. Combined index [c-statistics: 0.853 (95% confidence interval: CI, 0.848-0.856)] performed better than original Charlson [0.841 (95% CI, 0.835-0.844)] or Elixhauser [0.841 (95% CI, 0.837-0.844)] measures on ICD-10 cohort. All weight derivation methods provided close high discrimination results for the Combined index (Van Walraven: 0.852, Schneeweiss: 0.851, Charlson: 0.849). Results were consistent across both coding systems. The Combined index remains valid with both ICD-9 and ICD-10 coding systems and the 3 weight derivation methods evaluated provided consistent high performance across those coding systems.

Improving clustering with metabolic pathway data.

PubMed

Milone, Diego H; Stegmayer, Georgina; López, Mariana; Kamenetzky, Laura; Carrari, Fernando

2014-04-10

It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.The algorithm is available as a web-demo at http://fich.unl.edu.ar/sinc/web-demo/bsom-lite/. The source code and the data sets supporting the results of this article are available at http://sourceforge.net/projects/sourcesinc/files/bsom.

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.

Validation of the National Aeronautics and Space Administration Task Load Index as a tool to evaluate the learning curve for endoscopy training.

PubMed

Mohamed, Rachid; Raman, Maitreyi; Anderson, John; McLaughlin, Kevin; Rostom, Alaa; Coderre, Sylvain

2014-03-01

Although workplace workload assessments exist in different fields, an endoscopy-specific workload assessment tool is lacking. To validate such a workload tool and use it to map the progression of novice trainees in gastroenterology in performing their first endoscopies. The National Aeronautics and Space Administration Task Load Index (NASA-TLX) workload assessment tool was completed by eight novice trainees in gastroenterology and 10 practicing gastroenterologists⁄surgeons. An exploratory factor analysis was performed to construct a streamlined endoscopy-specific task load index, which was subsequently validated. The 'Endoscopy Task Load Index' was used to monitor progression of trainee exertion and self-assessed performance over their first 40 procedures. From the factor analysis of the NASA-TLX, two principal components emerged: a measure of exertion and a measure of self-efficacy. These items became the components of the newly validated Endoscopy Task Load Index. There was a steady decline in self-perceived exertion over the training period, which was more rapid for gastroscopy than colonoscopy. The self-efficacy scores for gastroscopy rapidly increased over the first few procedures, reaching a plateau after this period of time. For colonoscopy, there was a progressive increase in reported self-efficacy over the first three quartiles of procedures, followed by a drop in self-efficacy scores over the final quartile. The present study validated an Endoscopy Task Load Index that can be completed in <1 min. Practical implications of such a tool in endoscopy education include identifying periods of higher perceived exertion among novice endoscopists, facilitating appropriate levels of guidance from trainers.

Psychometric properties of the medical outcomes study sleep scale in Spanish postmenopausal women.

PubMed

Zagalaz-Anula, Noelia; Hita-Contreras, Fidel; Martínez-Amat, Antonio; Cruz-Díaz, David; Lomas-Vega, Rafael

2017-07-01

This study aimed to analyze the reliability and validity of the Spanish version of the Medical Outcomes Study Sleep Scale (MOS-SS), and its ability to discriminate between poor and good sleepers among a Spanish population with vestibular disorders. In all, 121 women (50-76 years old) completed the Spanish version of the MOS-SS. Internal consistency, test-retest reliability, and construct validity (exploratory factor analysis) were analyzed. Concurrent validity was evaluated using the Pittsburgh Sleep Quality Index and the 36-item Short Form Health Survey. To analyze the ability of the MOS-SS scores to discriminate between poor and good sleepers, a receiver-operating characteristic curve analysis was performed. The Spanish version of the MOS-SS showed excellent and substantial reliability in Sleep Problems Index I (two sleep disturbance items, one somnolence item, two sleep adequacy items, and awaken short of breath or with headache) and Sleep Problems Index II (four sleep disturbance items, two somnolence items, two sleep adequacy items, and awaken short of breath or with headache), respectively, and good internal consistency with optimal Cronbach's alpha values in all domains and indexes (0.70-0.90). Factor analysis suggested a coherent four-factor structure (explained variance 70%). In concurrent validity analysis, MOS-SS indexes showed significant and strong correlation with the Pittsburgh Sleep Quality Index total score, and moderate with the 36-item Short Form Health Survey component summaries. Several domains and the two indexes were significantly able to discriminate between poor and good sleepers (P < 0.05). Optimal cut-off points were above 20 for "sleep disturbance" domain, with above 22.22 and above 33.33 for Sleep Problems Index I and II. The Spanish version of the MOS-SS is a valid and reliable instrument, suitable to assess sleep quality in Spanish postmenopausal women, with satisfactory general psychometric properties. It discriminates well between good and poor sleepers.

Detection of a Double Relic in the Torpedo Cluster: SPT-CL J0245-5302

NASA Astrophysics Data System (ADS)

Zheng, Q.; Johnston-Hollitt, M.; Duchesne, S. W.; Li, W. T.

2018-06-01

The Torpedo cluster, SPT-CL J0245-5302 (S0295) is a massive, merging cluster at a redshift of z = 0.300, which exhibits a strikingly similar morphology to the Bullet cluster 1E 0657-55.8 (z = 0.296), including a classic bow shock in the cluster's intra-cluster medium revealed by Chandra X-ray observations. We present Australia Telescope Compact Array data centred at 2.1 GHz and Murchison Widefield Array data at frequencies between 72 MHz and 231 MHz which we use to study the properties of the cluster. We characterise a number of discrete and diffuse radio sources in the cluster, including the detection of two previously unknown radio relics on the cluster periphery. The average spectral index of the diffuse emission between 70 MHz and 3.1 GHz is α =-1.63_{-0.10}^{+0.10} and a radio-derived Mach number for the shock in the west of the cluster is calculated as M = 2.04. The Torpedo cluster is thus a double relic system at moderate redshift.

A DISTANT RADIO MINI-HALO IN THE PHOENIX GALAXY CLUSTER

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

Van Weeren, R. J.; Andrade-Santos, F.; Forman, W. R.

We report the discovery of extended radio emission in the Phoenix cluster (SPT-CL J2344-4243, z = 0.596) with the Giant Metrewave Radio Telescope (GMRT) at 610 MHz. The diffuse emission extends over a region of at least 400-500 kpc and surrounds the central radio source of the Brightest Cluster Galaxy, but does not appear to be directly associated with it. We classify the diffuse emission as a radio mini-halo, making it the currently most distant mini-halo known. Radio mini-halos have been explained by synchrotron emitting particles re-accelerated via turbulence, possibly induced by gas sloshing generated from a minor merger event. Chandra observationsmore » show a non-concentric X-ray surface brightness distribution, which is consistent with this sloshing interpretation. The mini-halo has a flux density of 17 ± 5 mJy, resulting in a 1.4 GHz radio power of (10.4 ± 3.5) × 10{sup 24} W Hz{sup –1}. The combined cluster emission, which includes the central compact radio source, is also detected in a shallow GMRT 156 MHz observation and together with the 610 MHz data we compute a spectral index of –0.84 ± 0.12 for the overall cluster radio emission. Given that mini-halos typically have steeper radio spectra than cluster radio galaxies, this spectral index should be taken as an upper limit for the mini-halo.« less

Rural cases of equine West Nile virus encephalomyelitis and the normalized difference vegetation index

USGS Publications Warehouse

Ward, M.P.; Ramsay, B.H.; Gallo, K.

2005-01-01

Data from an outbreak (August to October, 2002) of West Nile virus (WNV) encephalomyelitis in a population of horses located in northern Indiana was scanned for clusters in time and space. One significant (p = 0.04) cluster of case premises was detected, occurring between September 4 and 10 in the south-west part of the study area (85.70??N, 45.50??W). It included 10 case premises (3.67 case premises expected) within a radius of 2264 m. Image data were acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensor onboard a National Oceanic and Atmospheric Administration polar-orbiting satellite. The Normalized Difference Vegetation Index (NDVI) was calculated from visible and near-infrared data of daily observations, which were composited to produce a weekly-1km2 resolution raster image product. During the epidemic, a significant (p<0.01) decrease (0.025 per week) in estimated NDVI was observed at all case and control premise sites. The median estimated NDVI (0.659) for case premises within the cluster identified was significantly (p<0.01) greater than the median estimated NDVI for other case (0.571) and control (0.596) premises during the same period. The difference in median estimated NDVI for case premises within this cluster, compared to cases not included in this cluster, was greatest (5.3% and 5.1%, respectively) at 1 and 5 weeks preceding occurrence of the cluster. The NDVI may be useful for identifying foci of WNV transmission. ?? Mary Ann Liebert, Inc.

The XMM Cluster Survey: the halo occupation number of BOSS galaxies in X-ray clusters

NASA Astrophysics Data System (ADS)

Mehrtens, Nicola; Romer, A. Kathy; Nichol, Robert C.; Collins, Chris A.; Sahlén, Martin; Rooney, Philip J.; Mayers, Julian A.; Bermeo-Hernandez, A.; Bristow, Martyn; Capozzi, Diego; Christodoulou, L.; Comparat, Johan; Hilton, Matt; Hoyle, Ben; Kay, Scott T.; Liddle, Andrew R.; Mann, Robert G.; Masters, Karen; Miller, Christopher J.; Parejko, John K.; Prada, Francisco; Ross, Ashley J.; Schneider, Donald P.; Stott, John P.; Streblyanska, Alina; Viana, Pedro T. P.; White, Martin; Wilcox, Harry; Zehavi, Idit

2016-12-01

We present a direct measurement of the mean halo occupation distribution (HOD) of galaxies taken from the eleventh data release (DR11) of the Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS). The HOD of BOSS low-redshift (LOWZ: 0.2 < z < 0.4) and Constant-Mass (CMASS: 0.43 < z < 0.7) galaxies is inferred via their association with the dark matter haloes of 174 X-ray-selected galaxy clusters drawn from the XMM Cluster Survey (XCS). Halo masses are determined for each galaxy cluster based on X-ray temperature measurements, and range between log10(M180/M⊙) = 13 and 15. Our directly measured HODs are consistent with the HOD-model fits inferred via the galaxy-clustering analyses of Parejko et al. for the BOSS LOWZ sample and White et al. for the BOSS CMASS sample. Under the simplifying assumption that the other parameters that describe the HOD hold the values measured by these authors, we have determined a best-fitting alpha-index of 0.91 ± 0.08 and 1.27^{+0.03}_{-0.04} for the CMASS and LOWZ HOD, respectively. These alpha-index values are consistent with those measured by White et al. and Parejko et al. In summary, our study provides independent support for the HOD models assumed during the development of the BOSS mock-galaxy catalogues that have subsequently been used to derive BOSS cosmological constraints.

[Evaluation of the family focus and community orientation in the Family Health Strategy].

PubMed

Alencar, Monyk Neves de; Coimbra, Liberata Campos; Morais, Ana Patrícia Pereira; Silva, Antônio Augusto Moura da; Pinheiro, Siane Rocha de Almeida; Queiroz, Rejane Christine de Sousa

2014-02-01

The Family Health Strategy should be focused on the family unit and constructed operationally within the community sphere. The research assessed the family focus and community orientation as attributes of Primary Health Care, comparing if the responses differed among users, professionals and managers. It is an evaluative study of a population-based quantitative approach conducted between January 2010 and March 2011 in São Luís in the state of Maranhão. The study involved a population of 32 managers and 80 professionals with more than six months experience in the Family Health Strategy, and 883 users were selected by means of cluster sampling. Questionnaires validated in Brazil were used based on the components of the Primary Care Assessment Tool (PCATool). The composite index of the family focus was 2.7 for users, 4.9 for professionals and 5.3 for managers. In the posttest phase, differences were detected between users and professionals, and users and managers. The composite index of community orientation was 2.9 for users, 3.9 for professionals and 4.8 for managers (p < 0.001). Managers attributed higher percentages in all indicators, followed by professionals and lastly users. Both attributes were rated as being unsatisfactory in the perception of the users.

Glycemic index and disease.

PubMed

Pi-Sunyer, F Xavier

2002-07-01

It has been suggested that foods with a high glycemic index are detrimental to health and that healthy people should be told to avoid these foods. This paper takes the position that not enough valid scientific data are available to launch a public health campaign to disseminate such a recommendation. This paper explores the glycemic index and its validity and discusses the effect of postprandial glucose and insulin responses on food intake, obesity, type 1 diabetes, and cardiovascular disease. Presented herein are the reasons why it is premature to recommend that the general population avoid foods with a high glycemic index.

Development of a risk index for prediction of abnormal pap test results in Serbia.

PubMed

Vukovic, Dejana; Antic, Ljiljana; Vasiljevic, Mladenko; Antic, Dragan; Matejic, Bojana

2015-01-01

Serbia is one of the countries with highest incidence and mortality rates for cervical cancer in Central and South Eastern Europe. Introducing a risk index could provide a powerful means for targeting groups at high likelihood of having an abnormal cervical smear and increase efficiency of screening. The aim of the present study was to create and assess validity ofa index for prediction of an abnormal Pap test result. The study population was drawn from patients attending Departments for Women's Health in two primary health care centers in Serbia. Out of 525 respondents 350 were randomly selected and data obtained from them were used as the index creation dataset. Data obtained from the remaining 175 were used as an index validation data set. Age at first intercourse under 18, more than 4 sexual partners, history of STD and multiparity were attributed statistical weights 16, 15, 14 and 13, respectively. The distribution of index scores in index-creation data set showed that most respondents had a score 0 (54.9%). In the index-creation dataset mean index score was 10.3 (SD-13.8), and in the validation dataset the mean was 9.1 (SD=13.2). The advantage of such scoring system is that it is simple, consisting of only four elements, so it could be applied to identify women with high risk for cervical cancer that would be referred for further examination.

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

PubMed

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

2015-06-04

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

Validation of a Spanish version of the Spine Functional Index.

PubMed

Cuesta-Vargas, Antonio I; Gabel, Charles P

2014-06-27

The Spine Functional Index (SFI) is a recently published, robust and clinimetrically valid patient reported outcome measure. The purpose of this study was the adaptation and validation of a Spanish-version (SFI-Sp) with cultural and linguistic equivalence. A two stage observational study was conducted. The SFI was cross-culturally adapted to Spanish through double forward and backward translation then validated for its psychometric characteristics. Participants (n = 226) with various spine conditions of >12 weeks duration completed the SFI-Sp and a region specific measure: for the back, the Roland Morris Questionnaire (RMQ) and Backache Index (BADIX); for the neck, the Neck Disability Index (NDI); for general health the EQ-5D and SF-12. The full sample was employed to determine internal consistency, concurrent criterion validity by region and health, construct validity and factor structure. A subgroup (n = 51) was used to determine reliability at seven days. The SFI-Sp demonstrated high internal consistency (α = 0.85) and reliability (r = 0.96). The factor structure was one-dimensional and supported construct validity. Criterion specific validity for function was high with the RMQ (r = 0.79), moderate with the BADIX (r = 0.59) and low with the NDI (r = 0.46). For general health it was low with the EQ-5D and inversely correlated (r = -0.42) and fair with the Physical and Mental Components of the SF-12 and inversely correlated (r = -0.56 and r = -0.48), respectively. The study limitations included the lack of longitudinal data regarding other psychometric properties, specifically responsiveness. The SFI-Sp was demonstrated as a valid and reliable spine-regional outcome measure. The psychometric properties were comparable to and supported those of the English-version, however further longitudinal investigations are required.

Construct validity of the PROMIS® sexual function and satisfaction measures in patients with cancer

PubMed Central

2013-01-01

Background With data from a diverse sample of patients either in treatment for cancer or post-treatment for cancer, we examine inter-domain and cross-domain correlations among the core domains of the Patient-Reported Outcomes Measurement Information System Sexual Function and Satisfaction measures (PROMIS® SexFS) and the corresponding domains from conceptually-similar measures of sexual function, the International Index of Erectile Function and the Female Sexual Function Index. Findings Men (N=389) and women (N=430) were recruited from a tumor registry, oncology clinics, and an internet panel. The PROMIS SexFS, International Index of Erectile Function, and Female Sexual Function Index were used to collect participants’ self-reported sexual function. The domains shared among the measures include desire/interest in sexual activity, lubrication and vaginal discomfort/pain (women), erectile function (men), orgasm, and satisfaction. We examined correlations among different domains within the same instrument (discriminant validity) and correlations among similar domains measured by different instruments (convergent validity). Correlations demonstrating discriminant validity ranged from 0.38 to 0.73 for men and 0.48 to 0.74 for women, while correlations demonstrating convergent validity ranged from 0.62 to 0.83 for men and 0.71 to 0.92 for women. As expected, correlations demonstrating convergent validity were higher than correlations demonstrating discriminant validity, with one exception (orgasm for men). Conclusions Construct validity was supported by convergent and discriminant validity in a diverse sample of patients with cancer. For patients with cancer who may or may not have sexual dysfunction, the PROMIS SexFS measures provide a comprehensive assessment of key domains of sexual function and satisfaction. PMID:23497200

A motor speech assessment for children with severe speech disorders: reliability and validity evidence.

PubMed

Strand, Edythe A; McCauley, Rebecca J; Weigand, Stephen D; Stoeckel, Ruth E; Baas, Becky S

2013-04-01

In this article, the authors report reliability and validity evidence for the Dynamic Evaluation of Motor Speech Skill (DEMSS), a new test that uses dynamic assessment to aid in the differential diagnosis of childhood apraxia of speech (CAS). Participants were 81 children between 36 and 79 months of age who were referred to the Mayo Clinic for diagnosis of speech sound disorders. Children were given the DEMSS and a standard speech and language test battery as part of routine evaluations. Subsequently, intrajudge, interjudge, and test-retest reliability were evaluated for a subset of participants. Construct validity was explored for all 81 participants through the use of agglomerative cluster analysis, sensitivity measures, and likelihood ratios. The mean percentage of agreement for 171 judgments was 89% for test-retest reliability, 89% for intrajudge reliability, and 91% for interjudge reliability. Agglomerative hierarchical cluster analysis showed that total DEMSS scores largely differentiated clusters of children with CAS vs. mild CAS vs. other speech disorders. Positive and negative likelihood ratios and measures of sensitivity and specificity suggested that the DEMSS does not overdiagnose CAS but sometimes fails to identify children with CAS. The value of the DEMSS in differential diagnosis of severe speech impairments was supported on the basis of evidence of reliability and validity.

Subtypes of firesetters.

PubMed

Dalhuisen, Lydia; Koenraadt, Frans; Liem, Marieke

2017-02-01

Prior research has classified firesetters by motive. The multi-trajectory theory of adult firesetting (M-TTAF) takes a more aetiological perspective, differentiating between five hypothesised trajectories towards firesetting: antisocial cognition, grievance, fire interest, emotionally expressive/need for recognition and multifaceted trajectories. The objective of this study was to validate the five routes to firesetting as proposed in the M-TTAF. All 389 adult firesetters referred for forensic mental health assessment to one central clinic in the Netherlands between 1950 and 2012 were rated on variables linked to the M-TTAF. Cluster analysis was then applied. A reliable cluster solution emerged revealing five subtypes of firesetters - labelled instrumental, reward, multi-problem, disturbed relationship and disordered. Significant differences were observed regarding both offender and offence characteristics. Our five-cluster solution with five subtypes of firesetters partially validates the proposed M-TTAF trajectories and suggests that for offenders with and without mental disorder, this classification may be useful. If further validated with larger and more diverse samples, the M-TTAF could provide guidance on staging evidence-based treatment. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Translation, Adaptation, and Preliminary Validation of the Female Sexual Function Index into Spanish (Colombia).

PubMed

Vallejo-Medina, Pablo; Pérez-Durán, Claudia; Saavedra-Roa, Alejandro

2018-04-01

The Female Sexual Function Index (FSFI) subjectively explores the dimensions of female sexual functioning. This research undertook to adapt and validate the FSFI to Spanish language in a Colombian sample. To this effect, this study was conducted in two steps, namely: (1) cultural adaptation of the scale with the collaboration of seven experts; and (2) preliminary validation of the scale in a sample of 925 participants. Reliability indices were appropriate in this sample, and external validity in relation to other measures showed significant relationships. Findings suggest that the FSFI is reliable and valid in Spanish for a Colombian population. Further research is needed to establish the test-retest reliability and discriminant validity of this Spanish version.

Development and Validation of a qRT-PCR Classifier for Lung Cancer Prognosis

PubMed Central

Chen, Guoan; Kim, Sinae; Taylor, Jeremy MG; Wang, Zhuwen; Lee, Oliver; Ramnath, Nithya; Reddy, Rishindra M; Lin, Jules; Chang, Andrew C; Orringer, Mark B; Beer, David G

2011-01-01

Purpose This prospective study aimed to develop a robust and clinically-applicable method to identify high-risk early stage lung cancer patients and then to validate this method for use in future translational studies. Patients and Methods Three published Affymetrix microarray data sets representing 680 primary tumors were used in the survival-related gene selection procedure using clustering, Cox model and random survival forest (RSF) analysis. A final set of 91 genes was selected and tested as a predictor of survival using a qRT-PCR-based assay utilizing an independent cohort of 101 lung adenocarcinomas. Results The RSF model built from 91 genes in the training set predicted patient survival in an independent cohort of 101 lung adenocarcinomas, with a prediction error rate of 26.6%. The mortality risk index (MRI) was significantly related to survival (Cox model p < 0.00001) and separated all patients into low, medium, and high-risk groups (HR = 1.00, 2.82, 4.42). The MRI was also related to survival in stage 1 patients (Cox model p = 0.001), separating patients into low, medium, and high-risk groups (HR = 1.00, 3.29, 3.77). Conclusions The development and validation of this robust qRT-PCR platform allows prediction of patient survival with early stage lung cancer. Utilization will now allow investigators to evaluate it prospectively by incorporation into new clinical trials with the goal of personalized treatment of lung cancer patients and improving patient survival. PMID:21792073

A comparison of four embedded validity indices for the RBANS in a memory disorders clinic.

PubMed

Paulson, Daniel; Horner, Michael David; Bachman, David

2015-05-01

This examination of four embedded validity indices for the Repeated Battery for the Assessment of Neuropsychological Status (RBANS) explores the potential utility of integrating cognitive and self-reported depressive measures. Examined indices include the proposed RBANS Performance Validity Index (RBANS PVI) and the Charleston Revised Index of Effort for the RBANS (CRIER). The CRIER represented the novel integration of cognitive test performance and depression self-report information. The sample included 234 patients without dementia who could be identified as having demonstrated either valid or invalid responding, based on standardized criteria. Sensitivity and specificity for invalid responding varied widely, with the CRIER emerging as the best all-around index (sensitivity = 0.84, specificity = 0.90, AUC = 0.94). Findings support the use of embedded response validity indices, and suggest that the integration of cognitive and self-report depression data may optimize detection of invalid responding among older Veterans. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

iNJclust: Iterative Neighbor-Joining Tree Clustering Framework for Inferring Population Structure.

PubMed

Limpiti, Tulaya; Amornbunchornvej, Chainarong; Intarapanich, Apichart; Assawamakin, Anunchai; Tongsima, Sissades

2014-01-01

Understanding genetic differences among populations is one of the most important issues in population genetics. Genetic variations, e.g., single nucleotide polymorphisms, are used to characterize commonality and difference of individuals from various populations. This paper presents an efficient graph-based clustering framework which operates iteratively on the Neighbor-Joining (NJ) tree called the iNJclust algorithm. The framework uses well-known genetic measurements, namely the allele-sharing distance, the neighbor-joining tree, and the fixation index. The behavior of the fixation index is utilized in the algorithm's stopping criterion. The algorithm provides an estimated number of populations, individual assignments, and relationships between populations as outputs. The clustering result is reported in the form of a binary tree, whose terminal nodes represent the final inferred populations and the tree structure preserves the genetic relationships among them. The clustering performance and the robustness of the proposed algorithm are tested extensively using simulated and real data sets from bovine, sheep, and human populations. The result indicates that the number of populations within each data set is reasonably estimated, the individual assignment is robust, and the structure of the inferred population tree corresponds to the intrinsic relationships among populations within the data.

Low oxidation state aluminum-containing cluster anions: Cp{sup ∗}Al{sub n}H{sup −}, n = 1–3

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

Zhang, Xinxing; Ganteför, Gerd; Bowen, Kit, E-mail: AKandalam@wcupa.edu, E-mail: kbowen@jhu.edu

Three new, low oxidation state, aluminum-containing cluster anions, Cp*Al{sub n}H{sup −}, n = 1–3, were prepared via reactions between aluminum hydride cluster anions, Al{sub n}H{sub m}{sup −}, and Cp*H ligands. These were characterized by mass spectrometry, anion photoelectron spectroscopy, and density functional theory based calculations. Agreement between the experimentally and theoretically determined vertical detachment energies and adiabatic detachment energies validated the computed geometrical structures. Reactions between aluminum hydride cluster anions and ligands provide a new avenue for discovering low oxidation state, ligated aluminum clusters.

Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

PubMed

Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2013-07-01

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Psychometric Properties of a Screening Instrument for Domestic Violence in a Sample of Iranian Women

PubMed Central

Azadarmaki, Taghi; Kassani, Aziz; Menati, Rostam; Hassanzadeh, Jafar; Menati, Walieh

2016-01-01

Background Domestic violence against women is regarded as an important health problem among women and a serious concern in issues related to human rights. To date, a few screening tools for domestic violence exist for Iranian married women, but they assess only some of the domestic violence components. Objectives The present study aimed to design and determine the validity and reliability of a screening instrument for domestic violence in a sample of Iranian women. Materials and Methods The present study was a cross-sectional psychometric evaluation conducted on 350 married women in Ilam, Iran, in 2014. The samples were selected through multistage sampling and the main method was cluster sampling. A 20-item, self-administered questionnaire was validated by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). An Eigen value > 1 and a loading factor > 0.3 for each component were considered as indices for extracting domestic violence components. Reliability was calculated by test-retest and Cronbach’s alpha. Also, the content validity index (CVI) and content validity ratio (CVR) were used to measure content validity. The data were analyzed using SPSS-13 and LISREL 8.8 software programs. Results The self-administered instrument was completed by 334 women. The CFA and EFA methods confirmed embedding items and the three-factor structure of the instrument including psychological, physical, and sexual violence, which explained 66% of the total variance of the domestic violence. The ICC and Cronbach’s alpha coefficients were > 0.7 for the components of the questionnaire. The test-retest also revealed strong correlations for each of the domestic violence components (r > 0.6). Conclusions The used instrument for measuring domestic violence had desirable validity and reliability and can be used as a suitable instrument in health and social researches in the local population. PMID:27331052

Development of a two-fluid drag law for clustered particles using direct numerical simulation and validation through experiments

NASA Astrophysics Data System (ADS)

Abbasi Baharanchi, Ahmadreza

This dissertation focused on development and utilization of numerical and experimental approaches to improve the CFD modeling of fluidization flow of cohesive micron size particles. The specific objectives of this research were: (1) Developing a cluster prediction mechanism applicable to Two-Fluid Modeling (TFM) of gas-solid systems (2) Developing more accurate drag models for Two-Fluid Modeling (TFM) of gas-solid fluidization flow with the presence of cohesive interparticle forces (3) using the developed model to explore the improvement of accuracy of TFM in simulation of fluidization flow of cohesive powders (4) Understanding the causes and influential factor which led to improvements and quantification of improvements (5) Gathering data from a fast fluidization flow and use these data for benchmark validations. Simulation results with two developed cluster-aware drag models showed that cluster prediction could effectively influence the results in both the first and second cluster-aware models. It was proven that improvement of accuracy of TFM modeling using three versions of the first hybrid model was significant and the best improvements were obtained by using the smallest values of the switch parameter which led to capturing the smallest chances of cluster prediction. In the case of the second hybrid model, dependence of critical model parameter on only Reynolds number led to the fact that improvement of accuracy was significant only in dense section of the fluidized bed. This finding may suggest that a more sophisticated particle resolved DNS model, which can span wide range of solid volume fraction, can be used in the formulation of the cluster-aware drag model. The results of experiment suing high speed imaging indicated the presence of particle clusters in the fluidization flow of FCC inside the riser of FIU-CFB facility. In addition, pressure data was successfully captured along the fluidization column of the facility and used as benchmark validation data for the second hybrid model developed in the present dissertation. It was shown the second hybrid model could predict the pressure data in the dense section of the fluidization column with better accuracy.

Structural Validity of the Life Regard Index

ERIC Educational Resources Information Center

Steger, Michael F.

2007-01-01

Counselors and researchers interested in examining meaning in life often use the Life Regard Index (LRI; J. Battista & R. Almond, 1973). In this study, confirmatory factor analyses (CFAs) of several factor models based on J. Battista & R. Almond's work failed to support the structural validity of the LRI. CFA results suggested an influence of…

Construct Validity of the Anxiety Sensitivity Index-3 in Clinical Samples

ERIC Educational Resources Information Center

Kemper, Christoph J.; Lutz, Johannes; Bahr, Tobias; Ruddel, Heinz; Hock, Michael

2012-01-01

Using two clinical samples of patients, the presented studies examined the construct validity of the recently revised Anxiety Sensitivity Index-3 (ASI-3). Confirmatory factor analyses established a clear three-factor structure that corresponds to the postulated subdivision of the construct into correlated somatic, social, and cognitive components.…

Validation of simple indexes to assess insulin sensitivity during pregnancy in Wistar and Sprague-Dawley rats.

PubMed

Cacho, J; Sevillano, J; de Castro, J; Herrera, E; Ramos, M P

2008-11-01

Insulin resistance plays a role in the pathogenesis of diabetes, including gestational diabetes. The glucose clamp is considered the gold standard for determining in vivo insulin sensitivity, both in human and in animal models. However, the clamp is laborious, time consuming and, in animals, requires anesthesia and collection of multiple blood samples. In human studies, a number of simple indexes, derived from fasting glucose and insulin levels, have been obtained and validated against the glucose clamp. However, these indexes have not been validated in rats and their accuracy in predicting altered insulin sensitivity remains to be established. In the present study, we have evaluated whether indirect estimates based on fasting glucose and insulin levels are valid predictors of insulin sensitivity in nonpregnant and 20-day-pregnant Wistar and Sprague-Dawley rats. We have analyzed the homeostasis model assessment of insulin resistance (HOMA-IR), the quantitative insulin sensitivity check index (QUICKI), and the fasting glucose-to-insulin ratio (FGIR) by comparing them with the insulin sensitivity (SI(Clamp)) values obtained during the hyperinsulinemic-isoglycemic clamp. We have performed a calibration analysis to evaluate the ability of these indexes to accurately predict insulin sensitivity as determined by the reference glucose clamp. Finally, to assess the reliability of these indexes for the identification of animals with impaired insulin sensitivity, performance of the indexes was analyzed by receiver operating characteristic (ROC) curves in Wistar and Sprague-Dawley rats. We found that HOMA-IR, QUICKI, and FGIR correlated significantly with SI(Clamp), exhibited good sensitivity and specificity, accurately predicted SI(Clamp), and yielded lower insulin sensitivity in pregnant than in nonpregnant rats. Together, our data demonstrate that these indexes provide an easy and accurate measure of insulin sensitivity during pregnancy in the rat.

Validation of an obstetric comorbidity index in an external population.

PubMed

Metcalfe, A; Lix, L M; Johnson, J-A; Currie, G; Lyon, A W; Bernier, F; Tough, S C

2015-12-01

An obstetric comorbidity index has been developed recently with superior performance characteristics relative to general comorbidity measures in an obstetric population. This study aimed to externally validate this index and to examine the impact of including hospitalisation/delivery records only when estimating comorbidity prevalence and discriminative performance of the obstetric comorbidity index. Validation study. Alberta, Canada. Pregnant women who delivered a live or stillborn infant in hospital (n = 5995). Administrative databases were linked to create a population-based cohort. Comorbid conditions were identified from diagnoses for the delivery hospitalisation, all hospitalisations and all healthcare contacts (i.e. hospitalisations, emergency room visits and physician visits) that occurred during pregnancy and 3 months pre-conception. Logistic regression was used to test the discriminative performance of the comorbidity index. Maternal end-organ damage and extended length of stay for delivery. Although prevalence estimates for comorbid conditions were consistently lower in delivery records and hospitalisation data than in data for all healthcare contacts, the discriminative performance of the comorbidity index was constant for maternal end-organ damage [all healthcare contacts area under the receiver operating characteristic curve (AUC) = 0.70; hospitalisation data AUC = 0.67; delivery data AUC = 0.65] and extended length of stay for delivery (all healthcare contacts AUC = 0.60; hospitalisation data AUC = 0.58; delivery data AUC = 0.58). The obstetric comorbidity index shows similar performance characteristics in an external population and is a valid measure of comorbidity in an obstetric population. Furthermore, the discriminative performance of the comorbidity index was similar for comorbidities ascertained at the time of delivery, in hospitalisation data or through all healthcare contacts. © 2015 The Authors. BJOG An International Journal of Obstetrics and Gynaecology published by John Wiley & Sons Ltd on behalf of Royal College of Obstetricians and Gynaecologists.

Measurement-based quantum computation on two-body interacting qubits with adiabatic evolution.

PubMed

Kyaw, Thi Ha; Li, Ying; Kwek, Leong-Chuan

2014-10-31

A cluster state cannot be a unique ground state of a two-body interacting Hamiltonian. Here, we propose the creation of a cluster state of logical qubits encoded in spin-1/2 particles by adiabatically weakening two-body interactions. The proposal is valid for any spatial dimensional cluster states. Errors induced by thermal fluctuations and adiabatic evolution within finite time can be eliminated ensuring fault-tolerant quantum computing schemes.

Reliability and Validity of the Chinese Version of FACIT-AI, a New Tool for Assessing Quality of Life in Patients with Malignant Ascites.

PubMed

Lou, Yanni; Lu, Linghui; Li, Yuan; Liu, Meng; Bredle, Jason M; Jia, Liqun

2015-10-01

The study objective was to determine the reliability and validity of the Chinese version of the Functional Assessment of Chronic Illness Therapy - Ascites Index (FACIT-AI). A forward-backward translation procedure was adopted to develop the Chinese version of the FACIT-AI, which was tested in 69 patients with malignant ascites. Cronbach's α, split-half reliability, and test-retest reliability were used to assess the reliability of the scale. The content validity index was used to assess the content validity, while factor analysis was used for construct validity and correlation analysis was used for criterion validity. The Cronbach's α was 0.772 for the total scale, and the split-half reliability was 0.693. The test-retest correlation was 0.972. The content validity index for the scale was 0.8-1.0. Four factors were extracted by factor analysis, and these contributed 63.51% of the total variance. Item-total correlations ranged from 0.591 to 0.897, and these were correlated with visual analog scale scores (correlation coefficient, 0.889; P<0.01). The Chinese version of the FACIT-AI has good reliability and validity and can be used as a tool to measure quality of life in Chinese patients with malignant ascites.

Effectiveness and feasibility of long-lasting insecticide-treated curtains and water container covers for dengue vector control in Colombia: a cluster randomised trial.

PubMed

Quintero, Juliana; García-Betancourt, Tatiana; Cortés, Sebastian; García, Diana; Alcalá, Lucas; González-Uribe, Catalina; Brochero, Helena; Carrasquilla, Gabriel

2015-02-01

Long-lasting insecticide-treated net (LLIN) window and door curtains alone or in combination with LLIN water container covers were analysed regarding effectiveness in reducing dengue vector density, and feasibility of the intervention. A cluster randomised trial was conducted in an urban area of Colombia comparing 10 randomly selected control and 10 intervention clusters. In control clusters, routine vector control activities were performed. The intervention delivered first, LLIN curtains (from July to August 2013) and secondly, water container covers (from October to March 2014). Cross-sectional entomological surveys were carried out at baseline (February 2013 to June 2013), 9 weeks after the first intervention (August to October 2013), and 4-6 weeks after the second intervention (March to April 2014). Curtains were installed in 922 households and water container covers in 303 households. The Breteau index (BI) fell from 14 to 6 in the intervention group and from 8 to 5 in the control group. The additional intervention with LLIN covers for water containers showed a significant reduction in pupae per person index (PPI) (p=0.01). In the intervention group, the PPI index showed a clear decline of 71% compared with 25% in the control group. Costs were high but options for cost savings were identified. Short term impact evaluation indicates that the intervention package can reduce dengue vector density but sustained effect will depend on multiple factors. © The author 2015. The World Health Organization has granted Oxford University Press permission for the reproduction of this article.

Construction and validation of a measure of integrative well-being in seven languages: the Pemberton Happiness Index.

PubMed

Hervás, Gonzalo; Vázquez, Carmelo

2013-04-22

We introduce the Pemberton Happiness Index (PHI), a new integrative measure of well-being in seven languages, detailing the validation process and presenting psychometric data. The scale includes eleven items related to different domains of remembered well-being (general, hedonic, eudaimonic, and social well-being) and ten items related to experienced well-being (i.e., positive and negative emotional events that possibly happened the day before); the sum of these items produces a combined well-being index. A distinctive characteristic of this study is that to construct the scale, an initial pool of items, covering the remembered and experienced well-being domains, were subjected to a complete selection and validation process. These items were based on widely used scales (e.g., PANAS, Satisfaction With Life Scale, Subjective Happiness Scale, and Psychological Well-Being Scales). Both the initial items and reference scales were translated into seven languages and completed via Internet by participants (N = 4,052) aged 16 to 60 years from nine countries (Germany, India, Japan, Mexico, Russia, Spain, Sweden, Turkey, and USA). Results from this initial validation study provided very good support for the psychometric properties of the PHI (i.e., internal consistency, a single-factor structure, and convergent and incremental validity). Given the PHI's good psychometric properties, this simple and integrative index could be used as an instrument to monitor changes in well-being. We discuss the utility of this integrative index to explore well-being in individuals and communities.

Validity of triglyceride-glucose index as an indicator for metabolic syndrome in children and adolescents: the CASPIAN-V study.

PubMed

Angoorani, Pooneh; Heshmat, Ramin; Ejtahed, Hanieh-Sadat; Motlagh, Mohammad Esmaeil; Ziaodini, Hasan; Taheri, Majzoubeh; Aminaee, Tahereh; Goodarzi, Azam; Qorbani, Mostafa; Kelishadi, Roya

2018-02-16

The purpose of this study was to determine the cut-off values of triglycerides and glucose (TyG) index as one of the indirect indices for metabolic syndrome (MetS) in a pediatric population. This national study was conducted in 2015 on 14400 students, aged 7-18 years. They were selected by random cluster sampling from 30 provinces of our country during the fifth survey of a national school-based surveillance program. MetS was defined based on the Adult Treatment Panel III (ATP III) criteria modified for the pediatric age group. The cut-off values of TyG index for MetS were obtained using the receiver operation characteristic (ROC) curve analysis by gender and age groups. Totally, 3843 students (52.3% boys) with mean (SD) age of 12.45 (3.04) years were assessed. The area under the ROC curve of TyG index for MetS was 0.83 in total participants. According to the ATP III criteria the cut-off values of the TyG index were 8.33 (8.21-8.45) in total students, 8.47 (8.36-8.58) in boys, and 8.33 (8.18-8.48) in girls. In the 7-12 and 13-18 years' age groups, these values were 8.47 (8.32-8.63) and 8.34 (8.22-8.45) in total, 8.39 (8.26-8.52) and 8.47 (8.33-8.61) in boys, 8.33 (8.11-8.55) and 8.35 (8.22-8.47) in girls, respectively. The findings of this study can be clinically helpful for screening MetS in children and adolescents but the effectiveness of these criteria needs to be evaluated by further longitudinal surveys. Level V, cross-sectional descriptive study (National surveillance study).

Discovery of large-scale diffuse radio emission in low-mass galaxy cluster Abell 1931

NASA Astrophysics Data System (ADS)

Brüggen, M.; Rafferty, D.; Bonafede, A.; van Weeren, R. J.; Shimwell, T.; Intema, H.; Röttgering, H.; Brunetti, G.; Di Gennaro, G.; Savini, F.; Wilber, A.; O'Sullivan, S.; Ensslin, T. A.; De Gasperin, F.; Hoeft, M.

2018-04-01

Extended, steep-spectrum radio synchrotron sources are pre-dominantly found in massive galaxy clusters as opposed to groups. LOFAR Two-Metre Sky Survey images have revealed a diffuse, ultra-steep spectrum radio source in the low-mass cluster Abell 1931. The source has a fairly irregular morphology with a largest linear size of about 550 kpc. The source is only seen in LOFAR observations at 143 MHz and GMRT observations at 325 MHz. The spectral index of the total source between 143 MHz and 325 MHz is α _{143}^{325} = -2.86 ± 0.36. The source remains invisible in Very Large Array (1-2 GHz) observations as expected given the spectral index. Chandra X-ray observations of the cluster revealed a bolometric luminosity of LX = (1.65 ± 0.39) × 1043 erg s-1 and a temperature of 2.92_{-0.87}^{+1.89} keV which implies a mass of around ˜1014M⊙. We conclude that the source is a remnant radio galaxy that has shut off around 200 Myr ago. The brightest cluster galaxy, a radio-loud elliptical galaxy, could be the source for this extinct source. Unlike remnant sources studied in the literature, our source has a steep spectrum at low radio frequencies. Studying such remnant radio galaxies at low radio frequencies is important for understanding the scarcity of such sources and their role in feedback processes.

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

NASA Astrophysics Data System (ADS)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Speeding up the Consensus Clustering methodology for microarray data analysis

PubMed Central

2011-01-01

Background The inference of the number of clusters in a dataset, a fundamental problem in Statistics, Data Analysis and Classification, is usually addressed via internal validation measures. The stated problem is quite difficult, in particular for microarrays, since the inferred prediction must be sensible enough to capture the inherent biological structure in a dataset, e.g., functionally related genes. Despite the rich literature present in that area, the identification of an internal validation measure that is both fast and precise has proved to be elusive. In order to partially fill this gap, we propose a speed-up of Consensus (Consensus Clustering), a methodology whose purpose is the provision of a prediction of the number of clusters in a dataset, together with a dissimilarity matrix (the consensus matrix) that can be used by clustering algorithms. As detailed in the remainder of the paper, Consensus is a natural candidate for a speed-up. Results Since the time-precision performance of Consensus depends on two parameters, our first task is to show that a simple adjustment of the parameters is not enough to obtain a good precision-time trade-off. Our second task is to provide a fast approximation algorithm for Consensus. That is, the closely related algorithm FC (Fast Consensus) that would have the same precision as Consensus with a substantially better time performance. The performance of FC has been assessed via extensive experiments on twelve benchmark datasets that summarize key features of microarray applications, such as cancer studies, gene expression with up and down patterns, and a full spectrum of dimensionality up to over a thousand. Based on their outcome, compared with previous benchmarking results available in the literature, FC turns out to be among the fastest internal validation methods, while retaining the same outstanding precision of Consensus. Moreover, it also provides a consensus matrix that can be used as a dissimilarity matrix, guaranteeing the same performance as the corresponding matrix produced by Consensus. We have also experimented with the use of Consensus and FC in conjunction with NMF (Nonnegative Matrix Factorization), in order to identify the correct number of clusters in a dataset. Although NMF is an increasingly popular technique for biological data mining, our results are somewhat disappointing and complement quite well the state of the art about NMF, shedding further light on its merits and limitations. Conclusions In summary, FC with a parameter setting that makes it robust with respect to small and medium-sized datasets, i.e, number of items to cluster in the hundreds and number of conditions up to a thousand, seems to be the internal validation measure of choice. Moreover, the technique we have developed here can be used in other contexts, in particular for the speed-up of stability-based validation measures. PMID:21235792

Recent status scores for version 6 of the Addiction Severity Index (ASI-6).

PubMed

Cacciola, John S; Alterman, Arthur I; Habing, Brian; McLellan, A Thomas

2011-09-01

To describe the derivation of recent status scores (RSSs) for version 6 of the Addiction Severity Index (ASI-6). 118 ASI-6 recent status items were subjected to nonparametric item response theory (NIRT) analyses followed by confirmatory factor analysis (CFA). Generalizability and concurrent validity of the derived scores were determined. A total of 607 recent admissions to variety of substance abuse treatment programs constituted the derivation sample; a subset (n = 252) comprised the validity sample. The ASI-6 interview and a validity battery of primarily self-report questionnaires that included at least one measure corresponding to each of the seven ASI domains were administered. Nine summary scales describing recent status that achieved or approached both high scalability and reliability were derived; one scale for each of six areas (medical, employment/finances, alcohol, drug, legal, psychiatric) and three scales for the family/social area. Intercorrelations among the RSSs also supported the multi-dimensionality of the ASI-6. Concurrent validity analyses yielded strong evidence supporting the validity of six of the RSSs (medical, alcohol, drug, employment, family/social problems, psychiatric). Evidence was weaker for the legal, family/social support and child problems RSSs. Generalizability analyses of the scales to males versus females and whites versus blacks supported the comparability of the findings, with slight exceptions. The psychometric analyses to derive Addiction Severity Index version 6 recent status scores support the multi-dimensionality of the Addiction Severity Index version 6 (i.e. the relative independence of different life functioning areas), consistent with research on earlier editions of the instrument. In general, the Addiction Severity Index version 6 scales demonstrate acceptable scalability, reliability and concurrent validity. While questions remain about the generalizability of some scales to population subgroups, the overall findings coupled with updated and more extensive content in the Addiction Severity Index version 6 support its use in clinical practice and research. © 2011 The Authors, Addiction © 2011 Society for the Study of Addiction.

Pathological Gambling in Parkinson's disease patients: Dopaminergic medication or personality traits fault?

PubMed

Brusa, L; Pavino, V; Massimetti, M C; Ceravolo, R; Stefani, S; Stanzione, P

2016-07-15

Impulse control disorders (ICDs) are clinically relevant in Parkinson disease (PD) patients, with an established association with PD medication. Aim of our study was to study whether the increased frequency of pathological gambling (PG), reported in subgroups of PD patients, is related to specific personality tracts additional to dopaminergic medications. Thirty-seven PD patients with a personal history of PG where enrolled. Twenty one PD patients, matched for disease and dopaminergic therapy, never experiencing PG, were enrolled as controls. All subjects were tested with the Minnesota Multiphasic Inventory Personality scales (MMPI-2). Our data showed that PD group with PG exhibited significantly higher mean values of the three validity scales in comparison to the non-PG-PD group, demonstrating an higher tendency to lie. Content scales showed a significant increase of cynicism and bizarre ideation scales score in the PG-PD group, not exhibiting pathological values at the validity scales, (p: 0.02) in comparison to non-PG PD patients. According to our results, PG seems to be associated with precise personality tracts. Personality profiles of cluster A personality disturbances - Axys 2 according with DSM-5 TR (paranoid type) at MMPI-2 might be a warning index helpful in selecting dopaminergic treatment, to avoid subsequent ICDs appearance. Copyright © 2016 Elsevier B.V. All rights reserved.

Relationships of health literacy, health behavior, and health status regarding infectious respiratory diseases: application of a skill-based measure.

PubMed

Sun, Xinying; Yang, Shuaishuai; Fisher, Edwin B; Shi, Yuhui; Wang, Yanling; Zeng, Qingqi; Ji, Ying; Chang, Chun; Du, Weijing

2014-01-01

This study aimed to explain the relationships among health literacy, health behavior, and health status, using a newly developed skills-based measure of health literacy regarding respiratory infectious diseases. This instrument was designed to measure individuals' reading, understanding, and calculating ability, as well as their oral communication and Internet-based information-seeking abilities. A pilot survey was conducted with 489 residents in Beijing, China, to test the reliability and validity of the new measure. Next, a larger study with 3,222 residents in three cities with multistage stratified cluster sampling was implemented to validate a latent variable model (goodness of fit index=0.918, root mean square residual=0.076). In this model higher educational attainment (β=0.356) and more health knowledge (β=0.306) were positively and directly associated with greater health literacy skill, while age was negatively associated with it (β=-0.341). Age (β=0.201) and health knowledge (β=0.246) had positive and direct relationship with health behavior, which was, in turn, positively associated with health status (β=0.209). The results illustrate the complex relationships among these constructs and should be considered when developing respiratory intervention strategies to promote health behavior and health status.

WEIGHING GALAXY CLUSTERS WITH GAS. I. ON THE METHODS OF COMPUTING HYDROSTATIC MASS BIAS

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

Lau, Erwin T.; Nagai, Daisuke; Nelson, Kaylea, E-mail: erwin.lau@yale.edu

2013-11-10

Mass estimates of galaxy clusters from X-ray and Sunyeav-Zel'dovich observations assume the intracluster gas is in hydrostatic equilibrium with their gravitational potential. However, since galaxy clusters are dynamically active objects whose dynamical states can deviate significantly from the equilibrium configuration, the departure from the hydrostatic equilibrium assumption is one of the largest sources of systematic uncertainties in cluster cosmology. In the literature there have been two methods for computing the hydrostatic mass bias based on the Euler and the modified Jeans equations, respectively, and there has been some confusion about the validity of these two methods. The word 'Jeans' wasmore » a misnomer, which incorrectly implies that the gas is collisionless. To avoid further confusion, we instead refer these methods as 'summation' and 'averaging' methods respectively. In this work, we show that these two methods for computing the hydrostatic mass bias are equivalent by demonstrating that the equation used in the second method can be derived from taking spatial averages of the Euler equation. Specifically, we identify the correspondences of individual terms in these two methods mathematically and show that these correspondences are valid to within a few percent level using hydrodynamical simulations of galaxy cluster formation. In addition, we compute the mass bias associated with the acceleration of gas and show that its contribution is small in the virialized regions in the interior of galaxy clusters, but becomes non-negligible in the outskirts of massive galaxy clusters. We discuss future prospects of understanding and characterizing biases in the mass estimate of galaxy clusters using both hydrodynamical simulations and observations and their implications for cluster cosmology.« less

Weighing Galaxy Clusters with Gas. I. On the Methods of Computing Hydrostatic Mass Bias

NASA Astrophysics Data System (ADS)

Lau, Erwin T.; Nagai, Daisuke; Nelson, Kaylea

2013-11-01

Mass estimates of galaxy clusters from X-ray and Sunyeav-Zel'dovich observations assume the intracluster gas is in hydrostatic equilibrium with their gravitational potential. However, since galaxy clusters are dynamically active objects whose dynamical states can deviate significantly from the equilibrium configuration, the departure from the hydrostatic equilibrium assumption is one of the largest sources of systematic uncertainties in cluster cosmology. In the literature there have been two methods for computing the hydrostatic mass bias based on the Euler and the modified Jeans equations, respectively, and there has been some confusion about the validity of these two methods. The word "Jeans" was a misnomer, which incorrectly implies that the gas is collisionless. To avoid further confusion, we instead refer these methods as "summation" and "averaging" methods respectively. In this work, we show that these two methods for computing the hydrostatic mass bias are equivalent by demonstrating that the equation used in the second method can be derived from taking spatial averages of the Euler equation. Specifically, we identify the correspondences of individual terms in these two methods mathematically and show that these correspondences are valid to within a few percent level using hydrodynamical simulations of galaxy cluster formation. In addition, we compute the mass bias associated with the acceleration of gas and show that its contribution is small in the virialized regions in the interior of galaxy clusters, but becomes non-negligible in the outskirts of massive galaxy clusters. We discuss future prospects of understanding and characterizing biases in the mass estimate of galaxy clusters using both hydrodynamical simulations and observations and their implications for cluster cosmology.

The relative vertex clustering value - a new criterion for the fast discovery of functional modules in protein interaction networks

PubMed Central

2015-01-01

Background Cellular processes are known to be modular and are realized by groups of proteins implicated in common biological functions. Such groups of proteins are called functional modules, and many community detection methods have been devised for their discovery from protein interaction networks (PINs) data. In current agglomerative clustering approaches, vertices with just a very few neighbors are often classified as separate clusters, which does not make sense biologically. Also, a major limitation of agglomerative techniques is that their computational efficiency do not scale well to large PINs. Finally, PIN data obtained from large scale experiments generally contain many false positives, and this makes it hard for agglomerative clustering methods to find the correct clusters, since they are known to be sensitive to noisy data. Results We propose a local similarity premetric, the relative vertex clustering value, as a new criterion allowing to decide when a node can be added to a given node's cluster and which addresses the above three issues. Based on this criterion, we introduce a novel and very fast agglomerative clustering technique, FAC-PIN, for discovering functional modules and protein complexes from a PIN data. Conclusions Our proposed FAC-PIN algorithm is applied to nine PIN data from eight different species including the yeast PIN, and the identified functional modules are validated using Gene Ontology (GO) annotations from DAVID Bioinformatics Resources. Identified protein complexes are also validated using experimentally verified complexes. Computational results show that FAC-PIN can discover functional modules or protein complexes from PINs more accurately and more efficiently than HC-PIN and CNM, the current state-of-the-art approaches for clustering PINs in an agglomerative manner. PMID:25734691

Modularization of biochemical networks based on classification of Petri net t-invariants.

PubMed

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.

Modularization of biochemical networks based on classification of Petri net t-invariants

PubMed Central

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-01-01

Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. Results We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. Conclusion We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis. PMID:18257938

The BioPrompt-box: an ontology-based clustering tool for searching in biological databases.

PubMed

Corsi, Claudio; Ferragina, Paolo; Marangoni, Roberto

2007-03-08

High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This scenario generates severe problems not only at indexing time, where suitable algorithmic techniques for data indexing and retrieval are required, but also at query time, since a user query may produce such a large set of results that their browsing and "understanding" becomes humanly impractical. This problem is well known to the Web community, where a new generation of Web search engines is being developed, like Vivisimo. These tools organize on-the-fly the results of a user query in a hierarchy of labeled folders that ease their browsing and knowledge extraction. We investigate this approach on biological data, and propose the so called The BioPrompt-boxsoftware system which deploys ontology-driven clustering strategies for making the searching process of biologists more efficient and effective. The BioPrompt-box (Bpb) defines a document as a biological sequence plus its associated meta-data taken from the underneath databank--like references to ontologies or to external databanks, and plain texts as comments of researchers and (title, abstracts or even body of) papers. Bpboffers several tools to customize the search and the clustering process over its indexed documents. The user can search a set of keywords within a specific field of the document schema, or can execute Blastto find documents relative to homologue sequences. In both cases the search task returns a set of documents (hits) which constitute the answer to the user query. Since the number of hits may be large, Bpbclusters them into groups of homogenous content, organized as a hierarchy of labeled clusters. The user can actually choose among several ontology-based hierarchical clustering strategies, each offering a different "view" of the returned hits. Bpbcomputes these views by exploiting the meta-data present within the retrieved documents such as the references to Gene Ontology, the taxonomy lineage, the organism and the keywords. Of course, the approach is flexible enough to leave room for future additions of other meta-information. The ultimate goal of the clustering process is to provide the user with several different readings of the (maybe numerous) query results and show possible hidden correlations among them, thus improving their browsing and understanding. Bpb is a powerful search engine that makes it very easy to perform complex queries over the indexed databanks (currently only UNIPROT is considered). The ontology-based clustering approach is efficient and effective, and could thus be applied successfully to larger databanks, like GenBank or EMBL.

The BioPrompt-box: an ontology-based clustering tool for searching in biological databases

PubMed Central

Corsi, Claudio; Ferragina, Paolo; Marangoni, Roberto

2007-01-01

Background High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This scenario generates severe problems not only at indexing time, where suitable algorithmic techniques for data indexing and retrieval are required, but also at query time, since a user query may produce such a large set of results that their browsing and "understanding" becomes humanly impractical. This problem is well known to the Web community, where a new generation of Web search engines is being developed, like Vivisimo. These tools organize on-the-fly the results of a user query in a hierarchy of labeled folders that ease their browsing and knowledge extraction. We investigate this approach on biological data, and propose the so called The BioPrompt-boxsoftware system which deploys ontology-driven clustering strategies for making the searching process of biologists more efficient and effective. Results The BioPrompt-box (Bpb) defines a document as a biological sequence plus its associated meta-data taken from the underneath databank – like references to ontologies or to external databanks, and plain texts as comments of researchers and (title, abstracts or even body of) papers. Bpboffers several tools to customize the search and the clustering process over its indexed documents. The user can search a set of keywords within a specific field of the document schema, or can execute Blastto find documents relative to homologue sequences. In both cases the search task returns a set of documents (hits) which constitute the answer to the user query. Since the number of hits may be large, Bpbclusters them into groups of homogenous content, organized as a hierarchy of labeled clusters. The user can actually choose among several ontology-based hierarchical clustering strategies, each offering a different "view" of the returned hits. Bpbcomputes these views by exploiting the meta-data present within the retrieved documents such as the references to Gene Ontology, the taxonomy lineage, the organism and the keywords. Of course, the approach is flexible enough to leave room for future additions of other meta-information. The ultimate goal of the clustering process is to provide the user with several different readings of the (maybe numerous) query results and show possible hidden correlations among them, thus improving their browsing and understanding. Conclusion Bpb is a powerful search engine that makes it very easy to perform complex queries over the indexed databanks (currently only UNIPROT is considered). The ontology-based clustering approach is efficient and effective, and could thus be applied successfully to larger databanks, like GenBank or EMBL. PMID:17430575

Validity and test-retest reliability of the self-completion adult social care outcomes toolkit (ASCOT-SCT4) with adults with long-term physical, sensory and mental health conditions in England.

PubMed

Rand, Stacey; Malley, Juliette; Towers, Ann-Marie; Netten, Ann; Forder, Julien

2017-08-18

The Adult Social Care Outcomes Toolkit (ASCOT-SCT4) is a multi-attribute utility index designed for the evaluation of long-term social care services. The measure comprises eight attributes that capture aspects of social care-related quality of life. The instrument has previously been validated with a sample of older adults who used home care services in England. This paper aims to demonstrate the instrument's test-retest reliability and provide evidence for its validity in a diverse sample of adults who use publicly-funded, community-based social care in England. A survey of 770 social care service users was conducted in England. A subsample of 100 services users participated in a follow-up interview between 7 and 21 days after baseline. Spearman rank correlation coefficients between the ASCOT-SCT4 index score and the EQ-5D-3 L, the ICECAP-A or ICECAP-O and overall quality of life were used to assess convergent validity. Data on variables hypothesised to be related to the ASCOT-SCT4 index score, as well as rating of individual attributes, were also collected. Hypothesised relationships were tested using one-way ANOVA or Fisher's exact test. Test-retest reliability was assessed using the intra-class correlation coefficient for the ASCOT-SCT4 index score at baseline and follow-up. There were moderate to strong correlations between the ASCOT-SCT4 index and EQ-5D-3 L, the ICECAP-A or ICECAP-O, and overall quality of life (all correlations ≥ 0.3). The construct validity was further supported by statistically significant hypothesised relationships between the ASCOT-SCT4 index and individual characteristics in univariate and multivariate analysis. There was also further evidence for the construct validity for the revised Food and drink and Dignity items. The test-retest reliability was considered to be good (ICC = 0.783; 95% CI: 0.678-0.857). The ASCOT-SCT4 index has good test-retest reliability for adults with physical or sensory disabilities who use social care services. The index score and the attributes appear to be valid for adults receiving social care for support reasons connected to underlying mental health problems, and physical or sensory disabilities. Further reliability testing with a wider sample of social care users is warranted, as is further exploration of the relationship between the ASCOT-SCT4, ICECAP-A/O and EQ-5D-3 L indices.

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

The Children's Dermatology Life Quality Index (CDLQI): linguistic and cultural validation in Serbian.

PubMed

Janković, Slavenka; Vukićević, Jelica; Djordjević, Sanja; Janković, Janko; Marinković, Jelena; Erić, Miloš

2013-01-01

The Children's Dermatology Life Quality Index (CDLQI) evaluates the impact of skin diseases on the patient's quality of life. The purpose of the study was to translate and to validate the CDLQI into Serbian. The CDLQI was translated into Serbian following international recommendations for translation and cultural adaptation. The validation study was carried out on a large cohort of secondary schoolchildren who self-reported acne. Translating the CDLQI consisted of forward translation, reconciliation, back translation, back-translation review, and cognitive debriefing. The good internal consistency of the scale was demonstrated with a Cronbach alpha coefficient of 0.87. A Spearman correlation coefficient of 0.66 between the CDLQI and the Cardiff Acne Disability Index (CADI) was deemed satisfactory to demonstrate concurrent validity. The translation, cross-cultural adaptation, and psychometric qualities of the CDLQI were satisfactory, enabling its application in clinical practice and future studies.

Validation of the Acoustic Voice Quality Index Version 03.01 and the Acoustic Breathiness Index in the Spanish language.

PubMed

Delgado Hernández, Jonathan; León Gómez, Nieves M; Jiménez, Alejandra; Izquierdo, Laura M; Barsties V Latoszek, Ben

2018-05-01

The aim of this study was to validate the Acoustic Voice Quality Index 03.01 (AVQIv3) and the Acoustic Breathiness Index (ABI) in the Spanish language. Concatenated voice samples of continuous speech (cs) and sustained vowel (sv) from 136 subjects with dysphonia and 47 vocally healthy subjects were perceptually judged for overall voice quality and breathiness severity. First, to reach a higher level of ecological validity, the proportions of cs and sv were equalized regarding the time length of 3 seconds sv part and voiced cs part, respectively. Second, concurrent validity and diagnostic accuracy were verified. A moderate reliability of overall voice quality and breathiness severity from 5 experts was used. It was found that 33 syllables as standardization of the cs part, which represents 3 seconds of voiced cs, allows the equalization of both speech tasks. A strong correlation was revealed between AVQIv3 and overall voice quality and ABI and perceived breathiness severity. Additionally, the best diagnostic outcome was identified at a threshold of 2.28 and 3.40 for AVQIv3 and ABI, respectively. The AVQIv3 and ABI showed in the Spanish language valid and robust results to quantify abnormal voice qualities regarding overall voice quality and breathiness severity.

The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation

PubMed Central

Casadio, Rita

2017-01-01

Abstract BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. PMID:28453653

Automatic insertion of simulated microcalcification clusters in a software breast phantom

NASA Astrophysics Data System (ADS)

Shankla, Varsha; Pokrajac, David D.; Weinstein, Susan P.; DeLeo, Michael; Tuite, Catherine; Roth, Robyn; Conant, Emily F.; Maidment, Andrew D.; Bakic, Predrag R.

2014-03-01

An automated method has been developed to insert realistic clusters of simulated microcalcifications (MCs) into computer models of breast anatomy. This algorithm has been developed as part of a virtual clinical trial (VCT) software pipeline, which includes the simulation of breast anatomy, mechanical compression, image acquisition, image processing, display and interpretation. An automated insertion method has value in VCTs involving large numbers of images. The insertion method was designed to support various insertion placement strategies, governed by probability distribution functions (pdf). The pdf can be predicated on histological or biological models of tumor growth, or estimated from the locations of actual calcification clusters. To validate the automated insertion method, a 2-AFC observer study was designed to compare two placement strategies, undirected and directed. The undirected strategy could place a MC cluster anywhere within the phantom volume. The directed strategy placed MC clusters within fibroglandular tissue on the assumption that calcifications originate from epithelial breast tissue. Three radiologists were asked to select between two simulated phantom images, one from each placement strategy. Furthermore, questions were posed to probe the rationale behind the observer's selection. The radiologists found the resulting cluster placement to be realistic in 92% of cases, validating the automated insertion method. There was a significant preference for the cluster to be positioned on a background of adipose or mixed adipose/fibroglandular tissues. Based upon these results, this automated lesion placement method will be included in our VCT simulation pipeline.

Translation and validation of the Rhinosinusitis Disability Index for use in Nigeria.

PubMed

Asoegwu, C N; Nwawolo, C C; Okubadejo, N U

2017-07-01

The Rhinosinusitis Disability Index (RSDI) is a validated and reliable measure of severity of chronic rhinosinusitis. The objective of this study was to translate and validate the instrument for use in Nigeria. This is a methodological study. 71 patients with chronic rhinosinusitis attending two Otolaryngology clinics in Lagos, Nigeria. Using standardized methods and trained translators, the RSDI was translated to vernacular (Yoruba language) and back-translated to culturally appropriate English. Data analysis comprised of assessment of the item quality, content validity and internal consistency of the back-translated Rhinosinusitis Disability Index (bRSDI), and correlation to the original RSDI. Content validity (floor and ceiling effects) showed 0% floor and ceiling effects for the total scores, 0% ceiling effects for all domains and floor effect for physical domain, and 9.9 and 8.5% floor effects for functional and emotional domains, respectively. The mean item-own correlation for physical domain was 0.54 ± 0.08, 0.72 ± 0.08 for functional domain and 0.74 ± 0.07 for emotional domain. All domain item-own correlations were higher than item-other domain correlations. The total Cronbach's alpha was 0.936 and was higher than 0.70 for all the domains representing good internal consistency. Pearson correlation analysis showed strong correlation of RSDI to bRSDI (total score 0.881; p = 0.000, and domain subscores-physical: 0.788; p = 0.000, functional: 0.830; p = 0.000, and emotional: 0.888; p = 0.000). The back-translated Rhinosinusitis Disability Index shows good face and content validity with good internal consistency while correlating linearly and significantly with the original Rhinosinusitis Disability Index and is recommended for use in Nigeria.

The development and validation of a test of science critical thinking for fifth graders.

PubMed

Mapeala, Ruslan; Siew, Nyet Moi

2015-01-01

The paper described the development and validation of the Test of Science Critical Thinking (TSCT) to measure the three critical thinking skill constructs: comparing and contrasting, sequencing, and identifying cause and effect. The initial TSCT consisted of 55 multiple choice test items, each of which required participants to select a correct response and a correct choice of critical thinking used for their response. Data were obtained from a purposive sampling of 30 fifth graders in a pilot study carried out in a primary school in Sabah, Malaysia. Students underwent the sessions of teaching and learning activities for 9 weeks using the Thinking Maps-aided Problem-Based Learning Module before they answered the TSCT test. Analyses were conducted to check on difficulty index (p) and discrimination index (d), internal consistency reliability, content validity, and face validity. Analysis of the test-retest reliability data was conducted separately for a group of fifth graders with similar ability. Findings of the pilot study showed that out of initial 55 administered items, only 30 items with relatively good difficulty index (p) ranged from 0.40 to 0.60 and with good discrimination index (d) ranged within 0.20-1.00 were selected. The Kuder-Richardson reliability value was found to be appropriate and relatively high with 0.70, 0.73 and 0.92 for identifying cause and effect, sequencing, and comparing and contrasting respectively. The content validity index obtained from three expert judgments equalled or exceeded 0.95. In addition, test-retest reliability showed good, statistically significant correlations ([Formula: see text]). From the above results, the selected 30-item TSCT was found to have sufficient reliability and validity and would therefore represent a useful tool for measuring critical thinking ability among fifth graders in primary science.

Sub-250nm room temperature optical gain from AlGaN materials with strong compositional fluctuations

NASA Astrophysics Data System (ADS)

Pecora, Emanuele; Zhang, Wei; Sun, Haiding; Nikiforov, A.; Yin, Jian; Paiella, Roberto; Moustakas, Theodore; Dal Negro, Luca

2013-03-01

Compact and portable deep-UV LEDs and laser sources are needed for a number of engineering applications including optical communications, gas sensing, biochemical agent detection, disinfection, biotechnology and medical diagnostics. We investigate the deep-UV optical emission and gain properties of AlxGa1-xN/AlyGa1-yN multiple quantum wells structure. These structures were grown by molecular-beam epitaxy on 6H-SiC substrates resulting in either homogeneous wells or various degrees of band-structure compositional fluctuations in the form of cluster-like features within the wells. We measured the TE-polarized amplified spontaneous emission in the sample with cluster-like features and quantified the optical absorption/gain coefficients and gain spectra by the Variable Stripe Length (VSL) technique under ultrafast optical pumping. We report blue-shift and narrowing of the emission, VSL traces, gain spectra, polarization studies, and the validity of the Schalow-Townes relation to demonstrate a maximum net modal gain of 120 cm-1 at 250 nm in the sample with strong compositional fluctuations. Moreover, we measure a very low gain threshold (15 μJ/cm2) . On the other hand, we found that samples with homogeneous quantum wells lead to absorption only. In addition, we report gain measurements in graded-index-separate-confined heterostructure (GRINSCH) designed to increase the device optical confinement factor.

The HARPS-N archive through a Cassandra, NoSQL database suite?

NASA Astrophysics Data System (ADS)

Molinari, Emilio; Guerra, Jose; Harutyunyan, Avet; Lodi, Marcello; Martin, Adrian

2016-07-01

The TNG-INAF is developing the science archive for the WEAVE instrument. The underlying architecture of the archive is based on a non relational database, more precisely, on Apache Cassandra cluster, which uses a NoSQL technology. In order to test and validate the use of this architecture, we created a local archive which we populated with all the HARPSN spectra collected at the TNG since the instrument's start of operations in mid-2012, as well as developed tools for the analysis of this data set. The HARPS-N data set is two orders of magnitude smaller than WEAVE, but we want to demonstrate the ability to walk through a complete data set and produce scientific output, as valuable as that produced by an ordinary pipeline, though without accessing directly the FITS files. The analytics is done by Apache Solr and Spark and on a relational PostgreSQL database. As an example, we produce observables like metallicity indexes for the targets in the archive and compare the results with the ones coming from the HARPS-N regular data reduction software. The aim of this experiment is to explore the viability of a high availability cluster and distributed NoSQL database as a platform for complex scientific analytics on a large data set, which will then be ported to the WEAVE Archive System (WAS) which we are developing for the WEAVE multi object, fiber spectrograph.

Quantitative Tumor Segmentation for Evaluation of Extent of Glioblastoma Resection to Facilitate Multisite Clinical Trials12

PubMed Central

Cordova, James S; Schreibmann, Eduard; Hadjipanayis, Costas G; Guo, Ying; Shu, Hui-Kuo G; Shim, Hyunsuk; Holder, Chad A

2014-01-01

Standard-of-care therapy for glioblastomas, the most common and aggressive primary adult brain neoplasm, is maximal safe resection, followed by radiation and chemotherapy. Because maximizing resection may be beneficial for these patients, improving tumor extent of resection (EOR) with methods such as intraoperative 5-aminolevulinic acid fluorescence-guided surgery (FGS) is currently under evaluation. However, it is difficult to reproducibly judge EOR in these studies due to the lack of reliable tumor segmentation methods, especially for postoperative magnetic resonance imaging (MRI) scans. Therefore, a reliable, easily distributable segmentation method is needed to permit valid comparison, especially across multiple sites. We report a segmentation method that combines versatile region-of-interest blob generation with automated clustering methods. We applied this to glioblastoma cases undergoing FGS and matched controls to illustrate the method's reliability and accuracy. Agreement and interrater variability between segmentations were assessed using the concordance correlation coefficient, and spatial accuracy was determined using the Dice similarity index and mean Euclidean distance. Fuzzy C-means clustering with three classes was the best performing method, generating volumes with high agreement with manual contouring and high interrater agreement preoperatively and postoperatively. The proposed segmentation method allows tumor volume measurements of contrast-enhanced T1-weighted images in the unbiased, reproducible fashion necessary for quantifying EOR in multicenter trials. PMID:24772206

Bioclimatic Classification of Northeast Asia for climate change response

NASA Astrophysics Data System (ADS)

Choi, Y.; Jeon, S. W.; Lim, C. H.

2016-12-01

As climate change has been getting worse, we should monitor the change of biodiversity, and distribution of species to handle the crisis and take advantage of climate change. The development of bioclimatic map which classifies land into homogenous zones by similar environment properties is the first step to establish a strategy. Statistically derived classifications of land provide useful spatial frameworks to support ecosystem research, monitoring and policy decisions. Many countries are trying to make this kind of map and actively utilize it to ecosystem conservation and management. However, the Northeast Asia including North Korea doesn't have detailed environmental information, and has not built environmental classification map. Therefore, this study presents a bioclimatic map of Northeast Asia based on statistical clustering of bioclimate data. Bioclim data ver1.4 which provided by WorldClim were considered for inclusion in a model. Eight of the most relevant climate variables were selected by correlation analysis, based on previous studies. Principal Components Analysis (PCA) was used to explain 86% of the variation into three independent dimensions, which were subsequently clustered using an ISODATA clustering. The bioclimatic zone of Northeast Asia could consist of 29, 35, and 50 zones. This bioclimatic map has a 30' resolution. To assess the accuracy, the correlation coefficient was calculated between the first principal component values of the classification variables and the vegetation index, Gross Primary Production (GPP). It shows about 0.5 Pearson correlation coefficient. This study constructed Northeast Asia bioclimatic map by statistical method with high resolution, but in order to better reflect the realities, the variety of climate variables should be considered. Also, further studies should do more quantitative and qualitative validation in various ways. Then, this could be used more effectively to support decision making on climate change adaptation.

Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

NASA Astrophysics Data System (ADS)

Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin

2014-06-01

This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.

Cross-cultural adaptation, reliability and validity of the Arabic version of the reduced Western Ontario and McMaster Universities Osteoarthritis index in patients with knee osteoarthritis.

PubMed

Alghadir, Ahmad; Anwer, Shahnawaz; Iqbal, Zaheen Ahmed; Alsanawi, Hisham Abdulaziz

2016-01-01

We adapted the reduced Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index for the Arabic language and tested its metric properties in patients with knee osteoarthritis (OA). One hundred and twenty-one consecutive patients who were referred for physiotherapy to the outpatient department were asked to answer the Arabic version of the reduced WOMAC index (ArWOMAC). After the completion of the ArWOMAC, the intensity of knee pain and general health status were assessed using the visual analog scale (VAS) and the 12-item short form health survey (SF-12), respectively. A second assessment was performed at least 48 h after the first session to assess test-retest reliability. The test-retest reliability was quantified using the intra-class correlation coefficient (ICC), and Cronbach's alpha was calculated to assess the internal consistency of the Arabic questionnaire. The construct validity was assessed using Spearman rank correlation coefficients. The total ArWOMAC scale and pain and function subscales were internally consistent with Cronbach's coefficient alpha of 0.91, 0.89 and 0.90, respectively. Test-retest reliability was good to excellent with ICC of 0.91, 0.89 and 0.90, respectively. SF-12 and VAS score significantly correlated with ArWOMAC index (p < 0.01), which support the construct validity. The standard error of measurement (SEM) of the total scale was 2.94, based on repeated measurements for test-retest. The minimum detectable change based on the SEM for test-retest was 8.15. The ArWOMAC index is a reliable and valid instrument for evaluating the severity of knee OA, with metric properties in agreement with the original version. Although, the reduced WOMAC index has been clinically utilized within the Saudi population, the Arabic version of this instrument is not validated for an Arab population to measure lower limb functional disability caused by OA. The Arabic version of reduced WOMAC (ArWOMAC) index is a reliable and valid scale to measure lower limb functional disability in patients with knee OA. The ArWOMAC index could be suitable in Saudi Arabia and other Arab countries where the language, culture and the life style are similar.

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.

The Volunteer Satisfaction Index: A Validation Study in the Chinese Cultural Context

ERIC Educational Resources Information Center

Wong, Lok Ping; Chui, Wing Hong; Kwok, Yan Yuen

2011-01-01

Using a Hong Kong-sourced sample of 261 participants, this study set out to validate the Volunteer Satisfaction Index (VSI) in the Chinese cultural context and to evaluate its psychometric properties. The VSI was originally developed by Galindo-Kuhn and Guzley (2001) to measure the outcomes of volunteer experiences. In this study, exploratory…

Validation of the Parenting Stress Index--Short Form with Minority Caregivers

ERIC Educational Resources Information Center

Lee, Sang Jung; Gopalan, Geetha; Harrington, Donna

2016-01-01

Objectives: There has been little examination of the structural validity of the Parenting Stress Index--Short Form (PSI-SF) for minority populations in clinical contexts in the Unites States. This study aimed to test prespecified factor structures (one-factor, two-factor, and three-factor models) of the PSI-SF. Methods: This study used…

Application of the Cluster Expansion to a Mathematical Model of the Long Memory Phenomenon in a Financial Market

NASA Astrophysics Data System (ADS)

Kuroda, Koji; Maskawa, Jun-ichi; Murai, Joshin

2013-08-01

Empirical studies of the high frequency data in stock markets show that the time series of trade signs or signed volumes has a long memory property. In this paper, we present a discrete time stochastic process for polymer model which describes trader's trading strategy, and show that a scale limit of the process converges to superposition of fractional Brownian motions with Hurst exponents and Brownian motion, provided that the index γ of the time scale about the trader's investment strategy coincides with the index δ of the interaction range in the discrete time process. The main tool for the investigation is the method of cluster expansion developed in the mathematical study of statistical mechanics.

A Multicriteria Decision Making Approach for Estimating the Number of Clusters in a Data Set

PubMed Central

Peng, Yi; Zhang, Yong; Kou, Gang; Shi, Yong

2012-01-01

Determining the number of clusters in a data set is an essential yet difficult step in cluster analysis. Since this task involves more than one criterion, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes a multiple criteria decision making (MCDM)-based approach to estimate the number of clusters for a given data set. In this approach, MCDM methods consider different numbers of clusters as alternatives and the outputs of any clustering algorithm on validity measures as criteria. The proposed method is examined by an experimental study using three MCDM methods, the well-known clustering algorithm–k-means, ten relative measures, and fifteen public-domain UCI machine learning data sets. The results show that MCDM methods work fairly well in estimating the number of clusters in the data and outperform the ten relative measures considered in the study. PMID:22870181

Dynamic Trajectory Extraction from Stereo Vision Using Fuzzy Clustering

NASA Astrophysics Data System (ADS)

Onishi, Masaki; Yoda, Ikushi

In recent years, many human tracking researches have been proposed in order to analyze human dynamic trajectory. These researches are general technology applicable to various fields, such as customer purchase analysis in a shopping environment and safety control in a (railroad) crossing. In this paper, we present a new approach for tracking human positions by stereo image. We use the framework of two-stepped clustering with k-means method and fuzzy clustering to detect human regions. In the initial clustering, k-means method makes middle clusters from objective features extracted by stereo vision at high speed. In the last clustering, c-means fuzzy method cluster middle clusters based on attributes into human regions. Our proposed method can be correctly clustered by expressing ambiguity using fuzzy clustering, even when many people are close to each other. The validity of our technique was evaluated with the experiment of trajectories extraction of doctors and nurses in an emergency room of a hospital.

Semi-supervised clustering for parcellating brain regions based on resting state fMRI data

NASA Astrophysics Data System (ADS)

Cheng, Hewei; Fan, Yong

2014-03-01

Many unsupervised clustering techniques have been adopted for parcellating brain regions of interest into functionally homogeneous subregions based on resting state fMRI data. However, the unsupervised clustering techniques are not able to take advantage of exiting knowledge of the functional neuroanatomy readily available from studies of cytoarchitectonic parcellation or meta-analysis of the literature. In this study, we propose a semi-supervised clustering method for parcellating amygdala into functionally homogeneous subregions based on resting state fMRI data. Particularly, the semi-supervised clustering is implemented under the framework of graph partitioning, and adopts prior information and spatial consistent constraints to obtain a spatially contiguous parcellation result. The graph partitioning problem is solved using an efficient algorithm similar to the well-known weighted kernel k-means algorithm. Our method has been validated for parcellating amygdala into 3 subregions based on resting state fMRI data of 28 subjects. The experiment results have demonstrated that the proposed method is more robust than unsupervised clustering and able to parcellate amygdala into centromedial, laterobasal, and superficial parts with improved functionally homogeneity compared with the cytoarchitectonic parcellation result. The validity of the parcellation results is also supported by distinctive functional and structural connectivity patterns of the subregions and high consistency between coactivation patterns derived from a meta-analysis and functional connectivity patterns of corresponding subregions.

External validation of a Cox prognostic model: principles and methods

PubMed Central

2013-01-01

Background A prognostic model should not enter clinical practice unless it has been demonstrated that it performs a useful role. External validation denotes evaluation of model performance in a sample independent of that used to develop the model. Unlike for logistic regression models, external validation of Cox models is sparsely treated in the literature. Successful validation of a model means achieving satisfactory discrimination and calibration (prediction accuracy) in the validation sample. Validating Cox models is not straightforward because event probabilities are estimated relative to an unspecified baseline function. Methods We describe statistical approaches to external validation of a published Cox model according to the level of published information, specifically (1) the prognostic index only, (2) the prognostic index together with Kaplan-Meier curves for risk groups, and (3) the first two plus the baseline survival curve (the estimated survival function at the mean prognostic index across the sample). The most challenging task, requiring level 3 information, is assessing calibration, for which we suggest a method of approximating the baseline survival function. Results We apply the methods to two comparable datasets in primary breast cancer, treating one as derivation and the other as validation sample. Results are presented for discrimination and calibration. We demonstrate plots of survival probabilities that can assist model evaluation. Conclusions Our validation methods are applicable to a wide range of prognostic studies and provide researchers with a toolkit for external validation of a published Cox model. PMID:23496923

Standard Setting Methods for Pass/Fail Decisions on High-Stakes Objective Structured Clinical Examinations: A Validity Study.

PubMed

Yousuf, Naveed; Violato, Claudio; Zuberi, Rukhsana W

2015-01-01

CONSTRUCT: Authentic standard setting methods will demonstrate high convergent validity evidence of their outcomes, that is, cutoff scores and pass/fail decisions, with most other methods when compared with each other. The objective structured clinical examination (OSCE) was established for valid, reliable, and objective assessment of clinical skills in health professions education. Various standard setting methods have been proposed to identify objective, reliable, and valid cutoff scores on OSCEs. These methods may identify different cutoff scores for the same examinations. Identification of valid and reliable cutoff scores for OSCEs remains an important issue and a challenge. Thirty OSCE stations administered at least twice in the years 2010-2012 to 393 medical students in Years 2 and 3 at Aga Khan University are included. Psychometric properties of the scores are determined. Cutoff scores and pass/fail decisions of Wijnen, Cohen, Mean-1.5SD, Mean-1SD, Angoff, borderline group and borderline regression (BL-R) methods are compared with each other and with three variants of cluster analysis using repeated measures analysis of variance and Cohen's kappa. The mean psychometric indices on the 30 OSCE stations are reliability coefficient = 0.76 (SD = 0.12); standard error of measurement = 5.66 (SD = 1.38); coefficient of determination = 0.47 (SD = 0.19), and intergrade discrimination = 7.19 (SD = 1.89). BL-R and Wijnen methods show the highest convergent validity evidence among other methods on the defined criteria. Angoff and Mean-1.5SD demonstrated least convergent validity evidence. The three cluster variants showed substantial convergent validity with borderline methods. Although there was a high level of convergent validity of Wijnen method, it lacks the theoretical strength to be used for competency-based assessments. The BL-R method is found to show the highest convergent validity evidences for OSCEs with other standard setting methods used in the present study. We also found that cluster analysis using mean method can be used for quality assurance of borderline methods. These findings should be further confirmed by studies in other settings.

IVGTT-based simple assessment of glucose tolerance in the Zucker fatty rat: Validation against minimal models.

PubMed

Morettini, Micaela; Faelli, Emanuela; Perasso, Luisa; Fioretti, Sandro; Burattini, Laura; Ruggeri, Piero; Di Nardo, Francesco

2017-01-01

For the assessment of glucose tolerance from IVGTT data in Zucker rat, minimal model methodology is reliable but time- and money-consuming. This study aimed to validate for the first time in Zucker rat, simple surrogate indexes of insulin sensitivity and secretion against the glucose-minimal-model insulin sensitivity index (SI) and against first- (Φ1) and second-phase (Φ2) β-cell responsiveness indexes provided by C-peptide minimal model. Validation of the surrogate insulin sensitivity index (ISI) and of two sets of coupled insulin-based indexes for insulin secretion, differing from the cut-off point between phases (FPIR3-SPIR3, t = 3 min and FPIR5-SPIR5, t = 5 min), was carried out in a population of ten Zucker fatty rats (ZFR) and ten Zucker lean rats (ZLR). Considering the whole rat population (ZLR+ZFR), ISI showed a significant strong correlation with SI (Spearman's correlation coefficient, r = 0.88; P<0.001). Both FPIR3 and FPIR5 showed a significant (P<0.001) strong correlation with Φ1 (r = 0.76 and r = 0.75, respectively). Both SPIR3 and SPIR5 showed a significant (P<0.001) strong correlation with Φ2 (r = 0.85 and r = 0.83, respectively). ISI is able to detect (P<0.001) the well-recognized reduction in insulin sensitivity in ZFRs, compared to ZLRs. The insulin-based indexes of insulin secretion are able to detect in ZFRs (P<0.001) the compensatory increase of first- and second-phase secretion, associated to the insulin-resistant state. The ability of the surrogate indexes in describing glucose tolerance in the ZFRs was confirmed by the Disposition Index analysis. The model-based validation performed in the present study supports the utilization of low-cost, insulin-based indexes for the assessment of glucose tolerance in Zucker rat, reliable animal model of human metabolic syndrome.

Development and preliminary validation of an index for indicating the risks of the design of working hours to health and wellbeing.

PubMed

Schomann, Carsten; Giebel, Ole; Nachreiner, Friedhelm

2006-01-01

BASS 4, a computer program for the design and evaluation of workings hours, is an example of an ergonomics-based software tool that can be used by safety practitioners at the shop floor with regard to legal, ergonomic, and economic criteria. Based on experiences with this computer program, a less sophisticated Working-Hours-Risk Index for assessing the quality of work schedules (including flexible work hours) to indicate risks to health and wellbeing has been developed to provide a quick and easy applicable tool for legally required risk assessments. The results of a validation study show that this risk index seems to be a promising indicator for predicting risks of health complaints and wellbeing. The purpose of the Risk Index is to simplify the evaluation process at the shop floor and provide some more general information about the quality of a work schedule that can be used for triggering preventive interventions. Such a risk index complies with practitioners' expectations and requests for easy, useful, and valid instruments.

Hydrogeochemistry and water quality of the Kordkandi-Duzduzan plain, NW Iran: application of multivariate statistical analysis and PoS index.

PubMed

Soltani, Shahla; Asghari Moghaddam, Asghar; Barzegar, Rahim; Kazemian, Naeimeh; Tziritis, Evangelos

2017-08-18

Kordkandi-Duzduzan plain is one of the fertile plains of East Azarbaijan Province, NW of Iran. Groundwater is an important resource for drinking and agricultural purposes due to the lack of surface water resources in the region. The main objectives of the present study are to identify the hydrogeochemical processes and the potential sources of major, minor, and trace metals and metalloids such as Cr, Mn, Cd, Fe, Al, and As by using joint hydrogeochemical techniques and multivariate statistical analysis and to evaluate groundwater quality deterioration with the use of PoS environmental index. To achieve these objectives, 23 groundwater samples were collected in September 2015. Piper diagram shows that the mixed Ca-Mg-Cl is the dominant groundwater type, and some of the samples have Ca-HCO 3 , Ca-Cl, and Na-Cl types. Multivariate statistical analyses indicate that weathering and dissolution of different rocks and minerals, e.g., silicates, gypsum, and halite, ion exchange, and agricultural activities influence the hydrogeochemistry of the study area. The cluster analysis divides the samples into two distinct clusters which are completely different in EC (and its dependent variables such as Na + , K + , Ca 2+ , Mg 2+ , SO 4 2- , and Cl - ), Cd, and Cr variables according to the ANOVA statistical test. Based on the median values, the concentrations of pH, NO 3 - , SiO 2 , and As in cluster 1 are elevated compared with those of cluster 2, while their maximum values occur in cluster 2. According to the PoS index, the dominant parameter that controls quality deterioration is As, with 60% of contribution. Samples of lowest PoS values are located in the southern and northern parts (recharge area) while samples of the highest values are located in the discharge area and the eastern part.

A Clustered Extragalactic Foreground Model for the EoR

NASA Astrophysics Data System (ADS)

Murray, S. G.; Trott, C. M.; Jordan, C. H.

2018-05-01

We review an improved statistical model of extra-galactic point-source foregrounds first introduced in Murray et al. (2017), in the context of the Epoch of Reionization. This model extends the instrumentally-convolved foreground covariance used in inverse-covariance foreground mitigation schemes, by considering the cosmological clustering of the sources. In this short work, we show that over scales of k ~ (0.6, 40.)hMpc-1, ignoring source clustering is a valid approximation. This is in contrast to Murray et al. (2017), who found a possibility of false detection if the clustering was ignored. The dominant cause for this change is the introduction of a Galactic synchrotron component which shadows the clustering of sources.

STANDARD STARS AND EMPIRICAL CALIBRATIONS FOR Hα AND Hβ PHOTOMETRY

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

Joner, Michael D.; Hintz, Eric G., E-mail: joner@byu.edu, E-mail: hintz@byu.edu

2015-12-15

We define an Hα photometric system that is designed as a companion to the well established Hβ index. The new system is built on spectrophotometric observations of field stars as well as stars in benchmark open clusters. We present data for 75 field stars, 12 stars from the Coma star cluster, 24 stars from the Hyades, 17 stars from the Pleiades, and 8 stars from NGC 752 to be used as primary standard stars in the new systems. We show that the system transformations are relatively insensitive to the shape of the filter functions. We make comparisons of the Hαmore » index to the Hβ index and illustrate the relationship between the two systems. In addition, we present relations that relate both hydrogen indices to equivalent width and effective temperature. We derive equations to calibrate both systems for Main Sequence stars with spectral types in the range O9 to K2 for equivalent width and A2 to K2 for effective temperature.« less

Evaluating and Recommending Greek Newspapers' Websites Using Clustering

ERIC Educational Resources Information Center

Kanellopoulos, Dimitris; Kotsiantis, Sotiris

2012-01-01

Purpose: The aim of this work is to evaluate Greek newspaper websites using clustering and a number of criteria obtained from the Alexa search engine. Furthermore, a recommendation approach is proposed for matching Greek online newspapers with the profiles of potential readers. The paper presents the implementation and validation of a recommender…

Clustering molecular dynamics trajectories for optimizing docking experiments.

PubMed

De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

[Spatial analysis of autumn-winter type scrub typhus in Shandong province, 2006-2014].

PubMed

Yang, H; Bi, Z W; Kou, Z Q; Zheng, L; Zhao, Z T

2016-05-01

To discuss the spatial-temporal distribution and epidemic trends of autumn-winter type scrub typhus in Shandong province, and provide scientific evidence for further study for the prevention and control of the disease. The scrub typhus surveillance data during 2006-2014 were collected from Shandong Disease Reporting Information System. The data was analyzed by using software ArcGIS 9.3(ESRI Inc., Redlands, CA, USA), GeoDa 0.9.5-i and SatScan 9.1.1. The Moran' s I, log-likelihood ratio(LLR), relative risk(RR)were calculated and the incidence choropleth maps, local indicators of spatial autocorrelation cluster maps and space scaning cluster maps were drawn. A total of 4 453 scrub typhus cases were reported during 2006-2014, and the annual incidence increased with year. Among the 17 prefectures(municipality)in Shandong, 13 were affected by scrub typhus. The global Moran's I index was 0.501 5(P<0.01). The differences in local Moran' s I index among 16 prefectures were significant(P<0.01). The " high-high" clustering areas were mainly Wulian county, Lanshan district and Juxian county of Rizhao, Xintai county of Tai' an, Gangcheng and Laicheng districts of Laiwu, Yiyuan county of Zibo and Mengyin county of Linyi. Spatial scan analysis showed that an eastward moving trend of high-risk clusters and two new high-risk clusters were found in Zaozhuang in 2014. The centers of the most likely clusters were in the south central mountainous areas during 2006-2010 and in 2012, eastern hilly areas in 2011, 2013 and 2014, and the size of the clusters expanded in 2008, 2011, 2013 and 2014. One spatial-temporal cluster was detected from October 1, 2014 to November 30, 2014, the center of the cluster was in Rizhao and the radius was 222.34 kilometers. A positive spatial correlation and spatial agglomerations were found in the distribution of autumn-winter type scrub typhus in Shandong. Since 2006, the epidemic area of the disease has expanded and the number of high-risk areas has increased. Moreover, the eastward moving and periodically expanding trends of high-risk clusters were detected.

Identification of "binge-prone" women: an experimentally and psychometrically validated cluster analysis in a college population.

PubMed

Beebe, D W; Holmbeck, G N; Albright, J S; Noga, K; DeCastro, B

1995-01-01

This study investigated the escape model of binge eating through a cluster analysis using standardized measures. A sample of 126 undergraduate women underwent a manipulation of their level of cognition and were asked to "taste-test" several flavors of ice cream. Questionnaire data from these women were entered into a cluster analysis. Two groups emerged: women in the "binge-prone" group were significantly more depressed, had lower self-esteem, had more chaotic and extreme eating patterns, and were more self-conscious than those in the control group. In validation work, binge-prone women were shown to report elevated levels of bulimic symptomatology and, when in the presence of a food they enjoyed, to respond to increases in level of cognition by eating more. These results were consistent with some, but not all, of the components of the escape model.

UVBY beta photometry of the young southern cluster NGC3293 and comparison with other young clusters

NASA Astrophysics Data System (ADS)

Shobbrook, R. R.

1980-09-01

Stromgren uvby photometry has been obtained for 42 members and beta photometry for 37 members of the young southern galactic cluster NGC 3293. The distance modulus obtained from using Crawford's beta/M(V) calibration is 12.75 mag, corresponding to a distance of 3.55 kpc. Comparison of the colour/colour and the HR diagrams of NGC 3293 with those of the five other young northern and southern clusters reveals large differences between the clusters which may possibly be due to metal abundance variations across the Galaxy. Apparently correlated with this effect is a variation of the luminosities of the lower main sequences over about 1 mag. The fainter stars in the southern clusters appear to be an average of 0.7 mag brighter than those in the northern clusters, but it is not certain at present how much of this difference is due to possible systematic errors in the beta index zero point between the northern and southern hemispheres.

Chinese cross-cultural adaptation and validation of the Foot Function Index as tool to measure patients with foot and ankle functional limitations.

PubMed

González-Sánchez, Manuel; Ruiz-Muñoz, Maria; Li, Guang Zhi; Cuesta-Vargas, Antonio I

2018-08-01

To perform a cross-cultural adaptation and validation of the Foot Function Index (FFI) questionnaire to develop the Chinese version. Three hundred and six patients with foot and ankle neuromusculoskeletal diseases participated in this observational study. Construct validity, internal consistency and criterion validity were calculated for the FFI Chinese version after the translation and transcultural adaptation process. Internal consistency ranged from 0.996 to 0.998. Test-retest analysis ranged from 0.985 to 0.994; minimal detectable change 90: 2.270; standard error of measurement: 0.973. Load distribution of the three factors had an eigenvalue greater than 1. Chi-square value was 9738.14 (p < 0.001). Correlations with the three factors were significant between Factor 1 and the other two: r = -0.634 (Factor 2) and r = -0.191 (Factor 1). Foot Function Index (Taiwan Version), Short-Form 12 (Version 2) and EuroQol-5D were used for criterion validity. Factors 1 and 2 showed significant correlation with 15/16 and 14/16 scales and subscales, respectively. Foot Function Index Chinese version psychometric characteristics were good to excellent. Chinese researchers and clinicians may use this tool for foot and ankle assessment and monitoring. Implications for rehabilitation A cross-cultural adaptation of the FFI has been done from original version to Chinese. Consistent results and satisfactory psychometric properties of the Foot Function Index Chinese version have been reported. For Chinese speaking researcher and clinician FFI-Ch could be used as a tool to assess patients with foot disease.

Construction and validation of a measure of integrative well-being in seven languages: The Pemberton Happiness Index

PubMed Central

2013-01-01

Purpose We introduce the Pemberton Happiness Index (PHI), a new integrative measure of well-being in seven languages, detailing the validation process and presenting psychometric data. The scale includes eleven items related to different domains of remembered well-being (general, hedonic, eudaimonic, and social well-being) and ten items related to experienced well-being (i.e., positive and negative emotional events that possibly happened the day before); the sum of these items produces a combined well-being index. Methods A distinctive characteristic of this study is that to construct the scale, an initial pool of items, covering the remembered and experienced well-being domains, were subjected to a complete selection and validation process. These items were based on widely used scales (e.g., PANAS, Satisfaction With Life Scale, Subjective Happiness Scale, and Psychological Well-Being Scales). Both the initial items and reference scales were translated into seven languages and completed via Internet by participants (N = 4,052) aged 16 to 60 years from nine countries (Germany, India, Japan, Mexico, Russia, Spain, Sweden, Turkey, and USA). Results Results from this initial validation study provided very good support for the psychometric properties of the PHI (i.e., internal consistency, a single-factor structure, and convergent and incremental validity). Conclusions Given the PHI’s good psychometric properties, this simple and integrative index could be used as an instrument to monitor changes in well-being. We discuss the utility of this integrative index to explore well-being in individuals and communities. PMID:23607679

Fuzzy Clustering-Based Modeling of Surface Interactions and Emulsions of Selected Whey Protein Concentrate Combined to i-Carrageenan and Gum Arabic Solutions

USDA-ARS?s Scientific Manuscript database

Gums and proteins are valuable ingredients with a wide spectrum of applications. Surface properties (surface tension, interfacial tension, emulsion activity index “EAI” and emulsion stability index “ESI”) of 4% whey protein concentrate (WPC) in a combination with '- carrageenan (0.05%, 0.1%, and 0.5...

Microbial biodiversity in arable soils is affected by agricultural practices

NASA Astrophysics Data System (ADS)

Wolińska, Agnieszka; Górniak, Dorota; Zielenkiewicz, Urszula; Goryluk-Salmonowicz, Agata; Kuźniar, Agnieszka; Stępniewska, Zofia; Błaszczyk, Mieczysław

2017-04-01

The aim of the study was to examine the differences in microbial community structure as a result of agricultural practices. Sixteen samples of cultivated and the same number of non-cultivated soils were selected. Gel bands were identified using the GelCompar software to create the presence-absence matrix, where each band represented a bacterial operational taxonomic unit. The data were used for principal-component analysis and additionally, the Shannon- Weaver index of general diversity, Simpson index of dominance and Simpson index of diversity were calculated. Denaturing gradient gel electrophoresis profiles clearly indicated differentiation of tested samples into two clusters: cultivated and non-cultivated soils. Greater numbers of dominant operational taxonomic units (65) in non-cultivated soils were noted compared to cultivated soils (47 operational taxonomic units). This implies that there was a reduction of dominant bacterial operational taxonomic units by nearly 30% in cultivated soils. Simpson dominance index expressing the number of species weighted by their abundance amounted to 1.22 in cultivated soils, whereas a 3-fold higher value (3.38) was observed in non-cultivated soils. Land-use practices seemed to be a important factors affected on biodiversity, because more than soil type determined the clustering into groups.

Intrachromosomal karyotype asymmetry in Orchidaceae.

PubMed

Medeiros-Neto, Enoque; Nollet, Felipe; Moraes, Ana Paula; Felix, Leonardo P

2017-01-01

The asymmetry indexes have helped cytotaxonomists to interpret and classify plant karyotypes for species delimitation efforts. However, there is no consensus about the best method to calculate the intrachromosomal asymmetry. The present study aimed to compare different intrachromosomal asymmetry indexes in order to indicate which are more efficient for the estimation of asymmetry in different groups of orchids. Besides, we aimed to compare our results with the Orchidaceae phylogenetic proposal to test the hypothesis of Stebbins (1971). Through a literature review, karyotypes were selected and analyzed comparatively with ideal karyotypes in a cluster analysis. All karyotypes showed some level of interchromosomal asymmetry, ranging from slightly asymmetric to moderately asymmetric. The five tested intrachromosomal asymmetry indexes indicated Sarcoglottis grandiflora as the species with the most symmetrical karyotype and Christensonella pachyphylla with the most asymmetrical karyotype. In the cluster analysis, the largest number of species were grouped with the intermediary ideal karyotypes B or C. Considering our results, we recommend the combined use of at least two indexes, especially Ask% or A1 with Syi, for cytotaxonomic analysis in groups of orchids. In an evolutionary perspective, our results support Stebbins' hypothesis that asymmetric karyotypes derive from a symmetric karyotypes.

Intrachromosomal karyotype asymmetry in Orchidaceae

PubMed Central

Medeiros-Neto, Enoque; Nollet, Felipe; Moraes, Ana Paula; Felix, Leonardo P.

2017-01-01

Abstract The asymmetry indexes have helped cytotaxonomists to interpret and classify plant karyotypes for species delimitation efforts. However, there is no consensus about the best method to calculate the intrachromosomal asymmetry. The present study aimed to compare different intrachromosomal asymmetry indexes in order to indicate which are more efficient for the estimation of asymmetry in different groups of orchids. Besides, we aimed to compare our results with the Orchidaceae phylogenetic proposal to test the hypothesis of Stebbins (1971). Through a literature review, karyotypes were selected and analyzed comparatively with ideal karyotypes in a cluster analysis. All karyotypes showed some level of interchromosomal asymmetry, ranging from slightly asymmetric to moderately asymmetric. The five tested intrachromosomal asymmetry indexes indicated Sarcoglottis grandiflora as the species with the most symmetrical karyotype and Christensonella pachyphylla with the most asymmetrical karyotype. In the cluster analysis, the largest number of species were grouped with the intermediary ideal karyotypes B or C. Considering our results, we recommend the combined use of at least two indexes, especially Ask% or A1 with Syi, for cytotaxonomic analysis in groups of orchids. In an evolutionary perspective, our results support Stebbins’ hypothesis that asymmetric karyotypes derive from a symmetric karyotypes. PMID:28644507

Cross-cultural adaptation, validation, and responsiveness of the Korean version of the AUSCAN Osteoarthritis Index.

PubMed

Moon, Ki Won; Lee, Shin-Seok; Kim, Jin Hyun; Song, Ran; Lee, Eun Young; Song, Yeong Wook; Bellamy, Nicholas; Lee, Eun Bong

2012-11-01

The Australian/Canadian Osteoarthritis Hand Index (AUSCAN) is a patient self-reported 15-item questionnaire measuring the severity of hand osteoarthritis symptoms in the respect of pain, stiffness, and function. In this study, we developed a Korean version of the AUSCAN Index (K-AUSCAN) and confirmed its reliability, validity, and responsiveness. The AUSCAN Index was translated into Korean by 3 translators and translated back into English by 3 different translators. In a group of 53 patients with clinical hand osteoarthritis (mean age 58.3 ± 7.6 years), validity was evaluated against other outcome measures, including the Functional Index for Hand Osteoarthritis (FIHOA) and Multidimensional Health Assessment Questionnaire (MDHAQ). Test-retest reliability was assessed at a 2-weeks interval in 51 patients. Internal consistency of K-AUSCAN was evaluated by Cronbach's α. Responsiveness was measured by standardized response mean (SRM). The test-retest reliability of K-AUSCAN yielded intraclass correlation coefficient of 0.46 for pain, 0.58 for stiffness, and 0.67 for function. The internal consistency of K-AUSCAN was satisfactory with Cronbach's α of 0.89 for pain and 0.93 for function. The K-AUSCAN index showed good correlation with other measures (r (2) was 0.67 for K-AUSCAN pain and MDHAQ pain; r (2) was 0.72 for K-AUSCAN function and FIHOA). The pain and function of K-AUSCAN correlated substantially with each other and moderately with stiffness subscale. The average SRM for K-AUSCAN pain, stiffness, and function was -0.92, -0.48, and -0.84, respectively. The Korean version of the AUSCAN Index is a valid, reliable, and responsive tool for the assessment of hand osteoarthritis symptoms.

Validating the Heat Stress Indices for Using In Heavy Work Activities in Hot and Dry Climates.

PubMed

Hajizadeh, Roohalah; Golbabaei, Farideh; Farhang Dehghan, Somayeh; Beheshti, Mohammad Hossein; Jafari, Sayed Mohammad; Taheri, Fereshteh

2016-01-01

Necessity of evaluating heat stress in the workplace, require validation of indices and selection optimal index. The present study aimed to assess the precision and validity of some heat stress indices and select the optimum index for using in heavy work activities in hot and dry climates. It carried out on 184 workers from 40 brick kilns workshops in the city of Qom, central Iran (as representative hot and dry climates). After reviewing the working process and evaluation the activity of workers and the type of work, environmental and physiological parameters according to standards recommended by International Organization for Standardization (ISO) including ISO 7243 and ISO 9886 were measured and indices were calculated. Workers engaged in indoor kiln experienced the highest values of natural wet temperature, dry temperature, globe temperature and relative humidity among studied sections (P<0.05). Indoor workplaces had the higher levels of all environmental parameters than outdoors (P=0.0001), except for air velocity. The wet-bulb globe temperature (WBGT) and heat stress index (HSI) indices had the highest correlation with other physiological parameters among the other heat stress indices. Relationship between WBGT index and carotid artery temperature (r=0.49), skin temperature (r=0.319), and oral temperature (r=0.203) was statistically significant (P=0.006). Since WBGT index, as the most applicable index for evaluating heat stress in workplaces is approved by ISO, and due to the positive features of WBGT such as ease of measurement and calculation, and with respect to some limitation in application of HSI; WBGT can be introduced as the most valid empirical index of heat stress in the brick workshops.

Evaluation of Nine Consensus Indices in Delphi Foresight Research and Their Dependency on Delphi Survey Characteristics: A Simulation Study and Debate on Delphi Design and Interpretation.

PubMed

Birko, Stanislav; Dove, Edward S; Özdemir, Vural

2015-01-01

The extent of consensus (or the lack thereof) among experts in emerging fields of innovation can serve as antecedents of scientific, societal, investor and stakeholder synergy or conflict. Naturally, how we measure consensus is of great importance to science and technology strategic foresight. The Delphi methodology is a widely used anonymous survey technique to evaluate consensus among a panel of experts. Surprisingly, there is little guidance on how indices of consensus can be influenced by parameters of the Delphi survey itself. We simulated a classic three-round Delphi survey building on the concept of clustered consensus/dissensus. We evaluated three study characteristics that are pertinent for design of Delphi foresight research: (1) the number of survey questions, (2) the sample size, and (3) the extent to which experts conform to group opinion (the Group Conformity Index) in a Delphi study. Their impacts on the following nine Delphi consensus indices were then examined in 1000 simulations: Clustered Mode, Clustered Pairwise Agreement, Conger's Kappa, De Moivre index, Extremities Version of the Clustered Pairwise Agreement, Fleiss' Kappa, Mode, the Interquartile Range and Pairwise Agreement. The dependency of a consensus index on the Delphi survey characteristics was expressed from 0.000 (no dependency) to 1.000 (full dependency). The number of questions (range: 6 to 40) in a survey did not have a notable impact whereby the dependency values remained below 0.030. The variation in sample size (range: 6 to 50) displayed the top three impacts for the Interquartile Range, the Clustered Mode and the Mode (dependency = 0.396, 0.130, 0.116, respectively). The Group Conformity Index, a construct akin to measuring stubbornness/flexibility of experts' opinions, greatly impacted all nine Delphi consensus indices (dependency = 0.200 to 0.504), except the Extremity CPWA and the Interquartile Range that were impacted only beyond the first decimal point (dependency = 0.087 and 0.083, respectively). Scholars in technology design, foresight research and future(s) studies might consider these new findings in strategic planning of Delphi studies, for example, in rational choice of consensus indices and sample size, or accounting for confounding factors such as experts' variable degrees of conformity (stubbornness/flexibility) in modifying their opinions.

Evaluation of Nine Consensus Indices in Delphi Foresight Research and Their Dependency on Delphi Survey Characteristics: A Simulation Study and Debate on Delphi Design and Interpretation

PubMed Central

Birko, Stanislav; Dove, Edward S.; Özdemir, Vural

2015-01-01

The extent of consensus (or the lack thereof) among experts in emerging fields of innovation can serve as antecedents of scientific, societal, investor and stakeholder synergy or conflict. Naturally, how we measure consensus is of great importance to science and technology strategic foresight. The Delphi methodology is a widely used anonymous survey technique to evaluate consensus among a panel of experts. Surprisingly, there is little guidance on how indices of consensus can be influenced by parameters of the Delphi survey itself. We simulated a classic three-round Delphi survey building on the concept of clustered consensus/dissensus. We evaluated three study characteristics that are pertinent for design of Delphi foresight research: (1) the number of survey questions, (2) the sample size, and (3) the extent to which experts conform to group opinion (the Group Conformity Index) in a Delphi study. Their impacts on the following nine Delphi consensus indices were then examined in 1000 simulations: Clustered Mode, Clustered Pairwise Agreement, Conger’s Kappa, De Moivre index, Extremities Version of the Clustered Pairwise Agreement, Fleiss’ Kappa, Mode, the Interquartile Range and Pairwise Agreement. The dependency of a consensus index on the Delphi survey characteristics was expressed from 0.000 (no dependency) to 1.000 (full dependency). The number of questions (range: 6 to 40) in a survey did not have a notable impact whereby the dependency values remained below 0.030. The variation in sample size (range: 6 to 50) displayed the top three impacts for the Interquartile Range, the Clustered Mode and the Mode (dependency = 0.396, 0.130, 0.116, respectively). The Group Conformity Index, a construct akin to measuring stubbornness/flexibility of experts’ opinions, greatly impacted all nine Delphi consensus indices (dependency = 0.200 to 0.504), except the Extremity CPWA and the Interquartile Range that were impacted only beyond the first decimal point (dependency = 0.087 and 0.083, respectively). Scholars in technology design, foresight research and future(s) studies might consider these new findings in strategic planning of Delphi studies, for example, in rational choice of consensus indices and sample size, or accounting for confounding factors such as experts’ variable degrees of conformity (stubbornness/flexibility) in modifying their opinions. PMID:26270647

Perception of competence in middle school physical education: instrument development and validation.

PubMed

Scrabis-Fletcher, Kristin; Silverman, Stephen

2010-03-01

Perception of Competence (POC) has been studied extensively in physical activity (PA) research with similar instruments adapted for physical education (PE) research. Such instruments do not account for the unique PE learning environment. Therefore, an instrument was developed and the scores validated to measure POC in middle school PE. A multiphase design was used consisting of an intensive theoretical review, elicitation study, prepilot study, pilot study, content validation study, and final validation study (N=1281). Data analysis included a multistep iterative process to identify the best model fit. A three-factor model for POC was tested and resulted in root mean square error of approximation = .09, root mean square residual = .07, goodness offit index = .90, and adjusted goodness offit index = .86 values in the acceptable range (Hu & Bentler, 1999). A two-factor model was also tested and resulted in a good fit (two-factor fit indexes values = .05, .03, .98, .97, respectively). The results of this study suggest that an instrument using a three- or two-factor model provides reliable and valid scores ofPOC measurement in middle school PE.

Psychometric Evaluation of the Revised Michigan Diabetes Knowledge Test (V.2016) in Arabic: Translation and Validation

PubMed Central

Alhaiti, Ali Hassan; Alotaibi, Alanod Raffa; Jones, Linda Katherine; DaCosta, Cliff

2016-01-01

Objective. To translate the revised Michigan Diabetes Knowledge Test into the Arabic language and examine its psychometric properties. Setting. Of the 139 participants recruited through King Fahad Medical City in Riyadh, Saudi Arabia, 34 agreed to the second-round sample for retesting purposes. Methods. The translation process followed the World Health Organization's guidelines for the translation and adaptation of instruments. All translations were examined for their validity and reliability. Results. The translation process revealed excellent results throughout all stages. The Arabic version received 0.75 for internal consistency via Cronbach's alpha test and excellent outcomes in terms of the test-retest reliability of the instrument with a mean of 0.90 infraclass correlation coefficient. It also received positive content validity index scores. The item-level content validity index for all instrument scales fell between 0.83 and 1 with a mean scale-level index of 0.96. Conclusion. The Arabic version is proven to be a reliable and valid measure of patient's knowledge that is ready to be used in clinical practices. PMID:27995149

Validity of Combining History Elements and Physical Examination Tests to Diagnose Patellofemoral Pain.

PubMed

Décary, Simon; Frémont, Pierre; Pelletier, Bruno; Fallaha, Michel; Belzile, Sylvain; Martel-Pelletier, Johanne; Pelletier, Jean-Pierre; Feldman, Debbie; Sylvestre, Marie-Pierre; Vendittoli, Pascal-André; Desmeules, François

2018-04-01

To assess the validity of diagnostic clusters combining history elements and physical examination tests to diagnose or exclude patellofemoral pain (PFP). Prospective diagnostic study. Orthopedic outpatient clinics, family medicine clinics, and community-dwelling. Consecutive patients (N=279) consulting one of the participating orthopedic surgeons (n=3) or sport medicine physicians (n=2) for any knee complaint. Not applicable. History elements and physical examination tests were obtained by a trained physiotherapist blinded to the reference standard: a composite diagnosis including both physical examination tests and imaging results interpretation performed by an expert physician. Penalized logistic regression (least absolute shrinkage and selection operator) was used to identify history elements and physical examination tests associated with the diagnosis of PFP, and recursive partitioning was used to develop diagnostic clusters. Diagnostic accuracy measures including sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios with associated 95% confidence intervals (CIs) were calculated. Two hundred seventy-nine participants were evaluated, and 75 had a diagnosis of PFP (26.9%). Different combinations of history elements and physical examination tests including the age of participants, knee pain location, difficulty descending stairs, patellar facet palpation, and passive knee extension range of motion were associated with a diagnosis of PFP and used in clusters to accurately discriminate between individuals with PFP and individuals without PFP. Two diagnostic clusters developed to confirm the presence of PFP yielded a positive likelihood ratio of 8.7 (95% CI, 5.2-14.6) and 3 clusters to exclude PFP yielded a negative likelihood ratio of .12 (95% CI, .06-.27). Diagnostic clusters combining common history elements and physical examination tests that can accurately diagnose or exclude PFP compared to various knee disorders were developed. External validation is required before clinical use. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

The Communication AssessmenT Checklist in Health (CATCH): a tool for assessing the quality of printed educational materials for clinicians.

PubMed

Genova, Juliana; Nahon-Serfaty, Isaac; Dansokho, Selma Chipenda; Gagnon, Marie-Pierre; Renaud, Jean-Sébastien; Giguère, Anik M C

2014-01-01

There is little guidance available on strategies to improve the communication quality of printed educational materials (PEMs) for clinicians. The purposes of this study were to conceptualize PEM communication quality, develop a checklist based on this conceptualization, and validate the checklist with a selection of PEMs. From a literature review of the strategies influencing communication quality, we generated a conceptual map and developed the Communication AssessmenT Checklist in Health (CATCH) consisting of 55 items nested in 12 concepts. Two raters independently applied CATCH to 45 PEMs evaluated in the studies included in a Cochrane systematic review. From these results, we conducted an item analysis and assessed content validity of CATCH using a hierarchical cluster analysis to explore the extent to which our CATCH operationalization truly represented the communication quality concepts. Some concepts were better covered in the studied PEMs, whereas others were not covered consistently. We observed 3 contrasting PEM clusters. A first cluster (n = 22) was characterized by longer PEMs and comprised mostly high-impact peer-reviewed scientific articles or clinical practice guidelines. A second cluster (n = 22) consisted of PEMs shorter than 4 pages that used special fonts, color, pictures, and graphics. A third cluster consisted of a single brief PEM. With CATCH it is possible to categorize and understand the mechanisms that can trigger a change in behavior in health care providers. Additional research is needed to validate CATCH before it can be recommended for use. © 2014 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on Continuing Medical Education, Association for Hospital Medical Education.

Revising the Rorschach Ego Impairment Index to Accommodate Recent Recommendations about Improving Rorschach Validity

ERIC Educational Resources Information Center

Viglione, Donald J.; Perry, William; Giromini, Luciano; Meyer, Gregory J.

2011-01-01

We used multiple regression to calculate a new Ego Impairment Index (EII-3). The aim was to incorporate changes in the component variables and distribution of the number of responses as found in the new Rorschach Performance Assessment System, while sustaining the validity and reliability of previous EIIs. The EII-3 formula was derived from a…

Sixteen-Item Anxiety Sensitivity Index: Confirmatory Factor Analytic Evidence, Internal Consistency, and Construct Validity in a Young Adult Sample from the Netherlands

ERIC Educational Resources Information Center

Vujanovic, Anka A.; Arrindell, Willem A.; Bernstein, Amit; Norton, Peter J.; Zvolensky, Michael J.

2007-01-01

The present investigation examined the factor structure, internal consistency, and construct validity of the 16-item Anxiety Sensitivity Index (ASI; Reiss Peterson, Gursky, & McNally 1986) in a young adult sample (n = 420) from the Netherlands. Confirmatory factor analysis was used to comparatively evaluate two-factor, three-factor, and…

Uncertainty Analysis in the Creation of a Fine-Resolution Leaf Area Index (LAI) Reference Map for Validation of Moderate Resolution LAI Products

EPA Science Inventory

The validation process for a moderate resolution leaf area index (LAI) product (i.e., MODIS) involves the creation of a high spatial resolution LAI reference map (Lai-RM), which when scaled to the moderate LAI resolution (i.e., >1 km) allows for comparison and analysis with this ...

Validity of the classical monte carlo method to model the magnetic properties of a large transition-metal cluster: Mn19.

PubMed

Lima, Nicola; Caneschi, Andrea; Gatteschi, Dante; Kritikos, Mikael; Westin, L Gunnar

2006-03-20

The susceptibility of the large transition-metal cluster [Mn19O12(MOE)14(MOEH)10].MOEH (MOE = OC2H2O-CH3) has been fitted through classical Monte Carlo simulation, and an estimation of the exchange coupling constants has been done. With these results, it has been possible to perform a full-matrix diagonalization of the cluster core, which was used to provide information on the nature of the low-lying levels.

A Novel Quantum Blind Signature Scheme with Four-Particle Cluster States

NASA Astrophysics Data System (ADS)

Fan, Ling

2016-03-01

In an arbitrated quantum signature scheme, the signer signs the message and the receiver verifies the signature's validity with the assistance of the arbitrator. We present an arbitrated quantum blind signature scheme by measuring four-particle cluster states and coding. By using the special relationship of four-particle cluster states, we cannot only support the security of quantum signature, but also guarantee the anonymity of the message owner. It has a wide application to E-payment system, E-government, E-business, and etc.

A statistical method (cross-validation) for bone loss region detection after spaceflight

PubMed Central

Zhao, Qian; Li, Wenjun; Li, Caixia; Chu, Philip W.; Kornak, John; Lang, Thomas F.

2010-01-01

Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes. PMID:20632144

Cherry-picking functionally relevant substates from long md trajectories using a stratified sampling approach.

PubMed

Chandramouli, Balasubramanian; Mancini, Giordano

2016-01-01

Classical Molecular Dynamics (MD) simulations can provide insights at the nanoscopic scale into protein dynamics. Currently, simulations of large proteins and complexes can be routinely carried out in the ns-μs time regime. Clustering of MD trajectories is often performed to identify selective conformations and to compare simulation and experimental data coming from different sources on closely related systems. However, clustering techniques are usually applied without a careful validation of results and benchmark studies involving the application of different algorithms to MD data often deal with relatively small peptides instead of average or large proteins; finally clustering is often applied as a means to analyze refined data and also as a way to simplify further analysis of trajectories. Herein, we propose a strategy to classify MD data while carefully benchmarking the performance of clustering algorithms and internal validation criteria for such methods. We demonstrate the method on two showcase systems with different features, and compare the classification of trajectories in real and PCA space. We posit that the prototype procedure adopted here could be highly fruitful in clustering large trajectories of multiple systems or that resulting especially from enhanced sampling techniques like replica exchange simulations. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.

Laboratory-based validation of the baseline sensors of the ITER diagnostic residual gas analyzer

NASA Astrophysics Data System (ADS)

Klepper, C. C.; Biewer, T. M.; Marcus, C.; Andrew, P.; Gardner, W. L.; Graves, V. B.; Hughes, S.

2017-10-01

The divertor-specific ITER Diagnostic Residual Gas Analyzer (DRGA) will provide essential information relating to DT fusion plasma performance. This includes pulse-resolving measurements of the fuel isotopic mix reaching the pumping ducts, as well as the concentration of the helium generated as the ash of the fusion reaction. In the present baseline design, the cluster of sensors attached to this diagnostic's differentially pumped analysis chamber assembly includes a radiation compatible version of a commercial quadrupole mass spectrometer, as well as an optical gas analyzer using a plasma-based light excitation source. This paper reports on a laboratory study intended to validate the performance of this sensor cluster, with emphasis on the detection limit of the isotopic measurement. This validation study was carried out in a laboratory set-up that closely prototyped the analysis chamber assembly configuration of the baseline design. This includes an ITER-specific placement of the optical gas measurement downstream from the first turbine of the chamber's turbo-molecular pump to provide sufficient light emission while preserving the gas dynamics conditions that allow for \\textasciitilde 1 s response time from the sensor cluster [1].

Subtyping adolescents with bulimia nervosa.

PubMed

Chen, Eunice Y; Le Grange, Daniel

2007-12-01

Cluster analyses of eating disorder patients have yielded a "dietary-depressive" subtype, typified by greater negative affect, and a "dietary" subtype, typified by dietary restraint. This study aimed to replicate these findings in an adolescent sample with bulimia nervosa (BN) from a randomized controlled trial and to examine the validity and reliability of this methodology. In the sample of BN adolescents (N=80), cluster analysis revealed a "dietary-depressive" subtype (37.5%) and a "dietary" subtype (62.5%) using the Beck Depression Inventory, Rosenberg Self-Esteem Scale and Eating Disorder Examination Restraint subscale. The "dietary-depressive" subtype compared to the "dietary" subtype was significantly more likely to: (1) report co-occurring disorders, (2) greater eating and weight concerns, and (3) less vomiting abstinence at post-treatment (all p's<.05). The cluster analysis based on "dietary" and "dietary-depressive" subtypes appeared to have concurrent validity, yielding more distinct groups than subtyping by vomiting frequency. In order to assess the reliability of the subtyping scheme, a larger sample of adolescents with mixed eating and weight disorders in an outpatient eating disorder clinic (N=149) was subtyped, yielding similar subtypes. These results support the validity and reliability of the subtyping strategy in two adolescent samples.

Identification of Clusters that Condition Resistance to Anthracnose in the Common Bean Differential Cultivars AB136 and MDRK.

PubMed

Campa, Ana; Trabanco, Noemí; Ferreira, Juan José

2017-12-01

The correct identification of the anthracnose resistance systems present in the common bean cultivars AB136 and MDRK is important because both are included in the set of 12 differential cultivars proposed for use in classifying the races of the anthracnose causal agent, Colletrotrichum lindemuthianum. In this work, the responses against seven C. lindemuthianum races were analyzed in a recombinant inbred line population derived from the cross AB136 × MDRK. A genetic linkage map of 100 molecular markers distributed across the 11 bean chromosomes was developed in this population to locate the gene or genes conferring resistance against each race, based on linkage analyses and χ 2 tests of independence. The identified anthracnose resistance genes were organized in clusters. Two clusters were found in AB136: one located on linkage group Pv07, which corresponds to the anthracnose resistance cluster Co-5, and the other located at the end of linkage group Pv11, which corresponds to the Co-2 cluster. The presence of resistance genes at the Co-5 cluster in AB136 was validated through an allelism test conducted in the F 2 population TU × AB136. The presence of resistance genes at the Co-2 cluster in AB136 was validated through genetic dissection using the F 2:3 population ABM3 × MDRK, in which it was directly mapped to a genomic position between 46.01 and 47.77 Mb of chromosome Pv11. In MDRK, two independent clusters were identified: one located on linkage group Pv01, corresponding to the Co-1 cluster, and the second located on LG Pv04, corresponding to the Co-3 cluster. This report enhances the understanding of the race-specific Phaseolus vulgaris-C. lindemuthianum interactions and will be useful in breeding programs.

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 hierarchical clustering methodology for the estimation of toxicity.

PubMed

Martin, Todd M; Harten, Paul; Venkatapathy, Raghuraman; Das, Shashikala; Young, Douglas M

2008-01-01

ABSTRACT A quantitative structure-activity relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural similarity is defined in terms of 2-D physicochemical descriptors (such as connectivity and E-state indices). A genetic algorithm-based technique is used to generate statistically valid QSAR models for each cluster (using the pool of descriptors described above). The toxicity for a given query compound is estimated using the weighted average of the predictions from the closest cluster from each step in the hierarchical clustering assuming that the compound is within the domain of applicability of the cluster. The hierarchical clustering methodology was tested using a Tetrahymena pyriformis acute toxicity data set containing 644 chemicals in the training set and with two prediction sets containing 339 and 110 chemicals. The results from the hierarchical clustering methodology were compared to the results from several different QSAR methodologies.

Psychometric Properties of the Persian Language Version of Yang Internet Addiction Questionnaire: An Explanatory Factor Analysis.

PubMed

Mohammadsalehi, Narges; Mohammadbeigi, Abolfazl; Jadidi, Rahmatollah; Anbari, Zohreh; Ghaderi, Ebrahim; Akbari, Mojtaba

2015-09-01

Reliability and validity are the key concepts in measurement processes. Young internet addiction test (YIAT) is regarded as a valid and reliable questionnaire in English speaking countries for diagnosis of Internet-related behavior disorders. This study aimed at validating the Persian version of YIAT in the Iranian society. A pilot and a cross-sectional study were conducted on 28 and 254 students of Qom University of Medical Sciences, respectively, in order to validate the Persian version of YIAT. Forward and backward translations were conducted to develop a Persian version of the scale. Reliability was measured by test-retest, Cronbach's alpha and interclass correlation coefficient (ICC). Face, content and construct validity were approved by the importance score index, content validity ratio (CVR), content validity index (CVI), correlation matrix and factor analysis. The SPSS software was used for data analysis. The Cronbach's alpha was 0.917 (CI 95%; 0.901 - 0.931). The average of scale-level CVI was calculated to be 0.74; the CVI index for each item was higher than 0.83 and the average of CVI index was equal to 0.89. Factor analysis extracted three factors including personal activities disorder (PAD), emotional and mood disorder (EMD) and social activities disorder (SAD), with more than 55.8% of total variances. The ICC for different factors of Persian version of Young Questionnaire including PAD, EMD and for SAD was r = 0.884; CI 95%; 0.861 - 0.904, r = 0.766; CI 95%; 0.718 - 0.808 and r = 0.745; CI 95%; 0.686 - 0.795, respectively. Our study showed that the Persian version of YIAT is good and usable on Iranian people. The reliability of the instrument was very good. Moreover, the validity of the Persian translated version of the scale was sufficient. In addition, the reliability and validity of the three extracted factors of YIAT were evaluated and were acceptable.

Psychometric Properties of the Persian Language Version of Yang Internet Addiction Questionnaire: An Explanatory Factor Analysis

PubMed Central

Mohammadsalehi, Narges; Mohammadbeigi, Abolfazl; Jadidi, Rahmatollah; Anbari, Zohreh; Ghaderi, Ebrahim; Akbari, Mojtaba

2015-01-01

Background: Reliability and validity are the key concepts in measurement processes. Young internet addiction test (YIAT) is regarded as a valid and reliable questionnaire in English speaking countries for diagnosis of Internet-related behavior disorders. Objectives: This study aimed at validating the Persian version of YIAT in the Iranian society. Patients and Methods: A pilot and a cross-sectional study were conducted on 28 and 254 students of Qom University of Medical Sciences, respectively, in order to validate the Persian version of YIAT. Forward and backward translations were conducted to develop a Persian version of the scale. Reliability was measured by test-retest, Cronbach’s alpha and interclass correlation coefficient (ICC). Face, content and construct validity were approved by the importance score index, content validity ratio (CVR), content validity index (CVI), correlation matrix and factor analysis. The SPSS software was used for data analysis. Results: The Cronbach’s alpha was 0.917 (CI 95%; 0.901 - 0.931). The average of scale-level CVI was calculated to be 0.74; the CVI index for each item was higher than 0.83 and the average of CVI index was equal to 0.89. Factor analysis extracted three factors including personal activities disorder (PAD), emotional and mood disorder (EMD) and social activities disorder (SAD), with more than 55.8% of total variances. The ICC for different factors of Persian version of Young Questionnaire including PAD, EMD and for SAD was r = 0.884; CI 95%; 0.861 - 0.904, r = 0.766; CI 95%; 0.718 - 0.808 and r = 0.745; CI 95%; 0.686 - 0.795, respectively. Conclusions: Our study showed that the Persian version of YIAT is good and usable on Iranian people. The reliability of the instrument was very good. Moreover, the validity of the Persian translated version of the scale was sufficient. In addition, the reliability and validity of the three extracted factors of YIAT were evaluated and were acceptable. PMID:26495253

Quantifying site-specific physical heterogeneity within an estuarine seascape

USGS Publications Warehouse

Kennedy, Cristina G.; Mather, Martha E.; Smith, Joseph M.

2017-01-01

Quantifying physical heterogeneity is essential for meaningful ecological research and effective resource management. Spatial patterns of multiple, co-occurring physical features are rarely quantified across a seascape because of methodological challenges. Here, we identified approaches that measured total site-specific heterogeneity, an often overlooked aspect of estuarine ecosystems. Specifically, we examined 23 metrics that quantified four types of common physical features: (1) river and creek confluences, (2) bathymetric variation including underwater drop-offs, (3) land features such as islands/sandbars, and (4) major underwater channel networks. Our research at 40 sites throughout Plum Island Estuary (PIE) provided solutions to two problems. The first problem was that individual metrics that measured heterogeneity of a single physical feature showed different regional patterns. We solved this first problem by combining multiple metrics for a single feature using a within-physical feature cluster analysis. With this approach, we identified sites with four different types of confluences and three different types of underwater drop-offs. The second problem was that when multiple physical features co-occurred, new patterns of total site-specific heterogeneity were created across the seascape. This pattern of total heterogeneity has potential ecological relevance to structure-oriented predators. To address this second problem, we identified sites with similar types of total physical heterogeneity using an across-physical feature cluster analysis. Then, we calculated an additive heterogeneity index, which integrated all physical features at a site. Finally, we tested if site-specific additive heterogeneity index values differed for across-physical feature clusters. In PIE, the sites with the highest additive heterogeneity index values were clustered together and corresponded to sites where a fish predator, adult striped bass (Morone saxatilis), aggregated in a related acoustic tracking study. In summary, we have shown general approaches to quantifying site-specific heterogeneity.

LOFAR, VLA, and Chandra observations of the Toothbrush Galaxy Cluster

DOE PAGES

van Weeren, R. J.; Brunetti, G.; Bruggen, M.; ...

2016-02-22

We present deep LOFAR observations between 120 {181 MHz of the `Toothbrush' (RX J0603.3+4214), a cluster that contains one of the brightest radio relic sources known. Our LOFAR observations exploit a new and novel calibration scheme to probe 10 times deeper than any previous study in this relatively unexplored part of the spectrum. The LOFAR observations, when combined with VLA, GMRT, and Chandra X-ray data, provide new information about the nature of cluster merger shocks and their role in re-accelerating relativistic particles. We derive a spectral index of α = -0:8±0:1 at the northern edge of the main radio relic,more » steepening towards the south to α ≈ -2. The spectral index of the radio halo is remarkably uniform (α = -1:16, with an intrinsic scatter of ≤ 0:04). The observed radio relic spectral index gives a Mach number of M = 2:8 +0:5 -0:3, assuming diffusive shock acceleration (DSA). However, the gas density jump at the northern edge of the large radio relic implies a much weaker shock (M≈1:2, with an upper limit ofM≈1:5). The discrepancy between the Mach numbers calculated from the radio and X-rays can be explained if either (i) the relic traces a complex shock surface along the line of sight, or (ii) if the radio relic emission is produced by a re-accelerated population of fossil particles from a radio galaxy. Our results highlight the need for additional theoretical work and numerical simulations of particle acceleration and re-acceleration at cluster merger shocks.« less

Combined multivariate statistical techniques, Water Pollution Index (WPI) and Daniel Trend Test methods to evaluate temporal and spatial variations and trends of water quality at Shanchong River in the Northwest Basin of Lake Fuxian, China.

PubMed

Wang, Quan; Wu, Xianhua; Zhao, Bin; Qin, Jie; Peng, Tingchun

2015-01-01

Understanding spatial and temporal variations in river water quality and quantitatively evaluating the trend of changes are important in order to study and efficiently manage water resources. In this study, an analysis of Water Pollution Index (WPI), Daniel Trend Test, Cluster Analysis and Discriminant Analysis are applied as an integrated approach to quantitatively explore the spatial and temporal variations and the latent sources of water pollution in the Shanchong River basin, Northwest Basin of Lake Fuxian, China. We group all field surveys into 2 clusters (dry season and rainy season). Moreover, 14 sampling sites have been grouped into 3 clusters for the rainy season (highly polluted, moderately polluted and less polluted sites) and 2 clusters for the dry season (highly polluted and less polluted sites) based on their similarities and the level of pollution during the two seasons. The results show that the main trend of pollution was aggravated during the transition from the dry to the rainy season. The Water Pollution Index of Total Nitrogen is the highest of all pollution parameters, whereas the Chemical Oxygen Demand (Chromium) is the lowest. Our results also show that the main sources of pollution are farming activities alongside the Shanchong River, soil erosion and fish culture at Shanchong River reservoir area and domestic sewage from scattered rural residential area. Our results suggest that strategies to prevent water pollutionat the Shanchong River basin need to focus on non-point pollution control by employing appropriate fertilizer formulas in farming, and take the measures of soil and water conservation at Shanchong reservoir area, and purifying sewage from scattered villages.

Determining the efficacy of guppies and pyriproxyfen (Sumilarv® 2MR) combined with community engagement on dengue vectors in Cambodia: study protocol for a randomized controlled trial.

PubMed

Hustedt, John; Doum, Dyna; Keo, Vanney; Ly, Sokha; Sam, BunLeng; Chan, Vibol; Alexander, Neal; Bradley, John; Prasetyo, Didot Budi; Rachmat, Agus; Muhammad, Shafique; Lopes, Sergio; Leang, Rithea; Hii, Jeffrey

2017-08-04

Evidence on the effectiveness of low-cost, sustainable, biological vector-control tools for the Aedes mosquitoes is limited. Therefore, the purpose of this trial is to estimate the impact of guppy fish (guppies), in combination with the use of the larvicide pyriproxyfen (Sumilarv® 2MR), and Communication for Behavioral Impact (COMBI) activities to reduce entomological indices in Cambodia. In this cluster randomized controlled, superiority trial, 30 clusters comprising one or more villages each (with approximately 170 households) will be allocated, in a 1:1:1 ratio, to receive either (1) three interventions (guppies, Sumilarv® 2MR, and COMBI activities), (2) two interventions (guppies and COMBI activities), or (3) control (standard vector control). Households will be invited to participate, and entomology surveys among 40 randomly selected households per cluster will be carried out quarterly. The primary outcome will be the population density of adult female Aedes mosquitoes (i.e., number per house) trapped using adult resting collections. Secondary outcome measures will include the House Index, Container Index, Breteau Index, Pupae Per House, Pupae Per Person, mosquito infection rate, guppy fish coverage, Sumilarv® 2MR coverage, and percentage of respondents with knowledge about Aedes mosquitoes causing dengue. In the primary analysis, adult female Aedes density and mosquito infection rates will be aggregated over follow-up time points to give a single rate per cluster. This will be analyzed by negative binomial regression, yielding density ratios. This trial is expected to provide robust estimates of the intervention effect. A rigorous evaluation of these vector-control interventions is vital to developing an evidence-based dengue control strategy and to help direct government resources. Current Controlled Trials, ID: ISRCTN85307778 . Registered on 25 October 2015.

Combined Multivariate Statistical Techniques, Water Pollution Index (WPI) and Daniel Trend Test Methods to Evaluate Temporal and Spatial Variations and Trends of Water Quality at Shanchong River in the Northwest Basin of Lake Fuxian, China

PubMed Central

Wang, Quan; Wu, Xianhua; Zhao, Bin; Qin, Jie; Peng, Tingchun

2015-01-01

Understanding spatial and temporal variations in river water quality and quantitatively evaluating the trend of changes are important in order to study and efficiently manage water resources. In this study, an analysis of Water Pollution Index (WPI), Daniel Trend Test, Cluster Analysis and Discriminant Analysis are applied as an integrated approach to quantitatively explore the spatial and temporal variations and the latent sources of water pollution in the Shanchong River basin, Northwest Basin of Lake Fuxian, China. We group all field surveys into 2 clusters (dry season and rainy season). Moreover, 14 sampling sites have been grouped into 3 clusters for the rainy season (highly polluted, moderately polluted and less polluted sites) and 2 clusters for the dry season (highly polluted and less polluted sites) based on their similarities and the level of pollution during the two seasons. The results show that the main trend of pollution was aggravated during the transition from the dry to the rainy season. The Water Pollution Index of Total Nitrogen is the highest of all pollution parameters, whereas the Chemical Oxygen Demand (Chromium) is the lowest. Our results also show that the main sources of pollution are farming activities alongside the Shanchong River, soil erosion and fish culture at Shanchong River reservoir area and domestic sewage from scattered rural residential area. Our results suggest that strategies to prevent water pollutionat the Shanchong River basin need to focus on non-point pollution control by employing appropriate fertilizer formulas in farming, and take the measures of soil and water conservation at Shanchong reservoir area, and purifying sewage from scattered villages. PMID:25837673

Identification of alterations associated with age in the clustering structure of functional brain networks.

PubMed

Guzman, Grover E C; Sato, Joao R; Vidal, Maciel C; Fujita, Andre

2018-01-01

Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals' functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.

Sedentary behaviour and clustered metabolic risk in adolescents: the HELENA study.

PubMed

Rey-López, J P; Bel-Serrat, S; Santaliestra-Pasías, A; de Moraes, A C; Vicente-Rodríguez, G; Ruiz, J R; Artero, E G; Martínez-Gómez, D; Gottrand, F; De Henauw, S; Huybrechts, I; Polito, A; Molnar, D; Manios, Y; Moreno, L A

2013-10-01

Although sedentary behaviours are linked with mortality for cardiovascular reasons, it is not clear whether they are negatively related with cardio-metabolic risk factors. The aim was to examine the association between time engaged in television (TV) viewing or playing with videogames and a clustered cardio-metabolic risk in adolescents. Sedentary behaviours and physical activity were assessed in 769 adolescents (376 boys, aged 12.5-17.5 years) from the HELENA-CSS study. We measured systolic blood pressure, HOMA index, triglycerides, TC/HDL-c, VO₂max and the sum of four skinfolds, and a clustered metabolic risk index was computed. A multilevel regression model (by Poisson) was performed to calculate the prevalence ratio of having a clustered metabolic risk. In boys, playing >4 h/day with videogames (weekend) and moderate to vigorous PA (MVPA) was associated with cardio-metabolic risk after adjustment for age, maternal education and MVPA. In contrast, TV viewing was not associated with the presence of cardio-metabolic risk. In boys, playing with videogames may impair cardio-metabolic health during the adolescence. Adolescents should be encouraged to increase their participation in physical activity of at least moderate intensity to obtain a more favourable risk factor profile. Copyright © 2012 Elsevier B.V. All rights reserved.

A cloud-based framework for large-scale traditional Chinese medical record retrieval.

PubMed

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

Classification and Validation of Behavioral Subtypes of Learning-Disabled Children.

ERIC Educational Resources Information Center

Speece, Deborah L.; And Others

1985-01-01

Using the Classroom Behavior Inventory, teachers rated the behaviors of 63 school-identified, learning-disabled first and second graders. Hierarchical cluster analysis techniques identified seven distinct behavioral subtypes. Internal validation techniques indicated that the subtypes were replicable and had profile patterns different from a sample…

The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation.

PubMed

Profiti, Giuseppe; Martelli, Pier Luigi; Casadio, Rita

2017-07-03

BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.