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Sample records for variability index predicts

  1. Amniotic fluid index predicts the relief of variable decelerations after amnioinfusion bolus.

    Science.gov (United States)

    Spong, C Y; McKindsey, F; Ross, M G

    1996-10-01

    Our purpose was to determine whether intrapartum amniotic fluid index before amnioinfusion can be used to predict response to therapeutic amnioinfusion. Intrapartum patients (n = 85) with repetitive variable decelerations in fetal heart rate that necessitated amnioinfusion (10 ml/min for 60 minutes) underwent determination of amniotic fluid index before and after bolus amnioinfusion. The fetal heart tracing was scored (scorer blinded to amniotic fluid index values) for number and characteristics of variable decelerations before and 1 hour after initiation of amnioinfusion. The amnioinfusion was considered successful if it resulted in a decrease of > or = 50% in total number of variable decelerations or a decrease of > or = 50% in the rate of atypical or severe variable decelerations after administration of the bolus. Spontaneous vaginal births before completion of administration of the bolus (n = 18) were excluded from analysis. The probability of success of amnioinfusion in relation to amniotic fluid index was analyzed with the chi(2) test for progressive sequence. The mean amniotic fluid index before amnioinfusion was 6.2 +/- 3.3 cm. An amniotic fluid index of amnioinfusion decreased with increasing amniotic fluid index before amnioinfusion (76% [16/21] when initial amniotic fluid index was 0 to 4 cm, 63% [17/27] when initial amniotic fluid index was 4 to 8 cm, 44% [7/16] when initial amniotic fluid index was 8 to 12 cm, and 33% [1/3] when initial amniotic fluid index was > 12 cm, p = 0.03). The incidence of nuchal cords or true umbilical cord knots increased in relation to amniotic fluid index before amnioinfusion. Amniotic fluid index before amnioinfusion can be used to predict the success of amnioinfusion for relief of variable decelerations in fetal heart rate. Failure of amnioinfusion at a high amniotic fluid index before amnioinfusion may be explained by the increased prevalence of nuchal cords or true knots in the umbilical cord.

  2. Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

    Science.gov (United States)

    Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

    2016-09-01

    As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for

  3. Using a topographic index to distribute variable source area runoff predicted with the SCS curve-number equation

    Science.gov (United States)

    Lyon, Steve W.; Walter, M. Todd; Gérard-Marchant, Pierre; Steenhuis, Tammo S.

    2004-10-01

    Because the traditional Soil Conservation Service curve-number (SCS-CN) approach continues to be used ubiquitously in water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed and tested a distributed approach for applying the traditional SCS-CN equation to watersheds where VSA hydrology is a dominant process. Predicting the location of source areas is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non-point-source pollution. The method presented here used the traditional SCS-CN approach to predict runoff volume and spatial extent of saturated areas and a topographic index, like that used in TOPMODEL, to distribute runoff source areas through watersheds. The resulting distributed CN-VSA method was applied to two subwatersheds of the Delaware basin in the Catskill Mountains region of New York State and one watershed in south-eastern Australia to produce runoff-probability maps. Observed saturated area locations in the watersheds agreed with the distributed CN-VSA method. Results showed good agreement with those obtained from the previously validated soil moisture routing (SMR) model. When compared with the traditional SCS-CN method, the distributed CN-VSA method predicted a similar total volume of runoff, but vastly different locations of runoff generation. Thus, the distributed CN-VSA approach provides a physically based method that is simple enough to be incorporated into water quality models, and other tools that currently use the traditional SCS-CN method, while still adhering to the principles of VSA hydrology.

  4. Predicting long-term streamflow variability in moist eucalypt forests using forest growth models and a sapwood area index

    Science.gov (United States)

    Jaskierniak, D.; Kuczera, G.; Benyon, R.

    2016-04-01

    A major challenge in surface hydrology involves predicting streamflow in ungauged catchments with heterogeneous vegetation and spatiotemporally varying evapotranspiration (ET) rates. We present a top-down approach for quantifying the influence of broad-scale changes in forest structure on ET and hence streamflow. Across three catchments between 18 and 100 km2 in size and with regenerating Eucalyptus regnans and E. delegatensis forest, we demonstrate how variation in ET can be mapped in space and over time using LiDAR data and commonly available forest inventory data. The model scales plot-level sapwood area (SA) to the catchment-level using basal area (BA) and tree stocking density (N) estimates in forest growth models. The SA estimates over a 69 year regeneration period are used in a relationship between SA and vegetation induced streamflow loss (L) to predict annual streamflow (Q) with annual rainfall (P) estimates. Without calibrating P, BA, N, SA, and L to Q data, we predict annual Q with R2 between 0.68 and 0.75 and Nash Sutcliffe efficiency (NSE) between 0.44 and 0.48. To remove bias, the model was extended to allow for runoff carry-over into the following year as well as minor correction to rainfall bias, which produced R2 values between 0.72 and 0.79, and NSE between 0.70 and 0.79. The model under-predicts streamflow during drought periods as it lacks representation of ecohydrological processes that reduce L with either reduced growth rates or rainfall interception during drought. Refining the relationship between sapwood thickness and forest inventory variables is likely to further improve results.

  5. Quantifying human disturbance in watersheds: Variable selection and performance of a GIS-based disturbance index for predicting the biological condition of perennial streams

    Science.gov (United States)

    Falcone, James A.; Carlisle, Daren M.; Weber, Lisa C.

    2010-01-01

    Characterizing the relative severity of human disturbance in watersheds is often part of stream assessments and is frequently done with the aid of Geographic Information System (GIS)-derived data. However, the choice of variables and how they are used to quantify disturbance are often subjective. In this study, we developed a number of disturbance indices by testing sets of variables, scoring methods, and weightings of 33 potential disturbance factors derived from readily available GIS data. The indices were calibrated using 770 watersheds located in the western United States for which the severity of disturbance had previously been classified from detailed local data by the United States Environmental Protection Agency (USEPA) Environmental Monitoring and Assessment Program (EMAP). The indices were calibrated by determining which variable or variable combinations and aggregation method best differentiated between least- and most-disturbed sites. Indices composed of several variables performed better than any individual variable, and best results came from a threshold method of scoring using six uncorrelated variables: housing unit density, road density, pesticide application, dam storage, land cover along a mainstem buffer, and distance to nearest canal/pipeline. The final index was validated with 192 withheld watersheds and correctly classified about two-thirds (68%) of least- and most-disturbed sites. These results provide information about the potential for using a disturbance index as a screening tool for a priori ranking of watersheds at a regional/national scale, and which landscape variables and methods of combination may be most helpful in doing so.

  6. Stock market index prediction using neural networks

    Science.gov (United States)

    Komo, Darmadi; Chang, Chein-I.; Ko, Hanseok

    1994-03-01

    A neural network approach to stock market index prediction is presented. Actual data of the Wall Street Journal's Dow Jones Industrial Index has been used for a benchmark in our experiments where Radial Basis Function based neural networks have been designed to model these indices over the period from January 1988 to Dec 1992. A notable success has been achieved with the proposed model producing over 90% prediction accuracies observed based on monthly Dow Jones Industrial Index predictions. The model has also captured both moderate and heavy index fluctuations. The experiments conducted in this study demonstrated that the Radial Basis Function neural network represents an excellent candidate to predict stock market index.

  7. Climate Prediction Center - Site Index

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Means Bulletins Annual Winter Stratospheric Ozone Climate Diagnostics Bulletin (Most Recent) Climate (Hazards Outlook) Climate Assessment: Dec. 1999-Feb. 2000 (Seasonal) Climate Assessment: Mar-May 2000

  8. Predictive Value of Beat-to-Beat QT Variability Index across the Continuum of Left Ventricular Dysfunction: Competing Risks of Non-cardiac or Cardiovascular Death, and Sudden or Non-Sudden Cardiac Death

    Science.gov (United States)

    Tereshchenko, Larisa G.; Cygankiewicz, Iwona; McNitt, Scott; Vazquez, Rafael; Bayes-Genis, Antoni; Han, Lichy; Sur, Sanjoli; Couderc, Jean-Philippe; Berger, Ronald D.; de Luna, Antoni Bayes; Zareba, Wojciech

    2012-01-01

    Background The goal of this study was to determine the predictive value of beat-to-beat QT variability in heart failure (HF) patients across the continuum of left ventricular dysfunction. Methods and Results Beat-to-beat QT variability index (QTVI), heart rate variance (LogHRV), normalized QT variance (QTVN), and coherence between heart rate variability and QT variability have been measured at rest during sinus rhythm in 533 participants of the Muerte Subita en Insuficiencia Cardiaca (MUSIC) HF study (mean age 63.1±11.7; males 70.6%; LVEF >35% in 254 [48%]) and in 181 healthy participants from the Intercity Digital Electrocardiogram Alliance (IDEAL) database. During a median of 3.7 years of follow-up, 116 patients died, 52 from sudden cardiac death (SCD). In multivariate competing risk analyses, the highest QTVI quartile was associated with cardiovascular death [hazard ratio (HR) 1.67(95%CI 1.14-2.47), P=0.009] and in particular with non-sudden cardiac death [HR 2.91(1.69-5.01), P<0.001]. Elevated QTVI separated 97.5% of healthy individuals from subjects at risk for cardiovascular [HR 1.57(1.04-2.35), P=0.031], and non-sudden cardiac death in multivariate competing risk model [HR 2.58(1.13-3.78), P=0.001]. No interaction between QTVI and LVEF was found. QTVI predicted neither non-cardiac death (P=0.546) nor SCD (P=0.945). Decreased heart rate variability (HRV) rather than increased QT variability was the reason for increased QTVI in this study. Conclusions Increased QTVI due to depressed HRV predicts cardiovascular mortality and non-sudden cardiac death, but neither SCD nor excracardiac mortality in HF across the continuum of left ventricular dysfunction. Abnormally augmented QTVI separates 97.5% of healthy individuals from HF patients at risk. PMID:22730411

  9. Predicting fiber refractive index from a measured preform index profile

    Science.gov (United States)

    Kiiveri, P.; Koponen, J.; Harra, J.; Novotny, S.; Husu, H.; Ihalainen, H.; Kokki, T.; Aallos, V.; Kimmelma, O.; Paul, J.

    2018-02-01

    When producing fiber lasers and amplifiers, silica glass compositions consisting of three to six different materials are needed. Due to the varying needs of different applications, substantial number of different glass compositions are used in the active fiber structures. Often it is not possible to find material parameters for theoretical models to estimate thermal and mechanical properties of those glass compositions. This makes it challenging to predict accurately fiber core refractive index values, even if the preform index profile is measured. Usually the desired fiber refractive index value is achieved experimentally, which is expensive. To overcome this problem, we analyzed statistically the changes between the measured preform and fiber index values. We searched for correlations that would help to predict the Δn-value change from preform to fiber in a situation where we don't know the values of the glass material parameters that define the change. Our index change models were built using the data collected from preforms and fibers made by the Direct Nanoparticle Deposition (DND) technology.

  10. Prediction of massive bleeding. Shock index and modified shock index.

    Science.gov (United States)

    Terceros-Almanza, L J; García-Fuentes, C; Bermejo-Aznárez, S; Prieto-Del Portillo, I J; Mudarra-Reche, C; Sáez-de la Fuente, I; Chico-Fernández, M

    2017-12-01

    To determine the predictive value of the Shock Index and Modified Shock Index in patients with massive bleeding due to severe trauma. Retrospective cohort. Severe trauma patient's initial attention at the intensive care unit of a tertiary hospital. Patients older than 14 years that were admitted to the hospital with severe trauma (Injury Severity Score >15) form January 2014 to December 2015. We studied the sensitivity (Se), specificity (Sp), positive and negative predictive value (PV+ and PV-), positive and negative likelihood ratio (LR+ and LR-), ROC curves (Receiver Operating Characteristics) and the area under the same (AUROC) for prediction of massive hemorrhage. 287 patients were included, 76.31% (219) were male, mean age was 43,36 (±17.71) years and ISS was 26 (interquartile range [IQR]: 21-34). The overall frequency of massive bleeding was 8.71% (25). For Shock Index: AUROC was 0.89 (95% confidence intervals [CI] 0.84 to 0.94), with an optimal cutoff at 1.11, Se was 91.3% (95% CI: 73.2 to 97.58) and Sp was 79.69% (95% CI: 74.34 to 84.16). For the Modified Shock Index: AUROC was 0.90 (95% CI: 0.86 to 0.95), with an optimal cutoff at 1.46, Se was 95.65% (95% CI: 79.01 to 99.23) and Sp was 75.78% (95% CI: 70.18 to 80.62). Shock Index and Modified Shock Index are good predictors of massive bleeding and could be easily incorporated to the initial workup of patients with severe trauma. Copyright © 2017 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

  11. Estimating Search Engine Index Size Variability

    DEFF Research Database (Denmark)

    Van den Bosch, Antal; Bogers, Toine; De Kunder, Maurice

    2016-01-01

    One of the determining factors of the quality of Web search engines is the size of their index. In addition to its influence on search result quality, the size of the indexed Web can also tell us something about which parts of the WWW are directly accessible to the everyday user. We propose a novel...... method of estimating the size of a Web search engine’s index by extrapolating from document frequencies of words observed in a large static corpus of Web pages. In addition, we provide a unique longitudinal perspective on the size of Google and Bing’s indices over a nine-year period, from March 2006...... until January 2015. We find that index size estimates of these two search engines tend to vary dramatically over time, with Google generally possessing a larger index than Bing. This result raises doubts about the reliability of previous one-off estimates of the size of the indexed Web. We find...

  12. Fatty liver incidence and predictive variables

    International Nuclear Information System (INIS)

    Tsuneto, Akira; Seto, Shinji; Maemura, Koji; Hida, Ayumi; Sera, Nobuko; Imaizumi, Misa; Ichimaru, Shinichiro; Nakashima, Eiji; Akahoshi, Masazumi

    2010-01-01

    Although fatty liver predicts ischemic heart disease, the incidence and predictors of fatty liver need examination. The objective of this study was to determine fatty liver incidence and predictive variables. Using abdominal ultrasonography, we followed biennially through 2007 (mean follow-up, 11.6±4.6 years) 1635 Nagasaki atomic bomb survivors (606 men) without fatty liver at baseline (November 1990 through October 1992). We examined potential predictive variables with the Cox proportional hazard model and longitudinal trends with the Wilcoxon rank-sum test. In all, 323 (124 men) new fatty liver cases were diagnosed. The incidence was 19.9/1000 person-years (22.3 for men, 18.6 for women) and peaked in the sixth decade of life. After controlling for age, sex, and smoking and drinking habits, obesity (relative risk (RR), 2.93; 95% confidence interval (CI), 2.33-3.69, P<0.001), low high-density lipoprotein-cholesterol (RR, 1.87; 95% CI, 1.42-2.47; P<0.001), hypertriglyceridemia (RR, 2.49; 95% CI, 1.96-3.15; P<0.001), glucose intolerance (RR, 1.51; 95% CI, 1.09-2.10; P=0.013) and hypertension (RR, 1.63; 95% CI, 1.30-2.04; P<0.001) were predictive of fatty liver. In multivariate analysis including all variables, obesity (RR, 2.55; 95% CI, 1.93-3.38; P<0.001), hypertriglyceridemia (RR, 1.92; 95% CI, 1.41-2.62; P<0.001) and hypertension (RR, 1.31; 95% CI, 1.01-1.71; P=0.046) remained predictive. In fatty liver cases, body mass index and serum triglycerides, but not systolic or diastolic blood pressure, increased significantly and steadily up to the time of the diagnosis. Obesity, hypertriglyceridemia and, to a lesser extent, hypertension might serve as predictive variables for fatty liver. (author)

  13. The Relationship between Macroeconomic Variables and ISE Industry Index

    Directory of Open Access Journals (Sweden)

    Ahmet Ozcan

    2012-01-01

    Full Text Available In this study, the relationship between macroeconomic variables and Istanbul Stock Exchange (ISE industry index is examined. Over the past years, numerous studies have analyzed these relationships and the different results obtained from these studies have motivated further research. The relationship between stock exchange index and macroeconomic variables has been well documented for the developed markets. However, there are few studies regarding the relationship between macroeconomic variables and stock exchange index for the developing markets. Thus, this paper seeks to address the question of whether macroeconomic variables have a significant relationship with ISE industry index using monthly data for the period from 2003 to 2010. The selected macroeconomic variables for the study include interest rates, consumer price index, money supply, exchange rate, gold prices, oil prices, current account deficit and export volume. The Johansen’s cointegration test is utilized to determine the impact of selected macroeconomic variables on ISE industry index. The result of the Johansen’s cointegration shows that macroeconomic variables exhibit a long run equilibrium relationship with the ISE industry index.

  14. The interannual variability of the Haines Index over North America

    Science.gov (United States)

    Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman; Joseph J. Charney

    2013-01-01

    The Haines index (HI) is a fire-weather index that is widely used as an indicator of the potential for dry, low-static-stability air in the lower atmosphere to contribute to erratic fire behavior or large fire growth. This study examines the interannual variability of HI over North America and its relationship to indicators of large-scale circulation anomalies. The...

  15. Predicting waist circumference from body mass index.

    Science.gov (United States)

    Bozeman, Samuel R; Hoaglin, David C; Burton, Tanya M; Pashos, Chris L; Ben-Joseph, Rami H; Hollenbeak, Christopher S

    2012-08-03

    Being overweight or obese increases risk for cardiometabolic disorders. Although both body mass index (BMI) and waist circumference (WC) measure the level of overweight and obesity, WC may be more important because of its closer relationship to total body fat. Because WC is typically not assessed in clinical practice, this study sought to develop and verify a model to predict WC from BMI and demographic data, and to use the predicted WC to assess cardiometabolic risk. Data were obtained from the Third National Health and Nutrition Examination Survey (NHANES) and the Atherosclerosis Risk in Communities Study (ARIC). We developed linear regression models for men and women using NHANES data, fitting waist circumference as a function of BMI. For validation, those regressions were applied to ARIC data, assigning a predicted WC to each individual. We used the predicted WC to assess abdominal obesity and cardiometabolic risk. The model correctly classified 88.4% of NHANES subjects with respect to abdominal obesity. Median differences between actual and predicted WC were -0.07 cm for men and 0.11 cm for women. In ARIC, the model closely estimated the observed WC (median difference: -0.34 cm for men, +3.94 cm for women), correctly classifying 86.1% of ARIC subjects with respect to abdominal obesity and 91.5% to 99.5% as to cardiometabolic risk.The model is generalizable to Caucasian and African-American adult populations because it was constructed from data on a large, population-based sample of men and women in the United States, and then validated in a population with a larger representation of African-Americans. The model accurately estimates WC and identifies cardiometabolic risk. It should be useful for health care practitioners and public health officials who wish to identify individuals and populations at risk for cardiometabolic disease when WC data are unavailable.

  16. Classification and prediction of port variables

    Energy Technology Data Exchange (ETDEWEB)

    Molina Serrano, B.

    2016-07-01

    Many variables are included in planning and management of port terminals. They can beeconomic, social, environmental and institutional. Agent needs to know relationshipbetween these variables to modify planning conditions. Use of Bayesian Networks allowsfor classifying, predicting and diagnosing these variables. Bayesian Networks allow forestimating subsequent probability of unknown variables, basing on know variables.In planning level, it means that it is not necessary to know all variables because theirrelationships are known. Agent can know interesting information about how port variablesare connected. It can be interpreted as cause-effect relationship. Bayesian Networks can beused to make optimal decisions by introduction of possible actions and utility of theirresults.In proposed methodology, a data base has been generated with more than 40 port variables.They have been classified in economic, social, environmental and institutional variables, inthe same way that smart port studies in Spanish Port System make. From this data base, anetwork has been generated using a non-cyclic conducted grafo which allows for knowingport variable relationships - parents-children relationships-. Obtained network exhibits thateconomic variables are – in cause-effect terms- cause of rest of variable typologies.Economic variables represent parent role in the most of cases. Moreover, whenenvironmental variables are known, obtained network allows for estimating subsequentprobability of social variables.It has been concluded that Bayesian Networks allow for modeling uncertainty in aprobabilistic way, even when number of variables is high as occurs in planning andmanagement of port terminals. (Author)

  17. Predicting waist circumference from body mass index

    Directory of Open Access Journals (Sweden)

    Bozeman Samuel R

    2012-08-01

    Full Text Available Abstract Background Being overweight or obese increases risk for cardiometabolic disorders. Although both body mass index (BMI and waist circumference (WC measure the level of overweight and obesity, WC may be more important because of its closer relationship to total body fat. Because WC is typically not assessed in clinical practice, this study sought to develop and verify a model to predict WC from BMI and demographic data, and to use the predicted WC to assess cardiometabolic risk. Methods Data were obtained from the Third National Health and Nutrition Examination Survey (NHANES and the Atherosclerosis Risk in Communities Study (ARIC. We developed linear regression models for men and women using NHANES data, fitting waist circumference as a function of BMI. For validation, those regressions were applied to ARIC data, assigning a predicted WC to each individual. We used the predicted WC to assess abdominal obesity and cardiometabolic risk. Results The model correctly classified 88.4% of NHANES subjects with respect to abdominal obesity. Median differences between actual and predicted WC were − 0.07 cm for men and 0.11 cm for women. In ARIC, the model closely estimated the observed WC (median difference: − 0.34 cm for men, +3.94 cm for women, correctly classifying 86.1% of ARIC subjects with respect to abdominal obesity and 91.5% to 99.5% as to cardiometabolic risk. The model is generalizable to Caucasian and African-American adult populations because it was constructed from data on a large, population-based sample of men and women in the United States, and then validated in a population with a larger representation of African-Americans. Conclusions The model accurately estimates WC and identifies cardiometabolic risk. It should be useful for health care practitioners and public health officials who wish to identify individuals and populations at risk for cardiometabolic disease when WC data are unavailable.

  18. A Body Shape Index and Heart Rate Variability in Healthy Indians with Low Body Mass Index

    Directory of Open Access Journals (Sweden)

    Sharma Sowmya

    2014-01-01

    Full Text Available Background. One third of Indian population is said to be suffering from chronic energy deficiency (CED, with increased risk of developing chronic diseases. A new anthropometric measure called A Body Shape Index (ABSI is said to be a better index in predicting risks for premature mortality. ABSI is also in part said to be a surrogate of visceral fat. Objective. The present study aimed to explore the association between indices of HRV (heart rate variability, BMI, WC, and ABSI in healthy Indian males with low BMI (BMI < 18.5 kg/m2 and to compare with normal BMI group (BMI 18.5 to 24.9 kg/m2. Methodology. ABSI and BMI were derived from anthropometric parameters, namely, height, weight, and waist circumference in 178 males aged 18 to 78 years. Subjects were categorized into two groups based on their BMI. Results and Conclusions. Power spectral analysis of HRV demonstrated a significant negative correlation between Log HF (high frequency and ABSI in both low BMI [−24.2 (9.4, P<0.05] and normal BMI group [−23.41 (10.1, P<0.05] even after controlling for age. Thus even with slight increase in BMI among low BMI individuals, there could be a greater risk of cardiovascular morbidity and mortality.

  19. Reproducibility of the Pleth Variability Index in premature infants

    NARCIS (Netherlands)

    Den Boogert, W.J. (Wilhelmina J.); H.A. van Elteren (Hugo); T.G. Goos (Tom); I.K.M. Reiss (Irwin); R.C.J. de Jonge (Rogier); V.J. van den Berg (Victor J.)

    2017-01-01

    textabstractThe aim was to assess the reproducibility of the Pleth Variability Index (PVI), developed for non-invasive monitoring of peripheral perfusion, in preterm neonates below 32 weeks of gestational age. Three PVI measurements were consecutively performed in stable, comfortable preterm

  20. Reproducibility of the Pleth Variability Index in premature infants

    NARCIS (Netherlands)

    Den Boogert, Wilhelmina J.; Van Elteren, Hugo A.; Goos, T.G.; Reiss, Irwin K.M.; De Jonge, Rogier C.J.; van Den Berg, Victor J.

    2017-01-01

    The aim was to assess the reproducibility of the Pleth Variability Index (PVI), developed for non-invasive monitoring of peripheral perfusion, in preterm neonates below 32 weeks of gestational age. Three PVI measurements were consecutively performed in stable, comfortable preterm neonates in the

  1. VARIABILITY OF THE THERMAL CONTINENTALITY INDEX IN CENTRAL EUROPE

    Directory of Open Access Journals (Sweden)

    CIARANEK1 DOMINIKA

    2014-03-01

    Full Text Available The paper presents the spatial and temporal variability of thermal continentality in Central Europe. Gorczyński’s and Johansson-Ringleb’s formulae were used to derive the continentality index. The study also looked at the annual patterns of air temperature amplitude (A, a component of both of these formulae, and D; the difference between the average temperatures of autumn (Sep.-Nov. and spring (Mar.-May. Records of six weather stations representing the climate of Central Europe were included in the study covering the period 1775-2012 (Potsdam, Drezden, Prague, Vienna, Krakow, Debrecen. The highest continentality index was found in Debrecen and the lowest in Potsdam. The continentality index fluctuated with time with two pronounced dips at the turn of the 19th century and in the second half of the 20th century. The highest continentality index values were recorded during the 1930s and 1940s.

  2. [Evaluation of circulatory state using pulse oximeter: 2. PI (perfusion index) x PVI (pleth variability index)].

    Science.gov (United States)

    Kaneda, Toru; Suzuki, Toshiyasu

    2009-07-01

    Pulse oximeter expressed by SpO2 is used for monitoring respiratory state during operation and in ICU. Perfusion index (PI) and pleth variability index (PVI) as new indexes are calculated from pulse oximeter (Masimo SET Radical-7, Masimo Corp., USA, 1998) waveforms. And these indices were used as parameters to evaluate the circulatory state. For PI calculation, the pulsatile infrared signal is indexed against the nonpulsatile infrared signal and expressed as a percentage. It might thus be of future value in assessment of perioperative changes in peripheral perfusion. PVI is a measure of a dynamic change in PI that occurs during complete respiratory cycle. It might be thought that PVI, an index automatically derived from the pulse oximeter waveform analysis, had potentially clinical applications for noninvasive hypovolemia detection and fluid responsiveness monitoring.

  3. Predictability and Variability of Wave and Wind

    DEFF Research Database (Denmark)

    Chozas, Julia Fernandez; Kofoed, Jens Peter; Sørensen, Hans Christian

    This project covers two fields of study: a) Wave energy predictability and electricity markets. b) Variability of the power output of WECs in diversified systems : diversified renewable systems with wave and offshore wind production. See page 2-4 in the report for a executive summery....

  4. Climate Prediction Center Southern Oscillation Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This is one of the CPC?s Monthly Atmospheric and Sea Surface Temperature (SST)Indices. It contains Southern Oscillation Index which is standardized sea level...

  5. New social adaptability index predicts overall mortality.

    Science.gov (United States)

    Goldfarb-Rumyantzev, Alexander; Barenbaum, Anna; Rodrigue, James; Rout, Preeti; Isaacs, Ross; Mukamal, Kenneth

    2011-08-01

    Definitions of underprivileged status based on race, gender and geographic location are neither sensitive nor specific; instead we proposed and validated a composite index of social adaptability (SAI). Index of social adaptability was calculated based on employment, education, income, marital status, and substance abuse, each factor contributing from 0 to 3 points. Index of social adaptability was validated in NHANES-3 by association with all-cause and cause-specific mortality. Weighted analysis of 19,593 subjects demonstrated mean SAI of 8.29 (95% CI 8.17-8.40). Index of social adaptability was higher in Whites, followed by Mexican-Americans and then the African-American population (ANOVA, p adaptability with a strong association with mortality, which can be used to identify underprivileged populations at risk of death.

  6. Prediction of Baseflow Index of Catchments using Machine Learning Algorithms

    Science.gov (United States)

    Yadav, B.; Hatfield, K.

    2017-12-01

    We present the results of eight machine learning techniques for predicting the baseflow index (BFI) of ungauged basins using a surrogate of catchment scale climate and physiographic data. The tested algorithms include ordinary least squares, ridge regression, least absolute shrinkage and selection operator (lasso), elasticnet, support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Our work seeks to identify the dominant controls of BFI that can be readily obtained from ancillary geospatial databases and remote sensing measurements, such that the developed techniques can be extended to ungauged catchments. More than 800 gauged catchments spanning the continental United States were selected to develop the general methodology. The BFI calculation was based on the baseflow separated from daily streamflow hydrograph using HYSEP filter. The surrogate catchment attributes were compiled from multiple sources including digital elevation model, soil, landuse, climate data, other publicly available ancillary and geospatial data. 80% catchments were used to train the ML algorithms, and the remaining 20% of the catchments were used as an independent test set to measure the generalization performance of fitted models. A k-fold cross-validation using exhaustive grid search was used to fit the hyperparameters of each model. Initial model development was based on 19 independent variables, but after variable selection and feature ranking, we generated revised sparse models of BFI prediction that are based on only six catchment attributes. These key predictive variables selected after the careful evaluation of bias-variance tradeoff include average catchment elevation, slope, fraction of sand, permeability, temperature, and precipitation. The most promising algorithms exceeding an accuracy score (r-square) of 0.7 on test data include support vector machine, gradient boosted regression trees, random forests, and extremely randomized

  7. Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

    Directory of Open Access Journals (Sweden)

    Mingyue Qiu

    Full Text Available In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA. We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

  8. Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

    Science.gov (United States)

    Qiu, Mingyue; Song, Yu

    2016-01-01

    In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

  9. Predicting Covariance Matrices with Financial Conditions Indexes

    NARCIS (Netherlands)

    A. Opschoor (Anne); D.J.C. van Dijk (Dick); M. van der Wel (Michel)

    2013-01-01

    textabstractWe model the impact of financial conditions on asset market volatility and correlation. We propose extensions of (factor-)GARCH models for volatility and DCC models for correlation that allow for including indexes that measure financial conditions. In our empirical application we

  10. Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

    Science.gov (United States)

    Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

    2016-07-01

    The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  11. Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

    Science.gov (United States)

    Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

    2013-01-01

    Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

  12. Climate Prediction Center - Monitoring & Data Index

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Oceanic & Atmospheric Monitoring and Data Monitoring Weather & Climate in Realtime Climate Diagnostics Bulletin Preliminary Climate Diagnostics Bulletin Figures Monthly Atmospheric & Sea Surface

  13. Climate Prediction Center - Expert Assessments Index

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Global Climate Data & Maps > ; Global Regional Climate Maps Regional Climate Maps Banner The Monthly regional analyses products are

  14. Climate Prediction Center - Monitoring and Data Index

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News ; Atmospheric Monitoring and Data Monitoring Weather & Climate in Realtime Climate Diagnostics Bulletin Preliminary Climate Diagnostics Bulletin Figures Monthly Atmospheric & Sea Surface Temperature Indices

  15. Evidence for increasingly variable Palmer Drought Severity Index in the United States since 1895.

    Science.gov (United States)

    Rayne, Sierra; Forest, Kaya

    2016-02-15

    Annual and summertime trends towards increasingly variable values of the Palmer Drought Severity Index (PDSI) over a sub-decadal period (five years) were investigated within the contiguous United States between 1895 and the present. For the contiguous United States as a whole, there is a significant increasing trend in the five-year running minimum-maximum ranges for the annual PDSI (aPDSI5 yr(min|max, range)). During this time frame, the average aPDSI5 yr(min|max, range) has increased by about one full unit, indicating a substantial increase in drought variability over short time scales across the United States. The end members of the running aPDSI5 yr(min|max, range) highlight even more rapid changes in the drought index variability within the past 120 years. This increasing variability in the aPDSI5 yr(min|max, range) is driven primarily by changes taking place in the Pacific and Atlantic Ocean coastal climate regions, climate regions which collectively comprise one-third the area of the contiguous United States. Similar trends were found for the annual and summertime Palmer Hydrological Drought Index (PHDI), the Palmer Modified Drought Index (PMDI), and the Palmer Z Index (PZI). Overall, interannual drought patterns in the contiguous United States are becoming more extreme and difficult to predict, posing a challenge to agricultural and other water-resource related planning efforts. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Rehabilitation after stroke: predictive power of Barthel Index versus a cognitive and a motor index

    DEFF Research Database (Denmark)

    Engberg, A; Bentzen, L; Garde, B

    1995-01-01

    The aim of the present study was to investigate the predictive power of ratings of Barthel Index at Day 40 post stroke, compared with and/or combined with simultaneous ratings from a mobility scale (EG motor index) and a rather simple cognitive test scale (CT50). The parameter to be individually...... predicted was the need for special living facilities and support at discharge from a rehabilitation hospital, as well as six months later; 53 stroke patients with age median 68 years were included in this prospective study. It was shown that a combination of Barthel Index and CT50 had a stronger predictive...

  17. Polychotomization of continuous variables in regression models based on the overall C index

    Directory of Open Access Journals (Sweden)

    Bax Leon

    2006-12-01

    Full Text Available Abstract Background When developing multivariable regression models for diagnosis or prognosis, continuous independent variables can be categorized to make a prediction table instead of a prediction formula. Although many methods have been proposed to dichotomize prognostic variables, to date there has been no integrated method for polychotomization. The latter is necessary when dichotomization results in too much loss of information or when central values refer to normal states and more dispersed values refer to less preferable states, a situation that is not unusual in medical settings (e.g. body temperature, blood pressure. The goal of our study was to develop a theoretical and practical method for polychotomization. Methods We used the overall discrimination index C, introduced by Harrel, as a measure of the predictive ability of an independent regressor variable and derived a method for polychotomization mathematically. Since the naïve application of our method, like some existing methods, gives rise to positive bias, we developed a parametric method that minimizes this bias and assessed its performance by the use of Monte Carlo simulation. Results The overall C is closely related to the area under the ROC curve and the produced di(polychotomized variable's predictive performance is comparable to the original continuous variable. The simulation shows that the parametric method is essentially unbiased for both the estimates of performance and the cutoff points. Application of our method to the predictor variables of a previous study on rhabdomyolysis shows that it can be used to make probability profile tables that are applicable to the diagnosis or prognosis of individual patient status. Conclusion We propose a polychotomization (including dichotomization method for independent continuous variables in regression models based on the overall discrimination index C and clarified its meaning mathematically. To avoid positive bias in

  18. Climate Prediction Center (CPC) Madden-Julian Oscillation (MJO) Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) Madden Julian Oscillation index (MJO) is a dataset that allows evaluation of the strength and phase of the MJO during the dataset...

  19. Development of an Integrated Moisture Index for predicting species composition

    Science.gov (United States)

    Louis R. Iverson; Charles T. Scott; Martin E. Dale; Anantha Prasad

    1996-01-01

    A geographic information system (GIS) approach was used to develop an Integrated Moisture Index (IMI), which was used to predict species composition for Ohio forests. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and the water-holding capacity of the soil) were derived from elevation and soils...

  20. The Economic Value of Predicting Stock Index Returns and Volatility

    NARCIS (Netherlands)

    Marquering, W.; Verbeek, M.J.C.M.

    2000-01-01

    In this paper, we analyze the economic value of predicting index returns as well as volatility. On the basis of fairly simple linear models, estimated recursively, we produce genuine out-of-sample forecasts for the return on the S&P 500 index and its volatility. Using monthly data from 1954-1998, we

  1. Variable Lifting Index (VLI): A New Method for Evaluating Variable Lifting Tasks.

    Science.gov (United States)

    Waters, Thomas; Occhipinti, Enrico; Colombini, Daniela; Alvarez-Casado, Enrique; Fox, Robert

    2016-08-01

    We seek to develop a new approach for analyzing the physical demands of highly variable lifting tasks through an adaptation of the Revised NIOSH (National Institute for Occupational Safety and Health) Lifting Equation (RNLE) into a Variable Lifting Index (VLI). There are many jobs that contain individual lifts that vary from lift to lift due to the task requirements. The NIOSH Lifting Equation is not suitable in its present form to analyze variable lifting tasks. In extending the prior work on the VLI, two procedures are presented to allow users to analyze variable lifting tasks. One approach involves the sampling of lifting tasks performed by a worker over a shift and the calculation of the Frequency Independent Lift Index (FILI) for each sampled lift and the aggregation of the FILI values into six categories. The Composite Lift Index (CLI) equation is used with lifting index (LI) category frequency data to calculate the VLI. The second approach employs a detailed systematic collection of lifting task data from production and/or organizational sources. The data are organized into simplified task parameter categories and further aggregated into six FILI categories, which also use the CLI equation to calculate the VLI. The two procedures will allow practitioners to systematically employ the VLI method to a variety of work situations where highly variable lifting tasks are performed. The scientific basis for the VLI procedure is similar to that for the CLI originally presented by NIOSH; however, the VLI method remains to be validated. The VLI method allows an analyst to assess highly variable manual lifting jobs in which the task characteristics vary from lift to lift during a shift. © 2015, Human Factors and Ergonomics Society.

  2. Rehabilitation after stroke: predictive power of Barthel Index versus a cognitive and a motor index

    DEFF Research Database (Denmark)

    Engberg, A; Bentzen, L; Garde, B

    1995-01-01

    The aim of the present study was to investigate the predictive power of ratings of Barthel Index at Day 40 post stroke, compared with and/or combined with simultaneous ratings from a mobility scale (EG motor index) and a rather simple cognitive test scale (CT50). The parameter to be individually...

  3. Environmental variability and its relationship to site index in Mediterranean maritine pine

    Energy Technology Data Exchange (ETDEWEB)

    Bravo-Oviedo, A.; Roig, S.; Bravo, F.; Montero, G.; Rio, M. del

    2011-07-01

    Environmental variability and site productivity relationships, estimated by means of soil-site equations, are considered a milestone in decision making of forest management. The adequacy of silviculture systems is related to tree response to environmental conditions. The objectives of this paper are to study climatic and edaphic variability in Mediterranean Maritime pine (Pinus pinaster) forests in Spain, and the practical use of such variability in determining forest productivity by means of site index estimation. Principal component analysis was used to describe environmental conditions and patterns. Site index predictive models were fitted using partial least squares and parsimoniously by ordinary least square. Climatic variables along with parent material defined an ecological regionalization from warm and humid to cold and dry sites. Results showed that temperature and precipitation in autumn and winter, along with longitudinal gradient define extreme site qualities. The best qualities are located in warm and humid sites whereas the poorest ones are found in cold and dry regions. Site index values are poorly explained by soil properties. However, clay content in the first mineral horizon improved the soil-site model considerably. Climate is the main driver of productivity of Mediterranean Maritime pine in a broad scale. Site index differences within a homogenous climatic region are associated to soil properties. (Author) 47 refs.

  4. US Climate Variability and Predictability Project

    Energy Technology Data Exchange (ETDEWEB)

    Patterson, Mike [University Corporation for Atmospheric Research (UCAR), Boulder, CO (United States)

    2017-11-14

    The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year support of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.

  5. Predictive Variable Gain Iterative Learning Control for PMSM

    Directory of Open Access Journals (Sweden)

    Huimin Xu

    2015-01-01

    Full Text Available A predictive variable gain strategy in iterative learning control (ILC is introduced. Predictive variable gain iterative learning control is constructed to improve the performance of trajectory tracking. A scheme based on predictive variable gain iterative learning control for eliminating undesirable vibrations of PMSM system is proposed. The basic idea is that undesirable vibrations of PMSM system are eliminated from two aspects of iterative domain and time domain. The predictive method is utilized to determine the learning gain in the ILC algorithm. Compression mapping principle is used to prove the convergence of the algorithm. Simulation results demonstrate that the predictive variable gain is superior to constant gain and other variable gains.

  6. Variable classifications of glycemic index determined by glucose meters.

    Science.gov (United States)

    Lin, Meng-Hsueh Amanda; Wu, Ming-Chang; Lin, Jenshinn

    2010-07-01

    THE STUDY EVALUATED AND COMPARED THE DIFFERENCES OF GLUCOSE RESPONSES, INCREMENTAL AREA UNDER CURVE (IAUC), GLYCEMIC INDEX (GI) AND THE CLASSIFICATION OF GI VALUES BETWEEN MEASURED BY BIOCHEMICAL ANALYZER (FUJI AUTOMATIC BIOCHEMISTRY ANALYZER (FAA)) AND THREE GLUCOSE METERS: Accue Chek Advantage (AGM), BREEZE 2 (BGM), and Optimum Xceed (OGM). Ten healthy subjects were recruited for the study. The results showed OGM yield highest postprandial glucose responses of 119.6 +/- 1.5, followed by FAA, 118.4 +/- 1.2, BGM, 117.4 +/- 1.4 and AGM, 112.6 +/- 1.3 mg/dl respectively. FAA reached highest mean IAUC of 4156 +/- 208 mg x min/dl, followed by OGM (3835 +/- 270 mg x min/dl), BGM (3730 +/- 241 mg x min/dl) and AGM (3394 +/- 253 mg x min/dl). Among four methods, OGM produced highest mean GI value than FAA (87 +/- 5) than FAA, followed by BGM and AGM (77 +/- 1, 68 +/- 4 and 63 +/- 5, pOGM are more variable methods to determine IAUC, GI and rank GI value of food than FAA. The present result does not necessarily apply to other glucose meters. The performance of glucose meter to determine GI value of food should be evaluated and calibrated before use.

  7. Perfusion index and plethysmographic variability index in patients with interscalene nerve catheters.

    Science.gov (United States)

    Sebastiani, Anne; Philippi, Larissa; Boehme, Stefan; Closhen, Dorothea; Schmidtmann, Irene; Scherhag, Anton; Markstaller, Klaus; Engelhard, Kristin; Pestel, Gunther

    2012-12-01

    Interscalene nerve blocks provide adequate analgesia, but there are no objective criteria for early assessment of correct catheter placement. In the present study, pulse oximetry technology was used to evaluate changes in the perfusion index (PI) in both blocked and unblocked arms, and changes in the plethysmographic variability index (PVI) were evaluated once mechanical ventilation was instituted. The PI and PVI values were assessed using a Radical-7™ finger pulse oximetry device (Masimo Corp., Irvine, CA, USA) in both arms of 30 orthopedic patients who received an interscalene catheter at least 25 min before induction of general anesthesia. Data were evaluated at baseline, on application of local anesthetics; five, ten, and 15 min after onset of interscalene nerve blocks; after induction of general anesthesia; before and after a 500 mL colloid fluid challenge; and five minutes thereafter. In the 25 patients with successful blocks, the difference between the PI values in the blocked arm and the PI values in the contralateral arm increased within five minutes of the application of the local anesthetics (P < 0.05) and increased progressively until 15 min. After induction of general anesthesia, the PI increased in the unblocked arm while it remained relatively constant in the blocked arm, thus reducing the difference in the PI. A fluid challenge resulted in a decrease in PVI values in both arms. The perfusion index increases after successful interscalene nerve blockade and may be used as an indicator for successful block placement in awake patients. The PVI values before and after a fluid challenge can be useful to detect changes in preload, and this can be performed in both blocked and unblocked arms.

  8. Upper-Level Mediterranean Oscillation index and seasonal variability of rainfall and temperature

    Science.gov (United States)

    Redolat, Dario; Monjo, Robert; Lopez-Bustins, Joan A.; Martin-Vide, Javier

    2018-02-01

    The need for early seasonal forecasts stimulates continuous research in climate teleconnections. The large variability of the Mediterranean climate presents a greater difficulty in predicting climate anomalies. This article reviews teleconnection indices commonly used for the Mediterranean basin and explores possible extensions of one of them, the Mediterranean Oscillation index (MOi). In particular, the anomalies of the geopotential height field at 500 hPa are analyzed using segmentation of the Mediterranean basin in seven spatial windows: three at eastern and four at western. That is, different versions of an Upper-Level Mediterranean Oscillation index (ULMOi) were calculated, and monthly and annual variability of precipitation and temperature were analyzed for 53 observatories from 1951 to 2015. Best versions were selected according to the Pearson correlation, its related p value, and two measures of standardized error. The combination of the Balearic Sea and Libya/Egypt windows was the best for precipitation and temperature, respectively. The ULMOi showed the highest predictive ability in combination with the Atlantic Multidecadal Oscillation index (AMOi) for the annual temperature throughout the Mediterranean basin. The best model built from the indices presented a final mean error between 15 and 25% in annual precipitation for most of the studied area.

  9. Effectively Indexing Uncertain Moving Objects for Predictive Queries

    DEFF Research Database (Denmark)

    Zhang, Meihui; Chen, Su; Jensen, Christian Søndergaard

    2009-01-01

    in more complex and stochastic ways. This paper investigates the possibility of a marriage between moving-object indexing and probabilistic object modelling. Given the distributions of the current locations and velocities of moving objects, we devise an efficient inference method for the prediction...

  10. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Directory of Open Access Journals (Sweden)

    Montri Inthachot

    2016-01-01

    Full Text Available This study investigated the use of Artificial Neural Network (ANN and Genetic Algorithm (GA for prediction of Thailand’s SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid’s prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

  11. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Science.gov (United States)

    Boonjing, Veera; Intakosum, Sarun

    2016-01-01

    This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

  12. Spatial and temporal variability of Aridity Index in Greece

    Science.gov (United States)

    Nastos, Panagiotis; Politi, Nadia; Douvis, Kostas

    2010-05-01

    Drought events have deteriorated in most European regions during the last decades in frequency, duration, or intensity. Besides, increased drying associated with higher temperatures and decreased precipitation have contributed to changes in drought. Drought-affected areas are projected to increase in extent, with the potential for adverse impacts on multiple sectors, e.g. agriculture, water supply, energy production and health, according to IPCC. The objective of this study is the spatial and temporal variability of the Aridity Index (AI) per decade, in Greece during the period 1951-2000, as far as the projections of AI for the period 2051-2100, based on simulations of ensemble regional climate models (RCMs), for A1B SRES scenario. The climatic data used for the analysis concern monthly values of precipitation and air temperature from 28 meteorological stations; 22 stations from the National Hellenic Meteorological Service and 6 stations from neighboring countries. According to the United Nations Environment Programme (UNEP), AI is defined as P/PET, where P is the average annual precipitation and PET is the potential evapotranspiration, estimated by the Thornthwaite method; PET and P must be expressed in same units, e.g., in milimetres. All the meteorological data processing was carried out by the application of Geographical Information System (GIS). The results of the analysis showed that within the examined period a clear shift from "humid" class that characterized the greater area of Greece in 1950's to "sub-humid" and "semi-dry" classes appeared in mainly the eastern regions of Greece, such as eastern Crete Island, Cyclades Islands, Evia and Attica in 1990's. The future projections derived by the simulations of ensemble RCMs indicated that drier conditions are very likely to appear in Greece associated with significant socio-economic consequences. The decreasing precipitation along with the high rates of evapotranspiration, because of increase in the air

  13. Spatial and temporal variability of the Aridity Index in Greece

    Science.gov (United States)

    Nastos, Panagiotis T.; Politi, Nadia; Kapsomenakis, John

    2013-01-01

    The objective of this paper is to study the spatial and temporal variability of the Aridity Index (AI) in Greece, per decade, during the 50-year period (1951-2000). Besides, the projected changes in ensemble mean AI between the period 1961-1990 (reference period) and the periods 2021-2050 (near future) and 2071-2100 (far future) along with the inter-model standard deviations were presented, based on the simulation results, derived from a number of Regional Climatic Models (RCMs), within the ENSEMBLE European Project. The projection of the future climate was done under SRES A1B. The climatic data used, concern monthly precipitation totals and air temperature from 28 meteorological stations (22 stations from the Hellenic National Meteorological Service and 6 stations from neighboring countries, taken from the Monthly Climatic Data for the World). The estimation of the AI was carried out based on the potential evapotranspiration (PET) defined by Thornthwaite (1948). The data processing was done by the application of the statistical package R-project and the Geographical Information Systems (GIS). The results of the analysis showed that, within the examined period (1951-2000), a progressive shift from the "humid" class, which characterized the wider area of Greece, towards the "sub-humid" and "semi-arid" classes appeared in the eastern Crete Island, the Cyclades complex, the Evia and Attica, that is mainly the eastern Greece. The most significant change appears during the period 1991-2000. The future projections at the end of twentieth century, using ensemble mean simulations from 8 RCMs, show that drier conditions are expected to establish in regions of Greece (Attica, eastern continental Greece, Cyclades, Dodecanese, eastern Crete Island and northern Aegean). The inter-model standard deviation over these regions ranges from 0.02 to 0.05 against high values (0.09-0.15) illustrated in western mountainous continental Greece, during 2021-2050. Higher values of inter

  14. Predicted impact and evaluation of North Carolina's phosphorus indexing tool.

    Science.gov (United States)

    Johnson, Amy M; Osmond, Deanna L; Hodges, Steven C

    2005-01-01

    Increased concern about potential losses of phosphorus (P) from agricultural fields receiving animal waste has resulted in the implementation of new state and federal regulations related to nutrient management. In response to strengthened nutrient management standards that require consideration of P, North Carolina has developed a site-specific P indexing system called the Phosphorus Loss Assessment Tool (PLAT) to predict relative amounts of potential P loss from agricultural fields. The purpose of this study was to apply the PLAT index on farms throughout North Carolina in an attempt to predict the percentage and types of farms that will be forced to change management practices due to implementation of new regulations. Sites from all 100 counties were sampled, with the number of samples taken from each county depending on the proportion of the state's agricultural land that occurs in that county. Results showed that approximately 8% of producers in the state will be required to apply animal waste or inorganic fertilizer on a P rather than nitrogen basis, with the percentage increasing for farmers who apply animal waste (approximately 27%). The PLAT index predicted the greatest amounts of P loss from sites in the Coastal Plain region of North Carolina and from sites receiving poultry waste. Loss of dissolved P through surface runoff tended to be greater than other loss pathways and presents an area of concern as no best management practices (BMPs) currently exist for the reduction of in-field dissolved P. The PLAT index predicted the areas in the state that are known to be disproportionately vulnerable to P loss due to histories of high P applications, high densities of animal units, or soil type and landscapes that are most susceptible to P loss.

  15. Forecasting Construction Tender Price Index in Ghana using Autoregressive Integrated Moving Average with Exogenous Variables Model

    Directory of Open Access Journals (Sweden)

    Ernest Kissi

    2018-03-01

    Full Text Available Prices of construction resources keep on fluctuating due to unstable economic situations that have been experienced over the years. Clients knowledge of their financial commitments toward their intended project remains the basis for their final decision. The use of construction tender price index provides a realistic estimate at the early stage of the project. Tender price index (TPI is influenced by various economic factors, hence there are several statistical techniques that have been employed in forecasting. Some of these include regression, time series, vector error correction among others. However, in recent times the integrated modelling approach is gaining popularity due to its ability to give powerful predictive accuracy. Thus, in line with this assumption, the aim of this study is to apply autoregressive integrated moving average with exogenous variables (ARIMAX in modelling TPI. The results showed that ARIMAX model has a better predictive ability than the use of the single approach. The study further confirms the earlier position of previous research of the need to use the integrated model technique in forecasting TPI. This model will assist practitioners to forecast the future values of tender price index. Although the study focuses on the Ghanaian economy, the findings can be broadly applicable to other developing countries which share similar economic characteristics.

  16. Ratio index variables or ANCOVA? Fisher's cats revisited.

    Science.gov (United States)

    Tu, Yu-Kang; Law, Graham R; Ellison, George T H; Gilthorpe, Mark S

    2010-01-01

    Over 60 years ago Ronald Fisher demonstrated a number of potential pitfalls with statistical analyses using ratio variables. Nonetheless, these pitfalls are largely overlooked in contemporary clinical and epidemiological research, which routinely uses ratio variables in statistical analyses. This article aims to demonstrate how very different findings can be generated as a result of less than perfect correlations among the data used to generate ratio variables. These imperfect correlations result from measurement error and random biological variation. While the former can often be reduced by improvements in measurement, random biological variation is difficult to estimate and eliminate in observational studies. Moreover, wherever the underlying biological relationships among epidemiological variables are unclear, and hence the choice of statistical model is also unclear, the different findings generated by different analytical strategies can lead to contradictory conclusions. Caution is therefore required when interpreting analyses of ratio variables whenever the underlying biological relationships among the variables involved are unspecified or unclear. (c) 2009 John Wiley & Sons, Ltd.

  17. The PAPAS index: a novel index for the prediction of hepatitis C-related fibrosis.

    Science.gov (United States)

    Ozel, Banu D; Poyrazoğlu, Orhan K; Karaman, Ahmet; Karaman, Hatice; Altinkaya, Engin; Sevinç, Eylem; Zararsiz, Gökmen

    2015-08-01

    Several noninvasive tests have been developed to determine the degree of hepatic fibrosis in patients with chronic hepatitis C (CHC) without performing liver biopsy. This study aimed to determine the performance of the PAPAS (Platelet/Age/Phosphatase/AFP/AST) index in patients with CHC for the prediction of significant fibrosis and cirrhosis and to compare it with other noninvasive tests. To date, no study has evaluated the application of the PAPAS index in CHC-associated liver fibrosis. This retrospective study included 137 consecutive patients with CHC who had undergone a percutaneous liver biopsy before treatment. The aspartate aminotransferase/platelet ratio (APRI), aspartate aminotransferase/alanine transaminase ratio (AAR), age-platelet index (API), FIB4, cirrhosis discriminate score (CDS), the Göteborg University cirrhosis index (GUCI), and PAPAS were calculated and compared with the diagnostic accuracies of all fibrosis indices between the groups F0-F2 (no-mild fibrosis) versus F3-F6 (significant fibrosis) and F0-F4 (no cirrhosis) versus F5-F6 (cirrhosis). To predict significant fibrosis, the area under curve (95% confidence interval) for FIB4 was 0.727 followed by GUCI (0.721), PAPAS≈APRI≈CDS (0.716), and API (0.68). To predict cirrhosis, the area under curve (95% confidence interval) for FIB4 was calculated to be 0.735, followed by GUCI (0.723), PAPAS≈APRI≈CDS≈(0.71), and API (0.66). No statistically significant difference was observed among these predictors to exclude both significant fibrosis and cirrhosis (P>0.05). The diagnostic capability of the PAPAS index has moderate efficiency and was not superior to other fibrosis markers for the identification of fibrosis in CHC patients. There is a need for more comprehensive prospective studies to help determine the diagnostic value of PAPAS for liver fibrosis.

  18. Cumulative Mass and NIOSH Variable Lifting Index Method for Risk Assessment: Possible Relations.

    Science.gov (United States)

    Stucchi, Giulia; Battevi, Natale; Pandolfi, Monica; Galinotti, Luca; Iodice, Simona; Favero, Chiara

    2018-02-01

    Objective The aim of this study was to explore whether the Variable Lifting Index (VLI) can be corrected for cumulative mass and thus test its efficacy in predicting the risk of low-back pain (LBP). Background A validation study of the VLI method was published in this journal reporting promising results. Although several studies highlighted a positive correlation between cumulative load and LBP, cumulative mass has never been considered in any of the studies investigating the relationship between manual material handling and LBP. Method Both VLI and cumulative mass were calculated for 2,374 exposed subjects using a systematic approach. Due to high variability of cumulative mass values, a stratification within VLI categories was employed. Dummy variables (1-4) were assigned to each class and used as a multiplier factor for the VLI, resulting in a new index (VLI_CMM). Data on LBP were collected by occupational physicians at the study sites. Logistic regression was used to estimate the risk of acute LBP within levels of risk exposure when compared with a control group formed by 1,028 unexposed subjects. Results Data showed greatly variable values of cumulative mass across all VLI classes. The potential effect of cumulative mass on damage emerged as not significant ( p value = .6526). Conclusion When comparing VLI_CMM with raw VLI, the former failed to prove itself as a better predictor of LBP risk. Application To recognize cumulative mass as a modifier, especially for lumbar degenerative spine diseases, authors of future studies should investigate potential association between the VLI and other damage variables.

  19. Empirical modelling to predict the refractive index of human blood

    Science.gov (United States)

    Yahya, M.; Saghir, M. Z.

    2016-02-01

    Optical techniques used for the measurement of the optical properties of blood are of great interest in clinical diagnostics. Blood analysis is a routine procedure used in medical diagnostics to confirm a patient’s condition. Measuring the optical properties of blood is difficult due to the non-homogenous nature of the blood itself. In addition, there is a lot of variation in the refractive indices reported in the literature. These are the reasons that motivated the researchers to develop a mathematical model that can be used to predict the refractive index of human blood as a function of concentration, temperature and wavelength. The experimental measurements were conducted on mimicking phantom hemoglobin samples using the Abbemat Refractometer. The results analysis revealed a linear relationship between the refractive index and concentration as well as temperature, and a non-linear relationship between refractive index and wavelength. These results are in agreement with those found in the literature. In addition, a new formula was developed based on empirical modelling which suggests that temperature and wavelength coefficients be added to the Barer formula. The verification of this correlation confirmed its ability to determine refractive index and/or blood hematocrit values with appropriate clinical accuracy.

  20. Empirical modelling to predict the refractive index of human blood

    International Nuclear Information System (INIS)

    Yahya, M; Saghir, M Z

    2016-01-01

    Optical techniques used for the measurement of the optical properties of blood are of great interest in clinical diagnostics. Blood analysis is a routine procedure used in medical diagnostics to confirm a patient’s condition. Measuring the optical properties of blood is difficult due to the non-homogenous nature of the blood itself. In addition, there is a lot of variation in the refractive indices reported in the literature. These are the reasons that motivated the researchers to develop a mathematical model that can be used to predict the refractive index of human blood as a function of concentration, temperature and wavelength. The experimental measurements were conducted on mimicking phantom hemoglobin samples using the Abbemat Refractometer. The results analysis revealed a linear relationship between the refractive index and concentration as well as temperature, and a non-linear relationship between refractive index and wavelength. These results are in agreement with those found in the literature. In addition, a new formula was developed based on empirical modelling which suggests that temperature and wavelength coefficients be added to the Barer formula. The verification of this correlation confirmed its ability to determine refractive index and/or blood hematocrit values with appropriate clinical accuracy. (paper)

  1. Prediction of Cerebral Hyperperfusion Syndrome with Velocity Blood Pressure Index

    Directory of Open Access Journals (Sweden)

    Zhi-Chao Lai

    2015-01-01

    Full Text Available Background: Cerebral hyperperfusion syndrome is an important complication of carotid endarterectomy (CEA. An >100% increase in middle cerebral artery velocity (MCAV after CEA is used to predict the cerebral hyperperfusion syndrome (CHS development, but the accuracy is limited. The increase in blood pressure (BP after surgery is a risk factor of CHS, but no study uses it to predict CHS. This study was to create a more precise parameter for prediction of CHS by combined the increase of MCAV and BP after CEA. Methods: Systolic MCAV measured by transcranial Doppler and systematic BP were recorded preoperatively; 30 min postoperatively. The new parameter velocity BP index (VBI was calculated from the postoperative increase ratios of MCAV and BP. The prediction powers of VBI and the increase ratio of MCAV (velocity ratio [VR] were compared for predicting CHS occurrence. Results: Totally, 6/185 cases suffered CHS. The best-fit cut-off point of 2.0 for VBI was identified, which had 83.3% sensitivity, 98.3% specificity, 62.5% positive predictive value and 99.4% negative predictive value for CHS development. This result is significantly better than VR (33.3%, 97.2%, 28.6% and 97.8%. The area under the curve (AUC of receiver operating characteristic: AUC VBI = 0.981, 95% confidence interval [CI] 0.949-0.995; AUC VR = 0.935, 95% CI 0.890-0.966, P = 0.02. Conclusions: The new parameter VBI can more accurately predict patients at risk of CHS after CEA. This observation needs to be validated by larger studies.

  2. Prediction of Cerebral Hyperperfusion Syndrome with Velocity Blood Pressure Index.

    Science.gov (United States)

    Lai, Zhi-Chao; Liu, Bao; Chen, Yu; Ni, Leng; Liu, Chang-Wei

    2015-06-20

    Cerebral hyperperfusion syndrome is an important complication of carotid endarterectomy (CEA). An >100% increase in middle cerebral artery velocity (MCAV) after CEA is used to predict the cerebral hyperperfusion syndrome (CHS) development, but the accuracy is limited. The increase in blood pressure (BP) after surgery is a risk factor of CHS, but no study uses it to predict CHS. This study was to create a more precise parameter for prediction of CHS by combined the increase of MCAV and BP after CEA. Systolic MCAV measured by transcranial Doppler and systematic BP were recorded preoperatively; 30 min postoperatively. The new parameter velocity BP index (VBI) was calculated from the postoperative increase ratios of MCAV and BP. The prediction powers of VBI and the increase ratio of MCAV (velocity ratio [VR]) were compared for predicting CHS occurrence. Totally, 6/185 cases suffered CHS. The best-fit cut-off point of 2.0 for VBI was identified, which had 83.3% sensitivity, 98.3% specificity, 62.5% positive predictive value and 99.4% negative predictive value for CHS development. This result is significantly better than VR (33.3%, 97.2%, 28.6% and 97.8%). The area under the curve (AUC) of receiver operating characteristic: AUC(VBI) = 0.981, 95% confidence interval [CI] 0.949-0.995; AUC(VR) = 0.935, 95% CI 0.890-0.966, P = 0.02. The new parameter VBI can more accurately predict patients at risk of CHS after CEA. This observation needs to be validated by larger studies.

  3. Granger Causality Between The Stock Market Index and Macroeconomic Variables. A Study of Malaysia and Singapore

    OpenAIRE

    Sircar, Shadee Mosaddek

    2009-01-01

    This paper investigates the causal relationships that may be present between the stock market index of developing countries and their macroeconomic variables based on the Vector Error Correction Model (VECM) framework. The countries Malaysia and Singapore are chosen for the purpose of this paper, where FTSE KLCI index and the FTSE STI index are used to represent the stock market performances respectively for each country. The four macroeconomic variables analyzed and used in this paper are Co...

  4. Macroeconomic Variables Affecting Bist30 Index Value in Turkey

    OpenAIRE

    Özge KORKMAZ; Eşref Savas BASCI; Süleyman Serdar KARACA

    2016-01-01

    In finance literature, main financial stock indices are important to determine country’s financial development and it’s behavior against the effect of macro-economic conditions. These conditions can listed as interest rate, inflation rate, money supply, exchange rate, industrial production index, and etc.  In changing world economy, macro economic conditions can affect to the financial stability and capital markets. Some economies have a financial vulnerability, and it is important to measure...

  5. AIR POLLUITON INDEX PREDICTION USING MULTIPLE NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Zainal Ahmad

    2017-05-01

    Full Text Available Air quality monitoring and forecasting tools are necessary for the purpose of taking precautionary measures against air pollution, such as reducing the effect of a predicted air pollution peak on the surrounding population and ecosystem. In this study a single Feed-forward Artificial Neural Network (FANN is shown to be able to predict the Air Pollution Index (API with a Mean Squared Error (MSE and coefficient determination, R2, of 0.1856 and 0.7950 respectively. However, due to the non-robust nature of single FANN, a selective combination of Multiple Neural Networks (MNN is introduced using backward elimination and a forward selection method. The results show that both selective combination methods can improve the robustness and performance of the API prediction with the MSE and R2 of 0.1614 and 0.8210 respectively. This clearly shows that it is possible to reduce the number of networks combined in MNN for API prediction, without losses of any information in terms of the performance of the final API prediction model.

  6. Accuracy of Body Mass Index Versus Lean Mass Index for Prediction of Sarcopenia in Older Women.

    Science.gov (United States)

    Benton, M J; Silva-Smith, A L

    2018-01-01

    We compared accuracy of body mass index (BMI) versus lean mass index (LMI) to predict sarcopenia in 58 community-dwelling women (74.1±0.9 years). Lean mass was measured with multi-frequency bioelectrical impedance analysis, and strength was measured with Arm Curl test, Chair Stand test, and handgrip dynamometry. Sarcopenia was defined as low LMI. When categorized by BMI, normal women had less absolute lean mass (37.6±1.0 vs. 42.6±0.9 kg; Plean mass (14.1±0.2 vs. 16.1±0.2 kg/m2; Plean mass (44.0±0.7 vs. 35.7±0.7 kg; Plean mass (16.2±0.2 vs. 13.8±0.2 kg/m2; Plean mass and strength. For clinical assessment, calculation of LMI rather than BMI is appropriate.

  7. distribution of hourly variability index of sky clearness

    African Journals Online (AJOL)

    Mgina

    Clouds affect the values of insolation for solar technology and other applications. To detect the presence of variability in the sky ... It appears that the site has great potential for application of solar technologies. INTRODUCTION. Knowledge about the .... for solar collectors-part 1. Thermal performance of glazed liquid heating.

  8. Predictive Index The Incidence Of Tuberculosis Children In South Kalimantan Province

    Directory of Open Access Journals (Sweden)

    Bahrul Ilmi

    2015-08-01

    Full Text Available The research objective to formulate predictive index of Tuberculosis Children in South Kalimantan province. Research methods combined mixed methods with a combination of research model Sequential Exploratory Design qualitative approach to support quantitative and centered on quantitative Sugiono 2012 case control design. The number of qualitative sample was 16 respondents to interviews and 48 respondents for FGD. The number of quantitative research sample was 216 consisted of 62 cases and 154 controls. Qualitative sampling by purposive sampling and quantitative Multi-stage Cluster random sampling on 3 stages. The analysis technique used is descriptive qualitative and Confirmatory Factor Analysis Confirmatory Factor Analysis measure the latent of variables by using path analysis path analysis with the program Linear Structural Relationships LISREL. The results showed a positive effect on the socio-cultural environment and significantly associated with the incidence of Tuberculosis Children. While the physical environment of the house positively and significantly with biological environments and the incidence of Tuberculosis Children and immunization and nutrition status of children positively and significantly to the incidence of Tuberculosis of the Child as well as to the biological environment positive and significant effect on the incidence of TB Children. Formulation Predictive Index of Tuberculosis Children in South Kalimantan province. is index 019 Physical Environment Home 044 053 Biological Environment Social Environment Culture 019 Status Immunization and Child Nutrition. The results of all the R-square value indicates that all of the R-square values 0.5. This means that a predictive model of TB Kids index has met the required Goodness of Fit. New findings from research of this dissertation are 1. Research Variable of social networks social support and collective efficacy were associated with the incidence of Tuberculosis Children. 2

  9. The predictive content of CBOE crude oil volatility index

    Science.gov (United States)

    Chen, Hongtao; Liu, Li; Li, Xiaolei

    2018-02-01

    Volatility forecasting is an important issue in the area of econophysics. The information content of implied volatility for financial return volatility has been well documented in the literature but very few studies focus on oil volatility. In this paper, we show that the CBOE crude oil volatility index (OVX) has predictive ability for spot volatility of WTI and Brent oil returns, from both in-sample and out-of-sample perspectives. Including OVX-based implied volatility in GARCH-type volatility models can improve forecasting accuracy most of time. The predictability from OVX to spot volatility is also found for longer forecasting horizons of 5 days and 20 days. The simple GARCH(1,1) and fractionally integrated GARCH with OVX performs significantly better than the other OVX models and all 6 univariate GARCH-type models without OVX. Robustness test results suggest that OVX provides different information from as short-term interest rate.

  10. Limit theorems for multi-indexed sums of random variables

    CERN Document Server

    Klesov, Oleg

    2014-01-01

    Presenting the first unified treatment of limit theorems for multiple sums of independent random variables, this volume fills an important gap in the field. Several new results are introduced, even in the classical setting, as well as some new approaches that are simpler than those already established in the literature. In particular, new proofs of the strong law of large numbers and the Hajek-Renyi inequality are detailed. Applications of the described theory include Gibbs fields, spin glasses, polymer models, image analysis and random shapes. Limit theorems form the backbone of probability theory and statistical theory alike. The theory of multiple sums of random variables is a direct generalization of the classical study of limit theorems, whose importance and wide application in science is unquestionable. However, to date, the subject of multiple sums has only been treated in journals. The results described in this book will be of interest to advanced undergraduates, graduate students and researchers who ...

  11. Predictive modeling and reducing cyclic variability in autoignition engines

    Science.gov (United States)

    Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob

    2016-08-30

    Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.

  12. Prediction of Mortality with A Body Shape Index in Young Asians: Comparison with Body Mass Index and Waist Circumference.

    Science.gov (United States)

    Lee, Da-Young; Lee, Mi-Yeon; Sung, Ki-Chul

    2018-06-01

    This paper investigated the impact of A Body Shape Index (ABSI) on the risk of all-cause mortality compared with the impact of waist circumference (WC) and body mass index (BMI). This paper reviewed data of 213,569 Korean adults who participated in health checkups between 2002 and 2012 at Kangbuk Samsung Hospital in Seoul, Korea. A multivariate Cox proportional hazard analysis was performed on the BMI, WC, and ABSI z score continuous variables as well as quintiles. During 1,168,668.7 person-years, 1,107 deaths occurred. As continuous variables, a significant positive relationship with the risk of all-cause death was found only in ABSI z scores after adjustment for age, sex, current smoking, alcohol consumption, regular exercise, presence of diabetes or hypertension, and history of cardiovascular diseases. In Cox analysis of quintiles, quintile 5 of the ABSI z score showed significantly increased hazard ratios (HRs) for mortality risk (HR [95% CI] was 1.32 [1.05-1.66]), whereas the risk for all-cause mortality, on the other hand, decreased in quintiles 3 through 5 of BMI and WC compared with their first quintiles after adjusting for several confounders. This study showed that the predictive value of ABSI for mortality risk was strong for a sample of young Asian participants and that its usefulness was better than BMI or WC. © 2018 The Obesity Society.

  13. An efficient link prediction index for complex military organization

    Science.gov (United States)

    Fan, Changjun; Liu, Zhong; Lu, Xin; Xiu, Baoxin; Chen, Qing

    2017-03-01

    Quality of information is crucial for decision-makers to judge the battlefield situations and design the best operation plans, however, real intelligence data are often incomplete and noisy, where missing links prediction methods and spurious links identification algorithms can be applied, if modeling the complex military organization as the complex network where nodes represent functional units and edges denote communication links. Traditional link prediction methods usually work well on homogeneous networks, but few for the heterogeneous ones. And the military network is a typical heterogeneous network, where there are different types of nodes and edges. In this paper, we proposed a combined link prediction index considering both the nodes' types effects and nodes' structural similarities, and demonstrated that it is remarkably superior to all the 25 existing similarity-based methods both in predicting missing links and identifying spurious links in a real military network data; we also investigated the algorithms' robustness under noisy environment, and found the mistaken information is more misleading than incomplete information in military areas, which is different from that in recommendation systems, and our method maintained the best performance under the condition of small noise. Since the real military network intelligence must be carefully checked at first due to its significance, and link prediction methods are just adopted to purify the network with the left latent noise, the method proposed here is applicable in real situations. In the end, as the FINC-E model, here used to describe the complex military organizations, is also suitable to many other social organizations, such as criminal networks, business organizations, etc., thus our method has its prospects in these areas for many tasks, like detecting the underground relationships between terrorists, predicting the potential business markets for decision-makers, and so on.

  14. Pulmonary edema predictive scoring index (PEPSI), a new index to predict risk of reperfusion pulmonary edema and improvement of hemodynamics in percutaneous transluminal pulmonary angioplasty.

    Science.gov (United States)

    Inami, Takumi; Kataoka, Masaharu; Shimura, Nobuhiko; Ishiguro, Haruhisa; Yanagisawa, Ryoji; Taguchi, Hiroki; Fukuda, Keiichi; Yoshino, Hideaki; Satoh, Toru

    2013-07-01

    This study sought to identify useful predictors for hemodynamic improvement and risk of reperfusion pulmonary edema (RPE), a major complication of this procedure. Percutaneous transluminal pulmonary angioplasty (PTPA) has been reported to be effective for the treatment of chronic thromboembolic pulmonary hypertension (CTEPH). PTPA has not been widespread because RPE has not been well predicted. We included 140 consecutive procedures in 54 patients with CTEPH. The flow appearance of the target vessels was graded into 4 groups (Pulmonary Flow Grade), and we proposed PEPSI (Pulmonary Edema Predictive Scoring Index) = (sum total change of Pulmonary Flow Grade scores) × (baseline pulmonary vascular resistance). Correlations between occurrence of RPE and 11 variables, including hemodynamic parameters, number of target vessels, and PEPSI, were analyzed. Hemodynamic parameters significantly improved after median observation period of 6.4 months, and the sum total changes in Pulmonary Flow Grade scores were significantly correlated with the improvement in hemodynamics. Multivariate analysis revealed that PEPSI was the strongest factor correlated with the occurrence of RPE (p PEPSI to be a useful marker of the risk of RPE (cutoff value 35.4, negative predictive value 92.3%). Pulmonary Flow Grade score is useful in determining therapeutic efficacy, and PEPSI is highly supportive to reduce the risk of RPE after PTPA. Using these 2 indexes, PTPA could become a safe and common therapeutic strategy for CTEPH. Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  15. Can bispectral index or auditory evoked potential index predict implicit memory during propofol-induced sedation?

    Science.gov (United States)

    Wang, Yun; Yue, Yun; Sun, Yong-hai; Wu, An-shi

    2006-06-05

    Some patients still suffer from implicit memory of intraoperative events under adequate depth of anaesthesia. The elimination of implicit memory should be a necessary aim of clinical general anaesthesia. However, implicit memory cannot be tested during anaesthesia yet. We propose bispectral index (BIS) and auditory evoked potential index (AEPI), as predictors of implicit memory during anaesthesia. Thirty-six patients were equally divided into 3 groups according to the Observer's Assessment of Alertness/Sedation Score: A, level 3; B, level 2; and C, level 1. Every patient was given the first auditory stimulus before sedation. Then every patient received the second auditory stimulus after the target level of sedation had been reached. BIS and AEPI were monitored before and after the second auditory stimulus presentation. Four hours later, the inclusion test and exclusion test were performed on the ward using process dissociation procedure and the scores of implicit memory estimated. In groups A and B but not C, implicit memory estimates were statistically greater than zero (P memory scores in group A did not differ significantly from those in group B (P > 0.05). Implicit memory scores correlated with BIS and AEPI (P AEPI. The 95% cutoff points of BIS and AEPI for predicting implicit memory are 47 and 28, respectively. Implicit memory does not disappear until the depth of sedation increases to level 1 of OAA/S score. Implicit memory scores correlate well with BIS and AEPI during sedation. BIS is a better index for predicting implicit memory than AEPI during propofol induced sedation.

  16. Extremes of shock index predicts death in trauma patients

    Directory of Open Access Journals (Sweden)

    Stephen R Odom

    2016-01-01

    Full Text Available Context: We noted a bimodal relationship between mortality and shock index (SI, the ratio of heart rate to systolic blood pressure. Aims: To determine if extremes of SI can predict mortality in trauma patients. Settings and Designs: Retrospective evaluation of adult trauma patients at a tertiary care center from 2000 to 2012 in the United States. Materials and Methods: We examined the SI in trauma patients and determined the adjusted mortality for patients with and without head injuries. Statistical Analysis Used: Descriptive statistics and multivariable logistic regression. Results: SI values demonstrated a U-shaped relationship with mortality. Compared with patients with a SI between 0.5 and 0.7, patients with a SI of 1.3 had an odds ratio of death of 3.1. (95% CI 1.6–5.9. Elevated SI is associated with increased mortality in patients with isolated torso injuries, and is associated with death at both low and high values in patients with head injury. Conclusion: Our data indicate a bimodal relationship between SI and mortality in head injured patients that persists after correction for various co-factors. The distribution of mortality is different between head injured patients and patients without head injuries. Elevated SI predicts death in all trauma patients, but low SI values only predict death in head injured patients.

  17. Variable discrete ordinates method for radiation transfer in plane-parallel semi-transparent media with variable refractive index

    Science.gov (United States)

    Sarvari, S. M. Hosseini

    2017-09-01

    The traditional form of discrete ordinates method is applied to solve the radiative transfer equation in plane-parallel semi-transparent media with variable refractive index through using the variable discrete ordinate directions and the concept of refracted radiative intensity. The refractive index are taken as constant in each control volume, such that the direction cosines of radiative rays remain non-variant through each control volume, and then, the directions of discrete ordinates are changed locally by passing each control volume, according to the Snell's law of refraction. The results are compared by the previous studies in this field. Despite simplicity, the results show that the variable discrete ordinate method has a good accuracy in solving the radiative transfer equation in the semi-transparent media with arbitrary distribution of refractive index.

  18. Droughts in Amazonia: Spatiotemporal Variability, Teleconnections, and Seasonal Predictions

    Science.gov (United States)

    Lima, Carlos H. R.; AghaKouchak, Amir

    2017-12-01

    Most Amazonia drought studies have focused on rainfall deficits and their impact on river discharges, while the analysis of other important driver variables, such as temperature and soil moisture, has attracted less attention. Here we try to better understand the spatiotemporal dynamics of Amazonia droughts and associated climate teleconnections as characterized by the Palmer Drought Severity Index (PDSI), which integrates information from rainfall deficit, temperature anomalies, and soil moisture capacity. The results reveal that Amazonia droughts are most related to one dominant pattern across the entire region, followed by two seesaw kind of patterns: north-south and east-west. The main two modes are correlated with sea surface temperature (SST) anomalies in the tropical Pacific and Atlantic oceans. The teleconnections associated with global SST are then used to build a seasonal forecast model for PDSI over Amazonia based on predictors obtained from a sparse canonical correlation analysis approach. A unique feature of the presented drought prediction method is using only a few number of predictors to avoid excessive noise in the predictor space. Cross-validated results show correlations between observed and predicted spatial average PDSI up to 0.60 and 0.45 for lead times of 5 and 9 months, respectively. To the best of our knowledge, this is the first study in the region that, based on cross-validation results, leads to appreciable forecast skills for lead times beyond 4 months. This is a step forward in better understanding the dynamics of Amazonia droughts and improving risk assessment and management, through improved drought forecasting.

  19. Does the arrival index predict physiological stress reactivity in children.

    Science.gov (United States)

    de Veld, Danielle M J; Riksen-Walraven, J Marianne; de Weerth, Carolina

    2014-09-01

    Knowledge about children's stress reactivity and its correlates is mostly based on one stress task, making it hard to assess the generalizability of the results. The development of an additional stress paradigm for children, that also limits stress exposure and test time, could greatly advance this field of research. Research in adults may provide a starting point for the development of such an additional stress paradigm, as changes in salivary cortisol and alpha-amylase (sAA) over a 1-h pre-stress period in the laboratory correlated strongly with subsequent reactivity to stress task (Balodis et al., 2010, Psychoneuroendocrinology 35:1363-73). The present study examined whether such strong correlations could be replicated in 9- to 11-year-old children. Cortisol and sAA samples were collected from 158 children (83 girls) during a 2.5-h visit to the laboratory. This visit included a 1-h pre-stress period in which children performed some non-stressful tasks and relaxed before taking part in a psychosocial stress task (TSST-C). A higher cortisol arrival index was significantly and weakly correlated with a higher AUCg but unrelated to cortisol reactivity to the stressor. A higher sAA arrival index was significantly and moderately related to lower stress reactivity and to a lower AUCi. Children's personality and emotion regulation variables were unrelated to the cortisol and sAA arrival indices. The results of this study do not provide a basis for the development of an additional stress paradigm for children. Further replications in children and adults are needed to clarify the potential meaning of an arrival index.

  20. Macroeconomic Variables, International Islamic Indices, and The Return Volatility in Jakarta Islamic Index

    Directory of Open Access Journals (Sweden)

    Yoghi Citra Pratama

    2018-01-01

    Full Text Available According to understand the behavior of Islamic equity markets the primary objective of this research is to analyze the effect of macroeconomic indicators and International Islamic Index on return volatility of Jakarta Islamic Index. The analysis method used in this study is AutoRegressive Conditional Heteroscedastic-Generalized AutoRegressive Conditional Heteroscedastic (ARCH-GARCH. The result of this research showed that all variables, i.e., BI rate, inflation rate, IDR-USD exchange rate, DJIUS index, DJIUK index, FTSJP index and FTSMY index have a simultaneously significant impact on return volatility of JII. While t-test results show that BI rate, IDR-USD exchange rate, DJIUK index and FTSMY index have a substantial effect on return volatility of JII.DOI: 10.15408/aiq.v10i1.5550

  1. Prediction of Massive Transfusion in Trauma Patients with Shock Index, Modified Shock Index, and Age Shock Index

    Directory of Open Access Journals (Sweden)

    Cheng-Shyuan Rau

    2016-07-01

    Full Text Available Objectives: The shock index (SI and its derivations, the modified shock index (MSI and the age shock index (Age SI, have been used to identify trauma patients with unstable hemodynamic status. The aim of this study was to evaluate their use in predicting the requirement for massive transfusion (MT in trauma patients upon arrival at the hospital. Participants: A patient receiving transfusion of 10 or more units of packed red blood cells or whole blood within 24 h of arrival at the emergency department was defined as having received MT. Detailed data of 2490 patients hospitalized for trauma between 1 January 2009, and 31 December 2014, who had received blood transfusion within 24 h of arrival at the emergency department, were retrieved from the Trauma Registry System of a level I regional trauma center. These included 99 patients who received MT and 2391 patients who did not. Patients with incomplete registration data were excluded from the study. The two-sided Fisher exact test or Pearson chi-square test were used to compare categorical data. The unpaired Student t-test was used to analyze normally distributed continuous data, and the Mann-Whitney U-test was used to compare non-normally distributed data. Parameters including systolic blood pressure (SBP, heart rate (HR, hemoglobin level (Hb, base deficit (BD, SI, MSI, and Age SI that could provide cut-off points for predicting the patients’ probability of receiving MT were identified by the development of specific receiver operating characteristic (ROC curves. High accuracy was defined as an area under the curve (AUC of more than 0.9, moderate accuracy was defined as an AUC between 0.9 and 0.7, and low accuracy was defined as an AUC less than 0.7. Results: In addition to a significantly higher Injury Severity Score (ISS and worse outcome, the patients requiring MT presented with a significantly higher HR and lower SBP, Hb, and BD, as well as significantly increased SI, MSI, and Age SI. Among

  2. Predicting Bond Betas using Macro-Finance Variables

    DEFF Research Database (Denmark)

    Aslanidis, Nektarios; Christiansen, Charlotte; Cipollini, Andrea

    We conduct in-sample and out-of-sample forecasting using the new approach of combining explanatory variables through complete subset regressions (CSR). We predict bond CAPM betas and bond returns conditioning on various macro-fi…nance variables. We explore differences across long-term government ...... bonds, investment grade corporate bonds, and high-yield corporate bonds. The CSR method performs well in predicting bond betas, especially in-sample, and, mainly high-yield bond betas when the focus is out-of-sample. Bond returns are less predictable than bond betas....

  3. An analysis of prediction skill of monthly mean climate variability

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Arun; Chen, Mingyue; Wang, Wanqiu [Climate Prediction Center, National Centers for Environmental Prediction (CPC/NCEP), Camp Springs, MD (United States)

    2011-09-15

    In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30-40 days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability. (orig.)

  4. Identify the dominant variables to predict stream water temperature

    Science.gov (United States)

    Chien, H.; Flagler, J.

    2016-12-01

    Stream water temperature is a critical variable controlling water quality and the health of aquatic ecosystems. Accurate prediction of water temperature and the assessment of the impacts of environmental variables on water temperature variation are critical for water resources management, particularly in the context of water quality and aquatic ecosystem sustainability. The objective of this study is to measure stream water temperature and air temperature and to examine the importance of streamflow on stream water temperature prediction. The measured stream water temperature and air temperature will be used to test two hypotheses: 1) streamflow is a relatively more important factor than air temperature in regulating water temperature, and 2) by combining air temperature and streamflow data stream water temperature can be more accurately estimated. Water and air temperature data loggers are placed at two USGS stream gauge stations #01362357and #01362370, located in the upper Esopus Creek watershed in Phonecia, NY. The ARIMA (autoregressive integrated moving average) time series model is used to analyze the measured water temperature data, identify the dominant environmental variables, and predict the water temperature with identified dominant variable. The preliminary results show that streamflow is not a significant variable in predicting stream water temperature at both USGS gauge stations. Daily mean air temperature is sufficient to predict stream water temperature at this site scale.

  5. Predictive model for the heat capacity of ionic liquids using the mass connectivity index

    International Nuclear Information System (INIS)

    Valderrama, Jose O.; Martinez, Gwendolyn; Rojas, Roberto E.

    2011-01-01

    A simple and accurate model to predict the heat capacity of ionic liquids is presented. The proposed model considers variables readily available for ionic liquids and that have important effect on heat capacity, according to the literature information. Additionally a recently defined structural parameter known as mass connectivity index is incorporated into the model. A set of 602 heat capacity data for 146 ionic liquids have been used in the study. The results were compared with experimental data and with values reported by other available estimation methods. Results show that the new simple correlation gives low deviations and can be used with confidence in thermodynamic and engineering calculations.

  6. Variability of the autoregulation index decreases after removing the effect of the very low frequency band

    NARCIS (Netherlands)

    Elting, J. W.; Maurits, N. M.; Aries, M. J. H.

    Dynamic cerebral autoregulation (dCA) estimates show large between and within subject variability. Sources of variability include low coherence and influence of CO2 in the very low frequency (VLF) band, where dCA is active. This may lead to unreliable transfer function and autoregulation index (ARI)

  7. The TyG index may predict the development of cardiovascular events.

    Science.gov (United States)

    Sánchez-Íñigo, Laura; Navarro-González, David; Fernández-Montero, Alejandro; Pastrana-Delgado, Juan; Martínez, Jose Alfredo

    2016-02-01

    Cardiovascular disease (CVD) is the worldwide leading cause of morbidity and mortality. An early risk detection of apparently healthy people before CVD onset has clinical relevance in the prevention of cardiovascular events. We evaluated the association between the product of fasting plasma glucose and triglycerides (TyG index) and CVD. A total of 5014 patients of the Vascular Metabolic CUN cohort (VMCUN cohort) were followed up during a median period of 10 years. We used a Cox proportional-hazard ratio with repeated measures to estimate the risk of incidence of CVD across quintiles of the TyG index, calculated as ln[fasting triglycerides (mg/dL) × fasting plasma glucose (mg(dL)/2], and plotted a receiver-operating characteristics (ROC) curve to compare a prediction model fitted on the variables used in the Framingham risk score, a new model containing the Framingham variables with the TyG index, and the risk of coronary heart disease. A higher level of TyG index was significantly associated with an increased risk of developing CVD independent of confounding factors with a value of 2·32 (95% CI: 1·65-3·26) for those in the highest quintile and 1·52 (95% CI: 1·07-2·16) for those in the fourth quintile. The areas under the curve (AUC) of the ROC plots were 0·708 (0·68-0·73) for the Framingham model and 0·719 (0·70-0·74) for the Framingham + TyG index model (P = 0·014). The TyG index, a simple measure reflecting insulin resistance, might be useful to early identify individuals at a high risk of developing a cardiovascular event. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

  8. The dynamic relationship between Bursa Malaysia composite index and macroeconomic variables

    Science.gov (United States)

    Ismail, Mohd Tahir; Rose, Farid Zamani Che; Rahman, Rosmanjawati Abd.

    2017-08-01

    This study investigates and analyzes the long run and short run relationships between Bursa Malaysia Composite index (KLCI) and nine macroeconomic variables in a VAR/VECM framework. After regression analysis seven out the nine macroeconomic variables are chosen for further analysis. The use of Johansen-Juselius Cointegration and Vector Error Correction Model (VECM) technique indicate that there are long run relationships between the seven macroeconomic variables and KLCI. Meanwhile, Granger causality test shows that bidirectional relationship between KLCI and oil price. Furthermore, after 12 months the shock on KLCI are explained by innovations of the seven macroeconomic variables. This indicate the close relationship between macroeconomic variables and KLCI.

  9. Prediction Center (CPC) Polar Eurasia Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Polar-Eurasia teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal...

  10. Climate Prediction Center (CPC) Pacific Transition Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Pacific Transition teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal...

  11. Climate Prediction Center (CPC) East Atlantic Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the East Atlantic Teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal...

  12. Prediction Center (CPC) Tropical/ Northern Hemisphere Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Tropical/ Northern Hemisphere teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated...

  13. Climate Prediction Center (CPC) West Pacific Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the West Pacific (WP) teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal...

  14. Climate Prediction Center (CPC) Scandinavia Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Scandinavia teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal component...

  15. Nuclear Division Index may Predict Neoplastic Colorectal Lesions.

    Science.gov (United States)

    Ionescu, Mirela E; Ciocirlan, Mihai; Becheanu, Gabriel; Nicolaie, Tudor; Ditescu, Cristina; Teiusanu, Adriana G; Gologan, Serban I; Arbanas, Tudor; Diculescu, Mircea M

    2011-07-01

    Colorectal cancer (CRC) develops by accumulation of multiple genetic damages leading to genetic instability that can be evaluated by cytogenetic methods. In the current study we used Cytokinesis-Blocked Micronucleus Assay (CBMN) technique to assess the behavior of Nuclear Division Index(NDI) in peripheral lymphocytes of patients with CRC and polyps versus patients with normal colonoscopy. Blood samples were collected from patients after informed consent. By CBMN technique we assessed the proportion of mono-nucleated, bi-nucleated, tri-nucleated and tetra-nucleated cells/500 cells, to calculate NDI. Data were statistically analyzed using the SPSS 11.0 package. 45 patients were available for analysis, 23 men and 22 women, with a mean age of 58.7±13.5. 17 had normal colonoscopy, 17 colonic polyps and 11 CRC. The mean NDI values were significantly smaller for patients with CRC or polyps than in patients with normal colonoscopy (1.57 vs 1.73, p=0.013). The difference persisted for patients with neoplastic lesions (adenomas and carcinomas) when compared with patients with normal colonoscopy or non neoplastic (hyperplastic) polyps (1.56 vs.1.71, p=0.018). The NDI cut-off value to predict the presence of adenomas or carcinomas was equal to 1.55 with a 54.2% sensitivity and 81% specificity of lower values (p=0.019). The NDI cut off value to predict the presence of advanced adenomas or cancer was 1.525 for a sensitivity of 56.3% and a specificity of 82.8% (p=0.048). NDI may be useful in screening strategies for colorectal cancer as simple, noninvasive, inexpensive cytogenetic biomarker.

  16. Variable context Markov chains for HIV protease cleavage site prediction.

    Science.gov (United States)

    Oğul, Hasan

    2009-06-01

    Deciphering the knowledge of HIV protease specificity and developing computational tools for detecting its cleavage sites in protein polypeptide chain are very desirable for designing efficient and specific chemical inhibitors to prevent acquired immunodeficiency syndrome. In this study, we developed a generative model based on a generalization of variable order Markov chains (VOMC) for peptide sequences and adapted the model for prediction of their cleavability by certain proteases. The new method, called variable context Markov chains (VCMC), attempts to identify the context equivalence based on the evolutionary similarities between individual amino acids. It was applied for HIV-1 protease cleavage site prediction problem and shown to outperform existing methods in terms of prediction accuracy on a common dataset. In general, the method is a promising tool for prediction of cleavage sites of all proteases and encouraged to be used for any kind of peptide classification problem as well.

  17. Days on radiosensitivity: individual variability and predictive tests

    International Nuclear Information System (INIS)

    2008-01-01

    The radiosensitivity is a part of usual clinical observations. It is already included in the therapy protocols. however, some questions stay on its individual variability and on the difficulty to evaluate it. The point will be stocked on its origin and its usefulness in predictive medicine. Through examples on the use of predictive tests and ethical and legal questions that they raise, concrete cases will be presented by specialists such radio biologists, geneticists, immunologists, jurists and occupational physicians. (N.C.)

  18. Air pollution forecast in cities by an air pollution index highly correlated with meteorological variables

    International Nuclear Information System (INIS)

    Cogliani, E.

    2001-01-01

    There are many different air pollution indexes which represent the global urban air pollution situation. The daily index studied here is also highly correlated with meteorological variables and this index is capable of identifying those variables that significantly affect the air pollution. The index is connected with attention levels of NO 2 , CO and O 3 concentrations. The attention levels are fixed by a law proposed by the Italian Ministries of Health and Environment. The relation of that index with some meteorological variables is analysed by the linear multiple partial correlation statistical method. Florence, Milan and Vicence were selected to show the correlation among the air pollution index and the daily thermic excursion, the previous day's air pollution index and the wind speed. During the January-March period the correlation coefficient reaches 0.85 at Milan. The deterministic methods of forecasting air pollution concentrations show very high evaluation errors and are applied on limited areas around the observation stations, as opposed to the whole urban areas. The global air pollution, instead of the concentrations at specific observation stations, allows the evaluation of the level of the sanitary risk regarding the whole urban population. (Author)

  19. Utility of Childhood Glucose Homeostasis Variables in Predicting Adult Diabetes and Related Cardiometabolic Risk Factors

    OpenAIRE

    Nguyen, Quoc Manh; Srinivasan, Sathanur R.; Xu, Ji-Hua; Chen, Wei; Kieltyka, Lyn; Berenson, Gerald S.

    2009-01-01

    OBJECTIVE This study examines the usefulness of childhood glucose homeostasis variables (glucose, insulin, and insulin resistance index [homeostasis model assessment of insulin resistance {HOMA-IR}]) in predicting pre-diabetes and type 2 diabetes and related cardiometabolic risk factors in adulthood. RESEARCH DESIGN AND METHODS This retrospective cohort study consisted of normoglycemic (n = 1,058), pre-diabetic (n = 37), and type 2 diabetic (n = 25) adults aged 19–39 years who were followed o...

  20. Hydroclimatic variability and predictability: a survey of recent research

    Directory of Open Access Journals (Sweden)

    R. D. Koster

    2017-07-01

    Full Text Available Recent research in large-scale hydroclimatic variability is surveyed, focusing on five topics: (i variability in general, (ii droughts, (iii floods, (iv land–atmosphere coupling, and (v hydroclimatic prediction. Each surveyed topic is supplemented by illustrative examples of recent research, as presented at a 2016 symposium honoring the career of Professor Eric Wood. Taken together, the recent literature and the illustrative examples clearly show that current research into hydroclimatic variability is strong, vibrant, and multifaceted.

  1. Predicting pavement condition index using international roughness index in Washington DC.

    Science.gov (United States)

    2014-09-01

    A number of pavement condition indices are used to conduct pavement management assessments, two of which are the : International Roughness Index (IRI) and Pavement Condition Index (PCI). The IRI is typically measured using specialized : equipment tha...

  2. Association between different measurements of blood pressure variability by ABP monitoring and ankle-brachial index.

    Science.gov (United States)

    Wittke, Estefânia; Fuchs, Sandra C; Fuchs, Flávio D; Moreira, Leila B; Ferlin, Elton; Cichelero, Fábio T; Moreira, Carolina M; Neyeloff, Jeruza; Moreira, Marina B; Gus, Miguel

    2010-11-05

    Blood pressure (BP) variability has been associated with cardiovascular outcomes, but there is no consensus about the more effective method to measure it by ambulatory blood pressure monitoring (ABPM). We evaluated the association between three different methods to estimate BP variability by ABPM and the ankle brachial index (ABI). In a cross-sectional study of patients with hypertension, BP variability was estimated by the time rate index (the first derivative of SBP over time), standard deviation (SD) of 24-hour SBP; and coefficient of variability of 24-hour SBP. ABI was measured with a doppler probe. The sample included 425 patients with a mean age of 57 ± 12 years, being 69.2% women, 26.1% current smokers and 22.1% diabetics. Abnormal ABI (≤ 0.90 or ≥ 1.40) was present in 58 patients. The time rate index was 0.516 ± 0.146 mmHg/min in patients with abnormal ABI versus 0.476 ± 0.124 mmHg/min in patients with normal ABI (P = 0.007). In a logistic regression model the time rate index was associated with ABI, regardless of age (OR = 6.9, 95% CI = 1.1- 42.1; P = 0.04). In a multiple linear regression model, adjusting for age, SBP and diabetes, the time rate index was strongly associated with ABI (P < 0.01). None of the other indexes of BP variability were associated with ABI in univariate and multivariate analyses. Time rate index is a sensible method to measure BP variability by ABPM. Its performance for risk stratification of patients with hypertension should be explored in longitudinal studies.

  3. Prediction of County-Level Corn Yields Using an Energy-Crop Growth Index.

    Science.gov (United States)

    Andresen, Jeffrey A.; Dale, Robert F.; Fletcher, Jerald J.; Preckel, Paul V.

    1989-01-01

    Weather conditions significantly affect corn yields. while weather remains as the major uncontrolled variable in crop production, an understanding of the influence of weather on yields can aid in early and accurate assessment of the impact of weather and climate on crop yields and allow for timely agricultural extension advisories to help reduce farm management costs and improve marketing, decisions. Based on data for four representative countries in Indiana from 1960 to 1984 (excluding 1970 because of the disastrous southern corn leaf blight), a model was developed to estimate corn (Zea mays L.) yields as a function of several composite soil-crop-weather variables and a technology-trend marker, applied nitrogen fertilizer (N). The model was tested by predicting corn yields for 15 other counties. A daily energy-crop growth (ECG) variable in which different weights were used for the three crop-weather variables which make up the daily ECG-solar radiation intercepted by the canopy, a temperature function, and the ratio of actual to potential evapotranspiration-performed better than when the ECG components were weighted equally. The summation of the weighted daily ECG over a relatively short period (36 days spanning silk) was found to provide the best index for predicting county average corn yield. Numerical estimation results indicate that the ratio of actual to potential evapotranspiration (ET/PET) is much more important than the other two ECG factors in estimating county average corn yield in Indiana.

  4. Radiosurgery for brain metastases: a score index for predicting prognosis

    International Nuclear Information System (INIS)

    Weltman, Eduardo; Salvajoli, Joao Victor; Brandt, Reynaldo Andre; Morais Hanriot, Rodrigo de; Prisco, Flavio Eduardo; Cruz, Jose Carlos; Oliveira Borges, Sandra Regina de; Wajsbrot, Dalia Ballas

    2000-01-01

    Purpose: To analyze a prognostic score index for patients with brain metastases submitted to stereotactic radiosurgery (the Score Index for Radiosurgery in Brain Metastases [SIR]). Methods and Materials: Actuarial survival of 65 brain metastases patients treated with radiosurgery between July 1993 and December 1997 was retrospectively analyzed. Prognostic factors included age, Karnofsky performance status (KPS), extracranial disease status, number of brain lesions, largest brain lesion volume, lesions site, and receiving or not whole brain irradiation. The SIR was obtained through summation of the previously noted first five prognostic factors. Kaplan-Meier actuarial survival curves for all prognostic factors, SIR, and recursive partitioning analysis (RPA) (RTOG prognostic score) were calculated. Survival curves of subsets were compared by log-rank test. Application of the Cox model was utilized to identify any correlation between prognostic factors, prognostic scores, and survival. Results: Median overall survival from radiosurgery was 6.8 months. Utilizing univariate analysis, extracranial disease status, KPS, number of brain lesions, largest brain lesion volume, RPA, and SIR were significantly correlated with prognosis. Median survival for the RPA classes 1, 2, and 3 was 20.19 months, 7.75 months, and 3.38 months respectively (p = 0.0131). Median survival for patients, grouped under SIR from 1 to 3, 4 to 7, and 8 to 10, was 2.91 months, 7.00 months, and 31.38 months respectively (p = 0.0001). Using the Cox model, extracranial disease status and KPS demonstrated significant correlation with prognosis (p 0.0001 and 0.0004 respectively). Multivariate analysis also demonstrated significance for SIR and RPA when tested individually (p = 0.0001 and 0.0040 respectively). Applying the Cox Model to both SIR and RPA, only SIR reached independent significance (p = 0.0004). Conclusions: Systemic disease status, KPS, SIR, and RPA are reliable prognostic factors for patients

  5. Heart rate variability analysis as an index of emotion regulation processes: interest of the Analgesia Nociception Index (ANI).

    Science.gov (United States)

    De Jonckheere, J; Rommel, D; Nandrino, J L; Jeanne, M; Logier, R

    2012-01-01

    Autonomic Nervous System (ANS) variations are strongly influence by emotion regulation processes. Indeed, emotional stimuli are at the origin of an activation of the ANS and the way an individual pass from a state of alert in the case of emotional situation to a state of calm is closely coupled with the ANS flexibility. We have previously described and developed an Analgesia Nociception Index (ANI) for real time pain measurement during surgical procedure under general anesthesia. This index, based on heart rate variability analysis, constitutes a measure of parasympathetic tone and can be used in several other environments. In this paper, we hypothesized that such an index could be used as a tool to investigate the processes of emotional regulation of a human subject. To test this hypothesis, we analyzed ANI's response to a negative emotional stimulus. This analysis showed that the index decreases during the emotion induction phase and returns to its baseline after 2 minutes. This result confirms that ANI could be a good indicator of parasympathetic changes in emotional situation.

  6. Relative Contributions of Socio-Cultural Variables to the Prediction ...

    African Journals Online (AJOL)

    Erah

    the Prediction of Maternal Mortality in Edo South. Senatorial ... variables across the two locations (rural and urban) was early marriage/early child bearing (R2 = 0.200;. F = 401.40 ... severe bleeding, infections, obstructed or prolonged .... Analytical System (SAS) mode. Descriptive .... incontinence of urine and faeces due to.

  7. Predicting travel time variability for cost-benefit analysis

    NARCIS (Netherlands)

    Peer, S.; Koopmans, C.; Verhoef, E.T.

    2010-01-01

    Unreliable travel times cause substantial costs to travelers. Nevertheless, they are not taken into account in many cost-benefit-analyses (CBA), or only in very rough ways. This paper aims at providing simple rules on how variability can be predicted, based on travel time data from Dutch highways.

  8. Applying reaction condition index to predict sandstone type uranium deposit

    International Nuclear Information System (INIS)

    Chen Gongxin; Liu Jinhui; Cheng Hai

    2002-01-01

    On the basic of the explanation of reaction condition index, the deduction of reaction condition index calculation principle, the hydrogeological setting in Gongpoquan basin in Baishan, Gansu province and the study of reaction condition index of its water source point, the north Luotuoquan area in Gongpoquan basin seems to be a favourable place for sandstone type uranium deposit, and the prospect area for sandstone type uranium deposit is delimitated

  9. Idiopathic Pulmonary Fibrosis: Gender-Age-Physiology Index Stage for Predicting Future Lung Function Decline.

    Science.gov (United States)

    Salisbury, Margaret L; Xia, Meng; Zhou, Yueren; Murray, Susan; Tayob, Nabihah; Brown, Kevin K; Wells, Athol U; Schmidt, Shelley L; Martinez, Fernando J; Flaherty, Kevin R

    2016-02-01

    Idiopathic pulmonary fibrosis is a progressive lung disease with variable course. The Gender-Age-Physiology (GAP) Index and staging system uses clinical variables to stage mortality risk. It is unknown whether clinical staging predicts future decline in pulmonary function. We assessed whether the GAP stage predicts future pulmonary function decline and whether interval pulmonary function change predicts mortality after accounting for stage. Patients with idiopathic pulmonary fibrosis (N = 657) were identified retrospectively at three tertiary referral centers, and baseline GAP stages were assessed. Mixed models were used to describe average trajectories of FVC and diffusing capacity of the lung for carbon monoxide (Dlco). Multivariable Cox proportional hazards models were used to assess whether declines in pulmonary function ≥ 10% in 6 months predict mortality after accounting for GAP stage. Over a 2-year period, GAP stage was not associated with differences in yearly lung function decline. After accounting for stage, a 10% decrease in FVC or Dlco over 6 months independently predicted death or transplantation (FVC hazard ratio, 1.37; Dlco hazard ratio, 1.30; both, P ≤ .03). Patients with GAP stage 2 with declining pulmonary function experienced a survival profile similar to patients with GAP stage 3, with 1-year event-free survival of 59.3% (95% CI, 49.4-67.8) vs 56.9% (95% CI, 42.2-69.1). Baseline GAP stage predicted death or lung transplantation but not the rate of future pulmonary function decline. After accounting for GAP stage, a decline of ≥ 10% over 6 months independently predicted death or lung transplantation. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

  10. VizieR Online Data Catalog: AAVSO International Variable Star Index VSX (Watson+, 2006-2014)

    Science.gov (United States)

    Watson, C.; Henden, A. A.; Price, A.

    2018-05-01

    This file contains Galactic stars known or suspected to be variable. It lists all stars that have an entry in the AAVSO International Variable Star Index (VSX; http://www.aavso.org/vsx). The database consisted initially of the General Catalogue of Variable Stars (GCVS) and the New Catalogue of Suspected Variables (NSV) and was then supplemented with a large number of variable star catalogues, as well as individual variable star discoveries or variables found in the literature. Effort has also been invested to update the entries with the latest information regarding position, type and period and to remove duplicates. The VSX database is being continually updated and maintained. For historical reasons some objects outside of the Galaxy have been included. (3 data files).

  11. Predicting sun protection behaviors using protection motivation variables.

    Science.gov (United States)

    Ch'ng, Joanne W M; Glendon, A Ian

    2014-04-01

    Protection motivation theory components were used to predict sun protection behaviors (SPBs) using four outcome measures: typical reported behaviors, previous reported behaviors, current sunscreen use as determined by interview, and current observed behaviors (clothing worn) to control for common method bias. Sampled from two SE Queensland public beaches during summer, 199 participants aged 18-29 years completed a questionnaire measuring perceived severity, perceived vulnerability, response efficacy, response costs, and protection motivation (PM). Personal perceived risk (similar to threat appraisal) and response likelihood (similar to coping appraisal) were derived from their respective PM components. Protection motivation predicted all four SPB criterion variables. Personal perceived risk and response likelihood predicted protection motivation. Protection motivation completely mediated the effect of response likelihood on all four criterion variables. Alternative models are considered. Strengths and limitations of the study are outlined and suggestions made for future research.

  12. Climate Prediction Center - Outlooks: Current UV Index Forecast Map

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Service NOAA Center for Weather and Climate Prediction Climate Prediction Center 5830 University Research Court College Park, Maryland 20740 Page Author: Climate Prediction Center Internet Team Disclaimer

  13. Association between different measurements of blood pressure variability by ABP monitoring and ankle-brachial index

    Directory of Open Access Journals (Sweden)

    Moreira Leila B

    2010-11-01

    Full Text Available Abstract Background Blood pressure (BP variability has been associated with cardiovascular outcomes, but there is no consensus about the more effective method to measure it by ambulatory blood pressure monitoring (ABPM. We evaluated the association between three different methods to estimate BP variability by ABPM and the ankle brachial index (ABI. Methods and Results In a cross-sectional study of patients with hypertension, BP variability was estimated by the time rate index (the first derivative of SBP over time, standard deviation (SD of 24-hour SBP; and coefficient of variability of 24-hour SBP. ABI was measured with a doppler probe. The sample included 425 patients with a mean age of 57 ± 12 years, being 69.2% women, 26.1% current smokers and 22.1% diabetics. Abnormal ABI (≤ 0.90 or ≥ 1.40 was present in 58 patients. The time rate index was 0.516 ± 0.146 mmHg/min in patients with abnormal ABI versus 0.476 ± 0.124 mmHg/min in patients with normal ABI (P = 0.007. In a logistic regression model the time rate index was associated with ABI, regardless of age (OR = 6.9, 95% CI = 1.1- 42.1; P = 0.04. In a multiple linear regression model, adjusting for age, SBP and diabetes, the time rate index was strongly associated with ABI (P Conclusion Time rate index is a sensible method to measure BP variability by ABPM. Its performance for risk stratification of patients with hypertension should be explored in longitudinal studies.

  14. Seasonal predictions of Fire Weather Index: Paving the way for their operational applicability in Mediterranean Europe

    Directory of Open Access Journals (Sweden)

    Joaquín Bedia

    2018-01-01

    Full Text Available Managers of wildfire-prone landscapes in the Euro-Mediterranean region would greatly benefit from fire weather predictions a few months in advance, and particularly from the reliable prediction of extreme fire seasons. However, in some cases model biases prevent from a direct application of these predictions in an operational context. Fire risk management requires precise knowledge of the likely consequences of climate on fire risk, and the interest for decision-makers is focused on multi-variable fire danger indices, calculated through the combination of different model output variables. In this paper we consider whether the skill in dynamical seasonal predictions of one of the most widely applied of such indices (the Canadian Fire Weather Index, FWI is sufficient to inform management decisions, and we examine various methodological aspects regarding the calibration of model outputs prior to its verification and operational applicability. We find that there is significant skill in predicting above average summer FWI in parts of SE Europe at 1 month lead time, but poor skill elsewhere. These results are largely linked to the predictability of relative humidity. Moreover, practical recommendations are given for the use of empirical quantile mapping in probabilistic seasonal FWI forecasts. Furthermore, we show how researchers, fire managers and other stakeholders can take advantage of a new open-source climate service in order to undertake all the necessary steps for data download, post-processing, analysis and verification in a straightforward and fully reproducible manner. Keywords: Climate impact indicators, Quantile mapping, Bias correction, System 4, Fire danger, Seasonal forecasting

  15. Climate Prediction Center(CPC)Daily GOES Precipitation Index (GPI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GOES Precipitation Index (GPI) is a precipitation estimation algorithm. The GPI technique estimates tropical rainfall using cloud-top temperature as the sole...

  16. Climate Prediction Center (CPC)Oceanic Nino Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oceanic Nino Index (ONI) is one of the primary indices used to monitor the El Nino-Southern Oscillation (ENSO). The ONI is calculated by averaging sea surface...

  17. Cortical Response Variability as a Developmental Index of Selective Auditory Attention

    Science.gov (United States)

    Strait, Dana L.; Slater, Jessica; Abecassis, Victor; Kraus, Nina

    2014-01-01

    Attention induces synchronicity in neuronal firing for the encoding of a given stimulus at the exclusion of others. Recently, we reported decreased variability in scalp-recorded cortical evoked potentials to attended compared with ignored speech in adults. Here we aimed to determine the developmental time course for this neural index of auditory…

  18. Towards cheminformatics-based estimation of drug therapeutic index: Predicting the protective index of anticonvulsants using a new quantitative structure-index relationship approach.

    Science.gov (United States)

    Chen, Shangying; Zhang, Peng; Liu, Xin; Qin, Chu; Tao, Lin; Zhang, Cheng; Yang, Sheng Yong; Chen, Yu Zong; Chui, Wai Keung

    2016-06-01

    The overall efficacy and safety profile of a new drug is partially evaluated by the therapeutic index in clinical studies and by the protective index (PI) in preclinical studies. In-silico predictive methods may facilitate the assessment of these indicators. Although QSAR and QSTR models can be used for predicting PI, their predictive capability has not been evaluated. To test this capability, we developed QSAR and QSTR models for predicting the activity and toxicity of anticonvulsants at accuracy levels above the literature-reported threshold (LT) of good QSAR models as tested by both the internal 5-fold cross validation and external validation method. These models showed significantly compromised PI predictive capability due to the cumulative errors of the QSAR and QSTR models. Therefore, in this investigation a new quantitative structure-index relationship (QSIR) model was devised and it showed improved PI predictive capability that superseded the LT of good QSAR models. The QSAR, QSTR and QSIR models were developed using support vector regression (SVR) method with the parameters optimized by using the greedy search method. The molecular descriptors relevant to the prediction of anticonvulsant activities, toxicities and PIs were analyzed by a recursive feature elimination method. The selected molecular descriptors are primarily associated with the drug-like, pharmacological and toxicological features and those used in the published anticonvulsant QSAR and QSTR models. This study suggested that QSIR is useful for estimating the therapeutic index of drug candidates. Copyright © 2016. Published by Elsevier Inc.

  19. Fatty Liver Index and Lipid Accumulation Product Can Predict Metabolic Syndrome in Subjects without Fatty Liver Disease

    Directory of Open Access Journals (Sweden)

    Yuan-Lung Cheng

    2017-01-01

    Full Text Available Background. Fatty liver index (FLI and lipid accumulation product (LAP are indexes originally designed to assess the risk of fatty liver and cardiovascular disease, respectively. Both indexes have been proven to be reliable markers of subsequent metabolic syndrome; however, their ability to predict metabolic syndrome in subjects without fatty liver disease has not been clarified. Methods. We enrolled consecutive subjects who received health check-up services at Taipei Veterans General Hospital from 2002 to 2009. Fatty liver disease was diagnosed by abdominal ultrasonography. The ability of the FLI and LAP to predict metabolic syndrome was assessed by analyzing the area under the receiver operating characteristic (AUROC curve. Results. Male sex was strongly associated with metabolic syndrome, and the LAP and FLI were better than other variables to predict metabolic syndrome among the 29,797 subjects. Both indexes were also better than other variables to detect metabolic syndrome in subjects without fatty liver disease (AUROC: 0.871 and 0.879, resp., and the predictive power was greater among women. Conclusion. Metabolic syndrome increases the cardiovascular disease risk. The FLI and LAP could be used to recognize the syndrome in both subjects with and without fatty liver disease who require lifestyle modifications and counseling.

  20. Making oneself predictable: Reduced temporal variability facilitates joint action coordination

    DEFF Research Database (Denmark)

    Vesper, Cordula; van der Wel, Robrecht; Knoblich, Günther

    2011-01-01

    Performing joint actions often requires precise temporal coordination of individual actions. The present study investigated how people coordinate their actions at discrete points in time when continuous or rhythmic information about others’ actions is not available. In particular, we tested...... the hypothesis that making oneself predictable is used as a coordination strategy. Pairs of participants were instructed to coordinate key presses in a two-choice reaction time task, either responding in synchrony (Experiments 1 and 2) or in close temporal succession (Experiment 3). Across all experiments, we...... found that coactors reduced the variability of their actions in the joint context compared with the same task performed individually. Correlation analyses indicated that the less variable the actions were, the better was interpersonal coordination. The relation between reduced variability and improved...

  1. Variability in Predictions from Online Tools: A Demonstration Using Internet-Based Melanoma Predictors.

    Science.gov (United States)

    Zabor, Emily C; Coit, Daniel; Gershenwald, Jeffrey E; McMasters, Kelly M; Michaelson, James S; Stromberg, Arnold J; Panageas, Katherine S

    2018-02-22

    Prognostic models are increasingly being made available online, where they can be publicly accessed by both patients and clinicians. These online tools are an important resource for patients to better understand their prognosis and for clinicians to make informed decisions about treatment and follow-up. The goal of this analysis was to highlight the possible variability in multiple online prognostic tools in a single disease. To demonstrate the variability in survival predictions across online prognostic tools, we applied a single validation dataset to three online melanoma prognostic tools. Data on melanoma patients treated at Memorial Sloan Kettering Cancer Center between 2000 and 2014 were retrospectively collected. Calibration was assessed using calibration plots and discrimination was assessed using the C-index. In this demonstration project, we found important differences across the three models that led to variability in individual patients' predicted survival across the tools, especially in the lower range of predictions. In a validation test using a single-institution data set, calibration and discrimination varied across the three models. This study underscores the potential variability both within and across online tools, and highlights the importance of using methodological rigor when developing a prognostic model that will be made publicly available online. The results also reinforce that careful development and thoughtful interpretation, including understanding a given tool's limitations, are required in order for online prognostic tools that provide survival predictions to be a useful resource for both patients and clinicians.

  2. Estimating search engine index size variability: a 9-year longitudinal study.

    Science.gov (United States)

    van den Bosch, Antal; Bogers, Toine; de Kunder, Maurice

    One of the determining factors of the quality of Web search engines is the size of their index. In addition to its influence on search result quality, the size of the indexed Web can also tell us something about which parts of the WWW are directly accessible to the everyday user. We propose a novel method of estimating the size of a Web search engine's index by extrapolating from document frequencies of words observed in a large static corpus of Web pages. In addition, we provide a unique longitudinal perspective on the size of Google and Bing's indices over a nine-year period, from March 2006 until January 2015. We find that index size estimates of these two search engines tend to vary dramatically over time, with Google generally possessing a larger index than Bing. This result raises doubts about the reliability of previous one-off estimates of the size of the indexed Web. We find that much, if not all of this variability can be explained by changes in the indexing and ranking infrastructure of Google and Bing. This casts further doubt on whether Web search engines can be used reliably for cross-sectional webometric studies.

  3. Prediction of immediate postoperative pain using the analgesia/nociception index: a prospective observational study.

    Science.gov (United States)

    Boselli, E; Bouvet, L; Bégou, G; Dabouz, R; Davidson, J; Deloste, J-Y; Rahali, N; Zadam, A; Allaouchiche, B

    2014-04-01

    The analgesia/nociception index (ANI) is derived from heart rate variability, ranging from 0 (maximal nociception) to 100 (maximal analgesia), to reflect the analgesia/nociception balance during general anaesthesia. This should be correlated with immediate postoperative pain in the post-anaesthesia care unit (PACU). The aim of this study was to evaluate the performance of ANI measured at arousal from general anaesthesia to predict immediate postoperative pain on arrival in PACU. Two hundred patients undergoing ear, nose, and throat or lower limb orthopaedic surgery with general anaesthesia using an inhalational agent and remifentanil were included in this prospective observational study. The ANI was measured immediately before tracheal extubation and pain intensity was assessed within 10 min of arrival in PACU using a 0-10 numerical rating scale (NRS). The relationship between ANI and NRS was assessed using linear regression. A receiver-operating characteristic (ROC) curve was used to evaluate the performance of ANI to predict NRS>3. A negative linear relationship was observed between ANI immediately before extubation and NRS on arrival in PACU. Using a threshold of 3 were both 86% with 92% negative predictive value, corresponding to an area under the ROC curve of 0.89. The measurement of ANI immediately before extubation after inhalation-remifentanil anaesthesia was significantly associated with pain intensity on arrival in PACU. The performance of ANI for the prediction of immediate postoperative pain is good and may assist physicians in optimizing acute pain management. ClinicalTrials.gov NCT01796249.

  4. Predictive coding of dynamical variables in balanced spiking networks.

    Science.gov (United States)

    Boerlin, Martin; Machens, Christian K; Denève, Sophie

    2013-01-01

    Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.

  5. Predicting volatility and correlations with Financial Conditions Indexes

    NARCIS (Netherlands)

    Opschoor, A.; van Dijk, D.; van der Wel, M.

    2014-01-01

    We model the impact of financial conditions on asset market volatilities and correlations. We extend the Spline-GARCH model for volatility and DCC model for correlation to allow for inclusion of indexes that measure financial conditions. In our empirical application we consider daily stock returns

  6. Predicting Volatility and Correlations with Financial Conditions Indexes

    NARCIS (Netherlands)

    A. Opschoor (Anne); D.J.C. van Dijk (Dick); M. van der Wel (Michel)

    2014-01-01

    textabstractWe model the impact of financial conditions on asset market volatilities and correlations. We extend the Spline-GARCH model for volatility and DCC model for correlation to allow for inclusion of indexes that measure financial conditions. In our empirical application we consider daily

  7. Genetically Predicted Body Mass Index and Breast Cancer Risk

    DEFF Research Database (Denmark)

    Guo, Yan; Warren Andersen, Shaneda; Shu, Xiao-Ou

    2016-01-01

    BACKGROUND: Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or enviro...

  8. Uncertainty in wave energy resource assessment. Part 2: Variability and predictability

    International Nuclear Information System (INIS)

    Mackay, Edward B.L.; Bahaj, AbuBakr S.; Challenor, Peter G.

    2010-01-01

    The uncertainty in estimates of the energy yield from a wave energy converter (WEC) is considered. The study is presented in two articles. The first article considered the accuracy of the historic data and the second article, presented here, considers the uncertainty which arises from variability in the wave climate. Mean wave conditions exhibit high levels of interannual variability. Moreover, many previous studies have demonstrated longer-term decadal changes in wave climate. The effect of interannual and climatic changes in wave climate on the predictability of long-term mean WEC power is examined for an area off the north coast of Scotland. In this location anomalies in mean WEC power are strongly correlated with the North Atlantic Oscillation (NAO) index. This link enables the results of many previous studies on the variability of the NAO and its sensitivity to climate change to be applied to WEC power levels. It is shown that the variability in 5, 10 and 20 year mean power levels is greater than if annual power anomalies were uncorrelated noise. It is also shown that the change in wave climate from anthropogenic climate change over the life time of a wave farm is likely to be small in comparison to the natural level of variability. Finally, it is shown that despite the uncertainty related to variability in the wave climate, improvements in the accuracy of historic data will improve the accuracy of predictions of future WEC yield. (author)

  9. Impact of vegetation variability on potential predictability and skill of EC-Earth simulations

    Energy Technology Data Exchange (ETDEWEB)

    Weiss, Martina; Hurk, Bart van den; Haarsma, Reindert; Hazeleger, Wilco [Royal Netherlands Meteorological Institute (KNMI), De Bilt (Netherlands)

    2012-12-15

    Climate models often use a simplified and static representation of vegetation characteristics to determine fluxes of energy, momentum and water vapour between surface and lower atmosphere. In order to analyse the impact of short term variability in vegetation phenology, we use remotely-sensed leaf area index and albedo products to examine the role of vegetation in the coupled land-atmosphere system. Perfect model experiments are carried out to determine the impact of realistic temporal variability of vegetation on potential predictability of evaporation and temperature, as well as model skill of EC-Earth simulations. The length of the simulation period is hereby limited by the availability of satellite products to 2000-2010. While a realistic representation of vegetation positively influences the simulation of evaporation and its potential predictability, a positive impact on 2 m temperature is of smaller magnitude, regionally confined and more pronounced in climatically extreme years. (orig.)

  10. Interobserver variability of sonography for prediction of placenta accreta.

    Science.gov (United States)

    Bowman, Zachary S; Eller, Alexandra G; Kennedy, Anne M; Richards, Douglas S; Winter, Thomas C; Woodward, Paula J; Silver, Robert M

    2014-12-01

    The sensitivity of sonography to predict accreta has been reported as higher than 90%. However, most studies are from single expert investigators. Our objective was to analyze interobserver variability of sonography for prediction of placenta accreta. Patients with previa with and without accreta were ascertained, and images with placental views were collected, deidentified, and placed in random sequence. Three radiologists and 3 maternal-fetal medicine specialists interpreted each study for the presence of accreta and specific findings reported to be associated with its diagnosis. Investigator-specific sensitivity, specificity, and accuracy were calculated. κ statistics were used to assess variability between individuals and types of investigators. A total of 229 sonographic studies from 55 patients with accreta and 56 control patients were examined. Accuracy ranged from 55.9% to 76.4%. Of imaging studies yielding diagnoses, sensitivity ranged from 53.4% to 74.4%, and specificity ranged from 70.8% to 94.8%. Overall interobserver agreement was moderate (mean κ ± SD = 0.47 ± 0.12). κ values between pairs of investigators ranged from 0.32 (fair agreement) to 0.73 (substantial agreement). Average individual agreement ranged from fair (κ = 0.35) to moderate (κ = 0.53). Blinded from clinical data, sonography has significant interobserver variability for the diagnosis of placenta accreta. © 2013 by the American Institute of Ultrasound in Medicine.

  11. Refractive Index Imaging of Cells with Variable-Angle Near-Total Internal Reflection (TIR) Microscopy.

    Science.gov (United States)

    Bohannon, Kevin P; Holz, Ronald W; Axelrod, Daniel

    2017-10-01

    The refractive index in the interior of single cells affects the evanescent field depth in quantitative studies using total internal reflection (TIR) fluorescence, but often that index is not well known. We here present method to measure and spatially map the absolute index of refraction in a microscopic sample, by imaging a collimated light beam reflected from the substrate/buffer/cell interference at variable angles of incidence. Above the TIR critical angle (which is a strong function of refractive index), the reflection is 100%, but in the immediate sub-critical angle zone, the reflection intensity is a very strong ascending function of incidence angle. By analyzing the angular position of that edge at each location in the field of view, the local refractive index can be estimated. In addition, by analyzing the steepness of the edge, the distance-to-substrate can be determined. We apply the technique to liquid calibration samples, silica beads, cultured Chinese hamster ovary cells, and primary culture chromaffin cells. The optical technique suffers from decremented lateral resolution, scattering, and interference artifacts. However, it still provides reasonable results for both refractive index (~1.38) and for distance-to-substrate (~150 nm) for the cells, as well as a lateral resolution to about 1 µm.

  12. Prediction of Shanghai Index based on Additive Legendre Neural Network

    Directory of Open Access Journals (Sweden)

    Yang Bin

    2017-01-01

    Full Text Available In this paper, a novel Legendre neural network model is proposed, namely additive Legendre neural network (ALNN. A new hybrid evolutionary method besed on binary particle swarm optimization (BPSO algorithm and firefly algorithm is proposed to optimize the structure and parameters of ALNN model. Shanghai stock exchange composite index is used to evaluate the performance of ALNN. Results reveal that ALNN performs better than LNN model.

  13. Estimating the reliability of glycemic index values and potential sources of methodological and biological variability.

    Science.gov (United States)

    Matthan, Nirupa R; Ausman, Lynne M; Meng, Huicui; Tighiouart, Hocine; Lichtenstein, Alice H

    2016-10-01

    The utility of glycemic index (GI) values for chronic disease risk management remains controversial. Although absolute GI value determinations for individual foods have been shown to vary significantly in individuals with diabetes, there is a dearth of data on the reliability of GI value determinations and potential sources of variability among healthy adults. We examined the intra- and inter-individual variability in glycemic response to a single food challenge and methodologic and biological factors that potentially mediate this response. The GI value for white bread was determined by using standardized methodology in 63 volunteers free from chronic disease and recruited to differ by sex, age (18-85 y), and body mass index [BMI (in kg/m 2 ): 20-35]. Volunteers randomly underwent 3 sets of food challenges involving glucose (reference) and white bread (test food), both providing 50 g available carbohydrates. Serum glucose and insulin were monitored for 5 h postingestion, and GI values were calculated by using different area under the curve (AUC) methods. Biochemical variables were measured by using standard assays and body composition by dual-energy X-ray absorptiometry. The mean ± SD GI value for white bread was 62 ± 15 when calculated by using the recommended method. Mean intra- and interindividual CVs were 20% and 25%, respectively. Increasing sample size, replication of reference and test foods, and length of blood sampling, as well as AUC calculation method, did not improve the CVs. Among the biological factors assessed, insulin index and glycated hemoglobin values explained 15% and 16% of the variability in mean GI value for white bread, respectively. These data indicate that there is substantial variability in individual responses to GI value determinations, demonstrating that it is unlikely to be a good approach to guiding food choices. Additionally, even in healthy individuals, glycemic status significantly contributes to the variability in GI value

  14. Options for refractive index and viscosity matching to study variable density flows

    Science.gov (United States)

    Clément, Simon A.; Guillemain, Anaïs; McCleney, Amy B.; Bardet, Philippe M.

    2018-02-01

    Variable density flows are often studied by mixing two miscible aqueous solutions of different densities. To perform optical diagnostics in such environments, the refractive index of the fluids must be matched, which can be achieved by carefully choosing the two solutes and the concentration of the solutions. To separate the effects of buoyancy forces and viscosity variations, it is desirable to match the viscosity of the two solutions in addition to their refractive index. In this manuscript, several pairs of index matched fluids are compared in terms of viscosity matching, monetary cost, and practical use. Two fluid pairs are studied in detail, with two aqueous solutions (binary solutions of water and a salt or alcohol) mixed into a ternary solution. In each case: an aqueous solution of isopropanol mixed with an aqueous solution of sodium chloride (NaCl) and an aqueous solution of glycerol mixed with an aqueous solution of sodium sulfate (Na_2SO_4). The first fluid pair allows reaching high-density differences at low cost, but brings a large difference in dynamic viscosity. The second allows matching dynamic viscosity and refractive index simultaneously, at reasonable cost. For each of these four solutes, the density, kinematic viscosity, and refractive index are measured versus concentration and temperature, as well as wavelength for the refractive index. To investigate non-linear effects when two index-matched, binary solutions are mixed, the ternary solutions formed are also analyzed. Results show that density and refractive index follow a linear variation with concentration. However, the viscosity of the isopropanol and NaCl pair deviates from the linear law and has to be considered. Empirical correlations and their coefficients are given to create index-matched fluids at a chosen temperature and wavelength. Finally, the effectiveness of the refractive index matching is illustrated with particle image velocimetry measurements performed for a buoyant jet in a

  15. Protein construct storage: Bayesian variable selection and prediction with mixtures.

    Science.gov (United States)

    Clyde, M A; Parmigiani, G

    1998-07-01

    Determining optimal conditions for protein storage while maintaining a high level of protein activity is an important question in pharmaceutical research. A designed experiment based on a space-filling design was conducted to understand the effects of factors affecting protein storage and to establish optimal storage conditions. Different model-selection strategies to identify important factors may lead to very different answers about optimal conditions. Uncertainty about which factors are important, or model uncertainty, can be a critical issue in decision-making. We use Bayesian variable selection methods for linear models to identify important variables in the protein storage data, while accounting for model uncertainty. We also use the Bayesian framework to build predictions based on a large family of models, rather than an individual model, and to evaluate the probability that certain candidate storage conditions are optimal.

  16. Variability, Predictability, and Race Factors Affecting Performance in Elite Biathlon.

    Science.gov (United States)

    Skattebo, Øyvind; Losnegard, Thomas

    2018-03-01

    To investigate variability, predictability, and smallest worthwhile performance enhancement in elite biathlon sprint events. In addition, the effects of race factors on performance were assessed. Data from 2005 to 2015 including >10,000 and >1000 observations for each sex for all athletes and annual top-10 athletes, respectively, were included. Generalized linear mixed models were constructed based on total race time, skiing time, shooting time, and proportions of targets hit. Within-athlete race-to-race variability was expressed as coefficient of variation of performance times and standard deviation (SD) in proportion units (%) of targets hit. The models were adjusted for random and fixed effects of subject identity, season, event identity, and race factors. The within-athlete variability was independent of sex and performance standard of athletes: 2.5-3.2% for total race time, 1.5-1.8% for skiing time, and 11-15% for shooting times. The SD of the proportion of hits was ∼10% in both shootings combined (meaning ±1 hit in 10 shots). The predictability in total race time was very high to extremely high for all athletes (ICC .78-.84) but trivial for top-10 athletes (ICC .05). Race times during World Championships and Olympics were ∼2-3% faster than in World Cups. Moreover, race time increased by ∼2% per 1000 m of altitude, by ∼5% per 1% of gradient, by 1-2% per 1 m/s of wind speed, and by ∼2-4% on soft vs hard tracks. Researchers and practitioners should focus on strategies that improve biathletes' performance by at least 0.8-0.9%, corresponding to the smallest worthwhile enhancement (0.3 × within-athlete variability).

  17. THE EFFECT OF MACROECONOMIC VARIABLES ON BANKING STOCK PRICE INDEX IN INDONESIA STOCK EXCHANGE

    Directory of Open Access Journals (Sweden)

    Laduna R.

    2018-01-01

    Full Text Available Stock price index can be regarded as a barometer in the measuremet of a nation’s economic condition, besides it can also be used in conducting statistical analysis on the current market. Stock is the proof of one’s share in a company in the form of securities issued by the listed go-public companies. This study was conducted to measure the effect of macroeconomic variables such as inflation, interest rate, and exchange rate on banking stock price index in Indonesia stock exchange or Bursa Efek Indonesia (BEI. The results of study show that inflation and exchange rate posively influence the stock price index. The positive effect of the exchange rate shows that issuers who were positively affected by Rupiah (IDR depreciation appear to be the most dominant group. Meanwhile, the interest rate or Suku Bunga (SBI has a negative effect. Lower interest rate stimulates higher investments and better economic activities which increase the stock price.

  18. Prediction of monthly average global solar radiation based on statistical distribution of clearness index

    International Nuclear Information System (INIS)

    Ayodele, T.R.; Ogunjuyigbe, A.S.O.

    2015-01-01

    In this paper, probability distribution of clearness index is proposed for the prediction of global solar radiation. First, the clearness index is obtained from the past data of global solar radiation, then, the parameters of the appropriate distribution that best fit the clearness index are determined. The global solar radiation is thereafter predicted from the clearness index using inverse transformation of the cumulative distribution function. To validate the proposed method, eight years global solar radiation data (2000–2007) of Ibadan, Nigeria are used to determine the parameters of appropriate probability distribution for clearness index. The calculated parameters are then used to predict the future monthly average global solar radiation for the following year (2008). The predicted values are compared with the measured values using four statistical tests: the Root Mean Square Error (RMSE), MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error) and the coefficient of determination (R"2). The proposed method is also compared to the existing regression models. The results show that logistic distribution provides the best fit for clearness index of Ibadan and the proposed method is effective in predicting the monthly average global solar radiation with overall RMSE of 0.383 MJ/m"2/day, MAE of 0.295 MJ/m"2/day, MAPE of 2% and R"2 of 0.967. - Highlights: • Distribution of clearnes index is proposed for prediction of global solar radiation. • The clearness index is obtained from the past data of global solar radiation. • The parameters of distribution that best fit the clearness index are determined. • Solar radiation is predicted from the clearness index using inverse transformation. • The method is effective in predicting the monthly average global solar radiation.

  19. Predicting lodgepole pine site index from climatic parameters in Alberta.

    Science.gov (United States)

    Robert A. Monserud; Shongming Huang; Yuqing. Yang

    2006-01-01

    We sought to evaluate the impact of climatic variables on site productivity of lodgepole pine (Pinus contorta var. latifolia Engelm.) for the province of Alberta. Climatic data were obtained from the Alberta Climate Model, which is based on 30-year normals from the provincial weather station network. Mapping methods were based...

  20. Variable importance and prediction methods for longitudinal problems with missing variables.

    Directory of Open Access Journals (Sweden)

    Iván Díaz

    Full Text Available We present prediction and variable importance (VIM methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patients, a field in which current medical practice involves rules of thumb and scoring methods that only use a few variables and ignore the dynamic and high-dimensional nature of trauma recovery. Well-principled prediction and VIM methods can provide a tool to make care decisions informed by the high-dimensional patient's physiological and clinical history. Our VIM parameters are analogous to slope coefficients in adjusted regressions, but are not dependent on a specific statistical model, nor require a certain functional form of the prediction regression to be estimated. In addition, they can be causally interpreted under causal and statistical assumptions as the expected outcome under time-specific clinical interventions, related to changes in the mean of the outcome if each individual experiences a specified change in the variable (keeping other variables in the model fixed. Better yet, the targeted MLE used is doubly robust and locally efficient. Because the proposed VIM does not constrain the prediction model fit, we use a very flexible ensemble learner (the SuperLearner, which returns a linear combination of a list of user-given algorithms. Not only is such a prediction algorithm intuitive appealing, it has theoretical justification as being asymptotically equivalent to the oracle selector. The results of the analysis show effects whose size and significance would have been not been found using a parametric approach (such as stepwise regression or LASSO. In addition, the procedure is even more compelling as the predictor on which it is based showed significant improvements in cross-validated fit, for instance area under the curve (AUC for a receiver-operator curve (ROC. Thus, given that 1 our VIM

  1. The c-index is not proper for the evaluation of $t$-year predicted risks.

    Science.gov (United States)

    Blanche, Paul; Kattan, Michael W; Gerds, Thomas A

    2018-02-16

    We show that the widely used concordance index for time to event outcome is not proper when interest is in predicting a $t$-year risk of an event, for example 10-year mortality. In the situation with a fixed prediction horizon, the concordance index can be higher for a misspecified model than for a correctly specified model. Impropriety happens because the concordance index assesses the order of the event times and not the order of the event status at the prediction horizon. The time-dependent area under the receiver operating characteristic curve does not have this problem and is proper in this context.

  2. Pulmonary function vascular index predicts prognosis in idiopathic interstitial pneumonia

    NARCIS (Netherlands)

    Corte, Tamera J.; Wort, Stephen J.; MacDonald, Peter S.; Edey, Anthony; Hansell, David M.; Renzoni, Elisabetta; Maher, Toby M.; Nicholson, Andrew G.; Bandula, Steven; Bresser, Paul; Wells, Athol U.

    2012-01-01

    Background and objective: Pulmonary hypertension (PH) is associated with increased mortality in fibrotic idiopathic interstitial pneumonia (IIP). We hypothesize that baseline KCO (diffusing capacity of carbon monoxide/alveolar volume) and 6-month decline in KCO reflect PH, thus predicting mortality

  3. Global variability in angina pectoris and its association with body mass index and poverty.

    Science.gov (United States)

    Liu, Longjian; Ma, Jixiang; Yin, Xiaoyan; Kelepouris, Ellie; Eisen, Howard J

    2011-03-01

    In the absence of a previous global comparison, we examined the variability in the prevalence of angina across 52 countries and its association with body weight and the poverty index using data from the World Health Organization-World Health Survey. The participants with angina were defined as those who had positive results using a Rose angina questionnaire and/or self-report of a physician diagnosis of angina. The body mass index (BMI) was determined as the weight in kilograms divided by the square of the height in meters. The poverty index (a standard score of socioeconomic status for a given country) was extracted from the United Nations' statistics. The associations of angina with the BMI and poverty index were analyzed cross-sectionally using univariate and multivariate analyses. The results showed that the total participants (n = 210,787) had an average age of 40.64 years. The prevalence of angina ranged from 2.44% in Tunisia to 23.89% in Chad. Those participants with a BMI of poverty status was considered. A tendency was seen for underweight status and a poverty index >14.65% to be associated with the risk of having angina, although these associations were not statistically significant in the multilevel models. In conclusion, significant variations were found in the anginal rates across 52 countries worldwide. An increased BMI was significantly associated with the odds of having angina. Published by Elsevier Inc.

  4. Can biomechanical variables predict improvement in crouch gait?

    Science.gov (United States)

    Hicks, Jennifer L.; Delp, Scott L.; Schwartz, Michael H.

    2011-01-01

    Many patients respond positively to treatments for crouch gait, yet surgical outcomes are inconsistent and unpredictable. In this study, we developed a multivariable regression model to determine if biomechanical variables and other subject characteristics measured during a physical exam and gait analysis can predict which subjects with crouch gait will demonstrate improved knee kinematics on a follow-up gait analysis. We formulated the model and tested its performance by retrospectively analyzing 353 limbs of subjects who walked with crouch gait. The regression model was able to predict which subjects would demonstrate ‘improved’ and ‘unimproved’ knee kinematics with over 70% accuracy, and was able to explain approximately 49% of the variance in subjects’ change in knee flexion between gait analyses. We found that improvement in stance phase knee flexion was positively associated with three variables that were drawn from knowledge about the biomechanical contributors to crouch gait: i) adequate hamstrings lengths and velocities, possibly achieved via hamstrings lengthening surgery, ii) normal tibial torsion, possibly achieved via tibial derotation osteotomy, and iii) sufficient muscle strength. PMID:21616666

  5. Analysis and Prediction of Micromilling Stability with Variable Tool Geometry

    Directory of Open Access Journals (Sweden)

    Ziyang Cao

    2014-11-01

    Full Text Available Micromilling can fabricate miniaturized components using micro-end mill at high rotational speeds. The analysis of machining stability in micromilling plays an important role in characterizing the cutting process, estimating the tool life, and optimizing the process. A numerical analysis and experimental method are presented to investigate the chatter stability in micro-end milling process with variable milling tool geometry. The schematic model of micromilling process is constructed and the calculation formula to predict cutting force and displacements is derived. This is followed by a detailed numerical analysis on micromilling forces between helical ball and square end mills through time domain and frequency domain method and the results are compared. Furthermore, a detailed time domain simulation for micro end milling with straight teeth and helical teeth end mill is conducted based on the machine-tool system frequency response function obtained through modal experiment. The forces and displacements are predicted and the simulation result between variable cutter geometry is deeply compared. The simulation results have important significance for the actual milling process.

  6. Analyst-to-Analyst Variability in Simulation-Based Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Glickman, Matthew R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Romero, Vicente J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-02-01

    This report describes findings from the culminating experiment of the LDRD project entitled, "Analyst-to-Analyst Variability in Simulation-Based Prediction". For this experiment, volunteer participants solving a given test problem in engineering and statistics were interviewed at different points in their solution process. These interviews are used to trace differing solutions to differing solution processes, and differing processes to differences in reasoning, assumptions, and judgments. The issue that the experiment was designed to illuminate -- our paucity of understanding of the ways in which humans themselves have an impact on predictions derived from complex computational simulations -- is a challenging and open one. Although solution of the test problem by analyst participants in this experiment has taken much more time than originally anticipated, and is continuing past the end of this LDRD, this project has provided a rare opportunity to explore analyst-to-analyst variability in significant depth, from which we derive evidence-based insights to guide further explorations in this important area.

  7. Predicting heat stress index in Sasso hens using automatic linear modeling and artificial neural network

    Science.gov (United States)

    Yakubu, A.; Oluremi, O. I. A.; Ekpo, E. I.

    2018-03-01

    There is an increasing use of robust analytical algorithms in the prediction of heat stress. The present investigation therefore, was carried out to forecast heat stress index (HSI) in Sasso laying hens. One hundred and sixty seven records on the thermo-physiological parameters of the birds were utilized. They were reared on deep litter and battery cage systems. Data were collected when the birds were 42- and 52-week of age. The independent variables fitted were housing system, age of birds, rectal temperature (RT), pulse rate (PR), and respiratory rate (RR). The response variable was HSI. Data were analyzed using automatic linear modeling (ALM) and artificial neural network (ANN) procedures. The ALM model building method involved Forward Stepwise using the F Statistic criterion. As regards ANN, multilayer perceptron (MLP) with back-propagation network was used. The ANN network was trained with 90% of the data set while 10% were dedicated to testing for model validation. RR and PR were the two parameters of utmost importance in the prediction of HSI. However, the fractional importance of RR was higher than that of PR in both ALM (0.947 versus 0.053) and ANN (0.677 versus 0.274) models. The two models also predicted HSI effectively with high degree of accuracy [r = 0.980, R 2 = 0.961, adjusted R 2 = 0.961, and RMSE = 0.05168 (ALM); r = 0.983, R 2 = 0.966; adjusted R 2 = 0.966, and RMSE = 0.04806 (ANN)]. The present information may be exploited in the development of a heat stress chart based largely on RR. This may aid detection of thermal discomfort in a poultry house under tropical and subtropical conditions.

  8. The Bird Community Resilience Index: a novel remote sensing-based biodiversity variable for quantifying ecological integrity

    Science.gov (United States)

    Michel, N. L.; Wilsey, C.; Burkhalter, C.; Trusty, B.; Langham, G.

    2017-12-01

    Scalable indicators of biodiversity change are critical to reporting overall progress towards national and global targets for biodiversity conservation (e.g. Aichi Targets) and sustainable development (SDGs). These essential biodiversity variables capitalize on new remote sensing technologies and growth of community science participation. Here we present a novel biodiversity metric quantifying resilience of bird communities and, by extension, of their associated ecological communities. This metric adds breadth to the community composition class of essential biodiversity variables that track trends in condition and vulnerability of ecological communities. We developed this index for use with North American grassland birds, a guild that has experienced stronger population declines than any other avian guild, in order to evaluate gains from the implementation of best management practices on private lands. The Bird Community Resilience Index was designed to incorporate the full suite of species-specific responses to management actions, and be flexible enough to work across broad climatic, land cover, and bird community gradients (i.e., grasslands from northern Mexico through Canada). The Bird Community Resilience Index consists of four components: density estimates of grassland and arid land birds; weighting based on conservation need; a functional diversity metric to incorporate resiliency of bird communities and their ecosystems; and a standardized scoring system to control for interannual variation caused by extrinsic factors (e.g., climate). We present an analysis of bird community resilience across ranches in the Northern Great Plains region of the United States. As predicted, Bird Community Resilience was higher in lands implementing best management practices than elsewhere. While developed for grassland birds, this metric holds great potential for use as an Essential Biodiversity Variable for community composition in a variety of habitat.

  9. On the predictability of land surface fluxes from meteorological variables

    Science.gov (United States)

    Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.

    2018-01-01

    Previous research has shown that land surface models (LSMs) are performing poorly when compared with relatively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appear to provide information about land surface fluxes that LSMs are not fully utilising. Here, we further quantify the information available in the meteorological forcing data that are used by LSMs for predicting land surface fluxes, by interrogating FLUXNET data, and extending the benchmarking methodology used in previous experiments. We show that substantial performance improvement is possible for empirical models using meteorological data alone, with no explicit vegetation or soil properties, thus setting lower bounds on a priori expectations on LSM performance. The process also identifies key meteorological variables that provide predictive power. We provide an ensemble of empirical benchmarks that are simple to reproduce and provide a range of behaviours and predictive performance, acting as a baseline benchmark set for future studies. We reanalyse previously published LSM simulations and show that there is more diversity between LSMs than previously indicated, although it remains unclear why LSMs are broadly performing so much worse than simple empirical models.

  10. It's the People, Stupid: The Role of Personality and Situational Variable in Predicting Decisionmaker Behavior

    National Research Council Canada - National Science Library

    Sticha, Paul J; Buede, Dennis M; Rees, Richard L

    2006-01-01

    .... to identity assumptions and determinant variables, and to quantify each variable's relative contribution to the prediction, producing a graphical representation of the analysis with explicit levels of uncertainty...

  11. A predictive model for pressure ulcer outcome: the Wound Healing Index.

    Science.gov (United States)

    Horn, Susan D; Barrett, Ryan S; Fife, Caroline E; Thomson, Brett

    2015-12-01

    The purpose of this learning activity is to provide information regarding the creation of a risk-stratification system to predict the likelihood of the healing of body and heel pressure ulcers (PrUs). This continuing education activity is intended for physicians and nurses with an interest in skin and wound care. After participating in this educational activity, the participant should be better able to:1. Explain the need for a PrU risk stratification tool.2. Describe the purpose and methodology of the study.3. Delineate the results of the study and development of the Wound Healing Index. : To create a validated system to predict the healing likelihood of patients with body and heel pressure ulcers (PrUs), incorporating only patient- and wound-specific variables. The US Wound Registry data were examined retrospectively and assigned a clear outcome (healed, amputated, and so on). Significant variables were identified with bivariate analyses. Multivariable logistic regression models were created based on significant factors (P wound clinics in 24 states : A total of 7973 body PrUs and 2350 heel PrUs were eligible for analysis. Not applicable : Healed PrU MAIN RESULTS:: Because of missing data elements, the logistic regression development model included 6640 body PrUs, of which 4300 healed (64.8%), and the 10% validation sample included 709 PrUs, of which 477 healed (67.3%). For heel PrUs, the logistic regression development model included 1909 heel PrUs, of which 1240 healed (65.0%), and the 10% validation sample included 203 PrUs, of which 133 healed (65.5%). Variables significantly predicting healing were PrU size, PrU age, number of concurrent wounds of any etiology, PrU Stage III or IV, evidence of bioburden/infection, patient age, being nonambulatory, having renal transplant, paralysis, malnutrition, and/or patient hospitalization for any reason. Body and heel PrU Wound Healing Indices are comprehensive, user-friendly, and validated predictive models for

  12. Building and verifying a severity prediction model of acute pancreatitis (AP) based on BISAP, MEWS and routine test indexes.

    Science.gov (United States)

    Ye, Jiang-Feng; Zhao, Yu-Xin; Ju, Jian; Wang, Wei

    2017-10-01

    To discuss the value of the Bedside Index for Severity in Acute Pancreatitis (BISAP), Modified Early Warning Score (MEWS), serum Ca2+, similarly hereinafter, and red cell distribution width (RDW) for predicting the severity grade of acute pancreatitis and to develop and verify a more accurate scoring system to predict the severity of AP. In 302 patients with AP, we calculated BISAP and MEWS scores and conducted regression analyses on the relationships of BISAP scoring, RDW, MEWS, and serum Ca2+ with the severity of AP using single-factor logistics. The variables with statistical significance in the single-factor logistic regression were used in a multi-factor logistic regression model; forward stepwise regression was used to screen variables and build a multi-factor prediction model. A receiver operating characteristic curve (ROC curve) was constructed, and the significance of multi- and single-factor prediction models in predicting the severity of AP using the area under the ROC curve (AUC) was evaluated. The internal validity of the model was verified through bootstrapping. Among 302 patients with AP, 209 had mild acute pancreatitis (MAP) and 93 had severe acute pancreatitis (SAP). According to single-factor logistic regression analysis, we found that BISAP, MEWS and serum Ca2+ are prediction indexes of the severity of AP (P-value0.05). The multi-factor logistic regression analysis showed that BISAP and serum Ca2+ are independent prediction indexes of AP severity (P-value0.05); BISAP is negatively related to serum Ca2+ (r=-0.330, P-valuemodel is as follows: ln()=7.306+1.151*BISAP-4.516*serum Ca2+. The predictive ability of each model for SAP follows the order of the combined BISAP and serum Ca2+ prediction model>Ca2+>BISAP. There is no statistical significance for the predictive ability of BISAP and serum Ca2+ (P-value>0.05); however, there is remarkable statistical significance for the predictive ability using the newly built prediction model as well as BISAP

  13. A fear index to predict oil futures returns

    International Nuclear Information System (INIS)

    Chevallier, Julien; Sevi, Benoit

    2013-01-01

    This paper evaluates the predictability of WTI light sweet crude oil futures by using the variance risk premium, i.e. the difference between model-free measures of implied and realized volatilities. Additional regressors known for their ability to explain crude oil futures prices are also considered, capturing macro-economic, financial and oil-specific influences. The results indicate that the explanatory power of the (negative) variance risk premium on oil excess returns is particularly strong (up to 25% for the adjusted R-squared across our regressions). It complements other financial (e.g. default spread) and oil-specific (e.g. US oil stocks) factors highlighted in previous literature. (authors)

  14. A new body shape index predicts mortality hazard independently of body mass index.

    Directory of Open Access Journals (Sweden)

    Nir Y Krakauer

    Full Text Available Obesity, typically quantified in terms of Body Mass Index (BMI exceeding threshold values, is considered a leading cause of premature death worldwide. For given body size (BMI, it is recognized that risk is also affected by body shape, particularly as a marker of abdominal fat deposits. Waist circumference (WC is used as a risk indicator supplementary to BMI, but the high correlation of WC with BMI makes it hard to isolate the added value of WC.We considered a USA population sample of 14,105 non-pregnant adults (age ≥ 18 from the National Health and Nutrition Examination Survey (NHANES 1999-2004 with follow-up for mortality averaging 5 yr (828 deaths. We developed A Body Shape Index (ABSI based on WC adjusted for height and weight: ABSI ≡ WC/(BMI(2/3height(1/2. ABSI had little correlation with height, weight, or BMI. Death rates increased approximately exponentially with above average baseline ABSI (overall regression coefficient of +33% per standard deviation of ABSI [95% confidence interval: +20%-+48%, whereas elevated death rates were found for both high and low values of BMI and WC. 22% (8%-41% of the population mortality hazard was attributable to high ABSI, compared to 15% (3%-30% for BMI and 15% (4%-29% for WC. The association of death rate with ABSI held even when adjusted for other known risk factors including smoking, diabetes, blood pressure, and serum cholesterol. ABSI correlation with mortality hazard held across the range of age, sex, and BMI, and for both white and black ethnicities (but not for Mexican ethnicity, and was not weakened by excluding deaths from the first 3 yr of follow-up.Body shape, as measured by ABSI, appears to be a substantial risk factor for premature mortality in the general population derivable from basic clinical measurements. ABSI expresses the excess risk from high WC in a convenient form that is complementary to BMI and to other known risk factors.

  15. Prediction of low birth weight: the placental T2* estimated by MRI versus the uterine artery pulsatility index

    DEFF Research Database (Denmark)

    Sinding, Marianne Munk; Peters, David Alberg; Frøkjær, Jens Brøndum

    (MRI) variable T2* reflects the placental oxygenation and thereby placental function. Therefore, we aimed to evaluate the performance of placental T2* in the prediction of low birth weight using the uterine artery (UtA) pulsatility index (PI) as gold standard. Methods: The study population......CONTROL ID: 2516296 ABSTRACT FINAL ID: P22.05 TITLE: Prediction of low birth weight: the placental T2* estimated by MRI versus the uterine artery pulsatility index AUTHORS (FIRST NAME, LAST NAME): Marianne Sinding1, David Peters2, Jens B. Frøkjær3, 4, Ole B. Christiansen1, 4, Astrid Petersen5...... had an EFW T2* was measured by MRI at 1.5T. A gradient recalled echo MRI sequence with readout at 16 echo times was used, and the placental T2* value was obtained by fitting the signal intensity as a function of the echo times...

  16. Marine heatwaves off eastern Tasmania: Trends, interannual variability, and predictability

    Science.gov (United States)

    Oliver, Eric C. J.; Lago, Véronique; Hobday, Alistair J.; Holbrook, Neil J.; Ling, Scott D.; Mundy, Craig N.

    2018-02-01

    Surface waters off eastern Tasmania are a global warming hotspot. Here, mean temperatures have been rising over several decades at nearly four times the global average rate, with concomitant changes in extreme temperatures - marine heatwaves. These changes have recently caused the marine biodiversity, fisheries and aquaculture industries off Tasmania's east coast to come under stress. In this study we quantify the long-term trends, variability and predictability of marine heatwaves off eastern Tasmania. We use a high-resolution ocean model for Tasmania's eastern continental shelf. The ocean state over the 1993-2015 period is hindcast, providing daily estimates of the three-dimensional temperature and circulation fields. Marine heatwaves are identified at the surface and subsurface from ocean temperature time series using a consistent definition. Trends in marine heatwave frequency are positive nearly everywhere and annual marine heatwave days and penetration depths indicate significant positive changes, particularly off southeastern Tasmania. A decomposition into modes of variability indicates that the East Australian Current is the dominant driver of marine heatwaves across the domain. Self-organising maps are used to identify 12 marine heatwave types, each with its own regionality, seasonality, and associated large-scale oceanic and atmospheric circulation patterns. The implications of this work for marine ecosystems and their management were revealed through review of past impacts and stakeholder discussions regarding use of these data.

  17. On Use of the Variable Zagreb vM2 Index in QSPR: Boiling Points of Benzenoid Hydrocarbons

    Directory of Open Access Journals (Sweden)

    Albin Jurić

    2004-12-01

    Full Text Available The variable Zagreb vM2 index is introduced and applied to the structure-boiling point modeling of benzenoid hydrocarbons. The linear model obtained (thestandard error of estimate for the fit model Sfit=6.8 oC is much better than thecorresponding model based on the original Zagreb M2 index (Sfit=16.4 oC. Surprisingly,the model based on the variable vertex-connectivity index (Sfit=6.8 oC is comparable tothe model based on vM2 index. A comparative study with models based on the vertex-connectivity index, edge-connectivity index and several distance indices favours modelsbased on the variable Zagreb vM2 index and variable vertex-connectivity index.However, the multivariate regression with two-, three- and four-descriptors givesimproved models, the best being the model with four-descriptors (but vM2 index is notamong them with Sfit=5 oC, though the four-descriptor model contaning vM2 index isonly slightly inferior (Sfit=5.3 oC.

  18. A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.

    Directory of Open Access Journals (Sweden)

    Magdalena Ydreborg

    Full Text Available Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI in the paper, was based on the model: Log-odds (predicting cirrhosis = -12.17+ (age × 0.11 + (BMI (kg/m(2 × 0.23 + (D7-lathosterol (μg/100 mg cholesterol×(-0.013 + (Platelet count (x10(9/L × (-0.018 + (Prothrombin-INR × 3.69. The area under the ROC curve (AUROC for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96. The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98. In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.

  19. Predictive value of European Scleroderma Group Activity Index in an early scleroderma cohort.

    Science.gov (United States)

    Nevskaya, Tatiana; Baron, Murray; Pope, Janet E

    2017-07-01

    To estimate the effect of disease activity, as measured by the European Scleroderma Research Group Activity Index (EScSG-AI), on the risk of subsequent organ damage in a large systemic sclerosis (SSc) cohort. Of 421 SSc patients from the Canadian Scleroderma Research Group database with disease duration of ⩽ 3 years, 197 who had no evidence of end-stage organ damage initially and available 3 year follow-up were included. Disease activity was assessed by the EScSG-AI with two variability measures: the adjusted mean EScSG-AI (the area under the curve of the EScSG-AI over the observation period) and persistently active disease/flare. Outcomes were based on the Medsger severity scale and included accrual of a new severity score (Δ ⩾ 1) overall and within organ systems or reaching a significant level of deterioration in health status. After adjustment for covariates, the adjusted mean EScSG-AI was the most consistent predictor of risk across the study outcomes over 3 years in dcSSc: disease progression defined as Δ ⩾ 1 in any major internal organ, significant decline in forced vital capacity and diffusing capacity of carbon monoxide, severity of visceral disease and HAQ Disability Index worsening. In multivariate analysis, progression of lung disease was predicted solely by adjusted mean EScSG-AI, while the severity of lung disease was predicted the adjusted mean EScSG-AI, older age, modified Rodnan skin score (mRSS) and initial severity. The EScSG-AI was associated with patient- and physician-assessed measures of health status and overpowered the mRSS in predicting disease outcomes. Disease activity burden quantified with the adjusted mean EScSG-AI predicted the risk of deterioration in health status and severe organ involvement in dcSSc. The EScSG-AI is more responsive when done repeatedly and averaged. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email

  20. Fluorescence microscopy point spread function model accounting for aberrations due to refractive index variability within a specimen.

    Science.gov (United States)

    Ghosh, Sreya; Preza, Chrysanthe

    2015-07-01

    A three-dimensional (3-D) point spread function (PSF) model for wide-field fluorescence microscopy, suitable for imaging samples with variable refractive index (RI) in multilayered media, is presented. This PSF model is a key component for accurate 3-D image restoration of thick biological samples, such as lung tissue. Microscope- and specimen-derived parameters are combined with a rigorous vectorial formulation to obtain a new PSF model that accounts for additional aberrations due to specimen RI variability. Experimental evaluation and verification of the PSF model was accomplished using images from 175-nm fluorescent beads in a controlled test sample. Fundamental experimental validation of the advantage of using improved PSFs in depth-variant restoration was accomplished by restoring experimental data from beads (6  μm in diameter) mounted in a sample with RI variation. In the investigated study, improvement in restoration accuracy in the range of 18 to 35% was observed when PSFs from the proposed model were used over restoration using PSFs from an existing model. The new PSF model was further validated by showing that its prediction compares to an experimental PSF (determined from 175-nm beads located below a thick rat lung slice) with a 42% improved accuracy over the current PSF model prediction.

  1. Assessment of the de Hirsch Predictive Index Tests of Reading Failure.

    Science.gov (United States)

    Askov, Warren; And Others

    The predictive validity and the general usability of a battery of 10 tests reported by de Hirsch, Jansky, and Langford, the de Hirsch Predictive Index Tests of reading failure, were examined. The de Hirsch battery was administered to 433 kindergarten children in six public schools. When the pupils entered first grade, the Metropolitan Readiness…

  2. Predicting nosocomial lower respiratory tract infections by a risk index based system

    NARCIS (Netherlands)

    Chen, Yong; Shan, Xue; Zhao, Jingya; Han, Xuelin; Tian, Shuguang; Chen, Fangyan; Su, Xueting; Sun, Yansong; Huang, Liuyu; Grundmann, Hajo; Wang, Hongyuan; Han, Li

    2017-01-01

    Although belonging to one of the most common type of nosocomial infection, there was currently no simple prediction model for lower respiratory tract infections (LRTIs). This study aims to develop a risk index based system for predicting nosocomial LRTIs based on data from a large point-prevalence

  3. Construction of prediction intervals for Palmer Drought Severity Index using bootstrap

    Science.gov (United States)

    Beyaztas, Ufuk; Bickici Arikan, Bugrayhan; Beyaztas, Beste Hamiye; Kahya, Ercan

    2018-04-01

    In this study, we propose an approach based on the residual-based bootstrap method to obtain valid prediction intervals using monthly, short-term (three-months) and mid-term (six-months) drought observations. The effects of North Atlantic and Arctic Oscillation indexes on the constructed prediction intervals are also examined. Performance of the proposed approach is evaluated for the Palmer Drought Severity Index (PDSI) obtained from Konya closed basin located in Central Anatolia, Turkey. The finite sample properties of the proposed method are further illustrated by an extensive simulation study. Our results revealed that the proposed approach is capable of producing valid prediction intervals for future PDSI values.

  4. Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer.

    Science.gov (United States)

    Loeb, Stacy; Shin, Sanghyuk S; Broyles, Dennis L; Wei, John T; Sanda, Martin; Klee, George; Partin, Alan W; Sokoll, Lori; Chan, Daniel W; Bangma, Chris H; van Schaik, Ron H N; Slawin, Kevin M; Marks, Leonard S; Catalona, William J

    2017-07-01

    To examine the use of the Prostate Health Index (PHI) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study. The study population included 728 men, with prostate-specific antigen (PSA) levels of 2-10 ng/mL and a negative digital rectal examination, enrolled in a prospective, multi-site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [PCPT] and European Randomised Study of Screening for Prostate Cancer [ERSPC] risk calculators). We also designed and internally validated a new PHI-based multivariable predictive model, and created a nomogram. Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI, with an area under the curve of 0.746. The bootstrap-corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision-curve analysis. Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

  5. Using a Budyko Derived Index to Evaluate the Internal Hydrological Variability of Catchments in Complex Terrain

    Science.gov (United States)

    Dominguez, M.

    2017-12-01

    Headwater catchments in complex terrain typically exhibit significant variations in microclimatic conditions across slopes. This microclimatic variability in turn, modifies land surface properties presumably altering the hydrologic dynamics of these catchments. The extent to which differences in microclimate and land cover dictate the partition of water and energy fluxes within a catchment is still poorly understood. In this study, we attempt to do an assessment of the effects of aspect, elevation and latitude (which are the principal factors that define microclimate conditions) on the hydrologic behavior of the hillslopes within catchments with complex terrain. Using a distributed hydrologic model on a number of catchments at different latitudes, where data is available for calibration and validation, we estimate the different components of the water balance to obtain the aridity index (AI = PET/P) and the evaporative index (EI = AET/P) of each slope for a number of years. We use Budyko's curve as a framework to characterize the inter-annual variability in the hydrologic response of the hillslopes in the studied catchments, developing a hydrologic sensitivity index (HSi) based on the relative change in Budyko's curve components (HSi=ΔAI/ΔEI). With this method, when the HSi values of a given hillslope are larger than 1 the hydrologic behavior of that part of the catchment is considered sensitive to changes in climatic conditions, while values approaching 0 would indicate the opposite. We use this approach as a diagnostic tool to discern the effect of aspect, elevation, and latitude on the hydrologic regime of the slopes in complex terrain catchments and to try to explain observed patterns of land cover conditions on these types of catchments.

  6. Measuring psychosocial variables that predict older persons' oral health behaviour.

    Science.gov (United States)

    Kiyak, H A

    1996-12-01

    The importance of recognising psychosocial characteristics of older people that influence their oral health behaviours and the potential success of dental procedures is discussed. Three variables and instruments developed and tested by the author and colleagues are presented. A measure of perceived importance of oral health behaviours has been found to be a significant predictor of dental service utilization in three studies. Self-efficacy regarding oral health has been found to be lower than self-efficacy regarding general health and medication use among older adults, especially among non-Western ethnic minorities. The significance of self-efficacy for predicting changes in caries and periodontal disease is described. Finally, a measure of expectations regarding specific dental procedures has been used with older people undergoing implant therapy. Studies with this instrument reveal that patients have concerns about the procedure far different than those focused on by dental providers. All three instruments can be used in clinical practice as a means of understanding patients' values, perceived oral health abilities, and expectations from dental care. These instruments can enhance dentist-patient rapport and improve the chances of successful dental outcomes for older patients.

  7. Fatty liver index and hepatic steatosis index for prediction of non-alcoholic fatty liver disease in type 1 diabetes.

    Science.gov (United States)

    Sviklāne, Laura; Olmane, Evija; Dzērve, Zane; Kupčs, Kārlis; Pīrāgs, Valdis; Sokolovska, Jeļizaveta

    2018-01-01

    Little is known about the diagnostic value of hepatic steatosis index (HSI) and fatty liver index (FLI), as well as their link to metabolic syndrome in type 1 diabetes mellitus. We have screened the effectiveness of FLI and HSI in an observational pilot study of 40 patients with type 1 diabetes. FLI and HSI were calculated for 201 patients with type 1 diabetes. Forty patients with FLI/HSI values corresponding to different risk of liver steatosis were invited for liver magnetic resonance study. In-phase/opposed-phase technique of magnetic resonance was used. Accuracy of indices was assessed from the area under the receiver operating characteristic curve. Twelve (30.0%) patients had liver steatosis. For FLI, sensitivity was 90%; specificity, 74%; positive likelihood ratio, 3.46; negative likelihood ratio, 0.14; positive predictive value, 0.64; and negative predictive value, 0.93. For HSI, sensitivity was 86%; specificity, 66%; positive likelihood ratio, 1.95; negative likelihood ratio, 0.21; positive predictive value, 0.50; and negative predictive value, 0.92. Area under the receiver operating characteristic curve for FLI was 0.86 (95% confidence interval [0.72; 0.99]); for HSI 0.75 [0.58; 0.91]. Liver fat correlated with liver enzymes, waist circumference, triglycerides, and C-reactive protein. FLI correlated with C-reactive protein, liver enzymes, and blood pressure. HSI correlated with waist circumference and C-reactive protein. FLI ≥ 60 and HSI ≥ 36 were significantly associated with metabolic syndrome and nephropathy. The tested indices, especially FLI, can serve as surrogate markers for liver fat content and metabolic syndrome in type 1 diabetes. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  8. Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

    Science.gov (United States)

    Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

    2018-03-01

    The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

  9. Leaf area index from litter collection: impact of specific leaf area variability within a beech stand

    Energy Technology Data Exchange (ETDEWEB)

    Bouriaud, O. [Inst. National de la Recherche Agronomique, Centre de Recherches Forestieres de Nancy, Champenoux (France); Soudani, K. [Univ. Paris-Sud XI, Dept. d' Ecophysiologie Vegetale, Lab. Ecologie Systematique et Evolution, Orsay Cedex (France); Breda, N. [Inst. National de la Recherche Agronomique, Centre de Recherches Forestieres de Nancy, Champenoux (France)

    2003-06-01

    Litter fall collection is a direct method widely used to estimate leaf area index (LAI) in broad-leaved forest stands. Indirect measurements using radiation transmittance and gap fraction theory are often compared and calibrated against litter fall, which is considered as a reference method, but few studies address the question of litter specific leaf area (SLA) measurement and variability. SLA (leaf area per unit of dry weight, m{sup 2}{center_dot}g{sup -1}) is used to convert dry leaf litter biomass (g .m{sup -}2) into leaf area per ground unit area (m{sup 2}{center_dot}m{sup -2}). We paid special attention to this parameter in two young beech stands (dense and thinned) in northeastern France. The variability of both canopy (closure, LAI) and site conditions (soil properties, vegetation) was investigated as potential contributing factors to beech SLA variability. A systematic description of soil and floristic composition was performed and three types of soil were identified. Ellenberg's indicator values were averaged for each plot to assess nitrogen soil content. SLA of beech litter was measured three times during the fall in 23 plots in the stands (40 ha). Litter was collected bimonthly in square-shaped traps (0.5 m{sup 2}) and dried. Before drying, 30 leaves per plot and for each date were sampled, and leaf length, width, and area were measured with the help of a LI-COR areameter. SLA was calculated as the ratio of cumulated leaf area to total dry weight of the 30 leaves. Leaves characteristics per plot were averaged for the three dates of litter collection. Plant area index (PAI), estimated using the LAI-2000 plant canopy analyser and considering only the upper three rings, ranged from 2.9 to 8.1. Specific leaf area of beech litter was also highly different from one plot to the other, ranging from 150 to 320 cm{sup 2}{center_dot}g{sup -1}. Nevertheless, no relationship was found between SLA and stand canopy closure or PAI On the contrary, a significant

  10. Leaf area index from litter collection: impact of specific leaf area variability within a beech stand

    International Nuclear Information System (INIS)

    Bouriaud, O.; Soudani, K.; Breda, N.

    2003-01-01

    Litter fall collection is a direct method widely used to estimate leaf area index (LAI) in broad-leaved forest stands. Indirect measurements using radiation transmittance and gap fraction theory are often compared and calibrated against litter fall, which is considered as a reference method, but few studies address the question of litter specific leaf area (SLA) measurement and variability. SLA (leaf area per unit of dry weight, m 2 ·g -1 ) is used to convert dry leaf litter biomass (g .m - 2) into leaf area per ground unit area (m 2 ·m -2 ). We paid special attention to this parameter in two young beech stands (dense and thinned) in northeastern France. The variability of both canopy (closure, LAI) and site conditions (soil properties, vegetation) was investigated as potential contributing factors to beech SLA variability. A systematic description of soil and floristic composition was performed and three types of soil were identified. Ellenberg's indicator values were averaged for each plot to assess nitrogen soil content. SLA of beech litter was measured three times during the fall in 23 plots in the stands (40 ha). Litter was collected bimonthly in square-shaped traps (0.5 m 2 ) and dried. Before drying, 30 leaves per plot and for each date were sampled, and leaf length, width, and area were measured with the help of a LI-COR areameter. SLA was calculated as the ratio of cumulated leaf area to total dry weight of the 30 leaves. Leaves characteristics per plot were averaged for the three dates of litter collection. Plant area index (PAI), estimated using the LAI-2000 plant canopy analyser and considering only the upper three rings, ranged from 2.9 to 8.1. Specific leaf area of beech litter was also highly different from one plot to the other, ranging from 150 to 320 cm 2 ·g -1 . Nevertheless, no relationship was found between SLA and stand canopy closure or PAI On the contrary, a significant relationship between SLA and soil properties was observed. Both SLA

  11. Joint spatiotemporal variability of global sea surface temperatures and global Palmer drought severity index values

    Science.gov (United States)

    Apipattanavis, S.; McCabe, G.J.; Rajagopalan, B.; Gangopadhyay, S.

    2009-01-01

    Dominant modes of individual and joint variability in global sea surface temperatures (SST) and global Palmer drought severity index (PDSI) values for the twentieth century are identified through a multivariate frequency domain singular value decomposition. This analysis indicates that a secular trend and variability related to the El Niño–Southern Oscillation (ENSO) are the dominant modes of variance shared among the global datasets. For the SST data the secular trend corresponds to a positive trend in Indian Ocean and South Atlantic SSTs, and a negative trend in North Pacific and North Atlantic SSTs. The ENSO reconstruction shows a strong signal in the tropical Pacific, North Pacific, and Indian Ocean regions. For the PDSI data, the secular trend reconstruction shows high amplitudes over central Africa including the Sahel, whereas the regions with strong ENSO amplitudes in PDSI are the southwestern and northwestern United States, South Africa, northeastern Brazil, central Africa, the Indian subcontinent, and Australia. An additional significant frequency, multidecadal variability, is identified for the Northern Hemisphere. This multidecadal frequency appears to be related to the Atlantic multidecadal oscillation (AMO). The multidecadal frequency is statistically significant in the Northern Hemisphere SST data, but is statistically nonsignificant in the PDSI data.

  12. Association of Body Mass Index with Depression, Anxiety and Suicide-An Instrumental Variable Analysis of the HUNT Study.

    Directory of Open Access Journals (Sweden)

    Johan Håkon Bjørngaard

    Full Text Available While high body mass index is associated with an increased risk of depression and anxiety, cumulative evidence indicates that it is a protective factor for suicide. The associations from conventional observational studies of body mass index with mental health outcomes are likely to be influenced by reverse causality or confounding by ill-health. In the present study, we investigated the associations between offspring body mass index and parental anxiety, depression and suicide in order to avoid problems with reverse causality and confounding by ill-health.We used data from 32,457 mother-offspring and 27,753 father-offspring pairs from the Norwegian HUNT-study. Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale and suicide death from national registers. Associations between offspring and own body mass index and symptoms of anxiety and depression and suicide mortality were estimated using logistic and Cox regression. Causal effect estimates were estimated with a two sample instrument variable approach using offspring body mass index as an instrument for parental body mass index.Both own and offspring body mass index were positively associated with depression, while the results did not indicate any substantial association between body mass index and anxiety. Although precision was low, suicide mortality was inversely associated with own body mass index and the results from the analysis using offspring body mass index supported these results. Adjusted odds ratios per standard deviation body mass index from the instrumental variable analysis were 1.22 (95% CI: 1.05, 1.43 for depression, 1.10 (95% CI: 0.95, 1.27 for anxiety, and the instrumental variable estimated hazard ratios for suicide was 0.69 (95% CI: 0.30, 1.63.The present study's results indicate that suicide mortality is inversely associated with body mass index. We also found support for a positive association between body mass index and depression, but not

  13. Prediction of melanoma metastasis by the Shields index based on lymphatic vessel density

    Directory of Open Access Journals (Sweden)

    Metcalfe Chris

    2010-05-01

    Full Text Available Abstract Background Melanoma usually presents as an initial skin lesion without evidence of metastasis. A significant proportion of patients develop subsequent local, regional or distant metastasis, sometimes many years after the initial lesion was removed. The current most effective staging method to identify early regional metastasis is sentinel lymph node biopsy (SLNB, which is invasive, not without morbidity and, while improving staging, may not improve overall survival. Lymphatic density, Breslow's thickness and the presence or absence of lymphatic invasion combined has been proposed to be a prognostic index of metastasis, by Shields et al in a patient group. Methods Here we undertook a retrospective analysis of 102 malignant melanomas from patients with more than five years follow-up to evaluate the Shields' index and compare with existing indicators. Results The Shields' index accurately predicted outcome in 90% of patients with metastases and 84% without metastases. For these, the Shields index was more predictive than thickness or lymphatic density. Alternate lymphatic measurement (hot spot analysis was also effective when combined into the Shields index in a cohort of 24 patients. Conclusions These results show the Shields index, a non-invasive analysis based on immunohistochemistry of lymphatics surrounding primary lesions that can accurately predict outcome, is a simple, useful prognostic tool in malignant melanoma.

  14. PDW Index - A Simple Model for the Prediction of Liver Fibrosis in Chronic Viral Hepatitis

    International Nuclear Information System (INIS)

    Ashraf, S.; Ali, N.

    2013-01-01

    Objectives: To assess the accuracy of platelets, platelet morphological parameters, mean platelet volume(MPV) and platelet distribution width, (PDW) to diagnose advanced fibrosis. Study Design: Validation study. Place and Duration of Study: Combined Military Hospital, Malir, from Jun 2008 to Jun 2009. Patients and Methods: Simple laboratory tests, aspartate aminotransferase (AST) alanine aminotransferase (ALT) platelet count and platelet morphological parameters were measured in 91 chronic viral hepatitis patients. All patients had liver biopsy performed. A new index, PDW index was derived to detect the opposing effects of liver fibrosis on platelet count, MPV, and PDW. The predictive value of the index for advanced fibrosis (F3-F4) was assessed through descriptive statistics and area under the ROC curves. Results: Two cut-offs were chosen to qualify different stages of fibrosis. A value of > 8.00 predicted advanced fibrosis, F3-F4, with a specificity of 94% and positive predictive value of 78%. A value of < 6.00 ruled out advanced fibrosis with a negative predictive value of 93% and a sensitivity of 82%. The area under the ROC curve for advanced fibrosis was 0.840. PDW Index values outside of these cut-offs correctly classified 60% of patients. Conclusion: A simple index comprising platelet as only parameters have high diagnostic value for the advanced stages of fibrosis. (author)

  15. Prediction of higher cost of antiretroviral therapy (ART) according to clinical complexity. A validated clinical index.

    Science.gov (United States)

    Velasco, Cesar; Pérez, Inaki; Podzamczer, Daniel; Llibre, Josep Maria; Domingo, Pere; González-García, Juan; Puig, Inma; Ayala, Pilar; Martín, Mayte; Trilla, Antoni; Lázaro, Pablo; Gatell, Josep Maria

    2016-03-01

    The financing of antiretroviral therapy (ART) is generally determined by the cost incurred in the previous year, the number of patients on treatment, and the evidence-based recommendations, but not the clinical characteristics of the population. To establish a score relating the cost of ART and patient clinical complexity in order to understand the costing differences between hospitals in the region that could be explained by the clinical complexity of their population. Retrospective analysis of patients receiving ART in a tertiary hospital between 2009 and 2011. Factors potentially associated with a higher cost of ART were assessed by bivariate and multivariate analysis. Two predictive models of "high-cost" were developed. The normalized estimated (adjusted for the complexity scores) costs were calculated and compared with the normalized real costs. In the Hospital Index, 631 (16.8%) of the 3758 patients receiving ART were responsible for a "high-cost" subgroup, defined as the highest 25% of spending on ART. Baseline variables that were significant predictors of high cost in the Clinic-B model in the multivariate analysis were: route of transmission of HIV, AIDS criteria, Spanish nationality, year of initiation of ART, CD4+ lymphocyte count nadir, and number of hospital admissions. The Clinic-B score ranged from 0 to 13, and the mean value (5.97) was lower than the overall mean value of the four hospitals (6.16). The clinical complexity of the HIV patient influences the cost of ART. The Clinic-B and Clinic-BF scores predicted patients with high cost of ART and could be used to compare and allocate costs corrected for the patient clinical complexity. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

  16. Fall Risk Index predicts functional decline regardless of fall experiences among community-dwelling elderly.

    Science.gov (United States)

    Ishimoto, Yasuko; Wada, Taizo; Kasahara, Yoriko; Kimura, Yumi; Fukutomi, Eriko; Chen, Wenling; Hirosaki, Mayumi; Nakatsuka, Masahiro; Fujisawa, Michiko; Sakamoto, Ryota; Ishine, Masayuki; Okumiya, Kiyohito; Otsuka, Kuniaki; Matsubayashi, Kozo

    2012-10-01

    The 21-item Fall Risk Index (FRI-21) has been used to detect elderly persons at risk for falls. The aim of this longitudinal study was to evaluate the FRI-21 as a predictor of decline in basic activities of daily living (BADL) among Japanese community-dwelling elderly persons independent of fall risk. The study population consisted of 518 elderly participants aged 65 years and older who were BADL independent at baseline in Tosa, Japan. We examined risk factors for BADL decline from 2008 to 2009 by multiple logistic regression analysis on the FRI-21 and other functional status measures in all participants. We carried out the same analysis in selected participants who had no experience of falls to remove the effect of falls. A total of 45 of 518 participants showed decline in BADL within 1 year. Multivariate logistic regression analysis showed that age (odds ratio [OR] 1.13, 95% confidence interval [CI] 1.05-1.20), FRI-21 ≥ 10 (OR 3.81, 95% CI 1.49-9.27), intellectual activity dependence (OR 3.25, 95% CI 1.42-7.44) and history of osteoarthropathy (OR 3.17, 95% CI 1.40-7.21) were significant independent risk factors for BADL decline within 1 year. FRI-21 ≥ 10 and intellectual activity dependence (≤ 3) remained significant predictors, even in selected non-fallers. FRI-21 ≥ 10 and intellectual activity dependence were significant predictive factors of BADL decline, regardless of fall experience, after adjustment for confounding variables. The FRI-21 is a brief, useful tool not only for predicting falls, but also future decline in functional ability in community-dwelling elderly persons. © 2012 Japan Geriatrics Society.

  17. Resting heart rate variability predicts safety learning and fear extinction in an interoceptive fear conditioning paradigm.

    Directory of Open Access Journals (Sweden)

    Meike Pappens

    Full Text Available This study aimed to investigate whether interindividual differences in autonomic inhibitory control predict safety learning and fear extinction in an interoceptive fear conditioning paradigm. Data from a previously reported study (N = 40 were extended (N = 17 and re-analyzed to test whether healthy participants' resting heart rate variability (HRV - a proxy of cardiac vagal tone - predicts learning performance. The conditioned stimulus (CS was a slight sensation of breathlessness induced by a flow resistor, the unconditioned stimulus (US was an aversive short-lasting suffocation experience induced by a complete occlusion of the breathing circuitry. During acquisition, the paired group received 6 paired CS-US presentations; the control group received 6 explicitly unpaired CS-US presentations. In the extinction phase, both groups were exposed to 6 CS-only presentations. Measures included startle blink EMG, skin conductance responses (SCR and US-expectancy ratings. Resting HRV significantly predicted the startle blink EMG learning curves both during acquisition and extinction. In the unpaired group, higher levels of HRV at rest predicted safety learning to the CS during acquisition. In the paired group, higher levels of HRV were associated with better extinction. Our findings suggest that the strength or integrity of prefrontal inhibitory mechanisms involved in safety- and extinction learning can be indexed by HRV at rest.

  18. Body mass index predicts risk for complications from transtemporal cerebellopontine angle surgery.

    Science.gov (United States)

    Mantravadi, Avinash V; Leonetti, John P; Burgette, Ryan; Pontikis, George; Marzo, Sam J; Anderson, Douglas

    2013-03-01

    To determine the relationship between body mass index (BMI) and risk for specific complications from transtemporal cerebellopontine angle (CPA) surgery for nonmalignant disease. Case series with chart review. Tertiary-care academic hospital. Retrospective review of 134 consecutive patients undergoing transtemporal cerebellopontine angle surgery for nonmalignant disease from 2009 to 2011. Data were collected regarding demographics, body mass index, intraoperative details, hospital stay, and complications including cerebrospinal fluid leak, wound complications, and brachial plexopathy. One hundred thirty-four patients were analyzed with a mean preoperative body mass index of 28.58. Statistical analysis demonstrated a significant difference in body mass index between patients with a postoperative cerebrospinal fluid leak and those without (P = .04), as well as a similar significant difference between those experiencing postoperative brachial plexopathy and those with no such complication (P = .03). Logistical regression analysis confirmed that body mass index is significant in predicting both postoperative cerebrospinal fluid leak (P = .004; odds ratio, 1.10) and brachial plexopathy (P = .04; odds ratio, 1.07). Elevated body mass index was not significant in predicting wound complications or increased hospital stay beyond postoperative day 3. Risk of cerebrospinal fluid leak and brachial plexopathy is increased in patients with elevated body mass index undergoing surgery of the cerebellopontine angle. Consideration should be given to preoperative optimization via dietary and lifestyle modifications as well as intraoperative somatosensory evoked potential monitoring of the brachial plexus to decrease these risks.

  19. Prediction of university student’s addictability based on some demographic variables, academic procrastination, and interpersonal variables

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Tavakoli

    2014-02-01

    Full Text Available Objectives: This study aimed to predict addictability among the students, based on demographic variables, academic procrastination, and interpersonal variables, and also to study the prevalence of addictability among these students. Method: The participants were 500 students (260 females, 240 males selected through a stratified random sampling among the students in Islamic Azad University Branch Abadan. The participants were assessed through Individual specification inventory, addiction potential scale and Aitken procrastination Inventory. Findings: The findings showed %23/6 of students’ readiness for addiction. Men showed higher addictability than women, but age wasn’t an issue. Also variables such as economic status, age, major, and academic procrastination predicted %13, and among interpersonal variables, the variables of having friends who use drugs and dissociated family predicted %13/2 of the variance in addictability. Conclusion: This study contains applied implications for addiction prevention.

  20. Intra and interobserver variability of renal allograft ultrasound volume and resistive index measurements

    International Nuclear Information System (INIS)

    Mancini, Marcello; Liuzzi, Raffaele; Daniele, Stefania; Raffio, Teresa; Salvatore, Marco; Sabbatini, Massimo; Cianciaruso, Bruno; Ferrara, Liberato Aldo

    2005-01-01

    Purpose: Aim of the presents study was to evaluate the repeatability and reproducibility of the Doppler Resistive Index (R.I.) and the Ultrasound renal volume measurement in renal transplants. Materials and methods: Twenty -six consecutive patients (18 men, 8 women) mean age of 42,8±12,4 years (M±SD)(range 22-65 years) were studied twice by each of two trained sonographers using a color Doppler ultrasound scanner. Twelve of them had a normal allograft function (defined as stable serum creatinine levels ≤123,76 μmol/L), whilst the remaining 14 had decreased allograft function (serum creatinine 132.6-265.2 μmol/L). Results were given as mean of 6 measurements performed at upper, middle and lower pole of the kidney. Intra- and interobserver variability was assessed by the repeatability coefficient and coefficient of variation (CV). Results: Regarding Resistive Index measurement, repeatability coefficient was between 0.04 and 0.06 and the coefficient of variation was [it

  1. Evaluation of the Cerebral State Index in Cats under Isoflurane Anaesthesia: Dose-Effect Relationship and Prediction of Clinical Signs

    Directory of Open Access Journals (Sweden)

    Joana R. Sousa

    2014-01-01

    Full Text Available The performance of the cerebral state index (CSI in reflecting different levels of isoflurane anaesthesia was evaluated in ten cats subjected to four end-tidal isoflurane concentrations (EtIso, each maintained for 15 minutes (0.8%, 1.2%, 1.6%, or 2.0% EtIso. The CSI, hemodynamic data, ocular reflexes, and eye position were recorded for each EtIso concentration. Pharmacodynamic analysis of CSI with EtIso was performed, as well as prediction probability analysis with a clinical scale based on the eye reflexes. The CSI values showed great variability. Between all parameters, burst suppression ratio showed the better fitting with the sigmoidal concentration-effect model (R2=0.93 followed by CSI (R2=0.82 and electromyographic activity (R2=0.79. EtIso was the variable with better prediction of the clinical scale of anaesthesia (prediction probability value of 0.94. Although the CSI values decrease with increasing isoflurane concentrations, the huge variability in CSI values may be a strong limitation for its use in cats and it seems to be no better than EtIso as a predictor of clinical signs.

  2. The importance of histopathological and clinical variables in predicting the evolution of colon cancer.

    Science.gov (United States)

    Diculescu, Mircea; Iacob, Răzvan; Iacob, Speranţa; Croitoru, Adina; Becheanu, Gabriel; Popeneciu, Valentin

    2002-09-01

    It has been a consensus that prognostic factors should always be taken into account before planning treatment in colorectal cancer. A 5 year prospective study was conducted, in order to assess the importance of several histopathological and clinical prognostic variables in the prediction of evolution in colon cancer. Some of the factors included in the analysis are still subject to dispute by different authors. 46 of 53 screened patients qualified to enter the study and underwent a potentially curative resection of the tumor, followed, when necessary, by adjuvant chemotherapy. Univariate and multivariate analyses were carried out in order to identify independent prognostic indicators. The endpoint of the study was considered the recurrence of the tumor or the detection of metastases. 65.2% of the patients had a good evolution during the follow up period. Multivariate survival analysis performed by Cox proportional hazard model identified 3 independent prognostic factors: Dukes stage (p = 0.00002), the grade of differentiation (p = 0.0009) and the weight loss index, representing the weight loss of the patient divided by the number of months when it was actually lost (p = 0.02). Age under 40 years, sex, microscopic aspect of the tumor, tumor location, anemia degree were not identified by our analysis as having prognostic importance. Histopathological factors continue to be the most valuable source of information regarding the possible evolution of patients with colorectal cancer. Individual clinical symptoms or biological parameters such as erytrocyte sedimentation rate or hemoglobin level are of little or no prognostic value. More research is required relating to the impact of a performance status index (which could include also weight loss index) as another reliable prognostic variable.

  3. Mastication effects on the glycaemic index: impact on variability and practical implications.

    Science.gov (United States)

    Ranawana, V; Leow, M K-S; Henry, C J K

    2014-01-01

    Glycaemic variability challenges the accuracy and use of the glycaemic index (GI). The purpose of the current study was to determine the role of mastication on GI. Using a randomized, controlled, crossover, non-blind design, 15 healthy young subjects returned on 5 separate days for three glucose and two rice test sessions. At the rice sessions, subjects chewed each mouthful either 15 or 30 times. Rice chewed 15 times produced a total glycaemic response (GR; 155 mmol min/l), peak GR (2.4 mmol/l) and GI (68) significantly lower than when chewed for longer (30 times) (184 mmol min/l, 2.8 mmol/l and 88, respectively). The study shows that the GI of rice is affected by the degree of mastication. Chewing 15 times compared with 30 times significantly attenuates the GI, suggesting that mastication may potentially contribute to the glycaemic variability of rice. While future work must establish the extent and limits to which mastication affects glycaemia, it could also explore the potential of using mastication to reduce the glycaemic load of rice.

  4. Normalized difference vegetation index for the South American continent used as a climatic variability indicator

    International Nuclear Information System (INIS)

    Liu, W.T.; Massambani, O.; Festa, M.

    1992-01-01

    The NOAA AVHRR GAC data set was used to produce Normalized Difference Vegetation Index (NDVI) maps for the South American Continent covering the period from August 1, 1981 to June 30, 1987. A 15-day maximum value composite procedure was used to partially eliminate the cloud contamination and atmospheric attenuation. Monthly evolution of NDVI for a dry and a wet year within the period studied was used to estimate the area covered by NDVI value less than 0.223, This value was used as an indicator of the drought area and the delineation of the Low rainfall areas in the continent. It was observed a well defined regional dependence of the drought area variability for the Northeast, Southwest and Northwest continent and also for the Amazon region. It is shown a relative estimation of the area coverage with NDVI less than 0.223 for the years 1982/83 and 1984/85. The dynamics of the drought area evolution in the continent is discussed. It is also presented a diagnosis of regional variability of the continental distribution of drought area from 1981 to 1987 for the months of May and September. This information is also used to discuss its relationship with the EL-Nino-Southern Oscillation (ENSO) and the South American Precipitation patterns during this period. It is suggested that the use of NDVI image to identify the dynamics of the drought induced by low rainfall may provide us valuable information to study the large scale climatic variation

  5. How well do financial and macroeconomic variables predict stock returns

    DEFF Research Database (Denmark)

    Rasmussen, Anne-Sofie Reng

    Recent evidence of mean reversion in stock returns has led to an explosion in the development of forecasting variables. This paper evaluates the relative performance of these many variables in both time-series and cross-sectional setups. We collect the different measures and compare their forecas......Recent evidence of mean reversion in stock returns has led to an explosion in the development of forecasting variables. This paper evaluates the relative performance of these many variables in both time-series and cross-sectional setups. We collect the different measures and compare...... their forecasting ability for stock returns, and we examine the forecasting variables' ability to reduce pricing errors in the conditional C-CAPM. A key result of the analysis is that the traditional pricedividend ratio performs surprisingly well compared to the many new forecasting variables. We also find...

  6. Quantifying Net Synergy/Redundancy of Spontaneous Variability Regulation via Predictability and Transfer Entropy Decomposition Frameworks.

    Science.gov (United States)

    Porta, Alberto; Bari, Vlasta; De Maria, Beatrice; Takahashi, Anielle C M; Guzzetti, Stefano; Colombo, Riccardo; Catai, Aparecida M; Raimondi, Ferdinando; Faes, Luca

    2017-11-01

    Objective: Indexes assessing the balance between redundancy and synergy were hypothesized to be helpful in characterizing cardiovascular control from spontaneous beat-to-beat variations of heart period (HP), systolic arterial pressure (SAP), and respiration (R). Methods: Net redundancy/synergy indexes were derived according to predictability and transfer entropy decomposition strategies via a multivariate linear regression approach. Indexes were tested in two protocols inducing modifications of the cardiovascular regulation via baroreflex loading/unloading (i.e., head-down tilt at -25° and graded head-up tilt at 15°, 30°, 45°, 60°, 75°, and 90°, respectively). The net redundancy/synergy of SAP and R to HP and of HP and R to SAP were estimated over stationary sequences of 256 successive values. Results: We found that: 1) regardless of the target (i.e., HP or SAP) redundancy was prevalent over synergy and this prevalence was independent of type and magnitude of the baroreflex challenge; 2) the prevalence of redundancy disappeared when decoupling inputs from output via a surrogate approach; 3) net redundancy was under autonomic control given that it varied in proportion to the vagal withdrawal during graded head-up tilt; and 4) conclusions held regardless of the decomposition strategy. Conclusion: Net redundancy indexes can monitor changes of cardiovascular control from a perspective completely different from that provided by more traditional univariate and multivariate methods. Significance: Net redundancy measures might provide a practical tool to quantify the reservoir of effective cardiovascular regulatory mechanisms sharing causal influences over a target variable. Objective: Indexes assessing the balance between redundancy and synergy were hypothesized to be helpful in characterizing cardiovascular control from spontaneous beat-to-beat variations of heart period (HP), systolic arterial pressure (SAP), and respiration (R). Methods: Net redundancy

  7. Indexed

    CERN Document Server

    Hagy, Jessica

    2008-01-01

    Jessica Hagy is a different kind of thinker. She has an astonishing talent for visualizing relationships, capturing in pictures what is difficult for most of us to express in words. At indexed.blogspot.com, she posts charts, graphs, and Venn diagrams drawn on index cards that reveal in a simple and intuitive way the large and small truths of modern life. Praised throughout the blogosphere as “brilliant,” “incredibly creative,” and “comic genius,” Jessica turns her incisive, deadpan sense of humor on everything from office politics to relationships to religion. With new material along with some of Jessica’s greatest hits, this utterly unique book will thrill readers who demand humor that makes them both laugh and think.

  8. Using the Speech Transmission Index for predicting non-native speech intelligibility

    NARCIS (Netherlands)

    Wijngaarden, S.J. van; Bronkhorst, A.W.; Houtgast, T.; Steeneken, H.J.M.

    2004-01-01

    While the Speech Transmission Index ~STI! is widely applied for prediction of speech intelligibility in room acoustics and telecommunication engineering, it is unclear how to interpret STI values when non-native talkers or listeners are involved. Based on subjectively measured psychometric functions

  9. Predictive Variables of Success for Latino Enrollment in Higher Education

    Science.gov (United States)

    Sanchez, Jafeth E.; Usinger, Janet; Thornton, Bill W.

    2015-01-01

    It is necessary to better understand the unique variables that serve as predictors of Latino students' postsecondary enrollment and success. Impacts of various variables were examined among 850 Latino and Caucasian students (76% and 24% of the sample, respectively). Gender, ethnicity, perceived affordability, high school grade point average, and…

  10. Improved predictability of droughts over southern Africa using the standardized precipitation evapotranspiration index and ENSO

    Science.gov (United States)

    Manatsa, Desmond; Mushore, Terrence; Lenouo, Andre

    2017-01-01

    The provision of timely and reliable climate information on which to base management decisions remains a critical component in drought planning for southern Africa. In this observational study, we have not only proposed a forecasting scheme which caters for timeliness and reliability but improved relevance of the climate information by using a novel drought index called the standardised precipitation evapotranspiration index (SPEI), instead of the traditional precipitation only based index, the standardised precipitation index (SPI). The SPEI which includes temperature and other climatic factors in its construction has a more robust connection to ENSO than the SPI. Consequently, the developed ENSO-SPEI prediction scheme can provide quantitative information about the spatial extent and severity of predicted drought conditions in a way that reflects more closely the level of risk in the global warming context of the sub region. However, it is established that the ENSO significant regional impact is restricted only to the period December-March, implying a revisit to the traditional ENSO-based forecast scheme which essentially divides the rainfall season into the two periods, October to December and January to March. Although the prediction of ENSO events has increased with the refinement of numerical models, this work has demonstrated that the prediction of drought impacts related to ENSO is also a reality based only on observations. A large temporal lag is observed between the development of ENSO phenomena (typically in May of the previous year) and the identification of regional SPEI defined drought conditions. It has been shown that using the Southern Africa Regional Climate Outlook Forum's (SARCOF) traditional 3-month averaged Nino 3.4 SST index (June to August) as a predictor does not have an added advantage over using only the May SST index values. In this regard, the extended lead time and improved skill demonstrated in this study could immensely benefit

  11. [Evaluation of thermal comfort in a student population: predictive value of an integrated index (Fanger's predicted mean value].

    Science.gov (United States)

    Catenacci, G; Terzi, R; Marcaletti, G; Tringali, S

    1989-01-01

    Practical applications and predictive values of a thermal comfort index (Fanger's PRV) were verified on a sample school population (1236 subjects) by studying the relationships between thermal sensations (subjective analysis), determined by means of an individual questionnaire, and the values of thermal comfort index (objective analysis) obtained by calculating the PMV index individually in the subjects under study. In homogeneous conditions of metabolic expenditure rate and thermal impedence from clothing, significant differences were found between the two kinds of analyses. At 22 degrees C mean radiant and operative temperature, the PMV values averaged 0 and the percentage of subjects who experienced thermal comfort did not exceed 60%. The high level of subjects who were dissatisfied with their environmental thermal conditions confirms the doubts regarding the use of the PMV index as a predictive indicator of thermal comfort, especially considering that the negative answers were not homogeneous nor attributable to the small thermal fluctuations (less than 0.5 degree C) measured in the classrooms.

  12. Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF.

    Directory of Open Access Journals (Sweden)

    Shanna L Ashley

    Full Text Available Biomarkers in easily accessible compartments like peripheral blood that can predict disease progression in idiopathic pulmonary fibrosis (IPF would be clinically useful regarding clinical trial participation or treatment decisions for patients. In this study, we used unbiased proteomics to identify relevant disease progression biomarkers in IPF.Plasma from IPF patients was measured using an 1129 analyte slow off-rate modified aptamer (SOMAmer array, and patient outcomes were followed over the next 80 weeks. Receiver operating characteristic (ROC curves evaluated sensitivity and specificity for levels of each biomarker and estimated area under the curve (AUC when prognostic biomarker thresholds were used to predict disease progression. Both logistic and Cox regression models advised biomarker selection for a composite disease progression index; index biomarkers were weighted via expected progression-free days lost during follow-up with a biomarker on the unfavorable side of the threshold.A six-analyte index, scaled 0 to 11, composed of markers of immune function, proteolysis and angiogenesis [high levels of ficolin-2 (FCN2, cathepsin-S (Cath-S, legumain (LGMN and soluble vascular endothelial growth factor receptor 2 (VEGFsR2, but low levels of inducible T cell costimulator (ICOS or trypsin 3 (TRY3] predicted better progression-free survival in IPF with a ROC AUC of 0.91. An index score ≥ 3 (group ≥ 2 was strongly associated with IPF progression after adjustment for age, gender, smoking status, immunomodulation, forced vital capacity % predicted and diffusing capacity for carbon monoxide % predicted (HR 16.8, 95% CI 2.2-126.7, P = 0.006.This index, derived from the largest proteomic analysis of IPF plasma samples to date, could be useful for clinical decision making in IPF, and the identified analytes suggest biological processes that may promote disease progression.

  13. Visuomotor correction is a robust contributor to force variability during index finger abduction by older adults

    Directory of Open Access Journals (Sweden)

    Brian L Tracy

    2015-12-01

    Full Text Available We examined aging-related differences in the contribution of visuomotor correction to force fluctuations during index finger abduction via the analysis of two datasets from similar subjects. Study 1 Young (N= 27, 23+/-8 yrs and older adults (N=14, 72+/- 9 yrs underwent assessment of maximum voluntary contraction force (MVC and force steadiness during constant-force (CF index finger abduction (2.5, 30, 65% MVC. For each trial, visual feedback of the force (VIS was provided for 8-10 s and removed for 8-10s (NOVIS. Visual gain of the force feedback at 2.5% MVC was high; 12- and 26-fold greater than the 30% and 65% MVC targets. Mean force, standard deviation (SD of force, and coefficient of variation (CV of force was calculated for detrended (<0.5Hz drift removed VIS and NOVIS data segments. Study 2 A similar group of 14 older adults performed discrete, randomly-ordered VIS or NOVIS trials at low target forces (1-3% MVC and high visual gain. Study 1 For young adults the CV of force was similar between VIS and NOVIS for the 2.5% (4.8 vs. 4.3%, 30% (3.2 vs. 3.2% and 65% (3.5 vs. 4.2% target forces. In contrast, for older adults the CV of force was greater for VIS than NOVIS for 2.5% MVC (6.6 vs. 4.2%, P<0.001, but not for the 30% (2.4 vs. 2.4% and 65% (3.1 vs. 3.3% target forces. At 2.5% MVC, the increase in CV of force for VIS compared with NOVIS was significantly greater (age x visual condition P=0.008 for older than young adults. Study 2 Similarly, for older adults performing discrete, randomly ordered trials the CV of force was greater for VIS than NOVIS (6.04 vs. 3.81%, P=0.01. When visual force feedback was a dominant source of information at low forces, normalized force variability was ~58% greater for older adults, but only 11% greater for young adults. The significant effect of visual feedback for older adults was not dependent on the order of presentation of visual conditions. The results indicate that impaired processing of visuomotor

  14. Racial Discrimination and Low Household Education Predict Higher Body Mass Index in African American Youth.

    Science.gov (United States)

    Nelson, Devin S; Gerras, Julia M; McGlumphy, Kellye C; Shaver, Erika R; Gill, Amaanat K; Kanneganti, Kamala; Ajibewa, Tiwaloluwa A; Hasson, Rebecca E

    The purpose of this study was to examine the relationships between environmental factors, including household education, community violence exposure, racial discrimination, and cultural identity, and BMI in African American adolescents. A community-based sample of 198 African American youth (120 girls, 78 boys; ages 11-19 years) from Washtenaw County, Michigan, were included in this analysis. Violence exposure was assessed by using the Survey of Children's Exposure to Community Violence; racial discrimination by using the Adolescent Discrimination Distress Index; cultural identity by using the Acculturation, Habits, and Interests Multicultural Scale for Adolescents; and household education by using a seven-category variable. Measured height and body weight were used to calculate BMI. Racial discrimination was positively associated with BMI, whereas household education was inversely associated with BMI in African American adolescents (discrimination: β = 0.11 ± 0.04, p = 0.01; education: β = -1.13 ± 0.47, p = 0.02). These relationships were significant when accounting for the confounding effects of stress, activity, diet, and pubertal development. Significant gender interactions were observed with racial discrimination and low household education associated with BMI in girls only (discrimination: β = 0.16 ± 0.05, p = 0.003; education: β = -1.12 ± 0.55, p = 0.045). There were no significant relationships between culture, community violence exposure, and BMI (all p's > 0.05). Environmental factors, including racial discrimination and low household education, predicted higher BMI in African American adolescents, particularly among girls. Longitudinal studies are needed to better understand the mechanisms by which these environmental factors increase obesity risk in African American youth.

  15. Executive function impairments in fibromyalgia syndrome: Relevance of clinical variables and body mass index

    Science.gov (United States)

    2018-01-01

    Background Several investigations suggest the presence of deterioration of executive function in fibromyalgia syndrome (FMS). The study quantified executive functions in patients with FMS. A wide array of functions was assessed, including updating, shifting and inhibition, as well as decision making and mental planning. Moreover, clinical variables were investigated as possible mediators of executive dysfunction, including pain severity, psychiatric comorbidity, medication and body mass index (BMI). Methods Fifty-two FMS patients and 32 healthy controls completed a battery of 14 neuropsychological tests. Clinical interviews were conducted and the McGill Pain Questionnaire, Beck Depression Inventory, State-Trait Anxiety Inventory, Fatigue Severity Scale and Oviedo Quality of Sleep Questionnaire were presented. Results Patients performed poorer than controls on the Letter Number Sequencing, Arithmetic and Similarities subtests of the Wechsler Adult Intelligence Scale, the Spatial Span subtest of the Wechsler Memory Scale, an N-back task, a verbal fluency task, the Ruff Figural Fluency Test, the Inhibition score of the Stroop Test, the Inhibition and Shifting scores of the Five Digits Test, the Key Search Test and the Zoo Map Task. Moreover, patients exhibited less steep learning curves on the Iowa Gambling Task. Among clinical variables, BMI and pain severity explained the largest proportion of performance variance. Conclusions This study demonstrated impairments in executive functions of updating, shifting inhibition, decision making and planning in FMS. While the mediating role of pain in cognitive impairments in FMS had been previously established, the influence of BMI is a novel finding. Overweight and obesity should be considered by FMS researchers, and in the treatment of the condition. PMID:29694417

  16. Executive function impairments in fibromyalgia syndrome: Relevance of clinical variables and body mass index.

    Science.gov (United States)

    Muñoz Ladrón de Guevara, Cristina; Fernández-Serrano, María José; Reyes Del Paso, Gustavo A; Duschek, Stefan

    2018-01-01

    Several investigations suggest the presence of deterioration of executive function in fibromyalgia syndrome (FMS). The study quantified executive functions in patients with FMS. A wide array of functions was assessed, including updating, shifting and inhibition, as well as decision making and mental planning. Moreover, clinical variables were investigated as possible mediators of executive dysfunction, including pain severity, psychiatric comorbidity, medication and body mass index (BMI). Fifty-two FMS patients and 32 healthy controls completed a battery of 14 neuropsychological tests. Clinical interviews were conducted and the McGill Pain Questionnaire, Beck Depression Inventory, State-Trait Anxiety Inventory, Fatigue Severity Scale and Oviedo Quality of Sleep Questionnaire were presented. Patients performed poorer than controls on the Letter Number Sequencing, Arithmetic and Similarities subtests of the Wechsler Adult Intelligence Scale, the Spatial Span subtest of the Wechsler Memory Scale, an N-back task, a verbal fluency task, the Ruff Figural Fluency Test, the Inhibition score of the Stroop Test, the Inhibition and Shifting scores of the Five Digits Test, the Key Search Test and the Zoo Map Task. Moreover, patients exhibited less steep learning curves on the Iowa Gambling Task. Among clinical variables, BMI and pain severity explained the largest proportion of performance variance. This study demonstrated impairments in executive functions of updating, shifting inhibition, decision making and planning in FMS. While the mediating role of pain in cognitive impairments in FMS had been previously established, the influence of BMI is a novel finding. Overweight and obesity should be considered by FMS researchers, and in the treatment of the condition.

  17. relationship of some variables in predicting pre service teachers

    African Journals Online (AJOL)

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    and gender could predict their problem solving performance in chemistry. The sample for the study ... accessible methods for obtaining the solution to the question, goal or objective. These ... the selected quantitative problems. Secondly ...

  18. Spatial Variability of Physical Soil Quality Index of an Agricultural Field

    Directory of Open Access Journals (Sweden)

    Sheikh M. Fazle Rabbi

    2014-01-01

    Full Text Available A field investigation was carried out to evaluate the spatial variability of physical indicators of soil quality of an agricultural field and to construct a physical soil quality index (SQIP map. Surface soil samples were collected using 10  m×10 m grid from an Inceptisol on Ganges Tidal Floodplain of Bangladesh. Five physical soil quality indicators, soil texture, bulk density, porosity, saturated hydraulic conductivity (KS, and aggregate stability (measured as mean weight diameter, MWD were determined. The spatial structures of sand, clay, and KS were moderate but the structure was strong for silt, bulk density, porosity, and MWD. Each of the physical soil quality indicators was transformed into 0 and 1 using threshold criteria which are required for crop production. The transformed indicators were the combined into SQIP. The kriged SQIP map showed that the agricultural field studied could be divided into two parts having “good physical quality” and “poor physical soil quality.”

  19. Dissipative advective accretion disc solutions with variable adiabatic index around black holes

    Science.gov (United States)

    Kumar, Rajiv; Chattopadhyay, Indranil

    2014-10-01

    We investigated accretion on to black holes in presence of viscosity and cooling, by employing an equation of state with variable adiabatic index and multispecies fluid. We obtained the expression of generalized Bernoulli parameter which is a constant of motion for an accretion flow in presence of viscosity and cooling. We obtained all possible transonic solutions for a variety of boundary conditions, viscosity parameters and accretion rates. We identified the solutions with their positions in the parameter space of generalized Bernoulli parameter and the angular momentum on the horizon. We showed that a shocked solution is more luminous than a shock-free one. For particular energies and viscosity parameters, we obtained accretion disc luminosities in the range of 10- 4 - 1.2 times Eddington luminosity, and the radiative efficiency seemed to increase with the mass accretion rate too. We found steady state shock solutions even for high-viscosity parameters, high accretion rates and for wide range of composition of the flow, starting from purely electron-proton to lepton-dominated accretion flow. However, similar to earlier studies of inviscid flow, accretion shock was not obtained for electron-positron pair plasma.

  20. A behavioral economic reward index predicts drinking resolutions: moderation revisited and compared with other outcomes.

    Science.gov (United States)

    Tucker, Jalie A; Roth, David L; Vignolo, Mary J; Westfall, Andrew O

    2009-04-01

    Data were pooled from 3 studies of recently resolved community-dwelling problem drinkers to determine whether a behavioral economic index of the value of rewards available over different time horizons distinguished among moderation (n = 30), abstinent (n = 95), and unresolved (n = 77) outcomes. Moderation over 1- to 2-year prospective follow-up intervals was hypothesized to involve longer term behavior regulation processes than abstinence or relapse and to be predicted by more balanced preresolution monetary allocations between short-term and longer term objectives (i.e., drinking and saving for the future). Standardized odds ratios (ORs) based on changes in standard deviation units from a multinomial logistic regression indicated that increases on this "Alcohol-Savings Discretionary Expenditure" index predicted higher rates of abstinence (OR = 1.93, p = .004) and relapse (OR = 2.89, p moderation outcomes. The index had incremental utility in predicting moderation in complex models that included other established predictors. The study adds to evidence supporting a behavioral economic analysis of drinking resolutions and shows that a systematic analysis of preresolution spending patterns aids in predicting moderation.

  1. Discriminative ability of commonly used indices to predict adverse outcomes after poster lumbar fusion: a comparison of demographics, ASA, the modified Charlson Comorbidity Index, and the modified Frailty Index.

    Science.gov (United States)

    Ondeck, Nathaniel T; Bohl, Daniel D; Bovonratwet, Patawut; McLynn, Ryan P; Cui, Jonathan J; Shultz, Blake N; Lukasiewicz, Adam M; Grauer, Jonathan N

    2018-01-01

    As research tools, the American Society of Anesthesiologists (ASA) physical status classification system, the modified Charlson Comorbidity Index (mCCI), and the modified Frailty Index (mFI) have been associated with complications following spine procedures. However, with respect to clinical use for various adverse outcomes, no known study has compared the predictive performance of these indices specifically following posterior lumbar fusion (PLF). This study aimed to compare the discriminative ability of ASA, mCCI, and mFI, as well as demographic factors including age, body mass index, and gender for perioperative adverse outcomes following PLF. A retrospective review of prospectively collected data was performed. Patients undergoing elective PLF with or without interbody fusion were extracted from the 2011-2014 American College of Surgeons National Surgical Quality Improvement Program (NSQIP). Perioperative adverse outcome variables assessed included the occurrence of minor adverse events, severe adverse events, infectious adverse events, any adverse event, extended length of hospital stay, and discharge to higher-level care. Patient comorbidity indices and characteristics were delineated and assessed for discriminative ability in predicting perioperative adverse outcomes using an area under the curve analysis from the receiver operating characteristics curves. In total, 16,495 patients were identified who met the inclusion criteria. The most predictive comorbidity index was ASA and demographic factor was age. Of these two factors, age had the larger discriminative ability for three out of the six adverse outcomes and ASA was the most predictive for one out of six adverse outcomes. A combination of the most predictive demographic factor and comorbidity index resulted in improvements in discriminative ability over the individual components for five of the six outcome variables. For PLF, easily obtained patient ASA and age have overall similar or better

  2. Changes in the Oswestry Disability Index that predict improvement after lumbar fusion.

    Science.gov (United States)

    Djurasovic, Mladen; Glassman, Steven D; Dimar, John R; Crawford, Charles H; Bratcher, Kelly R; Carreon, Leah Y

    2012-11-01

    Clinical studies use both disease-specific and generic health outcomes measures. Disease-specific measures focus on health domains most relevant to the clinical population, while generic measures assess overall health-related quality of life. There is little information about which domains of the Oswestry Disability Index (ODI) are most important in determining improvement in overall health-related quality of life, as measured by the 36-Item Short Form Health Survey (SF-36), after lumbar spinal fusion. The objective of the study is to determine which clinical elements assessed by the ODI most influence improvement of overall health-related quality of life. A single tertiary spine center database was used to identify patients undergoing lumbar fusion for standard degenerative indications. Patients with complete preoperative and 2-year outcomes measures were included. Pearson correlation was used to assess the relationship between improvement in each item of the ODI with improvement in the SF-36 physical component summary (PCS) score, as well as achievement of the SF-36 PCS minimum clinically important difference (MCID). Multivariate regression modeling was used to examine which items of the ODI best predicted achievement for the SF-36 PCS MCID. The effect size and standardized response mean were calculated for each of the items of the ODI. A total of 1104 patients met inclusion criteria (674 female and 430 male patients). The mean age at surgery was 57 years. All items of the ODI showed significant correlations with the change in SF-36 PCS score and achievement of MCID for the SF-36 PCS, but only pain intensity, walking, and social life had r values > 0.4 reflecting moderate correlation. These 3 variables were also the dimensions that were independent predictors of the SF-36 PCS, and they were the only dimensions that had effect sizes and standardized response means that were moderate to large. Of the health dimensions measured by the ODI, pain intensity, walking

  3. Inverse radiation problem of temperature distribution in one-dimensional isotropically scattering participating slab with variable refractive index

    International Nuclear Information System (INIS)

    Namjoo, A.; Sarvari, S.M. Hosseini; Behzadmehr, A.; Mansouri, S.H.

    2009-01-01

    In this paper, an inverse analysis is performed for estimation of source term distribution from the measured exit radiation intensities at the boundary surfaces in a one-dimensional absorbing, emitting and isotropically scattering medium between two parallel plates with variable refractive index. The variation of refractive index is assumed to be linear. The radiative transfer equation is solved by the constant quadrature discrete ordinate method. The inverse problem is formulated as an optimization problem for minimizing an objective function which is expressed as the sum of square deviations between measured and estimated exit radiation intensities at boundary surfaces. The conjugate gradient method is used to solve the inverse problem through an iterative procedure. The effects of various variables on source estimation are investigated such as type of source function, errors in the measured data and system parameters, gradient of refractive index across the medium, optical thickness, single scattering albedo and boundary emissivities. The results show that in the case of noisy input data, variation of system parameters may affect the inverse solution, especially at high error values in the measured data. The error in measured data plays more important role than the error in radiative system parameters except the refractive index distribution; however the accuracy of source estimation is very sensitive toward error in refractive index distribution. Therefore, refractive index distribution and measured exit intensities should be measured accurately with a limited error bound, in order to have an accurate estimation of source term in a graded index medium.

  4. Fecal Calprotectin is an Accurate Tool and Correlated to Seo Index in Prediction of Relapse in Iranian Patients With Ulcerative Colitis.

    Science.gov (United States)

    Hosseini, Seyed Vahid; Jafari, Peyman; Taghavi, Seyed Alireza; Safarpour, Ali Reza; Rezaianzadeh, Abbas; Moini, Maryam; Mehrabi, Manoosh

    2015-02-01

    The natural clinical course of Ulcerative Colitis (UC) is characterized by episodes of relapse and remission. Fecal Calprotectin (FC) is a relatively new marker of intestinal inflammation and is an available, non-expensive tool for predicting relapse of quiescent UC. The Seo colitis activity index is a clinical index for assessment of the severity of UC. The present study aimed to evaluate the accuracy of FC and the Seo colitis activity index and their correlation in prediction of UC exacerbation. In this prospective cohort study, 157 patients with clinical and endoscopic diagnosis of UC selected randomly from 1273 registered patients in Fars province's IBD registry center in Shiraz, Iran, were followed from October 2012 to October 2013 for 12 months or shorter, if they had a relapse. Two patients left the study before completion and one patient had relapse because of discontinuation of drugs. The participants' clinical and serum factors were evaluated every three months. Furthermore, stool samples were collected at the beginning of study and every three months and FC concentration (commercially available enzyme linked immunoassay) and the Seo Index were assessed. Then univariate analysis, multiple variable logistic regression, Receiver Operating Characteristics (ROC) curve analysis, and Pearson's correlation test (r) were used for statistical analysis of data. According to the results, 74 patients (48.1%) relapsed during the follow-up (33 men and 41 women). Mean ± SD of FC was 862.82 ± 655.97 μg/g and 163.19 ± 215.85 μg/g in relapsing and non-relapsing patients, respectively (P Seo index were significant predictors of relapse. ROC curve analysis of FC level and Seo activity index for prediction of relapse demonstrated area under the curve of 0.882 (P Seo index was significant in prediction of relapse (r = 0.63, P Seo activity index in prediction of relapse in the course of quiescent UC in Iranian patients.

  5. Emotionally Excited Eyeblink-Rate Variability Predicts an Experience of Transportation into the Narrative World

    Directory of Open Access Journals (Sweden)

    Ryota eNomura

    2015-04-01

    Full Text Available Collective spectator communications such as oral presentations, movies, and storytelling performances are ubiquitous in human culture. This study investigated the effects of past viewing experiences and differences in expressive performance on an audience’s transportive experience into a created world of a storytelling performance. In the experiment, 60 participants (mean age = 34.12 yrs., SD = 13.18 yrs., range 18–63 yrs. were assigned to watch one of two videotaped performances that were played (1 in an orthodox way for frequent viewers and (2 in a modified way aimed at easier comprehension for first-time viewers. Eyeblink synchronization among participants was quantified by employing distance-based measurements of spike trains, Dspike and Dinterval (Victor & Purpura, 1997. The results indicated that even non-familiar participants’ eyeblinks were synchronized as the story progressed and that the effect of the viewing experience on transportation was weak. Rather, the results of a multiple regression analysis demonstrated that the degrees of transportation could be predicted by a retrospectively reported humor experience and higher real-time variability (i.e., logarithmic transformed standard deviation of inter blink intervals during a performance viewing. The results are discussed from the viewpoint in which the extent of eyeblink synchronization and eyeblink-rate variability acts as an index of the inner experience of audience members.

  6. Appraisal and Reliability of Variable Engagement Model Prediction ...

    African Journals Online (AJOL)

    The variable engagement model based on the stress - crack opening displacement relationship and, which describes the behaviour of randomly oriented steel fibres composite subjected to uniaxial tension has been evaluated so as to determine the safety indices associated when the fibres are subjected to pullout and with ...

  7. Predicting Teacher Retention Using Stress and Support Variables

    Science.gov (United States)

    Sass, Daniel A.; Seal, Andrea K.; Martin, Nancy K.

    2011-01-01

    Purpose: Teacher attrition is a significant international concern facing administrators. Although a considerable amount of literature exists related to the causes of job dissatisfaction and teachers leaving the profession, relatively few theoretical models test the complex interrelationships between these variables. The goal of this paper is to…

  8. The role of socio demographic variables in predicting patients ...

    African Journals Online (AJOL)

    Background: Radiological examination remains a vital and integral aspect of health services delivery and patient satisfaction with radiological service remains beneficial both to patients and hospitals. Aim: To evaluate the influence of patient's socio demographic variables on satisfaction with radiological services. Subjects ...

  9. Prediction of clamp-derived insulin sensitivity from the oral glucose insulin sensitivity index

    DEFF Research Database (Denmark)

    Tura, Andrea; Chemello, Gaetano; Szendroedi, Julia

    2018-01-01

    that underwent both a clamp and an OGTT or meal test, thereby allowing calculation of both the M value and OGIS. The population was divided into a training and a validation cohort (n = 359 and n = 154, respectively). After a stepwise selection approach, the best model for M value prediction was applied......AIMS/HYPOTHESIS: The euglycaemic-hyperinsulinaemic clamp is the gold-standard method for measuring insulin sensitivity, but is less suitable for large clinical trials. Thus, several indices have been developed for evaluating insulin sensitivity from the oral glucose tolerance test (OGTT). However......, most of them yield values different from those obtained by the clamp method. The aim of this study was to develop a new index to predict clamp-derived insulin sensitivity (M value) from the OGTT-derived oral glucose insulin sensitivity index (OGIS). METHODS: We analysed datasets of people...

  10. Starch digestibility and predicted glycemic index of fried sweet potato cultivars

    Directory of Open Access Journals (Sweden)

    Amaka Odenigbo

    2012-07-01

    Full Text Available Background: Sweet potato (Ipomoea batatas L. is a very rich source of starch. There is increased interest in starch digestibility and the prevention and management of metabolic diseases.Objective: The aim of this study was to evaluate the levels of starch fractions and predicted glycemic index of different cultivars of sweet potato. Material and Method: French fries produced from five cultivars of sweet potato (‘Ginseng Red’, ‘Beauregard’, ‘White Travis’, ‘Georgia Jet clone #2010’ and ‘Georgia Jet’ were used. The level of total starch (TS, resistant starch (RS, digestible starch (DS, and starch digestion index starch digestion index in the samples were evaluated. In vitro starch hydrolysis at 30, 90, and 120 min were determined enzymatically for calculation of rapidly digestible starch (RDS, predicted glycemic index (pGI and slowly digestible starch (SDS respectively. Results: The RS content in all samples had an inversely significant correlation with pGI (-0.52; P<0.05 while RDS had positive and significant influence on both pGI (r=0.55; P<0.05 and SDI (r= 0.94; P<0.01. ‘White Travis’ and ‘Ginseng Red’ had higher levels of beneficial starch fractions (RS and SDS with low pGI and starch digestion Index (SDI, despite their higher TS content. Generally, all the cultivars had products with low to moderate GI values. Conclusion: The glycemic index of these food products highlights the health promoting characteristics of sweet potato cultivars.

  11. Chaos game representation of the D st index and prediction of geomagnetic storm events

    International Nuclear Information System (INIS)

    Yu, Z.G.; Anh, V.V.; Wanliss, J.A.; Watson, S.M.

    2007-01-01

    This paper proposes a two-dimensional chaos game representation (CGR) for the D st index. The CGR provides an effective method to characterize the multifractality of the D st time series. The probability measure of this representation is then modeled as a recurrent iterated function system in fractal theory, which leads to an algorithm for prediction of a storm event. We present an analysis and modeling of the D st time series over the period 1963-2003. The numerical results obtained indicate that the method is useful in predicting storm events one day ahead

  12. Child Support Payment: A Structural Model of Predictive Variables.

    Science.gov (United States)

    Wright, David W.; Price, Sharon J.

    A major area of concern in divorced families is compliance with child support payments. Aspects of the former spouse relationship that are predictive of compliance with court-ordered payment of child support were investigated in a sample of 58 divorced persons all of whom either paid or received child support. Structured interviews and…

  13. Variable input parameter influence on river corridor prediction

    NARCIS (Netherlands)

    Zerfu, T.; Beevers, L.; Crosato, A.; Wright, N.

    2015-01-01

    This paper considers the erodible river corridor, which is the area in which the main river channel is free to migrate over a period of time. Due to growing anthropogenic pressure, predicting the corridor width has become increasingly important for the planning of development along rivers. Several

  14. Novel Radiobiological Gamma Index for Evaluation of 3-Dimensional Predicted Dose Distribution

    Energy Technology Data Exchange (ETDEWEB)

    Sumida, Iori, E-mail: sumida@radonc.med.osaka-u.ac.jp [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Yamaguchi, Hajime; Kizaki, Hisao; Aboshi, Keiko; Tsujii, Mari; Yoshikawa, Nobuhiko; Yamada, Yuji [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan); Suzuki, Osamu; Seo, Yuji [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Isohashi, Fumiaki [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan); Yoshioka, Yasuo [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Ogawa, Kazuhiko [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan)

    2015-07-15

    Purpose: To propose a gamma index-based dose evaluation index that integrates the radiobiological parameters of tumor control (TCP) and normal tissue complication probabilities (NTCP). Methods and Materials: Fifteen prostate and head and neck (H&N) cancer patients received intensity modulated radiation therapy. Before treatment, patient-specific quality assurance was conducted via beam-by-beam analysis, and beam-specific dose error distributions were generated. The predicted 3-dimensional (3D) dose distribution was calculated by back-projection of relative dose error distribution per beam. A 3D gamma analysis of different organs (prostate: clinical [CTV] and planned target volumes [PTV], rectum, bladder, femoral heads; H&N: gross tumor volume [GTV], CTV, spinal cord, brain stem, both parotids) was performed using predicted and planned dose distributions under 2%/2 mm tolerance and physical gamma passing rate was calculated. TCP and NTCP values were calculated for voxels with physical gamma indices (PGI) >1. We propose a new radiobiological gamma index (RGI) to quantify the radiobiological effects of TCP and NTCP and calculate radiobiological gamma passing rates. Results: The mean RGI gamma passing rates for prostate cases were significantly different compared with those of PGI (P<.03–.001). The mean RGI gamma passing rates for H&N cases (except for GTV) were significantly different compared with those of PGI (P<.001). Differences in gamma passing rates between PGI and RGI were due to dose differences between the planned and predicted dose distributions. Radiobiological gamma distribution was visualized to identify areas where the dose was radiobiologically important. Conclusions: RGI was proposed to integrate radiobiological effects into PGI. This index would assist physicians and medical physicists not only in physical evaluations of treatment delivery accuracy, but also in clinical evaluations of predicted dose distribution.

  15. Contouring Variability of the Penile Bulb on CT Images: Quantitative Assessment Using a Generalized Concordance Index

    Energy Technology Data Exchange (ETDEWEB)

    Carillo, Viviana [Department of Medical Physics, San Raffaele Scientific Institute, Milano (Italy); Cozzarini, Cesare [Department of Radiotherapy, San Raffaele Scientific Institute, Milano (Italy); Perna, Lucia; Calandra, Mauro [Department of Medical Physics, San Raffaele Scientific Institute, Milano (Italy); Gianolini, Stefano [Medical Software Solutions GmbH, Hagendorn (Switzerland); Rancati, Tiziana [Prostate Cancer Program, IRCCS National Institute of Cancer, Milano (Italy); Spinelli, Antonello Enrico [Department of Medical Physics, San Raffaele Scientific Institute, Milano (Italy); Vavassori, Vittorio [Department of Radiotherapy, Cliniche Gavazzeni Humanitas, Bergamo (Italy); Villa, Sergio [Department of Radiotherapy 1, IRCCS National Institute of Cancer, Milano (Italy); Valdagni, Riccardo [Prostate Cancer Program, IRCCS National Institute of Cancer, Milano (Italy); Department of Radiotherapy 1, IRCCS National Institute of Cancer, Milano (Italy); Fiorino, Claudio, E-mail: fiorino.claudio@hsr.it [Department of Medical Physics, San Raffaele Scientific Institute, Milano (Italy)

    2012-11-01

    Purpose: Within a multicenter study (DUE-01) focused on the search of predictors of erectile dysfunction and urinary toxicity after radiotherapy for prostate cancer, a dummy run exercise on penile bulb (PB) contouring on computed tomography (CT) images was carried out. The aim of this study was to quantitatively assess interobserver contouring variability by the application of the generalized DICE index. Methods and Materials: Fifteen physicians from different Institutes drew the PB on CT images of 10 patients. The spread of DICE values was used to objectively select those observers who significantly disagreed with the others. The analyses were performed with a dedicated module in the VODCA software package. Results: DICE values were found to significantly change among observers and patients. The mean DICE value was 0.67, ranging between 0.43 and 0.80. The statistics of DICE coefficients identified 4 of 15 observers who systematically showed a value below the average (p value range, 0.013 - 0.059): Mean DICE values were 0.62 for the 4 'bad' observers compared to 0.69 of the 11 'good' observers. For all bad observers, the main cause of the disagreement was identified. Average DICE values were significantly worse from the average in 2 of 10 patients (0.60 vs. 0.70, p < 0.05) because of the limited visibility of the PB. Excluding the bad observers and the 'bad' patients,' the mean DICE value increased from 0.67 to 0.70; interobserver variability, expressed in terms of standard deviation of DICE spread, was also reduced. Conclusions: The obtained values of DICE around 0.7 shows an acceptable agreement, considered the small dimension of the PB. Additional strategies to improve this agreement are under consideration and include an additional tutorial of the so-called bad observers with a recontouring procedure, or the recontouring by a single observer of the PB for all patients included in the DUE-01 study.

  16. Contouring Variability of the Penile Bulb on CT Images: Quantitative Assessment Using a Generalized Concordance Index

    International Nuclear Information System (INIS)

    Carillo, Viviana; Cozzarini, Cesare; Perna, Lucia; Calandra, Mauro; Gianolini, Stefano; Rancati, Tiziana; Spinelli, Antonello Enrico; Vavassori, Vittorio; Villa, Sergio; Valdagni, Riccardo; Fiorino, Claudio

    2012-01-01

    Purpose: Within a multicenter study (DUE-01) focused on the search of predictors of erectile dysfunction and urinary toxicity after radiotherapy for prostate cancer, a dummy run exercise on penile bulb (PB) contouring on computed tomography (CT) images was carried out. The aim of this study was to quantitatively assess interobserver contouring variability by the application of the generalized DICE index. Methods and Materials: Fifteen physicians from different Institutes drew the PB on CT images of 10 patients. The spread of DICE values was used to objectively select those observers who significantly disagreed with the others. The analyses were performed with a dedicated module in the VODCA software package. Results: DICE values were found to significantly change among observers and patients. The mean DICE value was 0.67, ranging between 0.43 and 0.80. The statistics of DICE coefficients identified 4 of 15 observers who systematically showed a value below the average (p value range, 0.013 — 0.059): Mean DICE values were 0.62 for the 4 “bad” observers compared to 0.69 of the 11 “good” observers. For all bad observers, the main cause of the disagreement was identified. Average DICE values were significantly worse from the average in 2 of 10 patients (0.60 vs. 0.70, p < 0.05) because of the limited visibility of the PB. Excluding the bad observers and the “bad” patients,” the mean DICE value increased from 0.67 to 0.70; interobserver variability, expressed in terms of standard deviation of DICE spread, was also reduced. Conclusions: The obtained values of DICE around 0.7 shows an acceptable agreement, considered the small dimension of the PB. Additional strategies to improve this agreement are under consideration and include an additional tutorial of the so-called bad observers with a recontouring procedure, or the recontouring by a single observer of the PB for all patients included in the DUE-01 study.

  17. A Bimodel Algorithm with Data-Divider to Predict Stock Index

    Directory of Open Access Journals (Sweden)

    Zhaoyue Wang

    2018-01-01

    Full Text Available There is not yet reliable software for stock prediction, because most experts of this area have been trying to predict an exact stock index. Considering that the fluctuation of a stock index usually is no more than 1% in a day, the error between the forecasted and the actual values should be no more than 0.5%. It is too difficult to realize. However, forecasting whether a stock index will rise or fall does not need to be so exact a numerical value. A few scholars noted the fact, but their systems do not yet work very well because different periods of a stock have different inherent laws. So, we should not depend on a single model or a set of parameters to solve the problem. In this paper, we developed a data-divider to divide a set of historical stock data into two parts according to rising period and falling period, training, respectively, two neural networks optimized by a GA. Above all, the data-divider enables us to avoid the most difficult problem, the effect of unexpected news, which could hardly be predicted. Experiments show that the accuracy of our method increases 20% compared to those of traditional methods.

  18. Evaluating Variability and Uncertainty of Geological Strength Index at a Specific Site

    Science.gov (United States)

    Wang, Yu; Aladejare, Adeyemi Emman

    2016-09-01

    Geological Strength Index (GSI) is an important parameter for estimating rock mass properties. GSI can be estimated from quantitative GSI chart, as an alternative to the direct observational method which requires vast geological experience of rock. GSI chart was developed from past observations and engineering experience, with either empiricism or some theoretical simplifications. The GSI chart thereby contains model uncertainty which arises from its development. The presence of such model uncertainty affects the GSI estimated from GSI chart at a specific site; it is, therefore, imperative to quantify and incorporate the model uncertainty during GSI estimation from the GSI chart. A major challenge for quantifying the GSI chart model uncertainty is a lack of the original datasets that have been used to develop the GSI chart, since the GSI chart was developed from past experience without referring to specific datasets. This paper intends to tackle this problem by developing a Bayesian approach for quantifying the model uncertainty in GSI chart when using it to estimate GSI at a specific site. The model uncertainty in the GSI chart and the inherent spatial variability in GSI are modeled explicitly in the Bayesian approach. The Bayesian approach generates equivalent samples of GSI from the integrated knowledge of GSI chart, prior knowledge and observation data available from site investigation. Equations are derived for the Bayesian approach, and the proposed approach is illustrated using data from a drill and blast tunnel project. The proposed approach effectively tackles the problem of how to quantify the model uncertainty that arises from using GSI chart for characterization of site-specific GSI in a transparent manner.

  19. Impact of Hospital Variables on Case Mix Index as a Marker of Disease Severity

    Science.gov (United States)

    Mendez, Carmen M.; Harrington, Darrell W.; Christenson, Peter

    2014-01-01

    Abstract Case mix index (CMI) has become a standard indicator of hospital disease severity in the United States and internationally. However, CMI was designed to calculate hospital payments, not to track disease severity, and is highly dependent on documentation and coding accuracy. The authors evaluated whether CMI varied by characteristics affecting hospitals' disease severity (eg, trauma center or not). The authors also evaluated whether CMI was lower at public hospitals than private hospitals, given the diminished financial resources to support documentation enhancement at public hospitals. CMI data for a 14-year period from a large public database were analyzed longitudinally and cross-sectionally to define the impact of hospital variables on average CMI within and across hospital groups. Between 1996 and 2007, average CMI declined by 0.4% for public hospitals, while rising significantly for private for-profit (14%) and nonprofit (6%) hospitals. After the introduction of the Medicare Severity Diagnosis Related Group (MS-DRG) system in 2007, average CMI increased for all 3 hospital types but remained lowest in public vs. private for-profit or nonprofit hospitals (1.05 vs. 1.25 vs. 1.20; P<0.0001). By multivariate analysis, teaching hospitals, level 1 trauma centers, and larger hospitals had higher average CMI, consistent with a marker of disease severity, but only for private hospitals. Public hospitals had lower CMI across all subgroups. Although CMI had some characteristics of a disease severity marker, it was lower across all strata for public hospitals. Hence, caution is warranted when using CMI to adjust for disease severity across public vs. private hospitals. (Population Health Management 2014;17:28–34) PMID:23965045

  20. The prostate health index PHI predicts oncological outcome and biochemical recurrence after radical prostatectomy - analysis in 437 patients.

    Science.gov (United States)

    Maxeiner, Andreas; Kilic, Ergin; Matalon, Julia; Friedersdorff, Frank; Miller, Kurt; Jung, Klaus; Stephan, Carsten; Busch, Jonas

    2017-10-03

    The purpose of this study was to investigate the Prostate-Health-Index (PHI) for pathological outcome prediction following radical prostatectomy and also for biochemical recurrence prediction in comparison to established parameters such as Gleason-score, pathological tumor stage, resection status (R0/1) and prostate-specific antigen (PSA). Out of a cohort of 460 cases with preoperative PHI-measurements (World Health Organization calibration: Beckman Coulter Access-2-Immunoassay) between 2001 and 2014, 437 patients with complete follow up data were included. From these 437 patients, 87 (19.9%) developed a biochemical recurrence. Patient characteristics were compared by using chi-square test. Predictors were analyzed by multivariate adjusted logistic and Cox regression. The median follow up for a biochemical recurrence was 65 (range 3-161) months. PHI, PSA, [-2]proPSA, PHI- and PSA-density performed as significant variables (p PHI, PSA, %fPSA, [-2]proPSA, PHI- and PSA-density significantly discriminated between stages PHI. In biochemical recurrence prediction PHI, PSA, [-2]proPSA, PHI- and PSA-density were the strongest predictors. In conclusion, due to heterogeneity of time spans to biochemical recurrence, longer follow up periods are crucial. This study with a median follow up of more than 5 years, confirmed a clinical value for PHI as an independent biomarker essential for biochemical recurrence prediction.

  1. Prediction of default probability in banking industry using CAMELS index: A case study of Iranian banks

    Directory of Open Access Journals (Sweden)

    Mohammad Khodaei Valahzaghard

    2013-04-01

    Full Text Available This study examines the relationship between CAMELS index and default probability among 20 Iranian banks. The proposed study gathers the necessary information from their financial statements over the period 2005-2011. The study uses logistic regression along with Pearson correlation analysis to consider the relationship between default probability and six independent variables including capital adequacy, asset quality, management quality, earning quality, liquidity quality and sensitivity of market risk. The results indicate that there were no meaningful relationship between default probability and three independent variables including capital adequacy, asset quality and sensitivity of market risk. However, the results of our statistical tests support such relationship between default probability and three other variables including management quality, earning quality and liquidity quality.

  2. APPLICATILITY OF THE VISCERAL ADIPOSITY INDEX (VAI) IN THE PREDICTION OF THE COMPONENTS OF THE METABOLIC SYNDROME IN ELDERLY.

    Science.gov (United States)

    Goldani, Heloisa; Adami, Fernanda Scherer; Antunes, Maria Terezinha; Rosa, Luis Henrique; Fassina, Patrícia; Quevedo Grave, Magali Terezinha; Morelo Dal Bosco, Simone

    2015-10-01

    The nutritional assessment may detect a state of malnutrition, overweight and cardiometabolic risk in the elderly. Easy to apply instruments enable the identification of risk factors for cardiovascular diseases (CVD). to analyze the applicability of Visceral Adiposity Index (VAI) in the prediction of MS components in the elderly. cross-sectional study with 221 elderly at a mean age of 70.65 ± 7.34 years; 53.4% female and 46.4% male. Weight, height, waist circumference (WC), fasting glucose, triglycerides (TG), total cholesterol (TC), HDL cholesterol (HDL-C), LDL cholesterol (LDL-C), and blood pressure (BP), data was obtained, as well as information about lifestyle. There were calculated the Body Mass Index (BMI), the Waist-Hip Ratio (WHR), and the VAI. The adiposity measures were compared with the components of MS, and for the VAI there was determined the capability of predicting the occurrence of MS components. by analyzing the association among the biochemical and pressoric variables and MS components with the anthropometric indicators of obesity, there was a direct and significant correlation of the BMI, the weight and the VAI with blood glucose, HDL and TG (p. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

  3. An application of plot-scale NDVI in predicting carbon dioxide exchange and leaf area index in heterogeneous subarctic tundra

    Energy Technology Data Exchange (ETDEWEB)

    Dagg, J.; Lafleur, P.

    2010-07-01

    This paper reported on a study that examined the flow of carbon into and out of tundra ecosystems. It is necessary to accurately predict carbon dioxide (CO{sub 2}) exchange in the Tundra because of the impacts of climate change on carbon stored in permafrost. Understanding the relationships between the normalized difference vegetation index (NDVI) and vegetation and CO{sub 2} exchange may explain how small-scale variation in vegetation community extends to remotely sensed estimates of landscape characteristics. In this study, CO{sub 2} fluxes were measured with a portable chamber in a range of Tundra vegetation communities. Biomass and leaf area were measured with destructive harvest, and NDVI was obtained using a hand-held infrared camera. There was a weak correlation between NDVI and leaf area index in some vegetation communities, but a significant correlation between NDVI and biomass, including mosses. NDVI was found to be strongly related to photosynthetic activity and net CO{sub 2} uptake in all vegetation groups. However, NDVI related to ecosystem respiration only in wet sedge. It was concluded that at plot scale, the ability of NDVI to predict ecosystem properties and CO{sub 2} exchange in heterogeneous Tundra vegetation is variable.

  4. An application of plot-scale NDVI in predicting carbon dioxide exchange and leaf area index in heterogeneous subarctic tundra

    International Nuclear Information System (INIS)

    Dagg, J.; Lafleur, P.

    2010-01-01

    This paper reported on a study that examined the flow of carbon into and out of tundra ecosystems. It is necessary to accurately predict carbon dioxide (CO 2 ) exchange in the Tundra because of the impacts of climate change on carbon stored in permafrost. Understanding the relationships between the normalized difference vegetation index (NDVI) and vegetation and CO 2 exchange may explain how small-scale variation in vegetation community extends to remotely sensed estimates of landscape characteristics. In this study, CO 2 fluxes were measured with a portable chamber in a range of Tundra vegetation communities. Biomass and leaf area were measured with destructive harvest, and NDVI was obtained using a hand-held infrared camera. There was a weak correlation between NDVI and leaf area index in some vegetation communities, but a significant correlation between NDVI and biomass, including mosses. NDVI was found to be strongly related to photosynthetic activity and net CO 2 uptake in all vegetation groups. However, NDVI related to ecosystem respiration only in wet sedge. It was concluded that at plot scale, the ability of NDVI to predict ecosystem properties and CO 2 exchange in heterogeneous Tundra vegetation is variable.

  5. Accuracy of shock index versus ABC score to predict need for massive transfusion in trauma patients.

    Science.gov (United States)

    Schroll, Rebecca; Swift, David; Tatum, Danielle; Couch, Stuart; Heaney, Jiselle B; Llado-Farrulla, Monica; Zucker, Shana; Gill, Frances; Brown, Griffin; Buffin, Nicholas; Duchesne, Juan

    2018-01-01

    Various scoring systems have been developed to predict need for massive transfusion in traumatically injured patients. Assessments of Blood Consumption (ABC) score and Shock Index (SI) have been shown to be reliable predictors for Massive Transfusion Protocol (MTP) activation. However, no study has directly compared these two scoring systems to determine which is a better predictor for MTP activation. The primary objective was to determine whether ABC or SI better predicted the need for MTP in adult trauma patients with severe hemorrhage. This was a retrospective cohort study which included all injured patients who were trauma activations between January 1, 2009 and December 31, 2013 at an urban Level I trauma center. Patients ABC and SI were calculated for each patient. MTP was defined as need for >10 units PRBC transfusion within 24h of emergency department arrival. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were used to evaluate scoring systems' ability to predict effective MTP utilization. A total of 645 patients had complete data for analysis. Shock Index ≥1 had sensitivity of 67.7% (95% CI 49.5%-82.6%) and specificity of 81.3% (95% CI 78.0%-84.3%) for predicting MTP, and ABC score ≥2 had sensitivity of 47.0% (95% CI 29.8%-64.9%) and specificity of 89.8% (95% CI 87.2%-92.1%). AUROC analyses showed SI to be the strongest predictor followed by ABC score with AUROC values of 0.83 and 0.74, respectively. SI had a significantly greater sensitivity (P=0.035), but a significantly weaker specificity (PABC score. ABC score and Shock Index can both be used to predict need for massive transfusion in trauma patients, however SI is more sensitive and requires less technical skill than ABC score. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

    Science.gov (United States)

    Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

    2015-04-01

    Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for

  7. Index for Predicting Insurance Claims from Wind Storms with an Application in France.

    Science.gov (United States)

    Mornet, Alexandre; Opitz, Thomas; Luzi, Michel; Loisel, Stéphane

    2015-11-01

    For insurance companies, wind storms represent a main source of volatility, leading to potentially huge aggregated claim amounts. In this article, we compare different constructions of a storm index allowing us to assess the economic impact of storms on an insurance portfolio by exploiting information from historical wind speed data. Contrary to historical insurance portfolio data, meteorological variables show fewer nonstationarities between years and are easily available with long observation records; hence, they represent a valuable source of additional information for insurers if the relation between observations of claims and wind speeds can be revealed. Since standard correlation measures between raw wind speeds and insurance claims are weak, a storm index focusing on high wind speeds can afford better information. A storm index approach has been applied to yearly aggregated claim amounts in Germany with promising results. Using historical meteorological and insurance data, we assess the consistency of the proposed index constructions with respect to various parameters and weights. Moreover, we are able to place the major insurance events since 1998 on a broader horizon beyond 40 years. Our approach provides a meteorological justification for calculating the return periods of extreme-storm-related insurance events whose magnitude has rarely been reached. © 2015 Society for Risk Analysis.

  8. Contact parameter identification for vibrational response variability prediction

    DEFF Research Database (Denmark)

    Creixell Mediante, Ester; Brunskog, Jonas; Jensen, Jakob Søndergaard

    2018-01-01

    industry, where the vibrational behavior of the structures within the hearing frequency range is critical for the performance of the devices. A procedure to localize the most probable contact areas and determine the most sensitive contact points with respect to variations in the modes of vibration......Variability in the dynamic response of assembled structures can arise due to variations in the contact conditions between the parts that conform them. Contact conditions are difficult to model accurately due to randomness in physical properties such as contact surface, load distribution...... or geometric details. Those properties can vary for a given structure due to the assembly and disassembly process, and also across nominally equal items that are produced in series. This work focuses on modeling the contact between small light-weight plastic pieces such as those used in the hearing aid...

  9. Physical attraction to reliable, low variability nervous systems: Reaction time variability predicts attractiveness.

    Science.gov (United States)

    Butler, Emily E; Saville, Christopher W N; Ward, Robert; Ramsey, Richard

    2017-01-01

    The human face cues a range of important fitness information, which guides mate selection towards desirable others. Given humans' high investment in the central nervous system (CNS), cues to CNS function should be especially important in social selection. We tested if facial attractiveness preferences are sensitive to the reliability of human nervous system function. Several decades of research suggest an operational measure for CNS reliability is reaction time variability, which is measured by standard deviation of reaction times across trials. Across two experiments, we show that low reaction time variability is associated with facial attractiveness. Moreover, variability in performance made a unique contribution to attractiveness judgements above and beyond both physical health and sex-typicality judgements, which have previously been associated with perceptions of attractiveness. In a third experiment, we empirically estimated the distribution of attractiveness preferences expected by chance and show that the size and direction of our results in Experiments 1 and 2 are statistically unlikely without reference to reaction time variability. We conclude that an operating characteristic of the human nervous system, reliability of information processing, is signalled to others through facial appearance. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. [Reliability of the PROFUND index to predict 4-year mortality in polypathological patients].

    Science.gov (United States)

    Díez-Manglano, Jesús; Del Corral Beamonte, Esther; Ramos Ibáñez, Rosa; Lambán Aranda, María Pilar; Toyas Miazza, Carla; Rodero Roldán, María Del Mar; Ortiz Domingo, Concepción; Munilla López, Eulalia; de Escalante Yangüela, Begoña

    2016-09-16

    To determine the usefullness of the PROFUND index to assess the risk of global death after 4 years in polypathological patients. Multicenter prospective cohort (Internal Medicine and Geriatrics) study. Polypathological patients admitted between March 1st and June 30th 2011 were included. For each patient, data concerning age, sex, living at home or in a nursing residence, polypathology categories, Charlson, Barthel and Lawton-Brody indexes, Pfeiffer questionnaire, socio-familial Gijon scale, delirium, number of drugs, hemoglobin and creatinine values were gathered, and the PROFUND index was calculated. The follow-up lasted 4 years. We included 441 patients, 324 from Internal Medicine and 117 from Geriatrics, with a mean age of 80.9 (8.7) years. Of them, 245 (55.6%) were women. Heart (62.7%), neurological (41.4%) and respiratory (37.3%) diseases were the most frequent. Geriatrics inpatients were older and more dependants and presented greater cognitive deterioration. After 4 years, 335 (76%) patients died. Mortality was associated with age, dyspnoea, Barthel index<60, delirium, advanced neoplasia and≥4 admissions in the last year. The area under the curve of the PROFUND index was 0.748, 95% CI 0.689-0.806, P<.001 in Internal Medicine and 0.517, 95% CI 0.369-0.666, P=.818 in Geriatrics patients, respectively. The PROFUND index is a reliable tool for predicting long-term global mortality in polypathological patients from Internal Medicine but not from Geriatrics departments. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

  11. Index to Predict In-hospital Mortality in Older Adults after Non-traumatic Emergency Department Intubations

    Directory of Open Access Journals (Sweden)

    Kei Ouchi

    2017-04-01

    Full Text Available Introduction: Our goal was to develop and validate an index to predict in-hospital mortality in older adults after non-traumatic emergency department (ED intubations. Methods: We used Vizient administrative data from hospitalizations of 22,374 adults ≥75 years who underwent non-traumatic ED intubation from 2008–2015 at nearly 300 U.S. hospitals to develop and validate an index to predict in-hospital mortality. We randomly selected one half of participants for the development cohort and one half for the validation cohort. Considering 25 potential predictors, we developed a multivariable logistic regression model using least absolute shrinkage and selection operator method to determine factors associated with in-hospital mortality. We calculated risk scores using points derived from the final model’s beta coefficients. To evaluate calibration and discrimination of the final model, we used Hosmer-Lemeshow chi-square test and receiver-operating characteristic analysis and compared mortality by risk groups in the development and validation cohorts. Results: Death during the index hospitalization occurred in 40% of cases. The final model included six variables: history of myocardial infarction, history of cerebrovascular disease, history of metastatic cancer, age, admission diagnosis of sepsis, and admission diagnosis of stroke/ intracranial hemorrhage. Those with low-risk scores (10 had 58% risk of in-hospital mortality. The Hosmer-Lemeshow chi-square of the model was 6.47 (p=0.09, and the c-statistic was 0.62 in the validation cohort. Conclusion: The model may be useful in identifying older adults at high risk of death after ED intubation.

  12. Wetland habitat disturbance best predicts metrics of an amphibian index of biotic integrity

    Science.gov (United States)

    Stapanian, Martin A.; Micacchion, Mick; Adams, Jean V.

    2015-01-01

    Regression and classification trees were used to identify the best predictors of the five component metrics of the Ohio Amphibian Index of Biotic Integrity (AmphIBI) in 54 wetlands in Ohio, USA. Of the 17 wetland- and surrounding landscape-scale variables considered, the best predictor for all AmphIBI metrics was habitat alteration and development within the wetland. The results were qualitatively similar to the best predictors for a wetland vegetation index of biotic integrity, suggesting that similar management practices (e.g., reducing or eliminating nutrient enrichment from agriculture, mowing, grazing, logging, and removing down woody debris) within the boundaries of the wetland can be applied to effectively increase the quality of wetland vegetation and amphibian communities.

  13. Starch digestibility and predicted glycemic index in the bread fortified with pomelo (Citrus maxima) fruit segments.

    Science.gov (United States)

    Reshmi, S K; Sudha, M L; Shashirekha, M N

    2017-12-15

    The aim of this study was to evaluate the starch digestibility and predicted glycemic index in breads incorporated with pomelo fruit (Citrus maxima) segments. Volume of the white and brown breads supplemented with pomelo fresh segments increased, while the crumb firmness decreased. Bread with 20% fresh and 5% dry pomelo segments were sensorily acceptable. Bioactive components such as phenolics, flavonoids, naringin and carotenoids were retained to a greater extent in bread containing dry pomelo segments. The pomelo incorporated bread had higher levels of resistant starch fractions (3.87-10.96%) with low predicted glycemic index (62.97-53.13%), despite their higher total starch (69.87-75.47%) content compared to control bread. Thus pomelo segments in the product formulations lowered the glycemic index probably by inhibiting carbohydrate hydrolyzing enzyme activity which could be attributed to naringin. Hence fortified bread prepared from pomelo fruit segment is recommended to gain nutritional value and to decrease the risk of diabetes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Screening for Sleep Apnoea in Mild Cognitive Impairment: The Utility of the Multivariable Apnoea Prediction Index

    Directory of Open Access Journals (Sweden)

    Georgina Wilson

    2014-01-01

    Full Text Available Purpose. Mild cognitive impairment (MCI is considered an “at risk” state for dementia and efforts are needed to target modifiable risk factors, of which Obstructive sleep apnoea (OSA is one. This study aims to evaluate the predictive utility of the multivariate apnoea prediction index (MAPI, a patient self-report survey, to assess OSA in MCI. Methods. Thirty-seven participants with MCI and 37 age-matched controls completed the MAPI and underwent polysomnography (PSG. Correlations were used to compare the MAPI and PSG measures including oxygen desaturation index and apnoea-hypopnoea index (AHI. Receiver-operating characteristics (ROC curve analyses were performed using various cut-off scores for apnoea severity. Results. In controls, there was a significant moderate correlation between higher MAPI scores and more severe apnoea (AHI: r=0.47, P=0.017. However, this relationship was not significant in the MCI sample. ROC curve analysis indicated much lower area under the curve (AUC in the MCI sample compared to the controls across all AHI severity cut-off scores. Conclusions. In older people, the MAPI moderately correlates with AHI severity but only in those who are cognitively intact. Development of further screening tools is required in order to accurately screen for OSA in MCI.

  15. Relationship between depression with FEV1 percent predicted and BODE index in chronic obstructive pulmonary disease

    Science.gov (United States)

    Gunawan, H.; Hanum, H.; Abidin, A.; Hanida, W.

    2018-03-01

    WHO reported more than 3 million people die from COPD in 2012 and are expected to rank third after cardiovascular and cancer diseases in the future. Recent studies reported the prevalence of depression in COPD patients was higher than in control group. So, it’s important for clinicians to understand the relationship of depression symptoms with clinical aspects of COPD. For determining the association of depression symptoms with lung function and BODE index in patients with stable COPD, a cross-sectional study was in 98 stable COPD outpatients from January to June 2017. Data were analyzed using Independent t-test, Mann-Whitney test, and Spearman’s rank correlation. COPD patients with depression had higher mMRC scores, and lower FEV1 percent predicted, and then 6-Minutes Walk Test compared to those without depression. There was a moderate strength of correlation (r=-0.43) between depression symptoms and FEV1 percent predicted, and strong correlation (r=0.614) between depression symptoms and BODE index. It indicates that BODE index is more accurate to describe symptoms of depression in COPD patients.

  16. Development of a risk index for the prediction of chronic post-surgical pain.

    Science.gov (United States)

    Althaus, A; Hinrichs-Rocker, A; Chapman, R; Arránz Becker, O; Lefering, R; Simanski, C; Weber, F; Moser, K-H; Joppich, R; Trojan, S; Gutzeit, N; Neugebauer, E

    2012-07-01

    The incidence of chronic post-surgical pain (CPSP) after various common operations is 10% to 50%. Identification of patients at risk of developing chronic pain, and the management and prevention of CPSP remains inadequate. The aim of this study was to develop an easily applicable risk index for the detection of high-risk patients that takes into account the multifactorial aetiology of CPSP. A comprehensive item pool was derived from a systematic literature search. Items that turned out significant in bivariate analyses were then analysed multivariately, using logistic regression analyses. The items that yielded significant predictors in the multivariate analyses were compiled into an index. The cut-off score for a high risk of developing CPSP with an optimal trade-off between sensitivity and specificity was identified. The data of 150 patients who underwent different types of surgery were included in the analyses. Six months after surgery, 43.3% of the patients reported CPSP. Five predictors multivariately contributed to the prediction of CPSP: capacity overload, preoperative pain in the operating field, other chronic preoperative pain, post-surgical acute pain and co-morbid stress symptoms. These results suggest that several easily assessable preoperative and perioperative patient characteristics can predict a patient's risk of developing CPSP. The risk index may help caregivers to tailor individual pain management and to assist high-risk patients with pain coping. © 2011 European Federation of International Association for the Study of Pain Chapters.

  17. Evaluating climate variables, indexes and thresholds governing Arctic urban sustainability: case study of Russian permafrost regions

    Science.gov (United States)

    Anisimov, O. A.; Kokorev, V.

    2013-12-01

    Addressing Arctic urban sustainability today forces planners to deal with the complex interplay of multiple factors, including governance and economic development, demography and migration, environmental changes and land use, changes in the ecosystems and their services, and climate change. While the latter can be seen as a factor that exacerbates the existing vulnerabilities to other stressors, changes in temperature, precipitation, snow, river and lake ice, and the hydrological regime also have direct implications for the cities in the North. Climate change leads to reduced demand for heating energy, on one hand, and heightened concerns about the fate of the infrastructure built upon thawing permafrost, on the other. Changes in snowfall are particularly important and have direct implications for the urban economy, as together with heating costs, expenses for snow removal from streets, airport runways, roofs and ventilation corridors underneath buildings erected on pile foundations on permafrost constitute the bulk of the city's maintenance budget. Many cities are located in river valleys and are prone to flooding that leads to enormous economic losses and casualties, including human deaths. The severity of the northern climate has direct implications for demographic changes governed by regional migration and labor flows. Climate could thus be viewed as an inexhaustible public resource that creates opportunities for sustainable urban development. Long-term trends show that climate as a resource is becoming more readily available in the Russian North, notwithstanding the general perception that globally climate change is one of the challenges facing humanity in the 21st century. In this study we explore the sustainability of the Arctic urban environment under changing climatic conditions. We identify key governing variables and indexes and study the thresholds beyond which changes in the governing climatic parameters have significant impact on the economy

  18. Review of some advances of the literature about predictive variables concerning subjective well-being

    Directory of Open Access Journals (Sweden)

    Gloria Cajiao

    2013-06-01

    Full Text Available This review of scientific literature presents some tendencies, conceptual advances, empirical findings and tests that measure the predictive variables of subjective well-being. It was done through the search in bibliographical database like ProQuest, PsycArticles, Psyctest, OVID SP, books and Thesis. Two types of predictive variables were recognized- internal and external to the individual-. Both of them influence the achievement of the subjective well-being. Besides, the studies and conceptualization about Subjetive well-being and some of the Predictive Variables were analyzed in the conclusion.

  19. Model Predictive Control of a Nonlinear System with Known Scheduling Variable

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2012-01-01

    Model predictive control (MPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Consequently...... the control problem of the nonlinear system is simplied into a quadratic programming. Wind turbine is chosen as the case study and we choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....

  20. Leg pain and psychological variables predict outcome 2-3 years after lumbar fusion surgery.

    Science.gov (United States)

    Abbott, Allan D; Tyni-Lenné, Raija; Hedlund, Rune

    2011-10-01

    Prediction studies testing a thorough range of psychological variables in addition to demographic, work-related and clinical variables are lacking in lumbar fusion surgery research. This prospective cohort study aimed at examining predictions of functional disability, back pain and health-related quality of life (HRQOL) 2-3 years after lumbar fusion by regressing nonlinear relations in a multivariate predictive model of pre-surgical variables. Before and 2-3 years after lumbar fusion surgery, patients completed measures investigating demographics, work-related variables, clinical variables, functional self-efficacy, outcome expectancy, fear of movement/(re)injury, mental health and pain coping. Categorical regression with optimal scaling transformation, elastic net regularization and bootstrapping were used to investigate predictor variables and address predictive model validity. The most parsimonious and stable subset of pre-surgical predictor variables explained 41.6, 36.0 and 25.6% of the variance in functional disability, back pain intensity and HRQOL 2-3 years after lumbar fusion. Pre-surgical control over pain significantly predicted functional disability and HRQOL. Pre-surgical catastrophizing and leg pain intensity significantly predicted functional disability and back pain while the pre-surgical straight leg raise significantly predicted back pain. Post-operative psychomotor therapy also significantly predicted functional disability while pre-surgical outcome expectations significantly predicted HRQOL. For the median dichotomised classification of functional disability, back pain intensity and HRQOL levels 2-3 years post-surgery, the discriminative ability of the prediction models was of good quality. The results demonstrate the importance of pre-surgical psychological factors, leg pain intensity, straight leg raise and post-operative psychomotor therapy in the predictions of functional disability, back pain and HRQOL-related outcomes.

  1. Importance of the macroeconomic variables for variance prediction: A GARCH-MIDAS approach

    DEFF Research Database (Denmark)

    Asgharian, Hossein; Hou, Ai Jun; Javed, Farrukh

    2013-01-01

    This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long-term compone......This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long...

  2. A simplified donor risk index for predicting outcome after deceased donor kidney transplantation.

    Science.gov (United States)

    Watson, Christopher J E; Johnson, Rachel J; Birch, Rhiannon; Collett, Dave; Bradley, J Andrew

    2012-02-15

    We sought to determine the deceased donor factors associated with outcome after kidney transplantation and to develop a clinically applicable Kidney Donor Risk Index. Data from the UK Transplant Registry on 7620 adult recipients of adult deceased donor kidney transplants between 2000 and 2007 inclusive were analyzed. Donor factors potentially influencing transplant outcome were investigated using Cox regression, adjusting for significant recipient and transplant factors. A United Kingdom Kidney Donor Risk Index was derived from the model and validated. Donor age was the most significant factor predicting poor transplant outcome (hazard ratio for 18-39 and 60+ years relative to 40-59 years was 0.78 and 1.49, respectively, Pinformed consent.

  3. Modeling Chronic Toxicity: A Comparison of Experimental Variability With (QSAR/Read-Across Predictions

    Directory of Open Access Journals (Sweden)

    Christoph Helma

    2018-04-01

    Full Text Available This study compares the accuracy of (QSAR/read-across predictions with the experimental variability of chronic lowest-observed-adverse-effect levels (LOAELs from in vivo experiments. We could demonstrate that predictions of the lazy structure-activity relationships (lazar algorithm within the applicability domain of the training data have the same variability as the experimental training data. Predictions with a lower similarity threshold (i.e., a larger distance from the applicability domain are also significantly better than random guessing, but the errors to be expected are higher and a manual inspection of prediction results is highly recommended.

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

    Science.gov (United States)

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

    2016-01-01

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

  5. A combination of compositional index and genetic algorithm for predicting transmembrane helical segments.

    Directory of Open Access Journals (Sweden)

    Nazar Zaki

    Full Text Available Transmembrane helix (TMH topology prediction is becoming a focal problem in bioinformatics because the structure of TM proteins is difficult to determine using experimental methods. Therefore, methods that can computationally predict the topology of helical membrane proteins are highly desirable. In this paper we introduce TMHindex, a method for detecting TMH segments using only the amino acid sequence information. Each amino acid in a protein sequence is represented by a Compositional Index, which is deduced from a combination of the difference in amino acid occurrences in TMH and non-TMH segments in training protein sequences and the amino acid composition information. Furthermore, a genetic algorithm was employed to find the optimal threshold value for the separation of TMH segments from non-TMH segments. The method successfully predicted 376 out of the 378 TMH segments in a dataset consisting of 70 test protein sequences. The sensitivity and specificity for classifying each amino acid in every protein sequence in the dataset was 0.901 and 0.865, respectively. To assess the generality of TMHindex, we also tested the approach on another standard 73-protein 3D helix dataset. TMHindex correctly predicted 91.8% of proteins based on TM segments. The level of the accuracy achieved using TMHindex in comparison to other recent approaches for predicting the topology of TM proteins is a strong argument in favor of our proposed method.The datasets, software together with supplementary materials are available at: http://faculty.uaeu.ac.ae/nzaki/TMHindex.htm.

  6. GIS Based Distributed Runoff Predictions in Variable Source Area Watersheds Employing the SCS-Curve Number

    Science.gov (United States)

    Steenhuis, T. S.; Mendoza, G.; Lyon, S. W.; Gerard Marchant, P.; Walter, M. T.; Schneiderman, E.

    2003-04-01

    Because the traditional Soil Conservation Service Curve Number (SCS-CN) approach continues to be ubiquitously used in GIS-BASED water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed within an integrated GIS modeling environment a distributed approach for applying the traditional SCS-CN equation to watersheds where VSA hydrology is a dominant process. Spatial representation of hydrologic processes is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non-point source pollution. The methodology presented here uses the traditional SCS-CN method to predict runoff volume and spatial extent of saturated areas and uses a topographic index to distribute runoff source areas through watersheds. The resulting distributed CN-VSA method was incorporated in an existing GWLF water quality model and applied to sub-watersheds of the Delaware basin in the Catskill Mountains region of New York State. We found that the distributed CN-VSA approach provided a physically-based method that gives realistic results for watersheds with VSA hydrology.

  7. Higher resting heart rate variability predicts skill in expressing some emotions.

    Science.gov (United States)

    Tuck, Natalie L; Grant, Rosemary C I; Sollers, John J; Booth, Roger J; Consedine, Nathan S

    2016-12-01

    Vagally mediated heart rate variability (vmHRV) is a measure of cardiac vagal tone, and is widely viewed as a physiological index of the capacity to regulate emotions. However, studies have not directly tested whether vmHRV is associated with the ability to facially express emotions. In extending prior work, the current report tested links between resting vmHRV and the objectively assessed ability to facially express emotions, hypothesizing that higher vmHRV would predict greater expressive skill. Eighty healthy women completed self-reported measures, before attending a laboratory session in which vmHRV and the ability to express six emotions in the face were assessed. A repeated measures analysis of variance revealed a marginal main effect for vmHRV on skill overall; individuals with higher resting vmHRV were only better able to deliberately facially express anger and interest. Findings suggest that differences in resting vmHRV are associated with the objectively assessed ability to facially express some, but not all, emotions, with potential implications for health and well-being. © 2016 Society for Psychophysiological Research.

  8. Analysis of variability and predictability challenges of wind and solar power

    NARCIS (Netherlands)

    Haan, de J.E.S.; Virag, A.; Kling, W.L.

    2013-01-01

    In power systems, reserves are essential to ensure system security, certainly when challenges of predictability (inaccurate forecast) and variability (imperfect correlation of renewable generation and system load) are causing power imbalances. Different techniques can be used to size and allocate

  9. Pre-operative Tei Index does not predict left ventricular function immediately after mitral valve repair

    Directory of Open Access Journals (Sweden)

    Chirojit Mukherjee

    2012-01-01

    Full Text Available Echocardiographic assessment of systolic left ventricular (LV function in patients with severe mitral regurgitation (MR undergoing mitral valve (MV repair can be challenging because the measurement of ejection fraction (EF or fractional area change (FAC in pathological states is of questionable value. The aim of our study was to evaluate the usefulness of the pre-operative Tei Index in predicting left ventricular EF or FAC immediately after MV repair. One hundred and thirty patients undergoing MV repair with sinus rhythm pre- and post-operatively were enrolled in this prospective study. Twenty-six patients were excluded due to absence of sinus rhythm post-operatively. Standard transesophageal examination(IE 33,Philips,Netherlands was performed before and after cardiopulmonary bypass according to the guidelines of the ASE/SCA. FAC was determined in the transgastric midpapillary short-axis view. LV EF was measured in the midesophageal four- and two-chamber view. For calculation of the Tei Index, the deep transgastric and the midesophageal four-chamber view were used. Statistical analysis was performed with SPSS 17.0. values are expressed as mean with standard deviation. LV FAC and EF decreased significantly after MV repair (FAC: 56±12% vs. 50±14%, P<0.001; EF: 58±11 vs. 50±12Έ P<0.001. The Tei Index decreased from 0.66±0.23 before MV repair to 0.41±0.19 afterwards (P<0.001. No relationship between pre-operative Tei Index and post-operative FAC or post-operative EF were found (FAC: r=−0.061, P=0.554; EF: r=−0.29, P=0.771. Conclusion: Pre-operative Tei Index is not a good predictor for post-operative FAC and EF in patients undergoing MV repair.

  10. The Predictive Value of the Foot Posture Index on Dynamic Function

    DEFF Research Database (Denmark)

    Mølgaard, Carsten Møller; Olesen Gammelgaard, Christian; Nielsen, R. G.

    2008-01-01

    Keenan et. al. identified the six-item version of the Foot Posture Index (FPI) as a valid, simple and clinically useful tool. The model combines measures of the standing foot posture in multiple planes and anatomical segments. It provides an alternative to existing static clinical measures when...... dynamic measures are not feasible. Redmond et. al. found the model able to predict 41% of the variation in the complex rotation of the ankle joint, representing inversion/eversion, during midstance of walking. To our knowledge no studies have been published on the relationship between FPI and the movement...

  11. Transvaginal cervical length and amniotic fluid index: can it predict delivery latency following preterm premature rupture of membranes?

    Science.gov (United States)

    Mehra, Suwan; Amon, Erol; Hopkins, Sarah; Gavard, Jeffrey A; Shyken, Jaye

    2015-03-01

    We sought to determine whether transvaginal cervical length (TVCL), amniotic fluid index (AFI), or a combination of both can predict delivery latency within 7 days in women presenting with preterm premature rupture of membranes (PPROM). This was a prospective observational study of TVCL measurements in 106 singleton pregnancies with PPROM between 23-33 weeks. Delivery latency was defined as the period (in days) from the initial TVCL after PPROM to delivery of the infant, with our primary outcome being delivery within 7 days of TVCL. The independent predictability of significant characteristics for delivery within 7 days was determined using multiple logistic regression. Sensitivity, specificity, and predictive values were used to examine whether the presence of a short TVCL, AFI, or a combination of both affected the risk of delivery within 7 days. Delivery within 7 days occurred in 51/106 (48%) of pregnancies. Median duration (interquartile range) from PPROM to delivery and TVCL to delivery was 8 days (4.0-16.0) and 8 days (3.0-15.0), respectively. Using multiple regression TVCL as a continuous variable (odds ratio, 0.65; 95% confidence interval, 0.44-0.97; P 7 days for TVCL >2 cm alone was 61%. This predictive value changed when analyzed in conjunction with an AFI ≤5 cm and >5 cm at 42% and 89%, respectively. A shorter TVCL and an AFI ≤5 cm independently predict delivery within 7 days in women presenting with PPROM. The combination of an AFI >5 cm and TVCL >2 cm greatly improved the potential to remain undelivered at 7 days following cervical length assessment. These findings may be helpful for counseling and optimizing maternal and neonatal care in women with PPROM. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Efficacy of the Omega-3 Index in predicting non-alcoholic fatty liver disease in overweight and obese adults: a pilot study.

    Science.gov (United States)

    Parker, Helen M; O'Connor, Helen T; Keating, Shelley E; Cohn, Jeffrey S; Garg, Manohar L; Caterson, Ian D; George, Jacob; Johnson, Nathan A

    2015-09-14

    Non-alcoholic fatty liver disease (NAFLD) is an independent predictor of CVD in otherwise healthy individuals. Low n-3 PUFA intake has been associated with the presence of NAFLD; however, the relationship between a biomarker of n-3 status - the Omega-3 Index - and liver fat is yet to be elucidated. A total of eighty overweight adults (fifty-six men) completed the anthropometric and biochemical measurements, including the Omega-3 Index, and underwent proton magnetic resonance spectroscopy assessment of liver fat. Bivariate correlations and multiple regression analyses were performed with reference to prediction of liver fat percentage. The mean Omega-3 Index was high in both NAFLD (intrahepatic lipid concentration≥5·5 %) and non-NAFLD groups. The Omega-3 Index, BMI, waist circumference, glucose, insulin, TAG, high-sensitive C-reactive protein (hsCRP) and alanine aminotransferase (ALT) were positively correlated, and HDL and erythrocyte n-6:n-3 ratio negatively correlated with liver fat concentration. Regression analysis found that simple anthropometric and demographic variables (waist, age) accounted for 31 % of the variance in liver fat and the addition of traditional cardiometabolic blood markers (TAG, HDL, hsCRP and ALT) increased the predictive power to 43 %. The addition of the novel erythrocyte fatty acid variable (Omega-3 Index) to the model only accounted for a further 3 % of the variance (P=0·049). In conclusion, the Omega-3 Index was associated with liver fat concentration but did not improve the overall capacity of demographic, anthropometric and blood markers to predict NAFLD.

  13. Properties of power series of analytic in a bidisc functions of bounded $\\mathbf{L}$-index in joint variables

    Directory of Open Access Journals (Sweden)

    A. I. Bandura

    2017-07-01

    Full Text Available We generalized some criteria of boundedness of $\\mathbf{L}$-index in joint variables for analytic in a bidisc functions, where $\\mathbf{L}(z=(l_1(z_1,z_2,$ $l_{2}(z_1,z_2,$ $l_j:\\mathbb{D}^2\\to \\mathbb{R}_+$ is a continuous function, $j\\in\\{1,2\\},$ $\\mathbb{D}^2$ is a bidisc $\\{(z_1,z_2\\in\\mathbb{C}^2: |z_1|<1,|z_2|<1\\}.$ The propositions describe a behaviour of power series expansion on a skeleton of a bidisc. We estimated power series expansion by a dominating homogeneous polynomial with the degree that does not exceed some number depending only from radii of bidisc. Replacing universal quantifier by existential quantifier for radii of bidisc, we also proved sufficient conditions of boundedness of $\\mathbf{L}$-index in joint variables for analytic functions which are weaker than necessary conditions.

  14. Perceived exertion is as effective as the perceptual strain index in predicting physiological strain when wearing personal protective clothing.

    Science.gov (United States)

    Borg, David N; Costello, Joseph T; Bach, Aaron J; Stewart, Ian B

    2017-02-01

    The perceptual strain index (PeSI) has been shown to overcome the limitations associated with the assessment of the physiological strain index (PSI), primarily the need to obtain a core body temperature measurement. The PeSI uses the subjective scales of thermal sensation and perceived exertion (RPE) to provide surrogate measures of core temperature and heart rate, respectively. Unfortunately, thermal sensation has shown large variability in providing an estimation of core body temperature. Therefore, the primary aim of this study was to determine if thermal comfort improved the ability of the PeSI to predict the PSI during exertional-heat stress. Eighteen healthy males (age: 23.5years; body mass: 79.4kg; maximal aerobic capacity: 57.2ml·kg -1 ·min -1 ) wore four different chemical/biological protective garments while walking on treadmill at a low (temperatures 21, 30 or 37°C. Trials were terminated when heart rate exceeded 90% of maximum, when core body temperature reached 39°C, at 120min or due to volitional fatigue. Core body temperature, heart rate, thermal sensation, thermal comfort and RPE were recorded at 15min intervals and at termination. Multiple statistical methods were used to determine the most accurate perceptual predictor. Significant moderate relationships were observed between the PeSI (r=0.74; pestimate physiological strain during exertional-heat stress under these work conditions. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Do Assault-Related Variables Predict Response to Cognitive Behavioral Treatment for PTSD?

    Science.gov (United States)

    Hembree, Elizabeth A.; Street, Gordon P.; Riggs, David S.; Foa, Edna B.

    2004-01-01

    This study examined the hypothesis that variables such as history of prior trauma, assault severity, and type of assault, previously found to be associated with natural recovery, would also predict treatment outcome. Trauma-related variables were examined as predictors of posttreatment posttraumatic stress disorder (PTSD) severity in a sample of…

  16. Variables Predicting Foreign Language Reading Comprehension and Vocabulary Acquisition in a Linear Hypermedia Environment

    Science.gov (United States)

    Akbulut, Yavuz

    2007-01-01

    Factors predicting vocabulary learning and reading comprehension of advanced language learners of English in a linear multimedia text were investigated in the current study. Predictor variables of interest were multimedia type, reading proficiency, learning styles, topic interest and background knowledge about the topic. The outcome variables of…

  17. Probabilistic approaches to accounting for data variability in the practical application of bioavailability in predicting aquatic risks from metals.

    Science.gov (United States)

    Ciffroy, Philippe; Charlatchka, Rayna; Ferreira, Daniel; Marang, Laura

    2013-07-01

    The biotic ligand model (BLM) theoretically enables the derivation of environmental quality standards that are based on true bioavailable fractions of metals. Several physicochemical variables (especially pH, major cations, dissolved organic carbon, and dissolved metal concentrations) must, however, be assigned to run the BLM, but they are highly variable in time and space in natural systems. This article describes probabilistic approaches for integrating such variability during the derivation of risk indexes. To describe each variable using a probability density function (PDF), several methods were combined to 1) treat censored data (i.e., data below the limit of detection), 2) incorporate the uncertainty of the solid-to-liquid partitioning of metals, and 3) detect outliers. From a probabilistic perspective, 2 alternative approaches that are based on log-normal and Γ distributions were tested to estimate the probability of the predicted environmental concentration (PEC) exceeding the predicted non-effect concentration (PNEC), i.e., p(PEC/PNEC>1). The probabilistic approach was tested on 4 real-case studies based on Cu-related data collected from stations on the Loire and Moselle rivers. The approach described in this article is based on BLM tools that are freely available for end-users (i.e., the Bio-Met software) and on accessible statistical data treatments. This approach could be used by stakeholders who are involved in risk assessments of metals for improving site-specific studies. Copyright © 2013 SETAC.

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

    Science.gov (United States)

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

    2018-03-01

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

  19. Global warming influence on climatic variables and thermal comfort index in Paraíba state, Brazil

    OpenAIRE

    Silva, Gustavo de Assis; Instituto Agronômico de Pernambuco; Souza, Bonifácio Benicio de; Universidade Federal Campina Grande; Silva, Elisângela Maria Nunes da; UFCG

    2015-01-01

    The increase in the concentration of greenhouse gases originated from burning fossil fuels, along with breeding, been appointed as the main causes of global climate change resulting from global warming in earth's atmosphere. These changes can cause serious impacts on the lives and livestock production mainly in tropical regions. Therefore, the aim with this work was to evaluate the effect of global warming on the climatological variables, thermal comfort index and animal production in the sta...

  20. Predicting Eight Grade Students' Equation Solving Performances via Concepts of Variable and Equality

    Science.gov (United States)

    Ertekin, Erhan

    2017-01-01

    This study focused on how two algebraic concepts- equality and variable- predicted 8th grade students' equation solving performance. In this study, predictive design as a correlational research design was used. Randomly selected 407 eight-grade students who were from the central districts of a city in the central region of Turkey participated in…

  1. The predictive value of the baseline Oswestry Disability Index in lumbar disc arthroplasty.

    Science.gov (United States)

    Deutsch, Harel

    2010-06-01

    The goal of the study was to determine patient factors predictive of good outcome after lumbar disc arthroplasty. Specifically, the paper examines the relationship of the preoperative Oswestry Disability Index (ODI) to patient outcome at 1 year. The study is a retrospective review of 20 patients undergoing a 1-level lumbar disc arthroplasty at the author's institution between 2004 and 2008. All data were collected prospectively. Data included the ODI, visual analog scale scores, and patient demographics. All patients underwent a 1-level disc arthroplasty at L4-5 or L5-S1. The patients were divided into 2 groups based on their baseline ODI. Patients with an ODI between 38 and 59 demonstrated better outcomes with lumbar disc arthroplasty. Only 1 (20%) of 5 patients with a baseline ODI higher than 60 reported a good outcome. In contrast, 13 (87%) of 15 patients with an ODI between 38 and 59 showed a good outcome (p = 0.03). The negative predictive value of using ODI > 60 is 60% in patients who are determined to be candidates for lumbar arthroplasty. Lumbar arthroplasty is very effective in some patients. Other patients do not improve after surgery. The baseline ODI results are predictive of outcome in patients selected for lumbar disc arthroplasty. A baseline ODI > 60 is predictive of poor outcome. A high ODI may be indicative of psychosocial overlay.

  2. Consciousness Indexing and Outcome Prediction with Resting-State EEG in Severe Disorders of Consciousness.

    Science.gov (United States)

    Stefan, Sabina; Schorr, Barbara; Lopez-Rolon, Alex; Kolassa, Iris-Tatjana; Shock, Jonathan P; Rosenfelder, Martin; Heck, Suzette; Bender, Andreas

    2018-04-17

    We applied the following methods to resting-state EEG data from patients with disorders of consciousness (DOC) for consciousness indexing and outcome prediction: microstates, entropy (i.e. approximate, permutation), power in alpha and delta frequency bands, and connectivity (i.e. weighted symbolic mutual information, symbolic transfer entropy, complex network analysis). Patients with unresponsive wakefulness syndrome (UWS) and patients in a minimally conscious state (MCS) were classified into these two categories by fitting and testing a generalised linear model. We aimed subsequently to develop an automated system for outcome prediction in severe DOC by selecting an optimal subset of features using sequential floating forward selection (SFFS). The two outcome categories were defined as UWS or dead, and MCS or emerged from MCS. Percentage of time spent in microstate D in the alpha frequency band performed best at distinguishing MCS from UWS patients. The average clustering coefficient obtained from thresholding beta coherence performed best at predicting outcome. The optimal subset of features selected with SFFS consisted of the frequency of microstate A in the 2-20 Hz frequency band, path length obtained from thresholding alpha coherence, and average path length obtained from thresholding alpha coherence. Combining these features seemed to afford high prediction power. Python and MATLAB toolboxes for the above calculations are freely available under the GNU public license for non-commercial use ( https://qeeg.wordpress.com ).

  3. Evaluation of renal resistive index in cirrhotic patients for predicting the hepatirenal syndrome

    Energy Technology Data Exchange (ETDEWEB)

    Baek, Seung Yon; Kim, Hyae young; Yi, Sun Young [Ewha WoMans Univ. Mokdong Hospital, Seoul (Korea, Republic of)

    1996-04-01

    To evaluate the usefulness of renal resistive index(RI) in patients with liver cirrhosis as an indicator for predicting hepatorenal syndrome. Renal RIs of thirty cirrhotic patients were analyzed using the gray-scale and Doppler ultrasonograms. As a control group, eight normal subjects were included. Renal RIs were measured at three sites of interlobar or arcuate arteries of both kidneys. The patients were divided into three groups (A, B, or C) according to the Child-Turcotte-Pugh classification and their serum BUN and creatinine levels were compared. We determined whether RIs of normal controls differed from those of cirrhotic patients or whether RIs of cirrhotic patients correlated with the Child-Turcotte-Pugh classification or BUN and creatinine levels. Mean RIs(0.63 {+-}0.33) of normal subjects were statistically different from those(0.67 {+-} 0.05) of cirrhotic patients(P=0.009). RIs of group A(n=6), B(n=9) and C(n=15) were 0.65 {+-} 0.03, 0.65 {+-} 0.04 and 0.70 {+-} 0.04, respectively. The ANOVA test revealed statistically significant differences between the three groups(F ratio=4.472, P=0.021). RIs did not correlate with BUN or creatinine levels. RI could be used as an index for predicting hepatorenal syndrome before the renal function becomes impaired.

  4. Evaluation of renal resistive index in cirrhotic patients for predicting the hepatirenal syndrome

    International Nuclear Information System (INIS)

    Baek, Seung Yon; Kim, Hyae young; Yi, Sun Young

    1996-01-01

    To evaluate the usefulness of renal resistive index(RI) in patients with liver cirrhosis as an indicator for predicting hepatorenal syndrome. Renal RIs of thirty cirrhotic patients were analyzed using the gray-scale and Doppler ultrasonograms. As a control group, eight normal subjects were included. Renal RIs were measured at three sites of interlobar or arcuate arteries of both kidneys. The patients were divided into three groups (A, B, or C) according to the Child-Turcotte-Pugh classification and their serum BUN and creatinine levels were compared. We determined whether RIs of normal controls differed from those of cirrhotic patients or whether RIs of cirrhotic patients correlated with the Child-Turcotte-Pugh classification or BUN and creatinine levels. Mean RIs(0.63 ±0.33) of normal subjects were statistically different from those(0.67 ± 0.05) of cirrhotic patients(P=0.009). RIs of group A(n=6), B(n=9) and C(n=15) were 0.65 ± 0.03, 0.65 ± 0.04 and 0.70 ± 0.04, respectively. The ANOVA test revealed statistically significant differences between the three groups(F ratio=4.472, P=0.021). RIs did not correlate with BUN or creatinine levels. RI could be used as an index for predicting hepatorenal syndrome before the renal function becomes impaired

  5. Development of the statistical ARIMA model: an application for predicting the upcoming of MJO index

    Science.gov (United States)

    Hermawan, Eddy; Nurani Ruchjana, Budi; Setiawan Abdullah, Atje; Gede Nyoman Mindra Jaya, I.; Berliana Sipayung, Sinta; Rustiana, Shailla

    2017-10-01

    This study is mainly concerned in development one of the most important equatorial atmospheric phenomena that we call as the Madden Julian Oscillation (MJO) which having strong impacts to the extreme rainfall anomalies over the Indonesian Maritime Continent (IMC). In this study, we focused to the big floods over Jakarta and surrounded area that suspecting caused by the impacts of MJO. We concentrated to develop the MJO index using the statistical model that we call as Box-Jenkis (ARIMA) ini 1996, 2002, and 2007, respectively. They are the RMM (Real Multivariate MJO) index as represented by RMM1 and RMM2, respectively. There are some steps to develop that model, starting from identification of data, estimated, determined model, before finally we applied that model for investigation some big floods that occurred at Jakarta in 1996, 2002, and 2007 respectively. We found the best of estimated model for the RMM1 and RMM2 prediction is ARIMA (2,1,2). Detailed steps how that model can be extracted and applying to predict the rainfall anomalies over Jakarta for 3 to 6 months later is discussed at this paper.

  6. Predictive validity of the Work Ability Index and its individual items in the general population.

    Science.gov (United States)

    Lundin, Andreas; Leijon, Ola; Vaez, Marjan; Hallgren, Mats; Torgén, Margareta

    2017-06-01

    This study assesses the predictive ability of the full Work Ability Index (WAI) as well as its individual items in the general population. The Work, Health and Retirement Study (WHRS) is a stratified random national sample of 25-75-year-olds living in Sweden in 2000 that received a postal questionnaire ( n = 6637, response rate = 53%). Current and subsequent sickness absence was obtained from registers. The ability of the WAI to predict long-term sickness absence (LTSA; ⩾ 90 consecutive days) during a period of four years was analysed by logistic regression, from which the Area Under the Receiver Operating Characteristic curve (AUC) was computed. There were 313 incident LTSA cases among 1786 employed individuals. The full WAI had acceptable ability to predict LTSA during the 4-year follow-up (AUC = 0.79; 95% CI 0.76 to 0.82). Individual items were less stable in their predictive ability. However, three of the individual items: current work ability compared with lifetime best, estimated work impairment due to diseases, and number of diagnosed current diseases, exceeded AUC > 0.70. Excluding the WAI item on number of days on sickness absence did not result in an inferior predictive ability of the WAI. The full WAI has acceptable predictive validity, and is superior to its individual items. For public health surveys, three items may be suitable proxies of the full WAI; current work ability compared with lifetime best, estimated work impairment due to diseases, and number of current diseases diagnosed by a physician.

  7. Seasonal variability of leaf area index and foliar nitrogen in contrasting dry-mesic tundras

    DEFF Research Database (Denmark)

    Campioli, Matteo; Michelsen, Anders; Lemeur, Raoul

    2009-01-01

    Assimilation and exchange of carbon for arctic ecosystems depend strongly on leaf area index (LAI) and total foliar nitrogen (TFN). For dry-mesic tundras, the seasonality of these characteristics is unexplored. We addressed this knowledge gap by measuring variations of LAI and TFN at five contras...

  8. A GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (U.S.A.)

    Science.gov (United States)

    Louis R. Iverson; Martin E. Dale; Charles T. Scott; Anantha Prasad; Anantha Prasad

    1997-01-01

    A geographic information system (GIS) approach was used in conjunction with forest-plot data to develop an integrated moisture index (IMI), which was then used to predict forest productivity (site index) and species composition for forests in Ohio. In this region, typical of eastern hardwoods across the Midwest and southern Appalachians, topographic aspect and position...

  9. FTO genotype is associated with phenotypic variability of body mass index

    NARCIS (Netherlands)

    Yang, J.; Loos, R.J.; Powell, J.E.; Medland, S.E.; Speliotes, E.K.; Chasman, D.I.; Rose, L.M.; Thorleifsson, G.; Steinthorsdottir, V.; Mägi, R.; Waite, L.; Smith, A.V.; Yerges-Armstrong, L.M.; Monda, K.L.; Hadley, D.; Mahajan, A.; Li, G.; Kapur, K.; Vitart, V.; Huffman, J.E.; Wang, S.R.; Palmer, C.; Esko, T.; Fischer, K.; Zhao, J.H.; Demirkan, A.; Isaacs, A.; Feitosa, M.F.; Luan, J.; Heard-Costa, N.L.; White, C.; Jackson, A.U.; Preuss, M; Ziegler, A.; Eriksson, J.; Kutalik, Z.; Frau, F.; Nolte, I.M.; van Vliet-Ostaptchouk, J.V.; Hottenga, J.J.; Jacobs, K.B.; Verweij, N.; Goel, A.; Medina-Gomez, C.; Estrada, K.; Bragg-Gresham, J.L.; Sanna, S.; Sidore, C.; Tyrer, J.; Teumer, A.; Prokopenko, I.; Mangino, M.; Lindgren, C.M.; Assimes, T.L.; Shuldiner, A.R.; Hui, J.; Beilby, J.P.; McArdle, W.L.; Hall, P.; Haritunians, T.; Zgaga, L.; Kolcic, I.; Polasek, O.; Zemunik, T.; Oostra, B.A.; Junttila, M.J.; Grönberg, H.; Schreiber, S; Peters, A.; Hicks, A.A.; Stephens, J.; Foad, N.S.; Laitinen, J.; Pouta, A.; Kaakinen, M.; Willemsen, G.; Vink, J.M.; Wild, S.H.; Navis, G.; Asselbergs, F.W.; Homuth, G.; John, U.; Iribarren, C.; Harris, T.; Launer, L.J.; Gudnason, V.; O'Connell, J.R.; Boerwinkle, E.; Cadby, G.; Palmer, L.J.; James, A.L.; Musk, A.W.; Ingelsson, E.; Psaty, B.M.; Beckmann, J.S.; Waeber, G.; Vollenweider, P.; Hayward, C.; Wright, A.F.; Rudan, I.; Groop, L.C.; Metspalu, A.; Thee Khaw, K.; van Duijn, C.M.; Borecki, I.B.; Province, M.A.; Wareham, N.J.; Tardif, J.C.; Huikuri, H.V.; Cupples, L.A.; Atwood, L.D.; Fox, C.S.; Boehnke, M.; Collins, F.S.; Mohlke, K.L.; Erdmann, J.; Schunkert, H.; Hengstenberg, C.; Stark, K.; Lorentzon, M.; Ohlsson, C.; Cusi, D.; Staessen, J.A.; van der Klauw, M.M.; Pramstaller, P.P.; Kathiresan, S.; Jolley, D.J.; Ripatti, S.; Jarvelin, M.-R.; de Geus, E.J.C.; Boomsma, D.I.; Penninx, B.W.J.H.; Wilson, J.F.; Campbell, H.; Chanock, S.J.; van der Harst, P.; Hamsten, A.; Watkins, H.; Hofman, A.; Witteman, J.C.; Zillikens, M.C.; Uitterlinden, A.G.; Rivadeneira, F.; Kiemeney, L.A.; Vermeulen, S.H.; Abecasis, G.R.; Schlessinger, D.; Schipf, S.; Stumvoll, M.; Tönjes, A.; Spector, T.D.; North, K.E.; Lettre, G.; McCarthy, M.I.; Berndt, S.I.; Heath, A.C.; Madden, P.A.F.; Nyholt, DR; Montgomery, G.W.; Martin, N.G.; McKnight, B.; Strachan, D.P.; Hill, W.G.; Snieder, H.; Ridker, P.M.; Thorsteinsdottir, U.; Stefansson, K.; Frayling, T.M.; Hirschhorn, J.N.; Goddard, M.E.; Visscher, P.M.

    2012-01-01

    There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human

  10. Robust Model Predictive Control of a Nonlinear System with Known Scheduling Variable and Uncertain Gain

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2012-01-01

    Robust model predictive control (RMPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Because...... of the special structure of the problem, uncertainty is only in the B matrix (gain) of the state space model. Therefore by taking advantage of this structure, we formulate a tractable minimax optimization problem to solve robust model predictive control problem. Wind turbine is chosen as the case study and we...... choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....

  11. Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables.

    Directory of Open Access Journals (Sweden)

    Michelle G Swainson

    Full Text Available The conventional measurement of obesity utilises the body mass index (BMI criterion. Although there are benefits to this method, there is concern that not all individuals at risk of obesity-associated medical conditions are being identified. Whole-body fat percentage (%FM, and specifically visceral adipose tissue (VAT mass, are correlated with and potentially implicated in disease trajectories, but are not fully accounted for through BMI evaluation. The aims of this study were (a to compare five anthropometric predictors of %FM and VAT mass, and (b to explore new cut-points for the best of these predictors to improve the characterisation of obesity.BMI, waist circumference (WC, waist-to-hip ratio (WHR, waist-to-height ratio (WHtR and waist/height0.5 (WHT.5R were measured and calculated for 81 adults (40 women, 41 men; mean (SD age: 38.4 (17.5 years; 94% Caucasian. Total body dual energy X-ray absorptiometry with Corescan (GE Lunar iDXA, Encore version 15.0 was also performed to quantify %FM and VAT mass. Linear regression analysis, stratified by sex, was applied to predict both %FM and VAT mass for each anthropometric variable. Within each sex, we used information theoretic methods (Akaike Information Criterion; AIC to compare models. For the best anthropometric predictor, we derived tentative cut-points for classifying individuals as obese (>25% FM for men or >35% FM for women, or > highest tertile for VAT mass.The best predictor of both %FM and VAT mass in men and women was WHtR. Derived cut-points for predicting whole body obesity were 0.53 in men and 0.54 in women. The cut-point for predicting visceral obesity was 0.59 in both sexes.In the absence of more objective measures of central obesity and adiposity, WHtR is a suitable proxy measure in both women and men. The proposed DXA-%FM and VAT mass cut-offs require validation in larger studies, but offer potential for improvement of obesity characterisation and the identification of individuals

  12. Both Reaction Time and Accuracy Measures of Intraindividual Variability Predict Cognitive Performance in Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Björn U. Christ

    2018-04-01

    Full Text Available Dementia researchers around the world prioritize the urgent need for sensitive measurement tools that can detect cognitive and functional change at the earliest stages of Alzheimer's disease (AD. Sensitive indicators of underlying neural pathology assist in the early detection of cognitive change and are thus important for the evaluation of early-intervention clinical trials. One method that may be particularly well-suited to help achieve this goal involves the quantification of intraindividual variability (IIV in cognitive performance. The current study aimed to directly compare two methods of estimating IIV (fluctuations in accuracy-based scores vs. those in latency-based scores to predict cognitive performance in AD. Specifically, we directly compared the relative sensitivity of reaction time (RT—and accuracy-based estimates of IIV to cognitive compromise. The novelty of the present study, however, centered on the patients we tested [a group of patients with Alzheimer's disease (AD] and the outcome measures we used (a measure of general cognitive function and a measure of episodic memory function. Hence, we compared intraindividual standard deviations (iSDs from two RT tasks and three accuracy-based memory tasks in patients with possible or probable Alzheimer's dementia (n = 23 and matched healthy controls (n = 25. The main analyses modeled the relative contributions of RT vs. accuracy-based measures of IIV toward the prediction of performance on measures of (a overall cognitive functioning, and (b episodic memory functioning. Results indicated that RT-based IIV measures are superior predictors of neurocognitive impairment (as indexed by overall cognitive and memory performance than accuracy-based IIV measures, even after adjusting for the timescale of measurement. However, one accuracy-based IIV measure (derived from a recognition memory test also differentiated patients with AD from controls, and significantly predicted episodic memory

  13. Predicting the need for institutional care shortly after admission to rehabilitation: Rasch analysis and predictive validity of the BRASS Index.

    Science.gov (United States)

    Panella, L; La Porta, F; Caselli, S; Marchisio, S; Tennant, A

    2012-09-01

    Effective discharge planning is increasingly recognised as a critical component of hospital-based Rehabilitation. The BRASS index is a risk screening tool for identification, shortly after hospital admission, of patients who are at risk of post-discharge problems. To evaluate the internal construct validity and reliability of the Blaylock Risk Assessment Screening Score (BRASS) within the rehabilitation setting. Observational prospective study. Rehabilitation ward of an Italian district hospital. One hundred and four consecutively admitted patients. Using classical psychometric methods and Rasch analysis (RA), the internal construct validity and reliability of the BRASS were examined. Also, external and predictive validity of the Rasch-modified BRASS (RMB) score were determined. Reliability of the original BRASS was low (Cronbach's alpha=0.595) and factor analyses showed that it was clearly multidimensional. A RA, based on a reduced 7-BRASS item set (RMB), satisfied model's expectations. Reliability was 0.777. The RMB scores strongly correlated with the original BRASS (rho=0.952; P28 days (RR=7.6, 95%CI=1.8-31.9). This study demonstrated that the original BRASS was multidimensional and unreliable. However, the RMB holds adequate internal construct validity and is sufficiently reliable as a predictor of discharge problems for group, but not individual use. The application of tools and methods (such as the BRASS Index) developed under the biomedical paradigm in a Physical and Rehabilitation Medicine setting may have limitations. Further research is needed to develop, within the rehabilitation setting, a valid measuring tool of risk of post-discharge problems at the individual level.

  14. Prediction of Lateral Ankle Sprains in Football Players Based on Clinical Tests and Body Mass Index.

    Science.gov (United States)

    Gribble, Phillip A; Terada, Masafumi; Beard, Megan Q; Kosik, Kyle B; Lepley, Adam S; McCann, Ryan S; Pietrosimone, Brian G; Thomas, Abbey C

    2016-02-01

    The lateral ankle sprain (LAS) is the most common injury suffered in sports, especially in football. While suggested in some studies, a predictive role of clinical tests for LAS has not been established. To determine which clinical tests, focused on potentially modifiable factors of movement patterns and body mass index (BMI), could best demonstrate risk of LAS among high school and collegiate football players. Case-control study; Level of evidence, 3. A total of 539 high school and collegiate football players were evaluated during the preseason with the Star Excursion Balance Test (SEBT) and Functional Movement Screen as well as BMI. Results were compared between players who did and did not suffer an LAS during the season. Logistic regression analyses and calculated odds ratios were used to determine which measures predicted risk of LAS. The LAS group performed worse on the SEBT-anterior reaching direction (SEBT-ANT) and had higher BMI as compared with the noninjured group (P football players. BMI was also significantly higher in football players who sustained an LAS. Identifying clinical tools for successful LAS injury risk prediction will be a critical step toward the creation of effective prevention programs to reduce risk of sustaining an LAS during participation in football. © 2015 The Author(s).

  15. Role of Transition Zone Index in the Prediction of Clinical Benign Prostatic Hyperplasia

    Directory of Open Access Journals (Sweden)

    Muhammet Güzelsoy

    2016-12-01

    Full Text Available Objective The objective of this study was to determine the role of the transition zone (TZ index (TZI in the prediction of clinical benign prostatic hyperplasia (BPH in patients who underwent transurethral prostatectomy (TUR-P and to analyze the correlation between the amount of resected tissue and TZ volume (TZV. Materials and Methods Twenty-six male clinical BPH patients with obstructive complaints and 17 male benign prostate enlargement (BPE patients without any complaints were included in the study. Both the groups were over the age of 50. Clinical BPH patients underwent complete TUR-P. Statistical analysis was done with SPSS. Sensitivity, specificity, positive and negative predictive values of TZI-as a method of assessing clinical BPH-were measured. Results There was a statistically significant difference in prostate volume, uroflowmetry patterns, prostate-specific antigen (PSA, International prostate symptom score (IPSS, TZV and TZI between the two groups. There was a correlation between TZV and the amount of resected tissue (r=0.97; p0.40 has a high level of sensitivity and specificity in the prediction of clinical BPH among patients who undergo TUR-P due to obstructive symptoms and reported as BPH. There is a strong correlation between the amount of resected tissue and TZV. TZI is a valuable tool in diagnosis, and TZV gives valuable information about the patient to the surgeon.

  16. Use of the Charlson Combined Comorbidity Index To Predict Postradiotherapy Quality of Life for Prostate Cancer Patients

    International Nuclear Information System (INIS)

    Wahlgren, Thomas; Levitt, Seymour; Kowalski, Jan; Nilsson, Sten; Brandberg, Yvonne

    2011-01-01

    Purpose: To determine the impact of pretreatment comorbidity on late health-related quality of life (HRQoL) scores after patients have undergone combined radiotherapy for prostate cancer, including high-dose rate brachytherapy boost and hormonal deprivation therapy. Methods and Materials: Results from the European Organization for Research and Treatment of Cancer QLQ-C30 questionnaire survey of 158 patients 5 years or more after completion of therapy were used from consecutively accrued subjects treated with curative radiotherapy at our institution, with no signs of disease at the time of questionnaire completion. HRQoL scores were compared with the Charlson combined comorbidity index (CCI), using analysis of covariance and multivariate regression models together with pretreatment factors including tumor stage, tumor grade, pretreatment prostate-specific antigen level, neoadjuvant hormonal treatment, diabetes status, cardiovascular status, and age and Charlson score as separate variables or the composite CCI. Results: An inverse correlation between the two HRQoL domains, long-term global health (QL) and physical function (PF) scores, and the CCI score was observed, indicating an impact of comorbidity in these function areas. Selected pretreatment factors poorly explained the variation in functional HRQoL in the multivariate models; however, a statistically significant impact was found for the CCI (with QL and PF scores) and the presence of diabetes (with QL and emotional function). Cognitive function and social function were not statistically significantly predicted by any of the pretreatment factors. Conclusions: The CCI proved to be valid in this context, but it seems useful mainly in predicting long-term QL and PF scores. Of the other variables investigated, diabetes had more impact than cardiovascular morbidity on HRQoL outcomes in prostate cancer.

  17. Use of the Charlson Combined Comorbidity Index To Predict Postradiotherapy Quality of Life for Prostate Cancer Patients

    Energy Technology Data Exchange (ETDEWEB)

    Wahlgren, Thomas, E-mail: thomas.wahlgren@telia.com [Department of Oncology-Pathology, Karolinska University Hospital and Institutet, Stockholm (Sweden); Levitt, Seymour [Department of Oncology-Pathology, Karolinska University Hospital and Institutet, Stockholm (Sweden); Department of Therapeutic Radiology, University of Minnesota, Minneapolis, Minnesota (United States); Kowalski, Jan [Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm (Sweden); Nilsson, Sten; Brandberg, Yvonne [Department of Oncology-Pathology, Karolinska University Hospital and Institutet, Stockholm (Sweden)

    2011-11-15

    Purpose: To determine the impact of pretreatment comorbidity on late health-related quality of life (HRQoL) scores after patients have undergone combined radiotherapy for prostate cancer, including high-dose rate brachytherapy boost and hormonal deprivation therapy. Methods and Materials: Results from the European Organization for Research and Treatment of Cancer QLQ-C30 questionnaire survey of 158 patients 5 years or more after completion of therapy were used from consecutively accrued subjects treated with curative radiotherapy at our institution, with no signs of disease at the time of questionnaire completion. HRQoL scores were compared with the Charlson combined comorbidity index (CCI), using analysis of covariance and multivariate regression models together with pretreatment factors including tumor stage, tumor grade, pretreatment prostate-specific antigen level, neoadjuvant hormonal treatment, diabetes status, cardiovascular status, and age and Charlson score as separate variables or the composite CCI. Results: An inverse correlation between the two HRQoL domains, long-term global health (QL) and physical function (PF) scores, and the CCI score was observed, indicating an impact of comorbidity in these function areas. Selected pretreatment factors poorly explained the variation in functional HRQoL in the multivariate models; however, a statistically significant impact was found for the CCI (with QL and PF scores) and the presence of diabetes (with QL and emotional function). Cognitive function and social function were not statistically significantly predicted by any of the pretreatment factors. Conclusions: The CCI proved to be valid in this context, but it seems useful mainly in predicting long-term QL and PF scores. Of the other variables investigated, diabetes had more impact than cardiovascular morbidity on HRQoL outcomes in prostate cancer.

  18. A Risk Prediction Index for Advanced Colorectal Neoplasia at Screening Colonoscopy.

    Science.gov (United States)

    Schroy, Paul C; Wong, John B; O'Brien, Michael J; Chen, Clara A; Griffith, John L

    2015-07-01

    Eliciting patient preferences within the context of shared decision making has been advocated for colorectal cancer screening. Risk stratification for advanced colorectal neoplasia (ACN) might facilitate more effective shared decision making when selecting an appropriate screening option. Our objective was to develop and validate a clinical index for estimating the probability of ACN at screening colonoscopy. We conducted a cross-sectional analysis of 3,543 asymptomatic, mostly average-risk patients 50-79 years of age undergoing screening colonoscopy at two urban safety net hospitals. Predictors of ACN were identified using multiple logistic regression. Model performance was internally validated using bootstrapping methods. The final index consisted of five independent predictors of risk (age, smoking, alcohol intake, height, and a combined sex/race/ethnicity variable). Smoking was the strongest predictor (net reclassification improvement (NRI), 8.4%) and height the weakest (NRI, 1.5%). Using a simplified weighted scoring system based on 0.5 increments of the adjusted odds ratio, the risk of ACN ranged from 3.2% (95% confidence interval (CI), 2.6-3.9) for the low-risk group (score ≤2) to 8.6% (95% CI, 7.4-9.7) for the intermediate/high-risk group (score 3-11). The model had moderate to good overall discrimination (C-statistic, 0.69; 95% CI, 0.66-0.72) and good calibration (P=0.73-0.93). A simple 5-item risk index based on readily available clinical data accurately stratifies average-risk patients into low- and intermediate/high-risk categories for ACN at screening colonoscopy. Uptake into clinical practice could facilitate more effective shared decision-making for CRC screening, particularly in situations where patient and provider test preferences differ.

  19. VALIDITY OF GARBER MODEL IN PREDICTING PAVEMENT CONDITION INDEX OF FLEXIBLE PAVEMENT IN KERBALA CITY

    Directory of Open Access Journals (Sweden)

    Hussein A. Ewadh

    2018-05-01

    Full Text Available Pavement Condition Index (PCI is one of the important basics in pavement maintenance management system (PMMS, and it is used to evaluate the current and future pavement condition. This importantance in decision making to limit the maintenance needs, types of treatment, and maintenance priority. The aim of this research is to estimate the PCI value for flexible pavement urban roads in the study area (kerbala city by using Garber et al. developed model. Based on previous researches, data are collected for variables that have a significant impact on pavement condition. Data for pavement age (AGE, average daily traffic (ADT, and structural number (SN were collected for 44 sections in the network roads. A field survey (destructive test (core test and laboratory test (Marshall Test were used to determine the capacity of structure layer of pavement (SN. The condition index (CI output from a developed model was compared with the PCI output of PAVER 6.5.7 by using statistical analysis test. The developed model overestimates value of CI rather than PCI estimated from PAVER 6.5.7 due to statistical test to a 95% degree of confidence, (R = 0.771 for 44 sections (arterial and collector.

  20. The bilateral bispectral and the composite variability indexes during anesthesia for unilateral surgical procedure

    Directory of Open Access Journals (Sweden)

    Pedro Lopes-Pimentel

    2017-01-01

    Conclusions: Our results indicate that the large interindividual variability of BIS and CVI limits their usefulness. We found differences between the left and right measurements in a right-handed series of patients during surgical stimuli though they were not clinically relevant.

  1. Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance.

    Science.gov (United States)

    Pradhan, Maheswar; Rao, A Suryachandra; Srivastava, Ankur; Dakate, Ashish; Salunke, Kiran; Shameera, K S

    2017-10-27

    Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2-3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.

  2. Dynamic Variables Fail to Predict Fluid Responsiveness in an Animal Model With Pericardial Effusion.

    Science.gov (United States)

    Broch, Ole; Renner, Jochen; Meybohm, Patrick; Albrecht, Martin; Höcker, Jan; Haneya, Assad; Steinfath, Markus; Bein, Berthold; Gruenewald, Matthias

    2016-10-01

    The reliability of dynamic and volumetric variables of fluid responsiveness in the presence of pericardial effusion is still elusive. The aim of the present study was to investigate their predictive power in a porcine model with hemodynamic relevant pericardial effusion. A single-center animal investigation. Twelve German domestic pigs. Pigs were studied before and during pericardial effusion. Instrumentation included a pulmonary artery catheter and a transpulmonary thermodilution catheter in the femoral artery. Hemodynamic variables like cardiac output (COPAC) and stroke volume (SVPAC) derived from pulmonary artery catheter, global end-diastolic volume (GEDV), stroke volume variation (SVV), and pulse-pressure variation (PPV) were obtained. At baseline, SVV, PPV, GEDV, COPAC, and SVPAC reliably predicted fluid responsiveness (area under the curve 0.81 [p = 0.02], 0.82 [p = 0.02], 0.74 [p = 0.07], 0.74 [p = 0.07], 0.82 [p = 0.02]). After establishment of pericardial effusion the predictive power of dynamic variables was impaired and only COPAC and SVPAC and GEDV allowed significant prediction of fluid responsiveness (area under the curve 0.77 [p = 0.04], 0.76 [p = 0.05], 0.83 [p = 0.01]) with clinically relevant changes in threshold values. In this porcine model, hemodynamic relevant pericardial effusion abolished the ability of dynamic variables to predict fluid responsiveness. COPAC, SVPAC, and GEDV enabled prediction, but their threshold values were significantly changed. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Gait Deviation Index, Gait Profile Score and Gait Variable Score in children with spastic cerebral palsy

    DEFF Research Database (Denmark)

    Rasmussen, Helle Mätzke; Nielsen, Dennis Brandborg; Pedersen, Niels Wisbech

    2015-01-01

    Abstract The Gait Deviation Index (GDI) and Gait Profile Score (GPS) are the most used summary measures of gait in children with cerebral palsy (CP). However, the reliability and agreement of these indices have not been investigated, limiting their clinimetric quality for research and clinical...... to good reliability with ICCs of 0.4–0.7. The agreement for the GDI and the logarithmically transformed GPS, in terms of the standard error of measurement as a percentage of the grand mean (SEM%) varied from 4.1 to 6.7%, whilst the smallest detectable change in percent (SDC%) ranged from 11.3 to 18...

  4. Reference curves of the body fat index in adolescents and their association with anthropometric variables

    Directory of Open Access Journals (Sweden)

    Renata Rago Frignani

    2015-05-01

    Full Text Available Objectives: To develop reference curves for the body fat index (BFI in the pediatric population, in adolescents from the city of São Paulo, Brazil, and verify their association with body mass index and body fat percentage. Methods: The study is part of the research project “Nutritional Profile of Adolescents from Public and Private Schools of São Paulo” that was performed in 2004-2005. A total of 4,686 adolescents (2,130 boys and 2,556 girls aged 10-15 years were divided into two groups: 10-12 and 13-15 years of age. Body mass, height, body mass index, hip circumference, body fat percentage, body fat index, and sexual maturation performed by the self-assessment method (prepubertal, pubertal, and postpubertal were analyzed. ANOVA was performed, as well as percentile distribution, Pearson's correlation, and Bland-Altman plot. Results: In boys, there was an increase in body mass, height, body mass index, and hip circumference with advancing age and Tanner stage. In girls, there was an increase in body fat index and body fat percentage with advancing age and stage of sexual maturation. An association was found between body fat index and body mass index (r = 0.67 in boys and 0.80 in girls, p < 0.001 and body fat percentage (r = 0.71 in boys and 0.68 in girls, p < 0.001. Conclusion: The body fat index seems to reflect well the phenomena of sexual dimorphism in adolescence, is easy to perform, and represents a method that should be used in population samples. Resumo: Objetivos: Desenvolver curvas de referência do índice de adiposidade corporal para população pediátrica, em adolescentes da cidade de São Paulo, Brasil, e verificar a sua relação com o índice de massa corporal e percentual de gordura corporal. Métodos: O estudo faz parte do projeto de pesquisa “Perfil Nutricional de Adolescentes de escolas Públicas e Privadas de São Paulo” realizado em 2004/2005. 4.686 adolescentes (2.130 meninos e 2.556 meninas de 10-15 anos

  5. The variable refractive index correction algorithm based on a stereo light microscope

    International Nuclear Information System (INIS)

    Pei, W; Zhu, Y Y

    2010-01-01

    Refraction occurs at least twice on both the top and the bottom surfaces of the plastic plate covering the micro channel in a microfluidic chip. The refraction and the nonlinear model of a stereo light microscope (SLM) may severely affect measurement accuracy. In this paper, we study the correlation between optical paths of the SLM and present an algorithm to adjust the refractive index based on the SLM. Our algorithm quantizes the influence of cover plate and double optical paths on the measurement accuracy, and realizes non-destructive, non-contact and precise 3D measurement of a hyaloid and closed container

  6. In vitro starch digestibility and predicted glycemic index of microwaved and conventionally baked pound cake.

    Science.gov (United States)

    Sánchez-Pardo, María Elena; Ortiz-Moreno, Alicia; Mora-Escobedo, Rosalva; Necoechea-Mondragón, Hugo

    2007-09-01

    The present study compares the effect of baking process (microwave vs conventional oven) on starch bioavailability in fresh pound cake crumbs and in crumbs from pound cake stored for 8 days. Proximal chemical analysis, resistant starch (RS), retrograded starch (RS3) and starch hydrolysis index (HI) were evaluated. The empirical formula suggested by Granfeldt was used to determine the predicted glycemic index (pGI). Pound cake, one of Mexico's major bread products, was selected for analysis because the quality defects often associated with microwave baking might be reduced with the use of high-fat, high-moisture, batted dough. Differences in product moisture, RS and RS3 were observed in fresh microwave-baked and conventionally baked pound cake. RS3 increased significantly in conventionally baked products stored for 8 days at room temperature, whereas no significantly changes in RS3 were observed in the microwaved product. HI values for freshly baked and stored microwaved product were 59 and 62%, respectively (P > 0.05), whereas the HI value for the conventionally baked product decreased significantly after 8 days of storage. A pound cake with the desired HI and GI characteristics might be obtained by adjusting the microwave baking process.

  7. Age-adjusted Charlson Comorbidity Index predicts prognosis of laryngopharyngeal cancer treated with radiation therapy.

    Science.gov (United States)

    Takemura, Kazuya; Takenaka, Yukinori; Ashida, Naoki; Shimizu, Kotaro; Oya, Ryohei; Kitamura, Takahiro; Yamamoto, Yoshifumi; Uno, Atsuhiko

    2017-12-01

    To examine the ability of comorbidity indices to predict the prognosis of laryngopharyngeal cancer and their association with treatment modalities. This retrospective study included 198 patients with laryngeal, hypopharyngeal, and oropharyngeal cancers. The effect of comorbidity indices on overall survival between surgery and (chemo)-radiation therapy ((C)RT) groups was analyzed. The cumulative incidence rates for cancer mortality and other mortalities according to the age-adjusted Charlson Comorbidity Index (ACCI) and Charlson Comorbidity Index (CCI) were compared. Univariate survival analyses showed a significant association between the ACCI and overall survival in the (C)RT group, but not in the surgery group. The association between the CCI and overall survival was not significant in either group. In multivariate analyses, a high ACCI score was an independent prognostic factor in the (C)RT group (HR 2.89, 95% confidence interval (CI) 1.28-6.49), but not in the surgery group (HR 1.39, 95%CI 0.27-5.43). The higher ACCI group had increased mortality from other causes compared with the lower ACCI group (5-year cumulative incidence, 8.5% and 17.8%, respectively, p = .003). The ACCI was a better prognostic factor than the CCI. Surgery may be more beneficial than radiation for patients with a high ACCI.

  8. Development of a Summarized Health Index (SHI for use in predicting survival in sea turtles.

    Directory of Open Access Journals (Sweden)

    Tsung-Hsien Li

    Full Text Available Veterinary care plays an influential role in sea turtle rehabilitation, especially in endangered species. Physiological characteristics, hematological and plasma biochemistry profiles, are useful references for clinical management in animals, especially when animals are during the convalescence period. In this study, these factors associated with sea turtle surviving were analyzed. The blood samples were collected when sea turtles remained alive, and then animals were followed up for surviving status. The results indicated that significantly negative correlation was found between buoyancy disorders (BD and sea turtle surviving (p < 0.05. Furthermore, non-surviving sea turtles had significantly higher levels of aspartate aminotranspherase (AST, creatinine kinase (CK, creatinine and uric acid (UA than surviving sea turtles (all p < 0.05. After further analysis by multiple logistic regression model, only factors of BD, creatinine and UA were included in the equation for calculating summarized health index (SHI for each individual. Through evaluation by receiver operating characteristic (ROC curve, the result indicated that the area under curve was 0.920 ± 0.037, and a cut-off SHI value of 2.5244 showed 80.0% sensitivity and 86.7% specificity in predicting survival. Therefore, the developed SHI could be a useful index to evaluate health status of sea turtles and to improve veterinary care at rehabilitation facilities.

  9. Examining spatial-temporal variability and prediction of rainfall in North-eastern Nigeria

    Science.gov (United States)

    Muhammed, B. U.; Kaduk, J.; Balzter, H.

    2012-12-01

    In the last 50 years rainfall in North-eastern Nigeria under the influence of the West African Monsoon (WAM) has been characterised by large annual variations with severe droughts recorded in 1967-1973, and 1983-1987. This variability in rainfall has a large impact on the regions agricultural output, economy and security where the majority of the people depend on subsistence agriculture. In the 1990s there was a sign of recovery with higher annual rainfall totals compared to the 1961-1990 period but annual totals were slightly above the long term mean for the century. In this study we examine how significant this recovery is by analysing medium-term (1980-2006) rainfall of the region using the Climate Research Unit (CRU) and National Centre for Environment Prediction (NCEP) precipitation ½ degree, 6 hourly reanalysis data set. Percentage coefficient of variation increases northwards for annual rainfall (10%-35%) and the number of rainy days (10%-50%). The standardized precipitation index (SPI) of the area shows 7 years during the period as very wet (1996, 1999, 2003 and 2004) with SPI≥1.5 and moderately wet (1993, 1998, and 2006) with values of 1.0≥SPI≤1.49. Annual rainfall indicates a recovery from the 1990s and onwards but significant increases (in the amount of rainfall and number of days recorded with rainfall) is only during the peak of the monsoon season in the months of August and September (pARIMA) model. The model is further evaluated using 24 months rainfall data yielding r=0.79 (regression slope=0.8; pARIMA model and the rainfall data used for this study indicates that the model can be satisfactorily used in forecasting rainfall in the in the sub-humid part of North-eastern Nigeria over a 24 months period.

  10. Waist circumference as compared with body-mass index in predicting mortality from specific causes.

    Directory of Open Access Journals (Sweden)

    Michael F Leitzmann

    2011-04-01

    Full Text Available Whether waist circumference provides clinically meaningful information not delivered by body-mass index regarding prediction of cause-specific death is uncertain.We prospectively examined waist circumference (WC and body-mass index (BMI in relation to cause-specific death in 225,712 U.S. women and men. Cox regression was used to estimate relative risks and 95% confidence intervals (CI. Statistical analyses were conducted using SAS version 9.1.During follow-up from 1996 through 2005, we documented 20,977 deaths. Increased WC consistently predicted risk of death due to any cause as well as major causes of death, including deaths from cancer, cardiovascular disease, and non-cancer/non-cardiovascular diseases, independent of BMI, age, sex, race/ethnicity, smoking status, and alcohol intake. When WC and BMI were mutually adjusted in a model, WC was related to 1.37 fold increased risk of death from any cancer and 1.82 fold increase risk of death from cardiovascular disease, comparing the highest versus lowest WC categories. Importantly, WC, but not BMI showed statistically significant positive associations with deaths from lung cancer and chronic respiratory disease. Participants in the highest versus lowest WC category had a relative risk of death from lung cancer of 1.77 (95% CI, 1.41 to 2.23 and of death from chronic respiratory disease of 2.77 (95% CI, 1.95 to 3.95. In contrast, subjects in the highest versus lowest BMI category had a relative risk of death from lung cancer of 0.94 (95% CI, 0.75 to 1.17 and of death from chronic respiratory disease of 1.18 (95% CI, 0.89 to 1.56.Increased abdominal fat measured by WC was related to a higher risk of deaths from major specific causes, including deaths from lung cancer and chronic respiratory disease, independent of BMI.

  11. Waist-Hip Ratio Surrogate Is More Predictive Than Body Mass Index of Wound Complications After Pelvic and Acetabulum Surgery.

    Science.gov (United States)

    Jaeblon, Todd; Perry, Kevin J; Kufera, Joseph A

    2018-04-01

    To determine whether a novel surrogate of waist-hip ratio (WHR) is more predictive of wound complications after pelvis or acetabulum stabilization than body mass index (BMI) and describe the method of measuring a WHR proxy (WHRp). Retrospective review. One Level 1 Trauma Center. One hundred sixty-one patients after operative repair of pelvis and acetabulum fractures. Operative stabilization of a pelvic ring injury or acetabular fracture. Infection (pin, superficial, and deep) and wound healing complication. We retrospectively reviewed 161 subjects after operative repair of pelvic and acetabular fractures. Primary outcome was any wound complication. BMI was acquired from medical records. WHRp was derived from anteroposterior and lateral computed tomography scout images. BMI and WHRp results were analyzed as continuous and categorical variables. BMI was grouped into high-risk categories of ≥30 and ≥40. WHRp data were grouped utilizing the WHO's high-risk profile for females (>0.85) and males (>0.90). An alternative optimal WHR was also assessed. Covariate analysis included demographic data, Injury Severity Score, mechanism, tobacco use, presence and types of open approach, injury type, associated injuries and comorbidities, failure of fixation, and thromboembolism. The mean follow-up was 15.9 months. Twenty-four (15%) patients developed wound complications. Increasing BMI (P < 0.007) and WHRp (P < 0.001) as continuous variables and female sex (P < 0.009) were associated with wound complications. Applying unadjusted continuous data to a receiver operating characteristic curve revealed a greater area under the curve for WHRp than for BMI (P < 0.001). The optimal predictive WHRp was ≥1.0 (P < 0.001, odds ratio 43.11). The receiver operating characteristic curve from adjusted data demonstrated a greater area under the curve for WHRp ≥1.0 (0.93) compared with BMI ≥30 (0.78) or ≥40 (0.75) and WHO WHRp (0.82). Computed tomography generated WHRp demonstrated

  12. The Doppler echocardiographic myocardial performance index predicts left-ventricular dilation and cardiac death after myocardial infarction

    DEFF Research Database (Denmark)

    Møller, J E; Søndergaard, E; Poulsen, S H

    2001-01-01

    To investigate the value of the Doppler-derived myocardial performance index to predict early left-ventricular (LV) dilation and cardiac death after a first acute myocardial infarction (AMI), Doppler echocardiography was performed within 24 h of hospital admission, on day 5, 1 and 3 months after...... AMI in 125 consecutive patients. The index measured on day 1 correlated well with the change in end-diastolic volume index observed from day 1 to 3 months following AMI (r = 0.66, p 0.0001). One-year survival in patients with Doppler index index > or = 0......, we conclude that the Doppler echocardiographic myocardial performance index is a predictor of LV dilation and cardiac death after a first AMI....

  13. The impact of macroeconomic and conventional stock market variables on Islamic index returns under regime switching

    Directory of Open Access Journals (Sweden)

    Slah Bahloul

    2017-03-01

    Full Text Available The objective of this paper is to study the impact of conventional stock market return and volatility and various macroeconomic variables (including inflation rate, short-term interest rate, the slope of the yield curve and money supply on Islamic stock markets returns for twenty developed and emerging markets using Markov switching regression models. The empirical results for the period 2002–2014 show that both developed and emerging Islamic stock indices are influenced by conventional stock indices returns and money supply for both the low and high volatility regimes. However, the other macroeconomic variables fail to explain the dynamics of Islamic stock indices especially in the high volatility regime. Similar conclusions are obtained by using the MS-VAR model.

  14. Body mass index and other anthropometric variables in children with sickle cell anaemia.

    Science.gov (United States)

    Odetunde, Odutola Israel; Chinawa, Josephat Maduabuchi; Achigbu, Kingsley Ihedioha; Achigbu, Eberechukwu O

    2016-01-01

    The objectives of this study were to determine the anthropometric variables of children with sickle cell anaemia and comparing it with those with normal haemoglobin genotype. A cross sectional study of anthropometric measurements was conducted over a period of six months. Children with sickle cell anaemia in steady state aged between 6-20 years were recruited. Nutritional assessment was done using anthropometrical variables. Data were analyzed using the Statistical Package for Social Sciences program (SPSS), version 20. The sickle cell patients comprised of 20 males and 20 females. There were an equal number of controls with an equal male to female ratio of 1:1. Forty eight percent (19) of the children with sickle cell anemia were underweight (sickle cell anemia were low when compared with children with normal Haemoglobin genotype.

  15. Are Macro variables good predictors? A prediction based on the number of total medals acquired

    Directory of Open Access Journals (Sweden)

    Shahram Shafiee

    2012-01-01

    Full Text Available A large amount of effort is spent on forecasting the outcome of sporting events. Moreover, there are large quantities of data regarding the outcomes of sporting events and the factors which are assumed to contribute to those outcomes. In this paper we tried to predict the success of nations at the Asian Games through macro-economic, political, social and cultural variables. we used the information of variables include urban population, Education Expenditures, Age Structure, GDP Real Growth Rate, GDP Per Capita, Unemployment Rate, Population, Inflation Average, current account balance, life expectancy at birth and Merchandise Trade for all of the participating countries in Asian Games from 1970 to 2006 in order to build the model and then this model was tested by the information of variables in 2010. The prediction is based on the number of total medals acquired each country. In this research we used WEKA software that is a popular suite of machine learning software written in Java. The value of correlation coefficient between the predicted and original ranks is 90.42%. Neural Network Model, between 28 countries mentioned, predicts their ranks according to the maximum difference between predicted and original ranks of 19 countries (67.85% is 3, the maximum difference between predicted and original ranks of 8 countries (28.57% is between 4 to 6 and the difference between predicted and original ranks of 1 countries (3.57% is more than 6.

  16. Fatigue life prediction of rotor blade composites: Validation of constant amplitude formulations with variable amplitude experiments

    International Nuclear Information System (INIS)

    Westphal, T; Nijssen, R P L

    2014-01-01

    The effect of Constant Life Diagram (CLD) formulation on the fatigue life prediction under variable amplitude (VA) loading was investigated based on variable amplitude tests using three different load spectra representative for wind turbine loading. Next to the Wisper and WisperX spectra, the recently developed NewWisper2 spectrum was used. Based on these variable amplitude fatigue results the prediction accuracy of 4 CLD formulations is investigated. In the study a piecewise linear CLD based on the S-N curves for 9 load ratios compares favourably in terms of prediction accuracy and conservativeness. For the specific laminate used in this study Boerstra's Multislope model provides a good alternative at reduced test effort

  17. Fatigue life prediction of rotor blade composites: Validation of constant amplitude formulations with variable amplitude experiments

    Science.gov (United States)

    Westphal, T.; Nijssen, R. P. L.

    2014-12-01

    The effect of Constant Life Diagram (CLD) formulation on the fatigue life prediction under variable amplitude (VA) loading was investigated based on variable amplitude tests using three different load spectra representative for wind turbine loading. Next to the Wisper and WisperX spectra, the recently developed NewWisper2 spectrum was used. Based on these variable amplitude fatigue results the prediction accuracy of 4 CLD formulations is investigated. In the study a piecewise linear CLD based on the S-N curves for 9 load ratios compares favourably in terms of prediction accuracy and conservativeness. For the specific laminate used in this study Boerstra's Multislope model provides a good alternative at reduced test effort.

  18. Optimal no-go theorem on hidden-variable predictions of effect expectations

    Science.gov (United States)

    Blass, Andreas; Gurevich, Yuri

    2018-03-01

    No-go theorems prove that, under reasonable assumptions, classical hidden-variable theories cannot reproduce the predictions of quantum mechanics. Traditional no-go theorems proved that hidden-variable theories cannot predict correctly the values of observables. Recent expectation no-go theorems prove that hidden-variable theories cannot predict the expectations of observables. We prove the strongest expectation-focused no-go theorem to date. It is optimal in the sense that the natural weakenings of the assumptions and the natural strengthenings of the conclusion make the theorem fail. The literature on expectation no-go theorems strongly suggests that the expectation-focused approach is more general than the value-focused one. We establish that the expectation approach is not more general.

  19. Obesity Index That Better Predict Metabolic Syndrome: Body Mass Index, Waist Circumference, Waist Hip Ratio, or Waist Height Ratio

    Directory of Open Access Journals (Sweden)

    Abdulbari Bener

    2013-01-01

    Full Text Available Aim. The aim was to compare body mass index (BMI, waist circumference (WC, waist hip ratio (WHR, and waist height ratio (WHtR to identify the best predictor of metabolic syndrome (MetS among Qatari adult population. Methods. A cross-sectional survey from April 2011 to December 2012. Data was collected from 1552 participants followed by blood sampling. MetS was defined according to Third Adult Treatment Panel (ATPIII and International Diabetes Federation (IDF. Receiver operating characteristics (ROC curve analysis was performed. Results. Among men, WC followed by WHR and WHtR yielded the highest area under the curve (AUC (0.78; 95% CI 0.74–0.82 and 0.75; 95% CI 0.71–0.79, resp.. Among women, WC followed by WHtR yielded the highest AUC (0.81; 95% CI 0.78–0.85 & 0.79; 95% CI 0.76–0.83, resp.. Among men, WC at a cut-off 99.5 cm resulted in the highest Youden index with sensitivity 81.6% and 63.9% specificity. Among women, WC at a cut-off 91 cm resulted in the highest Youden index with the corresponding sensitivity and specificity of 86.5% and 64.7%, respectively. BMI had the lowest sensitivity and specificity in both genders. Conclusion. WC at cut-off 99.5 cm in men and 91 cm in women was the best predictor of MetS in Qatar.

  20. Understanding interannual, decadal level variability in paralytic shellfish poisoning toxicity in the Gulf of Maine: The HAB Index

    Science.gov (United States)

    Anderson, Donald M.; Couture, Darcie A.; Kleindinst, Judith L.; Keafer, Bruce A.; McGillicuddy, Dennis J., Jr.; Martin, Jennifer L.; Richlen, Mindy L.; Hickey, J. Michael; Solow, Andrew R.

    2014-05-01

    A major goal in harmful algal bloom (HAB) research has been to identify mechanisms underlying interannual variability in bloom magnitude and impact. Here the focus is on variability in Alexandrium fundyense blooms and paralytic shellfish poisoning (PSP) toxicity in Maine, USA, over 34 years (1978-2011). The Maine coastline was divided into two regions - eastern and western Maine, and within those two regions, three measures of PSP toxicity (the percent of stations showing detectable toxicity over the year, the cumulative amount of toxicity per station measured in all shellfish (mussel) samples during that year, and the duration of measurable toxicity) were examined for each year in the time series. These metrics were combined into a simple HAB Index that provides a single measure of annual toxin severity across each region. The three toxin metrics, as well as the HAB Index that integrates them, reveal significant variability in overall toxicity between individual years as well as long-term, decadal patterns or regimes. Based on different conceptual models of the system, we considered three trend formulations to characterize the long-term patterns in the Index - a three-phase (mean-shift) model, a linear two-phase model, and a pulse-decline model. The first represents a “regime shift” or multiple equilibria formulation as might occur with alternating periods of sustained high and low cyst abundance or favorable and unfavorable growth conditions, the second depicts a scenario of more gradual transitions in cyst abundance or growth conditions of vegetative cells, and the third characterizes a ”sawtooth” pattern in which upward shifts in toxicity are associated with major cyst recruitment events, followed by a gradual but continuous decline until the next pulse. The fitted models were compared using both residual sum of squares and Akaike's Information Criterion. There were some differences between model fits, but none consistently gave a better fit than the

  1. Effects of growth reducer and nitrogen fertilization on morphological variables, SPAD index, interception of radiation and productivity of wheat

    OpenAIRE

    Elvis Felipe Elli; Braulio Otomar Caron; Sandro Luis Petter Medeiros; Elder Eloy; Gean Charles Monteiro; Denise Schmidt

    2015-01-01

    ABSTRACT The objective of this study was to evaluate the effect of growth reducer and nitrogen fertilization on morphological variables, SPAD index, radiation interception, and grain yield of three cultivars of wheat. The experimental design was a randomized block in factorial scheme 3x5x2, with three cultivars (Mestre, Iguaçú and Itaipú), five nitrogen doses (0, 40, 80, 120, 160 Kg ha-1), and application or no application of a growth reducer, with three replications. The following characteri...

  2. Portfolio theory of optimal isometric force production: Variability predictions and nonequilibrium fluctuation dissipation theorem

    Science.gov (United States)

    Frank, T. D.; Patanarapeelert, K.; Beek, P. J.

    2008-05-01

    We derive a fundamental relationship between the mean and the variability of isometric force. The relationship arises from an optimal collection of active motor units such that the force variability assumes a minimum (optimal isometric force). The relationship is shown to be independent of the explicit motor unit properties and of the dynamical features of isometric force production. A constant coefficient of variation in the asymptotic regime and a nonequilibrium fluctuation-dissipation theorem for optimal isometric force are predicted.

  3. Portfolio theory of optimal isometric force production: Variability predictions and nonequilibrium fluctuation-dissipation theorem

    International Nuclear Information System (INIS)

    Frank, T.D.; Patanarapeelert, K.; Beek, P.J.

    2008-01-01

    We derive a fundamental relationship between the mean and the variability of isometric force. The relationship arises from an optimal collection of active motor units such that the force variability assumes a minimum (optimal isometric force). The relationship is shown to be independent of the explicit motor unit properties and of the dynamical features of isometric force production. A constant coefficient of variation in the asymptotic regime and a nonequilibrium fluctuation-dissipation theorem for optimal isometric force are predicted

  4. PREDICTION OF OUTCOME USING THE MANNHEIM PERITONITIS INDEX IN CASES OF PERITONITIS

    Directory of Open Access Journals (Sweden)

    Sanjeev

    2015-08-01

    Full Text Available BACKGROUND: Peritonitis still presents an extremely common & dreaded problem in emergency surgery. Despite aggressive surgical techniques, the prognosis of peritonitis and intra - abdominal sepsis is very poor, especially when multiple organ failure develops. Therefore early objective & reliable classification of the severity of peritonitis and intra - abdominal sepsis is needed not only to predict prognosis & to select patients for these aggressive surgical techniques but also to evaluate & compare the results of different treatment regimens. So, in this prospective st udy of 60 cases of peritonitis, the reliability of the Mannheim peritonitis index is assessed & its predictive power evaluated. MATERIALS & METHOD S : This prospective study was carried out in the department of surgery, GMCH, Udaipur from June 2014 to June 2 015 after taking the permission from institutional ethics committee. Patients from both sexes of various age groups having peritonitis of varied aetiology & who had undergone laparotomy were taken. A detailed history, thorough clinical examination & necess ary investigations were performed in e ach case according to planned p r o forma. After resuscitation laparotomy was done & operative findings were noted carefully and a proper note on the progress of each patient was maintained and any complications encounter ed were noted. So, early classification of patients presenting with peritonitis by means of objective scoring system was done to select patients for aggressive surgery & overall morbidity & mortality were analyzed. RESULTS: Total 60 patients of peritonitis were examined and common causes were peptic (61.6%, typhoid (21.6% and appendicular (8.3 %. Most common age group was found to be 21 to 50 years and male to female ratio was 4:1. Peritonitis was more common in patients involved in hard work and chronic Be di smokers (61.6%. About 46% of patients who presented for treatment within 48 hours of onset of illness

  5. Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models

    Directory of Open Access Journals (Sweden)

    B. M. Brentan

    2017-01-01

    Full Text Available Operational and economic aspects of water distribution make water demand forecasting paramount for water distribution systems (WDSs management. However, water demand introduces high levels of uncertainty in WDS hydraulic models. As a result, there is growing interest in developing accurate methodologies for water demand forecasting. Several mathematical models can serve this purpose. One crucial aspect is the use of suitable predictive variables. The most used predictive variables involve weather and social aspects. To improve the interrelation knowledge between water demand and various predictive variables, this study applies three algorithms, namely, classical Principal Component Analysis (PCA and machine learning powerful algorithms such as Self-Organizing Maps (SOMs and Random Forest (RF. We show that these last algorithms help corroborate the results found by PCA, while they are able to unveil hidden features for PCA, due to their ability to cope with nonlinearities. This paper presents a correlation study of three district metered areas (DMAs from Franca, a Brazilian city, exploring weather and social variables to improve the knowledge of residential demand for water. For the three DMAs, temperature, relative humidity, and hour of the day appear to be the most important predictive variables to build an accurate regression model.

  6. [EVALUATION OF THE BODY ADIPOSITY INDEX IN PREDICTING PERCENTAGE BODY FAT AMONG COLOMBIAN ADULTS].

    Science.gov (United States)

    González-Ruíz, Katherine; Correa-Bautista, Jorge Enrique; Ramírez-Vélez, Robinson

    2015-07-01

    the body adiposity index (BAI) is a new simplistic method for predicting body fat percentage (BF%) via a simple equation of hip circumference to height. Up to now, few studies have evaluated the performance of BAI in determining excess fat in Colombians. The aim of this study was to evaluate the usefulness of BAI as a predictor of body fat in among Colombian adults. cross-sectional study carried out in a sample of 204 male belonging to the education sector from Bogotá, Colombia. BAI was calculated based on the equation reported in the Bergman et al. %BF determined by tetrapolar bioimpedance analysis (BIA) was used as the reference measure of adiposity. Bland-Altman analysis was used to assess the agreement between the two methods: BAI and BIA. Associations between anthropometric measures of adiposity were investigated by Pearson correlation analysis. in general pupulation, the BAI overestimates %BF (mean difference: 12.5 % [95%CI = -4.04 % to -21.02 %]), mainly at lower levels of adiposity (mean difference: 10.2 ± 3.3). Significant correlations were found between BAI and all measurements, being the strongest-moderate correlation with %BF (r = 0.777, p Colombian adults and has a tendency to provide overestimated values as BF% decreases. Therefore, this method can be a useful tool to predict %BF in Colombian adults, although it has some limitations. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

  7. Epileptic Seizure Prediction Using a New Similarity Index for Chaotic Signals

    Science.gov (United States)

    Niknazar, Hamid; Nasrabadi, Ali Motie

    Epileptic seizures are generated by abnormal activity of neurons. The prediction of epileptic seizures is an important issue in the field of neurology, since it may improve the quality of life of patients suffering from drug resistant epilepsy. In this study a new similarity index based on symbolic dynamic techniques which can be used for extracting behavior of chaotic time series is presented. Using Freiburg EEG dataset, it is found that the method is able to detect the behavioral changes of the neural activity prior to epileptic seizures, so it can be used for prediction of epileptic seizure. A sensitivity of 63.75% with 0.33 false positive rate (FPR) in all 21 patients and sensitivity of 96.66% with 0.33 FPR in eight patients were achieved using the proposed method. Moreover, the method was evaluated by applying on Logistic and Tent map with different parameters to demonstrate its robustness and ability in determining similarity between two time series with the same chaotic characterization.

  8. Bayesian data fusion for spatial prediction of categorical variables in environmental sciences

    Science.gov (United States)

    Gengler, Sarah; Bogaert, Patrick

    2014-12-01

    First developed to predict continuous variables, Bayesian Maximum Entropy (BME) has become a complete framework in the context of space-time prediction since it has been extended to predict categorical variables and mixed random fields. This method proposes solutions to combine several sources of data whatever the nature of the information. However, the various attempts that were made for adapting the BME methodology to categorical variables and mixed random fields faced some limitations, as a high computational burden. The main objective of this paper is to overcome this limitation by generalizing the Bayesian Data Fusion (BDF) theoretical framework to categorical variables, which is somehow a simplification of the BME method through the convenient conditional independence hypothesis. The BDF methodology for categorical variables is first described and then applied to a practical case study: the estimation of soil drainage classes using a soil map and point observations in the sandy area of Flanders around the city of Mechelen (Belgium). The BDF approach is compared to BME along with more classical approaches, as Indicator CoKringing (ICK) and logistic regression. Estimators are compared using various indicators, namely the Percentage of Correctly Classified locations (PCC) and the Average Highest Probability (AHP). Although BDF methodology for categorical variables is somehow a simplification of BME approach, both methods lead to similar results and have strong advantages compared to ICK and logistic regression.

  9. Bayesian data fusion for spatial prediction of categorical variables in environmental sciences

    International Nuclear Information System (INIS)

    Gengler, Sarah; Bogaert, Patrick

    2014-01-01

    First developed to predict continuous variables, Bayesian Maximum Entropy (BME) has become a complete framework in the context of space-time prediction since it has been extended to predict categorical variables and mixed random fields. This method proposes solutions to combine several sources of data whatever the nature of the information. However, the various attempts that were made for adapting the BME methodology to categorical variables and mixed random fields faced some limitations, as a high computational burden. The main objective of this paper is to overcome this limitation by generalizing the Bayesian Data Fusion (BDF) theoretical framework to categorical variables, which is somehow a simplification of the BME method through the convenient conditional independence hypothesis. The BDF methodology for categorical variables is first described and then applied to a practical case study: the estimation of soil drainage classes using a soil map and point observations in the sandy area of Flanders around the city of Mechelen (Belgium). The BDF approach is compared to BME along with more classical approaches, as Indicator CoKringing (ICK) and logistic regression. Estimators are compared using various indicators, namely the Percentage of Correctly Classified locations (PCC) and the Average Highest Probability (AHP). Although BDF methodology for categorical variables is somehow a simplification of BME approach, both methods lead to similar results and have strong advantages compared to ICK and logistic regression

  10. [Cardiac rhythm variability as an index of vegetative heart regulation in a situation of psychoemotional tension].

    Science.gov (United States)

    Revina, N E

    2006-01-01

    Differentiated role of segmental and suprasegmental levels of cardiac rhythm variability regulation in dynamics of motivational human conflict was studied for the first time. The author used an original method allowing simultaneous analysis of psychological and physiological parameters of human activity. The study demonstrates that will and anxiety, as components of motivational activity spectrum, form the "energetic" basis of voluntary-constructive and involuntary-affective behavioral strategies, selectively uniting various levels of suprasegmental and segmental control of human heart functioning in a conflict situation.

  11. Days on radiosensitivity: individual variability and predictive tests; Radiosensibilite: variabilite individuelle et tests predictifs

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2008-07-01

    The radiosensitivity is a part of usual clinical observations. It is already included in the therapy protocols. however, some questions stay on its individual variability and on the difficulty to evaluate it. The point will be stocked on its origin and its usefulness in predictive medicine. Through examples on the use of predictive tests and ethical and legal questions that they raise, concrete cases will be presented by specialists such radio biologists, geneticists, immunologists, jurists and occupational physicians. (N.C.)

  12. Scaling prediction errors to reward variability benefits error-driven learning in humans.

    Science.gov (United States)

    Diederen, Kelly M J; Schultz, Wolfram

    2015-09-01

    Effective error-driven learning requires individuals to adapt learning to environmental reward variability. The adaptive mechanism may involve decays in learning rate across subsequent trials, as shown previously, and rescaling of reward prediction errors. The present study investigated the influence of prediction error scaling and, in particular, the consequences for learning performance. Participants explicitly predicted reward magnitudes that were drawn from different probability distributions with specific standard deviations. By fitting the data with reinforcement learning models, we found scaling of prediction errors, in addition to the learning rate decay shown previously. Importantly, the prediction error scaling was closely related to learning performance, defined as accuracy in predicting the mean of reward distributions, across individual participants. In addition, participants who scaled prediction errors relative to standard deviation also presented with more similar performance for different standard deviations, indicating that increases in standard deviation did not substantially decrease "adapters'" accuracy in predicting the means of reward distributions. However, exaggerated scaling beyond the standard deviation resulted in impaired performance. Thus efficient adaptation makes learning more robust to changing variability. Copyright © 2015 the American Physiological Society.

  13. Remote detection of water stress conditions via a diurnal photochemical reflectance index (PRI) improves yield prediction in rainfed wheat

    Science.gov (United States)

    Magney, T. S.; Vierling, L. A.; Eitel, J.

    2014-12-01

    Employing remotely sensed techniques to quantify the existence and magnitude of midday photosynthetic downregulation using the photochemical reflectance index (PRI) may reveal new information about plant responses to abiotic stressors in space and time. However, the interpretation and application of the PRI can be confounded because of its sensitivity to several variables changing at the diurnal (e.g., irradiation, shadow fraction) and seasonal (e.g., leaf area, chlorophyll and carotene pigment concentrations, irradiation) time scales. We explored different techniques to correct the PRI for variations in canopy structure and relative chlorophyll content (ChlR) using highly temporally resolved (frequency = five minutes) in-situ radiometric measurements of PRI and the Normalized Difference Vegetation Index (NDVI) over eight soft white spring wheat (Triticum aestivum L.)field plots under varying nitrogen and soil water conditions over two seasons. Our results suggest that the influence of seasonal variation in canopy ChlR and LAI on the diurnally measured PRI (PRIdiurnal) can be minimized using simple correction techniques, therefore improving the strength of PRI as a tool to quantify abiotic stressors such as daily changes in soil volumetric water content (SVWC), and vapor pressure deficit (VPD). PRIdiurnal responded strongly to available nitrogen, and linearly tracked seasonal changes in SVWC, VPD, and stomatal conductance (gc). Utilizing the PRI as an indicator of stress, yield predictions significantly over greenness indices such as the NDVI. This study provides insight towards the future interpretation and scaling of PRI to quantify rapid changes in photosynthesis, and as an indicator of plant stress.

  14. Heart rate variability indexes as a marker of chronic adaptation in athletes: a systematic review.

    Science.gov (United States)

    da Silva, Vanessa Pereira; de Oliveira, Natacha Alves; Silveira, Heitor; Mello, Roger Gomes Tavares; Deslandes, Andrea Camaz

    2015-03-01

    Regular exercise promotes functional and structural changes in the central and peripheral mechanisms of the cardiovascular system. Heart rate variability (HRV) measurement provides a sensitive indicator of the autonomic balance. However, because of the diversity of methods and variables used, the results are difficult to compare in the sports sciences. Since the protocol (supine, sitting, or standing position) and measure (time or frequency domain) are not well defined, the aim of this study is to investigate the HRV measures that better indicates the chronic adaptations of physical exercise in athletes. PubMed (MEDLINE), Web of Science, SciELO (Scientific Electronic Library), and Scopus databases were consulted. Original complete articles in English with short-term signals evaluating young and adult athletes, between 17 and 40 years old, with a control group, published up to 2013 were included. Selected 19 of 1369 studies, for a total sample pool of 333 male and female athletes who practice different sports. The main protocols observed were the supine or standing positions in free or controlled breathing conditions. The main statistical results found in this study were the higher mean RR, standard deviation of RR intervals, and high frequency in athletes group. In addition, the analyses of Cohen's effect size showed that factors as modality of sport, protocol used and unit of measure selected could influence this expected results. Our findings indicate that time domain measures are more consistent than frequency domain to describe the chronic cardiovascular autonomic adaptations in athletes. © 2014 Wiley Periodicals, Inc.

  15. The estimation of soil parameters using observations on crop biophysical variables and the crop model STICS improve the predictions of agro environmental variables.

    Science.gov (United States)

    Varella, H.-V.

    2009-04-01

    Dynamic crop models are very useful to predict the behavior of crops in their environment and are widely used in a lot of agro-environmental work. These models have many parameters and their spatial application require a good knowledge of these parameters, especially of the soil parameters. These parameters can be estimated from soil analysis at different points but this is very costly and requires a lot of experimental work. Nevertheless, observations on crops provided by new techniques like remote sensing or yield monitoring, is a possibility for estimating soil parameters through the inversion of crop models. In this work, the STICS crop model is studied for the wheat and the sugar beet and it includes more than 200 parameters. After a previous work based on a large experimental database for calibrate parameters related to the characteristics of the crop, a global sensitivity analysis of the observed variables (leaf area index LAI and absorbed nitrogen QN provided by remote sensing data, and yield at harvest provided by yield monitoring) to the soil parameters is made, in order to determine which of them have to be estimated. This study was made in different climatic and agronomic conditions and it reveals that 7 soil parameters (4 related to the water and 3 related to the nitrogen) have a clearly influence on the variance of the observed variables and have to be therefore estimated. For estimating these 7 soil parameters, a Bayesian data assimilation method is chosen (because of available prior information on these parameters) named Importance Sampling by using observations, on wheat and sugar beet crop, of LAI and QN at various dates and yield at harvest acquired on different climatic and agronomic conditions. The quality of parameter estimation is then determined by comparing the result of parameter estimation with only prior information and the result with the posterior information provided by the Bayesian data assimilation method. The result of the

  16. Improved variable reduction in partial least squares modelling based on predictive-property-ranked variables and adaptation of partial least squares complexity.

    Science.gov (United States)

    Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

    2011-10-31

    The calibration performance of partial least squares for one response variable (PLS1) can be improved by elimination of uninformative variables. Many methods are based on so-called predictive variable properties, which are functions of various PLS-model parameters, and which may change during the variable reduction process. In these methods variable reduction is made on the variables ranked in descending order for a given variable property. The methods start with full spectrum modelling. Iteratively, until a specified number of remaining variables is reached, the variable with the smallest property value is eliminated; a new PLS model is calculated, followed by a renewed ranking of the variables. The Stepwise Variable Reduction methods using Predictive-Property-Ranked Variables are denoted as SVR-PPRV. In the existing SVR-PPRV methods the PLS model complexity is kept constant during the variable reduction process. In this study, three new SVR-PPRV methods are proposed, in which a possibility for decreasing the PLS model complexity during the variable reduction process is build in. Therefore we denote our methods as PPRVR-CAM methods (Predictive-Property-Ranked Variable Reduction with Complexity Adapted Models). The selective and predictive abilities of the new methods are investigated and tested, using the absolute PLS regression coefficients as predictive property. They were compared with two modifications of existing SVR-PPRV methods (with constant PLS model complexity) and with two reference methods: uninformative variable elimination followed by either a genetic algorithm for PLS (UVE-GA-PLS) or an interval PLS (UVE-iPLS). The performance of the methods is investigated in conjunction with two data sets from near-infrared sources (NIR) and one simulated set. The selective and predictive performances of the variable reduction methods are compared statistically using the Wilcoxon signed rank test. The three newly developed PPRVR-CAM methods were able to retain

  17. Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

    Science.gov (United States)

    Wimmer, Valentin; Lehermeier, Christina; Albrecht, Theresa; Auinger, Hans-Jürgen; Wang, Yu; Schön, Chris-Carolin

    2013-10-01

    In genome-based prediction there is considerable uncertainty about the statistical model and method required to maximize prediction accuracy. For traits influenced by a small number of quantitative trait loci (QTL), predictions are expected to benefit from methods performing variable selection [e.g., BayesB or the least absolute shrinkage and selection operator (LASSO)] compared to methods distributing effects across the genome [ridge regression best linear unbiased prediction (RR-BLUP)]. We investigate the assumptions underlying successful variable selection by combining computer simulations with large-scale experimental data sets from rice (Oryza sativa L.), wheat (Triticum aestivum L.), and Arabidopsis thaliana (L.). We demonstrate that variable selection can be successful when the number of phenotyped individuals is much larger than the number of causal mutations contributing to the trait. We show that the sample size required for efficient variable selection increases dramatically with decreasing trait heritabilities and increasing extent of linkage disequilibrium (LD). We contrast and discuss contradictory results from simulation and experimental studies with respect to superiority of variable selection methods over RR-BLUP. Our results demonstrate that due to long-range LD, medium heritabilities, and small sample sizes, superiority of variable selection methods cannot be expected in plant breeding populations even for traits like FRIGIDA gene expression in Arabidopsis and flowering time in rice, assumed to be influenced by a few major QTL. We extend our conclusions to the analysis of whole-genome sequence data and infer upper bounds for the number of causal mutations which can be identified by LASSO. Our results have major impact on the choice of statistical method needed to make credible inferences about genetic architecture and prediction accuracy of complex traits.

  18. Conventional heart rate variability analysis of ambulatory electrocardiographic recordings fails to predict imminent ventricular fibrillation

    Science.gov (United States)

    Vybiral, T.; Glaeser, D. H.; Goldberger, A. L.; Rigney, D. R.; Hess, K. R.; Mietus, J.; Skinner, J. E.; Francis, M.; Pratt, C. M.

    1993-01-01

    OBJECTIVES. The purpose of this report was to study heart rate variability in Holter recordings of patients who experienced ventricular fibrillation during the recording. BACKGROUND. Decreased heart rate variability is recognized as a long-term predictor of overall and arrhythmic death after myocardial infarction. It was therefore postulated that heart rate variability would be lowest when measured immediately before ventricular fibrillation. METHODS. Conventional indexes of heart rate variability were calculated from Holter recordings of 24 patients with structural heart disease who had ventricular fibrillation during monitoring. The control group consisted of 19 patients with coronary artery disease, of comparable age and left ventricular ejection fraction, who had nonsustained ventricular tachycardia but no ventricular fibrillation. RESULTS. Heart rate variability did not differ between the two groups, and no consistent trends in heart rate variability were observed before ventricular fibrillation occurred. CONCLUSIONS. Although conventional heart rate variability is an independent long-term predictor of adverse outcome after myocardial infarction, its clinical utility as a short-term predictor of life-threatening arrhythmias remains to be elucidated.

  19. Effects of growth reducer and nitrogen fertilization on morphological variables, SPAD index, interception of radiation and productivity of wheat

    Directory of Open Access Journals (Sweden)

    Elvis Felipe Elli

    2015-12-01

    Full Text Available ABSTRACT The objective of this study was to evaluate the effect of growth reducer and nitrogen fertilization on morphological variables, SPAD index, radiation interception, and grain yield of three cultivars of wheat. The experimental design was a randomized block in factorial scheme 3x5x2, with three cultivars (Mestre, Iguaçú and Itaipú, five nitrogen doses (0, 40, 80, 120, 160 Kg ha-1, and application or no application of a growth reducer, with three replications. The following characteristics were evaluated: plant height, SPAD index, leaf area index (LAI, Global Radiation Interception (GRI and grain yield. The Tukey test (p < 0.05 was used for the comparison between the means of cultivar and growth reducer factors, and for a regression analysis to evaluate N levels. Increasing the dose of nitrogen promotes an increase in LAI of plants of wheat crops differently among cultivars, which leads to a greater degree of global radiation interception. At doses higher or equal to 120 Kg ha-1 of nitrogen, there are significant differences in grain yield between treatments with and without the application of the growth reducer. The significant interaction between growth reducer and nitrogen dose, showed that applications of growth reducer increase the GRI at doses above and below 80 Kg ha-1 of nitrogen. Nitrogen rates of 138 and 109 Kg ha-1 are responsible for maximum grain yields of wheat, which is 4235 and 3787 Kg ha-1 with and without the use of growth reducer, respectively.

  20. A critical discussion on the applicability of Compound Topographic Index (CTI) for predicting ephemeral gully erosion

    Science.gov (United States)

    Casalí, Javier; Chahor, Youssef; Giménez, Rafael; Campo-Bescós, Miguel

    2016-04-01

    The so-called Compound Topographic Index (CTI) can be calculated for each grid cell in a DEM and be used to identify potential locations for ephemeral gullies (e. g.) based on land topography (CTI = A.S.PLANC, where A is upstream drainage area, S is local slope and PLANC is planform curvature, a measure of the landscape convergence) (Parker et al., 2007). It can be shown that CTI represents stream power per unit bed area and it considers the major parameters controlling the pattern and intensity of concentrated surface runoff in the field (Parker et al., 2007). However, other key variables controlling e.g. erosion (e. g. e.) such as soil characteristics, land-use and management, are not had into consideration. The critical CTI value (CTIc) "represents the intensity of concentrated overland flow necessary to initiate erosion and channelised flow under a given set of circumstances" (Parker et al., 2007). AnnAGNPS (Annualized Agriculture Non-Point Source) pollution model is an important management tool developed by (USDA) and uses CTI to locate potential ephemeral gullies. Then, and depending on rainfall characteristics of the period simulated by AnnAGNPS, potential e. g. can become "actual", and be simulated by the model accordingly. This paper presents preliminary results and a number of considerations after evaluating the CTI tool in Navarre. CTIc values found are similar to those cited by other authors, and the e. g. networks that on average occur in the area have been located reasonably well. After our experience we believe that it is necessary to distinguish between the CTIc corresponding to the location of headcuts whose migrations originate the e. g. (CTIc1); and the CTIc necessary to represent the location of the gully networks in the watershed (CTIc2), where gully headcuts are located in the upstream end of the gullies. Most scientists only consider one CTIc value, although, from our point of view, the two situations are different. CTIc1 would represent the

  1. Left Atrial Volume Index and Prediction of Events in Acute Coronary Syndrome: Solar Registry

    Directory of Open Access Journals (Sweden)

    Jose Alves Secundo Junior

    2014-10-01

    Full Text Available Background: According to some international studies, patients with acute coronary syndrome (ACS and increased left atrial volume index (LAVI have worse long-term prognosis. However, national Brazilian studies confirming this prediction are still lacking. Objective: To evaluate LAVI as a predictor of major cardiovascular events (MCE in patients with ACS during a 365-day follow-up. Methods: Prospective cohort of 171 patients diagnosed with ACS whose LAVI was calculated within 48 hours after hospital admission. According to LAVI, two groups were categorized: normal LAVI (≤ 32 mL/m2 and increased LAVI (> 32 mL/m2. Both groups were compared regarding clinical and echocardiographic characteristics, in- and out-of-hospital outcomes, and occurrence of ECM in up to 365 days. Results: Increased LAVI was observed in 78 patients (45%, and was associated with older age, higher body mass index, hypertension, history of myocardial infarction and previous angioplasty, and lower creatinine clearance and ejection fraction. During hospitalization, acute pulmonary edema was more frequent in patients with increased LAVI (14.1% vs. 4.3%, p = 0.024. After discharge, the occurrence of combined outcome for MCE was higher (p = 0.001 in the group with increased LAVI (26% as compared to the normal LAVI group (7% [RR (95% CI = 3.46 (1.54-7.73 vs. 0.80 (0.69-0.92]. After Cox regression, increased LAVI increased the probability of MCE (HR = 3.08, 95% CI = 1.28-7.40, p = 0.012. Conclusion: Increased LAVI is an important predictor of MCE in a one-year follow-up.

  2. Avoiding transthoracic echocardiography and transesophageal echocardiography for patients with variable body mass indexes in infective endocarditis

    Directory of Open Access Journals (Sweden)

    Robert Sogomonian

    2016-04-01

    Full Text Available Background: Echocardiography has been a popular modality used to aid in the diagnosis of infective endocarditis (IE with the modified Duke criteria. We evaluated the necessity between the uses of either a transthoracic echocardiography (TTE or transesophageal echocardiography (TEE in patients with a body mass index (BMI greater than or equal to 25 kg/m2 and less than 25 kg/m2. Methods: A single-centered, retrospective study of 198 patients between 2005 and 2012 diagnosed with IE based on modified Duke criteria. Patients, required to be above age 18, had undergone an echocardiogram study and had blood cultures to be included in the study. Results: Among 198 patients, two echocardiographic groups were evaluated as 158 patients obtained a TTE, 143 obtained a TEE, and 103 overlapped with TEE and TTE. Out of these patients, 167 patients were included in the study as 109 (65% were discovered to have native valve vegetations on TEE and 58 (35% with TTE. TTE findings were compared with TEE results for true negatives and positives to isolate valvular vegetations. Overall sensitivity of TTE was calculated to be 67% with a specificity of 93%. Patients were further divided into two groups with the first group having a BMI ≥25 kg/m2 and the subsequent group with a BMI <25 kg/m2. Patients with a BMI ≥25 kg/m2 who underwent a TTE study had a sensitivity and specificity of 54 and 92%, respectively. On the contrary, patients with a BMI < 25 kg/m2 had a TTE sensitivity and specificity of 78 and 95%, respectively. Conclusions: Patients with a BMI <25 kg/m2 and a negative TTE should refrain from further diagnostic studies, with TEE strong clinical judgment is warranted. Patients with a BMI ≥ 25 kg/m2 may proceed directly to TEE as the initial study, possibly avoiding an additional study with a TTE.

  3. Predicting suicidal ideation in primary care: An approach to identify easily assessable key variables.

    Science.gov (United States)

    Jordan, Pascal; Shedden-Mora, Meike C; Löwe, Bernd

    To obtain predictors of suicidal ideation, which can also be used for an indirect assessment of suicidal ideation (SI). To create a classifier for SI based on variables of the Patient Health Questionnaire (PHQ) and sociodemographic variables, and to obtain an upper bound on the best possible performance of a predictor based on those variables. From a consecutive sample of 9025 primary care patients, 6805 eligible patients (60% female; mean age = 51.5 years) participated. Advanced methods of machine learning were used to derive the prediction equation. Various classifiers were applied and the area under the curve (AUC) was computed as a performance measure. Classifiers based on methods of machine learning outperformed ordinary regression methods and achieved AUCs around 0.87. The key variables in the prediction equation comprised four items - namely feelings of depression/hopelessness, low self-esteem, worrying, and severe sleep disturbances. The generalized anxiety disorder scale (GAD-7) and the somatic symptom subscale (PHQ-15) did not enhance prediction substantially. In predicting suicidal ideation researchers should refrain from using ordinary regression tools. The relevant information is primarily captured by the depression subscale and should be incorporated in a nonlinear model. For clinical practice, a classification tree using only four items of the whole PHQ may be advocated. Copyright © 2018 Elsevier Inc. All rights reserved.

  4. Beyond the mean: the role of variability in predicting ecological effects of stream temperature on salmon

    Science.gov (United States)

    E. Ashley Steel; Abby Tillotson; Donald A. Larson; Aimee H. Fullerton; Keith P. Denton; Brian R. Beckman

    2012-01-01

    Alterations in variance of riverine thermal regimes have been observed and are predicted with climate change and human development. We tested whether changes in daily or seasonal thermal variability, aside from changes in mean temperature, could have biological consequences by exposing Chinook salmon (Oncorhynchus tshawytscha) eggs to eight...

  5. Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

    Science.gov (United States)

    Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

    2017-12-01

    Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

  6. Predictive Value of Triglyceride Glucose Index for the Risk of Incident Diabetes: A 4-Year Retrospective Longitudinal Study

    OpenAIRE

    Lee, Da Young; Lee, Eun Seo; Kim, Ji Hyun; Park, Se Eun; Park, Cheol-Young; Oh, Ki-Won; Park, Sung-Woo; Rhee, Eun-Jung; Lee, Won-Young

    2016-01-01

    The Triglyceride Glucose Index (TyG index) is considered a surrogate marker of insulin resistance. The aim of this study is to investigate whether the TyG index has a predictive role in identifying individuals with a high risk of incident diabetes and to compare it with other indicators of metabolic health. A total 2900 non-diabetic adults who attended five consecutive annual health check-ups at Kangbuk Samsung Hospital was divided into four subgroups using three methods: (1) baseline TyG ind...

  7. Vigorous physical activity predicts higher heart rate variability among younger adults.

    Science.gov (United States)

    May, Richard; McBerty, Victoria; Zaky, Adam; Gianotti, Melino

    2017-06-14

    Baseline heart rate variability (HRV) is linked to prospective cardiovascular health. We tested intensity and duration of weekly physical activity as predictors of heart rate variability in young adults. Time and frequency domain indices of HRV were calculated based on 5-min resting electrocardiograms collected from 82 undergraduate students. Hours per week of both moderate and vigorous activity were estimated using the International Physical Activity Questionnaire. In regression analyses, hours of vigorous physical activity, but not moderate activity, significantly predicted greater time domain and frequency domain indices of heart rate variability. Adjusted for weekly frequency, greater daily duration of vigorous activity failed to predict HRV indices. Future studies should test direct measurements of vigorous activity patterns as predictors of autonomic function in young adulthood.

  8. New considerations on variability of creep rupture data and life prediction

    International Nuclear Information System (INIS)

    Kim, Seon Jin; Jeong, Won Taek; Kong, Yu Sik

    2009-01-01

    This paper deals with the variability analysis of short term creep rupture test data based on the previous creep rupture tests and the possibility of the creep life prediction. From creep tests performed by constant uniaxial stresses at 600, 650 and 700 .deg. C elevated temperature, in order to investigate the variability of short-term creep rupture data, the creep curves were analyzed for normalized creep strain divided by initial strain. There are some variability in thee creep rupture data. And, the difference between general creep curves and normalized creep curves were obtained. The effects of the creep rupture time and state steady creep rate on the Weibull distribution parameters were investigated. There were good relation between normal Weibull parameters and normalized Weibull parameters. Finally, the predicted creep life were compared with the Monkman-Grant model.

  9. New Considerations on Variability of Creep Rupture Data and Life Prediction

    International Nuclear Information System (INIS)

    Jung, Won Taek; Kong, Yu Sik; Kim, Seon Jin

    2009-01-01

    This paper deals with the variability analysis of short term creep rupture test data based on the previous creep rupture tests and the possibility of the creep life prediction. From creep tests performed by constant uniaxial stresses at 600, 650 and 700 .deg. C elevated temperature, in order to investigate the variability of short-term creep rupture data, the creep curves were analyzed for normalized creep strain divided by initial strain. There are some variability in the creep rupture data. And, the difference between general creep curves and normalized creep curves were obtained. The effects of the creep rupture time (RT) and steady state creep rate (SSCR) on the Weibull distribution parameters were investigated. There were good relation between normal Weibull parameters and normalized Weibull parameters. Finally, the predicted creep life were compared with the Monkman-Grant model

  10. THE RELATIVE IMPORTANCE OF FINANCIAL RATIOS AND NONFINANCIAL VARIABLES IN PREDICTING OF INSOLVENCY

    Directory of Open Access Journals (Sweden)

    Ivica Pervan

    2013-02-01

    Full Text Available One of the most important decisions in every bank is approving loans to firms, which is based on evaluated credit risk and collateral. Namely, it is necessary to evaluate the risk that client will be unable to repay the obligations according to the contract. After Beaver's (1967 and Altman's (1968 seminal papers many authors extended the initial research by changing the methodology, samples, countries, etc. But majority of business failure papers as predictors use financial ratios, while in the real life banks combine financial and nonfinancial variables. In order to test predictive power of nonfinancial variables authors in the paper compare two insolvency prediction models. The first model that used financial rations resulted with classification accuracy of 82.8%, while the combined model with financial and nonfinancial variables resulted with classification accuracy of 88.1%.

  11. Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

    Science.gov (United States)

    Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

    2018-01-01

    Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.

  12. Asymptotically Constant-Risk Predictive Densities When the Distributions of Data and Target Variables Are Different

    Directory of Open Access Journals (Sweden)

    Keisuke Yano

    2014-05-01

    Full Text Available We investigate the asymptotic construction of constant-risk Bayesian predictive densities under the Kullback–Leibler risk when the distributions of data and target variables are different and have a common unknown parameter. It is known that the Kullback–Leibler risk is asymptotically equal to a trace of the product of two matrices: the inverse of the Fisher information matrix for the data and the Fisher information matrix for the target variables. We assume that the trace has a unique maximum point with respect to the parameter. We construct asymptotically constant-risk Bayesian predictive densities using a prior depending on the sample size. Further, we apply the theory to the subminimax estimator problem and the prediction based on the binary regression model.

  13. Predictive and Descriptive CoMFA Models: The Effect of Variable Selection.

    Science.gov (United States)

    Sepehri, Bakhtyar; Omidikia, Nematollah; Kompany-Zareh, Mohsen; Ghavami, Raouf

    2018-01-01

    Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  14. Climate Prediction Center (CPC) East Atlantic/ Western Russia Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the East Atlantic/ Western Russia teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated...

  15. Climate Prediction Center (CPC) Monthly Pacific North American Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Pacific/ North American teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated...

  16. Climate Prediction Center (CPC) East Pacific/ North Pacific Teleconnection Pattern Index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the East Pacific/ North Pacific teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated...

  17. Climate Prediction Center (CPC) Monthly North Atlantic Oscillation (NAO) teleconnection index

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the North Atlantic Oscillation (NAO) teleconnection pattern. The data spans the period 1950 to present. The index is derived from a...

  18. Predictive validity of the tobacco marketing receptivity index among non-smoking youth.

    Science.gov (United States)

    Braun, Sandra; Abad-Vivero, Erika Nayeli; Mejía, Raúl; Barrientos, Inti; Sargent, James D; Thrasher, James F

    2018-05-01

    In a previous cross-sectional study of early adolescents, we developed a marketing receptivity index (MRI) that integrates point-of-sale (PoS) marketing exposures, brand recall, and ownership of branded merchandise. The MRI had independent, positive associations with smoking susceptibility among never smokers and with current smoking behavior. The current longitudinal study assessed the MRI's predictive validity among adolescents who have never smoked cigarettes METHODS: Data come from a longitudinal, school-based survey of 33 secondary schools in Argentina. Students who had never smoked at baseline were followed up approximately 17months later (n=1700). Questions assessed: PoS marketing exposure by querying frequency of going to stores where tobacco is commonly sold; cued recall of brand names for 3 cigarette packages from dominant brands but with the brand name removed; and ownership of branded merchandise. A four-level MRI was derived: 1.low PoS marketing exposure only; 2. high PoS exposure or recall of 1 brand; 3. recall of 2 or more brands; and 4. ownership of branded merchandise. Logistic regression models regressed smoking initiation by follow up survey on the MRI, each of its components, and students' willingness to try a brand, adjusting for sociodemographics, social network smoking, and sensation seeking. The MRI had an independent positive association with smoking initiation. When analyzed separately, each MRI component was associated with outcomes except branded merchandise ownership. The MRI and its components were associated with smoking initiation, except for branded merchandise ownership, which may better predict smoking progression than initiation. The MRI appears valid and useful for future studies. Copyright © 2018 Elsevier Ltd. All rights reserved.

  19. Prostate Health Index (PHI) Predicts High-stage Pathology in African American Men.

    Science.gov (United States)

    Schwen, Zeyad R; Tosoian, Jeffrey J; Sokoll, Lori J; Mangold, Leslie; Humphreys, Elizabeth; Schaeffer, Edward M; Partin, Alan W; Ross, Ashley E

    2016-04-01

    To evaluate the association between the Prostate Health Index (PHI) and adverse pathology in a cohort of African American (AA) men undergoing radical prostatectomy. Eighty AA men with prostate-specific antigen (PSA) of 2-10 ng/mL underwent measurement of PSA, free PSA (fPSA), and p2PSA prior to radical prostatectomy. PHI was calculated as [(p2PSA/fPSA) × (PSA)(½)]. Biomarker association with pT3 disease was assessed using logistic regression, and covariates were added to a baseline multivariable model including digital rectal examination. Biomarker ability to predict pT3 disease was measured using the area under the receiver operator characteristic curve. Sixteen men (20%) demonstrated pT3 disease on final pathology. Mean age, PSA, and %fPSA were similar in men with and without pT3 disease (all P  >  .05), whereas PHI was significantly greater in men with pT3 disease (mean 57.2 vs 46.6, P  =  .04). Addition of PHI to the baseline multivariable model improved discriminative ability by 12.9% (P  =. .04) and yielded greater diagnostic accuracy than models, including other individual biomarkers. In AA men with PSA of 2-10 ng/mL, PHI was predictive of pT3 prostate cancer and may help to identify men at increased risk of adverse pathology. Additional studies are needed to substantiate these findings and identify appropriate thresholds for clinical use. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Body mass index for predicting hyperglycemia and serum lipid changes in Brazilian adolescents.

    Science.gov (United States)

    Vieira, Ana Carolina R; Alvarez, Marlene M; Kanaan, Salim; Sichieri, Rosely; Veiga, Gloria V

    2009-02-01

    To determine the best cut-offs of body mass index for identifying alterations of blood lipids and glucose in adolescents. A probabilistic sample including 577 adolescent students aged 12-19 years in 2003 (210 males and 367 females) from state public schools in the city of Niterói, Southeastern Brazil, was studied. The Receiver Operating Characteristic curve was used to identify the best age-adjusted BMI cut-off for predicting high levels of serum total cholesterol (> or =150 mg/dL), LDL-C (> or =100 mg/dL), serum triglycerides (> or =100 mg/dL), plasma glucose (> 100 mg/dL) and low levels of HDL-C (international and two American. The most prevalent metabolic alterations (>50%) were: high total cholesterol and low HDL-C. BMI predicted high levels of triglycerides in males, high LDL-C in females, and high total cholesterol and the occurrence of three or more metabolic alterations in both males and females (areas under the curve range: 0.59 to 0.67), with low sensitivity (57%-66%) and low specificity (58%-66%). The best BMI cut-offs for this sample (20.3 kg/m(2) to 21.0 kg/m(2)) were lower than those proposed in the references studied. Although BMI values lower than the International cut-offs were better predictor of some metabolic abnormalities in Brazilian adolescents, overall BMI is not a good predictor of these abnormalities in this population.

  1. Application of Intelligent Dynamic Bayesian Network with Wavelet Analysis for Probabilistic Prediction of Storm Track Intensity Index

    Directory of Open Access Journals (Sweden)

    Ming Li

    2018-06-01

    Full Text Available The effective prediction of storm track (ST is greatly beneficial for analyzing the development and anomalies of mid-latitude weather systems. For the non-stationarity, nonlinearity, and uncertainty of ST intensity index (STII, a new probabilistic prediction model was proposed based on dynamic Bayesian network (DBN and wavelet analysis (WA. We introduced probability theory and graph theory for the first time to quantitatively describe the nonlinear relationship and uncertain interaction of the ST system. Then a casual prediction network (i.e., DBN was constructed through wavelet decomposition, structural learning, parameter learning, and probabilistic inference, which was used for expression of relation among predictors and probabilistic prediction of STII. The intensity prediction of the North Pacific ST with data from 1961–2010 showed that the new model was able to give more comprehensive prediction information and higher prediction accuracy and had strong generalization ability and good stability.

  2. Interannual Variability, Global Teleconnection, and Potential Predictability Associated with the Asian Summer Monsoon

    Science.gov (United States)

    Lau, K. M.; Kim, K. M.; Li, J. Y.

    2001-01-01

    In this Chapter, aspects of global teleconnections associated with the interannual variability of the Asian summer monsoon (ASM) are discussed. The basic differences in the basic dynamics of the South Asian Monsoon and the East Asian monsoon, and their implications on global linkages are discussed. Two teleconnection modes linking ASM variability to summertime precipitation over the continental North America were identified. These modes link regional circulation and precipitation anomalies over East Asia and continental North America, via coupled atmosphere-ocean variations over the North Pacific. The first mode has a large zonally symmetrical component and appears to be associated with subtropical jetstream variability and the second mode with Rossby wave dispersion. Both modes possess strong sea surface temperature (SST) expressions in the North Pacific. Results show that the two teleconnection modes may have its origin in intrinsic modes of sea surface temperature variability in the extratropical oceans, which are forced in part by atmospheric variability and in part by air-sea interaction. The potential predictability of the ASM associated with SST variability in different ocean basins is explored using a new canonical ensemble correlation prediction scheme. It is found that SST anomalies in tropical Pacific, i.e., El Nino, is the most dominant forcing for the ASM, especially over the maritime continent and eastern Australia. SST anomalies in the India Ocean may trump the influence from El Nino in western Australia and western maritime continent. Both El Nino, and North Pacific SSTs contribute to monsoon precipitation anomalies over Japan, southern Korea, northern and central China. By optimizing SST variability signals from the world ocean basins using CEC, the overall predictability of ASM can be substantially improved.

  3. An index predictive of cognitive outcome in retired professional American Football players with a history of sports concussion.

    Science.gov (United States)

    Wright, Mathew J; Woo, Ellen; Birath, J Brandon; Siders, Craig A; Kelly, Daniel F; Wang, Christina; Swerdloff, Ronald; Romero, Elizabeth; Kernan, Claudia; Cantu, Robert C; Guskiewicz, Kevin

    2016-01-01

    Various concussion characteristics and personal factors are associated with cognitive recovery in athletes. We developed an index based on concussion frequency, severity, and timeframe, as well as cognitive reserve (CR), and we assessed its predictive power regarding cognitive ability in retired professional football players. Data from 40 retired professional American football players were used in the current study. On average, participants had been retired from football for 20 years. Current neuropsychological performances, indicators of CR, concussion history, and play data were used to create an index for predicting cognitive outcome. The sample displayed a range of concussions, concussion severities, seasons played, CR, and cognitive ability. Many of the participants demonstrated cognitive deficits. The index strongly predicted global cognitive ability (R(2) = .31). The index also predicted the number of areas of neuropsychological deficit, which varied as a function of the deficit classification system used (Heaton: R(2) = .15; Wechsler: R(2) = .28). The current study demonstrated that a unique combination of CR, sports concussion, and game-related data can predict cognitive outcomes in participants who had been retired from professional American football for an average of 20 years. Such indices may prove to be useful for clinical decision making and research.

  4. The Prognostic Nutritional Index Predicts Survival and Identifies Aggressiveness of Gastric Cancer.

    Science.gov (United States)

    Eo, Wan Kyu; Chang, Hye Jung; Suh, Jungho; Ahn, Jin; Shin, Jeong; Hur, Joon-Young; Kim, Gou Young; Lee, Sookyung; Park, Sora; Lee, Sanghun

    2015-01-01

    Nutritional status has been associated with long-term outcomes in cancer patients. The prognostic nutritional index (PNI) is calculated by serum albumin concentration and absolute lymphocyte count, and it may be a surrogate biomarker for nutritional status and possibly predicts overall survival (OS) of gastric cancer. We evaluated the value of the PNI as a predictor for disease-free survival (DFS) in addition to OS in a cohort of 314 gastric cancer patients who underwent curative surgical resection. There were 77 patients in PNI-low group (PNI ≤ 47.3) and 237 patients in PNI-high group (PNI > 47.3). With a median follow-up of 36.5 mo, 5-yr DFS rates in PNI-low group and PNI-high group were 63.5% and 83.6% and 5-yr OS rates in PNI-low group and PNI-high group were 63.5% and 88.4%, respectively (DFS, P < 0.0001; OS, P < 0.0001). In the multivariate analysis, the only predictors for DFS were PNI, tumor-node-metastasis (TNM) stage, and perineural invasion, whereas the only predictors for OS were PNI, age, TNM stage, and perineural invasion. In addition, the PNI was independent of various inflammatory markers. In conclusion, the PNI is an independent prognostic factor for both DFS and OS, and provides additional prognostic information beyond pathologic parameters.

  5. Predicting dyslexia at age 11 from a risk index questionnaire at age 5.

    Science.gov (United States)

    Helland, Turid; Plante, Elena; Hugdahl, Kenneth

    2011-08-01

    This study focused on predicting dyslexia in children ahead of formal literacy training. Because dyslexia is a constitutional impairment, risk factors should be seen in preschool. It was hypothesized that data gathered at age 5 using questions targeting the dyslexia endophenotype should be reliable and valid predictors of dyslexia at age 11. A questionnaire was given to caretakers of 120 5-year-old children, and a risk index score was calculated based on questions regarding health, laterality, motor skills, language, special needs education and heredity. An at-risk group (n = 25) and matched controls (n = 24) were followed until age 11, when a similar questionnaire and literacy tests were administered to the children who participated in the follow-up study (22 at risk and 20 control). Half of the at-risk children and two of the control children at age 5 were identified as having dyslexia at age 11 (8 girls and 5 boys). It is concluded that it is possible to identify children at the age of 5 who will have dyslexia at the age of 11 through a questionnaire approach. Copyright © 2011 John Wiley & Sons, Ltd.

  6. [Preoperative Prognostic Nutrition Index Is a Predictive Factor of Complications in Laparoscopic Colorectal Surgery].

    Science.gov (United States)

    Yano, Yuki; Sagawa, Masano; Yokomizo, Hajime; Okayama, Sachiyo; Yamada, Yasufumi; Usui, Takebumi; Yamaguchi, Kentaro; Shiozawa, Shunichi; Yoshimatsu, Kazuhiko; Shimakawa, Takeshi; Katsube, Takao; Kato, Hiroyuki; Naritaka, Yoshihiko

    2017-10-01

    Paitients and methods: We retrospectively reviewed a database of 188 patients who underwent resection for colorectal cancer with laparoscopic surgery between July 2007 and March 2015. The prognostic nutrition index(PNI), modified Glas- gow prognostic score(mGPS), controlling nutritional status(CONUT), and neutrophil/lymphocyte ratio(N/L)were measured in these patients. We examined the association between postoperative complications and clinicopathological factors. The study included 110 men and 78 women. Median age was 68 years. The site of the primary lesion was colon in 118 and rectum in 70 patients. Postoperative complications higher than Grade II(Clavien-Dindo classification)were reported in 24(12.8%)patients: Surgical site infection(SSI)in 12, remote infection in 7, ileus in 5, and others in 2 patients. Clinicopathological factors related to complications were rectal surgery, large amount of intraoperative bleeding, and long operative time. The related immunologic and nutritional factors were mGPS 2, PNI below 40, and N/L above 3. CONUT was not associated with complications in ourcases. mGPS, PNI, and N/L are predictive factors for complications in laparoscopic colorectal surgery.

  7. Use of Radiographic Densitometry to Predict the Bone Healing Index in Distraction Osteogenesis

    Directory of Open Access Journals (Sweden)

    A Saw

    2008-04-01

    Full Text Available Bone lengthening with distraction osteogenesis involves prolonged application of an external fixator frame. Qualitative and quantitative evaluation of callus has been described using various imaging modalities but there is no simple reliable and readily available method. This study aims to investigate the use of a densitometer to analyze plain radiographic images and correlate them with the rate of new bone formation as represented by the bone healing index. A total of 34 bone lengthening procedures in 29 patients were retrospectively reviewed. We used an X-Rite 301 densitometer to measure densities of new callus on plain radiographs taken at 4 and 8 weeks after surgery. Patients aged below 16y had significantly lower BHIs indicating faster bone healing and shorter duration of treatment. The ratio of radiographic densities between centre and edge of the new bone measured from plain radiographs taken at 8 weeks correlated positively with the eventual BHI of the patient. This method provides a simple and easy way to predict the rate of bone healing at an early stage of treatment and may also allow remedial action to be taken for those with poor progress in bone formation.

  8. The Renal Arterial Resistance Index Predicts Worsening Renal Function in Chronic Heart Failure Patients

    Science.gov (United States)

    Iacoviello, Massimo; Monitillo, Francesco; Leone, Marta; Citarelli, Gaetano; Doronzo, Annalisa; Antoncecchi, Valeria; Puzzovivo, Agata; Rizzo, Caterina; Lattarulo, Maria Silvia; Massari, Francesco; Caldarola, Pasquale; Ciccone, Marco Matteo

    2016-01-01

    Background/Aim The renal arterial resistance index (RRI) is a Doppler measure, which reflects abnormalities in the renal blood flow. The aim of this study was to verify the value of RRI as a predictor of worsening renal function (WRF) in a group of chronic heart failure (CHF) outpatients. Methods We enrolled 266 patients in stable clinical conditions and on conventional therapy. Peak systolic velocity and end diastolic velocity of a segmental renal artery were obtained by pulsed Doppler flow, and RRI was calculated. Creatinine serum levels were evaluated at baseline and at 1 year, and the changes were used to assess WRF occurrence. Results During follow-up, 34 (13%) patients showed WRF. RRI was associated with WRF at univariate (OR: 1.13; 95% CI: 1.07–1.20) as well as at a forward stepwise multivariate logistic regression analysis (OR: 1.09; 95% CI: 1.03–1.16; p = 0.005) including the other univariate predictors. Conclusions Quantification of arterial renal perfusion provides a new parameter that independently predicts the WRF in CHF outpatients. Its possible role in current clinical practice to better define the risk of cardiorenal syndrome progression is strengthened. PMID:27994601

  9. A Novel Fibrosis Index Comprising a Non-Cholesterol Sterol Accurately Predicts HCV-Related Liver Cirrhosis

    DEFF Research Database (Denmark)

    Ydreborg, Magdalena; Lisovskaja, Vera; Lagging, Martin

    2014-01-01

    of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive...

  10. Interannual variability of the normalized difference vegetation index on the Tibetan Plateau and its relationship with climate change

    Science.gov (United States)

    Zhou, Dingwen; Fan, Guangzhou; Huang, Ronghui; Fang, Zhifang; Liu, Yaqin; Li, Hongquan

    2007-05-01

    The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index (NDVI) dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982 2002. The temporal variation also exhibits striking regional differences: an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability.

  11. Bayesian spatial prediction of the site index in the study of the Missouri Ozark Forest Ecosystem Project

    Science.gov (United States)

    Xiaoqian Sun; Zhuoqiong He; John Kabrick

    2008-01-01

    This paper presents a Bayesian spatial method for analysing the site index data from the Missouri Ozark Forest Ecosystem Project (MOFEP). Based on ecological background and availability, we select three variables, the aspect class, the soil depth and the land type association as covariates for analysis. To allow great flexibility of the smoothness of the random field,...

  12. Prediction of Bispectral Index during Target-controlled Infusion of Propofol and Remifentanil: A Deep Learning Approach.

    Science.gov (United States)

    Lee, Hyung-Chul; Ryu, Ho-Geol; Chung, Eun-Jin; Jung, Chul-Woo

    2018-03-01

    The discrepancy between predicted effect-site concentration and measured bispectral index is problematic during intravenous anesthesia with target-controlled infusion of propofol and remifentanil. We hypothesized that bispectral index during total intravenous anesthesia would be more accurately predicted by a deep learning approach. Long short-term memory and the feed-forward neural network were sequenced to simulate the pharmacokinetic and pharmacodynamic parts of an empirical model, respectively, to predict intraoperative bispectral index during combined use of propofol and remifentanil. Inputs of long short-term memory were infusion histories of propofol and remifentanil, which were retrieved from target-controlled infusion pumps for 1,800 s at 10-s intervals. Inputs of the feed-forward network were the outputs of long short-term memory and demographic data such as age, sex, weight, and height. The final output of the feed-forward network was the bispectral index. The performance of bispectral index prediction was compared between the deep learning model and previously reported response surface model. The model hyperparameters comprised 8 memory cells in the long short-term memory layer and 16 nodes in the hidden layer of the feed-forward network. The model training and testing were performed with separate data sets of 131 and 100 cases. The concordance correlation coefficient (95% CI) were 0.561 (0.560 to 0.562) in the deep learning model, which was significantly larger than that in the response surface model (0.265 [0.263 to 0.266], P deep learning model-predicted bispectral index during target-controlled infusion of propofol and remifentanil more accurately compared to the traditional model. The deep learning approach in anesthetic pharmacology seems promising because of its excellent performance and extensibility.

  13. Predicting Spatial Distribution of Key Honeybee Pests in Kenya Using Remotely Sensed and Bioclimatic Variables: Key Honeybee Pests Distribution Models

    Directory of Open Access Journals (Sweden)

    David M. Makori

    2017-02-01

    Full Text Available Bee keeping is indispensable to global food production. It is an alternate income source, especially in rural underdeveloped African settlements, and an important forest conservation incentive. However, dwindling honeybee colonies around the world are attributed to pests and diseases whose spatial distribution and influences are not well established. In this study, we used remotely sensed data to improve the reliability of pest ecological niche (EN models to attain reliable pest distribution maps. Occurrence data on four pests (Aethina tumida, Galleria mellonella, Oplostomus haroldi and Varroa destructor were collected from apiaries within four main agro-ecological regions responsible for over 80% of Kenya’s bee keeping. Africlim bioclimatic and derived normalized difference vegetation index (NDVI variables were used to model their ecological niches using Maximum Entropy (MaxEnt. Combined precipitation variables had a high positive logit influence on all remotely sensed and biotic models’ performance. Remotely sensed vegetation variables had a substantial effect on the model, contributing up to 40.8% for G. mellonella and regions with high rainfall seasonality were predicted to be high-risk areas. Projections (to 2055 indicated that, with the current climate change trend, these regions will experience increased honeybee pest risk. We conclude that honeybee pests could be modelled using bioclimatic data and remotely sensed variables in MaxEnt. Although the bioclimatic data were most relevant in all model results, incorporating vegetation seasonality variables to improve mapping the ‘actual’ habitat of key honeybee pests and to identify risk and containment zones needs to be further investigated.

  14. Endometriosis fertility index predicts live births following surgical resection of moderate and severe endometriosis.

    Science.gov (United States)

    Maheux-Lacroix, S; Nesbitt-Hawes, E; Deans, R; Won, H; Budden, A; Adamson, D; Abbott, J A

    2017-11-01

    Can live birth be accurately predicted following surgical resection of moderate-severe (Stage III-IV) endometriosis? Live births can accurately be predicted with the endometriosis fertility index (EFI), with adnexal function being the most important factor to predict non-assisted reproductive technology (non-ART) fertility or the requirement for ART (www.endometriosisefi.com). Fertility prognosis is important to many women with severe endometriosis. Controversy persists regarding optimal post-operative management to achieve pregnancy and the counselling of patients regarding duration of conventional treatments before undergoing ART. The EFI is reported to correlate with expectant management pregnancy rate, although external validation has been performed without specifically addressing fertility in women with moderate and severe endometriosis. Retrospective cohort study of 279 women from September 2001 to June 2016. We included women undergoing laparoscopic resection of Stage III-IV endometriosis who attempted pregnancy post-operatively. The EFI was calculated based on detailed operative reports and surgical images. Fertility outcomes were obtained by direct patient contact. Kaplan-Meier model, log rank test and Cox regression were used for analyses. The follow-up rate was 84% with a mean duration of 4.1 years. A total of 147 women (63%) had a live birth following surgery, 94 of them (64%) without ART. The EFI was highly associated with live births (P years was 0% and steadily increased up to 91% with an EFI of 9-10, while the proportion of women who attempted ART and had a live birth, steadily increased from 38 to 71% among the same EFI strata (P = 0.1). A low least function score was the most significant predictor of failure (P = 0.003), followed by having had a previous resection (P = 0.019) or incomplete resection (P = 0.028), being older than 40 compared to years of age (P = 0.027), and having leiomyomas (P = 0.037). The main limitation of this study is its

  15. Dynamic interactions between hydrogeological and exposure parameters in daily dose prediction under uncertainty and temporal variability

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Vikas, E-mail: vikas.kumar@urv.cat [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Barros, Felipe P.J. de [Sonny Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles 90089, CA (United States); Schuhmacher, Marta [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier [Hydrogeology Group, Department of Geotechnical Engineering and Geosciences, University Politècnica de Catalunya-BarcelonaTech, Barcelona 08034 (Spain)

    2013-12-15

    Highlights: • Dynamic parametric interaction in daily dose prediction under uncertainty. • Importance of temporal dynamics associated with the dose. • Different dose experienced by different population cohorts as a function of time. • Relevance of uncertainty reduction in the input parameters shows temporal dynamism. -- Abstract: We study the time dependent interaction between hydrogeological and exposure parameters in daily dose predictions due to exposure of humans to groundwater contamination. Dose predictions are treated stochastically to account for an incomplete hydrogeological and geochemical field characterization, and an incomplete knowledge of the physiological response. We used a nested Monte Carlo framework to account for uncertainty and variability arising from both hydrogeological and exposure variables. Our interest is in the temporal dynamics of the total dose and their effects on parametric uncertainty reduction. We illustrate the approach to a HCH (lindane) pollution problem at the Ebro River, Spain. The temporal distribution of lindane in the river water can have a strong impact in the evaluation of risk. The total dose displays a non-linear effect on different population cohorts, indicating the need to account for population variability. We then expand the concept of Comparative Information Yield Curves developed earlier (see de Barros et al. [29]) to evaluate parametric uncertainty reduction under temporally variable exposure dose. Results show that the importance of parametric uncertainty reduction varies according to the temporal dynamics of the lindane plume. The approach could be used for any chemical to aid decision makers to better allocate resources towards reducing uncertainty.

  16. Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

    Science.gov (United States)

    Lin, Shu-Yu; Lee, Wei-Ju; Chou, Ming-Yueh; Peng, Li-Ning; Chiou, Shu-Ti; Chen, Liang-Kung

    2016-01-01

    Frailty Index, defined as an individual's accumulated proportion of listed health-related deficits, is a well-established metric used to assess the health status of old adults; however, it has not yet been developed in Taiwan, and its local related structure factors remain unclear. The objectives were to construct a Taiwan Frailty Index to predict mortality risk, and to explore the structure of its factors. Analytic data on 1,284 participants aged 53 and older were excerpted from the Social Environment and Biomarkers of Aging Study (2006), in Taiwan. A consensus workgroup of geriatricians selected 159 items according to the standard procedure for creating a Frailty Index. Cox proportional hazard modeling was used to explore the association between the Taiwan Frailty Index and mortality. Exploratory factor analysis was used to identify structure factors and produce a shorter version-the Taiwan Frailty Index Short-Form. During an average follow-up of 4.3 ± 0.8 years, 140 (11%) subjects died. Compared to those in the lowest Taiwan Frailty Index tertile ( 0.23) had significantly higher risk of death (Hazard ratio: 3.2; 95% CI 1.9-5.4). Thirty-five items of five structure factors identified by exploratory factor analysis, included: physical activities, life satisfaction and financial status, health status, cognitive function, and stresses. Area under the receiver operating characteristic curves (C-statistics) of the Taiwan Frailty Index and its Short-Form were 0.80 and 0.78, respectively, with no statistically significant difference between them. Although both the Taiwan Frailty Index and Short-Form were associated with mortality, the Short-Form, which had similar accuracy in predicting mortality as the full Taiwan Frailty Index, would be more expedient in clinical practice and community settings to target frailty screening and intervention.

  17. Variables that Predict Serve Efficacy in Elite Men's Volleyball with Different Quality of Opposition Sets.

    Science.gov (United States)

    Valhondo, Álvaro; Fernández-Echeverría, Carmen; González-Silva, Jara; Claver, Fernando; Moreno, M Perla

    2018-03-01

    The objective of this study was to determine the variables that predicted serve efficacy in elite men's volleyball, in sets with different quality of opposition. 3292 serve actions were analysed, of which 2254 were carried out in high quality of opposition sets and 1038 actions were in low quality of opposition sets, corresponding to a total of 24 matches played during the Men's European Volleyball Championships held in 2011. The independent variables considered in this study were the serve zone, serve type, serving player, serve direction, reception zone, receiving player and reception type; the dependent variable was serve efficacy and the situational variable was quality of opposition sets. The variables that acted as predictors in both high and low quality of opposition sets were the serving player, reception zone and reception type. The serve type variable only acted as a predictor in high quality of opposition sets, while the serve zone variable only acted as a predictor in low quality of opposition sets. These results may provide important guidance in men's volleyball training processes.

  18. Generating temporal model using climate variables for the prediction of dengue cases in Subang Jaya, Malaysia

    Science.gov (United States)

    Dom, Nazri Che; Hassan, A Abu; Latif, Z Abd; Ismail, Rodziah

    2013-01-01

    Objective To develop a forecasting model for the incidence of dengue cases in Subang Jaya using time series analysis. Methods The model was performed using the Autoregressive Integrated Moving Average (ARIMA) based on data collected from 2005 to 2010. The fitted model was then used to predict dengue incidence for the year 2010 by extrapolating dengue patterns using three different approaches (i.e. 52, 13 and 4 weeks ahead). Finally cross correlation between dengue incidence and climate variable was computed over a range of lags in order to identify significant variables to be included as external regressor. Results The result of this study revealed that the ARIMA (2,0,0) (0,0,1)52 model developed, closely described the trends of dengue incidence and confirmed the existence of dengue fever cases in Subang Jaya for the year 2005 to 2010. The prediction per period of 4 weeks ahead for ARIMA (2,0,0)(0,0,1)52 was found to be best fit and consistent with the observed dengue incidence based on the training data from 2005 to 2010 (Root Mean Square Error=0.61). The predictive power of ARIMA (2,0,0) (0,0,1)52 is enhanced by the inclusion of climate variables as external regressor to forecast the dengue cases for the year 2010. Conclusions The ARIMA model with weekly variation is a useful tool for disease control and prevention program as it is able to effectively predict the number of dengue cases in Malaysia.

  19. Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks.

    Science.gov (United States)

    Rudi, Gabrielle; Bailly, Jean-Stéphane; Vinatier, Fabrice

    2018-01-01

    To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute

  20. Predicting forested catchment evapotranspiration and streamflow from stand sapwood area and Aridity Index

    Science.gov (United States)

    Lane, Patrick

    2016-04-01

    Estimating the water balance of ungauged catchments has been the subject of decades of research. An extension of the fundamental problem of estimating the hydrology is then understanding how do changes in catchment attributes affect the water balance component? This is a particular issue in forest hydrology where vegetation exerts such a strong influence on evapotranspiration (ET), and consequent streamflow (Q). Given the primacy of trees in the water balance, and the potential for change to species and density through logging, fire, pests and diseases and drought, methods that directly relate ET/Q to vegetation structure, species, and stand density are very powerful. Plot studies on tree water use routinely use sapwood area (SA) to calculate transpiration and upscale to the stand/catchment scale. Recent work in south eastern Australian forests have found stand-wide SA to be linearly correlated (R2 = 0.89) with long term mean annual loss (P-Q), and hence, long term mean annual catchment streamflow. Robust relationships can be built between basal area (BA), tree density and stand SA. BA and density are common forest inventory measurements. Until now, no research has related the fundamental stand attribute of SA to streamflow. The data sets include catchments that have been thinned and with varying age classes. Thus far these analyses have been for energy limited systems in wetter forest types. SA has proven to be a more robust biometric than leaf area index which varies seasonally. That long term ET/Q is correlated with vegetation conforms to the Budyko framework. Use of a downscaled (20 m) Aridity Index (AI) has shown distinct correlations with stand SA, and therefore T. Structural patterns at a the hillslope scale not only correlate with SA and T, but also with interception (I) and forest floor evaporation (Es). These correlations between AI and I and Es have given R2 > 0.8. The result of these studies suggest an ability to estimate mean annual ET fluxes at sub

  1. Limited accuracy of the hyperbaric index, ambulatory blood pressure and sphygmomanometry measurements in predicting gestational hypertension and preeclampsia

    NARCIS (Netherlands)

    Vollebregt, Karlijn Corien; Gisolf, Janneke; Guelen, Ilja; Boer, Kees; van Montfrans, Gert; Wolf, Hans

    2010-01-01

    Objective The aim of this study was to validate the hyperbaric index (HBI) for first trimester prediction of preeclampsia and gestational hypertension. Methods Participants were low-risk and high-risk nulliparous women and high-risk multiparous women, and were recruited between April 2004 and June

  2. Generalizability of the Disease State Index Prediction Model for Identifying Patients Progressing from Mild Cognitive Impairment to Alzheimer's Disease

    NARCIS (Netherlands)

    Hall, A.; Munoz-Ruiz, M.; Mattila, J.; Koikkalainen, J.; Tsolaki, M.; Mecocci, P.; Kloszewska, I.; Vellas, B.; Lovestone, S.; Visser, P.J.; Lotjonen, J.; Soininen, H.

    2015-01-01

    Background: The Disease State Index (DSI) prediction model measures the similarity of patient data to diagnosed stable and progressive mild cognitive impairment (MCI) cases to identify patients who are progressing to Alzheimer's disease. Objectives: We evaluated how well the DSI generalizes across

  3. Digital Cover Photography for Estimating Leaf Area Index (LAI in Apple Trees Using a Variable Light Extinction Coefficient

    Directory of Open Access Journals (Sweden)

    Carlos Poblete-Echeverría

    2015-01-01

    Full Text Available Leaf area index (LAI is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io and transmitted radiation (I through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAID, which was compared with LAI estimated by the proposed digital photography method (LAIM. Results showed that the LAIM was able to estimate LAID with an error of 25% using a constant light extinction coefficient (k = 0.68. However, when k was estimated using an exponential function based on the fraction of foliage cover (ff derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.

  4. Digital cover photography for estimating leaf area index (LAI) in apple trees using a variable light extinction coefficient.

    Science.gov (United States)

    Poblete-Echeverría, Carlos; Fuentes, Sigfredo; Ortega-Farias, Samuel; Gonzalez-Talice, Jaime; Yuri, Jose Antonio

    2015-01-28

    Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAI(D)), which was compared with LAI estimated by the proposed digital photography method (LAI(M)). Results showed that the LAI(M) was able to estimate LAI(D) with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (f(f)) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.

  5. Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient

    Science.gov (United States)

    Poblete-Echeverría, Carlos; Fuentes, Sigfredo; Ortega-Farias, Samuel; Gonzalez-Talice, Jaime; Yuri, Jose Antonio

    2015-01-01

    Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAID), which was compared with LAI estimated by the proposed digital photography method (LAIM). Results showed that the LAIM was able to estimate LAID with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (ff) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions. PMID:25635411

  6. Evaluation of Different Score Index for Predicting Prognosis in Gamma Knife Radiosurgical Treatment for Brain Metastasis

    International Nuclear Information System (INIS)

    Franzin, Alberto; Snider, Silvia; Picozzi, Piero; Bolognesi, Angelo; Serra, Carlo; Vimercati, Alberto; Passarin, Olga; Mortini, Pietro

    2009-01-01

    Purpose: To assess the utility of the Radiation Therapy Oncology Group Recursive Partitioning Analysis (RPA) and Score Index for Radiosurgery (SIR) stratification systems in predicting survival in patients with brain metastasis treated with Gamma Knife radiosurgery (GKRS). Methods and Materials: A total of 185 patients were included in the study. Patients were stratified according to RPA and SIR classes. The RPA and SIR classes, age, Karnofsky Performance Status (KPS), and systemic disease were correlated with survival. Results: Five patients were lost to follow-up. Median survival in patients in RPA Class 1 (30 patients) was 17 months; in Class 2 (140 patients), 10 months; and in Class 3 (10 patients), 3 months. Median survival in patients in SIR Class 1 (30 patients) was 3 months; in Class 2 (135 patients), 8 months; and in Class 3 (15 patients), 20 months. In univariate testing, age younger than 65 years (p = 0.0004), KPS higher than 70 (p = 0.0001), RPA class (p = 0.0078), SIR class (p = 0.0002), and control of the primary tumor (p = 0.02) were significantly associated with improved outcome. In multivariate analysis, KPS (p < 0.0001), SIR class (p = 0.0008), and RPA class (p = 0.03) had statistical value. Conclusions: This study supports the use of GKRS as a single-treatment modality in this selected group of patients. Stratification systems are useful in the estimation of patient eligibility for GKRS. A second-line treatment was necessary in 30% of patients to achieve distal or local brain control. This strategy is useful to control brain metastasis in long-surviving patients.

  7. Predictive validity of a brief antiretroviral adherence index: Retrospective cohort analysis under conditions of repetitive administration

    Directory of Open Access Journals (Sweden)

    Colwell Bradford

    2008-08-01

    Full Text Available Abstract Background Newer antiretroviral (ARV agents have improved pharmacokinetics, potency, and tolerability and have enabled the design of regimens with improved virologic outcomes. Successful antiretroviral therapy is dependent on patient adherence. In previous research, we validated a subset of items from the ACTG adherence battery as prognostic of virologic suppression at 6 months and correlated with adherence estimates from the Medication Event Monitoring System (MEMS. The objective of the current study was to validate the longitudinal use of the Owen Clinic adherence index in analyses of time to initial virologic suppression and maintenance of suppression. Results 278 patients (naïve n = 168, experienced n = 110 met inclusion criteria. Median [range] time on the first regimen during the study period was 286 (30 – 1221 days. 217 patients (78% achieved an undetectable plasma viral load (pVL at median 63 days. 8.3% (18/217 of patients experienced viral rebound (pVL > 400 after initial suppression. Adherence scores varied from 0 – 25 (mean 1.06, median 0. The lowest detectable adherence score cut point using this instrument was ≥ 5 for both initial suppression and maintenance of suppression. In the final Cox model of time to first undetectable pVL, controlling for prior treatment experience and baseline viral load, the adjusted hazard ratio for time updated adherence score was 0.36score ≥ 5 (95% CI: 0.19–0.69 [reference: score ≥ 5 (0.05–0.66 [reference: Conclusion A brief, longitudinally administered self report adherence instrument predicted both initial virologic suppression and maintenance of suppression in patients using contemporary ARV regimens. The survey can be used for identification of sub-optimal adherence with subsequent appropriate intervention.

  8. Body mass index predicts aldosterone production in normotensive adults on a high-salt diet.

    Science.gov (United States)

    Bentley-Lewis, Rhonda; Adler, Gail K; Perlstein, Todd; Seely, Ellen W; Hopkins, Paul N; Williams, Gordon H; Garg, Rajesh

    2007-11-01

    The mechanisms underlying obesity-mediated cardiovascular disease are not fully understood. Aldosterone and insulin resistance both are associated with obesity and cardiovascular disease. The objectives of this study were to test the hypotheses that aldosterone production is elevated and associated with insulin resistance in overweight adults on a high-sodium diet. Healthy normotensive adults were categorized as lean body mass index (BMI) less than 25 kg/m(2) (n = 63) or overweight BMI 25 kg/m(2) or greater (n = 57). After 7 d of a high-sodium diet, participants fasted overnight and remained supine throughout hemodynamic and laboratory assessments and angiotensin II (AngII) stimulation. The overweight group, compared with the lean group, had higher 24-h urinary aldosterone (9.0 +/- 0.8 vs. 6.6 +/- 0.5 microg per 24 h; P = 0.003) and higher AngII-stimulated serum aldosterone (11.4 +/- 1.0 vs. 9.0 +/- 0.6 ng/dl; P = 0.04). There were no differences in 24-h urinary cortisol or sodium or supine measurements of plasma renin activity, serum aldosterone, or serum potassium. The homeostasis model assessment of insulin resistance was predicted by urinary aldosterone excretion (r = 0.32, P = 0.03) and serum aldosterone response to AngII stimulation (r = 0.28, P = 0.02) independent of age and BMI. Urinary aldosterone excretion and AngII-stimulated aldosterone are increased in overweight, compared with lean, normotensive adults. The correlation of these measures of aldosterone production with insulin resistance suggests a potential role for aldosterone in the pathophysiology of obesity-mediated insulin resistance.

  9. Predictive Value of Triglyceride Glucose Index for the Risk of Incident Diabetes: A 4-Year Retrospective Longitudinal Study.

    Science.gov (United States)

    Lee, Da Young; Lee, Eun Seo; Kim, Ji Hyun; Park, Se Eun; Park, Cheol-Young; Oh, Ki-Won; Park, Sung-Woo; Rhee, Eun-Jung; Lee, Won-Young

    The Triglyceride Glucose Index (TyG index) is considered a surrogate marker of insulin resistance. The aim of this study is to investigate whether the TyG index has a predictive role in identifying individuals with a high risk of incident diabetes and to compare it with other indicators of metabolic health. A total 2900 non-diabetic adults who attended five consecutive annual health check-ups at Kangbuk Samsung Hospital was divided into four subgroups using three methods: (1) baseline TyG index; (2) obesity status (body mass index ≥25 kg/m2) and cutoff value of TyG index; (3) obesity status and metabolic health, defined as having fewer than two of the five components of high blood pressure, fasting blood glucose, triglyceride, low high-density lipoprotein cholesterol, and highest decile of homeostasis model assessment-insulin resistance. The development of diabetes was assessed annually using self-questionnaire, fasting glucose, and glycated hemoglobin. We compared the risk of incident diabetes using multivariate Cox analysis. During 11623 person-years there were 101 case of incident diabetes. Subjects with high TyG index had a high risk of diabetes. For TyG index quartiles, hazard ratios (HRs) of quartiles 3 and 4 were 4.06 (p = 0.033) and 5.65 (p = 0.006) respectively. When the subjects were divided by obesity status and cutoff value of TyG index of 8.8, the subgroups with TyG index ≥ 8.8 regardless of obesity had a significantly high risk for diabetes (HR 2.40 [p = 0.024] and 2.25 [p = 0.048]). For obesity status and metabolic health, the two metabolically unhealthy subgroups regardless of obesity had a significantly high risk for diabetes (HRs 2.54 [p = 0.024] and 2.73 [p = 0.021]). In conclusion, the TyG index measured at a single time point may be an indicator of the risk for incident diabetes. The predictive value of the TyG index was comparable to that of metabolic health.

  10. Predicting farm-level animal populations using environmental and socioeconomic variables.

    Science.gov (United States)

    van Andel, Mary; Jewell, Christopher; McKenzie, Joanna; Hollings, Tracey; Robinson, Andrew; Burgman, Mark; Bingham, Paul; Carpenter, Tim

    2017-09-15

    Accurate information on the geographic distribution of domestic animal populations helps biosecurity authorities to efficiently prepare for and rapidly eradicate exotic diseases, such as Foot and Mouth Disease (FMD). Developing and maintaining sufficiently high-quality data resources is expensive and time consuming. Statistical modelling of population density and distribution has only begun to be applied to farm animal populations, although it is commonly used in wildlife ecology. We developed zero-inflated Poisson regression models in a Bayesian framework using environmental and socioeconomic variables to predict the counts of livestock units (LSUs) and of cattle on spatially referenced farm polygons in a commercially available New Zealand farm database, Agribase. Farm-level counts of cattle and of LSUs varied considerably by region, because of the heterogeneous farming landscape in New Zealand. The amount of high quality pasture per farm was significantly associated with the presence of both cattle and LSUs. Internal model validation (predictive performance) showed that the models were able to predict the count of the animal population on groups of farms that were located in randomly selected 3km zones with a high level of accuracy. Predicting cattle or LSU counts on individual farms was less accurate. Predicted counts were statistically significantly more variable for farms that were contract grazing dry stock, such as replacement dairy heifers and dairy cattle not currently producing milk, compared with other farm types. This analysis presents a way to predict numbers of LSUs and cattle for farms using environmental and socio-economic data. The technique has the potential to be extrapolated to predicting other pastoral based livestock species. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. MEDEX 2015: Heart Rate Variability Predicts Development of Acute Mountain Sickness.

    Science.gov (United States)

    Sutherland, Angus; Freer, Joseph; Evans, Laura; Dolci, Alberto; Crotti, Matteo; Macdonald, Jamie Hugo

    2017-09-01

    Sutherland, Angus, Joseph Freer, Laura Evans, Alberto Dolci, Matteo Crotti, and Jamie Hugo Macdonald. MEDEX 2015: Heart rate variability predicts development of acute mountain sickness. High Alt Med Biol. 18: 199-208, 2017. Acute mountain sickness (AMS) develops when the body fails to acclimatize to atmospheric changes at altitude. Preascent prediction of susceptibility to AMS would be a useful tool to prevent subsequent harm. Changes to peripheral oxygen saturation (SpO 2 ) on hypoxic exposure have previously been shown to be of poor predictive value. Heart rate variability (HRV) has shown promise in the early prediction of AMS, but its use pre-expedition has not previously been investigated. We aimed to determine whether pre- and intraexpedition HRV assessment could predict susceptibility to AMS at high altitude with better diagnostic accuracy than SpO 2 . Forty-four healthy volunteers undertook an expedition in the Nepali Himalaya to >5000 m. SpO 2 and HRV parameters were recorded at rest in normoxia and in a normobaric hypoxic chamber before the expedition. On the expedition HRV parameters and SpO 2 were collected again at 3841 m. A daily Lake Louise Score was obtained to assess AMS symptomology. Low frequency/high frequency (LF/HF) ratio in normoxia (cutpoint ≤2.28 a.u.) and LF following 15 minutes of exposure to normobaric hypoxia had moderate (area under the curve ≥0.8) diagnostic accuracy. LF/HF ratio in normoxia had the highest sensitivity (85%) and specificity (88%) for predicting AMS on subsequent ascent to altitude. In contrast, pre-expedition SpO 2 measurements had poor (area under the curve <0.7) diagnostic accuracy and inferior sensitivity and specificity. Pre-ascent measurement of HRV in normoxia was found to be of better diagnostic accuracy for AMS prediction than all measures of HRV in hypoxia, and better than peripheral oxygen saturation monitoring.

  12. External validation of the endometriosis fertility index (EFI) staging system for predicting non-ART pregnancy after endometriosis surgery.

    Science.gov (United States)

    Tomassetti, C; Geysenbergh, B; Meuleman, C; Timmerman, D; Fieuws, S; D'Hooghe, T

    2013-05-01

    . Subjects were censored when they were lost to follow-up, had subsequent surgery for endometriosis, started ovarian suppression or underwent ART. As K-M estimates might overestimate the actual event rate, cumulative incidence estimates treating ART as competing event were also calculated. Cox regression analysis was used to assess the performance of EFI and constituting variables. Performance of the score (prediction, discrimination) was quantified with the following methods: mean squared error of prediction (Brier score), areas under the receiver-operating curve and global concordance index C(τ). There was a highly significant relationship between the EFI and the time to non-ART pregnancy (cumulative overall pregnancy rate, P = 0.0004), with the K-M estimate of cumulative overall pregnancy rate at 12 months after surgery equal to 45.5% [95% confidence interval (CI) 39.47-49.87]-ranging from 16.67% (95% CI 5.01-47.65) for EFI scores 0-3, to 62.55% (95% CI 55.18-69.94) for EFI scores 9-10. For each increase of 1 point in the EFI score, the relative risk of becoming pregnant increased by 31% (95% CI 16-47%; i.e. hazard ratio 1.31). The 'least function score'-which assesses the tubal/ovarian function at conclusion of surgery-was found to be the most important contributor to the total EFI score among all the other variables (age, duration of infertility, prior pregnancy, AFS endometriosis lesion and total score). The EFI score had a moderate performance in the prediction of the pregnancy rate. Indeed, the decrease in prediction error was rather small, as shown by the decrease in Brier score from 0.213 to 0.198, and low estimates for R² (13%) and C(τ) (0.629). As the EFI was validated externally in our own European population after initial testing by Adamson and Pasta (Endometriosis fertility index: the new, validated endometriosis staging system. Fertil Steril 2010;94:1609-1615) in an American population, it appears that the EFI can be used clinically to counsel infertile

  13. Different minimally important clinical difference (MCID) scores lead to different clinical prediction rules for the Oswestry disability index for the same sample of patients.

    Science.gov (United States)

    Schwind, Julie; Learman, Kenneth; O'Halloran, Bryan; Showalter, Christopher; Cook, Chad

    2013-05-01

    Minimal clinically important difference (MCID) scores for outcome measures are frequently used evidence-based guides to gage meaningful changes. There are numerous outcome instruments used for analyzing pain, disability, and dysfunction of the low back; perhaps the most common of these is the Oswestry disability index (ODI). A single agreed-upon MCID score for the ODI has yet to be established. What is also unknown is whether selected baseline variables will be universal predictors regardless of the MCID used for a particular outcome measure. To explore the relationship between predictive models and the MCID cutpoint on the ODI. Data were collected from 16 outpatient physical therapy clinics in 10 states. Secondary database analysis using backward stepwise deletion logistic regression of data from a randomized controlled trial (RCT) to create prognostic clinical prediction rules (CPR). One hundred and forty-nine patients with low back pain (LBP) were enrolled in the RCT. All were treated with manual therapy, with a majority also receiving spine-strengthening exercises. The resultant predictive models were dependent upon the MCID used and baseline sample characteristics. All CPR were statistically significant (P < 001). All six MCID cutpoints used resulted in completely different significant predictor variables with no predictor significant across all models. The primary limitations include sub-optimal sample size and study design. There is extreme variability among predictive models created using different MCIDs on the ODI within the same patient population. Our findings highlight the instability of predictive modeling, as these models are significantly affected by population baseline characteristics along with the MCID used. Clinicians must be aware of the fragility of CPR prior to applying each in clinical practice.

  14. How long the singular value decomposed entropy predicts the stock market? - Evidence from the Dow Jones Industrial Average Index

    Science.gov (United States)

    Gu, Rongbao; Shao, Yanmin

    2016-07-01

    In this paper, a new concept of multi-scales singular value decomposition entropy based on DCCA cross correlation analysis is proposed and its predictive power for the Dow Jones Industrial Average Index is studied. Using Granger causality analysis with different time scales, it is found that, the singular value decomposition entropy has predictive power for the Dow Jones Industrial Average Index for period less than one month, but not for more than one month. This shows how long the singular value decomposition entropy predicts the stock market that extends Caraiani's result obtained in Caraiani (2014). On the other hand, the result also shows an essential characteristic of stock market as a chaotic dynamic system.

  15. Variables that predict academic procrastination behavior in prospective primary school teachers

    Directory of Open Access Journals (Sweden)

    Asuman Seda SARACALOĞLU

    2016-04-01

    Full Text Available This study aimed to examine the variables predicting academic procrastination behavior of prospective primary school teachers and is conducted using the correlational survey model. The study group is composed of 294 undergraduate students studying primary school teaching programs in faculties of education at Adnan Menderes, Pamukkale, and Muğla Sıtkı Koçman Universities in Turkey. The data collection instruments used were the Procrastination Assessment Scale Students (PASS, Academic Self-Efficacy Scale (ASES, and Academic Motivation Scale (AMS. While analyzing the gathered data, descriptive analysis techniques were utilized. Moreover, while analyzing the data, power of variables namely reasons of academic procrastination, academic motivation, and academic efficacy to predict prospective primary school teachers’ academic procrastination tendencies were tested. For that purpose, stepwise regression analysis was employed. It was found that nearly half of the prospective primary school teachers displayed no academic procrastination behavior. Participants’ reasons for procrastination were fear of failure, laziness, taking risks, and rebellion against control. An average level significant correlation was found between participants’ academic procrastination and other variables. As a result, it was identified that prospective primary school teachers had less academic procrastination than reported in literature and laziness, fear of failure, academic motivation predicted academic procrastination.

  16. [Prediction of mathematics achievement: effect of personal, socioeducational and contextual variables].

    Science.gov (United States)

    Rosário, Pedro; Lourenço, Abílio; Paiva, Olímpia; Rodrigues, Adriana; Valle, Antonio; Tuero-Herrero, Ellián

    2012-05-01

    Based upon the self-regulated learning theoretical framework this study examined to what extent students' Math school achievement (fifth to ninth graders from compulsory education) can be explained by different cognitive-motivational, social, educational, and contextual variables. A sample of 571 students (10 to 15 year old) enrolled in the study. Findings suggest that Math achievement can be predicted by self-efficacy in Math, school success and self-regulated learning and that these same variables can be explained by other motivational (ej., achievement goals) and contextual variables (school disruption) stressing this way the main importance of self-regulated learning processes and the role context can play in the promotion of school success. The educational implications of the results to the school levels taken are also discussed in the present paper.

  17. The role of socio-cognitive variables in predicting learning satisfaction in smart schools

    Directory of Open Access Journals (Sweden)

    Mohammad Reza Firoozi

    2017-03-01

    Full Text Available The present study aimed to investigate the role of Socio-Cognitive variables in predicting learning satisfaction in Smart Schools. The population was all the primary school students studying in smart schools in the city of Shiraz in the school year 2014-2015. The sample, randomly chosen through multi-stage cluster sampling, was 383 primary school students studying in smart schools in Shiraz. The instruments were the Computer Self-Efficiency Questionnaire developed by Torkzadeh (2003, Performance Expectation Questionnaire developed by Compeau and Higgins (1995, System Functionality and Content Feature Questionnaire developed by Pituch and Lee (2006, Interaction Questionnaire developed by Johnston, Killion and Oomen (2005, Learning Climate Questionnaire developed by Chou` and Liu (2005 and Learning Satisfaction Questionnaire developed by Chou and Liu (2005. In order to determine the possible relationship between variables and to predict the changes in the degree of satisfaction, we made use of correlational procedures and step-wise regression analysis. The results indicated that all the socio-cognitive variables have a positive and significant correlation with learning satisfaction. Out of the socio-cognitive variables in question, Computer Self-Efficiency, Performance Expectation and Learning Climate significantly explained 53% of the variance of learning satisfaction.

  18. The Role of Socio-Cognitive Variables in Predicting Learning Satisfaction in Smart Schools

    Directory of Open Access Journals (Sweden)

    Mohammad Reza FIROOZI

    2017-03-01

    Full Text Available The present study aimed to investigate the role of Socio-Cognitive variables in predicting learning satisfaction in Smart Schools. The population was all the primary school students studying in smart schools in the city of Shiraz in the school year 2014-2015. The sample, randomly chosen through multi-stage cluster sampling, was 383 primary school students studying in smart schools in Shiraz. The instruments were the Computer Self-Efficiency Questionnaire developed by Torkzadeh (2003, Performance Expectation Questionnaire developed by Compeau and Higgins (1995, System Functionality and Content Feature Questionnaire developed by Pituch and Lee (2006, Interaction Questionnaire developed by Johnston, Killion and Oomen (2005, Learning Climate Questionnaire developed by Chou` and Liu (2005 and Learning Satisfaction Questionnaire developed by Chou and Liu (2005. In order to determine the possible relationship between variables and to predict the changes in the degree of satisfaction, we made use of correlational procedures and step-wise regression analysis. The results indicated that all the socio-cognitive variables have a positive and significant correlation with learning satisfaction. Out of the socio-cognitive variables in question, Computer Self-Efficiency, Performance Expectation and Learning Climate significantly explained 53% of the variance of learning satisfaction.

  19. Variability in Cadence During Forced Cycling Predicts Motor Improvement in Individuals With Parkinson’s Disease

    Science.gov (United States)

    Ridgel, Angela L.; Abdar, Hassan Mohammadi; Alberts, Jay L.; Discenzo, Fred M.; Loparo, Kenneth A.

    2014-01-01

    Variability in severity and progression of Parkinson’s disease symptoms makes it challenging to design therapy interventions that provide maximal benefit. Previous studies showed that forced cycling, at greater pedaling rates, results in greater improvements in motor function than voluntary cycling. The precise mechanism for differences in function following exercise is unknown. We examined the complexity of biomechanical and physiological features of forced and voluntary cycling and correlated these features to improvements in motor function as measured by the Unified Parkinson’s Disease Rating Scale (UPDRS). Heart rate, cadence, and power were analyzed using entropy signal processing techniques. Pattern variability in heart rate and power were greater in the voluntary group when compared to forced group. In contrast, variability in cadence was higher during forced cycling. UPDRS Motor III scores predicted from the pattern variability data were highly correlated to measured scores in the forced group. This study shows how time series analysis methods of biomechanical and physiological parameters of exercise can be used to predict improvements in motor function. This knowledge will be important in the development of optimal exercise-based rehabilitation programs for Parkinson’s disease. PMID:23144045

  20. Age adjusted hematopoietic stem cell transplant comorbidity index predicts survival in a T-cell depleted cohort.

    Science.gov (United States)

    Saeed, Hayder; Yalamanchi, Swati; Liu, Meng; Van Meter, Emily; Gul, Zartash; Monohan, Gregory; Howard, Dianna; Hildebrandt, Gerhard C; Herzig, Roger

    2018-02-01

    Allogeneic hematopoietic stem cell transplant (HCT) continues to evolve with the treatment in higher risk patient population. This practice mandates stringent update and validation of risk stratification prior to undergoing such a complex and potentially fatal procedure. We examined the adoption of the new comorbidity index (HCT-CI/Age) proposed by the Seattle group after the addition of age variable and compared it to the pre-transplant assessment of mortality (PAM) that already incorporates age as part of its evaluation criteria. A retrospective analysis of adult patients who underwent HCT at our institution from January 2010 through August 2014 was performed. Kaplan-Meier's curve, log-rank tests, Cox model and Pearson correlation was used in the analysis. Of the 114 patients that underwent allogeneic transplant in our institution, 75.4% were ≥40 years old. More than 58% had a DLCO ≤80%. Although scores were positively correlated (correlation coefficient 0.43, p < 0.001), HCT-CI/Age more accurately predicted 2-year overall survival (OS) and non-relapse mortality (NRM) in patients with lower (0-4) and higher (5-7) scores (52% and 36% versus 24% and 76%, p = 0.004, 0.003 respectively). PAM score did not reach statistical significance for difference in OS nor NRM between the low (<24) and high-risk (≥24) groups (p = 0.19 for both). Despite our small sample population, HCT-CI/Age was more discriminative to identify patients with poor outcome that might benefit from intensified management strategies or other therapeutic approaches rather than allogeneic HCT. Copyright © 2018. Published by Elsevier B.V.

  1. Genomic prediction for Nordic Red Cattle using one-step and selection index blending

    DEFF Research Database (Denmark)

    Guosheng, Su; Madsen, Per; Nielsen, Ulrik Sander

    2012-01-01

    This study investigated the accuracy of direct genomic breeding values (DGV) using a genomic BLUP model, genomic enhanced breeding values (GEBV) using a one-step blending approach, and GEBV using a selection index blending approach for 15 traits of Nordic Red Cattle. The data comprised 6,631 bulls...... genotyped and nongenotyped bulls for one-step blending, and to scale DGV and its expected reliability in the selection index blending. Weighting (scaling) factors had a small influence on reliabilities of GEBV, but a large influence on the variation of GEBV. Based on the validation analyses, averaged over...... the 15 traits, the reliability of DGV for bulls without daughter records was 11.0 percentage points higher than the reliability of conventional pedigree index. Further gain of 0.9 percentage points was achieved by combining information from conventional pedigree index using the selection index blending...

  2. The hemorrhagic transformation index score: a prediction tool in middle cerebral artery ischemic stroke.

    Science.gov (United States)

    Kalinin, Mikhail N; Khasanova, Dina R; Ibatullin, Murat M

    2017-09-07

    We aimed to develop a tool, the hemorrhagic transformation (HT) index (HTI), to predict any HT within 14 days after middle cerebral artery (MCA) stroke onset regardless of the intravenous recombinant tissue plasminogen activator (IV rtPA) use. That is especially important in the light of missing evidence-based data concerning the timing of anticoagulant resumption after stroke in patients with atrial fibrillation (AF). We retrospectively analyzed 783 consecutive MCA stroke patients. Clinical and brain imaging data at admission were recorded. A follow-up period was 2 weeks after admission. The patients were divided into derivation (DC) and validation (VC) cohorts by generating Bernoulli variates with probability parameter 0.7. Univariate/multivariate logistic regression, and factor analysis were used to extract independent predictors. Validation was performed with internal consistency reliability and receiver operating characteristic (ROC) analysis. Bootstrapping was used to reduce bias. The HTI was composed of 4 items: Alberta Stroke Program Early CT score (ASPECTS), National Institutes of Health Stroke Scale (NIHSS), hyperdense MCA (HMCA) sign, and AF on electrocardiogram (ECG) at admission. According to the predicted probability (PP) range, scores were allocated to ASPECTS as follows: 10-7 = 0; 6-5 = 1; 4-3 = 2; 2-0 = 3; to NIHSS: 0-11 = 0; 12-17 = 1; 18-23 = 2; >23 = 3; to HMCA sign: yes = 1; to AF on ECG: yes = 1. The HTI score varied from 0 to 8. For each score, adjusted PP of any HT with 95% confidence intervals (CI) was as follows: 0 = 0.027 (0.011-0.042); 1 = 0.07 (0.043-0.098); 2 = 0.169 (0.125-0.213); 3 = 0.346 (0.275-0.417); 4 = 0.571 (0.474-0.668); 5 = 0.768 (0.676-0.861); 6 = 0.893 (0.829-0.957); 7 = 0.956 (0.92-0.992); 8 = 0.983 (0.965-1.0). The optimal cutpoint score to differentiate between HT-positive and negative groups was 2 (95% normal-based CI, 1-3) for the DC and VC alike. ROC area

  3. Prediction of SYM-H index during large storms by NARX neural network from IMF and solar wind data

    Directory of Open Access Journals (Sweden)

    L. Cai

    2010-02-01

    Full Text Available Similar to the Dst index, the SYM-H index may also serve as an indicator of magnetic storm intensity, but having distinct advantage of higher time-resolution. In this study the NARX neural network has been used for the first time to predict SYM-H index from solar wind (SW and IMF parameters. In total 73 time intervals of great storm events with IMF/SW data available from ACE satellite during 1998 to 2006 are used to establish the ANN model. Out of them, 67 are used to train the network and the other 6 samples for test. Additionally, the NARX prediction model is also validated using IMF/SW data from WIND satellite for 7 great storms during 1995–1997 and 2005, as well as for the July 2000 Bastille day storm and November 2001 superstorm using Geotail and OMNI data at 1 AU, respectively. Five interplanetary parameters of IMF Bz, By and total B components along with proton density and velocity of solar wind are used as the original external inputs of the neural network to predict the SYM-H index about one hour ahead. For the 6 test storms registered by ACE including two super-storms of min. SYM-H<−200 nT, the correlation coefficient between observed and NARX network predicted SYM-H is 0.95 as a whole, even as high as 0.95 and 0.98 with average relative variance of 13.2% and 7.4%, respectively, for the two super-storms. The prediction for the 7 storms with WIND data is also satisfactory, showing averaged correlation coefficient about 0.91 and RMSE of 14.2 nT. The newly developed NARX model shows much better capability than Elman network for SYM-H prediction, which can partly be attributed to a key feedback to the input layer from the output neuron with a suitable length (about 120 min. This feedback means that nearly real information of the ring current status is effectively directed to take part in the prediction of SYM-H index by ANN. The proper history length of the output-feedback may mainly reflect

  4. Prediction of SYM-H index during large storms by NARX neural network from IMF and solar wind data

    Directory of Open Access Journals (Sweden)

    L. Cai

    2010-02-01

    Full Text Available Similar to the Dst index, the SYM-H index may also serve as an indicator of magnetic storm intensity, but having distinct advantage of higher time-resolution. In this study the NARX neural network has been used for the first time to predict SYM-H index from solar wind (SW and IMF parameters. In total 73 time intervals of great storm events with IMF/SW data available from ACE satellite during 1998 to 2006 are used to establish the ANN model. Out of them, 67 are used to train the network and the other 6 samples for test. Additionally, the NARX prediction model is also validated using IMF/SW data from WIND satellite for 7 great storms during 1995–1997 and 2005, as well as for the July 2000 Bastille day storm and November 2001 superstorm using Geotail and OMNI data at 1 AU, respectively. Five interplanetary parameters of IMF Bz, By and total B components along with proton density and velocity of solar wind are used as the original external inputs of the neural network to predict the SYM-H index about one hour ahead. For the 6 test storms registered by ACE including two super-storms of min. SYM-H<−200 nT, the correlation coefficient between observed and NARX network predicted SYM-H is 0.95 as a whole, even as high as 0.95 and 0.98 with average relative variance of 13.2% and 7.4%, respectively, for the two super-storms. The prediction for the 7 storms with WIND data is also satisfactory, showing averaged correlation coefficient about 0.91 and RMSE of 14.2 nT. The newly developed NARX model shows much better capability than Elman network for SYM-H prediction, which can partly be attributed to a key feedback to the input layer from the output neuron with a suitable length (about 120 min. This feedback means that nearly real information of the ring current status is effectively directed to take part in the prediction of SYM-H index by ANN. The proper history length of the output-feedback may mainly reflect on average the characteristic time of ring

  5. A variable capacitance based modeling and power capability predicting method for ultracapacitor

    Science.gov (United States)

    Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang

    2018-01-01

    Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

  6. Removing batch effects for prediction problems with frozen surrogate variable analysis

    Directory of Open Access Journals (Sweden)

    Hilary S. Parker

    2014-09-01

    Full Text Available Batch effects are responsible for the failure of promising genomic prognostic signatures, major ambiguities in published genomic results, and retractions of widely-publicized findings. Batch effect corrections have been developed to remove these artifacts, but they are designed to be used in population studies. But genomic technologies are beginning to be used in clinical applications where samples are analyzed one at a time for diagnostic, prognostic, and predictive applications. There are currently no batch correction methods that have been developed specifically for prediction. In this paper, we propose an new method called frozen surrogate variable analysis (fSVA that borrows strength from a training set for individual sample batch correction. We show that fSVA improves prediction accuracy in simulations and in public genomic studies. fSVA is available as part of the sva Bioconductor package.

  7. Recent and Past Musical Activity Predicts Cognitive Aging Variability: Direct Comparison with Leisure Activities

    Directory of Open Access Journals (Sweden)

    Brenda eHanna-Pladdy

    2012-07-01

    Full Text Available Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years on preserved cognitive functioning in advanced age . These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to nonmusical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study examined the type of leisure activity (musical versus other as well as the timing of engagement (age of acquisition, past versus recent in predictive models of successful cognitive aging. Seventy age and education matched older musicians (> 10 years and nonmusicians (ages 59-80 were evaluated on neuropsychological tests and life-style activities (AAP. Partition analyses were conducted on significant cognitive measures to explain performance variance in musicians. Musicians scored higher on tests of phonemic fluency, verbal immediate recall, judgment of line orientation (JLO, and Letter Number Sequencing (LNS, but not the AAP. The first partition analysis revealed education best predicted JLO in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (< 9 years predicted enhanced LNS in musicians, while analyses for AAP, verbal recall and fluency were not predictive. Recent and past musical activity, but not leisure activity, predicted variability across verbal and visuospatial domains in aging. Early musical acquisition predicted auditory

  8. Waist Circumference, Body Mass Index, and Other Measures of Adiposity in Predicting Cardiovascular Disease Risk Factors among Peruvian Adults

    OpenAIRE

    Knowles, K. M.; Paiva, L. L.; Sanchez, S. E.; Revilla, L.; Lopez, T.; Yasuda, M. B.; Yanez, N. D.; Gelaye, B.; Williams, M. A.

    2011-01-01

    Objectives. To examine the extent to which measures of adiposity can be used to predict selected components of metabolic syndrome (MetS) and elevated C-reactive protein (CRP). Methods. A total of 1,518 Peruvian adults were included in this study. Waist circumference (WC), body mass index (BMI), waist-hip ratio (WHR), waist-height ratio (WHtR), and visceral adiposity index (VAI) were examined. The prevalence of each MetS component was determined according to tertiles of each anthropometric mea...

  9. A comparative study on approximate entropy measure and poincaré plot indexes of minimum foot clearance variability in the elderly during walking

    Directory of Open Access Journals (Sweden)

    Begg Rezaul K

    2008-02-01

    Full Text Available Abstract Background Trip-related falls which is a major problem in the elderly population, might be linked to declines in the balance control function due to ageing. Minimum foot clearance (MFC which provides a more sensitive measure of the motor function of the locomotor system, has been identified as a potential gait parameter associated with trip-related falls in older population. This paper proposes nonlinear indexes (approximate entropy (ApEn and Poincaré plot indexes of MFC variability and investigates the relationship of MFC with derived indexes of elderly gait patterns. The main aim is to find MFC variability indexes that well correlate with balance impairments. Methods MFC data during treadmill walking for 14 healthy elderly and 10 elderly participants with balance problems and a history of falls (falls risk were analysed using a PEAK-2D motion analysis system. ApEn and Poincaré plot indexes of all MFC data sets were calculated and compared. Results Significant relationships of mean MFC with Poincaré plot indexes (SD1, SD2 and ApEn (r = 0.70, p Conclusion Results have implication for quantifying gait dynamics in normal and pathological conditions, thus could be useful for the early diagnosis of at-risk gait. Further research should provide important information on whether falls prevention intervention can improve the gait performance of falls risk elderly by monitoring the change in MFC variability indexes.

  10. Drivers and potential predictability of summer time North Atlantic polar front jet variability

    Science.gov (United States)

    Hall, Richard J.; Jones, Julie M.; Hanna, Edward; Scaife, Adam A.; Erdélyi, Róbert

    2017-06-01

    The variability of the North Atlantic polar front jet stream is crucial in determining summer weather around the North Atlantic basin. Recent extreme summers in western Europe and North America have highlighted the need for greater understanding of this variability, in order to aid seasonal forecasting and mitigate societal, environmental and economic impacts. Here we find that simple linear regression and composite models based on a few predictable factors are able to explain up to 35 % of summertime jet stream speed and latitude variability from 1955 onwards. Sea surface temperature forcings impact predominantly on jet speed, whereas solar and cryospheric forcings appear to influence jet latitude. The cryospheric associations come from the previous autumn, suggesting the survival of an ice-induced signal through the winter season, whereas solar influences lead jet variability by a few years. Regression models covering the earlier part of the twentieth century are much less effective, presumably due to decreased availability of data, and increased uncertainty in observational reanalyses. Wavelet coherence analysis identifies that associations fluctuate over the study period but it is not clear whether this is just internal variability or genuine non-stationarity. Finally we identify areas for future research.

  11. Using a predictive model to evaluate spatiotemporal variability in streamflow permanence across the Pacific Northwest region

    Science.gov (United States)

    Jaeger, K. L.

    2017-12-01

    The U.S. Geological Survey (USGS) has developed the PRObability Of Streamflow PERmanence (PROSPER) model, a GIS-based empirical model that provides predictions of the annual probability of a stream channel having year-round flow (Streamflow permanence probability; SPP) for any unregulated and minimally-impaired stream channel in the Pacific Northwest (Washington, Oregon, Idaho, western Montana). The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions, and static physiographic variables associated with the upstream basin. Prediction locations correspond to the channel network consistent with the National Hydrography Dataset stream grid and are publicly available through the USGS StreamStats platform (https://water.usgs.gov/osw/streamstats/). In snowmelt-driven systems, the most informative predictor variable was mean upstream snow water equivalent on May 1, which highlights the influence of late spring snow cover for supporting streamflow in mountain river networks. In non-snowmelt-driven systems, the most informative variable was mean annual precipitation. Streamflow permanence probabilities varied across the study area by geography and from year-to-year. Notably lower SPP corresponded to the climatically drier subregions of the study area. Higher SPP were concentrated in coastal and higher elevation mountain regions. In addition, SPP appeared to trend with average hydroclimatic conditions, which were also geographically coherent. The year-to-year variability lends support for the growing recognition of the spatiotemporal dynamism of streamflow permanence. An analysis of three focus basins located in contrasting geographical and hydroclimatic settings demonstrates differences in the sensitivity of streamflow permanence to antecedent climate conditions as a function of geography. Consequently, results suggest that PROSPER model can be a useful tool to evaluate regions of the

  12. A Behavioral Economic Reward Index Predicts Drinking Resolutions: Moderation Re-visited and Compared with Other Outcomes

    Science.gov (United States)

    Tucker, Jalie A.; Roth, David L.; Vignolo, Mary J.; Westfall, Andrew O.

    2014-01-01

    Data were pooled from three studies of recently resolved community-dwelling problem drinkers to determine whether a behavioral economic index of the value of rewards available over different time horizons distinguished among moderation (n = 30), abstinent (n = 95), and unresolved (n = 77) outcomes. Moderation over 1-2 year prospective follow-up intervals was hypothesized to involve longer term behavior regulation processes compared to abstinence or relapse and to be predicted by more balanced pre-resolution monetary allocations between short- and longer-term objectives (i.e., drinking and saving for the future). Standardized odds ratios (OR) based on changes in standard deviation units from a multinomial logistic regression indicated that increases on this “Alcohol-Savings Discretionary Expenditure” index predicted higher rates of both abstinence (OR = 1.93, p = .004) and relapse (OR = 2.89, p moderation outcomes. The index had incremental utility in predicting moderation in complex models that included other established predictors. The study adds to evidence supporting a behavioral economic analysis of drinking resolutions and shows that a systematic analysis of pre-resolution spending patterns aids in predicting moderation. PMID:19309182

  13. Hemolysis is associated with low reticulocyte production index and predicts blood transfusion in severe malarial anemia.

    Directory of Open Access Journals (Sweden)

    Rolf Fendel

    Full Text Available BACKGROUND: Falciparum Malaria, an infectious disease caused by the apicomplexan parasite Plasmodium falciparum, is among the leading causes of death and morbidity attributable to infectious diseases worldwide. In Gabon, Central Africa, one out of four inpatients have severe malarial anemia (SMA, a life-threatening complication if left untreated. Emerging drug resistant parasites might aggravate the situation. This case control study investigates biomarkers of enhanced hemolysis in hospitalized children with either SMA or mild malaria (MM. METHODS AND FINDINGS: Ninety-one children were included, thereof 39 SMA patients. Strict inclusion criteria were chosen to exclude other causes of anemia. At diagnosis, erythrophagocytosis (a direct marker for extravascular hemolysis, EVH was enhanced in SMA compared to MM patients (5.0 arbitrary units (AU (interquartile range (IR: 2.2-9.6 vs. 2.1 AU (IR: 1.3-3.9, p<0.01. Furthermore, indirect markers for EVH, (i.e. serum neopterin levels, spleen size enlargement and monocyte pigment were significantly increased in SMA patients. Markers for erythrocyte ageing, such as CD35 (complement receptor 1, CD55 (decay acceleration factor and phosphatidylserine exposure (annexin-V-binding were investigated by flow cytometry. In SMA patients, levels of CD35 and CD55 on the red blood cell surface were decreased and erythrocyte removal markers were increased when compared to MM or reconvalescent patients. Additionally, intravascular hemolysis (IVH was quantified using several indirect markers (LDH, alpha-HBDH, haptoglobin and hemopexin, which all showed elevated IVH in SMA. The presence of both IVH and EVH predicted the need for blood transfusion during antimalarial treatment (odds ratio 61.5, 95% confidence interval (CI: 8.9-427. Interestingly, this subpopulation is characterized by a significantly lowered reticulocyte production index (RPI, p<0.05. CONCLUSIONS: Our results show the multifactorial pathophysiology of SMA

  14. Predictive performance of the visceral adiposity index for a visceral adiposity-related risk: Type 2 Diabetes

    Directory of Open Access Journals (Sweden)

    Azizi Fereidoun

    2011-05-01

    Full Text Available Abstract Background Visceral adiposity index (VAI has recently been developed based on waist circumference, body mass index (BMI, triglycerides (TGs, and high-density lipoprotein cholesterol (HDL-C. We examined predictive performances for incident diabetes of the VAI per se and as compared to the metabolic syndrome (MetS and waist-to-height-ratio (WHtR. Methods Participants free of diabetes at baseline with at least one follow-up examination (5,964 were included for the current study. Weibull regression models were developed for interval-censored survival data. Absolute and relative integrated discriminatory improvement index (IDI and cut-point-based and cut-point-free net reclassification improvement index (NRI were used as measures of predictive ability for incident diabetes added by VAI, as compared to the MetS and WHtR. Results The annual incidence rate of diabetes was 0.85 per 1000 person. Mean VAI was 3.06 (95%CIs 2.99-3.13. Diabetes risk factors levels increased in stepwise fashion across VAI quintiles. Risk gradient between the highest and lowest quintile of VAI was 4.5 (95%CIs 3.0-6.9. VAI significantly improved predictive ability of the MetS. The relative IDI and cut-point free NRI for predictive ability added to MetS by VAI were 30.3% (95%CIs 18.8-41.8% and 30.7% (95%CIs 20.8-40.7%, respectively. WHtR, outperformed VAI with cut-point-free NRI of 24.6% (95%CIs 14.1-35.2%. Conclusions In conclusion, although VAI could be a prognostic tool for incident diabetes events, gathering information on its components (WC, BMI, TGs, and HDL-C is unlikely to improve the prediction ability beyond what could be achieved by the simply assessable and commonly available information on WHtR.

  15. A study on the abundance of quartz in thermal coals of India and its relation to abrasion index: Development of predictive model for abrasion

    Energy Technology Data Exchange (ETDEWEB)

    Bandopadhyay, A.K. [Central Institute of Mining and Fuel Research Digwadih Campus, P.O.-FRI, Dhanbad-828108, Jharkhand (India)

    2010-10-01

    The quartz content of each of the 61 thermal coals used in power stations in India has been determined using Fourier Transform Infra-Red (FTIR) Spectroscopy. It has been observed that quartz is abundant in the thermal coals and its proportion varies from 5 to 20% by wt. The abrasion index (AI), a measure of abrasion caused by coals, has been determined for each coal according to the procedure laid down in Indian Standard IS: 9949-1986. The data generated on abrasion together with ash and quartz percentages of the coals studied have been subjected to regression and correlation analysis. Positive correlations have been found between AI and quartz content and between AI and ash yield, but the correlation between AI and ash (A) and quartz (Q) percentages has been observed to be the most significant (R{sup 2} = 0.86). The linear regression model AI = 1.00A + 1.35Q thus developed has the ability to predict AI of the thermal coals within {+-} 10 mg/kg at 95.5% confidence level. Results of application of the model to predicting abrasion of a limited number of foreign coals with different origins have been found to be encouraging. Integration of other variables like the size and the shape of the abrading particles along with other physical properties of coal, like the bulk density and the grindability, with the model, in addition to the variables already considered, has been suggested for improved prediction. (author)

  16. Predictive value of body mass index to metabolic syndrome risk factors in Syrian adolescents.

    Science.gov (United States)

    Al-Bachir, Mahfouz; Bakir, Mohamad Adel

    2017-06-25

    Obesity has become a serious epidemic health problem in both developing and developed countries. There is much evidence that obesity among adolescents contributed significantly to the development of type 2 diabetes and coronary heart disease in adulthood. Very limited information exists on the prevalence of overweight, obesity, and associated metabolic risk factors among Syrian adolescents. Therefore, the purpose of this study was to determine the relationship between obesity determined by body mass index and the major metabolic risk factors among Syrian adolescents. A cross-sectional study of a randomly selected sample of 2064 apparently healthy Syrian adolescents aged 18 to 19 years from Damascus city, in Syria, was performed. Body mass index and blood pressure were measured. Serum concentrations of glucose, triglycerides, total cholesterol, high-density lipoprotein-cholesterol, and low-density lipoprotein-cholesterol were determined. Metabolic syndrome was defined using the national criteria for each determined metabolic risk factor. Individuals with a body mass index 25 to 29.9 were classified as overweight, whereas individuals with a body mass index ≥30 were classified as obese. A receiver operating characteristics curve was drawn to determine appropriate cut-off points of the body mass index for defining overweight and obesity, and to indicate the performance of body mass index as a predictor of risk factors. The obtained data showed that blood pressure and the overall mean concentrations of fasting blood sugar, triglycerides, cholesterol, low-density lipoprotein-cholesterol, and triglycerides/high-density lipoprotein-cholesterol were significantly higher in overweight and obese adolescent groups (p index and some metabolic risks, the data suggest the best body mass index cut-offs ranged between 23.25 and 24.35 kg/m 2 . A strong association between overweight and obesity as determined by body mass index and high concentrations of metabolic syndrome

  17. Multi-omics facilitated variable selection in Cox-regression model for cancer prognosis prediction.

    Science.gov (United States)

    Liu, Cong; Wang, Xujun; Genchev, Georgi Z; Lu, Hui

    2017-07-15

    New developments in high-throughput genomic technologies have enabled the measurement of diverse types of omics biomarkers in a cost-efficient and clinically-feasible manner. Developing computational methods and tools for analysis and translation of such genomic data into clinically-relevant information is an ongoing and active area of investigation. For example, several studies have utilized an unsupervised learning framework to cluster patients by integrating omics data. Despite such recent advances, predicting cancer prognosis using integrated omics biomarkers remains a challenge. There is also a shortage of computational tools for predicting cancer prognosis by using supervised learning methods. The current standard approach is to fit a Cox regression model by concatenating the different types of omics data in a linear manner, while penalty could be added for feature selection. A more powerful approach, however, would be to incorporate data by considering relationships among omics datatypes. Here we developed two methods: a SKI-Cox method and a wLASSO-Cox method to incorporate the association among different types of omics data. Both methods fit the Cox proportional hazards model and predict a risk score based on mRNA expression profiles. SKI-Cox borrows the information generated by these additional types of omics data to guide variable selection, while wLASSO-Cox incorporates this information as a penalty factor during model fitting. We show that SKI-Cox and wLASSO-Cox models select more true variables than a LASSO-Cox model in simulation studies. We assess the performance of SKI-Cox and wLASSO-Cox using TCGA glioblastoma multiforme and lung adenocarcinoma data. In each case, mRNA expression, methylation, and copy number variation data are integrated to predict the overall survival time of cancer patients. Our methods achieve better performance in predicting patients' survival in glioblastoma and lung adenocarcinoma. Copyright © 2017. Published by Elsevier

  18. Recent and past musical activity predicts cognitive aging variability: direct comparison with general lifestyle activities.

    Science.gov (United States)

    Hanna-Pladdy, Brenda; Gajewski, Byron

    2012-01-01

    Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years) on preserved cognitive functioning in advanced age. These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to non-musical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in general lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study controlled for general activity level in evaluating cognition between musicians and nomusicians. Also, the timing of engagement (age of acquisition, past versus recent) was assessed in predictive models of successful cognitive aging. Seventy age and education matched older musicians (>10 years) and non-musicians (ages 59-80) were evaluated on neuropsychological tests and general lifestyle activities. Musicians scored higher on tests of phonemic fluency, verbal working memory, verbal immediate recall, visuospatial judgment, and motor dexterity, but did not differ in other general leisure activities. Partition analyses were conducted on significant cognitive measures to determine aspects of musical training predictive of enhanced cognition. The first partition analysis revealed education best predicted visuospatial functions in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (memory in musicians, while analyses for other measures were not predictive. Recent and past musical activity, but not general lifestyle activities, predicted variability

  19. Stochastic variability in stress, sleep duration, and sleep quality across the distribution of body mass index: insights from quantile regression.

    Science.gov (United States)

    Yang, Tse-Chuan; Matthews, Stephen A; Chen, Vivian Y-J

    2014-04-01

    Obesity has become a problem in the USA and identifying modifiable factors at the individual level may help to address this public health concern. A burgeoning literature has suggested that sleep and stress may be associated with obesity; however, little is know about whether these two factors moderate each other and even less is known about whether their impacts on obesity differ by gender. This study investigates whether sleep and stress are associated with body mass index (BMI) respectively, explores whether the combination of stress and sleep is also related to BMI, and demonstrates how these associations vary across the distribution of BMI values. We analyze the data from 3,318 men and 6,689 women in the Philadelphia area using quantile regression (QR) to evaluate the relationships between sleep, stress, and obesity by gender. Our substantive findings include: (1) high and/or extreme stress were related to roughly an increase of 1.2 in BMI after accounting for other covariates; (2) the pathways linking sleep and BMI differed by gender, with BMI for men increasing by 0.77-1 units with reduced sleep duration and BMI for women declining by 0.12 unit with 1 unit increase in sleep quality; (3) stress- and sleep-related variables were confounded, but there was little evidence for moderation between these two; (4) the QR results demonstrate that the association between high and/or extreme stress to BMI varied stochastically across the distribution of BMI values, with an upward trend, suggesting that stress played a more important role among adults with higher BMI (i.e., BMI > 26 for both genders); and (5) the QR plots of sleep-related variables show similar patterns, with stronger effects on BMI at the upper end of BMI distribution. Our findings suggested that sleep and stress were two seemingly independent predictors for BMI and their relationships with BMI were not constant across the BMI distribution.

  20. Ferritin and body mass index predict cardiac dysfunction in female adolescents with anorexia of the restrictive type.

    Science.gov (United States)

    Docx, Martine K F; Weyler, Joost; Simons, Annik; Ramet, José; Mertens, Luc

    2015-08-01

    Decreased left ventricular mass index in anorexia nervosa is amply reported. The aim of this study is to identify non-burdensome predictors of reduced left yentricular mass/height (cLVM) in a cohort of adolescent restrictive anorexic girls. This is a retrospective study of all anorexic girls of the restrictive type referred to our tertiary eating disorder unit between September 2002 and December 2012, for somatic assessment of weig ht loss. All subjects fulfilled DMS-IV criteria, without a family history of cardiac or cardiovascular diseases. In all, 283 restrictive anorexic girls (age: 14.63 +/- 1.65 y; body mass index: 15.72 +/- 1.81 kg/m2) were included. Ferritin and body mass index were independent, statistically significant predictors of the corrected left ventricular mass (P anorexia nervosa of the restrictive type. Two factors predicted decreased cLVM in our population: ferritin and BMI.

  1. Models for the prediction of the cetane index of biofuels obtained from different vegetable oils using their fatty acid composition

    International Nuclear Information System (INIS)

    Sanchez Borroto, Yisel; Piloto Rodriguez, Ramon; Goyos Perez, Leonardo

    2011-01-01

    The objective of the present work is to obtain a physical-mathematical model that establishes a relationship between the cetane index of biofuels obtained from different vegetable oils and its composition of essential fatty acid. This model is based on experimental data obtained by the authors of the present work and an experimental data reported by different extracted authors of indexed databases. The adjustment of the coefficients of the model is based on the obtaining of residual minima in the capacity of prediction of the model. Starting from these results it is established a very useful tool for the determination of such an important parameter for the fuel diesel as it is the cetane index obtained from an analysis of chemical composition and not obtained from tests in engines banks, to save time and economic resources. (author)

  2. Biographical and demographical variables as moderators in the prediction of turnover intentions

    Directory of Open Access Journals (Sweden)

    Janine du Plooy

    2013-04-01

    Full Text Available Orientation: The aim of the study was to explore the possible moderation effects of biographical and demographical variables on a prediction model of turnover intention (TI. Research purpose: The main purpose of the study was to determine how biographical and demographical variables have an impact on predictors of turnover intentions. Motivation for the study: Twenty-first century organisations face significant challenges in the management of talent and human capital. One in particular is voluntary employee turnover and the lack of appropriate business models to track this process. Research design, approach, and method: A secondary data analysis (SDA was performed in a quantitative research tradition on the cross-sectional survey sample (n = 2429. Data were collected from a large South African Information and Communication Technologies (ICT sector company (N = 23 134. Main findings: The results of the study confirmed significant moderation effects regarding race, age, and marital status in the prediction equations of TIs. Practical and managerial implications: Practical implications of the study suggested increased understanding of workforce diversity effects within the human resource (HR value chain, with resultant evidence-based, employee retention strategies and interventions. Issues concerning talent management could also be addressed. Contribution and value-add: The study described in this article took Industrial/Organisational (I/O psychological concepts and linked them in unique combinations to establish better predictive validity of a more comprehensive turnover intentions model.

  3. Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure

    Directory of Open Access Journals (Sweden)

    Yong-Hong Zhang

    2015-05-01

    Full Text Available Assessing the human placental barrier permeability of drugs is very important to guarantee drug safety during pregnancy. Quantitative structure–activity relationship (QSAR method was used as an effective assessing tool for the placental transfer study of drugs, while in vitro human placental perfusion is the most widely used method. In this study, the partial least squares (PLS variable selection and modeling procedure was used to pick out optimal descriptors from a pool of 620 descriptors of 65 compounds and to simultaneously develop a QSAR model between the descriptors and the placental barrier permeability expressed by the clearance indices (CI. The model was subjected to internal validation by cross-validation and y-randomization and to external validation by predicting CI values of 19 compounds. It was shown that the model developed is robust and has a good predictive potential (r2 = 0.9064, RMSE = 0.09, q2 = 0.7323, rp2 = 0.7656, RMSP = 0.14. The mechanistic interpretation of the final model was given by the high variable importance in projection values of descriptors. Using PLS procedure, we can rapidly and effectively select optimal descriptors and thus construct a model with good stability and predictability. This analysis can provide an effective tool for the high-throughput screening of the placental barrier permeability of drugs.

  4. What variables are important in predicting bovine viral diarrhea virus? A random forest approach.

    Science.gov (United States)

    Machado, Gustavo; Mendoza, Mariana Recamonde; Corbellini, Luis Gustavo

    2015-07-24

    Bovine viral diarrhea virus (BVDV) causes one of the most economically important diseases in cattle, and the virus is found worldwide. A better understanding of the disease associated factors is a crucial step towards the definition of strategies for control and eradication. In this study we trained a random forest (RF) prediction model and performed variable importance analysis to identify factors associated with BVDV occurrence. In addition, we assessed the influence of features selection on RF performance and evaluated its predictive power relative to other popular classifiers and to logistic regression. We found that RF classification model resulted in an average error rate of 32.03% for the negative class (negative for BVDV) and 36.78% for the positive class (positive for BVDV).The RF model presented area under the ROC curve equal to 0.702. Variable importance analysis revealed that important predictors of BVDV occurrence were: a) who inseminates the animals, b) number of neighboring farms that have cattle and c) rectal palpation performed routinely. Our results suggest that the use of machine learning algorithms, especially RF, is a promising methodology for the analysis of cross-sectional studies, presenting a satisfactory predictive power and the ability to identify predictors that represent potential risk factors for BVDV investigation. We examined classical predictors and found some new and hard to control practices that may lead to the spread of this disease within and among farms, mainly regarding poor or neglected reproduction management, which should be considered for disease control and eradication.

  5. Discrete curved ray-tracing method for radiative transfer in an absorbing-emitting semitransparent slab with variable spatial refractive index

    International Nuclear Information System (INIS)

    Liu, L.H.

    2004-01-01

    A discrete curved ray-tracing method is developed to analyze the radiative transfer in one-dimensional absorbing-emitting semitransparent slab with variable spatial refractive index. The curved ray trajectory is locally treated as straight line and the complicated and time-consuming computation of ray trajectory is cut down. A problem of radiative equilibrium with linear variable spatial refractive index is taken as an example to examine the accuracy of the proposed method. The temperature distributions are determined by the proposed method and compared with the data in references, which are obtained by other different methods. The results show that the discrete curved ray-tracing method has a good accuracy in solving the radiative transfer in one-dimensional semitransparent slab with variable spatial refractive index

  6. Can transient elastography, Fib-4, Forns Index, and Lok Score predict esophageal varices in HCV-related cirrhotic patients?

    Science.gov (United States)

    Hassan, Eman M; Omran, Dalia A; El Beshlawey, Mohamad L; Abdo, Mahmoud; El Askary, Ahmad

    2014-02-01

    Gastroesophageal varices are present in approximately 50% of patients with liver cirrhosis. The aim of this study was to evaluate liver stiffness measurement (LSM), Fib-4, Forns Index and Lok Score as noninvasive predictors of esophageal varices (EV). This prospective study included 65 patients with HCV-related liver cirrhosis. All patients underwent routine laboratory tests, transient elastograhy (TE) and esophagogastroduodenoscopy. FIB-4, Forns Index and Lok Score were calculated. The diagnostic performances of these methods were assessed using sensitivity, specificity, positive predictive value, negative predictive value, accuracy and receiver operating characteristic curves. All predictors (LSM, FIB-4, Forns Index and Lok Score) demonstrated statistically significant correlation with the presence and the grade of EV. TE could diagnose EV at a cutoff value of 18.2kPa. Fib-4, Forns Index, and Lok Score could diagnose EV at cutoff values of 2.8, 6.61 and 0.63, respectively. For prediction of large varices (grade 2, 3), LSM showed the highest accuracy (80%) with a cutoff of 22.4kPa and AUROC of 0.801. Its sensitivity was 84%, specificity 72%, PPV 84% and NPV 72%. The diagnostic accuracies of FIB-4, Forns Index and Lok Score were 70%, 70% and76%, respectively, at cutoffs of 3.3, 6.9 and 0.7, respectively. For diagnosis of large esophageal varices, adding TE to each of the other diagnostic indices (serum fibrosis scores) increased their sensitivities with little decrease in their specificities. Moreover, this combination decreased the LR- in all tests. Noninvasive predictors can restrict endoscopic screening. This is very important as non invasiveness is now a major goal in hepatology. Copyright © 2013 Elsevier España, S.L. and AEEH y AEG. All rights reserved.

  7. Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi

    Science.gov (United States)

    Hayes, Catherine

    2005-07-01

    This study sought to identify a variable or variables predictive of attrition among baccalaureate nursing students. The study was quantitative in design and multivariate correlational statistics and discriminant statistical analysis were used to identify a model for prediction of attrition. The analysis then weighted variables according to their predictive value to determine the most parsimonious model with the greatest predictive value. Three public university nursing education programs in Mississippi offering a Bachelors Degree in Nursing were selected for the study. The population consisted of students accepted and enrolled in these three programs for the years 2001 and 2002 and graduating in the years 2003 and 2004 (N = 195). The categorical dependent variable was attrition (includes academic failure or withdrawal) from the program of nursing education. The ten independent variables selected for the study and considered to have possible predictive value were: Grade Point Average for Pre-requisite Course Work; ACT Composite Score, ACT Reading Subscore, and ACT Mathematics Subscore; Letter Grades in the Courses: Anatomy & Physiology and Lab I, Algebra I, English I (101), Chemistry & Lab I, and Microbiology & Lab I; and Number of Institutions Attended (Universities, Colleges, Junior Colleges or Community Colleges). Descriptive analysis was performed and the means of each of the ten independent variables was compared for students who attrited and those who were retained in the population. The discriminant statistical analysis performed created a matrix using the ten variable model that was able to correctly predicted attrition in the study's population in 77.6% of the cases. Variables were then combined and recombined to produce the most efficient and parsimonious model for prediction. A six variable model resulted which weighted each variable according to predictive value: GPA for Prerequisite Coursework, ACT Composite, English I, Chemistry & Lab I, Microbiology

  8. Global scale variability of the mineral dust long-wave refractive index: a new dataset of in situ measurements for climate modeling and remote sensing

    Science.gov (United States)

    Di Biagio, Claudia; Formenti, Paola; Balkanski, Yves; Caponi, Lorenzo; Cazaunau, Mathieu; Pangui, Edouard; Journet, Emilie; Nowak, Sophie; Caquineau, Sandrine; Andreae, Meinrat O.; Kandler, Konrad; Saeed, Thuraya; Piketh, Stuart; Seibert, David; Williams, Earle; Doussin, Jean-François

    2017-02-01

    Modeling the interaction of dust with long-wave (LW) radiation is still a challenge because of the scarcity of information on the complex refractive index of dust from different source regions. In particular, little is known about the variability of the refractive index as a function of the dust mineralogical composition, which depends on the specific emission source, and its size distribution, which is modified during transport. As a consequence, to date, climate models and remote sensing retrievals generally use a spatially invariant and time-constant value for the dust LW refractive index. In this paper, the variability of the mineral dust LW refractive index as a function of its mineralogical composition and size distribution is explored by in situ measurements in a large smog chamber. Mineral dust aerosols were generated from 19 natural soils from 8 regions: northern Africa, the Sahel, eastern Africa and the Middle East, eastern Asia, North and South America, southern Africa, and Australia. Soil samples were selected from a total of 137 available samples in order to represent the diversity of sources from arid and semi-arid areas worldwide and to account for the heterogeneity of the soil composition at the global scale. Aerosol samples generated from soils were re-suspended in the chamber, where their LW extinction spectra (3-15 µm), size distribution, and mineralogical composition were measured. The generated aerosol exhibits a realistic size distribution and mineralogy, including both the sub- and super-micron fractions, and represents in typical atmospheric proportions the main LW-active minerals, such as clays, quartz, and calcite. The complex refractive index of the aerosol is obtained by an optical inversion based upon the measured extinction spectrum and size distribution. Results from the present study show that the imaginary LW refractive index (k) of dust varies greatly both in magnitude and spectral shape from sample to sample, reflecting the

  9. Effect of coffee and tea on the glycaemic index of foods: no effect on mean but reduced variability.

    Science.gov (United States)

    Aldughpassi, Ahmed; Wolever, Thomas M S

    2009-05-01

    Coffee and tea may influence glycaemic responses but it is not clear whether they affect the glycaemic index (GI) value of foods. Therefore, to see if coffee and tea affected the mean and SEM of GI values, the GI of fruit leather (FL) and cheese puffs (CP) were determined twice in ten subjects using the FAO/WHO protocol with white bread as the reference food. In one series subjects chose to drink 250 ml of either coffee or tea with all test meals, while in the other series they drank 250 ml water. The tests for both series were conducted as a single experiment with the order of all tests being randomised. Coffee and tea increased the overall mean peak blood glucose increment compared with water by 0.25 (SEM 0.09) mmol/l (P=0.02), but did not significantly affect the incremental area under the glucose response curve. Mean GI values were not affected by coffee or tea but the SEM was reduced by about 30% (FL: 31 (SEM 4) v. 35 (SEM 7) and CP: 76 (SEM 6) v. 75 (SEM 8) for coffee or tea v. water, respectively). The error mean square term from the ANOVA of the GI values was significantly smaller for coffee or tea v. water (F(18, 18) = 2.31; P=0.04). We conclude that drinking coffee or tea with test meals does not affect the mean GI value obtained, but may reduce variability and, hence, improve precision.

  10. Identifying psychosocial variables that predict safer-sex intentions in adolescents and young adults

    Directory of Open Access Journals (Sweden)

    Phil eBrüll

    2016-04-01

    Full Text Available Young people are especially vulnerable to sexually transmitted infections. The triad of deliberate and effective safer-sex behavior encompasses condom use, combined with additional information about a partner’s sexual health, and the kind of sex acts usually performed. To identify psychosocial predictors of young people’s intentions to have safer sex, as related to this triad we conducted an online study with 211 sexually active participants aged between 18 and 24 years. Predictors (i.e. perceived behavioural control, subjective norms and intention taken from Fishbein and Ajzen’s Reasoned Action Approach (RAA, were combined with more distal variables (e.g. behavioral inhibition, sensation seeking, parental monitoring, and knowledge about sexually transmitted infections. Beyond the highly predictive power of RAA variables, additional variance was explained by the number of instances of unprotected sexual intercourse during the last twelve months and reasons for using barrier protection during first sexual intercourse. In particular, past condom nonuse behavior moderated perceived behavioral control related to intended condom use. Further, various distal variables showed significant univariate associations with intentions related to the three behaviors of interest. It may, therefore, be helpful to include measures of past behavior as well as certain additional distal variables in future safer-sex programs designed to promote health sustaining sexual behavior.

  11. 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.

  12. Effects of hypocaloric diets with different glycemic indexes on endothelial function and glycemic variability in overweight and in obese adult patients at increased cardiovascular risk.

    Science.gov (United States)

    Buscemi, Silvio; Cosentino, Loretta; Rosafio, Giuseppe; Morgana, Manuela; Mattina, Alessandro; Sprini, Delia; Verga, Salvatore; Rini, Giovam Battista

    2013-06-01

    The role of glycemic index of the diet in glucose control and cardiovascular prevention is still not clear. The aim of this study was to determine the effects of hypocaloric diets with different glycemic indexes and glycemic loads on endothelial function and glycemic variability in nondiabetic participants at increased cardiovascular risk. Forty nondiabetic obese participants were randomly assigned to a three-month treatment with either a low glycemic index (LGI; n=19) or high glycemic index (HGI; n=21) hypocaloric diet with similar macronutrient and fiber content. Endothelial function was measured as flow-mediated dilatation (FMD) of the brachial artery before and after dieting. In addition, 48-h continuous subcutaneous glucose monitoring was done before and after dieting in a subgroup of 24 participants. The amount of weight loss after dieting was similar in both groups. The glycemic index of the diet significantly influenced the FMD (Pdiet, and -0.9±3.6% after the HGI diet (Pdiet on results was observed. The glycemic index of the diet significantly influenced the 48-h glycemic variability measured as coefficient of variability (CV%; Pdiet (from 23.5 to 20.0%) and increased after the HGI diet (from 23.6 to 26.6%). The change in percentage of FMD was inversely correlated with the change in the 48-h glycemic CV% (r=-0.45; Phypocaloric diet in nondiabetic obese persons. ISRCTN56834511. Copyright © 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

  13. Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

    Science.gov (United States)

    Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

    2017-12-01

    Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in

  14. Seasonal predictions of Fire Weather Index: Paving the way for their operational applicability in Mediterranean Europe

    OpenAIRE

    Joaquín Bedia; Nicola Golding; Ana Casanueva; Maialen Iturbide; Carlo Buontempo; Jose Manuel Gutiérrez

    2018-01-01

    Managers of wildfire-prone landscapes in the Euro-Mediterranean region would greatly benefit from fire weather predictions a few months in advance, and particularly from the reliable prediction of extreme fire seasons. However, in some cases model biases prevent from a direct application of these predictions in an operational context. Fire risk management requires precise knowledge of the likely consequences of climate on fire risk, and the interest for decision-makers is focused on multi-var...

  15. Combining biological and psychosocial baseline variables did not improve prediction of outcome of a very-low-energy diet in a clinic referral population.

    Science.gov (United States)

    Sumithran, P; Purcell, K; Kuyruk, S; Proietto, J; Prendergast, L A

    2018-02-01

    Consistent, strong predictors of obesity treatment outcomes have not been identified. It has been suggested that broadening the range of predictor variables examined may be valuable. We explored methods to predict outcomes of a very-low-energy diet (VLED)-based programme in a clinically comparable setting, using a wide array of pre-intervention biological and psychosocial participant data. A total of 61 women and 39 men (mean ± standard deviation [SD] body mass index: 39.8 ± 7.3 kg/m 2 ) underwent an 8-week VLED and 12-month follow-up. At baseline, participants underwent a blood test and assessment of psychological, social and behavioural factors previously associated with treatment outcomes. Logistic regression, linear discriminant analysis, decision trees and random forests were used to model outcomes from baseline variables. Of the 100 participants, 88 completed the VLED and 42 attended the Week 60 visit. Overall prediction rates for weight loss of ≥10% at weeks 8 and 60, and attrition at Week 60, using combined data were between 77.8 and 87.6% for logistic regression, and lower for other methods. When logistic regression analyses included only baseline demographic and anthropometric variables, prediction rates were 76.2-86.1%. In this population, considering a wide range of biological and psychosocial data did not improve outcome prediction compared to simply-obtained baseline characteristics. © 2017 World Obesity Federation.

  16. Variability, trends, and predictability of seasonal sea ice retreat and advance in the Chukchi Sea

    Science.gov (United States)

    Serreze, Mark C.; Crawford, Alex D.; Stroeve, Julienne C.; Barrett, Andrew P.; Woodgate, Rebecca A.

    2016-10-01

    As assessed over the period 1979-2014, the date that sea ice retreats to the shelf break (150 m contour) of the Chukchi Sea has a linear trend of -0.7 days per year. The date of seasonal ice advance back to the shelf break has a steeper trend of about +1.5 days per year, together yielding an increase in the open water period of 80 days. Based on detrended time series, we ask how interannual variability in advance and retreat dates relate to various forcing parameters including radiation fluxes, temperature and wind (from numerical reanalyses), and the oceanic heat inflow through the Bering Strait (from in situ moorings). Of all variables considered, the retreat date is most strongly correlated (r ˜ 0.8) with the April through June Bering Strait heat inflow. After testing a suite of statistical linear models using several potential predictors, the best model for predicting the date of retreat includes only the April through June Bering Strait heat inflow, which explains 68% of retreat date variance. The best model predicting the ice advance date includes the July through September inflow and the date of retreat, explaining 67% of advance date variance. We address these relationships by discussing heat balances within the Chukchi Sea, and the hypothesis of oceanic heat transport triggering ocean heat uptake and ice-albedo feedback. Developing an operational prediction scheme for seasonal retreat and advance would require timely acquisition of Bering Strait heat inflow data. Predictability will likely always be limited by the chaotic nature of atmospheric circulation patterns.

  17. Predictions of Tropospheric Zenithal Delay for South America : Seasonal Variability and Quality Evaluation

    Directory of Open Access Journals (Sweden)

    Luiz Augusto Toledo Machado

    2006-12-01

    Full Text Available The Zenithal Tropospheric Delay (Z TD is an important error source in the observable involved in the positioning methods using artificial satellite. Frequently, the Z TD influence in the positioning is minimized by applying empirical models. However, such models are not able to supply the precision required to some real time applications, such as navigation and steak out. In 2010 it will be implanted the new navigation and administration system of the air traffic, denominated CNS-ATM (Communication Navigation Surveillance - Air Traffic Management. In this new system the application of positioning techniques by satellites in the air traffic will be quite explored because they provide good precision in real time. The predictions of Z TD values from Numeric Weather Prediction (NWP, denominated dynamic modeling, is an alternative to model the atmospheric gases effects in the radio-frequency signals in real time. The Center for Weather Forecasting and Climate Studies (CPTEC has generated operationally prediction of Z TD values to South American Continent since March, 2004. The aims of the present paper are to investigate the Z TD seasonal variability and evaluate the quality of predicted Z TD values. One year of GPS data from Brazilian Continuous GPS Network (RBMC was used in this evaluation. The RMS values resulting from this evaluation were in the range of 4 to 11 cm. Considering the Z TDtemporal variability, the advantages provide by this modeling, the results obtained in this evaluation and the future improvements, this work shows that the dynamic modeling has great potential to become the most appropriate alternative to model Z TD in real time.

  18. A minimal model of the Atlantic Multidecadal Variability: its genesis and predictability

    Energy Technology Data Exchange (ETDEWEB)

    Ou, Hsien-Wang [Lamont-Doherty Earth Observatory of Columbia University, Department of Earth and Environmental Sciences, Palisades, NY (United States)

    2012-02-15

    Through a box model of the subpolar North Atlantic, we examine the genesis and predictability of the Atlantic Multidecadal Variability (AMV), posited as a linear perturbation sustained by the stochastic atmosphere. Postulating a density-dependent thermohaline circulation (THC), the latter would strongly differentiate the thermal and saline damping, and facilitate a negative feedback between the two fields. This negative feedback preferentially suppresses the low-frequency thermal variance to render a broad multidecadal peak bounded by the thermal and saline damping time. We offer this ''differential variance suppression'' as an alternative paradigm of the AMV in place of the ''damped oscillation'' - the latter generally not allowed by the deterministic dynamics and in any event bears no relation to the thermal peak. With the validated dynamics, we then assess the AMV predictability based on the relative entropy - a difference of the forecast and climatological probability distributions, which decays through both error growth and dynamical damping. Since the stochastic forcing is mainly in the surface heat flux, the thermal noise grows rapidly and together with its climatological variance limited by the THC-aided thermal damping, they strongly curtail the thermal predictability. The latter may be prolonged if the initial thermal and saline anomalies are of the same sign, but even rare events of less than 1% chance of occurrence yield a predictable time that is well short of a decade; we contend therefore that the AMV is in effect unpredictable. (orig.)

  19. HLA-A and -B alleles and haplotypes in 240 index patients with common variable immunodeficiency and selective IgG subclass deficiency in central Alabama

    Directory of Open Access Journals (Sweden)

    Barton James C

    2003-06-01

    Full Text Available Abstract Background We wanted to quantify HLA-A and -B phenotype and haplotype frequencies in Alabama index patients with common variable immunodeficiency (CVID and selective IgG subclass deficiency (IgGSD, and in control subjects. Methods Phenotypes were detected using DNA-based typing (index cases and microlymphocytotoxicity typing (controls. Results A and B phenotypes were determined in 240 index cases (114 CVID, 126 IgGSD and 1,321 controls and haplotypes in 195 index cases and 751 controls. Phenotyping revealed that the "uncorrected" frequencies of A*24, B*14, B*15, B*35, B*40, B*49, and B*50 were significantly greater in index cases, and frequencies of B*35, B*58, B*62 were significantly lower in index cases. After Bonferroni corrections, the frequencies of phenotypes A*24, B*14, and B*40 were significantly greater in index cases, and the frequency of B*62 was significantly lower in index cases. The most common haplotypes in index cases were A*02-B*44 (frequency 0.1385, A*01-B*08 (frequency 0.1308, and A*03-B*07 (frequency 0.1000, and the frequency of each was significantly greater in index cases than in control subjects ("uncorrected" values of p p p = 0.0166. Most phenotype and haplotype frequencies in CVID and IgGSD were similar. 26.7% of index patients were HLA-haploidentical with one or more other index patients. We diagnosed CVID or IgGSD in first-degree or other relatives of 26 of 195 index patients for whom HLA-A and -B haplotypes had been ascertained; A*01-B*08, A*02-B*44, and A*29-B*44 were most frequently associated with CVID or IgGSD in these families. We conservatively estimated the combined population frequency of CVID and IgGSD to be 0.0092 in adults, based on the occurrence of CVID and IgGSD in spouses of the index cases. Conclusions CVID and IgGSD in adults are significantly associated with several HLA haplotypes, many of which are also common in the Alabama Caucasian population. Immunoglobulin phenotype variability

  20. Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability.

    Directory of Open Access Journals (Sweden)

    Shaowei Sang

    Full Text Available Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF, a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose.Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8% imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags.Imported DF cases and mosquito

  1. Using lexical variables to predict picture-naming errors in jargon aphasia

    Directory of Open Access Journals (Sweden)

    Catherine Godbold

    2015-04-01

    Full Text Available Introduction Individuals with jargon aphasia produce fluent output which often comprises high proportions of non-word errors (e.g., maf for dog. Research has been devoted to identifying the underlying mechanisms behind such output. Some accounts posit a reduced flow of spreading activation between levels in the lexical network (e.g., Robson et al., 2003. If activation level differences across the lexical network are a cause of non-word outputs, we would predict improved performance when target items reflect an increased flow of activation between levels (e.g. more frequently-used words are often represented by higher resting levels of activation. This research investigates the effect of lexical properties of targets (e.g., frequency, imageability on accuracy, error type (real word vs. non-word and target-error overlap of non-word errors in a picture naming task by individuals with jargon aphasia. Method Participants were 17 individuals with Wernicke’s aphasia, who produced a high proportion of non-word errors (>20% of errors on the Philadelphia Naming Test (PNT; Roach et al., 1996. The data were retrieved from the Moss Aphasic Psycholinguistic Database Project (MAPPD, Mirman et al., 2010. We used a series of mixed models to test whether lexical variables predicted accuracy, error type (real word vs. non-word and target-error overlap for the PNT data. As lexical variables tend to be highly correlated, we performed a principal components analysis to reduce the variables into five components representing variables associated with phonology (length, phonotactic probability, neighbourhood density and neighbourhood frequency, semantics (imageability and concreteness, usage (frequency and age-of-acquisition, name agreement and visual complexity. Results and Discussion Table 1 shows the components that made a significant contribution to each model. Individuals with jargon aphasia produced more correct responses and fewer non-word errors relative to

  2. The predictive value of the foot posture index on dynamic function

    DEFF Research Database (Denmark)

    Nielsen, Rasmus Gottschalk; Rathleff, Michael Skovdal; Kersting, U G

    2008-01-01

    Keenan et. al. identified the six-item version of the Foot Posture Index (FPI) as a valid, simple and clinically useful tool. The model combines measures of the standing foot posture in multiple planes and anatomical segments. It provides an alternative to existing static clinical measures when d...

  3. Automated procedure for candidate compound selection in GCMS metabolomics based on prediction of Kovats retention index

    NARCIS (Netherlands)

    Mihaleva, V.V.; Verhoeven, H.A.; Vos, de C.H.; Hall, R.D.; Ham, van R.C.H.J.

    2009-01-01

    Motivation: Matching both the retention index (RI) and the mass spectrum of an unknown compound against a mass spectral reference library provides strong evidence for a correct identification of that compound. Data on retention indices are, however, available for only a small fraction of the

  4. A Behavioral Economic Reward Index Predicts Drinking Resolutions: Moderation Revisited and Compared with Other Outcomes

    Science.gov (United States)

    Tucker, Jalie A.; Roth, David L.; Vignolo, Mary J.; Westfall, Andrew O.

    2009-01-01

    Data were pooled from 3 studies of recently resolved community-dwelling problem drinkers to determine whether a behavioral economic index of the value of rewards available over different time horizons distinguished among moderation (n = 30), abstinent (n = 95), and unresolved (n = 77) outcomes. Moderation over 1- to 2-year prospective follow-up…

  5. Relative codon adaptation: a generic codon bias index for prediction of gene expression.

    Science.gov (United States)

    Fox, Jesse M; Erill, Ivan

    2010-06-01

    The development of codon bias indices (CBIs) remains an active field of research due to their myriad applications in computational biology. Recently, the relative codon usage bias (RCBS) was introduced as a novel CBI able to estimate codon bias without using a reference set. The results of this new index when applied to Escherichia coli and Saccharomyces cerevisiae led the authors of the original publications to conclude that natural selection favours higher expression and enhanced codon usage optimization in short genes. Here, we show that this conclusion was flawed and based on the systematic oversight of an intrinsic bias for short sequences in the RCBS index and of biases in the small data sets used for validation in E. coli. Furthermore, we reveal that how the RCBS can be corrected to produce useful results and how its underlying principle, which we here term relative codon adaptation (RCA), can be made into a powerful reference-set-based index that directly takes into account the genomic base composition. Finally, we show that RCA outperforms the codon adaptation index (CAI) as a predictor of gene expression when operating on the CAI reference set and that this improvement is significantly larger when analysing genomes with high mutational bias.

  6. The Predictive Value of the Foot Posture Index on Dynamic Function

    DEFF Research Database (Denmark)

    Mølgaard, Carsten Møller; Olesen Gammelgaard, Christian; Nielsen, R. G.

    Keenan et. al. identified the six-item version of the Foot Posture Index (FPI) as a valid, simple and clinically useful tool. The model combines measures of the standing foot posture in multiple planes and anatomical segments. It provides an alternative to existing static clinical measures when...

  7. BMD PREDICTION OF DEATH IS ENCAPSULATED BY THE MORPHOLOGICAL ATHEROSCLEROSIS CALCIFICATION DISTRIBUTION (MACD) INDEX

    DEFF Research Database (Denmark)

    Ganz, Melanie; Nielsen, Mads; Karsdal, Morten

    2009-01-01

    .3±0.3 years and of which CVD, cancer, and all cause deaths were recorded. The spine BMD and aortic calcification markers, AC24 and the recently proposed Morphological Atherosclerosis Calcification Distribution (MACD) index, were quantified from DXA scans and lateral X-rays respectively. The MACD...

  8. Easy prediction of the refractive index for binary mixtures of ionic liquids with water or ethanol

    International Nuclear Information System (INIS)

    Rilo, E.; Domínguez-Pérez, M.; Vila, J.; Segade, L.; García, M.; Varela, L.M.; Cabeza, O.

    2012-01-01

    Highlights: ► We measure refractive index, n, in seven systems formed by IL + water or ethanol. ► Independently, theoretical estimations of the refractive index values were performed. ► To do that we use Gladstone–Dale and Newton models, relating n and density. ► We calculate density of each system from the value of the pure components. ► The agreement between experimental and calculated n values is about 99.8%. - Abstract: In this paper, we demonstrate that it is possible to know the refractive index, n D , of every given mixture of 1-alkyl-3methyl imidazolium tetrafluoroborate with water and ethanol just from the knowledge of the refractive index and density of pure components. To do that, we measured n D for seven different mixtures in all range of existing concentrations and, independently, we deduce n D theoretically. Both sets of values differ less than a 0.2% on average. The theoretical deduction takes into account that these mixtures are quasi-ideal from the molar volume point of view, as recently published, and so density for any composition of the mixture can be obtained with a precision better than 0.5% from the pure compounds value. Now we simply apply Newton or Gladstone–Dale models, which relate the refractive index of a binary mixture with its density from the value of both pure components, without any fitting parameter. Both models are very similar in form and in the values they deduce (less than a 0.2% of difference), but while that of Newton performs slightly better for ethanol mixtures, the model of Gladstone–Dale gives some better results for aqueous mixtures. We think that these results can be extended to the majority of ionic liquid plus solvent systems.

  9. Prediction of fermentation index of cocoa beans (Theobroma cacao L.) based on color measurement and artificial neural networks.

    Science.gov (United States)

    León-Roque, Noemí; Abderrahim, Mohamed; Nuñez-Alejos, Luis; Arribas, Silvia M; Condezo-Hoyos, Luis

    2016-12-01

    Several procedures are currently used to assess fermentation index (FI) of cocoa beans (Theobroma cacao L.) for quality control. However, all of them present several drawbacks. The aim of the present work was to develop and validate a simple image based quantitative procedure, using color measurement and artificial neural network (ANNs). ANN models based on color measurements were tested to predict fermentation index (FI) of fermented cocoa beans. The RGB values were measured from surface and center region of fermented beans in images obtained by camera and desktop scanner. The FI was defined as the ratio of total free amino acids in fermented versus non-fermented samples. The ANN model that included RGB color measurement of fermented cocoa surface and R/G ratio in cocoa bean of alkaline extracts was able to predict FI with no statistical difference compared with the experimental values. Performance of the ANN model was evaluated by the coefficient of determination, Bland-Altman plot and Passing-Bablok regression analyses. Moreover, in fermented beans, total sugar content and titratable acidity showed a similar pattern to the total free amino acid predicted through the color based ANN model. The results of the present work demonstrate that the proposed ANN model can be adopted as a low-cost and in situ procedure to predict FI in fermented cocoa beans through apps developed for mobile device. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Strain dyssynchrony index determined by three-dimensional speckle area tracking can predict response to cardiac resynchronization therapy

    Directory of Open Access Journals (Sweden)

    Onishi Tetsuari

    2011-04-01

    Full Text Available Abstract Background We have previously reported strain dyssynchrony index assessed by two-dimensional speckle tracking strain, and a marker of both dyssynchrony and residual myocardial contractility, can predict response to cardiac resynchronization therapy (CRT. A newly developed three-dimensional (3-D speckle tracking system can quantify endocardial area change ratio (area strain, which coupled with the factors of both longitudinal and circumferential strain, from all 16 standard left ventricular (LV segments using complete 3-D pyramidal datasets. Our objective was to test the hypothesis that strain dyssynchrony index using area tracking (ASDI can quantify dyssynchrony and predict response to CRT. Methods We studied 14 heart failure patients with ejection fraction of 27 ± 7% (all≤35% and QRS duration of 172 ± 30 ms (all≥120 ms who underwent CRT. Echocardiography was performed before and 6-month after CRT. ASDI was calculated as the average difference between peak and end-systolic area strain of LV endocardium obtained from 3-D speckle tracking imaging using 16 segments. Conventional dyssynchrony measures were assessed by interventricular mechanical delay, Yu Index, and two-dimensional radial dyssynchrony by speckle-tracking strain. Response was defined as a ≥15% decrease in LV end-systolic volume 6-month after CRT. Results ASDI ≥ 3.8% was the best predictor of response to CRT with a sensitivity of 78%, specificity of 100% and area under the curve (AUC of 0.93 (p Conclusions ASDI can predict responders and LV reverse remodeling following CRT. This novel index using the 3-D speckle tracking system, which shows circumferential and longitudinal LV dyssynchrony and residual endocardial contractility, may thus have clinical significance for CRT patients.

  11. Intraindividual Variability in Basic Reaction Time Predicts Middle-Aged and Older Pilots’ Flight Simulator Performance

    Science.gov (United States)

    2013-01-01

    Objectives. Intraindividual variability (IIV) is negatively associated with cognitive test performance and is positively associated with age and some neurological disorders. We aimed to extend these findings to a real-world task, flight simulator performance. We hypothesized that IIV predicts poorer initial flight performance and increased rate of decline in performance among middle-aged and older pilots. Method. Two-hundred and thirty-six pilots (40–69 years) completed annual assessments comprising a cognitive battery and two 75-min simulated flights in a flight simulator. Basic and complex IIV composite variables were created from measures of basic reaction time and shifting and divided attention tasks. Flight simulator performance was characterized by an overall summary score and scores on communication, emergencies, approach, and traffic avoidance components. Results. Although basic IIV did not predict rate of decline in flight performance, it had a negative association with initial performance for most flight measures. After taking into account processing speed, basic IIV explained an additional 8%–12% of the negative age effect on initial flight performance. Discussion. IIV plays an important role in real-world tasks and is another aspect of cognition that underlies age-related differences in cognitive performance. PMID:23052365

  12. Intraindividual variability in basic reaction time predicts middle-aged and older pilots' flight simulator performance.

    Science.gov (United States)

    Kennedy, Quinn; Taylor, Joy; Heraldez, Daniel; Noda, Art; Lazzeroni, Laura C; Yesavage, Jerome

    2013-07-01

    Intraindividual variability (IIV) is negatively associated with cognitive test performance and is positively associated with age and some neurological disorders. We aimed to extend these findings to a real-world task, flight simulator performance. We hypothesized that IIV predicts poorer initial flight performance and increased rate of decline in performance among middle-aged and older pilots. Two-hundred and thirty-six pilots (40-69 years) completed annual assessments comprising a cognitive battery and two 75-min simulated flights in a flight simulator. Basic and complex IIV composite variables were created from measures of basic reaction time and shifting and divided attention tasks. Flight simulator performance was characterized by an overall summary score and scores on communication, emergencies, approach, and traffic avoidance components. Although basic IIV did not predict rate of decline in flight performance, it had a negative association with initial performance for most flight measures. After taking into account processing speed, basic IIV explained an additional 8%-12% of the negative age effect on initial flight performance. IIV plays an important role in real-world tasks and is another aspect of cognition that underlies age-related differences in cognitive performance.

  13. Predictive value of clinical and laboratory variables for vesicoureteral reflux in children.

    Science.gov (United States)

    Soylu, Alper; Kasap, Belde; Demir, Korcan; Türkmen, Mehmet; Kavukçu, Salih

    2007-06-01

    We aimed to determine the predictability of clinical and laboratory variables for vesicoureteral reflux (VUR) in children with urinary tract infection (UTI). Data of children with febrile UTI who underwent voiding cystoureterography between 2002 and 2005 were evaluated retrospectively for clinical (age, gender, fever > or = 38.5 degrees C, recurrent UTI), laboratory [leukocytosis, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), pyuria, serum creatinine (S(Cr))] and imaging (renal ultrasonography) variables. Children with VUR (group 1) vs. no VUR (group 2) and children with high-grade (III-V) VUR (group 3) vs. no or low-grade (I-II) VUR (group 4) were compared. Among 88 patients (24 male), 38 had VUR and 21 high-grade VUR. Fever > or = 38.5 degrees C was associated with VUR [odds ratio (OR): 7.5]. CRP level of 50 mg/l was the best cut-off level for predicting high-grade VUR (OR 15.5; discriminative ability 0.89 +/- 0.05). Performing voiding cystourethrography based on this CRP level would result in failure to notice 9% of patients with high-grade VUR, whereas 69% of children with no/low-grade VUR would be spared from this invasive test. In conclusion, fever > or = 38 degrees C and CRP > 50 mg/l seem to be potentially useful clinical predictors of VUR and high-grade VUR, respectively, in pediatric patients with UTI. Further validation of these findings could limit unnecessary voiding cystourethrography.

  14. Spatial Variability and Geostatistical Prediction of Some Soil Hydraulic Coefficients of a Calcareous Soil

    Directory of Open Access Journals (Sweden)

    Ali Akbar Moosavi

    2017-02-01

    Full Text Available Introduction: Saturated hydraulic conductivity and the other hydraulic properties of soils are essential vital soil attributes that play role in the modeling of hydrological phenomena, designing irrigation-drainage systems, transportation of salts and chemical and biological pollutants within the soil. Measurement of these hydraulic properties needs some special instruments, expert technician, and are time consuming and expensive and due to their high temporal and spatial variability, a large number of measurements are needed. Nowadays, prediction of these attributes using the readily available soil data using pedotransfer functions or using the limited measurement with applying the geostatistical approaches has been receiving high attention. The study aimed to determine the spatial variability and prediction of saturated (Ks and near saturated (Kfs hydraulic conductivity, the power of Gardner equation (α, sorptivity (S, hydraulic diffusivity (D and matric flux potential (Фm of a calcareous soil. Material and Methods: The study was carried out on the soil series of Daneshkadeh located in the Bajgah Agricultural Experimental Station of Agricultural College, Shiraz University, Shiraz, Iran (1852 m above the mean sea level. This soil series with about 745 ha is a deep yellowish brow calcareous soil with textural classes of loam to clay. In the studied soil series 50 sampling locations with the sampling distances of 16, 8 , and 4 m were selected on the relatively regular sampling design. The saturated hydraulic conductivity (Ks, near saturated hydraulic conductivity (Kfs, the power of Gardner equation (α, sorptivity (S, hydraulic diffusivity (D and matric flux potential (Фm of the aforementioned sampling locations was determined using the Single Ring and Droplet methods. After, initial statistical processing, including a normality test of data, trend and stationary analysis of data, the semivariograms of each studied hydraulic attributes were

  15. Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J. [Iowa State Univ., Ames, IA (United States)

    2017-12-28

    This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASM can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes

  16. Integrating interannual climate variability forecasts into weather-indexed crop insurance. The case of Malawi, Kenya and Tanzania

    Science.gov (United States)

    Vicarelli, M.; Giannini, A.; Osgood, D.

    2009-12-01

    In this study we explore the potential for re-insurance schemes built on regional climatic forecasts. We focus on micro-insurance contracts indexed on precipitation in 9 villages in Kenya, Tanzania (Eastern Africa) and Malawi (Southern Africa), and analyze the precipitation patterns and payouts resulting from El Niño Southern Oscillation (ENSO). The inability to manage future climate risk represents a “poverty trap” for several African regions. Weather shocks can potentially destabilize not only household, but also entire countries. Governments in drought-prone countries, donors and relief agencies are becoming aware of the importance to develop an ex-ante risk management framework for weather risk. Joint efforts to develop innovative mechanisms to spread and pool risk such as microinsurance and microcredit are currently being designed in several developing countries. While ENSO is an important component in modulating the rainfall regime in tropical Africa, the micro-insurance experiments currently under development to address drought risk among smallholder farmers in this region do not take into account ENSO monitoring or forecasting yet. ENSO forecasts could be integrated in the contracts and reinsurance schemes could be designed at the continental scale taking advantage of the different impact of ENSO on different regions. ENSO is associated to a bipolar precipitation pattern in Southern and Eastern Africa. La Niña years (i.e. Cold ENSO Episodes) are characterized by dry climate in Eastern Africa and wet climate in Southern Africa. During El Niño (or Warm Episode) the precipitation dipole is inverted, and Eastern Africa experiences increased probability for above normal rainfall (Halpert and Ropelewski, 1992, Journal of Climate). Our study represents the first exercise in trying to include ENSO forecasts in micro weather index insurance contract design. We analyzed the contracts payouts with respect to climate variability. In particular (i) we simulated

  17. Fatty liver index vs waist circumference for predicting non-alcoholic fatty liver disease.

    Science.gov (United States)

    Motamed, Nima; Sohrabi, Masoudreza; Ajdarkosh, Hossein; Hemmasi, Gholamreza; Maadi, Mansooreh; Sayeedian, Fatemeh Sima; Pirzad, Reza; Abedi, Khadijeh; Aghapour, Sivil; Fallahnezhad, Mojtaba; Zamani, Farhad

    2016-03-14

    To determine the discriminatory performance of fatty liver index (FLI) for non-alcoholic fatty liver disease (NAFLD). The data of 5052 subjects aged over 18 years were analyzed. FLI was calculated from body mass index, waist circumference (WC), triglyceride, and gamma glutamyl transferase data. Logistic regression analysis was conducted to determine the association between FLI and NAFLD. The discriminatory performance of FLI in the diagnosis of NAFLD was evaluated by receiver operating characteristic analysis. Area under the curves (AUCs) and related confidence intervals were estimated. Optimal cutoff points of FLI in the diagnosis of NAFLD were determined based on the maximum values of Youden's index. The mean age of men and women in the study population were 44.8 ± 16.8 and 43.78 ± 15.43, respectively (P = 0.0216). The prevalence of NAFLD was 40.1% in men and 44.2% in women (P < 0.0017). FLI was strongly associated with NAFLD, so that even a one unit increase in FLI increased the chance of developing NAFLD by 5.8% (OR = 1.058, 95%CI: 1.054-1.063, P < 0.0001). Although FLI showed good performance in the diagnosis of NAFLD (AUC = 0.8656 (95%CI: 0.8548-0.8764), there was no significant difference with regards to WC (AUC = 0.8533, 95%CI: 0.8419-0.8646). The performance of FLI was not significantly different between men (AUC = 0.8648, 95%CI: 0.8505-0.8791) and women (AUC = 0.8682, 95%CI: 0.8513-0.8851). The highest performance with regards to age was related to the 18-39 age group (AUC = 0.8930, 95%CI: 0.8766-0.9093). The optimal cutoff points of FLI were 46.9 in men (sensitivity = 0.8242, specificity = 0.7687, Youden's index = 0.5929) and 53.8 in women (sensitivity = 0.8233, specificity = 0.7655, Youden's index = 0.5888). Although FLI had acceptable discriminatory power in the diagnosis of NAFLD, WC was a simpler and more accessible index with a similar performance.

  18. Modelling and prediction of pig iron variables in the blast furnace

    Energy Technology Data Exchange (ETDEWEB)

    Saxen, H; Laaksonen, M; Waller, M [Aabo Akademi, Turku (Finland). Heat Engineering Lab.

    1997-12-31

    The blast furnace, where pig iron for steelmaking is produced, is an extremely complicated process, with heat and mass transfer and chemical reactions between several phases. Very few direct measurements on the internal state are available in the operation of the process. A main problem in on-line analysis and modelling is that the state of the furnace may undergo spontaneous changes, which alter the dynamic behaviour of the process. Moreover, large internal disturbances frequently occur, which affect the product quality. The work in this research project focuses on a central problem in the control of the blast furnace process, i.e., short-term prediction of pig iron variables. The problem is of considerable importance for fuel economy, product quality, and for an optimal decision making in integrated steel plants. The operation of the blast furnace aims at producing a product (hot metal) with variables maintained on a stable level (close to their setpoints) without waste of expensive fuel (metallurgical coke). The hot metal temperature and composition affect the downstream (steelmaking) processes, so fluctuations in the pig iron quality must be `corrected` in the steel plant. The goal is to develop a system which predicts the evolution of the hot metal variables (temperature, chemical composition) during the next few taps, and that can be used for decision-making in the operation of the blast furnace. Because of the complicated behaviour of the process, it is considered important to include both deterministic and stochastic components in the modelling: Mathematical models, which on the basis of measurements describe the physical state of the process, and statistical (black-box) models will be combined in the system. Moreover, different models will be applied in different domains in order to capture structural changes in the dynamics of the process SULA 2 Research Programme; 17 refs.

  19. Modelling and prediction of pig iron variables in the blast furnace

    Energy Technology Data Exchange (ETDEWEB)

    Saxen, H.; Laaksonen, M.; Waller, M. [Aabo Akademi, Turku (Finland). Heat Engineering Lab.

    1996-12-31

    The blast furnace, where pig iron for steelmaking is produced, is an extremely complicated process, with heat and mass transfer and chemical reactions between several phases. Very few direct measurements on the internal state are available in the operation of the process. A main problem in on-line analysis and modelling is that the state of the furnace may undergo spontaneous changes, which alter the dynamic behaviour of the process. Moreover, large internal disturbances frequently occur, which affect the product quality. The work in this research project focuses on a central problem in the control of the blast furnace process, i.e., short-term prediction of pig iron variables. The problem is of considerable importance for fuel economy, product quality, and for an optimal decision making in integrated steel plants. The operation of the blast furnace aims at producing a product (hot metal) with variables maintained on a stable level (close to their setpoints) without waste of expensive fuel (metallurgical coke). The hot metal temperature and composition affect the downstream (steelmaking) processes, so fluctuations in the pig iron quality must be `corrected` in the steel plant. The goal is to develop a system which predicts the evolution of the hot metal variables (temperature, chemical composition) during the next few taps, and that can be used for decision-making in the operation of the blast furnace. Because of the complicated behaviour of the process, it is considered important to include both deterministic and stochastic components in the modelling: Mathematical models, which on the basis of measurements describe the physical state of the process, and statistical (black-box) models will be combined in the system. Moreover, different models will be applied in different domains in order to capture structural changes in the dynamics of the process SULA 2 Research Programme; 17 refs.

  20. Intraindividual variability in reaction time predicts cognitive outcomes 5 years later.

    Science.gov (United States)

    Bielak, Allison A M; Hultsch, David F; Strauss, Esther; Macdonald, Stuart W S; Hunter, Michael A

    2010-11-01

    Building on results suggesting that intraindividual variability in reaction time (inconsistency) is highly sensitive to even subtle changes in cognitive ability, this study addressed the capacity of inconsistency to predict change in cognitive status (i.e., cognitive impairment, no dementia [CIND] classification) and attrition 5 years later. Two hundred twelve community-dwelling older adults, initially aged 64-92 years, remained in the study after 5 years. Inconsistency was calculated from baseline reaction time performance. Participants were assigned to groups on the basis of their fluctuations in CIND classification over time. Logistic and Cox regressions were used. Baseline inconsistency significantly distinguished among those who remained or transitioned into CIND over the 5 years and those who were consistently intact (e.g., stable intact vs. stable CIND, Wald (1) = 7.91, p < .01, Exp(β) = 1.49). Average level of inconsistency over time was also predictive of study attrition, for example, Wald (1) = 11.31, p < .01, Exp(β) = 1.24. For both outcomes, greater inconsistency was associated with a greater likelihood of being in a maladaptive group 5 years later. Variability based on moderately cognitively challenging tasks appeared to be particularly sensitive to longitudinal changes in cognitive ability. Mean rate of responding was a comparable predictor of change in most instances, but individuals were at greater relative risk of being in a maladaptive outcome group if they were more inconsistent rather than if they were slower in responding. Implications for the potential utility of intraindividual variability in reaction time as an early marker of cognitive decline are discussed. (c) 2010 APA, all rights reserved

  1. Can Social History Variables Predict Prison Inmates’ Risk for Latent Tuberculosis Infection?

    Directory of Open Access Journals (Sweden)

    Tyler E. Weant

    2012-01-01

    Full Text Available Improved screening and treatment of latent tuberculosis infection (LTBI in correctional facilities may improve TB control. The Ohio Department of Rehabilitation and Correction (ODRC consists of 32 prisons. Inmates are screened upon entry to ODRC and yearly thereafter. The objective of the study was to determine if social history factors such as tobacco, alcohol, and drug use are significant predictors of LTBI and treatment outcomes. We reviewed the medical charts of inmates and randomly selected age-matched controls at one ODRC facility for 2009. We used a conditional logistic regression to assess associations between selected social history variables and LTBI diagnosis. Eighty-nine inmates with a history of LTBI and 88 controls were identified. No social history variable was a significant predictor of LTBI. Medical comorbidities such as asthma, rheumatoid arthritis, and hepatitis C were significantly higher in inmates with LTBI. 84% of inmates diagnosed with LTBI had either completed or were on treatment. Annual TB screening may not be cost-effective in all inmate populations. Identification of factors to help target screening populations at risk for TB is critical. Social history variables did not predict LTBI in our inmate population. Additional studies are needed to identify inmates for the targeted TB testing.

  2. Predicting Students' Skills in the Context of Scientific Inquiry with Cognitive, Motivational, and Sociodemographic Variables

    Science.gov (United States)

    Nehring, Andreas; Nowak, Kathrin H.; Belzen, Annette Upmeier zu; Tiemann, Rüdiger

    2015-06-01

    Research on predictors of achievement in science is often targeted on more traditional content-based assessments and single student characteristics. At the same time, the development of skills in the field of scientific inquiry constitutes a focal point of interest for science education. Against this background, the purpose of this study was to investigate to which extent multiple student characteristics contribute to skills of scientific inquiry. Based on a theoretical framework describing nine epistemological acts, we constructed and administered a multiple-choice test that assesses these skills in lower and upper secondary school level (n = 780). The test items contained problem-solving situations that occur during chemical investigations in school and had to be solved by choosing an appropriate inquiry procedure. We collected further data on 12 cognitive, motivational, and sociodemographic variables such as conceptual knowledge, enjoyment of chemistry, or language spoken at home. Plausible values were drawn to quantify students' inquiry skills. The results show that students' characteristics predict their inquiry skills to a large extent (55%), whereas 9 out of 12 variables contribute significantly on a multivariate level. The influence of sociodemographic traits such as gender or the social background becomes non-significant after controlling for cognitive and motivational variables. Furthermore, the performance advance of students from upper secondary school level can be explained by controlling for cognitive covariates. We discuss our findings with regard to curricular aspects and raise the question whether the inquiry skills can be considered as an autonomous trait in science education research.

  3. Sensitivity, Specificity and Predictive Value of Heart Rate Variability Indices in Type 1 Diabetes Mellitus

    Directory of Open Access Journals (Sweden)

    Anne Kastelianne França da Silva

    Full Text Available Abstract Background: Heart rate variability (HRV indices may detect autonomic changes with good diagnostic accuracy. Type diabetes mellitus (DM individuals may have changes in autonomic modulation; however, studies of this nature in this population are still scarce. Objective: To compare HRV indices between and assess their prognostic value by measurements of sensitivity, specificity and predictive values in young individuals with type 1 DM and healthy volunteers. Methods: In this cross-sectional study, physical and clinical assessment was performed in 39 young patients with type 1 DM and 43 young healthy controls. For HRV analysis, beat-to-beat heart rate variability was measured in dorsal decubitus, using a Polar S810i heart rate monitor, for 30 minutes. The following indices were calculated: SDNN, RMSSD, PNN50, TINN, RRTri, LF ms2, HF ms2, LF un, HF un, LF/HF, SD1, SD2, SD1/SD2, and ApEn. Results: Type 1 DM subjects showed a decrease in sympathetic and parasympathetic activities, and overall variability of autonomic nervous system. The RMSSD, SDNN, PNN50, LF ms2, HF ms2, RRTri, SD1 and SD2 indices showed greater diagnostic accuracy in discriminating diabetic from healthy individuals. Conclusion: Type 1 DM individuals have changes in autonomic modulation. The SDNN, RMSSD, PNN50, RRtri, LF ms2, HF ms2, SD1 and SD2 indices may be alternative tools to discriminate individuals with type 1 DM.

  4. Blood profile of proteins and steroid hormones predicts weight change after weight loss with interactions of dietary protein level and glycemic index.

    Directory of Open Access Journals (Sweden)

    Ping Wang

    2011-02-01

    Full Text Available Weight regain after weight loss is common. In the Diogenes dietary intervention study, high protein and low glycemic index (GI diet improved weight maintenance.To identify blood predictors for weight change after weight loss following the dietary intervention within the Diogenes study.Blood samples were collected at baseline and after 8-week low caloric diet-induced weight loss from 48 women who continued to lose weight and 48 women who regained weight during subsequent 6-month dietary intervention period with 4 diets varying in protein and GI levels. Thirty-one proteins and 3 steroid hormones were measured.Angiotensin I converting enzyme (ACE was the most important predictor. Its greater reduction during the 8-week weight loss was related to continued weight loss during the subsequent 6 months, identified by both Logistic Regression and Random Forests analyses. The prediction power of ACE was influenced by immunoproteins, particularly fibrinogen. Leptin, luteinizing hormone and some immunoproteins showed interactions with dietary protein level, while interleukin 8 showed interaction with GI level on the prediction of weight maintenance. A predictor panel of 15 variables enabled an optimal classification by Random Forests with an error rate of 24±1%. A logistic regression model with independent variables from 9 blood analytes had a prediction accuracy of 92%.A selected panel of blood proteins/steroids can predict the weight change after weight loss. ACE may play an important role in weight maintenance. The interactions of blood factors with dietary components are important for personalized dietary advice after weight loss.ClinicalTrials.gov NCT00390637.

  5. Construction of possible integrated predictive index based on EGFR and ANXA3 polymorphisms for chemotherapy response in fluoropyrimidine-treated Japanese gastric cancer patients using a bioinformatic method

    International Nuclear Information System (INIS)

    Takahashi, Hiro; Kaniwa, Nahoko; Saito, Yoshiro; Sai, Kimie; Hamaguchi, Tetsuya; Shirao, Kuniaki; Shimada, Yasuhiro; Matsumura, Yasuhiro; Ohtsu, Atsushi; Yoshino, Takayuki; Doi, Toshihiko; Takahashi, Anna; Odaka, Yoko; Okuyama, Misuzu; Sawada, Jun-ichi; Sakamoto, Hiromi; Yoshida, Teruhiko

    2015-01-01

    Variability in drug response between individual patients is a serious concern in medicine. To identify single-nucleotide polymorphisms (SNPs) related to drug response variability, many genome-wide association studies have been conducted. We previously applied a knowledge-based bioinformatic approach to a pharmacogenomics study in which 119 fluoropyrimidine-treated gastric cancer patients were genotyped at 109,365 SNPs using the Illumina Human-1 BeadChip. We identified the SNP rs2293347 in the human epidermal growth factor receptor (EGFR) gene as a novel genetic factor related to chemotherapeutic response. In the present study, we reanalyzed these hypothesis-free genomic data using extended knowledge. We identified rs2867461 in annexin A3 (ANXA3) gene as another candidate. Using logistic regression, we confirmed that the performance of the rs2867461 + rs2293347 model was superior to those of the single factor models. Furthermore, we propose a novel integrated predictive index (iEA) based on these two polymorphisms in EGFR and ANXA3. The p value for iEA was 1.47 × 10 −8 by Fisher’s exact test. Recent studies showed that the mutations in EGFR is associated with high expression of dihydropyrimidine dehydrogenase, which is an inactivating and rate-limiting enzyme for fluoropyrimidine, and suggested that the combination of chemotherapy with fluoropyrimidine and EGFR-targeting agents is effective against EGFR-overexpressing gastric tumors, while ANXA3 overexpression confers resistance to tyrosine kinase inhibitors targeting the EGFR pathway. These results suggest that the iEA index or a combination of polymorphisms in EGFR and ANXA3 may serve as predictive factors of drug response, and therefore could be useful for optimal selection of chemotherapy regimens. The online version of this article (doi:10.1186/s12885-015-1721-z) contains supplementary material, which is available to authorized users

  6. A model for estimating pathogen variability in shellfish and predicting minimum depuration times.

    Science.gov (United States)

    McMenemy, Paul; Kleczkowski, Adam; Lees, David N; Lowther, James; Taylor, Nick

    2018-01-01

    Norovirus is a major cause of viral gastroenteritis, with shellfish consumption being identified as one potential norovirus entry point into the human population. Minimising shellfish norovirus levels is therefore important for both the consumer's protection and the shellfish industry's reputation. One method used to reduce microbiological risks in shellfish is depuration; however, this process also presents additional costs to industry. Providing a mechanism to estimate norovirus levels during depuration would therefore be useful to stakeholders. This paper presents a mathematical model of the depuration process and its impact on norovirus levels found in shellfish. Two fundamental stages of norovirus depuration are considered: (i) the initial distribution of norovirus loads within a shellfish population and (ii) the way in which the initial norovirus loads evolve during depuration. Realistic assumptions are made about the dynamics of norovirus during depuration, and mathematical descriptions of both stages are derived and combined into a single model. Parameters to describe the depuration effect and norovirus load values are derived from existing norovirus data obtained from U.K. harvest sites. However, obtaining population estimates of norovirus variability is time-consuming and expensive; this model addresses the issue by assuming a 'worst case scenario' for variability of pathogens, which is independent of mean pathogen levels. The model is then used to predict minimum depuration times required to achieve norovirus levels which fall within possible risk management levels, as well as predictions of minimum depuration times for other water-borne pathogens found in shellfish. Times for Escherichia coli predicted by the model all fall within the minimum 42 hours required for class B harvest sites, whereas minimum depuration times for norovirus and FRNA+ bacteriophage are substantially longer. Thus this study provides relevant information and tools to assist

  7. Extreme Environment Damage Index and Accumulation Model for CMC Laminate Fatigue Life Prediction, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Materials Research & Design (MR&D) is proposing in the SBIR Phase II an effort to develop a tool for predicting the fatigue life of C/SiC composite...

  8. Prediction model for prevalence and incidence of advanced age-related macular degeneration based on genetic, demographic, and environmental variables.

    Science.gov (United States)

    Seddon, Johanna M; Reynolds, Robyn; Maller, Julian; Fagerness, Jesen A; Daly, Mark J; Rosner, Bernard

    2009-05-01

    The joint effects of genetic, ocular, and environmental variables were evaluated and predictive models for prevalence and incidence of AMD were assessed. Participants in the multicenter Age-Related Eye Disease Study (AREDS) were included in a prospective evaluation of 1446 individuals, of which 279 progressed to advanced AMD (geographic atrophy or neovascular disease) and 1167 did not progress during 6.3 years of follow-up. For prevalent AMD, 509 advanced cases were compared with 222 controls. Covariates for the incidence analysis included age, sex, education, smoking, body mass index (BMI), baseline AMD grade, and the AREDS vitamin-mineral treatment assignment. DNA specimens were evaluated for six variants in five genes related to AMD. Unconditional logistic regression analyses were performed for prevalent and incident advanced AMD. An algorithm was developed and receiver operating characteristic curves and C statistics were calculated to assess the predictive ability of risk scores to discriminate progressors from nonprogressors. All genetic polymorphisms were independently related to prevalence of advanced AMD, controlling for genetic factors, smoking, BMI, and AREDS treatment. Multivariate odds ratios (ORs) were 3.5 (95% confidence interval [CI], 1.7-7.1) for CFH Y402H; 3.7 (95% CI, 1.6-8.4) for CFH rs1410996; 25.4 (95% CI, 8.6-75.1) for LOC387715 A69S (ARMS2); 0.3 (95% CI, 0.1-0.7) for C2 E318D; 0.3 (95% CI, 0.1-0.5) for CFB; and 3.6 (95% CI, 1.4-9.4) for C3 R102G, comparing the homozygous risk/protective genotypes to the referent genotypes. For incident AMD, all these variants except CFB were significantly related to progression to advanced AMD, after controlling for baseline AMD grade and other factors, with ORs from 1.8 to 4.0 for presence of two risk alleles and 0.4 for the protective allele. An interaction was seen between CFH402H and treatment, after controlling for all genotypes. Smoking was independently related to AMD, with a multiplicative joint

  9. Healthy Life Style Behaviors of University Students of School of Physical Education and Sports in Terms of Body Mass Index and Other Variables

    Science.gov (United States)

    Bozlar, Volkan; Arslanoglu, Cansel

    2016-01-01

    The aim of this study is to determine Healthy Lifestyle Behaviors of students in the Schools of Physical Education and Sport (SPES) utilizing Body Mass Index (BMI) and other various variables. The study is composed of 1,695 students studying in SPES, in 14 different universities across Turkey. It is made up of 1,067 male and 624 female students.…

  10. Nonlinear Conte-Zbilut-Federici (CZF Method of Computing LF/HF Ratio: A More Reliable Index of Changes in Heart Rate Variability

    Directory of Open Access Journals (Sweden)

    Vernon Bond Jr

    2016-09-01

    Full Text Available Objectives: Acupuncture treatments are safe and effective for a wide variety of diseases involving autonomic dysregulation. Heart rate variability (HRV is a noninvasive method for assessing sympathovagal balance. The low frequency/high frequency (LF/HF spectral power ratio is an index of sympathovagal influence on heart rate and of cardi

  11. Prognostic nutritional index predicts postoperative complications and long-term outcomes of gastric cancer.

    Science.gov (United States)

    Jiang, Nan; Deng, Jing-Yu; Ding, Xue-Wei; Ke, Bin; Liu, Ning; Zhang, Ru-Peng; Liang, Han

    2014-08-14

    To investigate the impact of prognostic nutritional index (PNI) on the postoperative complications and long-term outcomes in gastric cancer patients undergoing total gastrectomy. The data for 386 patients with gastric cancer were extracted and analyzed between January 2003 and December 2008 in our center. The patients were divided into two groups according to the cutoff value of the PNI: those with a PNI ≥ 46 and those with a PNI gastric cancer patients.

  12. Use of Radiographic Densitometry to Predict the Bone Healing Index in Distraction Osteogenesis

    OpenAIRE

    A Saw; S Manimaran; S Faizal; AM Bulgiba

    2008-01-01

    Bone lengthening with distraction osteogenesis involves prolonged application of an external fixator frame. Qualitative and quantitative evaluation of callus has been described using various imaging modalities but there is no simple reliable and readily available method. This study aims to investigate the use of a densitometer to analyze plain radiographic images and correlate them with the rate of new bone formation as represented by the bone healing index. A total of 34 bone lengthening pro...

  13. The Predictive Value of Integrated Pulmonary Index after Off-Pump Coronary Artery Bypass Grafting: A Prospective Observational Study

    Directory of Open Access Journals (Sweden)

    Evgenia V. Fot

    2017-08-01

    Full Text Available BackgroundThe early warning scores may increase the safety of perioperative period. The objective of this study was to assess the diagnostic and predictive role of Integrated Pulmonary Index (IPI after off-pump coronary artery bypass grafting (OPCAB.Materials and MethodsForty adult patients undergoing elective OPCAB were enrolled into a single-center prospective observational study. We assessed respiratory function using IPI that includes oxygen saturation, end-tidal CO2, respiratory rate, and pulse rate. In addition, we evaluated blood gas analyses and hemodynamics, including ECG, invasive arterial pressure, and cardiac index. The measurements were performed after transfer to the intensive care unit, after spontaneous breathing trial and at 2, 6, 12, and 18 h after extubation.Results and DiscussionThe value of IPI registered during respiratory support correlated weakly with cardiac index (rho = 0.4; p = 0.04 and ScvO2 (rho = 0.4, p = 0.02. After extubation, IPI values decreased significantly, achieving a minimum by 18 h. The IPI value ≤9 at 6 h after extubation was a predictor of complicated early postoperative period (AUC = 0.71; p = 0.04 observed in 13 patients.ConclusionIn off-pump coronary surgery, the IPI decreases significantly after tracheal extubation and may predict postoperative complications.

  14. Using body mass index to predict optimal thyroid dosing after thyroidectomy.

    Science.gov (United States)

    Ojomo, Kristin A; Schneider, David F; Reiher, Alexandra E; Lai, Ngan; Schaefer, Sarah; Chen, Herbert; Sippel, Rebecca S

    2013-03-01

    Current postoperative thyroid replacement dosing is weight based, with adjustments made after thyroid-stimulating hormone values. This method can lead to considerable delays in achieving euthyroidism and often fails to accurately dose over- and underweight patients. Our aim was to develop an accurate dosing method that uses patient body mass index (BMI) data. A retrospective review of a prospectively collected thyroid database was performed. We selected adult patients undergoing thyroidectomy, with benign pathology, who achieved euthyroidism on thyroid hormone supplementation. Body mass index and euthyroid dose were plotted and regression was used to fit curves to the data. Statistical analysis was performed using STATA 10.1 software (Stata Corp). One hundred twenty-two patients met inclusion criteria. At initial follow-up, only 39 patients were euthyroid (32%). Fifty-three percent of patients with BMI >30 kg/m(2) were overdosed, and 46% of patients with BMI regression equation was derived for calculating initial levothyroxine dose (μg/kg/d = -0.018 × BMI + 2.13 [F statistic = 52.7, root mean square error of 0.24]). The current standard of weight-based thyroid replacement fails to appropriately dose underweight and overweight patients. Body mass index can be used to more accurately dose thyroid hormone using a simple formula. Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  15. Cine dyscontractility index: A novel marker of mechanical dyssynchrony that predicts response to cardiac resynchronization therapy.

    Science.gov (United States)

    Werys, Konrad; Petryka-Mazurkiewicz, Joanna; Błaszczyk, Łukasz; Miśko, Jolanta; Śpiewak, Mateusz; Małek, Łukasz A; Mazurkiewicz, Łukasz; Miłosz-Wieczorek, Barbara; Marczak, Magdalena; Kubik, Agata; Dąbrowska, Agnieszka; Piątkowska-Janko, Ewa; Sawionek, Błażej; Wijesurendra, Rohan; Piechnik, Stefan K; Bogorodzki, Piotr

    2016-12-01

    To investigate whether magnetic resonance imaging (MRI) cine-derived dyssynchrony indices provide additional information compared to conventional tagged MRI (tMRI) acquisitions in heart failure patients undergoing cardiac resynchronization therapy (CRT). Patients scheduled for CRT (n = 52) underwent preprocedure MRI including cine and tMRI acquisitions. Segmental strain curves were calculated for both cine and tMRI to produce a range of standard indices for direct comparison between modalities. We also proposed and evaluated a novel index of "dyscontractility," which detects the presence of focal areas with paradoxically positive circumferential strain. Across conventional strain indices, there was only moderate-to-poor (R = 0.3-0.6) correlation between modalities; eight cine-derived indices showed statistically significant (P cine images (cine dyscontractility index, "CDI") was the single best predictor of clinical response to CRT (area under the curve AUC = 0.81, P Cine-derived strain indices offer potentially new information compared to tMRI. Specifically, the novel CDI is most strongly linked to response to cardiac resynchronization therapy in a contemporary patient cohort. It utilizes readily available MRI data, is relatively straightforward to process, and compares favorably with any conventional tagging index. J. Magn. Reson. Imaging 2016;44:1483-1492. © 2016 International Society for Magnetic Resonance in Medicine.

  16. A predictability study of Lorenz's 28-variable model as a dynamical system

    Science.gov (United States)

    Krishnamurthy, V.

    1993-01-01

    The dynamics of error growth in a two-layer nonlinear quasi-geostrophic model has been studied to gain an understanding of the mathematical theory of atmospheric predictability. The growth of random errors of varying initial magnitudes has been studied, and the relation between this classical approach and the concepts of the nonlinear dynamical systems theory has been explored. The local and global growths of random errors have been expressed partly in terms of the properties of an error ellipsoid and the Liapunov exponents determined by linear error dynamics. The local growth of small errors is initially governed by several modes of the evolving error ellipsoid but soon becomes dominated by the longest axis. The average global growth of small errors is exponential with a growth rate consistent with the largest Liapunov exponent. The duration of the exponential growth phase depends on the initial magnitude of the errors. The subsequent large errors undergo a nonlinear growth with a steadily decreasing growth rate and attain saturation that defines the limit of predictability. The degree of chaos and the largest Liapunov exponent show considerable variation with change in the forcing, which implies that the time variation in the external forcing can introduce variable character to the predictability.

  17. 10 km running performance predicted by a multiple linear regression model with allometrically adjusted variables.

    Science.gov (United States)

    Abad, Cesar C C; Barros, Ronaldo V; Bertuzzi, Romulo; Gagliardi, João F L; Lima-Silva, Adriano E; Lambert, Mike I; Pires, Flavio O

    2016-06-01

    The aim of this study was to verify the power of VO 2max , peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO 2max and PTV; 2) a constant submaximal run at 12 km·h -1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO 2max , PTV and RE) and adjusted variables (VO 2max 0.72 , PTV 0.72 and RE 0.60 ) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO 2max . Significant correlations (p 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV 0.72 and RE 0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.

  18. Value of Serial Heart Rate Variability Measurement for Prediction of Appropriate ICD Discharge in Patients with Heart Failure

    NARCIS (Netherlands)

    ten Sande, Judith N.; Damman, Peter; Tijssen, Jan G. P.; de Groot, Joris R.; Knops, Reinoud E.; Wilde, Arthur A. M.; van Dessel, Pascal F. H. M.

    2014-01-01

    HRV and Appropriate ICD Shock in Heart Failure Introduction Decreased heart rate variability (HRV) is associated with adverse outcomes in patients with heart failure. Our objective was to examine whether decreased HRV predicts appropriate implantable cardioverter defibrillator (ICD) shocks. Methods

  19. Review: The variability of the eating quality of beef can be reduced by predicting consumer satisfaction.

    Science.gov (United States)

    Bonny, S P F; Hocquette, J-F; Pethick, D W; Legrand, I; Wierzbicki, J; Allen, P; Farmer, L J; Polkinghorne, R J; Gardner, G E

    2018-04-02

    The Meat Standards Australia (MSA) grading scheme has the ability to predict beef eating quality for each 'cut×cooking method combination' from animal and carcass traits such as sex, age, breed, marbling, hot carcass weight and fatness, ageing time, etc. Following MSA testing protocols, a total of 22 different muscles, cooked by four different cooking methods and to three different degrees of doneness, were tasted by over 19 000 consumers from Northern Ireland, Poland, Ireland, France and Australia. Consumers scored the sensory characteristics (tenderness, flavor liking, juiciness and overall liking) and then allocated samples to one of four quality grades: unsatisfactory, good-every-day, better-than-every-day and premium. We observed that 26% of the beef was unsatisfactory. As previously reported, 68% of samples were allocated to the correct quality grades using the MSA grading scheme. Furthermore, only 7% of the beef unsatisfactory to consumers was misclassified as acceptable. Overall, we concluded that an MSA-like grading scheme could be used to predict beef eating quality and hence underpin commercial brands or labels in a number of European countries, and possibly the whole of Europe. In addition, such an eating quality guarantee system may allow the implementation of an MSA genetic index to improve eating quality through genetics as well as through management. Finally, such an eating quality guarantee system is likely to generate economic benefits to be shared along the beef supply chain from farmers to retailors, as consumers are willing to pay more for a better quality product.

  20. Fuel temperature prediction using a variable bypass gap size in the prismatic VHTR

    International Nuclear Information System (INIS)

    Lee, Sung Nam; Tak, Nam-il; Kim, Min Hwan

    2016-01-01

    Highlights: • The bypass flow of the prismatic very high temperature reactor is analyzed. • The bypass gap sizes are calculated considering the effect of the neutron fluences and thermal expansion. • The fuel hot spot temperature and temperature profiles are calculated using the variable gap size. • The BOC, MOC and EOC condition at the cycle 07 and 14 are applied. - Abstract: The temperature gradient and hot spot temperatures were calculated in the prismatic very high temperature reactor as a function of the variable bypass gap size. Many previous studies have predicted the temperature of the reactor core based on a fixed bypass gap size. The graphite matrix of the assemblies in the reactor core undergoes a dimensional change during the operation due to thermal expansion and neutron fluence. The expansion and shrinkage of the bypass gaps change the coolant flow fractions into the coolant channels, the control rod holes, and the bypass gaps. Therefore, the temperature of the assemblies may differ compared to those for the fixed bypass gap case. The temperature gradient and the hot spot temperatures are important for the design of reactor structures to ensure their safety and efficiency. In the present study, the temperature variation of the PMR200 is studied at the beginning (BOC), middle (MOC), and end (EOC) of cycles 07 and 14. CORONA code which has been developed in KAERI is applied to solve the thermal-hydraulics of the reactor core of the PMR200. CORONA solves a fluid region using a one-dimensional formulation and a solid region using a three-dimensional formulation to enhance the computational speed and still obtain a reasonable accuracy. The maximum temperatures in the fuel assemblies using the variable bypass gaps did not differ much from the corresponding temperatures using the fixed bypass gaps. However, the maximum temperatures in the reflector assemblies using the variable bypass gaps differ significantly from the corresponding temperatures

  1. Variability and predictability of decadal mean temperature and precipitation over China in the CCSM4 last millennium simulation

    Science.gov (United States)

    Ying, Kairan; Frederiksen, Carsten S.; Zheng, Xiaogu; Lou, Jiale; Zhao, Tianbao

    2018-02-01

    The modes of variability that arise from the slow-decadal (potentially predictable) and intra-decadal (unpredictable) components of decadal mean temperature and precipitation over China are examined, in a 1000 year (850-1850 AD) experiment using the CCSM4 model. Solar variations, volcanic aerosols, orbital forcing, land use, and greenhouse gas concentrations provide the main forcing and boundary conditions. The analysis is done using a decadal variance decomposition method that identifies sources of potential decadal predictability and uncertainty. The average potential decadal predictabilities (ratio of slow-to-total decadal variance) are 0.62 and 0.37 for the temperature and rainfall over China, respectively, indicating that the (multi-)decadal variations of temperature are dominated by slow-decadal variability, while precipitation is dominated by unpredictable decadal noise. Possible sources of decadal predictability for the two leading predictable modes of temperature are the external radiative forcing, and the combined effects of slow-decadal variability of the Arctic oscillation (AO) and the Pacific decadal oscillation (PDO), respectively. Combined AO and PDO slow-decadal variability is associated also with the leading predictable mode of precipitation. External radiative forcing as well as the slow-decadal variability of PDO are associated with the second predictable rainfall mode; the slow-decadal variability of Atlantic multi-decadal oscillation (AMO) is associated with the third predictable precipitation mode. The dominant unpredictable decadal modes are associated with intra-decadal/inter-annual phenomena. In particular, the El Niño-Southern Oscillation and the intra-decadal variability of the AMO, PDO and AO are the most important sources of prediction uncertainty.

  2. PREDICTION OF WATER QUALITY INDEX USING BACK PROPAGATION NETWORK ALGORITHM. CASE STUDY: GOMBAK RIVER

    Directory of Open Access Journals (Sweden)

    FARIS GORASHI

    2012-08-01

    Full Text Available The aim of this study is to enable prediction of water quality parameters with conjunction to land use attributes and to find a low-end alternative for water quality monitoring techniques, which are typically expensive and tedious. It also aims to ensure sustainable development, which is essentially has effects on water quality. The research approach followed in this study is via using artificial neural networks, and geographical information system to provide a reliable prediction model. Back propagation network algorithm was used for the purpose of this study. The proposed approach minimized most of anomalies associated with prediction methods and provided water quality prediction with precision. The study used 5 hidden nodes in this network. The network was optimized to complete 23145 cycles before it reaches the best error of 0.65. Stations 18 had shown the greatest fluctuation among the three stations as it reflects an area of on-going rapid development of Gombak river watershed. The results had shown a very close prediction with best error of 0.67 in a sensitivity test that was carried afterwards.

  3. Seasonal Variability of Aragonite Saturation State in the North Pacific Ocean Predicted by Multiple Linear Regression

    Science.gov (United States)

    Kim, T. W.; Park, G. H.

    2014-12-01

    Seasonal variation of aragonite saturation state (Ωarag) in the North Pacific Ocean (NPO) was investigated, using multiple linear regression (MLR) models produced from the PACIFICA (Pacific Ocean interior carbon) dataset. Data within depth ranges of 50-1200m were used to derive MLR models, and three parameters (potential temperature, nitrate, and apparent oxygen utilization (AOU)) were chosen as predictor variables because these parameters are associated with vertical mixing, DIC (dissolved inorganic carbon) removal and release which all affect Ωarag in water column directly or indirectly. The PACIFICA dataset was divided into 5° × 5° grids, and a MLR model was produced in each grid, giving total 145 independent MLR models over the NPO. Mean RMSE (root mean square error) and r2 (coefficient of determination) of all derived MLR models were approximately 0.09 and 0.96, respectively. Then the obtained MLR coefficients for each of predictor variables and an intercept were interpolated over the study area, thereby making possible to allocate MLR coefficients to data-sparse ocean regions. Predictability from the interpolated coefficients was evaluated using Hawaiian time-series data, and as a result mean residual between measured and predicted Ωarag values was approximately 0.08, which is less than the mean RMSE of our MLR models. The interpolated MLR coefficients were combined with seasonal climatology of World Ocean Atlas 2013 (1° × 1°) to produce seasonal Ωarag distributions over various depths. Large seasonal variability in Ωarag was manifested in the mid-latitude Western NPO (24-40°N, 130-180°E) and low-latitude Eastern NPO (0-12°N, 115-150°W). In the Western NPO, seasonal fluctuations of water column stratification appeared to be responsible for the seasonal variation in Ωarag (~ 0.5 at 50 m) because it closely followed temperature variations in a layer of 0-75 m. In contrast, remineralization of organic matter was the main cause for the seasonal

  4. Association of Climatic Variability, Vector Population and Malarial Disease in District of Visakhapatnam, India: A Modeling and Prediction Analysis.

    Science.gov (United States)

    Srimath-Tirumula-Peddinti, Ravi Chandra Pavan Kumar; Neelapu, Nageswara Rao Reddy; Sidagam, Naresh

    2015-01-01

    Malarial incidence, severity, dynamics and distribution of malaria are strongly determined by climatic factors, i.e., temperature, precipitation, and relative humidity. The objectives of the current study were to analyse and model the relationships among climate, vector and malaria disease in district of Visakhapatnam, India to understand malaria transmission mechanism (MTM). Epidemiological, vector and climate data were analysed for the years 2005 to 2011 in Visakhapatnam to understand the magnitude, trends and seasonal patterns of the malarial disease. Statistical software MINITAB ver. 14 was used for performing correlation, linear and multiple regression analysis. Perennial malaria disease incidence and mosquito population was observed in the district of Visakhapatnam with peaks in seasons. All the climatic variables have a significant influence on disease incidence as well as on mosquito populations. Correlation coefficient analysis, seasonal index and seasonal analysis demonstrated significant relationships among climatic factors, mosquito population and malaria disease incidence in the district of Visakhapatnam, India. Multiple regression and ARIMA (I) models are best suited models for modeling and prediction of disease incidences and mosquito population. Predicted values of average temperature, mosquito population and malarial cases increased along with the year. Developed MTM algorithm observed a major MTM cycle following the June to August rains and occurring between June to September and minor MTM cycles following March to April rains and occurring between March to April in the district of Visakhapatnam. Fluctuations in climatic factors favored an increase in mosquito populations and thereby increasing the number of malarial cases. Rainfall, temperatures (20°C to 33°C) and humidity (66% to 81%) maintained a warmer, wetter climate for mosquito growth, parasite development and malaria transmission. Changes in climatic factors influence malaria directly by

  5. Predictive validity of the GOSLON Yardstick index in patients with unilateral cleft lip and palate: A systematic review.

    Directory of Open Access Journals (Sweden)

    Cindy Buj-Acosta

    Full Text Available Among the various indices developed for measuring the results of treatment in patients born with unilateral cleft lip and palate (UCLP, the GOSLON Yardstick index is the most widely used to assess the efficacy of treatment and treatment outcomes, which in UCLP cases are closely linked to jaw growth. The aim of this study was to conduct a systematic review to validate the predictability of growth using the GOSLON Yardstick in patients born with UCLP. A systematic literature review was conducted in four Internet databases: Medline, Cochrane Library, Scopus and Embase, complemented by a manual search and a further search in the databases of the leading journals that focus on this topic. An electronic search was also conducted among grey literature. The search identified a total of 131 articles. Duplicated articles were excluded and after reading titles and abstracts, any articles not related to the research objective were excluded, leaving a total of 21 texts. After reading the complete text, only three articles fulfilled the inclusion criteria. The results showed a predictive validity of between 42.2% and 64.7%, which points to a lack of evidence in the literature for the predictive validity of the GOSLON Yardstick index used in children born with UCLP.

  6. Role of bedside index for severity of acute pancreatitis (bisap score in predicting outcome in acute pancreatitis

    Directory of Open Access Journals (Sweden)

    Shahnawaz Bashir Bhat

    2015-12-01

    Full Text Available Objective: To investigate the role of Bedside index for severity of acute pancreatitis (BISAP score in predicting the outcome of acute pancreatitis. Methods: This single hospital based prospective study included fifty patients of acute pancreatitis admitted within 48 hours of onset of symptoms, who were divided into two groups according to admission BISAP score. BISAP score 3 (severe acute pancreatitis. The ability of BISAP score to predict mortality, morbidity and hospital stay in acute pancreatitis patients was analyzed. Results: A BISAP score of >3 was associated with increased risk of development of transient organ failure, persistent organ failure and pancreatic necrosis (Statistically significant. Mortality in group with BISAP and #8805;3 was 23.5% (4 patients which was statistically higher than group with BISAP score and #706;3 (0 patients (p=0.019.The mean duration of hospital stay of patients in group with BISAP score < 3 was 7.58 +/- 4.04 days and in group with BISAP score and #8805;3 was 15.35 +/- 1.66.(p=0.02. Conclusion: Bedside index for severity in acute pancreatitis (BISAP score, at admission is an excellent score in predicting the mortality, morbidity and hospital stay and hence management protocol in patients admitted with acute pancreatitis. [J Contemp Med 2015; 5(4.000: 215-220

  7. Dengue Baidu Search Index data can improve the prediction of local dengue epidemic: A case study in Guangzhou, China.

    Directory of Open Access Journals (Sweden)

    Zhihao Li

    2017-03-01

    Full Text Available Dengue fever (DF in Guangzhou, Guangdong province in China is an important public health issue. The problem was highlighted in 2014 by a large, unprecedented outbreak. In order to respond in a more timely manner and hence better control such potential outbreaks in the future, this study develops an early warning model that integrates internet-based query data into traditional surveillance data.A Dengue Baidu Search Index (DBSI was collected from the Baidu website for developing a predictive model of dengue fever in combination with meteorological and demographic factors. Generalized additive models (GAM with or without DBSI were established. The generalized cross validation (GCV score and deviance explained indexes, intraclass correlation coefficient (ICC and root mean squared error (RMSE, were respectively applied to measure the fitness and the prediction capability of the models. Our results show that the DBSI with one-week lag has a positive linear relationship with the local DF occurrence, and the model with DBSI (ICC:0.94 and RMSE:59.86 has a better prediction capability than the model without DBSI (ICC:0.72 and RMSE:203.29.Our study suggests that a DSBI combined with traditional disease surveillance and meteorological data can improve the dengue early warning system in Guangzhou.

  8. Modified GAP index for prediction of acute exacerbation of idiopathic pulmonary fibrosis in non-small cell lung cancer.

    Science.gov (United States)

    Kobayashi, Haruki; Omori, Shota; Nakashima, Kazuhisa; Wakuda, Kazushige; Ono, Akira; Kenmotsu, Hirotsugu; Naito, Tateaki; Murakami, Haruyasu; Endo, Masahiro; Takahashi, Toshiaki

    2017-10-01

    Predicting the incidence rate of acute exacerbation (AE) of idiopathic pulmonary fibrosis (IPF) and its prognosis in patients with non-small cell lung cancer (NSCLC) and IPF is difficult. The aim was to study the incidence of IPF-AE during the clinical course of the disease and its prognosis in patients with both NSCLC and IPF. In this retrospective study, we compared the incidence rate of AE during the clinical course of the disease as well as the 1-year survival rate and overall survival (OS) of patients with NSCLC and IPF using a modified gender, age and physiology (mGAP) staging system based on gender, age and percent predicted forced vital capacity. Of 43 patients with NSCLC and IPF included in the final analysis, 17 patients (40%; 95% CI: 26-54%) experienced AE during the clinical course of the disease. One-year survival and median OS were 41.9% (95% CI: 28-57%) and 9.4 months, respectively. Further analysis showed that the incidence of IPF-AE gradually increased and that the 1-year survival rate and median OS gradually decreased with increasing mGAP index score and stage. Our study suggested that mGAP index score and cancer stage may predict IPF-AE and its prognosis in patients with NSCLC and IPF. © 2017 Asian Pacific Society of Respirology.

  9. Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study.

    Science.gov (United States)

    Pekkala, Timo; Hall, Anette; Lötjönen, Jyrki; Mattila, Jussi; Soininen, Hilkka; Ngandu, Tiia; Laatikainen, Tiina; Kivipelto, Miia; Solomon, Alina

    2017-01-01

    This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study. The CAIDE study was based on previous population-based midlife surveys. CAIDE participants were re-examined twice in late-life, and the first late-life re-examination was used as baseline for the present study. The main study population included 709 cognitively normal subjects at first re-examination who returned to the second re-examination up to 10 years later (incident dementia n = 39). An extended population (n = 1009, incident dementia 151) included non-participants/non-survivors (national registers data). DSI was used to develop a dementia index based on first re-examination assessments. Performance in predicting dementia was assessed as area under the ROC curve (AUC). AUCs for DSI were 0.79 and 0.75 for main and extended populations. Included predictors were cognition, vascular factors, age, subjective memory complaints, and APOE genotype. The supervised machine learning method performed well in identifying comprehensive profiles for predicting dementia development up to 10 years later. DSI could thus be useful for identifying individuals who are most at risk and may benefit from dementia prevention interventions.

  10. The property distance index PD predicts peptides that cross-react with IgE antibodies

    Science.gov (United States)

    Ivanciuc, Ovidiu; Midoro-Horiuti, Terumi; Schein, Catherine H.; Xie, Liping; Hillman, Gilbert R.; Goldblum, Randall M.; Braun, Werner

    2009-01-01

    Similarities in the sequence and structure of allergens can explain clinically observed cross-reactivities. Distinguishing sequences that bind IgE in patient sera can be used to identify potentially allergenic protein sequences and aid in the design of hypo-allergenic proteins. The property distance index PD, incorporated in our Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/), may identify potentially cross-reactive segments of proteins, based on their similarity to known IgE epitopes. We sought to obtain experimental validation of the PD index as a quantitative predictor of IgE cross-reactivity, by designing peptide variants with predetermined PD scores relative to three linear IgE epitopes of Jun a 1, the dominant allergen from mountain cedar pollen. For each of the three epitopes, 60 peptides were designed with increasing PD values (decreasing physicochemical similarity) to the starting sequence. The peptides synthesized on a derivatized cellulose membrane were probed with sera from patients who were allergic to Jun a 1, and the experimental data were interpreted with a PD classification method. Peptides with low PD values relative to a given epitope were more likely to bind IgE from the sera than were those with PD values larger than 6. Control sequences, with PD values between 18 and 20 to all the three epitopes, did not bind patient IgE, thus validating our procedure for identifying negative control peptides. The PD index is a statistically validated method to detect discrete regions of proteins that have a high probability of cross-reacting with IgE from allergic patients. PMID:18950868

  11. Predicting AEA dosage by Foam Index and adsorption on Fly Ash

    OpenAIRE

    Jacobsen, Stefan; Ollendorff, Margrethe; Geiker, Mette Rica; Tunstall, Lori; Scherer, George W.

    2012-01-01

    Abstract: The unpredictable air entrainment in fly ash concrete caused by carbon in fly ash was studied by measuring adsorption of Air Entraining Agents (AEA) on the fly ash and by Foam Index (FI) testing. The FI test measures the mass ratio of AEA/binder required to obtain stable foam when shaking a mixture of water, binder powder and AEA, while increasing AEA-dosage stepwise. A review of concrete air entrainment and new studies combining adsorption (TGA, NMR) of AEA on fly ash with various ...

  12. Predicting Soil Strength in Terms of Cone Index and California Bearing Ratio for Trafficability

    Science.gov (United States)

    2016-03-01

    in Equation 4 (Anderson 1983). One can see the variation to Equation 1 (McDaniel and Smith 1971). Collins and Molthan suggested the lower and upper...and the amount of drainage, as defined by a wetness index term ( Collins 1971; Molthan 1967). ERDC/GSL TN-16-1 March 2016 4 2 123 0 008 0 693 4...since its development in the 1940s. It was devised by Jim Porter ( 1 9 5 0 ) of the California Division of Highways. Porter developed curves showing the

  13. Comparison between frailty index of deficit accumulation and fracture risk assessment tool (FRAX) in prediction of risk of fractures.

    Science.gov (United States)

    Li, Guowei; Thabane, Lehana; Papaioannou, Alexandra; Adachi, Jonathan D

    2015-08-01

    A frailty index (FI) of deficit accumulation could quantify and predict the risk of fractures based on the degree of frailty in the elderly. We aimed to compare the predictive powers between the FI and the fracture risk assessment tool (FRAX) in predicting risk of major osteoporotic fracture (hip, upper arm or shoulder, spine, or wrist) and hip fracture, using the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort. There were 3985 women included in the study, with the mean age of 69.4 years (standard deviation [SD] = 8.89). During the follow-up, there were 149 (3.98%) incident major os