Univaried models in the series of temperature of the air

International Nuclear Information System (INIS)

Leon Aristizabal Gloria esperanza

2000-01-01

The theoretical framework for the study of the air's temperature time series is the theory of stochastic processes, particularly those known as ARIMA, that make it possible to carry out a univaried analysis. ARIMA models are built in order to explain the structure of the monthly temperatures corresponding to the mean, the absolute maximum, absolute minimum, maximum mean and minimum mean temperatures, for four stations in Colombia. By means of those models, the possible evolution of the latter variables is estimated with predictive aims in mind. The application and utility of the models is discussed

Comparison between the univariate and multivariate analysis on the partial characterization of the endoglucanase produced in the solid state fermentation by Aspergillus oryzae ATCC 10124.

Science.gov (United States)

de Brito, Aila Riany; Santos Reis, Nadabe Dos; Silva, Tatielle Pereira; Ferreira Bonomo, Renata Cristina; Trovatti Uetanabaro, Ana Paula; de Assis, Sandra Aparecida; da Silva, Erik Galvão Paranhos; Aguiar-Oliveira, Elizama; Oliveira, Julieta Rangel; Franco, Marcelo

2017-11-26

Endoglucanase production by Aspergillus oryzae ATCC 10124 cultivated in rice husks or peanut shells was optimized by experimental design as a function of humidity, time, and temperature. The optimum temperature for the endoglucanase activity was estimated by a univariate analysis (one factor at the time) as 50°C (rice husks) and 60°C (peanut shells), however, by a multivariate analysis (synergism of factors), it was determined a different temperature (56°C) for endoglucanase from peanut shells. For the optimum pH, values determined by univariate and multivariate analysis were 5 and 5.2 (rice husk) and 5 and 7.6 (peanut shells). In addition, the best half-lives were observed at 50°C as 22.8 hr (rice husks) and 7.3 hr (peanut shells), also, 80% of residual activities was obtained between 30 and 50°C for both substrates, and the pH stability was improved at 5-7 (rice hulls) and 6-9 (peanut shells). Both endoglucanases obtained presented different characteristics as a result of the versatility of fungi in different substrates.

Characteristics of genomic signatures derived using univariate methods and mechanistically anchored functional descriptors for predicting drug- and xenobiotic-induced nephrotoxicity.

Science.gov (United States)

Shi, Weiwei; Bugrim, Andrej; Nikolsky, Yuri; Nikolskya, Tatiana; Brennan, Richard J

2008-01-01

ABSTRACT The ideal toxicity biomarker is composed of the properties of prediction (is detected prior to traditional pathological signs of injury), accuracy (high sensitivity and specificity), and mechanistic relationships to the endpoint measured (biological relevance). Gene expression-based toxicity biomarkers ("signatures") have shown good predictive power and accuracy, but are difficult to interpret biologically. We have compared different statistical methods of feature selection with knowledge-based approaches, using GeneGo's database of canonical pathway maps, to generate gene sets for the classification of renal tubule toxicity. The gene set selection algorithms include four univariate analyses: t-statistics, fold-change, B-statistics, and RankProd, and their combination and overlap for the identification of differentially expressed probes. Enrichment analysis following the results of the four univariate analyses, Hotelling T-square test, and, finally out-of-bag selection, a variant of cross-validation, were used to identify canonical pathway maps-sets of genes coordinately involved in key biological processes-with classification power. Differentially expressed genes identified by the different statistical univariate analyses all generated reasonably performing classifiers of tubule toxicity. Maps identified by enrichment analysis or Hotelling T-square had lower classification power, but highlighted perturbed lipid homeostasis as a common discriminator of nephrotoxic treatments. The out-of-bag method yielded the best functionally integrated classifier. The map "ephrins signaling" performed comparably to a classifier derived using sparse linear programming, a machine learning algorithm, and represents a signaling network specifically involved in renal tubule development and integrity. Such functional descriptors of toxicity promise to better integrate predictive toxicogenomics with mechanistic analysis, facilitating the interpretation and risk assessment of

Forecasting electricity spot-prices using linear univariate time-series models

International Nuclear Information System (INIS)

Cuaresma, Jesus Crespo; Hlouskova, Jaroslava; Kossmeier, Stephan; Obersteiner, Michael

2004-01-01

This paper studies the forecasting abilities of a battery of univariate models on hourly electricity spot prices, using data from the Leipzig Power Exchange. The specifications studied include autoregressive models, autoregressive-moving average models and unobserved component models. The results show that specifications, where each hour of the day is modelled separately present uniformly better forecasting properties than specifications for the whole time-series, and that the inclusion of simple probabilistic processes for the arrival of extreme price events can lead to improvements in the forecasting abilities of univariate models for electricity spot prices. (Author)

Regression Is a Univariate General Linear Model Subsuming Other Parametric Methods as Special Cases.

Science.gov (United States)

Vidal, Sherry

Although the concept of the general linear model (GLM) has existed since the 1960s, other univariate analyses such as the t-test and the analysis of variance models have remained popular. The GLM produces an equation that minimizes the mean differences of independent variables as they are related to a dependent variable. From a computer printout…

Comparison of different Methods for Univariate Time Series Imputation in R

OpenAIRE

Moritz, Steffen; Sardá, Alexis; Bartz-Beielstein, Thomas; Zaefferer, Martin; Stork, Jörg

2015-01-01

Missing values in datasets are a well-known problem and there are quite a lot of R packages offering imputation functions. But while imputation in general is well covered within R, it is hard to find functions for imputation of univariate time series. The problem is, most standard imputation techniques can not be applied directly. Most algorithms rely on inter-attribute correlations, while univariate time series imputation needs to employ time dependencies. This paper provides an overview of ...

Evaluation of in-line Raman data for end-point determination of a coating process: Comparison of Science-Based Calibration, PLS-regression and univariate data analysis.

Science.gov (United States)

Barimani, Shirin; Kleinebudde, Peter

2017-10-01

A multivariate analysis method, Science-Based Calibration (SBC), was used for the first time for endpoint determination of a tablet coating process using Raman data. Two types of tablet cores, placebo and caffeine cores, received a coating suspension comprising a polyvinyl alcohol-polyethylene glycol graft-copolymer and titanium dioxide to a maximum coating thickness of 80µm. Raman spectroscopy was used as in-line PAT tool. The spectra were acquired every minute and correlated to the amount of applied aqueous coating suspension. SBC was compared to another well-known multivariate analysis method, Partial Least Squares-regression (PLS) and a simpler approach, Univariate Data Analysis (UVDA). All developed calibration models had coefficient of determination values (R 2 ) higher than 0.99. The coating endpoints could be predicted with root mean square errors (RMSEP) less than 3.1% of the applied coating suspensions. Compared to PLS and UVDA, SBC proved to be an alternative multivariate calibration method with high predictive power. Copyright © 2017 Elsevier B.V. All rights reserved.

Combinatorial bounds on the α-divergence of univariate mixture models

KAUST Repository

Nielsen, Frank; Sun, Ke

2017-01-01

We derive lower- and upper-bounds of α-divergence between univariate mixture models with components in the exponential family. Three pairs of bounds are presented in order with increasing quality and increasing computational cost. They are verified

Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model

Directory of Open Access Journals (Sweden)

Erasmo Cadenas

2016-02-01

Full Text Available Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA. This method’s performance is well studied for a large number of prediction problems. The other is a multivariate model developed using a nonlinear autoregressive exogenous artificial neural network (NARX. This uses the variables: barometric pressure, air temperature, wind direction and solar radiation or relative humidity, as well as delayed wind speed. Both models were developed from two databases from two sites: an hourly average measurements database from La Mata, Oaxaca, Mexico, and a ten minute average measurements database from Metepec, Hidalgo, Mexico. The main objective was to compare the impact of the various meteorological variables on the performance of the multivariate model of wind speed prediction with respect to the high performance univariate linear model. The NARX model gave better results with improvements on the ARIMA model of between 5.5% and 10. 6% for the hourly database and of between 2.3% and 12.8% for the ten minute database for mean absolute error and mean squared error, respectively.

Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry

International Nuclear Information System (INIS)

Batista Braga, Jez Willian; Trevizan, Lilian Cristina; Nunes, Lidiane Cristina; Aparecida Rufini, Iolanda; Santos, Dario; Krug, Francisco Jose

2010-01-01

The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance, but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation.

Nuisance forecasting. Univariate modelling and very-short-term forecasting of winter smog episodes; Immissionsprognose. Univariate Modellierung und Kuerzestfristvorhersage von Wintersmogsituationen

Energy Technology Data Exchange (ETDEWEB)

Schlink, U.

1996-12-31

The work evaluates specifically the nuisance data provided by the measuring station in the centre of Leipig during the period from 1980 to 1993, with the aim to develop an algorithm for making very short-term forecasts of excessive nuisances. Forecasting was to be univariate, i.e., based exclusively on the half-hourly readings of SO{sub 2} concentrations taken in the past. As shown by Fourier analysis, there exist three main and mutually independent spectral regions: the high-frequency sector (period < 12 hours) of unstable irregularities, the seasonal sector with the periods of 24 and 12 hours, and the low-frequency sector (period > 24 hours). After breaking the measuring series up into components, the low-frequency sector is termed trend component, or trend for short. For obtaining the components, a Kalman filter is used. It was found that smog episodes are most adequately described by the trend component. This is therefore more closely investigated. The phase representation then shows characteristic trajectories of the trends. (orig./KW) [Deutsch] In der vorliegende Arbeit wurden speziell die Immissionsdaten der Messstation Leipzig-Mitte des Zeitraumes 1980-1993 mit dem Ziel der Erstellung eines Algorithmus fuer die Kuerzestfristprognose von Ueberschreitungssituationen untersucht. Die Prognosestellung sollte allein anhand der in der Vergangenheit registrierten Halbstundenwerte der SO{sub 2}-Konzentration, also univariat erfolgen. Wie die Fourieranalyse zeigt, gibt es drei wesentliche und voneinander unabhaengige Spektralbereiche: Den hochfrequenten Bereich (Periode <12 Stunden) der instabilen Irregularitaeten, den saisonalen Anteil mit den Perioden von 24 und 12 Stunden und den niedrigfrequenten Bereich (Periode >24 Stunden). Letzterer wird nach einer Zerlegung der Messreihe in Komponenten als Trendkomponente (oder kurz Trend) bezeichnet. Fuer die Komponentenzerlegung wird ein Kalman-Filter verwendet. Es stellt sich heraus, dass Smogepisoden am deutlichsten

Acceleration techniques in the univariate Lipschitz global optimization

Science.gov (United States)

Sergeyev, Yaroslav D.; Kvasov, Dmitri E.; Mukhametzhanov, Marat S.; De Franco, Angela

2016-10-01

Univariate box-constrained Lipschitz global optimization problems are considered in this contribution. Geometric and information statistical approaches are presented. The novel powerful local tuning and local improvement techniques are described in the contribution as well as the traditional ways to estimate the Lipschitz constant. The advantages of the presented local tuning and local improvement techniques are demonstrated using the operational characteristics approach for comparing deterministic global optimization algorithms on the class of 100 widely used test functions.

Univariate decision tree induction using maximum margin classification

OpenAIRE

Yıldız, Olcay Taner

2012-01-01

In many pattern recognition applications, first decision trees are used due to their simplicity and easily interpretable nature. In this paper, we propose a new decision tree learning algorithm called univariate margin tree where, for each continuous attribute, the best split is found using convex optimization. Our simulation results on 47 data sets show that the novel margin tree classifier performs at least as good as C4.5 and linear discriminant tree (LDT) with a similar time complexity. F...

Effect Sizes for Research Univariate and Multivariate Applications

CERN Document Server

Grissom, Robert J

2011-01-01

Noted for its comprehensive coverage, this greatly expanded new edition now covers the use of univariate and multivariate effect sizes. Many measures and estimators are reviewed along with their application, interpretation, and limitations. Noted for its practical approach, the book features numerous examples using real data for a variety of variables and designs, to help readers apply the material to their own data. Tips on the use of SPSS, SAS, R, and S-Plus are provided. The book's broad disciplinary appeal results from its inclusion of a variety of examples from psychology, medicine, educa

Combinatorial bounds on the α-divergence of univariate mixture models

KAUST Repository

Nielsen, Frank

2017-06-20

We derive lower- and upper-bounds of α-divergence between univariate mixture models with components in the exponential family. Three pairs of bounds are presented in order with increasing quality and increasing computational cost. They are verified empirically through simulated Gaussian mixture models. The presented methodology generalizes to other divergence families relying on Hellinger-type integrals.

Investigating univariate temporal patterns for intrinsic connectivity networks based on complexity and low-frequency oscillation: a test-retest reliability study.

Science.gov (United States)

Wang, X; Jiao, Y; Tang, T; Wang, H; Lu, Z

2013-12-19

Intrinsic connectivity networks (ICNs) are composed of spatial components and time courses. The spatial components of ICNs were discovered with moderate-to-high reliability. So far as we know, few studies focused on the reliability of the temporal patterns for ICNs based their individual time courses. The goals of this study were twofold: to investigate the test-retest reliability of temporal patterns for ICNs, and to analyze these informative univariate metrics. Additionally, a correlation analysis was performed to enhance interpretability. Our study included three datasets: (a) short- and long-term scans, (b) multi-band echo-planar imaging (mEPI), and (c) eyes open or closed. Using dual regression, we obtained the time courses of ICNs for each subject. To produce temporal patterns for ICNs, we applied two categories of univariate metrics: network-wise complexity and network-wise low-frequency oscillation. Furthermore, we validated the test-retest reliability for each metric. The network-wise temporal patterns for most ICNs (especially for default mode network, DMN) exhibited moderate-to-high reliability and reproducibility under different scan conditions. Network-wise complexity for DMN exhibited fair reliability (ICC<0.5) based on eyes-closed sessions. Specially, our results supported that mEPI could be a useful method with high reliability and reproducibility. In addition, these temporal patterns were with physiological meanings, and certain temporal patterns were correlated to the node strength of the corresponding ICN. Overall, network-wise temporal patterns of ICNs were reliable and informative and could be complementary to spatial patterns of ICNs for further study. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia.

Science.gov (United States)

Aboagye-Sarfo, Patrick; Mai, Qun; Sanfilippo, Frank M; Preen, David B; Stewart, Louise M; Fatovich, Daniel M

2015-10-01

To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters' models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters' method. VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand. Copyright © 2015 Elsevier Inc. All rights reserved.

Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

Directory of Open Access Journals (Sweden)

Abdel Samee Nagwan M

2012-08-01

Full Text Available Abstract Background Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC. The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. Results In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy. A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer in the top ten genes of the list of intersected genes. Conclusions To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when

Trend and forecasting rate of cancer deaths at a public university hospital using univariate modeling

Science.gov (United States)

Ismail, A.; Hassan, Noor I.

2013-09-01

Cancer is one of the principal causes of death in Malaysia. This study was performed to determine the pattern of rate of cancer deaths at a public hospital in Malaysia over an 11 year period from year 2001 to 2011, to determine the best fitted model of forecasting the rate of cancer deaths using Univariate Modeling and to forecast the rates for the next two years (2012 to 2013). The medical records of the death of patients with cancer admitted at this Hospital over 11 year's period were reviewed, with a total of 663 cases. The cancers were classified according to 10th Revision International Classification of Diseases (ICD-10). Data collected include socio-demographic background of patients such as registration number, age, gender, ethnicity, ward and diagnosis. Data entry and analysis was accomplished using SPSS 19.0 and Minitab 16.0. The five Univariate Models used were Naïve with Trend Model, Average Percent Change Model (ACPM), Single Exponential Smoothing, Double Exponential Smoothing and Holt's Method. The overall 11 years rate of cancer deaths showed that at this hospital, Malay patients have the highest percentage (88.10%) compared to other ethnic groups with males (51.30%) higher than females. Lung and breast cancer have the most number of cancer deaths among gender. About 29.60% of the patients who died due to cancer were aged 61 years old and above. The best Univariate Model used for forecasting the rate of cancer deaths is Single Exponential Smoothing Technique with alpha of 0.10. The forecast for the rate of cancer deaths shows a horizontally or flat value. The forecasted mortality trend remains at 6.84% from January 2012 to December 2013. All the government and private sectors and non-governmental organizations need to highlight issues on cancer especially lung and breast cancers to the public through campaigns using mass media, media electronics, posters and pamphlets in the attempt to decrease the rate of cancer deaths in Malaysia.

Which DTW Method Applied to Marine Univariate Time Series Imputation

OpenAIRE

Phan , Thi-Thu-Hong; Caillault , Émilie; Lefebvre , Alain; Bigand , André

2017-01-01

International audience; Missing data are ubiquitous in any domains of applied sciences. Processing datasets containing missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Therefore, the aim of this paper is to build a framework for filling missing values in univariate time series and to perform a comparison of different similarity metrics used for the imputation task. This allows to suggest the most suitable methods for the imp...

Validated univariate and multivariate spectrophotometric methods for the determination of pharmaceuticals mixture in complex wastewater

Science.gov (United States)

Riad, Safaa M.; Salem, Hesham; Elbalkiny, Heba T.; Khattab, Fatma I.

2015-04-01

Five, accurate, precise, and sensitive univariate and multivariate spectrophotometric methods were developed for the simultaneous determination of a ternary mixture containing Trimethoprim (TMP), Sulphamethoxazole (SMZ) and Oxytetracycline (OTC) in waste water samples collected from different cites either production wastewater or livestock wastewater after their solid phase extraction using OASIS HLB cartridges. In univariate methods OTC was determined at its λmax 355.7 nm (0D), while (TMP) and (SMZ) were determined by three different univariate methods. Method (A) is based on successive spectrophotometric resolution technique (SSRT). The technique starts with the ratio subtraction method followed by ratio difference method for determination of TMP and SMZ. Method (B) is successive derivative ratio technique (SDR). Method (C) is mean centering of the ratio spectra (MCR). The developed multivariate methods are principle component regression (PCR) and partial least squares (PLS). The specificity of the developed methods is investigated by analyzing laboratory prepared mixtures containing different ratios of the three drugs. The obtained results are statistically compared with those obtained by the official methods, showing no significant difference with respect to accuracy and precision at p = 0.05.

A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

Science.gov (United States)

Zhang, Jing; Liang, Lichen; Anderson, Jon R; Gatewood, Lael; Rottenberg, David A; Strother, Stephen C

2008-01-01

As functional magnetic resonance imaging (fMRI) becomes widely used, the demands for evaluation of fMRI processing pipelines and validation of fMRI analysis results is increasing rapidly. The current NPAIRS package, an IDL-based fMRI processing pipeline evaluation framework, lacks system interoperability and the ability to evaluate general linear model (GLM)-based pipelines using prediction metrics. Thus, it can not fully evaluate fMRI analytical software modules such as FSL.FEAT and NPAIRS.GLM. In order to overcome these limitations, a Java-based fMRI processing pipeline evaluation system was developed. It integrated YALE (a machine learning environment) into Fiswidgets (a fMRI software environment) to obtain system interoperability and applied an algorithm to measure GLM prediction accuracy. The results demonstrated that the system can evaluate fMRI processing pipelines with univariate GLM and multivariate canonical variates analysis (CVA)-based models on real fMRI data based on prediction accuracy (classification accuracy) and statistical parametric image (SPI) reproducibility. In addition, a preliminary study was performed where four fMRI processing pipelines with GLM and CVA modules such as FSL.FEAT and NPAIRS.CVA were evaluated with the system. The results indicated that (1) the system can compare different fMRI processing pipelines with heterogeneous models (NPAIRS.GLM, NPAIRS.CVA and FSL.FEAT) and rank their performance by automatic performance scoring, and (2) the rank of pipeline performance is highly dependent on the preprocessing operations. These results suggest that the system will be of value for the comparison, validation, standardization and optimization of functional neuroimaging software packages and fMRI processing pipelines.

Impact of BCL2 and p53 on postmastectomy radiotherapy response in high-risk breast cancer. A subgroup analysis of DBCG82 b&c

DEFF Research Database (Denmark)

Kyndi, Marianne; Sørensen, Flemming Brandt; Knudsen, Helle

2008-01-01

-Meier probability plots showed a significantly improved overall survival after PMRT for the BCL2 positive subgroup, whereas practically no survival improvement was seen after PMRT for the BCL2 negative subgroup. In multivariate analysis of OS, however, no significant interaction was found between BCL2......PURPOSE: To examine p53 and BCL2 expression in high-risk breast cancer patients randomized to postmastectomy radiotherapy (PMRT). PATIENTS AND METHODS: The present analysis included 1 000 of 3 083 high-risk breast cancer patients randomly assigned to PMRT in the DBCG82 b&c studies. Tissue...... tests, Kaplan-Meier probability plots, Log-rank test, and Cox univariate and multivariate regression analyses. RESULTS: p53 accumulation was not significantly associated with increased overall mortality, DM or LRR probability in univariate or multivariate Cox regression analyses. Kaplan...

Cellulose I crystallinity determination using FT-Raman spectroscopy : univariate and multivariate methods

Science.gov (United States)

Umesh P. Agarwal; Richard S. Reiner; Sally A. Ralph

2010-01-01

Two new methods based on FT–Raman spectroscopy, one simple, based on band intensity ratio, and the other using a partial least squares (PLS) regression model, are proposed to determine cellulose I crystallinity. In the simple method, crystallinity in cellulose I samples was determined based on univariate regression that was first developed using the Raman band...

Impact of BCL2 and p53 on postmastectomy radiotherapy response in high-risk breast cancer. A subgroup analysis of DBCG82 b

DEFF Research Database (Denmark)

Kyndi, M.; Sorensen, F.B.; Alsner, J.

2008-01-01

-Meier probability plots showed a significantly improved overall survival after PMRT for the BCL2 positive subgroup, whereas practically no survival improvement was seen after PMRT for the BCL2 negative subgroup. In multivariate analysis of OS, however, no significant interaction was found between BCL2......Purpose. To examine p53 and BCL2 expression in high-risk breast cancer patients randomized to postmastectomy radiotherapy (PMRT). Patients and methods. The present analysis included 1000 of 3 083 high-risk breast cancer patients randomly assigned to PMRT in the DBCG82 b&c studies. Tissue microarray......, Kaplan-Meier probability plots, Log-rank test, and Cox univariate and multivariate regression analyses. Results. p53 accumulation was not significantly associated with increased overall mortality, DM or LRR probability in univariate or multivariate Cox regression analyses. Kaplan-Meier probability plots...

Forecasting electric vehicles sales with univariate and multivariate time series models: The case of China.

Science.gov (United States)

Zhang, Yong; Zhong, Miner; Geng, Nana; Jiang, Yunjian

2017-01-01

The market demand for electric vehicles (EVs) has increased in recent years. Suitable models are necessary to understand and forecast EV sales. This study presents a singular spectrum analysis (SSA) as a univariate time-series model and vector autoregressive model (VAR) as a multivariate model. Empirical results suggest that SSA satisfactorily indicates the evolving trend and provides reasonable results. The VAR model, which comprised exogenous parameters related to the market on a monthly basis, can significantly improve the prediction accuracy. The EV sales in China, which are categorized into battery and plug-in EVs, are predicted in both short term (up to December 2017) and long term (up to 2020), as statistical proofs of the growth of the Chinese EV industry.

Modeling the potential risk factors of bovine viral diarrhea prevalence in Egypt using univariable and multivariable logistic regression analyses

Directory of Open Access Journals (Sweden)

Abdelfattah M. Selim

2018-03-01

Full Text Available Aim: The present cross-sectional study was conducted to determine the seroprevalence and potential risk factors associated with Bovine viral diarrhea virus (BVDV disease in cattle and buffaloes in Egypt, to model the potential risk factors associated with the disease using logistic regression (LR models, and to fit the best predictive model for the current data. Materials and Methods: A total of 740 blood samples were collected within November 2012-March 2013 from animals aged between 6 months and 3 years. The potential risk factors studied were species, age, sex, and herd location. All serum samples were examined with indirect ELIZA test for antibody detection. Data were analyzed with different statistical approaches such as Chi-square test, odds ratios (OR, univariable, and multivariable LR models. Results: Results revealed a non-significant association between being seropositive with BVDV and all risk factors, except for species of animal. Seroprevalence percentages were 40% and 23% for cattle and buffaloes, respectively. OR for all categories were close to one with the highest OR for cattle relative to buffaloes, which was 2.237. Likelihood ratio tests showed a significant drop of the -2LL from univariable LR to multivariable LR models. Conclusion: There was an evidence of high seroprevalence of BVDV among cattle as compared with buffaloes with the possibility of infection in different age groups of animals. In addition, multivariable LR model was proved to provide more information for association and prediction purposes relative to univariable LR models and Chi-square tests if we have more than one predictor.

[Retrospective statistical analysis of clinical factors of recurrence in chronic subdural hematoma: correlation between univariate and multivariate analysis].

Science.gov (United States)

Takayama, Motoharu; Terui, Keita; Oiwa, Yoshitsugu

2012-10-01

Chronic subdural hematoma is common in elderly individuals and surgical procedures are simple. The recurrence rate of chronic subdural hematoma, however, varies from 9.2 to 26.5% after surgery. The authors studied factors of the recurrence using univariate and multivariate analyses in patients with chronic subdural hematoma We retrospectively reviewed 239 consecutive cases of chronic subdural hematoma who received burr-hole surgery with irrigation and closed-system drainage. We analyzed the relationships between recurrence of chronic subdural hematoma and factors such as sex, age, laterality, bleeding tendency, other complicated diseases, density on CT, volume of the hematoma, residual air in the hematoma cavity, use of artificial cerebrospinal fluid. Twenty-one patients (8.8%) experienced a recurrence of chronic subdural hematoma. Multiple logistic regression found that the recurrence rate was higher in patients with a large volume of the residual air, and was lower in patients using artificial cerebrospinal fluid. No statistical differences were found in bleeding tendency. Techniques to reduce the air in the hematoma cavity are important for good outcome in surgery of chronic subdural hematoma. Also, the use of artificial cerebrospinal fluid reduces recurrence of chronic subdural hematoma. The surgical procedures can be the same for patients with bleeding tendencies.

Influence of microclimatic ammonia levels on productive performance of different broilers' breeds estimated with univariate and multivariate approaches.

Science.gov (United States)

Soliman, Essam S; Moawed, Sherif A; Hassan, Rania A

2017-08-01

Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people's health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Ammonia levels were significantly higher (p0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (pbroiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. The study revealed that broiler's growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers' growth performance parameters data using multivariate discriminant function analysis.

Lower bounds on the run time of the univariate marginal distribution algorithm on OneMax

DEFF Research Database (Denmark)

Krejca, Martin S.; Witt, Carsten

2017-01-01

The Univariate Marginal Distribution Algorithm (UMDA), a popular estimation of distribution algorithm, is studied from a run time perspective. On the classical OneMax benchmark function, a lower bound of Ω(μ√n + n log n), where μ is the population size, on its expected run time is proved...... values maintained by the algorithm, including carefully designed potential functions. These techniques may prove useful in advancing the field of run time analysis for estimation of distribution algorithms in general........ This is the first direct lower bound on the run time of the UMDA. It is stronger than the bounds that follow from general black-box complexity theory and is matched by the run time of many evolutionary algorithms. The results are obtained through advanced analyses of the stochastic change of the frequencies of bit...

R package imputeTestbench to compare imputations methods for univariate time series

OpenAIRE

Bokde, Neeraj; Kulat, Kishore; Beck, Marcus W; Asencio-Cortés, Gualberto

2016-01-01

This paper describes the R package imputeTestbench that provides a testbench for comparing imputation methods for missing data in univariate time series. The imputeTestbench package can be used to simulate the amount and type of missing data in a complete dataset and compare filled data using different imputation methods. The user has the option to simulate missing data by removing observations completely at random or in blocks of different sizes. Several default imputation methods are includ...

Influence of microclimatic ammonia levels on productive performance of different broilers’ breeds estimated with univariate and multivariate approaches

Science.gov (United States)

Soliman, Essam S.; Moawed, Sherif A.; Hassan, Rania A.

2017-01-01

Background and Aim: Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people’s health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. Materials and Methods: A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Results: Ammonia levels were significantly higher (p0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (pbroiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. Conclusion: The study revealed that broiler’s growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers’ growth performance parameters data using multivariate discriminant function analysis. PMID:28919677

QRS complex detection based on continuous density hidden Markov models using univariate observations

Science.gov (United States)

Sotelo, S.; Arenas, W.; Altuve, M.

2018-04-01

In the electrocardiogram (ECG), the detection of QRS complexes is a fundamental step in the ECG signal processing chain since it allows the determination of other characteristics waves of the ECG and provides information about heart rate variability. In this work, an automatic QRS complex detector based on continuous density hidden Markov models (HMM) is proposed. HMM were trained using univariate observation sequences taken either from QRS complexes or their derivatives. The detection approach is based on the log-likelihood comparison of the observation sequence with a fixed threshold. A sliding window was used to obtain the observation sequence to be evaluated by the model. The threshold was optimized by receiver operating characteristic curves. Sensitivity (Sen), specificity (Spc) and F1 score were used to evaluate the detection performance. The approach was validated using ECG recordings from the MIT-BIH Arrhythmia database. A 6-fold cross-validation shows that the best detection performance was achieved with 2 states HMM trained with QRS complexes sequences (Sen = 0.668, Spc = 0.360 and F1 = 0.309). We concluded that these univariate sequences provide enough information to characterize the QRS complex dynamics from HMM. Future works are directed to the use of multivariate observations to increase the detection performance.

MULTIVARIANT AND UNIVARIANT INTERGROUP DIFFERENCES IN THE INVESTIGATED SPECIFIC MOTOR SPACE BETWEEN RESPONDENTS JUNIORS AND SENIORS MEMBERS OF THE MACEDONIAN NATIONAL KARATE TEAM

Directory of Open Access Journals (Sweden)

Kеnan Аsani

2013-07-01

Full Text Available The aim is to establish intergroup multivariant and univariant investigated differences in specific motor space between respondents juniors and seniors members of the Macedonian karate team. The sample of 30 male karate respondents covers juniors on 16,17 and seniors over 18 years.In the research were applied 20 specific motor tests. Based on Graph 1 where it is presented multivariant analysis of variance Manova and Anova can be noted that respondents juniors and seniors, although not belonging to the same population are not different in multivariant understudied area.W. lambda of .19, Rao-wool R - Approximation of 1.91 degrees of freedom df 1 = 20 and df 2 = 9 provides the level of significance of p =, 16. Based on univariant analysis for each variable separately can be seen that has been around intergroup statistically significant difference in seven SMAEGERI (kick in the sack with favoritism leg mae geri for 10 sec., SMAVASI (kick in the sack with favoritism foot mavashi geri by 10 sec., SUSIRO (kick in the sack with favoritism leg ushiro geri for 10 sec., SKIZAME (kick in the sack with favoritism hand kizame cuki for 10 sec., STAPNSR (taping with foot in sagital plane for 15 sec. SUDMNR (hitting a moving target with weaker hand and SUDMPN (hitting a moving target with favoritism foot of twenty applied manifest variables. There are no intergroup differences in multivariant investigated specific - motor space among the respondents juniors and seniors members of the Macedonian karate team. Based on univariant analysis for each variable separately can be seen that has been around intergroup statistically significant difference in seven SMAEGERI (kick in the sack with favoritism leg mae geri for 10 sec., SMAVASI (kick in the sack with favoritism foot mavashi geri by 10 sec., SUSIRO (kick in the sack with favoritism leg ushiro geri for 10 sec., SKIZAME (kick in the sack with favoritism hand kizame cuki for 10 sec., STAPNSR (taping with foot in

Segmentation of Coronary Angiograms Using Gabor Filters and Boltzmann Univariate Marginal Distribution Algorithm

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Fernando Cervantes-Sanchez

2016-01-01

Full Text Available This paper presents a novel method for improving the training step of the single-scale Gabor filters by using the Boltzmann univariate marginal distribution algorithm (BUMDA in X-ray angiograms. Since the single-scale Gabor filters (SSG are governed by three parameters, the optimal selection of the SSG parameters is highly desirable in order to maximize the detection performance of coronary arteries while reducing the computational time. To obtain the best set of parameters for the SSG, the area (Az under the receiver operating characteristic curve is used as fitness function. Moreover, to classify vessel and nonvessel pixels from the Gabor filter response, the interclass variance thresholding method has been adopted. The experimental results using the proposed method obtained the highest detection rate with Az=0.9502 over a training set of 40 images and Az=0.9583 with a test set of 40 images. In addition, the experimental results of vessel segmentation provided an accuracy of 0.944 with the test set of angiograms.

Visual classification of very fine-grained sediments: Evaluation through univariate and multivariate statistics

Science.gov (United States)

Hohn, M. Ed; Nuhfer, E.B.; Vinopal, R.J.; Klanderman, D.S.

1980-01-01

Classifying very fine-grained rocks through fabric elements provides information about depositional environments, but is subject to the biases of visual taxonomy. To evaluate the statistical significance of an empirical classification of very fine-grained rocks, samples from Devonian shales in four cored wells in West Virginia and Virginia were measured for 15 variables: quartz, illite, pyrite and expandable clays determined by X-ray diffraction; total sulfur, organic content, inorganic carbon, matrix density, bulk density, porosity, silt, as well as density, sonic travel time, resistivity, and ??-ray response measured from well logs. The four lithologic types comprised: (1) sharply banded shale, (2) thinly laminated shale, (3) lenticularly laminated shale, and (4) nonbanded shale. Univariate and multivariate analyses of variance showed that the lithologic classification reflects significant differences for the variables measured, difference that can be detected independently of stratigraphic effects. Little-known statistical methods found useful in this work included: the multivariate analysis of variance with more than one effect, simultaneous plotting of samples and variables on canonical variates, and the use of parametric ANOVA and MANOVA on ranked data. ?? 1980 Plenum Publishing Corporation.

Automatic Image Segmentation Using Active Contours with Univariate Marginal Distribution

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I. Cruz-Aceves

2013-01-01

Full Text Available This paper presents a novel automatic image segmentation method based on the theory of active contour models and estimation of distribution algorithms. The proposed method uses the univariate marginal distribution model to infer statistical dependencies between the control points on different active contours. These contours have been generated through an alignment process of reference shape priors, in order to increase the exploration and exploitation capabilities regarding different interactive segmentation techniques. This proposed method is applied in the segmentation of the hollow core in microscopic images of photonic crystal fibers and it is also used to segment the human heart and ventricular areas from datasets of computed tomography and magnetic resonance images, respectively. Moreover, to evaluate the performance of the medical image segmentations compared to regions outlined by experts, a set of similarity measures has been adopted. The experimental results suggest that the proposed image segmentation method outperforms the traditional active contour model and the interactive Tseng method in terms of segmentation accuracy and stability.

In situ calibration using univariate analyses based on the onboard ChemCam targets: first prediction of Martian rock and soil compositions

International Nuclear Information System (INIS)

Fabre, C.; Cousin, A.; Wiens, R.C.; Ollila, A.; Gasnault, O.; Maurice, S.; Sautter, V.; Forni, O.; Lasue, J.; Tokar, R.; Vaniman, D.; Melikechi, N.

2014-01-01

Curiosity rover landed on August 6th, 2012 in Gale Crater, Mars and it possesses unique analytical capabilities to investigate the chemistry and mineralogy of the Martian soil. In particular, the LIBS technique is being used for the first time on another planet with the ChemCam instrument, and more than 75,000 spectra have been returned in the first year on Mars. Curiosity carries body-mounted calibration targets specially designed for the ChemCam instrument, some of which are homgeneous glasses and others that are fine-grained glass-ceramics. We present direct calibrations, using these onboard standards to infer elements and element ratios by ratioing relative peak areas. As the laser spot size is around 300 μm, the LIBS technique provides measurements of the silicate glass compositions representing homogeneous material and measurements of the ceramic targets that are comparable to fine-grained rock or soil. The laser energy and the auto-focus are controlled for all sequences used for calibration. The univariate calibration curves present relatively to very good correlation coefficients with low RSDs for major and ratio calibrations. Trace element calibration curves (Li, Sr, and Mn), down to several ppm, can be used as a rapid tool to draw attention to remarkable rocks and soils along the traverse. First comparisons to alpha-particle X-ray spectroscopy (APXS) data, on selected targets, show good agreement for most elements and for Mg# and Al/Si estimates. SiO 2 estimates using univariate cannot be yet used. Na 2 O and K 2 O estimates are relevant for high alkali contents, but probably under estimated due to the CCCT initial compositions. Very good results for CaO and Al 2 O 3 estimates and satisfactory results for FeO are obtained. - Highlights: • In situ LIBS univariate calibrations are done using the Curiosity onboard standards. • Major and minor element contents can be rapidly obtained. • Trace element contents can be used as a rapid tool along the

Univariate and multivariate forecasting of hourly solar radiation with artificial intelligence techniques

Energy Technology Data Exchange (ETDEWEB)

Sfetsos, A. [7 Pirsou Str., Athens (Greece); Coonick, A.H. [Imperial Coll. of Science Technology and Medicine, Dept. of Electrical and Electronic Engineering, London (United Kingdom)

2000-07-01

This paper introduces a new approach for the forecasting of mean hourly global solar radiation received by a horizontal surface. In addition to the traditional linear methods, several artificial-intelligence-based techniques are studied. These include linear, feed-forward, recurrent Elman and Radial Basis neural networks alongside the adaptive neuro-fuzzy inference scheme. The problem is examined initially for the univariate case, and is extended to include additional meteorological parameters in the process of estimating the optimum model. The results indicate that the developed artificial intelligence models predict the solar radiation time series more effectively compared to the conventional procedures based on the clearness index. The forecasting ability of some models can be further enhanced with the use of additional meteorological parameters. (Author)

Identifying individuals at high risk of psychosis: predictive utility of Support Vector Machine using structural and functional MRI data

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Isabel eValli

2016-04-01

Full Text Available The identification of individuals at high risk of developing psychosis is entirely based on clinical assessment, associated with limited predictive potential. There is therefore increasing interest in the development of biological markers that could be used in clinical practice for this purpose. We studied 25 individuals with an At Risk Mental State for psychosis and 25 healthy controls using structural MRI, and functional MRI in conjunction with a verbal memory task. Data were analysed using a standard univariate analysis, and with Support Vector Machine (SVM, a multivariate pattern recognition technique that enables statistical inferences to be made at the level of the individual, yielding results with high translational potential. The application of SVM to structural MRI data permitted the identification of individuals at high risk of psychosis with a sensitivity of 68% and a specificity of 76%, resulting in an accuracy of 72% (p<0.001. Univariate volumetric between-group differences did not reach statistical significance. In contrast, the univariate fMRI analysis identified between-group differences (p<0.05 corrected while the application of SVM to the same data did not. Since SVM is well suited at identifying the pattern of abnormality that distinguishes two groups, whereas univariate methods are more likely to identify regions that individually are most different between two groups, our results suggest the presence of focal functional abnormalities in the context of a diffuse pattern of structural abnormalities in individuals at high clinical risk of psychosis.

An exercise in model validation: Comparing univariate statistics and Monte Carlo-based multivariate statistics

International Nuclear Information System (INIS)

Weathers, J.B.; Luck, R.; Weathers, J.W.

2009-01-01

The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.

An exercise in model validation: Comparing univariate statistics and Monte Carlo-based multivariate statistics

Energy Technology Data Exchange (ETDEWEB)

Weathers, J.B. [Shock, Noise, and Vibration Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: James.Weathers@ngc.com; Luck, R. [Department of Mechanical Engineering, Mississippi State University, 210 Carpenter Engineering Building, P.O. Box ME, Mississippi State, MS 39762-5925 (United States)], E-mail: Luck@me.msstate.edu; Weathers, J.W. [Structural Analysis Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: Jeffrey.Weathers@ngc.com

2009-11-15

The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

Science.gov (United States)

Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-01

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier

International Nuclear Information System (INIS)

Lauss, Martin; Frigyesi, Attila; Ryden, Tobias; Höglund, Mattias

2010-01-01

Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms. The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies. We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at http://cran.r-project.org/web/packages/rocc/index.html

In situ calibration using univariate analyses based on the onboard ChemCam targets: first prediction of Martian rock and soil compositions

Energy Technology Data Exchange (ETDEWEB)

Fabre, C. [GeoRessources lab, Université de Lorraine, Nancy (France); Cousin, A.; Wiens, R.C. [Los Alamos National Laboratory, Los Alamos, NM (United States); Ollila, A. [University of NM, Albuquerque (United States); Gasnault, O.; Maurice, S. [IRAP, Toulouse (France); Sautter, V. [Museum National d' Histoire Naturelle, Paris (France); Forni, O.; Lasue, J. [IRAP, Toulouse (France); Tokar, R.; Vaniman, D. [Planetary Science Institute, Tucson, AZ (United States); Melikechi, N. [Delaware State University (United States)

2014-09-01

Curiosity rover landed on August 6th, 2012 in Gale Crater, Mars and it possesses unique analytical capabilities to investigate the chemistry and mineralogy of the Martian soil. In particular, the LIBS technique is being used for the first time on another planet with the ChemCam instrument, and more than 75,000 spectra have been returned in the first year on Mars. Curiosity carries body-mounted calibration targets specially designed for the ChemCam instrument, some of which are homgeneous glasses and others that are fine-grained glass-ceramics. We present direct calibrations, using these onboard standards to infer elements and element ratios by ratioing relative peak areas. As the laser spot size is around 300 μm, the LIBS technique provides measurements of the silicate glass compositions representing homogeneous material and measurements of the ceramic targets that are comparable to fine-grained rock or soil. The laser energy and the auto-focus are controlled for all sequences used for calibration. The univariate calibration curves present relatively to very good correlation coefficients with low RSDs for major and ratio calibrations. Trace element calibration curves (Li, Sr, and Mn), down to several ppm, can be used as a rapid tool to draw attention to remarkable rocks and soils along the traverse. First comparisons to alpha-particle X-ray spectroscopy (APXS) data, on selected targets, show good agreement for most elements and for Mg# and Al/Si estimates. SiO{sub 2} estimates using univariate cannot be yet used. Na{sub 2}O and K{sub 2}O estimates are relevant for high alkali contents, but probably under estimated due to the CCCT initial compositions. Very good results for CaO and Al{sub 2}O{sub 3} estimates and satisfactory results for FeO are obtained. - Highlights: • In situ LIBS univariate calibrations are done using the Curiosity onboard standards. • Major and minor element contents can be rapidly obtained. • Trace element contents can be used as a

Univariate time series modeling and an application to future claims amount in SOCSO's invalidity pension scheme

Science.gov (United States)

Chek, Mohd Zaki Awang; Ahmad, Abu Bakar; Ridzwan, Ahmad Nur Azam Ahmad; Jelas, Imran Md.; Jamal, Nur Faezah; Ismail, Isma Liana; Zulkifli, Faiz; Noor, Syamsul Ikram Mohd

2012-09-01

The main objective of this study is to forecast the future claims amount of Invalidity Pension Scheme (IPS). All data were derived from SOCSO annual reports from year 1972 - 2010. These claims consist of all claims amount from 7 benefits offered by SOCSO such as Invalidity Pension, Invalidity Grant, Survivors Pension, Constant Attendance Allowance, Rehabilitation, Funeral and Education. Prediction of future claims of Invalidity Pension Scheme will be made using Univariate Forecasting Models to predict the future claims among workforce in Malaysia.

Univariate Lp and ɭ p Averaging, 0 < p < 1, in Polynomial Time by Utilization of Statistical Structure

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John E. Lavery

2012-10-01

Full Text Available We present evidence that one can calculate generically combinatorially expensive Lp and lp averages, 0 < p < 1, in polynomial time by restricting the data to come from a wide class of statistical distributions. Our approach differs from the approaches in the previous literature, which are based on a priori sparsity requirements or on accepting a local minimum as a replacement for a global minimum. The functionals by which Lp averages are calculated are not convex but are radially monotonic and the functionals by which lp averages are calculated are nearly so, which are the keys to solvability in polynomial time. Analytical results for symmetric, radially monotonic univariate distributions are presented. An algorithm for univariate lp averaging is presented. Computational results for a Gaussian distribution, a class of symmetric heavy-tailed distributions and a class of asymmetric heavy-tailed distributions are presented. Many phenomena in human-based areas are increasingly known to be represented by data that have large numbers of outliers and belong to very heavy-tailed distributions. When tails of distributions are so heavy that even medians (L1 and l1 averages do not exist, one needs to consider using lp minimization principles with 0 < p < 1.

The Use of Univariate and Multivariate Analyses in the Geochemical Exploration, Ravanj Lead Mine, Delijan, Iran

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Mostafa Nejadhadad

2017-11-01

Full Text Available A geochemical exploration program was applied to recognize the anomalous geochemical haloes at the Ravanj lead mine, Delijan, Iran. Sampling of unweathered rocks were undertaken across rock exposures on a 10 × 10 meter grid (n = 302 as well as the accessible parts of underground mine A (n = 42. First, the threshold values of all elements were determined using the cut-off values used in the exploratory data analysis (EDA method. Then, for further studies, elements with lognormal distributions (Pb, Zn, Ag, As, Cd, Co, Cu, Sb, S, Sr, Th, Ba, Bi, Fe, Ni and Mn were selected. Robustness against outliers is achieved by application of central log ratio transformation to address the closure problems with compositional data prior to principle components analysis (PCA. Results of these analyses show that, in the Ravanj deposit, Pb mineralization is characterized by a Pb-Ba-Ag-Sb ± Zn ± Cd association. The supra-mineralization haloes are characterized by barite and tetrahedrite in a Ba- Th- Ag- Cu- Sb- As- Sr association and sub-mineralization haloes are comprised of pyrite and tetrahedrite, probably reflecting a Fe-Cu-As-Bi-Ni-Co-Mo-Mn association. Using univariate and multivariate geostatistical analyses (e.g., EDA and robust PCA, four anomalies were detected and mapped in Block A of the Ravanj deposit. Anomalies 1 and 2 are around the ancient orebodies. Anomaly 3 is located in a thin bedded limestone-shale intercalation unit that does not show significant mineralization. Drilling of the fourth anomaly suggested a low grade, non-economic Pb mineralization.

Guaranteed Bounds on Information-Theoretic Measures of Univariate Mixtures Using Piecewise Log-Sum-Exp Inequalities

KAUST Repository

Nielsen, Frank

2016-12-09

Information-theoreticmeasures, such as the entropy, the cross-entropy and the Kullback-Leibler divergence between two mixture models, are core primitives in many signal processing tasks. Since the Kullback-Leibler divergence of mixtures provably does not admit a closed-form formula, it is in practice either estimated using costly Monte Carlo stochastic integration, approximated or bounded using various techniques. We present a fast and generic method that builds algorithmically closed-form lower and upper bounds on the entropy, the cross-entropy, the Kullback-Leibler and the α-divergences of mixtures. We illustrate the versatile method by reporting our experiments for approximating the Kullback-Leibler and the α-divergences between univariate exponential mixtures, Gaussian mixtures, Rayleigh mixtures and Gamma mixtures.

Cost-effectiveness Analysis of Nutritional Support for the Prevention of Pressure Ulcers in High-Risk Hospitalized Patients.

Science.gov (United States)

Tuffaha, Haitham W; Roberts, Shelley; Chaboyer, Wendy; Gordon, Louisa G; Scuffham, Paul A

2016-06-01

To evaluate the cost-effectiveness of nutritional support compared with standard care in preventing pressure ulcers (PrUs) in high-risk hospitalized patients. An economic model using data from a systematic literature review. A meta-analysis of randomized controlled trials on the efficacy of nutritional support in reducing the incidence of PrUs was conducted. Modeled cohort of hospitalized patients at high risk of developing PrUs and malnutrition simulated during their hospital stay and up to 1 year. Standard care included PrU prevention strategies, such as redistribution surfaces, repositioning, and skin protection strategies, along with standard hospital diet. In addition to the standard care, the intervention group received nutritional support comprising patient education, nutrition goal setting, and the consumption of high-protein supplements. The analysis was from a healthcare payer perspective. Key outcomes of the model included the average costs and quality-adjusted life years. Model results were tested in univariate sensitivity analyses, and decision uncertainty was characterized using a probabilistic sensitivity analysis. Compared with standard care, nutritional support was cost saving at AU $425 per patient and marginally more effective with an average 0.005 quality-adjusted life years gained. The probability of nutritional support being cost-effective was 87%. Nutritional support to prevent PrUs in high-risk hospitalized patients is cost-effective with substantial cost savings predicted. Hospitals should implement the recommendations from the current PrU practice guidelines and offer nutritional support to high-risk patients.

Univariate and multiple linear regression analyses for 23 single nucleotide polymorphisms in 14 genes predisposing to chronic glomerular diseases and IgA nephropathy in Han Chinese.

Science.gov (United States)

Wang, Hui; Sui, Weiguo; Xue, Wen; Wu, Junyong; Chen, Jiejing; Dai, Yong

2014-09-01

Immunoglobulin A nephropathy (IgAN) is a complex trait regulated by the interaction among multiple physiologic regulatory systems and probably involving numerous genes, which leads to inconsistent findings in genetic studies. One possibility of failure to replicate some single-locus results is that the underlying genetics of IgAN nephropathy is based on multiple genes with minor effects. To learn the association between 23 single nucleotide polymorphisms (SNPs) in 14 genes predisposing to chronic glomerular diseases and IgAN in Han males, the 23 SNPs genotypes of 21 Han males were detected and analyzed with a BaiO gene chip, and their associations were analyzed with univariate analysis and multiple linear regression analysis. Analysis showed that CTLA4 rs231726 and CR2 rs1048971 revealed a significant association with IgAN. These findings support the multi-gene nature of the etiology of IgAN and propose a potential gene-gene interactive model for future studies.

Evaluation of 10 AMD Associated Polymorphisms as a Cause of Choroidal Neovascularization in Highly Myopic Eyes.

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Alvaro Velazquez-Villoria

Full Text Available Choroidal neovascularization (CNV commonly occurs in age related macular degeneration and pathological myopia patients. In this study we conducted a case-control prospective study including 431 participants. The aim of this study was to determine the potential association between 10 single nucleotide polymorphisms (SNPs located in 4 different genetic regions (CFI, COL8A1, LIPC, and APOE, and choroidal neovascularization in age-related macular degeneration and the development of choroidal neovascularization in highly myopic eyes of a Caucasian population. Univariate and multivariate logistic regression analysis adjusted for age, sex and hypertension was performed for each allele, genotype and haplotype frequency analysis. We found that in the univariate analysis that both single-nucleotide polymorphisms in COL8A1 gene (rs13095226 and rs669676 together with age, sex and hypertension were significantly associated with myopic CNV development in Spanish patients (p0.05; however, analysis of the axial length between genotypes of rs13095226 revealed an important influence of COL8A1 in the development of CNV in high myopia. Furthermore we conducted a meta-analysis of COL8A1, CFI and LIPC genes SNPs (rs669676, rs10033900 and rs10468017 and found that only rs669676 of these SNPs were associated with high myopia neovascularization.

High serum uric acid concentration predicts poor survival in patients with breast cancer.

Science.gov (United States)

Yue, Cai-Feng; Feng, Pin-Ning; Yao, Zhen-Rong; Yu, Xue-Gao; Lin, Wen-Bin; Qian, Yuan-Min; Guo, Yun-Miao; Li, Lai-Sheng; Liu, Min

2017-10-01

Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of BCL2 and p53 on postmastectomy radiotherapy response in high-risk breast cancer. A subgroup analysis of DBCG82 b and c

International Nuclear Information System (INIS)

Kyndi, M.; Alsner, J.; Nielsen, H.M.; Overgaard, J.; Soerensen, F.B.; Knudsen, H.; Overgaard, M.

2008-01-01

Purpose. To examine p53 and BCL2 expression in high-risk breast cancer patients randomized to postmastectomy radiotherapy (PMRT). Patients and methods. The present analysis included 1 000 of 3 083 high-risk breast cancer patients randomly assigned to PMRT in the DBCG82 b and c studies. Tissue microarray sections were stained with immunohistochemistry for p53 and BCL2. Median potential follow-up was 17 years. Clinical endpoints were locoregional recurrence (LRR), distant metastases (DM), overall mortality, and overall survival (OS). Statistical analyses included Kappa statistics, χ2 or exact tests, Kaplan-Meier probability plots, Log-rank test, and Cox univariate and multivariate regression analyses. Results. p53 accumulation was not significantly associated with increased overall mortality, DM or LRR probability in univariate or multivariate Cox regression analyses. Kaplan-Meier probability plots showed reduced OS and improved DM and LRR probabilities after PMRT within subgroups of both p53 negative and p53 positive patients. Negative BCL2 expression was significantly associated with increased overall mortality, DM and LRR probability in multivariate Cox regression analyses. Kaplan-Meier probability plots showed a significantly improved overall survival after PMRT for the BCL2 positive subgroup, whereas practically no survival improvement was seen after PMRT for the BCL2 negative subgroup. In multivariate analysis of OS, however, no significant interaction was found between BCL2 and randomization status. Significant reductions in LRR probability after PMRT were recorded within both the BCL2 positive and BCL2 negative subgroups. Conclusion. p53 was not associated with survival after radiotherapy in high-risk breast cancer, but BCL2 might be

Study of Ecotype and Sowing Date Interaction in Cumin (Cuminum cyminum L. using Different Univariate Stability Parameters

Directory of Open Access Journals (Sweden)

J Ghanbari

2017-06-01

Full Text Available Introduction Cumin is one of the most important medicinal plants in Iran and today, it is in the second level of popularity between spices in the world after black pepper. Cumin is an aromatic plant used as flavoring and seasoning agent in foods. Cumin seeds have been found to possess significant biological and have been used for treatment of toothache, dyspepsia, diarrhoea, epilepsy and jaundice. Knowledge of GEI is advantageous to have a cultivar that gives consistently high yield in a broad range of environments and to increase efficiency of breeding program and selection of best genotypes. A genotype that has stable trait expression across environments contributes little to GEI and its performance should be more predictable from the main several statistical methods have been proposed for stability analysis, with the aim of explaining the information contained in the GEI. Regression technique was proposed by Finlay and Wilkinson (1963 and was improved by Eberhart and Russell (1966. Generally, genotype stability was estimated by the slope of and deviation from the regression line for each of the genotypes. This is a popular method in stability analysis and has been applied in many crops. Non-parametric methods (rank mean (R, standard deviation rank (SDR and yield index ratio (YIR, environmental variance (S2i and genotypic variation coefficient (CVi Wricke's ecovalence and Shukla's stability variance (Shukla, 1972 have been used to determine genotype-by-environment interaction in many studies. This study was aimed to evaluate the ecotype × sowing date interaction in cumin and to evaluation of genotypic response of cumin to different sowing dates using univariate stability parameters. Materials and Methods In order to study of ecotype × sowing date interaction, different cumin ecotypes: Semnan, Fars, Yazd, Golestan, Khorasan-Razavi, Khorasan-Shomali, Khorasan-Jonoubi, Isfahan and Kerman in 5 different sowing dates (26th December, 10th January

18F-FET PET prior to recurrent high-grade glioma re-irradiation-additional prognostic value of dynamic time-to-peak analysis and early static summation images?

Science.gov (United States)

Fleischmann, Daniel F; Unterrainer, Marcus; Bartenstein, Peter; Belka, Claus; Albert, Nathalie L; Niyazi, Maximilian

2017-04-01

Most high-grade gliomas (HGG) recur after initial multimodal therapy and re-irradiation (Re-RT) has been shown to be a valuable re-treatment option in selected patients. We evaluated the prognostic value of dynamic time-to-peak analysis and early static summation images in O-(2- 18 F-fluoroethyl)-l-tyrosine ( 18 F-FET) PET for patients treated with Re-RT ± concomitant bevacizumab. We retrospectively analyzed 72 patients suffering from recurrent HGG with 18 F-FET PET prior to Re-RT. PET analysis revealed the maximal tumor-to-background-ratio (TBR max ), the biological tumor volume, the number of PET-foci and pattern of time-activity-curves (TACs; increasing vs. decreasing). Furthermore, the novel PET parameters early TBR max (at 5-15 min post-injection) and minimal time-to-peak (TTP min ) were evaluated. Additional analysis was performed for gender, age, KPS, O6-methylguanine-DNA methyltransferase methylation status, isocitrate dehydrogenase 1 mutational status, WHO grade and concomitant bevacizumab therapy. The influence of PET and clinical parameters on post-recurrence survival (PRS) was investigated. Shorter TTP min was related to shorter PRS after Re-RT with 6 months for TTP min  25 min (p = 0.027). TTP min had a significant impact on PRS both on univariate (p = 0.027; continuous) and multivariate analysis (p = 0.011; continuous). Other factors significantly related to PRS on multivariate analysis were increasing vs. decreasing TACs (p = 0.008) and Karnofsky Performance Score (p = 0.015; PET parameters were not significantly related to PRS on univariate analysis. Dynamic 18 F-FET PET with TTP min provides a high prognostic value for recurrent HGG prior to Re-RT, whereas early TBR max does not. Dynamic 18 F-FET PET using TTP min might help to personalize Re-RT treatment regimens in future through voxelwise TTP min analysis for dose painting purposes and PET-guided dose escalation.

Preoperative C-reactive protein as a prognostic predictor for upper tract urothelial carcinoma: A systematic review and meta-analysis.

Science.gov (United States)

Luo, You; Fu, Sheng Jun; She, Dong Li; Xiong, H U; Yang, L I

2015-07-01

Upper tract urothelial carcinoma (UTUC) is a relatively rare and highly aggressive tumor. However, the prognosis of UTUC is rarely predicted accurately due to the lack of reliable biomarkers. C-reactive protein (CRP) has been found to be correlated with several types of cancer. In this study, we performed a systematic review and meta-analysis to determine the association between CRP levels and prognosis in UTUC. A computerized search was conducted through PubMed, Embase, Web of Science, the Cochrane Library and CBM databases to identify clinical studies that have evaluated the association between preoperative CRP levels and prognosis of UTUC. The prognostic outcomes included recurrence-free survival (RFS), cancer-specific survival (CSS) and overall survival (OS). We extracted and synthesized corresponding hazard ratios (HRs) and confidence intervals (CIs) using Review Manager 5.3 software. We identified 7 retrospective cohort studies including a total of 1,919 patients and analyzed these studies using univariate and multivariate models. Our meta-analysis results revealed that RFS and CSS were significantly different between patients with elevated CRP levels and those with low CRP levels (P<0.0001 and P<0.00001, respectively); however, that was not the case for OS (P=0.22) in the multivariate or the univariate model. The pooled HR of RFS was 2.90 (95% CI: 1.87-4.51, P<0.00001) in the univariate analysis and 1.57 (95% CI: 1.26-1.97, P<0.0001) in the multivariate analysis. The pooled HRs of CSS were 2.78 (95% CI: 1.75-4.43, P<0.0001) and 1.64 (95% CI: 1.32-2.03, P<0.00001) in the univariate and multivariate analysis, respectively. However, the pooled HRs of OS were not significant in the univariate [1.24 (95% CI: 0.72-2.15, P=0.43)] or the multivariate analysis [1.24 (95% CI: 0.88-1.75, P=0.22)]. In conclusion, our meta-analysis results suggested that CRP level may be a prognostic predictor in UTUC.

Reciprocal Benefits of Mass-Univariate and Multivariate Modeling in Brain Mapping: Applications to Event-Related Functional MRI, H215O-, and FDG-PET

Directory of Open Access Journals (Sweden)

James R. Moeller

2006-01-01

Full Text Available In brain mapping studies of sensory, cognitive, and motor operations, specific waveforms of dynamic neural activity are predicted based on theoretical models of human information processing. For example in event-related functional MRI (fMRI, the general linear model (GLM is employed in mass-univariate analyses to identify the regions whose dynamic activity closely matches the expected waveforms. By comparison multivariate analyses based on PCA or ICA provide greater flexibility in detecting spatiotemporal properties of experimental data that may strongly support alternative neuroscientific explanations. We investigated conjoint multivariate and mass-univariate analyses that combine the capabilities to (1 verify activation of neural machinery we already understand and (2 discover reliable signatures of new neural machinery. We examined combinations of GLM and PCA that recover latent neural signals (waveforms and footprints with greater accuracy than either method alone. Comparative results are illustrated with analyses of real fMRI data, adding to Monte Carlo simulation support.

Time series analysis in the social sciences the fundamentals

CERN Document Server

Shin, Youseop

2017-01-01

Times Series Analysis in the Social Sciences is a practical and highly readable introduction written exclusively for students and researchers whose mathematical background is limited to basic algebra. The book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and re

A Course in Time Series Analysis

CERN Document Server

Peña, Daniel; Tsay, Ruey S

2011-01-01

New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, a

Cost minimization analysis of high-dose-rate versus low-dose-rate brachytherapy in endometrial cancer

International Nuclear Information System (INIS)

Pinilla, James

1998-01-01

Purpose: Endometrial cancer is a common, usually curable malignancy whose treatment frequently involves low-dose-rate (LDR) or high-dose-rate (HDR) brachytherapy. These treatments involve substantial resource commitments and this is increasingly important. This paper presents a cost minimization analysis of HDR versus LDR brachytherapy in the treatment of endometrial cancer. Methods and Materials: The perspective of the analysis is that of the payor, in this case the Ministry of Health. One course of LDR treatment is compared to two courses of HDR treatment. The two alternatives are considered to be comparable with respect to local control, survival, and toxicities. Labor, overhead, and capital costs are accounted for and carefully measured. A 5% inflation rate is used where applicable. A univariate sensitivity analysis is performed. Results: The HDR regime is 22% less expensive compared to the LDR regime. This is $991.66 per patient or, based on the current workload of this department (30 patients per year) over the useful lifetime of the after loader, $297,498 over 10 years in 1997 dollars. Conclusion: HDR brachytherapy minimizes costs in the treatment of endometrial cancer relative to LDR brachytherapy. These results may be used by other centers to make rational decisions regarding brachytherapy equipment replacement or acquisition

Univariate and Cross Tabulation Analysis of Construction Accidents in the Aegean Region

OpenAIRE

BARADAN, Selim; AKBOĞA, Özge; ÇETİNKAYA, Ufuk; USMEN, Mümtaz A.

2016-01-01

It is crucial toinvestigate case studies and analyze accident statistics to establish safetyand health culture in the construction industry, which exhibits high fatalityrates. However, it is difficult to find reliable and accurate constructionaccidents data in Turkeydue to inadequate accident reporting and recordkeeping system, which hindersstatistical safety research. Therefore, an independent database was generatedby using inspection reports in this research study. Data mining was performed...

The issue of multiple univariate comparisons in the context of neuroelectric brain mapping: an application in a neuromarketing experiment.

Science.gov (United States)

Vecchiato, G; De Vico Fallani, F; Astolfi, L; Toppi, J; Cincotti, F; Mattia, D; Salinari, S; Babiloni, F

2010-08-30

This paper presents some considerations about the use of adequate statistical techniques in the framework of the neuroelectromagnetic brain mapping. With the use of advanced EEG/MEG recording setup involving hundred of sensors, the issue of the protection against the type I errors that could occur during the execution of hundred of univariate statistical tests, has gained interest. In the present experiment, we investigated the EEG signals from a mannequin acting as an experimental subject. Data have been collected while performing a neuromarketing experiment and analyzed with state of the art computational tools adopted in specialized literature. Results showed that electric data from the mannequin's head presents statistical significant differences in power spectra during the visualization of a commercial advertising when compared to the power spectra gathered during a documentary, when no adjustments were made on the alpha level of the multiple univariate tests performed. The use of the Bonferroni or Bonferroni-Holm adjustments returned correctly no differences between the signals gathered from the mannequin in the two experimental conditions. An partial sample of recently published literature on different neuroscience journals suggested that at least the 30% of the papers do not use statistical protection for the type I errors. While the occurrence of type I errors could be easily managed with appropriate statistical techniques, the use of such techniques is still not so largely adopted in the literature. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Real-time prediction of extreme ambient carbon monoxide concentrations due to vehicular exhaust emissions using univariate linear stochastic models

International Nuclear Information System (INIS)

Sharma, P.; Khare, M.

2000-01-01

Historical data of the time-series of carbon monoxide (CO) concentration was analysed using Box-Jenkins modelling approach. Univariate Linear Stochastic Models (ULSMs) were developed to examine the degree of prediction possible for situations where only a limited data set, restricted only to the past record of pollutant data are available. The developed models can be used to provide short-term, real-time forecast of extreme CO concentrations for an Air Quality Control Region (AQCR), comprising a major traffic intersection in a Central Business District of Delhi City, India. (author)

A kernel version of spatial factor analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2009-01-01

. Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press et al. describe kernel methods among many other subjects. Nielsen and Canty use kernel PCA to detect change in univariate airborne digital camera images. The kernel...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

Monitoring endemic livestock diseases using laboratory diagnostic data: A simulation study to evaluate the performance of univariate process monitoring control algorithms.

Science.gov (United States)

Lopes Antunes, Ana Carolina; Dórea, Fernanda; Halasa, Tariq; Toft, Nils

2016-05-01

Surveillance systems are critical for accurate, timely monitoring and effective disease control. In this study, we investigated the performance of univariate process monitoring control algorithms in detecting changes in seroprevalence for endemic diseases. We also assessed the effect of sample size (number of sentinel herds tested in the surveillance system) on the performance of the algorithms. Three univariate process monitoring control algorithms were compared: Shewart p Chart(1) (PSHEW), Cumulative Sum(2) (CUSUM) and Exponentially Weighted Moving Average(3) (EWMA). Increases in seroprevalence were simulated from 0.10 to 0.15 and 0.20 over 4, 8, 24, 52 and 104 weeks. Each epidemic scenario was run with 2000 iterations. The cumulative sensitivity(4) (CumSe) and timeliness were used to evaluate the algorithms' performance with a 1% false alarm rate. Using these performance evaluation criteria, it was possible to assess the accuracy and timeliness of the surveillance system working in real-time. The results showed that EWMA and PSHEW had higher CumSe (when compared with the CUSUM) from week 1 until the end of the period for all simulated scenarios. Changes in seroprevalence from 0.10 to 0.20 were more easily detected (higher CumSe) than changes from 0.10 to 0.15 for all three algorithms. Similar results were found with EWMA and PSHEW, based on the median time to detection. Changes in the seroprevalence were detected later with CUSUM, compared to EWMA and PSHEW for the different scenarios. Increasing the sample size 10 fold halved the time to detection (CumSe=1), whereas increasing the sample size 100 fold reduced the time to detection by a factor of 6. This study investigated the performance of three univariate process monitoring control algorithms in monitoring endemic diseases. It was shown that automated systems based on these detection methods identified changes in seroprevalence at different times. Increasing the number of tested herds would lead to faster

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.

Science.gov (United States)

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-07-01

A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Quantitative coronary plaque analysis predicts high-risk plaque morphology on coronary computed tomography angiography: results from the ROMICAT II trial.

Science.gov (United States)

Liu, Ting; Maurovich-Horvat, Pál; Mayrhofer, Thomas; Puchner, Stefan B; Lu, Michael T; Ghemigian, Khristine; Kitslaar, Pieter H; Broersen, Alexander; Pursnani, Amit; Hoffmann, Udo; Ferencik, Maros

2018-02-01

Semi-automated software can provide quantitative assessment of atherosclerotic plaques on coronary CT angiography (CTA). The relationship between established qualitative high-risk plaque features and quantitative plaque measurements has not been studied. We analyzed the association between quantitative plaque measurements and qualitative high-risk plaque features on coronary CTA. We included 260 patients with plaque who underwent coronary CTA in the Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography (ROMICAT) II trial. Quantitative plaque assessment and qualitative plaque characterization were performed on a per coronary segment basis. Quantitative coronary plaque measurements included plaque volume, plaque burden, remodeling index, and diameter stenosis. In qualitative analysis, high-risk plaque was present if positive remodeling, low CT attenuation plaque, napkin-ring sign or spotty calcium were detected. Univariable and multivariable logistic regression analyses were performed to assess the association between quantitative and qualitative high-risk plaque assessment. Among 888 segments with coronary plaque, high-risk plaque was present in 391 (44.0%) segments by qualitative analysis. In quantitative analysis, segments with high-risk plaque had higher total plaque volume, low CT attenuation plaque volume, plaque burden and remodeling index. Quantitatively assessed low CT attenuation plaque volume (odds ratio 1.12 per 1 mm 3 , 95% CI 1.04-1.21), positive remodeling (odds ratio 1.25 per 0.1, 95% CI 1.10-1.41) and plaque burden (odds ratio 1.53 per 0.1, 95% CI 1.08-2.16) were associated with high-risk plaque. Quantitative coronary plaque characteristics (low CT attenuation plaque volume, positive remodeling and plaque burden) measured by semi-automated software correlated with qualitative assessment of high-risk plaque features.

Application of Raman Spectroscopy and Univariate Modelling As a Process Analytical Technology for Cell Therapy Bioprocessing

Science.gov (United States)

Baradez, Marc-Olivier; Biziato, Daniela; Hassan, Enas; Marshall, Damian

2018-01-01

Cell therapies offer unquestionable promises for the treatment, and in some cases even the cure, of complex diseases. As we start to see more of these therapies gaining market authorization, attention is turning to the bioprocesses used for their manufacture, in particular the challenge of gaining higher levels of process control to help regulate cell behavior, manage process variability, and deliver product of a consistent quality. Many processes already incorporate the measurement of key markers such as nutrient consumption, metabolite production, and cell concentration, but these are often performed off-line and only at set time points in the process. Having the ability to monitor these markers in real-time using in-line sensors would offer significant advantages, allowing faster decision-making and a finer level of process control. In this study, we use Raman spectroscopy as an in-line optical sensor for bioprocess monitoring of an autologous T-cell immunotherapy model produced in a stirred tank bioreactor system. Using reference datasets generated on a standard bioanalyzer, we develop chemometric models from the Raman spectra for glucose, glutamine, lactate, and ammonia. These chemometric models can accurately monitor donor-specific increases in nutrient consumption and metabolite production as the primary T-cell transition from a recovery phase and begin proliferating. Using a univariate modeling approach, we then show how changes in peak intensity within the Raman spectra can be correlated with cell concentration and viability. These models, which act as surrogate markers, can be used to monitor cell behavior including cell proliferation rates, proliferative capacity, and transition of the cells to a quiescent phenotype. Finally, using the univariate models, we also demonstrate how Raman spectroscopy can be applied for real-time monitoring. The ability to measure these key parameters using an in-line Raman optical sensor makes it possible to have immediate

Application of Raman Spectroscopy and Univariate Modelling As a Process Analytical Technology for Cell Therapy Bioprocessing.

Science.gov (United States)

Baradez, Marc-Olivier; Biziato, Daniela; Hassan, Enas; Marshall, Damian

2018-01-01

Cell therapies offer unquestionable promises for the treatment, and in some cases even the cure, of complex diseases. As we start to see more of these therapies gaining market authorization, attention is turning to the bioprocesses used for their manufacture, in particular the challenge of gaining higher levels of process control to help regulate cell behavior, manage process variability, and deliver product of a consistent quality. Many processes already incorporate the measurement of key markers such as nutrient consumption, metabolite production, and cell concentration, but these are often performed off-line and only at set time points in the process. Having the ability to monitor these markers in real-time using in-line sensors would offer significant advantages, allowing faster decision-making and a finer level of process control. In this study, we use Raman spectroscopy as an in-line optical sensor for bioprocess monitoring of an autologous T-cell immunotherapy model produced in a stirred tank bioreactor system. Using reference datasets generated on a standard bioanalyzer, we develop chemometric models from the Raman spectra for glucose, glutamine, lactate, and ammonia. These chemometric models can accurately monitor donor-specific increases in nutrient consumption and metabolite production as the primary T-cell transition from a recovery phase and begin proliferating. Using a univariate modeling approach, we then show how changes in peak intensity within the Raman spectra can be correlated with cell concentration and viability. These models, which act as surrogate markers, can be used to monitor cell behavior including cell proliferation rates, proliferative capacity, and transition of the cells to a quiescent phenotype. Finally, using the univariate models, we also demonstrate how Raman spectroscopy can be applied for real-time monitoring. The ability to measure these key parameters using an in-line Raman optical sensor makes it possible to have immediate

Application of Raman Spectroscopy and Univariate Modelling As a Process Analytical Technology for Cell Therapy Bioprocessing

Directory of Open Access Journals (Sweden)

Marc-Olivier Baradez

2018-03-01

Full Text Available Cell therapies offer unquestionable promises for the treatment, and in some cases even the cure, of complex diseases. As we start to see more of these therapies gaining market authorization, attention is turning to the bioprocesses used for their manufacture, in particular the challenge of gaining higher levels of process control to help regulate cell behavior, manage process variability, and deliver product of a consistent quality. Many processes already incorporate the measurement of key markers such as nutrient consumption, metabolite production, and cell concentration, but these are often performed off-line and only at set time points in the process. Having the ability to monitor these markers in real-time using in-line sensors would offer significant advantages, allowing faster decision-making and a finer level of process control. In this study, we use Raman spectroscopy as an in-line optical sensor for bioprocess monitoring of an autologous T-cell immunotherapy model produced in a stirred tank bioreactor system. Using reference datasets generated on a standard bioanalyzer, we develop chemometric models from the Raman spectra for glucose, glutamine, lactate, and ammonia. These chemometric models can accurately monitor donor-specific increases in nutrient consumption and metabolite production as the primary T-cell transition from a recovery phase and begin proliferating. Using a univariate modeling approach, we then show how changes in peak intensity within the Raman spectra can be correlated with cell concentration and viability. These models, which act as surrogate markers, can be used to monitor cell behavior including cell proliferation rates, proliferative capacity, and transition of the cells to a quiescent phenotype. Finally, using the univariate models, we also demonstrate how Raman spectroscopy can be applied for real-time monitoring. The ability to measure these key parameters using an in-line Raman optical sensor makes it possible

a meta-analysis

Indian Academy of Sciences (India)

Chrissa G. Tsiara

2018-03-13

Mar 13, 2018 ... a meta-analysis of case–control studies was conducted. Univariate and ...... recent hepatitis C virus: potential benefit for ribavirin use in. HCV/HIV ... C/G polymorphism in breast pathologies and in HIV-infected patients.

Systemic Immune-Inflammation Index and Circulating T-Cell Immune Index Predict Outcomes in High-Risk Acral Melanoma Patients Treated with High-Dose Interferon

Directory of Open Access Journals (Sweden)

Jiayi Yu

2017-10-01

Full Text Available High-dose interferon alfa-2b (IFN-α-2b improves the survival of patients with high-risk melanoma. We aimed to identify baseline peripheral blood biomarkers to predict the outcome of acral melanoma patients treated with IFN-α-2b. Pretreatment baseline parameters and clinical data were assessed in 226 patients with acral melanoma. Relapse-free survival (RFS and overall survival (OS were assessed using the Kaplan-Meier method, and multivariate Cox regression analyses were applied after adjusting for stage, lactate dehydrogenase (LDH, and ulceration. Univariate analysis showed that neutrophil-to-lymphocyte ratio ≥2.35, platelet-to-lymphocyte ratio ≥129, systemic immune-inflammation index (SII ≥615 × 109/l, and elevated LDH were significantly associated with poor RFS and OS. The SII is calculated as follows: platelet count × neutrophil count/lymphocyte count. On multivariate analysis, the SII was associated with RFS [hazard ratio (HR=1.661, 95% confidence interval (CI: 1.066-2.586, P=.025] and OS (HR=2.071, 95% CI: 1.204-3.564, P=.009. Additionally, we developed a novel circulating T-cell immune index (CTII calculated as follows: cytotoxic T lymphocytes/(CD4+ regulatory T cells × CD8+ regulatory T cells. On univariate analysis, the CTII was associated with OS (HR=1.73, 95% CI: 1.01-2.94, P=.044. The SII and CTII might serve as prognostic indicators in acral melanoma patients treated with IFN-α-2b. The indexes are easily obtainable via routine tests in clinical practice.

Who uses nursing theory? A univariate descriptive analysis of five years' research articles.

Science.gov (United States)

Bond, A Elaine; Eshah, Nidal Farid; Bani-Khaled, Mohammed; Hamad, Atef Omar; Habashneh, Samira; Kataua', Hussein; al-Jarrah, Imad; Abu Kamal, Andaleeb; Hamdan, Falastine Rafic; Maabreh, Roqia

2011-06-01

Since the early 1950s, nursing leaders have worked diligently to build the Scientific Discipline of Nursing, integrating Theory, Research and Practice. Recently, the role of theory has again come into question, with some scientists claiming nurses are not using theory to guide their research, with which to improve practice. The purposes of this descriptive study were to determine: (i) Were nursing scientists' research articles in leading nursing journals based on theory? (ii) If so, were the theories nursing theories or borrowed theories? (iii) Were the theories integrated into the studies, or were they used as organizing frameworks? Research articles from seven top ISI journals were analysed, excluding regularly featured columns, meta-analyses, secondary analysis, case studies and literature reviews. The authors used King's dynamic Interacting system and Goal Attainment Theory as an organizing framework. They developed consensus on how to identify the integration of theory, searching the Title, Abstract, Aims, Methods, Discussion and Conclusion sections of each research article, whether quantitative or qualitative. Of 2857 articles published in the seven journals from 2002 to, and including, 2006, 2184 (76%) were research articles. Of the 837 (38%) authors who used theories, 460 (55%) used nursing theories, 377 (45%) used other theories: 776 (93%) of those who used theory integrated it into their studies, including qualitative studies, while 51 (7%) reported they used theory as an organizing framework for their studies. Closer analysis revealed theory principles were implicitly implied, even in research reports that did not explicitly report theory usage. Increasing numbers of nursing research articles (though not percentagewise) continue to be guided by theory, and not always by nursing theory. Newer nursing research methods may not explicitly state the use of nursing theory, though it is implicitly implied. © 2010 The Authors. Scandinavian Journal of Caring

Improving the performance of univariate control charts for abnormal detection and classification

Science.gov (United States)

Yiakopoulos, Christos; Koutsoudaki, Maria; Gryllias, Konstantinos; Antoniadis, Ioannis

2017-03-01

Bearing failures in rotating machinery can cause machine breakdown and economical loss, if no effective actions are taken on time. Therefore, it is of prime importance to detect accurately the presence of faults, especially at their early stage, to prevent sequent damage and reduce costly downtime. The machinery fault diagnosis follows a roadmap of data acquisition, feature extraction and diagnostic decision making, in which mechanical vibration fault feature extraction is the foundation and the key to obtain an accurate diagnostic result. A challenge in this area is the selection of the most sensitive features for various types of fault, especially when the characteristics of failures are difficult to be extracted. Thus, a plethora of complex data-driven fault diagnosis methods are fed by prominent features, which are extracted and reduced through traditional or modern algorithms. Since most of the available datasets are captured during normal operating conditions, the last decade a number of novelty detection methods, able to work when only normal data are available, have been developed. In this study, a hybrid method combining univariate control charts and a feature extraction scheme is introduced focusing towards an abnormal change detection and classification, under the assumption that measurements under normal operating conditions of the machinery are available. The feature extraction method integrates the morphological operators and the Morlet wavelets. The effectiveness of the proposed methodology is validated on two different experimental cases with bearing faults, demonstrating that the proposed approach can improve the fault detection and classification performance of conventional control charts.

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

Science.gov (United States)

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

Is the prognostic significance of O6-methylguanine- DNA methyltransferase promoter methylation equally important in glioblastomas of patients from different continents? A systematic review with meta-analysis.

Science.gov (United States)

Meng, Wei; Jiang, Yangyang; Ma, Jie

2017-01-01

O6-methylguanine-DNA methyltransferase (MGMT) is an independent predictor of therapeutic response and potential prognosis in patients with glioblastoma multiforme (GBM). However, its significance of clinical prognosis in different continents still needs to be explored. To explore the effects of MGMT promoter methylation on both progression-free survival (PFS) and overall survival (OS) among GBM patients from different continents, a systematic review of published studies was conducted. A total of 5103 patients from 53 studies were involved in the systematic review and the total percentage of MGMT promoter methylation was 45.53%. Of these studies, 16 studies performed univariate analyses and 17 performed multivariate analyses of MGMT promoter methylation on PFS. The pooled hazard ratio (HR) estimated for PFS was 0.55 (95% CI 0.50, 0.60) by univariate analysis and 0.43 (95% CI 0.38, 0.48) by multivariate analysis. The effect of MGMT promoter methylation on OS was explored in 30 studies by univariate analysis and in 30 studies by multivariate analysis. The combined HR was 0.48 (95% CI 0.44, 0.52) and 0.42 (95% CI 0.38, 0.45), respectively. In each subgroup divided by areas, the prognostic significance still remained highly significant. The proportion of methylation in each group was in inverse proportion to the corresponding HR in the univariate and multivariate analyses of PFS. However, from the perspective of OS, compared with data from Europe and the US, higher methylation rates in Asia did not bring better returns.

Development of a Univariate Membrane-Based Mid-Infrared Method for Protein Quantitation and Total Lipid Content Analysis of Biological Samples

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Ivona Strug

2014-01-01

Full Text Available Biological samples present a range of complexities from homogeneous purified protein to multicomponent mixtures. Accurate qualification of such samples is paramount to downstream applications. We describe the development of an MIR spectroscopy-based analytical method offering simultaneous protein quantitation (0.25–5 mg/mL and analysis of total lipid or detergent species, as well as the identification of other biomolecules present in biological samples. The method utilizes a hydrophilic PTFE membrane engineered for presentation of aqueous samples in a dried format compatible with fast infrared analysis. Unlike classical quantification techniques, the reported method is amino acid sequence independent and thus applicable to complex samples of unknown composition. By comparison to existing platforms, this MIR-based method enables direct quantification using minimal sample volume (2 µL; it is well-suited where repeat access and limited sample size are critical parameters. Further, accurate results can be derived without specialized training or knowledge of IR spectroscopy. Overall, the simplified application and analysis system provides a more cost-effective alternative to high-throughput IR systems for research laboratories with minimal throughput demands. In summary, the MIR-based system provides a viable alternative to current protein quantitation methods; it also uniquely offers simultaneous qualification of other components, notably lipids and detergents.

Comparative study of the efficiency of computed univariate and multivariate methods for the estimation of the binary mixture of clotrimazole and dexamethasone using two different spectral regions

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Fayez, Yasmin Mohammed; Tawakkol, Shereen Mostafa; Fahmy, Nesma Mahmoud; Lotfy, Hayam Mahmoud; Shehata, Mostafa Abdel-Aty

2018-04-01

Three methods of analysis are conducted that need computational procedures by the Matlab® software. The first is the univariate mean centering method which eliminates the interfering signal of the one component at a selected wave length leaving the amplitude measured to represent the component of interest only. The other two multivariate methods named PLS and PCR depend on a large number of variables that lead to extraction of the maximum amount of information required to determine the component of interest in the presence of the other. Good accurate and precise results are obtained from the three methods for determining clotrimazole in the linearity range 1-12 μg/mL and 75-550 μg/mL with dexamethasone acetate 2-20 μg/mL in synthetic mixtures and pharmaceutical formulation using two different spectral regions 205-240 nm and 233-278 nm. The results obtained are compared statistically to each other and to the official methods.

Multivariate refined composite multiscale entropy analysis

International Nuclear Information System (INIS)

Humeau-Heurtier, Anne

2016-01-01

Multiscale entropy (MSE) has become a prevailing method to quantify signals complexity. MSE relies on sample entropy. However, MSE may yield imprecise complexity estimation at large scales, because sample entropy does not give precise estimation of entropy when short signals are processed. A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. Nevertheless, RCMSE is for univariate signals only. The simultaneous analysis of multi-channel (multivariate) data often over-performs studies based on univariate signals. We therefore introduce an extension of RCMSE to multivariate data. Applications of multivariate RCMSE to simulated processes reveal its better performances over the standard multivariate MSE. - Highlights: • Multiscale entropy quantifies data complexity but may be inaccurate at large scale. • A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. • Nevertheless, RCMSE is adapted to univariate time series only. • We herein introduce an extension of RCMSE to multivariate data. • It shows better performances than the standard multivariate multiscale entropy.

Prospective multifactorial analysis of preseason risk factors for shoulder and elbow injuries in high school baseball pitchers.

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Shitara, Hitoshi; Kobayashi, Tsutomu; Yamamoto, Atsushi; Shimoyama, Daisuke; Ichinose, Tsuyoshi; Tajika, Tsuyoshi; Osawa, Toshihisa; Iizuka, Haku; Takagishi, Kenji

2017-10-01

To prospectively identify preseason physical factors for shoulder and elbow injuries during the season in high school baseball pitchers. The study included 105 high school baseball pitchers [median age 16 (15-17) years]. The range of motion of the shoulder (90° abducted external and internal rotation) and elbow (extension/flexion), shoulder muscle strength (abduction and prone internal and external rotation), shoulder and elbow laxity, horizontal flexion, and scapular dyskinesis were assessed. After the season, the participants completed questionnaires regarding shoulder and/or elbow injuries, with injury defined as an inability to play for ≥1 week due to elbow/shoulder problems. The results of two groups (injured and noninjured) were compared using t tests and Chi-square analyses. Stepwise forward logistic regression models were developed to identify risk factors. Twenty-one injuries were observed. In univariate analysis, 90° abducted internal rotation and total arc of the dominant shoulder and the ratio of prone external rotation in the dominant to nondominant sides in the injured group were significantly less than those in the noninjured group (P = 0.02, 0.04, and 0.01, respectively). In logistic regression analysis, 90° abducted internal rotation in the dominant shoulder and prone external rotation ratio were significantly associated with injuries (P = 0.02 and 0.03, respectively). A low prone external rotation ratio and decreased 90° abducted internal rotation in the dominant shoulder in the preseason were significant risk factors for shoulder and elbow injuries in high school baseball pitchers. The results may contribute to reduce the incidence of these injuries. II.

Recurrence Patterns and Survival for Patients With Intermediate- and High-Grade Myxofibrosarcoma

International Nuclear Information System (INIS)

Haglund, Karl E.; Raut, Chandrajit P.; Nascimento, Alessandra F.; Wang, Qian; George, Suzanne; Baldini, Elizabeth H.

2012-01-01

Purpose: Myxofibrosarcoma (MFS) is a rare sarcoma with a predilection for multiple local recurrences (LR), for which optimal treatment has not been defined. We reviewed our experience to determine the impact of surgery and radiation therapy (RT) on pattern of recurrence, limb salvage, and overall survival (OS). Methods and Materials: Between 1995 and 2005, 36 patients with localized intermediate- or high-grade MFS were treated at our institution. Data on clinicopathologic features, treatments, and patient outcomes were reviewed and analyzed. Results: Median age was 72.5 years (range, 42–96 years). Median tumor size was 7.5 cm, and 34 tumors (94%) were high grade. All patients underwent surgery at our institution, including re-resections in 20 patients (56%) after initial surgery elsewhere. Margins were microscopically positive in 9 patients (25%). RT was given to 28 patients (78%) pre - and/or postoperatively. After a median follow-up of 3.5 years (range, 0.4–12.4 years), 11 patients (31%) developed LR. There were no significant predictors for LR on univariate analysis, including margin status or use of RT. Limb salvage was ultimately achieved in only 5 of 11 LRs (45%) because of multiple subsequent LRs. Distant recurrence (DR) occurred in 6 patients (17%). Median and 4-year OS were 96 months and 65%, respectively. Seven patients (19%) died of tumor-related causes, 6 of whom had DRs. On univariate analysis, tumor size was associated with OS. Conclusions: Despite aggressive surgery and RT, intermediate- and high-grade MFS are associated with a high rate of LR that adversely affects limb preservation. More aggressive local treatment strategies are necessary.

Effects of univariate and multivariate regression on the accuracy of hydrogen quantification with laser-induced breakdown spectroscopy

Science.gov (United States)

Ytsma, Cai R.; Dyar, M. Darby

2018-01-01

Hydrogen (H) is a critical element to measure on the surface of Mars because its presence in mineral structures is indicative of past hydrous conditions. The Curiosity rover uses the laser-induced breakdown spectrometer (LIBS) on the ChemCam instrument to analyze rocks for their H emission signal at 656.6 nm, from which H can be quantified. Previous LIBS calibrations for H used small data sets measured on standards and/or manufactured mixtures of hydrous minerals and rocks and applied univariate regression to spectra normalized in a variety of ways. However, matrix effects common to LIBS make these calibrations of limited usefulness when applied to the broad range of compositions on the Martian surface. In this study, 198 naturally-occurring hydrous geological samples covering a broad range of bulk compositions with directly-measured H content are used to create more robust prediction models for measuring H in LIBS data acquired under Mars conditions. Both univariate and multivariate prediction models, including partial least square (PLS) and the least absolute shrinkage and selection operator (Lasso), are compared using several different methods for normalization of H peak intensities. Data from the ChemLIBS Mars-analog spectrometer at Mount Holyoke College are compared against spectra from the same samples acquired using a ChemCam-like instrument at Los Alamos National Laboratory and the ChemCam instrument on Mars. Results show that all current normalization and data preprocessing variations for quantifying H result in models with statistically indistinguishable prediction errors (accuracies) ca. ± 1.5 weight percent (wt%) H2O, limiting the applications of LIBS in these implementations for geological studies. This error is too large to allow distinctions among the most common hydrous phases (basalts, amphiboles, micas) to be made, though some clays (e.g., chlorites with ≈ 12 wt% H2O, smectites with 15-20 wt% H2O) and hydrated phases (e.g., gypsum with ≈ 20

Role of hormonal therapy in the management of intermediate- to high-risk prostate cancer treated with permanent radioactive seed implantation

International Nuclear Information System (INIS)

Lee, Lucille N.; Stock, Richard G.; Stone, Nelson N.

2002-01-01

Purpose: To study the impact of hormonal therapy (HTx) on intermediate- to high-risk prostate cancer treated with permanent radioactive seed implantation. Methods and Materials: Patients with Stage T1b-T3bN0 prostate cancer, and Gleason score ≥7 or prostate-specific antigen (PSA) level >10 ng/mL were treated with seed implantation with or without HTx. Their disease was defined as intermediate risk (PSA 10-20, Gleason score 7, or Stage T2b) or high risk (two or more intermediate criteria, or PSA >20 ng/mL, Gleason score 8-10, or Stage T2c-T3). The median follow-up for 201 eligible patients was 42 months (range 18-110). Biochemical failure was defined as a rising PSA >1.0 ng/mL. Pretreatment disease characteristics, implant dose, and HTx were evaluated using univariate and multivariate analyses. Results: HTx significantly improved 5-year actuarial freedom from biochemical failure rate, 79% vs. 54% without HTx. In addition, high-dose, PSA ≤15 ng/mL, intermediate risk, and Stage T2a or lower significantly improved outcome in the univariate analyses. HTx was the most significant predictor of 5-year actuarial freedom from biochemical failure (p <0.0001) in a multivariate analysis. The best outcome was in the intermediate-risk patients treated with a high implant dose and HTx, resulting in a 4-year actuarial freedom from biochemical failure rate of 94%. Conclusion: In this retrospective review, HTx improved outcome in intermediate- to high-risk prostate cancer patients treated with brachytherapy. HTx was the most important prognostic factor in the univariate and multivariate analyses

Meta-Analysis in Stata Using Gllamm

Science.gov (United States)

Bagos, Pantelis G.

2015-01-01

There are several user-written programs for performing meta-analysis in Stata (Stata Statistical Software: College Station, TX: Stata Corp LP). These include metan, metareg, mvmeta, and glst. However, there are several cases for which these programs do not suffice. For instance, there is no software for performing univariate meta-analysis with…

Radical prostatectomy in clinically localized high-risk prostate cancer

DEFF Research Database (Denmark)

Røder, Martin Andreas; Berg, Kasper Drimer; Christensen, Ib Jarle

2013-01-01

) is regarded as primary therapy by others. This study examined the outcome for high-risk localized PCa patients treated with RP. Material and methods. Of 1300 patients who underwent RP, 231 were identified as high-risk. Patients were followed for biochemical recurrence (BCR) (defined as prostate-specific......Abstract Objective. The optimal therapeutic strategy for high-risk localized prostate cancer (PCa) is controversial. Supported by randomized trials, the combination of external beam radiation therapy (EBRT) and endocrine therapy (ET) is advocated by many, while radical prostatectomy (RP...... antigen ≥ 0.2 ng/ml), metastatic disease and survival. Excluding node-positive patients, none of the patients received adjuvant therapy before BCR was confirmed. Univariate and multivariate analysis was performed with Kaplan-Meier and Cox proportional hazard models. Results. Median follow-up was 4.4 years...

A comparison of two follow-up analyses after multiple analysis of variance, analysis of variance, and descriptive discriminant analysis: A case study of the program effects on education-abroad programs

Science.gov (United States)

Alvin H. Yu; Garry. Chick

2010-01-01

This study compared the utility of two different post-hoc tests after detecting significant differences within factors on multiple dependent variables using multivariate analysis of variance (MANOVA). We compared the univariate F test (the Scheffé method) to descriptive discriminant analysis (DDA) using an educational-tour survey of university study-...

Comparison of spectrum normalization techniques for univariate ...

Indian Academy of Sciences (India)

2016-02-29

Feb 29, 2016 ... 1Fuel Chemistry Division, Bhabha Atomic Research Centre, Mumbai 400 085, India. 2Department of ... their three-point smoothing methods were studied using LIBS for quantification of Cr, Mn and Ni ... nique for the qualitative and quantitative analysis of the samples. .... SEP is a type of mean square error.

Need for High Radiation Dose (≥70 Gy) in Early Postoperative Irradiation After Radical Prostatectomy: A Single-Institution Analysis of 334 High-Risk, Node-Negative Patients

International Nuclear Information System (INIS)

Cozzarini, Cesare; Montorsi, Francesco; Fiorino, Claudio; Alongi, Filippo; Bolognesi, Angelo; Da Pozzo, Luigi Filippo; Guazzoni, Giorgio; Freschi, Massimo; Roscigno, Marco; Scattoni, Vincenzo; Rigatti, Patrizio; Di Muzio, Nadia

2009-01-01

Purpose: To determine the clinical benefit of high-dose early adjuvant radiotherapy (EART) in high-risk prostate cancer (hrCaP) patients submitted to radical retropubic prostatectomy plus pelvic lymphadenectomy. Patients and Methods: The clinical outcome of 334 hrCaP (pT3-4 and/or positive resection margins) node-negative patients submitted to radical retropubic prostatectomy plus pelvic lymphadenectomy before 2004 was analyzed according to the EART dose delivered to the prostatic bed, <70.2 Gy (lower dose, median 66.6 Gy, n = 153) or ≥70.2 Gy (median 70.2 Gy, n = 181). Results: The two groups were comparable except for a significant difference in terms of median follow-up (10 vs. 7 years, respectively) owing to the gradual increase of EART doses over time. Nevertheless, median time to prostate-specific antigen (PSA) failure was almost identical, 38 and 36 months, respectively. At univariate analysis, both 5-year biochemical relapse-free survival (bRFS) and disease-free survival (DFS) were significantly higher (83% vs. 71% [p = 0.001] and 94% vs. 88% [p = 0.005], respectively) in the HD group. Multivariate analysis confirmed EART dose ≥70 Gy to be independently related to both bRFS (hazard ratio 2.5, p = 0.04) and DFS (hazard ratio 3.6, p = 0.004). Similar results were obtained after the exclusion of patients receiving any androgen deprivation. After grouping the hormone-naive patients by postoperative PSA level the statistically significant impact of high-dose EART on both 5-year bRFS and DFS was maintained only for those with undetectable values, possibly owing to micrometastatic disease outside the irradiated area in case of detectable postoperative PSA values. Conclusion: This series provides strong support for the use of EART doses ≥70 Gy after radical retropubic prostatectomy in hrCaP patients with undetectable postoperative PSA levels.

Analysis of Medication Errors in Simulated Pediatric Resuscitation by Residents

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Evelyn Porter

2014-07-01

Full Text Available Introduction: The objective of our study was to estimate the incidence of prescribing medication errors specifically made by a trainee and identify factors associated with these errors during the simulated resuscitation of a critically ill child. Methods: The results of the simulated resuscitation are described. We analyzed data from the simulated resuscitation for the occurrence of a prescribing medication error. We compared univariate analysis of each variable to medication error rate and performed a separate multiple logistic regression analysis on the significant univariate variables to assess the association between the selected variables. Results: We reviewed 49 simulated resuscitations . The final medication error rate for the simulation was 26.5% (95% CI 13.7% - 39.3%. On univariate analysis, statistically significant findings for decreased prescribing medication error rates included senior residents in charge, presence of a pharmacist, sleeping greater than 8 hours prior to the simulation, and a visual analog scale score showing more confidence in caring for critically ill children. Multiple logistic regression analysis using the above significant variables showed only the presence of a pharmacist to remain significantly associated with decreased medication error, odds ratio of 0.09 (95% CI 0.01 - 0.64. Conclusion: Our results indicate that the presence of a clinical pharmacist during the resuscitation of a critically ill child reduces the medication errors made by resident physician trainees.

High bone sialoprotein (BSP expression correlates with increased tumor grade and predicts a poorer prognosis of high-grade glioma patients.

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Tao Xu

Full Text Available OBJECTIVES: To investigate the expression and prognostic value of bone sialoprotein (BSP in glioma patients. METHODS: We determined the expression of BSP using real-time RT-PCR and immunohistochemistry in tissue microarrays containing 15 normal brain and 270 glioma samples. Cumulative survival was calculated by the Kaplan-Meier method and analyzed by the log-rank test. Univariate and multivariate analyses were performed by the stepwise forward Cox regression model. RESULTS: Both BSP mRNA and protein levels were significantly elevated in high-grade glioma tissues compared with those of normal brain and low-grade glioma tissues, and BSP expression positively correlated with tumor grade (P<0.001. Univariate and multivariate analysis showed high BSP expression was an independent prognostic factor for a shorter progression-free survival (PFS and overall survival (OS in both grade III and grade IV glioma patients [hazard ratio (HR = 2.549 and 3.154 for grade III glioma, and HR = 1.637 and 1.574 for grade IV glioma, respectively]. Patients with low BSP expression had a significantly longer median OS and PFS than those with high BSP expression. Small extent of resection and lineage of astrocyte served as independent risk factors of both shorter PFS and OS in grade III glioma patients; GBM patients without O(6-methylguanine (O(6-meG DNA methyltransferase (MGMT methylation and Karnofsky performance score (KPS less than 70 points were related to poor prognosis. Lack of radiotherapy related to shorter OS but not affect PFS in both grade III and grade IV glioma patients. CONCLUSION: High BSP expression occurs in a significant subset of high-grade glioma patients and predicts a poorer outcome. The study identifies a potentially useful molecular marker for the categorization and targeted therapy of gliomas.

Ischemic risk stratification by means of multivariate analysis of the heart rate variability

International Nuclear Information System (INIS)

Valencia, José F; Vallverdú, Montserrat; Caminal, Pere; Porta, Alberto; Voss, Andreas; Schroeder, Rico; Vázquez, Rafael; Bayés de Luna, Antonio

2013-01-01

In this work, a univariate and multivariate statistical analysis of indexes derived from heart rate variability (HRV) was conducted to stratify patients with ischemic dilated cardiomyopathy (IDC) in cardiac risk groups. Indexes conditional entropy, refined multiscale entropy (RMSE), detrended fluctuation analysis, time and frequency analysis, were applied to the RR interval series (beat-to-beat series), for single and multiscale complexity analysis of the HRV in IDC patients. Also, clinical parameters were considered. Two different end-points after a follow-up of three years were considered: (i) analysis A, with 151 survivor patients as a low risk group and 13 patients that suffered sudden cardiac death as a high risk group; (ii) analysis B, with 192 survivor patients as a low risk group and 30 patients that suffered cardiac mortality as a high risk group. A univariate and multivariate linear discriminant analysis was used as a statistical technique for classifying patients in risk groups. Sensitivity (Sen) and specificity (Spe) were calculated as diagnostic criteria in order to evaluate the performance of the indexes and their linear combinations. Sen and Spe values of 80.0% and 72.9%, respectively, were obtained during daytime by combining one clinical parameter and one index from RMSE, and during nighttime Sen = 80% and Spe = 73.4% were attained by combining one clinical factor and two indexes from RMSE. In particular, relatively long time scales were more relevant for classifying patients into risk groups during nighttime, while during daytime shorter scales performed better. The results suggest that the left atrial size, indexed to body surface and RMSE indexes are those that allow enhanced classification of ischemic patients in their respective risk groups, confirming that a single measurement is not enough to fully characterize ischemic risk patients and the clinical relevance of HRV complexity measures. (paper)

Prognostic value of preoperative dynamic contrast-enhanced MRI perfusion parameters for high-grade glioma patients

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Ulyte, Agne [Vilnius University, Faculty of Medicine, Vilnius (Lithuania); Katsaros, Vasileios K. [General Anticancer and Oncological Hospital ' ' St. Savvas' ' , Department of Advanced Imaging Modalities - CT and MRI, Athens (Greece); University of Athens, Department of Neurosurgery, Evangelismos Hospital, Athens (Greece); Liouta, Evangelia; Stranjalis, Georgios [University of Athens, Department of Neurosurgery, Evangelismos Hospital, Athens (Greece); Boskos, Christos [University of Athens, Department of Neurosurgery, Evangelismos Hospital, Athens (Greece); General Anticancer and Oncological Hospital ' ' St. Savvas' ' , Department of Radiation Oncology, Athens (Greece); Papanikolaou, Nickolas [Champalimaud Foundation, Department of Radiology, Centre for the Unknown, Lisbon (Portugal); Usinskiene, Jurgita [National Cancer Institute, Vilnius (Lithuania); Affidea Lietuva, Vilnius (Lithuania); Bisdas, Sotirios [University College London Hospitals, Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, London (United Kingdom)

2016-12-15

The prognostic value of the dynamic contrast-enhanced (DCE) MRI perfusion and its histogram analysis-derived metrics is not well established for high-grade glioma (HGG) patients. The aim of this prospective study was to investigate DCE perfusion transfer coefficient (K{sup trans}), vascular plasma volume fraction (v{sub p}), extracellular volume fraction (v{sub e}), reverse transfer constant (k{sub ep}), and initial area under gadolinium concentration time curve (IAUGC) as predictors of progression-free (PFS) and overall survival (OS) in HGG patients. Sixty-nine patients with suspected anaplastic astrocytoma or glioblastoma underwent preoperative DCE-MRI scans. DCE perfusion whole tumor region histogram parameters, clinical details, and PFS and OS data were obtained. Univariate, multivariate, and Kaplan-Meier survival analyses were conducted. Receiver operating characteristic (ROC) curve analysis was employed to identify perfusion parameters with the best differentiation performance. On univariate analysis, v{sub e} and skewness of v{sub p} had significant negative impacts, while k{sub ep} had significant positive impact on OS (P < 0.05). v{sub e} was also a negative predictor of PFS (P < 0.05). Patients with lower v{sub e} and IAUGC had longer median PFS and OS on Kaplan-Meier analysis (P < 0.05). K{sup trans} and v{sub e} could also differentiate grade III from IV gliomas (area under the curve 0.819 and 0.791, respectively). High v{sub e} is a consistent predictor of worse PFS and OS in HGG glioma patients. v{sub p} skewness and k{sub ep} are also predictive for OS. K{sup trans} and v{sub e} demonstrated the best diagnostic performance for differentiating grade III from IV gliomas. (orig.)

The influence of different classification standards of age groups on prognosis in high-grade hemispheric glioma patients.

Science.gov (United States)

Chen, Jian-Wu; Zhou, Chang-Fu; Lin, Zhi-Xiong

2015-09-15

Although age is thought to correlate with the prognosis of glioma patients, the most appropriate age-group classification standard to evaluate prognosis had not been fully studied. This study aimed to investigate the influence of age-group classification standards on the prognosis of patients with high-grade hemispheric glioma (HGG). This retrospective study of 125 HGG patients used three different classification standards of age-groups (≤ 50 and >50 years old, ≤ 60 and >60 years old, ≤ 45 and 45-65 and ≥ 65 years old) to evaluate the impact of age on prognosis. The primary end-point was overall survival (OS). The Kaplan-Meier method was applied for univariate analysis and Cox proportional hazards model for multivariate analysis. Univariate analysis showed a significant correlation between OS and all three classification standards of age-groups as well as between OS and pathological grade, gender, location of glioma, and regular chemotherapy and radiotherapy treatment. Multivariate analysis showed that the only independent predictors of OS were classification standard of age-groups ≤ 50 and > 50 years old, pathological grade and regular chemotherapy. In summary, the most appropriate classification standard of age-groups as an independent prognostic factor was ≤ 50 and > 50 years old. Pathological grade and chemotherapy were also independent predictors of OS in post-operative HGG patients. Copyright © 2015. Published by Elsevier B.V.

Multivariate two-part statistics for analysis of correlated mass spectrometry data from multiple biological specimens.

Science.gov (United States)

Taylor, Sandra L; Ruhaak, L Renee; Weiss, Robert H; Kelly, Karen; Kim, Kyoungmi

2017-01-01

High through-put mass spectrometry (MS) is now being used to profile small molecular compounds across multiple biological sample types from the same subjects with the goal of leveraging information across biospecimens. Multivariate statistical methods that combine information from all biospecimens could be more powerful than the usual univariate analyses. However, missing values are common in MS data and imputation can impact between-biospecimen correlation and multivariate analysis results. We propose two multivariate two-part statistics that accommodate missing values and combine data from all biospecimens to identify differentially regulated compounds. Statistical significance is determined using a multivariate permutation null distribution. Relative to univariate tests, the multivariate procedures detected more significant compounds in three biological datasets. In a simulation study, we showed that multi-biospecimen testing procedures were more powerful than single-biospecimen methods when compounds are differentially regulated in multiple biospecimens but univariate methods can be more powerful if compounds are differentially regulated in only one biospecimen. We provide R functions to implement and illustrate our method as supplementary information CONTACT: sltaylor@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

Science.gov (United States)

Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability.

Acute exacerbation of idiopathic pulmonary fibrosis: high-resolution CT scores predict mortality

International Nuclear Information System (INIS)

Fujimoto, Kiminori; Taniguchi, Hiroyuki; Kondoh, Yasuhiro; Kataoka, Kensuke; Johkoh, Takeshi; Ichikado, Kazuya; Sumikawa, Hiromitsu; Ogura, Takashi; Endo, Takahiro; Kawaguchi, Atsushi; Mueller, Nestor L.

2012-01-01

To determine high-resolution computed tomography (HRCT) findings helpful in predicting mortality in patients with acute exacerbation of idiopathic pulmonary fibrosis (AEx-IPF). Sixty patients with diagnosis of AEx-IPF were reviewed retrospectively. Two groups (two observers each) independently evaluated pattern, distribution, and extent of HRCT findings at presentation and calculated an HRCT score at AEx based on normal attenuation areas and extent of abnormalities, such as areas of ground-glass attenuation and/or consolidation with or without traction bronchiectasis or bronchiolectasis and areas of honeycombing. The correlation between the clinical data including the HRCT score and mortality (cause-specific survival) was evaluated using the univariate and multivariate Cox-regression analyses. Serum KL-6 level, PaCO 2 , and the HRCT score were statistically significant predictors on univariate analysis. Multivariate analysis revealed that the HRCT score was an independently significant predictor of outcome (hazard ratio, 1.13; 95% confidence interval, 1.06-1.19, P = 0.0002). The area under receiver operating characteristics curve for the HRCT score was statistically significant in the classification of survivors or nonsurvivors (0.944; P < 0.0001). Survival in patients with HRCT score ≥245 was worse than those with lower score (log-rank test, P < 0.0001). The HRCT score at AEx is independently related to prognosis in patients with AEx-IPF. (orig.)

Acute exacerbation of idiopathic pulmonary fibrosis: high-resolution CT scores predict mortality

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Fujimoto, Kiminori [Kurume University School of Medicine, and Center for Diagnostic Imaging, Kurume University Hospital, Department of Radiology, Kurume, Fukuoka (Japan); Taniguchi, Hiroyuki; Kondoh, Yasuhiro; Kataoka, Kensuke [Tosei General Hospital, Department of Respiratory Medicine and Allergy, Seto, Aichi (Japan); Johkoh, Takeshi [Kinki Central Hospital of Mutual Aid Association of Public School Teachers, Department of Radiology, Itami (Japan); Ichikado, Kazuya [Saiseikai Kumamoto Hospital, Division of Respiratory Medicine, Kumamoto (Japan); Sumikawa, Hiromitsu [Osaka University Graduate School of Medicine, Department of Radiology, Suita, Osaka (Japan); Ogura, Takashi; Endo, Takahiro [Kanagawa Cardiovascular and Respiratory Center, Department of Respiratory Medicine, Yokohama, Kanagawa (Japan); Kawaguchi, Atsushi [Kurume University School of Medicine, Biostatistics Center, Kurume (Japan); Mueller, Nestor L. [University of British Columbia and Vancouver General Hospital, Department of Radiology, Vancouver, B.C. (Canada)

2012-01-15

To determine high-resolution computed tomography (HRCT) findings helpful in predicting mortality in patients with acute exacerbation of idiopathic pulmonary fibrosis (AEx-IPF). Sixty patients with diagnosis of AEx-IPF were reviewed retrospectively. Two groups (two observers each) independently evaluated pattern, distribution, and extent of HRCT findings at presentation and calculated an HRCT score at AEx based on normal attenuation areas and extent of abnormalities, such as areas of ground-glass attenuation and/or consolidation with or without traction bronchiectasis or bronchiolectasis and areas of honeycombing. The correlation between the clinical data including the HRCT score and mortality (cause-specific survival) was evaluated using the univariate and multivariate Cox-regression analyses. Serum KL-6 level, PaCO{sub 2}, and the HRCT score were statistically significant predictors on univariate analysis. Multivariate analysis revealed that the HRCT score was an independently significant predictor of outcome (hazard ratio, 1.13; 95% confidence interval, 1.06-1.19, P = 0.0002). The area under receiver operating characteristics curve for the HRCT score was statistically significant in the classification of survivors or nonsurvivors (0.944; P < 0.0001). Survival in patients with HRCT score {>=}245 was worse than those with lower score (log-rank test, P < 0.0001). The HRCT score at AEx is independently related to prognosis in patients with AEx-IPF. (orig.)

Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis

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Jacques Duchêne

2008-05-01

Full Text Available The aim of this paper was to compare empirical mode decomposition (EMD and two new extended methods of  EMD named complex empirical mode decomposition (complex-EMD and bivariate empirical mode decomposition (bivariate-EMD. All methods were used to analyze stabilogram center of pressure (COP time series. The two new methods are suitable to be applied to complex time series to extract complex intrinsic mode functions (IMFs before the Hilbert transform is subsequently applied on the IMFs. The trace of the analytic IMF in the complex plane has a circular form, with each IMF having its own rotation frequency. The area of the circle and the average rotation frequency of IMFs represent efficient indicators of the postural stability status of subjects. Experimental results show the effectiveness of these indicators to identify differences in standing posture between groups.

Adaptive Analysis of Functional MRI Data

International Nuclear Information System (INIS)

Friman, Ola

2003-01-01

Functional Magnetic Resonance Imaging (fMRI) is a recently developed neuro-imaging technique with capacity to map neural activity with high spatial precision. To locate active brain areas, the method utilizes local blood oxygenation changes which are reflected as small intensity changes in a special type of MR images. The ability to non-invasively map brain functions provides new opportunities to unravel the mysteries and advance the understanding of the human brain, as well as to perform pre-surgical examinations in order to optimize surgical interventions. This dissertation introduces new approaches for the analysis of fMRI data. The detection of active brain areas is a challenging problem due to high noise levels and artifacts present in the data. A fundamental tool in the developed methods is Canonical Correlation Analysis (CCA). CCA is used in two novel ways. First as a method with the ability to fully exploit the spatio-temporal nature of fMRI data for detecting active brain areas. Established analysis approaches mainly focus on the temporal dimension of the data and they are for this reason commonly referred to as being mass-univariate. The new CCA detection method encompasses and generalizes the traditional mass-univariate methods and can in this terminology be viewed as a mass-multivariate approach. The concept of spatial basis functions is introduced as a spatial counterpart of the temporal basis functions already in use in fMRI analysis. The spatial basis functions implicitly perform an adaptive spatial filtering of the fMRI images, which significantly improves detection performance. It is also shown how prior information can be incorporated into the analysis by imposing constraints on the temporal and spatial models and a constrained version of CCA is devised to this end. A general Principal Component Analysis technique for generating and constraining temporal and spatial subspace models is proposed to be used in combination with the constrained CCA

High peritoneal transport status is not an independent risk factor for high mortality in patients treated with automated peritoneal dialysis.

Science.gov (United States)

Chang, Tae Ik; Park, Jung Tak; Lee, Dong Hyung; Lee, Ju Hyun; Yoo, Tae Hyun; Kim, Beom Seok; Kang, Shin-Wook; Lee, Ho Yung; Choi, Kyu Hun

2010-09-01

We undertook this study to elucidate whether baseline peritoneal membrane transport characteristics are associated with high mortality in incident automated peritoneal dialysis (APD) patients. This retrospective study includes 117 patients who started APD at Yonsei University Health System from 1996 to 2008 and had a PET within 3 months of APD initiation. High transporters were significantly older and had a higher incidence of cardiovascular disease. Patient survival for years 1, 3, and 5 were 85%, 64%, and 35% for high transporter and 94%, 81%, and 68% for non-high transporter group (Ptransport status was not a significant predictor for mortality in this population when the other covariates were included. Even though high transport was significantly associated with mortality in the univariate analysis, its role seemed to be influenced by other comorbid conditions. These findings suggest that the proper management of these comorbid conditions, as well as appropriate ultrafiltration by use of APD and/or icodextrin, must be considered as protective strategies to improve survival in peritoneal dialysis patients with high transport.

Analysis of Biochemical Control and Prognostic Factors in Patients Treated With Either Low-Dose Three-Dimensional Conformal Radiation Therapy or High-Dose Intensity-Modulated Radiotherapy for Localized Prostate Cancer

International Nuclear Information System (INIS)

Vora, Sujay A.; Wong, William W.; Schild, Steven E.; Ezzell, Gary A.; Halyard, Michele Y.

2007-01-01

Purpose: To identify prognostic factors and evaluate biochemical control rates for patients with localized prostate cancer treated with either high-dose intensity-modulated radiotherapy (IMRT) or conventional-dose three-dimensional conformal radiotherapy 3D-CRT. Methods: Four hundred sixteen patients with a minimum follow-up of 3 years (median, 5 years) were included. Two hundred seventy-one patients received 3D-CRT with a median dose of 68.4 Gy (range, 66-71 Gy). The next 145 patients received IMRT with a median dose of 75.6 Gy (range, 70.2-77.4 Gy). Biochemical control rates were calculated according to both American Society for Therapeutic Radiology and Oncology (ASTRO) consensus definitions. Prognostic factors were identified using both univariate and multivariate analyses. Results: The 5-year biochemical control rate was 60.4% for 3D-CRT and 74.1% for IMRT (p < 0.0001, first ASTRO Consensus definition). Using the ASTRO Phoenix definition, the 5-year biochemical control rate was 74.4% and 84.6% with 3D-RT and IMRT, respectively (p = 0.0326). Univariate analyses determined that PSA level, T stage, Gleason score, perineural invasion, and radiation dose were predictive of biochemical control. On multivariate analysis, dose, Gleason score, and perineural invasion remained significant. Conclusion: On the basis of both ASTRO definitions, dose, Gleason score, and perineural invasion were predictive of biochemical control. Intensity-modulated radiotherapy allowed delivery of higher doses of radiation with very low toxicity, resulting in improved biochemical control

High risk factors for severe hand, foot and mouth disease: A multicenter retrospective survey in Anhui Province China, 2008-2009

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Jiahua Pan

2012-01-01

Full Text Available Objectives: This study sought to determine the high risk factors for severe hand, foot, and mouth disease (HFMD. Materials and Methods: Retrospective 229 severe HFMD cases from four hospitals in FuYang, HeFei, and BoZhou (Anhui Provincial Hospital, Fuyang City People′s Hospital, No. 2 People′s Hospital of Fuyang and Bozhou city People′s Hospital in 2008-2009 were studied, with 140 mild HFMD cases in the same area. Using univariate and multivariate logistic regression analyses, the high risk factors of HFMD were identified by comparing clinical and laboratory findings between severe cases and mild cases. Results: There was a significant difference in age, total duration of fever, rate of respiratory and heart, shake of limbs, white blood cell count, blood sugar, and CK-MB between the two groups. Univariate logistic regression analysis showed that severe cases were associated with age (<3 years, withdrawnness and lethargy, shake of limbs, tachycardia, total leukocyte count (≥17×10 9 /l, blood sugar (≥7 mmol/l, and CK-MB (≥16 mmol/l. Furthermore, age (<3 years, withdrawnness, and lethargy, shake of limbs, WBC (≥17×10 9 /l, and CK-MB (≥16 mmol/l were found to be high risk factors for severe cases after multivariate logistic regression analysis. Conclusions: Clinicians should give importance to these risk factors. Early recognition of children at risk and timely intervention is the key to reduce acute mortality and morbidity.

To what extent have high schools in California been able to implement state-mandated nutrition standards?

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Samuels, Sarah E; Bullock, Sally Lawrence; Woodward-Lopez, Gail; Clark, Sarah E; Kao, Janice; Craypo, Lisa; Barry, Jay; Crawford, Patricia B

2009-09-01

To determine extent and factors associated with implementation of California's school nutrition standards 1 year after standards became active. Information on competitive foods and beverages available in schools was collected from a representative sample of 56 public high schools in California. Adherence to nutrition standards was calculated for each item and summarized for each school by venue. The association between schools' sociodemographic characteristics and adherence to standards was determined by multivariate analysis. The majority of schools were adhering to the required beverage standards. None of the schools selling competitive foods were 100% adherent to the food standards. Adherence to both standards tended to be highest in food service venues. In univariate analyses, percent nonwhite enrollment, population density, percent free/reduced-price (FRP) meal eligibility, and school size were significantly correlated with the beverage adherence rate. Percent nonwhite enrollment and population density remained significant in the multivariate regression model. Percent nonwhite enrollment and percent FRP meal eligibility were significantly correlated with the food adherence rate in univariate analysis, but neither remained significant in the multiple regression model. California high schools are making progress toward implementation of the state nutrition standards. Beverage standards appear easier to achieve than nutrient-based food standards. Additional support is needed to provide schools with resources to implement and monitor these policies. Simpler standards and/or a reduction in the foods and beverages sold could better enable schools to achieve and monitor adherence.

The use of principal components and univariate charts to control multivariate processes

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Marcela A. G. Machado

2008-04-01

Full Text Available In this article, we evaluate the performance of the T² chart based on the principal components (PC X chart and the simultaneous univariate control charts based on the original variables (SU charts or based on the principal components (SUPC charts. The main reason to consider the PC chart lies on the dimensionality reduction. However, depending on the disturbance and on the way the original variables are related, the chart is very slow in signaling, except when all variables are negatively correlated and the principal component is wisely selected. Comparing the SU , the SUPC and the T² charts we conclude that the SU X charts (SUPC charts have a better overall performance when the variables are positively (negatively correlated. We also develop the expression to obtain the power of two S² charts designed for monitoring the covariance matrix. These joint S² charts are, in the majority of the cases, more efficient than the generalized variance chart.Neste artigo, avaliamos o desempenho do gráfico de T² baseado em componentes principais (gráfico PC e dos gráficos de controle simultâneos univariados baseados nas variáveis originais (gráfico SU X ou baseados em componentes principais (gráfico SUPC. A principal razão para o uso do gráfico PC é a redução de dimensionalidade. Entretanto, dependendo da perturbação e da correlação entre as variáveis originais, o gráfico é lento em sinalizar, exceto quando todas as variáveis são negativamente correlacionadas e a componente principal é adequadamente escolhida. Comparando os gráficos SU X, SUPC e T² concluímos que o gráfico SU X (gráfico SUPC tem um melhor desempenho global quando as variáveis são positivamente (negativamente correlacionadas. Desenvolvemos também uma expressão para obter o poder de detecção de dois gráficos de S² projetados para controlar a matriz de covariâncias. Os gráficos conjuntos de S² são, na maioria dos casos, mais eficientes que o gr

Panel data analysis using EViews

CERN Document Server

Agung, I Gusti Ngurah

2013-01-01

A comprehensive and accessible guide to panel data analysis using EViews software This book explores the use of EViews software in creating panel data analysis using appropriate empirical models and real datasets. Guidance is given on developing alternative descriptive statistical summaries for evaluation and providing policy analysis based on pool panel data. Various alternative models based on panel data are explored, including univariate general linear models, fixed effect models and causal models, and guidance on the advantages and disadvantages of each one is given. Panel Data Analysis

Will initiatives to promote hydroelectricity consumption be effective? Evidence from univariate and panel LM unit root tests with structural breaks

International Nuclear Information System (INIS)

Lean, Hooi Hooi; Smyth, Russell

2014-01-01

This paper examines whether initiatives to promote hydroelectricity consumption are likely to be effective by applying univariate and panel Lagrange Multiplier (LM) unit root tests to hydroelectricity consumption in 55 countries over the period 1965–2011. We find that for the panel, as well as about four-fifths of individual countries, that hydroelectricity consumption is stationary. This result implies that shocks to hydroelectricity consumption in most countries will only result in temporary deviations from the long-run growth path. An important consequence of this finding is that initiatives designed to have permanent positive effects on hydroelectricity consumption, such as large-scale dam construction, are unlikely to be effective in increasing the share of hydroelectricity, relative to consumption of fossil fuels. - Highlights: • Applies unit root tests to hydroelectricity consumption. • Hydroelectricity consumption is stationary. • Shocks to hydroelectricity consumption result in temporary deviations from the long-run growth path

Evaluation of genetic diversity among soybean (Glycine max) genotypes using univariate and multivariate analysis.

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Oliveira, M M; Sousa, L B; Reis, M C; Silva Junior, E G; Cardoso, D B O; Hamawaki, O T; Nogueira, A P O

2017-05-31

The genetic diversity study has paramount importance in breeding programs; hence, it allows selection and choice of the parental genetic divergence, which have the agronomic traits desired by the breeder. This study aimed to characterize the genetic divergence between 24 soybean genotypes through their agronomic traits, using multivariate clustering methods to select the potential genitors for the promising hybrid combinations. Six agronomic traits evaluated were number of days to flowering and maturity, plant height at flowering and maturity, insertion height of the first pod, and yield. The genetic divergence evaluated by multivariate analysis that esteemed first the Mahalanobis' generalized distance (D 2 ), then the clustering using Tocher's optimization methods, and then the unweighted pair group method with arithmetic average (UPGMA). Tocher's optimization method and the UPGMA agreed with the groups' constitution between each other, the formation of eight distinct groups according Tocher's method and seven distinct groups using UPGMA. The trait number of days for flowering (45.66%) was the most efficient to explain dissimilarity between genotypes, and must be one of the main traits considered by the breeder in the moment of genitors choice in soybean-breeding programs. The genetic variability allowed the identification of dissimilar genotypes and with superior performances. The hybridizations UFU 18 x UFUS CARAJÁS, UFU 15 x UFU 13, and UFU 13 x UFUS CARAJÁS are promising to obtain superior segregating populations, which enable the development of more productive genotypes.

A high plasma: red blood cell transfusion ratio during liver transplantation is associated with decreased blood utilization.

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Pagano, M B; Metcalf, R A; Hess, J R; Reyes, J; Perkins, J D; Montenovo, M I

2018-04-01

During massive transfusion, the volume ratio of administered plasma (PL Vol) to red blood cell (RBC Vol) appears to be associated with reduced blood utilization and improved survival. The aim of this study was to evaluate the optimal component ratio in the setting of liver transplantation. This is a retrospective chart review of patients who underwent liver transplantation and received at least 500 ml of red blood cells from January 2013 through December 2015. Kernel smoothing analysis determined the proper component ratios to evaluate were a ≥0·85:1 ratio (high) to a ≤0·85:1 ratio (low). Two groups, plasma volume to RBC volume (PL Vol/RBC Vol) and plasma contained in the platelet units added to the plasma calculation [PL + PLT (platelet)] Vol/RBC Vol, were used to evaluate the component ratios. A total of 188 patients were included in the analysis. In the PL Vol/RBC Vol evaluation, a low ratio revealed that 1238 ml (977-1653 ml) (P ratio, in the univariable and multivariable analysis, respectively. In the PL +PLT Vol/RBC Vol evaluation, a low ratio used 734 ml (193-1275) (P = 0·008) and 886 ml (431-1340) (P ratio in the univariable and multivariable analysis, respectively. In patients undergoing liver transplantation, the transfusion of plasma to RBC ratio ≥0·85 was associated with decreased need of RBC transfusions. © 2018 International Society of Blood Transfusion.

Multivariate Meta-Analysis Using Individual Participant Data

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Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2015-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is…

The study of gastronomic tourism in Cordoba and the association of the cuisine. An econometric analysis

OpenAIRE

Millán Vázquez de la Torre, Genoveva; Hernández Rojas, Ricardo; Navajas Romero, Virginia

2016-01-01

Purpose – As the city aspires to declare itself as a quality dinning destination, this paper aims to provide some guidelines to achieve that goal. Design – The paper aims to appraise as to what extent the gastronomic product supply of Córdoba can be considered a high quality and differentiated one, which may serve as a basis for tourism product development. Methodology – we use a univariate and bivariate analysis in order to describe the socioeconomic variables to explain the variety of...

Analysis of association of clinical aspects and IL1B tagSNPs with severe preeclampsia.

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Leme Galvão, Larissa Paes; Menezes, Filipe Emanuel; Mendonca, Caio; Barreto, Ikaro; Alvim-Pereira, Claudia; Alvim-Pereira, Fabiano; Gurgel, Ricardo

2016-01-01

This study investigates the association between IL1B genotypes using a tag SNP (single polymorphism) approach, maternal and environmental factors in Brazilian women with severe preeclampsia. A case-control study with a total of 456 patients (169 preeclamptic women and 287 controls) was conducted in the two reference maternity hospitals of Sergipe state, Northeast Brazil. A questionnaire was administered and DNA was extracted to genotype the population for four tag SNPs of the IL1Beta: rs 1143643, rs 1143633, rs 1143634 and rs 1143630. Haplotype association analysis and p-values were calculated using the THESIAS test. Odds ratio (OR) estimation, confidence interval (CI) and multivariate logistic regression were performed. High pregestational body mass index (pre-BMI), first gestation, cesarean section, more than six medical visits, low level of consciousness on admission and TC and TT genotype in rs1143630 of IL1Beta showed association with the preeclamptic group in univariate analysis. After multivariate logistic regression pre-BMI, first gestation and low level of consciousness on admission remained associated. We identified an association between clinical variables and preeclampsia. Univariate analysis suggested that inflammatory process-related genes, such as IL1B, may be involved and should be targeted in further studies. The identification of the genetic background involved in preeclampsia host response modulation is mandatory in order to understand the preeclampsia process.

Is there light at the end of the tunnel; symptoms and chest x-ray help identify patients at high risk of lung cancer

International Nuclear Information System (INIS)

Toori, K.U.; Nomani, A.Z.; Winson, M.; Rehman, M.U.

2015-01-01

Objectives: Late recognition of lung cancer is the major factor contributing towards its unsuccessful treatment. We conducted a prospective study to define any significant relationship of presenting symptoms with the diagnosis of lung cancer with a view to develop a model to identify those at high risk. Methods: A consecutive series of 587 patients referred to our rapid access chest clinic with the suspicion of lung cancer were included. The presenting symptoms, chest x-ray findings and final diagnosis of all the patients were recorded. Chi-square and t-test were used for univariate analysis. A model was generated from logistic regression analysis and the discriminatory power of the model was assessed using area under receiver operator characteristic curve. Results: Univariate analysis demonstrated that smoking, anorexia, weight loss and voice change were significantly more common in patients with lung cancer (p<0.05). Cough, expectoration and hemoptysis were significantly less common (p<0.05). Regression analysis qualified age, weight loss and smoking as significant predictors of lung cancer. Conclusion: Only few of the historically accepted symptoms demonstrated a strong association with lung cancer and the model developed on these can form basis for a scoring tool that can perhaps help identify those at higher risk of cancer. Further refinement of the tool is required to accommodate cases presenting at primary care level. (author)

Risk factors associated with high linezolid trough plasma concentrations.

Science.gov (United States)

Morata, L; De la Calle, C; Gómez-Cerquera, J M; Manzanedo, L; Casals, G; Brunet, M; Cobos-Trigueros, N; Martínez, J A; Mensa, J; Soriano, A

2016-06-01

The major concern of linezolid is the adverse events. High linezolid trough serum concentration (Cmin) has been associated with toxicity. The aim of this study was to analyze factors associated with high Cmin. Main clinical characteristics of 104 patients treated with 600 mg/12 hours of linezolid were retrospectively reviewed. Samples were obtained just before the next dose after at least three doses and within the first 8 days of treatment. High Cmin was considered when it was >8 mg/L. Univariate and multivariate analysis were performed. 34.6% patients had a Cmin >8 mg/L, and they were older and had more frequently an estimated glomerular filtration by MDRD 8 was the renal function. Patients with an eGF 80 mL/min (OR: 4.273) and there was a trend towards a high Cmin in patients with eGF between 40-80 mL/min (OR: 2.109). High Cmin were frequent, especially in patients with MDRD <40 mL/min. Therapeutic drug monitoring could be useful to avoid toxicity in patients with renal dysfunction.

High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies.

Science.gov (United States)

Goudey, Benjamin; Abedini, Mani; Hopper, John L; Inouye, Michael; Makalic, Enes; Schmidt, Daniel F; Wagner, John; Zhou, Zeyu; Zobel, Justin; Reumann, Matthias

2015-01-01

Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucleotide polymorphisms (SNPs) which are associated with a given disease. Univariate analysis approaches commonly employed may miss important SNP associations that only appear through multivariate analysis in complex diseases. However, multivariate SNP analysis is currently limited by its inherent computational complexity. In this work, we present a computational framework that harnesses supercomputers. Based on our results, we estimate a three-way interaction analysis on 1.1 million SNP GWAS data requiring over 5.8 years on the full "Avoca" IBM Blue Gene/Q installation at the Victorian Life Sciences Computation Initiative. This is hundreds of times faster than estimates for other CPU based methods and four times faster than runtimes estimated for GPU methods, indicating how the improvement in the level of hardware applied to interaction analysis may alter the types of analysis that can be performed. Furthermore, the same analysis would take under 3 months on the currently largest IBM Blue Gene/Q supercomputer "Sequoia" at the Lawrence Livermore National Laboratory assuming linear scaling is maintained as our results suggest. Given that the implementation used in this study can be further optimised, this runtime means it is becoming feasible to carry out exhaustive analysis of higher order interaction studies on large modern GWAS.

Prospective Analysis of Surgical Bone Margins After Partial Foot Amputation in Diabetic Patients Admitted With Moderate to Severe Foot Infections.

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Schmidt, Brian M; McHugh, Jonathan B; Patel, Rajiv M; Wrobel, James S

2018-04-01

Osteomyelitis is common in diabetic foot infections and medical management can lead to poor outcomes. Surgical management involves sending histopathologic and microbiologic specimens which guides future intervention. We examined the effect of obtainment of surgical margins in patients undergoing forefoot amputations to identify patient characteristics associated with outcomes. Secondary aims included evaluating interobserver reliability of histopathologic data at both the distal-to and proximal-to surgical bone margin. Data were prospectively collected on 72 individuals and was pooled for analysis. Standardized method to retrieve intraoperative bone margins was established. A univariate analysis was performed. Negative outcomes, including major lower extremity amputation, wound dehiscence, reulceration, reamputation, or death were recorded. Viable proximal margins were obtained in 63 out of 72 cases (87.5%). Strong interobserver reliability of histopathology was recorded. Univariate analysis demonstrated preoperative platelets, albumin, probe-to-bone testing, absolute toe pressures, smaller wound surface area were associated with obtaining viable margins. Residual osteomyelitis resulted in readmission 2.6 times more often and more postoperative complications. Certain patients were significantly different in the viable margin group versus dirty margin group. High interobserver reliability was demonstrated. Obtainment of viable margins resulted in reduced rates of readmission and negative outcomes. Prognostic, Level I: Prospective.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

Science.gov (United States)

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-04

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Time of flight secondary ion mass spectrometry: A powerful high throughput screening tool

International Nuclear Information System (INIS)

Smentkowski, Vincent S.; Ostrowski, Sara G.

2007-01-01

Combinatorial materials libraries are becoming more complicated; successful screening of these libraries requires the development of new high throughput screening methodologies. Time of flight secondary ion mass spectrometry (ToF-SIMS) is a surface analytical technique that is able to detect and image all elements (including hydrogen which is problematic for many other analysis instruments) and molecular fragments, with high mass resolution, during a single measurement. Commercial ToF-SIMS instruments can image 500 μm areas by rastering the primary ion beam over the region of interest. In this work, we will show that large area analysis can be performed, in one single measurement, by rastering the sample under the ion beam. We show that an entire 70 mm diameter wafer can be imaged in less than 90 min using ToF-SIMS stage (macro)rastering techniques. ToF-SIMS data sets contain a wealth of information since an entire high mass resolution mass spectrum is saved at each pixel in an ion image. Multivariate statistical analysis (MVSA) tools are being used in the ToF-SIMS community to assist with data interpretation; we will demonstrate that MVSA tools provide details that were not obtained using manual (univariate) analysis

Handbook of univariate and multivariate data analysis and interpretation with SPSS

CERN Document Server

Ho, Robert

2006-01-01

Many statistics texts tend to focus more on the theory and mathematics underlying statistical tests than on their applications and interpretation. This can leave readers with little understanding of how to apply statistical tests or how to interpret their findings. While the SPSS statistical software has done much to alleviate the frustrations of social science professionals and students who must analyze data, they still face daunting challenges in selecting the proper tests, executing the tests, and interpreting the test results.With emphasis firmly on such practical matters, this handbook se

A Quantitative Analysis of the Extrinsic and Intrinsic Turnover Factors of Relational Database Support Professionals

Science.gov (United States)

Takusi, Gabriel Samuto

2010-01-01

This quantitative analysis explored the intrinsic and extrinsic turnover factors of relational database support specialists. Two hundred and nine relational database support specialists were surveyed for this research. The research was conducted based on Hackman and Oldham's (1980) Job Diagnostic Survey. Regression analysis and a univariate ANOVA…

Thyroid V50 Highly Predictive of Hypothyroidism in Head-and-Neck Cancer Patients Treated With Intensity-modulated Radiotherapy (IMRT).

Science.gov (United States)

Sachdev, Sean; Refaat, Tamer; Bacchus, Ian D; Sathiaseelan, Vythialinga; Mittal, Bharat B

2017-08-01

Radiation-induced hypothyroidism affects a significant number of patients with head-and-neck squamous cell cancer (HNSCC). We examined detailed dosimetric and clinical parameters to better determine the risk of hypothyroidism in euthyroid HNSCC patients treated with intensity-modulated radiation therapy (IMRT). From 2006 to 2010, 75 clinically euthyroid patients with HNSCC were treated with sequential IMRT. The cohort included 59 men and 16 females with a median age of 55 years (range, 30 to 89 y) who were treated to a median dose of 70 Gy (range, 60 to 75 Gy) with concurrent chemotherapy in nearly all (95%) cases. Detailed thyroid dosimetric parameters including maximum dose, mean dose, and other parameters (eg, V50-percent volume receiving at least 50 Gy) were obtained. Freedom from hypothyroidism was evaluated using the Kaplan-Meier method. Univariate and multivariate analyses were conducted using Cox regression. After a median follow-up period of 50 months, 25 patients (33%) became hypothyroid. On univariate analysis, thyroid V50 was highly correlated with developing hypothyroidism (P=0.035). Other dosimetric paramaters including mean thyroid dose (P=0.11) and maximum thyroid dose (P=0.39) did not reach statistical significance. On multivariate analysis incorporating patient, tumor, and treatment variables, V50 remained highly statistically significant (P=0.037). Regardless of other factors, for V50>60%, the odds ratio of developing hypothyroidism was 6.76 (P=0.002). In HNSCC patients treated with IMRT, thyroid V50 highly predicts the risk of developing hypothyroidism. V50>60% puts patients at a significantly higher risk of becoming hypothyroid. This can be a useful dose constraint to consider during treatment planning.

Analysis of prognostic factors in stage IIB-IVA cervical carcinoma treated with radiation therapy: value of computed tomography

International Nuclear Information System (INIS)

Ogino, Ichiro; Okamoto, Naoyuki; Andoh, Kazuo; Kitamura, Tatsuo; Okajima, Hiroyuki; Matsubara, Sho

1997-01-01

Purpose: To define the influence of the tumor size measured by computed tomography (CT) and lymph node involvement detected by CT in patients treated with radiation therapy for Stage IIB-IVA carcinoma of intact uterine cervix. Methods and Materials: This was a retrospective analysis of 233 patients with uterine cervical cancer managed with both external irradiation and high-dose-rate intracavitary brachytherapy (HDR-ICR) at Kanagawa Cancer Center. The results were analyzed for the end points of absolute survival (AS), disease-free survival (DFS), pelvic control (PC), and central control (CC). The parameters of stage, CT-measured anterior-posterior (AP) cervix size, and CT-detected lymph node metastases were evaluated using univariate and multivariate analysis. Results: The stage, AP cervix size, and lymph node involvement were significant pretreatment factors in univariate analysis with respect to AS, DFS, PC, and CC. Multivariate analysis confirmed that significant risk was associated with certain prognostic parameters. Those in terms of AS, in order of decreasing significance, were lymph node involvement, AP cervix size, age, and total HDR-ICR dose. When DFS was studied, lymph node involvement and AP cervix size were demonstrated to have a significant effect. Stage and lymph node involvement significantly affected PC. Conclusion: Because the International Federation of Gynecological Obstetrics staging system fails to incorporate important prognostic information about tumor volume and lymph node involvement, CT-detected lymph node metastases as well as CT-measured cervix size should be determined as complementary additional prognostic measures

Bivariate Rainfall and Runoff Analysis Using Shannon Entropy Theory

Science.gov (United States)

Rahimi, A.; Zhang, L.

2012-12-01

Rainfall-Runoff analysis is the key component for many hydrological and hydraulic designs in which the dependence of rainfall and runoff needs to be studied. It is known that the convenient bivariate distribution are often unable to model the rainfall-runoff variables due to that they either have constraints on the range of the dependence or fixed form for the marginal distributions. Thus, this paper presents an approach to derive the entropy-based joint rainfall-runoff distribution using Shannon entropy theory. The distribution derived can model the full range of dependence and allow different specified marginals. The modeling and estimation can be proceeded as: (i) univariate analysis of marginal distributions which includes two steps, (a) using the nonparametric statistics approach to detect modes and underlying probability density, and (b) fitting the appropriate parametric probability density functions; (ii) define the constraints based on the univariate analysis and the dependence structure; (iii) derive and validate the entropy-based joint distribution. As to validate the method, the rainfall-runoff data are collected from the small agricultural experimental watersheds located in semi-arid region near Riesel (Waco), Texas, maintained by the USDA. The results of unviariate analysis show that the rainfall variables follow the gamma distribution, whereas the runoff variables have mixed structure and follow the mixed-gamma distribution. With this information, the entropy-based joint distribution is derived using the first moments, the first moments of logarithm transformed rainfall and runoff, and the covariance between rainfall and runoff. The results of entropy-based joint distribution indicate: (1) the joint distribution derived successfully preserves the dependence between rainfall and runoff, and (2) the K-S goodness of fit statistical tests confirm the marginal distributions re-derived reveal the underlying univariate probability densities which further

Preliminary Toxicity Analysis of 3-Dimensional Conformal Radiation Therapy Versus Intensity Modulated Radiation Therapy on the High-Dose Arm of the Radiation Therapy Oncology Group 0126 Prostate Cancer Trial

Energy Technology Data Exchange (ETDEWEB)

Michalski, Jeff M., E-mail: jmichalski@radonc.wustl.edu [Department of Radiation Oncology Washington University Medical Center, St. Louis, Missouri (United States); Yan, Yan [Radiation Therapy Oncology Group Statistical Center, Philadelphia, Pennsylvania (United States); Watkins-Bruner, Deborah [Emory University School of Nursing, Atlanta, Georgia (United States); Bosch, Walter R. [Department of Radiation Oncology Washington University Medical Center, St. Louis, Missouri (United States); Winter, Kathryn [Radiation Therapy Oncology Group Statistical Center, Philadelphia, Pennsylvania (United States); Galvin, James M. [Department of Radiation Oncology Thomas Jefferson University Hospital, Philadelphia, Pennsylvania (United States); Bahary, Jean-Paul [Department of Radiation Oncology Centre Hospitalier de l' Université de Montréal-Notre Dame, Montreal, QC (Canada); Morton, Gerard C. [Department of Radiation Oncology Toronto-Sunnybrook Regional Cancer Centre, Toronto, ON (Canada); Parliament, Matthew B. [Department of Oncology Cross Cancer Institute, Edmonton, AB (Canada); Sandler, Howard M. [Department of Radiation Oncology Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California (United States)

2013-12-01

Purpose: To give a preliminary report of clinical and treatment factors associated with toxicity in men receiving high-dose radiation therapy (RT) on a phase 3 dose-escalation trial. Methods and Materials: The trial was initiated with 3-dimensional conformal RT (3D-CRT) and amended after 1 year to allow intensity modulated RT (IMRT). Patients treated with 3D-CRT received 55.8 Gy to a planning target volume that included the prostate and seminal vesicles, then 23.4 Gy to prostate only. The IMRT patients were treated to the prostate and proximal seminal vesicles to 79.2 Gy. Common Toxicity Criteria, version 2.0, and Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer late morbidity scores were used for acute and late effects. Results: Of 763 patients randomized to the 79.2-Gy arm of Radiation Therapy Oncology Group 0126 protocol, 748 were eligible and evaluable: 491 and 257 were treated with 3D-CRT and IMRT, respectively. For both bladder and rectum, the volumes receiving 65, 70, and 75 Gy were significantly lower with IMRT (all P<.0001). For grade (G) 2+ acute gastrointestinal/genitourinary (GI/GU) toxicity, both univariate and multivariate analyses showed a statistically significant decrease in G2+ acute collective GI/GU toxicity for IMRT. There were no significant differences with 3D-CRT or IMRT for acute or late G2+ or 3+ GU toxicities. Univariate analysis showed a statistically significant decrease in late G2+ GI toxicity for IMRT (P=.039). On multivariate analysis, IMRT showed a 26% reduction in G2+ late GI toxicity (P=.099). Acute G2+ toxicity was associated with late G3+ toxicity (P=.005). With dose–volume histogram data in the multivariate analysis, RT modality was not significant, whereas white race (P=.001) and rectal V70 ≥15% were associated with G2+ rectal toxicity (P=.034). Conclusions: Intensity modulated RT is associated with a significant reduction in acute G2+ GI/GU toxicity. There is a trend for a

Development and validation of a method for the determination of regulated fragrance allergens by High-Performance Liquid Chromatography and Parallel Factor Analysis 2.

Science.gov (United States)

Pérez-Outeiral, Jessica; Elcoroaristizabal, Saioa; Amigo, Jose Manuel; Vidal, Maider

2017-12-01

This work presents the development and validation of a multivariate method for quantitation of 6 potentially allergenic substances (PAS) related to fragrances by ultrasound-assisted emulsification microextraction coupled with HPLC-DAD and PARAFAC2 in the presence of other 18 PAS. The objective is the extension of a previously proposed univariate method to be able to determine the 24 PAS currently considered as allergens. The suitability of the multivariate approach for the qualitative and quantitative analysis of the analytes is discussed through datasets of increasing complexity, comprising the assessment and validation of the method performance. PARAFAC2 showed to adequately model the data facing up different instrumental and chemical issues, such as co-elution profiles, overlapping spectra, unknown interfering compounds, retention time shifts and baseline drifts. Satisfactory quality parameters of the model performance were obtained (R 2 ≥0.94), as well as meaningful chromatographic and spectral profiles (r≥0.97). Moreover, low errors of prediction in external validation standards (below 15% in most cases) as well as acceptable quantification errors in real spiked samples (recoveries from 82 to 119%) confirmed the suitability of PARAFAC2 for resolution and quantification of the PAS. The combination of the previously proposed univariate approach, for the well-resolved peaks, with the developed multivariate method allows the determination of the 24 regulated PAS. Copyright © 2017 Elsevier B.V. All rights reserved.

Cement Leakage in Percutaneous Vertebral Augmentation for Osteoporotic Vertebral Compression Fractures: Analysis of Risk Factors.

Science.gov (United States)

Xie, Weixing; Jin, Daxiang; Ma, Hui; Ding, Jinyong; Xu, Jixi; Zhang, Shuncong; Liang, De

2016-05-01

The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA). To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures. PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial. A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis. The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (Pcement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively. High bone density and vertebral cortical bone defect are independent risk factors associated with bone cement leakage.

Textural analysis of pre-therapeutic [18F]-FET-PET and its correlation with tumor grade and patient survival in high-grade gliomas

Energy Technology Data Exchange (ETDEWEB)

Pyka, Thomas; Hiob, Daniela; Wester, Hans-Juergen [Klinikum Rechts der Isar der TU Muenchen, Department of Nuclear Medicine, Munich (Germany); Gempt, Jens; Ringel, Florian; Meyer, Bernhard [Klinikum Rechts der Isar der TU Muenchen, Neurosurgic Department, Munich (Germany); Schlegel, Juergen [Klinikum Rechts der Isar der TU Muenchen, Institute of Pathology and Neuropathology, Munich (Germany); Bette, Stefanie [Klinikum Rechts der Isar der TU Muenchen, Neuroradiologic department, Munich (Germany); Foerster, Stefan [Klinikum Rechts der Isar der TU Muenchen, Department of Nuclear Medicine, Munich (Germany); Klinikum Rechts der Isar der TU Muenchen, TUM Neuroimaging Center (TUM-NIC), Munich (Germany)

2016-01-15

Amino acid positron emission tomography (PET) with [18F]-fluoroethyl-L-tyrosine (FET) is well established in the diagnostic work-up of malignant brain tumors. Analysis of FET-PET data using tumor-to-background ratios (TBR) has been shown to be highly valuable for the detection of viable hypermetabolic brain tumor tissue; however, it has not proven equally useful for tumor grading. Recently, textural features in 18-fluorodeoxyglucose-PET have been proposed as a method to quantify the heterogeneity of glucose metabolism in a variety of tumor entities. Herein we evaluate whether textural FET-PET features are of utility for grading and prognostication in patients with high-grade gliomas. One hundred thirteen patients (70 men, 43 women) with histologically proven high-grade gliomas were included in this retrospective study. All patients received static FET-PET scans prior to first-line therapy. TBR (max and mean), volumetric parameters and textural parameters based on gray-level neighborhood difference matrices were derived from static FET-PET images. Receiver operating characteristic (ROC) and discriminant function analyses were used to assess the value for tumor grading. Kaplan-Meier curves and univariate and multivariate Cox regression were employed for analysis of progression-free and overall survival. All FET-PET textural parameters showed the ability to differentiate between World Health Organization (WHO) grade III and IV tumors (p < 0.001; AUC 0.775). Further improvement in discriminatory power was possible through a combination of texture and metabolic tumor volume, classifying 85 % of tumors correctly (AUC 0.830). TBR and volumetric parameters alone were correlated with tumor grade, but showed lower AUC values (0.644 and 0.710, respectively). Furthermore, a correlation of FET-PET texture but not TBR was shown with patient PFS and OS, proving significant in multivariate analysis as well. Volumetric parameters were predictive for OS, but this correlation did not

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.

Statistical Analysis of Research Data | Center for Cancer Research

Science.gov (United States)

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data. The Statistical Analysis of Research Data (SARD) course will be held on April 5-6, 2018 from 9 a.m.-5 p.m. at the National Institutes of Health's Natcher Conference Center, Balcony C on the Bethesda Campus. SARD is designed to provide an overview on the general principles of statistical analysis of research data.  The first day will feature univariate data analysis, including descriptive statistics, probability distributions, one- and two-sample inferential statistics.

Age is highly associated with stereo blindness among surgeons

DEFF Research Database (Denmark)

Fergo, Charlotte; Burcharth, Jakob; Pommergaard, Hans-Christian

2016-01-01

BACKGROUND: The prevalence of stereo blindness in the general population varies greatly within a range of 1-30 %. Stereo vision adds an extra dimension to aid depth perception and gives a binocular advantage in task completion. Lack of depth perception may lower surgical performance, potentially...... and stereo tested by the use of the Random Dot E stereo test. Upon stereo testing, a demographic questionnaire was completed. Multivariate logistic regression analysis was employed to assess the association between stereo blindness and the variables resulting from the univariate analysis. RESULTS: Three...

Development of automatic image analysis methods for high-throughput and high-content screening

NARCIS (Netherlands)

Di, Zi

2013-01-01

This thesis focuses on the development of image analysis methods for ultra-high content analysis of high-throughput screens where cellular phenotype responses to various genetic or chemical perturbations that are under investigation. Our primary goal is to deliver efficient and robust image analysis

Flood risk analysis for flood control and sediment transportation in sandy regions: A case study in the Loess Plateau, China

Science.gov (United States)

Guo, Aijun; Chang, Jianxia; Wang, Yimin; Huang, Qiang; Zhou, Shuai

2018-05-01

Traditional flood risk analysis focuses on the probability of flood events exceeding the design flood of downstream hydraulic structures while neglecting the influence of sedimentation in river channels on regional flood control systems. This work advances traditional flood risk analysis by proposing a univariate and copula-based bivariate hydrological risk framework which incorporates both flood control and sediment transport. In developing the framework, the conditional probabilities of different flood events under various extreme precipitation scenarios are estimated by exploiting the copula-based model. Moreover, a Monte Carlo-based algorithm is designed to quantify the sampling uncertainty associated with univariate and bivariate hydrological risk analyses. Two catchments located on the Loess plateau are selected as study regions: the upper catchments of the Xianyang and Huaxian stations (denoted as UCX and UCH, respectively). The univariate and bivariate return periods, risk and reliability in the context of uncertainty for the purposes of flood control and sediment transport are assessed for the study regions. The results indicate that sedimentation triggers higher risks of damaging the safety of local flood control systems compared with the event that AMF exceeds the design flood of downstream hydraulic structures in the UCX and UCH. Moreover, there is considerable sampling uncertainty affecting the univariate and bivariate hydrologic risk evaluation, which greatly challenges measures of future flood mitigation. In addition, results also confirm that the developed framework can estimate conditional probabilities associated with different flood events under various extreme precipitation scenarios aiming for flood control and sediment transport. The proposed hydrological risk framework offers a promising technical reference for flood risk analysis in sandy regions worldwide.

Characterising the extent of misreporting of high blood pressure, high cholesterol, and diabetes using the Australian Health Survey.

Science.gov (United States)

Peterson, Karen Louise; Jacobs, Jane Philippa; Allender, Steven; Alston, Laura Veronica; Nichols, Melanie

2016-08-02

Measuring and monitoring the true prevalence of risk factors for chronic conditions is essential for evidence-based policy and health service planning. Understanding the prevalence of risk factors for cardiovascular disease (CVD) in Australia relies heavily on self-report measures from surveys, such as the triennial National Health Survey. However, international evidence suggests that self-reported data may substantially underestimate actual risk factor prevalence. This study sought to characterise the extent of misreporting in a large, nationally-representative health survey that included objective measures of clinical risk factors for CVD. This study employed a cross-sectional analysis of 7269 adults aged 18 years and over who provided fasting blood samples as part of the 2011-12 Australian Health Survey. Self-reported prevalence of high blood pressure, high cholesterol and diabetes was compared to measured prevalence, and univariate and multivariate logistic regression analyses identified socio-demographic characteristics associated with underreporting for each risk factor. Approximately 16 % of the total sample underreported high blood pressure (measured to be at high risk but didn't report a diagnosis), 33 % underreported high cholesterol, and 1.3 % underreported diabetes. Among those measured to be at high risk, 68 % did not report a diagnosis for high blood pressure, nor did 89 % of people with high cholesterol and 29 % of people with high fasting plasma glucose. Younger age was associated with underreporting high blood pressure and high cholesterol, while lower area-level disadvantage and higher income were associated with underreporting diabetes. Underreporting has important implications for CVD risk factor surveillance, policy planning and decisions, and clinical best-practice guidelines. This analysis highlights concerns about the reach of primary prevention efforts in certain groups and implications for patients who may be unaware of their

Characterising the extent of misreporting of high blood pressure, high cholesterol, and diabetes using the Australian Health Survey

Directory of Open Access Journals (Sweden)

Karen Louise Peterson

2016-08-01

Full Text Available Abstract Background Measuring and monitoring the true prevalence of risk factors for chronic conditions is essential for evidence-based policy and health service planning. Understanding the prevalence of risk factors for cardiovascular disease (CVD in Australia relies heavily on self-report measures from surveys, such as the triennial National Health Survey. However, international evidence suggests that self-reported data may substantially underestimate actual risk factor prevalence. This study sought to characterise the extent of misreporting in a large, nationally-representative health survey that included objective measures of clinical risk factors for CVD. Methods This study employed a cross-sectional analysis of 7269 adults aged 18 years and over who provided fasting blood samples as part of the 2011–12 Australian Health Survey. Self-reported prevalence of high blood pressure, high cholesterol and diabetes was compared to measured prevalence, and univariate and multivariate logistic regression analyses identified socio-demographic characteristics associated with underreporting for each risk factor. Results Approximately 16 % of the total sample underreported high blood pressure (measured to be at high risk but didn’t report a diagnosis, 33 % underreported high cholesterol, and 1.3 % underreported diabetes. Among those measured to be at high risk, 68 % did not report a diagnosis for high blood pressure, nor did 89 % of people with high cholesterol and 29 % of people with high fasting plasma glucose. Younger age was associated with underreporting high blood pressure and high cholesterol, while lower area-level disadvantage and higher income were associated with underreporting diabetes. Conclusions Underreporting has important implications for CVD risk factor surveillance, policy planning and decisions, and clinical best-practice guidelines. This analysis highlights concerns about the reach of primary prevention efforts in certain

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study.

Directory of Open Access Journals (Sweden)

Binod Neupane

Full Text Available In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when

Multivariate analysis with LISREL

CERN Document Server

Jöreskog, Karl G; Y Wallentin, Fan

2016-01-01

This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis.

Applied quantitative analysis in the social sciences

CERN Document Server

Petscher, Yaacov; Compton, Donald L

2013-01-01

To say that complex data analyses are ubiquitous in the education and social sciences might be an understatement. Funding agencies and peer-review journals alike require that researchers use the most appropriate models and methods for explaining phenomena. Univariate and multivariate data structures often require the application of more rigorous methods than basic correlational or analysis of variance models. Additionally, though a vast set of resources may exist on how to run analysis, difficulties may be encountered when explicit direction is not provided as to how one should run a model

Upper esophageal sphincter (UES) metrics on high-resolution manometry (HRM) differentiate achalasia subtypes.

Science.gov (United States)

Blais, P; Patel, A; Sayuk, G S; Gyawali, C P

2017-12-01

The upper esophageal sphincter (UES) reflexively responds to bolus presence within the esophageal lumen, therefore UES metrics can vary in achalasia. Within consecutive patients undergoing esophageal high-resolution manometry (HRM), 302 patients (58.2±1.0 year, 57% F) with esophageal outflow obstruction were identified, and compared to 16 asymptomatic controls (27.7±0.7 year, 56% F). Esophageal outflow obstruction was segregated into achalasia subtypes 1, 2, and 3, and esophagogastric junction outflow obstruction (EGJOO with intact peristalsis) using Chicago Classification v3.0. UES and lower esophageal sphincter (LES) metrics were compared between esophageal outflow obstruction and normal controls using univariate and multivariate analysis. Linear regression excluded multicollinearity of pressure metrics that demonstrated significant differences across individual subtype comparisons. LES integrated relaxation pressure (IRP) had utility in differentiating achalasia from controls (P<.0001), but no utility in segregating between subtypes (P=.27). In comparison to controls, patients collectively demonstrated univariate differences in UES mean basal pressure, relaxation time to nadir, recovery time, and residual pressure (UES-RP) (P≤.049). UES-RP was highest in type 2 achalasia (P<.0001 compared to other subtypes and controls). In multivariate analysis, only UES-RP retained significance in comparison between each of the subgroups (P≤.02 for each comparison). Intrabolus pressure was highest in type 3 achalasia; this demonstrated significant differences across some but not all subtype comparisons. Nadir UES-RP can differentiate achalasia subtypes within the esophageal outflow obstruction spectrum, with highest values in type 2 achalasia. This metric likely represents a surrogate marker for esophageal pressurization. © 2017 John Wiley & Sons Ltd.

Multivariate meta-analysis: Potential and promise

Science.gov (United States)

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

Results of radiotherapy for meningeomas with high risk for local recurrence. A retrospective analysis; Ergebnisse der Strahlentherapie bei Meningeomen mit hohem Rezidivrisiko. Eine retrospektive Analyse

Energy Technology Data Exchange (ETDEWEB)

Winkler, C.; Dornfeld, S.; Friedrich, S.; Baumann, M. [Technische Univ. Dresden (Germany). Klinik und Poliklinik fuerStrahlentherapie und Radioonkologie; Schwarz, R. [Universitaetskrankenhaus Hamburg-Eppendorf (Germany). Abt. fuer Strahlentherapie

1998-12-01

Aim: Retrospective assessment of the efficacy of radiatiotherapy for meningeomas with high risk for local recurrence. Patients and methods: Records of 67 patients with meningeomas treated from 1974 to 1995 at 2 centres were analyzed. Follow-up time ranged from 0.8 to 213 months (median: 61 months). Radiation therapy was given either after local failure or after biopsy or subtotal resection. The ratio between malignant (n=20) and benign (n=47) meningenoma was 1:2.4. Median age of the patients was 55 years (7 to 77 years). Radiation treatment was given at 1.5 to 2 Gy per fraction to 36 to 79.5 Gy. Survival rates were calculated by the Kaplan-Meier method. Statistical comparisons were performed with the log-rank test and the Cox proportional hazards model. The Bonferroni method was used to correct for multiple comparisons. Results: Five- and 10-year disease-free survival rates were 82%{+-}5% (standard error) and 70%{+-}9%. Local control rates at 5 and 10 years were 78%{+-}5% and 68%{+-}9%. In uni- and multivariate analysis histology, sex, total dose and center showed no significant influence on the results. Patients age was significant for local control (univariate p=0.02; multivariate p=0.03) and disease-free survival (univariate/multivariate p=0.04). The postoperative tumor burden had a significant influence of disease-free survival (multivariate P=0.04). After Bonferroni correction no significant influenc e was observed. We did not observe late side effects, especially brain necrosis. Conclusions: Despite of the negative selection of our patients we observed high survival- and local control rates after radiation therapy. This underscores the role of radiation therapy in the treatment of meningeomas with high risk of local failure. (orig.) [Deutsch] Hintergrund: Retrospektive Auswertung der Behandlungsergebnisse der Bestrahlung von Meningeomen mit hohem Rezidivrisiko. Patienten und Methode: Im Zeitraum zwischen 1974 und 1995 wurden an zwei Zentren insgesamt 67

Statistical Analysis Of Reconnaissance Geochemical Data From ...

African Journals Online (AJOL)

, Co, Mo, Hg, Sb, Tl, Sc, Cr, Ni, La, W, V, U, Th, Bi, Sr and Ga in 56 stream sediment samples collected from Orle drainage system were subjected to univariate and multivariate statistical analyses. The univariate methods used include ...

Estimating an Effect Size in One-Way Multivariate Analysis of Variance (MANOVA)

Science.gov (United States)

Steyn, H. S., Jr.; Ellis, S. M.

2009-01-01

When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…

Uncertainty Visualization Using Copula-Based Analysis in Mixed Distribution Models.

Science.gov (United States)

Hazarika, Subhashis; Biswas, Ayan; Shen, Han-Wei

2018-01-01

Distributions are often used to model uncertainty in many scientific datasets. To preserve the correlation among the spatially sampled grid locations in the dataset, various standard multivariate distribution models have been proposed in visualization literature. These models treat each grid location as a univariate random variable which models the uncertainty at that location. Standard multivariate distributions (both parametric and nonparametric) assume that all the univariate marginals are of the same type/family of distribution. But in reality, different grid locations show different statistical behavior which may not be modeled best by the same type of distribution. In this paper, we propose a new multivariate uncertainty modeling strategy to address the needs of uncertainty modeling in scientific datasets. Our proposed method is based on a statistically sound multivariate technique called Copula, which makes it possible to separate the process of estimating the univariate marginals and the process of modeling dependency, unlike the standard multivariate distributions. The modeling flexibility offered by our proposed method makes it possible to design distribution fields which can have different types of distribution (Gaussian, Histogram, KDE etc.) at the grid locations, while maintaining the correlation structure at the same time. Depending on the results of various standard statistical tests, we can choose an optimal distribution representation at each location, resulting in a more cost efficient modeling without significantly sacrificing on the analysis quality. To demonstrate the efficacy of our proposed modeling strategy, we extract and visualize uncertain features like isocontours and vortices in various real world datasets. We also study various modeling criterion to help users in the task of univariate model selection.

Average-case analysis of numerical problems

CERN Document Server

2000-01-01

The average-case analysis of numerical problems is the counterpart of the more traditional worst-case approach. The analysis of average error and cost leads to new insight on numerical problems as well as to new algorithms. The book provides a survey of results that were mainly obtained during the last 10 years and also contains new results. The problems under consideration include approximation/optimal recovery and numerical integration of univariate and multivariate functions as well as zero-finding and global optimization. Background material, e.g. on reproducing kernel Hilbert spaces and random fields, is provided.

Serial Expression Analysis: a web tool for the analysis of serial gene expression data

Science.gov (United States)

Nueda, Maria José; Carbonell, José; Medina, Ignacio; Dopazo, Joaquín; Conesa, Ana

2010-01-01

Serial transcriptomics experiments investigate the dynamics of gene expression changes associated with a quantitative variable such as time or dosage. The statistical analysis of these data implies the study of global and gene-specific expression trends, the identification of significant serial changes, the comparison of expression profiles and the assessment of transcriptional changes in terms of cellular processes. We have created the SEA (Serial Expression Analysis) suite to provide a complete web-based resource for the analysis of serial transcriptomics data. SEA offers five different algorithms based on univariate, multivariate and functional profiling strategies framed within a user-friendly interface and a project-oriented architecture to facilitate the analysis of serial gene expression data sets from different perspectives. SEA is available at sea.bioinfo.cipf.es. PMID:20525784

School violence: An analysis from different interaction contexts

Directory of Open Access Journals (Sweden)

Rosa María Varela Garay

2013-04-01

Full Text Available The aim of the current study was to analyze the differences between adolescents scoring high and low on school violence in the following areas: individual (self-esteem, loneliness, satisfaction with life, and empathy; family (family climate, communication with father and mother; academic (classroom climate, attitudes toward authority, and sociometric status; and community (community involvement, community participation, social support from formal systems, and social support from informal systems. Differences in these relationships between boys and girls scoring high on school violence were also examined. Participants in the study were 1723 adolescents, aged 12 to 18 years old, in four secondary schools. Multivariate and univariate analysis of variance were performed. Results showed that adolescents with high levels of school violence scored higher on loneliness, depressive symptomatology, offensive and avoidance communication with father and mother, family conflict, and attitude towards transgression, as compared to adolescents with low levels of school violence. Furthermore, girls scoring high on school violence reported higher scores on academic self-esteem, empathy, and sociometric status, and lower scores on open communication with father and community participation, as compared to boys scoring high in school violence. Finally, these results and their practical implications are discussed.

An analysis of respondent-driven sampling with injecting drug users in a high HIV prevalent state of India.

Science.gov (United States)

Phukan, Sanjib Kumar; Medhi, Gajendra Kumar; Mahanta, Jagadish; Adhikary, Rajatashuvra; Thongamba, Gay; Paranjape, Ramesh S; Akoijam, Brogen S

2017-07-03

Personal networks are significant social spaces to spread of HIV or other blood-borne infections among hard-to-reach population, viz., injecting drug users, female sex workers, etc. Sharing of infected needles or syringes among drug users is one of the major routes of HIV transmission in Manipur, a high HIV prevalence state in India. This study was carried out to describe the network characteristics and recruitment patterns of injecting drug users and to assess the association of personal network with injecting risky behaviors in Manipur. A total of 821 injecting drug users were recruited into the study using respondent-driven sampling (RDS) from Bishnupur and Churachandpur districts of Manipur; data on demographic characteristics, HIV risk behaviors, and network size were collected from them. Transition probability matrices and homophily indices were used to describe the network characteristics, and recruitment patterns of injecting drug users. Univariate and multivariate binary logistic regression models were performed to analyze the association between the personal networks and sharing of needles or syringes. The average network size was similar in both the districts. Recruitment analysis indicates injecting drug users were mostly engaged in mixed age group setting for injecting practice. Ever married and new injectors showed lack of in-group ties. Younger injecting drug users had mainly recruited older injecting drug users from their personal network. In logistic regression analysis, higher personal network was found to be significantly associated with increased likelihood of injecting risky behaviors. Because of mixed personal network of new injectors and higher network density associated with HIV exposure, older injecting drug users may act as a link for HIV transmission or other blood-borne infections to new injectors and also to their sexual partners. The information from this study may be useful to understanding the network pattern of injecting drug users

What marketing scholars should know about time series analysis : time series applications in marketing

NARCIS (Netherlands)

Horváth, Csilla; Kornelis, Marcel; Leeflang, Peter S.H.

2002-01-01

In this review, we give a comprehensive summary of time series techniques in marketing, and discuss a variety of time series analysis (TSA) techniques and models. We classify them in the sets (i) univariate TSA, (ii) multivariate TSA, and (iii) multiple TSA. We provide relevant marketing

High Heels: A Study of Personality and Fashion Conscience

Directory of Open Access Journals (Sweden)

Suzane Strehlau

2013-06-01

Full Text Available This article investigates the relationship between the use of high heels, personality traits, and fashion consciousness of adult women. The theory of consumer behavior states that the personality of the consumer is a psychological factor that affects consumer decisions, as well as the attitude towards fashion. A survey with 83 women was conducted with two questionnaires. One questionnaire was about fashion consciousness and the use of high heels, and the other utilized the HumanGuide test. The analysis used univariate and multivariate techniques with the aid of SPSS software and Partial Least Squares. The results indicate that 60% of respondents feel pain when wearing high heels. Although designers indicate that a high heel height is above 8 cm, this research indicates that women consider a high heel from 5 cm. Only 27.3% of the responders over 50 years of age use high heels over 8.5 cm. The HumanGuide proved to be useful for Marketing in the sense that the respondents had no difficulty in answering the questions. The use of high heels is mostly explained by fashion consciousness. The most influential factor was the stability of personality, individuals described as conservative, traditional, economical, stable, cautious, steady, and serious. Thus, it appears that these respondents wear high heels because they are related to an elegant traditional dress.DOI: 10.5585/remark.v12i2.2563

High-Grade Hydronephrosis Predicts Poor Outcomes After Radical Cystectomy in Patients with Bladder Cancer

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Kim, Dong Suk; Cho, Kang Su; Lee, Young Hoon; Cho, Nam Hoon; Oh, Young Taek

2010-01-01

We examined whether the presence and severity of preoperative hydronephrosis have prognostic significance in patients who underwent radical cystectomy for transitional cell carcinoma of the bladder. The medical records of 457 patients who underwent radical cystectomy for bladder cancer between 1986 and 2005 were retrospectively reviewed. Following the Society for Fetal Urology grading system, patients were divided into low-, and high-grade hydronephrosis groups. Clinicopathologic factors associated with preoperative hydronephrosis and survival were evaluated. Of a total of 406 patients, unilateral hydronephrosis was found in 74 (18.2%), bilateral hydronephrosis in 11 (2.7%), and no hydronephoris in 321 (79.1%). Low-grade hydronephrosis was found in 57 (12.2%) patients and high-grade hydronephrosis in 28 (6%). Preoperative hydronephrosis was related to higher pT stage and lymph node invasion. In univariate analysis, the presence of hydronephrosis, hydronephrosis grade, age, pT and pN stage, tumor grade, surgical margin, number of retrieved nodes, carcinoma in situ, and lymphovascular invasion were significant prognostic factors for cancer-specific survival. In multivariate analysis, bilateral hydronephrosis and high-grade hydronephrosis remained significant predictors for decreased survival. The presence of preoperative hydronephrosis, and high-grade hydronephrosis are significant prognostic factors in patients with bladder cancer after radical cystectomy. PMID:20191034

DCE-MRI texture analysis with tumor subregion partitioning for predicting Ki-67 status of estrogen receptor-positive breast cancers

KAUST Repository

Fan, Ming

2017-12-08

Breast tumor heterogeneity is related to risk factors that lead to worse prognosis, yet such heterogeneity has not been well studied.To predict the Ki-67 status of estrogen receptor (ER)-positive breast cancer patients via analysis of tumor heterogeneity with subgroup identification based on patterns of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).Retrospective study.Seventy-seven breast cancer patients with ER-positive breast cancer were investigated, of whom 51 had low Ki-67 expression.T1 -weighted 3.0T DCE-MR images.Each tumor was partitioned into multiple subregions using three methods based on patterns of dynamic enhancement: 1) time to peak (TTP), 2) peak enhancement rate (PER), and 3) kinetic pattern clustering (KPC). In each tumor subregion, 18 texture features were computed.Univariate and multivariate logistic regression analyses were performed using a leave-one-out-based cross-validation (LOOCV) method. The partitioning results were compared with the same feature extraction methods across the whole tumor.In the univariate analysis, the best-performing feature was the texture statistic of sum variance in the tumor subregion with early TTP for differentiating between patients with high and low Ki-67 expression (area under the receiver operating characteristic curves, AUC = 0.748). Multivariate analysis showed that features from the tumor subregion associated with early TTP yielded the highest performance (AUC = 0.807) among the subregions for predicting the Ki-67 status. Among all regions, the tumor area with high PER at a precontrast MR image achieved the highest performance (AUC = 0.722), while the subregion that exhibited the highest overall enhancement rate based on KPC had an AUC of 0.731. These three models based on intratumoral texture analysis significantly (P < 0.01) outperformed the model using features from the whole tumor (AUC = 0.59).Texture analysis of intratumoral heterogeneity has the potential to serve as a valuable

A retrospective analysis of survival and prognostic factors after stereotactic radiosurgery for aggressive meningiomas

International Nuclear Information System (INIS)

Ferraro, Daniel J; Zoberi, Imran; Simpson, Joseph R; Jaboin, Jerry J; Funk, Ryan K; Blackett, John William; Ju, Michelle R; DeWees, Todd A; Chicoine, Michael R; Dowling, Joshua L; Rich, Keith M; Drzymala, Robert E

2014-01-01

While most meningiomas are benign, aggressive meningiomas are associated with high levels of recurrence and mortality. A single institution’s Gamma Knife radiosurgical experience with atypical and malignant meningiomas is presented, stratified by the most recent WHO classification. Thirty-one patients with atypical and 4 patients with malignant meningiomas treated with Gamma Knife radiosurgery between July 2000 and July 2011 were retrospectively reviewed. All patients underwent prior surgical resection. Overall survival was the primary endpoint and rate of disease recurrence in the brain was a secondary endpoint. Patients who had previous radiotherapy or prior surgical resection were included. Kaplan-Meier and Cox proportional hazards models were used to estimate survival and identify factors predictive of recurrence and survival. Post-Gamma Knife recurrence was identified in 11 patients (31.4%) with a median overall survival of 36 months and progression-free survival of 25.8 months. Nine patients (25.7%) had died. Three-year overall survival (OS) and progression-free survival (PFS) rates were 78.0% and 65.0%, respectively. WHO grade II 3-year OS and PFS were 83.4% and 70.1%, while WHO grade III 3-year OS and PFS were 33.3% and 0%. Recurrence rate was significantly higher in patients with a prior history of benign meningioma, nuclear atypia, high mitotic rate, spontaneous necrosis, and WHO grade III diagnosis on univariate analysis; only WHO grade III diagnosis was significant on multivariate analysis. Overall survival was adversely affected in patients with WHO grade III diagnosis, prior history of benign meningioma, prior fractionated radiotherapy, larger tumor volume, and higher isocenter number on univariate analysis; WHO grade III diagnosis and larger treated tumor volume were significant on multivariate analysis. Atypical and anaplastic meningiomas remain difficult tumors to treat. WHO grade III diagnosis and treated tumor volume were significantly

Factors associated with HIV among female sex workers in a high HIV prevalent state of India.

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Medhi, Gajendra Kumar; Mahanta, Jagadish; Paranjape, Ramesh S; Adhikary, Rajatashuvra; Laskar, Nabjyoti; Ngully, P

2012-01-01

The study was carried out to assess the factors associated with HIV seropositivity among female sex workers (FSWs) in Dimapur, Nagaland, a high HIV prevalence state of India. A total of 426 FSWs were recruited into the study using respondent driven sampling (RDS). Data on demographic characteristics, sexual and injecting risk behaviours were collected from them and were tested for HIV, Syphilis, Neisseria gonorrhoeae and Chlamydia trachomatis. RDS-weighted univariate and multivariate logistic regression analysis was performed to assess the factors associated with HIV seropositivity. Consistent condom use with regular and occasional sexual clients was 9% and 16.4%, respectively. About 25% of the participants ever used and 5.7% ever injected illicit drugs. RDS adjusted HIV prevalence was 11.6%. In the univariate analysis, factors associated with HIV were initiating sexual intercourse before the age of 15 years, ≥2 years duration of sex work, serving clients at lodge/hotel, positive test result for one or more sexually transmitted infections (STIs), lifetime history of injecting drug use, lifetime history of consuming illicit drugs, ever having exchanged sex for drugs, having sexual partners who engaged in risky injecting practices and having been widowed or divorced. In multivariate analysis, factors found to be independently associated with HIV included lifetime injecting drug use, initiating sexual intercourse before the age of 15 years, positive test result for one or more STIs and having been widowed. Injecting drug use was found to be most potent independent risk factor for HIV (OR: 3.17, CI: 1.02-9.89). Because of lower consistent condom use among them, FSWs may act as bridge for HIV transmission to general population from injecting drug users (IDU) through their sexual clients. The informations from this study may be useful for enriching the HIV preventions effort for FSWs in this region.

The Impact of Multiple Endpoint Dependency on "Q" and "I"[superscript 2] in Meta-Analysis

Science.gov (United States)

Thompson, Christopher Glen; Becker, Betsy Jane

2014-01-01

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures "Q" and…

Unplanned Readmission in Outpatient Hand Surgery: An Analysis of 23,613 Patients in the NSQIP Data Set.

Science.gov (United States)

Donato, Daniel P; Kwok, Alvin C; Bishop, Michael O; Presson, Angela P; Agarwal, Jayant P

2017-01-01

Objective: In an era of controlling cost and improving care, 30-day readmission rates have become an important quality measure. The purpose of this study was to identify the rates of 30-day unplanned readmission and the associated risk factors in patients undergoing outpatient hand surgery. Methods: The 2011-2014 National Surgical Quality Improvement Project data were queried for patients who met 368 hand-specific Current Procedural Terminology codes. Univariable and multivariable analyses were performed to identify patient- and surgery-specific risk factors associated with unplanned readmission within 30 days. Results: Of the 368 Current Procedural Terminology codes queried, 208 were represented in the data, for a total of 23,613 patients. The overall unplanned readmission rate was 0.88% (207/23,613). On both univariable and multivariable analyses, operative year (2012), increasing age, obesity, smoking status, chronic obstructive pulmonary disease, preoperative steroid use, preoperative anemia, increasing American Society of Anesthesiologists classification, increasing operative time, and a procedure performed by a surgeon other than a plastic or orthopedic surgeon were associated with increased readmission rates. Diabetes, hypertension, low albumin levels, elevated international normalized ratio, and dirty/infected wound classification were only significant in univariable analysis. Current Procedural Terminology codes associated with the highest readmission rates were related to amputations. The most common readmission diagnoses were wound complications, followed by uncontrolled postoperative pain. Conclusions: The incidence of unplanned readmission is low in patients undergoing outpatient hand surgery. Specific patient comorbidities are associated with increased unplanned readmission rates. This information may be useful in identifying patients at higher risk for unplanned readmission and in counseling of high-risk patients preparing for surgery.

Prognostic factors for long-term outcome after percutaneous thermal ablation for hepatocellular carcinoma: a survival analysis of 137 consecutive patients

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Xu, H.-X. [Department of Medical Ultrasonics, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou (China); Lu, M.-D. [Department of Hepatobiliary Surgery, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou (China); Xie, X.-Y. [Department of Medical Ultrasonics, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou (China); Yin, X.-Y. [Department of Hepatobiliary Surgery, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou (China); Kuang, M. [Department of Hepatobiliary Surgery, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou (China); Chen, J.-W. [Department of Hepatobiliary Surgery, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou (China); Xu, Z.-F. [Department of Medical Ultrasonics, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou (China); Liu, G.-J. [Department of Medical Ultrasonics, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou (China)

2005-09-01

AIM: To identify prognostic factors for long-term outcome for patients with hepatocellular carcinoma (HCC) after percutaneous microwave or radiofrequency ablation. MATERIALS AND METHODS: In total, 137 consecutive patients with HCC underwent microwave or radiofrequency ablation with curative intent; 16 possible prognostic factors were evaluated for their association with overall survival (OS) and disease-free survival (DFS) using univariate and multivariate analysis. RESULTS: The median OS and DFS were 27.0 months and 8.2 months, respectively. OS rates for all patients at 1, 2, 3, 4 and 5 years were 73.9%, 52.1%, 42.8%, 26.2% and 20.1%, respectively. DFS rates at 1, 2, 3 and 4 years were 38.1%, 21.9%, 18.8%, and 14.1%, respectively. Pretreatment serum alpha-fetoprotein (AFP) >200 ng/ml, pretreatment serum albumin {<=}35 g/dl, liver function Child's class C and incomplete ablation were found to be significant predictors for OS by univariate analysis. Using multivariate analysis, incomplete ablation was identified to be the most significant independent predictor for OS. Other independent predictors for OS were serum albumin level, serum AFP level and Child-Pugh classification. Recurrence after hepatectomy and prothrombin time >14 s were identified to be significant predictors for DFS by univariate analysis, and the former was the only independent predictor for DFS by multivariate analysis. CONCLUSION: Prognosis for patients with HCC after thermal ablation with curative intent was determined by treatment response to ablation, pretreatment serum AFP, and liver function reserve. Tumour response to treatment was the most predictive factor for long-term survival and was related to tumour size, thus careful selection of patients for ablation therapy is recommended.

Prognostic factors for long-term outcome after percutaneous thermal ablation for hepatocellular carcinoma: a survival analysis of 137 consecutive patients

International Nuclear Information System (INIS)

Xu, H.-X.; Lu, M.-D.; Xie, X.-Y.; Yin, X.-Y.; Kuang, M.; Chen, J.-W.; Xu, Z.-F.; Liu, G.-J.

2005-01-01

AIM: To identify prognostic factors for long-term outcome for patients with hepatocellular carcinoma (HCC) after percutaneous microwave or radiofrequency ablation. MATERIALS AND METHODS: In total, 137 consecutive patients with HCC underwent microwave or radiofrequency ablation with curative intent; 16 possible prognostic factors were evaluated for their association with overall survival (OS) and disease-free survival (DFS) using univariate and multivariate analysis. RESULTS: The median OS and DFS were 27.0 months and 8.2 months, respectively. OS rates for all patients at 1, 2, 3, 4 and 5 years were 73.9%, 52.1%, 42.8%, 26.2% and 20.1%, respectively. DFS rates at 1, 2, 3 and 4 years were 38.1%, 21.9%, 18.8%, and 14.1%, respectively. Pretreatment serum alpha-fetoprotein (AFP) >200 ng/ml, pretreatment serum albumin ≤35 g/dl, liver function Child's class C and incomplete ablation were found to be significant predictors for OS by univariate analysis. Using multivariate analysis, incomplete ablation was identified to be the most significant independent predictor for OS. Other independent predictors for OS were serum albumin level, serum AFP level and Child-Pugh classification. Recurrence after hepatectomy and prothrombin time >14 s were identified to be significant predictors for DFS by univariate analysis, and the former was the only independent predictor for DFS by multivariate analysis. CONCLUSION: Prognosis for patients with HCC after thermal ablation with curative intent was determined by treatment response to ablation, pretreatment serum AFP, and liver function reserve. Tumour response to treatment was the most predictive factor for long-term survival and was related to tumour size, thus careful selection of patients for ablation therapy is recommended

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification.

Science.gov (United States)

Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing.

Prognostic factors in children and adolescents with acute myeloid leukemia (excluding children with Down syndrome and acute promyelocytic leukemia): univariate and recursive partitioning analysis of patients treated on Pediatric Oncology Group (POG) Study 8821.

Science.gov (United States)

Chang, M; Raimondi, S C; Ravindranath, Y; Carroll, A J; Camitta, B; Gresik, M V; Steuber, C P; Weinstein, H

2000-07-01

The purpose of the paper was to define clinical or biological features associated with the risk for treatment failure for children with acute myeloid leukemia. Data from 560 children and adolescents with newly diagnosed acute myeloid leukemia who entered the Pediatric Oncology Group Study 8821 from June 1988 to March 1993 were analyzed by univariate and recursive partitioning methods. Children with Down syndrome or acute promyelocytic leukemia were excluded from the study. Factors examined included age, number of leukocytes, sex, FAB morphologic subtype, cytogenetic findings, and extramedullary disease at the time of diagnosis. The overall event-free survival (EFS) rate at 4 years was 32.7% (s.e. = 2.2%). Age > or =2 years, fewer than 50 x 10(9)/I leukocytes, and t(8;21) or inv(16), and normal chromosomes were associated with higher rates of EFS (P value = 0.003, 0.049, 0.0003, 0.031, respectively), whereas the M5 subtype of AML (P value = 0.0003) and chromosome abnormalities other than t(8;21) and inv(16) were associated with lower rates of EFS (P value = 0.0001). Recursive partitioning analysis defined three groups of patients with widely varied prognoses: female patients with t(8;21), inv(16), or a normal karyotype (n = 89) had the best prognosis (4-year EFS = 55.1%, s.e. = 5.7%); male patients with t(8;21), inv(16) or normal chromosomes (n = 106) had an intermediate prognosis (4-year EFS = 38.1%, s.e. = 5.3%); patients with chromosome abnormalities other than t(8;21) and inv(16) (n = 233) had the worst prognosis (4-year EFS = 27.0%, s.e. = 3.2%). One hundred and thirty-two patients (24%) could not be grouped because of missing cytogenetic data, mainly due to inadequate marrow samples. The results suggest that pediatric patients with acute myeloid leukemia can be categorized into three potential risk groups for prognosis and that differences in sex and chromosomal abnormalities are associated with differences in estimates of EFS. These results are tentative and

High serum folate is associated with reduced biochemical recurrence after radical prostatectomy: Results from the SEARCH Database

Directory of Open Access Journals (Sweden)

Daniel M. Moreira

2013-06-01

Full Text Available Introduction To analyze the association between serum levels of folate and risk of biochemical recurrence after radical prostatectomy among men from the Shared Equal Access Regional Cancer Hospital (SEARCH database. Materials and Methods Retrospective analysis of 135 subjects from the SEARCH database treated between 1991-2009 with available preoperative serum folate levels. Patients' characteristics at the time of the surgery were analyzed with ranksum and linear regression. Uni- and multivariable analyses of folate levels (log-transformed and time to biochemical recurrence were performed with Cox proportional hazards. Results The median preoperative folate level was 11.6ng/mL (reference = 1.5-20.0ng/mL. Folate levels were significantly lower among African-American men than Caucasians (P = 0.003. In univariable analysis, higher folate levels were associated with more recent year of surgery (P < 0.001 and lower preoperative PSA (P = 0.003. In univariable analysis, there was a trend towards lower risk of biochemical recurrence among men with high folate levels (HR = 0.61, 95%CI = 0.37-1.03, P = 0.064. After adjustments for patients characteristics' and pre- and post-operative clinical and pathological findings, higher serum levels of folate were independently associated with lower risk for biochemical recurrence (HR = 0.42, 95%CI = 0.20-0.89, P = 0.023. Conclusion In a cohort of men undergoing radical prostatectomy at several VAs across the country, higher serum folate levels were associated with lower PSA and lower risk for biochemical failure. While the source of the folate in the serum in this study is unknown (i.e. diet vs. supplement, these findings, if confirmed, suggest a potential role of folic acid supplementation or increased consumption of folate rich foods to reduce the risk of recurrence.

Prevalence and risk factors associated with dry eye syndrome among senior high school students in a county of Shandong Province, China.

Science.gov (United States)

Zhang, Ying; Chen, Hongmei; Wu, Xinyi

2012-08-01

To determine the prevalence and risk factors for dry eye syndrome (DES) among senior high school students in Shouguang, a county of Shandong Province, China. A cross-sectional survey was conducted in July 2010, and 1902 senior high school students were selected by multi-stage sampling to answer a questionnaire assessing the prevalence and risk factors for DES. DES was defined as the presence of a previous clinical diagnosis of DES or severe symptoms (both dryness and irritation constantly or often). Risk factors associated with DES were evaluated with a χ(2) test and logistic regression analyses. The prevalence of DES was 23.7%. In univariate analysis, myopia (P sleep quality (P = 0.007) were significantly associated with DES. In multivariate analysis, inadequate refractive correction (P sleep quality (P = 0.001, OR 1.342; 95% CI 1.054-1.709) were significant risk factors for DES. Senior high school students are a neglected population with a high prevalence of DES. Preventive measures directed against risks factors for DES among senior high school students may help reduce the prevalence and provide a positive impact on students' health.

Longitudinal categorical data analysis

CERN Document Server

Sutradhar, Brajendra C

2014-01-01

This is the first book in longitudinal categorical data analysis with parametric correlation models developed based on dynamic relationships among repeated categorical responses. This book is a natural generalization of the longitudinal binary data analysis to the multinomial data setup with more than two categories. Thus, unlike the existing books on cross-sectional categorical data analysis using log linear models, this book uses multinomial probability models both in cross-sectional and longitudinal setups. A theoretical foundation is provided for the analysis of univariate multinomial responses, by developing models systematically for the cases with no covariates as well as categorical covariates, both in cross-sectional and longitudinal setups. In the longitudinal setup, both stationary and non-stationary covariates are considered. These models have also been extended to the bivariate multinomial setup along with suitable covariates. For the inferences, the book uses the generalized quasi-likelihood as w...

Ultra-high Performance Liquid Chromatography in Steroid Analysis

OpenAIRE

Salonen, Fanny

2017-01-01

The latest version of liquid chromatography is ultra-high performance (or pressure) chromatography (UHPLC). In the technique, short and narrow-bore columns with particle sizes below 3 µm are used. The extremely high pressure used results in very short analysis times, excellent separation, and good resolution. This makes UHPLC a good choice for steroidal analysis. Steroids are a highly interesting area of study; they can be recognized as biomarkers for several diseases and are a relevant topic...

Analysis of Factors Related to Hypopituitarism in Patients with Nonsellar Intracranial Tumor.

Science.gov (United States)

Lu, Song-Song; Gu, Jian-Jun; Luo, Xiao-Hong; Zhang, Jian-He; Wang, Shou-Sen

2017-09-01

Previous studies have suggested that postoperative hypopituitarism in patients with nonsellar intracranial tumors is caused by traumatic surgery. However, with development of minimally invasive and precise neurosurgical techniques, the degree of injury to brain tissue has been reduced significantly, especially for parenchymal tumors. Therefore, understanding preexisting hypopituitarism and related risk factors can improve perioperative management for patients with nonsellar intracranial tumors. Chart data were collected retrospectively from 83 patients with nonsellar intracranial tumors admitted to our hospital from May 2014 to April 2015. Pituitary function of each subject was determined based on results of preoperative serum pituitary hormone analysis. Univariate and multivariate logistic regression methods were used to analyze relationships between preoperative hypopituitarism and factors including age, sex, history of hypertension and secondary epilepsy, course of disease, tumor mass effect, site of tumor, intracranial pressure (ICP), cerebrospinal fluid content, and pituitary morphology. A total of 30 patients (36.14%) presented with preoperative hypopituitarism in either 1 axis or multiple axes; 23 (27.71%) were affected in 1 axis, and 7 (8.43%) were affected in multiple axes. Univariate analysis showed that risk factors for preoperative hypopituitarism in patients with a nonsellar intracranial tumor include an acute or subacute course (≤3 months), intracranial hypertension (ICP >200 mm H 2 O), and mass effect (P hypopituitarism in patients with nonsellar intracranial tumors (P hypopituitarism is high in patients with nonsellar intracranial tumors. The occurrence of hypopituitarism is correlated with factors including an acute or subacute course (≤3 months), intracranial hypertension (ICP >200 mm H 2 O), and mass effect (P hypopituitarism. Copyright © 2017 Elsevier Inc. All rights reserved.

High priority tank sampling and analysis report

International Nuclear Information System (INIS)

Brown, T.M.

1998-01-01

In July 1993, the Defense Nuclear Facilities Board issued Recommendation 93-5 (Conway 1993) which noted that there was insufficient tank waste technical information and the pace to obtain it was too slow to ensure that Hanford Site wastes could be safely stored, that associated operations could be conducted safely, and that future disposal data requirements could be met. In response, the US Department of Energy, in May 1996, issued Revision 1 of the Recommendation 93-5 Implementation Plan (DOE-RL 1996). The Implementation Plan presented a modified approach to achieve the original plan's objectives, concentrating on actions necessary to ensure that wastes can be safely stored, that operations can be safely conducted, and that timely characterization information for the tank waste Disposal Program could be obtained. The Implementation Plan proposed 28 High Priority tanks for near term core sampling and analysis, which along with sampling and analysis of other non-High Priority tanks, could provide the scientific and technical data to confirm assumptions, calibrate models, and.measure safety related phenomenology of the waste. When the analysis results of the High Priority and other-tank sampling were reviewed, it was expected that a series of 12 questions, 9 related to safety issues and 3 related to planning for the disposal process, should be answered allowing key decisions to be made. This report discusses the execution of the Implementation Plan and the results achieved in addressing the questions. Through sampling and analysis, all nine safety related questions have been answered and extensive data for the three disposal planning related questions have been collected, allowing for key decision making. Many more tanks than the original 28 High Priority tanks identified in the Implementation Plan were sampled and analyzed. Twenty-one High Priority tanks and 85 other tanks were core sampled and used to address the questions. Thirty-eight additional tanks were auger

Analysis of high burnup fuel safety issues

Energy Technology Data Exchange (ETDEWEB)

Lee, Chan Bock; Kim, D. H.; Bang, J. G.; Kim, Y. M.; Yang, Y. S.; Jung, Y. H.; Jeong, Y. H.; Nam, C.; Baik, J. H.; Song, K. W.; Kim, K. S

2000-12-01

Safety issues in steady state and transient behavior of high burnup LWR fuel above 50 - 60 MWD/kgU were analyzed. Effects of burnup extension upon fuel performance parameters was reviewed, and validity of both the fuel safety criteria and the performance analysis models which were based upon the lower burnup fuel test results was analyzed. It was found that further tests would be necessary in such areas as fuel failure and dispersion for RIA, and high temperature cladding corrosion and mechanical deformation for LOCA. Since domestic fuels have been irradiated in PWR up to burnup higher than 55 MWD/kgU-rod. avg., it can be said that Korea is in the same situation as the other countries in the high burnup fuel safety issues. Therefore, necessary research areas to be performed in Korea were derived. Considering that post-irradiation examination(PIE) for the domestic fuel of burnup higher than 30 MWD/kgU has not been done so far at all, it is primarily necessary to perform PIE for high burnup fuel, and then simulation tests for RIA and LOCA could be performed by using high burnup fuel specimens. For the areas which can not be performed in Korea, international cooperation will be helpful to obtain the test results. With those data base, safety of high burnup domestic fuels will be confirmed, current fuel safety criteria will be re-evaluated, and finally transient high burnup fuel behavior analysis technology will be developed through the fuel performance analysis code development.

Analysis of high burnup fuel safety issues

International Nuclear Information System (INIS)

Lee, Chan Bock; Kim, D. H.; Bang, J. G.; Kim, Y. M.; Yang, Y. S.; Jung, Y. H.; Jeong, Y. H.; Nam, C.; Baik, J. H.; Song, K. W.; Kim, K. S

2000-12-01

Safety issues in steady state and transient behavior of high burnup LWR fuel above 50 - 60 MWD/kgU were analyzed. Effects of burnup extension upon fuel performance parameters was reviewed, and validity of both the fuel safety criteria and the performance analysis models which were based upon the lower burnup fuel test results was analyzed. It was found that further tests would be necessary in such areas as fuel failure and dispersion for RIA, and high temperature cladding corrosion and mechanical deformation for LOCA. Since domestic fuels have been irradiated in PWR up to burnup higher than 55 MWD/kgU-rod. avg., it can be said that Korea is in the same situation as the other countries in the high burnup fuel safety issues. Therefore, necessary research areas to be performed in Korea were derived. Considering that post-irradiation examination(PIE) for the domestic fuel of burnup higher than 30 MWD/kgU has not been done so far at all, it is primarily necessary to perform PIE for high burnup fuel, and then simulation tests for RIA and LOCA could be performed by using high burnup fuel specimens. For the areas which can not be performed in Korea, international cooperation will be helpful to obtain the test results. With those data base, safety of high burnup domestic fuels will be confirmed, current fuel safety criteria will be re-evaluated, and finally transient high burnup fuel behavior analysis technology will be developed through the fuel performance analysis code development

An analysis of predictors of enrollment and successful achievement for girls in high school Advanced Placement physics

Science.gov (United States)

Depalma, Darlene M.

A problem within science education in the United States persists. U.S students rank lower in science than most other students from participating countries on international tests of achievement (National Center for Education Statistics, 2003). In addition, U.S. students overall enrollment rate in high school Advanced Placement (AP) physics is still low compared to other academic domains, especially for females. This problem is the background for the purpose of this study. This investigation examined cognitive and motivational variables thought to play a part in the under-representation of females in AP physics. Cognitive variables consisted of mathematics, reading, and science knowledge, as measured by scores on the 10th and 11th grade Florida Comprehensive Assessment Tests (FCAT). The motivational factors of attitude, stereotypical views toward science, self-efficacy, and epistemological beliefs were measured by a questionnaire developed with questions taken from previously proven reliable and valid instruments. A general survey regarding participation in extracurricular activities was also included. The sample included 12th grade students from two high schools located in Seminole County, Florida. Of the 106 participants, 20 girls and 27 boys were enrolled in AP physics, and 39 girls and 20 boys were enrolled in other elective science courses. Differences between males and females enrolled in AP physics were examined, as well as differences between females enrolled in AP physics and females that chose not to participate in AP physics, in order to determine predictors that apply exclusively to female enrollment in high school AP physics and predictors of an anticipated science related college major. Data were first analyzed by Exploratory Factor Analysis, followed by Analysis of Variance (ANOVA), independent t-tests, univariate analysis, and logistic regression analysis. One overall theme that emerged from this research was findings that refute the ideas that

Prevalence of gestational diabetes mellitus in Europe: A meta-analysis.

Science.gov (United States)

Eades, Claire E; Cameron, Dawn M; Evans, Josie M M

2017-07-01

Estimates of the prevalence of gestational diabetes vary widely. It is important to have a clear understanding of the prevalence of this condition to be able to plan interventions and health care provision. This paper describes a meta-analysis of primary research data reporting the prevalence of gestational diabetes mellitus in the general pregnant population of developed countries in Europe. Four electronic databases were systematically searched in May 2016. English language articles reporting gestational diabetes mellitus prevalence using universal screening in general pregnant population samples from developed countries in Europe were included. All papers identified by the search were screened by one author, and then half screened independently by a second author and half by a third author. Data were extracted by one author. Values for the measures of interest were combined using a random effects model and analysis of the effects of moderator variables was carried out. A total of 3258 abstracts were screened, with 40 studies included in the review. Overall prevalence of gestational diabetes mellitus was 5.4% (3.8-7.8). Maternal age, year of data collection, country, area of Europe, week of gestation at testing, and diagnostic criteria were found to have a significant univariate effect on GDM prevalence, and area, week of gestation at testing and year of data collection remained statistically significant in multivariate analysis. Quality category was significant in multivariate but not univariate analysis. This meta-analysis shows prevalence of GDM that is at the upper end of previous estimates in Europe. Copyright © 2017 Elsevier B.V. All rights reserved.

Clinical analysis of urinary tract infection in patients undergoing transurethral resection of the prostate.

Science.gov (United States)

Li, Y-H; Li, G-Q; Guo, S-M; Che, Y-N; Wang, X; Cheng, F-T

2017-10-01

To analyze the related influencing factors of urinary tract infection in patients undergoing transurethral resection of the prostate (TURP). A total of 343 patients with benign prostatic hyperplasia admitted to this hospital from January 2013 to December 2016, were selected and treated by TURP. Patients were divided into infection group and non-infection group according to the occurrence of urinary tract infection after operation. The possible influencing factors were collected to perform univariate and multivariate logistic regression analysis. There were 53 cases with urinary tract infection after operation among 343 patients with benign prostatic hyperplasia, accounting for 15.5%. The univariate analysis displayed that the occurrence of urinary tract infection in patients undergoing TURP was closely associated with patient's age ≥ 65 years old, complicated diabetes, catheterization for urinary retention before operation, no use of antibiotics before operation and postoperative indwelling catheter duration ≥ 5 d (p urinary tract infection in patients receiving TURP (p urinary tract infection after TURP, while preoperative prophylactic utilization of anti-infective drugs can reduce the occurrence of postoperative urinary tract infection.

Handbook of Time Series Analysis Recent Theoretical Developments and Applications

CERN Document Server

Schelter, Björn; Timmer, Jens

2006-01-01

This handbook provides an up-to-date survey of current research topics and applications of time series analysis methods written by leading experts in their fields. It covers recent developments in univariate as well as bivariate and multivariate time series analysis techniques ranging from physics' to life sciences' applications. Each chapter comprises both methodological aspects and applications to real world complex systems, such as the human brain or Earth's climate. Covering an exceptionally broad spectrum of topics, beginners, experts and practitioners who seek to understand the latest de

Neutron activation analysis of high purity substances

International Nuclear Information System (INIS)

Gil'bert, Eh.N.

1987-01-01

Peculiarities of neutron-activation analysis (NAA) of high purity substances are considered. Simultaneous determination of a wide series of elements, high sensitivity (the lower bound of determined contents 10 -9 -10 -10 %), high selectivity and accuracy (Sr=0.10-0.15, and may be decreased up to 0.001), possibility of analysis of the samples from several micrograms to hundreds of grams, simplicity of calibration may be thought NAA advantages. Questions of accounting of NAA systematic errors associated with the neutron flux screening by the analysed matrix and with production of radionuclides of determined elements from accompanying elements according to concurrent nuclear reactions, as well as accounting of errors due to self-absorption of recorded radiation by compact samples, are considered

Kernel based methods for accelerated failure time model with ultra-high dimensional data

Directory of Open Access Journals (Sweden)

Jiang Feng

2010-12-01

Full Text Available Abstract Background Most genomic data have ultra-high dimensions with more than 10,000 genes (probes. Regularization methods with L1 and Lp penalty have been extensively studied in survival analysis with high-dimensional genomic data. However, when the sample size n ≪ m (the number of genes, directly identifying a small subset of genes from ultra-high (m > 10, 000 dimensional data is time-consuming and not computationally efficient. In current microarray analysis, what people really do is select a couple of thousands (or hundreds of genes using univariate analysis or statistical tests, and then apply the LASSO-type penalty to further reduce the number of disease associated genes. This two-step procedure may introduce bias and inaccuracy and lead us to miss biologically important genes. Results The accelerated failure time (AFT model is a linear regression model and a useful alternative to the Cox model for survival analysis. In this paper, we propose a nonlinear kernel based AFT model and an efficient variable selection method with adaptive kernel ridge regression. Our proposed variable selection method is based on the kernel matrix and dual problem with a much smaller n × n matrix. It is very efficient when the number of unknown variables (genes is much larger than the number of samples. Moreover, the primal variables are explicitly updated and the sparsity in the solution is exploited. Conclusions Our proposed methods can simultaneously identify survival associated prognostic factors and predict survival outcomes with ultra-high dimensional genomic data. We have demonstrated the performance of our methods with both simulation and real data. The proposed method performs superbly with limited computational studies.

High-capacity neutron activation analysis facility

International Nuclear Information System (INIS)

Hochel, R.C.

1979-01-01

A high-capacity neutron activation analysis facility, the Reactor Activation Facility, was designed and built and has been in operation for about a year at one of the Savannah River Plant's production reactors. The facility determines uranium and about 19 other trace elements in hydrogeochemical samples collected in the National Uranium Resource Evaluation program. The facility has a demonstrated average analysis rate of over 10,000 samples per month, and a peak rate of over 16,000 samples per month. Uranium is determined by cyclic activation and delayed neutron counting of the U-235 fission products; other elements are determined from gamma-ray spectra recorded in subsequent irradiation, decay, and counting steps. The method relies on the absolute activation technique and is highly automated for round-the-clock unattended operation

Analysis strategies for high-resolution UHF-fMRI data.

Science.gov (United States)

Polimeni, Jonathan R; Renvall, Ville; Zaretskaya, Natalia; Fischl, Bruce

2018-03-01

Functional MRI (fMRI) benefits from both increased sensitivity and specificity with increasing magnetic field strength, making it a key application for Ultra-High Field (UHF) MRI scanners. Most UHF-fMRI studies utilize the dramatic increases in sensitivity and specificity to acquire high-resolution data reaching sub-millimeter scales, which enable new classes of experiments to probe the functional organization of the human brain. This review article surveys advanced data analysis strategies developed for high-resolution fMRI at UHF. These include strategies designed to mitigate distortion and artifacts associated with higher fields in ways that attempt to preserve spatial resolution of the fMRI data, as well as recently introduced analysis techniques that are enabled by these extremely high-resolution data. Particular focus is placed on anatomically-informed analyses, including cortical surface-based analysis, which are powerful techniques that can guide each step of the analysis from preprocessing to statistical analysis to interpretation and visualization. New intracortical analysis techniques for laminar and columnar fMRI are also reviewed and discussed. Prospects for single-subject individualized analyses are also presented and discussed. Altogether, there are both specific challenges and opportunities presented by UHF-fMRI, and the use of proper analysis strategies can help these valuable data reach their full potential. Copyright © 2017 Elsevier Inc. All rights reserved.

Genetic and environmental dissections of sub-phenotypes of metabolic syndrome in the chinese population: a twin-based heritability study

DEFF Research Database (Denmark)

Duan, Haiping; Pang, Zengchang; Zhang, Dongfeng

2011-01-01

contains 654 twins collected in the Qingdao municipality. A total of 10 phenotypes covering anthropometric measurements, plasma glucose levels, lipids, blood pressures etc. were examined. Univariate and bivariate structural equation models were fitted for assessing the genetic and environmental...... contributions. Results: The AE model combining additive genetic (A) and unique environmental (E) factors produced the best fit for all phenotypes except for triglyceride. Modest to high heritability estimates were obtained in univariate analysis ranging from 0.5 for total cholesterol to 0.78 for weight...

Metabolomic differentiation of maca (Lepidium meyenii) accessions cultivated under different conditions using NMR and chemometric analysis.

Science.gov (United States)

Zhao, Jianping; Avula, Bharathi; Chan, Michael; Clément, Céline; Kreuzer, Michael; Khan, Ikhlas A

2012-01-01

To gain insights on the effects of color type, cultivation history, and growing site on the composition alterations of maca (Lepidium meyenii Walpers) hypocotyls, NMR profiling combined with chemometric analysis was applied to investigate the metabolite variability in different maca accessions. Maca hypocotyls with different colors (yellow, pink, violet, and lead-colored) cultivated at different geographic sites and different areas were examined for differences in metabolite expression. Differentiations of the maca accessions grown under the different cultivation conditions were determined by principle component analyses (PCAs) which were performed on the datasets derived from their ¹H NMR spectra. A total of 16 metabolites were identified by NMR analysis, and the changes in metabolite levels in relation to the color types and growing conditions of maca hypocotyls were evaluated using univariate statistical analysis. In addition, the changes of the correlation pattern among the metabolites identified in the maca accessions planted at the two different sites were examined. The results from both multivariate and univariate analysis indicated that the planting site was the major determining factor with regards to metabolite variations in maca hypocotyls, while the color of maca accession seems to be of minor importance in this respect. © Georg Thieme Verlag KG Stuttgart · New York.

Multivariate survival analysis and competing risks

CERN Document Server

Crowder, Martin J

2012-01-01

Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate data and distributions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametric methods. There are many books covering survival analysis, but very few that cover the multivariate case in any depth. Written for a graduate-level audience in statistics/biostatistics, this book includes practical exercises and R code for the examples. The author is renowned for his clear writing style, and this book continues that trend. It is an excellent reference for graduate students and researchers looking for grounding in this burgeoning field of research.

Outcome predictors in the management of intramedullary classic ependymoma: An integrative survival analysis.

Science.gov (United States)

Wang, Yinqing; Cai, Ranze; Wang, Rui; Wang, Chunhua; Chen, Chunmei

2018-06-01

This is a retrospective study.The aim of this study was to illustrate the survival outcomes of patients with classic ependymoma (CE) and identify potential prognostic factors.CE is the most common category of spinal ependymomas, but few published studies have discussed predictors of the survival outcome.A Boolean search of the PubMed, Embase, and OVID databases was conducted by 2 investigators independently. The objects were intramedullary grade II ependymoma according to 2007 WHO classification. Univariate Kaplan-Meier analysis and Log-Rank tests were performed to identify variables associated with progression-free survival (PFS) or overall survival (OS). Multivariate Cox regression was performed to assess hazard ratios (HRs) with 95% confidence intervals (95% CIs). Statistical analysis was performed by SPSS version 23.0 (IBM Corp.) with statistical significance defined as P analysis showed that patients who had undergone total resection (TR) had better PFS and OS than those with subtotal resection (STR) and biopsy (P = .002, P = .004, respectively). Within either univariate or multivariate analysis (P = .000, P = .07, respectively), histological type was an independent prognostic factor for PFS of CE [papillary type: HR 0.002, 95% CI (0.000-0.073), P = .001, tanycytic type: HR 0.010, 95% CI (0.000-0.218), P = .003].It was the first integrative analysis of CE to elucidate the correlation between kinds of factors and prognostic outcomes. Definite histological type and safely TR were foundation of CE's management. 4.

Recent advances in quantitative high throughput and high content data analysis.

Science.gov (United States)

Moutsatsos, Ioannis K; Parker, Christian N

2016-01-01

High throughput screening has become a basic technique with which to explore biological systems. Advances in technology, including increased screening capacity, as well as methods that generate multiparametric readouts, are driving the need for improvements in the analysis of data sets derived from such screens. This article covers the recent advances in the analysis of high throughput screening data sets from arrayed samples, as well as the recent advances in the analysis of cell-by-cell data sets derived from image or flow cytometry application. Screening multiple genomic reagents targeting any given gene creates additional challenges and so methods that prioritize individual gene targets have been developed. The article reviews many of the open source data analysis methods that are now available and which are helping to define a consensus on the best practices to use when analyzing screening data. As data sets become larger, and more complex, the need for easily accessible data analysis tools will continue to grow. The presentation of such complex data sets, to facilitate quality control monitoring and interpretation of the results will require the development of novel visualizations. In addition, advanced statistical and machine learning algorithms that can help identify patterns, correlations and the best features in massive data sets will be required. The ease of use for these tools will be important, as they will need to be used iteratively by laboratory scientists to improve the outcomes of complex analyses.

Sensitivity Analysis of Corrosion Rate Prediction Models Utilized for Reinforced Concrete Affected by Chloride

Science.gov (United States)

Siamphukdee, Kanjana; Collins, Frank; Zou, Roger

2013-06-01

Chloride-induced reinforcement corrosion is one of the major causes of premature deterioration in reinforced concrete (RC) structures. Given the high maintenance and replacement costs, accurate modeling of RC deterioration is indispensable for ensuring the optimal allocation of limited economic resources. Since corrosion rate is one of the major factors influencing the rate of deterioration, many predictive models exist. However, because the existing models use very different sets of input parameters, the choice of model for RC deterioration is made difficult. Although the factors affecting corrosion rate are frequently reported in the literature, there is no published quantitative study on the sensitivity of predicted corrosion rate to the various input parameters. This paper presents the results of the sensitivity analysis of the input parameters for nine selected corrosion rate prediction models. Three different methods of analysis are used to determine and compare the sensitivity of corrosion rate to various input parameters: (i) univariate regression analysis, (ii) multivariate regression analysis, and (iii) sensitivity index. The results from the analysis have quantitatively verified that the corrosion rate of steel reinforcement bars in RC structures is highly sensitive to corrosion duration time, concrete resistivity, and concrete chloride content. These important findings establish that future empirical models for predicting corrosion rate of RC should carefully consider and incorporate these input parameters.

Data analysis in high-dimensional sparse spaces

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder

classification techniques for high-dimensional problems are presented: Sparse discriminant analysis, sparse mixture discriminant analysis and orthogonality constrained support vector machines. The first two introduces sparseness to the well known linear and mixture discriminant analysis and thereby provide low...... are applied to classifications of fish species, ear canal impressions used in the hearing aid industry, microbiological fungi species, and various cancerous tissues and healthy tissues. In addition, novel applications of sparse regressions (also called the elastic net) to the medical, concrete, and food...

Dynamical analysis of highly excited molecular spectra

Energy Technology Data Exchange (ETDEWEB)

Kellman, M.E. [Univ. of Oregon, Eugene (United States)

1993-12-01

The goal of this program is new methods for analysis of spectra and dynamics of highly excited vibrational states of molecules. In these systems, strong mode coupling and anharmonicity give rise to complicated classical dynamics, and make the simple normal modes analysis unsatisfactory. New methods of spectral analysis, pattern recognition, and assignment are sought using techniques of nonlinear dynamics including bifurcation theory, phase space classification, and quantization of phase space structures. The emphasis is chaotic systems and systems with many degrees of freedom.

Propensity score analysis of recurrence for neutrophil-to-lymphocyte ratio in colorectal cancer.

Science.gov (United States)

Balde, Alpha I; Fang, Suzhen; He, Linyun; Cai, Zhai; Han, Shuai; Wang, Weiwei; Li, Zhou; Kang, Liang

2017-11-01

The perioperative serum neutrophil-to-lymphocyte ratio (NLR) has been proposed to predict adverse prognosis in colorectal cancer (CRC). However, its interpretation remains unclear. The present study aimed to clarify the prognostic value of NLR in predicting survival among CRC patients. A single-centre, retrospective, propensity score-matched study of adenocarcinoma patients who underwent D3 lymphadenectomy via laparoscopic or open surgery between 2010 and 2016 was conducted. A cutoff of 3.5 was used based on the receiver operating characteristic curve. To overcome selection biases, we performed a 1:1 match using six covariates. The high-preoperative NLR group had a higher recurrence rate than the low group (P analysis showed that increased NLR (P analysis showed that N2 (hazard ratio [HR], 2.492; P = 0.008) was an adverse prognostic factor for RFS. Univariate analysis for overall survival (OS) revealed that high perioperative NLR (P = 0.001), N1 (P = 0.01), N2 (P analysis showed that M1 (HR, 3.973; P < 0.001) and N2 (HR, 2.381; P = 0.013) were highly adverse factors for OS. Clinical assessments performed during a 21.14 (±16.20)-mo follow-up revealed that OS (P = 0.001) and RFS (P < 0.001) were worse in the high-perioperative group than in the low group between the matched groups. An elevated preoperative NLR is a strong predictor of worse RFS and OS in CRC patients. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis and topology optimization design of high-speed driving spindle

Science.gov (United States)

Wang, Zhilin; Yang, Hai

2018-04-01

The three-dimensional model of high-speed driving spindle is established by using SOLIDWORKS. The model is imported through the interface of ABAQUS, A finite element analysis model of high-speed driving spindle was established by using spring element to simulate bearing boundary condition. High-speed driving spindle for the static analysis, the spindle of the stress, strain and displacement nephogram, and on the basis of the results of the analysis on spindle for topology optimization, completed the lightweight design of high-speed driving spindle. The design scheme provides guidance for the design of axial parts of similar structures.

High-capacity neutron activation analysis facility

International Nuclear Information System (INIS)

Hochel, R.C.; Bowman, W.W.; Zeh, C.W.

1980-01-01

A high-capacity neutron activation analysis facility, the Reactor Activation Facility, was designed and built and has been in operation for about a year at one of the Savannah River Plant's production reactors. The facility determines uranium and about 19 other elements in hydrogeochemical samples collected in the National Uranium Resource Evaluation program, which is sponsored and funded by the United States Department of Energy, Grand Junction Office. The facility has a demonstrated average analysis rate of over 10,000 samples per month, and a peak rate of over 16,000 samples per month. Uranium is determined by cyclic activation and delayed neutron counting of the U-235 fission products; other elements are determined from gamma-ray spectra recorded in subsequent irradiation, decay, and counting steps. The method relies on the absolute activation technique and is highly automated for round-the-clock unattended operation

High throughput on-chip analysis of high-energy charged particle tracks using lensfree imaging

Energy Technology Data Exchange (ETDEWEB)

Luo, Wei; Shabbir, Faizan; Gong, Chao; Gulec, Cagatay; Pigeon, Jeremy; Shaw, Jessica; Greenbaum, Alon; Tochitsky, Sergei; Joshi, Chandrashekhar [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Ozcan, Aydogan, E-mail: ozcan@ucla.edu [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Bioengineering Department, University of California, Los Angeles, California 90095 (United States); California NanoSystems Institute (CNSI), University of California, Los Angeles, California 90095 (United States)

2015-04-13

We demonstrate a high-throughput charged particle analysis platform, which is based on lensfree on-chip microscopy for rapid ion track analysis using allyl diglycol carbonate, i.e., CR-39 plastic polymer as the sensing medium. By adopting a wide-area opto-electronic image sensor together with a source-shifting based pixel super-resolution technique, a large CR-39 sample volume (i.e., 4 cm × 4 cm × 0.1 cm) can be imaged in less than 1 min using a compact lensfree on-chip microscope, which detects partially coherent in-line holograms of the ion tracks recorded within the CR-39 detector. After the image capture, using highly parallelized reconstruction and ion track analysis algorithms running on graphics processing units, we reconstruct and analyze the entire volume of a CR-39 detector within ∼1.5 min. This significant reduction in the entire imaging and ion track analysis time not only increases our throughput but also allows us to perform time-resolved analysis of the etching process to monitor and optimize the growth of ion tracks during etching. This computational lensfree imaging platform can provide a much higher throughput and more cost-effective alternative to traditional lens-based scanning optical microscopes for ion track analysis using CR-39 and other passive high energy particle detectors.

Visualization and Data Analysis for High-Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Sewell, Christopher Meyer [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-09-27

This is a set of slides from a guest lecture for a class at the University of Texas, El Paso on visualization and data analysis for high-performance computing. The topics covered are the following: trends in high-performance computing; scientific visualization, such as OpenGL, ray tracing and volume rendering, VTK, and ParaView; data science at scale, such as in-situ visualization, image databases, distributed memory parallelism, shared memory parallelism, VTK-m, "big data", and then an analysis example.

Prognostic and survival analysis of 837 Chinese colorectal cancer patients.

Science.gov (United States)

Yuan, Ying; Li, Mo-Dan; Hu, Han-Guang; Dong, Cai-Xia; Chen, Jia-Qi; Li, Xiao-Fen; Li, Jing-Jing; Shen, Hong

2013-05-07

To develop a prognostic model to predict survival of patients with colorectal cancer (CRC). Survival data of 837 CRC patients undergoing surgery between 1996 and 2006 were collected and analyzed by univariate analysis and Cox proportional hazard regression model to reveal the prognostic factors for CRC. All data were recorded using a standard data form and analyzed using SPSS version 18.0 (SPSS, Chicago, IL, United States). Survival curves were calculated by the Kaplan-Meier method. The log rank test was used to assess differences in survival. Univariate hazard ratios and significant and independent predictors of disease-specific survival and were identified by Cox proportional hazard analysis. The stepwise procedure was set to a threshold of 0.05. Statistical significance was defined as P analysis suggested age, preoperative obstruction, serum carcinoembryonic antigen level at diagnosis, status of resection, tumor size, histological grade, pathological type, lymphovascular invasion, invasion of adjacent organs, and tumor node metastasis (TNM) staging were positive prognostic factors (P analysis showed a significant statistical difference in 3-year survival among these groups: LNR1, 73%; LNR2, 55%; and LNR3, 42% (P analysis results showed that histological grade, depth of bowel wall invasion, and number of metastatic lymph nodes were the most important prognostic factors for CRC if we did not consider the interaction of the TNM staging system (P < 0.05). When the TNM staging was taken into account, histological grade lost its statistical significance, while the specific TNM staging system showed a statistically significant difference (P < 0.0001). The overall survival of CRC patients has improved between 1996 and 2006. LNR is a powerful factor for estimating the survival of stage III CRC patients.

High-Level Overview of Data Needs for RE Analysis

Energy Technology Data Exchange (ETDEWEB)

Lopez, Anthony

2016-12-22

This presentation provides a high level overview of analysis topics and associated data needs. Types of renewable energy analysis are grouped into two buckets: First, analysis for renewable energy potential, and second, analysis for other goals. Data requirements are similar but and they build upon one another.

Exact analysis of discrete data

CERN Document Server

Hirji, Karim F

2005-01-01

Researchers in fields ranging from biology and medicine to the social sciences, law, and economics regularly encounter variables that are discrete or categorical in nature. While there is no dearth of books on the analysis and interpretation of such data, these generally focus on large sample methods. When sample sizes are not large or the data are otherwise sparse, exact methods--methods not based on asymptotic theory--are more accurate and therefore preferable.This book introduces the statistical theory, analysis methods, and computation techniques for exact analysis of discrete data. After reviewing the relevant discrete distributions, the author develops the exact methods from the ground up in a conceptually integrated manner. The topics covered range from univariate discrete data analysis, a single and several 2 x 2 tables, a single and several 2 x K tables, incidence density and inverse sampling designs, unmatched and matched case -control studies, paired binary and trinomial response models, and Markov...

High temperature structure design for FBRs and analysis technology

International Nuclear Information System (INIS)

Iwata, Koji

1986-01-01

In the case of FBRs, the operation temperature exceeds 500 deg C, therefore, the design taking the inelastic characteristics of structural materials, such as plasticity and creep, into account is required, and the high grade and detailed evaluation of design is demanded. This new high temperature structure design technology has been advanced in respective countries taking up experimental, prototype and demonstration reactors as the targets. The development of FBRs in Japan was begun with the experimental reactor 'Joyo' which has been operated since 1977, and now, the prototype FBR 'Monju' of 280 MWe is under construction, which is expected to attain the criticality in 1992. In order to realize FBRs which can compete with LWRs through the construction of a demonstration FBR, the construction of large scale plants and the heightening of the economy and reliability are necessary. The features and the role of FBR structural design, the method of high temperature structure design and the trend of its standardization, the trend of the structural analysis technology for FBRs such as inelastic analysis, buckling analysis and fluid and structure coupled vibration analysis, the present status of structural analysis programs, and the subjects for the future of high temperature structure design are explained. (Kako, I.)

Improvement of the cost-benefit analysis algorithm for high-rise construction projects

Directory of Open Access Journals (Sweden)

Gafurov Andrey

2018-01-01

Full Text Available The specific nature of high-rise investment projects entailing long-term construction, high risks, etc. implies a need to improve the standard algorithm of cost-benefit analysis. An improved algorithm is described in the article. For development of the improved algorithm of cost-benefit analysis for high-rise construction projects, the following methods were used: weighted average cost of capital, dynamic cost-benefit analysis of investment projects, risk mapping, scenario analysis, sensitivity analysis of critical ratios, etc. This comprehensive approach helped to adapt the original algorithm to feasibility objectives in high-rise construction. The authors put together the algorithm of cost-benefit analysis for high-rise construction projects on the basis of risk mapping and sensitivity analysis of critical ratios. The suggested project risk management algorithms greatly expand the standard algorithm of cost-benefit analysis in investment projects, namely: the “Project analysis scenario” flowchart, improving quality and reliability of forecasting reports in investment projects; the main stages of cash flow adjustment based on risk mapping for better cost-benefit project analysis provided the broad range of risks in high-rise construction; analysis of dynamic cost-benefit values considering project sensitivity to crucial variables, improving flexibility in implementation of high-rise projects.

Improvement of the cost-benefit analysis algorithm for high-rise construction projects

Science.gov (United States)

Gafurov, Andrey; Skotarenko, Oksana; Plotnikov, Vladimir

2018-03-01

The specific nature of high-rise investment projects entailing long-term construction, high risks, etc. implies a need to improve the standard algorithm of cost-benefit analysis. An improved algorithm is described in the article. For development of the improved algorithm of cost-benefit analysis for high-rise construction projects, the following methods were used: weighted average cost of capital, dynamic cost-benefit analysis of investment projects, risk mapping, scenario analysis, sensitivity analysis of critical ratios, etc. This comprehensive approach helped to adapt the original algorithm to feasibility objectives in high-rise construction. The authors put together the algorithm of cost-benefit analysis for high-rise construction projects on the basis of risk mapping and sensitivity analysis of critical ratios. The suggested project risk management algorithms greatly expand the standard algorithm of cost-benefit analysis in investment projects, namely: the "Project analysis scenario" flowchart, improving quality and reliability of forecasting reports in investment projects; the main stages of cash flow adjustment based on risk mapping for better cost-benefit project analysis provided the broad range of risks in high-rise construction; analysis of dynamic cost-benefit values considering project sensitivity to crucial variables, improving flexibility in implementation of high-rise projects.

Impact of Dose to the Bladder Trigone on Long-Term Urinary Function After High-Dose Intensity Modulated Radiation Therapy for Localized Prostate Cancer

Energy Technology Data Exchange (ETDEWEB)

Ghadjar, Pirus; Zelefsky, Michael J.; Spratt, Daniel E. [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Munck af Rosenschöld, Per; Oh, Jung Hun; Hunt, Margie [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Kollmeier, Marisa [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Happersett, Laura; Yorke, Ellen; Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Jackson, Andrew, E-mail: jacksona@mskcc.org [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States)

2014-02-01

Purpose: To determine the potential association between genitourinary (GU) toxicity and planning dose–volume parameters for GU pelvic structures after high-dose intensity modulated radiation therapy in localized prostate cancer patients. Methods and Materials: A total of 268 patients who underwent intensity modulated radiation therapy to a prescribed dose of 86.4 Gy in 48 fractions during June 2004-December 2008 were evaluated with the International Prostate Symptom Score (IPSS) questionnaire. Dose–volume histograms of the whole bladder, bladder wall, urethra, and bladder trigone were analyzed. The primary endpoint for GU toxicity was an IPSS sum increase ≥10 points over baseline. Univariate and multivariate analyses were done by the Kaplan-Meier method and Cox proportional hazard models, respectively. Results: Median follow-up was 5 years (range, 3-7.7 years). Thirty-nine patients experienced an IPSS sum increase ≥10 during follow-up; 84% remained event free at 5 years. After univariate analysis, lower baseline IPSS sum (P=.006), the V90 of the trigone (P=.006), and the maximal dose to the trigone (P=.003) were significantly associated with an IPSS sum increase ≥10. After multivariate analysis, lower baseline IPSS sum (P=.009) and increased maximal dose to the trigone (P=.005) remained significantly associated. Seventy-two patients had both a lower baseline IPSS sum and a higher maximal dose to the trigone and were defined as high risk, and 68 patients had both a higher baseline IPSS sum and a lower maximal dose to the trigone and were defined as low risk for development of an IPSS sum increase ≥10. Twenty-one of 72 high-risk patients (29%) and 5 of 68 low-risk patients (7%) experienced an IPSS sum increase ≥10 (P=.001; odds ratio 5.19). Conclusions: The application of hot spots to the bladder trigone was significantly associated with relevant changes in IPSS during follow-up. Reduction of radiation dose to the lower bladder and specifically the

High expression of SDF-1 and VEGF is associated with poor prognosis in patients with synovial sarcomas.

Science.gov (United States)

Feng, Qi; Guo, Peng; Wang, Jin; Zhang, Xiaoyu; Yang, Hui-Chai; Feng, Jian-Gang

2018-03-01

Stromal cell-derived factor-1 (SDF-1) predicts poor clinical outcomes of certain types of cancer. Furthermore, vascular endothelial growth factor (VEGF) promotes the growth and metastasis of solid tumors. The aim of the present study was to examine the expression of SDF-1 and VEGF in patients with synovial sarcoma and to determine their expression is correlated with unfavorable outcomes. Levels of SDF-1 and VEGF proteins were evaluated in 54 patients with synovial sarcoma using immunohistochemical and immunofluorescence staining. Potential associations between the expression of SDF-1 and VEGF and various clinical parameters were analyzed using Pearson's χ 2 test and the Spearman-rho test. Additionally, univariate and multivariate Cox regression analyses were used to identify potential prognostic factors, and the Kaplan-Meier method was used to analyze the overall survival rates of patients. Low SDF-1 and VEGF expression was detected in 20.4% (11/54) and 22.2% (12/54) of patients with synovial sarcoma; moderate expression was detected in 35.2% (19/54) and 37.0% (20/54) of patients and high expression was detected in 44.4% (24 of 54) and 40.7% (22 of 54) of patients, respectively. Levels of SDF-1 and VEGF proteins were significantly associated with histological grade (P<0.05), metastasis (P<0.05) and American Joint Committee on Cancer staging (P<0.05). In addition, levels of SDF-1 and VEGF expression were positively correlated with each other (P<0.001). Univariate analysis also indicated that VEGF expression was associated with shorter overall survival rates in (P<0.05), whereas multivariate analysis demonstrated that SDF-1 expression was associated with shorter patient survival rates (P<0.05). Finally, both SDF-1 and VEGF expression were associated with various characteristics of synovial sarcoma. Therefore, SDF-1 expression may be a potential independent prognostic indicator in patients with synovial sarcomas.

Virological success after 12 and 24 months of antiretroviral therapy in sub-Saharan Africa: Comparing results of trials, cohorts and cross-sectional studies using a systematic review and meta-analysis.

Science.gov (United States)

Taieb, Fabien; Madec, Yoann; Cournil, Amandine; Delaporte, Eric

2017-01-01

UNAIDS recently defined the 90-90-90 target as a way to end the HIV epidemic. However, the proportion of virological success following antiretroviral therapy (ART) may not be as high as the anticipated 90%, and may in fact be highly heterogeneous. We aimed to describe the proportion of virological success in sub-Saharan Africa and to identify factors associated with the proportion of virological success. We performed a systematic review and meta-analysis focusing on the proportion of patients in sub-Saharan Africa who demonstrate virological success at 12 and 24 months since ART initiation, as well as at 6 and 36 months, where possible. Programme factors associated with the proportion of virological success were identified using meta-regression. Analyses were conducted using both on-treatment (OT) and intention-to-treat (ITT) approaches. Eighty-five articles were included in the meta-analysis, corresponding to 125 independent study populations. Using an on-treatment approach, the proportions (95% confidence interval (CI)) of virological success at 12 (n = 64) and at 24 (n = 32) months since ART initiation were 87.7% (81.3-91.0) and 83.7% (79.8-87.6), respectively. Univariate analysis indicated that the proportion of virological success was not different by study design. Multivariate analysis at 24 months showed that the proportion of virological success was significantly larger in studies conducted in public sector sites than in other sites (p = 0.045). Using an ITT approach, the proportions (95% CI) of virological success at 12 (n = 50) and at 24 (n = 20) months were 65.4% (61.8-69.1) and 56.8% (51.3-62.4), respectively. At 12 months, multivariate analysis showed that the proportion of success was significantly lower in cohort studies than in trials (63.0% vs. 71.1%; p = 0.017). At 24 months, univariate analysis demonstrated that the proportion of success was also lower in cohorts. Regardless of the time following ART initiation, and of the threshold, proportions

Teenager Attitude in Globalization Era in Senior High School in Yogyakarta

Directory of Open Access Journals (Sweden)

Surahma Asti Mulasari

2017-11-01

Full Text Available The students that come from outside of the city, stay alone without parental presence and direct supervision. The dynamic and variation of culture, rapid flow of information, and accessible information source contribute to increasing of the knowledge, attitude, and behavior of teenagers, either with the positive or negative tendency. The objective was assess teenager’s attitude in religion-based private high school in Yogyakarta used an analytic observational study with cross sectional design. The population and sample of this research were high school students in religion-based private school in Yogyakarta. The sample was selected by proportional stratified random sampling method. The results were analyzed using univariate and bivariate analysis. Bullying, truancy, school tardiness, dating, unwanted pregnancies, brawls/fights, gang students, poor manners, smoking, and pornography were the negative attitudes found in the subject of this research. About 45,3% of them had a bad attitude and 33,7% of them had a bad attitude. Several approaches for example, asking the commitment from a certain organization which concerns on mentoring and coaching of students, cooperation with student parents, and make the school environment more pleasant.

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

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Ahmadalipour, Ali; Rana, Arun; Moradkhani, Hamid; Sharma, Ashish

2017-04-01

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.

High resolution melting (HRM) analysis of DNA--its role and potential in food analysis.

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Druml, Barbara; Cichna-Markl, Margit

2014-09-01

DNA based methods play an increasing role in food safety control and food adulteration detection. Recent papers show that high resolution melting (HRM) analysis is an interesting approach. It involves amplification of the target of interest in the presence of a saturation dye by the polymerase chain reaction (PCR) and subsequent melting of the amplicons by gradually increasing the temperature. Since the melting profile depends on the GC content, length, sequence and strand complementarity of the product, HRM analysis is highly suitable for the detection of single-base variants and small insertions or deletions. The review gives an introduction into HRM analysis, covers important aspects in the development of an HRM analysis method and describes how HRM data are analysed and interpreted. Then we discuss the potential of HRM analysis based methods in food analysis, i.e. for the identification of closely related species and cultivars and the identification of pathogenic microorganisms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multiscale Thermo-Mechanical Design and Analysis of High Frequency and High Power Vacuum Electron Devices

Science.gov (United States)

Gamzina, Diana

Diana Gamzina March 2016 Mechanical and Aerospace Engineering Multiscale Thermo-Mechanical Design and Analysis of High Frequency and High Power Vacuum Electron Devices Abstract A methodology for performing thermo-mechanical design and analysis of high frequency and high average power vacuum electron devices is presented. This methodology results in a "first-pass" engineering design directly ready for manufacturing. The methodology includes establishment of thermal and mechanical boundary conditions, evaluation of convective film heat transfer coefficients, identification of material options, evaluation of temperature and stress field distributions, assessment of microscale effects on the stress state of the material, and fatigue analysis. The feature size of vacuum electron devices operating in the high frequency regime of 100 GHz to 1 THz is comparable to the microstructure of the materials employed for their fabrication. As a result, the thermo-mechanical performance of a device is affected by the local material microstructure. Such multiscale effects on the stress state are considered in the range of scales from about 10 microns up to a few millimeters. The design and analysis methodology is demonstrated on three separate microwave devices: a 95 GHz 10 kW cw sheet beam klystron, a 263 GHz 50 W long pulse wide-bandwidth sheet beam travelling wave tube, and a 346 GHz 1 W cw backward wave oscillator.

Pulmonary Toxicity in Stage III Non-Small Cell Lung Cancer Patients Treated With High-Dose (74 Gy) 3-Dimensional Conformal Thoracic Radiotherapy and Concurrent Chemotherapy Following Induction Chemotherapy: A Secondary Analysis of Cancer and Leukemia Group B (CALGB) Trial 30105

International Nuclear Information System (INIS)

Salama, Joseph K.; Stinchcombe, Thomas E.; Gu Lin; Wang Xiaofei; Morano, Karen; Bogart, Jeffrey A.; Crawford, Jeffrey C.; Socinski, Mark A.; Blackstock, A. William; Vokes, Everett E.

2011-01-01

Purpose: Cancer and Leukemia Group B (CALGB) 30105 tested two different concurrent chemoradiotherapy platforms with high-dose (74 Gy) three-dimensional conformal radiotherapy (3D-CRT) after two cycles of induction chemotherapy for Stage IIIA/IIIB non–small cell lung cancer (NSCLC) patients to determine if either could achieve a primary endpoint of >18-month median survival. Final results of 30105 demonstrated that induction carboplatin and gemcitabine and concurrent gemcitabine 3D-CRT was not feasible because of treatment-related toxicity. However, induction and concurrent carboplatin/paclitaxel with 74 Gy 3D-CRT had a median survival of 24 months, and is the basis for the experimental arm in CALGB 30610/RTOG 0617/N0628. We conducted a secondary analysis of all patients to determine predictors of treatment-related pulmonary toxicity. Methods and Materials: Patient, tumor, and treatment-related variables were analyzed to determine their relation with treatment-related pulmonary toxicity. Results: Older age, higher N stage, larger planning target volume (PTV)1, smaller total lung volume/PTV1 ratio, larger V20, and larger mean lung dose were associated with increasing pulmonary toxicity on univariate analysis. Multivariate analysis confirmed that V20 and nodal stage as well as treatment with concurrent gemcitabine were associated with treatment-related toxicity. A high-risk group comprising patients with N3 disease and V20 >38% was associated with 80% of Grades 3-5 pulmonary toxicity cases. Conclusions: Elevated V20 and N3 disease status are important predictors of treatment related pulmonary toxicity in patients treated with high-dose 3D-CRT and concurrent chemotherapy. Further studies may use these metrics in considering patients for these treatments.

Pulmonary Toxicity in Stage III Non-Small Cell Lung Cancer Patients Treated With High-Dose (74 Gy) 3-Dimensional Conformal Thoracic Radiotherapy and Concurrent Chemotherapy Following Induction Chemotherapy: A Secondary Analysis of Cancer and Leukemia Group B (CALGB) Trial 30105

Energy Technology Data Exchange (ETDEWEB)

Salama, Joseph K., E-mail: joseph.salama@duke.edu [Duke University Medical Center, Durham, NC (United States); Stinchcombe, Thomas E. [University of North Carolina at Chapel Hill, Chapel Hill, NC (United States); Gu Lin; Wang Xiaofei [CALGB Statistical Center, Duke University Medical Center, Durham, NC (United States); Morano, Karen [Quality Assurance Review Center, Lincoln, RI (United States); Bogart, Jeffrey A. [State University of New York Upstate Medical University, Syracuse, NY (United States); Crawford, Jeffrey C. [Duke University Medical Center, Durham, NC (United States); Socinski, Mark A. [University of North Carolina at Chapel Hill, Chapel Hill, NC (United States); Blackstock, A. William [Wake Forest University School of Medicine, Winston-Salem, NC (United States); Vokes, Everett E. [University of Chicago, Chicago, IL (United States)

2011-11-15

Purpose: Cancer and Leukemia Group B (CALGB) 30105 tested two different concurrent chemoradiotherapy platforms with high-dose (74 Gy) three-dimensional conformal radiotherapy (3D-CRT) after two cycles of induction chemotherapy for Stage IIIA/IIIB non-small cell lung cancer (NSCLC) patients to determine if either could achieve a primary endpoint of >18-month median survival. Final results of 30105 demonstrated that induction carboplatin and gemcitabine and concurrent gemcitabine 3D-CRT was not feasible because of treatment-related toxicity. However, induction and concurrent carboplatin/paclitaxel with 74 Gy 3D-CRT had a median survival of 24 months, and is the basis for the experimental arm in CALGB 30610/RTOG 0617/N0628. We conducted a secondary analysis of all patients to determine predictors of treatment-related pulmonary toxicity. Methods and Materials: Patient, tumor, and treatment-related variables were analyzed to determine their relation with treatment-related pulmonary toxicity. Results: Older age, higher N stage, larger planning target volume (PTV)1, smaller total lung volume/PTV1 ratio, larger V20, and larger mean lung dose were associated with increasing pulmonary toxicity on univariate analysis. Multivariate analysis confirmed that V20 and nodal stage as well as treatment with concurrent gemcitabine were associated with treatment-related toxicity. A high-risk group comprising patients with N3 disease and V20 >38% was associated with 80% of Grades 3-5 pulmonary toxicity cases. Conclusions: Elevated V20 and N3 disease status are important predictors of treatment related pulmonary toxicity in patients treated with high-dose 3D-CRT and concurrent chemotherapy. Further studies may use these metrics in considering patients for these treatments.

Can we avoid high levels of dose escalation for high-risk prostate cancer in the setting of androgen deprivation?

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Shakespeare, Thomas P; Wilcox, Shea W; Aherne, Noel J

2016-01-01

Both dose-escalated external beam radiotherapy (DE-EBRT) and androgen deprivation therapy (ADT) improve outcomes in patients with high-risk prostate cancer. However, there is little evidence specifically evaluating DE-EBRT for patients with high-risk prostate cancer receiving ADT, particularly for EBRT doses >74 Gy. We aimed to determine whether DE-EBRT >74 Gy improves outcomes for patients with high-risk prostate cancer receiving long-term ADT. Patients with high-risk prostate cancer were treated on an institutional protocol prescribing 3-6 months neoadjuvant ADT and DE-EBRT, followed by 2 years of adjuvant ADT. Between 2006 and 2012, EBRT doses were escalated from 74 Gy to 76 Gy and then to 78 Gy. We interrogated our electronic medical record to identify these patients and analyzed our results by comparing dose levels. In all, 479 patients were treated with a 68-month median follow-up. The 5-year biochemical disease-free survivals for the 74 Gy, 76 Gy, and 78 Gy groups were 87.8%, 86.9%, and 91.6%, respectively. The metastasis-free survivals were 95.5%, 94.5%, and 93.9%, respectively, and the prostate cancer-specific survivals were 100%, 94.4%, and 98.1%, respectively. Dose escalation had no impact on any outcome in either univariate or multivariate analysis. There was no benefit of DE-EBRT >74 Gy in our cohort of high-risk prostate patients treated with long-term ADT. As dose escalation has higher risks of radiotherapy-induced toxicity, it may be feasible to omit dose escalation beyond 74 Gy in this group of patients. Randomized studies evaluating dose escalation for high-risk patients receiving ADT should be considered.

Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis

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Till, Kevin; Jones, Ben L.; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B.

2016-01-01

Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; ptalent identification. PMID:27224653

Identifying Talent in Youth Sport: A Novel Methodology Using Higher-Dimensional Analysis.

Science.gov (United States)

Till, Kevin; Jones, Ben L; Cobley, Stephen; Morley, David; O'Hara, John; Chapman, Chris; Cooke, Carlton; Beggs, Clive B

2016-01-01

Prediction of adult performance from early age talent identification in sport remains difficult. Talent identification research has generally been performed using univariate analysis, which ignores multivariate relationships. To address this issue, this study used a novel higher-dimensional model to orthogonalize multivariate anthropometric and fitness data from junior rugby league players, with the aim of differentiating future career attainment. Anthropometric and fitness data from 257 Under-15 rugby league players was collected. Players were grouped retrospectively according to their future career attainment (i.e., amateur, academy, professional). Players were blindly and randomly divided into an exploratory (n = 165) and validation dataset (n = 92). The exploratory dataset was used to develop and optimize a novel higher-dimensional model, which combined singular value decomposition (SVD) with receiver operating characteristic analysis. Once optimized, the model was tested using the validation dataset. SVD analysis revealed 60 m sprint and agility 505 performance were the most influential characteristics in distinguishing future professional players from amateur and academy players. The exploratory dataset model was able to distinguish between future amateur and professional players with a high degree of accuracy (sensitivity = 85.7%, specificity = 71.1%; ptalent identification.

A high level of estrogen-stimulated proteins selects breast cancer patients treated with adjuvant endocrine therapy with good prognosis

DEFF Research Database (Denmark)

L H Weischenfeldt, Katrine; Kirkegaard, Tove; Rasmussen, Birgitte B

2017-01-01

, univariate and multivariate analysis revealed HR (95% CI) and p values for disease-free survival (DFS) of 2.00 (1.20-3.22), 0.008 and 1.70 (1.01-2.84), 0.04 and for the overall survival (OS) of 2.33 (1.19-4.57), 0.01 and 1.90 (0.97-3.79), 0.06, respectively. The high ER activity profile did not disclose......BACKGROUND: Adjuvant endocrine therapy has significantly improved survival of estrogen receptor α (ER)-positive breast cancer patients, but around 20% relapse within 10 years. High expression of ER-stimulated proteins like progesterone receptor (PR), Bcl-2 and insulin-like growth factor receptor I...... enrolled in BIG 1-98, a randomized phase-III clinical trial comparing adjuvant letrozole, tamoxifen or a sequence of the two drugs. Immunohistochemical staining for ER, HER-2, PR, Bcl-2 and IGF-IR was performed and determined by Allred scoring (ER, PR and Bcl-2) or HercepTest (HER-2 and IGF-IR). RESULTS...

High order depletion sensitivity analysis

International Nuclear Information System (INIS)

Naguib, K.; Adib, M.; Morcos, H.N.

2002-01-01

A high order depletion sensitivity method was applied to calculate the sensitivities of build-up of actinides in the irradiated fuel due to cross-section uncertainties. An iteration method based on Taylor series expansion was applied to construct stationary principle, from which all orders of perturbations were calculated. The irradiated EK-10 and MTR-20 fuels at their maximum burn-up of 25% and 65% respectively were considered for sensitivity analysis. The results of calculation show that, in case of EK-10 fuel (low burn-up), the first order sensitivity was found to be enough to perform an accuracy of 1%. While in case of MTR-20 (high burn-up) the fifth order was found to provide 3% accuracy. A computer code SENS was developed to provide the required calculations

High incidence of rickets in extremely low birth weight infants with severe parenteral nutrition-associated cholestasis and bronchopulmonary dysplasia.

Science.gov (United States)

Lee, Soon Min; Namgung, Ran; Park, Min Soo; Eun, Ho Sun; Park, Kook In; Lee, Chul

2012-12-01

Risk factors for rickets of prematurity have not been re-examined since introduction of high mineral formula, particularly in ELBW infants. We analyzed the incidence and the risk factors of rickets in extremely low birth weight (ELBW) infants. As a retrospective case-control study from 2004 to 2008, risk factors were analyzed in 24 patients with rickets versus 31 patients without. The frequency of rickets in ELBW infants was 24/55 (44%). Infants with rickets were diagnosed at 48.2 ± 16.1 days of age, and improved by 85.3 ± 25.3 days. By radiologic evaluation, 29% were grade 1 rickets, 58% grade 2 and 13% grade 3. In univariate analysis, infants with rickets had significantly higher incidence of patent ductus arteriosus, parenteral nutrition associated cholestasis (PNAC), severe PNAC and moderate/severe bronchopulmonary dysplasia (BPD). In multiple regression analysis, after adjustment for gestation and birth weight, rickets significantly correlated with severe PNAC and with moderate/severe BPD. Serum peak alkaline phosphatase levels were significantly elevated in rickets (P rickets of prematurity remains high and the incidence of severe PNAC and moderate/severe BPD was significantly increased 18 and 3 times, respectively.

Nested case-control study on the risk of nasopharyngeal carcinoma in the high background radiation areas of Yangjiang, China

International Nuclear Information System (INIS)

Zou Jianming; Sun Quanfu; Yuan Yongling

2003-01-01

Objective: To identify the major determinants of nasopharyngeal carcinoma (NPC) in the high-background radiation areas (HBRA) in Yangjiang, China. Methods: A nested case-control study was conducted based on 106517 subjects. 98 cases that died of NPC were detected during a follow-up program for 9 years. Univariate analysis and multivariate non-conditional logistic regression were used to analyze associations between the exposure factors and NPC. Results: Multivariate conditional logistic regression analysis revealed that education levels, salted fish intake, the history of chronic rhinitis and the family history of NPC were independent risk factors of NPC. Tobacco smoking and alcohol consumption were not significantly related to NPC risk. The ORs of NPC risk comparing HBRA and a nearby control area before and after adjustment for the major risk determinants identified in the present study was 0.86 and 0.87, respectively. Conclusion: Salted fish intake was a strong risk factor of NPC. Education, the history of chronic rhinitis and the family history of NPC were also related to NPC risk. The exposure to high background radiation in HBRA of Yangjiang was not related to NPC risk with or without the adjustment for those major risk determinants of NPC

Clinical analysis of post-irradiation sensorineural hearing loss in patients suffering from nasopharyngeal carcinoma

International Nuclear Information System (INIS)

Lu Xueguan; Liu Zhiyong; Zhang Liyuan; Tian Ye

2005-01-01

Objective: To investigate the incidence of post-irradiation sensorineural hearing loss (SNHL) in patients suffering from nasopharyngeal carcinoma and to evaluate its potentially contributing factors. Methods: Pure tonetest and impedance audiography were carried out in patients suffering from nasopharyngeal carcinoma with a post-irradiation follow-up time over 1 year. Additionally, the test results were combined with clinical data and analyzed retrospectively. Results: The follow-up time of all patients ranged from 12 to 94 months (median 53 months). The incidences of SNHL at low and high frequencies were 8% and 42% respectively. Univariate analysis showed that patient's age and follow-up time affected the incidence of SNHL at high frequencies (t=2.051, P=0.0269; t=2.978, P=0.0011), but sex, preirradiation subjective hearing loss, irradiation dose and chemotherapy including cisplatin had no significance. Multivariate analysis by Binary Logistic Regression revealed that the risk of SNHL was correlated with patient's age and follow-up time (P=0.02; P=0.009). Conclusion: Post-irradiation SNHL at high frequencies in patients suffering from nasopharyngeal carcinoma is more common than that at low frequencies. The independent prognostic factors for development of SNHL at high frequencies are patient's age and follow-up time. But the role of preirradiation hearing level ,irradiation dose and chemotherapy including cisplatin are not conclusive and further research is needed. (authors)

Comparison study of inelastic analysis codes for high temperature structure

Energy Technology Data Exchange (ETDEWEB)

Kim, Jong Bum; Lee, H. Y.; Park, C. K.; Geon, G. P.; Lee, J. H

2004-02-01

LMR high temperature structures subjected to operating and transient loadings may exhibit very complex deformation behaviors due to the use of ductile material such as 316SS and the systematic analysis technology of high temperature structure for reliable safety assessment is essential. In this project, comparative study with developed inelastic analysis program NONSTA and the existing analysis codes was performed applying various types of loading including non-proportional loading. The performance of NONSTA was confirmed and the effect of inelastic constants on the analysis result was analyzed. Also, the applicability of the inelastic analysis was enlarged as a result of applying both the developed program and the existing codes to the analyses of the enhanced creep behavior and the elastic follow-up behavior of high temperature structures and the necessary items for improvements were deduced. Further studies on the improvement of NONSTA program and the decision of the proper values of inelastic constants are necessary.

High preoperative serum CA19-9 level is predictive of poor prognosis for patients with colorectal liver oligometastases undergoing hepatic resection.

Science.gov (United States)

Lu, Zhenhai; Peng, Jianhong; Wang, Zhiqiang; Pan, Zhizhong; Yuan, Yunfei; Wan, Desen; Li, Binkui

2016-11-01

Oligometastasis is defined as a transitional state between localized and widespread systemic metastatic cancers. In colorectal cancer, the prognostic factors and prognostic value of preoperative serum carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) for patients with colorectal liver oligometastases (CLOM) undergoing hepatic resection have not been well explored. Therefore, the present study included 141 patients with CLOM (≤5 liver metastases) who underwent R0 resection from 2005 to 2012. The association of clinicopathological factors including preoperative CA19-9 and CEA levels with overall survival (OS) was analyzed with univariate and multivariate analyses. Kaplan-Meier analysis showed that patients with high CA19-9 levels tended to have poorer OS than those with low levels (median OS 21.5 vs. 64.0 months, P = 0.002). Preoperative CEA levels were not significantly associated with OS (P > 0.05). Univariate and multivariate analyses demonstrated that larger tumor size of liver metastases (HR 1.911; 95 % CI 1.172-3.114; P = 0.009), bilobar distribution (HR 1.776; 95 % CI 1.097-2.873; P = 0.019), and higher preoperative CA19-9 levels (HR 1.954; 95 % CI 1.177-3.242; P = 0.010) were independent predictors of poor OS for patients with CLOM. Our study identified tumor size, distribution, and preoperative CA19-9 levels as independent prognostic factors for OS of patients with CLOM. In particular, measurement of preoperative CA19-9 levels offers an easy tool that could help identify high-risk patients and aid in improving the management of patients with CLOM.

Multivariate Analysis of the Predictors of Survival for Patients with Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization: Focusing on Superselective Chemoembolization

International Nuclear Information System (INIS)

Ji, Suk Kyeong; Cho, Yun Ku; Ahn, Yong Sik; Kim, Mi Young; Park, Yoon Ok; Kim, Jae Kyun; Kim, Wan Tae

2008-01-01

While the prognostic factors of survival for patients with hepatocellular carcinoma (HCC) who underwent transarterial chemoembolization (TACE) are well known, the clinical significance of performing selective TACE for HCC patients has not been clearly documented. We tried to analyze the potential factors of disease-free survival for these patients, including the performance of selective TACE. A total of 151 patients with HCC who underwent TACE were retrospectively analyzed for their disease-free survival (a median follow- up of 23 months, range: 1-88 months). Univariate and multivariate analyses were performed for 20 potential factors by using the Cox proportional hazard model, including 19 baseline factors and one procedure-related factor (conventional versus selective TACE). The parameters that proved to be significant on the univariate analysis were subsequently tested with the multivariate model. Conventional or selective TACE was performed for 40 and 111 patients, respectively. Univariate and multivariate analyses revealed that tumor multiplicity, venous tumor thrombosis and selective TACE were the only three independent significant prognostic factors of disease-free survival (p = 0.002, 0.015 and 0.019, respectively). In our study, selective TACE was a favorable prognostic factor for the disease-free survival of patients with HCC who underwent TACE

[Analysis of the risk factors of acute respiratory distress syndrome of Berlin new definition in patients with sepsis in emergency department].

Science.gov (United States)

Qiao, Liang; Liu, Zhi

2015-07-01

To discuss the risk factors of acute respiratory distress syndrome (ARDS) in patients with sepsis in emergency department. 312 patients with sepsis admitted to Department of Emergency of China Medical University Affiliated First Hospital were retrospectively analyzed, and they were divided into two groups according to development of ARDS, which was defined according to the Berlin new definition. The age, gender, vital signs, laboratory results, underlying disease, the mortality in emergency department sepsis (MEDS) score and lung injury prediction score (LIPS) were collected. Univariate analysis was done for each parameter. Statistical significance results were evaluated by multivariate logistic regression analysis. Receiver operating characteristic (ROC) curve was plotted to analyze the predictive value of the parameter for ARDS. The incidence of sepsis-related ARDS was 11.2% (35/312). Within 35 cases of ARDS, there were 10 cases of mild ARDS, 18 cases of moderate ARDS, and 7 cases of severe ARDS. Univariate analysis showed that age (t=-2.134, P=0.035), oxygenation index (t=-4.245, P=0.001), arterial lactate (Lac, t=6.245, Pemergency department, which may be a reference for the early clinical diagnosis of ARDS.

MRI differentiation of low-grade from high-grade appendicular chondrosarcoma

International Nuclear Information System (INIS)

Douis, Hassan; Singh, Leanne; Saifuddin, Asif

2014-01-01

To identify magnetic resonance imaging (MRI) features which differentiate low-grade chondral lesions (atypical cartilaginous tumours/grade 1 chondrosarcoma) from high-grade chondrosarcomas (grade 2, grade 3 and dedifferentiated chondrosarcoma) of the major long bones. We identified all patients treated for central atypical cartilaginous tumours and central chondrosarcoma of major long bones (humerus, femur, tibia) over a 13-year period. The MRI studies were assessed for the following features: bone marrow oedema, soft tissue oedema, bone expansion, cortical thickening, cortical destruction, active periostitis, soft tissue mass and tumour length. The MRI-features were compared with the histopathological tumour grading using univariate, multivariate logistic regression and receiver operating characteristic curve (ROC) analyses. One hundred and seventy-nine tumours were included in this retrospective study. There were 28 atypical cartilaginous tumours, 79 grade 1 chondrosarcomas, 36 grade 2 chondrosarcomas, 13 grade 3 chondrosarcomas and 23 dedifferentiated chondrosarcomas. Multivariate analysis demonstrated that bone expansion (P = 0.001), active periostitis (P = 0.001), soft tissue mass (P < 0.001) and tumour length (P < 0.001) were statistically significant differentiating factors between low-grade and high-grade chondral lesions with an area under the ROC curve of 0.956. On MRI, bone expansion, active periostitis, soft tissue mass and tumour length can reliably differentiate high-grade chondrosarcomas from low-grade chondral lesions of the major long bones. (orig.)

MRI differentiation of low-grade from high-grade appendicular chondrosarcoma

Energy Technology Data Exchange (ETDEWEB)

Douis, Hassan; Singh, Leanne; Saifuddin, Asif [The Royal National Orthopaedic Hospital NHS Trust, Department of Radiology, Stanmore, Middlesex (United Kingdom)

2014-01-15

To identify magnetic resonance imaging (MRI) features which differentiate low-grade chondral lesions (atypical cartilaginous tumours/grade 1 chondrosarcoma) from high-grade chondrosarcomas (grade 2, grade 3 and dedifferentiated chondrosarcoma) of the major long bones. We identified all patients treated for central atypical cartilaginous tumours and central chondrosarcoma of major long bones (humerus, femur, tibia) over a 13-year period. The MRI studies were assessed for the following features: bone marrow oedema, soft tissue oedema, bone expansion, cortical thickening, cortical destruction, active periostitis, soft tissue mass and tumour length. The MRI-features were compared with the histopathological tumour grading using univariate, multivariate logistic regression and receiver operating characteristic curve (ROC) analyses. One hundred and seventy-nine tumours were included in this retrospective study. There were 28 atypical cartilaginous tumours, 79 grade 1 chondrosarcomas, 36 grade 2 chondrosarcomas, 13 grade 3 chondrosarcomas and 23 dedifferentiated chondrosarcomas. Multivariate analysis demonstrated that bone expansion (P = 0.001), active periostitis (P = 0.001), soft tissue mass (P < 0.001) and tumour length (P < 0.001) were statistically significant differentiating factors between low-grade and high-grade chondral lesions with an area under the ROC curve of 0.956. On MRI, bone expansion, active periostitis, soft tissue mass and tumour length can reliably differentiate high-grade chondrosarcomas from low-grade chondral lesions of the major long bones. (orig.)

Analysis and Design of High-Order Parallel Resonant Converters

Science.gov (United States)

Batarseh, Issa Eid

1990-01-01

In this thesis, a special state variable transformation technique has been derived for the analysis of high order dc-to-dc resonant converters. Converters comprised of high order resonant tanks have the advantage of utilizing the parasitic elements by making them part of the resonant tank. A new set of state variables is defined in order to make use of two-dimensional state-plane diagrams in the analysis of high order converters. Such a method has been successfully used for the analysis of the conventional Parallel Resonant Converters (PRC). Consequently, two -dimensional state-plane diagrams are used to analyze the steady state response for third and fourth order PRC's when these converters are operated in the continuous conduction mode. Based on this analysis, a set of control characteristic curves for the LCC-, LLC- and LLCC-type PRC are presented from which various converter design parameters are obtained. Various design curves for component value selections and device ratings are given. This analysis of high order resonant converters shows that the addition of the reactive components to the resonant tank results in converters with better performance characteristics when compared with the conventional second order PRC. Complete design procedure along with design examples for 2nd, 3rd and 4th order converters are presented. Practical power supply units, normally used for computer applications, were built and tested by using the LCC-, LLC- and LLCC-type commutation schemes. In addition, computer simulation results are presented for these converters in order to verify the theoretical results.

Analysis on risk factors for post-stroke emotional incontinence

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Xiao-chun ZHANG

2018-01-01

Full Text Available Objective To investigate the occurrence rate and related risk factors for post-stroke emotional incontinence (PSEI. Methods The clinical data [sex, age, body mass index (BMI, education, marital status, medical history (hypertension, heart disease, diabetes, hyperlipemia, smoking and drinking and family history of stroke] of 162 stroke patients were recorded. Serum homocysteine (Hcy level was examined. Head CT and/or MRI were used to indicate stroke subtype, site of lesion and number of lesion. Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-Ⅴ Chinese version and Hamilton Depression Rating Scale-17 Items (HAMD-17 were used to evaluate the degree of depression. House diagnostic standard was used to diagnose PSEI. Univariate and multivariate backward Logistic regression analysis was used to screen related risk factor for PSEI. Spearman rank correlation analysis was used to discuss the correlation between PSEI and post-stroke depression (PSD. Results Among 162 stroke patients, 12 cases were diagnosed as PSEI (7.41% . The ratio of age < 60 years in PSEI group was significantly higher than non-PSEI group (P = 0.045. The ratio of smoking in PSEI group was significantly lower than non-PSEI group (P = 0.036. Univariate and multivariate backward Logistic regression analysis showed age < 60 years was independent risk factor for PSEI (OR = 4.000, 95%CI: 1.149-13.924; P = 0.029. Ten cases were combined with PSD in 12 PSEI patients, and the co-morbidity rate of PSEI and PSD was83.33%. Spearman rank correlation analysis showed PSEI was positively related to PSD (rs = 0.305, P = 0.000. Conclusions PSEI is common affective disorder in stroke patients, which easily happens in patients under 60 years of age. DOI: 10.3969/j.issn.1672-6731.2017.12.010

A cost analysis of implementing a behavioral weight loss intervention in community mental health settings: Results from the ACHIEVE trial.

Science.gov (United States)

Janssen, Ellen M; Jerome, Gerald J; Dalcin, Arlene T; Gennusa, Joseph V; Goldsholl, Stacy; Frick, Kevin D; Wang, Nae-Yuh; Appel, Lawrence J; Daumit, Gail L

2017-06-01

In the ACHIEVE randomized controlled trial, an 18-month behavioral intervention accomplished weight loss in persons with serious mental illness who attended community psychiatric rehabilitation programs. This analysis estimates costs for delivering the intervention during the study. It also estimates expected costs to implement the intervention more widely in a range of community mental health programs. Using empirical data, costs were calculated from the perspective of a community psychiatric rehabilitation program delivering the intervention. Personnel and travel costs were calculated using time sheet data. Rent and supply costs were calculated using rent per square foot and intervention records. A univariate sensitivity analysis and an expert-informed sensitivity analysis were conducted. With 144 participants receiving the intervention and a mean weight loss of 3.4 kg, costs of $95 per participant per month and $501 per kilogram lost in the trial were calculated. In univariate sensitivity analysis, costs ranged from $402 to $725 per kilogram lost. Through expert-informed sensitivity analysis, it was estimated that rehabilitation programs could implement the intervention for $68 to $85 per client per month. Costs of implementing the ACHIEVE intervention were in the range of other intensive behavioral weight loss interventions. Wider implementation of efficacious lifestyle interventions in community mental health settings will require adequate funding mechanisms. © 2017 The Obesity Society.

Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin

Science.gov (United States)

zhang, L.

2011-12-01

Copula has become a very powerful statistic and stochastic methodology in case of the multivariate analysis in Environmental and Water resources Engineering. In recent years, the popular one-parameter Archimedean copulas, e.g. Gumbel-Houggard copula, Cook-Johnson copula, Frank copula, the meta-elliptical copula, e.g. Gaussian Copula, Student-T copula, etc. have been applied in multivariate hydrological analyses, e.g. multivariate rainfall (rainfall intensity, duration and depth), flood (peak discharge, duration and volume), and drought analyses (drought length, mean and minimum SPI values, and drought mean areal extent). Copula has also been applied in the flood frequency analysis at the confluences of river systems by taking into account the dependence among upstream gauge stations rather than by using the hydrological routing technique. In most of the studies above, the annual time series have been considered as stationary signal which the time series have been assumed as independent identically distributed (i.i.d.) random variables. But in reality, hydrological time series, especially the daily and monthly hydrological time series, cannot be considered as i.i.d. random variables due to the periodicity existed in the data structure. Also, the stationary assumption is also under question due to the Climate Change and Land Use and Land Cover (LULC) change in the fast years. To this end, it is necessary to revaluate the classic approach for the study of hydrological time series by relaxing the stationary assumption by the use of nonstationary approach. Also as to the study of the dependence structure for the hydrological time series, the assumption of same type of univariate distribution also needs to be relaxed by adopting the copula theory. In this paper, the univariate monthly hydrological time series will be studied through the nonstationary time series analysis approach. The dependence structure of the multivariate monthly hydrological time series will be

Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

Science.gov (United States)

Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2018-02-01

The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).

STATCAT, Statistical Analysis of Parametric and Non-Parametric Data

International Nuclear Information System (INIS)

David, Hugh

1990-01-01

1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required

Transport analysis of high radiation and high density plasmas in the ASDEX Upgrade tokamak

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Casali L.

2014-01-01

Full Text Available Future fusion reactors, foreseen in the “European road map” such as DEMO, will operate under more demanding conditions compared to present devices. They will require high divertor and core radiation by impurity seeding to reduce heat loads on divertor target plates. In addition, DEMO will have to work at high core densities to reach adequate fusion performance. The performance of fusion reactors depends on three essential parameters: temperature, density and energy confinement time. The latter characterizes the loss rate due to both radiation and transport processes. The DEMO foreseen scenarios described above were not investigated so far, but are now addressed at the ASDEX Upgrade tokamak. In this work we present the transport analysis of such scenarios. Plasma with high radiation by impurity seeding: transport analysis taking into account the radiation distribution shows no change in transport during impurity seeding. The observed confinement improvement is an effect of higher pedestal temperatures which extend to the core via stiffness. A non coronal radiation model was developed and compared to the bolometric measurements in order to provide a reliable radiation profile for transport calculations. High density plasmas with pellets: the analysis of kinetic profiles reveals a transient phase at the start of the pellet fuelling due to a slower density build up compared to the temperature decrease. The low particle diffusion can explain the confinement behaviour.

Multivariate Analysis for the Processing of Signals

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Beattie J.R.

2014-01-01

Full Text Available Real-world experiments are becoming increasingly more complex, needing techniques capable of tracking this complexity. Signal based measurements are often used to capture this complexity, where a signal is a record of a sample’s response to a parameter (e.g. time, displacement, voltage, wavelength that is varied over a range of values. In signals the responses at each value of the varied parameter are related to each other, depending on the composition or state sample being measured. Since signals contain multiple information points, they have rich information content but are generally complex to comprehend. Multivariate Analysis (MA has profoundly transformed their analysis by allowing gross simplification of the tangled web of variation. In addition MA has also provided the advantage of being much more robust to the influence of noise than univariate methods of analysis. In recent years, there has been a growing awareness that the nature of the multivariate methods allows exploitation of its benefits for purposes other than data analysis, such as pre-processing of signals with the aim of eliminating irrelevant variations prior to analysis of the signal of interest. It has been shown that exploiting multivariate data reduction in an appropriate way can allow high fidelity denoising (removal of irreproducible non-signals, consistent and reproducible noise-insensitive correction of baseline distortions (removal of reproducible non-signals, accurate elimination of interfering signals (removal of reproducible but unwanted signals and the standardisation of signal amplitude fluctuations. At present, the field is relatively small but the possibilities for much wider application are considerable. Where signal properties are suitable for MA (such as the signal being stationary along the x-axis, these signal based corrections have the potential to be highly reproducible, and highly adaptable and are applicable in situations where the data is noisy or

Targeting human c-Myc promoter duplex DNA with actinomycin D by use of multi-way analysis of quantum-dot-mediated fluorescence resonance energy transfer

DEFF Research Database (Denmark)

Gholami, Somayeh; Kompany Zare, Mohsen

2013-01-01

Actinomycin D (Act D), an oncogenic c-Myc promoter binder, interferes with the action of RNA polymerase. There is great demand for high-throughput technology able to monitor the activity of DNA-binding drugs. To this end, binding of 7-aminoactinomycin D (7AAD) to the duplex c-Myc promoter...... pairs resulted in efficient energy transfer from drug to QD via fluorescence resonance energy transfer (FRET). Multi-way analysis of the three-way data array obtained from titration experiments was performed by use of restricted Tucker3 and hard trilinear decomposition (HTD). These techniques enable...... the important advantage over univariate classical methods of enabling us to investigate the source of variance in the fluorescence signal of the DNA-drug complex. It was established that hard trilinear decomposition analysis of FRET-measured data overcomes the problem of rank deficiency, enabling calculation...

High Sensitivity and High Detection Specificity of Gold-Nanoparticle-Grafted Nanostructured Silicon Mass Spectrometry for Glucose Analysis.

Science.gov (United States)

Tsao, Chia-Wen; Yang, Zhi-Jie

2015-10-14

Desorption/ionization on silicon (DIOS) is a high-performance matrix-free mass spectrometry (MS) analysis method that involves using silicon nanostructures as a matrix for MS desorption/ionization. In this study, gold nanoparticles grafted onto a nanostructured silicon (AuNPs-nSi) surface were demonstrated as a DIOS-MS analysis approach with high sensitivity and high detection specificity for glucose detection. A glucose sample deposited on the AuNPs-nSi surface was directly catalyzed to negatively charged gluconic acid molecules on a single AuNPs-nSi chip for MS analysis. The AuNPs-nSi surface was fabricated using two electroless deposition steps and one electroless etching step. The effects of the electroless fabrication parameters on the glucose detection efficiency were evaluated. Practical application of AuNPs-nSi MS glucose analysis in urine samples was also demonstrated in this study.

DESIGN ANALYSIS FOR THE DEFENSE HIGH-LEVEL WASTE DISPOSAL CONTAINER

International Nuclear Information System (INIS)

Radulesscu, G.; Tang, J.S.

2000-01-01

The purpose of ''Design Analysis for the Defense High-Level Waste Disposal Container'' analysis is to technically define the defense high-level waste (DHLW) disposal container/waste package using the Waste Package Department's (WPD) design methods, as documented in ''Waste Package Design Methodology Report'' (CRWMS M andO [Civilian Radioactive Waste Management System Management and Operating Contractor] 2000a). The DHLW disposal container is intended for disposal of commercial high-level waste (HLW) and DHLW (including immobilized plutonium waste forms), placed within disposable canisters. The U.S. Department of Energy (DOE)-managed spent nuclear fuel (SNF) in disposable canisters may also be placed in a DHLW disposal container along with HLW forms. The objective of this analysis is to demonstrate that the DHLW disposal container/waste package satisfies the project requirements, as embodied in Defense High Level Waste Disposal Container System Description Document (SDD) (CRWMS M andO 1999a), and additional criteria, as identified in Waste Package Design Sensitivity Report (CRWMS M andQ 2000b, Table 4). The analysis briefly describes the analytical methods appropriate for the design of the DHLW disposal contained waste package, and summarizes the results of the calculations that illustrate the analytical methods. However, the analysis is limited to the calculations selected for the DHLW disposal container in support of the Site Recommendation (SR) (CRWMS M andO 2000b, Section 7). The scope of this analysis is restricted to the design of the codisposal waste package of the Savannah River Site (SRS) DHLW glass canisters and the Training, Research, Isotopes General Atomics (TRIGA) SNF loaded in a short 18-in.-outer diameter (OD) DOE standardized SNF canister. This waste package is representative of the waste packages that consist of the DHLW disposal container, the DHLW/HLW glass canisters, and the DOE-managed SNF in disposable canisters. The intended use of this

DESIGN ANALYSIS FOR THE DEFENSE HIGH-LEVEL WASTE DISPOSAL CONTAINER

Energy Technology Data Exchange (ETDEWEB)

G. Radulesscu; J.S. Tang

2000-06-07

The purpose of ''Design Analysis for the Defense High-Level Waste Disposal Container'' analysis is to technically define the defense high-level waste (DHLW) disposal container/waste package using the Waste Package Department's (WPD) design methods, as documented in ''Waste Package Design Methodology Report'' (CRWMS M&O [Civilian Radioactive Waste Management System Management and Operating Contractor] 2000a). The DHLW disposal container is intended for disposal of commercial high-level waste (HLW) and DHLW (including immobilized plutonium waste forms), placed within disposable canisters. The U.S. Department of Energy (DOE)-managed spent nuclear fuel (SNF) in disposable canisters may also be placed in a DHLW disposal container along with HLW forms. The objective of this analysis is to demonstrate that the DHLW disposal container/waste package satisfies the project requirements, as embodied in Defense High Level Waste Disposal Container System Description Document (SDD) (CRWMS M&O 1999a), and additional criteria, as identified in Waste Package Design Sensitivity Report (CRWMS M&Q 2000b, Table 4). The analysis briefly describes the analytical methods appropriate for the design of the DHLW disposal contained waste package, and summarizes the results of the calculations that illustrate the analytical methods. However, the analysis is limited to the calculations selected for the DHLW disposal container in support of the Site Recommendation (SR) (CRWMS M&O 2000b, Section 7). The scope of this analysis is restricted to the design of the codisposal waste package of the Savannah River Site (SRS) DHLW glass canisters and the Training, Research, Isotopes General Atomics (TRIGA) SNF loaded in a short 18-in.-outer diameter (OD) DOE standardized SNF canister. This waste package is representative of the waste packages that consist of the DHLW disposal container, the DHLW/HLW glass canisters, and the DOE-managed SNF in disposable

High-Temperature Structural Analysis of a Small-Scale Prototype of a Process Heat Exchanger (IV) - Macroscopic High-Temperature Elastic-Plastic Analysis -

International Nuclear Information System (INIS)

Song, Kee Nam; Hong, Sung Deok; Park, Hong Yoon

2011-01-01

A PHE (Process Heat Exchanger) is a key component required to transfer heat energy of 950 .deg. C generated in a VHTR (Very High Temperature Reactor) to a chemical reaction that yields a large quantity of hydrogen. A small-scale PHE prototype made of Hastelloy-X was scheduled for testing in a small-scale gas loop at the Korea Atomic Energy Research Institute. In this study, as a part of the evaluation of the high-temperature structural integrity of the PHE prototype, high-temperature structural analysis modeling, and macroscopic thermal and elastic-plastic structural analysis of the PHE prototype were carried out under the gas-loop test conditions as a preliminary qwer123$ study before carrying out the performance test in the gas loop. The results obtained in this study will be used to design the performance test setup for the modified PHE prototype

Safety analysis of the transportation of high-level radioactive waste

International Nuclear Information System (INIS)

Murphy, E.S.; Winegardner, W.K.

1975-01-01

An analysis of the risk from transportation of solidified high-level waste is being performed at Battelle-Northwest as part of a comprehensive study of the management of high-level waste. The risk analysis study makes use of fault trees to identify failure events and to specify combinations of events which could result in breach of containment and a release of radioactive material to the environment. Contributions to risk analysis methodology which have been made in connection with this study include procedures for identification of dominant failure sequences, methods for quantifying the effects of probabilistic failure events, and computer code development. Preliminary analysis based on evaluation of the rail transportation fault tree indicates that the dominant failure sequences for transportation of solidified high-level waste will be those related to railroad accidents. Detailed evaluation of rail accident failure sequences is proceeding and is making use of the limited frequency-severity data which is available in the literature. (U.S.)

Patterns of white matter microstructure in individuals at ultra-high-risk for psychosis

DEFF Research Database (Denmark)

Krakauer, K; Ebdrup, B H; Glenthøj, B Y

2017-01-01

BACKGROUND: Individuals at ultra-high-risk (UHR) for psychosis present with emerging symptoms and decline in functioning. Previous univariate analyses have indicated widespread white matter (WM) aberrations in multiple brain regions in UHR individuals and patients with schizophrenia. Using multiv......, MO, and higher RD. CONCLUSIONS: UHR individuals demonstrate complex brain patterns of WM abnormalities. Despite the subtle psychopathology of UHR individuals, aberrations in WM appear associated with positive and negative symptoms as well as level of functioning....

The discriminatory analysis about factors correlative with the early hypothyroidism after 131I therapy for hyperthyroidism

International Nuclear Information System (INIS)

Xiong Lingjing; Liang Changhua; Deng Haoyu; Li Xinhui; Hu Shuo

2002-01-01

Objective: To explore the factors correlative with the early hypothyroidism after 131 I therapy for Graves' hyperthyroidism so as to cure it and decrease the early hypothyroidism occurring and prevent it from becoming irreversible hypothyroidism. Methods: Logistic regression discriminatory analysis by introducing multiple factors from group data and forward stepwise selection of 11 independent variables of 240 hyperthyroidism patients from clinical data and 1 dependent variable from follow-up data after 131 I therapy was conducted. Univariate analysis of each observed factor was performed, too. Results: (1)The results of multivariate analysis showed that the age of patients, the weight of thyroid, the suffering situation, the curve of 131 I absorption rate and the giving 131 I dosage/g thyroid tissue were correlated to early hypothyroidism. The results of univariate analysis showed that the weight of thyroid, the highest absorption of 131 I, the total treatment dosage of 131 I were correlated to early hypothyroidism. (2) The logistic regression equation was statistically significant. (3) The positive and negative predicting accuracy of the early hypothyroidism occurring was 64.08 %, 78.83 %, respectively, the overall predicting accuracy was 72.50%. Conclusions: The dosage of 131 I for treatment of hyperthyroid is the key factor according to the five correlative factors which are relating to the early hypothyroidism and the discriminatory classification. Enhanced follow-up and in time supplement of thyroid hormone are important measures for preventing the early hypothyroidism from becoming irreversible hypothyroidism

Post hoc analysis of plasma amino acid profiles: towards a specific pattern in autism spectrum disorder and intellectual disability.

Science.gov (United States)

Delaye, Jean-Baptiste; Patin, Franck; Lagrue, Emmanuelle; Le Tilly, Olivier; Bruno, Clement; Vuillaume, Marie-Laure; Raynaud, Martine; Benz-De Bretagne, Isabelle; Laumonnier, Frederic; Vourc'h, Patrick; Andres, Christian; Blasco, Helene

2018-01-01

Objectives Autism spectrum disorders and intellectual disability present a challenge for therapeutic and dietary management. We performed a re-analysis of plasma amino acid chromatography of children with autism spectrum disorders ( n = 22) or intellectual disability ( n = 29) to search for a metabolic signature that can distinguish individuals with these disorders from controls ( n = 30). Methods We performed univariate and multivariate analyses using different machine learning strategies, from the raw data of the amino acid chromatography. Finally, we analysed the metabolic pathways associated with discriminant biomarkers. Results Multivariate analysis revealed models to discriminate patients with autism spectrum disorders or intellectual disability and controls from plasma amino acid profiles ( P intellectual disability patients shared similar differences relative to controls, including lower glutamate ( P intellectual disability revealed the involvement of urea, 3-methyl-histidine and histidine metabolism. Biosigner analysis and univariate analysis confirmed the role of 3-methylhistidine ( P = 0.004), histidine ( P = 0.003), urea ( P = 0.0006) and lysine ( P = 0.002). Conclusions We revealed discriminant metabolic patterns between autism spectrum disorders, intellectual disability and controls. Amino acids known to play a role in neurotransmission were discriminant in the models comparing autism spectrum disorders or intellectual disability to controls, and histidine and b-alanine metabolism was specifically highlighted in the model.

Otoacoustic Emissions in Rural Nicaragua: Cost Analysis and Implications for Newborn Hearing Screening.

Science.gov (United States)

Wong, Lye-Yeng; Espinoza, Francisca; Alvarez, Karen Mojica; Molter, Dave; Saunders, James E

2017-05-01

Objective (1) Determine the incidence and risk factors for congenital hearing loss. (2) Perform cost analysis of screening programs. Study Design Proportionally distributed cross-sectional survey. Setting Jinotega, Nicaragua. Subjects and Methods Otoacoustic emissions (OAEs) were used to screen 640 infants home birth settings. Data on 15 risk factors were analyzed. Cost of 4 implementation strategies was studied: universal screening, screening at the regional health center (RHC), targeted screening, and screening at the RHC plus targeted screening. Cost-effectiveness analysis over 10 years was based on disability-adjusted life year estimates, with the World Health Organization standard of cost-effectiveness ratio (CER) / gross domestic product (GDP) births, 325 (50.8%) were in the RHC, 69 (10.8%) in the neonatal intensive care unit, and 29 (4.5%) at home. Family history and birth defect were significant in univariate analysis; birth defect was significant in multivariate analysis. Cost-effectiveness analysis demonstrated that OAE screening is cost-effective without treatment (CER/GDP = 0.06-2.00) and with treatment (CER/GDP = 0.58-2.52). Conclusions Our rate of OAE failures was comparable to those of developed countries and lower than hearing loss rates noted among Nicaraguan schoolchildren, suggesting acquired or progressive etiology in the latter. Birth defects and familial hearing loss correlated with OAE failure. OAE screening of infants is feasible and cost-effective in rural Nicaragua, although highly influenced by estimated hearing loss severity in identified infants and the high travel costs incurred in a targeted screening strategy.

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

Science.gov (United States)

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

Anemia and growth failure among HIV-infected children in India: a retrospective analysis

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Shet Anita

2009-06-01

Full Text Available Abstract Background Anemia and poor nutrition have been previously described as independent risk factors for death among HIV-infected children. We sought to describe nutritional status, anemia burden and HIV disease correlates among infected children in India. Methods We analyzed retrospective data from 248 HIV-infected children aged 1–12 years attending three outpatient clinics in South India (2004–2006. Standard WHO definitions were used for anemia, HIV staging and growth parameters. Statistical analysis included chi square, t tests, univariate and multivariate logistic regression analyses. Results The overall prevalence of anemia (defined as hemoglobin Conclusion The high prevalence and strong interrelationship of anemia and poor nutrition among HIV-infected children in India, particularly those living in rural areas underscores the need for incorporating targeted nutritional interventions during national scale up of care, support and treatment among HIV-infected children.

The prognostic role of mTOR and p-mTOR for survival in non-small cell lung cancer: a systematic review and meta-analysis.

Directory of Open Access Journals (Sweden)

Lei Li

Full Text Available The mammalian target of rapamycin (mTOR and phosphorylated mTOR (p-mTOR are potential prognostic markers and therapeutic targets for non-small cell lung cancer (NSCLC. However, the association between mTOR/p-mTOR expression and NSCLC patients' prognosis remains controversial. Thus, a meta-analysis of existing studies evaluating the prognostic role of mTOR/p-mTOR expression for NSCLC was conducted.A systemically literature search was performed via Pubmed, Embase, Medline as well as CNKI (China National Knowledge Infrastructure. Studies were included that reported the hazard ratio (HR and 95%CI for the association between mTOR/p-mTOR expression and NSCLC patients' survival. Random-effects model was used to pool HRs.Ten eligible studies were included in this meta-analysis, with 4 about m-TOR and 7 about p-mTOR. For mTOR, the pooled HR of overall survival (OS was 1.00 (95%CI 0.5 to 1.99 by univariate analysis and 1.22 (95%CI 0.53 to 2.82 by multivariate analysis. For p-mTOR, the pooled HR was 1.39 (95%CI 0.97 to 1.98 by univariate analysis and 1.42 (95%CI 0.56 to 3.60 by multivariate analysis.The results indicated that no statistically significant association was found between mTOR/p-mTOR expression and NSCLC patients' prognosis.

Cost-Effectiveness Analysis of Test-Based versus Presumptive Treatment of Uncomplicated Malaria in Children under Five Years in an Area of High Transmission in Central Ghana

DEFF Research Database (Denmark)

Tawiah, Theresa; Hansen, Kristian Schultz; Baiden, Frank

2016-01-01

about household cost incurred on transport, drugs, fees, and special food during a period of one week after the health centre visit as well as days unable to work. A decision model approach was used to calculate the incremental cost-effectiveness ratios (ICERs). Univariate and multivariate sensitivity...... (ACT) in all suspected malaria patients. The use of malaria rapid diagnostic tests (mRDTs) would make it possible for prescribers to diagnose malaria at point-of-care and better target the use of antimalarials. Therefore, a cost-effectiveness analysis was performed on the introduction of m......) or clinical judgement (control) was used to measure the effect of mRDTs on appropriate treatment: ‘a child with a positive reference diagnosis prescribed a course of ACT or a child with a negative reference diagnosis not given an ACT’. Cost data was collected from five purposively selected health centres...

Exploring Radiotherapy Targeting Strategy and Dose: A Pooled Analysis of Cooperative Group Trials of Combined Modality Therapy for Stage III Non-Small Cell Lung Cancer.

Science.gov (United States)

Schild, Steven E; Fan, Wen; Stinchcombe, Thomas E; Vokes, Everett E; Ramalingam, Suresh S; Bradley, Jeffrey D; Kelly, Karen; Pang, Herbert H; Wang, Xiaofei

2018-04-21

Concurrent chemoradiotherapy(CRT) is standard therapy for locally-advanced non-small-cell lung cancer(LA-NSCLC)patients. This study was performed to examine thoracic radiotherapy(TRT) parameters and their impact on patient survival. We collected Individual patient data(IPD) from 3600LA-NSCLC patients participating in 16 cooperative group trials of concurrent CRT. The primary TRT parameters examined included field design strategy(elective nodal irradiation(ENI) compared to involved field TRT(IF-TRT)), total dose, and biologically effective dose(BED). Hazard ratios(HRs) for overall survival were calculated with univariable and multivariable Cox models. TRT doses ranged from 60 to 74 Gy with most treatments administered once-daily. ENI was associated with poorer survival than IF-TRT(univariable HR,1.37;95%CI,1.24-1.51,pENI patients were 24 and 16 months, respectively. Patients were divided into 3 dose groups: low total dose(60 Gy), medium total dose(>60Gy-66Gy) and high total dose(>66Gy-74 Gy). With reference to the low dose group, the multivariable HR's were 1.08 for the medium dose group(95%CI=0.93-1.25) and 1.12 for the high dose group(CI=0.97-1.30).The univariate p=0.054 and multivariable p=0.17. BED was grouped as follows: low(55.5 Gy 10 ). With reference to the low BED group, the HR was 1.00(95%CI=0.85-1.18) for the medium BED group and 1.10(95%CI=0.93-1.31) for the high BED group. The univariable p=0.076 and multivariable p=0.16. For LA-NSCLC patients treated with concurrent CRT, IF-TRT was associated with significantly better survival than ENI-TRT. TRT total and BED dose levels were not significantly associated with patient survival. Future progress will require research focusing on better systemic therapy and TRT. Copyright © 2018. Published by Elsevier Inc.

Dynamic Stability Analysis Using High-Order Interpolation

Directory of Open Access Journals (Sweden)

Juarez-Toledo C.

2012-10-01

Full Text Available A non-linear model with robust precision for transient stability analysis in multimachine power systems is proposed. The proposed formulation uses the interpolation of Lagrange and Newton's Divided Difference. The High-Order Interpolation technique developed can be used for evaluation of the critical conditions of the dynamic system.The technique is applied to a 5-area 45-machine model of the Mexican interconnected system. As a particular case, this paper shows the application of the High-Order procedure for identifying the slow-frequency mode for a critical contingency. Numerical examples illustrate the method and demonstrate the ability of the High-Order technique to isolate and extract temporal modal behavior.

Analysis of chaos in high-dimensional wind power system.

Science.gov (United States)

Wang, Cong; Zhang, Hongli; Fan, Wenhui; Ma, Ping

2018-01-01

A comprehensive analysis on the chaos of a high-dimensional wind power system is performed in this study. A high-dimensional wind power system is more complex than most power systems. An 11-dimensional wind power system proposed by Huang, which has not been analyzed in previous studies, is investigated. When the systems are affected by external disturbances including single parameter and periodic disturbance, or its parameters changed, chaotic dynamics of the wind power system is analyzed and chaotic parameters ranges are obtained. Chaos existence is confirmed by calculation and analysis of all state variables' Lyapunov exponents and the state variable sequence diagram. Theoretical analysis and numerical simulations show that the wind power system chaos will occur when parameter variations and external disturbances change to a certain degree.

Towards quantitative laser-induced breakdown spectroscopy analysis of soil samples

International Nuclear Information System (INIS)

Bousquet, B.; Sirven, J.-B.; Canioni, L.

2007-01-01

A quantitative analysis of chromium in soil samples is presented. Different emission lines related to chromium are studied in order to select the best one for quantitative features. Important matrix effects are demonstrated from one soil to the other, preventing any prediction of concentration in different soils on the basis of a univariate calibration curve. Finally, a classification of the LIBS data based on a series of Principal Component Analyses (PCA) is applied to a reduced dataset of selected spectral lines related to the major chemical elements in the soils. LIBS data of heterogeneous soils appear to be widely dispersed, which leads to a reconsideration of the sampling step in the analysis process

High energy backscattering analysis using RUMP

International Nuclear Information System (INIS)

Doolittle, L.R.

1990-01-01

A backscattering analysis program such as RUMP fundamentally requires two reference sets of data in order to accomplish anything useful: stopping powers and scattering cross sections. Users of original versions of RUMP had to be satisfied with polynomial stopping powers geared for 1 to 3 MeV, and purely Rutherford scattering cross sections. As people increasingly turn to high beam energies to solve difficult materials analysis problems, RUMP has evolved greater flexibility for its reference data. It now allows data files to be loaded describing different stopping powers and arbitrary scattering cross sections. Auxiliary programs have been written to generate the reference data files, either from a theory or from measured reference data. Descriptions are given of both the underlying physics and the operational details of the software

Framework for Multidisciplinary Analysis, Design, and Optimization with High-Fidelity Analysis Tools

Science.gov (United States)

Orr, Stanley A.; Narducci, Robert P.

2009-01-01

A plan is presented for the development of a high fidelity multidisciplinary optimization process for rotorcraft. The plan formulates individual disciplinary design problems, identifies practical high-fidelity tools and processes that can be incorporated in an automated optimization environment, and establishes statements of the multidisciplinary design problem including objectives, constraints, design variables, and cross-disciplinary dependencies. Five key disciplinary areas are selected in the development plan. These are rotor aerodynamics, rotor structures and dynamics, fuselage aerodynamics, fuselage structures, and propulsion / drive system. Flying qualities and noise are included as ancillary areas. Consistency across engineering disciplines is maintained with a central geometry engine that supports all multidisciplinary analysis. The multidisciplinary optimization process targets the preliminary design cycle where gross elements of the helicopter have been defined. These might include number of rotors and rotor configuration (tandem, coaxial, etc.). It is at this stage that sufficient configuration information is defined to perform high-fidelity analysis. At the same time there is enough design freedom to influence a design. The rotorcraft multidisciplinary optimization tool is built and substantiated throughout its development cycle in a staged approach by incorporating disciplines sequentially.

Effects of Vegetarian Diets on Blood Lipids: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Science.gov (United States)

Wang, Fenglei; Zheng, Jusheng; Yang, Bo; Jiang, Jiajing; Fu, Yuanqing; Li, Duo

2015-10-27

Vegetarian diets exclude all animal flesh and are being widely adopted by an increasing number of people; however, effects on blood lipid concentrations remain unclear. This meta-analysis aimed to quantitatively assess the overall effects of vegetarian diets on blood lipids. We searched PubMed, Scopus, Embase, ISI Web of Knowledge, and the Cochrane Library through March 2015. Studies were included if they described the effectiveness of vegetarian diets on blood lipids (total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglyceride). Weighted mean effect sizes were calculated for net changes by using a random-effects model. We performed subgroup and univariate meta-regression analyses to explore sources of heterogeneity. Eleven trials were included in the meta-analysis. Vegetarian diets significantly lowered blood concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and non-high-density lipoprotein cholesterol, and the pooled estimated changes were -0.36 mmol/L (95% CI -0.55 to -0.17; PVegetarian diets did not significantly affect blood triglyceride concentrations, with a pooled estimated mean difference of 0.04 mmol/L (95% CI -0.05 to 0.13; P=0.40). This systematic review and meta-analysis provides evidence that vegetarian diets effectively lower blood concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and non-high-density lipoprotein cholesterol. Such diets could be a useful nonpharmaceutical means of managing dyslipidemia, especially hypercholesterolemia. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

CMMI High Maturity Measurement and Analysis Workshop Report: March 2008

National Research Council Canada - National Science Library

Stoddard, II, Robert W; Goldenson, Dennis R; Zubrow, Dave; Harper, Erin

2008-01-01

.... In response to the need for clarification and guidance on implementing measurement and analysis in the context of high maturity processes, members of the SEI s Software Engineering Measurement and Analysis (SEMA...

[High activity antiretroviral therapy change associated to adverse drug reactions in a specialized center in Venezuela].

Science.gov (United States)

Subiela, José D; Dapena, Elida

2016-03-01

Adverse drug reactions (ADRs) represent the first cause of change of the first-line highly active antiretroviral therapy (HAART) regimen, therefore, they constitute the main limiting factor in the long-term follow up of HIV patients in treatment. A retrospective study was carried out in a specialized center in Lara State, Venezuela, including 99 patients over 18 years of age who had change of first-line HAART regimen due to ADRs, between 2010 and 2013. The aims of this research were to describe the sociodemographic and clinical variables, frequency of ADRs related to change of HAART, duration of the first-line HAART regimen, to determine the drugs associated with ARVs and to identify the risk factors. The ADRs constituted 47.5% of all causes of change of first-line HAART regimen, the median duration was 1.08±0.28 years. The most frequent ADRs were anemia (34.3%), hypersensitivity reactions (20.2%) and gastrointestinal intolerance (13.1%). The most frequent ARV regimen type was the protease inhibitors-based regimen (59.6%), but zidovudine was the ARV most linked to ADRs (41.4%). The regression analysis showed increased risk of ADRs in singles and students in the univariate analysis and heterosexuals and homosexuals in multivariate analysis; and decreased risk in active workers. The present work shows the high prevalence of ADRs in the studied population and represents the first case-based study that describes the pharmacoepidemiology of a cohort of HIV-positive patients treated in Venezuela.

The Prognostic Value of International Prognostic Index and MIB-l Immunostaining of Peripheral Lymphoid Tissues and Bone Marrow in Patients with High-Grade Non-Hodgkin's Lymphoma

International Nuclear Information System (INIS)

Assem, M.M.

2001-01-01

Cell kinetic data are important indicator of the aggressiveness of tumour and clinical response. The Ki-67 antigen plays a pivotal role in maintaining cell proliferation and the expression of this antigen was found to be a valuable indicator for aggressive disease in a variety of neoplastic disorders. Aim of the study: This study aimed to assess the prognostic significance of the expression of Ki-67 antigen in peripheral lymphoid tissues and bone marrow, using the monoclonal antibody MIB-l that is applicable in formaline-fixed paraffin embedded samples in cases with high-grade non-Hodgkin's lymphomas. Material and methods: The MIB-I immunostaining was performed on 96 samples from 48 patients with high-grade non-Hodgkin's lymphomas. The study was performed on tissue sections, nodal or extra nodal, as well as on BM smears or BM paraffin embedded sections of same patients. Ki-67 index was determined using image analyzer. Results: Forty-five out of the studied 48 cases (93.8%) were positive with a median labelling index of 20.425% (Range, 0-58%). We were able to detect bone marrow involvement by detecting MIB-l positive cells in BM samples of 29 patients who were not morphologically diagnosed to have BM infiltration. There was a strong correlation between BM positivity for Ki-67 and Ki-67 labelling index (p < 0.001). Twenty-eight (58.3%) out of the studied 48 cases achieved complete remission (CR). The median duration of CR was 35 months (range, 8-42 months) and the overall survival at 48 months was 35.4% (median 22 months, 95% CI, 13-31 months). The median Ki-67 index (20.425%) was chosen as a cut-off level for statistical analysis of the variables that influence clinical outcome. The probability of inducing CR was associated with low and low intermediate International Prognostic Index (IPI) whereas a low growth fraction was associated, although not significant, with a trend toward a higher probability of inducing a CR. In univariate analysis, high MIB1 labelling

Small Renal Masses in Close Proximity to the Collecting System and Renal Sinus Are Enriched for Malignancy and High Fuhrman Grade and Should Be Considered for Early Intervention.

Science.gov (United States)

Correa, Andres F; Toussi, Amir; Amin, Milon; Hrebinko, Ronald L; Gayed, Bishoy A; Parwani, Anil V; Maranchie, Jodi K

2018-02-05

Recent reports show a correlation between renal tumor radiographic characteristics and pathologic features. We hypothesize that a more central location within the relatively hypoxic renal medulla might confer a more aggressive tumor phenotype. To test this, radiographic tumor characteristics were compared with tumor grade and histology. We retrospectively reviewed renal masses anatomic features with incidence of malignancy and high nuclear grade. A total of 334 renal tumors had information available for analysis. Univariate analysis showed that increasing endophycity and proximity to the collecting system (anatomical variable predictive of malignancy (odds ratio [OR], 3.58; 95% confidence interval [CI], 1.06-12.05; P = .04) and high nuclear grade (OR, 2.81; 95% CI, 1.44-5.51; P = .003). Malignancy and high tumor grade occur with much greater frequency when tumors are located deep in the kidney, in close proximity to the collecting system and renal sinus. Ninety-six percent of small renal masses in this region were cancers and nearly half were Fuhrman Grade 3 or 4, suggesting that these small centrally located tumors should be targeted for early intervention. Copyright © 2018 Elsevier Inc. All rights reserved.

CASAS: Cancer Survival Analysis Suite, a web based application.

Science.gov (United States)

Rupji, Manali; Zhang, Xinyan; Kowalski, Jeanne

2017-01-01

We present CASAS, a shiny R based tool for interactive survival analysis and visualization of results. The tool provides a web-based one stop shop to perform the following types of survival analysis:  quantile, landmark and competing risks, in addition to standard survival analysis.  The interface makes it easy to perform such survival analyses and obtain results using the interactive Kaplan-Meier and cumulative incidence plots.  Univariate analysis can be performed on one or several user specified variable(s) simultaneously, the results of which are displayed in a single table that includes log rank p-values and hazard ratios along with their significance. For several quantile survival analyses from multiple cancer types, a single summary grid is constructed. The CASAS package has been implemented in R and is available via http://shinygispa.winship.emory.edu/CASAS/. The developmental repository is available at https://github.com/manalirupji/CASAS/.

msBiodat analysis tool, big data analysis for high-throughput experiments.

Science.gov (United States)

Muñoz-Torres, Pau M; Rokć, Filip; Belužic, Robert; Grbeša, Ivana; Vugrek, Oliver

2016-01-01

Mass spectrometry (MS) are a group of a high-throughput techniques used to increase knowledge about biomolecules. They produce a large amount of data which is presented as a list of hundreds or thousands of proteins. Filtering those data efficiently is the first step for extracting biologically relevant information. The filtering may increase interest by merging previous data with the data obtained from public databases, resulting in an accurate list of proteins which meet the predetermined conditions. In this article we present msBiodat Analysis Tool, a web-based application thought to approach proteomics to the big data analysis. With this tool, researchers can easily select the most relevant information from their MS experiments using an easy-to-use web interface. An interesting feature of msBiodat analysis tool is the possibility of selecting proteins by its annotation on Gene Ontology using its Gene Id, ensembl or UniProt codes. The msBiodat analysis tool is a web-based application that allows researchers with any programming experience to deal with efficient database querying advantages. Its versatility and user-friendly interface makes easy to perform fast and accurate data screening by using complex queries. Once the analysis is finished, the result is delivered by e-mail. msBiodat analysis tool is freely available at http://msbiodata.irb.hr.

Towards high resolution polarisation analysis using double polarisation and ellipsoidal analysers

CERN Document Server

Martin-Y-Marero, D

2002-01-01

Classical polarisation analysis methods lack the combination of high resolution and high count rate necessary to cope with the demand of modern condensed-matter experiments. In this work, we present a method to achieve high resolution polarisation analysis based on a double polarisation system. Coupling this method with an ellipsoidal wavelength analyser, a high count rate can be achieved whilst delivering a resolution of around 10 mu eV. This method is ideally suited to pulsed sources, although it can be adapted to continuous sources as well. (orig.)

Analysis of High Plains Resource Risk and Economic Impacts

Energy Technology Data Exchange (ETDEWEB)

Tidwell, Vincent C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vargas, Vanessa N [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Shannon M [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Dealy, Bern Caudill [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shaneyfelt, Calvin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Smith, Braeton James [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moreland, Barbara Denise [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-04-01

The importance of the High Plains Aquifer is broadly recognized as is its vulnerability to continued overuse. T his study e xplore s how continued depletions of the High Plains Aquifer might impact both critical infrastructure and the economy at the local, r egional , and national scale. This analysis is conducted at the county level over a broad geographic region within the states of Kansas and Nebraska. In total , 140 counties that overlie the High Plains Aquifer in these two states are analyzed. The analysis utilizes future climate projections to estimate crop production. Current water use and management practices are projected into the future to explore their related impact on the High Plains Aquifer , barring any changes in water management practices, regulat ion, or policy. Finally, the impact of declining water levels and even exhaustion of groundwater resources are projected for specific sectors of the economy as well as particular elements of the region's critical infrastructure.

BEAMGAA. A chance for high precision analysis of big samples

International Nuclear Information System (INIS)

Goerner, W.; Berger, A.; Haase, O.; Segebade, Chr.; Alber, D.; Monse, G.

2005-01-01

In activation analysis of traces in small samples, the non-equivalence of the activating radiation doses of sample and calibration material gives rise to sometimes tolerable systematic errors. Conversely, analysis of major components usually demands high trueness and precision. To meet this, beam geometry activation analysis (BEAMGAA) procedures have been developed for instrumental photon (IPAA) and neutron activation analysis (INAA) in which the activating neutron/photon beam exhibits broad, flat-topped characteristics. This results in a very low lateral activating flux gradient compared to known radiation facilities, however, at significantly lower flux density. The axial flux gradient can be accounted for by a monitor-sample-monitor assembly. As a first approach, major components were determined in high purity substances as well as selenium in a cattle fodder additive. (author)

Multivariate analysis of prognostic factors for idiopathic sudden sensorineural hearing loss in children.

Science.gov (United States)

Chung, Jae Ho; Cho, Seok Hyun; Jeong, Jin Hyeok; Park, Chul Won; Lee, Seung Hwan

2015-09-01

To evaluate clinical characteristics and possible associated factors of idiopathic sudden sensorineural hearing loss (ISSNHL) in children using univariate and multivariate analyses. A retrospective case series with comparisons. From January 2007 to December 2013, medical records of 37 pediatric ISSNHL patients were reviewed to assess hearing recovery rate and examine factors associated with prognosis (gender; side of hearing loss; opposite side hearing loss; treatment onset; presence of vertigo, tinnitus, and ear fullness; initial hearing threshold), using univariate and multivariate analysis, and compare them with 276 adult ISSNHL patients. Pediatric patients comprised only 6.6% of pediatric/adult cases of ISSNHL, and those below 10 years old were only 0.7%. The overall recovery rates (complete and partial) of the pediatric and adult patients were 57.4% and 47.2%, respectively. The complete recovery rate of the pediatric group (46.6%) was higher than that of the adult group (30.8%, P = .040). According to multivariate analysis, absence of tinnitus, later onset of treatment, and higher hearing threshold at initial presentation were associated with a poor prognosis in pediatric ISSNHL. The recovery rate of ISSNHL in pediatric patients is higher than in adults, and the presence of tinnitus and earlier treatment onset is associated with favorable outcomes. 4. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

The prognostic value of time parameters in adjuvant radiotherapy of head and neck cancer. A retrospective analysis of 138 patients

International Nuclear Information System (INIS)

Dietl, B.; Schaefer, C.; Koelbl, O.

2005-01-01

Purpose: to answer the question, how the parameters waiting time, radiation treatment time and overall treatment time (OTT) influenced the endpoints overall (OS), event-free (EFS) and local recurrence-free survival (LRFS) in patients with locally advanced head-and-neck cancer, who had received postoperative radiotherapy. Patients and methods: 138 patients were included into a retrospective analysis from 10/1993 to 05/2000. Besides the time parameters waiting time, radiation treatment time and OTT, tumor- and therapy-related parameters (T-, N-, R-status, grading, tumor site, surgical technique, and postoperative hemoglobin < 12 g/dl) with potential impact on the endpoints were investigated in the univariate analysis (Kaplan-Meier log-rank test). Individual parameters with a significant impact (p = 0.05) were subjected to a multivariate Cox regression analysis. Results: besides a postoperative hemoglobin value < 12 g/dl, in the univariate analysis an OTT ≥ 105 days negatively influenced all endpoints, as well as a radiation treatment time ≥ 60 days. On multivariate Cox regression analysis, postoperative hemoglobin < 12 g/dl and an OTT ≥ 105 days were identified as independent negative prognostic factors for all endpoints. Conclusion: the waiting time should be managed according to the ASARA (as short as reasonably achievable) recommendation, radiation treatment should not be protracted exceeding an overall treatment of 105 days. Generally, time parameters should be routinely included in the standard tumor documentation, thus facilitating further evaluation of these prognostically relevant factors. (orig.)

Risk factors for surgical site infection following operative ankle fracture fixation.

Science.gov (United States)

Kelly, E G; Cashman, J P; Groarke, P J; Morris, S F

2013-09-01

Ankle fracture is a common injury and there is an increasingly greater emphasis on operative fixation. The purpose of the study was to determine the complication rate in this cohort of patients and, in doing so, determine risk factors which predispose to surgical site infection. A prospective cohort study was performed at a tertiary referral trauma center examining risk factors for surgical site infection in operatively treated ankle fractures. Univariate and multivariate analysis was performed. Female gender and advancing age were determined to be the risk factors in univariate analysis. Drain usage and peri-operative pyrexia were found to be significant for infection in multivariate analysis. This study allows surgeons to identify those at increased risk of infection and counsel them appropriately. It also allows for a high level of vigilance with regard to soft tissue handling intra-operatively in this higher risk group.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

Science.gov (United States)

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

High spatial resolution and high brightness ion beam probe for in-situ elemental and isotopic analysis

Science.gov (United States)

Long, Tao; Clement, Stephen W. J.; Bao, Zemin; Wang, Peizhi; Tian, Di; Liu, Dunyi

2018-03-01

A high spatial resolution and high brightness ion beam from a cold cathode duoplasmatron source and primary ion optics are presented and applied to in-situ analysis of micro-scale geological material with complex structural and chemical features. The magnetic field in the source as well as the influence of relative permeability of magnetic materials on source performance was simulated using COMSOL to confirm the magnetic field strength of the source. Based on SIMION simulation, a high brightness and high spatial resolution negative ion optical system has been developed to achieve Critical (Gaussian) illumination mode. The ion source and primary column are installed on a new Time-of-Flight secondary ion mass spectrometer for analysis of geological samples. The diameter of the ion beam was measured by the knife-edge method and a scanning electron microscope (SEM). Results show that an O2- beam of ca. 5 μm diameter with a beam intensity of ∼5 nA and an O- beam of ca. 5 μm diameter with a beam intensity of ∼50 nA were obtained, respectively. This design will open new possibilities for in-situ elemental and isotopic analysis in geological studies.

Survival benefit of radiotherapy to patients with small cell esophagus carcinoma: an analysis of Surveillance Epidemiology and End Results (SEER) data.

Science.gov (United States)

Song, Yaqi; Wang, Wanwei; Tao, Guangzhou; Zhu, Weiguo; Zhou, Xilei; Pan, Peng

2016-03-29

Small cell esophageal carcinoma (SCEC) is a rare malignant tumor. So far, few studies are found to research the effect of radiotherapy (RT) to it. This study is designed to explore the prognostic factors, and analyze survival benefit of RT to patients with SCEC. Patients with SCEC were more likely to be in female, older, higher disease stage than those with non-small cell esophageal carcinoma. RT was used in more than 50% SCEC patients. RT tended be reduced as the disease stage raise in SCEC. Univariate and multivariate analysis showed that age, year, disease stage, and RT were the prognostic factors of survival (P 0.05) and nearly 30% risks of death in distant stage (P > 0.05). SCEC patients between 1973 and 2012 were searched from the Surveillance Epidemiology and End Results (SEER) data. Clinical factors including age, year, sex, race, stage, surgery, and RT were summarized. Univariate and multivariate analysis were performed to explore the independent prognostic factors of SCEC. Cox regression survival analysis was performed to evaluate the effect of RT to SCEC based on different stages. Stage, age, year, and RT are independent prognostic factors of SCEC. Survival benefit of RT exists in any disease stage, but is only statistically significant in localized stage of SCEC.

Advanced Analysis Methods in High Energy Physics

Energy Technology Data Exchange (ETDEWEB)

Pushpalatha C. Bhat

2001-10-03

During the coming decade, high energy physics experiments at the Fermilab Tevatron and around the globe will use very sophisticated equipment to record unprecedented amounts of data in the hope of making major discoveries that may unravel some of Nature's deepest mysteries. The discovery of the Higgs boson and signals of new physics may be around the corner. The use of advanced analysis techniques will be crucial in achieving these goals. The author discusses some of the novel methods of analysis that could prove to be particularly valuable for finding evidence of any new physics, for improving precision measurements and for exploring parameter spaces of theoretical models.

Predictive factors for complete removal in soft tissue sarcomas: a retrospective analysis in a series of 592 cases.

Science.gov (United States)

Sastre-Garau, X; Coindre, J M; Leroyer, A; Terrier, P; Ollivier, L; Stöckle, E; Bonichon, F; Collin, F; Le Doussal, V; Contesso, G; Vilain, M O; Jacquemier, J; Nguyen, B B

1997-07-01

In order to specify the indications for conservative surgery and preoperative therapeutic approaches of soft tissues sarcomas (STS), we looked for the clinico-pathological parameters associated with the failure to obtain a complete removal (CRm) of the tumor. We retrospectively analyzed a series of 592 cases of primary non-metastatic STS. Surgery was performed in 495 cases as a primary treatment and in 88 cases after chemo- or radiotherapy. Nine patients were treated by chemotherapy-radiotherapy. In a univariate analysis, 20 parameters were tested for their association with CRm. A multivariate analysis was then used to define the independent parameters linked to the achievement of a CRm. In the univariate analysis, 15 parameters were found to be linked to the achievement of a CRm. Three of them proved to be independent in the multivariate analysis: T in the TNM classification, tumor location, and tumor necrosis. By the combination of these risk factors, four groups of patients were defined, with respective rates of CRm of 97% (no factor), 95% (one factor), 70% (two factors), and 48% (three factors). The achievement of a CRm after surgery of STS depends not only on the accessibility of the lesion, but also on tumor aggressiveness, a reflection of which is necrosis. The detection of necrosis by imaging procedures may thus help predicting the resectability of tumors and defining the indications for neoadjuvant therapies, likely to broaden the use of conservative surgery.

Prognostic Value of microRNA-9 in Various Cancers: a Meta-analysis.

Science.gov (United States)

Zhang, Yunyuan; Zhou, Jun; Sun, Meiling; Sun, Guirong; Cao, Yongxian; Zhang, Haiping; Tian, Runhua; Zhou, Lan; Duan, Liang; Chen, Xian; Lun, Limin

2017-07-01

Recently, there are more and more evidences from studies have revealed the association between microRNA-9 (miR-9) expression and outcome in multiple cancers, but inconsistent results have also been reported. It is necessary to rationalize a meta analysis of all available data to clarify the prognostic role of miR-9. Eligible studies were selected through multiple search strategies and the quality was assessed by MOOSE. Data was extracted from studies according to the key statistics index. All analyses were performed using STATA software. Twenty studies were selected in the meta-analysis to evaluate the prognostic role of miR-9 in multiple tumors. MiR-9 expression level was an independent prognostic biomarker for OS in tumor patients using multivariate and univariate analyses. High expression levels of miR-9 was demonstrated to associated with poor overall survival (OS) (HR = 2.23, 95 % CI: 1.56-3.17, P analysis showed that residence region (China and Japan), sample size, cancer type (solid or leukemia), follow-up months and analysis method (qPCR) did not alter the predictive value of miR-9 on OS in various cancers. Furthermore, no significant associations were detected for miR-9 expression and lymph node metastasis or distant metastasis. The present results suggest that promoted miR-9 expression is associated with poor OS in patients with general cancers.

Solving nonlinear, High-order partial differential equations using a high-performance isogeometric analysis framework

KAUST Repository

Cortes, Adriano Mauricio; Vignal, Philippe; Sarmiento, Adel; Garcí a, Daniel O.; Collier, Nathan; Dalcin, Lisandro; Calo, Victor M.

2014-01-01

In this paper we present PetIGA, a high-performance implementation of Isogeometric Analysis built on top of PETSc. We show its use in solving nonlinear and time-dependent problems, such as phase-field models, by taking advantage of the high-continuity of the basis functions granted by the isogeometric framework. In this work, we focus on the Cahn-Hilliard equation and the phase-field crystal equation.

FUNSTAT and statistical image representations

Science.gov (United States)

Parzen, E.

1983-01-01

General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.

Prognostic impact of the level of nodal involvement: retrospective analysis of patients with advanced oral squamous cell carcinoma.

Science.gov (United States)

Murakami, R; Nakayama, H; Semba, A; Hiraki, A; Nagata, M; Kawahara, K; Shiraishi, S; Hirai, T; Uozumi, H; Yamashita, Y

2017-01-01

We retrospectively evaluated the prognostic impact of the level of nodal involvement in patients with advanced oral squamous cell carcinoma (SCC). Between 2005 and 2010, 105 patients with clinical stage III or IV oral SCC had chemoradiotherapy preoperatively. Clinical (cN) and pathological nodal (pN) involvement was primarily at levels Ib and II. We defined nodal involvement at levels Ia and III-V as anterior and inferior extensions, respectively, and recorded such findings as extensive. With respect to pretreatment variables (age, clinical stage, clinical findings of the primary tumour, and nodal findings), univariate analysis showed that extensive cN was the only significant factor for overall survival (hazard ratio [HR], 3.27; 95% CI 1.50 to 7.13; p=0.001). Univariate analysis showed that all pN findings, including the nodal classification (invaded nodes, multiple, and contralateral) and extensive involvement were significant, and multivariate analysis confirmed that extensive pN (HR 4.71; 95% CI 1.85 to 11.97; p=0.001) and multiple pN (HR 2.59; 95% CI 1.10 to 6.09; p=0.029) were independent predictors of overall survival. Assessment based on the level of invaded neck nodes may be a better predictor of survival than the current nodal classification. Copyright © 2016 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

High priority tank sampling and analysis report

Energy Technology Data Exchange (ETDEWEB)

Brown, T.M.

1998-03-05

In July 1993, the Defense Nuclear Facilities Safety Board (DNFSB) transmitted Recommendation 93-5 (Conway 1993) to the US Department of Energy (DOE). Recommendation 93-5 noted that there was insufficient tank waste technical information and the pace to obtain it was too slow to ensure that Hanford Site wastes could be safely stored, that associated operations could be conducted safely, and that future disposal data requirements could be met. In May 1996, the DOE issued Revision 1 of the Recommendation 93-5 Implementation Plan (DOE-RL 1996). The Implementation Plan revision presented a modified approach to achieve the original plan`s objectives. The approach concentrated on actions necessary to ensure that wastes can be safely stored, that operations can be safely conducted, and that timely characterization information for the tank waste Disposal Program could be obtained. The Implementation Plan proposed 28 High Priority tanks, which, if sampled and analyzed, were expected to provide information to answer questions regarding safety and disposal issues. The High Priority tank list was originally developed in Section 9.0 of the Tank Waste Characterization Basis (Brown et al. 1995) by integrating the needs of the various safety and disposal programs. The High Priority tank list represents a set of tanks that were expected to provide the highest information return for characterization resources expended. The High Priority tanks were selected for near-term core sampling and were not expected to be the only tanks that would provide meaningful information. Sampling and analysis of non-High Priority tanks also could be used to provide scientific and technical data to confirm assumptions, calibrate models, and measure safety related phenomenological characteristics of the waste. When the sampling and analysis results of the High Priority and other tanks were reviewed, it was expected that a series of questions should be answered allowing key decisions to be made. The first

High priority tank sampling and analysis report

International Nuclear Information System (INIS)

Brown, T.M.

1998-01-01

In July 1993, the Defense Nuclear Facilities Safety Board (DNFSB) transmitted Recommendation 93-5 (Conway 1993) to the US Department of Energy (DOE). Recommendation 93-5 noted that there was insufficient tank waste technical information and the pace to obtain it was too slow to ensure that Hanford Site wastes could be safely stored, that associated operations could be conducted safely, and that future disposal data requirements could be met. In May 1996, the DOE issued Revision 1 of the Recommendation 93-5 Implementation Plan (DOE-RL 1996). The Implementation Plan revision presented a modified approach to achieve the original plan's objectives. The approach concentrated on actions necessary to ensure that wastes can be safely stored, that operations can be safely conducted, and that timely characterization information for the tank waste Disposal Program could be obtained. The Implementation Plan proposed 28 High Priority tanks, which, if sampled and analyzed, were expected to provide information to answer questions regarding safety and disposal issues. The High Priority tank list was originally developed in Section 9.0 of the Tank Waste Characterization Basis (Brown et al. 1995) by integrating the needs of the various safety and disposal programs. The High Priority tank list represents a set of tanks that were expected to provide the highest information return for characterization resources expended. The High Priority tanks were selected for near-term core sampling and were not expected to be the only tanks that would provide meaningful information. Sampling and analysis of non-High Priority tanks also could be used to provide scientific and technical data to confirm assumptions, calibrate models, and measure safety related phenomenological characteristics of the waste. When the sampling and analysis results of the High Priority and other tanks were reviewed, it was expected that a series of questions should be answered allowing key decisions to be made. The first

Cross-Sectional Analysis of Neurocognitive Function, Retinopathy, and Retinal Thinning by Spectral-Domain Optical Coherence Tomography in Sickle Cell Patients.

Science.gov (United States)

Oltra, Erica Z; Chow, Clement C; Wubben, Thomas; Lim, Jennifer I; Chau, Felix Y; Moss, Heather E

2016-01-01

The purpose was to examine the relationship between neurocognitive function and two distinct forms of retinopathy in sickle cell disease. Patients with sickle cell disease (n = 44, age range: 19-56 years, 70% female) were prospectively recruited for this cross-sectional study. Retinopathy was characterized by: (1) Presence of focal retinal thinning on spectral domain optical coherence tomography and (2) determination of the sickle retinopathy stage on funduscopic exam based on Goldberg classification. Neurocognitive function was assessed using the Philadelphia Brief Assessment of Cognition (PBAC), a validated test of cognition. Univariate and multivariate analyses for PBAC score outcomes were performed. Retinal thinning and retinopathy stage were primary variables of interest and age, gender, genotype, education, and history of stroke were covariates. Univariate analysis revealed associations with total PBAC score and age (P = 0.049), history of stroke (P = 0.04), and genotype (P retinopathy stage were not associated with each other in this sample. Neither the presence of focal retinal thinning nor degree of retinopathy was associated with total PBAC score in univariate or multivariate analyses. We find an association between lower cognitive function and older age, history of stroke and sickle cell genotype SS in patients with sickle cell disease. Our data do not provide evidence to support an association between cognitive function and retinopathy in sickle cell patients.

SEISMIC Analysis of high-rise buildings with composite metal damper

Directory of Open Access Journals (Sweden)

Chen Ruixue

2015-01-01

Full Text Available This paper mainly studies on the mechanical characteristics and application effect of composite metal damper in the high-rise buildings via the numerical simulation analysis. The research adopts the elastic and elastic-plastic dynamic approach and the displacement time history response and damper energy dissipation capacity and so on of the high-rise building are compared and analyzed before and after installation. The analysis found that the energy dissipation characteristic of metallic dampers is good. High-rise building story drift significantly is reduced and the extent of damage of the walls and coupling beams is decreased, achieved a good energy dissipation effect. Composite metal damper can effectively and economically improve the seismic performance of high-rise buildings, meet the requirement of the 3-level design for seismic resistance. The result has certain reference significance for the application of metallic damper in the high-rise buildings.

Some aspects of ICP-AES analysis of high purity rare earths

International Nuclear Information System (INIS)

Murty, P.S.; Biswas, S.S.

1991-01-01

Inductively coupled plasma atomic emission spectrometry (ICP-AES) is a technique capable of giving high sensitivity in trace elemental analysis. While the technique possesses high sensitivity, it lacks high selectivity. Selectivity is important where substances emitting complex spectra are to be analysed for trace elements. Rare earths emit highly complex spectra in a plasma source and the determination of adjacent rare earths in a high purity rare earth matrix, with high sensitivity, is not possible due to the inadequate selectivity of ICP-AES. One approach that has yielded reasonably good spectral selectivity in the high purity rare earth analysis by ICP-AES is by employing a combination of wavelength modulation techniques and high resolution echelle grating. However, it was found that by using a high resolution monochromator senstitivities either comparable to or better than those reported by the wavelength modulation technique could be obtained. (author). 2 refs., 2 figs., 2 tabs

Analysis of Discrete L2 Projection on Polynomial Spaces with Random Evaluations

KAUST Repository

Migliorati, Giovanni; Nobile, Fabio; von Schwerin, Erik; Tempone, Raul

2014-01-01

We analyze the problem of approximating a multivariate function by discrete least-squares projection on a polynomial space starting from random, noise-free observations. An area of possible application of such technique is uncertainty quantification for computational models. We prove an optimal convergence estimate, up to a logarithmic factor, in the univariate case, when the observation points are sampled in a bounded domain from a probability density function bounded away from zero and bounded from above, provided the number of samples scales quadratically with the dimension of the polynomial space. Optimality is meant in the sense that the weighted L2 norm of the error committed by the random discrete projection is bounded with high probability from above by the best L∞ error achievable in the given polynomial space, up to logarithmic factors. Several numerical tests are presented in both the univariate and multivariate cases, confirming our theoretical estimates. The numerical tests also clarify how the convergence rate depends on the number of sampling points, on the polynomial degree, and on the smoothness of the target function. © 2014 SFoCM.

Analysis of Discrete L2 Projection on Polynomial Spaces with Random Evaluations

KAUST Repository

Migliorati, Giovanni

2014-03-05

We analyze the problem of approximating a multivariate function by discrete least-squares projection on a polynomial space starting from random, noise-free observations. An area of possible application of such technique is uncertainty quantification for computational models. We prove an optimal convergence estimate, up to a logarithmic factor, in the univariate case, when the observation points are sampled in a bounded domain from a probability density function bounded away from zero and bounded from above, provided the number of samples scales quadratically with the dimension of the polynomial space. Optimality is meant in the sense that the weighted L2 norm of the error committed by the random discrete projection is bounded with high probability from above by the best L∞ error achievable in the given polynomial space, up to logarithmic factors. Several numerical tests are presented in both the univariate and multivariate cases, confirming our theoretical estimates. The numerical tests also clarify how the convergence rate depends on the number of sampling points, on the polynomial degree, and on the smoothness of the target function. © 2014 SFoCM.

High-throughput reactor system with individual temperature control for the investigation of monolith catalysts

Science.gov (United States)

Dellamorte, Joseph C.; Vijay, Rohit; Snively, Christopher M.; Barteau, Mark A.; Lauterbach, Jochen

2007-07-01

A high-throughput parallel reactor system has been designed and constructed to improve the reliability of results from large diameter catalysts such as monoliths. The system, which is expandable, consists of eight quartz reactors, 23.5mm in diameter. The eight reactors were designed with separate K type thermocouples and radiant heaters, allowing for the independent measurement and control of each reactor temperature. This design gives steady state temperature distributions over the eight reactors within 0.5°C of a common setpoint from 50to700°C. Analysis of the effluent from these reactors is performed using rapid-scan Fourier transform infrared (FTIR) spectroscopic imaging. The integration of this technique to the reactor system allows a chemically specific, truly parallel analysis of the reactor effluents with a time resolution of approximately 8s. The capabilities of this system were demonstrated via investigation of catalyst preparation conditions on the direct epoxidation of ethylene, i.e., on the ethylene conversion and the ethylene oxide selectivity. The ethylene, ethylene oxide, and carbon dioxide concentrations were calibrated based on spectra from FTIR imaging using univariate and multivariate chemometric techniques. The results from this analysis showed that the calcination conditions significantly affect the ethylene conversion, with a threefold increase in the conversion when the catalyst was calcined for 3h versus 12h at 400°C.

High Accuracy, High Energy He-Erd Analysis of H,C, and T

International Nuclear Information System (INIS)

Browning, James F.; Langley, Robert A.; Doyle, Barney L.; Banks, James C.; Wampler, William R.

1999-01-01

A new analysis technique using high-energy helium ions for the simultaneous elastic recoil detection of all three hydrogen isotopes in metal hydride systems extending to depths of several microm's is presented. Analysis shows that it is possible to separate each hydrogen isotope in a heavy matrix such as erbium to depths of 5 microm using incident 11.48MeV 4 He 2 ions with a detection system composed of a range foil and ΔE-E telescope detector. Newly measured cross sections for the elastic recoil scattering of 4 He 2 ions from protons and deuterons are presented in the energy range 10 to 11.75 MeV for the laboratory recoil angle of 30degree

Spatio-spectral analysis of ionization times in high-harmonic generation

Energy Technology Data Exchange (ETDEWEB)

Soifer, Hadas, E-mail: hadas.soifer@weizmann.ac.il [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel); Dagan, Michal; Shafir, Dror; Bruner, Barry D. [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel); Ivanov, Misha Yu. [Department of Physics, Imperial College London, South Kensington Campus, SW7 2AZ London (United Kingdom); Max-Born Institute for Nonlinear Optics and Short Pulse Spectroscopy, Max-Born-Strasse 2A, D-12489 Berlin (Germany); Serbinenko, Valeria; Barth, Ingo; Smirnova, Olga [Max-Born Institute for Nonlinear Optics and Short Pulse Spectroscopy, Max-Born-Strasse 2A, D-12489 Berlin (Germany); Dudovich, Nirit [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel)

2013-03-12

Graphical abstract: A spatio-spectral analysis of the two-color oscillation phase allows us to accurately separate short and long trajectories and reconstruct their ionization times. Highlights: ► We perform a complete spatio-spectral analysis of the high harmonic generation process. ► We analyze the ionization times across the entire spatio-spectral plane of the harmonics. ► We apply this analysis to reconstruct the ionization times of both short and long trajectories. - Abstract: Recollision experiments have been very successful in resolving attosecond scale dynamics. However, such schemes rely on the single atom response, neglecting the macroscopic properties of the interaction and the effects of using multi-cycle laser fields. In this paper we perform a complete spatio-spectral analysis of the high harmonic generation process and resolve the distribution of the subcycle dynamics of the recolliding electron. Specifically, we focus on the measurement of ionization times. Recently, we have demonstrated that the addition of a weak, crossed polarized second harmonic field allows us to resolve the moment of ionization (Shafir, 2012) [1]. In this paper we extend this measurement and perform a complete spatio-spectral analysis. We apply this analysis to reconstruct the ionization times of both short and long trajectories showing good agreement with the quantum path analysis.

Differentiating high-grade from low-grade chondrosarcoma with MR imaging

Energy Technology Data Exchange (ETDEWEB)

Yoo, Hye Jin; Hong, Sung Hwan; Choi, Ja-Young; Choi, Jung-Ah; Kang, Heung Sik [Seoul National University College of Medicine, Department of Radiology and Institute of Radiation Medicine, Seoul (Korea); Moon, Kyung Chul [Seoul National University College of Medicine, Department of Pathology, Seoul (Korea); Kim, Han-Soo [Seoul National University College of Medicine, Department of Orthopedic Surgery, Seoul (Korea)

2009-12-15

The purpose of the study was to evaluate the MR imaging features that differentiate between low-grade chondrosarcoma (LGCS) and high-grade chondrosarcoma (HGCS) and to determine the most reliable predictors for differentiation. MR images of 42 pathologically proven chondrosarcomas (28 LGCS and 14 HGCS) were retrospectively reviewed. There were 13 male and 29 female patients with an age range of 23-72 years (average age 51 years). On MR images, signal intensity, specific morphological characteristics including entrapped fat, internal lobular architecture, and outer lobular margin, soft tissue mass formation and contrast enhancement pattern were analysed. MR imaging features used to identify LGCS and HGCS were compared using univariate analysis and multivariate stepwise logistic regression analysis. On T1-weighted images, a central area of high signal intensity, which was not seen in LGCS, was frequently observed in HGCS (n = 5, 36%) (p < 0.01). Entrapped fat within the tumour was commonly seen in LGCS (n = 26, 93%), but not in HGCS (n = 1, 4%) (p < 0.01). LGCS more commonly (n = 24, 86%) preserved the characteristic internal lobular structures within the tumour than HGCSs (n = 4, 29%) (p < 0.01). Soft tissue formation was more frequently observed in HGCS (n = 11, 79%) than in LGCS (n = 1, 4%) (p < 0.01). On gadolinium-enhanced images, large central nonenhancing areas were exhibited in only two (7.1%) of LGCS, while HGCS frequently (n = 9, 64%) had a central nonenhancing portion (p < 0.01). Results of multivariate stepwise logistic regression analysis showed that soft tissue formation and entrapped fat within the tumour were the variables that could be used to independently differentiate LGCS from HGCS. There were several MR imaging features of chondrosarcoma that could be helpful in distinguishing HGCS from LGCS. Among them, soft tissue mass formation favoured the diagnosis of HGCS, and entrapped fat within the tumour was highly indicative of LGCS. (orig.)

Differentiating high-grade from low-grade chondrosarcoma with MR imaging

International Nuclear Information System (INIS)

Yoo, Hye Jin; Hong, Sung Hwan; Choi, Ja-Young; Choi, Jung-Ah; Kang, Heung Sik; Moon, Kyung Chul; Kim, Han-Soo

2009-01-01

The purpose of the study was to evaluate the MR imaging features that differentiate between low-grade chondrosarcoma (LGCS) and high-grade chondrosarcoma (HGCS) and to determine the most reliable predictors for differentiation. MR images of 42 pathologically proven chondrosarcomas (28 LGCS and 14 HGCS) were retrospectively reviewed. There were 13 male and 29 female patients with an age range of 23-72 years (average age 51 years). On MR images, signal intensity, specific morphological characteristics including entrapped fat, internal lobular architecture, and outer lobular margin, soft tissue mass formation and contrast enhancement pattern were analysed. MR imaging features used to identify LGCS and HGCS were compared using univariate analysis and multivariate stepwise logistic regression analysis. On T1-weighted images, a central area of high signal intensity, which was not seen in LGCS, was frequently observed in HGCS (n = 5, 36%) (p < 0.01). Entrapped fat within the tumour was commonly seen in LGCS (n = 26, 93%), but not in HGCS (n = 1, 4%) (p < 0.01). LGCS more commonly (n = 24, 86%) preserved the characteristic internal lobular structures within the tumour than HGCSs (n = 4, 29%) (p < 0.01). Soft tissue formation was more frequently observed in HGCS (n = 11, 79%) than in LGCS (n = 1, 4%) (p < 0.01). On gadolinium-enhanced images, large central nonenhancing areas were exhibited in only two (7.1%) of LGCS, while HGCS frequently (n = 9, 64%) had a central nonenhancing portion (p < 0.01). Results of multivariate stepwise logistic regression analysis showed that soft tissue formation and entrapped fat within the tumour were the variables that could be used to independently differentiate LGCS from HGCS. There were several MR imaging features of chondrosarcoma that could be helpful in distinguishing HGCS from LGCS. Among them, soft tissue mass formation favoured the diagnosis of HGCS, and entrapped fat within the tumour was highly indicative of LGCS. (orig.)

The expression of cytoglobin as a prognostic factor in gliomas: a retrospective analysis of 88 patients

International Nuclear Information System (INIS)

Xu, Hong-Wu; Huang, Hai-Hua; Wei, Xiao-Long; Man, Kwan; Zhang, Guo-Jun; Huang, Yue-Jun; Xie, Ze-Yu; Lin, Lan; Guo, Yan-Chun; Zhuang, Ze-Rui; Lin, Xin-Peng; Zhou, Wen; Li, Mu

2013-01-01

Evidence suggests that cytoglobin (Cygb) may function as a tumor suppressor gene. We immunohistochemically evaluated the expression of Cygb, phosphatidylinositol-3 kinase (PI-3K), phosphorylated (p)-Akt, Interleukin-6 (IL-6), tumor necrosis factor-α (TNFα) and vascular endothelial growth factor (VEGF) in 88 patients with 41 high-grade gliomas and 47 low-grade gliomas. Intratumoral microvessel density (IMD) was also determined and associated with clinicopathological factors. Low expression of Cygb was significantly associated with the higher histological grading and tumor recurrence. A significant negative correlation emerged between Cygb expression and PI3K, p-Akt, IL-6, TNFα or VEGF expression. Cygb expression was negatively correlated with IMD. There was a positive correlation between PI3K, p-Akt, IL-6, TNFα and VEGF expression with IMD.High histologic grade, tumor recurrence, decreased Cygb expression, increased PI3K expression, increased p-Akt expression and increased VEGF expression correlated with patients’ overall survival in univariate analysis. However, only histological grading and Cygb expression exhibited a relationship with survival of patients as independent prognostic factors of glioma by multivariate analysis. Cygb loss may contribute to tumor recurrence and a worse prognosis in gliomas. Cygb may serve as an independent predictive factor for prognosis of glioma patients

Power analysis for multivariate and repeated measures designs: a flexible approach using the SPSS MANOVA procedure.

Science.gov (United States)

D'Amico, E J; Neilands, T B; Zambarano, R

2001-11-01

Although power analysis is an important component in the planning and implementation of research designs, it is often ignored. Computer programs for performing power analysis are available, but most have limitations, particularly for complex multivariate designs. An SPSS procedure is presented that can be used for calculating power for univariate, multivariate, and repeated measures models with and without time-varying and time-constant covariates. Three examples provide a framework for calculating power via this method: an ANCOVA, a MANOVA, and a repeated measures ANOVA with two or more groups. The benefits and limitations of this procedure are discussed.

Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

Science.gov (United States)

Xia, Jianguo; Wishart, David S

2016-09-07

MetaboAnalyst (http://www.metaboanalyst.ca) is a comprehensive Web application for metabolomic data analysis and interpretation. MetaboAnalyst handles most of the common metabolomic data types from most kinds of metabolomics platforms (MS and NMR) for most kinds of metabolomics experiments (targeted, untargeted, quantitative). In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst also supports a number of data analysis and data visualization tasks using a range of univariate, multivariate methods such as PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), heatmap clustering and machine learning methods. MetaboAnalyst also offers a variety of tools for metabolomic data interpretation including MSEA (metabolite set enrichment analysis), MetPA (metabolite pathway analysis), and biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. This unit provides an overview of the main functional modules and the general workflow of the latest version of MetaboAnalyst (MetaboAnalyst 3.0), followed by eight detailed protocols. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Dose-volume histogram analysis as predictor of radiation pneumonitis in primary lung cancer patients treated with radiotherapy

International Nuclear Information System (INIS)

Fay, Michael; Tan, Alex; Fisher, Richard; Mac Manus, Michael; Wirth, Andrew; Ball, David

2005-01-01

Purpose: To determine the relationship between various parameters derived from lung dose-volume histogram analysis and the risk of symptomatic radiation pneumonitis (RP) in patients undergoing radical radiotherapy for primary lung cancer. Methods and Materials: The records of 156 patients with lung cancer who had been treated with radical radiotherapy (≥45 Gy) and for whom dose-volume histogram data were available were reviewed. The incidence of symptomatic RP was correlated with a variety of parameters derived from the dose-volume histogram data, including the volume of lung receiving 10 Gy (V 10 ) through 50 Gy (V 50 ) and the mean lung dose (MLD). Results: The rate of RP at 6 months was 15% (95% confidence interval 9-22%). On univariate analysis, only V 30 (p = 0.036) and MLD (p = 0.043) were statistically significantly related to RP. V 30 correlated highly positively with MLD (r = 0.96, p 30 and MLD can be used to predict the risk of RP in lung cancer patients undergoing radical radiotherapy

High spirituality may be associated with right hemispheric lateralization in Korean adults living with epilepsy.

Science.gov (United States)

Lee, Sang-Ahm; Ko, Myung-Ah; Choi, Eun-Ju; Jeon, Ji-Ye; Ryu, Han Uk

2017-11-01

Although it is known that epilepsy and spirituality are related, spirituality in epilepsy has received relatively little clinical and scientific attention. Therefore, we investigated which epilepsy-related factors are associated with high spirituality in Korean adults living with epilepsy. This cross-sectional study was conducted in two university hospitals in Korea. Spirituality was assessed using the 6-item Spirituality Self-Rating Scale (SSRS). The participants were categorized into high and low spirituality groups according to the median SSRS score. The presumptive seizure onset zone was determined based on the clinical semiology, electroencephalography, and magnetic resonance imaging findings. Of the 180 participants, 61.7% declared that they had a religious affiliation. The median SSRS score was 15 (interquartile range: 7, 22). The high spirituality subgroup consisted of 92 (51.1%) participants. In the univariate analyses, the high spirituality group was significantly associated with female sex (p<0.05), older age (p<0.01), longer epilepsy duration (p<0.05), polytherapy (p<0.05), complex partial seizure (p<0.05), levetiracetam or topiramate usage (p<0.05), and a right-lateralized seizure onset zone. The multiple logistic regression analysis identified right hemispheric lateralization as the only independent factor associated with high spirituality (odds ratio: 2.410, 95% confidence interval: 1.051-5.528, p<0.05). High spirituality may be associated with right hemispheric lateralization but not with the temporal localization of the seizure onset zone in Korean adults with epilepsy. Copyright © 2017 Elsevier Inc. All rights reserved.

High ALK mRNA expression has a negative prognostic significance in rhabdomyosarcoma

Science.gov (United States)

Bonvini, P; Zin, A; Alaggio, R; Pawel, B; Bisogno, G; Rosolen, A

2013-01-01

Background: Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase aberrantly expressed in cancer, but its clinical and functional importance remain controversial. Mutation or amplification of ALK, as well as its expression levels assessed by conventional immunohistochemistry methods, has been linked to prognosis in cancer, although with potential bias because of the semi-quantitative approaches. Herein, we measured ALK mRNA expression in rhabdomyosarcoma (RMS) and determined its clinical impact on patients' stratification and outcome. Methods: Specimens were obtained from RMS patients and cell lines, and ALK expression was analysed by quantitative RT–PCR, western blotting, IHC, and copy number analysis. Results: High ALK mRNA expression was detected in the vast majority of PAX3/7-FOXO1-positive tumours, whereas PAX3/7-FOXO1-negative RMS displayed considerably lower amounts of both mRNA and protein. Notably, ALK mRNA distinguished unfavourable PAX3/7-FOXO1-positive tumours from PAX3/7-FOXO1-negative RMS (Ptumour size (PALK mRNA levels were of prognostic relevance by Cox univariate regression analysis and correlated with increased risk of relapse (P=0.001) and survival (P=0.01), whereas by multivariate analysis elevated ALK mRNA expression resulted a negative prognostic marker when clinical stage was not included. Conclusion: Quantitative assessment of ALK mRNA expression helps to improve risk stratification of RMS patients and identifies tumours with adverse biological characteristics and aggressive behaviour. PMID:24149177

Maintaining high precision of isotope ratio analysis over extended periods of time.

Science.gov (United States)

Brand, Willi A

2009-06-01

Stable isotope ratios are reliable and long lasting process tracers. In order to compare data from different locations or different sampling times at a high level of precision, a measurement strategy must include reliable traceability to an international stable isotope scale via a reference material (RM). Since these international RMs are available in low quantities only, we have developed our own analysis schemes involving laboratory working RM. In addition, quality assurance RMs are used to control the long-term performance of the delta-value assignments. The analysis schemes allow the construction of quality assurance performance charts over years of operation. In this contribution, the performance of three typical techniques established in IsoLab at the MPI-BGC in Jena is discussed. The techniques are (1) isotope ratio mass spectrometry with an elemental analyser for delta(15)N and delta(13)C analysis of bulk (organic) material, (2) high precision delta(13)C and delta(18)O analysis of CO(2) in clean-air samples, and (3) stable isotope analysis of water samples using a high-temperature reaction with carbon. In addition, reference strategies on a laser ablation system for high spatial resolution delta(13)C analysis in tree rings is exemplified briefly.

WE-E-17A-05: Complementary Prognostic Value of CT and 18F-FDG PET Non-Small Cell Lung Cancer Tumor Heterogeneity Features Quantified Through Texture Analysis

Energy Technology Data Exchange (ETDEWEB)

Desseroit, M; Cheze Le Rest, C; Tixier, F [CHU Poitiers Poitiers (France); INSERM LaTIM UMR 1101, Brest (France); Majdoub, M; Visvikis, D; Hatt, M [INSERM LaTIM UMR 1101, Brest (France); Guillevin, R; Perdrisot, R [CHU Poitiers Poitiers (France)

2014-06-15

Purpose: Previous studies have shown that CT or 18F-FDG PET intratumor heterogeneity features computed using texture analysis may have prognostic value in Non-Small Cell Lung Cancer (NSCLC), but have been mostly investigated separately. The purpose of this study was to evaluate the potential added value with respect to prognosis regarding the combination of non-enhanced CT and 18F-FDG PET heterogeneity textural features on primary NSCLC tumors. Methods: One hundred patients with non-metastatic NSCLC (stage I–III), treated with surgery and/or (chemo)radiotherapy, that underwent staging 18F-FDG PET/CT images, were retrospectively included. Morphological tumor volumes were semi-automatically delineated on non-enhanced CT using 3D SlicerTM. Metabolically active tumor volumes (MATV) were automatically delineated on PET using the Fuzzy Locally Adaptive Bayesian (FLAB) method. Intratumoral tissue density and FDG uptake heterogeneities were quantified using texture parameters calculated from co-occurrence, difference, and run-length matrices. In addition to these textural features, first order histogram-derived metrics were computed on the whole morphological CT tumor volume, as well as on sub-volumes corresponding to fine, medium or coarse textures determined through various levels of LoG-filtering. Association with survival regarding all extracted features was assessed using Cox regression for both univariate and multivariate analysis. Results: Several PET and CT heterogeneity features were prognostic factors of overall survival in the univariate analysis. CT histogram-derived kurtosis and uniformity, as well as Low Grey-level High Run Emphasis (LGHRE), and PET local entropy were independent prognostic factors. Combined with stage and MATV, they led to a powerful prognostic model (p<0.0001), with median survival of 49 vs. 12.6 months and a hazard ratio of 3.5. Conclusion: Intratumoral heterogeneity quantified through textural features extracted from both CT and FDG PET

A comparison of univariate and multivariate methods for analyzing clinal variation in an invasive species

Czech Academy of Sciences Publication Activity Database

Edwards, K.R.; Bastlová, D.; Edwards-Jonášová, Magda; Květ, J.

2011-01-01

Roč. 674, č. 1 (2011), s. 119-131 ISSN 0018-8158 Institutional research plan: CEZ:AV0Z60870520 Keywords : common garden * life history traits * local adaptation * principal components analysis * purple loosestrife * redundancy analysis Subject RIV: EH - Ecology, Behaviour Impact factor: 1.784, year: 2011 http://www.springerlink.com/content/71r10n3367m98jxl/

One Hundred Ways to be Non-Fickian - A Rigorous Multi-Variate Statistical Analysis of Pore-Scale Transport

Science.gov (United States)

Most, Sebastian; Nowak, Wolfgang; Bijeljic, Branko

2015-04-01

Fickian transport in groundwater flow is the exception rather than the rule. Transport in porous media is frequently simulated via particle methods (i.e. particle tracking random walk (PTRW) or continuous time random walk (CTRW)). These methods formulate transport as a stochastic process of particle position increments. At the pore scale, geometry and micro-heterogeneities prohibit the commonly made assumption of independent and normally distributed increments to represent dispersion. Many recent particle methods seek to loosen this assumption. Hence, it is important to get a better understanding of the processes at pore scale. For our analysis we track the positions of 10.000 particles migrating through the pore space over time. The data we use come from micro CT scans of a homogeneous sandstone and encompass about 10 grain sizes. Based on those images we discretize the pore structure and simulate flow at the pore scale based on the Navier-Stokes equation. This flow field realistically describes flow inside the pore space and we do not need to add artificial dispersion during the transport simulation. Next, we use particle tracking random walk and simulate pore-scale transport. Finally, we use the obtained particle trajectories to do a multivariate statistical analysis of the particle motion at the pore scale. Our analysis is based on copulas. Every multivariate joint distribution is a combination of its univariate marginal distributions. The copula represents the dependence structure of those univariate marginals and is therefore useful to observe correlation and non-Gaussian interactions (i.e. non-Fickian transport). The first goal of this analysis is to better understand the validity regions of commonly made assumptions. We are investigating three different transport distances: 1) The distance where the statistical dependence between particle increments can be modelled as an order-one Markov process. This would be the Markovian distance for the process, where

Experience with conventional inelastic analysis procedures in very high temperature applications

International Nuclear Information System (INIS)

Mallett, R.H.; Thompson, J.M.; Swindeman, R.W.

1991-01-01

Conventional incremental plasticity and creep analysis procedures for inelastic analysis are applied to hot flue gas cleanup system components. These flue gas systems operate at temperatures where plasticity and creep are very much intertwined while the two phenomena are treated separately in the conventional inelastic analysis procedure. Data for RA333 material are represented in forms appropriate for the conventional inelastic analysis procedures. Behavior is predicted for typical operating cycles. Creep-fatigue damage is estimated based upon usage fractions. Excessive creep damage is predicted; the major contributions occur during high stress short term intervals caused by rapid temperature changes. In this paper these results are presented for discussion of the results and their interpretation in terms of creep-fatigue damage for very high temperature applications

When Does Neoadjuvant Chemotherapy Really Avoid Radiotherapy? Clinical Predictors of Adjuvant Radiotherapy in Cervical Cancer.

Science.gov (United States)

Papadia, Andrea; Bellati, Filippo; Bogani, Giorgio; Ditto, Antonino; Martinelli, Fabio; Lorusso, Domenica; Donfrancesco, Cristina; Gasparri, Maria Luisa; Raspagliesi, Francesco

2015-12-01

The aim of this study was to identify clinical variables that may predict the need for adjuvant radiotherapy after neoadjuvant chemotherapy (NACT) and radical surgery in locally advanced cervical cancer patients. A retrospective series of cervical cancer patients with International Federation of Gynecology and Obstetrics (FIGO) stages IB2-IIB treated with NACT followed by radical surgery was analyzed. Clinical predictors of persistence of intermediate- and/or high-risk factors at final pathological analysis were investigated. Statistical analysis was performed using univariate and multivariate analysis and using a model based on artificial intelligence known as artificial neuronal network (ANN) analysis. Overall, 101 patients were available for the analyses. Fifty-two (51 %) patients were considered at high risk secondary to parametrial, resection margin and/or lymph node involvement. When disease was confined to the cervix, four (4 %) patients were considered at intermediate risk. At univariate analysis, FIGO grade 3, stage IIB disease at diagnosis and the presence of enlarged nodes before NACT predicted the presence of intermediate- and/or high-risk factors at final pathological analysis. At multivariate analysis, only FIGO grade 3 and tumor diameter maintained statistical significance. The specificity of ANN models in evaluating predictive variables was slightly superior to conventional multivariable models. FIGO grade, stage, tumor diameter, and histology are associated with persistence of pathological intermediate- and/or high-risk factors after NACT and radical surgery. This information is useful in counseling patients at the time of treatment planning with regard to the probability of being subjected to pelvic radiotherapy after completion of the initially planned treatment.

Prognostic value of the neutrophil to lymphocyte ratio in lung cancer: A meta-analysis.

Science.gov (United States)

Yin, Yongmei; Wang, Jun; Wang, Xuedong; Gu, Lan; Pei, Hao; Kuai, Shougang; Zhang, Yingying; Shang, Zhongbo

2015-07-01

Recently, a series of studies explored the correlation between the neutrophil to lymphocyte ratio and the prognosis of lung cancer. However, the current opinion regarding the prognostic role of the neutrophil to lymphocyte ratio in lung cancer is inconsistent. We performed a meta-analysis of published articles to investigate the prognostic value of the neutrophil to lymphocyte ratio in lung cancer. The hazard ratio (HR) and its 95% confidence interval (CI) were calculated. An elevated neutrophil to lymphocyte ratio predicted worse overall survival, with a pooled HR of 1.243 (95%CI: 1.106-1.397; P(heterogeneity)=0.001) from multivariate studies and 1.867 (95%CI: 1.487-2.344; P(heterogeneity)=0.047) from univariate studies. Subgroup analysis showed that a high neutrophil to lymphocyte ratio yielded worse overall survival in non-small cell lung cancer (NSCLC) (HR=1.192, 95%CI: 1.061-1.399; P(heterogeneity)=0.003) as well as small cell lung cancer (SCLC) (HR=1.550, 95% CI: 1.156-2.077; P(heterogeneity)=0.625) in multivariate studies. The synthesized evidence from this meta-analysis of published articles demonstrated that an elevated neutrophil to lymphocyte ratio was a predictor of poor overall survival in patients with lung cancer.

Local buckling failure analysis of high-strength pipelines

Institute of Scientific and Technical Information of China (English)

Yan Li; Jian Shuai; Zhong-Li Jin; Ya-Tong Zhao; Kui Xu

2017-01-01

Pipelines in geological disaster regions typically suffer the risk of local buckling failure because of slender structure and complex load.This paper is meant to reveal the local buckling behavior of buried pipelines with a large diameter and high strength,which are under different conditions,including pure bending and bending combined with internal pressure.Finite element analysis was built according to previous data to study local buckling behavior of pressurized and unpressurized pipes under bending conditions and their differences in local buckling failure modes.In parametric analysis,a series of parameters,including pipe geometrical dimension,pipe material properties and internal pressure,were selected to study their influences on the critical bending moment,critical compressive stress and critical compressive strain of pipes.Especially the hardening exponent of pipe material was introduced to the parameter analysis by using the Ramberg-Osgood constitutive model.Results showed that geometrical dimensions,material and internal pressure can exert similar effects on the critical bending moment and critical compressive stress,which have different,even reverse effects on the critical compressive strain.Based on these analyses,more accurate design models of critical bending moment and critical compressive stress have been proposed for high-strength pipelines under bending conditions,which provide theoretical methods for highstrength pipeline engineering.

Analysis of risk factors for non-anastomotic biliary stricture following liver transplantation

Directory of Open Access Journals (Sweden)

WU Xiaofeng

2013-06-01

Full Text Available ObjectiveTo investigate the risk factors for non-anastomotic biliary stricture (NABS following liver transplantation. MethodsA retrospective analysis was performed on 175 patients who underwent liver transplantation from January 2004 to December 2010 to analyze the risk factors for NABS, which included sex, age, primary disease, blood type, T-tube placement, acute rejection, biliary tract infection, cytomegalovirus infection, Child-Pugh score, cold ischemia time, warm ischemia time, duration of anhepatic phase, and mean hepatic artery blood flow within one week after operation. These patients were divided into early group, who underwent operation from January 2004 to December 2006, and late group, who underwent operation from January 2007 to December 2010; each group was further divided into two subgroups according to whether they developed NABS. The risk factors for NABS were determined by univariate and multivariate logistic regression analyses. ResultsThe univariate logistic regression analysis showed that the risk factors for NABS were biliary tract infection, T-tube placement, and acute rejection in the early group (P＜0.05 and that acute rejection was the risk factor in the late group (P=0003. The multivariate logistic regression analysis showed that acute rejection was significantly associated with NABS in the early group (P=0.014. ConclusionThe risk factors for NABS following liver transplantation from January 2004 to December 2006; biliary tract infection and T-tube placement could be prevented by perioperative interventions, thus reducing the incidence of NABS. The incidence of acute rejection was reduced from January 2007 to December 2010, but it was still significantly associated with NABS.

Safety analysis of a high temperature gas-cooled reactor

International Nuclear Information System (INIS)

Shimazu, Akira; Morimoto, Toshio

1975-01-01

In recent years, in order to satisfy the social requirements of environment and safety and also to cope with the current energy stringency, the installation of safe nuclear power plants is indispensable. Herein, safety analysis and evaluation to confirm quantitatively the safety design of a nuclear power plant become more and more important. The safety analysis and its methods for a high temperature gas-cooled reactor are described, with emphasis placed on the practices by Fuji Electric Manufacturing Co. Fundamental rule of securing plant safety ; safety analysis in normal operation regarding plant dynamic characteristics and radioactivity evaluation ; and safety analysis at the time of accidents regarding plant response to the accidents and radioactivity evaluation are explained. (Mori, K.)

CCF analysis of high redundancy systems safety/relief valve data analysis and reference BWR application

International Nuclear Information System (INIS)

Mankamo, T.; Bjoere, S.; Olsson, Lena

1992-12-01

Dependent failure analysis and modeling were developed for high redundancy systems. The study included a comprehensive data analysis of safety and relief valves at the Finnish and Swedish BWR plants, resulting in improved understanding of Common Cause Failure mechanisms in these components. The reference application on the Forsmark 1/2 reactor relief system, constituting of twelve safety/relief lines and two regulating relief lines, covered different safety criteria cases of reactor depressurization and overpressure protection function, and failure to re close sequences. For the quantification of dependencies, the Alpha Factor Model, the Binomial Probability Model and the Common Load Model were compared for applicability in high redundancy systems

High-dose-rate brachytherapy in the treatment of uterine cervix cancer. Analysis of dose effectiveness and late complications

International Nuclear Information System (INIS)

Ferrigno, Robson; Novaes, Paulo Eduardo Ribeiro dos Santos; Pellizzon, Antonio Cassio Assis; Maia, Maria Aparecida Conte; Fogarolli, Ricardo Cesar; Gentil, Andre Cavalcanti; Salvajoli, Joao Victor

2001-01-01

Purpose: This retrospective analysis aims to report results of patients with cervix cancer treated by external beam radiotherapy (EBR) and high-dose-rate (HDR) brachytherapy. Methods and Materials: From September 1992 to December 1996, 138 patients with FIGO Stages II and III and mean age of 56 years were treated. Median EBR to the whole pelvis was 45 Gy in 25 fractions. Parametrial boost was performed in 93% of patients, with a median dose of 14.4 Gy. Brachytherapy with HDR was performed during EBR or following its completion with a dose of 24 Gy in four weekly fractions of 6 Gy to point A. Median overall treatment time was of 60 days. Patient age, tumor stage, and overall treatment time were variables analyzed for survival and local control. Cumulative biologic effective dose (BED) at rectal and bladder reference points were correlated with late complications in these organs and dose of EBR at parametrium was correlated with small bowel complications. Results: Median follow-up time was 38 months. Overall survival, disease-free survival, and local control at 5 years was 53.7%, 52.7%, and 62%, respectively. By multivariate and univariate analysis, overall treatment time up to 50 days was the only statistically significant adverse variable for overall survival (p=0.003) and actuarial local control (p=0.008). The 5-year actuarial incidence of rectal, bladder, and small bowel late complications was 16%, 11%, and 14%, respectively. Patients treated with cumulative BED at rectum points above 110 Gy 3 and at bladder point above 125 Gy 3 had a higher but not statistically significant 5-year actuarial rate of complications at these organs (18% vs. 12%, p=0.49 and 17% vs. 9%, p=0.20, respectively). Patients who received parametrial doses larger than 59 Gy had a higher 5-year actuarial rate of complications in the small bowel; however, this was not statistically significant (19% vs. 10%, p=0.260). Conclusion: This series suggests that 45 Gy to the whole pelvis combined with

Automated analysis of high-content microscopy data with deep learning.

Science.gov (United States)

Kraus, Oren Z; Grys, Ben T; Ba, Jimmy; Chong, Yolanda; Frey, Brendan J; Boone, Charles; Andrews, Brenda J

2017-04-18

Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization. We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone-arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. We offer an open-source implementation that enables updating DeepLoc on new microscopy datasets. This study highlights deep learning as an important tool for the expedited analysis of high-content microscopy data. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Risk factors and long-term outcomes of pediatric liver transplant recipients with chronic high Epstein-Barr virus loads.

Science.gov (United States)

Kamei, Hideya; Ito, Yoshinori; Kawada, Junichi; Ogiso, Satoshi; Onishi, Yasuharu; Komagome, Masahiko; Kurata, Nobuhiko; Ogura, Yasuhiro

2018-04-20

Serial monitoring of Epstein-Barr virus (EBV) reveals that certain pediatric liver transplant (LT) recipients exhibit high EBV loads for long periods. We investigated the incidence and risk factors of chronic high EBV (CHEBV) loads (continuous EBV DNA >10 000 IU/mL of whole blood for ≥6 months) and long-term outcomes. This single center, retrospective observational study investigated pediatric LT recipients who survived ≥6 months. We quantitated EBV DNA weekly during hospitalization and subsequently every 4 or 6 weeks at the outpatient clinic. Tacrolimus was maintained at a low trough level (5000 IU/mL). Thirty-one of 77 LT recipients developed CHEBV. Univariate analysis revealed that age 35 minutes, graft-to-recipient weight ratio (GRWR) >2.7%, and preoperative EBV seronegativity were significantly associated with the development of CHEBV loads. Multivariate analysis identified significant associations of CHEBV with WIT >35 minutes, GRWR >2.7%, and preoperative seronegative. None of the recipients developed post-transplantation lymphoproliferative disorder. Survival rates of patients with and without CHEBV loads were not significantly different. A significant number of pediatric LT recipients developed CHEBV loads. Long WIT, high GRWR, and preoperative EBV seronegativity were significantly associated with the development of CHEBV loads. Although the long-term outcomes of patients with or without CHEBV loads were not significantly different, further studies of more subjects are warranted. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Fault analysis and strategy of high pulsed power supply for high power laser

International Nuclear Information System (INIS)

Liu Kefu; Qin Shihong; Li Jin; Pan Yuan; Yao Zonggan; Zheng Wanguo; Guo Liangfu; Zhou Peizhang; Li Yizheng; Chen Dehuai

2001-01-01

according to the requirements of driving flash-lamp, a high pulsed power supply (PPS) based on capacitors as energy storage elements is designed. The author analyzes in detail the faults of high pulsed power supply for high power laser. Such as capacitor internal short-circuit, main bus breakdown to ground, flashlamp sudden short or break. The fault current and voltage waveforms were given by circuit simulations. Based on the analysis and computation, the protection strategy with the fast fuse and ZnO was put forward, which can reduce the damage of PPS to the lower extent and provide the personnel safe and collateral property from the all threats. The preliminary experiments demonstrated that the design of the PPS can satisfy the project requirements

Elements of nonlinear time series analysis and forecasting

CERN Document Server

De Gooijer, Jan G

2017-01-01

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible...

Analysis of Prognostic Factors in 541 Female Patients with Advanced Non-small Cell Lung Cancer

Directory of Open Access Journals (Sweden)

Meina WU

2011-03-01

Full Text Available Background and objective As there is a sharp increase in the incidence of lung cancer in women in recent years, it has brought broad concerns with its unique clinical and epidemiological characteristics and better prognosis. The aim of this study is to analyze the clinical data of women with advanced non-small cell lung cancer (NSCLC retrospectively to explore the prognostic factors. Methods Clinical data of 541 female patients with advanced NSCLC were collected and followed up till death. The primary endpoint is overall survival (OS. SPSS 11.0 statistical analysis software was used for univariate and multivariate analysis. Results The mean age is 59 years (20 years-86 years, adenocarcinoma account for 80.2% (434/541. The median OS was 15 months (95%CI: 13.87-16.13, and 1, 2, 5-year survival rates were 58.8%, 23.7% and 3.20% respectively. Univariate analysis showed that clinical stage, ECOG score, weight loss, clinical symptoms, liver/bone/brain metastasis and received more than one chemotherapy regimen, good response to the first-line chemotherapy, EGFR-TKI targeted therapy and radiotherapy treatment were significantly correlated with the OS and survival rate (P < 0.05. Combined with multivariate analysis, weight loss before treatment, ECOG score, received EGFR-TKI targeted therapy and response to first-line chemotherapy were independent prognostic factor for survival (P < 0.05. Conclusion There is a higher percentage of adenocarcinoma in female NSCLC. Weight loss before treatment, ECOG score, EGFR-TKI targeted therapy and response to first-line chemotherapy may become independent prognostic factors for survival of female patients with advanced NSCLC.

Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

Science.gov (United States)

Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

1984-01-01

An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.

High-Resolution Melt Analysis for Rapid Comparison of Bacterial Community Compositions

DEFF Research Database (Denmark)

Hjelmsø, Mathis Hjort; Hansen, Lars Hestbjerg; Bælum, Jacob

2014-01-01

In the study of bacterial community composition, 16S rRNA gene amplicon sequencing is today among the preferred methods of analysis. The cost of nucleotide sequence analysis, including requisite computational and bioinformatic steps, however, takes up a large part of many research budgets. High......-resolution melt (HRM) analysis is the study of the melt behavior of specific PCR products. Here we describe a novel high-throughput approach in which we used HRM analysis targeting the 16S rRNA gene to rapidly screen multiple complex samples for differences in bacterial community composition. We hypothesized...... that HRM analysis of amplified 16S rRNA genes from a soil ecosystem could be used as a screening tool to identify changes in bacterial community structure. This hypothesis was tested using a soil microcosm setup exposed to a total of six treatments representing different combinations of pesticide...

High Nrf2 expression in alveolar type I pneumocytes is associated with low recurrences in primary spontaneous pneumothorax.

Science.gov (United States)

Chen, Yu-Wen; Chiu, Wen-Chin; Chou, Shah-Hwa; Su, Yu-Han; Huang, Ying-Fong; Lee, Yen-Lung; Yuan, Shyng-Shiou F; Lee, Yi-Chen

2017-10-01

Recurrent primary spontaneous pneumothorax (PSP) is a troublesome problem and a major concern for the patients. This study examined whether nuclear factor erythroid 2-related factor 2 (Nrf2) expression in alveolar type I pneumocytes was associated with the clinical manifestations of PSP patients including disease recurrence. Eighty-eight PSP patients who were managed with needlescopic video-assisted thoracoscopic surgery (NVATS) were included in this study. Immunohistochemistry (IHC) was assessed to determine Nrf2 expression in resected lung tissues and the results were correlated with clinicopathological characteristics by the chi-square or the Fisher's exact test. The prognostic value of Nrf2 for overall recurrence was evaluated by univariate and multivariable Cox regression model. The expression of Nrf2 was observed in type I pneumocytes of lung tissues from PSP patients by IHC. We found that low Nrf2 expression in PSP patients, especially in young (age ≤ 20, p = 0.033) and body mass index (BMI) ≥18 kg/m 2 (p = 0.019) groups, was significantly correlated with PSP recurrence. In the univariate and multivariate analyses, high Nrf2 expression was a significant protective factor for overall recurrence in PSP patients (univariate: p = 0.026; multivariate: p = 0.004). The expression level of Nrf2 in alveolar type I pneumocytes was a potential factor involved in PSP recurrence. Our findings suggest that elevated Nrf2 expression in PSP patients may be a promising way for reducing PSP recurrence. Copyright © 2017. Published by Elsevier Taiwan.

NOAA High-Resolution Sea Surface Temperature (SST) Analysis Products

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This archive covers two high resolution sea surface temperature (SST) analysis products developed using an optimum interpolation (OI) technique. The analyses have a...

Progress in element analysis on a high-voltage electron microscope

International Nuclear Information System (INIS)

Tivol, W.F.; Barnard, D.; Guha, T.

1985-01-01

X-Ray microprobe (XMA) and electron energy-loss (EELS) spectrometers have been installed on the high-voltage electron microscope (HVEM). The probe size has been measured and background reduction is in progress for XMA and EELS as are improvements in electron optics for EELS and sensitivity measurements. XMA is currently useful for qualitative analysis and has been used by several investigators from our laboratory and outside laboratories. However, EELS background levels are still too high for meaningful results to be obtained. Standards suitable for biological specimens are being measured, and a library for quantitative analysis is being compiled

Analysis of biopsy outcome after three-dimensional conformal radiation therapy of prostate cancer using dose-distribution variables and tumor control probability models

International Nuclear Information System (INIS)

Levegruen, Sabine; Jackson, Andrew; Zelefsky, Michael J.; Venkatraman, Ennapadam S.; Skwarchuk, Mark W.; Schlegel, Wolfgang; Fuks, Zvi; Leibel, Steven A.; Ling, C. Clifton

2000-01-01

Purpose: To investigate tumor control following three-dimensional conformal radiation therapy (3D-CRT) of prostate cancer and to identify dose-distribution variables that correlate with local control assessed through posttreatment prostate biopsies. Methods and Material: Data from 132 patients, treated at Memorial Sloan-Kettering Cancer Center (MSKCC), who had a prostate biopsy 2.5 years or more after 3D-CRT for T1c-T3 prostate cancer with prescription doses of 64.8-81 Gy were analyzed. Variables derived from the dose distribution in the PTV included: minimum dose (Dmin), maximum dose (Dmax), mean dose (Dmean), dose to n% of the PTV (Dn), where n = 1%, ..., 99%. The concept of the equivalent uniform dose (EUD) was evaluated for different values of the surviving fraction at 2 Gy (SF 2 ). Four tumor control probability (TCP) models (one phenomenologic model using a logistic function and three Poisson cell kill models) were investigated using two sets of input parameters, one for low and one for high T-stage tumors. Application of both sets to all patients was also investigated. In addition, several tumor-related prognostic variables were examined (including T-stage, Gleason score). Univariate and multivariate logistic regression analyses were performed. The ability of the logistic regression models (univariate and multivariate) to predict the biopsy result correctly was tested by performing cross-validation analyses and evaluating the results in terms of receiver operating characteristic (ROC) curves. Results: In univariate analysis, prescription dose (Dprescr), Dmax, Dmean, dose to n% of the PTV with n of 70% or less correlate with outcome (p 2 : EUD correlates significantly with outcome for SF 2 of 0.4 or more, but not for lower SF 2 values. Using either of the two input parameters sets, all TCP models correlate with outcome (p 2 , is limited because the low dose region may not coincide with the tumor location. Instead, for MSKCC prostate cancer patients with their

Modeling high temperature materials behavior for structural analysis

CERN Document Server

Naumenko, Konstantin

2016-01-01

This monograph presents approaches to characterize inelastic behavior of materials and structures at high temperature. Starting from experimental observations, it discusses basic features of inelastic phenomena including creep, plasticity, relaxation, low cycle and thermal fatigue. The authors formulate constitutive equations to describe the inelastic response for the given states of stress and microstructure. They introduce evolution equations to capture hardening, recovery, softening, ageing and damage processes. Principles of continuum mechanics and thermodynamics are presented to provide a framework for the modeling materials behavior with the aim of structural analysis of high-temperature engineering components.

Cost-Effectiveness Analysis of Regorafenib for Metastatic Colorectal Cancer.

Science.gov (United States)

Goldstein, Daniel A; Ahmad, Bilal B; Chen, Qiushi; Ayer, Turgay; Howard, David H; Lipscomb, Joseph; El-Rayes, Bassel F; Flowers, Christopher R

2015-11-10

Regorafenib is a standard-care option for treatment-refractory metastatic colorectal cancer that increases median overall survival by 6 weeks compared with placebo. Given this small incremental clinical benefit, we evaluated the cost-effectiveness of regorafenib in the third-line setting for patients with metastatic colorectal cancer from the US payer perspective. We developed a Markov model to compare the cost and effectiveness of regorafenib with those of placebo in the third-line treatment of metastatic colorectal cancer. Health outcomes were measured in life-years and quality-adjusted life-years (QALYs). Drug costs were based on Medicare reimbursement rates in 2014. Model robustness was addressed in univariable and probabilistic sensitivity analyses. Regorafenib provided an additional 0.04 QALYs (0.13 life-years) at a cost of $40,000, resulting in an incremental cost-effectiveness ratio of $900,000 per QALY. The incremental cost-effectiveness ratio for regorafenib was > $550,000 per QALY in all of our univariable and probabilistic sensitivity analyses. Regorafenib provides minimal incremental benefit at high incremental cost per QALY in the third-line management of metastatic colorectal cancer. The cost-effectiveness of regorafenib could be improved by the use of value-based pricing. © 2015 by American Society of Clinical Oncology.

Prevalence of premenstrual syndrome in Iran: A systematic review and meta-analysis

Directory of Open Access Journals (Sweden)

Mehdi Ranjbaran

2017-11-01

Full Text Available Background: Premenstrual syndrome (PMS is a common disorder characterized by physical, mental and behavioral changes in the luteal phase of the menstrual cycle in the reproductive age women. Objective: The present study aimed to determine the overall prevalence of PMS in Iran by a systematic review and meta-analysis study. Materials and Methods: In this systematic review and meta-analysis, we searched international databases included ISI Web of Knowledge, PubMed/Medline, Scopus, Google Scholar, and also local databases including Iranmedex, Scientific Information Database, and Magiran for articles in English and Persian language published up to September 2016. We carried out data analysis with Stata version 11. We examined heterogeneity in the results of studies through I2 statistics and Chi-square based Q test. Also, we investigated the effects of potential heterogeneity factors in the prevalence of PMS by meta-regression. Results: We studied a total of 9147 reproductive-age women from 24 articles which entered to meta-analysis. Based on the result of random effect model, we estimated the overall prevalence of PMS 70.8% [95% CI: 63.8-77.7]. The results of subgroup analysis revealed that prevalence of PMS was 80.4% (95% CI; 66.9-93.9 among high school students, 68.9% (95% CI; 59.2-78.6 among university students, and 54.9% (95% CI; 51.6-58.2 in general population. Univariate meta-regression model showed that prevalence of PMS was decreased by increasing the age of subjects but this was not statistically significant (p=0.155. Conclusion: Our finding showed that PMS was prevalent in Iranian reproductive age women especially among high school students. More epidemiological research for determining factors that affect PMS prevalence seems essential.

Lymphatic vessel invasion detected by the endothelial lymphatic marker D2-40 (podoplanin is predictive of regional lymph node status and an independent prognostic factor in patients with resected esophageal cancer

Directory of Open Access Journals (Sweden)

Jerzy Laudański

2011-04-01

Full Text Available The discovery of markers to lymphatic endothelial cells and the development of novel antibodies to these markers have brought increasing attention to the lymphatics and progress in the understanding of lymphangiogenesis and cancer metastasis. In this study, we investigate the presence of lymphatic vessel invasion (LVI detected by D2-40 immunohistochemical staining in resected esophageal cancer and correlated with clinicopathologic data and patient survival. Sixty nine patients, who had a primary resection of esophageal cancer, were analyzed by univariate and multivariate logistic regression, and univariate and multivariate survival analysis. The total rate of LVI was 72% (50/69. Positive LVI was significantly correlated with lymph node metastasis (p < 0.001, tumor size (p < 0.001, histological grading (p = 0.017, tumor depth (p = 0.001, and stage (p < 0.001. Multivariate logistic analysis identified LVI (p = 0.036 as a predictor of regional lymph node metastasis. On univariate survival analysis, patients with LVI had a significantly shorter disease-free survival, cancer-specific survival and overall survival. Multivariate analysis proved that LVI diagnosed by D2-40 is an independent prognostic factor of both disease-free survival (p = 0.04 and overall survival (p = 0.032 in resected esophageal cancer. These results show that LVI assessment identifies patients at high risk for regional lymph node metastasis and that LVI is an independent prognostic factor in patients with esophageal cancer. (Folia Histochemica et Cytobiologica 2011; Vol. 49, No. 1, pp. 90–97