WorldWideScience

Sample records for variability index predicts

  1. 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

  2. Symptomless Multi-Variable Apnea Prediction Index Assesses Obstructive Sleep Apnea Risk and Adverse Outcomes in Elective Surgery.

    Science.gov (United States)

    Lyons, M Melanie; Keenan, Brendan T; Li, Junxin; Khan, Tanya; Elkassabany, Nabil; Walsh, Colleen M; Williams, Noel N; Pack, Allan I; Gurubhagavatula, Indira

    2017-03-01

    To validate that the symptomless Multi-Variable Apnea Prediction index (sMVAP) is associated with Obstructive Sleep Apnea (OSA) diagnosis and assess the relationship between sMVAP and adverse outcomes in patients having elective surgery. We also compare associations between Bariatric surgery, where preoperative screening for OSA risk is mandatory, and non-Bariatric surgery groups who are not screened routinely for OSA. Using data from 40 432 elective inpatient surgeries, we used logistic regression to determine the relationship between sMVAP and previous OSA, current hypertension, and postoperative complications: extended length of stay (ELOS), intensive-care-unit-stay (ICU-stay), and respiratory complications (pulmonary embolism, acute respiratory distress syndrome, and/or aspiration pneumonia). Higher sMVAP was associated with increased likelihood of previous OSA, hypertension and all postoperative complications (p risk measured by sMVAP correlates with higher risk for select postoperative complications. Associations are stronger for non-Bariatric surgeries, where preoperative screening for OSA is not routinely performed. Thus, preoperative screening may reduce OSA-related risk for adverse postoperative outcomes.

  3. Formula for predicting OSA and the Apnea-Hypopnea Index in Koreans with suspected OSA using clinical, anthropometric, and cephalometric variables.

    Science.gov (United States)

    Kim, Seon Tae; Park, Kee Hyung; Shin, Seung-Heon; Kim, Ji-Eun; Pae, Chi-Un; Ko, Kwang-Pil; Hwang, Hee Young; Kang, Seung-Gul

    2017-12-01

    This study developed formulas to predict obstructive sleep apnea (OSA) and the Apnea-Hypopnea Index (AHI) in Korean patients with suspected OSA using clinical, anthropometric, and cephalometric variables. We evaluated relevant variables in 285 subjects with suspected OSA. These included demographic characteristics, sleep-related symptoms, medical history, clinical scales, anthropometric measurements including facial surface measurements, and cephalometric measurements. All participants underwent full-night laboratory polysomnography. The prediction formula for the probability of OSA was created by logistic regression analysis and confirmed by the bootstrap resampling technique. The formula for predicting the AHI was developed using multiple linear regression analysis. The probability of having OSA was as follows: p = 1 / (1 + exponential (exp)-f ), where f = -16.508 + 1.445 × loudness of snoring 4 + 0.485 × loudness of snoring 3 + 0.078 × waist circumference + 0.209 × subnasale-to-stomion distance + 0.183 × thickness of the uvula (UTH) supine + 0.041 × age. The AHI prediction formula was as follows: -112.606 + 3.516 × body mass index + 0.683 × mandibular plane-hyoid supine + 10.915 × loudness of snoring 4 + 6.933 × loudness of snoring 3 + 1.297 × UTH supine + 0.272 × age. This is the first study to establish formulas to predict OSA and the AHI in Koreans with suspected OSA using cephalometric and other variables. These results will contribute to prioritizing the order in which patients with suspected OSA are referred for polysomnography.

  4. Grid of streamflow variability index for Ohio

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — A generalized streamflow-variability index coverage was created by interpolating a grid (with 6,066-ft^2 cells) from at-site values of the streamflow-variability...

  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. Linear and Nonlinear Heart Rate Variability Indexes in Clinical Practice

    Directory of Open Access Journals (Sweden)

    Buccelletti Francesco

    2012-01-01

    Full Text Available Biological organisms have intrinsic control systems that act in response to internal and external stimuli maintaining homeostasis. Human heart rate is not regular and varies in time and such variability, also known as heart rate variability (HRV, is not random. HRV depends upon organism's physiologic and/or pathologic state. Physicians are always interested in predicting patient's risk of developing major and life-threatening complications. Understanding biological signals behavior helps to characterize patient's state and might represent a step toward a better care. The main advantage of signals such as HRV indexes is that it can be calculated in real time in noninvasive manner, while all current biomarkers used in clinical practice are discrete and imply blood sample analysis. In this paper HRV linear and nonlinear indexes are reviewed and data from real patients are provided to show how these indexes might be used in clinical practice.

  7. Predictive value of beat-to-beat QT variability index across the continuum of left ventricular dysfunction: competing risks of noncardiac or cardiovascular death and sudden or nonsudden 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

    2012-08-01

    The goal of the present study was to determine the predictive value of beat-to-beat QT variability in heart failure patients across the continuum of left ventricular dysfunction. Beat-to-beat QT variability index (QTVI), log-transformed heart rate variance, normalized QT variance, 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 heart failure study (mean age, 63.1±11.7; men, 70.6%; left ventricular ejection fraction >35% in 254 [48%]) and in 181 healthy participants from the Intercity Digital Electrocardiogram Alliance 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 (subhazard ratio, 1.67 [95% CI, 1.14-2.47]; P=0.009) and, in particular, with non-SCD (subhazard ratio, 2.91 [1.69-5.01]; P<0.001). Elevated QTVI separated 97.5% of healthy individuals from subjects at risk for cardiovascular (subhazard ratio, 1.57 [1.04-2.35]; P=0.031) and non-SCD in multivariate competing risk model (subhazard ratio, 2.58 [1.13-3.78]; P=0.001). No interaction between QTVI and left ventricular ejection fraction was found. QTVI predicted neither noncardiac death (P=0.546) nor SCD (P=0.945). Decreased heart rate variability rather than increased QT variability was the reason for increased QTVI in the present study. Increased QTVI because of depressed heart rate variability predicts cardiovascular mortality and non-SCD but neither SCD nor extracardiac mortality in heart failure across the continuum of left ventricular dysfunction. Abnormally augmented QTVI separates 97.5% of healthy individuals from heart failure patients at risk.

  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. A variable polytrope index applied to planet and material models

    Science.gov (United States)

    Thielen, Kevin; Weppner, Stephen; Zielinski, Alexander

    2016-01-01

    We introduce a new approach to a century-old assumption which enhances not only planetary interior calculations but also high-pressure material physics. We show that the polytropic index is the derivative of the bulk modulus with respect to pressure. We then augment the traditional polytrope theory by including a variable polytrope index within the confines of the Lane-Emden differential equation. To investigate the possibilities of this method, we create a high-quality universal equation of state, transforming the traditional polytrope method to a tool with the potential for excellent predictive power. The theoretical foundation of our equation of state is the same elastic observable which we found equivalent to the polytrope index, the derivative of the bulk modulus with respect to pressure. We calculate the density-pressure of six common materials up to 1018 Pa, mass-radius relationships for the same materials, and produce plausible density-radius models for the rocky planets of our Solar system. We argue that the bulk modulus and its derivatives have been underutilized in previous planet formation methods. We constrain the material surface observables for the inner core, outer core, and mantle of planet Earth in a systematic way including pressure, bulk modulus, and the polytrope index in the analysis. We believe that this variable polytrope method has the necessary apparatus to be extended further to gas giants and stars. As supplemental material we provide computer code to calculate multi-layered planets.

  10. 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...

  11. Entire functions of several variables of bounded index

    OpenAIRE

    Bandura, Andriy; Skaskiv, Oleh

    2015-01-01

    This monograph is devoted to the theory of entire functions of several variables. A definition of bounded index was supposed by B. Lepson. We generalised his definition for several variables and obtained criteria of L-index boundedness in direction. In particular we obtained obtain analogues of one-dimensional criterion of boundedness L-index in terms of behaviour the logarithmic derivative outside of zero sets, sufficient conditions of L-index boundedness in direction for some subclass of en...

  12. QT variability index on 24-hour Holter independently predicts mortality in patients with heart failure: analysis of Gruppo Italiano per lo Studio della Sopravvivenza nell'Insufficienza Cardiaca (GISSI-HF) trial.

    Science.gov (United States)

    Dobson, Craig P; La Rovere, Maria Teresa; Pinna, Gian Domenico; Goldstein, Robert; Olsen, Cara; Bernardinangeli, Marino; Veniani, Marco; Midi, Paolo; Tavazzi, Luigi; Haigney, Mark

    2011-08-01

    Increased temporal variability of repolarization, as reflected by QT interval variability measured over 10-15 minutes, predicted spontaneous ventricular arrhythmias and death in implantable cardioverter-defibrillator patients in mild to moderate heart failure (HF). The purpose of this study was to test our hypothesis that increased mean QT variability over 24 hours would be associated with increased cardiovascular (CV) mortality in a heterogeneous HF population. The Gruppo Italiano per lo Studio della Sopravvivenza nell'Insufficienza Cardiaca-Heart Failure trial prospectively enrolled subjects with HF of any cause. Twenty-four-hour Holter recordings from 268 subjects were analyzed using a template-matching, semiautomatic algorithm to measure QT and heart rate time series in sequential 5-minute epochs over 24 hours. The QT variability index (QTVI) was expressed as the log ratio of the normalized QT variance over normalized heart rate variance. Total and CV mortality were assessed as a function of continuous and dichotomous QTVI (>-0.84) in univariate and multivariable Cox proportional hazards models, adjusting for significant clinical predictors. After a median of 47 months, there were 53 deaths, of which 44 were from CV causes. A significant association with the outcome was found for QTVI both as continuous and dichotomous variables after adjustment for clinical covariates (age >70, New York Heart Association class III-IV, left ventricular ejection fraction, nonsustained ventricular tachycardia, creatinine): QTVI hazard ratio (HR) 4.0 (confidence interval [CI] 1.8-88; P = .008) for total and 4.4 (CI 1.9-10.1; P = .0006) for CV mortality; QTVI >-0.84 HR 2.0 (CI 1.1-3.6; P = .02) for total and 2.1 (CI 1.1-3.8; P = .02) for CV mortality. Increased repolarization lability, as reflected in QTVI measured over 24 hours, is associated with increased risk for total and CV mortality in a heterogeneous population with chronic HF. Published by Elsevier Inc.

  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. Distribution of hourly variability index of sky clearness | Madhlopa ...

    African Journals Online (AJOL)

    Clouds affect the values of insolation for solar technology and other applications. To detect the presence of variability in the sky clearness, an hourly variability index ( 3) is calculated. The present study examined the frequency distribution of this variable as a tool for assessing the utilizability of solar radiation at a site.

  15. Chatter Prediction for Variable Pitch and Variable Helix Milling

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2015-01-01

    Full Text Available Regenerative chatter is a self-excited vibration that can occur during milling, which shortens the lifetime of the tool and results in unacceptable surface quality. In this paper, an improved semidiscretization method for modeling and simulation with variable pitch and variable helix milling is proposed. Because the delay between each flute varies along the axial depth of the tool in milling, the cutting tool is discrete into some axial layers to simplify calculation. A comparison of the predicted and observed performance of variable pitch and variable helix against uniform pitch and uniform helix milling is presented. It is shown that variable pitch and variable helix milling can obtain larger stable cutting area than uniform pitch and uniform helix milling. Thus, it is concluded that variable pitch and variable helix milling are an effective way for suppressing chatter.

  16. 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...

  17. 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)

  18. Process capability index-based control chart for variables

    OpenAIRE

    Adeoti, Olatunde Adebayo; Olaomi, John Olutunji

    2017-01-01

    This paper proposes a process capability index-based control chart for variables using the Downton estimator with a specified Cp value. The proposed chart is able to address the issue of control and capability simultaneously. We also provide a control chart constant to construct the process capability index-based control chart. A numerical example is presented to demonstrate the application of the proposed chart, and the effect of non-normality is discussed. The result shows that the proposed...

  19. Predictive power of Mannheim Peritonitis Index.

    Science.gov (United States)

    Qureshi, Abrar Maqbool; Zafar, Afsheen; Saeed, Khurram; Quddus, Abdul

    2005-11-01

    To evaluate Mannheim Peritonitis Index (MPI) in predicting outcome in patients with secondary peritonitis and to assess each risk factor independently regarding its contribution towards final outcome. Prospective analytical study. Surgical Unit-II of Rawalpindi General Hospital, from December 1999 to January 2001. One hundred and twenty-six patients who presented to the department with secondary peritonitis were included in the study. MPI score was calculated for each patient on a pre-designed proforma and the patients were followed-up till death or discharged from the hospital. Death was the main outcome measure against which the MPI scores were analyzed under two categories; (i) score > or = 26 and 29. Data was analyzed on software SPSS (version 11.0). Chi-square test was used to assess any significant association between scores and outcome. Odds ratios were calculated for individual risk factors. Mortality rate for MPI score > or = 26 was 28.1% while for scores less than 26 it was 4.3%. For MPI scores pound 20 mortality rate was 1.9%, for scores 21-29 it was 21.9% and for score 30 or more it was 28.1%. Chi-square showed significant association between mortality and increasing MPI score (p 50 years, malignancy, organ failure, pre-operative duration of peritonitis > 24 hours and cloudy, purulent exudate. Increasing MPI score is strongly associated with outcome in secondary peritonitis.

  20. 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....

  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. Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

    Science.gov (United States)

    Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga

    2011-01-01

    A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

  3. Process capability index-based control chart for variables

    Directory of Open Access Journals (Sweden)

    Adeoti, Olatunde Adebayo

    2017-08-01

    Full Text Available This paper proposes a process capability index-based control chart for variables using the Downton estimator with a specified Cp value. The proposed chart is able to address the issue of control and capability simultaneously. We also provide a control chart constant to construct the process capability index-based control chart. A numerical example is presented to demonstrate the application of the proposed chart, and the effect of non-normality is discussed. The result shows that the proposed control chart performs better in monitoring and assessing processes, and eliminates the usual two-stage procedure reflected in the literature.

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. Heart rate variability and Omega-3 Index in euthymic patients with bipolar disorders.

    Science.gov (United States)

    Voggt, A; Berger, M; Obermeier, M; Löw, A; Seemueller, F; Riedel, M; Moeller, H J; Zimmermann, R; Kirchberg, F; Von Schacky, C; Severus, E

    2015-02-01

    Affective disorders are associated with an increased risk of cardiovascular disease, which, at least partly, appears to be independent of psychopharmacological treatments used to manage these disorders. Reduced heart rate variability (SDNN) and a low Omega-3 Index have been shown to be associated with increased risk for death after myocardial infarction. Therefore, we set out to investigate heart rate variability and the Omega-3 Index in euthymic patients with bipolar disorders. We assessed heart rate variability (SDNN) and the Omega-3 Index in 90 euthymic, mostly medicated patients with bipolar disorders (Bipolar-I, Bipolar-II) on stable psychotropic medication, free of significant medical comorbidity and in 62 healthy controls. Heart rate variability was measured from electrocardiography under a standardized 30 minutes resting state condition. Age, sex, BMI, smoking, alcohol consumption and caffeine consumption as potential confounders were also assessed. Heart rate variability (SDNN) was significantly lower in patients with bipolar disorders compared to healthy controls (35.4 msec versus 60.7 msec; Pbipolar disorders versus healthy controls) and age significantly predicted heart rate variability (SDNN). Heart rate variability (SDNN) may provide a useful tool to study the impact of interventions aimed at reducing the increased risk of cardiovascular disease in euthymic patients with bipolar disorders. The difference in SDNN between cases and controls cannot be explained by a difference in the Omega-3 Index. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  9. Neural Variability Quenching Predicts Individual Perceptual Abilities.

    Science.gov (United States)

    Arazi, Ayelet; Censor, Nitzan; Dinstein, Ilan

    2017-01-04

    Neural activity during repeated presentations of a sensory stimulus exhibits considerable trial-by-trial variability. Previous studies have reported that trial-by-trial neural variability is reduced (quenched) by the presentation of a stimulus. However, the functional significance and behavioral relevance of variability quenching and the potential physiological mechanisms that may drive it have been studied only rarely. Here, we recorded neural activity with EEG as subjects performed a two-interval forced-choice contrast discrimination task. Trial-by-trial neural variability was quenched by ∼40% after the presentation of the stimulus relative to the variability apparent before stimulus presentation, yet there were large differences in the magnitude of variability quenching across subjects. Individual magnitudes of quenching predicted individual discrimination capabilities such that subjects who exhibited larger quenching had smaller contrast discrimination thresholds and steeper psychometric function slopes. Furthermore, the magnitude of variability quenching was strongly correlated with a reduction in broadband EEG power after stimulus presentation. Our results suggest that neural variability quenching is achieved by reducing the amplitude of broadband neural oscillations after sensory input, which yields relatively more reproducible cortical activity across trials and enables superior perceptual abilities in individuals who quench more. Variability quenching is a phenomenon in which neural variability across trials is reduced by the presentation of a stimulus. Although this phenomenon has been reported across a variety of animal and human studies, its functional significance and behavioral relevance have been examined only rarely. Here, we report novel empirical evidence from humans revealing that variability quenching differs dramatically across individual subjects and explains to a certain degree why some individuals exhibit better perceptual abilities than

  10. 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.

  11. 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

    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......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...

  12. 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

  13. 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...

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

    NARCIS (Netherlands)

    W.A. Marquering (Wessel); M.J.C.M. Verbeek (Marno)

    2001-01-01

    textabstractIn this paper, we analyze the economic value of predicting stock index returns as well as volatility. On the basis of 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

  15. 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

  16. 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.

  17. 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...

  18. Forecasting neutron star temperatures: predictability and variability.

    Science.gov (United States)

    Page, Dany; Reddy, Sanjay

    2013-12-13

    It is now possible to model thermal relaxation of neutron stars after bouts of accretion during which the star is heated out of equilibrium by nuclear reactions in its crust. Major uncertainties in these models can be encapsulated in modest variations of a handful of control parameters that change the fiducial crustal thermal conductivity, specific heat, and heating rates. Observations of thermal relaxation constrain these parameters and allow us to predict longer term variability in terms of the neutron star core temperature. We demonstrate this explicitly by modeling ongoing thermal relaxation in the neutron star XTE J1701-462. Its future cooling, over the next 5 to 30 years, is strongly constrained and depends mostly on its core temperature, uncertainties in crust physics having essentially been pinned down by fitting to the first three years of observations.

  19. Cast index in predicting outcome of proximal pediatric forearm fractures

    Directory of Open Access Journals (Sweden)

    Hassaan Qaiser Sheikh

    2015-01-01

    Conclusion: Cast index is useful in predicting redisplacement of manipulated distal forearm fractures. We found that in proximal half forearm fractures it is difficult to achieve a CI of <0.8, but increased CI does not predict loss of position in these fractures. We therefore discourage the use of CI in proximal half forearm fractures.

  20. 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.

  1. [Developing a predictive model for the caregiver strain index].

    Science.gov (United States)

    Álvarez-Tello, Margarita; Casado-Mejía, Rosa; Praena-Fernández, Juan Manuel; Ortega-Calvo, Manuel

    Patient homecare with multiple morbidities is an increasingly common occurrence. The caregiver strain index is tool in the form of questionnaire that is designed to measure the perceived burden of those who care for their families. The aim of this study is to construct a diagnostic nomogram of informal caregiver burden using data from a predictive model. The model was drawn up using binary logistic regression and the questionnaire items as dichotomous factors. The dependent variable was the final score obtained with the questionnaire but categorised in accordance with that in the literature. Scores between 0 and 6 were labelled as "no" (no caregiver stress) and at or greater than 7 as "yes". The version 3.1.1R statistical software was used. To construct confidence intervals for the ROC curve 2000 boot strap replicates were used. A sample of 67 caregivers was obtained. A diagnosing nomogram was made up with its calibration graph (Brier scaled = 0.686, Nagelkerke R2=0.791), and the corresponding ROC curve (area under the curve=0.962). The predictive model generated using binary logistic regression and the nomogram contain four items (1, 4, 5 and 9) of the questionnaire. R plotting functions allow a very good solution for validating a model like this. The area under the ROC curve (0.96; 95% CI: 0.994-0.941) achieves a high discriminative value. Calibration also shows high goodness of fit values, suggesting that it may be clinically useful in community nursing and geriatric establishments. Copyright © 2015 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.

  2. On impact of transport conditions on variability of the seasonal pollen index.

    Science.gov (United States)

    Sofiev, M

    2017-01-01

    This discussion paper reveals the contribution of pollen transport conditions to the inter-annual variability of the seasonal pollen index (SPI). This contribution is quantified as a sensitivity of the pollen model predictions to meteorological variability and is shown to be a noticeable addition to the SPI variability caused by plant reproduction cycles. A specially designed SILAM model re-analysis of pollen seasons 1980-2014 was performed, resulting in the 35 years of the SPI predictions over Europe, which was used to compute the SPI inter-annual variability. The current paper presents the results for birch and grass. Throughout the re-analysis, the source term formulations and habitation maps were kept constant, which allowed attributing the obtained variability exclusively to the pollen release and transport conditions during the flowering seasons. It is shown that the effect is substantial: it amounts to 10-20% (grass) and 20-40% (birch) of the observed SPI year-to-year changes reported in the literature. The phenomenon has well-pronounced spatial- and species-specific patterns. The findings were compared with observation-based statistical models for the SPI prediction, showing that such models highlight the same processes as the analysis with the SILAM model.

  3. Climate variability and predictability in Northwest Africa

    Science.gov (United States)

    Baddour, O.; Djellouli, Y.

    2003-04-01

    Northwest Africa defined here as the area including Morocco, Algeria and Tunisia, occupies a large territory in North Africa with an area exceeding 3.5 million km2. The geographical contrast is very important: while most of the southern part is desert, the northern and northwestern parts exhibit a contrasting geography including large flat areas in the western part of Morocco, northern Algeria and eastern part of Tunisia and the formidable Atlas mountains barrier extends from south west of Morocco toward north west of Tunisia crossing central Morocco and north Algeria. Agriculture is one of major socio-economic activities in the region with an extensive cash-crop for exporting to Europe especially from Morocco and Tunisia. The influence of the recurring droughts during the 80s and 90s was very crucial for the economic and societal aspects of the region. In Morocco, severe droughts have caused GDP fluctuation within past 20 years from 10% increase down to negative values in some particular years. Recent studies have investigated seasonal rainfall variability and prediction over MOROCCO in the framework of regional and international collaboration. Results from this work has shown that the main general circulation feature associated with the rainfall variability within Morocco is the North Atlantic Oscillation. The relationship is in fact due to the major role played by the AZORES high pressure with its role in modulating the main position of the active synoptic systems in the north Atlantic area and therefore in modulating the frequency and the intensity of the weather systems that impact the western part of the region. Mediterranean sea plays also major role in the mid of the region. In this paper we applied EOF technique on 500 hPa. The data used are monthly reanalysis NCEP/NCAR analyses for November from 1960 to 1990 climatological time series. Correlation analysis is then performed between EOF time series and global 4x4 degre SST anomalies. The results we

  4. Psoriasis disability index: The role of sociodemographic and clinical variables

    Directory of Open Access Journals (Sweden)

    Şebnem Aktan

    2014-12-01

    Full Text Available Background and Design: A variety of studies have demonstrated that psoriasis can affect psychological, social and physical functions. The purpose of this study was to determine the impact of the sociodemographic and clinical characteristics on Psoriasis Disability Index (PDI, which is a psoriasis-specific health-related quality of life instrument. Materials and Methods: A total of 70 patients with psoriasis were included in this study and sociodemographic features of the patients, psoriasis area severity index scores evaluated by physician and patient (PASI and SAPASI and the presence of subjective symptoms associated with psoriasis were recorded. In addition, the patients were asked to complete a questionnaire (PDI consisting of a series of 15 questions related to daily activities, work/school, personal relationships, leisure and treatment, dealing with the past four weeks. Correlations between PDI and its subscale scores with sociodemographic and clinical features were analyzed. Results: There were statistically significant positive correlations between mean PDI scores and both of mean PASI and SAPASI scores. Activities of leisure and work/school were found to be more effected in men than in women. PDI and daily activities, personal, work/school and/or leisure activities were also detected to be more effected in patients with cosmetic involvement, severe psoriasis, long duration of disease (≥10 years and young age of onset. In addition, in patients with subjective symptoms, such as pruritus, muscle pain and fatigue, personal relations, daily and work/school activities were found to be negatively affected. Conclusion: In this study, mean PDI scores correlated significantly both with clinical severity and sociodemographic variables. Nevertheless, we assume that addition of questions examining quality of life related to subjective symptoms such as pruritus would be appropriate.

  5. Modeling Using Dryness Index to Predict Evapotranspiration in a ...

    African Journals Online (AJOL)

    Based on crop-climate studies from the viewpoint of modeling and predictability, this paper presents a new dryness index (DI), the ratio of rainfall over reference evapotranspiration (ET), for Ilorin (8.48o N) in the transition zone between humid and semi-arid climatic belts in Nigeria. The ET values were computed using the ...

  6. Binaural intelligibility prediction based on the speech transmission index

    NARCIS (Netherlands)

    Wijngaarden, S.J. van; Drullman, R.

    2008-01-01

    Although the speech transmission index STI is a well-accepted and standardized method for objective prediction of speech intelligibility in a wide range of environments and applications, it is essentially a monaural model. Advantages of binaural hearing in speech intelligibility are disregarded. In

  7. 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...

  8. Indian monsoon variability in relation to Regional Pressure Index

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Indian Institute of Tropical Meteorology, Pune 411 008, India. In this paper Regional Pressure Index (RPI) over the Indian region (20◦N–40◦N and ... zonal index cycle in Northern Hemisphere (NH) and Southern Hemisphere (SH). But in spite of these zonal indices the Regional Pressure Index. (RPI) may play quite a ...

  9. 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.

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

    Science.gov (United States)

    Inthachot, Montri; 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.

  11. The Role of Predictability in Intonational Variability.

    Science.gov (United States)

    Turnbull, Rory

    2017-03-01

    Predictability is known to affect many properties of speech production. In particular, it has been observed that highly predictable elements (words, syllables) are produced with less phonetic prominence (shorter duration, less peripheral vowels) than less predictable elements. This tendency has been proposed to be a general property of language. This paper examines whether predictability is correlated with fundamental frequency (F0) production, through analysis of experimental corpora of American English. Predictability was variously defined as discourse mention, utterance probability, and semantic focus. The results revealed consistent effects of utterance probability and semantic focus on F0, in the expected direction: less predictable words were produced with a higher F0 than more predictable words. However, no effect of discourse mention was observed. These results provide further empirical support for the generalization that phonetic prominence is inversely related to linguistic predictability. In addition, the divergent results for different predictability measures suggests that the parameterization of predictability within a particular experimental design can have significant impact on the interpretation of results, and that it cannot be assumed that two measures necessarily reflect the same cognitive reality.

  12. [Predictive mortality value of the peritonitis index of Mannheim].

    Science.gov (United States)

    Barrera Melgarejo, Elizabeth; Rodríguez Castro, Manuel; Borda Luque, Giuliano; Najar Trujillo, Néstor

    2010-01-01

    To determine the predictive value of the index of peritonitis of Mannheim in patients with peritonitis in the Hospital Nacional Cayetano Heredia. A prospective study appears, of 103 patients, greater of 14 years, with I diagnose of peritonitis, between November 2004 to April 2005. For its analysis I am used the square test of chi with coefficient of Pearson, and the test of T of student. For the analysis of the data two modalities were used, the first patients were divided in 3 groups, according to the value of the index of Mannheim, 29, and in 2 groups, d 26 and > 26 points. I am made considered of survival of Kaplan the Meier, using statistical program STATA 8.0 a mortality of 50% in patients with greater index of 26 points was obtained. One was a sensitivity 95.9%, a specificity of 80%, with positive a predictive value 98.9% and a negative predictive value of 50%. When considering 3 groups, 29 points, was a mortality of 60% in patients with greater index of 29. I am made a survival curve obtaining itself a significant difference with a p=0, 0098. Figure 2. We found that the classification in 3 groups presents statistically significant difference, reason why recommended its use for the evaluation and beginning of aggressive measures.

  13. Predictive Validity of the Expanded Susceptibility to Smoke Index.

    Science.gov (United States)

    Strong, David R; Hartman, Sheri J; Nodora, Jesse; Messer, Karen; James, Lisa; White, Martha; Portnoy, David B; Choiniere, Conrad J; Vullo, Genevieve C; Pierce, John

    2015-07-01

    The susceptibility to smoking index can be improved as it only identifies one third of future adult smokers. Adding curiosity to this index may increase the identification of future smokers and improve the identification of effective prevention messages. Analyses used data from the California Longitudinal Study of Smoking Transitions in Youth, for whom tobacco use behaviors, attitudes, and beliefs were assessed at 3 time points from age 12 through early adulthood. Logistic regressions were used to evaluate whether baseline curiosity about smoking was predictive of smoking during the 6-year follow-up period and whether curiosity about smoking provided evidence of incremental validity over existing measures of susceptibility to smoking. Compared to those who were classified as definitely not curious about smoking, teens who were classified as probably not curious (OR adj = 1.90, 95% CI = 1.28-2.81) and those classified as definitely curious (OR adj = 2.38, 95% CI= 1.49-3.79) had an increase in the odds of becoming a young adult smoker. Adding curiosity to the original susceptibility to smoking index increased the sensitivity of the enhanced susceptibility index to 78.9% compared to 62.2% identified by the original susceptibility index. However, a loss of specificity meant there was no improvement in the positive predictive value. The enhanced susceptibility index significantly improves identification of teens at risk for becoming young adult smokers. Thus, this enhanced index is preferred for identifying and testing potentially effective prevention messages. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  14. Lymphatic invasion and the Shields index in predicting melanoma metastases.

    Science.gov (United States)

    Špirić, Zorica; Erić, Mirela; Eri, Živka

    2017-11-01

    Findings of the prognostic significance of lymphatic invasion are contradictory. To determine an as efficient cutaneous melanoma metastasis predictor as possible, Shields et al. created a new prognostic index. This study aimed to examine whether the lymphatic invasion analysis and the Shields index calculation can be used in predicting lymph node status in patients with cutaneous melanoma. Lymphatic invasion of 100 melanoma specimens was detected by dual immunohistochemistry staining for the lymphatic endothelial marker D2-40 and melanoma cell S-100 protein. The Shields index was calculated as a logarithm by multiplying the melanoma thickness, square of peritumoural lymphatic vessel density and the number "2" for the present lymphatic invasion. No statistically significant difference was observed between lymph node metastatic and nonmetastatic melanomas regarding the lymphatic invasion. Metastatic melanomas showed a significantly higher Shields index value than nonmetastatic melanomas (p = 0.00). Area under the receiver operator characteristic (ROC) curve (AUC) proved that the Shields index (AUC = 0.86, 95% confidence interval (CI) 0.79-0.93, p = 0.00) was the most accurate predictor of lymph node status, followed by the melanoma thickness (AUC = 0.76, 95% CI 0.67-0.86, p = 0.00) and American Joint Committee on Cancer (AJCC) staging (AUC = 0.75, 95% CI 0.66-0.85, p = 0.00), while lymphatic invasion was not successful in predicting (AUC = 0.56, 95% CI 0.45-0.67, p = 0.31). The Shields index achieved 81.3% sensitivity and 75% specificity (cut-off mean value). Our findings show that D2-40/S-100 immunohistochemical analysis of lymphatic invasion cannot be used for predicting the lymph node status, while the Shields index calculation predicts disease outcome more accurately than the melanoma thickness and AJCC staging. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights

  15. Evaluation of the Gini-index for Studying Branch Prediction Features

    Science.gov (United States)

    Desmet, Veerle; Eeckhout, Lieven; De Bosschere, Koen

    2004-08-01

    Predicting future outcomes based on past observational data is a common application in data mining. While the primary goal is usually to achieve the highest possible prediction accuracy, the interpretation of the resulting prediction model is important to understand its shortcomings for further improvements. Throughout this paper we focus on branch prediction, where the (binary) outcome of a test is needed for enhancing the performance of pipelined computer architectures. Many research has been done in this domain and different branch prediction solutions are described in the literature. The quality of a prediction model is highly dependent on the quality of the available data. Especially the choice of the related variables or features to base the prediction on is important. In this paper we evaluate the predictive power of different branch prediction features using the metric Gini-index, which is used as feature selection measure in the construction of decision trees. We observe that through this Gini-metric an explanation can be provided for the performance of existing branch predictors. We show that the Gini-index is a good metric for comparing branch prediction features. Further, we found that a feature can have good discriminative capacities, although this does not result in very good accuracies because of shortcomings in the predictor implementation.

  16. A Geographically Variable Water Quality Index Used in Oregon.

    Science.gov (United States)

    Dunnette, D. A.

    1979-01-01

    Discusses the procedure developed in Oregon to formulate a valid water quality index which accounts for the specific conditions in the water body of interest. Parameters selected include oxygen depletion, BOD, eutrophication, dissolved substances, health hazards, and physical characteristics. (CS)

  17. Predicting multiyear North Atlantic Ocean variability

    NARCIS (Netherlands)

    Hazeleger, W.; Wouters, B.; Oldenborgh, van G.J.; Corti, S.; Palmer, T.; Lloyd Smith, D.; Dunstone, N.; Kroger, J.; Pohlmann, H.; Storch, von J.S.

    2013-01-01

    We assess the skill of retrospective multiyear forecasts of North Atlantic ocean characteristics obtained with ocean-atmosphere-sea ice models that are initialized with estimates from the observed ocean state. We show that these multimodel forecasts can skilfully predict surface and subsurface ocean

  18. Combining SNPs in latent variables to improve genomic prediction

    DEFF Research Database (Denmark)

    Heuven, Henri C M; Rosa, G J M; Janss, Luc

    The objective of this study was to develop and test hierarchical genomic models with latent variables that represent parts of the genomic values. An interaction model and a chromosome model were compared with a model based on variable selection in a simulated and real dataset. The program Bayz......: Hierarchical genetic model; Predictive value; Gibbs sampling; Variable selection....

  19. Predicting and characterizing data sequences from structure-variable systems

    CERN Document Server

    Fangi, H P

    1995-01-01

    Abstract: In principle, all the natural systems such as biological, ecological and economical systems are structure-variable systems (in which some environment parameters are not fixed). In this Letter we show that data sequences from many structure-variable systems are short-term predictable. We also argue how to characterize the data sequences from structure-variable systems.

  20. Crown fuel spatial variability and predictability of fire spread

    Science.gov (United States)

    Russell A. Parsons; Jeremy Sauer; Rodman R. Linn

    2010-01-01

    Fire behavior predictions, as well as measures of uncertainty in those predictions, are essential in operational and strategic fire management decisions. While it is becoming common practice to assess uncertainty in fire behavior predictions arising from variability in weather inputs, uncertainty arising from the fire models themselves is difficult to assess. This is...

  1. 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

    2017-09-01

    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.

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

    Science.gov (United States)

    Yahya, M; Saghir, M Z

    2016-02-21

    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.

  3. Field potential soil variability index to identify precision agriculture opportunity

    Science.gov (United States)

    Precision agriculture (PA) technologies used for identifying and managing within-field variability are not widely used despite decades of advancement. Technological innovations in agronomic tools, such as canopy reflectance or electrical conductivity sensors, have created opportunities to achieve a ...

  4. 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.

  5. Prediction of ATLS hypovolemic shock class in rats using the perfusion index and lactate concentration.

    Science.gov (United States)

    Choi, Soo Beom; Park, Jee Soo; Chung, Jai Won; Kim, Sung Woo; Kim, Deok Won

    2015-04-01

    It is necessary to quickly and accurately determine Advanced Trauma Life Support (ATLS) hemorrhagic shock class for triage in cases of acute hemorrhage caused by trauma. However, the ATLS classification has limitations, namely, with regard to primary vital signs. This study identified the optimal variables for appropriate triage of hemorrhage severity, including the peripheral perfusion index and serum lactate concentration in addition to the conventional primary vital signs. To predict the four ATLS classes, three popular machine learning algorithms with four feature selection methods for multicategory classification were applied to a rat model of acute hemorrhage. A total of 78 anesthetized rats were divided into four groups for ATLS classification based on blood loss (in percent). The support vector machine one-versus-one model with the Kruskal-Wallis feature selection method performed best, with 80.8% accuracy, relative classifier information of 0.629, and a kappa index of 0.732. The new hemorrhage-induced severity index (lactate concentration/perfusion index), diastolic blood pressure, mean arterial pressure, and the perfusion index were selected as the optimal variables for predicting the four ATLS classes by support vector machine one-versus-one with the Kruskal-Wallis method. These four variables were also selected for binary classification to predict ATLS classes I and II versus III and IV for blood transfusion requirement. The suggested ATLS classification system would be helpful to first responders by indicating the severity of patients, allowing physicians to prepare suitable resuscitation before hospital arrival, which could hasten treatment initiation.

  6. 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.

  7. 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.

  8. Apoptotic index for prediction of postmolar gestational trophoblastic neoplasia.

    Science.gov (United States)

    Braga, Antonio; Maestá, Izildinha; Rocha Soares, Renan; Elias, Kevin M; Custódio Domingues, Maria Aparecida; Barbisan, Luis Fernando; Berkowitz, Ross S

    2016-09-01

    Although 85% of patients with a complete hydatidiform mole achieve spontaneous remission after a few months, 15% of them will experience gestational trophoblastic neoplasia, which requires chemotherapy. To date, there is no biomarker to predict post-molar gestational trophoblastic neoplasia before the initiation of human chorionic gonadotropin surveillance. The purpose of this study was to assess the relationship between the expression of apoptosis markers in the molar villous trophoblasts and the subsequent development of gestational trophoblastic neoplasia after the evacuation of a complete hydatidiform mole. This was a retrospective cohort study of patients with complete hydatidiform mole who were diagnosed, treated, and followed at the Center of Trophoblastic Diseases (Botucatu/São Paulo State and Rio de Janeiro/Rio de Janeiro State, Brazil) from 1995-2014. Patients were divided temporally into derivation (1995-2004) and validation (2005-2014) cohorts. Immunohistochemistry was used to examine tissue expression of the apoptosis inhibitor survivin or the pro-apoptotic enzyme caspase-3. Survivin stains for cytoplasmic and nuclear expression were evaluated independently. Caspase-3 expression was measured as an apoptotic index of positive staining cells over negative staining cells multiplied by 100. Receiver operating characteristic curves were then constructed, and the area under the curve was calculated to test the performance characteristics of the staining to predict the subsequent development of gestational trophoblastic neoplasia. The final study population comprised 780 patients, with 390 patients in each temporal cohort: 590 patients entered spontaneous remission, and 190 patients experienced post-molar gestational trophoblastic neoplasia. Neither nuclear nor cytoplasmic survivin expression performed well as a predictor of subsequent gestational trophoblastic neoplasia. The caspase-3 apoptotic index was a strong risk factor for subsequent gestational

  9. Indian monsoon variability in relation to Regional Pressure Index

    Indian Academy of Sciences (India)

    In this paper Regional Pressure Index (RPI) over the Indian region (20°N-40°N and 70°E-85°E) has been constructed for 101 years (1899-1999) on a monthly scale. The relationship of these indices was carried out with the Indian Summer Monsoon Rainfall (June-September) (ISMR) over the various homogeneous regions, ...

  10. Prediction of Line Voltage Stability Index Using Supervised Learning

    Directory of Open Access Journals (Sweden)

    Ankit Kumar Sharma

    2017-12-01

    Full Text Available In deregulated environment, stability issues have become dominant. Reliability of the power is essential for successful operation of the power system. Often high and dynamic loading conditions present new challenges in terms of decision of the control strategies to the system operator at energy management centre. For the achievement of voltage stability, identification of weak buses is very important. Line stability indices are important predictors of the weak buses in the over loaded system. Identification of the weak buses is the first step of control strategy. This paper presents an effective methodology based on Artificial Neural Network (ANN to predict the Fast Voltage Stability Index (FVSI. Comparative analysis of different topologies of ANN is carried out based on the capability of the prediction of FVSI. Results are validated through offline Newton Raphson (NR simulation method. The proposed methodology is tested over IEEE-14 and IEEE-30 test bus System.

  11. Genetically Predicted Body Mass Index and Breast Cancer Risk

    DEFF Research Database (Denmark)

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

    2016-01-01

    is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons......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 environmental factors. METHODS: We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated...

  12. 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.......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...

  13. Development of the Adherence Predictive Index (API for Medication Taking

    Directory of Open Access Journals (Sweden)

    Jon C Schommer

    2016-03-01

    Full Text Available The objective for this study was to explore if characteristics of personality type using the Preferred Communication Style Questionnaire, in concert with the demographic characteristics of age, education, and race/ethnicity, are associated with, and help predict, individuals’ medication adherence behavior. Data were collected via an on-line survey, sent to a sample of adults residing in the United States, between April 28 and June 22, 2015. Out of 26,173 responses to the survey, 16,736 reported taking one or more medications and were eligible for inclusion in this study. The development of the Adherence Predictive Index (API used mean Morisky Medication Adherence Scale (MMAS-8 scores for each of eight personality types as a starting point. API scores were calculated by adding or subtracting specific values to each group’s mean MMAS-8 score based on personality type, age, education and race/ethnicity characteristics which were demonstrated to have significant effects on adherence. The weighting system was informed by linear regression, logistic regression, personality type literature, researcher experience, and previous qualitative and quantitative research. The resultant score was converted to an API score that ranged from 1 to 5 so that it would be feasible for health care providers to understand and use. The findings showed that an Adherence Predictive Index (API could be developed based upon a relatively small number of questions that focus on personality type and generational, educational, and cultural experiences. It was developed in order to be a component of a comprehensive program that has the goals of (1 identifying and describing specific behavioral strategies individuals are most likely to successfully employ, (2 motivating patients by using their preferred communication style, and (3 predicting each patient’s propensity to adhere. Future research is needed to evaluate the index’s validity, sensitivity, and effectiveness in

  14. Variables affecting darbepoetin resistance index in hemodialysis patients

    Directory of Open Access Journals (Sweden)

    Fayez Hejaili

    2017-01-01

    Full Text Available Erythropoietin resistance index calculation has been used as a tool to evaluate anemia response to erythropoietin therapy. Very little has been reported in its use when using darbepoetin and factors influencing in Arab patients. Darbepoetin resistance index (DRI was calculated in all our patients using darbepoetin. This was correlated to demographic, clinical, and laboratory parameters. Of the 250 patients, 40.4% were diabetic, 71.1% on hemodialysis, and 28.6% on hemodiafiltration, 23.9% with PermCaths (PC, and 76.1 % with arteriovenous fistula (AVF. The mean DRI was 10.96 ± 12.9 I. Females had 45% higher DRI than males (P = 0.005, and patients with PC had a 66% higher DRI than those with AVF (P = 0.029. Patients with Vitamin D level below the 50th percentile had 55.9% higher DRI than those above it (P = 0.05. DRI was negatively correlated with age (P = 0.018, dialysis vintage (P = 0.039, interdialytic weight gain P = 0.007, Vitamin D level, and serum albumin (P = 0.005 and positively correlate with parathyroid hormone (PTH level (P = 0.000. No impact was seen by the mode of dialysis, being diabetic, using anti-hypertensive therapy, body mass index, Kt/V, serum iron, total iron binding capacity, transferrin saturation, ferritin, C-reactive protein, Ca, or P. DRI in our Arab patients was comparable to erythropoietin resistance indices reported in other communities. Higher DRI was observed in females, PC users, lower serum albumin, lower Vitamin D, and shorter dialysis vintage. A negative correlation existed between DRI and age, dialysis vintage, interdialytic weight, and serum albumin and a positive correlation with PTH level.

  15. 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.

  16. 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 ...

  17. Variability of the Atlantic Forest based on the EVI index and climate variables in Cunha-SP, Brazil

    Directory of Open Access Journals (Sweden)

    Marianna Fernandes Santana

    2016-08-01

    Full Text Available The aim of this study was to evaluate the variability of the Atlantic Forest in the municipality of Cunha-SP, Brazil, based EVI index (Enhanced Vegetation Index and climatic variables (air temperature and rainfall. Images of MOD13Q1 product from MODIS sensor, which represent the index EVI were used. The descriptive statistics and multiple were applied to climate variables and EVI for the cycle 2007/2008 (strong La Niña event. The lowest average values of the rain were found for 2008 (171.60 mm, while the highest average rainfall was found for 2007 (187.02 mm. The vegetation behaved in a manner contrary, where the lowest average EVI index was found for 2007 (0.38, already 2008 had the highest rate (0.46, respectively. The coefficient of determination between the rainfall and the EVI in 2007 (R² = 0.43 higher than in 2008 (R² = 0.12, followed by correlation indexes in 2007 (r = 0.65 and 2008 (r = 0.34. However, both indexes were low, except correlation index in 2007. In the multiple regression analysis for the year 2007 obtained 87% correlation, while in 2008 only 27%. There is no correlation between vegetation and air temperature.

  18. The acrosome index, radical buffer capacity and number of isolated progressively motile spermatozoa predict IVF results.

    Science.gov (United States)

    Rhemrev, J P; Menkveld, R; Roseboom, T J; van Overveld, F W; Teerlink, T; Lombard, C; Vermeiden, J P

    2001-09-01

    The accuracy by which a number of newly described semen variables can predict either total fertilization failure (TFF) or pregnancy outcome in IVF, has not previously been investigated. The study aim was, therefore, to determine prospectively the predictive value of these variables. The semen variables investigated were the post-wash total progressively motile sperm cell count (TPMC(post-wash)), the acrosome index (AI), 'cytoplasmic residues' and normal sperm morphology, evaluated according to the strict criteria ('strict criteria'), as well as the fast and slow total radical trapping antioxidant potential ('fast TRAP' and 'slow TRAP' respectively). The study group (n = 87) showed a mean (+/- SD) number of 10.2 +/- SD retrieved oocytes, 12.6% TFF, a mean fertilization rate of 59.7% and a pregnancy rate of 19.5% (17/87). TFF was significantly predicted by TPMC(post-wash), 'strict criteria', AI and 'cytoplasmic residues' (all P < 0.05). The outcome after embryo transfer was significantly predicted by AI and 'fast TRAP'. Semen samples with an AI <5% and a 'fast TRAP' <1.14 mmol/l in particular did not result in any pregnancies after IVF-embryo transfer. Of all the measured and calculated semen variables, TPMC(post-wash) was the best predictor of TFF, whilst AI and 'fast TRAP' were the best predictors of pregnancy after IVF.

  19. 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.

  20. 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 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...... that at short and mid-range horizons Lettau and Ludvigson's (2001a) consumption-aggregate wealth variable offers the strongest forecasting ability, although this variable's predictive ability is sensitive to the sample period chosen. At longer horizons, price-normalized variables such as the traditional price...

  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. Childhood body mass index trajectories predicting cardiovascular risk in adolescence.

    Science.gov (United States)

    Boyer, Brittany P; Nelson, Jackie A; Holub, Shayla C

    2015-06-01

    The present study compared growth parameters of girls' and boys' body mass index (BMI) trajectories from infancy to middle childhood and evaluated these parameters as predictors of cardiovascular disease (CVD) risk in adolescence. Using 657 children from the NICHD Study of Early Child Care and Youth Development, quadratic growth curve analyses were conducted to establish growth parameters (intercept, slope, and quadratic term) for girls and boys from age 15 months to 10.5 years. Parameters were compared across gender and evaluated as predictors of a CVD risk index at the age of 15 years, controlling for characteristics of the adiposity rebound (AR) including age at which it occurred and children's BMI at the rebound. Boys had more extreme trajectories of growth than girls with higher initial BMI at age 15 months (intercept), more rapid declines in BMI before the AR (slope), and sharper rebound growth in BMI after the rebound (quadratic term). For boys and girls, higher intercept, slope, and quadratic term values predicted higher CVD risk at the age of 15 years, controlling for characteristics of the AR. Findings suggest that individuals at risk for developing CVD later in life may be identified before the AR by elevated BMI at 15 months and slow BMI declines. Because of the importance of early intervention in altering lifelong health trajectories, consistent BMI monitoring is essential in identifying high-risk children. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  3. Using Baidu Search Index to Predict Dengue Outbreak in China

    Science.gov (United States)

    Liu, Kangkang; Wang, Tao; Yang, Zhicong; Huang, Xiaodong; Milinovich, Gabriel J.; Lu, Yi; Jing, Qinlong; Xia, Yao; Zhao, Zhengyang; Yang, Yang; Tong, Shilu; Hu, Wenbiao; Lu, Jiahai

    2016-12-01

    This study identified the possible threshold to predict dengue fever (DF) outbreaks using Baidu Search Index (BSI). Time-series classification and regression tree models based on BSI were used to develop a predictive model for DF outbreak in Guangzhou and Zhongshan, China. In the regression tree models, the mean autochthonous DF incidence rate increased approximately 30-fold in Guangzhou when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 382. When the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 91.8, there was approximately 9-fold increase of the mean autochthonous DF incidence rate in Zhongshan. In the classification tree models, the results showed that when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 99.3, there was 89.28% chance of DF outbreak in Guangzhou, while, in Zhongshan, when the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 68.1, the chance of DF outbreak rose up to 100%. The study indicated that less cost internet-based surveillance systems can be the valuable complement to traditional DF surveillance in China.

  4. A two-county comparison of the HOUSES index on predicting self-rated health.

    Science.gov (United States)

    Butterfield, Michael C; Williams, Arthur R; Beebe, Tim; Finnie, Dawn; Liu, Heshan; Liesinger, Juliette; Sloan, Jeff; Wheeler, Philip H; Yawn, Barbara; Juhn, Young J

    2011-03-01

    Mortality, incidence of most diseases, and prevalence of adverse health behaviours follow an inverse gradient with social class. Many proxies for socioeconomic status (SES) exist; however, each bears a different relation to health outcomes, probably following a different aetiological pathway. Additionally, data on SES can be quite difficult to gather. Five measures of SES were compared, including a novel measure, the HOUSES index, in the prediction of self-rated health (SRH) in two Midwestern settings, Olmsted County, Minnesota, and Jackson County, Missouri. Using a probability sampling design, a cross-sectional telephone survey was administered to a randomised sample of households. The questionnaire collected a variety of sociodemographic and personal health information. The dependent variable, SRH, was dichotomised into excellent/very good/good versus fair/poor health. Information for the HOUSES index was collected through public property records and corroborated through the telephone questionnaire. Participants were parents/guardians of children aged 1-17 residing in Olmsted County (n = 746) and Jackson County (n = 704). The HOUSES index was associated with adverse SRH in Jackson County adults. All five SES measures were significant predictors in this group. Composite SES indices showed significant associations with SRH in Olmsted County adults. The HOUSES index makes a unique contribution to the measurement of SES and prediction of health outcomes. Its utility is qualified by specific social contexts, and it should be used in concert with other SES indices.

  5. Predictive Variables of Half-Marathon Performance for Male Runners.

    Science.gov (United States)

    Gómez-Molina, Josué; Ogueta-Alday, Ana; Camara, Jesus; Stickley, Christoper; Rodríguez-Marroyo, José A; García-López, Juan

    2017-06-01

    The aims of this study were to establish and validate various predictive equations of half-marathon performance. Seventy-eight half-marathon male runners participated in two different phases. Phase 1 (n = 48) was used to establish the equations for estimating half-marathon performance, and Phase 2 (n = 30) to validate these equations. Apart from half-marathon performance, training-related and anthropometric variables were recorded, and an incremental test on a treadmill was performed, in which physiological (VO2max, speed at the anaerobic threshold, peak speed) and biomechanical variables (contact and flight times, step length and step rate) were registered. In Phase 1, half-marathon performance could be predicted to 90.3% by variables related to training and anthropometry (Equation 1), 94.9% by physiological variables (Equation 2), 93.7% by biomechanical parameters (Equation 3) and 96.2% by a general equation (Equation 4). Using these equations, in Phase 2 the predicted time was significantly correlated with performance (r = 0.78, 0.92, 0.90 and 0.95, respectively). The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners, considered from different approaches. Furthermore, they improved the prediction performance of previous studies, which makes them a highly practical application in the field of training and performance.

  6. Predictive Variables of Half-Marathon Performance for Male Runners

    Directory of Open Access Journals (Sweden)

    Josué Gómez-Molina, Ana Ogueta-Alday, Jesus Camara, Christoper Stickley, José A. Rodríguez-Marroyo, Juan García-López

    2017-06-01

    Full Text Available The aims of this study were to establish and validate various predictive equations of half-marathon performance. Seventy-eight half-marathon male runners participated in two different phases. Phase 1 (n = 48 was used to establish the equations for estimating half-marathon performance, and Phase 2 (n = 30 to validate these equations. Apart from half-marathon performance, training-related and anthropometric variables were recorded, and an incremental test on a treadmill was performed, in which physiological (VO2max, speed at the anaerobic threshold, peak speed and biomechanical variables (contact and flight times, step length and step rate were registered. In Phase 1, half-marathon performance could be predicted to 90.3% by variables related to training and anthropometry (Equation 1, 94.9% by physiological variables (Equation 2, 93.7% by biomechanical parameters (Equation 3 and 96.2% by a general equation (Equation 4. Using these equations, in Phase 2 the predicted time was significantly correlated with performance (r = 0.78, 0.92, 0.90 and 0.95, respectively. The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners, considered from different approaches. Furthermore, they improved the prediction performance of previous studies, which makes them a highly practical application in the field of training and performance.

  7. 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)

  8. Using the detectability index to predict P300 speller performance

    Science.gov (United States)

    Mainsah, B. O.; Collins, L. M.; Throckmorton, C. S.

    2016-12-01

    Objective. The P300 speller is a popular brain-computer interface (BCI) system that has been investigated as a potential communication alternative for individuals with severe neuromuscular limitations. To achieve acceptable accuracy levels for communication, the system requires repeated data measurements in a given signal condition to enhance the signal-to-noise ratio of elicited brain responses. These elicited brain responses, which are used as control signals, are embedded in noisy electroencephalography (EEG) data. The discriminability between target and non-target EEG responses defines a user’s performance with the system. A previous P300 speller model has been proposed to estimate system accuracy given a certain amount of data collection. However, the approach was limited to a static stopping algorithm, i.e. averaging over a fixed number of measurements, and the row-column paradigm. A generalized method that is also applicable to dynamic stopping (DS) algorithms and other stimulus paradigms is desirable. Approach. We developed a new probabilistic model-based approach to predicting BCI performance, where performance functions can be derived analytically or via Monte Carlo methods. Within this framework, we introduce a new model for the P300 speller with the Bayesian DS algorithm, by simplifying a multi-hypothesis to a binary hypothesis problem using the likelihood ratio test. Under a normality assumption, the performance functions for the Bayesian algorithm can be parameterized with the detectability index, a measure which quantifies the discriminability between target and non-target EEG responses. Main results. Simulations with synthetic and empirical data provided initial verification of the proposed method of estimating performance with Bayesian DS using the detectability index. Analysis of results from previous online studies validated the proposed method. Significance. The proposed method could serve as a useful tool to initially assess BCI performance

  9. 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.

  10. 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.

  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. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

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

    African Journals Online (AJOL)

    Erah

    ORIGINAL RESEARCH ARTICLE. Relative Contributions of Socio-Cultural Variables to the Prediction of Maternal Mortality in Edo South. Senatorial District, Nigeria. Chinwe Lucy Marchie, Francisca Chika Anyanwu. 2. ABSTRACT. The study examined the extent of contributions of socio-cultural factors to maternal mortality ( ...

  18. 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.

  19. Prediction of hemodynamic reactivity using dynamic variations of Analgesia/Nociception Index (∆ANI).

    Science.gov (United States)

    Boselli, E; Logier, R; Bouvet, L; Allaouchiche, B

    2016-12-01

    The Analgesia/Nociception Index (ANI), a 0-100 non-invasive index calculated from heart rate variability, reflects the analgesia/nociception balance during general anesthesia. We hypothesized that dynamic variations of ANI (∆ANI) would provide better performance than static values to predict hemodynamic reactivity during desflurane/remifentanil general anesthesia. One hundred and twenty-eight patients undergoing ear-nose-throat or lower limb orthopedic surgery were analyzed in this prospective observational study. The ANI, heart rate and systolic blood pressure were recorded before induction, at skin incision, during procedure and at emergence from general anesthesia. Changes in these variables were recorded after 1 min for ANI (ANI1min) and 5 min for heart rate and systolic blood pressure. The dynamic variation of ANI at the different time points was defined as: ∆ANI = (ANI1min - ANI)/([ANI + ANI1min]/2). Receiver-operating characteristic (ROC) curves were built to evaluate the performance of ANI, ANI1 min and ∆ANI to predict hemodynamic reactivity (increase by more than 20 % in heart rate and/or systolic blood pressure within 5 min). For the prediction of hemodynamic reactivity, better performance was observed with ∆ANI (area under ROC curve (AUC ROC) = 0.90) in comparison to ANI (ROC AUC = 0.50) and ANI1min (ROC AUC = 0.77). A ∆ANI threshold of -19 % predicts hemodynamic reactivity with 85 % [95 % CI 77-91] sensitivity and 85 % [95 % CI 81-89] specificity. Dynamic variations of ANI provide better performance than static values to predict hemodynamic reactivity during desflurane/remifentanil general anesthesia. These findings may be of interest for the individual adaptation of remifentanil doses guided by ∆ANI during general anesthesia, although this remains to be demonstrated.

  20. Binaural intelligibility prediction based on the speech transmission index.

    Science.gov (United States)

    van Wijngaarden, Sander J; Drullman, Rob

    2008-06-01

    Although the speech transmission index (STI) is a well-accepted and standardized method for objective prediction of speech intelligibility in a wide range of environments and applications, it is essentially a monaural model. Advantages of binaural hearing in speech intelligibility are disregarded. In specific conditions, this leads to considerable mismatches between subjective intelligibility and the STI. A binaural version of the STI was developed based on interaural cross correlograms, which shows a considerably improved correspondence with subjective intelligibility in dichotic listening conditions. The new binaural STI is designed to be a relatively simple model, which adds only few parameters to the original standardized STI and changes none of the existing model parameters. For monaural conditions, the outcome is identical to the standardized STI. The new model was validated on a set of 39 dichotic listening conditions, featuring anechoic, classroom, listening room, and strongly echoic environments. For these 39 conditions, speech intelligibility [consonant-vowel-consonant (CVC) word score] and binaural STI were measured. On the basis of these conditions, the relation between binaural STI and CVC word scores closely matches the STI reference curve (standardized relation between STI and CVC word score) for monaural listening. A better-ear STI appears to perform quite well in relation to the binaural STI model; the monaural STI performs poorly in these cases.

  1. 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.

  2. Chinese Stock Index Futures Price Fluctuation Analysis and Prediction Based on Complementary Ensemble Empirical Mode Decomposition

    National Research Council Canada - National Science Library

    Chen, Ruoyang; Pan, Bin

    2016-01-01

      Since the CSI 300 index futures officially began trading on April 15, 2010, analysis and predictions of the price fluctuations of Chinese stock index futures prices have become a popular area of active research...

  3. Utilizing the AAVSO's Variable Star Index (VSX) in Undergraduate Research Projects (Poster abstract)

    Science.gov (United States)

    Larsen, K.

    2016-12-01

    (Abstract only) Among the many important services that the American Association of Variable Star Observers (AAVSO) provides to the astronomical community is the Variable Star Index (VSX; https://www.aavso.org/vsx/). This online catalog of variable stars is the repository of data on over 334,000 variable stars, including information on spectral type, range of magnitude, period, and type of variable, among other properties. A number of these stars were identified as being variable through automated telescope surveys, such as ASAS (All Sky Automated Survey). The computer code of this survey classified newly discovered variables as best it could, but a significant number of false classifications have been noted. The reclassification of ASAS variables in the VSX data, as well as a closer look at variables identified as miscellaneous type in VSX, are two of many projects that can be undertaken by interested undergraduates. In doing so, students learn about the physical properties of various types of variable stars as well as statistical analysis and computer software, especially the vstar variable star data visualization and analysis tool that is available to the astronomical community free of charge on the AAVSO website (https://www.aavso.org/vstar-overview). Three such projects are described in this presentation, to identify BY Draconis variables misidentified as Cepheids or "miscellaneous", and SRD semiregular variables and ELL (rotating ellipsoidal) variables misidentified as "miscellaneous", in ASAS data and VSX.

  4. 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.

  5. 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......, and gain of 1.3 percentage points was achieved by combining information of genotyped and nongenotyped bulls simultaneously applying the one-step blending. These results indicate that genomic selection can greatly improve the accuracy of preselection for young bulls in Nordic Red population, and the one...... of which 4,408 bulls were genotyped using Illumina Bovine SNP50 BeadChip (Illumina, San Diego, CA). To validate reliability of genomic predictions, about 20% of the youngest genotyped bulls were taken as test data set. Deregressed proofs (DRP) were used as response variables for genomic predictions...

  6. Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office

    Energy Technology Data Exchange (ETDEWEB)

    Ng, K.C. [Department of Research and Applications, O.Y.L. R and D Center, Lot 4739, Jalan BRP 8/2, Taman Bukit Rahman Putra, 47000, Sungai Buloh, Selangor Darul Ehsan (Malaysia); Kadirgama, K. [Department of Mechanical Engineering, Universiti Tenaga Nasional, Km. 7, Jalan Kajang-Puchong, 43009 Kajang, Selangor Darul Ehsan (Malaysia); Ng, E.Y.K. [School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798 (Singapore)

    2008-07-01

    Based on the Response Surface Methodology (RSM), the development of first- and second-order models for predicting the Air Diffusion Performance Index (ADPI) in a displacement-ventilated office is presented. By adopting the technique of Computational Fluid Dynamics (CFD), the new ADPI models developed are used to investigate the effect of simultaneous variation of three design variables in a displacement ventilation case, i.e. location of the displacement diffuser (L{sub dd}), supply temperature (T) and exhaust position (L{sub ex}) on the comfort parameter ADPI. The RSM analyses are carried out with the aid of a statistical software package MINITAB. In the current study, the separate effect of individual design variable as well as the second-order interactions between these variables, are investigated. Based on the variance analyses of both the first- and second-order RSM models, the most influential design variable is the supply temperature. In addition, it is found that the interactions of supply temperature with other design variables are insignificant, as deduced from the second-order RSM model. The optimised ADPI value is subsequently obtained from the model equations. (author)

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

    Science.gov (United States)

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

    2017-11-01

    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).

  8. Characterization of spatial variability of the relative chlorophyll index in wheat crop

    Directory of Open Access Journals (Sweden)

    Osmar Henrique de Castro Pias

    2014-09-01

    Full Text Available Site-specific nitrogen application, based on relative chlorophyll index from leaves, may provide many economic and environmental benefits, however, the knowledge on sampling methodologies is still incipient. Thus, this study aimed to evaluate the use of different sampling grids to characterize the spatial variability of relative chlorophyll index of leaves from wheat crop and elaborate thematic maps for site-specific nitrogen application. For determining the relative chlorophyll index, a CFL 1030 chlorophyll meter was used on a regular sampling grid of 10 m x 10 m with 472 sampling points. Based on the initial sampling grid, by using the point elimination method, the simulation was performed in the following sampling grids: 10 m x 20 m; 20 m x 20 m; 20 m x 30 m; 30 m x 30 m; 30 m x 40 m; and 40 m x 40 m. The increase of the sampling grid reduced the diagnostic accuracy of relative chlorophyll index in wheat leaves. As the sampling grid increased, the maps became more general and information on the spatial variability of the relative chlorophyll index were lost. Sampling grids smaller or equal to 20 m x 20 m were effective to detect the spatial variability of the relative chlorophyll index in wheat leaves and enable the elaboration of thematic maps for site-specific nitrogen application.

  9. Body mass index and depressive symptoms: instrumental-variables regression with genetic risk score.

    Science.gov (United States)

    Jokela, M; Elovainio, M; Keltikangas-Järvinen, L; Batty, G D; Hintsanen, M; Seppälä, I; Kähönen, M; Viikari, J S; Raitakari, O T; Lehtimäki, T; Kivimäki, M

    2012-11-01

    The causal role of obesity in the development of depression remains uncertain. We applied instrumental-variables regression (Mendelian randomization) to examine the association of adolescent and adult body mass index (BMI) with adult depressive symptoms. Participants were from the Young Finns prospective cohort study (n = 1731 persons, 2844 person-observations), with repeated measurements of BMI and depressive symptoms (modified Beck's Depression Inventory). Genetic risk score of 31 single nucleotide polymorphisms previously identified as robust genetic markers of body weight was used as a proxy for variation in BMI. In standard linear regression analysis, higher adult depressive symptoms were predicted by higher adolescent BMI (B = 0.33, CI = 0.06-0.60, P = 0.017) and adult BMI (B = 0.47, CI = 0.32-0.63, P regression (P = 0.04). These findings provide additional evidence to support a causal role for high BMI in increasing symptoms of depression. However, the present analysis also demonstrates potential limitations of applying Mendelian randomization when using complex phenotypes. © 2012 The Authors. Genes, Brain and Behavior © 2012 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.

  10. Speech based transmission index for all: An intelligibility metric for variable hearing ability.

    Science.gov (United States)

    Mechergui, Nader; Djaziri-Larbi, Sonia; Jaïdane, Mériem

    2017-03-01

    A method to measure the speech intelligibility in public address systems for normal hearing and hearing impaired persons is presented. The proposed metric is an extension of the speech based Speech Transmission Index to account for accurate perceptual masking and variable hearing ability: The sound excitation pattern generated at the ear is accurately computed using an auditory filter model, and its shapes depend on frequency, sound level, and hearing impairment. This extension yields a better prediction of the intensity of auditory masking which is used to rectify the modulation transfer function and thus to objectively assess the speech intelligibility experienced by hearing impaired as well as by normal hearing persons in public spaces. The proposed metric was developed within the framework of the European Active and Assisted Living research program, and was labeled "SB-STI for All." Extensive subjective in-Lab and in vivo tests have been conducted and the proposed metric proved to have a good correlation with subjective intelligibility scores.

  11. Seabed variability and its influence on acoustic prediction uncertainty

    Science.gov (United States)

    Holland, Charles W.; Calder, Brian; Kraft, Barbara; Mayer, Larry; Goff, John; Harrison, Chris

    2005-09-01

    Kevin LePage (Naval Research Laboratory, Washington, DC), Robert I. Odom (University of Washington, Applied Physics Laboratory), Irina Overeem, James Syvitski (University of Colorado, INSTAAR, Boulder, CO) and Lincoln Pratson (Duke University, Durham, NC). The weakest link in performance prediction for naval systems operating in coastal regions is the environmental data that drive the models. In shallow-water downward refracting environments, the seabed properties and morphology often are the controlling environmental factors. In order to address the issue of uncertainty in seabed properties, we focused on two overarching goals: (1) assess and characterize seafloor variability in shelf environments, (2) determine the impact of the seafloor variability on acoustic prediction uncertainty. Our inherently multidisciplinary approach brought marine geology/geophysics and ocean acoustics together at the intersection of geoacoustic modeling. This talk will review results from a 3-year collaboration under the ONR Capturing Uncertainty DRI. [Work supported by the Office of Naval Research.

  12. Preliminary prediction model for the ROTI index at high latitude

    Science.gov (United States)

    Rochel Grimald, Sandrine; Boscher, Daniel; Fabbro, Vincent; Rougerie, Sébastien

    2017-04-01

    The variation of electron density can be described by the ROTI index (i.e. the Rate of change of Total electron content Index). This index is indicative of the electron density gradients which can be responsible of loss of satellite communications or loss of lock of GNSS system.. At high latitude, the ionosphere is connected to the magnetosphere through the magnetic field lines. When the magnetic activity increases, particles from the magnetosphere are injected in the ionosphere along the magnetic field lines. They disturb the ionospheric layer and are responsible of changes in the ROTI index. In this paper, we will use the NOAA POES satellites data to study the link between the ROTI index value and the particles flux in the inner magnetosphere. Then we will use the results to developp a preliminary ROTI model.

  13. Respiratory Pattern Variability Analysis Based on Nonlinear Prediction Methods

    Science.gov (United States)

    2001-10-25

    weaning trials from mechanical ventilation have been studied at two different PSV levels. High statistically significant differences have been obtained...ACQUISITION A group of 12 patients on weaning trials from mechanical ventilation has been studied in the Department of Intensive Care Medicine at Santa Creu i...study the respiratory pattern variability at different levels of pressure support ventilation (PSV) has been analyzed using nonlinear prediction

  14. 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.

  15. The Index Offence Representation Scales; a predictive clinical tool in the management of dangerous, violent patients with personality disorder?

    Science.gov (United States)

    McGauley, Gill; Ferris, Scott; Marin-Avellan, Luisa; Fonagy, Peter

    2013-10-01

    Forensic mental health professionals attach considerable importance to their patient's description of his or her index offence. Despite this, there is no systematic approach to examining and formulating the patient's offence narrative. To use the index offence narratives and capacity to mentalize of violent offender-patients with personality disorder to develop a tool to predict their progress and to evaluate that tool. In a prospective, cohort study, the index offence narratives of 66 violent high security hospital patients with personality disorder were obtained from a semi-structured interview and used to generate the Index Offence Representational Scales (IORS). The predictive validity of these scales was investigated across a range of outcome variables, controlling for the association between initial and final value of the dependent variable. The degree to which patients held internal representations of interpersonal violence and malevolence, as measured by the IORS, predicted subsequent violent behaviour. In contrast to their actual aggressive behaviour, these patients rated themselves as having fewer symptoms on the Symptom Checklist-90-R (SCL-90-R) and fewer problems in interpersonal relationships on the Inventory of Interpersonal Problems. A more empathic victim representation on the IORS predicted better engagement with treatment. The IORS show promise for helping clinicians formulate the early institutional pathway of seriously violent people with personality disorder, particularly with respect to their overt aggression and prosocial engagement. Replication studies are, however, indicated. Copyright © 2013 John Wiley & Sons, Ltd.

  16. Predicting Site Index in Young Black Walnut Plantations

    Science.gov (United States)

    Craig K. Losche; Richard C. Schlesinger

    1975-01-01

    Prediction of black walnut height at age 25 is graphically represented for two soil-site groups. The landowner or manager can use this growth prediction to assess the productivity of yung black walnut plantations.

  17. Variable Ki67 proliferative index in 65 cases of nodular fasciitis, compared with fibrosarcoma and fibromatosis

    Science.gov (United States)

    2013-01-01

    Abstract Nodular fasciitis is the most common pseudosarcomatous lesion of soft tissue. Ki67 was considered as a useful marker for distinguishing some benign and malignant lesions. To study the usefulness of Ki67 in diagnosis of nodular fasciitis, the expression of Ki67 was examined by using immunostaining in 65 nodular fasciitis specimens, 15 desmoid fibromatosis specimens and 20 fibrosarcoma specimens. The results showed that there was a variable Ki67 index in all 65 cases of nodular fasciitis, and the mean labeling index was 23.71±15.01%. In majority (70.77%) of all cases,the index was ranged from 10% to 50%, in 6.15% (4/65) of cases the higher Ki67 index (over 50%) could be seen. The Ki67 proliferative index was closely related to duration of lesion, but not to age distribution, lesion size, sites of lesions and gender. Moreover, the mean proliferative index in desmoid fibromatosis and fibrosarcoma was 3.20±1.26% and 26.15±3.30% respectively. The mean Ki67 index of nodular fasciitis was not significantly lower than fibrosarcoma, but higher than desmoid fibromatosis. The variable and high Ki67 index in nodular fasciitis may pose a diagnostic challenge. We should not misdiagnose nodular fasciitis as a sarcoma because of its high Ki67 index. The recurrence of nodular fasciitis is rare; and the utility of Ki67 immunostaining may be not suitable for recurrence assessment in nodular fasciitis. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/4782335818876666 PMID:23531088

  18. 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...

  19. Climate Prediction Center Equatorial Southern Oscillation Index (1949-present)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This is one of the CPC?s Monthly Atmospheric and SST Indices. It contains Equatorial Southern Oscillation Index (standardized sea level pressure differences between...

  20. Predictive Validity of the Expanded Susceptibility to Smoke Index

    OpenAIRE

    Strong, David R.; Hartman, Sheri J.; Nodora, Jesse; Messer, Karen; James, Lisa; White, Martha; Portnoy, David B.; Choiniere, Conrad J.; Vullo, Genevieve C.; Pierce, John

    2014-01-01

    Objectives:The susceptibility to smoking index can be improved as it only identifies one third of future adult smokers. Adding curiosity to this index may increase the identification of future smokers and improve the identification of effective prevention messages.Methods:Analyses used data from the California Longitudinal Study of Smoking Transitions in Youth, for whom tobacco use behaviors, attitudes, and beliefs were assessed at 3 time points from age 12 through early adulthood. Logistic r...

  1. 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.

  2. Short-term variability in body weight predicts long-term weight gain1

    Science.gov (United States)

    Lowe, Michael R; Feig, Emily H; Winter, Samantha R; Stice, Eric

    2015-01-01

    Background: Body weight in lower animals and humans is highly stable despite a very large flux in energy intake and expenditure over time. Conversely, the existence of higher-than-average variability in weight may indicate a disruption in the mechanisms responsible for homeostatic weight regulation. Objective: In a sample chosen for weight-gain proneness, we evaluated whether weight variability over a 6-mo period predicted subsequent weight change from 6 to 24 mo. Design: A total of 171 nonobese women were recruited to participate in this longitudinal study in which weight was measured 4 times over 24 mo. The initial 3 weights were used to calculate weight variability with the use of a root mean square error approach to assess fluctuations in weight independent of trajectory. Linear regression analysis was used to examine whether weight variability in the initial 6 mo predicted weight change 18 mo later. Results: Greater weight variability significantly predicted amount of weight gained. This result was unchanged after control for baseline body mass index (BMI) and BMI change from baseline to 6 mo and for measures of disinhibition, restrained eating, and dieting. Conclusions: Elevated weight variability in young women may signal the degradation of body weight regulatory systems. In an obesogenic environment this may eventuate in accelerated weight gain, particularly in those with a genetic susceptibility toward overweight. Future research is needed to evaluate the reliability of weight variability as a predictor of future weight gain and the sources of its predictive effect. The trial on which this study is based is registered at clinicaltrials.gov as NCT00456131. PMID:26354535

  3. Scattering of Light by a Sphere with an Arbitrary Radially Variable Refractive Index

    Science.gov (United States)

    Perelman, A. Y.; Zinov'eva, T. V.; Mosseev, I. G.

    Based on the piecewise-continuous hyperbolic approximation (PCHA), we have developed a numerically stable and accurate algorithm for computation of the internal and scattered fields, as well as energetic characteristics, of a sphere with an arbitrary radially variable complex refractive index. The algorithm is cast in terms of the power functions, which overcomes a number of problems associated with round-off errors. The method of computation is tested with known solutions relating to the particular cases of the problem. The PCHA is proved to be convergent. The PCHA allows one to solve the scattering problem associated with an arbitrary complex radially variable refractive index in terms of the simplest functions. The PCHA makes it possible to construct the formal refractive index contour reproducing the scattering experimental data considerably more accurately than the Mie theory. This result is of importance in remote sensing problems. Several examples of calculations for the scattering function of cosmic fluffy dust particles are presented.

  4. Airborne fungal spores of Alternaria, meteorological parameters and predicting variables

    Science.gov (United States)

    Filali Ben Sidel, Farah; Bouziane, Hassan; del Mar Trigo, Maria; El Haskouri, Fatima; Bardei, Fadoua; Redouane, Abdelbari; Kadiri, Mohamed; Riadi, Hassane; Kazzaz, Mohamed

    2015-03-01

    Alternaria is frequently found as airborne fungal spores and is recognized as an important cause of respiratory allergies. The aerobiological monitoring of fungal spores was performed using a Burkard volumetric spore traps. To establish predicting variables for daily and weakly spore counts, a stepwise multiple regression between spore concentrations and independent variables (meteorological parameters and lagged values from the series of spore concentrations: previous day or week concentration (Alt t - 1) and mean concentration of the same day or week in other years ( C mean)) was made with data obtained during 2009-2011. Alternaria conidia are present throughout the year in the atmosphere of Tetouan, although they show important seasonal fluctuations. The highest levels of Alternaria spores were recorded during the spring and summer or autumn. Alternaria showed maximum daily values in April, May or October depending on year. When the spore variables of Alternaria, namely C mean and Alt t - 1, and meteorological parameters were included in the equation, the resulting R 2 satisfactorily predict future concentrations for 55.5 to 81.6 % during the main spore season and the pre-peak 2. In the predictive model using weekly values, the adjusted R 2 varied from 0.655 to 0.676. The Wilcoxon test was used to compare the results from the expected values and the pre-peak spore data or weekly values for 2012, indicating that there were no significant differences between series compared. This test showed the C mean, Alt t - 1, frequency of the wind third quadrant, maximum wind speed and minimum relative humidity as the most efficient independent variables to forecast the overall trend of this spore in the air.

  5. 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.

  6. 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.

  7. Explaining the variability of Photochemical Reflectance Index (PRI): deconvolution of variability related to Light Use Efficiency and Canopy attributes.

    Science.gov (United States)

    Merlier, Elodie; Hmimina, Gabriel; Dufrêne, Eric; Soudani, Kamel

    2014-05-01

    The Photochemical Reflectance Index (PRI) was designed as a proxy of the state of xanthophyll cycle which is used as a response of plants to excess of light (Gamon et al., 1990; 1992). Strong relationships between PRI and LUE were shown at leaf and canopy scales and over a wide range of species (Garbulsky et al., 2011). However, its use at canopy scale was shown to be significantly hampered by effects of confounding factors such as the PRI sensitivity to leaf pigment content (Gamon et al. 2001; Nakaji et al. 2006) and to canopy structure (Hilker et al. 2008). Several approaches aimed at correcting such effects and recent works focused on the deconvolution of LUE related and LUE unrelated PRI variability (Rahimzadeh-Bajgiran et al. 2012).In this study, the PRI variability at canopy scale is investigated over two years on three species (Fagus sylvatica, Quercus robur and Pinus sylvestris) growing under two water regimes. At daily scale, PRI variability is mainly explained by radiation conditions. As already reported at leaf scale in Hmimina et al. (2014), analysis of PRI responses to incoming photosynthetically active radiation over seasonal scale allowed to separate two sources of variability : a constitutive variability mainly related to canopy structure and leaf chlorophyll content and a facultative variability mainly related to LUE and soil moisture content. These results highlight the composite nature of PRI signal measured at canopy scale and the importance of disentangling its sources of variability in order to accurately assess ecosystem light use efficiency. Gamon JA, Field CB, Bilger W, Björkman O, Fredeen AL, Peñuelas J. 1990. Remote sensing of the xanthophyll cycle and chlorophyll fluorescence in sunflower leaves and canopies. Oecologia 85, 1-7. Gamon JA, Field CB, Fredeen A AL, Thayer S. 2001. Assessing photosynthetic downregulation in sunflower stands with an optically-based model. Photosynthesis Research 67, 113-125. Gamon JA, Peñuelas J, Field CB

  8. Ambivalence About Interpersonal Problems and Traits Predicts Cross-Situational Variability of Social Behavior.

    Science.gov (United States)

    Erickson, Thane M; Newman, Michelle G; Peterson, Jessica; Scarsella, Gina

    2015-08-01

    Multiple theoretical perspectives suggest that maladjusted personality is characterized by not only distress, but also opposing or "ambivalent" self-perceptions and behavioral lability across social interactions. However, the degree to which ambivalence about oneself predicts cross-situational variability in social behavior has not been examined empirically. Using the interpersonal circumplex (IPC) as a nomological framework, the present study investigated the extent to which endorsing opposing or "ambivalent" tendencies on IPC measures predicted variability in social behavior across a range of hypothetical interpersonal scenarios (Part 1; N = 288) and naturalistic social interactions (Part 2; N = 192). Ambivalent responding for interpersonal problems and traits was associated with measures of distress, maladaptive interpersonal tendencies, and greater variability of social behavior across both hypothetical and daily social interactions, though more consistently for interpersonal problems. More conservative tests suggested that ambivalence predicted some indexes of behavioral variability even when accounting for mean levels and squared means of social behaviors, vector length, gender, and depressive symptoms. Results suggest that processes theorized as typifying personality disorder may apply more broadly to personality maladjustment occurring outside of clinical samples. © 2014 Wiley Periodicals, Inc.

  9. 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

  10. 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

  11. Monitoring of plethysmography variability index and total hemoglobin levels during cesarean sections with antepartum hemorrhage for early detection of bleeding

    Directory of Open Access Journals (Sweden)

    Ahmed Elsakka

    2017-01-01

    Conclusion: Plethysmography variability index and non invasive hemoglobin monitoring as well can be used for optimization of intravascular volume status during cesarean sections in parturients with antepartum hemorrhage.

  12. Computation of geographic variables for air pollution prediction models in South Korea.

    Science.gov (United States)

    Eum, Youngseob; Song, Insang; Kim, Hwan-Cheol; Leem, Jong-Han; Kim, Sun-Young

    2015-01-01

    Recent cohort studies have relied on exposure prediction models to estimate individuallevel air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA). For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside sites. This study

  13. Computation of geographic variables for air pollution prediction models in South Korea

    Directory of Open Access Journals (Sweden)

    Youngseob Eum

    2015-10-01

    Full Text Available Recent cohort studies have relied on exposure prediction models to estimate individuallevel air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA. For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside

  14. 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

  15. Detecting genomic regions associated with a disease using variability functions and Adjusted Rand Index

    Directory of Open Access Journals (Sweden)

    Makarenkov Vladimir

    2011-10-01

    Full Text Available Abstract Background The identification of functional regions contained in a given multiple sequence alignment constitutes one of the major challenges of comparative genomics. Several studies have focused on the identification of conserved regions and motifs. However, most of existing methods ignore the relationship between the functional genomic regions and the external evidence associated with the considered group of species (e.g., carcinogenicity of Human Papilloma Virus. In the past, we have proposed a method that takes into account the prior knowledge on an external evidence (e.g., carcinogenicity or invasivity of the considered organisms and identifies genomic regions related to a specific disease. Results and conclusion We present a new algorithm for detecting genomic regions that may be associated with a disease. Two new variability functions and a bipartition optimization procedure are described. We validate and weigh our results using the Adjusted Rand Index (ARI, and thus assess to what extent the selected regions are related to carcinogenicity, invasivity, or any other species classification, given as input. The predictive power of different hit region detection functions was assessed on synthetic and real data. Our simulation results suggest that there is no a single function that provides the best results in all practical situations (e.g., monophyletic or polyphyletic evolution, and positive or negative selection, and that at least three different functions might be useful. The proposed hit region identification functions that do not benefit from the prior knowledge (i.e., carcinogenicity or invasivity of the involved organisms can provide equivalent results than the existing functions that take advantage of such a prior knowledge. Using the new algorithm, we examined the Neisseria meningitidis FrpB gene product for invasivity and immunologic activity, and human papilloma virus (HPV E6 oncoprotein for carcinogenicity, and confirmed

  16. An inflammation-based prognostic index predicts survival advantage after transarterial chemoembolization in hepatocellular carcinoma.

    Science.gov (United States)

    Pinato, David J; Sharma, Rohini

    2012-08-01

    Transarterial chemoembolization (TACE) is the preferred treatment for unresectable, intermediate-stage hepatocellular carcinoma (HCC). However, survival after TACE can be highly variable, suggesting the need for more accurate patient selection to improve therapeutic outcome. We have explored the prognostic ability of the blood neutrophil-to-lymphocyte ratio (NLR), a biomarker of systemic inflammation, as a predictor of survival after TACE. Fifty-four patients with a diagnosis of HCC eligible for TACE were selected. Clinicopathologic variables were collected, including demographics, tumor staging, liver functional reserve, and laboratory variables. Dynamic changes in the NLR before and after TACE were studied as predictors of survival using both a univariate and multivariate Cox regression model. Patients in whom the NLR remained stable or normalized after TACE showed a significant improvement in overall survival of 26 months compared with patients showing a persistently abnormal index (P = 0.006). Other predictors of survival on univariate analysis were Cancer of the Liver Italian Program score (P = 0.05), intrahepatic spread (P = 0.01), tumor diameter > 5 cm (P = 0.02), > 1 TACE (P = 0.01), alpha-fetoprotein ≥ 400 (P = 0.002), and radiologic response to TACE (P analysis. Changes in alpha-fetoprotein after treatment did not predict survival. Patients with a persistently increased NLR have a worse outcome after TACE. NLR is a simple and universally available stratifying biomarker that can help identify patients with a significant survival advantage after TACE. Copyright © 2012 Mosby, Inc. All rights reserved.

  17. D-index: A New Scoring System in Febrile Neutropenic Patients for Predicting Invasive Fungal Infections

    Directory of Open Access Journals (Sweden)

    Gülden Yılmaz

    2016-05-01

    Full Text Available Objective: Neutropenia is a critical risk factor for invasive fungal infections (IFIs. We retrospectively performed this study to assess the performance of the D-index, a new test that combines both the duration and the severity of neutropenia, in predicting IFIs among patients with acute myelogenous leukemia. Materials and Methods: Fifteen patients with IFIs and 28 patients who did not develop IFIs were enrolled in the study. The D-index was defined as the area over the neutrophil curve, whereas the cumulativeD-index (c-D-index was the area over the neutrophil curve from the start of neutropenia until the first clinical manifestation of IFI. Results: The D-index and the c-D-index tended to be significantly higher in patients with IFIs, with medians of 10,150 (range: 4000- 22,000 and 5300 (range: 2300-22,200, respectively (p=0.037 and p=0.003, respectively. The receiver operating characteristic analyses showed that there was a cutoff point of 3875 for the D-index in predicting IFI; the sensitivity, specificity, and positive and negative predictive values were 100%, 67.9%, 35.4%, and 100%, respectively. There was also a cutoff point of 4225 for the c-D-index in predicting IFI; the sensitivity, specificity, and positive and negative predictive values for the c-D-index were 93.3%, 71.4%, 36.6%, and 98.4%. Conclusion: The D-index and especially the c-D-index could be useful tools with high negative predictive value to exclude as well as to predict IFIs in the management of neutropenic patients.

  18. Prediction of the insulin sensitivity index using Bayesian networks

    DEFF Research Database (Denmark)

    Bøttcher, Susanne Gammelgaard; Dethlefsen, Claus

    The insulin sensitivity index () can be used in assessing the risk of developing type 2 diabetes. An intravenous study is used to determine using Bergmans minimal model. However, an intravenous study is time consuming and expensive and therefore not suitable for large scale epidemiological studie...... test instead of an intravenous study. The methodology is applied to a dataset with 187 patients. We find that the values from this study are highly correlated to the values determined from the intravenous study. S_I S_I S_I S_I S_I......The insulin sensitivity index () can be used in assessing the risk of developing type 2 diabetes. An intravenous study is used to determine using Bergmans minimal model. However, an intravenous study is time consuming and expensive and therefore not suitable for large scale epidemiological studies...

  19. 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.

  20. Estimating the reliability of glycemic index values and potential sources of methodological and biological variability123

    Science.gov (United States)

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

    2016-01-01

    Background: 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. Objective: 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. Design: 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/m2): 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. Results: 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. Conclusions: 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

  1. 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/m2): 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

  2. Evaluation of MM5 model resolution when applied to prediction of national fire danger rating indexes

    Science.gov (United States)

    Jeanne L. Hoadley; Miriam L. Rorig; Larry Bradshaw; Sue A. Ferguson; Kenneth J. Westrick; Scott L. Goodrick; Paul Werth

    2006-01-01

    Weather predictions from the MM5 mesoscale model were used to compute gridded predictions of National Fire Danger Rating System (NFDRS) indexes. The model output was applied to a case study of the 2000 fire season in Northern Idaho and Western Montana to simulate an extreme event. To determine the preferred resolution for automating NFD RS predictions, model...

  3. 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.

  4. 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...

  5. Prediction Feasibility of Cutaneous Leishmaniasis Using Climatic Variables in Poldokhtar

    Directory of Open Access Journals (Sweden)

    Behroz Parvaneh

    2017-03-01

    Full Text Available Background: The increasing number of patients suffering from cutaneous leishmaniasis in Poldokhtar County during the last 10 years and technological advances in data generation has increased the necessity to produce the predicting models of disease prevalence in the region. Therefore, climatic variables were used in this study to predict the cutaneous leishmaniasis. Materials and Methods: In this study using regression model, the relationship between number of patients with cutaneous leishmaniasis and climatic signals were taken simultaneously and with one, two, three and four months of regression lag. Results: Totally there was a significant relationship between January patients with January NINO1 climatic signal, March patients with February PNA climatic signal, April patients with March AAMM climatic signal, May patients with April AO climatic signal, and August patients with June TSA climatic signal, at 5% significance level. Furthermore, there was a significant relationship between February patients with January NINO1 climatic signal, at 10% significance level. Conclusion: This investigation showed that use of climatic signals with lags for predicting the disease was better than simultaneous application of signals and disease. Correlation between statistics relating to diseases during the entire period and PDO signal with 2 months of lag was obtained as 84.53. In addition, results indicated that approximately during half of the months in a year, there was a good correlation between prevalence of cutaneous leishmaniasis and the climatic signals and thus enabling us to discover prevalence of cutaneous leishmaniasis using the climatic signals.

  6. Validation of the prostate health index in a predictive model of prostate cancer.

    Science.gov (United States)

    Sanchís-Bonet, A; Barrionuevo-González, M; Bajo-Chueca, A M; Pulido-Fonseca, L; Ortega-Polledo, L E; Tamayo-Ruiz, J C; Sánchez-Chapado, M

    To validate and analyse the clinical usefulness of a predictive model of prostate cancer that incorporates the biomarker «[-2] pro prostate-specific antigen» using the prostate health index (PHI) in decision making for performing prostate biopsies. We isolated serum from 197 men with an indication for prostate biopsy to determine the total prostate-specific antigen (tPSA), the free PSA fraction (fPSA) and the [-2] proPSA (p2PSA). The PHI was calculated as p2PSA/fPSA×√tPSA. We created 2 predictive models that incorporated clinical variables along with tPSA or PHI. The performance of PHI was assessed with a discriminant analysis using receiver operating characteristic curves, internal calibration and decision curves. The areas under the curve for the tPSA and PHI models were 0.71 and 0.85, respectively. The PHI model showed a better ability to discriminate and better calibration for predicting prostate cancer but not for predicting a Gleason score in the biopsy ≥7. The decision curves showed a greater net benefit with the PHI model for diagnosing prostate cancer when the probability threshold was 15-35% and greater savings (20%) in the number of biopsies. The incorporation of p2PSA through PHI in predictive models of prostate cancer improves the accuracy of the risk stratification and helps in the decision-making process for performing prostate biopsies. Copyright © 2017 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

  7. Renal resistive index reflects Fontan pathophysiology and predicts mortality.

    Science.gov (United States)

    Ohuchi, Hideo; Negishi, Jun; Hayama, Yohsuke; Miyazaki, Aya; Shiraishi, Isao; Ichikawa, Hajime

    2017-10-01

    The renal resistive index (RRI) reflects non-renal pathophysiology, such as great artery stiffness, haemodynamics and even end-organ damage in patients with hypertension. This study was conducted to clarify the clinical significance of the RRI in Fontan pathophysiology. We measured the RRI in 280 consecutive Fontan patients and 36 healthy controls. The patients exhibited a higher RRI than the controls (0.71±0.07 vs 0.60±0.04, ppathophysiology. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  8. Prediction Of Clearness Index For Some Nigerian Stations Using ...

    African Journals Online (AJOL)

    The tests of performance of the model for the five stations have been done in terms of the widely used statistical indicators, Mean Bias Error (MBE) and Root Mean Square Error (RMSE). It was found from statistical model performance indicators that the models provided reasonably high degree of precision in the prediction of ...

  9. Prediction of Outcome Using the Mannheim peritonitis Index in ...

    African Journals Online (AJOL)

    Background: Successful management of peritonitis has, for decades, presented a challenge to surgeons despite advancements in medicine. This led to the development of disease severity grading systems that would aid in stratifying patients by individual risk factors and hence appropriately predict possible outcome.

  10. Heart rate variability as a biomarker for epilepsy seizure prediction.

    Science.gov (United States)

    Moridani, M K; Farhadi, H

    2017-01-01

    Epilepsy is a neurological disorder that causes seizures of many different types. Recent research has shown that epileptic seizures can be predicted by using the electrocardiogrami instead of the electroencephalogram. In this study, we used the heart rate variability that is generated by the fluctuating balance of sympathetic and parasympathetic nervous systems to predict epileptic seizures. We studied 11 epilepsy patients to predict the seizure interval. With regar tos the fact that HRV signals are nonstationary, our analysis focused on linear features in the time and frequency domain of HRV signal such as RR Interval (RRI), mean heart rate (HR), high-frequency (HF) (0.15-0.40 Hz) and low-frequency (LF) (0.04-0.15 Hz), as well as LF/HF. Also, quantitative analyses of Poincaré plot features (SD1, SD2, and SD1/SD2 ratio) were performed. HRV signal was divided into intervals of 5 minutes. In each segment linear and nonlinear features were extracted and then the amount of each segment compared to the previous segment using a threshold. Finally, we evaluated the performance of our method using specificity and sensitivity. During seizures, mean HR, LF/HF, and SD2/SD1 ratio significantly increased while RRI significantly decreased. Significant differences between two groups were identified for several HRV features. Therefore, these parameters can be used as a useful feature to discriminate a seizure from a non-seizure The seizure prediction algorithm proposed based on HRV achieved 88.3% sensitivity and 86.2 % specificity. These results indicate that the HRV signal contains valuable information and can be a predictor for epilepsy seizure. Although our results in comparison with EEG ares a little bit weaker, the recording of ECG is much easier and faster than EEG. Also, our finding showed the results of this study are considerably better than recent research based on ECG (Tab. 1, Fig. 10, Ref. 17).

  11. A Simpler Creatinine Index Can Predict Long-Term Survival in Chinese Hemodialysis Patients

    Science.gov (United States)

    Lee, Szu-Ying; Yang, Chung-Wei; Hung, Szu-Chun; Chiang, Chih-Kang; Huang, Jenq-Wen; Hung, Kuan-Yu

    2016-01-01

    Background Low lean body mass (LBM) is an indicator of malnutrition inflammation syndrome, which is common in hemodialysis (HD) patients. The creatinine index (CI) has been validated as a reliable method to estimate LBM and evaluate the protein-energy status of HD patients. However, the traditional creatinine index formula was complex. We sought to investigate the impact of CI derived from a new simple formula on Chinese HD patient outcomes. Methods In this retrospective cohort study, we enrolled 1269 patients who initiated HD between February 1981 and February 2012 and followed them until the end of February 2013. CI was calculated using the simple creatinine kinetic model (CKM) formula. Multiple linear regression analysis and Cox regression proportional hazard analysis were used to define independent variables and compare survival between groups. Results The 1269 HD patients were categorized into 3 groups according to the tertiles of calculated CI between men and women. Each group consisted of 423 patients (50.6% men, 49.4% women). Patients in the highest sex-specific tertile of CI had longer overall survival (HR, 0.46; P 0.002). BMI did not significantly associate with survival after adjustment (HR,0.99; P 0.613). Conclusions CI derived from the simple CKM formula serves as a good parameter than BMI to predict the survival of HD patients. The formula could extend its convenient use in clinical practice for HD patients. PMID:27780214

  12. Prediction of insomnia severity based on cognitive, metacognitive, and emotional variables in college students.

    Science.gov (United States)

    Doos Ali Vand, Hoda; Gharraee, Banafsheh; Farid, Ali-Asghar Asgharnejad; Bandi, MirFarhad Ghaleh

    2014-01-01

    Insomnia is the most common sleep disorder whose origin is attributed to various variables. The current study aims to predict the symptoms of insomnia by investigating some of its predictors. Numerous variables such as depression and anxiety symptoms, worry, pre-sleep arousal (cognitive arousal and somatic arousal), dysfunctional cognitions, and metacognitive beliefs about sleep were assessed as insomnia predictors. A total of 400 students of Tehran University of Medical Sciences completed the Depression Anxiety Stress Scale (DASS), the Penn State Worry Questionnaire (PSWQ), the Pre-Sleep Arousal Scale (PSAS), the Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-10), the Metacognitions Questionnaire-Insomnia (MCQ-I), and the Insomnia Severity Index (ISI). All variables were significantly correlated with insomnia symptoms (P depressive symptoms. The findings underline the significant role of cognitive and metacognitive variables for predicting insomnia symptoms. Moreover, the results suggest that metacognitive beliefs about sleep may need to be considered as a significant component in the context of insomnia. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Predicting Thermodynamic Properties of PBXTHs with New Quantum Topological Indexes.

    Science.gov (United States)

    Xiao, Fangzhu; Peng, Guowen; Nie, Changming; Yu, Limei

    2016-01-01

    Novel group quantitative structure-property relationship (QSPR) models on the thermodynamic properties of PBXTHs were presented, by the multiple linear regression (MLR) analysis method. Four thermodynamic properties were studied: the entropy (Sθ), the standard enthalpy of formation (ΔfHθ), the standard Gibbs energy of formation (ΔfGθ), and the relative standard Gibbs energy of formation (ΔRGθ). The results by the formula indicate that the calculated and predicted data in this study are in good agreement with those in literature and the deviation is within the experimental errors. To validate the estimation reliability for internal samples and the predictive ability for other samples, leave-one-out (LOO) cross validation (CV) and external validation were performed, and the results show that the models are satisfactory.

  14. PASTA ADDED WITH CHICKPEA FLOUR: CHEMICAL COMPOSITION, IN VITRO STARCH DIGESTIBILITY AND PREDICTED GLYCEMIC INDEX

    National Research Council Canada - National Science Library

    Osorio-Díaz, P; Agama-Acevedo, E; Mendoza-Vinalay, M; Tovar, J; Bello-Pérez, L. A

    2008-01-01

    Pasta was prepared with of durum wheat flour mixed with chickpea flour at two different levels and its chemical composition, in vitro starch digestibility and predicted glycemic index were assessed...

  15. Accounting for Rainfall Spatial Variability in Prediction of Flash Floods

    Science.gov (United States)

    Saharia, M.; Kirstetter, P. E.; Gourley, J. J.; Hong, Y.; Vergara, H. J.

    2016-12-01

    Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 20,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. Next the model is used to predict flash flooding characteristics all over the continental U.S., specifically over regions poorly covered by hydrological observations. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the

  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. The acrosome index, radical buffer capacity and number of isolated progressively motile spermatozoa predict IVF results

    NARCIS (Netherlands)

    Rhemrev, J. P.; Menkveld, R.; Roseboom, T. J.; van Overveld, F. W.; Teerlink, T.; Lombard, C.; Vermeiden, J. P.

    2001-01-01

    BACKGROUND: The accuracy by which a number of newly described semen variables can predict either total fertilization failure (TFF) or pregnancy outcome in IVF, has not previously been investigated. The study aim was, therefore, to determine prospectively the predictive value of these variables.

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

    Science.gov (United States)

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

    2014-05-01

    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) estimates. We tested whether variability of the ARI could be decreased by suppressing the effect of the VLF band through filtering. We also evaluated whether filtering had any effect on mean group differences between healthy subjects and acute stroke patients. Data from a recent mobilization stroke study were re-analyzed. Middle cerebral artery cerebral blood flow velocity (MCA-CBFV), mean arterial blood pressure (MABP) and end tidal PCO2 (PetCO2) were obtained in 16 healthy subjects and 27 acute ischemic stroke patients in the supine position. The ARI index was calculated from the transfer function (TF) by using spontaneous BP fluctuations. Three different filtering strategies were compared; no filtering (NF), a high pass filter at 0.04 Hz (Time Domain Filtering: TDF) and a high pass Transfer Function Filter (TFF) at 0.04 Hz. In addition, a simulation study was done to obtain further insight into the effects of the applied filters. The variability of the ARI index decreased significantly only with TFF in healthy subjects (standard deviation (left vs. right) after NF 2.28 vs. 2.36, after TDF 2.13 vs. 2.31 after TFF 1.09 vs. 1.19, pproperties when using TFA for ARI calculation. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

  19. Heart rate variability predicts mortality in peritoneal dialysis patients.

    Science.gov (United States)

    Pei, Juan; Tang, Wen; Li, Li-Xian; Su, Chun-Yan; Wang, Tao

    2015-08-01

    The predictive value of heart rate variability (HRV) in peritoneal dialysis (PD) has never been tested. In this study, the associations between HRV measures and the mortality in 81 PD patients were analyzed. HRV was measured by using 5-min recordings of a stationary system by a standardized method. Both time domain and frequency domain parameters were analyzed. During a follow-up period of 43.78 ± 14.77 months, 25 patients died, four patients were transferred to hemodialysis. Of the 81 patients, the time domain parameters, such as the standard deviation of differences between adjacent normal sinus to normal sinus (NN) intervals (SDSD) and the square root of the mean of the squared differences between adjacent normal NN intervals (RMSSD), were higher; the frequency domain parameters, such as the ratio of low-frequency power to high-frequency power (LF/HF) and the normalized LF, were lower, and the normalized HF was higher in the non-survived group as compared with the survived group. A Cox proportional hazards model analysis revealed that, of the HRV measures, decrease of the normalized LF, LF/HF and increase of rMSSD, SDSD, normalized HF had significant predictive value for mortality. After adjustment for other univariate predictors including age, urine volume, renal Kt/V, high-sensitivity C-reactive protein (hs-CRP), the predictive value of decreased LF/HF remained significant. Kaplan-Meier survival analysis showed mortality rate was much higher in patients with a low LF/HF (median value of 1.56). The decreases of LF/HF which reflects impaired sympathetic nerve regulation is an independent predictor of mortality in PD patients.

  20. LDL electronegativity index: a potential novel index for predicting cardiovascular disease.

    Science.gov (United States)

    Ivanova, Ekaterina A; Bobryshev, Yuri V; Orekhov, Alexander N

    2015-01-01

    High cardiovascular risk conditions are frequently associated with altered plasma lipoprotein profile, such as elevated low-density lipoprotein (LDL) and LDL cholesterol and decreased high-density lipoprotein. There is, however, accumulating evidence that specific subclasses of LDL may play an important role in cardiovascular disease development, and their relative concentration can be regarded as a more relevant risk factor. LDL particles undergo multiple modifications in plasma that can lead to the increase of their negative charge. The resulting electronegative LDL [LDL(-)] subfraction has been demonstrated to be especially atherogenic, and became a subject of numerous recent studies. In this review, we discuss the physicochemical properties of LDL(-), methods of its detection, atherogenic activity, and relevance of the LDL electronegativity index as a potential independent predictor of cardiovascular risk.

  1. Ozone Concentration Prediction via Spatiotemporal Autoregressive Model With Exogenous Variables

    Science.gov (United States)

    Kamoun, W.; Senoussi, R.

    2009-04-01

    Forecast of environmental variables are nowadays of main concern for public health or agricultural management. In this context a large literature is devoted to spatio-temporal modelling of these variables using different statistical approaches. However, most of studies ignored the potential contribution of local (e.g. meteorological and/or geographical) covariables as well as the dynamical characteristics of observations. In this study, we present a spatiotemporal short term forecasting model for ozone concentration based on regularly observed covariables in predefined geographical sites. Our driving system simply combines a multidimensional second order autoregressive structured process with a linear regression model over influent exogenous factors and reads as follows: ‘2 ‘q j Z (t) = A (Î&,cedil;D )Ã- [ αiZ(t- i)]+ B (Î&,cedil;D )Ã- [ βjX (t)]+ ɛ(t) i=1 j=1 Z(t)=(Z1(t),…,Zn(t)) represents the vector of ozone concentration at time t of the n geographical sites, whereas Xj(t)=(X1j(t),…,Xnj(t)) denotes the jth exogenous variable observed over these sites. The nxn matrix functions A and B account for the spatial relationships between sites through the inter site distance matrix D and a vector parameter Î&.cedil; Multidimensional white noise ɛ is assumed to be Gaussian and spatially correlated but temporally independent. A covariance structure of Z that takes account of noise spatial dependences is deduced under a stationary hypothesis and then included in the likelihood function. Statistical model and estimation procedure: Contrarily to the widely used choice of a {0,1}-valued neighbour matrix A, we put forward two more natural choices of exponential or power decay. Moreover, the model revealed enough stable to readily accommodate the crude observations without the usual tedious and somewhat arbitrarily variable transformations. Data set and preliminary analysis: In our case, ozone variable represents here the daily maximum ozone

  2. Heart Rate Variability Indexes in Dementia: A Systematic Review with a Quantitative Analysis.

    Science.gov (United States)

    da Silva, Vanessa Pereira; Ramalho Oliveira, Bruno Ribeiro; Tavares Mello, Roger Gomes; Moraes, Helena; Deslandes, Andrea Camaz; Laks, Jerson

    2018-01-01

    Decreased heart rate variability (HRV) indexes indicate low vagal activity and may be associated with development of dementia. The neurodegenerative process is associated with the cardiovascular autonomic control. The aim of this systematic review was to investigate the effect size (ES) magnitude of the HRV indexes in the evaluation of autonomic dysfunction in older persons with dementia. PubMed (Medline), Web of Science, Scopus, Scielo, Lilacs, and APA Psycnet were consulted. Complete original articles published in English or Portuguese, investigating the association between autonomic dysfunction and dementia, using the HRV indexes were included. The search identified 97 potentially relevant articles. After screening the full text, eight articles were included in the qualitative analysis and six were included in the quantitative analysis. Almost all indexes showed a negative ES for all types of dementia and mild cognitive impairment. The most common frequency band of the power spectrum density function was the high frequency, which was reported by six studies. The meta-analysis of high frequency power in Alzheimer's disease group showed high heterogeneity and inconsistent results. The negative effect size suggests an autonomic dysfunction in all types of dementia as well as mild cognitive impairment. However, further analysis is necessary to support these results. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  3. Spatial variability of vegetation index and soil properties in an integrated crop-livestock system

    Directory of Open Access Journals (Sweden)

    Alberto C. de C. Bernardi

    Full Text Available ABSTRACT The knowledge of soil property spatial variability is useful for determining the rational use of inputs, such as the site-specific application of lime and fertilizer. The objective of this study was to evaluate the vegetation index and spatial variability of physical and chemical soil properties in an integrated crop-livestock system (ICLS. Soil samples were taken from a 6.9 ha area in a regular hexagon grid at 0-0.20 m depths. Soil P, K, Ca, Mg, and cation exchange capacity - CEC; base saturation; clay and sand were analyzed. Soil electrical conductivity (ECa was measured with a contact sensor. The site was evaluated at the end of the corn season (April and during forage production (October using Landsat 5 images, remote sensing techniques and a geographic information system (GIS. Results showed that the normalized difference vegetation index (NDVI was associated with ECa and soil parameters, indicating crop and pasture variations in the ICLS. Geostatistics and GIS were effective tools for collecting data regarding the spatial variability of soil and crop indicators, identifying variation trends in the data, and assisting data interpretation to determine adequate management strategies.

  4. 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.

  5. Prediction of geomagnetic indexes with the help of artificial neural networks

    Science.gov (United States)

    Myagkova, Irina; Shiroky, Vladimir; Dolenko, Sergey

    2017-10-01

    The results of prediction of geomagnetic indexes characterizing the state of the Earth's magnetosphere obtained with the help of artificial neural networks (ANN) for various prediction horizons are presented. The forecasts are based on multivariate time series including the values of the geomagnetic indices themselves, as well as data about the parameters of solar wind and interplanetary magnetic field, during several latest hours.

  6. 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

  7. 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...... practice. The aim of this study was to investigate the intra-rater reliability and agreement of summary measures of gait (GDI; GPS; and the Gait Variable Score (GVS) derived from the GPS). The intra-rater reliability and agreement were investigated across two repeated sessions in 18 children aged 5...

  8. Validation of the Shock Index, Modified Shock Index, and Age Shock Index for Predicting Mortality of Geriatric Trauma Patients in Emergency Departments.

    Science.gov (United States)

    Kim, Soon Yong; Hong, Ki Jeong; Shin, Sang Do; Ro, Young Sun; Ahn, Ki Ok; Kim, Yu Jin; Lee, Eui Jung

    2016-12-01

    The shock index (SI), modified shock index (MSI), and age multiplied by SI (Age SI) are used to assess the severity and predict the mortality of trauma patients, but their validity for geriatric patients is controversial. The purpose of this investigation was to assess predictive value of the SI, MSI, and Age SI for geriatric trauma patients. We used the Emergency Department-based Injury In-depth Surveillance (EDIIS), which has data from 20 EDs across Korea. Patients older than 65 years who had traumatic injuries from January 2008 to December 2013 were enrolled. We compared in-hospital and ED mortality of groups categorized as stable and unstable according to indexes. We also assessed their predictive power of each index by calculating the area under the each receiver operating characteristic (AUROC) curve. A total of 45,880 cases were included. The percentage of cases classified as unstable was greater among non-survivors than survivors for the SI (36.6% vs. 1.8%, P < 0.001), the MSI (38.6% vs. 2.2%, P < 0.001), and the Age SI (69.4% vs. 21.3%, P < 0.001). Non-survivors had higher median values than survivors on the SI (0.84 vs. 0.57, P < 0.001), MSI (0.79 vs. 1.14, P < 0.001), and Age SI (64.0 vs. 41.5, P < 0.001). The predictive power of the Age SI for in-hospital mortality was higher than SI (AUROC: 0.740 vs. 0.674, P < 0.001) or MSI (0.682, P < 0.001) in geriatric trauma patients.

  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

    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...

  10. Liver transplant length of stay (LOS) index: A novel predictive score for hospital length of stay following liver transplantation.

    Science.gov (United States)

    Rana, Abbas; Witte, Ellen D; Halazun, Karim J; Sood, Gagan K; Mindikoglu, Ayse L; Sussman, Norman L; Vierling, John M; Kueht, Michael L; Galvan, Nhu Thao N; Cotton, Ronald T; O'Mahony, Christine A; Goss, John A

    2017-12-01

    An index to predict hospital length of stay after liver transplantation could address unmet clinical needs. Length of stay is an important surrogate for hospital costs and efforts to limit stays can preserve our healthcare resources. Here, we devised a scoring system that predicts hospital length of stay following liver transplantation. We used univariate and multivariate analyses on 73 635 adult liver transplant recipient data and identified independent recipient and donor risk factors for prolonged hospital stay (>30 days). Multiple imputation was used to account for missing variables. We identified 22 factors as significant predictors of prolonged hospital stay, including the most significant risk factors: intensive care unit (ICU) admission (OR 1.75, CI 1.58-1.95) and previous transplant (OR 1.60, CI 1.47-1.75). The length of stay (LOS) index assigns weighted risk points to each significant factor in a scoring system to predict prolonged hospital stay after liver transplantation with a c-statistic of 0.75. The LOS index demonstrated good discrimination across the entire population, dividing the cohort into tertiles, which had odds ratios of 2.25 (CI 2.06-2.46) and 7.90 (7.29-8.56) for prolonged hospital stay (>30 days). The LOS index utilizes 22 significant donor and recipient factors to accurately predict hospital length of stay following liver transplantation. The index further demonstrates the basis for a clear clinical recommendation to mitigate risk of long hospitalization by minimizing cold ischemia time. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. Variable Connectivity Index as a Tool for Modeling Structure-Property Relationships

    Directory of Open Access Journals (Sweden)

    Subhash C. Basak

    2004-12-01

    Full Text Available We report on the calculation of normal boiling points for a series of n = 58 aliphatic alcohols using the variable connectivity index in which variables x and y are used to modify the weights on carbon (x and oxygen atoms (y in molecular graphs, respectively. The optimal regressions are found for x = 0.80 and y = -0.90. Comparison is made with available regressions on the same data reported previously in the literature. A refinement of the model was considered by introducing different weights for primary, secondary, tertiary, and quaternary carbon atoms. The standard error in the case of the normal boiling points of alcohols was slightly reduced with optimal weights for different carbon atoms from s = 4.1°C (when all carbon atoms were treated as alike to s = 3.9 °C.

  12. 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.

  13. Bone Scan Index predicts outcome in patients with metastatic hormone-sensitive prostate cancer.

    Science.gov (United States)

    Poulsen, Mads H; Rasmussen, Janne; Edenbrandt, Lars; Høilund-Carlsen, Poul F; Gerke, Oke; Johansen, Allan; Lund, Lars

    2016-05-01

    To evaluate the Bone Scan Index (BSI) for prediction of castration resistance and prostate cancer-specific survival (PCSS). In this retrospective study, we used novel computer-assisted software for automated detection/quantification of bone metastases by BSI. Patients with prostate cancer are M-staged by whole-body bone scintigraphy (WBS) and categorised as M0 or M1. Within the M1 group, there is a wide range of clinical outcomes. The BSI was introduced a decade ago providing quantification of bone metastases by estimating the percentage of bone involvement. Being too time consuming, it never gained widespread clinical use. In all, 88 patients with prostate cancer awaiting initiation of androgen-deprivation therapy due to metastases were included. WBS was performed using a two-headed γ-camera. BSI was obtained using the automated platform EXINI bone (EXINI Diagnostics AB, Lund, Sweden). In Cox proportional hazard models, time to castration-resistant prostate cancer (CRPC) and PCSS were modelled as the dependent variables, whereas prostate-specific antigen (PSA) level, Gleason score and BSI were used as explanatory factors. For Kaplan-Meier estimates, BSI groups were dichotomously split into: BSI Gleason score was 7.7 (2-10), and the mean (range) BSI was 1.0 (0-9.2). During a mean (range) follow-up of 26 (8-49) months, 48 patients became castration resistant and 15 had died; most (13) from prostate cancer. In multivariate analysis including PSA level, Gleason score and BSI, only prediction by BSI was statistically significant. This was true both for time to CRPC (hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.22-1.74; C-index increase from 0.49 to 0.69) and for PCSS (HR 1.34, 95% CI 1.07-1.67; C-index increase from 0.76 to 0.95). BSI obtained using a novel automated computer-assisted algorithm appears to be a useful predictor of outcome for time to CRPC and PCSS in patients with hormone-sensitive metastatic prostate cancer. © 2015 The Authors BJU

  14. Some properties of analytic in a ball functions of bounded $\\mathbf{L}$-index in joint variables

    OpenAIRE

    Bandura, Andriy; Skaskiv, Oleh

    2017-01-01

    A concept of boundedness of the $\\mathbf{L}$-index in joint variables (see in Bandura A. I., Bordulyak M. T., Skaskiv O. B. "Sufficient conditions of boundedness of L-index in joint variables", Mat. Stud. 45 (2016), 12--26. dx.doi.org/10.15330/ms.45.1.12-26) is generalized for analytic in a ball function. There are proved criteria of boundedness of the $\\mathbf{L}$-index in joint variables which describe local behavior of partial derivatives and maximum modudus on a skeleton of a polydisc, pr...

  15. Body mass index (BMI) predicts percent body fat better than body adiposity index (BAI) in school children.

    Science.gov (United States)

    Zhao, Dapeng; Zhang, Yunzhao

    2015-01-01

    Child obesity is associated with increased risk of adult obesity, and is considered as one important health risk factor. Appropriate indicators are required to identify potential risks of child adiposity. This study for the first time compares body mass index (BMI) and body adiposity index (BAI) for predicting percent body fat (PBF) in children. We measured statures, weights, and hip circumferences of 527 children of Han ethnicity and calculated BMI and BAI. PBF was obtained by bioelectrical impedance analysis. We adopted Pearson correlation analysis, linear regression analysis, and receiver operating characteristic (ROC) analysis. For each sex, we found that: 1) BMI and BAI were significantly correlated with PBF; 2) the correlation coefficient between BMI and PBF was higher than that between BAI and PBF; 3) BMI better predicted PBF in the linear regression analysis; 4) the discriminatory capacity of the BMI is higher than the one of BAI in ROC analysis. Taken together, BMI is a more reliable PBF indicator predicting adiposity in children. This finding may aid future obesity monitoring and intervention in children.

  16. A new index to optimally design and compare continuous glucose monitoring glucose prediction algorithms.

    Science.gov (United States)

    Facchinetti, Andrea; Sparacino, Giovanni; Trifoglio, Emanuele; Cobelli, Claudio

    2011-02-01

    Continuous glucose monitoring (CGM) data can be exploited to prevent hypo-/hyperglycemic events in real time by forecasting future glucose levels. In the last few years, several glucose prediction algorithms have been proposed, but how to compare them (e.g., methods based on polynomial rather than autoregressive time-series models) and even how to determine the optimal parameter set for a given method (e.g., prediction horizon and forgetting) are open problems. A new index, J, is proposed to optimally design a prediction algorithm by taking into account two key components: the regularity of the predicted profile and the time gained thanks to prediction. Effectiveness of J is compared with previously proposed criteria such as the root mean square error (RMSE) and continuous glucose-error grid analysis (CG-EGA) on 20 Menarini (Florence, Italy) Glucoday® CGM data sets. For a given prediction algorithm, the new index J is able to suggest a more consistent and better parameter set (e.g., prediction horizon and forgetting factor of choice) than RMSE and CG-EGA. In addition, the minimization of J can reliably be used as a selection criterion in comparing different prediction methods. The new index can be used to compare different prediction strategies and to optimally design their parameters.

  17. Body mass index is related to autonomic nervous system activity as measured by heart rate variability.

    Science.gov (United States)

    Molfino, A; Fiorentini, A; Tubani, L; Martuscelli, M; Rossi Fanelli, F; Laviano, A

    2009-10-01

    Autonomic nervous system activity is involved in body weight regulation. We assessed whether the body mass index (BMI) is related to the autonomic nervous system activity as assessed by heart rate variability (HRV). Twenty-five adult normotensive, euglycemic healthy males (M) and females (F) were studied (M/F=13/12). BMI was assessed in each individual. HRV was assessed and the domains of low frequencies (LF, index of the sympathetic modulation) and high frequencies (HF, index of the parasympathetic modulation) were measured. Data were statistically analyzed and are presented as mean+/-s.d. Mean BMI did not correlate with either HF or LF. It inversely related to HF (r=-0.50, P<0.01), whereas its relationship with LF was marginally significant (r=-0.39, P=0.05). The HF in individuals with BMI <20 kg/m(2) was significantly higher from those measured in the remaining subjects (P<0.05). The results support the role of parasympathetic activity in influencing BMI through likely modulation of body weight.

  18. 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.

  19. The Aberdeen Trauma Screening Index: an instrument to predict post-accident psychopathology.

    Science.gov (United States)

    Klein, S; Alexander, D A; Hutchinson, J D; Simpson, J A; Simpson, J M; Bell, J S

    2002-07-01

    A key challenge in trauma care is the prevention of psychopathology. However, no definitive method of identifying individuals at risk of developing psychopathology exists. The Aberdeen Trauma Screening Index (ATSI) is a brief screening tool developed for use in a clinical setting by non-mental health professionals to facilitate the early identification of individuals most at risk of psychopathology 3-months post-accident. The ATSI derived from a prospective study of a 150 out of an initial pool of 213 consecutive admissions to the Orthopaedic Trauma Unit and the Accident and Emergency Department of Aberdeen Royal Infirmary. Potential predictors were identified by a comprehensive assessment conducted within 1-week post-accident. Outcome at 3-months post-accident was measured using 'caseness' according to the General Health Questionnaire (GHQ-28). The ATSI is based on a final model comprising only seven variables with a sensitivity of 79% and specificity of 65%. A predictive index score (0-100) was produced to ensure the practical utility of the ATSI in a clinical setting. A ROC curve was constructed to illustrate the relationship between sensitivity and the specificity values with their corresponding threshold scores. On the basis of a prevalence rate of 55% 'caseness', as identified in the present study, a cut-off point of 45 provides the optimal outcome with a sensitivity value of 70% and a specificity value of 71%. The ATSI can accurately identify those most at risk of developing psychopathology 3-months post-accident in a sample of accidentally injured adult subjects recruited as consecutive admissions to an urban hospital in the North East of Scotland. However, to establish the generalizability of these findings, it is important that the ATSI be validated in both similar and diverse populations.

  20. 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.

  1. Prediction of persistent post-operative pain: Pain-specific psychological variables compared with acute post-operative pain and general psychological variables.

    Science.gov (United States)

    Horn-Hofmann, C; Scheel, J; Dimova, V; Parthum, A; Carbon, R; Griessinger, N; Sittl, R; Lautenbacher, S

    2018-01-01

    Psychological variables and acute post-operative pain are of proven relevance for the prediction of persistent post-operative pain. We aimed at investigating whether pain-specific psychological variables like pain catastrophizing add to the predictive power of acute pain and more general psychological variables like depression. In all, 104 young male patients undergoing thoracic surgery for pectus excavatum correction were studied on the pre-operative day (T0) and 1 week (T1) and 3 months (T2) after surgery. They provided self-report ratings (pain-related: Pain Catastrophizing Scale, Pain Anxiety Symptoms Scale = PASS, Pain Vigilance and Awareness Questionnaire = PVAQ; general psychological: Screening for Somatoform Symptoms, State-Anxiety Inventory-X1, Center for Epidemiologic Studies Depression Scale = CES-D). Additional predictors (T1) as well as criterion variables (T2) were pain intensity (Numerical Rating Scale) and pain disability (Pain Disability Index). Three months after surgery, 25% of the patients still reported clinically relevant pain (pain intensity ≥3) and over 50% still reported pain-related disability. Acute post-operative pain as well as general psychological variables did not allow for a significant prediction of persistent post-operative pain; in contrast, pain-related psychological variables did. The best single predictors were PASS for pain intensity and PVAQ for pain disability. Pain-related psychological variables derived from the fear-avoidance model contributed significantly to the prediction of persistent post-operative pain. The best possible compilation of these measures requires further research. More general psychological variables may become relevant predictors later in the medical history. Our results suggest that pain-specific psychological variables such as pain anxiety and pain hypervigilance add significantly to the prediction of persistent post-operative pain and might even outperform established predictors such as

  2. Organized Physical Activity in Young School Children Predicts Subsequent 4-Year Change in Body Mass Index

    Science.gov (United States)

    Dunton, Genevieve; McConnell, Rob; Jerrett, Michael; Wolch, Jennifer; Lam, Claudia; Gilliland, Frank; Berhane, Kiros

    2012-01-01

    Objective To determine whether participation in organized outdoor team sports and structured indoor non-school activity programs in kindergarten and first grade predicted subsequent 4-year change in Body Mass Index (BMI) across the adiposity rebound period of childhood. Design Longitudinal cohort study. Setting Forty-five schools in 13 communities across Southern California. Participants Largely Hispanic and non-Hispanic white children (N = 4,550; average age at study entry 6.60 years, standard deviation 0.65). Main Exposures Parents completed questionnaires assessing physical activity, demographic characteristics and other relevant covariates at baseline. Data on built and social environmental variables were linked to the neighborhood around children’s homes using geographical information systems (GIS). Main Outcome Measures Each child’s height and weight were measured annually during 4-years of follow-up. Results After adjusting for several confounders, BMI increased at a 0.05 unit per year slower rate for children who participated in outdoor organized team sports at least twice per week as compared to children who did not. For participation in each additional indoor non-school structured activity classes, lessons, and program, BMI increased at a 0.05 unit per year slower rate, and the attained BMI level at age 10 was 0.48 units lower. Conclusions Engagement in organized sports and activity programs as early as kindergarten and the first grade may result in smaller increases in BMI during the adiposity rebound period of childhood. PMID:22869403

  3. Pernambuco index: predictability of the complexity of surgery for impacted lower third molars.

    Science.gov (United States)

    de Carvalho, R W F; Vasconcelos, B C

    2018-02-01

    This study aimed to develop and validate an index of surgical difficulty for the removal of impacted lower third molars. The study was performed in two steps. The first was a cross-sectional analysis of clinical, demographic, and radiographic variables collected from patients undergoing the removal of an impacted lower third molar between 2008 and 2012. The second step was a prospective cohort study involving the same surgical procedures to validate the index; this was performed between 2013 and 2016. Univariate regression analysis was applied, followed by multiple linear regression analysis. A total of 753 surgical procedures were analyzed in the first stage, which led to the identification of the most important variables and their levels of significance. The index was then applied to 280 surgical procedures. The preoperative difficulty was in concordance with the index results in all cases. Among cases with a low level of difficulty, 93.1% had been indexed as low difficulty; likewise, among cases with a high level of difficulty, there was 87.9% concordance with the index. With the use of reference statistics in the development and quality assurance processes, this validated index has proven to be a reliable and easily applicable instrument, with high sensitivity, specificity, and accuracy. Copyright © 2017 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

  4. 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.

  5. Real Time Monitoring and Prediction of the Monsoon Intraseasonal Oscillations: An index based on Nonlinear Laplacian Spectral Analysis Technique

    Science.gov (United States)

    Cherumadanakadan Thelliyil, S.; Ravindran, A. M.; Giannakis, D.; Majda, A.

    2016-12-01

    An improved index for real time monitoring and forecast verification of monsoon intraseasonal oscillations (MISO) is introduced using the recently developed Nonlinear Laplacian Spectral Analysis (NLSA) algorithm. Previous studies has demonstrated the proficiency of NLSA in capturing low frequency variability and intermittency of a time series. Using NLSA a hierarchy of Laplace-Beltrami (LB) eigen functions are extracted from the unfiltered daily GPCP rainfall data over the south Asian monsoon region. Two modes representing the full life cycle of complex northeastward propagating boreal summer MISO are identified from the hierarchy of Laplace-Beltrami eigen functions. These two MISO modes have a number of advantages over the conventionally used Extended Empirical Orthogonal Function (EEOF) MISO modes including higher memory and better predictability, higher fractional variance over the western Pacific, Western Ghats and adjoining Arabian Sea regions and more realistic representation of regional heat sources associated with the MISO. The skill of NLSA based MISO indices in real time prediction of MISO is demonstrated using hindcasts of CFSv2 extended range prediction runs. It is shown that these indices yield a higher prediction skill than the other conventional indices supporting the use of NLSA in real time prediction of MISO. Real time monitoring and prediction of MISO finds its application in agriculture, construction and hydro-electric power sectors and hence an important component of monsoon prediction.

  6. 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

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

    Science.gov (United States)

    Bjørngaard, Johan Håkon; Carslake, David; Lund Nilsen, Tom Ivar; Linthorst, Astrid C E; Davey Smith, George; Gunnell, David; Romundstad, Pål Richard

    2015-01-01

    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 for anxiety.

  8. 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.

  9. Analgesia Nociception Index (ANI) to predict intraoperative haemodynamic changes: results of a pilot investigation.

    Science.gov (United States)

    Ledowski, T; Averhoff, L; Tiong, W S; Lee, C

    2014-01-01

    The Analgesia Nociception Index has been described to reflect different levels of intraoperative nociceptive stimulation during total intravenous anaesthesia. The association between this index and haemodynamic changes during sevoflurane-based anaesthesia was investigated in 30 patients with the hypothesis that changes in the Analgesia Nociception Index may coincide with or even predict haemodynamic changes. The Analgesia Nociception Index as well as blood pressure and heart rate were observed during induction, at skin incision, at times of an Analgesia Noceception Index decrease > 20% ('event') and pre-/post-fentanyl administration. The Analgesia Nociception Index decreased with airway manipulation [mean: 52 (before) vs. 33 (after); P 10% was low (heart rate 0.61; blood pressure 0.59). The Analgesia Nociception Index appears to reflect different levels of stimulation during sevoflurane-based general anaesthesia. However, it was of little predictive value to pre-empt significant haemodynamic changes. © 2013 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

  10. Predicted Thermal Sensation Index for the Hot Environment in the Spinning Workshop

    Directory of Open Access Journals (Sweden)

    Rui-Liang Yang

    2015-01-01

    Full Text Available The spinning workshop is the most typical cotton textile workshop in the textile mill and is characterized by the feature of high temperature all the year. To effectively evaluate the general thermal sensation of the textile worker exposed to the hot environment in the spinning workshop, a new heat index named predicted thermal sensation (PTS index was proposed in this paper. The PTS index based on the heat balance equation can be derived by the empirical equations of air temperature and heat imbalance. A one-month-long continuous research was carried out to investigate the actual thermal condition and judge the validity of the PTS index. Actual workshop temperatures in the spinning workshop during the measuring period were all above 32°C, belonging to extreme hot environment. The calculated thermal sensation by the PTS index is very close to the actual thermal sensation, which means that the PTS index can accurately estimate the actual thermal sensation of the textile workers exposed to the hot environment in the spinning workshop. Compared to other indices, the PTS index can more effectively predict the mean thermal response of a large group of textile workers exposed to the hot environment in the spinning workshop.

  11. Response variability in rapid automatized naming predicts reading comprehension.

    Science.gov (United States)

    Li, James J; Cutting, Laurie E; Ryan, Matthew; Zilioli, Monica; Denckla, Martha B; Mahone, E Mark

    2009-10-01

    A total of 37 children ages 8 to 14 years, screened for word-reading difficulties (23 with attention-deficit/hyperactivity disorder, ADHD; 14 controls) completed oral reading and rapid automatized naming (RAN) tests. RAN trials were segmented into pause and articulation time and intraindividual variability. There were no group differences on reading or RAN variables. Color- and letter-naming pause times and number-naming articulation time were significant predictors of reading fluency. In contrast, number and letter pause variability were predictors of comprehension. Results support analysis of subcomponents of RAN and add to literature emphasizing intraindividual variability as a marker for response preparation, which has relevance to reading comprehension.

  12. [Behavior of predictive variables of exacerbations of the COPD in the neumological hospital of Cuba.

    Science.gov (United States)

    León Valdivies, Yusbiel José; Sánchez de la Osa, Reinaldo B; Garcia Silvera, Eberto; Machado Molina, Delfina; Oses Herrera, Liliana

    2017-01-01

    The use of predictive variables of exacerbations of the COPD is not a practice generalized in our environment, for what we cannot characterize the exacerbating patient neither to design strategies for its integral handling. There was carried out a prospective descriptive study to correlate in patient with diagnosis of COPD from the Neumologic Hospital of Cuba, with the objective of determining the association between clinical, functional variables and imagenological and the exacerbations frequency a year. The population was constituted for patients with clinical diagnosis of COPD and the sample for those patients with confirmed diagnosis that they completed the inclusion approaches. The correlation among the variables was carried out by means of the Coefficient of Correlation of Pearson with an interval of Trust of 95% and the test t student with a significance level (p) smaller than 0.05. 81.82% of the very serious patients are exacerbating with emphysema. 75% of the patients with index of the lung artery / aorta have more than two exacerbations a year. 84.61% of the patient exacerbating presented degree four of the dyspnea. The half pressure of the lung artery next to the VEF1 constituted the best exacerbations predictors in the group of studied patients.

  13. 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.

  14. Apnea-hypopnea index as the outcome variable in multiple linear regression analysis: statistical issues.

    Science.gov (United States)

    Chan, Chung-hong; Ng, Daniel K

    2007-08-01

    It is common for apnea-hypopnea index (AHI) to be used as an outcome variable in ordinary least squares linear regression. However, the distribution of AHI is not tested. The assumption of ordinary least squares linear regression may be violated. The distribution of AHI from a pediatric sleep laboratory was assessed by Kolomgorov-Smirnov test. Transformation of AHI was attempted. In addition, we fitted an ordinary linear regression model (OLSM) and negative binomial regression model (NBRM) of the relationship between body mass index and the rate of apnea and hypopnea events. OLSM and NBRM were evaluated by residuals analysis. AHI from the studied population deviated significantly from normal distribution. Commonly used transformation algorithm could not transform AHI to normal distribution. In addition, OLSM violated the underlying statistical assumptions of homogeneity of variance and normality of error. NBRM, on the other hand, was not restricted by these assumptions. The current study suggested AHI is not likely to be normally distributed and its distribution cannot be transformed to normal. Negative binomial regression of the total number of apnea and hypopnea with an offset of log TST should be used in data analysis. 2007 Wiley-Liss, Inc.

  15. Assessing the Influence of Sleep-Wake Variables on Body Mass Index (BMI in Adolescents

    Directory of Open Access Journals (Sweden)

    Christoph Randler

    2013-05-01

    Full Text Available Recent work has established an association between overweight/obesity and sleep duration, suggesting that short sleep duration and timing of sleeping may lead to overweight. Most of these studies considered sleep-length rather than any other aspects associated with the sleep and wake rhythm, e.g. chronotype, which is a measure of timing of sleeping (‘when to sleep’; based on the midpoint of sleep. The objective of this study was to assess the influence of different factors of the sleep-wake cycle and of co-variates on the Body Mass Index in a cross-sectional questionnaire study. Nine hundred and thirteen pupils (406 boys, 507 girls from Southwestern Germany participated in this study. Mean age was 13.7 ± 1.5 (SD years and range was between 11 – 16 years. We found that chronotype (β = .079 and social jetlag (β = .063 showed a significant influence on Body Mass Index (BMI, while sleep duration did not. Social jetlag is the absolute difference between mid-sleep time on workdays and free days. Further, screen time (in front of TV, computer, β = .13 was positively related with BMI. Self-efficacy on nutrition (β = -.11, a psychological variable important in health-behaviour models, showed an influence with high scores on self-efficacy related to lower BMI. A high BMI was correlated with low fast-food consumption (β = -.12 suggesting that adolescents with high BMI may exert some control over their eating.

  16. Important meteorological variables for statistical long-term air quality prediction in eastern China

    Science.gov (United States)

    Zhang, Libo; Liu, Yongqiang; Zhao, Fengjun

    2017-09-01

    Weather is an important factor for air quality. While there have been increasing attentions to long-term (monthly and seasonal) air pollution such as regional hazes from land-clearing fires during El Niño, the weather-air quality relationships are much less understood at long-term than short-term (daily and weekly) scales. This study is aimed to fill this gap through analyzing correlations between meteorological variables and air quality at various timescales. A regional correlation scale was defined to measure the longest time with significant correlations at a substantial large number of sites. The air quality index (API) and five meteorological variables during 2001-2012 at 40 eastern China sites were used. The results indicate that the API is correlated to precipitation negatively and air temperature positively across eastern China, and to wind, relative humidity and air pressure with spatially varied signs. The major areas with significant correlations vary with meteorological variables. The correlations are significant not only at short-term but also at long-term scales, and the important variables are different between the two types of scales. The concurrent regional correlation scales reach seasonal at p air temperature and relative humidity. Precipitation, which was found to be the most important variable for short-term air quality conditions, and air pressure are not important for long-term air quality. The lagged correlations are much smaller in magnitude than the concurrent correlations and their regional correction scales are at long term only for wind speed and relative humidity. It is concluded that wind speed should be considered as a primary predictor for statistical prediction of long-term air quality in a large region over eastern China. Relative humidity and temperature are also useful predictors but at less significant levels.

  17. Index Prediction in Tehran Stock Exchange Using Hybrid Model of Artificial Neural Networks and Genetic Algorithms

    OpenAIRE

    Farzad Karimi; Mohsen Dastgir; Monireh Shariati

    2014-01-01

    Nowadays, investment in the bource organizes the important part of country economy. So the prediction of stocks index is very important for stockholders to earn the highest return from their investment. The changes of stock market influence by several factors such as political, economical and social factors and maybe, using the classic methods for stock market prediction result in exact results. Since, the intelligent method have this capability that consider the complex effects of above fact...

  18. Is the h-index predictive of greater NIH funding success among academic radiologists?

    Science.gov (United States)

    Rezek, Issa; McDonald, Robert J; Kallmes, David F

    2011-11-01

    Despite rapid adoption of the Hirsch index (h-index) as a measure of academic success, the correlations between the h-index and other metrics of productivity remain poorly understood. The aims of this study were to determine whether h-indices were associated with greater National Institutes of Health (NIH) funding success among academic radiologists. Using the Scopus database, h-indices were calculated for a random sample of academic radiologists with the rank of professor. Using the NIH tool Research Portfolio Online Reporting Tools Expenditures and Reports, we determined the number, classification, and total years of NIH grant funding as principal investigator for each radiologist. Differences in h-index, sorted by funding status, were determined using Wilcoxon's tests. Associations between h-index and funding status were determined using logistic regression. Significant correlations between h-index and grant metrics were determined using Spearman's ρ. Among 210 professors of radiology, 48 (23%) secured at least one NIH grant. The mean h-index was significantly higher among individuals who secured at least one NIH grant (19.1) compared to those who did not (10.4) (P 10 were significantly less likely to receive NIH funding (odds ratio, 0.07; P = .0321). However, h-indices > 10 were not significantly predictive of greater funding. No significant relationships were observed between h-index and the number of grant awards, years of prior funding, the amounts of grant awards, or grant classification. Having obtained at least one NIH grant was associated with a higher h-index, yet multiple or large grants, such as those for program projects, were not predictive of higher h-indices. Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.

  19. Standard mandibular canine index of the Malaysian Indian student used for sex prediction in forensic dentistry

    Directory of Open Access Journals (Sweden)

    Beh Wee Ren

    2010-03-01

    Full Text Available Identification of the unknown body is a medical, legal and humane responsibility of the forensic team to evaluate data relevant to the identification. The purpose of this research was to obtain necessary data to compute and analyze the Mandibular Canine Index (MCI between Malaysian Indian males and females studying in Universitas Padjadjaran as well as to determine the Standard Mandibular Canine Index (Standard MCI for the Malaysian Indian community. This research used a descriptive and analytical survey approach and was done though a stratified random proportional sampling technique. The result of this research established a statistical significant difference between males and females Mandibular Canine Index (MCI with the level of confidence of 95% with the mean of males as 0.260±0.019 and females as 0.236±0.012. The Standard Mandibular Canine Index of the Malaysian Indian community was 0.248. The overall success to predict the sex using this Standard Mandibular Canine Index was 76.67%. It was concluded that Standard Mandibular Canine Index could be used for sex prediction as a supporting technique.

  20. Prioritizing Highway Safety Manual's crash prediction variables using boosted regression trees.

    Science.gov (United States)

    Saha, Dibakar; Alluri, Priyanka; Gan, Albert

    2015-06-01

    The Highway Safety Manual (HSM) recommends using the empirical Bayes (EB) method with locally derived calibration factors to predict an agency's safety performance. However, the data needs for deriving these local calibration factors are significant, requiring very detailed roadway characteristics information. Many of the data variables identified in the HSM are currently unavailable in the states' databases. Moreover, the process of collecting and maintaining all the HSM data variables is cost-prohibitive. Prioritization of the variables based on their impact on crash predictions would, therefore, help to identify influential variables for which data could be collected and maintained for continued updates. This study aims to determine the impact of each independent variable identified in the HSM on crash predictions. A relatively recent data mining approach called boosted regression trees (BRT) is used to investigate the association between the variables and crash predictions. The BRT method can effectively handle different types of predictor variables, identify very complex and non-linear association among variables, and compute variable importance. Five years of crash data from 2008 to 2012 on two urban and suburban facility types, two-lane undivided arterials and four-lane divided arterials, were analyzed for estimating the influence of variables on crash predictions. Variables were found to exhibit non-linear and sometimes complex relationship to predicted crash counts. In addition, only a few variables were found to explain most of the variation in the crash data. Published by Elsevier Ltd.

  1. 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.

  2. Climatic variability of a fire-weather index based on turbulent kinetic energy and the Haines Index

    Science.gov (United States)

    Warren E. Heilman; Xindi Bian

    2010-01-01

    Combining the Haines Index (HI) with near-surface turbulent kinetic energy (TKEs) through a product of the two values (HITKEs) has shown promise as an indicator of the atmospheric potential for extreme and erratic fire behavior in the U.S. Numerical simulations of fire-weather evolution during past wildland fire episodes in...

  3. Accuracy of body mass index in predicting pre-eclampsia: bivariate meta-analysis

    NARCIS (Netherlands)

    Cnossen, J. S.; Leeflang, M. M. G.; de Haan, E. E. M.; Mol, B. W. J.; van der Post, J. A. M.; Khan, K. S.; ter Riet, G.

    2007-01-01

    OBJECTIVE: The objective of this study was to determine the accuracy of body mass index (BMI) (pre-pregnancy or at booking) in predicting pre-eclampsia and to explore its potential for clinical application. DESIGN: Systematic review and bivariate meta-analysis. SETTING: Medline, Embase, Cochrane

  4. Predicting postoperative complications after bariatric surgery: the Bariatric Surgery Index for Complications, BASIC

    NARCIS (Netherlands)

    Coblijn, U.K. (Usha K.); J. Karres (Julian); de Raaff, C.A.L. (Christel A. L.); S.M.M. de Castro (Steve); S.M. Lagarde (Sjoerd); W.F. van Tets (Willem); H.J. Bonjer (H. Jaap); B.A. van Wagensveld (Bart)

    2017-01-01

    textabstractBackground: Around 20% of bariatric surgery patients develop a short- or long-term complication. Objective: Aim of this study was to develop a risk model predicting complications: the Bariatric Surgery Index for Complications (BASIC). Setting: The Obesity Center Amsterdam, located in a

  5. Stock Index Returns' Density Prediction using GARCH Models: Frequentist or Bayesian Estimation?

    NARCIS (Netherlands)

    L.F. Hoogerheide (Lennart); D. David (David); N. Corre (Nienke)

    2011-01-01

    textabstractUsing well-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is found between the qualities of the forecasts of the whole density, whereas the Bayesian

  6. 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

  7. 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

  8. Treatment success in neck pain: The added predictive value of psychosocial variables in addition to clinical variables.

    Science.gov (United States)

    Groeneweg, Ruud; Haanstra, Tsjitske; Bolman, Catherine A W; Oostendorp, Rob A B; van Tulder, Maurits W; Ostelo, Raymond W J G

    2017-01-01

    Identification of psychosocial variables may influence treatment outcome. The objective of this study was to prospectively examine whether psychosocial variables, in addition to clinical variables (pain, functioning, general health, previous neck pain, comorbidity), are predictive factors for treatment outcome (i.e. global perceived effect, functioning and pain) in patients with sub-acute and chronic non-specific neck pain undergoing physical therapy or manual therapy. Psychosocial factors included treatment outcome expectancy and treatment credibility, health locus of control, and fear avoidance beliefs. This study reports a secondary analysis of a primary care-based pragmatic randomized controlled trial. Potential predictors were measured at baseline and outcomes, in 181 patients, at 7 weeks and 26 weeks. Hierarchical logistic regression models showed that treatment outcome expectancy predicted outcome success, in addition to clinical and demographic variables. Expectancy explained additional variance, ranging from 6% (pain) to 17% (functioning) at 7 weeks, and 8% (pain) to 16% (functioning) at 26 weeks. Locus of control and fear avoidance beliefs did not add significantly to predicting outcome. Based on the results of this study we conclude that outcome expectancy, in patients with non-specific sub-acute and chronic neck pain, has additional predictive value for treatment success above and beyond clinical and demographic variables. Psychological processes, health perceptions and how these factors relate to clinical variables may be important for treatment decision making regarding therapeutic options for individual patients. Copyright © 2016 Scandinavian Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  9. Predicting Ozone Uptake from Meteorological and Environmental Variables.

    Science.gov (United States)

    Fredericksen, T S; Skelly, J M; Snyder, K R; Steiner, K C; Kolb, T E

    1996-05-01

    Predictions of foliar ozone uptake rates of seedling and canopy black cherry trees (Prunus serotina Ehrh.) were made using concurrent measurements of ambient ozone concentration and other environmental and meteorological data during two growing seasons in north-central Pennsylvania.

  10. Anxiety Sensitivity Index (ASI-3) subscales predict unique variance in anxiety and depressive symptoms.

    Science.gov (United States)

    Olthuis, Janine V; Watt, Margo C; Stewart, Sherry H

    2014-03-01

    Anxiety sensitivity (AS) has been implicated in the development and maintenance of a range of mental health problems. The development of the Anxiety Sensitivity Index - 3, a psychometrically sound index of AS, has provided the opportunity to better understand how the lower-order factors of AS - physical, psychological, and social concerns - are associated with unique forms of psychopathology. The present study investigated these associations among 85 treatment-seeking adults with high AS. Participants completed measures of AS, anxiety, and depression. Multiple regression analyses controlling for other emotional disorder symptoms revealed unique associations between AS subscales and certain types of psychopathology. Only physical concerns predicted unique variance in panic, only cognitive concerns predicted unique variance in depressive symptoms, and social anxiety was predicted by only social concerns. Findings emphasize the importance of considering the multidimensional nature of AS in understanding its role in anxiety and depression and their treatment. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Increased non-Gaussianity of heart rate variability predicts cardiac mortality after an acute myocardial infarction

    Directory of Open Access Journals (Sweden)

    Junichiro eHayano

    2011-09-01

    Full Text Available Non-Gaussianity index (λ is a new index of heart rate variability (HRV that characterizes increased probability of the large heart rate deviations from its trend. A previous study has reported that increased λ is an independent mortality predictor among patients with chronic heart failure. The present study examined predictive value of λ in patients after acute myocardial infarction (AMI. Among 670 post-AMI patients, we performed 24-hr Holter monitoring to assess λ and other HRV predictors, including standard deviation of normal-to-normal interval, very-low frequency power, scaling exponent α1 of detrended fluctuation analysis, deceleration capacity, and heart rate turbulence (HRT. At baseline, λ was not correlated substantially with other HRV indices (|r| <0.4 with either indices and was decreased in patients taking β-blockers (P = 0.04. During a median follow up period of 25 months, 45 (6.7% patients died (32 cardiac and 13 non-cardiac and 39 recurrent nonfatal AMI occurred among survivors. While all of these HRV indices but λ were significant predictors of both cardiac and non-cardiac deaths, increased λ predicted exclusively cardiac death (RR [95% CI], 1.6 [1.3-2.0] per 1 SD increment, P <0.0001. The predictive power of increased λ was significant even after adjustments for clinical risk factors, such as age, diabetes, left ventricular function, renal function, prior AMI, heart failure, and stroke, Killip class, and treatment ([95% CI], 1.4 [1.1-2.0] per 1 SD increment, P = 0.01. The prognostic power of increased λ for cardiac death was also independent of all other HRV indices and the combination of increased λ and abnormal HRT provided the best predictive model for cardiac death. Neither λ nor other HRV indices was an independent predictor of AMI recurrence. Among post-AMI patients, increased λ is associated exclusively with increased cardiac mortality risk and its predictive power is independent of clinical risk factors and

  12. 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

    2017-12-06

    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.

  13. The Geriatric Nutritional Risk Index Predicts Survival in Elderly Esophageal Squamous Cell Carcinoma Patients with Radiotherapy.

    Science.gov (United States)

    Bo, Yacong; Wang, Kunlun; Liu, Yang; You, Jie; Cui, Han; Zhu, Yiwei; Lu, Quanjun; Yuan, Ling

    2016-01-01

    The impact of nutritional status on survival among elderly esophageal squamous cell carcinoma (ESCC) patients undergoing radiotherapy is unclear. In this study, we aimed at validating the performance of the geriatric nutritional risk index (GNRI) in predicting overall survival time in elderly ESCC patients with radiotherapy. A retrospective cohort study was conducted on 239 ESCC patients aged 60 and over admitted consecutively from January 2008 to November 2014 in the Department of Radiotherapy, Henan Tumor Hospital (Affiliated Tumor Hospital of Zhengzhou University), Zhengzhou, Henan, China. All patients were subjected to nutritional screening using GNRI, and were followed for the occurrence of lymphatic node metastasis, radiation complication and mortality. The Kaplan-Meier method with Log-rank test was used to estimate survival curves. Univariable Cox regression analysis was used to identify variables associated with overall survival time. Among the 239 patients, 184 patients (76.9%) took no nutritional risk, 32 patients (13.4%) took moderate risk of malnutrition, and 23 patients (9.7%) took a high risk of malnutrition. Univariable Cox regression showed that both high nutritional risk group and moderate nutritional risk group were significantly less likely to survive than no nutritional risk patients (hazard ratio (HR) = 1.688, 95% confidence interval (CI) = 1.019-2.798 for moderate risk group, and HR = 2.699, 95% CI = 1.512-4.819 for high risk group, respectively). The GNRI is an independent prognostic factor for overall survival time in elderly ESCC patients with radiotherapy. A GNRI ≤98 can be suggested as an indicator of surviving less.

  14. Systemic inflammation response index (SIRI) predicts prognosis in hepatocellular carcinoma patients

    Science.gov (United States)

    Xu, Litao; Yu, Shulin; Zhuang, Liping; Wang, Peng; Shen, Yehua; Lin, Junhua; Meng, Zhiqiang

    2017-01-01

    The systemic inflammation response index (SIRI) is a useful tool for predicting prognosis in some types of cancer. In this retrospective study, we evaluated the efficacy of SIRI in predicting overall survival in hepatocellular carcinoma (HCC) patients following local or systemic therapy. A cutoff value of 1.05 was identified for SIRI using ROC analysis in a training patient cohort. In the validation cohort, survival analysis revealed that median overall survival was longer in HCC patients with SIRI scores SIRI was associated with overall survival and was more predictive of overall survival that the AFP level or Child-Pugh score. However, SIRI and Barcelona Clinic Liver Cancer (BCLC) stage were equally effective for predicting survival. In addition, HCC patients with BCLC stage C had higher SIRI scores and poorer overall survival. SIRI also correlated with liver function parameters. Thus SIRI may be a convenient, low cost and reliable tumor marker for predicting prognosis in HCC patients. PMID:28430597

  15. The Best Use of the Charlson Comorbidity Index With Electronic Health Care Database to Predict Mortality.

    Science.gov (United States)

    Bannay, Aurélie; Chaignot, Christophe; Blotière, Pierre-Olivier; Basson, Mickaël; Weill, Alain; Ricordeau, Philippe; Alla, François

    2016-02-01

    The most used score to measure comorbidity is the Charlson index. Its application to a health care administrative database including International Classification of Diseases, 10th edition (ICD-10) codes, medical procedures, and medication required studying its properties on survival. Our objectives were to adapt the Charlson comorbidity index to the French National Health Insurance database to predict 1-year mortality of discharged patients and to compare discrimination and calibration of different versions of the Charlson index. Our cohort included all adults discharged from a hospital stay in France in 2010 registered in the French National Health Insurance general scheme. The pathologies of the Charlson index were identified through ICD-10 codes of discharge diagnoses and long-term disease, specific medical procedures, and reimbursement of specific medications in the past 12 months before inclusion. We included 6,602,641 subjects at the date of their first discharge from medical, surgical, or obstetrical department in 2010. One-year survival was 94.88%, decreasing from 98.41% for Charlson index of 0-71.64% for Charlson index of ≥5. With a discrimination of 0.91 and an appropriate calibration curve, we retained the crude Cox model including the age-adjusted Charlson index as a 4-level score. Our study is the first to adapt the Charlson index to a large health care database including >6 million of inpatients. When mortality is the outcome, we recommended using the age-adjusted Charlson index as 4-level score to take into account comorbidities.

  16. Predicting the difficulty of a transvenous lead extraction procedure: Validation of the LED index.

    Science.gov (United States)

    Bontempi, Luca; Vassanelli, Francesca; Cerini, Manuel; Inama, Lorenza; Salghetti, Francesca; Giacopelli, Daniele; Gargaro, Alessio; Raweh, Abdallah; Curnis, Antonio

    2017-07-01

    A lead extraction difficulty (LED) score was proposed to predict the difficult transvenous lead extraction (TLE) procedures, defined by means of the fluoroscopy time. The aim of this study was to validate the estimation model based on the LED index above 10 on an independent data set of TLE cases. Consecutive patients undergoing TLE between January 2014 and January 2016 were included in this analysis. The fluoroscopy time related to the leads removal was dichotomized as above or below its 90th percentile (PCTL). In total, 446 permanent leads were removed during 233 TLE procedures. Complete procedural success was achieved in 232 (99.1%) patients. The LED index resulted >10 in 83(35.6%) procedures. Among these cases, 20 had fluoroscopy time above the 90th PCTL (23.3 minutes) and were classified as true positive. Over the 150 procedures with LED score LED index in predicting complex cases resulted 86.9 (confidence interval [CI] 66.4-97.2)%, 70.0 (CI 63.3-76.1)%, and 98.0 (CI 94.3-99.6)%, respectively. The multivariate logistic regression analysis confirmed a 12% increased risk of high fluoroscopy for each additional point of the LED score (OR 1.12, CI 1.05-1.21, P = 0.001). The validation of the estimation model based on the LED index <10 confirmed its high efficacy in predicting simple TLE procedures. © 2017 Wiley Periodicals, Inc.

  17. Geriatric nutritional risk index accurately predicts cardiovascular mortality in incident hemodialysis patients.

    Science.gov (United States)

    Takahashi, Hiroshi; Ito, Yasuhiko; Ishii, Hideki; Aoyama, Toru; Kamoi, Daisuke; Kasuga, Hirotake; Yasuda, Kaoru; Maruyama, Shoichi; Matsuo, Seiichi; Murohara, Toyoaki; Yuzawa, Yukio

    2014-07-01

    Cardiovascular disease (CVD) is a leading cause of death in end-stage renal disease (ESRD) patients. Protein-energy wasting (PEW) or malnutrition is common in this population, and is associated with increasing risk of mortality. The geriatric nutritional risk index (GNRI) has been developed as a tool to assess the nutritional risk, and is associated with mortality not only in elderly patients but also in ESRD patients. However, whether the GNRI could predict the mortality due to CVD remains unclear in this population. We investigated the prognostic value of GNRI at initiation of hemodialysis (HD) therapy for CVD mortality in a large cohort of ESRD patients. Serum albumin, body weight, and height for calculating GNRI were measured in 1568 ESRD patients. Thereafter, the patients were divided into quartiles according to GNRI levels [quartile 1 (Q1): 97.3], and were followed up for up to 10 years. GNRI levels independently correlated with serum C-reactive-protein levels (β = -0.126, p index was also greater in an established CVD risk model with GNRI (0.749) compared to that with albumin (0.730), body mass index (0.732), and alone (0.710). Similar results were observed for all-cause mortality. GNRI at initiation of HD therapy could predict CVD mortality with incremental value of the predictability compared to serum albumin and body mass index in ESRD patients. Copyright © 2013 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

  18. Intelligent Monitoring System on Prediction of Building Damage Index using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Reni Suryanita

    2012-03-01

    Full Text Available An earthquake potentially destroys a tall building. The building damage can be indexed by FEMA into three categories namely Immediate Occupancy (IO, Life Safety (LS, and Collapse Prevention (CP. To determine the damage index, the building model has been simulated into structure analysis software. Acceleration data has been analyzed using non linear method in structure analysis program. The earthquake load is time history at surface, PGA=0105g. This work proposes an intelligent monitoring system utilizing Artificial Neural Network to predict the building damage index. The system also provides an alert system and notification to inform the status of the damage. Data learning is trained on ANN utilizing feed forward and back propagation algorithm. The alert system is designed to be able to activate the alarm sound, view the alert bar or text, and send notification via email to the security or management. The system is tested using sample data represented in three conditions involving IO, LS, and CP. The results show that the proposed intelligent monitoring system could provide prediction of up to 92% rate of accuracy and activate the alert. Implementation of the system in building monitoring would allow for rapid, intelligent and accurate prediction of the building damage index due to earthquake.

  19. 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.

  20. Possible Influence of Volcanic Activity on the Decadal Potential Predictability of the Natural Variability in Near-Term Climate Predictions

    Directory of Open Access Journals (Sweden)

    Hideo Shiogama

    2010-01-01

    Full Text Available Initialization based on data assimilations using historical observations possibly improves near-term climate predictions. Significant volcanic activity in the future is unpredictable and not assumed in future climate predictions. To examine the possible influence of unpredictable future volcanic activity on the decadal potential predictability of the natural variability, we performed a 2006–2035 climate prediction experiment with the assumption that the 1991  Mt. Pinatubo eruption would take place again in 2010. The Pinatubo forcing induced not only significant cooling responses but also considerable noises in the natural variability. The errors due to the Pinatubo forcing grew faster than that arising from imperfect knowledge of the observed state, leading to a rapid reduction of the decadal potential predictability of the natural variability.

  1. Predicting drought in an agricultural watershed given climate variability

    Science.gov (United States)

    Changes in the future hydrologic cycle due to changes in temperature (T) and precipitation (P) are likely to be associated with increases in hydrologic extremes. This study evaluates the impacts of climate variability on drought using the Soil and Water Assessment Tool (SWAT) in Goodwater Creek Expe...

  2. 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 ...

  3. Predicting Classroom Communication Anxiety through Students' Motivational Variables.

    Science.gov (United States)

    Tussey, Jim

    Anxiety has been shown to have detrimental effects on students in the classroom. This study examined the relations between motivational variables and anxiety. In particular, this study utilized goal orientation theory to examine whether the personal goals a student adopts and the goal structures a student perceives in the classroom are predictors…

  4. Using neural networks for prediction of air pollution index in industrial city

    Science.gov (United States)

    Rahman, P. A.; Panchenko, A. A.; Safarov, A. M.

    2017-10-01

    This scientific paper is dedicated to the use of artificial neural networks for the ecological prediction of state of the atmospheric air of an industrial city for capability of the operative environmental decisions. In the paper, there is also the described development of two types of prediction models for determining of the air pollution index on the basis of neural networks: a temporal (short-term forecast of the pollutants content in the air for the nearest days) and a spatial (forecast of atmospheric pollution index in any point of city). The stages of development of the neural network models are briefly overviewed and description of their parameters is also given. The assessment of the adequacy of the prediction models, based on the calculation of the correlation coefficient between the output and reference data, is also provided. Moreover, due to the complexity of perception of the «neural network code» of the offered models by the ordinary users, the software implementations allowing practical usage of neural network models are also offered. It is established that the obtained neural network models provide sufficient reliable forecast, which means that they are an effective tool for analyzing and predicting the behavior of dynamics of the air pollution in an industrial city. Thus, this scientific work successfully develops the urgent matter of forecasting of the atmospheric air pollution index in industrial cities based on the use of neural network models.

  5. Effect of Water Invasion on Outburst Predictive Index of Low Rank Coals in Dalong Mine.

    Directory of Open Access Journals (Sweden)

    Jingyu Jiang

    Full Text Available To improve the coal permeability and outburst prevention, coal seam water injection and a series of outburst prevention measures were tested in outburst coal mines. These methods have become important technologies used for coal and gas outburst prevention and control by increasing the external moisture of coal or decreasing the stress of coal seam and changing the coal pore structure and gas desorption speed. In addition, techniques have had a significant impact on the gas extraction and outburst prevention indicators of coal seams. Globally, low rank coals reservoirs account for nearly half of hidden coal reserves and the most obvious feature of low rank coal is the high natural moisture content. Moisture will restrain the gas desorption and will affect the gas extraction and accuracy of the outburst prediction of coals. To study the influence of injected water on methane desorption dynamic characteristics and the outburst predictive index of coal, coal samples were collected from the Dalong Mine. The methane adsorption/desorption test was conducted on coal samples under conditions of different injected water contents. Selective analysis assessed the variations of the gas desorption quantities and the outburst prediction index (coal cutting desorption index. Adsorption tests indicated that the Langmuir volume of the Dalong coal sample is ~40.26 m3/t, indicating a strong gas adsorption ability. With the increase of injected water content, the gas desorption amount of the coal samples decreased under the same pressure and temperature. Higher moisture content lowered the accumulation desorption quantity after 120 minutes. The gas desorption volumes and moisture content conformed to a logarithmic relationship. After moisture correction, we obtained the long-flame coal outburst prediction (cutting desorption index critical value. This value can provide a theoretical basis for outburst prediction and prevention of low rank coal mines and similar

  6. Effect of Water Invasion on Outburst Predictive Index of Low Rank Coals in Dalong Mine

    Science.gov (United States)

    Jiang, Jingyu; Cheng, Yuanping; Mou, Junhui; Jin, Kan; Cui, Jie

    2015-01-01

    To improve the coal permeability and outburst prevention, coal seam water injection and a series of outburst prevention measures were tested in outburst coal mines. These methods have become important technologies used for coal and gas outburst prevention and control by increasing the external moisture of coal or decreasing the stress of coal seam and changing the coal pore structure and gas desorption speed. In addition, techniques have had a significant impact on the gas extraction and outburst prevention indicators of coal seams. Globally, low rank coals reservoirs account for nearly half of hidden coal reserves and the most obvious feature of low rank coal is the high natural moisture content. Moisture will restrain the gas desorption and will affect the gas extraction and accuracy of the outburst prediction of coals. To study the influence of injected water on methane desorption dynamic characteristics and the outburst predictive index of coal, coal samples were collected from the Dalong Mine. The methane adsorption/desorption test was conducted on coal samples under conditions of different injected water contents. Selective analysis assessed the variations of the gas desorption quantities and the outburst prediction index (coal cutting desorption index). Adsorption tests indicated that the Langmuir volume of the Dalong coal sample is ~40.26 m3/t, indicating a strong gas adsorption ability. With the increase of injected water content, the gas desorption amount of the coal samples decreased under the same pressure and temperature. Higher moisture content lowered the accumulation desorption quantity after 120 minutes. The gas desorption volumes and moisture content conformed to a logarithmic relationship. After moisture correction, we obtained the long-flame coal outburst prediction (cutting desorption) index critical value. This value can provide a theoretical basis for outburst prediction and prevention of low rank coal mines and similar occurrence conditions

  7. Predicting hydrological signatures in ungauged catchments using spatial interpolation, index model, and rainfall-runoff modelling

    Science.gov (United States)

    Zhang, Yongqiang; Vaze, Jai; Chiew, Francis H. S.; Teng, Jin; Li, Ming

    2014-09-01

    Understanding a catchment's behaviours in terms of its underlying hydrological signatures is a fundamental task in surface water hydrology. It can help in water resource management, catchment classification, and prediction of runoff time series. This study investigated three approaches for predicting six hydrological signatures in southeastern Australia. These approaches were (1) spatial interpolation with three weighting schemes, (2) index model that estimates hydrological signatures using catchment characteristics, and (3) classical rainfall-runoff modelling. The six hydrological signatures fell into two categories: (1) long-term aggregated signatures - annual runoff coefficient, mean of log-transformed daily runoff, and zero flow ratio, and (2) signatures obtained from daily flow metrics - concavity index, seasonality ratio of runoff, and standard deviation of log-transformed daily flow. A total of 228 unregulated catchments were selected, with half the catchments randomly selected as gauged (or donors) for model building and the rest considered as ungauged (or receivers) to evaluate performance of the three approaches. The results showed that for two long-term aggregated signatures - the log-transformed daily runoff and runoff coefficient, the index model and rainfall-runoff modelling performed similarly, and were better than the spatial interpolation methods. For the zero flow ratio, the index model was best and the rainfall-runoff modelling performed worst. The other three signatures, derived from daily flow metrics and considered to be salient flow characteristics, were best predicted by the spatial interpolation methods of inverse distance weighting (IDW) and kriging. Comparison of flow duration curves predicted by the three approaches showed that the IDW method was best. The results found here provide guidelines for choosing the most appropriate approach for predicting hydrological behaviours at large scales.

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

    African Journals Online (AJOL)

    Results indicate that the model as used is very safe for the prediction of fibre reinforced concrete and with associated small or negligible failure probabilities, since safety indices ranged between 25 and 160 for fibres fracture without bending, while it ranges between 2 and 4 for fibres fracture with pullout and bending. Also ...

  9. Relationship of Some Variables in Predicting Pre-Service Teachers ...

    African Journals Online (AJOL)

    The study examines the extent to which the relationship between pre-service Nigerian Certificate in Education (NCE) teachers' academic level, college specialization and gender could predict their problem solving performance in chemistry. The sample for the study involved two hundred and four, 200 and 300 level, ...

  10. 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.”

  11. Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia

    Science.gov (United States)

    Deo, Ravinesh C.; Şahin, Mehmet

    2015-02-01

    The prediction of future drought is an effective mitigation tool for assessing adverse consequences of drought events on vital water resources, agriculture, ecosystems and hydrology. Data-driven model predictions using machine learning algorithms are promising tenets for these purposes as they require less developmental time, minimal inputs and are relatively less complex than the dynamic or physical model. This paper authenticates a computationally simple, fast and efficient non-linear algorithm known as extreme learning machine (ELM) for the prediction of Effective Drought Index (EDI) in eastern Australia using input data trained from 1957-2008 and the monthly EDI predicted over the period 2009-2011. The predictive variables for the ELM model were the rainfall and mean, minimum and maximum air temperatures, supplemented by the large-scale climate mode indices of interest as regression covariates, namely the Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and the Indian Ocean Dipole moment. To demonstrate the effectiveness of the proposed data-driven model a performance comparison in terms of the prediction capabilities and learning speeds was conducted between the proposed ELM algorithm and the conventional artificial neural network (ANN) algorithm trained with Levenberg-Marquardt back propagation. The prediction metrics certified an excellent performance of the ELM over the ANN model for the overall test sites, thus yielding Mean Absolute Errors, Root-Mean Square Errors, Coefficients of Determination and Willmott's Indices of Agreement of 0.277, 0.008, 0.892 and 0.93 (for ELM) and 0.602, 0.172, 0.578 and 0.92 (for ANN) models. Moreover, the ELM model was executed with learning speed 32 times faster and training speed 6.1 times faster than the ANN model. An improvement in the prediction capability of the drought duration and severity by the ELM model was achieved. Based on these results we aver that out of the two machine learning

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

    Science.gov (United States)

    Bjørngaard, Johan Håkon; Carslake, David; Lund Nilsen, Tom Ivar; Linthorst, Astrid C. E.; Davey Smith, George; Gunnell, David; Romundstad, Pål Richard

    2015-01-01

    Objective 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. Methods 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. Results 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). Conclusion 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

  13. Prediction of global rainfall probabilities using phases of the Southern Oscillation Index

    Science.gov (United States)

    Stone, Roger C.; Hammer, Graeme L.; Marcussen, Torben

    1996-11-01

    THE El Niño/Southern Oscillation (ENSO) is a quasi-periodic interannual variation in global atmospheric and oceanic circulation patterns, known to be correlated with variations in the global pattern of rainfall1-3. Good predictive models for ENSO, if they existed, would allow accurate prediction of global rainfall variations, thus leading to better management of world agricultural production4,5, as well as improving profits and reducing risks for farmers6,7. But our current ability to predict ENSO variation is limited. Here we describe a probabilistic rainfall 'forecasting' system that does not require ENSO predictive ability, but is instead based on the identification of lag-relationships between values of the Southern Oscillation Index, which provides a quantitative measure of the phase of the ENSO cycle, and future rainfall. The system provides rainfall probability distributions three to six months in advance for regions worldwide, and is simple enough to be incorporated into management systems now.

  14. 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.

  15. Predicting active-layer soil thickness using topographic variables at a small watershed scale.

    Science.gov (United States)

    Li, Aidi; Tan, Xing; Wu, Wei; Liu, Hongbin; Zhu, Jie

    2017-01-01

    Knowledge about the spatial distribution of active-layer (AL) soil thickness is indispensable for ecological modeling, precision agriculture, and land resource management. However, it is difficult to obtain the details on AL soil thickness by using conventional soil survey method. In this research, the objective is to investigate the possibility and accuracy of mapping the spatial distribution of AL soil thickness through random forest (RF) model by using terrain variables at a small watershed scale. A total of 1113 soil samples collected from the slope fields were randomly divided into calibration (770 soil samples) and validation (343 soil samples) sets. Seven terrain variables including elevation, aspect, relative slope position, valley depth, flow path length, slope height, and topographic wetness index were derived from a digital elevation map (30 m). The RF model was compared with multiple linear regression (MLR), geographically weighted regression (GWR) and support vector machines (SVM) approaches based on the validation set. Model performance was evaluated by precision criteria of mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). Comparative results showed that RF outperformed MLR, GWR and SVM models. The RF gave better values of ME (0.39 cm), MAE (7.09 cm), and RMSE (10.85 cm) and higher R2 (62%). The sensitivity analysis demonstrated that the DEM had less uncertainty than the AL soil thickness. The outcome of the RF model indicated that elevation, flow path length and valley depth were the most important factors affecting the AL soil thickness variability across the watershed. These results demonstrated the RF model is a promising method for predicting spatial distribution of AL soil thickness using terrain parameters.

  16. Predicting active-layer soil thickness using topographic variables at a small watershed scale.

    Directory of Open Access Journals (Sweden)

    Aidi Li

    Full Text Available Knowledge about the spatial distribution of active-layer (AL soil thickness is indispensable for ecological modeling, precision agriculture, and land resource management. However, it is difficult to obtain the details on AL soil thickness by using conventional soil survey method. In this research, the objective is to investigate the possibility and accuracy of mapping the spatial distribution of AL soil thickness through random forest (RF model by using terrain variables at a small watershed scale. A total of 1113 soil samples collected from the slope fields were randomly divided into calibration (770 soil samples and validation (343 soil samples sets. Seven terrain variables including elevation, aspect, relative slope position, valley depth, flow path length, slope height, and topographic wetness index were derived from a digital elevation map (30 m. The RF model was compared with multiple linear regression (MLR, geographically weighted regression (GWR and support vector machines (SVM approaches based on the validation set. Model performance was evaluated by precision criteria of mean error (ME, mean absolute error (MAE, root mean square error (RMSE, and coefficient of determination (R2. Comparative results showed that RF outperformed MLR, GWR and SVM models. The RF gave better values of ME (0.39 cm, MAE (7.09 cm, and RMSE (10.85 cm and higher R2 (62%. The sensitivity analysis demonstrated that the DEM had less uncertainty than the AL soil thickness. The outcome of the RF model indicated that elevation, flow path length and valley depth were the most important factors affecting the AL soil thickness variability across the watershed. These results demonstrated the RF model is a promising method for predicting spatial distribution of AL soil thickness using terrain parameters.

  17. Geometric index of heart rate variability in chronic obstructive pulmonary disease

    Directory of Open Access Journals (Sweden)

    T. Dias de Carvalho

    2011-11-01

    Full Text Available Background: It was already evidenced decreased heart rate variability (HRV in chronic obstructive pulmonary disease (COPD patients at rest. Objective: In order to insert new elements in the literature regarding this issue, we evaluated geometric index of HRV in COPD subjects. Method: We analyzed data from 34 volunteers, divided into two groups according to spirometric values: COPD (17 volunteers, FEV1/FVC = 47.3 ± 10.2; FEV1 = 50.8 ± 15.7 and control (17 volunteers, FEV1/FVC = 78.8 ± 10.8; FEV1 = 100.1 ± 14.7. For analysis of HRV indexes the volunteers remained in the supine position for 30minutes. We analyzed the following indexes: triangular index (RRtri, triangular interpolation of RR intervals (TINN and Poincaré plot (SD1, SD2 and SD1/SD2. Student's t-test for unpaired samples and Mann–Whitney test were used for data analysis. Results: We observed statistically significant reductions in geometric indexes in the COPD group: RRtri (0.043 ± 0.01 vs. 0.059 ± 0.02; p = 0.018, TINN (105.88 ± 51.82 vs. 151.47 ± 49.9; p = 0.014, SD1 (9.76 ± 4.66 vs. 14.55 ± 6.04; p = 0.014 and SD2 (34.86 ± 17.02 vs. 51.51 ± 18.38; p = 0.010. SD1/SD2 (0.30 ± 0.11 vs. 0.28 ± 0.07; p = 0.605 were not significantly different between groups. Patients with COPD presented a visual analysis of Poincaré plot of lower dispersion of RR intervals both beat-to-beat and the long-term. Conclusion: Subjects with COPD present reduction of geometric indexes of HRV, indicating reduced heart rate variability. Resumo: Introdução: A redução da variabilidade da frequência cardíaca (VFC em pacientes com doença pulmonar obstrutiva crónica (DPOC em repouso já foi evidenciada na literatura. Objetivo: Com intuito de inserir elementos na literatura sobre essa temática, foram

  18. Climate variability effects on field crops in Iberian Peninsula. Predictability

    OpenAIRE

    Capa Morocho, M.

    2015-01-01

    La presente Tesis constituye un avance en el conocimiento de los efectos de la variabilidad climática en los cultivos en la Península Ibérica (PI). Es bien conocido que la temperatura del océano, particularmente de la región tropical, es una de las variables más convenientes para ser utilizado como predictor climático. Los océanos son considerados como la principal fuente de almacenamiento de calor del planeta debido a la alta capacidad calorífica del agua. Cuando se libera esta energía, alte...

  19. Prediction and analysis of variable reluctance stepmotor drive systems

    Science.gov (United States)

    Pulle, D. W. J.

    1982-01-01

    A relationship between the electric terminal parameters and output/input power is derived for conventional doubly-salient synchronous machines and extended to include the variable reluctance motor. The advantages and limitations of the drive-schemes are shown in Blondel diagrams and torque speed curves. A general method for obtaining a quantitative assessment of drive-schemes is developed by the introduction of so-called performance figures, related to the output power and efficiency. From this method applied to four drive schemes, it is concluded that severe performance degradation is the result of using a forging resistance in a drive-scheme. A forced decay unipolar chopper drive is presented.

  20. 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

  1. 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 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.

  2. Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity.

    Science.gov (United States)

    Khalsa, Sakh; Mayhew, Stephen D; Przezdzik, Izabela; Wilson, Rebecca; Hale, Joanne; Goldstone, Aimee; Bagary, Manny; Bagshaw, Andrew P

    2016-01-01

    We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN). Resting state functional magnetic resonance imaging (fMRI) study using seed-based FC analysis combined with 14-d wrist actigraphy, sleep diaries, and subjective questionnaires (N = 33 healthy adults, mean age 34.3, standard deviation ± 11.6 y). Data were statistically analyzed using multiple linear regression. Fourteen consecutive days of wrist actigraphy in participant's home environment and fMRI scanning on day 14 at the Birmingham University Imaging Centre. Seed-based FC analysis on ICNs from resting-state fMRI data and multiple linear regression analysis performed for each ICN seed and target. cTST was used to predict FC (controlling for age). cTST was specific predictor of intranetwork FC when the mesial prefrontal cortex (MPFC) region of the DMN was used as a seed for FC, with a positive correlation between FC and cTST observed. No significant relationship between FC and cTST was seen for any pair of nodes not including the MPFC. Internetwork FC between the DMN (MPFC) and SN (right anterior insula) was also predicted by cTST, with a negative correlation observed between FC and cTST. This study improves understanding of the relationship between intranetwork and internetwork functional connectivity of intrinsically connected networks (ICNs) in relation to habitual sleep quality and duration. The cumulative amount of sleep that participants achieved over a 14-d period was significantly predictive of intranetwork and inter-network functional connectivity of ICNs, an observation that may underlie the link between sleep status and cognitive performance.

  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. Ionospheric weather: cloning missed foF2 observations for derivation of variability index

    Directory of Open Access Journals (Sweden)

    T. L. Gulyaeva

    2008-02-01

    Full Text Available A techique for filling the gaps of the missing F2-layer critical frequency is proposed and applied for the derivation of the ionospheric weather index, characterizing the degree of disturbance at each particular station. A daily-hourly analysis of ionosonde observations of foF2 for 16 stations at latitude range 37° to 70° N, longitudes of 10° W to 150° E, is performed during the solar minimum, 2006. Missed ionosonde observations are reconstructed by cloning data of another station. The process of gap filling considers hourly values of the F peak density NmF2 (deduced from foF2, normalized to the respective median, and assumes that this ratio remains the same for the parent and cloned data. It is shown that the correlation coefficient between cloned fcF2 and observed foF2 is greater than 0.75 for the positive and negative ionospheric disturbed days during a year at solar minimum, independent of the distance between the stations in high and middle latitudes. The quiet reference is determined as a running daily-hourly median for 27 days, preceding the day of observation calibrated for a seasonal trend with ITU-R foF2 predictions. The hourly deviation DNmF2 is defined as the logarithm of ratio of NmF2/NmF2med. A segmented logarithmic scale of the ionospheric weather index, W, is introduced, so that W=±1 refers to the quiet state, W=±2 to a moderate disturbance, W=±3 to the ionospheric storm, and W=±4 to the extreme or anomalous conditions. The catalog of the ionospheric disturbances for W exceeding ±2 at least during 3 consecutive hours is produced and presented online at the SRC and IZMIRAN web pages. It is found that the moderate disturbance is a prevailing state of the ionospheric weather for all stations. The stormy conditions comprise 1 to 20% of the times which occur more frequently at high latitudes, by night, during equinox and winter.

  5. 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.

  6. 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.

  7. Predicting body composition in college students using the womersley and durnin body mass index equation.

    Science.gov (United States)

    Loenneke, Jeremy P; Hirt, Kathryn M; Wilson, Jacob M; Barnes, Jeremy T; Pujol, Thomas J

    2013-06-01

    When assessing fitness levels, body composition is usually measured. The purpose of this study was to determine the overall efficacy of a body mass index (BMI) equation for predicting body composition with respect to college aged participants. Body composition was measured using dual-energy x-ray absorptiometry (DXA) and was estimated using the Womersley and Durnin BMI prediction equation. There was no significant (P=0.8) percent body fat (%BF) difference between the BMI prediction equation and DXA (BMI Predicted=25 (10) [min=6; max=52] %BF vs DXA=25 (6) [min=10; max=45] %BF). In addition, a significant correlation was found between the two approaches (r=0.791, P=0.001). However, both the standard error of estimate (6.32 %BF) and total error (6.63 %BF) were outside acceptable ranges for prediction equations. The Womersley and Durnin equation for estimating %BF was not found to be a good estimate. Therefore, although the BMI predicted %BF has been previously found to predict skinfold estimated %BF, it does not appear valid in estimating %BF from DXA.

  8. 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.

  9. 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....

  10. 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.

  11. Combination of intravesical prostatic protrusion and resistive index is useful to predict bladder outlet obstruction in patients with lower urinary tract symptoms suggestive of benign prostatic hyperplasia.

    Science.gov (United States)

    Suzuki, Takahisa; Otsuka, Atsushi; Ozono, Seiichiro

    2016-11-01

    To examine which parameters obtained from transrectal ultrasonography are accurate predictors of urodynamically-confirmed bladder outlet obstruction in patients with lower urinary tract symptoms suggestive of benign prostatic hyperplasia. The records of 350 patients with complaints of lower urinary tract symptoms suggestive of benign prostatic hyperplasia were reviewed. Baseline parameters were international prostate symptom score, quality of life score, postvoid residual urine volume, prostate-specific antigen, and data obtained from uroflowmetry and transrectal ultrasonography. Urodynamic studies were carried out to determine bladder outlet obstruction. Receiver operator characteristic curves were generated to compare the accuracy of the different parameters, and the area under the curve of each parameter was calculated. Bladder outlet obstruction index positively correlated with intravesical prostatic protrusion, total prostate volume, transition zone volume, transition zone index, resistive index and prostate-specific antigen. Further, resistive index was only a significant independent variable with intravesical prostatic protrusion. Intravesical prostatic protrusion had the highest area under the curve of 0.790 among all variables, and its cut-off value was 10 mm. The positive predictive value of intravesical prostatic protrusion was 76.2%. In addition, the positive predictive value of the combined parameters intravesical prostatic protrusion and resistive index increased to 83.8%. Intravesical prostatic protrusion and resistive index are useful parameters for predicting bladder outlet obstruction in patients with lower urinary tract symptoms suggestive of benign prostatic hyperplasia. In clinical practice, the combination of intravesical prostatic protrusion and resistive index on ultrasound can be diagnostic of bladder outlet obstruction. © 2016 The Japanese Urological Association.

  12. Geriatric Nutritional Risk Index (GNRI) Independently Predicts Amputation Inchronic Criticallimb Ischemia (CLI).

    Science.gov (United States)

    Luo, Han; Yang, Hongliu; Huang, Bin; Yuan, Ding; Zhu, Jingqiang; Zhao, Jichun

    2016-01-01

    General malnutrition usually occurs in critical limb ischemia (CLI) patients because of shortness of appetite and sleeplessness leaded by chronic pain. And amputation frequently is end-point of CLI patients. So the aim of this study was to assess the predictive ability of Geriatric nutritional risk index (GNRI) for predicting amputation in patients with CLI. A retrospective study was designed. Demographics, history, comorbidity, and risk factors for peripheral vascular disease of admitted patients, and laboratory study were documented. Patients' height, weight and BMI were recorded. Amputation was identified as end-point during follow-up. Patients' amputation-free survival (AFS) was recorded. 172 patients were identified, with mean age 71.98±3.12. Geriatric nutritional risk index (GNRI) = 90 was taken as cutoff value of high risk of amputation for CLI patients via using receiver operating characteristic (ROC) curve. Span of follow-up was 12-48 months. During follow-up, 60 patients (36.04%) received amputation surgery. And analyzed by Cox proportional hazards model, it is found that GNRI was the independent predictive factor for amputation in long term. This study revealed that GNRI was a reliable and effective predictive marker for AFS. GNRI could identify patients with high risk for amputation in early time.

  13. Hypsarrhythmia paroxysm index: A tool for early prediction of infantile spasms.

    Science.gov (United States)

    Altunel, Attila; Sever, Ali; Altunel, Emine Özlem

    2015-03-01

    Recurrence of infantile spasms (ISs) is common subsequent to treatment with adrenocorticotropic hormone (ACTH) for West syndrome, and prolonged hypsarrhythmia results in psychomotor deterioration. The evolution to hypsarrhythmia involves conversion of prehypsarrhythmic EEG findings to sporadic hypsarrhythmia paroxysms (HPs), and when paroxysms reach a certain frequency, ISs begin to occur. This retrospective chart study aimed to determine the HP threshold frequency after which ISs begin. Recorded either prior (Group A) or subsequent (Group B) to IS relapse, 248 EEGs were examined in 42 patients. The number of HPs in non-rapid eye movement (NREM) sleep divided by NREM duration constituted the countable hypsarrhythmia paroxysms index (cHPI). After reaching a rate of approximately 10/min, the cHPI lost its feasibility due to the merging of HPs. The durational HPI (dHPI) was also calculated (total duration of HPs during NREM/NREM sleep time×100). ACTH treatment was administered if cHPI was ≥2/min, with the aim of preventing relapse. The mean cHPI value without a concomitant spasm relapse (in Group A) was 1.20/min. Following relapse, this value rose to 4.10/min. EEGs performed subsequent to relapse (in Group B) were classified into three subgroups (B1, B2, and B3) according to the duration of the time interval between IS relapse and the succeeding EEG recording. One-way analysis of variance (ANOVA) indicated that cHPI values differed significantly between the Group B subgroups. In subgroups B2 and B3, a higher number of EEGs were evaluated via dHPI. Linear regression analysis established that the interval between recurrence and the succeeding EEG recording significantly predicted cHPI values and accounted for 54.2% of the explained variability in cHPI values. Therefore, use of the cHPI for early recognition and intervention may aid in preventing the onset and recurrence of ISs and further deterioration of psychomotor development. Copyright © 2015 Elsevier B.V. All

  14. Body mass index, waist circumference and triceps skinfold for prediction of lipid abnormalities in children

    Directory of Open Access Journals (Sweden)

    Claudia Cruz Lunardi

    2009-09-01

    Full Text Available Introduction: Investigation of lipid levels is carried out by laboratory analyses, however there are anthropometric methods (noninvasive and of low cost such as body mass index (BMI, waist circumference (Wcir and triceps skin fold (TR that can be used as markers of dyslipidemia. Objective: To suggest cutoff points for these anthropometric measurements and to test whether the reference values recommended by the International Obesity Task Force (IOTF and Conde and Monteiro (C&M can be used to screen schoolchildren aged 10 to 12 years for lipid abnormalities. Methodology: The BMI, Wcir and TR were determined for 374 schoolchildren from the public education system of Santa Maria, RS, Brazil. Subjects were selected by stratification by public or private school and by sex. Laboratory analysis (gold standard was used to determine Total Cholesterol (TC, Low Density Lipoprotein (LDL-C, High Density Lipoprotein (HDL-C and Triglycerides (TG. Analysis employed descriptive statistics, calculations of sensitivity, specificity and negative and positive predictive values, and area under the ROC curve with a 95% confidence interval. Results: The prevalence rates of overweight calculated by the two different methods were statistically different, IOTF (24.7% and C&M (28.6%. Sensitivity (33% - 83% and specificity (62% - 80% varied widely between the cutoff points employed to indicate dyslipidemia. The anthropometric variables only exhibited diagnostic capacity for TG among the girls and for CT and LDL-C for the boys. Conclusions: The cutoff points proposed by the IOTF and by C&M can be used to screen for elevated CT and LDL-C among males. Either the IOTF or the C&M cutoffs can be used to identify people without dyslipidemia, since both have high specificity. A BMI of 19.3kg.m-2 is a diagnostic value for abnormal TG levels in females and for abnormal CT and LDL-C among males. Elevated concentrations of CT and LDL-C can also bediagnosed in boys using cut-off values

  15. Heart rate variability predicts 30-day all-cause mortality in intensive ...

    African Journals Online (AJOL)

    HRV), has shown promise in predicting clinically important outcomes in the critical care setting; however, there is debate concerning its utility. ... Keywords: APACHE II, autonomic nervous system, critical care, heart rate variability, mortality ...

  16. 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.

  17. Macronutrient Balance and Dietary Glycemic Index in Pregnancy Predict Neonatal Body Composition

    Directory of Open Access Journals (Sweden)

    Nathalie V. Kizirian

    2016-05-01

    Full Text Available The influence of maternal macronutrient balance and dietary glycemic index (GI on neonatal body composition has received little study. We hypothesized that the overall quantity and quality of macronutrients, particularly carbohydrate, in the maternal diet could have trimester-specific effects on neonatal growth and body composition in women at risk of gestational diabetes. Maternal diet was assessed using 3-day food records in mid (n = 96 and late (n = 88 pregnancy as part of the GI Baby 3 study. Neonatal body composition was assessed by air-displacement plethysmography within 48 h of birth, adjusted for length, and expressed as fat mass index (FMI and fat-free mass index (FFMI. In mid pregnancy, higher maternal intake of carbohydrate energy was negatively correlated with infant FFMI (p = 0.037. In late pregnancy, higher dietary GI was associated with lower FFMI (p = 0.010 and higher carbohydrate energy predicted lower FMI (p = 0.034. Higher fat intake (%E and saturated fat, but not protein, also predicted neonatal body composition (higher FFMI in mid pregnancy and higher FMI in late pregnancy. Depending on pregnancy stage, a high carbohydrate-low fat diet, particularly from high glycemic sources, may reduce neonatal indices of both lean mass and adiposity.

  18. 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.

  19. Prediction of postoperative facial swelling, pain and trismus following third molar surgery based on preoperative variables

    Science.gov (United States)

    de Souza-Santos, Jadson A.; Martins-Filho, Paulo R.; da Silva, Luiz C.; de Oliveira e Silva, Emanuel D.; Gomes, Ana C.

    2013-01-01

    Objective: This paper investigates the relationship between preoperative findings and short-term outcome in third molar surgery. Study design: A prospective study was carried out involving 80 patients who required 160 surgical extractions of impacted mandibular third molars between January 2009 and December 2010. All extractions were performed under local anesthesia by the same dental surgeon. Swelling and maximal inter-incisor distance were measured at 48 h and on the 7th day postoperatively. Mean visual analogue pain scores were determined at four different time periods. Results: One-hundred eight (67.5%) of the 160 extractions were performed on male subjects and 52 (32.5%) were performed on female subjects. Median age was 22.46 years. The amount of facial swelling varied depending on gender and operating time. Trismus varied depending on gender, operating time and tooth sectioning. The influence of age, gender and operating time varied depending on the pain evaluation period (p trismus and pain) differ depending on the patients’ characteristics (age, gender and body mass index). Moreover, surgery characteristics such as operating time and tooth sectioning were also associated with postoperative variables. Key words:Third molar extraction, pain, swelling, trismus, postoperative findings, prediction. PMID:23229245

  20. Prediction of Elderly Anthropometric Dimension Based On Age, Gender, Origin, and Body Mass Index

    Science.gov (United States)

    Indah, P.; Sari, A. D.; Suryoputro, M. R.; Purnomo, H.

    2016-01-01

    Introduction: Studies have indicated that elderly anthropometric dimensions will different for each person. To determine whether there are differences in the anthropometric data of Javanese elderly, this study will analyze whether the variables of age, gender, origin, and body mass index (BMI) have been associated with elderly anthropometric dimensions. Age will be divided into elderly and old categories, gender will divide into male and female, origins were divided into Yogyakarta and Central Java, and for BMI only use the normal category. Method: Anthropometric studies were carried out on 45 elderly subjects in Sleman,Yogyakarta. Results and Discussion: The results showed that some elderly anthropometric dimensions were influenced by age, origin, and body mass index but gender doesn't significantly affect the elderly anthropometric dimensions that exist in the area of Sleman. The analysis has provided important aid when designing products that intended to the Javanese elderly Population.

  1. Comparison of motor importance scale functional independence and Barthel index to predict mortality after hip fractures in the elderly population

    Directory of Open Access Journals (Sweden)

    Aleksić Milica

    2017-01-01

    Full Text Available Introduction: Hip fractures represent an important medical, social, and economical problem of modern age. Between 14% and 36% of people with hip fracture die in the first year after the fracture. The largest number of survivors fail to regain the pre-injury walking ability and level of activity. High rates of mortality and morbidity point out the necessity of identifying and defining the determinants of outcome, which could potentially be influenced on with the aim to reduce mortality, and disability, as are result of this event. The aim: To determine whether two different scales to measure functional disability are equally sensitive predictors of mortality in elderly patients with hip fracture. Materials and Methods: The study included 299 patients older than 65 years that were operatively treated at the Institute for Orthopaedic Surgery and Traumatology for a period of one year, due to acute hip fracture. Preoperatively, patients were questioned regarding socio-demographic variables, cognitive status, functional disability before the accident, type of hip fracture and operational risk. Functional disability before the accident was measured using the motor subscale of the functional test of independence (motor FIM and Barthel index. In order to examine the association between different preoperative variables and intrahospital/one-year mortality as starting variables, multivariate logistic regression analysis were performed, in which the influence of motor FIM and the Barthel index were examined separately. Results: The study confirmed that patients who had a higher level of functional disability before fracture, have a higher risk of short-term and long-term mortality after hip fracture. The most important result of this work is that Barthel's index and motor FIM test are equally effective predictors of short-term and long-term mortality. Conclusion: Our study revealed the importance of functional impairment prior to injury, for the prediction

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

    OpenAIRE

    Gloria Cajiao; Dennis Lissete Morales Arias; Genny Carolina Garzón Romero; Liliana Benavides Basante; José Leonardo Acevedo Rincón

    2013-01-01

    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 conceptu...

  3. VALIDITY OF SINGLE VARIABLES AND COMPOSITE INDEXES FOR MEASURING DISEASE-ACTIVITY IN RHEUMATOID-ARTHRITIS

    NARCIS (Netherlands)

    VANDERHEIJDE, DMFM; VANTHOF, MA; VANRIEL, PLCM; VANLEEUWEN, MA; VANRIJSWIJK, MH; VANDEPUTTE, LBA

    There is no agreement as to which variable best mirrors disease activity in rheumatoid arthritis (RA) and no studies have been performed on the validity of disease activity variables. In this study the validity of 10 commonly used single variables and three composite indices was tested. All patients

  4. 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

  5. Comparison of multiple regression to two latent variable techniques for estimation and prediction.

    Science.gov (United States)

    Wall, Melanie M; Li, Ruifeng

    2003-12-15

    In the areas of epidemiology, psychology, sociology, and other social and behavioural sciences, researchers often encounter situations where there are not only many variables contributing to a particular phenomenon, but there are also strong relationships among many of the predictor variables of interest. By using the traditional multiple regression on all the predictor variables, it is possible to have problems with interpretation and multicollinearity. As an alternative to multiple regression, we explore the use of a latent variable model that can address the relationship among the predictor variables. We consider two different methods for estimation and prediction for this model: one that uses multiple regression on factor score estimates and the other that uses structural equation modelling. The first method uses multiple regression but on a set of predicted underlying factors (i.e. factor scores), and the second method is a full-information maximum-likelihood technique that incorporates the complete covariance structure of the data. In this tutorial, we will explain the model and each estimation method, including how to carry out prediction. A data example will be used for demonstration, where respiratory disease death rates by county in Minnesota are predicted by five county-level census variables. A simulation study is performed to evaluate the efficiency of prediction using the two latent variable modelling techniques compared to multiple regression. Copyright 2003 John Wiley & Sons, Ltd.

  6. Preoperative Nutritional Risk Index to predict postoperative survival time in primary liver cancer patients.

    Science.gov (United States)

    Bo, Yacong; Yao, Mingjie; Zhang, Ling; Bekalo, Wolde; Lu, Weiquan; Lu, Quanjun

    2015-01-01

    We designed this study to determine the predictive value of Nutritional Risk Index (NRI) for postoperative survival time of patients who had undergone hepatectomy for primary liver cancer. The 620 patients who underwent hepatectomy for primary liver cancer (PLC) in the Department of Hepatobiliary Surgery, Cancer Hospital of Henan Province, Zhengzhou, China from December 1, 2008 to December 1, 2012 were followed up. A nutritional risk index (NRI) was used to screen the patients with malnutrition (NRI100) patients had longer postoperative survival time compared with malnourished patients. NRI values>100 was sig-nificantly associated with longer postoperative survival time. Cox proportional hazards model showed that NRI was an independent predictor of postoperative survival time and that NRI varied inversely with the risk of death. The patients with NRI values>100 survived longer than those with NRI values

  7. Prediction of reverberation time and speech transmission index in long enclosures.

    Science.gov (United States)

    Li, Kai Ming; Lam, Pou Man

    2005-06-01

    It is known that the sound field in a long space is not diffuse, and that the classic theory of room acoustics is not applicable. A theoretical model is developed for the prediction of reverberation time and speech transmission index in rectangular long enclosures, such as corridors and train stations, where the acoustic quality is important for speech. The model is based on an image-source method, and both acoustically hard and impedance boundaries are investigated. An approximate analytical solution is used to predict the frequency response of the sound field. The reverberation time is determined from the decay curve which is computed by a reverse-time integration of the squared impulse response. The angle-dependence of reflection coefficients of the boundaries and the change of phase upon reflection are incorporated in this model. Due to the relatively long distance of sound propagation, the effect of atmospheric absorption is also considered. Measurements of reverberation time and speech transmission index taken from a real tunnel, a corridor, and a model tunnel are presented. The theoretical predictions are found to agree well with the experimental data. An application of the proposed model has been suggested.

  8. Prediction of reverberation time and speech transmission index in long enclosures

    Science.gov (United States)

    Li, Kai Ming; Lam, Pou Man

    2005-06-01

    It is known that the sound field in a long space is not diffuse, and that the classic theory of room acoustics is not applicable. A theoretical model is developed for the prediction of reverberation time and speech transmission index in rectangular long enclosures, such as corridors and train stations, where the acoustic quality is important for speech. The model is based on an image-source method, and both acoustically hard and impedance boundaries are investigated. An approximate analytical solution is used to predict the frequency response of the sound field. The reverberation time is determined from the decay curve which is computed by a reverse-time integration of the squared impulse response. The angle-dependence of reflection coefficients of the boundaries and the change of phase upon reflection are incorporated in this model. Due to the relatively long distance of sound propagation, the effect of atmospheric absorption is also considered. Measurements of reverberation time and speech transmission index taken from a real tunnel, a corridor, and a model tunnel are presented. The theoretical predictions are found to agree well with the experimental data. An application of the proposed model has been suggested. .

  9. An Analysis of Macroeconomic Variables Affecting Real Sector Confidence Index: The Case of Turkey

    Directory of Open Access Journals (Sweden)

    İsmail Canöz

    2017-11-01

    Full Text Available Traditional finance theories are not sufficient to explain investor’s sentiment and psychology. This situation leads to emergence of Behavioral Finance. The aim of this paper is to analyze the macroeconomic factors affecting Real Sector Confidence Index (RSCI of Central Bank of the Republic of Turkey (CBRT. Within this scope, monthly data for the period between 2007:01 and 2017:03 is analyzed by using Johansen Cointegration Test and Granger Causality Test. According to the results of the analysis, CBRT Composite Leading Indicators Index, Capacity Utilization Rate of Manufacturing Industry (CURMI, Turkish Lira Reference Interest Rate (TRLIBOR and BIST100 Return Index affect RSCI.

  10. Comparison of predictive capabilities of diabetic exchange lists and glycemic index of foods.

    Science.gov (United States)

    Laine, D C; Thomas, W; Levitt, M D; Bantle, J P

    1987-01-01

    To determine whether the diabetic exchange lists or the glycemic index of foods better predicts postprandial responses to carbohydrate-containing foods eaten as part of a mixed meal, three test meals were developed and fed to 12 subjects with non-insulin-dependent diabetes mellitus (NIDDM) and 13 healthy subjects. Each test meal contained exactly the same exchanges (1 milk, 4 starch, 2 fruit, 2 meat, 3 fat, 1 vegetable). In one meal, foods of high glycemic index (GI) were used, in a second meal, foods of intermediate GI were used, and in a third meal foods of low GI were used. The total GIs of the meals were: high, 184; intermediate, 131; and low, 107, thus predicting responses to intermediate and low GI, which were 71 and 58%, respectively, of the responses to high GI. Although some of the observed differences in the glycemic responses to the test meals were statistically significant, primarily in healthy subjects, the differences were usually much less than predicted by the GIs of the meals. In NIDDM subjects, peak postprandial plasma glucose, plasma glucose area, plasma glucose area increment, and mean plasma glucose responses after intermediate and low GI were greater than 90% of the corresponding responses to high GI. In healthy subjects, only the plasma glucose area increment after the low-GI meal was close to the predicted response. High GI produced significantly greater insulin responses than low GI in healthy subjects. We conclude that the diabetic exchange lists more accurately predict postprandial responses to carbohydrate-containing foods eaten as part of a mixed meal than does the GI of foods.(ABSTRACT TRUNCATED AT 250 WORDS)

  11. Maximum likelihood estimation for predicting the probability of obtaining variable shortleaf pine regeneration densities

    Science.gov (United States)

    Thomas B. Lynch; Jean Nkouka; Michael M. Huebschmann; James M. Guldin

    2003-01-01

    A logistic equation is the basis for a model that predicts the probability of obtaining regeneration at specified densities. The density of regeneration (trees/ha) for which an estimate of probability is desired can be specified by means of independent variables in the model. When estimating parameters, the dependent variable is set to 1 if the regeneration density (...

  12. 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...

  13. The SOMERS Index: a simple instrument designed to predict the likelihood of rural career choice.

    Science.gov (United States)

    Somers, George T; Jolly, Brian; Strasser, Roger P

    2011-04-01

    The World Health Organization has drawn up a set of strategies to encourage health workers to live and work in remote and rural areas. A comprehensive instrument designed to evaluate the effectiveness of such programs has not yet been tested. Factors such as Stated rural intention, Optional rural training, Medical sub-specialization, Ease (or self-efficacy) and Rural Status have been used individually or in limited combinations. This paper examines the development, validity, structure and reliability of the easily-administered SOMERS Index. Limited literature review and cross-sectional cohort study. Australian medical school.   A total of 345 Australian undergraduate-entry medical students in years 1 to 4 of the 5-year course.   Validity of the factors as predictors of rural career choice was sought in the international literature. Structure of the index was investigated through Principal Components Analysis and regression modelling. Cronbach's alpha was the test for reliability. The international literature strongly supported the validity of the components of the index. Factor analysis revealed a single, strong factor (eigenvalue: 2.78) explaining 56% of the variance. Multiple regression modelling revealed that each of the other variables contributed independently and strongly to Stated Rural Intent (semi-partial correlation coefficients range: 0.20-0.25). Cronbach's alpha was high at 0.78. This paper presents the reliability and validity of an index, which seeks to estimate the likelihood of rural career choice. The index might be useful in student selection, the allocation of rural undergraduate and postgraduate resources and the evaluation of programs designed to increase rural career choice. © 2011 The Authors. Australian Journal of Rural Health © National Rural Health Alliance Inc.

  14. Canine sense and sensibility: tipping points and response latency variability as an optimism index in a canine judgement bias assessment.

    Science.gov (United States)

    Starling, Melissa J; Branson, Nicholas; Cody, Denis; Starling, Timothy R; McGreevy, Paul D

    2014-01-01

    Recent advances in animal welfare science used judgement bias, a type of cognitive bias, as a means to objectively measure an animal's affective state. It is postulated that animals showing heightened expectation of positive outcomes may be categorised optimistic, while those showing heightened expectations of negative outcomes may be considered pessimistic. This study pioneers the use of a portable, automated apparatus to train and test the judgement bias of dogs. Dogs were trained in a discrimination task in which they learned to touch a target after a tone associated with a lactose-free milk reward and abstain from touching the target after a tone associated with water. Their judgement bias was then probed by presenting tones between those learned in the discrimination task and measuring their latency to respond by touching the target. A Cox's Proportional Hazards model was used to analyse censored response latency data. Dog and Cue both had a highly significant effect on latency and risk of touching a target. This indicates that judgement bias both exists in dogs and differs between dogs. Test number also had a significant effect, indicating that dogs were less likely to touch the target over successive tests. Detailed examination of the response latencies revealed tipping points where average latency increased by 100% or more, giving an indication of where dogs began to treat ambiguous cues as predicting more negative outcomes than positive ones. Variability scores were calculated to provide an index of optimism using average latency and standard deviation at cues after the tipping point. The use of a mathematical approach to assessing judgement bias data in animal studies offers a more detailed interpretation than traditional statistical analyses. This study provides proof of concept for the use of an automated apparatus for measuring cognitive bias in dogs.

  15. Canine sense and sensibility: tipping points and response latency variability as an optimism index in a canine judgement bias assessment.

    Directory of Open Access Journals (Sweden)

    Melissa J Starling

    Full Text Available Recent advances in animal welfare science used judgement bias, a type of cognitive bias, as a means to objectively measure an animal's affective state. It is postulated that animals showing heightened expectation of positive outcomes may be categorised optimistic, while those showing heightened expectations of negative outcomes may be considered pessimistic. This study pioneers the use of a portable, automated apparatus to train and test the judgement bias of dogs. Dogs were trained in a discrimination task in which they learned to touch a target after a tone associated with a lactose-free milk reward and abstain from touching the target after a tone associated with water. Their judgement bias was then probed by presenting tones between those learned in the discrimination task and measuring their latency to respond by touching the target. A Cox's Proportional Hazards model was used to analyse censored response latency data. Dog and Cue both had a highly significant effect on latency and risk of touching a target. This indicates that judgement bias both exists in dogs and differs between dogs. Test number also had a significant effect, indicating that dogs were less likely to touch the target over successive tests. Detailed examination of the response latencies revealed tipping points where average latency increased by 100% or more, giving an indication of where dogs began to treat ambiguous cues as predicting more negative outcomes than positive ones. Variability scores were calculated to provide an index of optimism using average latency and standard deviation at cues after the tipping point. The use of a mathematical approach to assessing judgement bias data in animal studies offers a more detailed interpretation than traditional statistical analyses. This study provides proof of concept for the use of an automated apparatus for measuring cognitive bias in dogs.

  16. 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.

  17. 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.

  18. A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures

    Science.gov (United States)

    Chen, Yun; Yang, Hui

    2016-12-01

    In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering.

  19. 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.

  20. APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility.

    Science.gov (United States)

    Xia, Jun-Feng; Zhao, Xing-Ming; Song, Jiangning; Huang, De-Shuang

    2010-04-08

    It is well known that most of the binding free energy of protein interaction is contributed by a few key hot spot residues. These residues are crucial for understanding the function of proteins and studying their interactions. Experimental hot spots detection methods such as alanine scanning mutagenesis are not applicable on a large scale since they are time consuming and expensive. Therefore, reliable and efficient computational methods for identifying hot spots are greatly desired and urgently required. In this work, we introduce an efficient approach that uses support vector machine (SVM) to predict hot spot residues in protein interfaces. We systematically investigate a wide variety of 62 features from a combination of protein sequence and structure information. Then, to remove redundant and irrelevant features and improve the prediction performance, feature selection is employed using the F-score method. Based on the selected features, nine individual-feature based predictors are developed to identify hot spots using SVMs. Furthermore, a new ensemble classifier, namely APIS (A combined model based on Protrusion Index and Solvent accessibility), is developed to further improve the prediction accuracy. The results on two benchmark datasets, ASEdb and BID, show that this proposed method yields significantly better prediction accuracy than those previously published in the literature. In addition, we also demonstrate the predictive power of our proposed method by modelling two protein complexes: the calmodulin/myosin light chain kinase complex and the heat shock locus gene products U and V complex, which indicate that our method can identify more hot spots in these two complexes compared with other state-of-the-art methods. We have developed an accurate prediction model for hot spot residues, given the structure of a protein complex. A major contribution of this study is to propose several new features based on the protrusion index of amino acid residues, which

  1. 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.

  2. Body mass index for predicting hyperglycemia and serum lipid changes in Brazilian adolescents

    OpenAIRE

    Vieira, Ana Carolina R; Alvarez,Marlene M; Kanaan, Salim; Sichieri, Rosely; Veiga,Gloria V

    2009-01-01

    OBJECTIVE: To determine the best cut-offs of body mass index for identifying alterations of blood lipids and glucose in adolescents. METHODS: 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 (>150mg/...

  3. Predicting Reading Growth with Event-Related Potentials: Thinking Differently about Indexing "Responsiveness"

    Science.gov (United States)

    Lemons, Christopher J; Key, Alexandra P F; Fuchs, Douglas; Yoder, Paul J; Fuchs, Lynn S; Compton, Donald L; Williams, Susan M; Bouton, Bobette

    2010-06-01

    The purpose of this study was to determine if event-related potential (ERP) data collected during three reading-related tasks (Letter Sound Matching, Nonword Rhyming, and Nonword Reading) could be used to predict short-term reading growth on a curriculum-based measure of word identification fluency over 19 weeks in a sample of 29 first-grade children. Results indicate that ERP responses to the Letter Sound Matching task were predictive of reading change and remained so after controlling for two previously validated behavioral predictors of reading, Rapid Letter Naming and Segmenting. ERP data for the other tasks were not correlated with reading change. The potential for cognitive neuroscience to enhance current methods of indexing responsiveness in a response-to-intervention (RTI) model is discussed.

  4. United Kingdom windspeed: Measurement, climatology, predictability and link to tropical Atlantic variability

    Science.gov (United States)

    George, Steven Edward

    Windspeed impacts the business performance of many industries yet has received relatively little attention compared with other meteorological fields. The present study addresses this inconsistency. A UK seasonal windspeed climatology is de veloped using a new dataset of United Kingdom hourly windspeed measurements comprising 30 years of observations from 52 geographically dispersed sites. The data are shown to contain significant errors associated with non-ideal measurement conditions. A correction algorithm is described and on application the adjusted site-records exhibit improved homogeneity. Seasonal climatological windspeed char acteristics are modelled using the Weibull distribution: results indicate that central southern England can expect 1-6 near-gale events each winter, compared with 22-27 near-gale events in southwest England. Rare (strong) event return periods are modelled using Gumbell extreme-value theory. Seasonal predictability of winter storminess is investigated using an index defined by the 95th percentile of winter daily maximum windspeed (SI). The interannual variability of SI over Europe is dominated by the North Atlantic Oscillation (NAO, 34% Percentage Variance Ex plained (PVE)). Conversely, a secondary SI mode of variability (SI2, 19% PVE) is seen to have a significant impact over the UK. Multi-field correlation analysis is employed to assess potential SI2 predictability, with statistical forecast models built from the results: the models show mixed skill performance. Tropical North Atlantic (TNA) windspeed is shown to co-vary with winter NAO: surface tradewinds for Dec- Jan-Feb are 19% higher in strong-NAO composite years compared to weak-NAO composite years. In turn this impacts the subsequent distribution of Caribbean rainfall: wet-season precipitation is significantly reduced following a strong winter NAO. It is hypothesised that changes in the TNA trade winds create long lasting SST anomalies, which in turn feedback onto wet season

  5. 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....

  6. 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.

  7. Latent variable modeling improves AKI risk factor identification and AKI prediction compared to traditional methods.

    Science.gov (United States)

    Smith, Loren E; Smith, Derek K; Blume, Jeffrey D; Siew, Edward D; Billings, Frederic T

    2017-02-08

    Acute kidney injury (AKI) is diagnosed based on postoperative serum creatinine change, but AKI models have not consistently performed well, in part due to the omission of clinically important but practically unmeasurable variables that affect creatinine. We hypothesized that a latent variable mixture model of postoperative serum creatinine change would partially account for these unmeasured factors and therefore increase power to identify risk factors of AKI and improve predictive accuracy. We constructed a two-component latent variable mixture model and a linear model using data from a prospective, 653-subject randomized clinical trial of AKI following cardiac surgery (NCT00791648) and included established AKI risk factors and covariates known to affect serum creatinine. We compared model fit, discrimination, power to detect AKI risk factors, and ability to predict AKI between the latent variable mixture model and the linear model. The latent variable mixture model demonstrated superior fit (likelihood ratio of 6.68 × 1071) and enhanced discrimination (permutation test of Spearman's correlation coefficients, p variable mixture model was 94% (-13 to 1132%) more powerful (median [range]) at identifying risk factors than the linear model, and demonstrated increased ability to predict change in serum creatinine (relative mean square error reduction of 6.8%). A latent variable mixture model better fit a clinical cohort of cardiac surgery patients than a linear model, thus providing better assessment of the associations between risk factors of AKI and serum creatinine change and more accurate prediction of AKI. Incorporation of latent variable mixture modeling into AKI research will allow clinicians and investigators to account for clinically meaningful patient heterogeneity resulting from unmeasured variables, and therefore provide improved ability to examine risk factors, measure mechanisms and mediators of kidney injury, and more accurately predict AKI in

  8. A Risk Prediction Index for Amiodarone-Induced Thyrotoxicosis in Adults with Congenital Heart Disease

    Directory of Open Access Journals (Sweden)

    Marius N. Stan

    2012-01-01

    Full Text Available Amiodarone therapy in adults with congenital heart disease (CHD is associated with a significant risk of amiodarone-induced thyrotoxicosis (AIT. We developed a risk index to identify those patients being considered for amiodarone treatment who are at high risk for AIT. We reviewed the health records of adults with CHD and assessed the association between potential clinical predictors and AIT. Significant predictors were included in multivariate analyses. The parameter estimates from multivariate analysis were subsequently used to develop a risk index. 169 adults met eligibility criteria and 23 developed AIT. The final model included age, cyanotic heart disease and BMI. The risk index developed identified 3 categories of risk. Their AIT likelihood ratios were: 0.37 for low risk (95% CI 0.15–0.92; 1.12 for medium risk (95% CI 0.65–1.91; and 3.47 for high risk (95% CI 1.7–7.11. The AIT predicted risk in our population was 5% for the low risk group, 15% for the medium risk group and 47% for the high risk group. Conclusions. We derived the first model to quantify the risk for developing AIT among adults with CHD. Before using it clinically to help selecting among alternative antiarrhythmic options, it needs validation in an independent population.

  9. Forearm muscle oxidative capacity index predicts sport rock-climbing performance.

    Science.gov (United States)

    Fryer, Simon; Stoner, Lee; Stone, K; Giles, D; Sveen, Joakim; Garrido, Inma; España-Romero, Vanesa

    2016-08-01

    Rock-climbing performance is largely dependent on the endurance of the forearm flexors. Recently, it was reported that forearm flexor endurance in elite climbers is independent of the ability to regulate conduit artery (brachial) blood flow, suggesting that endurance is not primarily dependent on the ability of the brachial artery to deliver oxygen, but rather the ability of the muscle to perfuse and use oxygen, i.e., skeletal muscle oxidative capacity. The aim of the study was to determine whether an index of oxidative capacity in the flexor digitorum profundus (FDP) predicts the best sport climbing red-point grade within the last 6 months. Participants consisted of 46 sport climbers with a range of abilities. Using near-infrared spectroscopy, the oxidative capacity index of the FDP was assessed by calculating the half-time for tissue oxygen resaturation (O2HTR) following 3-5 min of ischemia. Linear regression, adjusted for age, sex, BMI, and training experience, revealed a 1-s decrease in O2HTR was associated with an increase in red-point grade by 0.65 (95 % CI 0.35-0.94, Adj R (2)  = 0.53). Considering a grade of 0.4 separated the top four competitors in the 2015 International Federation Sport Climbing World Cup, this finding suggests that forearm flexor oxidative capacity index is an important determinant of rock-climbing performance.

  10. Amniotic fluid index and estimated fetal weight for prediction of fetal macrosomia: a prospective observational study.

    Science.gov (United States)

    El Khouly, Nabih I; Elkelani, Osama A; Saleh, Said A

    2017-08-01

    The purpose of this study was to assess the value of combining the estimated fetal weight (EFW) and amniotic fluid index (AFI) measured in term patients early in labor with intact membranes for prediction of macrosomia. In a single center, prospective observational study, 600 patients in the first stage of labor before rupture of membranes in whom ultrasonography was performed to measure AFI and EFW, and these data were analyzed statistically to evaluate prediction of fetal macrosomia. Macrosomia occurred in 64 cases (10.6%). The AFI was significantly higher in the macrosomic group (p = 0.001). It was noted that the area under receiver operating characteristic (ROC) curves for EFW was 0.93 and that of AFI was 0.67. Based on suggested combined EFW and AFI cutoffs of 4000 g and 164 mm, respectively, the positive predictive value (PPV) for combined parameters (92.3%) was higher than that of EFW (75%) and that of AFI (27%) and the likelihood ratio for combination (93.7%) was higher than that of EFW (24.7%) and that of AFI (21%). Combined use of EFW and AFI improves prediction of macrosomia at birth rather than the EFW alone.

  11. Prediction of body mass index in mice using dense molecular markers and a regularized neural network.

    Science.gov (United States)

    Okut, Hayrettin; Gianola, Daniel; Rosa, Guilherme J M; Weigel, Kent A

    2011-06-01

    Bayesian regularization of artificial neural networks (BRANNs) were used to predict body mass index (BMI) in mice using single nucleotide polymorphism (SNP) markers. Data from 1896 animals with both phenotypic and genotypic (12 320 loci) information were used for the analysis. Missing genotypes were imputed based on estimated allelic frequencies, with no attempt to reconstruct haplotypes based on family information or linkage disequilibrium between markers. A feed-forward multilayer perceptron network consisting of a single output layer and one hidden layer was used. Training of the neural network was done using the Bayesian regularized backpropagation algorithm. When the number of neurons in the hidden layer was increased, the number of effective parameters, γ, increased up to a point and stabilized thereafter. A model with five neurons in the hidden layer produced a value of γ that saturated the data. In terms of predictive ability, a network with five neurons in the hidden layer attained the smallest error and highest correlation in the test data although differences among networks were negligible. Using inherent weight information of BRANN with different number of neurons in the hidden layer, it was observed that 17 SNPs had a larger impact on the network, indicating their possible relevance in prediction of BMI. It is concluded that BRANN may be at least as useful as other methods for high-dimensional genome-enabled prediction, with the advantage of its potential ability of capturing non-linear relationships, which may be useful in the study of quantitative traits under complex gene action.

  12. Nutritional Risk Index predicts mortality in hospitalized advanced heart failure patients.

    Science.gov (United States)

    Adejumo, Oluwayemisi L; Koelling, Todd M; Hummel, Scott L

    2015-11-01

    Hospitalized advanced heart failure (HF) patients are at high risk for malnutrition and death. The Nutritional Risk Index (NRI) is a simple, well-validated tool for identifying patients at risk for nutrition-related complications. We hypothesized that, in advanced HF patients from the ESCAPE (Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness) trial, the NRI would improve risk discrimination for 6-month all-cause mortality. We analyzed the 160 ESCAPE index admission survivors with complete follow-up and NRI data, calculated as follows: NRI = (1.519 × discharge serum albumin [in g/dl]) + (41.7 × discharge weight [in kg] / ideal body weight [in kg]); as in previous studies, if discharge weight is greater than ideal body weight (IBW), this ratio was set to 1. The previously developed ESCAPE mortality model includes: age; 6-minute walk distance; cardiopulmonary resuscitation/mechanical ventilation; discharge β-blocker prescription and diuretic dose; and discharge serum sodium, blood urea nitrogen and brain natriuretic peptide levels. We used Cox proportional hazards modeling for the outcome of 6-month all-cause mortality. Thirty of 160 patients died within 6 months of hospital discharge. The median NRI was 96 (IQR 91 to 102), reflecting mild-to-moderate nutritional risk. The NRI independently predicted 6-month mortality, with adjusted HR 0.60 (95% CI 0.39 to 0.93, p = 0.02) per 10 units, and increased Harrell's c-index from 0.74 to 0.76 when added to the ESCAPE model. Body mass index and NRI at hospital admission did not predict 6-month mortality. The discharge NRI was most helpful in patients with high (≥ 20%) predicted mortality by the ESCAPE model, where observed 6-month mortality was 38% in patients with NRI 100 (p = 0.04). The NRI is a simple tool that can improve mortality risk stratification at hospital discharge in hospitalized patients with advanced HF. Published by Elsevier Inc.

  13. A simple, noninvasively determined index predicting hepatic failure following liver resection for hepatocellular carcinoma.

    Science.gov (United States)

    Ichikawa, Tsuyoshi; Uenishi, Takahiro; Takemura, Shigekazu; Oba, Kazuki; Ogawa, Masao; Kodai, Shintaro; Shinkawa, Hiroji; Tanaka, Hiromu; Yamamoto, Takatsugu; Tanaka, Shogo; Yamamoto, Satoshi; Hai, Seikan; Shuto, Taichi; Hirohashi, Kazuhiro; Kubo, Shoji

    2009-01-01

    A novel index, the serum aspartate aminotransferase activity/platelet count ratio index (APRI), has been identified as a biochemical surrogate for histological fibrogenesis and fibrosis in cirrhosis. We evaluated the ability of preoperative APRI to predict hepatic failure following liver resection for hepatocellular carcinoma. Potential preoperative risk factors for postoperative hepatic failure (hepatic coma with hyperbilirubinemia, four patients; intractable pleural effusion or ascites, 30 patients; and variceal bleeding, one patient) as well as APRI were evaluated in 366 patients undergoing liver resection for hepatocellular carcinoma. Prognostic significance was determined by univariate and multivariate analyses. Hepatic failure developed postoperatively in 30 patients, causing death in four. APRI correlated with histological intensity of hepatitis activity and degree of hepatic fibrosis, and was significantly higher in patients who developed postoperative hepatic failure than in others without failure. Risk of postoperative hepatic failure increased as the serum albumin concentration and platelet count decreased and as indocyanine green retention rate at 15 min, aspartate and alanine aminotransferase activities, and APRI increased. Only APRI was an independent preoperative factor on multivariate analysis. Of the four patients who died of postoperative hepatic failure, three had an APRI of at least 10. Preoperative APRI independently predicted hepatic failure following liver resection for hepatocellular carcinoma. Patients with an APRI of 10 or more have a high risk of postoperative hepatic failure.

  14. AE Geomagnetic Index Predictability for High Speed Solar Wind Streams: A Wavelet Decomposition Technique

    Science.gov (United States)

    Guarnieri, Fernando L.; Tsurutani, Bruce T.; Hajra, Rajkumar; Echer, Ezequiel; Gonzalez, Walter D.; Mannucci, Anthony J.

    2014-01-01

    High speed solar wind streams cause geomagnetic activity at Earth. In this study we have applied a wavelet interactive filtering and reconstruction technique on the solar wind magnetic field components and AE index series to allowed us to investigate the relationship between the two. The IMF Bz component was found as the most significant solar wind parameter responsible by the control of the AE activity. Assuming magnetic reconnection associated to southward directed Bz is the main mechanism transferring energy into the magnetosphere, we adjust parameters to forecast the AE index. The adjusted routine is able to forecast AE, based only on the Bz measured at the L1 Lagrangian point. This gives a prediction approximately 30-70 minutes in advance of the actual geomagnetic activity. The correlation coefficient between the observed AE data and the forecasted series reached values higher than 0.90. In some cases the forecast reproduced particularities observed in the signal very well.The high correlation values observed and the high efficacy of the forecasting can be taken as a confirmation that reconnection is the main physical mechanism responsible for the energy transfer during HILDCAAs. The study also shows that the IMF Bz component low frequencies are most important for AE prediction.

  15. Automated chart review utilizing natural language processing algorithm for asthma predictive index.

    Science.gov (United States)

    Kaur, Harsheen; Sohn, Sunghwan; Wi, Chung-Il; Ryu, Euijung; Park, Miguel A; Bachman, Kay; Kita, Hirohito; Croghan, Ivana; Castro-Rodriguez, Jose A; Voge, Gretchen A; Liu, Hongfang; Juhn, Young J

    2018-02-13

    Thus far, no algorithms have been developed to automatically extract patients who meet Asthma Predictive Index (API) criteria from the Electronic health records (EHR) yet. Our objective is to develop and validate a natural language processing (NLP) algorithm to identify patients that meet API criteria. This is a cross-sectional study nested in a birth cohort study in Olmsted County, MN. Asthma status ascertained by manual chart review based on API criteria served as gold standard. NLP-API was developed on a training cohort (n = 87) and validated on a test cohort (n = 427). Criterion validity was measured by sensitivity, specificity, positive predictive value and negative predictive value of the NLP algorithm against manual chart review for asthma status. Construct validity was determined by associations of asthma status defined by NLP-API with known risk factors for asthma. Among the eligible 427 subjects of the test cohort, 48% were males and 74% were White. Median age was 5.3 years (interquartile range 3.6-6.8). 35 (8%) had a history of asthma by NLP-API vs. 36 (8%) by abstractor with 31 by both approaches. NLP-API predicted asthma status with sensitivity 86%, specificity 98%, positive predictive value 88%, negative predictive value 98%. Asthma status by both NLP and manual chart review were significantly associated with the known asthma risk factors, such as history of allergic rhinitis, eczema, family history of asthma, and maternal history of smoking during pregnancy (p value NLP-API and abstractor, and the effect sizes were similar between the reviews with 4.4 vs 4.2 respectively. NLP-API was able to ascertain asthma status in children mining from EHR and has a potential to enhance asthma care and research through population management and large-scale studies when identifying children who meet API criteria.

  16. 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

  17. Do genetic risk scores for body mass index predict risk of phobic anxiety? Evidence for a shared genetic risk factor.

    Science.gov (United States)

    Walter, S; Glymour, M M; Koenen, K; Liang, L; Tchetgen Tchetgen, E J; Cornelis, M; Chang, S-C; Rewak, M; Rimm, E; Kawachi, I; Kubzansky, L D

    2015-01-01

    Obesity and anxiety are often linked but the direction of effects is not clear. Using genetic instrumental variable (IV) analyses in 5911 female participants from the Nurses' Health Study (NHS, initiated 1976) and 3697 male participants from the Health Professional Follow-up Study (HPFS, initiated 1986), we aimed to determine whether obesity increases symptoms of phobic anxiety. As instrumental variables we used the fat mass and obesity-associated (FTO) gene, the melanocortin 4 receptor (MC4R) gene and a genetic risk score (GRS) based on 32 single nucleotide polymorphisms (SNPs) that significantly predict body mass index (BMI). 'Functional' GRSs corresponding with specific biological pathways that shape BMI (adipogenesis, appetite and cardiopulmonary) were considered. The main outcome was phobic anxiety measured by the Crown Crisp Index (CCI) in 2004 in the NHS and in 2000 in the HPFS. In observational analysis, a 1-unit higher BMI was associated with higher phobic anxiety symptoms [women: β = 0.05, 95% confidence interval (CI) 0.030-0.068; men: β = 0.04, 95% CI 0.016-0.071). IV analyses showed that BMI was associated with higher phobic anxiety symptoms in the FTO-instrumented analysis (p = 0.005) but not in the GRS-instrumented analysis (p = 0.256). Functional GRSs showed heterogeneous, non-significant effects of BMI on phobic anxiety symptoms. Our findings do not provide conclusive evidence in favor of the hypothesis that higher BMI leads to higher levels of phobic anxiety, but rather suggest that genes that influence obesity, in particular FTO, may have direct effects on phobic anxiety, and hence that obesity and phobic anxiety may share common genetic determinants.

  18. The labor induction: integrated clinical and sonographic variables that predict the outcome.

    Science.gov (United States)

    Bueno, B; San-Frutos, L; Pérez-Medina, T; Barbancho, C; Troyano, J; Bajo, J

    2007-01-01

    To analyze the clinical and sonographic variables that predicts the success of labor induction. We studied the Bishop score, cervical length and parity in 196 pregnant women in the prediction of successful vaginal delivery within 24 h of induction. Logistic regression and segmentation analysis were performed. Cervical length (odds ratio (OR) 1.089, P<0.001), Bishop score (OR 0.751, P=0.001) and parity (OR 4.7, P<0.001) predict the success of labor induction. In a global analysis of the variables studied, the best statistic sequence that predicts the labor induction was found when we introduced parity in the first place. The success of labor induction in nulliparous was 50.8 and 83.3% in multiparous women (P=0.0001). Cervical length, Bishop score and parity, integrated in a flow chart, provide independent prediction of vaginal delivery within 24 h of induction.

  19. 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...

  20. A new centennial index to study the Western North Pacific Monsoon decadal variability

    Science.gov (United States)

    Vega, Inmaculada; Gómez-Delgado, F. de Paula; Gallego, David; Ribera, Pedro; Peña-Ortiz, Cristina; García-Herrera, Ricardo

    2016-04-01

    The concept of the Western North Pacific Summer Monsoon (WNPSM) appeared for the first time in 1987. It is, unlike the Indian Summer Monsoon (ISM) and the East Asian summer monsoon (EASM), an oceanic monsoon mostly driven by the meridional gradient of sea surface temperature. Its circulation is characterized by a northwest-southeast oriented monsoon trough with intense precipitation and low-level southwesterlies and upper-tropospheric easterlies in the region [100°-130° E, 5°-15°N]. Up to now, the primary index to characterize the WNPSM has been the Western North Pacific Monsoon Index (WNPMI) which covers the 1949-2013 period. The original WNPMI was defined as the difference of 850-hPa westerlies between two regions: D1 [5°-15°N, 100°-130°E] and D2 [20°-30°N, 110°-140°E]. Both domains are included in the main historical ship routes circumnavigating Asia for hundreds of years. Many of the logbooks of these ships have been preserved in historical archives and they usually contain daily observations of wind force and direction. Therefore, it has been possible to compute a new index of instrumental character, which reconstructs the WNPSM back to the middle of the 19th Century, by using solely historical wind direction records preserved in logbooks. We define the monthly Western North Pacific Directional Index (WNPDI) as the sum of the persistence of the low-level westerly winds in D1 and easterly winds in D2. The advantages of this new index are its nature (instrumental) and its length (1849-2013), which is 100 years longer than the WNPMI (which was based on reanalysis data). Our WNPDI shows a high correlation (r=+0.87, pCompetitividad through the project INCITE (CGL2013-44530-P, BES-2014-069733).

  1. Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets.

    Science.gov (United States)

    Pyo, Sujin; Lee, Jaewook; Cha, Mincheol; Jang, Huisu

    2017-01-01

    The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied to forecast financial markets. This study predicts the trends of the Korea Composite Stock Price Index 200 (KOSPI 200) prices using nonparametric machine learning models: artificial neural network, support vector machines with polynomial and radial basis function kernels. In addition, this study states controversial issues and tests hypotheses about the issues. Accordingly, our results are inconsistent with those of the precedent research, which are generally considered to have high prediction performance. Moreover, Google Trends proved that they are not effective factors in predicting the KOSPI 200 index prices in our frameworks. Furthermore, the ensemble methods did not improve the accuracy of the prediction.

  2. Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets.

    Directory of Open Access Journals (Sweden)

    Sujin Pyo

    Full Text Available The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied to forecast financial markets. This study predicts the trends of the Korea Composite Stock Price Index 200 (KOSPI 200 prices using nonparametric machine learning models: artificial neural network, support vector machines with polynomial and radial basis function kernels. In addition, this study states controversial issues and tests hypotheses about the issues. Accordingly, our results are inconsistent with those of the precedent research, which are generally considered to have high prediction performance. Moreover, Google Trends proved that they are not effective factors in predicting the KOSPI 200 index prices in our frameworks. Furthermore, the ensemble methods did not improve the accuracy of the prediction.

  3. Serum substance P concentrations to predict oocyte maturation index and clinical pregnancy.

    Science.gov (United States)

    Sahin, Yavuz; Özkaya, Enis; Kayatas Eser, Semra; Kutlu, Tayfun; Sanverdi, Ilhan; Tunali, Gulden; Karateke, Ates

    2017-03-01

    The aim of this study was to assess the predictive value of serum substance P (SP) concentrations on oocyte maturation and clinical pregnancy. Ninety-three women with unexplained infertility underwent intracytoplasmic sperm injection (ICSI) cycles. Antagonist protocol was started for each participant and at the day of oocyte pick up, serum samples were obtained from each participant to assess SP concentrations, and these concentrations were utilized to predict mature/total oocyte ratio and clinical pregnancy. SP concentration was a significant predictor for mature/total oocyte ratio > 0.75 and clinical pregnancy. In correlation analyses, maturation index was significantly correlated with FSH (r= -0.226, p = 0.03), estradiol (r = 0.239, p = 0.021), peak estradiol (r = 0.414, p < 0.001), and substance P (r = 0.796, p < 0.001). In multivariate analyses, number of immature (beta coefficient = -0.379, p < 0.001), mature oocyte (beta coefficient = 0.473, p < 0.001), SP concentration (beta coefficient = 0.723, p < 0.001) and maturation index (beta coefficient = -0.387, p = 0.003) were significantly associated with clinical pregnancy. SP concentrations at the day of oocyte pick up may be used to predict clinical pregnancy and may be an indirect indicator for cycle outcome in assisted reproductive technology (ART).

  4. 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.

  5. Clinicopathological variables predicting HER-2 gene status in immunohistochemistry-equivocal (2+) invasive breast cancer.

    Science.gov (United States)

    Ji, Yongling; Sheng, Liming; Du, Xianghui; Qiu, Guoqin; Chen, Bo; Wang, Xiaojia

    2014-07-01

    Human epidermal growth factor receptor-2 (HER-2) gene status is crucial to guide treatment decisions regarding the use of HER-2-targeted therapies in breast cancer. An invasive breast cancer with HER-2 2+ score is regarded as HER-2 status equivocal and should further determine by fluorescent in situ hybridization (FISH), which is considered the standard test for HER-2 status. Here, we aimed to establish a risk score to allow for prediction of the presence of HER-2 gene status. A total of 182 HER-2 2+ by immunohistochemistry (IHC) invasive breast cancer cases were enrolled in this study. The association between clinicopathological variables like age, sex, tumor grade, hormone receptor (HR) status, P53 and proliferation index (Ki67), and FISH result using US Food and Drug Administration (FDA) criteria was evaluated. Also, we compared the HER-2 FISH results using FDA criteria and 2013 American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) guideline. The study population had a median age of 48 years (range, 29-78 years). Estrogen receptor (ER) was expressed in 131 (72.0%) patients. 73.1% of patients (133/182) were progesterone receptor (PR) positive. The median Ki67 value was 20% (range, 3-90%). There was good agreement between the FDA and 2013 ASCO/CAP guideline. Sixty-three of all patients were HER-2 FISH amplified (positive) based on FDA criteria. Tumors with HER-2 amplified were more likely to harbor ER negative (58.8% vs. 25.2%, PHER-2 amplified groups (P=0.006). We created a risk score that comprised HR, P53 and Ki67. A significant association between risk score and HER-2 FISH amplification was observed (χ(2)=30.41, PHER-2 gene status in invasive breast cancer.

  6. Can metabolic control variables of diabetic patients predict their quality of life?

    Science.gov (United States)

    Dogan, Hakan; Harman, Ece; Kocoglu, Hakan; Sargin, Gokhan

    2016-01-01

    The type and the complexity of regimen aimed at achieving better glycemic control may impact patient's health-related quality of life (HRQoL) in diabetic patients. But, the relationship between HbA1c levels of diabetic patients and their HRQoL is not clear. Our study aims to determine whether metabolic control variables can predict HRQoL or not and also the impact of hypertension (HT) on HRQoL in type II diabetic patients. A total of 469 patients with type II diabetes and 134 control subjects were studied. Medical Outcomes Study Short-Form-General Health Survey (SF-36) questionnaire was used as a health survey tool to measure the QoL of patients in the study. SF-36 includes 8 individual subscales and two summary scales (physical component summary [PCS] and mental component summary [MCS]). Age, gender, fasting blood glucose, postprandial blood glucose, HbA1c, high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglyceride, total cholesterol, Apolipoprotein B (apoB), non-HDL-C, and body mass index values of the subjects were recorded. For statistical evaluation, SPSS (Statistical Package for the Social Sciences) 15 under Windows 7 was used. MCS values of patients group were statistically lower than control group (P .05). Diabetic patients with HT had significantly lower PCS and MCS values than those without HT. In addition, there was a negative correlation between HbA1c level and PCS and MCS values (P diabetic patients had significantly higher fasting blood glucose, postprandial blood glucose, HbA1c, HDL-C, LDL-C, total cholesterol, and body mass index values than hypertensive control subjects (P diabetic patients also had significantly lower PCS value than normotensive control subjects (P .05). PCS values in diabetic male patients were significantly higher than in diabetic female patients (P diabetic patients (P > .05). In our study, it is clear that diabetes affected the patients' HRQoL. In addition, we showed negative

  7. Deconvolution of pigment and physiologically related photochemical reflectance index variability at the canopy scale over an entire growing season.

    Science.gov (United States)

    Hmimina, G; Merlier, E; Dufrêne, E; Soudani, K

    2015-08-01

    The sensitivity of the photochemical reflectance index (PRI) to leaf pigmentation and its impacts on its potential as a proxy for light-use efficiency (LUE) have recently been shown to be problematic at the leaf scale. Most leaf-to-leaf and seasonal variability can be explained by such a confounding effect. This study relies on the analysis of PRI light curves that were generated at the canopy scale under natural conditions to derive a precise deconvolution of pigment-related and physiologically related variability in the PRI. These sources of variability were explained by measured or estimated physiologically relevant variables, such as soil water content, that can be used as indicators of water availability and canopy chlorophyll content. The PRI mainly reflected the variability in the pigment content of the canopy. However, the corrected PRI, which was obtained by subtracting the pigment-related seasonal variability from the PRI measurement, was highly correlated with the upscaled LUE measurements. Moreover, the sensitivity of the PRI to the leaf pigment content may mask the PRI versus LUE relationship or result in an artificial relationship that reflects the relationship of chlorophyll versus LUE, depending on the species phenology. © 2015 John Wiley & Sons Ltd.

  8. 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.

  9. 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).

  10. 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.

  11. Predicting the sound reduction index of finite size specimen by a simplified spatial windowing technique

    Science.gov (United States)

    Vigran, T. E.

    2009-08-01

    The transfer matrix technique is an efficient tool for calculating sound transmission through multilayered structures. However, due to the assumption of infinite size layers important discrepancies may be found between predicted and experimental data. The spatial windowing technique introduced by Villot et al. [Predicting the acoustical radiation of finite size multi-layered structures by applying windowing on infinite structures, Journal of Sound and Vibration 245 (2001) 433-455] has shown to give data much closer to measurement results than other measures, such as limiting the maximum angle of incidence when integrating to obtain the sound reduction index for diffuse incidence. Using a two-dimensional spatial window, also including the azimuth angle implies, however, that two double numerical integrations must be performed. As predicted results are compared with laboratory data, where the aspect ratio of the test object is required to be less than 1:2, a simplified procedure may be applied involving two single integrals only. It is shown that the accuracy in the end result may in practice be maintained by this simplified procedure.

  12. Evaluating the predictive ability of childhood body mass index classification systems for overweight and obesity at 18 years.

    Science.gov (United States)

    Brann, Ebba; Sjöberg, Agneta; Chaplin, John E; Leu, Monica; Mehlig, Kirsten; Albertsson-Wikland, Kerstin; Lissner, Lauren

    2015-12-01

    To evaluate the performance of three childhood body mass index classification systems defining weight status at age 10, for predicting overweight and obesity at 18 years, according to the World Health Organization adult body mass index classification. Weight and height of 4235 Swedish girls and boys were measured both at around ages 10 and 18 years. Predictive ability of the extended International Obesity Task Force body mass index cut-offs (2012), the World Health Organization body mass index-for-age (2007) and a Swedish body mass index reference (2001) were assessed for sensitivity and specificity. For predicting overweight including obesity at 18 years, the World Health Organization 2007 and the Swedish body mass index reference 2001 had similar sensitivity, 68% and 71%. The International Obesity Task Force 2012 had a significantly lower sensitivity, 53%. Specificity was 82-91% and highest for International Obesity Task Force 2012. For predicting obesity, the sensitivity for International Obesity Task Force 2012 was 29%, significantly lower than for the other two, 63% and 70%. Specificity was 94-100%, and highest for International Obesity Task Force 2012. In situations when optimal screening sensitivity is required for identifying as many high-risk children as possible, the World Health Organization 2007 and the Swedish body mass index reference 2001 performed better than the International Obesity Task Force 2012. However, it is important to keep in mind that the International Obesity Task Force 2012 will identify the fewest false positives. © 2015 the Nordic Societies of Public Health.

  13. Glycemic variability in relation to oral disposition index in the subjects with different stages of glucose tolerance.

    Science.gov (United States)

    Chen, Tong; Xu, Feng; Su, Jian-Bin; Wang, Xue-Qin; Chen, Jin-Feng; Wu, Gang; Jin, Yan; Wang, Xiao-Hua

    2013-01-01

    Glucose variability could be an independent risk factor for diabetes complications in addition to average glucose. The deficiency in islet β cell secretion and insulin sensitivity, the two important pathophysiological mechanisms of diabetes, are responsible for glycemic disorders. The oral disposition index evaluated by product of insulin secretion and sensitivity is a useful marker of islet β cell function. The aim of the study is to investigate glycemic variability in relation to oral disposition index in the subjects across a range of glucose tolerance from the normal to overt type 2 diabetes. 75-g oral glucose tolerance test (OGTT) was performed in total 220 subjects: 47 with normal glucose regulation (NGR), 52 with impaired glucose metabolism (IGM, 8 with isolated impaired fasting glucose [IFG], 18 with isolated impaired glucose tolerance [IGT] and 26 with combined IFG and IGT), 61 screen-diagnosed diabetes by isolated 2-h glucose (DM2h) and 60 newly diagnosed diabetes by both fasting and 2-h glucose (DM). Insulin sensitivity index (Matsuda index, ISI), insulin secretion index (ΔI30/ΔG30), and integrated β cell function measured by the oral disposition index (ΔI30/ΔG30 multiplied by the ISI) were derived from OGTT. All subjects were monitored using the continuous glucose monitoring system for consecutive 72 hours. The multiple parameters of glycemic variability included the standard deviation of blood glucose (SD), mean of blood glucose (MBG), high blood glucose index (HBGI), continuous overlapping net glycemic action calculated every 1 h (CONGA1), mean of daily differences (MODD) and mean amplitude of glycemic excursions (MAGE). From the NGR to IGM to DM2h to DM group, the respective values of SD (mean ± SD) (0.9 ± 0.3, 1.5 ± 0.5, 1.9 ± 0.6 and 2.2 ± 0.6 mmol/), MBG (5.9 ± 0.5, 6.7 ± 0.7, 7.7 ± 1.0 and 8.7 ± 1.5 mmol/L), HGBI [median(Q1-Q3)][0.8(0.2-1.2), 2.0(1.2-3.7), 3.8(2.4-5.6) and 6

  14. Latent variable modeling improves AKI risk factor identification and AKI prediction compared to traditional methods

    OpenAIRE

    Smith, Loren E.; Smith, Derek K.; Blume, Jeffrey D.; Siew, Edward D.; Billings, Frederic T.

    2017-01-01

    Background Acute kidney injury (AKI) is diagnosed based on postoperative serum creatinine change, but AKI models have not consistently performed well, in part due to the omission of clinically important but practically unmeasurable variables that affect creatinine. We hypothesized that a latent variable mixture model of postoperative serum creatinine change would partially account for these unmeasured factors and therefore increase power to identify risk factors of AKI and improve predictive ...

  15. Ability to predict the development of surgical site infection in cardiac surgery using the Australian Clinical Risk Index versus the National Nosocomial Infections Surveillance-derived Risk Index.

    Science.gov (United States)

    Figuerola-Tejerina, A; Bustamante, E; Tamayo, E; Mestres, C A; Bustamante-Munguira, J

    2017-06-01

    Surgical site infection (SSI) is a major infectious complication that increases mortality, morbidity, and healthcare costs. There are scores attempting to classify patients for calculating SSI risk. Our objectives were to validate the Australian Clinical Risk Index (ACRI) in a European population after cardiac surgery, comparing it against the National Nosocomial Infections Surveillance-derived risk index (NNIS) and analyzing the predictive power of ACRI for SSI in valvular patients. All the patients that who underwent cardiac surgery in a tertiary university hospital between 2011 and 2015 were analyzed. The patients were divided into valvular and coronary groups, excluding mixed patients. The ACRI score was validated in both groups and its ability to predict SSI was compared to the NNIS risk index. We analyzed 1,657 procedures. In the valvular patient group (n: 1119), a correlation between the ACRI score and SSI development (p < 0.05) was found; there was no such correlation with the NNIS index. The area under the receiver-operating characteristic curve (AUC) was 0.64 (confidence interval [CI] 95%, 0.5-0.7) for ACRI and 0.62 (95% CI, 0.5-0.7) for NNIS. In the coronary group (n: 281), there was a correlation between ACRI and SSI but no between NNIS and SSI. The ACRI AUC was 0.70 (95% CI, 0.5-0.8) and the NNIS AUC was 0.60 (95% CI, 0.4-0.7). The ACRI score has insufficient predictive power, although it predicts SSI development better than the NNIS index, fundamentally in coronary artery bypass grafting (CABG). Further studies analyzing determining factors are needed.

  16. Adding items that assess changes in activities of daily living does not improve the predictive accuracy of the Palliative Prognostic Index.

    Science.gov (United States)

    Hamano, Jun; Tokuda, Yasuharu; Kawagoe, Shohei; Shinjo, Takuya; Shirayama, Hiroto; Ozawa, Taketoshi; Shishido, Hideki; Otomo, Sen; Nagayama, Jun; Baba, Mika; Tei, Yo; Hiramoto, Shuji; Suga, Akihiko; Hisanaga, Takayuki; Ishihara, Tatsuhiko; Iwashita, Tomoyuki; Kaneishi, Keisuke; Kuriyama, Toshiyuki; Maeda, Takashi; Morita, Tatsuya

    2017-03-01

    Changes in activities of daily living in cancer patients may predict their survival. The Palliative Prognostic Index is a useful tool to evaluate cancer patients, and adding an item about activities of daily living changes might improve its predictive value. To clarify whether adding an item about activities of daily living changes improves the accuracy of Palliative Prognostic Index. Multicenter prospective cohort study. A total of 58 palliative care services in Japan. Patients aged >20 years diagnosed with locally extensive or metastatic cancer (including hematological neoplasms) who had been admitted to palliative care units, were receiving care by hospital-based palliative care teams, or were receiving home-based palliative care. Palliative care physicians recorded clinical variables at the first assessment and followed up patients 6 months later. A total of 2425 subjects were recruited and 2343 of these had analyzable data. The C-statistic of the original Palliative Prognostic Index was 0.801, and those of modified Palliative Prognostic Indices ranged from 0.793 to 0.805 at 3 weeks. For 6-week survival predictions, the C-statistic of the original Palliative Prognostic Index was 0.802, and those of modified Palliative Prognostic Indices ranged from 0.791 to 0.799. The weighted kappa of the original Palliative Prognostic Index was 0.510, and those of modified Palliative Prognostic Indices ranged from 0.484 to 0.508. Adding items about activities of daily living changes to the Palliative Prognostic Index did not improve prognostic value in advanced cancer patients.

  17. Springback prediction and optimization of variable stretch force trajectory in three-dimensional stretch bending process

    Science.gov (United States)

    Teng, Fei; Zhang, Wanxi; Liang, Jicai; Gao, Song

    2015-11-01

    Most of the existing studies use constant force to reduce springback while researching stretch force. However, variable stretch force can reduce springback more efficiently. The current research on springback prediction in stretch bending forming mainly focuses on artificial neural networks combined with the finite element simulation. There is a lack of springback prediction by support vector regression (SVR). In this paper, SVR is applied to predict springback in the three-dimensional stretch bending forming process, and variable stretch force trajectory is optimized. Six parameters of variable stretch force trajectory are chosen as the input parameters of the SVR model. Sixty experiments generated by design of experiments (DOE) are carried out to train and test the SVR model. The experimental results confirm that the accuracy of the SVR model is higher than that of artificial neural networks. Based on this model, an optimization algorithm of variable stretch force trajectory using particle swarm optimization (PSO) is proposed. The springback amount is used as the objective function. Changes of local thickness are applied as the criterion of forming constraints. The objection and constraints are formulated by response surface models. The precision of response surface models is examined. Six different stretch force trajectories are employed to certify springback reduction in the optimum stretch force trajectory, which can efficiently reduce springback. This research proposes a new method of springback prediction using SVR and optimizes variable stretch force trajectory to reduce springback.

  18. Variables predicting low infant developmental scores: maternal age above 30 years is a main predictor.

    Science.gov (United States)

    Alvik, Astrid

    2014-03-01

    To explore variables predicting low developmental scores in 6-month-old infants in a population-based study. In a longitudinal study representative of pregnant women in Oslo, Norway, questionnaires were answered at 17 and 30 weeks of pregnancy and 6 months after term; N = 1053 after exclusions (women with non-Scandinavian ethnicity, twin births, infants 7.0 months corrected age, and birth weight infant having older siblings predicted a low score on ASQ Total. These variables also predicted low scores on several ASQ areas (i.e. Communication, Gross motor, Fine motor, Problem-solving and Personal social), together with maternal major lifetime depression and feeling lonely. Protective variables were increasing infant birth weight (Gross motor) and pregnancy smoking (Communication). Other maternal sociodemographic variables, and infant sex, had no predictive power. Already at a maternal age of 31, the mean age of the pregnant women, the possibility of a low infant score increased significantly. In this population-based study, higher maternal age, having older siblings, and a history of maternal major lifetime depression, mainly predicts low developmental scores in 6-month-old infants.

  19. Can we predict fall asthma exacerbations? Validation of the seasonal asthma exacerbation index.

    Science.gov (United States)

    Hoch, Heather E; Calatroni, Agustin; West, Joseph B; Liu, Andrew H; Gergen, Peter J; Gruchalla, Rebecca S; Khurana Hershey, Gurjit K; Kercsmar, Carolyn M; Kim, Haejin; Lamm, Carin I; Makhija, Melanie M; Mitchell, Herman E; Teach, Stephen J; Wildfire, Jeremy J; Busse, William W; Szefler, Stanley J

    2017-10-01

    A Seasonal Asthma Exacerbation Predictive Index (saEPI) was previously reported based on 2 prior National Institute of Allergy and Infectious Diseases Inner City Asthma Consortium trials. This study sought to validate the saEPI in a separate trial designed to prevent fall exacerbations with omalizumab therapy. The saEPI and its components were analyzed to characterize those who had an asthma exacerbation during the Preventative Omalizumab or Step-Up Therapy for Fall Exacerbations (PROSE) study. We characterized those inner-city children with and without asthma exacerbations in the fall period treated with guidelines-based therapy (GBT) in the absence and presence of omalizumab. A higher saEPI was associated with an exacerbation in both the GBT alone (P asthma exacerbation in both groups. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. All rights reserved.

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

    Science.gov (United States)

    van Wijngaarden, Sander J.; Bronkhorst, Adelbert W.; Houtgast, Tammo; Steeneken, Herman J. M.

    2004-03-01

    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 for sentence intelligibility in noise, for populations of native and non-native communicators, a correction function for the interpretation of the STI is derived. This function is applied to determine the appropriate STI ranges with qualification labels (``bad''-``excellent''), for specific populations of non-natives. The correction function is derived by relating the non-native psychometric function to the native psychometric function by a single parameter (ν). For listeners, the ν parameter is found to be highly correlated with linguistic entropy. It is shown that the proposed correction function is also valid for conditions featuring bandwidth limiting and reverberation.

  1. 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.)

  2. Predicting Vegetation Condition from ASCAT Soil Water Index over Southwest India

    Science.gov (United States)

    Pfeil, Isabella Maria; Hochstöger, Simon; Amarnath, Giriraj; Pani, Peejush; Enenkel, Markus; Wagner, Wolfgang

    2017-04-01

    In India, extreme water scarcity events are expected to occur on average every five years. Record-breaking droughts affecting millions of human beings and livestock are common. If the south-west monsoon (summer monsoon) is delayed or brings less rainfall than expected, a season's harvest can be destroyed despite optimal farm management, leading to, in the worst case, life-threatening circumstances for a large number of farmers. Therefore, the monitoring of key drought indicators, such as the healthiness of the vegetation, and subsequent early warning is crucial. The aim of this work is to predict vegetation state from earth observation data instead of relying on models which need a lot of input data, increasing the complexity of error propagation, or seasonal forecasts, that are often too uncertain to be used as a regression component for a vegetation parameter. While precipitation is the main water supply for large parts of India's agricultural areas, vegetation datasets such as the Normalized Difference Vegetation Index (NDVI) provide reliable estimates of vegetation greenness that can be related to vegetation health. Satellite-derived soil moisture represents the missing link between a deficit in rainfall and the response of vegetation. In particular the water available in the root zone plays an important role for near-future vegetation health. Exploiting the added-value of root zone soil moisture is therefore crucial, and its use in vegetation studies presents an added value for drought analyses and decision-support. The soil water index (SWI) dataset derived from the Advanced Scatterometer (ASCAT) on board the Metop satellites represents the water content that is available in the root zone. This dataset shows a strong correlation with NDVI data obtained from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is exploited in this study. A linear regression function is fit to the multi-year SWI and NDVI dataset with a temporal

  3. 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.

  4. Diastolic Heart Failure Predicted by Left Atrial Expansion Index in Patients with Severe Diastolic Dysfunction.

    Directory of Open Access Journals (Sweden)

    Shih-Hung Hsiao

    Full Text Available Left atrial (LA echocardiographic parameters are increasingly used to predict clinically relevant cardiovascular events. The study aims to evaluate the LA expansion index (LAEI for predicting diastolic heart failure (HF in patients with severe left ventricular (LV diastolic dysfunction.This prospective study enrolled 162 patients (65% male with preserved LV systolic function and severe diastolic dysfunction (132 grade 2 patients, 30 grade 3 patients. All patients had sinus rhythm at enrollment. The LAEI was calculated as (Volmax - Volmin x 100% / Volmin, where Volmax was defined as maximal LA volume and Volmin was defined as minimal volume. The endpoint was hospitalization for HF withp reserved LV ejection fraction (HFpEF.The median follow-up duration was 2.9 years. Fifty-four patients had cardiovascular events, including 41 diastolic and 8 systolic HF hospitalizations. In these 54 patients, 13 in-hospital deaths and 5 sudden out-of-hospital deaths occurred. Multivariate analyses revealed that HFpEF was associated with LAEI.and atrial fibrillation during follow-up. For predicting HFpEF, the LAEI had a hazard ratio of 1.197per 10% decrease. In patients who had HFpEF events, the LAEI significantly (P< 0.0001 decreased from 69±18% to 39±11% during hospitalization. Although the LAEI improved during follow-up (53±13%, it did not return to baseline.The LAEI predicts HFpEF in patients with severe diastolic dysfunction; it worsens during HFpEF events and partially recovers during followup.

  5. Real-time index for predicting successful golf putting motion using multichannel EEG.

    Science.gov (United States)

    Muangjaroen, Piyachat; Wongsawat, Yodchanan

    2012-01-01

    A skill in goal-directed sport performance is an ability involving with many factors of both external and internal concernment. External factors are still developed while internal factors are challenged topic to understand for improving the performance. Internal concernment is explained an effective performance as estimation, solving strategy, planning and decision on the brain. These conjunctions are relevant to somatosensory information, focus attention and fine motor control of cortical activity. Five skilled right-handed golfers were recruited to be subjected of studying the criteria on how to predict golf putt success. Each of their putts was calculated in power spectral analysis by comparing to the pre-movement period. Successful and unsuccessful putt were classified by focusing on the frontal-midline(Fz), parietal-midline(Pz), central midline(Cz), left central(C3) and right central(C4) which supported by few consistency studies that they are related to a primary sensory motor area, focus attention and working memory processing. Results were shown that high alpha power on C4, theta power on Fz, theta power and high alpha power on Pz can be calculated to use as index of predicting golf putt success. Real-time monitoring system with friendly GUI was proposed in this study as promising preliminary study. Expected goal in the future is to apply this real-time golf putting prediction system into a biofeedback system to increase the golf putting's accuracy. However, it still needs more subjects to increase credibility and accuracy of the prediction.

  6. 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.

  7. [Interest of Geriatric Nutritional Risk Index for mortality prediction in hemodialysis patients: preliminary study].

    Science.gov (United States)

    Sirajedine, Khaled; Fardous, Rida; Al Adib, Mohamad; Colomb, Henry; Maurin, Audrey

    2012-07-01

    Geriatric Nutritional Risk Index (GNRI) is a simple and quantitative method (based on three objective measurements: weight, height, albumin) for screening patients at risk for malnutrition. However no data are available regarding its relation with mortality in Caucasian hemodialysis patients. We tested the predictive value of GNRI on mortality in a hemodialysis population followed up prospectively for 18 months. A total of 46 stable prevalent (mean age: 76 ± 11 years, range: 42-95) hemodialysis patients from one center were included in the study. GNRI with other nutritional parameters were evaluated for all patients. Sixteen patients (35%) died during the 18 months of follow-up. Multiple logistic model showed that GNRI and Charlson co-morbidity score were significant predictors of mortality. Age and gender were not significant. Our preliminary study carried out on a series of prevalent hemodialysis patients suggests that GNRI is predictor of mortality. To recommend the use of this index for the screening of hemodialysis patients with malnutrition at risk of mortality, our results should be confirmed by a large cohort study. Copyright © 2012 Association Société de néphrologie. Published by Elsevier SAS. All rights reserved.

  8. Recursive Partitioning Analysis Index Is Predictive for Overall Survival in Patients Undergoing Spine Stereotactic Body Radiation Therapy for Spinal Metastases

    Energy Technology Data Exchange (ETDEWEB)

    Chao, Samuel T., E-mail: chaos@ccf.org [Department of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Brain Tumor and Neuro-oncology Center, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Koyfman, Shlomo A.; Woody, Neil [Department of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Angelov, Lilyana [Department of Neurosurgery, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Brain Tumor and Neuro-oncology Center, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Soeder, Sherry L. [Department of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Brain Tumor and Neuro-oncology Center, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Reddy, Chandana A. [Department of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Rybicki, Lisa A. [Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Djemil, Toufik [Department of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Suh, John H. [Department of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Brain Tumor and Neuro-oncology Center, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States); Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio 44195 (United States)

    2012-04-01

    Purpose: To generate a prognostic index using recursive partitioning analysis (RPA) for patients undergoing spine stereotactic body radiation therapy (sSBRT) for spinal metastases (sMet). Methods and Materials: From an institutional review board-approved database, 174 patients were treated for sMet with sSBRT between February 2006 and August 2009. Median dose was 14 Gy (range, 8-24 Gy), typically in a single fraction (range, 1-5). Kaplan-Meier analysis was performed to detect any correlation between survival and histology. Histologies were divided into favorable (breast and prostate), radioresistant (renal cell, melanoma and sarcoma), and other (all other histologies). RPA was performed to identify any association of the following variables with overall survival (OS) following sSBRT: histology, gender, age, Karnofsky performance status (KPS), control of primary, extraosseous metastases, time from primary diagnosis (TPD), dose of sSBRT ({<=}14 Gy vs. >14 Gy), extent of spine disease (epidural only, bone and epidural, bone only), upfront or salvage treatment, presence of paraspinal extension, and previous surgery. Results: Median follow-up was 8.9 months. Median OS time from sSBRT was 10.7 months. Median OS intervals for favorable histologies were 14 months, 11.2 months for radioresistant histologies, and 7.3 months for other histologies (p = 0.02). RPA analysis resulted in three classes (p < 0.0001). Class 1 was defined as TPD of >30 months and KPS of >70; Class 2 was TPD of >30 months and KPS of {<=}70 or a TPD of {<=}30 months and age <70 years old; Class 3 was TPD of {<=}30 months and age {>=}70 years old. Median OS was 21.1 months for Class 1 (n = 59), 8.7 months for Class 2 (n = 104), and 2.4 months for Class 3 (n = 11). Conclusion: sSBRT patients treated for sMet have a wide variability in OS. We developed an RPA classification system that is predictive of OS. While many patients are treated for palliation of pain or to avoid symptomatic progression, this

  9. A clinical index to predict progression from mild cognitive impairment to dementia due to Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Sei J Lee

    Full Text Available BACKGROUND: Mild cognitive impairment is often a precursor to dementia due to Alzheimer's disease, but many patients with mild cognitive impairment never develop dementia. New diagnostic criteria may lead to more patients receiving a diagnosis of mild cognitive impairment. OBJECTIVE: To develop a prediction index for the 3-year risk of progression from mild cognitive impairment to dementia relying only on information that can be readily obtained in most clinical settings. DESIGN AND PARTICIPANTS: 382 participants diagnosed with amnestic mild cognitive impairment enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI, a multi-site, longitudinal, observational study. MAIN PREDICTORS MEASURES: Demographics, comorbid conditions, caregiver report of participant symptoms and function, and participant performance on individual items from basic neuropsychological scales. MAIN OUTCOME MEASURE: Progression to probable Alzheimer's disease. KEY RESULTS: Subjects had a mean (SD age of 75 (7 years and 43% progressed to probable Alzheimer's disease within 3 years. Important independent predictors of progression included being female, resisting help, becoming upset when separated from caregiver, difficulty shopping alone, forgetting appointments, number of words recalled from a 10-word list, orientation and difficulty drawing a clock. The final point score could range from 0 to 16 (mean [SD]: 4.2 [2.9]. The optimism-corrected Harrell's c-statistic was 0.71(95% CI: 0.68-0.75. Fourteen percent of subjects with low risk scores (0-2 points, n = 124 converted to probable Alzheimer's disease over 3 years, compared to 51% of those with moderate risk scores (3-8 points, n = 223 and 91% of those with high risk scores (9-16 points, n = 35. CONCLUSIONS: An index using factors that can be obtained in most clinical settings can predict progression from amnestic mild cognitive impairment to probable Alzheimer's disease and may help clinicians

  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. 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 patients with 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....

  12. Predicting timothy mineral concentrations, dietary cation-anion difference, and grass tetany index by near-infrared reflectance spectroscopy.

    Science.gov (United States)

    Tremblay, G F; Nie, Z; Bélanger, G; Pelletier, S; Allard, G

    2009-09-01

    The mineral concentration of forage grasses plays a significant role in 2 metabolic disorders in dairy cattle production, namely, hypocalcemia (milk fever) and hypomagnesemia (grass tetany). Risks of occurrence of these 2 metabolic disorders can be evaluated by determining the dietary cation-anion difference (DCAD) and the grass tetany (GT) index of forages and specific rations. The objective of this study was to evaluate the feasibility of predicting timothy (Phleum pratense L.) mineral concentrations of Na, K, Ca, Mg, Cl, S, and P, the DCAD, and the GT index by near-infrared reflectance spectroscopy (NIRS). Timothy samples (n = 1,108) were scanned using NIRS and analyzed for the concentration of 7 mineral elements. Calculations of the DCAD were made using 3 different formulas, and the GT index was also calculated. Samples were divided into calibration (n = 240) and validation (n = 868) sets. The calibration, cross-validation, and prediction for mineral concentrations, the DCAD, and the GT index were performed using modified partial least squares regression. Concentrations of K, Ca, Mg, Cl, and P were successfully predicted with coefficients of determination of prediction (R(P)2) of 0.69 to 0.92 and coefficients of variation of prediction (CV(P)) ranging from 6.6 to 11.4%. The prediction of Na and S concentrations failed, with respective R(P)2 of 0.58 and 0.53 and CV(P) of 82.2 and 12.9%. The 3 calculated DCAD and the GT index were predicted successfully, with R(P)2 >0.90 and CV(P) <20%. Our results confirm the feasibility of using NIRS to predict K, Ca, Mg, and Cl concentrations, as well as the DCAD and the GT index, in timothy.

  13. Spike-train variability of auditory neurons in vivo: dynamic responses follow predictions from constant stimuli.

    Science.gov (United States)

    Schaette, Roland; Gollisch, Tim; Herz, Andreas V M

    2005-06-01

    Reliable accounts of the variability observed in neural spike trains are a prerequisite for the proper interpretation of neural dynamics and coding principles. Models that accurately describe neural variability over a wide range of stimulation and response patterns are therefore highly desirable, especially if they can explain this variability in terms of basic neural observables and parameters such as firing rate and refractory period. In this work, we analyze the response variability recorded in vivo from locust auditory receptor neurons under acoustic stimulation. In agreement with results from other systems, our data suggest that neural refractoriness has a strong influence on spike-train variability. We therefore explore a stochastic model of spike generation that includes refractoriness through a recovery function. Because our experimental data are consistent with a renewal process, the recovery function can be derived from a single interspike-interval histogram obtained under constant stimulation. The resulting description yields quantitatively accurate predictions of the response variability over the whole range of firing rates for constant-intensity as well as amplitude-modulated sound stimuli. Model parameters obtained from constant stimulation can be used to predict the variability in response to dynamic stimuli. These results demonstrate that key ingredients of the stochastic response dynamics of a sensory neuron are faithfully captured by a simple stochastic model framework.

  14. Working memory and intraindividual variability as neurocognitive indicators in ADHD: examining competing model predictions.

    Science.gov (United States)

    Kofler, Michael J; Alderson, R Matt; Raiker, Joseph S; Bolden, Jennifer; Sarver, Dustin E; Rapport, Mark D

    2014-05-01

    The current study examined competing predictions of the default mode, cognitive neuroenergetic, and functional working memory models of attention-deficit/hyperactivity disorder (ADHD) regarding the relation between neurocognitive impairments in working memory and intraindividual variability. Twenty-two children with ADHD and 15 typically developing children were assessed on multiple tasks measuring intraindividual reaction time (RT) variability (ex-Gaussian: tau, sigma) and central executive (CE) working memory. Latent factor scores based on multiple, counterbalanced tasks were created for each construct of interest (CE, tau, sigma) to reflect reliable variance associated with each construct and remove task-specific, test-retest, and random error. Bias-corrected, bootstrapped mediation analyses revealed that CE working memory accounted for 88% to 100% of ADHD-related RT variability across models, and between-group differences in RT variability were no longer detectable after accounting for the mediating role of CE working memory. In contrast, RT variability accounted for 10% to 29% of between-group differences in CE working memory, and large magnitude CE working memory deficits remained after accounting for this partial mediation. Statistical comparison of effect size estimates across models suggests directionality of effects, such that the mediation effects of CE working memory on RT variability were significantly greater than the mediation effects of RT variability on CE working memory. The current findings question the role of RT variability as a primary neurocognitive indicator in ADHD and suggest that ADHD-related RT variability may be secondary to underlying deficits in CE working memory.

  15. 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

  16. 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

    2017-12-28

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

  17. 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.

  18. A prospective study evaluating utility of Mannheim peritonitis index in predicting prognosis of perforation peritonitis.

    Science.gov (United States)

    Sharma, Rajesh; Ranjan, Vikrant; Jain, Suraj; Joshi, Tulika; Tyagi, Anurag; Chaphekar, Rohan

    2015-08-01

    We aimed to validate Mannheim peritonitis index (MPI) for prediction of outcome in patients with perforation peritonitis. A prospective study involving 100 subjects operated for perforation peritonitis over the period of 2 years was designed. Postevaluation of predesigned performa, MPI score was calculated and analyzed for each patient with death being the main outcome measure. The MPI scores were divided into three categories; scores 25 (category 3). Our study consisted of 82 males and 18 females (male:female ratio 4.56:1), with the mean patients age of 37.96 ± 17.49 years. 47, 26, and 27 cases belonged to MPI score categories 1, 2, and 3, respectively. The most common origin of sepsis was ileal with small intestine dominating the source of perforation. When the individual parameters of MPI score were assessed against the mortality only, age >50 years (P = 0.015), organ failure (P = 0.0001), noncolonic origin of sepsis (P = 0.002), and generalized peritonitis (P = 0.0001) significantly associated with mortality. The sensitivity of MPI was 92% with a specificity of 78% in receiver operating characteristic curves. MPI is an effective tool for prediction of mortality in cases of perforation peritonitis.

  19. Location of breakfast consumption predicts body mass index change in young Hong Kong children.

    Science.gov (United States)

    Tin, S P P; Ho, S Y; Mak, K H; Wan, K L; Lam, T H

    2012-07-01

    An association between weight gain and breakfast skipping has been reported, but breakfast location was rarely considered. We investigated the prospective associations between breakfast location, breakfast skipping and body mass index (BMI) change in a large cohort of Chinese children. Our baseline cohort consisted of 113,457 primary 4 (US grade 4) participants of the Hong Kong Department of Health Student Health Service in 1998-2000. Of these, 68,606 (60.5%) had complete records and were successfully followed-up 2 years later. Data on breakfast consumption and location were collected at both time points along with other lifestyle characteristics. BMI was derived from objectively measured height and weight. Associations between breakfast habits and BMI change were assessed by multivariable linear regression, adjusting for demographic, socioeconomic and lifestyle characteristics. At baseline, 85.3, 9.4 and 5.2% of children had breakfast at home, away from home and skipped breakfast, respectively. Prospectively, having breakfast away from home (vs at home) predicted a greater BMI increase over two years (β = 0.15; 95% CI: 0.11-0.18). Breakfast skipping had a comparable, slightly smaller effect (0.13; 0.09-0.18). Both breakfast skipping and eating breakfast away from home predict greater increases in BMI during childhood, the effect being slightly stronger in the latter. Having breakfast, particularly at home, could have important implications for weight management and reducing obesity in children. Further research is required to gain insight into potential underlying mechanisms.

  20. Gender, body mass index, and PPARγ polymorphism are good indicators in hyperuricemia prediction for Han Chinese.

    Science.gov (United States)

    Lee, Ming-Fen; Liou, Tsan-Hon; Wang, Weu; Pan, Wen-Harn; Lee, Wei-Jei; Hsu, Chung-Tan; Wu, Suh-Fen; Chen, Hsin-Hung

    2013-01-01

    Hyperuricemia is closely associated with obesity and metabolic abnormalities, which is also an independent risk factor for cardiovascular diseases. The PPARγ gene, which is linked to obesity and metabolic abnormalities in Han Chinese, might be considered a top candidate gene that is involved in hyperuricemia. This study recruited 457 participants, aged 20-40 years old, to investigate the associations of the PPARγ gene and metabolic parameters with hyperuricemia. Three tag-single nucleotide polymorphisms, rs2292101, rs4684846, and rs1822825, of the PPARγ gene were selected to explore their association with hyperuricemia. Risk genotypes on rs1822825 of the PPARγ gene exhibited statistical significance with hyperuricemia (odds ratio: 1.9; 95% confidence interval: 1.05-3.57). Although gender, body mass index (BMI), serum total cholesterol concentration, or protein intake per day were statistically associated with hyperuricemia, the combination of BMI, gender, and rs1822825, rather than that of age, serum lipid profile, blood pressure, and protein intake per day, satisfied the predictability for hyperuricemia (sensitivity: 69.3%; specificity: 83.7%) in Taiwan-born obese Han Chinese. BMI, gender, and the rs1822825 polymorphism in the PPARγ gene appeared good biomarkers in hyperuricemia; therefore, these powerful indicators may be included in the prediction of hyperuricemia to increase the accuracy of the analysis.

  1. Interaction between geriatric nutritional risk index and decoy receptor 3 predicts mortality in chronic hemodialysis patients.

    Science.gov (United States)

    Tsai, Ming-Tsun; Hu, Fen-Hsiang; Lien, Tse-Jen; Chen, Ping-Jen; Huang, Tung-Po; Tarng, Der-Cherng

    2014-01-01

    Protein-energy wasting (PEW) is common and associated with poor outcome in hemodialysis patients. In hemodialysis patients, geriatric nutritional risk index (GNRI) and decoy receptor 3 (DcR3) have been shown as the nutritional and inflammatory markers, respectively. The present study aimed to assess the predictive ability of GNRI and DcR3 for PEW status and long-term outcomes in chronic hemodialysis patients. A prospective cohort of 318 hemodialysis patients was conducted with a median follow-up of 54 months. Malnutrition-inflammation score (MIS) was used as the reference standard for the presence of PEW. Endpoints were cardiovascular and all-cause mortality. Baseline GNRI had a strong negative correlation with DcR3 and MIS score. For patients with age risk factors, GNRI together with DcR3 further significantly improved the predictability for overall mortality (c statistic, 0.823). Low GNRI and high DcR3 were the alternatives for identifying hemodialysis patients at risk of PEW and overall mortality. Further studies are needed to verify whether timely recognition of hemodialysis patients with a high malnutrition-inflammation risk could reduce their mortality by appropriate interventional strategies.

  2. 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.

  3. Can Patient Variables Measured on Arrival to the Emergency Department Predict Disposition in Medium-acuity Patients?

    Science.gov (United States)

    Riordan, John P; Dell, Wayne L; Patrie, James T

    2017-05-01

    Emergency department crowding has led to innovative "front end" care models to safely and efficiently care for medium and lower acuity patients. In the United States, most treatment algorithms rely on the emergency severity index (ESI) triage tool to sort patients. However, there are no objective criteria used to differentiate ESI 3 patients. We seek to derive and validate a model capable of predicting patient discharge disposition (DD) using variables present on arrival to the emergency department for ESI 3 patients. Our retrospective cohort study included adult patients with an ESI triage designation 3 treated in an academic emergency department over the course of 2 successive years (2013-2015). The main outcome was DD. Two datasets were used in the modeling process. One dataset, the derivation dataset (n = 25,119), was used to develop the statistical model, while the second dataset, the validation dataset (n = 24,639), was used to evaluate the statistical model's prediction performance. All variables included in the derivation model were uniquely associated with DD status (p saturation (1.06 [95% CI 1.01-1.10]), temperature (1.10 [95% CI 1.06-1.15]), systolic blood pressure (1.18 [95% CI 1.12-1.25]), diastolic blood pressure (1.16 [95% CI 1.09-1.22]), respiratory rate (1.05 [95% CI 1.01-1.10]), and pain score (1.13 [95% CI 1.06-1.21]). The validation C-statistic was 0.73. We derived and validated a model and created a nomogram with acceptable discrimination of ESI 3 patients on arrival for purposes of predicting DD. Incorporating these variables into the care of these patients could improve patient flow by identifying patients who are likely to be discharged. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. The Role of Socio-Cognitive Variables in Predicting Learning Satisfaction in Smart Schools

    Science.gov (United States)

    Firoozi, Mohammad Reza; Kazemi, Ali; Jokar, Maryam

    2017-01-01

    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…

  5. Prediction of 6-yr symptom course trajectories of anxiety disorders by diagnostic, clinical and psychological variables

    NARCIS (Netherlands)

    Spinhoven, Philip; Batelaan, Neeltje; Rhebergen, Didi; van Balkom, Anton; Schoevers, Robert; Penninx, Brenda W.

    2016-01-01

    This study aimed to identify course trajectories of anxiety disorder using a data-driven method and to determine the incremental predictive value of clinical and psychological variables over and above diagnostic categories. 703 patients with DSM-IV panic disorder with or without agoraphobia,

  6. 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...

  7. Automatic prediction of cardiovascular and cerebrovascular events using heart rate variability analysis.

    Directory of Open Access Journals (Sweden)

    Paolo Melillo

    Full Text Available There is consensus that Heart Rate Variability is associated with the risk of vascular events. However, Heart Rate Variability predictive value for vascular events is not completely clear. The aim of this study is to develop novel predictive models based on data-mining algorithms to provide an automatic risk stratification tool for hypertensive patients.A database of 139 Holter recordings with clinical data of hypertensive patients followed up for at least 12 months were collected ad hoc. Subjects who experienced a vascular event (i.e., myocardial infarction, stroke, syncopal event were considered as high-risk subjects. Several data-mining algorithms (such as support vector machine, tree-based classifier, artificial neural network were used to develop automatic classifiers and their accuracy was tested by assessing the receiver-operator characteristics curve. Moreover, we tested the echographic parameters, which have been showed as powerful predictors of future vascular events.The best predictive model was based on random forest and enabled to identify high-risk hypertensive patients with sensitivity and specificity rates of 71.4% and 87.8%, respectively. The Heart Rate Variability based classifier showed higher predictive values than the conventional echographic parameters, which are considered as significant cardiovascular risk factors.Combination of Heart Rate Variability measures, analyzed with data-mining algorithm, could be a reliable tool for identifying hypertensive patients at high risk to develop future vascular events.

  8. Predicting First-Year Student Success in Learning Communities: The Power of Pre-College Variables

    Science.gov (United States)

    Sperry, Rita A.

    2015-01-01

    The study used pre-college variables in the prediction of retention and probation status of first-year students in learning communities at a regional public university in South Texas. The correlational study employed multivariate analyses on data collected from the campus registrar about three consecutive cohorts (N = 4,215) of first-year…

  9. Preliminary probabilistic prediction of ice/snow accretion on stay cables based on meteorological variables

    DEFF Research Database (Denmark)

    Roldsgaard, Joan Hee; Kiremidjian, A.; Georgakis, Christos T.

    for the representation of the meteorological variables and evaluated both by goodness-of-fit test and qualitatively. Conditional probability curves are developed to predict the amount of ice accretion given a set of meteorological conditions using the Gaussian Kernel Smoothing method. The fitted probability distribution...

  10. On the Mitigation of Solar Index Variability for High Precision Orbit Determination in Low Earth Orbit

    Science.gov (United States)

    2016-09-16

    causing increased difficulty in achieving and maintaining high precision orbit predictions for satellites operating in low Earth orbit . In particular, the...Geodetic satellites with high precision satellite laser ranging data are used as test cases for the Naval Research Laboratory’s Orbit Covariance Estimation...forces imparted upon a satellite . For satellites in Low Earth Orbit (LEO), atmospheric drag forces are typically the largest source of force modeling error

  11. The Stochastic predictability limits of GCM internal variability and the Stochastic Seasonal to Interannual Prediction System (StocSIPS)

    Science.gov (United States)

    Del Rio Amador, Lenin; Lovejoy, Shaun

    2017-04-01

    Over the past ten years, a key advance in our understanding of atmospheric variability is the discovery that between the weather and climate regime lies an intermediate "macroweather" regime, spanning the range of scales from ≈10 days to ≈30 years. Macroweather statistics are characterized by two fundamental symmetries: scaling and the factorization of the joint space-time statistics. In the time domain, the scaling has low intermittency with the additional property that successive fluctuations tend to cancel. In space, on the contrary the scaling has high (multifractal) intermittency corresponding to the existence of different climate zones. These properties have fundamental implications for macroweather forecasting: a) the temporal scaling implies that the system has a long range memory that can be exploited for forecasting; b) the low temporal intermittency implies that mathematically well-established (Gaussian) forecasting techniques can be used; and c), the statistical factorization property implies that although spatial correlations (including teleconnections) may be large, if long enough time series are available, they are not necessarily useful in improving forecasts. Theoretically, these conditions imply the existence of stochastic predictability limits in our talk, we show that these limits apply to GCM's. Based on these statistical implications, we developed the Stochastic Seasonal and Interannual Prediction System (StocSIPS) for the prediction of temperature from regional to global scales and from one month to many years horizons. One of the main components of StocSIPS is the separation and prediction of both the internal and externally forced variabilities. In order to test the theoretical assumptions and consequences for predictability and predictions, we use 41 different CMIP5 model outputs from preindustrial control runs that have fixed external forcings: whose variability is purely internally generated. We first show that these statistical

  12. Adaptation of Sediment Connectivity Index for Swedish catchments and application for flood prediction of roads

    Science.gov (United States)

    Cantone, Carolina; Kalantari, Zahra; Cavalli, Marco; Crema, Stefano

    2016-04-01

    Climate changes are predicted to increase precipitation intensities and occurrence of extreme rainfall events in the near future. Scandinavia has been identified as one of the most sensitive regions in Europe to such changes; therefore, an increase in the risk for flooding, landslides and soil erosion is to be expected also in Sweden. An increase in the occurrence of extreme weather events will impose greater strain on the built environment and major transport infrastructures such as roads and railways. This research aimed to identify the risk of flooding at the road-stream intersections, crucial locations where water and debris can accumulate and cause failures of the existing drainage facilities. Two regions in southwest of Sweden affected by an extreme rainfall event in August 2014, were used for calibrating and testing a statistical flood prediction model. A set of Physical Catchment Descriptors (PCDs) including road and catchment characteristics was identified for the modelling. Moreover, a GIS-based topographic Index of Sediment Connectivity (IC) was used as PCD. The novelty of this study relies on the adaptation of IC for describing sediment connectivity in lowland areas taking into account contribution of soil type, land use and different patterns of precipitation during the event. A weighting factor for IC was calculated by estimating runoff calculated with SCS Curve Number method, assuming a constant value of precipitation for a given time period, corresponding to the critical event. The Digital Elevation Model of the study site was reconditioned at the drainage facilities locations to consider the real flow path in the analysis. These modifications led to highlight the role of rainfall patterns and surface runoff for modelling sediment delivery in lowland areas. Moreover, it was observed that integrating IC into the statistic prediction model increased its accuracy and performance. After the calibration procedure in one of the study areas, the model was

  13. Child body mass index, genotype and parenting in the prediction of restrictive feeding.

    Science.gov (United States)

    Bost, K K; Teran-Garcia, M; Donovan, S M; Fiese, B H

    2017-04-21

    Restrictive feeding is implicated in pediatric obesity, and caregivers increase controlling feeding practices on the basis of higher child weight status. However, few studies have examined how child genetic and parenting characteristics together impact restrictive feeding. We examined whether child body mass index (BMI) status predicts caregiver use of restrictive feeding and if this association is moderated by (i) caregiver strategies to manage their children's distress and (ii) child variations in the catechol-O-methyltransferase (COMT) gene (Val(158) Met, rs4680). Participants included 126 Caucasian children (50% girls) and their caregivers who were participating in a larger study in the USA. Caregivers reported on their feeding practices and responses to child distress when children were 2.5-3.5 years of age. Child anthropometric measurements were also obtained. Restrictive feeding was assessed again 1-1.5 years later. Genomic DNA was obtained from saliva samples, and COMT-rs4680 was genotyped using TaqMan® methodology. Child BMI percentile predicted subsequent caregiver restrictive feeding for children who were Met/Met and who had caregivers reporting higher use of negative responses to child distress. For Val carriers, BMI percentile predicted restrictive feeding when caregivers were below the mean on these responses. Caregivers are at risk for use of restrictive feeding practices when their children are at higher BMI percentiles, and this association increases when caregivers use more ineffective stress regulation practices and their children are homozygous for the Met allele. Prevention programmes might focus on parenting behaviours that foster emotion regulation and consider variation in child responses to parenting. © 2017 World Obesity Federation.

  14. 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.

  15. Successful prediction of cardiovascular risk by new non-invasive vascular indexes using suprasystolic cuff oscillometric waveform analysis.

    Science.gov (United States)

    Sasaki-Nakashima, Rie; Kino, Tabito; Chen, Lin; Doi, Hiroshi; Minegishi, Shintaro; Abe, Kaito; Sugano, Teruyasu; Taguri, Masataka; Ishigami, Tomoaki

    2017-01-01

    Recently, new non-invasive vascular indexes named arterial velocity pulse index (AVI) and arterial pressure volume index (API), which is evaluated by a multifunctional blood pressure monitoring device, were developed using cuff oscillometric technologies and suprasystolic cuff oscillometric wave measurement. However, although a few studies including a computational model have been performed, data on subjects with cardiovascular diseases in actual outpatient clinics remain scant. We examined a total 252 consecutive outpatients and analyzed two vascular indexes with various clinical parameters to explore potential utilities of these two indexes in actual clinical settings. Although we found that two indexes were correlated with each other, the clinical implications of these indexes seemed to differ. Our analyses showed that AVI significantly correlated with augmentation index, but not with flow-mediated dilatation, and multivariate analyses suggested that enhanced AVI represents increased workload on the heart with elevated central blood pressure. In contrast, although the results of analyses performed to identify clinical parameters independently related to API were obscure and non-specific, after adjustment for multiple clinical variables, API was found to be significantly and independently associated with both Framingham Cardiovascular Risk Score and the Suita Score, suggesting that API is a useful predictor of future cardiovascular events. These two new vascular indexes might be useful in actual clinical settings to evaluate cardiovascular risks with various clinical backgrounds. Copyright © 2016 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

  16. Cross-Validated Variable Selection in Tree-Based Methods Improves Predictive Performance.

    Science.gov (United States)

    Painsky, Amichai; Rosset, Saharon

    2016-12-07

    Recursive partitioning methods producing tree-like models are a long standing staple of predictive modeling. However, a fundamental flaw in the partitioning (or splitting) rule of commonly used tree building methods precludes them from treating different types of variables equally. This most clearly manifests in these methods' inability to properly utilize categorical variables with a large number of categories, which are ubiquitous in the new age of big data. We propose a framework to splitting using leave-one-out (LOO) cross validation (CV) for selecting the splitting variable, then performing a regular split (in our case, following CART's approach) for the selected variable. The most important consequence of our approach is that categorical variables with many categories can be safely used in tree building and are only chosen if they contribute to predictive power. We demonstrate in extensive simulation and real data analysis that our splitting approach significantly improves the performance of both single tree models and ensemble methods that utilize trees. Importantly, we design an algorithm for LOO splitting variable selection which under reasonable assumptions does not substantially increase the overall computational complexity compared to CART for two-class classification.

  17. The art versus science of predicting prognosis: can a prognostic index predict short-term mortality better than experienced nurses do?

    Science.gov (United States)

    Casarett, David J; Farrington, Sue; Craig, Teresa; Slattery, Julie; Harrold, Joan; Oldanie, Betty; Roy, Jason; Biehl, Richard; Teno, Joan

    2012-06-01

    To determine whether a prognostic index could predict one-week mortality more accurately than hospice nurses can. An electronic health record-based retrospective cohort study of 21,074 hospice patients was conducted in three hospice programs in the Southeast, Northeast, and Midwest United States. Model development used logistic regression with bootstrapped confidence intervals and multiple imputation to account for missing data. The main outcome measure was mortality within 7 days of hospice enrollment. A total of 21,074 patients were admitted to hospice between October 1, 2008 and May 31, 2011, and 5562 (26.4%) died within 7 days. An optimal predictive model included the Palliative Performance Scale (PPS) score, admission from a hospital, and gender. The model had a c-statistic of 0.86 in the training sample and 0.84 in the validation sample, which was greater than that of nurses' predictions (0.72). The index's performance was best for patients with pulmonary disease (0.89) and worst for patients with cancer and dementia (both 0.80). The index's predictions of mortality rates in each index category were within 5.0% of actual rates, whereas nurses underestimated mortality by up to 18.9%. Using the optimal index threshold (<3), the index's predictions had a better c-statistic (0.78 versus 0.72) and higher sensitivity (74.4% versus 47.8%) than did nurses' predictions but a lower specificity (80.6% versus 95.1%). Although nurses can often identify patients who will die within 7 days, a simple model based on available clinical information offers improved accuracy and could help to identify those patients who are at high risk for short-term mortality.

  18. Body mass index continues to accurately predict percent body fat as women age despite changes in muscle mass and height.

    Science.gov (United States)

    Ablove, Tova; Binkley, Neil; Leadley, Sarah; Shelton, James; Ablove, Robert

    2015-07-01

    Body mass index (BMI) is commonly used to predict obesity in clinical practice because it is suggested to closely correlate with percent body fat (%BF). With aging, women lose both lean mass and height. Because of this, many clinicians question whether BMI is an accurate predictor of obesity in aging women. In evaluating the equation for BMI (weight/height(2)), it is clear that both variables can have a dramatic effect on BMI calculation. We evaluated the relationship between BMI and %BF, as measured by dual-energy x-ray absorptiometry, in the setting of age-related changes in height loss and body composition in women. Our objective is to determine whether BMI continues to correlate with %BF as women age. Study participants were identified using data from five osteoporosis clinical trials, where healthy participants had full-body dual-energy x-ray absorptiometry scans. Deidentified data from 274 women aged between 35 and 95 years were evaluated. %BF, weight, age, tallest height, actual height, and appendicular lean mass were collected from all participants. BMI was calculated using the actual height and the tallest height of each study participant. %BF was compared with BMI and stratified for age. BMI calculated using the tallest height and BMI calculated using actual height both had strong correlations with %BF. Surprisingly, the effects of changes in height and lean body mass balance each other out in BMI calculation. There continues to be a strong correlation between BMI and %BF in adult women as they age.

  19. 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

    had an EFW PI was measured by Doppler ultrasound and the placental 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...... (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...... was 14%. Median time interval between measurements and birth was 7.2 weeks (interquartile range 2.7- 13.7 weeks). Linear regression revealed a significant association between birth weight (Z-score) and placental T2* (Z-score) (r=0.66, pPI (Z-score) (r=-0.41 and p=0.0001). Receiver...

  20. Predictive validity of the total health index for all-cause mortality assessed in the Komo-Ise cohort.

    Science.gov (United States)

    Asano, Hiroaki; Takeuchi, Kazuo; Sasazawa, Yosiaki; Otani, Tetsuya; Koyama, Hiroshi; Suzuki, Shosuke

    2008-01-01

    The Total Health Index (THI), a self-administered questionnaire developed in Japan, is used for symptom assessment and stress management of employees and others; however, it has not been reported whether it can predict mortality risk. The THI, with 12 primary and 5 secondary scales, was applied to a cohort consisting of middle-aged residents in Japan. This study, called the Komo-Ise cohort study, was started in 1993. The scale scores were related to 481 deaths from all causes among 10,816 residents over 93 months. The statistics were tested by the Cox hazard model and adjusted for three background variables (sex, age, and district where the subject resided). Five of the scales [depression and aggression (primary scales), and psychosomatics, neurotics, and schizophrenics (secondary scales)] indicated significant hazard ratios for mortality. The lowest quintile group of the aggression scale score had the largest hazard ratio of 2.58, compared with the middle quintile group (95% confidence interval: 1.88-3.52). The psychosomatics, neurotic scales and depression scales also had a minimum hazard ratio in the middle quintile group. One of the secondary scales, T1, which represents a somatoform disorder, had a significant linear relationship with the mortality risk, although its proportionality with the cumulative mortality rates was not satisfactory. Five scales of the THI were significantly related to mortality risk in the Komo-Ise cohort, which could be used for score evaluation and in the personal health advice system of the THI.

  1. A Bioequivalence Approach for Generic Narrow Therapeutic Index Drugs: Evaluation of the Reference-Scaled Approach and Variability Comparison Criterion.

    Science.gov (United States)

    Jiang, Wenlei; Makhlouf, Fairouz; Schuirmann, Donald J; Zhang, Xinyuan; Zheng, Nan; Conner, Dale; Yu, Lawrence X; Lionberger, Robert

    2015-07-01

    Various health communities have expressed concerns regarding whether average bioequivalence (BE) limits (80.00-125.00%) for the 90% confidence interval of the test-to-reference geometric mean ratio are sufficient to ensure therapeutic equivalence between a generic narrow therapeutic index (NTI) drug and its reference listed drug (RLD). Simulations were conducted to investigate the impact of different BE approaches for NTI drugs on study power, including (1) direct tightening of average BE limits and (2) a scaled average BE approach where BE limits are tightened based on the RLD's within-subject variability. Addition of a variability comparison (using a one-tailed F test) increased the difficulty for generic NTIs more variable than their corresponding RLDs to demonstrate bioequivalence. Based on these results, the authors evaluate the fully replicated, 2-sequence, 2-treatment, 4-period crossover study design for NTI drugs where the test product demonstrates BE based on a scaled average bioequivalence criterion and a within-subject variability comparison criterion.

  2. Seasonality and Predictability of the Indian Ocean Dipole Mode: ENSO Forcing and Internal Variability

    Science.gov (United States)

    Yang, Y.

    2015-12-01

    This study evaluates the relative contributions to the Indian Ocean Dipole (IOD) mode of interannual variability from the El Niño-Southern Oscillation (ENSO) forcing and ocean-atmosphere feedbacks internal to the Indian Ocean. The ENSO forcing and internal variability is extracted by conducting a 10-member coupled simulation for 1950-2012 where sea surface temperature (SST) is restored to the observed anomalies over the tropical Pacific but interactive with the atmosphere over the rest of the world ocean. In these experiments, the ensemble mean is due to ENSO forcing and the inter-member difference arises from internal variability of the climate system independent of ENSO. These elements contribute one third and two thirds of the total IOD variance, respectively. Both types of IOD variability develop into an east-west dipole pattern due to Bjerknes feedback and peak in September-November. The ENSO forced and internal IOD modes differ in several important ways. The forced IOD mode develops in August with a broad meridional pattern, and eventually evolves into the Indian Ocean Basin mode; while the internal IOD mode grows earlier in June, is more confined to the equator and decays rapidly after October. The internal IOD mode is more skewed than the ENSO forced response. The destructive interference of ENSO forcing and internal variability can explain early-terminating IOD events, referred to IOD-like perturbations that fail to grow during boreal summer. Our results have implications for predictability. Internal variability, as represented by pre-season sea surface height anomalies off Sumatra, contributes to predictability considerably. Including this indicator of internal variability, together with ENSO, improves the predictability of IOD.

  3. A comparison between the APACHE II and Charlson Index Score for predicting hospital mortality in critically ill patients.

    Science.gov (United States)

    Quach, Susan; Hennessy, Deirdre A; Faris, Peter; Fong, Andrew; Quan, Hude; Doig, Christopher

    2009-07-30

    Risk adjustment and mortality prediction in studies of critical care are usually performed using acuity of illness scores, such as Acute Physiology and Chronic Health Evaluation II (APACHE II), which emphasize physiological derangement. Common risk adjustment systems used in administrative datasets, like the Charlson index, are entirely based on the presence of co-morbid illnesses. The purpose of this study was to compare the discriminative ability of the Charlson index to the APACHE II in predicting hospital mortality in adult multisystem ICU patients. This was a population-based cohort design. The study sample consisted of adult (>17 years of age) residents of the Calgary Health Region admitted to a multisystem ICU between April 2002 and March 2004. Clinical data were collected prospectively and linked to hospital outcome data. Multiple regression analyses were used to compare the performance of APACHE II and the Charlson index. The Charlson index was a poor predictor of mortality (C = 0.626). There was minimal difference between a baseline model containing age, sex and acute physiology score (C = 0.74) and models containing either chronic health points (C = 0.76) or Charlson index variations (C = 0.75, 0.76, 0.77). No important improvement in prediction occurred when the Charlson index was added to the full APACHE II model (C = 0.808 to C = 0.813). The Charlson index does not perform as well as the APACHE II in predicting hospital mortality in ICU patients. However, when acuity of illness scores are unavailable or are not recorded in a standard way, the Charlson index might be considered as an alternative method of risk adjustment and therefore facilitate comparisons between intensive care units.

  4. Which Foetal-Pelvic Variables Are Useful for Predicting Caesarean Section and Instrumental Assistance?

    Science.gov (United States)

    Frémondière, P; Thollon, L; Adalian, P; Delotte, J; Marchal, F

    2017-01-01

    To assess the variables useful to predict caesarean delivery (CD) and instrumental assistance, through the analysis of a large number of foetal-pelvic variables, using discriminant analysis. One hundred and fourteen pregnant women were included in this single-centre prospective study. For each mother-foetus pair, 43 pelvic and 18 foetal variables were measured. Partial least squares-discriminant analysis was performed to identify foetal-pelvic variables that could statistically separate the 3 delivery modality groups: spontaneous vaginal delivery (SVD), CD, and instrument-assisted delivery (IAD). For the SVD versus CD model, voluminous foetuses and women with a narrow pelvic inlet had a greater risk for requiring CD. The most efficient variables for discrimination were the transverse diameter and foetal weight. The antero-posterior inlet and obstetric conjugate were considered in this model, with the former being a useful variable but not the latter. For the SVD versus IAD model, the most important variables were the foetal variables, particularly the bi-parietal diameter. Women with a reduced antero-posterior outlet diameter and a narrow pubic arch were more at risk of requiring an IAD. The antero-posterior inlet was an efficient variable unlike the obstetric conjugate. The obstetric conjugate diameter should no longer be considered a useful variable in estimating the arrest of labour. Antero-posterior inlet diameter was a sagittal variable that should be taken into account. The comparison of sub-pubic angle and bi-parietal and antero-posterior outlet diameters was useful in identifying a risk of requiring instrumental assistance. © 2017 S. Karger AG, Basel.

  5. 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

  6. 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.

  7. Trends and variability of meteorological drought over the districts of India using standardized precipitation index

    Science.gov (United States)

    Guhathakurta, P.; Menon, Preetha; Inkane, P. M.; Krishnan, Usha; Sable, S. T.

    2018-02-01

    Meteorological drought during the southwest monsoon season and for the northeast monsoon season over five meteorological subdivisions of India for the period 1901-2015 has been examined using district and all India standardized precipitation index (SPI). Whenever all India southwest monsoon rainfall was less than -10% or below normal, for those years all India SPI was found as -1 or less. Composite analysis of SPI for the below normal years, viz., less than -15% and -20% of normal rainfall years indicate that during those years more than 30% of country's area was under drought condition, whenever all India southwest monsoon rainfall was -15% or less than normal. Trend analysis of monthly SPI for the monsoon months identified the districts experiencing significant increase in drought occurrences. Significant positive correlation has been found with the meteorological drought over most of the districts of central, northern and peninsular India, while negative correlation was seen over the districts of eastern India with NINO 3.4 SST. For the first time, meteorological drought analysis over districts and its association with equatorial pacific SST and probability analysis has been done for the northeast monsoon over the affected regions of south peninsular India. Temporal correlation of all India southwest monsoon SPI and south peninsular India northeast monsoon SPI has been done with the global SST to identify the teleconnection of drought in India with global parameters.

  8. 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.

  9. PREDICTION OF CRITERIA VARIABLE SOCIAL DANCES RESULT ON MORPHOLOGICAL CHARACTERISTIC BASIS

    Directory of Open Access Journals (Sweden)

    Amra Nožinović Mujanović

    2008-08-01

    Full Text Available In this research we had the sample of male students, from Faculty of physical education and sport in Tuzla, age of 20 to 22 years old. The number of whole sample was 156. Mesuring is being done by using 20 tests of morphological characteristics and 4 Social. Regression analysis was used in the aim of establishment the influence largness of preliminary mentioned prediction set on criteria variable. With regression analysis of Social dances in manifested space of morphological variables, we got enough information about used variables influence on success of performing treated criteria variable, respectively, the coefficients of multiplecorrelation are high. Those kinds of research are pretty unusually, so we suppose this could be a small contribution to make a better training quality, by Social dances as also by other dance distributions.

  10. Using Canopy Reflectance and Crop Stress Index to Enhance Wheat Yield Prediction

    Science.gov (United States)

    Asadi, S.; Zare, H.; Paymard, P.; Lashkari, A.; Salehnia, N.; Bannayan, M.

    2015-12-01

    Canopy reflectance can be useful indicator of crop health status. Canopy stress index (CSI) is usually expressed as canopy temperature minus air temperature, and this value is higher and a positive number in a well irrigated wheat field. Three main environmental variables constructing CSI are: plant canopy temperature (Tc), air temperature (Ta) and atmospheric vapor pressure deficiency (VPD). CSI is effected by biological and environmental factors such as soil water status, wind speed, evapotranspiration, conduction systems, plant metabolism, air temperature, relative humidity, etc. which all influence on final yield. This paper aims to investigate the relation of CSI calculated by Landsat images and wheat yield. So, eighteen wheat fields were selected for two years (2009 and 2010) and 5 Landsat images (TM and ETM+) from April to Jun were used to monitor field status in each year. Tc was calculated by applying single-channel method and VPD was computed from Tc, air temperature and humidity. Each single Landsat bands and CSI were defined as the descriptor variables. Relation between wheat yield and the descriptors was assessed by means of linear correlation. The results of stepwise correlation depicted that band 1 (blue) and 3 (red) had the most correlations to yield until grain filling stage. This reflects the importance of photosynthesis rate which absorb blue and red wavelength during mentioned period. This two bands also could capture yield changes (r2=0.77). However, during grain filling period CSI was the only descriptor determining yield volatility (r2=0.85). Low temperature is one of the key factors which increase remobilization of carbohydrate to grain. Therefore, grain yield in the canopy which has less temperature in compared to air temperature would be higher than others.

  11. Mannheim Peritoneal Index in the Prediction of Postoperative Complications in Patients with Peritonitis

    Directory of Open Access Journals (Sweden)

    N. N. Aksenova

    2009-01-01

    Full Text Available Objective: to study the diagnostic and prognostic values of the Mannheim peritoneal index (MPI in the development of postoperative local and systemic complications in patients with peritonitis. Materials and methods. The case histories of 92 patients with generalized peritonitis of varying etiology (other than pancreatogenic one were analyzed. The patients were retrospectively divided into 3 groups according to the outcomes and occurrence of postoperative local complications. The postoperative complications were classified by the procedure developed by A. L. Kostyuchenko et al. as local and systemic ones. When the patients had two signs or more of the systemic inflammatory response syndrome, they were stated to have systemic complications and to be diagnosed as having abdominal sepsis with the pattern of organ dysfunctions being described in accordance with the sepsis classification proposed by R. S. Bone et al. (1992. The number of organ dysfunctions was daily counted in each patient over time in the postoperative period. On the first postoperative day, MPI was calculated in scores for each patient; the mean MPI was estimated for all patient groups. The predictable mortality was calculated using the MPI plot. Results. All the patients with generalized peritonitis in the development of local postoperative complications were observed to have sepsis in the postoperative period, without developing local complication in 84.6% of the patients. A direct correlation was found between the MPI and the quantity of organ dysfunctions (r=0.6; p=0.001. In patients with local postoperative complications being developed, the MPI values were higher (p<0.05 than in those without them. The mortality rates that have been predicted by means of MPI (16.3% and actual (15.2% are actually in agreement. Conclusion. There is evidence for the diagnostic and prognostic values of MPI in the development of local and systemic postoperative complications in patients with

  12. 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.

  13. Mechanisms and predictability of multiyear ecosystem variability in the North Pacific

    Science.gov (United States)

    Chikamoto, Megumi O.; Timmermann, Axel; Chikamoto, Yoshimitsu; Tokinaga, Hiroki; Harada, Naomi

    2015-11-01

    Aleutian Low variations provide vorticity, buoyancy, and heat-flux forcing to the North Pacific Ocean, which in turn cause changes in ocean circulation, mixed layer characteristics and sea ice coverage. In this process the white noise atmospheric characteristics are integrated dynamically and thermodynamically to generate red noise ocean spectra. Using the Community Earth System Model (version 1.0.3) we study the resulting biogeochemical and ecosystem responses in the North Pacific. We find that ocean dynamical variables have an impact on the tendencies of key nutrients and biological production, which leads to a further reddening of biogeochemical spectra resulting in potential predictability on time scales of 2-4 years. However, this low-pass filtering does not apply to all biogeochemical variables and is regionally dependent. It is shown that phytoplankton biomass in the Central North Pacific adjusts to the much shorter-term variability associated with changes in mixed layer depth, light availability, and zooplankton grazing, thus limiting the predictability of phytoplankton anomalies to about 1 year. In the eastern North Pacific the slow advection of anomalous nutrient concentrations leads to longer persistence of phytoplankton variability and increased potential predictability of up to 3 years.

  14. [Spatial pattern of soil fertility in Bashan tea garden: a prediction based on environmental auxiliary variables].

    Science.gov (United States)

    Qin, Le-feng; Yang, Chao; Lin, Fen-fang; Yang, Ning; Zheng, Xin-yu; Xu, Hong-wei; Wang, Ke

    2010-12-01

    Taking topographic factors and NDVI as auxiliary variables, and by using regression-kriging method, the spatial variation pattern of soil fertility in Bashan tea garden in the hilly area of Fuyang City was explored. The spatial variability of the soil fertility was mainly attributed to the structural factors such as relative elevation and flat/vertical curvature. The lower the relative elevation, the worse the soil fertility was. The overall soil fertility level was relatively high, and the area with lower soil fertility only accounted for 5% of the total. By using regression-kriging method with relative elevation as auxiliary variable, the prediction accuracy of soil fertility was obviously higher than that by using ordinary kriging method, with the mean error and root mean square error being 0. 028 and 0. 108, respectively. It was suggested that the prediction method used in this paper could fully reflect the effects of environmental variables on soil fertility , improve the prediction accuracy about the spatial pattern of soil fertility, and provide scientific basis for the precise management of tea garden.

  15. 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.

  16. Selection of haplotype variables from a high-density marker map for genomic prediction.

    Science.gov (United States)

    Cuyabano, Beatriz Cd; Su, Guosheng; Lund, Mogens S

    2015-08-01

    Using haplotype blocks as predictors rather than individual single nucleotide polymorphisms (SNPs) may improve genomic predictions, since haplotypes are in stronger linkage disequilibrium with the quantitative trait loci than are individual SNPs. It has also been hypothesized that an appropriate selection of a subset of haplotype blocks can result in similar or better predictive ability than when using the whole set of haplotype blocks. This study investigated genomic prediction using a set of haplotype blocks that contained the SNPs with large effects estimated from an individual SNP prediction model. We analyzed protein yield, fertility and mastitis of Nordic Holstein cattle, and used high-density markers (about 770k SNPs). To reach an optimum number of haplotype variables for genomic prediction, predictions were performed using subsets of haplotype blocks that contained a range of 1000 to 50 000 main SNPs. The use of haplotype blocks improved the prediction reliabilities, even when selection focused on only a group of haplotype blocks. In this case, the use of haplotype blocks that contained the 20 000 to 50 000 SNPs with the highest effect was sufficient to outperform the model that used all individual SNPs as predictors (up to 1.3 % improvement in prediction reliability for mastitis, compared to individual SNP approach), and the achieved reliabilities were similar to those using all haplotype blocks available in the genome data (from 0.6 % lower to 0.8 % higher reliability). Haplotype blocks used as predictors can improve the reliability of genomic prediction compared to the individual SNP model. Furthermore, the use of a subset of haplotype blocks that contains the main SNP effects from genomic data could be a feasible approach to genomic prediction in dairy cattle, given an increase in density of genotype data available. The predictive ability of the models that use a subset of haplotype blocks was similar to that obtained using either all haplotype blocks

  17. 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.

  18. Body mass index predicts plasma aldosterone concentrations in overweight-obese primary hypertensive patients.

    Science.gov (United States)

    Rossi, Gian Paolo; Belfiore, Anna; Bernini, Giampaolo; Fabris, Bruno; Caridi, Graziella; Ferri, Claudio; Giacchetti, Gilberta; Letizia, Claudio; Maccario, Mauro; Mannelli, Massimo; Palumbo, Gaetana; Patalano, Anna; Rizzoni, Damiano; Rossi, Ermanno; Pessina, Achille C; Mantero, Franco

    2008-07-01

    Body mass index (BMI) shows a direct correlation with plasma aldosterone concentration (PAC) and urinary aldosterone excretion in normotensive individuals; whether the same applies to hypertensive patients is unknown. Our objective was to determine if BMI predicts PAC and the PAC/plasma renin activity ratio [aldosterone renin ratio (ARR)] in hypertensive patients, and if this affects the identification of primary aldosteronism (PA). This was a prospective evaluation of consecutive hypertensive patients referred nationwide to specialized hypertension centers. Sitting PAC, plasma renin activity, and the ARR, baseline and after 50 mg captopril orally with concomitant assessment of parameters, including BMI and daily sodium intake, were calculated. Complete biochemical data and a definite diagnosis were obtained in 1125 consecutive patients. Of them 999 had primary (essential) hypertension (PH) and 126 (11.2%) PA caused by an aldosterone-producing adenoma in 54 (4.8%). BMI independently predicted PAC (beta = 0.153; P < 0.0001) in PH, particularly in the overweight-obese, but not in the PA group. Covariance analysis and formal comparison of the raw, and the BMI-, sex-, and sodium intake-adjusted ARR with receiver operator characteristic curves, showed no significant improvement for the discrimination of aldosterone-producing adenoma from PH patients with covariate-adjusted ARR. BMI correlated with PAC independent of age, sex, and sodium intake in PH, but not in PA patients. This association of BMI is particularly evident in overweight-obese PH patients, and suggests a pathophysiological link between visceral adiposity and aldosterone secretion. However, it does not impact on the diagnostic accuracy of the ARR for discriminating PA from PH patients.

  19. Is heart rate recovery index a predictive factor for cardioinhibitory syncope?

    Science.gov (United States)

    Emren, Volkan; Kocabaş, Uğur

    2018-01-01

    Cardioinhibitory syncope is related with excessive bradycardia or asystole due to parasympathetic response. We investigated whether patients with cardioinhibitory syncope have higher heart rate recovery index (HRRi) considered as a parasympathetic system activation in exercise stress testing (EST) than in those with other neurogenic syncope forms. A total of 262 patients who had neurogenic syncope documented by head-up tilt test (HUTT) and 199 healthy control individuals were examined. A maximal EST was applied to all patients after the HUTT. The HRRi was obtained by subtracting the heart rate that was measured at the first (HRRi-1), second (HRRi-2), and third minute (HRRi-3) of the recovery period from the maximal heart rate that was measured during the test. Eighty patients had cardioinhibitory syncope, 118 patients had vasodepressor syncope, and 64 patients had mixed-type syncope. The HRRi-1 was higher in patients with syncope (43.3 ± 7.7) compared to the control group (34.5 ± 4.8; p < 0.001). Post hoc analysis showed that among the syncope groups, there was no difference between patients with vasodepressor syncope (42.2 ± 7.6) and those with mixed type syncope (40.7 ± 4.1) in terms of HRRi-1 (p = 0.420). However, patients with cardioinhibitory syncope (47 ± 8.7) had a higher HRRi-1 than vasodepressor and mixed-type syncope groups (p < 0.05). The threshold value of the HRRi-1, which can be used for the prediction of cardioinhibitory syncope development, was determined to be 41 with 75% sensitivity and 72% specificity. The HRRi-1 was higher in patients with cardioinhibitory syncope compared to the controls. The HRRi-1 has the predictive feature of differentiating cardioinhibitory syncope from other syncope types.

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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

  5. Habitat and Vegetation Variables Are Not Enough When Predicting Tick Populations in the Southeastern United States.

    Directory of Open Access Journals (Sweden)

    R T Trout Fryxell

    Full Text Available Two tick-borne diseases with expanding case and vector distributions are ehrlichiosis (transmitted by Amblyomma americanum and rickettiosis (transmitted by A. maculatum and Dermacentor variabilis. There is a critical need to identify the specific habitats where each of these species is likely to be encountered to classify and pinpoint risk areas. Consequently, an in-depth tick prevalence study was conducted on the dominant ticks in the southeast. Vegetation, soil, and remote sensing data were used to test the hypothesis that habitat and vegetation variables can predict tick abundances. No variables were significant predictors of A. americanum adult and nymph tick abundance, and no clustering was evident because this species was found throughout the study area. For A. maculatum adult tick abundance was predicted by NDVI and by the interaction between habitat type and plant diversity; two significant population clusters were identified in a heterogeneous area suitable for quail habitat. For D. variabilis no environmental variables were significant predictors of adult abundance; however, D. variabilis collections clustered in three significant areas best described as agriculture areas with defined edges. This study identified few landscape and vegetation variables associated with tick presence. While some variables were significantly associated with tick populations, the amount of explained variation was not useful for predicting reliably where ticks occur; consequently, additional research that includes multiple sampling seasons and locations throughout the southeast are warranted. This low amount of explained variation may also be due to the use of hosts for dispersal, and potentially to other abiotic and biotic variables. Host species play a large role in the establishment, maintenance, and dispersal of a tick species, as well as the maintenance of disease cycles, dispersal to new areas, and identification of risk areas.

  6. Variability in the heritability of body mass index: a systematic review and meta-regression

    Directory of Open Access Journals (Sweden)

    Cathy E Elks

    2012-02-01

    Full Text Available Evidence for a major role of genetic factors in the determination of body mass index (BMI comes from studies of related individuals. However, heritability estimates for BMI vary widely between studies and the reasons for this remain unclear. While some variation is natural due to differences between populations and settings, study design factors may also explain some of the heterogeneity. We performed a systematic review that identified eighty-eight independent estimates of BMI heritability from twin studies (total 140,525 twins and twenty-seven estimates from family studies (42,968 family members. BMI heritability estimates from twin studies ranged from 0.47 to 0.90 (5th/50th/95th centiles: 0.58/0.75/0.87 and were generally higher than those from family studies (range: 0.24-0.81; 5th/50th/95th centiles: 0.25/0.46/0.68. Meta-regression of the results from twin studies showed that BMI heritability estimates were 0.07 (P=0.001 higher in children than in adults; estimates increased with mean age among childhood studies (+0.012 per year, P=0.002, but decreased with mean age in adult studies (-0.002 per year, P=0.002. Heritability estimates derived from AE twin models (which assume no contribution of shared environment were 0.12 higher than those from ACE models (P<0.001, whilst lower estimates were associated with self-reported versus DNA-based determination of zygosity (-0.04, P=0.02, and with self-reported versus measured BMI (-0.05, P=0.03. Together, the above factors explained 47% of the heterogeneity in estimates of BMI heritability from twin studies. In summary, while some variation in BMI heritability is expected due to population-level differences, study design factors explained nearly half the heterogeneity reported in twin studies. The genetic contribution to BMI appears to vary with age and may have a greater influence during childhood than adult life.

  7. Ankle-brachial blood pressure index predicts all-cause and cardiovascular mortality in hemodialysis patients.

    Science.gov (United States)

    Ono, Kumeo; Tsuchida, Akiyasu; Kawai, Hironobu; Matsuo, Hidenori; Wakamatsu, Ryouji; Maezawa, Akira; Yano, Shintarou; Kawada, Tomoyuki; Nojima, Yoshihisa

    2003-06-01

    A reduction in ankle-brachial BP index (ABPI) is associated with generalized atherosclerotic diseases and predicts cardiovascular mortality and morbidity in several patient populations. However, a large-scale analysis of ABPI is lacking for hemodialysis (HD) patients, and its use in this population is not fully validated. A cohort of 1010 Japanese patients undergoing chronic hemodialysis was studied between November 1999 and May 2002. Mean age at entry was 60.6 +/- 12.5 yr, and duration of follow-up was 22.3 +/- 5.6 mo. Patients were stratified into five groups ( or = 0.9 to or = 1.0 to or = 1.1 to or = 1.3) by ABPI measured at entry by an oscillometric method. The frequency distribution of ABPI was 16.5% of patients or = 0.9 to or = to or 1.1 to or = 1.3). The relative risk of a history of diabetes mellitus (DM), cardiovascular, and cerebrovascular disease was significantly higher in patients with lower ABPI than those with ABPI > or = 1.1 to or = 0.9 to or = 1.3) also had poor prognosis (HR, 2.33 [1.11 to 4.89] and 3.04 [1.14 to 8.12] for all-cause and cardiovascular mortality, respectively). Thus, the present findings validate ABPI as a powerful and independent predictor for all-cause and cardiovascular mortality among hemodialysis patients.

  8. Mannheim Peritonitis Index and APACHE II--prediction of outcome in patients with peritonitis.

    Science.gov (United States)

    Malik, Ajaz Ahmad; Wani, Khurshid Alam; Dar, Latif Ahmad; Wani, Mehmood Ahmed; Wani, Rauf Ahmad; Parray, Fazl Qadir

    2010-01-01

    Early prognostic evaluation of patients with peritonitis is desirable to select high-risk patients for intensive management and also to provide a reliable objective classification of severity and operative risk. This study attempts to evaluate the use of scoring systems such as Acute Physiological and Chronic Health Evaluation score (APACHE II) and Mannheim Peritonitis Index (MPI) in patients with peritonitis. A prospective study was conducted using 101 consecutive patients (69 male, 32 female) having generalized peritonitis over a two-year period. Both scoring systems were applied to patients before laparotomy. Based upon the scores, patients were arranged into three groups. The outcome of patients was noted and the accuracy of the two systems was evaluated. In the MPI system, mortality was 0 in the group of patients with a score of less than 15, while it was 4% in the patients scoring 16-25 and 82.3% in those with scores of more than 25. Similarly, in the APACHE II system, no mortality was noted in patients with scores less than 10. Mortality was 35.29% and 91.7% in the groups scoring 10-20 and more than 20, respectively. Both scoring systems are accurate in predicting mortality; however, the APACHE II has definitive advantages and is therefore more useful.

  9. Prognosis Prediction for Postoperative Esophageal Cancer Patients Using Onodera's Prognostic Nutritional Index.

    Science.gov (United States)

    Matsumoto, Hideo; Okamoto, Yuko; Kawai, Akimasa; Ueno, Daisuke; Kubota, Hisako; Murakami, Haruaki; Higashida, Masaharu; Hirai, Toshihiro

    2017-01-01

    Preoperative nutritional status may impact surgical outcome and prognosis. We evaluated the predictive value of Onodera's prognostic nutritional index (O's-PNI) of surgical outcome following esophagectomy in esophageal cancer patients. In total, 144 patients undergoing esophagectomy for esophageal cancer from April 2010 to May 2015 were evaluated, retrospectively. Eighty-four patients were enrolled in this study. O's-PNIs were calculated before surgery, discharge, and 1, 2, and 6 mo after discharge. The relationship between O's-PNI and occurrence of complications as classified by the Clavien-Dindo (C-D) classification, length of hospital stay, and survival time was investigated. The mean O's-PNI for patients with complications of more than Grade 2 by the C-D classification was 37.4, which was significantly lower than that for Grades 0 or 1 (40.5, P = 0.0094). A negative correlation was obtained between O's-PNI and hospital stay length (P = 0.0006), whereas a positive correlation was obtained for O's-PNI at 6 mo postsurgery and overall survival (P = 0.0171, P = 0.0201). O's-PNI may represent a useful indicator of the occurrence of complications and length of hospital stay, and may influence overall survival at 6 mo postsurgery. Nutritional management during the perioperative period could therefore contribute to satisfactory outcomes following esophagectomy in esophageal cancer patients.

  10. A high oxidative stress index predicts endothelial dysfunction in young male smokers.

    Science.gov (United States)

    Karahan, O; Manduz, S; Bektasoglu, G; Zorlu, A; Turkdogan, K A; Bozok, S

    2013-01-01

    Experimental studies have shown that smoking was related to endothelial dysfunction via oxidative stress. However, the degree of oxidative stress to be associated with endothelial dysfunction is unknown. Oxidative stress index (OSI) might be a useful and easy way of determining the endothelial dysfunction. Hence, we aimed to evaluate the relationship between OSI and flow mediated dilatation (FMD) in smoking healthy male volunteers. Eighty smoking healthy male volunteers were enrolled in the study. Participants were classified as having normal and abnormal FMD response. In an univariate analysis; systolic and diastolic blood pressures, C-reactive protein (CRP), low-density lipoprotein cholesterol, OSI and lipid peroxidation (LPO) levels were predictive for abnormal FMD response. In a multivariable logistic regression analysis with forward stepwise method, OSI (OR: 3.194, 95% CI: 1.710-5.966, ppredicting abnormal FMD response in young male smokers. The optimal cut-off value of OSI for detecting abnormal FMD response was found to be >3.35, with 100 % sensitivity and 84.1 % specificity. We have shown that critical endothelial dysfunction can easily be detected by OSI in individuals, at risk for developing coronary artery disease, such as smokers (Tab. 3, Fig. 3, Ref. 30). Text in PDF www.elis.sk.

  11. 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.

  12. The utility of low frequency heart rate variability as an index of sympathetic cardiac tone : A review with emphasis on a reanalysis of previous studies

    NARCIS (Netherlands)

    Reyes del Paso, Gustavo A.; Langewitz, Wolf; Mulder, Lambertus J. M.; Van Roon, Arie; Duschek, Stefan

    This article evaluates the suitability of low frequency (LF) heart rate variability (HRV) as an index of sympathetic cardiac control and the LF/high frequency (HF) ratio as an index of autonomic balance. It includes a comprehensive literature review and a reanalysis of some previous studies on

  13. 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.

  14. Ecological dissimilarity among land-use/land-cover types improves a heterogeneity index for predicting biodiversity in agricultural landscapes.

    Science.gov (United States)

    Yoshioka, Akira; Fukasawa, Keita; Mishima, Yoshio; Sasaki, Keiko; Kadoya, Taku

    2017-12-01

    Land-use/land-cover heterogeneity is among the most important factors influencing biodiversity in agricultural landscapes and is the key to the conservation of multi-habitat dwellers that use both terrestrial and aquatic habitats. Heterogeneity indices based on land-use/land-cover maps typically do not integrate ecological dissimilarity between land-use/land-cover types. Here, we applied the concept of functional diversity to an existing land-use/land-cover diversity index (Satoyama index) to incorporate ecological dissimilarity and proposed a new index called the dissimilarity-based Satoyama index (DSI). Using Japan as a case study, we calculated the DSI for three land-use/land-cover maps with different spatial resolutions and derived similarity information from normalized difference vegetation index values. The DSI showed better performance in the prediction of Japanese damselfly species richness than that of the existing index, and a higher correlation between the index and species richness was obtained for higher resolution maps. Thus, our approach to improve the land-use/land-cover diversity index holds promise for future development and can be effective for conservation and monitoring efforts.

  15. QT Interval Variability Index and QT Interval Duration in Different Sleep Stages: Analysis of Polysomnographic Recordings in Nonapneic Male Patients

    Directory of Open Access Journals (Sweden)

    Moonika Viigimae

    2015-01-01

    Full Text Available The aim of the study was to determine whether different sleep stages, especially REM sleep, affect QT interval duration and variability in male patients without obstructive sleep apnea (OSA. Polysomnographic recordings of 30 patients were analyzed. Beat-to-beat QT interval variability was calculated using QTV index (QTVI formula. For QTc interval calculation, in addition to Bazett’s formula, linear and parabolic heart rate correction formulas with two separate α values were used. QTVI and QTc values were calculated as means of 2 awake, 3 NREM, and 3 REM sleep episodes; the duration of each episode was 300 sec. Mean QTVI values were not statistically different between sleep stages. Therefore, elevated QTVI values found in patients with OSA cannot be interpreted as physiological sympathetic impact during REM sleep and should be considered as a risk factor for potentially life-threatening ventricular arrhythmias. The absence of difference of the mean QTc interval values between NREM and REM stages seems to confirm our conclusion that sympathetic surges during REM stage do not induce repolarization variability. In patients without notable structural and electrical remodeling of myocardium, physiological elevation in sympathetic activity during REM sleep remains subthreshold concerning clinically significant increase of myocardial electrical instability.

  16. Ankle-Brachial Index: A Simple Way to Predict Mortality among Patients on Hemodialysis - A Prospective Study

    OpenAIRE

    Zaida Noemy Cabrera Jimenez; Benedito Jorge Pereira; João Egidio Romão; Sonia Cristina da Silva Makida; Hugo Abensur; Rosa Maria Affonso Moyses; Rosilene Motta Elias

    2012-01-01

    Background: Ankle-brachial index (ABI) can access peripheral artery disease and predict mortality in prevalent patients on hemodialysis. However, ABI has not yet been tested in incident patients, who present significant mortality. Typically, ABI is measured by Doppler, which is not always available, limiting its use in most patients. We therefore hypothesized that ABI, evaluated by a simplified method, can predict mortality in an incident hemodialysis population. Methodology/Principal Finding...

  17. 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 live birth rate at five 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 <35 years of age (P = 0.027), and having leiomyomas (P = 0.037). The main

  18. 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 (SpO2) 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 SpO2. Forty-four healthy volunteers undertook an expedition in the Nepali Himalaya to >5000 m. SpO2 and HRV parameters were recorded at rest in normoxia and in a normobaric hypoxic chamber before the expedition. On the expedition HRV parameters and SpO2 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 SpO2 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.

  19. Interannual Variability and Predictability in an Ensemble of Climate Simulations with the MRI-JMA AGCM

    OpenAIRE

    Xiaogu, ZHENG; Masato, Sugi; Carsten S., FREDERIKSEN; National Institute of Water and Atmospheric Research; Meteorological Research Institute; Bureau of Meteorology Research Centre

    2004-01-01

    An analysis of variance approach, for systematically studying and evaluating the nterannual variability and predictability of seasonal mean fields, is demonstrated using an ensemble of six 50-year simulations of the 500 hPa geopotential height field from the Meteorological Research Institute-Japan Meteorological Agency (MRI-JMA) global atmosphere model forced by observed sea surface temperatures (SSTs). The model performance is analysed, for the seasons June-July-August (JJA) and December-Jan...

  20. Efficient knowledge retrieval to calibrate input variables in forest fire prediction

    OpenAIRE

    Wendt, Kerstin

    2008-01-01

    Forest fires are a serious threat to humans and nature from an ecological, social and economic point of view. Predicting their behaviour by simulation still delivers unreliable results and remains a challenging task. Latest approaches try to calibrate input variables, often tainted with imprecision, using optimisation techniques like Genetic Algorithms. To converge faster towards fitter solutions, the GA is guided with knowledge obtained from historical or synthetical fires. We developed a ro...

  1. Variables that predict academic procrastination behavior in prospective primary school teachers

    OpenAIRE

    SARACALOĞLU, Asuman Seda; İbrahim GÖKDAŞ

    2016-01-01

    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-Eff...

  2. [Formulation of an equation to predict fat mass using bioelectrical impedance in adults in a wide range of ages and body mass index].

    Science.gov (United States)

    Schifferli, Ingrid; Carrasco, Fernando; Inostroza, Jorge

    2011-12-01

    Bioelectrical impedance (BIA) has a good correlation and agreement with reference techniques, such as dual energy X-ray absorptiometry (DEXA), to assess body composition. To develop and assess the concordance of an equation to predict body fat mass derived from anthropometric data, gender, age and resistance obtained from bioelectrical impedance in adults, using DEXA as the reference method. Cross-sectional study of 62 women and 59 men aged 18 to 64 years with a body mass index ranging from 18.5 to 34.8 kg/ m². The equation was constructed using a predictive statistical model, considering sex, age, weight, resistance index (height²(cm)/ resistance (ohms)), as independent variables, and fat mass as the dependent variable. The R² of the regression model was 0.96, and the standard error of estimation was 2.58 kg (p equation developed in this work and that proposed by the manufacturer of the BIA equipment. However, the latter equation, underestimated FM by -2.5 ± 9.5% (p > 0.05) and - 4.5 ± 8,9% (p mass by the formula developed in this work and by DEXA was better than the estimation obtained using the formula proposed by the manufacturer of the BIA equipment.

  3. 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.

  4. Prediction of 6-yr symptom course trajectories of anxiety disorders by diagnostic, clinical and psychological variables.

    Science.gov (United States)

    Spinhoven, Philip; Batelaan, Neeltje; Rhebergen, Didi; van Balkom, Anton; Schoevers, Robert; Penninx, Brenda W

    2016-12-01

    This study aimed to identify course trajectories of anxiety disorder using a data-driven method and to determine the incremental predictive value of clinical and psychological variables over and above diagnostic categories. 703 patients with DSM-IV panic disorder with or without agoraphobia, agoraphobia, social phobia, or generalized anxiety disorder were selected from a prospective cohort study. Latent Growth Mixture Modeling was conducted, based on symptoms of anxiety and avoidance as assessed with the Life Chart Interview covering a 6-year time period. In 44% of the participants symptoms of anxiety and avoidance improved, in 24% remained stable, in 25% slightly increased, and in 7% severely increased. Identified course trajectories were predicted by baseline DSM-IV anxiety categories, clinical variables (i.e., severity and duration and level of disability) and psychological predictors (i.e., neuroticism, extraversion, anxiety sensitivity, worry, and rumination). Clinical variables better predicted unfavorable course trajectories than psychological predictors, over and above diagnostic categories. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. 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

  6. Transcranial direct current stimulation improves the QT variability index and autonomic cardiac control in healthy subjects older than 60 years

    Directory of Open Access Journals (Sweden)

    Piccirillo G

    2016-11-01

    Full Text Available Gianfranco Piccirillo,1 Cristina Ottaviani,2 Claudia Fiorucci,1 Nicola Petrocchi,2 Federica Moscucci,1 Claudia Di Iorio,1 Fabiola Mastropietri,1 Ilaria Parrotta,1 Matteo Pascucci,1 Damiano Magrì3 1Department of Cardiovascular, Respiratory, Nephrological, Anestesiological and Geriatric Sciences, “Sapienza” University, 2Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, 3Department of Clinical and Molecular Medicine, University of Rome “Sapienza”, Rome, Italy Background: Noninvasive brain stimulation technique is an interesting tool to investigate the causal relation between cortical functioning and autonomic nervous system (ANS responses. Objective: The objective of this report is to evaluate whether anodal transcranial direct current stimulation (tDCS over the temporal cortex influences short-period temporal ventricular repolarization dispersion and cardiovascular ANS control in elderly subjects. Subjects and methods: In 50 healthy subjects (29 subjects younger than 60 years and 21 subjects older than 60 years matched for gender, short-period RR and systolic blood pressure spectral variability, QT variability index (QTVI, and noninvasive hemodynamic data were obtained during anodal tDCS or sham stimulation. Results: In the older group, the QTVI, low-frequency (LF power expressed in normalized units, the ratio between LF and high-frequency (HF power, and systemic peripheral resistances decreased, whereas HF power expressed in normalized units and α HF power increased during the active compared to the sham condition (P<0.05. Conclusion: In healthy subjects older than 60 years, tDCS elicits cardiovascular and autonomic changes. Particularly, it improves temporal ventricular repolarization dispersion, reduces sinus sympathetic activity and systemic peripheral resistance, and increases vagal sinus activity and baroreflex sensitivity. Keywords: transcranial direct current stimulation, QT variability, heart rate variability

  7. 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.

  8. Role of heart rate variability in predicting the severity of severe acute pancreatitis.

    Science.gov (United States)

    Zhang, Luyao; Zhou, Jing; Ke, Lu; Nie, Yao; Tong, Zhihui; Li, Weiqin; Li, Jieshou

    2014-10-01

    Infected pancreatic necrosis (IPN) and multiple organ dysfunction syndrome (MODS) are major complications of acute pancreatitis which determine disease severity and outcome. The aim of this study is to investigate the value of admission heart rate variability as a marker of IPN or MODS in severe acute pancreatitis (SAP) patients. Forty-one SAP patients within 72 h of symptoms onset were included in this prospective observational study. General demographics, laboratory data and the acute physiology and chronic health evaluation (APACHE) II scores were recorded at admission. 5-minute ECG signals were obtained at the same time for heart rate variability analyses to assess SAP severity. The baseline heart rate variability measurements, levels of low frequency/high frequency (LF/HF) were significantly lower whereas high frequency norm (nHF) levels were significantly higher in patients who present with IPN and MODS or died (P procalcitonin. nHF and LF/HF were better than APACHE II in predicting IPN and LF/HF showed superiority over APACHE II in the prediction of MODS. Admission heart rate variability is a good marker of IPN and MODS in SAP patients.

  9. 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

  10. 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

    2013-05-01

    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.

  11. Determination of variables in the prediction of strontium distribution coefficients for selected sediments

    Science.gov (United States)

    Pace, M.N.; Rosentreter, J.J.; Bartholomay, R.C.

    2001-01-01

    Idaho State University and the US Geological Survey, in cooperation with the US Department of Energy, conducted a study to determine and evaluate strontium distribution coefficients (Kds) of subsurface materials at the Idaho National Engineering and Environmental Laboratory (INEEL). The Kds were determined to aid in assessing the variability of strontium Kds and their effects on chemical transport of strontium-90 in the Snake River Plain aquifer system. Data from batch experiments done to determine strontium Kds of five sediment-infill samples and six standard reference material samples were analyzed by using multiple linear regression analysis and the stepwise variable-selection method in the statistical program, Statistical Product and Service Solutions, to derive an equation of variables that can be used to predict strontium Kds of sediment-infill samples. The sediment-infill samples were from basalt vesicles and fractures from a selected core at the INEEL; strontium Kds ranged from ???201 to 356 ml g-1. The standard material samples consisted of clay minerals and calcite. The statistical analyses of the batch-experiment results showed that the amount of strontium in the initial solution, the amount of manganese oxide in the sample material, and the amount of potassium in the initial solution are the most important variables in predicting strontium Kds of sediment-infill samples.

  12. Improving the Prediction of Maturity From Anthropometric Variables Using a Maturity Ratio.

    Science.gov (United States)

    Fransen, Job; Bush, Stephen; Woodcock, Stephen; Novak, Andrew; Deprez, Dieter; Baxter-Jones, Adam D G; Vaeyens, Roel; Lenoir, Matthieu

    2017-10-12

    This study aimed to improve the prediction accuracy of age at peak height velocity (APHV) from anthropometric assessment using nonlinear models and a maturity ratio rather than a maturity offset. The dataset used to develop the original prediction equations was used to test a new prediction model, utilizing the maturity ratio and a polynomial prediction equation. This model was then applied to a sample of male youth academy soccer players (n = 1330) to validate the new model in youth athletes. A new equation was developed to estimate APHV more accurately than the original model (new model: Akaike information criterion: -6062.1, R(2) = 90.82%; original model: Akaike information criterion = 3048.7, R(2) = 88.88%) within a general population of boys, particularly with relatively high/low APHVs. This study has also highlighted the successful application of the new model to estimate APHV using anthropometric variables in youth athletes, thereby supporting the use of this model in sports talent identification and development. This study argues that this newly developed equation should become standard practice for the estimation of maturity from anthropometric variables in boys from both a general and an athletic population.

  13. 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.

  14. The influence of body size, condition index and tidal exposure on the variability in metal bioaccumulation in Mytilus edulis

    Energy Technology Data Exchange (ETDEWEB)

    Mubiana, Valentine K. [Laboratory of Ecophysiology, Biochemistry and Toxicology, Department of Biology, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium)]. E-mail: kayawevalentine.mubiana@ua.ac.be; Vercauteren, Kathleen [Laboratory of Ecophysiology, Biochemistry and Toxicology, Department of Biology, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Blust, Ronny [Laboratory of Ecophysiology, Biochemistry and Toxicology, Department of Biology, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium)

    2006-11-15

    Mussels are commonly used to monitor metal pollution despite high inter-individual variability in tissue concentrations. In this study, influences of body size, condition index and tidal height on concentrations of As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn were investigated. Body weight was inversely related to metal concentrations and for Cd, Mn, Pb and Zn the regression was affected by tidal height. Except for As, Fe and Mn metal concentrations were inversely related to physiological status though no differences between essential and non-essential metals were obvious. After correcting for body size, tidal height was related positively to As, Cd and Zn, negatively related to Cu, Fe and Mn while Co, Cr, Ni and Pb were independent of tidal height. The study recommends stringent measures during sampling for biomonitoring or metal concentrations at each location must be normalized to a common body size, CI and tidal height. - Body size, condition index and shore height can modify metal concentrations in mussels and if not taken into account, can lead to wrong interpretation of monitoring data.

  15. 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

  16. 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.

  17. 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.

  18. 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 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.

  19. 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

  20. The new body mass index system in predicting renal graft outcomes.

    Science.gov (United States)

    Wang, H-H; Lin, K-J; Chu, S-H; Chiang, Y-J; Liu, K-L; Hsieh, C-Y

    2014-01-01

    Obesity has been related to poor renal graft function. The aim of this study was to compare the long-term graft outcomes of living-related kidney recipients regarding donor-to-recipient body mass index (BMI) parameters using the old Quetelet BMI formula and the new Trefethen BMI formula. From November 2002 to November 2010, 62 consecutive living-related kidney transplantations were reviewed retrospectively. Four donor-to-recipient BMI parameters were used: (1) BMI difference by the old formula, (2) BMI difference by the new formula, (3) BMI ratio by the old formula, and (4) BMI ratio by the new formula. Long-term outcomes, including graft survival (GS) and rejection-free graft survival (RFGS) either overall or at 5 years post-transplantation, were analysed according to these parameters. The baseline demography was similar among tertiles according to the four BMI parameters tested. Although there is no significant difference in the long-term survivals by the old and new BMI formula, we found that the area under receiver operating characteristic (ROC) curve is larger using the new formula, either by BMI difference (0.584 vs 0.559 in 5-year GS and 0.658 vs 0.636 in 5-year RFGS) or by BMI ratio (0.584 vs 0.561 in 5-year GS and 0.644 vs 0.626 in 5-year RFGS). The same trend was observed in overall survival outcomes. The new Trefethen BMI formula seems to predict long-term renal graft outcomes better than the old Quetelet BMI formula. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Body Mass Index Predicts Progression of Mild Cognitive Impairment to Dementia.

    Science.gov (United States)

    Cova, Ilaria; Clerici, Francesca; Maggiore, Laura; Pomati, Simone; Cucumo, Valentina; Ghiretti, Roberta; Galimberti, Daniela; Scarpini, Elio; Mariani, Claudio; Caracciolo, Barbara

    2016-01-01

    To examine the relationship between body mass index (BMI) and progression to dementia and Alzheimer's disease (AD) in mild cognitive impairment (MCI). Two hundred and twenty-eight MCI subjects (mean age 74.04 ± 6.94 years; 57% female) from a memory clinic were followed for 2.40 ± 1.58 years. Baseline height and weight were used to calculate the BMI. The main outcome was progression to dementia (DSM-IV criteria) and AD (NINCDS-ADRDA criteria). Cox proportional hazard models were used to assess the longitudinal association of BMI with dementia and AD, adjusting for a comprehensive set of covariates, including vascular risk factors/diseases and neuroimaging profiles. Out of 228 subjects with MCI, 117 (51.3%) progressed to dementia. Eighty-nine (76%) of the incident dementia cases had AD. In both unadjusted and multi-adjusted models, a higher BMI was associated with a reduced risk of dementia (multi-adjusted HR 0.9; 95% CI 0.8-0.9) and AD (multi-adjusted HR 0.9; 95% CI 0.8-0.9). Being underweight increased the risk of all types of dementia (multi-adjusted HR 2.5; 95% CI 1.2-5.1) but was not specifically associated with AD (multi-adjusted HR 2.2; 95% CI 0.9-5.3). BMI predicted progression of MCI to dementia and AD. In particular, a higher BMI was associated with a lower risk of dementia and AD, and underweight was associated with a higher risk of dementia. BMI assessment may improve the prognostic accuracy of MCI in clinical practice. © 2016 S. Karger AG, Basel.

  2. Predictive validity of a brief antiretroviral adherence index: retrospective cohort analysis under conditions of repetitive administration.

    Science.gov (United States)

    Mathews, William C; Barker, Eva; Winter, Erica; Ballard, Craig; Colwell, Bradford; May, Susanne

    2008-08-29

    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. 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 0.36(score >/= 5) (95% CI: 0.19-0.69) [reference: score was 0.17(score >/= 5) (0.05-0.66) [reference: <5]. 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.

  3. 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.

  4. Assessing conservation relevance of organism-environment relations using predicted changes in response variables

    Science.gov (United States)

    Gutzwiller, Kevin J.; Barrow, Wylie C.; White, Joseph D.; Johnson-Randall, Lori; Cade, Brian S.; Zygo, Lisa M.

    2010-01-01

    1. Organism–environment models are used widely in conservation. The degree to which they are useful for informing conservation decisions – the conservation relevance of these relations – is important because lack of relevance may lead to misapplication of scarce conservation resources or failure to resolve important conservation dilemmas. Even when models perform well based on model fit and predictive ability, conservation relevance of associations may not be clear without also knowing the magnitude and variability of predicted changes in response variables. 2. We introduce a method for evaluating the conservation relevance of organism–environment relations that employs confidence intervals for predicted changes in response variables. The confidence intervals are compared to a preselected magnitude of change that marks a threshold (trigger) for conservation action. To demonstrate the approach, we used a case study from the Chihuahuan Desert involving relations between avian richness and broad-scale patterns of shrubland. We considered relations for three winters and two spatial extents (1- and 2-km-radius areas) and compared predicted changes in richness to three thresholds (10%, 20% and 30% change). For each threshold, we examined 48 relations. 3. The method identified seven, four and zero conservation-relevant changes in mean richness for the 10%, 20% and 30% thresholds respectively. These changes were associated with major (20%) changes in shrubland cover, mean patch size, the coefficient of variation for patch size, or edge density but not with major changes in shrubland patch density. The relative rarity of conservation-relevant changes indicated that, overall, the relations had little practical value for informing conservation decisions about avian richness. 4. The approach we illustrate is appropriate for various response and predictor variables measured at any temporal or spatial scale. The method is broadly applicable across ecological

  5. 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.

  6. 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.

  7. A season-of-birth/DRD4 interaction predicts maximal body mass index in women with bulimia nervosa.

    Science.gov (United States)

    Levitan, Robert D; Kaplan, Allan S; Davis, Caroline; Lam, Raymond W; Kennedy, James L

    2010-07-01

    We have earlier reported that season of birth interacts with the hypofunctional 7-repeat (7R) allele of the dopamine-4 receptor gene (DRD4) to promote weight gain and obesity in women with seasonal affective disorder (SAD). This study examined whether this gene-environment interaction influences body weight regulation in women with bulimia nervosa (BN). In 188 female probands with BN, we performed an analysis of covariance predicting maximum lifetime body mass index (BMI) using season-of-birth, DRD4 genotype (7R present/absent), and past history of anorexia nervosa (yes/no) as independent variables, and age at maximum weight as the co-variate. Consistent with our SAD study, the birth-season x DRD4 interaction was a significant predictor of maximal BMI. Although in SAD, the spring-birth/7R+ group had markedly elevated maximal BMIs and high rates of obesity, in this BN sample, the fall-birth/7R+ group exhibited the highest BMI values (N=17: mean maximal BMI=28.2 kg/m(2) (SE 0.9) vs 25.2 kg/ m(2) (SE 0.3) for all other probands combined (N=171); p=0.002). The lifetime rate of obesity (BMI>30) was also higher in the fall-birth/7R+ vs 'other' group (29.9 vs 8.8%, respectively, p=0.008). These data offer further evidence that season of birth interacts with the 7R allele of DRD4 to influence body weight regulation in female overeating populations.

  8. Water quality indexing for predicting variation of water quality over time

    African Journals Online (AJOL)

    PPoonoosamy

    evaluate the quality of a given water body in such a way that it is easily understood by managers. ... the problem of 'eclipsing' which arises during aggregation process. ... to improve the Water Quality index, mainly to stress on the importance of the ... Thus, since the water quality indexing method yields a single value, it is.

  9. A Fit-Fat Index for Predicting Incident Diabetes in Apparently Healthy Men: A Prospective Cohort Study.

    Directory of Open Access Journals (Sweden)

    Robert A Sloan

    Full Text Available The purpose of this study was to examine the impact of combined cardiorespiratory fitness and waist-to-height ratio in the form of a fit-fat index on incident diabetes risk. Additionally, the independent predictive performance of cardiorespiratory fitness, waist-to-height ratio, and body mass index also were estimated and compared.This was a prospective cohort study of 10,381 men who had a normal electrocardiogram and no history of major chronic disease at baseline from 1979 to 2005. Random survival forest models and traditional Cox proportional hazards models were used to predict diabetes at 5-, 10-, and 15-year incidence horizons.Overall, 4.8% of the participants developed diabetes. Receiver operating characteristic curve analyses for incidence risk demonstrated good discrimination using random survival forest models across fitness and fatness measures; Cox models were poor to fair. The differences between fitness and fatness measures across horizons were clinically negligible. Smoothed random survival forest estimates demonstrated the impact of each fitness and fatness measure on incident diabetes was intuitive and graded.Although fitness and fatness measures showed a similar discriminative ability in predicting incident diabetes, unique to the study was the ability of the fit-fat index to demonstrate a better indication of incident risk when compared to fitness or fatness alone. A single index combining cardiorespiratory fitness and waist-to-height ratio may be more useful because it can indicate improvements in either or both of the measures.

  10. The Kuroshio Extension low-frequency variability analyzed with altimeter data through an ad hoc composite index

    Science.gov (United States)

    Pierini, Stefano; Gentile, Vittorio; de Ruggiero, Paola; Pietranera, Luca

    2017-04-01

    The Kuroshio Extension (KE) low-frequency variability (LFV) is analyzed with the satellite altimeter data distributed by AVISO from January 1993 to November 2015 through a new ad hoc composite index [1] that links the mean latitudinal position L of the KE jet and an integrated wavelet amplitude A measuring the high-frequency variability (HFV) of the KE path. This approach allows one to follow the KE evolution as an orbit in the (L,A) plane, as typically done in dynamical systems theory. Three intervals, I1 (1993-1998), I2 (1998-2006) and I3 (2006-November 2015) are separately analyzed also with sea surface height (SSH) maps. In I1 and I3, L and A are mostly anti-correlated and a recharging phase (characterized by a weak convoluted jet experiencing a rapid increase of the HFV) begins when negative SSH anomalies, remotely generated by the Pacific Decadal Oscillation, reach the KE region. On the other hand, in I2 the KE evolution is described by a hysteresis loop: this starts with a weak jet state followed by a recharging phase leading, in turn, to a persistent two-meander state, to its progressive and rapid erosion and, eventually, to the reestablishment of a weak jet state. This loop is found to correspond quite closely to the highly nonlinear intrinsic relaxation oscillation obtained in numerical process studies [1,2]. This supports the hypothesis that the KE LFV may have been controlled, during I2, by an intrinsic oceanic mode of variability. [1] Pierini S., 2015. J. Climate, 28, 5873-5881. [2] Pierini S., 2006. J. Phys. Oceanogr., 36, 1605-1625.

  11. Speed and Cardiac Recovery Variables Predict the Probability of Elimination in Equine Endurance Events.

    Directory of Open Access Journals (Sweden)

    Mohamed Younes

    Full Text Available Nearly 50% of the horses participating in endurance events are eliminated at a veterinary examination (a vet gate. Detecting unfit horses before a health problem occurs and treatment is required is a challenge for veterinarians but is essential for improving equine welfare. We hypothesized that it would be possible to detect unfit horses earlier in the event by measuring heart rate recovery variables. Hence, the objective of the present study was to compute logistic regressions of heart rate, cardiac recovery time and average speed data recorded at the previous vet gate (n-1 and thus predict the probability of elimination during successive phases (n and following in endurance events. Speed and heart rate data were extracted from an electronic database of endurance events (80-160 km in length organized in four countries. Overall, 39% of the horses that started an event were eliminated--mostly due to lameness (64% or metabolic disorders (15%. For each vet gate, logistic regressions of explanatory variables (average speed, cardiac recovery time and heart rate measured at the previous vet gate and categorical variables (age and/or event distance were computed to estimate the probability of elimination. The predictive logistic regressions for vet gates 2 to 5 correctly classified between 62% and 86% of the eliminated horses. The robustness of these results was confirmed by high areas under the receiving operating characteristic curves (0.68-0.84. Overall, a horse has a 70% chance of being eliminated at the next gate if its cardiac recovery time is longer than 11 min at vet gate 1 or 2, or longer than 13 min at vet gates 3 or 4. Heart rate recovery and average speed variables measured at the previous vet gate(s enabled us to predict elimination at the following vet gate. These variables should be checked at each veterinary examination, in order to detect unfit horses as early as possible. Our predictive method may help to improve equine welfare and

  12. Lower heart rate variability predicts increased level of C-reactive protein 4 years later in healthy, nonsmoking adults.

    Science.gov (United States)

    Jarczok, M N; Koenig, J; Mauss, D; Fischer, J E; Thayer, J F

    2014-12-01

    Inflammation and vagally mediated heart rate variability (vmHRV) have been implicated in a number of conditions including diabetes and cardiovascular disease. Consistent with the inflammatory reflex termed the 'cholinergic anti-inflammatory pathway', numerous cross-sectional studies have demonstrated negative associations between vmHRV and inflammatory markers such as C-reactive protein (CRP). The only prospective study, however, showed the opposite: higher CRP at baseline predicted higher high-frequency heart rate variability (HF-HRV) at follow-up. Thus, additional studies are needed to examine the prospective association between vmHRV and CRP. Healthy employees participated in a voluntary on-site health assessment. Blood samples and ambulatory heart rate recordings were obtained, and night-time HF-HRV was calculated. Useable heart rate data were available in 2007 for 106 nonsmoking employees (9% women; age 44.4 ± 8 years), all of whom returned for an identical follow-up health assessment in 2011. Bootstrapped (500 replications) bivariate (r) and partial Pearson's correlations (ppc) adjusting for sex, age and body mass index at baseline (2007) were calculated. Zero-order correlations indicated that higher HF-HRV was associated with lower levels of CRP at both time-points (2007: r = -0.19, P < 0.05; 2011: r = -0.34, P < 0.001). After adjustment, HF-HRV remained a significant predictor of CRP (ppc = -0.20, P < 0.05). In this study, we have provided in vivo support for the cholinergic anti-inflammatory pathway in humans. Cardiac vagal modulation at baseline predicts level of CRP 4 years later. Our findings have important implications for the role of vmHRV as a risk factor for cardiovascular disease morbidity and mortality. Interventions targeted at vmHRV might be useful in the prevention of diseases associated with elevated systemic inflammation. © 2014 The Association for the Publication of the Journal of Internal Medicine.

  13. Clinical utility of serum biochemical variables for predicting acid-base balance in critically ill horses.

    Science.gov (United States)

    Stämpfli, Henry R; Schoster, Angelika; Constable, Peter D

    2014-12-01

    Profiles from serum biochemical analyzers include the concentration of strong electrolytes (including l-lactate), total carbon dioxide (tCO2 ), and total protein. These variables are associated with changes in acid-base balance. Application of physicochemical principles may allow predicting acid-base balance from serum biochemistry without measuring whole blood pH and pCO2 . The purpose of the study was to determine if the acid-base status of critically ill horses could be accurately predicted using variables included in standard serum biochemical profiles. Two jugular venous blood samples were prospectively obtained from critically ill horses and foals. Samples were analyzed using a whole blood gas and pH analyzer (BG) and a serum biochemistry multi analyzer system (AMAS). Linear regression, Deming regression, and Bland-Altman plots were used for method comparison and P acid base interpretation, were different between the AMAS and BG analyzer. Using physicochemical principles, BG results accurately predicted pH, whereas the AMAS results did not when a fixed value for pCO2 was used. Measurement of pCO2 is required in critically ill horses for accurate prediction of whole blood pH. Differences in the measured values of Na and Cl concentration exist when measured in serum by the AMAS and in whole blood or plasma by BG, indicating that the accurate prediction of whole blood pH is analyzer-dependent. Application of physicochemical principles to plasma or serum provides a practical method to evaluate analyzer accuracy. © 2014 American Society for Veterinary Clinical Pathology.

  14. Biographical and demographical variables as moderators in the prediction of turnover intentions

    Directory of Open Access Journals (Sweden)

    Janine du Plooy

    2013-01-01

    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.

  15. Variable performance of models for predicting methicillin-resistant Staphylococcus aureus carriage in European surgical wards.

    Science.gov (United States)

    Lee, Andie S; Pan, Angelo; Harbarth, Stephan; Patroni, Andrea; Chalfine, Annie; Daikos, George L; Garilli, Silvia; Martínez, José Antonio; Cooper, Ben S

    2015-02-27

    Predictive models to identify unknown methicillin-resistant Staphylococcus aureus (MRSA) carriage on admission may optimise targeted MRSA screening and efficient use of resources. However, common approaches to model selection can result in overconfident estimates and poor predictive performance. We aimed to compare the performance of various models to predict previously unknown MRSA carriage on admission to surgical wards. The study analysed data collected during a prospective cohort study which enrolled consecutive adult patients admitted to 13 surgical wards in 4 European hospitals. The participating hospitals were located in Athens (Greece), Barcelona (Spain), Cremona (Italy) and Paris (France). Universal admission MRSA screening was performed in the surgical wards. Data regarding demographic characteristics and potential risk factors for MRSA carriage were prospectively collected during the study period. Four logistic regression models were used to predict probabilities of unknown MRSA carriage using risk factor data: "Stepwise" (variables selected by backward elimination); "Best BMA" (model with highest posterior probability using Bayesian model averaging which accounts for uncertainty in model choice); "BMA" (average of all models selected with BMA); and "Simple" (model including variables selected >50% of the time by both Stepwise and BMA approaches applied to repeated random sub-samples of 50% of the data). To assess model performance, cross-validation against data not used for model fitting was conducted and net reclassification improvement (NRI) was calculated. Of 2,901 patients enrolled, 111 (3.8%) were newly identified MRSA carriers. Recent hospitalisation and presence of a wound/ulcer were significantly associated with MRSA carriage in all models. While all models demonstrated limited predictive ability (mean c-statistics MRSA-positive individuals despite screening fewer patients than the Stepwise model. Moreover, the Simple model improved

  16. 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

  17. 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

  18. Generation of a predictive melphalan resistance index by drug screen of B-cell cancer cell lines.

    Directory of Open Access Journals (Sweden)

    Martin Boegsted

    Full Text Available BACKGROUND: Recent reports indicate that in vitro drug screens combined with gene expression profiles (GEP of cancer cell lines may generate informative signatures predicting the clinical outcome of chemotherapy. In multiple myeloma (MM a range of new drugs have been introduced and now challenge conventional therapy including high dose melphalan. Consequently, the generation of predictive signatures for response to melphalan may have a clinical impact. The hypothesis is that melphalan screens and GEPs of B-cell cancer cell lines combined with multivariate statistics may provide predictive clinical information. MATERIALS AND METHODS: Microarray based GEPs and a melphalan growth inhibition screen of 59 cancer cell lines were downloaded from the National Cancer Institute database. Equivalent data were generated for 18 B-cell cancer cell lines. Linear discriminant analyses (LDA, sparse partial least squares (SPLS and pairwise comparisons of cell line data were used to build resistance signatures from both cell line panels. A melphalan resistance index was defined and estimated for each MM patient in a publicly available clinical data set and evaluated retrospectively by Cox proportional hazards and Kaplan-Meier survival analysis. PRINCIPAL FINDINGS: Both cell line panels performed well with respect to internal validation of the SPLS approach but only the B-cell panel was able to predict a significantly higher risk of relapse and death with increasing resistance index in the clinical data sets. The most sensitive and resistant cell lines, MOLP-2 and RPMI-8226 LR5, respectively, had high leverage, which suggests their differentially expressed genes to possess important predictive value. CONCLUSION: The present study presents a melphalan resistance index generated by analysis of a B-cell panel of cancer cell lines. However, the resistance index needs to be functionally validated and correlated to known MM biomarkers in independent data sets in order to

  19. 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.

  20. [Values of the sperm deformity index, acrosome abnormity rate, and sperm DNA fragmentation index of optimized sperm in predicting IVF fertilization failure].

    Science.gov (United States)

    Jiang, Wei-jie; Jin, Fan; Zhou, Li-ming

    2016-02-01

    To investigate the values of the sperm deformity index (SDI), acrosome abnormity rate (AAR), and DNA fragmentation index (DFI) of optimized sperm in the prediction of fertilization failure (fertilization rate fertilization (IVF). We selected 695 cycles of conventional IVF for pure oviductal infertility in this study, including 603 cycles of normal fertilization and 92 cycles of fertilization failure. On the day of oocyte retrieval, we examined sperm morphology, acrosome morphology, and DNA fragmentation using the Diff-Quik, PSA-FITC and SCD methods. We established the joint predictor (JP) by logistic equation and analyzed the values of different parameters in predicting fertilization failure with the receiver operating characteristic (ROC) curve. The fertilization rate was negatively correlated with SDI (r = - 0.07; P = 0.03), AAR (r = -0.49; P fertilization group were 1.24 ± 0.20, (7.75 ± 2.28)%, and (7.87 ± 3.15)%, and those in the fertilization failure group were 1.42 ± 0.15, (12.02 ± 3.06)%, and (13.32 ± 4.13)%, respectively, all with statistically significant differences between the two groups (P fertilization failure ( OR = 2.68, 14.11, and 3.85; P = 0.01, fertilization failure were approximately 1.45, 10%, and 12%. The SDI, AAR and DFI of optimized sperm are closely associated with the fertilization rate, and all have the value for predicting fertilization failure in IVF. The AAR is more valuable than the other single predictors, but JP is more effective than the AAR.

  1. Variability in depressive symptoms predicts cognitive decline in age-related macular degeneration.

    Science.gov (United States)

    Rovner, Barry W; Casten, Robin J; Leiby, Benjamin E

    2009-07-01

    The measurement of affective symptoms in older persons who decline cognitively is uncertain. The authors investigated whether mood variability predicts dementia in patients with age-related macular degeneration (AMD). Three-year observational study after a clinical trial. Community follow-up of outpatients ascertained from retina clinics. One hundred sixty patients with AMD. Geriatric Depression Scale (GDS) administered every 2 weeks for 6 months to subjects; Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) administered to subjects' knowledgeable informants. Twenty-three subjects (14.4%) declined cognitively. Age, education, baseline GDS score > or =5, and variability in GDS scores (i.e., fluctuations between adjacent time points) were associated with cognitive decline. For GDS variability, each 1 unit increase in the residual standard deviation (SD) of the GDS increased the risk for cognitive decline by 93% (IDR = 1.92; 95% CI [1.27-2.91]). Thus, subjects with a residual SD of 1 were nearly twice as likely to become demented as subjects with no variability in GDS scores. The risk for subjects with SDs of 2 increased more than threefold (IDR = 3.68; 95% CI [1.61-8.47]). A multiple regression analysis showed that GDS variability was a significant risk factor for dementia after controlling for significant covariates. These data suggest a useful approach to conceptualizing and measuring depressive symptoms in older persons. Variability in self-reported mood may be an early sign of dementia and may offer new insights into the neurobiological mechanisms linking depression and cognition

  2. The Adult Deformity Surgery Complexity Index (ADSCI): a valid tool to quantify the complexity of posterior adult spinal deformity surgery and predict postoperative complications.

    Science.gov (United States)

    Pellisé, Ferran; Vila-Casademunt, Alba; Núñez-Pereira, Susana; Domingo-Sàbat, Montse; Bagó, Juan; Vidal, Xavier; Alanay, Ahmet; Acaroglu, Emre; Kleinstück, Frank; Obeid, Ibrahim; Pérez-Grueso, Francisco J S; Lafage, Virginie; Bess, Shay; Ames, Christopher; Mannion, Anne F

    2017-07-04

    Anesthesiologists I/II). Fifty-one international experts participated in the Delphi consensus process. The surgical variables selected by consensus and included in the equation were divided into actions and factors. Actions selected were number of fused segments, decompressions, interbody fusions, and cemented levels; number and type of posterior osteotomies; and use of pelvic fixation. The factors included were implant density, revision surgery, and team experience. ADSCI-RM-Mixed (regression model with Delphi formula interactions) provided the best estimates and predictive value, well above Mirza's invasiveness index. The ADSCI-RM-Mixed, with greater AUCs (>0.70), was also the most sensitive and specific for both of the dependent variables studied and for complication prediction. ADSCI-RM-Mixed obtained also the highest R2 value in the validation cohort in predicting blood loss (R2=0.34) and surgical time (R2=0.26) with effect sizes similar to those for the derivation cohort. The ADSCI is the first tool to be specifically developed for the preoperative assessment of the complexity of ASD surgery. This study confirms its validity, specificity, and sensitivity, and shows that it has greater predictive capability than the more generic Mirza invasiveness index. The ADSCI should be useful for quantitatively estimating the increased risk associated with more invasive surgery and adjusting for surgical case-mix when making safety comparisons in ASDS. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. 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

  4. A new somatic cell count index to more accurately predict milk yield losses

    Directory of Open Access Journals (Sweden)

    J. Jeretina

    2017-10-01

    Full Text Available Intramammary infection and clinical mastitis in dairy cows leads to considerable economic losses for farmers. The somatic cell concentration in cow's milk has been shown to be an excellent indicator for the prevalence of subclinical mastitis. In this study, a new somatic cell count index (SCCI was proposed for the accurate prediction of milk yield losses caused by elevated somatic cell count (SCC. In all, 97 238 lactations (55 207 Holstein cows from 2328 herds were recorded between 2010 and 2014 under different scenarios (high and low levels of SCC, four lactation stages, different milk yield intensities, and parities (1, 2, and  ≥  3. The standard shape of the curve for SCC was determined using completed standard lactations of healthy cows. The SCCI was defined as the sum of the differences between the measured interpolated values of the natural logarithm of SCC (ln(SCC and the values for the standard shape of the curve for SCC for a particular period, divided by the total area enclosed by the standard curve and upper limit of ln(SCC  =  10 for SCC. The phenotypic potential of milk yield (305-day milk yield – MY305 was calculated using regression coefficients estimated from the linear regression model for parity and breeding values of cows for milk yield. The extent of daily milk yield loss caused by increased SCC was found to be mainly related to the early stage of lactation. Depending on the possible scenarios, the estimated milk yield loss from MY305 for primiparous cows was at least 0.8 to 0.9 kg day−1 and for multiparous cows it ranged from 1.3 to 4.3 kg day−1. Thus, the SCCI was a suitable indicator for estimating daily milk yield losses associated with increased SCC and might provide farmers reliable information to take appropriate measures for ensuring good health of cows and reducing milk yield losses at the herd level.

  5. 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.

  6. Haptoglobin Phenotype Predicts a Low Heart Rate Variability in Patients with Chronic Kidney Disease

    DEFF Research Database (Denmark)

    Svensson, My; Strandhave, Charlotte; Krarup, H.B.

    F-PO1096 Haptoglobin Phenotype Predicts a Low Heart Rate Variability in Patients with Chronic Kidney Disease My Svensson,1 Charlotte Strandhave,1 Henrik My Svensson,1 Charlotte Strandhave,1 HenrikKrarup,2 Jeppe H. Christensen.1 1Department of Nephrology, Aalborg Hospital, Aalborg, Denmark; 2...... to a phenotype-dependent antioxidant capacity where Hp 2-2 exhibits a low antioxidant ability, increasing the risk of cardiovascular disease. An attenuated heart rate variability (HRV) may be an important predictor of mortality in patients with chronic kidney disease (CKD). In the present study, we examined......Department of Clinical Biochemistry, Aalborg Hospital, Aalborg, Denmark. Introduction Three major phenotypes for the haptoglobin (Hp) gene has been identified: Hp 1-1, Hp 2-2, and the heterozygous Hp 2-1. Hp 2-2 is associated with a poor outcome in patients with cardiovascular disease. This may be due...

  7. The Climate Variability & Predictability (CVP) Program at NOAA - DYNAMO Recent Project Advancements

    Science.gov (United States)

    Lucas, S. E.; Todd, J. F.; Higgins, W.

    2013-12-01

    The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International Geosphere-Biosphere Programme (IGBP), and the U.S. Global Change Research Program (USGCRP). The CVP program sits within the Earth System Science (ESS) Division at NOAA's Climate Program Office. Dynamics of the Madden-Julian Oscillation (DYNAMO): The Indian Ocean is one of Earth's most sensitive regions because the interactions between ocean and atmosphere there have a discernable effect on global climate patterns. The tropical weather that brews in that region can move eastward along the equator and reverberate around the globe, shaping weather and climate in far-off places. The vehicle for this variability is a phenomenon called the Madden-Julian Oscillation, or MJO. The MJO, which originates over the Indian Ocean roughly every 30 to 90 days, is known to influence the Asian and Australian monsoons. It can also enhance hurricane activity in the northeast Pacific and Gulf of Mexico, trigger torrential rainfall along the west coast of North America, and affect the onset of El Niño. CVP-funded scientists participated in the DYNAMO field campaign in 2011-12. Results from this international campaign are expected to improve researcher's insights into this influential phenomenon. A better understanding of the processes governing MJO is an essential step toward

  8. Prognostic Nutritional Index Predicts Severe Complications, Recurrence, and Poor Prognosis in Patients With Colorectal Cancer Undergoing Primary Tumor Resection.

    Science.gov (United States)

    Tokunaga, Ryuma; Sakamoto, Yasuo; Nakagawa, Shigeki; Miyamoto, Yuji; Yoshida, Naoya; Oki, Eiji; Watanabe, Masayuki; Baba, Hideo

    2015-11-01

    The prognostic nutritional index is reportedly related to postoperative outcomes. The aim of this study was to elucidate the clinical importance of the prognostic nutritional index in patients with colorectal cancer who were undergoing primary tumor resection. This is a retrospective study from a single institution. This study was conducted at a colorectal surgery service in an academic teaching hospital. The 556 patients with colorectal cancer who were undergoing surgery between March 2005 and August 2014 were eligible for this study. The preoperative prognostic nutritional index was calculated. Classification and regression tree analysis was performed to determine the prognostic nutritional index cutoff value. The associations of the prognostic nutritional index status with clinicopathological factors and postoperative outcomes were examined using univariate and multivariate analyses. Classification and regression tree analysis demonstrated that 45.5 was the optimal cutoff value. The low status (≤45.5) was correlated with older age, low BMI, low estimated glomerular filtration rate, CEA positivity, carbohydrate antigen 19-9 positivity, preoperative chemotherapy, tumors invading muscular or deeper layers, distant metastasis, poor differentiation, severe postoperative complications, tumor recurrence, and poor survival. In multivariate analysis, the low status was an independent risk factor for severe postoperative complications (OR = 2.06 [95% CI, 1.22-3.50]; p = 0.007) and low overall survival (HR =3.98 [95% CI, 2.38-6.89]; p nutritional index status, not considering the postoperative host status. The preoperative prognostic nutritional index predicts severe complications, recurrence, and poor prognosis in patients with colorectal cancer who are undergoing primary tumor resection. Investigation of the nutritional and immunologic statuses using the prognostic nutritional index could be a useful clinical approach.

  9. The Total Joint Arthroplasty Cardiac Risk Index for Predicting Perioperative Myocardial Infarction and Cardiac Arrest After Primary Total Knee and Hip Arthroplasty.

    Science.gov (United States)

    Waterman, Brian R; Belmont, Philip J; Bader, Julia O; Schoenfeld, Andrew J

    2016-06-01

    Current indices fail to consistently predict risk for major adverse cardiac events after major total joint arthroplasty. All primary total knee arthroplasty (TKA) and total hip arthroplasty (THA) were identified from the National Surgical Quality Improvement Program data set. Based on prior analyses, age ≥80 years, history of hypertension, and history of cardiac disease were evaluated as predictors of myocardial infarction and cardiac arrest using stepwise multivariate logistic regression. A series of predictive scores were constructed and weighted to identify the influence of each variable on 30-day postoperative cardiac events, while comparing with the Revised Cardiac Risk Index (RCRI). Among 85,129 patients, age ≥80 years, hypertension, and a history of cardiac disease were all statistically significant predictors of postoperative cardiac events (0.32%; n = 275) after TKA and THA (P ≤ .02). Equal weighting of all variables maintained the highest discriminative capacity in both THA and TKA cohorts. Adjusted models explained 75% and 71% of the variation in postoperative cardiac events for those with THA and TKA, respectively, without statistically significant lack of fit (P = .52; P = .23, respectively). Conversely, the RCRI was not a significant predictor of postoperative cardiac events after TKA (odds ratio, 3.36; 95% CI, 0.19, 58.04; P = .40), although it maintained a similar discriminative capacity after THA (76%). The current total joint arthroplasty Cardiac Risk Index score was the most economical in predicting postoperative cardiac complication after primary unilateral TKA and THA. The RCRI was not a significant predictor of perioperative cardiac events for TKA patients but performed similarly to the current model for THA. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Comparison between genomic predictions using daughter yield deviation and conventional estimated breeding value as response variables

    DEFF Research Database (Denmark)

    Guo, Gang; Lund, Mogens Sandø; Zhang, Y

    2010-01-01

    This study compared genomic predictions using conventional estimated breeding values (EBV) and daughter yield deviations (DYD) as response variables based on simulated data. Eight scenarios were simulated in regard to heritability (0.05 and 0.30), number of daughters per sire (30, 100, and unequal...... scenarios, the EBV approach was as effective as or slightly better than the DYD approach at predicting breeding value, dependent on simulated scenarios and statistical models. Applying a Bayesian common prior model (the same prior distribution of marker effect variance) and a linear mixed model (GBLUP......), the EBV and DYD approaches provided similar genomic estimated breeding value (GEBV) reliabilities, except for scenarios with unequal numbers of daughters and half of sires without genotype, for which the EBV approach was superior to the DYD approach (by 1.2 and 2.4%). Using a Bayesian mixture prior model...

  11. Does Body Mass Index Predict Premature Cardiomyopathy Onset for Duchenne Muscular Dystrophy?

    Science.gov (United States)

    McKane, Meghann; Soslow, Jonathan H; Xu, Meng; Saville, Benjamin R; Slaughter, James C; Burnette, W Bryan; Markham, Larry W

    2017-04-01

    Duchenne muscular dystrophy leads to cardiomyopathy. The objective of this study was to estimate the association of body mass index with cardiomyopathy onset. Cardiomyopathy was defined as left ventricular ejection fraction Duchenne muscular dystrophy subjects and age of cardiomyopathy onset.

  12. 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.

  13. 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.)

  14. 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.

  15. The taxonomic distinctness of macroinvertebrate communities of Atlantic Forest streams cannot be predicted by landscape and climate variables, but traditional biodiversity indices can.

    Science.gov (United States)

    Roque, F O; Guimarães, E A; Ribeiro, M C; Escarpinati, S C; Suriano, M T; Siqueira, T

    2014-11-01

    Predicting how anthropogenic activities may influence the various components of biodiversity is essential for finding ways to reduce diversity loss. This challenge involves: a) understanding how environmental factors influence diversity across different spatial scales, and b) developing ways to measure these relationships in a way that is fast, economical, and easy to communicate. In this study, we investigate whether landscape and bioclimatic variables could explain variation in biodiversity indices in macroinvertebrate communities from 39 Atlantic Forest streams. In addition to traditional diversity measures, i.e., species richness, abundance and Shannon index, we used a taxonomic distinctness index that measures the degree of phylogenetic relationship among taxa. The amount of variation in the diversity measures that was explained by environmental and spatial variables was estimated using variation partitioning based on multiple regression. Our study demonstrates that taxonomic distinctness does not respond in the same way as the traditional used in biodiversity studies. We found no evidence that taxonomic distinctness responds predictably to variation in landscape metrics, indicating the need for the incorporation of predictors at multiple scales in this type of study. The lack of congruence between taxonomic distinctness and other indices and its low predictability may be related to the fact that this measure expresses long-term evolutionary adaptation to ecosystem conditions, while the other traditional biodiversity metrics respond to short-term environmental changes.

  16. 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.

  17. Predictive Value of Middle Cerebral Artery to Uterine Artery Pulsatility Index Ratio in Hypertensive Disorders of Pregnancy

    Directory of Open Access Journals (Sweden)

    Prashanth Adiga

    2015-01-01

    Full Text Available Aims and Objectives. (i To determine the predictive value of cerebrouterine (CU ratio (middle cerebral artery to uterine artery pulsatility index, MCA/UT PI in assessing perinatal outcome among hypertensive disorders of pregnancy. (ii To compare between CU ratio and CP ratio (MCA/Umbilical artery PI as a predictor of adverse perinatal outcome. Methods. A prospective observational study was done in a tertiary medical college hospital, from September 2012 to August 2013. One hundred singleton pregnancies complicated by hypertension peculiar to pregnancy were enrolled. Both CU and CP ratios were estimated. The perinatal outcomes were studied. Results. Both cerebrouterine and cerebroplacental ratios had a better negative predictive value in predicting adverse perinatal outcome. However, both CU and CP ratios when applied together were able to predict adverse outcomes better than individual ratios. The sensitivity, specificity, positive predictive value, and the negative predictive values for an adverse neonatal outcome with CU ratio were 61.3%, 70.3%, 56%, and 78.9%, respectively, compared to 42%, 57.5%, 62%, and 76% as with CP ratio. Conclusion. Cerebrouterine ratio and cerebroplacental ratio were complementary to each other in predicting the adverse perinatal outcomes. Individually, both ratios were reassuring for favorable perinatal outcome with high negative predictive value.

  18. Benchmarking of essential climate variables: Gamma index theory and results for surface albedo and aerosol optical depth.

    Science.gov (United States)

    Cappucci, Fabrizio; Gobron, Nadine

    2017-12-15

    This paper proposes a benchmarking method for assessing the level of spatio-temporal variability of Essential Climate Variable (ECV) products against a reference taking into account acceptance criteria in terms of intensity and physical distance tolerances. This is based on a modified version of the gamma index that could be suitable for fitness-for-purpose assessment given that one can choose various criteria depending on applications. The method is first presented and then applied to both land and atmospheric ECVs. The terrestrial analysis concerns the global surface albedo, using monthly white-sky surface albedo in the visible, near-infrared and shortwave broadband spectral ranges at a spatial resolution of 0.05° using three sources of products. The latter study is conducted using monthly aerosol optical depth (AOD) products at 550 nm at a spatial resolution of 1° with four different datasets at the global scale. The analysis shows how the values of the gamma criteria impact the spatial and temporal results. As an example, if the Global Climate Observing System (GCOS) actual target measurements uncertainty is used as an acceptance criteria for the intensity tolerance the results show that: 1) the seasonal agreement for the surface albedo products varies over 20% to 40% of the terrestrial surface in the shortwave and near-infrared broadband and from 10% to 30% in the visible one and 2) the three aerosols optical depth products agree with the reference one for over 50% of the land surface only when the tolerance distance term is at 224km.

  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. Determination of fruit maturity and its prediction model based on the pericarp index of absorbance difference (IAD for peaches.

    Directory of Open Access Journals (Sweden)

    Binbin Zhang

    Full Text Available Harvest maturity is closely related to peach fruit quality and has a very important effect on the fresh fruit market. Unfortunately, at present, it is difficult to determine the maturity level of peach fruits by artificial methods. The objectives of this study were to develop quadratic polynomial regression models using near-infrared spectroscopy that could determine the peel color difference, fruit firmness, soluble solids content (SSC, soluble sugar, organic acid components, and their relationships with the absorbance of chlorophyll (index of absorbance difference, IAD in late maturing 'Xiahui 8' peach and 'Xiaguang' nectarine fruits. The analysis was based on data for fruits at veraison, fruits at harvesting maturity, and all fruits. The results showed that firmness has the highest correlation coefficient with IAD. Prediction models for fruit maturity were established between firmness and the IAD of the two cultivars using the quadratic polynomial regression method. Further variance analysis on the one degree term and quadratic term of each equation showed that every partial regression coefficient reached a significant or extremely significant level. No significant difference was observed between estimated and observed values after regression prediction. The regression equations seem to fit well. Other peach and nectarine varieties were used to test the feasibility of maturity prediction by this method, and it was found that maturity was successfully predicted in all the samples. The result indicated that the IAD can be used as an index to predict peach fruit maturity.

  1. Determination of fruit maturity and its prediction model based on the pericarp index of absorbance difference (IAD) for peaches.

    Science.gov (United States)

    Zhang, Binbin; Peng, Bin; Zhang, Chunhua; Song, Zhizhong; Ma, Ruijuan

    2017-01-01

    Harvest maturity is closely related to peach fruit quality and has a very important effect on the fresh fruit market. Unfortunately, at present, it is difficult to determine the maturity level of peach fruits by artificial methods. The objectives of this study were to develop quadratic polynomial regression models using near-infrared spectroscopy that could determine the peel color difference, fruit firmness, soluble solids content (SSC), soluble sugar, organic acid components, and their relationships with the absorbance of chlorophyll (index of absorbance difference, IAD) in late maturing 'Xiahui 8' peach and 'Xiaguang' nectarine fruits. The analysis was based on data for fruits at veraison, fruits at harvesting maturity, and all fruits. The results showed that firmness has the highest correlation coefficient with IAD. Prediction models for fruit maturity were established between firmness and the IAD of the two cultivars using the quadratic polynomial regression method. Further variance analysis on the one degree term and quadratic term of each equation showed that every partial regression coefficient reached a significant or extremely significant level. No significant difference was observed between estimated and observed values after regression prediction. The regression equations seem to fit well. Other peach and nectarine varieties were used to test the feasibility of maturity prediction by this method, and it was found that maturity was successfully predicted in all the samples. The result indicated that the IAD can be used as an index to predict peach fruit maturity.

  2. 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 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 components has been

  3. Predicting Disability after Ischemic Stroke Based on Comorbidity Index and Stroke Severity—From the Virtual International Stroke Trials Archive-Acute Collaboration

    Directory of Open Access Journals (Sweden)

    Thanh G. Phan

    2017-05-01

    Full Text Available Background and aimThe availability and access of hospital administrative data [coding for Charlson comorbidity index (CCI] in large data form has resulted in a surge of interest in using this information to predict mortality from stroke. The aims of this study were to determine the minimum clinical data set to be included in models for predicting disability after ischemic stroke adjusting for CCI and clinical variables and to evaluate the impact of CCI on prediction of outcome.MethodWe leverage anonymized clinical trial data in the Virtual International Stroke Trials Archive. This repository contains prospective data on stroke severity and outcome. The inclusion criteria were patients with available stroke severity score such as National Institutes of Health Stroke Scale (NIHSS, imaging data, and outcome disability score such as 90-day Rankin Scale. We calculate CCI based on comorbidity data in this data set. For logistic regression, we used these calibration statistics: Nagelkerke generalised R2 and Brier score; and for discrimination we used: area under the receiver operating characteristics curve (AUC and integrated discrimination improvement (IDI. The IDI was used to evaluate improvement in disability prediction above baseline model containing age, sex, and CCI.ResultsThe clinical data among 5,206 patients (55% males were as follows: mean age 69 ± 13 years, CCI 4.2 ± 0.8, and median NIHSS of 12 (IQR 8, 17 on admission and 9 (IQR 5, 15 at 24 h. In Model 2, adding admission NIHSS to the baseline model improved AUC from 0.67 (95% CI 0.65–0.68 to 0.79 (95% CI 0.78–0.81. In Model 3, adding 24-h NIHSS to the baseline model resulted in substantial improvement in AUC to 0.90 (95% CI 0.89–0.91 and increased IDI by 0.23 (95% CI 0.22–0.24. Adding the variable recombinant tissue plasminogen activator did not result in a further change in AUC or IDI to this regression model. In Model 3, the variable NIHSS at 24 h explains 87.3% of

  4. Predicting Local Dengue Transmission in Guangzhou, China, through the Influence of Imported Cases, Mosquito Density and Climate Variability

    Science.gov (United States)

    Sang, Shaowei; Yin, Wenwu; Bi, Peng; Zhang, Honglong; Wang, Chenggang; Liu, Xiaobo; Chen, Bin; Yang, Weizhong; Liu, Qiyong

    2014-01-01

    Introduction 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. Methodology and Principal Findings 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

  5. 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

  6. Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability.

    Science.gov (United States)

    Sang, Shaowei; Yin, Wenwu; Bi, Peng; Zhang, Honglong; Wang, Chenggang; Liu, Xiaobo; Chen, Bin; Yang, Weizhong; Liu, Qiyong

    2014-01-01

    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 density play a

  7. 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

  8. 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