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75th World Foundry Congress, WFC 2024

作者： Wilk-Kolodziejczyk, Dorota Witkowski, Mateusz Jaśkowiec, Krzysztof Malysza, Marcin Bitka, Adama Marcjan, Lukasz Department of Applied Computer Science and Modelling Faculty of Metals Engineering and Industrial Computer Science AGH University of Krakow Czarnowiejska 66 Krakow30-054 Poland Lukasiewicz – Krakow Institute of Technology Zakopiańska 73 Kraków30-418 Poland

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RMSD Calculations for Comparing Protein Three-Dimensional Structures 10th

RMSD Calculations for Comparing Protein Three-Dimensional S...

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10th International Conference on Numerical methods and Applications, NMA 2022

作者： Sapundzhi, Fatima Popstoilov, Metodi Lazarova, Meglena Department of Communication and Computer Engineering Faculty of Engineering South-West University "Neofit Rilski" Blagoevgrad2700 Bulgaria Department of Mathematical Modelling and Numerical Methods Faculty of Applied Mathematics and Informatics Technical University of Sofia Sofia1000 Bulgaria

ISBN: (纸本)9783031324116

The root Mean Square Deviation (RMSD) is a popular measure of structural similarity between protein structures in the field of bioinformatics. The RMSD calculations involve alignment and optimal superposition between matched pairs of atoms, searching for the lowest RMSD result for both structures. Among the popular methods for calculating the optimal rotation matrix that minimizes the RMSD are the Kabsch algorithm and the Quaternion algorithm. The aim of this research is to present a simple tool for calculation of the RMSD between pairs of aligned three dimensional structures by applying the methods mentioned above. As an implementation language the object-oriented C# programming language has been chosen. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Proteins

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modelling of diffraction of X-rays in perovskite superlattices 7

Modelling of diffraction of X-rays in perovskite superlattic...

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7th International Conference of Computational methods in Engineering Science, CMES 2022

作者： Kokosza, L. Mitura, Z. Department of Applied Computer Science and Modelling Faculty of Metals Engineering and Industrial Computer Science AGH University of Science and Technology al. Mickiewicza 30 Kraków30-059 Poland

Nowadays, different perovskite structures are widely investigated because they can be potentially used in many branches of industry. If two materials are deposited alternately on a substrate, then a superlattice having some unique properties can be formed. However, X-ray intensity distributions for perovskite superlattices, especially for very thin films, are difficult to be computationally determined, because many different parameters need to be considered to reproduce a superstructure of a sample. The main purpose of this work is to demonstrate how basic intensity distributions can be generated for perovskites, XRD technique and how to improve results using specific numerical methods. The computer application with a user-friendly graphical interface has been developed employing Unity software (with 3D graphics tools) and Oracle Database (through Oracle Cloud Infrastructure). The calculations are based on the kinematical theory of diffraction. The values of some important parameters and the results are stored in the assigned database. It is assumed that epitaxial superlattices can be prepared on substrates using molecular beam epitaxy or pulsed laser deposition methods. The desktop application allows for designing samples of different thicknesses and combinations of monolayers. The results are more realistic if Monte Carlo simulations are done although longer computation time is required. The software developed should be helpful to compare in detail virtual model results with experimental data. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Perovskite

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Prototype for the Model-Based Assets and Liabilities Management Support System

Prototype for the Model-Based Assets and Liabilities Managem...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Aleksandra Zhukova Anna Flerova Maxim Tarasenko Alexey Chernov Ruslan Gabbasov Department of Mathematical Modelling of Economic Systems Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia Department of Mathematical Modelling of Economic Systems FRC CSC RAS Moscow Russia Laboratory of Numerical Methods of Applied Structural Optimization MIPT Moscow Russia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This paper presents the prototype of the instrument that supports the control of assets and liabilities by a bank using the mathematical computations. The specifics of the approach lies in the application of the recent advances in the control theory to provide the strategic analysis for various planning horizons and scenarios of external and internal factors.

关键词： Instruments Computational modeling Prototypes Mathematical models Planning Control theory Information technology

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Selection of the optimal heat treatment conditions using advanced phase transformation models 4

Selection of the optimal heat treatment conditions using adv...

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4th International Conference on Design and Manufacturing Engineering

作者： Bzowski, Krzysztof Rauch, Lukasz Pietrzyk, MacIej Department of Applied Computer Science and Modelling AGH University of Science and Technology Krakow Poland

The paper focuses on the problem of optimal cooling cycle selection for steel sheets after hot rolling in order to obtain a given phase composition using complex numerical model. The proposed model driven by diffusion of carbon with the moving boundary (Stefan problem) was designed and implemented on the basis of Level Set equations coupled with diffusion equation. Application of implicit method for interface evolution allows to overcome the limitations associated with the complicated representation of material microstructure, but also in a natural way reflects the impact of front curvature and influence of chemical forces on the velocity of the interface. The article discusses the details of the model as well as the applied optimization technique. Three test scenarios are analyzed and the results are discussed. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Hot rolling

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Selection of the optimal heat treatment conditions using advanced phase transformation models

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IOP Conference Series: Materials Science and Engineering 2019年第1期627卷

作者： Krzysztof Bzowski Lukasz Rauch Maciej Pietrzyk Department of Applied Computer Science and Modelling AGH University of Science and Technology Krakow Poland

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Solving Lur'e equations through zeroing neural networks

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Information Sciences 2025年 718卷

作者： Yu He Xiaojuan Wang Yafei Tie Huanqi Yang Theodore E. Simos Spyridon D. Mourtas Vasilios N. Katsikis School of Computer Science and Artificial Intelligence Huanghuai University Zhumadian 463000 China Henan International Joint Laboratory of Behavior Optimization Control for Smart Robots Henan 463000 China Henan Key Laboratory of Smart Lighting Zhumadian 46300 China Hangzhou Dianzi University School of Mechanical Engineering Er Hao Da Jie 1158 Xiasha Hangzhou 310018 China Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology West Mishref 32093 Kuwait Section of Mathematics Dept. of Civil Engineering Democritus Univ. of Thrace Xanthi 67100 Greece Department of Economics Division of Mathematics-Informatics and Statistics-Econometrics National and Kapodistrian University of Athens Sofokleous 1 Street 10559 Athens Greece Laboratory “Hybrid Methods of Modelling and Optimization in Complex Systems” Siberian Federal University Prosp. Svobodny 79 660041 Krasnoyarsk Russia

Solving Lur'e equations plays a critical role in addressing linear-quadratic optimal control (LQOC) problems, especially in cases where the control cost matrices are singular. This paper introduces, for the first time, two novel zeroing neural network (ZNN) models—ZNNLE and ZNNLE-LQOC—specifically designed to solve the Lur'e equation system and the LQOC problem, respectively. The proposed models extend the applicability of the ZNN methodology to these challenging scenarios by offering robust and efficient solutions to time-varying matrix equations. Theoretical analyses confirm the validity of both models, while numerical simulations and practical applications demonstrate their effectiveness. Moreover, a comparative study with an enhanced alternating-direction implicit (ADI) method highlights the superior performance of the ZNNLE-LQOC model in solving LQOC problems.

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Sensitivity analysis on HPC systems with Scalarm platform

Sensitivity analysis on HPC systems with Scalarm platform

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作者： Bachniak, Daniel Rauch, Lukasz Król, Dariusz Liput, Jakub Slota, Renata Kitowski, Jacek Pietrzyk, Maciej Faculty of Metals Engineering and Industrial Computer Science Department of Applied Computer Science and Modelling AGH University of Science and Technology Krakow Poland ACC Cyfronet AGH AGH University of Science and Technology Krakow Poland Faculty of Computer Science Electronics and Telecommunications Department of Computer Science AGH University of Science and Technology Krakow Poland

Sensitivity analysis is widely used in numerical simulations applied in industry. The robustness of such applications is crucial, which means they have to be fast and precise at the same time. However, the conventional approach to sensitivity analysis assumes realization of multiple execution of computationally intensive simulations to discover input/output dependencies. In this paper, we present a novel computational approach for performing large-scale sensitivity analysis integrated with an extended platform for parameter studies – Scalarm – to make use of modern e-infrastructures for distribution and parallelization purposes, profitable for complicated industrial problems. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： Sensitivity analysis

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Substituting of a thermodynamic simulation with a metamodel in the scope of multiscale modelling 9th

Substituting of a thermodynamic simulation with a metamodel ...

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9th International Conference on Processing and Manufacturing of Advanced Materials, THERMEC 2016

作者： Maciol, Piotr Szeliga, Danuta Sztangret, Lukasz AGH University of Science and Technology Department of Applied Computer Science and Modelling Al. A. Mickiewicza 30 Kraków30-059 Poland

ISBN: (纸本)9783035711295

A typical multiscale simulation consists of numerous fine scale models, usually one for each computational point of a coarse scale model. One of possible ways of limiting computing power requirements is replacing fine scale models with some simplified and speeded up ersatz ones. In this paper, the authors attempt to develop a metamodel, replacing direct thermodynamic computations of precipitation kinetic with an advanced approximating model. MatCalc simulator has been used for thermodynamic modelling of precipitation kinetic. Typical heat treatment of P91 steel grade was examined. Selected variables were chosen to be modelled with approximating models. Several attempts with various approximation variants (interpolation algorithms and Artificial Neural Networks) have been investigated and its comparison is included in the paper. © 2017 Trans Tech Publications, Switzerland.

关键词： Sensitivity analysis

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National identity predicts public health support during a global pandemic (vol 13, 517, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-14页

作者： Van Bavel, Jay J. Cichocka, Aleksandra Capraro, Valerio Sjastad, Hallgeir Nezlek, John B. Pavlovic, Tomislav Alfano, Mark Gelfand, Michele J. Azevedo, Flavio Birtel, Michele D. Cislak, Aleksandra Lockwood, Patricia L. Ross, Robert Malcolm Abts, Koen Agadullina, Elena Aruta, John Jamir Benzon Besharati, Sahba Nomvula Bor, Alexander Choma, Becky L. Crabtree, Charles David Cunningham, William A. De, Koustav Ejaz, Waqas Elbaek, Christian T. Findor, Andrej Flichtentrei, Daniel Franc, Renata Gjoneska, Biljana Gruber, June Gualda, Estrella Horiuchi, Yusaku Huynh, Toan Luu Duc Ibanez, Agustin Imran, Mostak Ahamed Israelashvili, Jacob Jasko, Katarzyna Kantorowicz, Jaroslaw Kantorowicz-Reznichenko, Elena Krouwel, Andre Laakasuo, Michael Lamm, Claus Leygue, Caroline Lin, Ming-Jen Mansoor, Mohammad Sabbir Marie, Antoine Mayiwar, Lewend Mazepus, Honorata McHugh, Cillian Minda, John Paul Mitkidis, Panagiotis Olsson, Andreas Otterbring, Tobias Packer, Dominic J. Perry, Anat Petersen, Michael Bang Puthillam, Arathy Riano-Moreno, Julian C. Rothmund, Tobias Santamaria-Garcia, Hernando Schmid, Petra C. Stoyanov, Drozdstoy Tewari, Shruti Todosijevic, Bojan Tsakiris, Manos Tung, Hans H. Umbres, Radu G. Vanags, Edmunds Vlasceanu, Madalina Vonasch, Andrew Yucel, Meltem Zhang, Yucheng Abad, Mohcine Adler, Eli Akrawi, Narin Mdarhri, Hamza Alaoui Amara, Hanane Amodio, David M. Antazo, Benedict G. Apps, Matthew Ay, F. Ceren Ba, Mouhamadou Hady Barbosa, Sergio Bastian, Brock Berg, Anton Bernal-Zarate, Maria P. Bernstein, Michael Bialek, Michal Bilancini, Ennio Bogatyreva, Natalia Boncinelli, Leonardo Booth, Jonathan E. Borau, Sylvie Buchel, Ondrej Cameron, C. Daryl Carvalho, Chrissie F. Celadin, Tatiana Cerami, Chiara Chalise, Hom Nath Cheng, Xiaojun Cian, Luca Cockcroft, Kate Conway, Jane Cordoba-Delgado, Mateo Andres Crespi, Chiara Crouzevialle, Marie Cutler, Jo Cypryanska, Marzena Dabrowska, Justyna Daniels, Michael A. Davis, Victoria H. Dayley, Pamala N. Delouvee, Sylvain Denkovski, Ognjan Dezecache, Guillaume Dhaliwal, Nathan A. Diato, Department of Psychology and Neural Science New York University New York NY USA Department of Psychology University of Amsterdam Amsterdam Netherlands School of Psychology University of Kent Canterbury England Department of Economics Middlesex University London London England Department of Strategy and Management Norwegian School of Economics Bergen Norway SWPS University of Social Sciences and Humanities Poznań Poland Department of Psychological Sciences College of William and Mary Williamsburg VA USA Institute of Social Sciences Ivo Pilar Zagreb Croatia Department of Philosophy Macquarie University Sydney NSW Australia Stanford Graduate School of Business Stanford University Stanford CA USA Institute of Communication Science Friedrich-Schiller University Jena Jena Germany School of Human Sciences Institute for Lifecourse Development University of Greenwich London England Department of Experimental Psychology University of Oxford Oxford England Center for Human Brain Health School of Psychology University of Birmingham Birmingham England Department of Psychology Macquarie University Sydney NSW Australia KU Leuven Leuven Belgium National Research University Higher School of Economics (HSE) Moscow Russia De La Salle University Manila Philippines Department of Psychology University of the Witwatersrand Johannesburg South Africa Department of Political Science Aarhus University Aarhus Denmark X University Toronto Canada Department of Government Dartmouth College Hanover NH USA Department of Psychology University of Toronto Toronto ON Canada Gatton College of Business and Economics University of Kentucky Lexington KY USA Department of Mass Communication National University of Science and Technology (NUST) Islamabad Pakistan Department of Management Aarhus University Aarhus Denmark Center for Advanced Hindsight Duke University Durham NC USA Faculty of Social and Economic Sciences Comenius University Bratislava Slovakia IntraMed B

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1,N= 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N= 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r= −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.

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