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Sample records for solubility parameter prediction

  1. The Solubility Parameters of Ionic Liquids

    Science.gov (United States)

    Marciniak, Andrzej

    2010-01-01

    The Hildebrand’s solubility parameters have been calculated for 18 ionic liquids from the inverse gas chromatography measurements of the activity coefficients at infinite dilution. Retention data were used for the calculation. The solubility parameters are helpful for the prediction of the solubility in the binary solvent mixtures. From the solubility parameters, the standard enthalpies of vaporization of ionic liquids were estimated. PMID:20559495

  2. The Solubility Parameters of Ionic Liquids

    Directory of Open Access Journals (Sweden)

    Andrzej Marciniak

    2010-04-01

    Full Text Available The Hildebrand’s solubility parameters have been calculated for 18 ionic liquids from the inverse gas chromatography measurements of the activity coefficients at infinite dilution. Retention data were used for the calculation. The solubility parameters are helpful for the prediction of the solubility in the binary solvent mixtures. From the solubility parameters, the standard enthalpies of vaporization of ionic liquids were estimated.

  3. Prediction of Permeation Resistance of Protective Gloves, etc. from Solubility Parameters

    DEFF Research Database (Denmark)

    Henriksen, H. Risvig; Madsen, Jørgen Øgaard

    1997-01-01

    ). A starting point was the authoritative conclusion (Coletta et al., 1978), that permeation in protective clothing could not be predicted. As a spin off, the predictive concept indicated that new types of polymers sometimes should be incorporated to reach a reasonable (long) breakthrough time and (low...

  4. Revisiting Hansen Solubility Parameters by Including Thermodynamics

    NARCIS (Netherlands)

    Louwerse, Manuel J; Fernández-Maldonado, Ana María; Rousseau, Simon; Moreau-Masselon, Chloe; Roux, Bernard; Rothenberg, Gadi

    2017-01-01

    The Hansen solubility parameter approach is revisited by implementing the thermodynamics of dissolution and mixing. Hansen's pragmatic approach has earned its spurs in predicting solvents for polymer solutions, but for molecular solutes improvements are needed. By going into the details of entropy

  5. Hansen Solubility Parameters for Octahedral Oligomeric Silsesquioxanes

    Science.gov (United States)

    2012-08-28

    1997, 80, 386-&. 5. Hansen, C. M. The three-dimensional solubility parameter -- key to paint component affinities I. J. Paint Technol. 1967, 39, 104...Chai, J.; Zhang, Q. X.; Han, D. X.; Niu, L. Synthesis and Application of Widely Soluble Graphene Sheets. Langmuir 2010, 26, 12314-12320. 12. Hansen, C

  6. The Hildebrand Solubility Parameters of Ionic Liquids—Part 2

    Science.gov (United States)

    Marciniak, Andrzej

    2011-01-01

    The Hildebrand solubility parameters have been calculated for eight ionic liquids. Retention data from the inverse gas chromatography measurements of the activity coefficients at infinite dilution were used for the calculation. From the solubility parameters, the enthalpies of vaporization of ionic liquids were estimated. Results are compared with solubility parameters estimated by different methods. PMID:21747694

  7. The Hildebrand solubility parameters of ionic liquids-part 2.

    Science.gov (United States)

    Marciniak, Andrzej

    2011-01-01

    The Hildebrand solubility parameters have been calculated for eight ionic liquids. Retention data from the inverse gas chromatography measurements of the activity coefficients at infinite dilution were used for the calculation. From the solubility parameters, the enthalpies of vaporization of ionic liquids were estimated. Results are compared with solubility parameters estimated by different methods.

  8. The Hildebrand Solubility Parameters of Ionic Liquids—Part 2

    Directory of Open Access Journals (Sweden)

    Andrzej Marciniak

    2011-06-01

    Full Text Available The Hildebrand solubility parameters have been calculated for eight ionic liquids. Retention data from the inverse gas chromatography measurements of the activity coefficients at infinite dilution were used for the calculation. From the solubility parameters, the enthalpies of vaporization of ionic liquids were estimated. Results are compared with solubility parameters estimated by different methods.

  9. The Chameleonic Behavior of Ionic Liquids and its Impact on the Solubility Parameters Estimation

    DEFF Research Database (Denmark)

    Batista, Marta; Neves, Catarina S; Carvalho, Pedro Jorge

    2011-01-01

    The possibility to develop a solubility parameter scale, with the purpose of predicting the performance and help the selection of ILs, is here evaluated. For the estimation of solubility parameters infinite dilution activity coefficient data is used. The results allowed the identification of a cu...

  10. Scoring function to predict solubility mutagenesis

    Directory of Open Access Journals (Sweden)

    Deutsch Christopher

    2010-10-01

    Full Text Available Abstract Background Mutagenesis is commonly used to engineer proteins with desirable properties not present in the wild type (WT protein, such as increased or decreased stability, reactivity, or solubility. Experimentalists often have to choose a small subset of mutations from a large number of candidates to obtain the desired change, and computational techniques are invaluable to make the choices. While several such methods have been proposed to predict stability and reactivity mutagenesis, solubility has not received much attention. Results We use concepts from computational geometry to define a three body scoring function that predicts the change in protein solubility due to mutations. The scoring function captures both sequence and structure information. By exploring the literature, we have assembled a substantial database of 137 single- and multiple-point solubility mutations. Our database is the largest such collection with structural information known so far. We optimize the scoring function using linear programming (LP methods to derive its weights based on training. Starting with default values of 1, we find weights in the range [0,2] so that predictions of increase or decrease in solubility are optimized. We compare the LP method to the standard machine learning techniques of support vector machines (SVM and the Lasso. Using statistics for leave-one-out (LOO, 10-fold, and 3-fold cross validations (CV for training and prediction, we demonstrate that the LP method performs the best overall. For the LOOCV, the LP method has an overall accuracy of 81%. Availability Executables of programs, tables of weights, and datasets of mutants are available from the following web page: http://www.wsu.edu/~kbala/OptSolMut.html.

  11. Prediction of the solubility in lipidic solvent mixture: Investigation of the modeling approach and thermodynamic analysis of solubility.

    Science.gov (United States)

    Patel, Shruti V; Patel, Sarsvatkumar

    2015-09-18

    Self-micro emulsifying drug delivery system (SMEDDS) is one of the methods to improve solubility and bioavailability of poorly soluble drug(s). The knowledge of the solubility of pharmaceuticals in pure lipidic solvents and solvent mixtures is crucial for designing the SMEDDS of poorly soluble drug substances. Since, experiments are very time consuming, a model, which allows for solubility predictions in solvent mixtures based on less experimental data is desirable for efficiency. Solvents employed were Labrafil® M1944CS and Labrasol® as lipidic solvents; Capryol-90®, Capryol-PGMC® and Tween®-80 as surfactants; Transcutol® and PEG-400 as co-solvents. Solubilities of both drugs were determined in single solvent systems at temperature (T) range of 283-333K. In present study, we investigated the applicability of the thermodynamic model to understand the solubility behavior of drugs in the lipiodic solvents. By using the Van't Hoff and general solubility theory, the thermodynamic functions like Gibbs free energy, enthalpy and entropy of solution, mixing and solvation for drug in single and mixed solvents were understood. The thermodynamic parameters were understood in the framework of drug-solvent interaction based on their chemical similarity and dissimilarity. Clotrimazole and Fluconazole were used as active ingredients whose solubility was measured in single solvent as a function of temperature and the data obtained were used to derive mathematical models which can predict solubility in multi-component solvent mixtures. Model dependent parameters for each drug were calculated at each temperature. The experimental solubility data of solute in mixed solvent system were measured experimentally and further correlated with the calculates values obtained from exponent model and log-linear model of Yalkowsky. The good correlation was observed between experimental solubility and predicted solubility. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. In vitro dynamic solubility test: influence of various parameters.

    Science.gov (United States)

    Thélohan, S; de Meringo, A

    1994-10-01

    This article discusses the dissolution of mineral fibers in simulated physiological fluids (SPF), and the parameters that affect the solubility measurement in a dynamic test where an SPF runs through a cell containing fibers (Scholze and Conradt test). Solutions simulate either the extracellular fluid (pH 7.6) or the intracellular fluid (pH 4.5). The fibers have various chemical compositions and are either continuously drawn or processed as wool. The fiber solubility is determined by the amount of SiO2 (and occasionally other ions) released in the solution. Results are stated as percentage of the initial silica content released or as dissolution rate v in nm/day. The reproducibility of the test is higher with the less soluble fibers (10% solubility), than with highly soluble fibers (20% solubility). The influence of test parameters, including SPF, test duration, and surface area/volume (SA/V), has been studied. The pH and the inorganic buffer salts have a major influence: industrial glasswool composition is soluble at pH 7.6 but not at pH 4.5. The opposite is true for rock- (basalt) wool composition. For slightly soluble fibers, the dissolution rate v remains constant with time, whereas for highly soluble fibers, the dissolution rate decreases rapidly. The dissolution rates believed to occur are v1, initial dissolution rate, and v2, dissolution rate of the residual fibers. The SA of fibers varies with the mass of the fibers tested, or with the fiber diameter at equal mass. Volume, V, is the chosen flow rate. An increase in the SA/V ratio leads to a decrease in the dissolution rate.(ABSTRACT TRUNCATED AT 250 WORDS)

  13. Internal pressure and solubility parameter as a function of pressure

    DEFF Research Database (Denmark)

    Verdier, Sylvain Charles Roland; Andersen, Simon Ivar

    2005-01-01

    The main goal of this work was to measure the solubility parameter of a complex mixture, such as a crude oil, especially as a function of pressure. Thus, its definition is explained, as well as the main approximations generally used in literature. Then, the internal pressure is investigated, since...... pure compounds (four hydrocarbons and I alcohol) were investigated at 303.15 K and up to 30 MPa, as well as a dead crude oil. The "physical" solubility parameter is slightly increasing with pressure (up to 0.8 MPa1/2 for cyclohexane) and, at 0.1 MPa, the difference with literature data is less than 1...

  14. Predicting the Solubility of 1,1-Difluoroethane in Polystyrene Using the Perturbed Soft Chain Theory

    DEFF Research Database (Denmark)

    Pretel, Eduardo; Hong, Seong-Uk

    1998-01-01

    In this study, the solubility of 1,1-difluoroethane in polystyrene was correlated and predicted using the Perturbed Soft Chain Theory (PSCT) and compared with experimental data from the literature. For correlation, a binary interaction parameter was determined by using experimental solubility data...

  15. Hansen solubility parameters for a carbon fiber/epoxy composite

    DEFF Research Database (Denmark)

    Launay, Helene; Hansen, Charles M.; Almdal, Kristoffer

    2007-01-01

    In this study, the physical affinity between an epoxy matrix and oxidized, unsized carbon fibers has been evaluated using Hansen solubility (cohesion) parameters (HSP). A strong physical compatibility has been shown, since their respective HSP are close. The use of a glassy carbon substrate...... as a model for unsized carbon fiber has been demonstrated as appropriate for the study of interactions between the materials in composite carbon fiber-epoxy systems. The HSP of glassy carbon are similar to those of carbon fibers and epoxy matrix. (C) 2007 Elsevier Ltd. All rights reserved....

  16. Method for Predicting Solubilities of Solids in Mixed Solvents

    DEFF Research Database (Denmark)

    Ellegaard, Martin Dela; Abildskov, Jens; O'Connell, J. P.

    2009-01-01

    A method is presented for predicting solubilities of solid solutes in mixed solvents, based on excess Henry's law constants. The basis is statistical mechanical fluctuation solution theory for composition derivatives of solute/solvent infinite dilution activity coefficients. Suitable approximatio...

  17. SOLUBILITY PREDICTION OF SULFONAMIDES AT VARIOUS TEMPERATURES USING A SINGLE DETERMINATION

    Directory of Open Access Journals (Sweden)

    JALAL HANAEE

    2005-04-01

    Full Text Available Solubility of sulphamethoxazole, sulphisoxazole and sulphasalazine in six solvents namely water,methanol, ethanol, 1-propanol, acetone and chloroform were determined at 15, 25, 37 and 45 °C. Two models derived from the Hildebrand solubility approach are proposed for solubility prediction at different temperatures using a single determination. The experimental data of the present work as well as data gathered from the literature have been employed to investigate the accuracy and prediction capability of the proposed models. The overall percent deviations between the predicted and experimental values were 10.78 and 14.63% which were comparable to those of the classical two and three parameter models. The proposed models were much superior to the two pure predictive models i.e., the ones which do not require experimental solubility determination, as the overall percent deviations produced by the latter models were 150.09 and 161.00%.

  18. HIGH PRESSURE PHASE EQUILIBRIUM: PREDICTION OF ESSENTIAL OIL SOLUBILITY

    Directory of Open Access Journals (Sweden)

    Lúcio CARDOZO-FILHO

    1997-12-01

    Full Text Available This work describes a method to predict the solubility of essential oils in supercritical carbon dioxide. The method is based on the formulation proposed in 1979 by Asselineau, Bogdanic and Vidal. The Peng-Robinson and Soave-Redlich-Kwong cubic equations of state were used with the van der Waals mixing rules with two interaction parameters. Method validation was accomplished calculating orange essential oil solubility in pressurized carbon dioxide. The solubility of orange essential oil in carbon dioxide calculated at 308.15 K for pressures of 50 to 70 bar varied from 1.7± 0.1 to 3.6± 0.1 mg/g. For same the range of conditions, experimental solubility varied from 1.7± 0.1 to 3.6± 0.1 mg/g. Predicted values were not very sensitive to initial oil composition.Este trabalho descreve uma metodologia para o cálculo da solubilidade de óleos essenciais em dióxido de carbono a altas pressões baseada na formulação proposta em 1979 por Asselineau, Bogdanic e Vidal. Foram utilizadas as equações cúbicas de estado de Peng-Robinson e Soave-Redlich-Kwong com regras de mistura de van der Waals com dois parâmetros de interação. O cálculo da solubilidade do óleo essencial de laranja em dióxido de carbono pressurizado foi usado para validação do método. A solubilidade calculada a 308,15 K para pressões entre 50 e 70 bar variou entre 1,5 e 4,1 mg/g. Valores experimentais para as mesmas condições variam entre 1,7± 0.1 a 3,6± 0.1 mg/g. Os valores preditos não são muito sensíveis à composição inicial do óleo essencial.

  19. Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption.

    Science.gov (United States)

    Newby, Danielle; Freitas, Alex A; Ghafourian, Taravat

    2015-01-27

    Oral absorption of compounds depends on many physiological, physiochemical and formulation factors. Two important properties that govern oral absorption are in vitro permeability and solubility, which are commonly used as indicators of human intestinal absorption. Despite this, the nature and exact characteristics of the relationship between these parameters are not well understood. In this study a large dataset of human intestinal absorption was collated along with in vitro permeability, aqueous solubility, melting point, and maximum dose for the same compounds. The dataset allowed a permeability threshold to be established objectively to predict high or low intestinal absorption. Using this permeability threshold, classification decision trees incorporating a solubility-related parameter such as experimental or predicted solubility, or the melting point based absorption potential (MPbAP), along with structural molecular descriptors were developed and validated to predict oral absorption class. The decision trees were able to determine the individual roles of permeability and solubility in oral absorption process. Poorly permeable compounds with high solubility show low intestinal absorption, whereas poorly water soluble compounds with high or low permeability may have high intestinal absorption provided that they have certain molecular characteristics such as a small polar surface or specific topology. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  20. Use of Hansen Solubility Parameters in Fuel Treatment Processes

    Science.gov (United States)

    2014-03-17

    Clearance # Considerations for Rocket Fuel Objective: Utilize liquid/liquid extraction process to improve performance, increase availability, and...1/4)(H1 - H0)2 - (D2 – D0)2 - (1/4) (P2 - P0)2 - (1/4)(H2 - H0)2 ] + RT ln (V1/ V2 ) K = C0,2 / CO,1 Partition coefficient RT ln K = V0( D1...02 – D2-02 ) + RT ln (V1/ V2 ) Di-0 is the distance in “solubility parameter space” between liquid i and impurity 0. For reference, phase 1 = fuel

  1. A single parameter representation of hygroscopic growth and cloud condensation nucleus activity – Part 2: Including solubility

    Directory of Open Access Journals (Sweden)

    M. D. Petters

    2008-10-01

    Full Text Available The ability of a particle to serve as a cloud condensation nucleus in the atmosphere is determined by its size, hygroscopicity and its solubility in water. Usually size and hygroscopicity alone are sufficient to predict CCN activity. Single parameter representations for hygroscopicity have been shown to successfully model complex, multicomponent particles types. Under the assumption of either complete solubility, or complete insolubility of a component, it is not necessary to explicitly include that component's solubility into the single parameter framework. This is not the case if sparingly soluble materials are present. In this work we explicitly account for solubility by modifying the single parameter equations. We demonstrate that sensitivity to the actual value of solubility emerges only in the regime of 2×10−1–5×10−4, where the solubility values are expressed as volume of solute per unit volume of water present in a saturated solution. Compounds that do not fall inside this sparingly soluble envelope can be adequately modeled assuming they are either infinitely soluble in water or completely insoluble.

  2. Rational Design of Molecular Gelator - Solvent Systems Guided by Solubility Parameters

    Science.gov (United States)

    Lan, Yaqi

    Self-assembled architectures, such as molecular gels, have attracted wide interest among chemists, physicists and engineers during the past decade. However, the mechanism behind self-assembly remains largely unknown and no capability exists to predict a priori whether a small molecule will gelate a specific solvent or not. The process of self-assembly, in molecular gels, is intricate and must balance parameters influencing solubility and those contrasting forces that govern epitaxial growth into axially symmetric elongated aggregates. Although the gelator-gelator interactions are of paramount importance in understanding gelation, the solvent-gelator specific (i.e., H-bonding) and nonspecific (dipole-dipole, dipole-induced and instantaneous dipole induced forces) intermolecular interactions are equally important. Solvent properties mediate the self-assembly of molecular gelators into their self-assembled fibrillar networks. Herein, solubility parameters of solvents, ranging from partition coefficients (logP), to Henry's law constants (HLC), to solvatochromic ET(30) parameters, to Kamlet-Taft parameters (beta, alpha and pi), to Hansen solubility parameters (deltap, deltad, deltah), etc., are correlated with the gelation ability of numerous classes of molecular gelators. Advanced solvent clustering techniques have led to the development of a priori tools that can identify the solvents that will be gelled and not gelled by molecular gelators. These tools will greatly aid in the development of novel gelators without solely relying on serendipitous discoveries.

  3. Prediction of aqueous and nonaqueous solubilities of chemicals with environmental interest by UNIFAC

    International Nuclear Information System (INIS)

    Kan, A.T.; Tomson, M.B.

    1995-01-01

    This paper is to investigate the accuracy and precision of predicting the aqueous and non-aqueous solubilities of a vast number of chemicals with significant environmental roles using the latest version of UNIFAC group interaction parameters. A few critical measurements to test specific UNIFAC calculations of nonaqueous solubilities are also reported. The chemicals included in the calculation have aqueous solubilities that span eleven orders of magnitude. Good agreement was observed between the UNIFAC predicted and literature reported aqueous solubilities for eleven groups of compounds. Similarly, UNIFAC successfully predicts the co-solvency of PCB in methanol/water solutions. The error between predicted and literature reported aqueous solubilities was larger for three groups of chemicals: long chain alkanes, phthalates, and chlorinated alkenes. The average absolute error in UNIFAC precision of aqueous solubilities is about 0.5 log units, but the average absolute error is only about 0.2 log units for chlorinated aromatic compounds in organic solvents. The application of UNIFAC approach to predict the fate of hydrocarbons and PCBs in soil column flushing, cosolvency and in natural gas pipeline liquids will be discussed

  4. Importance of critical micellar concentration for the prediction of solubility enhancement in biorelevant media.

    Science.gov (United States)

    Ottaviani, G; Wendelspiess, S; Alvarez-Sánchez, R

    2015-04-06

    This study evaluated if the intrinsic surface properties of compounds are related to the solubility enhancement (SE) typically observed in biorelevant media like fasted state simulated intestinal fluids (FaSSIF). The solubility of 51 chemically diverse compounds was measured in FaSSIF and in phosphate buffer and the surface activity parameters were determined. This study showed that the compound critical micellar concentration parameter (CMC) correlates strongly with the solubility enhancement (SE) observed in FaSSIF compared to phosphate buffer. Thus, the intrinsic capacity of molecules to form micelles is also a determinant for each compound's affinity to the micelles of biorelevant surfactants. CMC correlated better with SE than lipophilicity (logD), especially over the logD range typically covered by drugs (2 < logD < 4). CMC can become useful to guide drug discovery scientists to better diagnose, improve, and predict solubility in biorelevant media, thereby enhancing oral bioavailability of drug candidates.

  5. Linear correlation of interfacial tension at water-solvent interface, solubility of water in organic solvents, and SE* scale parameters

    International Nuclear Information System (INIS)

    Mezhov, E.A.; Khananashvili, N.L.; Shmidt, V.S.

    1988-01-01

    A linear correlation has been established between the solubility of water in water-immiscible organic solvents and the interfacial tension at the water-solvent interface on the one hand and the parameters of the SE* and π* scales for these solvents on the other hand. This allows us, using the known tabulated SE* or π* parameters for each solvent, to predict the values of the interfacial tension and the solubility of water for the corresponding systems. We have shown that the SE* scale allows us to predict these values more accurately than other known solvent scales, since in contrast to other scales it characterizes solvents found in equilibrium with water

  6. The importance of the accuracy of the experimental data for the prediction of solubility

    Directory of Open Access Journals (Sweden)

    SLAVICA ERIĆ

    2010-04-01

    Full Text Available Aqueous solubility is an important factor influencing several aspects of the pharmacokinetic profile of a drug. Numerous publications present different methodologies for the development of reliable computational models for the prediction of solubility from structure. The quality of such models can be significantly affected by the accuracy of the employed experimental solubility data. In this work, the importance of the accuracy of the experimental solubility data used for model training was investigated. Three data sets were used as training sets – data set 1, containing solubility data collected from various literature sources using a few criteria (n = 319, data set 2, created by substituting 28 values from data set 1 with uniformly determined experimental data from one laboratory (n = 319, and data set 3, created by including 56 additional components, for which the solubility was also determined under uniform conditions in the same laboratory, in the data set 2 (n = 375. The selection of the most significant descriptors was performed by the heuristic method, using one-parameter and multi-parameter analysis. The correlations between the most significant descriptors and solubility were established using multi-linear regression analysis (MLR for all three investigated data sets. Notable differences were observed between the equations corresponding to different data sets, suggesting that models updated with new experimental data need to be additionally optimized. It was successfully shown that the inclusion of uniform experimental data consistently leads to an improvement in the correlation coefficients. These findings contribute to an emerging consensus that improving the reliability of solubility prediction requires the inclusion of many diverse compounds for which solubility was measured under standardized conditions in the data set.

  7. Solubility Temperature Dependence Predicted from 2D Structure

    Directory of Open Access Journals (Sweden)

    Alex Avdeef

    2015-12-01

    Full Text Available The objective of the study was to find a computational procedure to normalize solubility data determined at various temperatures (e.g., 10 – 50 oC to values at a “reference” temperature (e.g., 25 °C. A simple procedure was devised to predict enthalpies of solution, ΔHsol, from which the temperature dependence of intrinsic (uncharged form solubility, log S0, could be calculated. As dependent variables, values of ΔHsol at 25 °C were subjected to multiple linear regression (MLR analysis, using melting points (mp and Abraham solvation descriptors. Also, the enthalpy data were subjected to random forest regression (RFR and recursive partition tree (RPT analyses. A total of 626 molecules were examined, drawing on 2040 published solubility values measured at various temperatures, along with 77 direct calori    metric measurements. The three different prediction methods (RFR, RPT, MLR all indicated that the estimated standard deviations in the enthalpy data are 11-15 kJ mol-1, which is concordant with the 10 kJ mol-1 propagation error estimated from solubility measurements (assuming 0.05 log S errors, and consistent with the 7 kJ mol-1 average reproducibility in enthalpy values from interlaboratory replicates. According to the MLR model, higher values of mp, H‑bond acidity, polarizability/dipolarity, and dispersion forces relate to more positive (endothermic enthalpy values. However, molecules that are large and have high H-bond basicity are likely to possess negative (exothermic enthalpies of solution. With log S0 values normalized to 25 oC, it was shown that the interlaboratory average standard deviations in solubility measurement are reduced to 0.06 ‑ 0.17 log unit, with higher errors for the least-soluble druglike molecules. Such improvements in data mining are expected to contribute to more reliable in silico prediction models of solubility for use in drug discovery.

  8. The solubility of solid fission products in carbides and nitrides of uranium and plutonium: Pt.2. Solubility rules based on lattice parameter differences

    International Nuclear Information System (INIS)

    Benedict, U.

    1977-01-01

    The Relative Lattice Parameter Difference (RLPD) is defined for a solute element with respect to cubic carbides and nitrides of uranium and plutonium as solvents. Rules are given for the relationship between the solubility and the RLPD. NaCl type monocarbides with RLPD's from -10.2% to +7.8% are completely miscible with UC and PuC. NaCl type mononitrides with RLPD's from -7.5% to +8.5% are completely miscible with UN and PuN. The solubility in the sesquicarbides increases with decreasing RPLD and becomes complete in Pu 2 C 3 at RLPD = +4%, and in U 2 C 3 at RLPD approximately +1.5%. Solubilities are predicted on the basis of these rules for the cases where no experimental results are available

  9. Can human experts predict solubility better than computers?

    Science.gov (United States)

    Boobier, Samuel; Osbourn, Anne; Mitchell, John B O

    2017-12-13

    In this study, we design and carry out a survey, asking human experts to predict the aqueous solubility of druglike organic compounds. We investigate whether these experts, drawn largely from the pharmaceutical industry and academia, can match or exceed the predictive power of algorithms. Alongside this, we implement 10 typical machine learning algorithms on the same dataset. The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R 2 of 0.706. We would not have predicted the relative success of this particular algorithm in advance. We found that the best individual human predictor generated an almost identical prediction quality with an RMSE of 0.942 log S units and an R 2 of 0.723. The collection of algorithms contained a higher proportion of reasonably good predictors, nine out of ten compared with around half of the humans. We found that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median generated excellent predictivity. While our consensus human predictor achieved very slightly better headline figures on various statistical measures, the difference between it and the consensus machine learning predictor was both small and statistically insignificant. We conclude that human experts can predict the aqueous solubility of druglike molecules essentially equally well as machine learning algorithms. We find that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median is a powerful way of benefitting from the wisdom of crowds.

  10. Predicting Soluble Nickel in Soils Using Soil Properties and Total Nickel.

    Science.gov (United States)

    Zhang, Xiaoqing; Li, Jumei; Wei, Dongpu; Li, Bo; Ma, Yibing

    2015-01-01

    Soil soluble nickel (Ni) concentration is very important for determining soil Ni toxicity. In the present study, the relationships between soil properties, total and soluble Ni concentrations in soils were developed in a wide range of soils with different properties and climate characteristics. The multiple regressions showed that soil pH and total soil Ni concentrations were the most significant parameters in predicting soluble Ni concentrations with the adjusted determination coefficients (Radj2) values of 0.75 and 0.68 for soils spiked with soluble Ni salt and the spiked soils leached with artificial rainwater to mimic field conditions, respectively. However, when the soils were divided into three categories (pH 8), they obtained better predictions with Radj2 values of 0.78-0.90 and 0.79-0.94 for leached and unleached soils, respectively. Meanwhile, the other soil properties, such as amorphous Fe and Al oxides and clay, were also found to be important for determining soluble Ni concentrations, indicating that they were also presented as active adsorbent surfaces. Additionally, the whole soil speciation including bulk soil properties and total soils Ni concentrations were analyzed by mechanistic speciation models WHAM VI and Visual MINTEQ3.0. It was found that WHAM VI provided the best predictions for the soils with pH 8. The Visual MINTEQ3.0 could provide better estimation for pH 8. These results indicated the possibility and applicability of these models to predict soil soluble Ni concentration by soil properties.

  11. Parameter prediction for microwave garnets

    International Nuclear Information System (INIS)

    Ramer, R.

    1996-01-01

    Full text: Linearity of the microwave parameters (resonance linewidth ΔH and effective linewidth ΔH eff ) is demonstrated and their use in the Computer-aided design (CAD)/Computer-aided manufacturing (CAM) of new microwave garnets is proposed. Such an approach would combine a numerical database of microwave data and several computational programs. The model is an applied formulation of the analysis of a wide range of microwave garnets

  12. Soluble L-selectin levels predict survival in sepsis

    DEFF Research Database (Denmark)

    Seidelin, Jakob B; Nielsen, Ole H; Strøm, Jens

    2002-01-01

    To evaluate serum soluble L-selectin as a prognostic factor for survival in patients with sepsis.......To evaluate serum soluble L-selectin as a prognostic factor for survival in patients with sepsis....

  13. Predictions of flavonoid solubility in ionic liquids by COSMO-RS: experimental verification, structural elucidation, and solvation characterization

    DEFF Research Database (Denmark)

    Guo, Zheng; Lue, Bena-Marie; Thomsen, Kaj

    2007-01-01

    Predictions of the solubility of flavonoids in a large variety of ionic liquids (ILs) with over 1800 available structures were examined based on COSMO-RS computation. The results show that the solubilities of flavonoids are strongly anion-dependent. Experimental measurement of the solubilities...... of esculin and rutin in 12 ILs with varying anions and cations show that predicted and experimental results generally have a good agreement. Based on the sound physical basis of COSMO-RS, the solubility changes of flavonoids were quantitatively associated with solvation interactions and structural...... characteristics of ILs. COSMO-RS derived parameters, i.e. misfit, H-bonding and van der Waals interaction energy, are shown to be capable of characterizing the complicated multiple interactions in the IL system effectively. H-bonding interaction is the most dominant interaction for ILs (followed by misfit and van...

  14. Predicting water solubility of congeners: Chloronaphthalenes-A case study

    Energy Technology Data Exchange (ETDEWEB)

    Puzyn, Tomasz, E-mail: puzi@qsar.eu.org [Faculty of Chemistry, University of Gdansk, Sobieskiego 18, 80-952 Gdansk (Poland); Mostrag, Aleksandra; Falandysz, Jerzy [Faculty of Chemistry, University of Gdansk, Sobieskiego 18, 80-952 Gdansk (Poland); Kholod, Yana; Leszczynski, Jerzy [NSF CREST Nanotoxicity Center, Department of Chemistry, Jackson State University, 1325 Lynch St, Jackson, MS 39217-0510 (United States)

    2009-10-30

    Since the important physicochemical data for chloronaphtalenes (PCNs) are still scarce, we have predicted water solubility (log S) of all 75 congeners with the Quantitative Structure-Property Relationship (QSPR) scheme. The values of log S, predicted by the most efficient model, varied from 0.01 to 1660 {mu}g dm{sup -3} (2.85 x 10{sup -11}-1.02 x 10{sup -5} mol dm{sup -3}), depending on the number of chlorine atoms present in the molecule and the substitution pattern. We found that the main factor determining relative differences in solubility between the congeners is the solvent accessible volume related to the cavitation process occurring in the solvent. The results are presented as a case study of QSPR modeling for those Persistent Organic Pollutants (POPs) that exist as families of congeners. By investigating the impact of (i) the way of the molecular descriptors' calculation, (ii) the size of applied database and (iii) chemometric method of modeling (Multiple Linear Regression, MLR, and/or Partial Least Squares regression, PLS) on the quality of the models we proposed general recommendations for dealing with congeners. We found that the combination of the B3LYP functional with 6-311++G(d,p) basis set was the most optimal technique of the molecular descriptors' calculation for congeners when comparing with semi-empirical PM3, ab initio Hartee-Fock (HF), and Moller-Pleset 2 (MP2) method carried out with different-size basis sets. Moreover, the model developed with a larger and more general database that includes chloronaphthalenes, polychlorinated dibezno-p-dioxins, furans and biphenyls predicted the values of log S for PCNs noticeable worse than the model calibrated only on PCNs. In the later case it was possible to obtain satisfactory results by employing even the simplest MLR method and only one molecular descriptor. The values of log S were also calculated with the WSKOWIN and COSMO-RS models as the reference techniques and then compared to our

  15. Predicting water solubility of congeners: Chloronaphthalenes-A case study

    International Nuclear Information System (INIS)

    Puzyn, Tomasz; Mostrag, Aleksandra; Falandysz, Jerzy; Kholod, Yana; Leszczynski, Jerzy

    2009-01-01

    Since the important physicochemical data for chloronaphtalenes (PCNs) are still scarce, we have predicted water solubility (log S) of all 75 congeners with the Quantitative Structure-Property Relationship (QSPR) scheme. The values of log S, predicted by the most efficient model, varied from 0.01 to 1660 μg dm -3 (2.85 x 10 -11 -1.02 x 10 -5 mol dm -3 ), depending on the number of chlorine atoms present in the molecule and the substitution pattern. We found that the main factor determining relative differences in solubility between the congeners is the solvent accessible volume related to the cavitation process occurring in the solvent. The results are presented as a case study of QSPR modeling for those Persistent Organic Pollutants (POPs) that exist as families of congeners. By investigating the impact of (i) the way of the molecular descriptors' calculation, (ii) the size of applied database and (iii) chemometric method of modeling (Multiple Linear Regression, MLR, and/or Partial Least Squares regression, PLS) on the quality of the models we proposed general recommendations for dealing with congeners. We found that the combination of the B3LYP functional with 6-311++G(d,p) basis set was the most optimal technique of the molecular descriptors' calculation for congeners when comparing with semi-empirical PM3, ab initio Hartee-Fock (HF), and Moller-Pleset 2 (MP2) method carried out with different-size basis sets. Moreover, the model developed with a larger and more general database that includes chloronaphthalenes, polychlorinated dibezno-p-dioxins, furans and biphenyls predicted the values of log S for PCNs noticeable worse than the model calibrated only on PCNs. In the later case it was possible to obtain satisfactory results by employing even the simplest MLR method and only one molecular descriptor. The values of log S were also calculated with the WSKOWIN and COSMO-RS models as the reference techniques and then compared to our results.

  16. WHIM-3D-QSPR APPROACH FOR PREDICTING AQUEOUS SOLUBILITY OF CHLORINATED HYDROCARBONS

    Directory of Open Access Journals (Sweden)

    Oman Zuas

    2010-06-01

    Full Text Available The weighted holistic invariant molecular-three dimensional-quantitative structure property relationship (WHIM-3D-QSPR approach has been applied to the study of the aqueous solubility (- log Sw of chlorinated hydrocarbon compounds (CHC's. The obtained QSPR model is predictive and only requires four WHIM-3D descriptors in the calculation. The correlation equation of the model that is based on a training set of 50 CHC's compound has statistical parameters: standard coefficient correlation (R2 = 0.948; cross-validated correlation coefficients (Q2 = 0.935; Standard Error of Validation (SEV = 0.35; and average absolute error (AAE = 0.31. The application of the best model to a testing set of 50 CHC's demonstrates a reliable result with good predictability. Besides, it was possible to construct new model by applying WHIM-3D-QSPR approach without require any experimental physicochemical properties in the calculation of aqueous solubility.   Keywords: WHIM-3D; QSPR; aqueous solubility; - Log Sw, chlorinated hydrocarbons, CHC's

  17. On linear correlation between interfacial tension of water-solvent interface solubility of water in organic solvents and parameters of diluent effect scale

    International Nuclear Information System (INIS)

    Mezhov, Eh.A.; Khananashvili, N.L.; Shmidt, V.S.

    1988-01-01

    Presence of linear correlation between water solubility in nonmiscible with it organic solvents, interfacial tension of water-solvent interface, on the one hand, and solvent effect scale parameters and these solvents π* - on the other hand, is established. It allows, using certain tabular parameters of solvent effect or each solvent π*, to predict values of interfacial tension and water solubility for corresponding systems. It is shown, that solvent effect scale allows to predict values more accurately, than other known solvent scales, as it in contrast to other scales characterizes solvents, which are in equilibrium with water

  18. Predicting pear (cv. Clara Frijs) dry matter and soluble solids content with near infrared spectroscopy

    DEFF Research Database (Denmark)

    Travers, Sylvia; Bertelsen, Marianne; Petersen, Karen

    2014-01-01

    Regression models for predicting preharvest dry matter (DM) and soluble solids content (SSC), based on two spectral ranges (680-1000 nm and 1100-2350 nm), were compared. Models based on longer NIR spectra were more successful for both parameters (DM/SSC: R2 = 0.78-0.84; RMECV = 0.78/0.44; LVs = 6....../7). SSC prediction was better than expected considering the presence of starch in fruit. Generally poor SSC prediction in the presence of starch could be related to the inability of models to distinguish between forms of carbohydrate. Variable selection and regression coefficients highlighted...... fruit. Further research is needed to qualify and build on the results presented here....

  19. Prediction of pH-dependent aqueous solubility of druglike molecules

    DEFF Research Database (Denmark)

    Hansen, Niclas Tue; Kouskoumvekaki, Irene; Jørgensen, Flemming Steen

    2012-01-01

    In the present work, the Henderson-Hasselbalch (HH) equation has been employed for the development of a tool for the prediction of pH-dependent aqueous solubility of drugs and drug candidates. A new prediction method for the intrinsic solubility was developed, based on artificial neural networks...

  20. Steel corrosion products solubility under conditions simulating various water chemistry parameters in power plants

    International Nuclear Information System (INIS)

    Slobodov, A.A.; Kritskij, V.G.; Zarembo, V.I.; Puchkov, L.V.

    1988-01-01

    To simulate construction material corrosion product mass transfer model in power plant circuits calculation of iron oxide and hydroxide solubility, depending on water chemistry parameters: temperature, pH-value, content of dissolved in water hydrogen and oxygen, is carried out

  1. Simulated rat intestinal fluid improves oral exposure prediction for poorly soluble compounds over a wide dose range

    Directory of Open Access Journals (Sweden)

    Joerg Berghausen

    2016-03-01

    Full Text Available Solubility can be the absorption limiting factor for drug candidates and is therefore a very important input parameter for oral exposure prediction of compounds with limited solubility. Biorelevant media of the fasted and fed state have been published for humans, as well as for dogs in the fasted state. In a drug discovery environment, rodents are the most common animal model to assess the oral exposure of drug candidates. In this study a rat simulated intestinal fluid (rSIF is proposed as a more physiologically relevant media to describe drug solubility in rats. Equilibrium solubility in this medium was tested as input parameter for physiologically-based pharmacokinetics (PBPK simulations of oral pharmacokinetics in the rat. Simulations were compared to those obtained using other solubility values as input parameters, like buffer at pH 6.8, human simulated intestinal fluid and a comprehensive dissolution assay based on rSIF. Our study on nine different compounds demonstrates that the incorporation of rSIF equilibrium solubility values into PBPK models of oral drug exposure can significantly improve the reliability of simulations in rats for doses up to 300 mg/kg compared to other media. The comprehensive dissolution assay may help to improve further simulation outcome, but the greater experimental effort as compared to equilibrium solubility may limit its use in a drug discovery environment. Overall, PBPK simulations based on solubility in the proposed rSIF medium can improve prioritizing compounds in drug discovery as well as planning dose escalation studies, e.g. during toxicological investigations.

  2. Methods for calculation of engineering parameters for gas separation. [vapor pressure and solubility of gases in organic liquids

    Science.gov (United States)

    Lawson, D. D.

    1979-01-01

    A group additivity method is generated which allows estimation, from the structural formulas alone, of the energy of vaporization and the molar volume at 25 C of many nonpolar organic liquids. Using these two parameters and appropriate thermodynamic relations, the vapor pressure of the liquid phase and the solubility of various gases in nonpolar organic liquids are predicted. It is also possible to use the data to evaluate organic and some inorganic liquids for use in gas separation stages or liquids as heat exchange fluids in prospective thermochemical cycles for hydrogen production.

  3. Comparative Study on Dispersion and Interfacial Properties of Single Walled Carbon Nanotube/Polymer Composites Using Hansen Solubility Parameters

    DEFF Research Database (Denmark)

    Ma, Jing; Larsen, Mikael

    2013-01-01

    fabricated by solution blending 1 wt % SWNTs with various modification (nonmodified, nitric acid functionalized, and amine functionalized SWNTs) and three kinds of polymeric materials (polycarbonate, polyvinylidene fluoride, and epoxy). Chemical compatibilities between SWNTs and solvents or polymers...... are calculated by the Hansen solubility parameters (HSP) method. The dispersion of the SWNTs in solvents is evaluated by dynamic light scattering. The dispersion of SWNTs in polymers evaluated by a light optical microscope (LOM) generally agrees with the HSP prediction. The strain transfer from the matrix...

  4. Estimation of the solubility parameters of model plant surfaces and agrochemicals: a valuable tool for understanding plant surface interactions.

    Science.gov (United States)

    Khayet, Mohamed; Fernández, Victoria

    2012-11-14

    Most aerial plant parts are covered with a hydrophobic lipid-rich cuticle, which is the interface between the plant organs and the surrounding environment. Plant surfaces may have a high degree of hydrophobicity because of the combined effects of surface chemistry and roughness. The physical and chemical complexity of the plant cuticle limits the development of models that explain its internal structure and interactions with surface-applied agrochemicals. In this article we introduce a thermodynamic method for estimating the solubilities of model plant surface constituents and relating them to the effects of agrochemicals. Following the van Krevelen and Hoftyzer method, we calculated the solubility parameters of three model plant species and eight compounds that differ in hydrophobicity and polarity. In addition, intact tissues were examined by scanning electron microscopy and the surface free energy, polarity, solubility parameter and work of adhesion of each were calculated from contact angle measurements of three liquids with different polarities. By comparing the affinities between plant surface constituents and agrochemicals derived from (a) theoretical calculations and (b) contact angle measurements we were able to distinguish the physical effect of surface roughness from the effect of the chemical nature of the epicuticular waxes. A solubility parameter model for plant surfaces is proposed on the basis of an increasing gradient from the cuticular surface towards the underlying cell wall. The procedure enabled us to predict the interactions among agrochemicals, plant surfaces, and cuticular and cell wall components, and promises to be a useful tool for improving our understanding of biological surface interactions.

  5. The determination of solubility parameters of solvents and polymers by means of correlations with other physical quantities

    NARCIS (Netherlands)

    Koenhen, D.M.; Smolders, C.A.

    1975-01-01

    Correlations of solvent solubility parameters with molar attraction constants and with properties like surface tension, dipole moment, and index of refraction have been explored. From relations found to be valid for solvents, it is possible to calculate the solubility parameters for polymers. A

  6. Le Chatelier's Principle and the Prediction Temperature on Solubilities.

    Science.gov (United States)

    Fernandez-Prini, R.

    1982-01-01

    Discusses Le Chatelier's Principle from a thermodynamic perspective and applies it to the effect of temperature on the solubility of gases in liquids. Rationale of this discussion is to evaluate data in a previous article claimed to be contradictory to the Principle. (Author/JN)

  7. Limitations of polyethylene glycol-induced precipitation as predictive tool for protein solubility during formulation development.

    Science.gov (United States)

    Hofmann, Melanie; Winzer, Matthias; Weber, Christian; Gieseler, Henning

    2018-05-01

    Polyethylene glycol (PEG)-induced protein precipitation is often used to extrapolate apparent protein solubility at specific formulation compositions. The procedure was used for several fields of application such as protein crystal growth but also protein formulation development. Nevertheless, most studies focused on applicability in protein crystal growth. In contrast, this study focuses on applicability of PEG-induced precipitation during high-concentration protein formulation development. In this study, solubility of three different model proteins was investigated over a broad range of pH. Solubility values predicted by PEG-induced precipitation were compared to real solubility behaviour determined by either turbidity or content measurements. Predicted solubility by PEG-induced precipitation was confirmed for an Fc fusion protein and a monoclonal antibody. In contrast, PEG-induced precipitation failed to predict solubility of a single-domain antibody construct. Applicability of PEG-induced precipitation as indicator of protein solubility during formulation development was found to be not valid for one of three model molecules. Under certain conditions, PEG-induced protein precipitation is not valid for prediction of real protein solubility behaviour. The procedure should be used carefully as tool for formulation development, and the results obtained should be validated by additional investigations. © 2017 Royal Pharmaceutical Society.

  8. Predicting the equilibrium solubility of solid polycyclic aromatic hydrocarbons and dibenzothiophene using a combination of MOSCED plus molecular simulation or electronic structure calculations

    Science.gov (United States)

    Phifer, Jeremy R.; Cox, Courtney E.; da Silva, Larissa Ferreira; Nogueira, Gabriel Gonçalves; Barbosa, Ana Karolyne Pereira; Ley, Ryan T.; Bozada, Samantha M.; O'Loughlin, Elizabeth J.; Paluch, Andrew S.

    2017-06-01

    Methods to predict the equilibrium solubility of non-electrolyte solids are important for the design of novel separation processes. Here we demonstrate how conventional molecular simulation free energy calculations or electronic structure calculations in a continuum solvent, here SMD or SM8, can be used to predict parameters for the MOdified Separation of Cohesive Energy Density (MOSCED) method. The method is applied to the solutes naphthalene, anthracene, phenanthrene, pyrene and dibenzothiophene, compounds of interested to the petroleum industry and for environmental remediation. Adopting the melting point temperature and enthalpy of fusion of these compounds from experiment, we are able to predict equilibrium solubilities. Comparing to a total of 422 non-aqueous and 193 aqueous experimental solubilities, we find the proposed method is able to well correlate the data. The use of MOSCED is additionally advantageous as it is a solubility parameter-based method useful for intuitive solvent selection and formulation.

  9. Effect of solubility parameter of monomers on electron beam induced graft-polymerization onto polyethylene films

    International Nuclear Information System (INIS)

    Mori, Koji; Koshiishi, Kenji; Masuhara, Ken-ichi

    1991-01-01

    Electron beam induced graft-polymerization by the mutual irradiation technique of monomers with different solubility parameters δ onto low density polyethylene films (LDPE) and high density polyethylene films (HDPE) were investigated at high dose rates (25 Mrad per second). Graft-polymerization mechanisms were discussed on the basis of grafting rates, surface tensions, atomic ratios of surface by XPS, and SEM images of the grafted films. Grafting rates decreased with increasing δ of monomers, and grafting rates onto LDPE were larger than those onto HDPE. Graft chain contents on surface, which were evaluated in terms of surface tensions and atomic ratios of the surface, increased with increasing δ of monomers, and graft chain contents on surface of HDPE were higher than those of LDPE. It is assumed that mutual solubility of PE and monomers, i.e., infiltration of monomers into PE during graft-polymerization influence grafting rates and graft sites in films. In case of high mutual solubility, grafting rates were large and graft sites spread from the surface into bulk. On the other hand, in case of low mutual solubility, grafting rates were small and graft sites localized on the surface of films. (author)

  10. Effect of solubility parameter of solvents on electron beam induced graft-polymerization onto polyethylene films

    International Nuclear Information System (INIS)

    Mori, Koji; Koshiishi, Kenji; Masuhara, Ken-ichi

    1992-01-01

    Electron beam induced graft-polymerization by the mutual irradiation technique of methyl methacrylate (MMA) and methacrylic acid (MAAc) blended with solvents, which have different solubility parameters δ, onto high density polyethylene films (PE) were investigated at high dose rates (25 Mrad per second). Graft-polymerization mechanisms were discussed on the basis of grafting rates, surface tensions, atomic rations on the surface by XPS, and SEM images of the grafted films. Grafting rates decreased with increasing δ of solvents, and grafting rates for MMA were larger than those for MAAc. Graft chain contents on the surface, which were evaluated in terms of surface tensions and atomic ratios on the surface, increased with increasing δ of solvents, and graft chain contents on the surface of MAAc grafted PE were higher than those of MMA grafted PE. It is assumed that mutual solubility of PE and solvents (monomer solutions), i.e., infiltration of monomer solutions into PE during graft-polymerization, influenced grafting rates and graft sites in films. In case of high mutual solubility, grafting rates were large and graft sites spread from the surface into bulk. On the other hand, in case of low mutual solubility, grafting rates were small and graft sites localized on the surface of films. (author)

  11. Prediction of the solubility of selected pharmaceuticals in water and alcohols with a group contribution method

    International Nuclear Information System (INIS)

    Pelczarska, Aleksandra; Ramjugernath, Deresh; Rarey, Jurgen; Domańska, Urszula

    2013-01-01

    Highlights: ► The prediction of solubility of pharmaceuticals in water and alcohols was presented. ► Improved group contribution method UNIFAC was proposed for 42 binary mixtures. ► Infinite activity coefficients were used in a model. ► A semi-predictive model with one experimental point was proposed. ► This model qualitatively describes the temperature dependency of Pharms. -- Abstract: An improved group contribution approach using activity coefficients at infinite dilution, which has been proposed by our group, was used for the prediction of the solubility of selected pharmaceuticals in water and alcohols [B. Moller, Activity of complex multifunctional organic compounds in common solvents, PhD Thesis, Chemical Engineering, University of KwaZulu-Natal, 2009]. The solubility of 16 different pharmaceuticals in water, ethanol and octan-1-ol was predicted over a fairly wide range of temperature with this group contribution model. The predicted values, along with values computed with the Schroeder-van Laar equation, are compared to experimental results published by us previously for 42 binary mixtures. The predicted solubility values were lower than those from the experiments for most of the mixtures. In order to improve the prediction method, a semi-predictive calculation using one experimental solubility value was implemented. This one point prediction has given acceptable results when comparison is made to experimental values

  12. Optimal design criteria - prediction vs. parameter estimation

    Science.gov (United States)

    Waldl, Helmut

    2014-05-01

    G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

  13. Multimodel Predictive System for Carbon Dioxide Solubility in Saline Formation Waters

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Zan; Small, Mitchell J; Karamalidis, Athanasios K

    2013-02-05

    The prediction of carbon dioxide solubility in brine at conditions relevant to carbon sequestration (i.e., high temperature, pressure, and salt concentration (T-P-X)) is crucial when this technology is applied. Eleven mathematical models for predicting CO{sub 2} solubility in brine are compared and considered for inclusion in a multimodel predictive system. Model goodness of fit is evaluated over the temperature range 304–433 K, pressure range 74–500 bar, and salt concentration range 0–7 m (NaCl equivalent), using 173 published CO{sub 2} solubility measurements, particularly selected for those conditions. The performance of each model is assessed using various statistical methods, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Different models emerge as best fits for different subranges of the input conditions. A classification tree is generated using machine learning methods to predict the best-performing model under different T-P-X subranges, allowing development of a multimodel predictive system (MMoPS) that selects and applies the model expected to yield the most accurate CO{sub 2} solubility prediction. Statistical analysis of the MMoPS predictions, including a stratified 5-fold cross validation, shows that MMoPS outperforms each individual model and increases the overall accuracy of CO{sub 2} solubility prediction across the range of T-P-X conditions likely to be encountered in carbon sequestration applications.

  14. Prediction of solubilities for ginger bioactive compounds in hot water by the COSMO-RS method

    Science.gov (United States)

    Zaimah Syed Jaapar, Syaripah; Azian Morad, Noor; Iwai, Yoshio

    2013-04-01

    The solubilities in water of four main ginger bioactives, 6-gingerol, 6-shogaol, 8-gingerol and 10-gingerol, were predicted using a conductor-like screening model for real solvent (COSMO-RS) calculations. This study was conducted since no experimental data are available for ginger bioactive solubilities in hot water. The σ-profiles of these selected molecules were calculated using Gaussian software and the solubilities were calculated using the COSMO-RS method. The solubilities of these ginger bioactives were calculated at 50 to 200 °C. In order to validate the accuracy of the COSMO-RS method, the solubilities of five hydrocarbon molecules were calculated using the COSMO-RS method and compared with the experimental data in the literature. The selected hydrocarbon molecules were 3-pentanone, 1-hexanol, benzene, 3-methylphenol and 2-hydroxy-5-methylbenzaldehyde. The calculated results of the hydrocarbon molecules are in good agreement with the data in the literature. These results confirm that the solubilities of ginger bioactives can be predicted using the COSMO-RS method. The solubilities of the ginger bioactives are lower than 0.0001 at temperatures lower than 130 °C. At 130 to 200 °C, the solubilities increase dramatically with the highest being 6-shogaol, which is 0.00037 mole fraction, and the lowest is 10-gingerol, which is 0.000039 mole fraction at 200 °C.

  15. Prediction of solubilities for ginger bioactive compounds in hot water by the COSMO-RS method

    International Nuclear Information System (INIS)

    Jaapar, Syaripah Zaimah Syed; Iwai, Yoshio; Morad, Noor Azian

    2013-01-01

    The solubilities in water of four main ginger bioactives, 6-gingerol, 6-shogaol, 8-gingerol and 10-gingerol, were predicted using a conductor-like screening model for real solvent (COSMO-RS) calculations. This study was conducted since no experimental data are available for ginger bioactive solubilities in hot water. The σ-profiles of these selected molecules were calculated using Gaussian software and the solubilities were calculated using the COSMO-RS method. The solubilities of these ginger bioactives were calculated at 50 to 200 °C. In order to validate the accuracy of the COSMO-RS method, the solubilities of five hydrocarbon molecules were calculated using the COSMO-RS method and compared with the experimental data in the literature. The selected hydrocarbon molecules were 3-pentanone, 1-hexanol, benzene, 3-methylphenol and 2-hydroxy-5-methylbenzaldehyde. The calculated results of the hydrocarbon molecules are in good agreement with the data in the literature. These results confirm that the solubilities of ginger bioactives can be predicted using the COSMO-RS method. The solubilities of the ginger bioactives are lower than 0.0001 at temperatures lower than 130 °C. At 130 to 200 °C, the solubilities increase dramatically with the highest being 6-shogaol, which is 0.00037 mole fraction, and the lowest is 10-gingerol, which is 0.000039 mole fraction at 200 °C.

  16. Use of tritium to predict soluble pollutants transport in Ebro River waters (Spain).

    Science.gov (United States)

    Pujol, L; Sanchez-Cabeza, J A

    2000-05-01

    The Ebro River, in Northeast Spain, discharges into the Mediterranean Sea after flowing through several large cities and agricultural, mining and industrial areas. The Ascó nuclear power plant (NPP) is located in its lower section and comprises two pressurised water reactor units, from which low-level liquid radioactive waste is released to river waters under authority control. Tritium routinely released by the NPP was used as a radiotracer to determine the longitudinal dispersion coefficient and velocity of the river waters. Several field experiments, in co-ordination with the NPP, were carried out during 1991 and 1992. During each field experiment, the flow rate was kept constant by dams located upstream from the NPP. After each tritium release, water was sampled downstream at periodic intervals over several hours and tritium was measured with a low-background liquid scintillation counter. Velocity and dispersion coefficient were determined in river waters for several river discharges using an analytical, box-type and numerical approach to solve the one-dimensional advection-diffusion equation. The set of calibrated parameters was used to predict the displacement and dispersion of soluble pollutants in river waters. Velocity was determined as a function of river discharge and river slope, and dispersion coefficient was determined as a function of distance. Finally, sensitivity of the model predictions was studied and uncertainties of the fitted parameters were estimated.

  17. Soluble L-selectin levels predict survival in sepsis

    DEFF Research Database (Denmark)

    Seidelin, Jakob B; Nielsen, Ole H; Strøm, Jens

    2002-01-01

    OBJECTIVE: To evaluate serum soluble L-selectin as a prognostic factor for survival in patients with sepsis. DESIGN: A prospective study of mortality in patients with sepsis whose serum levels of sL-selectin were measured on admission to an intensive care unit (ICU) and 4 days later. Follow-up data......, and 3 and 12 months after admission. Serum sL-selectin levels were significantly lower in the patients than in the controls. Sepsis nonsurvivors had significantly lower levels than survivors. Efficiency analysis and receiver operation characteristics showed that the ideal cutoff point for s......L-selectin as a test for sepsis survival was 470 ng/ml. The accumulated mortality in patients with subnormal sL-selectin levels on admission was significantly increased. No correlation was found between clinical or paraclinical markers, including SAPS II and sL-selectin, and no relationship to the microbial diagnosis...

  18. Experimental determination of solubility parameters of oils as a function of pressure

    DEFF Research Database (Denmark)

    Verdier, Sylvain Charles Roland; Duong, Diep; Andersen, Simon Ivar

    2005-01-01

    In this work, the solubility parameter of dead and live crude oils was measured at 303.15 K and up to 300 bar, using the internal pressure approach. An indirect technique was chosen, using thermal expansivities (determined from microcalorimetric measurements) and isothermal compressibilities (cal...... are measured and given as input. Therefore, a more appropriate characterization method should give better results....... (calculated from density measurements). This method was tested on seven pure compounds, and the deviation with literature data is method based on the refractive index was used to examine the validity of the results for the oils, and a deviation of ... parameter was also calculated from two cubic equations of state and compared to experimental results. In this case, the deviations are larger (up to 6.5 MPa1/2), whereas this approach gives accurate results for pure compounds. This might be due to the characterization procedure, because the volumes...

  19. [Soluble interleukin 2 receptor as activity parameter in serum of systemic and discoid lupus erythematosus].

    Science.gov (United States)

    Blum, C; Zillikens, D; Tony, H P; Hartmann, A A; Burg, G

    1993-05-01

    The evaluation of disease activity in systemic lupus erythematosus (SLE) is important for selection of the appropriate therapeutic regimen. In addition to the clinical picture, various laboratory parameters are taken into account. However, no validated criteria for the evaluation of the disease activity in SLE have yet been established. Recently, serum levels of soluble interleukin-2 receptor (sIL-2R) have been proposed as a potential parameter for disease activity in SLE. However, the studies reported on this subject so far have focused mainly on certain subsets of the disease, and the evaluation of the disease activity was based on a very limited number of parameters. In the present study, we determined serum levels of sIL-2R in 23 patients with SLE and 30 patients with discoid LE (DLE). Evaluation of disease activity in SLE was based on a comprehensive scale which considered numerous clinical signs and laboratory parameters. In SLE, serum levels of sIL-2R showed a better correlation with disease activity than all the other parameters investigated, including proteinuria, erythrocyte sedimentation rate, serum globulin concentration, titre of antibodies against double-stranded DNA, serum albumin concentration, serum complement levels and white blood cell count. For the first time, we report on elevated serum levels of sIL-2R in DLE, which also correlated with disease activity.

  20. PON-Sol: prediction of effects of amino acid substitutions on protein solubility.

    Science.gov (United States)

    Yang, Yang; Niroula, Abhishek; Shen, Bairong; Vihinen, Mauno

    2016-07-01

    Solubility is one of the fundamental protein properties. It is of great interest because of its relevance to protein expression. Reduced solubility and protein aggregation are also associated with many diseases. We collected from literature the largest experimentally verified solubility affecting amino acid substitution (AAS) dataset and used it to train a predictor called PON-Sol. The predictor can distinguish both solubility decreasing and increasing variants from those not affecting solubility. PON-Sol has normalized correct prediction ratio of 0.491 on cross-validation and 0.432 for independent test set. The performance of the method was compared both to solubility and aggregation predictors and found to be superior. PON-Sol can be used for the prediction of effects of disease-related substitutions, effects on heterologous recombinant protein expression and enhanced crystallizability. One application is to investigate effects of all possible AASs in a protein to aid protein engineering. PON-Sol is freely available at http://structure.bmc.lu.se/PON-Sol The training and test data are available at http://structure.bmc.lu.se/VariBench/ponsol.php mauno.vihinen@med.lu.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Predicting trace metal solubility and fractionation in Urban soils from isotopic exchangeability

    International Nuclear Information System (INIS)

    Mao, L.C.; Young, S.D.; Tye, A.M.; Bailey, E.H.

    2017-01-01

    Metal-salt amended soils (MA, n = 23), and historically-contaminated urban soils from two English cities (Urban, n = 50), were investigated to assess the effects of soil properties and contaminant source on metal lability and solubility. A stable isotope dilution method, with and without a resin purification step, was used to measure the lability of Cd, Cu, Ni, Pb and Zn. For all five metals in MA soils, lability (%E-values) could be reasonably well predicted from soil pH value with a simple logistic equation. However, there was evidence of continuing time-dependent fixation of Cd and Zn in the MA soils, following more than a decade of storage under air-dried conditions, mainly in high pH soils. All five metals in MA soils remained much more labile than in Urban soils, strongly indicating an effect of contaminant source on metal lability in the latter. Metal solubility was predicted for both sets of soil by the geochemical speciation model WHAM-VII, using E-value as an input variable. For soils with low metal solution concentrations, over-estimation of Cd, Ni and Zn solubility was associated with binding to the Fe oxide fraction while accurate prediction of Cu solubility was dependent on humic acid content. Lead solubility was most poorly described, especially in the Urban soils. Generally, slightly poorer estimation of metal solubility was observed in Urban soils, possibly due to a greater incidence of high pH values. The use of isotopically exchangeable metal to predict solubility is appropriate both for historically contaminated soils and where amendment with soluble forms of metal is used, as in toxicological trials. However, the major limitation to predicting solubility may lie with the accuracy of model input variables such as humic acid and Fe oxide contents where there is often a reliance on relatively crude analytical estimations of these variables. Trace metal reactivity in urban soils depends on both soil properties and the original source material

  2. Solubility of Methane, Ethane, and Propane in Pure Water Using New Binary Interaction Parameters

    Directory of Open Access Journals (Sweden)

    Masoud Behrouz

    2015-07-01

    Full Text Available Solubility of hydrocarbons in water is important due to ecological concerns and new restrictions on the existence of organic pollutants in water streams. Also, the creation of a thermodynamic model has required an advanced study of the phase equilibrium between water (as a basis for the widest spread muds and amines and gas hydrocarbon phases in wide temperature and pressure ranges. Therefore, it is of great interest to develop semi-empirical correlations, charts, or thermodynamic models for estimating the solubility of hydrocarbons in liquid water. In this work, a thermodynamic model based on Mathias modification of Sova-Redlich-Kwong (SRK equation of state is suggested using classical mixing rules with new binary interaction parameters which were used for two-component systems of hydrocarbons and water. Finally, the model results and their deviations in comparison with the experimental data are presented; these deviations were equal to 5.27, 6.06, and 4.1% for methane, ethane, and propane respectively.

  3. Effect of electrical stunning frequency on meat quality, plasma parameters, and protein solubility of broilers.

    Science.gov (United States)

    Huang, J C; Yang, J; Zhang, B H; Huang, M; Chen, K J; Xu, X L; Zhou, G H

    2017-08-01

    This study was designed to compare the effects of different stunning frequencies of pulsed direct current on meat quality of broilers. This was achieved by investigating plasma parameters, blood loss, carcass damage, meat water-holding capacity, meat color, meat shear value, muscle pH, and protein solubility. A total of 400 broilers was divided into 5 treatment groups and stunned with 500, 600, 700, 800, and 900 Hz at 15 V for 10 seconds. Blood samples were collected immediately after cutting the neck. Pectoralis major muscles were removed from the carcass after chilling and placed in ice. Breast muscle pH and meat color were determined at both 2 and 24 h postmortem. Drip loss, cooking loss, pressing loss, and cooked breast meat-shear values were determined at 24 h postmortem. Treatment at 500 and 900 Hz significantly increased (P meat color were not affected by stunning frequency. In the 500 and 900 Hz groups, the protein solubility and shear force values were significantly lower (P < 0.05) and drip loss was significantly higher (P < 0.05) than in the 700 Hz group. This study indicates that the waveform of the pulsed direct current is acceptable for stunning broilers at a stunning frequency of 700 Hz. © 2017 Poultry Science Association Inc.

  4. Thermodynamic models to predict gas-liquid solubilities in the methanol synthesis, the methanol-higher alcohol synthesis, and the Fischer-Tropsch synthesis via gas-slurry processes

    NARCIS (Netherlands)

    Breman, B.B; Beenackers, A.A C M

    1996-01-01

    Various thermodynamic models were tested concerning their applicability to predict gas-liquid solubilities, relevant for synthesis gas conversion to methanol, higher alcohols, and hydrocarbons via gas-slurry processes. Without any parameter optimization the group contribution equation of state

  5. Model evaluation for the prediction of solubility of active pharmaceutical ingredients (APIs to guide solid–liquid separator design

    Directory of Open Access Journals (Sweden)

    Kuveneshan Moodley

    2018-05-01

    Full Text Available The assumptions and models for solubility modelling or prediction in systems using non-polar solvents, or water and complex triterpene and other active pharmaceutical ingredients as solutes aren't well studied. Furthermore, the assumptions concerning heat capacity effects (negligibility, experimental values or approximations are explored, using non-polar solvents (benzene, or water as reference solvents, for systems with solute melting points in the range of 306–528 K and molecular weights in the range of 90–442 g/mol. New empirical estimation methods for the ΔfusCpi of APIs are presented which correlate the solute molecular masses and van der Waals surface areas with ΔfusCpi. Separate empirical parameters were required for oxygenated and non-oxygenated solutes. Subsequently, the predictive capabilities of the various approaches to solubility modelling for complex pharmaceuticals, for which data is limited, are analysed. The solute selection is based on a principal component analysis, considering molecular weights, fusion temperatures, and solubilities in a non-polar solvent, alcohol, and water, where data was available. New NRTL-SAC parameters were determined for selected steroids, by regression. The original UNIFAC, modified UNIFAC (Dortmund, COSMO-RS (OL, and COSMO-SAC activity coefficient predictions are then conducted, based on the availability of group constants and sigma profiles. These are undertaken to assess the predictive capabilities of these models when each assumption concerning heat capacity is employed. The predictive qualities of the models are assessed, based on the mean square deviation and provide guidelines for model selection, and assumptions concerning phase equilibrium, when designing solid–liquid separators for the pharmaceutical industry on process simulation software. The most suitable assumption regarding ΔfusCpi was found to be system specific, with modified UNIFAC (Dortmund performing well in benzene as

  6. Solubility of water in fluorocarbons: Experimental and COSMO-RS prediction results

    International Nuclear Information System (INIS)

    Freire, Mara G.; Carvalho, Pedro J.; Santos, Luis M.N.B.F.; Gomes, Ligia R.; Marrucho, Isabel M.; Coutinho, Joao A.P.

    2010-01-01

    This work aims at providing experimental and theoretical information about the water-perfluorocarbon molecular interactions. For that purpose, experimental solubility results for water in cyclic and aromatic perfluorocarbons (PFCs), over the temperature range between (288.15 and 318.15) K, and at atmospheric pressure, were obtained and are presented. From the experimental solubility dependence on temperature, the partial molar solution and solvation thermodynamic functions such as Gibbs free energy, enthalpy and entropy were determined and are discussed. The process of dissolution of water in PFCs is shown to be spontaneous for cyclic and aromatic compounds. It is demonstrated that the interactions between the non-aromatic PFCs and water are negligible while those between aromatic PFCs and water are favourable. The COSMO-RS predictive capability was explored for the description of the water solubility in PFCs and others substituted fluorocompounds. The COSMO-RS is shown to be a useful model to provide reasonable predictions of the solubility values, as well as to describe their temperature and structural modifications dependence. Moreover, the molar Gibbs free energy and molar enthalpy of solution of water are predicted remarkably well by COSMO-RS while the main deviations appear for the prediction of the molar entropy of solution.

  7. Hansen solubility parameters (HSP) for prescreening formulation of solid lipid nanoparticles (SLN): in vitro testing of curcumin-loaded SLN in MCF-7 and BT-474 cell lines.

    Science.gov (United States)

    Doktorovova, Slavomira; Souto, Eliana B; Silva, Amélia M

    2018-01-01

    Curcumin, a phenolic compound from turmeric rhizome (Curcuma longa), has many interesting pharmacological effects, but shows very low aqueous solubility. Consequently, several drug delivery systems based on polymeric and lipid raw materials have been proposed to increase its bioavailability. Solid lipid nanoparticles (SLN), consisting of solid lipid matrix and a surfactant layer can load poorly water-soluble drugs, such as curcumin, deliver them at defined rates and enhance their intracellular uptake. In the present work, we demonstrate that, despite the drug's affinity to lipids frequently used in SLN production, the curcumin amount loaded in most SLN formulations may be too low to exhibit anticancer properties. The predictive curcumin solubility in solid lipids has been thoroughly analyzed by Hansen solubility parameters, in parallel with the lipid-screening solubility tests for a range of selected lipids. We identified the most suitable lipid materials for curcumin-loaded SLN, producing physicochemically stable particles with high encapsulation efficiency (>90%). Loading capacity of curcumin in SLN allowed preventing the cellular damage caused by cationic SLN on MCF-7 and BT-474 cells but was not sufficient to exhibit drug's anticancer properties. But curcumin-loaded SLN exhibited antioxidant properties, substantiating the conclusions that curcumin's effect in cancer cells is highly dose dependent.

  8. Measurement and prediction of the solubility of acid gases in monoethanolamine solutions at low partial pressures

    Energy Technology Data Exchange (ETDEWEB)

    Nasir, P; Mather, A E

    1977-12-01

    An apparatus for the determination of the solubility of hydrogen sulfide, carbon dioxide, and their mixtures in ethanolamine solutions at low pressures is described. With this apparatus, the solubility of H/sub 2/S, CO/sub 2/ and their mixtures in aqueous solutions of monoethanolamine was measured at partial pressures between 0.001 kPa and 9 kPa at temperatures of 80 and 100/sup 0/C. The results for the mixture were compared with two methods of prediction based on a thermodynamic model. 6 figures, 4 tables.

  9. Comparative Study of Different Methods for the Prediction of Drug-Polymer Solubility

    DEFF Research Database (Denmark)

    Knopp, Matthias Manne; Tajber, Lidia; Tian, Yiwei

    2015-01-01

    monomer weight ratios. The drug–polymer solubility at 25 °C was predicted using the Flory–Huggins model, from data obtained at elevated temperature using thermal analysis methods based on the recrystallization of a supersaturated amorphous solid dispersion and two variations of the melting point......, which suggests that this method can be used as an initial screening tool if a liquid analogue is available. The learnings of this important comparative study provided general guidance for the selection of the most suitable method(s) for the screening of drug–polymer solubility....

  10. Measurement and ANN prediction of pH-dependent solubility of nitrogen-heterocyclic compounds.

    Science.gov (United States)

    Sun, Feifei; Yu, Qingni; Zhu, Jingke; Lei, Lecheng; Li, Zhongjian; Zhang, Xingwang

    2015-09-01

    Based on the solubility of 25 nitrogen-heterocyclic compounds (NHCs) measured by saturation shake-flask method, artificial neural network (ANN) was employed to the study of the quantitative relationship between the structure and pH-dependent solubility of NHCs. With genetic algorithm-multivariate linear regression (GA-MLR) approach, five out of the 1497 molecular descriptors computed by Dragon software were selected to describe the molecular structures of NHCs. Using the five selected molecular descriptors as well as pH and the partial charge on the nitrogen atom of NHCs (QN) as inputs of ANN, a quantitative structure-property relationship (QSPR) model without using Henderson-Hasselbalch (HH) equation was successfully developed to predict the aqueous solubility of NHCs in different pH water solutions. The prediction model performed well on the 25 model NHCs with an absolute average relative deviation (AARD) of 5.9%, while HH approach gave an AARD of 36.9% for the same model NHCs. It was found that QN played a very important role in the description of NHCs and, with QN, ANN became a potential tool for the prediction of pH-dependent solubility of NHCs. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Use Of Stream Analyzer For Solubility Predictions Of Selected Hanford Tank Waste

    International Nuclear Information System (INIS)

    Pierson, Kayla; Belsher, Jeremy; Ho, Quynh-dao

    2012-01-01

    The Hanford Tank Waste Operations Simulator (HTWOS) models the mission to manage, retrieve, treat and vitrify Hanford waste for long-term storage and disposal. HTWOS is a dynamic, flowsheet, mass balance model of waste retrieval and treatment activities. It is used to evaluate the impact of changes on long-term mission planning. The project is to create and evaluate the integrated solubility model (ISM). The ISM is a first step in improving the chemistry basis in HTWOS. On principal the ISM is better than the current HTWOS solubility. ISM solids predictions match the experimental data well, with a few exceptions. ISM predictions are consistent with Stream Analyzer predictions except for chromium. HTWOS is producing more realistic results with the ISM

  12. Dst Prediction Based on Solar Wind Parameters

    Directory of Open Access Journals (Sweden)

    Yoon-Kyung Park

    2009-12-01

    Full Text Available We reevaluate the Burton equation (Burton et al. 1975 of predicting Dst index using high quality hourly solar wind data supplied by the ACE satellite for the period from 1998 to 2006. Sixty magnetic storms with monotonously decreasing main phase are selected. In order to determine the injection term (Q and the decay time (tau of the equation, we examine the relationships between Dst* and VB_s, Delta Dst* and VB_s, and Delta Dst* and Dst* during the magnetic storms. For this analysis, we take into account one hour of the propagation time from the ACE satellite to the magnetopause, and a half hour of the response time of the magnetosphere/ring current to the solar wind forcing. The injection term is found to be Q({nT}/h=-3.56VB_s for VB_s>0.5mV/m and Q({nT}/h=0 for VB_s leq0.5mV/m. The tau (hour is estimated as 0.060 Dst* + 16.65 for Dst*>-175nT and 6.15 hours for Dst* leq -175nT. Based on these empirical relationships, we predict the 60 magnetic storms and find that the correlation coefficient between the observed and predicted Dst* is 0.88. To evaluate the performance of our prediction scheme, the 60 magnetic storms are predicted again using the models by Burton et al. (1975 and O'Brien & McPherron (2000a. The correlation coefficients thus obtained are 0.85, the same value for both of the two models. In this respect, our model is slightly improved over the other two models as far as the correlation coefficients is concerned. Particularly our model does a better job than the other two models in predicting intense magnetic storms (Dst* lesssim -200nT.

  13. Prediction of room acoustical parameters (A)

    DEFF Research Database (Denmark)

    Gade, Anders Christian

    1991-01-01

    -averaged acoustical data. The results are presented in the form of linear, multiple regression formulas that may be used to predict the values of the newer measures of level, clarity, spaciousness, and musicians' conditions on the orchestra platform in halls with given RT and geometry....

  14. Interaction of antimicrobial preservatives with blow-fill-seal packs: correlating sorption with solubility parameters.

    Science.gov (United States)

    Amin, Aeshna; Dare, Manish; Sangamwar, Abhay; Bansal, Arvind Kumar

    2012-01-01

    The aim of this work was to study the interaction of four commonly used ophthalmic antimicrobial preservatives [benzyl alcohol (BA), chlorbutol (CBL), benzalkonium chloride (BKC), and chlorhexidine gluconate (CG)] with Blow-Fill-Seal (BFS) packs. Effect of packaging material [low-density polyethylene (LDPE), polypropylene (PP)], humidity (25% RH, 75% RH) and concentration (0.5, 1.0, 2.0 mM BA/CBL in LDPE) was studied. BKC and CG gave negligible loss (<4%) in BFS packs over a period of 3 months. BA and CBL, however, gave marked losses in LDPE (ca. 70-90%) and PP (ca. 7-25%) packs. Humidity did not have any effect on the sorption loss of any preservative. Loss of BA switched from Case II to anomalous behavior with increasing initial concentration. A two-stage sorption behavior was inherent at all concentrations. Loss of CBL followed anomalous behavior with biphasic kinetics of loss. It was concluded that all the four preservatives were appropriate for use in PP BFS packs. However, only BKC and CG were amenable to be used in LDPE BFS packs. Lastly, an empirical expression consisting of the "solubility parameter distance" and "molar volume" of preservatives was developed to correlate the preservative loss in LDPE with the physicochemical properties of the preservatives.

  15. Solubility of corrosion products of plain steel in oxygen-containing water solutions at high parameters

    International Nuclear Information System (INIS)

    Martynova, O.I.; Samojlov, Yu.F.; Petrova, T.I.; Kharitonova, N.L.

    1983-01-01

    Technique for calculation of solubility of iron corrosion products in oxygen-containing aqueous solutions in the 298-573 K temperature range is presented. Solubility of corrosion products of plain steel in deeply-desalinizated water in the presence of oxygen for the such range of the temperatures is experimentally determined. Rather good convergence between calculated and experimental data is noted

  16. System Predicts Critical Runway Performance Parameters

    Science.gov (United States)

    Millen, Ernest W.; Person, Lee H., Jr.

    1990-01-01

    Runway-navigation-monitor (RNM) and critical-distances-process electronic equipment designed to provide pilot with timely and reliable predictive navigation information relating to takeoff, landing and runway-turnoff operations. Enables pilot to make critical decisions about runway maneuvers with high confidence during emergencies. Utilizes ground-referenced position data only to drive purely navigational monitor system independent of statuses of systems in aircraft.

  17. EFFECTS OF INHALATION OF SOLUBLE METALLIC CONSTITUENTS OF PARTICULATE MATTER ON CARDIOPULMONARY, THERMOREGULATORY, AND BIOCHEMICAL PARAMETERS IN GUINEA PIGS

    Science.gov (United States)

    EFFECTS OF INHALATION OF SOLUBLE METALLIC CONSTITUENTS OF PARTICULATE MATTER ON CARDIOPULMONARY, THERMOREGULATORY, AND BIOCHEMICAL PARAMETERS IN GUINEA PIGS. JP Nolan1, LB Wichers2, J Stanek3, UP Kodavanti1, MCJ Schladweiler1, PA Evansky1, ER Lappi1, DL Costa1, and WP Watkinson1...

  18. Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption

    OpenAIRE

    Newby, Danielle; Freitas, Alex. A.; Ghafourian, Taravat

    2015-01-01

    Oral absorption of compounds depends on many physiological, physiochemical and formulation factors. Two important properties that govern oral absorption are in vitro permeability and solubility, which are commonly used as indicators of human intestinal absorption. Despite this, the nature and exact characteristics of the relationship between these parameters are not well understood. In this study a large dataset of human intestinal absorption was collated along with in vitro permeability, aqu...

  19. Thermodynamic approach to improving solubility prediction of co-crystals in comparison with individual poorly soluble components

    International Nuclear Information System (INIS)

    Perlovich, German L.

    2014-01-01

    Highlights: • Thermodynamic approach for solubility improvement of co-crystal was developed. • The graphical technique for estimation of co-crystal solubility was elaborated. • Hydration enthalpies of some drugs and amino acids were calculated. • Applicability/operability of the approach was exemplified by some drugs and amino acids. - Abstract: A novel thermodynamic approach to compare poorly soluble components (active pharmaceutical ingredient (API)) both in co-crystals and individual compounds was developed. An algorithm of choosing potential co-crystals with improved solubility characteristics on the basis of the known solvation/hydration API and co-former enthalpies is described. The applicability and operability of the algorithm were tested exemplified by some drugs and amino acids

  20. Potable NIR spectroscopy predicting soluble solids content of pears based on LEDs

    Energy Technology Data Exchange (ETDEWEB)

    Liu Yande; Liu Wei; Sun Xudong; Gao Rongjie; Pan Yuanyuan; Ouyang Aiguo, E-mail: jxliuyd@163.com [School of Mechatronics Engineering, East China Jiaotong University, Changbei Open and Developing District, Nanchang, 330013 (China)

    2011-01-01

    A portable near-infrared (NIR) instrument was developed for predicting soluble solids content (SSC) of pears equipped with light emitting diodes (LEDs). NIR spectra were collected on the calibration and prediction sets (145:45). Relationships between spectra and SSC were developed by multivariate linear regression (MLR), partial least squares (PLS) and artificial neural networks (ANNs) in the calibration set. The 45 unknown pears were applied to evaluate the performance of them in terms of root mean square errors of prediction (RMSEP) and correlation coefficients (r). The best result was obtained by PLS with RMSEP of 0.62{sup 0}Brix and r of 0.82. The results showed that the SSC of pears could be predicted by the portable NIR instrument.

  1. Potable NIR spectroscopy predicting soluble solids content of pears based on LEDs

    International Nuclear Information System (INIS)

    Liu Yande; Liu Wei; Sun Xudong; Gao Rongjie; Pan Yuanyuan; Ouyang Aiguo

    2011-01-01

    A portable near-infrared (NIR) instrument was developed for predicting soluble solids content (SSC) of pears equipped with light emitting diodes (LEDs). NIR spectra were collected on the calibration and prediction sets (145:45). Relationships between spectra and SSC were developed by multivariate linear regression (MLR), partial least squares (PLS) and artificial neural networks (ANNs) in the calibration set. The 45 unknown pears were applied to evaluate the performance of them in terms of root mean square errors of prediction (RMSEP) and correlation coefficients (r). The best result was obtained by PLS with RMSEP of 0.62 0 Brix and r of 0.82. The results showed that the SSC of pears could be predicted by the portable NIR instrument.

  2. Can we predict uranium bioavailability based on soil parameters? Part 1: Effect of soil parameters on soil solution uranium concentration

    International Nuclear Information System (INIS)

    Vandenhove, H.; Hees, M. van; Wouters, K.; Wannijn, J.

    2007-01-01

    Present study aims to quantify the influence of soil parameters on soil solution uranium concentration for 238 U spiked soils. Eighteen soils collected under pasture were selected such that they covered a wide range for those parameters hypothesised as being potentially important in determining U sorption. Maximum soil solution uranium concentrations were observed at alkaline pH, high inorganic carbon content and low cation exchange capacity, organic matter content, clay content, amorphous Fe and phosphate levels. Except for the significant correlation between the solid-liquid distribution coefficients (K d , L kg -1 ) and the organic matter content (R 2 = 0.70) and amorphous Fe content (R 2 = 0.63), there was no single soil parameter significantly explaining the soil solution uranium concentration (which varied 100-fold). Above pH = 6, log(K d ) was linearly related with pH [log(K d ) = - 1.18 pH + 10.8, R 2 = 0.65]. Multiple linear regression analysis did result in improved predictions of the soil solution uranium concentration but the model was complex. - Uranium solubility in soil can be predicted from organic matter or amorphous iron content and pH or with complex multilinear models considering several soil parameters

  3. Prediction of non-polar gas solubilities in water, alcohols and aqueous alcohol solutions by the modified ASOG method

    Energy Technology Data Exchange (ETDEWEB)

    Tochigi, K.; Kojima, K.

    1982-07-01

    This study evaluated a technique for predicting gas solubilities based on a modified ASOG group-contribution method, considering water, alcohols, and aqueous alcohol solutions as the solvents. The nonpolar gaseous solutes considered were oxygen, nitrogen, hydrogen, carbon dioxide, argon, methane, ethane, ethylene, propane, and butane. Gas solubilities were correlated and predicted for a partial gas pressure of 1 atm and a temperature range of 50/sup 0/-100/sup 0/F (10/sup 0/-40/sup 0/C) in pure solvents, and then predicted for the same pressure and temperature range in mixed solvents using only the solubility data for the pure solvents. The deviations between the observed and predicted solubilities averaged 6.0% in pure systems and 10.2% in mixed solvents.

  4. Tsunami Prediction and Earthquake Parameters Estimation in the Red Sea

    KAUST Repository

    Sawlan, Zaid A

    2012-01-01

    parameters and topography. This thesis introduces a real-time tsunami forecasting method that combines tsunami model with observations using a hybrid ensemble Kalman filter and ensemble Kalman smoother. The filter is used for state prediction while

  5. Factors predictive of abnormal semen parameters in male partners ...

    African Journals Online (AJOL)

    analysis was used to determine the predictive factors associated with abnormal semen parameters. .... for frequency, mean and χ2 with the level of significance set at p<0.05. ... was obtained from each couple participating in the study, following.

  6. Clinicopathologic and gene expression parameters predict liver cancer prognosis

    International Nuclear Information System (INIS)

    Hao, Ke; Zhong, Hua; Greenawalt, Danielle; Ferguson, Mark D; Ng, Irene O; Sham, Pak C; Poon, Ronnie T; Molony, Cliona; Schadt, Eric E; Dai, Hongyue; Luk, John M; Lamb, John; Zhang, Chunsheng; Xie, Tao; Wang, Kai; Zhang, Bin; Chudin, Eugene; Lee, Nikki P; Mao, Mao

    2011-01-01

    The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome

  7. pH-dependent solubility and permeability profiles: A useful tool for prediction of oral bioavailability.

    Science.gov (United States)

    Sieger, P; Cui, Y; Scheuerer, S

    2017-07-15

    pH-dependent solubility - permeability profiles offer a simple way to predict bioavailability after oral application, if bioavailability is only solubility and permeability driven. Combining both pH-dependent solubility and pH-dependent permeability in one diagram provides a pH-window (=ΔpH sol-perm ) from which the conditions for optimal oral bioavailability can be taken. The size of this window is directly proportional to the observed oral bioavailability. A set of 21 compounds, with known absolute human oral bioavailability, was used to establish this correlation. Compounds with ΔpH sol-perm bioavailability (bioavailability typically by approximately 25%. For compounds where ΔpH sol-perm ≥3 but still showing poor bioavailability, most probably other pharmacokinetic aspects (e.g. high clearance), are limiting exposure. Interestingly, the location of this pH-window seems to have a negligible influence on the observed oral bioavailability. In scenarios, where the bioavailability is impaired by certain factors, like for example proton pump inhibitor co-medication or food intake, the exact position of this pH-window might be beneficial for understanding the root cause. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Predicting the solubility of gases in Nitrile Butadiene Rubber in extreme conditions using molecular simulation

    Science.gov (United States)

    Khawaja, Musab; Molinari, Nicola; Sutton, Adrian; Mostofi, Arash

    In the oil and gas industry, elastomer seals play an important role in protecting sensitive monitoring equipment from contamination by gases - a problem that is exacerbated by the high pressures and temperatures found down-hole. The ability to predict and prevent such permeative failure has proved elusive to-date. Nitrile butadiene rubber (NBR) is a common choice of elastomer for seals due to its resistance to heat and fuels. In the conditions found in the well it readily absorbs small molecular weight gases. How this behaviour changes quantitatively for different gases as a function of temperature and pressure is not well-understood. In this work a series of fully atomistic simulations are performed to understand the effect of extreme conditions on gas solubility in NBR. Widom particle insertion is used to compute solubilities. The importance of sampling and allowing structural relaxation upon compression are highlighted, and qualitatively reasonable trends reproduced. Finally, while at STP it has previously been shown that the solubility of CO2 is higher than that of He in NBR, we observe that under the right circumstances it is possible to reverse this trend.

  9. Prediction and experimental determination of the solubility of exotic scales at high temperatures - Zinc sulfide

    DEFF Research Database (Denmark)

    Carolina Figueroa Murcia, Diana; Fosbøl, Philip Loldrup; Thomsen, Kaj

    2016-01-01

    The presence of "exotic" scale such as Zinc Sulfide (ZnS), Lead Sulfide (PbS) and Iron Sulfide (FeS) in HP/HT reservoirs has been identified. "Exotic" scale materials come as a new challenge in HP/HT reservoirs. This has led to the development of more advanced tools to predict their behavior...... at extreme conditions. The aim of this work is to include ZnS into the group of scale materials that can be modeled with the Extended UNIQUAC model. Solubility data for ZnS are scarce in the open literature. In order to improve the available data, we study the experimental behavior of ZnS solubility at high...... temperatures. The determination of the solubility of ZnS is carried out at temperatures up to 250°C. Zinc sulfide (99.99%) and ultra-pure water are placed in a vial in a reduced oxygen atmosphere. The sample is placed in a controlled bath and stirred until equilibrium is attained. The suspension is filtered...

  10. Prediction of pH-dependent aqueous solubility of Histone Deacetylase (HDAC) inhibitors

    DEFF Research Database (Denmark)

    Kouskoumvekaki, Irene; Hansen, Niclas Tue; Bjorkling, F.

    2008-01-01

    on the series of HDAC inhibitors by use of Self-Organizing Maps (SOM) and 2D-projection of the HDAC inhibitors on the chemical space of the training data set of the artificial neural network (ANN) module. The model was refined for the particular chemical space of interest, which led to two modifications...... can develop models that are more accurate in predicting differences in the solubility of structurally very similar compounds than models that have been trained on structurally unbiased, diverse data sets. Such 'tailor-made' models have the potential to become trustworthy enough to replace time...

  11. Gels of ferulated arabinoxylans extracted from distillers dried grains with solubles: rheology, structural parameters and microstructure

    Science.gov (United States)

    One of the major by-products of bioethanol production is distillers dried grains with solubles (DDGS). Maize is one of the main sources for the production of this biofuel. In this way, dietary fiber represents the principal fraction of DDGS, which could be a potential source of added-value biomolecu...

  12. Gas release during salt-well pumping: Model predictions and laboratory validation studies for soluble and insoluble gases

    International Nuclear Information System (INIS)

    Peurrung, L.M.; Caley, S.M.; Gauglitz, P.A.

    1997-08-01

    The Hanford Site has 149 single-shell tanks (SSTs) containing radioactive wastes that are complex mixes of radioactive and chemical products. Of these, 67 are known or suspected to have leaked liquid from the tanks into the surrounding soil. Salt-well pumping, or interim stabilization, is a well-established operation for removing drainable interstitial liquid from SSTs. The overall objective of this ongoing study is to develop a quantitative understanding of the release rates and cumulative releases of flammable gases from SSTs as a result of salt-well pumping. The current study is an extension of the previous work reported by Peurrung et al. (1996). The first objective of this current study was to conduct laboratory experiments to quantify the release of soluble and insoluble gases. The second was to determine experimentally the role of characteristic waste heterogeneities on the gas release rates. The third objective was to evaluate and validate the computer model STOMP (Subsurface Transport over Multiple Phases) used by Peurrung et al. (1996) to predict the release of both soluble (typically ammonia) and insoluble gases (typically hydrogen) during and after salt-well pumping. The fourth and final objective of the current study was to predict the gas release behavior for a range of typical tank conditions and actual tank geometry. In these models, the authors seek to include all the pertinent salt-well pumping operational parameters and a realistic range of physical properties of the SST wastes. For predicting actual tank behavior, two-dimensional (2-D) simulations were performed with a representative 2-D tank geometry

  13. Measurement and prediction of dabigatran etexilate mesylate Form II solubility in mono-solvents and mixed solvents

    International Nuclear Information System (INIS)

    Xiao, Yan; Wang, Jingkang; Wang, Ting; Ouyang, Jinbo; Huang, Xin; Hao, Hongxun; Bao, Ying; Fang, Wen; Yin, Qiuxiang

    2016-01-01

    Highlights: • Solubility of DEM Form II in mono-solvents and binary solvent mixtures was measured. • Regressed UNIFAC model was used to predict the solubility in solvent mixtures. • The experimental solubility data were correlated by different models. - Abstract: UV spectrometer method was used to measure the solubility data of dabigatran etexilate mesylate (DEM) Form II in five mono-solvents (methanol, ethanol, ethane-1,2-diol, DMF, DMAC) and binary solvent mixtures of methanol and ethanol in the temperature range from 287.37 K to 323.39 K. The experimental solubility data in mono-solvents were correlated with modified Apelblat equation, van’t Hoff equation and λh equation. GSM model and Modified Jouyban-Acree model were employed to correlate the solubility data in mixed solvent systems. And Regressed UNIFAC model was used to predict the solubility of DEM Form II in the binary solvent mixtures. Results showed that the predicted data were consistent with the experimental data.

  14. Screening of genetic parameters for soluble protein expression in Escherichia coli

    DEFF Research Database (Denmark)

    Vernet, Erik; Kotzsch, Alexander; Voldborg, Bjørn

    2011-01-01

    Soluble expression of proteins in a relevant form for functional and structural investigations still often remains a challenge. Although many biochemical factors are known to affect solubility, a thorough investigation of yield-limiting factors is normally not feasible in high-throughput efforts....... Here we present a screening strategy for expression of biomedically relevant proteins in Escherichia coli using a panel of six different genetic variations. These include engineered strains for rare codon supplementation, increased disulfide bond formation in the cytoplasm and novel vectors...... for secretion to the periplasm or culture medium. Combining these variants with expression construct truncations design, we report on parallel cloning and expression of more than 300 constructs representing 24 selected proteins; including full-length variants of human growth factors, interleukins and growth...

  15. Tsunami Prediction and Earthquake Parameters Estimation in the Red Sea

    KAUST Repository

    Sawlan, Zaid A

    2012-12-01

    Tsunami concerns have increased in the world after the 2004 Indian Ocean tsunami and the 2011 Tohoku tsunami. Consequently, tsunami models have been developed rapidly in the last few years. One of the advanced tsunami models is the GeoClaw tsunami model introduced by LeVeque (2011). This model is adaptive and consistent. Because of different sources of uncertainties in the model, observations are needed to improve model prediction through a data assimilation framework. Model inputs are earthquake parameters and topography. This thesis introduces a real-time tsunami forecasting method that combines tsunami model with observations using a hybrid ensemble Kalman filter and ensemble Kalman smoother. The filter is used for state prediction while the smoother operates smoothing to estimate the earthquake parameters. This method reduces the error produced by uncertain inputs. In addition, state-parameter EnKF is implemented to estimate earthquake parameters. Although number of observations is small, estimated parameters generates a better tsunami prediction than the model. Methods and results of prediction experiments in the Red Sea are presented and the prospect of developing an operational tsunami prediction system in the Red Sea is discussed.

  16. Bead-bead interaction parameters in dissipative particle dynamics: Relation to bead-size, solubility parameter, and surface tension

    Science.gov (United States)

    Maiti, Amitesh; McGrother, Simon

    2004-01-01

    Dissipative particle dynamics (DPD) is a mesoscale modeling method for simulating equilibrium and dynamical properties of polymers in solution. The basic idea has been around for several decades in the form of bead-spring models. A few years ago, Groot and Warren [J. Chem. Phys. 107, 4423 (1997)] established an important link between DPD and the Flory-Huggins χ-parameter theory for polymer solutions. We revisit the Groot-Warren theory and investigate the DPD interaction parameters as a function of bead size. In particular, we show a consistent scheme of computing the interfacial tension in a segregated binary mixture. Results for three systems chosen for illustration are in excellent agreement with experimental results. This opens the door for determining DPD interactions using interfacial tension as a fitting parameter.

  17. Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation

    Science.gov (United States)

    Paluch, Andrew S.; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L.

    2015-01-01

    We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

  18. Updated climatological model predictions of ionospheric and HF propagation parameters

    International Nuclear Information System (INIS)

    Reilly, M.H.; Rhoads, F.J.; Goodman, J.M.; Singh, M.

    1991-01-01

    The prediction performances of several climatological models, including the ionospheric conductivity and electron density model, RADAR C, and Ionospheric Communications Analysis and Predictions Program, are evaluated for different regions and sunspot number inputs. Particular attention is given to the near-real-time (NRT) predictions associated with single-station updates. It is shown that a dramatic improvement can be obtained by using single-station ionospheric data to update the driving parameters for an ionospheric model for NRT predictions of f(0)F2 and other ionospheric and HF circuit parameters. For middle latitudes, the improvement extends out thousands of kilometers from the update point to points of comparable corrected geomagnetic latitude. 10 refs

  19. Prediction of soluble solids content and ph in red wine by visible and near infrared spectroscopy

    Science.gov (United States)

    Wang, Li; He, Yong; Wang, Yanyan

    2008-02-01

    Soluble solids content (SSC) and pH are two major characteristic used for assessing quality of red wine, and they are also two important quality indexes in the manufacture of red wine. For rapid detection of SSC and pH in red wine, visible and near infrared (Vis/NIR) transmittance spectroscopy technique combined with partial least squares (PLS) and least squares support vector machines (LS-SVM) were used in this study. First, the near infrared transmittance spectra of 175 red wine samples were obtained using Vis/NIR spectroradiometer, then, PLS was applied for reducing the dimensionality of the original spectra, latent variables (LVs) selected by PLS could be used to replace the complex spectral data. All samples were randomly separated into calibration set and validation set. The LVs (selected by PLS) of each sample in calibration set was used as the inputs to train the LS-SVM model, then the optimal model was used to predict the SSC and pH values of samples in validation set based on their LVs. Standard error prediction (SEP) and determination coefficient (r2) were used as the evaluation standards, and the results indicated that the SEP and r2 for the prediction of SSC were 0.2313 and 0.9348; while 0.0071 and 0.9986 for pH. This prediction model was more accurate compared with the related research.

  20. Determination of the solubility parameter of ionic liquid 1-butyl-3-methylimidazolium tetrafluoroborate by inverse gas chromatography.

    Science.gov (United States)

    Ma, Xiaohong; Wang, Qiang; Li, Xiaoping; Tang, Jun; Zhang, Zhengfang

    2015-11-01

    Thermodynamic properties of ionic liquid 1-butyl-3-methylimidazolium tetrafluoroborate ([BMIM] BF4) were determined via inverse gas chromatography (IGC). Two groups of solvents with different chemical natures and polarities were used to obtain information about [BMIM] BF4-solvent interactions. The specific retention volume, molar heat of sorption, weight fraction activity coefficient, Flory-Huggins interaction parameter as well as solubility parameter were also determined in a temperature range of 333 - 373 K. The results showed that the selected solvents n-C10 to n-C12, carbon tetrachloride, cyclohexane and toluene were poor solvents for [BMIM] BF4, while dichloromethane, acetone, chloroform, methyl acetate, ethanol and methanol were favorite solvents for [BMIM] BF4. In addition, the solubility parameter of [ BMIM] BF4 was determined as 23.39 (J/cm3)0.5 by the extrapolation at 298 K. The experiment proved that IGC was a simple and accurate method to obtain the thermodynamic properties of ionic liquids. This study could be used as a reference to the application and research of the ionic liquids.

  1. Modelling hydrodynamic parameters to predict flow assisted corrosion

    International Nuclear Information System (INIS)

    Poulson, B.; Greenwell, B.; Chexal, B.; Horowitz, J.

    1992-01-01

    During the past 15 years, flow assisted corrosion has been a worldwide problem in the power generating industry. The phenomena is complex and depends on environment, material composition, and hydrodynamic factors. Recently, modeling of flow assisted corrosion has become a subject of great importance. A key part of this effort is modeling the hydrodynamic aspects of this issue. This paper examines which hydrodynamic parameter should be used to correlate the occurrence and rate of flow assisted corrosion with physically meaningful parameters, discusses ways of measuring the relevant hydrodynamic parameter, and describes how the hydrodynamic data is incorporated into the predictive model

  2. Solubility of hot fuel particles from Chernobyl--influencing parameters for individual radiation dose calculations.

    Science.gov (United States)

    Garger, Evgenii K; Meisenberg, Oliver; Odintsov, Oleksiy; Shynkarenko, Viktor; Tschiersch, Jochen

    2013-10-15

    Nuclear fuel particles of Chernobyl origin are carriers of increased radioactivity (hot particles) and are still present in the atmosphere of the Chernobyl exclusion zone. Workers in the zone may inhale these particles, which makes assessment necessary. The residence time in the lungs and the transfer in the blood of the inhaled radionuclides are crucial for inhalation dose assessment. Therefore, the dissolution of several kinds of nuclear fuel particles from air filters sampled in the Chernobyl exclusion zone was studied. For this purpose filter fragments with hot particles were submersed in simulated lung fluids (SLFs). The activities of the radionuclides (137)Cs, (90)Sr, (239+240)Pu and (241)Am were measured in the SLF and in the residuum of the fragments by radiometric methods after chemical treatment. Soluble fractions as well as dissolution rates of the nuclides were determined. The influence of the genesis of the hot particles, represented by the (137)Cs/(239+240)Pu ratio, on the availability of (137)Cs was demonstrated, whereas the dissolution of (90)Sr, (239+240)Pu and (241)Am proved to be independent of genesis. No difference in the dissolution of (137)Cs and (239+240)Pu was observed for the two applied types of SLF. Increased solubility was found for smaller hot particles. A two-component exponential model was used to describe the dissolution of the nuclides as a function of time. The results were applied for determining individual inhalation dose coefficients for the workers at the Chernobyl construction site. Greater dose coefficients for the respiratory tract and smaller coefficients for the other organs were calculated (compared to ICRP default values). The effective doses were in general lower for the considered radionuclides, for (241)Am even by one order of magnitude. © 2013 Elsevier B.V. All rights reserved.

  3. Prediction of Starch, Soluble Sugars and Amino Acids in Potatoes (Solanum tuberosum L.) Using Hyperspectral Imaging, Dielectric and LF-NMR Methodologies

    DEFF Research Database (Denmark)

    Kjær, Anders; Nielsen, Glenn; Stærke, Søren

    2016-01-01

    Handling and processing of potatoes is performed in increasingly large and more automated facilities, and the industry calls for more automated machinery for quality assessment and sorting by concentration of starch, soluble sugars, protein, amino acids etc. of the potato tubers. The present study...... cultivars were simultaneously sampled for analyses of content and scanned by the five different scanning methods. The resulting multivariate dataset was used to estimate the prediction ability of the individual scanning methods on starch-related parameters, selected simple sugars, selected amino acids......, conductivity of pressed cell sap and cell sizes. Results showed that most types of spectral analyses had relatively high potential for predicting the starch-related parameters and medium potential for predicting the concentration of the reducing sugars fructose and glucose. Most methods showed medium potential...

  4. Optimal parameters of the SVM for temperature prediction

    Directory of Open Access Journals (Sweden)

    X. Shi

    2015-05-01

    Full Text Available This paper established three different optimization models in order to predict the Foping station temperature value. The dimension was reduced to change multivariate climate factors into a few variables by principal component analysis (PCA. And the parameters of support vector machine (SVM were optimized with genetic algorithm (GA, particle swarm optimization (PSO and developed genetic algorithm. The most suitable method was applied for parameter optimization by comparing the results of three different models. The results are as follows: The developed genetic algorithm optimization parameters of the predicted values were closest to the measured value after the analog trend, and it is the most fitting measured value trends, and its homing speed is relatively fast.

  5. Effect of uncertainty parameters on graphene sheets Young's modulus prediction

    International Nuclear Information System (INIS)

    Sahlaoui, Habib; Sidhom Habib; Guedri, Mohamed

    2013-01-01

    Software based on molecular structural mechanics approach (MSMA) and using finite element method (FEM) has been developed to predict the Young's modulus of graphene sheets. Obtained results have been compared to results available in the literature and good agreement has been shown when the same values of uncertainty parameters are used. A sensibility of the models to their uncertainty parameters has been investigated using a stochastic finite element method (SFEM). The different values of the used uncertainty parameters, such as molecular mechanics force field constants k_r and k_θ, thickness (t) of a graphene sheet and length ( L_B) of a carbon carbon bonds, have been collected from the literature. Strong sensibilities of 91% to the thickness and of 21% to the stretching force (k_r) have been shown. The results justify the great difference between Young's modulus predicted values of the graphene sheets and their large disagreement with experimental results.

  6. A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli.

    Science.gov (United States)

    Habibi, Narjeskhatoon; Mohd Hashim, Siti Z; Norouzi, Alireza; Samian, Mohammed Razip

    2014-05-08

    Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and economic volume. Although logical strategies of genetic engineering have been established, protein overexpression is still an art. In particular, heterologous expression is often hindered by low level of production and frequent fail due to opaque reasons. The problem is accentuated because there is no generic solution available to enhance heterologous overexpression. For a given protein, the extent of its solubility can indicate the quality of its function. Over 30% of synthesized proteins are not soluble. In certain experimental circumstances, including temperature, expression host, etc., protein solubility is a feature eventually defined by its sequence. Until now, numerous methods based on machine learning are proposed to predict the solubility of protein merely from its amino acid sequence. In spite of the 20 years of research on the matter, no comprehensive review is available on the published methods. This paper presents an extensive review of the existing models to predict protein solubility in Escherichia coli recombinant protein overexpression system. The models are investigated and compared regarding the datasets used, features, feature selection methods, machine learning techniques and accuracy of prediction. A discussion on the models is provided at the end. This study aims to investigate extensively the machine learning based methods to predict recombinant protein solubility, so as to offer a general as well as a detailed understanding for researches in the field. Some of the models present acceptable prediction performances and convenient user interfaces. These models can be considered as valuable tools to predict recombinant protein overexpression results before performing real laboratory experiments, thus saving labour, time and cost.

  7. Predictive value of serum soluble corin in the risk of hyperglycemia: A population-based prospective cohort study in China.

    Science.gov (United States)

    Zhu, Zhengbao; Zhang, Qiu; Peng, Hao; Zhong, Chongke; Guo, Daoxia; Huangfu, Xinfeng; Chao, Xiangqin; Wang, Aili; Jin, Jianhua; Zhang, Yonghong

    2018-04-01

    Serum soluble corin has been suggested to be associated with hyperglycemia by cross-sectional study. However, the prospective relationship between them remains unclear, and whether lipid component influences the relationship between them has not yet been studied. A total of 1961 participants who were free from hyperglycemia were enrolled at baseline in 2010. The serum soluble corin concentrations were measured at baseline and all participants were followed up for hyperglycemia in 2014. The association between serum soluble corin and hyperglycemia incidence was appreciably modified by high density lipoprotein cholesterol (HDL-C) (P interaction  = 0.04). Elevated serum soluble corin was associated with the risk of hyperglycemia only in the HDL-C ≥1.04 mmol/l subgroup rather than all participants. In participants with HDL-C ≥1.04 mmol/l, the adjusted odds ratio (95% CU) of hyperglycemia associated with the fourth quartiles of corin was 1.78 (1.08-2.94) compared with the lowest quartile of serum soluble corin, and there was a positive linear dose-response relationship between them (P for linearity <0.01). The ordinal analysis showed an association between serum soluble corin and hyperglycemia severity (adjusted OR, 1.81; 95% CI, 1.10-2.99; P trend  = 0.02, when 2 extreme quartiles were compared). The addition of serum soluble corin to conventional risk factors improved risk prediction for hyperglycemia (net reclassification index: 0.16; integrated discrimination improvement: 0.01) in participants with HDL-C ≥1.04 mmol/l. Serum soluble corin might be a valuable biomarker in prediction of future hyperglycemia in population with HDL-C ≥1.04 mmol/l, suggesting that corin might play a potential role in glucose metabolism. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. Predicting corrosion product transport in nuclear power stations using a solubility-based model for flow-accelerated corrosion

    International Nuclear Information System (INIS)

    Burrill, K.A.; Cheluget, E.L.

    1995-01-01

    A general model of solubility-driven flow-accelerated corrosion of carbon steel was derived based on the assumption that the solubilities of ferric oxyhydroxide and magnetite control the rate of film dissolution. This process involves the dissolution of an oxide film due to fast-flowing coolant unsaturated in iron. The soluble iron is produced by (i) the corrosion of base metal under a porous oxide film and (ii) the dissolution of the oxide film at the fluid-oxide film interface. The iron released at the pipe wall is transferred into the bulk flow by turbulent mass transfer. The model is suitable for calculating concentrations of dissolved iron in feedtrain lines. These iron levels were used to calculate sludge transport rates around the feedtrain. The model was used to predict sludge transport rates due to flow accelerated corrosion of major feedtrain piping in a CANDU reactor. The predictions of the model compare well with plant measurements

  9. Prediction of interest rate using CKLS model with stochastic parameters

    International Nuclear Information System (INIS)

    Ying, Khor Chia; Hin, Pooi Ah

    2014-01-01

    The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ (j) of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ (j) , we assume that φ (j) depends on φ (j−m) , φ (j−m+1) ,…, φ (j−1) and the interest rate r j+n at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r j+n+1 of the interest rate at the next time point when the value r j+n of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r j+n+d at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters

  10. Prediction of interest rate using CKLS model with stochastic parameters

    Energy Technology Data Exchange (ETDEWEB)

    Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)

    2014-06-19

    The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.

  11. Different Vocal Parameters Predict Perceptions of Dominance and Attractiveness.

    Science.gov (United States)

    Hodges-Simeon, Carolyn R; Gaulin, Steven J C; Puts, David A

    2010-12-01

    Low mean fundamental frequency (F(0)) in men's voices has been found to positively influence perceptions of dominance by men and attractiveness by women using standardized speech. Using natural speech obtained during an ecologically valid social interaction, we examined relationships between multiple vocal parameters and dominance and attractiveness judgments. Male voices from an unscripted dating game were judged by men for physical and social dominance and by women in fertile and non-fertile menstrual cycle phases for desirability in short-term and long-term relationships. Five vocal parameters were analyzed: mean F(0) (an acoustic correlate of vocal fold size), F(0) variation, intensity (loudness), utterance duration, and formant dispersion (D(f), an acoustic correlate of vocal tract length). Parallel but separate ratings of speech transcripts served as controls for content. Multiple regression analyses were used to examine the independent contributions of each of the predictors. Physical dominance was predicted by low F(0) variation and physically dominant word content. Social dominance was predicted only by socially dominant word content. Ratings of attractiveness by women were predicted by low mean F(0), low D(f), high intensity, and attractive word content across cycle phase and mating context. Low D(f) was perceived as attractive by fertile-phase women only. We hypothesize that competitors and potential mates may attend more strongly to different components of men's voices because of the different types of information these vocal parameters provide.

  12. Investigation on Cardiovascular Risk Prediction Using Physiological Parameters

    Directory of Open Access Journals (Sweden)

    Wan-Hua Lin

    2013-01-01

    Full Text Available Cardiovascular disease (CVD is the leading cause of death worldwide. Early prediction of CVD is urgently important for timely prevention and treatment. Incorporation or modification of new risk factors that have an additional independent prognostic value of existing prediction models is widely used for improving the performance of the prediction models. This paper is to investigate the physiological parameters that are used as risk factors for the prediction of cardiovascular events, as well as summarizing the current status on the medical devices for physiological tests and discuss the potential implications for promoting CVD prevention and treatment in the future. The results show that measures extracted from blood pressure, electrocardiogram, arterial stiffness, ankle-brachial blood pressure index (ABI, and blood glucose carry valuable information for the prediction of both long-term and near-term cardiovascular risk. However, the predictive values should be further validated by more comprehensive measures. Meanwhile, advancing unobtrusive technologies and wireless communication technologies allow on-site detection of the physiological information remotely in an out-of-hospital setting in real-time. In addition with computer modeling technologies and information fusion. It may allow for personalized, quantitative, and real-time assessment of sudden CVD events.

  13. Predicting plant biomass accumulation from image-derived parameters

    Science.gov (United States)

    Chen, Dijun; Shi, Rongli; Pape, Jean-Michel; Neumann, Kerstin; Graner, Andreas; Chen, Ming; Klukas, Christian

    2018-01-01

    Abstract Background Image-based high-throughput phenotyping technologies have been rapidly developed in plant science recently, and they provide a great potential to gain more valuable information than traditionally destructive methods. Predicting plant biomass is regarded as a key purpose for plant breeders and ecologists. However, it is a great challenge to find a predictive biomass model across experiments. Results In the present study, we constructed 4 predictive models to examine the quantitative relationship between image-based features and plant biomass accumulation. Our methodology has been applied to 3 consecutive barley (Hordeum vulgare) experiments with control and stress treatments. The results proved that plant biomass can be accurately predicted from image-based parameters using a random forest model. The high prediction accuracy based on this model will contribute to relieving the phenotyping bottleneck in biomass measurement in breeding applications. The prediction performance is still relatively high across experiments under similar conditions. The relative contribution of individual features for predicting biomass was further quantified, revealing new insights into the phenotypic determinants of the plant biomass outcome. Furthermore, methods could also be used to determine the most important image-based features related to plant biomass accumulation, which would be promising for subsequent genetic mapping to uncover the genetic basis of biomass. Conclusions We have developed quantitative models to accurately predict plant biomass accumulation from image data. We anticipate that the analysis results will be useful to advance our views of the phenotypic determinants of plant biomass outcome, and the statistical methods can be broadly used for other plant species. PMID:29346559

  14. High pre-transplant soluble CD30 levels are predictive of the grade of rejection.

    Science.gov (United States)

    Rajakariar, Ravindra; Jivanji, Naina; Varagunam, Mira; Rafiq, Mohammad; Gupta, Arun; Sheaff, Michael; Sinnott, Paul; Yaqoob, M M

    2005-08-01

    In renal transplantation, serum soluble CD30 (sCD30) levels in graft recipients are associated with increased rejection and graft loss. We investigated whether pre-transplant sCD30 concentrations are predictive of the grade of rejection. Pre-transplant sera of 51 patients with tubulointerstitial rejection (TIR), 16 patients with vascular rejection (VR) and an age-matched control group of 41 patients with no rejection (NR) were analyzed for sCD30. The transplant biopsies were immunostained for C4d. The median sCD30 level was significantly elevated in the group with VR (248 Units (U)/mL, range: 92-802) when compared with TIR (103 U/mL, range: 36-309, psCD30 levels compared to NR. Based on C4d staining, a TH2 driven process, the median sCD30 levels were significantly raised in C4d+ patients compared with C4d- group (177 U/mL vs. 120 U/mL, psCD30 levels measured at time of transplantation correlate with the grade of rejection. High pre-transplant levels are associated with antibody-mediated rejection which carries a poorer prognosis. sCD30 could be another tool to assess immunological risk prior to transplantation and enable a patient centered approach to immunosuppression.

  15. Soluble CD30 in renal transplant recipients: is it a good biomarker to predict rejection?

    Science.gov (United States)

    Azarpira, Negar; Aghdaie, Mahdokht Hosein; Malekpour, Zahra

    2010-01-01

    It has been suggested that the serum soluble CD30 (sCD30) level may be a poten-tial marker for the prediction of acute allograft rejection in kidney transplant recipients. Therefore, its serum concentrations might offer a promising non-invasive tool to recognize patients with an increased risk for developing an acute graft rejection. We retrospectively correlate pre and post transplant level on post transplant graft survival, incidence of acute rejection and graft function using stored serum samples. Ninety-nine patients were divided in two separate groups: Group A in whom sample collection was done one day before transplantation and Group B where sample collection was done five days after transplantation. Younger recipients (aged less than 20 years) had higher sCD30 levels (P= 0.02). There was neither significant difference in the incidence of acute rejection nor incomplete response rate after anti rejection therapy in relation to pre transplant or post transplant sCD30. We could not find a significantly inferior graft survival rate in the high sCD30 group. In conclusion, younger patients had higher sCD30 concentrations however no correlation existed between the serum concentrations and occurrence of rejection episodes or graft survival.

  16. Soluble CD30 for the prediction and detection of kidney transplant rejection.

    Science.gov (United States)

    Arjona, Alvaro

    2009-09-01

    Although safer and more effective immunosuppressants as well as enhanced immunosuppressive protocols are continuously being developed in order to increase graft survival, they come at the steep price of drug-related complications and important side effects. In addition, the value of panel reactive antibodies determination, which at present is the single most used indicator of an increased risk of transplant rejection, is now being reevaluated. Therefore, effective tailoring of immunosuppressive therapy minimizing the above-mentioned pitfalls requires the existence of dependable biomarkers that adequately monitor rejection risk both before and after transplantation. Here we review the data yielded by studies assessing the usefulness of measuring soluble CD30 levels (sCD30) in kidney transplant rejection. These data collectively show that sCD30 serum content has a considerable predictive/diagnostic value for acute rejection of renal grafts, particularly when measured a few days after transplantation. Copyright 2009 Prous Science, S.A.U. or its licensors. All rights reserved.

  17. Prediction of solubility and permeability class membership: provisional BCS classification of the world's top oral drugs.

    Science.gov (United States)

    Dahan, Arik; Miller, Jonathan M; Amidon, Gordon L

    2009-12-01

    The Biopharmaceutics Classification System (BCS) categorizes drugs into one of four biopharmaceutical classes according to their water solubility and membrane permeability characteristics and broadly allows the prediction of the rate-limiting step in the intestinal absorption process following oral administration. Since its introduction in 1995, the BCS has generated remarkable impact on the global pharmaceutical sciences arena, in drug discovery, development, and regulation, and extensive validation/discussion/extension of the BCS is continuously published in the literature. The BCS has been effectively implanted by drug regulatory agencies around the world in setting bioavailability/bioequivalence standards for immediate-release (IR) oral drug product approval. In this review, we describe the BCS scientific framework and impact on regulatory practice of oral drug products and review the provisional BCS classification of the top drugs on the global market. The Biopharmaceutical Drug Disposition Classification System and its association with the BCS are discussed as well. One notable finding of the provisional BCS classification is that the clinical performance of the majority of approved IR oral drug products essential for human health can be assured with an in vitro dissolution test, rather than empirical in vivo human studies.

  18. NIR calibration of soluble stem carbohydrates for predicting drought tolerance in spring wheat

    Science.gov (United States)

    Soluble stem carbohydrates are a component of drought response in wheat (Triticum aestivum L.) and other grasses. Near-infrared spectroscopy (NIR) can rapidly assay for soluble carbohydrates indirectly, but this requires a statistical model for calibration. The objectives of this study were: (i) to ...

  19. Prediction of acute renal allograft rejection in early post-transplantation period by soluble CD30.

    Science.gov (United States)

    Dong, Wang; Shunliang, Yang; Weizhen, Wu; Qinghua, Wang; Zhangxin, Zeng; Jianming, Tan; He, Wang

    2006-06-01

    To evaluate the feasibility of serum sCD30 for prediction of acute graft rejection, we analyzed clinical data of 231 patients, whose serum levels of sCD30 were detected by ELISA before and after transplantation. They were divided into three groups: acute rejection group (AR, n = 49), uncomplicated course group (UC, n = 171) and delayed graft function group (DGF, n = 11). Preoperative sCD30 levels of three groups were 183 +/- 74, 177 +/- 82 and 168 +/- 53 U/ml, respectively (P = 0.82). Significant decrease of sCD30 was detected in three groups on day 5 and 10 post-transplantation respectively (52 +/- 30 and 9 +/- 5 U/ml respectively, P sCD30 values on day 5 post-transplantation (92 +/- 27 U/ml vs. 41 +/- 20 U/ml and 48 +/- 18 U/ml, P sCD30 levels on day 10 post-transplantation were virtually similar in patients of three groups (P = 0.43). Receiver operating characteristic (ROC) curve demonstrated that sCD30 level on day 5 post-transplantation could differentiate patients who subsequently suffered acute allograft rejection from others (area under ROC curve 0.95). According to ROC curve, 65 U/ml may be the optimal operational cut-off level to predict impending graft rejection (specificity 91.8%, sensitivity 87.1%). Measurement of soluble CD30 on day 5 post-transplantation might offer a noninvasive means to recognize patients at risk of impending acute graft rejection during early post-transplantation period.

  20. A prediction of the inert gas solubilities in stoichiometric molten UO2

    International Nuclear Information System (INIS)

    Gunnerson, F.S.; Cronenberg, A.W.

    1975-01-01

    To analyze the effect of fission gas behaviour on fast reactor fuels during a hypothetical overpower transient, the solubility characteristics of the noble gases in molten UO 2 have been assessed. To accomplish this, a theoretical estimation of such solubilities is made by determining the reversible work required to introduce a hard sphere, the size of the gas atom, into the liquid solvent. Results indicate that the solubility of the noble gases in molten UO 2 is quite low, the molar fraction of gas-to-liquid being approximately 10 -6 . Such a low solubility of fission gases suggests that for preirradiated fuels, added swelling or formation may occur upon melting. In addition, such low solubility potential indicates that the fission gases do not play an appreciable role in the fragmentation of molten UO 2 upon quenching in sodium coolant. (Auth.)

  1. Using neural networks for prediction of nuclear parameters

    Energy Technology Data Exchange (ETDEWEB)

    Pereira Filho, Leonidas; Souto, Kelling Cabral, E-mail: leonidasmilenium@hotmail.com, E-mail: kcsouto@bol.com.br [Instituto Federal de Educacao, Ciencia e Tecnologia do Rio de Janeiro (IFRJ), Rio de Janeiro, RJ (Brazil); Machado, Marcelo Dornellas, E-mail: dornemd@eletronuclear.gov.br [Eletrobras Termonuclear S.A. (GCN.T/ELETRONUCLEAR), Rio de Janeiro, RJ (Brazil). Gerencia de Combustivel Nuclear

    2013-07-01

    Dating from 1943, the earliest work on artificial neural networks (ANN), when Warren Mc Cullock and Walter Pitts developed a study on the behavior of the biological neuron, with the goal of creating a mathematical model. Some other work was done until after the 80 witnessed an explosion of interest in ANNs, mainly due to advances in technology, especially microelectronics. Because ANNs are able to solve many problems such as approximation, classification, categorization, prediction and others, they have numerous applications in various areas, including nuclear. Nodal method is adopted as a tool for analyzing core parameters such as boron concentration and pin power peaks for pressurized water reactors. However, this method is extremely slow when it is necessary to perform various core evaluations, for example core reloading optimization. To overcome this difficulty, in this paper a model of Multi-layer Perceptron (MLP) artificial neural network type backpropagation will be trained to predict these values. The main objective of this work is the development of Multi-layer Perceptron (MLP) artificial neural network capable to predict, in very short time, with good accuracy, two important parameters used in the core reloading problem - Boron Concentration and Power Peaking Factor. For the training of the neural networks are provided loading patterns and nuclear data used in cycle 19 of Angra 1 nuclear power plant. Three models of networks are constructed using the same input data and providing the following outputs: 1- Boron Concentration and Power Peaking Factor, 2 - Boron Concentration and 3 - Power Peaking Factor. (author)

  2. Using neural networks for prediction of nuclear parameters

    International Nuclear Information System (INIS)

    Pereira Filho, Leonidas; Souto, Kelling Cabral; Machado, Marcelo Dornellas

    2013-01-01

    Dating from 1943, the earliest work on artificial neural networks (ANN), when Warren Mc Cullock and Walter Pitts developed a study on the behavior of the biological neuron, with the goal of creating a mathematical model. Some other work was done until after the 80 witnessed an explosion of interest in ANNs, mainly due to advances in technology, especially microelectronics. Because ANNs are able to solve many problems such as approximation, classification, categorization, prediction and others, they have numerous applications in various areas, including nuclear. Nodal method is adopted as a tool for analyzing core parameters such as boron concentration and pin power peaks for pressurized water reactors. However, this method is extremely slow when it is necessary to perform various core evaluations, for example core reloading optimization. To overcome this difficulty, in this paper a model of Multi-layer Perceptron (MLP) artificial neural network type backpropagation will be trained to predict these values. The main objective of this work is the development of Multi-layer Perceptron (MLP) artificial neural network capable to predict, in very short time, with good accuracy, two important parameters used in the core reloading problem - Boron Concentration and Power Peaking Factor. For the training of the neural networks are provided loading patterns and nuclear data used in cycle 19 of Angra 1 nuclear power plant. Three models of networks are constructed using the same input data and providing the following outputs: 1- Boron Concentration and Power Peaking Factor, 2 - Boron Concentration and 3 - Power Peaking Factor. (author)

  3. Solubility of fragrance raw materials in water: Experimental study, correlations, and Mod. UNIFAC (Do) predictions

    Energy Technology Data Exchange (ETDEWEB)

    Domanska, Urszula, E-mail: ula@ch.pw.edu.p [Department of Physical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw (Poland); Paduszynski, Kamil; Niszczota, Zaneta K. [Department of Physical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw (Poland)

    2011-01-15

    The (liquid + liquid) and (solid + liquid) phase equilibria of nine binary mixtures containing fragrance raw materials (FRM) such as aliphatic ketones and compounds based on cyclohexane with water were investigated. The systems {l_brace}2-heptanone, or 2-nonanone, or 2-undecanone, or 2-tridecanone, or cyclohexyl carboxylic acid (CCA), or cyclohexyl acetic acid (CAA), or 2-cyclohexyl ethanol (2CE) or cyclohexyl acetate (CA), or 2-cyclohexyl ethyl acetate (2CEA) + water (2){r_brace} have been measured by a dynamic method in wide range of temperatures from (290 to 360) K and ambient pressure. For all systems immiscibility in the liquid phase was detected. The experimental data was correlated by means of the NRTL equation, utilizing parameters derived from the (liquid + liquid) equilibrium. Additionally, the binary mixtures were predicted with the Mod. UNIFAC (Do) model, with known from literature parameters, with very good results.

  4. Solubility of fragrance raw materials in water: Experimental study, correlations, and Mod. UNIFAC (Do) predictions

    International Nuclear Information System (INIS)

    Domanska, Urszula; Paduszynski, Kamil; Niszczota, Zaneta K.

    2011-01-01

    The (liquid + liquid) and (solid + liquid) phase equilibria of nine binary mixtures containing fragrance raw materials (FRM) such as aliphatic ketones and compounds based on cyclohexane with water were investigated. The systems {2-heptanone, or 2-nonanone, or 2-undecanone, or 2-tridecanone, or cyclohexyl carboxylic acid (CCA), or cyclohexyl acetic acid (CAA), or 2-cyclohexyl ethanol (2CE) or cyclohexyl acetate (CA), or 2-cyclohexyl ethyl acetate (2CEA) + water (2)} have been measured by a dynamic method in wide range of temperatures from (290 to 360) K and ambient pressure. For all systems immiscibility in the liquid phase was detected. The experimental data was correlated by means of the NRTL equation, utilizing parameters derived from the (liquid + liquid) equilibrium. Additionally, the binary mixtures were predicted with the Mod. UNIFAC (Do) model, with known from literature parameters, with very good results.

  5. Mathematical models to predict rheological parameters of lateritic hydromixtures

    Directory of Open Access Journals (Sweden)

    Gabriel Hernández-Ramírez

    2017-10-01

    Full Text Available The present work had as objective to establish mathematical models that allow the prognosis of the rheological parameters of the lateritic pulp at concentrations of solids from 35% to 48%, temperature of the preheated hydromixture superior to 82 ° C and number of mineral between 3 and 16. Four samples of lateritic pulp were used in the study at different process locations. The results allowed defining that the plastic properties of the lateritic pulp in the conditions of this study conform to the Herschel-Bulkley model for real plastics. In addition, they show that for current operating conditions, even for new situations, UPD mathematical models have a greater ability to predict rheological parameters than least squares mathematical models.

  6. High serum soluble CD30 does not predict acute rejection in liver transplant patients.

    Science.gov (United States)

    Matinlauri, I; Höckerstedt, K; Isoniemi, H

    2006-12-01

    Increased pre- and posttransplantation values of soluble CD30 (sCD30) have been shown to be associated with acute kidney transplant rejection. We sought to study whether high sCD30 could predict rejection early after liver transplantation. The study population included 54 consecutive liver transplant patients, whose samples were collected before liver transplantation and at discharge, which was at a mean time of 3 weeks after transplantation. During the first 6 months posttransplantation, 22 patients experienced an acute rejection episode. Serum sCD30 concentrations were measured by an enzyme-linked immunoassay; changes in serum sCD30 levels posttransplantation were also expressed as relative values compared with pretransplantation results. Liver patients before transplantation displayed higher serum sCD30 values compared with healthy controls: mean values +/- SD were 93 +/- 58 IU/mL vs 17 +/- 8 IU/mL, respectively. At 3 weeks after transplantation the mean sCD30 concentration in liver transplant patients decreased to 59 +/- 42 IU/mL (P = .005). The mean pretransplantation serum sCD30 value was slightly lower among rejecting vs nonrejecting patients: 78 +/- 43 IU/mL vs 104 +/- 65 IU/mL (P = NS). Posttransplantation values in both groups decreased significantly: 47 +/- 34 IU/mL in patients with rejection (P = .014) vs 69 +/- 45 IU/mL in patients without rejection (P = .012). The relative value at 3 weeks posttransplantation decreased slightly more among patients with vs without rejection (70% vs 88%; NS). No correlation was found between serum sCD30 and anti-HLA class I antibodies or crossmatch positivity. In conclusion, neither pre- nor posttransplantation sCD30 levels were associated with acute rejection in liver transplant patients.

  7. Soluble CD30 levels in recipients undergoing heart transplantation do not predict post-transplant outcome.

    Science.gov (United States)

    Ypsilantis, Efthymios; Key, Timothy; Bradley, J Andrew; Morgan, C Helen; Tsui, Stephen; Parameshwar, Jayan; Taylor, Craig J

    2009-11-01

    The pre-transplant serum level of soluble CD30 (sCD30), a proteolytic derivative of the lymphocyte surface receptor CD30, has been suggested as a biomarker for immunologic risk after organ transplantation. Pre-transplant serum sCD30 levels were determined in 200 consecutive adult heart transplant recipients undertaken at a single center. Transplant outcome (acute rejection in the first 12 months and patient survival up to 5 years post-transplant) was determined. Patients treated with a left ventricular assist device (LVAD) prior to transplantation (n = 28) had higher levels of sCD30 (median 64 U/ml, range 12 to 112 U/ml) than those (n = 172) with no LVAD (median 36 U/ml, range 1 to 158 U/ml, p sCD30 levels were "low" (lower quartile, 58 U/ml, n = 50). Neither acute rejection nor recipient survival differed according to sCD30 level, with values (mean +/- SEM) of 0.30 +/- 0.04, 0.23 +/- 0.03 and 0.30 +/- 0.05 acute rejection episodes per 100 days in the low, intermediate and high groups, respectively, with recipient survival rates at 1 year of 77.7%, 84.9% and 86% and at 5 years of 73.6%, 67.9% and 75.8%, respectively. Pre-transplant serum sCD30 level does not predict acute allograft rejection or recipient survival after heart transplantation, although sCD30 levels are increased by LVAD, possibly as a result of biomaterial-host immune interaction.

  8. Representative parameter of immunostimulatory ginseng polysaccharide to predict radioprotection

    Energy Technology Data Exchange (ETDEWEB)

    Son, Hyeog Jin; Shim, Ji Young; Ahn, Ji Yeon; Yun, Yeon Sook; Song, Jie Young [Korea Institute of Radiological and Medical Sciences, Seoul (Korea, Republic of)

    2008-09-15

    According to the increase in the use of radiotherapy to cancer patients, many approaches have been tried to develop new agents for the protection of surrounding normal tissues. However, it is still few applied in the clinic as a radioprotector. We aim to find a representative parameter for radioprotection to easily predict the activity of in vivo experiment from the results of in vitro screening. The polysaccharide extracted from Panax ginseng was used in this study because the immunostimulator has been regarded as one of the radioprotective agent category and was already reported having a promising radioprotective activity through the increase of hematopoietic cells and the production of several cytokines. Mitogenic activity, AK cells activity and nitric oxide production were monitored for the in vitro immunological assay, and endogenous Colony-Forming Unit (e-CFU) was measured as in vivo radioprotective parameter. The immunological activity was increased by the galactose contents of ginseng polysaccharide dependently. The result of this study suggests that mitogenic activity of splenocytes demonstrated a good correlation with in vivo radioprotective effect, and may be used as a representative parameter to screen the candidates for radioprotector.

  9. Do Urinary Cystine Parameters Predict Clinical Stone Activity?

    Science.gov (United States)

    Friedlander, Justin I; Antonelli, Jodi A; Canvasser, Noah E; Morgan, Monica S C; Mollengarden, Daniel; Best, Sara; Pearle, Margaret S

    2018-02-01

    An accurate urinary predictor of stone recurrence would be clinically advantageous for patients with cystinuria. A proprietary assay (Litholink, Chicago, Illinois) measures cystine capacity as a potentially more reliable estimate of stone forming propensity. The recommended capacity level to prevent stone formation, which is greater than 150 mg/l, has not been directly correlated with clinical stone activity. We investigated the relationship between urinary cystine parameters and clinical stone activity. We prospectively followed 48 patients with cystinuria using 24-hour urine collections and serial imaging, and recorded stone activity. We compared cystine urinary parameters at times of stone activity with those obtained during periods of stone quiescence. We then performed correlation and ROC analysis to evaluate the performance of cystine parameters to predict stone activity. During a median followup of 70.6 months (range 2.2 to 274.6) 85 stone events occurred which could be linked to a recent urine collection. Cystine capacity was significantly greater for quiescent urine than for stone event urine (mean ± SD 48 ± 107 vs -38 ± 163 mg/l, p stone activity (r = -0.29, p r = -0.88, p r = -0.87, p stone quiescence. Decreasing the cutoff to 90 mg/l or greater improved sensitivity to 25.2% while maintaining specificity at 90.9%. Our results suggest that the target for capacity should be lower than previously advised. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  10. Structural and solubility parameter correlations of gelation abilities for dihydroxylated derivatives of long-chain, naturally occurring fatty acids.

    Science.gov (United States)

    Zhang, Mohan; Selvakumar, Sermadurai; Zhang, Xinran; Sibi, Mukund P; Weiss, Richard G

    2015-06-01

    Creating structure-property correlations at different distance scales is one of the important challenges to the rational design of molecular gelators. Here, a series of dihydroxylated derivatives of long-chain fatty acids, derived from three naturally occurring molecules-oleic, erucic and ricinoleic acids-are investigated as gelators of a wide variety of liquids. Conclusions about what constitutes a more (or less!) efficient gelator are based upon analyses of a variety of thermal, structural, molecular modeling, and rheological results. Correlations between the manner of molecular packing in the neat solid or gel states of the gelators and Hansen solubility data from the liquids leads to the conclusion that diol stereochemistry, the number of carbon atoms separating the two hydroxyl groups, and the length of the alkanoic chains are the most important structural parameters controlling efficiency of gel formation for these gelators. Some of the diol gelators are as efficient or even more efficient than the well-known, excellent gelator, (R)-12-hydroxystearic acid; others are much worse. The ability to form extensive intermolecular H-bonding networks along the alkyl chains appears to play a key role in promoting fiber growth and, thus, gelation. In toto, the results demonstrate how the efficiency of gelation can be modulated by very small structural changes and also suggest how other structural modifications may be exploited to create efficient gelators. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Evaluating the influence of process parameters on soluble microbial products formation using response surface methodology coupled with grey relational analysis.

    Science.gov (United States)

    Xu, Juan; Sheng, Guo-Ping; Luo, Hong-Wei; Fang, Fang; Li, Wen-Wei; Zeng, Raymond J; Tong, Zhong-Hua; Yu, Han-Qing

    2011-01-01

    Soluble microbial products (SMPs) present a major part of residual chemical oxygen demand (COD) in the effluents from biological wastewater treatment systems, and the SMP formation is greatly influenced by a variety of process parameters. In this study, response surface methodology (RSM) coupled with grey relational analysis (GRA) method was used to evaluate the effects of substrate concentration, temperature, NH(4)(+)-N concentration and aeration rate on the SMP production in batch activated sludge reactors. Carbohydrates were found to be the major component of SMP, and the influential priorities of these factors were: temperature>substrate concentration > aeration rate > NH(4)(+)-N concentration. On the basis of the RSM results, the interactive effects of these factors on the SMP formation were evaluated, and the optimal operating conditions for a minimum SMP production in such a batch activated sludge system also were identified. These results provide useful information about how to control the SMP formation of activated sludge and ensure the bioreactor high-quality effluent. Copyright © 2010 Elsevier Ltd. All rights reserved.

  12. Major Source of Error in QSPR Prediction of Intrinsic Thermodynamic Solubility of Drugs: Solid vs Nonsolid State Contributions?

    Science.gov (United States)

    Abramov, Yuriy A

    2015-06-01

    The main purpose of this study is to define the major limiting factor in the accuracy of the quantitative structure-property relationship (QSPR) models of the thermodynamic intrinsic aqueous solubility of the drug-like compounds. For doing this, the thermodynamic intrinsic aqueous solubility property was suggested to be indirectly "measured" from the contributions of solid state, ΔGfus, and nonsolid state, ΔGmix, properties, which are estimated by the corresponding QSPR models. The QSPR models of ΔGfus and ΔGmix properties were built based on a set of drug-like compounds with available accurate measurements of fusion and thermodynamic solubility properties. For consistency ΔGfus and ΔGmix models were developed using similar algorithms and descriptor sets, and validated against the similar test compounds. Analysis of the relative performances of these two QSPR models clearly demonstrates that it is the solid state contribution which is the limiting factor in the accuracy and predictive power of the QSPR models of the thermodynamic intrinsic solubility. The performed analysis outlines a necessity of development of new descriptor sets for an accurate description of the long-range order (periodicity) phenomenon in the crystalline state. The proposed approach to the analysis of limitations and suggestions for improvement of QSPR-type models may be generalized to other applications in the pharmaceutical industry.

  13. Prediction and correlation of high-pressure gas solubility in polymers with simplified PC-SAFT

    DEFF Research Database (Denmark)

    von Solms, Nicolas; Michelsen, Michael Locht; Kontogeorgis, Georgios

    2005-01-01

    Using simplified PC-SAFT we have modeled gas solubilities at high temperatures and pressures for the gases methane and carbon dioxide in each of the three polymers high-density polyethylene (HDPE), nylon polyamide-11 (PA-11), and poly(vinylidene fluoride) (PVDF). In general the results are satisf......Using simplified PC-SAFT we have modeled gas solubilities at high temperatures and pressures for the gases methane and carbon dioxide in each of the three polymers high-density polyethylene (HDPE), nylon polyamide-11 (PA-11), and poly(vinylidene fluoride) (PVDF). In general the results...

  14. Macrophage activation marker soluble CD163 may predict disease progression in hepatocellular carcinoma

    DEFF Research Database (Denmark)

    Kazankov, Konstantin; Rode, Anthony; Simonsen, Kira Schreiner

    2016-01-01

    BACKGROUND: Tumor associated macrophages are present in hepatocellular carcinoma (HCC) and associated with a poor prognosis. The aim of the present study was to investigate the levels and dynamics of soluble (s)CD163, a specific macrophage activation marker, in patients with HCC. METHODS: In a co...

  15. Predicting the solubility of mixtures of sugars and their replacers using the Flory-Huggins theory

    NARCIS (Netherlands)

    Sman, van der R.G.M.

    2017-01-01

    In this paper we investigate whether the Flory-Huggins theory can describe the thermodynamics of solutions of simple carbohydrates, like sugars and polyols. In particular, we focus on the description of the solubility of the carbohydrates in water. This is investigated for both binary and ternary

  16. Fasting serum soluble CD 163 predicts risk of type 2 diabetes in ...

    African Journals Online (AJOL)

    grade inflammation is believed to play a central role in the evolution of type 2 diabetes. Aim: To assess whether a new macrophage-derived biomarker, soluble CD163, identifies at-risk individuals with metabolic syndrome before overt disease ...

  17. Serum soluble CD163 predicts risk of type 2 diabetes in the general population

    DEFF Research Database (Denmark)

    Møller, Holger Jon; Frikke-Schmidt, Ruth; Moestrup, Søren

    2011-01-01

    Activation of adipose tissue macrophages with concomitant low-grade inflammation is believed to play a central role in the development of type 2 diabetes. We tested whether a new macrophage-derived biomarker, soluble CD163 (sCD163), identifies at-risk individuals before overt disease has developed....

  18. Consideration on thermodynamic data for predicting solubility and chemical species of elements in groundwater. Part 1: Tc, U, Am

    Energy Technology Data Exchange (ETDEWEB)

    Yamaguchi, Tetsuji; Takeda, Seiji [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    1999-01-01

    The solubility determines the release of radionuclides from waste form and is used as a source term in radionuclide migration analysis in performance assessment of radioactive waste repository. Complexations of radionuclides by ligands in groundwater affect the interaction between radionuclides and geologic media, thus affect their migration behavior. Thermodynamic data for Tc, Am and U were reviewed and compiled to be used for predicting the solubility and chemical species in groundwater. Thermodynamic data were reviewed with emphasis on the hydrolysis and carbonate complexation that can dominate the speciation in typical groundwater. Thermodynamic data for other species were selected based on existing database. Thermodynamic data for other important elements are under investigation, thus shown in an appendix for temporary use. (author)

  19. Consideration on thermodynamic data for predicting solubility and chemical species of elements in groundwater. Part 2: Np, Pu

    International Nuclear Information System (INIS)

    Yamaguchi, Tetsuji

    2000-11-01

    The solubility determines the release of a radionuclide from waste form and is used as a source term in radionuclide migration analysis in performance assessment of radioactive waste repository. Complexations of the radionuclide by ligands in groundwater affect the interaction between radionuclides and geologic media, thus affect their migration behavior. It is essential to estimate the solubility and to predict the chemical species for the radionuclide based on thermodynamic data. The thermodynamic data of aqueous species and compounds were reviewed and compiled for Np and Pu. Thermodynamic data were reviewed with emphasis on the hydrolysis and carbonate complexation that can dominate the speciation in groundwater. Thermodynamic data for other species were selected based on existing databases. Thermodynamic data for other important elements are under investigation, thus shown in an appendix for temporary use. (author)

  20. Achieving concentrated graphene dispersions in water/acetone mixtures by the strategy of tailoring Hansen solubility parameters

    International Nuclear Information System (INIS)

    Yi Min; Shen Zhigang; Zhang Xiaojing; Ma Shulin

    2013-01-01

    Although exfoliating graphite to give graphene paves a new way for graphene preparation, a general strategy of low-boiling-point solvents and high graphene concentration is still highly required. In this study, using the strategy of tailoring Hansen solubility parameters (HSP), a method based on exfoliation of graphite in water/acetone mixtures is demonstrated to achieve concentrated graphene dispersions. It is found that in the scope of blending two mediocre solvents, tailoring the HSP of water/acetone mixtures to approach the HSP of graphene could yield graphene dispersions at a high concentration of up to 0.21 mg ml -1 . The experimentally determined optimum composition of the mixtures occurs at an acetone mass fraction of ∼75%. The trend of concentration varying with mixture compositions could be well predicated by the model, which relates the concentration to the mixing enthalpy within the scope of HSP theory. The resultant dispersion is highly stabilized. Atomic force microscopic statistical analysis shows that up to ∼50% of the prepared nanosheets are less than 1 nm thick after 4 h sonication and 114g centrifugation. Analyses based on diverse characterizations indicate the graphene sheets to be largely free of basal plane defects and oxidation. The filtered films are also investigated in terms of their electrical and optical properties to show reasonable conductivity and transparency. The strategy of tailoring HSP, which can be easily extended to various solvent systems, and water/acetone mixtures here, extends the scope for large-scale production of graphene in low-boiling-point solutions.

  1. Evaluation Of The Integrated Solubility Model, A Graded Approach For Predicting Phase Distribution In Hanford Tank Waste

    International Nuclear Information System (INIS)

    Pierson, Kayla L.; Belsher, Jeremy D.; Seniow, Kendra R.

    2012-01-01

    The mission of the DOE River Protection Project (RPP) is to store, retrieve, treat and dispose of Hanford's tank waste. Waste is retrieved from the underground tanks and delivered to the Waste Treatment and Immobilization Plant (WTP). Waste is processed through a pretreatment facility where it is separated into low activity waste (LAW), which is primarily liquid, and high level waste (HLW), which is primarily solid. The LAW and HLW are sent to two different vitrification facilities and glass canisters are then disposed of onsite (for LAW) or shipped off-site (for HLW). The RPP mission is modeled by the Hanford Tank Waste Operations Simulator (HTWOS), a dynamic flowsheet simulator and mass balance model that is used for mission analysis and strategic planning. The integrated solubility model (ISM) was developed to improve the chemistry basis in HTWOS and better predict the outcome of the RPP mission. The ISM uses a graded approach to focus on the components that have the greatest impact to the mission while building the infrastructure for continued future improvement and expansion. Components in the ISM are grouped depending upon their relative solubility and impact to the RPP mission. The solubility of each group of components is characterized by sub-models of varying levels of complexity, ranging from simplified correlations to a set of Pitzer equations used for the minimization of Gibbs Energy

  2. Evaluation Of The Integrated Solubility Model, A Graded Approach For Predicting Phase Distribution In Hanford Tank Waste

    Energy Technology Data Exchange (ETDEWEB)

    Pierson, Kayla L.; Belsher, Jeremy D.; Seniow, Kendra R.

    2012-10-19

    The mission of the DOE River Protection Project (RPP) is to store, retrieve, treat and dispose of Hanford's tank waste. Waste is retrieved from the underground tanks and delivered to the Waste Treatment and Immobilization Plant (WTP). Waste is processed through a pretreatment facility where it is separated into low activity waste (LAW), which is primarily liquid, and high level waste (HLW), which is primarily solid. The LAW and HLW are sent to two different vitrification facilities and glass canisters are then disposed of onsite (for LAW) or shipped off-site (for HLW). The RPP mission is modeled by the Hanford Tank Waste Operations Simulator (HTWOS), a dynamic flowsheet simulator and mass balance model that is used for mission analysis and strategic planning. The integrated solubility model (ISM) was developed to improve the chemistry basis in HTWOS and better predict the outcome of the RPP mission. The ISM uses a graded approach to focus on the components that have the greatest impact to the mission while building the infrastructure for continued future improvement and expansion. Components in the ISM are grouped depending upon their relative solubility and impact to the RPP mission. The solubility of each group of components is characterized by sub-models of varying levels of complexity, ranging from simplified correlations to a set of Pitzer equations used for the minimization of Gibbs Energy.

  3. Parameter estimation and prediction of nonlinear biological systems: some examples

    NARCIS (Netherlands)

    Doeswijk, T.G.; Keesman, K.J.

    2006-01-01

    Rearranging and reparameterizing a discrete-time nonlinear model with polynomial quotient structure in input, output and parameters (xk = f(Z, p)) leads to a model linear in its (new) parameters. As a result, the parameter estimation problem becomes a so-called errors-in-variables problem for which

  4. Predictive parameters of infectiologic complications in patients after TIPSS

    International Nuclear Information System (INIS)

    Cohnen, M.; Saleh, A.; Moedder, U.; Luethen, R.; Bode, J.; Haeussinger, D.; Daeubener, W.

    2003-01-01

    Aim To define predictive parameters of a complicated clinical course after the TIPSS procedure. Blood cultures were drawn prospectively in 41 patients from a central line and from the portal venous blood before stent placement as well as from the central line 20 min after intervention. C-reactive proteine (CRP) (mg/dl) and white blood cell count (WBC,/μl) on the day of TIPSS-procedure (d0), the first (d1) and seven (d7) days after TIPSS were compared in patients with a complicated clinical course (spontaneous bacterial peritonitis, pneumonia, sepsis; group I) to patients without clinical complications (group II) Group I showed a significant increase in CRP (d0: 1.8±1.0; d1: 3.2±1.5; d7: 4.3±3.2), and white blood cell count (d0: 7700±2600; d1: 10800±2800; d7: 7500±1800) on the first day after TIPSS-procedure in comparison to group II (CRP: d0: 1.6±0.6; d1: 1.8±1.0; d7: 1.9±0.6. WBC: d0: 6900±1500; d1: 8000±1600; d7: 7600±1400).Microbiological analysis showed in 12% skin or oral flora in the last sample. The course of CRP and WBC-count during the first week after TIPSS procedure may indicate patients with a potential risk of a complicated clinical course. (orig.) [de

  5. Macrophage serum markers in pneumococcal bacteremia: Prediction of survival by soluble CD163

    DEFF Research Database (Denmark)

    Møller, Holger Jon; K. Moestrup, Søren; Weis, Nina Margrethe

    2006-01-01

    OBJECTIVE: Soluble CD163 (sCD163) is a new macrophage-specific serum marker. This study investigated sCD163 and other markers of macrophage activation (neopterin, ferritin, transcobalamin, and soluble urokinase plasminogen activator receptor [suPAR]) as prognostic factors in patients...... analyses at the time of first positive blood culture. MEASUREMENTS AND MAIN RESULTS: sCD163 was highly correlated with other macrophage markers and was significantly elevated (median [25-75 percentiles], 4.6 mg/L [2.8-8.9]) compared with healthy controls (2.7 mg/L [2.1-3.3], p ..., all macrophage markers were increased in patients who died from their infection compared with survivors, whereas no change was observed in any of the markers in the very old age. At cutoff levels of 9.5 mg/L (sCD163) and 1650 nmol/L (C-reactive protein), the relative risk for fatal outcome in patients...

  6. Nonlinear Time Series Prediction Using LS-SVM with Chaotic Mutation Evolutionary Programming for Parameter Optimization

    International Nuclear Information System (INIS)

    Xu Ruirui; Chen Tianlun; Gao Chengfeng

    2006-01-01

    Nonlinear time series prediction is studied by using an improved least squares support vector machine (LS-SVM) regression based on chaotic mutation evolutionary programming (CMEP) approach for parameter optimization. We analyze how the prediction error varies with different parameters (σ, γ) in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.

  7. Prediction of response to medical therapy by serum soluble (pro)renin receptor levels in Graves' disease.

    Science.gov (United States)

    Mizuguchi, Yuki; Morimoto, Satoshi; Kimura, Shihori; Takano, Noriyoshi; Yamashita, Kaoru; Seki, Yasufumi; Bokuda, Kanako; Yatabe, Midori; Yatabe, Junichi; Watanabe, Daisuke; Ando, Takashi; Ichihara, Atsuhiro

    2018-01-01

    Antithyroid drugs are generally selected as the first-line treatment for Graves' Disease (GD); however, the existence of patients showing resistance or severe side effects to these drugs is an important issue to be solved. The (pro)renin receptor [(P)RR] is a multi-functional protein that activates the tissue renin-angiotensin system and is an essential constituent of vacuolar H+-ATPase, necessary for the autophagy-lysosome pathway. (P)RR is cleaved to soluble (s)(P)RR, which reflects the status of (P)RR expression. In this retrospective study, we aimed to investigate whether serum s(P)RR concentration can be used as a biomarker to predict the outcome of antithyroid drug treatment in GD patients. Serum s(P)RR levels were measured in 54 untreated GD patients and 47 control participants. Effects of medical treatment with antithyroid drugs on these levels were investigated in GD patients. Serum s(P)RR levels were significantly higher in patients with Graves' disease than in control subjects (PGraves' disease. High serum s(P)RR levels were associated with resistance to antithyroid drug treatment, suggesting that serum s(P)RR concentration can be used as a useful biomarker to predict the outcome of antithyroid drug treatment in these patients. Patients with Graves' disease with low body mass index showed higher levels of serum soluble (pro)renin receptor levels than those with high body mass index. In addition, in patients with Graves' disease, serum triglyceride levels were negatively correlated with serum soluble (pro)renin receptor levels. All these data indicated an association between low nutrient condition due to hyperthyroidism and increased (pro)renin receptor expression in these patients, suggesting that (pro)renin receptor expression could be increased in the process of stimulating intracellular energy production via activating autophagy function to compensate energy loss.

  8. Prediction of response to medical therapy by serum soluble (pro)renin receptor levels in Graves’ disease

    Science.gov (United States)

    Kimura, Shihori; Takano, Noriyoshi; Yamashita, Kaoru; Seki, Yasufumi; Bokuda, Kanako; Yatabe, Midori; Yatabe, Junichi; Watanabe, Daisuke; Ando, Takashi

    2018-01-01

    Antithyroid drugs are generally selected as the first-line treatment for Graves’ Disease (GD); however, the existence of patients showing resistance or severe side effects to these drugs is an important issue to be solved. The (pro)renin receptor [(P)RR] is a multi-functional protein that activates the tissue renin-angiotensin system and is an essential constituent of vacuolar H+-ATPase, necessary for the autophagy-lysosome pathway. (P)RR is cleaved to soluble (s)(P)RR, which reflects the status of (P)RR expression. In this retrospective study, we aimed to investigate whether serum s(P)RR concentration can be used as a biomarker to predict the outcome of antithyroid drug treatment in GD patients. Serum s(P)RR levels were measured in 54 untreated GD patients and 47 control participants. Effects of medical treatment with antithyroid drugs on these levels were investigated in GD patients. Serum s(P)RR levels were significantly higher in patients with Graves’ disease than in control subjects (Pantithyroid drug treatment, suggesting that serum s(P)RR concentration can be used as a useful biomarker to predict the outcome of antithyroid drug treatment in these patients. Patients with Graves’ disease with low body mass index showed higher levels of serum soluble (pro)renin receptor levels than those with high body mass index. In addition, in patients with Graves’ disease, serum triglyceride levels were negatively correlated with serum soluble (pro)renin receptor levels. All these data indicated an association between low nutrient condition due to hyperthyroidism and increased (pro)renin receptor expression in these patients, suggesting that (pro)renin receptor expression could be increased in the process of stimulating intracellular energy production via activating autophagy function to compensate energy loss. PMID:29621332

  9. Prediction of environmental parameters of polycyclic aromatic hydrocarbons with COSMO-RS

    NARCIS (Netherlands)

    Schröder, B.; Santos, L.M.N.B.F.; Alves da Rocha, M.A.; Oliveira, M.B.; Marrucho, I.M.; Coutinho, J.A.P.

    2010-01-01

    The methodology for the prediction of properties of environmental relevance of polycyclic aromatic hydrocarbons based on the conductor-like screening model for real solvents (COSMO-RS/COSMOtherm) is presented and evaluated, with a special focus on the aqueous solubility of polycyclic aromatic

  10. Serum soluble CD163 predicts risk of type 2 diabetes in the general population

    DEFF Research Database (Denmark)

    Møller, Holger J; Frikke-Schmidt, Ruth; Moestrup, Søren K

    2011-01-01

    has developed. METHODS: A prospective cohort study of 8849 study participants from the general population, the Copenhagen City Heart Study, was followed for 18 years for incidence of type 2 diabetes. Risk of disease was calculated according to age- and sex-adjusted percentile categories of serum s......BACKGROUND: Activation of adipose tissue macrophages with concomitant low-grade inflammation is believed to play a central role in the development of type 2 diabetes. We tested whether a new macrophage-derived biomarker, soluble CD163 (sCD163), identifies at-risk individuals before overt disease......CD163 concentrations: 0%-33%, 34%-66%, 67%-90%, 91%-95%, and 96%-100%. RESULTS: A total of 568 participants developed type 2 diabetes. The cumulative incidence increased with increasing baseline sCD163 (trend P

  11. Parameter transferability within homogeneous regions and comparisons with predictions from a priori parameters in the eastern United States

    Science.gov (United States)

    Chouaib, Wafa; Alila, Younes; Caldwell, Peter V.

    2018-05-01

    The need for predictions of flow time-series persists at ungauged catchments, motivating the research goals of our study. By means of the Sacramento model, this paper explores the use of parameter transfer within homogeneous regions of similar climate and flow characteristics and makes comparisons with predictions from a priori parameters. We assessed the performance using the Nash-Sutcliffe (NS), bias, mean monthly hydrograph and flow duration curve (FDC). The study was conducted on a large dataset of 73 catchments within the eastern US. Two approaches to the parameter transferability were developed and evaluated; (i) the within homogeneous region parameter transfer using one donor catchment specific to each region, (ii) the parameter transfer disregarding the geographical limits of homogeneous regions, where one donor catchment was common to all regions. Comparisons between both parameter transfers enabled to assess the gain in performance from the parameter regionalization and its respective constraints and limitations. The parameter transfer within homogeneous regions outperformed the a priori parameters and led to a decrease in bias and increase in efficiency reaching a median NS of 0.77 and a NS of 0.85 at individual catchments. The use of FDC revealed the effect of bias on the inaccuracy of prediction from parameter transfer. In one specific region, of mountainous and forested catchments, the prediction accuracy of the parameter transfer was less satisfactory and equivalent to a priori parameters. In this region, the parameter transfer from the outsider catchment provided the best performance; less-biased with smaller uncertainty in medium flow percentiles (40%-60%). The large disparity of energy conditions explained the lack of performance from parameter transfer in this region. Besides, the subsurface stormflow is predominant and there is a likelihood of lateral preferential flow, which according to its specific properties further explained the reduced

  12. Wavelet neural network modeling in QSPR for prediction of solubility of 25 anthraquinone dyes at different temperatures and pressures in supercritical carbon dioxide.

    Science.gov (United States)

    Tabaraki, R; Khayamian, T; Ensafi, A A

    2006-09-01

    A wavelet neural network (WNN) model in quantitative structure property relationship (QSPR) was developed for predicting solubility of 25 anthraquinone dyes in supercritical carbon dioxide over a wide range of pressures (70-770 bar) and temperatures (291-423 K). A large number of descriptors were calculated with Dragon software and a subset of calculated descriptors was selected from 18 classes of Dragon descriptors with a stepwise multiple linear regression (MLR) as a feature selection technique. Six calculated and two experimental descriptors, pressure and temperature, were selected as the most feasible descriptors. The selected descriptors were used as input nodes in a wavelet neural network (WNN) model. The wavelet neural network architecture and its parameters were optimized simultaneously. The data was randomly divided to the training, prediction and validation sets. The predictive ability of the model was evaluated using validation data set. The root mean squares error (RMSE) and mean absolute errors were 0.339 and 0.221, respectively, for the validation data set. The performance of the WNN model was also compared with artificial neural network (ANN) model and the results showed the superiority of the WNN over ANN model.

  13. Prediction of meteorological parameters - 3: Rainfall and droughts

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-11-01

    We describe two new methods by which rainfall and hence meteorological droughts at any location on the earth may be predicted. The first method is based upon well supported observations that rainfall distribution at a given location during any local sunspot-related temperature/heat cycle is approximately similar to the distribution during another cycle associated with approximately similar sunspot cycle provided that the two temperature/heat cycles involved are immediately preceded by approximately similar sunspot cycles. The second method is based upon the fact that rainfall belts or patterns seem to be closely related to certain spatial and time-dependent temperature/heat patterns in the earth-atmosphere system. Reasonable predictions of these temperature/heat patterns may be made, and hence the associated rainfall patterns or belts may correspondingly be predicted. Specific examples are given to illustrate the two prediction methods. (author). 12 refs, 11 figs, 1 tab

  14. Thorium oxalate solubility and morphology

    International Nuclear Information System (INIS)

    Monson, P.R. Jr.; Hall, R.

    1981-10-01

    Thorium was used as a stand-in for studying the solubility and precipitation of neptunium and plutonium oxalates. Thorium oxalate solubility was determined over a range of 0.001 to 10.0 in the concentration parameter [H 2 C 2 O 4 ]/[HNO 3 ] 2 . Morphology of thorium oxide made from the oxalate precipitates was characterized by scanning electron microscopy. The different morphologies found for oxalate-lean and oxalate-rich precipitations were in agreement with predictions based on precipitation theory

  15. Comparing and correlating solubility parameters governing the self-assembly of molecular gels using 1,3:2,4-dibenzylidene sorbitol as the gelator.

    Science.gov (United States)

    Lan, Yaqi; Corradini, Maria G; Liu, Xia; May, Tim E; Borondics, Ferenc; Weiss, Richard G; Rogers, Michael A

    2014-12-02

    Solvent properties play a central role in mediating the aggregation and self-assembly of molecular gelators and their growth into fibers. Numerous attempts have been made to correlate the solubility parameters of solvents and gelation abilities of molecular gelators, but a comprehensive comparison of the most important parameters has yet to appear. Here, the degree to which partition coefficients (log P), Henry's law constants (HLC), dipole moments, static relative permittivities (ε(r)), solvatochromic E(T)(30) parameters, Kamlet-Taft parameters (β, α, and π), Catalan's solvatochromic parameters (SPP, SB, and SA), Hildebrand solubility parameters (δ(i)), and Hansen solubility parameters (δ(p), δ(d), δ(h)) and the associated Hansen distance (R(ij)) of 62 solvents (covering a wide range of properties) can be correlated with the self-assembly and gelation of 1,3:2,4-dibenzylidene sorbitol (DBS) gelation, a classic molecular gelator, is assessed systematically. The approach presented describes the basis for each of the parameters and how it can be applied. As such, it is an instructional blueprint for how to assess the appropriate type of solvent parameter for use with other molecular gelators as well as with molecules forming other types of self-assembled materials. The results also reveal several important insights into the factors favoring the gelation of solvents by DBS. The ability of a solvent to accept or donate a hydrogen bond is much more important than solvent polarity in determining whether mixtures with DBS become solutions, clear gels, or opaque gels. Thermodynamically derived parameters could not be correlated to the physical properties of the molecular gels unless they were dissected into their individual HSPs. The DBS solvent phases tend to cluster in regions of Hansen space and are highly influenced by the hydrogen-bonding HSP, δ(h). It is also found that the fate of this molecular gelator, unlike that of polymers, is influenced not only by

  16. Soluble CD163 predicts incident chronic lung, kidney and liver disease in HIV infection

    DEFF Research Database (Denmark)

    Kirkegaard-Klitbo, Ditte M; Mejer, Niels; Knudsen, Troels B

    2017-01-01

    OBJECTIVE: To examine if monocyte and macrophage activity may be on the mechanistic pathway to non-AIDS comorbidity by investigating the associations between plasma-soluble CD163 (sCD163) and incident non-AIDS comorbidities in well treated HIV-infected individuals. DESIGN: Prospective single...... was examined using multivariable Cox proportional hazards models adjusted for pertinent covariates. RESULTS: In HIV-1-infected individuals (n = 799), the highest quartile of plasma sCD163 was associated with incident chronic lung disease [adjusted hazard ratio (aHR), 3.2; 95% confidence interval (CI): 1.34; 7.......46] and incident chronic kidney disease (aHR, 10.94; 95% CI: 2.32; 51.35), when compared with lowest quartiles. Further, (every 1 mg) increase in plasma sCD163 was positively correlated with incident liver disease (aHR, 1.12; 95% CI: 1.05; 1.19). The sCD163 level was not associated with incident cancer...

  17. Elevated soluble urokinase plasminogen activator receptor (suPAR) predicts mortality in Staphylococcus aureus bacteremia

    DEFF Research Database (Denmark)

    Mölkänen, T; Ruotsalainen, E; Thorball, C W

    2011-01-01

    The soluble form of urokinase-type plasminogen activator receptor (suPAR) is a new inflammatory marker. High suPAR levels have been shown to associate with mortality in cancer and in chronic infections like HIV and tuberculosis, but reports on the role of suPAR in acute bacteremic infections...... are scarce. To elucidate the role of suPAR in a common bacteremic infection, the serum suPAR levels in 59 patients with Staphylococcus aureus bacteremia (SAB) were measured using the suPARnostic ELISA assay and associations to 1-month mortality and with deep infection focus were analyzed. On day three, after...... the first positive blood culture for S. aureus, suPAR levels were higher in 19 fatalities (median 12.3; range 5.7-64.6 ng/mL) than in 40 survivors (median 8.4; range 3.7-17.6 ng/mL, p = 0.002). This difference persisted for 10 days. The presence of deep infection focus was not associated with elevated su...

  18. Increased serum concentrations of soluble ST2 predict mortality after burn injury.

    Science.gov (United States)

    Hacker, Stefan; Dieplinger, Benjamin; Werba, Gregor; Nickl, Stefanie; Roth, Georg A; Krenn, Claus G; Mueller, Thomas; Ankersmit, Hendrik J; Haider, Thomas

    2018-06-27

    Large burn injuries induce a systemic response in affected patients. Soluble ST2 (sST2) acts as a decoy receptor for interleukin-33 (IL-33) and has immunosuppressive effects. sST2 has been described previously as a prognostic serum marker. Our aim was to evaluate serum concentrations of sST2 and IL-33 after thermal injury and elucidate whether sST2 is associated with mortality in these patients. We included 32 burn patients (total body surface area [TBSA] >10%) admitted to our burn intensive care unit and compared them to eight healthy probands. Serum concentrations of sST2 and IL-33 were measured serially using an enzyme-linked immunosorbent assay (ELISA) technique. The mean TBSA was 32.5%±19.6%. Six patients (18.8%) died during the hospital stay. Serum analyses showed significantly increased concentrations of sST2 and reduced concentrations of IL-33 in burn patients compared to healthy controls. In our study cohort, higher serum concentrations of sST2 were a strong independent predictor of mortality. Burn injuries cause an increment of sST2 serum concentrations with a concomitant reduction of IL-33. Higher concentrations of sST2 are associated with increased in-hospital mortality in burn patients.

  19. Wear prediction on total ankle replacement effect of design parameters

    CERN Document Server

    Saad, Amir Putra Bin Md; Harun, Muhamad Noor; Kadir, Mohammed Rafiq Abdul

    2016-01-01

    This book develops and analyses computational wear simulations of the total ankle replacement for the stance phase of gait cycle. The emphasis is put on the relevant design parameters. The book presents a model consisting of three components; tibial, bearing and talar representing their physiological functions.

  20. Preterm delivery predicted by soluble CD163 and CRP in women with symptoms of preterm delivery

    DEFF Research Database (Denmark)

    Vogel, Ida; Grove, Jakob; Thorsen, Poul

    2005-01-01

    : High levels of sCD163 or CRP are associated with an increased risk of preterm delivery in women with symptoms of delivery. Good prediction of preterm delivery before 34 weeks of gestation was obtained by a combination of preterm prelabour rupture of membranes (PPROM), overweight, relaxin, CRP and s...

  1. Variable input parameter influence on river corridor prediction

    NARCIS (Netherlands)

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

    2015-01-01

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

  2. Soluble CD30 and Hepatocyte growth factor as predictive markers of antibody-mediated rejection of the kidney allograft.

    Science.gov (United States)

    Pavlova, Yelena; Viklicky, Ondrej; Slatinska, Janka; Bürgelova, Marcela; Süsal, Caner; Skibova, Jelena; Honsová, Eva; Striz, Ilja; Kolesar, Libor; Slavcev, Antonij

    2011-07-01

    Our retrospective study was aimed to assess the relevance of pre- and post-transplant measurements of serum concentrations of the soluble CD30 molecule (soluble CD30, sCD30) and the cytokine Hepatocyte growth factor (HGF) for prediction of the risk for development of antibody-mediated rejection (AMR) in kidney transplant patients. Evaluation of sCD30, HGF levels and the presence of HLA-specific antibodies in a cohort of 205 patients was performed before, 2weeks and 6months after transplantation. Patients were followed up for kidney graft function and survival for two years. We found a tendency of higher incidence of AMR in retransplanted patients with elevated pre-transplant sCD30 (≥100U/ml) (p=0.051), however no such correlation was observed in first-transplant patients. Kidney recipients with simultaneously high sCD30 and HLA-specific antibodies (sCD30+/Ab+) before transplantation had significantly lower AMR-free survival compared to the other patient groups (psCD30 showed increased incidence of AMR in recipients with elevated pretransplant sCD30 and low HGF levels. the predictive value of pretransplant sCD30 for the development of antibody-mediated rejection after transplantation is significantly potentiated by the co-presence of HLA specific antibodies. The role of HGF as a rejection-protective factor in patients with high pretransplant HGF levels would need further investigation. Copyright © 2011 Elsevier B.V. All rights reserved.

  3. Evaluation of DOE radionuclide solubility data and selected retardation parameters: description of calculational and confirmatory experimental activities

    International Nuclear Information System (INIS)

    Kelmers, A.D.; Clark, R.J.; Cutshall, N.H.; Johnson, J.S.; Kessler, J.H.

    1983-01-01

    An experimentally oriented program has been initiated to support the NRC analysis and licensing activities related to high-level nuclear waste repositories. The program will allow the NRC to independently confirm key geochemical values used in the site performance assessments submitted by the DOE candidate repository site projects. Key radionuclide retardation factor values, particularly radionuclide solubility and sorption values under site specific geochemical conditions, are being confirmed. The initial efforts are being directed toward basalt rock/groundwater systems relevant to the BWIP candidate site in the Pasco Basin. Future work will consider tuff (NNWSI candidate site in Yucca Mountain) and salt (unspecified ONWI bedded or domal salt sites) rock/groundwater systems. Initial experimental results with technetium have confirmed the BWIP values for basalt/groundwater systems under oxic redox conditions: high solubility and no sorption. Under reducing redox conditions, however, the experimental work did not confirm the proposed technetium values recommended by BWIP. In the presence of hydrazine to establish reducing conditions, an apparent solubility limit for technetium of about 5E-7 mol/L was encountered; BWIP recommended calculated values of 1E-12 or greater than or equal to 1E-14 mol/L. Experimental evidence concerning sorption of reduced technetium species is incomplete at this time. Equilibrium speciation and saturation indices were calculated for well water data sets from BWIP using the computer code PHREEQUE. Oversaturation was indicated for hematite and quartz in all data sets. Near surface samples were undersaturated with respect to calcite, but most deep samples were oversaturated with respect to calcite and other carbonate minerals

  4. Serum Soluble Fms-Like Tyrosine Kinase 1 (sFlt-1 Predicts the Severity of Acute Pancreatitis

    Directory of Open Access Journals (Sweden)

    Paulina Dumnicka

    2016-12-01

    Full Text Available Organ failure is the most important determinant of the severity of acute pancreatitis (AP. Soluble fms-like tyrosine kinase 1 (sFlt-1 is positively associated with organ failure in sepsis. Our aim was to evaluate the diagnostic utility of automated sFlt-1 measurements for early prediction of AP severity. Adult patients (66 with AP were recruited, including 46 with mild (MAP, 15 with moderately-severe (MSAP and 5 with severe AP (SAP. Serum and urine samples were collected twice. Serum sFlt-1 was measured with automated electrochemiluminescence immunoassay. Serum concentrations of sFlt-1 were significantly higher in patients with MSAP and SAP as compared to MAP. SAP patients had the highest concentrations. At 24 and 48 h, sFlt-1 positively correlated with inflammatory markers (leukocyte count, C-reactive protein, kidney function (creatinine, urea, cystatin C, serum and urine neutrophil gelatinase-associated lipocalin, urine albumin/creatinine ratio, D-dimer and angiopoietin-2. sFlt-1 positively correlated with the bedside index of severity in AP (BISAP score and the duration of hospital stay. Serum sFlt-1 above 139 pg/mL predicted more severe AP (MSAP + SAP. In the early phase of AP, sFlt-1 is positively associated with the severity of AP and predicts organ failure, in particular kidney failure. Serum sFlt-1 may be a practical way to improve early assessment of AP severity.

  5. Improved prediction of octanol-water partition coefficients from liquid-solute water solubilities and molar volumes

    Science.gov (United States)

    Chiou, C.T.; Schmedding, D.W.; Manes, M.

    2005-01-01

    A volume-fraction-based solvent-water partition model for dilute solutes, in which the partition coefficient shows a dependence on solute molar volume (V??), is adapted to predict the octanol-water partition coefficient (K ow) from the liquid or supercooled-liquid solute water solubility (Sw), or vice versa. The established correlation is tested for a wide range of industrial compounds and pesticides (e.g., halogenated aliphatic hydrocarbons, alkylbenzenes, halogenated benzenes, ethers, esters, PAHs, PCBs, organochlorines, organophosphates, carbamates, and amidesureas-triazines), which comprise a total of 215 test compounds spanning about 10 orders of magnitude in Sw and 8.5 orders of magnitude in Kow. Except for phenols and alcohols, which require special considerations of the Kow data, the correlation predicts the Kow within 0.1 log units for most compounds, much independent of the compound type or the magnitude in K ow. With reliable Sw and V data for compounds of interest, the correlation provides an effective means for either predicting the unavailable log Kow values or verifying the reliability of the reported log Kow data. ?? 2005 American Chemical Society.

  6. Mathematical models to predict rheological parameters of lateritic hydromixtures

    OpenAIRE

    Gabriel Hernández-Ramírez; Arístides A. Legrá-Lobaina; Beatriz Ramírez-Serrano; Liudmila Pérez-García

    2017-01-01

    The present work had as objective to establish mathematical models that allow the prognosis of the rheological parameters of the lateritic pulp at concentrations of solids from 35% to 48%, temperature of the preheated hydromixture superior to 82 ° C and number of mineral between 3 and 16. Four samples of lateritic pulp were used in the study at different process locations. The results allowed defining that the plastic properties of the lateritic pulp in the conditions of this study conform to...

  7. Different Vocal Parameters Predict Perceptions of Dominance and Attractiveness

    OpenAIRE

    Hodges-Simeon, Carolyn R.; Gaulin, Steven J. C.; Puts, David A.

    2010-01-01

    Low mean fundamental frequency (F 0) in men’s voices has been found to positively influence perceptions of dominance by men and attractiveness by women using standardized speech. Using natural speech obtained during an ecologically valid social interaction, we examined relationships between multiple vocal parameters and dominance and attractiveness judgments. Male voices from an unscripted dating game were judged by men for physical and social dominance and by women in fert...

  8. Clinical parameters predictive of malignancy of thyroid follicular neoplasms

    International Nuclear Information System (INIS)

    Davis, N.L.; Gordon, M.; Germann, E.; Robins, R.E.; McGregor, G.I.

    1991-01-01

    Needle aspiration biopsy is commonly employed in the evaluation of thyroid nodules. Unfortunately, the cytologic finding of a 'follicular neoplasm' does not distinguish between a thyroid adenoma and a follicular cancer. The purpose of this study was to identify clinical parameters that characterize patients with an increased risk of having a thyroid follicular cancer who preoperatively have a 'follicular neoplasm' identified by needle aspiration biopsy. A total of 395 patients initially treated at Vancouver General Hospital and the British Columbia Cancer Agency between the years of 1965 and 1985 were identified and their data were entered into a computer database. Patients with thyroid adenomas were compared to patients with follicular cancer using the chi-square test and Student's t-test. Statistically significant parameters that distinguished patients at risk of having a thyroid cancer (p less than 0.05) included age greater than 50 years, nodule size greater than 3 cm, and a history of neck irradiation. Sex, family history of goiter or neoplasm, alcohol and tobacco use, and use of exogenous estrogen were not significant parameters. Patients can be identified preoperatively to be at an increased risk of having a follicular cancer and accordingly appropriate surgical resection can be planned

  9. The Prognostic and Predictive Value of Soluble Type IV Collagen in Colorectal Cancer

    DEFF Research Database (Denmark)

    Rolff, Hans Christian; Christensen, Ib Jarle; Vainer, Ben

    2016-01-01

    PURPOSE: To investigate the prognostic and predictive biomarker value of type IV collagen in colorectal cancer. EXPERIMENTAL DESIGN: Retrospective evaluation of two independent cohorts of patients with colorectal cancer included prospectively in 2004-2005 (training set) and 2006-2008 (validation....... RESULTS: High levels of type IV collagen showed independent prognostic significance in both cohorts with hazard ratios (HRs; for a one-unit change on the log base 2 scale) of 2.25 [95% confidence intervals (CIs), 1.78-2.84; P ... and validation set, respectively. The prognostic impact was present both in patients with metastatic and nonmetastatic disease. The predictive value of the marker was investigated in stage II and III patients. In the training set, type IV collagen was prognostic both in the subsets of patients receiving...

  10. Prediction of Milk Quality Parameters Using Vibrational Spectroscopy and Chemometrics

    DEFF Research Database (Denmark)

    Eskildsen, Carl Emil Aae

    fatty acids, protein fractions and coagulation properties from Fourier transform infrared measurements. This thesis shows how such predictions are trapped in a cage of covariance with major milk constituents like total fat and protein content. The prediction models for detailed milk composition...... are not based on causal relationships and this may seriously compromise calibration robustness. It is not recommended to implement indirect models for detailed milk composition in milk recording or breeding programs as such model are providing information on, for example, total protein rather than the specific...... protein fractions. If Fourier transform infrared based models on detailed milk composition are to be implemented in, for example, breeding programs it is recommended to decompose, for example, the individual fatty acids into functional groups, such as methyl, methylene, olefinic and carboxylic groups...

  11. Hydrological model parameter dimensionality is a weak measure of prediction uncertainty (discussion paper)

    NARCIS (Netherlands)

    Pande, S.; Arkesteijn, L.; Savenije, H.H.G.; Bastidas, L.A.

    2014-01-01

    This paper presents evidence that model prediction uncertainty does not necessarily rise with parameter dimensionality (the number of parameters). Here by prediction we mean future simulation of a variable of interest conditioned on certain future values of input variables. We utilize a relationship

  12. Prediction of compressibility parameters of the soils using artificial neural network.

    Science.gov (United States)

    Kurnaz, T Fikret; Dagdeviren, Ugur; Yildiz, Murat; Ozkan, Ozhan

    2016-01-01

    The compression index and recompression index are one of the important compressibility parameters to determine the settlement calculation for fine-grained soil layers. These parameters can be determined by carrying out laboratory oedometer test on undisturbed samples; however, the test is quite time-consuming and expensive. Therefore, many empirical formulas based on regression analysis have been presented to estimate the compressibility parameters using soil index properties. In this paper, an artificial neural network (ANN) model is suggested for prediction of compressibility parameters from basic soil properties. For this purpose, the input parameters are selected as the natural water content, initial void ratio, liquid limit and plasticity index. In this model, two output parameters, including compression index and recompression index, are predicted in a combined network structure. As the result of the study, proposed ANN model is successful for the prediction of the compression index, however the predicted recompression index values are not satisfying compared to the compression index.

  13. Plasma Levels of Soluble HLA-E and HLA-F at Diagnosis May Predict Overall Survival of Neuroblastoma Patients

    Directory of Open Access Journals (Sweden)

    Fabio Morandi

    2013-01-01

    Full Text Available The purpose of this study was to identify the plasma/serum biomarkers that are able to predict overall survival (OS of neuroblastoma (NB patients. Concentration of soluble (s biomarkers was evaluated in plasma (sHLA-E, sHLA-F, chromogranin, and B7H3 or serum (calprotectin samples from NB patients or healthy children. The levels of biomarkers that were significantly higher in NB patients were then analyzed considering localized or metastatic subsets. Finally, biomarkers that were significantly different in these two subsets were correlated with patient’s outcome. With the exception of B7H3, levels of all molecules were significantly higher in NB patients than those in controls. However, only chromogranin, sHLA-E, and sHLA-F levels were different between patients with metastatic and localized tumors. sHLA-E and -F levels correlated with each other but not chromogranin. Chromogranin levels correlated with different event-free survival (EFS, whereas sHLA-E and -F levels also correlated with different OS. Association with OS was also detected considering only patients with metastatic disease. In conclusion, low levels of sHLA-E and -F significantly associated with worse EFS/OS in the whole cohort of NB patients and in patients with metastatic NB. Thus, these molecules deserve to be tested in prospective studies to evaluate their predictive power for high-risk NB patients.

  14. Evaluation of pre- and posttransplantation serum interferon-gamma and soluble CD30 for predicting liver allograft rejection.

    Science.gov (United States)

    Kim, K H; Oh, E-J; Jung, E-S; Park, Y-J; Choi, J Y; Kim, D-G; Lee, K Y; Kang, C S

    2006-06-01

    The aim of the present study was to identify whether the serum interferon-gamma (IFNgamma), a Th1 cytokine, or soluble CD30 (sCD30), a marker for activation of Th2 cytokine-producing T cells, predict acute cellular rejection episodes among liver graft patients. Pretransplant and posttransplant sera from 32 living donor liver transplant recipients obtained on days 1, 3, and 7 after surgery were tested for serum IFNgamma and sCD30 concentrations using commercial enzyme-linked immunosorbent assay kits. Recipients with an acute rejection episode (ARE) (n=14) displayed significantly higher IFNgamma concentrations pretransplant than did the patients with no ARE (n=18) (PsCD30 were not different between the non-ARE and ARE groups. However, in comparison with the non-ARE group, who showed steadily decreasing serum sCD30 levels after transplantation, 12 among the 14 patients in the ARE group showed increasing sCD30 levels from day 1 to day 3 after transplantation (PsCD30 increment during the early period after liver transplantation affects the immune response of rejection. This observation emphasizes the clinical relevance of serum sCD30, in addition to serum IFNgamma, as predictive markers for acute liver graft rejection.

  15. Deep architectures and deep learning in chemoinformatics: the prediction of aqueous solubility for drug-like molecules.

    Science.gov (United States)

    Lusci, Alessandro; Pollastri, Gianluca; Baldi, Pierre

    2013-07-22

    Shallow machine learning methods have been applied to chemoinformatics problems with some success. As more data becomes available and more complex problems are tackled, deep machine learning methods may also become useful. Here, we present a brief overview of deep learning methods and show in particular how recursive neural network approaches can be applied to the problem of predicting molecular properties. However, molecules are typically described by undirected cyclic graphs, while recursive approaches typically use directed acyclic graphs. Thus, we develop methods to address this discrepancy, essentially by considering an ensemble of recursive neural networks associated with all possible vertex-centered acyclic orientations of the molecular graph. One advantage of this approach is that it relies only minimally on the identification of suitable molecular descriptors because suitable representations are learned automatically from the data. Several variants of this approach are applied to the problem of predicting aqueous solubility and tested on four benchmark data sets. Experimental results show that the performance of the deep learning methods matches or exceeds the performance of other state-of-the-art methods according to several evaluation metrics and expose the fundamental limitations arising from training sets that are too small or too noisy. A Web-based predictor, AquaSol, is available online through the ChemDB portal ( cdb.ics.uci.edu ) together with additional material.

  16. Neptunium (IV) oxalate solubility

    International Nuclear Information System (INIS)

    Luerkens, D.W.

    1983-07-01

    The equilibrium solubility of neptunium (IV) oxalate in nitric/oxalic acid solutions was determined at 22 0 C, 45 0 C, and 60 0 C. The concentrations of nitric/oxalic acid solutions represented a wide range of free oxalate ion concentration. A mathematical solubility model was developed which is based on the formation of the known complexes of neptunium (IV) oxalate. the solubility model uses a simplified concentration parameter which is proportional to the free oxalate ion concentration. The solubility model can be used to estimate the equilibrium solubility of neptunium (IV) oxalate over a wide range of oxalic and nitric acid concentrations at each temperature

  17. Evaluation of accelerated test parameters for CMOS IC total dose hardness prediction

    International Nuclear Information System (INIS)

    Sogoyan, A.V.; Nikiforov, A.Y.; Chumakov, A.I.

    1999-01-01

    The approach to accelerated test parameters evaluation is presented in order to predict CMOS IC total dose behavior in variable dose-rate environment. The technique is based on the analytical model of MOSFET parameters total dose degradation. The simple way to estimate model parameter is proposed using IC's input-output MOSFET radiation test results. (authors)

  18. Cognitive Models of Risky Choice: Parameter Stability and Predictive Accuracy of Prospect Theory

    Science.gov (United States)

    Glockner, Andreas; Pachur, Thorsten

    2012-01-01

    In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are…

  19. Long-range hydrometeorological ensemble predictions of drought parameters

    Science.gov (United States)

    Fundel, F.; Jörg-Hess, S.; Zappa, M.

    2012-06-01

    Low streamflow as consequence of a drought event affects numerous aspects of life. Economic sectors that may be impacted by drought are, e.g. power production, agriculture, tourism and water quality management. Numerical models have increasingly been used to forecast low-flow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the low-flow indices duration, severity and magnitude, with a forecast lead-time of one month, to assess their potential usefulness for predictions. The ECMWF VarEPS 5 member reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification shows that, compared to peak flow, probabilistic low-flow forecasts are skillful for longer lead-times, low-flow index forecasts could also be beneficially included in a decision-making process. The results suggest monthly runoff forecasts are useful for accessing the risk of hydrological droughts.

  20. Prediction of the association state of insulin using spectral parameters.

    Science.gov (United States)

    Uversky, Vladimir N; Garriques, Liza Nielsen; Millett, Ian S; Frokjaer, Sven; Brange, Jens; Doniach, Sebastian; Fink, Anthony L

    2003-04-01

    Human insulin exists in different association states, from monomer to hexamer, depending on the conditions. In the presence of zinc the "normal" state is a hexamer. The structural properties of 20 variants of human insulin were studied by near-UV circular dichroism, fluorescence spectroscopy, and small-angle X-ray scattering (SAXS). The mutants showed different degrees of association (monomer, dimers, tetramers, and hexamers) at neutral pH. A correlation was shown between the accessibility of tyrosines to acrylamide quenching and the degree of association of the insulin mutants. The near-UV CD spectra of the insulins were affected by protein association and by mutation-induced structural perturbations. However, the shape and intensity of difference CD spectra, obtained by subtraction of the spectra measured in 20% acetic acid (where all insulin species were monomeric) from the corresponding spectra measured at neutral pH, correlate well with the degree of insulin association. In fact, the near-UV CD difference spectra for monomeric, dimeric, tetrameric, and hexameric insulin are very distinctive, both in terms of intensity and shape. The results show that the spectral properties of the insulins reflect their state of association, and can be used to predict their oligomeric state. Copyright 2003 Wiley-Liss, Inc. and the American Pharmaceutical Association J Pharm Sci 92:847-858, 2003

  1. Determining the solubility parameter and the cross-link density of medical grade silicones: effect of increasing the range of swelling liquids.

    Science.gov (United States)

    Mahomed, Aziza; Kocharian, Areg

    2015-01-01

    Four samples of four medical grade silicones were swollen in six "good" liquids (i.e. those with a good swelling ability, in which silicones swell appreciably) at 25°C, until they reached constant mass (i.e. equilibrium). The volume fraction, ϕ, of the silicone in the swollen sample was calculated for each grade of silicone. Using a combination of the six ϕ values obtained in this study and four of those obtained in a previous study, for each silicone grade, ϕ was plotted against δl, the liquid solubility parameter for the ten liquids used. Using a curve fitting technique a second-order polynomial was plotted through the data points; the minimum in this polynomial provided a value for δp (the polymer solubility parameter). Furthermore, the results showed that the δp values obtained in this study (using ten liquids) were slightly but significantly greater (pliquids), for grade C6-165 only. Similarly, the χ and υ values obtained in the two studies were only significantly different (p<0.05) from each other, for grade C6-165.

  2. Soluble Suppression of Tumorigenicity-2 Predicts Hospital Mortality in Burn Patients: An Observational Prospective Cohort Pilot Study.

    Science.gov (United States)

    Ruiz-Castilla, Mireia; Bosacoma, Pau; Dos Santos, Bruce; Baena, Jacinto; Guilabert, Patricia; Marin-Corral, Judith; Masclans, Joan R; Roca, Oriol; Barret, Juan P

    2018-04-10

    The IL33/ST2 pathway has been implicated in the pathogenesis of different inflammatory diseases. Our aim was to analyze whether plasma levels of biomarkers involved in the IL33/ST2 axis might help to predict mortality in burn patients. Single-center prospective observational cohort pilot study performed at the Burns Unit of the Plastic and Reconstructive Surgery Department of the Vall d'Hebron University Hospital (Barcelona). All patients aged ≥18 years old with second or third-degree burns requiring admission to the Burns Unit were considered for inclusion. Blood samples were taken to measure levels of interleukins (IL)6, IL8, IL33, and soluble suppression of tumorigenicity-2 (sST2) within 24 h of admission to the Burns Unit and at day 3. Results are expressed as medians and interquartile ranges or as frequencies and percentages. Sixty-nine patients (58 [84.1%] male, mean age 52 [35-63] years, total body surface area burned 21% [13%-30%], Abbreviated Burn Severity Index 6 [4-8]) were included. Thirteen (18.8%) finally died in the Burns Unit. Plasma levels of sST2 measured at day 3 after admission demonstrated the best prediction accuracy for survival (area under the ROC curve 0.85 [0.71-0.99]; P < 0.001). The best cutoff point for the AUROC index was estimated to be 2,561. In the Cox proportional hazards model, after adjusting for potential confounding, a plasma sST2 level ≥2,561 measured at day 3 was significantly associated with mortality (HR 6.94 [1.73-27.74]; P = 0.006). Plasma sST2 at day 3 predicts hospital mortality in burn patients.

  3. A proposal of parameter to predict biaxial fatigue life for CF8M cast stainless steels

    International Nuclear Information System (INIS)

    Park, Joong Cheul; Kwon, Jae Do

    2005-01-01

    Biaxial low cycle fatigue test was carried out to predict fatigue life under combined axial-torsional loading condition which is that of in-phase and out-of-phase for CF8M cast stainless steels. Fatemi Socie(FS) parameter which is based on critical plane approach is not only one of methods but also the best method that can predict fatigue life under biaxial loading condition. But the result showed that, biaxial fatigue life prediction by using FS parameter with several different parameters for the CF8M cast stainless steels is not conservative but best results. So in this present research, we proposed new fatigue life prediction parameter considering effective shear stress instead of FS parameter which considers the maximum normal stress acting on maximum shear strain and its effectiveness was verified

  4. Effect of bubble interface parameters on predicted of bubble departure diameter in a narrow channel

    International Nuclear Information System (INIS)

    Xu Jianjun; Xie Tianzhou; Zhou Wenbin; Chen Bingde; Huang Yanping

    2014-01-01

    The predicted model on the bubble departure diameter in a narrow channel is built by analysis of forces acting on the bubble, and effects of bubble interface parameters such as the bubble inclination angle, upstream contact angle, downstream contact angle and bubble contact diameter on predicted bubble departure diameters in a narrow channel are analysed by comparing with the visual experimental data. Based on the above results, the bubble interface parameters as the input parameters used to obtain the bubble departure diameter in a narrow channel are assured, and the bubble departure diameters in a narrow channel are predicted by solving the force equation. The predicted bubble departure diameters are verified by the 58 bubble departure diameters obtained from the vertical and inclined visual experiment, and the predicted results agree with the experimental results. The different forces acting on the bubble are obtained and the effect of thermal parameters in this experiment on bubble departure diameters is analysed. (authors)

  5. The influence of distillers dried grains with solubles in broiler’s feed mixtures on their growth parameters

    Directory of Open Access Journals (Sweden)

    Šárka Hošková

    2010-01-01

    Full Text Available The effect of distillers dried grains with solubles (DDGS in broiler feed mixtures on the performance was studied in an experiment with 1000 male broiler chickens Ross 308 from 12 to 35 days of age. DDGS were produced from wheat (90 % and triticale (10 %. Cockerels were divided into 5 groups and were housed on deep litter. Experimental feed mixtures were formulated to contain: 0, 10, 15, 20 and 25 % DDGS and were calculated as iso-nitrogenous. Weighing of chickens was realized at the 12th, 26th and 35th day of age. Control group of cockerels (0 % DDGS had the highest final live weight and its average daily weight gain was significantly higher (P < 0.01 than in birds from groups with 10, 15 and 25 % DDGS. Broilers from control group (0 % DDGS had the highest consumption of dry matter of feed mixture per bird. There were no significantly differences in feed consumption per bird and in feed conversion between groups. The results show that incorporation from 10 to 25 % DDGS decreased final weights and weight gains however there were no significantly differences in feed consumption and feed conversion.

  6. A practical approach to parameter estimation applied to model predicting heart rate regulation

    DEFF Research Database (Denmark)

    Olufsen, Mette; Ottesen, Johnny T.

    2013-01-01

    Mathematical models have long been used for prediction of dynamics in biological systems. Recently, several efforts have been made to render these models patient specific. One way to do so is to employ techniques to estimate parameters that enable model based prediction of observed quantities....... Knowledge of variation in parameters within and between groups of subjects have potential to provide insight into biological function. Often it is not possible to estimate all parameters in a given model, in particular if the model is complex and the data is sparse. However, it may be possible to estimate...... a subset of model parameters reducing the complexity of the problem. In this study, we compare three methods that allow identification of parameter subsets that can be estimated given a model and a set of data. These methods will be used to estimate patient specific parameters in a model predicting...

  7. Synthesis of silica nanoparticles for encapsulation of oncology drugs with low water solubility: effect of processing parameters on structural evolution

    Energy Technology Data Exchange (ETDEWEB)

    Bürglová, Kristýna; Hlaváč, Jan [Institute of Molecular and Translational Medicine, Palacký University Olomouc, Faculty of Medicine and Dentistry (Czech Republic); Bartlett, John R., E-mail: JBartlett@usc.edu.au [University of the Sunshine Coast, Faculty of Science, Health, Education and Engineering (Australia)

    2015-12-15

    Silica nanoparticles with tailored properties have been developed for a variety of biomedical applications, with particular emphasis on their use as carriers for the encapsulation and controlled release of bioactive species. Among the various strategies described, silica nanoparticles with uniform mesoporosity (MSN) prepared in aqueous solution at elevated temperatures using cetyltrimethylammonium bromide as a template have a range of desirable properties. However, the processing windows available to control the dimensions and other key properties of such nanoparticles prepared using fluoride salts as catalysts have not been elucidated, with mixed products containing gel fragments and non-uniform products obtained under many conditions. Here, we present a parametric study of the synthesis of MSN under fluoride-catalysed conditions using tetraethylorthosilicate as silica precursor. The processing conditions required to produce uniform nanoparticles with controlled dimensions are elucidated, together with the conditions under which dried powders can be re-dispersed in aqueous solution after long-term storage to regenerate unaggregated nanospheres with dimensions (as measured by dynamic light scattering) comparable to those measured via scanning electron microscopy analysis of the dried material. The ability to dry and store such powders for extended periods of time is an important requirement for the use of such materials in drug delivery applications. Preliminary results demonstrating the use of such MSNs as hosts for oncology drugs [substituted 3-hydroxyquinolinones (3-HQ)] with low water solubility (≪1 µg/g H{sub 2}O) are presented, with loadings of several wt% demonstrated. The ability of the silica host to protect the 3-HQ from oxidative degradation during impregnation and release is discussed.

  8. Application of mixture experimental design to simvastatin apparent solubility predictions in the microemulsifion formed by self-microemulsifying.

    Science.gov (United States)

    Meng, Jian; Zheng, Liangyuan

    2007-09-01

    Self-microemulsifying drug delivery systems (SMEDDS) are useful to improve the bioavailability of poorly water-soluble drugs by increasing their apparent solubility through solubilization. However, very few studies, to date, have systematically examined the level of drug apparent solubility in o/w microemulsion formed by self-microemulsifying. In this study, a mixture experimental design was used to simulate the influence of the compositions on simvastatin apparent solubility quantitatively through an empirical model. The reduced cubic polynomial equation successfully modeled the evolution of simvastatin apparent solubility. The results were presented using an analysis of response surface showing a scale of possible simvastatin apparent solubility between 0.0024 ~ 29.0 mg/mL. Moreover, this technique showed that simvastatin apparent solubility was mainly influenced by microemulsion concentration and, suggested that the drug would precipitate in the gastrointestinal tract due to dilution by gastrointestinal fluids. Furthermore, the model would help us design the formulation to maximize the drug apparent solubility and avoid precipitation of the drug.

  9. Soluble CD30 does not predict late acute rejection or safe tapering of immunosuppression in renal transplantation.

    Science.gov (United States)

    Valke, Lars L F G; van Cranenbroek, Bram; Hilbrands, Luuk B; Joosten, Irma

    2015-01-01

    Previous reports revealed the potential value of the soluble CD30 level (sCD30) as biomarker for the risk of acute rejection and graft failure after renal transplantation, here we examined its use for the prediction of safe tapering of calcineurin inhibitors as well as late acute rejection. In a cohort of renal transplant patients receiving triple immunosuppressive therapy we examined whether sCD30 can be used as a marker for safe (rejection-free) discontinuation of tacrolimus at six months after transplantation (TDS cohort: 24 rejectors and 44 non-rejecting controls). Also, in a second cohort of patients (n=22, rejectors n=11 and non-rejectors n=11), participating in a clinical trial of rituximab as induction therapy after renal transplantation (RITS cohort), we examined whether sCD30 could predict the occurrence of late (>3months post-transplant) acute rejection episodes. sCD30 was measured by ELISA in serum taken before and at several time points after transplantation. Overall, in the TDS cohort sCD30 decreased after transplantation. No difference in sCD30 was observed between rejectors and non-rejecting controls at any of the time points measured. In addition, in the RITS cohort, sCD30 measured at three months after transplantation were not indicative for the occurrence of late acute rejection. In two prospectively followed cohorts of renal transplant patients we found no association between sCD30 and the occurrence of either late acute rejection or acute rejection after reduction of immunosuppression. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. The solubility-permeability interplay and its implications in formulation design and development for poorly soluble drugs.

    Science.gov (United States)

    Dahan, Arik; Miller, Jonathan M

    2012-06-01

    While each of the two key parameters of oral drug absorption, the solubility and the permeability, has been comprehensively studied separately, the relationship and interplay between the two have been largely ignored. For instance, when formulating a low-solubility drug using various solubilization techniques: what are we doing to the apparent permeability when we increase the solubility? Permeability is equal to the drug's diffusion coefficient through the membrane times the membrane/aqueous partition coefficient divided by the membrane thickness. The direct correlation between the intestinal permeability and the membrane/aqueous partitioning, which in turn is dependent on the drug's apparent solubility in the GI milieu, suggests that the solubility and the permeability are closely associated, exhibiting a certain interplay between them, and the current view of treating the one irrespectively of the other may not be sufficient. In this paper, we describe the research that has been done thus far, and present new data, to shed light on this solubility-permeability interplay. It has been shown that decreased apparent permeability accompanies the solubility increase when using different solubilization methods. Overall, the weight of the evidence indicates that the solubility-permeability interplay cannot be ignored when using solubility-enabling formulations; looking solely at the solubility enhancement that the formulation enables may be misleading with regards to predicting the resulting absorption, and hence, the solubility-permeability interplay must be taken into account to strike the optimal solubility-permeability balance, in order to maximize the overall absorption.

  11. Improvement of the photovoltaic parameters of perovskite solar cells using a reduced-graphene-oxide-modified titania layer and soluble copper phthalocyanine as a hole transporter.

    Science.gov (United States)

    Nouri, Esmaiel; Mohammadi, Mohammad Reza; Xu, Zong-Xiang; Dracopoulos, Vassilios; Lianos, Panagiotis

    2018-01-24

    Functional perovskite solar cells can be made by using a simple, inexpensive and stable soluble tetra-n-butyl-substituted copper phthalocyanine (CuBuPc) as a hole transporter. In the present study, TiO 2 /reduced graphene oxide (T/RGO) hybrids were synthesized via an in situ solvothermal process and used as electron acceptor/transport mediators in mesoscopic perovskite solar cells based on soluble CuBuPc as a hole transporter and on graphene oxide (GO) as a buffer layer. The impact of the RGO content on the optoelectronic properties of T/RGO hybrids and on the solar cell performance was studied, suggesting improved electron transport characteristics and photovoltaic parameters. An enhanced electron lifetime and recombination resistance led to an increase in the short circuit current density, open circuit voltage and fill factor. The device based on a T/RGO mesoporous layer with an optimal RGO content of 0.2 wt% showed 22% higher photoconversion efficiency and higher stability compared with pristine TiO 2 -based devices.

  12. A framework for API solubility modelling

    DEFF Research Database (Denmark)

    Conte, Elisa; Gani, Rafiqul; Crafts, Peter

    . In addition, most of the models are not predictive and requires experimental data for the calculation of the needed parameters. This work aims at developing an efficient framework for the solubility modelling of Active Pharmaceutical Ingredients (API) in water and organic solvents. With this framework......-SAFT) are used for solubility calculations when the needed interaction parameters or experimental data are available. The CI-UNIFAC is instead used when the previous models lack interaction parameters or when solubility data are not available. A new GC+ model for APIs solvent selection based...... on the hydrophobicity, hydrophilicity and polarity information of the API and solvent is also developed, for performing fast solvent selection and screening. Eventually, all the previous developments are integrated in a framework for their efficient and integrated use. Two case studies are presented: the first...

  13. Prediction of chemical, physical and sensory data from process parameters for frozen cod using multivariate analysis

    DEFF Research Database (Denmark)

    Bechmann, Iben Ellegaard; Jensen, H.S.; Bøknæs, Niels

    1998-01-01

    Physical, chemical and sensory quality parameters were determined for 115 cod (Gadus morhua) samples stored under varying frozen storage conditions. Five different process parameters (period of frozen storage, frozen storage. temperature, place of catch, season for catching and state of rigor) were...... varied systematically at two levels. The data obtained were evaluated using the multivariate methods, principal component analysis (PCA) and partial least squares (PLS) regression. The PCA models were used to identify which process parameters were actually most important for the quality of the frozen cod....... PLS models that were able to predict the physical, chemical and sensory quality parameters from the process parameters of the frozen raw material were generated. The prediction abilities of the PLS models were good enough to give reasonable results even when the process parameters were characterised...

  14. Pre-transplant and post-transplant soluble CD30 for prediction and diagnosis of acute kidney allograft rejection.

    Science.gov (United States)

    Nafar, Mohsen; Farrokhi, Farhat; Vaezi, Mohammad; Entezari, Amir-Ebrahim; Pour-Reza-Gholi, Fatemeh; Firoozan, Ahmad; Eniollahi, Behzad

    2009-01-01

    Serum levels of soluble CD30 (sCD30) have been considered as a predictor of acute kidney allograft rejection. We have evaluated the pre-transplant and post-transplant levels of sCD30 with the aim of determining its value in predicting and diagnosing kidney rejection. We measured sCD30 serum levels before kidney transplantation, 5 days post-operatively, and at creatinine elevation episodes. The predictive value of sCD30 for diagnosing acute rejection (AR) within the first 6 post-operative months was assessed in 203 kidney recipients from living donors. Pre-transplant and post-operative levels of serum sCD30 were 58.10 +/- 52.55 and 51.55 +/- 49.65 U/ml, respectively (P = 0.12). Twenty-three patients experienced biopsy-proven acute rejection, and 28 had acute allograft dysfunction due to non-immunologic diseases. The pre-transplant sCD30 level was not different between patients with and without AR. However, post-transplant sCD30 was higher in the AR group. The median serum level of post-transplant sCD30 was 52 U/ml in the AR group and 26.3 U/ml in a control group (P sCD30 on day 5 were higher in patients with AR (P = 0.003). Based on post-transplant sCD30 levels, we were able to differentiate between kidney recipients who experienced an AR within 6 months post-surgery and those without an AR (cutoff value 41 U/ml; sensitivity 70%; specificity 71.7%). The level of sCD30 during periods of elevated serum creatinine was not independently associated with the diagnosis of AR. Post-transplant sCD30 levels and their relative changes are higher in patients experiencing AR. We propose further studies on the post-transplant trend of this marker for the prediction of AR.

  15. Solubility-Parameter-Guided Solvent Selection to Initiate Ostwald Ripening for Interior Space-Tunable Structures with Architecture-Dependent Electrochemical Performance.

    Science.gov (United States)

    Mao, Baoguang; Guo, Donglei; Qin, Jinwen; Meng, Tao; Wang, Xin; Cao, Minhua

    2018-01-08

    Despite significant advancement in preparing various hollow structures by Ostwald ripening, one common problem is the intractable uncontrollability of initiating Ostwald ripening due to the complexity of the reaction processes. Here, a new strategy on Hansen solubility parameter (HSP)-guided solvent selection to initiate Ostwald ripening is proposed. Based on this comprehensive principle for solvent optimization, N,N-dimethylformamide (DMF) was screened out, achieving accurate synthesis of interior space-tunable MoSe 2 spherical structures (solid, core-shell, yolk-shell and hollow spheres). The resultant MoSe 2 structures exhibit architecture-dependent electrochemical performances towards hydrogen evolution reaction and sodium-ion batteries. This pre-solvent selection strategy can effectively provide researchers great possibility in efficiently synthesizing various hollow structures. This work paves a new pathway for deeply understanding Ostwald ripening. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Physical properties and solubility parameters of 1-ethyl-3-methylimidazolium based ionic liquids/DMSO mixtures at 298.15 K

    Science.gov (United States)

    Saba, H.; Yumei, Z.; Huaping, W.

    2015-12-01

    Densities, refractive indices, conductivities and viscosities of binary mixtures of 1-ethyl-3-methylimidazolium-based ionic liquids (ILs) with dimethyl sulfoxide at 298.15 K are reported. Excess molar volumes have been calculated from experimental data and were fitted with Redlich-Kister equation. The density and refractive index were found to increase with increasing concentration in all cases except [EMIM]COOH. The free mobility of ions has found to enhance conductivity and decrease viscosity to varying extent in all mixtures being studied. It has been observed that solubility parameters, dielectric constants and nature of anions of ILs being used play a vital role in determining the subsequent characteristics. As DMSO has high dielectric constant therefore, it was able to form interactions with most of ILs except with [EMIM]COOH due to anomalous nature of anion.

  17. The Prediction of Item Parameters Based on Classical Test Theory and Latent Trait Theory

    Science.gov (United States)

    Anil, Duygu

    2008-01-01

    In this study, the prediction power of the item characteristics based on the experts' predictions on conditions try-out practices cannot be applied was examined for item characteristics computed depending on classical test theory and two-parameters logistic model of latent trait theory. The study was carried out on 9914 randomly selected students…

  18. Prediction of earth rotation parameters based on improved weighted least squares and autoregressive model

    Directory of Open Access Journals (Sweden)

    Sun Zhangzhen

    2012-08-01

    Full Text Available In this paper, an improved weighted least squares (WLS, together with autoregressive (AR model, is proposed to improve prediction accuracy of earth rotation parameters(ERP. Four weighting schemes are developed and the optimal power e for determination of the weight elements is studied. The results show that the improved WLS-AR model can improve the ERP prediction accuracy effectively, and for different prediction intervals of ERP, different weight scheme should be chosen.

  19. Toward an Efficient Prediction of Solar Flares: Which Parameters, and How?

    Directory of Open Access Journals (Sweden)

    Manolis K. Georgoulis

    2013-11-01

    Full Text Available Solar flare prediction has become a forefront topic in contemporary solar physics, with numerous published methods relying on numerous predictive parameters, that can even be divided into parameter classes. Attempting further insight, we focus on two popular classes of flare-predictive parameters, namely multiscale (i.e., fractal and multifractal and proxy (i.e., morphological parameters, and we complement our analysis with a study of the predictive capability of fundamental physical parameters (i.e., magnetic free energy and relative magnetic helicity. Rather than applying the studied parameters to a comprehensive statistical sample of flaring and non-flaring active regions, that was the subject of our previous studies, the novelty of this work is their application to an exceptionally long and high-cadence time series of the intensely eruptive National Oceanic and Atmospheric Administration (NOAA active region (AR 11158, observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Aiming for a detailed study of the temporal evolution of each parameter, we seek distinctive patterns that could be associated with the four largest flares in the AR in the course of its five-day observing interval. We find that proxy parameters only tend to show preflare impulses that are practical enough to warrant subsequent investigation with sufficient statistics. Combining these findings with previous results, we conclude that: (i carefully constructed, physically intuitive proxy parameters may be our best asset toward an efficient future flare-forecasting; and (ii the time series of promising parameters may be as important as their instantaneous values. Value-based prediction is the only approach followed so far. Our results call for novel signal and/or image processing techniques to efficiently utilize combined amplitude and temporal-profile information to optimize the inferred solar-flare probabilities.

  20. Soluble Forms of Intercellular and Vascular Cell Adhesion Molecules Independently Predict Progression to Type 2 Diabetes in Mexican American Families.

    Directory of Open Access Journals (Sweden)

    Hemant Kulkarni

    Full Text Available While the role of type 2 diabetes (T2D in inducing endothelial dysfunction is fairly well-established the etiological role of endothelial dysfunction in the onset of T2D is still a matter of debate. In the light of conflicting evidence in this regard, we conducted a prospective study to determine the association of circulating levels of soluble intercellular adhesion molecule 1 (sICAM-1 and soluble vessel cell adhesion molecule 1 (sVCAM-1 with incident T2D.Data from this study came from 1,269 Mexican Americans of whom 821 initially T2D-free individuals were longitudinally followed up in the San Antonio Family Heart Study. These individuals were followed for 9752.95 person-years for development of T2D. Prospective association of sICAM-1 and sVCAM-1 with incident T2D was studied using Kaplan-Meier survival plots and mixed effects Cox proportional hazards modeling to account for relatedness among study participants. Incremental value of adhesion molecule biomarkers was studied using integrated discrimination improvement (IDI and net reclassification improvement (NRI indexes.Decreasing median values for serum concentrations of sICAM-1 and sVCAM-1 were observed in the following groups in this order: individuals with T2D at baseline, individuals who developed T2D during follow-up, individuals with prediabetes at baseline and normal glucose tolerant (NGT individuals who remained T2D-free during follow-up. Top quartiles for sICAM-1 and sVCAM-1 were strongly and significantly associated with homeostatic model of assessment--insulin resistance (HOMA-IR. Mixed effects Cox proportional hazards modeling revealed that after correcting for important clinical confounders, high sICAM-1 and sVCAM-1 concentrations were associated with 2.52 and 1.99 times faster progression to T2D as compared to low concentrations, respectively. Individuals with high concentrations for both sICAM-1 and sVCAM-1 progressed to T2D 3.42 times faster than those with low values for both

  1. Soluble Receptor for Advanced Glycation End-Products Predicts Impaired Alveolar Fluid Clearance in Acute Respiratory Distress Syndrome.

    Science.gov (United States)

    Jabaudon, Matthieu; Blondonnet, Raiko; Roszyk, Laurence; Bouvier, Damien; Audard, Jules; Clairefond, Gael; Fournier, Mathilde; Marceau, Geoffroy; Déchelotte, Pierre; Pereira, Bruno; Sapin, Vincent; Constantin, Jean-Michel

    2015-07-15

    Levels of the soluble form of the receptor for advanced glycation end-products (sRAGE) are elevated during acute respiratory distress syndrome (ARDS) and correlate with severity and prognosis. Alveolar fluid clearance (AFC) is necessary for the resolution of lung edema but is impaired in most patients with ARDS. No reliable marker of this process has been investigated to date. To verify whether sRAGE could predict AFC during ARDS. Anesthetized CD-1 mice underwent orotracheal instillation of hydrochloric acid. At specified time points, lung injury was assessed by analysis of blood gases, alveolar permeability, lung histology, AFC, and plasma/bronchoalveolar fluid measurements of proinflammatory cytokines and sRAGE. Plasma sRAGE and AFC rates were also prospectively assessed in 30 patients with ARDS. The rate of AFC was inversely correlated with sRAGE levels in the plasma and the bronchoalveolar fluid of acid-injured mice (Spearman's ρ = -0.73 and -0.69, respectively; P < 10(-3)), and plasma sRAGE correlated with AFC in patients with ARDS (Spearman's ρ = -0.59; P < 10(-3)). Similarly, sRAGE levels were significantly associated with lung injury severity, and decreased over time in mice, whereas AFC was restored and lung injury resolved. Our results indicate that sRAGE levels could be a reliable predictor of impaired AFC during ARDS, and should stimulate further studies on the pathophysiologic implications of RAGE axis in the mechanisms leading to edema resolution. Clinical trial registered with www.clinicaltrials.gov (NCT 00811629).

  2. Development of computer code for determining prediction parameters of radionuclide migration in soil layer

    International Nuclear Information System (INIS)

    Ogawa, Hiromichi; Ohnuki, Toshihiko

    1986-07-01

    A computer code (MIGSTEM-FIT) has been developed to determine the prediction parameters, retardation factor, water flow velocity, dispersion coefficient, etc., of radionuclide migration in soil layer from the concentration distribution of radionuclide in soil layer or in effluent. In this code, the solution of the predicting equation for radionuclide migration is compared with the concentration distribution measured, and the most adequate values of parameter can be determined by the flexible tolerance method. The validity of finite differential method, which was one of the method to solve the predicting equation, was confirmed by comparison with the analytical solution, and also the validity of fitting method was confirmed by the fitting of the concentration distribution calculated from known parameters. From the examination about the error, it was found that the error of the parameter obtained by using this code was smaller than that of the concentration distribution measured. (author)

  3. Prediction of betavoltaic battery output parameters based on SEM measurements and Monte Carlo simulation

    International Nuclear Information System (INIS)

    Yakimov, Eugene B.

    2016-01-01

    An approach for a prediction of "6"3Ni-based betavoltaic battery output parameters is described. It consists of multilayer Monte Carlo simulation to obtain the depth dependence of excess carrier generation rate inside the semiconductor converter, a determination of collection probability based on the electron beam induced current measurements, a calculation of current induced in the semiconductor converter by beta-radiation, and SEM measurements of output parameters using the calculated induced current value. Such approach allows to predict the betavoltaic battery parameters and optimize the converter design for any real semiconductor structure and any thickness and specific activity of beta-radiation source. - Highlights: • New procedure for betavoltaic battery output parameters prediction is described. • A depth dependence of beta particle energy deposition for Si and SiC is calculated. • Electron trajectories are assumed isotropic and uniformly started under simulation.

  4. Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

    Science.gov (United States)

    Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

    2015-09-15

    The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Prediction of pork quality parameters by applying fractals and data mining on MRI

    DEFF Research Database (Denmark)

    Caballero, Daniel; Pérez-Palacios, Trinidad; Caro, Andrés

    2017-01-01

    This work firstly investigates the use of MRI, fractal algorithms and data mining techniques to determine pork quality parameters non-destructively. The main objective was to evaluate the capability of fractal algorithms (Classical Fractal algorithm, CFA; Fractal Texture Algorithm, FTA and One...... Point Fractal Texture Algorithm, OPFTA) to analyse MRI in order to predict quality parameters of loin. In addition, the effect of the sequence acquisition of MRI (Gradient echo, GE; Spin echo, SE and Turbo 3D, T3D) and the predictive technique of data mining (Isotonic regression, IR and Multiple linear...... regression, MLR) were analysed. Both fractal algorithm, FTA and OPFTA are appropriate to analyse MRI of loins. The sequence acquisition, the fractal algorithm and the data mining technique seems to influence on the prediction results. For most physico-chemical parameters, prediction equations with moderate...

  6. Characterization of Initial Parameter Information for Lifetime Prediction of Electronic Devices.

    Science.gov (United States)

    Li, Zhigang; Liu, Boying; Yuan, Mengxiong; Zhang, Feifei; Guo, Jiaqiang

    2016-01-01

    Newly manufactured electronic devices are subject to different levels of potential defects existing among the initial parameter information of the devices. In this study, a characterization of electromagnetic relays that were operated at their optimal performance with appropriate and steady parameter values was performed to estimate the levels of their potential defects and to develop a lifetime prediction model. First, the initial parameter information value and stability were quantified to measure the performance of the electronics. In particular, the values of the initial parameter information were estimated using the probability-weighted average method, whereas the stability of the parameter information was determined by using the difference between the extrema and end points of the fitting curves for the initial parameter information. Second, a lifetime prediction model for small-sized samples was proposed on the basis of both measures. Finally, a model for the relationship of the initial contact resistance and stability over the lifetime of the sampled electromagnetic relays was proposed and verified. A comparison of the actual and predicted lifetimes of the relays revealed a 15.4% relative error, indicating that the lifetime of electronic devices can be predicted based on their initial parameter information.

  7. Characterization of Initial Parameter Information for Lifetime Prediction of Electronic Devices.

    Directory of Open Access Journals (Sweden)

    Zhigang Li

    Full Text Available Newly manufactured electronic devices are subject to different levels of potential defects existing among the initial parameter information of the devices. In this study, a characterization of electromagnetic relays that were operated at their optimal performance with appropriate and steady parameter values was performed to estimate the levels of their potential defects and to develop a lifetime prediction model. First, the initial parameter information value and stability were quantified to measure the performance of the electronics. In particular, the values of the initial parameter information were estimated using the probability-weighted average method, whereas the stability of the parameter information was determined by using the difference between the extrema and end points of the fitting curves for the initial parameter information. Second, a lifetime prediction model for small-sized samples was proposed on the basis of both measures. Finally, a model for the relationship of the initial contact resistance and stability over the lifetime of the sampled electromagnetic relays was proposed and verified. A comparison of the actual and predicted lifetimes of the relays revealed a 15.4% relative error, indicating that the lifetime of electronic devices can be predicted based on their initial parameter information.

  8. Reflow Process Parameters Analysis and Reliability Prediction Considering Multiple Characteristic Values

    Directory of Open Access Journals (Sweden)

    Guo Yu

    2016-01-01

    Full Text Available As a major step surface mount technology, reflow process is the key factor affecting the quality of the final product. The setting parameters and characteristic value of temperature curve shows a nonlinear relationship. So parameter impacts on characteristic values are analyzed and the parameters adjustment process based on orthogonal experiment is proposed in the paper. First, setting parameters are determined and the orthogonal test is designed according to production conditions. Then each characteristic value for temperature profile is calculated. Further, multi-index orthogonal experiment is analyzed for acquiring the setting parameters which impacts the PCBA product quality greater. Finally, reliability prediction is carried out considering the main influencing parameters for providing a theoretical basis of parameters adjustment and product quality evaluation in engineering process.

  9. Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions

    Science.gov (United States)

    Hsu, Ling-Yuan; Chen, Tsung-Lin

    2012-01-01

    This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event. PMID:23202231

  10. Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Bambang Wahono

    2015-07-01

    Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.

  11. Can we predict uranium bioavailability based on soil parameters? Part 1: effect of soil parameters on soil solution uranium concentration.

    Science.gov (United States)

    Vandenhove, H; Van Hees, M; Wouters, K; Wannijn, J

    2007-01-01

    Present study aims to quantify the influence of soil parameters on soil solution uranium concentration for (238)U spiked soils. Eighteen soils collected under pasture were selected such that they covered a wide range for those parameters hypothesised as being potentially important in determining U sorption. Maximum soil solution uranium concentrations were observed at alkaline pH, high inorganic carbon content and low cation exchange capacity, organic matter content, clay content, amorphous Fe and phosphate levels. Except for the significant correlation between the solid-liquid distribution coefficients (K(d), L kg(-1)) and the organic matter content (R(2)=0.70) and amorphous Fe content (R(2)=0.63), there was no single soil parameter significantly explaining the soil solution uranium concentration (which varied 100-fold). Above pH=6, log(K(d)) was linearly related with pH [log(K(d))=-1.18 pH+10.8, R(2)=0.65]. Multiple linear regression analysis did result in improved predictions of the soil solution uranium concentration but the model was complex.

  12. Prediction of crude protein digestibility of animal by-product meals for dogs by the protein solubility in pepsin method.

    Science.gov (United States)

    Kawauchi, Iris M; Sakomura, Nilva K; Pontieri, Cristiana F F; Rebelato, Aline; Putarov, Thaila C; Malheiros, Euclides B; Gomes, Márcia de O S; Castrillo, Carlos; Carciofi, Aulus C

    2014-01-01

    Animal by-product meals have large variability in crude protein (CP) content and digestibility. In vivo digestibility procedures are precise but laborious, and in vitro methods could be an alternative to evaluate and classify these ingredients. The present study reports prediction equations to estimate the CP digestibility of meat and bone meal (MBM) and poultry by-product meal (PM) using the protein solubility in pepsin method (PSP). Total tract CP digestibility of eight MBM and eight PM samples was determined in dogs by the substitution method. A basal diet was formulated for dog maintenance, and sixteen diets were produced by mixing 70 % of the basal diet and 30 % of each tested meal. Six dogs per diet were used to determine ingredient digestibility. In addition, PSP of the MBM and PM samples was determined using three pepsin concentrations: 0·02, 0·002 and 0·0002 %. The CP content of MBM and PM ranged from 39 to 46 % and 57 to 69 %, respectively, and their mean CP digestibility by dogs was 76 (2·4) and 85 (2·6) %, respectively. The pepsin concentration with higher Pearson correlation coefficients with the in vivo results were 0·0002 % for MBM (r 0·380; P = 0·008) and 0·02 % for PM (r 0·482; P = 0·005). The relationship between the in vivo and in vitro results was better explained by the following equations: CP digestibility of MBM = 61·7 + 0·2644 × PSP at 0·0002 % (P = 0·008; R (2) 0·126); and CP digestibility of PM = 54·1 + 0·3833 × PSP at 0·02 % (P = 0·005; R (2) 0·216). Although significant, the coefficients of determination were low, indicating that the models were weak and need to be used with caution.

  13. Predicting prognosis in hepatocellular carcinoma after curative surgery with common clinicopathologic parameters

    International Nuclear Information System (INIS)

    Hao, Ke; Sham, Pak C; Poon, Ronnie TP; Luk, John M; Lee, Nikki PY; Mao, Mao; Zhang, Chunsheng; Ferguson, Mark D; Lamb, John; Dai, Hongyue; Ng, Irene O

    2009-01-01

    Surgical resection is one important curative treatment for hepatocellular carcinoma (HCC), but the prognosis following surgery differs substantially and such large variation is mainly unexplained. A review of the literature yields a number of clinicopathologic parameters associated with HCC prognosis. However, the results are not consistent due to lack of systemic approach to establish a prediction model incorporating all these parameters. We conducted a retrospective analysis on the common clinicopathologic parameters from a cohort of 572 ethnic Chinese HCC patients who received curative surgery. The cases were randomly divided into training (n = 272) and validation (n = 300) sets. Each parameter was individually tested and the significant parameters were entered into a linear classifier for model building, and the prediction accuracy was assessed in the validation set Our findings based on the training set data reveal 6 common clinicopathologic parameters (tumor size, number of tumor nodules, tumor stage, venous infiltration status, and serum α-fetoprotein and total albumin levels) that were significantly associated with the overall HCC survival and disease-free survival (time to recurrence). We next built a linear classifier model by multivariate Cox regression to predict prognostic outcomes of HCC patients after curative surgery This analysis detected a considerable fraction of variance in HCC prognosis and the area under the ROC curve was about 70%. We further evaluated the model using two other protocols; leave-one-out procedure (n = 264) and independent validation (n = 300). Both were found to have excellent prediction power. The predicted score could separate patients into distinct groups with respect to survival (p-value = 1.8e-12) and disease free survival (p-value = 3.2e-7). This described model will provide valuable guidance on prognosis after curative surgery for HCC in clinical practice. The adaptive nature allows easy accommodation for future new

  14. Predictions of the marviken subcooled critical mass flux using the critical flow scaling parameters

    Energy Technology Data Exchange (ETDEWEB)

    Park, Choon Kyung; Chun, Se Young; Cho, Seok; Yang, Sun Ku; Chung, Moon Ki [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1997-12-31

    A total of 386 critical flow data points from 19 runs of 27 runs in the Marviken Test were selected and compared with the predictions by the correlations based on the critical flow scaling parameters. The results show that the critical mass flux in the very large diameter pipe can be also characterized by two scaling parameters such as discharge coefficient and dimensionless subcooling (C{sub d,ref} and {Delta}{Tau}{sup *} {sub sub}). The agreement between the measured data and the predictions are excellent. 8 refs., 8 figs. 1 tab. (Author)

  15. Predictions of the marviken subcooled critical mass flux using the critical flow scaling parameters

    Energy Technology Data Exchange (ETDEWEB)

    Park, Choon Kyung; Chun, Se Young; Cho, Seok; Yang, Sun Ku; Chung, Moon Ki [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1998-12-31

    A total of 386 critical flow data points from 19 runs of 27 runs in the Marviken Test were selected and compared with the predictions by the correlations based on the critical flow scaling parameters. The results show that the critical mass flux in the very large diameter pipe can be also characterized by two scaling parameters such as discharge coefficient and dimensionless subcooling (C{sub d,ref} and {Delta}{Tau}{sup *} {sub sub}). The agreement between the measured data and the predictions are excellent. 8 refs., 8 figs. 1 tab. (Author)

  16. Monitoring of Physiological Parameters to Predict Exacerbations of Chronic Obstructive Pulmonary Disease (COPD: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Ahmed M. Al Rajeh

    2016-11-01

    Full Text Available Introduction: The value of monitoring physiological parameters to predict chronic obstructive pulmonary disease (COPD exacerbations is controversial. A few studies have suggested benefit from domiciliary monitoring of vital signs, and/or lung function but there is no existing systematic review. Objectives: To conduct a systematic review of the effectiveness of monitoring physiological parameters to predict COPD exacerbation. Methods: An electronic systematic search compliant with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA guidelines was conducted. The search was updated to April 6, 2016. Five databases were examined: Medical Literature Analysis and Retrieval System Online, or MEDLARS Online (Medline, Excerpta Medica dataBASE (Embase, Allied and Complementary Medicine Database (AMED, Cumulative Index of Nursing and Allied Health Literature (CINAHL and the Cochrane clinical trials database. Results: Sixteen articles met the pre-specified inclusion criteria. Fifteen of these articules reported positive results in predicting COPD exacerbation via monitoring of physiological parameters. Nine studies showed a reduction in peripheral oxygen saturation (SpO2% prior to exacerbation onset. Three studies for peak flow, and two studies for respiratory rate reported a significant variation prior to or at exacerbation onset. A particular challenge is accounting for baseline heterogeneity in parameters between patients. Conclusion: There is currently insufficient information on how physiological parameters vary prior to exacerbation to support routine domiciliary monitoring for the prediction of exacerbations in COPD. However, the method remains promising.

  17. Computer simulation for prediction of performance and thermodynamic parameters of high energy materials

    International Nuclear Information System (INIS)

    Muthurajan, H.; Sivabalan, R.; Talawar, M.B.; Asthana, S.N.

    2004-01-01

    A new code viz., Linear Output Thermodynamic User-friendly Software for Energetic Systems (LOTUSES) developed during this work predicts the theoretical performance parameters such as density, detonation factor, velocity of detonation, detonation pressure and thermodynamic properties such as heat of detonation, heat of explosion, volume of explosion gaseous products. The same code also assists in the prediction of possible explosive decomposition products after explosion and power index. The developed code has been validated by calculating the parameters of standard explosives such as TNT, PETN, RDX, and HMX. Theoretically predicated parameters are accurate to the order of ±5% deviation. To the best of our knowledge, no such code is reported in literature which can predict a wide range of characteristics of known/unknown explosives with minimum input parameters. The code can be used to obtain thermochemical and performance parameters of high energy materials (HEMs) with reasonable accuracy. The code has been developed in Visual Basic having enhanced windows environment, and thereby advantages over the conventional codes, written in Fortran. The theoretically predicted HEMs performance can be directly printed as well as stored in text (.txt) or HTML (.htm) or Microsoft Word (.doc) or Adobe Acrobat (.pdf) format in the hard disk. The output can also be copied into the Random Access Memory as clipboard text which can be imported/pasted in other software as in the case of other codes

  18. Prediction of detonation and JWL eos parameters of energetic materials using EXPLO5 computer code

    CSIR Research Space (South Africa)

    Peter, Xolani

    2016-09-01

    Full Text Available Ballistic Organization Cape Town, South Africa 27-29 September 2016 1 PREDICTION OF DETONATION AND JWL EOS PARAMETERS OF ENERGETIC MATERIALS USING EXPLO5 COMPUTER CODE X. Peter*, Z. Jiba, M. Olivier, I.M. Snyman, F.J. Mostert and T.J. Sono.... Nowadays many numerical methods and programs are being used for carrying out thermodynamic calculations of the detonation parameters of condensed explosives, for example a BKW Fortran (Mader, 1967), Ruby (Cowperthwaite and Zwisler, 1974) TIGER...

  19. Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation

    International Nuclear Information System (INIS)

    Gershgorin, B.; Harlim, J.; Majda, A.J.

    2010-01-01

    The filtering and predictive skill for turbulent signals is often limited by the lack of information about the true dynamics of the system and by our inability to resolve the assumed dynamics with sufficiently high resolution using the current computing power. The standard approach is to use a simple yet rich family of constant parameters to account for model errors through parameterization. This approach can have significant skill by fitting the parameters to some statistical feature of the true signal; however in the context of real-time prediction, such a strategy performs poorly when intermittent transitions to instability occur. Alternatively, we need a set of dynamic parameters. One strategy for estimating parameters on the fly is a stochastic parameter estimation through partial observations of the true signal. In this paper, we extend our newly developed stochastic parameter estimation strategy, the Stochastic Parameterization Extended Kalman Filter (SPEKF), to filtering sparsely observed spatially extended turbulent systems which exhibit abrupt stability transition from time to time despite a stable average behavior. For our primary numerical example, we consider a turbulent system of externally forced barotropic Rossby waves with instability introduced through intermittent negative damping. We find high filtering skill of SPEKF applied to this toy model even in the case of very sparse observations (with only 15 out of the 105 grid points observed) and with unspecified external forcing and damping. Additive and multiplicative bias corrections are used to learn the unknown features of the true dynamics from observations. We also present a comprehensive study of predictive skill in the one-mode context including the robustness toward variation of stochastic parameters, imperfect initial conditions and finite ensemble effect. Furthermore, the proposed stochastic parameter estimation scheme applied to the same spatially extended Rossby wave system demonstrates

  20. Cervical Vertebral Body's Volume as a New Parameter for Predicting the Skeletal Maturation Stages

    OpenAIRE

    Choi, Youn-Kyung; Kim, Jinmi; Yamaguchi, Tetsutaro; Maki, Koutaro; Ko, Ching-Chang; Kim, Yong-Il

    2016-01-01

    This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies ...

  1. Application of ann for predicting water quality parameters in the mediterranean sea along gaza-palestine

    International Nuclear Information System (INIS)

    Zaqoot, H.A.; Unar, M.A.

    2008-01-01

    Seawater pollution problems are gaining interest world wide because of their health impacts and other environmental issues. Intense human activities in areas surrounding enclosed and semi-enclosed seas such as the Mediterranean Sea always produce in the long term a strong environmental impact in the form of coastal and marine degradation. This paper is concerned with the use of ANNs (Artificial Neural Networks) MLP ( Multilayer Perceptron) model for the prediction of pH and EC (Electrical Conductivity) in water quality parameters along Gaza city coast. MLP neural networks are trained and developed with reference to three major oceanographic parameters (water temperature, wind speed and turbidity) to predict the values of pH and EC; these parameters are considered as inputs of the neural network. The data collected comprised of four years and collected from nine locations along Gaza coastline. Results show that the model has high capability and accuracy in predicting both parameters. The network performance has been validated with different data sets and the results show satisfactory performance. Results of the developed model have been compared with multiple regression statistical models and found that MLP predictions are slightly better than the conventional methods. Prediction results prove that the proposed approach is suitable for modeling the water quality in the Mediterranean Sea along Gaza. (author)

  2. Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Gergely Takács

    2014-01-01

    Full Text Available This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

  3. Parameter estimation techniques and uncertainty in ground water flow model predictions

    International Nuclear Information System (INIS)

    Zimmerman, D.A.; Davis, P.A.

    1990-01-01

    Quantification of uncertainty in predictions of nuclear waste repository performance is a requirement of Nuclear Regulatory Commission regulations governing the licensing of proposed geologic repositories for high-level radioactive waste disposal. One of the major uncertainties in these predictions is in estimating the ground-water travel time of radionuclides migrating from the repository to the accessible environment. The cause of much of this uncertainty has been attributed to a lack of knowledge about the hydrogeologic properties that control the movement of radionuclides through the aquifers. A major reason for this lack of knowledge is the paucity of data that is typically available for characterizing complex ground-water flow systems. Because of this, considerable effort has been put into developing parameter estimation techniques that infer property values in regions where no measurements exist. Currently, no single technique has been shown to be superior or even consistently conservative with respect to predictions of ground-water travel time. This work was undertaken to compare a number of parameter estimation techniques and to evaluate how differences in the parameter estimates and the estimation errors are reflected in the behavior of the flow model predictions. That is, we wished to determine to what degree uncertainties in flow model predictions may be affected simply by the choice of parameter estimation technique used. 3 refs., 2 figs

  4. A fast-running core prediction model based on neural networks for load-following operations in a soluble boron-free reactor

    Energy Technology Data Exchange (ETDEWEB)

    Jang, Jin-wook [Korea Atomic Energy Research Institute, P.O. Box 105, Yusong, Daejon 305-600 (Korea, Republic of)], E-mail: Jinwook@kaeri.re.kr; Seong, Seung-Hwan [Korea Atomic Energy Research Institute, P.O. Box 105, Yusong, Daejon 305-600 (Korea, Republic of)], E-mail: shseong@kaeri.re.kr; Lee, Un-Chul [Department of Nuclear Engineering, Seoul National University, Shinlim-Dong, Gwanak-Gu, Seoul 151-742 (Korea, Republic of)

    2007-09-15

    A fast prediction model for load-following operations in a soluble boron-free reactor has been proposed, which can predict the core status when three or more control rod groups are moved at a time. This prediction model consists of two multilayer feedforward neural network models to retrieve the axial offset and the reactivity, and compensation models to compensate for the reactivity and axial offset arising from the xenon transient. The neural network training data were generated by taking various overlaps among the control rod groups into consideration for training the neural network models, and the accuracy of the constructed neural network models was verified. Validation results of predicting load following operations for a soluble boron-free reactor show that this model has a good capability to predict the positions of the control rods for sustaining the criticality of a core during load-following operations to ensure that the tolerable axial offset band is not exceeded and it can provide enough corresponding time for the operators to take the necessary actions to prevent a deviation from the tolerable operating band.

  5. A fast-running core prediction model based on neural networks for load-following operations in a soluble boron-free reactor

    International Nuclear Information System (INIS)

    Jang, Jin-wook; Seong, Seung-Hwan; Lee, Un-Chul

    2007-01-01

    A fast prediction model for load-following operations in a soluble boron-free reactor has been proposed, which can predict the core status when three or more control rod groups are moved at a time. This prediction model consists of two multilayer feedforward neural network models to retrieve the axial offset and the reactivity, and compensation models to compensate for the reactivity and axial offset arising from the xenon transient. The neural network training data were generated by taking various overlaps among the control rod groups into consideration for training the neural network models, and the accuracy of the constructed neural network models was verified. Validation results of predicting load following operations for a soluble boron-free reactor show that this model has a good capability to predict the positions of the control rods for sustaining the criticality of a core during load-following operations to ensure that the tolerable axial offset band is not exceeded and it can provide enough corresponding time for the operators to take the necessary actions to prevent a deviation from the tolerable operating band

  6. Prediction Model of Interval Grey Numbers with a Real Parameter and Its Application

    Directory of Open Access Journals (Sweden)

    Bo Zeng

    2014-01-01

    Full Text Available Grey prediction models have become common methods which are widely employed to solve the problems with “small examples and poor information.” However, modeling objects of existing grey prediction models are limited to the homogenous data sequences which only contain the same data type. This paper studies the methodology of building prediction models of interval grey numbers that are grey heterogeneous data sequence, with a real parameter. Firstly, the position of the real parameter in an interval grey number sequence is discussed, and the real number is expanded into an interval grey number by adopting the method of grey generation. On this basis, a prediction model of interval grey number with a real parameter is deduced and built. Finally, this novel model is successfully applied to forecast the concentration of organic pollutant DDT in the atmosphere. The analysis and research results in this paper extend the object of grey prediction from homogenous data sequence to grey heterogeneous data sequence. Those research findings are of positive significance in terms of enriching and improving the theory system of grey prediction models.

  7. Effect of the structure, solid state and lipophilicity on the solubility of novel bicyclic derivatives

    International Nuclear Information System (INIS)

    Blokhina, Svetlana V.; Ol’khovich, Marina V.; Sharapova, Angelica V.; Volkova, Tatyana V.; Proshin, Alexey N.; Perlovich, German L.

    2014-01-01

    Highlights: • The solubility in buffer pH 7.4 of novel bicyclo-derivatives of amine were measured. • The influence of melting parameters and lipophilicity on the solubility was studied. • The thermodynamic parameters of the solubility process were calculated. - Abstract: Novel bicyclic derivatives have been synthesized. The solubility of drug-like substances in phosphate buffer rH 7.4 has been measured within the range of (9.02 · 10 −5 to 1.05 · 10 −4 ) mol/l. The relationship between the chemical nature and the structure of the aryl substituents and the solubility parameter was investigated. The fusion temperatures, enthalpies and entropies have been determined experimentally. The influence of thermophysical characteristics and lipophilicity on the solubility was studied using regression analysis. The calculations by the solubility/lipophilicity equation showed an overall improvement of the predictions equal to 0.5 log units. It was concluded that the solvation has a considerable influence on the solubility of the compounds under consideration. It was also determined that the alkyl- and halogen-derivatives solubility values correlate with HYBOT descriptors characterizing the (donor + acceptor) properties of the substances. The thermodynamic parameters of the solubility process were calculated using the temperature dependences. The study also revealed that the solubility of the bicyclic compounds is characterized by high endothermicity of the processes and negative entropies

  8. Using ANFIS for selection of more relevant parameters to predict dew point temperature

    International Nuclear Information System (INIS)

    Mohammadi, Kasra; Shamshirband, Shahaboddin; Petković, Dalibor; Yee, Por Lip; Mansor, Zulkefli

    2016-01-01

    Highlights: • ANFIS is used to select the most relevant variables for dew point temperature prediction. • Two cities from the central and south central parts of Iran are selected as case studies. • Influence of 5 parameters on dew point temperature is evaluated. • Appropriate selection of input variables has a notable effect on prediction. • Considering the most relevant combination of 2 parameters would be more suitable. - Abstract: In this research work, for the first time, the adaptive neuro fuzzy inference system (ANFIS) is employed to propose an approach for identifying the most significant parameters for prediction of daily dew point temperature (T_d_e_w). The ANFIS process for variable selection is implemented, which includes a number of ways to recognize the parameters offering favorable predictions. According to the physical factors influencing the dew formation, 8 variables of daily minimum, maximum and average air temperatures (T_m_i_n, T_m_a_x and T_a_v_g), relative humidity (R_h), atmospheric pressure (P), water vapor pressure (V_P), sunshine hour (n) and horizontal global solar radiation (H) are considered to investigate their effects on T_d_e_w. The used data include 7 years daily measured data of two Iranian cities located in the central and south central parts of the country. The results indicate that despite climate difference between the considered case studies, for both stations, V_P is the most influential variable while R_h is the least relevant element. Furthermore, the combination of T_m_i_n and V_P is recognized as the most influential set to predict T_d_e_w. The conducted examinations show that there is a remarkable difference between the errors achieved for most and less relevant input parameters, which highlights the importance of appropriate selection of input parameters. The use of more than two inputs may not be advisable and appropriate; thus, considering the most relevant combination of 2 parameters would be more suitable

  9. Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

    Science.gov (United States)

    Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

    2015-04-01

    This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

  10. Modeling of Salt Solubilities in Mixed Solvents

    DEFF Research Database (Denmark)

    Chiavone-Filho, O.; Rasmussen, Peter

    2000-01-01

    A method to correlate and predict salt solubilities in mixed solvents using a UNIQUAC+Debye-Huckel model is developed. The UNIQUAC equation is applied in a form with temperature-dependent parameters. The Debye-Huckel model is extended to mixed solvents by properly evaluating the dielectric...... constants and the liquid densities of the solvent media. To normalize the activity coefficients, the symmetric convention is adopted. Thermochemical properties of the salt are used to estimate the solubility product. It is shown that the proposed procedure can describe with good accuracy a series of salt...

  11. Evaluation of the simultaneous effects of processing parameters on the iron and zinc solubility of infant sorghum porridge by response surface methodology.

    Science.gov (United States)

    Kayodé, A P Polycarpe; Nout, Martinus J R; Bakker, Evert J; Van Boekel, Martinus A J S

    2006-06-14

    The purpose of this study was to improve the micronutrient quality of indigenous African infant flour using traditional techniques available in the region. Response surface methodology was used to study the effect of duration of soaking, germination, and fermentation on phytate and phenolic compounds (PC), pH, viscosity, and the in vitro solubility (IVS) of iron and zinc in infant sorghum flour. The phytate and the PC concentrations of the flour were significantly modified as a result of the duration of germination and fermentation and their mutual interaction. These modifications were accompanied by a significant increase in % IVS Zn after 24 h of sprouting. Except for the interaction of soaking and fermentation, none of the processing parameters exerted a significant effect on the % IVS Fe. The viscosity of the porridge prepared with the flour decreased significantly with the duration of germination, making it possible to produce a porridge with high energy and nutrient density. The use of germination in combination with fermentation is recommended in the processing of cereals for infant feeding in developing countries.

  12. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

    Science.gov (United States)

    We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

  13. An improved robust model predictive control for linear parameter-varying input-output models

    NARCIS (Netherlands)

    Abbas, H.S.; Hanema, J.; Tóth, R.; Mohammadpour, J.; Meskin, N.

    2018-01-01

    This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal

  14. A New Energy-Critical Plane Damage Parameter for Multiaxial Fatigue Life Prediction of Turbine Blades

    Directory of Open Access Journals (Sweden)

    Zheng-Yong Yu

    2017-05-01

    Full Text Available As one of fracture critical components of an aircraft engine, accurate life prediction of a turbine blade to disk attachment is significant for ensuring the engine structural integrity and reliability. Fatigue failure of a turbine blade is often caused under multiaxial cyclic loadings at high temperatures. In this paper, considering different failure types, a new energy-critical plane damage parameter is proposed for multiaxial fatigue life prediction, and no extra fitted material constants will be needed for practical applications. Moreover, three multiaxial models with maximum damage parameters on the critical plane are evaluated under tension-compression and tension-torsion loadings. Experimental data of GH4169 under proportional and non-proportional fatigue loadings and a case study of a turbine disk-blade contact system are introduced for model validation. Results show that model predictions by Wang-Brown (WB and Fatemi-Socie (FS models with maximum damage parameters are conservative and acceptable. For the turbine disk-blade contact system, both of the proposed damage parameters and Smith-Watson-Topper (SWT model show reasonably acceptable correlations with its field number of flight cycles. However, life estimations of the turbine blade reveal that the definition of the maximum damage parameter is not reasonable for the WB model but effective for both the FS and SWT models.

  15. A polynomial chaos ensemble hydrologic prediction system for efficient parameter inference and robust uncertainty assessment

    Science.gov (United States)

    Wang, S.; Huang, G. H.; Baetz, B. W.; Huang, W.

    2015-11-01

    This paper presents a polynomial chaos ensemble hydrologic prediction system (PCEHPS) for an efficient and robust uncertainty assessment of model parameters and predictions, in which possibilistic reasoning is infused into probabilistic parameter inference with simultaneous consideration of randomness and fuzziness. The PCEHPS is developed through a two-stage factorial polynomial chaos expansion (PCE) framework, which consists of an ensemble of PCEs to approximate the behavior of the hydrologic model, significantly speeding up the exhaustive sampling of the parameter space. Multiple hypothesis testing is then conducted to construct an ensemble of reduced-dimensionality PCEs with only the most influential terms, which is meaningful for achieving uncertainty reduction and further acceleration of parameter inference. The PCEHPS is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability. A detailed comparison between the HYMOD hydrologic model, the ensemble of PCEs, and the ensemble of reduced PCEs is performed in terms of accuracy and efficiency. Results reveal temporal and spatial variations in parameter sensitivities due to the dynamic behavior of hydrologic systems, and the effects (magnitude and direction) of parametric interactions depending on different hydrological metrics. The case study demonstrates that the PCEHPS is capable not only of capturing both expert knowledge and probabilistic information in the calibration process, but also of implementing an acceleration of more than 10 times faster than the hydrologic model without compromising the predictive accuracy.

  16. Comparison of predictability for human pharmacokinetics parameters among monkeys, rats, and chimeric mice with humanised liver.

    Science.gov (United States)

    Miyamoto, Maki; Iwasaki, Shinji; Chisaki, Ikumi; Nakagawa, Sayaka; Amano, Nobuyuki; Hirabayashi, Hideki

    2017-12-01

    1. The aim of the present study was to evaluate the usefulness of chimeric mice with humanised liver (PXB mice) for the prediction of clearance (CL t ) and volume of distribution at steady state (Vd ss ), in comparison with monkeys, which have been reported as a reliable model for human pharmacokinetics (PK) prediction, and with rats, as a conventional PK model. 2. CL t and Vd ss values in PXB mice, monkeys and rats were determined following intravenous administration of 30 compounds known to be mainly eliminated in humans via the hepatic metabolism by various drug-metabolising enzymes. Using single-species allometric scaling, human CL t and Vd ss values were predicted from the three animal models. 3. Predicted CL t values from PXB mice exhibited the highest predictability: 25 for PXB mice, 21 for monkeys and 14 for rats were predicted within a three-fold range of actual values among 30 compounds. For predicted human Vd ss values, the number of compounds falling within a three-fold range was 23 for PXB mice, 24 for monkeys, and 16 for rats among 29 compounds. PXB mice indicated a higher predictability for CL t and Vd ss values than the other animal models. 4. These results demonstrate the utility of PXB mice in predicting human PK parameters.

  17. Nomogram including pretherapeutic parameters for prediction of survival after SIRT of hepatic metastases from colorectal cancer

    International Nuclear Information System (INIS)

    Fendler, Wolfgang Peter; Ilhan, Harun; Paprottka, Philipp M.; Jakobs, Tobias F.; Heinemann, Volker; Bartenstein, Peter; Haug, Alexander R.; Khalaf, Feras; Ezziddin, Samer; Hacker, Marcus

    2015-01-01

    Pre-therapeutic prediction of outcome is important for clinicians and patients in determining whether selective internal radiation therapy (SIRT) is indicated for hepatic metastases of colorectal cancer (CRC). Pre-therapeutic characteristics of 100 patients with colorectal liver metastases (CRLM) treated by radioembolization were analyzed to develop a nomogram for predicting survival. Prognostic factors were selected by univariate Cox regression analysis and subsequent tested by multivariate analysis for predicting patient survival. The nomogram was validated with reference to an external patient cohort (n = 25) from the Bonn University Department of Nuclear Medicine. Of the 13 parameters tested, four were independently associated with reduced patient survival in multivariate analysis. These parameters included no liver surgery before SIRT (HR:1.81, p = 0.014), CEA serum level ≥ 150 ng/ml (HR:2.08, p = 0.001), transaminase toxicity level ≥2.5 x upper limit of normal (HR:2.82, p = 0.001), and summed computed tomography (CT) size of the largest two liver lesions ≥10 cm (HR:2.31, p < 0.001). The area under the receiver-operating characteristic curve for our prediction model was 0.83 for the external patient cohort, indicating superior performance of our multivariate model compared to a model ignoring covariates. The nomogram developed in our study entailing four pre-therapeutic parameters gives good prediction of patient survival post SIRT. (orig.)

  18. Nomogram including pretherapeutic parameters for prediction of survival after SIRT of hepatic metastases from colorectal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Fendler, Wolfgang Peter [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Klinik und Poliklinik fuer Nuklearmedizin, Munich (Germany); Ilhan, Harun [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Paprottka, Philipp M. [Ludwig-Maximilians-University of Munich, Department of Clinical Radiology, Munich (Germany); Jakobs, Tobias F. [Hospital Barmherzige Brueder, Department of Diagnostic and Interventional Radiology, Munich (Germany); Heinemann, Volker [Ludwig-Maximilians-University of Munich, Department of Internal Medicine III, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Bartenstein, Peter; Haug, Alexander R. [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Khalaf, Feras [University Hospital Bonn, Department of Nuclear Medicine, Bonn (Germany); Ezziddin, Samer [Saarland University Medical Center, Department of Nuclear Medicine, Homburg (Germany); Hacker, Marcus [Vienna General Hospital, Department of Nuclear Medicine, Vienna (Austria)

    2015-09-15

    Pre-therapeutic prediction of outcome is important for clinicians and patients in determining whether selective internal radiation therapy (SIRT) is indicated for hepatic metastases of colorectal cancer (CRC). Pre-therapeutic characteristics of 100 patients with colorectal liver metastases (CRLM) treated by radioembolization were analyzed to develop a nomogram for predicting survival. Prognostic factors were selected by univariate Cox regression analysis and subsequent tested by multivariate analysis for predicting patient survival. The nomogram was validated with reference to an external patient cohort (n = 25) from the Bonn University Department of Nuclear Medicine. Of the 13 parameters tested, four were independently associated with reduced patient survival in multivariate analysis. These parameters included no liver surgery before SIRT (HR:1.81, p = 0.014), CEA serum level ≥ 150 ng/ml (HR:2.08, p = 0.001), transaminase toxicity level ≥2.5 x upper limit of normal (HR:2.82, p = 0.001), and summed computed tomography (CT) size of the largest two liver lesions ≥10 cm (HR:2.31, p < 0.001). The area under the receiver-operating characteristic curve for our prediction model was 0.83 for the external patient cohort, indicating superior performance of our multivariate model compared to a model ignoring covariates. The nomogram developed in our study entailing four pre-therapeutic parameters gives good prediction of patient survival post SIRT. (orig.)

  19. Bioavailability of elemental iron powders to rats is less than bakery-grade ferrous sulfate and predicted by iron solubility and particle surface area.

    Science.gov (United States)

    Swain, James H; Newman, Samuel M; Hunt, Janet R

    2003-11-01

    Foods are fortified with elemental forms of iron to reduce iron deficiency. However, the nutritional efficacy of current, commercially produced elemental iron powders has not been verified. We determined the bioavailability of six commercial elemental iron powders and examined how physicochemistry influences bioavailability. Relative biological value (RBV) of the iron powders was determined using a hemoglobin repletion/slope ratio method, treating iron-deficient rats with repletion diets fortified with graded quantities of iron powders, bakery-grade ferrous sulfate or no added iron. Iron powders were assessed physicochemically by measuring iron solubility in hydrochloric acid at pH 1.0 and 1.7, surface area by nitrogen gas adsorption and surface microstructure by electron microscopy. Bioavailability from the iron powders, based on absolute iron intake, was significantly less than from FeSO4 (100%; P Electrolytic (54%; A-131, U.S.) > Electrolytic (46%; Electrolytic Iron, India) > H-Reduced (42%; AC-325, U.S.) > Reduced (24%; ATOMET 95SP, Canada) > CO-Reduced (21%; RSI-325, Sweden). Solubility testing of the iron powders resulted in different relative rankings and better RBV predictability with increasing time at pH 1.7 (R2 = 0.65 at 150 min). The prediction was improved with less time and lower pH (R2 = 0.82, pH 1.0 at 30 min). Surface area, ranging from 90 to 370 m2/kg, was also highly predictive of RBV (R2 = 0.80). Bioavailability of iron powders is less than bakery-grade ferrous sulfate and varies up to three times among different commercial forms. Solubility at pH 1.0 and surface area were predictive of iron bioavailability in rats.

  20. Lactate Parameters Predict Clinical Outcomes in Patients with Nonvariceal Upper Gastrointestinal Bleeding.

    Science.gov (United States)

    Lee, Seung Hoon; Min, Yang Won; Bae, Joohwan; Lee, Hyuk; Min, Byung Hoon; Lee, Jun Haeng; Rhee, Poong Lyul; Kim, Jae J

    2017-11-01

    The predictive role of lactate in patients with nonvariceal upper gastrointestinal bleeding (NVUGIB) has been suggested. This study evaluated several lactate parameters in terms of predicting outcomes of bleeding patients and sought to establish a new scoring model by combining lactate parameters and the AIMS65 score. A total of 114 patients with NVUGIB who underwent serum lactate level testing at least twice and endoscopic hemostasis within 24 hours after admission were retrospectively analyzed. The associations between five lactate parameters and clinical outcomes were evaluated and the predictive power of lactate parameter combined AIMS65s (L-AIMS65s) and AIMS56 scoring was compared. The most common cause of bleeding was gastric ulcer (48.2%). Lactate clearance rate (LCR) was associated with 30-day rebleeding (odds ratio [OR], 0.931; 95% confidence interval [CI], 0.872-0.994; P = 0.033). Initial lactate (OR, 1.313; 95% CI, 1.050-1.643; P = 0.017), maximal lactate (OR, 1.277; 95% CI, 1.037-1.573; P = 0.021), and average lactate (OR, 1.535; 95% CI, 1.137-2.072; P = 0.005) levels were associated with 30-day mortality. Initial lactate (OR, 1.213; 95% CI, 1.027-1.432; P = 0.023), maximal lactate (OR, 1.271; 95% CI, 1.074-1.504; P = 0.005), and average lactate (OR, 1.501; 95% CI, 1.150-1.959; P = 0.003) levels were associated with admission over 7 days. Although L-AIMS65s showed the highest area under the curve for prediction of each outcome, differences between L-AIMS65s and AIMS65 did not reach statistical significance. In conclusion, lactate parameters have a prognostic role in patients with NVUGIB. However, they do not increase the predictive power of AIMS65 when combined. © 2017 The Korean Academy of Medical Sciences.

  1. The predicted influence of climate change on lesser prairie-chicken reproductive parameters

    Science.gov (United States)

    Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

    2013-01-01

    The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

  2. Uranium solubility and speciation in ground water

    International Nuclear Information System (INIS)

    Ollila, K.

    1985-04-01

    The purpose of this study has been to assess the solubility and possible species of uranium in groundwater at the disposal conditions of spent fuel. The effects of radiolysis and bentonite are considered. The assessment is based on the theoretical calculations found in the literature. The Finnish experimental results are included. The conservative estimate for uranium solubility under the oxidizing conditions caused by alpha radiolysis is based on the oxidation of uranium to the U(VI) state and formation of carbonate complex. For the groundwater with the typical carbonate content of 275 mg/l and the high carbonate content of 485 mg/l due to bentonite, the solubility values of 360 mg u/l and 950 mg U/l, are obtained, respectively. The experimental results predict considerably lower values, 0.5-20 mg U/l. The solubility of uranium under the undisturbed reducing conditions may be calculated based on the hydrolysis, carbonate complexation and redox reactions. The results vary considerably depending on the thermodynamic data used. The wide ranges of the most important groundwater parameters are seen in the solubility values. The experimental results show the same trends. As a conservative value for the solubility in reducing groundwater 50-500 μg U/l is estimated. (author)

  3. Unchanged Levels of Soluble CD14 and IL-6 Over Time Predict Serious Non-AIDS Events in HIV-1-Infected People

    Science.gov (United States)

    Sunil, Meena; Nigalye, Maitreyee; Somasunderam, Anoma; Martinez, Maria Laura; Yu, Xiaoying; Arduino, Roberto C.; Bell, Tanvir K.

    2016-01-01

    Abstract HIV-1-infected persons have increased risk of serious non-AIDS events (SNAEs) despite suppressive antiretroviral therapy. Increased circulating levels of soluble CD14 (sCD14), soluble CD163 (sCD163), and interleukin-6 (IL-6) at a single time point have been associated with SNAEs. However, whether changes in these biomarker levels predict SNAEs in HIV-1-infected persons is unknown. We hypothesized that greater decreases in inflammatory biomarkers would be associated with fewer SNAEs. We identified 39 patients with SNAEs, including major cardiovascular events, end stage renal disease, decompensated cirrhosis, non-AIDS-defining malignancies, and death of unknown cause, and age- and sex-matched HIV-1-infected controls. sCD14, sCD163, and IL-6 were measured at study enrollment (T1) and proximal to the event (T2) or equivalent duration in matched controls. Over ∼34 months, unchanged rather than decreasing levels of sCD14 and IL-6 predicted SNAEs. Older age and current illicit substance abuse, but not HCV coinfection, were associated with SNAEs. In a multivariate analysis, older age, illicit substance use, and unchanged IL-6 levels remained significantly associated with SNAEs. Thus, the trajectories of sCD14 and IL-6 levels predict SNAEs. Interventions to decrease illicit substance use may decrease the risk of SNAEs in HIV-1-infected persons. PMID:27344921

  4. Improving weather predictability by including land-surface model parameter uncertainty

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

    2016-04-01

    The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by

  5. Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures

    Science.gov (United States)

    Lucas, D. D.; Klein, R.; Tannahill, J.; Brandon, S.; Covey, C. C.; Domyancic, D.; Ivanova, D. P.

    2012-12-01

    Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Statistical analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation failures of the Parallel Ocean Program (POP2). About 8.5% of our POP2 runs failed for numerical reasons at certain combinations of parameter values. We apply support vector machine (SVM) classification from the fields of pattern recognition and machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. The SVM classifiers readily predict POP2 failures in an independent validation ensemble, and are subsequently used to determine the causes of the failures via a global sensitivity analysis. Four parameters related to ocean mixing and viscosity are identified as the major sources of POP2 failures. Our method can be used to improve the robustness of complex scientific models to parameter perturbations and to better steer UQ ensembles. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).

  6. Adaptability and Prediction of Anticipatory Muscular Activity Parameters to Different Movements in the Sitting Position.

    Science.gov (United States)

    Chikh, Soufien; Watelain, Eric; Faupin, Arnaud; Pinti, Antonio; Jarraya, Mohamed; Garnier, Cyril

    2016-08-01

    Voluntary movement often causes postural perturbation that requires an anticipatory postural adjustment to minimize perturbation and increase the efficiency and coordination during execution. This systematic review focuses specifically on the relationship between the parameters of anticipatory muscular activities and movement finality in sitting position among adults, to study the adaptability and predictability of anticipatory muscular activities parameters to different movements and conditions in sitting position in adults. A systematic literature search was performed using PubMed, Science Direct, Web of Science, Springer-Link, Engineering Village, and EbscoHost. Inclusion and exclusion criteria were applied to retain the most rigorous and specific studies, yielding 76 articles, Seventeen articles were excluded at first reading, and after the application of inclusion and exclusion criteria, 23 were retained. In a sitting position, central nervous system activity precedes movement by diverse anticipatory muscular activities and shows the ability to adapt anticipatory muscular activity parameters to the movement direction, postural stability, or charge weight. In addition, these parameters could be adapted to the speed of execution, as found for the standing position. Parameters of anticipatory muscular activities (duration, order, and amplitude of muscle contractions constituting the anticipatory muscular activity) could be used as a predictive indicator of forthcoming movement. In addition, this systematic review may improve methodology in empirical studies and assistive technology for people with disabilities. © The Author(s) 2016.

  7. A network security situation prediction model based on wavelet neural network with optimized parameters

    Directory of Open Access Journals (Sweden)

    Haibo Zhang

    2016-08-01

    Full Text Available The security incidents ion networks are sudden and uncertain, it is very hard to precisely predict the network security situation by traditional methods. In order to improve the prediction accuracy of the network security situation, we build a network security situation prediction model based on Wavelet Neural Network (WNN with optimized parameters by the Improved Niche Genetic Algorithm (INGA. The proposed model adopts WNN which has strong nonlinear ability and fault-tolerance performance. Also, the parameters for WNN are optimized through the adaptive genetic algorithm (GA so that WNN searches more effectively. Considering the problem that the adaptive GA converges slowly and easily turns to the premature problem, we introduce a novel niche technology with a dynamic fuzzy clustering and elimination mechanism to solve the premature convergence of the GA. Our final simulation results show that the proposed INGA-WNN prediction model is more reliable and effective, and it achieves faster convergence-speed and higher prediction accuracy than the Genetic Algorithm-Wavelet Neural Network (GA-WNN, Genetic Algorithm-Back Propagation Neural Network (GA-BPNN and WNN.

  8. Genetic Learning of Fuzzy Parameters in Predictive and Decision Support Modelling

    Directory of Open Access Journals (Sweden)

    Nebot

    2012-04-01

    Full Text Available In this research a genetic fuzzy system (GFS is proposed that performs discretization parameter learning in the context of the Fuzzy Inductive Reasoning (FIR methodology and the Linguistic Rule FIR (LR-FIR algorithm. The main goal of the GFS is to take advantage of the potentialities of GAs to learn the fuzzification parameters of the FIR and LR-FIR approaches in order to obtain reliable and useful predictive (FIR models and decision support (LR-FIR models. The GFS is evaluated in an e-learning context.

  9. Predicting Collateral Status With Magnetic Resonance Perfusion Parameters: Probabilistic Approach With a Tmax-Derived Prediction Model.

    Science.gov (United States)

    Lee, Mi Ji; Son, Jeong Pyo; Kim, Suk Jae; Ryoo, Sookyung; Woo, Sook-Young; Cha, Jihoon; Kim, Gyeong-Moon; Chung, Chin-Sang; Lee, Kwang Ho; Bang, Oh Young

    2015-10-01

    Good collateral flow is an important predictor for favorable responses to recanalization therapy and successful outcomes after acute ischemic stroke. Magnetic resonance perfusion-weighted imaging (MRP) is widely used in patients with stroke. However, it is unclear whether the perfusion parameters and thresholds would predict collateral status. The present study evaluated the relationship between hypoperfusion severity and collateral status to develop a predictive model for good collaterals using MRP parameters. Patients who were eligible for recanalization therapy that underwent both serial diffusion-weighted imaging and serial MRP were enrolled into the study. A collateral flow map derived from MRP source data was generated through automatic postprocessing. Hypoperfusion severity, presented as proportions of every 2-s Tmax strata to the entire hypoperfusion volume (Tmax≥2 s), was compared between patients with good and poor collaterals. Prediction models for good collaterals were developed with each Tmax strata proportion and cerebral blood volumes. Among 66 patients, 53 showed good collaterals based on MRP-based collateral grading. Although no difference was noted in delays within 16 s, more severe Tmax delays (Tmax16-18 s, Tmax18-22 s, Tmax22-24 s, and Tmax>24 s) were associated with poor collaterals. The probability equation model using Tmax strata proportion demonstrated high predictive power in a receiver operating characteristic analysis (area under the curve=0.9303; 95% confidence interval, 0.8682-0.9924). The probability score was negatively correlated with the volume of infarct growth (P=0.030). Collateral status is associated with more severe Tmax delays than previously defined. The present Tmax severity-weighted model can determine good collaterals and subsequent infarct growth. © 2015 American Heart Association, Inc.

  10. Plutonium solubilities

    International Nuclear Information System (INIS)

    Puigdomnech, I.; Bruno, J.

    1991-02-01

    Thermochemical data has been selected for plutonium oxide, hydroxide, carbonate and phosphate equilibria. Equilibrium constants have been evaluated in the temperature range 0 to 300 degrees C at a pressure of 1 bar to T≤100 degrees C and at the steam saturated pressure at higher temperatures. Measured solubilities of plutonium that are reported in the literature for laboratory experiments have been collected. Solubility data on oxides, hydroxides, carbonates and phosphates have been selected. No solubility data were found at temperatures higher than 60 degrees C. The literature solubility data have been compared with plutonium solubilities calculated with the EQ3/6 geochemical modelling programs, using the selected thermodynamic data for plutonium. (authors)

  11. Nonlinear Prediction As A Tool For Determining Parameters For Phase Space Reconstruction In Meteorology

    Science.gov (United States)

    Miksovsky, J.; Raidl, A.

    Time delays phase space reconstruction represents one of useful tools of nonlinear time series analysis, enabling number of applications. Its utilization requires the value of time delay to be known, as well as the value of embedding dimension. There are sev- eral methods how to estimate both these parameters. Typically, time delay is computed first, followed by embedding dimension. Our presented approach is slightly different - we reconstructed phase space for various combinations of mentioned parameters and used it for prediction by means of the nearest neighbours in the phase space. Then some measure of prediction's success was computed (correlation or RMSE, e.g.). The position of its global maximum (minimum) should indicate the suitable combination of time delay and embedding dimension. Several meteorological (particularly clima- tological) time series were used for the computations. We have also created a MS- Windows based program in order to implement this approach - its basic features will be presented as well.

  12. Parameters Online Detection and Model Predictive Control during the Grain Drying Process

    Directory of Open Access Journals (Sweden)

    Lihui Zhang

    2013-01-01

    Full Text Available In order to improve the grain drying quality and automation level, combined with the structural characteristics of the cross-flow circulation grain dryer designed and developed by us, the temperature, moisture, and other parameters measuring sensors were placed on the dryer, to achieve online automatic detection of process parameters during the grain drying process. A drying model predictive control system was set up. A grain dry predictive control model at constant velocity and variable temperature was established, in which the entire process was dried at constant velocity (i.e., precipitation rate per hour is a constant and variable temperature. Combining PC with PLC, and based on LabVIEW, a system control platform was designed.

  13. Model structural uncertainty quantification and hydrologic parameter and prediction error analysis using airborne electromagnetic data

    DEFF Research Database (Denmark)

    Minsley, B. J.; Christensen, Nikolaj Kruse; Christensen, Steen

    Model structure, or the spatial arrangement of subsurface lithological units, is fundamental to the hydrological behavior of Earth systems. Knowledge of geological model structure is critically important in order to make informed hydrological predictions and management decisions. Model structure...... is never perfectly known, however, and incorrect assumptions can be a significant source of error when making model predictions. We describe a systematic approach for quantifying model structural uncertainty that is based on the integration of sparse borehole observations and large-scale airborne...... electromagnetic (AEM) data. Our estimates of model structural uncertainty follow a Bayesian framework that accounts for both the uncertainties in geophysical parameter estimates given AEM data, and the uncertainties in the relationship between lithology and geophysical parameters. Using geostatistical sequential...

  14. Clinical Significance of Hemostatic Parameters in the Prediction for Type 2 Diabetes Mellitus and Diabetic Nephropathy

    Directory of Open Access Journals (Sweden)

    Lianlian Pan

    2018-01-01

    Full Text Available It would be important to predict type 2 diabetes mellitus (T2DM and diabetic nephropathy (DN. This study was aimed at evaluating the predicting significance of hemostatic parameters for T2DM and DN. Plasma coagulation and hematologic parameters before treatment were measured in 297 T2DM patients. The risk factors and their predicting power were evaluated. T2DM patients without complications exhibited significantly different activated partial thromboplastin time (aPTT, platelet (PLT, and D-dimer (D-D levels compared with controls (P<0.01. Fibrinogen (FIB, PLT, and D-D increased in DN patients compared with those without complications (P<0.001. Both aPTT and PLT were the independent risk factors for T2DM (OR: 1.320 and 1.211, P<0.01, resp., and FIB and PLT were the independent risk factors for DN (OR: 1.611 and 1.194, P<0.01, resp.. The area under ROC curve (AUC of aPTT and PLT was 0.592 and 0.647, respectively, with low sensitivity in predicting T2DM. AUC of FIB was 0.874 with high sensitivity (85% and specificity (76% for DN, and that of PLT was 0.564, with sensitivity (60% and specificity (89% based on the cutoff values of 3.15 g/L and 245 × 109/L, respectively. This study suggests that hemostatic parameters have a low predicting value for T2DM, whereas fibrinogen is a powerful predictor for DN.

  15. Safety analysis methodology with assessment of the impact of the prediction errors of relevant parameters

    International Nuclear Information System (INIS)

    Galia, A.V.

    2011-01-01

    The best estimate plus uncertainty approach (BEAU) requires the use of extensive resources and therefore it is usually applied for cases in which the available safety margin obtained with a conservative methodology can be questioned. Outside the BEAU methodology, there is not a clear approach on how to deal with the issue of considering the uncertainties resulting from prediction errors in the safety analyses performed for licensing submissions. However, the regulatory document RD-310 mentions that the analysis method shall account for uncertainties in the analysis data and models. A possible approach is presented, that is simple and reasonable, representing just the author's views, to take into account the impact of prediction errors and other uncertainties when performing safety analysis in line with regulatory requirements. The approach proposes taking into account the prediction error of relevant parameters. Relevant parameters would be those plant parameters that are surveyed and are used to initiate the action of a mitigating system or those that are representative of the most challenging phenomena for the integrity of a fission barrier. Examples of the application of the methodology are presented involving a comparison between the results with the new approach and a best estimate calculation during the blowdown phase for two small breaks in a generic CANDU 6 station. The calculations are performed with the CATHENA computer code. (author)

  16. Doppler Ultrasonographic Parameters for Predicting Cerebral Vascular Reserve in Patients with Acute Ischemic Stroke

    International Nuclear Information System (INIS)

    Jung, Han Young; Lee, Hui Joong; Kim, Hye Jung; Kim, Yong Sun; Kang, Duk Sik

    2006-01-01

    We investigated Doppler ultrasonographic (US) parameters of patients with acute stroke to predict the cerebral vascular reserve (CVR) measured by SPECT. We reviewed the flow velocity and cross-sectional area of the circular vessel at the common, external, and internal carotid arteries (ICA) and the vertebral arteries (VA) in 109 acute stroke patients who underwent SPECT. Flow volume (FV) of each artery was calculated as the product of the angle-corrected time averaged flow velocity and cross-sectional area of the circular vessel. Total cerebral FV (TCBFV) was determined as the sum of the FVs of the right and left ICA and VA. We compared the Doppler US parameters between 44 cases of preserved and 65 cases of impaired CVR. In the preserved CVR group, ICA FV, anterior circulating FV (ACFV) and TCBFV were higher than in the impaired CVR group (p < 0.05, independent t-test). In the impaired CVR group, the ROC curves showed ACFV and TCBFV were suitable parameters to predict CVR (p < 0.05). Doppler US was helpful for understanding the hemodynamic state of acute stroke. FV measurement by Doppler US was useful for predicting CVR

  17. Predicting hepatic steatosis and liver fat content in obese children based on biochemical parameters and anthropometry.

    Science.gov (United States)

    Zhang, H-X; Xu, X-Q; Fu, J-F; Lai, C; Chen, X-F

    2015-04-01

    Predictors of quantitative evaluation of hepatic steatosis and liver fat content (LFC) using clinical and laboratory variables available in the general practice in the obese children are poorly identified. To build predictive models of hepatic steatosis and LFC in obese children based on biochemical parameters and anthropometry. Hepatic steatosis and LFC were determined using proton magnetic resonance spectroscopy in 171 obese children aged 5.5-18.0 years. Routine clinical and laboratory parameters were also measured in all subjects. Group analysis, univariable correlation analysis, and multivariate logistic and linear regression analysis were used to develop a liver fat score to identify hepatic steatosis and a liver fat equation to predict LFC in each subject. The predictive model of hepatic steatosis in our participants based on waist circumference and alanine aminotransferase had an area under the receiver operating characteristic curve of 0.959 (95% confidence interval: 0.927-0.990). The optimal cut-off value of 0.525 for determining hepatic steatosis had sensitivity of 93% and specificity of 90%. A liver fat equation was also developed based on the same parameters of hepatic steatosis liver fat score, which would be used to calculate the LFC in each individual. The liver fat score and liver fat equation, consisting of routinely available variables, may help paediatricians to accurately determine hepatic steatosis and LFC in clinical practice, but external validation is needed before it can be employed for this purpose. © 2014 The Authors. Pediatric Obesity © 2014 World Obesity.

  18. An improved method for predicting the evolution of the characteristic parameters of an information system

    Science.gov (United States)

    Dushkin, A. V.; Kasatkina, T. I.; Novoseltsev, V. I.; Ivanov, S. V.

    2018-03-01

    The article proposes a forecasting method that allows, based on the given values of entropy and error level of the first and second kind, to determine the allowable time for forecasting the development of the characteristic parameters of a complex information system. The main feature of the method under consideration is the determination of changes in the characteristic parameters of the development of the information system in the form of the magnitude of the increment in the ratios of its entropy. When a predetermined value of the prediction error ratio is reached, that is, the entropy of the system, the characteristic parameters of the system and the depth of the prediction in time are estimated. The resulting values of the characteristics and will be optimal, since at that moment the system possessed the best ratio of entropy as a measure of the degree of organization and orderliness of the structure of the system. To construct a method for estimating the depth of prediction, it is expedient to use the maximum principle of the value of entropy.

  19. A bi-layer model for nondestructive prediction of soluble solids content in apple based on reflectance spectra and peel pigments.

    Science.gov (United States)

    Tian, Xi; Li, Jiangbo; Wang, Qingyan; Fan, Shuxiang; Huang, Wenqian

    2018-01-15

    Hyperspectral imaging technology was used to investigate the effect of various peel colors on soluble solids content (SSC) prediction model and build a SSC model insensitive to the color distribution of apple peel. The SSC and peel pigments were measured, effective wavelengths (EWs) of SSC and pigments were selected from the acquired hyperspectral images of the intact and peeled apple samples, respectively. The effect of pigments on the SSC prediction was studied and optimal SSC EWs were selected from the peel-flesh layers spectra after removing the chlorophyll and anthocyanin EWs. Then, the optimal bi-layer model for SSC prediction was built based on the finally selected optimal SSC EWs. Results showed that the correlation coefficient of prediction, root mean square error of prediction and selected bands of the bi-layer model were 0.9560, 0.2528 and 41, respectively, which will be more acceptable for future online SSC prediction of various colors of apple. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Comparative evaluation of red cell-labelling parameters of three lipid-soluble 111-In-chelates: Effect of lipid solubility on membrane incorporation and stability constant on transchelation

    International Nuclear Information System (INIS)

    Rao, S.A.; Dewanjee, M.K.

    1982-01-01

    A rabbit red cell model was used to determined the cell labeling properties of three lipid-soluble 111 In-complexes: 111 In-oxine, 111 In-acetylacetone, and 111 In-tropolone. Partition coefficients (olive oil/buffer) were measured to determine the lipid solubility and were 3.54, 7.93, and 18.18 for 111 In-oxine, 111 In-acetylacetone, and 111 In-tropolone respectively. The effect of the concentration of these three chelating agents on labeling efficiencies was studied. The factors influencing the labeling efficiencies of these complexes such as cell density, time of incubation, influence of temperature, pH, effect of plasma proteins, and citrate ion concentration in the cell-labeling medium were studied. Labeling yields as high as 95.15 +- 4.15% were achieved with 111 In-tropolone after a 10-min incubation at 37 0 C. The optimum pH for cell labeling was 6.5 Excess critrate ion (> 3.02 mg/ml) and small amounts of plasma proteins (> 10 μl/ml) decreased the labeling efficiencies in all three cases. Distribution of these 111 In-complexes in membrane, membrane frgments, and hemoglobin was studied after hemolysis. In spite of the higher lipid solubility of 111 In-tropolone, the transchelation capacity appears to be similar to that of 111 In-oxine. 111 In-acetylacetone had the highest transchelation capacity. (orig.)

  1. Development of Health Parameter Model for Risk Prediction of CVD Using SVM

    Directory of Open Access Journals (Sweden)

    P. Unnikrishnan

    2016-01-01

    Full Text Available Current methods of cardiovascular risk assessment are performed using health factors which are often based on the Framingham study. However, these methods have significant limitations due to their poor sensitivity and specificity. We have compared the parameters from the Framingham equation with linear regression analysis to establish the effect of training of the model for the local database. Support vector machine was used to determine the effectiveness of machine learning approach with the Framingham health parameters for risk assessment of cardiovascular disease (CVD. The result shows that while linear model trained using local database was an improvement on Framingham model, SVM based risk assessment model had high sensitivity and specificity of prediction of CVD. This indicates that using the health parameters identified using Framingham study, machine learning approach overcomes the low sensitivity and specificity of Framingham model.

  2. Estimating unknown input parameters when implementing the NGA ground-motion prediction equations in engineering practice

    Science.gov (United States)

    Kaklamanos, James; Baise, Laurie G.; Boore, David M.

    2011-01-01

    The ground-motion prediction equations (GMPEs) developed as part of the Next Generation Attenuation of Ground Motions (NGA-West) project in 2008 are becoming widely used in seismic hazard analyses. However, these new models are considerably more complicated than previous GMPEs, and they require several more input parameters. When employing the NGA models, users routinely face situations in which some of the required input parameters are unknown. In this paper, we present a framework for estimating the unknown source, path, and site parameters when implementing the NGA models in engineering practice, and we derive geometrically-based equations relating the three distance measures found in the NGA models. Our intent is for the content of this paper not only to make the NGA models more accessible, but also to help with the implementation of other present or future GMPEs.

  3. An investigation of engine performance parameters and artificial intelligent emission prediction of hydrogen powered car

    International Nuclear Information System (INIS)

    Ho, Tien; Karri, Vishy; Lim, Daniel; Barret, Danny

    2008-01-01

    With the depletion of fossil fuel resources and the potential consequences of climate change due to fossil fuel use, much effort has been put into the search for alternative fuels for transportation. Although there are several potential alternative fuels, which have low impact on the environment, none of these fuels have the ability to be used as the sole 'fuel of the future'. One fuel which is likely to become a part of the over all solution to the transportation fuel dilemma is hydrogen. In this paper, The Toyota Corolla four cylinder, 1.8 l engine running on petrol is systematically converted to run on hydrogen. Several ancillary instruments for measuring various engine operating parameters and emissions are fitted to appraise the performance of the hydrogen car. The effect of hydrogen as a fuel compares with gasoline on engine operating parameters and effect of engine operating parameters on emission characteristics is discussed. Based on the experimental setup, a suite of neural network models were tested to accurately predict the effect of major engine operating conditions on the hydrogen car emissions. Predictions were found to be ±4% to the experimental values. This work provided better understanding of the effect of engine process parameters on emissions. (author)

  4. Prediction of polycystic ovarian syndrome based on ultrasound findings and clinical parameters.

    Science.gov (United States)

    Moschos, Elysia; Twickler, Diane M

    2015-03-01

    To determine the accuracy of sonographic-diagnosed polycystic ovaries and clinical parameters in predicting polycystic ovarian syndrome. Medical records and ultrasounds of 151 women with sonographically diagnosed polycystic ovaries were reviewed. Sonographic criteria for polycystic ovaries were based on 2003 Rotterdam European Society of Human Reproduction and Embryology/American Society for Reproductive Medicine guidelines: at least one ovary with 12 or more follicles measuring 2-9 mm and/or increased ovarian volume >10 cm(3) . Clinical variables of age, gravidity, ethnicity, body mass index, and sonographic indication were collected. One hundred thirty-five patients had final outcomes (presence/absence of polycystic ovarian syndrome). Polycystic ovarian syndrome was diagnosed if a patient had at least one other of the following two criteria: oligo/chronic anovulation and/or clinical/biochemical hyperandrogenism. A logistic regression model was constructed using stepwise selection to identify variables significantly associated with polycystic ovarian syndrome (p polycystic ovaries and 115 (89.8%) had polycystic ovarian syndrome (p = .009). Lower gravidity, abnormal bleeding, and body mass index >33 were significant in predicting polycystic ovarian syndrome (receiver operating characteristics curve, c = 0.86). Pain decreased the likelihood of polycystic ovarian syndrome. Polycystic ovaries on ultrasound were sensitive in predicting polycystic ovarian syndrome. Ultrasound, combined with clinical parameters, can be used to generate a predictive index for polycystic ovarian syndrome. © 2014 Wiley Periodicals, Inc.

  5. Improved time series prediction with a new method for selection of model parameters

    International Nuclear Information System (INIS)

    Jade, A M; Jayaraman, V K; Kulkarni, B D

    2006-01-01

    A new method for model selection in prediction of time series is proposed. Apart from the conventional criterion of minimizing RMS error, the method also minimizes the error on the distribution of singularities, evaluated through the local Hoelder estimates and its probability density spectrum. Predictions of two simulated and one real time series have been done using kernel principal component regression (KPCR) and model parameters of KPCR have been selected employing the proposed as well as the conventional method. Results obtained demonstrate that the proposed method takes into account the sharp changes in a time series and improves the generalization capability of the KPCR model for better prediction of the unseen test data. (letter to the editor)

  6. Micro-scale prediction method for API-solubility in polymeric matrices and process model for forming amorphous solid dispersion by hot-melt extrusion.

    Science.gov (United States)

    Bochmann, Esther S; Neumann, Dirk; Gryczke, Andreas; Wagner, Karl G

    2016-10-01

    A new predictive micro-scale solubility and process model for amorphous solid dispersions (ASDs) by hot-melt extrusion (HME) is presented. It is based on DSC measurements consisting of an annealing step and a subsequent analysis of the glass transition temperature (Tg). The application of a complex mathematical model (BCKV-equation) to describe the dependency of Tg on the active pharmaceutical ingredient (API)/polymer ratio, enables the prediction of API solubility at ambient conditions (25°C). Furthermore, estimation of the minimal processing temperature for forming ASDs during HME trials could be defined and was additionally confirmed by X-ray powder diffraction data. The suitability of the DSC method was confirmed with melt rheological trials (small amplitude oscillatory system). As an example, ball milled physical mixtures of dipyridamole, indomethacin, itraconazole and nifedipine in poly(vinylpyrrolidone-co-vinylacetate) (copovidone) and polyvinyl caprolactam-polyvinyl acetate-polyethylene glycol graft copolymer (Soluplus®) were used. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Serum markers of macrophage activation in pre-eclampsia: no predictive value of soluble CD163 and neopterin

    DEFF Research Database (Denmark)

    Kronborg, Camilla S; Knudsen, Ulla Breth; Moestrup, Søren K

    2007-01-01

    BACKGROUND: Alternatively activated macrophages expressing the CD163 and CD206 surface receptors are the dominant immune-cell type found in the placenta. The placental number and distribution of macrophages is altered in pre-eclampsia, and the generalised inflammatory reaction associated with pre-eclampsia...... might lead to shedding of soluble CD163 into the circulation. METHODS: Serum samples from 18 women with pre-eclampsia and 90 normal pregnancies were obtained from a longitudinal study of 955 pregnant women at Randers County Hospital, Denmark. sCD163 and Neopterin were measured by ELISA on samples....... Neopterin increased throughout pregnancy in both healthy (from median 5.4 to 6.7 nmol/l, ppre-eclampsia...

  8. Combining in vitro and in silico methods for better prediction of surfactant effects on the absorption of poorly water soluble drugs-a fenofibrate case example.

    Science.gov (United States)

    Berthelsen, Ragna; Sjögren, Erik; Jacobsen, Jette; Kristensen, Jakob; Holm, René; Abrahamsson, Bertil; Müllertz, Anette

    2014-10-01

    The aim of this study was to develop a sensitive and discriminative in vitro-in silico model able to simulate the in vivo performance of three fenofibrate immediate release formulations containing different surfactants. In addition, the study was designed to investigate the effect of dissolution volume when predicting the oral bioavailability of the formulations. In vitro dissolution studies were carried out using the USP apparatus 2 or a mini paddle assembly, containing 1000 mL or 100mL fasted state biorelevant medium, respectively. In silico simulations of small intestinal absorption were performed using the GI-Sim absorption model. All simulation runs were performed twice adopting either a total small intestinal volume of 533 mL or 105 mL, in order to examine the implication of free luminal water volumes for the in silico predictions. For the tested formulations, the use of a small biorelevant dissolution volume was critical for in vitro-in silico prediction of drug absorption. Good predictions, demonstrating rank order in vivo-in vitro-in silico correlations for Cmax, were obtained with in silico predictions utilizing a 105 mL estimate for the human intestinal water content combined with solubility and dissolution data performed in a mini paddle apparatus with 100mL fasted state simulated media. Copyright © 2014. Published by Elsevier B.V.

  9. Semen parameters can be predicted from environmental factors and lifestyle using artificial intelligence methods.

    Science.gov (United States)

    Girela, Jose L; Gil, David; Johnsson, Magnus; Gomez-Torres, María José; De Juan, Joaquín

    2013-04-01

    Fertility rates have dramatically decreased in the last two decades, especially in men. It has been described that environmental factors as well as life habits may affect semen quality. In this paper we use artificial intelligence techniques in order to predict semen characteristics resulting from environmental factors, life habits, and health status, with these techniques constituting a possible decision support system that can help in the study of male fertility potential. A total of 123 young, healthy volunteers provided a semen sample that was analyzed according to the World Health Organization 2010 criteria. They also were asked to complete a validated questionnaire about life habits and health status. Sperm concentration and percentage of motile sperm were related to sociodemographic data, environmental factors, health status, and life habits in order to determine the predictive accuracy of a multilayer perceptron network, a type of artificial neural network. In conclusion, we have developed an artificial neural network that can predict the results of the semen analysis based on the data collected by the questionnaire. The semen parameter that is best predicted using this methodology is the sperm concentration. Although the accuracy for motility is slightly lower than that for concentration, it is possible to predict it with a significant degree of accuracy. This methodology can be a useful tool in early diagnosis of patients with seminal disorders or in the selection of candidates to become semen donors.

  10. Systematic review of dose-volume parameters in the prediction of esophagitis in thoracic radiotherapy

    International Nuclear Information System (INIS)

    Rose, Jim; Rodrigues, George; Yaremko, Brian; Lock, Michael; D'Souza, David

    2009-01-01

    Purpose: With dose escalation and increasing use of concurrent chemoradiotherapy, radiation esophagitis (RE) remains a common treatment-limiting acute side effect in the treatment of thoracic malignancies. The advent of 3DCT planning has enabled investigators to study esophageal dose-volume histogram (DVH) parameters as predictors of RE. The purpose of this study was to assess published dosimetric parameters and toxicity data systematically in order to define reproducible predictors of RE, both for potential clinical use, and to provide recommendations for future research in the field. Materials and methods: We performed a systematic literature review of published studies addressing RE in the treatment of lung cancer and thymoma. Our search strategy included a variety of electronic medical databases, textbooks and bibliographies. Both prospective and retrospective clinical studies were included. Information relating to the relationship among measured dosimetric parameters, patient demographics, tumor characteristics, chemotherapy and RE was extracted and analyzed. Results: Eighteen published studies were suitable for analysis. Eleven of these assessed acute RE, while the remainder assessed both acute and chronic RE together. Heterogeneity of esophageal contouring practices, individual differences in information reporting and variability of RE outcome definitions were assessed. Well-described clinical and logistic modeling directly related V 35Gy , V 60Gy and SA 55Gy to clinically significant RE. Conclusions: Several reproducible dosimetric parameters exist in the literature, and these may be potentially relevant in the prediction of RE in the radiotherapy of thoracic malignancies. Further clarification of the predictive relationship between such standardized dosimetric parameters and observed RE outcomes is essential to develop efficient radiation treatment planning in locally advanced NSCLC in the modern concurrent chemotherapy and image-guided IMRT era.

  11. Guidelineness of the parameters using integrated test in down syndrome risk prediction

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jin Won [Graduate School of Catholic University of Pusan, Busan (Korea, Republic of); Go, Sung Jin; Kang, Se Sik; Kim, Chang Soo [Dept. Radiological Science, College of Health Sciences, Catholic University of Pusan, Busan (Korea, Republic of)

    2016-12-15

    This study was an evaluation of the significance of each parameter through aimed at pregnant women subjected to screening test(integrated test) in predicting risk of Down syndrome. We retrospectively analysed the correlation of risk of Down's syndrome with Nuchal Translucency(NT) images measured by ultrasound, Pregnancy Associated Plasma Protein A(PAPP-A), alpha-fetoprotein(AFP), unconjugated estriol(uE3), human chorionic gonadotrophin(hCG) and Inhibin A by maternal serum. As a result, a significant correlation with NT, uE3, hCG, Inhibin A is revealed with Down's syndrome risk(P<.001). In ROC analysis, AUC of Inhibin A is analysed as the biggest predictor of Down's syndrome(0.859). And the criterion for cut-off was inhibin A 1.4 MoM(sensitivity 81.8%, specificity 75.9%). In conclusion, Inhibin A was the most useful in parameters to predict Down's syndrome in the integrated test. If we make up for the weakness based on the cut-off value of parameters they will be able to be used as an independent indicator in the risk of Down's syndrome screening.

  12. A Bayesian approach for parameter estimation and prediction using a computationally intensive model

    International Nuclear Information System (INIS)

    Higdon, Dave; McDonnell, Jordan D; Schunck, Nicolas; Sarich, Jason; Wild, Stefan M

    2015-01-01

    Bayesian methods have been successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model η(θ), where θ denotes the uncertain, best input setting. Hence the statistical model is of the form y=η(θ)+ϵ, where ϵ accounts for measurement, and possibly other, error sources. When nonlinearity is present in η(⋅), the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and nonstandard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. Although generally applicable, MCMC requires thousands (or even millions) of evaluations of the physics model η(⋅). This requirement is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we present an approach adapted from Bayesian model calibration. This approach combines output from an ensemble of computational model runs with physical measurements, within a statistical formulation, to carry out inference. A key component of this approach is a statistical response surface, or emulator, estimated from the ensemble of model runs. We demonstrate this approach with a case study in estimating parameters for a density functional theory model, using experimental mass/binding energy measurements from a collection of atomic nuclei. We also demonstrate how this approach produces uncertainties in predictions for recent mass measurements obtained at Argonne National Laboratory. (paper)

  13. Guidelineness of the parameters using integrated test in down syndrome risk prediction

    International Nuclear Information System (INIS)

    Lee, Jin Won; Go, Sung Jin; Kang, Se Sik; Kim, Chang Soo

    2016-01-01

    This study was an evaluation of the significance of each parameter through aimed at pregnant women subjected to screening test(integrated test) in predicting risk of Down syndrome. We retrospectively analysed the correlation of risk of Down's syndrome with Nuchal Translucency(NT) images measured by ultrasound, Pregnancy Associated Plasma Protein A(PAPP-A), alpha-fetoprotein(AFP), unconjugated estriol(uE3), human chorionic gonadotrophin(hCG) and Inhibin A by maternal serum. As a result, a significant correlation with NT, uE3, hCG, Inhibin A is revealed with Down's syndrome risk(P<.001). In ROC analysis, AUC of Inhibin A is analysed as the biggest predictor of Down's syndrome(0.859). And the criterion for cut-off was inhibin A 1.4 MoM(sensitivity 81.8%, specificity 75.9%). In conclusion, Inhibin A was the most useful in parameters to predict Down's syndrome in the integrated test. If we make up for the weakness based on the cut-off value of parameters they will be able to be used as an independent indicator in the risk of Down's syndrome screening

  14. A predictive thermal dynamic model for parameter generation in the laser assisted direct write process

    International Nuclear Information System (INIS)

    Shang Shuo; Fearon, Eamonn; Wellburn, Dan; Sato, Taku; Edwardson, Stuart; Dearden, G; Watkins, K G

    2011-01-01

    The laser assisted direct write (LADW) method can be used to generate electrical circuitry on a substrate by depositing metallic ink and curing the ink thermally by a laser. Laser curing has emerged over recent years as a novel yet efficient alternative to oven curing. This method can be used in situ, over complicated 3D contours of large parts (e.g. aircraft wings) and selectively cure over heat sensitive substrates, with little or no thermal damage. In previous studies, empirical methods have been used to generate processing windows for this technique, relating to the several interdependent processing parameters on which the curing quality and efficiency strongly depend. Incorrect parameters can result in a track that is cured in some areas and uncured in others, or in damaged substrates. This paper addresses the strong need for a quantitative model which can systematically output the processing conditions for a given combination of ink, substrate and laser source; transforming the LADW technique from a purely empirical approach, to a simple, repeatable, mathematically sound, efficient and predictable process. The method comprises a novel and generic finite element model (FEM) that for the first time predicts the evolution of the thermal profile of the ink track during laser curing and thus generates a parametric map which indicates the most suitable combination of parameters for process optimization. Experimental data are compared with simulation results to verify the accuracy of the model.

  15. Multiobjective design of aquifer monitoring networks for optimal spatial prediction and geostatistical parameter estimation

    Science.gov (United States)

    Alzraiee, Ayman H.; Bau, Domenico A.; Garcia, Luis A.

    2013-06-01

    Effective sampling of hydrogeological systems is essential in guiding groundwater management practices. Optimal sampling of groundwater systems has previously been formulated based on the assumption that heterogeneous subsurface properties can be modeled using a geostatistical approach. Therefore, the monitoring schemes have been developed to concurrently minimize the uncertainty in the spatial distribution of systems' states and parameters, such as the hydraulic conductivity K and the hydraulic head H, and the uncertainty in the geostatistical model of system parameters using a single objective function that aggregates all objectives. However, it has been shown that the aggregation of possibly conflicting objective functions is sensitive to the adopted aggregation scheme and may lead to distorted results. In addition, the uncertainties in geostatistical parameters affect the uncertainty in the spatial prediction of K and H according to a complex nonlinear relationship, which has often been ineffectively evaluated using a first-order approximation. In this study, we propose a multiobjective optimization framework to assist the design of monitoring networks of K and H with the goal of optimizing their spatial predictions and estimating the geostatistical parameters of the K field. The framework stems from the combination of a data assimilation (DA) algorithm and a multiobjective evolutionary algorithm (MOEA). The DA algorithm is based on the ensemble Kalman filter, a Monte-Carlo-based Bayesian update scheme for nonlinear systems, which is employed to approximate the posterior uncertainty in K, H, and the geostatistical parameters of K obtained by collecting new measurements. Multiple MOEA experiments are used to investigate the trade-off among design objectives and identify the corresponding monitoring schemes. The methodology is applied to design a sampling network for a shallow unconfined groundwater system located in Rocky Ford, Colorado. Results indicate that

  16. Dynamic interactions between hydrogeological and exposure parameters in daily dose prediction under uncertainty and temporal variability

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Vikas, E-mail: vikas.kumar@urv.cat [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Barros, Felipe P.J. de [Sonny Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles 90089, CA (United States); Schuhmacher, Marta [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier [Hydrogeology Group, Department of Geotechnical Engineering and Geosciences, University Politècnica de Catalunya-BarcelonaTech, Barcelona 08034 (Spain)

    2013-12-15

    Highlights: • Dynamic parametric interaction in daily dose prediction under uncertainty. • Importance of temporal dynamics associated with the dose. • Different dose experienced by different population cohorts as a function of time. • Relevance of uncertainty reduction in the input parameters shows temporal dynamism. -- Abstract: We study the time dependent interaction between hydrogeological and exposure parameters in daily dose predictions due to exposure of humans to groundwater contamination. Dose predictions are treated stochastically to account for an incomplete hydrogeological and geochemical field characterization, and an incomplete knowledge of the physiological response. We used a nested Monte Carlo framework to account for uncertainty and variability arising from both hydrogeological and exposure variables. Our interest is in the temporal dynamics of the total dose and their effects on parametric uncertainty reduction. We illustrate the approach to a HCH (lindane) pollution problem at the Ebro River, Spain. The temporal distribution of lindane in the river water can have a strong impact in the evaluation of risk. The total dose displays a non-linear effect on different population cohorts, indicating the need to account for population variability. We then expand the concept of Comparative Information Yield Curves developed earlier (see de Barros et al. [29]) to evaluate parametric uncertainty reduction under temporally variable exposure dose. Results show that the importance of parametric uncertainty reduction varies according to the temporal dynamics of the lindane plume. The approach could be used for any chemical to aid decision makers to better allocate resources towards reducing uncertainty.

  17. Prediction of Marshall Parameters of Modified Bituminous Mixtures Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Sunil Khuntia

    2014-09-01

    Full Text Available This study presents the application of artificial neural networks (ANN and least square support vector machine (LS-SVM for prediction of Marshall parameters obtained from Marshall tests for waste polyethylene (PE modified bituminous mixtures. Waste polyethylene in the form of fibres processed from utilized milk packets has been used to modify the bituminous mixes in order to improve their engineering properties. Marshall tests were carried out on mix specimens with variations in polyethylene and bitumen contents. It has been observed that the addition of waste polyethylene results in the improvement of Marshall characteristics such as stability, flow value and air voids, used to evaluate a bituminous mix. The proposed neural network (NN model uses the quantities of ingredients used for preparation of Marshall specimens such as polyethylene, bitumen and aggregate in order to predict the Marshall stability, flow value and air voids obtained from the tests. Out of two techniques used, the NN based model is found to be compact, reliable and predictable when compared with LS-SVM model. A sensitivity analysis has been performed to identify the importance of the parameters considered.

  18. Predictive parameters of infectiologic complications in patients after TIPSS; Praediktive Parameter infektiologischer Komplikationen bei Patienten nach TIPSS-Anlage

    Energy Technology Data Exchange (ETDEWEB)

    Cohnen, M.; Saleh, A.; Moedder, U. [Institut fuer Diagnostische Radiologie, Universitaetsklinikum Duesseldorf (Germany); Luethen, R.; Bode, J.; Haeussinger, D. [Klinik fuer Gastroenterologie, Hepatologie und Infektiologie, Universitaetsklinikum Duesseldorf (Germany); Daeubener, W. [Institut fuer Mikrobiologie und Virologie, Universitaetsklinikum Duesseldorf (Germany)

    2003-02-01

    Aim To define predictive parameters of a complicated clinical course after the TIPSS procedure. Blood cultures were drawn prospectively in 41 patients from a central line and from the portal venous blood before stent placement as well as from the central line 20 min after intervention. C-reactive proteine (CRP) (mg/dl) and white blood cell count (WBC,/{mu}l) on the day of TIPSS-procedure (d0), the first (d1) and seven (d7) days after TIPSS were compared in patients with a complicated clinical course (spontaneous bacterial peritonitis, pneumonia, sepsis; group I) to patients without clinical complications (group II) Group I showed a significant increase in CRP (d0: 1.8{+-}1.0; d1: 3.2{+-}1.5; d7: 4.3{+-}3.2), and white blood cell count (d0: 7700{+-}2600; d1: 10800{+-}2800; d7: 7500{+-}1800) on the first day after TIPSS-procedure in comparison to group II (CRP: d0: 1.6{+-}0.6; d1: 1.8{+-}1.0; d7: 1.9{+-}0.6. WBC: d0: 6900{+-}1500; d1: 8000{+-}1600; d7: 7600{+-}1400).Microbiological analysis showed in 12% skin or oral flora in the last sample. The course of CRP and WBC-count during the first week after TIPSS procedure may indicate patients with a potential risk of a complicated clinical course. (orig.) [German] Fragestellung Definition praediktiver Parameter infektiologischer Komplikationen bei Patienten nach TIPSS-Anlage.Methodik Bei 41 Patienten wurden Blutproben prospektiv vor intrahepatischer Stentanlage zentralvenoes und portalvenoes sowie 20 min postinterventionell erneut zentralvenoes entnommen und mikrobiologisch analysiert. C-reaktives Protein (CRP) (mg/dl) und Leukozytenzahl (/{mu}l) wurden am Interventionstag (d0), am 1. (d1) sowie 7 Tage (d7) postinterventionell bestimmt. Patienten mit kompliziertem Verlauf (spontane bakterielle Peritonitis,Pneumonie, Sepsis; Gruppe 1) wurden von Patienten ohne klinische Komplikationen (Gruppe 2) unterschieden.Ergebnisse Gruppe 1 wies einen signifikanten Anstieg des CRP (d0: 1,8{+-}1,0; d1: 3,2{+-}1,5; d7: 4,3{+-}3,2) und

  19. Application of a simple parameter estimation method to predict effluent transport in the Savannah River

    International Nuclear Information System (INIS)

    Hensel, S.J.; Hayes, D.W.

    1993-01-01

    A simple parameter estimation method has been developed to determine the dispersion and velocity parameters associated with stream/river transport. The unsteady one dimensional Burgers' equation was chosen as the model equation, and the method has been applied to recent Savannah River dye tracer studies. The computed Savannah River transport coefficients compare favorably with documented values, and the time/concentration curves calculated from these coefficients compare well with the actual tracer data. The coefficients were used as a predictive capability and applied to Savannah River tritium concentration data obtained during the December 1991 accidental tritium discharge from the Savannah River Site. The peak tritium concentration at the intersection of Highway 301 and the Savannah River was underpredicted by only 5% using the coefficients computed from the dye data

  20. [The role of epicardial fat and obesity parameters in the prediction of coronary heart disease].

    Science.gov (United States)

    Prídavková, Dana; Kantárová, Daniela; Lišková, Renáta; Červeň, Peter; Kovář, František; Mokáň, Marián

    2016-04-01

    To assess the relationship of parameters of obesity in relationship to coronary angiography findings with correlation of epicardial fat (EF) thickness in uppermentioned context. There were 80 patients examined (43 males, 37 postmenopausal females) undergoing elective coronary angiography. We examined the regular obesity parameters - BMI, waist circumference (WC), neck circumference (NC), total body fat (TBF), and visceral fat (VF) using bioimpedance. We assessed the echocardiographically measured EF thickness. We added examination of lipidogram, glycaemia, HOMA-IR (insulin resistance index) and AIP (aterogenic index of plasma). The set was divided into group with coronarographically proved stenosis or stenoses (withCS), and a group without finding of quantifiable stenosis or stenoses (withoutCS). The average thickness of EF in withCS group was 6.3 vs 5.6 mm in group withoutCS (p obesity parameters in assessment of pre-clinical stages of coronary atherosclerosis and prediction of risk of coronary heart disease. In adipose parameters, EF thickness was correlated the most by WC. Risk stratification of coronary artery disease is supplemented by increased HOMA-IR and AIP.

  1. Cervical Vertebral Body’s Volume as a New Parameter for Predicting the Skeletal Maturation Stages

    Directory of Open Access Journals (Sweden)

    Youn-Kyung Choi

    2016-01-01

    Full Text Available This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5–18 years of age. We performed Pearson’s correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P<0.05. The simple regression model with the greatest R-square indicated the fourth-cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level.

  2. Cervical Vertebral Body's Volume as a New Parameter for Predicting the Skeletal Maturation Stages.

    Science.gov (United States)

    Choi, Youn-Kyung; Kim, Jinmi; Yamaguchi, Tetsutaro; Maki, Koutaro; Ko, Ching-Chang; Kim, Yong-Il

    2016-01-01

    This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5-18 years of age). We performed Pearson's correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level.

  3. MODEL JARINGAN SYARAF TIRUAN UNTUK MEMPREDIKSI PARAMETER KUALITAS TOMAT BERDASARKAN PARAMETER WARNA RGB (An artificial neural network model for predicting tomato quality parameters based on color

    Directory of Open Access Journals (Sweden)

    Rudiati Evi Masithoh

    2013-03-01

    Full Text Available Artificial neural networks (ANN was used to predict the quality parameters of tomato, i.e. Brix, citric acid, total carotene, and vitamin C. ANN was developed from Red Green Blue (RGB image data of tomatoes measured using a developed computer vision system (CVS. Qualitative analysis of tomato compositions were obtained from laboratory experiments. ANN model was based on a feedforward backpropagation network with different training functions, namely gradient descent (traingd, gradient descent with the resilient backpropagation (trainrp, Broyden, Fletcher, Goldfrab and Shanno (BFGS quasi-Newton (trainbfg, as well as Levenberg Marquardt (trainlm.  The network structure using logsig and linear (purelin activation function at the hidden and output layer, respectively, and using  the trainlm as a training function resulted in the best performance. Correlation coefficient (r of training and validation process were 0.97 - 0.99 and 0.92 - 0.99, whereas the MAE values ​​ranged from 0.01 to 0.23 and 0.03 to 0.59, respectively. Keywords: Artificial neural network, trainlm, tomato, RGB   Jaringan syaraf tiruan (JST digunakan untuk memprediksi parameter kualitas tomat, yaitu Brix, asam sitrat, karoten total, dan vitamin C. JST dikembangkan dari data Red Green Blue (RGB  citra tomat yang diukur menggunakan computer vision system. Data kualitas tomat diperoleh dari analisis di laboratorium. Struktur model JST didasarkan pada jaringan feedforward backpropagation dengan berbagai fungsi pelatihan, yaitu gradient descent (traingd, gradient descent dengan resilient backpropagation (trainrp, Broyden, Fletcher, Goldfrab dan Shanno (BFGS quasi-Newton (trainbfg, serta Levenberg Marquardt (trainlm. Fungsi pelatihan yang terbaik adalah menggunakan trainlm, serta pada struktur jaringan digunakan fungsi aktivasi logsig pada lapisan tersembunyi dan linier (purelin pada lapisan keluaran. dengan 1000 epoch. Nilai koefisien korelasi (r pada tahap pelatihan dan validasi

  4. Evolving chemometric models for predicting dynamic process parameters in viscose production

    Energy Technology Data Exchange (ETDEWEB)

    Cernuda, Carlos [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Lughofer, Edwin, E-mail: edwin.lughofer@jku.at [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Suppan, Lisbeth [Kompetenzzentrum Holz GmbH, St. Peter-Str. 25, 4021 Linz (Austria); Roeder, Thomas; Schmuck, Roman [Lenzing AG, 4860 Lenzing (Austria); Hintenaus, Peter [Software Research Center, Paris Lodron University Salzburg (Austria); Maerzinger, Wolfgang [i-RED Infrarot Systeme GmbH, Linz (Austria); Kasberger, Juergen [Recendt GmbH, Linz (Austria)

    2012-05-06

    Highlights: Black-Right-Pointing-Pointer Quality assurance of process parameters in viscose production. Black-Right-Pointing-Pointer Automatic prediction of spin-bath concentrations based on FTNIR spectra. Black-Right-Pointing-Pointer Evolving chemometric models for efficiently handling changing system dynamics over time (no time-intensive re-calibration needed). Black-Right-Pointing-Pointer Significant reduction of huge errors produced by statistical state-of-the-art calibration methods. Black-Right-Pointing-Pointer Sufficient flexibility achieved by gradual forgetting mechanisms. - Abstract: In viscose production, it is important to monitor three process parameters in order to assure a high quality of the final product: the concentrations of H{sub 2}SO{sub 4}, Na{sub 2}SO{sub 4} and Z{sub n}SO{sub 4}. During on-line production these process parameters usually show a quite high dynamics depending on the fiber type that is produced. Thus, conventional chemometric models, which are trained based on collected calibration spectra from Fourier transform near infrared (FT-NIR) measurements and kept fixed during the whole life-time of the on-line process, show a quite imprecise and unreliable behavior when predicting the concentrations of new on-line data. In this paper, we are demonstrating evolving chemometric models which are able to adapt automatically to varying process dynamics by updating their inner structures and parameters in a single-pass incremental manner. These models exploit the Takagi-Sugeno fuzzy model architecture, being able to model flexibly different degrees of non-linearities implicitly contained in the mapping between near infrared spectra (NIR) and reference values. Updating the inner structures is achieved by moving the position of already existing local regions and by evolving (increasing non-linearity) or merging (decreasing non-linearity) new local linear predictors on demand, which are guided by distance-based and similarity criteria. Gradual

  5. Evaluation of selected predictive models and parameters for the environmental transport and dosimetry of radionuclides

    International Nuclear Information System (INIS)

    Miller, C.W.; Dunning, D.E. Jr.; Etnier, E.L.; Hoffman, F.O.; Little, C.A.; Meyer, H.R.; Shaeffer, D.L.; Till, J.E.

    1979-07-01

    Evaluations of selected predictive models and parameters used in the assessment of the environmental transport and dosimetry of radionuclides are summarized. Mator sections of this report include a validation of the Gaussian plume disperson model, comparison of the output of a model for the transport of 131 I from vegetation to milk with field data, validation of a model for the fraction of aerosols intercepted by vegetation, an evaluation of dose conversion factors for 232 Th, an evaluation of considering the effect of age dependency on population dose estimates, and a summary of validation results for hydrologic transport models

  6. Predictive value of elevated soluble CD40 ligand in patients undergoing primary angioplasty for ST-segment elevation myocardial infarction.

    Science.gov (United States)

    Pusuroglu, Hamdi; Akgul, Ozgur; Erturk, Mehmet; Uyarel, Huseyin; Bulut, Umit; Akkaya, Emre; Buturak, Ali; Surgit, Ozgur; Fuat, Ali; Cetin, Mustafa; Yldrm, Aydn

    2014-11-01

    The aim of this study was to evaluate the prognostic value of soluble CD40 ligand (sCD40L) in patients with ST-segment elevation myocardial infarction (STEMI) undergoing a primary percutaneous coronary intervention (PCI). The prognostic value of sCD40L has been documented in patients with acute coronary syndrome; however, its value in acute STEMI remains unclear. We prospectively enrolled 499 consecutive STEMI patients (397 men, 102 women) undergoing primary PCI. The study population was divided into tertiles on the basis of admission sCD40L values. The high sCD40L group (n=168) included patients with a value in the third tertile (≥0.947 mg/l) and the low sCD40L group (n=331) included patients with a value in the lower two tertiles (0.947 mg/l) is a powerful independent predictor of 1-year all-cause mortality (odds ratio: 3.68; 95% confidence interval: 1.54-8.77; P=0.003). The results of this study suggest that a high sCD40L level at admission is associated with increased in-hospital and 1-year all-cause mortality rates in patients with STEMI undergoing primary PCI.

  7. The Chaotic Prediction for Aero-Engine Performance Parameters Based on Nonlinear PLS Regression

    Directory of Open Access Journals (Sweden)

    Chunxiao Zhang

    2012-01-01

    Full Text Available The prediction of the aero-engine performance parameters is very important for aero-engine condition monitoring and fault diagnosis. In this paper, the chaotic phase space of engine exhaust temperature (EGT time series which come from actual air-borne ACARS data is reconstructed through selecting some suitable nearby points. The partial least square (PLS based on the cubic spline function or the kernel function transformation is adopted to obtain chaotic predictive function of EGT series. The experiment results indicate that the proposed PLS chaotic prediction algorithm based on biweight kernel function transformation has significant advantage in overcoming multicollinearity of the independent variables and solve the stability of regression model. Our predictive NMSE is 16.5 percent less than that of the traditional linear least squares (OLS method and 10.38 percent less than that of the linear PLS approach. At the same time, the forecast error is less than that of nonlinear PLS algorithm through bootstrap test screening.

  8. Chairside CAD/CAM materials. Part 3: Cyclic fatigue parameters and lifetime predictions.

    Science.gov (United States)

    Wendler, Michael; Belli, Renan; Valladares, Diana; Petschelt, Anselm; Lohbauer, Ulrich

    2018-06-01

    Chemical and mechanical degradation play a key role on the lifetime of dental restorative materials. Therefore, prediction of their long-term performance in the oral environment should base on fatigue, rather than inert strength data, as commonly observed in the dental material's field. The objective of the present study was to provide mechanistic fatigue parameters of current dental CAD/CAM materials under cyclic biaxial flexure and assess their suitability in predicting clinical fracture behaviors. Eight CAD/CAM materials, including polycrystalline zirconia (IPS e.max ZirCAD), reinforced glasses (Vitablocs Mark II, IPS Empress CAD), glass-ceramics (IPS e.max CAD, Suprinity PC, Celtra Duo), as well as hybrid materials (Enamic, Lava Ultimate) were evaluated. Rectangular plates (12×12×1.2mm 3 ) with highly polished surfaces were prepared and tested in biaxial cyclic fatigue in water until fracture using the Ball-on-Three-Balls (B3B) test. Cyclic fatigue parameters n and A* were obtained from the lifetime data for each material and further used to build SPT diagrams. The latter were used to compare in-vitro with in-vivo fracture distributions for IPS e.max CAD and IPS Empress CAD. Susceptibility to subcritical crack growth under cyclic loading was observed for all materials, being more severe (n≤20) in lithium-based glass-ceramics and Vitablocs Mark II. Strength degradations of 40% up to 60% were predicted after only 1 year of service. Threshold stress intensity factors (K th ) representing the onset of subcritical crack growth (SCG), were estimated to lie in the range of 0.37-0.44 of K Ic for the lithium-based glass-ceramics and Vitablocs Mark II and between 0.51-0.59 of K Ic for the other materials. Failure distributions associated with mechanistic estimations of strength degradation in-vitro showed to be useful in interpreting failure behavior in-vivo. The parameter K th stood out as a better predictor of clinical performance in detriment to the SCG n

  9. Predicting hospital-acquired infections by scoring system with simple parameters.

    Directory of Open Access Journals (Sweden)

    Ying-Jui Chang

    Full Text Available BACKGROUND: Hospital-acquired infections (HAI are associated with increased attributable morbidity, mortality, prolonged hospitalization, and economic costs. A simple, reliable prediction model for HAI has great clinical relevance. The objective of this study is to develop a scoring system to predict HAI that was derived from Logistic Regression (LR and validated by Artificial Neural Networks (ANN simultaneously. METHODOLOGY/PRINCIPAL FINDINGS: A total of 476 patients from all the 806 HAI inpatients were included for the study between 2004 and 2005. A sample of 1,376 non-HAI inpatients was randomly drawn from all the admitted patients in the same period of time as the control group. External validation of 2,500 patients was abstracted from another academic teaching center. Sixteen variables were extracted from the Electronic Health Records (EHR and fed into ANN and LR models. With stepwise selection, the following seven variables were identified by LR models as statistically significant: Foley catheterization, central venous catheterization, arterial line, nasogastric tube, hemodialysis, stress ulcer prophylaxes and systemic glucocorticosteroids. Both ANN and LR models displayed excellent discrimination (area under the receiver operating characteristic curve [AUC]: 0.964 versus 0.969, p = 0.507 to identify infection in internal validation. During external validation, high AUC was obtained from both models (AUC: 0.850 versus 0.870, p = 0.447. The scoring system also performed extremely well in the internal (AUC: 0.965 and external (AUC: 0.871 validations. CONCLUSIONS: We developed a scoring system to predict HAI with simple parameters validated with ANN and LR models. Armed with this scoring system, infectious disease specialists can more efficiently identify patients at high risk for HAI during hospitalization. Further, using parameters either by observation of medical devices used or data obtained from EHR also provided good prediction

  10. Alternative Bio-Based Solvents for Extraction of Fat and Oils: Solubility Prediction, Global Yield, Extraction Kinetics, Chemical Composition and Cost of Manufacturing

    Directory of Open Access Journals (Sweden)

    Anne-Gaëlle Sicaire

    2015-04-01

    Full Text Available The present study was designed to evaluate the performance of alternative bio-based solvents, more especially 2-methyltetrahydrofuran, obtained from crop’s byproducts for the substitution of petroleum solvents such as hexane in the extraction of fat and oils for food (edible oil and non-food (bio fuel applications. First a solvent selection as well as an evaluation of the performance was made with Hansen Solubility Parameters and the COnductor-like Screening MOdel for Realistic Solvation (COSMO-RS simulations. Experiments were performed on rapeseed oil extraction at laboratory and pilot plant scale for the determination of lipid yields, extraction kinetics, diffusion modeling, and complete lipid composition in term of fatty acids and micronutrients (sterols, tocopherols and tocotrienols. Finally, economic and energetic evaluations of the process were conducted to estimate the cost of manufacturing using 2-methyltetrahydrofuran (MeTHF as alternative solvent compared to hexane as petroleum solvent.

  11. High serum soluble tumor necrosis factor receptor 1 predicts poor treatment response in acute-stage schizophrenia.

    Science.gov (United States)

    Nishimon, Shohei; Ohnuma, Tohru; Takebayashi, Yuto; Katsuta, Narimasa; Takeda, Mayu; Nakamura, Toru; Sannohe, Takahiro; Higashiyama, Ryoko; Kimoto, Ayako; Shibata, Nobuto; Gohda, Tomohito; Suzuki, Yusuke; Yamagishi, Sho-Ichi; Tomino, Yasuhiko; Arai, Heii

    2017-06-02

    Inflammation may be involved in the pathophysiology of schizophrenia. However, few cross-sectional or longitudinal studies have examined changes in biomarker expression to evaluate diagnostic and prognostic efficacy in acute-stage schizophrenia. We compared serum inflammatory biomarker concentrations in 87 patients with acute-stage schizophrenia on admission to 105 age-, sex-, and body mass index (BMI)-matched healthy controls. The measured biomarkers were soluble tumor necrosis factor receptor 1 (sTNFR1) and adiponectin, which are associated with inflammatory responses, and pigment epithelium-derived factor (PEDF), which has anti-inflammatory properties. We then investigated biomarker concentrations and associations with clinical factors in 213 patients (including 42 medication-free patients) and 110 unmatched healthy controls to model conditions typical of clinical practice. Clinical symptoms were assessed using the Brief Psychiatric Rating Scale and Global Assessment of Function. In 121 patients, biomarker levels and clinical status were evaluated at both admission and discharge. Serum sTNFR1 was significantly higher in patients with acute-stage schizophrenia compared to matched controls while no significant group differences were observed for the other markers. Serum sTNFR1 was also significantly higher in the 213 patients compared to unmatched controls. The 42 unmedicated patients had significantly lower PEDF levels compared to controls. Between admission and discharge, sTNFR1 levels decreased significantly; however, biomarker changes did not correlate with clinical symptoms. The discriminant accuracy of sTNFR1 was 93.2% between controls and patients, showing no symptom improvement during care. Inflammation and a low-level anti-inflammatory state may be involved in both schizophrenia pathogenesis and acute-stage onset. High serum sTNFR1 in the acute stage could be a useful prognostic biomarker for treatment response in clinical practice. Copyright © 2017

  12. Incorporating Pitzer equations in a new thermodynamic model for the prediction of acid gases solubility in aqueous alkanolamine solutions

    NARCIS (Netherlands)

    Alhseinat, E.; Mota Martinez, M.; Peters, C.J.; Banat, F.

    2014-01-01

    In gas sweetening, acid gases such as CO2 and/or H2S are usually removed by "chemical" absorption through aqueous amine solutions such as N-Methyldiethanolamine (MDEA) solution. Reliable prediction of equilibrium properties (vapor–liquid equilibrium and species distribution) is needed for a rigorous

  13. Prediction of Radionuclide transfer based on soil parameters: application to vulnerability studies

    International Nuclear Information System (INIS)

    Roig, M.; Vidal, M.; Rauret, G.

    1998-01-01

    The multi factorial character of the radiocaesium and radiostrontium soil-to-plan transfer, which depends on the radionuclide level in the soil solution amplified by a plant factor, prevents from establishing univariate relationships between transfer factors and soil and/or plant parameters. The plant factor is inversely proportional to the level of competitive species in the soil solution (Ca and Mg, for radiostrontium, and K and NH 4 for radiocaesium). Radionuclide level in soil solution depends on the radionuclide available fraction and its distribution coefficient. For radiostrontium, this may be obtained from the Cationic Exchange Capacity (CEC), whereas for radiocaesium the Specific Interception Potential should be calculate, both corrected by the concentrations of the competitive species and selectivity coefficients. Therefore, the transfer factor eventually depends on soil solution composition, the available fraction and the number of sorption sites, as well as on the plant factor. For a given plant, a relative sequence of transfer can be set up based solely on soil parameters, since the plant factor is cancelled. This prediction model has been compared with transfer data from experiments with Mediterranean, mineral soils, contaminated with a thermo generated aerosol, and with podzolic and organic soils, contaminated by the Chernobyl fallout. These studies revealed that it was possible to predict a relative scale of transfer for any type of soil, also allowing a scale of soil vulnerability to radiostrontium and radiocaesium contamination to be set up. (Author)

  14. Which nerve conduction parameters can predict spontaneous electromyographic activity in carpal tunnel syndrome?

    Science.gov (United States)

    Chang, Chia-Wei; Lee, Wei-Ju; Liao, Yi-Chu; Chang, Ming-Hong

    2013-11-01

    We investigate electrodiagnostic markers to determine which parameters are the best predictors of spontaneous electromyographic (EMG) activity in carpal tunnel syndrome (CTS). We enrolled 229 patients with clinically proven and nerve conduction study (NCS)-proven CTS, as well as 100 normal control subjects. All subjects were evaluated using electrodiagnostic techniques, including median distal sensory latencies (DSLs), sensory nerve action potentials (SNAPs), distal motor latencies (DMLs), compound muscle action potentials (CMAPs), forearm median nerve conduction velocities (FMCVs) and wrist-palm motor conduction velocities (W-P MCVs). All CTS patients underwent EMG examination of the abductor pollicis brevis (APB) muscle, and the presence or absence of spontaneous EMG activities was recorded. Normal limits were determined by calculating the means ± 2 standard deviations from the control data. Associations between parameters from the NCS and EMG findings were investigated. In patients with clinically diagnosed CTS, abnormal median CMAP amplitudes were the best predictors of spontaneous activity during EMG examination (p95% (positive predictive rate >95%). If the median CMAP amplitude was higher than the normal limit (>4.9 mV), the rate of no spontaneous EMG activity was >94% (negative predictive rate >94%). An abnormal SNAP amplitude was the second best predictor of spontaneous EMG activity (p<0.001; OR 4.13; 95% CI 2.16-7.90), and an abnormal FMCV was the third best predictor (p=0.01; OR 2.10; 95% CI 1.20-3.67). No other nerve conduction parameters had significant power to predict spontaneous activity upon EMG examination. The CMAP amplitudes of the APB are the most powerful predictors of the occurrence of spontaneous EMG activity. Low CMAP amplitudes are strongly associated with spontaneous activity, whereas high CMAP amplitude are less associated with spontaneous activity, implying that needle EMG examination should be recommended for the detection of

  15. [Application of the concetrations ratio of soluble receptor tyrosine kinase type 1, and placental growth factor for short-term prediction and diagnosis of preeclampsia].

    Science.gov (United States)

    Bubeníková, Š; Cíchová, A; Roubalová, L; Durdová, V; Vlk, R

    Bring a comprehensive overview of the available information about applications of the concetration ratio of soluble receptor tyrosine kinase type 1 (sFlt-1), and placental growth factor for short-term prediction and diagnosis of preeclampsia. Overview study. Department of Midwifery, Faculty of Health Sciences, Olomouc; Department of Clinical Biochemistry, University Hospital Olomouc; Department of Obstetrics and Gynecology, University Hospital Olomouc; Department of Obstetrics and Gynecology, 2nd Faculty of Medicine, Charles University in Prague and Motol University Hospital. Analysis of literary sources and databases Ovid, Medline (2001-2016). Preeclampsia is a multisystem disease with not fully understood etiology. This disease occurs in 2-5% of pregnant women. Preeclampsia is one of the main causes of global maternal and perinatal morbidity and mortality. It manifests itself as a newborn hypertension and proteinuria after 20 weeks of pregnancy in previously normotensive women. The only effective treatment is the delivery of the child. Diagnosis of preeclampsia comprises measuring blood pressure and proteinuria. These indicators have low diagnostic sensitivity and specificity. In preeclampsia, there is a decrease of serum levels of placental growth factor (PlGF). Soluble receptor tyrosine kinase type 1 (sFlt-1) is an antagonist of PlGF. Increased levels of sFlt-1 in proportion to the reduced level of PlGF are associated with an increased risk of preeclampsia. The sFlt-1/PlGF ratio can be a better predictive marker in the diagnosis of pre-eclampsia after 20 weeks of gestation.

  16. Parameter optimization of parenchymal texture analysis for prediction of false-positive recalls from screening mammography

    Science.gov (United States)

    Ray, Shonket; Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina

    2016-03-01

    This work details a methodology to obtain optimal parameter values for a locally-adaptive texture analysis algorithm that extracts mammographic texture features representative of breast parenchymal complexity for predicting falsepositive (FP) recalls from breast cancer screening with digital mammography. The algorithm has two components: (1) adaptive selection of localized regions of interest (ROIs) and (2) Haralick texture feature extraction via Gray- Level Co-Occurrence Matrices (GLCM). The following parameters were systematically varied: mammographic views used, upper limit of the ROI window size used for adaptive ROI selection, GLCM distance offsets, and gray levels (binning) used for feature extraction. Each iteration per parameter set had logistic regression with stepwise feature selection performed on a clinical screening cohort of 474 non-recalled women and 68 FP recalled women; FP recall prediction was evaluated using area under the curve (AUC) of the receiver operating characteristic (ROC) and associations between the extracted features and FP recall were assessed via odds ratios (OR). A default instance of mediolateral (MLO) view, upper ROI size limit of 143.36 mm (2048 pixels2), GLCM distance offset combination range of 0.07 to 0.84 mm (1 to 12 pixels) and 16 GLCM gray levels was set. The highest ROC performance value of AUC=0.77 [95% confidence intervals: 0.71-0.83] was obtained at three specific instances: the default instance, upper ROI window equal to 17.92 mm (256 pixels2), and gray levels set to 128. The texture feature of sum average was chosen as a statistically significant (p<0.05) predictor and associated with higher odds of FP recall for 12 out of 14 total instances.

  17. Prediction and optimization of friction welding parameters for super duplex stainless steel (UNS S32760) joints

    International Nuclear Information System (INIS)

    Udayakumar, T.; Raja, K.; Afsal Husain, T.M.; Sathiya, P.

    2014-01-01

    Highlights: • Corrosion resistance and impact strength – predicted by response surface methodology. • Burn off length has highest significance on corrosion resistance. • Friction force is a strong determinant in changing impact strength. • Pareto front points generated by genetic algorithm aid to fix input control variable. • Pareto front will be a trade-off between corrosion resistance and impact strength. - Abstract: Friction welding finds widespread industrial use as a mass production process for joining materials. Friction welding process allows welding of several materials that are extremely difficult to fusion weld. Friction welding process parameters play a significant role in making good quality joints. To produce a good quality joint it is important to set up proper welding process parameters. This can be done by employing optimization techniques. This paper presents a multi objective optimization method for optimizing the process parameters during friction welding process. The proposed method combines the response surface methodology (RSM) with an intelligent optimization algorithm, i.e. genetic algorithm (GA). Corrosion resistance and impact strength of friction welded super duplex stainless steel (SDSS) (UNS S32760) joints were investigated considering three process parameters: friction force (F), upset force (U) and burn off length (B). Mathematical models were developed and the responses were adequately predicted. Direct and interaction effects of process parameters on responses were studied by plotting graphs. Burn off length has high significance on corrosion current followed by upset force and friction force. In the case of impact strength, friction force has high significance followed by upset force and burn off length. Multi objective optimization for maximizing the impact strength and minimizing the corrosion current (maximizing corrosion resistance) was carried out using GA with the RSM model. The optimization procedure resulted in

  18. Predictive Models for Different Roughness Parameters During Machining Process of Peek Composites Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    Mata-Cabrera Francisco

    2013-10-01

    Full Text Available Polyetheretherketone (PEEK composite belongs to a group of high performance thermoplastic polymers and is widely used in structural components. To improve the mechanical and tribological properties, short fibers are added as reinforcement to the material. Due to its functional properties and potential applications, it’s impor- tant to investigate the machinability of non-reinforced PEEK (PEEK, PEEK rein- forced with 30% of carbon fibers (PEEK CF30, and reinforced PEEK with 30% glass fibers (PEEK GF30 to determine the optimal conditions for the manufacture of the parts. The present study establishes the relationship between the cutting con- ditions (cutting speed and feed rate and the roughness (Ra , Rt , Rq , Rp , by develop- ing second order mathematical models. The experiments were planned as per full factorial design of experiments and an analysis of variance has been performed to check the adequacy of the models. These state the adequacy of the derived models to obtain predictions for roughness parameters within ranges of parameters that have been investigated during the experiments. The experimental results show that the most influence of the cutting parameters is the feed rate, furthermore, proved that glass fiber reinforcements produce a worse machinability.

  19. Genetic Algorithms for Estimating Effective Parameters in a Lumped Reactor Model for Reactivity Predictions

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico

    2001-01-01

    The control system of a reactor should be able to predict, in real time, the amount of reactivity to be inserted (e.g., by control rod movements and boron injection and dilution) to respond to a given electrical load demand or to undesired, accidental transients. The real-time constraint renders impractical the use of a large, detailed dynamic reactor code. One has, then, to resort to simplified analytical models with lumped effective parameters suitably estimated from the reactor data.The simple and well-known Chernick model for describing the reactor power evolution in the presence of xenon is considered and the feasibility of using genetic algorithms for estimating the effective nuclear parameters involved and the initial nonmeasurable xenon and iodine conditions is investigated. This approach has the advantage of counterbalancing the inherent model simplicity with the periodic reestimation of the effective parameter values pertaining to each reactor on the basis of its recent history. By so doing, other effects, such as burnup, are automatically taken into account

  20. An Adaptive Medium Access Parameter Prediction Scheme for IEEE 802.11 Real-Time Applications

    Directory of Open Access Journals (Sweden)

    Estefanía Coronado

    2017-01-01

    Full Text Available Multimedia communications have experienced an unprecedented growth due mainly to the increase in the content quality and the emergence of smart devices. The demand for these contents is tending towards wireless technologies. However, these transmissions are quite sensitive to network delays. Therefore, ensuring an optimum QoS level becomes of great importance. The IEEE 802.11e amendment was released to address the lack of QoS capabilities in the original IEEE 802.11 standard. Accordingly, the Enhanced Distributed Channel Access (EDCA function was introduced, allowing it to differentiate traffic streams through a group of Medium Access Control (MAC parameters. Although EDCA recommends a default configuration for these parameters, it has been proved that it is not optimum in many scenarios. In this work a dynamic prediction scheme for these parameters is presented. This approach ensures an appropriate traffic differentiation while maintaining compatibility with the stations without QoS support. As the APs are the only devices that use this algorithm, no changes are required to current network cards. The results show improvements in both voice and video transmissions, as well as in the QoS level of the network that the proposal achieves with regard to EDCA.

  1. Preoperative Biometric Parameters Predict the Vault after ICL Implantation: A Retrospective Clinical Study.

    Science.gov (United States)

    Zheng, Qian-Yin; Xu, Wen; Liang, Guan-Lu; Wu, Jing; Shi, Jun-Ting

    2016-01-01

    To investigate the correlation between the preoperative biometric parameters of the anterior segment and the vault after implantable Collamer lens (ICL) implantation via this retrospective study. Retrospective clinical study. A total of 78 eyes from 41 patients who underwent ICL implantation surgery were included in this study. Preoperative biometric parameters, including white-to-white (WTW) diameter, central corneal thickness, keratometer, pupil diameter, anterior chamber depth, sulcus-to-sulcus diameter, anterior chamber area (ACA) and central curvature radius of the anterior surface of the lens (Lenscur), were measured. Lenscur and ACA were measured with Rhinoceros 5.0 software on the image scanned with ultrasound biomicroscopy (UBM). The vault was assessed by UBM 3 months after surgery. Multiple stepwise regression analysis was employed to identify the variables that were correlated with the vault. The results showed that the vault was correlated with 3 variables: ACA (22.4 ± 4.25 mm2), WTW (11.36 ± 0.29 mm) and Lenscur (9.15 ± 1.21 mm). The regressive equation was: vault (mm) = 1.785 + 0.017 × ACA + 0.051 × Lenscur - 0.203 × WTW. Biometric parameters of the anterior segment (ACA, WTW and Lenscur) can predict the vault after ICL implantation using a new regression equation. © 2016 The Author(s) Published by S. Karger AG, Basel.

  2. Evaluation of the performance and limitations of empirical partition-relations and process based multisurface models to predict trace element solubility in soils

    Energy Technology Data Exchange (ETDEWEB)

    Groenenberg, J.E.; Bonten, L.T.C. [Alterra, Wageningen UR, P.O. Box 47, 6700 AA Wageningen (Netherlands); Dijkstra, J.J. [Energy research Centre of the Netherlands ECN, P.O. Box 1, 1755 ZG Petten (Netherlands); De Vries, W. [Department of Environmental Systems Analysis, Wageningen University, Wageningen UR, P.O. Box 47, 6700 AA Wageningen (Netherlands); Comans, R.N.J. [Department of Soil Quality, Wageningen University, Wageningen UR, P.O. Box 47, 6700 AA Wageningen (Netherlands)

    2012-07-15

    Here we evaluate the performance and limitations of two frequently used model-types to predict trace element solubility in soils: regression based 'partition-relations' and thermodynamically based 'multisurface models', for a large set of elements. For this purpose partition-relations were derived for As, Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, Sb, Se, V, Zn. The multi-surface model included aqueous speciation, mineral equilibria, sorption to organic matter, Fe/Al-(hydr)oxides and clay. Both approaches were evaluated by their application to independent data for a wide variety of conditions. We conclude that Freundlich-based partition-relations are robust predictors for most cations and can be used for independent soils, but within the environmental conditions of the data used for their derivation. The multisurface model is shown to be able to successfully predict solution concentrations over a wide range of conditions. Predicted trends for oxy-anions agree well for both approaches but with larger (random) deviations than for cations.

  3. The Effect of Process and Model Parameters in Temperature Prediction for Hot Stamping of Boron Steel

    Directory of Open Access Journals (Sweden)

    Chaoyang Sun

    2013-01-01

    Full Text Available Finite element models of the hot stamping and cold die quenching process for boron steel sheet were developed using either rigid or elastic tools. The effect of tool elasticity and process parameters on workpiece temperature was investigated. Heat transfer coefficient between blank and tools was modelled as a function of gap and contact pressure. Temperature distribution and thermal history in the blank were predicted, and thickness distribution of the blank was obtained. Tests were carried out and the test results are used for the validation of numerical predictions. The effect of holding load and the size of cooling ducts on temperature distribution during the forming and the cool die quenching process was also studied by using two models. The results show that higher accuracy predictions of blank thickness and temperature distribution during deformation were obtained using the elastic tool model. However, temperature results obtained using the rigid tool model were close to those using the elastic tool model for a range of holding load.

  4. Prediction uncertainty assessment of a systems biology model requires a sample of the full probability distribution of its parameters

    Directory of Open Access Journals (Sweden)

    Simon van Mourik

    2014-06-01

    Full Text Available Multi-parameter models in systems biology are typically ‘sloppy’: some parameters or combinations of parameters may be hard to estimate from data, whereas others are not. One might expect that parameter uncertainty automatically leads to uncertain predictions, but this is not the case. We illustrate this by showing that the prediction uncertainty of each of six sloppy models varies enormously among different predictions. Statistical approximations of parameter uncertainty may lead to dramatic errors in prediction uncertainty estimation. We argue that prediction uncertainty assessment must therefore be performed on a per-prediction basis using a full computational uncertainty analysis. In practice this is feasible by providing a model with a sample or ensemble representing the distribution of its parameters. Within a Bayesian framework, such a sample may be generated by a Markov Chain Monte Carlo (MCMC algorithm that infers the parameter distribution based on experimental data. Matlab code for generating the sample (with the Differential Evolution Markov Chain sampler and the subsequent uncertainty analysis using such a sample, is supplied as Supplemental Information.

  5. Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

    Science.gov (United States)

    Doherty, John E.; Hunt, Randall J.; Tonkin, Matthew J.

    2010-01-01

    Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncertainty analysis with regard to models can be very computationally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system properties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints). Enforcement of knowledge and calibration constraints on parameters used by a model does not eliminate the uncertainty in those parameters. In fact, in many cases, enforcement of calibration constraints simply reduces the uncertainties associated with a number of broad-scale combinations of model parameters that collectively describe spatially averaged system properties. The uncertainties associated with other combinations of parameters, especially those that pertain to small-scale parameter heterogeneity, may not be reduced through the calibration process. To the extent that a prediction depends on system-property detail, its postcalibration variability may be reduced very little, if at all, by applying calibration constraints; knowledge constraints remain the only limits on the variability of predictions that depend on such detail. Regrettably, in many common modeling applications, these constraints are weak. Though the PEST software suite was initially developed as a tool for model calibration, recent developments have focused on the evaluation of model-parameter and predictive uncertainty. As a complement to functionality that it provides for highly parameterized inversion (calibration) by means of formal mathematical regularization techniques, the PEST suite provides utilities for linear and nonlinear error-variance and uncertainty analysis in

  6. Toe Pressures are Superior to Duplex Parameters in Predicting Wound Healing following Toe and Foot Amputations.

    Science.gov (United States)

    Stone, Patrick A; Glomski, Alexis; Thompson, Stephanie N; Adams, Elliott

    2018-01-01

    No criteria, including preamputation vascular diagnostic thresholds, have been established to reliably predict healing versus nonhealing following minor lower extremity amputations. Thus, the goal of our study was to identify clinical factors, including noninvasive vascular laboratory measures, associated with wound healing following toe, forefoot, and midfoot amputations. We retrospectively examined records of patients receiving elective toe, forefoot, or midfoot amputation at our institution over a 5-year span (2010-2015). A total of 333 amputations received noninvasive vascular assessment of the lower extremity preamputation and follow-up at 90 days postamputation. Multivariate binomial logistic regression was used to identify variables predicting wound healing as defined as the absence of reamputation due to wound breakdown. Wound healing occurred in 81% of amputations. A total of 23 (7%) patients required revisions of the foot while 39 (12%) patients required major amputations by 90 days. Chi-squared analysis found that toe pressure at or above the value of 47 mm Hg (P = 0.04), bi/triphasic anterior tibial (P = 0.01), and posterior tibial artery (P = 0.01) waveforms were associated with wound healing. When these diagnostic parameters were examined in the presence of confounders (increasing age, chronic kidney disease, and concomitant revascularization), only toe pressure ≥ 47 mm Hg predicted amputation site healing (odds ratio: 3.1 [95% CI: 1.0-9.4], P = 0.04). Preamputation toe pressures of 47 mm Hg and above are associated with wound healing. No other noninvasive vascular studies predicted wound healing in the presence of confounders. Thus, toe pressures may assist in clinical decision-making and should be routinely obtained preamputation. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Soil erosion model predictions using parent material/soil texture-based parameters compared to using site-specific parameters

    Science.gov (United States)

    R. B. Foltz; W. J. Elliot; N. S. Wagenbrenner

    2011-01-01

    Forested areas disturbed by access roads produce large amounts of sediment. One method to predict erosion and, hence, manage forest roads is the use of physically based soil erosion models. A perceived advantage of a physically based model is that it can be parameterized at one location and applied at another location with similar soil texture or geological parent...

  8. On-Line Flutter Prediction Tool for Wind Tunnel Flutter Testing using Parameter Varying Estimation Methodology, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool for wind tunnel model using the parameter varying estimation (PVE) technique to...

  9. Prediction efficiency of the hydrographical parameters as related to distribution patterns of the Pleuromamma species in the Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Jayalakshmy, K.V.; Saraswathy, M.

    . Multiple regression model of P. indica abundance on the parameters: temperature, salinity, dissolved oxygen and phosphate-phosphorus could explain more than 85% of the variation in the predicted abundance, while those of 8 species obtained from...

  10. Prediction of moisture transfer parameters for convective drying of shrimp at different pretreatments

    Directory of Open Access Journals (Sweden)

    Marcus Vinicius da COSTA

    2018-04-01

    Full Text Available Abstract By the analytical model proposed by Dincer and Dost, the mass transfer parameters (moisture transfer coefficient and moisture diffusivity of shrimp samples were determined. Three sets of drying experiments were performed with three samples of shrimp: without boiling (WB, boiled in salt solution (SB and boiled in salt solution and subjected to liquid smoking process (SBS. The experiments were performed under controlled conditions of drying air at temperature of 60°C and velocity of 1.5 m/s. Experimental dimensionless moisture content data were used to calculate the drying coefficients and lag factors, which were then incorporated into the analytical model for slab and cylinder shapes. The results showed an adequate fit between the experimental data and the values predicted from the correlation. The boiling is the most recommended pretreatment, because provided a shorter drying time, with high values of moisture transfer coefficient and moisture diffusivity.

  11. Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO

    Directory of Open Access Journals (Sweden)

    Adel Taieb

    2017-01-01

    Full Text Available This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO Fuzzy Optimal Model Predictive Control (FOMPC using the Adaptive Particle Swarm Optimization (APSO algorithm. The aim of this proposed control, called FOMPC-APSO, is to develop an efficient algorithm that is able to have good performance by guaranteeing a minimal control. This is done by determining the optimal weights of the objective function. Our method is considered an optimization problem based on the APSO algorithm. The MIMO system to be controlled is modeled by a Takagi-Sugeno (TS fuzzy system whose parameters are identified using weighted recursive least squares method. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, Continuous Stirred Tank Reactor (CSTR and Tank system, where the proposed approach provides better performances compared with other methods.

  12. Predicting future conflict between team-members with parameter-free models of social networks

    Science.gov (United States)

    Rovira-Asenjo, Núria; Gumí, Tània; Sales-Pardo, Marta; Guimerà, Roger

    2013-06-01

    Despite the well-documented benefits of working in teams, teamwork also results in communication, coordination and management costs, and may lead to personal conflict between team members. In a context where teams play an increasingly important role, it is of major importance to understand conflict and to develop diagnostic tools to avert it. Here, we investigate empirically whether it is possible to quantitatively predict future conflict in small teams using parameter-free models of social network structure. We analyze data of conflict appearance and resolution between 86 team members in 16 small teams, all working in a real project for nine consecutive months. We find that group-based models of complex networks successfully anticipate conflict in small teams whereas micro-based models of structural balance, which have been traditionally used to model conflict, do not.

  13. Dose-volumetric parameters for predicting hypothyroidism after radiotherapy for head and neck cancer

    International Nuclear Information System (INIS)

    Kim, Mi Young; Yu, Tosol; Wu, Hong-Gyun

    2014-01-01

    To investigate predictors affecting the development of hypothyroidism after radiotherapy for head and neck cancer, focusing on radiation dose-volumetric parameters, and to determine the appropriate radiation dose-volumetric threshold of radiation-induced hypothyroidism. A total of 114 patients with head and neck cancer whose radiotherapy fields included the thyroid gland were analysed. The purpose of the radiotherapy was either definitive (n=81) or post-operative (n=33). Thyroid function was monitored before starting radiotherapy and after completion of radiotherapy at 1 month, 6 months, 1 year and 2 years. A diagnosis of hypothyroidism was based on a thyroid stimulating hormone value greater than the maximum value of laboratory range, regardless of symptoms. In all patients, dose volumetric parameters were analysed. Median follow-up duration was 25 months (range; 6-38). Forty-six percent of the patients were diagnosed as hypothyroidism after a median time of 8 months (range; 1-24). There were no significant differences in the distribution of age, gender, surgery, radiotherapy technique and chemotherapy between the euthyroid group and the hypothyroid group. In univariate analysis, the mean dose and V35-V50 results were significantly associated with hypothyroidism. The V45 is the only variable that independently contributes to the prediction of hypothyroidism in multivariate analysis and V45 of 50% was a threshold value. If V45 was <50%, the cumulative incidence of hypothyroidism at 1 year was 22.8%, whereas the incidence was 56.1% if V45 was ≥50%. (P=0.034). The V45 may predict risk of developing hypothyroidism after radiotherapy for head and neck cancer, and a V45 of 50% can be a useful dose-volumetric threshold of radiation-induced hypothyroidism. (author)

  14. Meckel's Diverticulum in Children-Parameters Predicting the Presence of Gastric Heterotopia.

    Science.gov (United States)

    Slívová, Ivana; Vávrová, Zuzana; Tomášková, Hana; Okantey, Okaikor; Penka, Igor; Ihnát, Peter

    2018-05-10

    The presence of gastric ectopic mucosa in Meckel's diverticulum is associated with a higher risk of development of complications. The aim of the present study was to investigate which demographic/clinical parameters predict the presence of gastric heterotopia in Meckel's diverticulum. This was a retrospective cohort study conducted in a single institution (University Hospital Ostrava, Czech republic). All children who underwent laparoscopic/open resection of Meckel's diverticulum within a 20-year study period were included in the study. In total, 88 pediatric patients underwent analysis. The mean age of the children was 4.6 ± 4.73 years; the male-female ratio was approximately 2:1. There were 50 (56.8%) patients with asymptomatic Meckel's diverticulum in our study group. Laparoscopic resection was performed in 24 (27.3%) patients; segmental bowel resection through laparotomy was performed in 13 (14.8%) patients. Gastric heterotopia was found in 39 (44.3%) patients; resection margins of all patients were clear of gastric heterotopia. No correlation was found between the presence of gastric heterotopia and the following parameters: age, gender, maternal age, prematurity, low birth weight, perinatal asphyxia, distance from Bauhin's valve and length of Meckel's diverticulum. The width of the diverticulum base was significantly higher in patients with gastric heterotopia (2.1 ± 0.57 vs. 1.2 ± 0.41 cm; p < 0.001). According to the study outcomes, the width of the diverticulum base seems to be a significant predictive factor associated with the presence of gastric heterotopia in Meckel's diverticulum. The laparoscopic/open resection of asymptomatic MD with a wide base should therefore be recommended.

  15. Predicting the solubility and lability of Zn, Cd, and Pb in soils from a minespoil-contaminated catchment by stable isotopic exchange

    Science.gov (United States)

    Marzouk, E. R.; Chenery, S. R.; Young, S. D.

    2013-12-01

    The Rookhope catchment of Weardale, England, has a diverse legacy of contaminated soils due to extensive lead mining activity over four centuries. We measured the isotopically exchangeable content of Pb, Cd and Zn (E-values) in a large representative subset of the catchment soils (n = 246) using stable isotope dilution. All three metals displayed a wide range of %E-values (c. 1-100%) but relative lability followed the sequence Cd > Pb > Zn. A refinement of the stable isotope dilution approach also enabled detection of non-reactive metal contained within suspended sub-micron (dilution, in a diverse range of soil ecosystems within the catchment of an old Pb/Zn mining area. Assess the controlling influences of soil properties on metal lability and develop predictive algorithms for metal lability in the contaminated catchment based on simple soil properties (such as pH, organic matter (LOI), and total metal content). Examine the incidence of non-isotopically-exchangeable metal held within suspended colloidal particles (SCP-metal) in filtered soil solutions (<0.22 μm) by comparing E-values from isotopic abundance in solutions equilibrated with soil and in a resin phase equilibrated with the separated solution. Assess the ability of a geochemical speciation model, WHAM(VII), to predict metal solubility using isotopically exchangeable metal as an input variable.

  16. Logic-based models in systems biology: a predictive and parameter-free network analysis method.

    Science.gov (United States)

    Wynn, Michelle L; Consul, Nikita; Merajver, Sofia D; Schnell, Santiago

    2012-11-01

    Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network's dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples.

  17. Hemorheological and Glycemic Parameters and HDL Cholesterol for the Prediction of Cardiovascular Events

    International Nuclear Information System (INIS)

    Cho, Sung Woo; Kim, Byung Gyu; Kim, Byung Ok; Byun, Young Sup; Goh, Choong Won; Rhee, Kun Joo; Kwon, Hyuck Moon; Lee, Byoung Kwon

    2016-01-01

    Hemorheological and glycemic parameters and high density lipoprotein (HDL) cholesterol are used as biomarkers of atherosclerosis and thrombosis. To investigate the association and clinical relevance of erythrocyte sedimentation rate (ESR), fibrinogen, fasting glucose, glycated hemoglobin (HbA1c), and HDL cholesterol in the prediction of major adverse cardiovascular events (MACE) and coronary heart disease (CHD) in an outpatient population. 708 stable patients who visited the outpatient department were enrolled and followed for a mean period of 28.5 months. Patients were divided into two groups, patients without MACE and patients with MACE, which included cardiac death, acute myocardial infarction, newly diagnosed CHD, and cerebral vascular accident. We compared hemorheological and glycemic parameters and lipid profiles between the groups. Patients with MACE had significantly higher ESR, fibrinogen, fasting glucose, and HbA1c, while lower HDL cholesterol compared with patients without MACE. High ESR and fibrinogen and low HDL cholesterol significantly increased the risk of MACE in multivariate regression analysis. In patients with MACE, high fibrinogen and HbA1c levels increased the risk of multivessel CHD. Furthermore, ESR and fibrinogen were significantly positively correlated with HbA1c and negatively correlated with HDL cholesterol, however not correlated with fasting glucose. Hemorheological abnormalities, poor glycemic control, and low HDL cholesterol are correlated with each other and could serve as simple and useful surrogate markers and predictors for MACE and CHD in outpatients

  18. Hemorheological and Glycemic Parameters and HDL Cholesterol for the Prediction of Cardiovascular Events

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Sung Woo [Division of Cardiology - Department of Internal Medicine - Sanggye Paik Hospital, Inje University College of Medicine, Seoul (Korea, Republic of); Division of Cardiology - Department of Medicine - Samsung Medical Center, Seoul (Korea, Republic of); Kim, Byung Gyu; Kim, Byung Ok; Byun, Young Sup; Goh, Choong Won; Rhee, Kun Joo [Division of Cardiology - Department of Internal Medicine - Sanggye Paik Hospital, Inje University College of Medicine, Seoul (Korea, Republic of); Kwon, Hyuck Moon; Lee, Byoung Kwon, E-mail: cardiobk@yuhs.ac [Division of Cardiology - Department of Internal Medicine - Gangnam Severance Hospital - Yonsei University College of Medicine, Seoul (Korea, Republic of)

    2016-01-15

    Hemorheological and glycemic parameters and high density lipoprotein (HDL) cholesterol are used as biomarkers of atherosclerosis and thrombosis. To investigate the association and clinical relevance of erythrocyte sedimentation rate (ESR), fibrinogen, fasting glucose, glycated hemoglobin (HbA1c), and HDL cholesterol in the prediction of major adverse cardiovascular events (MACE) and coronary heart disease (CHD) in an outpatient population. 708 stable patients who visited the outpatient department were enrolled and followed for a mean period of 28.5 months. Patients were divided into two groups, patients without MACE and patients with MACE, which included cardiac death, acute myocardial infarction, newly diagnosed CHD, and cerebral vascular accident. We compared hemorheological and glycemic parameters and lipid profiles between the groups. Patients with MACE had significantly higher ESR, fibrinogen, fasting glucose, and HbA1c, while lower HDL cholesterol compared with patients without MACE. High ESR and fibrinogen and low HDL cholesterol significantly increased the risk of MACE in multivariate regression analysis. In patients with MACE, high fibrinogen and HbA1c levels increased the risk of multivessel CHD. Furthermore, ESR and fibrinogen were significantly positively correlated with HbA1c and negatively correlated with HDL cholesterol, however not correlated with fasting glucose. Hemorheological abnormalities, poor glycemic control, and low HDL cholesterol are correlated with each other and could serve as simple and useful surrogate markers and predictors for MACE and CHD in outpatients.

  19. Logic-based models in systems biology: a predictive and parameter-free network analysis method†

    Science.gov (United States)

    Wynn, Michelle L.; Consul, Nikita; Merajver, Sofia D.

    2012-01-01

    Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network’s dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples. PMID:23072820

  20. Prediction models for solitary pulmonary nodules based on curvelet textural features and clinical parameters.

    Science.gov (United States)

    Wang, Jing-Jing; Wu, Hai-Feng; Sun, Tao; Li, Xia; Wang, Wei; Tao, Li-Xin; Huo, Da; Lv, Ping-Xin; He, Wen; Guo, Xiu-Hua

    2013-01-01

    Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.

  1. Antioxidant defense parameters as predictive biomarkers for fermentative capacity of active dried wine yeast.

    Science.gov (United States)

    Gamero-Sandemetrio, Esther; Gómez-Pastor, Rocío; Matallana, Emilia

    2014-08-01

    The production of active dried yeast (ADY) is a common practice in industry for the maintenance of yeast starters and as a means of long term storage. The process, however, causes multiple cell injuries, with oxidative damage being one of the most important stresses. Consequentially, dehydration tolerance is a highly appreciated property in yeast for ADY production. In this study we analyzed the cellular redox environment in three Saccharomyces cerevisiae wine strains, which show markedly different fermentative capacities after dehydration. To measure/quantify the effect of dehydration on the S. cerevisiae strains, we used: (i) fluorescent probes; (ii) antioxidant enzyme activities; (ii) intracellular damage; (iii) antioxidant metabolites; and (iv) gene expression, to select a minimal set of biochemical parameters capable of predicting desiccation tolerance in wine yeasts. Our results show that naturally enhanced antioxidant defenses prevent oxidative damage after wine yeast biomass dehydration and improve fermentative capacity. Based on these results we chose four easily assayable parameters/biomarkers for the selection of industrial yeast strains of interest for ADY production: trehalose and glutathione levels, and glutathione reductase and catalase enzymatic activities. Yeast strains selected in accordance with this process display high levels of trehalose, low levels of oxidized glutathione, a high induction of glutathione reductase activity, as well as a high basal level and sufficient induction of catalase activity, which are properties inherent in superior ADY strains. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Prediction of scaling physics laws for proton acceleration with extended parameter space of the NIF ARC

    Science.gov (United States)

    Bhutwala, Krish; Beg, Farhat; Mariscal, Derek; Wilks, Scott; Ma, Tammy

    2017-10-01

    The Advanced Radiographic Capability (ARC) laser at the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory is the world's most energetic short-pulse laser. It comprises four beamlets, each of substantial energy ( 1.5 kJ), extended short-pulse duration (10-30 ps), and large focal spot (>=50% of energy in 150 µm spot). This allows ARC to achieve proton and light ion acceleration via the Target Normal Sheath Acceleration (TNSA) mechanism, but it is yet unknown how proton beam characteristics scale with ARC-regime laser parameters. As theory has also not yet been validated for laser-generated protons at ARC-regime laser parameters, we attempt to formulate the scaling physics of proton beam characteristics as a function of laser energy, intensity, focal spot size, pulse length, target geometry, etc. through a review of relevant proton acceleration experiments from laser facilities across the world. These predicted scaling laws should then guide target design and future diagnostics for desired proton beam experiments on the NIF ARC. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and funded by the LLNL LDRD program under tracking code 17-ERD-039.

  3. Multidetector-CT angiography in pulmonary embolism - can image parameters predict clinical outcome?

    Energy Technology Data Exchange (ETDEWEB)

    Heyer, Christoph M.; Lemburg, Stefan P.; Nicolas, Volkmar; Roggenland, Daniela [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Ruhr-University of Bochum, Institute of Diagnostic Radiology, Interventional Radiology and Nuclear Medicine, Bochum (Germany); Knoop, Heiko [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Medical Clinic III - Pneumology, Allergology, and Sleep Medicine, Bochum (Germany); Holland-Letz, Tim [Ruhr-University of Bochum, Department of Medical Informatics, Biometry and Epidemiology, Bochum (Germany)

    2011-09-15

    To assess if pulmonary CT angiography (CTA) can predict outcome in patients with pulmonary embolism (PE). Retrospective analysis of CTA studies of patients with PE and documentation of pulmonary artery (PA)/aorta ratio, right ventricular (RV)/left ventricular (LV) ratio, superior vena cava (SVC) diameter, pulmonary obstruction index (POI), ventricular septal bowing (VSB), venous contrast reflux (VCR), pulmonary infarction and pleural effusion. Furthermore, duration of total hospital stay, necessity for/duration of ICU therapy, necessity for mechanical ventilation and mortality were recorded. Comparison was performed by logistic/linear regression analysis with significance at 5%. 152 patients were investigated. Mean duration of hospital stay was 21 {+-} 24 days. 66 patients were admitted to the ICU; 20 received mechanical ventilation. Mean duration of ICU therapy was 3 {+-} 8 days. Mortality rate was 8%. Significant positive associations of POI, VCR and pulmonary infarction with necessity for ICU therapy were shown. VCR was significantly associated with necessity for mechanical ventilation and duration of ICU treatment. Pleural effusions were significantly associated with duration of total hospital stay whereas the RV/LV ratio correlated with mortality. Selected CTA findings showed significant associations with the clinical course of PE and may thus be used as predictive parameters. (orig.)

  4. Prediction of ecotoxicity of hydrocarbon-contaminated soils using physicochemical parameters

    Energy Technology Data Exchange (ETDEWEB)

    Wong, D.C.L.; Chai, E.Y.; Chu, K.K.; Dorn, P.B.

    1999-11-01

    The physicochemical properties of eight hydrocarbon-contaminated soils were used to predict toxicity to earthworms (Eisenia fetida) and plants. The toxicity of these preremediated soils was assessed using earthworm avoidance, survival, and reproduction and seed germination and root growth in four plant species. No-observed-effect and 25% inhibitory concentrations were determined from the earthworm and plant assays. Physical property measurements and metals analyses of the soils were conducted. Hydrocarbon contamination was characterized by total petroleum hydrocarbons, oil and grease, and GC boiling-point distribution. Univariate and multivariate statistical methods were used to examine relationships between physical and chemical properties and biological endpoints. Soil groupings based on physicochemical properties and toxicity from cluster and principal component analyses were generally similar. Correlation analysis identified a number of significant relationships between soil parameters and toxicity that were used in univariate model development. Total petroleum hydrocarbons by gas chromatography and polars were identified as predictors of earthworm avoidance and survival and seed germination, explaining 65 to 75% of the variation in the data. Asphaltenes also explained 83% of the variation in seed germination. Gravimetric total petroleum hydrocarbons explained 40% of the variation in earthworm reproduction, whereas 43% of the variation in plant root growth was explained by asphaltenes. Multivariate one-component partial least squares models, which identified predictors similar to those identified by the univariate models, were also developed for worm avoidance and survival and seed germination and had predictive powers of 42 and 29%, respectively.

  5. Infection parameters in the sand fly vector that predict transmission of Leishmania major.

    Science.gov (United States)

    Stamper, Lisa W; Patrick, Rachel L; Fay, Michael P; Lawyer, Phillip G; Elnaiem, Dia-Eldin A; Secundino, Nagila; Debrabant, Alain; Sacks, David L; Peters, Nathan C

    2011-08-01

    To identify parameters of Leishmania infection within a population of infected sand flies that reliably predict subsequent transmission to the mammalian host, we sampled groups of infected flies and compared infection intensity and degree of metacyclogenesis with the frequency of transmission. The percentage of parasites within the midgut that were metacyclic promastigotes had the highest correlation with the frequency of transmission. Meta-analysis of multiple transmission experiments allowed us to establish a percent-metacyclic "cutoff" value that predicted transmission competence. Sand fly infections initiated with variable doses of parasites resulted in correspondingly altered percentages of metacyclic promastigotes, resulting in altered transmission frequency and disease severity. Lastly, alteration of sand fly oviposition status and environmental conditions at the time of transmission also influenced transmission frequency. These observations have implications for transmission of Leishmania by the sand fly vector in both the laboratory and in nature, including how the number of organisms acquired by the sand fly from an infection reservoir may influence the clinical outcome of infection following transmission by bite.

  6. Serum parameters predict the severity of ultrasonographicifndingsinnon-alcoholic fatty liver disease

    Institute of Scientific and Technical Information of China (English)

    Mohsen Razavizade; Raika Jamali; Abbas Arj; Hamidreza Talari

    2012-01-01

    BACKGROUND: Controversy exists about the correlation between liver ultrasonography and serum parameters for evaluating the severity of liver involvement in non-alcoholic fatty liver disease (NAFLD). This study was designed to determine the association between liver ultrasonography staging in NAFLD and serum parameters correlated with disease severity in previous studies; and set optimal cut-off points for those serum parameters correlated with NAFLD staging at ultrasonography, in order to differentiate ultrasonographic groups (USGs). METHODS: This cross-sectional study evaluated outpatients with evidence of NAFLD in ultrasonography referred to a general hospital. Those with positive viral markers, abnormal serum ceruloplasmin or gamma-globulin concentrations were excluded. A radiologist performed the ultrasonography staging and stratiifed the patients into mild, moderate, and severe groups. Fasting serum alanine aminotransferase (ALT), aspartate aminotransferase, alkaline phosphatase, triglyceride (TG), high and low density lipoprotein (HDL, LDL), and cholesterol were checked. RESULTS:Two hundred and forty-ifve patients with a mean age (±standard deviation) of 41.63(±11.46) years were included. There were no signiifcant differences when mean laboratory concentrations were compared between moderate and severe USGs. Therefore, these groups were combined to create revised USGs ("mild"versus"moderate or severe"). There were associations between the revised USGs, and ALT, TG, HDL levels, and diabetes mellitus [odds ratios=2.81 (95%conifdence interval (CI):1.37-5.76), 2.48 (95%CI:1.29-4.78), 0.36 (95%CI:0.18-0.74), and 5.65 (95%CI:2.86-11.16) respectively;all P values CONCLUSIONS: Serum ALT, TG, and HDL concentrations seem to be associated with the staging by liver ultrasonography in NAFLD. They might be used to predict the staging of liver ultrasonography in these patients.

  7. Predicting the wheel rolling resistance regarding important motion parameters using the artificial neural network

    Directory of Open Access Journals (Sweden)

    F Gheshlaghi

    2016-04-01

    the analytical and statistical methods. It is expected that the neural network can more accurately predict the rolling resistance. In this study, the neural network for experimental data was trained and the relationship among some parameters of velocity, dynamic load and tire pressure and rolling resistance were evaluated. Materials and Methods: The soil bin and single wheel tester of Biosystem Engineering Mechanics Department of Urmia University was used in this study. This soil bin has 24 m length, 2 m width and 1 m depth including a single-wheel tester and the carrier. Tester consists of four horizontal arms and a vertical arm to vertical load. The S-shaped load cells were employed in horizontal arms with a load capacity of 200 kg and another 500 kg in the vertical arm was embedded. The tire used in this study was a general pneumatic tire (Good year 9.5L-14, 6 ply In this study, artificial neural networks were used for optimizing the rolling resistance by 35 neurons, 6 inputs and 1 output choices. Comparison of neural network models according to the mean square error and correlation coefficient was used. In addition, 60% of the data on training, 20% on test and finally 20% of the credits was allocated to the validation and Output parameter of the neural network model has determined the tire rolling resistance. Finally, this study predicts the effects of changing parameters of tire pressure, vertical load and velocity on rolling resistance using a trained neural network. Results and Discussion: Based on obtained error of Levenberg- Marquardt algorithm, neural network with 35 neurons in the hidden layer with sigmoid tangent function and one neuron in the output layer with linear actuator function were selected. The regression coefficient of tested network is 0.92 which seems acceptable, considering the complexity of the studied process. Some of the input parameters to the network are speed, pressure and vertical load which their relationship with the rolling

  8. Predictive value of some hematological parameters for non-invasive and invasive mole pregnancies.

    Science.gov (United States)

    Abide Yayla, Cigdem; Özkaya, Enis; Yenidede, Ilter; Eser, Ahmet; Ergen, Evrim Bostancı; Tayyar, Ahter Tanay; Şentürk, Mehmet Baki; Karateke, Ates

    2018-02-01

    The aim of this study was to discriminate mole pregnancies and invasive forms among cases with first trimester vaginal bleeding by the utilization of some complete blood count parameters conjunct to sonographic findings and beta human chorionic gonadotropin concentration. Consecutive 257 cases with histopathologically confirmed mole pregnancies and 199 women without mole pregnancy presented with first trimester vaginal bleeding who admitted to Zeynep Kamil Women and Children's Health Training Hospital between January 2012 and January 2016 were included in this cross-sectional study. The serum beta HCG level at presentation, and beta hCG levels at 1st, 2nd and 3rd weeks of postevacuation with some parameters of complete blood count were utilized to discriminate cases with molar pregnancy and cases with invasive mole among first trimester pregnants presented with vaginal bleeding and abnormal sonographic findings. Levels of beta hCG at baseline (AUC = 0.700, p < 0.05) and 1st (AUC = 0.704, p < 0.05), 2nd (AUC = 0.870, p < 0.001) and 3rd (AUC = 0.916, p < 0.001) weeks of postevacuation period were significant predictors for the cases with persistent disease. While area under curve for mean platelet volume is 0.715, it means that mean platelet volume has 21.5% additional diagnostic value for predicting persistency in molar patients. For 8.55 cut-off point for mean platelet volume, sensitivity is 84.6% and specificity is 51.6%. Area under curve for platelet/lymphocyte ratio is 0.683 means that platelet/lymphocyte ratio has additional 18.3% diagnostic value. For 102.25 cut-off point sensitivity is 86.6% and specificity is 46.2. Simple, widely available complete blood count parameters may be used as an adjunct to other risk factors to diagnose molar pregnancies and predict postevacuation trophoblastic disease.

  9. Genetic parameters for the prediction of abdominal fat traits using blood biochemical indicators in broilers.

    Science.gov (United States)

    Zhang, H L; Xu, Z Q; Yang, L L; Wang, Y X; Li, Y M; Dong, J Q; Zhang, X Y; Jiang, X Y; Jiang, X F; Li, H; Zhang, D X; Zhang, H

    2018-02-01

    1. Excessive deposition of body fat, especially abdominal fat, is detrimental in chickens and the prevention of excessive fat accumulation is an important problem. The aim of this study was to identify blood biochemical indicators that could be used as criteria to select lean Yellow-feathered chicken lines. 2. Levels of blood biochemical indicators in the fed and fasted states and the abdominal fat traits were measured in 332 Guangxi Yellow chickens. In the fed state, the genetic correlations (r g ) of triglycerides and very low density lipoprotein levels were positive for the abdominal fat traits (0.47 ≤ r g  ≤ 0.67), whereas total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) showed higher negative correlations with abdominal fat traits (-0.59 ≤ r g  ≤ -0.33). Heritabilities of these blood biochemical parameters were high, varying from 0.26 to 0.60. 3. In the fasted state, HDL-C:LDL-C level was positively correlated with abdominal fat traits (0.35 ≤ r g  ≤ 0.38), but triglycerides, total cholesterol, HDL-C, LDL-C, total protein, albumin, aspartate transaminase, uric acid and creatinine levels were negatively correlated with abdominal fat traits (-0.79 ≤ r g  ≤ -0.35). The heritabilities of these 10 blood biochemical parameters were high (0.22 ≤ h 2  ≤ 0.59). 4. In the fed state, optimal multiple regression models were constructed to predict abdominal fat traits by using triglycerides and LDL-C. In the fasted state, triglycerides, total cholesterol, HDL-C, LDL-C, total protein, albumin and uric acid could be used to predict abdominal fat content. 5. It was concluded that these models in both nutritional states could be used to predict abdominal fat content in Guangxi Yellow broiler chickens.

  10. Predictive Performance of Echocardiographic Parameters for Cardiovascular Events Among Elderly Treated Hypertensive Patients.

    Science.gov (United States)

    Chowdhury, Enayet K; Jennings, Garry L R; Dewar, Elizabeth; Wing, Lindon M H; Reid, Christopher M

    2016-07-01

    Hypertension leads to cardiac structural and functional changes, commonly assessed by echocardiography. In this study, we assessed the predictive performance of different echocardiographic parameters including left ventricular hypertrophy (LVH) on future cardiovascular outcomes in elderly hypertensive patients without heart failure. Data from LVH substudy of the Second Australian National Blood Pressure trial were used. Echocardiograms were performed at entry into the study. Cardiovascular outcomes were identified over short term (median 4.2 years) and long term (median 10.9 years). LVH was defined using threshold values of LV mass (LVM) indexed to either body surface area (BSA) or height(2.7): >115/95g/m(2) (LVH-BSA(115/95)) or ≥49/45g/m(2.7) (LVH-ht(49/45)) in males/females, respectively, and ≥125g/m(2) (LVH-BSA(125)) or ≥51g/m(2.7) (LVH-ht(51)) for both sexes. In the 666 participants aged ≥65 years in this analysis, LVH prevalence at baseline was 33%-70% depending on definition; and after adjusting for potential risk factors, only LVH-BSA(115/95) predicted both short- and long-term cardiovascular outcomes. Participants having LVH-BSA(115/95) (69%) at baseline had twice the risk of having any first cardiovascular event over the short term (hazard ratio, 95% confidence interval: 2.00, 1.12-3.57, P = 0.02) and any fatal cardiovascular events (2.11, 1.21-3.68, P = 0.01) over the longer term. Among other echocardiographic parameters, LVM and LVM indexed to either BSA or height(2.7) predicted cardiovascular events over both short and longer term. In elderly treated hypertensive patients without heart failure, determining LVH by echocardiography is highly dependent on the methodology adopted. LVH-BSA(115/95) is a reliable predictor of future cardiovascular outcomes in the elderly. © American Journal of Hypertension, Ltd 2016. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  11. Quantitative predictions from competition theory with incomplete information on model parameters tested against experiments across diverse taxa

    OpenAIRE

    Fort, Hugo

    2017-01-01

    We derive an analytical approximation for making quantitative predictions for ecological communities as a function of the mean intensity of the inter-specific competition and the species richness. This method, with only a fraction of the model parameters (carrying capacities and competition coefficients), is able to predict accurately empirical measurements covering a wide variety of taxa (algae, plants, protozoa).

  12. Prediction of DVH parameter changes due to setup errors for breast cancer treatment based on 2D portal dosimetry

    International Nuclear Information System (INIS)

    Nijsten, S. M. J. J. G.; Elmpt, W. J. C. van; Mijnheer, B. J.; Minken, A. W. H.; Persoon, L. C. G. G.; Lambin, P.; Dekker, A. L. A. J.

    2009-01-01

    Electronic portal imaging devices (EPIDs) are increasingly used for portal dosimetry applications. In our department, EPIDs are clinically used for two-dimensional (2D) transit dosimetry. Predicted and measured portal dose images are compared to detect dose delivery errors caused for instance by setup errors or organ motion. The aim of this work is to develop a model to predict dose-volume histogram (DVH) changes due to setup errors during breast cancer treatment using 2D transit dosimetry. First, correlations between DVH parameter changes and 2D gamma parameters are investigated for different simulated setup errors, which are described by a binomial logistic regression model. The model calculates the probability that a DVH parameter changes more than a specific tolerance level and uses several gamma evaluation parameters for the planning target volume (PTV) projection in the EPID plane as input. Second, the predictive model is applied to clinically measured portal images. Predicted DVH parameter changes are compared to calculated DVH parameter changes using the measured setup error resulting from a dosimetric registration procedure. Statistical accuracy is investigated by using receiver operating characteristic (ROC) curves and values for the area under the curve (AUC), sensitivity, specificity, positive and negative predictive values. Changes in the mean PTV dose larger than 5%, and changes in V 90 and V 95 larger than 10% are accurately predicted based on a set of 2D gamma parameters. Most pronounced changes in the three DVH parameters are found for setup errors in the lateral-medial direction. AUC, sensitivity, specificity, and negative predictive values were between 85% and 100% while the positive predictive values were lower but still higher than 54%. Clinical predictive value is decreased due to the occurrence of patient rotations or breast deformations during treatment, but the overall reliability of the predictive model remains high. Based on our

  13. Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

    Science.gov (United States)

    Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

    2010-05-01

    There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial

  14. What predicts inattention in adolescents? An experience-sampling study comparing chronotype, subjective, and objective sleep parameters.

    Science.gov (United States)

    Hennig, Timo; Krkovic, Katarina; Lincoln, Tania M

    2017-10-01

    Many adolescents sleep insufficiently, which may negatively affect their functioning during the day. To improve sleep interventions, we need a better understanding of the specific sleep-related parameters that predict poor functioning. We investigated to which extent subjective and objective parameters of sleep in the preceding night (state parameters) and the trait variable chronotype predict daytime inattention as an indicator of poor functioning. We conducted an experience-sampling study over one week with 61 adolescents (30 girls, 31 boys; mean age = 15.5 years, standard deviation = 1.1 years). Participants rated their inattention two times each day (morning, afternoon) on a smartphone. Subjective sleep parameters (feeling rested, positive affect upon awakening) were assessed each morning on the smartphone. Objective sleep parameters (total sleep time, sleep efficiency, wake after sleep onset) were assessed with a permanently worn actigraph. Chronotype was assessed with a self-rated questionnaire at baseline. We tested the effect of subjective and objective state parameters of sleep on daytime inattention, using multilevel multiple regressions. Then, we tested whether the putative effect of the trait parameter chronotype on inattention is mediated through state sleep parameters, again using multilevel regressions. We found that short sleep time, but no other state sleep parameter, predicted inattention to a small effect. As expected, the trait parameter chronotype also predicted inattention: morningness was associated with less inattention. However, this association was not mediated by state sleep parameters. Our results indicate that short sleep time causes inattention in adolescents. Extended sleep time might thus alleviate inattention to some extent. However, it cannot alleviate the effect of being an 'owl'. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. How Sensitive Are Transdermal Transport Predictions by Microscopic Stratum Corneum Models to Geometric and Transport Parameter Input?

    Science.gov (United States)

    Wen, Jessica; Koo, Soh Myoung; Lape, Nancy

    2018-02-01

    While predictive models of transdermal transport have the potential to reduce human and animal testing, microscopic stratum corneum (SC) model output is highly dependent on idealized SC geometry, transport pathway (transcellular vs. intercellular), and penetrant transport parameters (e.g., compound diffusivity in lipids). Most microscopic models are limited to a simple rectangular brick-and-mortar SC geometry and do not account for variability across delivery sites, hydration levels, and populations. In addition, these models rely on transport parameters obtained from pure theory, parameter fitting to match in vivo experiments, and time-intensive diffusion experiments for each compound. In this work, we develop a microscopic finite element model that allows us to probe model sensitivity to variations in geometry, transport pathway, and hydration level. Given the dearth of experimentally-validated transport data and the wide range in theoretically-predicted transport parameters, we examine the model's response to a variety of transport parameters reported in the literature. Results show that model predictions are strongly dependent on all aforementioned variations, resulting in order-of-magnitude differences in lag times and permeabilities for distinct structure, hydration, and parameter combinations. This work demonstrates that universally predictive models cannot fully succeed without employing experimentally verified transport parameters and individualized SC structures. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  16. Predicting CYP2C19 Catalytic Parameters for Enantioselective Oxidations Using Artificial Neural Networks and a Chirality Code

    Science.gov (United States)

    Hartman, Jessica H.; Cothren, Steven D.; Park, Sun-Ha; Yun, Chul-Ho; Darsey, Jerry A.; Miller, Grover P.

    2013-01-01

    Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (kcat, Km, and kcat/Km), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (kcat and Km) were more consistent with experimental values than those for catalytic efficiency (kcat/Km). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds. PMID:23673224

  17. Histopathological Parameters predicting Occult Nodal Metastases in Tongue Carcinoma Cases: An Indian Perspective.

    Science.gov (United States)

    Jacob, Tina Elizabeth; Malathi, N; Rajan, Sharada T; Augustine, Dominic; Manish, N; Patil, Shankargouda

    2016-01-01

    It is a well-established fact that in squamous cell carcinoma cases, the presence of lymph node metastases decreased the 5-year survival rate by 50% and also caused the recurrence of the primary tumor with development of distant metastases. Till date, the predictive factors for occult cervical lymph nodes metastases in cases of tongue squamous cell carcinoma remain inconclusive. Therefore, it is imperative to identify patients who are at the greatest risk for occult cervical metastases. This study was thus performed with the aim to identify various histopathologic parameters of the primary tumor that predict occult nodal metastases. The clinicopathologic features of 56 cases of lateral tongue squamous cell carcinoma with cT1NoMo/cT2NoMo as the stage and without prior radiotherapy or chemotherapy were considered. The surgical excision of primary tumor was followed by elective neck dissection. The glossectomy specimen along with the neck nodes were fixed in formalin and 5 urn thick sections were obtained. The hematoxylin & eosin stained sections were then subjected to microscopic examination. The primary tumor characteristics that were analyzed include tumor grade, invading front, depth of tumor, lymphovascular invasion, perineural invasion and inflammatory response. The nodes were examined for possible metastases using hematoxylin & eosin followed by cytokeratin immunohistochemistry. A total of 12 cases were found with positive occult nodal metastases. On performing univariate analysis, the histopathologic parameters that were found to be statistically significant were lymphovascular invasion (p = 0.004) and perineural invasion (p = 0.003) along with a cut-off depth of infiltration more than 5 mm (p = 0.01). Histopathologic assessment of the primary tumor specimen therefore continues to provide information that is central to guide clinical management, particularly in cases of occult nodal metastases. Clinical significance The study highlights the importance of

  18. Predictive Clinical Parameters and Glycemic Efficacy of Vildagliptin Treatment in Korean Subjects with Type 2 Diabetes

    Directory of Open Access Journals (Sweden)

    Jin-Sun Chang

    2013-02-01

    Full Text Available BackgroundThe aims of this study are to investigate the glycemic efficacy and predictive parameters of vildagliptin therapy in Korean subjects with type 2 diabetes.MethodsIn this retrospective study, we retrieved data for subjects who were on twice-daily 50 mg vildagliptin for at least 6 months, and classified the subjects into five treatment groups. In three of the groups, we added vildagliptin to their existing medication regimen; in the other two groups, we replaced one of their existing medications with vildagliptin. We then analyzed the changes in glucose parameters and clinical characteristics.ResultsUltimately, 327 subjects were analyzed in this study. Vildagliptin significantly improved hemoglobin A1c (HbA1c levels over 6 months. The changes in HbA1c levels (ΔHbA1c at month 6 were -2.24% (P=0.000, -0.77% (P=0.000, -0.80% (P=0.001, -0.61% (P=0.000, and -0.34% (P=0.025 for groups 1, 2, 3, 4, and 5, respectively, with significance. We also found significant decrements in fasting plasma glucose levels in groups 1, 2, 3, and 4 (P<0.05. Of the variables, initial HbA1c levels (P=0.032 and history of sulfonylurea use (P=0.026 were independently associated with responsiveness to vildagliptin treatment.ConclusionVildagliptin was effective when it was used in subjects with poor glycemic control. It controlled fasting plasma glucose levels as well as sulfonylurea treatment in Korean type 2 diabetic subjects.

  19. Optimization of Process Parameters During End Milling and Prediction of Work Piece Temperature Rise

    Directory of Open Access Journals (Sweden)

    Bhirud N.L.

    2017-09-01

    Full Text Available During the machining processes, heat gets generated as a result of plastic deformation of metal and friction along the tool–chip and tool–work piece interface. In materials having high thermal conductivity, like aluminium alloys, large amount of this heat is absorbed by the work piece. This results in the rise in the temperature of the work piece, which may lead to dimensional inaccuracies, surface damage and deformation. So, it is needed to control rise in the temperature of the work piece. This paper focuses on the measurement, analysis and prediction of work piece temperature rise during the dry end milling operation of Al 6063. The control factors used for experimentation were number of flutes, spindle speed, depth of cut and feed rate. The Taguchi method was employed for the planning of experimentation and L18 orthogonal array was selected. The temperature rise of the work piece was measured with the help of K-type thermocouple embedded in the work piece. Signal to noise (S/N ratio analysis was carried out using the lower-the-better quality characteristics. Depth of cut was identified as the most significant factor affecting the work piece temperature rise, followed by spindle speed. Analysis of variance (ANOVA was employed to find out the significant parameters affecting the work piece temperature rise. ANOVA results were found to be in line with the S/N ratio analysis. Regression analysis was used for developing empirical equation of temperature rise. The temperature rise of the work piece was calculated using the regression equation and was found to be in good agreement with the measured values. Finally, confirmation tests were carried out to verify the results obtained. From the confirmation test it was found that the Taguchi method is an effective method to determine optimised parameters for minimization of work piece temperature.

  20. Agrometeorological parameters for prediction of the maturation period of Arabica coffee cultivars

    Science.gov (United States)

    Pezzopane, José Ricardo Macedo; Salva, Terezinha de Jesus Garcia; de Lima, Valéria Bittencourt; Fazuoli, Luiz Carlos

    2012-09-01

    The objective of this study was to determine the harvest period of coffee fruits based on the relationship between agrometeorological parameters and sucrose accumulation in the seeds. Over the crop years 2004/2005 and 2006/2007, from 150 days after flowering (DAF) onwards, samples of 50 fruits of cultivars Mundo Novo IAC 376-4, Obatã IAC 1669-20 and Catuaí Vermelho IAC 144 were collected from coffee trees located in Campinas, Brazil. The endosperm of the fruits was freeze-dried, ground and analyzed for sucrose content by high-performance liquid chromatography. A weather station provided data to calculate the accumulated growing degree-day (GDD) units, and the reference (ETo) and actual (ETr) evapotranspiration rates. The results showed that the highest rates of sucrose accumulation occurred at the transition from the cane-green to the cherry phenological stage. Models for the estimation of sucrose content during maturation based on meteorological variables exhibited similar or better performance than the DAF variable, with better results for the variables GDD and ETo. The Mundo Novo cultivar reached the highest sucrose level in the endosperm after 2,790 GDD, while cultivar Catuaí attained its maximum sucrose concentration after the accumulated evapotranspiration rate has reached a value of 870 mm. As for cultivar Obatã, the maximum sucrose concentration was predicted with the same degree of accuracy using any of the parameters investigated. For the Obatã cultivar, the values of the variables calculated for the maximum sucrose concentration to be reached were 249 DAF, 3,090 GDD, 1,020 ETo and 900 ETr.

  1. Prediction of the area affected by earthquake-induced landsliding based on seismological parameters

    Science.gov (United States)

    Marc, Odin; Meunier, Patrick; Hovius, Niels

    2017-07-01

    We present an analytical, seismologically consistent expression for the surface area of the region within which most landslides triggered by an earthquake are located (landslide distribution area). This expression is based on scaling laws relating seismic moment, source depth, and focal mechanism with ground shaking and fault rupture length and assumes a globally constant threshold of acceleration for onset of systematic mass wasting. The seismological assumptions are identical to those recently used to propose a seismologically consistent expression for the total volume and area of landslides triggered by an earthquake. To test the accuracy of the model we gathered geophysical information and estimates of the landslide distribution area for 83 earthquakes. To reduce uncertainties and inconsistencies in the estimation of the landslide distribution area, we propose an objective definition based on the shortest distance from the seismic wave emission line containing 95 % of the total landslide area. Without any empirical calibration the model explains 56 % of the variance in our dataset, and predicts 35 to 49 out of 83 cases within a factor of 2, depending on how we account for uncertainties on the seismic source depth. For most cases with comprehensive landslide inventories we show that our prediction compares well with the smallest region around the fault containing 95 % of the total landslide area. Aspects ignored by the model that could explain the residuals include local variations of the threshold of acceleration and processes modulating the surface ground shaking, such as the distribution of seismic energy release on the fault plane, the dynamic stress drop, and rupture directivity. Nevertheless, its simplicity and first-order accuracy suggest that the model can yield plausible and useful estimates of the landslide distribution area in near-real time, with earthquake parameters issued by standard detection routines.

  2. The Role of Lipidogram Parameters during Pregnancy in the Prediction of Preeclampsia Development

    Directory of Open Access Journals (Sweden)

    I.B. Ventskovskaya

    2016-08-01

    Full Text Available Aim of investigation. To study the correlation between lipid metabolism during pregnancy and the risk of preeclampsia (PE. Material and methods. We have studied parameters of lipid metabolism in the blood serum of 267 pregnant women with the help of diagnostic kits. Blood sampling was carried out in I and II gestation trimesters. Total cholesterol (TC and triglycerides (TG were determined by colorimetric, enzymatic methods; high density lipoproteins (HDL — with homogeneous method, low density lipoproteins (LDL — with the direct method. Very low density lipoproteins (VLDL concentration was calculated from the Friedwald equation: VLDL = TG / 2.2. Depending on the clinical picture of PE, 43 pregnant women were divided into groups with mild and moderate-to-severe courses of the disease. Results. Among women with PE, we observed significant changes of the lipid profile parameters in the II trimester. These women had elevated TG levels in the blood serum: I group — 1.73 ± 0.14 mM/l, II group — 1.86 ± 0.18 mM/l as compared to the group III (controls — 1.32 ± 0.29 mM/l; decreased HDL indices: I group — 0.79 ± 0.19 mM/l; group II — 0.64 ± 0.04 mM/l in comparison with the control group — 1.17 ± 0.12 mM/l and increased VLDL — 0.78 ± 0.09 mM/l for group I, 0.90 ± 0.06 mM/l in women of group II unlike group III — 0.60 ± 0.16 mM/l. TC and LDL levels among patients with PE did not differ from pregnant women in the control group. Conclusions. It was demonstrated the existence of an imbalance in the synthesis of lipoproteins in women, whose pregnancies were complicated by development of PE that manifested by hypertriglyceridemia with predominance of atherogenic fractions. It was found that the investigation of the parameters of lipid profile in the II trimester of pregnancy allows us to predict the risk of PE and its long-term cardiovascular and metabolic consequences.

  3. Solubility of Carbon in Nanocrystalline -Iron

    OpenAIRE

    Alexander Kirchner; Bernd Kieback

    2012-01-01

    A thermodynamic model for nanocrystalline interstitial alloys is presented. The equilibrium solid solubility of carbon in -iron is calculated for given grain size. Inside the strained nanograins local variation of the carbon content is predicted. Due to the nonlinear relation between strain and solubility, the averaged solubility in the grain interior increases with decreasing grain size. The majority of the global solubility enhancement is due to grain boundary enrichment however. Therefor...

  4. The combination of kinetic and flow cytometric semen parameters as a tool to predict fertility in cryopreserved bull semen.

    Science.gov (United States)

    Gliozzi, T M; Turri, F; Manes, S; Cassinelli, C; Pizzi, F

    2017-11-01

    Within recent years, there has been growing interest in the prediction of bull fertility through in vitro assessment of semen quality. A model for fertility prediction based on early evaluation of semen quality parameters, to exclude sires with potentially low fertility from breeding programs, would therefore be useful. The aim of the present study was to identify the most suitable parameters that would provide reliable prediction of fertility. Frozen semen from 18 Italian Holstein-Friesian proven bulls was analyzed using computer-assisted semen analysis (CASA) (motility and kinetic parameters) and flow cytometry (FCM) (viability, acrosomal integrity, mitochondrial function, lipid peroxidation, plasma membrane stability and DNA integrity). Bulls were divided into two groups (low and high fertility) based on the estimated relative conception rate (ERCR). Significant differences were found between fertility groups for total motility, active cells, straightness, linearity, viability and percentage of DNA fragmented sperm. Correlations were observed between ERCR and some kinetic parameters, and membrane instability and some DNA integrity indicators. In order to define a model with high relation between semen quality parameters and ERCR, backward stepwise multiple regression analysis was applied. Thus, we obtained a prediction model that explained almost half (R 2=0.47, P<0.05) of the variation in the conception rate and included nine variables: five kinetic parameters measured by CASA (total motility, active cells, beat cross frequency, curvilinear velocity and amplitude of lateral head displacement) and four parameters related to DNA integrity evaluated by FCM (degree of chromatin structure abnormality Alpha-T, extent of chromatin structure abnormality (Alpha-T standard deviation), percentage of DNA fragmented sperm and percentage of sperm with high green fluorescence representative of immature cells). A significant relationship (R 2=0.84, P<0.05) was observed between

  5. Analysis of direct contact membrane distillation based on a lumped-parameter dynamic predictive model

    KAUST Repository

    Karam, Ayman M.

    2016-10-03

    Membrane distillation (MD) is an emerging technology that has a great potential for sustainable water desalination. In order to pave the way for successful commercialization of MD-based water desalination techniques, adequate and accurate dynamical models of the process are essential. This paper presents the predictive capabilities of a lumped-parameter dynamic model for direct contact membrane distillation (DCMD) and discusses the results under wide range of steady-state and dynamic conditions. Unlike previous studies, the proposed model captures the time response of the spacial temperature distribution along the flow direction. It also directly solves for the local temperatures at the membrane interfaces, which allows to accurately model and calculate local flux values along with other intrinsic variables of great influence on the process, like the temperature polarization coefficient (TPC). The proposed model is based on energy and mass conservation principles and analogy between thermal and electrical systems. Experimental data was collected to validated the steady-state and dynamic responses of the model. The obtained results shows great agreement with the experimental data. The paper discusses the results of several simulations under various conditions to optimize the DCMD process efficiency and analyze its response. This demonstrates some potential applications of the proposed model to carry out scale up and design studies. © 2016

  6. Analysis of direct contact membrane distillation based on a lumped-parameter dynamic predictive model

    KAUST Repository

    Karam, Ayman M.; Alsaadi, Ahmad Salem; Ghaffour, NorEddine; Laleg-Kirati, Taous-Meriem

    2016-01-01

    Membrane distillation (MD) is an emerging technology that has a great potential for sustainable water desalination. In order to pave the way for successful commercialization of MD-based water desalination techniques, adequate and accurate dynamical models of the process are essential. This paper presents the predictive capabilities of a lumped-parameter dynamic model for direct contact membrane distillation (DCMD) and discusses the results under wide range of steady-state and dynamic conditions. Unlike previous studies, the proposed model captures the time response of the spacial temperature distribution along the flow direction. It also directly solves for the local temperatures at the membrane interfaces, which allows to accurately model and calculate local flux values along with other intrinsic variables of great influence on the process, like the temperature polarization coefficient (TPC). The proposed model is based on energy and mass conservation principles and analogy between thermal and electrical systems. Experimental data was collected to validated the steady-state and dynamic responses of the model. The obtained results shows great agreement with the experimental data. The paper discusses the results of several simulations under various conditions to optimize the DCMD process efficiency and analyze its response. This demonstrates some potential applications of the proposed model to carry out scale up and design studies. © 2016

  7. Predicting HIV-1 transmission and antibody neutralization efficacy in vivo from stoichiometric parameters.

    Directory of Open Access Journals (Sweden)

    Oliver F Brandenberg

    2017-05-01

    Full Text Available The potential of broadly neutralizing antibodies targeting the HIV-1 envelope trimer to prevent HIV-1 transmission has opened new avenues for therapies and vaccines. However, their implementation remains challenging and would profit from a deepened mechanistic understanding of HIV-antibody interactions and the mucosal transmission process. In this study we experimentally determined stoichiometric parameters of the HIV-1 trimer-antibody interaction, confirming that binding of one antibody is sufficient for trimer neutralization. This defines numerical requirements for HIV-1 virion neutralization and thereby enables mathematical modelling of in vitro and in vivo antibody neutralization efficacy. The model we developed accurately predicts antibody efficacy in animal passive immunization studies and provides estimates for protective mucosal antibody concentrations. Furthermore, we derive estimates of the probability for a single virion to start host infection and the risks of male-to-female HIV-1 transmission per sexual intercourse. Our work thereby delivers comprehensive quantitative insights into both the molecular principles governing HIV-antibody interactions and the initial steps of mucosal HIV-1 transmission. These insights, alongside the underlying, adaptable modelling framework presented here, will be valuable for supporting in silico pre-trial planning and post-hoc evaluation of HIV-1 vaccination or antibody treatment trials.

  8. Study on the Influence of the Work Hardening Models Constitutive Parameters Identification in the Springback Prediction

    International Nuclear Information System (INIS)

    Oliveira, M.C.; Menezes, L. F.; Alves, J.L.; Chaparro, B.M.

    2005-01-01

    The main goal of this work is to determine the influence of the work hardening model in the numerical prediction of springback. This study will be performed according with the specifications of the first phase of the 'Benchmark 3' of the Numisheet'2005 Conference: the 'Channel Draw'. Several work hardening constitutive models are used in order to allow a better description of the different material mechanical behavior. Two are classical pure isotropic hardening models described by a power law (Swift) or a Voce type saturation equation. Those two models were also combined with a non-linear (Lemaitre and Chaboche) kinematic hardening rule. The final one is the Teodosiu microstructural hardening model. The study is performed for two commonly used steels of the automotive industry: mild (DC06) and dual phase (DP600) steels. The mechanical characterization, as well as the constitutive parameters identification of each work hardening models, was performed by LPMTM, based on an appropriate set of experimental data such as uniaxial tensile tests, monotonic and Bauschinger simple shear tests and orthogonal strain path tests, all at various orientations with respect to the rolling direction. All the simulations were carried out with the CEMUC's home code DD3IMP (contraction of 'Deep Drawing 3-D IMPlicit code')

  9. Predictive Blood Chemistry Parameters for Pansteatitis-Affected Mozambique Tilapia (Oreochromis mossambicus)

    Science.gov (United States)

    Chapman, Robert W.; Somerville, Stephen E.; Guillette, Matthew P.; Botha, Hannes; Hoffman, Andre; Luus-Powell, Wilmien J.; Smit, Willem J.; Lebepe, Jeffrey; Myburgh, Jan; Govender, Danny; Tucker, Jonathan; Boggs, Ashley S. P.

    2016-01-01

    One of the largest river systems in South Africa, the Olifants River, has experienced significant changes in water quality due to anthropogenic activities. Since 2005, there have been various “outbreaks” of the inflammatory disease pansteatitis in several vertebrate species. Large-scale pansteatitis-related mortality events have decimated the crocodile population at Lake Loskop and decreased the population at Kruger National Park. Most pansteatitis-related diagnoses within the region are conducted post-mortem by either gross pathology or histology. The application of a non-lethal approach to assess the prevalence and pervasiveness of pansteatitis in the Olifants River region would be of great importance for the development of a management plan for this disease. In this study, several plasma-based biomarkers accurately classified pansteatitis in Mozambique tilapia (Oreochromis mossambicus) collected from Lake Loskop using a commercially available benchtop blood chemistry analyzer combined with data interpretation via artificial neural network analysis. According to the model, four blood chemistry parameters (calcium, sodium, total protein and albumin), in combination with total length, diagnose pansteatitis to a predictive accuracy of 92 percent. In addition, several morphometric traits (total length, age, weight) were also associated with pansteatitis. On-going research will focus on further evaluating the use of blood chemistry to classify pansteatitis across different species, trophic levels, and within different sites along the Olifants River. PMID:27115488

  10. Toward Structure Prediction for Short Peptides Using the Improved SAAP Force Field Parameters

    Directory of Open Access Journals (Sweden)

    Kenichi Dedachi

    2013-01-01

    Full Text Available Based on the observation that Ramachandran-type potential energy surfaces of single amino acid units in water are in good agreement with statistical structures of the corresponding amino acid residues in proteins, we recently developed a new all-atom force field called SAAP, in which the total energy function for a polypeptide is expressed basically as a sum of single amino acid potentials and electrostatic and Lennard-Jones potentials between the amino acid units. In this study, the SAAP force field (SAAPFF parameters were improved, and classical canonical Monte Carlo (MC simulation was carried out for short peptide models, that is, Met-enkephalin and chignolin, at 300 K in an implicit water model. Diverse structures were reasonably obtained for Met-enkephalin, while three folded structures, one of which corresponds to a native-like structure with three native hydrogen bonds, were obtained for chignolin. The results suggested that the SAAP-MC method is useful for conformational sampling for the short peptides. A protocol of SAAP-MC simulation followed by structural clustering and examination of the obtained structures by ab initio calculation or simply by the number of the hydrogen bonds (or the hardness was demonstrated to be an effective strategy toward structure prediction for short peptide molecules.

  11. Predictive Blood Chemistry Parameters for Pansteatitis-Affected Mozambique Tilapia (Oreochromis mossambicus.

    Directory of Open Access Journals (Sweden)

    John A Bowden

    Full Text Available One of the largest river systems in South Africa, the Olifants River, has experienced significant changes in water quality due to anthropogenic activities. Since 2005, there have been various "outbreaks" of the inflammatory disease pansteatitis in several vertebrate species. Large-scale pansteatitis-related mortality events have decimated the crocodile population at Lake Loskop and decreased the population at Kruger National Park. Most pansteatitis-related diagnoses within the region are conducted post-mortem by either gross pathology or histology. The application of a non-lethal approach to assess the prevalence and pervasiveness of pansteatitis in the Olifants River region would be of great importance for the development of a management plan for this disease. In this study, several plasma-based biomarkers accurately classified pansteatitis in Mozambique tilapia (Oreochromis mossambicus collected from Lake Loskop using a commercially available benchtop blood chemistry analyzer combined with data interpretation via artificial neural network analysis. According to the model, four blood chemistry parameters (calcium, sodium, total protein and albumin, in combination with total length, diagnose pansteatitis to a predictive accuracy of 92 percent. In addition, several morphometric traits (total length, age, weight were also associated with pansteatitis. On-going research will focus on further evaluating the use of blood chemistry to classify pansteatitis across different species, trophic levels, and within different sites along the Olifants River.

  12. DMol3/COSMO-RS prediction of aqueous solubility and reactivity of selected Azo dyes: Effect of global orbital cut-off and COSMO segment variation

    CSIR Research Space (South Africa)

    Wahab, OO

    2018-01-01

    Full Text Available Aqueous solubility and reactivity of four azo dyes were investigated by DMol3/COSMO-RS calculation to examine the effects of global orbital cut-off and COSMO segment variation on the accuracies of theoretical solubility and reactivity. The studied...

  13. Diagnostic accuracy of soluble urokinase plasminogen activator receptor (suPAR) for prediction of bacteremia in patients with systemic inflammatory response syndrome.

    Science.gov (United States)

    Hoenigl, Martin; Raggam, Reinhard B; Wagner, Jasmin; Valentin, Thomas; Leitner, Eva; Seeber, Katharina; Zollner-Schwetz, Ines; Krammer, Werner; Prüller, Florian; Grisold, Andrea J; Krause, Robert

    2013-02-01

    Soluble urokinase plasminogen activator receptor (suPAR) serum concentrations have recently been described to reflect the severity status of systemic inflammation. In this study, the diagnostic accuracy of suPAR, C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) to predict bacteremia in patients with systemic inflammatory response syndrome (SIRS) was compared. A total of 132 patients with SIRS were included. In 55 patients blood cultures had resulted positive (study group 1, Gram positive bacteria: Staphylococcus aureus and Streptococcus spp., n=15; study group 2, Gram-negative bacteria, n=40) and 77 patients had negative blood culture results (control group, n=77). Simultaneously with blood cultures suPAR, CRP, PCT, IL-6 and white blood count (WBC) were determined. SuPAR values were significantly higher in study group 1 (median 8.11; IQR 5.78-15.53; p=0.006) and study group 2 (median 9.62; IQR 6.52-11.74; p<0.001) when compared with the control group (median 5.65; IQR 4.30-7.83). ROC curve analysis revealed an AUC of 0.726 for suPAR in differentiating SIRS patients with bacteremia from those without. The biomarkers PCT and IL-6 showed comparable results. Regarding combinations of biomarkers multiplying suPAR, PCT and IL-6 was most promising and resulted in an AUC value of 0.804. Initial suPAR serum concentrations were significantly higher (p=0.028) in patients who died within 28 days than in those who survived. No significant difference was seen for PCT, IL-6 and CRP. In conclusion, suPAR, IL-6 and PCT may contribute to predicting bacteremia in SIRS patients. Copyright © 2012 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  14. Indomethacin solubility estimation in 1,4-dioxane + water mixtures by the extended hildebrand solubility approach

    Directory of Open Access Journals (Sweden)

    Miller A Ruidiaz

    2011-09-01

    Full Text Available Extended Hildebrand Solubility Approach (EHSA was successfully applied to evaluate the solubility of Indomethacin in 1,4-dioxane + water mixtures at 298.15 K. An acceptable correlation-performance of EHSA was found by using a regular polynomial model in order four of the W interaction parameter vs. solubility parameter of the mixtures (overall deviation was 8.9%. Although the mean deviation obtained was similar to that obtained directly by means of an empiric regression of the experimental solubility vs. mixtures solubility parameters, the advantages of EHSA are evident because it requires physicochemical properties easily available for drugs.

  15. Predicting the activity coefficients of free-solvent for concentrated globular protein solutions using independently determined physical parameters.

    Directory of Open Access Journals (Sweden)

    Devin W McBride

    Full Text Available The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations.

  16. Parameter definition using vibration prediction software leads to significant drilling performance improvements

    Energy Technology Data Exchange (ETDEWEB)

    Amorim, Dalmo; Hanley, Chris Hanley; Fonseca, Isaac; Santos, Juliana [National Oilwell Varco, Houston TX (United States); Leite, Daltro J.; Borella, Augusto; Gozzi, Danilo [Petroleo Brasileiro S.A. (PETROBRAS), Rio de Janeiro, RJ (Brazil)

    2012-07-01

    field monitoring. Vibration prediction diminishes the importance of trial-and-error procedures such as drill-off tests, which are valid only for short sections. It also solves an existing lapse in Mechanical Specific Energy (MSE) real-time drilling control programs applying the theory of Teale, which states that a drilling system is perfectly efficient when it spends the exact energy to overcome the in situ rock strength. Using the proprietary software tool this paper will examine the resonant vibration modes that may be initiated while drilling with different BHA's and drill string designs, showing that the combination of a proper BHA design along with the correct selection of input parameters results in an overall improvement to drilling efficiency. Also, being the BHA predictively analyzed, it will be reduced the potential for vibration or stress fatigue in the drill string components, leading to a safer operation. In the recent years there has been an increased focus on vibration detection, analysis, and mitigation techniques, where new technologies, like the Drilling Dynamics Data Recorders (DDDR), may provide the capability to capture high frequency dynamics data at multiple points along the drilling system. These tools allow the achievement of drilling performance improvements not possible before, opening a whole new array of opportunities for optimization and for verification of predictions calculated by the drill string dynamics modeling software tool. The results of this study will identify how the dynamics from the drilling system, interacting with formation, directly relate to inefficiencies and to the possible solutions to mitigate drilling vibrations in order to improve drilling performance. Software vibration prediction and downhole measurements can be used for non-drilling operations like drilling out casing or reaming, where extremely high vibration levels - devastating to the cutting structure of the bit before it has even touched bottom - have

  17. Predictive value of semen parameters and age of the couple in pregnancy outcome after Intrauterine insemination

    Directory of Open Access Journals (Sweden)

    Marjan Sabbaghian

    2013-11-01

    Full Text Available Background: Intrauterine insemination (IUI is one the most common methods in infertility treatment, but its efficiency in infertile couples with male factor is controversial. This study is a retrospective study about correlation between semen parameters and male and female age with successful rate of IUI in patients attending to Royan Institute.Methods: A total of 998 consecutive couples in a period of 6 months undergoing IUI were included. They were classified into two groups: couples with successful and unsuccessful pregnancy. Main outcome was clinical pregnancy. Data about male and female ages and semen analysis including concentration, total sperm motility, class A motility, class B motility, class A+B motility and normal morphology was extracted from patients’ records. Semen samples were collected by masturbation or coitus after 2 to 7 days of abstinence. Their female partners were reported to have no chronic medi-cal conditions and have normal menstrual cycles.Results: One hundred and fifty seven of total 998 cycles (15.7% achieved pregnancy. The average of female age in successful and unsuccessful group was 28.95±4.19 and 30.00±4.56 years, respectively. Mean of male age was 33.97±4.85 years in successful group and 34.44±4.62 years in unsuccessful group. In successful and unsuccessful groups, average of sperm concentration was 53.62±38.45 and 46.26±26.59 (million sperm/ml, normal morphology of sperm was 8.98±4.31 (% and 8.68±4.81 (%, sperm total motility was 47.24±18.92 (% and 43.70±20.22 (% and total motile sperm count was 80.10±63.61 million and 78.57±68.22 million, respectively.Conclusion: There was no significant difference in mean of females’ age and males’ age between successful and unsuccessful groups (P<0.05. In addition, there was no significant difference in semen parameters including concentration, total sperm motility, class A motility, class B motility, class A+B motility and normal morphology between two

  18. Utility of Clinical Parameters and Multiparametric MRI as Predictive Factors for Differentiating Uterine Sarcoma From Atypical Leiomyoma.

    Science.gov (United States)

    Bi, Qiu; Xiao, Zhibo; Lv, Fajin; Liu, Yao; Zou, Chunxia; Shen, Yiqing

    2018-02-05

    The objective of this study was to find clinical parameters and qualitative and quantitative magnetic resonance imaging (MRI) features for differentiating uterine sarcoma from atypical leiomyoma (ALM) preoperatively and to calculate predictive values for uterine sarcoma. Data from 60 patients with uterine sarcoma and 88 patients with ALM confirmed by surgery and pathology were collected. Clinical parameters, qualitative MRI features, diffusion-weighted imaging with apparent diffusion coefficient values, and quantitative parameters of dynamic contrast-enhanced MRI of these two tumor types were compared. Predictive values for uterine sarcoma were calculated using multivariable logistic regression. Patient clinical manifestations, tumor locations, margins, T2-weighted imaging signals, mean apparent diffusion coefficient values, minimum apparent diffusion coefficient values, and time-signal intensity curves of solid tumor components were obvious significant parameters for distinguishing between uterine sarcoma and ALM (all P Abnormal vaginal bleeding, tumors located mainly in the uterine cavity, ill-defined tumor margins, and mean apparent diffusion coefficient values of uterine sarcoma. When the overall scores of these four predictors were greater than or equal to 7 points, the sensitivity, the specificity, the accuracy, and the positive and negative predictive values were 88.9%, 99.9%, 95.7%, 97.0%, and 95.1%, respectively. The use of clinical parameters and multiparametric MRI as predictive factors was beneficial for diagnosing uterine sarcoma preoperatively. These findings could be helpful for guiding treatment decisions. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  19. Debris-flows scale predictions based on basin spatial parameters calculated from Remote Sensing images in Wenchuan earthquake area

    International Nuclear Information System (INIS)

    Zhang, Huaizhen; Chi, Tianhe; Liu, Tianyue; Wang, Wei; Yang, Lina; Zhao, Yuan; Shao, Jing; Yao, Xiaojing; Fan, Jianrong

    2014-01-01

    Debris flow is a common hazard in the Wenchuan earthquake area. Collapse and Landslide Regions (CLR), caused by earthquakes, could be located from Remote Sensing images. CLR are the direct material source regions for debris flow. The Spatial Distribution of Collapse and Landslide Regions (SDCLR) strongly impact debris-flow formation. In order to depict SDCLR, we referred to Strahler's Hypsometric analysis method and developed 3 functional models to depict SDCLR quantitatively. These models mainly depict SDCLR relative to altitude, basin mouth and main gullies of debris flow. We used the integral of functions as the spatial parameters of SDCLR and these parameters were employed during the process of debris-flows scale predictions. Grouping-occurring debris-flows triggered by the rainstorm, which occurred on September 24th 2008 in Beichuan County, Sichuan province China, were selected to build the empirical equations for debris-flows scale predictions. Given the existing data, only debris-flows runout zone parameters (Max. runout distance L and Lateral width B) were estimated in this paper. The results indicate that the predicted results were more accurate when the spatial parameters were used. Accordingly, we suggest spatial parameters of SDCLR should be considered in the process of debris-flows scale prediction and proposed several strategies to prevent debris flow in the future

  20. On the Effect of Unit-Cell Parameters in Predicting the Elastic Response of Wood-Plastic Composites

    Directory of Open Access Journals (Sweden)

    Fatemeh Alavi

    2013-01-01

    Full Text Available This paper presents a study on the effect of unit-cell geometrical parameters in predicting elastic properties of a typical wood plastic composite (WPC. The ultimate goal was obtaining the optimal values of representative volume element (RVE parameters to accurately predict the mechanical behavior of the WPC. For each unit cell, defined by a given combination of the above geometrical parameters, finite element simulation in ABAQUS was carried out, and the corresponding stress-strain curve was obtained. A uniaxial test according to ASTM D638-02a type V was performed on the composite specimen. Modulus of elasticity was determined using hyperbolic tangent function, and the results were compared to the sets of finite element analyses. Main effects of RVE parameters and their interactions were demonstrated and discussed, specially regarding the inclusion of two adjacent wood particles within one unit cell of the material. Regression analysis was performed to mathematically model the RVE parameter effects and their interactions over the modulus of elasticity response. The model was finally employed in an optimization analysis to arrive at an optimal set of RVE parameters that minimizes the difference between the predicted and experimental moduli of elasticity.

  1. Solubility of Oxygen in Liquid Sodium and the Interpretation of Predictions for the Corrosion Rate of Stainless Steels in Liquid Sodium

    International Nuclear Information System (INIS)

    Claxton, K. T.

    1979-01-01

    A statistical analysis of all oxygen in sodium solubility data has been made. The results indicate a real difference. between levels of oxygen reported by UK und US workers. Analysis using sub-sets of culled data to derive a compromise solubility function are considered less than adequate. It is considered preferable and more realistic to distinguish data sub-sets by the analytical technique employed. The vacuum distillation method yields results differing amongst them selves by up to a factor of five at cold trap temperatures of relevance to fast reactor operation. The vanadium wire and electrochemical cell techniques give the lowest solubility values. (Author) 51 refs

  2. Augmented chaos-multiple linear regression approach for prediction of wave parameters

    Directory of Open Access Journals (Sweden)

    M.A. Ghorbani

    2017-06-01

    The inter-comparisons demonstrated that the Chaos-MLR and pure MLR models yield almost the same accuracy in predicting the significant wave heights and the zero-up-crossing wave periods. Whereas, the augmented Chaos-MLR model is performed better results in term of the prediction accuracy vis-a-vis the previous prediction applications of the same case study.

  3. Baseline 18F-FDG PET image-derived parameters for therapy response prediction in oesophageal cancer

    International Nuclear Information System (INIS)

    Hatt, Mathieu; Visvikis, Dimitris; Cheze-le Rest, Catherine; Pradier, Olivier

    2011-01-01

    The objectives of this study were to investigate the predictive value of tumour measurements on 2-deoxy-2-[ 18 F]fluoro-D-glucose ( 18 F-FDG) positron emission tomography (PET) pretreatment scan regarding therapy response in oesophageal cancer and to evaluate the impact of tumour delineation strategies. Fifty patients with oesophageal cancer treated with concomitant radiochemotherapy between 2004 and 2008 were retrospectively considered and classified as complete, partial or non-responders (including stable and progressive disease) according to Response Evaluation Criteria in Solid Tumors (RECIST). The classification of partial and complete responders was confirmed by biopsy. Tumours were delineated on the 18 F-FDG pretreatment scan using an adaptive threshold and the automatic fuzzy locally adaptive Bayesian (FLAB) methodologies. Several parameters were then extracted: maximum and peak standardized uptake value (SUV), tumour longitudinal length (TL) and volume (TV), SUV mean , and total lesion glycolysis (TLG = TV x SUV mean ). The correlation between each parameter and response was investigated using Kruskal-Wallis tests, and receiver-operating characteristic methodology was used to assess performance of the parameters to differentiate patients. Whereas commonly used parameters such as SUV measurements were not significant predictive factors of the response, parameters related to tumour functional spatial extent (TL, TV, TLG) allowed significant differentiation of all three groups of patients, independently of the delineation strategy, and could identify complete and non-responders with sensitivity above 75% and specificity above 85%. A systematic although not statistically significant trend was observed regarding the hierarchy of the delineation methodologies and the parameters considered, with slightly higher predictive value obtained with FLAB over adaptive thresholding, and TLG over TV and TL. TLG is a promising predictive factor of concomitant

  4. Baseline {sup 18}F-FDG PET image-derived parameters for therapy response prediction in oesophageal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Hatt, Mathieu; Visvikis, Dimitris; Cheze-le Rest, Catherine [CHU Morvan, LaTIM, INSERM U650, Brest (France); Pradier, Olivier [CHU Morvan, LaTIM, INSERM U650, Brest (France); CHU Morvan, Department of Radiotherapy, Brest (France)

    2011-09-15

    The objectives of this study were to investigate the predictive value of tumour measurements on 2-deoxy-2-[{sup 18}F]fluoro-D-glucose ({sup 18}F-FDG) positron emission tomography (PET) pretreatment scan regarding therapy response in oesophageal cancer and to evaluate the impact of tumour delineation strategies. Fifty patients with oesophageal cancer treated with concomitant radiochemotherapy between 2004 and 2008 were retrospectively considered and classified as complete, partial or non-responders (including stable and progressive disease) according to Response Evaluation Criteria in Solid Tumors (RECIST). The classification of partial and complete responders was confirmed by biopsy. Tumours were delineated on the {sup 18}F-FDG pretreatment scan using an adaptive threshold and the automatic fuzzy locally adaptive Bayesian (FLAB) methodologies. Several parameters were then extracted: maximum and peak standardized uptake value (SUV), tumour longitudinal length (TL) and volume (TV), SUV{sub mean}, and total lesion glycolysis (TLG = TV x SUV{sub mean}). The correlation between each parameter and response was investigated using Kruskal-Wallis tests, and receiver-operating characteristic methodology was used to assess performance of the parameters to differentiate patients. Whereas commonly used parameters such as SUV measurements were not significant predictive factors of the response, parameters related to tumour functional spatial extent (TL, TV, TLG) allowed significant differentiation of all three groups of patients, independently of the delineation strategy, and could identify complete and non-responders with sensitivity above 75% and specificity above 85%. A systematic although not statistically significant trend was observed regarding the hierarchy of the delineation methodologies and the parameters considered, with slightly higher predictive value obtained with FLAB over adaptive thresholding, and TLG over TV and TL. TLG is a promising predictive factor of

  5. Rationalization and prediction of in vivo metabolite exposures: The role of metabolite kinetics, clearance predictions and in vitro parameters

    Science.gov (United States)

    Lutz, Justin D.; Fujioka, Yasushi; Isoherranen, Nina

    2010-01-01

    Importance of the field Due to growing concerns over toxic or active metabolites, significant efforts have been focused on qualitative identification of potential in vivo metabolites from in vitro data. However, limited tools are available to quantitatively predict their human exposures. Areas covered in this review Theory of clearance predictions and metabolite kinetics is reviewed together with supporting experimental data. In vitro and in vivo data of known circulating metabolites and their parent drugs was collected and the predictions of in vivo exposures of the metabolites were evaluated. What the reader will gain The theory and data reviewed will be useful in early identification of human metabolites that will circulate at significant levels in vivo and help in designing in vivo studies that focus on characterization of metabolites. It will also assist in rationalization of metabolite-to-parent ratios used as markers of specific enzyme activity. Take home message The relative importance of a metabolite in comparison to the parent compound as well as other metabolites in vivo can only be predicted using the metabolites in vitro formation and elimination clearances, and the in vivo disposition of a metabolite can only be rationalized when the elimination pathways of that metabolite are known. PMID:20557268

  6. High variation of individual soluble serum CD30 levels of pre-transplantation patients: sCD30 a feasible marker for prediction of kidney allograft rejection?

    Science.gov (United States)

    Altermann, Wolfgang; Schlaf, Gerald; Rothhoff, Anita; Seliger, Barbara

    2007-10-01

    Previous studies have suggested that the pre-transplant levels of the soluble CD30 molecule (sCD30) represent a non-invasive tool which can be used as a biomarker for the prediction of kidney allograft rejections. In order to evaluate the feasibility of sCD30 for pre-transplantation monitoring the sera of potential kidney recipients (n = 652) were collected four times in a 3 months interval. Serum from healthy blood donors (n = 203) served as controls. The sCD30 concentrations of all samples were determined using a commercially available ELISA. This strategy allowed the detection of possible variations of individual sCD30 levels over time. Heterogeneous sCD30 concentrations were found in the samples obtained from individual putative kidney transplant recipients when quarterly measured over 1 year. Total 95% of serum samples obtained from healthy controls exhibited sCD30 values 30 U/ml). Total 524 patients (80.4%) constantly exhibited serum concentrations of sCD30 values >100 U/ml was significantly lower than that previously reported. The high degree of variation does not allow the stratification of patients into high and low immunological risk groups based on a single sCD30 value > 100 U/ml. Due to the heterogeneity of sCD30 levels during time course and the high values of SD, its implementation as a pre-transplant marker cannot be justified to generate special provisions for the organ allocation to patients with single sCD30 values > 100 U/ml.

  7. Soluble CD30 and ELISA-detected human leukocyte antigen antibodies for the prediction of acute rejection in pediatric renal transplant recipients.

    Science.gov (United States)

    Billing, Heiko; Sander, Anja; Süsal, Caner; Ovens, Jörg; Feneberg, Reinhard; Höcker, Britta; Vondrak, Karel; Grenda, Ryszard; Friman, Stybjorn; Milford, David V; Lucan, Mihai; Opelz, Gerhard; Tönshoff, Burkhard

    2013-03-01

    Biomarker-based post-transplant immune monitoring for the prediction of impending graft rejection requires validation in specific patient populations. Serum of 28 pediatric renal transplant recipients within the framework of a well-controlled prospective randomized trial was analyzed pre- and post-transplant for soluble CD30 (sCD30), a biomarker reflecting mainly T-cell reactivity, and anti-human leukocyte antigen (anti-HLA) antibody reactivity, a biomarker for B-cell activation. A sCD30 concentration ≥40.3 U/ml on day 14 was able to discriminate between patients with or without biopsy-proven acute rejection (BPAR) with a sensitivity of 100% and a specificity of 76%. Six of seven patients (86%) with BPAR showed a sCD30 above this cut-off, whereas only 3/21 patients (14%) without BPAR had a sCD30 above this cut-off (P = 0.004). For pre- and post-transplant anti-HLA class II reactivities by enzyme-linked immunosorbent assay, a cut-off value of 140 optical density was able to discriminate rejecters from nonrejecters with a sensitivity of 86% or 71% and a specificity of 81% or 90%, respectively. Withdrawal of steroids was associated with a approximately twofold higher serum sCD30 compared to controls, but did not affect anti-HLA reactivities. An increased post-transplant sCD30 serum concentration and positive pre- and post-transplant anti-HLA class II reactivities are informative biomarkers for impending BPAR in pediatric renal transplant recipients. (TWIST, Clinical Trial No: FG-506-02-43). © 2012 The Authors Transplant International © 2012 European Society for Organ Transplantation. Published by Blackwell Publishing Ltd.

  8. Artificial neural network and response surface methodology modeling in mass transfer parameters predictions during osmotic dehydration of Carica papaya L.

    Directory of Open Access Journals (Sweden)

    J. Prakash Maran

    2013-09-01

    Full Text Available In this study, a comparative approach was made between artificial neural network (ANN and response surface methodology (RSM to predict the mass transfer parameters of osmotic dehydration of papaya. The effects of process variables such as temperature, osmotic solution concentration and agitation speed on water loss, weight reduction, and solid gain during osmotic dehydration were investigated using a three-level three-factor Box-Behnken experimental design. Same design was utilized to train a feed-forward multilayered perceptron (MLP ANN with back-propagation algorithm. The predictive capabilities of the two methodologies were compared in terms of root mean square error (RMSE, mean absolute error (MAE, standard error of prediction (SEP, model predictive error (MPE, chi square statistic (χ2, and coefficient of determination (R2 based on the validation data set. The results showed that properly trained ANN model is found to be more accurate in prediction as compared to RSM model.

  9. Relationship of the Content of Systemic and Endobronchial Soluble Molecules of CD25, CD38, CD8, and HLA-I-CD8 and Lung Function Parameters in COPD Patients

    Directory of Open Access Journals (Sweden)

    Nailya Kubysheva

    2017-01-01

    Full Text Available The definition of new markers of local and systemic inflammation of chronic obstructive pulmonary disease (COPD is one of the priority directions in the study of pathogenesis and diagnostic methods improvement for this disease. We investigated 91 patients with COPD and 21 healthy nonsmokers. The levels of soluble CD25, CD38, CD8, and HLA-I-CD8 molecules in the blood serum and exhaled breath condensate (EBC in moderate-to-severe COPD patients during exacerbation and stable phase were studied. An unidirectional change in the content of sCD25, sCD38, and sCD8 molecules with increasing severity of COPD was detected. The correlations between the parameters of lung function and sCD8, sCD25, and sHLA-I-CD8 levels in the blood serum and EBC were discovered in patients with severe COPD. The findings suggest a pathogenetic role of the investigated soluble molecules of the COPD development and allow considering the content of sCD8, sCD25, and sHLA-I-CD8 molecules as additional novel systemic and endobronchial markers of the progression of chronic inflammation of this disease.

  10. PREDICTIVE ACCURACY OF TRANSCEREBELLAR DIAMETER IN COMPARISON WITH OTHER FOETAL BIOMETRIC PARAMETERS FOR GESTATIONAL AGE ESTIMATION AMONG PREGNANT NIGERIAN WOMEN.

    Science.gov (United States)

    Adeyekun, A A; Orji, M O

    2014-04-01

    To compare the predictive accuracy of foetal trans-cerebellar diameter (TCD) with those of other biometric parameters in the estimation of gestational age (GA). A cross-sectional study. The University of Benin Teaching Hospital, Nigeria. Four hundred and fifty healthy singleton pregnant women, between 14-42 weeks gestation. Trans-cerebellar diameter (TCD), biparietal diameter (BPD), femur length (FL), abdominal circumference (AC) values across the gestational age range studied. Correlation and predictive values of TCD compared to those of other biometric parameters. The range of values for TCD was 11.9 - 59.7mm (mean = 34.2 ± 14.1mm). TCD correlated more significantly with menstrual age compared with other biometric parameters (r = 0.984, p = 0.000). TCD had a higher predictive accuracy of 96.9% ± 12 days), BPD (93.8% ± 14.1 days). AC (92.7% ± 15.3 days). TCD has a stronger predictive accuracy for gestational age compared to other routinely used foetal biometric parameters among Nigerian Africans.

  11. A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non-Gaussian errors

    NARCIS (Netherlands)

    Schoups, G.; Vrugt, J.A.

    2010-01-01

    Estimation of parameter and predictive uncertainty of hydrologic models has traditionally relied on several simplifying assumptions. Residual errors are often assumed to be independent and to be adequately described by a Gaussian probability distribution with a mean of zero and a constant variance.

  12. Thermodynamic Solubility Profile of Carbamazepine-Cinnamic Acid Cocrystal at Different pH.

    Science.gov (United States)

    Keramatnia, Fatemeh; Shayanfar, Ali; Jouyban, Abolghasem

    2015-08-01

    Pharmaceutical cocrystal formation is a direct way to dramatically influence physicochemical properties of drug substances, especially their solubility and dissolution rate. Because of their instability in the solution, thermodynamic solubility of cocrystals could not be determined in the common way like other compounds; therefore, the thermodynamic solubility is calculated through concentration of their components in the eutectic point. The objective of this study is to investigate the effect of an ionizable coformer in cocrystal with a nonionizable drug at different pH. Carbamazepine (CBZ), a nonionizable drug with cinnamic acid (CIN), which is an acidic coformer, was selected to prepare CBZ-CIN cocrystal and its thermodynamic solubility was studied in pH range 2-7. Instead of HPLC that is a costly and time-consuming method, a chemometric-based approach, net analyte signal standard addition method, was selected for simultaneous determination of CBZ and CIN in solution. The result showed that, as pH increases, CIN ionization leads to change in CBZ-CIN cocrystal solubility and stability in solution. In addition, the results of this study indicated that there is no significant difference between intrinsic solubility of CBZ and cocrystal despite the higher ideal solubility of cocrystal. This verifies that ideal solubility is not good parameter to predict cocrystal solubility. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

  13. Theoretical prediction of Grüneisen parameter for SiO_2.TiO_2 bulk metallic glasses

    International Nuclear Information System (INIS)

    Singh, Chandra K.; Pandey, Brijesh K.; Pandey, Anjani K.

    2016-01-01

    The Grüneisen parameter (γ) is very important to decide the limitations for the prediction of thermoelastic properties of bulk metallic glasses. It can be defined in terms of microscopic and macroscopic parameters of the material in which former is based on vibrational frequencies of atoms in the material while later is closely related to its thermodynamic properties. Different formulation and equation of states are used by the pioneer researchers of this field to predict the true sense of Gruneisen parameter for BMG but for SiO_2.TiO_2 very few and insufficient information is available till now. In the present work we have tested the validity of two different isothermal EOS viz. Poirrior-Tarantola EOS and Usual-Tait EOS to predict the true value of Gruneisen parameter for SiO_2.TiO_2 as a function of compression. Using different thermodynamic limitations related to the material constraints and analyzing obtained result it is concluded that the Poirrior-Tarantola EOS gives better numeric values of Grüneisen parameter (γ) for SiO_2.TiO_2 BMG.

  14. Accuracy of various iron parameters in the prediction of iron deficiency in an acute care hospital

    NARCIS (Netherlands)

    Ong, K. H.; Tan, H. L.; Lai, H. C.; Kuperan, P.

    2005-01-01

    INTRODUCTION: Iron parameters like serum ferritin and iron saturation are routinely used in diagnosing iron deficiency. However, these tests are influenced by many factors. We aimed to review the accuracy of iron parameters among inpatients in an acute care hospital. MATERIALS AND METHODS: From

  15. Parameter Estimation and Prediction of a Nonlinear Storage Model: an algebraic approach

    NARCIS (Netherlands)

    Doeswijk, T.G.; Keesman, K.J.

    2005-01-01

    Generally, parameters that are nonlinear in system models are estimated by nonlinear least-squares optimization algorithms. In this paper, if a nonlinear discrete-time model with a polynomial quotient structure in input, output, and parameters, a method is proposed to re-parameterize the model such

  16. Impacts of Earth rotation parameters on GNSS ultra-rapid orbit prediction: Derivation and real-time correction

    Science.gov (United States)

    Wang, Qianxin; Hu, Chao; Xu, Tianhe; Chang, Guobin; Hernández Moraleda, Alberto

    2017-12-01

    Analysis centers (ACs) for global navigation satellite systems (GNSSs) cannot accurately obtain real-time Earth rotation parameters (ERPs). Thus, the prediction of ultra-rapid orbits in the international terrestrial reference system (ITRS) has to utilize the predicted ERPs issued by the International Earth Rotation and Reference Systems Service (IERS) or the International GNSS Service (IGS). In this study, the accuracy of ERPs predicted by IERS and IGS is analyzed. The error of the ERPs predicted for one day can reach 0.15 mas and 0.053 ms in polar motion and UT1-UTC direction, respectively. Then, the impact of ERP errors on ultra-rapid orbit prediction by GNSS is studied. The methods for orbit integration and frame transformation in orbit prediction with introduced ERP errors dominate the accuracy of the predicted orbit. Experimental results show that the transformation from the geocentric celestial references system (GCRS) to ITRS exerts the strongest effect on the accuracy of the predicted ultra-rapid orbit. To obtain the most accurate predicted ultra-rapid orbit, a corresponding real-time orbit correction method is developed. First, orbits without ERP-related errors are predicted on the basis of ITRS observed part of ultra-rapid orbit for use as reference. Then, the corresponding predicted orbit is transformed from GCRS to ITRS to adjust for the predicted ERPs. Finally, the corrected ERPs with error slopes are re-introduced to correct the predicted orbit in ITRS. To validate the proposed method, three experimental schemes are designed: function extrapolation, simulation experiments, and experiments with predicted ultra-rapid orbits and international GNSS Monitoring and Assessment System (iGMAS) products. Experimental results show that using the proposed correction method with IERS products considerably improved the accuracy of ultra-rapid orbit prediction (except the geosynchronous BeiDou orbits). The accuracy of orbit prediction is enhanced by at least 50

  17. A new model using routinely available clinical parameters to predict significant liver fibrosis in chronic hepatitis B.

    Directory of Open Access Journals (Sweden)

    Wai-Kay Seto

    Full Text Available OBJECTIVE: We developed a predictive model for significant fibrosis in chronic hepatitis B (CHB based on routinely available clinical parameters. METHODS: 237 treatment-naïve CHB patients [58.4% hepatitis B e antigen (HBeAg-positive] who had undergone liver biopsy were randomly divided into two cohorts: training group (n = 108 and validation group (n = 129. Liver histology was assessed for fibrosis. All common demographics, viral serology, viral load and liver biochemistry were analyzed. RESULTS: Based on 12 available clinical parameters (age, sex, HBeAg status, HBV DNA, platelet, albumin, bilirubin, ALT, AST, ALP, GGT and AFP, a model to predict significant liver fibrosis (Ishak fibrosis score ≥3 was derived using the five best parameters (age, ALP, AST, AFP and platelet. Using the formula log(index+1 = 0.025+0.0031(age+0.1483 log(ALP+0.004 log(AST+0.0908 log(AFP+1-0.028 log(platelet, the PAPAS (Platelet/Age/Phosphatase/AFP/AST index predicts significant fibrosis with an area under the receiving operating characteristics (AUROC curve of 0.776 [0.797 for patients with ALT <2×upper limit of normal (ULN] The negative predictive value to exclude significant fibrosis was 88.4%. This predictive power is superior to other non-invasive models using common parameters, including the AST/platelet/GGT/AFP (APGA index, AST/platelet ratio index (APRI, and the FIB-4 index (AUROC of 0.757, 0.708 and 0.723 respectively. Using the PAPAS index, 67.5% of liver biopsies for patients being considered for treatment with ALT <2×ULN could be avoided. CONCLUSION: The PAPAS index can predict and exclude significant fibrosis, and may reduce the need for liver biopsy in CHB patients.

  18. Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction

    Directory of Open Access Journals (Sweden)

    Cobaugh Christian W

    2004-08-01

    Full Text Available Abstract Background A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1. Results The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases. Conclusion Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.

  19. Geoelectrical parameter-based multivariate regression borehole yield model for predicting aquifer yield in managing groundwater resource sustainability

    Directory of Open Access Journals (Sweden)

    Kehinde Anthony Mogaji

    2016-07-01

    Full Text Available This study developed a GIS-based multivariate regression (MVR yield rate prediction model of groundwater resource sustainability in the hard-rock geology terrain of southwestern Nigeria. This model can economically manage the aquifer yield rate potential predictions that are often overlooked in groundwater resources development. The proposed model relates the borehole yield rate inventory of the area to geoelectrically derived parameters. Three sets of borehole yield rate conditioning geoelectrically derived parameters—aquifer unit resistivity (ρ, aquifer unit thickness (D and coefficient of anisotropy (λ—were determined from the acquired and interpreted geophysical data. The extracted borehole yield rate values and the geoelectrically derived parameter values were regressed to develop the MVR relationship model by applying linear regression and GIS techniques. The sensitivity analysis results of the MVR model evaluated at P ⩽ 0.05 for the predictors ρ, D and λ provided values of 2.68 × 10−05, 2 × 10−02 and 2.09 × 10−06, respectively. The accuracy and predictive power tests conducted on the MVR model using the Theil inequality coefficient measurement approach, coupled with the sensitivity analysis results, confirmed the model yield rate estimation and prediction capability. The MVR borehole yield prediction model estimates were processed in a GIS environment to model an aquifer yield potential prediction map of the area. The information on the prediction map can serve as a scientific basis for predicting aquifer yield potential rates relevant in groundwater resources sustainability management. The developed MVR borehole yield rate prediction mode provides a good alternative to other methods used for this purpose.

  20. Prediction of pharmacokinetic and toxicological parameters of a 4-phenylcoumarin isolated from geopropolis: In silico and in vitro approaches.

    Science.gov (United States)

    da Cunha, Marcos Guilherme; Franco, Gilson César Nobre; Franchin, Marcelo; Beutler, John A; de Alencar, Severino Matias; Ikegaki, Masaharu; Rosalen, Pedro Luiz

    2016-11-30

    In silico and in vitro methodologies have been used as important tools in the drug discovery process, including from natural sources. The aim of this study was to predict pharmacokinetic and toxicity (ADME/Tox) properties of a coumarin isolated from geopropolis using in silico and in vitro approaches. Cinnamoyloxy-mammeisin (CNM) isolated from Brazilian M. scutellaris geopropolis was evaluated for its pharmacokinetic parameters by in silico models (ACD/Percepta™ and MetaDrug™ software). Genotoxicity was assessed by in vitro DNA damage signaling PCR array. CNM did not pass all parameters of Lipinski's rule of five, with a predicted low oral bioavailability and high plasma protein binding, but with good predicted blood brain barrier penetration. CNM was predicted to show low affinity to cytochrome P450 family members. Furthermore, the predicted Ames test indicated potential mutagenicity of CNM. Also, the probability of toxicity for organs and tissues was classified as moderate and high for liver and kidney, and moderate and low for skin and eye irritation, respectively. The PCR array analysis showed that CNM significantly upregulated about 7% of all DNA damage-related genes. By exploring the biological function of these genes, it was found that the predicted CNM genotoxicity is likely to be mediated by apoptosis. The predicted ADME/Tox profile suggests that external use of CNM may be preferable to systemic exposure, while its genotoxicity was characterized by the upregulation of apoptosis-related genes after treatment. The combined use of in silico and in vitro approaches to evaluate these parameters generated useful hypotheses to guide further preclinical studies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  1. Parameter uncertainty and model predictions: a review of Monte Carlo results

    International Nuclear Information System (INIS)

    Gardner, R.H.; O'Neill, R.V.

    1979-01-01

    Studies of parameter variability by Monte Carlo analysis are reviewed using repeated simulations of the model with randomly selected parameter values. At the beginning of each simulation, parameter values are chosen from specific frequency distributions. This process is continued for a number of iterations sufficient to converge on an estimate of the frequency distribution of the output variables. The purpose was to explore the general properties of error propagaton in models. Testing the implicit assumptions of analytical methods and pointing out counter-intuitive results produced by the Monte Carlo approach are additional points covered

  2. Stochastic rainfall-runoff forecasting: parameter estimation, multi-step prediction, and evaluation of overflow risk

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Madsen, Henrik

    2014-01-01

    Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date...... the identification of models for cases with noisy in-sewer observations. For the prediction of the overflow risk, no improvement was demonstrated through the application of stochastic forecasts instead of point predictions, although this result is thought to be caused by the notably simplified setup used...

  3. Real Time Predictive Flutter Analysis and Continuous Parameter Identification of Accelerating Aircraft

    National Research Council Canada - National Science Library

    Farhat, Charles

    1998-01-01

    ... Parameter Identification of Accelerating Aircraft. Flutter clearance, which is part of any new aircraft or fighter weapon system development, is a lengthy and tedious process from both computational and flight testing viewpoint...

  4. A Well-Designed Parameter Estimation Method for Lifetime Prediction of Deteriorating Systems with Both Smooth Degradation and Abrupt Damage

    Directory of Open Access Journals (Sweden)

    Chuanqiang Yu

    2015-01-01

    Full Text Available Deteriorating systems, which are subject to both continuous smooth degradation and additional abrupt damages due to a shock process, can be often encountered in engineering. Modeling the degradation evolution and predicting the lifetime of this kind of systems are both interesting and challenging in practice. In this paper, we model the degradation trajectory of the deteriorating system by a random coefficient regression (RCR model with positive jumps, where the RCR part is used to model the continuous smooth degradation of the system and the jump part is used to characterize the abrupt damages due to random shocks. Based on a specified threshold level, the probability density function (PDF and cumulative distribution function (CDF of the lifetime can be derived analytically. The unknown parameters associated with the derived lifetime distributions can be estimated via a well-designed parameter estimation procedure on the basis of the available degradation recordings of the deteriorating systems. An illustrative example is finally provided to demonstrate the implementation and superiority of the newly proposed lifetime prediction method. The experimental results reveal that our proposed lifetime prediction method with the dedicated parameter estimation strategy can get more accurate lifetime predictions than the rival model in literature.

  5. QSPR studies for predicting polarity parameter of organic compounds in methanol using support vector machine and enhanced replacement method.

    Science.gov (United States)

    Golmohammadi, H; Dashtbozorgi, Z

    2016-12-01

    In the present work, enhanced replacement method (ERM) and support vector machine (SVM) were used for quantitative structure-property relationship (QSPR) studies of polarity parameter (p) of various organic compounds in methanol in reversed phase liquid chromatography based on molecular descriptors calculated from the optimized structures. Diverse kinds of molecular descriptors were calculated to encode the molecular structures of compounds, such as geometric, thermodynamic, electrostatic and quantum mechanical descriptors. The variable selection method of ERM was employed to select an optimum subset of descriptors. The five descriptors selected using ERM were used as inputs of SVM to predict the polarity parameter of organic compounds in methanol. The coefficient of determination, r 2 , between experimental and predicted polarity parameters for the prediction set by ERM and SVM were 0.952 and 0.982, respectively. Acceptable results specified that the ERM approach is a very effective method for variable selection and the predictive aptitude of the SVM model is superior to those obtained by ERM. The obtained results demonstrate that SVM can be used as a substitute influential modeling tool for QSPR studies.

  6. Application of decomposition method and inverse prediction of parameters in a moving fin

    International Nuclear Information System (INIS)

    Singla, Rohit K.; Das, Ranjan

    2014-01-01

    Highlights: • Adomian decomposition is used to study a moving fin. • Effects of different parameters on the temperature and efficiency are studied. • Binary-coded GA is used to solve an inverse problem. • Sensitivity analyses of important parameters are carried out. • Measurement error up to 8% is found to be tolerable. - Abstract: The application of the Adomian decomposition method (ADM) is extended to study a conductive–convective and radiating moving fin having variable thermal conductivity. Next, through an inverse approach, ADM in conjunction with a binary-coded genetic algorithm (GA) is also applied for estimation of unknown properties in order to satisfy a given temperature distribution. ADM being one of the widely-used numerical methods for solving non-linear equations, the required temperature field has been obtained using a forward method involving ADM. In the forward problem, the temperature field and efficiency are investigated for various parameters such as convection–conduction parameter, radiation–conduction parameter, Peclet number, convection sink temperature, radiation sink temperature, and dimensionless thermal conductivity. Additionally, in the inverse problem, the effect of random measurement errors, iterative variation of parameters, sensitivity coefficients of unknown parameters are investigated. The performance of GA is compared with few other optimization methods as well as with different temperature measurement points. It is found from the present study that the results obtained from ADM are in good agreement with the results of the differential transformation method available in the literature. It is also observed that for satisfactory reconstruction of the temperature field, the measurement error should be within 8% and the temperature field is strongly dependent on the speed than thermal parameters of the moving fin

  7. Volumetric PET/CT parameters predict local response of head and neck squamous cell carcinoma to chemoradiotherapy

    International Nuclear Information System (INIS)

    Hanamoto, Atsushi; Tatsumi, Mitsuaki; Takenaka, Yukinori; Hamasaki, Toshimitsu; Yasui, Toshimichi; Nakahara, Susumu; Yamamoto, Yoshifumi; Seo, Yuji; Isohashi, Fumiaki; Ogawa, Kazuhiko; Hatazawa, Jun; Inohara, Hidenori

    2014-01-01

    It is not well established whether pretreatment 18 F-FDG PET/CT can predict local response of head and neck squamous cell carcinoma (HNSCC) to chemoradiotherapy (CRT). We examined 118 patients: 11 with nasopharyngeal cancer (NPC), 30 with oropharyngeal cancer (OPC), and 77 with laryngohypopharyngeal cancer (LHC) who had completed CRT. PET/CT parameters of primary tumor, including metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum and mean standardized uptake value (SUV max and SUV mean ), were correlated with local response, according to primary site and human papillomavirus (HPV) status. Receiver-operating characteristic analyses were made to access predictive values of the PET/CT parameters, while logistic regression analyses were used to identify independent predictors. Area under the curve (AUC) of the PET/CT parameters ranged from 0.53 to 0.63 in NPC and from 0.50 to 0.54 in OPC. HPV-negative OPC showed AUC ranging from 0.51 to 0.58, while all of HPV-positive OPCs showed complete response. In contrast, AUC ranged from 0.71 to 0.90 in LHC. Moreover, AUCs of MTV and TLG were significantly higher than those of SUV max and SUV mean (P < 0.01). After multivariate analysis, high MTV >25.0 mL and high TLG >144.8 g remained as independent, significant predictors of incomplete response compared with low MTV (odds ratio [OR], 13.4; 95% confidence interval [CI], 2.5–72.9; P = 0.003) and low TLG (OR, 12.8; 95% CI, 2.4–67.9; P = 0.003), respectively. In conclusion, predictive efficacy of pretreatment 18 F-FDG PET/CT varies with different primary sites and chosen parameters. Local response of LHC is highly predictable by volume-based PET/CT parameters

  8. Functional parameter screening for predicting durability of rolling sliding contacts with different surface finishes

    Science.gov (United States)

    Dimkovski, Z.; Lööf, P.-J.; Rosén, B.-G.; Nilsson, P. H.

    2018-06-01

    The reliability and lifetime of machine elements such as gears and rolling bearings depend on their wear and fatigue resistance. In order to screen the wear and surface damage, three finishing processes: (i) brushing, (ii) manganese phosphating and (iii) shot peening were applied on three disc pairs and long-term tested on a twin-disc tribometer. In this paper, the elastic contact of the disc surfaces (measured after only few revolutions) was simulated and a number of functional and roughness parameters were correlated. The functional parameters consisted of subsurface stresses at different depths and a new parameter called ‘pressure spikes’ factor’. The new parameter is derived from the pressure distribution and takes into account the proximity and magnitude of the pressure spikes. Strong correlations were found among the pressure spikes’ factor and surface peak/height parameters. The orthogonal shear stresses and Von Mises stresses at the shallowest depths under the surface have shown the highest correlations but no good correlations were found when the statistics of the whole stress fields was analyzed. The use of the new parameter offers a fast way to screen the durability of the contacting surfaces operating at similar conditions.

  9. THE EFFICACY OF ANGLE-MATCHED ISOKINETIC KNEE FLEXOR AND EXTENSOR STRENGTH PARAMETERS IN PREDICTING AGILITY TEST PERFORMANCE.

    Science.gov (United States)

    Greig, Matt; Naylor, James

    2017-10-01

    Agility is a fundamental performance element in many sports, but poses a high risk of injury. Hierarchical modelling has shown that eccentric hamstring strength is the primary determinant of agility performance. The purpose of this study was to investigate the relationship between knee flexor and extensor strength parameters and a battery of agility tests. Controlled laboratory study. Nineteen recreational intermittent games players completed an agility battery and isokinetic testing of the eccentric knee flexors (eccH) and concentric knee extensors (conQ) at 60, 180 and 300°·s -1 . Peak torque and the angle at which peak torque occurred were calculated for eccH and conQ at each speed. Dynamic control ratios (eccH:conQ) and fast:slow ratios (300:60) were calculated using peak torque values, and again using angle-matched data, for eccH and conQ. The agility test battery differentiated linear vs directional changes and prescriptive vs reactive tasks. Linear regression showed that eccH parameters were generally a better predictor of agility performance than conQ parameters. Stepwise regression showed that only angle-matched strength ratios contributed to the prediction of each agility test. Trdaitionally calculated strength ratios using peak torque values failed to predict performance. Angle-matched strength parameters were able to account for 80% of the variation in T-test performance, 70% of deceleration distance, 55% of 10m sprint performance, and 44% of reactive change of direction speed. Traditionally calculated strength ratios failed to predict agility performance, whereas angle-matched strength ratios had better predictive ability and featured in a predictive stepwise model for each agility task. 2c.

  10. Prediction of surface roughness in turning of Ti-6Al-4V using cutting parameters, forces and tool vibration

    Science.gov (United States)

    Sahu, Neelesh Kumar; Andhare, Atul B.; Andhale, Sandip; Raju Abraham, Roja

    2018-04-01

    Present work deals with prediction of surface roughness using cutting parameters along with in-process measured cutting force and tool vibration (acceleration) during turning of Ti-6Al-4V with cubic boron nitride (CBN) inserts. Full factorial design is used for design of experiments using cutting speed, feed rate and depth of cut as design variables. Prediction model for surface roughness is developed using response surface methodology with cutting speed, feed rate, depth of cut, resultant cutting force and acceleration as control variables. Analysis of variance (ANOVA) is performed to find out significant terms in the model. Insignificant terms are removed after performing statistical test using backward elimination approach. Effect of each control variables on surface roughness is also studied. Correlation coefficient (R2 pred) of 99.4% shows that model correctly explains the experiment results and it behaves well even when adjustment is made in factors or new factors are added or eliminated. Validation of model is done with five fresh experiments and measured forces and acceleration values. Average absolute error between RSM model and experimental measured surface roughness is found to be 10.2%. Additionally, an artificial neural network model is also developed for prediction of surface roughness. The prediction results of modified regression model are compared with ANN. It is found that RSM model and ANN (average absolute error 7.5%) are predicting roughness with more than 90% accuracy. From the results obtained it is found that including cutting force and vibration for prediction of surface roughness gives better prediction than considering only cutting parameters. Also, ANN gives better prediction over RSM models.

  11. Predicting deformation and stress as a function of additive manufacturing process parameters for Europa drill

    Data.gov (United States)

    National Aeronautics and Space Administration — We will combine part-level FEM model of residual stresses with phase-field transformation model to predict deformation and cracking due to thermal stresses from the...

  12. Prediction of thermal hydraulic parameters in the loss of coolant accident by using artificial neural networks

    International Nuclear Information System (INIS)

    Vaziri, N.; Erfani, A.; Monsefi, M.; Hajabri, A.

    2008-01-01

    In a reactor accident like loss of coolant accident , one or more signals may not be monitored by control panel for some reasons such as interruptions and so on. Therefore a fast alternative method could guarantee the safe and reliable exploration of nuclear power planets. In this study, we used artificial neural network with Elman recurrent structure to predict six thermal hydraulic signals in a loss of coolant accident after upper plenum break. In the prediction procedure, a few previous samples are fed to the artificial neural network and the output value or next time step is estimated by the network output. The Elman recurrent network is trained with the data obtained from the benchmark simulation of loss of coolant accident in VVER. The results reveal that the predicted values follow the real trends well and artificial neural network can be used as a fast alternative prediction tool in loss of coolant accident

  13. Hydrological model parameter dimensionality is a weak measure of prediction uncertainty (discussion paper)

    NARCIS (Netherlands)

    Pande, S.; Arkesteijn, L.; Savenije, H.H.G.; Bastidas, L.A.

    2015-01-01

    This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is

  14. Identification and prediction of diabetic sensorimotor polyneuropathy using individual and simple combinations of nerve conduction study parameters.

    Directory of Open Access Journals (Sweden)

    Alanna Weisman

    Full Text Available OBJECTIVE: Evaluation of diabetic sensorimotor polyneuropathy (DSP is hindered by the need for complex nerve conduction study (NCS protocols and lack of predictive biomarkers. We aimed to determine the performance of single and simple combinations of NCS parameters for identification and future prediction of DSP. MATERIALS AND METHODS: 406 participants (61 with type 1 diabetes and 345 with type 2 diabetes with a broad spectrum of neuropathy, from none to severe, underwent NCS to determine presence or absence of DSP for cross-sectional (concurrent validity analysis. The 109 participants without baseline DSP were re-evaluated for its future onset (predictive validity. Performance of NCS parameters was compared by area under the receiver operating characteristic curve (AROC. RESULTS: At baseline there were 246 (60% Prevalent Cases. After 3.9 years mean follow-up, 25 (23% of the 109 Prevalent Controls that were followed became Incident DSP Cases. Threshold values for peroneal conduction velocity and sural amplitude potential best identified Prevalent Cases (AROC 0.90 and 0.83, sensitivity 80 and 83%, specificity 89 and 72%, respectively. Baseline tibial F-wave latency, peroneal conduction velocity and the sum of three lower limb nerve conduction velocities (sural, peroneal, and tibial best predicted 4-year incidence (AROC 0.79, 0.79, and 0.85; sensitivity 79, 70, and 81%; specificity 63, 74 and 77%, respectively. DISCUSSION: Individual NCS parameters or their simple combinations are valid measures for identification and future prediction of DSP. Further research into the predictive roles of tibial F-wave latencies, peroneal conduction velocity, and sum of conduction velocities as markers of incipient nerve injury is needed to risk-stratify individuals for clinical and research protocols.

  15. A prediction model for spontaneous regression of cervical intraepithelial neoplasia grade 2, based on simple clinical parameters.

    Science.gov (United States)

    Koeneman, Margot M; van Lint, Freyja H M; van Kuijk, Sander M J; Smits, Luc J M; Kooreman, Loes F S; Kruitwagen, Roy F P M; Kruse, Arnold J

    2017-01-01

    This study aims to develop a prediction model for spontaneous regression of cervical intraepithelial neoplasia grade 2 (CIN 2) lesions based on simple clinicopathological parameters. The study was conducted at Maastricht University Medical Center, the Netherlands. The prediction model was developed in a retrospective cohort of 129 women with a histologic diagnosis of CIN 2 who were managed by watchful waiting for 6 to 24months. Five potential predictors for spontaneous regression were selected based on the literature and expert opinion and were analyzed in a multivariable logistic regression model, followed by backward stepwise deletion based on the Wald test. The prediction model was internally validated by the bootstrapping method. Discriminative capacity and accuracy were tested by assessing the area under the receiver operating characteristic curve (AUC) and a calibration plot. Disease regression within 24months was seen in 91 (71%) of 129 patients. A prediction model was developed including the following variables: smoking, Papanicolaou test outcome before the CIN 2 diagnosis, concomitant CIN 1 diagnosis in the same biopsy, and more than 1 biopsy containing CIN 2. Not smoking, Papanicolaou class predictive of disease regression. The AUC was 69.2% (95% confidence interval, 58.5%-79.9%), indicating a moderate discriminative ability of the model. The calibration plot indicated good calibration of the predicted probabilities. This prediction model for spontaneous regression of CIN 2 may aid physicians in the personalized management of these lesions. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Pharmacokinetic parameters derived from dynamic contrast enhanced MRI of cervical cancers predict chemoradiotherapy outcome

    International Nuclear Information System (INIS)

    Andersen, Erlend K.F.; Hole, Knut Håkon; Lund, Kjersti V.; Sundfør, Kolbein; Kristensen, Gunnar B.; Lyng, Heidi; Malinen, Eirik

    2013-01-01

    Purpose: To assess the prognostic value of pharmacokinetic parameters derived from pre-chemoradiotherapy dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of cervical cancer patients. Materials and methods: Seventy-eight patients with locally advanced cervical cancer underwent DCE-MRI with Gd-DTPA before chemoradiotherapy. The pharmacokinetic Brix and Tofts models were fitted to contrast enhancement curves in all tumor voxels, providing histograms of several pharmacokinetic parameters (Brix: A Brix , k ep , k el , Tofts: K trans , ν e ). A percentile screening approach including log-rank survival tests was undertaken to identify the clinically most relevant part of the intratumoral parameter distribution. Clinical endpoints were progression-free survival (PFS) and locoregional control (LRC). Multivariate analysis including FIGO stage and tumor volume was used to assess the prognostic significance of the imaging parameters. Results: A Brix , k el , and K trans were significantly (P e was significantly positively correlated with PFS only. k ep showed no association with any endpoint. A Brix was positively correlated with K trans and ν e , and showed the strongest association with endpoint in the log-rank testing. k el and K trans were independent prognostic factors in multivariate analysis with LRC as endpoint. Conclusions: Parameters estimated by pharmacokinetic analysis of DCE-MR images obtained prior to chemoradiotherapy may be used for identifying patients at risk of treatment failure

  17. Spatial extrapolation of light use efficiency model parameters to predict gross primary production

    Directory of Open Access Journals (Sweden)

    Karsten Schulz

    2011-12-01

    Full Text Available To capture the spatial and temporal variability of the gross primary production as a key component of the global carbon cycle, the light use efficiency modeling approach in combination with remote sensing data has shown to be well suited. Typically, the model parameters, such as the maximum light use efficiency, are either set to a universal constant or to land class dependent values stored in look-up tables. In this study, we employ the machine learning technique support vector regression to explicitly relate the model parameters of a light use efficiency model calibrated at several FLUXNET sites to site-specific characteristics obtained by meteorological measurements, ecological estimations and remote sensing data. A feature selection algorithm extracts the relevant site characteristics in a cross-validation, and leads to an individual set of characteristic attributes for each parameter. With this set of attributes, the model parameters can be estimated at sites where a parameter calibration is not possible due to the absence of eddy covariance flux measurement data. This will finally allow a spatially continuous model application. The performance of the spatial extrapolation scheme is evaluated with a cross-validation approach, which shows the methodology to be well suited to recapture the variability of gross primary production across the study sites.

  18. Handbook of parameter values for the prediction of radionuclide transfer to wildlife

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2014-06-15

    This handbook provides generic parameter values for estimating the transfer of radionuclides from environmental media to wildlife for the purpose of assessing potential radiation exposure under equilibrium conditions. These data are intended for use where site specific data are either not available or not required, and to parameterize generic assessment models. They are based on a comprehensive review of the available literature, including many Russian language publications that have not previously been available in English. The publication addresses the limitations of the parameter values and the applicability of data. Some general background information on the assessment of potential impacts of radioactive releases on wildlife is also included. It complements the existing handbook in the same IAEA series with parameter to assess the radiological impact to humans.

  19. A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters

    Directory of Open Access Journals (Sweden)

    Mingjie Wang

    2016-01-01

    Full Text Available For the frequency response analysis of acoustic field with random and interval parameters, a nonintrusive uncertain analysis method named Polynomial Chaos Response Surface (PCRS method is proposed. In the proposed method, the polynomial chaos expansion method is employed to deal with the random parameters, and the response surface method is used to handle the interval parameters. The PCRS method does not require efforts to modify model equations due to its nonintrusive characteristic. By means of the PCRS combined with the existing interval analysis method, the lower and upper bounds of expectation, variance, and probability density function of the frequency response can be efficiently evaluated. Two numerical examples are conducted to validate the accuracy and efficiency of the approach. The results show that the PCRS method is more efficient compared to the direct Monte Carlo simulation (MCS method based on the original numerical model without causing significant loss of accuracy.

  20. Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).

    Science.gov (United States)

    Notas, George; Bariotakis, Michail; Kalogrias, Vaios; Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

    2015-01-01

    Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.

  1. Handbook of parameter values for the prediction of radionuclide transfer in temperate environments

    International Nuclear Information System (INIS)

    1994-01-01

    This Handbook has been prepared in response to a widely expressed interest in having a convenient and authoritative reference for radionuclide transfer parameter values used in biospheric assessment models. It draws on data from North America and Europe, much of which was collected through projects of the International Union of Radioecologists (IUR) and the Commission of European Communities (CEC) over the last decade. It is intended to supplement existing IAEA publications on environmental assessment methodology, primarily Generic Models and Parameters for Assessing the Environmental Transfer of Radionuclides from Routine Releases, IAEA Safety Series No. 57 (1982). 219 refs, 3 figs, 32 tabs

  2. A proposal of parameter determination method in the residual strength degradation model for the prediction of fatigue life (I)

    International Nuclear Information System (INIS)

    Kim, Sang Tae; Jang, Seong Soo

    2001-01-01

    The static and fatigue tests have been carried out to verify the validity of a generalized residual strength degradation model. And a new method of parameter determination in the model is verified experimentally to account for the effect of tension-compression fatigue loading of spheroidal graphite cast iron. It is shown that the correlation between the experimental results and the theoretical prediction on the statistical distribution of fatigue life by using the proposed method is very reasonable. Furthermore, it is found that the correlation between the theoretical prediction and the experimental results of fatigue life in case of tension-tension fatigue data in composite material appears to be reasonable. Therefore, the proposed method is more adjustable in the determination of the parameter than maximum likelihood method and minimization technique

  3. A two-parameter model to predict fracture in the transition

    International Nuclear Information System (INIS)

    DeAquino, C.T.; Landes, J.D.; McCabe, D.E.

    1995-01-01

    A model is proposed that uses a numerical characterization of the crack tip stress field modified by the J - Q constraint theory and a weak link assumption to predict fracture behavior in the transition for reactor vessel steels. This model predicts the toughness scatter band for a component model from a toughness scatter band measured on a test specimen geometry. The model has been applied previously to two-dimensional through cracks. Many applications to actual components structures involve three-dimensional surface flaws. These cases require a more difficult level of analysis and need additional information. In this paper, both the current model for two-dimensional cracks and an approach needed to extend the model for the prediction of transition fracture behavior in three-dimensional surface flaws are discussed. Examples are presented to show how the model can be applied and in some cases to compare with other test results. (author). 13 refs., 7 figs

  4. Developing a computational tool for predicting physical parameters of a typical VVER-1000 core based on artificial neural network

    International Nuclear Information System (INIS)

    Mirvakili, S.M.; Faghihi, F.; Khalafi, H.

    2012-01-01

    Highlights: ► Thermal–hydraulics parameters of a VVER-1000 core based on neural network (ANN), are carried out. ► Required data for ANN training are found based on modified COBRA-EN code and then linked each other using MATLAB software. ► Based on ANN method, average and maximum temperature of fuel and clad as well as MDNBR of each FA are predicted. -- Abstract: The main goal of the present article is to design a computational tool to predict physical parameters of the VVER-1000 nuclear reactor core based on artificial neural network (ANN), taking into account a detailed physical model of the fuel rods and coolant channels in a fuel assembly. Predictions of thermal characteristics of fuel, clad and coolant are performed using cascade feed forward ANN based on linear fission power distribution and power peaking factors of FAs and hot channels factors (which are found based on our previous neutronic calculations). A software package has been developed to prepare the required data for ANN training which applies a modified COBRA-EN code for sub-channel analysis and links the codes using the MATLAB software. Based on the current estimation system, five main core TH parameters are predicted, which include the average and maximum temperatures of fuel and clad as well as the minimum departure from nucleate boiling ratio (MDNBR) for each FA. To get the best conditions for the considered ANNs training, a comprehensive sensitivity study has been performed to examine the effects of variation of hidden neurons, hidden layers, transfer functions, and the learning algorithms on the training and simulation results. Performance evaluation results show that the developed ANN can be trained to estimate the core TH parameters of a typical VVER-1000 reactor quickly without loss of accuracy.

  5. Soluble form of membrane attack complex independently predicts mortality and cardiovascular events in patients with ST-elevation myocardial infarction treated with primary percutaneous coronary intervention

    DEFF Research Database (Denmark)

    Lindberg, Søren; Pedersen, Sune H; Mogelvang, Rasmus

    2012-01-01

    The complement system is an important mediator of inflammation, which plays a pivotal role in atherosclerosis and acute myocardial infarction (AMI). Animal studies suggest that activation of the complement cascade resulting in the formation of soluble membrane attack complex (sMAC), contributes...

  6. The serum level of soluble urokinase receptor is elevated in tuberculosis patients and predicts mortality during treatment: a community study from Guinea-Bissau

    DEFF Research Database (Denmark)

    Eugen-Olsen, Jesper; Gustafson, P; Sidenius, N

    2002-01-01

    OBJECTIVE: To investigate whether the serum level of soluble urokinase plasminogen activator receptor (suPAR) carries prognostic information in individuals infected with Mycobacterium tuberculosis. DESIGN: suPAR was measured by ELISA in 262 individuals at the time of enrolment into a cohort based...

  7. Online peak power prediction based on a parameter and state estimator for lithium-ion batteries in electric vehicles

    International Nuclear Information System (INIS)

    Pei, Lei; Zhu, Chunbo; Wang, Tiansi; Lu, Rengui; Chan, C.C.

    2014-01-01

    The goal of this study is to realize real-time predictions of the peak power/state of power (SOP) for lithium-ion batteries in electric vehicles (EVs). To allow the proposed method to be applicable to different temperature and aging conditions, a training-free battery parameter/state estimator is presented based on an equivalent circuit model using a dual extended Kalman filter (DEKF). In this estimator, the model parameters are no longer taken as functions of factors such as SOC (state of charge), temperature, and aging; instead, all parameters will be directly estimated under the present conditions, and the impact of the temperature and aging on the battery model will be included in the parameter identification results. Then, the peak power/SOP will be calculated using the estimated results under the given limits. As an improvement to the calculation method, a combined limit of current and voltage is proposed to obtain results that are more reasonable. Additionally, novel verification experiments are designed to provide the true values of the cells' peak power under various operating conditions. The proposed methods are implemented in experiments with LiFePO 4 /graphite cells. The validating results demonstrate that the proposed methods have good accuracy and high adaptability. - Highlights: • A real-time peak power/SOP prediction method for lithium-ion batteries is proposed. • A training-free method based on DEKF is presented for parameter identification. • The proposed method can be applied to different temperature and aging conditions. • The calculation of peak power under the current and voltage limits is improved. • Validation experiments are designed to verify the accuracy of prediction results

  8. Analysis and prediction of the alpha-function parameters used in cubic equations of state

    DEFF Research Database (Denmark)

    Privata, Romain; Viscontea, Maxime; Zazoua-Khames, Anis

    2015-01-01

    and compared regarding their ability to reproduce vapor pressure, heat of vaporization, liquid heat capacity, liquid density and second virial coefficient data. To reach this objective, extensive databanks of alpha function parameters were created. In particular, pitfalls of Twu-type alpha functions were...

  9. Using machine learning to predict soil bulk density on the basis of visual parameters

    NARCIS (Netherlands)

    Bondi, Giulia; Creamer, Rachel; Ferrari, Alessio; Fenton, Owen; Wall, David

    2018-01-01

    Soil structure is a key factor that supports all soil functions. Extracting intact soil cores and horizon specific samples for determination of soil physical parameters (e.g. bulk density (Bd) or particle size distribution) is a common practice for assessing indicators of soil structure. However,

  10. House thermal model parameter estimation method for Model Predictive Control applications

    NARCIS (Netherlands)

    van Leeuwen, Richard Pieter; de Wit, J.B.; Fink, J.; Smit, Gerardus Johannes Maria

    In this paper we investigate thermal network models with different model orders applied to various Dutch low-energy house types with high and low interior thermal mass and containing floor heating. Parameter estimations are performed by using data from TRNSYS simulations. The paper discusses results

  11. Analyzing the effects of geological and parameter uncertainty on prediction of groundwater head and travel time

    DEFF Research Database (Denmark)

    He, X.; Sonneborg, T.O.; Jørgensen, F.

    2013-01-01

    in three scenarios involving simulation of groundwater head distribution and travel time. The first scenario implied 100 stochastic geological models all assigning the same hydraulic parameters for the same geological units. In the second scenario the same 100 geological models were subjected to model...

  12. Semen molecular and cellular features: these parameters can reliably predict subsequent ART outcome in a goat model

    Directory of Open Access Journals (Sweden)

    Mereu Paolo

    2009-11-01

    Full Text Available Abstract Currently, the assessment of sperm function in a raw or processed semen sample is not able to reliably predict sperm ability to withstand freezing and thawing procedures and in vivo fertility and/or assisted reproductive biotechnologies (ART outcome. The aim of the present study was to investigate which parameters among a battery of analyses could predict subsequent spermatozoa in vitro fertilization ability and hence blastocyst output in a goat model. Ejaculates were obtained by artificial vagina from 3 adult goats (Capra hircus aged 2 years (A, B and C. In order to assess the predictive value of viability, computer assisted sperm analyzer (CASA motility parameters and ATP intracellular concentration before and after thawing and of DNA integrity after thawing on subsequent embryo output after an in vitro fertility test, a logistic regression analysis was used. Individual differences in semen parameters were evident for semen viability after thawing and DNA integrity. Results of IVF test showed that spermatozoa collected from A and B lead to higher cleavage rates (0

  13. Predicting pneumococcal community-acquired pneumonia in the emergency department: evaluation of clinical parameters.

    Science.gov (United States)

    Huijts, S M; Boersma, W G; Grobbee, D E; Gruber, W C; Jansen, K U; Kluytmans, J A J W; Kuipers, B A F; Palmen, F; Pride, M W; Webber, C; Bonten, M J M

    2014-12-01

    The aim of this study was to quantify the value of clinical predictors available in the emergency department (ED) in predicting Streptococcus pneumoniae as the cause of community-acquired pneumonia (CAP). A prospective, observational, cohort study of patients with CAP presenting in the ED was performed. Pneumococcal aetiology of CAP was based on either bacteraemia, or S. pneumoniae being cultured from sputum, or urinary immunochromatographic assay positivity, or positivity of a novel serotype-specific urinary antigen detection test. Multivariate logistic regression was used to identify independent predictors and various cut-off values of probability scores were used to evaluate the usefulness of the model. Three hundred and twenty-eight (31.0%) of 1057 patients with CAP had pneumococcal CAP. Nine independent predictors for pneumococcal pneumonia were identified, but the clinical utility of this prediction model was disappointing, because of low positive predictive values or a small yield. Clinical criteria have insufficient diagnostic capacity to predict pneumococcal CAP. Rapid antigen detection tests are needed to diagnose S. pneumoniae at the time of hospital admission. © 2014 The Authors Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.

  14. Crack under biaxial loading: Two-parameter description and prediction of crack growth direction

    Czech Academy of Sciences Publication Activity Database

    Seitl, Stanislav

    2014-01-01

    Roč. 31, APR (2014), s. 44-49 ISSN 0213-3725 R&D Projects: GA MŠk(CZ) 7AMB14AT012 Institutional support: RVO:68081723 Keywords : Concrete * T-stress * cracks growth prediction * numerical calculation * biaxial loading Subject RIV: JL - Materials Fatigue, Friction Mechanics

  15. Prediction of the saturated hydraulic conductivity from Brooks and Corey’s water retention parameters

    NARCIS (Netherlands)

    Nasta, P.; Vrugt, J.A.; Romano, N.

    2013-01-01

    Prediction of flow through variably saturated porous media requires accurate knowledge of the soil hydraulic properties, namely the water retention function (WRF) and the hydraulic conductivity function (HCF). Unfortunately, direct measurement of the HCF is time consuming and expensive. In this

  16. Validation of Occupants’ Behaviour Models for Indoor Quality Parameter and Energy Consumption Prediction

    DEFF Research Database (Denmark)

    Fabi, Valentina; Sugliano, Martina; Andersen, Rune Korsholm

    2015-01-01

    Occupants’ behaviour related to building control system plays a significant role to achieve thermal comfort and air quality in naturally-ventilated buildings. Generally, the published models of occupant's behavior are not validated, meaning that the predictive power has not yet been tested. For t...

  17. Influence of precision of emission characteristic parameters on model prediction error of VOCs/formaldehyde from dry building material.

    Directory of Open Access Journals (Sweden)

    Wenjuan Wei

    Full Text Available Mass transfer models are useful in predicting the emissions of volatile organic compounds (VOCs and formaldehyde from building materials in indoor environments. They are also useful for human exposure evaluation and in sustainable building design. The measurement errors in the emission characteristic parameters in these mass transfer models, i.e., the initial emittable concentration (C 0, the diffusion coefficient (D, and the partition coefficient (K, can result in errors in predicting indoor VOC and formaldehyde concentrations. These errors have not yet been quantitatively well analyzed in the literature. This paper addresses this by using modelling to assess these errors for some typical building conditions. The error in C 0, as measured in environmental chambers and applied to a reference living room in Beijing, has the largest influence on the model prediction error in indoor VOC and formaldehyde concentration, while the error in K has the least effect. A correlation between the errors in D, K, and C 0 and the error in the indoor VOC and formaldehyde concentration prediction is then derived for engineering applications. In addition, the influence of temperature on the model prediction of emissions is investigated. It shows the impact of temperature fluctuations on the prediction errors in indoor VOC and formaldehyde concentrations to be less than 7% at 23±0.5°C and less than 30% at 23±2°C.

  18. A Design of Experiment approach to predict product and process parameters for a spray dried influenza vaccine.

    Science.gov (United States)

    Kanojia, Gaurav; Willems, Geert-Jan; Frijlink, Henderik W; Kersten, Gideon F A; Soema, Peter C; Amorij, Jean-Pierre

    2016-09-25

    Spray dried vaccine formulations might be an alternative to traditional lyophilized vaccines. Compared to lyophilization, spray drying is a fast and cheap process extensively used for drying biologicals. The current study provides an approach that utilizes Design of Experiments for spray drying process to stabilize whole inactivated influenza virus (WIV) vaccine. The approach included systematically screening and optimizing the spray drying process variables, determining the desired process parameters and predicting product quality parameters. The process parameters inlet air temperature, nozzle gas flow rate and feed flow rate and their effect on WIV vaccine powder characteristics such as particle size, residual moisture content (RMC) and powder yield were investigated. Vaccine powders with a broad range of physical characteristics (RMC 1.2-4.9%, particle size 2.4-8.5μm and powder yield 42-82%) were obtained. WIV showed no significant loss in antigenicity as revealed by hemagglutination test. Furthermore, descriptive models generated by DoE software could be used to determine and select (set) spray drying process parameter. This was used to generate a dried WIV powder with predefined (predicted) characteristics. Moreover, the spray dried vaccine powders retained their antigenic stability even after storage for 3 months at 60°C. The approach used here enabled the generation of a thermostable, antigenic WIV vaccine powder with desired physical characteristics that could be potentially used for pulmonary administration. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  19. Application of Time-series Model to Predict Groundwater Quality Parameters for Agriculture: (Plain Mehran Case Study)

    Science.gov (United States)

    Mehrdad Mirsanjari, Mir; Mohammadyari, Fatemeh

    2018-03-01

    Underground water is regarded as considerable water source which is mainly available in arid and semi arid with deficient surface water source. Forecasting of hydrological variables are suitable tools in water resources management. On the other hand, time series concepts is considered efficient means in forecasting process of water management. In this study the data including qualitative parameters (electrical conductivity and sodium adsorption ratio) of 17 underground water wells in Mehran Plain has been used to model the trend of parameters change over time. Using determined model, the qualitative parameters of groundwater is predicted for the next seven years. Data from 2003 to 2016 has been collected and were fitted by AR, MA, ARMA, ARIMA and SARIMA models. Afterward, the best model is determined using information criterion or Akaike (AIC) and correlation coefficient. After modeling parameters, the map of agricultural land use in 2016 and 2023 were generated and the changes between these years were studied. Based on the results, the average of predicted SAR (Sodium Adsorption Rate) in all wells in the year 2023 will increase compared to 2016. EC (Electrical Conductivity) average in the ninth and fifteenth holes and decreases in other wells will be increased. The results indicate that the quality of groundwater for Agriculture Plain Mehran will decline in seven years.

  20. Effect of Imaging Parameter Thresholds on MRI Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes.

    Directory of Open Access Journals (Sweden)

    Wei-Ching Lo

    Full Text Available The purpose of this study is to evaluate the predictive performance of magnetic resonance imaging (MRI markers in breast cancer patients by subtype. Sixty-four patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy were enrolled in this study. Each patient received a dynamic contrast-enhanced (DCE-MRI at baseline, after 1 cycle of chemotherapy and before surgery. Functional tumor volume (FTV, the imaging marker measured by DCE-MRI, was computed at various thresholds of percent enhancement (PEt and signal-enhancement ratio (SERt. Final FTV before surgery and percent changes of FTVs at the early and final treatment time points were used to predict patients' recurrence-free survival. The full cohort and each subtype defined by the status of hormone receptor and human epidermal growth factor receptor 2 (HR+/HER2-, HER2+, triple negative were analyzed. Predictions were evaluated using the Cox proportional hazard model when PEt changed from 30% to 200% in steps of 10% and SERt changed from 0 to 2 in steps of 0.2. Predictions with high hazard ratios and low p-values were considered as strong. Different profiles of FTV as predictors for recurrence-free survival were observed in each breast cancer subtype and strong associations with survival were observed at different PEt/SERt combinations that resulted in different FTVs. Findings from this retrospective study suggest that the predictive performance of imaging markers based on FTV may be improved with enhancement thresholds being optimized separately for clinically-relevant subtypes defined by HR and HER2 receptor expression.

  1. Analysis of americium, plutonium and technetium solubility in groundwater

    International Nuclear Information System (INIS)

    Takeda, Seiji

    1999-08-01

    Safety assessments for geologic disposal of radioactive waste generally use solubilities of radioactive elements as the parameter restricting the dissolution of the elements from a waste matrix. This study evaluated americium, plutonium and technetium solubilities under a variety of geochemical conditions using the geochemical model EQ3/6. Thermodynamic data of elements used in the analysis were provided in the JAERI-data base. Chemical properties of both natural groundwater and interstitial water in buffer materials (bentonite and concrete) were investigated to determine the variations in Eh, pH and ligand concentrations (CO 3 2- , F - , PO 4 3- , SO 4 2- , NO 3 - and NH 4 + ). These properties can play an important role in the complexation of radioactive elements. Effect of the groundwater chemical properties on the solubility and formation of chemical species for americium, plutonium and technetium was predicted based on the solubility analyses under a variety of geochemical conditions. The solubility and speciation of the radioactive elements were estimated, taking into account the possible range of chemical compositions determined from the groundwater investigation. (author)

  2. Generation and mid-IR measurement of a gas-phase to predict security parameters of aviation jet fuel.

    Science.gov (United States)

    Gómez-Carracedo, M P; Andrade, J M; Calviño, M A; Prada, D; Fernández, E; Muniategui, S

    2003-07-27

    The worldwide use of kerosene as aviation jet fuel makes its safety considerations of most importance not only for aircraft security but for the workers' health (chronic and/or acute exposure). As most kerosene risks come from its vapours, this work focuses on predicting seven characteristics (flash point, freezing point, % of aromatics and four distillation points) which assess its potential hazards. Two experimental devices were implemented in order to, first, generate a kerosene vapour phase and, then, to measure its mid-IR spectrum. All the working conditions required to generate the gas phase were optimised either in a univariate or a multivariate (SIMPLEX) approach. Next, multivariate prediction models were deployed using partial least squares regression and it was found that both the average prediction errors and precision parameters were satisfactory, almost always well below the reference figures.

  3. Prediction of geomagnetic storm using neural networks: Comparison of the efficiency of the Satellite and ground-based input parameters

    International Nuclear Information System (INIS)

    Stepanova, Marina; Antonova, Elizavieta; Munos-Uribe, F A; Gordo, S L Gomez; Torres-Sanchez, M V

    2008-01-01

    Different kinds of neural networks have established themselves as an effective tool in the prediction of different geomagnetic indices, including the Dst being the most important constituent for determination of the impact of Space Weather on the human life. Feed-forward networks with one hidden layer are used to forecast the Dst variation, using separately the solar wind paramenters, polar cap index, and auroral electrojet index as input parameters. It was found that in all three cases the storm-time intervals were predicted much more precisely as quite time intervals. The majority of cross-correlation coefficients between predicted and observed Dst of strong geomagnetic storms are situated between 0.8 and 0.9. Changes in the neural network architecture, including the number of nodes in the input and hidden layers and the transfer functions between them lead to an improvement of a network performance up to 10%.

  4. Hydrogen solubility in austenite of Fe-Ni-Cr alloys

    International Nuclear Information System (INIS)

    Zhirnova, V.V.; Mogutnov, B.M.; Tomilin, I.A.

    1981-01-01

    Hydrogen solubility in Fe-Ni-Cr alloys at 600-1000 deg C is determined. Hydrogen solubility in ternary alloys can not be predicted on the basis of the data on its solubility in binary Fe-Ni, Fe-Cr alloys. Chromium and nickel effect on hydrogen solubility in iron is insignificant in comparison with the effect of these elements on carbon or nitrogen solubility [ru

  5. Clinical validation of the LKB model and parameter sets for predicting radiation-induced pneumonitis from breast cancer radiotherapy

    International Nuclear Information System (INIS)

    Tsougos, Ioannis; Mavroidis, Panayiotis; Theodorou, Kyriaki; Rajala, J; Pitkaenen, M A; Holli, K; Ojala, A T; Hyoedynmaa, S; Jaervenpaeae, Ritva; Lind, Bengt K; Kappas, Constantin

    2006-01-01

    The choice of the appropriate model and parameter set in determining the relation between the incidence of radiation pneumonitis and dose distribution in the lung is of great importance, especially in the case of breast radiotherapy where the observed incidence is fairly low. From our previous study based on 150 breast cancer patients, where the fits of dose-volume models to clinical data were estimated (Tsougos et al 2005 Evaluation of dose-response models and parameters predicting radiation induced pneumonitis using clinical data from breast cancer radiotherapy Phys. Med. Biol. 50 3535-54), one could get the impression that the relative seriality is significantly better than the LKB NTCP model. However, the estimation of the different NTCP models was based on their goodness-of-fit on clinical data, using various sets of published parameters from other groups, and this fact may provisionally justify the results. Hence, we sought to investigate further the LKB model, by applying different published parameter sets for the very same group of patients, in order to be able to compare the results. It was shown that, depending on the parameter set applied, the LKB model is able to predict the incidence of radiation pneumonitis with acceptable accuracy, especially when implemented on a sub-group of patients (120) receiving D-bar-bar vertical bar EUD higher than 8 Gy. In conclusion, the goodness-of-fit of a certain radiobiological model on a given clinical case is closely related to the selection of the proper scoring criteria and parameter set as well as to the compatibility of the clinical case from which the data were derived. (letter to the editor)

  6. Better estimation of protein-DNA interaction parameters improve prediction of functional sites

    Directory of Open Access Journals (Sweden)

    O'Flanagan Ruadhan A

    2008-12-01

    Full Text Available Abstract Background Characterizing transcription factor binding motifs is a common bioinformatics task. For transcription factors with variable binding sites, we need to get many suboptimal binding sites in our training dataset to get accurate estimates of free energy penalties for deviating from the consensus DNA sequence. One procedure to do that involves a modified SELEX (Systematic Evolution of Ligands by Exponential Enrichment method designed to produce many such sequences. Results We analyzed low stringency SELEX data for E. coli Catabolic Activator Protein (CAP, and we show here that appropriate quantitative analysis improves our ability to predict in vitro affinity. To obtain large number of sequences required for this analysis we used a SELEX SAGE protocol developed by Roulet et al. The sequences obtained from here were subjected to bioinformatic analysis. The resulting bioinformatic model characterizes the sequence specificity of the protein more accurately than those sequence specificities predicted from previous analysis just by using a few known binding sites available in the literature. The consequences of this increase in accuracy for prediction of in vivo binding sites (and especially functional ones in the E. coli genome are also discussed. We measured the dissociation constants of several putative CAP binding sites by EMSA (Electrophoretic Mobility Shift Assay and compared the affinities to the bioinformatics scores provided by methods like the weight matrix method and QPMEME (Quadratic Programming Method of Energy Matrix Estimation trained on known binding sites as well as on the new sites from SELEX SAGE data. We also checked predicted genome sites for conservation in the related species S. typhimurium. We found that bioinformatics scores based on SELEX SAGE data does better in terms of prediction of physical binding energies as well as in detecting functional sites. Conclusion We think that training binding site detection

  7. Soil parameters are key factors to predict metal bioavailability to snails based on chemical extractant data

    International Nuclear Information System (INIS)

    Pauget, B.; Gimbert, F.; Scheifler, R.; Coeurdassier, M.; Vaufleury, A. de

    2012-01-01

    Although soil characteristics modulate metal mobility and bioavailability to organisms, they are often ignored in the risk assessment of metal transfer. This paper aims to determine the ability of chemical methods to assess and predict cadmium (Cd), lead (Pb) and zinc (Zn) environmental bioavailability to the land snail Cantareus aspersus. Snails were exposed in the laboratory for 28 days to 17 soils from around a former smelter. The soils were selected for their range of pH, organic matter, clay content, and Cd, Pb and Zn concentrations. The influence of soil properties on environmental availability (estimated using HF-HClO 4 , EDTA, CaCl 2 , NH 4 NO 3 , NaNO 3 , free ion activity and total dissolved metal concentration in soil solution) and on environmental bioavailability (modelled using accumulation kinetics) was identified. Among the seven chemical methods, only the EDTA and the total soil concentration can be used to assess Cd and Pb environmental bioavailability to snails (r² adj = 0.67 and 0.77, respectively). For Zn, none of the chemical methods were suitable. Taking into account the influence of the soil characteristics (pH and CEC) allows a better prediction of Cd and Pb environmental bioavailability (r² adj = 0.82 and 0.83, respectively). Even though alone none of the chemical methods tested could assess Zn environmental bioavailability to snails, the addition of pH, iron and aluminium oxides allowed the variation of assimilation fluxes to be predicted. A conceptual and practical method to use soil characteristics for risk assessment is proposed based on these results. We conclude that as yet there is no universal chemical method to predict metal environmental bioavailability to snails, and that the soil factors having the greatest impact depend on the metal considered. - Highlights: ► New approach to identify chemical methods able to predict metal bioavailability to snails. ► Bioavailability of cadmium, lead and zinc to snails was determined by

  8. Soil parameters are key factors to predict metal bioavailability to snails based on chemical extractant data

    Energy Technology Data Exchange (ETDEWEB)

    Pauget, B.; Gimbert, F., E-mail: frederic.gimbert@univ-fcomte.fr; Scheifler, R.; Coeurdassier, M.; Vaufleury, A. de

    2012-08-01

    Although soil characteristics modulate metal mobility and bioavailability to organisms, they are often ignored in the risk assessment of metal transfer. This paper aims to determine the ability of chemical methods to assess and predict cadmium (Cd), lead (Pb) and zinc (Zn) environmental bioavailability to the land snail Cantareus aspersus. Snails were exposed in the laboratory for 28 days to 17 soils from around a former smelter. The soils were selected for their range of pH, organic matter, clay content, and Cd, Pb and Zn concentrations. The influence of soil properties on environmental availability (estimated using HF-HClO{sub 4}, EDTA, CaCl{sub 2}, NH{sub 4}NO{sub 3}, NaNO{sub 3}, free ion activity and total dissolved metal concentration in soil solution) and on environmental bioavailability (modelled using accumulation kinetics) was identified. Among the seven chemical methods, only the EDTA and the total soil concentration can be used to assess Cd and Pb environmental bioavailability to snails (r Superscript-Two {sub adj} = 0.67 and 0.77, respectively). For Zn, none of the chemical methods were suitable. Taking into account the influence of the soil characteristics (pH and CEC) allows a better prediction of Cd and Pb environmental bioavailability (r Superscript-Two {sub adj} = 0.82 and 0.83, respectively). Even though alone none of the chemical methods tested could assess Zn environmental bioavailability to snails, the addition of pH, iron and aluminium oxides allowed the variation of assimilation fluxes to be predicted. A conceptual and practical method to use soil characteristics for risk assessment is proposed based on these results. We conclude that as yet there is no universal chemical method to predict metal environmental bioavailability to snails, and that the soil factors having the greatest impact depend on the metal considered. - Highlights: Black-Right-Pointing-Pointer New approach to identify chemical methods able to predict metal bioavailability

  9. Estimation of aqueous solubility of TODGA using group contribution method

    International Nuclear Information System (INIS)

    Balasubramonian, S.; Kumar, Shekhar; Sampath, M.; Sivakumar, D.; Kamachi Mudali, U.

    2017-01-01

    The aqueous solubility of N, N, N', N'-tetraoctyl-3-oxapentanediamide normally referred as TODGA is experimentally measured. The aqueous solubility was also predicted using Marrero and Gani group contribution method. The modification of original Marrero and Gani method was proposed to accurately predict TODGA solubility. The predicted solubility of TODGA using original Marrero and Gani method, Modified Marrero and Gani method and UNIFAC Model was compared. The predicted solubility of TODGA using modified Marrero and Gani method is 0.0237 g/l against the experimentally measured value of 0.0226 g/l. (author)

  10. Prediction of the Dynamic Yield Strength of Metals Using Two Structural-Temporal Parameters

    Science.gov (United States)

    Selyutina, N. S.; Petrov, Yu. V.

    2018-02-01

    The behavior of the yield strength of steel and a number of aluminum alloys is investigated in a wide range of strain rates, based on the incubation time criterion of yield and the empirical models of Johnson-Cook and Cowper-Symonds. In this paper, expressions for the parameters of the empirical models are derived through the characteristics of the incubation time criterion; a satisfactory agreement of these data and experimental results is obtained. The parameters of the empirical models can depend on some strain rate. The independence of the characteristics of the incubation time criterion of yield from the loading history and their connection with the structural and temporal features of the plastic deformation process give advantage of the approach based on the concept of incubation time with respect to empirical models and an effective and convenient equation for determining the yield strength in a wider range of strain rates.

  11. Prediction of the Voltage Quality in an Overhead Transmission Line with Distributed Parameters

    OpenAIRE

    Bulyga Leonid L.; Tarasov Evgeniy V.; Ushakov Vasily Ya.; Kharlov Nikolay N.

    2015-01-01

    The present work is devoted to investigation of an electrical transmission line with allowance for distributed parameters. From the results of voltage measurements at terminals of an actual transmission line, effective values of the voltage are calculated for every line section. Special attention is given to higher harmonics and asymmetry. Spectral composition of the voltage is presented and changes in values of harmonic components are analyzed. The effect of higher harmonics on the equipment...

  12. Prediction of the Voltage Quality in an Overhead Transmission Line with Distributed Parameters

    Directory of Open Access Journals (Sweden)

    Bulyga Leonid L.

    2015-01-01

    Full Text Available The present work is devoted to investigation of an electrical transmission line with allowance for distributed parameters. From the results of voltage measurements at terminals of an actual transmission line, effective values of the voltage are calculated for every line section. Special attention is given to higher harmonics and asymmetry. Spectral composition of the voltage is presented and changes in values of harmonic components are analyzed. The effect of higher harmonics on the equipment operation is analyzed.

  13. Interrelated Dimensional Chains in Predicting Accuracy of Turbine Wheel Assembly Parameters

    Science.gov (United States)

    Yanyukina, M. V.; Bolotov, M. A.; Ruzanov, N. V.

    2018-03-01

    The working capacity of any device primarily depends on the assembly accuracy which, in its turn, is determined by the quality of each part manufactured, i.e., the degree of conformity between final geometrical parameters and the set ones. However, the assembly accuracy depends not only on a qualitative manufacturing process but also on the assembly process correctness. In this connection, there were preliminary calculations of assembly stages in terms of conformity to real geometrical parameters with their permissible values. This task is performed by means of the calculation of dimensional chains. The calculation of interrelated dimensional chains in the aircraft industry requires particular attention. The article considers the issues of dimensional chain calculation modelling by the example of the turbine wheel assembly process. The authors described the solution algorithm in terms of mathematical statistics implemented in Matlab. The paper demonstrated the results of a dimensional chain calculation for a turbine wheel in relation to the draw of turbine blades to the shroud ring diameter. Besides, the article provides the information on the influence of a geometrical parameter tolerance for the dimensional chain link elements on a closing one.

  14. Parameter estimations in predictive microbiology: Statistically sound modelling of the microbial growth rate.

    Science.gov (United States)

    Akkermans, Simen; Logist, Filip; Van Impe, Jan F

    2018-04-01

    When building models to describe the effect of environmental conditions on the microbial growth rate, parameter estimations can be performed either with a one-step method, i.e., directly on the cell density measurements, or in a two-step method, i.e., via the estimated growth rates. The two-step method is often preferred due to its simplicity. The current research demonstrates that the two-step method is, however, only valid if the correct data transformation is applied and a strict experimental protocol is followed for all experiments. Based on a simulation study and a mathematical derivation, it was demonstrated that the logarithm of the growth rate should be used as a variance stabilizing transformation. Moreover, the one-step method leads to a more accurate estimation of the model parameters and a better approximation of the confidence intervals on the estimated parameters. Therefore, the one-step method is preferred and the two-step method should be avoided. Copyright © 2017. Published by Elsevier Ltd.

  15. Critical reappraisal of embryo quality as a predictive parameter for pregnancy outcome: a pilot study.

    Science.gov (United States)

    Campo, R; Binda, M M; Van Kerkhoven, G; Frederickx, V; Serneels, A; Roziers, P; Lopes, A S; Gordts, S; Puttemans, P; Gordts, S

    2010-01-01

    Pilot study to analyse the efficacy and embryo morphology using a new human embryo culture medium (GM501) versus the conventional used medium (ISM1). Over a four-month period, all patients at the Leuven Institute of Fertility and Embryology (LIFE) were -randomly allocated to have their embryos cultured in either the standard sequential culture medium ISM1 (control) or in a new universal medium (GM501) (study group). Primary outcome parameters were clinical pregnancy and live birth rate. The secondary outcome parameter was the correlation of embryo fragmentation rate with pregnancy outcome. We did not observe any differences between the ISM1 control group and GM501 study group with regard to fertilization, pregnancy, implantation rates, ongoing pregnancy, and babies born. The number of embryos with a minimal fragmentation rate (less than 30%) was significantly higher in the GM501 study group. Although a significant higher embryo fragmentation rate was seen in In vitro culture of embryos in GM501, pregnancy outcome results were comparable to those of embryos cultured in ISM1. According to our results the value of embryo morphological criteria as a parameter for pregnancy outcome should be examined and discussed again.

  16. Can cell kinetic parameters predict the response of tumours to radiotherapy?

    Science.gov (United States)

    McNally, N J

    1989-11-01

    Three potential predictive assays of the repopulation component in tumour response to therapy are considered. (1) The DNA index can easily be measured. It is of prognostic value for cancers of certain sites, aneuploidy being a bad prognostic indicator. It is not strictly an indicator of cell proliferation. (2) The in vitro labelling index is of predictive value in early stage operable breast cancer and in head and neck cancer. In the former a high pretreatment labelling index can identify patients who could benefit from adjuvant chemotherapy. (3) The tumour potential doubling time (Tpot) can be measured rapidly following in vivo labelling with bromodeoxyuridine or iododeoxyuridine. We have measured Tpot in over 100 solid tumours with a success rate of about 75 per cent. Nearly 50 per cent of the tumours have a pre-treatment potential doubling time of 5 days or less. These would be suitable candidates for accelerated fractionation.

  17. Can cell kinetic parameters predict the response of tumours to radiotherapy?

    International Nuclear Information System (INIS)

    McNally, N.J.

    1989-01-01

    Three potential predictive assays of the repopulation component in tumour response to therapy are considered. (1) The DNA index can easily be measured. It is of prognostic value for cancers of certain sites, aneuploidy being a bad prognostic indicator. It is not strictly an indicator of cell proliferation. (2) The in vitro labelling index is of predictive value in early stage operable breast cancer and in head and neck cancer. In the former a high pretreatment labelling index can identify patients who could benefit from adjuvant chemotherapy. (3) The tumour potential doubling time can be measured rapidly following in vivo labelling with bromodeoxyuridine or iododeoxyuridine. The authors measured T pot in over 100 solid tumours with a success rate of about 75%. Nearly 50% of the tumours have a pre-treatment potential doubling time of 5 days or less. These would be suitable candidates for accelerated fractionation. (author)

  18. Parameter importance and uncertainty in predicting runoff pesticide reduction with filter strips.

    Science.gov (United States)

    Muñoz-Carpena, Rafael; Fox, Garey A; Sabbagh, George J

    2010-01-01

    Vegetative filter strips (VFS) are an environmental management tool used to reduce sediment and pesticide transport from surface runoff. Numerical models of VFS such as the Vegetative Filter Strip Modeling System (VFSMOD-W) are capable of predicting runoff, sediment, and pesticide reduction and can be useful tools to understand the effectiveness of VFS and environmental conditions under which they may be ineffective. However, as part of the modeling process, it is critical to identify input factor importance and quantify uncertainty in predicted runoff, sediment, and pesticide reductions. This research used state-of-the-art global sensitivity and uncertainty analysis tools, a screening method (Morris) and a variance-based method (extended Fourier Analysis Sensitivity Test), to evaluate VFSMOD-W under a range of field scenarios. The three VFS studies analyzed were conducted on silty clay loam and silt loam soils under uniform, sheet flow conditions and included atrazine, chlorpyrifos, cyanazine, metolachlor, pendimethalin, and terbuthylazine data. Saturated hydraulic conductivity was the most important input factor for predicting infiltration and runoff, explaining >75% of the total output variance for studies with smaller hydraulic loading rates ( approximately 100-150 mm equivalent depths) and approximately 50% for the higher loading rate ( approximately 280-mm equivalent depth). Important input factors for predicting sedimentation included hydraulic conductivity, average particle size, and the filter's Manning's roughness coefficient. Input factor importance for pesticide trapping was controlled by infiltration and, therefore, hydraulic conductivity. Global uncertainty analyses suggested a wide range of reductions for runoff (95% confidence intervals of 7-93%), sediment (84-100%), and pesticide (43-100%) . Pesticide trapping probability distributions fell between runoff and sediment reduction distributions as a function of the pesticides' sorption. Seemingly

  19. Analysis of Orbital Lifetime Prediction Parameters in Preparation for Post-Mission Disposal

    Directory of Open Access Journals (Sweden)

    Ha–Yeon Choi

    2015-12-01

    Full Text Available Atmospheric drag force is an important source of perturbation of Low Earth Orbit (LEO orbit satellites, and solar activity is a major factor for changes in atmospheric density. In particular, the orbital lifetime of a satellite varies with changes in solar activity, so care must be taken in predicting the remaining orbital lifetime during preparation for post-mission disposal. In this paper, the System Tool Kit (STK® Long-term Orbit Propagator is used to analyze the changes in orbital lifetime predictions with respect to solar activity. In addition, the STK® Lifetime tool is used to analyze the change in orbital lifetime with respect to solar flux data generation, which is needed for the orbital lifetime calculation, and its control on the drag coefficient control. Analysis showed that the application of the most recent solar flux file within the Lifetime tool gives a predicted trend that is closest to the actual orbit. We also examine the effect of the drag coefficient, by performing a comparative analysis between varying and constant coefficients in terms of solar activity intensities.

  20. Computational prediction of the spectroscopic parameters of methanediol, an elusive molecule for interstellar detection

    Energy Technology Data Exchange (ETDEWEB)

    Barrientos, Carmen; Redondo, Pilar; Largo, Antonio [Departamento de Química Física y Química Inorgánica, Facultad de Ciencias, Universidad de Valladolid, Campus Miguel Delibes, Paseo de Belén 7, E-47011 Valladolid (Spain); Martínez, Henar, E-mail: alargo@qf.uva.es [Departamento de Química Orgánica, Escuela de Ingenierías Industriales, Universidad de Valladolid, Campus Esgueva, Paseo del Cauce 59, E-47011 Valladolid (Spain)

    2014-04-01

    The molecular structure of methanediol has been investigated by means of quantum chemical calculations. Two conformers, corresponding to C{sub 2} and C {sub s} symmetries, respectively, were considered. The C{sub 2} conformer is found to lie about 1.7 (at 298 K) or 2.3 (at 0 K) kcal mol{sup –1} below the C {sub s} conformer. Predictions for their rotational constants, vibrational frequencies, IR intensities, and dipole moments have been provided. The lowest-lying isomer has a very low dipole moment, around 0.03 D, whereas the C {sub s} conformer has a relatively high dipole moment, namely, 2.7 D. The barrier for the C {sub s} →C{sub 2} process is predicted to be around 0.7-1 kcal mol{sup –1}. Based on the energetic results the proportion of the C{sub s} conformer is likely to be negligible under low temperature conditions, such as in the interstellar medium. Therefore, it is predicted that detection by radioastronomy of methanediol would be rather unlikely.

  1. Search for morphological parameters influential for prediction of the mechanical characteristics of an austeno-ferritic duplex stainless steel

    International Nuclear Information System (INIS)

    Messiaen, L.

    1997-01-01

    Duplex stainless steels are commonly used (among others in nuclear industry) for their good properties. However these steels may 'age' in service condition at high temperatures. As their mechanical properties (Charpy impact toughness, resistance to ductile tearing) are often very scattered and tend to decrease after ageing, it has become essential to predict them with high precision. For this, we propose to explain a part of the scattering of the mechanical properties with measurable parameters in relation with the particularly complicated two-phase morphology. The two-phase and bi-percolated morphology of the ferrite and austenite phases is first characterised from the observation of 2D images and from the reconstitution of a 3D image. At the same time we precise the genesis of the formation's mechanisms of the structure (germination and growth of the austenitic phase in the solidified ferri tic one) in relation with the literature. The morphological characteristics so observed corresponding with classical notions of mathematical morphology, - size, covariance, connexity -, we use morphological operators to measure morphological variables by image analysis. We establish then a link between toughness and a parameter measuring fineness of the morphology. The lack of data for very aged steels prevent us from proposing a model of toughness which could take this parameter into consideration at these ageing states, for which it is properly the more crucial to obtain specially precise predictions. A mathematical mo del of the 3D structure of the steel is finally proposed. We choose an homogeneous Markov chain of 3D spatial processes, whose evolution in time mimes the solidification. The morphology of the microstructure is so summarised with 8 parameters. This model is liable to be coupled with a model of toughness, for which it would so enlarge the possibilities of prediction. It could also be used to simulate subsequently the damage and the rupture of two

  2. Critical thresholds of liver function parameters for ketosis prediction in dairy cows using receiver operating characteristic (ROC) analysis.

    Science.gov (United States)

    Sun, Yuhang; Wang, Bo; Shu, Shi; Zhang, Hongyou; Xu, Chuang; Wu, Ling; Xia, Cheng

    2015-01-01

    Fatty liver syndrome and ketosis are important metabolic disorders in high-producing cows during early lactation with fatty liver usually preceding ketosis. To date, parameters for early prediction of the risk of ketosis have not been investigated in China. To determine the predictive value of some parameters on the risk of ketosis in China. In a descriptive study, 48 control and 32 ketotic Holstein Friesian cows were randomly selected from one farm with a serum β-hydroxybutyrate (BHBA) concentration of 1.20 mmol/L as cutoff point. The risk prediction thresholds for ketosis were determined by receiver operating characteristic (ROC) analysis. In line with a high BHBA concentration, blood glucose concentration was significantly lower in ketotic cows compared to control animals (2.77 ± 0.24 versus 3.34 ± 0.03 mmol/L; P = 0.02). Thresholds were more than 0.76 mmol/L for nonesterified fatty acids (NEFA, with 65% sensitivity and 92% specificity), more than 104 U/L for aspartate aminotransferase (AST, 74% and 85%, respectively), less than 140 U/L for cholinesterase (CHE, 75% and 59%, respectively), and more than 3.3 µmol/L for total bilirubin (TBIL, 58% and 83%, respectively). There were significant correlations between BHBA and glucose (R = -4.74), or CHE (R = -0.262), BHBA and NEFA (R = 0.520), or AST (R = 0.525), or TBIL (R = 0.278), or direct bilirubin (DBIL, R = 0.348). AST, CHE, TBIL and NEFA may be useful parameters for risk prediction of ketosis. This study might be of value in addressing novel directions for future research on the connection between ketosis and liver dysfunction.

  3. Different diagnostic values of imaging parameters to predict pseudoprogression in glioblastoma subgroups stratified by MGMT promoter methylation

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Ra Gyoung [Catholic Kwandong University International St. Mary' s Hospital, Department of Radiology, Catholic Kwandong University College of Medicine, Incheon (Korea, Republic of); Kim, Ho Sung; Shim, Woo Hyun; Kim, Sang Joon [University of Ulsan College of Medicine, Asan Medical Center, Department of Radiology and Research Institute of Radiology, Seoul (Korea, Republic of); Paik, Wooyul [Dankook Unversity Hospital, Department of Radiology, Cheonan-si, Chungcheongnam-do (Korea, Republic of); Kim, Jeong Hoon [University of Ulsan College of Medicine, Asan Medical Center, Department of Neurosurgery, Seoul (Korea, Republic of)

    2017-01-15

    The aim of this study was to determine whether diffusion and perfusion imaging parameters demonstrate different diagnostic values for predicting pseudoprogression between glioblastoma subgroups stratified by O{sup 6}-mythylguanine-DNA methyltransferase (MGMT) promoter methylation status. We enrolled seventy-five glioblastoma patients that had presented with enlarged contrast-enhanced lesions on magnetic resonance imaging (MRI) one month after completing concurrent chemoradiotherapy and undergoing MGMT promoter methylation testing. The imaging parameters included 10 or 90 % histogram cutoffs of apparent diffusion coefficient (ADC10), normalized cerebral blood volume (nCBV90), and initial area under the time signal-intensity curve (IAUC90). The results of the areas under the receiver operating characteristic curve (AUCs) with cross-validation were compared between MGMT methylation and unmethylation groups. MR imaging parameters demonstrated a trend toward higher accuracy in the MGMT promoter methylation group than in the unmethylation group (cross-validated AUCs = 0.70-0.95 and 0.56-0.87, respectively). The combination of MGMT methylation status with imaging parameters improved the AUCs from 0.70 to 0.75-0.90 for both readers in comparison with MGMT methylation status alone. The probability of pseudoprogression was highest (95.7 %) when nCBV90 was below 4.02 in the MGMT promoter methylation group. MR imaging parameters could be stronger predictors of pseudoprogression in glioblastoma patients with the methylated MGMT promoter than in patients with the unmethylated MGMT promoter. (orig.)

  4. Seasonal dependence of the "forecast parameter" based on the EIA characteristics for the prediction of Equatorial Spread F (ESF

    Directory of Open Access Journals (Sweden)

    S. V. Thampi

    2008-06-01

    Full Text Available In an earlier study, Thampi et al. (2006 have shown that the strength and asymmetry of Equatorial Ionization Anomaly (EIA, obtained well ahead of the onset time of Equatorial Spread F (ESF have a definite role on the subsequent ESF activity, and a new "forecast parameter" has been identified for the prediction of ESF. This paper presents the observations of EIA strength and asymmetry from the Indian longitudes during the period from August 2005–March 2007. These observations are made using the line of sight Total Electron Content (TEC measured by a ground-based beacon receiver located at Trivandrum (8.5° N, 77° E, 0.5° N dip lat in India. It is seen that the seasonal variability of EIA strength and asymmetry are manifested in the latitudinal gradients obtained using the relative TEC measurements. As a consequence, the "forecast parameter" also displays a definite seasonal pattern. The seasonal variability of the EIA strength and asymmetry, and the "forecast parameter" are discussed in the present paper and a critical value for has been identified for each month/season. The likely "skill factor" of the new parameter is assessed using the data for a total of 122 days, and it is seen that when the estimated value of the "forecast parameter" exceeds the critical value, the ESF is seen to occur on more than 95% of cases.

  5. Procalcitonin and proinflammatory parameters in diabetic foot infection as new predictive factor

    Science.gov (United States)

    Raheem, Shler Gh.; Al-Barzinji, Ruqaya M.; Mansoor, Husham Y.; Al-Dabbagh, Ali A.

    2017-09-01

    Diabetic foot is a common complication of diabetes due to changes in blood vessels and nerves, often leads to ulceration and subsequent limb amputation if not treated early. A new diagnostic marker of bacterial infections is procalcitonin. C-reactive protein, Interleukin1β, Interleukin-6 and tumor necrosis factor-α as proinflammatory parameters increased in Diabetic foot infection. We evaluated above parameters in patients with diabetic foot infections in different grades. A total of 130 diabetic patients were enrolled in this case control study between June 2011 and March 2012 in Rizgary, Emergency and Hawler Teaching Hospitals, 90 of them with diabetic foot lesion as a patient group. 40 without foot lesion, as a patient control and 20 individuals as healthy control. Assessment of above parameters in sera of study groups and also bacteriological tests (bacterial isolation and identification) were done. Serum procalcitonin levels significantly increased in patients with diabetic foot with higher Wagner grades (III, IV and V) (0.28 ± 0.04, 0.30 ± 0.07 and 0.60 ± 0.11) respectively (Pfoot ulcer based on Wagner classification system was also associated with circulating levels of C-reactive protein, Interleukin1β, Interleukin-6 and tumor necrosis factor-α (G III, IV and V) (5.36 ± 0.70, 6.38 ± 0.65, and 9.13 ± 0.88), (1.21 ± 0.08, 1.56 ± 0.16 and 2.02 ± 0.07), (23.02 ± 2.98, 36.32 ± 5.75 and 43.36 ± 6.16), and (215.39 ± 16.8, 259.21 ± 40.7 and 398.45 ± 33.4) respectively (Pdiabetic foot patients may be a procalcitonin especially in those with higher Wagner grades and with polymicrobial infection.

  6. Prediction of operating parameters range for ammonia removal unit in coke making by-products

    Science.gov (United States)

    Tiwari, Hari Prakash; Kumar, Rajesh; Bhattacharjee, Arunabh; Lingam, Ravi Kumar; Roy, Abhijit; Tiwary, Shambhu

    2018-02-01

    Coke oven gas treatment plants are well equipped with distributed control systems (DCS) and therefore recording the vast amount of operational data efficiently. Analyzing the stored information manually from historians is practically impossible. In this study, data mining technique was examined for lowering the ammonia concentration in clean coke oven gas. Results confirm that concentration of ammonia in clean coke oven gas depends on the average PCDC temperature; gas scrubber temperatures stripped liquor flow, stripped liquor concentration and stripped liquor temperature. The optimum operating ranges of the above dependent parameters using data mining technique for lowering the concentration of ammonia is described in this paper.

  7. On the estimation of stellar parameters with uncertainty prediction from Generative Artificial Neural Networks: application to Gaia RVS simulated spectra

    Science.gov (United States)

    Dafonte, C.; Fustes, D.; Manteiga, M.; Garabato, D.; Álvarez, M. A.; Ulla, A.; Allende Prieto, C.

    2016-10-01

    Aims: We present an innovative artificial neural network (ANN) architecture, called Generative ANN (GANN), that computes the forward model, that is it learns the function that relates the unknown outputs (stellar atmospheric parameters, in this case) to the given inputs (spectra). Such a model can be integrated in a Bayesian framework to estimate the posterior distribution of the outputs. Methods: The architecture of the GANN follows the same scheme as a normal ANN, but with the inputs and outputs inverted. We train the network with the set of atmospheric parameters (Teff, log g, [Fe/H] and [α/ Fe]), obtaining the stellar spectra for such inputs. The residuals between the spectra in the grid and the estimated spectra are minimized using a validation dataset to keep solutions as general as possible. Results: The performance of both conventional ANNs and GANNs to estimate the stellar parameters as a function of the star brightness is presented and compared for different Galactic populations. GANNs provide significantly improved parameterizations for early and intermediate spectral types with rich and intermediate metallicities. The behaviour of both algorithms is very similar for our sample of late-type stars, obtaining residuals in the derivation of [Fe/H] and [α/ Fe] below 0.1 dex for stars with Gaia magnitude Grvs satellite. Conclusions: Uncertainty estimation of computed astrophysical parameters is crucial for the validation of the parameterization itself and for the subsequent exploitation by the astronomical community. GANNs produce not only the parameters for a given spectrum, but a goodness-of-fit between the observed spectrum and the predicted one for a given set of parameters. Moreover, they allow us to obtain the full posterior distribution over the astrophysical parameters space once a noise model is assumed. This can be used for novelty detection and quality assessment.

  8. Prediction ofWater Quality Parameters (NO3, CL in Karaj Riverby Usinga Combinationof Wavelet Neural Network, ANN and MLRModels

    Directory of Open Access Journals (Sweden)

    T. Rajaee

    2016-10-01

    Full Text Available IntroductionThe water quality is an issue of ongoing concern. Evaluation of the quantity and quality of running waters is considerable in hydro-environmental management.The prediction and control of the quality of Karaj river water, as one of the important needed water supply sources of Tehran, possesses great importance. In this study, Performance of Artificial Neural Network (ANN, Wavelet Neural Network combination (WANN and multi linear regression (MLR models, to predict next month the Nitrate (NO3 and Chloride (CL ions of "gate ofBylaqan sluice" station located in Karaj River has been evaluated. Materials and MethodsIn this research two separate ANN models for prediction of NO3 and CL has been expanded. Each one of the parameters for prediction (NO3 / CL has been put related to the past amounts of the same time series (NO3 / CL and its amounts of Q in past months.From astatisticalperiod of10yearswas usedforthe input of the models. Hence 80% of entire data from (96 initial months of data as training set, next 10% of data (12 months and 10% of the end of time series (terminal 12 months were considered as for validation and test of the models, respectively. In WANNcombination model, the real monthly observed time series of river discharge (Q and mentioned qualityparameters(NO3 / CL were decomposed to some sub-time series at different levels by wavelet analysis.Then the decomposed quality parameters to predict and Q time series were used at different levels as inputs to the ANN technique for predicting one-step-ahead Nitrate and Chloride. These time series play various roles in the original time series and the behavior of each is distinct, so the contribution to the original time series varies from each other. In addition, prediction of high NO3 and CL values greater than mean of data that have great importancewere investigated by the models. The capability of the models was evaluated by Coefficient of Efficiency (E and the Root Mean Square

  9. Predicted Infiltration for Sodic/Saline Soils from Reclaimed Coastal Areas: Sensitivity to Model Parameters

    Directory of Open Access Journals (Sweden)

    Dongdong Liu

    2014-01-01

    Full Text Available This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline and 1960 (Soil B, nonsaline were used, with bulk densities of 1.4 or 1.5 g/cm3. A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ0 was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.

  10. Predicted infiltration for sodic/saline soils from reclaimed coastal areas: sensitivity to model parameters.

    Science.gov (United States)

    Liu, Dongdong; She, Dongli; Yu, Shuang'en; Shao, Guangcheng; Chen, Dan

    2014-01-01

    This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline) and 1960 (Soil B, nonsaline) were used, with bulk densities of 1.4 or 1.5 g/cm(3). A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ₀ was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.

  11. Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis

    Science.gov (United States)

    Hatanaka, Rafael Rodrigues; Flumignan, Danilo Luiz; de Oliveira, José Eduardo

    2018-01-01

    Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10), 50% (T50), and 85% (T85) recovery; cetane index; and biodiesel content) through attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and the multivariate regression method, partial least square (PLS). For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000–650 cm−1. The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time. PMID:29629209

  12. Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis

    Directory of Open Access Journals (Sweden)

    Maurilio Gustavo Nespeca

    2018-01-01

    Full Text Available Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10, 50% (T50, and 85% (T85 recovery; cetane index; and biodiesel content through attenuated total reflection Fourier transform infrared (ATR-FTIR spectroscopy and the multivariate regression method, partial least square (PLS. For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000–650 cm−1. The use of the multivariate filters, generalized least squares weighting (GLSW and orthogonal signal correction (OSC, was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS, backward interval PLS (BiPLS, and genetic algorithm (GA. The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time.

  13. Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis.

    Science.gov (United States)

    Nespeca, Maurilio Gustavo; Hatanaka, Rafael Rodrigues; Flumignan, Danilo Luiz; de Oliveira, José Eduardo

    2018-01-01

    Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10), 50% (T50), and 85% (T85) recovery; cetane index; and biodiesel content) through attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and the multivariate regression method, partial least square (PLS). For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000-650 cm -1 . The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time.

  14. Model parameter-related optimal perturbations and their contributions to El Niño prediction errors

    Science.gov (United States)

    Tao, Ling-Jiang; Gao, Chuan; Zhang, Rong-Hua

    2018-04-01

    Errors in initial conditions and model parameters (MPs) are the main sources that limit the accuracy of ENSO predictions. In addition to exploring the initial error-induced prediction errors, model errors are equally important in determining prediction performance. In this paper, the MP-related optimal errors that can cause prominent error growth in ENSO predictions are investigated using an intermediate coupled model (ICM) and a conditional nonlinear optimal perturbation (CNOP) approach. Two MPs related to the Bjerknes feedback are considered in the CNOP analysis: one involves the SST-surface wind coupling ({α _τ } ), and the other involves the thermocline effect on the SST ({α _{Te}} ). The MP-related optimal perturbations (denoted as CNOP-P) are found uniformly positive and restrained in a small region: the {α _τ } component is mainly concentrated in the central equatorial Pacific, and the {α _{Te}} component is mainly located in the eastern cold tongue region. This kind of CNOP-P enhances the strength of the Bjerknes feedback and induces an El Niño- or La Niña-like error evolution, resulting in an El Niño-like systematic bias in this model. The CNOP-P is also found to play a role in the spring predictability barrier (SPB) for ENSO predictions. Evidently, such error growth is primarily attributed to MP errors in small areas based on the localized distribution of CNOP-P. Further sensitivity experiments firmly indicate that ENSO simulations are sensitive to the representation of SST-surface wind coupling in the central Pacific and to the thermocline effect in the eastern Pacific in the ICM. These results provide guidance and theoretical support for the future improvement in numerical models to reduce the systematic bias and SPB phenomenon in ENSO predictions.

  15. Dosimetric parameters predicting contralateral liver hypertrophy after unilobar radioembolization of hepatocellular carcinoma

    International Nuclear Information System (INIS)

    Palard, Xavier; Edeline, Julien; Rolland, Yan; Le Sourd, Samuel; Pracht, Marc; Laffont, Sophie; Lenoir, Laurence; Boudjema, Karim; Ugen, Thomas; Brun, Vanessa; Mesbah, Habiba; Haumont, Laure-Anne; Loyer, Pascal; Garin, Etienne

    2018-01-01

    This study aimed at identifying prior therapy dosimetric parameters using 99m Tc-labeled macro-aggregates of albumin (MAA) that are associated with contralateral hepatic hypertrophy occurring after unilobar radioembolization of hepatocellular carcinoma (HCC) performed with 90 Y-loaded glass microspheres. The dosimetry data of 73 HCC patients were collected prior to the treatment with 90 Y-loaded microspheres for unilateral disease. The injected liver dose (ILD), the tumor dose (TD) and healthy injected liver dose (HILD) were calculated based on MAA quantification. Following treatment, the maximal hypertrophy (MHT) of an untreated lobe was calculated. Mean MHT was 35.4 ± 40.4%. When using continuous variables, the MHT was not correlated with any tested variable, i.e., injected activity, ILD, HILD or TD except with a percentage of future remnant liver (FRL) following the 90 Y-microspheres injection (r = -0.56). MHT ≥ 10% was significantly more frequent for patients with HILD ≥ 88 Gy, (52% of the cases), i.e., in 92.2% versus 65.7% for HILD < 88 Gy (p = 0.032). MHT ≥ 10% was also significantly more frequent for patients with a TD ≥ 205 Gy and a tumor volume (VT) ≥ 100 cm 3 in patients with initial FRL < 50%. MHT ≥10% was seen in 83.9% for patients with either an HILD ≥ 88 Gy or a TD ≥ 205 Gy for tumors larger than 100cm 3 (85% of the cases), versus only 54.5% (p = 0.0265) for patients with none of those parameters. MHT ≥10% was also associated with FRL and the Child-Pugh score. Using multivariate analysis, the Child-Pugh score (p < 0.0001), FRL (p = 0.0023) and HILD (p = 0.0029) were still significantly associated with MHT ≥10%. This study demonstrates for the first time that HILD is significantly associated with liver hypertrophy. There is also an impact of high tumor doses in large lesions in one subgroup of patients. Larger prospective studies evaluating the MAA dosimetric parameters have to be conducted to confirm these promising results

  16. Dosimetric parameters predicting contralateral liver hypertrophy after unilobar radioembolization of hepatocellular carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Palard, Xavier [Cancer Institute Eugene Marquis, Department of Nuclear Medicine, Rennes (France); University of Rennes 1, Rennes (France); Edeline, Julien [University of Rennes 1, Rennes (France); INSERM, INRA, Univ Rennes 1, Univ Bretagne Loire, Nutrition Metabolisms and Cancer (NuMeCan), Rennes (France); Cancer Institute Eugene Marquis, Department of Medical Oncology, Rennes (France); Rolland, Yan [Cancer Institute Eugene Marquis, Department of Medical Imaging, Rennes (France); Le Sourd, Samuel; Pracht, Marc [Cancer Institute Eugene Marquis, Department of Medical Oncology, Rennes (France); Laffont, Sophie; Lenoir, Laurence [Cancer Institute Eugene Marquis, Department of Nuclear Medicine, Rennes (France); Boudjema, Karim [CHU Pontchaillou, Department of Hepatobiliary Surgery, Rennes (France); Ugen, Thomas [CHU Pontchaillou, Department of Hepatology, Rennes (France); Brun, Vanessa [CHU Pontchaillou, Department of Medical Imaging, Rennes (France); Mesbah, Habiba; Haumont, Laure-Anne [Cancer Institute Eugene Marquis, Department of Medical Information, Rennes (France); Loyer, Pascal [INSERM, INRA, Univ Rennes 1, Univ Bretagne Loire, Nutrition Metabolisms and Cancer (NuMeCan), Rennes (France); Garin, Etienne [Cancer Institute Eugene Marquis, Department of Nuclear Medicine, Rennes (France); University of Rennes 1, Rennes (France); INSERM, INRA, Univ Rennes 1, Univ Bretagne Loire, Nutrition Metabolisms and Cancer (NuMeCan), Rennes (France)

    2018-03-15

    This study aimed at identifying prior therapy dosimetric parameters using {sup 99m}Tc-labeled macro-aggregates of albumin (MAA) that are associated with contralateral hepatic hypertrophy occurring after unilobar radioembolization of hepatocellular carcinoma (HCC) performed with {sup 90}Y-loaded glass microspheres. The dosimetry data of 73 HCC patients were collected prior to the treatment with {sup 90}Y-loaded microspheres for unilateral disease. The injected liver dose (ILD), the tumor dose (TD) and healthy injected liver dose (HILD) were calculated based on MAA quantification. Following treatment, the maximal hypertrophy (MHT) of an untreated lobe was calculated. Mean MHT was 35.4 ± 40.4%. When using continuous variables, the MHT was not correlated with any tested variable, i.e., injected activity, ILD, HILD or TD except with a percentage of future remnant liver (FRL) following the {sup 90}Y-microspheres injection (r = -0.56). MHT ≥ 10% was significantly more frequent for patients with HILD ≥ 88 Gy, (52% of the cases), i.e., in 92.2% versus 65.7% for HILD < 88 Gy (p = 0.032). MHT ≥ 10% was also significantly more frequent for patients with a TD ≥ 205 Gy and a tumor volume (VT) ≥ 100 cm{sup 3} in patients with initial FRL < 50%. MHT ≥10% was seen in 83.9% for patients with either an HILD ≥ 88 Gy or a TD ≥ 205 Gy for tumors larger than 100cm{sup 3} (85% of the cases), versus only 54.5% (p = 0.0265) for patients with none of those parameters. MHT ≥10% was also associated with FRL and the Child-Pugh score. Using multivariate analysis, the Child-Pugh score (p < 0.0001), FRL (p = 0.0023) and HILD (p = 0.0029) were still significantly associated with MHT ≥10%. This study demonstrates for the first time that HILD is significantly associated with liver hypertrophy. There is also an impact of high tumor doses in large lesions in one subgroup of patients. Larger prospective studies evaluating the MAA dosimetric parameters have to be conducted to confirm

  17. Ground Motion Prediction for Great Interplate Earthquakes in Kanto Basin Considering Variation of Source Parameters

    Science.gov (United States)

    Sekiguchi, H.; Yoshimi, M.; Horikawa, H.

    2011-12-01

    Broadband ground motions are estimated in the Kanto sedimentary basin which holds Tokyo metropolitan area inside for anticipated great interplate earthquakes along surrounding plate boundaries. Possible scenarios of great earthquakes along Sagami trough are modeled combining characteristic properties of the source area and adequate variation in source parameters in order to evaluate possible ground motion variation due to next Kanto earthquake. South to the rupture area of the 2011 Tohoku earthquake along the Japan trench, we consider possible M8 earthquake. The ground motions are computed with a four-step hybrid technique. We first calculate low-frequency ground motions at the engineering basement. We then calculate higher-frequency ground motions at the same position, and combine the lower- and higher-frequency motions using a matched filter. We finally calculate ground motions at the surface by computing the response of the alluvium-diluvium layers to the combined motions at the engineering basement.

  18. Prediction of changes in important physical parameters during composting of separated animal slurry solid fractions

    DEFF Research Database (Denmark)

    Chowdhury, Md Albarune; de Neergaard, Andreas; Jensen, Lars Stoumann

    2014-01-01

    Solid-liquid separation of animal slurry, with solid fractions used for composting, has gained interest recently. However, efficient composting of separated animal slurry solid fractions (SSFs) requires a better understanding of the process dynamics in terms of important physical parameters...... and their interacting physical relationships in the composting matrix. Here we monitored moisture content, bulk density, particle density and air-filled porosity (AFP) during composting of SSF collected from four commercially available solid-liquid separators. Composting was performed in laboratory-scale reactors...... for 30 days (d) under forced aeration and measurements were conducted on the solid samples at the beginning of composting and at 10-d intervals during composting. The results suggest that differences in initial physical properties of SSF influence the development of compost maximum temperatures (40...

  19. Prediction of the working parameters of a wood waste gasifier through an equilibrium model

    Energy Technology Data Exchange (ETDEWEB)

    Altafini, Carlos R.; Baretto, Ronaldo M. [Caxias do Sul Univ., Dept. of Mechanical Engineering, Caxias do Sul, RS (Brazil); Wander, Paulo R. [Caxias do Sul Univ., Dept. of Mechanical Engineering, Caxias do Sul, RS (Brazil); Federal Univ. of Rio Grande do Sul State (UFRGS), Mechanical Engineering Postgraduation Program (PROMEC), RS (Brazil)

    2003-10-01

    This paper deals with the computational simulation of a wood waste (sawdust) gasifier using an equilibrium model based on minimization of the Gibbs free energy. The gasifier has been tested with Pinus Elliotis sawdust, an exotic specie largely cultivated in the South of Brazil. The biomass used in the tests presented a moisture of nearly 10% (wt% on wet basis), and the average composition results of the gas produced (without tar) are compared with the equilibrium models used. Sensitivity studies to verify the influence of the moisture sawdust content on the fuel gas composition and on its heating value were made. More complex models to reproduce with better accuracy the gasifier studied were elaborated. Although the equilibrium models do not represent the reactions that occur at relatively high temperatures ( {approx_equal} 800 deg C) very well, these models can be useful to show some tendencies on the working parameter variations of a gasifier. (Author)

  20. Retrograde curves of solidus and solubility

    International Nuclear Information System (INIS)

    Vasil'ev, M.V.

    1979-01-01

    The investigation was concerned with the constitutional diagrams of the eutectic type with ''retrograde solidus'' and ''retrograde solubility curve'' which must be considered as diagrams with degenerate monotectic transformation. The solidus and the solubility curves form a retrograde curve with a common retrograde point representing the solubility maximum. The two branches of the Aetrograde curve can be described with the aid of two similar equations. Presented are corresponding equations for the Cd-Zn system and shown is the possibility of predicting the run of the solubility curve

  1. Prediction of qualitative parameters of slab steel ingot using numerical modelling

    Directory of Open Access Journals (Sweden)

    M. Tkadlečková

    2016-07-01

    Full Text Available The paper describes the verification of casting and solidification of heavy slab ingot weighing 40 t from tool steel by means of numerical modelling with use of a finite element method. The pre-processing, processing and post-processing phases of numerical modelling are outlined. Also, the problems with determination of the thermodynamic properties of materials and with determination of the heat transfer between the individual parts of the casting system are discussed. The final porosity, macrosegregation and the risk of cracks were predicted. The results allowed us to use the slab ingot instead of the conventional heavy steel ingot and to improve the ratio, the chamfer and the external shape of the wall of the new design of the slab ingot.

  2. Extensive cardinal parameter model to predict growth of pseudomonads in salt-reduced lightly preserved seafood

    DEFF Research Database (Denmark)

    Martinez Rios, Veronica; Dalgaard, Paw

    Interest in and demand for preserved seafood with reduced salt/sodium content is increasing. As a consequence of the reduced salt content potential growth of psychrotolerant pseudomonads to unacceptable high concentration where they cause product spoilage is an increasing challenge. Innovation...... include the effect of temperatures and salt. However, these simple secondary models do not include the effect of a broader range of product characteristics and therefore they cannot be used to predict how the inhibiting effect of salt can be replaced by changes in other environmental factors The objective...... and including terms for temperature, pH, aw/NaCl, lactic- and sorbic acids (Martinez-Rios et al., Int. J. Food Microbiol. 216. 110-120, 2016). MIC-values for acetic-, benzoic- and citric acids were determined in broth and terms modelling their antimicrobial effect were added to the model. The new and expanded...

  3. Predictive statistical modelling of cadmium content in durum wheat grain based on soil parameters.

    Science.gov (United States)

    Viala, Yoann; Laurette, Julien; Denaix, Laurence; Gourdain, Emmanuelle; Méléard, Benoit; Nguyen, Christophe; Schneider, André; Sappin-Didier, Valérie

    2017-09-01

    Regulatory limits on cadmium (Cd) content in food products are tending to become stricter, especially in cereals, which are a major contributor to dietary intake of Cd by humans. This is of particular importance for durum wheat, which accumulates more Cd than bread wheat. The contamination of durum wheat grain by Cd depends not only on the genotype but also to a large extent on soil Cd availability. Assessing the phytoavailability of Cd for durum wheat is thus crucial, and appropriate methods are required. For this purpose, we propose a statistical model to predict Cd accumulation in durum wheat grain based on soil geochemical properties related to Cd availability in French agricultural soils with low Cd contents and neutral to alkaline pH (soils commonly used to grow durum wheat). The best model is based on the concentration of total Cd in the soil solution, the pH of a soil CaCl 2 extract, the cation exchange capacity (CEC), and the content of manganese oxides (Tamm's extraction) in the soil. The model variables suggest a major influence of cadmium buffering power of the soil and of Cd speciation in solution. The model successfully explains 88% of Cd variability in grains with, generally, below 0.02 mg Cd kg -1 prediction error in wheat grain. Monte Carlo cross-validation indicated that model accuracy will suffice for the European Community project to reduce the regulatory limit from 0.2 to 0.15 mg Cd kg -1 grain, but not for the intermediate step at 0.175 mg Cd kg -1 . The model will help farmers assess the risk that the Cd content of their durum wheat grain will exceed regulatory limits, and help food safety authorities test different regulatory thresholds to find a trade-off between food safety and the negative impact a too strict regulation could have on farmers.

  4. The value of arterial blood gas parameters for prediction of mortality in survivors of out-of-hospital cardiac arrest

    Directory of Open Access Journals (Sweden)

    Katharina Isabel von Auenmueller

    2017-01-01

    Full Text Available Context: Sudden cardiac death is one of the leading causes of death in Europe, and early prognostication remains challenging. There is a lack of valid parameters for the prediction of survival after cardiac arrest. Aims: This study aims to investigate if arterial blood gas parameters correlate with mortality of patients after out-of-hospital cardiac arrest. Materials and Methods: All patients who were admitted to our hospital after resuscitation following out-of-hospital cardiac arrest between January 1, 2008, and December 31, 2013, were included in this retrospective study. The patient's survival 5 days after resuscitation defined the study end-point. For the statistical analysis, the mean, standard deviation, Student's t-test, Chi-square test, and logistic regression analyses were used (level of significance P< 0.05. Results: Arterial blood gas samples were taken from 170 patients. In particular, pH < 7.0 (odds ratio [OR]: 7.20; 95% confidence interval [CI]: 3.11–16.69; P< 0.001 and lactate ≥ 5.0 mmol/L (OR: 6.79; 95% CI: 2.77–16.66; P< 0.001 showed strong and independent correlations with mortality within the first 5 days after hospital admission. Conclusion: Our study results indicate that several arterial blood gas parameters correlate with mortality of patients after out-of-hospital resuscitation. The most relevant parameters are pH and lactate because they are strongly and independently associated with mortality within the first 5 days after resuscitation. Despite this correlation, none of these parameters by oneself is strong enough to allow an early prognostication. Still, these parameters can contribute as part of a multimodal approach to assessing the patients' prognosis.

  5. Dynamic Contrast-Enhanced MRI of Cervical Cancers: Temporal Percentile Screening of Contrast Enhancement Identifies Parameters for Prediction of Chemoradioresistance

    International Nuclear Information System (INIS)

    Andersen, Erlend K.F.; Hole, Knut Håkon; Lund, Kjersti V.; Sundfør, Kolbein; Kristensen, Gunnar B.; Lyng, Heidi; Malinen, Eirik

    2012-01-01

    Purpose: To systematically screen the tumor contrast enhancement of locally advanced cervical cancers to assess the prognostic value of two descriptive parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods and Materials: This study included a prospectively collected cohort of 81 patients who underwent DCE-MRI with gadopentetate dimeglumine before chemoradiotherapy. The following descriptive DCE-MRI parameters were extracted voxel by voxel and presented as histograms for each time point in the dynamic series: normalized relative signal increase (nRSI) and normalized area under the curve (nAUC). The first to 100th percentiles of the histograms were included in a log-rank survival test, resulting in p value and relative risk maps of all percentile–time intervals for each DCE-MRI parameter. The maps were used to evaluate the robustness of the individual percentile–time pairs and to construct prognostic parameters. Clinical endpoints were locoregional control and progression-free survival. The study was approved by the institutional ethics committee. Results: The p value maps of nRSI and nAUC showed a large continuous region of percentile–time pairs that were significantly associated with locoregional control (p < 0.05). These parameters had prognostic impact independent of tumor stage, volume, and lymph node status on multivariate analysis. Only a small percentile–time interval of nRSI was associated with progression-free survival. Conclusions: The percentile–time screening identified DCE-MRI parameters that predict long-term locoregional control after chemoradiotherapy of cervical cancer.

  6. Support vector machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel

    Science.gov (United States)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive Support Vector Machine (SVM) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For SVM modelling, different values for radial basis function (RBF) kernel width and penalty parameters (C) were considered and the optimum values were then found. The results demonstrate that SVM is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve complete combustion of the fuel and reduce the exhaust emissions significantly.

  7. Blood coagulation parameters and platelet indices: changes in normal and preeclamptic pregnancies and predictive values for preeclampsia.

    Directory of Open Access Journals (Sweden)

    Lei Han

    Full Text Available Preeclampsia (PE is an obstetric disorder with high morbidity and mortality rates but without clear pathogeny. The dysfunction of the blood coagulation-fibrinolysis system is a salient characteristic of PE that varies in severity, and necessitates different treatments. Therefore, it is necessary to find suitable predictors for the onset and severity of PE.We aimed to evaluate blood coagulation parameters and platelet indices as potential predictors for the onset and severity of PE.Blood samples from 3 groups of subjects, normal pregnant women (n = 79, mild preeclampsia (mPE (n = 53 and severe preeclampsia (sPE (n = 42, were collected during early and late pregnancy. The levels of coagulative parameters and platelet indices were measured and compared among the groups. The receiver-operating characteristic (ROC curves of these indices were generated, and the area under the curve (AUC was calculated. The predictive values of the selected potential parameters were examined in binary regression analysis.During late pregnancy in the normal pregnancy group, the activated partial thromboplastin time (APTT, prothrombin time (PT, thrombin time (TT and platelet count decreased, while the fibrinogen level and mean platelet volume (MPV increased compared to early pregnancy (p<0.05. However, the PE patients presented with increased APTT, TT, MPV and D-dimer (DD during the third trimester. In the analysis of subjects with and without PE, TT showed the largest AUC (0.743 and high predictive value. In PE patients with different severities, MPV showed the largest AUC (0.671 and ideal predictive efficiency.Normal pregnancy causes a maternal physiological hypercoagulable state in late pregnancy. PE may trigger complex disorders in the endogenous coagulative pathways and consume platelets and FIB, subsequently activating thrombopoiesis and fibrinolysis. Thrombin time and MPV may serve as early monitoring markers for the onset and severity of PE

  8. Correlation and prediction of osmotic coefficient and water activity of aqueous electrolyte solutions by a two-ionic parameter model

    International Nuclear Information System (INIS)

    Pazuki, G.R.

    2005-01-01

    In this study, osmotic coefficients and water activities in aqueous solutions have been modeled using a new approach based on the Pitzer model. This model contains two physically significant ionic parameters regarding ionic solvation and the closest distance of approach between ions in a solution. The proposed model was evaluated by estimating the osmotic coefficients of nine electrolytes in aqueous solutions. The obtained results showed that the model is suitable for predicting the osmotic coefficients in aqueous electrolyte solutions. Using adjustable parameters, which have been calculated from regression between the experimental osmotic coefficient and the results of this model, the water activity coefficients of aqueous solutions were calculated. The average absolute relative deviations of the osmotic coefficients between the experimental data and the calculated results were in agreement

  9. Gas solubilities widespread applications

    CERN Document Server

    Gerrard, William

    1980-01-01

    Gas Solubilities: Widespread Applications discusses several topics concerning the various applications of gas solubilities. The first chapter of the book reviews Henr's law, while the second chapter covers the effect of temperature on gas solubility. The third chapter discusses the various gases used by Horiuti, and the following chapters evaluate the data on sulfur dioxide, chlorine data, and solubility data for hydrogen sulfide. Chapter 7 concerns itself with solubility of radon, thoron, and actinon. Chapter 8 tackles the solubilities of diborane and the gaseous hydrides of groups IV, V, and

  10. Pre-stimulation parameters predicting live birth after IVF in the long GnRH agonist protocol

    DEFF Research Database (Denmark)

    Pettersson, Göran; Andersen, Anders Nyboe; Broberg, Per

    2010-01-01

    This retrospective study aimed to identify novel pre-stimulation parameters associated with live birth in IVF and to develop a model for prediction of the chances of live birth at an early phase of the treatment cycle. Data were collected from a randomized trial in couples with unexplained...... infertility, tubal factor, mild male factor or other reason for infertility. All women (n=731) had undergone an IVF cycle (no intracytoplasmic sperm injection) after stimulation with human menopausal gonadotrophin or follicle-stimulating hormone following the long gonadotrophin-releasing hormone agonist...

  11. Pre-stimulation parameters predicting live birth after IVF in the long GnRH agonist protocol

    DEFF Research Database (Denmark)

    Pettersson, Göran; Andersen, Anders Nyboe; Broberg, Per

    2010-01-01

    infertility, tubal factor, mild male factor or other reason for infertility. All women (n=731) had undergone an IVF cycle (no intracytoplasmic sperm injection) after stimulation with human menopausal gonadotrophin or follicle-stimulating hormone following the long gonadotrophin-releasing hormone agonist......This retrospective study aimed to identify novel pre-stimulation parameters associated with live birth in IVF and to develop a model for prediction of the chances of live birth at an early phase of the treatment cycle. Data were collected from a randomized trial in couples with unexplained...

  12. Predictive significance of standardized uptake value parameters of FDG-PET in patients with non-small cell lung carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Duan, X-Y.; Wang, W.; Li, M.; Li, Y.; Guo, Y-M. [PET-CT Center, The First Affiliated Hospital of Xi' an, Jiaotong University, Xi' an, Shaanxi (China)

    2015-02-03

    {sup 18}F-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) is widely used to diagnose and stage non-small cell lung cancer (NSCLC). The aim of this retrospective study was to evaluate the predictive ability of different FDG standardized uptake values (SUVs) in 74 patients with newly diagnosed NSCLC. {sup 18}F-FDG PET/CT scans were performed and different SUV parameters (SUV{sub max}, SUV{sub avg}, SUV{sub T/L}, and SUV{sub T/A}) obtained, and their relationship with clinical characteristics were investigated. Meanwhile, correlation and multiple stepwise regression analyses were performed to determine the primary predictor of SUVs for NSCLC. Age, gender, and tumor size significantly affected SUV parameters. The mean SUVs of squamous cell carcinoma were higher than those of adenocarcinoma. Poorly differentiated tumors exhibited higher SUVs than well-differentiated ones. Further analyses based on the pathologic type revealed that the SUV{sub max}, SUV{sub avg}, and SUV{sub T/L} of poorly differentiated adenocarcinoma tumors were higher than those of moderately or well-differentiated tumors. Among these four SUV parameters, SUV{sub T/L} was the primary predictor for tumor differentiation. However, in adenocarcinoma, SUV{sub max} was the determining factor for tumor differentiation. Our results showed that these four SUV parameters had predictive significance related to NSCLC tumor differentiation; SUV{sub T/L} appeared to be most useful overall, but SUV{sub max} was the best index for adenocarcinoma tumor differentiation.

  13. Can preoperative sex-related differences in hemostatic parameters predict bleeding in orthognathic surgery?

    DEFF Research Database (Denmark)

    Jared Olsen, Jesper; Ingerslev, Janne; Thorn, Jens Jørgen

    2016-01-01

    PURPOSE: Bleeding volume in orthognathic surgery (OS) varies considerably, although OS comprises standardized procedures and the patient population consists of young healthy individuals. The aim of this prospective cohort study was to investigate the influence of preoperative sex-related differen......PURPOSE: Bleeding volume in orthognathic surgery (OS) varies considerably, although OS comprises standardized procedures and the patient population consists of young healthy individuals. The aim of this prospective cohort study was to investigate the influence of preoperative sex......-related differences in hemostatic parameters on intraoperative bleeding (IOB) volume in OS. MATERIALS AND METHODS: Patients scheduled for routine OS in our department in Esbjerg, Denmark, were included as study patients in this short-term cohort study. The primary predictor variable was patient sex, and the primary...... the χ(2) test, Mann-Whitney U test, Pearson product moment correlation analysis, and analysis of covariance for analyses of dichotomous variables, comparison between sex, correlations between IOB volume and secondary predictors, and adjustment for confounders, respectively. RESULTS: Forty...

  14. BAYESIAN PREDICTION OF GENETIC PARAMETERS IN Eucalyptus globulus CLONES UNDER WATER SUPPLY CONDITIONS

    Directory of Open Access Journals (Sweden)

    Freddy Mora

    2013-06-01

    Full Text Available http://dx.doi.org/10.5902/198050989297A Bayesian analysis of genetic parameters for growth traits at twelve months after planting was carried out in twenty nine Eucalyptus globulus clones in southern Chile. Two different environmental conditions were considered: 1 Non-irrigation and; 2 Plants were irrigated with a localized irrigation system. The Bayesian approach was performed using Gibbs sampling algorithm in a clone-environment interaction model. Inheritability values ​​were high in the water supply condition (posterior mode: H2=0.41, 0.36 and 0.39 for height, diameter and sectional area, respectively, while in the environment without irrigation, the inheritabilities were significantly lower, which was confirmed by the Bayesian credible intervals (95% probability. The posterior mode of the genetic correlation between sites was positive and high for all traits (r=0.7, 0.65 and 0.8, for height, diameter and sectional area, respectively and according to the credible interval, it was statistically different from zero, indicating a non-significant interaction.

  15. Application of artificial neural networks for the prediction of traction performance parameters

    Directory of Open Access Journals (Sweden)

    Hamid Taghavifar

    2014-01-01

    Full Text Available This study handles artificial neural networks (ANN modeling to predict tire contact area and rolling resistance due to the complex and nonlinear interactions between soil and wheel that mathematical, numerical and conventional models fail to investigate multivariate input and output relationships with nonlinear and complex characteristics. Experimental data acquisitioning was carried out using a soil bin facility with single-wheel tester at seven inflation pressures of tire (i.e. 100–700 kPa and seven different wheel loads (1–7 KN with two soil textures and two tire types. The experimental datasets were used to develop a feed-forward with back propagation ANN model. Four criteria (i.e. R-value, T value, mean squared error, and model simplicity were used to evaluate model’s performance. A well-trained optimum 4-6-2 ANN provided the best accuracy in modeling contact area and rolling resistance with regression coefficients of 0.998 and 0.999 and T value and MSE of 0.996 and 2.55 × 10−12, respectively. It was found that ANNs due to faster, more precise, and considerably reliable computation of multivariable, nonlinear, and complex computations are highly appropriate for soil–wheel interaction modeling.

  16. Using Bronson Equation to Accurately Predict the Dog Brain Weight Based on Body Weight Parameter

    Directory of Open Access Journals (Sweden)

    L. Miguel Carreira

    2016-12-01

    Full Text Available The study used 69 brains (n = 69 from adult dog cadavers, divided by their skull type into three groups, brachi (B, dolicho (D and mesaticephalic (M (n = 23 each, and aimed: (1 to determine whether the Bronson equation may be applied, without reservation, to estimate brain weight (BW in brachy (B, dolicho (D, and mesaticephalic (M dog breeds; and (2 to evaluate which breeds are more closely related to each other in an evolutionary scenario. All subjects were identified by sex, age, breed, and body weight (bw. An oscillating saw was used for a circumferential craniotomy to open the skulls; the brains were removed and weighed using a digital scale. For statistical analysis, p-values < 0.05 were considered significant. The work demonstrated a strong relationship between the observed and predicted BW by using the Bronson equation. It was possible to hypothesize that groups B and D present a greater encephalization level than M breeds, that B and D dog breeds are more closely related to each other than to M, and from the three groups, the D individuals presented the highest brain mass mean.

  17. Prediction of changes in important physical parameters during composting of separated animal slurry solid fractions.

    Science.gov (United States)

    Chowdhury, Md Albarune; de Neergaard, Andreas; Jensen, Lars Stoumann

    2014-01-01

    Solid-liquid separation of animal slurry, with solid fractions used for composting, has gained interest recently. However, efficient composting of separated animal slurry solid fractions (SSFs) requires a better understanding of the process dynamics in terms of important physical parameters and their interacting physical relationships in the composting matrix. Here we monitored moisture content, bulk density, particle density and air-filled porosity (AFP) during composting of SSF collected from four commercially available solid-liquid separators. Composting was performed in laboratory-scale reactors for 30 days (d) under forced aeration and measurements were conducted on the solid samples at the beginning of composting and at 10-d intervals during composting. The results suggest that differences in initial physical properties of SSF influence the development of compost maximum temperatures (40-70 degreeC). Depending on SSF, total wet mass and volume losses (expressed as % of initial value) were up to 37% and 34%, respectively. After 30 d of composting, relative losses of total solids varied from 17.9% to 21.7% and of volatile solids (VS) from 21.3% to 27.5%, depending on SSF. VS losses in all composts showed different dynamics as described by the first-order kinetic equation. The estimated component particle density of 1441 kg m-3 for VS and 2625 kg m-3 for fixed solids can be used to improve estimates of AFP for SSF within the range tested. The linear relationship between wet bulk density and AFP reported by previous researchers held true for SSF.

  18. Predicting surgical outcome in cases of cervical myelopathy with magnetic resonance imaging. Critical parameters

    International Nuclear Information System (INIS)

    Akiyama, Takashi

    1997-01-01

    In this study, the author attempted to correlate clinical factors significant in cases of cervical myelopathy with postoperative recovery. It is hoped that the results will aid in the preoperative prediction of surgical outcomes. The factors considered were the transverse area of the spinal cord, the cord compression rate, the presence of a high intensity area in T2-weighted MRI, the duration of symptoms before surgery, and age at surgery. Because there are variations in the transverse area of the spinal cord, 100 normal individuals were selected and the standard transverse area was calculated. The transverse area of the spinal cord and the cord constriction rate in the myelopathy cases was then measured and compared to the standard. The data indicated that the constriction rate was most relevant to recovery rate. Clinical thresholds found to correlate with a better than average rate of recovery in cases of cervical spondylotic myelopathy (CSM) were: a cord constriction rate; under 28.7%, cord compression rate; over 0.38, duration of symptoms before surgery; less than 9.2 months, and age at surgery; under 59.2 yrs. In patients with ossification of the longitudinal ligament (OPLL), cord constriction rate; under 36.2%, cord compression rate; over 0.30, duration of symptoms before surgery; less than 14.2 months, and age at surgery; under 57.6 yrs., all correlated with superior recovery, as did cord constriction rate; under 22.3%, and duration of symptoms before surgery; less than 3.7 months with patients suffering from cervical disc herniation (CDH). Furthermore, the absence of a T2-weighted high intensity area in CSM and OPLL patients also correlated with improved recovery. These results suggest that a favorable postoperative recovery rate can be expected in cases of cervical myelopathy that conform to the above criteria. (author)

  19. A simplified model for predicting malaria entomologic inoculation rates based on entomologic and parasitologic parameters relevant to control.

    Science.gov (United States)

    Killeen, G F; McKenzie, F E; Foy, B D; Schieffelin, C; Billingsley, P F; Beier, J C

    2000-05-01

    Malaria transmission intensity is modeled from the starting perspective of individual vector mosquitoes and is expressed directly as the entomologic inoculation rate (EIR). The potential of individual mosquitoes to transmit malaria during their lifetime is presented graphically as a function of their feeding cycle length and survival, human biting preferences, and the parasite sporogonic incubation period. The EIR is then calculated as the product of 1) the potential of individual vectors to transmit malaria during their lifetime, 2) vector emergence rate relative to human population size, and 3) the infectiousness of the human population to vectors. Thus, impacts on more than one of these parameters will amplify each other's effects. The EIRs transmitted by the dominant vector species at four malaria-endemic sites from Papua New Guinea, Tanzania, and Nigeria were predicted using field measurements of these characteristics together with human biting rate and human reservoir infectiousness. This model predicted EIRs (+/- SD) that are 1.13 +/- 0.37 (range = 0.84-1.59) times those measured in the field. For these four sites, mosquito emergence rate and lifetime transmission potential were more important determinants of the EIR than human reservoir infectiousness. This model and the input parameters from the four sites allow the potential impacts of various control measures on malaria transmission intensity to be tested under a range of endemic conditions. The model has potential applications for the development and implementation of transmission control measures and for public health education.

  20. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.

    Science.gov (United States)

    Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu

    2015-09-01

    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. SITE-94. Discrete-feature modelling of the Aespoe Site: 3. Predictions of hydrogeological parameters for performance assessment

    International Nuclear Information System (INIS)

    Geier, J.E.

    1996-12-01

    A 3-dimensional, discrete-feature hydrological model is developed. The model integrates structural and hydrologic data for the Aespoe site, on scales ranging from semi regional fracture zones to individual fractures in the vicinity of the nuclear waste canisters. Predicted parameters for the near field include fracture spacing, fracture aperture, and Darcy velocity at each of forty canister deposition holes. Parameters for the far field include discharge location, Darcy velocity, effective longitudinal dispersion coefficient and head gradient, flow porosity, and flow wetted surface, for each canister source that discharges to the biosphere. Results are presented in the form of statistical summaries for a total of 42 calculation cases, which treat a set of 25 model variants in various combinations. The variants for the SITE-94 Reference Case model address conceptual and parametric uncertainty related to the site-scale hydrogeologic model and its properties, the fracture network within the repository, effective semi regional boundary conditions for the model, and the disturbed-rock zone around the repository tunnels and shafts. Two calculation cases simulate hydrologic conditions that are predicted to occur during future glacial episodes. 30 refs

  2. A New Approach on Estimation of Solubility and n-Octanol/ Water Partition Coefficient for Organohalogen Compounds

    Directory of Open Access Journals (Sweden)

    Chenzhong Cao

    2008-06-01

    Full Text Available The aqueous solubility (logW and n-octanol/water partition coefficient (logPOW are important properties for pharmacology, toxicology and medicinal chemistry. Based on an understanding of the dissolution process, the frontier orbital interaction model was suggested in the present paper to describe the solvent-solute interactions of organohalogen compounds and a general three-parameter model was proposed to predict the aqueous solubility and n-octanol/water partition coefficient for the organohalogen compounds containing nonhydrogen-binding interactions. The model has satisfactory prediction accuracy. Furthermore, every item in the model has a very explicit meaning, which should be helpful to understand the structure-solubility relationship and may be provide a new view on estimation of solubility.

  3. Evaluation of several FDG PET parameters for prediction of soft tissue tumour grade at primary diagnosis and recurrence

    Energy Technology Data Exchange (ETDEWEB)

    Fendler, Wolfgang P. [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Department of Nuclear Medicine, Munich (Germany); Chalkidis, Rebecca P.; Ilhan, Harun [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Knoesel, Thomas [Ludwig-Maximilians-University of Munich, Institute of Pathology, Munich (Germany); Herrmann, Ken [Julius-Maximilians-University of Wuerzburg, Department of Nuclear Medicine, Wuerzburg (Germany); Issels, Rolf D.; Lindner, Lars H. [Ludwig-Maximilians-University of Munich, Department of Internal Medicine III, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Bartenstein, Peter [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Cyran, Clemens C. [Ludwig-Maximilians-University of Munich, Department of Clinical Radiology, Munich (Germany); Hacker, Marcus [Vienna General Hospital, Department of Nuclear Medicine, Vienna (Austria)

    2015-08-15

    This study evaluates the diagnostic accuracy of SUV-based parameters derived from [{sup 18} F]-2-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) in order to optimize non-invasive prediction of soft tissue tumour (STT) grade. One hundred and twenty-nine lesions from 123 patients who underwent FDG-PET for primary staging (n = 79) or assessment of recurrence (n = 44) of STT were analyzed retrospectively. Histopathology was the reference standard for tumour grading. Absolute values and tumour-to-liver ratios of several standardized uptake value (SUV) parameters were correlated with tumour grading. At primary diagnosis SUV{sub max}, SUV{sub peak}, SUV{sub max}/SUV{sub liver} and SUV{sub peak}/SUV{sub liver} showed good correlation with tumour grade. SUV{sub peak} (area under the receiver-operating-characteristic, AUC-ROC: 0.82) and SUV{sub peak}/SUV{sub liver} (AUC-ROC: 0.82) separated best between low grade (WHO intermediate, grade 1 sarcoma, and low risk gastrointestinal stromal tumours, GISTs) and high grade (grade 2/3 sarcoma and intermediate/high risk GISTs) lesions: optimal threshold for SUV{sub peak}/SUV{sub liver} was 2.4, which resulted in a sensitivity of 79 % and a specificity of 81 %. At disease recurrence, the AUC-ROC was <0.75 for each parameter. A tumour SUV{sub peak} of at least 2.4 fold mean liver uptake predicts high grade histopathology with good diagnostic accuracy at primary staging. At disease recurrence, FDG-PET does not reliably separate high and low grade lesions. (orig.)

  4. A Toolkit to Study Sensitivity of the Geant4 Predictions to the Variations of the Physics Model Parameters

    Energy Technology Data Exchange (ETDEWEB)

    Fields, Laura [Fermilab; Genser, Krzysztof [Fermilab; Hatcher, Robert [Fermilab; Kelsey, Michael [SLAC; Perdue, Gabriel [Fermilab; Wenzel, Hans [Fermilab; Wright, Dennis H. [SLAC; Yarba, Julia [Fermilab

    2017-08-21

    Geant4 is the leading detector simulation toolkit used in high energy physics to design detectors and to optimize calibration and reconstruction software. It employs a set of carefully validated physics models to simulate interactions of particles with matter across a wide range of interaction energies. These models, especially the hadronic ones, rely largely on directly measured cross-sections and phenomenological predictions with physically motivated parameters estimated by theoretical calculation or measurement. Because these models are tuned to cover a very wi