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Software News and Updates MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations

JOURNAL OF COMPUTATIONAL CHEMISTRY 2011年第10期32卷 2319-2327页

作者： Michaud-Agrawal, Naveen Denning, Elizabeth J. Woolf, Thomas B. Beckstein, Oliver Johns Hopkins Sch Med Dept Biophys Baltimore MD 21205 USA Univ Maryland Sch Pharm Dept Pharmaceut Chem Baltimore MD 21201 USA Johns Hopkins Sch Med Dept Physiol Baltimore MD 21205 USA Univ Oxford Dept Biochem Oxford OX1 3QU England

MDAnalysis is an object-oriented library for structural and temporal analysis of molecular dynamics (MD) simulation trajectories and individual protein structures. It is written in the python language with some performance-critical code in C. It uses the powerful NumPy package to expose trajectory data as fast and efficient NumPy arrays. It has been tested on systems of millions of particles. Many common file formats of simulation packages including CHARMM, Gromacs, Amber, and NAMD and the Protein Data Bank format can be read and written. Atoms can be selected with a syntax similar to CHARMM's powerful selection commands. MDAnalysis enables both novice and experienced programmers to rapidly write their own analytical tools and access data stored in trajectories in an easily accessible manner that facilitates interactive explorative analysis. MDAnalysis has been tested on and works for most Unix-based platforms such as Linux and Mac OS X. It is freely available under the GNU General Public License from http://***. (C) 2011 Wiley Periodicals, Inc. J Comput Chem 32: 2319-2327, 2011

关键词： molecular dynamics simulations analysis proteins object-oriented design software membrane systems python programming language

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A python Application for Visualizing the 3D Stratigraphic Architecture of the Onshore Llobregat River Delta in NE Spain

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WATER 2022年第12期14卷 1882-1882页

作者： Bullejos, Manuel Cabezas, David Martin-Martin, Manuel Javier Alcala, Francisco Univ Granada Dept Algebra Granada 18010 Spain Univ Granada Dept Anal Matemat Granada 18010 Spain Univ Alicante Dept Ciencias Tierra & Medio Ambiente Alicante 03080 Spain Estn Expt Zonas Aridas EEZA CSIC Dept Desertificac & Geoecol Almeria 04120 Spain Univ Autonoma Chile Fac Ingn Inst Ciencias Quim Aplicadas Santiago 7500138 Chile

This paper introduces a python application for visualizing the 3D stratigraphic architecture of porous sedimentary media. The application uses the parameter granulometry deduced from borehole lithological records to create interactive 3D HTML models of essential stratigraphic elements. On the basis of the high density of boreholes and the subsequent geological knowledge gained during the last six decades, the Quaternary onshore Llobregat River Delta (LRD) in northeastern Spain was selected to show the application. The public granulometry dataset produced by the Water Authority of Catalonia from 433 boreholes in this strategic coastal groundwater body was clustered into the clay-silt, coarse sand, and gravel classes. Three interactive 3D HTML models were created. The first shows the location of the boreholes granulometry. The second includes the main gravel and coarse sand sedimentary bodies (lithosomes) associated with the identified three stratigraphic intervals, called lower (>50 m b.s.l.) in the distal LRD sector, middle (20-50 m b.s.l.) in the central LRD, and upper (<20 m b.s.l.) spread over the entire LRD. The third deals with the basement (Pliocene and older rocks) top surface, which shows an overall steeped shape deepening toward the marine platform and local horsts, probably due to faulting. The modeled stratigraphic elements match well with the sedimentary structures reported in recent scientific publications. This proves the good performance of this incipient python application for visualizing the 3D stratigraphic architecture, which is a crucial stage for groundwater management and governance.

关键词： Llobregat River Delta stratigraphic architecture granulometry 3D modeling application python programming language convex hull algorithm IDW interpolation algorithm

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Harnessing Artificial Neural Networks for Financial Analysis of Investments in a Shower Heat Exchanger

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ENERGIES 2024年第14期17卷 3584页

作者： Kordana-Obuch, Sabina Starzec, Mariusz Piotrowska, Beata Rzeszow Univ Technol Dept Infrastruct & Water Management Al Powstancow Warszawy 6 PL-35959 Rzeszow Poland

This study focused on assessing the financial efficiency of investing in a horizontal shower heat exchanger. The analysis was based on net present value (NPV). The research also examined the possibility of using artificial neural networks and SHapley Additive exPlanation (SHAP) analysis to assess the profitability of the investment and the significance of individual parameters affecting the NPV of the project related to installing the heat exchanger in buildings. Comprehensive research was conducted, considering a wide range of input parameters. As a result, 1,215,000 NPV values were obtained, ranging from EUR -1996.40 to EUR 36,933.83. Based on these values, artificial neural network models were generated, and the one exhibiting the highest accuracy in prediction was selected (R-2 approximate to 0.999, RMSE approximate to 57). SHAP analysis identified total daily shower length and initial energy price as key factors influencing the profitability of the shower heat exchanger. The least influential parameter was found to be the efficiency of the hot water heater. The research results can contribute to improving systems for assessing the profitability of investments in shower heat exchangers. The application of the developed model can also help in selecting appropriate technical parameters of the system to achieve maximum financial benefits.

关键词： net present value (NPV) waste heat recovery machine learning multilayer perceptron SHAP analysis python programming language

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Drone Elevation Control Based on python-Unity Integrated Framework for Reinforcement Learning Applications

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DRONES 2023年第4期7卷 225-225页

作者： Abbass, Mahmoud Abdelkader Bashery Kang, Hyun-Soo Chungbuk Natl Univ Sch Elect & Comp Engn Dept Informat & Commun Engn Cheongju 28644 South Korea Helwan Univ Dept Mech Power Engn Cairo 11772 Egypt

Reinforcement learning (RL) applications require a huge effort to become established in real-world environments, due to the injury and break down risks during interactions between the RL agent and the environment, in the online training process. In addition, the RL platform tools (e.g., python OpenAI's Gym, Unity ML-Agents, PyBullet, DART, MoJoCo, RaiSim, Isaac, and AirSim), that are required to reduce the real-world challenges, suffer from drawbacks (e.g., the limited number of examples and applications, and difficulties in implementation of the RL algorithms, due to difficulties with the programing language). This paper presents an integrated RL framework, based on python-Unity interaction, to demonstrate the ability to create a new RL platform tool, based on making a stable user datagram protocol (UDP) communication between the RL agent algorithm (developed using the python programing language as a server), and the simulation environment (created using the Unity simulation software as a client). This python-Unity integration process, increases the advantage of the overall RL platform (i.e., flexibility, scalability, and robustness), with the ability to create different environment specifications. The challenge of RL algorithms' implementation and development is also achieved. The proposed framework is validated by applying two popular deep RL algorithms (i.e., Vanilla Policy Gradient (VPG) and Actor-Critic (A2C)), on an elevation control challenge for a quadcopter drone. The validation results for these experimental tests, prove the innovation of the proposed framework, to be used in RL applications, because both implemented algorithms achieve high stability, by achieving convergence to the required performance through the semi-online training process.

关键词： reinforcement learning agent simulation platform python programming language Unity simulation software UDP communication protocol Vanilla Policy Gradient algorithm Actor-Critic algorithm

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Efficiency and accuracy of GPU-parallelized Fourier spectral methods for solving phase-field models

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COMPUTATIONAL MATERIALS SCIENCE 2023年第1期228卷

作者： Boccardo, A. D. Tong, M. Leen, S. B. Tourret, D. Segurado, J. Univ Galway Coll Sci & Engn Sch Engn Mech Engn Univ Rd Galway H91 HX31 Ireland Univ Galway I Form Adv Mfg Res Ctr Univ Rd Galway H91 HX31 Ireland IMDEA Mat Inst C Er Kandel 2 Getafe 28906 Madrid Spain Univ Politecn Madrid Dept Mat Sci ETSI Caminos C Prof Aranguren 3 Madrid 28040 Spain

Phase-field models are widely employed to simulate microstructure evolution during processes such as solidification or heat treatment. The resulting partial differential equations, often strongly coupled together, may be solved by a broad range of numerical methods, but this often results in a high computational cost, which calls for advanced numerical methods to accelerate their resolution. Here, we quantitatively test the efficiency and accuracy of semi-implicit Fourier spectral-based methods, implemented in python programming language and parallelized on a graphics processing unit (GPU), for solving a phase-field model coupling Cahn-Hilliard and Allen-Cahn equations. We compare computational performance and accuracy with a standard explicit finite difference (FD) implementation with similar GPU parallelization on the same hardware. For a similar spatial discretization, the semi-implicit Fourier spectral (FS) solvers outperform the FD resolution as soon as the time step can be taken 5 to 6 times higher than afforded for the stability of the FD scheme. The accuracy of the FS methods also remains excellent even for coarse grids, while that of FD deteriorates significantly. Therefore, for an equivalent level of accuracy, semi-implicit FS methods severely outperform explicit FD, by up to 4 orders of magnitude, as they allow much coarser spatial and temporal discretization.

关键词： Phase-field model Fourier spectral method python programming language Graphic processing unit

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Spacing and block volume estimation in discontinuous rock masses using image processing technique: a case study

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ENVIRONMENTAL EARTH SCIENCES 2021年第14期80卷 471-471页

作者： Azarafza, Mohammad Kockar, Mustafa K. Faramarzi, Lohrasb Hacettepe Univ Dept Civil Engn Ankara Turkey Isfahan Univ Technol Dept Min Engn Esfahan Iran

Application of the image processing techniques (IPT) to identify rock mass geometry provides more fast information about discontinuity properties used in geo-engineering characteristics. In this regard, the field survey can be improved using IPT. This study has utilised the IPT to identify the discontinuity and block volume characteristics in a discontinuous rock mass. For this purpose, a visual evaluation of the rock mass outcrop with discontinuities from a road slope cut located in the South Pars Special Zone, Assalouyeh, Iran, was considered. A three-step IPT analysis (i.e. pre-processing, main processing, and post-processing) was conducted to extract the features through the python programming language. Regarding the IPT methodology, the studied rock mass characteristics consist of four major discontinuity sets and rock block volumes between the intersections of the discontinuities, as confirmed with a scan-line field survey. The evaluated data indicated that the maximum, minimum, and average block volumes processed by the IPT were 1.068, 0.479, and 1.055 m(3), and their field measurement results were 1.092, 0.479, and 1.065 m(3), respectively. Additionally, the orientations of the estimated discontinuity properties and their spacings determined by IPT for the rock mass ranging between 32 and 69.9 degrees and 0.5 and 2.18 m, respectively. Similarly, the orientations of the field measurement results were also obtained between 33 and 71 degrees and 0.58 and 2.25 m, respectively. The results of the IPT and the field survey were close, which revealed that the IPT is a reliable method for determining discontinuity spacing and rock block volume along large cut slopes. This approach provided rapid data processing with spatial extensions in a short period, making it possible to achieve accurate results in discontinuity network characteristics.

关键词： Image processing technique Artificial intelligence python programming language Rock engineering

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Computing the number of perfumes that constitute the gandharnava and kacchaputa of Varahamihira

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INDIAN JOURNAL OF HISTORY OF SCIENCE 2021年第2期56卷 85-92页

作者： Chauthaiwale, Shriram Deopujari, Jayant Chauthaiwale, Atharva Amolakchand Coll Math Yavatmal Maharashtra India Govt India Minist AYUSH Natl Commiss Indian Syst Med New Delhi India SLACK Technol Pune Maharashtra India

The sixth-century Indian scholar Varahamihira elaborated on the processes for the preparation of perfumes in the 'gandhayukti' chapter of the Brhatsamhita. He adapted the combinatorial analysis and magic square structure for arriving at the possible number of perfumes from the set of specified substances. This attempt is an excellent example of the multidisciplinary thought process of the Indian scholars in general and Varahamihira in particular. This paper focuses on the verses under the captions 'gandharnava' and 'kacchaputa'. In the first case, four substances are selected from sixteen, and the chosen four are permuted with the pre-defined proportions. In the second case, selected substances are placed in a 4 x 4 magic square. The claims by Varahamihira and the same amended by the commentator Bhattotpala for the number of perfumes are verified here. The constraints imposed by Varahamihira in the first case on the proportions of the two substances are considered. The correct number for the possible perfumes is determined mathematically in the first case and by the specially designed computer program in the second case. Valid lists of perfumes with ingredients obtained as the output are attached in the form of web links in the first case, and the same is placed in the Appendix for the second case.

关键词： Bhattotpala Gandharnava Kacchaputa Permutations and combinations python programming language Varahamihira

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On lazy evaluation as a tool to optimize the efficiency of large scale numerical simulations in python

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Procedia Computer Science 2010年第1期1卷 2145-2153页

作者： L. Gross A. Amirbekyan J. Fenwick L. Gao A. Mohajeri H. Muhlhaus Earth Systems Science Computational Center School of Earth Sciences The University of Queensland St. Lucia QLD 4072 Australia

Scientists working on mathematical models want to concentrate on the design of models. They pay little attention to numerical methods such as the finite element method (FEM), their implementation and parallelization. The escript module in python provides an environment in which scientists can define new models using a language of partial differential equation (PDE) and spatial functions which is natural for the formulation of continuous models. This approach defines a high level of abstraction from the underlying data structures and frees modelers from issues of optimized implementation and parallelization. In its current implementation escript evaluates expressions which define PDE coefficients immediately for all nodes or elements of an FEM mesh. In the paper we will demonstrate that for complex rheologies such as the Drucker–Prager plasticity model, the memory requirements for this strategy are the limiting factor for scaling up the mesh size. The python module is backed by an escript C++ library where the processing is performed. We will discuss an new extension to the PDE coefficient handling provided by this C++ library which uses a lazy evaluation technique and will demonstrate the efficiency of this new extension in terms of compute time and memory usage for a practical engineering application, namely the simulation of elastic-plastic, saturated porous media.

关键词： python programming language Partial differential equations Finite element methods

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Evaluating the Effective Factors of Hospital Rooms on Patients' Recovery Using the Data Mining Method

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HERD-HEALTH ENVIRONMENTS RESEARCH & DESIGN JOURNAL 2022年第1期15卷 97-114页

作者： Nikabadi, S. Zabihi, H. Shahcheraghi, A. Islamic Azad Univ Dept Architecture Sci & Res Branch Tehran Iran Islamic Azad Univ Dept Urban Dev Sci & Res Branch Tehran Iran

Objectives: This study aims to investigate the effective environmental factors of hospital rooms in patients' recovery through data mining techniques. Background: Previous studies have shown the positive effect of the interior environment of the hospitals on patients' recovery. The methods of these studies were mainly based on the evidence and patients' perception while hospital environments are associated with a large amount of data that make them an appropriate case for data mining studies. But data mining studies in hospitals mainly focused on medical and management purposes rather than evaluating the interior environment condition. Methods: We analyzed the hospital information system data of a hospital using python programming language and some of its libraries. Preprocessing and eliminating the outliers, labeling and clustering of diseases, data visualization and analysis, final evaluation, and concluding were done using the knowledge discovery in databases process. Results: Pearson coefficient value for rooms' area was .5 and, respectively, for the distance from the ward entrance and nursing station were .75 and .70. The chi(2) values for the variables of room types, location, and occupation were 24.62, 18.98, and 21.53, respectively, and for the beds' location was 0.12. Conclusions: The results confirmed the correlation of the length of stay with the room types, location, and occupation, distance from the nursing station and ward entrance and also showed a moderate correlation with the rooms' area. However, no evidence was found about the relationship between the beds' location in rooms and patients' length of hospital stay.

关键词： data mining hospital information system hospital room features length of stay python programming language

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Local Radial Basis Function Methods: Comparison, Improvements, and Implementation

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Journal of Applied Mathematics and Physics 2023年第12期11卷 3867-3886页

作者： Scott A. Sarra Department of Mathematics Marshall University Huntington USA

Radial Basis Function methods for scattered data interpolation and for the numerical solution of PDEs were originally implemented in a global manner. Subsequently, it was realized that the methods could be implemented more efficiently in a local manner and that the local approaches could match or even surpass the accuracy of the global implementations. In this work, three localization approaches are compared: a local RBF method, a partition of unity method, and a recently introduced modified partition of unity method. A simple shape parameter selection method is introduced and the application of artificial viscosity to stabilize each of the local methods when approximating time-dependent PDEs is reviewed. Additionally, a new type of quasi-random center is introduced which may be better choices than other quasi-random points that are commonly used with RBF methods. All the results within the manuscript are reproducible as they are included as examples in the freely available python Radial Basis Function Toolbox.

关键词： Radial Basis Functions Shape Parameter Selection Quasi-Random Centers Numerical PDEs Scientific Computing Open Source Software python programming language Reproducible Research

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