scholarly journals Calculation of Cement Composition Using a New Model Compared to the Bogue Model

Materials ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4663
Author(s):  
Sang-Hyo Shim ◽  
Tae-Hee Lee ◽  
Seong-Joon Yang ◽  
Norhazilan Bin Md. Noor ◽  
Jang-Ho-Jay Kim
Keyword(s):  
Experimental Data ◽  
Chemical Compositions ◽  
Data Sets ◽  
Accuracy Improvement ◽  
Study Results ◽  
New Models ◽  
Applicable Range ◽  
Precise Prediction ◽  
Composition Ratios ◽  
Cement Compounds

The major cement composition ratios of alite, belite, aluminate, and ferrite have been calculated with the Bogue models until now. However, a recent comprehensive analysis based on various experimental data has revealed that the chemical composition of alite, belite, aluminate, and ferrite implemented by the Bogue models are slightly different than the experimental data, where small amounts of Al2O3 and Fe2O3 existing in alite and belite can change the prediction of cement composition. Since the amounts of cement compound are very important factors in determining the properties of concrete, improvement in the calculation would give more precise prediction for application usages such as climate change adaptable cement and high durable concrete manufacturing. For this purpose, 20 new models are proposed by modifying chemical compositions of the cement compounds and verified with the 50 experimental data sets. From the verification, the most accurate models are identified. The calculation using new models exhibit an accuracy improvement of approximately 5% compared to the Bogue models. Their applicable range is also presented. The study results are discussed in detail in the paper.

scholarly journals Predicting Genome Architecture: Challenges and Solutions

2021 ◽  
Vol 11 ◽  
Author(s):  
Polina Belokopytova ◽  
Veniamin Fishman
Keyword(s):  
Experimental Data ◽  
Gene Regulation ◽  
Genome Organization ◽  
Genome Architecture ◽  
Data Sets ◽  
Structural Variations ◽  
New Models ◽  
Statistical Approaches ◽  
Chromatin Profiling ◽  
Predictive Approaches

Genome architecture plays a pivotal role in gene regulation. The use of high-throughput methods for chromatin profiling and 3-D interaction mapping provide rich experimental data sets describing genome organization and dynamics. These data challenge development of new models and algorithms connecting genome architecture with epigenetic marks. In this review, we describe how chromatin architecture could be reconstructed from epigenetic data using biophysical or statistical approaches. We discuss the applicability and limitations of these methods for understanding the mechanisms of chromatin organization. We also highlight the emergence of new predictive approaches for scoring effects of structural variations in human cells.

scholarly journals Polyconvex hyperelastic modeling of rubberlike materials

2021 ◽  
Vol 43 (7) ◽  
Author(s):  
Cyprian Suchocki ◽  
Stanisław Jemioło
Keyword(s):  
Experimental Data ◽  
Power Law ◽  
Curve Fitting ◽  
Constitutive Relations ◽  
Data Sets ◽  
Power Law Model ◽  
Stored Energy ◽  
Data Approximation ◽  
Exponential Power ◽  
Hyperelastic Models

AbstractIn this work a number of selected, isotropic, invariant-based hyperelastic models are analyzed. The considered constitutive relations of hyperelasticity include the model by Gent (G) and its extension, the so-called generalized Gent model (GG), the exponential-power law model (Exp-PL) and the power law model (PL). The material parameters of the models under study have been identified for eight different experimental data sets. As it has been demonstrated, the much celebrated Gent’s model does not always allow to obtain an acceptable quality of the experimental data approximation. Furthermore, it is observed that the best curve fitting quality is usually achieved when the experimentally derived conditions that were proposed by Rivlin and Saunders are fulfilled. However, it is shown that the conditions by Rivlin and Saunders are in a contradiction with the mathematical requirements of stored energy polyconvexity. A polyconvex stored energy function is assumed in order to ensure the existence of solutions to a properly defined boundary value problem and to avoid non-physical material response. It is found that in the case of the analyzed hyperelastic models the application of polyconvexity conditions leads to only a slight decrease in the curve fitting quality. When the energy polyconvexity is assumed, the best experimental data approximation is usually obtained for the PL model. Among the non-polyconvex hyperelastic models, the best curve fitting results are most frequently achieved for the GG model. However, it is shown that both the G and the GG models are problematic due to the presence of the locking effect.

A New Method for Characterizing Replacement Rate Variation in Molecular Sequences: Application of the Fourier and Wavelet Models to Drosophila and Mammalian Proteins

Genetics ◽  
2000 ◽  
Vol 154 (1) ◽  
pp. 381-395
Author(s):  
Pavel Morozov ◽  
Tatyana Sitnikova ◽  
Gary Churchill ◽  
Francisco José Ayala ◽  
Andrey Rzhetsky
Keyword(s):  
Wavelet Transforms ◽  
Parametric Bootstrap ◽  
Real Data ◽  
New Method ◽  
Rate Variation ◽  
Discrete Wavelet ◽  
Data Sets ◽  
Ratio Test ◽  
Replacement Rate ◽  
New Models

Abstract We propose models for describing replacement rate variation in genes and proteins, in which the profile of relative replacement rates along the length of a given sequence is defined as a function of the site number. We consider here two types of functions, one derived from the cosine Fourier series, and the other from discrete wavelet transforms. The number of parameters used for characterizing the substitution rates along the sequences can be flexibly changed and in their most parameter-rich versions, both Fourier and wavelet models become equivalent to the unrestricted-rates model, in which each site of a sequence alignment evolves at a unique rate. When applied to a few real data sets, the new models appeared to fit data better than the discrete gamma model when compared with the Akaike information criterion and the likelihood-ratio test, although the parametric bootstrap version of the Cox test performed for one of the data sets indicated that the difference in likelihoods between the two models is not significant. The new models are applicable to testing biological hypotheses such as the statistical identity of rate variation profiles among homologous protein families. These models are also useful for determining regions in genes and proteins that evolve significantly faster or slower than the sequence average. We illustrate the application of the new method by analyzing human immunoglobulin and Drosophilid alcohol dehydrogenase sequences.

Mathematical Model of the Sintering Process of Iron-Copper Bearings

2007 ◽  
Vol 23 ◽  
pp. 119-122
Author(s):  
Cristina Teișanu ◽  
Stefan Gheorghe ◽  
Ion Ciupitu
Keyword(s):  
Experimental Data ◽  
Mechanical Properties ◽  
Mathematical Model ◽  
Regression Analysis ◽  
Function Optimization ◽  
Chemical Compositions ◽  
Sintering Process ◽  
Molybdenum Disulphide ◽  
Iron Copper ◽  
Antifriction Properties

The most important features of the self-lubricating bearings are the antifriction properties such as friction coefficient and wear resistence and some mechanical properties such as hardness, tensile strength and radial crushing strength. In order to improve these properties new antifriction materials based on iron-copper powders with several additional components (tin, lead and molybdenum disulphide) have been developed by PM techniques. To find the optimal relationship between chemical compositions, antifriction and mechanical properties, in this paper a mathematical model of the sintering process is developed, which highlighted the accordance of the model with data by regression analysis. For the statistical processing of the experimental data the VH5 hardness values of the studied materials were considered. The development of mathematical model includes the enunciation of the model, the establishment of the performance function (optimization) and the establishment of the model equations and verifying. The accordance of the model with experimental data has been highlighted by regression analysis

Recent and Planned Developments of the Program OxCal

Radiocarbon ◽  
2013 ◽  
Vol 55 (2) ◽  
pp. 720-730 ◽  
Author(s):  
Christopher Bronk Ramsey ◽  
Sharen Lee
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Software Package ◽  
Model Averaging ◽  
Data Sets ◽  
Radiocarbon Dates ◽  
New Approach ◽  
New Models ◽  
Multiphase Models ◽  
Deposition Models

OxCal is a widely used software package for the calibration of radiocarbon dates and the statistical analysis of 14C and other chronological information. The program aims to make statistical methods easily available to researchers and students working in a range of different disciplines. This paper will look at the recent and planned developments of the package. The recent additions to the statistical methods are primarily aimed at providing more robust models, in particular through model averaging for deposition models and through different multiphase models. The paper will look at how these new models have been implemented and explore the implications for researchers who might benefit from their use. In addition, a new approach to the evaluation of marine reservoir offsets will be presented. As the quantity and complexity of chronological data increase, it is also important to have efficient methods for the visualization of such extensive data sets and methods for the presentation of spatial and geographical data embedded within planned future versions of OxCal will also be discussed.

scholarly journals BioNetLink - An Architecture for Working with Network Data

2014 ◽  
Vol 11 (2) ◽  
pp. 68-79
Author(s):  
Matthias Klapperstück ◽  
Falk Schreiber
Keyword(s):  
Experimental Data ◽  
Biological Networks ◽  
Regulatory Networks ◽  
Large Data ◽  
Biological Data ◽  
Network Data ◽  
Data Sets ◽  
Dynamic Views ◽  
Gene Regulatory ◽  
Multiple Network

Summary The visualization of biological data gained increasing importance in the last years. There is a large number of methods and software tools available that visualize biological data including the combination of measured experimental data and biological networks. With growing size of networks their handling and exploration becomes a challenging task for the user. In addition, scientists also have an interest in not just investigating a single kind of network, but on the combination of different types of networks, such as metabolic, gene regulatory and protein interaction networks. Therefore, fast access, abstract and dynamic views, and intuitive exploratory methods should be provided to search and extract information from the networks. This paper will introduce a conceptual framework for handling and combining multiple network sources that enables abstract viewing and exploration of large data sets including additional experimental data. It will introduce a three-tier structure that links network data to multiple network views, discuss a proof of concept implementation, and shows a specific visualization method for combining metabolic and gene regulatory networks in an example.

New analysis of the low-energy π±p differential cross-sections of the CHAOS Collaboration

2015 ◽  
Vol 24 (07) ◽  
pp. 1550050 ◽  
Author(s):  
E. Matsinos ◽  
G. Rasche
Keyword(s):  
Experimental Data ◽  
Cross Sections ◽  
Differential Cross ◽  
Form Factors ◽  
Partial Wave Analysis ◽  
Meson Mass ◽  
Data Sets ◽  
Differential Cross Sections ◽  
Pion Nucleon ◽  
Meson Factory

In a previous paper, we reported the results of a partial-wave analysis (PWA) of the pion–nucleon (πN) differential cross-sections (DCSs) of the CHAOS Collaboration and came to the conclusion that the angular distribution of their π+p data sets is incompatible with the rest of the modern (meson factory) database. The present work, re-addressing this issue, has been instigated by a number of recent improvements in our analysis, namely regarding the inclusion of the theoretical uncertainties when investigating the reproduction of experimental data sets on the basis of a given "theoretical" solution, modifications in the parametrization of the form factors of the proton and of the pion entering the electromagnetic part of the πN amplitude, and the inclusion of the effects of the variation of the σ-meson mass when fitting the ETH model of the πN interaction to the experimental data. The new analysis of the CHAOS DCSs confirms our earlier conclusions and casts doubt on the value for the πN Σ term, which Stahov, Clement and Wagner have extracted from these data.

Concentration Dependence of the Surface Tension of Three and Four-Component Systems with Peculiarities in the Surface Tension Isotherms of Lateral Binary Melts

2021 ◽  
Vol 1022 ◽  
pp. 194-202
Author(s):  
R.Kh. Dadashev ◽  
R.A. Kutuev
Keyword(s):  
Experimental Data ◽  
Surface Tension ◽  
Concentration Dependence ◽  
Experimental Error ◽  
Binary Systems ◽  
Experimental Studies ◽  
Study Results ◽  
Component Systems ◽  
Minimum Depth ◽  
Surface Tension Isotherms

The experimental study results of the melts concentration dependence of the surface tension of the four-component indium-tin-lead-bismuth system and its constituent binary systems of indium-tin, indium-lead, indium-bismuth, tin-lead, tin-bismuth, lead-bismuth are presented in the paper. It is shown that the concentration dependence of the melts surface tension of the In-Sn-Pb-Bi four-component system can be predicted from the data on ST (surface tension) values of lateral binary systems. Features in the ST isotherms in the form of a minimum are observed only in the indium-tin lateral system from all lateral binaries. A distinctive feature of the detected minimum is that the minimum depth slightly exceeds the experimental error. Therefore, in addition to the fact that the area of average compositions was studied more thoroughly, we carried out the surface tension measurements by two independent methods. The experimental data obtained by both methods coincide within the experimental error and indicate the extremum availability on ST isotherms. Thus, ST experimental studies by two independent methods confirmed the presence of a flat minimum on ST isotherms of the indium-tin binary system increasing the reliability of the obtained data. The obtained outcomes and their comparison with experimental data have shown that the considered models for predicting surface properties based on data due to similar properties of lateral binary systems adequately reflect the experimental dependences. However, the prediction model based on Kohler's method of excess values describes the experimental curves more accurately.

scholarly journals QCD: THEORETICAL DEVELOPMENTS

2004 ◽  
Vol 19 (06) ◽  
pp. 851-863 ◽  
Author(s):  
T. GEHRMANN
Keyword(s):  
Experimental Data ◽  
Quantum Chromodynamics ◽  
High Energy ◽  
Precise Prediction ◽  
Theoretical Developments

I review recent theoretical advances in quantum chromodynamics. Particular emphasis is put on developments related to the precise prediction and interpretation of experimental data from present and future high energy colliders.

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