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Journal of Thermal Analysis and Calorimetry
Authors:
Mihaela-Ligia Ungureşan
,
Andrada Măicăneanu
,
Francisc-Vasile Dulf
,
Eva-Henrietta Dulf
, and
Delia Maria Gligor

, modifications to a number of similar phenomena such as ion exclusion and ligand exchange [ 9 ]. Linear regression analysis has been the most commonly used technique to evaluate the fit of experimental data and isotherm models for ion exchange on natural

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, A. B. & Chittleborough , D. J., 1995. Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging. Geoderma. 67 . 215–226. Chittleborough D J

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Abstract  

In principle, the kinetic analysis of thermal effects has limitations when based on a single measurement. Using a simulated example and the dehydration of Ca(OH)2 , it will be shown that, through the simultaneous application of non-linear regression to several measurements run at different heating rates (multivariate non-linear regression), the difficult problem of determining the probable reaction type can be reliably solved.

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Abstract  

A new method of calculation of parameters of enthalpy relaxation models is proposed. Regression analysis treatment compares the experimental and calculated values of relaxation enthalpy. The experimental values of relaxation enthalpy are obtained by numerical integration of the difference between the two DSC curves. Contrary to the overall shape of the DSC curve the integral values are not affected by particular heat flow conditions during the DSC experiment. The Narayanaswamy's numerical model based on the Kohlrausch—William—Watts relaxation function was used to calculate the theoretical values of relaxation enthalpy. The application of the proposed method on the DSC experimental data of enthalpy relaxation of As2Se3 is shown.

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models [ 9 , 12–14 ] as well as calculating the root mean square error (RMSE), etc. In the present study linear regression models as a simple approach for predicting the LRIs in gas chromatographic analysis of volatile components of essential oils for

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Abstract  

A scaling model was built to calculate the activity of alpha emitting radionuclides in contaminated soil in the lysimeter field. Linear regression can be applied for the evaluation of radioactivity measurement data. Activities of the radionuclides 241Am, 238Pu, 239,240Pu and 90Sr obtained by experiments from real contaminated soils of the experimental lysimeter placed in a nuclear power plant (NPP) in Slovakia were evaluated using linear regression models with the method of least squares. A suitable scaling model for monitoring the 241Am, 238Pu, 239,240Pu alpha radionuclide activity was built using the regression triplet analysis and regression diagnostics. A regular designed scaling model opens the possibilities of longtime activity monitoring of these radionuclides, thus decreasing the number of necessary radiochemical analyses. The Fisher-Snedecor test, however, confirmed that the regression model for 90Sr activity monitoring by 241Am, 239,240Pu activity determination in contaminated soils can not be recommended.

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A comparative QSAR and QSRR study has been conducted by multiple linear regression (MLR), principal-component regression (PCR), and partial least-squares (PLS) analysis. Comparisons based on these regression methods have been used to model the chromatographic retention (lipophilicity) of thirteen new oxadiazoline derivatives by means of descriptors obtained by use of the Alchemy software package. Retention indices were determined by reversed-phased high-performance thin-layer chromatography on C 18 plates. The retention indices predicted were quite satisfactory and in very good agreement with the molecular structure of the compounds investigated.

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Abstract  

The decommissioning of the nuclear power plant (NPP) A1 Jaslovské Bohunice (Slovakia) is a complicated set of problems that is highly demanding both technically and financially. The basic goal of the decommissioning process is the total elimination of radioactive materials from the nuclear power plant area, and radwaste treatment to a form suitable for its safe disposal. The initial conditions of decommissioning also include elimination of the operational events, preparation and transport of the fuel from the plant territory, radiochemical and physical–chemical characterization of the radioactive wastes. One of the problems was and still is the processing of the liquid radioactive wastes. Such media is also the cooling water of the long-term storage of spent fuel. A suitable scaling model for predicting the activity of hard-to-detect radionuclides 239,240Pu, 90Sr and summary beta in cooling water using a regression triplet technique has been built using the regression triplet analysis and regression diagnostics.

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Abstract  

Characterization of radionuclide concentrations in soil profiles requires accurate evaluation of the depth distribution of the concentrations as measured by gamma emissions. Recent studies of 137Cs activity at the Idaho National Laboratory indicate that these data consistently follow exponential trends when the fraction of radioactivity below depth is plotted against depth. The slope of the exponential regression fit is defined as alpha/rho (α/ρ), the depth profile parameter. A weighted exponential regression procedure has been developed to compute a mean α/ρ for a group of related soil samples. Regression results from different areas or from different time periods can be used to compare representative radionuclide concentrations for the specified groupings.

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Abstract  

A simple ALGOL program for activation analysis data handling is presented The program, although designed in principle for processing single-channel spectrometry data, may also be used for multichannel spectrometry, on condition that the peak area is computed separately. The calculations of instrumental error and standard deviation are carried out. The outliers are tested, and the regression line diagram with the related observations are plotted by the program.

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