Direct Measurement of the Angular Pair Correlation Coefficients in Molecular Liquids Using NMR. Benchmarking Force Fields for Atomistic Simulations

2017 ◽  
Vol 121 (16) ◽  
pp. 4174-4183
Author(s):  
Leah M. Heist ◽  
Chi-Duen Poon ◽  
Edward T. Samulski ◽  
Demetri J. Photinos
Keyword(s):  
Direct Measurement ◽  
Force Fields ◽  
Pair Correlation ◽  
Correlation Coefficients ◽  
Atomistic Simulations ◽  
Molecular Liquids

Subshell-pair correlation coefficients of atoms in momentum space

2005 ◽  
Vol 115 (4) ◽  
pp. 287-290 ◽  
Author(s):  
Hisashi Matsuyama ◽  
Toshikatsu Koga ◽  
Yoshihisa Kawata
Keyword(s):  
Momentum Space ◽  
Pair Correlation ◽  
Correlation Coefficients

scholarly journals Modeling and Forecasting of Socio-Economic Development of the Region

2018 ◽  
pp. 404-410
Keyword(s):  
Economic Development ◽  
Pair Correlation ◽  
Consumer Price Index ◽  
Correlation Coefficients ◽  
Analysis Data ◽  
Annual Number ◽  
Modeling And Forecasting ◽  
Socio Economic Development ◽  
Per Capita ◽  
Average Annual Number

The article is devoted to the modeling and forecasting of socio-economic development of the region. The dependence of GRP per capita of the Belgorod region on the average annual number of employed in the economy, the consolidated budget revenues, the volume of innovative works and services, the consumer price index, the industrial production index, the balanced financial result, exports was established. The analysis of the matrix of pair correlation coefficients of the selected indicators allowed to choose as the most significant explanatory variables the consolidated budget revenues and the average annual number of employees in the economy. The models of socio-economic development of the region were built. The quality of the models was evaluated. It was revealed that the most accurate is the power regression model. The forecast of further changes in GRP per capita was built on the basis of the retrospective analysis data. The method of extrapolation based on the construction of trend models for each explanatory variable was used to carry out the forecast.

scholarly journals Development of regression model of proteins attackability process in meat food (in vitro)

2021 ◽  
Vol 6 (3) ◽  
pp. 236-241
Author(s):  
A. S. Pulatov ◽  
M. A. Nikitina
Keyword(s):  
Regression Model ◽  
Human Body ◽  
Proteolytic Enzymes ◽  
Pair Correlation ◽  
Linear Equations ◽  
Meat Products ◽  
Chemical Properties ◽  
Correlation Coefficients ◽  
Raw Material

In the presented article the authors consider the issues of development of regression model for process of food digestion by proteolytic enzymes in human body. The authors use correlation analysis. They analyze the main nutritional values and physical and chemical properties of meat products, the modes of heat treatment of semi-finished lamb products. The essential parameters and features are determined to find the dependence between the factor values and efficient values of the basic raw material, which affect the quality of the technological processes and, in general, the finished product. The regression model equation is mathematically calculated by methods of solving K. Gauss linear equations. The standard deviations of parameters are calculated, the initial data are normalized; the matrices of the pair correlation coefficients, lower and upper limits of their values are compiled. Equations of the mathematical regression model of meat proteins attackability by proteolytic enzymes — in vitro (pepsin, trypsin) are developed. It is proved that the obtained equation represents a regression model of the process of meat food proteins attackability by enzymes (pepsin, trypsin and chymotrypsin), depending on the determined 3 essential factors (weight of a meat piece, duration of frying, collagen content in lamb meat). Also this equation reflects the process of lamb digestibility in a digestive tract of a human body.

CORRELATION ANALYSIS OF DAILY RIVER FLOWS IN THE REGION

2020 ◽  
pp. 48-54
Author(s):  
V.A. Naumov ◽  
Keyword(s):  
Information System ◽  
Correlation Coefficient ◽  
Pair Correlation ◽  
Correlation Coefficients ◽  
State Monitoring ◽  
River Flows ◽  
Average Value ◽  
Automated Information System ◽  
Annual Distribution ◽  
The City

The Automated Information System for State Monitoring of Water Bodies provided an array of daily river flows in 12 sections of Kaliningrad Rivers for 2008-2018. The pair correlation coefficients between these flows were calculated. The coefficient values were quite high, with the exception of 2013 for the Mamonovka River. The most typical intra-annual distribution of runoff for the region was found in the Pregel River near the city of Chernyakhovsk by the highest average value of the correlation coefficient. It should be recommended as an analog for medium-sized rivers in the region. The most typical intra-annual distribution of small watercourses is observed in the Zlay River. The correlation coefficient dependence on the water content of the year was not confirmed.

Experimental uncertainties of three-dimensional pair distribution function investigations exemplified on the diffuse scattering from a tris-tert-butyl-1,3,5-benzene tricarboxamide single crystal

2014 ◽  
Vol 47 (6) ◽  
pp. 2011-2018 ◽  
Author(s):  
Arkadiy Simonov ◽  
Thomas Weber ◽  
Walter Steurer
Keyword(s):  
Distribution Function ◽  
Single Crystal ◽  
Diffuse Scattering ◽  
Pair Distribution Function ◽  
Pair Correlation ◽  
Three Dimensional ◽  
Correlation Coefficients ◽  
Careful Analysis ◽  
Systematic Errors ◽  
The Impact

Diffuse scattering from a substitutionally disordered tris-tert-butyl-1,3,5-benzene tricarboxamide single crystal is analyzed with the three-dimensional difference pair distribution function (3D-ΔPDF) method. The real structure of the crystal is shown to consist of infinite polar molecular stacks along thecaxis, which are laterally packed in a hexagonal fashion. The orientation of the stacks is disordered, but neighboring stacks strongly prefer antiparallel arrangements. Quantitative orientational pair correlation coefficients are determined for all lateral pairs separated by less than 100 Å. A careful analysis of the factors influencing the accuracy of the 3D-ΔPDF refinement is presented. It is shown that the effect of statistical errors is small compared to systematic errors coming from diffraction geometry distortions, reciprocal space resolution or incompletely corrected background. Various strategies for identifying and decreasing systematic errors are discussed. The impact of the systematic errors on the uncertainty of the results is not just specific for 3D-ΔPDF investigations but also relevant for other quantitative diffuse scattering modeling techniques.

scholarly journals The profitability of second-tier banks: essence and main influencing factors

2021 ◽  
Vol 101 (1) ◽  
pp. 36-47
Author(s):  
Zh.T. Yeveskina ◽  
Keyword(s):  
Regression Analysis ◽  
Pair Correlation ◽  
Correlation Coefficients ◽  
Net Income ◽  
Testing Hypotheses ◽  
Factors Affecting ◽  
Main Factors ◽  
Second Tier ◽  
The Republic ◽  
The Relationship

Object. In this article, based on the aggregate indicators of second-tier banks of the Republic of Kazakhstan, what factors and how they affect the net income of the bank is determined. Methods. During the analysis, a correlation-regression analysis of banking data was carried out using the Stata statistical package, and conclusions were drawn. Findings. To identify the factors that affect the profitability of banks, the interdependencies between the selected indicators were identified. The correlation analysis revealed the relationship between the selected factors and the bank's net income. The density of bonds was determined by testing hypotheses calculated based on pair correlation coefficients. Conclusions. The factor analysis carried out made it possible to identify the main factors affecting the bank's activities and assess the degree of their impact. As a result of the analysis of factors affecting the bank's income in the aggregate indicator of second-tier banks of the Republic of Kazakhstan, the compliance of the results obtained with the expected results was determined.

scholarly journals Active Learning for Robust, High-Complexity Reactive Atomistic Simulations

2020 ◽  
Author(s):  
Rebecca Lindsey ◽  
Laurence E. Fried ◽  
Nir Goldman ◽  
Sorin Bastea
Keyword(s):  
Active Learning ◽  
Density Functional ◽  
Force Fields ◽  
Atomistic Simulations ◽  
Management Approach ◽  
Linear Combinations ◽  
Functional Theory ◽  
Automated Generation ◽  
Reactive Force Fields ◽  
Polynomial Expansions

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. Here we present an active learning approach based on cluster analysis and Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. Use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training repository management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory (DFT) in terms of structure, dynamics, and speciation.

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