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

Science.gov (United States)

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…

Swiss solar power statistics 2007 - Significant expansion

International Nuclear Information System (INIS)

Hostettler, T.

2008-01-01

This article presents and discusses the 2007 statistics for solar power in Switzerland. A significant number of new installations is noted as is the high production figures from newer installations. The basics behind the compilation of the Swiss solar power statistics are briefly reviewed and an overview for the period 1989 to 2007 is presented which includes figures on the number of photovoltaic plant in service and installed peak power. Typical production figures in kilowatt-hours (kWh) per installed kilowatt-peak power (kWp) are presented and discussed for installations of various sizes. Increased production after inverter replacement in older installations is noted. Finally, the general political situation in Switzerland as far as solar power is concerned are briefly discussed as are international developments.

Statistical Research of Investment Development of Russian Regions

Science.gov (United States)

Burtseva, Tatiana A.; Aleshnikova, Vera I.; Dubovik, Mayya V.; Naidenkova, Ksenya V.; Kovalchuk, Nadezda B.; Repetskaya, Natalia V.; Kuzmina, Oksana G.; Surkov, Anton A.; Bershadskaya, Olga I.; Smirennikova, Anna V.

2016-01-01

This article the article is concerned with a substantiation of procedures ensuring the implementation of statistical research and monitoring of investment development of the Russian regions, which would be pertinent for modern development of the state statistics. The aim of the study is to develop the methodological framework in order to estimate…

Test for the statistical significance of differences between ROC curves

International Nuclear Information System (INIS)

Metz, C.E.; Kronman, H.B.

1979-01-01

A test for the statistical significance of observed differences between two measured Receiver Operating Characteristic (ROC) curves has been designed and evaluated. The set of observer response data for each ROC curve is assumed to be independent and to arise from a ROC curve having a form which, in the absence of statistical fluctuations in the response data, graphs as a straight line on double normal-deviate axes. To test the significance of an apparent difference between two measured ROC curves, maximum likelihood estimates of the two parameters of each curve and the associated parameter variances and covariance are calculated from the corresponding set of observer response data. An approximate Chi-square statistic with two degrees of freedom is then constructed from the differences between the parameters estimated for each ROC curve and from the variances and covariances of these estimates. This statistic is known to be truly Chi-square distributed only in the limit of large numbers of trials in the observer performance experiments. Performance of the statistic for data arising from a limited number of experimental trials was evaluated. Independent sets of rating scale data arising from the same underlying ROC curve were paired, and the fraction of differences found (falsely) significant was compared to the significance level, α, used with the test. Although test performance was found to be somewhat dependent on both the number of trials in the data and the position of the underlying ROC curve in the ROC space, the results for various significance levels showed the test to be reliable under practical experimental conditions

On detection and assessment of statistical significance of Genomic Islands

Directory of Open Access Journals (Sweden)

Chaudhuri Probal

2008-04-01

Full Text Available Abstract Background Many of the available methods for detecting Genomic Islands (GIs in prokaryotic genomes use markers such as transposons, proximal tRNAs, flanking repeats etc., or they use other supervised techniques requiring training datasets. Most of these methods are primarily based on the biases in GC content or codon and amino acid usage of the islands. However, these methods either do not use any formal statistical test of significance or use statistical tests for which the critical values and the P-values are not adequately justified. We propose a method, which is unsupervised in nature and uses Monte-Carlo statistical tests based on randomly selected segments of a chromosome. Such tests are supported by precise statistical distribution theory, and consequently, the resulting P-values are quite reliable for making the decision. Results Our algorithm (named Design-Island, an acronym for Detection of Statistically Significant Genomic Island runs in two phases. Some 'putative GIs' are identified in the first phase, and those are refined into smaller segments containing horizontally acquired genes in the refinement phase. This method is applied to Salmonella typhi CT18 genome leading to the discovery of several new pathogenicity, antibiotic resistance and metabolic islands that were missed by earlier methods. Many of these islands contain mobile genetic elements like phage-mediated genes, transposons, integrase and IS elements confirming their horizontal acquirement. Conclusion The proposed method is based on statistical tests supported by precise distribution theory and reliable P-values along with a technique for visualizing statistically significant islands. The performance of our method is better than many other well known methods in terms of their sensitivity and accuracy, and in terms of specificity, it is comparable to other methods.

Increasing the statistical significance of entanglement detection in experiments.

Science.gov (United States)

Jungnitsch, Bastian; Niekamp, Sönke; Kleinmann, Matthias; Gühne, Otfried; Lu, He; Gao, Wei-Bo; Chen, Yu-Ao; Chen, Zeng-Bing; Pan, Jian-Wei

2010-05-28

Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. Experimentally, we observe this phenomenon in a four-photon experiment, testing the Mermin and Ardehali inequality for different levels of noise. Furthermore, we provide a way to develop entanglement tests with high statistical significance.

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

Science.gov (United States)

Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

Region 7 Significant Ecological Resource Areas (ECO_RES.SIG_REGIONS)

Data.gov (United States)

U.S. Environmental Protection Agency — SIG_REGIONS is a boundary layer that displays Region 7's Significant Ecological Resource Areas. This layer represents large areas within which different ecosystem...

TECHNIQUE OF THE STATISTICAL ANALYSIS OF INVESTMENT APPEAL OF THE REGION

Directory of Open Access Journals (Sweden)

А. А. Vershinina

2014-01-01

Full Text Available The technique of the statistical analysis of investment appeal of the region is given in scientific article for direct foreign investments. Definition of a technique of the statistical analysis is given, analysis stages reveal, the mathematico-statistical tools are considered.

Statistical Significance for Hierarchical Clustering

Science.gov (United States)

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Cloud Statistics and Discrimination in the Polar Regions

Science.gov (United States)

Chan, M.; Comiso, J. C.

2012-12-01

Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice

Statistical significance of trends in monthly heavy precipitation over the US

KAUST Repository

Mahajan, Salil

2011-05-11

Trends in monthly heavy precipitation, defined by a return period of one year, are assessed for statistical significance in observations and Global Climate Model (GCM) simulations over the contiguous United States using Monte Carlo non-parametric and parametric bootstrapping techniques. The results from the two Monte Carlo approaches are found to be similar to each other, and also to the traditional non-parametric Kendall\\'s τ test, implying the robustness of the approach. Two different observational data-sets are employed to test for trends in monthly heavy precipitation and are found to exhibit consistent results. Both data-sets demonstrate upward trends, one of which is found to be statistically significant at the 95% confidence level. Upward trends similar to observations are observed in some climate model simulations of the twentieth century, but their statistical significance is marginal. For projections of the twenty-first century, a statistically significant upwards trend is observed in most of the climate models analyzed. The change in the simulated precipitation variance appears to be more important in the twenty-first century projections than changes in the mean precipitation. Stochastic fluctuations of the climate-system are found to be dominate monthly heavy precipitation as some GCM simulations show a downwards trend even in the twenty-first century projections when the greenhouse gas forcings are strong. © 2011 Springer-Verlag.

Mixed deterministic statistical modelling of regional ozone air pollution

KAUST Repository

Kalenderski, Stoitchko

2011-03-17

We develop a physically motivated statistical model for regional ozone air pollution by separating the ground-level pollutant concentration field into three components, namely: transport, local production and large-scale mean trend mostly dominated by emission rates. The model is novel in the field of environmental spatial statistics in that it is a combined deterministic-statistical model, which gives a new perspective to the modelling of air pollution. The model is presented in a Bayesian hierarchical formalism, and explicitly accounts for advection of pollutants, using the advection equation. We apply the model to a specific case of regional ozone pollution-the Lower Fraser valley of British Columbia, Canada. As a predictive tool, we demonstrate that the model vastly outperforms existing, simpler modelling approaches. Our study highlights the importance of simultaneously considering different aspects of an air pollution problem as well as taking into account the physical bases that govern the processes of interest. © 2011 John Wiley & Sons, Ltd..

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance.

Science.gov (United States)

Kramer, Karen L; Veile, Amanda; Otárola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children's growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children's monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1) as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2) competition from young siblings will negatively impact child growth during the post weaning period; 3) however because of their economic value, older siblings will have a negligible effect on young children's growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children's growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children's growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance.

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance.

Directory of Open Access Journals (Sweden)

Karen L Kramer

Full Text Available Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children's growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children's monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1 as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2 competition from young siblings will negatively impact child growth during the post weaning period; 3 however because of their economic value, older siblings will have a negligible effect on young children's growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children's growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children's growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance.

Increasing the statistical significance of entanglement detection in experiments

Energy Technology Data Exchange (ETDEWEB)

Jungnitsch, Bastian; Niekamp, Soenke; Kleinmann, Matthias; Guehne, Otfried [Institut fuer Quantenoptik und Quanteninformation, Innsbruck (Austria); Lu, He; Gao, Wei-Bo; Chen, Zeng-Bing [Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei (China); Chen, Yu-Ao; Pan, Jian-Wei [Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei (China); Physikalisches Institut, Universitaet Heidelberg (Germany)

2010-07-01

Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. We show this to be the case for an error model in which the variance of an observable is interpreted as its error and for the standard error model in photonic experiments. Specifically, we demonstrate that the Mermin inequality yields a Bell test which is statistically more significant than the Ardehali inequality in the case of a photonic four-qubit state that is close to a GHZ state. Experimentally, we observe this phenomenon in a four-photon experiment, testing the above inequalities for different levels of noise.

Reporting effect sizes as a supplement to statistical significance ...

African Journals Online (AJOL)

The purpose of the article is to review the statistical significance reporting practices in reading instruction studies and to provide guidelines for when to calculate and report effect sizes in educational research. A review of six readily accessible (online) and accredited journals publishing research on reading instruction ...

Statistical Analysis of the Impacts of Regional Transportation on the Air Quality in Beijing

Science.gov (United States)

Huang, Zhongwen; Zhang, Huiling; Tong, Lei; Xiao, Hang

2016-04-01

From October to December 2015, Beijing-Tianjin-Hebei (BTH) region had experienced several severe haze events. In order to assess the effects of the regional transportation on the air quality in Beijing, the air monitoring data (PM2.5, SO2, NO2 and CO) from that period published by Chinese National Environmental Monitoring Center (CNEMC) was collected and analyzed with various statistical models. The cities within BTH area were clustered into three groups according to the geographical conditions, while the air pollutant concentrations of cities within a group sharing similar variation trends. The Granger causality test results indicate that significant causal relationships exist between the air pollutant data of Beijing and its surrounding cities (Baoding, Chengde, Tianjin and Zhangjiakou) for the reference period. Then, linear regression models were constructed to capture the interdependency among the multiple time series. It shows that the observed air pollutant concentrations in Beijing were well consistent with the model-fitted results. More importantly, further analysis suggests that the air pollutants in Beijing were strongly affected by regional transportation, as the local sources only contributed 17.88%, 27.12%, 14.63% and 31.36% of PM2.5, SO2, NO2 and CO concentrations, respectively. And the major foreign source for Beijing was from Southwest (Baoding) direction, account for more than 42% of all these air pollutants. Thus, by combining various statistical models, it may not only be able to quickly predict the air qualities of any cities on a regional scale, but also to evaluate the local and regional source contributions for a particular city. Key words: regional transportation, air pollution, Granger causality test, statistical models

Your Chi-Square Test Is Statistically Significant: Now What?

Science.gov (United States)

Sharpe, Donald

2015-01-01

Applied researchers have employed chi-square tests for more than one hundred years. This paper addresses the question of how one should follow a statistically significant chi-square test result in order to determine the source of that result. Four approaches were evaluated: calculating residuals, comparing cells, ransacking, and partitioning. Data…

Detection by voxel-wise statistical analysis of significant changes in regional cerebral glucose uptake in an APP/PS1 transgenic mouse model of Alzheimer's disease.

Science.gov (United States)

Dubois, Albertine; Hérard, Anne-Sophie; Delatour, Benoît; Hantraye, Philippe; Bonvento, Gilles; Dhenain, Marc; Delzescaux, Thierry

2010-06-01

Biomarkers and technologies similar to those used in humans are essential for the follow-up of Alzheimer's disease (AD) animal models, particularly for the clarification of mechanisms and the screening and validation of new candidate treatments. In humans, changes in brain metabolism can be detected by 1-deoxy-2-[(18)F] fluoro-D-glucose PET (FDG-PET) and assessed in a user-independent manner with dedicated software, such as Statistical Parametric Mapping (SPM). FDG-PET can be carried out in small animals, but its resolution is low as compared to the size of rodent brain structures. In mouse models of AD, changes in cerebral glucose utilization are usually detected by [(14)C]-2-deoxyglucose (2DG) autoradiography, but this requires prior manual outlining of regions of interest (ROI) on selected sections. Here, we evaluate the feasibility of applying the SPM method to 3D autoradiographic data sets mapping brain metabolic activity in a transgenic mouse model of AD. We report the preliminary results obtained with 4 APP/PS1 (64+/-1 weeks) and 3 PS1 (65+/-2 weeks) mice. We also describe new procedures for the acquisition and use of "blockface" photographs and provide the first demonstration of their value for the 3D reconstruction and spatial normalization of post mortem mouse brain volumes. Despite this limited sample size, our results appear to be meaningful, consistent, and more comprehensive than findings from previously published studies based on conventional ROI-based methods. The establishment of statistical significance at the voxel level, rather than with a user-defined ROI, makes it possible to detect more reliably subtle differences in geometrically complex regions, such as the hippocampus. Our approach is generic and could be easily applied to other biomarkers and extended to other species and applications. Copyright 2010 Elsevier Inc. All rights reserved.

Confidence intervals permit, but don't guarantee, better inference than statistical significance testing

Directory of Open Access Journals (Sweden)

Melissa Coulson

2010-07-01

Full Text Available A statistically significant result, and a non-significant result may differ little, although significance status may tempt an interpretation of difference. Two studies are reported that compared interpretation of such results presented using null hypothesis significance testing (NHST, or confidence intervals (CIs. Authors of articles published in psychology, behavioural neuroscience, and medical journals were asked, via email, to interpret two fictitious studies that found similar results, one statistically significant, and the other non-significant. Responses from 330 authors varied greatly, but interpretation was generally poor, whether results were presented as CIs or using NHST. However, when interpreting CIs respondents who mentioned NHST were 60% likely to conclude, unjustifiably, the two results conflicted, whereas those who interpreted CIs without reference to NHST were 95% likely to conclude, justifiably, the two results were consistent. Findings were generally similar for all three disciplines. An email survey of academic psychologists confirmed that CIs elicit better interpretations if NHST is not invoked. Improved statistical inference can result from encouragement of meta-analytic thinking and use of CIs but, for full benefit, such highly desirable statistical reform requires also that researchers interpret CIs without recourse to NHST.

Significance analysis of the regional differences on icing time of water onto fire protective clothing

Science.gov (United States)

Zhao, L. Z.; Jing, L. S.; Zhang, X. Z.; Xia, J. J.; Chen, Y.; Chen, T.; Hu, C.; Bao, Z. M.; Fu, X. C.; Wang, R. J.; Wang, Y.; Wang, Y. J.

2017-09-01

The object of this work was to determine the icing temperature in icing experiment. Firstly, a questionnaire investigation was carried out on 38 fire detachments in different regions. These Statistical percentage results were divided into northern east group and northern west group. Secondly, a significance analysis between these two results was made using Mann-Whitney U test. Then the icing temperature was determined in different regions. Thirdly, the icing experiment was made in the environment of -20°C in Daxing’an Mountain. The anti-icing effect of new fire protective clothing was verified in this icing.

Testing statistical significance scores of sequence comparison methods with structure similarity

Directory of Open Access Journals (Sweden)

Leunissen Jack AM

2006-10-01

Full Text Available Abstract Background In the past years the Smith-Waterman sequence comparison algorithm has gained popularity due to improved implementations and rapidly increasing computing power. However, the quality and sensitivity of a database search is not only determined by the algorithm but also by the statistical significance testing for an alignment. The e-value is the most commonly used statistical validation method for sequence database searching. The CluSTr database and the Protein World database have been created using an alternative statistical significance test: a Z-score based on Monte-Carlo statistics. Several papers have described the superiority of the Z-score as compared to the e-value, using simulated data. We were interested if this could be validated when applied to existing, evolutionary related protein sequences. Results All experiments are performed on the ASTRAL SCOP database. The Smith-Waterman sequence comparison algorithm with both e-value and Z-score statistics is evaluated, using ROC, CVE and AP measures. The BLAST and FASTA algorithms are used as reference. We find that two out of three Smith-Waterman implementations with e-value are better at predicting structural similarities between proteins than the Smith-Waterman implementation with Z-score. SSEARCH especially has very high scores. Conclusion The compute intensive Z-score does not have a clear advantage over the e-value. The Smith-Waterman implementations give generally better results than their heuristic counterparts. We recommend using the SSEARCH algorithm combined with e-values for pairwise sequence comparisons.

Statistical significance versus clinical relevance.

Science.gov (United States)

van Rijn, Marieke H C; Bech, Anneke; Bouyer, Jean; van den Brand, Jan A J G

2017-04-01

In March this year, the American Statistical Association (ASA) posted a statement on the correct use of P-values, in response to a growing concern that the P-value is commonly misused and misinterpreted. We aim to translate these warnings given by the ASA into a language more easily understood by clinicians and researchers without a deep background in statistics. Moreover, we intend to illustrate the limitations of P-values, even when used and interpreted correctly, and bring more attention to the clinical relevance of study findings using two recently reported studies as examples. We argue that P-values are often misinterpreted. A common mistake is saying that P < 0.05 means that the null hypothesis is false, and P ≥0.05 means that the null hypothesis is true. The correct interpretation of a P-value of 0.05 is that if the null hypothesis were indeed true, a similar or more extreme result would occur 5% of the times upon repeating the study in a similar sample. In other words, the P-value informs about the likelihood of the data given the null hypothesis and not the other way around. A possible alternative related to the P-value is the confidence interval (CI). It provides more information on the magnitude of an effect and the imprecision with which that effect was estimated. However, there is no magic bullet to replace P-values and stop erroneous interpretation of scientific results. Scientists and readers alike should make themselves familiar with the correct, nuanced interpretation of statistical tests, P-values and CIs. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Statistical significance of epidemiological data. Seminar: Evaluation of epidemiological studies

International Nuclear Information System (INIS)

Weber, K.H.

1993-01-01

In stochastic damages, the numbers of events, e.g. the persons who are affected by or have died of cancer, and thus the relative frequencies (incidence or mortality) are binomially distributed random variables. Their statistical fluctuations can be characterized by confidence intervals. For epidemiologic questions, especially for the analysis of stochastic damages in the low dose range, the following issues are interesting: - Is a sample (a group of persons) with a definite observed damage frequency part of the whole population? - Is an observed frequency difference between two groups of persons random or statistically significant? - Is an observed increase or decrease of the frequencies with increasing dose random or statistically significant and how large is the regression coefficient (= risk coefficient) in this case? These problems can be solved by sttistical tests. So-called distribution-free tests and tests which are not bound to the supposition of normal distribution are of particular interest, such as: - χ 2 -independence test (test in contingency tables); - Fisher-Yates-test; - trend test according to Cochran; - rank correlation test given by Spearman. These tests are explained in terms of selected epidemiologic data, e.g. of leukaemia clusters, of the cancer mortality of the Japanese A-bomb survivors especially in the low dose range as well as on the sample of the cancer mortality in the high background area in Yangjiang (China). (orig.) [de

9th Annual UNCG Regional Mathematics and Statistics Conference

CERN Document Server

Chhetri, Maya; Gupta, Sat; Shivaji, Ratnasingham

2015-01-01

This volume contains rigorously reviewed papers on the topics presented by students at The 9th Annual University of North Carolina at Greensboro Regional Mathematics and Statistics Conference (UNCG RMSC) that took place on November 2, 2013.  All papers are coauthored by student researchers and their faculty mentors. This conference series was inaugurated in 2005, and it now attracts over 150 participants from over 30 universities from North Carolina and surrounding states. The conference is specifically tailored for students to present their research projects that encompass a broad spectrum of topics in mathematics, mathematical biology, statistics, and computer science.

Statistical Significance and Effect Size: Two Sides of a Coin.

Science.gov (United States)

Fan, Xitao

This paper suggests that statistical significance testing and effect size are two sides of the same coin; they complement each other, but do not substitute for one another. Good research practice requires that both should be taken into consideration to make sound quantitative decisions. A Monte Carlo simulation experiment was conducted, and a…

Publication of statistically significant research findings in prosthodontics & implant dentistry in the context of other dental specialties.

Science.gov (United States)

Papageorgiou, Spyridon N; Kloukos, Dimitrios; Petridis, Haralampos; Pandis, Nikolaos

2015-10-01

To assess the hypothesis that there is excessive reporting of statistically significant studies published in prosthodontic and implantology journals, which could indicate selective publication. The last 30 issues of 9 journals in prosthodontics and implant dentistry were hand-searched for articles with statistical analyses. The percentages of significant and non-significant results were tabulated by parameter of interest. Univariable/multivariable logistic regression analyses were applied to identify possible predictors of reporting statistically significance findings. The results of this study were compared with similar studies in dentistry with random-effects meta-analyses. From the 2323 included studies 71% of them reported statistically significant results, with the significant results ranging from 47% to 86%. Multivariable modeling identified that geographical area and involvement of statistician were predictors of statistically significant results. Compared to interventional studies, the odds that in vitro and observational studies would report statistically significant results was increased by 1.20 times (OR: 2.20, 95% CI: 1.66-2.92) and 0.35 times (OR: 1.35, 95% CI: 1.05-1.73), respectively. The probability of statistically significant results from randomized controlled trials was significantly lower compared to various study designs (difference: 30%, 95% CI: 11-49%). Likewise the probability of statistically significant results in prosthodontics and implant dentistry was lower compared to other dental specialties, but this result did not reach statistical significant (P>0.05). The majority of studies identified in the fields of prosthodontics and implant dentistry presented statistically significant results. The same trend existed in publications of other specialties in dentistry. Copyright © 2015 Elsevier Ltd. All rights reserved.

Significant Statistics: Viewed with a Contextual Lens

Science.gov (United States)

Tait-McCutcheon, Sandi

2010-01-01

This paper examines the pedagogical and organisational changes three lead teachers made to their statistics teaching and learning programs. The lead teachers posed the research question: What would the effect of contextually integrating statistical investigations and literacies into other curriculum areas be on student achievement? By finding the…

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

Science.gov (United States)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is

"What If" Analyses: Ways to Interpret Statistical Significance Test Results Using EXCEL or "R"

Science.gov (United States)

Ozturk, Elif

2012-01-01

The present paper aims to review two motivations to conduct "what if" analyses using Excel and "R" to understand the statistical significance tests through the sample size context. "What if" analyses can be used to teach students what statistical significance tests really do and in applied research either prospectively to estimate what sample size…

Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions

Science.gov (United States)

Santos, João A.; Malheiro, Aureliano C.; Karremann, Melanie K.; Pinto, Joaquim G.

2011-03-01

The impact of projected climate change on wine production was analysed for the Demarcated Region of Douro, Portugal. A statistical grapevine yield model (GYM) was developed using climate parameters as predictors. Statistically significant correlations were identified between annual yield and monthly mean temperatures and monthly precipitation totals during the growing cycle. These atmospheric factors control grapevine yield in the region, with the GYM explaining 50.4% of the total variance in the yield time series in recent decades. Anomalously high March rainfall (during budburst, shoot and inflorescence development) favours yield, as well as anomalously high temperatures and low precipitation amounts in May and June (May: flowering and June: berry development). The GYM was applied to a regional climate model output, which was shown to realistically reproduce the GYM predictors. Finally, using ensemble simulations under the A1B emission scenario, projections for GYM-derived yield in the Douro Region, and for the whole of the twenty-first century, were analysed. A slight upward trend in yield is projected to occur until about 2050, followed by a steep and continuous increase until the end of the twenty-first century, when yield is projected to be about 800 kg/ha above current values. While this estimate is based on meteorological parameters alone, changes due to elevated CO2 may further enhance this effect. In spite of the associated uncertainties, it can be stated that projected climate change may significantly benefit wine yield in the Douro Valley.

Statistical vs. Economic Significance in Economics and Econometrics: Further comments on McCloskey & Ziliak

DEFF Research Database (Denmark)

Engsted, Tom

I comment on the controversy between McCloskey & Ziliak and Hoover & Siegler on statistical versus economic significance, in the March 2008 issue of the Journal of Economic Methodology. I argue that while McCloskey & Ziliak are right in emphasizing 'real error', i.e. non-sampling error that cannot...... be eliminated through specification testing, they fail to acknowledge those areas in economics, e.g. rational expectations macroeconomics and asset pricing, where researchers clearly distinguish between statistical and economic significance and where statistical testing plays a relatively minor role in model...

Regionally Significant Ecological Areas - MLCCS derived 2008

Data.gov (United States)

Minnesota Department of Natural Resources — This is an analysis of regionally significant Terrestrial and Wetland Ecological Areas in the seven county metropolitan area. Individual forest, grassland and...

Methodological Problems Of Statistical Study Of Regional Tourism And Tourist Expenditure

Directory of Open Access Journals (Sweden)

Anton Olegovich Ovcharov

2015-03-01

Full Text Available The aim of the work is the analysis of the problems of regional tourism statistics. The subject of the research is the tourism expenditure, the specificity of their recording and modeling. The methods of statistical observation and factor analysis are used. The article shows the features and directions of statistical methodology of tourism. A brief review of international publications on statistical studies of tourist expenditure is made. It summarizes the data from different statistical forms and shows the positive and negative trends in the development of tourism in Russia. It is concluded that the tourist industry in Russia is focused on outbound tourism rather than on inbound or internal. The features of statistical accounting and statistical analysis of tourism expenditure in Russian and international statistics are described. To assess the level of development of regional tourism the necessity of use the coefficient of efficiency of tourism. The reasons of the prevalence of imports over exports of tourism services are revealed using the data of the balance of payments. This is due to the raw material orientation of Russian exports and low specific weight of the account “Services” in the structure of the balance of payments. The additive model is also proposed in the paper. It describes the influence of three factors on the changes in tourist expenditure. These factors are the number of trips, the cost of a trip and structural changes in destinations and travel purposes. On the basis of the data from 2012–2013 we estimate the force and the direction of the influence of each factor. Testing of the model showed that the increase in tourism exports caused by the combined positive impact of all three factors, chief of which is the growing number of foreigners who visited Russia during the concerned period.

SAR Imagery Segmentation by Statistical Region Growing and Hierarchical Merging

Energy Technology Data Exchange (ETDEWEB)

Ushizima, Daniela Mayumi; Carvalho, E.A.; Medeiros, F.N.S.; Martins, C.I.O.; Marques, R.C.P.; Oliveira, I.N.S.

2010-05-22

This paper presents an approach to accomplish synthetic aperture radar (SAR) image segmentation, which are corrupted by speckle noise. Some ordinary segmentation techniques may require speckle filtering previously. Our approach performs radar image segmentation using the original noisy pixels as input data, eliminating preprocessing steps, an advantage over most of the current methods. The algorithm comprises a statistical region growing procedure combined with hierarchical region merging to extract regions of interest from SAR images. The region growing step over-segments the input image to enable region aggregation by employing a combination of the Kolmogorov-Smirnov (KS) test with a hierarchical stepwise optimization (HSWO) algorithm for the process coordination. We have tested and assessed the proposed technique on artificially speckled image and real SAR data containing different types of targets.

Distinguishing between statistical significance and practical/clinical meaningfulness using statistical inference.

Science.gov (United States)

Wilkinson, Michael

2014-03-01

Decisions about support for predictions of theories in light of data are made using statistical inference. The dominant approach in sport and exercise science is the Neyman-Pearson (N-P) significance-testing approach. When applied correctly it provides a reliable procedure for making dichotomous decisions for accepting or rejecting zero-effect null hypotheses with known and controlled long-run error rates. Type I and type II error rates must be specified in advance and the latter controlled by conducting an a priori sample size calculation. The N-P approach does not provide the probability of hypotheses or indicate the strength of support for hypotheses in light of data, yet many scientists believe it does. Outcomes of analyses allow conclusions only about the existence of non-zero effects, and provide no information about the likely size of true effects or their practical/clinical value. Bayesian inference can show how much support data provide for different hypotheses, and how personal convictions should be altered in light of data, but the approach is complicated by formulating probability distributions about prior subjective estimates of population effects. A pragmatic solution is magnitude-based inference, which allows scientists to estimate the true magnitude of population effects and how likely they are to exceed an effect magnitude of practical/clinical importance, thereby integrating elements of subjective Bayesian-style thinking. While this approach is gaining acceptance, progress might be hastened if scientists appreciate the shortcomings of traditional N-P null hypothesis significance testing.

Hierarchical probabilistic regionalization of volcanism for Sengan region in Japan using multivariate statistical techniques and geostatistical interpolation techniques

International Nuclear Information System (INIS)

Park, Jinyong; Balasingham, P.; McKenna, Sean Andrew; Kulatilake, Pinnaduwa H. S. W.

2004-01-01

Sandia National Laboratories, under contract to Nuclear Waste Management Organization of Japan (NUMO), is performing research on regional classification of given sites in Japan with respect to potential volcanic disruption using multivariate statistics and geo-statistical interpolation techniques. This report provides results obtained for hierarchical probabilistic regionalization of volcanism for the Sengan region in Japan by applying multivariate statistical techniques and geostatistical interpolation techniques on the geologic data provided by NUMO. A workshop report produced in September 2003 by Sandia National Laboratories (Arnold et al., 2003) on volcanism lists a set of most important geologic variables as well as some secondary information related to volcanism. Geologic data extracted for the Sengan region in Japan from the data provided by NUMO revealed that data are not available at the same locations for all the important geologic variables. In other words, the geologic variable vectors were found to be incomplete spatially. However, it is necessary to have complete geologic variable vectors to perform multivariate statistical analyses. As a first step towards constructing complete geologic variable vectors, the Universal Transverse Mercator (UTM) zone 54 projected coordinate system and a 1 km square regular grid system were selected. The data available for each geologic variable on a geographic coordinate system were transferred to the aforementioned grid system. Also the recorded data on volcanic activity for Sengan region were produced on the same grid system. Each geologic variable map was compared with the recorded volcanic activity map to determine the geologic variables that are most important for volcanism. In the regionalized classification procedure, this step is known as the variable selection step. The following variables were determined as most important for volcanism: geothermal gradient, groundwater temperature, heat discharge, groundwater

Codon Deviation Coefficient: a novel measure for estimating codon usage bias and its statistical significance

Directory of Open Access Journals (Sweden)

Zhang Zhang

2012-03-01

Full Text Available Abstract Background Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB. Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis. Results Here we propose a novel measure--Codon Deviation Coefficient (CDC--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance. Conclusions As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions.

Statistical Study of Corruption in the Region (on the Example of the Rostov Region

Directory of Open Access Journals (Sweden)

Kirill A. Belokrylov

2016-09-01

Full Text Available The paper proves the effectiveness of the using of statistical methods for evaluation of the corruption level as a result of its, on the one hand, latency, concealment of official statistical accounting, and on the other - the scale of corruption in Russia. The comparative analysis of the substantial characteristics of the nature of corruption by Russian and foreign scientists, as well as their reflection in the law has allowed to develop a questionnaire to adequately assess the levels, causes and the effectiveness of implementation of the policy on the fight against corruption as the most important social indicator of inefficient institutions. Analysis of the results of the economic and sociological survey of the population of the Rostov region revealed a shift of corruption performance in the region in the direction of the education system as a result of the dominance in the selection of students, but it led to the conclusion about the need to tighten legislation on the fight against corruption (72% of respondents, including the confiscation of the property (79,1%, the dismissal of corrupt officials, the ban on public office. The necessity of further in-depth statistical studies of corruption on the development of more effective measures is improved to combat it as a tool for removal of the Russian economy from the crisis and ensure that it is more sustainable growth than projected in the 2020s (the lost decade 1,5% positive GDP dynamics.

Statistics Refresher for Molecular Imaging Technologists, Part 2: Accuracy of Interpretation, Significance, and Variance.

Science.gov (United States)

Farrell, Mary Beth

2018-06-01

This article is the second part of a continuing education series reviewing basic statistics that nuclear medicine and molecular imaging technologists should understand. In this article, the statistics for evaluating interpretation accuracy, significance, and variance are discussed. Throughout the article, actual statistics are pulled from the published literature. We begin by explaining 2 methods for quantifying interpretive accuracy: interreader and intrareader reliability. Agreement among readers can be expressed simply as a percentage. However, the Cohen κ-statistic is a more robust measure of agreement that accounts for chance. The higher the κ-statistic is, the higher is the agreement between readers. When 3 or more readers are being compared, the Fleiss κ-statistic is used. Significance testing determines whether the difference between 2 conditions or interventions is meaningful. Statistical significance is usually expressed using a number called a probability ( P ) value. Calculation of P value is beyond the scope of this review. However, knowing how to interpret P values is important for understanding the scientific literature. Generally, a P value of less than 0.05 is considered significant and indicates that the results of the experiment are due to more than just chance. Variance, standard deviation (SD), confidence interval, and standard error (SE) explain the dispersion of data around a mean of a sample drawn from a population. SD is commonly reported in the literature. A small SD indicates that there is not much variation in the sample data. Many biologic measurements fall into what is referred to as a normal distribution taking the shape of a bell curve. In a normal distribution, 68% of the data will fall within 1 SD, 95% will fall within 2 SDs, and 99.7% will fall within 3 SDs. Confidence interval defines the range of possible values within which the population parameter is likely to lie and gives an idea of the precision of the statistic being

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

Science.gov (United States)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and

Systematic reviews of anesthesiologic interventions reported as statistically significant

DEFF Research Database (Denmark)

Imberger, Georgina; Gluud, Christian; Boylan, John

2015-01-01

statistically significant meta-analyses of anesthesiologic interventions, we used TSA to estimate power and imprecision in the context of sparse data and repeated updates. METHODS: We conducted a search to identify all systematic reviews with meta-analyses that investigated an intervention that may......: From 11,870 titles, we found 682 systematic reviews that investigated anesthesiologic interventions. In the 50 sampled meta-analyses, the median number of trials included was 8 (interquartile range [IQR], 5-14), the median number of participants was 964 (IQR, 523-1736), and the median number...

A Statistical Model for Regional Tornado Climate Studies.

Science.gov (United States)

Jagger, Thomas H; Elsner, James B; Widen, Holly M

2015-01-01

Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA). A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.

A Study on Grid-Square Statistics Based Estimation of Regional Electricity Demand and Regional Potential Capacity of Distributed Generators

Science.gov (United States)

Kato, Takeyoshi; Sugimoto, Hiroyuki; Suzuoki, Yasuo

We established a procedure for estimating regional electricity demand and regional potential capacity of distributed generators (DGs) by using a grid square statistics data set. A photovoltaic power system (PV system) for residential use and a co-generation system (CGS) for both residential and commercial use were taken into account. As an example, the result regarding Aichi prefecture was presented in this paper. The statistical data of the number of households by family-type and the number of employees by business category for about 4000 grid-square with 1km × 1km area was used to estimate the floor space or the electricity demand distribution. The rooftop area available for installing PV systems was also estimated with the grid-square statistics data set. Considering the relation between a capacity of existing CGS and a scale-index of building where CGS is installed, the potential capacity of CGS was estimated for three business categories, i.e. hotel, hospital, store. In some regions, the potential capacity of PV systems was estimated to be about 10,000kW/km2, which corresponds to the density of the existing area with intensive installation of PV systems. Finally, we discussed the ratio of regional potential capacity of DGs to regional maximum electricity demand for deducing the appropriate capacity of DGs in the model of future electricity distribution system.

P-Value, a true test of statistical significance? a cautionary note ...

African Journals Online (AJOL)

While it's not the intention of the founders of significance testing and hypothesis testing to have the two ideas intertwined as if they are complementary, the inconvenient marriage of the two practices into one coherent, convenient, incontrovertible and misinterpreted practice has dotted our standard statistics textbooks and ...

Codon Deviation Coefficient: A novel measure for estimating codon usage bias and its statistical significance

KAUST Repository

Zhang, Zhang

2012-03-22

Background: Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB). Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis.Results: Here we propose a novel measure--Codon Deviation Coefficient (CDC)--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance.Conclusions: As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions. 2012 Zhang et al; licensee BioMed Central Ltd.

Transition-Region Ultraviolet Explosive Events in IRIS Si IV: A Statistical Analysis

Science.gov (United States)

Bartz, Allison

2018-01-01

Explosive events (EEs) in the solar transition region are characterized by broad, non-Gaussian line profiles with wings at Doppler velocities exceeding the speed of sound. We present a statistical analysis of 23 IRIS (Interface Region Imaging Spectrograph) sit-and-stare observations, observed between April 2014 and March 2017. Using the IRIS Si IV 1394 Å and 1403 Å spectral windows and the 1400Å Slit Jaw images we have identified 581 EEs. We found that most EEs last less than 20 min. and have a spatial scale on the slit less than 10”, agreeing with measurements in previous work. We observed most EEs in active regions, regardless of date of observation, but selection bias of IRIS observations cannot be ruled out. We also present preliminary findings of optical depth effects from our statistical study.

Interpreting Statistical Significance Test Results: A Proposed New "What If" Method.

Science.gov (United States)

Kieffer, Kevin M.; Thompson, Bruce

As the 1994 publication manual of the American Psychological Association emphasized, "p" values are affected by sample size. As a result, it can be helpful to interpret the results of statistical significant tests in a sample size context by conducting so-called "what if" analyses. However, these methods can be inaccurate…

Measuring individual significant change on the Beck Depression Inventory-II through IRT-based statistics.

NARCIS (Netherlands)

Brouwer, D.; Meijer, R.R.; Zevalkink, D.J.

2013-01-01

Several researchers have emphasized that item response theory (IRT)-based methods should be preferred over classical approaches in measuring change for individual patients. In the present study we discuss and evaluate the use of IRT-based statistics to measure statistical significant individual

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

Science.gov (United States)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as "field" or "global" significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Monthly temperature climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the

Radiotherapy is associated with significant improvement in local and regional control in Merkel cell carcinoma

International Nuclear Information System (INIS)

Kang, Susan H; Haydu, Lauren E; Goh, Robin Yeong Hong; Fogarty, Gerald B

2012-01-01

Merkel cell carcinoma (MCC) is a rare tumour of skin. This study is a retrospective audit of patients with MCC from St Vincent’s and Mater Hospital, Sydney, Australia. The aim of this study was to investigate the influence of radiotherapy (RT) on the local and regional control of MCC lesions and survival of patients with MCC. The data bases in anatomical pathology, RT and surgery. We searched for patients having a diagnosis of MCC between 1996 and 2007. Patient, tumour and treatment characteristics were collected and analysed. Univariate survival analysis of categorical variables was conducted with the Kaplan-Meier method together with the Log-Rank test for statistical significance. Continuous variables were assessed using the Cox regression method. Multivariate analysis was performed for significant univariate results. Sixty seven patients were found. Sixty two who were stage I-III and were treated with radical intent were analysed. 68% were male. The median age was 74 years. Forty-two cases (68%) were stage I or II, and 20 cases (32%) were stage III. For the subset of 42 stage I and II patients, those that had RT to their primary site had a 2-year local recurrence free survival of 89% compared with 36% for patients not receiving RT (p<0.001). The cumulative 2-year regional recurrence free survival for patients having adjuvant regional RT was 84% compared with 43% for patients not receiving this treatment (p<0.001). Immune status at initial surgery was a significant predictor for OS and MCCSS. In a multivariate analysis combining macroscopic size (mm) and immune status at initial surgery, only immune status remained a significant predictor of overall survival (HR=2.096, 95% CI: 1.002-4.385, p=0.049). RT is associated with significant improvement in local and regional control in Merkel cell carcinoma. Immunosuppression is an important factor in overall survival

Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

Science.gov (United States)

Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

2014-01-01

This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

A Statistical Model for Regional Tornado Climate Studies.

Directory of Open Access Journals (Sweden)

Thomas H Jagger

Full Text Available Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA. A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.

Understanding Short-Term Nonmigrating Tidal Variability in the Ionospheric Dynamo Region from SABER Using Information Theory and Bayesian Statistics

Science.gov (United States)

Kumari, K.; Oberheide, J.

2017-12-01

Nonmigrating tidal diagnostics of SABER temperature observations in the ionospheric dynamo region reveal a large amount of variability on time-scales of a few days to weeks. In this paper, we discuss the physical reasons for the observed short-term tidal variability using a novel approach based on Information theory and Bayesian statistics. We diagnose short-term tidal variability as a function of season, QBO, ENSO, and solar cycle and other drivers using time dependent probability density functions, Shannon entropy and Kullback-Leibler divergence. The statistical significance of the approach and its predictive capability is exemplified using SABER tidal diagnostics with emphasis on the responses to the QBO and solar cycle. Implications for F-region plasma density will be discussed.

Assessment of hi-resolution multi-ensemble statistical downscaling regional climate scenarios over Japan

Science.gov (United States)

Dairaku, K.

2017-12-01

The Asia-Pacific regions are increasingly threatened by large scale natural disasters. Growing concerns that loss and damages of natural disasters are projected to further exacerbate by climate change and socio-economic change. Climate information and services for risk assessments are of great concern. Fundamental regional climate information is indispensable for understanding changing climate and making decisions on when and how to act. To meet with the needs of stakeholders such as National/local governments, spatio-temporal comprehensive and consistent information is necessary and useful for decision making. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 37 GCMs (RCP8.5) and a statistical downscaling (Bias Corrected Spatial Disaggregation (BCSD)) to investigate uncertainty of projected change associated with structural differences of the GCMs for the periods of historical climate (1950-2005) and near future climate (2026-2050). Statistical downscaling regional climate scenarios show good performance for annual and seasonal averages for precipitation and temperature. The regional climate scenarios show systematic underestimate of extreme events such as hot days of over 35 Celsius and annual maximum daily precipitation because of the interpolation processes in the BCSD method. Each model projected different responses in near future climate because of structural differences. The most of CMIP5 37 models show qualitatively consistent increase of average and extreme temperature and precipitation. The added values of statistical/dynamical downscaling methods are also investigated for locally forced nonlinear phenomena, extreme events.

On exploiting wavelet bases in statistical region-based segmentation

DEFF Research Database (Denmark)

Stegmann, Mikkel Bille; Forchhammer, Søren

2002-01-01

Statistical region-based segmentation methods such as the Active Appearance Models establish dense correspondences by modelling variation of shape and pixel intensities in low-resolution 2D images. Unfortunately, for high-resolution 2D and 3D images, this approach is rendered infeasible due to ex...... 9-7 wavelet on cardiac MRIs and human faces show that the segmentation accuracy is minimally degraded at compression ratios of 1:10 and 1:20, respectively....

Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods

DEFF Research Database (Denmark)

Jakobsen, Janus Christian; Wetterslev, Jorn; Winkel, Per

2014-01-01

BACKGROUND: Thresholds for statistical significance when assessing meta-analysis results are being insufficiently demonstrated by traditional 95% confidence intervals and P-values. Assessment of intervention effects in systematic reviews with meta-analysis deserves greater rigour. METHODS......: Methodologies for assessing statistical and clinical significance of intervention effects in systematic reviews were considered. Balancing simplicity and comprehensiveness, an operational procedure was developed, based mainly on The Cochrane Collaboration methodology and the Grading of Recommendations...... Assessment, Development, and Evaluation (GRADE) guidelines. RESULTS: We propose an eight-step procedure for better validation of meta-analytic results in systematic reviews (1) Obtain the 95% confidence intervals and the P-values from both fixed-effect and random-effects meta-analyses and report the most...

Comparative Estimation of Russia’s Regions Investment Potential on the Base of the Multivariate Statistical Analysis

Directory of Open Access Journals (Sweden)

Victor V. Nikitin

2013-01-01

Full Text Available The article introduces the algorithm of Russia’s regions investment potential estimation, developed by means of multivariate statistical methods, determines the factors, reflecting regions investment state. The integral indicator was developed on their basis, using statistical data. The article presents regions’ classification on the basis of the integral index

A new fast algorithm for the evaluation of regions of interest and statistical uncertainty in computed tomography

International Nuclear Information System (INIS)

Huesman, R.H.

1984-01-01

A new algorithm for region of interest evaluation in computed tomography is described. Region of interest evaluation is a technique used to improve quantitation of the tomographic imaging process by summing (or averaging) the reconstructed quantity throughout a volume of particular significance. An important application of this procedure arises in the analysis of dynamic emission computed tomographic data, in which the uptake and clearance of radiotracers are used to determine the blood flow and/or physiologica function of tissue within the significant volume. The new algorithm replaces the conventional technique of repeated image reconstructions with one in which projected regions are convolved and then used to form multiple vector inner products with the raw tomographic data sets. Quantitation of regions of interest is made without the need for reconstruction of tomographic images. The computational advantage of the new algorithm over conventional methods is between factors of 20 and of 500 for typical applications encountered in medical science studies. The greatest benefit is the ease with which the statistical uncertainty of the result is computed. The entire covariance matrix for the evaluation of regions of interest can be calculated with relatively few operations. (author)

Application of the Method of Statistical Equations of Dependences to Assess the Dynamics of Regional Human Development Index for Khmelnytsk Region

Directory of Open Access Journals (Sweden)

R. О.

2017-12-01

Full Text Available A statistical approach to assessment of the factor values required to have necessary (planned, predicted levels of a resulting indicator achieved, including for purposes of regional socio-economic programs, is developed, by applying the method of statistical equations of dependences. The main problems that can be solved by use of the method of statistical equations of dependences are: direct and inverse problem; computing the factors’ contributions in the resulting indicator; constructing graphs of multiple relation and computing the shares of influence (the weights of selected factors; analysis of functional and correlation dependences, etc. The developed approach is used to assess the dynamics of Regional Human Development Index (RHDI for Khmelnytsk region (Ukraine and its constituent factors, in 2011–2015. The computations show that the factors with the largest contribution in RHDI of Khmelnytsk region are as follows: “number of minimal food baskets that can be purchased for average per capita income in the region” (62.91%, “housing in cities (square area per person” (20.27%, and “total birth rate” (5.33%. The contributions of factors like “planned capacity of ambulatories and policlinics per 10 thousand population” or “coverage of children in school age by secondary education” range from 5.26 to 0.14%. It is concluded that the proposed approach to the application of the method of statistical equations of dependences for modeling of factor and resulting indicators contributing to human development parameters at regional level can be used for assessments at sectoral level, with modifying the nomenclature of indicators measuring the socio-economic development and the financial and economic performance of business entities in an economic sector.

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

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Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land

Estimates of statistical significance for comparison of individual positions in multiple sequence alignments

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Sadreyev Ruslan I

2004-08-01

Full Text Available Abstract Background Profile-based analysis of multiple sequence alignments (MSA allows for accurate comparison of protein families. Here, we address the problems of detecting statistically confident dissimilarities between (1 MSA position and a set of predicted residue frequencies, and (2 between two MSA positions. These problems are important for (i evaluation and optimization of methods predicting residue occurrence at protein positions; (ii detection of potentially misaligned regions in automatically produced alignments and their further refinement; and (iii detection of sites that determine functional or structural specificity in two related families. Results For problems (1 and (2, we propose analytical estimates of P-value and apply them to the detection of significant positional dissimilarities in various experimental situations. (a We compare structure-based predictions of residue propensities at a protein position to the actual residue frequencies in the MSA of homologs. (b We evaluate our method by the ability to detect erroneous position matches produced by an automatic sequence aligner. (c We compare MSA positions that correspond to residues aligned by automatic structure aligners. (d We compare MSA positions that are aligned by high-quality manual superposition of structures. Detected dissimilarities reveal shortcomings of the automatic methods for residue frequency prediction and alignment construction. For the high-quality structural alignments, the dissimilarities suggest sites of potential functional or structural importance. Conclusion The proposed computational method is of significant potential value for the analysis of protein families.

Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

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Hoffman, A.; Forest, C. E.; Kemanian, A.

2016-12-01

A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with

Functional network-based statistics in depression: Theory of mind subnetwork and importance of parietal region.

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Lai, Chien-Han; Wu, Yu-Te; Hou, Yuh-Ming

2017-08-01

The functional network analysis of whole brain is an emerging field for research in depression. We initiated this study to investigate which subnetwork is significantly altered within the functional connectome in major depressive disorder (MDD). The study enrolled 52 first-episode medication-naïve patients with MDD and 40 controls for functional network analysis. All participants received the resting-state functional imaging using a 3-Tesla magnetic resonance scanner. After preprocessing, we calculated the connectivity matrix of functional connectivity in whole brain for each subject. The network-based statistics of connectome was used to perform group comparisons between patients and controls. The correlations between functional connectivity and clinical parameters were also performed. MDD patients had significant alterations in the network involving "theory of mind" regions, such as the left precentral gyrus, left angular gyrus, bilateral rolandic operculums and left inferior frontal gyrus. The center node of significant network was the left angular gyrus. No significant correlations of functional connectivity within the subnetwork and clinical parameters were noted. Functional connectivity of "theory of mind" subnetwork may be the core issue for pathophysiology in MDD. In addition, the center role of parietal region should be emphasized in future study. Copyright © 2017. Published by Elsevier B.V.

Regional statistical and economic analysis of small and medium-sized businesses development in Zhytomyr region

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S.I. Pavlova

2017-08-01

Full Text Available Small and medium-sized businesses play an important role in the development of the regional economic system in particular and in solving a number of the following local problems: developing competition, developing the market for goods and services, providing jobs for the able-bodied population, raising living standards and improving the social environment in society. The purpose of this paper is to analyze the state and development of small and medium-sized businesses in the Zhytomyr region, to analyze its contribution to the economic development of the region, and to identify the main problems existing in the region. According to the indicators of state statistics, the author presents the general characteristics of enterprises in the Zhytomyr region from 2012 to 2016 in the context of indicators of the number of enterprises, the number of employed workers and the volume of the products sold, highlighting the activities of small enterprises and assessing their share in general levels. In addition, the paper provides the description of the activities of individual entrepreneurs. The structural comparison for the above-listed indicators of the distribution of influence on the economic system of the Zhytomyr region in terms of enterprises by size is presented. In terms of quantity 93,5 % are small enterprises that provide 31,4 % of the total number of employees with work and make up 23,1 % of the total volume of sales. Average enterprises in these indicators have 6,4 %, 62,0 % and 54,8 % respectively. The statistical and economic analysis of the structure of small enterprises by types of economic activity, by indicators of the number of registered enterprises, and by the volumes of sold products is carried out. The uniformity of the distribution is estimated using the index of the concentration coefficient. The indicators of revenues to budgets of different levels from small and medium-sized businesses are set. The paper presents and summarizes the

Particle Acceleration in a Statistically Modeled Solar Active-Region Corona

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Toutounzi, A.; Vlahos, L.; Isliker, H.; Dimitropoulou, M.; Anastasiadis, A.; Georgoulis, M.

2013-09-01

Elaborating a statistical approach to describe the spatiotemporally intermittent electric field structures formed inside a flaring solar active region, we investigate the efficiency of such structures in accelerating charged particles (electrons). The large-scale magnetic configuration in the solar atmosphere responds to the strong turbulent flows that convey perturbations across the active region by initiating avalanche-type processes. The resulting unstable structures correspond to small-scale dissipation regions hosting strong electric fields. Previous research on particle acceleration in strongly turbulent plasmas provides a general framework for addressing such a problem. This framework combines various electromagnetic field configurations obtained by magnetohydrodynamical (MHD) or cellular automata (CA) simulations, or by employing a statistical description of the field's strength and configuration with test particle simulations. Our objective is to complement previous work done on the subject. As in previous efforts, a set of three probability distribution functions describes our ad-hoc electromagnetic field configurations. In addition, we work on data-driven 3D magnetic field extrapolations. A collisional relativistic test-particle simulation traces each particle's guiding center within these configurations. We also find that an interplay between different electron populations (thermal/non-thermal, ambient/injected) in our simulations may also address, via a re-acceleration mechanism, the so called `number problem'. Using the simulated particle-energy distributions at different heights of the cylinder we test our results against observations, in the framework of the collisional thick target model (CTTM) of solar hard X-ray (HXR) emission. The above work is supported by the Hellenic National Space Weather Research Network (HNSWRN) via the THALIS Programme.

Global regionalized seismicity in view of Non-Extensive Statistical Physics

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Chochlaki, Kalliopi; Vallianatos, Filippos; Michas, Georgios

2018-03-01

In the present work we study the distribution of Earth's shallow seismicity on different seismic zones, as occurred from 1981 to 2011 and extracted from the Centroid Moment Tensor (CMT) catalog. Our analysis is based on the subdivision of the Earth's surface into seismic zones that are homogeneous with regards to seismic activity and orientation of the predominant stress field. For this, we use the Flinn-Engdahl regionalization (FE) (Flinn and Engdahl, 1965), which consists of fifty seismic zones as modified by Lombardi and Marzocchi (2007). The latter authors grouped the 50 FE zones into larger tectonically homogeneous ones, utilizing the cumulative moment tensor method, resulting into thirty-nine seismic zones. In each one of these seismic zones we study the distribution of seismicity in terms of the frequency-magnitude distribution and the inter-event time distribution between successive earthquakes, a task that is essential for hazard assessments and to better understand the global and regional geodynamics. In our analysis we use non-extensive statistical physics (NESP), which seems to be one of the most adequate and promising methodological tools for analyzing complex systems, such as the Earth's seismicity, introducing the q-exponential formulation as the expression of probability distribution function that maximizes the Sq entropy as defined by Tsallis, (1988). The qE parameter is significantly greater than one for all the seismic regions analyzed with value range from 1.294 to 1.504, indicating that magnitude correlations are particularly strong. Furthermore, the qT parameter shows some temporal correlations but variations with cut-off magnitude show greater temporal correlations when the smaller magnitude earthquakes are included. The qT for earthquakes with magnitude greater than 5 takes values from 1.043 to 1.353 and as we increase the cut-off magnitude to 5.5 and 6 the qT value ranges from 1.001 to 1.242 and from 1.001 to 1.181 respectively, presenting

Estimating External Costs of Transportation in Regional Areas: Using Available Statistical Data the Case of the Region of Campania

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Mariano Gallo

2010-04-01

Full Text Available In this paper simplified methods for estimating the external costs due to transportation in regional areas are proposed. The methods are based on data available by national and regional statistical sources and do not need specific surveys; they allow obtaining approximate estimates useful for a preliminary evaluation of transportation plans, policies and projects. In more detail, a negative externality is defined as a cost that is produced by subject A and is borne by subject B; moreover, subject A does not consider the effects of his/her behavior on subject B and does not compensate subject B for the costs that this last one is forced to bear. In this paper after a literature review on methodologies proposed for estimating external costs, in national and international ambits, the main external costs produced by transportation systems in the Region of Campania are estimated. The main external costs considered are: greenhouse gas emissions, air pollution, noise, accidents and congestion. In the paper the secondary external costs are neglected; the main ones are: water and soil pollution; landscape and nature damages; upstream and downstream effects; visual intrusion; separation effects; soil occupancy. In this paper the external costs estimated are the ones produced not only by road traffic, that anyway is the main “culprit”, but also by rail and air transportation systems. The evaluation of external costs has required the collection of several data on the regional mobility and the estimation of veh-kms per year produced in Campania by cars and freight vehicles. The estimation of veh-kms per year is based on circulating vehicles, subdivided by the COPERT classification, and on average yearly distances covered by each vehicle class. Other regional statistical data are collected about regional rail transport and air services at the main airports of the region. Moreover, since the evaluation of some external costs is based on damages on human

Intensive inpatient treatment for bulimia nervosa: Statistical and clinical significance of symptom changes.

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Diedrich, Alice; Schlegl, Sandra; Greetfeld, Martin; Fumi, Markus; Voderholzer, Ulrich

2018-03-01

This study examines the statistical and clinical significance of symptom changes during an intensive inpatient treatment program with a strong psychotherapeutic focus for individuals with severe bulimia nervosa. 295 consecutively admitted bulimic patients were administered the Structured Interview for Anorexic and Bulimic Syndromes-Self-Rating (SIAB-S), the Eating Disorder Inventory-2 (EDI-2), the Brief Symptom Inventory (BSI), and the Beck Depression Inventory-II (BDI-II) at treatment intake and discharge. Results indicated statistically significant symptom reductions with large effect sizes regarding severity of binge eating and compensatory behavior (SIAB-S), overall eating disorder symptom severity (EDI-2), overall psychopathology (BSI), and depressive symptom severity (BDI-II) even when controlling for antidepressant medication. The majority of patients showed either reliable (EDI-2: 33.7%, BSI: 34.8%, BDI-II: 18.1%) or even clinically significant symptom changes (EDI-2: 43.2%, BSI: 33.9%, BDI-II: 56.9%). Patients with clinically significant improvement were less distressed at intake and less likely to suffer from a comorbid borderline personality disorder when compared with those who did not improve to a clinically significant extent. Findings indicate that intensive psychotherapeutic inpatient treatment may be effective in about 75% of severely affected bulimic patients. For the remaining non-responding patients, inpatient treatment might be improved through an even stronger focus on the reduction of comorbid borderline personality traits.

Recent Literature on Whether Statistical Significance Tests Should or Should Not Be Banned.

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Deegear, James

This paper summarizes the literature regarding statistical significant testing with an emphasis on recent literature in various discipline and literature exploring why researchers have demonstrably failed to be influenced by the American Psychological Association publication manual's encouragement to report effect sizes. Also considered are…

Changing world extreme temperature statistics

Science.gov (United States)

Finkel, J. M.; Katz, J. I.

2018-04-01

We use the Global Historical Climatology Network--daily database to calculate a nonparametric statistic that describes the rate at which all-time daily high and low temperature records have been set in nine geographic regions (continents or major portions of continents) during periods mostly from the mid-20th Century to the present. This statistic was defined in our earlier work on temperature records in the 48 contiguous United States. In contrast to this earlier work, we find that in every region except North America all-time high records were set at a rate significantly (at least $3\\sigma$) higher than in the null hypothesis of a stationary climate. Except in Antarctica, all-time low records were set at a rate significantly lower than in the null hypothesis. In Europe, North Africa and North Asia the rate of setting new all-time highs increased suddenly in the 1990's, suggesting a change in regional climate regime; in most other regions there was a steadier increase.

A Statistical Study of Eiscat Electron and Ion Temperature Measurements In The E-region

Science.gov (United States)

Hussey, G.; Haldoupis, C.; Schlegel, K.; Bösinger, T.

Motivated by the large EISCAT data base, which covers over 15 years of common programme operation, and previous statistical work with EISCAT data (e.g., C. Hal- doupis, K. Schlegel, and G. Hussey, Auroral E-region electron density gradients mea- sured with EISCAT, Ann. Geopshysicae, 18, 1172-1181, 2000), a detailed statistical analysis of electron and ion EISCAT temperature measurements has been undertaken. This study was specifically concerned with the statistical dependence of heating events with other ambient parameters such as the electric field and electron density. The re- sults showed previously reported dependences such as the electron temperature being directly correlated with the ambient electric field and inversely related to the electron density. However, these correlations were found to be also dependent upon altitude. There was also evidence of the so called "Schlegel effect" (K. Schlegel, Reduced effective recombination coefficient in the disturbed polar E-region, J. Atmos. Terr. Phys., 44, 183-185, 1982); that is, the heated electron gas leads to increases in elec- tron density through a reduction in the recombination rate. This paper will present the statistical heating results and attempt to offer physical explanations and interpretations of the findings.

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

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Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Statistical modeling of temperature, humidity and wind fields in the atmospheric boundary layer over the Siberian region

Science.gov (United States)

Lomakina, N. Ya.

2017-11-01

The work presents the results of the applied climatic division of the Siberian region into districts based on the methodology of objective classification of the atmospheric boundary layer climates by the "temperature-moisture-wind" complex realized with using the method of principal components and the special similarity criteria of average profiles and the eigen values of correlation matrices. On the territory of Siberia, it was identified 14 homogeneous regions for winter season and 10 regions were revealed for summer. The local statistical models were constructed for each region. These include vertical profiles of mean values, mean square deviations, and matrices of interlevel correlation of temperature, specific humidity, zonal and meridional wind velocity. The advantage of the obtained local statistical models over the regional models is shown.

Change of diffusion anisotropy in patients with acute cerebral infarction using statistical parametric analysis

International Nuclear Information System (INIS)

Morita, Naomi; Harada, Masafumi; Uno, Masaaki; Furutani, Kaori; Nishitani, Hiromu

2006-01-01

We conducted statistical parametric comparison of fractional anisotropy (FA) images and quantified FA values to determine whether significant change occurs in the ischemic region. The subjects were 20 patients seen within 24 h after onset of ischemia. For statistical comparison of FA images, a sample FA image was coordinated by the Talairach template, and each FA map was normalized. Statistical comparison was conducted using statistical parametric mapping (SPM) 99. Regions of interest were set in the same region on apparent diffusion coefficient (ADC) and FA maps, the region being consistent with the hyperintense region on diffusion-weighted images (DWIs). The contralateral region was also measured to obtain asymmetry ratios of ADC and FA. Regions with areas of statistical significance on FA images were found only in the white matter of three patients, although the regions were smaller than hyperintense regions on DWIs. The mean ADC and FA ratios were 0.64±0.16 and 0.93±0.09, respectively, and the degree of FA change was less than that of the ADC change. Significant change in diffusion anisotropy was limited to the severely infarcted core of the white matter. We believe statistical comparison of FA maps to be useful for detecting different regions of diffusion anisotropy. (author)

Power, effects, confidence, and significance: an investigation of statistical practices in nursing research.

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Gaskin, Cadeyrn J; Happell, Brenda

2014-05-01

improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Statistical downscaling and future scenario generation of temperatures for Pakistan Region

Science.gov (United States)

Kazmi, Dildar Hussain; Li, Jianping; Rasul, Ghulam; Tong, Jiang; Ali, Gohar; Cheema, Sohail Babar; Liu, Luliu; Gemmer, Marco; Fischer, Thomas

2015-04-01

Finer climate change information on spatial scale is required for impact studies than that presently provided by global or regional climate models. It is especially true for regions like South Asia with complex topography, coastal or island locations, and the areas of highly heterogeneous land-cover. To deal with the situation, an inexpensive method (statistical downscaling) has been adopted. Statistical DownScaling Model (SDSM) employed for downscaling of daily minimum and maximum temperature data of 44 national stations for base time (1961-1990) and then the future scenarios generated up to 2099. Observed as well as Predictors (product of National Oceanic and Atmospheric Administration) data were calibrated and tested on individual/multiple basis through linear regression. Future scenario was generated based on HadCM3 daily data for A2 and B2 story lines. The downscaled data has been tested, and it has shown a relatively strong relationship with the observed in comparison to ECHAM5 data. Generally, the southern half of the country is considered vulnerable in terms of increasing temperatures, but the results of this study projects that in future, the northern belt in particular would have a possible threat of increasing tendency in air temperature. Especially, the northern areas (hosting the third largest ice reserves after the Polar Regions), an important feeding source for Indus River, are projected to be vulnerable in terms of increasing temperatures. Consequently, not only the hydro-agricultural sector but also the environmental conditions in the area may be at risk, in future.

Examining reproducibility in psychology : A hybrid method for combining a statistically significant original study and a replication

NARCIS (Netherlands)

Van Aert, R.C.M.; Van Assen, M.A.L.M.

2018-01-01

The unrealistically high rate of positive results within psychology has increased the attention to replication research. However, researchers who conduct a replication and want to statistically combine the results of their replication with a statistically significant original study encounter

A tutorial on hunting statistical significance by chasing N

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Denes Szucs

2016-09-01

Full Text Available There is increasing concern about the replicability of studies in psychology and cognitive neuroscience. Hidden data dredging (also called p-hacking is a major contributor to this crisis because it substantially increases Type I error resulting in a much larger proportion of false positive findings than the usually expected 5%. In order to build better intuition to avoid, detect and criticise some typical problems, here I systematically illustrate the large impact of some easy to implement and so, perhaps frequent data dredging techniques on boosting false positive findings. I illustrate several forms of two special cases of data dredging. First, researchers may violate the data collection stopping rules of null hypothesis significance testing by repeatedly checking for statistical significance with various numbers of participants. Second, researchers may group participants post-hoc along potential but unplanned independent grouping variables. The first approach 'hacks' the number of participants in studies, the second approach ‘hacks’ the number of variables in the analysis. I demonstrate the high amount of false positive findings generated by these techniques with data from true null distributions. I also illustrate that it is extremely easy to introduce strong bias into data by very mild selection and re-testing. Similar, usually undocumented data dredging steps can easily lead to having 20-50%, or more false positives.

Probability distribution and statistical properties of spherically compensated cosmic regions in ΛCDM cosmology

Science.gov (United States)

Alimi, Jean-Michel; de Fromont, Paul

2018-04-01

The statistical properties of cosmic structures are well known to be strong probes for cosmology. In particular, several studies tried to use the cosmic void counting number to obtain tight constrains on dark energy. In this paper, we model the statistical properties of these regions using the CoSphere formalism (de Fromont & Alimi) in both primordial and non-linearly evolved Universe in the standard Λ cold dark matter model. This formalism applies similarly for minima (voids) and maxima (such as DM haloes), which are here considered symmetrically. We first derive the full joint Gaussian distribution of CoSphere's parameters in the Gaussian random field. We recover the results of Bardeen et al. only in the limit where the compensation radius becomes very large, i.e. when the central extremum decouples from its cosmic environment. We compute the probability distribution of the compensation size in this primordial field. We show that this distribution is redshift independent and can be used to model cosmic voids size distribution. We also derive the statistical distribution of the peak parameters introduced by Bardeen et al. and discuss their correlation with the cosmic environment. We show that small central extrema with low density are associated with narrow compensation regions with deep compensation density, while higher central extrema are preferentially located in larger but smoother over/under massive regions.

Assessing Regional Scale Variability in Extreme Value Statistics Under Altered Climate Scenarios

Energy Technology Data Exchange (ETDEWEB)

Brunsell, Nathaniel [Univ. of Kansas, Lawrence, KS (United States); Mechem, David [Univ. of Kansas, Lawrence, KS (United States); Ma, Chunsheng [Wichita State Univ., KS (United States)

2015-02-20

Recent studies have suggested that low-frequency modes of climate variability can significantly influence regional climate. The climatology associated with extreme events has been shown to be particularly sensitive. This has profound implications for droughts, heat waves, and food production. We propose to examine regional climate simulations conducted over the continental United States by applying a recently developed technique which combines wavelet multi–resolution analysis with information theory metrics. This research is motivated by two fundamental questions concerning the spatial and temporal structure of extreme events. These questions are 1) what temporal scales of the extreme value distributions are most sensitive to alteration by low-frequency climate forcings and 2) what is the nature of the spatial structure of variation in these timescales? The primary objective is to assess to what extent information theory metrics can be useful in characterizing the nature of extreme weather phenomena. Specifically, we hypothesize that (1) changes in the nature of extreme events will impact the temporal probability density functions and that information theory metrics will be sensitive these changes and (2) via a wavelet multi–resolution analysis, we will be able to characterize the relative contribution of different timescales on the stochastic nature of extreme events. In order to address these hypotheses, we propose a unique combination of an established regional climate modeling approach and advanced statistical techniques to assess the effects of low-frequency modes on climate extremes over North America. The behavior of climate extremes in RCM simulations for the 20th century will be compared with statistics calculated from the United States Historical Climatology Network (USHCN) and simulations from the North American Regional Climate Change Assessment Program (NARCCAP). This effort will serve to establish the baseline behavior of climate extremes, the

Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system

Science.gov (United States)

Sharma, Sanjib; Siddique, Ridwan; Reed, Seann; Ahnert, Peter; Mendoza, Pablo; Mejia, Alfonso

2018-03-01

The relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1-7) are investigated. For this purpose, a regional hydrologic ensemble prediction system (RHEPS) is developed and implemented. The RHEPS is comprised of the following components: (i) hydrometeorological observations (multisensor precipitation estimates, gridded surface temperature, and gauged streamflow); (ii) weather ensemble forecasts (precipitation and near-surface temperature) from the National Centers for Environmental Prediction 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2); (iii) NOAA's Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM); (iv) heteroscedastic censored logistic regression (HCLR) as the statistical preprocessor; (v) two statistical postprocessors, an autoregressive model with a single exogenous variable (ARX(1,1)) and quantile regression (QR); and (vi) a comprehensive verification strategy. To implement the RHEPS, 1 to 7 days weather forecasts from the GEFSRv2 are used to force HL-RDHM and generate raw ensemble streamflow forecasts. Forecasting experiments are conducted in four nested basins in the US Middle Atlantic region, ranging in size from 381 to 12 362 km2. Results show that the HCLR preprocessed ensemble precipitation forecasts have greater skill than the raw forecasts. These improvements are more noticeable in the warm season at the longer lead times (> 3 days). Both postprocessors, ARX(1,1) and QR, show gains in skill relative to the raw ensemble streamflow forecasts, particularly in the cool season, but QR outperforms ARX(1,1). The scenarios that implement preprocessing and postprocessing separately tend to perform similarly, although the postprocessing-alone scenario is often more effective. The scenario involving both preprocessing and postprocessing consistently outperforms the other scenarios. In some cases

Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method

Directory of Open Access Journals (Sweden)

Yun Tian

2016-01-01

Full Text Available The segmentation of coronary arteries is a vital process that helps cardiovascular radiologists detect and quantify stenosis. In this paper, we propose a fully automated coronary artery segmentation from cardiac data volume. The method is built on a statistics region growing together with a heuristic decision. First, the heart region is extracted using a multi-atlas-based approach. Second, the vessel structures are enhanced via a 3D multiscale line filter. Next, seed points are detected automatically through a threshold preprocessing and a subsequent morphological operation. Based on the set of detected seed points, a statistics-based region growing is applied. Finally, results are obtained by setting conservative parameters. A heuristic decision method is then used to obtain the desired result automatically because parameters in region growing vary in different patients, and the segmentation requires full automation. The experiments are carried out on a dataset that includes eight-patient multivendor cardiac computed tomography angiography (CTA volume data. The DICE similarity index, mean distance, and Hausdorff distance metrics are employed to compare the proposed algorithm with two state-of-the-art methods. Experimental results indicate that the proposed algorithm is capable of performing complete, robust, and accurate extraction of coronary arteries.

Significant regional heterogeneity of coronary flow reserve in paediatric hypertrophic cardiomyopathy

International Nuclear Information System (INIS)

Tadamura, E.; Kudoh, T.; Kubo, S.; Konishi, J.; Motooka, M.; Nohara, R.; Matsumori, A.; Sasayama, S.; Matsuda, T.; Tamaki, N.

2000-01-01

Previous studies have indicated that cardiac events in young patients with hypertrophic cardiomyopathy (HCM) are related to ischaemia rather than to arrhythmia. We measured coronary flow reserve in paediatric HCM and compared the values with those in adult HCM. We studied 12 patients with HCM including six paediatric ( 20 years old: mean 62 years), and six healthy young adults (mean 29 years) as controls. Every patient underwent magnetic resonance imaging (MRI) for anatomical assessment. Myocardial blood flow at rest and after dipyridamole infusion was measured with dynamic nitrogen-13 ammonia positron emission tomography (PET). Partial volume effect was corrected for using the anatomical data obtained with MRI. In adult patients with HCM, coronary flow reserve in the hypertrophied septal region was not significantly different from that in the non-hypertrophied lateral wall (1.38±0.29 vs 1.77±0.39, respectively). In the paediatric patients, coronary flow reserve in the hypertrophied septal region was significantly lower than in the non-hypertrophied lateral wall (0.84±0.33 vs 2.74±0.90, respectively, P<0.01). In addition, coronary flow reserve in adult patients was lower than in control subjects both in the septal wall (1.38±0.29 vs 2.94±0.35, respectively, P<0.0001) and in the lateral wall (1.77±0.39 vs 2.85±0.69, respectively, P<0.05). In contrast, coronary flow reserve in paediatric patients was not significantly different from that in control subjects in the lateral wall (2.74±0.90 vs 2.85±0.69, respectively), while absolute reduction of myocardial blood flow was noted after pharmacological vasodilatation in the hypertrophied septal region. In conclusion, significant regional differences of coronary flow reserve were present in the paediatric patients with HCM. These results suggest that paediatric patients with HCM intrinsically have the potential to experience significant regional ischaemia even in the absence of coronary stenosis. (orig.)

A critical discussion of null hypothesis significance testing and statistical power analysis within psychological research

DEFF Research Database (Denmark)

Jones, Allan; Sommerlund, Bo

2007-01-01

The uses of null hypothesis significance testing (NHST) and statistical power analysis within psychological research are critically discussed. The article looks at the problems of relying solely on NHST when dealing with small and large sample sizes. The use of power-analysis in estimating...... the potential error introduced by small and large samples is advocated. Power analysis is not recommended as a replacement to NHST but as an additional source of information about the phenomena under investigation. Moreover, the importance of conceptual analysis in relation to statistical analysis of hypothesis...

Statistical significance estimation of a signal within the GooFit framework on GPUs

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Cristella Leonardo

2017-01-01

Full Text Available In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B+ → J/ψϕK+. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

Stimulating Sustainability in Multinational Companies: the Significance of Regional Headquarters

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Andreas G. M. NACHBAGAUER

2016-06-01

Full Text Available Recently, regional headquarters have gained practical importance and theoretical attention. Traditionally considered a mere transmission facility to manage complex organisations, advanced approaches, however, locate regional headquarters in a field of tension between hierarchical integration and strategic independence. Given the growing concern for global responsibility, stimulating sustainability also and particularly addresses regional headquarters. This conceptual article combines the call for sustainability with the upcoming importance of regional headquarters: which contributions can the regional headquarters of a multinational company deliver to stimulate the development of sustainable corporate strategy and operations? The main topics are the effects different versions of embedding regional headquarters into the corporate context have on opportunities to implement sustainability policies: Are there different chances for successful implementation depending on the strategic setup of the company? Does the distribution of competences matter? Which types of interaction between headquarters and branch are suitable to introduce sustainability sustainably? Is the mix of national contexts of headquarters and branch of importance? First results show that depending on the companywide strategy, and especially on the structure and distribution of competences, regional headquarters can play a significant role as trigger of sustainability. The literature favours strong involvement and large autonomy of both branches as well as regional headquarters for the development and management of sustainability. The parts of the company involved in a critical environment often are the starting point of sustainability policies.

Statistical Downscaling Of Local Climate In The Alpine Region

Science.gov (United States)

Kaspar, Severin; Philipp, Andreas; Jacobeit, Jucundus

2016-04-01

The impact of climate change on the alpine region was disproportional strong in the past decades compared to the surrounding areas, which becomes manifest in a higher increase in surface air temperature. Beside the thermal changes also implications for the hydrological cycle may be expected, acting as a very important factor not only for the ecosystem but also for mankind, in the form of water security or considering economical aspects like winter tourism etc. Therefore, in climate impact studies, it is necessary to focus on variables with high influence on the hydrological cycle, for example temperature, precipitation, wind, humidity and radiation. The aim of this study is to build statistical downscaling models which are able to reproduce temperature and precipitation at the mountainous alpine weather stations Zugspitze and Sonnblick and to further project these models into the future to identify possible changes in the behavior of these climate variables and with that in the hydrological cycle. Beside facing a in general very complex terrain in this high elevated regions, we have the advantage of a more direct atmospheric influence on the meteorology of the exposed weather stations from the large scale circulation. Two nonlinear statistical methods are developed to model the station-data series on a daily basis: On the one hand a conditional classification approach was used and on the other hand a model based on artificial neural networks (ANNs) was built. The latter is in focus of this presentation. One of the important steps of developing a new model approach is to find a reliable predictor setup with e.g. informative predictor variables or adequate location and size of the spatial domain. The question is: Can we include synoptic background knowledge to identify an optimal domain for an ANN approach? The yet developed ANN setups and configurations show promising results in downscaling both, temperature (up to 80 % of explained variance) and precipitation (up

Gene cluster statistics with gene families.

Science.gov (United States)

Raghupathy, Narayanan; Durand, Dannie

2009-05-01

Identifying genomic regions that descended from a common ancestor is important for understanding the function and evolution of genomes. In distantly related genomes, clusters of homologous gene pairs are evidence of candidate homologous regions. Demonstrating the statistical significance of such "gene clusters" is an essential component of comparative genomic analyses. However, currently there are no practical statistical tests for gene clusters that model the influence of the number of homologs in each gene family on cluster significance. In this work, we demonstrate empirically that failure to incorporate gene family size in gene cluster statistics results in overestimation of significance, leading to incorrect conclusions. We further present novel analytical methods for estimating gene cluster significance that take gene family size into account. Our methods do not require complete genome data and are suitable for testing individual clusters found in local regions, such as contigs in an unfinished assembly. We consider pairs of regions drawn from the same genome (paralogous clusters), as well as regions drawn from two different genomes (orthologous clusters). Determining cluster significance under general models of gene family size is computationally intractable. By assuming that all gene families are of equal size, we obtain analytical expressions that allow fast approximation of cluster probabilities. We evaluate the accuracy of this approximation by comparing the resulting gene cluster probabilities with cluster probabilities obtained by simulating a realistic, power-law distributed model of gene family size, with parameters inferred from genomic data. Surprisingly, despite the simplicity of the underlying assumption, our method accurately approximates the true cluster probabilities. It slightly overestimates these probabilities, yielding a conservative test. We present additional simulation results indicating the best choice of parameter values for data

STATISTICAL ANALYSIS OF COMPETITIVENESS FACTORS OF REGIONS OF THE RUSSIAN FEDERATION

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O. V. Bakanach

2015-01-01

Full Text Available In the conditions of market economy the competition is the main driving force of economic growth. The idea about existence of the interregional competition isn't conventional and demands the proof. The phenomena allowing to state existence of the interregional competitive relations which are realized through system of prerequisites of political, economic, legal and technological character were for this purpose studied. Competitiveness – one of the most important characteristics of the territory which level directly influences formation of positive tendencies in development of subjects of the Russian Federation. Productive indicators of level of competitiveness of the region are: a gross regional product on one occupied in economy, production of a gross regional product for one ruble of fixed assets, a gross regional product for one ruble of investments, a share of balanced financial result in a gross regional product. On the basis of private indicators the Pattern method received an integrated indicator of level of competitiveness of region. The quantitative assessment of the factors determining distinctions of regions of the Russian Federation by competitiveness level allowed to define that the competitiveness variation in the territory of regions in the greatest measure depends on a variation of number of graduates of educational institutions with higher education on 1000 people and the specific weight of investments into the enterprises occupied with mining. Regional values of competitiveness are most elastic relatively the specific weight of own investments, that is increase of this indicator for 1 % causes increase of competitiveness for 0.9 %. The practical importance of this work is caused by possibility of application of results of research by federal and regional executive authorities as information representation when developing programs of increase of level of competitiveness of regions of the Russian Federation. Besides, it is

Is statistical significance clinically important?--A guide to judge the clinical relevance of study findings

NARCIS (Netherlands)

Sierevelt, Inger N.; van Oldenrijk, Jakob; Poolman, Rudolf W.

2007-01-01

In this paper we describe several issues that influence the reporting of statistical significance in relation to clinical importance, since misinterpretation of p values is a common issue in orthopaedic literature. Orthopaedic research is tormented by the risks of false-positive (type I error) and

Statistical significance of theoretical predictions: A new dimension in nuclear structure theories (I)

International Nuclear Information System (INIS)

DUDEK, J; SZPAK, B; FORNAL, B; PORQUET, M-G

2011-01-01

In this and the follow-up article we briefly discuss what we believe represents one of the most serious problems in contemporary nuclear structure: the question of statistical significance of parametrizations of nuclear microscopic Hamiltonians and the implied predictive power of the underlying theories. In the present Part I, we introduce the main lines of reasoning of the so-called Inverse Problem Theory, an important sub-field in the contemporary Applied Mathematics, here illustrated on the example of the Nuclear Mean-Field Approach.

Statistical evaluation of fracture characteristics of RPV steels in the ductile-brittle transition temperature region

International Nuclear Information System (INIS)

Kang, Sung Sik; Chi, Se Hwan; Hong, Jun Hwa

1998-01-01

The statistical analysis method was applied to the evaluation of fracture toughness in the ductile-brittle transition temperature region. Because cleavage fracture in steel is of a statistical nature, fracture toughness data or values show a similar statistical trend. Using the three-parameter Weibull distribution, a fracture toughness vs. temperature curve (K-curve) was directly generated from a set of fracture toughness data at a selected temperature. Charpy V-notch impact energy was also used to obtain the K-curve by a K IC -CVN (Charpy V-notch energy) correlation. Furthermore, this method was applied to evaluate the neutron irradiation embrittlement of reactor pressure vessel(RPV) steel. Most of the fracture toughness data were within the 95 percent confidence limits. The prediction of a transition temperature shift by statistical analysis was compared with that from the experimental data. (author)

Multi region based image retrieval system

Indian Academy of Sciences (India)

data mining, information theory, statistics and psychology. ∗ .... ground complication and independent of image size and orientation (Zhang 2007). ..... Figure 2. Significant regions: (a) the input image, (b) the primary significant region, (c) the ...

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

Science.gov (United States)

Pavlacky, David C; Lukacs, Paul M; Blakesley, Jennifer A; Skorkowsky, Robert C; Klute, David S; Hahn, Beth A; Dreitz, Victoria J; George, T Luke; Hanni, David J

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer's sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

Directory of Open Access Journals (Sweden)

David C Pavlacky

Full Text Available Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1 coordination across organizations and regions, 2 meaningful management and conservation objectives, and 3 rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17. We provide two examples for the Brewer's sparrow (Spizella breweri in BCR 17 demonstrating the ability of the design to 1 determine hierarchical population responses to landscape change and 2 estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous

Statistical Significance of the Contribution of Variables to the PCA Solution: An Alternative Permutation Strategy

Science.gov (United States)

Linting, Marielle; van Os, Bart Jan; Meulman, Jacqueline J.

2011-01-01

In this paper, the statistical significance of the contribution of variables to the principal components in principal components analysis (PCA) is assessed nonparametrically by the use of permutation tests. We compare a new strategy to a strategy used in previous research consisting of permuting the columns (variables) of a data matrix…

Regional compensation for statistical maximum likelihood reconstruction error of PET image pixels

International Nuclear Information System (INIS)

Forma, J; Ruotsalainen, U; Niemi, J A

2013-01-01

In positron emission tomography (PET), there is an increasing interest in studying not only the regional mean tracer concentration, but its variation arising from local differences in physiology, the tissue heterogeneity. However, in reconstructed images this physiological variation is shadowed by a large reconstruction error, which is caused by noisy data and the inversion of tomographic problem. We present a new procedure which can quantify the error variation in regional reconstructed values for given PET measurement, and reveal the remaining tissue heterogeneity. The error quantification is made by creating and reconstructing the noise realizations of virtual sinograms, which are statistically similar with the measured sinogram. Tests with physical phantom data show that the characterization of error variation and the true heterogeneity are possible, despite the existing model error when real measurement is considered. (paper)

STATISTICAL ANALYSIS OF ACOUSTIC WAVE PARAMETERS NEAR SOLAR ACTIVE REGIONS

International Nuclear Information System (INIS)

Rabello-Soares, M. Cristina; Bogart, Richard S.; Scherrer, Philip H.

2016-01-01

In order to quantify the influence of magnetic fields on acoustic mode parameters and flows in and around active regions, we analyze the differences in the parameters in magnetically quiet regions nearby an active region (which we call “nearby regions”), compared with those of quiet regions at the same disk locations for which there are no neighboring active regions. We also compare the mode parameters in active regions with those in comparably located quiet regions. Our analysis is based on ring-diagram analysis of all active regions observed by the Helioseismic and Magnetic Imager (HMI) during almost five years. We find that the frequency at which the mode amplitude changes from attenuation to amplification in the quiet nearby regions is around 4.2 mHz, in contrast to the active regions, for which it is about 5.1 mHz. This amplitude enhacement (the “acoustic halo effect”) is as large as that observed in the active regions, and has a very weak dependence on the wave propagation direction. The mode energy difference in nearby regions also changes from a deficit to an excess at around 4.2 mHz, but averages to zero over all modes. The frequency difference in nearby regions increases with increasing frequency until a point at which the frequency shifts turn over sharply, as in active regions. However, this turnover occurs around 4.9 mHz, which is significantly below the acoustic cutoff frequency. Inverting the horizontal flow parameters in the direction of the neigboring active regions, we find flows that are consistent with a model of the thermal energy flow being blocked directly below the active region.

A Note on Comparing the Power of Test Statistics at Low Significance Levels.

Science.gov (United States)

Morris, Nathan; Elston, Robert

2011-01-01

It is an obvious fact that the power of a test statistic is dependent upon the significance (alpha) level at which the test is performed. It is perhaps a less obvious fact that the relative performance of two statistics in terms of power is also a function of the alpha level. Through numerous personal discussions, we have noted that even some competent statisticians have the mistaken intuition that relative power comparisons at traditional levels such as α = 0.05 will be roughly similar to relative power comparisons at very low levels, such as the level α = 5 × 10 -8 , which is commonly used in genome-wide association studies. In this brief note, we demonstrate that this notion is in fact quite wrong, especially with respect to comparing tests with differing degrees of freedom. In fact, at very low alpha levels the cost of additional degrees of freedom is often comparatively low. Thus we recommend that statisticians exercise caution when interpreting the results of power comparison studies which use alpha levels that will not be used in practice.

Integration of association statistics over genomic regions using Bayesian adaptive regression splines

Directory of Open Access Journals (Sweden)

Zhang Xiaohua

2003-11-01

Full Text Available Abstract In the search for genetic determinants of complex disease, two approaches to association analysis are most often employed, testing single loci or testing a small group of loci jointly via haplotypes for their relationship to disease status. It is still debatable which of these approaches is more favourable, and under what conditions. The former has the advantage of simplicity but suffers severely when alleles at the tested loci are not in linkage disequilibrium (LD with liability alleles; the latter should capture more of the signal encoded in LD, but is far from simple. The complexity of haplotype analysis could be especially troublesome for association scans over large genomic regions, which, in fact, is becoming the standard design. For these reasons, the authors have been evaluating statistical methods that bridge the gap between single-locus and haplotype-based tests. In this article, they present one such method, which uses non-parametric regression techniques embodied by Bayesian adaptive regression splines (BARS. For a set of markers falling within a common genomic region and a corresponding set of single-locus association statistics, the BARS procedure integrates these results into a single test by examining the class of smooth curves consistent with the data. The non-parametric BARS procedure generally finds no signal when no liability allele exists in the tested region (ie it achieves the specified size of the test and it is sensitive enough to pick up signals when a liability allele is present. The BARS procedure provides a robust and potentially powerful alternative to classical tests of association, diminishes the multiple testing problem inherent in those tests and can be applied to a wide range of data types, including genotype frequencies estimated from pooled samples.

Estimating long-term statistics for annual precipitation for six regions of the United States from tree-ring data

International Nuclear Information System (INIS)

Fritts, H.C.; DeWitt, E.; Gordon, G.A.; Hunt, J.H.; Lofgren, G.R.

1979-12-01

Spatial anomalies of seasonal precipitation for the United States and southwestern Canada have been reconstructed from 1602 through 1961 using dendrochronological and multivariate techniques on 65 arid-site tree-ring chronologies from western North America. Seasonal reconstructions are averaged to obtain mean annual precipitation values for six regions of importance to the Nuclear Regulatory Commission (NRC) Nuclear Waste Management Program (NWMP). Statistics calculated from the regionally averaged annual values for 25-year and longer intervals show annual precipitation in the seventeenth through nineteenth centuries to be lower than in the twentieth century for three regions in the American Southwest and higher for one region in the Northwest and two regions in the East. The variability of precipitation generally was higher in the past three centuries than in the present century. Twenty-five-year intervals with noteworthy statistics are identified and important results are summarized and tabulated for use in the hydrologic modeling of the NWMP. Additional research is recommended to incorporate temperature and precipitation into a single hydrologic parameter

ClusterSignificance: A bioconductor package facilitating statistical analysis of class cluster separations in dimensionality reduced data

DEFF Research Database (Denmark)

Serviss, Jason T.; Gådin, Jesper R.; Eriksson, Per

2017-01-01

, e.g. genes in a specific pathway, alone can separate samples into these established classes. Despite this, the evaluation of class separations is often subjective and performed via visualization. Here we present the ClusterSignificance package; a set of tools designed to assess the statistical...... significance of class separations downstream of dimensionality reduction algorithms. In addition, we demonstrate the design and utility of the ClusterSignificance package and utilize it to determine the importance of long non-coding RNA expression in the identity of multiple hematological malignancies....

Integrating Expert Knowledge with Statistical Analysis for Landslide Susceptibility Assessment at Regional Scale

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Christos Chalkias

2016-03-01

Full Text Available In this paper, an integration landslide susceptibility model by combining expert-based and bivariate statistical analysis (Landslide Susceptibility Index—LSI approaches is presented. Factors related with the occurrence of landslides—such as elevation, slope angle, slope aspect, lithology, land cover, Mean Annual Precipitation (MAP and Peak Ground Acceleration (PGA—were analyzed within a GIS environment. This integrated model produced a landslide susceptibility map which categorized the study area according to the probability level of landslide occurrence. The accuracy of the final map was evaluated by Receiver Operating Characteristics (ROC analysis depending on an independent (validation dataset of landslide events. The prediction ability was found to be 76% revealing that the integration of statistical analysis with human expertise can provide an acceptable landslide susceptibility assessment at regional scale.

A statistical approach to evaluate flood risk at the regional level: an application to Italy

Science.gov (United States)

Rossi, Mauro; Marchesini, Ivan; Salvati, Paola; Donnini, Marco; Guzzetti, Fausto; Sterlacchini, Simone; Zazzeri, Marco; Bonazzi, Alessandro; Carlesi, Andrea

2016-04-01

Floods are frequent and widespread in Italy, causing every year multiple fatalities and extensive damages to public and private structures. A pre-requisite for the development of mitigation schemes, including financial instruments such as insurance, is the ability to quantify their costs starting from the estimation of the underlying flood hazard. However, comprehensive and coherent information on flood prone areas, and estimates on the frequency and intensity of flood events, are not often available at scales appropriate for risk pooling and diversification. In Italy, River Basins Hydrogeological Plans (PAI), prepared by basin administrations, are the basic descriptive, regulatory, technical and operational tools for environmental planning in flood prone areas. Nevertheless, such plans do not cover the entire Italian territory, having significant gaps along the minor hydrographic network and in ungauged basins. Several process-based modelling approaches have been used by different basin administrations for the flood hazard assessment, resulting in an inhomogeneous hazard zonation of the territory. As a result, flood hazard assessments expected and damage estimations across the different Italian basin administrations are not always coherent. To overcome these limitations, we propose a simplified multivariate statistical approach for the regional flood hazard zonation coupled with a flood impact model. This modelling approach has been applied in different Italian basin administrations, allowing a preliminary but coherent and comparable estimation of the flood hazard and the relative impact. Model performances are evaluated comparing the predicted flood prone areas with the corresponding PAI zonation. The proposed approach will provide standardized information (following the EU Floods Directive specifications) on flood risk at a regional level which can in turn be more readily applied to assess flood economic impacts. Furthermore, in the assumption of an appropriate

Statistical significance versus clinical importance: trials on exercise therapy for chronic low back pain as example.

NARCIS (Netherlands)

van Tulder, M.W.; Malmivaara, A.; Hayden, J.; Koes, B.

2007-01-01

STUDY DESIGN. Critical appraisal of the literature. OBJECIVES. The objective of this study was to assess if results of back pain trials are statistically significant and clinically important. SUMMARY OF BACKGROUND DATA. There seems to be a discrepancy between conclusions reported by authors and

A statistical study of current-sheet formation above solar active regions based on selforganized criticality

Science.gov (United States)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M.; Anastasiadis, A.; Toutountzi, A.

2013-09-01

We treat flaring solar active regions as physical systems having reached the self-organized critical state. Their evolving magnetic configurations in the low corona may satisfy an instability criterion, related to the excession of a specific threshold in the curl of the magnetic field. This imposed instability criterion implies an almost zero resistivity everywhere in the solar corona, except in regions where magnetic-field discontinuities and. hence, local currents, reach the critical value. In these areas, current-driven instabilities enhance the resistivity by many orders of magnitude forming structures which efficiently accelerate charged particles. Simulating the formation of such structures (thought of as current sheets) via a refined SOC cellular-automaton model provides interesting information regarding their statistical properties. It is shown that the current density in such unstable regions follows power-law scaling. Furthermore, the size distribution of the produced current sheets is best fitted by power laws, whereas their formation probability is investigated against the photospheric magnetic configuration (e.g. Polarity Inversion Lines, Plage). The average fractal dimension of the produced current sheets is deduced depending on the selected critical threshold. The above-mentioned statistical description of intermittent electric field structures can be used by collisional relativistic test particle simulations, aiming to interpret particle acceleration in flaring active regions and in strongly turbulent media in astrophysical plasmas. The above work is supported by the Hellenic National Space Weather Research Network (HNSWRN) via the THALIS Programme.

Using the longest significance run to estimate region-specific p-values in genetic association mapping studies

Directory of Open Access Journals (Sweden)

Yang Hsin-Chou

2008-05-01

Full Text Available Abstract Background Association testing is a powerful tool for identifying disease susceptibility genes underlying complex diseases. Technological advances have yielded a dramatic increase in the density of available genetic markers, necessitating an increase in the number of association tests required for the analysis of disease susceptibility genes. As such, multiple-tests corrections have become a critical issue. However the conventional statistical corrections on locus-specific multiple tests usually result in lower power as the number of markers increases. Alternatively, we propose here the application of the longest significant run (LSR method to estimate a region-specific p-value to provide an index for the most likely candidate region. Results An advantage of the LSR method relative to procedures based on genotypic data is that only p-value data are needed and hence can be applied extensively to different study designs. In this study the proposed LSR method was compared with commonly used methods such as Bonferroni's method and FDR controlling method. We found that while all methods provide good control over false positive rate, LSR has much better power and false discovery rate. In the authentic analysis on psoriasis and asthma disease data, the LSR method successfully identified important candidate regions and replicated the results of previous association studies. Conclusion The proposed LSR method provides an efficient exploratory tool for the analysis of sequences of dense genetic markers. Our results show that the LSR method has better power and lower false discovery rate comparing with the locus-specific multiple tests.

Statistical dynamics of regional populations and economies

Science.gov (United States)

Huo, Jie; Wang, Xu-Ming; Hao, Rui; Wang, Peng

Quantitative analysis of human behavior and social development is becoming a hot spot of some interdisciplinary studies. A statistical analysis on the population and GDP of 150 cities in China from 1990 to 2013 is conducted. The result indicates the cumulative probability distribution of the populations and that of the GDPs obeying the shifted power law, respectively. In order to understand these characteristics, a generalized Langevin equation describing variation of population is proposed, which is based on the correlations between population and GDP as well as the random fluctuations of the related factors. The equation is transformed into the Fokker-Plank equation to express the evolution of population distribution. The general solution demonstrates a transition of the distribution from the normal Gaussian distribution to a shifted power law, which suggests a critical point of time at which the transition takes place. The shifted power law distribution in the supercritical situation is qualitatively in accordance with the practical result. The distribution of the GDPs is derived from the well-known Cobb-Douglas production function. The result presents a change, in supercritical situation, from a shifted power law to the Gaussian distribution. This is a surprising result-the regional GDP distribution of our world will be the Gaussian distribution one day in the future. The discussions based on the changing trend of economic growth suggest it will be true. Therefore, these theoretical attempts may draw a historical picture of our society in the aspects of population and economy.

Indirectional statistics and the significance of an asymmetry discovered by Birch

International Nuclear Information System (INIS)

Kendall, D.G.; Young, G.A.

1984-01-01

Birch (1982, Nature, 298, 451) reported an apparent 'statistical asymmetry of the Universe'. The authors here develop 'indirectional analysis' as a technique for investigating statistical effects of this kind and conclude that the reported effect (whatever may be its origin) is strongly supported by the observations. The estimated pole of the asymmetry is at RA 13h 30m, Dec. -37deg. The angular error in its estimation is unlikely to exceed 20-30deg. (author)

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

Science.gov (United States)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y; Drake, Steven K; Gucek, Marjan; Sacks, David B; Yu, Yi-Kuo

2018-06-05

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

A statistical study of ion energization at 1700 km in the auroral region

Directory of Open Access Journals (Sweden)

M. Hamrin

2002-12-01

Full Text Available We present a comprehensive overview of several potentially relevant causes for the oxygen energization in the auroral region. Data from the Freja satellite near 1700 km altitude are used for an unconditional statistical investigation. The data are obtained in the Northern Hemisphere during 21 months in the declining phase of the solar cycle. The importance of various wave types for the ion energization is statistically studied. We also investigate the correlation of ion heating with precipitating protons, accelerated auroral electrons, suprathermal electron bursts, the electron density variations, Kp index and solar illumination of the nearest conjugate ionosphere. We find that sufficiently strong broad-band ELF waves, electromagnetic ion cyclotron waves, and waves around the lower hybrid frequency are foremost associated with the ion heating. However, magnetosonic waves, with a sharp, lower frequency cutoff just below the proton gyrofrequency, are not found to contribute to the ion heating. In the absence of the first three wave emissions, transversely energized ions are rare. These wave types are approximately equally efficient in heating the ions, but we find that the main source for the heating is broadband ELF waves, since they are most common in the auroral region. We have also observed that the conditions for ion heating are more favourable for smaller ratios of the spectral densities SE /SB of the broadband ELF waves at the oxygen gyrofrequency.Key words. Ionosphere (auroral ionosphere; wave propogation Magnetospheric physics (electric fields

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data.

Science.gov (United States)

Kim, Sung-Min; Choi, Yosoon

2017-06-18

To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z -score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z -scores: high content with a high z -score (HH), high content with a low z -score (HL), low content with a high z -score (LH), and low content with a low z -score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1-4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data

Directory of Open Access Journals (Sweden)

Sung-Min Kim

2017-06-01

Full Text Available To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z-score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z-scores: high content with a high z-score (HH, high content with a low z-score (HL, low content with a high z-score (LH, and low content with a low z-score (LL. The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1–4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.

Regional regression equations for the estimation of selected monthly low-flow duration and frequency statistics at ungaged sites on streams in New Jersey

Science.gov (United States)

Watson, Kara M.; McHugh, Amy R.

2014-01-01

Regional regression equations were developed for estimating monthly flow-duration and monthly low-flow frequency statistics for ungaged streams in Coastal Plain and non-coastal regions of New Jersey for baseline and current land- and water-use conditions. The equations were developed to estimate 87 different streamflow statistics, which include the monthly 99-, 90-, 85-, 75-, 50-, and 25-percentile flow-durations of the minimum 1-day daily flow; the August–September 99-, 90-, and 75-percentile minimum 1-day daily flow; and the monthly 7-day, 10-year (M7D10Y) low-flow frequency. These 87 streamflow statistics were computed for 41 continuous-record streamflow-gaging stations (streamgages) with 20 or more years of record and 167 low-flow partial-record stations in New Jersey with 10 or more streamflow measurements. The regression analyses used to develop equations to estimate selected streamflow statistics were performed by testing the relation between flow-duration statistics and low-flow frequency statistics for 32 basin characteristics (physical characteristics, land use, surficial geology, and climate) at the 41 streamgages and 167 low-flow partial-record stations. The regression analyses determined drainage area, soil permeability, average April precipitation, average June precipitation, and percent storage (water bodies and wetlands) were the significant explanatory variables for estimating the selected flow-duration and low-flow frequency statistics. Streamflow estimates were computed for two land- and water-use conditions in New Jersey—land- and water-use during the baseline period of record (defined as the years a streamgage had little to no change in development and water use) and current land- and water-use conditions (1989–2008)—for each selected station using data collected through water year 2008. The baseline period of record is representative of a period when the basin was unaffected by change in development. The current period is

Statistically significant faunal differences among Middle Ordovician age, Chickamauga Group bryozoan bioherms, central Alabama

Energy Technology Data Exchange (ETDEWEB)

Crow, C.J.

1985-01-01

Middle Ordovician age Chickamauga Group carbonates crop out along the Birmingham and Murphrees Valley anticlines in central Alabama. The macrofossil contents on exposed surfaces of seven bioherms have been counted to determine their various paleontologic characteristics. Twelve groups of organisms are present in these bioherms. Dominant organisms include bryozoans, algae, brachiopods, sponges, pelmatozoans, stromatoporoids and corals. Minor accessory fauna include predators, scavengers and grazers such as gastropods, ostracods, trilobites, cephalopods and pelecypods. Vertical and horizontal niche zonation has been detected for some of the bioherm dwelling fauna. No one bioherm of those studied exhibits all 12 groups of organisms; rather, individual bioherms display various subsets of the total diversity. Statistical treatment (G-test) of the diversity data indicates a lack of statistical homogeneity of the bioherms, both within and between localities. Between-locality population heterogeneity can be ascribed to differences in biologic responses to such gross environmental factors as water depth and clarity, and energy levels. At any one locality, gross aspects of the paleoenvironments are assumed to have been more uniform. Significant differences among bioherms at any one locality may have resulted from patchy distribution of species populations, differential preservation and other factors.

Identify fracture-critical regions inside the proximal femur using statistical parametric mapping

Science.gov (United States)

Li, Wenjun; Kornak, John; Harris, Tamara; Keyak, Joyce; Li, Caixia; Lu, Ying; Cheng, Xiaoguang; Lang, Thomas

2009-01-01

We identified regions inside the proximal femur that are most strongly associated with hip fracture. Bone densitometry based on such fracture-critical regions showed improved power in discriminating fracture patients from controls. Introduction Hip fractures typically occur in lateral falls, with focal mechanical failure of the sub-volumes of tissue in which the applied stress exceeds the strength. In this study, we describe a new methodology to identify proximal femoral tissue elements with highest association with hip fracture. We hypothesize that bone mineral density (BMD) measured in such sub-volumes discriminates hip fracture risk better than BMD in standard anatomic regions such as the femoral neck and trochanter. Materials and Methods We employed inter-subject registration to transform hip QCT images of 37 patients with hip fractures and 38 age-matched controls into a voxel-based statistical atlas. Within voxels, we performed t-tests between the two groups to identify the regions which differed most. We then randomly divided the 75 scans into a training set and a test set. From the training set, we derived a fracture-driven region of interest (ROI) based on association with fracture. In the test set, we measured BMD in this ROI to determine fracture discrimination efficacy using ROC analysis. Additionally, we compared the BMD distribution differences between the 29 patients with neck fractures and the 8 patients with trochanteric fractures. Results By evaluating fracture discrimination power based on ROC analysis, the fracture-driven ROI had an AUC (area under curve) of 0.92, while anatomic ROIs (including the entire proximal femur, the femoral neck, trochanter and their cortical and trabecular compartments) had AUC values between 0.78 and 0.87. We also observed that the neck fracture patients had lower BMD (p=0.014) in a small region near the femoral neck and the femoral head, and patients with trochanteric fractures had lower BMD in trochanteric regions

Detecting Statistically Significant Communities of Triangle Motifs in Undirected Networks

Science.gov (United States)

2016-04-26

Systems, Statistics & Management Science, University of Alabama, USA. 1 DISTRIBUTION A: Distribution approved for public release. Contents 1 Summary 5...13 5 Application to Real Networks 18 5.1 2012 FBS Football Schedule Network... football schedule network. . . . . . . . . . . . . . . . . . . . . . 21 14 Stem plot of degree-ordered vertices versus the degree for college football

Increased frequency of retinopathy of prematurity over the last decade and significant regional differences.

Science.gov (United States)

Holmström, Gerd; Tornqvist, Kristina; Al-Hawasi, Abbas; Nilsson, Åsa; Wallin, Agneta; Hellström, Ann

2018-03-01

Retinopathy of prematurity (ROP) causes childhood blindness globally in prematurely born infants. Although increased levels of oxygen supply lead to increased survival and reduced frequency of cerebral palsy, increased incidence of ROP is reported. With the help of a Swedish register for ROP, SWEDROP, national and regional incidences of ROP and frequencies of treatment were evaluated from 2008 to 2015 (n = 5734), as well as before and after targets of provided oxygen changed from 85-89% to 91-95% in 2014. Retinopathy of prematurity (ROP) was found in 31.9% (1829/5734) of all infants with a gestational age (GA) of <31 weeks at birth and 5.7% of the infants (329/5734) had been treated for ROP. Analyses of the national data revealed an increased incidence of ROP during the 8-year study period (p = 0.003), but there was no significant increase in the frequency of treatment. There were significant differences between the seven health regions of Sweden, regarding both incidence of ROP and frequency of treatment (p < 0.001). Comparison of regional data before and after the new oxygen targets revealed a significant increase in treated ROP in one region [OR: 2.24 (CI: 1.11-4.49), p = 0.024] and a borderline increase in one other [OR: 3.08 (CI: 0.99-9.60), p = 0.052]. The Swedish national ROP register revealed an increased incidence of ROP during an 8-year period and significant regional differences regarding the incidence of ROP and frequency of treatment. © 2017 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review

International Nuclear Information System (INIS)

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-01-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0–0.10 m, or 0–0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component

A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data.

Science.gov (United States)

Lu, Qiongshi; Hu, Yiming; Sun, Jiehuan; Cheng, Yuwei; Cheung, Kei-Hoi; Zhao, Hongyu

2015-05-27

Identifying functional regions in the human genome is a major goal in human genetics. Great efforts have been made to functionally annotate the human genome either through computational predictions, such as genomic conservation, or high-throughput experiments, such as the ENCODE project. These efforts have resulted in a rich collection of functional annotation data of diverse types that need to be jointly analyzed for integrated interpretation and annotation. Here we present GenoCanyon, a whole-genome annotation method that performs unsupervised statistical learning using 22 computational and experimental annotations thereby inferring the functional potential of each position in the human genome. With GenoCanyon, we are able to predict many of the known functional regions. The ability of predicting functional regions as well as its generalizable statistical framework makes GenoCanyon a unique and powerful tool for whole-genome annotation. The GenoCanyon web server is available at http://genocanyon.med.yale.edu.

Conducting tests for statistically significant differences using forest inventory data

Science.gov (United States)

James A. Westfall; Scott A. Pugh; John W. Coulston

2013-01-01

Many forest inventory and monitoring programs are based on a sample of ground plots from which estimates of forest resources are derived. In addition to evaluating metrics such as number of trees or amount of cubic wood volume, it is often desirable to make comparisons between resource attributes. To properly conduct statistical tests for differences, it is imperative...

Statistical analysis of content of Cs-137 in soils in Bansko-Razlog region

International Nuclear Information System (INIS)

Kobilarov, R. G.

2014-01-01

Statistical analysis of the data set consisting of the activity concentrations of 137 Cs in soils in Bansko–Razlog region is carried out in order to establish the dependence of the deposition and the migration of 137 Cs on the soil type. The descriptive statistics and the test of normality show that the data set have not normal distribution. Positively skewed distribution and possible outlying values of the activity of 137 Cs in soils were observed. After reduction of the effects of outliers, the data set is divided into two parts, depending on the soil type. Test of normality of the two new data sets shows that they have a normal distribution. Ordinary kriging technique is used to characterize the spatial distribution of the activity of 137 Cs over an area covering 40 km 2 (whole Razlog valley). The result (a map of the spatial distribution of the activity concentration of 137 Cs) can be used as a reference point for future studies on the assessment of radiological risk to the population and the erosion of soils in the study area

Remote sensing estimation of the total phosphorus concentration in a large lake using band combinations and regional multivariate statistical modeling techniques.

Science.gov (United States)

Gao, Yongnian; Gao, Junfeng; Yin, Hongbin; Liu, Chuansheng; Xia, Ting; Wang, Jing; Huang, Qi

2015-03-15

Remote sensing has been widely used for ater quality monitoring, but most of these monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating the phosphorus concentration in water. The total phosphorus (TP) in lakes has been estimated from remotely sensed observations, primarily using the simple individual band ratio or their natural logarithm and the statistical regression method based on the field TP data and the spectral reflectance. In this study, we investigated the possibility of establishing a spatial modeling scheme to estimate the TP concentration of a large lake from multi-spectral satellite imagery using band combinations and regional multivariate statistical modeling techniques, and we tested the applicability of the spatial modeling scheme. The results showed that HJ-1A CCD multi-spectral satellite imagery can be used to estimate the TP concentration in a lake. The correlation and regression analysis showed a highly significant positive relationship between the TP concentration and certain remotely sensed combination variables. The proposed modeling scheme had a higher accuracy for the TP concentration estimation in the large lake compared with the traditional individual band ratio method and the whole-lake scale regression-modeling scheme. The TP concentration values showed a clear spatial variability and were high in western Lake Chaohu and relatively low in eastern Lake Chaohu. The northernmost portion, the northeastern coastal zone and the southeastern portion of western Lake Chaohu had the highest TP concentrations, and the other regions had the lowest TP concentration values, except for the coastal zone of eastern Lake Chaohu. These results strongly suggested that the proposed modeling scheme, i.e., the band combinations and the regional multivariate

Statistical Analysis of the labor Market in Ukraine Using Multidimensional Classification Methods: the Regional Aspect

Directory of Open Access Journals (Sweden)

Korepanov Oleksiy S.

2017-12-01

Full Text Available The aim of the article is to study the labor market in Ukraine in the regional context using cluster analysis methods. The current state of the labor market in regions of Ukraine is analyzed, and a system of statistical indicators that influence the state and development of this market is formed. The expediency of using cluster analysis for grouping regions according to the level of development of the labor market is substantiated. The essence of cluster analysis is revealed, its main goal, key tasks, which can be solved by means of such analysis, are presented, basic stages of the analysis are considered. The main methods of clustering are described and, based on the results of the simulation, the advantages and disadvantages of each method are justified. In the work the clustering of regions of Ukraine by the level of labor market development using different methods of cluster analysis is carried out, conclusions on the results of the calculations performed are presented, and the main directions for further research are outlined.

Statistical downscaling of regional climate scenarios for the French Alps : Impacts on snow cover

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Rousselot, M.; Durand, Y.; Giraud, G.; Mérindol, L.; Déqué, M.; Sanchez, E.; Pagé, C.; Hasan, A.

2010-12-01

Mountain areas are particularly vulnerable to climate change. Owing to the complexity of mountain terrain, climate research at scales relevant for impacts studies and decisive for stakeholders is challenging. A possible way to bridge the gap between these fine scales and those of the general circulation models (GCMs) consists of combining high-resolution simulations of Regional Climate Models (RCMs) to statistical downscaling methods. The present work is based on such an approach. It aims at investigating the impacts of climate change on snow cover in the French Alps for the periods 2021-2050 and 2071-2100 under several IPCC hypotheses. An analogue method based on high resolution atmospheric fields from various RCMs and climate reanalyses is used to simulate local climate scenarios. These scenarios, which provide meteorological parameters relevant for snowpack evolution, subsequently feed the CROCUS snow model. In these simulations, various sources of uncertainties are thus considered (several greenhouse gases emission scenarios and RCMs). Results are obtained for different regions of the French Alps at various altitudes. For all scenarios, temperature increase is relatively uniform over the Alps. This regional warming is larger than that generally modeled at the global scale (IPCC, 2007), and particularly strong in summer. Annual precipitation amounts seem to decrease, mainly as a result of decreasing precipitation trends in summer and fall. As a result of these climatic evolutions, there is a general decrease of the mean winter snow depth and seasonal snow duration for all massifs. Winter snow depths are particularly reduced in the Northern Alps. However, the impact on seasonal snow duration is more significant in the Southern and Extreme Southern Alps, since these regions are already characterized by small winter snow depths at low elevations. Reference : IPCC (2007a). Climate change 2007 : The physical science basis. Contribution of working group I to the

Statistical region based active contour using a fractional entropy descriptor: Application to nuclei cell segmentation in confocal \\ud microscopy images

OpenAIRE

Histace, A; Meziou, B J; Matuszewski, Bogdan; Precioso, F; Murphy, M F; Carreiras, F

2013-01-01

We propose an unsupervised statistical region based active contour approach integrating an original fractional entropy measure for image segmentation with a particular application to single channel actin tagged fluorescence confocal microscopy image segmentation. Following description of statistical based active contour segmentation and the mathematical definition of the proposed fractional entropy descriptor, we demonstrate comparative segmentation results between the proposed approach and s...

The distribution of P-values in medical research articles suggested selective reporting associated with statistical significance.

Science.gov (United States)

Perneger, Thomas V; Combescure, Christophe

2017-07-01

Published P-values provide a window into the global enterprise of medical research. The aim of this study was to use the distribution of published P-values to estimate the relative frequencies of null and alternative hypotheses and to seek irregularities suggestive of publication bias. This cross-sectional study included P-values published in 120 medical research articles in 2016 (30 each from the BMJ, JAMA, Lancet, and New England Journal of Medicine). The observed distribution of P-values was compared with expected distributions under the null hypothesis (i.e., uniform between 0 and 1) and the alternative hypothesis (strictly decreasing from 0 to 1). P-values were categorized according to conventional levels of statistical significance and in one-percent intervals. Among 4,158 recorded P-values, 26.1% were highly significant (P values values equal to 1, and (3) about twice as many P-values less than 0.05 compared with those more than 0.05. The latter finding was seen in both randomized trials and observational studies, and in most types of analyses, excepting heterogeneity tests and interaction tests. Under plausible assumptions, we estimate that about half of the tested hypotheses were null and the other half were alternative. This analysis suggests that statistical tests published in medical journals are not a random sample of null and alternative hypotheses but that selective reporting is prevalent. In particular, significant results are about twice as likely to be reported as nonsignificant results. Copyright © 2017 Elsevier Inc. All rights reserved.

Age and gender effects on normal regional cerebral blood flow studied using two different voxel-based statistical analyses

International Nuclear Information System (INIS)

Pirson, A.S.; George, J.; Krug, B.; Vander Borght, T.; Van Laere, K.; Jamart, J.; D'Asseler, Y.; Minoshima, S.

2009-01-01

Fully automated analysis programs have been applied more and more to aid for the reading of regional cerebral blood flow SPECT study. They are increasingly based on the comparison of the patient study with a normal database. In this study, we evaluate the ability of Three-Dimensional Stereotactic Surface Projection (3 D-S.S.P.) to isolate effects of age and gender in a previously studied normal population. The results were also compared with those obtained using Statistical Parametric Mapping (S.P.M.99). Methods Eighty-nine 99m Tc-E.C.D.-SPECT studies performed in carefully screened healthy volunteers (46 females, 43 males; age 20 - 81 years) were analysed using 3 D-S.S.P.. A multivariate analysis based on the general linear model was performed with regions as intra-subject factor, gender as inter-subject factor and age as co-variate. Results Both age and gender had a significant interaction effect with regional tracer uptake. An age-related decline (p < 0.001) was found in the anterior cingulate gyrus, left frontal association cortex and left insula. Bilateral occipital association and left primary visual cortical uptake showed a significant relative increase with age (p < 0.001). Concerning the gender effect, women showed higher uptake (p < 0.01) in the parietal and right sensorimotor cortices. An age by gender interaction (p < 0.01) was only found in the left medial frontal cortex. The results were consistent with those obtained with S.P.M.99. Conclusion 3 D-S.S.P. analysis of normal r.C.B.F. variability is consistent with the literature and other automated voxel-based techniques, which highlight the effects of both age and gender. (authors)

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios: A Case Study of Swedish Precipitation

Institute of Scientific and Technical Information of China (English)

无

2006-01-01

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project (CMIP2) are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.

ChIPnorm: a statistical method for normalizing and identifying differential regions in histone modification ChIP-seq libraries.

Science.gov (United States)

Nair, Nishanth Ulhas; Sahu, Avinash Das; Bucher, Philipp; Moret, Bernard M E

2012-01-01

The advent of high-throughput technologies such as ChIP-seq has made possible the study of histone modifications. A problem of particular interest is the identification of regions of the genome where different cell types from the same organism exhibit different patterns of histone enrichment. This problem turns out to be surprisingly difficult, even in simple pairwise comparisons, because of the significant level of noise in ChIP-seq data. In this paper we propose a two-stage statistical method, called ChIPnorm, to normalize ChIP-seq data, and to find differential regions in the genome, given two libraries of histone modifications of different cell types. We show that the ChIPnorm method removes most of the noise and bias in the data and outperforms other normalization methods. We correlate the histone marks with gene expression data and confirm that histone modifications H3K27me3 and H3K4me3 act as respectively a repressor and an activator of genes. Compared to what was previously reported in the literature, we find that a substantially higher fraction of bivalent marks in ES cells for H3K27me3 and H3K4me3 move into a K27-only state. We find that most of the promoter regions in protein-coding genes have differential histone-modification sites. The software for this work can be downloaded from http://lcbb.epfl.ch/software.html.

Epidemiology of bovine fascioliasis in the Nile Delta region of Egypt: Its prevalence, evaluation of risk factors, and its economic significance.

Science.gov (United States)

El-Tahawy, Abdelgawad S; Bazh, Eman K; Khalafalla, Reda E

2017-10-01

This study focuses on the risk factors associated with the prevalence of Fasciola affecting cattle population in three provinces belonging to the Nile Delta of Egypt and to estimate the economic losses as a result of fascioliasis. From January 2015 to end of December 2015, records of 21 farms (4976 cattle) were analyzed to screen the prevalence of fascioliasis among cattle farms, to identify its associated risk factors and its economic impacts on Nile Delta region of Egypt. The overall prevalence of fascioliasis in the Nile Delta region of Egypt was 9.77%. The prevalence of fascioliasis was found to be statistically significantly associated with age, sex, breed, and type of farms. The highest prevalence was observed in 3 age groups (8.35%). In terms of body condition scores, cattle with medium and poor conditions were associated with fascioliasis more than those with good body condition. Besides, cattle raised in organic farms were associated with lower risk of fascioliasis than those in conventional farms. The prevalence of fascioliasis was noted more prominent in districts with moderate temperatures and with relative humidity (>60%). The annual overall costs for fascioliasis were estimated to be 221.2 USD/cow due to the significant reduction in body weight, reduction in milk production, and the treatment costs for fascioliasis. The results provided could be helpful for improving the control and preventive strategies.

The Statistical Analysis of Migration of Strong Earthquakes-Taking the North China Region as an Example

Institute of Scientific and Technical Information of China (English)

Qin Chengzhi; Zhou Chenghu; Pei Tao; Li Quanlin

2004-01-01

The migration of strong earthquakes is an important research topic because the migration phenomena reflect partly the seismic mechanism and involve the prediction of tendency of seismic activity. Research on migration of strong earthquakes has mostly focused on finding the phenomena. Some attempts on getting regularity were comparatively subjective. This paper suggests that there should be indices of migration in earthquake dataset and the indexes should have statistical meaning if there is regularity in the migration of strong earthquakes. In this study, three derivative attributes of migration, i.e., migration orientation, migration distance and migration time interval, were statistically analyzed. Results in the North China region show that the migration of strong earthquakes has statistical meaning. There is a dominant migration orientation (W by S to E by N), a dominant distance ( ≤ 100km and on the confines of 300 ～ 700km), and a dominant time interval ( ≤ 1 a and on the confines of 3 ～ 4a). The results also show that the migration will differ slightly with different magnitude range or earthquake activity phase.

Learning Predictive Statistics: Strategies and Brain Mechanisms.

Science.gov (United States)

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-08-30

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions. SIGNIFICANCE STATEMENT Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. Past work has studied how humans identify repetitive patterns and associative pairings. However, the natural environment contains regularities that vary in complexity from simple repetition to complex probabilistic combinations. Here, we combine behavior and multisession fMRI to track the brain mechanisms that mediate our ability to adapt to

An Application of Multivariate Statistical Analysis for Query-Driven Visualization

Energy Technology Data Exchange (ETDEWEB)

Gosink, Luke J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Garth, Christoph [Univ. of California, Davis, CA (United States); Anderson, John C. [Univ. of California, Davis, CA (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Joy, Kenneth I. [Univ. of California, Davis, CA (United States)

2011-03-01

Driven by the ability to generate ever-larger, increasingly complex data, there is an urgent need in the scientific community for scalable analysis methods that can rapidly identify salient trends in scientific data. Query-Driven Visualization (QDV) strategies are among the small subset of techniques that can address both large and highly complex datasets. This paper extends the utility of QDV strategies with a statistics-based framework that integrates non-parametric distribution estimation techniques with a new segmentation strategy to visually identify statistically significant trends and features within the solution space of a query. In this framework, query distribution estimates help users to interactively explore their query's solution and visually identify the regions where the combined behavior of constrained variables is most important, statistically, to their inquiry. Our new segmentation strategy extends the distribution estimation analysis by visually conveying the individual importance of each variable to these regions of high statistical significance. We demonstrate the analysis benefits these two strategies provide and show how they may be used to facilitate the refinement of constraints over variables expressed in a user's query. We apply our method to datasets from two different scientific domains to demonstrate its broad applicability.

Shape Analysis of HII Regions - I. Statistical Clustering

Science.gov (United States)

Campbell-White, Justyn; Froebrich, Dirk; Kume, Alfred

2018-04-01

We present here our shape analysis method for a sample of 76 Galactic HII regions from MAGPIS 1.4 GHz data. The main goal is to determine whether physical properties and initial conditions of massive star cluster formation is linked to the shape of the regions. We outline a systematic procedure for extracting region shapes and perform hierarchical clustering on the shape data. We identified six groups that categorise HII regions by common morphologies. We confirmed the validity of these groupings by bootstrap re-sampling and the ordinance technique multidimensional scaling. We then investigated associations between physical parameters and the assigned groups. Location is mostly independent of group, with a small preference for regions of similar longitudes to share common morphologies. The shapes are homogeneously distributed across Galactocentric distance and latitude. One group contains regions that are all younger than 0.5 Myr and ionised by low- to intermediate-mass sources. Those in another group are all driven by intermediate- to high-mass sources. One group was distinctly separated from the other five and contained regions at the surface brightness detection limit for the survey. We find that our hierarchical procedure is most sensitive to the spatial sampling resolution used, which is determined for each region from its distance. We discuss how these errors can be further quantified and reduced in future work by utilising synthetic observations from numerical simulations of HII regions. We also outline how this shape analysis has further applications to other diffuse astronomical objects.

Hydrochemical analysis of groundwater using multivariate statistical methods - The Volta region, Ghana

Science.gov (United States)

Banoeng-Yakubo, B.; Yidana, S.M.; Nti, E.

2009-01-01

Q and R-mode multivariate statistical analyses were applied to groundwater chemical data from boreholes and wells in the northern section of the Volta region Ghana. The objective was to determine the processes that affect the hydrochemistry and the variation of these processes in space among the three main geological terrains: the Buem formation, Voltaian System and the Togo series that underlie the area. The analyses revealed three zones in the groundwater flow system: recharge, intermediate and discharge regions. All three zones are clearly different with respect to all the major chemical parameters, with concentrations increasing from the perceived recharge areas through the intermediate regions to the discharge areas. R-mode HCA and factor analysis (using varimax rotation and Kaiser Criterion) were then applied to determine the significant sources of variation in the hydrochemistry. This study finds that groundwater hydrochemistry in the area is controlled by the weathering of silicate and carbonate minerals, as well as the chemistry of infiltrating precipitation. This study finds that the ??D and ??18O data from the area fall along the Global Meteoric Water Line (GMWL). An equation of regression derived for the relationship between ??D and ??18O bears very close semblance to the equation which describes the GMWL. On the basis of this, groundwater in the study area is probably meteoric and fresh. The apparently low salinities and sodicities of the groundwater seem to support this interpretation. The suitability of groundwater for domestic and irrigation purposes is related to its source, which determines its constitution. A plot of the sodium adsorption ratio (SAR) and salinity (EC) data on a semilog axis, suggests that groundwater serves good irrigation quality in the area. Sixty percent (60%), 20% and 20% of the 67 data points used in this study fall within the medium salinity - low sodicity (C2-S1), low salinity -low sodicity (C1-S1) and high salinity - low

Image Segmentation of Cattle Muzzle Using Region Merging Statistical Technic

Directory of Open Access Journals (Sweden)

Jullend Gatc

2015-12-01

Full Text Available Making an identification system that able to assist in obtaining, recording and organizing information is the first step in developing any kind of recording system. Nowadays, many recording systems were developed with artificial markers although it has been proved that it has many limitations. Biometrics use of animals provides a solution to these restrictions. On a cattle, biometric features contained in the cattle muzzle that can be used as a pattern recognition sample. Pattern recognition methods can be used for the development of cattle identification system utilizing biometric found on the cattle muzzle using digital image processing techniques. In this study, we proposed cattle muzzle identification method using segmentation Statistical Region Merging (SRM. This method aims to identify specific patterns found on the cattle muzzle by separating the object pattern (foreground from unnecessary information (background This method is able to identified individual cattle based on the pattern of it muzzle. Based on our evaluation, this method can provide good performance results. This method good performance can be seen from the precision and recall : 87% and the value of ROC : 0.976. Hopefully this research can be used to help identify cattle accurately on the recording process.

Statistics from dynamics in curved spacetime

International Nuclear Information System (INIS)

Parker, L.; Wang, Y.

1989-01-01

We consider quantum fields of spin 0, 1/2, 1, 3/2, and 2 with a nonzero mass in curved spacetime. We show that the dynamical Bogolubov transformations associated with gravitationally induced particle creation imply the connection between spin and statistics: By embedding two flat regions in a curved spacetime, we find that only when one imposes Bose-Einstein statistics for an integer-spin field and Fermi-Dirac statistics for a half-integer-spin field in the first flat region is the same type of statistics propagated from the first to the second flat region. This derivation of the flat-spacetime spin-statistics theorem makes use of curved-spacetime dynamics and does not reduce to any proof given in flat spacetime. We also show in the same manner that parastatistics, up to the fourth order, are consistent with the dynamical evolution of curved spacetime

ChIP-seq Analysis in R (CSAR): An R package for the statistical detection of protein-bound genomic regions

NARCIS (Netherlands)

Muino, J.M.; Kaufmann, K.; Ham, van R.C.H.J.; Angenent, G.C.; Krajewski, P.

2011-01-01

Background In vivo detection of protein-bound genomic regions can be achieved by combining chromatin-immunoprecipitation with next-generation sequencing technology (ChIP-seq). The large amount of sequence data produced by this method needs to be analyzed in a statistically proper and computationally

Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

Science.gov (United States)

Santos, Monica; Fragoso, Marcelo

2010-05-01

Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude

Sigsearch: a new term for post hoc unplanned search for statistically significant relationships with the intent to create publishable findings.

Science.gov (United States)

Hashim, Muhammad Jawad

2010-09-01

Post-hoc secondary data analysis with no prespecified hypotheses has been discouraged by textbook authors and journal editors alike. Unfortunately no single term describes this phenomenon succinctly. I would like to coin the term "sigsearch" to define this practice and bring it within the teaching lexicon of statistics courses. Sigsearch would include any unplanned, post-hoc search for statistical significance using multiple comparisons of subgroups. It would also include data analysis with outcomes other than the prespecified primary outcome measure of a study as well as secondary data analyses of earlier research.

Mask effects on cosmological studies with weak-lensing peak statistics

International Nuclear Information System (INIS)

Liu, Xiangkun; Pan, Chuzhong; Fan, Zuhui; Wang, Qiao

2014-01-01

With numerical simulations, we analyze in detail how the bad data removal, i.e., the mask effect, can influence the peak statistics of the weak-lensing convergence field reconstructed from the shear measurement of background galaxies. It is found that high peak fractions are systematically enhanced because of the presence of masks; the larger the masked area is, the higher the enhancement is. In the case where the total masked area is about 13% of the survey area, the fraction of peaks with signal-to-noise ratio ν ≥ 3 is ∼11% of the total number of peaks, compared with ∼7% of the mask-free case in our considered cosmological model. This can have significant effects on cosmological studies with weak-lensing convergence peak statistics, inducing a large bias in the parameter constraints if the effects are not taken into account properly. Even for a survey area of 9 deg 2 , the bias in (Ω m , σ 8 ) is already intolerably large and close to 3σ. It is noted that most of the affected peaks are close to the masked regions. Therefore, excluding peaks in those regions in the peak statistics can reduce the bias effect but at the expense of losing usable survey areas. Further investigations find that the enhancement of the number of high peaks around the masked regions can be largely attributed to the smaller number of galaxies usable in the weak-lensing convergence reconstruction, leading to higher noise than that of the areas away from the masks. We thus develop a model in which we exclude only those very large masks with radius larger than 3' but keep all the other masked regions in peak counting statistics. For the remaining part, we treat the areas close to and away from the masked regions separately with different noise levels. It is shown that this two-noise-level model can account for the mask effect on peak statistics very well, and the bias in cosmological parameters is significantly reduced if this model is applied in the parameter fitting.

Statistical inference and visualization in scale-space for spatially dependent images

KAUST Repository

Vaughan, Amy

2012-03-01

SiZer (SIgnificant ZERo crossing of the derivatives) is a graphical scale-space visualization tool that allows for statistical inferences. In this paper we develop a spatial SiZer for finding significant features and conducting goodness-of-fit tests for spatially dependent images. The spatial SiZer utilizes a family of kernel estimates of the image and provides not only exploratory data analysis but also statistical inference with spatial correlation taken into account. It is also capable of comparing the observed image with a specific null model being tested by adjusting the statistical inference using an assumed covariance structure. Pixel locations having statistically significant differences between the image and a given null model are highlighted by arrows. The spatial SiZer is compared with the existing independent SiZer via the analysis of simulated data with and without signal on both planar and spherical domains. We apply the spatial SiZer method to the decadal temperature change over some regions of the Earth. © 2011 The Korean Statistical Society.

Sensitivity of regional climate to global temperature and forcing

International Nuclear Information System (INIS)

Tebaldi, Claudia; O’Neill, Brian; Lamarque, Jean-François

2015-01-01

The sensitivity of regional climate to global average radiative forcing and temperature change is important for setting global climate policy targets and designing scenarios. Setting effective policy targets requires an understanding of the consequences exceeding them, even by small amounts, and the effective design of sets of scenarios requires the knowledge of how different emissions, concentrations, or forcing need to be in order to produce substantial differences in climate outcomes. Using an extensive database of climate model simulations, we quantify how differences in global average quantities relate to differences in both the spatial extent and magnitude of climate outcomes at regional (250–1250 km) scales. We show that differences of about 0.3 °C in global average temperature are required to generate statistically significant changes in regional annual average temperature over more than half of the Earth’s land surface. A global difference of 0.8 °C is necessary to produce regional warming over half the land surface that is not only significant but reaches at least 1 °C. As much as 2.5 to 3 °C is required for a statistically significant change in regional annual average precipitation that is equally pervasive. Global average temperature change provides a better metric than radiative forcing for indicating differences in regional climate outcomes due to the path dependency of the effects of radiative forcing. For example, a difference in radiative forcing of 0.5 W m −2 can produce statistically significant differences in regional temperature over an area that ranges between 30% and 85% of the land surface, depending on the forcing pathway. (letter)

Influence of the Budgetary Decentralization on the Economic Growth of Regions of Ukraine: Statistical Estimation

Directory of Open Access Journals (Sweden)

Voznyak Halyna V.

2017-06-01

Full Text Available The aim of the article is to define, determine and analyze the interrelationships between the budgetary decentralization and the economic growth of regions of Ukraine under conditions of reforming the power and financial resources. A statistical estimation of the influence of the budgetary decentralization on the economic growth of regions of Ukraine for 2015-2016 is carried out. The application of the panel data modeling allowed to build econometric models that made it possible to determine the ambiguous nature of the budgetary decentralization and identify key factors of its influence. It is shown that in terms of the income and expenditures the budgetary decentralization is positively associated with the economic growth of regions of Ukraine during the chosen time range of the study. The dynamic growth of the own revenues of local budgets is not a catalyst for the economic development of the regions. A strong negative effect of transfers on the dependent variable is confirmed. Among the variables included in the model and additionally characterizing the budgetary decentralization, the single tax and subsidies for the socio-economic development of individual territories attract attention. As a result of the study, the author justifies the need to minimize the transfer dependence of the regions at a simultaneous increasing of their own revenue base with local taxes and fees serving as a reliable basis for a long-term planning and development.

Statistical downscaling of historical monthly mean winds over a coastal region of complex terrain. II. Predicting wind components

Energy Technology Data Exchange (ETDEWEB)

Kamp, Derek van der [University of Victoria, Pacific Climate Impacts Consortium, Victoria, BC (Canada); University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada); Curry, Charles L. [Environment Canada University of Victoria, Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada); Monahan, Adam H. [University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada)

2012-04-15

A regression-based downscaling technique was applied to monthly mean surface wind observations from stations throughout western Canada as well as from buoys in the Northeast Pacific Ocean over the period 1979-2006. A predictor set was developed from principal component analysis of the three wind components at 500 hPa and mean sea-level pressure taken from the NCEP Reanalysis II. Building on the results of a companion paper, Curry et al. (Clim Dyn 2011), the downscaling was applied to both wind speed and wind components, in an effort to evaluate the utility of each type of predictand. Cross-validated prediction skill varied strongly with season, with autumn and summer displaying the highest and lowest skill, respectively. In most cases wind components were predicted with better skill than wind speeds. The predictive ability of wind components was found to be strongly related to their orientation. Wind components with the best predictions were often oriented along topographically significant features such as constricted valleys, mountain ranges or ocean channels. This influence of directionality on predictive ability is most prominent during autumn and winter at inland sites with complex topography. Stations in regions with relatively flat terrain (where topographic steering is minimal) exhibit inter-station consistencies including region-wide seasonal shifts in the direction of the best predicted wind component. The conclusion that wind components can be skillfully predicted only over a limited range of directions at most stations limits the scope of statistically downscaled wind speed predictions. It seems likely that such limitations apply to other regions of complex terrain as well. (orig.)

Fisher statistics for analysis of diffusion tensor directional information.

Science.gov (United States)

Hutchinson, Elizabeth B; Rutecki, Paul A; Alexander, Andrew L; Sutula, Thomas P

2012-04-30

A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (pstatistical comparison of tissue structural orientation. Copyright © 2012 Elsevier B.V. All rights reserved.

Epidemiology of bovine fascioliasis in the Nile Delta region of Egypt: Its prevalence, evaluation of risk factors, and its economic significance

Directory of Open Access Journals (Sweden)

Abdelgawad S. El-Tahawy

2017-10-01

Full Text Available Aim: This study focuses on the risk factors associated with the prevalence of Fasciola affecting cattle population in three provinces belonging to the Nile Delta of Egypt and to estimate the economic losses as a result of fascioliasis. Materials and Methods: From January 2015 to end of December 2015, records of 21 farms (4976 cattle were analyzed to screen the prevalence of fascioliasis among cattle farms, to identify its associated risk factors and its economic impacts on Nile Delta region of Egypt. Results: The overall prevalence of fascioliasis in the Nile Delta region of Egypt was 9.77%. The prevalence of fascioliasis was found to be statistically significantly associated with age, sex, breed, and type of farms. The highest prevalence was observed in 3 age groups (8.35%. In terms of body condition scores, cattle with medium and poor conditions were associated with fascioliasis more than those with good body condition. Besides, cattle raised in organic farms were associated with lower risk of fascioliasis than those in conventional farms. The prevalence of fascioliasis was noted more prominent in districts with moderate temperatures and with relative humidity (>60%. The annual overall costs for fascioliasis were estimated to be 221.2 USD/cow due to the significant reduction in body weight, reduction in milk production, and the treatment costs for fascioliasis. Conclusion: The results provided could be helpful for improving the control and preventive strategies.

Epidemiology of bovine fascioliasis in the Nile Delta region of Egypt: Its prevalence, evaluation of risk factors, and its economic significance

Science.gov (United States)

El-Tahawy, Abdelgawad S.; Bazh, Eman K.; Khalafalla, Reda E.

2017-01-01

Aim: This study focuses on the risk factors associated with the prevalence of Fasciola affecting cattle population in three provinces belonging to the Nile Delta of Egypt and to estimate the economic losses as a result of fascioliasis. Materials and Methods: From January 2015 to end of December 2015, records of 21 farms (4976 cattle) were analyzed to screen the prevalence of fascioliasis among cattle farms, to identify its associated risk factors and its economic impacts on Nile Delta region of Egypt. Results: The overall prevalence of fascioliasis in the Nile Delta region of Egypt was 9.77%. The prevalence of fascioliasis was found to be statistically significantly associated with age, sex, breed, and type of farms. The highest prevalence was observed in 3 age groups (8.35%). In terms of body condition scores, cattle with medium and poor conditions were associated with fascioliasis more than those with good body condition. Besides, cattle raised in organic farms were associated with lower risk of fascioliasis than those in conventional farms. The prevalence of fascioliasis was noted more prominent in districts with moderate temperatures and with relative humidity (>60%). The annual overall costs for fascioliasis were estimated to be 221.2 USD/cow due to the significant reduction in body weight, reduction in milk production, and the treatment costs for fascioliasis. Conclusion: The results provided could be helpful for improving the control and preventive strategies. PMID:29184371

Industrial commodity statistics yearbook 2001. Production statistics (1992-2001)

International Nuclear Information System (INIS)

2003-01-01

This is the thirty-fifth in a series of annual compilations of statistics on world industry designed to meet both the general demand for information of this kind and the special requirements of the United Nations and related international bodies. Beginning with the 1992 edition, the title of the publication was changed to industrial Commodity Statistics Yearbook as the result of a decision made by the United Nations Statistical Commission at its twenty-seventh session to discontinue, effective 1994, publication of the Industrial Statistics Yearbook, volume I, General Industrial Statistics by the Statistics Division of the United Nations. The United Nations Industrial Development Organization (UNIDO) has become responsible for the collection and dissemination of general industrial statistics while the Statistics Division of the United Nations continues to be responsible for industrial commodity production statistics. The previous title, Industrial Statistics Yearbook, volume II, Commodity Production Statistics, was introduced in the 1982 edition. The first seven editions in this series were published under the title The Growth of World industry and the next eight editions under the title Yearbook of Industrial Statistics. This edition of the Yearbook contains annual quantity data on production of industrial commodities by country, geographical region, economic grouping and for the world. A standard list of about 530 commodities (about 590 statistical series) has been adopted for the publication. The statistics refer to the ten-year period 1992-2001 for about 200 countries and areas

Industrial commodity statistics yearbook 2002. Production statistics (1993-2002)

International Nuclear Information System (INIS)

2004-01-01

This is the thirty-sixth in a series of annual compilations of statistics on world industry designed to meet both the general demand for information of this kind and the special requirements of the United Nations and related international bodies. Beginning with the 1992 edition, the title of the publication was changed to industrial Commodity Statistics Yearbook as the result of a decision made by the United Nations Statistical Commission at its twenty-seventh session to discontinue, effective 1994, publication of the Industrial Statistics Yearbook, volume I, General Industrial Statistics by the Statistics Division of the United Nations. The United Nations Industrial Development Organization (UNIDO) has become responsible for the collection and dissemination of general industrial statistics while the Statistics Division of the United Nations continues to be responsible for industrial commodity production statistics. The previous title, Industrial Statistics Yearbook, volume II, Commodity Production Statistics, was introduced in the 1982 edition. The first seven editions in this series were published under the title 'The Growth of World industry' and the next eight editions under the title 'Yearbook of Industrial Statistics'. This edition of the Yearbook contains annual quantity data on production of industrial commodities by country, geographical region, economic grouping and for the world. A standard list of about 530 commodities (about 590 statistical series) has been adopted for the publication. The statistics refer to the ten-year period 1993-2002 for about 200 countries and areas

Industrial commodity statistics yearbook 2000. Production statistics (1991-2000)

International Nuclear Information System (INIS)

2002-01-01

This is the thirty-third in a series of annual compilations of statistics on world industry designed to meet both the general demand for information of this kind and the special requirements of the United Nations and related international bodies. Beginning with the 1992 edition, the title of the publication was changed to industrial Commodity Statistics Yearbook as the result of a decision made by the United Nations Statistical Commission at its twenty-seventh session to discontinue, effective 1994, publication of the Industrial Statistics Yearbook, volume I, General Industrial Statistics by the Statistics Division of the United Nations. The United Nations Industrial Development Organization (UNIDO) has become responsible for the collection and dissemination of general industrial statistics while the Statistics Division of the United Nations continues to be responsible for industrial commodity production statistics. The previous title, Industrial Statistics Yearbook, volume II, Commodity Production Statistics, was introduced in the 1982 edition. The first seven editions in this series were published under the title The Growth of World industry and the next eight editions under the title Yearbook of Industrial Statistics. This edition of the Yearbook contains annual quantity data on production of industrial commodities by country, geographical region, economic grouping and for the world. A standard list of about 530 commodities (about 590 statistical series) has been adopted for the publication. Most of the statistics refer to the ten-year period 1991-2000 for about 200 countries and areas

Clinical significance of promoter region hypermethylation of microRNA-148a in gastrointestinal cancers

Directory of Open Access Journals (Sweden)

Sun JX

2014-05-01

Full Text Available Jingxu Sun,1,* Yongxi Song,1,* Zhenning Wang,1 Guoli Wang,2 Peng Gao,1 Xiaowan Chen,1 Zhaohua Gao,1 Huimian Xu1 1Department of Surgical Oncology and General Surgery, First Hospital of China Medical University, Shenyang, People’s Republic of China; 2Department of Biochemistry and Molecular Biology, China Medical University, Shenyang, People’s Republic of China *These authors contributed equally to this work Background: MicroRNAs are associated with tumor genesis and progression in various carcinomas. MicroRNA-148a (miR-148a was reported to have low expression in gastrointestinal cancers, and might be regulated by promoter region DNA methylation. Methods: Bisulfite-modified sequencing was used to determine the promoter region DNA methylation status of human gastrointestinal cancer cell lines. Expression levels of miR-148a in cell lines treated with 5-aza-2′-deoxycytidine were determined by quantitative real-time polymerase chain reaction. Total DNA was extracted from the tissues of 64 patients with gastric cancer and 51 patients with colorectal cancer. Methylation status was determined by methylation-specific polymerase chain reaction. All statistical analyses were performed with SPSS 17.0 software. Results: The promoter regions of genes in human gastrointestinal cancer cell lines were all hypermethylated, except for HT-29, and the expression of miR-148a tended to be higher than in controls after treatment with 5-aza-2′-deoxycytidine. The methylation-specific polymerase chain reaction results showed that 56.25% of gastric cancer tissues and 19.61% of colorectal cancer tissues were hypermethylated. A strong correlation was found between the expression of miR-148a and the methylation status of promoter regions (P<0.001, chi-square test and Pearson’s correlation. Furthermore, promoter region CpG site hypermethylation of miR-148a was correlated with increased tumor size (P=0.01 in gastric cancer after analyzing the correlation between

WPRDC Statistics

Data.gov (United States)

Allegheny County / City of Pittsburgh / Western PA Regional Data Center — Data about the usage of the WPRDC site and its various datasets, obtained by combining Google Analytics statistics with information from the WPRDC's data portal.

Statistical analysis of wind speed using two-parameter Weibull distribution in Alaçatı region

International Nuclear Information System (INIS)

Ozay, Can; Celiktas, Melih Soner

2016-01-01

Highlights: • Wind speed & direction data from September 2008 to March 2014 has been analyzed. • Mean wind speed for the whole data set has been found to be 8.11 m/s. • Highest wind speed is observed in July with a monthly mean value of 9.10 m/s. • Wind speed with the most energy has been calculated as 12.77 m/s. • Observed data has been fit to a Weibull distribution and k &c parameters have been calculated as 2.05 and 9.16. - Abstract: Weibull Statistical Distribution is a common method for analyzing wind speed measurements and determining wind energy potential. Weibull probability density function can be used to forecast wind speed, wind density and wind energy potential. In this study a two-parameter Weibull statistical distribution is used to analyze the wind characteristics of Alaçatı region, located in Çeşme, İzmir. The data used in the density function are acquired from a wind measurement station in Alaçatı. Measurements were gathered on three different heights respectively 70, 50 and 30 m between 10 min intervals for five and half years. As a result of this study; wind speed frequency distribution, wind direction trends, mean wind speed, and the shape and the scale (k&c) Weibull parameters have been calculated for the region. Mean wind speed for the entirety of the data set is found to be 8.11 m/s. k&c parameters are found as 2.05 and 9.16 in relative order. Wind direction analysis along with a wind rose graph for the region is also provided with the study. Analysis suggests that higher wind speeds which range from 6–12 m/s are prevalent between the sectors 340–360°. Lower wind speeds, from 3 to 6 m/s occur between sectors 10–29°. Results of this study contribute to the general knowledge about the regions wind energy potential and can be used as a source for investors and academics.

Intelligent system for statistically significant expertise knowledge on the basis of the model of self-organizing nonequilibrium dissipative system

Directory of Open Access Journals (Sweden)

E. A. Tatokchin

2017-01-01

Full Text Available Development of the modern educational technologies caused by broad introduction of comput-er testing and development of distant forms of education does necessary revision of methods of an examination of pupils. In work it was shown, need transition to mathematical criteria, exami-nations of knowledge which are deprived of subjectivity. In article the review of the problems arising at realization of this task and are offered approaches for its decision. The greatest atten-tion is paid to discussion of a problem of objective transformation of rated estimates of the ex-pert on to the scale estimates of the student. In general, the discussion this question is was con-cluded that the solution to this problem lies in the creation of specialized intellectual systems. The basis for constructing intelligent system laid the mathematical model of self-organizing nonequilibrium dissipative system, which is a group of students. This article assumes that the dissipative system is provided by the constant influx of new test items of the expert and non-equilibrium – individual psychological characteristics of students in the group. As a result, the system must self-organize themselves into stable patterns. This patern will allow for, relying on large amounts of data, get a statistically significant assessment of student. To justify the pro-posed approach in the work presents the data of the statistical analysis of the results of testing a large sample of students (> 90. Conclusions from this statistical analysis allowed to develop intelligent system statistically significant examination of student performance. It is based on data clustering algorithm (k-mean for the three key parameters. It is shown that this approach allows you to create of the dynamics and objective expertise evaluation.

China's energy statistics in a global context: A methodology to develop regional energy balances for East, Central and West China

DEFF Research Database (Denmark)

Mischke, Peggy

2013-01-01

for research and policy analysis. An improved understanding of the quality and reliability of Chinese economic and energy data is becoming more important to to understanding global energy markets and future greenhouse gas emissions. China’s national statistical system to track such changes is however still...... developing and, in some instances, energy data remain unavailable in the public domain. This working paper discusses China’s energy and economic statistics in view of identifying suitable indicators to develop a simplified regional energy systems for China from a variety of publicly available data. As China......’s national statistical system continuous to be debated and criticised in terms of data quality, comparability and reliability, an overview of the milestones, status and main issues of China’s energy statistics is given. In a next step, the energy balance format of the International Energy Agency is used...

Statistical-Dynamical Seasonal Forecasts of Central-Southwest Asian Winter Precipitation.

Science.gov (United States)

Tippett, Michael K.; Goddard, Lisa; Barnston, Anthony G.

2005-06-01

Interannual precipitation variability in central-southwest (CSW) Asia has been associated with East Asian jet stream variability and western Pacific tropical convection. However, atmospheric general circulation models (AGCMs) forced by observed sea surface temperature (SST) poorly simulate the region's interannual precipitation variability. The statistical-dynamical approach uses statistical methods to correct systematic deficiencies in the response of AGCMs to SST forcing. Statistical correction methods linking model-simulated Indo-west Pacific precipitation and observed CSW Asia precipitation result in modest, but statistically significant, cross-validated simulation skill in the northeast part of the domain for the period from 1951 to 1998. The statistical-dynamical method is also applied to recent (winter 1998/99 to 2002/03) multimodel, two-tier December-March precipitation forecasts initiated in October. This period includes 4 yr (winter of 1998/99 to 2001/02) of severe drought. Tercile probability forecasts are produced using ensemble-mean forecasts and forecast error estimates. The statistical-dynamical forecasts show enhanced probability of below-normal precipitation for the four drought years and capture the return to normal conditions in part of the region during the winter of 2002/03.May Kabul be without gold, but not without snow.—Traditional Afghan proverb

The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care--Illustrated Using the Swedish Stroke Register.

Directory of Open Access Journals (Sweden)

Anita Lindmark

Full Text Available When profiling hospital performance, quality inicators are commonly evaluated through hospital-specific adjusted means with confidence intervals. When identifying deviations from a norm, large hospitals can have statistically significant results even for clinically irrelevant deviations while important deviations in small hospitals can remain undiscovered. We have used data from the Swedish Stroke Register (Riksstroke to illustrate the properties of a benchmarking method that integrates considerations of both clinical relevance and level of statistical significance.The performance measure used was case-mix adjusted risk of death or dependency in activities of daily living within 3 months after stroke. A hospital was labeled as having outlying performance if its case-mix adjusted risk exceeded a benchmark value with a specified statistical confidence level. The benchmark was expressed relative to the population risk and should reflect the clinically relevant deviation that is to be detected. A simulation study based on Riksstroke patient data from 2008-2009 was performed to investigate the effect of the choice of the statistical confidence level and benchmark value on the diagnostic properties of the method.Simulations were based on 18,309 patients in 76 hospitals. The widely used setting, comparing 95% confidence intervals to the national average, resulted in low sensitivity (0.252 and high specificity (0.991. There were large variations in sensitivity and specificity for different requirements of statistical confidence. Lowering statistical confidence improved sensitivity with a relatively smaller loss of specificity. Variations due to different benchmark values were smaller, especially for sensitivity. This allows the choice of a clinically relevant benchmark to be driven by clinical factors without major concerns about sufficiently reliable evidence.The study emphasizes the importance of combining clinical relevance and level of statistical

The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care--Illustrated Using the Swedish Stroke Register.

Science.gov (United States)

Lindmark, Anita; van Rompaye, Bart; Goetghebeur, Els; Glader, Eva-Lotta; Eriksson, Marie

2016-01-01

When profiling hospital performance, quality inicators are commonly evaluated through hospital-specific adjusted means with confidence intervals. When identifying deviations from a norm, large hospitals can have statistically significant results even for clinically irrelevant deviations while important deviations in small hospitals can remain undiscovered. We have used data from the Swedish Stroke Register (Riksstroke) to illustrate the properties of a benchmarking method that integrates considerations of both clinical relevance and level of statistical significance. The performance measure used was case-mix adjusted risk of death or dependency in activities of daily living within 3 months after stroke. A hospital was labeled as having outlying performance if its case-mix adjusted risk exceeded a benchmark value with a specified statistical confidence level. The benchmark was expressed relative to the population risk and should reflect the clinically relevant deviation that is to be detected. A simulation study based on Riksstroke patient data from 2008-2009 was performed to investigate the effect of the choice of the statistical confidence level and benchmark value on the diagnostic properties of the method. Simulations were based on 18,309 patients in 76 hospitals. The widely used setting, comparing 95% confidence intervals to the national average, resulted in low sensitivity (0.252) and high specificity (0.991). There were large variations in sensitivity and specificity for different requirements of statistical confidence. Lowering statistical confidence improved sensitivity with a relatively smaller loss of specificity. Variations due to different benchmark values were smaller, especially for sensitivity. This allows the choice of a clinically relevant benchmark to be driven by clinical factors without major concerns about sufficiently reliable evidence. The study emphasizes the importance of combining clinical relevance and level of statistical confidence when

Properties of permutation-based gene tests and controlling type 1 error using a summary statistic based gene test.

Science.gov (United States)

Swanson, David M; Blacker, Deborah; Alchawa, Taofik; Ludwig, Kerstin U; Mangold, Elisabeth; Lange, Christoph

2013-11-07

The advent of genome-wide association studies has led to many novel disease-SNP associations, opening the door to focused study on their biological underpinnings. Because of the importance of analyzing these associations, numerous statistical methods have been devoted to them. However, fewer methods have attempted to associate entire genes or genomic regions with outcomes, which is potentially more useful knowledge from a biological perspective and those methods currently implemented are often permutation-based. One property of some permutation-based tests is that their power varies as a function of whether significant markers are in regions of linkage disequilibrium (LD) or not, which we show from a theoretical perspective. We therefore develop two methods for quantifying the degree of association between a genomic region and outcome, both of whose power does not vary as a function of LD structure. One method uses dimension reduction to "filter" redundant information when significant LD exists in the region, while the other, called the summary-statistic test, controls for LD by scaling marker Z-statistics using knowledge of the correlation matrix of markers. An advantage of this latter test is that it does not require the original data, but only their Z-statistics from univariate regressions and an estimate of the correlation structure of markers, and we show how to modify the test to protect the type 1 error rate when the correlation structure of markers is misspecified. We apply these methods to sequence data of oral cleft and compare our results to previously proposed gene tests, in particular permutation-based ones. We evaluate the versatility of the modification of the summary-statistic test since the specification of correlation structure between markers can be inaccurate. We find a significant association in the sequence data between the 8q24 region and oral cleft using our dimension reduction approach and a borderline significant association using the

Climatic change of summer temperature and precipitation in the Alpine region - a statistical-dynamical assessment

Energy Technology Data Exchange (ETDEWEB)

Heimann, D.; Sept, V.

1998-12-01

Climatic changes in the Alpine region due to increasing greenhouse gas concentrations are assessed by using statistical-dynamical downscaling. The downscaling procedure is applied to two 30-year periods (1971-2000 and 2071-2100, summer months only) of the output of a transient coupled ocean/atmosphere climate scenario simulation. The downscaling results for the present-day climate are in sufficient agreement with observations. The estimated regional climate change during the next 100 years shows a general warming. The mean summer temperatures increase by about 3 to more than 5 Kelvin. The most intense climatic warming is predicted in the western parts of the Alps. The amount of summer precipitation decreases in most parts of central Europe by more than 20 percent. Only over the Adriatic area and parts of eastern central Europe an increase in precipitation is simulated. The results are compared with observed trends and results of regional climate change simulations of other authors. The observed trends and the majority of the simulated trends agree with our results. However, there are also climate change estimates which completely contradict with ours. (orig.) 29 refs.

Lagrangian statistics across the turbulent-nonturbulent interface in a turbulent plane jet.

Science.gov (United States)

Taveira, Rodrigo R; Diogo, José S; Lopes, Diogo C; da Silva, Carlos B

2013-10-01

Lagrangian statistics from millions of particles are used to study the turbulent entrainment mechanism in a direct numerical simulation of a turbulent plane jet at Re(λ) ≈ 110. The particles (tracers) are initially seeded at the irrotational region of the jet near the turbulent shear layer and are followed as they are drawn into the turbulent region across the turbulent-nonturbulent interface (TNTI), allowing the study of the enstrophy buildup and thereby characterizing the turbulent entrainment mechanism in the jet. The use of Lagrangian statistics following fluid particles gives a more correct description of the entrainment mechanism than in previous works since the statistics in relation to the TNTI position involve data from the trajectories of the entraining fluid particles. The Lagrangian statistics for the particles show the existence of a velocity jump and a characteristic vorticity jump (with a thickness which is one order of magnitude greater than the Kolmogorov microscale), in agreement with previous results using Eulerian statistics. The particles initially acquire enstrophy by viscous diffusion and later by enstrophy production, which becomes "active" only deep inside the turbulent region. Both enstrophy diffusion and production near the TNTI differ substantially from inside the turbulent region. Only about 1% of all particles find their way into pockets of irrotational flow engulfed into the turbulent shear layer region, indicating that "engulfment" is not significant for the present flow, indirectly suggesting that the entrainment is largely due to "nibbling" small-scale mechanisms acting along the entire TNTI surface. Probability density functions of particle positions suggests that the particles spend more time crossing the region near the TNTI than traveling inside the turbulent region, consistent with the particles moving tangent to the interface around the time they cross it.

Governance and Regional Variation of Homicide Rates: Evidence From Cross-National Data.

Science.gov (United States)

Cao, Liqun; Zhang, Yan

2017-01-01

Criminological theories of cross-national studies of homicide have underestimated the effects of quality governance of liberal democracy and region. Data sets from several sources are combined and a comprehensive model of homicide is proposed. Results of the spatial regression model, which controls for the effect of spatial autocorrelation, show that quality governance, human development, economic inequality, and ethnic heterogeneity are statistically significant in predicting homicide. In addition, regions of Latin America and non-Muslim Sub-Saharan Africa have significantly higher rates of homicides ceteris paribus while the effects of East Asian countries and Islamic societies are not statistically significant. These findings are consistent with the expectation of the new modernization and regional theories. © The Author(s) 2015.

Test the Overall Significance of p-values by Using Joint Tail Probability of Ordered p-values as Test Statistic

NARCIS (Netherlands)

Fang, Yongxiang; Wit, Ernst

2008-01-01

Fisher’s combined probability test is the most commonly used method to test the overall significance of a set independent p-values. However, it is very obviously that Fisher’s statistic is more sensitive to smaller p-values than to larger p-value and a small p-value may overrule the other p-values

OECD eXplorer: Making Regional Statistics Come Alive through a Geo-Visual Web-Tool

Directory of Open Access Journals (Sweden)

Monica Brezzi

2011-06-01

Full Text Available Recent advances in web-enabled graphics technologies have the potential to make a dramatic impact on developing highly interactive Geovisual Analytics applications for the Internet. An emerging and challenging application domain is geovisualization of regional (sub-national statistics. Higher integration drivenby institutional processes and economic globalisation is eroding national borders and creating competition along regional lines in the world market. Sound information at sub-national level and benchmark of regions across borders have gained importance in the policy agenda of many countries. In this paper, we introduce “OECD eXplorer” — an interactive tool for analyzing and communicating gained insights and discoveries about spatial-temporal and multivariate OECD regional data. This database is a potential treasure chest for policy-makers, researchers and citizens to gain a better understanding of a region’s structure and performance and to carry out analysis of territorial trends and disparities based on sound information comparableacross countries. Many approaches and tools have been developed in spatial-related knowledge discovery but generally they do not scale well with dynamic visualization of larger spatial data on the Internet. In this context, we introduce a web-compliant Geovisual Analytics toolkit that supports a broad collection offunctional components for analysis, hypothesis generation and validation. The same tool enables the communicationof results on the basis of a snapshot mechanism that captures, re-uses and shares task-related explorative findings. Further developments underway are in the creation of a generic highly interactive web “eXplorer” platform that can be the foundation for easy customization of similar web applications usingdifferent geographical boundaries and indicators. Given this global dimension, a “generic eXplorer” will be a powerful tool to explore different territorial dimensions

Personal birth preferences and actual mode of delivery outcomes of obstetricians and gynaecologists in South West England; with comparison to regional and national birth statistics.

Science.gov (United States)

Lightly, Katie; Shaw, Elisabeth; Dailami, Narges; Bisson, Dina

2014-10-01

To determine personal birth preferences of obstetricians in various clinical scenarios, in particular elective caesarean section for maternal request. To determine actual rates of modes of deliveries amongst the same group. To compare the obstetrician's mode of delivery rates, to the general population. Following ethical approval, a piloted online survey link was sent via email to 242 current obstetricians and gynaecologists, (consultants and trainees) in South West England. Mode of delivery results were compared to regional and national population data, using Hospital Episode Statistics and subjected to statistical analysis. The response rate was 68%. 90% would hypothetically plan a vaginal delivery, 10% would consider a caesarean section in an otherwise uncomplicated primiparous pregnancy. Of the 94/165 (60%) respondents with children (201 children), mode of delivery for the first born child; normal vaginal delivery 48%, caesarean section 26.5% (elective 8.5%, emergency 18%), instrumental 24.5% and vaginal breech 1%. Only one chose an elective caesarean for maternal request. During 2006-2011 obstetricians have the same overall actual modes of birth as the population (p=0.9). Ten percent of obstetricians report they would consider requesting caesarean section for themselves/their partner, which is the lowest rate reported within UK studies. However only 1% actually had a caesarean solely for maternal choice. When compared to regional/national statistics obstetricians currently have modes of delivery that are not significantly different than the population and suggests that they choose non interventional delivery if possible. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Statistical determination of significant curved I-girder bridge seismic response parameters

Science.gov (United States)

Seo, Junwon

2013-06-01

Curved steel bridges are commonly used at interchanges in transportation networks and more of these structures continue to be designed and built in the United States. Though the use of these bridges continues to increase in locations that experience high seismicity, the effects of curvature and other parameters on their seismic behaviors have been neglected in current risk assessment tools. These tools can evaluate the seismic vulnerability of a transportation network using fragility curves. One critical component of fragility curve development for curved steel bridges is the completion of sensitivity analyses that help identify influential parameters related to their seismic response. In this study, an accessible inventory of existing curved steel girder bridges located primarily in the Mid-Atlantic United States (MAUS) was used to establish statistical characteristics used as inputs for a seismic sensitivity study. Critical seismic response quantities were captured using 3D nonlinear finite element models. Influential parameters from these quantities were identified using statistical tools that incorporate experimental Plackett-Burman Design (PBD), which included Pareto optimal plots and prediction profiler techniques. The findings revealed that the potential variation in the influential parameters included number of spans, radius of curvature, maximum span length, girder spacing, and cross-frame spacing. These parameters showed varying levels of influence on the critical bridge response.

Automated Analysis of 123I-beta-CIT SPECT Images with Statistical Probabilistic Anatomical Mapping

International Nuclear Information System (INIS)

Eo, Jae Seon; Lee, Hoyoung; Lee, Jae Sung; Kim, Yu Kyung; Jeon, Bumseok; Lee, Dong Soo

2014-01-01

Population-based statistical probabilistic anatomical maps have been used to generate probabilistic volumes of interest for analyzing perfusion and metabolic brain imaging. We investigated the feasibility of automated analysis for dopamine transporter images using this technique and evaluated striatal binding potentials in Parkinson's disease and Wilson's disease. We analyzed 2β-Carbomethoxy-3β-(4- 123 I-iodophenyl)tropane ( 123 I-beta-CIT) SPECT images acquired from 26 people with Parkinson's disease (M:F=11:15,mean age=49±12 years), 9 people with Wilson's disease (M: F=6:3, mean age=26±11 years) and 17 normal controls (M:F=5:12, mean age=39±16 years). A SPECT template was created using striatal statistical probabilistic map images. All images were spatially normalized onto the template, and probability-weighted regional counts in striatal structures were estimated. The binding potential was calculated using the ratio of specific and nonspecific binding activities at equilibrium. Voxel-based comparisons between groups were also performed using statistical parametric mapping. Qualitative assessment showed that spatial normalizations of the SPECT images were successful for all images. The striatal binding potentials of participants with Parkinson's disease and Wilson's disease were significantly lower than those of normal controls. Statistical parametric mapping analysis found statistically significant differences only in striatal regions in both disease groups compared to controls. We successfully evaluated the regional 123 I-beta-CIT distribution using the SPECT template and probabilistic map data automatically. This procedure allows an objective and quantitative comparison of the binding potential, which in this case showed a significantly decreased binding potential in the striata of patients with Parkinson's disease or Wilson's disease

Active Contour Driven by Local Region Statistics and Maximum A Posteriori Probability for Medical Image Segmentation

Directory of Open Access Journals (Sweden)

Xiaoliang Jiang

2014-01-01

Full Text Available This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances. Then, we use the Gaussian distribution with bias field as a local region descriptor in level set formulation for segmentation and bias field correction of the images with inhomogeneous intensities. Therefore, image segmentation and bias field estimation are simultaneously achieved by minimizing the level set formulation. Experimental results demonstrate desirable performance of the proposed method for different medical images with weak boundaries and noise.

Arsenic health risk assessment in drinking water and source apportionment using multivariate statistical techniques in Kohistan region, northern Pakistan.

Science.gov (United States)

Muhammad, Said; Tahir Shah, M; Khan, Sardar

2010-10-01

The present study was conducted in Kohistan region, where mafic and ultramafic rocks (Kohistan island arc and Indus suture zone) and metasedimentary rocks (Indian plate) are exposed. Water samples were collected from the springs, streams and Indus river and analyzed for physical parameters, anions, cations and arsenic (As(3+), As(5+) and arsenic total). The water quality in Kohistan region was evaluated by comparing the physio-chemical parameters with permissible limits set by Pakistan environmental protection agency and world health organization. Most of the studied parameters were found within their respective permissible limits. However in some samples, the iron and arsenic concentrations exceeded their permissible limits. For health risk assessment of arsenic, the average daily dose, hazards quotient (HQ) and cancer risk were calculated by using statistical formulas. The values of HQ were found >1 in the samples collected from Jabba, Dubair, while HQ values were pollution load was also calculated by using multivariate statistical techniques like one-way ANOVA, correlation analysis, regression analysis, cluster analysis and principle component analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

Statistical Study in the mid-altitude cusp region: wave and particle data comparison using a normalized cusp crossing duration

Science.gov (United States)

Grison, B.; Escoubet, C. P.; Pitout, F.; Cornilleau-Wehrlin, N.; Dandouras, I.; Lucek, E.

2009-04-01

In the mid altitude cusp region the DC magnetic field presents a diamagnetic cavity due to intense ion earthward flux coming from the magnetosheath. A strong ultra low frequency (ULF) magnetic activity is also commonly observed in this region. Most of the mid altitude cusp statistical studies have focused on the location of the cusp and its dependence and response to solar wind, interplanetary magnetic field, dipole tilt angle parameters. In our study we use the database build by Pitout et al. (2006) in order to study the link of wave power in the ULF range (0.35-10Hz) measured by STAFF SC instrument with the ion plasma properties as measured by CIS (and CODIF) instrument as well as the diamagnetic cavity in the mid-altitude cusp region with FGM data. To compare the different crossings we don`t use the cusp position and dynamics but we use a normalized cusp crossing duration that permits to easily average the properties over a large number of crossings. As usual in the cusp, it is particularly relevant to sort the crossings by the corresponding interplanetary magnetic field (IMF) orientation in order to analyse the results. In particular we try to find out what is the most relevant parameter to link the strong wave activity with. The global statistic confirms previous single case observations that have noticed a simultaneity between ion injections and wave activity enhancements. We will also present results concerning other ion parameters and the diamagnetic cavity observed in the mid altitude cusp region.

Statistical analysis of wind power in the region of Veracruz (Mexico)

Energy Technology Data Exchange (ETDEWEB)

Cancino-Solorzano, Yoreley [Departamento de Ing Electrica-Electronica, Instituto Tecnologico de Veracruz, Calzada Miguel A. de Quevedo 2779, 91860 Veracruz (Mexico); Xiberta-Bernat, Jorge [Departamento de Energia, Escuela Tecnica Superior de Ingenieros de Minas, Universidad de Oviedo, C/Independencia, 13, 2a Planta, 33004 Oviedo (Spain)

2009-06-15

The capacity of the Mexican electricity sector faces the challenge of satisfying the demand of the 80 GW forecast by 2016. This value supposes a steady yearly average increase of some 4.9%. The electricity sector increases for the next eight years will be mainly made up of combined cycle power plants which could be a threat to the energy supply of the country due to the fact that the country is not self-sufficient in natural gas. As an alternative wind energy resource could be a more suitable option compared with combined cycle power plants. This option is backed by market trends indicating that wind technology costs will continue to decrease in the near future as has happened in recent years. Evaluation of the eolic potential in different areas of the country must be carried out in order to achieve the best use possible of this option. This paper gives a statistical analysis of the wind characteristics in the region of Veracruz. The daily, monthly and annual wind speed values have been studied together with their prevailing direction. The data analyzed correspond to five meteorological stations and two anemometric stations located in the aforementioned area. (author)

Statistical analysis of wind power in the region of Veracruz (Mexico)

International Nuclear Information System (INIS)

Cancino-Solorzano, Yoreley; Xiberta-Bernat, Jorge

2009-01-01

The capacity of the Mexican electricity sector faces the challenge of satisfying the demand of the 80 GW forecast by 2016. This value supposes a steady yearly average increase of some 4.9%. The electricity sector increases for the next eight years will be mainly made up of combined cycle power plants which could be a threat to the energy supply of the country due to the fact that the country is not self-sufficient in natural gas. As an alternative wind energy resource could be a more suitable option compared with combined cycle power plants. This option is backed by market trends indicating that wind technology costs will continue to decrease in the near future as has happened in recent years. Evaluation of the eolic potential in different areas of the country must be carried out in order to achieve the best use possible of this option. This paper gives a statistical analysis of the wind characteristics in the region of Veracruz. The daily, monthly and annual wind speed values have been studied together with their prevailing direction. The data analyzed correspond to five meteorological stations and two anemometric stations located in the aforementioned area. (author)

Significance of Tl-201 redistribution on infarcted region assessed by coronary sinus flow and lactate metabolism

International Nuclear Information System (INIS)

Mori, Takao; Yamabe, Hiroshi; Suda, Kenichirou; Ohnishi, Masataka; Shiotani, Hideyuki; Kurimoto, Yasuyuki; Kobayashi, Katsuya; Maeda, Kazumi; Fukuzaki, Hisashi

1987-01-01

To clarify the significance of Tl-201 redistribution on infarcted regions, coronary sinus and great cardiac vein flow response and lactate metabolism assessed by Webster catheter on 14 infarcted regions after dipyridamole administration were compared with Tl-201 redistribution phenomenon. The regional coronary flow response and lactate extraction ratio in 11 regions with Tl-201 redistribution were lower than those in 3 regions without Tl-201 redistribution. Only 5 regions in 11 with Tl-201 redistribution showed lactate production. The coronary flow response in 5 regions with lactate production was not different from those in 6 without lactate production (1.16 ± 0.89 vs. 1.47 ± 0.67; n.s.). The degree of Tl-201 redistribution assessed by relative activity was not different between regions with and without lactate production. The left ventricular end-diastolic pressure elevated in 5 regions with lactate production (17.8 ± 5.4 mmHg to 29.6 ± 4.9 mmHg; p < 0.05), but didn't in 6 regions without lactate production. Five regions with lactate production contained 4 hypokinetic regions, on the other hand 6 regions without lactate production contained only 3 hypokinetic regions. In conclusion, Tl-201 redistribution on infarcted region revealed not only ischemia but also decreased coronary flow response without lactate production and/or left ventricular dysfunction. (author)

Statistical downscaling of sea-surface wind over the Peru-Chile upwelling region: diagnosing the impact of climate change from the IPSL-CM4 model

Energy Technology Data Exchange (ETDEWEB)

Goubanova, K. [CNES/CNRS/IRD/UPS, Laboratoire d' Etudes en Geophysique et Oceanographie Spatiale, Toulouse (France); Instituto del Mar del Peru, Callao (Peru); Echevin, V.; Terray, P. [IPSL/UPMC/IRD, Laboratoire d' Oceanographie et de Climatologie, Experimentation et Approches Numeriques, Paris (France); Dewitte, B. [CNES/CNRS/IRD/UPS, Laboratoire d' Etudes en Geophysique et Oceanographie Spatiale, Toulouse (France); Instituto del Mar del Peru, Callao (Peru); Instituto Geofisico del Peru, Lima (Peru); Codron, F. [UPMC/CNRS, Laboratoire de Meteorologie Dynamique, Paris (France); Takahashi, K. [Instituto Geofisico del Peru, Lima (Peru); Vrac, M. [IPSL/CNRS/CEA/UVSQ, Laboratoire des Sciences du Climat et de l' Environnement, Gif-sur-Yvette (France)

2011-04-15

The key aspect of the ocean circulation off Peru-Chile is the wind-driven upwelling of deep, cold, nutrient-rich waters that promote a rich marine ecosystem. It has been suggested that global warming may be associated with an intensification of upwelling-favorable winds. However, the lack of high-resolution long-term observations has been a limitation for a quantitative analysis of this process. In this study, we use a statistical downscaling method to assess the regional impact of climate change on the sea-surface wind over the Peru-Chile upwelling region as simulated by the global coupled general circulation model IPSL-CM4. Taking advantage of the high-resolution QuikSCAT wind product and of the NCEP reanalysis data, a statistical model based on multiple linear regressions is built for the daily mean meridional and zonal wind at 10 m for the period 2000-2008. The large-scale 10 m wind components and sea level pressure are used as regional circulation predictors. The skill of the downscaling method is assessed by comparing with the surface wind derived from the ERS satellite measurements, with in situ wind observations collected by ICOADS and through cross-validation. It is then applied to the outputs of the IPSL-CM4 model over stabilized periods of the pre-industrial, 2 x CO{sub 2} and 4 x CO{sub 2} IPCC climate scenarios. The results indicate that surface along-shore winds off central Chile (off central Peru) experience a significant intensification (weakening) during Austral winter (summer) in warmer climates. This is associated with a general decrease in intra-seasonal variability. (orig.)

Wind energy statistics 2012; Vindkraftsstatistik 2012

Energy Technology Data Exchange (ETDEWEB)

NONE

2013-04-15

The publication 'Wind Energy Statistics' is an annual publication. Since 2010, the reported statistics of installed power, number of plants and regional distribution, even semi-annually, and in tabular form on the Agency's website. The publication is produced in a new way this year, which will result in some data differ from previous publications. Due to the certificate system there is basically full statistics on wind energy in this publication which are presented in different styles. Here we present the regional distribution, ie. how the number of turbines and installed capacity is allocated to counties and municipalities. The electricity produced divided by county, where for reasons of confidentiality possible, are also reported. The wind power is becoming increasingly important in the Swedish energy system which provides an increased demand for statistics and other divisions than that presented in the official statistics. Therefore, this publication, which are not official statistics, has been developed.

Regionalization of Drought across South Korea Using Multivariate Methods

Directory of Open Access Journals (Sweden)

Muhammad Azam

2017-12-01

Full Text Available Topographic and hydro-climatic features of South Korea are highly heterogeneous and able to influence the drought phenomena in the region. The complex topographical and hydro-climatic features of South Korea need a statistically accurate method to find homogeneous regions. Regionalization of drought in a bivariate framework has scarcely been applied in South Korea before. Hierarchical Classification on Principal Components (HCPC algorithm together with Principal Component Analysis (PCA method and cluster validation indices were investigated and used for the regionalization of drought across the South Korean region. Statistical homogeneity and discordancy of the region was tested on univariate and bivariate frameworks. HCPC indicate that South Korea should be divided into four regions which are closer to being homogeneous. Univariate and bivariate homogeneity and discordancy tests showed the significant difference in their results due to the inability of univariate homogeneity and discordancy measures to consider the joint behavior of duration and severity. Regionalization of drought for SPI time scale of 1, 3, 6, 12, and 24 months showed significant variation in discordancy and homogeneity of the region with the change in SPI time scale. The results of this study can be used as basic data required to establish a drought mitigation plan on regional scales.

Stimulating Sustainability in Multinational Companies: the Significance of Regional Headquarters

OpenAIRE

Andreas G. M. NACHBAGAUER

2016-01-01

Recently, regional headquarters have gained practical importance and theoretical attention. Traditionally considered a mere transmission facility to manage complex organisations, advanced approaches, however, locate regional headquarters in a field of tension between hierarchical integration and strategic independence. Given the growing concern for global responsibility, stimulating sustainability also and particularly addresses regional headquarters. This conceptual article combines the call...

Growing Significance of EU Institutions in Promotion of Inter-regional policies

Directory of Open Access Journals (Sweden)

Ella V. Ermakova

2014-01-01

Full Text Available The article explores the variety of tools and vehicles applied within the EU to expand the prerogative of the regions of the EU member states. The author uses as an example the inter-regional policies in Belgium in respect of the Flemish Region and the Walloon Region. The author analyzes the mechanisms of promotion of external regional relations in Belgium as a means of addressing different problems both on national and all-European level, supporting the arguments and conclusions by examples of relevant EU initiatives. The article details the activities of the EU Regional Committee (RC, the EU advisory body with the powers of political initiative, upholding the principle ofsubsidarity in the implementation of the EU member states' regional policies. The involvement of the Flemish Region and the Walloon Region in the activities of EU RC is described and summarized. As a case study, the article deals with Belgium's rotating six months presidency in the EUin 2010 when the country, which was going through a severe political crisis with no federal government in place, was represented by the two regions. The special focus of the article is on the strategic EU program "Europe2020" and its implementation by the regions of Belgium. There is an account of the initiatives undertaken by the Flemish Region and the Walloon Region within the framework of this program outlining the interaction of the two regions. The author provides a comprehensive analysis of the involvement of the Flemish Region and the Walloon Region with various EU institutions describing how each party achieves the promotion of its regional interests. Within this context, it is a noteworthy development that the Flemish Region is participating in the international program "Pact 2020" on energy all by its own. The article features quotations by Flemish and Walloon political figures which serve as an illustration of the prevailing attitudes in the Belgian society to the process of

Statistically significant dependence of the Xaa-Pro peptide bond conformation on secondary structure and amino acid sequence

Directory of Open Access Journals (Sweden)

Leitner Dietmar

2005-04-01

Full Text Available Abstract Background A reliable prediction of the Xaa-Pro peptide bond conformation would be a useful tool for many protein structure calculation methods. We have analyzed the Protein Data Bank and show that the combined use of sequential and structural information has a predictive value for the assessment of the cis versus trans peptide bond conformation of Xaa-Pro within proteins. For the analysis of the data sets different statistical methods such as the calculation of the Chou-Fasman parameters and occurrence matrices were used. Furthermore we analyzed the relationship between the relative solvent accessibility and the relative occurrence of prolines in the cis and in the trans conformation. Results One of the main results of the statistical investigations is the ranking of the secondary structure and sequence information with respect to the prediction of the Xaa-Pro peptide bond conformation. We observed a significant impact of secondary structure information on the occurrence of the Xaa-Pro peptide bond conformation, while the sequence information of amino acids neighboring proline is of little predictive value for the conformation of this bond. Conclusion In this work, we present an extensive analysis of the occurrence of the cis and trans proline conformation in proteins. Based on the data set, we derived patterns and rules for a possible prediction of the proline conformation. Upon adoption of the Chou-Fasman parameters, we are able to derive statistically relevant correlations between the secondary structure of amino acid fragments and the Xaa-Pro peptide bond conformation.

CONFIDENCE LEVELS AND/VS. STATISTICAL HYPOTHESIS TESTING IN STATISTICAL ANALYSIS. CASE STUDY

Directory of Open Access Journals (Sweden)

ILEANA BRUDIU

2009-05-01

Full Text Available Estimated parameters with confidence intervals and testing statistical assumptions used in statistical analysis to obtain conclusions on research from a sample extracted from the population. Paper to the case study presented aims to highlight the importance of volume of sample taken in the study and how this reflects on the results obtained when using confidence intervals and testing for pregnant. If statistical testing hypotheses not only give an answer "yes" or "no" to some questions of statistical estimation using statistical confidence intervals provides more information than a test statistic, show high degree of uncertainty arising from small samples and findings build in the "marginally significant" or "almost significant (p very close to 0.05.

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

Science.gov (United States)

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

Significant Differences in Physicochemical Properties of Human Immunoglobulin Kappa and Lambda CDR3 Regions.

Science.gov (United States)

Townsend, Catherine L; Laffy, Julie M J; Wu, Yu-Chang Bryan; Silva O'Hare, Joselli; Martin, Victoria; Kipling, David; Fraternali, Franca; Dunn-Walters, Deborah K

2016-01-01

Antibody variable regions are composed of a heavy and a light chain, and in humans, there are two light chain isotypes: kappa and lambda. Despite their importance in receptor editing, the light chain is often overlooked in the antibody literature, with the focus being on the heavy chain complementarity-determining region (CDR)-H3 region. In this paper, we set out to investigate the physicochemical and structural differences between human kappa and lambda light chain CDR regions. We constructed a dataset containing over 29,000 light chain variable region sequences from IgM-transcribing, newly formed B cells isolated from human bone marrow and peripheral blood. We also used a published human naïve dataset to investigate the CDR-H3 properties of heavy chains paired with kappa and lambda light chains and probed the Protein Data Bank to investigate the structural differences between kappa and lambda antibody CDR regions. We found that kappa and lambda light chains have very different CDR physicochemical and structural properties, whereas the heavy chains with which they are paired do not differ significantly. We also observed that the mean CDR3 N nucleotide addition in the kappa, lambda, and heavy chain gene rearrangements are correlated within donors but can differ between donors. This indicates that terminal deoxynucleotidyl transferase may work with differing efficiencies between different people but the same efficiency in the different classes of immunoglobulin chain within one person. We have observed large differences in the physicochemical and structural properties of kappa and lambda light chain CDR regions. This may reflect different roles in the humoral immune response.

Solutions for Determining the Significance Region Using the Johnson-Neyman Type Procedure in Generalized Linear (Mixed) Models

Science.gov (United States)

Lazar, Ann A.; Zerbe, Gary O.

2011-01-01

Researchers often compare the relationship between an outcome and covariate for two or more groups by evaluating whether the fitted regression curves differ significantly. When they do, researchers need to determine the "significance region," or the values of the covariate where the curves significantly differ. In analysis of covariance (ANCOVA),…

Clinical significance of SNP (rs2596542 in histocompatibility complex class I-related gene A promoter region among hepatitis C virus related hepatocellular carcinoma cases

Directory of Open Access Journals (Sweden)

Amal A. Mohamed

2017-07-01

Full Text Available The major histocompatibility complex class I-related gene A (MICA is an antigen induced by stress and performs an integral role in immune responses as an anti-infectious and antitumor agent. This work was designed to investigate whether (SNP rs2596542C/T in MICA promoter region is predictive of liver cirrhosis (LC and hepatocellular carcinoma (HCC or not. Forty-seven healthy controls and 94 HCV-infected patients, subdivided into 47 LC and 47 HCC subjects were enrolled in this study. SNP association was studied using real time PCR and soluble serum MICA concentration was measured using ELISA. Results showed that heterozygous genotype rs2596542CT was significantly (P = 0.022 distributed between HCC and LC related CHC patients. The sMICA was significantly higher (P = 0.0001 among HCC and LC. No significant association (P = 0.56 between rs2596542CT genotypes and sMICA levels was observed. Studying SNP rs2596542C/T association with HCC and LC susceptibility revealed that statistical significant differences (P = 0.013, P = 0.027 were only observed between SNP rs2596542C/T and each of HCC and LC, respectively, versus healthy controls, indicating that the rs2596542C/T genetic variation is not a significant contributor to HCC development in LC patients. Moreover, the T allele was considered a risk factor for HCC and LC vulnerability in HCV patients (OR = 1.93 and 2.1, respectively, while the C allele contributes to decreasing HCC risk. Therefore, SNP (rs2596542C/T in MICA promoter region and sMICA levels might be potential useful markers in the assessment of liver disease progression to LC and HCC.

Improvement of Measurement and Evaluation of Regional Authorities Activity: Model and Statistical Approach

Directory of Open Access Journals (Sweden)

Petrova Elena Аleksandrovna

2014-11-01

Full Text Available Formation of strategy of long-term social and economic development is a basis for effective functioning of executive authorities and the assessment of its efficiency in general. Modern theories of assessment of public administration productivity are guided by the process approach when it is expedient to carry out the formation of business processes of regional executive authorities according to strategic indicators of territorial development. In this regard, there is a problem of modeling of interrelation of indicators of social and economic development of the region and quantitative indices of results of business processes of executive authorities. At the first stage of modeling, two main directions of strategic development, namely innovative and investment activity of regional economic systems are considered. In this regard, the work presents the results of modeling the interrelation between the indicators of regional social and economic development and innovative and investment activity. Therefore, for carrying out the analysis, the social and economic system of the region is presented in space of the main indicators of social and economic development of the territory and indicators of innovative and investment activity. The analysis is made on values of the indicators calculated for regions of the Russian Federation during 2000, 2005, 2008, 2010 and 2011. It was revealed that strategic indicators of innovative and investment activity have the most significant impact on key signs of social and economic development.

Wind energy statistics 2011; Vindkraftsstatistik 2011

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-11-01

Wind energy statistics 2011 is the fifth publication in the annual series. The report's focus is on regional distribution, i e the number of plants and installed capacity allocated to counties and municipalities. The publication also reports a division between sea- and land-based plants and the size of wind farms in Sweden in terms of installed capacity. The publication is published in spring in report form and since 2010 statistics on number of plants, installed capacity, and regional distribution semi-annually are also presented on the Swedish Energy Agency's website. The statistics relating to installed capacity, number of wind farms and location in this publication is taken from the electricity certificate system, introduced in May 2003. Thanks to the electricity certificate system there is in principle comprehensive statistics of wind energy which in this publication is presented in different intersections. Statistics related to electricity production is taken from the Swedish Kraftnaets [Swedish national grid's] registry Cesar.

The problem of low variance voxels in statistical parametric mapping; a new hat avoids a 'haircut'.

Science.gov (United States)

Ridgway, Gerard R; Litvak, Vladimir; Flandin, Guillaume; Friston, Karl J; Penny, Will D

2012-02-01

Statistical parametric mapping (SPM) locates significant clusters based on a ratio of signal to noise (a 'contrast' of the parameters divided by its standard error) meaning that very low noise regions, for example outside the brain, can attain artefactually high statistical values. Similarly, the commonly applied preprocessing step of Gaussian spatial smoothing can shift the peak statistical significance away from the peak of the contrast and towards regions of lower variance. These problems have previously been identified in positron emission tomography (PET) (Reimold et al., 2006) and voxel-based morphometry (VBM) (Acosta-Cabronero et al., 2008), but can also appear in functional magnetic resonance imaging (fMRI) studies. Additionally, for source-reconstructed magneto- and electro-encephalography (M/EEG), the problems are particularly severe because sparsity-favouring priors constrain meaningfully large signal and variance to a small set of compactly supported regions within the brain. (Acosta-Cabronero et al., 2008) suggested adding noise to background voxels (the 'haircut'), effectively increasing their noise variance, but at the cost of contaminating neighbouring regions with the added noise once smoothed. Following theory and simulations, we propose to modify--directly and solely--the noise variance estimate, and investigate this solution on real imaging data from a range of modalities. Copyright © 2011 Elsevier Inc. All rights reserved.

Dynamics of EEG functional connectivity during statistical learning.

Science.gov (United States)

Tóth, Brigitta; Janacsek, Karolina; Takács, Ádám; Kóbor, Andrea; Zavecz, Zsófia; Nemeth, Dezso

2017-10-01

Statistical learning is a fundamental mechanism of the brain, which extracts and represents regularities of our environment. Statistical learning is crucial in predictive processing, and in the acquisition of perceptual, motor, cognitive, and social skills. Although previous studies have revealed competitive neurocognitive processes underlying statistical learning, the neural communication of the related brain regions (functional connectivity, FC) has not yet been investigated. The present study aimed to fill this gap by investigating FC networks that promote statistical learning in humans. Young adults (N=28) performed a statistical learning task while 128-channels EEG was acquired. The task involved probabilistic sequences, which enabled to measure incidental/implicit learning of conditional probabilities. Phase synchronization in seven frequency bands was used to quantify FC between cortical regions during the first, second, and third periods of the learning task, respectively. Here we show that statistical learning is negatively correlated with FC of the anterior brain regions in slow (theta) and fast (beta) oscillations. These negative correlations increased as the learning progressed. Our findings provide evidence that dynamic antagonist brain networks serve a hallmark of statistical learning. Copyright © 2017 Elsevier Inc. All rights reserved.

A comparison of dynamical and statistical downscaling methods for regional wave climate projections along French coastlines.

Science.gov (United States)

Laugel, Amélie; Menendez, Melisa; Benoit, Michel; Mattarolo, Giovanni; Mendez, Fernando

2013-04-01

Wave climate forecasting is a major issue for numerous marine and coastal related activities, such as offshore industries, flooding risks assessment and wave energy resource evaluation, among others. Generally, there are two main ways to predict the impacts of the climate change on the wave climate at regional scale: the dynamical and the statistical downscaling of GCM (Global Climate Model). In this study, both methods have been applied on the French coast (Atlantic , English Channel and North Sea shoreline) under three climate change scenarios (A1B, A2, B1) simulated with the GCM ARPEGE-CLIMAT, from Météo-France (AR4, IPCC). The aim of the work is to characterise the wave climatology of the 21st century and compare the statistical and dynamical methods pointing out advantages and disadvantages of each approach. The statistical downscaling method proposed by the Environmental Hydraulics Institute of Cantabria (Spain) has been applied (Menendez et al., 2011). At a particular location, the sea-state climate (Predictand Y) is defined as a function, Y=f(X), of several atmospheric circulation patterns (Predictor X). Assuming these climate associations between predictor and predictand are stationary, the statistical approach has been used to project the future wave conditions with reference to the GCM. The statistical relations between predictor and predictand have been established over 31 years, from 1979 to 2009. The predictor is built as the 3-days-averaged squared sea level pressure gradient from the hourly CFSR database (Climate Forecast System Reanalysis, http://cfs.ncep.noaa.gov/cfsr/). The predictand has been extracted from the 31-years hindcast sea-state database ANEMOC-2 performed with the 3G spectral wave model TOMAWAC (Benoit et al., 1996), developed at EDF R&D LNHE and Saint-Venant Laboratory for Hydraulics and forced by the CFSR 10m wind field. Significant wave height, peak period and mean wave direction have been extracted with an hourly-resolution at

Computer-assisted segmentation of CT images by statistical region merging for the production of voxel models of anatomy for CT dosimetry

Czech Academy of Sciences Publication Activity Database

Caon, M.; Sedlář, Jiří; Bajger, M.; Lee, G.

2014-01-01

Roč. 37, č. 2 (2014), s. 393-403 ISSN 0158-9938 Institutional support: RVO:67985556 Keywords : Voxel model * Image segmentation * Statistical region merging * CT dosimetry Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.882, year: 2014 http://library.utia.cas.cz/separaty/2014/ZOI/sedlar-0428537.pdf

Poverty determinants of acute respiratory infections among Mapuche indigenous peoples in Chile's Ninth Region of Araucania, using GIS and spatial statistics to identify health disparities.

Science.gov (United States)

Rojas, Flavio

2007-07-02

This research concerns Araucanía, often called the Ninth Region, the poorest region of Chile where inequalities are most extreme. Araucanía hasn't enjoyed the economic success Chile achieved when the country returned to democracy in 1990. The Ninth Region also has the largest ethnic Mapuche population, located in rural areas and attached to small agricultural properties. Written and oral histories of diseases have been the most frequently used methods to explore the links between an ancestral population's perception of health conditions and their deprived environments. With census data and hospital records, it is now possible to incorporate statistical data about the links between poverty and disease among ethnic communities and compare results with non-Mapuche population. Hospital discharge records from Health Services North N = 24,126 patients, year 2003, and 7 hospitals), Health Services South (N = 81,780 patients and 25 hospitals); CAS-2/Family records (N = 527,539 individuals, 439 neighborhoods, 32 Comunas). Given the over-dispersion of data and the clustered nature of observations, we used the global Moran's I and General G Gettis-Ord procedures to test spatial dependence. These tests confirmed the clusters of disease and the need to use spatial regression within a General Linear Mixed Model perspective. Health outcomes indicate significantly higher morbidity rates for the Mapuche compared to non-Mapuche in both age groups Mapuches than non-Mapuches for the entire Ninth Region and for all age groups. Mortality caused by respiratory infections is higher among Mapuches than non-Mapuches in all age-groups. A major finding is the link between poverty and respiratory infections. Poverty is significantly associated with respiratory infections in the population of Chile's Ninth Region. High deprivation areas are associated with poverty, and poverty is a predictor of respiratory infections. Mapuches are at higher risk of deaths caused by respiratory infections in

Multi-Site and Multi-Variables Statistical Downscaling Technique in the Monsoon Dominated Region of Pakistan

Science.gov (United States)

Khan, Firdos; Pilz, Jürgen

2016-04-01

South Asia is under the severe impacts of changing climate and global warming. The last two decades showed that climate change or global warming is happening and the first decade of 21st century is considered as the warmest decade over Pakistan ever in history where temperature reached 53 0C in 2010. Consequently, the spatio-temporal distribution and intensity of precipitation is badly effected and causes floods, cyclones and hurricanes in the region which further have impacts on agriculture, water, health etc. To cope with the situation, it is important to conduct impact assessment studies and take adaptation and mitigation remedies. For impact assessment studies, we need climate variables at higher resolution. Downscaling techniques are used to produce climate variables at higher resolution; these techniques are broadly divided into two types, statistical downscaling and dynamical downscaling. The target location of this study is the monsoon dominated region of Pakistan. One reason for choosing this area is because the contribution of monsoon rains in this area is more than 80 % of the total rainfall. This study evaluates a statistical downscaling technique which can be then used for downscaling climatic variables. Two statistical techniques i.e. quantile regression and copula modeling are combined in order to produce realistic results for climate variables in the area under-study. To reduce the dimension of input data and deal with multicollinearity problems, empirical orthogonal functions will be used. Advantages of this new method are: (1) it is more robust to outliers as compared to ordinary least squares estimates and other estimation methods based on central tendency and dispersion measures; (2) it preserves the dependence among variables and among sites and (3) it can be used to combine different types of distributions. This is important in our case because we are dealing with climatic variables having different distributions over different meteorological

Significant differences in physicochemical properties of human immunoglobulin kappa and lambda CDR3 regions

Directory of Open Access Journals (Sweden)

Catherine L Townsend

2016-09-01

Full Text Available Antibody variable regions are composed of a heavy and a light chain and in humans there are two light chain isotypes: kappa and lambda. Despite their importance in receptor editing, the light chain is often overlooked in the antibody literature, with the focus being on the heavy chain CDR-H3 region. In this paper, we set out to investigate the physicochemical and structural differences between human kappa and lambda light chain CDR regions. We constructed a dataset containing over 29,000 - light chain variable region sequences from IgM-transcribing, newly formed B cells isolated from human bone marrow and peripheral blood. We also used a published human naïve dataset to investigate the CDR-H3 properties of heavy chains paired with kappa and lambda light chains, and probed the Protein Data Bank (PDB to investigate the structural differences between kappa and lambda antibody CDR regions. We found that kappa and lambda light chains have very different CDR physicochemical and structural properties, whereas the heavy chains with which they are paired do not differ significantly. We also observed that the mean CDR3 N nucleotide addition in the kappa, lambda and heavy chain gene rearrangements are correlated within donors, but can differ between donors. This indicates that TdT may work with differing efficiencies between different people, but the same efficiency in the different classes of immunoglobulin chain within one person. We have observed large differences in the physicochemical and structural properties of kappa and lambda light chain CDR regions. This may reflect different roles in the humoral immune response.

Statistical analysis of mirror mode waves in sheath regions driven by interplanetary coronal mass ejection

Science.gov (United States)

Ala-Lahti, Matti M.; Kilpua, Emilia K. J.; Dimmock, Andrew P.; Osmane, Adnane; Pulkkinen, Tuija; Souček, Jan

2018-05-01

We present a comprehensive statistical analysis of mirror mode waves and the properties of their plasma surroundings in sheath regions driven by interplanetary coronal mass ejection (ICME). We have constructed a semi-automated method to identify mirror modes from the magnetic field data. We analyze 91 ICME sheath regions from January 1997 to April 2015 using data from the Wind spacecraft. The results imply that similarly to planetary magnetosheaths, mirror modes are also common structures in ICME sheaths. However, they occur almost exclusively as dip-like structures and in mirror stable plasma. We observe mirror modes throughout the sheath, from the bow shock to the ICME leading edge, but their amplitudes are largest closest to the shock. We also find that the shock strength (measured by Alfvén Mach number) is the most important parameter in controlling the occurrence of mirror modes. Our findings suggest that in ICME sheaths the dominant source of free energy for mirror mode generation is the shock compression. We also suggest that mirror modes that are found deeper in the sheath are remnants from earlier times of the sheath evolution, generated also in the vicinity of the shock.

STATISTICAL GROWTH MODELING OF LONGITUDINAL DT-MRI FOR REGIONAL CHARACTERIZATION OF EARLY BRAIN DEVELOPMENT.

Science.gov (United States)

Sadeghi, Neda; Prastawa, Marcel; Fletcher, P Thomas; Gilmore, John H; Lin, Weili; Gerig, Guido

2012-01-01

A population growth model that represents the growth trajectories of individual subjects is critical to study and understand neurodevelopment. This paper presents a framework for jointly estimating and modeling individual and population growth trajectories, and determining significant regional differences in growth pattern characteristics applied to longitudinal neuroimaging data. We use non-linear mixed effect modeling where temporal change is modeled by the Gompertz function. The Gompertz function uses intuitive parameters related to delay, rate of change, and expected asymptotic value; all descriptive measures which can answer clinical questions related to growth. Our proposed framework combines nonlinear modeling of individual trajectories, population analysis, and testing for regional differences. We apply this framework to the study of early maturation in white matter regions as measured with diffusion tensor imaging (DTI). Regional differences between anatomical regions of interest that are known to mature differently are analyzed and quantified. Experiments with image data from a large ongoing clinical study show that our framework provides descriptive, quantitative information on growth trajectories that can be directly interpreted by clinicians. To our knowledge, this is the first longitudinal analysis of growth functions to explain the trajectory of early brain maturation as it is represented in DTI.

The Significance of Regional Analysis in Applied Geography.

Science.gov (United States)

Sommers, Lawrence M.

Regional analysis is central to applied geographic research, contributing to better planning and policy development for a variety of societal problems facing the United States. The development of energy policy serves as an illustration of the capabilities of this type of analysis. The United States has had little success in formulating a national…

Comparison of different methods for assessment of left ventricular regional motility using the gated blood pool method

International Nuclear Information System (INIS)

Neumann, P.; Schicha, H.; Karsch, K.R.; Kreuzer, H.; Emrich, D.

1983-01-01

The following methods of evaluation were compared: qualitative analysis of cine mode; qualitative analysis of parametric scans obtained by Fourier analysis including the phase histogram; quantitative analysis of regional ejection fraction (EF). Regional wall motion abnormalities of high degree (akinesia, dyskinesia) were recognized by all three methods with a high sensitivity of 89.7-96.6% without statistically significant differences. The sensitivity for detecting hypokinetic segments was significantly lower (50.0-68.2%) without statistically significant differences between the three methods. Sensitivity for all kinds of wall motion abnormalities could be increased by combining the quantitative method of regional EF with the qualitative evaluation after Fourier analysis

Significance of Future Biogenic and Fire Emissions on Regional Aerosol Burden

Science.gov (United States)

Lim, A.; Tai, A. P. K.; Val Martin, M.

2017-12-01

Land-use and land cover changes have been found to substantially affect atmospheric aerosols and climate worldwide1,2, but the complex mechanisms and pathways involved in the interactions between terrestrial processes and aerosols are not well understood. Here we use a global coupled aerosol chemistry-climate-land model (CESM with CAM5 using Modal Aerosol Module 3 and CLM4.5 in Satellite Phenology mode) to investigate how aerosols respond to future climate and land-use changes, and in turn, affects cloud cover and other hydrometeorological variables in the long term. Time-sliced simulations are conducted for a base year (2000) as a base case; then three future projected scenarios for year 2050 driven by land-use and climate projections following the Representative Concentration Pathways RCP8.53 are conducted. The first scenario considers future projected biogenic emissions, allowing us to investigate the effect of increased plant activity and enhanced biogenic emissions due to future land-use and climate on aerosol burden. The second scenario considers future biomass burning emissions, allowing us to investigate the effect of increased biomass burning emissions due to future land-use and climate on aerosol burden. The third scenario combines the projected changes in the two emissions. We find that both biogenic and biomass burning emissions contribute significantly to local aerosol and cloud condensation nuclei (CCN) concentrations. The contribution from biogenic emissions to local aerosol burden is smaller in magnitude (10% to 20%), but the effects are ubiquitous in many places globally. Meanwhile, the contribution from biomass burning emissions can be much higher in magnitude (63%)4, but concentrated in heavily burned regions and occurs only during burning season. Effects of both emissions are not additive since a larger flux of emissions causes greater deposition. The resulting further impacts of land-use change on regional hydrometeorology are also explored

Patterns of regional development in Serbia: A multivariate statistical analysis

Directory of Open Access Journals (Sweden)

Čoček Ladislav

2010-01-01

Full Text Available The primary objective of this paper is to examine patterns of regional development in Serbia and to identify underlying geographical factors of these patterns. Principal component analysis is used to reveal the basic dimensions of regional differentiation. Its results are described in the context of findings from thematically similar research on Central European countries. An area's position in the national settlement system hierarchy has been identified as the strongest determinant of regional differentiation in Serbia. Other strong patterns seem to be connected with macro-geographical position. Success in economic development is most apparent in regions near the metropolitan area of Belgrade, and the general development level, along with a predisposition for agriculture, exhibits a strong north-south polarization. Specific attention is directed at demographic development, which is characterized by a west-east gradient. Central patterns of regional differentiation are similar to those uncovered in previous Central European research. Regional policy in Serbia should, therefore, try to learn from experience within this region to cope with processes and problems that are often quite similar. .

Statistical properties of turbulent transport and fluctuations in tokamak and stellarator devices

Energy Technology Data Exchange (ETDEWEB)

Hidalgo, C; Pedrosa, M A; Milligen, B Van; Sanchez, E; Balbin, R; Garcia-Cortes, I [Euratom-CIEMAT Association, Madrid (Spain); Bleuel, J; Giannone, L.; Niedermeyer, H [Euratom-IPP Association, Garching (Germany)

1997-05-01

The statistical properties of fluctuations and turbulent transport have been studied in the plasma boundary region of stellarator (TJ-IU, W7-AS) and tokamak (TJ-I) devices. The local flux probability distribution function shows the bursty character of the flux and presents a systematic change as a function of the radial location. There exist large amplitude transport bursts that account for a significant part of the total flux. There is a strong similarity between the statistical properties of the turbulent fluxes in different devices. The value of the radial coherence associated with fluctuations and turbulent transport is strongly intermittent. This result emphasizes the importance of measurements with time resolution in understanding the interplay between the edge and the core regions in the plasma. For measurements in the plasma edge region of the TJ-IU torsatron, the turbulent flux does not, in general, show a larger radial coherence than the one associated with the fluctuations. (author). 14 refs, 6 figs.

Estimating annual high-flow statistics and monthly and seasonal low-flow statistics for ungaged sites on streams in Alaska and conterminous basins in Canada

Science.gov (United States)

Wiley, Jeffrey B.; Curran, Janet H.

2003-01-01

Methods for estimating daily mean flow-duration statistics for seven regions in Alaska and low-flow frequencies for one region, southeastern Alaska, were developed from daily mean discharges for streamflow-gaging stations in Alaska and conterminous basins in Canada. The 15-, 10-, 9-, 8-, 7-, 6-, 5-, 4-, 3-, 2-, and 1-percent duration flows were computed for the October-through-September water year for 222 stations in Alaska and conterminous basins in Canada. The 98-, 95-, 90-, 85-, 80-, 70-, 60-, and 50-percent duration flows were computed for the individual months of July, August, and September for 226 stations in Alaska and conterminous basins in Canada. The 98-, 95-, 90-, 85-, 80-, 70-, 60-, and 50-percent duration flows were computed for the season July-through-September for 65 stations in southeastern Alaska. The 7-day, 10-year and 7-day, 2-year low-flow frequencies for the season July-through-September were computed for 65 stations for most of southeastern Alaska. Low-flow analyses were limited to particular months or seasons in order to omit winter low flows, when ice effects reduce the quality of the records and validity of statistical assumptions. Regression equations for estimating the selected high-flow and low-flow statistics for the selected months and seasons for ungaged sites were developed from an ordinary-least-squares regression model using basin characteristics as independent variables. Drainage area and precipitation were significant explanatory variables for high flows, and drainage area, precipitation, mean basin elevation, and area of glaciers were significant explanatory variables for low flows. The estimating equations can be used at ungaged sites in Alaska and conterminous basins in Canada where streamflow regulation, streamflow diversion, urbanization, and natural damming and releasing of water do not affect the streamflow data for the given month or season. Standard errors of estimate ranged from 15 to 56 percent for high-duration flow

Estimating Selected Streamflow Statistics Representative of 1930-2002 in West Virginia

Science.gov (United States)

Wiley, Jeffrey B.

2008-01-01

Regional equations and procedures were developed for estimating 1-, 3-, 7-, 14-, and 30-day 2-year; 1-, 3-, 7-, 14-, and 30-day 5-year; and 1-, 3-, 7-, 14-, and 30-day 10-year hydrologically based low-flow frequency values for unregulated streams in West Virginia. Regional equations and procedures also were developed for estimating the 1-day, 3-year and 4-day, 3-year biologically based low-flow frequency values; the U.S. Environmental Protection Agency harmonic-mean flows; and the 10-, 25-, 50-, 75-, and 90-percent flow-duration values. Regional equations were developed using ordinary least-squares regression using statistics from 117 U.S. Geological Survey continuous streamflow-gaging stations as dependent variables and basin characteristics as independent variables. Equations for three regions in West Virginia - North, South-Central, and Eastern Panhandle - were determined. Drainage area, precipitation, and longitude of the basin centroid are significant independent variables in one or more of the equations. Estimating procedures are presented for determining statistics at a gaging station, a partial-record station, and an ungaged location. Examples of some estimating procedures are presented.

Statistical magnetohydrodynamics and reversed-field-pinch quiescence

International Nuclear Information System (INIS)

Turner, L.

1982-01-01

A statistical model of a bounded, incompressible, cylindrical magnetofluid is presented. This model predicts the presence of magnetic fluctuations about a cylindrically-symmetric, Bessel-function-model, mean magnetic field, which satisfies del x = μ . As theta → 1.56, the model predicts that the significant region of the fluctuation spectrum narrows down to a single (coherent) m = 1 mode. An analogy between the Debye length of an electrostatic plasma and μ -1 suggests the physical validity o the model's prediction of when /r - r'/ greater than or equal to μ -1

AUTOMATIC LUNG NODULE DETECTION BASED ON STATISTICAL REGION MERGING AND SUPPORT VECTOR MACHINES

Directory of Open Access Journals (Sweden)

Elaheh Aghabalaei Khordehchi

2017-06-01

Full Text Available Lung cancer is one of the most common diseases in the world that can be treated if the lung nodules are detected in their early stages of growth. This study develops a new framework for computer-aided detection of pulmonary nodules thorough a fully-automatic analysis of Computed Tomography (CT images. In the present work, the multi-layer CT data is fed into a pre-processing step that exploits an adaptive diffusion-based smoothing algorithm in which the parameters are automatically tuned using an adaptation technique. After multiple levels of morphological filtering, the Regions of Interest (ROIs are extracted from the smoothed images. The Statistical Region Merging (SRM algorithm is applied to the ROIs in order to segment each layer of the CT data. Extracted segments in consecutive layers are then analyzed in such a way that if they intersect at more than a predefined number of pixels, they are labeled with a similar index. The boundaries of the segments in adjacent layers which have the same indices are then connected together to form three-dimensional objects as the nodule candidates. After extracting four spectral, one morphological, and one textural feature from all candidates, they are finally classified into nodules and non-nodules using the Support Vector Machine (SVM classifier. The proposed framework has been applied to two sets of lung CT images and its performance has been compared to that of nine other competing state-of-the-art methods. The considerable efficiency of the proposed approach has been proved quantitatively and validated by clinical experts as well.

Network similarity and statistical analysis of earthquake seismic data

OpenAIRE

Deyasi, Krishanu; Chakraborty, Abhijit; Banerjee, Anirban

2016-01-01

We study the structural similarity of earthquake networks constructed from seismic catalogs of different geographical regions. A hierarchical clustering of underlying undirected earthquake networks is shown using Jensen-Shannon divergence in graph spectra. The directed nature of links indicates that each earthquake network is strongly connected, which motivates us to study the directed version statistically. Our statistical analysis of each earthquake region identifies the hub regions. We cal...

Statistical sampling approaches for soil monitoring

NARCIS (Netherlands)

Brus, D.J.

2014-01-01

This paper describes three statistical sampling approaches for regional soil monitoring, a design-based, a model-based and a hybrid approach. In the model-based approach a space-time model is exploited to predict global statistical parameters of interest such as the space-time mean. In the hybrid

Methods for estimating flow-duration and annual mean-flow statistics for ungaged streams in Oklahoma

Science.gov (United States)

Esralew, Rachel A.; Smith, S. Jerrod

2010-01-01

-basin characteristics by using a k-means cluster analysis. Three regions were identified for Oklahoma on the basis of the clustering of gaging stations and a manual delineation of distinguishable hydrologic and geologic boundaries: Region 1 (western Oklahoma excluding the Oklahoma and Texas Panhandles), Region 2 (north- and south-central Oklahoma), and Region 3 (eastern and central Oklahoma). A total of 228 regression equations (225 flow-duration regressions and three annual mean-flow regressions) were developed using ordinary least-squares and left-censored (Tobit) multiple-regression techniques. These equations can be used to estimate 75 flow-duration statistics and annual mean-flow for ungaged streams in the three regions. Drainage-basin characteristics that were statistically significant independent variables in the regression analyses were (1) contributing drainage area; (2) station elevation; (3) mean drainage-basin elevation; (4) channel slope; (5) percentage of forested canopy; (6) mean drainage-basin hillslope; (7) soil permeability; and (8) mean annual, seasonal, and monthly precipitation. The accuracy of flow-duration regression equations generally decreased from high-flow exceedance (low-exceedance probability) to low-flow exceedance (high-exceedance probability) . This decrease may have happened because a greater uncertainty exists for low-flow estimates and low-flow is largely affected by localized geology that was not quantified by the drainage-basin characteristics selected. The standard errors of estimate of regression equations for Region 1 (western Oklahoma) were substantially larger than those standard errors for other regions, especially for low-flow exceedances. These errors may be a result of greater variability in low flow because of increased irrigation activities in this region. Regression equations may not be reliable for sites where the drainage-basin characteristics are outside the range of values of independent vari

Statistical significance approximation in local trend analysis of high-throughput time-series data using the theory of Markov chains.

Science.gov (United States)

Xia, Li C; Ai, Dongmei; Cram, Jacob A; Liang, Xiaoyi; Fuhrman, Jed A; Sun, Fengzhu

2015-09-21

Local trend (i.e. shape) analysis of time series data reveals co-changing patterns in dynamics of biological systems. However, slow permutation procedures to evaluate the statistical significance of local trend scores have limited its applications to high-throughput time series data analysis, e.g., data from the next generation sequencing technology based studies. By extending the theories for the tail probability of the range of sum of Markovian random variables, we propose formulae for approximating the statistical significance of local trend scores. Using simulations and real data, we show that the approximate p-value is close to that obtained using a large number of permutations (starting at time points >20 with no delay and >30 with delay of at most three time steps) in that the non-zero decimals of the p-values obtained by the approximation and the permutations are mostly the same when the approximate p-value is less than 0.05. In addition, the approximate p-value is slightly larger than that based on permutations making hypothesis testing based on the approximate p-value conservative. The approximation enables efficient calculation of p-values for pairwise local trend analysis, making large scale all-versus-all comparisons possible. We also propose a hybrid approach by integrating the approximation and permutations to obtain accurate p-values for significantly associated pairs. We further demonstrate its use with the analysis of the Polymouth Marine Laboratory (PML) microbial community time series from high-throughput sequencing data and found interesting organism co-occurrence dynamic patterns. The software tool is integrated into the eLSA software package that now provides accelerated local trend and similarity analysis pipelines for time series data. The package is freely available from the eLSA website: http://bitbucket.org/charade/elsa.

Test the Overall Significance of p-values by Using Joint Tail Probability of Ordered p-values as Test Statistic

OpenAIRE

Fang, Yongxiang; Wit, Ernst

2008-01-01

Fisher’s combined probability test is the most commonly used method to test the overall significance of a set independent p-values. However, it is very obviously that Fisher’s statistic is more sensitive to smaller p-values than to larger p-value and a small p-value may overrule the other p-values and decide the test result. This is, in some cases, viewed as a flaw. In order to overcome this flaw and improve the power of the test, the joint tail probability of a set p-values is proposed as a ...

Infodemiological data of high-school drop-out related web searches in Canada correlating with real-world statistical data in the period 2004–2012

Directory of Open Access Journals (Sweden)

Anna Siri

2016-12-01

Examining the data broken down by gender, the correlations were higher and statistically significant in males than in females. GT-based data for drop-out resulted best modeled by an ARMA(1,0 model. Considering the cross correlation of Canadian regions, all of them resulted statistically significant at lag 0, apart from for New Brunswick, Newfoundland and Labrador and the Prince Edward island. A number or cross-correlations resulted statistically significant also at lag −1 (namely, Alberta, Manitoba, New Brunswick and Saskatchewan.

Poverty determinants of acute respiratory infections among Mapuche indigenous peoples in Chile's Ninth Region of Araucania, using GIS and spatial statistics to identify health disparities

Directory of Open Access Journals (Sweden)

Rojas Flavio

2007-07-01

Full Text Available Abstract Background This research concerns Araucanía, often called the Ninth Region, the poorest region of Chile where inequalities are most extreme. Araucanía hasn't enjoyed the economic success Chile achieved when the country returned to democracy in 1990. The Ninth Region also has the largest ethnic Mapuche population, located in rural areas and attached to small agricultural properties. Written and oral histories of diseases have been the most frequently used methods to explore the links between an ancestral population's perception of health conditions and their deprived environments. With census data and hospital records, it is now possible to incorporate statistical data about the links between poverty and disease among ethnic communities and compare results with non-Mapuche population. Data sources Hospital discharge records from Health Services North N = 24,126 patients, year 2003, and 7 hospitals, Health Services South (N = 81,780 patients and 25 hospitals; CAS-2/Family records (N = 527,539 individuals, 439 neighborhoods, 32 Comunas. Methods Given the over-dispersion of data and the clustered nature of observations, we used the global Moran's I and General G Gettis-Ord procedures to test spatial dependence. These tests confirmed the clusters of disease and the need to use spatial regression within a General Linear Mixed Model perspective. Results Health outcomes indicate significantly higher morbidity rates for the Mapuche compared to non-Mapuche in both age groups Mapuches than non-Mapuches for the entire Ninth Region and for all age groups. Mortality caused by respiratory infections is higher among Mapuches than non-Mapuches in all age-groups. A major finding is the link between poverty and respiratory infections. Conclusion Poverty is significantly associated with respiratory infections in the population of Chile's Ninth Region. High deprivation areas are associated with poverty, and poverty is a predictor of respiratory infections

Timber resource statistics for Oregon.

Science.gov (United States)

Sally Campbell; Paul Dunham; David. Azuma

2004-01-01

This report is a summary of timber resource statistics for all ownerships in Oregon. Data were collected as part of several statewide multiresource inventories, including those conducted by the Pacific Northwest Region (Region 6) on National Forest System lands in Oregon, by the Bureau of Land Management (BLM) on BLM lands in western Oregon, and by the Pacific...

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

Science.gov (United States)

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis

Architecture of a spatial data service system for statistical analysis and visualization of regional climate changes

Science.gov (United States)

Titov, A. G.; Okladnikov, I. G.; Gordov, E. P.

2017-11-01

The use of large geospatial datasets in climate change studies requires the development of a set of Spatial Data Infrastructure (SDI) elements, including geoprocessing and cartographical visualization web services. This paper presents the architecture of a geospatial OGC web service system as an integral part of a virtual research environment (VRE) general architecture for statistical processing and visualization of meteorological and climatic data. The architecture is a set of interconnected standalone SDI nodes with corresponding data storage systems. Each node runs a specialized software, such as a geoportal, cartographical web services (WMS/WFS), a metadata catalog, and a MySQL database of technical metadata describing geospatial datasets available for the node. It also contains geospatial data processing services (WPS) based on a modular computing backend realizing statistical processing functionality and, thus, providing analysis of large datasets with the results of visualization and export into files of standard formats (XML, binary, etc.). Some cartographical web services have been developed in a system’s prototype to provide capabilities to work with raster and vector geospatial data based on OGC web services. The distributed architecture presented allows easy addition of new nodes, computing and data storage systems, and provides a solid computational infrastructure for regional climate change studies based on modern Web and GIS technologies.

Towards better error statistics for atmospheric inversions of methane surface fluxes

Directory of Open Access Journals (Sweden)

A. Berchet

2013-07-01

Full Text Available We adapt general statistical methods to estimate the optimal error covariance matrices in a regional inversion system inferring methane surface emissions from atmospheric concentrations. Using a minimal set of physical hypotheses on the patterns of errors, we compute a guess of the error statistics that is optimal in regard to objective statistical criteria for the specific inversion system. With this very general approach applied to a real-data case, we recover sources of errors in the observations and in the prior state of the system that are consistent with expert knowledge while inferred from objective criteria and with affordable computation costs. By not assuming any specific error patterns, our results depict the variability and the inter-dependency of errors induced by complex factors such as the misrepresentation of the observations in the transport model or the inability of the model to reproduce well the situations of steep gradients of concentrations. Situations with probable significant biases (e.g., during the night when vertical mixing is ill-represented by the transport model can also be diagnosed by our methods in order to point at necessary improvement in a model. By additionally analysing the sensitivity of the inversion to each observation, guidelines to enhance data selection in regional inversions are also proposed. We applied our method to a recent significant accidental methane release from an offshore platform in the North Sea and found methane fluxes of the same magnitude than what was officially declared.

Estimation of selected seasonal streamflow statistics representative of 1930-2002 in West Virginia

Science.gov (United States)

Wiley, Jeffrey B.; Atkins, John T.

2010-01-01

Regional equations and procedures were developed for estimating seasonal 1-day 10-year, 7-day 10-year, and 30-day 5-year hydrologically based low-flow frequency values for unregulated streams in West Virginia. Regional equations and procedures also were developed for estimating the seasonal U.S. Environmental Protection Agency harmonic-mean flows and the 50-percent flow-duration values. The seasons were defined as winter (January 1-March 31), spring (April 1-June 30), summer (July 1-September 30), and fall (October 1-December 31). Regional equations were developed using ordinary least squares regression using statistics from 117 U.S. Geological Survey continuous streamgage stations as dependent variables and basin characteristics as independent variables. Equations for three regions in West Virginia-North, South-Central, and Eastern Panhandle Regions-were determined. Drainage area, average annual precipitation, and longitude of the basin centroid are significant independent variables in one or more of the equations. The average standard error of estimates for the equations ranged from 12.6 to 299 percent. Procedures developed to estimate the selected seasonal streamflow statistics in this study are applicable only to rural, unregulated streams within the boundaries of West Virginia that have independent variables within the limits of the stations used to develop the regional equations: drainage area from 16.3 to 1,516 square miles in the North Region, from 2.78 to 1,619 square miles in the South-Central Region, and from 8.83 to 3,041 square miles in the Eastern Panhandle Region; average annual precipitation from 42.3 to 61.4 inches in the South-Central Region and from 39.8 to 52.9 inches in the Eastern Panhandle Region; and longitude of the basin centroid from 79.618 to 82.023 decimal degrees in the North Region. All estimates of seasonal streamflow statistics are representative of the period from the 1930 to the 2002 climatic year.

Application of statistical and dynamics models for snow avalanche hazard assessment in mountain regions of Russia

Science.gov (United States)

Turchaninova, A.

2012-04-01

The estimation of extreme avalanche runout distances, flow velocities, impact pressures and volumes is an essential part of snow engineering in mountain regions of Russia. It implies the avalanche hazard assessment and mapping. Russian guidelines accept the application of different avalanche models as well as approaches for the estimation of model input parameters. Consequently different teams of engineers in Russia apply various dynamics and statistical models for engineering practice. However it gives more freedom to avalanche practitioners and experts but causes lots of uncertainties in case of serious limitations of avalanche models. We discuss these problems by presenting the application results of different well known and widely used statistical (developed in Russia) and avalanche dynamics models for several avalanche test sites in the Khibini Mountains (The Kola Peninsula) and the Caucasus. The most accurate and well-documented data from different powder and wet, big rare and small frequent snow avalanche events is collected from 1960th till today in the Khibini Mountains by the Avalanche Safety Center of "Apatit". This data was digitized and is available for use and analysis. Then the detailed digital avalanche database (GIS) was created for the first time. It contains contours of observed avalanches (ESRI shapes, more than 50 years of observations), DEMs, remote sensing data, description of snow pits, photos etc. Thus, the Russian avalanche data is a unique source of information for understanding of an avalanche flow rheology and the future development and calibration of the avalanche dynamics models. GIS database was used to analyze model input parameters and to calibrate and verify avalanche models. Regarding extreme dynamic parameters the outputs using different models can differ significantly. This is unacceptable for the engineering purposes in case of the absence of the well-defined guidelines in Russia. The frequency curves for the runout distance

After statistics reform : Should we still teach significance testing?

NARCIS (Netherlands)

A. Hak (Tony)

2014-01-01

textabstractIn the longer term null hypothesis significance testing (NHST) will disappear because p- values are not informative and not replicable. Should we continue to teach in the future the procedures of then abolished routines (i.e., NHST)? Three arguments are discussed for not teaching NHST in

The economic and social significance of RCA regional co-operative projects

International Nuclear Information System (INIS)

Fowler, E.E.

1979-01-01

The regional Co-operative Agreement for Research, Development and Training Related to Nuclear Science and Technology (RCA) is an established and valuable instrument between the International Atomic Energy Agency (IAEA) and Member States in South Asia, Southeast Asia and the Pacific or Far East for assisting in the transfer of modern technology to areas having economic and social importance to the region. The purpose of this review is to identify on-going or planned work which is designed to help achieve this goal. Currently approved RCA Regional Co-operative Research Projects are listed

An application of an optimal statistic for characterizing relative orientations

Science.gov (United States)

Jow, Dylan L.; Hill, Ryley; Scott, Douglas; Soler, J. D.; Martin, P. G.; Devlin, M. J.; Fissel, L. M.; Poidevin, F.

2018-02-01

We present the projected Rayleigh statistic (PRS), a modification of the classic Rayleigh statistic, as a test for non-uniform relative orientation between two pseudo-vector fields. In the application here, this gives an effective way of investigating whether polarization pseudo-vectors (spin-2 quantities) are preferentially parallel or perpendicular to filaments in the interstellar medium. For example, there are other potential applications in astrophysics, e.g. when comparing small-scale orientations with larger scale shear patterns. We compare the efficiency of the PRS against histogram binning methods that have previously been used for characterizing the relative orientations of gas column density structures with the magnetic field projected on the plane of the sky. We examine data for the Vela C molecular cloud, where the column density is inferred from Herschel submillimetre observations, and the magnetic field from observations by the Balloon-borne Large-Aperture Submillimetre Telescope in the 250-, 350- and 500-μm wavelength bands. We find that the PRS has greater statistical power than approaches that bin the relative orientation angles, as it makes more efficient use of the information contained in the data. In particular, the use of the PRS to test for preferential alignment results in a higher statistical significance, in each of the four Vela C regions, with the greatest increase being by a factor 1.3 in the South-Nest region in the 250 - μ m band.

Worry, Intolerance of Uncertainty, and Statistics Anxiety

Science.gov (United States)

Williams, Amanda S.

2013-01-01

Statistics anxiety is a problem for most graduate students. This study investigates the relationship between intolerance of uncertainty, worry, and statistics anxiety. Intolerance of uncertainty was significantly related to worry, and worry was significantly related to three types of statistics anxiety. Six types of statistics anxiety were…

Reducing statistics anxiety and enhancing statistics learning achievement: effectiveness of a one-minute strategy.

Science.gov (United States)

Chiou, Chei-Chang; Wang, Yu-Min; Lee, Li-Tze

2014-08-01

Statistical knowledge is widely used in academia; however, statistics teachers struggle with the issue of how to reduce students' statistics anxiety and enhance students' statistics learning. This study assesses the effectiveness of a "one-minute paper strategy" in reducing students' statistics-related anxiety and in improving students' statistics-related achievement. Participants were 77 undergraduates from two classes enrolled in applied statistics courses. An experiment was implemented according to a pretest/posttest comparison group design. The quasi-experimental design showed that the one-minute paper strategy significantly reduced students' statistics anxiety and improved students' statistics learning achievement. The strategy was a better instructional tool than the textbook exercise for reducing students' statistics anxiety and improving students' statistics achievement.

Evaluation of significantly modified water bodies in Vojvodina by using multivariate statistical techniques

Directory of Open Access Journals (Sweden)

Vujović Svetlana R.

2013-01-01

Full Text Available This paper illustrates the utility of multivariate statistical techniques for analysis and interpretation of water quality data sets and identification of pollution sources/factors with a view to get better information about the water quality and design of monitoring network for effective management of water resources. Multivariate statistical techniques, such as factor analysis (FA/principal component analysis (PCA and cluster analysis (CA, were applied for the evaluation of variations and for the interpretation of a water quality data set of the natural water bodies obtained during 2010 year of monitoring of 13 parameters at 33 different sites. FA/PCA attempts to explain the correlations between the observations in terms of the underlying factors, which are not directly observable. Factor analysis is applied to physico-chemical parameters of natural water bodies with the aim classification and data summation as well as segmentation of heterogeneous data sets into smaller homogeneous subsets. Factor loadings were categorized as strong and moderate corresponding to the absolute loading values of >0.75, 0.75-0.50, respectively. Four principal factors were obtained with Eigenvalues >1 summing more than 78 % of the total variance in the water data sets, which is adequate to give good prior information regarding data structure. Each factor that is significantly related to specific variables represents a different dimension of water quality. The first factor F1 accounting for 28 % of the total variance and represents the hydrochemical dimension of water quality. The second factor F2 accounting for 18% of the total variance and may be taken factor of water eutrophication. The third factor F3 accounting 17 % of the total variance and represents the influence of point sources of pollution on water quality. The fourth factor F4 accounting 13 % of the total variance and may be taken as an ecological dimension of water quality. Cluster analysis (CA is an

Testing earthquake prediction algorithms: Statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992-1997

Science.gov (United States)

Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.

1999-01-01

Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier

Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution.

Science.gov (United States)

Gangnon, Ronald E

2012-03-01

The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, whereas rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. © 2011, The International Biometric Society.

Energy statistics yearbook 2002

International Nuclear Information System (INIS)

2005-01-01

The Energy Statistics Yearbook 2002 is a comprehensive collection of international energy statistics prepared by the United Nations Statistics Division. It is the forty-sixth in a series of annual compilations which commenced under the title World Energy Supplies in Selected Years, 1929-1950. It updates the statistical series shown in the previous issue. Supplementary series of monthly and quarterly data on production of energy may be found in the Monthly Bulletin of Statistics. The principal objective of the Yearbook is to provide a global framework of comparable data on long-term trends in the supply of mainly commercial primary and secondary forms of energy. Data for each type of fuel and aggregate data for the total mix of commercial fuels are shown for individual countries and areas and are summarized into regional and world totals. The data are compiled primarily from the annual energy questionnaire distributed by the United Nations Statistics Division and supplemented by official national statistical publications. Where official data are not available or are inconsistent, estimates are made by the Statistics Division based on governmental, professional or commercial materials. Estimates include, but are not limited to, extrapolated data based on partial year information, use of annual trends, trade data based on partner country reports, breakdowns of aggregated data as well as analysis of current energy events and activities

Energy statistics yearbook 2001

International Nuclear Information System (INIS)

2004-01-01

The Energy Statistics Yearbook 2001 is a comprehensive collection of international energy statistics prepared by the United Nations Statistics Division. It is the forty-fifth in a series of annual compilations which commenced under the title World Energy Supplies in Selected Years, 1929-1950. It updates the statistical series shown in the previous issue. Supplementary series of monthly and quarterly data on production of energy may be found in the Monthly Bulletin of Statistics. The principal objective of the Yearbook is to provide a global framework of comparable data on long-term trends in the supply of mainly commercial primary and secondary forms of energy. Data for each type of fuel and aggregate data for the total mix of commercial fuels are shown for individual countries and areas and are summarized into regional and world totals. The data are compiled primarily from the annual energy questionnaire distributed by the United Nations Statistics Division and supplemented by official national statistical publications. Where official data are not available or are inconsistent, estimates are made by the Statistics Division based on governmental, professional or commercial materials. Estimates include, but are not limited to, extrapolated data based on partial year information, use of annual trends, trade data based on partner country reports, breakdowns of aggregated data as well as analysis of current energy events and activities

Energy statistics yearbook 2000

International Nuclear Information System (INIS)

2002-01-01

The Energy Statistics Yearbook 2000 is a comprehensive collection of international energy statistics prepared by the United Nations Statistics Division. It is the forty-third in a series of annual compilations which commenced under the title World Energy Supplies in Selected Years, 1929-1950. It updates the statistical series shown in the previous issue. Supplementary series of monthly and quarterly data on production of energy may be found in the Monthly Bulletin of Statistics. The principal objective of the Yearbook is to provide a global framework of comparable data on long-term trends in the supply of mainly commercial primary and secondary forms of energy. Data for each type of fuel and aggregate data for the total mix of commercial fuels are shown for individual countries and areas and are summarized into regional and world totals. The data are compiled primarily from the annual energy questionnaire distributed by the United Nations Statistics Division and supplemented by official national statistical publications. Where official data are not available or are inconsistent, estimates are made by the Statistics Division based on governmental, professional or commercial materials. Estimates include, but are not limited to, extrapolated data based on partial year information, use of annual trends, trade data based on partner country reports, breakdowns of aggregated data as well as analysis of current energy events and activities

Statistical Study of Corrosion Types in Constructions in South Region of Rio De Janeiro – Brazil

Directory of Open Access Journals (Sweden)

Carolina Lacerda da Cruz

2016-05-01

Full Text Available Some of the most difficult and troubling problems encountered in construction are those caused by corrosive processes. The corrosion processes are constituted by some material degradation, generally metallic material, by means of chemical or electrochemical actions of environment in which the material are and can or cannot be combined with mechanical stress. Corrosion is present in the materials in general. Their deterioration is caused by such physical-chemical interaction between the material and the corrosive environment where it causes major problems in several activities. In order to prevent material losses, anticorrosive techniques are used which include coatings, medium modification techniques, anodic and cathodic protection, and corrosion inhibitors such as the organic compounds use. This article analyses the statistical study of corrosion types in construction in south region of Rio de Janeiro, Brazil.

Spatio-temporal analysis of regional PV generation

DEFF Research Database (Denmark)

Nuño Martinez, Edgar; Cutululis, Nicolaos Antonio

2016-01-01

Photovoltaic (PV) power is growing in importance worldwide and hence needs to be represented in operation and planning of power system. As opposed to traditional generation technologies, it is characterized by exhibiting both a high variability and a significant spatial dependence. This paper...... presents a fundamental analysis of regional solar generation time series, aiming to potentially facilitate large-scale solar integration. It will focus on characterizing the underlying dependence structure at the system level as well as describing both statistical and temporal properties of regional PV...

Sigma and beta convergence in regional mortality: A case study of the Netherlands

Directory of Open Access Journals (Sweden)

Fanny Janssen

2016-07-01

Full Text Available Background: For allocation of health budgets it is important to know whether regional mortality differences tend to decline or to increase. Sigma convergence tests can measure whether the dispersion of the regional distribution of mortality has declined. Beta convergence tests can examine whether regions with a low level of life expectancy have experienced a stronger increase than regions with a high level. In demographic research, however, sigma and beta convergence have not been formally assessed simultaneously. Objective: We demonstrate the application of both sigma and beta convergence tests to the study of trends in regional mortality differences for the Netherlands. Methods: Using all-cause mortality and population data for 40 Dutch NUTS-3 regions, by year (1988‒2009, age group, and sex, we assess both sigma and beta convergence, and ist significance. Results: Beta convergence proved statistically significant. The regions with the lowest life expectancy in 1988 generally exhibited the highest increase from 1988 to 2009, and vice versa. However, dispersion measures displayed no statistically significant sigma convergence. Conclusions: Whereas the absence of sigma convergence shows that regional mortality differences have not declined, beta convergence indicates that the disadvantage of regions with low life expectancy is not persistent. Contribution: We demonstrated the added value of simultaneously studying sigma convergence, beta convergence, and trajectories of regions in the tails of the distribution. Where absence of sigma convergence does not imply that disadvantaged regions did not improve, beta convergence does not always indicate complete convergence due to structural differences across regions.

A statistical-dynamical downscaling procedure for global climate simulations

International Nuclear Information System (INIS)

Frey-Buness, A.; Heimann, D.; Sausen, R.; Schumann, U.

1994-01-01

A statistical-dynamical downscaling procedure for global climate simulations is described. The procedure is based on the assumption that any regional climate is associated with a specific frequency distribution of classified large-scale weather situations. The frequency distributions are derived from multi-year episodes of low resolution global climate simulations. Highly resolved regional distributions of wind and temperature are calculated with a regional model for each class of large-scale weather situation. They are statistically evaluated by weighting them with the according climate-specific frequency. The procedure is exemplarily applied to the Alpine region for a global climate simulation of the present climate. (orig.)

Computational statistics and biometry: which discipline drives which?

Directory of Open Access Journals (Sweden)

Edler, Lutz

2005-06-01

Full Text Available A biometrician's work is defined through the biological or medical problem and the mathematical and statistical methods needed for its solution. This requires in most instances statistical data analysis and the use of methods of computational statistics. At first, it seems quite obvious that the computational needs of the biometric problem determine what has to be developed by the discipline of computational statistics. However, viewing the development of biometry and computational statistics in Germany for the past decades in more details reveals an interesting interaction between the activities of the German Region of the International Biometric Society and groups engaged in computational statistics within Germany. Exact methods of statistical inference and permutation tests, simulations and the use of the Bootstrap, and interactive graphical statistical methods are examples of this fruitful reciprocal benefit. This contribution examines therefore relationships between the historical development of biometry and computational statistics in Germany using as sources of information contributions to the scientific literature, presentations and sessions at scientific conferences on biometry and on computational statistics which influenced the development of both disciplines and exhibits a reciprocal dependency. The annual workshops organized on the Reisensburg now for more than 30 years are recognized as an outstanding factor of this interrelationship. This work aims at the definition of the present status of computational statistics in the German Region of the International Biometric Society and intends to guide and to foster the discussion of the future development of this discipline among biometricians.

Rocky Mountain Regional CO{sub 2} Storage Capacity and Significance

Energy Technology Data Exchange (ETDEWEB)

Laes, Denise; Eisinger, Chris; Esser, Richard; Morgan, Craig; Rauzi, Steve; Scholle, Dana; Matthews, Vince; McPherson, Brian

2013-08-30

The purpose of this study includes extensive characterization of the most promising geologic CO{sub 2} storage formations on the Colorado Plateau, including estimates of maximum possible storage capacity. The primary targets of characterization and capacity analysis include the Cretaceous Dakota Formation, the Jurassic Entrada Formation and the Permian Weber Formation and their equivalents in the Colorado Plateau region. The total CO{sub 2} capacity estimates for the deep saline formations of the Colorado Plateau region range between 9.8 metric GT and 143 metric GT, depending on assumed storage efficiency, formations included, and other factors.

A novel complete-case analysis to determine statistical significance between treatments in an intention-to-treat population of randomized clinical trials involving missing data.

Science.gov (United States)

Liu, Wei; Ding, Jinhui

2018-04-01

The application of the principle of the intention-to-treat (ITT) to the analysis of clinical trials is challenged in the presence of missing outcome data. The consequences of stopping an assigned treatment in a withdrawn subject are unknown. It is difficult to make a single assumption about missing mechanisms for all clinical trials because there are complicated reactions in the human body to drugs due to the presence of complex biological networks, leading to data missing randomly or non-randomly. Currently there is no statistical method that can tell whether a difference between two treatments in the ITT population of a randomized clinical trial with missing data is significant at a pre-specified level. Making no assumptions about the missing mechanisms, we propose a generalized complete-case (GCC) analysis based on the data of completers. An evaluation of the impact of missing data on the ITT analysis reveals that a statistically significant GCC result implies a significant treatment effect in the ITT population at a pre-specified significance level unless, relative to the comparator, the test drug is poisonous to the non-completers as documented in their medical records. Applications of the GCC analysis are illustrated using literature data, and its properties and limits are discussed.

Identification of reliable gridded reference data for statistical downscaling methods in Alberta

Science.gov (United States)

Eum, H. I.; Gupta, A.

2017-12-01

Climate models provide essential information to assess impacts of climate change at regional and global scales. However, statistical downscaling methods have been applied to prepare climate model data for various applications such as hydrologic and ecologic modelling at a watershed scale. As the reliability and (spatial and temporal) resolution of statistically downscaled climate data mainly depend on a reference data, identifying the most reliable reference data is crucial for statistical downscaling. A growing number of gridded climate products are available for key climate variables which are main input data to regional modelling systems. However, inconsistencies in these climate products, for example, different combinations of climate variables, varying data domains and data lengths and data accuracy varying with physiographic characteristics of the landscape, have caused significant challenges in selecting the most suitable reference climate data for various environmental studies and modelling. Employing various observation-based daily gridded climate products available in public domain, i.e. thin plate spline regression products (ANUSPLIN and TPS), inverse distance method (Alberta Townships), and numerical climate model (North American Regional Reanalysis) and an optimum interpolation technique (Canadian Precipitation Analysis), this study evaluates the accuracy of the climate products at each grid point by comparing with the Adjusted and Homogenized Canadian Climate Data (AHCCD) observations for precipitation, minimum and maximum temperature over the province of Alberta. Based on the performance of climate products at AHCCD stations, we ranked the reliability of these publically available climate products corresponding to the elevations of stations discretized into several classes. According to the rank of climate products for each elevation class, we identified the most reliable climate products based on the elevation of target points. A web-based system

Statistical investigation of expected wave energy and its reliability

International Nuclear Information System (INIS)

Ozger, M.; Altunkaynak, A.; Sen, Z.

2004-01-01

The statistical behavior of wave energy at a single site is derived by considering simultaneous variations in the period and wave height. In this paper, the general wave power formulation is derived by using the theory of perturbation. This method leads to a general formulation of the wave power expectation and other statistical parameter expressions, such as standard deviation and coefficient of variation. The statistical parameters, namely the mean value and variance of wave energy, are found in terms of the simple statistical parameters of period, significant wave height and zero up-crossing period. The elegance of these parameters is that they are distribution free. These parameters provide a means for defining the wave energy distribution function by employing the Chebyschev's inequality. Subsequently, an approximate probability distribution function of the wave energy is also derived for assessment of risk and reliability associated with wave energy. Necessary simple charts are given for risk and reliability assessments. Two procedures are presented for such assessments in wave energy calculations and the applications of these procedures are provided for wave energy potential assessment in the regions of the Pacific Ocean off the west coast of U.S. (author)

Statistical investigation of expected wave energy and its reliability

International Nuclear Information System (INIS)

Oezger, Mehmet; Altunkaynak, Abduesselam; Sen, Zekai

2004-01-01

The statistical behavior of wave energy at a single site is derived by considering simultaneous variations in the period and wave height. In this paper, the general wave power formulation is derived by using the theory of perturbation. This method leads to a general formulation of the wave power expectation and other statistical parameter expressions, such as standard deviation and coefficient of variation. The statistical parameters, namely the mean value and variance of wave energy, are found in terms of the simple statistical parameters of period, significant wave height and zero up-crossing period. The elegance of these parameters is that they are distribution free. These parameters provide a means for defining the wave energy distribution function by employing the Chebyschev's inequality. Subsequently, an approximate probability distribution function of the wave energy is also derived for assessment of risk and reliability associated with wave energy. Necessary simple charts are given for risk and reliability assessments. Two procedures are presented for such assessments in wave energy calculations and the applications of these procedures are provided for wave energy potential assessment in the regions of the Pacific Ocean off the west coast of U.S

Regionally variant collagen alignment correlates with viscoelastic properties of the disc of the human temporomandibular joint.

Science.gov (United States)

Gutman, Shawn; Kim, Daniel; Tarafder, Solaiman; Velez, Sergio; Jeong, Julia; Lee, Chang H

2018-02-01

To determine the regionally variant quality of collagen alignment in human TMJ discs and its statistical correlation with viscoelastic properties. For quantitative analysis of the quality of collagen alignment, horizontal sections of human TMJ discs with Pricrosirius Red staining were imaged under circularly polarized microscopy. Mean angle and angular deviation of collagen fibers in each region were analyzed using a well-established automated image-processing for angular gradient. Instantaneous and relaxation moduli of each disc region were measured under stress-relaxation test both in tensile and compression. Then Spearman correlation analysis was performed between the angular deviation and the moduli. To understand the effect of glycosaminoglycans on the correlation, TMJ disc samples were treated by chondroitinase ABC (C-ABC). Our imaging processing analysis showed the region-variant direction of collagen alignment, consistently with previous findings. Interestingly, the quality of collagen alignment, not only the directions, was significantly different in between the regions. The angular deviation of fiber alignment in the anterior and intermediate regions were significantly smaller than the posterior region. Medial and lateral regions showed significantly bigger angular deviation than all the other regions. The regionally variant angular deviation values showed statistically significant correlation with the tensile instantaneous modulus and the relaxation modulus, partially dependent on C-ABC treatment. Our findings suggest the region-variant degree of collagen fiber alignment is likely attributed to the heterogeneous viscoelastic properties of TMJ disc that may have significant implications in development of regenerative therapy for TMJ disc. Copyright © 2017 Elsevier Ltd. All rights reserved.

Where did Venomous Snakes Strike? A Spatial Statistical Analysis of Snakebite Cases in Bondowoso Regency, Indonesia

Directory of Open Access Journals (Sweden)

Farid Rifaie

2017-07-01

Full Text Available Snakebite envenomation in Indonesia is a health burden that receives no attention from stakeholders. The high mortality and morbidity rate caused by snakebite in Indonesia is estimated from regional reports. The true burden of this issue in Indonesia needs to be revealed even starting from a small part of the country. Medical records from a Hospital in Bondowoso Regency were the data source of the snakebite cases. Three spatial statistical summaries were applied to analyze the spatial pattern of snakebite incidents. The comparison between statistical functions and the theoretical model of random distributions shows a significant clustering pattern of the events. The pattern indicates that five subdistricts in Bondowoso have a substantial number of snakebite cases more than other regions. This finding shows the potential application of spatial statistics for the snakebite combating strategy in this area by identifying the priority locations of the snakebite cases.

Role of sufficient statistics in stochastic thermodynamics and its implication to sensory adaptation

Science.gov (United States)

Matsumoto, Takumi; Sagawa, Takahiro

2018-04-01

A sufficient statistic is a significant concept in statistics, which means a probability variable that has sufficient information required for an inference task. We investigate the roles of sufficient statistics and related quantities in stochastic thermodynamics. Specifically, we prove that for general continuous-time bipartite networks, the existence of a sufficient statistic implies that an informational quantity called the sensory capacity takes the maximum. Since the maximal sensory capacity imposes a constraint that the energetic efficiency cannot exceed one-half, our result implies that the existence of a sufficient statistic is inevitably accompanied by energetic dissipation. We also show that, in a particular parameter region of linear Langevin systems there exists the optimal noise intensity at which the sensory capacity, the information-thermodynamic efficiency, and the total entropy production are optimized at the same time. We apply our general result to a model of sensory adaptation of E. coli and find that the sensory capacity is nearly maximal with experimentally realistic parameters.

Effects of hypoglycaemia on working memory and regional cerebral blood flow in type 1 diabetes: a randomised, crossover trial

DEFF Research Database (Denmark)

Gejl, Michael; Gjedde, Albert; Brock, Birgitte

2018-01-01

(PET) per session. RESULTS: Working memory was impaired during hypoglycaemia as indicated by a statistically significantly lower mDSST score (estimated treatment difference [ETD] -0.63 [95% CI -1.13, -0.14], p = 0.014) and a statistically significantly longer response time (ETD 2.86 s [7%] [95% CI 0.......67, 5.05], p = 0.013) compared with euglycaemia. During hypoglycaemia, mDSST task performance was associated with increased activity in the frontal lobe regions, superior parietal lobe and thalamus, and decreased activity in the temporal lobe regions (p Working memory activation (mDSST - c......DSST) statistically significantly increased blood flow in the striatum during hypoglycaemia (ETD 0.0374% [95% CI 0.0157, 0.0590], p = 0.002). CONCLUSIONS/INTERPRETATION: During hypoglycaemia (mean PG 2.9 mmol/l), working memory performance was impaired. Altered performance was associated with significantly increased...

Comparative statistical analysis of carcinogenic and non-carcinogenic effects of uranium in groundwater samples from different regions of Punjab, India

International Nuclear Information System (INIS)

Saini, Komal; Singh, Parminder; Bajwa, Bikramjit Singh

2016-01-01

LED flourimeter has been used for microanalysis of uranium concentration in groundwater samples collected from six districts of South West (SW), West (W) and North East (NE) Punjab, India. Average value of uranium content in water samples of SW Punjab is observed to be higher than WHO, USEPA recommended safe limit of 30 µg l −1 as well as AERB proposed limit of 60 µg l −1 . Whereas, for W and NE region of Punjab, average level of uranium concentration was within AERB recommended limit of 60 µg l −1 . Average value observed in SW Punjab is around 3–4 times the value observed in W Punjab, whereas its value is more than 17 times the average value observed in NE region of Punjab. Statistical analysis of carcinogenic as well as non carcinogenic risks due to uranium have been evaluated for each studied district. - Highlights: • Uranium level in groundwater samples have been assessed in different regions of Punjab. • Comparative study of carcinogenic and non carcinogenic effects of uranium has been done. • Wide variation has been found for different geological regions. • It has been found that South west Punjab is worst affected by uranium contamination in its water. • For west and north east regions of Punjab, uranium levels in groundwater laid under recommended safe limits.

Regional Aspects of New Industrialization

Directory of Open Access Journals (Sweden)

Yakov Petrovich Silin

2017-09-01

Full Text Available In the article, the authors substantiate the need to consider the regional economic and other conditions when carrying out various essential transformations in the national economy of the country. We have argued the importance of new industrialization for overcoming the technological lag of the country and its regions and for supporting the large-scale structural transformations. We have proved that the complex set of the interconnected concepts and the theories of macro- and microlevels may be the theoretical platform for the paradigm of new industrialization. These are the theory of economic growth, the theory of the modernization of the economy, the theory of the change of technological ways during the industrial revolutions, theories of innovative development, developments in the field of the institutional theory. The authors have shown that the transition to new industrialization is the fundamental historical pattern for the majority of the countries of the world, including industrially developed ones. The purpose of the article is to identify the brightest tendencies and features of the development of the Ural macro-region in the years of market reforms as well as the definition of the strategic transformations in the context of the formation of new industrialization. The hypothesis of the research assumes that the revealed regional features of the Ural macroregion’s economic development are the prerequisites of its development as the centre of the modernization of the Russian economy. On the basis of the analysis of three groups of statistic data for the twenty-five year period of liberal and monetary reforms, the brightest tendencies and features of the development of the Ural macro-region are revealed. We have emphasized that the Ural macro-region has managed to keep its historically developed code — the industrial model of the economy, which have been developing for many decades. The authors have made a significant contribution of

The Euclid Statistical Matrix Tool

Directory of Open Access Journals (Sweden)

Curtis Tilves

2017-06-01

Full Text Available Stataphobia, a term used to describe the fear of statistics and research methods, can result from a lack of improper training in statistical methods. Poor statistical methods training can have an effect on health policy decision making and may play a role in the low research productivity seen in developing countries. One way to reduce Stataphobia is to intervene in the teaching of statistics in the classroom; however, such an intervention must tackle several obstacles, including student interest in the material, multiple ways of learning materials, and language barriers. We present here the Euclid Statistical Matrix, a tool for combatting Stataphobia on a global scale. This free tool is comprised of popular statistical YouTube channels and web sources that teach and demonstrate statistical concepts in a variety of presentation methods. Working with international teams in Iran, Japan, Egypt, Russia, and the United States, we have also developed the Statistical Matrix in multiple languages to address language barriers to learning statistics. By utilizing already-established large networks, we are able to disseminate our tool to thousands of Farsi-speaking university faculty and students in Iran and the United States. Future dissemination of the Euclid Statistical Matrix throughout the Central Asia and support from local universities may help to combat low research productivity in this region.

A multimodal wave spectrum-based approach for statistical downscaling of local wave climate

Science.gov (United States)

Hegermiller, Christie; Antolinez, Jose A A; Rueda, Ana C.; Camus, Paula; Perez, Jorge; Erikson, Li; Barnard, Patrick; Mendez, Fernando J.

2017-01-01

Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g. the Pacific). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, we address these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “wave families,” defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications.

Assessment of genetically significant doses to the Sofia population from natural gamma background

International Nuclear Information System (INIS)

Vasilev, G.; Khristova, M.

1977-01-01

Genetically significant dose to the population of Sofia city was assessed within a program covering larger urban communities in the country. Measurements were made of gamma background exposure rates in the gonadal region. Gonad doses were estimated using a screening factor of 0.73. Based on statistical data for total number of inhabitants and number of people of reproductive age, and on the mean annual gonad doses derived, calculations were made of genetically significant dose to the Sofia population. Base-line data were thus provided for an assessment of extra radiation dose resulting from occupational radiation exposure. (author)

Statistical measurement of power spectrum density of large aperture optical component

International Nuclear Information System (INIS)

Xu Jiancheng; Xu Qiao; Chai Liqun

2010-01-01

According to the requirement of ICF, a method based on statistical theory has been proposed to measure the power spectrum density (PSD) of large aperture optical components. The method breaks the large-aperture wavefront into small regions, and obtains the PSD of the large-aperture wavefront by weighted averaging of the PSDs of the regions, where the weight factor is each region's area. Simulation and experiment demonstrate the effectiveness of the proposed method. They also show that, the obtained PSDs of the large-aperture wavefront by statistical method and sub-aperture stitching method fit well, when the number of small regions is no less than 8 x 8. The statistical method is not sensitive to translation stage's errors and environment instabilities, thus it is appropriate for PSD measurement during the process of optical fabrication. (authors)

Evaluating statistical and clinical significance of intervention effects in single-case experimental designs: an SPSS method to analyze univariate data.

Science.gov (United States)

Maric, Marija; de Haan, Else; Hogendoorn, Sanne M; Wolters, Lidewij H; Huizenga, Hilde M

2015-03-01

Single-case experimental designs are useful methods in clinical research practice to investigate individual client progress. Their proliferation might have been hampered by methodological challenges such as the difficulty applying existing statistical procedures. In this article, we describe a data-analytic method to analyze univariate (i.e., one symptom) single-case data using the common package SPSS. This method can help the clinical researcher to investigate whether an intervention works as compared with a baseline period or another intervention type, and to determine whether symptom improvement is clinically significant. First, we describe the statistical method in a conceptual way and show how it can be implemented in SPSS. Simulation studies were performed to determine the number of observation points required per intervention phase. Second, to illustrate this method and its implications, we present a case study of an adolescent with anxiety disorders treated with cognitive-behavioral therapy techniques in an outpatient psychotherapy clinic, whose symptoms were regularly assessed before each session. We provide a description of the data analyses and results of this case study. Finally, we discuss the advantages and shortcomings of the proposed method. Copyright © 2014. Published by Elsevier Ltd.

Performance studies of GooFit on GPUs vs RooFit on CPUs while estimating the statistical significance of a new physical signal

Science.gov (United States)

Di Florio, Adriano

2017-10-01

In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B + → J/ψϕK +. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

A brief report on the statistical study of net electric current in solar active regions with longitudinal fields of opposite polarity

International Nuclear Information System (INIS)

Gao Yu

2013-01-01

Dynamic processes occurring in solar active regions are dominated by the solar magnetic field. As of now, observations using a solar magnetograph have supplied us with the vector components of a solar photospheric magnetic field. The two transverse components of a photospheric magnetic field allow us to compute the amount of electric current. We found that the electric current in areas with positive (negative) polarity due to the longitudinal magnetic field have both positive and negative signs in an active region, however, the net current is found to be an order-of-magnitude less than the mean absolute magnitude and has a preferred sign. In particular, we have statistically found that there is a systematic net electric current from areas with negative (positive) polarity to areas with positive (negative) polarity in solar active regions in the northern (southern) hemisphere, but during the solar minimum this tendency is reversed over time at some latitudes. The result indicates that there is weak net electric current in areas of solar active regions with opposite polarity, thus providing further details about the hemispheric helicity rule found in a series of previous studies.

Identification and Analysis of Significant Factors Influencing Visitor Satisfaction at Heritage Sites – The Case of Serbian Medieval Fortresses

Directory of Open Access Journals (Sweden)

Ivana Blešić

2013-01-01

Full Text Available With increased appreciation of general public, heritage sites gained more attention regarding contemporary tourism and management studies. Accordingly, the assessment of visitors’ satisfaction on these sites is important tool for both financial and organization management. The aim of this research is to identify the main (statistically significant factors that influence visitors’ satisfaction. Data was obtained by survey conducted during the visit of three medieval fortresses in Serbia, with aim to capture tourist’s expectations and perceptions on ten given attributes. The results of factor and descriptive statistical analysis indicate three factors: “regional settings”, “marketing”, “aesthetic appeal” significant for visitors’ satisfaction of the investigated heritage sites.

An evaluation of satellite and in situ based sea surface temperature datasets in the North Indian Ocean region

Digital Repository Service at National Institute of Oceanography (India)

Sreejith, O.P.; Shenoi, S.S.C.

for all three datasets. There was very little difference in the error statistics from one region to another. The error statistics differed significantly from year to year. The PFSST fields reported cooler SSTs approx. 0.5 degrees C, during August 1991...

Global industry with regional significance. Social perspectives

International Nuclear Information System (INIS)

2005-05-01

As the world's third largest exporter of oil, Norway is an energy superpower in an international context. 2004 was a record-breaking year on the Norwegian Shelf. Never before did production reach such heights. The oil and gas industry is Norway's largest and most important industry. It is responsible for one-third of the State's revenues, and nearly half of Norway's total export revenues. The report provides an overview of the Norwegian Shelf today, and facts about Norway concerning the economy and standard of living. The industry's role in regional business development is also analysed, as well as expertise and technological development. Aspects on the environment and co-existence at sea are reviewed, with information on emissions to air and discharges to sea. Environmental considerations and technological challenges are briefly reported. The petroleum industry has set the standard within Health, Safety and the Environment (HSE). The work has been based on close cooperation between the authorities and the operating companies, their organizations and the employee organizations on the Shelf. Details on these activities are reported. Finally, responsibility for the community and issues concerning corporate social responsibility are mentioned (ml)

Statistics of the tripolar electrostatic solitary waves within magnetic reconnection diffusion region in the near-Earth magnetotail

Science.gov (United States)

Li, S. Y.; Zhang, S. F.; Cai, H.; Chen, X. Q.; Deng, X. H.

2013-06-01

In this paper, we report the observations and statistical characteristics of tripolar electrostatic solitary waves (ESWs) along the plasma sheet boundary layer near the magnetic reconnection X line in the near-Earth magnetotail. Within reconnection diffusion region, the tripolar ESWs are ample and are continuously observed during one burst interval (8.75 s) of the Geotail/WaveForm Capture in the neutral plasma sheet where β > 1 on 10:20 UT, 2 February 1996. The tripolar ESW is suggested to be one kind of steady-going solitary structure. More than 200 waveforms with clear tripolar characteristics are differentiated for statistical analysis, and result shows that (1) their amplitude is within 100->500 μV/m, with an average amplitude of about 254 μV/m; (2) the pulse width of the tripolar ESWs is 0.5-1.0 ms, with an average value of about 0.75 ms; (3) it is asymmetrical in both the amplitude and pulse width of the tripolar ESWs: most part of the tripolar ESWs (about 76.5%) are asymmetrical in the amplitude of one hump and the other one, and more than 75% (about 177 amount the 236 waveforms) of the tripolar ESWs are asymmetrical in the time duration of the two humps in the waveform; (4) most of the tripolar ESWs are with the potential humps of 10-60 mV, small ratio of them with potential humps larger than 100 mV. The tripolar ESWs with net potential drop of about 10-50 mV can be interpreted as "weak" double layers. The possible generation mechanism of tripolar ESWs and their role in reconnection are discussed by studying the particle distribution during which the tripolar ESWs are continuously observed. The observation of tripolar ESWs presents evidence of complex structure of electron holes within the reconnection diffusion region and is helpful to the understanding of the energy release process of reconnection.

Statistical core design

International Nuclear Information System (INIS)

Oelkers, E.; Heller, A.S.; Farnsworth, D.A.; Kearfott, K.J.

1978-01-01

The report describes the statistical analysis of DNBR thermal-hydraulic margin of a 3800 MWt, 205-FA core under design overpower conditions. The analysis used LYNX-generated data at predetermined values of the input variables whose uncertainties were to be statistically combined. LYNX data were used to construct an efficient response surface model in the region of interest; the statistical analysis was accomplished through the evaluation of core reliability; utilizing propagation of the uncertainty distributions of the inputs. The response surface model was implemented in both the analytical error propagation and Monte Carlo Techniques. The basic structural units relating to the acceptance criteria are fuel pins. Therefore, the statistical population of pins with minimum DNBR values smaller than specified values is determined. The specified values are designated relative to the most probable and maximum design DNBR values on the power limiting pin used in present design analysis, so that gains over the present design criteria could be assessed for specified probabilistic acceptance criteria. The results are equivalent to gains ranging from 1.2 to 4.8 percent of rated power dependent on the acceptance criterion. The corresponding acceptance criteria range from 95 percent confidence that no pin will be in DNB to 99.9 percent of the pins, which are expected to avoid DNB

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

Science.gov (United States)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

Current-voltage relationship in the auroral particle acceleration region

Directory of Open Access Journals (Sweden)

M. Morooka

2004-11-01

Full Text Available The current-voltage relationship in the auroral particle acceleration region has been studied statistically by the Akebono (EXOS-D satellite in terms of the charge carriers of the upward field-aligned current. The Akebono satellite often observed field-aligned currents which were significantly larger than the model value predicted by Knight (1973. We compared the upward field-aligned current estimated by three different methods, and found that low-energy electrons often play an important role as additional current carriers, together with the high-energy primary electrons which are expected from Knight's relation. Such additional currents have been observed especially at high and middle altitudes of the particle acceleration region. Some particular features of electron distribution functions, such as "cylindrical distribution functions" and "electron conics", have often been observed coinciding with the additional currents. They indicated time variability of the particle acceleration region. Therefore, we have concluded that the low-energy electrons within the "forbidden" region of electron phase space in the stationary model often contribute to charge carriers of the current because of the rapid time variability of the particle acceleration region. "Cylindrical distribution functions" are expected to be found below the time-varying potential difference. We statistically examined the locations of "cylindrical distribution function", and found that their altitudes are related to the location where the additional currents have been observed. This result is consistent with the idea that the low-energy electrons can also carry significant current when the acceleration region changes in time.

GUIDANCE FOR STATISTICAL DETERMINATION OF APPROPRIATE PERCENT MINORITY AND PERCENT POVERTY DISTRIBUTIONAL CUTOFF VALUES USING CENSUS DATA FOR AND EPA REGION II ENVIRONMENTAL JUSTICE PROJECT

Science.gov (United States)

The purpose of this report is to assist Region H by providing a statistical analysis identifying the areas with minority and below poverty populations known as "Community of Concern" (COC). The aim was to find a cutoff value as a threshold to identify a COC using demographic data...

Robust statistical methods for significance evaluation and applications in cancer driver detection and biomarker discovery

DEFF Research Database (Denmark)

Madsen, Tobias

2017-01-01

In the present thesis I develop, implement and apply statistical methods for detecting genomic elements implicated in cancer development and progression. This is done in two separate bodies of work. The first uses the somatic mutation burden to distinguish cancer driver mutations from passenger m...

Sources of Regional Banks Capitalization

Directory of Open Access Journals (Sweden)

Olga Sergeevna Miroshnichenko

2018-03-01

Full Text Available Searching of sources to increase the capitalization of Russian banks is an important economic problem for both the national and regional economy. Moreover, a strong capital base allows to credit institutions to meet the demands of economic agents for banking service. The research focuses on the choice of sources of regulatory capital for the banks of Tyumen region in the context of changing supervisory requirements in the period of 2005–2016, in different phases of the business cycle. We apply econometric methods of statistical information using IBM SPSS Statistics software. We have calculated the individual correlations of regional banks’ capital with gross domestic product (GDP (excluding gross regional product (GRP and GRP (with the exception of the effect of GDP. These calculations have shown that the capital of regional banks is related only to GDP. The increase in the capital of regional banks is accompanied by a change in its structure: the share of authorized capital has halved, and the share of subordinated debt has grown. All sources of capital, other than the reserve fund, are related to GDP. Authorized capital is associated with the profit of profitable lending institutions; retained earnings in the capital of regional banks — with the aggregated amount of risks of the banking system of the Russian Federation. Subordinated debt, like capital as a whole, is negatively affected by the profitability of the banking sector. The change in the capital of regional banks is determined by the change in retained earnings, subordinated debt and reserve fund. Modelling of these relations has allowed to obtain a system of equations. This system synthesizes linear regression models of changing the capital of regional banks in the context of their sourcing. The results of this study are significant for theoretical justification and practical development of a balanced financial policy of regional banks. Our research will contribute to

Comparative statistical analysis of carcinogenic and non-carcinogenic effects of uranium in groundwater samples from different regions of Punjab, India.

Science.gov (United States)

Saini, Komal; Singh, Parminder; Bajwa, Bikramjit Singh

2016-12-01

LED flourimeter has been used for microanalysis of uranium concentration in groundwater samples collected from six districts of South West (SW), West (W) and North East (NE) Punjab, India. Average value of uranium content in water samples of SW Punjab is observed to be higher than WHO, USEPA recommended safe limit of 30µgl -1 as well as AERB proposed limit of 60µgl -1 . Whereas, for W and NE region of Punjab, average level of uranium concentration was within AERB recommended limit of 60µgl -1 . Average value observed in SW Punjab is around 3-4 times the value observed in W Punjab, whereas its value is more than 17 times the average value observed in NE region of Punjab. Statistical analysis of carcinogenic as well as non carcinogenic risks due to uranium have been evaluated for each studied district. Copyright © 2016 Elsevier Ltd. All rights reserved.

Functional MRI approach for assessing hemispheric predominance of regions activated by a phonological and a semantic task

Energy Technology Data Exchange (ETDEWEB)

Cousin, Emilie; Peyrin, Carole; Pichat, Cedric [Laboratoire de Psychologie et Neurocognition, UMR CNRS 5105, Universite Pierre Mendes-France, BP 47, 38040 Grenoble Cedex 09 (France); Lamalle, Laurent; Le Bas, Jean-Francois [Unite IRM, IFR1, CHU Grenoble (France); Baciu, Monica [Laboratoire de Psychologie et Neurocognition, UMR CNRS 5105, Universite Pierre Mendes-France, BP 47, 38040 Grenoble Cedex 09 (France)], E-mail: mbaciu@upmf-grenoble.fr

2007-08-15

This fMRI study performed in healthy subjects aimed at using a statistical approach in order to determine significant functional differences between hemispheres and to assess specialized regions activated during a phonological and during a semantic task. This approach ('flip' method and subsequent statistical analyses of the parameter estimates extracted from regions of interest) allows identifying: (a) hemispheric specialized regions for each language task [semantic (living categorization) and phonological (rhyme detection)] and (b) condition-specific regions with respect to paradigm conditions (task and control). Our results showed that the rhyme-specific task regions were the inferior frontal (sub-region of BA 44, 45) and left inferior parietal (BA 40, 39) lobules. Furthermore, within the inferior parietal lobule, the angular gyrus was specific to target (rhyming) items (related to successfully grapho-phonemic processing). The categorization-specific task regions were the left inferior frontal (sub-region of BA 44, 45) and superior temporal (BA 22) cortices. Furthermore, the superior temporal gyrus was related to non-target (non-living) items (correlated to task difficulty). The relatively new approach used in this study has the advantage of providing: (a) statistical significance of the hemispheric specialized regions for a given language task and (b) supplementary information in terms of paradigm condition-specificity of the activated regions. The results (standard hemispheric specialized regions for a semantic and for a phonological task) obtained in healthy subjects may constitute a basement for mapping language and assessing hemispheric predominance in epileptic patients before surgery and avoiding post-surgical impairments of language.

Functional MRI approach for assessing hemispheric predominance of regions activated by a phonological and a semantic task

International Nuclear Information System (INIS)

Cousin, Emilie; Peyrin, Carole; Pichat, Cedric; Lamalle, Laurent; Le Bas, Jean-Francois; Baciu, Monica

2007-01-01

This fMRI study performed in healthy subjects aimed at using a statistical approach in order to determine significant functional differences between hemispheres and to assess specialized regions activated during a phonological and during a semantic task. This approach ('flip' method and subsequent statistical analyses of the parameter estimates extracted from regions of interest) allows identifying: (a) hemispheric specialized regions for each language task [semantic (living categorization) and phonological (rhyme detection)] and (b) condition-specific regions with respect to paradigm conditions (task and control). Our results showed that the rhyme-specific task regions were the inferior frontal (sub-region of BA 44, 45) and left inferior parietal (BA 40, 39) lobules. Furthermore, within the inferior parietal lobule, the angular gyrus was specific to target (rhyming) items (related to successfully grapho-phonemic processing). The categorization-specific task regions were the left inferior frontal (sub-region of BA 44, 45) and superior temporal (BA 22) cortices. Furthermore, the superior temporal gyrus was related to non-target (non-living) items (correlated to task difficulty). The relatively new approach used in this study has the advantage of providing: (a) statistical significance of the hemispheric specialized regions for a given language task and (b) supplementary information in terms of paradigm condition-specificity of the activated regions. The results (standard hemispheric specialized regions for a semantic and for a phonological task) obtained in healthy subjects may constitute a basement for mapping language and assessing hemispheric predominance in epileptic patients before surgery and avoiding post-surgical impairments of language

1992 Energy statistics Yearbook

International Nuclear Information System (INIS)

1994-01-01

The principal objective of the Yearbook is to provide a global framework of comparable data on long-term trends in the supply of mainly commercial primary and secondary forms of energy. Data for each type of fuel and aggregate data for the total mix of commercial fuels are shown for individual countries and areas and are summarized into regional and world totals. The data are compiled primarily from annual questionnaires distributed by the United Nations Statistical Division and supplemented by official national statistical publications. Where official data are not available or are inconsistent, estimates are made by the Statistical Division based on governmental, professional or commercial materials. Estimates include, but are not limited to, extrapolated data based on partial year information, use of annual trends, trade data based on partner country reports, breakdowns of aggregated data as well as analysis of current energy events and activities

The statistical analysis of anisotropies

International Nuclear Information System (INIS)

Webster, A.

1977-01-01

One of the many uses to which a radio survey may be put is an analysis of the distribution of the radio sources on the celestial sphere to find out whether they are bunched into clusters or lie in preferred regions of space. There are many methods of testing for clustering in point processes and since they are not all equally good this contribution is presented as a brief guide to what seems to be the best of them. The radio sources certainly do not show very strong clusering and may well be entirely unclustered so if a statistical method is to be useful it must be both powerful and flexible. A statistic is powerful in this context if it can efficiently distinguish a weakly clustered distribution of sources from an unclustered one, and it is flexible if it can be applied in a way which avoids mistaking defects in the survey for true peculiarities in the distribution of sources. The paper divides clustering statistics into two classes: number density statistics and log N/log S statistics. (Auth.)

Significance evaluation in factor graphs

DEFF Research Database (Denmark)

Madsen, Tobias; Hobolth, Asger; Jensen, Jens Ledet

2017-01-01

in genomics and the multiple-testing issues accompanying them, accurate significance evaluation is of great importance. We here address the problem of evaluating statistical significance of observations from factor graph models. Results Two novel numerical approximations for evaluation of statistical...... significance are presented. First a method using importance sampling. Second a saddlepoint approximation based method. We develop algorithms to efficiently compute the approximations and compare them to naive sampling and the normal approximation. The individual merits of the methods are analysed both from....... Conclusions The applicability of saddlepoint approximation and importance sampling is demonstrated on known models in the factor graph framework. Using the two methods we can substantially improve computational cost without compromising accuracy. This contribution allows analyses of large datasets...

The region of influence of significant defects and the mechanical vibrations of linear elastic solids

International Nuclear Information System (INIS)

Suarez Antola, R.

2004-12-01

The presence of cracks, voids or fields of pores, and their growth under applied forces or environmental actions, can produce a meaningful lowering in the proper frequencies of normal modes of mechanical vibration in machines and structures. A quite general expression for the square of modes proper frequency as a functional of displacement field, density field and elastic moduli fields is used as a starting point. The effect of defects on frequency are modeled as equivalent changes in density and elastic moduli fields, introducing the concept of region of influence of each defect. This region of influence is derived from the relation between the stress field of flawed components in machines or structures, and the elastic energy released from a suitable reference state, due to the presence of significant defects in the above mentioned mechanical components. An approximate analytical expression is obtained, which relates the relative variation in the square of mode s proper frequency with position, size, shape and orientation of defects in mode displacement field. Some simple mathematical models of machine and structural elements with cracks or fields of pores are considered as examples. The connections between the relative lowering in the square of mode s proper frequency and the stress intensity factor of a defect are discussed : the concept of region of influence of a defect is used as a bridge between (low frequency and low amplitude) vibration dynamics and linear elastic fracture mechanics. Some limitations of the present approach are discussed as well as the possibility of applying the region of influence of defects to the damping of normal modes of vibration

Accurate corresponding point search using sphere-attribute-image for statistical bone model generation

International Nuclear Information System (INIS)

Saito, Toki; Nakajima, Yoshikazu; Sugita, Naohiko; Mitsuishi, Mamoru; Hashizume, Hiroyuki; Kuramoto, Kouichi; Nakashima, Yosio

2011-01-01

Statistical deformable model based two-dimensional/three-dimensional (2-D/3-D) registration is a promising method for estimating the position and shape of patient bone in the surgical space. Since its accuracy depends on the statistical model capacity, we propose a method for accurately generating a statistical bone model from a CT volume. Our method employs the Sphere-Attribute-Image (SAI) and has improved the accuracy of corresponding point search in statistical model generation. At first, target bone surfaces are extracted as SAIs from the CT volume. Then the textures of SAIs are classified to some regions using Maximally-stable-extremal-regions methods. Next, corresponding regions are determined using Normalized cross-correlation (NCC). Finally, corresponding points in each corresponding region are determined using NCC. The application of our method to femur bone models was performed, and worked well in the experiments. (author)

Mixed deterministic statistical modelling of regional ozone air pollution

KAUST Repository

Kalenderski, Stoitchko; Steyn, Douw G.

2011-01-01

formalism, and explicitly accounts for advection of pollutants, using the advection equation. We apply the model to a specific case of regional ozone pollution-the Lower Fraser valley of British Columbia, Canada. As a predictive tool, we demonstrate

Development of a statistically-based lower bound fracture toughness curve (Ksub(IR) curve)

International Nuclear Information System (INIS)

Wullaert, R.A.; Server, W.L.; Oldfield, W.; Stahlkopf, K.E.

1977-01-01

A program of initiation fracture toughness measurements on fifty heats of nuclear pressure vessel production materials (including weldments) was used to develop a methodology for establishing a revised reference toughness curve. The new methodology was statistically developed and provides a predefined confidence limit (or tolerance limit) for fracture toughness based upon many heats of a particular type of material. Overall reference curves were developed for seven specific materials using large specimen static and dynamic fracture toughness results. The heat-to-heat variation was removed by normalizing both the fracture toughness and temperature data with the precracked Charpy tanh curve coefficients for each particular heat. The variance and distribution about the curve were determined, and lower bounds of predetermined statistical significance were drawn based upon a Pearson distribution in the lower shelf region (since the data were skewed to high values) and a t-distribution in the transition temperature region (since the data were normally distributed)

Ensemble-based Regional Climate Prediction: Political Impacts

Science.gov (United States)

Miguel, E.; Dykema, J.; Satyanath, S.; Anderson, J. G.

2008-12-01

Accurate forecasts of regional climate, including temperature and precipitation, have significant implications for human activities, not just economically but socially. Sub Saharan Africa is a region that has displayed an exceptional propensity for devastating civil wars. Recent research in political economy has revealed a strong statistical relationship between year to year fluctuations in precipitation and civil conflict in this region in the 1980s and 1990s. To investigate how climate change may modify the regional risk of civil conflict in the future requires a probabilistic regional forecast that explicitly accounts for the community's uncertainty in the evolution of rainfall under anthropogenic forcing. We approach the regional climate prediction aspect of this question through the application of a recently demonstrated method called generalized scalar prediction (Leroy et al. 2009), which predicts arbitrary scalar quantities of the climate system. This prediction method can predict change in any variable or linear combination of variables of the climate system averaged over a wide range spatial scales, from regional to hemispheric to global. Generalized scalar prediction utilizes an ensemble of model predictions to represent the community's uncertainty range in climate modeling in combination with a timeseries of any type of observational data that exhibits sensitivity to the scalar of interest. It is not necessary to prioritize models in deriving with the final prediction. We present the results of the application of generalized scalar prediction for regional forecasts of temperature and precipitation and Sub Saharan Africa. We utilize the climate predictions along with the established statistical relationship between year-to-year rainfall variability in Sub Saharan Africa to investigate the potential impact of climate change on civil conflict within that region.

Statistical yearbook 2002-2004. Data available as of February 2005. 49 ed

International Nuclear Information System (INIS)

2005-09-01

This is the forty-ninth issue of the United Nations Statistical Yearbook, prepared by the Statistics Division, Department of Economic and Social Affairs of the United Nations Secretariat. The data included generally cover the years between 1993 and 2003 and are, for the most part, those statistics which were available to the Statistics Division as of February 2005. The 81 tables of the Yearbook are based on data compiled by the Statistics Division from over 35 international and national sources. These sources include the United Nations Statistics Division in the fields of national accounts, industry, energy, transport and international trade, the United Nations Statistics Division and Population Division in the field of demographic statistics, and over 20 offices of the United Nations system and international organizations in other specialized fields. The Yearbook is organized in four parts. The first part, World and Region Summary, presents key world and regional aggregates and totals. In the other three parts, the subject matter is generally presented by countries or areas, with world and regional aggregates shown in some cases only. Parts two, three and four cover, respectively, population and social topics, national economic activity, and international economic relations. Each chapter ends with brief technical notes on statistical sources and methods for the tables it includes. References to sources and related methodological publications are provided at the end of the Yearbook in the section 'Statistical sources and references'. Annex I provides complete information on country and area nomenclature, and regional and other groupings used in the Yearbook. Annex II lists conversion coefficients and factors used in various tables. A list of tables added to or omitted from the last issue of the Yearbook is given in annex III. Symbols and conventions used in the Yearbook are shown in the section 'Explanatory notes, preceding the Introduction

Statistical parametric mapping of Tc-99m HMPAO SPECT cerebral perfusion in the normal elderly

International Nuclear Information System (INIS)

Turlakow, A.; Scott, A.M.; Berlangieri, S.U.; Sonkila, C.; Wardill, T.D.; Crowley, K.; Abbott, D.; Egan, G.F.; McKay, W.J.; Hughes, A.

1998-01-01

Full text: The clinical value of Tc-99m HMPAO SPECT cerebral blood flow studies in cognitive and neuropsychiatric disorders has been well described. Currently, interpretation of these studies relies on qualitative or semi- quantitative techniques. The aim of our study is to generate statistical measures of regional cerebral perfusion in the normal elderly using statistical parametric mapping (Friston et al, Wellcome Department of Cognitive Neurology, London, UK) in order to facilitate the objective analysis of cerebral blood flow studies in patient groups. A cohort of 20 healthy, elderly volunteers, aged 68 to 81 years, was prospectively selected on the basis of normal physical examination and neuropsychological testing. Subjects with risk factors, or a history of cognitive impairment were excluded from our study group. All volunteers underwent SPECT cerebral blood flow imaging, 30 minutes following the administration of 370 MBq Tc-99m HMPAO, on a Trionix Triad XLT triple-headed scanner (Trionix Research Laboratory Twinsburg, OH) using high resolution, fan-beam collimators resulting in a system resolution of 10 mm full width at half-maximum (FWHM). The SPECT cerebral blood flow studies were analysed using statistical parametric mapping (SPM) software specifically developed for the routine statistical analysis of functional neuroimaging data. The SPECT images were coregistered with each individual's T1-weighted MR volume brain scan and spatially normalized to standardised Talairach space. Using SPM, these data were analyzed for differences in interhemispheric regional cerebral blood flow. Significant asymmetry of cerebral perfusion was detected in the pre-central gyrus at the 95th percentile. In conclusion, the interpretation of cerebral blood flow studies in the elderly should take into account the statistically significant asymmetry in interhemispheric pre-central cortical blood flow. In the future, clinical studies will be compared to statistical data sets in age

Statistical parametric mapping of Tc-99m HMPAO SPECT cerebral perfusion in the normal elderly

Energy Technology Data Exchange (ETDEWEB)

Turlakow, A.; Scott, A.M.; Berlangieri, S.U.; Sonkila, C.; Wardill, T.D.; Crowley, K.; Abbott, D.; Egan, G.F.; McKay, W.J.; Hughes, A. [Austin and Repatriation Medical Centre, Heidelberg, VIC (Australia). Departments of Nuclear Medicine and Centre for PET Neurology and Clinical Neuropsychology

1998-06-01

Full text: The clinical value of Tc-99m HMPAO SPECT cerebral blood flow studies in cognitive and neuropsychiatric disorders has been well described. Currently, interpretation of these studies relies on qualitative or semi- quantitative techniques. The aim of our study is to generate statistical measures of regional cerebral perfusion in the normal elderly using statistical parametric mapping (Friston et al, Wellcome Department of Cognitive Neurology, London, UK) in order to facilitate the objective analysis of cerebral blood flow studies in patient groups. A cohort of 20 healthy, elderly volunteers, aged 68 to 81 years, was prospectively selected on the basis of normal physical examination and neuropsychological testing. Subjects with risk factors, or a history of cognitive impairment were excluded from our study group. All volunteers underwent SPECT cerebral blood flow imaging, 30 minutes following the administration of 370 MBq Tc-99m HMPAO, on a Trionix Triad XLT triple-headed scanner (Trionix Research Laboratory Twinsburg, OH) using high resolution, fan-beam collimators resulting in a system resolution of 10 mm full width at half-maximum (FWHM). The SPECT cerebral blood flow studies were analysed using statistical parametric mapping (SPM) software specifically developed for the routine statistical analysis of functional neuroimaging data. The SPECT images were coregistered with each individual`s T1-weighted MR volume brain scan and spatially normalized to standardised Talairach space. Using SPM, these data were analyzed for differences in interhemispheric regional cerebral blood flow. Significant asymmetry of cerebral perfusion was detected in the pre-central gyrus at the 95th percentile. In conclusion, the interpretation of cerebral blood flow studies in the elderly should take into account the statistically significant asymmetry in interhemispheric pre-central cortical blood flow. In the future, clinical studies will be compared to statistical data sets in age

Regional and municipal energetic statistics - Sao Paulo State - 1987

International Nuclear Information System (INIS)

1989-01-01

The main Brazilian energetic information for subsidizing planning studies in regional and municipal level are presented, including data for the year 1987 that represent the sale of the main petroleum by-product and hydrated alcohol and the electricity consumption. (C.G.C.)

New selection effect of statistical investigations of supernova remnants

International Nuclear Information System (INIS)

Allakhverdiev, A.O.; Gusejnov, O.Kh.; Kasumov, F.K.

1986-01-01

The influence of H2 regions on the parameters of Supernova remnants (SNR) is investigated. It has been shown that the projection of such regions on the SNRs leads to local changes of morphological structure of young shell-type SNRs and considerable distortions of integral parameters of evolved shell-type SNRs (with D > 10 pc) and plerions, up to their complete undetectability on the background of classical and gigantic H2 regions. A new selection effect, in fact, arises from these factors connected with additional limitations made by the real structure of the interstellar medium on the statistical investigations of SNRs. The influence of this effect on the statistical completeness of objects has been estimated

New selection effect in statistical investigations of supernova remnants

Science.gov (United States)

Allakhverdiev, A. O.; Guseinov, O. Kh.; Kasumov, F. K.

1986-01-01

The influence of H II regions on the parameters of supernova remnants (SNR) is investigated. It has been shown that the projection of such regions on the SNRs leads to: a) local changes of morphological structure of young shell-type SNRs and b) considerable distortions of integral parameters of evolved shell-type SNRs (with D > 10 pc) and plerions, up to their complete undetectability on the background of classical and gigantic H II regions. A new selection effect, in fact, arises from these factors connected with additional limitations made by the real structure of the interstellar medium on the statistical investigations of SNRs. The influence of this effect on the statistical completeness of objects has been estimated.

Level set segmentation of medical images based on local region statistics and maximum a posteriori probability.

Science.gov (United States)

Cui, Wenchao; Wang, Yi; Lei, Tao; Fan, Yangyu; Feng, Yan

2013-01-01

This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Bayes' rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.

Local sequence alignments statistics: deviations from Gumbel statistics in the rare-event tail

Directory of Open Access Journals (Sweden)

Burghardt Bernd

2007-07-01

Full Text Available Abstract Background The optimal score for ungapped local alignments of infinitely long random sequences is known to follow a Gumbel extreme value distribution. Less is known about the important case, where gaps are allowed. For this case, the distribution is only known empirically in the high-probability region, which is biologically less relevant. Results We provide a method to obtain numerically the biologically relevant rare-event tail of the distribution. The method, which has been outlined in an earlier work, is based on generating the sequences with a parametrized probability distribution, which is biased with respect to the original biological one, in the framework of Metropolis Coupled Markov Chain Monte Carlo. Here, we first present the approach in detail and evaluate the convergence of the algorithm by considering a simple test case. In the earlier work, the method was just applied to one single example case. Therefore, we consider here a large set of parameters: We study the distributions for protein alignment with different substitution matrices (BLOSUM62 and PAM250 and affine gap costs with different parameter values. In the logarithmic phase (large gap costs it was previously assumed that the Gumbel form still holds, hence the Gumbel distribution is usually used when evaluating p-values in databases. Here we show that for all cases, provided that the sequences are not too long (L > 400, a "modified" Gumbel distribution, i.e. a Gumbel distribution with an additional Gaussian factor is suitable to describe the data. We also provide a "scaling analysis" of the parameters used in the modified Gumbel distribution. Furthermore, via a comparison with BLAST parameters, we show that significance estimations change considerably when using the true distributions as presented here. Finally, we study also the distribution of the sum statistics of the k best alignments. Conclusion Our results show that the statistics of gapped and ungapped local

The outlier sample effects on multivariate statistical data processing geochemical stream sediment survey (Moghangegh region, North West of Iran)

International Nuclear Information System (INIS)

Ghanbari, Y.; Habibnia, A.; Memar, A.

2009-01-01

In geochemical stream sediment surveys in Moghangegh Region in north west of Iran, sheet 1:50,000, 152 samples were collected and after the analyze and processing of data, it revealed that Yb, Sc, Ni, Li, Eu, Cd, Co, as contents in one sample is far higher than other samples. After detecting this sample as an outlier sample, the effect of this sample on multivariate statistical data processing for destructive effects of outlier sample in geochemical exploration was investigated. Pearson and Spear man correlation coefficient methods and cluster analysis were used for multivariate studies and the scatter plot of some elements together the regression profiles are given in case of 152 and 151 samples and the results are compared. After investigation of multivariate statistical data processing results, it was realized that results of existence of outlier samples may appear as the following relations between elements: - true relation between two elements, which have no outlier frequency in the outlier sample. - false relation between two elements which one of them has outlier frequency in the outlier sample. - complete false relation between two elements which both have outlier frequency in the outlier sample

[Micro-simulation of firms' heterogeneity on pollution intensity and regional characteristics].

Science.gov (United States)

Zhao, Nan; Liu, Yi; Chen, Ji-Ning

2009-11-01

In the same industrial sector, heterogeneity of pollution intensity exists among firms. There are some errors if using sector's average pollution intensity, which are calculated by limited number of firms in environmental statistic database to represent the sector's regional economic-environmental status. Based on the production function which includes environmental depletion as input, a micro-simulation model on firms' operational decision making is proposed. Then the heterogeneity of firms' pollution intensity can be mechanically described. Taking the mechanical manufacturing sector in Deyang city, 2005 as the case, the model's parameters were estimated. And the actual COD emission intensities of environmental statistic firms can be properly matched by the simulation. The model's results also show that the regional average COD emission intensity calculated by the environmental statistic firms (0.002 6 t per 10 000 yuan fixed asset, 0.001 5 t per 10 000 yuan production value) is lower than the regional average intensity calculated by all the firms in the region (0.003 0 t per 10 000 yuan fixed asset, 0.002 3 t per 10 000 yuan production value). The difference among average intensities in the six counties is significant as well. These regional characteristics of pollution intensity attribute to the sector's inner-structure (firms' scale distribution, technology distribution) and its spatial deviation.

Effect of regional anesthesia on the success rate of external cephalic version: a systematic review and meta-analysis.

Science.gov (United States)

Goetzinger, Katherine R; Harper, Lorie M; Tuuli, Methodius G; Macones, George A; Colditz, Graham A

2011-11-01

To estimate whether the use of regional anesthesia is associated with increased success of external cephalic version. We searched MEDLINE, EMBASE, the Cochrane Library, and clinical trial registries. Electronic databases were searched from 1966 through April 2011 for published, randomized controlled trials in the English language comparing regional anesthesia with no regional anesthesia for external cephalic version. The primary outcome was external cephalic version success. Secondary outcomes included cesarean delivery, maternal discomfort, and adverse events. Pooled risk ratios (relative risk) were calculated using a random-effects model. Heterogeneity was assessed using the Cochran's Q statistic and quantified using the I Z method. Six randomized controlled trials met criteria for study inclusion. Regional anesthesia was associated with a higher external cephalic version success rate compared with intravenous or no analgesia (59.7% compared with 37.6%; pooled relative risk 1.58; 95% confidence interval [CI] 1.29-1.93). This significant association persisted when the data were stratified by type of regional anesthesia (spinal compared with epidural). The number needed to treat with regional anesthesia to achieve one additional successful external cephalic version was five. There was no evidence of statistical heterogeneity (P=.32, I Z=14.9%) or publication bias (Harbord test P=.78). There was no statistically significant difference in the risk of cesarean delivery comparing regional anesthesia with intravenous or no analgesia (48.4% compared with 59.3%; pooled relative risk 0.80; 95% CI 0.55-1.17). Adverse events were rare and not significantly different between the two groups. Regional anesthesia is associated with a higher success rate of external cephalic version.

Statistical lamb wave localization based on extreme value theory

Science.gov (United States)

Harley, Joel B.

2018-04-01

Guided wave localization methods based on delay-and-sum imaging, matched field processing, and other techniques have been designed and researched to create images that locate and describe structural damage. The maximum value of these images typically represent an estimated damage location. Yet, it is often unclear if this maximum value, or any other value in the image, is a statistically significant indicator of damage. Furthermore, there are currently few, if any, approaches to assess the statistical significance of guided wave localization images. As a result, we present statistical delay-and-sum and statistical matched field processing localization methods to create statistically significant images of damage. Our framework uses constant rate of false alarm statistics and extreme value theory to detect damage with little prior information. We demonstrate our methods with in situ guided wave data from an aluminum plate to detect two 0.75 cm diameter holes. Our results show an expected improvement in statistical significance as the number of sensors increase. With seventeen sensors, both methods successfully detect damage with statistical significance.

The economic performance of regions in the Czech Republic

Directory of Open Access Journals (Sweden)

Lenka Procházková

2013-01-01

Full Text Available Regional development in the Czech Republic contributed to the fact that at present none of the regions is significant backward compared to other. Individual regions have shown among themselves certain differences. This applies in particular to the economic performance of regions. This paper introduce results of our research. Main aim of the work was to indentify economic performace affecting factors of regions NUTS 3 in Czech Republic. It was necessary to define quantity of economic performance to meet this goal. We used them to create method of valuating economic performance of regions. We weighed quantities (e.g. GDP, unemployment rate, net disposable income according to their importance. This procedure was applied to individual regions. We determined the level of economic performance of Czech regions. We present overview of factors and using statistical methods we test their importance to the economic performance of Czech regions.

A robust statistical method for association-based eQTL analysis.

Directory of Open Access Journals (Sweden)

Ning Jiang

Full Text Available It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS is statistical inference of linkage disequilibrium (LD between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation.We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations.The analyses show that the new method confers an improved statistical power for detecting genuine genetic association in subpopulations and an effective control of spurious associations stemmed from population structure when compared with other two popularly implemented methods in the literature of GWAS.

Integrating statistical and process-based models to produce probabilistic landslide hazard at regional scale

Science.gov (United States)

Strauch, R. L.; Istanbulluoglu, E.

2017-12-01

We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.

Whole-organ and segmental stiffness measured with liver magnetic resonance elastography in healthy adults: significance of the region of interest.

Science.gov (United States)

Rusak, Grażyna; Zawada, Elżbieta; Lemanowicz, Adam; Serafin, Zbigniew

2015-04-01

MR elastography (MRE) is a recent non-invasive technique that provides in vivo data on the viscoelasticity of the liver. Since the method is not well established, several different protocols were proposed that differ in results. The aim of the study was to analyze the variability of stiffness measurements in different regions of the liver. Twenty healthy adults aged 24-45 years were recruited. The examination was performed using a mechanical excitation of 64 Hz. MRE images were fused with axial T2WI breath-hold images (thickness 10 mm, spacing 10 mm). Stiffness was measured as a mean value of each cross section of the whole liver, on a single largest cross section, in the right lobe, and in ROIs (50 pix.) placed in the center of the left lobe, segments 5/6, 7, 8, and the parahilar region. Whole-liver stiffness ranged from 1.56 to 2.75 kPa. Mean segmental stiffness differed significantly between the tested regions (range from 1.55 ± 0.28 to 2.37 ± 0.32 kPa; P < 0.0001, ANOVA). Within-method variability of measurements ranged from 14 % for whole liver and segment 8-26 % for segment 7. Within-subject variability ranged from 13 to 31 %. Results of measurement within segment 8 were closest to the whole-liver method (ICC, 0.84). Stiffness of the liver presented significant variability depending on the region of measurement. The most reproducible method is averaging of cross sections of the whole liver. There was significant variability between stiffness in subjects considered healthy, which requires further investigation.

A statistical adjustment approach for climate projections of snow conditions in mountain regions using energy balance land surface models

Science.gov (United States)

Verfaillie, Deborah; Déqué, Michel; Morin, Samuel; Lafaysse, Matthieu

2017-04-01

Projections of future climate change have been increasingly called for lately, as the reality of climate change has been gradually accepted and societies and governments have started to plan upcoming mitigation and adaptation policies. In mountain regions such as the Alps or the Pyrenees, where winter tourism and hydropower production are large contributors to the regional revenue, particular attention is brought to current and future snow availability. The question of the vulnerability of mountain ecosystems as well as the occurrence of climate-related hazards such as avalanches and debris-flows is also under consideration. In order to generate projections of snow conditions, however, downscaling global climate models (GCMs) by using regional climate models (RCMs) is not sufficient to capture the fine-scale processes and thresholds at play. In particular, the altitudinal resolution matters, since the phase of precipitation is mainly controlled by the temperature which is altitude-dependent. Simulations from GCMs and RCMs moreover suffer from biases compared to local observations, due to their rather coarse spatial and altitudinal resolution, and often provide outputs at too coarse time resolution to drive impact models. RCM simulations must therefore be adjusted using empirical-statistical downscaling and error correction methods, before they can be used to drive specific models such as energy balance land surface models. In this study, time series of hourly temperature, precipitation, wind speed, humidity, and short- and longwave radiation were generated over the Pyrenees and the French Alps for the period 1950-2100, by using a new approach (named ADAMONT for ADjustment of RCM outputs to MOuNTain regions) based on quantile mapping applied to daily data, followed by time disaggregation accounting for weather patterns selection. We first introduce a thorough evaluation of the method using using model runs from the ALADIN RCM driven by a global reanalysis over the

Birth tourism: socio-demographic and statistical aspects

Directory of Open Access Journals (Sweden)

Anatoly V. Korotkov

2016-01-01

Full Text Available The purpose of the study is to research birth tourism issue. The article gives the socio-demographic and statistical aspects of research problems of birth inbound tourism in the Russian Federation. Following the literature analysis, the degree of study for birth tourism lags behind its actual size. Currently, the media has accumulated a significant amount of information on birth tourism in Russia, that requires processing, systematization and understanding that can and should become an independent area of study of sociologists and demographers to develop recommendations for the management of socio-demographic processes in birth tourism in our country. It is necessary to identify the problems that will inevitably arise. At present, this process is almost not regulated.These problems are complex, it requires the joint efforts of sociologists and demographers. However, it is impossible to obtain reliable results and to develop management decisions without attention to the statistical aspect of this problem. It is necessary to create methodological support for collecting and information processing and model development of the birth tourism. At the initial stage it is necessary to identify the direction and objectives of the analysis to determine the factors in the development of this process, to develop a hierarchical system of statistical indicators, to receive the information, needed for calculating of specific indicators.The complex research of the birth tourism issues should be based on the methodology of sociology, demography and statistics, including statistical observation, interviews with residents, structure analysis and birth tourism concentration in the country, the analysis of the dynamics, classification of factors and reasons, the grouping of regions for the development of the studied processes and, of course, the development of economic-statistical indicators.The article reveals the problem of the significant influence of the

Application of statistical method for FBR plant transient computation

International Nuclear Information System (INIS)

Kikuchi, Norihiro; Mochizuki, Hiroyasu

2014-01-01

Highlights: • A statistical method with a large trial number up to 10,000 is applied to the plant system analysis. • A turbine trip test conducted at the “Monju” reactor is selected as a plant transient. • A reduction method of trial numbers is discussed. • The result with reduced trial number can express the base regions of the computed distribution. -- Abstract: It is obvious that design tolerances, errors included in operation, and statistical errors in empirical correlations effect on the transient behavior. The purpose of the present study is to apply above mentioned statistical errors to a plant system computation in order to evaluate the statistical distribution contained in the transient evolution. A selected computation case is the turbine trip test conducted at 40% electric power of the prototype fast reactor “Monju”. All of the heat transport systems of “Monju” are modeled with the NETFLOW++ system code which has been validated using the plant transient tests of the experimental fast reactor Joyo, and “Monju”. The effects of parameters on upper plenum temperature are confirmed by sensitivity analyses, and dominant parameters are chosen. The statistical errors are applied to each computation deck by using a pseudorandom number and the Monte-Carlo method. The dSFMT (Double precision SIMD-oriented Fast Mersenne Twister) that is developed version of Mersenne Twister (MT), is adopted as the pseudorandom number generator. In the present study, uniform random numbers are generated by dSFMT, and these random numbers are transformed to the normal distribution by the Box–Muller method. Ten thousands of different computations are performed at once. In every computation case, the steady calculation is performed for 12,000 s, and transient calculation is performed for 4000 s. In the purpose of the present statistical computation, it is important that the base regions of distribution functions should be calculated precisely. A large number of

Dynamical and statistical downscaling of precipitation and temperature in a Mediterranean area

KAUST Repository

Pizzigalli, Claudia

2012-03-28

In this paper we present and discuss a comparison between statistical and regional climate modeling techniques for downscaling GCM prediction . The comparison is carried out over the “Capitanata” region, an area of agricultural interest in south-eastern Italy, for current (1961-1990) and future (2071–2100) climate. The statistical model is based on Canonical Correlation Analysis (CCA), associated with a data pre-filtering obtained by a Principal Component Analysis (PCA), whereas the Regional Climate Model REGCM3 was used for dynamical downscaling. Downscaling techniques were applied to estimate rainfall, maximum and minimum temperatures and average number of consecutive wet and dry days. Both methods have comparable skills in estimating stations data. They show good results for spring, the most important season for agriculture. Both statistical and dynamical models reproduce the statistical properties of precipitation well, the crucial variable for the growth of crops.

The significance of Good Chair as part of children’s school and home environment in the preventive treatment of body statistics distortions

OpenAIRE

Mirosław Mrozkowiak; Hanna Żukowska

2015-01-01

Mrozkowiak Mirosław, Żukowska Hanna. Znaczenie Dobrego Krzesła, jako elementu szkolnego i domowego środowiska ucznia, w profilaktyce zaburzeń statyki postawy ciała = The significance of Good Chair as part of children’s school and home environment in the preventive treatment of body statistics distortions. Journal of Education, Health and Sport. 2015;5(7):179-215. ISSN 2391-8306. DOI 10.5281/zenodo.19832 http://ojs.ukw.edu.pl/index.php/johs/article/view/2015%3B5%287%29%3A179-215 https:...

Higher-Order Moment Characterisation of Rogue Wave Statistics in Supercontinuum Generation

DEFF Research Database (Denmark)

Sørensen, Simon Toft; Bang, Ole; Wetzel, Benjamin

2012-01-01

The noise characteristics of supercontinuum generation are characterized using higherorder statistical moments. Measures of skew and kurtosis, and the coefficient of variation allow quantitative identification of spectral regions dominated by rogue wave like behaviour.......The noise characteristics of supercontinuum generation are characterized using higherorder statistical moments. Measures of skew and kurtosis, and the coefficient of variation allow quantitative identification of spectral regions dominated by rogue wave like behaviour....

Can a significance test be genuinely Bayesian?

OpenAIRE

Pereira, Carlos A. de B.; Stern, Julio Michael; Wechsler, Sergio

2008-01-01

The Full Bayesian Significance Test, FBST, is extensively reviewed. Its test statistic, a genuine Bayesian measure of evidence, is discussed in detail. Its behavior in some problems of statistical inference like testing for independence in contingency tables is discussed.

Bölgesel Yenilik Sistemlerinde Devletin Rolü: Düzey 2 Bölgelerine İlişkin Ampirik Bir Analiz(The Role of State in Regional Innovation System: An Empirical Analysis of NUTS 2 Region

Directory of Open Access Journals (Sweden)

Gökhan DÖKMEN

2012-01-01

Full Text Available The state has a regulatory role in regional innovation systems. The regulatory role of the state in systemic approach covers a variety of areas such as building habitats for innovation and entrepreneurship, promotion of clustering and supporting innovative networks. This study examines the impact of public policies such as public investment, investment subsidies and advanced technology investment in state university on regional innovation. The relation between regional innovation and public policy tools has been tested for 1999-2008 period on 20 NUTS 2 regions by using panel DOLS (dynamic ordinary least square method. The result showed a positive and statistically significant equilibrium relation regional innovation and public expenditure. Further, investment subsidies and advanced technology investment have no significant impact on regional innovation capacity in NUTS2 regions.

A Statistical study of the Doppler spectral width of high-latitude ionospheric F-region echoes recorded with SuperDARN coherent HF radars

Directory of Open Access Journals (Sweden)

J.-P. Villain

2002-11-01

Full Text Available The HF radars of the Super Dual Auroral Radar Network (SuperDARN provide measurements of the E × B drift of ionospheric plasma over extended regions of the high-latitude ionosphere. We have conducted a statistical study of the associated Doppler spectral width of ionospheric F-region echoes. The study has been conducted with all available radars from the Northern Hemisphere for 2 specific periods of time. Period 1 corresponds to the winter months of 1994, while period 2 covers October 1996 to March 1997. The distributions of data points and average spectral width are presented as a function of Magnetic Latitude and Magnetic Local Time. The databases are very consistent and exhibit the same features. The most stringent features are: a region of very high spectral width, collocated with the ionospheric LLBL/cusp/mantle region; an oval shaped region of high spectral width, whose equator-ward boundary matches the poleward limit of the Holzworth and Meng auroral oval. A simulation has been conducted to evaluate the geometrical and instrumental effects on the spectral width. It shows that these effects cannot account for the observed spectral features. It is then concluded that these specific spectral width characteristics are the signature of ionospheric/magnetospheric coupling phenomena.Key words. Ionosphere (auroral ionosphere; ionosphere-magnetosphere interactions; ionospheric irregularities

A Statistical study of the Doppler spectral width of high-latitude ionospheric F-region echoes recorded with SuperDARN coherent HF radars

Directory of Open Access Journals (Sweden)

J.-P. Villain

Full Text Available The HF radars of the Super Dual Auroral Radar Network (SuperDARN provide measurements of the E × B drift of ionospheric plasma over extended regions of the high-latitude ionosphere. We have conducted a statistical study of the associated Doppler spectral width of ionospheric F-region echoes. The study has been conducted with all available radars from the Northern Hemisphere for 2 specific periods of time. Period 1 corresponds to the winter months of 1994, while period 2 covers October 1996 to March 1997. The distributions of data points and average spectral width are presented as a function of Magnetic Latitude and Magnetic Local Time. The databases are very consistent and exhibit the same features. The most stringent features are: a region of very high spectral width, collocated with the ionospheric LLBL/cusp/mantle region; an oval shaped region of high spectral width, whose equator-ward boundary matches the poleward limit of the Holzworth and Meng auroral oval. A simulation has been conducted to evaluate the geometrical and instrumental effects on the spectral width. It shows that these effects cannot account for the observed spectral features. It is then concluded that these specific spectral width characteristics are the signature of ionospheric/magnetospheric coupling phenomena.

Key words. Ionosphere (auroral ionosphere; ionosphere-magnetosphere interactions; ionospheric irregularities

The modified signed likelihood statistic and saddlepoint approximations

DEFF Research Database (Denmark)

Jensen, Jens Ledet

1992-01-01

SUMMARY: For a number of tests in exponential families we show that the use of a normal approximation to the modified signed likelihood ratio statistic r * is equivalent to the use of a saddlepoint approximation. This is also true in a large deviation region where the signed likelihood ratio...... statistic r is of order √ n. © 1992 Biometrika Trust....

Bias expansion of spatial statistics and approximation of differenced ...

Indian Academy of Sciences (India)

Investigations of spatial statistics, computed from lattice data in the plane, can lead to a special lattice point counting problem. The statistical goal is to expand the asymptotic expectation or large-sample bias of certain spatial covariance estimators, where this bias typically depends on the shape of a spatial sampling region.

Age differences in intercorrelations between regional cerebral metabolic rates for glucose

International Nuclear Information System (INIS)

Horwitz, B.; Duara, R.; Rapoport, S.I.

1986-01-01

Patterns of cerebral metabolic intercorrelations were compared in the resting state in 15 healthy young men (ages 20 to 32 years) and 15 healthy elderly men (ages 64 to 83 years). Controlling for whole-brain glucose metabolism, partial correlation coefficients were determined between pairs of regional cerebral metabolic rates for glucose determined by positron emission tomography using [18F]fluorodeoxyglucose and obtained in 59 brain regions. Compared with the young men, the elderly men had fewer statistically significant correlations, with the most notable reductions observed between the parietal lobe regions, and between the parietal and frontal lobe regions. These results suggest that cerebral functional interactions are reduced in healthy elderly men

Trends in incidence of lung cancer in Croatia from 2001 to 2013: gender and regional differences.

Science.gov (United States)

Siroglavić, Katarina Josipa; Polić Vižintin, Marina; Tripković, Ingrid; Šekerija, Mario; Kukulj, Suzana

2017-10-31

To provide an overview of the lung cancer incidence trends in the City of Zagreb (Zagreb), Split-Dalmatia County (SDC), and Croatia in the period from 2001 to 2013. Incidence data were obtained from the Croatian National Cancer Registry. For calculating incidence rates per 100 000 population, we used population estimates for the period 2001-2013 from the Croatian Bureau of Statistics. Age-standardized rates of lung cancer incidence were calculated by the direct standardization method using the European Standard Population. To describe incidence trends, we used joinpoint regression analysis. Joinpoint analysis showed a statistically significant decrease in lung cancer incidence in men in all regions, with an annual percentage change (APC) of -2.2% for Croatia, 1.9% for Zagreb, and -2.0% for SDC. In women, joinpoint analysis showed a statistically significant increase in the incidence for Croatia, with APC of 1.4%, a statistically significant increase of 1.0% for Zagreb, and no significant change in trend for SDC. In both genders, joinpoint analysis showed a significant decrease in age-standardized incidence rates of lung cancer, with APC of -1.3% for Croatia, -1.1% for Zagreb, and -1.6% for SDC. There was an increase in female lung cancer incidence rate and a decrease in male lung cancer incidence rate in Croatia in 2001-20013 period, with similar patterns observed in all the investigated regions. These results highlight the importance of smoking prevention and cessation policies, especially among women and young people.

Aspects of statistical model for multifragmentation

International Nuclear Information System (INIS)

Bhattacharyya, P.; Das Gupta, S.; Mekjian, A. Z.

1999-01-01

We deal with two different aspects of an exactly soluble statistical model of fragmentation. First we show, using zero range force and finite temperature Thomas-Fermi theory, that a common link can be found between finite temperature mean field theory and the statistical fragmentation model. We show the latter naturally arises in the spinodal region. Next we show that although the exact statistical model is a canonical model and uses temperature, microcanonical results which use constant energy rather than constant temperature can also be obtained from the canonical model using saddle-point approximation. The methodology is extremely simple to implement and at least in all the examples studied in this work is very accurate. (c) 1999 The American Physical Society

STATISTICAL ANALYSIS AND TRENDS OF DRY DAYS IN SYLHET REGION OF BANGLADESH

Directory of Open Access Journals (Sweden)

Syed Mustakim Ali Shah

2014-01-01

Full Text Available The rainfall distribution in Bangladesh is not uniform and refl ecting topography. Hilly Sylhet region receives substantial rainfall every year compare to other regions of Bangladesh. Though Sylhet region is less vulnerable to drought but weather pattern is not constant and changing day by day. Hence as a part of drought an alysis, behavior of dry days is important. This study focuses on dry days pattern and associ ated changes from daily records of last 54 years for Sylhet region. Monthly, yearly and seasonal variations of dry days were analyzed to check for major changes. In order to inve stigate extreme dry events, time history of monthly dry days data were transformed into fre quency domain using the Fast Fourier Transform (FFT. Variability of dry days in tim e scale was also checked from filtered signals which is very useful for drought a nalysis, agricultural development and disaster management for the north-east region of Bangladesh.

Regional projection of climate impact indices over the Mediterranean region

Science.gov (United States)

Casanueva, Ana; Frías, M.; Dolores; Herrera, Sixto; Bedia, Joaquín; San Martín, Daniel; Gutiérrez, José Manuel; Zaninovic, Ksenija

2014-05-01

Climate Impact Indices (CIIs) are being increasingly used in different socioeconomic sectors to transfer information about climate change impacts and risks to stakeholders. CIIs are typically based on different weather variables such as temperature, wind speed, precipitation or humidity and comprise, in a single index, the relevant meteorological information for the particular impact sector (in this study wildfires and tourism). This dependence on several climate variables poses important limitations to the application of statistical downscaling techniques, since physical consistency among variables is required in most cases to obtain reliable local projections. The present study assesses the suitability of the "direct" downscaling approach, in which the downscaling method is directly applied to the CII. In particular, for illustrative purposes, we consider two popular indices used in the wildfire and tourism sectors, the Fire Weather Index (FWI) and the Physiological Equivalent Temperature (PET), respectively. As an example, two case studies are analysed over two representative Mediterranean regions of interest for the EU CLIM-RUN project: continental Spain for the FWI and Croatia for the PET. Results obtained with this "direct" downscaling approach are similar to those found from the application of the statistical downscaling to the individual meteorological drivers prior to the index calculation ("component" downscaling) thus, a wider range of statistical downscaling methods could be used. As an illustration, future changes in both indices are projected by applying two direct statistical downscaling methods, analogs and linear regression, to the ECHAM5 model. Larger differences were found between the two direct statistical downscaling approaches than between the direct and the component approaches with a single downscaling method. While these examples focus on particular indices and Mediterranean regions of interest for CLIM-RUN stakeholders, the same study

Statistics for experimentalists

CERN Document Server

Cooper, B E

2014-01-01

Statistics for Experimentalists aims to provide experimental scientists with a working knowledge of statistical methods and search approaches to the analysis of data. The book first elaborates on probability and continuous probability distributions. Discussions focus on properties of continuous random variables and normal variables, independence of two random variables, central moments of a continuous distribution, prediction from a normal distribution, binomial probabilities, and multiplication of probabilities and independence. The text then examines estimation and tests of significance. Topics include estimators and estimates, expected values, minimum variance linear unbiased estimators, sufficient estimators, methods of maximum likelihood and least squares, and the test of significance method. The manuscript ponders on distribution-free tests, Poisson process and counting problems, correlation and function fitting, balanced incomplete randomized block designs and the analysis of covariance, and experiment...

Energy statistics and balances of non-OECD countries 1991-1992

International Nuclear Information System (INIS)

1994-01-01

Contains a compilation of energy production and consumption statistics for 85 non-OECD countries and regions, including developing countries, Central and Eastern European countries and the former Soviet Union. Data are expressed in original units and in common units for coal, oil, gas, electricity and heat. Historical tables for both individual countries and regions summarize data on coal, gas and electricity production and consumption since 1971. Similar data for OECD are available in the IEA publications Energy Statistics and Energy Balances of OECD Countries

Regional variation in rates of pediatric perforated appendicitis.

Science.gov (United States)

Sarda, Samir; Short, Heather L; Hockenberry, Jason M; McCarthy, Ian; Raval, Mehul V

2017-09-01

While trends in perforated appendicitis (PA) rates have been studied, regional variability in pediatric admissions for PA remains unknown. A retrospective, cross-sectional analysis of the 2006-2012 Kids' Inpatient Database was conducted to examine variation in PA admission rates by region of the United States and insurance status. PA rates were calculated and reported as per 1000 admissions in accordance with national quality measure specifications. National PA rates per 1000 admissions for 2006, 2009, and 2012 were 313.9, 279.2, and 309.1, respectively. Similarly, all regions demonstrated a statistically significant decrease in PA rates between 2006 and 2009 (pappendicitis, geographic region and insurance status appear to be associated with perforation upon presentation. Understanding regional variation in pediatric PA rates may inform health policymakers in the constantly evolving insurance coverage landscape. Level III Treatment Study - Retrospective comparative study of appendicitis presentation in children by region of the country. Copyright © 2017 Elsevier Inc. All rights reserved.

THE MILKY WAY PROJECT: A STATISTICAL STUDY OF MASSIVE STAR FORMATION ASSOCIATED WITH INFRARED BUBBLES

International Nuclear Information System (INIS)

Kendrew, S.; Robitaille, T. P.; Simpson, R.; Lintott, C. J.; Bressert, E.; Povich, M. S.; Sherman, R.; Schawinski, K.; Wolf-Chase, G.

2012-01-01

The Milky Way Project citizen science initiative recently increased the number of known infrared bubbles in the inner Galactic plane by an order of magnitude compared to previous studies. We present a detailed statistical analysis of this data set with the Red MSX Source (RMS) catalog of massive young stellar sources to investigate the association of these bubbles with massive star formation. We particularly address the question of massive triggered star formation near infrared bubbles. We find a strong positional correlation of massive young stellar objects (MYSOs) and H II regions with Milky Way Project bubbles at separations of <2 bubble radii. As bubble sizes increase, a statistically significant overdensity of massive young sources emerges in the region of the bubble rims, possibly indicating the occurrence of triggered star formation. Based on numbers of bubble-associated RMS sources, we find that 67% ± 3% of MYSOs and (ultra-)compact H II regions appear to be associated with a bubble. We estimate that approximately 22% ± 2% of massive young stars may have formed as a result of feedback from expanding H II regions. Using MYSO-bubble correlations, we serendipitously recovered the location of the recently discovered massive cluster Mercer 81, suggesting the potential of such analyses for discovery of heavily extincted distant clusters.

THE MILKY WAY PROJECT: A STATISTICAL STUDY OF MASSIVE STAR FORMATION ASSOCIATED WITH INFRARED BUBBLES

Energy Technology Data Exchange (ETDEWEB)

Kendrew, S.; Robitaille, T. P. [Max-Planck-Institut fuer Astronomie, Koenigstuhl 17, D-69117 Heidelberg (Germany); Simpson, R.; Lintott, C. J. [Department of Astrophysics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH (United Kingdom); Bressert, E. [School of Physics, University of Exeter, Stocker Road, Exeter EX4 4QL (United Kingdom); Povich, M. S. [Department of Astronomy and Astrophysics, Pennsylvania State University, 525 Davey Laboratory, University Park, PA 16802 (United States); Sherman, R. [Department of Astronomy and Astrophysics, University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637 (United States); Schawinski, K. [Yale Center for Astronomy and Astrophysics, Yale University, P.O. Box 208121, New Haven, CT 06520 (United States); Wolf-Chase, G., E-mail: kendrew@mpia.de [Astronomy Department, Adler Planetarium, 1300 S. Lake Shore Drive, Chicago, IL 60605 (United States)

2012-08-10

The Milky Way Project citizen science initiative recently increased the number of known infrared bubbles in the inner Galactic plane by an order of magnitude compared to previous studies. We present a detailed statistical analysis of this data set with the Red MSX Source (RMS) catalog of massive young stellar sources to investigate the association of these bubbles with massive star formation. We particularly address the question of massive triggered star formation near infrared bubbles. We find a strong positional correlation of massive young stellar objects (MYSOs) and H II regions with Milky Way Project bubbles at separations of <2 bubble radii. As bubble sizes increase, a statistically significant overdensity of massive young sources emerges in the region of the bubble rims, possibly indicating the occurrence of triggered star formation. Based on numbers of bubble-associated RMS sources, we find that 67% {+-} 3% of MYSOs and (ultra-)compact H II regions appear to be associated with a bubble. We estimate that approximately 22% {+-} 2% of massive young stars may have formed as a result of feedback from expanding H II regions. Using MYSO-bubble correlations, we serendipitously recovered the location of the recently discovered massive cluster Mercer 81, suggesting the potential of such analyses for discovery of heavily extincted distant clusters.

Statistical Comparison of Cloud and Aerosol Vertical Properties between Two Eastern China Regions Based on CloudSat/CALIPSO Data

Directory of Open Access Journals (Sweden)

Yujun Qiu

2017-01-01

Full Text Available The relationship between cloud and aerosol properties was investigated over two 4° × 4° adjacent regions in the south (R1 and in the north (R2 in eastern China. The CloudSat/CALIPSO data were used to extract the cloud and aerosol profiles properties. The mean value of cloud occurrence probability (COP was the highest in the mixed cloud layer (−40°C~0°C and the lowest in the warm cloud layer (>0°C. The atmospheric humidity was more statistically relevant to COP in the warm cloud layer than aerosol condition. The differences in COP between the two regions in the mixed cloud layer and ice cloud layer (<−40°C had good correlations with those in the aerosol extinction coefficient. A radar reflectivity factor greater than −10 dBZ occurred mainly in warm cloud layers and mixed cloud layers. A high-COP zone appeared in the above-0°C layer with cloud thicknesses of 2-3 km in both regions and in all the four seasons, but the distribution of the zonal layer in R2 was more continuous than that in R1, which was consistent with the higher aerosol optical thickness in R2 than in R1 in the above-0°C layer, indicating a positive correlation between aerosol and cloud probability.

Fully automated rodent brain MR image processing pipeline on a Midas server: from acquired images to region-based statistics.

Science.gov (United States)

Budin, Francois; Hoogstoel, Marion; Reynolds, Patrick; Grauer, Michael; O'Leary-Moore, Shonagh K; Oguz, Ipek

2013-01-01

Magnetic resonance imaging (MRI) of rodent brains enables study of the development and the integrity of the brain under certain conditions (alcohol, drugs etc.). However, these images are difficult to analyze for biomedical researchers with limited image processing experience. In this paper we present an image processing pipeline running on a Midas server, a web-based data storage system. It is composed of the following steps: rigid registration, skull-stripping, average computation, average parcellation, parcellation propagation to individual subjects, and computation of region-based statistics on each image. The pipeline is easy to configure and requires very little image processing knowledge. We present results obtained by processing a data set using this pipeline and demonstrate how this pipeline can be used to find differences between populations.

On two methods of statistical image analysis

NARCIS (Netherlands)

Missimer, J; Knorr, U; Maguire, RP; Herzog, H; Seitz, RJ; Tellman, L; Leenders, K.L.

1999-01-01

The computerized brain atlas (CBA) and statistical parametric mapping (SPM) are two procedures for voxel-based statistical evaluation of PET activation studies. Each includes spatial standardization of image volumes, computation of a statistic, and evaluation of its significance. In addition,

Methods for estimating low-flow statistics for Massachusetts streams

Science.gov (United States)

Ries, Kernell G.; Friesz, Paul J.

2000-01-01

streamgaging stations had from 2 to 81 years of record, with a mean record length of 37 years. The low-flow partial-record stations had from 8 to 36 streamflow measurements, with a median of 14 measurements. All basin characteristics were determined from digital map data. The basin characteristics that were statistically significant in most of the final regression equations were drainage area, the area of stratified-drift deposits per unit of stream length plus 0.1, mean basin slope, and an indicator variable that was 0 in the eastern region and 1 in the western region of Massachusetts. The equations were developed by use of weighted-least-squares regression analyses, with weights assigned proportional to the years of record and inversely proportional to the variances of the streamflow statistics for the stations. Standard errors of prediction ranged from 70.7 to 17.5 percent for the equations to predict the 7-day, 10-year low flow and 50-percent duration flow, respectively. The equations are not applicable for use in the Southeast Coastal region of the State, or where basin characteristics for the selected ungaged site are outside the ranges of those for the stations used in the regression analyses. A World Wide Web application was developed that provides streamflow statistics for data collection stations from a data base and for ungaged sites by measuring the necessary basin characteristics for the site and solving the regression equations. Output provided by the Web application for ungaged sites includes a map of the drainage-basin boundary determined for the site, the measured basin characteristics, the estimated streamflow statistics, and 90-percent prediction intervals for the estimates. An equation is provided for combining regression and correlation estimates to obtain improved estimates of the streamflow statistics for low-flow partial-record stations. An equation is also provided for combining regression and drainage-area ratio estimates to obtain improved e

Statistical analysis of seismicity and hazard estimation for Italy (mixed approach). Statistical parameters of main shocks and aftershocks in the Italian region

International Nuclear Information System (INIS)

Molchan, G.M.; Kronrod, T.L.; Dmitrieva, O.E.

1995-03-01

The catalog of earthquakes of Italy (1900-1993) is analyzed in the present work. The following problems have been considered: 1) a choice of the operating magnitude, 2) an analysis of data completeness, and 3) a grouping (in time and in space). The catalog has been separated into main shocks and aftershocks. Statistical estimations of seismicity parameters (a,b) are performed for the seismogenetic zones defined by GNDT. The non-standard elements of the analysis performed are: (a) statistical estimation and comparison of seismicity parameters under the condition of arbitrary data grouping in magnitude, time and space; (b) use of a not conventional statistical method for the aftershock identification; the method is based on the idea of optimizing two kinds of errors in the aftershock identification process; (c) use of the aftershock zones to reveal seismically- interrelated seismogenic zones. This procedure contributes to the stability of the estimation of the ''b-value'' Refs, 25 figs, tabs

Efficient detection of differentially methylated regions using DiMmeR

DEFF Research Database (Denmark)

Almeida, Diogo Marinho; Uhrenfeldt Skov, Ida; Silva, Artur

2017-01-01

in the programming language R, have no user interface, and do not offer all necessary steps to guide users from raw data all the way down to statistically significant differentially methylated regions (DMRs) and the associated genes. RESULTS: Here, we present DiMmeR (Discovery of Multiple Differentially Methylated...... Regions), the first free standalone software that interactively guides with a user-friendly graphical user interface (GUI) scientists the whole way through EWAS data analysis. It offers parallelized statistical methods for efficiently identifying DMRs in both Illumina 450K and 850K EPIC chip data. Di......MmeR computes empirical p-values through randomization tests, even for big data sets of hundreds of patients and thousands of permutations within a few minutes on a standard desktop PC. It is independent of any third-party libraries, computes regression coefficients, p-values and empirical p...

Statistics Using Just One Formula

Science.gov (United States)

Rosenthal, Jeffrey S.

2018-01-01

This article advocates that introductory statistics be taught by basing all calculations on a single simple margin-of-error formula and deriving all of the standard introductory statistical concepts (confidence intervals, significance tests, comparisons of means and proportions, etc) from that one formula. It is argued that this approach will…

Statistics Anxiety among Postgraduate Students

Science.gov (United States)

Koh, Denise; Zawi, Mohd Khairi

2014-01-01

Most postgraduate programmes, that have research components, require students to take at least one course of research statistics. Not all postgraduate programmes are science based, there are a significant number of postgraduate students who are from the social sciences that will be taking statistics courses, as they try to complete their…

Statistical analyses to support guidelines for marine avian sampling. Final report

Science.gov (United States)

Kinlan, Brian P.; Zipkin, Elise; O'Connell, Allan F.; Caldow, Chris

2012-01-01

Interest in development of offshore renewable energy facilities has led to a need for high-quality, statistically robust information on marine wildlife distributions. A practical approach is described to estimate the amount of sampling effort required to have sufficient statistical power to identify species-specific “hotspots” and “coldspots” of marine bird abundance and occurrence in an offshore environment divided into discrete spatial units (e.g., lease blocks), where “hotspots” and “coldspots” are defined relative to a reference (e.g., regional) mean abundance and/or occurrence probability for each species of interest. For example, a location with average abundance or occurrence that is three times larger the mean (3x effect size) could be defined as a “hotspot,” and a location that is three times smaller than the mean (1/3x effect size) as a “coldspot.” The choice of the effect size used to define hot and coldspots will generally depend on a combination of ecological and regulatory considerations. A method is also developed for testing the statistical significance of possible hotspots and coldspots. Both methods are illustrated with historical seabird survey data from the USGS Avian Compendium Database. Our approach consists of five main components: 1. A review of the primary scientific literature on statistical modeling of animal group size and avian count data to develop a candidate set of statistical distributions that have been used or may be useful to model seabird counts. 2. Statistical power curves for one-sample, one-tailed Monte Carlo significance tests of differences of observed small-sample means from a specified reference distribution. These curves show the power to detect "hotspots" or "coldspots" of occurrence and abundance at a range of effect sizes, given assumptions which we discuss. 3. A model selection procedure, based on maximum likelihood fits of models in the candidate set, to determine an appropriate statistical

On Improving the Quality and Interpretation of Environmental Assessments using Statistical Analysis and Geographic Information Systems

Science.gov (United States)

Karuppiah, R.; Faldi, A.; Laurenzi, I.; Usadi, A.; Venkatesh, A.

2014-12-01

An increasing number of studies are focused on assessing the environmental footprint of different products and processes, especially using life cycle assessment (LCA). This work shows how combining statistical methods and Geographic Information Systems (GIS) with environmental analyses can help improve the quality of results and their interpretation. Most environmental assessments in literature yield single numbers that characterize the environmental impact of a process/product - typically global or country averages, often unchanging in time. In this work, we show how statistical analysis and GIS can help address these limitations. For example, we demonstrate a method to separately quantify uncertainty and variability in the result of LCA models using a power generation case study. This is important for rigorous comparisons between the impacts of different processes. Another challenge is lack of data that can affect the rigor of LCAs. We have developed an approach to estimate environmental impacts of incompletely characterized processes using predictive statistical models. This method is applied to estimate unreported coal power plant emissions in several world regions. There is also a general lack of spatio-temporal characterization of the results in environmental analyses. For instance, studies that focus on water usage do not put in context where and when water is withdrawn. Through the use of hydrological modeling combined with GIS, we quantify water stress on a regional and seasonal basis to understand water supply and demand risks for multiple users. Another example where it is important to consider regional dependency of impacts is when characterizing how agricultural land occupation affects biodiversity in a region. We developed a data-driven methodology used in conjuction with GIS to determine if there is a statistically significant difference between the impacts of growing different crops on different species in various biomes of the world.

An Experience of Statistical Method Application in Forest Survey at Angara River Region in 1932

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L. N. Vashchuk

2014-10-01

Full Text Available Report of the Angara forest economic expedition of forest economic survey in 1932 on the left bank of the Angara River has been found. The survey covered a part of Krasnoyarsk Territory and Irkutsk region, a total area of 18641.8 thousand ha. The report describes technology of forest inventory and achievements that have not previously been published. The survey was conducted by statistical method, which consisted of a sample by a continuous forest inventory enumeration of trees on sample plots (SP, arranged in an array on a particular system, followed by mathematical-statistical recalculation of the sample results to the entire survey. To do this, strip finders (sights were cut in the latitudinal direction at a distance from one another at 16 km. On the hacked sights, by every 2 km, 0.1 ha (10 × 100 m SP were established. In total 32 forest inventory sights were hacked, with total length of 9931 km, which incorporated 4817 SP. The accuracy of forest resources’ inventory characteristics determining also was investigated using smaller sample plots. For this purpose, each of the SP were cut to smaller area of 0.01 ha (10 × 10 m, where independent continuous enumeration of trees was conducted, andsample trees were cut, measured and bucked to the assortments, to explore the tree stand assortment structure. At each «sample cutting area» all the trees were felled out from 44 cm and above DBH. At half of the sample plot with 5 × 10 m size, located in the eastern end, all the trees were felled out and measured from 24 cm and above DBH. Every four «sample cutting area» in the fifth, all the trees with 12 cm and above DBH were cut down and measured. According to the results of the work, a detailed description of forest resources in the whole Angara river basin, and across 17 forest exploitation areas was completed.

Regional cerebral blood flow changes in chronic polidrug abusers

International Nuclear Information System (INIS)

Quintana, J.C.; Olea, E.; Seijas, D.; Haydn, V.

2002-01-01

Chronic exposure to cocaine and other drugs are in clear association with a variety of medical complications, involving many organ systems. The Central Nervous System (CNS) is particularly sensitive to such exposures: permanent behavioral, psychiatric and neurological complications are common in this group of patients. Regional cerebral blood perfusion (rCBF) analysis has been used to study these conditions with PET and SPECT for a long time. According to the literature, it is clear that drug exposure (particularly cocaine) does produce significant changes over rCBF, nevertheless the vast majority of SPECT and some PET studies are difficult to reproduce because they were analyzed using subjective (visual) and/or ROI's to address the changes. Aim: To study the pattern of rCBF change of chronic cocaine and other drugs (polidrug) users/abusers population using brain SPECT and SPM (Statistical Parametric Mapping). Material and Methods: From a population of 163 addicted patients, 55 chronic cocaine and other drugs users/abuser were selected. A pre-treatment brain SPECT under basal conditions was performed in all of them. 99mTc-ECD was used as rCBF tracer and SPM (Statistical Parametric Mapping) as a framework to address statistically significant rCBF variations of change. The whole group was compared with a population of normal patients (both sexes, aged between 20 and 40 y.o., no history of trauma, drug exposure, neurological or psychiatric disorders). Results: Significant areas of reduced (hypoperfusion) and increased (hyperperfusion) rCBF were identified in the patients group. The hypoperfusion areas involve mainly the left insula region and the surrounding frontal and temporal lobe and a smaller area in the anterior and inferior portion of the right frontal lobe. The increased perfusion areas were identified at the left thalamus and the right fronto-parietal cortical region. Conclusion: Our results suggest that chronic cocaine exposure produce activation/damage to

Regional Growth and Unemployment: The Validity of Okun's Law for the Finnish Regions

NARCIS (Netherlands)

Kangasharju, A.; Tavera, C.; Nijkamp, P.

2012-01-01

This paper offers a concise critical overview of Okun's Law, with particular attention for its relevance in open economic systems of regions. Based on an extensive set of economic data for Finnish regions, the existence of cointegration is tested using alternative statistical methods, viz. the

Lombardy (Italy) regional energy balance: 1984-1990 statistical data

International Nuclear Information System (INIS)

Berra, P.; Di Marzio, T.

1992-01-01

After a brief explanation of the scope and key econometric elements of the energy balance analysis, this paper tables energy supply and demand data for Italy's Lombardy Region. The primary and secondary energy data are expressed in metric quantities and in equivalent calorific values and are sub-divided according to type of energy source and consuming sector. Assessments are made of the degree of reliability of the information and sources of information

Statistical Reporting Errors and Collaboration on Statistical Analyses in Psychological Science.

Science.gov (United States)

Veldkamp, Coosje L S; Nuijten, Michèle B; Dominguez-Alvarez, Linda; van Assen, Marcel A L M; Wicherts, Jelte M

2014-01-01

Statistical analysis is error prone. A best practice for researchers using statistics would therefore be to share data among co-authors, allowing double-checking of executed tasks just as co-pilots do in aviation. To document the extent to which this 'co-piloting' currently occurs in psychology, we surveyed the authors of 697 articles published in six top psychology journals and asked them whether they had collaborated on four aspects of analyzing data and reporting results, and whether the described data had been shared between the authors. We acquired responses for 49.6% of the articles and found that co-piloting on statistical analysis and reporting results is quite uncommon among psychologists, while data sharing among co-authors seems reasonably but not completely standard. We then used an automated procedure to study the prevalence of statistical reporting errors in the articles in our sample and examined the relationship between reporting errors and co-piloting. Overall, 63% of the articles contained at least one p-value that was inconsistent with the reported test statistic and the accompanying degrees of freedom, and 20% of the articles contained at least one p-value that was inconsistent to such a degree that it may have affected decisions about statistical significance. Overall, the probability that a given p-value was inconsistent was over 10%. Co-piloting was not found to be associated with reporting errors.

An analysis of marketing mix elements in the business of small and medium enterprises dealing with NWFPs in the statistical region of Belgrade

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Keča Ljiljana

2013-01-01

Full Text Available Non-wood forest products (NWFPs appear as a raw material base for a range of final products used in the pharmaceutical industry, food industry, etc. In addition, along with the expansion of organic production, the importance of the NWFPs market has drastically increased, both at the regional and international levels. The aim of this paper is the analysis of selected marketing mix elements (product, price, promotion and distribution in small and medium enterprises engaged in the purchasing, processing and marketing of NWFPs in the statistical region of Belgrade. The purpose of this research is to highlight the potential of NWFPs in commercial terms, on the basis of the knowledge obtained. The research object is the volume of purchase and marketing of the most important NWFPs in domestic and foreign markets. The research is based on a time series analysis through trend formulation, as well as the analysis of the selected marketing mix elements. An increase in the purchase of raw products can be observed over a six-year period, as a result of the enhancement in the purchase of forest fruits, while the purchase volume of other products remains largely the same. When product placement on the domestic market is concerned, an increase in the purchase of products can be observed, particularly in the last three years of the observation period, as a result of the increased placement of forest fruits on the market, while other products are subject to less fluctuation. The most common products in the statistical region of Belgrade are medicinal herbs, forest fruits and mushrooms. [Projekat Ministarstva nauke Republike Srbije, br. EVBR 37008: Održivo gazdovanje ukupnim potencijalima šuma u Republici Srbiji i br. TP 31041: Šumski zasadi u funkciji povećanja pošumljenosti Srbije

[Study on the factors impacting on early cochlear implantation between the eastern and western region of China].

Science.gov (United States)

Xiao, Hanqiong; Li, Wei; Ma, Ruixia; Gong, Zhengpeng; Shi, Haibo; Li, Huawei; Chen, Bing; Jiang, Ye; Dai, Chunfu

2015-06-01

To describe tne regional different factors which impact on early cochlear implantation in prelingual deaf children between eastern and western regions of China. The charts of 113 children who received the cochlear implantation after 24 months old were reviewed and analyzed. Forty-five of them came from the eastern region (Jiangsu, Zhejiang or Shanghai) while 68 of them came from the western region (Ningxia or Guizhou). Parental interviews were conducted to collect information regarding the factors that impact on early cochlear implantation. Result:Based on the univariate logistic regression analysis, the odds ratio (OR) value of universal newborn hearing screening (UNHS) was 5. 481, which indicated the correlation of UNHS with early cochlear implantation is significant. There was statistical difference between the 2 groups (P0. 05). The multivariate analysis indicated that the UNHS and financial burden are statistically different between the eastern and western regions (P=0. 00 and 0. 040 respectively). The UNHS and financial burden are statistically different between the eastern reinforced in the western region. In addition, the government and society should provide powerful policy and more financial support in the western region of China. The innovation of management system is also helpful to the early cochlear implantation.

Confidence Intervals: From tests of statistical significance to confidence intervals, range hypotheses and substantial effects

Directory of Open Access Journals (Sweden)

Dominic Beaulieu-Prévost

2006-03-01

Full Text Available For the last 50 years of research in quantitative social sciences, the empirical evaluation of scientific hypotheses has been based on the rejection or not of the null hypothesis. However, more than 300 articles demonstrated that this method was problematic. In summary, null hypothesis testing (NHT is unfalsifiable, its results depend directly on sample size and the null hypothesis is both improbable and not plausible. Consequently, alternatives to NHT such as confidence intervals (CI and measures of effect size are starting to be used in scientific publications. The purpose of this article is, first, to provide the conceptual tools necessary to implement an approach based on confidence intervals, and second, to briefly demonstrate why such an approach is an interesting alternative to an approach based on NHT. As demonstrated in the article, the proposed CI approach avoids most problems related to a NHT approach and can often improve the scientific and contextual relevance of the statistical interpretations by testing range hypotheses instead of a point hypothesis and by defining the minimal value of a substantial effect. The main advantage of such a CI approach is that it replaces the notion of statistical power by an easily interpretable three-value logic (probable presence of a substantial effect, probable absence of a substantial effect and probabilistic undetermination. The demonstration includes a complete example.

Statistics 101 for Radiologists.

Science.gov (United States)

Anvari, Arash; Halpern, Elkan F; Samir, Anthony E

2015-10-01

Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. © RSNA, 2015.

Preventing statistical errors in scientific journals.

NARCIS (Netherlands)

Nuijten, M.B.

2016-01-01

There is evidence for a high prevalence of statistical reporting errors in psychology and other scientific fields. These errors display a systematic preference for statistically significant results, distorting the scientific literature. There are several possible causes for this systematic error

Recent earthquake activity in Trichonis region and its tectonic significance

Directory of Open Access Journals (Sweden)

N. DELIBASIS

1977-06-01

Full Text Available SUMMARY. - The aftershock activity associated with the central Greece
(Trichonis Lake earthquake of |une-Dec. 1975, has been studied, with emphasis
on the time and magnitude distribution. It has been found that the value of b,
in Gutenberg - R i c h t e r ' s relationship was near the same for the primary as
well as the secondary or second order aftershocks of the sequences, but depends
upon the focal depth.
A correlation between the calculated focal mechanisms and the associated
stress components to the distribution pattern of meizoseismic effects as well
as to the geological structure of the seismic region was found.
The seismic region lies at the top of an anticline which was found moving
downwards, apparently due to compressional stresses.
Within the series of three earthquakes the progress of the destruction of
the buildings was observed and reported. The interest is concentrated to modern
buildings out of reinforced concrete and infill brick walls. The relatively unexpected
rather bad performance of the later case of buildings was compared to that
of the traditional small houses out of brick or stone masonry, the behaviour of
which may be considered as better from what it was expected.

Basics of statistical physics

CERN Document Server

Müller-Kirsten, Harald J W

2013-01-01

Statistics links microscopic and macroscopic phenomena, and requires for this reason a large number of microscopic elements like atoms. The results are values of maximum probability or of averaging. This introduction to statistical physics concentrates on the basic principles, and attempts to explain these in simple terms supplemented by numerous examples. These basic principles include the difference between classical and quantum statistics, a priori probabilities as related to degeneracies, the vital aspect of indistinguishability as compared with distinguishability in classical physics, the differences between conserved and non-conserved elements, the different ways of counting arrangements in the three statistics (Maxwell-Boltzmann, Fermi-Dirac, Bose-Einstein), the difference between maximization of the number of arrangements of elements, and averaging in the Darwin-Fowler method. Significant applications to solids, radiation and electrons in metals are treated in separate chapters, as well as Bose-Eins...

Renyi statistics in equilibrium statistical mechanics

International Nuclear Information System (INIS)

Parvan, A.S.; Biro, T.S.

2010-01-01

The Renyi statistics in the canonical and microcanonical ensembles is examined both in general and in particular for the ideal gas. In the microcanonical ensemble the Renyi statistics is equivalent to the Boltzmann-Gibbs statistics. By the exact analytical results for the ideal gas, it is shown that in the canonical ensemble, taking the thermodynamic limit, the Renyi statistics is also equivalent to the Boltzmann-Gibbs statistics. Furthermore it satisfies the requirements of the equilibrium thermodynamics, i.e. the thermodynamical potential of the statistical ensemble is a homogeneous function of first degree of its extensive variables of state. We conclude that the Renyi statistics arrives at the same thermodynamical relations, as those stemming from the Boltzmann-Gibbs statistics in this limit.

Utilizing Healthcare Developments, Demographic Data with Statistical Techniques to Estimate the Diarrhoea Prevalence in India.

Science.gov (United States)

Srivastava, Shweta; Vatsalya, Vatsalya; Arora, Ashoo; Arora, Kashmiri L; Karch, Robert

2012-03-22

Diarrhoea is one of the leading causes of morbidity and mortality in developing countries in Africa and South Asia such as India. Prevalence of diarrheal diseases in those countries is higher than developed western world and largely has been associated with socio-economic and sanitary conditions. However, present available data has not been sufficiently evaluated to study the role of other factors like healthcare development, population density, sex and regional influence on diarrheal prevalence pattern. Study was performed to understand the relationship of diarrheal prevalence with specific measures namely; healthcare services development, demographics, population density, socio-economic conditions, sex, and regional prevalence patterns in India. Data from Annual national health reports and other epidemiological studies were included and statistically analyzed. Our results demonstrate significant correlation of the disease prevalence pattern with certain measures like healthcare centers, population growth rate, sex and region-specific morbidity. Available information on sanitation like water supply and toilet availability and socioeconomic conditions like poverty and literacy measures could only be associated as trends of significance. This study can be valuable for improvisation of appropriate strategies focused on important measures like healthcare resources, population growth and regional significances to evaluate prevalence patterns and management of the diarrhoea locally and globally.

Statistical inference for the lifetime performance index based on generalised order statistics from exponential distribution

Science.gov (United States)

Vali Ahmadi, Mohammad; Doostparast, Mahdi; Ahmadi, Jafar

2015-04-01

In manufacturing industries, the lifetime of an item is usually characterised by a random variable X and considered to be satisfactory if X exceeds a given lower lifetime limit L. The probability of a satisfactory item is then ηL := P(X ≥ L), called conforming rate. In industrial companies, however, the lifetime performance index, proposed by Montgomery and denoted by CL, is widely used as a process capability index instead of the conforming rate. Assuming a parametric model for the random variable X, we show that there is a connection between the conforming rate and the lifetime performance index. Consequently, the statistical inferences about ηL and CL are equivalent. Hence, we restrict ourselves to statistical inference for CL based on generalised order statistics, which contains several ordered data models such as usual order statistics, progressively Type-II censored data and records. Various point and interval estimators for the parameter CL are obtained and optimal critical regions for the hypothesis testing problems concerning CL are proposed. Finally, two real data-sets on the lifetimes of insulating fluid and ball bearings, due to Nelson (1982) and Caroni (2002), respectively, and a simulated sample are analysed.

Regionally-varying and regionally-uniform electricity pricing policies compared across four usage categories

International Nuclear Information System (INIS)

Cho, Seong-Hoon; Kim, Taeyoung; Kim, Hyun Jae; Park, Kihyun; Roberts, Roland K.

2015-01-01

The objective of our research is to predict how electricity demand varies spatially between status quo regionally-uniform electricity pricing and hypothetical regionally-varying electricity pricing across usage categories. We summarize the empirical results of a case study of electricity demand in South Korea with three key findings and their related implications. First, the price elasticities of electricity demand differ across usage categories. Specifically, electricity demands for manufacturing and retail uses are price inelastic and close to unit elastic, respectively, while those for agricultural and residential uses are not statistically significant. This information is important in designing energy policy, because higher electricity prices could reduce electricity demands for manufacturing and retail uses, resulting in slower growth in those sectors. Second, spatial spillovers in electricity demand vary across uses. Understanding the spatial structure of electricity demand provides useful information to energy policy makers for anticipating changes in demand across regions via regionally-varying electricity pricing for different uses. Third, simulation results suggest that spatial variations among electricity demands by usage category under a regionally-varying electricity-pricing policy differ from those under a regionally-uniform electricity-pricing policy. Differences in spatial changes between the policies provide information for developing a realistic regionally-varying electricity-pricing policy according to usage category. - Highlights: • We compare regionally-varying and regionally-uniform electricity pricing policies. • We summarize empirical results of a case study of electricity demand in South Korea. • We confirm that spatial spillovers in electricity demands vary across different uses. • We find positive spatial spillovers in the manufacturing and residential sectors. • Our methods help policy makers evaluate regionally-varying pricing

Sensitivity study on the parameters of the regional hydrology model for the Nevada nuclear waste storage investigations

International Nuclear Information System (INIS)

Iman, R.L.; Davenport, J.M.; Waddell, R.K.; Stephens, H.P.; Leap, D.I.

1979-01-01

Statistical methodology has been applied to the investigation of the regional hydrologic systems of a large area encompassing the Nevada Test Site (NTS) as a part of the overall evaluation of the NTS for deep geologic disposal of nuclear waste. Statistical techniques including Latin hypercube sampling were used to perform a sensitivity analysis on a two-dimensional finite-element code of 16 geohydrologic zones used to model the regional ground-water flow system. The Latin hypercube sample has been modified to include correlations between corresponding variables from zone to zone. From the results of sensitivity analysis it was found that: (1) the ranking of the relative importance of input variables between locations within the same geohydrologic zone were similar, but not identical; and (2) inclusion of a correlation structure for input variables had a significant effect on the ranking of their relative importance. The significance of these results is discussed with respect to the hydrology of the region

Altered glucose metabolism in juvenile myoclonic epilepsy: a PET study with statistical parametric mapping

International Nuclear Information System (INIS)

Lim, G. C.; Kim, J. H.; Kang, J. G.; Kim, J. S.; Yeo, J. S.; Lee, S. A.; Moon, D. H

2004-01-01

Juvenile myoclonic epilepsy (JME) is a hereditary, age-dependent epilepsy syndrome, characterized by myoclonic jerks on awakening and generalized tonic-clonic seizures. Although there have been considerable studies on the mechanism to elucidate pathogenesis of JME, the accurate pathogenesis of JME remains obscure. The aim of this study was to investigate alterations of cerebral glucose metabolism in patients with JME. We studied 16 JME patients (Mean age: 22 yrs, M/F: 9/7) with brain FDG-PET and simultaneous EEG recording. On the basis of the number of generalized spike-and-wave (GSW) discharges on the 30 min EEG recording after the injection of FDG (370MBq), we classified patients into two groups (patients in group A had 10 or more GSW and group B. 9 or less). We applied the automated and objective technique of statistical parametric mapping (SPM) to the analysis of FDG-PET to determine the significant hyper- and hypometabolic regions compared with those of 19 age matched normal control subjects. We found significant hypermetabolic regions in bilateral thalamus and central portion of upper brainstem in 16 patients with JME at a statistical threshold of uncorrected P < 0.05. These changes were also shown in group A (n=8), but not in group B (n=8). Additionally, we found significant hypometabolism in bilateral, widespread cortical regions in 16 patients with JME at a threshold of uncorrected P < 0.01. Similar hypometabolic patterns were also observed in both group A and group B, being more prominent in group A. This study provides evidence for the key role of the thalamus and brainstem reticular activating system in generating spontaneous GSW discharge, which is considered as a fundamental pathogenesis underlying JME. This study also suggests that patients with JME might suffer from subtle abnormalities of cognitive and executive cortical functions

Altered glucose metabolism in juvenile myoclonic epilepsy: a PET study with statistical parametric mapping

Energy Technology Data Exchange (ETDEWEB)

Lim, G. C.; Kim, J. H.; Kang, J. G.; Kim, J. S.; Yeo, J. S.; Lee, S. A.; Moon, D. H [Asan Medical Center, Seoul (Korea, Republic of)

2004-07-01

Juvenile myoclonic epilepsy (JME) is a hereditary, age-dependent epilepsy syndrome, characterized by myoclonic jerks on awakening and generalized tonic-clonic seizures. Although there have been considerable studies on the mechanism to elucidate pathogenesis of JME, the accurate pathogenesis of JME remains obscure. The aim of this study was to investigate alterations of cerebral glucose metabolism in patients with JME. We studied 16 JME patients (Mean age: 22 yrs, M/F: 9/7) with brain FDG-PET and simultaneous EEG recording. On the basis of the number of generalized spike-and-wave (GSW) discharges on the 30 min EEG recording after the injection of FDG (370MBq), we classified patients into two groups (patients in group A had 10 or more GSW and group B. 9 or less). We applied the automated and objective technique of statistical parametric mapping (SPM) to the analysis of FDG-PET to determine the significant hyper- and hypometabolic regions compared with those of 19 age matched normal control subjects. We found significant hypermetabolic regions in bilateral thalamus and central portion of upper brainstem in 16 patients with JME at a statistical threshold of uncorrected P < 0.05. These changes were also shown in group A (n=8), but not in group B (n=8). Additionally, we found significant hypometabolism in bilateral, widespread cortical regions in 16 patients with JME at a threshold of uncorrected P < 0.01. Similar hypometabolic patterns were also observed in both group A and group B, being more prominent in group A. This study provides evidence for the key role of the thalamus and brainstem reticular activating system in generating spontaneous GSW discharge, which is considered as a fundamental pathogenesis underlying JME. This study also suggests that patients with JME might suffer from subtle abnormalities of cognitive and executive cortical functions.

Multivariate Statistical Analysis of Water Quality data in Indian River Lagoon, Florida

Science.gov (United States)

Sayemuzzaman, M.; Ye, M.

2015-12-01

The Indian River Lagoon, is part of the longest barrier island complex in the United States, is a region of particular concern to the environmental scientist because of the rapid rate of human development throughout the region and the geographical position in between the colder temperate zone and warmer sub-tropical zone. Thus, the surface water quality analysis in this region always brings the newer information. In this present study, multivariate statistical procedures were applied to analyze the spatial and temporal water quality in the Indian River Lagoon over the period 1998-2013. Twelve parameters have been analyzed on twelve key water monitoring stations in and beside the lagoon on monthly datasets (total of 27,648 observations). The dataset was treated using cluster analysis (CA), principle component analysis (PCA) and non-parametric trend analysis. The CA was used to cluster twelve monitoring stations into four groups, with stations on the similar surrounding characteristics being in the same group. The PCA was then applied to the similar groups to find the important water quality parameters. The principal components (PCs), PC1 to PC5 was considered based on the explained cumulative variances 75% to 85% in each cluster groups. Nutrient species (phosphorus and nitrogen), salinity, specific conductivity and erosion factors (TSS, Turbidity) were major variables involved in the construction of the PCs. Statistical significant positive or negative trends and the abrupt trend shift were detected applying Mann-Kendall trend test and Sequential Mann-Kendall (SQMK), for each individual stations for the important water quality parameters. Land use land cover change pattern, local anthropogenic activities and extreme climate such as drought might be associated with these trends. This study presents the multivariate statistical assessment in order to get better information about the quality of surface water. Thus, effective pollution control/management of the surface

Regional differences of consumer preferences when shopping for regional products

Directory of Open Access Journals (Sweden)

Jitka Kalábová

2013-01-01

Full Text Available This paper presents partial results of a research on consumer preferences when shopping for groceries. It is focused on regional products and consumer preferences in relation to the country of origin of food products. The main objective of this paper is to find the existence of spatial relationships between spatial deployment of regional products and consumer preferences for regional products. It will be necessary to create a data model for monitoring the deployment of regional products and also a data model for tracking important indicators of consumer behavior in all regions of the Czech Republic. The results are based on questionnaire survey that was conducted within the period from October 2010 to January 2011 on a sample of 3767 respondents from the Czech Republic, via both online questionnaires and their printed version. For the data collection the questionnaire system ReLa, developed by the Department of Marketing and Trade at Faculty of Business and Economics at Mendel University in Brno, was used. Data was processed with statistical software STATISTICA (ver. 10. Spatial visualisation was processed with GIS software ArcGIS (ver. 10.1. Preferences for food of Czech origin were analysed in relation to identification criteria. The research results show that the origin of food has an important role in consumer purchase decision-making. There is no significant difference in importance of this factor based on gender of consumers, however, we could prove moderate dependence on respondent’s occupation, education and age. We could also experience regional differences in levels of preferences of local products or products of Czech origin in regard of 14 regions of the Czech Republic. χ2 (N = 3767 = 245.25; p < 0.001. Value of Pearson’s coefficient of contingency is 0.334.

Normal development of the muscular region of the interventricular septum--I. The significance of the ventricular trabeculations.

Science.gov (United States)

Contreras-Ramos, A; Sánchez-Gómez, C; García-Romero, H L; Cimarosti, L O

2008-10-01

The structures that participate in normal ventricular septation, and to what extent they do so, are questions not yet clarified. Even less is known about how much each of the embryonic structures contributes to the topography of the mature interventricular septum (IVS). The aim of the present paper is to investigate the significance of ventricular trabeculations in the normal development of the muscular region (the middle and apical thirds) of the IVS and to determine the direction in which it grows during cardiac septation. Anatomical studies and in vivo labelling were carried out in chicken embryo hearts at stage 18HH, tracing the labels up to stage 36HH. We analysed the results by measuring the distance between the labelled structures at the beginning and end of the experiments. We demonstrate that the muscular region of the septum originates by the fusion of the ventricular trabeculations with evidence that during cardiac development, the IVS as well as the ventricular cavities grow in opposite direction to the atria.

[Characteristic and clinical significance of DNA methyltransferase 3B overexpression in endometrial carcinoma].

Science.gov (United States)

Dong, Y; Zhou, M; Ba, X J; Si, J W; Li, W T; Wang, Y; Li, D; Li, T

2016-10-18

To determine the clinicopathological significance of the DNA methyltransferase 3B (DNMT3B) overexpression in endometrial carcinomas and to evaluate its correlation with hormone receptor status. Immunohistochemistry was performed to assess the expression of DNMT3B and hormone receptors in 104 endometrial carcinomas. DNMT3B overexpression occurred frequently in endometrioid carcinoma (EC, 54.8%) more than in nonendometrioid carcinoma (NEC, 30.0%) with statistical significance (P=0.028). Furthermore, there was a trend that EC with worse clinico-pathological variables and shorter survival had a higher DNMT3B expression, and the correlation between DNMT3B and tumor grade reached statistical significance (P=0.019).A negative correlation between DNMT3B and estrogen receptor (ER) or progesterone receptor (PR) expression was found in EC. NMT3B overexpression occurred frequently in the ER or PR negative subgroups (78.9%, 86.7%) more than in the positive subgroups (47.7%, 47.8%) with statistical significance (P=0.016, P=0.006). In addition, the DNMT3B overexpression increased in tumors with both ER and PR negative expression (92.9%, P=0.002). However, no such correlation was found in NEC (P>0.05). Sequence analyses demonstrated multiple ER and PR binding sites in the promoter regions of DNMT3B gene. This study showed that the expression of DNMT3B in EC and NEC was different. DNMT3B overexpression in EC was associated with the worse clinicopathological variables and might have predictive value. The methylation status of EC and NEC maybe different. In addition, in EC, DNMT3B overexpression negatively correlated with ER or PR expression. In NEC, the correlation between DNMT3B and ER or PR status was not present.

Revisiting regional flood frequency analysis in Slovakia: the region-of-influence method vs. traditional regional approaches

Science.gov (United States)

Gaál, Ladislav; Kohnová, Silvia; Szolgay, Ján.

2010-05-01

During the last 10-15 years, the Slovak hydrologists and water resources managers have been devoting considerable efforts to develop statistical tools for modelling probabilities of flood occurrence in a regional context. Initially, these models followed concepts to regional flood frequency analysis that were based on fixed regions, later the Hosking and Wallis's (HW; 1997) theory was adopted and modified. Nevertheless, it turned out to be that delineating homogeneous regions using these approaches is not a straightforward task, mostly due to the complex orography of the country. In this poster we aim at revisiting flood frequency analyses so far accomplished for Slovakia by adopting one of the pooling approaches, i.e. the region-of-influence (ROI) approach (Burn, 1990). In the ROI approach, unique pooling groups of similar sites are defined for each site under study. The similarity of sites is defined through Euclidean distance in the space of site attributes that had also proved applicability in former cluster analyses: catchment area, afforested area, hydrogeological catchment index and the mean annual precipitation. The homogeneity of the proposed pooling groups is evaluated by the built-in homogeneity test by Lu and Stedinger (1992). Two alternatives of the ROI approach are examined: in the first one the target size of the pooling groups is adjusted to the target return period T of the estimated flood quantiles, while in the other one, the target size is fixed, regardless of the target T. The statistical models of the ROI approach are inter-compared by the conventional regionalization approach based on the HW methodology where the parameters of flood frequency distributions were derived by means of L-moment statistics and a regional formula for the estimation of the index flood was derived by multiple regression methods using physiographic and climatic catchment characteristics. The inter-comparison of different frequency models is evaluated by means of the

Statistical evaluation of PCDD/Fs levels and profiles in milk and feedingstuffs from Campania region - Italy

Energy Technology Data Exchange (ETDEWEB)

Diletti, G.; Scortichini, G.; Conte, A.; Migliorati, G.; Caporale, V. [Ist. Zooprofilattico Sperimentale dell' Abruzzo e del Molise (Italy)

2004-09-15

PCDD/Fs levels exceeding the European Union (EU) tolerance limit were detected in milk and animal feed samples collected in Campania region in the years 2001-2003, as reported in a previous paper1. The analyses were performed on milk samples from different animal species (cow, sheep, goat and buffalo) and on animal feed samples (silage, hay, grass, cereals, premixes and mixed feeds) permitting to assess the levels and the geographical extension of the contamination. The preliminary results of this survey had given clear indications of the dioxin contamination of feedingstuffs and their contribution to the high PCDD/Fs levels recorded in milk but a more detailed analysis was needed in order to confirm the previous observations. Aim of this work is the evaluation of the correlation between the PCDD/Fs levels and patterns found in milk and animal feed samples through the statistical analysis of the congeners profiles and concentrations. Moreover, the typical congeners profiles of milk samples taken in the area under investigation were compared to those obtained from samples collected in the framework of the National Residues Surveillance Plan (NRSP) in 2003. The contamination phenomenon was also studied by means of the spatial correlation analysis.

Long term precipitation trends and variability within the Mediterranean region

Directory of Open Access Journals (Sweden)

C. M. Philandras

2011-12-01

Full Text Available In this study, the trends and variability of annual precipitation totals and annual rain days over land within the Mediterranean region are analyzed. Long term ground-based observations concerning, on one hand, monthly precipitation totals (1900–2010 and rain days (1965–2010 from 40 meteorological stations within the Mediterranean region were obtained from the Hellenic National Meteorological Service and the World Climate Data and Monitoring Programme (WCDMP of the World Meteorological Organization. On the other hand, high spatial resolution (0.5° × 0.5° gridded monthly data CRU TS 3.1 were acquired from the Climatic Research Unit, University of East Anglia, for the period 1901–2009. The two datasets were compared by means of trends and variability, while the influence of the North Atlantic Oscillation (NAO in the Mediterranean precipitation was examined. In the process, the climatic changes in the precipitation regime between the period 1961–1990 (reference period and the period 2071–2100 (future climate were presented using climate model simulations (RACMO2.1/KNMI. The future climate projections were based on SRES A1B.

The findings of the analysis showed that statistically significant (95% confidence level negative trends of the annual precipitation totals exist in the majority of Mediterranean regions during the period 1901–2009, with an exception of northern Africa, southern Italy and western Iberian peninsula, where slight positive trends (not statistically significant at 95% CL appear. Concerning the annual number of rain days, a pronounced decrease of 20 %, statistically significant (95% confidence level, appears in representative meteorological stations of east Mediterranean, while the trends are insignificant for west and central Mediterranean. Additionally, NAO index was found to be anticorrelated with the precipitation totals and the number of rain days mainly in Spain, southern France, Italy and Greece. These

Statistics: a Bayesian perspective

National Research Council Canada - National Science Library

Berry, Donald A

1996-01-01

...: it is the only introductory textbook based on Bayesian ideas, it combines concepts and methods, it presents statistics as a means of integrating data into the significant process, it develops ideas...

Model Accuracy Comparison for High Resolution Insar Coherence Statistics Over Urban Areas

Science.gov (United States)

Zhang, Yue; Fu, Kun; Sun, Xian; Xu, Guangluan; Wang, Hongqi

2016-06-01

The interferometric coherence map derived from the cross-correlation of two complex registered synthetic aperture radar (SAR) images is the reflection of imaged targets. In many applications, it can act as an independent information source, or give additional information complementary to the intensity image. Specially, the statistical properties of the coherence are of great importance in land cover classification, segmentation and change detection. However, compared to the amount of work on the statistical characters of SAR intensity, there are quite fewer researches on interferometric SAR (InSAR) coherence statistics. And to our knowledge, all of the existing work that focuses on InSAR coherence statistics, models the coherence with Gaussian distribution with no discrimination on data resolutions or scene types. But the properties of coherence may be different for different data resolutions and scene types. In this paper, we investigate on the coherence statistics for high resolution data over urban areas, by making a comparison of the accuracy of several typical statistical models. Four typical land classes including buildings, trees, shadow and roads are selected as the representatives of urban areas. Firstly, several regions are selected from the coherence map manually and labelled with their corresponding classes respectively. Then we try to model the statistics of the pixel coherence for each type of region, with different models including Gaussian, Rayleigh, Weibull, Beta and Nakagami. Finally, we evaluate the model accuracy for each type of region. The experiments on TanDEM-X data show that the Beta model has a better performance than other distributions.

MODEL ACCURACY COMPARISON FOR HIGH RESOLUTION INSAR COHERENCE STATISTICS OVER URBAN AREAS

Directory of Open Access Journals (Sweden)

Y. Zhang

2016-06-01

Full Text Available The interferometric coherence map derived from the cross-correlation of two complex registered synthetic aperture radar (SAR images is the reflection of imaged targets. In many applications, it can act as an independent information source, or give additional information complementary to the intensity image. Specially, the statistical properties of the coherence are of great importance in land cover classification, segmentation and change detection. However, compared to the amount of work on the statistical characters of SAR intensity, there are quite fewer researches on interferometric SAR (InSAR coherence statistics. And to our knowledge, all of the existing work that focuses on InSAR coherence statistics, models the coherence with Gaussian distribution with no discrimination on data resolutions or scene types. But the properties of coherence may be different for different data resolutions and scene types. In this paper, we investigate on the coherence statistics for high resolution data over urban areas, by making a comparison of the accuracy of several typical statistical models. Four typical land classes including buildings, trees, shadow and roads are selected as the representatives of urban areas. Firstly, several regions are selected from the coherence map manually and labelled with their corresponding classes respectively. Then we try to model the statistics of the pixel coherence for each type of region, with different models including Gaussian, Rayleigh, Weibull, Beta and Nakagami. Finally, we evaluate the model accuracy for each type of region. The experiments on TanDEM-X data show that the Beta model has a better performance than other distributions.

Asian/Australian region intercalibration and intercomparison programme for radon: statistical analysis and propagation of uncertainity protocols for scintillation cells of the reference laboratory

International Nuclear Information System (INIS)

Gan, T.H.; Solomon, S.B.; Peggie, J.R.

1990-01-01

A series of intercomparison for radon was orgarnized by the Australian Radiation Laboratory (ARL) for twenty-eight laboratories from nine countries in the Asian/Australasian region. Methodology, results of intercalibration and statistical analysis for the four groups of NEW scintillation cells are described. The variability in the calibration factor of 3.4% for one standard deviation for the NEW set of cells, compared with 5.7% for the OECD cells indicates that the NEW cells measurements give greater consistency to the results. 5 refs., 2 tabs, 1 fig

Thermodynamic properties of particles with intermediate statistics

International Nuclear Information System (INIS)

Joyce, G.S.; Sarkar, S.; Spal/ek, J.; Byczuk, K.

1996-01-01

Analytic expressions for the distribution function of an ideal gas of particles (exclusons) which have statistics intermediate between Fermi-Dirac and Bose-Einstein are obtained for all values of the Haldane statistics parameter α element-of[0,1]. The analytic structure of the distribution function is investigated and found to have no singularities in the physical region when the parameter α lies in the range 0 V of the D-dimensional excluson gas. The low-temperature series for the thermodynamic properties illustrate the pseudofermion nature of exclusons. copyright 1996 The American Physical Society

Field-aligned current signatures in the near-tail region. 2. Coupling between the region 1 and region 2 systems

International Nuclear Information System (INIS)

Ohtani, S.; Kokubun, S.; Nakamura, R.; Elphic, R.C.; Russell, C.T.; Baker, D.N.

1990-01-01

The development of the substorm-associated current system in the near-tail region is examined in the light of both experiment and theory. First, the March 28, 1979, event is examined intensively by using ground magnetometer data and satellite magnetic field and energetic particle data. The comparison of field-aligned current signatures at geosynchronous altitude and in the near-tail region indicates that the development of the region 1 system is not merely the enhancement in current intensity of the pre-existing system. This finding is consistent with the so-called current wedge model, in which the tail current is converted into a pair of field-aligned currents with the region 1 polarity at substorm onsets. Detailed inspection, however, suggests that the region 2 system is as important as the region 1 system. Statistical properties of the azimuthal magnetic component at synchronous orbit indicate that the deviation during disturbed periods is larger than expected from the enhancement of the region 1 current. These individual and statistical studies suggest that the region 2 system tends to develop in the synchronous region and that the coupling between the region 1 and the region 2 systems is important. The current closure in the magnetosphere is discussed from a viewpoint of the macroscopic behavior of plasma. It is suggested that the dawnside and the duskside region 2 currents are closed in the magnetosphere by the curvature current during the growth phase and by the magnetic gradient current during the expansion phase. The field-aligned currents of the region 1 and the region 2 systems are closed in the ionosphere by the Pedersen current. Consequently, the energy is dissipated as the Joule heating and this energy must be supplied from the magnetosphere. Therefore, the counter part of the Pedersen current, which closes the region 1 and the region 2 currents in magnetosphere, must be the dynamo current

Statistical Analysis and Evaluation of the Depth of the Ruts on Lithuanian State Significance Roads

Directory of Open Access Journals (Sweden)

Erinijus Getautis

2011-04-01

Full Text Available The aim of this work is to gather information about the national flexible pavement roads ruts depth, to determine its statistical dispersijon index and to determine their validity for needed requirements. Analysis of scientific works of ruts apearance in the asphalt and their influence for driving is presented in this work. Dynamical models of ruts in asphalt are presented in the work as well. Experimental outcome data of rut depth dispersijon in the national highway of Lithuania Vilnius – Kaunas is prepared. Conclusions are formulated and presented. Article in Lithuanian

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 2: Assessing the influence of vapor wall losses

OpenAIRE

Cappa, Christopher D.; Jathar, Shantanu H.; Kleeman, Michael J.; Docherty, Kenneth S.; Jimenez, Jose L.; Seinfeld, John H.; Wexler, Anthony S.

2016-01-01

The influence of losses of organic vapors to chamber walls during secondary organic aerosol (SOA) formation experiments has recently been established. Here, the influence of such losses on simulated ambient SOA concentrations and properties is assessed in the UCD/CIT regional air quality model using the statistical oxidation model (SOM) for SOA. The SOM was fit to laboratory chamber data both with and without accounting for vapor wall losses following the approa...

E-health: Determinants, opportunities, challenges and the way forward for countries in the WHO African Region

Directory of Open Access Journals (Sweden)

Gatwiri Doris

2005-12-01

Full Text Available Abstract Background The implementation of the 58th World Health Assembly resolution on e-health will pose a major challenge for the Member States of the World Health Organization (WHO African Region due to lack of information and communications technology (ICT and mass Internet connectivity, compounded by a paucity of ICT-related knowledge and skills. The key objectives of this article are to: (i explore the key determinants of personal computers (PCs, telephone mainline and cellular and Internet penetration/connectivity in the African Region; and (ii to propose actions needed to create an enabling environment for e-health services growth and utilization in the Region. Methods The effects of school enrolment, per capita income and governance variables on the number of PCs, telephone mainlines, cellular phone subscribers and Internet users were estimated using a double-log regression model and cross-sectional data on various Member States in the African Region. The analysis was based on 45 of the 46 countries that comprise the Region. The data were obtained from the United Nations Development Programme (UNDP, the World Bank and the International Telecommunications Union (ITU sources. Results There were a number of main findings: (i the adult literacy and total number of Internet users had a statistically significant (at 5% level in a t-distribution test positive effect on the number of PCs in a country; (ii the combined school enrolment rate and per capita income had a statistically significant direct effect on the number of telephone mainlines and cellular telephone subscribers; (iii the regulatory quality had statistically significant negative effect on the number of telephone mainlines; (iv similarly, the combined school enrolment ratio and the number of telephone mainlines had a statistically significant positive relationship with Internet usage; and (v there were major inequalities in ICT connectivity between upper-middle, lower-middle and

Regional and global significance of nuclear energy

International Nuclear Information System (INIS)

Schilling, H.D.

1995-01-01

Measures to combat poverty and improve the standard of living in countries of the Third World will inevitably boost global demand for energy, and energy conservation measures will not be able to offset this increase. Nuclear energy will regain significance in the framework of approaches adopted to resolve the energy problem, which primarily is an ecologic problem created by an extremely large flow of materials. The extraordinarily high energy density of nuclear fuels can contribute to markedly reduce the flow of materials; and at that, electric energy is an efficient substitute for primary energy forms. Thus nuclear electricity generation is of double benefit to the ecology. Engineering goals in nuclear technology thus gain a service aspect, with progress in power plant engineering and design aiming not only at enhanced engineered safety, but also at regaining public acceptance of and confidence in nuclear power plant technology. (orig./UA) [de

Statistical image analysis of cerebral blood flow in moyamoya disease

International Nuclear Information System (INIS)

Yamada, Masaru; Yuzawa, Izumi; Suzuki, Sachio; Kurata, Akira; Fujii, Kiyotaka; Asano, Yuji

2007-01-01

The Summary of this study was to investigate pathophysiology of moyamoya disease, we analyzed brain single photon emission tomography (SPECT) images of patients with this disease by using interface software for a 3-dimensional (3D) data extraction format. Presenting symptoms were transient ischemic attack (TIA) in 21 patients and hemorrhage in 6 patients. All the patients underwent brain SPECT scan of 123 I-iofetamine (IMP) at rest and after acetazolamide challenge (17 mg/kg iv, 2-day method). Cerebral blood flow (CBF) was quantitatively measured using arterial blood sampling and an autoradiography model. The group of the patients who presented with TIAs showed decreased CBF in the frontal lobe at rest compared to that of patients with hemorrhage, but Z-score ((mean-patient data)/ standard deviation (SD)) did not reach statistical significance. Significant CBF decrease after acetazolamide challenge was observed in a wider cerebral cortical area in the TIA group than in the hemorrhagic group. The brain region of hemodynamic ischemia (stage II) correlated well with the responsible cortical area for clinical symptoms of TIA. A hemodynamic ischemia stage image clearly represented recovery of reserve capacity after bypass surgery. Statistical evaluation of SPECT may be useful to understand and clarify the pathophysiology of this disease. (author)

Identifying Statistical Dependence in Genomic Sequences via Mutual Information Estimates

Directory of Open Access Journals (Sweden)

Wojciech Szpankowski

2007-12-01

Full Text Available Questions of understanding and quantifying the representation and amount of information in organisms have become a central part of biological research, as they potentially hold the key to fundamental advances. In this paper, we demonstrate the use of information-theoretic tools for the task of identifying segments of biomolecules (DNA or RNA that are statistically correlated. We develop a precise and reliable methodology, based on the notion of mutual information, for finding and extracting statistical as well as structural dependencies. A simple threshold function is defined, and its use in quantifying the level of significance of dependencies between biological segments is explored. These tools are used in two specific applications. First, they are used for the identification of correlations between different parts of the maize zmSRp32 gene. There, we find significant dependencies between the 5′ untranslated region in zmSRp32 and its alternatively spliced exons. This observation may indicate the presence of as-yet unknown alternative splicing mechanisms or structural scaffolds. Second, using data from the FBI's combined DNA index system (CODIS, we demonstrate that our approach is particularly well suited for the problem of discovering short tandem repeats—an application of importance in genetic profiling.

Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

Science.gov (United States)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2017-03-01

We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry.

GIA Model Statistics for GRACE Hydrology, Cryosphere, and Ocean Science

Science.gov (United States)

Caron, L.; Ivins, E. R.; Larour, E.; Adhikari, S.; Nilsson, J.; Blewitt, G.

2018-03-01

We provide a new analysis of glacial isostatic adjustment (GIA) with the goal of assembling the model uncertainty statistics required for rigorously extracting trends in surface mass from the Gravity Recovery and Climate Experiment (GRACE) mission. Such statistics are essential for deciphering sea level, ocean mass, and hydrological changes because the latter signals can be relatively small (≤2 mm/yr water height equivalent) over very large regions, such as major ocean basins and watersheds. With abundant new >7 year continuous measurements of vertical land motion (VLM) reported by Global Positioning System stations on bedrock and new relative sea level records, our new statistical evaluation of GIA uncertainties incorporates Bayesian methodologies. A unique aspect of the method is that both the ice history and 1-D Earth structure vary through a total of 128,000 forward models. We find that best fit models poorly capture the statistical inferences needed to correctly invert for lower mantle viscosity and that GIA uncertainty exceeds the uncertainty ascribed to trends from 14 years of GRACE data in polar regions.

Statistical analysis of hydrologic data for Yucca Mountain

International Nuclear Information System (INIS)

Rutherford, B.M.; Hall, I.J.; Peters, R.R.; Easterling, R.G.; Klavetter, E.A.

1992-02-01

The geologic formations in the unsaturated zone at Yucca Mountain are currently being studied as the host rock for a potential radioactive waste repository. Data from several drill holes have been collected to provide the preliminary information needed for planning site characterization for the Yucca Mountain Project. Hydrologic properties have been measured on the core samples and the variables analyzed here are thought to be important in the determination of groundwater travel times. This report presents a statistical analysis of four hydrologic variables: saturated-matrix hydraulic conductivity, maximum moisture content, suction head, and calculated groundwater travel time. It is important to modelers to have as much information about the distribution of values of these variables as can be obtained from the data. The approach taken in this investigation is to (1) identify regions at the Yucca Mountain site that, according to the data, are distinctly different; (2) estimate the means and variances within these regions; (3) examine the relationships among the variables; and (4) investigate alternative statistical methods that might be applicable when more data become available. The five different functional stratigraphic units at three different locations are compared and grouped into relatively homogeneous regions. Within these regions, the expected values and variances associated with core samples of different sizes are estimated. The results provide a rough estimate of the distribution of hydrologic variables for small core sections within each region

Linking the Lusi mud eruption dynamics with regional and global seismic activity: a statistical analysis.

Science.gov (United States)

Collignon, Marine; Hammer, Øyvind; Fallahi, Mohammad J.; Lupi, Matteo; Schmid, Daniel W.; Alwi, Husein; Hadi, Soffian; Mazzini, Adriano

2017-04-01

The 29th May 2006, gas water and mud breccia started to erupt at several localities along the Watukosek fault system in the Sidoarjo Regency in East Java Indonesia. The most prominent eruption site, named Lusi, is still active and the emitted material now covers a surface of nearly 7 km2, resulting in the displacement of 60.000 people (up to date). Due to its social and economic impacts, as well as its spectacular dimensions, the Lusi eruption still attracts the attention of international media and scientists. In the framework of the Lusi Lab project (ERC grant n° 308126), many efforts were made to develop a quasi-constant monitoring of the site and the regional areas. Several studies attempted to predict the flow rate evolution or ground deformation, resulting in either overestimating or underestimating the longevity of the eruption. Models have failed because Lusi is not a mud volcano but a sedimentary hosted hydrothermal system that became apparent after the M6.3 Yogyakarta earthquake. Another reason is because such models usually assume that the flow will decrease pacing the overpressure reduction during the deflation of the chamber. These models typically consider a closed system with a unique chamber that is not being recharged. Overall the flow rate has decreased over the past ten years, although it has been largely fluctuating with monthly periods of higher mud breccia discharge. Monitoring of the eruption has revealed that numerous anomalous events are temporally linked to punctual events such as earthquakes or volcanic eruptions. Nevertheless, the quantification of these events has never been investigated in details. In this study, we present a compilation of anomalous events observed at the Lusi site during the last 10 years. Using Monte Carlo simulations, we then statistically compare the displacement, recorded at different seismic stations around Lusi, with the regional and global earthquakes catalogue to test the probability that an earthquake

HYPE: a WFD tool for the identification of significant and sustained upward trends in groundwater time series

Science.gov (United States)

Lopez, Benjamin; Croiset, Nolwenn; Laurence, Gourcy

2014-05-01

The Water Framework Directive 2006/11/CE (WFD) on the protection of groundwater against pollution and deterioration asks Member States to identify significant and sustained upward trends in all bodies or groups of bodies of groundwater that are characterised as being at risk in accordance with Annex II to Directive 2000/60/EC. The Directive indicates that the procedure for the identification of significant and sustained upward trends must be based on a statistical method. Moreover, for significant increases of concentrations of pollutants, trend reversals are identified as being necessary. This means to be able to identify significant trend reversals. A specific tool, named HYPE, has been developed in order to help stakeholders working on groundwater trend assessment. The R encoded tool HYPE provides statistical analysis of groundwater time series. It follows several studies on the relevancy of the use of statistical tests on groundwater data series (Lopez et al., 2011) and other case studies on the thematic (Bourgine et al., 2012). It integrates the most powerful and robust statistical tests for hydrogeological applications. HYPE is linked to the French national database on groundwater data (ADES). So monitoring data gathered by the Water Agencies can be directly processed. HYPE has two main modules: - a characterisation module, which allows to visualize time series. HYPE calculates the main statistical characteristics and provides graphical representations; - a trend module, which identifies significant breaks, trends and trend reversals in time series, providing result table and graphical representation (cf figure). Additional modules are also implemented to identify regional and seasonal trends and to sample time series in a relevant way. HYPE has been used successfully in 2012 by the French Water Agencies to satisfy requirements of the WFD, concerning characterization of groundwater bodies' qualitative status and evaluation of the risk of non-achievement of

The prognostic significance of tracheostomy in carcinoma of the larynx treated with radiotherapy and surgery for salvage

International Nuclear Information System (INIS)

MacKenzie, Robert; Franssen, Edmee; Balogh, Judith; Birt, Derek; Gilbert, Ralph

1998-01-01

Purpose: To determine retrospectively the prognostic significance of airway compromise necessitating tracheostomy in carcinoma of the larynx managed with radical radiotherapy and surgery for salvage (RRSS). Methods and Materials: The charts of 270 patients managed with RRSS at the Toronto-Sunnybrook Regional Cancer Centre between June 1980 and December 1990 were reviewed. Airway compromise necessitating tracheostomy was documented in 26 patients prior to radiotherapy and 3 patients during radiotherapy. Of 29, 27 had T3T4 primaries. Patients have been followed for a median of 5 years. Results: Patients managed without tracheostomy had a 2-year disease-free survival of 74% compared to 41% for those managed with tracheostomy. The adverse impact of airway compromise was more marked in patients with glottic primaries (78% vs. 32%, p = 0.0001) than those with supraglottic primaries (64% vs. 47%, p = 0.18). Tracheostomy was identified in univariate analysis, but not in multivariate analysis, as having a statistically significant impact on local control and local-regional control. Radiotherapy controlled disease above the clavicles in 185 of 267 (69%) evaluable patients. 83% of isolated local-regional failures underwent salvage surgery. Among those managed without tracheostomy, ultimate local-regional control (LRC) was achieved in 161 (94%) of 172 glottic primaries and 54 (81%) of 67 supraglottic primaries. Among those managed with tracheostomy, ultimate LRC was achieved in 9 (69%) of 13 glottic primaries and 12 (80%) of 15 supraglottic primaries. In a subset analysis of 76 patients with T3T4 primaries, there was no statistically significant difference in larynx preservation, disease-free survival, or cause-specific survival between those managed with and without tracheostomy. Conclusion: Airway compromise necessitating tracheostomy is an adverse prognostic factor in patients with carcinoma of the larynx. However, larynx preservation is possible in over 40% of those

Perceived Statistical Knowledge Level and Self-Reported Statistical Practice Among Academic Psychologists

Directory of Open Access Journals (Sweden)

Laura Badenes-Ribera

2018-06-01

Full Text Available Introduction: Publications arguing against the null hypothesis significance testing (NHST procedure and in favor of good statistical practices have increased. The most frequently mentioned alternatives to NHST are effect size statistics (ES, confidence intervals (CIs, and meta-analyses. A recent survey conducted in Spain found that academic psychologists have poor knowledge about effect size statistics, confidence intervals, and graphic displays for meta-analyses, which might lead to a misinterpretation of the results. In addition, it also found that, although the use of ES is becoming generalized, the same thing is not true for CIs. Finally, academics with greater knowledge about ES statistics presented a profile closer to good statistical practice and research design. Our main purpose was to analyze the extension of these results to a different geographical area through a replication study.Methods: For this purpose, we elaborated an on-line survey that included the same items as the original research, and we asked academic psychologists to indicate their level of knowledge about ES, their CIs, and meta-analyses, and how they use them. The sample consisted of 159 Italian academic psychologists (54.09% women, mean age of 47.65 years. The mean number of years in the position of professor was 12.90 (SD = 10.21.Results: As in the original research, the results showed that, although the use of effect size estimates is becoming generalized, an under-reporting of CIs for ES persists. The most frequent ES statistics mentioned were Cohen's d and R2/η2, which can have outliers or show non-normality or violate statistical assumptions. In addition, academics showed poor knowledge about meta-analytic displays (e.g., forest plot and funnel plot and quality checklists for studies. Finally, academics with higher-level knowledge about ES statistics seem to have a profile closer to good statistical practices.Conclusions: Changing statistical practice is not

Statistical data processing with automatic system for environmental radiation monitoring

International Nuclear Information System (INIS)

Zarkh, V.G.; Ostroglyadov, S.V.

1986-01-01

Practice of statistical data processing for radiation monitoring is exemplified, and some results obtained are presented. Experience in practical application of mathematical statistics methods for radiation monitoring data processing allowed to develop a concrete algorithm of statistical processing realized in M-6000 minicomputer. The suggested algorithm by its content is divided into 3 parts: parametrical data processing and hypotheses test, pair and multiple correlation analysis. Statistical processing programms are in a dialogue operation. The above algorithm was used to process observed data over radioactive waste disposal control region. Results of surface waters monitoring processing are presented

Statistical mechanics of lattice Boson field theory

International Nuclear Information System (INIS)

1976-01-01

A lattice approximation to Euclidean, boson quantum field theory is expressed in terms of the thermodynamic properties of a classical statistical mechanical system near its critical point in a sufficiently general way to permit the inclusion of an anomalous dimension of the vacuum. Using the thermodynamic properties of the Ising model, one can begin to construct nontrivial (containing scattering) field theories in 2, 3 and 4 dimensions. It is argued that, depending on the choice of the bare coupling constant, there are three types of behavior to be expected: the perturbation theory region, the renormalization group fixed point region, and the Ising model region

Statistical mechanics of lattice boson field theory

International Nuclear Information System (INIS)

Baker, G.A. Jr.

1977-01-01

A lattice approximation to Euclidean, boson quantum field theory is expressed in terms of the thermodynamic properties of a classical statistical mechanical system near its critical point in a sufficiently general way to permit the inclusion of an anomalous dimension of the vacuum. Using the thermodynamic properties of the Ising model, one can begin to construct nontrivial (containing scattering) field theories in 2, 3, and 4 dimensions. It is argued that, depending on the choice of the bare coupling constant, there are three types of behavior to be expected: the perturbation theory region, the renormalization group fixed point region, and the Ising model region. 24 references

Understanding Statistics - Cancer Statistics

Science.gov (United States)

Annual reports of U.S. cancer statistics including new cases, deaths, trends, survival, prevalence, lifetime risk, and progress toward Healthy People targets, plus statistical summaries for a number of common cancer types.

Funding source and primary outcome changes in clinical trials registered on ClinicalTrials.gov are associated with the reporting of a statistically significant primary outcome: a cross-sectional study [v2; ref status: indexed, http://f1000r.es/5bj

Directory of Open Access Journals (Sweden)

Sreeram V Ramagopalan

2015-04-01

Full Text Available Background: We and others have shown a significant proportion of interventional trials registered on ClinicalTrials.gov have their primary outcomes altered after the listed study start and completion dates. The objectives of this study were to investigate whether changes made to primary outcomes are associated with the likelihood of reporting a statistically significant primary outcome on ClinicalTrials.gov. Methods: A cross-sectional analysis of all interventional clinical trials registered on ClinicalTrials.gov as of 20 November 2014 was performed. The main outcome was any change made to the initially listed primary outcome and the time of the change in relation to the trial start and end date. Findings: 13,238 completed interventional trials were registered with ClinicalTrials.gov that also had study results posted on the website. 2555 (19.3% had one or more statistically significant primary outcomes. Statistical analysis showed that registration year, funding source and primary outcome change after trial completion were associated with reporting a statistically significant primary outcome. Conclusions: Funding source and primary outcome change after trial completion are associated with a statistically significant primary outcome report on clinicaltrials.gov.

Analysis of data collected from right and left limbs: Accounting for dependence and improving statistical efficiency in musculoskeletal research.

Science.gov (United States)

Stewart, Sarah; Pearson, Janet; Rome, Keith; Dalbeth, Nicola; Vandal, Alain C

2018-01-01

Statistical techniques currently used in musculoskeletal research often inefficiently account for paired-limb measurements or the relationship between measurements taken from multiple regions within limbs. This study compared three commonly used analysis methods with a mixed-models approach that appropriately accounted for the association between limbs, regions, and trials and that utilised all information available from repeated trials. Four analysis were applied to an existing data set containing plantar pressure data, which was collected for seven masked regions on right and left feet, over three trials, across three participant groups. Methods 1-3 averaged data over trials and analysed right foot data (Method 1), data from a randomly selected foot (Method 2), and averaged right and left foot data (Method 3). Method 4 used all available data in a mixed-effects regression that accounted for repeated measures taken for each foot, foot region and trial. Confidence interval widths for the mean differences between groups for each foot region were used as a criterion for comparison of statistical efficiency. Mean differences in pressure between groups were similar across methods for each foot region, while the confidence interval widths were consistently smaller for Method 4. Method 4 also revealed significant between-group differences that were not detected by Methods 1-3. A mixed effects linear model approach generates improved efficiency and power by producing more precise estimates compared to alternative approaches that discard information in the process of accounting for paired-limb measurements. This approach is recommended in generating more clinically sound and statistically efficient research outputs. Copyright © 2017 Elsevier B.V. All rights reserved.

Brand as a significant element of the regional development strategy at the example of Devin

Directory of Open Access Journals (Sweden)

Goranova Penka

2015-01-01

Full Text Available The idea of (regional branding is an important issue in modern business environment. Theoretical studies in this area are few, compared to research papers that have been dedicated to traditional brands and branding. A practical research on brand as an important element of regional development strategy can thus provide a series of useful information that marketers can use in their marketing strategies and in branding process in particular. The aim of this article is an assessment of regional branding, at the example of Devin. The article consists of two main parts. The first part focuses on defining regional branding and discussing why regional branding is important. The second part analyses the brand Devin and shows how a regional brand can evolve from a concept to reality.

Statistical analysis and data management

International Nuclear Information System (INIS)

Anon.

1981-01-01

This report provides an overview of the history of the WIPP Biology Program. The recommendations of the American Institute of Biological Sciences (AIBS) for the WIPP biology program are summarized. The data sets available for statistical analyses and problems associated with these data sets are also summarized. Biological studies base maps are presented. A statistical model is presented to evaluate any correlation between climatological data and small mammal captures. No statistically significant relationship between variance in small mammal captures on Dr. Gennaro's 90m x 90m grid and precipitation records from the Duval Potash Mine were found

Regional variations in the management of testicular or ovotesticular disorders of sex development.

Science.gov (United States)

Josso, N; Audi, L; Shaw, G

2011-01-01

Disorders of sex development arise in parts of the world with different socio-economic and cultural characteristics. We wished to determine the regional variations in the management of these conditions. A questionnaire was e-mailed to the 650 members of the European Society for Paediatric Endocrinology (ESPE), an international society with a mainly European membership but which also includes professionals from other continents. Results were subjected to statistical analysis. A total of 62 answers were received, a satisfactory rate given that not all members are involved in this issue. Results show statistically significant regional differences for available diagnostic resources, age of the patient at gender assignment, parameters considered important for gender assignment, and timing of discussion of various issues with parents and patient. The regional variations exist not only between different continents, as already demonstrated by others, but also between Northern, Latin and Eastern European countries. This suggests that 'one-fits-all' guidelines for management are not appropriate. Copyright © 2011 S. Karger AG, Basel.

Confounding and Statistical Significance of Indirect Effects: Childhood Adversity, Education, Smoking, and Anxious and Depressive Symptomatology

Directory of Open Access Journals (Sweden)

Mashhood Ahmed Sheikh

2017-08-01

mediate the association between childhood adversity and ADS in adulthood. However, when education was excluded as a mediator-response confounding variable, the indirect effect of childhood adversity on ADS in adulthood was statistically significant (p < 0.05. This study shows that a careful inclusion of potential confounding variables is important when assessing mediation.

Sebum and Hydration Levels in Specific Regions of Human Face Significantly Predict the Nature and Diversity of Facial Skin Microbiome.

Science.gov (United States)

Mukherjee, Souvik; Mitra, Rupak; Maitra, Arindam; Gupta, Satyaranjan; Kumaran, Srikala; Chakrabortty, Amit; Majumder, Partha P

2016-10-27

The skin microbiome varies across individuals. The causes of these variations are inadequately understood. We tested the hypothesis that inter-individual variation in facial skin microbiome can be significantly explained by variation in sebum and hydration levels in specific facial regions of humans. We measured sebum and hydration from forehead and cheek regions of healthy female volunteers (n = 30). Metagenomic DNA from skin swabs were sequenced for V3-V5 regions of 16S rRNA gene. Altogether, 34 phyla were identified; predominantly Actinobacteria (66.3%), Firmicutes (17.7%), Proteobacteria (13.1%) and Bacteroidetes (1.4%). About 1000 genera were identified; predominantly Propionibacterium (58.6%), Staphylococcus (8.6%), Streptococcus (4.0%), Corynebacterium (3.6%) and Paracoccus (3.3%). A subset (n = 24) of individuals were sampled two months later. Stepwise multiple regression analysis showed that cheek sebum level was the most significant predictor of microbiome composition and diversity followed by forehead hydration level; forehead sebum and cheek hydration levels were not. With increase in cheek sebum, the prevalence of Actinobacteria (p = 0.001)/Propionibacterium (p = 0.002) increased, whereas microbiome diversity decreased (Shannon Index, p = 0.032); this was opposite for other phyla/genera. These trends were reversed for forehead hydration levels. Therefore, the nature and diversity of facial skin microbiome is jointly determined by site-specific lipid and water levels in the stratum corneum.

Superfund explanation of significant difference for the record of decision (EPA Region 3): Westinghouse Elevator Company Plant, Gettysburg, PA, August 3, 1998

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-09-01

The document explains significant differences to the remedy selected in the Record of Decision (ROD) for the Site signed by the Regional Administrator on June 30, 1992 (PB93-963911) for Operable Unit 1. The Significant Difference between the remedy presented in the June 30, 1992 ROD and the changes to the ROD that will be implemented are explained.

[Big data in official statistics].

Science.gov (United States)

Zwick, Markus

2015-08-01

The concept of "big data" stands to change the face of official statistics over the coming years, having an impact on almost all aspects of data production. The tasks of future statisticians will not necessarily be to produce new data, but rather to identify and make use of existing data to adequately describe social and economic phenomena. Until big data can be used correctly in official statistics, a lot of questions need to be answered and problems solved: the quality of data, data protection, privacy, and the sustainable availability are some of the more pressing issues to be addressed. The essential skills of official statisticians will undoubtedly change, and this implies a number of challenges to be faced by statistical education systems, in universities, and inside the statistical offices. The national statistical offices of the European Union have concluded a concrete strategy for exploring the possibilities of big data for official statistics, by means of the Big Data Roadmap and Action Plan 1.0. This is an important first step and will have a significant influence on implementing the concept of big data inside the statistical offices of Germany.

Statistical theory of dynamo

Science.gov (United States)

Kim, E.; Newton, A. P.

2012-04-01

One major problem in dynamo theory is the multi-scale nature of the MHD turbulence, which requires statistical theory in terms of probability distribution functions. In this contribution, we present the statistical theory of magnetic fields in a simplified mean field α-Ω dynamo model by varying the statistical property of alpha, including marginal stability and intermittency, and then utilize observational data of solar activity to fine-tune the mean field dynamo model. Specifically, we first present a comprehensive investigation into the effect of the stochastic parameters in a simplified α-Ω dynamo model. Through considering the manifold of marginal stability (the region of parameter space where the mean growth rate is zero), we show that stochastic fluctuations are conductive to dynamo. Furthermore, by considering the cases of fluctuating alpha that are periodic and Gaussian coloured random noise with identical characteristic time-scales and fluctuating amplitudes, we show that the transition to dynamo is significantly facilitated for stochastic alpha with random noise. Furthermore, we show that probability density functions (PDFs) of the growth-rate, magnetic field and magnetic energy can provide a wealth of useful information regarding the dynamo behaviour/intermittency. Finally, the precise statistical property of the dynamo such as temporal correlation and fluctuating amplitude is found to be dependent on the distribution the fluctuations of stochastic parameters. We then use observations of solar activity to constrain parameters relating to the effect in stochastic α-Ω nonlinear dynamo models. This is achieved through performing a comprehensive statistical comparison by computing PDFs of solar activity from observations and from our simulation of mean field dynamo model. The observational data that are used are the time history of solar activity inferred for C14 data in the past 11000 years on a long time scale and direct observations of the sun spot

Steadiness of Spinal Regions during Single-Leg Standing in Older Adults with and without Chronic Low Back Pain.

Directory of Open Access Journals (Sweden)

Yi-Liang Kuo

Full Text Available The aims of this study were to compare the steadiness index of spinal regions during single-leg standing in older adults with and without chronic low back pain (LBP and to correlate measurements of steadiness index with the performance of clinical balance tests. Thirteen community-dwelling older adults (aged 55 years or above with chronic LBP and 13 age- and gender-matched asymptomatic volunteers participated in this study. Data collection was conducted in a university research laboratory. Measurements were steadiness index of spinal regions (trunk, thoracic spine, lumbar spine, and pelvis during single-leg standing including relative holding time (RHT and relative standstill time (RST, and clinical balance tests (timed up and go test and 5-repetition sit to stand test. The LBP group had a statistically significantly smaller RHT than the control group, regardless of one leg stance on the painful or non-painful sides. The RSTs on the painful side leg in the LBP group were not statistically significantly different from the average RSTs of both legs in the control group; however, the RSTs on the non-painful side leg in the LBP group were statistically significantly smaller than those in the control group for the trunk, thoracic spine, and lumbar spine. No statistically significant intra-group differences were found in the RHTs and RSTs between the painful and non-painful side legs in the LBP group. Measurements of clinical balance tests also showed insignificant weak to moderate correlations with steadiness index. In conclusion, older adults with chronic LBP demonstrated decreased spinal steadiness not only in the symptomatic lumbar spine but also in the other spinal regions within the kinetic chain of the spine. When treating older adults with chronic LBP, clinicians may also need to examine their balance performance and spinal steadiness during balance challenging tests.

Impacts of climate change on wind energy resources in France: a regionalization study

International Nuclear Information System (INIS)

Najac, J.

2008-11-01

In this work, we study the impact of climate change on surface winds in France and draw conclusions concerning wind energy resources. Because of their coarse spatial resolution, climate models cannot properly reproduce the spatial variability of surface winds. Thus, 2 down-scaling methods are developed in order to regionalize an ensemble of climate scenarios: a statistical method based on weather typing and a statistic-dynamical method that resorts to high resolution mesoscale modelling. By 2050, significant but relatively small changes are depicted with, in particular, a decrease of the wind speed in the southern and an increase in the northern regions of France. The use of other down-scaling methods enables us to study several uncertainty sources: it appears that most of the uncertainty is due to the climate models. (author)

Screening for collusion: a spatial statistics approach

NARCIS (Netherlands)

Heijnen, P.; Haan, M.A.; Soetevent, A.R.

2012-01-01

We develop a method to screen for local cartels. We first test whether there is statistical evidence of clustering of outlets that score high on some characteristic that is consistent with collusive behavior. If so, we determine in a second step the most suspicious regions where further antitrust

Screening for collusion: a spatial statistics approach

NARCIS (Netherlands)

Heijnen, P.; Haan, M.A.; Soetevent, A.R.

2015-01-01

We develop a method to screen for local cartels. We first test whether there is statistical evidence of clustering of outlets that score high on some characteristic that is consistent with collusive behavior. If so, we determine in a second step the most suspicious regions where further antitrust

Screening for collusion : A spatial statistics approach

NARCIS (Netherlands)

Heijnen, Pim; Haan, Marco A.; Soetevent, Adriaan R.

2015-01-01

We develop a method to screen for local cartels. We first test whether there is statistical evidence of clustering of outlets that score high on some characteristic that is consistent with collusive behavior. If so, we determine in a second step the most suspicious regions where further antitrust

Estimation of regional mass anomalies from Gravity Recovery and Climate Experiment (GRACE) over Himalayan region

Science.gov (United States)

Agrawal, R.; Singh, S. K.; Rajawat, A. S.; Ajai

2014-11-01

Time-variable gravity changes are caused by a combination of postglacial rebound, redistribution of water and snow/ice on land and as well as in the ocean. The Gravity Recovery and Climate Experiment (GRACE) satellite mission, launched in 2002, provides monthly average of the spherical harmonic co-efficient. These spherical harmonic co-efficient describe earth's gravity field with a resolution of few hundred kilometers. Time-variability of gravity field represents the change in mass over regional level with accuracies in cm in terms of Water Equivalent Height (WEH). The WEH reflects the changes in the integrated vertically store water including snow cover, surface water, ground water and soil moisture at regional scale. GRACE data are also sensitive towards interior strain variation, surface uplift and surface subsidence cover over a large area. GRACE data was extracted over the three major Indian River basins, Indus, Ganga and Brahmaputra, in the Himalayas which are perennial source of fresh water throughout the year in Northern Indian Plain. Time series analysis of the GRACE data was carried out from 2003-2012 over the study area. Trends and amplitudes of the regional mass anomalies in the region were estimated using level 3 GRACE data product with a spatial resolution at 10 by 10 grid provided by Center for Space Research (CSR), University of Texas at Austin. Indus basin has shown a subtle decreasing trend from 2003-2012 however it was observed to be statistically insignificant at 95 % confidence level. Ganga and Brahmaputra basins have shown a clear decreasing trend in WEH which was also observed to be statistically significant. The trend analysis over Ganga and Brahamputra basins have shown an average annual change of -1.28 cm and -1.06 cm in terms of WEH whereas Indus basin has shown a slight annual change of -0.07 cm. This analysis will be helpful to understand the loss of mass in terms of WEH over Indian Himalayas and will be crucial for hydrological and

Regional Price Levels in the Czech Republic

Directory of Open Access Journals (Sweden)

Petr Musil

2017-06-01

Full Text Available International comparison belongs to statistical topics which attracts either experts or general public. Official statistics provides estimates of national price levels only. Therefore, official regional analysis is based on national price levels and does not take into account potential differences in prices among regions within a country. Fortunately, researchers have been dealing with them and estimates for several countries are available. The topic is also important in the Czech Republic even two papers focused on regional price levels were published in Statistika journal in 2016. The aim of the paper is to compare both approaches from various perspectives.

Brain SPECT analysis using statistical parametric mapping in patients with posttraumatic stress disorder

Energy Technology Data Exchange (ETDEWEB)

Kim, Euy Neyng; Sohn, Hyung Sun; Kim, Sung Hoon; Chung, Soo Kyo; Yang, Dong Won [College of Medicine, The Catholic Univ. of Korea, Seoul (Korea, Republic of)

2001-07-01

This study investigated alterations in regional cerebral blood flow (rCBF) in patients with posttraumatic stress disorder (PTSD) using statistical parametric mapping (SPM99). Noninvasive rCBF measurements using {sup 99m}Tc-ethyl cysteinate dimer (ECD) SPECT were performed on 23 patients with PTSD and 21 age matched normal controls without re-exposure to accident-related stimuli. The relative rCBF maps in patients with PTSD and controls were compared. In patients with PTSD, significant increased rCBF was found along the limbic system in the brain. There were a few foci of decreased rCBF in the superior frontal gyrus, parietal and temporal region. PTSD is associated with increased rCBF in limbic areas compared with age-matched normal controls. These findings implicate regions of the limbic brain, which may mediate the response to aversive stimuli in healthy individuals, play on important role in patients suffering from PTSD and suggest that ongoing hyperfunction of 'overlearned survival response' or flashbacks response in these regions after painful, life threatening, or horrifying events without re-exposure to same traumatic stimulus.

Brain SPECT analysis using statistical parametric mapping in patients with posttraumatic stress disorder

International Nuclear Information System (INIS)

Kim, Euy Neyng; Sohn, Hyung Sun; Kim, Sung Hoon; Chung, Soo Kyo; Yang, Dong Won

2001-01-01

This study investigated alterations in regional cerebral blood flow (rCBF) in patients with posttraumatic stress disorder (PTSD) using statistical parametric mapping (SPM99). Noninvasive rCBF measurements using 99m Tc-ethyl cysteinate dimer (ECD) SPECT were performed on 23 patients with PTSD and 21 age matched normal controls without re-exposure to accident-related stimuli. The relative rCBF maps in patients with PTSD and controls were compared. In patients with PTSD, significant increased rCBF was found along the limbic system in the brain. There were a few foci of decreased rCBF in the superior frontal gyrus, parietal and temporal region. PTSD is associated with increased rCBF in limbic areas compared with age-matched normal controls. These findings implicate regions of the limbic brain, which may mediate the response to aversive stimuli in healthy individuals, play on important role in patients suffering from PTSD and suggest that ongoing hyperfunction of 'overlearned survival response' or flashbacks response in these regions after painful, life threatening, or horrifying events without re-exposure to same traumatic stimulus

Summed Probability Distribution of 14C Dates Suggests Regional Divergences in the Population Dynamics of the Jomon Period in Eastern Japan.

Directory of Open Access Journals (Sweden)

Enrico R Crema

Full Text Available Recent advances in the use of summed probability distribution (SPD of calibrated 14C dates have opened new possibilities for studying prehistoric demography. The degree of correlation between climate change and population dynamics can now be accurately quantified, and divergences in the demographic history of distinct geographic areas can be statistically assessed. Here we contribute to this research agenda by reconstructing the prehistoric population change of Jomon hunter-gatherers between 7,000 and 3,000 cal BP. We collected 1,433 14C dates from three different regions in Eastern Japan (Kanto, Aomori and Hokkaido and established that the observed fluctuations in the SPDs were statistically significant. We also introduced a new non-parametric permutation test for comparing multiple sets of SPDs that highlights point of divergences in the population history of different geographic regions. Our analyses indicate a general rise-and-fall pattern shared by the three regions but also some key regional differences during the 6th millennium cal BP. The results confirm some of the patterns suggested by previous archaeological studies based on house and site counts but offer statistical significance and an absolute chronological framework that will enable future studies aiming to establish potential correlation with climatic changes.

Regional cerebral blood flow in fibromyalgia

International Nuclear Information System (INIS)

Kwiatek, R.; Barnden, L.; Rowe, C.; McKinnon, J.; Pile, K.

1998-01-01

Full text: Little is known of the aetiology of fibromyalgia (FM), a condition diagnosed on the basis of widespread chronic pain and multiple tender points. We have used Tc-99m HMPAO SPECT to compare regional cerebral bloodflow (rCBF) in 17 women who fulfill American College of Rheumatology criteria for FM to 22 age, sex and education matched controls. Both Statistical Parametric Mapping (SPM95) and coregistered MRI guided ROI were used for analysis. SPM95 revealed statistically significant hypoperfusion in the pontine tegmentum (p=0.048) and a trend to hypoperfusion in the left putamen (p=0.07). MRI guided ROI placement by an operator blinded to clinical information and the coregistered SPECT images, confirmed significant hypoperfusion of the left thalamus (p<0.0001) and the pontine tegmentum (p=0.001) and revealed trends towards hypoperfusion in the caudate nuclei and right thalamus. These results are consistent with the hypothesis that FM is due to dysfunction of central pain pathways. Spinothalamic neurones are known to be involved in pain perception and there are synapse connections to the thalamus in the gigantocellular part of the medulla and pons

Regional cerebral blood flow in fibromyalgia

Energy Technology Data Exchange (ETDEWEB)

Kwiatek, R.; Barnden, L.; Rowe, C.; McKinnon, J.; Pile, K. [The Queen Elizabeth Hospital , Adelaide, SA (Australia)

1998-06-01

Full text: Little is known of the aetiology of fibromyalgia (FM), a condition diagnosed on the basis of widespread chronic pain and multiple tender points. We have used Tc-99m HMPAO SPECT to compare regional cerebral bloodflow (rCBF) in 17 women who fulfill American College of Rheumatology criteria for FM to 22 age, sex and education matched controls. Both Statistical Parametric Mapping (SPM95) and coregistered MRI guided ROI were used for analysis. SPM95 revealed statistically significant hypoperfusion in the pontine tegmentum (p=0.048) and a trend to hypoperfusion in the left putamen (p=0.07). MRI guided ROI placement by an operator blinded to clinical information and the coregistered SPECT images, confirmed significant hypoperfusion of the left thalamus (p<0.0001) and the pontine tegmentum (p=0.001) and revealed trends towards hypoperfusion in the caudate nuclei and right thalamus. These results are consistent with the hypothesis that FM is due to dysfunction of central pain pathways. Spinothalamic neurones are known to be involved in pain perception and there are synapse connections to the thalamus in the gigantocellular part of the medulla and pons

Significant regional differences in Denmark in outcome after cochlear implants in children

DEFF Research Database (Denmark)

Percy-Smith, Lone; Busch, Georg Walter; Sandahl, Minna

2012-01-01

The objectives of the present study were to study regional differences in outcome for a paediatric cochlear implant (CI) population after the introduction of universal neonatal hearing screening (UNHS) and bilateral implantation in Denmark....

National Statistical Commission and Indian Official Statistics*

Indian Academy of Sciences (India)

IAS Admin

a good collection of official statistics of that time. With more .... statistical agencies and institutions to provide details of statistical activities .... ing several training programmes. .... ful completion of Indian Statistical Service examinations, the.

Multivariate Statistical Analysis: a tool for groundwater quality assessment in the hidrogeologic region of the Ring of Cenotes, Yucatan, Mexico.

Science.gov (United States)

Ye, M.; Pacheco Castro, R. B.; Pacheco Avila, J.; Cabrera Sansores, A.

2014-12-01

The karstic aquifer of Yucatan is a vulnerable and complex system. The first fifteen meters of this aquifer have been polluted, due to this the protection of this resource is important because is the only source of potable water of the entire State. Through the assessment of groundwater quality we can gain some knowledge about the main processes governing water chemistry as well as spatial patterns which are important to establish protection zones. In this work multivariate statistical techniques are used to assess the groundwater quality of the supply wells (30 to 40 meters deep) in the hidrogeologic region of the Ring of Cenotes, located in Yucatan, Mexico. Cluster analysis and principal component analysis are applied in groundwater chemistry data of the study area. Results of principal component analysis show that the main sources of variation in the data are due sea water intrusion and the interaction of the water with the carbonate rocks of the system and some pollution processes. The cluster analysis shows that the data can be divided in four clusters. The spatial distribution of the clusters seems to be random, but is consistent with sea water intrusion and pollution with nitrates. The overall results show that multivariate statistical analysis can be successfully applied in the groundwater quality assessment of this karstic aquifer.

Statistical parametric mapping of the regional distribution and ontogenetic scaling of foot pressures during walking in Asian elephants (Elephas maximus).

Science.gov (United States)

Panagiotopoulou, Olga; Pataky, Todd C; Hill, Zoe; Hutchinson, John R

2012-05-01

Foot pressure distributions during locomotion have causal links with the anatomical and structural configurations of the foot tissues and the mechanics of locomotion. Elephant feet have five toes bound in a flexible pad of fibrous tissue (digital cushion). Does this specialized foot design control peak foot pressures in such giant animals? And how does body size, such as during ontogenetic growth, influence foot pressures? We addressed these questions by studying foot pressure distributions in elephant feet and their correlation with body mass and centre of pressure trajectories, using statistical parametric mapping (SPM), a neuro-imaging technology. Our results show a positive correlation between body mass and peak pressures, with the highest pressures dominated by the distal ends of the lateral toes (digits 3, 4 and 5). We also demonstrate that pressure reduction in the elephant digital cushion is a complex interaction of its viscoelastic tissue structure and its centre of pressure trajectories, because there is a tendency to avoid rear 'heel' contact as an elephant grows. Using SPM, we present a complete map of pressure distributions in elephant feet during ontogeny by performing statistical analysis at the pixel level across the entire plantar/palmar surface. We hope that our study will build confidence in the potential clinical and scaling applications of mammalian foot pressures, given our findings in support of a link between regional peak pressures and pathogenesis in elephant feet.

Statistical study of auroral omega bands

Directory of Open Access Journals (Sweden)

N. Partamies

2017-09-01

Full Text Available The presence of very few statistical studies on auroral omega bands motivated us to test-use a semi-automatic method for identifying large-scale undulations of the diffuse aurora boundary and to investigate their occurrence. Five identical all-sky cameras with overlapping fields of view provided data for 438 auroral omega-like structures over Fennoscandian Lapland from 1996 to 2007. The results from this set of omega band events agree remarkably well with previous observations of omega band occurrence in magnetic local time (MLT, lifetime, location between the region 1 and 2 field-aligned currents, as well as current density estimates. The average peak emission height of omega forms corresponds to the estimated precipitation energies of a few keV, which experienced no significant change during the events. Analysis of both local and global magnetic indices demonstrates that omega bands are observed during substorm expansion and recovery phases that are more intense than average substorm expansion and recovery phases in the same region. The omega occurrence with respect to the substorm expansion and recovery phases is in a very good agreement with an earlier observed distribution of fast earthward flows in the plasma sheet during expansion and recovery phases. These findings support the theory that omegas are produced by fast earthward flows and auroral streamers, despite the rarity of good conjugate observations.

Official Statistics and Statistics Education: Bridging the Gap