General theory for multiple input-output perturbations in complex molecular systems. 1. Linear QSPR electronegativity models in physical, organic, and medicinal chemistry.

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González-Díaz, Humberto; Arrasate, Sonia; Gómez-SanJuan, Asier; Sotomayor, Nuria; Lete, Esther; Besada-Porto, Lina; Ruso, Juan M

2013-01-01

In general perturbation methods starts with a known exact solution of a problem and add "small" variation terms in order to approach to a solution for a related problem without known exact solution. Perturbation theory has been widely used in almost all areas of science. Bhor's quantum model, Heisenberg's matrix mechanincs, Feyman diagrams, and Poincare's chaos model or "butterfly effect" in complex systems are examples of perturbation theories. On the other hand, the study of Quantitative Structure-Property Relationships (QSPR) in molecular complex systems is an ideal area for the application of perturbation theory. There are several problems with exact experimental solutions (new chemical reactions, physicochemical properties, drug activity and distribution, metabolic networks, etc.) in public databases like CHEMBL. However, in all these cases, we have an even larger list of related problems without known solutions. We need to know the change in all these properties after a perturbation of initial boundary conditions. It means, when we test large sets of similar, but different, compounds and/or chemical reactions under the slightly different conditions (temperature, time, solvents, enzymes, assays, protein targets, tissues, partition systems, organisms, etc.). However, to the best of our knowledge, there is no QSPR general-purpose perturbation theory to solve this problem. In this work, firstly we review general aspects and applications of both perturbation theory and QSPR models. Secondly, we formulate a general-purpose perturbation theory for multiple-boundary QSPR problems. Last, we develop three new QSPR-Perturbation theory models. The first model classify correctly >100,000 pairs of intra-molecular carbolithiations with 75-95% of Accuracy (Ac), Sensitivity (Sn), and Specificity (Sp). The model predicts probabilities of variations in the yield and enantiomeric excess of reactions due to at least one perturbation in boundary conditions (solvent, temperature

QSPR Study of the Retention/release Property of Odorant Molecules in Water Using Statistical Methods

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Assia Belhassan

2017-10-01

Full Text Available An integrated approach physicochemistry and structures property relationships has been carried out to study the odorant molecules retention/release phenomenon in the water. This study aimed to identify the molecular properties (molecular descriptors that govern this phenomenon assuming that modifying the structure leads automatically to a change in the retention/release property of odorant molecules. ACD/ChemSketch, MarvinSketch, and ChemOffice programs were used to calculate several molecular descriptors of 51 odorant molecules (15 alcohols, 11 aldehydes, 9 ketones and 16 esters. A total of 37 molecules (2/3 of the data set were placed in the training set to build the QSPR models, whereas the remaining, 14 molecules (1/3 of the data set constitute the test set. The best descriptors were selected to establish the quantitative structure property relationship (QSPR of the retention/release property of odorant molecules in water using multiple linear regression (MLR, multiple non-linear regression (MNLR and an artificial neural network (ANN methods. We propose a quantitative model according to these analyses. The models were used to predict the retention/release property of the test set compounds, and agreement between the experimental and predicted values was verified. The descriptors showed by QSPR study are used for study and designing of new compounds. The statistical results indicate that the predicted values are in good agreement with the experimental results. To validate the predictive power of the resulting models, external validation multiple correlation coefficient was calculated and has both in addition to a performant prediction power, a favorable estimation of stability. DOI: http://dx.doi.org/10.17807/orbital.v9i4.978 

Potentialities and limits of QSPR and molecular modeling in the design of the extraction solvents used in hydrometallurgy

International Nuclear Information System (INIS)

Cote, G.; Chagnes, A.

2010-01-01

Due to new challenges, new extraction solvents based on innovative extractants are needed in hydrometallurgy for specific tasks. Thus, the aim of the present paper is to discuss the potentialities and limits of QSPR and molecular modeling for identifying new extractants. QSPR methods may have useful applications in such a complex problem as the design of ligands for metal separation. Nevertheless, the degree of reliability of the predictions is still limited and, in the present state of the art, these techniques are likely more useful for optimization within a given family of extractants than to build in silico new reagents. The molecular modeling techniques provide binding energies between target metals and given ligands, as well as optimized chemical structures of the formed complexes. Thus, in principle, the information which can be deduced from the molecular modeling computations is richer than that provided by QSPR methods. Nevertheless, an effort should be made to establish more tangible links between the calculated binding energies and the physical parameters used by the hydrometallurgists, such as the complexation constants in aqueous phase (β MAn ) or better the extraction constants (K ex ). (author)

Multi-target QSPR modeling for simultaneous prediction of multiple gas-phase kinetic rate constants of diverse chemicals

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Basant, Nikita; Gupta, Shikha

2018-03-01

The reactions of molecular ozone (O3), hydroxyl (•OH) and nitrate (NO3) radicals are among the major pathways of removal of volatile organic compounds (VOCs) in the atmospheric environment. The gas-phase kinetic rate constants (kO3, kOH, kNO3) are thus, important in assessing the ultimate fate and exposure risk of atmospheric VOCs. Experimental data for rate constants are not available for many emerging VOCs and the computational methods reported so far address a single target modeling only. In this study, we have developed a multi-target (mt) QSPR model for simultaneous prediction of multiple kinetic rate constants (kO3, kOH, kNO3) of diverse organic chemicals considering an experimental data set of VOCs for which values of all the three rate constants are available. The mt-QSPR model identified and used five descriptors related to the molecular size, degree of saturation and electron density in a molecule, which were mechanistically interpretable. These descriptors successfully predicted three rate constants simultaneously. The model yielded high correlations (R2 = 0.874-0.924) between the experimental and simultaneously predicted endpoint rate constant (kO3, kOH, kNO3) values in test arrays for all the three systems. The model also passed all the stringent statistical validation tests for external predictivity. The proposed multi-target QSPR model can be successfully used for predicting reactivity of new VOCs simultaneously for their exposure risk assessment.

QSPR models for predicting generator-column-derived octanol/water and octanol/air partition coefficients of polychlorinated biphenyls.

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Yuan, Jintao; Yu, Shuling; Zhang, Ting; Yuan, Xuejie; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

2016-06-01

Octanol/water (K(OW)) and octanol/air (K(OA)) partition coefficients are two important physicochemical properties of organic substances. In current practice, K(OW) and K(OA) values of some polychlorinated biphenyls (PCBs) are measured using generator column method. Quantitative structure-property relationship (QSPR) models can serve as a valuable alternative method of replacing or reducing experimental steps in the determination of K(OW) and K(OA). In this paper, two different methods, i.e., multiple linear regression based on dragon descriptors and hologram quantitative structure-activity relationship, were used to predict generator-column-derived log K(OW) and log K(OA) values of PCBs. The predictive ability of the developed models was validated using a test set, and the performances of all generated models were compared with those of three previously reported models. All results indicated that the proposed models were robust and satisfactory and can thus be used as alternative models for the rapid assessment of the K(OW) and K(OA) of PCBs. Copyright © 2016 Elsevier Inc. All rights reserved.

Characterization of Mixtures. Part 2: QSPR Models for Prediction of Excess Molar Volume and Liquid Density Using Neural Networks.

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Ajmani, Subhash; Rogers, Stephen C; Barley, Mark H; Burgess, Andrew N; Livingstone, David J

2010-09-17

In our earlier work, we have demonstrated that it is possible to characterize binary mixtures using single component descriptors by applying various mixing rules. We also showed that these methods were successful in building predictive QSPR models to study various mixture properties of interest. Here in, we developed a QSPR model of an excess thermodynamic property of binary mixtures i.e. excess molar volume (V(E) ). In the present study, we use a set of mixture descriptors which we earlier designed to specifically account for intermolecular interactions between the components of a mixture and applied successfully to the prediction of infinite-dilution activity coefficients using neural networks (part 1 of this series). We obtain a significant QSPR model for the prediction of excess molar volume (V(E) ) using consensus neural networks and five mixture descriptors. We find that hydrogen bond and thermodynamic descriptors are the most important in determining excess molar volume (V(E) ), which is in line with the theory of intermolecular forces governing excess mixture properties. The results also suggest that the mixture descriptors utilized herein may be sufficient to model a wide variety of properties of binary and possibly even more complex mixtures. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ant colony optimization as a descriptor selection in QSPR modeling: Estimation of the λmax of anthraquinones-based dyes

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Morteza Atabati

2016-09-01

Full Text Available Quantitative structure–property relationship (QSPR studies based on ant colony optimization (ACO were carried out for the prediction of λmax of 9,10-anthraquinone derivatives. ACO is a meta-heuristic algorithm, which is derived from the observation of real ants and proposed to feature selection. After optimization of 3D geometry of structures by the semi-empirical quantum-chemical calculation at AM1 level, different descriptors were calculated by the HyperChem and Dragon softwares (1514 descriptors. A major problem of QSPR is the high dimensionality of the descriptor space; therefore, descriptor selection is the most important step. In this paper, an ACO algorithm was used to select the best descriptors. Then selected descriptors were applied for model development using multiple linear regression. The average absolute relative deviation and correlation coefficient for the calibration set were obtained as 3.3% and 0.9591, respectively, while the average absolute relative deviation and correlation coefficient for the prediction set were obtained as 5.0% and 0.9526, respectively. The results showed that the applied procedure is suitable for prediction of λmax of 9,10-anthraquinone derivatives.

QSAR, QSPR and QSRR in Terms of 3-D-MoRSE Descriptors for In Silico Screening of Clofibric Acid Analogues.

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Di Tullio, Maurizio; Maccallini, Cristina; Ammazzalorso, Alessandra; Giampietro, Letizia; Amoroso, Rosa; De Filippis, Barbara; Fantacuzzi, Marialuigia; Wiczling, Paweł; Kaliszan, Roman

2012-07-01

A series of 27 analogues of clofibric acid, mostly heteroarylalkanoic derivatives, have been analyzed by a novel high-throughput reversed-phase HPLC method employing combined gradient of eluent's pH and organic modifier content. The such determined hydrophobicity (lipophilicity) parameters, log kw , and acidity constants, pKa , were subjected to multiple regression analysis to get a QSRR (Quantitative StructureRetention Relationships) and a QSPR (Quantitative Structure-Property Relationships) equation, respectively, describing these pharmacokinetics-determining physicochemical parameters in terms of the calculation chemistry derived structural descriptors. The previously determined in vitro log EC50 values - transactivation activity towards PPARα (human Peroxisome Proliferator-Activated Receptor α) - have also been described in a QSAR (Quantitative StructureActivity Relationships) equation in terms of the 3-D-MoRSE descriptors (3D-Molecule Representation of Structures based on Electron diffraction descriptors). The QSAR model derived can serve for an a priori prediction of bioactivity in vitro of any designed analogue, whereas the QSRR and the QSPR models can be used to evaluate lipophilicity and acidity, respectively, of the compounds, and hence to rational guide selection of structures of proper pharmacokinetics. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling adsorption of brominated, chlorinated and mixed bromo/chloro-dibenzo-p-dioxins on C60 fullerene using Nano-QSPR

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Piotr Urbaszek

2017-03-01

Full Text Available Many technological implementations in the field of nanotechnology have involved carbon nanomaterials, including fullerenes such as the buckminsterfullerene, C60. The unprecedented properties of such organic nanomaterials (in particular their large surface area gained extensive attention for their potential use as organic pollutant sorbents. Sorption interactions can be very hazardous and useful at the same time. This work investigates the influence of halogenation by bromine and/or chlorine in dibenzo-p-dioxins on their sorption ability on the C60 fullerene surface. Halogenated dibenzo-p-dioxins (PXDDs, where X = Br or Cl are ever-present in the environment and accidently produced in many technological processes in only approximately known quantities. If all combinatorial Br and/or Cl dioxin substitution possibilities are present in the environment, the experimental characterization and investigation of sorbent effectiveness is more than difficult. In this work, we have developed a quantitative structure–property relationship (QSPR model (R2 = 0.998, predicting the adsorption energy [kcal/mol] for 1,701 PXDDs adsorbed on C60 (PXDD@C60. Based on the QSPR model reported herein, we concluded that the lowest energy PXDD@C60 complexes are those that the World Health Organization (WHO considers to be less dangerous with respect to the aryl hydrocarbon receptor (AhR toxicity mechanism. Therefore, the effectiveness of fullerenes as sorbent agents may be underestimated as sorption could be less effective for toxic congeners than previously believed.

QSPR Models for Predicting Log Pliver Values for Volatile Organic Compounds Combining Statistical Methods and Domain Knowledge

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Mónica F. Díaz

2012-12-01

Full Text Available Volatile organic compounds (VOCs are contained in a variety of chemicals that can be found in household products and may have undesirable effects on health. Thereby, it is important to model blood-to-liver partition coefficients (log Pliver for VOCs in a fast and inexpensive way. In this paper, we present two new quantitative structure-property relationship (QSPR models for the prediction of log Pliver, where we also propose a hybrid approach for the selection of the descriptors. This hybrid methodology combines a machine learning method with a manual selection based on expert knowledge. This allows obtaining a set of descriptors that is interpretable in physicochemical terms. Our regression models were trained using decision trees and neural networks and validated using an external test set. Results show high prediction accuracy compared to previous log Pliver models, and the descriptor selection approach provides a means to get a small set of descriptors that is in agreement with theoretical understanding of the target property.

Quantitative Structure–Property Relationship (QSPR Models for a Local Quantum Descriptor: Investigation of the 4- and 3-Substituted-Cinnamic Acid Esterification

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Cláudio E. Rodrigues-Santos

2015-09-01

Full Text Available In this work, the theoretical description of the 4- and 3-substituted-cinnamic acid esterification with different electron donating and electron withdrawing groups was performed at the B3LYP and M06-2X levels, as a two-step process: the O-protonation and the nucleophile attack by ethanol. In parallel, an experimental work devoted to the synthesis and characterization of the substituted-cinnamate esters has also been performed. In order to quantify the substituents effects, quantitative structure–property relationship (QSPR models based on the atomic charges, Fukui functions and the Frontier Effective-for-Reaction Molecular Orbitals (FERMO energies were investigated. In fact, the Fukui functions, ƒ+C and ƒ−O, indicated poor correlations for each individual step, and in contrast with the general literature, the O-protonation step is affected both by the FERMO energies and the O-charges of the carbonyl group. Since the process was shown to not be totally described by either charge- or frontier-orbitals, it is proposed to be frontier-charge-miscere controlled. Moreover, the observed trend for the experimental reaction yields suggests that the electron withdrawing groups favor the reaction and the same was observed for Step 2, which can thus be pointed out as the determining step.

A QSPR STUDY OF NORMAL BOILING POINT OF ORGANIC COMPOUNDS (ALIPHATIC ALKANES USING MOLECULAR DESCRIPTORS

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B. Souyei

2013-12-01

Full Text Available A quantitative structure–property relationship (QSPR study is carried out to develop correlations that relate the molecular structures of organic compounds (Aliphatic Alkanes to their normal boiling point (NBP and two correlations were proposed for constitutionals and connectivity indices Models. The correlations are simple in application with good accuracy, which provide an easy, direct and relatively accurate way to calculate NBP. Such calculation gives us a model that gives results in remarkable correlations with the descriptors of blokes constitutionals (CON, and connectivity indices (CI (R2 = 0.950, δ = 0.766 (R2 = 0.969, δ = 0.782 respectively.

Ant colony optimization as a descriptor selection in QSPR modeling: Estimation of the λmax of anthraquinones-based dyes

OpenAIRE

Morteza Atabati; Kobra Zarei; Azam Borhani

2016-01-01

Quantitative structure–property relationship (QSPR) studies based on ant colony optimization (ACO) were carried out for the prediction of λmax of 9,10-anthraquinone derivatives. ACO is a meta-heuristic algorithm, which is derived from the observation of real ants and proposed to feature selection. After optimization of 3D geometry of structures by the semi-empirical quantum-chemical calculation at AM1 level, different descriptors were calculated by the HyperChem and Dragon softwares (1514 des...

QSPR study of solvent quenching of the 5D 0 → 7F 2 emission of Eu(6,6,7,7,8,8,8-heptafluoro-2,2-dimethyl-3,5-octanedionate) 3

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Mercader, Andrew G.; Duchowicz, Pablo R.; Fernández, Francisco M.; Castro, Eduardo A.; Wolcan, Ezequiel

2008-09-01

We performed a predictive analysis, based on quantitative structure-property relationships (QSPR), of the luminescence lifetime ( τ) of Eu(fod) 3 in different solvents. The Eu(fod) 3 luminescent properties have been helpful as replacements for radioactivity, alternatives to standard fluorescent dyes and donors in energy transfer experiments, and are gaining expanding applications in wide variety of bioanalytical assays. Our best QSPR linear model constructed from 23 molecular structures combines four molecular descriptors, selected from more than a thousand geometrical, topological, quantum-mechanical and electronic types of descriptors.

QSPR models of n-octanol/water partition coefficients and aqueous solubility of halogenated methyl-phenyl ethers by DFT method.

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Zeng, Xiao-Lan; Wang, Hong-Jun; Wang, Yan

2012-02-01

The possible molecular geometries of 134 halogenated methyl-phenyl ethers were optimized at B3LYP/6-31G(*) level with Gaussian 98 program. The calculated structural parameters were taken as theoretical descriptors to establish two new novel QSPR models for predicting aqueous solubility (-lgS(w,l)) and n-octanol/water partition coefficient (lgK(ow)) of halogenated methyl-phenyl ethers. The two models achieved in this work both contain three variables: energy of the lowest unoccupied molecular orbital (E(LUMO)), most positive atomic partial charge in molecule (q(+)), and quadrupole moment (Q(yy) or Q(zz)), of which R values are 0.992 and 0.970 respectively, their standard errors of estimate in modeling (SD) are 0.132 and 0.178, respectively. The results of leave-one-out (LOO) cross-validation for training set and validation with external test sets both show that the models obtained exhibited optimum stability and good predictive power. We suggests that two QSPR models derived here can be used to predict S(w,l) and K(ow) accurately for non-tested halogenated methyl-phenyl ethers congeners. Copyright © 2011 Elsevier Ltd. All rights reserved.

QSPR studies for predicting polarity parameter of organic compounds in methanol using support vector machine and enhanced replacement method.

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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.

A 2D-QSPR approach to predict blood-brain barrier penetration of drugs acting on the central nervous system

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Matheus Malta de Sá

2010-12-01

Full Text Available Drugs acting on the central nervous system (CNS have to cross the blood-brain barrier (BBB in order to perform their pharmacological actions. Passive BBB diffusion can be partially expressed by the blood/brain partition coefficient (logBB. As the experimental evaluation of logBB is time and cost consuming, theoretical methods such as quantitative structure-property relationships (QSPR can be useful to predict logBB values. In this study, a 2D-QSPR approach was applied to a set of 28 drugs acting on the CNS, using the logBB property as biological data. The best QSPR model [n = 21, r = 0.94 (r² = 0.88, s = 0.28, and Q² = 0.82] presented three molecular descriptors: calculated n-octanol/water partition coefficient (ClogP, polar surface area (PSA, and polarizability (α. Six out of the seven compounds from the test set were well predicted, which corresponds to good external predictability (85.7%. These findings can be helpful to guide future approaches regarding those molecular descriptors which must be considered for estimating the logBB property, and also for predicting the BBB crossing ability for molecules structurally related to the investigated set.Fármacos que atuam no sistema nervoso central (SNC devem atravessar a barreira hematoencefálica (BHE para exercerem suas ações farmacológicas. A difusão passiva através da BHE pode ser parcialmente expressa pelo coeficiente de partição entre os compartimentos encefálico e sanguíneo (logBB, brain/blood partition coefficient. Considerando-se que a avaliação experimental de logBB é dispendiosa e demorada, métodos teóricos como estudos das relações entre estrutura química e propriedade (QSPR, Quantitative Structure-Property Relationships podem ser utilizados na previsão dos valores de logBB. Neste estudo, uma abordagem de QSPR-2D foi aplicada a um conjunto de 28 moléculas com ação central, usando logBB como propriedade biológica. O melhor modelo de QSPR [n = 21, r = 0,94 (r

QSPR study of the retention/release property of odorant molecules in pectin gels using statistical methods

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Assia Belhassan

2017-11-01

Full Text Available The ACD/ChemSketch, MarvinSketch, and ChemOffice programmes were used to calculate several molecular descriptors of 51 odorant molecules (15 alcohols, 11 aldehydes, 9 ketones and 16 esters. The best descriptors were selected to establish the Quantitative Structure-Property Relationship (QSPR of the retention/release property of odorant molecules in pectin gels using Principal Components Analysis (PCA, Multiple Linear Regression (MLR, Multiple Non-linear Regression (MNLR and Artificial Neural Network (ANN methods We propose a quantitative model based on these analyses. PCA has been used to select descriptors that exhibit high correlation with the retention/release property. The MLR method yielded correlation coefficients of 0.960 and 0.958 for PG-0.4 (pectin concentration: 0.4% w/w and PG-0.8 (pectin concentration: 0.8% w/w media, respectively. Internal and external validations were used to determine the statistical quality of the QSPR of the two MLR models. The MNLR method, considering the relevant descriptors obtained from the MLR, yielded correlation coefficients of 0.978 and 0.975 for PG-0.4 and PG-0.8 media, respectively. The applicability domain of MLR models was investigated using simple and leverage approaches to detect outliers and outside compounds. The effects of different descriptors on the retention/release property are described, and these descriptors were used to study and design new compounds with higher and lower values of the property than the existing ones. Keywords: Odorant Molecules, Retention/Release, Pectin Gels, Quantitative Structure Property Relationship, Multiple Linear Regression, Artificial Neural Network

Prediction of boiling points of organic compounds by QSPR tools.

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Dai, Yi-min; Zhu, Zhi-ping; Cao, Zhong; Zhang, Yue-fei; Zeng, Ju-lan; Li, Xun

2013-07-01

The novel electro-negativity topological descriptors of YC, WC were derived from molecular structure by equilibrium electro-negativity of atom and relative bond length of molecule. The quantitative structure-property relationships (QSPR) between descriptors of YC, WC as well as path number parameter P3 and the normal boiling points of 80 alkanes, 65 unsaturated hydrocarbons and 70 alcohols were obtained separately. The high-quality prediction models were evidenced by coefficient of determination (R(2)), the standard error (S), average absolute errors (AAE) and predictive parameters (Qext(2),RCV(2),Rm(2)). According to the regression equations, the influences of the length of carbon backbone, the size, the degree of branching of a molecule and the role of functional groups on the normal boiling point were analyzed. Comparison results with reference models demonstrated that novel topological descriptors based on the equilibrium electro-negativity of atom and the relative bond length were useful molecular descriptors for predicting the normal boiling points of organic compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

2D Quantitative Structure-Property Relationship Study of Mycotoxins by Multiple Linear Regression and Support Vector Machine

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Fereshteh Shiri

2010-08-01

Full Text Available In the present work, support vector machines (SVMs and multiple linear regression (MLR techniques were used for quantitative structure–property relationship (QSPR studies of retention time (tR in standardized liquid chromatography–UV–mass spectrometry of 67 mycotoxins (aflatoxins, trichothecenes, roquefortines and ochratoxins based on molecular descriptors calculated from the optimized 3D structures. By applying missing value, zero and multicollinearity tests with a cutoff value of 0.95, and genetic algorithm method of variable selection, the most relevant descriptors were selected to build QSPR models. MLRand SVMs methods were employed to build QSPR models. The robustness of the QSPR models was characterized by the statistical validation and applicability domain (AD. The prediction results from the MLR and SVM models are in good agreement with the experimental values. The correlation and predictability measure by r2 and q2 are 0.931 and 0.932, repectively, for SVM and 0.923 and 0.915, respectively, for MLR. The applicability domain of the model was investigated using William’s plot. The effects of different descriptors on the retention times are described.

Random Forest Approach to QSPR Study of Fluorescence Properties Combining Quantum Chemical Descriptors and Solvent Conditions.

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Chen, Chia-Hsiu; Tanaka, Kenichi; Funatsu, Kimito

2018-04-22

The Quantitative Structure - Property Relationship (QSPR) approach was performed to study the fluorescence absorption wavelengths and emission wavelengths of 413 fluorescent dyes in different solvent conditions. The dyes included the chromophore derivatives of cyanine, xanthene, coumarin, pyrene, naphthalene, anthracene and etc., with the wavelength ranging from 250 nm to 800 nm. An ensemble method, random forest (RF), was employed to construct nonlinear prediction models compared with the results of linear partial least squares and nonlinear support vector machine regression models. Quantum chemical descriptors derived from density functional theory method and solvent information were also used by constructing models. The best prediction results were obtained from RF model, with the squared correlation coefficients [Formula: see text] of 0.940 and 0.905 for λ abs and λ em , respectively. The descriptors used in the models were discussed in detail in this report by comparing the feature importance of RF.

The Interplay between QSAR/QSPR Studiesand Partial Order Ranking and Formal Concept Analyses

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Lars Carlsen

2009-04-01

Full Text Available The often observed scarcity of physical-chemical and well as toxicological data hampers the assessment of potentially hazardous chemicals released to the environment. In such cases Quantitative Structure-Activity Relationships/Quantitative Structure-Property Relationships (QSAR/QSPR constitute an obvious alternative for rapidly, effectively and inexpensively generatng missing experimental values. However, typically further treatment of the data appears necessary, e.g., to elucidate the possible relations between the single compounds as well as implications and associations between the various parameters used for the combined characterization of the compounds under investigation. In the present paper the application of QSAR/QSPR in combination with Partial Order Ranking (POR methodologies will be reviewed and new aspects using Formal Concept Analysis (FCA will be introduced. Where POR constitutes an attractive method for, e.g., prioritizing a series of chemical substances based on a simultaneous inclusion of a range of parameters, FCA gives important information on the implications associations between the parameters. The combined approach thus constitutes an attractive method to a preliminary assessment of the impact on environmental and human health by primary pollutants or possibly by a primary pollutant well as a possible suite of transformation subsequent products that may be both persistent in and bioaccumulating and toxic.The present review focus on the environmental – and human health impact by residuals of the rocket fuel 1,1-dimethyl- hydrazine (heptyl and its transformation products as an illustrative example.

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

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Long Jiao

2015-05-01

Full Text Available The quantitative structure property relationship (QSPR for the boiling point (Tb of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs was investigated. The molecular distance-edge vector (MDEV index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR and artificial neural network (ANN, respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

Quantitative relationships for the prediction of the vapor pressure of some hydrocarbons from the van der Waals molecular surface

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Olariu Tudor

2015-01-01

Full Text Available A quantitative structure - property relationship (QSPR modeling of vapor pressure at 298.15 K, expressed as log (VP / Pa was performed for a series of 84 hydrocarbons (63 alkanes and 21 cycloalkanes using the van der Waals (vdW surface area, SW/Å2, calculated by the Monte Carlo method, as the molecular descriptor. The QSPR model developed from the subset of 63 alkanes (C1-C16, deemed as the training set, was successfully used for the prediction of the log (VP / Pa values of the 21 cycloalkanes, which was the external prediction (test subset. A QSPR model was also developed for a series composed of all 84 hydrocarbons. Both QSPR models were statistically tested for their ability to fit the data and for prediction. The results showed that the vdW molecular surface used as molecular descriptor (MD explains the variance of the majority of the log (VP / Pa values in this series of 84 hydrocarbons. This MD describes very well the intermolecular forces that hold neutral molecules together. The clear physical meaning of the molecular surface values, SW/Å2, could explain the success of the QSPR models obtained with a single structural molecular descriptor.

Considerations of nano-QSAR/QSPR models for nanopesticide risk assessment within the European legislative framework.

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Villaverde, Juan José; Sevilla-Morán, Beatriz; López-Goti, Carmen; Alonso-Prados, José Luis; Sandín-España, Pilar

2018-09-01

The European market for pesticides is currently legislated through the well-developed Regulation (EC) No. 1107/2009. This regulation promotes the competitiveness of European agriculture, recognizing the necessity of safe pesticides for human and animal health and the environment to protect crops against pests, diseases and weeds. In this sense, nanotechnology can provide a tremendous opportunity to achieve a more rational use of pesticides. However, the lack of information regarding nanopesticides and their fate and behavior in the environment and their effects on human and animal health is inhibiting rapid nanopesticide incorporation into European Union agriculture. This review analyzes the recent state of knowledge on nanopesticide risk assessment, highlighting the challenges that need to be overcame to accelerate the arrival of these new tools for plant protection to European agricultural professionals. Novel nano-Quantitative Structure-Activity/Structure-Property Relationship (nano-QSAR/QSPR) tools for risk assessment are analyzed, including modeling methods and validation procedures towards the potential of these computational instruments to meet the current requirements for authorization of nanoformulations. Future trends on these issues, of pressing importance within the context of the current European pesticide legislative framework, are also discussed. Standard protocols to make high-quality and well-described datasets for the series of related but differently sized nanoparticles/nanopesticides are required. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Prediction of the maximum absorption wavelength of azobenzene dyes by QSPR tools

Science.gov (United States)

Xu, Xuan; Luan, Feng; Liu, Huitao; Cheng, Jianbo; Zhang, Xiaoyun

2011-12-01

The maximum absorption wavelength ( λmax) of a large data set of 191 azobenzene dyes was predicted by quantitative structure-property relationship (QSPR) tools. The λmax was correlated with the 4 molecular descriptors calculated from the structure of the dyes alone. The multiple linear regression method (MLR) and the non-linear radial basis function neural network (RBFNN) method were applied to develop the models. The statistical parameters provided by the MLR model were R2 = 0.893, Radj2=0.893, qLOO2=0.884, F = 1214.871, RMS = 11.6430 for the training set; and R2 = 0.849, Radj2=0.845, qext2=0.846, F = 207.812, RMS = 14.0919 for the external test set. The RBFNN model gave even improved statistical results: R2 = 0.920, Radj2=0.919, qLOO2=0.898, F = 1664.074, RMS = 9.9215 for the training set, and R2 = 0.895, Radj2=0.892, qext2=0.895, F = 314.256, RMS = 11.6427 for the external test set. This theoretical method provides a simple, precise and an alternative method to obtain λmax of azobenzene dyes.

Solvent Extraction and QSPR of Catecholamines with a Bis(2-ethlhexyl) Hydrogen Phosphate

Energy Technology Data Exchange (ETDEWEB)

Yoshizuka, Kazuharu.; Fujimoto, Yuko.; Ota, Keisuke.; Inoue, Katsutoshi. [Saga University, Saga (Japan). Dept. of Applied Chemistry

1999-02-01

In order to develop an effective separation recess for catecholamine (CA), a basic investigation on solvent extraction of dopamine (DA), adrenaline (Ad) and noradrenaline (NA) from hydrochloric acid solution and their stripping is conducted at 30 degree C employing bis(2-ethylhexyl) hydrogen phosphate (D2EHPA) in chloroform, n-hexane and toluene as the organic diluents. From the dependencies of the distribution ratios on the concentrations of reactant species, i.e. CA, hydrogen ion and D2EHPA, it is elucidated that CA (RNH{sub 2}) is extracted with D2EHPA (HR`) according to the ion exchange mechanism, as the complex type, RNH{sub 3}R` (HR`){sub 3}, and the equilibrium constants (K{sub ex,CA}) for the extraction reactions are also evaluated. The quantitative structure property relationship (QSPR) of K{sub ex,CA} values for each organic diluent is discussed using molecular modeling with semi-empirical molecular orbital calculations considering the solvent effect. (author)

Field determination and QSPR prediction of equilibrium-status soil/vegetation partition coefficient of PCDD/Fs.

Science.gov (United States)

Li, Li; Wang, Qiang; Qiu, Xinghua; Dong, Yian; Jia, Shenglan; Hu, Jianxin

2014-07-15

Characterizing pseudo equilibrium-status soil/vegetation partition coefficient KSV, the quotient of respective concentrations in soil and vegetation of a certain substance at remote background areas, is essential in ecological risk assessment, however few previous attempts have been made for field determination and developing validated and reproducible structure-based estimates. In this study, KSV was calculated based on measurements of seventeen 2,3,7,8-substituted PCDD/F congeners in soil and moss (Dicranum angustum), and rouzi grass (Thylacospermum caespitosum) of two background sites, Ny-Ålesund of the Arctic and Zhangmu-Nyalam region of the Tibet Plateau, respectively. By both fugacity modeling and stepwise regression of field data, the air-water partition coefficient (KAW) and aqueous solubility (SW) were identified as the influential physicochemical properties. Furthermore, validated quantitative structure-property relationship (QSPR) model was developed to extrapolate the KSV prediction to all 210 PCDD/F congeners. Molecular polarizability, molecular size and molecular energy demonstrated leading effects on KSV. Copyright © 2014 Elsevier B.V. All rights reserved.

Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies.

Science.gov (United States)

Manoharan, Prabu; Vijayan, R S K; Ghoshal, Nanda

2010-10-01

The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by GlaxoSmithKline Pharmaceuticals as potential anti-Alzheimer agents. To address the issue of target selectivity, a major confounding factor in the development of selective BACE1 inhibitors, FB-QSSR models were developed using the reported off target activity values. A heat map constructed, based on the activity and selectivity profile of the individual R-group fragments, and was in turn used to identify superior R-group fragments. Further, simultaneous optimization of multiple properties, an issue encountered in real-world drug discovery scenario, and often overlooked in QSAR approaches, was addressed using a Multi Objective (MO-QSPR) method that balances properties, based on the defined objectives. MO-QSPR was implemented using Derringer and Suich desirability algorithm to identify the optimal level of independent variables (X) that could confer a trade-off between selectivity and activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields) studies. To exemplify the potentials of FB-QSAR and MO-QSPR in a pragmatic fashion, the insights gleaned from the MO-QSPR study was reverse engineered using Inverse-QSAR in a combinatorial fashion to enumerate some prospective novel, potent and selective BACE1 inhibitors.

Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies

Science.gov (United States)

Manoharan, Prabu; Vijayan, R. S. K.; Ghoshal, Nanda

2010-10-01

The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by GlaxoSmithKline Pharmaceuticals as potential anti-Alzheimer agents. To address the issue of target selectivity, a major confounding factor in the development of selective BACE1 inhibitors, FB-QSSR models were developed using the reported off target activity values. A heat map constructed, based on the activity and selectivity profile of the individual R-group fragments, and was in turn used to identify superior R-group fragments. Further, simultaneous optimization of multiple properties, an issue encountered in real-world drug discovery scenario, and often overlooked in QSAR approaches, was addressed using a Multi Objective (MO-QSPR) method that balances properties, based on the defined objectives. MO-QSPR was implemented using Derringer and Suich desirability algorithm to identify the optimal level of independent variables ( X) that could confer a trade-off between selectivity and activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields) studies. To exemplify the potentials of FB-QSAR and MO-QSPR in a pragmatic fashion, the insights gleaned from the MO-QSPR study was reverse engineered using Inverse-QSAR in a combinatorial fashion to enumerate some prospective novel, potent and selective BACE1 inhibitors.

Computational modeling of human oral bioavailability: what will be next?

Science.gov (United States)

Cabrera-Pérez, Miguel Ángel; Pham-The, Hai

2018-06-01

The oral route is the most convenient way of administrating drugs. Therefore, accurate determination of oral bioavailability is paramount during drug discovery and development. Quantitative structure-property relationship (QSPR), rule-of-thumb (RoT) and physiologically based-pharmacokinetic (PBPK) approaches are promising alternatives to the early oral bioavailability prediction. Areas covered: The authors give insight into the factors affecting bioavailability, the fundamental theoretical framework and the practical aspects of computational methods for predicting this property. They also give their perspectives on future computational models for estimating oral bioavailability. Expert opinion: Oral bioavailability is a multi-factorial pharmacokinetic property with its accurate prediction challenging. For RoT and QSPR modeling, the reliability of datasets, the significance of molecular descriptor families and the diversity of chemometric tools used are important factors that define model predictability and interpretability. Likewise, for PBPK modeling the integrity of the pharmacokinetic data, the number of input parameters, the complexity of statistical analysis and the software packages used are relevant factors in bioavailability prediction. Although these approaches have been utilized independently, the tendency to use hybrid QSPR-PBPK approaches together with the exploration of ensemble and deep-learning systems for QSPR modeling of oral bioavailability has opened new avenues for development promising tools for oral bioavailability prediction.

QSPR study of absorption maxima of organic dyes for dye-sensitized solar cells based on 3D descriptors

Science.gov (United States)

Xu, Jie; Zhang, Hui; Wang, Lei; Liang, Guijie; Wang, Luoxin; Shen, Xiaolin; Xu, Weilin

2010-07-01

A quantitative structure-property relationship (QSPR) study was performed for the prediction of the absorption maxima ( λmax) of organic dyes for dye-sensitized solar cells (DSSCs). The entire set of 70 dyes was divided into a training set of 53 dyes and a test set of 17 dyes according to Kennard and Stones algorithm. Three-dimensional (3D) descriptors were calculated to represent the dye molecules. A ten-descriptor model, with a squared correlation coefficient ( R2) of 0.9543 and a standard error of estimation ( s) of 14.7 nm, was produced by using the stepwise multilinear regression analysis (MLRA) on the training set. The reliability of the proposed model was further illustrated using various evaluation techniques: leave-one-out cross-validation procedure, randomization tests, and validation through the external test set. All descriptors involved in the model were derived solely from the chemical structure of the dye molecules, which makes the model very useful to estimate the λmax of dyes before they are actually synthesized.

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

Energy Technology Data Exchange (ETDEWEB)

Ghasemi, Jahan B.; Zolfonoun, Ehsan [Toosi University of Technology, Tehran (Korea, Republic of)

2012-05-15

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

International Nuclear Information System (INIS)

Ghasemi, Jahan B.; Zolfonoun, Ehsan

2012-01-01

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms

An approach to the interpretation of backpropagation neural network models in QSAR studies.

Science.gov (United States)

Baskin, I I; Ait, A O; Halberstam, N M; Palyulin, V A; Zefirov, N S

2002-03-01

An approach to the interpretation of backpropagation neural network models for quantitative structure-activity and structure-property relationships (QSAR/QSPR) studies is proposed. The method is based on analyzing the first and second moments of distribution of the values of the first and the second partial derivatives of neural network outputs with respect to inputs calculated at data points. The use of such statistics makes it possible not only to obtain actually the same characteristics as for the case of traditional "interpretable" statistical methods, such as the linear regression analysis, but also to reveal important additional information regarding the non-linear character of QSAR/QSPR relationships. The approach is illustrated by an example of interpreting a backpropagation neural network model for predicting position of the long-wave absorption band of cyane dyes.

3D-QSPR Method of Computational Technique Applied on Red Reactive Dyes by Using CoMFA Strategy

Directory of Open Access Journals (Sweden)

Shahnaz Perveen

2011-12-01

Full Text Available Cellulose fiber is a tremendous natural resource that has broad application in various productions including the textile industry. The dyes, which are commonly used for cellulose printing, are “reactive dyes” because of their high wet fastness and brilliant colors. The interaction of various dyes with the cellulose fiber depends upon the physiochemical properties that are governed by specific features of the dye molecule. The binding pattern of the reactive dye with cellulose fiber is called the ligand-receptor concept. In the current study, the three dimensional quantitative structure property relationship (3D-QSPR technique was applied to understand the red reactive dyes interactions with the cellulose by the Comparative Molecular Field Analysis (CoMFA method. This method was successfully utilized to predict a reliable model. The predicted model gives satisfactory statistical results and in the light of these, it was further analyzed. Additionally, the graphical outcomes (contour maps help us to understand the modification pattern and to correlate the structural changes with respect to the absorptivity. Furthermore, the final selected model has potential to assist in understanding the charachteristics of the external test set. The study could be helpful to design new reactive dyes with better affinity and selectivity for the cellulose fiber.

3D-QSPR method of computational technique applied on red reactive dyes by using CoMFA strategy.

Science.gov (United States)

Mahmood, Uzma; Rashid, Sitara; Ali, S Ishrat; Parveen, Rasheeda; Zaheer-Ul-Haq; Ambreen, Nida; Khan, Khalid Mohammed; Perveen, Shahnaz; Voelter, Wolfgang

2011-01-01

Cellulose fiber is a tremendous natural resource that has broad application in various productions including the textile industry. The dyes, which are commonly used for cellulose printing, are "reactive dyes" because of their high wet fastness and brilliant colors. The interaction of various dyes with the cellulose fiber depends upon the physiochemical properties that are governed by specific features of the dye molecule. The binding pattern of the reactive dye with cellulose fiber is called the ligand-receptor concept. In the current study, the three dimensional quantitative structure property relationship (3D-QSPR) technique was applied to understand the red reactive dyes interactions with the cellulose by the Comparative Molecular Field Analysis (CoMFA) method. This method was successfully utilized to predict a reliable model. The predicted model gives satisfactory statistical results and in the light of these, it was further analyzed. Additionally, the graphical outcomes (contour maps) help us to understand the modification pattern and to correlate the structural changes with respect to the absorptivity. Furthermore, the final selected model has potential to assist in understanding the characteristics of the external test set. The study could be helpful to design new reactive dyes with better affinity and selectivity for the cellulose fiber.

Development of Quantitative Structure-Property Relationship Models for Self-Emulsifying Drug Delivery System of 2-Aryl Propionic Acid NSAIDs

Directory of Open Access Journals (Sweden)

Chen-Wen Li

2011-01-01

Full Text Available We developed the quantative structure-property relationships (QSPRs models to correlate the molecular structures of surfactant, cosurfactant, oil, and drug with the solubility of poorly water-soluble 2-aryl propionic acid nonsteroidal anti-inflammatory drugs (2-APA-NSAIDs in self-emulsifying drug delivery systems (SEDDSs. The compositions were encoded with electronic, geometrical, topological, and quantum chemical descriptors. To obtain reliable predictions, we used multiple linear regression (MLR and artificial neural network (ANN methods for model development. The obtained equations were validated using a test set of 42 formulations and showed a great predictive power, and linear models were found to be better than nonlinear ones. The obtained QSPR models would greatly facilitate fast screening for the optimal formulations of SEDDS at the early stage of drug development and minimize experimental effort.

Quantitative Structure-Retention Relationships (QSRR) for Chromatographic Separation of Disazo and Trisazo 4,4'-Diaminobenzanilide-based Dyes

OpenAIRE

Funar-Timofei, Simona; Fabian, Walter M. F.; Simu, Georgeta M.; Suzukic, Takahiro

2006-01-01

For a series of 23 disazo and trisazo 4,4'-diaminobenzanilide-based direct dye molecules, thechromatographic mobilities, extrapolated to modifier-free conditions (RM0 values), were determinedfrom reverse-phase thin-layer chromatography (RP-TLC) experiments. Traditional and rational QSAR/QSPR modelling techniques have been applied to find a quantitative structure-retention relationship (QSRR) for the dyes. Molecular dye structures were energy minimized by both molecular mechanics and quantum c...

Power Conversion Efficiency of Arylamine Organic Dyes for Dye-Sensitized Solar Cells (DSSCs Explicit to Cobalt Electrolyte: Understanding the Structural Attributes Using a Direct QSPR Approach

Directory of Open Access Journals (Sweden)

Supratik Kar

2016-12-01

Full Text Available Post silicon solar cell era involves light-absorbing dyes for dye-sensitized solar systems (DSSCs. Therefore, there is great interest in the design of competent organic dyes for DSSCs with high power conversion efficiency (PCE to bypass some of the disadvantages of silicon-based solar cell technologies, such as high cost, heavy weight, limited silicon resources, and production methods that lead to high environmental pollution. The DSSC has the unique feature of a distance-dependent electron transfer step. This depends on the relative position of the sensitized organic dye in the metal oxide composite system. In the present work, we developed quantitative structure-property relationship (QSPR models to set up the quantitative relationship between the overall PCE and quantum chemical molecular descriptors. They were calculated from density functional theory (DFT and time-dependent DFT (TD-DFT methods as well as from DRAGON software. This allows for understanding the basic electron transfer mechanism along with the structural attributes of arylamine-organic dye sensitizers for the DSSCs explicit to cobalt electrolyte. The identified properties and structural fragments are particularly valuable for guiding time-saving synthetic efforts for development of efficient arylamine organic dyes with improved power conversion efficiency.

Quantitative structure-property relationships for octanol-water partition coefficients of polybrominated diphenyl ethers.

Science.gov (United States)

Li, Linnan; Xie, Shaodong; Cai, Hao; Bai, Xuetao; Xue, Zhao

2008-08-01

Theoretical molecular descriptors were tested against logK(OW) values for polybrominated diphenyl ethers (PBDEs) using the Partial Least-Squares Regression method which can be used to analyze data with many variables and few observations. A quantitative structure-property relationship (QSPR) model was successfully developed with a high cross-validated value (Q(cum)(2)) of 0.961, indicating a good predictive ability and stability of the model. The predictive power of the QSPR model was further cross-validated. The values of logK(OW) for PBDEs are mainly governed by molecular surface area, energy of the lowest unoccupied molecular orbital and the net atomic charges on the oxygen atom. All these descriptors have been discussed to interpret the partitioning mechanism of PBDE chemicals. The bulk property of the molecules represented by molecular surface area is the leading factor, and K(OW) values increase with the increase of molecular surface area. Higher energy of the lowest unoccupied molecular orbital and higher net atomic charge on the oxygen atom of PBDEs result in smaller K(OW). The energy of the lowest unoccupied molecular orbital and the net atomic charge on PBDEs oxygen also play important roles in affecting the partition of PBDEs between octanol and water by influencing the interactions between PBDEs and solvent molecules.

Adsorption of s-triazines onto polybenzimidazole: A quantitative structure-property relationship investigation

Energy Technology Data Exchange (ETDEWEB)

D' Archivio, Angelo Antonio, E-mail: angeloantonio.darchivio@univaq.it [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi dell' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy); Incani, Angela; Mazzeo, Pietro; Ruggieri, Fabrizio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi dell' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)

2009-09-21

The adsorption of 25 symmetric triazines (s-triazines) on polybenzimidazole (PBI) beads is investigated under equilibrium (batch) conditions. The observed adsorption isotherms of the selected compounds are accurately described by the Freundlich model, while the agreement between the Langmuir model and the experimental data is moderately worse, which seems to reflect the heterogeneous meso- and micro-porosity of PBI and polydispersion in the interaction mechanism. Methylthio- and methoxytriazines exhibit a greater adsorption tendency as compared with chlorotriazines, moreover, progressive dealkylation of amino groups results in a progressive increase of triazine uptake on PBI. Based on these evidences, the adsorption mechanism seems to be governed by a combination of {pi}-{pi} and hydrogen-bonding interactions. Genetic algorithm (GA) variable selection and multilinear regression (MLR) are combined in order to describe the effect of triazine structure on the extraction performance of PBI according to the quantitative structure-property relationship (QSPR) method. q{sub max}, the amount of triazine adsorbed per weight unit of PBI assuming homogeneous monolayer (Langmuir) mechanism, exhibits a great variability within the set of investigated triazines and is the quantity here modelled by QSPR. On the other hand, the Freundlich constant, K{sub F}, which expresses the adsorption efficiency under multilayer heterogeneous conditions, even if markedly increases passing from chloro- to methylthio- or methoxytriazines, is less noticeably affected by the fine details of the adsorbate structure, as the number or nature of alkyl fragments bound to the amino groups. To quantitatively relate q{sub max} with the triazine structure GA-MLR analysis is performed on the set of 1664 theoretical molecular descriptors provided by the software Dragon. Finally, a four-dimensional QSPR model is selected based on leave-one-out cross-validation and its prediction ability is further tested on

Adsorption of s-triazines onto polybenzimidazole: A quantitative structure-property relationship investigation

International Nuclear Information System (INIS)

D'Archivio, Angelo Antonio; Incani, Angela; Mazzeo, Pietro; Ruggieri, Fabrizio

2009-01-01

The adsorption of 25 symmetric triazines (s-triazines) on polybenzimidazole (PBI) beads is investigated under equilibrium (batch) conditions. The observed adsorption isotherms of the selected compounds are accurately described by the Freundlich model, while the agreement between the Langmuir model and the experimental data is moderately worse, which seems to reflect the heterogeneous meso- and micro-porosity of PBI and polydispersion in the interaction mechanism. Methylthio- and methoxytriazines exhibit a greater adsorption tendency as compared with chlorotriazines, moreover, progressive dealkylation of amino groups results in a progressive increase of triazine uptake on PBI. Based on these evidences, the adsorption mechanism seems to be governed by a combination of π-π and hydrogen-bonding interactions. Genetic algorithm (GA) variable selection and multilinear regression (MLR) are combined in order to describe the effect of triazine structure on the extraction performance of PBI according to the quantitative structure-property relationship (QSPR) method. q max , the amount of triazine adsorbed per weight unit of PBI assuming homogeneous monolayer (Langmuir) mechanism, exhibits a great variability within the set of investigated triazines and is the quantity here modelled by QSPR. On the other hand, the Freundlich constant, K F , which expresses the adsorption efficiency under multilayer heterogeneous conditions, even if markedly increases passing from chloro- to methylthio- or methoxytriazines, is less noticeably affected by the fine details of the adsorbate structure, as the number or nature of alkyl fragments bound to the amino groups. To quantitatively relate q max with the triazine structure GA-MLR analysis is performed on the set of 1664 theoretical molecular descriptors provided by the software Dragon. Finally, a four-dimensional QSPR model is selected based on leave-one-out cross-validation and its prediction ability is further tested on four

Computational models for structure-hydrophobicity relationships of 4-carboxyl-2,6-dinitrophenyl azo hydroxynaphthalenes.

Science.gov (United States)

Idowu, Olakunle S; Adegoke, Olajire A; Idowu, Abiola; Olaniyi, Ajibola A

2007-01-01

Some phenyl azo hydroxynaphthalene dyes (e.g., sunset yellow) are certified as approved colorants for food, cosmetics, and drug formulations. The hydrophobicity of 4 newly synthesized azo dyes of the phenyl azo hydroxynaphthalene class was investigated, as a training set, with the goal of developing models for quantitative structure-property relationships (QSPR). Retention behavior of the molecules reversed-phase thin-layer chromatography (RPTLC) was investigated using liquid paraffin-coated silica gel as the stationary phase. Mobile phases consisted of aqueous mixtures of methanol, acetone, and dimethylformamide (DMF). Basic hydrophobicity parameter (Rmw), specific hydrophobic surface area (S), and isocratic chromatographic hydrophobicity index (phio) were computed from the chromatographic data. The hydrophobicity index (Rm) decreased linearly with increasing concentration of organic modifiers. Extrapolated Rmw values obtained by using DMF and acetone differ significantly from the value obtained by using methanol as organic modifier [P dyes and may also play useful roles in computer-assisted molecular discovery of nontoxic azo dyes.

Excited States and Photodebromination of Selected Polybrominated Diphenyl Ethers: Computational and Quantitative Structure—Property Relationship Studies

Directory of Open Access Journals (Sweden)

Jin Luo

2015-01-01

Full Text Available This paper presents a density functional theory (DFT/time-dependent DFT (TD-DFT study on the lowest lying singlet and triplet excited states of 20 selected polybrominateddiphenyl ether (PBDE congeners, with the solvation effect included in the calculations using the polarized continuum model (PCM. The results obtained showed that for most of the brominated diphenyl ether (BDE congeners, the lowest singlet excited state was initiated by the electron transfer from HOMO to LUMO, involving a π–σ* excitation. In triplet excited states, structure of the BDE congeners differed notably from that of the BDE ground states with one of the specific C–Br bonds bending off the aromatic plane. In addition, the partial least squares regression (PLSR, principal component analysis-multiple linear regression analysis (PCA-MLR, and back propagation artificial neural network (BP-ANN approaches were employed for a quantitative structure-property relationship (QSPR study. Based on the previously reported kinetic data for the debromination by ultraviolet (UV and sunlight, obtained QSPR models exhibited a reasonable evaluation of the photodebromination reactivity even when the BDE congeners had same degree of bromination, albeit different patterns of bromination.

Advances in the replacement and enhanced replacement method in QSAR and QSPR theories.

Science.gov (United States)

Mercader, Andrew G; Duchowicz, Pablo R; Fernández, Francisco M; Castro, Eduardo A

2011-07-25

The selection of an optimal set of molecular descriptors from a much greater pool of such regression variables is a crucial step in the development of QSAR and QSPR models. The aim of this work is to further improve this important selection process. For this reason three different alternatives for the initial steps of our recently developed enhanced replacement method (ERM) and replacement method (RM) are proposed. These approaches had previously proven to yield near optimal results with a much smaller number of linear regressions than the full search. The algorithms were tested on four different experimental data sets, formed by collections of 116, 200, 78, and 100 experimental records from different compounds and 1268, 1338, 1187, and 1306 molecular descriptors, respectively. The comparisons showed that one of the new alternatives further improves the ERM, which has shown to be superior to genetic algorithms for the selection of an optimal set of molecular descriptors from a much greater pool. The new proposed alternative also improves the simpler and the lower computational demand algorithm RM.

Quantitative structure-property relationships of electroluminescent ...

Indian Academy of Sciences (India)

Thus, support vector machine is a good method to build QSPR models to predict the ... For high-quality OLED dis- ... it provides a guide to the development process and speeds up ... The free software ChemSketch 12.0 was used to draw 2-D.

Modeling the Dispersibility of Single Walled Carbon Nanotubes in Organic Solvents by Quantitative Structure-Activity Relationship Approach

Science.gov (United States)

Yilmaz, Hayriye; Rasulev, Bakhtiyor; Leszczynski, Jerzy

2015-01-01

The knowledge of physico-chemical properties of carbon nanotubes, including behavior in organic solvents is very important for design, manufacturing and utilizing of their counterparts with improved properties. In the present study a quantitative structure-activity/property relationship (QSAR/QSPR) approach was applied to predict the dispersibility of single walled carbon nanotubes (SWNTs) in various organic solvents. A number of additive descriptors and quantum-chemical descriptors were calculated and utilized to build QSAR models. The best predictability is shown by a 4-variable model. The model showed statistically good results (R2training = 0.797, Q2 = 0.665, R2test = 0.807), with high internal and external correlation coefficients. Presence of the X0Av descriptor and its negative term suggest that small size solvents have better SWCNTs solubility. Mass weighted descriptor ATS6m also indicates that heavier solvents (and small in size) most probably are better solvents for SWCNTs. The presence of the Dipole Z descriptor indicates that higher polarizability of the solvent molecule increases the solubility. The developed model and contributed descriptors can help to understand the mechanism of the dispersion process and predictorganic solvents that improve the dispersibility of SWNTs. PMID:28347035

Modeling the Dispersibility of Single Walled Carbon Nanotubes in Organic Solvents by Quantitative Structure-Activity Relationship Approach

Directory of Open Access Journals (Sweden)

Hayriye Yilmaz

2015-05-01

Full Text Available The knowledge of physico-chemical properties of carbon nanotubes, including behavior in organic solvents is very important for design, manufacturing and utilizing of their counterparts with improved properties. In the present study a quantitative structure-activity/property relationship (QSAR/QSPR approach was applied to predict the dispersibility of single walled carbon nanotubes (SWNTs in various organic solvents. A number of additive descriptors and quantum-chemical descriptors were calculated and utilized to build QSAR models. The best predictability is shown by a 4-variable model. The model showed statistically good results (R2training = 0.797, Q2 = 0.665, R2test = 0.807, with high internal and external correlation coefficients. Presence of the X0Av descriptor and its negative term suggest that small size solvents have better SWCNTs solubility. Mass weighted descriptor ATS6m also indicates that heavier solvents (and small in size most probably are better solvents for SWCNTs. The presence of the Dipole Z descriptor indicates that higher polarizability of the solvent molecule increases the solubility. The developed model and contributed descriptors can help to understand the mechanism of the dispersion process and predictorganic solvents that improve the dispersibility of SWNTs.

Rational Formulation of Alternative Fuels using QSPR Methods: Application to Jet Fuels Développement d’un outil d’aide à la formulation des carburants alternatifs utilisant des méthodes QSPR (Quantitative Structure Property Relationship: application aux carburéacteurs

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Saldana D.A.

2013-06-01

Full Text Available Alternative fuels are a promising solution for road transport but also for aircraft. In the aviation field, a huge amount of work has been done in the past years with the approval to use up to 50 % by volume of SPK (Synthetic Paraffinic Kerosene in blends with conventional fossil Jet A-1. SPK are Fischer-Tropsch (FT fuels but also Hydroprocessed Esters and Fatty Acids (HEFA. However, these alternative fuels can have different chemical properties depending on the process used for their production. These properties include normal to iso paraffin ratio, carbon chain length and level of branching. R&D studies of alternative fuels are based on the evaluation of products coming from identified production processes. However, it appears that a better way of studying them could be firstly to determine the best chemical composition regarding aviation problems and secondly to find the best process and finishing process in order to obtain such a product. The objective of this work is to design a tool that aims to guide the future formulation of alternative fuels for aviation through the prediction of targeted physical properties. Thus, it is proposed to apply a methodology that identifies relationships between the structure and properties of a molecule (QSPR for Quantitative Structure Property Relationship, with the aim of establishing predictive models. These models will be built for hydrocarbons (normal and iso paraffins, naphthenes, aromatics, etc. and oxygenated compounds (esters and alcohols. For aviation, oxygenated compounds are not considered as a drop-in fuel. It could be seen as a disruptive solution in a long term view. There are concerns with oxygenates in aviation that are covered in this paper such as the flash point but others such as the energetic content, the water affinity that are not taken into account in this paper. The properties currently studied are flash point, cetane number, density and viscosity. The data sets will contain data

Towards the Development of Global Nano-Quantitative Structure–Property Relationship Models: Zeta Potentials of Metal Oxide Nanoparticles

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Andrey A. Toropov

2018-04-01

Full Text Available Zeta potential indirectly reflects a charge of the surface of nanoparticles in solutions and could be used to represent the stability of the colloidal solution. As processes of synthesis, testing and evaluation of new nanomaterials are expensive and time-consuming, so it would be helpful to estimate an approximate range of properties for untested nanomaterials using computational modeling. We collected the largest dataset of zeta potential measurements of bare metal oxide nanoparticles in water (87 data points. The dataset was used to develop quantitative structure–property relationship (QSPR models. Essential features of nanoparticles were represented using a modified simplified molecular input line entry system (SMILES. SMILES strings reflected the size-dependent behavior of zeta potentials, as the considered quasi-SMILES modification included information about both chemical composition and the size of the nanoparticles. Three mathematical models were generated using the Monte Carlo method, and their statistical quality was evaluated (R2 for the training set varied from 0.71 to 0.87; for the validation set, from 0.67 to 0.82; root mean square errors for both training and validation sets ranged from 11.3 to 17.2 mV. The developed models were analyzed and linked to aggregation effects in aqueous solutions.

Quantitative structure-property relationship study of n-octanol-water partition coefficients of some of diverse drugs using multiple linear regression

International Nuclear Information System (INIS)

Ghasemi, Jahanbakhsh; Saaidpour, Saadi

2007-01-01

A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structures of 150 drug organic compounds to their n-octanol-water partition coefficients (log P o/w ). Molecular descriptors derived solely from 3D structures of the molecular drugs. A genetic algorithm was also applied as a variable selection tool in QSPR analysis. The models were constructed using 110 molecules as training set, and predictive ability tested using 40 compounds. Modeling of log P o/w of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR). Four descriptors for these compounds molecular volume (MV) (geometrical), hydrophilic-lipophilic balance (HLB) (constitutional), hydrogen bond forming ability (HB) (electronic) and polar surface area (PSA) (electrostatic) are taken as inputs for the model. The use of descriptors calculated only from molecular structure eliminates the need for experimental determination of properties for use in the correlation and allows for the estimation of log P o/w for molecules not yet synthesized. Application of the developed model to a testing set of 40 drug organic compounds demonstrates that the model is reliable with good predictive accuracy and simple formulation. The prediction results are in good agreement with the experimental value. The root mean square error of prediction (RMSEP) and square correlation coefficient (R 2 ) for MLR model were 0.22 and 0.99 for the prediction set log P o/w

Models for risk assessment of reactive chemicals in aquatic toxicology

NARCIS (Netherlands)

Freidig, Andreas Peter

2000-01-01

A quantitative structure property relationship (QSPR) for a,b-unsaturated carboxylates (mainly acrylates and methacrylates) was established in chapter 2. Chemical reaction rate constants were measured for 12 different chemicals with three different nucleophiles, namely H 2 O, OH - and glutathione

A primer on QSAR/QSPR modeling fundamental concepts

CERN Document Server

Roy, Kunal; Das, Rudra Narayan

2015-01-01

This brief goes back to basics and describes the Quantitative structure-activity/property relationships (QSARs/QSPRs) that represent predictive models derived from the application of statistical tools correlating biological activity (including therapeutic and toxic) and properties of chemicals (drugs/toxicants/environmental pollutants) with descriptors representative of molecular structure and/or properties. It explains how the sub-discipline of Cheminformatics is used for many applications such as risk assessment, toxicity prediction, property prediction and regulatory decisions apart from drug discovery and lead optimization. The authors also present, in basic terms, how QSARs and related chemometric tools are extensively involved in medicinal chemistry, environmental chemistry and agricultural chemistry for ranking of potential compounds and prioritizing experiments. At present, there is no standard or introductory publication available that introduces this important topic to students of chemistry and phar...

The application of feature selection to the development of Gaussian process models for percutaneous absorption.

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Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P

2010-06-01

The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it

QUANTITATIVE ANALYSIS OF RELATIONSHIP STRUCTURE AND ANIONIC SURFACTANT MICELLE CONCENTRATION CRITIC WITH SEMIEMPIRIS AM1

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Eva Vaulina Yulistia Delsy

2017-05-01

Full Text Available This research determines the mathematical equation which calculate the Concentration Micelle Critic theoretical anionic surfactant. The research was conducted the depiction of each surfactant anionic three-dimensional compound models, followed by optimizing the model structure anionic surfactant by using AM1 calculation method. Furthermore the calculation of descriptors (QSPR method, then it was analyzed statistically using Multiple Linear Regression (MLR. The results of statistical calculations showed that to calculate the theoretical CMC anionic surfactant can use the QSPR equation: log CMC = 4.157+0.118qC1+7.698qC2+0.425α–0.010µ-0.129RD–0.138 log P+0.021BM–0.034Avdw, n = 100 ; r = 0.927 ; r2 = 0.860 ; SE = 0.352 ; F= 30.888 ; PRESS = 23.506

Estimating persistence of brominated and chlorinated organic pollutants in air, water, soil, and sediments with the QSPR-based classification scheme.

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Puzyn, T; Haranczyk, M; Suzuki, N; Sakurai, T

2011-02-01

We have estimated degradation half-lives of both brominated and chlorinated dibenzo-p-dioxins (PBDDs and PCDDs), furans (PBDFs and PCDFs), biphenyls (PBBs and PCBs), naphthalenes (PBNs and PCNs), diphenyl ethers (PBDEs and PCDEs) as well as selected unsubstituted polycyclic aromatic hydrocarbons (PAHs) in air, surface water, surface soil, and sediments (in total of 1,431 compounds in four compartments). Next, we compared the persistence between chloro- (relatively well-studied) and bromo- (less studied) analogs. The predictions have been performed based on the quantitative structure-property relationship (QSPR) scheme with use of k-nearest neighbors (kNN) classifier and the semi-quantitative system of persistence classes. The classification models utilized principal components derived from the principal component analysis of a set of 24 constitutional and quantum mechanical descriptors as input variables. Accuracies of classification (based on an external validation) were 86, 85, 87, and 75% for air, surface water, surface soil, and sediments, respectively. The persistence of all chlorinated species increased with increasing halogenation degree. In the case of brominated organic pollutants (Br-OPs), the trend was the same for air and sediments. However, we noticed that the opposite trend for persistence in surface water and soil. The results suggest that, due to high photoreactivity of C-Br chemical bonds, photolytic processes occurring in surface water and soil are able to play significant role in transforming and removing Br-OPs from these compartments. This contribution is the first attempt of classifying together Br-OPs and Cl-OPs according to their persistence, in particular, environmental compartments.

Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

Science.gov (United States)

Fernandez, Michael; Boyd, Peter G; Daff, Thomas D; Aghaji, Mohammad Zein; Woo, Tom K

2014-09-04

In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar). The models were tested on a large set of 292 050 MOFs that were not part of the training set. The QSPR classifier could recover 945 of the top 1000 MOFs in the test set while flagging only 10% of the whole library for compute intensive screening. Thus, using the machine learning classifiers as part of a high-throughput screening protocol would result in an order of magnitude reduction in compute time and allow intractably large structure libraries and search spaces to be screened.

Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines

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Luckhana Lawtrakul

2009-05-01

Full Text Available The Particle Swarm Optimization (PSO and Support Vector Machines (SVMs approaches are used for predicting the thermodynamic parameters for the 1:1 inclusion complexation of chiral guests with β-cyclodextrin. A PSO is adopted for descriptor selection in the quantitative structure-property relationships (QSPR of a dataset of 74 chiral guests due to its simplicity, speed, and consistency. The modified PSO is then combined with SVMs for its good approximating properties, to generate a QSPR model with the selected features. Linear, polynomial, and Gaussian radial basis functions are used as kernels in SVMs. All models have demonstrated an impressive performance with R2 higher than 0.8.

Event-based criteria in GT-STAF information indices: theory, exploratory diversity analysis and QSPR applications.

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Barigye, S J; Marrero-Ponce, Y; Martínez López, Y; Martínez Santiago, O; Torrens, F; García Domenech, R; Galvez, J

2013-01-01

Versatile event-based approaches for the definition of novel information theory-based indices (IFIs) are presented. An event in this context is the criterion followed in the "discovery" of molecular substructures, which in turn serve as basis for the construction of the generalized incidence and relations frequency matrices, Q and F, respectively. From the resultant F, Shannon's, mutual, conditional and joint entropy-based IFIs are computed. In previous reports, an event named connected subgraphs was presented. The present study is an extension of this notion, in which we introduce other events, namely: terminal paths, vertex path incidence, quantum subgraphs, walks of length k, Sach's subgraphs, MACCs, E-state and substructure fingerprints and, finally, Ghose and Crippen atom-types for hydrophobicity and refractivity. Moreover, we define magnitude-based IFIs, introducing the use of the magnitude criterion in the definition of mutual, conditional and joint entropy-based IFIs. We also discuss the use of information-theoretic parameters as a measure of the dissimilarity of codified structural information of molecules. Finally, a comparison of the statistics for QSPR models obtained with the proposed IFIs and DRAGON's molecular descriptors for two physicochemical properties log P and log K of 34 derivatives of 2-furylethylenes demonstrates similar to better predictive ability than the latter.

Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 1. Evaluation and Adaptation of GastroPlus To Predict Bioavailability of Medchem Series.

Science.gov (United States)

Daga, Pankaj R; Bolger, Michael B; Haworth, Ian S; Clark, Robert D; Martin, Eric J

2018-03-05

When medicinal chemists need to improve bioavailability (%F) within a chemical series during lead optimization, they synthesize new series members with systematically modified properties mainly by following experience and general rules of thumb. More quantitative models that predict %F of proposed compounds from chemical structure alone have proven elusive. Global empirical %F quantitative structure-property (QSPR) models perform poorly, and projects have too little data to train local %F QSPR models. Mechanistic oral absorption and physiologically based pharmacokinetic (PBPK) models simulate the dissolution, absorption, systemic distribution, and clearance of a drug in preclinical species and humans. Attempts to build global PBPK models based purely on calculated inputs have not achieved the optimization. In this work, local GastroPlus PBPK models are instead customized for individual medchem series. The key innovation was building a local QSPR for a numerically fitted effective intrinsic clearance (CL loc ). All inputs are subsequently computed from structure alone, so the models can be applied in advance of synthesis. Training CL loc on the first 15-18 rat %F measurements gave adequate predictions, with clear improvements up to about 30 measurements, and incremental improvements beyond that.

Cheminformatics Modeling of Amine Solutions for Assessing their CO2 Absorption Properties.

Science.gov (United States)

Kuenemann, Melaine A; Fourches, Denis

2017-07-01

As stricter regulations on CO 2 emissions are adopted worldwide, identifying efficient chemical processes to capture and recycle CO 2 is of critical importance for industry. The most common process known as amine scrubbing suffers from the lack of available amine solutions capable of capturing CO 2 efficiently. Tertiary amines characterized by low heats of reaction are considered good candidates but their absorption properties can significantly differ from one analogue to another despite high structural similarity. Herein, after collecting and curating experimental data from the literature, we have built a modeling set of 41 amine structures with their absorption properties. Then we analyzed their chemical composition using molecular descriptors and non-supervised clustering. Furthermore, we developed a series of quantitative structure-property relationships (QSPR) to assess amines' CO 2 absorption properties from their structural characteristics. These models afforded reasonable prediction performances (e. g., Q 2 LOO =0.63 for CO 2 absorption amount) even though they are solely based on 2D chemical descriptors and individual machine learning techniques (random forest and neural network). Overall, we believe the chemical analysis and the series of QSPR models presented in this proof-of-concept study represent new knowledge and innovative tools that could be very useful for screening and prioritizing hypothetical amines to be synthesized and tested experimentally for their CO 2 absorption properties. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genetic algorithm as a variable selection procedure for the simulation of 13C nuclear magnetic resonance spectra of flavonoid derivatives using multiple linear regression.

Science.gov (United States)

Ghavami, Raoof; Najafi, Amir; Sajadi, Mohammad; Djannaty, Farhad

2008-09-01

In order to accurately simulate (13)C NMR spectra of hydroxy, polyhydroxy and methoxy substituted flavonoid a quantitative structure-property relationship (QSPR) model, relating atom-based calculated descriptors to (13)C NMR chemical shifts (ppm, TMS=0), is developed. A dataset consisting of 50 flavonoid derivatives was employed for the present analysis. A set of 417 topological, geometrical, and electronic descriptors representing various structural characteristics was calculated and separate multilinear QSPR models were developed between each carbon atom of flavonoid and the calculated descriptors. Genetic algorithm (GA) and multiple linear regression analysis (MLRA) were used to select the descriptors and to generate the correlation models. Analysis of the results revealed a correlation coefficient and root mean square error (RMSE) of 0.994 and 2.53ppm, respectively, for the prediction set.

OPERA models for predicting physicochemical properties and environmental fate endpoints.

Science.gov (United States)

Mansouri, Kamel; Grulke, Chris M; Judson, Richard S; Williams, Antony J

2018-03-08

The collection of chemical structure information and associated experimental data for quantitative structure-activity/property relationship (QSAR/QSPR) modeling is facilitated by an increasing number of public databases containing large amounts of useful data. However, the performance of QSAR models highly depends on the quality of the data and modeling methodology used. This study aims to develop robust QSAR/QSPR models for chemical properties of environmental interest that can be used for regulatory purposes. This study primarily uses data from the publicly available PHYSPROP database consisting of a set of 13 common physicochemical and environmental fate properties. These datasets have undergone extensive curation using an automated workflow to select only high-quality data, and the chemical structures were standardized prior to calculation of the molecular descriptors. The modeling procedure was developed based on the five Organization for Economic Cooperation and Development (OECD) principles for QSAR models. A weighted k-nearest neighbor approach was adopted using a minimum number of required descriptors calculated using PaDEL, an open-source software. The genetic algorithms selected only the most pertinent and mechanistically interpretable descriptors (2-15, with an average of 11 descriptors). The sizes of the modeled datasets varied from 150 chemicals for biodegradability half-life to 14,050 chemicals for logP, with an average of 3222 chemicals across all endpoints. The optimal models were built on randomly selected training sets (75%) and validated using fivefold cross-validation (CV) and test sets (25%). The CV Q 2 of the models varied from 0.72 to 0.95, with an average of 0.86 and an R 2 test value from 0.71 to 0.96, with an average of 0.82. Modeling and performance details are described in QSAR model reporting format and were validated by the European Commission's Joint Research Center to be OECD compliant. All models are freely available as an open

Using Combined Computational Techniques to Predict the Glass Transition Temperatures of Aromatic Polybenzoxazines

Science.gov (United States)

Mhlanga, Phumzile; Wan Hassan, Wan Aminah; Hamerton, Ian; Howlin, Brendan J.

2013-01-01

The Molecular Operating Environment software (MOE) is used to construct a series of benzoxazine monomers for which a variety of parameters relating to the structures (e.g. water accessible surface area, negative van der Waals surface area, hydrophobic volume and the sum of atomic polarizabilities, etc.) are obtained and quantitative structure property relationships (QSPR) models are formulated. Three QSPR models (formulated using up to 5 descriptors) are first used to make predictions for the initiator data set (n = 9) and compared to published thermal data; in all of the QSPR models there is a high level of agreement between the actual data and the predicted data (within 0.63–1.86 K of the entire dataset). The water accessible surface area is found to be the most important descriptor in the prediction of Tg. Molecular modelling simulations of the benzoxazine polymer (minus initiator) carried out at the same time using the Materials Studio software suite provide an independent prediction of Tg. Predicted Tg values from molecular modelling fall in the middle of the range of the experimentally determined Tg values, indicating that the structure of the network is influenced by the nature of the initiator used. Hence both techniques can provide predictions of glass transition temperatures and provide complementary data for polymer design. PMID:23326419

Using combined computational techniques to predict the glass transition temperatures of aromatic polybenzoxazines.

Directory of Open Access Journals (Sweden)

Phumzile Mhlanga

Full Text Available The Molecular Operating Environment software (MOE is used to construct a series of benzoxazine monomers for which a variety of parameters relating to the structures (e.g. water accessible surface area, negative van der Waals surface area, hydrophobic volume and the sum of atomic polarizabilities, etc. are obtained and quantitative structure property relationships (QSPR models are formulated. Three QSPR models (formulated using up to 5 descriptors are first used to make predictions for the initiator data set (n = 9 and compared to published thermal data; in all of the QSPR models there is a high level of agreement between the actual data and the predicted data (within 0.63-1.86 K of the entire dataset. The water accessible surface area is found to be the most important descriptor in the prediction of T(g. Molecular modelling simulations of the benzoxazine polymer (minus initiator carried out at the same time using the Materials Studio software suite provide an independent prediction of T(g. Predicted T(g values from molecular modelling fall in the middle of the range of the experimentally determined T(g values, indicating that the structure of the network is influenced by the nature of the initiator used. Hence both techniques can provide predictions of glass transition temperatures and provide complementary data for polymer design.

A quantitative structure- property relationship of gas chromatographic/mass spectrometric retention data of 85 volatile organic compounds as air pollutant materials by multivariate methods

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Sarkhosh Maryam

2012-05-01

Full Text Available Abstract A quantitative structure-property relationship (QSPR study is suggested for the prediction of retention times of volatile organic compounds. Various kinds of molecular descriptors were calculated to represent the molecular structure of compounds. Modeling of retention times of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR and artificial neural network (ANN. The stepwise regression was used for the selection of the variables which gives the best-fitted models. After variable selection ANN, MLR methods were used with leave-one-out cross validation for building the regression models. The prediction results are in very good agreement with the experimental values. MLR as the linear regression method shows good ability in the prediction of the retention times of the prediction set. This provided a new and effective method for predicting the chromatography retention index for the volatile organic compounds.

Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.

Science.gov (United States)

Murrell, Daniel S; Cortes-Ciriano, Isidro; van Westen, Gerard J P; Stott, Ian P; Bender, Andreas; Malliavin, Thérèse E; Glen, Robert C

2015-01-01

In silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process. camb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both advanced and beginner R users. camb's capabilities include the standardisation of chemical structure representation, computation of 905 one-dimensional and 14 fingerprint type descriptors for small molecules, 8 types of amino acid descriptors, 13 whole protein sequence descriptors, filtering methods for feature selection, generation of predictive models (using an interface to the R package caret), as well as techniques to create model ensembles using techniques from the R package caretEnsemble). Results can be visualised through high-quality, customisable plots (R package ggplot2). Overall, camb constitutes an open-source framework to perform the following steps: (1) compound standardisation, (2) molecular and protein descriptor calculation, (3) descriptor pre-processing and model training, visualisation and validation, and (4) bioactivity/property prediction for new molecules. camb aims to speed model generation, in order to provide reproducibility and tests of robustness. QSPR and proteochemometric case studies are included which demonstrate camb's application.Graphical abstractFrom compounds and data to models: a complete model building workflow in one package.

Modeling the binding affinity of structurally diverse industrial chemicals to carbon using the artificial intelligence approaches.

Science.gov (United States)

Gupta, Shikha; Basant, Nikita; Rai, Premanjali; Singh, Kunwar P

2015-11-01

Binding affinity of chemical to carbon is an important characteristic as it finds vast industrial applications. Experimental determination of the adsorption capacity of diverse chemicals onto carbon is both time and resource intensive, and development of computational approaches has widely been advocated. In this study, artificial intelligence (AI)-based ten different qualitative and quantitative structure-property relationship (QSPR) models (MLPN, RBFN, PNN/GRNN, CCN, SVM, GEP, GMDH, SDT, DTF, DTB) were established for the prediction of the adsorption capacity of structurally diverse chemicals to activated carbon following the OECD guidelines. Structural diversity of the chemicals and nonlinear dependence in the data were evaluated using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. The generalization and prediction abilities of the constructed models were established through rigorous internal and external validation procedures performed employing a wide series of statistical checks. In complete dataset, the qualitative models rendered classification accuracies between 97.04 and 99.93%, while the quantitative models yielded correlation (R(2)) values of 0.877-0.977 between the measured and the predicted endpoint values. The quantitative prediction accuracies for the higher molecular weight (MW) compounds (class 4) were relatively better than those for the low MW compounds. Both in the qualitative and quantitative models, the Polarizability was the most influential descriptor. Structural alerts responsible for the extreme adsorption behavior of the compounds were identified. Higher number of carbon and presence of higher halogens in a molecule rendered higher binding affinity. Proposed QSPR models performed well and outperformed the previous reports. A relatively better performance of the ensemble learning models (DTF, DTB) may be attributed to the strengths of the bagging and boosting algorithms which enhance the predictive accuracies. The

Robust modelling of solubility in supercritical carbon dioxide using Bayesian methods.

Science.gov (United States)

Tarasova, Anna; Burden, Frank; Gasteiger, Johann; Winkler, David A

2010-04-01

Two sparse Bayesian methods were used to derive predictive models of solubility of organic dyes and polycyclic aromatic compounds in supercritical carbon dioxide (scCO(2)), over a wide range of temperatures (285.9-423.2K) and pressures (60-1400 bar): a multiple linear regression employing an expectation maximization algorithm and a sparse prior (MLREM) method and a non-linear Bayesian Regularized Artificial Neural Network with a Laplacian Prior (BRANNLP). A randomly selected test set was used to estimate the predictive ability of the models. The MLREM method resulted in a model of similar predictivity to the less sparse MLR method, while the non-linear BRANNLP method created models of substantially better predictivity than either the MLREM or MLR based models. The BRANNLP method simultaneously generated context-relevant subsets of descriptors and a robust, non-linear quantitative structure-property relationship (QSPR) model for the compound solubility in scCO(2). The differences between linear and non-linear descriptor selection methods are discussed. (c) 2009 Elsevier Inc. All rights reserved.

Molecular structure-adsorption study on current textile dyes.

Science.gov (United States)

Örücü, E; Tugcu, G; Saçan, M T

2014-01-01

This study was performed to investigate the adsorption of a diverse set of textile dyes onto granulated activated carbon (GAC). The adsorption experiments were carried out in a batch system. The Langmuir and Freundlich isotherm models were applied to experimental data and the isotherm constants were calculated for 33 anthraquinone and azo dyes. The adsorption equilibrium data fitted more adequately to the Langmuir isotherm model than the Freundlich isotherm model. Added to a qualitative analysis of experimental results, multiple linear regression (MLR), support vector regression (SVR) and back propagation neural network (BPNN) methods were used to develop quantitative structure-property relationship (QSPR) models with the novel adsorption data. The data were divided randomly into training and test sets. The predictive ability of all models was evaluated using the test set. Descriptors were selected with a genetic algorithm (GA) using QSARINS software. Results related to QSPR models on the adsorption capacity of GAC showed that molecular structure of dyes was represented by ionization potential based on two-dimensional topological distances, chromophoric features and a property filter index. Comparison of the performance of the models demonstrated the superiority of the BPNN over GA-MLR and SVR models.

Filling the gap: Estimating physicochemical properties of the full array of polybrominated diphenyl ethers (PBDEs)

International Nuclear Information System (INIS)

Yue, Chaoyang; Li, Loretta Y.

2013-01-01

Physicochemical properties of PBDE congeners are important for modeling their transport, but data are often missing. The quantitative structure–property relationship (QSPR) approach is utilized to fill this gap. Individual research groups often report piecemeal properties through experimental measurements or estimation techniques, but these data seldom satisfy fundamental thermodynamic relationships because of errors. The data then lack internal consistency and cannot be used directly in environmental modeling. This paper critically reviews published experimental data to select the best QSPR models, which are then extended to all 209 PBDE congeners. Properties include aqueous solubility, vapor pressure, Henry's law constant, octanol–water partition coefficient and octanol–air partition coefficient. Their values are next adjusted to satisfy fundamental thermodynamic equations. The resulting values then take advantage of all measurements and provide quick references for modeling and PBDE-contaminated site assessment and remediation. PCBs are also compared with respect to their properties and estimation methods. -- Highlights: •Property data of PBDEs and reported experimental and estimation methods were reviewed. •Missing data were estimated for all 209 PBDEs based on selected methods. •All data were adjusted to meet thermodynamic constrains using a VisualBasic program. •The established database provides a quick reference for PBDE environmental modeling. -- Through careful selection of literature data, structure–property estimation and adjustment, key properties of 209 PBDE congeners are estimated with internal consistency

Bond-based linear indices of the non-stochastic and stochastic edge-adjacency matrix. 1. Theory and modeling of ChemPhys properties of organic molecules.

Science.gov (United States)

Marrero-Ponce, Yovani; Martínez-Albelo, Eugenio R; Casañola-Martín, Gerardo M; Castillo-Garit, Juan A; Echevería-Díaz, Yunaimy; Zaldivar, Vicente Romero; Tygat, Jan; Borges, José E Rodriguez; García-Domenech, Ramón; Torrens, Francisco; Pérez-Giménez, Facundo

2010-11-01

Novel bond-level molecular descriptors are proposed, based on linear maps similar to the ones defined in algebra theory. The kth edge-adjacency matrix (E(k)) denotes the matrix of bond linear indices (non-stochastic) with regard to canonical basis set. The kth stochastic edge-adjacency matrix, ES(k), is here proposed as a new molecular representation easily calculated from E(k). Then, the kth stochastic bond linear indices are calculated using ES(k) as operators of linear transformations. In both cases, the bond-type formalism is developed. The kth non-stochastic and stochastic total linear indices are calculated by adding the kth non-stochastic and stochastic bond linear indices, respectively, of all bonds in molecule. First, the new bond-based molecular descriptors (MDs) are tested for suitability, for the QSPRs, by analyzing regressions of novel indices for selected physicochemical properties of octane isomers (first round). General performance of the new descriptors in this QSPR studies is evaluated with regard to the well-known sets of 2D/3D MDs. From the analysis, we can conclude that the non-stochastic and stochastic bond-based linear indices have an overall good modeling capability proving their usefulness in QSPR studies. Later, the novel bond-level MDs are also used for the description and prediction of the boiling point of 28 alkyl-alcohols (second round), and to the modeling of the specific rate constant (log k), partition coefficient (log P), as well as the antibacterial activity of 34 derivatives of 2-furylethylenes (third round). The comparison with other approaches (edge- and vertices-based connectivity indices, total and local spectral moments, and quantum chemical descriptors as well as E-state/biomolecular encounter parameters) exposes a good behavior of our method in this QSPR studies. Finally, the approach described in this study appears to be a very promising structural invariant, useful not only for QSPR studies but also for similarity

Self-Models and Relationship Threat

Directory of Open Access Journals (Sweden)

Máire B. Ford

2015-07-01

Full Text Available This study investigated a key claim of risk regulation theory, namely, that psychological internalizing of a relationship threat will serve as a mediator of the link between self-models (self-esteem and attachment anxiety and relationship responses (moving closer to a partner vs. distancing from a partner. Participants (N = 101 received feedback that threatened their current romantic relationship (or no feedback and then completed measures of internal–external focus, relationship closeness–distancing, and acceptance–rejection of the feedback. Results showed that participants with negative self-models responded to the relationship threat by becoming more internally focused and by distancing from their partners, whereas those with positive self-models became more externally focused and moved closer to their partners. Mediation analyses indicated that the link between self-models and relationship closeness–distancing was partially explained by internal focus.

Structure-retention and mobile phase-retention relationships for reversed-phase high-performance liquid chromatography of several hydroxythioxanthone derivatives in binary acetonitrile-water mixtures

International Nuclear Information System (INIS)

Amiri, Ali Asghar; Hemmateenejad, Bahram; Safavi, Afsaneh; Sharghi, Hashem; Beni, Ali Reza Salimi; Shamsipur, Mojtaba

2007-01-01

The reversed-phase high-performance liquid chromatographic (RP-HPLC) behavior of some newly synthesized hydroxythioxanthone derivatives using binary acetonitrile-water mixtures as mobile phase has been examined. First, the variation in the retention time of each molecule as a function of mobile phase properties was studied by Kamlet-Taft solvatochromic equations. Then, the influences of molecular structure of the hydroxythioxanthone derivatives on their retention time in various mobile phase mixtures were investigated by quantitative structure-property relationship (QSPR) analysis. Finally, a unified model containing both the molecular structure parameters and mobile phase properties was developed to describe the chromatographic behavior of the systems studied. Among the solvent properties, polarity/polarizability parameter (π * ) and hydrogen-bond basicity (β), and among the solute properties, the most positive local charge (MPC), the sum of positive charges on hydrogen atoms contributing in hydrogen bonding (SPCH) and lipophilicity index (log P) were identified as controlling factors in the RP-HPLC behavior of hydroxythioxanthone derivatives in actonitrile-water binary solvents

QSPR Calculation of Normal Boiling Points of Organic Molecules Based on the Use of Correlation Weighting of Atomic Orbitals with Extended Connectivity of Zero- and First-Order Graphs of Atomic Orbitals

Directory of Open Access Journals (Sweden)

Eduardo A. Castro

2004-12-01

Full Text Available We report the results of a calculation of the normal boiling points of a representative set of 200 organic molecules through the application of QSPR theory. For this purpose we have used a particular set of flexible molecular descriptors, the so called Correlation Weighting of Atomic Orbitals with Extended Connectivity of Zero- and First-Order Graphs of Atomic Orbitals. Although in general the results show suitable behavior to predict this physical chemistry property, the existence of some deviant behaviors points to a need to complement this index with some other sort of molecular descriptors. Some possible extensions of this study are discussed.

Predicción del volumen molar y la entalpía molar de vaporización de moléculas orgánicas usando variables determinadas mediante el modelo de apantallamiento tipo conductor (COSMO

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José G. Parra

2011-12-01

Full Text Available Using the method of solvation Conductor-like Screening Model (COSMO and the method of Amovilli-Menucci GAMESS program content, we estimated the free energies of van der Waals and electrostatic of organic molecules in their dielectric medium. With these energy and volume of the solute cavity, we designed two models of structure-property relationship (QSPR to determine the molar volume and enthalpy of vaporization to the ebullition temperature of organic molecules. The best obtained model using the molecular volume presents a correlation equal to 0.9949 and the correlation of the model using the enthalpy of vaporization was 0. 9895.

Quantitative structure--property relationships for enhancing predictions of synthetic organic chemical removal from drinking water by granular activated carbon.

Science.gov (United States)

Magnuson, Matthew L; Speth, Thomas F

2005-10-01

Granular activated carbon is a frequently explored technology for removing synthetic organic contaminants from drinking water sources. The success of this technology relies on a number of factors based not only on the adsorptive properties of the contaminant but also on properties of the water itself, notably the presence of substances in the water which compete for adsorption sites. Because it is impractical to perform field-scale evaluations for all possible contaminants, the pore surface diffusion model (PSDM) has been developed and used to predict activated carbon column performance using single-solute isotherm data as inputs. Many assumptions are built into this model to account for kinetics of adsorption and competition for adsorption sites. This work further evaluates and expands this model, through the use of quantitative structure-property relationships (QSPRs) to predict the effect of natural organic matter fouling on activated carbon adsorption of specific contaminants. The QSPRs developed are based on a combination of calculated topographical indices and quantum chemical parameters. The QSPRs were evaluated in terms of their statistical predictive ability,the physical significance of the descriptors, and by comparison with field data. The QSPR-enhanced PSDM was judged to give results better than what could previously be obtained.

Externally predictive quantitative modeling of supercooled liquid vapor pressure of polychlorinated-naphthalenes through electron-correlation based quantum-mechanical descriptors.

Science.gov (United States)

Vikas; Chayawan

2014-01-01

For predicting physico-chemical properties related to environmental fate of molecules, quantitative structure-property relationships (QSPRs) are valuable tools in environmental chemistry. For developing a QSPR, molecular descriptors computed through quantum-mechanical methods are generally employed. The accuracy of a quantum-mechanical method, however, rests on the amount of electron-correlation estimated by the method. In this work, single-descriptor QSPRs for supercooled liquid vapor pressure of chloronaphthalenes and polychlorinated-naphthalenes are developed using molecular descriptors based on the electron-correlation contribution of the quantum-mechanical descriptor. The quantum-mechanical descriptors for which the electron-correlation contribution is analyzed include total-energy, mean polarizability, dipole moment, frontier orbital (HOMO/LUMO) energy, and density-functional theory (DFT) based descriptors, namely, absolute electronegativity, chemical hardness, and electrophilicity index. A total of 40 single-descriptor QSPRs were developed using molecular descriptors computed with advanced semi-empirical (SE) methods, namely, RM1, PM7, and ab intio methods, namely, Hartree-Fock and DFT. The developed QSPRs are validated using state-of-the-art external validation procedures employing an external prediction set. From the comparison of external predictivity of the models, it is observed that the single-descriptor QSPRs developed using total energy and correlation energy are found to be far more robust and predictive than those developed using commonly employed descriptors such as HOMO/LUMO energy and dipole moment. The work proposes that if real external predictivity of a QSPR model is desired to be explored, particularly, in terms of intra-molecular interactions, correlation-energy serves as a more appropriate descriptor than the polarizability. However, for developing QSPRs, computationally inexpensive advanced SE methods such as PM7 can be more reliable than

Quantitative modeling of flavonoid glycosides isolated from Paliurus spina-christi Mill.

OpenAIRE

Medić-Šarić, Marica; Maleš, Željan; Šarić, Slavko; Brantner, Adelheid

1996-01-01

Several QSPR models for predicting the properties of flavonoid glycosides isolated from Paliurus spina-christi Mill, and of some related flavonoids were described and evaluated. Log P values for all of them were calculated according to the method of Rekker. All investigated flavonoids showed expressive hydrophobicity. Significant correlation between the partition coefficient, log P, and van der Waals volume, Vw (calculated according to the method described by Moriguchi et al.) was obtained. T...

ADME evaluation in drug discovery. 1. Applications of genetic algorithms to the prediction of blood-brain partitioning of a large set of drugs.

Science.gov (United States)

Hou, Tingjun; Xu, Xiaojie

2002-12-01

In this study, the relationships between the brain-blood concentration ratio of 96 structurally diverse compounds with a large number of structurally derived descriptors were investigated. The linear models were based on molecular descriptors that can be calculated for any compound simply from a knowledge of its molecular structure. The linear correlation coefficients of the models were optimized by genetic algorithms (GAs), and the descriptors used in the linear models were automatically selected from 27 structurally derived descriptors. The GA optimizations resulted in a group of linear models with three or four molecular descriptors with good statistical significance. The change of descriptor use as the evolution proceeds demonstrates that the octane/water partition coefficient and the partial negative solvent-accessible surface area multiplied by the negative charge are crucial to brain-blood barrier permeability. Moreover, we found that the predictions using multiple QSPR models from GA optimization gave quite good results in spite of the diversity of structures, which was better than the predictions using the best single model. The predictions for the two external sets with 37 diverse compounds using multiple QSPR models indicate that the best linear models with four descriptors are sufficiently effective for predictive use. Considering the ease of computation of the descriptors, the linear models may be used as general utilities to screen the blood-brain barrier partitioning of drugs in a high-throughput fashion.

Developing descriptors to predict mechanical properties of nanotubes.

Science.gov (United States)

Borders, Tammie L; Fonseca, Alexandre F; Zhang, Hengji; Cho, Kyeongjae; Rusinko, Andrew

2013-04-22

Descriptors and quantitative structure property relationships (QSPR) were investigated for mechanical property prediction of carbon nanotubes (CNTs). 78 molecular dynamics (MD) simulations were carried out, and 20 descriptors were calculated to build quantitative structure property relationships (QSPRs) for Young's modulus and Poisson's ratio in two separate analyses: vacancy only and vacancy plus methyl functionalization. In the first analysis, C(N2)/C(T) (number of non-sp2 hybridized carbons per the total carbons) and chiral angle were identified as critical descriptors for both Young's modulus and Poisson's ratio. Further analysis and literature findings indicate the effect of chiral angle is negligible at larger CNT radii for both properties. Raman spectroscopy can be used to measure C(N2)/C(T), providing a direct link between experimental and computational results. Poisson's ratio approaches two different limiting values as CNT radii increases: 0.23-0.25 for chiral and armchair CNTs and 0.10 for zigzag CNTs (surface defects <3%). In the second analysis, the critical descriptors were C(N2)/C(T), chiral angle, and M(N)/C(T) (number of methyl groups per total carbons). These results imply new types of defects can be represented as a new descriptor in QSPR models. Finally, results are qualified and quantified against experimental data.

Prediction of the Formulation Dependence of the Glass Transition Temperature for Amine-Epoxy Copolymers Using a Quantitative Structure-Property Relationship Based on the AM1 Method

National Research Council Canada - National Science Library

Morrill, Jason

2004-01-01

A designer Quantitative Structure-Property Relationsbip (QSPR) based upon molecular properties calculated using the AM1 semi-empirical quantum mechanical metbod was developed to predict the glass transition temperature (Tg...

CALCULATION OF COEFFICIENT OF SHARING OCTANOL-WATER OF ORGANIC COMPOUNDS USING MOLECULAR DESCRIPTORS

Directory of Open Access Journals (Sweden)

B. Souyei

2010-12-01

Full Text Available A quantitative structure-property relationship (QSPR study is carried out to develop correlations that relate the molecular structures of organic compounds to their Octanol- Water partition coefficients, Kow , using molecular descriptors. The correlations are simple in application with good accuracy, which provide an easy, direct and relatively accurate way to calculate Kow. Such calculation gives us a model that gives results in remarkable correlation with the descriptors of blocks fragments of the atom-centered and functional groups (R2 = 0.949, δ = 0477 (R2 = 0.926,δ = 0,548 respectively.

On the Development and Use of Large Chemical Similarity Networks, Informatics Best Practices and Novel Chemical Descriptors Towards Materials Quantitative Structure Property Relationships

Science.gov (United States)

Krein, Michael

After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright cheating in the form of explicitly removing data to fit models. These actions do not serve the community well, nor are they beneficial to future predictions based on established models. In practice, in order to select combinations of descriptors and machine learning methods that might work best, one must consider the nature and size of the training and test datasets, be aware of existing hypotheses about the data, and resist the temptation to bias structure representation and modeling to explicitly fit the hypotheses. The definition and application of these best practices is important for obtaining actionable modeling outcomes, and for setting user expectations of modeling accuracy when predicting the endpoint values of unknowns. A wide variety of statistical learning approaches, descriptor types, and model validation strategies are explored herein, with the goals of helping end users understand the factors involved in creating and using QSPR models effectively, and to better understand relationships within the data, especially by looking at the problem space from multiple perspectives. Molecular relationships are commonly envisioned in a continuous high-dimensional space of numerical descriptors, referred to as chemistry space. Descriptor and similarity metric choice influence the partitioning of this space into regions corresponding to local structural similarity. These regions, known as domains of applicability, are most likely to be successfully modeled by a QSPR. In Chapter 2, the network topology and scaling relationships of several chemistry spaces are thoroughly investigated. Chemistry spaces studied include the

Artificial evolution of coumarin dyes for dye sensitized solar cells.

Science.gov (United States)

Venkatraman, Vishwesh; Abburu, Sailesh; Alsberg, Bjørn Kåre

2015-11-07

The design and discovery of novel molecular structures with optimal properties has been an ongoing effort for materials scientists. This field has in general been dominated by experiment driven trial-and-error approaches that are often expensive and time-consuming. Here, we investigate if a de novo computational design methodology can be applied to the design of coumarin-based dye sensitizers with improved properties for use in Grätzel solar cells. To address the issue of synthetic accessibility of the designed compounds, a fragment-based assembly is employed, wherein the combination of chemical motifs (derived from the existing databases of structures) is carried out with respect to user-adaptable set of rules. Rather than using computationally intensive density functional theory (DFT)/ab initio methods to screen candidate dyes, we employ quantitative structure-property relationship (QSPR) models (calibrated from empirical data) for rapid estimation of the property of interest, which in this case is the product of short circuit current (Jsc) and open circuit voltage (Voc). Since QSPR models have limited validity, pre-determined applicability domain criteria are used to prevent unacceptable extrapolation. DFT analysis of the top-ranked structures provides supporting evidence of their potential for dye sensitized solar cell applications.

Comparing estimates of genetic variance across different relationship models.

Science.gov (United States)

Legarra, Andres

2016-02-01

Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

Adaptive regression for modeling nonlinear relationships

CERN Document Server

Knafl, George J

2016-01-01

This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of outcome variables. Such nonlinear dependence is often not considered in applied research, yet nonlinear relationships are common and so need to be addressed. A standard linear analysis can produce misleading conclusions, while a nonlinear analysis can provide novel insights into data, not otherwise possible. A variety of examples of the benefits of modeling nonlinear relationships are presented throughout the book. Methods are covered using what are called fractional polynomials based on real-valued power transformations of primary predictor variables combined with model selection based on likelihood cross-validation. The book covers how to formulate and conduct such adaptive fractional polynomial modeling in the s...

Information Systems Outsourcing Relationship Model

Directory of Open Access Journals (Sweden)

Richard Flemming

2007-09-01

Full Text Available Increasing attention is being paid to what determines the success of an information systems outsourcing arrangement. The current research aims to provide an improved understanding of the factors influencing the outcome of an information systems outsourcing relationship and to provide a preliminary validation of an extended outsourcing relationship model by interviews with information systems outsourcing professionals in both the client and vendor of a major Australian outsourcing relationship. It also investigates whether the client and the vendor perceive the relationship differently and if so, how they perceive it differently and whether the two perspectives are interrelated.

Doctor-patient relationships in general practice--a different model.

Science.gov (United States)

Kushner, T

1981-09-01

Philosophical concerns cannot be excluded from even a cursory examination of the physician-patient relationship. Two possible alternatives for determining what this relationship entails are the teleological (outcome) approach vs the deontological (process) one. Traditionally, this relationship has been structured around the 'clinical model' which views the physician-patient relationship in teleological terms. Data on the actual content of general medical practice indicate the advisability of reassessing this relationship, and suggest that the 'clinical model' may be too limiting, and that a more appropriate basis for the physician-patient relationship is one described in this paper as the 'relational model'.

Personality, relationship conflict, and teamwork-related mental models.

Directory of Open Access Journals (Sweden)

Delia Vîrgă

Full Text Available This study seeks to explore whether neuroticism, agreeableness, and conscientiousness moderate the influence of relationship conflict experienced in groups on changes in group members' evaluative cognitions related to teamwork quality (teamwork-related mental models. Data from 216 students, nested in 48 groups were analyzed using a multilevel modeling approach. Our results show that the experience of relationship conflict leads to a negative shift from the pre-task to the post-task teamwork-related mental models. Moreover, the results indicate that conscientiousness buffered the negative association between relationship conflict and the change in teamwork-related mental models. Our results did not support the hypothesized moderating effect of agreeableness and show that the detrimental effect of relationship conflict on the shift in teamwork-related mental models is accentuated for group members scoring low rather than high on neuroticism. These findings open new research venues for exploring the association between personality, coping styles and change in teamwork-related mental models.

Personality, Relationship Conflict, and Teamwork-Related Mental Models

Science.gov (United States)

Vîrgă, Delia; CurŞeu, Petru Lucian; Maricuţoiu, Laurenţiu; Sava, Florin A.; Macsinga, Irina; Măgurean, Silvia

2014-01-01

This study seeks to explore whether neuroticism, agreeableness, and conscientiousness moderate the influence of relationship conflict experienced in groups on changes in group members' evaluative cognitions related to teamwork quality (teamwork-related mental models). Data from 216 students, nested in 48 groups were analyzed using a multilevel modeling approach. Our results show that the experience of relationship conflict leads to a negative shift from the pre-task to the post-task teamwork-related mental models. Moreover, the results indicate that conscientiousness buffered the negative association between relationship conflict and the change in teamwork-related mental models. Our results did not support the hypothesized moderating effect of agreeableness and show that the detrimental effect of relationship conflict on the shift in teamwork-related mental models is accentuated for group members scoring low rather than high on neuroticism. These findings open new research venues for exploring the association between personality, coping styles and change in teamwork-related mental models. PMID:25372143

Personality, relationship conflict, and teamwork-related mental models.

Science.gov (United States)

Vîrgă, Delia; Curşeu, Petru Lucian; CurŞeu, Petru Lucian; Maricuţoiu, Laurenţiu; Sava, Florin A; Macsinga, Irina; Măgurean, Silvia

2014-01-01

This study seeks to explore whether neuroticism, agreeableness, and conscientiousness moderate the influence of relationship conflict experienced in groups on changes in group members' evaluative cognitions related to teamwork quality (teamwork-related mental models). Data from 216 students, nested in 48 groups were analyzed using a multilevel modeling approach. Our results show that the experience of relationship conflict leads to a negative shift from the pre-task to the post-task teamwork-related mental models. Moreover, the results indicate that conscientiousness buffered the negative association between relationship conflict and the change in teamwork-related mental models. Our results did not support the hypothesized moderating effect of agreeableness and show that the detrimental effect of relationship conflict on the shift in teamwork-related mental models is accentuated for group members scoring low rather than high on neuroticism. These findings open new research venues for exploring the association between personality, coping styles and change in teamwork-related mental models.

Inclusion of Switching Behaviour into Relationship Marketing Model

DEFF Research Database (Denmark)

Alnaimi, Husam; Jones, Richard; Perkins, Helen

2011-01-01

Relationship marketing authors have attempted to develop distinct models suitable for investigating relationship marketing in different contexts. However, there is no agreement as yet about the antecedents that best capture the characteristics of the relational exchange that influences relationship...... marketing. Maintaining a long-term relationship with a customer is one of the fundamental factors determining the value that the customer provides to the company. A serious threat to achieving a long-term relationship is the customer’s switching behaviour. This study develops a theoretical model...... of relationship marketing, which includes customers’ switching behaviour (switchers and stayers), as a vital construct to understand the relationship development process between customers and service providers. Also, hypotheses to specify the association between the underlying models’ constructs were presented...

Multiphase, multicomponent phase behavior prediction

Science.gov (United States)

Dadmohammadi, Younas

quantitative structure-property parameter generalizations (QSPR). For ternary systems, where all three constituent binary systems were available, the NRTL-QSPR, UNIQUAC-QSPR, and UNIFAC-6 models produce comparable accuracy. For systems where at least one constituent binary is missing, the UNIFAC-6 model produces larger errors than the QSPR generalized models. In general, the LLE characterization results indicate the accuracy of the modified models in reproducing the findings of the original NRTL model.

Designing Customer Relationship Management Model in Hospital

OpenAIRE

Mohammad Abbaszadeh; Roohollah Askari; Morad Alizadeh; Mohammad Amin Bahrami

2017-01-01

Background: Customer relationship management is a modern marketing concept which is also considered as a successful business strategy. The present study aimed to design a customer relationship management model in the hospital. Methods: The study is an applied research performed in 2 phases of 1) texts investigation and 2) the experts' opinions to achieve consensus. Data were analyzed using SPSS 18 software along with descriptive statistics. Results: The designed model included areas of ...

Quantitative structure–reactivity study on sulfonation of amines, alcohols and phenols

Directory of Open Access Journals (Sweden)

Abolghasem Beheshti

2017-05-01

Full Text Available Quantitative structure–reactivity relationship (QSRR can be considered as a variant of quantitative structure property relationship (QSPR studies, where the chemical reactivity of reactants in a specified chemical reaction is related to chemical structure. As follows, the sulfonation reaction yield of 24 amines, alcohols and phenols with sulfonyl chloride was studied by QSRR. Quantum chemical calculations (b3lyp/6-31+g (d were carried out to obtain the optimized geometry. The suitable set of molecular descriptors was calculated to represent the molecular structures of compounds, such as constitutional, topological, geometrical, electrostatic and quantum-chemical descriptors. The genetic algorithm (GA was applied to select the variables that resulted in the best-fitted models. After the variable selection, multiple linear regression (MLR was utilized to construct linear QSRR models. The maximum relative error in prediction (5.26 showed that the predictive ability of the model was satisfactory and it can be used for designing similar reactants with efficient sulfonation reaction.

Inequity in work and intimate relationships: a Spillover-Crossover model.

Science.gov (United States)

Bakker, Arnold B; Petrou, Paraskevas; Tsaousis, Ioannis

2012-01-01

This study among 267 Greek teachers and their partners tested and expanded the recently proposed Spillover-Crossover model (SCM) of well-being. Accordingly, experiences built up at work spill over to the home domain, and then influence the partner. The authors integrated equity theory in the model by formulating hypotheses about exchange in interpersonal relationships. Structural equation modeling analyses supported the spillover hypothesis that teachers who lose their work engagement as a result of an inequitable relationship with their students invest less in the relationship with their partner. In addition, the results supported the crossover hypothesis that teachers' relationship investments, in turn, show a negative relationship with inequity in the intimate relationship as perceived by the partner; and inequity in the intimate relationship contributed to partner depression. The findings are discussed in light of the SCM of well-being.

Modeling of non-additive mixture properties using the Online CHEmical database and Modeling environment (OCHEM

Directory of Open Access Journals (Sweden)

Oprisiu Ioana

2013-01-01

Full Text Available Abstract The Online Chemical Modeling Environment (OCHEM, http://ochem.eu is a web-based platform that provides tools for automation of typical steps necessary to create a predictive QSAR/QSPR model. The platform consists of two major subsystems: a database of experimental measurements and a modeling framework. So far, OCHEM has been limited to the processing of individual compounds. In this work, we extended OCHEM with a new ability to store and model properties of binary non-additive mixtures. The developed system is publicly accessible, meaning that any user on the Web can store new data for binary mixtures and develop models to predict their non-additive properties. The database already contains almost 10,000 data points for the density, bubble point, and azeotropic behavior of binary mixtures. For these data, we developed models for both qualitative (azeotrope/zeotrope and quantitative endpoints (density and bubble points using different learning methods and specially developed descriptors for mixtures. The prediction performance of the models was similar to or more accurate than results reported in previous studies. Thus, we have developed and made publicly available a powerful system for modeling mixtures of chemical compounds on the Web.

Spaghetti Bridges: Modeling Linear Relationships

Science.gov (United States)

Kroon, Cindy D.

2016-01-01

Mathematics and science are natural partners. One of many examples of this partnership occurs when scientific observations are made, thus providing data that can be used for mathematical modeling. Developing mathematical relationships elucidates such scientific principles. This activity describes a data-collection activity in which students employ…

Prediction of toxicity of nitrobenzenes using ab initio and least squares support vector machines

International Nuclear Information System (INIS)

Niazi, Ali; Jameh-Bozorghi, Saeed; Nori-Shargh, Davood

2008-01-01

A quantitative structure-property relationship (QSPR) study is suggested for the prediction of toxicity (IGC 50 ) of nitrobenzenes. Ab initio theory was used to calculate some quantum chemical descriptors including electrostatic potentials and local charges at each atom, HOMO and LUMO energies, etc. Modeling of the IGC 50 of nitrobenzenes as a function of molecular structures was established by means of the least squares support vector machines (LS-SVM). This model was applied for the prediction of the toxicity (IGC 50 ) of nitrobenzenes, which were not in the modeling procedure. The resulted model showed high prediction ability with root mean square error of prediction of 0.0049 for LS-SVM. Results have shown that the introduction of LS-SVM for quantum chemical descriptors drastically enhances the ability of prediction in QSAR studies superior to multiple linear regression and partial least squares

Prediction of Surfactants’ Properties using Multiscale Molecular Modeling Tools: A Review Prédiction de propriétés des tensioactifs à l’aide d’outils de modélisation moléculaire : une revue

Directory of Open Access Journals (Sweden)

Creton B.

2013-01-01

Full Text Available During one of the existing Enhanced Oil Recovery (EOR procedures, a mixture of Alkaline/Surfactant/Polymer (ASP is injected into wells in order to move the trapped oil from the reservoir to the wellbores. The conception and/or the tuning of new ASP combinations, structures of surfactants and/or mixtures of surfactants is of primary interest to improve the efficiency of a such procedure. Molecular modeling tools can be used to understand microscopic effects, predict surfactants’ properties and finally to optimize structures and mixtures of surfactants. We propose in this article a review of the literature on the ability of molecular simulation techniques such as Molecular Dynamics (MD, Monte Carlo (MC simulations, Dissipative Particle Dynamics (DPD and upper scale modeling methods such as Quantitative Structure-Property Relationship (QSPR approaches to predict thermo-physical and structural properties of surfactants. Une des voies possibles de récupération assistée du pétrole, l’EOR (Enhanced Oil Recovery, consiste en l’injection d’un fluide ASP (Alkaline/Surfactant/Polymer dans le réservoir dans le but de déplacer le pétrole piégé vers le puits de production. La conception et/ou l’optimisation de mélanges ASP, de tensioactifs ou de mélanges de tensioactifs est donc d’un intérêt premier pour améliorer l’efficacité d’un tel procédé. Les codes de simulation moléculaire développés et largement validés durant ces dernières décennies apparaissent comme des outils incontournables pour la compréhension des effets microscopiques, la prédiction de propriétés de tensioactifs complexes ou encore l’optimisation des structures voire de la composition de mélanges de tensioactifs. Dans cet article, nous présentons une revue des travaux de la littérature sur le potentiel de diverses techniques de simulation moléculaire pour la prédiction de propriétés structurales ou thermophysiques des tensioactifs. Les

Externally predictive single-descriptor based QSPRs for physico-chemical properties of polychlorinated-naphthalenes: Exploring relationships of log SW, log KOA, and log KOW with electron-correlation

International Nuclear Information System (INIS)

Chayawan; Vikas

2015-01-01

Highlights: • Aqueous solubility and partition coefficient are modelled using single-parameter. • Electron-correlation observed as a vital predictorof physico-chemical properties. • For octanol-air partition coefficient, energy and polarizability yield best models. • Dipole-moment is found to be worst single-descriptor for the properties analysed. - Abstract: Quantitative structure–property relationships (QSPRs), based only on a single-parameter, are proposed for the prediction of physico-chemical properties, namely, aqueous solubility (log S W ), octanol–water partition coefficient (log K OW ) and octanol–air partition coefficient (log K OA ) of polychloronaphthalenes (PCNs) including all the 75 chloronaphthalene congeners. The QSPR models are developed using molecular descriptors computed through quantum mechanical methods including ab-initio as well as advanced semi-empirical methods. The predictivity of the developed models is tested through state-of-the-art external validation procedures employing an external prediction set of compounds. To analyse the role of instantaneous interactions between electrons (the electron-correlation), the models are also compared with those developed using only the electron-correlation contribution of the quantum chemical descriptor. The electron-correlation contribution towards the chemical hardness and the LUMO energy are observed to be the best predictors for octanol–water partition coefficient, whereas for the octanol–air partition coefficient, the total electronic energy and electron-correlation energy are found to be reliable descriptors, in fact, even better than the polarisability. For aqueous solubility of PCNs, the absolute electronegativity is observed to be the best predictor. This work suggests that the electron-correlation contribution of a quantum-chemical descriptor can be used as a reliable indicator for physico-chemical properties, particularly the partition coefficients

A Multi-Stage Maturity Model for Long-Term IT Outsourcing Relationship Success

Science.gov (United States)

Luong, Ming; Stevens, Jeff

2015-01-01

The Multi-Stage Maturity Model for Long-Term IT Outsourcing Relationship Success, a theoretical stages-of-growth model, explains long-term success in IT outsourcing relationships. Research showed the IT outsourcing relationship life cycle consists of four distinct, sequential stages: contract, transition, support, and partnership. The model was…

Event-Entity-Relationship Modeling in Data Warehouse Environments

DEFF Research Database (Denmark)

Bækgaard, Lars

We use the event-entity-relationship model (EVER) to illustrate the use of entity-based modeling languages for conceptual schema design in data warehouse environments. EVER is a general-purpose information modeling language that supports the specification of both general schema structures and multi...

Team Risk Management: A New Model for Customer-Supplier Relationships

Science.gov (United States)

1994-07-01

Management : A New Model for Customer - Supplier Relationships Ronald P. Higuera "Audrey J. Dorofee Julie A. Walker Ray C. Williams July 1994 ""•// 94...N/A N/A N/A 11. TITLE (Include Secuity Claaaificatioa) Team Risk Management : A New Model for Customer -Supplier Relationships 12. PERSONAL AUTHOR(S...by block number) FIELD GROUP SUB. GR. Customer - Supplier Relationships Risk Team Risk Management 19. ABSTRACT (cominus on = if necesaryd id’y by block

Modeling process-structure-property relationships for additive manufacturing

Science.gov (United States)

Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Yu, Cheng; Liu, Zeliang; Lian, Yanping; Wolff, Sarah; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

2018-02-01

This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the processstructure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a highefficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.

DESIGNING A MODEL OF CUSTOMER RELATIONSHIP MANAGEMENT FOR A MOBILE PHONE COMPANY

Directory of Open Access Journals (Sweden)

BRUTU MĂDĂLINA

2015-07-01

Full Text Available Customer relationship management refers to establishing, maintaining, developing and optimizing the relations between an organization and its customers and focuses on understanding and meeting its customers’ wishes and demands, the core items of the business strategy of any performant company. This paper aims at designing and testing a model of customer relationship management applicable within a mobile phone company. Starting from this purpose, the main objectives of the research were: presenting the concept of customer relationship management; the importance of companies’ orientation to the market; identifying a model of customer relationship management and, not least, analyzing the efficiency of this model. The results lead to the conclusion that the model of customer relationship management is extremely effective in the mobile phone industry, bringing significant profits.

Parental Modeling and Deidentification in Romantic Relationships Among Mexican-origin Youth.

Science.gov (United States)

Kuo, Sally I-Chun; Wheeler, Lorey A; Updegraff, Kimberly A; McHale, Susan M; Umaña-Taylor, Adriana J; Perez-Brena, Norma J

2017-10-01

This study investigated youth's modeling of and de-identification from parents in romantic relationships, using two phases of data from adolescent siblings, mothers, and fathers in 246 Mexican-origin families. Each parent reported his/her marital satisfaction and conflict, and youth reported on parent-adolescent warmth and conflict at Time 1. Youth's reports of modeling of and de-identification from their mothers and fathers and three romantic relationship outcomes were assessed at Time 2. Findings revealed that higher parental marital satisfaction, lower marital conflict, and higher warmth and lower conflict in parent-adolescent relationships were associated with more modeling and less de-identification from parents. Moreover, higher de-identification was linked to a greater likelihood of youth being involved in a romantic relationship and cohabitation, whereas more modeling was linked to a lower likelihood of cohabitation and older age of first sex. Discussion underscores the importance of assessing parental modeling and de-identification and understanding correlates of these processes.

Adolescents' working models and styles for relationships with parents, friends, and romantic partners.

Science.gov (United States)

Furman, Wyndol; Simon, Valerie A; Shaffer, Laura; Bouchey, Heather A

2002-01-01

This study examined the links among adolescents' representations of their relationships with parents, friends, and romantic partners. Sixty-eight adolescents were interviewed three times to assess their working models for each of these types of relationships. Working models of friendships were related to working models of relationships with parents and romantic partners. Working models of relationships with parents and romantic partners were inconsistently related. A similar pattern of results was obtained for self-report measures of relational styles for the three types of relationships. Perceived experiences were also related. Specifically, support in relationships with parents tended to be related to support in romantic relationships and friendships, but the latter two were unrelated. On the other hand, self and other controlling behaviors in friendships were related to corresponding behaviors in romantic relationships. Negative interactions in the three types of relationships also tended to be related. Taken together, the findings indicate that the representations of the three types of relationships are distinct, yet related. Discussion focuses on the nature of the links among the three.

Identifying and Evaluating the Relationships that Control a Land Surface Model's Hydrological Behavior

Science.gov (United States)

Koster, Randal D.; Mahanama, Sarith P.

2012-01-01

The inherent soil moisture-evaporation relationships used in today 's land surface models (LSMs) arguably reflect a lot of guesswork given the lack of contemporaneous evaporation and soil moisture observations at the spatial scales represented by regional and global models. The inherent soil moisture-runoff relationships used in the LSMs are also of uncertain accuracy. Evaluating these relationships is difficult but crucial given that they have a major impact on how the land component contributes to hydrological and meteorological variability within the climate system. The relationships, it turns out, can be examined efficiently and effectively with a simple water balance model framework. The simple water balance model, driven with multi-decadal observations covering the conterminous United States, shows how different prescribed relationships lead to different manifestations of hydrological variability, some of which can be compared directly to observations. Through the testing of a wide suite of relationships, the simple model provides estimates for the underlying relationships that operate in nature and that should be operating in LSMs. We examine the relationships currently used in a number of different LSMs in the context of the simple water balance model results and make recommendations for potential first-order improvements to these LSMs.

Advances in QSPR/QSTR models of ionic liquids for the design of greener solvents of the future.

Science.gov (United States)

Das, Rudra Narayan; Roy, Kunal

2013-02-01

In order to protect the life of all creatures living in the environment, the toxicity arising from various hazardous chemicals must be controlled. This imposes a serious responsibility on different chemical, pharmaceutical, and other biological industries to produce less harmful chemicals. Among various international initiatives on harmful aspects of chemicals, the 'Green Chemistry' ideology appears to be one of the most highlighted concepts that focus on the use of eco-friendly chemicals. Ionic liquids are a comparatively new addition to the huge garrison of chemical compounds released from the industry. Extensive research on ionic liquids in the past decade has shown them to be highly useful chemicals with a good degree of thermal and chemical stability, appreciable task specificity and minimal environmental release resulting in a notion of 'green chemical'. However, studies have also shown that ionic liquids are not intrinsically non-toxic agents and can pose severe degree of toxicity as well as the risk of bioaccumulation depending upon their structural components. Moreover, ionic liquids possess issues of waste generation during synthesis as well as separation problems. Predictive quantitative structure-activity relationship (QSAR) models constitute a rational opportunity to explore the structural attributes of ionic liquids towards various physicochemical and toxicological endpoints and thereby leading to the design of environmentally more benevolent analogues with higher process selectivity. Such studies on ionic liquids have been less extensive compared to other industrial chemicals. The present review attempts to summarize different QSAR studies performed on these chemicals and also highlights the safety, health and environmental issues along with the application specificity on the dogma of 'green chemistry'.

Some hybrid models applicable to dose-response relationships

International Nuclear Information System (INIS)

Kumazawa, Shigeru

1992-01-01

A new type of models of dose-response relationships has been studied as an initial stage to explore a reliable extrapolation of the relationships decided by high dose data to the range of low dose covered by radiation protection. The approach is to use a 'hybrid scale' of linear and logarithmic scales; the first model is that the normalized surviving fraction (ρ S > 0) in a hybrid scale decreases linearly with dose in a linear scale, and the second is that the induction in a log scale increases linearly with the normalized dose (τ D > 0) in a hybrid scale. The hybrid scale may reflect an overall effectiveness of a complex system against adverse events caused by various agents. Some data of leukemia in the atomic bomb survivors and of rodent experiments were used to show the applicability of hybrid scale models. The results proved that proposed models fit these data not less than the popular linear-quadratic models, providing the possible interpretation of shapes of dose-response curves, e.g. shouldered survival curves varied by recovery time. (author)

QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

Science.gov (United States)

Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Benfenati, Emilio

2010-04-01

Three different splits into the subtraining set (n = 22), the set of calibration (n = 21), and the test set (n = 12) of 55 antineoplastic agents have been examined. By the correlation balance of SMILES-based optimal descriptors quite satisfactory models for the octanol/water partition coefficient have been obtained on all three splits. The correlation balance is the optimization of a one-variable model with a target function that provides both the maximal values of the correlation coefficient for the subtraining and calibration set and the minimum of the difference between the above-mentioned correlation coefficients. Thus, the calibration set is a preliminary test set. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

Externally predictive single-descriptor based QSPRs for physico-chemical properties of polychlorinated-naphthalenes: Exploring relationships of log S{sub W}, log K{sub OA}, and log K{sub OW} with electron-correlation

Energy Technology Data Exchange (ETDEWEB)

Chayawan; Vikas, E-mail: qlabspu@pu.ac.in

2015-10-15

Highlights: • Aqueous solubility and partition coefficient are modelled using single-parameter. • Electron-correlation observed as a vital predictorof physico-chemical properties. • For octanol-air partition coefficient, energy and polarizability yield best models. • Dipole-moment is found to be worst single-descriptor for the properties analysed. - Abstract: Quantitative structure–property relationships (QSPRs), based only on a single-parameter, are proposed for the prediction of physico-chemical properties, namely, aqueous solubility (log S{sub W}), octanol–water partition coefficient (log K{sub OW}) and octanol–air partition coefficient (log K{sub OA}) of polychloronaphthalenes (PCNs) including all the 75 chloronaphthalene congeners. The QSPR models are developed using molecular descriptors computed through quantum mechanical methods including ab-initio as well as advanced semi-empirical methods. The predictivity of the developed models is tested through state-of-the-art external validation procedures employing an external prediction set of compounds. To analyse the role of instantaneous interactions between electrons (the electron-correlation), the models are also compared with those developed using only the electron-correlation contribution of the quantum chemical descriptor. The electron-correlation contribution towards the chemical hardness and the LUMO energy are observed to be the best predictors for octanol–water partition coefficient, whereas for the octanol–air partition coefficient, the total electronic energy and electron-correlation energy are found to be reliable descriptors, in fact, even better than the polarisability. For aqueous solubility of PCNs, the absolute electronegativity is observed to be the best predictor. This work suggests that the electron-correlation contribution of a quantum-chemical descriptor can be used as a reliable indicator for physico-chemical properties, particularly the partition coefficients.

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.

Accessing Data Bases Through Interface Views Using a Unified Graph-Oriented Entity-Relationship Model

DEFF Research Database (Denmark)

Kraft, Peter; Sørensen, Jens Otto

Interface Abstract: The paper describes an Entity Relationship (ER) model with a diagrammed schema and extensions modeled into a graph. The semantics of schema symbols are fundamentally simple implying a unified model where given conceptualizations of environments are diagrammed uniquely. By the ......Interface Abstract: The paper describes an Entity Relationship (ER) model with a diagrammed schema and extensions modeled into a graph. The semantics of schema symbols are fundamentally simple implying a unified model where given conceptualizations of environments are diagrammed uniquely...... with a unified graphic model is more efficient and less error-prone than working with more complex ER models and models based on lexical description. Key terms: Entity-relationship model, path expressions, entity-relationship language, derived interface view, view updates, graphical models....

Relationship between soil erodibility and modeled infiltration rate in different soils

Science.gov (United States)

Wang, Guoqiang; Fang, Qingqing; Wu, Binbin; Yang, Huicai; Xu, Zongxue

2015-09-01

The relationship between soil erodibility, which is hard to measure, and modeled infiltration rate were rarely researched. Here, the soil erodibility factors (K and Ke in the USLE, Ki and K1 in the WEPP) were calculated and the infiltration rates were modeled based on the designed laboratory simulation experiments and proposed infiltration model, in order to build their relationship. The impacts of compost amendment on the soil erosion characteristics and relationship were also studied. Two contrasting agricultural soils (bare and cultivated fluvo-aquic soils) were used, and different poultry compost contents (control, low and high) were applied to both soils. The results indicated that the runoff rate, sediment yield rate and soil erodibility of the bare soil treatments were generally higher than those of the corresponding cultivated soil treatments. The application of composts generally decreased sediment yield and soil erodibility but did not always decrease runoff. The comparison of measured and modeled infiltration rates indicated that the model represented the infiltration processes well with an N-S coefficient of 0.84 for overall treatments. Significant negative logarithmic correlations have been found between final infiltration rate (FIR) and the four soil erodibility factors, and the relationship between USLE-K and FIR demonstrated the best correlation. The application of poultry composts would not influence the logarithmic relationship between FIR and soil erodibility. Our study provided a useful tool to estimate soil erodibility.

[RELATIONSHIP BETWEEN JUNIOR AND SENIOR DOCTORS: A BUBERIAN MODEL].

Science.gov (United States)

Pougnet, Richard; Pougnet, Laurence

2016-01-01

Doctors in training work in services under the supervision of senior doctors. These professional relationships may lead to frustrations, or ill-being at work. Indeed doctors are often very busy with care and can hardly communicate. The purpose of this article is to propose ways to think in its ethical dimension this relationship, by learning from Martin Buber's ideas. He thought a philosophy of relationship in two word pairs: I-Thou and I-It. This thought can be useful in the context of the médical relationship and mentorship. Indeed we can see our colleague as a person or only as a caregiver. We offer a relationship model according to buberian thought, between junior and senior doctor caring about the same patients.

Coopetitive Supply Chain Relationship Model: Application to the Smartphone Manufacturing Network

Science.gov (United States)

Kwok, Jeremy Jie Ming; Lee, Dong-Yup

2015-01-01

Previous researches for understanding supply chain relationship have mostly focused on its vertical collaboration between buyers and suppliers. However, there have been some instances of volatile and stable collaborative relationships amongst competitors such as Apple-Samsung product manufacturer-component supplier relationship and airline alliances, respectively, which is recognized as coopetition. Even though there have been several qualitative studies and a number of game theory models on coopetition, it is rare to find any attempts on quantitative characterization of such coopetitive dynamic behavior in supply chain relationship. Hence, in this work, we formulated a MINLP model mathematically representing coopetitive relationships in a cost efficient supply chain network. In particular, the coopetition factor was newly introduced to measure the degree of coopetition among supply chain players and determine the optimal level of coopetition to engage in. The utility and practicality of the model were strongly demonstrated using a case study of a hypothetical smartphone supply chain network under different scenarios, thus proposing their strategically viable optimal interactions. Therefore, this exploratory study can herald a new era of global coopetitive business. PMID:26186227

Coopetitive Supply Chain Relationship Model: Application to the Smartphone Manufacturing Network.

Directory of Open Access Journals (Sweden)

Jeremy Jie Ming Kwok

Full Text Available Previous researches for understanding supply chain relationship have mostly focused on its vertical collaboration between buyers and suppliers. However, there have been some instances of volatile and stable collaborative relationships amongst competitors such as Apple-Samsung product manufacturer-component supplier relationship and airline alliances, respectively, which is recognized as coopetition. Even though there have been several qualitative studies and a number of game theory models on coopetition, it is rare to find any attempts on quantitative characterization of such coopetitive dynamic behavior in supply chain relationship. Hence, in this work, we formulated a MINLP model mathematically representing coopetitive relationships in a cost efficient supply chain network. In particular, the coopetition factor was newly introduced to measure the degree of coopetition among supply chain players and determine the optimal level of coopetition to engage in. The utility and practicality of the model were strongly demonstrated using a case study of a hypothetical smartphone supply chain network under different scenarios, thus proposing their strategically viable optimal interactions. Therefore, this exploratory study can herald a new era of global coopetitive business.

Coopetitive Supply Chain Relationship Model: Application to the Smartphone Manufacturing Network.

Science.gov (United States)

Kwok, Jeremy Jie Ming; Lee, Dong-Yup

2015-01-01

Previous researches for understanding supply chain relationship have mostly focused on its vertical collaboration between buyers and suppliers. However, there have been some instances of volatile and stable collaborative relationships amongst competitors such as Apple-Samsung product manufacturer-component supplier relationship and airline alliances, respectively, which is recognized as coopetition. Even though there have been several qualitative studies and a number of game theory models on coopetition, it is rare to find any attempts on quantitative characterization of such coopetitive dynamic behavior in supply chain relationship. Hence, in this work, we formulated a MINLP model mathematically representing coopetitive relationships in a cost efficient supply chain network. In particular, the coopetition factor was newly introduced to measure the degree of coopetition among supply chain players and determine the optimal level of coopetition to engage in. The utility and practicality of the model were strongly demonstrated using a case study of a hypothetical smartphone supply chain network under different scenarios, thus proposing their strategically viable optimal interactions. Therefore, this exploratory study can herald a new era of global coopetitive business.

Relationships between water table and model simulated ET

Science.gov (United States)

Prem B. Parajuli; Gretchen F. Sassenrath; Ying Ouyang

2013-01-01

This research was conducted to develop relationships among evapotranspiration (ET), percolation (PERC), groundwater discharge to the stream (GWQ), and water table fluctuations through a modeling approach. The Soil and Water Assessment Tool (SWAT) hydrologic and crop models were applied in the Big Sunflower River watershed (BSRW; 7660 km2) within the Yazoo River Basin...

Engineering and validation of a novel lipid thin film for biomembrane modeling in lipophilicity determination of drugs and xenobiotics

Directory of Open Access Journals (Sweden)

Ogbonna Udochi

2009-09-01

Full Text Available Abstract Background Determination of lipophilicity as a tool for predicting pharmacokinetic molecular behavior is limited by the predictive power of available experimental models of the biomembrane. There is current interest, therefore, in models that accurately simulate the biomembrane structure and function. A novel bio-device; a lipid thin film, was engineered as an alternative approach to the previous use of hydrocarbon thin films in biomembrane modeling. Results Retention behavior of four structurally diverse model compounds; 4-amino-3,5-dinitrobenzoic acid (ADBA, naproxen (NPX, nabumetone (NBT and halofantrine (HF, representing 4 broad classes of varying molecular polarities and aqueous solubility behavior, was investigated on the lipid film, liquid paraffin, and octadecylsilane layers. Computational, thermodynamic and image analysis confirms the peculiar amphiphilic configuration of the lipid film. Effect of solute-type, layer-type and variables interactions on retention behavior was delineated by 2-way analysis of variance (ANOVA and quantitative structure property relationships (QSPR. Validation of the lipid film was implemented by statistical correlation of a unique chromatographic metric with Log P (octanol/water and several calculated molecular descriptors of bulk and solubility properties. Conclusion The lipid film signifies a biomimetic artificial biological interface capable of both hydrophobic and specific electrostatic interactions. It captures the hydrophilic-lipophilic balance (HLB in the determination of lipophilicity of molecules unlike the pure hydrocarbon film of the prior art. The potentials and performance of the bio-device gives the promise of its utility as a predictive analytic tool for early-stage drug discovery science.

Event-Entity-Relationship Modeling in Data Warehouse Environments

DEFF Research Database (Denmark)

Bækgaard, Lars

We use the event-entity-relationship model (EVER) to illustrate the use of entity-based modeling languages for conceptual schema design in data warehouse environments. EVER is a general-purpose information modeling language that supports the specification of both general schema structures and multi......-dimensional schemes that are customized to serve specific information needs. EVER is based on an event concept that is very well suited for multi-dimensional modeling because measurement data often represent events in multi-dimensional databases...

Constitutive relationships and models in continuum theories of multiphase flows

International Nuclear Information System (INIS)

Decker, R.

1989-09-01

In April, 1989, a workshop on constitutive relationships and models in continuum theories of multiphase flows was held at NASA's Marshall Space Flight Center. Topics of constitutive relationships for the partial or per phase stresses, including the concept of solid phase pressure are discussed. Models used for the exchange of mass, momentum, and energy between the phases in a multiphase flow are also discussed. The program, abstracts, and texts of the presentations from the workshop are included

A phenomenological model of muscle fatigue and the power-endurance relationship.

Science.gov (United States)

James, A; Green, S

2012-11-01

The relationship between power output and the time that it can be sustained during exercise (i.e., endurance) at high intensities is curvilinear. Although fatigue is implicit in this relationship, there is little evidence pertaining to it. To address this, we developed a phenomenological model that predicts the temporal response of muscle power during submaximal and maximal exercise and which was based on the type, contractile properties (e.g., fatiguability), and recruitment of motor units (MUs) during exercise. The model was first used to predict power outputs during all-out exercise when fatigue is clearly manifest and for several distributions of MU type. The model was then used to predict times that different submaximal power outputs could be sustained for several MU distributions, from which several power-endurance curves were obtained. The model was simultaneously fitted to two sets of human data pertaining to all-out exercise (power-time profile) and submaximal exercise (power-endurance relationship), yielding a high goodness of fit (R(2) = 0.96-0.97). This suggested that this simple model provides an accurate description of human power output during submaximal and maximal exercise and that fatigue-related processes inherent in it account for the curvilinearity of the power-endurance relationship.

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

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.

QSAR as a random event: modeling of nanoparticles uptake in PaCa2 cancer cells.

Science.gov (United States)

Toropov, Andrey A; Toropova, Alla P; Puzyn, Tomasz; Benfenati, Emilio; Gini, Giuseppina; Leszczynska, Danuta; Leszczynski, Jerzy

2013-06-01

Quantitative structure-property/activity relationships (QSPRs/QSARs) are a tool to predict various endpoints for various substances. The "classic" QSPR/QSAR analysis is based on the representation of the molecular structure by the molecular graph. However, simplified molecular input-line entry system (SMILES) gradually becomes most popular representation of the molecular structure in the databases available on the Internet. Under such circumstances, the development of molecular descriptors calculated directly from SMILES becomes attractive alternative to "classic" descriptors. The CORAL software (http://www.insilico.eu/coral) is provider of SMILES-based optimal molecular descriptors which are aimed to correlate with various endpoints. We analyzed data set on nanoparticles uptake in PaCa2 pancreatic cancer cells. The data set includes 109 nanoparticles with the same core but different surface modifiers (small organic molecules). The concept of a QSAR as a random event is suggested in opposition to "classic" QSARs which are based on the only one distribution of available data into the training and the validation sets. In other words, five random splits into the "visible" training set and the "invisible" validation set were examined. The SMILES-based optimal descriptors (obtained by the Monte Carlo technique) for these splits are calculated with the CORAL software. The statistical quality of all these models is good. Copyright © 2013 Elsevier Ltd. All rights reserved.

Negative childhood experiences and adult love relationships: the role of internal working models of attachment.

Science.gov (United States)

McCarthy, Gerard; Maughan, Barbara

2010-09-01

This study investigated links between internal working models of attachment and the quality of adult love relationships in a high risk sample of women (n = 34), all of whom reported negative parenting in childhood. Half of the sample was identified as having a history of satisfying adult love relationships, while the remainder had experienced ongoing adult relationship problems. Measures of internal working models of attachment were made using the Adult Attachment Interview (AAI). A strong association was found between attachment classifications and the quality of adult love relationships. In addition, women with satisfying love relationships demonstrated significantly higher coherence of mind ratings than those with poor relationship histories. Insecure working models of attachment were associated with problems in adult love relationships. Although secure/autonomous attachment status was linked to optimal adult relationship outcomes, some women with a history of satisfying love relationships had insecure working models of attachment. These results suggest that the ways that adults process early experiences may influence later psychosocial functioning.

Molecular studies and plastic optical fiber device structures for nonlinear optical applications

Science.gov (United States)

Dirk, Carl W.; Nagarur, Aruna R.; Lu, Jin J.; Zhang, Lixia; Kalamegham, Priya; Fonseca, Joe; Gopalan, Saytha; Townsend, Scott; Gonzalez, Gabriel; Craig, Patrick; Rosales, Monica; Green, Leslie; Chan, Karen; Twieg, Robert J.; Ermer, Susan P.; Leung, Doris S.; Lovejoy, Steven M.; Lacroix, Suzanne; Godbout, Nicolas; Monette, Etienne

1995-10-01

Summarized are two project areas: First, the development of a quantitative structure property relationship for analyzing thermal decomposition differential scanning calorimetry data of electro-optic dyes is presented. The QSPR relationship suggest that thermal decomposition can be effectively correlated with structure by considering the kinds of atoms, their hybridization, and their nearest neighbor bonded atoms. Second, the simple preparation of clad plastic optical fibers (POF) is discussed with the intention of use for nonlinear optical applications. We discuss preparation techniques for single core and multiple core POF, and present some recent data on index profiles and the optimization of thermal stability in acrylate-based POF structures.

Building Customer Relationships: A Model for Vocational Education and Training Delivery.

Science.gov (United States)

Jarratt, Denise G.; Murphy, Tom; Lowry, Diannah

1997-01-01

Review of the theory of relational marketing and interviews with training providers identified a training delivery model that includes elements of trust and commitment, investment by relationship partners, and knowledge exchange, supporting relationship longevity. (SK)

A Model of Female Sexual Desire: Internalized Working Models of Parent-Child Relationships and Sexual Body Self-Representations.

Science.gov (United States)

Cherkasskaya, Eugenia; Rosario, Margaret

2017-11-01

The etiology of low female sexual desire, the most prevalent sexual complaint in women, is multi-determined, implicating biological and psychological factors, including women's early parent-child relationships and bodily self-representations. The current study evaluated a model that hypothesized that sexual body self-representations (sexual subjectivity, self-objectification, genital self-image) explain (i.e., mediate) the relation between internalized working models of parent-child relationships (attachment, separation-individuation, parental identification) and sexual desire in heterosexual women. We recruited 614 young, heterosexual women (M = 25.5 years, SD = 4.63) through social media. The women completed an online survey. Structural equation modeling was used. The hypotheses were supported in that the relation between internalized working models of parent-child relationships (attachment and separation-individuation) and sexual desire was mediated by sexual body self-representations (sexual body esteem, self-objectification, genital self-image). However, parental identification was not related significantly to sexual body self-representations or sexual desire in the model. Current findings demonstrated that understanding female sexual desire necessitates considering women's internalized working models of early parent-child relationships and their experiences of their bodies in a sexual context. Treatment of low or absent desire in women would benefit from modalities that emphasize early parent-child relationships as well as interventions that foster mind-body integration.

Personality, relationship conflict, and teamwork-related mental models

NARCIS (Netherlands)

Vîrgă, D.; Curseu, P.L.; Maricuţoiu, L.; Sava, S.A.; Macsinga, I.; Măgurean, S.

2014-01-01

This study seeks to explore whether neuroticism, agreeableness, and conscientiousness moderate the influence of relationship conflict experienced in groups on changes in group members' evaluative cognitions related to teamwork quality (teamwork-related mental models). Data from 216 students, nested

Complementary models of tree species-soil relationships in old-growth temperate forests

Science.gov (United States)

Cross, Alison; Perakis, Steven S.

2011-01-01

Ecosystem level studies identify plant soil feed backs as important controls on soil nutrient availability,particularly for nitrogen and phosphorus. Although site and species specific studies of tree species soil relationships are relatively common,comparatively fewer studies consider multiple coexisting speciesin old-growth forests across a range of sites that vary underlying soil fertility. We characterized patterns in forest floor and mineral soil nutrients associated with four common tree species across eight undisturbed old-growth forests in Oregon, USA, and used two complementary conceptual models to assess tree species soil relationships. Plant soil feedbacks that could reinforce sitelevel differences in nutrient availability were assessed using the context dependent relationships model, where by relative species based differences in each soil nutrient divergedorconvergedas nutrient status changed across sites. Tree species soil relationships that did not reflect strong feedbacks were evaluated using a site independent relationships model, where by forest floor and surface mineral soil nutrient tools differed consistently by tree species across sites,without variation in deeper mineral soils. We found that theorganically cycled elements carbon, nitrogen, and phosphorus exhibited context-dependent differences among species in both forest floor and mineral soil, and most of ten followed adivergence model,where by species differences were greatest at high-nutrient sites. These patterns are consistent with the oryemphasizing biotic control of these elements through plant soil feedback mechanisms. Site independent species differences were strongest for pool so if the weather able cations calcium, magnesium, potassium,as well as phosphorus, in mineral soils. Site independent species differences in forest floor nutrients we reattributable too nespecies that displayed significant greater forest floor mass accumulation. Our finding confirmed that site-independent and

In silico modeling on ADME properties of natural products: Classification models for blood-brain barrier permeability, its application to traditional Chinese medicine and in vitro experimental validation.

Science.gov (United States)

Zhang, Xiuqing; Liu, Ting; Fan, Xiaohui; Ai, Ni

2017-08-01

In silico modeling of blood-brain barrier (BBB) permeability plays an important role in early discovery of central nervous system (CNS) drugs due to its high-throughput and cost-effectiveness. Natural products (NP) have demonstrated considerable therapeutic efficacy against several CNS diseases. However, BBB permeation property of NP is scarcely evaluated both experimentally and computationally. It is well accepted that significant difference in chemical spaces exists between NP and synthetic drugs, which calls into doubt on suitability of available synthetic chemical based BBB permeability models for the evaluation of NP. Herein poor discriminative performance on BBB permeability of NP are first confirmed using internal constructed and previously published drug-derived computational models, which warrants the need for NP-oriented modeling. Then a quantitative structure-property relationship (QSPR) study on a NP dataset was carried out using four different machine learning methods including support vector machine, random forest, Naïve Bayes and probabilistic neural network with 67 selected features. The final consensus model was obtained with approximate 90% overall accuracy for the cross-validation study, which is further taken to predict passive BBB permeability of a large dataset consisting of over 10,000 compounds from traditional Chinese medicine (TCM). For 32 selected TCM molecules, their predicted BBB permeability were evaluated by in vitro parallel artificial membrane permeability assay and overall accuracy for in vitro experimental validation is around 81%. Interestingly, our in silico model successfully predicted different BBB permeation potentials of parent molecules and their known in vivo metabolites. Finally, we found that the lipophilicity, the number of hydrogen bonds and molecular polarity were important molecular determinants for BBB permeability of NP. Our results suggest that the consensus model proposed in current work is a reliable tool for

Remaining in an Abusive Relationship: An Investment Model Analysis of Nonvoluntary Dependence.

Science.gov (United States)

Rusbult, Caryl E.; Martz, John M.

1995-01-01

Analyzes the nature of interdependence in ongoing relationships, using an investment model to understand decisions to remain in abusive relationships. Found that feelings of commitment were greater among women who had poorer-quality economic alternatives, were more heavily invested in their relationship, and who experienced less dissatisfaction…

Modeling rainfall-runoff relationship using multivariate GARCH model

Science.gov (United States)

Modarres, R.; Ouarda, T. B. M. J.

2013-08-01

The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.

On the relationship between two popular lattice models for polymer melts

Science.gov (United States)

Subramanian, Gopinath; Shanbhag, Sachin

2008-10-01

A mapping between two well known lattice bond-fluctuation models for polymers [I. Carmesin and K. Kremer, Macromolecules 21, 2819 (1988); J. S. Shaffer, J. Chem. Phys. 101, 4205 (1994)] is investigated by performing primitive path analysis to identify the average number of monomers per entanglement. Simulations conducted using both models, and previously published data are compared in an attempt to establish relationships between molecular weight, lengthscale, and timescale. Using these relationships, an examination of the self-diffusion coefficient yields excellent agreement not only between the two models, but also with experimental data on polystyrene, polybutadiene, and polydimethylsiloxane. However, it is shown that even with the limited set of criteria examined in this paper, a true mapping between these two models is elusive. Nevertheless, a practical guide to convert between models is provided.

Game Theory and its Relationship with Linear Programming Models ...

African Journals Online (AJOL)

Game Theory and its Relationship with Linear Programming Models. ... This paper shows that game theory and linear programming problem are closely related subjects since any computing method devised for ... AJOL African Journals Online.

Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

Science.gov (United States)

Yamaura, Yuichi; Connor, Edward F.; Royle, Andy; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

2016-01-01

Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied

Modeling of microstructure property relationships in titanium-aluminum-vanadium

Science.gov (United States)

Tiley, Jaimie Scott

Fuzzy logic neural network models were developed to predict the room temperature tensile behavior of Ti-6Al-4V. This involved the development of a database relating microstructure to properties. This necessitated establishing heat treatment processes to develop microstructural features, mechanical testing of samples, creating rigorous stereology procedures, developing numerical models to predict mechanical behavior, and determining trends and inter-relationships relating microstructural features to mechanical properties. Microstructural features were developed using a Gleeble(TM) 1500 Thermal-mechanical simulator. Samples were obtained from mill annealed plate material and both alpha + beta forged and beta forged materials. A total of 72 samples were beta solutionized and heat treated using different heating and cooling conditions. Rigorous stereology procedures were developed to characterize the important microstructural features. The features included Widmanstatten alpha lath thickness, volume fraction of total alpha, volume fraction of Widmanstatten alpha, grain boundary alpha thickness, mean edge length, colony scale factor, and prior beta grain size factor. Chemical composition was also determined using standard chemical analysis and microscopy techniques. The samples were tested for yield strength, ultimate tensile strength, and elongation at room temperature. Results from the tests and the characterization were used to develop fuzzy logic neural network models to predict the mechanical behaviors and develop relationships between the microstructural features (using CubiCalc RTC(TM)). Results were compared to standard multi-variable regression models. The fuzzy logic neural network models were able to predict the yield, and ultimate tensile strength, within acceptable error ranges with a limited number of input data samples. The models also predicted the elongation values but with larger errors. Of particular importance, the models identified the importance of

Incentive Model Based on Cooperative Relationship in Sustainable Construction Projects

Directory of Open Access Journals (Sweden)

Guangdong Wu

2017-07-01

Full Text Available Considering the cooperative relationship between owners and contractors in sustainable construction projects, as well as the synergistic effects created by cooperative behaviors, a cooperative incentive model was developed using game theory. The model was formulated and analyzed under both non-moral hazard and moral hazard situations. Then, a numerical simulation and example were proposed to verify the conclusions derived from the model. The results showed that the synergistic effect increases the input intensity of one party’s resource transfer into the increase of marginal utility of the other party, thus the owner and contractor are willing to enhance their levels of effort. One party’s optimal benefit allocation coefficient is positively affected by its own output efficiency, and negatively affected by the other party’s output efficiency. The effort level and expected benefits of the owner and contractor can be improved by enhancing the cooperative relationship between the two parties, as well as enhancing the net benefits of a sustainable construction project. The synergistic effect cannot lower the negative effect of moral hazard behaviors during the implementation of sustainable construction projects. Conversely, the higher levels of the cooperative relationship, the wider the gaps amongst the optimal values under both non-moral hazard and moral hazard situations for the levels of effort, expected benefits and net project benefits. Since few studies to date have emphasized the effects of cooperative relationship on sustainable construction projects, this study constructed a game-based incentive model to bridge the gaps. This study contributes significant theoretical and practical insights into the management of cooperation amongst stakeholders, and into the enhancement of the overall benefits of sustainable construction projects.

A continuum model for pressure-flow relationship in human pulmonary circulation.

Science.gov (United States)

Huang, Wei; Zhou, Qinlian; Gao, Jian; Yen, R T

2011-06-01

A continuum model was introduced to analyze the pressure-flow relationship for steady flow in human pulmonary circulation. The continuum approach was based on the principles of continuum mechanics in conjunction with detailed measurement of vascular geometry, vascular elasticity and blood rheology. The pulmonary arteries and veins were considered as elastic tubes and the "fifth-power law" was used to describe the pressure-flow relationship. For pulmonary capillaries, the "sheet-flow" theory was employed and the pressure-flow relationship was represented by the "fourth-power law". In this paper, the pressure-flow relationship for the whole pulmonary circulation and the longitudinal pressure distribution along the streamlines were studied. Our computed data showed general agreement with the experimental data for the normal subjects and the patients with mitral stenosis and chronic bronchitis in the literature. In conclusion, our continuum model can be used to predict the changes of steady flow in human pulmonary circulation.

Development-based Trust: Proposing and Validating a New Trust Measurement Model for Buyer-Seller Relationships

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José Mauro da Costa Hernandez

2010-04-01

Full Text Available This study proposes and validates a trust measurement model for buyer-seller relationships. Baptized as development-based trust, the model encompasses three dimensions of trust: calculus-based, knowledge-based and identification-based. In addition to recognizing that trust is a multidimensional construct, the model also assumes that trust can evolve to take on a different character depending on the stage of the relationship. In order to test the proposed model and compare it to the characteristic-based trust measurement model, the measure most frequently used in the buyer-seller relationship literature, data were collected from 238 clients of an IT product wholesaler. The results show that the scales are valid and reliable and the proposed development-based trust measurement model is superior to the characteristic-based trust measurement model in terms of its ability to explain certain variables of interest in buyer-seller relationships (long-term relationship orientation, information sharing, behavioral loyalty and future intentions. Implications for practice, limitations and suggestions for future studies are discussed.

Modeling the Relationships between Subdimensions of Environmental Literacy

Science.gov (United States)

Genc, Murat; Akilli, Mustafa

2016-01-01

The aim of this study is to demonstrate the relationships between subdimensions of environmental literacy using Structural Equation Modeling (SEM). The study was conducted by the analysis of students' answers to questionnaires data using SEM. Initially, Kaiser-Meyer-Olkin and Bartlett's tests were done to test appropriateness of subdimensions to…

EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality

Science.gov (United States)

Masselot, Pierre; Chebana, Fateh; Bélanger, Diane; St-Hilaire, André; Abdous, Belkacem; Gosselin, Pierre; Ouarda, Taha B. M. J.

2018-01-01

In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of advantages. First, it accounts of the issues of non-stationarity associated to the data series. Second, this approach acts as a scan for the relationship between a response variable and the predictors at different time scales, providing new insights about this relationship. To illustrate the proposed methodology it is applied to study the relationship between weather and cardiovascular mortality in Montreal, Canada. The results shed new knowledge concerning the studied relationship. For instance, they show that the humidity can cause excess mortality at the monthly time scale, which is a scale not visible in classical models. A comparison is also conducted with state of the art methods which are the generalized additive models and distributed lag models, both widely used in weather-related health studies. The comparison shows that EMD-regression achieves better prediction performances and provides more details than classical models concerning the relationship.

Structure-based predictions of 13C-NMR chemical shifts for a series of 2-functionalized 5-(methylsulfonyl)-1-phenyl-1H-indoles derivatives using GA-based MLR method

Science.gov (United States)

Ghavami, Raouf; Sadeghi, Faridoon; Rasouli, Zolikha; Djannati, Farhad

2012-12-01

Experimental values for the 13C NMR chemical shifts (ppm, TMS = 0) at 300 K ranging from 96.28 ppm (C4' of indole derivative 17) to 159.93 ppm (C4' of indole derivative 23) relative to deuteride chloroform (CDCl3, 77.0 ppm) or dimethylsulfoxide (DMSO, 39.50 ppm) as internal reference in CDCl3 or DMSO-d6 solutions have been collected from literature for thirty 2-functionalized 5-(methylsulfonyl)-1-phenyl-1H-indole derivatives containing different substituted groups. An effective quantitative structure-property relationship (QSPR) models were built using hybrid method combining genetic algorithm (GA) based on stepwise selection multiple linear regression (SWS-MLR) as feature-selection tools and correlation models between each carbon atom of indole derivative and calculated descriptors. Each compound was depicted by molecular structural descriptors that encode constitutional, topological, geometrical, electrostatic, and quantum chemical features. The accuracy of all developed models were confirmed using different types of internal and external procedures and various statistical tests. Furthermore, the domain of applicability for each model which indicates the area of reliable predictions was defined.

Prediction of octanol-water partition coefficients of organic compounds by multiple linear regression, partial least squares, and artificial neural network.

Science.gov (United States)

Golmohammadi, Hassan

2009-11-30

A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structure of 141 organic compounds to their octanol-water partition coefficients (log P(o/w)). A genetic algorithm was applied as a variable selection tool. Modeling of log P(o/w) of these compounds as a function of theoretically derived descriptors was established by multiple linear regression (MLR), partial least squares (PLS), and artificial neural network (ANN). The best selected descriptors that appear in the models are: atomic charge weighted partial positively charged surface area (PPSA-3), fractional atomic charge weighted partial positive surface area (FPSA-3), minimum atomic partial charge (Qmin), molecular volume (MV), total dipole moment of molecule (mu), maximum antibonding contribution of a molecule orbital in the molecule (MAC), and maximum free valency of a C atom in the molecule (MFV). The result obtained showed the ability of developed artificial neural network to prediction of partition coefficients of organic compounds. Also, the results revealed the superiority of ANN over the MLR and PLS models. Copyright 2009 Wiley Periodicals, Inc.

Mining for elastic constants of intermetallics from the charge density landscape

Energy Technology Data Exchange (ETDEWEB)

Kong, Chang Sun; Broderick, Scott R. [Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011 (United States); Jones, Travis E. [Molecular Theory Group, Colorado School of Mines, Golden, CO 80401 (United States); Loyola, Claudia [Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011 (United States); Eberhart, Mark E. [Molecular Theory Group, Colorado School of Mines, Golden, CO 80401 (United States); Rajan, Krishna, E-mail: krajan@iastate.edu [Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011 (United States)

2015-02-01

There is a significant challenge in designing new materials for targeted properties based on their electronic structure. While in principle this goal can be met using knowledge of the electron charge density, the relationships between the density and properties are largely unknown. To help overcome this problem we develop a quantitative structure–property relationship (QSPR) between the charge density and the elastic constants for B2 intermetallics. Using a combination of informatics techniques for screening all the potentially relevant charge density descriptors, we find that C{sub 11} and C{sub 44} are determined solely from the magnitude of the charge density at its critical points, while C{sub 12} is determined by the shape of the charge density at its critical points. From this reduced charge density selection space, we develop models for predicting the elastic constants of an expanded number of intermetallic systems, which we then use to predict the mechanical stability of new systems. Having reduced the descriptors necessary for modeling elastic constants, statistical learning approaches may then be used to predict the reduced knowledge-based required as a function of the constituent characteristics.

An explanatory model regarding the relationships between psychological traits and creativity

Directory of Open Access Journals (Sweden)

María Luisa Sanz de Acedo Lizarraga

2014-01-01

Full Text Available This research tested a theoretical model of the relationships between certain psychological variables and creativity. Specifically, the relationships among intelligence, personality, intrinsic motivation, creative self-efficacy, and ideational creativity were examined. This study was conducted with a sample of 180 college students (136 women and 44 men who were evaluated with regard to the variables above in two sessions outside the regular academic schedule. The results obtained via structural equation analysis supported the model and revealed that the independent variables (intelligence and personality and the intermediate variables (intrinsic motivation and creative self-efficacy that comprise the proposed model influenced creativity. Furthermore, creative self-efficacy was the most significant trait associated with ideational creativity.

MARKETING RELATIONSHIP AND TRADING IN THE RELATIONSHIP BETWEEN SERVICE PROVIDERS, HEALTH OPERATORS AND FINAL CUSTOMER: THE SEARCH FOR AN INTEGRATING MODEL

Directory of Open Access Journals (Sweden)

Nilda Catalina, Tañski

2012-01-01

Full Text Available The marketing relationship finds similarities with the concept of cooperative bargaining, the purpose of this is to find solutions to mutual gains with long-term vision. Within this approach, we sought to build an integrative model of relationship marketing and negotiation in the relationship between service providers, health operators and final customers in the health plan market in Brazil, this relationship is complex, full of conflicts and stagnation. It was first used, first, as an exploratory research of direct observation of the phenomenon referred to relationship marketing, trading and health insurance to increase employment opportunities. Then, the method of data collection was in that environment through online questionnaires using the survey method, in the representative sector. The type of sample used, where n = 217 and the confidence level was 95%, not intentional probabilistic. In the final, it was concluded that the initially proposed model was fully accepted, taking into account the choice of methodology, then achieving the main objective of this study.

Derivatives in discrete mathematics: a novel graph-theoretical invariant for generating new 2/3D molecular descriptors. I. Theory and QSPR application.

Science.gov (United States)

Marrero-Ponce, Yovani; Santiago, Oscar Martínez; López, Yoan Martínez; Barigye, Stephen J; Torrens, Francisco

2012-11-01

among different atoms, an atomic weighting scheme (atom-type labels) is used in the formation of the matrix Q or in LOVIs state. The obtained indices were utilized to describe the partition coefficient (Log P) and the reactivity index (Log K) of the 34 derivatives of 2-furylethylenes. In all the cases, our MDs showed better statistical results than those previously obtained using some of the most used families of MDs in chemometric practice. Therefore, it has been demonstrated to that the proposed MDs are useful in molecular design and permit obtaining easier and robust mathematical models than the majority of those reported in the literature. All this range of mentioned possibilities open "the doors" to the creation of a new family of MDs, using the graph derivative, and avail a new tool for QSAR/QSPR and molecular diversity/similarity studies.

How an Evolution View of Workplace Mentoring Relationships Helps Avoid Negative Experiences: The Developmental Relationship Mentoring Model in Action

Science.gov (United States)

Washington, Rhianon; Cox, Elaine

2016-01-01

In this paper, we explore how the use of a specific mentoring model focusing on the evolution of the relationship between mentor and mentee, may influence the incidence of failure. In our research we employed a case study methodology to examine a regional public service mentoring scheme in the UK where a developmental relationship mentoring model…

A Relationship Strategy Perspective on Relationship Portfolios

DEFF Research Database (Denmark)

Ritter, Thomas; Andersen, Henrik

2014-01-01

The paper develops a three-dimensional portfolio model for business relationships which distinguishes among six different categories. Based on assessments of customer profitability, customer commitment, and growth potential, the positioning of a given customer relationship in the portfolio allows...... managers to determine appropriate customer relationship strategies and appropriate performance indicators. Results from applying the portfolio model are reported and managerial implications and future research are discussed.......The paper develops a three-dimensional portfolio model for business relationships which distinguishes among six different categories. Based on assessments of customer profitability, customer commitment, and growth potential, the positioning of a given customer relationship in the portfolio allows...

Dose-response relationships for environmentally mediated infectious disease transmission models.

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Andrew F Brouwer

2017-04-01

Full Text Available Environmentally mediated infectious disease transmission models provide a mechanistic approach to examining environmental interventions for outbreaks, such as water treatment or surface decontamination. The shift from the classical SIR framework to one incorporating the environment requires codifying the relationship between exposure to environmental pathogens and infection, i.e. the dose-response relationship. Much of the work characterizing the functional forms of dose-response relationships has used statistical fit to experimental data. However, there has been little research examining the consequences of the choice of functional form in the context of transmission dynamics. To this end, we identify four properties of dose-response functions that should be considered when selecting a functional form: low-dose linearity, scalability, concavity, and whether it is a single-hit model. We find that i middle- and high-dose data do not constrain the low-dose response, and different dose-response forms that are equally plausible given the data can lead to significant differences in simulated outbreak dynamics; ii the choice of how to aggregate continuous exposure into discrete doses can impact the modeled force of infection; iii low-dose linear, concave functions allow the basic reproduction number to control global dynamics; and iv identifiability analysis offers a way to manage multiple sources of uncertainty and leverage environmental monitoring to make inference about infectivity. By applying an environmentally mediated infectious disease model to the 1993 Milwaukee Cryptosporidium outbreak, we demonstrate that environmental monitoring allows for inference regarding the infectivity of the pathogen and thus improves our ability to identify outbreak characteristics such as pathogen strain.

Parent-adolescent relationship and adolescent internet addiction: A moderated mediation model.

Science.gov (United States)

Wang, Wei; Li, Dongping; Li, Xian; Wang, Yanhui; Sun, Wenqiang; Zhao, Liyan; Qiu, Lilan

2018-09-01

Substantial research has found that positive parent-adolescent relationship is associated with low levels of adolescent Internet addiction (IA). However, little is known about the mediating and moderating mechanisms underlying this relation. The present study examined a moderated mediation model that included the parent-adolescent relationship (predictor variable), emotion regulation ability (mediator), stressful life events (moderator), and IA (outcome variable) simultaneously. A total of 998 (M age  = 15.15 years, SD = 1.57) Chinese adolescents completed the Parent-Adolescent Relationship Scale, Emotion Regulation Ability Scale, Adolescent Stressful Life Events Scale, and Internet Addiction Diagnostic Questionnaire. After controlling for adolescent gender, age, and family socioeconomic status, results revealed that good parent-adolescent relationship was positively associated with adolescent emotion regulation ability, which in turn was negatively associated with their IA. Moreover, stressful life events moderated the second part of the mediation process. In accordance with the reverse stress-buffering model, the relation between emotion regulation ability and adolescent IA was stronger for adolescents who experienced lower levels of stressful life events. The findings and their implications are discussed and a resilient contextual perspective proposed. Copyright © 2018 Elsevier Ltd. All rights reserved.

A conceptual model for ethical business decision-making under the influence of personal relationships

OpenAIRE

Davidrajuh, Reggie

2008-01-01

This paper proposes a conceptual model for ethical business decision-making. The purpose of this model is to explore the ethical implications of personal relationship in business exchanges. Firstly, this paper introduces personal relationship in business exchanges. Secondly, three normative theories of ethics that are relevant to the business environment are presented. Thirdly, a literature study on the existing models and frameworks for ethical business decision-making is pres...

Prediction of ferric iron precipitation in bioleaching process using partial least squares and artificial neural network

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Golmohammadi Hassan

2013-01-01

Full Text Available A quantitative structure-property relationship (QSPR study based on partial least squares (PLS and artificial neural network (ANN was developed for the prediction of ferric iron precipitation in bioleaching process. The leaching temperature, initial pH, oxidation/reduction potential (ORP, ferrous concentration and particle size of ore were used as inputs to the network. The output of the model was ferric iron precipitation. The optimal condition of the neural network was obtained by adjusting various parameters by trial-and-error. After optimization and training of the network according to back-propagation algorithm, a 5-5-1 neural network was generated for prediction of ferric iron precipitation. The root mean square error for the neural network calculated ferric iron precipitation for training, prediction and validation set are 32.860, 40.739 and 35.890, respectively, which are smaller than those obtained by PLS model (180.972, 165.047 and 149.950, respectively. Results obtained reveal the reliability and good predictivity of neural network model for the prediction of ferric iron precipitation in bioleaching process.

Model Pengukuran Kinerja Customer Relationship Management dalam Industri Perbankan

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Freddy Simbolon

2014-05-01

Full Text Available High competition in the banking industry requires the banking industry to properly manage relationships with customers, as it is known as Customer Relationship Management (CRM. CRM applications will become effective when supported by information technology. Investment in information technology is not a small investment, because the higher the information technology, the greater the value of the investment. This study aims to obtain a model of CRM performance measurement in the banking industry efficiently and effective. The method in this study uses descriptive analytical method, while the results obtained in this study is a CRM Scorecard. CRM Scorecard is one of the approach models that correctly measure the performance of CRM, which is based on information technology. Through CRM Scorecard approach, information technology investment in CRM is no longer seen as a cost center, but seen to be a profit center, because the company can manage customers efficiently and effectively in order to enhance shareholder value in the future.

Relationship Marketing results: proposition of a cognitive mapping model

Directory of Open Access Journals (Sweden)

Iná Futino Barreto

2015-12-01

Full Text Available Objective - This research sought to develop a cognitive model that expresses how marketing professionals understand the relationship between the constructs that define relationship marketing (RM. It also tried to understand, using the obtained model, how objectives in this field are achieved. Design/methodology/approach – Through cognitive mapping, we traced 35 individual mental maps, highlighting how each respondent understands the interactions between RM elements. Based on the views of these individuals, we established an aggregate mental map. Theoretical foundation – The topic is based on a literature review that explores the RM concept and its main elements. Based on this review, we listed eleven main constructs. Findings – We established an aggregate mental map that represents the RM structural model. Model analysis identified that CLV is understood as the final result of RM. We also observed that the impact of most of the RM elements on CLV is brokered by loyalty. Personalization and quality, on the other hand, proved to be process input elements, and are the ones that most strongly impact others. Finally, we highlight that elements that punish customers are much less effective than elements that benefit them. Contributions - The model was able to insert core elements of RM, but absent from most formal models: CLV and customization. The analysis allowed us to understand the interactions between the RM elements and how the end result of RM (CLV is formed. This understanding improves knowledge on the subject and helps guide, assess and correct actions.

Relationship between US Societal Fatality Risk per Vehicle Miles of Travel and Mass, for Individual Vehicle Models over Time (Model Year)

Energy Technology Data Exchange (ETDEWEB)

Wenzel, Tom P. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Technologies Area. Building Technology and Urban Systems Division

2016-07-27

This report presents a new approach to analyze the relationship between vehicle mass and risk: tracking fatality risk by vehicle model year and mass, for individual vehicle models. This approach is appealing as it greatly minimizes the influence of driver characteristics and behavior, and crash circumstances, on fatality risk. However, only the most popular vehicle models, with the largest number of fatalities, can be analyzed in this manner. While the analysis of all vehicle models of a given type suggests that there is a relationship between increased mass and fatality risk, analysis of the ten most popular four-door car models separately suggests that this relationship is weak: in many cases when the mass of a specific vehicle model is increased societal fatality risk is unchanged or even increases. These results suggest that increasing the mass of an individual vehicle model does not necessarily lead to decreased societal fatality risk.

A Socio-Cultural Model Based on Empirical Data of Cultural and Social Relationship

DEFF Research Database (Denmark)

Lipi, Afia Akhter; Nakano, Yukiko; Rehm, Matthias

2010-01-01

The goal of this paper is to integrate culture and social relationship as a computational term in an embodied conversational agent system by employing empirical and theoretical approach. We propose a parameter-based model that predicts nonverbal expressions appropriate for specific cultures...... in different social relationship. So, first, we introduce the theories of social and cultural characteristics. Then, we did corpus analysis of human interaction of two cultures in two different social situations and extracted empirical data and finally, by integrating socio-cultural characteristics...... with empirical data, we establish a parameterized network model that generates culture specific non-verbal expressions in different social relationships....

NONPARAMETRIC FIXED EFFECT PANEL DATA MODELS: RELATIONSHIP BETWEEN AIR POLLUTION AND INCOME FOR TURKEY

Directory of Open Access Journals (Sweden)

Rabia Ece OMAY

2013-06-01

Full Text Available In this study, relationship between gross domestic product (GDP per capita and sulfur dioxide (SO2 and particulate matter (PM10 per capita is modeled for Turkey. Nonparametric fixed effect panel data analysis is used for the modeling. The panel data covers 12 territories, in first level of Nomenclature of Territorial Units for Statistics (NUTS, for period of 1990-2001. Modeling of the relationship between GDP and SO2 and PM10 for Turkey, the non-parametric models have given good results.

What do short-term and long-term relationships look like? Building the relationship coordination and strategic timing (ReCAST) model.

Science.gov (United States)

Eastwick, Paul W; Keneski, Elizabeth; Morgan, Taylor A; McDonald, Meagan A; Huang, Sabrina A

2018-05-01

Close relationships research has examined committed couples (e.g., dating relationships, marriages) using intensive methods that plot relationship development over time. But a substantial proportion of people's real-life sexual experiences take place (a) before committed relationships become "official" and (b) in short-term relationships; methods that document the time course of relationships have rarely been applied to these contexts. We adapted a classic relationship trajectory-plotting technique to generate the first empirical comparisons between the features of people's real-life short-term and long-term relationships across their entire timespan. Five studies compared long-term and short-term relationships in terms of the timing of relationship milestones (e.g., flirting, first sexual intercourse) and the occurrence/intensity of important relationship experiences (e.g., romantic interest, strong sexual desire, attachment). As romantic interest was rising and partners were becoming acquainted, long-term and short-term relationships were indistinguishable. Eventually, romantic interest in short-term relationships plateaued and declined while romantic interest in long-term relationships continued to rise, ultimately reaching a higher peak. As relationships progressed, participants evidenced more features characteristic of the attachment-behavioral system (e.g., attachment, caregiving) in long-term than short-term relationships but similar levels of other features (e.g., sexual desire, self-promotion, intrasexual competition). These data inform a new synthesis of close relationships and evolutionary psychological perspectives called the Relationship Coordination and Strategic Timing (ReCAST) model. ReCAST depicts short-term and long-term relationships as partially overlapping trajectories (rather than relationships initiated with distinct strategies) that differ in their progression along a normative relationship development sequence. (PsycINFO Database Record (c

Competing probabilistic models for catch-effort relationships in wildlife censuses

Energy Technology Data Exchange (ETDEWEB)

Skalski, J.R.; Robson, D.S.; Matsuzaki, C.L.

1983-01-01

Two probabilistic models are presented for describing the chance that an animal is captured during a wildlife census, as a function of trapping effort. The models in turn are used to propose relationships between sampling intensity and catch-per-unit-effort (C.P.U.E.) that were field tested on small mammal populations. Capture data suggests a model of diminshing C.P.U.E. with increasing levels of trapping intensity. The catch-effort model is used to illustrate optimization procedures in the design of mark-recapture experiments for censusing wild populations. 14 references, 2 tables.

Vp-Vs relationship and amplitude variation with offset modelling of glauconitic greensand

DEFF Research Database (Denmark)

Hossain, Zakir; Mukerji, Tapan; Fabricius, Ida Lykke

2012-01-01

The relationship between Vp and Vs may be used to predict Vs where only Vp is known. Vp/Vs is also used to identify pore fluids from seismic data and amplitude variation with offset analysis. Theoretical, physical, as well as statistical empirical Vp-Vs relationships have been proposed...... modelling works well for greensand shear-wave velocity prediction. We model the seismic response of glauconitic greensand by using laboratory data from the Nini field. Our studies here reveal that brine-saturated glauconitic greensand can have a similar seismic response to that from oil-saturated quartzitic...

The relationship between relational models and individualism and collectivism: evidence from culturally diverse work groups.

Science.gov (United States)

Vodosek, Markus

2009-04-01

Relational models theory (Fiske, 1991 ) proposes that all thinking about social relationships is based on four elementary mental models: communal sharing, authority ranking, equality matching, and market pricing. Triandis and his colleagues (e.g., Triandis, Kurowski, & Gelfand, 1994 ) have suggested a relationship between the constructs of horizontal and vertical individualism and collectivism and Fiske's relational models. However, no previous research has examined this proposed relationship empirically. The objective of the current study was to test the association between the two frameworks in order to further our understanding of why members of culturally diverse groups may prefer different relational models in interactions with other group members. Findings from this study support a relationship between Triandis' constructs and Fiske's four relational models and uphold Fiske's ( 1991 ) claim that the use of the relational models is culturally dependent. As hypothesized, horizontal collectivism was associated with a preference for equality matching and communal sharing, vertical individualism was related to a preference for authority ranking, and vertical collectivism was related to a preference for authority ranking and communal sharing. However, contrary to expectations, horizontal individualism was not related to a preference for equality matching and market pricing, and vertical individualism was not associated with market pricing. By showing that there is a relationship between Triandis' and Fiske's frameworks, this study closes a gap in relational models theory, namely how culture relates to people's preferences for relational models. Thus, the findings from this study will enable future researchers to explain and predict what relational models are likely to be used in a certain cultural context.

Selecting an optimal mixed products using grey relationship model

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Farshad Faezy Razi

2013-06-01

Full Text Available This paper presents an integrated supplier selection and inventory management using grey relationship model (GRM as well as multi-objective decision making process. The proposed model of this paper first ranks different suppliers based on GRM technique and then determines the optimum level of inventory by considering different objectives. To show the implementation of the proposed model, we use some benchmark data presented by Talluri and Baker [Talluri, S., & Baker, R. C. (2002. A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research, 141(3, 544-558.]. The preliminary results indicate that the proposed model of this paper is capable of handling different criteria for supplier selection.

Training mode's influences on the relationships between training-load models during basketball conditioning.

Science.gov (United States)

Scanlan, Aaron T; Wen, Neal; Tucker, Patrick S; Borges, Nattai R; Dalbo, Vincent J

2014-09-01

To compare perceptual and physiological training-load responses during various basketball training modes. Eight semiprofessional male basketball players (age 26.3 ± 6.7 y, height 188.1 ± 6.2 cm, body mass 92.0 ± 13.8 kg) were monitored across a 10-wk period in the preparatory phase of their training plan. Player session ratings of perceived exertion (sRPE) and heart-rate (HR) responses were gathered across base, specific, and tactical/game-play training modes. Pearson correlations were used to determine the relationships between the sRPE model and 2 HR-based models: the training impulse (TRIMP) and summated HR zones (SHRZ). One-way ANOVAs were used to compare training loads between training modes for each model. Stronger relationships between perceptual and physiological models were evident during base (sRPE-TRIMP r = .53, P training load than the TRIMP (15-65 AU) and SHRZ models (27-170 AU) transitioning between training modes. While the training-load models were significantly correlated during each training mode, weaker relationships were observed during specific conditioning. Comparisons suggest that the HR-based models were less effective in detecting periodized increases in training load, particularly during court-based, intermittent, multidirectional drills. The practical benefits and sensitivity of the sRPE model support its use across different basketball training modes.

Refusal of Treatment by Mentally Competent Patient: The Choice of Doctor-Patient Relationship Models

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Andrei M. Beliaev

2010-01-01

Full Text Available Introduction: In modern medicine professional relationship between the clinician and the patient is patient-centered. Patients become actively involved in the treatment decision making process and are encouraged to express their health-related preferences. Some patients may, however, refuse a favorable risk/benefit ratio treatment. This manuscript presents three cases of refusal of treatment by mentally competent surgical patients and discusses differences in their management. Conclusion: To achieve the best medical outcome for patients who possess the Actual Understanding test of mental competence clinicians use the deliberate model of medical professional relationship. For patients demonstrating the Understanding test of mental competence and wishing to utilize their health-related preferences physicians are obliged to deploy the interpretive model of doctor-patient relationship. In mentally competent patients with an illness-induced acute psychological regression the interpretive model of doctor-patient relationship as an initial strategy and cognitive behavior therapy can be useful in modifying treatment rejecting behavior and improving medical outcome.

Infertile Individuals’ Marital Relationship Status, Happiness, and Mental Health: A Causal Model

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Seyed Habiballah Ahmadi Forooshany

2014-11-01

Full Text Available Background: This study examined the causal model of relation between marital relationship status, happiness, and mental health in infertile individuals. Materials and Methods: In this descriptive study, 155 subjects (men: 52 and women: 78, who had been visited in one of the infertility Centers, voluntarily participated in a self-evaluation. Golombok Rust Inventory of Marital Status, Oxford Happiness Questionnaire, and General Health Questionnaire were used as instruments of the study. Data was analyzed by SPSS17 and Amos 5 software using descriptive statistics, independent sample t test, and path analysis. Results: Disregarding the gender factor, marital relationship status was directly related to happiness (p<0.05 and happiness was directly related to mental health, (p<0.05. Also, indirect relation between marital relationship status and mental health was significant (p<0.05. These results were confirmed in women participants but in men participants only the direct relation between happiness and mental health was significant (p<0.05. Conclusion: Based on goodness of model fit in fitness indexes, happiness had a mediator role in relation between marital relationship status and mental health in infertile individuals disregarding the gender factor. Also, considering the gender factor, only in infertile women, marital relationship status can directly and indirectly affect happiness and mental health.

Using fuzzy models to migrate from customer relationship management (CRM) to customer experience management (CEM)

OpenAIRE

Dr. Anna Maria Gil-Lafuente; Carolina Luis-Bassa

2011-01-01

Relationship Marketing has made rapid progress during the last ten years. Since the development of the customer-centric model, reinforced by the emergence of CRM (Customer Relationship Management) strategies, companies have focused on finding models and tools that allow them to get to know better their clients. The management of customer relationship with the company has evolved from seeking the customer satisfaction to seek customer loyalty, and later on to create a brand advocate consumer f...

Scaling and constitutive relationships in downcomer modeling

International Nuclear Information System (INIS)

Daly, B.J.; Harlow, F.H.

1978-12-01

Constitutive relationships to describe mass and momentum exchange in multiphase flow in a pressurized water reactor downcomer are presented. Momentum exchange between the phases is described by the product of the flux of momentum available for exchange and the effective area for interaction. The exchange of mass through condensation is assumed to occur along a distinct condensation boundary separating steam at saturation temperature from water in which the temperature falls off roughly linearly with distance from the boundary. Because of the abundance of nucleation sites in a typical churning flow in a downcomer, we propose an equilibrium evaporation process that produces sufficient steam per unit time to keep the water perpetually cooled to the saturation temperature. The transport equations, constitutive models, and boundary conditions used in the K-TIF numerical method are nondimensionalized to obtain scaling relationships for two-phase flow in the downcomer. The results indicate that, subject to idealized thermodynamic and hydraulic constraints, exact mathematical scaling can be achieved. Experiments are proposed to isolate the effects of parameters that contribute to mass, momentum, and energy exchange between the phases

HydroCube: an entity-relationship hydrogeological data model

Science.gov (United States)

Wojda, Piotr; Brouyère, Serge; Derouane, Johan; Dassargues, Alain

2010-12-01

Managing, handling and accessing hydrogeological information depends heavily on the applied hydrogeological data models, which differ between institutions and countries. The effective dissemination of hydrogeological information requires the convergence of such models to make hydrogeological information accessible to multiple users such as universities, water suppliers, and administration and research organisations. Furthermore, because hydrogeological studies are complex, they require a wide variety of high-quality hydrogeological data with appropriate metadata in clearly designed and coherent structures. A need exists, therefore, to develop and implement hydrogeological data models that cover, as much as possible, the full hydrogeological domain. A new data model, called HydroCube, was developed for the Walloon Region in Belgium in 2005. The HydroCube model presents an innovative holistic project-based approach which covers a full set of hydrogeological concepts and features, allowing for effective hydrogeological project management. The model stores data relating to the project locality, hydrogeological equipment, and related observations and measurements. In particular, it focuses on specialized hydrogeological field experiments such as pumping and tracer tests. This logical data model uses entity-relationship diagrams and it has been implemented in the Microsoft Access environment. It has been enriched with a fully functional user interface.

Barriers to Effective Doctor-Patient Relationship Based on PRECEDE PROCEED Model

Science.gov (United States)

Ghaffarifar, Saeideh; Ghofranipour, Fazlollah; Ahmadi, Fazlollah; Khoshbaten, Manouchehr

2015-01-01

Objective: This study intends to investigate interns and faculty members’ insights into constructing relationship between physicians and patients at 3 more accredited Iranian universities of medical sciences. Method: Applying PRECEDE PROCEED model, semi-structured interviews were completed with 7 interns and 14 faculty members and two themes were emerged from directed content analysis. The meaning units of the first theme, barriers to effective doctor-patient relationship, are discussed in this paper. Results: According to the participants, building doctor-patient relationship is influenced by many contextual and regulatory factors as well as content, process and perceptual skills of physicians. Conclusions: Faculty and curriculum development, as well as foundation of the department of communication skills at medical schools are recommended to eliminate the impact of poor communication on patients’ satisfaction and physicians’ self-efficacy specific to their communication skills. Practice Implications: Applying theories and models of health education and health promotion, researchers and educators can use the most predictive constructs of theories to design and implement effective interventions. PMID:26153160

Estimation in a multiplicative mixed model involving a genetic relationship matrix

Directory of Open Access Journals (Sweden)

Eccleston John A

2009-04-01

Full Text Available Abstract Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

Simulating pattern-process relationships to validate landscape genetic models

Science.gov (United States)

A. J. Shirk; S. A. Cushman; E. L. Landguth

2012-01-01

Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all...

Object and subject relations in adulthood--towards an integrative model of interpersonal relationships.

Science.gov (United States)

Zvelc, Gregor

2010-12-01

In the article the author presents a model of interpersonal relationships based on integration of object relations theory and theory of attachment. He proposes three main bipolar dimensions of interpersonal relationships: Independence - Dependence, Connectedness - Alienation and Reciprocity - Self-absorption. The author also proposes that it is important to distinguish between two main types of adult interpersonal relationships: object and subject relations. Object relations describe relationships in which the other person is perceived as an object that serves the satisfaction of the first person's needs. Object relations are a manifestation of the right pole of the three main dimensions of interpersonal relationships (Dependence, Alienation and Self-absorption). Subject relations are a counter-pole to the concept of object relations. They describe relationships with other people who are experienced as subjects with their own wishes, interests and needs. Subject relations are a manifestation of the left pole of the main dimensions (Independence, Connectedness and Reciprocity). In this article the author specifically focuses on definitions of object relations in adulthood through a description of six sub-dimensions of object relations: Symbiotic Merging, Separation Anxiety, Social Isolation, Fear of Engulfment, Egocentrism and Narcissism. Every sub-dimension is described in connection to adaptive and pathological functioning. Further research is needed to test the clinical and scientific validity of the model.

SST and OLR relationship during Indian summer monsoon: a coupled climate modelling perspective

Science.gov (United States)

Chaudhari, Hemantkumar S.; Hazra, Anupam; Pokhrel, Samir; Chakrabarty, Chandrima; Saha, Subodh Kumar; Sreenivas, P.

2018-04-01

The study mainly investigates sea surface temperature (SST) and outgoing longwave radiation (OLR) relationships in coupled climate model. To support the analysis, high-level cloud and OLR relationship is also investigated. High-level cloud and OLR relationship depicts significant negative correlation over the entire monsoon regime. Coupled climate model is able to produce the same. SST and OLR relationship in observation also depicts significant negative relationship, in particular, over the Equatorial Eastern Indian Ocean (EIO) region. Climate Forecast System version 2 (CFSv2) is able to portray the negative relationship over EIO region; however, it is underestimated as compared to observation. Significant negative correlations elucidate that local SSTs regulate the convection and further it initiates Bjerknes feedback in the central Indian Ocean. It connotes that SST anomalies during monsoon period tend to be determined by oceanic forcing. The heat content of the coastal Bay of Bengal shows highest response to EIO SST by a lag of 1 month. It suggests that the coastal region of the Bay of Bengal is marked by coastally trapped Kelvin waves, which might have come from EIO at a time lag of 1 month. Sea surface height anomalies, depth at 20 °C isotherms and depth at 26 isotherms also supports the above hypothesis. Composite analysis based on EIO index and coupled climate model sensitivity experiments also suggest that the coastal Bay of Bengal region is marked by coastally trapped Kelvin waves, which are propagated from EIO at a time lag of 1 month. Thus, SST and OLR relationship pinpoints that the Bay of Bengal OLR (convection) is governed by local ocean-atmospheric coupling, which is influenced by the delayed response from EIO brought forward through oceanic planetary waves at a lag of 1 month. These results have utmost predictive value for seasonal and extended range forecasting. Thus, OLR and SST relationship can constitute a pivotal role in investigating the

Use of Occupancy Models to Evaluate Expert Knowledge-based Species-Habitat Relationships

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Monica N. Iglecia

2012-12-01

Full Text Available Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens and Brown-headed Nuthatch (Sitta pusilla, occupancy was strongly influenced by vegetation types classified as "optimal habitat" by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

Maintaining Sexual Desire in Long-Term Relationships: A Systematic Review and Conceptual Model.

Science.gov (United States)

Mark, Kristen P; Lasslo, Julie A

The most universally experienced sexual response is sexual desire. Though research on this topic has increased in recent years, low and high desire are still problematized in clinical settings and the broader culture. However, despite knowledge that sexual desire ebbs and flows both within and between individuals, and that problems with sexual desire are strongly linked to problems with relationships, there is a critical gap in understanding the factors that contribute to maintaining sexual desire in the context of relationships. This article offers a systematic review of the literature to provide researchers, educators, clinicians, and the broader public with an overview and a conceptual model of nonclinical sexual desire in long-term relationships. First, we systematically identified peer-reviewed, English-language articles that focused on the maintenance of sexual desire in the context of nonclinical romantic relationships. Second, we reviewed a total of 64 articles that met inclusion criteria and synthesized them into factors using a socioecological framework categorized as individual, interpersonal, and societal in nature. These findings are used to build a conceptual model of maintaining sexual desire in long-term relationships. Finally, we discuss the limitations of the existing research and suggest clear directions for future research.

Linear Equating for the NEAT Design: Parameter Substitution Models and Chained Linear Relationship Models

Science.gov (United States)

Kane, Michael T.; Mroch, Andrew A.; Suh, Youngsuk; Ripkey, Douglas R.

2009-01-01

This paper analyzes five linear equating models for the "nonequivalent groups with anchor test" (NEAT) design with internal anchors (i.e., the anchor test is part of the full test). The analysis employs a two-dimensional framework. The first dimension contrasts two general approaches to developing the equating relationship. Under a "parameter…

Military-related posttraumatic stress disorder and intimate relationship behaviors: a developing dyadic relationship model.

Science.gov (United States)

Gerlock, April A; Grimesey, Jackie; Sayre, George

2014-07-01

The protracted conflict in Iraq and Afghanistan and an all-volunteer military has resulted in multiple war zone deployments for many service members. While quick redeployment turnaround has left little time for readjustment for either the service member or family, dealing with the long-term sequelae of combat exposure often leaves families and intimate partners ill-prepared for years after deployments. Using a modified grounded theory approach, digitally recorded couple interviews of 23 couples were purposefully selected from a larger sample of 441 couples to better understand the impact of war zone deployment on the couple. The veteran sample was recruited from a randomly selected cohort of men in treatment for posttraumatic stress disorder (PTSD). Overall, it was found when veterans experiencing deployment-related PTSD reenter or start new intimate relationships they may bring with them a unique cluster of interrelated issues which include PTSD symptoms, physical impairment, high rates of alcohol and/or drug abuse, and psychological and physical aggression. These factors contributed to a dynamic of exacerbating conflict. How these couples approached relationship qualities of mutuality, balanced locus of control and weakness tolerance across six axes of caregiving, disability, responsibility, trauma, communication, and community impacted the couple's capacity to communicate and resolve conflict. This dyadic relationship model is used to help inform implications for clinical practice. © 2013 American Association for Marriage and Family Therapy.

The model relationship of wastes for parameter design with green lean production of fresh water

Directory of Open Access Journals (Sweden)

Mastiadi Tamjidillah

2017-12-01

Full Text Available Lean manufacturing is about eliminating waste including the seven traditional, this writing suggested an observation on no value added of seven wastes influencing the process of fresh water production. The relationship value among waste was statistically verified to create an approach for continuous improvement action. Thus, the main goal of this research is to develop a methodology of relationship among wastes and eliminate them. In relationship among wastes, it could be known that the high value indicating how often it happened in the production process gave direct cause in the system of fresh water treatment. A recommendation to reduce the highest value of waste is by doing improvement on parameter setting to obtain an optimum mixing model between water supply, alum and stroke pump with Taguchi method. The interaction of relationship among these seven types of waste can be portrayed using fishbone diagram and a relationship model among wastes using PLS smart (partial least squares. The final relationship model with the highest value of waste was analyzed using off-line quality control to upgrade the quality of fresh water used as the basis to eliminate waste and find out the optimal parameter of mixing process in accordance with the health standard.

Development of knowledge models by linguistic analysis of lexical relationships in technical documents

International Nuclear Information System (INIS)

Seguela, Patrick

2001-01-01

This research thesis addresses the problem of knowledge acquisition and structuring from technical texts, and the use of this knowledge in the development of models. The author presents the Cameleon method which aims at extracting binary lexical relationships from technical texts by identifying linguistic markers. The relevance of this method is assessed in the case of four different corpuses: a written technical corpus, an oral technical corpus, a corpus of texts of instructions, and a corpus of academic texts. The author reports the development of a model of representation of knowledge of a specific field by using lexical relationships. The method is then applied to develop a model used in document search within a knowledge management system [fr

Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR.

Science.gov (United States)

Winkler, David A; Le, Tu C

2017-01-01

Neural networks have generated valuable Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models for a wide variety of small molecules and materials properties. They have grown in sophistication and many of their initial problems have been overcome by modern mathematical techniques. QSAR studies have almost always used so-called "shallow" neural networks in which there is a single hidden layer between the input and output layers. Recently, a new and potentially paradigm-shifting type of neural network based on Deep Learning has appeared. Deep learning methods have generated impressive improvements in image and voice recognition, and are now being applied to QSAR and QSAR modelling. This paper describes the differences in approach between deep and shallow neural networks, compares their abilities to predict the properties of test sets for 15 large drug data sets (the kaggle set), discusses the results in terms of the Universal Approximation theorem for neural networks, and describes how DNN may ameliorate or remove troublesome "activity cliffs" in QSAR data sets. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

DESIGNING A MODEL OF CUSTOMER RELATIONSHIP MANAGEMENT FOR A MOBILE PHONE COMPANY

OpenAIRE

BRUTU MĂDĂLINA; MIHAI DANIELA MELANIA

2015-01-01

Customer relationship management refers to establishing, maintaining, developing and optimizing the relations between an organization and its customers and focuses on understanding and meeting its customers’ wishes and demands, the core items of the business strategy of any performant company. This paper aims at designing and testing a model of customer relationship management applicable within a mobile phone company. Starting from this purpose, the main objectives of the research were: prese...

Analysis of the Attachment-Aversion Model of Consumer-brand Relationships in a Different Cultural Background

Directory of Open Access Journals (Sweden)

Veranika Novik

2017-09-01

Full Text Available Originally the Attachment-Aversion model of consumer-brand relationships, elaborated by Park, Eisingerich & Park in 2013, was analyzed with the help of the sample of English speaking respondents, living in Great Britain and the USA, and focused on two brands: Manchester United Football Club and Apple iPhone. The present study tries to validate the model regarding other type of brand and in conditions of another cultural background. The focal brand for the study was chosen from a high-end beauty category (Chanel. For the purposes of this research, a questionnaire was designed and spread online within the target population: the current students and alumni of Belarusian universities that are Russian/speaking, fluent in English and had a class in branding. A total of 273 responses was analysed using structural equation modelling. The outcomes of the research have shown that the Attachment-Aversion model of consumer-brand relationships has not proven to be totally versatile, while applied in the conditions of the other cultural background as some of the relationships of the model have shown to be insignificant. The enticing determinant has no effect on brand attachment relationship and the enabling determinant has no effect on the brand prominence. The implications of the findings are discussed.

Modeling the relationship between family home environment factors and parental health.

Science.gov (United States)

Didericksen, Katharine Wickel; Berge, Jerica M

2015-06-01

Understanding parental health is an important part of understanding family health. Previous research suggests that family meals, familial relationship satisfaction, and family physical activity may separately be related to physical health. The current study aims to combine these variables into a structural equation model to determine the collective relationship they have with adult health within a sample of parents (n = 1,435). Most parents were married, White, and highly educated. The relationship between family meals and parental health was significant (β = -.07, t = -2.29, p Familial relationship satisfaction and family physical activity were not found to be associated with parental health. Exploratory findings of the sample stratified by biological sex are described. Findings from the current study were consistent with a systemic perspective in that parents may have health benefits when they participate in family-level behavior (e.g., family meals). Additional areas for research and limitations to the current study are also discussed. (c) 2015 APA, all rights reserved).

Cost model relationships between textile manufacturing processes and design details for transport fuselage elements

Science.gov (United States)

Metschan, Stephen L.; Wilden, Kurtis S.; Sharpless, Garrett C.; Andelman, Rich M.

1993-01-01

Textile manufacturing processes offer potential cost and weight advantages over traditional composite materials and processes for transport fuselage elements. In the current study, design cost modeling relationships between textile processes and element design details were developed. Such relationships are expected to help future aircraft designers to make timely decisions on the effect of design details and overall configurations on textile fabrication costs. The fundamental advantage of a design cost model is to insure that the element design is cost effective for the intended process. Trade studies on the effects of processing parameters also help to optimize the manufacturing steps for a particular structural element. Two methods of analyzing design detail/process cost relationships developed for the design cost model were pursued in the current study. The first makes use of existing databases and alternative cost modeling methods (e.g. detailed estimating). The second compares design cost model predictions with data collected during the fabrication of seven foot circumferential frames for ATCAS crown test panels. The process used in this case involves 2D dry braiding and resin transfer molding of curved 'J' cross section frame members having design details characteristic of the baseline ATCAS crown design.

Distensibility and pressure-flow relationship of the pulmonary circulation. II. Multibranched model.

Science.gov (United States)

Bshouty, Z; Younes, M

1990-04-01

The contribution of distensibility and recruitment to the distinctive behavior of the pulmonary circulation is not known. To examine this question we developed a multibranched model in which an arterial vascular bed bifurcates sequentially up to 8 parallel channels that converge and reunite at the venous side to end in the left atrium. Eight resistors representing the capillary bed separate the arterial and venous beds. The elastic behavior of capillaries and extra-alveolar vessels was modeled after Fung and Sobin (Circ. Res. 30: 451-490, 1972) and Smith and Mitzner (J. Appl. Physiol. 48: 450-467, 1980), respectively. Forces acting on each component are modified and calculated individually, thus enabling the user to explore the effects of parallel and longitudinal heterogeneities in applied forces (e.g., gravity, vasomotor tone). Model predictions indicate that the contribution of distensibility to nonlinearities in the pressure-flow (P-F) and atrial-pulmonary arterial pressure (Pla-Ppa) relationships is substantial, whereas gravity-related recruitment contributes very little to these relationships. In addition, Pla-Ppa relationships, obtained at a constant flow, have no discriminating ability in identifying the presence or absence of a waterfall along the circulation. The P-F relationship is routinely shifted in a parallel fashion, within the physiological flow range, whenever extra forces (e.g., lung volume, tone) are applied uniformly at one or more branching levels, regardless of whether a waterfall is created. For a given applied force, the magnitude of parallel shift varies with proportion of the circulation subjected to the added force and with Pla.

The coach-athlete relationship: a motivational model.

Science.gov (United States)

Mageau, Geneviève A; Vallerand, Robert J

2003-11-01

The aim of this paper is to present a motivational model of the coach-athlete relationship that describes how coaches may influence athletes' motivation. In line with cognitive evaluation theory (Deci and Ryan, 1980, 1985) and the hierarchical model of intrinsic and extrinsic motivation (Vallerand, 1997, 2000), a motivational sequence is proposed where coaches' personal orientation towards coaching, the context within which they operate, and their perceptions of their athletes' behaviour and motivation influence coaches' behaviours. Also, coaches' behaviours in the form of autonomy-supportive behaviours, provision of structure and involvement have a beneficial impact on athletes' needs for autonomy, competence and relatedness, which, in turn, nurture athletes' intrinsic motivation and self-determined types of extrinsic motivation. Here, we first review coaches' autonomy-supportive behaviours. We then describe the psychological processes through which coaching behaviours have a positive influence on athletes' intrinsic and self-determined extrinsic motivation. Finally, we identify social and personality processes that determine coaching behaviours.

A revival of the autoregressive distributed lag model in estimating energy demand relationships

Energy Technology Data Exchange (ETDEWEB)

Bentzen, J.; Engsted, T.

1999-07-01

The findings in the recent energy economics literature that energy economic variables are non-stationary, have led to an implicit or explicit dismissal of the standard autoregressive distribution lag (ARDL) model in estimating energy demand relationships. However, Pesaran and Shin (1997) show that the ARDL model remains valid when the underlying variables are non-stationary, provided the variables are co-integrated. In this paper we use the ARDL approach to estimate a demand relationship for Danish residential energy consumption, and the ARDL estimates are compared to the estimates obtained using co-integration techniques and error-correction models (ECM's). It turns out that both quantitatively and qualitatively, the ARDL approach and the co-integration/ECM approach give very similar results. (au)

A revival of the autoregressive distributed lag model in estimating energy demand relationships

Energy Technology Data Exchange (ETDEWEB)

Bentzen, J; Engsted, T

1999-07-01

The findings in the recent energy economics literature that energy economic variables are non-stationary, have led to an implicit or explicit dismissal of the standard autoregressive distribution lag (ARDL) model in estimating energy demand relationships. However, Pesaran and Shin (1997) show that the ARDL model remains valid when the underlying variables are non-stationary, provided the variables are co-integrated. In this paper we use the ARDL approach to estimate a demand relationship for Danish residential energy consumption, and the ARDL estimates are compared to the estimates obtained using co-integration techniques and error-correction models (ECM's). It turns out that both quantitatively and qualitatively, the ARDL approach and the co-integration/ECM approach give very similar results. (au)

Adsorption of dyes onto activated carbon cloth: using QSPRs as tools to approach adsorption mechanisms.

Science.gov (United States)

Metivier-Pignon, Hélène; Faur, Catherine; Le Cloirec, Pierre

2007-01-01

The present study aimed to investigate the adsorption of dyes onto activated carbon cloths. Kinetics and isotherms were studied based on results of batch reactors to constitute databases for the adsorption rates and capacities of 22 commercial dyes. Added to a qualitative analysis of experimental results, quantitative structure property relationships (QSPRs) were used to determine the structural features that influence most adsorption processes. QSPRs consisted of multiple linear regressions correlating adsorption parameters with molecular connectivity indices (MCIs) as molecular descriptors. Results related to adsorption kinetics showed that the size of molecules was the significant feature, the high order MCIs involved in QSPRs indicating the influence of a critical size on adsorption rate. Improved statistical fits were obtained when the database was divided according to the chemical classes of dyes. As regards to adsorption isotherms, their particular form led to the use of saturation capacity as the adsorption parameter. By contrast with adsorption kinetics, molecular overcrowding seemed to be of less influence on adsorption equilibrium. In this case, MCIs included in the QSPR were more related to details of the molecular structure. The robustness of the QSPR assessed for azo dyes was studied for the other dyes. Although the small size of the database limited predictive ability, features relevant to the influence of the database composition on QSPRs have been highlighted.

The Development of Spelling-Sound Relationships in a Model of Phonological Reading.

Science.gov (United States)

Zorzi, Marco; Houghton, George; Butterworth, Brian

1998-01-01

Developmental aspects of spelling-to-sound mapping for English monosyllabic words are investigated with a simple two-layer network model using a simple, general learning rule. The model is trained on both regularly and irregularly spelled words but extracts regular spelling to sound relationships, which it can apply to new words. Training-related…

Using a High-Dimensional Graph of Semantic Space to Model Relationships among Words

Directory of Open Access Journals (Sweden)

Alice F Jackson

2014-05-01

Full Text Available The GOLD model (Graph Of Language Distribution is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what information may be extracted through theoretically-driven algorithms as well as standard graph analysis methods. The present study will employ GOLD to examine two types of relationship between words: semantic similarity and associative relatedness. Semantic similarity refers to the degree of overlap in meaning between words, while associative relatedness refers to the degree to which two words occur in the same schematic context. It is expected that a graph structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. However, it is hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Two versions the GOLD model that differed in terms of the co-occurence window, bigGOLD at the paragraph level and smallGOLD at the adjacent word level, were directly compared to the performance of a well-established distributional model, Latent Semantic Analysis (LSA. The superior performance of the GOLD models (big and small suggest that a single acquisition and storage mechanism, namely co-occurrence, can account for associative and conceptual relationships between words and is more psychologically plausible than models using singular value decomposition.

Using a high-dimensional graph of semantic space to model relationships among words.

Science.gov (United States)

Jackson, Alice F; Bolger, Donald J

2014-01-01

The GOLD model (Graph Of Language Distribution) is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what information may be extracted through theoretically-driven algorithms as well as standard graph analysis methods. The present study will employ GOLD to examine two types of relationship between words: semantic similarity and associative relatedness. Semantic similarity refers to the degree of overlap in meaning between words, while associative relatedness refers to the degree to which two words occur in the same schematic context. It is expected that a graph structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. However, it is hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Two versions the GOLD model that differed in terms of the co-occurence window, bigGOLD at the paragraph level and smallGOLD at the adjacent word level, were directly compared to the performance of a well-established distributional model, Latent Semantic Analysis (LSA). The superior performance of the GOLD models (big and small) suggest that a single acquisition and storage mechanism, namely co-occurrence, can account for associative and conceptual relationships between words and is more psychologically plausible than models using singular value decomposition (SVD).

Study of solar radiation prediction and modeling of relationships between solar radiation and meteorological variables

International Nuclear Information System (INIS)

Sun, Huaiwei; Zhao, Na; Zeng, Xiaofan; Yan, Dong

2015-01-01

Highlights: • We investigate relationships between solar radiation and meteorological variables. • A strong relationship exists between solar radiation and sunshine duration. • Daily global radiation can be estimated accurately with ARMAX–GARCH models. • MGARCH model was applied to investigate time-varying relationships. - Abstract: The traditional approaches that employ the correlations between solar radiation and other measured meteorological variables are commonly utilized in studies. It is important to investigate the time-varying relationships between meteorological variables and solar radiation to determine which variables have the strongest correlations with solar radiation. In this study, the nonlinear autoregressive moving average with exogenous variable–generalized autoregressive conditional heteroscedasticity (ARMAX–GARCH) and multivariate GARCH (MGARCH) time-series approaches were applied to investigate the associations between solar radiation and several meteorological variables. For these investigations, the long-term daily global solar radiation series measured at three stations from January 1, 2004 until December 31, 2007 were used in this study. Stronger relationships were observed to exist between global solar radiation and sunshine duration than between solar radiation and temperature difference. The results show that 82–88% of the temporal variations of the global solar radiation were captured by the sunshine-duration-based ARMAX–GARCH models and 55–68% of daily variations were captured by the temperature-difference-based ARMAX–GARCH models. The advantages of the ARMAX–GARCH models were also confirmed by comparison of Auto-Regressive and Moving Average (ARMA) and neutral network (ANN) models in the estimation of daily global solar radiation. The strong heteroscedastic persistency of the global solar radiation series was revealed by the AutoRegressive Conditional Heteroscedasticity (ARCH) and Generalized Auto

Phosphorus Export Model Development in a Terminal Lake Basin using Concentration-Streamflow Relationship

Science.gov (United States)

Jeannotte, T.; Mahmood, T. H.; Matheney, R.; Hou, X.

2017-12-01

Nutrient export to streams and lakes by anthropogenic activities can lead to eutrophication and degradation of surface water quality. In Devils Lake, ND, the only terminal lake in the Northern Great Plains, the algae boom is of great concern due to the recent increase in streamflow and consequent rise in phosphorus (P) export from prairie agricultural fields. However, to date, very few studies explored the concentration (c) -streamflow (q) relationship in the headwater catchments of the Devils Lake basin. A robust watershed-scale quantitative framework would aid understanding of the c-q relationship, simulating P concentration and load. In this study, we utilize c-q relationships to develop a simple model to estimate phosphorus concentration and export from two headwater catchments of different size (Mauvais Coulee: 1032 km2 and Trib 3: 160 km2) draining to Devils Lake. Our goal is to link the phosphorus export model with a physically based hydrologic model to identify major drivers of phosphorus export. USGS provided the streamflow measurements, and we collected water samples (filtered and unfiltered) three times daily during the spring snowmelt season (March 31, 2017- April 12, 2017) at the outlets of both headwater catchments. Our results indicate that most P is dissolved and very little is particulate, suggesting little export of fine-grained sediment from agricultural fields. Our preliminary analyses in the Mauvais Coulee catchment show a chemostatic c-q relationship in the rising limb of the hydrograph, while the recession limb shows a linear and positive c-q relationship. The poor correlation in the rising limb of the hydrograph suggests intense flushing of P by spring snowmelt runoff. Flushing then continues in the recession limb of the hydrograph, but at a more constant rate. The estimated total P load for the Mauvais Coulee basin is 193 kg/km2, consistent with other catchments of similar size across the Red River of the North basin to the east. We expect

Improvements of ENSO-monsoon relationship in CMIP5 models through statistical downscaling over India.

Science.gov (United States)

Akhter, J.; Das, L.; Deb, A.

2017-12-01

Present study has assessed the skills of global climate models (GCMS) from coupled model inter-comparison project phase five (CMIP5) in simulating ENSO-monsoon relationships over seven homogeneous zones of India. Observational sea surface temperature (SST) data has revealed that there has been a significant negative correlation between zonal precipitation and Nino 3.4 index over North Mountainous India, North West India, North Central India, West Peninsular India and South Peninsular India. First and third principal component (PC) of zonal precipitation explaining 44.4% and 14.2% variance respectively has also shown significant anti-correlation with Nino 3.4. Analysis with CMIP5 models revealed that majority of GCMs have failed to reproduce both magnitude and phase of such relationships mainly due to poor simulation of Nino 3.4 index. Therefore, an attempt has been made to improve the results through empirical orthogonal function (EOF) based statistical downscaling of CMIP5 GCMs. To downscale Nino 3.4 index, an optimal predictor combination of PCs extracted from EOF fields of large scale GCM predictors like Geo-potential height, u and v wind, Specific and relative humidity and air temperature at pressure levels 500, 850 and 1000 hpa, mean sea level pressure and atmospheric vapor content has been utilized. Results indicated improvements of downscaled CMIP5 models in simulating ENSO-monsoon relationship for zone wise precipitation. Multi-model ensemble (MME) of downscaled GCMs has better skill than individuals GCM. Therefore, downscaled MME may be used more reliably to investigate future ENSO-monsoon relationship under various warming scenarios

New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

Science.gov (United States)

Ehresmann, Bernd; de Groot, Marcel J; Alex, Alexander; Clark, Timothy

2004-01-01

New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.

The Relationship between entrepreneurial orientation, entrepreneurial competencies, entrepreneurial leadership, and firm performance: A proposed model

Directory of Open Access Journals (Sweden)

Chijioke Nwachukwu

2017-06-01

Full Text Available This study develops a conceptual model and propositions for researchers to explore the direct and indirect relationship between entrepreneurial orientation, entrepreneurial competencies, entrepreneurial leadership and firm performance. Authors searched various databases including ProQuest, EBSCOhost databases, Scopus for peer reviewed Journals, books, and other relevant publications on the subject. A conceptual review provides direction for researchers to empirically examine the direct relationships between entrepreneurial orientation (EO, entrepreneurial competencies (EC, and firm performance and the mediating effect of entrepreneurial leadership (EL in the relationship between EO, EC, and firm performance. We suggest the use of entrepreneurial orientation scale (EOS, The entrecomp framework (2016, Renko et al., 2015 entrepreneurial leadership styles scale (ENTRELEAD, and Santos & Brito (2012 subjective measurement model for firm performance for measurement of the constructs of EO, EC, EL and performance. For researchers and academics, the model provides a basis for further research by testing empirically the validity of the model. Testing of this model could provide a better understanding of the EO, EC constructs that better predicts strategic and financial performance.

An assessment Model for Customer Relationship Management Process in Iranian Private-Commercial Banks

Directory of Open Access Journals (Sweden)

Tahmoures Hasangholi Pour

2012-03-01

Full Text Available According to several reports, in spite of huge investment on customer relationship management (CRM, risk of implementing such projects is high. One of failure factors is having no method to assess CRM success comprehensively. Nowadays, classic financial methods are common ways for assessing marketing and CRM initiatives. But, the mentioned models are unsuitable to assess investments like CRM that we expect to have intangible, indirect and strategic benefits. So, we need a process-oriented approach to assess all tangible and intangible factors of CRM process and complete existing models. In this paper, using a qualitative approach and grounded theory, a comprehensive and process-oriented CRM assessment model will be provided that considers all factors of customer relationship management in private-commercial banks of Iran. Finally, based on analysis of developed model, some suggestions will be offered for banking managers and future researchers.

Modeling the relationship between energy consumption and economy development in China

International Nuclear Information System (INIS)

Zhang, Jing; Deng, Shihuai; Shen, Fei; Yang, Xinyao; Liu, Guodong; Guo, Hang; Li, Yuanwei; Hong, Xiao; Zhang, Yanzong; Peng, Hong; Zhang, Xiaohong; Li, Li; Wang, Yingjun

2011-01-01

This paper investigated the empirical relationship between economy development and energy consumption by material production, nonmaterial production and household. Empirical models accounting for the key influential factors were constructed. Ordinary Least Square Regression (OLS) analysis of the official data of China for the year 1985-2007 permitted the relationship between individual energy consumption components and the corresponding coefficients to be investigated. The results showed that (1) the Unit Energy Consumption by Primary Industry (UECPI), Secondary Industry (UECSI), and Tertiary Industry (UECTI) demonstrated an inverse relationship with Gross Domestic Product (GDP); (2) a linear relationship exists between the Energy Consumption by Nonmaterial Production (ECNP) and GDP; (3) the hypotheses that there is an inverse S-shaped relationship between Unit Energy Consumption by Household (UECH) and Personal Income (PI) is valid. Based on the above findings and an analysis of China's energy policies, suggestions on China's energy policy were given in the end. -- Highlights: → Decomposed total energy consumption in three parts, branch of material produces, branch of the immaterial production, and households. → Energy consumed by branch of material produces considered the economic scale and construction. → Energy consumed by immaterial production was first referred in this article. → The relationship between energy consumed by household and GDP fits the invert-S curve, which is first referred too.

THE MODERATING EFFECT OF STRENGTH OF MANUFACTURER’S BRANDS ON THE RELATIONSHIP BETWEEN RETAILER’S RELATIONSHIP SATISFACTION AND COMMITMENT: A THEORETICAL MODEL

Directory of Open Access Journals (Sweden)

Majid Mapkhot Goaill

2013-01-01

Full Text Available Many recent studies emphasized the importance of retailer's satisfaction and commitment to manufacturer/supplier. These studies investigated the relationship between them as an overall relationship. However, there is a dearth of studies that investigated the dimensions of retailer's satisfaction on commitment, and analyzed the mysterious relationship via strength of manufacturer's brands as a moderating effect. Therefore, this study is an attempt to provide a value conceptual model that explains the theoretical linkages existing between dimensions of retailer's satisfaction and commitment, and tries to explain the in-depth meaning of this relationship through the moderating effect of manufacturer's brand strength in the context of social exchange theory. Additionally, hypotheses on the association between the constructs are presented as a basis for further study.

The relationship of family characteristics and bipolar disorder using causal-pie models.

Science.gov (United States)

Chen, Y-C; Kao, C-F; Lu, M-K; Yang, Y-K; Liao, S-C; Jang, F-L; Chen, W J; Lu, R-B; Kuo, P-H

2014-01-01

Many family characteristics were reported to increase the risk of bipolar disorder (BPD). The development of BPD may be mediated through different pathways, involving diverse risk factor profiles. We evaluated the associations of family characteristics to build influential causal-pie models to estimate their contributions on the risk of developing BPD at the population level. We recruited 329 clinically diagnosed BPD patients and 202 healthy controls to collect information in parental psychopathology, parent-child relationship, and conflict within family. Other than logistic regression models, we applied causal-pie models to identify pathways involved with different family factors for BPD. The risk of BPD was significantly increased with parental depression, neurosis, anxiety, paternal substance use problems, and poor relationship with parents. Having a depressed mother further predicted early onset of BPD. Additionally, a greater risk for BPD was observed with higher numbers of paternal/maternal psychopathologies. Three significant risk profiles were identified for BPD, including paternal substance use problems (73.0%), maternal depression (17.6%), and through poor relationship with parents and conflict within the family (6.3%). Our findings demonstrate that different aspects of family characteristics elicit negative impacts on bipolar illness, which can be utilized to target specific factors to design and employ efficient intervention programs. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Expanding business-to-business customer relationships : modeling the customer's upgrade decision

NARCIS (Netherlands)

Bolton, R.; Lemon, K.N.; Verhoef, P.C.

This article develops a model of a business customer's decision to upgrade service contracts conditional on the decision to renew the contract. It proposes that the firm's upgrade decision is influenced by (1) decision-maker perceptions of the relationship with the supplier, (2) contract-level

Statistical Methods for Detecting and Modeling General Patterns and Relationships in Lifetime Data

Energy Technology Data Exchange (ETDEWEB)

Kvaloey, Jan Terje

1999-04-01

In this thesis, the author tries to develop methods of detecting and modeling general patterns and relationships in lifetime data. Tests with power against nonmonotonic trends and nonmonotonic co variate effects are considered, and nonparametric regression methods which allow estimation of fairly general nonlinear relationships are studied. Practical uses of some of the methods are illustrated although in a medical rather than engineering or technological context.

Exploring Third-Grade Student Model-Based Explanations about Plant Relationships within an Ecosystem

Science.gov (United States)

Zangori, Laura; Forbes, Cory T.

2015-01-01

Elementary students should have opportunities to develop scientific models to reason and build understanding about how and why plants depend on relationships within an ecosystem for growth and survival. However, scientific modeling practices are rarely included within elementary science learning environments and disciplinary content is often…

The great descriptor melting pot: mixing descriptors for the common good of QSAR models.

Science.gov (United States)

Tseng, Yufeng J; Hopfinger, Anton J; Esposito, Emilio Xavier

2012-01-01

The usefulness and utility of QSAR modeling depends heavily on the ability to estimate the values of molecular descriptors relevant to the endpoints of interest followed by an optimized selection of descriptors to form the best QSAR models from a representative set of the endpoints of interest. The performance of a QSAR model is directly related to its molecular descriptors. QSAR modeling, specifically model construction and optimization, has benefited from its ability to borrow from other unrelated fields, yet the molecular descriptors that form QSAR models have remained basically unchanged in both form and preferred usage. There are many types of endpoints that require multiple classes of descriptors (descriptors that encode 1D through multi-dimensional, 4D and above, content) needed to most fully capture the molecular features and interactions that contribute to the endpoint. The advantages of QSAR models constructed from multiple, and different, descriptor classes have been demonstrated in the exploration of markedly different, and principally biological systems and endpoints. Multiple examples of such QSAR applications using different descriptor sets are described and that examined. The take-home-message is that a major part of the future of QSAR analysis, and its application to modeling biological potency, ADME-Tox properties, general use in virtual screening applications, as well as its expanding use into new fields for building QSPR models, lies in developing strategies that combine and use 1D through nD molecular descriptors.

The Relationship Between Resilience and Internet Addiction: A Multiple Mediation Model Through Peer Relationship and Depression.

Science.gov (United States)

Zhou, Pingyan; Zhang, Cai; Liu, Jian; Wang, Zhe

2017-10-01

Heavy use of the Internet may lead to profound academic problems in elementary students, such as poor grades, academic probation, and even expulsion from school. It is of great concern that Internet addiction problems in elementary school students have increased sharply in recent years. In this study, 58,756 elementary school students from the Henan province of China completed four questionnaires to explore the mechanisms of Internet addiction. The results showed that resilience was negatively correlated with Internet addiction. There were three mediational paths in the model: (a) the mediational path through peer relationship with an effect size of 50.0 percent, (b) the mediational path through depression with an effect size of 15.6 percent, (c) the mediational path through peer relationship and depression with an effect size of 13.7 percent. The total mediational effect size was 79.27 percent. The effect size through peer relationship was the strongest among the three mediation paths. The current findings suggest that resilience is a predictor of Internet addiction. Improving children's resilience (such as toughness, emotional control, and problem solving) can be an effective way to reduce Internet addiction behavior. The current findings provide useful information for early detection and intervention for Internet addiction.

Grid-based Continual Analysis of Molecular Interior for Drug Discovery, QSAR and QSPR.

Science.gov (United States)

Potemkin, Andrey V; Grishina, Maria A; Potemkin, Vladimir A

2017-01-01

In 1979, R.D.Cramer and M.Milne made a first realization of 3D comparison of molecules by aligning them in space and by mapping their molecular fields to a 3D grid. Further, this approach was developed as the DYLOMMS (Dynamic Lattice- Oriented Molecular Modelling System) approach. In 1984, H.Wold and S.Wold proposed the use of partial least squares (PLS) analysis, instead of principal component analysis, to correlate the field values with biological activities. Then, in 1988, the method which was called CoMFA (Comparative Molecular Field Analysis) was introduced and the appropriate software became commercially available. Since 1988, a lot of 3D QSAR methods, algorithms and their modifications are introduced for solving of virtual drug discovery problems (e.g., CoMSIA, CoMMA, HINT, HASL, GOLPE, GRID, PARM, Raptor, BiS, CiS, ConGO,). All the methods can be divided into two groups (classes):1. Methods studying the exterior of molecules; 2) Methods studying the interior of molecules. A series of grid-based computational technologies for Continual Molecular Interior analysis (CoMIn) are invented in the current paper. The grid-based analysis is fulfilled by means of a lattice construction analogously to many other grid-based methods. The further continual elucidation of molecular structure is performed in various ways. (i) In terms of intermolecular interactions potentials. This can be represented as a superposition of Coulomb, Van der Waals interactions and hydrogen bonds. All the potentials are well known continual functions and their values can be determined in all lattice points for a molecule. (ii) In the terms of quantum functions such as electron density distribution, Laplacian and Hamiltonian of electron density distribution, potential energy distribution, the highest occupied and the lowest unoccupied molecular orbitals distribution and their superposition. To reduce time of calculations using quantum methods based on the first principles, an original quantum

The evolution of facility management business models in supplier–client relationships

DEFF Research Database (Denmark)

Nardelli, Giulia; Rajala, Risto

2018-01-01

Purpose – The study improves the current understanding of business model innovation by outlining how business models unfold over time within supplier–client relationships in facilities management (FM) services. Design/methodology/approach – This study of FM services in Denmark consists...... of an explorative case study and three case studies of facilities management clients. Both phases, related and overlapping, involved collection and analysis of in-depth, semi-structured interviews and archive data. Findings – Findings shows that business model innovation entails interorganisational collaboration...... consequences of changes in the ecosystem. Originality/value – This paper introduces new thinking on the subject of business model innovation to the context of FM. It presents the external orientation of FM business models as a way to combine planned and emergent business model innovation through...

Using Carl Rogers' person-centered model to explain interpersonal relationships at a school of nursing.

Science.gov (United States)

Bryan, Venise D; Lindo, Jascinth; Anderson-Johnson, Pauline; Weaver, Steve

2015-01-01

Faculty members are viewed as nurturers within the academic setting and may be able to influence students' behaviors through the formation of positive interpersonal relationships. Faculty members' attributes that best facilitated positive interpersonal relationships according to Carl Rogers' Person-Centered Model was studied. Students (n = 192) enrolled in a 3-year undergraduate nursing program in urban Jamaica were randomly selected to participate in this descriptive cross-sectional study. A 38-item questionnaire on interpersonal relationships with nursing faculty and students' perceptions of their teachers was utilized to collect data. Factor analysis was used to create factors of realness, prizing, and empathetic understanding. Multiple linear regression analysis on the interaction of the 3 factors and interpersonal relationship scores was performed while controlling for nursing students' study year and age. One hundred sixty-five students (mean age: 23.18 ± 4.51years; 99% female) responded. The regression model explained over 46% of the variance. Realness (β = 0.50, P < .001) was the only significant predictor of the interpersonal relationship scores assigned by the nursing students. Of the total number of respondents, 99 students (60%) reported satisfaction with the interpersonal relationships shared with faculty. Nursing students' perception of faculty members' realness appeared to be the most significant attribute in fostering positive interpersonal relationships. Copyright © 2015 Elsevier Inc. All rights reserved.

Formal and Informal Work Group Relationships With Performance: A Moderation Model Using Social

National Research Council Canada - National Science Library

Knost, Benjamin R

2006-01-01

.... This field study, conducted at a military training course, attempted to further refine this social network-performance relationship by modeling characteristics of both the formal and informal work...

Aligning drivers, contract, and management of IT-outsourcing relationships: a type-dependent model

DEFF Research Database (Denmark)

Arenfeldt, Katrine; Corty Dam, Amalie; Fenger, Kim Harder

2017-01-01

In today’s competitive business environment, information technology outsourcing has become a wide-spread reality across all industries and sectors. Researchers have investigated this complex phenomenon from various angles, and established a sound knowledge base regarding the drivers, management......, and success factors related to IT outsourcing. However, little is known about the relationship between outsourcing drivers and goals on the one hand, and contractual and managerial aspects on the other hand. To overcome this gap, this study presents a synthesized conceptual model of existing literature...... that relates aspects of contractual governance and relationship management to three generic types of IT outsourcing, based on their underlying drivers: task-based, process-based, and partnership-based outsourcing. Our model identifies the specific contractual and managerial factors relevant for each type...

Relationship between Temperament, Depression, Anxiety, and Hopelessness in Adolescents: A Structural Equation Model

Directory of Open Access Journals (Sweden)

Paolo Iliceto

2011-01-01

Full Text Available The purpose of this study was to test the validity of affective temperaments for predicting psychiatric morbidity and suicide risk, using a two-factor model to explain the relationships between temperament, anxiety, depression, and hopelessness. We investigated 210 high school students, 103 males and 107 females, 18-19 years old, who were administered self-report questionnaires to assess temperament (TEMPS-A, depression (BDI-II, anxiety (STAI and hopelessness (BHS. The final structural model had a good fit with the data, with two factors significantly correlated, the first labeled unstable cyclothymic temperament including Dysthymic/Cyclothymic/Anxious temperament, Irritable temperament and Depression, and the second labeled Demoralization including Anxiety (State/Trait and Hopelessness. Depression, anxiety and hopelessness are in a complex relationship partly mediated by temperament.

Perancangan Model Basis Data Sistem Operasional Berbasiskan Customer Relationship Management

Directory of Open Access Journals (Sweden)

Tanty Oktavia

2013-12-01

Full Text Available Data is a very important asset for a company since it describes the company’s running processes. Database as a part of the information system components provides a big influence in helping data integration in a company. Therefore, we need a system which can facilitate the availability of data to be processed and used as needed, This study takes a company engaged in the sale of bike and spare parts, namely PT TDI, as the object of the study. At this time, PT TDI uses an integrated system in helping the company's operations. Along with thevision and mission, PT TDI intends to build a new operating system by applying the concept of Customer Relationship Management (CRM which is believed to assist the company in maintaining relationships with customers using web-based platform. It aims to facilitate interaction with customers so that it can be done anytime and anywhere. This study implements the database design life cycle adjusted to the component aspects of CRM. The result achieved is a model that combines database CRM systems that can help companies improve relationships with customers.

Relationship Between Self-Assessed Fidelity and Self-Reported Employment in the Individual Placement and Support Model of Supported Employment.

Science.gov (United States)

Margolies, Paul J; Humensky, Jennifer L; Chiang, I-Chin; Covell, Nancy H; Jewell, Thomas C; Broadway-Wilson, Karen; Gregory, Raymond; Scannevin, Gary; Dixon, Lisa B

2018-05-01

A growing body of literature demonstrates that high-fidelity implementation of the individual placement and support (IPS) model of supported employment increases the chances of achieving desired outcomes. This study examined the relationship between IPS fidelity, as self-reported by program sites, and employment outcomes and determined whether this relationship was maintained over time. A total of 78 outpatient programs in New York State provided data on self-reported IPS fidelity and employment outcomes. Pearson correlations were used to determine the relationship between fidelity scores and competitive employment rates. A mixed-effects model examined the relationship between repeated fidelity and employment measures over time. A significant positive relationship was found between better self-reported IPS fidelity and greater employment. The relationship between IPS fidelity and employment was sustained over time (up to one year). Higher-fidelity implementation of the IPS model, as self-assessed by program sites, was associated with higher employment rates, which were sustained over time.

Hop-distance relationship analysis with quasi-UDG model for node localization in wireless sensor networks

Directory of Open Access Journals (Sweden)

Chen Ping

2011-01-01

Full Text Available Abstract In wireless sensor networks (WSNs, location information plays an important role in many fundamental services which includes geographic routing, target tracking, location-based coverage, topology control, and others. One promising approach in sensor network localization is the determination of location based on hop counts. A critical priori of this approach that directly influences the accuracy of location estimation is the hop-distance relationship. However, most of the related works on the hop-distance relationship assume the unit-disk graph (UDG model that is unrealistic in a practical scenario. In this paper, we formulate the hop-distance relationship for quasi-UDG model in WSNs where sensor nodes are randomly and independently deployed in a circular region based on a Poisson point process. Different from the UDG model, quasi-UDG model has the non-uniformity property for connectivity. We derive an approximated recursive expression for the probability of the hop count with a given geographic distance. The border effect and dependence problem are also taken into consideration. Furthermore, we give the expressions describing the distribution of distance with known hop counts for inner nodes and those suffered from the border effect where we discover the insignificance of the border effect. The analytical results are validated by simulations showing the accuracy of the employed approximation. Besides, we demonstrate the localization application of the formulated relationship and show the accuracy improvement in the WSN localization.

Parent-Adolescent Relationship Qualities, Internal Working Models, and Styles as Predictors of Adolescents’ Observed Interactions with Friends

Science.gov (United States)

Shomaker, Lauren B.; Furman, Wyndol

2010-01-01

This study examined how current parent-adolescent relationship qualities and adolescents’ representations of relationships with parents were related to friendship interactions in 200 adolescent-close friend dyads. Adolescents and friends were observed discussing problems during a series of structured tasks. Negative interactions with mothers were significantly related to adolescents’ greater conflict with friends, poorer focus on tasks, and poorer communication skills. Security of working models (as assessed by interview) was significantly associated with qualities of friendship interactions, whereas security of attachment styles (as assessed by questionnaire) was not. More dismissing (vs. secure) working models were associated with poorer focus on problem discussions and weaker communication skills with friends, even after accounting for gender differences and current parent-adolescent relationship qualities. We discuss possible mechanisms for the observed links between dimensions of parent-adolescent relationships and friendships. We also consider methodological and conceptual differences between working model and style measures of attachment representations. PMID:20174459

The relationships between internal and external training load models during basketball training.

Science.gov (United States)

Scanlan, Aaron T; Wen, Neal; Tucker, Patrick S; Dalbo, Vincent J

2014-09-01

The present investigation described and compared the internal and external training loads during basketball training. Eight semiprofessional male basketball players (mean ± SD, age: 26.3 ± 6.7 years; stature: 188.1 ± 6.2 cm; body mass: 92.0 ± 13.8 kg) were monitored across a 7-week period during the preparatory phase of the annual training plan. A total of 44 total sessions were monitored. Player session ratings of perceived exertion (sRPE), heart rate, and accelerometer data were collected across each training session. Internal training load was determined using the sRPE, training impulse (TRIMP), and summated-heart-rate-zones (SHRZ) training load models. External training load was calculated using an established accelerometer algorithm. Pearson product-moment correlations with 95% confidence intervals (CIs) were used to determine the relationships between internal and external training load models. Significant moderate relationships were observed between external training load and the sRPE (r42 = 0.49, 95% CI = 0.23-0.69, p external training load and the SHRZ model (r42 = 0.61, 95% CI = 0.38-0.77, p internal and external training load models, the magnitude of the correlations and low commonality suggest that internal training load models measure different constructs of the training process than the accelerometer training load model in basketball settings. Basketball coaching and conditioning professionals should not assume a linear dose-response between accelerometer and internal training load models during training and are recommended to combine internal and external approaches when monitoring training load in players.

Computational modeling of the structure-function relationship in human placental terminal villi.

OpenAIRE

Plitman, Mayo R; Olsthoorn, Jason; Charnock-Jones, David Stephen; Burton, Graham James; Oyen, Michelle Lynn

2016-01-01

Placental oxygen transport takes place at the final branches of the villous tree and is dictated by the relative arrangement of the maternal and fetal circulations. Modeling techniques have failed to accurately assess the structure-function relationship in the terminal villi due to the geometrical complexity. Three-dimensional blood flow and oxygen transport was modeled in four terminal villi reconstructed from confocal image stacks. The blood flow was analyzed along the center lines of capil...

The Relationship between Economic Growth and Money Laundering – a Linear Regression Model

Directory of Open Access Journals (Sweden)

Daniel Rece

2009-09-01

Full Text Available This study provides an overview of the relationship between economic growth and money laundering modeled by a least squares function. The report analyzes statistically data collected from USA, Russia, Romania and other eleven European countries, rendering a linear regression model. The study illustrates that 23.7% of the total variance in the regressand (level of money laundering is “explained” by the linear regression model. In our opinion, this model will provide critical auxiliary judgment and decision support for anti-money laundering service systems.

The Relationship between Spiritual Health and other Dimensions of Health: Presentation of a Model

Directory of Open Access Journals (Sweden)

Akram Heidari

2016-06-01

Full Text Available Attitudes to humankind will have different effects on health service delivery. Health might used to be intended to provide physical health in the past; today, however, many researchers and clinicians consider the concept health to be beyond physical health. In support of this claim, it is enough to indicate that the bio-psycho-social model has for years been held by scientific communities to be a fully admitted model. However, the missing ring in this model, as suggested by many, is the spiritual health. In recent years, the relationship between spirituality and clinical interventions with a comprehensive focus on health has been under increasing scrutiny. Although different models have been presented for investigation of the relationship between spiritual health and other dimensions, the fundamental challenge in this regard is the actual place of spiritual health compared with other dimensions. In this article, attempts are made to address the position and weight of spiritual health from the Islam’s point of view.

A linear solvation energy relationship model of organic chemical partitioning to dissolved organic carbon.

Science.gov (United States)

Kipka, Undine; Di Toro, Dominic M

2011-09-01

Predicting the association of contaminants with both particulate and dissolved organic matter is critical in determining the fate and bioavailability of chemicals in environmental risk assessment. To date, the association of a contaminant to particulate organic matter is considered in many multimedia transport models, but the effect of dissolved organic matter is typically ignored due to a lack of either reliable models or experimental data. The partition coefficient to dissolved organic carbon (K(DOC)) may be used to estimate the fraction of a contaminant that is associated with dissolved organic matter. Models relating K(DOC) to the octanol-water partition coefficient (K(OW)) have not been successful for many types of dissolved organic carbon in the environment. Instead, linear solvation energy relationships are proposed to model the association of chemicals with dissolved organic matter. However, more chemically diverse K(DOC) data are needed to produce a more robust model. For humic acid dissolved organic carbon, the linear solvation energy relationship predicts log K(DOC) with a root mean square error of 0.43. Copyright © 2011 SETAC.

A method for extending stage-discharge relationships using a hydrodynamic model and quantifying the associated uncertainty

Science.gov (United States)

Shao, Quanxi; Dutta, Dushmanta; Karim, Fazlul; Petheram, Cuan

2018-01-01

Streamflow discharge is a fundamental dataset required to effectively manage water and land resources. However, developing robust stage - discharge relationships called rating curves, from which streamflow discharge is derived, is time consuming and costly, particularly in remote areas and especially at high stage levels. As a result stage - discharge relationships are often heavily extrapolated. Hydrodynamic (HD) models are physically based models used to simulate the flow of water along river channels and over adjacent floodplains. In this paper we demonstrate a method by which a HD model can be used to generate a 'synthetic' stage - discharge relationship at high stages. The method uses a both-side Box-Cox transformation to calibrate the synthetic rating curve such that the regression residuals are as close to the normal distribution as possible. By doing this both-side transformation, the statistical uncertainty in the synthetically derived stage - discharge relationship can be calculated. This enables people trying to make decisions to determine whether the uncertainty in the synthetically generated rating curve at high stage levels is acceptable for their decision. The proposed method is demonstrated in two streamflow gauging stations in north Queensland, Australia.

Pharmacokinetic/Pharmacodynamic Relationship of Gabapentin in a CFA-induced Inflammatory Hyperalgesia Rat Model

DEFF Research Database (Denmark)

Larsen, Malte Selch; Keizer, Ron; Munro, Gordon

2016-01-01

PURPOSE: Gabapentin displays non-linear drug disposition, which complicates dosing for optimal therapeutic effect. Thus, the current study was performed to elucidate the pharmacokinetic/pharmacodynamic (PKPD) relationship of gabapentin's effect on mechanical hypersensitivity in a rat model of CFA......-induced inflammatory hyperalgesia. METHODS: A semi-mechanistic population-based PKPD model was developed using nonlinear mixed-effects modelling, based on gabapentin plasma and brain extracellular fluid (ECF) time-concentration data and measurements of CFA-evoked mechanical hyperalgesia following administration...

ETHICAL MODELS OF PHYSICIAN--PATIENT RELATIONSHIP REVISITED WITH REGARD TO PATIENT AUTONOMY, VALUES AND PATIENT EDUCATION.

Science.gov (United States)

Borza, Liana Rada; Gavrilovici, Cristina; Stockman, René

2015-01-01

The present paper revisits the ethical models of patient--physician relationship from the perspective of patient autonomy and values. It seems that the four traditional models of physician--patient relationship proposed by Emanuel & Emanuel in 1992 closely link patient values and patient autonomy. On the other hand, their reinterpretation provided by Agarwal & Murinson twenty years later emphasizes the independent expression of values and autonomy in individual patients. Additionally, patient education has been assumed to join patient values and patient autonomy. Moreover, several authors have noted that, over the past few decades, patient autonomy has gradually replaced the paternalistic approach based on the premise that the physician knows what is best for the patient. Neither the paternalistic model of physician-patient relationship, nor the informative model is considered to be satisfactory, as the paternalistic model excludes patient values from decision making, while the informative model excludes physician values from decision making. However, the deliberative model of patient-physician interaction represents an adequate alternative to the two unsatisfactory approaches by promoting shared decision making between the physician and the patient. It has also been suggested that the deliberative model would be ideal for exercising patient autonomy in chronic care and that the ethical role of patient education would be to make the deliberative model applicable to chronic care. In this regard, studies have indicated that the use of decision support interventions might increase the deliberative capacity of chronic patients.

Brand relationships: A study of five relationship constructs

DEFF Research Database (Denmark)

Bergkvist, Lars; Bech-Larsen, Tino

This study investigates the relationships between the five brand relationship constructs sense of community, brand identification, brand love, brand loyalty, and active engagement. Structural equation modelling with partial least squares showed provided support for six relational hypotheses...

Advances in applied homeostatic modelling of the relationship between thyrotropin and free thyroxine.

Directory of Open Access Journals (Sweden)

Rudolf Hoermann

Full Text Available The relationship between pituitary TSH and thyroid hormones is central to our understanding of thyroid physiology and thyroid function testing. Here, we generated distribution patterns by using validated tools of thyroid modelling.We simulated patterns of individual set points under various conditions, based on a homeostatic model of thyroid feedback control. These were compared with observed data points derived from clinical trials.A random mix of individual set points was reconstructed by simulative modelling with defined structural parameters. The pattern displayed by the cluster of hypothetical points resembled that observed in a natural control group. Moderate variation of the TSH-FT4 gradient over the functional range introduced further flexibility, implementing a scenario of adaptive set points. Such a scenario may be a realistic possibility for instance in treatment where relationships and equilibria between thyroid parameters are altered by various influences such as LT4 dose and conversion efficiency.We validated a physiologically based homeostatic model that permits simulative reconstruction of individual set points. This produced a pattern resembling the observed data under various conditions. Applied modelling, although still experimental at this stage, shows a potential to aid our physiological understanding of the interplay between TSH and thyroid hormones. It should eventually benefit personalised clinical decision making.

Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.

Science.gov (United States)

Schudoma, Christian; May, Patrick; Nikiforova, Viktoria; Walther, Dirk

2010-01-01

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts.

Relationships among Adolescents' Leisure Motivation, Leisure Involvement, and Leisure Satisfaction: A Structural Equation Model

Science.gov (United States)

Chen, Ying-Chieh; Li, Ren-Hau; Chen, Sheng-Hwang

2013-01-01

The purpose of this cross-sectional study was to test a cause-and-effect model of factors affecting leisure satisfaction among Taiwanese adolescents. A structural equation model was proposed in which the relationships among leisure motivation, leisure involvement, and leisure satisfaction were explored. The study collected data from 701 adolescent…

Modeling Chemical Interaction Profiles: I. Spectral Data-Activity Relationship and Structure-Activity Relationship Models for Inhibitors and Non-inhibitors of Cytochrome P450 CYP3A4 and CYP2D6 Isozymes

OpenAIRE

McPhail, Brooks; Tie, Yunfeng; Hong, Huixiao; Pearce, Bruce A.; Schnackenberg, Laura K.; Ge, Weigong; Valerio, Luis G.; Fuscoe, James C.; Tong, Weida; Buzatu, Dan A.; Wilkes, Jon G.; Fowler, Bruce A.; Demchuk, Eugene; Beger, Richard D.

2012-01-01

An interagency collaboration was established to model chemical interactions that may cause adverse health effects when an exposure to a mixture of chemicals occurs. Many of these chemicals—drugs, pesticides, and environmental pollutants—interact at the level of metabolic biotransformations mediated by cytochrome P450 (CYP) enzymes. In the present work, spectral data-activity relationship (SDAR) and structure-activity relationship (SAR) approaches were used to develop machine-learning classifi...

Leaving an Abusive Dating Relationship: A Prospective Analysis of the Investment Model and Theory of Planned Behavior.

Science.gov (United States)

Edwards, Katie M; Gidycz, Christine A; Murphy, Megan J

2015-10-01

The purpose of the current study was to build on the existing literature to better understand young women's leaving processes in abusive dating relationships using a prospective design. Two social psychological models-the investment model and theory of planned behavior-were tested. According to the investment model, relationship continuation is predicted by commitment, which is a function of investment, satisfaction, and low quality of alternatives. The theory of planned behavior asserts that a specific behavior is predicted by an individual's intention to use a behavior, which is a function of the individual's attitudes toward the behavior, the subjective norms toward the behavior, and the individual's perceived behavioral control over the behavior. College women (N = 169 young women in abusive relatinships) completed surveys at two time points, approximately 4 months apart, to assess initially for the presence of intimate partner violence (IPV) in a current relationship and investment model and theory of planned behavior variables; the purpose of the 4-month follow-up session was to determine if women had remained in or terminated their abusive relationship. Path analytic results demonstrated that both the theory of planned behavior and investment models were good fits to the data in prospectively predicting abused women's stay/leave decisions. However, the theory of planned behavior was a better fit to the data than the investment model. Implications for future research and intervention are discussed. © The Author(s) 2014.

Predictive and Explanatory Relationship Model between Procrastination, Motivation, Anxiety and Academic Achievement

Science.gov (United States)

Akpur, Ugur

2017-01-01

Purpose: The purpose of this study is to determine the predictive and explanatory relationship model between procrastination, motivation, anxiety and academic achievement of university students. Research Methods: In this study, a causal research design was used. The study group consisted of 211 participants. In order to determine their motivation…

Exploring the Relationship Between Business Model Innovation, Corporate Sustainability, and Organisational Values within the Fashion Industry

DEFF Research Database (Denmark)

Pedersen, Esben Rahbek Gjerdrum; Gwozdz, Wencke; Hvass, Kerli Kant

2018-01-01

their origin in the fundamental principles guiding the organisation. In addition, the study also finds a positive relationship between the core organisational values and financial performance. The analysis of the paper is based on survey responses from 492 managers within the Swedish fashion industry.......The objective of this paper is to examine the relationship between business model innovation, corporate sustainability, and the underlying organisational values. Moreover, the paper examines how the three dimensions correlate with corporate financial performance. It is concluded that companies...... with innovative business models are more likely to address corporate sustainability and that business model innovation and corporate sustainability alike are typically found in organisations rooted in values of flexibility and discretion. Business model innovation and corporate sustainability thus seem to have...

Evaluation of air-soil temperature relationships simulated by land surface models during winter across the permafrost region

Science.gov (United States)

Wang, Wenli; Rinke, Annette; Moore, John C.; Ji, Duoying; Cui, Xuefeng; Peng, Shushi; Lawrence, David M.; McGuire, A. David; Burke, Eleanor J.; Chen, Xiaodong; Delire, Christine; Koven, Charles; MacDougall, Andrew; Saito, Kazuyuki; Zhang, Wenxin; Alkama, Ramdane; Bohn, Theodore J.; Ciais, Philippe; Decharme, Bertrand; Gouttevin, Isabelle; Hajima, Tomohiro; Krinner, Gerhard; Lettenmaier, Dennis P.; Miller, Paul A.; Smith, Benjamin; Sueyoshi, Tetsuo

2016-01-01

 A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyze simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models and compare them with observations from 268 Russian stations. There are large across-model differences as expressed by simulated differences between near-surface soil and air temperatures, (ΔT), of 3 to 14 K, in the gradients between soil and air temperatures (0.13 to 0.96°C/°C), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, and hence guide improvements to the model’s conceptual structure and process parameterizations. Models with better performance apply multi-layer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (12–16 million km2). However, there is not a simple relationship between the quality of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, likely because several other factors such as differences in the treatment of soil organic matter, soil hydrology, surface energy calculations, and vegetation also provide important controls on simulated permafrost distribution.

A Structural Model of Depression Based on Interpersonal Relationships: The Mediating Role of Coping Strategies and Loneliness.

Science.gov (United States)

Majd Ara, Elahe; Talepasand, Siavash; Rezaei, Ali Mohammad

2017-06-01

The present study was conducted with the aim of examining the structural model of interpersonal relationships and depression using coping strategies and loneliness as mediators. Using multistage random sampling, 301 high-school students were selected from Minudasht city, Iran. The participants were aksed to complete the Network of Relationships Inventory (NRI); the Ways of Coping Questionnaire (Lazarus and Folkman); the Children's Loneliness Scale (CLS); and the Depression, Anxiety, and Stress Scale (DASS-21). Structural equation modeling was used to examine the pattern of direct and indirect effects. Findings of the present study show that the data are well fitted to the model. The indirect effect of the positive quality of relationships was significant on depression through loneliness. Moreover, the indirect effects of the negative quality of relationships on depression through loneliness and through emotion-focused coping strategies were statistically significant. Although the effect of loneliness and emotion-focused coping strategies on depression was significant, problem-focused coping strategies did not have a significant effect on depression. Additionally, the findings suggested that the indirect effect through loneliness on depression was stronger compared with the indirect effect through emotion-focused coping strategies. The positive or negative quality of interpersonal relationships, loneliness, and emotion-focused coping strategy can significantly predict depression.

The Sport Commitment Model: An Investigation of Structural Relationships with Thai Youth Athlete Populations

Science.gov (United States)

Choosakul, Chairat; Vongjaturapat, Naruepon; Li, Fuzhong; Harmer, Peter

2009-01-01

Grounded in the conceptual framework of the Sport Commitment Model and previous empirical studies conducted in Western countries, this study was designed to (a) test and validate a Thai version of the Athlete Opinion Survey to assess components of the Sport Commitment Model in Thai youth athletes and (b) examine structural relationships among…

Exploring the relationship between volunteering and hospice sustainability in the UK: a theoretical model.

Science.gov (United States)

Scott, Ros; Jindal-Snape, Divya; Manwaring, Gaye

2018-05-02

To explore the relationship between volunteering and the sustainability of UK voluntary hospices. A narrative literature review was conducted to inform the development of a theoretical model. Eight databases were searched: CINAHL (EBSCO), British Nursing Index, Intute: Health and Life Sciences, ERIC, SCOPUS, ASSIA (CSA), Cochrane Library and Google Scholar. A total of 90 documents were analysed. Emerging themes included the importance of volunteering to the hospice economy and workforce, the quality of services, and public and community support. Findings suggest that hospice sustainability is dependent on volunteers; however, the supply and retention of volunteers is affected by internal and external factors. A theoretical model was developed to illustrate the relationship between volunteering and hospice sustainability. It demonstrates the factors necessary for hospice sustainability and the reciprocal impact that these factors and volunteering have on each other. The model has a practical application as an assessment framework and strategic planning tool.

Dose-stochastic radiobiological effect relationship in model of two reactions and estimation of radiation risk

International Nuclear Information System (INIS)

Komochkov, M.M.

1997-01-01

The model of dose-stochastic effect relationship for biological systems capable of self-defence under danger factor effect is developed. A defence system is realized in two forms of organism reaction, which determine innate μ n and adaptive μ a radiosensitivities. The significances of μ n are determined by host (inner) factors; and the significances of μ a , by external factors. The possibilities of adaptive reaction are determined by the coefficient of capabilities of the defence system. The formulas of the dose-effect relationship are the solutions of differential equations of assumed process in the defence system of organism. The model and formulas have been checked both at cell and at human levels. Based on the model and personal monitoring data, the estimation of radiation risk at the Joint Institute for Nuclear Research is done

Infertile Individuals’ Marital Relationship Status, Happiness, and Mental Health: A Causal Model

Science.gov (United States)

Ahmadi Forooshany, Seyed Habiballah; Yazdkhasti, Fariba; Safari Hajataghaie, Saiede; Nasr Esfahani, Mohammad Hossein

2014-01-01

Background This study examined the causal model of relation between marital relation- ship status, happiness, and mental health in infertile individuals. Materials and Methods In this descriptive study, 155 subjects (men: 52 and women: 78), who had been visited in one of the infertility Centers, voluntarily participated in a self-evaluation. Golombok Rust Inventory of Marital Status, Oxford Happiness Ques- tionnaire, and General Health Questionnaire were used as instruments of the study. Data was analyzed by SPSS17 and Amos 5 software using descriptive statistics, independent sample t test, and path analysis. Results Disregarding the gender factor, marital relationship status was directly related to happiness (phappiness was directly related to mental health, (phappiness and mental health was significant (phappiness had a mediator role in relation between marital relationship status and mental health in infertile individu- als disregarding the gender factor. Also, considering the gender factor, only in infertile women, marital relationship status can directly and indirectly affect happiness and mental health. PMID:25379161

Infertile individuals' marital relationship status, happiness, and mental health: a causal model.

Science.gov (United States)

Ahmadi Forooshany, Seyed Habiballah; Yazdkhasti, Fariba; Safari Hajataghaie, Saiede; Nasr Esfahani, Mohammad Hossein

2014-10-01

This study examined the causal model of relation between marital relation- ship status, happiness, and mental health in infertile individuals. In this descriptive study, 155 subjects (men: 52 and women: 78), who had been visited in one of the infertility Centers, voluntarily participated in a self-evaluation. Golombok Rust Inventory of Marital Status, Oxford Happiness Ques- tionnaire, and General Health Questionnaire were used as instruments of the study. Data was analyzed by SPSS17 and Amos 5 software using descriptive statistics, independent sample t test, and path analysis. Disregarding the gender factor, marital relationship status was directly related to happiness (phappiness was directly related to mental health, (phappiness and mental health was significant (phappiness had a mediator role in relation between marital relationship status and mental health in infertile individu- als disregarding the gender factor. Also, considering the gender factor, only in infertile women, marital relationship status can directly and indirectly affect happiness and mental health.

Relationship between Family Adaptability, Cohesion and Adolescent Problem Behaviors: Curvilinearity of Circumplex Model

OpenAIRE

Joh, Ju Youn; Kim, Sun; Park, Jun Li; Kim, Yeon Pyo

2013-01-01

Background The Family Adaptability and Cohesion Evaluation Scale (FACES) III using the circumplex model has been widely used in investigating family function. However, the criticism of the curvilinear hypothesis of the circumplex model has always been from an empirical point of view. This study examined the relationship between adolescent adaptability, cohesion, and adolescent problem behaviors, and especially testing the consistency of the curvilinear hypotheses with FACES III. Methods We us...

Modeling the Relationship between Pre-Service Teachers' TPACK and Digital Nativity

Science.gov (United States)

Kabakci Yurdakul, Isil

2018-01-01

The purpose of this study is to build a structural equation model that predicts the relationship between Technological Pedagogical Content Knowledge (TPACK) competencies and digital nativity. The data was collected from 1493 Turkish pre-service teachers. Two instruments were used in the data collection; a TPACK-deep scale and a Turkish adaptation…

The love equation: Computational modeling of romantic relationships in French classical drama

NARCIS (Netherlands)

Karsdorp, F.; Kestemont, M.; Schöch, C.; Bosch, A.P.J. van den; Finlayson, M.; Miller, B.; Lieto, A.; Ronfard, R.

2015-01-01

We report on building a computational model of romantic relationships in a corpus of historical literary texts. We frame this task as a ranking problem in which, for a given character, we try to assign the highest rank to the character with whom (s)he is most likely to be romantically involved. As

The Love Equation : Computational Modeling of Romantic Relationships in French Classical Drama

NARCIS (Netherlands)

Karsdorp, F.B.; Kestemont, Mike; Schöch, Christof; van den Bosch, Antal; Finlayson, Mark; Miller, Ben; Lieto, Antonio; Ronfard, Remi

We report on building a computational model of romantic relationships in a corpus of historical literary texts. We frame this task as a ranking problem in which, for a given character, we try to assign the highest rank to the character with whom (s)he is most likely to be romantically involved. As

Perceived Social Relationships and Science Learning Outcomes for Taiwanese Eighth Graders: Structural Equation Modeling with a Complex Sampling Consideration

Science.gov (United States)

Jen, Tsung-Hau; Lee, Che-Di; Chien, Chin-Lung; Hsu, Ying-Shao; Chen, Kuan-Ming

2013-01-01

Based on the Trends in International Mathematics and Science Study 2007 study and a follow-up national survey, data for 3,901 Taiwanese grade 8 students were analyzed using structural equation modeling to confirm a social-relation-based affection-driven model (SRAM). SRAM hypothesized relationships among students' perceived social relationships in…

Information system success model for customer relationship management system in health promotion centers.

Science.gov (United States)

Choi, Wona; Rho, Mi Jung; Park, Jiyun; Kim, Kwang-Jum; Kwon, Young Dae; Choi, In Young

2013-06-01

Intensified competitiveness in the healthcare industry has increased the number of healthcare centers and propelled the introduction of customer relationship management (CRM) systems to meet diverse customer demands. This study aimed to develop the information system success model of the CRM system by investigating previously proposed indicators within the model. THE EVALUATION AREAS OF THE CRM SYSTEM INCLUDES THREE AREAS: the system characteristics area (system quality, information quality, and service quality), the user area (perceived usefulness and user satisfaction), and the performance area (personal performance and organizational performance). Detailed evaluation criteria of the three areas were developed, and its validity was verified by a survey administered to CRM system users in 13 nationwide health promotion centers. The survey data were analyzed by the structural equation modeling method, and the results confirmed that the model is feasible. Information quality and service quality showed a statistically significant relationship with perceived usefulness and user satisfaction. Consequently, the perceived usefulness and user satisfaction had significant influence on individual performance as well as an indirect influence on organizational performance. This study extends the research area on information success from general information systems to CRM systems in health promotion centers applying a previous information success model. This lays a foundation for evaluating health promotion center systems and provides a useful guide for successful implementation of hospital CRM systems.

Information System Success Model for Customer Relationship Management System in Health Promotion Centers

Science.gov (United States)

Choi, Wona; Rho, Mi Jung; Park, Jiyun; Kim, Kwang-Jum; Kwon, Young Dae

2013-01-01

Objectives Intensified competitiveness in the healthcare industry has increased the number of healthcare centers and propelled the introduction of customer relationship management (CRM) systems to meet diverse customer demands. This study aimed to develop the information system success model of the CRM system by investigating previously proposed indicators within the model. Methods The evaluation areas of the CRM system includes three areas: the system characteristics area (system quality, information quality, and service quality), the user area (perceived usefulness and user satisfaction), and the performance area (personal performance and organizational performance). Detailed evaluation criteria of the three areas were developed, and its validity was verified by a survey administered to CRM system users in 13 nationwide health promotion centers. The survey data were analyzed by the structural equation modeling method, and the results confirmed that the model is feasible. Results Information quality and service quality showed a statistically significant relationship with perceived usefulness and user satisfaction. Consequently, the perceived usefulness and user satisfaction had significant influence on individual performance as well as an indirect influence on organizational performance. Conclusions This study extends the research area on information success from general information systems to CRM systems in health promotion centers applying a previous information success model. This lays a foundation for evaluating health promotion center systems and provides a useful guide for successful implementation of hospital CRM systems. PMID:23882416

The Colonization of Private Relationships by the Economic Discourse: A Critic to Descriptive Models of Company

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Sergio Marcos Carvalho de Avila Negri

2015-12-01

Full Text Available Through the reconstructive method of approach and by adopting the communicative rationality habermasian as epistemological framework, this paper discusses the process of colonization of private relations by economic discourse in the corporate field. It examines, in particular, descriptive models of business relationships, as the nexus of contracts theory and dispute resolution forms as the "default rule" and the "hypothetical bargain." With a content analysis of these models, it investigates the hypothesis that there are non-problematized normative claims in the descriptions of business relationships and decision-making in the corporate field, such as specialization and efficiency while rationality parameters. It addresses procedural and substantive objections to the approached models.

Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

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Masanao Sato

Full Text Available Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2. This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i the components of the network are highly interconnected; and (ii negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector

Models of physician-patient relationships in pharmaceutical direct-to-consumer advertising and consumer interviews.

Science.gov (United States)

Arney, Jennifer; Lewin, Benjamin

2013-07-01

The rise of direct-to-consumer advertising (DTCA) has mirrored, if not facilitated, the shift toward more active health care consumers. We used content analysis to identify models of physician-patient interaction in DTCA from the 1997 to 2006 issues of a broad sample of women's, men's, and common readership magazines. We also conducted 36 in-depth interviews to examine the ways consumers receive and regard advertising messages, and to explore their preferences for clinical communication and decision making. We identified four models of physician-patient relationships that vary in their locus of control (physician, patient, or shared) and the form of support sought or obtained in the relationship (emotional or instrumental). Whereas consumer interviews reflected references to all four models of interaction, only two appeared in DTCA. The limited range of interactions seen in these advertisements creates a lack of congruity between interaction styles found in advertisements vs. styles reported by actual consumers.

Determination and prediction of octanol-air partition coefficients of hydroxylated and methoxylated polybrominated diphenyl ethers.

Science.gov (United States)

Zhao, Hongxia; Xie, Qing; Tan, Feng; Chen, Jingwen; Quan, Xie; Qu, Baocheng; Zhang, Xin; Li, Xiaona

2010-07-01

The octanol-air partition coefficient (K(OA)) of 19 hydroxylated polybrominated diphenyl ethers (OH-PBDEs) and 10 methoxylated polybrominated diphenyl ethers (MeO-PBDEs) were measured as a function of temperature using a gas chromatographic retention time technique. At room temperature (298.15K), log K(OA) ranged from 8.30 for monobrominated OH/MeO-PBDEs to 13.29 for hexabrominated OH/MeO-PBDEs. The internal energies of phase change from octanol to air (Delta(OA)U) for 29 OH/MeO-PBDE congeners ranged from 72 to 126 kJ mol(-1). Using partial least-squares (PLS) analysis, a statistically quantitative structure-property relationship (QSPR) model for logK(OA) of OH/MeO-PBDE congeners was developed based on the 16 fundamental quantum chemical descriptors computed by PM3 Hamiltonian, for which the Q(cum)(2) was about 0.937. The molecular weight (Mw) and energy of the lowest unoccupied molecular orbital (E(LUMO)) were found to be main factors governing the log K(OA). 2010 Elsevier Ltd. All rights reserved.

Corneal and conjunctival drug permeability: Systematic comparison and pharmacokinetic impact in the eye.

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Ramsay, Eva; Del Amo, Eva M; Toropainen, Elisa; Tengvall-Unadike, Unni; Ranta, Veli-Pekka; Urtti, Arto; Ruponen, Marika

2018-07-01

On the surface of the eye, both the cornea and conjunctiva are restricting ocular absorption of topically applied drugs, but barrier contributions of these two membranes have not been systemically compared. Herein, we studied permeability of 32 small molecular drug compounds across an isolated porcine cornea and built a quantitative structure-property relationship (QSPR) model for the permeability. Corneal drug permeability (data obtained for 25 drug molecules) showed a 52-fold range in permeability (0.09-4.70 × 10 -6  cm/s) and the most important molecular descriptors in predicting the permeability were hydrogen bond donor, polar surface area and halogen ratio. Corneal permeability values were compared to their conjunctival drug permeability values. Ocular drug bioavailability and systemic absorption via conjunctiva were predicted for this drug set with pharmacokinetic calculations. Drug bioavailability in the aqueous humour was simulated to be drug across the conjunctiva to the blood circulation restricts significantly ocular drug bioavailability and, therefore, ocular absorption does not increase proportionally with the increasing corneal drug permeability. Copyright © 2018 Elsevier B.V. All rights reserved.

For the Construction of a Historico-anthropological Model of Musical Relationships between Brazil, Portugal, and Africa

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Rafael José de Menezes Bastos

2016-02-01

Full Text Available The text postulates a model of a historico-anthropological nature for understanding the musical relationships from Brazil, Portugal, and Atlantic lusophone Africa during the XVII and XIX centuries. The model stars from the constitution of the Atlantic lusophone space as one of continual sociocultural relationships in general and musical in particular up to the first decades of the XIX century and even before. Those musical relationships are based on the existence of vast transatlantic system of musical and dance genres connected through historic and structural transformations. Because it belongs to that system, the lundu-modinha-fado transformation system will be studied, with emphasis on Bazilian dance and Portuguese song. The article elaborates the concept of "musical genre" from the notions of Mikhail Bakhtin´s "discursive genre" and Claude Lévi-Strauss and Marshall Sahlins’s "transformation".

Dog owner interaction style: the transmission of working models in human/non-human caregiving relationships

OpenAIRE

Taggart, Jill Monica

2011-01-01

A model of parental sensitivity in caregiving informs later romantic relationships and is transmitted in caregiving behaviours to children. Differences in parental caregiving contribute to individual differences in infant attachment style. The owner/dog bond mirrors this relationship as dog careseeking activates owner caregiving. The aim of this thesis was to investigate the role of individual differences in owner caregiving on dog attachment style.The first study defined dog attachment style...

The relationship between structural and functional connectivity: graph theoretical analysis of an EEG neural mass model

NARCIS (Netherlands)

Ponten, S.C.; Daffertshofer, A.; Hillebrand, A.; Stam, C.J.

2010-01-01

We investigated the relationship between structural network properties and both synchronization strength and functional characteristics in a combined neural mass and graph theoretical model of the electroencephalogram (EEG). Thirty-two neural mass models (NMMs), each representing the lump activity

Make or Buy in a Mature Industry? Models of Clientsupplier Relationships under TCT and RBV Perspectives

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Manuel Portugal Ferreira

2010-01-01

Full Text Available In this paper, we use the transaction cost theory [TCT] and the resource-based view [RBV] to discuss three propositions on the models of client-supplier relationships in mature industries. The two theories seem to advance different organizational forms of the client-supplier relationships, and in some instances are contradictory. How should firms organize to prosper and grow, namely in the international markets? Through the case study of three Portuguese packaging firms, with primary (interviews and secondary data, we discuss how the three firms deploy three distinct strategic organization models in a mature industry. One firm utilizes marketbased governance mechanisms, and concentrates its production in a few selected locations. Another firm vertically integrates almost the entire value chain of the product to provide full service to its clients. The third firm operates in a model of integrated outsourcing, with the installation wall to wall with its clients. The clientsupplier models adopted by these firms are based on efficient, stable, and trustworthy relationships that permit them to focus on their core competences and reduce transaction costs. The superior performance of firms requires a proper alignment of hierarchical and relational governance, taking the dimensions of their transactions into consideration.

A structural equation model of the relationship between insomnia, negative affect, and paranoid thinking.

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Alexander J Scott

Full Text Available A growing body of evidence points to relationships between insomnia, negative affect, and paranoid thinking. However, studies are needed to examine (i whether negative affect mediates the relation between insomnia and paranoid thinking, (ii whether different types of insomnia exert different effects on paranoia, and (iii to compare the impact of objective and self-reported sleeping difficulties.Structural equation modelling was therefore used to test competing models of the relationships between self-reported insomnia, negative affect, and paranoia. n = 348 participants completed measures of insomnia, negative affect and paranoia. A subset of these participants (n = 91 went on to monitor their sleep objectively (using a portable sleep monitor made by Zeo for seven consecutive nights. Associations between objectively recorded sleep, negative affect, and paranoia were explored using linear regression.The findings supported a fully mediated model where self-reported delayed sleep onset, but not self-reported problems with sleep maintenance or objective measures of sleep, was directly associated with negative affect that, in turn, was associated with paranoia. There was no evidence of a direct association between delayed sleep onset or sleep maintenance problems and paranoia.Taken together, the findings point to an association between perceived (but not objective difficulties initially falling asleep (but not maintaining sleep and paranoid thinking; a relationship that is fully mediated by negative affect. Future research should seek to disentangle the causal relationships between sleep, negative affect, and paranoia (e.g., by examining the effect of an intervention using prospective designs that incorporate experience sampling. Indeed, interventions might profitably target (i perceived sleep quality, (ii sleep onset, and / or (iii emotion regulation as a route to reducing negative affect and, thus, paranoid thinking.

Perceptions of Parent-Child Attachment Relationships and Friendship Qualities: Predictors of Romantic Relationship Involvement and Quality in Adolescence.

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Kochendorfer, Logan B; Kerns, Kathryn A

2017-05-01

Relationships with parents and friends are important contexts for developing romantic relationship skills. Parents and friends may influence both the timing of involvement and the quality of romantic relationships. Three models of the joint influence of parents and friends (direct effects model, mediation model, and moderator model) have been proposed. The present study uses data from a longitudinal study (n = 1012; 49.8% female; 81.1% Caucasian) to examine how attachment and friendship quality at age 10 years predict romantic relationship involvement and quality at ages 12 and 15 years. The results supported the direct effects model, with attachment and friendship quality uniquely predicting different romantic relationship outcomes. The findings provide further support for the important influence of family and friends on early romantic relationships.

Model of Communication Strategy for Public Relations in Private University in Building the Relationship with the Media

OpenAIRE

Darmastuti, Rini; Sinatra Wijaya, Lina

2009-01-01

The success of Public Relations work in Private University depends on the public relations strategy in building the relationship with the media. For knowing how effective PR strategy is in building the relationship with the media, A research has been done with 10 respondents ( 10 Private Universities in Central Java ) by using descriptive qualitative approach and direct observation. There are two relationship models that have been found from this research, they are “ Imbalanced Commensalisms ...

Stability of attachment-related anxiety and avoidance and their relationships with the five-factor model and the psychobiological model of personality.

Science.gov (United States)

Picardi, Angelo; Caroppo, Emanuele; Toni, Alessandro; Bitetti, Daniela; Di Maria, Giuseppe

2005-09-01

The stability of attachment-related anxiety and avoidance and their relationship with influential personality models are issues worth further investigation. Studying discriminant validity with respect to aspects of personality deemed as prevalently heritable, such as temperament, is particularly important. Our aims were to examine the stability of attachment dimensions and to study their relationship with psychological distress, the Big Five factors, and temperament and character dimensions. The Experiences in Close Relationships (ECR) questionnaire, the State-Trait Anxiety Inventory (STAI), the Zung depression scale (ZDS), the Temperament and Character Inventory (TCI-125), and the Big Five Questionnaire (BFQ) were administered to 222 undergraduate and graduate students. After 1 month, 115 participants completed again the ECR, the STAI, and the ZDS. Attachment-related anxiety was modestly correlated with depression and anxiety, while attachment-related avoidance was modestly correlated with depression. The test-retest reliability of ECR scores was high. Changes in attachment-related anxiety were not related to changes in depression or anxiety, and changes in attachment-related avoidance were modestly correlated with changes in depression. In separate multiple regression models also including gender and age, attachment-related anxiety was correlated with harm avoidance, reward dependence, low novelty seeking, low self-directedness and low cooperativeness; low energy/extraversion and low emotional stability; attachment-related avoidance was correlated with low reward dependence and tended to be correlated with low self-directedness. These findings corroborate the reliability and the convergent and discriminant validity of the ECR, and support the notion that the attachment dimensions are only modestly related to psychological distress and are not redundant with constructs developed within influential personality models such as the five-factor model and the

Defining the relationship between Plasmodium falciparum parasite rate and clinical disease: statistical models for disease burden estimation

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Snow Robert W

2009-08-01

Full Text Available Abstract Background Clinical malaria has proven an elusive burden to enumerate. Many cases go undetected by routine disease recording systems. Epidemiologists have, therefore, frequently defaulted to actively measuring malaria in population cohorts through time. Measuring the clinical incidence of malaria longitudinally is labour-intensive and impossible to undertake universally. There is a need, therefore, to define a relationship between clinical incidence and the easier and more commonly measured index of infection prevalence: the "parasite rate". This relationship can help provide an informed basis to define malaria burdens in areas where health statistics are inadequate. Methods Formal literature searches were conducted for Plasmodium falciparum malaria incidence surveys undertaken prospectively through active case detection at least every 14 days. The data were abstracted, standardized and geo-referenced. Incidence surveys were time-space matched with modelled estimates of infection prevalence derived from a larger database of parasite prevalence surveys and modelling procedures developed for a global malaria endemicity map. Several potential relationships between clinical incidence and infection prevalence were then specified in a non-parametric Gaussian process model with minimal, biologically informed, prior constraints. Bayesian inference was then used to choose between the candidate models. Results The suggested relationships with credible intervals are shown for the Africa and a combined America and Central and South East Asia regions. In both regions clinical incidence increased slowly and smoothly as a function of infection prevalence. In Africa, when infection prevalence exceeded 40%, clinical incidence reached a plateau of 500 cases per thousand of the population per annum. In the combined America and Central and South East Asia regions, this plateau was reached at 250 cases per thousand of the population per annum. A temporal

Investigating genotype-phenotype relationships in Saccharomyces cerevisiae metabolic network through stoichiometric modeling

DEFF Research Database (Denmark)

Brochado, Ana Rita

processes. Metabolism is an extensively studied and characterised subcellular system, for which several modeling approaches have been proposed over the last 20 years. Nowadays, stoichiometric modeling of metabolism is done at the genome scale and it has diverse applications, many of them for helping....... This chapter aims at providing the reader with relevant state-of-the-art information concerning Systems Biology, Genome-Scale Metabolic Modeling and Metabolic Engineering. Particular attention is given to the yeast Saccharomyces cerevisiae, the eukaryotic model organism used thought the thesis.......A holistic view of the cell is fundamental for gaining insights into genotype to phenotype relationships. Systems Biology is a discipline within Biology, which uses such holistic approach by focusing on the development and application of tools for studying the structure and dynamics of cellular...

Non-Linear Relationship between Economic Growth and CO₂ Emissions in China: An Empirical Study Based on Panel Smooth Transition Regression Models.

Science.gov (United States)

Wang, Zheng-Xin; Hao, Peng; Yao, Pei-Yi

2017-12-13

The non-linear relationship between provincial economic growth and carbon emissions is investigated by using panel smooth transition regression (PSTR) models. The research indicates that, on the condition of separately taking Gross Domestic Product per capita (GDPpc), energy structure (Es), and urbanisation level (Ul) as transition variables, three models all reject the null hypothesis of a linear relationship, i.e., a non-linear relationship exists. The results show that the three models all contain only one transition function but different numbers of location parameters. The model taking GDPpc as the transition variable has two location parameters, while the other two models separately considering Es and Ul as the transition variables both contain one location parameter. The three models applied in the study all favourably describe the non-linear relationship between economic growth and CO₂ emissions in China. It also can be seen that the conversion rate of the influence of Ul on per capita CO₂ emissions is significantly higher than those of GDPpc and Es on per capita CO₂ emissions.

EVOLUTION OF THEORIES AND EMPIRICAL MODELS OF A RELATIONSHIP BETWEEN ECONOMIC GROWTH, SCIENCE AND INNOVATIONS (PART I

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Kaneva M. A.

2017-12-01

Full Text Available This article is a first chapter of an analytical review of existing theoretical models of a relationship between economic growth / GRP and indicators of scientific development and innovation activities, as well as empirical approaches to testing this relationship. Aim of the paper is a systematization of existing approaches to modeling of economic growth geared by science and innovations. The novelty of the current review lies in the authors’ criteria of interconnectedness of theoretical and empirical studies in the systematization of a wide range of publications presented in a final table-scheme. In the first part of the article the authors discuss evolution of theoretical approaches, while the second chapter presents a time gap between theories and their empirical verification caused by the level of development of quantitative instruments such as econometric models. The results of this study can be used by researchers and graduate students for familiarization with current scientific approaches that manifest progress from theory to empirical verification of a relationship «economic growth-innovations» for improvement of different types of models in spatial econometrics. To apply these models to management practices the presented review could be supplemented with new criteria for classification of knowledge production functions and other theories about effect of science on economic growth.

An explanation for the multiplicative and the additive dose-effect relationship with the single-hit model

International Nuclear Information System (INIS)

Kottbauer, M.M.; Fleck, C.M.; Schoellnberger, H.

1997-01-01

For solid tumors and for leukemia the excess cancer rate after a single radiation dose D is different. The multiplicative model describes the excess solid tumor probability rate which is proportional to the background rate of cancer and dependent on dose D. The additive model describes the excess probability rate for leukaemia which is proportional to the dose D but unrelated to the spontaneous rate of cancer. A second great difference between the two models is the duration of the increased cancer probability rate. The multiplicative mode predicts that the additional cancer risk persist the whole lifetime after exposure and the additive model predicts excess risk over a period of time. With the Single-hit model (SHM) which is a multistage cancer model both dose-response relationships can be described. It will be shown that only small differences in the derivation will lead to the different relationships. We then analyze the incidence data of leukemia (1950-1987) and of all solid tumors (1958-1987) of the atomic bomb survivors. (author)

Mediating effects of emotional exhaustion on the relationship between job demand–control model and mental health.

Science.gov (United States)

Huang, Yu-Hwa; Du, Pey-Ian; Chen, Chin-Hui; Yang, Chin-Ann; Huang, Ing-Chung

2011-04-01

This study attempted to investigate the role of emotional exhaustion as a mediator on the relationship between job demands-control (JDC) model and mental health. Three-wave data from 297 employees were collected. The results showed that job demands were positively related to emotional exhaustion, and increasing job demands will increase the level of emotional exhaustion. Job control was negatively associated with emotional exhaustion; therefore, increasing job control will decrease the level of emotional exhaustion. Emotional exhaustion was negatively related to mental health. Emotional exhaustion fully mediated the relationship between job demands and mental health, and partially mediated the positive relationship between job control and mental health. In addition, job control was positively associated with mental health directly. The remarkable finding of the present study was that emotional exhaustion served as the key mediator between the JDC model and mental health. Theoretical and managerial implications and limitations were discussed.

Modeling Relationships Between Flight Crew Demographics and Perceptions of Interval Management

Science.gov (United States)

Remy, Benjamin; Wilson, Sara R.

2016-01-01

The Interval Management Alternative Clearances (IMAC) human-in-the-loop simulation experiment was conducted to assess interval management system performance and participants' acceptability and workload while performing three interval management clearance types. Twenty-four subject pilots and eight subject controllers flew ten high-density arrival scenarios into Denver International Airport during two weeks of data collection. This analysis examined the possible relationships between subject pilot demographics on reported perceptions of interval management in IMAC. Multiple linear regression models were created with a new software tool to predict subject pilot questionnaire item responses from demographic information. General patterns were noted across models that may indicate flight crew demographics influence perceptions of interval management.

The interpersonal relationship in clinical practice. The Barrett-Lennard Relationship Inventory as an assessment instrument.

Science.gov (United States)

Simmons, J; Roberge, L; Kendrick, S B; Richards, B

1995-03-01

The biomedical model that has long been central to medical practice is gradually being expanded to a broader biopsychosocial model. Relationship-building skills commensurate with the new paradigm need to be understood by educators and taught to medical practitioners. The person-centered, or humanistic, model of psychologist Carl Rogers provides a theoretical approach for the development of effective biopsychosocial relationships. The Barrett-Lennard Relationship Inventory (BLRI) was developed in 1962 as an assessment instrument for the person-centered model. In this article, the person-centered model and the use of the BLRI as an assessment instrument of this model are discussed. Current and potential uses of the BLRI are explored.

Newly synthesized benzanthrone derivatives as prospective fluorescent membrane probes

International Nuclear Information System (INIS)

Zhytniakivska, Olga; Trusova, Valeriya; Gorbenko, Galyna; Kirilova, Elena; Kalnina, Inta; Kirilov, Georgiy; Kinnunen, Paavo

2014-01-01

Fluorescence spectral properties of a series of novel benzanthrone derivatives have been explored in lipid bilayers composed of zwitterionic lipid phosphatidylcholine (PC) and its mixtures with cholesterol (Chol) and anionic phospholipid cardiolipin (CL). Analysis of partition coefficients showed that all the examined compounds possess rather high lipid-associating ability, with the amidino derivatives exhibiting stronger membrane partitioning compared with the aminobenzanthrones. To understand how benzanthrone partition properties correlate with their structure, quantitative structure property relationship (QSPR) analysis was performed involving a range of quantum chemical molecular descriptors. -- Highlights: • Benzanthrone partitioning into lipid bilayer correlates with lipophilicity of the dyes. • Partition properties of benzanthrones depend on the dye dipole moment. • Amidino derivatives exhibit higher membrane affinity than aminobenzanthrones

MODELLING THE RELATIONSHIP BETWEEN LAND SURFACE TEMPERATURE AND LANDSCAPE PATTERNS OF LAND USE LAND COVER CLASSIFICATION USING MULTI LINEAR REGRESSION MODELS

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A. M. Bernales

2016-06-01

Full Text Available The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC and land surface temperature (LST. Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric “Effective mesh size” was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas and looking for common predictors between LSTs of these two different farming periods.

Jealousy and Relationship Closeness

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Mark Attridge

2013-02-01

Full Text Available This study confirmed a hypothesis from the Emotion-in-Relationships conceptual model, which predicts that greater interdependence between relationship partners—or closeness—creates the potential for jealousy. The study also sought to better define the positive side of romantic jealousy in addition to its more negative attributes. College students in premarital relationships (N = 229 completed a questionnaire, including 27 different measures and the Multidimensional Jealousy Scale. Select data were obtained from 122 cases at 3-month follow-up. Each jealousy scale was tested for associations with demographic (age, sex, and race, person (life satisfaction, loneliness, romantic attachment styles, love styles, and romantic beliefs, and relationship (affective, closeness, and social exchange theory constructs. Results clearly distinguished emotional/reactive jealousy as mostly “good” and cognitive/suspicious jealousy as “bad.” Behavioral jealousy was associated with few measures. Implications are discussed for the interdependence model of relationships and the transactional model of jealousy.

Relationships between hormones and aggressive behavior in green anole lizards: an analysis using structural equation modeling.

Science.gov (United States)

Yang, Eun-Jin; Wilczynski, Walter

2002-09-01

We investigated the relationship between aggressive behavior and circulating androgens in the context of agonistic social interaction and examined the effect of this interaction on the androgen-aggression relationship in response to a subsequent social challenge in male Anolis carolinensis lizards. Individuals comprising an aggressive encounter group were exposed to an aggressive conspecific male for 10 min per day during a 5-day encounter period, while controls were exposed to a neutral stimulus for the same period. On the sixth day, their responses to an intruder test were observed. At intervals, individuals were sacrificed to monitor plasma androgen levels. Structural equation modeling (SEM) was used to test three a priori interaction models of the relationship between social stimulus, aggressive behavior, and androgen. Model 1 posits that exposure to a social stimulus influences androgen and aggressive behavior independently. In Model 2, a social stimulus triggers aggressive behavior, which in turn increases circulating levels of androgen. In Model 3, exposure to a social stimulus influences circulating androgen levels, which in turn triggers aggressive behavior. During the 5 days of the encounter period, circulating testosterone (T) levels of the aggressive encounter group followed the same pattern as their aggressive behavioral responses, while the control group did not show significant changes in their aggressive behavior or T level. Our SEM results supported Model 2. A means analysis showed that during the intruder test, animals with 5 days of aggressive encounters showed more aggressive responses than did control animals, while their circulating androgen levels did not differ. This further supports Model 2, suggesting that an animal's own aggressive behavior may trigger increases in levels of plasma androgen. Copyright 2002 Elsevier Science (USA)

Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

Science.gov (United States)

Naik, P K; Singh, T; Singh, H

2009-07-01

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

The relationship between multilevel models and non-parametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity.

Science.gov (United States)

Rights, Jason D; Sterba, Sonya K

2016-11-01

Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.

The Relationship between Ethical Culture and Unethical Behavior in Work Groups: Testing the Corporate Ethical Virtues Model

NARCIS (Netherlands)

S.P. Kaptein (Muel)

2008-01-01

textabstractThe Corporate Ethical Virtues Model, which is a model for measuring the ethical culture of organizations, has not been tested on its predictive validity. This study tests the relationship between this model and observed unethical behavior in work groups. The sample consists of 301 triads

Models of Workplace Incivility: The Relationships to Instigated Incivility and Negative Outcomes

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Kristoffer Holm

2015-01-01

Full Text Available The aim of the study was to investigate workplace incivility as a social process, examining its components and relationships to both instigated incivility and negative outcomes in the form of well-being, job satisfaction, turnover intentions, and sleeping problems. The different components of incivility that were examined were experienced and witnessed incivility from coworkers as well as supervisors. In addition, the organizational factors, social support, control, and job demands, were included in the models. A total of 2871 (2058 women and 813 men employees who were connected to the Swedish Hotel and Restaurant Workers Union completed an online questionnaire. Overall, the results from structural equation modelling indicate that whereas instigated incivility to a large extent was explained by witnessing coworker incivility, negative outcomes were to a high degree explained by experienced supervisor incivility via mediation through perceived low social support, low control, and high job demands. Unexpectedly, the relationships between incivility (experienced coworker and supervisor incivility, as well as witnessed supervisor incivility and instigated incivility were moderated by perceived high control and high social support. The results highlight the importance of including different components of workplace incivility and organizational factors in future studies of the area.

Models of Workplace Incivility: The Relationships to Instigated Incivility and Negative Outcomes.

Science.gov (United States)

Holm, Kristoffer; Torkelson, Eva; Bäckström, Martin

2015-01-01

The aim of the study was to investigate workplace incivility as a social process, examining its components and relationships to both instigated incivility and negative outcomes in the form of well-being, job satisfaction, turnover intentions, and sleeping problems. The different components of incivility that were examined were experienced and witnessed incivility from coworkers as well as supervisors. In addition, the organizational factors, social support, control, and job demands, were included in the models. A total of 2871 (2058 women and 813 men) employees who were connected to the Swedish Hotel and Restaurant Workers Union completed an online questionnaire. Overall, the results from structural equation modelling indicate that whereas instigated incivility to a large extent was explained by witnessing coworker incivility, negative outcomes were to a high degree explained by experienced supervisor incivility via mediation through perceived low social support, low control, and high job demands. Unexpectedly, the relationships between incivility (experienced coworker and supervisor incivility, as well as witnessed supervisor incivility) and instigated incivility were moderated by perceived high control and high social support. The results highlight the importance of including different components of workplace incivility and organizational factors in future studies of the area.

Precision comparison of the erosion rates derived from 137Cs measurements models with predictions based on empirical relationship

International Nuclear Information System (INIS)

Yang Mingyi; Liu Puling; Li Liqing

2004-01-01

The soil samples were collected in 6 cultivated runoff plots with grid sampling method, and the soil erosion rates derived from 137 Cs measurements were calculated. The models precision of Zhang Xinbao, Zhou Weizhi, Yang Hao and Walling were compared with predictions based on empirical relationship, data showed that the precision of 4 models is high within 50m slope length except for the slope with low slope angle and short length. Relatively, the precision of Walling's model is better than that of Zhang Xinbao, Zhou Weizhi and Yang Hao. In addition, the relationship between parameter Γ in Walling's improved model and slope angle was analyzed, the ralation is: Y=0.0109 X 1.0072 . (authors)

Conceptual Model of Relationships among Customer Perceptions of Components of Insurance Service

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Sebjan Urban

2015-04-01

Full Text Available The objective of this study was to examine the conceptual model and to study the relationships between customer perceptions of the benefits of sales promotion, quality, adequacy of premium, and adequacy of information about the coverage of insurance services. The research model was tested with structural equation modeling (SEM with a sample of 200 Slovenian users of insurance services. The results indicated that higher perceived benefits of sales promotion were associated with higher perceived quality of insurance services. In addition, higher perceived quality was associated with higher perceived adequacy of information about the coverage and the premium for insurance services. The study also found that higher perceived adequacy of premium was associated with higher perceived adequacy of information about the coverage of insurance services.

Different phylogenomic approaches to resolve the evolutionary relationships among model fish species.

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Negrisolo, Enrico; Kuhl, Heiner; Forcato, Claudio; Vitulo, Nicola; Reinhardt, Richard; Patarnello, Tomaso; Bargelloni, Luca

2010-12-01

Comparative genomics holds the promise to magnify the information obtained from individual genome sequencing projects, revealing common features conserved across genomes and identifying lineage-specific characteristics. To implement such a comparative approach, a robust phylogenetic framework is required to accurately reconstruct evolution at the genome level. Among vertebrate taxa, teleosts represent the second best characterized group, with high-quality draft genome sequences for five model species (Danio rerio, Gasterosteus aculeatus, Oryzias latipes, Takifugu rubripes, and Tetraodon nigroviridis), and several others are in the finishing lane. However, the relationships among the acanthomorph teleost model fishes remain an unresolved taxonomic issue. Here, a genomic region spanning over 1.2 million base pairs was sequenced in the teleost fish Dicentrarchus labrax. Together with genomic data available for the above fish models, the new sequence was used to identify unique orthologous genomic regions shared across all target taxa. Different strategies were applied to produce robust multiple gene and genomic alignments spanning from 11,802 to 186,474 amino acid/nucleotide positions. Ten data sets were analyzed according to Bayesian inference, maximum likelihood, maximum parsimony, and neighbor joining methods. Extensive analyses were performed to explore the influence of several factors (e.g., alignment methodology, substitution model, data set partitions, and long-branch attraction) on the tree topology. Although a general consensus was observed for a closer relationship between G. aculeatus (Gasterosteidae) and Di. labrax (Moronidae) with the atherinomorph O. latipes (Beloniformes) sister taxon of this clade, with the tetraodontiform group Ta. rubripes and Te. nigroviridis (Tetraodontiformes) representing a more distantly related taxon among acanthomorph model fish species, conflicting results were obtained between data sets and methods, especially with respect

External validation of structure-biodegradation relationship (SBR) models for predicting the biodegradability of xenobiotics.

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Devillers, J; Pandard, P; Richard, B

2013-01-01

Biodegradation is an important mechanism for eliminating xenobiotics by biotransforming them into simple organic and inorganic products. Faced with the ever growing number of chemicals available on the market, structure-biodegradation relationship (SBR) and quantitative structure-biodegradation relationship (QSBR) models are increasingly used as surrogates of the biodegradation tests. Such models have great potential for a quick and cheap estimation of the biodegradation potential of chemicals. The Estimation Programs Interface (EPI) Suite™ includes different models for predicting the potential aerobic biodegradability of organic substances. They are based on different endpoints, methodologies and/or statistical approaches. Among them, Biowin 5 and 6 appeared the most robust, being derived from the largest biodegradation database with results obtained only from the Ministry of International Trade and Industry (MITI) test. The aim of this study was to assess the predictive performances of these two models from a set of 356 chemicals extracted from notification dossiers including compatible biodegradation data. Another set of molecules with no more than four carbon atoms and substituted by various heteroatoms and/or functional groups was also embodied in the validation exercise. Comparisons were made with the predictions obtained with START (Structural Alerts for Reactivity in Toxtree). Biowin 5 and Biowin 6 gave satisfactorily prediction results except for the prediction of readily degradable chemicals. A consensus model built with Biowin 1 allowed the diminution of this tendency.

Leadership models with an emphasis on relationships and the completion of the project in information science

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Damaskinou, Aikaterini I.; Drivas, Ioannis C.; Sakas, Damianos P.

2015-02-01

While attempting decision-making in leadership, one of the criteria that should be considered is the actual behavior of the leader towards the work group. The object of this study is the prevalence of two key leadership models, the Task Behavior and the Relationship Behavior. Firstly, the leader's behavior is focused on completing the project combined with a leadership style which is more interventionist and less conciliatory. The second leadership model focuses on working relationships, developed between leaders and employees. In this case, the character of the model is associated with a leadership behavior more supportive, motivating and participative. This article refers to the characteristics of the two models and the mechanisms and strategies that can be adopted in both leadership behaviors. Furthermore, through the research which took place, we have come to conclusions regarding the public's views about the different leadership behaviors and, also, the possibility of combining the two styles of leadership.

A model of the instantaneous pressure-velocity relationships of the neonatal cerebral circulation.

Science.gov (United States)

Panerai, R B; Coughtrey, H; Rennie, J M; Evans, D H

1993-11-01

The instantaneous relationship between arterial blood pressure (BP) and cerebral blood flow velocity (CBFV), measured with Doppler ultrasound in the anterior cerebral artery, is represented by a vascular waterfall model comprising vascular resistance, compliance, and critical closing pressure. One min recordings obtained from 61 low birth weight newborns were fitted to the model using a least-squares procedures with correction for the time delay between the BP and CBFV signals. A sensitivity analysis was performed to study the effects of low-pass filtering (LPF), cutoff frequency, and noise on the estimated parameters of the model. Results indicate excellent fitting of the model (F-test, p model parameters have a mean correlation coefficient of 0.94 with the measured flow velocity tracing (N = 232 epochs). The model developed can be useful for interpreting clinical findings and as a framework for research into cerebral autoregulation.

Relationship outcomes as measurement criteria to assist communication strategists to manage organisational relationships

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E. Botha

2011-06-01

Full Text Available Nonfinancial assets like relationships are increasingly important to managers. Communication managers in particular are focusing on measuring and managing organisational relationships as a means to quantify the return on investment (ROI of public relations and communication strategies. Measuring relationships offers communication managers a way to evaluate its contribution to the organisation. A commonly agreed upon definition of these relationships, however, does not exist. If we consider communication management is a managerial function, it must first refine its instruments of measurement. This study looks at the three-stage model of organisational relationships (relationship antecedents, maintenance strategies and relationship outcomes proposed by Grunig & Huang (2000 to firstly review the development of the model. Secondly, the study takes an in-depth look at each relationship outcomes of trust, commitment, satisfaction and control mutuality. Lastly, we assess the reliability and validity of the use of current relationship outcome measures through a survey of 154 organisational relationships. Previous studies that have utilized these outcomes in the measurement of organisational relationships do not discuss the possible interaction (or relationship among these outcomes. This study contributes to current literature by both providing an improved framework for the measurement of relationship outcomes and hypothesizing about how these outcomes interact with one another. It also discusses the managerial implications of managing relationships through the constant measurement of trust, commitment, satisfaction and control mutuality

Relationship model and supporting activities of JIT, TQM and TPM

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Nuttapon SaeTong

2011-02-01

Full Text Available This paper gives a relationship model and supporting activities of Just-in-time (JIT, Total Quality Management (TQM,and Total Productive Maintenance (TPM. By reviewing the concepts, 5S, Kaizen, preventive maintenance, Kanban, visualcontrol, Poka-Yoke, and Quality Control tools are the main supporting activities. Based on the analysis, 5S, preventive maintenance,and Kaizen are the foundation of the three concepts. QC tools are required activities for implementing TQM, whereasPoka-Yoke and visual control are necessary activities for implementing TPM. After successfully implementing TQM andTPM, Kanban is needed for JIT.

The relationship between quality management practices and organisational performance: A structural equation modelling approach

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Jamaluddin, Z.; Razali, A. M.; Mustafa, Z.

2015-02-01

The purpose of this paper is to examine the relationship between the quality management practices (QMPs) and organisational performance for the manufacturing industry in Malaysia. In this study, a QMPs and organisational performance framework is developed according to a comprehensive literature review which cover aspects of hard and soft quality factors in manufacturing process environment. A total of 11 hypotheses have been put forward to test the relationship amongst the six constructs, which are management commitment, training, process management, quality tools, continuous improvement and organisational performance. The model is analysed using Structural Equation Modeling (SEM) with AMOS software version 18.0 using Maximum Likelihood (ML) estimation. A total of 480 questionnaires were distributed, and 210 questionnaires were valid for analysis. The results of the modeling analysis using ML estimation indicate that the fits statistics of QMPs and organisational performance model for manufacturing industry is admissible. From the results, it found that the management commitment have significant impact on the training and process management. Similarly, the training had significant effect to the quality tools, process management and continuous improvement. Furthermore, the quality tools have significant influence on the process management and continuous improvement. Likewise, the process management also has a significant impact to the continuous improvement. In addition the continuous improvement has significant influence the organisational performance. However, the results of the study also found that there is no significant relationship between management commitment and quality tools, and between the management commitment and continuous improvement. The results of the study can be used by managers to prioritize the implementation of QMPs. For instances, those practices that are found to have positive impact on organisational performance can be recommended to

Towards a unified model for leaf trait and trait-environment relationships

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Wang, H.; Harrison, S. P.; Prentice, I. C.; Peng, C.; Yang, Y.

2016-12-01

A widely accepted core set of leaf traits describes key aspects of plant function including the coupling among carbon, nitrogen and water cycles at the leaf, plant and ecosystem scales. Our current research focuses on two questions: (1) what dimensions of correlated variation among traits apply across all vascular plants irrespective of environment; (2) how, and to what extent, can variations in community mean values of leaf traits be predicted along environmental gradients? Based on a large quantitative trait data set covering the major environmental gradients across China, we are tackling these questions via two complementary approaches: multivariate analysis of trait-trait, trait-site, and trait-environment relationships, and the development of conceptual models and testable hypotheses for the dependencies of each trait on other traits and/or specific environmental predictors. Preliminary multivariate analyses suggest the existence of at least two independent axes of variation in leaf traits, and show robust relationships between trait syndromes and growing-season climate variables. A minimal conceptual model then considers nitrogen per unit leaf area (Narea) as a function of leaf mass per unit area (LMA) and carboxylation capacity (Vcmax); LMA as a function of irradiance, temperature and water and/or nutrient stress; Vcmax as a function of irradiance, temperature and the long-term ci:ca ratio (indexed by δ13C); and the ci:ca ratio as a function of vapour pressure deficit, temperature and atmospheric pressure. Each of these dependencies has support from observations, pointing the way towards a comprehensive set of equations to predict community-mean values of core traits in next-generation terrestrial ecosystem models.

IntPath--an integrated pathway gene relationship database for model organisms and important pathogens.

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Zhou, Hufeng; Jin, Jingjing; Zhang, Haojun; Yi, Bo; Wozniak, Michal; Wong, Limsoon

2012-01-01

Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. In this paper, we overcome these issues through extraction, normalization and integration of pathway data from several major public databases (KEGG, WikiPathways, BioCyc, etc). We build a database that not only hosts our integrated pathway gene relationship data for public access but also maintains the necessary updates in the long run. This public repository is named IntPath (Integrated Pathway gene relationship database for model organisms and important pathogens). Four organisms--S. cerevisiae, M. tuberculosis H37Rv, H. Sapiens and M. musculus--are included in this version (V2.0) of IntPath. IntPath uses the "full unification" approach to ensure no deletion and no introduced noise in this process. Therefore, IntPath contains much richer pathway-gene and pathway-gene pair relationships and much larger number of non-redundant genes and gene pairs than any of the single-source databases. The gene relationships of each gene (measured by average node degree) per pathway are significantly richer. The gene relationships in each pathway (measured by average number of gene pairs per pathway) are also considerably richer in the integrated pathways. Moderate manual curation are involved to get rid of errors and noises from source data (e.g., the gene ID errors in WikiPathways and

Developing a Customer Relationship Management Model for Better Health Examination Service

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Lyu Jr-Jung

2014-11-01

Full Text Available People emphasize on their own health and wish to know more about their conditions. Chronic diseases now take up to 50 percent of top 10 causes of death. As a result, the health-care industry has emerged and kept thriving. This work adopts a customer-oriented business model since most clients are proactive and spontaneous in taking the “distinguished” health examination programs. We adopt the soft system dynamics methodology (SSDM to develop and to evaluate the steps of introducing customer relationship management model into a case health examination organization. Quantitative results are also presented for a case physical examination center and to assess the improved efficiency. The case study shows that the procedures developed here could provide a better service.

Prediction of absolute entropy of ideal gas at 298 K of pure chemicals through GAMLR and FFNN

International Nuclear Information System (INIS)

Fazeli, Ali; Bagheri, Mehdi; Ghaniyari-Benis, Saeid; Aslebagh, Roshanak; Kamaloo, Elaheh

2011-01-01

Thermodynamical optimization for energy conversion system can be performed by decreasing entropy generation. For calculation of entropy, we need to know entropy of ideal gases at 298 K as a reference point. Entropy is a thermodynamic quantity which is not easily measured and prediction of entropy by molecular structures for new designed molecules may be a challenge. An easy and accurate equation for prediction of absolute entropy of pure ideal gas at 298 K was introduced for the first time based on the quantitative structure property relationship (QSPR) approach. Thousand seven hundred pure chemical compounds and 3224 molecular descriptors were used for finding this easy equation by genetic algorithm multi-linear regression (GAMLR) subset variable selection. Our work are based on 1700 chemicals in 81 chemical families that is the most comprehensive available data sets for absolute entropy of ideal gases. The final model is linear and has three molecular descriptors with the squared correlation coefficient of 0.9885 (R 2 = 0.9885). Also, feed forward neural network (FFNN) was used for considering non linearity effect of the model. It has the squared correlation coefficient of 0.9909 (R 2 = 0.9909). The model passes all validity check methods. The novel proposed model has the predictability for new designed molecules by having the molecular structures of them.

Dynamics of the Indian monsoon and ENSO relationships in the SINTEX global coupled model

Energy Technology Data Exchange (ETDEWEB)

Terray, P. [LODYC, Paris (France); Universite Paris 7, Paris (France); Guilyardi, E. [LSCE, Gif-sur-Yvette (France); CGAM, Reading (United Kingdom); Fischer, A.S. [LODYC, Paris (France); Delecluse, P. [LODYC, Paris (France); LSCE, Gif-sur-Yvette (France)

2005-02-01

This paper uses recent gridded climatological data and a coupled general circulation model (GCM) simulation in order to assess the relationships between the interannual variability of the Indian summer monsoon (ISM) and the El Nino-Southern Oscillation (ENSO). The focus is on the dynamics of the ISM-ENSO relationships and the ability of the state-of-the-art coupled GCM to reproduce the complex lead-lag relationships between the ISM and the ENSO. The coupled GCM is successful in reproducing the ISM circulation and rainfall climatology in the Indian areas even though the entire ISM circulation is weaker relative to that observed. In both observations and in the simulation, the ISM rainfall anomalies are significantly associated with fluctuations of the Hadley circulation and the 200 hPa zonal wind anomalies over the Indian Ocean. A quasi-biennial time scale is found to structure the ISM dynamical and rainfall indices in both cases. Moreover, ISM indices have a similar interannual variability in the simulation and observations. The coupled model is less successful in simulating the annual cycle in the tropical Pacific. Despite some problems in simulation of the annual cycle and the Southern Oscillation, the coupled model captures some aspects of the interannual variability in the tropical Pacific. ENSO events are phase-locked with the annual cycle as observed, but are of reduced amplitude relative to the observations. Wavelet analysis of the model Nino34 time series shows enhanced power in the 2-4 year band, as compared to the 2-8 year range for observations during the 1950-2000 period. The ISM circulation is weakened during ENSO years in both the simulation and the observations. However, the model fails to reproduce the lead-lag relationship between the ISM and Nino34 sea surface temperatures (SSTs). Furthermore, lag correlations show that the delayed response of the wind stress over the central Pacific to ISM variability is insignificant in the simulation. These

Relationship between Family Adaptability, Cohesion and Adolescent Problem Behaviors: Curvilinearity of Circumplex Model

Science.gov (United States)

Joh, Ju Youn; Kim, Sun; Park, Jun Li

2013-01-01

Background The Family Adaptability and Cohesion Evaluation Scale (FACES) III using the circumplex model has been widely used in investigating family function. However, the criticism of the curvilinear hypothesis of the circumplex model has always been from an empirical point of view. This study examined the relationship between adolescent adaptability, cohesion, and adolescent problem behaviors, and especially testing the consistency of the curvilinear hypotheses with FACES III. Methods We used the data from 398 adolescent participants who were in middle school. A self-reported questionnaire was used to evaluate the FACES III and Youth Self Report. Results According to the level of family adaptability, significant differences were evident in internalizing problems (P = 0.014). But, in externalizing problems, the results were not significant (P = 0.305). Also, according to the level of family cohesion, significant differences were in internalizing problems (P = 0.002) and externalizing problems (P = 0.004). Conclusion The relationship between the dimensions of adaptability, cohesion and adolescent problem behaviors was not curvilinear. In other words, adolescents with high adaptability and high cohesion showed low problem behaviors. PMID:23730484

Relationship between Family Adaptability, Cohesion and Adolescent Problem Behaviors: Curvilinearity of Circumplex Model.

Science.gov (United States)

Joh, Ju Youn; Kim, Sun; Park, Jun Li; Kim, Yeon Pyo

2013-05-01

The Family Adaptability and Cohesion Evaluation Scale (FACES) III using the circumplex model has been widely used in investigating family function. However, the criticism of the curvilinear hypothesis of the circumplex model has always been from an empirical point of view. This study examined the relationship between adolescent adaptability, cohesion, and adolescent problem behaviors, and especially testing the consistency of the curvilinear hypotheses with FACES III. We used the data from 398 adolescent participants who were in middle school. A self-reported questionnaire was used to evaluate the FACES III and Youth Self Report. According to the level of family adaptability, significant differences were evident in internalizing problems (P = 0.014). But, in externalizing problems, the results were not significant (P = 0.305). Also, according to the level of family cohesion, significant differences were in internalizing problems (P = 0.002) and externalizing problems (P = 0.004). The relationship between the dimensions of adaptability, cohesion and adolescent problem behaviors was not curvilinear. In other words, adolescents with high adaptability and high cohesion showed low problem behaviors.

Methods for Specifying Scientific Data Standards and Modeling Relationships with Applications to Neuroscience

Science.gov (United States)

Rübel, Oliver; Dougherty, Max; Prabhat; Denes, Peter; Conant, David; Chang, Edward F.; Bouchard, Kristofer

2016-01-01

Neuroscience continues to experience a tremendous growth in data; in terms of the volume and variety of data, the velocity at which data is acquired, and in turn the veracity of data. These challenges are a serious impediment to sharing of data, analyses, and tools within and across labs. Here, we introduce BRAINformat, a novel data standardization framework for the design and management of scientific data formats. The BRAINformat library defines application-independent design concepts and modules that together create a general framework for standardization of scientific data. We describe the formal specification of scientific data standards, which facilitates sharing and verification of data and formats. We introduce the concept of Managed Objects, enabling semantic components of data formats to be specified as self-contained units, supporting modular and reusable design of data format components and file storage. We also introduce the novel concept of Relationship Attributes for modeling and use of semantic relationships between data objects. Based on these concepts we demonstrate the application of our framework to design and implement a standard format for electrophysiology data and show how data standardization and relationship-modeling facilitate data analysis and sharing. The format uses HDF5, enabling portable, scalable, and self-describing data storage and integration with modern high-performance computing for data-driven discovery. The BRAINformat library is open source, easy-to-use, and provides detailed user and developer documentation and is freely available at: https://bitbucket.org/oruebel/brainformat. PMID:27867355

Structural equation modeling assessing relationship between mathematics beliefs, teachers' attitudes and teaching practices among novice teachers in Malaysia

Science.gov (United States)

Borhan, Noziati; Zakaria, Effandi

2017-05-01

This quantitative study was conducted to investigate the perception level of novice teachers about mathematics belief, teachers' attitude towards mathematics and teaching practices of mathematics in the classroom. In addition, it also aims to identify whether there is a correspondence model with the data obtained and to identify the relationship between the variables of beliefs, attitudes and practices among novice teachers in Malaysia. A total of 263 primary novice teachers throughout the country were involved in this study were selected randomly. Respondents are required to provide a response to the questionnaire of 66 items related to mathematics beliefs, attitudes and practices of the teaching mathematics. There are ten sub-factors which have been established in this instrument for three major constructs using a Likert scale rating of five points. The items of the constructs undergo the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) procedure involve of unidimensionality test, convergent validity, construct validity and discriminant validity. Descriptive statistics were used to describe the frequency, percentage, the mean and standard deviation for completing some research questions that have been expressed. As for inferential statistical analysis, the researchers used structural equation modeling (SEM) to answer the question of correspondents model and the relationship between these three variables. The results of the study were found that there exist a correspondence measurement and structural model with the data obtained. While the relationship between variable found that mathematics beliefs have a significant influence on teachers' attitudes towards mathematics as well as the relationship between the attitudes with teaching practices. Meanwhile, mathematics belief had no significant relationship with mathematics teaching practices among novice teachers in Malaysia.

Enacting Firm, Fair and Friendly Practice: A Model for Strengths-Based Child Protection Relationships?

Science.gov (United States)

Oliver, Carolyn; Charles, Grant

2016-06-01

Strengths-based solution-focused approaches are gaining ground in statutory child protection work, but few studies have asked front line practitioners how they navigate the complex worker-client relationships such approaches require. This paper describes one component of a mixed-methods study in a large Canadian statutory child protection agency in which 225 workers described how they applied the ideas of strengths-based practice in their daily work. Interviews with twenty-four practitioners were analysed using an interpretive description approach. Only four interviewees appeared to successfully enact a version of strengths-based practice that closely mirrored those described by key strengths-based child protection theorists and was fully congruent with their mandated role. They described navigating a shifting balance of collaboration and authority in worker-client relationships based on transparency, impartial judgement, attentiveness to the worker-client interaction and the value that clients were fellow human beings. Their accounts extend current conceptualisations of the worker-client relationship in strengths-based child protection work and are congruent with current understandings of effective mandated relationships. They provide what may be a useful model to help workers understand and navigate relationships in which they must reconcile their own authority and expertise with genuine support for the authority and expertise of their clients.

Prediction of supercooled liquid vapor pressures and n-octanol/air partition coefficients for polybrominated diphenyl ethers by means of molecular descriptors from DFT method

International Nuclear Information System (INIS)

Wang Zunyao; Zeng Xiaolan; Zhai Zhicai

2008-01-01

The molecular geometries of 209 polybrominated diphenyl ethers (PBDEs) were optimized at the B3LYP/6-31G* level with Gaussian 98 program. The calculated structural parameters were taken as theoretical descriptors to establish two novel QSPR models for predicting supercooled liquid vapor pressures (P L ) and octanol/air partition coefficients (K OA ) of PBDEs based on the theoretical linear solvation energy relationship (TLSER) model, respectively. The two models achieved in this work both contain three variables: most negative atomic partial charge in molecule (q - ), dipole moment of the molecules (μ) and mean molecular polarizability (α), of which R 2 values are both as high as 0.997, their root-mean-square errors in modeling (RSMEE) are 0.069 and 0.062 respectively. In addition, the F-value of two models are both evidently larger than critical values F 0.05 and the variation inflation factors (VIF) of variables herein are all less than 5.0, suggesting obvious statistic significance of the P L and K OA predicting models. The results of Leave-One-Out (LOO) cross-validation for training set and validation with external test set both show that the two models obtained exhibited optimum stability and good predictive power. We suggest that the QSPRs derived here can be used to predict accurately P L and K OA for non-tested PBDE congeners from Mono-BDEs to Hepta-BDEs and from Mono-BDEs to Hexa-BDEs, respectively

Seismic attenuation relationship with homogeneous and heterogeneous prediction-error variance models

Science.gov (United States)

Mu, He-Qing; Xu, Rong-Rong; Yuen, Ka-Veng

2014-03-01

Peak ground acceleration (PGA) estimation is an important task in earthquake engineering practice. One of the most well-known models is the Boore-Joyner-Fumal formula, which estimates the PGA using the moment magnitude, the site-to-fault distance and the site foundation properties. In the present study, the complexity for this formula and the homogeneity assumption for the prediction-error variance are investigated and an efficiency-robustness balanced formula is proposed. For this purpose, a reduced-order Monte Carlo simulation algorithm for Bayesian model class selection is presented to obtain the most suitable predictive formula and prediction-error model for the seismic attenuation relationship. In this approach, each model class (a predictive formula with a prediction-error model) is evaluated according to its plausibility given the data. The one with the highest plausibility is robust since it possesses the optimal balance between the data fitting capability and the sensitivity to noise. A database of strong ground motion records in the Tangshan region of China is obtained from the China Earthquake Data Center for the analysis. The optimal predictive formula is proposed based on this database. It is shown that the proposed formula with heterogeneous prediction-error variance is much simpler than the attenuation model suggested by Boore, Joyner and Fumal (1993).

A recalculation of the dose-effect-relationship of the ''life span study'' of Hiroshima and Nagasaki with the ''single-hit model''

International Nuclear Information System (INIS)

Kottbauer, M.M.; Fleck, C.M.; Schoellnberger, H.

1996-01-01

The basis of this new model is the multistage process of carcinogeneses. The Single-Hit Model is a further development of the Armitage-Doll Model [1] for the special case of a short exposure. It provides simultaneously the age-dependent mortality-rate (incidence-rate) of the spontaneous and radiation induced solid tumors and dose-effect relationships at any age after exposure. The model results in a biologically based dose-effect relationship, which is similar to the Relativ-Risk-Model suggested by the ICRP 60 [2]. The present model is able to describe the increased mortality rate of the bomb survivors more accurate than the Relativ-Risk-Model. (orig.) [de

Team Investment and Longitudinal Relationships: An Innovative Global Health Education Model.

Science.gov (United States)

Myers, Kimberly R; Fredrick, N Benjamin

2017-12-01

Increasing student interest in global health has resulted in medical schools offering more global health opportunities. However, concerns have been raised, particularly about one-time, short-term experiences, including lack of follow-through for students and perpetuation of unintentional messages of global health heroism, neocolonialism, and disregard for existing systems and communities of care. Medical schools must develop global health programs that address these issues. The Global Health Scholars Program (GHSP) was created in 2008-2009 at Penn State College of Medicine. This four-year program is based on values of team investment and longitudinal relationships and uses the service-learning framework of preparation, service, and reflection. Teams of approximately five students, with faculty oversight, participate in two separate monthlong trips abroad to the same host community in years 1 and 4, and in campus- and Web-based activities in years 2 and 3. As of December 2016, 191 students have been accepted into the GHSP. Since inception, applications have grown by 475% and program sites have expanded from one to seven sites on four continents. The response from students has been positive, but logistical challenges persist in sustaining team investment and maintaining longitudinal relationships between student teams and host communities. Formal methods of assessment should be used to compare the GHSP model with more traditional approaches to global health education. Other medical schools with similar aims can adapt the GHSP model to expand their global health programming.

The Relationship between the Big-Five Model of Personality and Self-Regulated Learning Strategies

Science.gov (United States)

Bidjerano, Temi; Dai, David Yun

2007-01-01

The study examined the relationship between the big-five model of personality and the use of self-regulated learning strategies. Measures of self-regulated learning strategies and big-five personality traits were administered to a sample of undergraduate students. Results from canonical correlation analysis indicated an overlap between the…

Predictor Relationships between Values Held by Married Individuals, Resilience and Conflict Resolution Styles: A Model Suggestion

Science.gov (United States)

Tosun, Fatma; Dilmac, Bulent

2015-01-01

The aim of the present research is to reveal the predictor relationships between the values held by married individuals, resilience and conflict resolution styles. The research adopts a relational screening model that is a sub-type of the general screening model. The sample of the research consists of 375 married individuals, of which 173 are…

Quantitative structure-activity relationship modeling of the toxicity of organothiophosphate pesticides to Daphnia magna and Cyprinus carpio

NARCIS (Netherlands)

Zvinavashe, E.; Du, T.; Griff, T.; Berg, van den J.H.J.; Soffers, A.E.M.F.; Vervoort, J.J.M.; Murk, A.J.; Rietjens, I.

2009-01-01

Within the REACH regulatory framework in the EU, quantitative structure-activity relationships (QSAR) models are expected to help reduce the number of animals used for experimental testing. The objective of this study was to develop QSAR models to describe the acute toxicity of organothiophosphate

The relationship between occupational culture dimensions and reward preferences: A structural equation modelling approach

Directory of Open Access Journals (Sweden)

Mark Bussin

2016-06-01

Full Text Available Orientation: Reward has links to employee attraction and retention and as such has a role to play in managing talent. However, despite a range of research, there is still lack of clarity on employee preferences relating to reward. Research purpose: The purpose of the research was to recommend and appraise a theoretical model of the relationship between occupational culture dimensions and reward preferences of specific occupational groups in the South African context. Motivation for the study: The motivation for this study was to address the gap that exists with reward preferences and occupational culture with a view to identifying and gaining insight into individual preferences. Research design, approach and method: A structural equation modelling approach was adopted in exploring the proposed relationships. A South African Information, Communication, and Technology (ICT organisation served as the population, and a web-based survey assisted in gathering study data (n = 1362. Main findings: The findings provided support for the relationship between occupational culture dimensions and certain reward preferences. In particular, statistically significant results were obtained with the inclusion of the Environment, Team, and Time occupational culture dimensions as independent variables. Practical implications and value-add: The study provides workable input to organisations and reward professionals in the design of their reward strategies and programmes. Keywords: compensation; employee preferences; occupational culture; remuneration; reward preferences

Characterization and Prediction of Chemical Functions and ...

Science.gov (United States)

Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents). We combined these functions with weight fraction data for 4115 personal care products (PCPs) to characterize the composition of 66 different product categories (e.g., shampoos). We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR) classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties). We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-b

Toward a multidimensional model of athletes' commitment to coach-athlete relationships and interdependent sport teams: a substantive-methodological synergy.

Science.gov (United States)

Jackson, Ben; Gucciardi, Daniel F; Dimmock, James A

2014-02-01

Drawing from a three-factor model of organizational commitment, we sought to provide validity evidence for a multidimensional conceptualization designed to capture adolescent athletes' commitment to their coach-athlete relationship or their team. In Study 1, 335 individual-sport athletes (Mage = 17.32, SD = 1.38) completed instruments assessing affective, normative, and continuance commitment to their relationship with their coach, and in Study 2, contextually modified instruments were administered to assess interdependent-sport athletes' (N = 286, Mage = 16.31, SD = 1.33) commitment to their team. Bayesian structural equation modeling revealed support for a three-factor (in comparison with a single-factor) model, along with relations between commitment dimensions and relevant correlates (e.g., satisfaction, return intentions, cohesion) that were largely consistent with theory. Guided by recent advancements in Bayesian modeling, these studies provide a new commitment instrument with the potential for use and refinement in team- and relationship-based settings and offer preliminary support for a conceptual framework that may help advance our understanding of the factors underpinning individuals' engagement in sport.

THREE-DIMENSIONAL QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIP (3D-QSPR) MODELS FOR PREDICTION OF THERMODYNAMIC PROPERTIES OF POLYCHLORINATED BIPHENYLS (PCBS): ENTHALPY OF VAPORIZATION. (R826133)

Science.gov (United States)

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Relationship between the transverse-field Ising model and the X Y model via the rotating-wave approximation

Science.gov (United States)

Kiely, Thomas G.; Freericks, J. K.

2018-02-01

In a large transverse field, there is an energy cost associated with flipping spins along the axis of the field. This penalty can be employed to relate the transverse-field Ising model in a large field to the X Y model in no field (when measurements are performed at the proper stroboscopic times). We describe the details for how this relationship works and, in particular, we also show under what circumstances it fails. We examine wave-function overlap between the two models and observables, such as spin-spin Green's functions. In general, the mapping is quite robust at short times, but will ultimately fail if the run time becomes too long. There is also a tradeoff between the length of time one can run a simulation out to and the time jitter of the stroboscopic measurements that must be balanced when planning to employ this mapping.

Analysis of albedo versus cloud fraction relationships in liquid water clouds using heuristic models and large eddy simulation

Science.gov (United States)

Feingold, Graham; Balsells, Joseph; Glassmeier, Franziska; Yamaguchi, Takanobu; Kazil, Jan; McComiskey, Allison

2017-07-01

The relationship between the albedo of a cloudy scene A and cloud fraction fc is studied with the aid of heuristic models of stratocumulus and cumulus clouds. Existing work has shown that scene albedo increases monotonically with increasing cloud fraction but that the relationship varies from linear to superlinear. The reasons for these differences in functional dependence are traced to the relationship between cloud deepening and cloud widening. When clouds deepen with no significant increase in fc (e.g., in solid stratocumulus), the relationship between A and fc is linear. When clouds widen as they deepen, as in cumulus cloud fields, the relationship is superlinear. A simple heuristic model of a cumulus cloud field with a power law size distribution shows that the superlinear A-fc behavior is traced out either through random variation in cloud size distribution parameters or as the cloud field oscillates between a relative abundance of small clouds (steep slopes on a log-log plot) and a relative abundance of large clouds (flat slopes). Oscillations of this kind manifest in large eddy simulation of trade wind cumulus where the slope and intercept of the power law fit to the cloud size distribution are highly correlated. Further analysis of the large eddy model-generated cloud fields suggests that cumulus clouds grow larger and deeper as their underlying plumes aggregate; this is followed by breakup of large plumes and a tendency to smaller clouds. The cloud and thermal size distributions oscillate back and forth approximately in unison.

Modeling the Contested Relationship between Analects, Mencius, and Xunzi

DEFF Research Database (Denmark)

Nichols, Ryan; Slingerland, Edward; Nielbo, Kristoffer Laigaard

2018-01-01

the other two; and explains topics that intersect all three texts. The authors’ results confirm many scholarly opinions derived from close-reading methods, suggest a reappraisal of Xunzi’s shared semantic content with Analects, and yield several actionable research questions for traditional scholarship......This article presents preliminary findings from a multi-year, multi-disciplinary text analysis project using an ancient and medieval Chinese corpus of over five million characters in works that date from the earliest received texts to the Song dynasty. It describes “distant reading” methods...... in the humanities and the authors’ corpus; introduces topic-modeling procedures; answers questions about the authors’ data; discusses complementary relationships between machine learning and human expertise; explains topics represented in Analects, Mencius, and Xunzi that set each of those texts apart from...

A comprehensive model of stress - The roles of experienced stress and neuroticism in explaining the stress-distress relationship

NARCIS (Netherlands)

De Jong, GM; van Sonderen, E; Emmelkamp, PMG

1999-01-01

Background: In this study, a complex theoretical model regarding the stress-distress relationship was evaluated. The various components in the model included experienced stress (daily hassles), psychological distress, neuroticism, problem-focused coping, avoidant coping, satisfaction with received

Garrison's model of self-directed learning: preliminary validation and relationship to academic achievement.

Science.gov (United States)

Abd-El-Fattah, Sabry M

2010-11-01

In this project, 119 undergraduates responded to a questionnaire tapping three psychological constructs implicated in Garrison's model of self-directed learning: self-management, self-monitoring, and motivation. Mediation analyses showed that these psychological constructs are interrelated and that motivation mediates the relationship between self-management and self-monitoring. Path modeling analyses revealed that self-management and self-monitoring significantly predicted academic achievement over two semesters with self-management being the strongest predictor. Motivation significantly predicted academic achievement over the second semester only. Implications of these findings for self-directed learning and academic achievement in a traditional classroom setting are discussed.

Coupling Longitudinal Data and Multilevel Modeling to Examine the Antecedents and Consequences of Jealousy Experiences in Romantic Relationships: A Test of the Relational Turbulence Model

Science.gov (United States)

Theiss, Jennifer A.; Solomon, Denise Haunani

2006-01-01

We used longitudinal data and multilevel modeling to examine how intimacy, relational uncertainty, and failed attempts at interdependence influence emotional, cognitive, and communicative responses to romantic jealousy, and how those experiences shape subsequent relationship characteristics. The relational turbulence model (Solomon & Knobloch,…

Using structural equation modeling to investigate relationships among ecological variables

Science.gov (United States)

Malaeb, Z.A.; Kevin, Summers J.; Pugesek, B.H.

2000-01-01

Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude -0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0

Modeled dosage-response relationship on the net photosynthetic rate for the sensitivity to acid rain of 21 plant species.

Science.gov (United States)

Deng, Shihuai; Gou, Shuzhen; Sun, Baiye; Lv, Wenlin; Li, Yuanwei; Peng, Hong; Xiao, Hong; Yang, Gang; Wang, Yingjun

2012-08-01

This study investigated the sensitivity of plant species to acid rain based on the modeled dosage-response relationship on the net photosynthetic rate (P (N)) of 21 types of plant species, subjected to the exposure of simulated acid rain (SAR) for 5 times during a period of 50 days. Variable responses of P (N) to SAR occurred depending on the type of plant. A majority (13 species) of the dosage-response relationship could be described by an S-shaped curve and be fitted with the Boltzmann model. Model fitting allowed quantitative evaluation of the dosage-response relationship and an accurate estimation of the EC(10), termed as the pH of the acid rain resulting in a P (N) 10 % lower than the reference value. The top 9 species (Camellia sasanqua, Cinnamomum camphora, etc. EC(10) ≤ 3.0) are highly endurable to very acid rain. The rare, relict plant Metasequoia glyptostroboides was the most sensitive species (EC(10) = 5.1) recommended for protection.

Exploring Longitudinal Risk-return Relationships

DEFF Research Database (Denmark)

Andersen, Torben J.; Bettis, Richard A.

2015-01-01

We study a longitudinal fit model of adaptation and its association with the longitudinal risk-return relationship. The model allows the firm to adjust its position in response to partial learning about a changing environment characterized by two path-dependent processes—a random walk and a stoch......We study a longitudinal fit model of adaptation and its association with the longitudinal risk-return relationship. The model allows the firm to adjust its position in response to partial learning about a changing environment characterized by two path-dependent processes—a random walk...... can lead to the inverse longitudinal risk-return relationships observed empirically. We discuss this apparent paradox and the possible resolution between mindless and conscious behavior as plausible causes of the longitudinal Bowman Paradox....

Characterization and prediction of chemical functions and weight fractions in consumer products

Directory of Open Access Journals (Sweden)

Kristin K. Isaacs

Full Text Available Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents. We combined these functions with weight fraction data for 4115 personal care products (PCPs to characterize the composition of 66 different product categories (e.g., shampoos. We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties. We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-based chemical prioritization. Keywords: Chemical function, Exposure modeling, Chemical prioritization, Consumer products, Cosmetics, ExpoCast

Examining Asymmetrical Relationships of Organizational Learning Antecedents: A Theoretical Model

Directory of Open Access Journals (Sweden)

Ery Tri Djatmika

2016-02-01

Full Text Available Global era is characterized by highly competitive advantage market demand. Responding to the challenge of rapid environmental changes, organizational learning is becoming a strategic way and solution to empower people themselves within the organization in order to create a novelty as valuable positioning source. For research purposes, determining the influential antecedents that affect organizational learning is vital to understand research-based solutions given for practical implications. Accordingly, identification of variables examined by asymmetrical relationships is critical to establish. Possible antecedent variables come from organizational and personal point of views. It is also possible to include a moderating one. A proposed theoretical model of asymmetrical effects of organizational learning and its antecedents is discussed in this article.

The Relationship Among School Safety, School Liking, and Students' Self-Esteem: Based on a Multilevel Mediation Model.

Science.gov (United States)

Zhang, Xinghui; Xuan, Xin; Chen, Fumei; Zhang, Cai; Luo, Yuhan; Wang, Yun

2016-03-01

Perceptions of school safety have an important effect on students' development. Based on the model of "context-process-outcomes," we examined school safety as a context variable to explore how school safety at the school level affected students' self-esteem. We used hierarchical linear modeling to examine the link between school safety at the school level and students' self-esteem, including school liking as a mediator. The data were from the National Children's Study of China (NCSC), in which 6618 fourth- to fifth-grade students in 79 schools were recruited from 100 counties in 31 provinces in China. Multilevel mediation analyses showed that the positive relationship between school safety at the school level and self-esteem was partially mediated by school liking, controlling for demographics at both student and school levels. Furthermore, a sex difference existed in the multilevel mediation model. For boys, school liking fully mediated the relationship between school safety at the school level and self-esteem. However, school liking partially mediated the relationship between school safety at the school level and self-esteem among girls. School safety should receive increasing attention from policymakers because of its impact on students' self-esteem. © 2016, American School Health Association.

Causal Relationship Model of the Information and Communication Technology Skill Affect the Technology Acceptance Process in the 21ST Century for Undergraduate Students

Directory of Open Access Journals (Sweden)

Thanyatorn Amornkitpinyo

2015-02-01

Full Text Available The objective of this study is to design a framework for a causal relationship model of the Information and Communication Technology skills that affect the Technology Acceptance Process (TAP for undergraduate students in the 21ST Century. This research uses correlational analysis. A consideration of the research methodology is divided into two sections. The first section involves a synthesis concept framework for process acceptance of the causal relationship model of the Information and Communication Technology skills that affect the Technology Acceptance Process for undergraduate students in the 21ST Century. The second section proposes the design concept framework of the model. The research findings are as follows: 1 The exogenous latent variables included in the causal relationship model of the Information and Communication Technology skills that affect the Technology Acceptance Process for undergraduate students in the 21ST Century are basic ICT skills and self-efficacy. 2 The mediating latent variables of the causal relationship model of the Information and Communication Technology skills that affect the Technology Acceptance Process for undergraduate students in the 21ST Century are from the TAM Model, these includes three components: 1 perceived usefulness, 2 perceived ease of use and 3 attitudes. 3 The outcome latent variable of the causal relationship model of the Information and Communication Technology skills that affect the Technology Acceptance Process for undergraduate students in the 21ST Century is behavioural intention.

Developing an Innovative Customer Relationship Management Model for Better Health Examination Service

Directory of Open Access Journals (Sweden)

Lyu JrJung

2014-11-01

Full Text Available People emphasize on their own health and wish to know more about their conditions. Chronic diseases now take up to 50 percent of top 10 causes of death. As a result, the health-care industry has emerged and kept thriving. This work adopts an innovative customer-oriented business model since most clients are proactive and spontaneous in taking the “distinguished” health examination programs. We adopt the soft system dynamics methodology (SSDM to develop and to evaluate the steps of introducing customer relationship management model into a case health examination organization. Quantitative results are also presented for a case physical examination center and to assess the improved efficiency. The case study shows that the procedures developed here could provide a better service.

Leveraging a Relationship with Biology to Expand a Relationship with Physics

Science.gov (United States)

Sawtelle, Vashti; Turpen, Chandra

2016-01-01

This work examines how experiences in one disciplinary domain (biology) can impact the relationship a student builds with another domain (physics). We present a model for disciplinary relationships using the constructs of identity, affect, and epistemology. With these constructs we examine an ethnographic case study of a student who experienced a…

The Entropy Solutions for the Lighthill-Whitham-Richards Traffic Flow Model with a Discontinuous Flow-Density Relationship

National Research Council Canada - National Science Library

Lu, Yadong; Wong, S. C; Zhang, Mengping; Shu, Chi-Wang

2007-01-01

...) traffic flow model with a flow-density relationship which is piecewise quadratic, concave, but not continuous at the junction points where two quadratic polynomials meet, and with piecewise linear...

Some insights for a relationship marketing model integrating SERVQUAL and customer loyalty in dental clinics

OpenAIRE

Vargas Perez, Ana Maria; Grijalvo Martin, Maria Mercedes; Mercado Idoeta, Carmelo

2012-01-01

The demand of new services, the emergence of new business models, insufficient innovation, underestimation of customer loyalty and reluctance to adopt new management are evidence of the deficiencies and the lack of research about the relations between patients and dental clinics. In this article we propose the structure of a model of Relationship Marketing (RM) in the dental clinic that integrates information from SERVQUAL, Customer Loyalty (CL) and activities of RM and combines the vision of...

Model test on the relationship feed energy and protein ratio to the production and quality of milk protein

Science.gov (United States)

Hartanto, R.; Jantra, M. A. C.; Santosa, S. A. B.; Purnomoadi, A.

2018-01-01

The purpose of this research was to find an appropriate relationship model between the feed energy and protein ratio with the amount of production and quality of milk proteins. This research was conducted at Getasan Sub-district, Semarang Regency, Central Java Province, Indonesia using 40 samples (Holstein Friesian cattle, lactation period II-III and lactation month 3-4). Data were analyzed using linear and quadratic regressions, to predict the production and quality of milk protein from feed energy and protein ratio that describe the diet. The significance of model was tested using analysis of variance. Coefficient of determination (R2), residual variance (RV) and root mean square prediction error (RMSPE) were reported for the developed equations as an indicator of the goodness of model fit. The results showed no relationship in milk protein (kg), milk casein (%), milk casein (kg) and milk urea N (mg/dl) as function of CP/TDN. The significant relationship was observed in milk production (L or kg) and milk protein (%) as function of CP/TDN, both in linear and quadratic models. In addition, a quadratic change in milk production (L) (P = 0.003), milk production (kg) (P = 0.003) and milk protein concentration (%) (P = 0.026) were observed with increase of CP/TDN. It can be concluded that quadratic equation was the good fitting model for this research, because quadratic equation has larger R2, smaller RV and smaller RMSPE than those of linear equation.

Diprotonation process of meso-tetraphenylporphyrin derivatives designed for Photodynamic Therapy of cancers: From Multivariate Curve Resolution to predictive QSPR modeling

Energy Technology Data Exchange (ETDEWEB)

Chauvin, Benoit, E-mail: benoit.chauvin@u-psud.fr [Univ. Paris-Sud, EA 4041, IFR 141, Faculte de Pharmacie, F-92296 Chatenay-Malabry (France); Institut Curie, UMR 176 CNRS, Centre Universitaire, Univ Paris-Sud, F-91405 Orsay (France); Kasselouri, Athena; Chaminade, Pierre; Quiameso, Rita [Univ. Paris-Sud, EA 4041, IFR 141, Faculte de Pharmacie, F-92296 Chatenay-Malabry (France); Nicolis, Ioannis [Laboratoire de Biomathematiques et Informatique, Departement de Sante publique et biostatistiques et EA 4466, Faculte de Pharmacie, Universite Paris Descartes, 4, avenue de l' Observatoire, 75270 Paris cedex 06 (France); Maillard, Philippe [Institut Curie, UMR 176 CNRS, Centre Universitaire, Univ Paris-Sud, F-91405 Orsay (France); Prognon, Patrice [Univ. Paris-Sud, EA 4041, IFR 141, Faculte de Pharmacie, F-92296 Chatenay-Malabry (France)

2011-10-31

Highlights: {yields} Diprotonation of 17 meso-tetraphenylporphyrin derivatives. {yields} MCR-ALS resolution of multi-component mixtures. {yields} Determination of stepwise protonation constants. {yields} Prediction of protonation constants from ET-State indices. - Abstract: Tetrapyrrole rings possess four nitrogen atoms, two of which act as Broendsted bases in acidic media. The two protonation steps occur on a close pH range, particularly in the case of meso-tetraphenylporphyrin (TPP) derivatives. If the cause of this phenomenon is well known - a protonation-induced distortion of the porphyrin ring - data on stepwise protonation constants and on electronic absorption spectra of monoprotonated TPPs are sparse. A multivariate approach has been systematically applied to a series of glycoconjugated and hydroxylated TPPs, potential anticancer drugs usable in Photodynamic Therapy. The dual purpose was determination of protonation constants and linking substitution with basicity. Hard-modeling version of MCR-ALS (Multivariate Curve Resolution Alternating Least Squares) has given access to spectra and distribution profile of pure components. Spectra of monoprotonated species (H{sub 3}TPP{sup +}) in solution resemble those of diprotonated species (H{sub 4}TPP{sup 2+}), mainly differing by a slight blue-shift of bands. Overlap of H{sub 3}TPP{sup +} and H{sub 4}TPP{sup 2+} spectra reinforces the difficulty to evidence an intermediate form only present in low relative abundance. Depending on macrocycle substitution, pK values ranged from 3.5 {+-} 0.1 to 5.1 {+-} 0.1 for the first protonation and from 3.2 {+-} 0.2 to 4.9 {+-} 0.1 for the second one. Inner nitrogens' basicity is affected by position, number and nature of peripheral substituents depending on their electrodonating character. pK values have been used to establish a predictive Multiple Linear Regression (MLR) model, relying on atom-type electrotopological indices. This model accurately describes our results and

Assessment of source-receptor relationships of aerosols: An integrated forward and backward modeling approach

Science.gov (United States)

Kulkarni, Sarika

This dissertation presents a scientific framework that facilitates enhanced understanding of aerosol source -- receptor (S/R) relationships and their impact on the local, regional and global air quality by employing a complementary suite of modeling methods. The receptor -- oriented Positive Matrix Factorization (PMF) technique is combined with Potential Source Contribution Function (PSCF), a trajectory ensemble model, to characterize sources influencing the aerosols measured at Gosan, Korea during spring 2001. It is found that the episodic dust events originating from desert regions in East Asia (EA) that mix with pollution along the transit path, have a significant and pervasive impact on the air quality of Gosan. The intercontinental and hemispheric transport of aerosols is analyzed by a series of emission perturbation simulations with the Sulfur Transport and dEposition Model (STEM), a regional scale Chemical Transport Model (CTM), evaluated with observations from the 2008 NASA ARCTAS field campaign. This modeling study shows that pollution transport from regions outside North America (NA) contributed ˜ 30 and 20% to NA sulfate and BC surface concentration. This study also identifies aerosols transported from Europe, NA and EA regions as significant contributors to springtime Arctic sulfate and BC. Trajectory ensemble models are combined with source region tagged tracer model output to identify the source regions and possible instances of quasi-lagrangian sampled air masses during the 2006 NASA INTEX-B field campaign. The impact of specific emission sectors from Asia during the INTEX-B period is studied with the STEM model, identifying residential sector as potential target for emission reduction to combat global warming. The output from the STEM model constrained with satellite derived aerosol optical depth and ground based measurements of single scattering albedo via an optimal interpolation assimilation scheme is combined with the PMF technique to

Minority stress and relationship functioning among young male same-sex couples: An examination of actor-partner interdependence models.

Science.gov (United States)

Feinstein, Brian A; McConnell, Elizabeth; Dyar, Christina; Mustanski, Brian; Newcomb, Michael E

2018-05-01

In different-sex couples, individual and partner stress can both have a negative impact on relationship functioning (actor and partner effects). Gay and bisexual men experience unique stress (sexual minority stress), but few studies have examined the effects of this stress on relationship functioning among young male couples. The current study examined (a) actor and partner effects of general and minority stress (internalized stigma, microaggressions, victimization, and outness) on relationship functioning (relationship quality and negative relationship interactions), (b) interactions between individual and partner stress as predictors of relationship functioning, and (c) dyadic coping and relationship length as moderators of actor and partner effects. Actor-partner interdependence models were tested using data from 153 young male couples. There was strong support for actor effects. Higher general stress and internalized stigma were associated with lower relationship quality, but only for those in longer relationships. Additionally, higher general stress, internalized stigma, and microaggressions, and lower outness, were associated with more negative relationship interactions. There was limited support for partner effects. Having a partner with higher internalized stigma was associated with more negative relationship interactions, but none of the other partner effects were significant. There was no support for individual and partner stress interacting to predict relationship functioning or for dyadic coping as a stress buffer. Findings highlight the influence of one's own experiences of general and minority stress on relationship functioning, but raise questions about how partner stress influences relationship functioning among young male couples. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Stage-discharge relationship in tidal channels

Science.gov (United States)

Kearney, W. S.; Mariotti, G.; Deegan, L.; Fagherazzi, S.

2016-12-01

Long-term records of the flow of water through tidal channels are essential to constrain the budgets of sediments and biogeochemical compounds in salt marshes. Statistical models which relate discharge to water level allow the estimation of such records from more easily obtained records of water stage in the channel. While there is clearly structure in the stage-discharge relationship, nonlinearity and nonstationarity of the relationship complicates the construction of statistical stage-discharge models with adequate performance for discharge estimation and uncertainty quantification. Here we compare four different types of stage-discharge models, each of which is designed to capture different characteristics of the stage-discharge relationship. We estimate and validate each of these models on a two-month long time series of stage and discharge obtained with an Acoustic Doppler Current Profiler in a salt marsh channel. We find that the best performance is obtained by models which account for the nonlinear and time-varying nature of the stage-discharge relationship. Good performance can also be obtained from a simplified version of these models which approximates the fully nonlinear and time-varying models with a piecewise linear formulation.

A structural equation model of patient-healthcare provider relationships and HIV-infected patient outcomes in Chinese populations.

Science.gov (United States)

Chen, Wei-Ti; Shiu, Chengshi; Yang, Joyce P; Chuang, Peing; Zhang, Lin; Bao, Meijuan; Lu, Hongzhou

2018-03-01

Obtaining maximum antiretroviral therapy (ART) adherence is critical for maintaining a high CD4 count and strong immune function in PLWHA. Key factors for achieving optimum adherence include good medication self-efficacy, decreased medication-taking difficulties, and positive patient-healthcare provider (HCP) relationships. Limited studies have analyzed the correlation of these factors and ART adherence in Chinese population. In this paper, structural equation modeling was performed to assess the proposed model of relations between patient-HCP relationships and adherence. Audio Computer-Assisted Self-Interview (ACASI) software was used to collect data on ART adherence and patient variables among 227 PLWHA in Shanghai and Taipei. Participants completed a one-time 60-minute ACASI survey that consisted of standardized measures to assess demographics, recent CD4 counts, self-efficacy, patient-HCP relationship, adherence, and medication-taking difficulties. The data shown the relationship between patient-HCP relationships and adherence was significantly consistent with mediation by medication self-efficacy. However, patient-HCP interaction did not directly influence medication-taking difficulties, and medication-taking difficulties did not significantly affect CD4 counts. Furthermore, patient-HCP interactions did not directly impact CD4 counts; rather, the relation was consistent with mediation (by either better medication self-efficacy or better adherence) or by improved adherence alone. Future interventions should be designed to enhance self-management and provide better patient-HCP communication. This improved communication will enhance medication self-efficacy and decrease medication-taking difficulties. This in turn will improve medication adherence and immune function among PLWHA.

Managers as role models for health: Moderators of the relationship of transformational leadership with employee exhaustion and cynicism.

Science.gov (United States)

Kranabetter, Caroline; Niessen, Cornelia

2017-10-01

Drawing on social learning literature, this study examined managers' health awareness and health behavior (health-related self-regulation) as a moderator of the relationships between transformational leadership and employee exhaustion and cynicism. In 2 organizations, employees (n = 247; n = 206) rated their own exhaustion and cynicism, and their managers' transformational leadership. Managers (n = 57; n = 30) assessed their own health-related self-regulation. Multilevel modeling showed that, as expected, managers' health awareness moderated the relationship between transformational leadership and employee exhaustion and cynicism. Employees experienced less exhaustion and cynicism when transformational leaders were aware of their own health. Managers' health behavior moderated the relationship between transformational leadership and employee exhaustion in 1 organization, but not in the other. With respect to health behavior, we found no significant results for employee cynicism. In sum, the results indicate that when managers are role models for health, employees will benefit more from the transformational leadership style. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Managing inter-organizational relationships

DEFF Research Database (Denmark)

Hald, Kim Sundtoft

2005-01-01

-term-orientation in relationships and relationship value we develop a conceptualmodel highlighting the components of attraction in business to business relationships.First we demonstrate how the force of attraction can be understood as partners expectedrelationship value and how expected relationship value in turn is strengthened...... maximizing own influence and control over them.Information gathering and model building are tactics normally used in this effort.However, in this article we discuss a third tactic, the tactic of attraction in dyadicrelationships. Founded on the theory of social exchange and based on literature reviewson long...... orweakened by partner- comfortability and dependability. Then we show how partnersperceived attraction towards an industrial company can be managed using a combinationof structural- and behavioral adjustments.Key words: Inter-organizational relationships; Relationship Management; Relationship-value...

Long-term relationships of major macro-variables in a resource-related economic model of Australia

International Nuclear Information System (INIS)

Harvie, Charles; Hoa, T. van

1993-01-01

The paper reports the results of a simple cointegration analysis applied to bivariate causality models using data on resource output, oil prices, terms of trade, current account and output growth to investigate the long-term relationships among these major macroeconomic aggregates in a resource-related economic model of Australia. For the period 1960-1990, the empirical evidence indicates that these five macro-variables, as formulated in our model, are not random walks. In addition, resource production and oil prices are significantly cointegrated, and they are also significantly cointegrated with the current account, terms of trade and economic growth. These findings provide support to the long-term adjustments foundation of our resource-related model. (author)

Sanctification and spiritual disclosure in parent-child relationships: implications for family relationship quality.

Science.gov (United States)

Brelsford, Gina M

2013-08-01

Social scientific research on family life, religion, and spirituality tends to focus on global religiousness and spirituality with few studies seeking to understand interpersonal religious and spiritual contributors, namely sanctification and spiritual disclosure, from multiple family members' perspectives. This study explored 91 mother-college student and 64 father-college student dyads who rated their use of spiritual disclosure and theistic and nontheistic sanctification of the parent-child dyad in relation to parent-child relationship quality (e.g., parent-child relationship satisfaction and open communication). Results indicate significant positive links between higher levels of spiritual disclosure and greater theistic and nontheistic sanctification, for mothers, fathers, and their children. However, only greater nontheistic sanctification and higher levels spiritual disclosure were significantly related to increased parent-child relationship quality. Through use of Actor-Partner Interdependence Models (APIMs) results indicated unique contributions of spiritual disclosure to parent-child relationship quality above nontheistic sanctification for open communication in the family. However, full models, which included nontheistic sanctification and spiritual disclosure, predict college students' relationship satisfaction with their mothers and fathers. Implications for interpersonal religiousness and spirituality as contributors to familial relationship quality in research and practice are discussed. © 2013 American Psychological Association

Governing IT outsourcing relationships

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Kuhlmann, Daniel

2012-01-01

Hauptbeschreibung The dynamics of the relationship between service recipient and service provider in IS outsourcing relationships recently gained increased attention as relationships are believed to have a considerable influence on IS outsourcing success. This study adds to this growing field of interest by developing an IS outsourcing relationship framework in the form of a process model. Three rather disjointed areas of research, namely contractual governance, relational norms, and control, have been set in a common context by interrelating them as the three main governance modes

Personal Wilderness Relationships: Building on a Transactional Approach

Science.gov (United States)

Dvorak, Robert G.; Borrie, William T.; Watson, Alan E.

2013-12-01

Wilderness managers are charged with the challenging goal of balancing resource protection and experience quality across a broad, value-laden landscape. While research has provided insight into visitors' motivations and their meanings for wilderness, a struggle exists to implement experiential concepts within current management frameworks. This research posits the human experience of wilderness to be an evolving, enduring relationship, and that research needs can be addressed by conceptualizing and investigating an individuals' personal wilderness relationship. The purpose of this study was to explore wilderness relationships of visitors to the Boundary Waters Canoe Area Wilderness. A predictive model was proposed to investigate the internal dimensions of a visitor's wilderness relationship. A mail-back questionnaire was distributed during the summer of 2007, resulting in a sample of 564 respondents. Data were analyzed using confirmatory factor analysis and structural equation modeling. Results from testing several relationship models provided support for a multidimensional structure consisting of five factors with a single overarching relationship factor. The preferred relationship model indicated the importance of identities and attachment in place relationships. Trust and commitment toward management were also important considerations. This research provided the preliminary evidence for a multidimensional wilderness relationship model and complements a perspective of wilderness experiences as wilderness. Findings may help to reframe decision-making and public-input processes that guide management actions to increased wilderness character protection and facilitate quality wilderness experiences.

Reliability of the Load-Velocity Relationship Obtained Through Linear and Polynomial Regression Models to Predict the One-Repetition Maximum Load.

Science.gov (United States)

Pestaña-Melero, Francisco Luis; Haff, G Gregory; Rojas, Francisco Javier; Pérez-Castilla, Alejandro; García-Ramos, Amador

2017-12-18

This study aimed to compare the between-session reliability of the load-velocity relationship between (1) linear vs. polynomial regression models, (2) concentric-only vs. eccentric-concentric bench press variants, as well as (3) the within-participants vs. the between-participants variability of the velocity attained at each percentage of the one-repetition maximum (%1RM). The load-velocity relationship of 30 men (age: 21.2±3.8 y; height: 1.78±0.07 m, body mass: 72.3±7.3 kg; bench press 1RM: 78.8±13.2 kg) were evaluated by means of linear and polynomial regression models in the concentric-only and eccentric-concentric bench press variants in a Smith Machine. Two sessions were performed with each bench press variant. The main findings were: (1) first-order-polynomials (CV: 4.39%-4.70%) provided the load-velocity relationship with higher reliability than second-order-polynomials (CV: 4.68%-5.04%); (2) the reliability of the load-velocity relationship did not differ between the concentric-only and eccentric-concentric bench press variants; (3) the within-participants variability of the velocity attained at each %1RM was markedly lower than the between-participants variability. Taken together, these results highlight that, regardless of the bench press variant considered, the individual determination of the load-velocity relationship by a linear regression model could be recommended to monitor and prescribe the relative load in the Smith machine bench press exercise.

Combined use of rapid-prototyping model and surgical guide in correction of mandibular asymmetry malformation patients with normal occlusal relationship.

Science.gov (United States)

Xu, Haisong; Zhang, Ce; Shim, Yoong Hoon; Li, Hongliang; Cao, Dejun

2015-03-01

The aim of this study is to discuss the application of rapid-prototyping model and surgical guide in the treatment of mandibular asymmetry malformation with normal occlusal relationship. Twenty-four mandibular asymmetry malformation patients with relatively normal occlusal relationship were included in this study. Surgical 3-dimensional rapid-prototyping mandibular models were made for all patients from the computed tomography (CT) DICOM data. The presurgical plan was designed on the model, and the surgical guiders for the osteotomy lines were manufactured. Genioplasty and/or mandibular osteotomy based on the presurgical plan were performed on these patients with the combined use of the rapid-prototyping model and surgical guides. All patients underwent postoperative CT scan and had at least 3-month follow-up. All patients were satisfied with the final results. According to the postoperative CT images and 3-month follow-up, all patients' mandibular asymmetry malformation was significantly improved, and the operation time was distinctly shortened relative to the conventional method. Rapid-prototyping model and surgical guide are viable auxiliary devices for the treatment of mandibular asymmetry malformation with relatively normal occlusal relationship. Combined use of them can make precise preoperative design, improve effects of operation, and shorten operating time.

Multivariate characterisation and quantitative structure-property relationship modelling of nitroaromatic compounds

Energy Technology Data Exchange (ETDEWEB)

Joensson, S. [Man-Technology-Environment Research Centre, Department of Natural Sciences, Orebro University, 701 82 Orebro (Sweden)], E-mail: sofie.jonsson@nat.oru.se; Eriksson, L.A. [Department of Natural Sciences and Orebro Life Science Center, Orebro University, 701 82 Orebro (Sweden); Bavel, B. van [Man-Technology-Environment Research Centre, Department of Natural Sciences, Orebro University, 701 82 Orebro (Sweden)

2008-07-28

A multivariate model to characterise nitroaromatics and related compounds based on molecular descriptors was calculated. Descriptors were collected from literature and through empirical, semi-empirical and density functional theory-based calculations. Principal components were used to describe the distribution of the compounds in a multidimensional space. Four components described 76% of the variation in the dataset. PC1 separated the compounds due to molecular weight, PC2 separated the different isomers, PC3 arranged the compounds according to different functional groups such as nitrobenzoic acids, nitrobenzenes, nitrotoluenes and nitroesters and PC4 differentiated the compounds containing chlorine from other compounds. Quantitative structure-property relationship models were calculated using partial least squares (PLS) projection to latent structures to predict gas chromatographic (GC) retention times and the distribution between the water phase and air using solid-phase microextraction (SPME). GC retention time was found to be dependent on the presence of polar amine groups, electronic descriptors including highest occupied molecular orbital, dipole moments and the melting point. The model of GC retention time was good, but the precision was not precise enough for practical use. An important environmental parameter was measured using SPME, the distribution between headspace (air) and the water phase. This parameter was mainly dependent on Henry's law constant, vapour pressure, log P, content of hydroxyl groups and atmospheric OH rate constant. The predictive capacity of the model substantially improved when recalculating a model using these five descriptors only.

Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.

Science.gov (United States)

Nandi, Sisir; Monesi, Alessandro; Drgan, Viktor; Merzel, Franci; Novič, Marjana

2013-10-30

In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.

The Relationship between Residential Electricity Consumption and Income: A Piecewise Linear Model with Panel Data

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Yanan Liu

2016-10-01

Full Text Available There are many uncertainties and risks in residential electricity consumption associated with economic development. Knowledge of the relationship between residential electricity consumption and its key determinant—income—is important to the sustainable development of the electric power industry. Using panel data from 30 provinces for the 1995–2012 period, this study investigates how residential electricity consumption changes as incomes increase in China. Previous studies typically used linear or quadratic double-logarithmic models imposing ex ante restrictions on the indistinct relationship between residential electricity consumption and income. Contrary to those models, we employed a reduced piecewise linear model that is self-adaptive and highly flexible and circumvents the problem of “prior restrictions”. Robust tests of different segment specifications and regression methods are performed to ensure the validity of the research. The results provide strong evidence that the income elasticity was approximately one, and it remained stable throughout the estimation period. The income threshold at which residential electricity consumption automatically remains stable or slows has not been reached. To ensure the sustainable development of the electric power industry, introducing higher energy efficiency standards for electrical appliances and improving income levels are vital. Government should also emphasize electricity conservation in the industrial sector rather than in residential sector.

Long-term Relationships

DEFF Research Database (Denmark)

Hémous, David; Olsen, Morten

2017-01-01

In the 1980s the Japanese “keiretsu” system of interconnected business groups was praised as a model to emulate, but since then Japan has often been criticized for being less innovative than the United States. In this paper we connect the two views and argue that tight business relationships can...... suppliers and start cooperation immediately with new suppliers. We first consider broad innovations: every period, one supplier has the opportunity to create a higher quality input that can be used by all producers. Since relationships are harder to break in the cooperative equilibrium the market size...... for potential innovators is smaller and the rate of innovation might be lower than in the noncooperative equilibrium. We contrast this with a setting with relationship-specific innovations that we show are encouraged by the establishment of relational contracts. We illustrate the predictions of the model using...

Gender role attitudes, relationship efficacy, and self-disclosure in intimate relationships.

Science.gov (United States)

Horne, Rebecca M; Johnson, Matthew D

2018-01-01

Drawing from the intimacy process model and data from 5,042 individuals who remained partnered across Waves 1 and 2 of the German Panel Analysis of Intimate Relationships and Family Dynamics (pairfam), this study examined the contributions of traditional gender role attitudes and relationship efficacy in predicting levels of self-disclosure within an intimate relationship. Independent samples t-tests demonstrated females scored higher than males on self-disclosure and relationship efficacy measures but lower on traditional gender role attitudes. An ordinary least squares regression analysis revealed relationship efficacy was a stronger predictor of self-disclosure compared to traditional gender role attitudes, which were not associated with self-disclosure. The findings suggest attitudes with an interpersonal motivational system may be especially important for setting the intimacy process into motion within an intimate union.

Evaluating the Relationship between Team Performance and Joint Attention with Longitudinal Multivariate Mixed Models

Science.gov (United States)

2016-09-23

Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147–177...Relationship between Team Performance and Joint Attention with Longitudinal Multivariate Mixed Models 5a. CONTRACT NUMBER FA8650-14-D-6501-0009 5b...Annual Meeting, 19-23 September 2016. 14. Previous research indicates that measures of joint attention provide unique insight into team cognition

The relationship between the key elements of Donabedian's conceptual model within the field of assistive technology

DEFF Research Database (Denmark)

Sund, Terje; Iwarsson, Susanne; Brandt, Åse

2015-01-01

Previous research has suggested that there is a relationship between the three key components of Donabedian's conceptual model for quality assessments: structure of care, process, and outcome of care. That is, structure predicted both process and outcome of care, and better processes predict better...

A model of buyer-supplier relationships in a transnational company: the role of the business network context

Directory of Open Access Journals (Sweden)

Matevž Rasković

2012-04-01

Full Text Available The paradigmatic shift in marketing from the beginning of the 1990’s has transformed marketing in its view of business exchange to increasingly start addressing the relational aspects of market exchanges. This is particularly true in transnational supply exchanges, where specialization and outsourcing have increased the importance of effective and efficient management of buyer-supplier relationships, and their corresponding networks in which they are embedded in. In this regard particularly, TNCs are seen “as a [key] method of organizing international exchange”. The purpose of this paper is to analyze selected elements of buyer-supplier relationships within a specific TNC business-to-business (B2B setting, vis-à-vis their impact on business performance and TNC competitiveness. This is done through the perspective of the TNC’s suppliers. The paper analyzes the impact of the functional aspect of the business network context on selected elements of buyer-supplier relationships, and their impact on business performance and the overall competitiveness. This is analyzed within a confirmatory testing of a reflective structural equation model. A unique feature of the model is its focus on the business network context - namely information obtained from the network and network spillover effects – as key network-embedded determinants of the “traditional” elements of buyer-supplier relationships (i.e. transaction-specific investments, trust, flexibility, and collaboration, where these elements have been so far mostly studied at the dyadic level in buyer-supplier relationships. The dataset includes a sample of 157 suppliers of the focal TNC world-wide (47.9 response rate on a web-based survey.

Modeling bioaccumulation in humans using poly-parameter linear free energy relationships (PPLFERS)

Energy Technology Data Exchange (ETDEWEB)

Undeman, Emma, E-mail: emma.undeman@itm.su.se; Czub, Gertje; McLachlan, Michael S.

2011-04-01

Chemical partition coefficients between environmental media and biological tissues are a key component of bioaccumulation models. The single-parameter linear free energy relationships (spLFERs) commonly used for predicting partitioning are often derived using apolar chemicals and may not accurately capture polar chemicals. In this study, a poly-parameter LFER (ppLFER) based model of organic chemical bioaccumulation in humans is presented. Chemical partitioning was described by an air-body partition coefficient that was a volume weighted average of ppLFER based partition coefficients for the major organs and tissues constituting the human body. This model was compared to a spLFER model treating the body as a mixture of lipid ({approx} octanol) and water. Although model agreement was good for hydrophobic chemicals (average difference 15% for log K{sub OW} > 4 and log K{sub OA} > 8), the ppLFER model predicted {approx} 90% lower body burdens for hydrophilic chemicals (log K{sub OW} < 0). This was mainly due to lower predictions of muscle and adipose tissue sorption capacity for these chemicals. A comparison of the predicted muscle and adipose tissue sorption capacities of hydrophilic chemicals with measurements indicated that the ppLFER and spLFER models' uncertainties were similar. Consequently, little benefit from the implementation of ppLFERs in this model was identified. - Research Highlights: {yields}Implementation of ppLFERs resulted in on average 90% lower predicted body burdens. {yields}Uncertainties in spLFER and ppLFER predictions were similar. {yields}The benefit from implementation of ppLFERs in bioaccumulation models was limited.

Testing the Bivalent Fear of Evaluation Model of Social Anxiety: The Relationship between Fear of Positive Evaluation, Social Anxiety, and Perfectionism.

Science.gov (United States)

Yap, Keong; Gibbs, Amy L; Francis, Andrew J P; Schuster, Sharynn E

2016-01-01

The Bivalent Fear of Evaluation (BFOE) model of social anxiety proposes that fear of negative evaluation (FNE) and fear of positive evaluation (FPE) play distinct roles in social anxiety. Research is however lacking in terms of how FPE is related to perfectionism and how these constructs interact to predict social anxiety. Participants were 382 individuals from the general community and included an oversampling of individuals with social anxiety. Measures of FPE, FNE, perfectionism, and social anxiety were administered. Results were mostly consistent with the predictions made by the BFOE model and showed that accounting for confounding variables, FPE correlated negatively with high standards but positively with maladaptive perfectionism. FNE was also positively correlated with maladaptive perfectionism, but there was no significant relationship between FNE and high standards. Also consistent with BFOE model, both FNE and FPE significantly moderated the relationship between maladaptive perfectionism and social anxiety with the relationship strengthened at high levels of FPE and FNE. These findings provide additional support for the BFOE model and implications are discussed.

A High-Dimensional, Multivariate Copula Approach to Modeling Multivariate Agricultural Price Relationships and Tail Dependencies

Science.gov (United States)

Xuan Chi; Barry Goodwin

2012-01-01

Spatial and temporal relationships among agricultural prices have been an important topic of applied research for many years. Such research is used to investigate the performance of markets and to examine linkages up and down the marketing chain. This research has empirically evaluated price linkages by using correlation and regression models and, later, linear and...

Does Your Terrestrial Model Capture Key Arctic-Boreal Relationships?: Functional Benchmarks in the ABoVE Model Benchmarking System

Science.gov (United States)

Stofferahn, E.; Fisher, J. B.; Hayes, D. J.; Schwalm, C. R.; Huntzinger, D. N.; Hantson, W.

2017-12-01

The Arctic-Boreal Region (ABR) is a major source of uncertainties for terrestrial biosphere model (TBM) simulations. These uncertainties are precipitated by a lack of observational data from the region, affecting the parameterizations of cold environment processes in the models. Addressing these uncertainties requires a coordinated effort of data collection and integration of the following key indicators of the ABR ecosystem: disturbance, vegetation / ecosystem structure and function, carbon pools and biogeochemistry, permafrost, and hydrology. We are continuing to develop the model-data integration framework for NASA's Arctic Boreal Vulnerability Experiment (ABoVE), wherein data collection is driven by matching observations and model outputs to the ABoVE indicators via the ABoVE Grid and Projection. The data are used as reference datasets for a benchmarking system which evaluates TBM performance with respect to ABR processes. The benchmarking system utilizes two types of performance metrics to identify model strengths and weaknesses: standard metrics, based on the International Land Model Benchmarking (ILaMB) system, which relate a single observed variable to a single model output variable, and functional benchmarks, wherein the relationship of one variable to one or more variables (e.g. the dependence of vegetation structure on snow cover, the dependence of active layer thickness (ALT) on air temperature and snow cover) is ascertained in both observations and model outputs. This in turn provides guidance to model development teams for reducing uncertainties in TBM simulations of the ABR.

Geometrical Modeling of Woven Fabrics Weavability-Limit New Relationships

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Dalal Mohamed

2017-03-01

Full Text Available The weavability limit and tightness for 2D and 3D woven fabrics is an important factor and depends on many geometric parameters. Based on a comprehensive review of the literature on textile fabric construction and property, and related research on fabric geometry, a study of the weavability limit and tightness relationships of 2D and 3D woven fabrics was undertaken. Experiments were conducted on a representative number of polyester and cotton woven fabrics which have been woven in our workshop, using three machines endowed with different insertion systems (rapier, projectiles and air jet. Afterwards, these woven fabrics have been analyzed in the laboratory to determine their physical and mechanical characteristics using air permeability-meter and KES-F KAWABATA Evaluation System for Fabrics. In this study, the current Booten’s weavability limit and tightness relationships based on Ashenhurst’s, Peirce’s, Love’s, Russell’s, Galuszynskl’s theory and maximum-weavability is reviewed and modified as new relationships to expand their use to general cases (2D and 3D woven fabrics, all fiber materiel, all yarns etc…. The theoretical relationships were examined and found to agree with experimental results. It was concluded that the weavability limit and tightness relationships are useful tools for weavers in predicting whether a proposed fabric construction was weavable and also in predicting and explaining their physical and mechanical properties.

Neurological soft signs and their relationships to neurocognitive functions: a re-visit with the structural equation modeling design.

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Raymond C K Chan

Full Text Available BACKGROUND: Neurological soft signs and neurocognitive impairments have long been considered important features of schizophrenia. Previous correlational studies have suggested that there is a significant relationship between neurological soft signs and neurocognitive functions. The purpose of the current study was to examine the underlying relationships between these two distinct constructs with structural equation modeling (SEM. METHODS: 118 patients with schizophrenia and 160 healthy controls were recruited for the current study. The abridged version of the Cambridge Neurological Inventory (CNI and a set of neurocognitive function tests were administered to all participants. SEM was then conducted independently in these two samples to examine the relationships between neurological soft signs and neurocognitive functions. RESULTS: Both the measurement and structural models showed that the models fit well to the data in both patients and healthy controls. The structural equations also showed that there were modest to moderate associations among neurological soft signs, executive attention, verbal memory, and visual memory, while the healthy controls showed more limited associations. CONCLUSIONS: The current findings indicate that motor coordination, sensory integration, and disinhibition contribute to the latent construct of neurological soft signs, whereas the subset of neurocognitive function tests contribute to the latent constructs of executive attention, verbal memory, and visual memory in the present sample. Greater evidence of neurological soft signs is associated with more severe impairment of executive attention and memory functions. Clinical and theoretical implications of the model findings are discussed.

Using the Expectancy Value Model of Motivation to Understand the Relationship between Student Attitudes and Achievement in Statistics

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Hood, Michelle; Creed, Peter A.; Neumann, David L.

2012-01-01

We tested a model of the relationship between attitudes toward statistics and achievement based on Eccles' Expectancy Value Model (1983). Participants (n = 149; 83% female) were second-year Australian university students in a psychology statistics course (mean age = 23.36 years, SD = 7.94 years). We obtained demographic details, past performance,…

Relationship between work-family balance and job satisfaction among employees in China: A moderated mediation model.

Science.gov (United States)

Yu, Yue; Wang, Yuchen; Zhang, Jianxin

2017-09-01

Previous studies have revealed the association between work-family balance and job satisfaction. The present research further explored the underlying mechanism of this association and aimed to provide a moderated mediation model to explain if personality traits moderate the relationship between work-family balance and job satisfaction through work engagement. A cross-sectional study was conducted in which 263 employees from a petrochemical enterprise in China completed self-report questionnaires including the Work-Family Balance Scale, the Utrecht Work Engagement Scale, the Big Five Inventory-10, and the Job Satisfaction Scale. Hierarchical regression analysis and structural equation modeling showed that work engagement partially mediated the relationship between work-family balance and job satisfaction, and the indirect effect was further moderated only by extraversion. Therefore, an integrative moderated mediation model was proposed wherein work-family balance boosts job satisfaction by first enhancing employees' work engagement, while the indirect effect was in turn moderated by extraversion. The results suggest that interventions for improving job satisfaction may be enhanced by targeting work engagement, especially for employees with higher extraversion. © 2017 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

The Evolution Process on Information Technology Outsourcing Relationship

Directory of Open Access Journals (Sweden)

Duan Weihua

2017-01-01

Full Text Available Information technology outsourcing relationship is one of the key issues to IT outsourcing success. To explore how to manage and promote IT outsourcing relationship, it is necessary to understand its evolution process. Firstly, the types of IT outsourcing based on relationship quality and IT outsourcing project level will be analyzed; Secondly, two evolution process models of IT outsourcing relationship are proposed based on relationship quality and IT outsourcing project level, and the IT outsourcing relationship evolution process is indicated; Finally, an IT outsourcing relationship evolution process model is developed, and the development process of IT outsourcing relationship from low to high under the internal and external power is explained.

Applying the Nominal Response Model within a Longitudinal Framework to Construct the Positive Family Relationships Scale

Science.gov (United States)

Preston, Kathleen Suzanne Johnson; Parral, Skye N.; Gottfried, Allen W.; Oliver, Pamella H.; Gottfried, Adele Eskeles; Ibrahim, Sirena M.; Delany, Danielle

2015-01-01

A psychometric analysis was conducted using the nominal response model under the item response theory framework to construct the Positive Family Relationships scale. Using data from the Fullerton Longitudinal Study, this scale was constructed within a long-term longitudinal framework spanning middle childhood through adolescence. Items tapping…

A Model for Investigation of the Intensity of Trust Relationships' Strength among Users in Social Media

Directory of Open Access Journals (Sweden)

rojiar pir mohammadiani

2017-06-01

Full Text Available Although trust relations among users in social media are the evidence of social influence, but the level of this impact depends on strength of trust among users. Therefore, in this paper we study the effect of trust relationships’ strength among users through the development of matrix factorization method. Matrix factorization is a method to predict the rate that user assign to the products. For this purpose, based on similarity factors the strength of trust relationship is measured, then this feature as an effective parameter was added to matrix factorization. The proposed model is applied on Epinions data set. The weight of trust relationships’ strength parameter is determined through the proposed model. Based on the results, by adding the strength of trust relationship the error rate is reduced. Furthermore, if the strength of trust between users is larger than 0.8, the error reduction will be more significant. Improving the results through more accurate estimation shows that this effect is set correctly.

Let it go: Relationship autonomy predicts pro-relationship responses to partner transgressions.

Science.gov (United States)

Hadden, Benjamin W; Baker, Zachary G; Knee, C Raymond

2017-11-24

The purpose of the present research is to better understand how relationship autonomy-having more self-determined reasons for being committed to a relationship-contributes to pro-relationship responses to transgressions in romantic relationships (e.g., forgiveness and accommodation). Study 1 employed a cross-sectional design (N = 350) and Study 2 used a weekly diary (N = 121) to test associations between relationship autonomy and pro-relationship responses to transgressions. Studies 3 and 4 utilized dyadic designs (Study 3: N = 200 couples, 400 individuals; Study 4: N = 275 couples, 550 individuals) to determine how both partners' relationship autonomy is associated with pro-relationship responses. Results revealed that relationship autonomy is robustly associated with pro-relationship responses to transgressions, both as general tendencies and as responses to idiosyncratic transgressions. Results of actor-partner interdependence model (APIM) analyses in Studies 3 and 4 provide evidence that one's partner's relationship autonomy is important for promoting pro-relationship responses as well. Study 4 also found that people perceive that partners respond better to transgressions if their partner is high in relationship autonomy. This research provides consistent and compelling evidence that the degree of self-determination underlying commitment is important for understanding how people respond to transgressions in their relationships, beyond their current levels of commitment. © 2017 Wiley Periodicals, Inc.

Healing relationships and the existential philosophy of Martin Buber

Science.gov (United States)

Scott, John G; Scott, Rebecca G; Miller, William L; Stange, Kurt C; Crabtree, Benjamin F

2009-01-01

The dominant unspoken philosophical basis of medical care in the United States is a form of Cartesian reductionism that views the body as a machine and medical professionals as technicians whose job is to repair that machine. The purpose of this paper is to advocate for an alternative philosophy of medicine based on the concept of healing relationships between clinicians and patients. This is accomplished first by exploring the ethical and philosophical work of Pellegrino and Thomasma and then by connecting Martin Buber's philosophical work on the nature of relationships to an empirically derived model of the medical healing relationship. The Healing Relationship Model was developed by the authors through qualitative analysis of interviews of physicians and patients. Clinician-patient healing relationships are a special form of what Buber calls I-Thou relationships, characterized by dialog and mutuality, but a mutuality limited by the inherent asymmetry of the clinician-patient relationship. The Healing Relationship Model identifies three processes necessary for such relationships to develop and be sustained: Valuing, Appreciating Power and Abiding. We explore in detail how these processes, as well as other components of the model resonate with Buber's concepts of I-Thou and I-It relationships. The resulting combined conceptual model illuminates the wholeness underlying the dual roles of clinicians as healers and providers of technical biomedicine. On the basis of our analysis, we argue that health care should be focused on healing, with I-Thou relationships at its core. PMID:19678950

Healing relationships and the existential philosophy of Martin Buber

Directory of Open Access Journals (Sweden)

Stange Kurt C

2009-08-01

Full Text Available Abstract The dominant unspoken philosophical basis of medical care in the United States is a form of Cartesian reductionism that views the body as a machine and medical professionals as technicians whose job is to repair that machine. The purpose of this paper is to advocate for an alternative philosophy of medicine based on the concept of healing relationships between clinicians and patients. This is accomplished first by exploring the ethical and philosophical work of Pellegrino and Thomasma and then by connecting Martin Buber's philosophical work on the nature of relationships to an empirically derived model of the medical healing relationship. The Healing Relationship Model was developed by the authors through qualitative analysis of interviews of physicians and patients. Clinician-patient healing relationships are a special form of what Buber calls I-Thou relationships, characterized by dialog and mutuality, but a mutuality limited by the inherent asymmetry of the clinician-patient relationship. The Healing Relationship Model identifies three processes necessary for such relationships to develop and be sustained: Valuing, Appreciating Power and Abiding. We explore in detail how these processes, as well as other components of the model resonate with Buber's concepts of I-Thou and I-It relationships. The resulting combined conceptual model illuminates the wholeness underlying the dual roles of clinicians as healers and providers of technical biomedicine. On the basis of our analysis, we argue that health care should be focused on healing, with I-Thou relationships at its core.

Mentoring: An Evolving Relationship.

Science.gov (United States)

Block, Michelle; Florczak, Kristine L

2017-04-01

The column concerns itself with mentoring as an evolving relationship between mentor and mentee. The collegiate mentoring model, the transformational transcendence model, and the humanbecoming mentoring model are considered in light of a dialogue with mentors at a Midwest university and conclusions are drawn.

Mapping using the Tsyganenko long magnetospheric model and its relationship to Viking auroral images

International Nuclear Information System (INIS)

Elphinstone, R.D.; Hearn, D.; Murphree, J.S.; Cogger, L.L.

1991-01-01

The Tsyganenko long magnetospheric model (1987) has been used in conjunction with ultra-violet images taken by the Viking spacecraft to investigate the relationship of the auroral distribution to different magnetospheric regions. The model describes the large-scale structure of the magnetosphere reasonably well for dipole tilt angles near zero, but it appears to break down at higher tilt angles. Even so, a wide variety of auroral configurations can be accurately described by the model. It appears that the open-closed field line boundary is a poor indicator of auroral arc systems with the possible exception of high-latitude polar arcs. The auroral distribution typically called the oval maps to a region in the equatorial plane quite close to the Earth and can be approximately located by mapping the model current density maximum from the equatorial plane into the ionosphere. Although the model may break down along the flanks of the magnetotail, the large-scale auroral distribution generally reflects variations in the near-Earth region and can be modeled quite effectively

A three-model comparison of the relationship between quality, satisfaction and loyalty: an empirical study of the Chinese healthcare system

Directory of Open Access Journals (Sweden)

Lei Ping

2012-11-01

Full Text Available Abstract Background Previous research has addressed the relationship between customer satisfaction, perceived quality and customer loyalty intentions in consumer markets. In this study, we test and compare three theoretical models of the quality–satisfaction–loyalty relationship in the Chinese healthcare system. Methods This research focuses on hospital patients as participants in the process of healthcare procurement. Empirical data were obtained from six Chinese public hospitals in Shanghai. A total of 630 questionnaires were collected in two studies. Study 1 tested the research instruments, and Study 2 tested the three models. Confirmatory factor analysis was used to assess the scales’ construct validity by testing convergent and discriminant validity. A structural equation model (SEM specified the distinctions between each construct. A comparison of the three theoretical models was conducted via AMOS analysis. Results The results of the SEM demonstrate that quality and satisfaction are distinct concepts and that the first model (satisfaction mediates quality and loyalty is the most appropriate one in the context of the Chinese healthcare environment. Conclusions In this study, we test and compare three theoretical models of the quality–satisfaction–loyalty relationship in the Chinese healthcare system. Findings show that perceived quality improvement does not lead directly to customer loyalty. The strategy of using quality improvement to maintain patient loyalty depends on the level of patient satisfaction. This implies that the measurement of patient experiences should include topics of importance for patients’ satisfaction with health care services.

A three-model comparison of the relationship between quality, satisfaction and loyalty: an empirical study of the Chinese healthcare system.

Science.gov (United States)

Lei, Ping; Jolibert, Alain

2012-11-30

Previous research has addressed the relationship between customer satisfaction, perceived quality and customer loyalty intentions in consumer markets. In this study, we test and compare three theoretical models of the quality-satisfaction-loyalty relationship in the Chinese healthcare system. This research focuses on hospital patients as participants in the process of healthcare procurement. Empirical data were obtained from six Chinese public hospitals in Shanghai. A total of 630 questionnaires were collected in two studies. Study 1 tested the research instruments, and Study 2 tested the three models. Confirmatory factor analysis was used to assess the scales' construct validity by testing convergent and discriminant validity. A structural equation model (SEM) specified the distinctions between each construct. A comparison of the three theoretical models was conducted via AMOS analysis. The results of the SEM demonstrate that quality and satisfaction are distinct concepts and that the first model (satisfaction mediates quality and loyalty) is the most appropriate one in the context of the Chinese healthcare environment. In this study, we test and compare three theoretical models of the quality-satisfaction-loyalty relationship in the Chinese healthcare system. Findings show that perceived quality improvement does not lead directly to customer loyalty. The strategy of using quality improvement to maintain patient loyalty depends on the level of patient satisfaction. This implies that the measurement of patient experiences should include topics of importance for patients' satisfaction with health care services.

A three-model comparison of the relationship between quality, satisfaction and loyalty: an empirical study of the Chinese healthcare system

Science.gov (United States)

2012-01-01

Background Previous research has addressed the relationship between customer satisfaction, perceived quality and customer loyalty intentions in consumer markets. In this study, we test and compare three theoretical models of the quality–satisfaction–loyalty relationship in the Chinese healthcare system. Methods This research focuses on hospital patients as participants in the process of healthcare procurement. Empirical data were obtained from six Chinese public hospitals in Shanghai. A total of 630 questionnaires were collected in two studies. Study 1 tested the research instruments, and Study 2 tested the three models. Confirmatory factor analysis was used to assess the scales’ construct validity by testing convergent and discriminant validity. A structural equation model (SEM) specified the distinctions between each construct. A comparison of the three theoretical models was conducted via AMOS analysis. Results The results of the SEM demonstrate that quality and satisfaction are distinct concepts and that the first model (satisfaction mediates quality and loyalty) is the most appropriate one in the context of the Chinese healthcare environment. Conclusions In this study, we test and compare three theoretical models of the quality–satisfaction–loyalty relationship in the Chinese healthcare system. Findings show that perceived quality improvement does not lead directly to customer loyalty. The strategy of using quality improvement to maintain patient loyalty depends on the level of patient satisfaction. This implies that the measurement of patient experiences should include topics of importance for patients’ satisfaction with health care services. PMID:23198824

Atom-type-based AI topological descriptors: application in structure-boiling point correlations of oxo organic compounds.

Science.gov (United States)

Ren, Biye

2003-01-01

Structure-boiling point relationships are studied for a series of oxo organic compounds by means of multiple linear regression (MLR) analysis. Excellent MLR models based on the recently introduced Xu index and the atom-type-based AI indices are obtained for the two subsets containing respectively 77 ethers and 107 carbonyl compounds and a combined set of 184 oxo compounds. The best models are tested using the leave-one-out cross-validation and an external test set, respectively. The MLR model produces a correlation coefficient of r = 0.9977 and a standard error of s = 3.99 degrees C for the training set of 184 compounds, and r(cv) = 0.9974 and s(cv) = 4.16 degrees C for the cross-validation set, and r(pred) = 0.9949 and s(pred) = 4.38 degrees C for the prediction set of 21 compounds. For the two subsets containing respectively 77 ethers and 107 carbonyl compounds, the quality of the models is further improved. The standard errors are reduced to 3.30 and 3.02 degrees C, respectively. Furthermore, the results obtained from this study indicate that the boiling points of the studied oxo compound dominantly depend on molecular size and also depend on individual atom types, especially oxygen heteroatoms in molecules due to strong polar interactions between molecules. These excellent structure-boiling point models not only provide profound insights into the role of structural features in a molecule but also illustrate the usefulness of these indices in QSPR/QSAR modeling of complex compounds.

Through the Looking Glass: No Wonderland Yet! (The Reciprocal Relationship between Methodology and Models of Reality).

Science.gov (United States)

Unger, Rhoda Kesler

1983-01-01

Discusses the relationship between conceptual frameworks and methodology in psychology. Argues that models of reality influence research in terms of question selection, causal factors hypothesized, and interpretation of data. Considers the position and role of women as objects and agents of research using a sociology of knowledge perspective.…

An update on modeling dose-response relationships: Accounting for correlated data structure and heterogeneous error variance in linear and nonlinear mixed models.

Science.gov (United States)

Gonçalves, M A D; Bello, N M; Dritz, S S; Tokach, M D; DeRouchey, J M; Woodworth, J C; Goodband, R D

2016-05-01

Advanced methods for dose-response assessments are used to estimate the minimum concentrations of a nutrient that maximizes a given outcome of interest, thereby determining nutritional requirements for optimal performance. Contrary to standard modeling assumptions, experimental data often present a design structure that includes correlations between observations (i.e., blocking, nesting, etc.) as well as heterogeneity of error variances; either can mislead inference if disregarded. Our objective is to demonstrate practical implementation of linear and nonlinear mixed models for dose-response relationships accounting for correlated data structure and heterogeneous error variances. To illustrate, we modeled data from a randomized complete block design study to evaluate the standardized ileal digestible (SID) Trp:Lys ratio dose-response on G:F of nursery pigs. A base linear mixed model was fitted to explore the functional form of G:F relative to Trp:Lys ratios and assess model assumptions. Next, we fitted 3 competing dose-response mixed models to G:F, namely a quadratic polynomial (QP) model, a broken-line linear (BLL) ascending model, and a broken-line quadratic (BLQ) ascending model, all of which included heteroskedastic specifications, as dictated by the base model. The GLIMMIX procedure of SAS (version 9.4) was used to fit the base and QP models and the NLMIXED procedure was used to fit the BLL and BLQ models. We further illustrated the use of a grid search of initial parameter values to facilitate convergence and parameter estimation in nonlinear mixed models. Fit between competing dose-response models was compared using a maximum likelihood-based Bayesian information criterion (BIC). The QP, BLL, and BLQ models fitted on G:F of nursery pigs yielded BIC values of 353.7, 343.4, and 345.2, respectively, thus indicating a better fit of the BLL model. The BLL breakpoint estimate of the SID Trp:Lys ratio was 16.5% (95% confidence interval [16.1, 17.0]). Problems with

Proposal of a social alliance success model from a relationship marketing perspective: A meta-analytical study of the theoretical foundations

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María Jesús Barroso-Méndez

2015-07-01

Full Text Available Partnerships between businesses and non-governmental organizations (NGOs have become widely adopted mechanisms for collaboration in addressing complex social issues, the aim being to take advantage of the two types of organizational rationale to generate mutual value. Many such alliances have proved to be unsuccessful, however. To assist managers improve the likelihood of success of their collaborative relationships, the authors propose a success model of business-NGO partnering processes based on Relationship Marketing Theory. They also analyse the theoretical bases of the model's hypotheses through a meta-analytical study of the existing literature.

Quantitative structure–activity relationship model for amino acids as corrosion inhibitors based on the support vector machine and molecular design

International Nuclear Information System (INIS)

Zhao, Hongxia; Zhang, Xiuhui; Ji, Lin; Hu, Haixiang; Li, Qianshu

2014-01-01

Highlights: • Nonlinear quantitative structure–activity relationship (QSAR) model was built by the support vector machine. • Descriptors for QSAR model were selected by principal component analysis. • Binding energy was taken as one of the descriptors for QSAR model. • Acidic solution and protonation of the inhibitor were considered. - Abstract: The inhibition performance of nineteen amino acids was studied by theoretical methods. The affection of acidic solution and protonation of inhibitor were considered in molecular dynamics simulation and the results indicated that the protonated amino-group was not adsorbed on Fe (1 1 0) surface. Additionally, a nonlinear quantitative structure–activity relationship (QSAR) model was built by the support vector machine. The correlation coefficient was 0.97 and the root mean square error, the differences between predicted and experimental inhibition efficiencies (%), was 1.48. Furthermore, five new amino acids were theoretically designed and their inhibition efficiencies were predicted by the built QSAR model

Relationships matter

DEFF Research Database (Denmark)

Nyanja, Tabitha Alexandria Njeri; Tulinius, Charlotte

2017-01-01

-depth interviews and focus group discussions with 37 sexually active HIV-positive women aged between 20 and 44 years, attending three health facilities within Dar-es-Salaam. The theoretical framework was a patient centred model. Four barriers were identified: the influence of the women’s spousal relationships...... women experienced conflicts, violence, abandonment and rejection. The loss in negotiating power for the women was in relation to their intimate partners, but also in the patient–healthcare provider relationship. The role of the male partner as a barrier to contraceptive use cannot be understated...

On the relationship between justice judgments, outcomes and identity orientations among Iranian EFL learners: A structural equation model

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Seyyed Ayatollah Razmjoo

2015-06-01

Full Text Available One problem which can be observed in the field of EFL/ESL learning is that a number of English major BA and MA students are not highly committed to their major and decide not to continue their graduate studies. Sometimes even graduate students from English majors prefer to extend their education or work in an unrelated field. This might be attributed to the extent to which they perceive evaluation procedures and outcomes as fair. Considering this, the present study investigates first the relationships between justice judgments, outcomes and identity orientations. The study, then, uses structural equation modeling in order to examine whether identity orientation has any mediating effect on the relationship between justice judgment and outcomes. Participants were74 students in Department of Foreign Languages and Linguistics, Shiraz University selected based on convenience sampling. They filled out three questionnaires on distributive and procedural justice judgments, rule compliance and outcome satisfaction, and personal and social identity orientations. The collected data was then analyzed using descriptive statistics, correlation, and structural equation modeling. Based on the obtained findings, procedural justice had significant positive correlation with rule compliance and distributive justice was significantly correlated with outcome satisfaction. The generated structural equation model also indicated that justice judgments only directly affected outcomes and identity had no mediating effect on the causal relationship between the two.

Modeling Chemical Interaction Profiles: I. Spectral Data-Activity Relationship and Structure-Activity Relationship Models for Inhibitors and Non-inhibitors of Cytochrome P450 CYP3A4 and CYP2D6 Isozymes

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Richard D. Beger

2012-03-01

Full Text Available An interagency collaboration was established to model chemical interactions that may cause adverse health effects when an exposure to a mixture of chemicals occurs. Many of these chemicals—drugs, pesticides, and environmental pollutants—interact at the level of metabolic biotransformations mediated by cytochrome P450 (CYP enzymes. In the present work, spectral data-activity relationship (SDAR and structure-activity relationship (SAR approaches were used to develop machine-learning classifiers of inhibitors and non-inhibitors of the CYP3A4 and CYP2D6 isozymes. The models were built upon 602 reference pharmaceutical compounds whose interactions have been deduced from clinical data, and 100 additional chemicals that were used to evaluate model performance in an external validation (EV test. SDAR is an innovative modeling approach that relies on discriminant analysis applied to binned nuclear magnetic resonance (NMR spectral descriptors. In the present work, both 1D 13C and 1D 15N-NMR spectra were used together in a novel implementation of the SDAR technique. It was found that increasing the binning size of 1D 13C-NMR and 15N-NMR spectra caused an increase in the tenfold cross-validation (CV performance in terms of both the rate of correct classification and sensitivity. The results of SDAR modeling were verified using SAR. For SAR modeling, a decision forest approach involving from 6 to 17 Mold2 descriptors in a tree was used. Average rates of correct classification of SDAR and SAR models in a hundred CV tests were 60% and 61% for CYP3A4, and 62% and 70% for CYP2D6, respectively. The rates of correct classification of SDAR and SAR models in the EV test were 73% and 86% for CYP3A4, and 76% and 90% for CYP2D6, respectively. Thus, both SDAR and SAR methods demonstrated a comparable performance in modeling a large set of structurally diverse data. Based on unique NMR structural descriptors, the new SDAR modeling method complements the existing SAR

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

Science.gov (United States)

Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

2015-04-01

The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Intraocular pressure, blood pressure, and retinal blood flow autoregulation: a mathematical model to clarify their relationship and clinical relevance.

Science.gov (United States)

Guidoboni, Giovanna; Harris, Alon; Cassani, Simone; Arciero, Julia; Siesky, Brent; Amireskandari, Annahita; Tobe, Leslie; Egan, Patrick; Januleviciene, Ingrida; Park, Joshua

2014-05-29

This study investigates the relationship between intraocular pressure (IOP) and retinal hemodynamics and predicts how arterial blood pressure (BP) and blood flow autoregulation (AR) influence this relationship. A mathematical model is developed to simulate blood flow in the central retinal vessels and retinal microvasculature as current flowing through a network of resistances and capacitances. Variable resistances describe active and passive diameter changes due to AR and IOP. The model is validated by using clinically measured values of retinal blood flow and velocity. The model simulations for six theoretical patients with high, normal, and low BP (HBP-, NBP-, LBP-) and functional or absent AR (-wAR, -woAR) are compared with clinical data. The model predicts that NBPwAR and HBPwAR patients can regulate retinal blood flow (RBF) as IOP varies between 15 and 23 mm Hg and between 23 and 29 mm Hg, respectively, whereas LBPwAR patients do not adequately regulate blood flow if IOP is 15 mm Hg or higher. Hemodynamic alterations would be noticeable only if IOP changes occur outside of the regulating range, which, most importantly, depend on BP. The model predictions are consistent with clinical data for IOP reduction via surgery and medications and for cases of induced IOP elevation. The theoretical model results suggest that the ability of IOP to induce noticeable changes in retinal hemodynamics depends on the levels of BP and AR of the individual. These predictions might help to explain the inconsistencies found in the clinical literature concerning the relationship between IOP and retinal hemodynamics. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Bank Relationship and Firm Profitability

NARCIS (Netherlands)

Degryse, H.A.; Ongena, S.

2000-01-01

This paper examines how bank relationships affect firm performance. An empirical implication of recent theoretical models is that firms maintaining multiple bank relationships are less profitable than their single-bank peers. We investigate this empirical implication using a data set containing

Constitutive relationships of hot stamping boron steel B1500HS based on the modified Arrhenius and Johnson–Cook model

International Nuclear Information System (INIS)

Li, Huiping; He, Lianfang; Zhao, Guoqun; Zhang, Lei

2013-01-01

Constitutive relationship of boron steel is one of the most necessary mathematical models in the numerical simulation of hot stamping; it describes the relationship of the flow stress with strain, strain rate and temperature. In order to attain the constitutive relationship of boron steel B1500HS, four types of samples with microstructure of austenite, ferrite+pearlite, bainite or martensite are prepared by the Gleeble 1500D thermo-mechanical simulator. Isothermal uniaxial tension testings for these specimens are performed at 20–900 °C at the strain rates of 0.01 s –1 , 0.1 s –1 , 1.0 s –1 and 10 s –1 by Gleeble 1500D, and the true stress–strain curves at the relative conditions are gained. The experimental results show that, the flow stress of samples with relative microstructure rises with the decrease of the deformation temperature, and with the increase of the strain rate. The modified Arrhenius model is used to describe the hot deformation of samples with austenite microstructure, and the modified Johnson–Cook model is used to describe the deformation process of samples with ferrite+pearlite, bainite or martensite microstructure. The constitutive equations depending on the strain, strain rate and temperature are attained by the regression analysis for the experimental data of flow stress, strain, strain rate, temperature, etc. The comparison of the computational data and the experimental results shows that, the computational data using the constitutive relationships are well consistent with the experimental data

Better and Worse: A Dual-Process Model of the Relationship between Core Self-evaluation and Work-Family Conflict.

Science.gov (United States)

Yu, Kun

2016-01-01

Based on both resource allocation theory (Becker, 1965; Bergeron, 2007) and role theory (Katz and Kahn, 1978), the current study aims to uncover the relationship between core self-evaluation (CSE) and three dimensions of work interference with family (WIF). A dual-process model was proposed, in which both work stress and career resilience mediate the CSE-WIF relationship. The mediation model was tested with a sample of employees from various organizations ( N = 561). The results first showed that CSE was negatively related to time-based and strain-based WIF and positively related to behavior-based WIF via the mediation of work stress. Moreover, CSE was positively associated with behavior-based and strain-based WIF via the mediation of career resilience, suggesting that CSE may also have its "dark-side."

Better and worse: A dual-process model of the relationship between core self-evaluation and work-family conflict

Directory of Open Access Journals (Sweden)

Kun Yu

2016-10-01

Full Text Available Based on both resource allocation theory (Becker, 1965; Bergeron, 2007 and role theory (Katz & Kahn, 1978, the current study aims to uncover the relationship between core self-evaluation (CSE and three dimensions of work interference with family (WIF. A dual-process model was proposed, in which both work stress and career resilience mediate the CSE-WIF relationship. The mediation model was tested with a sample of employees from various organizations (N = 561. The results first showed that CSE was negatively related to time-based and strain-based WIF and positively related to behavior-based WIF via the mediation of work stress. Moreover, CSE was positively associated with behavior-based and strain-based WIF via the mediation of career resilience, suggesting that CSE may also have its dark-side.

Regional variability among nonlinear chlorophyll-phosphorus relationships in lakes

Science.gov (United States)

Filstrup, Christopher T.; Wagner, Tyler; Soranno, Patricia A.; Stanley, Emily H.; Stow, Craig A.; Webster, Katherine E.; Downing, John A.

2014-01-01

The relationship between chlorophyll a (Chl a) and total phosphorus (TP) is a fundamental relationship in lakes that reflects multiple aspects of ecosystem function and is also used in the regulation and management of inland waters. The exact form of this relationship has substantial implications on its meaning and its use. We assembled a spatially extensive data set to examine whether nonlinear models are a better fit for Chl a—TP relationships than traditional log-linear models, whether there were regional differences in the form of the relationships, and, if so, which regional factors were related to these differences. We analyzed a data set from 2105 temperate lakes across 35 ecoregions by fitting and comparing two different nonlinear models and one log-linear model. The two nonlinear models fit the data better than the log-linear model. In addition, the parameters for the best-fitting model varied among regions: the maximum and lower Chl aasymptotes were positively and negatively related to percent regional pasture land use, respectively, and the rate at which chlorophyll increased with TP was negatively related to percent regional wetland cover. Lakes in regions with more pasture fields had higher maximum chlorophyll concentrations at high TP concentrations but lower minimum chlorophyll concentrations at low TP concentrations. Lakes in regions with less wetland cover showed a steeper Chl a—TP relationship than wetland-rich regions. Interpretation of Chl a—TP relationships depends on regional differences, and theory and management based on a monolithic relationship may be inaccurate.

Quantitative structure-activity relationship (QSAR) models for polycyclic aromatic hydrocarbons (PAHs) dissipation in rhizosphere based on molecular structure and effect size

International Nuclear Information System (INIS)

Ma Bin; Chen Huaihai; Xu Minmin; Hayat, Tahir; He Yan; Xu Jianming

2010-01-01

Rhizoremediation is a significant form of bioremediation for polycyclic aromatic hydrocarbons (PAHs). This study examined the role of molecular structure in determining the rhizosphere effect on PAHs dissipation. Effect size in meta-analysis was employed as activity dataset for building quantitative structure-activity relationship (QSAR) models and accumulative effect sizes of 16 PAHs were used for validation of these models. Based on the genetic algorithm combined with partial least square regression, models for comprehensive dataset, Poaceae dataset, and Fabaceae dataset were built. The results showed that information indices, calculated as information content of molecules based on the calculation of equivalence classes from the molecular graph, were the most important molecular structural indices for QSAR models of rhizosphere effect on PAHs dissipation. The QSAR model, based on the molecular structure indices and effect size, has potential to be used in studying and predicting the rhizosphere effect of PAHs dissipation. - Effect size based on meta-analysis was used for building PAHs dissipation quantitative structure-activity relationship (QSAR) models.

Quantitative structure-activity relationship (QSAR) models for polycyclic aromatic hydrocarbons (PAHs) dissipation in rhizosphere based on molecular structure and effect size

Energy Technology Data Exchange (ETDEWEB)

Ma Bin; Chen Huaihai; Xu Minmin; Hayat, Tahir [Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental and Natural Resource Sciences, Zhejiang University, Hangzhou 310029 (China); He Yan, E-mail: yhe2006@zju.edu.c [Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental and Natural Resource Sciences, Zhejiang University, Hangzhou 310029 (China); Xu Jianming, E-mail: jmxu@zju.edu.c [Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental and Natural Resource Sciences, Zhejiang University, Hangzhou 310029 (China)

2010-08-15

Rhizoremediation is a significant form of bioremediation for polycyclic aromatic hydrocarbons (PAHs). This study examined the role of molecular structure in determining the rhizosphere effect on PAHs dissipation. Effect size in meta-analysis was employed as activity dataset for building quantitative structure-activity relationship (QSAR) models and accumulative effect sizes of 16 PAHs were used for validation of these models. Based on the genetic algorithm combined with partial least square regression, models for comprehensive dataset, Poaceae dataset, and Fabaceae dataset were built. The results showed that information indices, calculated as information content of molecules based on the calculation of equivalence classes from the molecular graph, were the most important molecular structural indices for QSAR models of rhizosphere effect on PAHs dissipation. The QSAR model, based on the molecular structure indices and effect size, has potential to be used in studying and predicting the rhizosphere effect of PAHs dissipation. - Effect size based on meta-analysis was used for building PAHs dissipation quantitative structure-activity relationship (QSAR) models.

Parent-child relationships, partner relationships, and emotional adjustment: a birth-to-maturity prospective study.

Science.gov (United States)

Overbeek, Geertjan; Stattin, Håkan; Vermulst, Ad; Ha, Thao; Engels, Rutger C M E

2007-03-01

This study examined whether detrimental childhood relationships with parents were related to partner relationship quality and emotional adjustment in adulthood. The authors tested a theoretical model in which (a) low-quality parent-child relationships were related to conflict and low-quality communication with parents in adolescence, (b) parent-adolescent conflict and low-quality communication were linked to low-quality partner relationships in young adulthood, and (c) low-quality partner relationships in young adulthood were predictive of low-quality partner relationships as well as depression, anxiety, and dissatisfaction with life at midlife. Multi-informant data were used from 212 Swedish individuals who were followed from birth into adulthood. Results demonstrated that, as hypothesized, negative parent-child bonds were indirectly related to low-quality partner relationships and dissatisfaction with life in adulthood (but not anxiety and depression) through conflictual parent-adolescent communication and low-quality partner relationships in young adulthood.

ON THE INFLUENTIAL POINTS IN THE FUNCTIONAL CIRCULAR RELATIONSHIP MODELS WITH AN APPLICATION ON WIND DATA

Directory of Open Access Journals (Sweden)

ALi Hassan Abuzaid

2013-12-01

Full Text Available If the interest is to calibrate two instruments then the functional relationship model is more appropriate than regression models. Fitting a straight line when both variables are circular and subject to errors has not received much attention. In this paper, we consider the problem of detecting influential points in two functional relationship models for circular variables. The first is based on the simple circular regression the (SC, while the last is derived from the complex linear regression the (CL.   The covariance matrices are derived and then the COVRATIO statistics are formulated for both models. The cut-off points are obtained and the power of performance is assessed via simulation studies.   The performance of COVRATIO statistics depends on the concentration of error, sample size and level of contamination. In the case of linear relationship between two circular variables COVRATIO statistics of the (SC model performs better than the (CL.  On the other hand, a novel diagram, the so-called spoke plot, is utilized to detect possible influential points For illustration purposes, the proposed procedures are applied on real data of wind directions measured by two different instruments. COVRATIO statistics and the spoke plot were able to identify two observations as influential points. Normal 0 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"جدول عادي"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;}

The relationship between inter-organizational trust and performance

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Roman Fiala

2012-01-01

Full Text Available The article deals with an investigation of the relationship between inter-organizational trust and performance. Using data obtained in a questionnaire survey in 373 organizations with more than 20 employees with their seat in the Czech Republic, we found the relationship between inter-organizational trust and supplier performance, mediated by the level of conflict. Also, the statistically significant negative relationship between inter-organizational trust and costs of negotiation and the statistically significant positive relationship between supplier performance and perceived performance were confirmed. The hypothesis on the statistically significant relationship between inter-organizational trust and negotiating costs was not confirmed. The structural equation modelling technique was used in the calculations. The calculated model fit indices (CFI, NFI, NNFI with values over 0.9 demonstrate a very good quality of the model.

A Test and Extension of Lane and Terry's (2000) Conceptual Model of Mood-Performance Relationships Using a Large Internet Sample.

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Lane, Andrew M; Terry, Peter C; Devonport, Tracey J; Friesen, Andrew P; Totterdell, Peter A

2017-01-01

The present study tested and extended Lane and Terry (2000) conceptual model of mood-performance relationships using a large dataset from an online experiment. Methodological and theoretical advances included testing a more balanced model of pleasant and unpleasant emotions, and evaluating relationships among emotion regulation traits, states and beliefs, psychological skills use, perceptions of performance, mental preparation, and effort exerted during competition. Participants ( N = 73,588) completed measures of trait emotion regulation, emotion regulation beliefs, regulation efficacy, use of psychological skills, and rated their anger, anxiety, dejection, excitement, energy, and happiness before completing a competitive concentration task. Post-competition, participants completed measures of effort exerted, beliefs about the quality of mental preparation, and subjective performance. Results showed that dejection associated with worse performance with the no-dejection group performing 3.2% better. Dejection associated with higher anxiety and anger scores and lower energy, excitement, and happiness scores. The proposed moderating effect of dejection was supported for the anxiety-performance relationship but not the anger-performance relationship. In the no-dejection group, participants who reported moderate or high anxiety outperformed those reporting low anxiety by about 1.6%. Overall, results showed partial support for Lane and Terry's model. In terms of extending the model, results showed dejection associated with greater use of suppression, less frequent use of re-appraisal and psychological skills, lower emotion regulation beliefs, and lower emotion regulation efficacy. Further, dejection associated with greater effort during performance, beliefs that pre-competition emotions did not assist goal achievement, and low subjective performance. Future research is required to investigate the role of intense emotions in emotion regulation and performance.

Different relationships between temporal phylogenetic turnover and phylogenetic similarity and in two forests were detected by a new null model.

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Huang, Jian-Xiong; Zhang, Jian; Shen, Yong; Lian, Ju-yu; Cao, Hong-lin; Ye, Wan-hui; Wu, Lin-fang; Bin, Yue

2014-01-01

Ecologists have been monitoring community dynamics with the purpose of understanding the rates and causes of community change. However, there is a lack of monitoring of community dynamics from the perspective of phylogeny. We attempted to understand temporal phylogenetic turnover in a 50 ha tropical forest (Barro Colorado Island, BCI) and a 20 ha subtropical forest (Dinghushan in southern China, DHS). To obtain temporal phylogenetic turnover under random conditions, two null models were used. The first shuffled names of species that are widely used in community phylogenetic analyses. The second simulated demographic processes with careful consideration on the variation in dispersal ability among species and the variations in mortality both among species and among size classes. With the two models, we tested the relationships between temporal phylogenetic turnover and phylogenetic similarity at different spatial scales in the two forests. Results were more consistent with previous findings using the second null model suggesting that the second null model is more appropriate for our purposes. With the second null model, a significantly positive relationship was detected between phylogenetic turnover and phylogenetic similarity in BCI at a 10 m×10 m scale, potentially indicating phylogenetic density dependence. This relationship in DHS was significantly negative at three of five spatial scales. This could indicate abiotic filtering processes for community assembly. Using variation partitioning, we found phylogenetic similarity contributed to variation in temporal phylogenetic turnover in the DHS plot but not in BCI plot. The mechanisms for community assembly in BCI and DHS vary from phylogenetic perspective. Only the second null model detected this difference indicating the importance of choosing a proper null model.

Ancestral Relationships Using Metafounders: Finite Ancestral Populations and Across Population Relationships.

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Legarra, Andres; Christensen, Ole F; Vitezica, Zulma G; Aguilar, Ignacio; Misztal, Ignacy

2015-06-01

Recent use of genomic (marker-based) relationships shows that relationships exist within and across base population (breeds or lines). However, current treatment of pedigree relationships is unable to consider relationships within or across base populations, although such relationships must exist due to finite size of the ancestral population and connections between populations. This complicates the conciliation of both approaches and, in particular, combining pedigree with genomic relationships. We present a coherent theoretical framework to consider base population in pedigree relationships. We suggest a conceptual framework that considers each ancestral population as a finite-sized pool of gametes. This generates across-individual relationships and contrasts with the classical view which each population is considered as an infinite, unrelated pool. Several ancestral populations may be connected and therefore related. Each ancestral population can be represented as a "metafounder," a pseudo-individual included as founder of the pedigree and similar to an "unknown parent group." Metafounders have self- and across relationships according to a set of parameters, which measure ancestral relationships, i.e., homozygozities within populations and relationships across populations. These parameters can be estimated from existing pedigree and marker genotypes using maximum likelihood or a method based on summary statistics, for arbitrarily complex pedigrees. Equivalences of genetic variance and variance components between the classical and this new parameterization are shown. Segregation variance on crosses of populations is modeled. Efficient algorithms for computation of relationship matrices, their inverses, and inbreeding coefficients are presented. Use of metafounders leads to compatibility of genomic and pedigree relationship matrices and to simple computing algorithms. Examples and code are given. Copyright © 2015 by the Genetics Society of America.

Effects of Teacher Attachment History on Teacher-Child Relationships.

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Kesner, John E.