The mathematical modeling of real welding technologies based on a physicochemical analysis of the interaction between the phases (metal, slag, and gas) is employed in the present work. The model is based on the fundam...
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The mathematical modeling of real welding technologies based on a physicochemical analysis of the interaction between the phases (metal, slag, and gas) is employed in the present work. The model is based on the fundamental equations of thermodynamics and kinetics of high-temperature metallurgical reactions and factors which take into account the thermal and hydrodynamics conditions of the real process. Such an approach permits optimization of the composition of the materials and the technology of the process already in the planning stage with minimal expenditures of time and materials. The model is used to develop fundamentally new compositions for electrode coatings and flux-cored electrodes (including those based on the use of industrial waste products and recycled materials). The performance and adequacy of the model was tested using special technological experiments and as the research goes on the software is modified. The data base of the model includes the relevant experimental and theoretical data concerning the complex interaction of various alloying components. (c) 2006 Elsevier B.V. All rights reserved.
computational methods based on a linearized implicit scheme and a predictor-corrector method are proposed for the solution of the Kadomtsev-Petviashvili (KP) equation and its generalized from (GKP). The methods develo...
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computational methods based on a linearized implicit scheme and a predictor-corrector method are proposed for the solution of the Kadomtsev-Petviashvili (KP) equation and its generalized from (GKP). The methods developed for the KP equation are applied with minor modifications to the generalized case. An inportant advantage to be gained from the use of the linearized implicit method over the predictor-corrector method which is conditionally stable, is the ability to vary the mesh length, and thereby reducing the computational time. The methods are analysed with respect to stability criteria. Numerical results portraying a single line-soliton solution and the interaction of two-line solitons are reported for the KP equation. Moreover, a lump-like soliton (a solitary wave which decays to zero in all space dimensions) and the interaction of two lump solitons are reported for the KP equation.
Electron tomography (ET) has emerged as a powerful technique to address fundamental questions in molecular and cellular biology. It makes possible visualization of the molecular architecture of complex viruses, organe...
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Electron tomography (ET) has emerged as a powerful technique to address fundamental questions in molecular and cellular biology. It makes possible visualization of the molecular architecture of complex viruses, organelles and cells at a resolution of a few nanometres. In the last decade ET has allowed major breakthroughs that have provided exciting insights into a wide range of biological processes. In ET the biological sample is imaged with an electron microscope, and a series of images is taken from the sample at different views. Prior to imaging, the sample has to be specially prepared to withstand the conditions within the microscope. Subsequently, those images are processed and combined to yield the three-dimensional reconstruction or tomogram. Afterwards, a number of computational steps are necessary to facilitate the interpretation of the tomogram, such as noise reduction, segmentation and analysis of subvolumes. As the computational demands are huge in some of the stages, high performance computing (HPC) techniques are used to make the problem affordable in reasonable time. This article intends to comprehensively review the methods, technologies and tools involved in the different computational stages behind structural studies by Er, from image acquisition to interpretation of tomograms. The HPC techniques usually employed to cope with the computational demands are also briefly described. (C) 2012 Elsevier Ltd. All rights reserved.
The cellular automaton model of computation has drawn the interest of researchers from different disciplines including computer science, biology, mathematics, economy, biochemistry and philosophy. Although a cellular ...
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The cellular automaton model of computation has drawn the interest of researchers from different disciplines including computer science, biology, mathematics, economy, biochemistry and philosophy. Although a cellular automaton is based on a set of simple rules, over time complex patterns may evolve. We present computational methods for implementing and optimizing a well known two-state cellular automaton, Conway's Game of Life, on a 16-core Intel Xeon. The evaluation is based on three multicore algorithms. The first algorithm is coherent and utilizes shared memory and barrier synchronization. The remaining two algorithms are distributed and utilize private memories and explicit core-to-core message passing. We provide a link to our open source simulation software. (C) 2013 Elsevier B.V. All rights reserved.
作者：
Haider, ShozebUCL
UCL Sch Pharm 29-39 Brunswick Sq London WC1N 1AX England
Quadruplexes are four-stranded DNA or RNA structures formed from tandem repeats of guanine-rich sequences. They are present throughout the genome, namely at telomeres, in promoter and untranslated regions of important...
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Quadruplexes are four-stranded DNA or RNA structures formed from tandem repeats of guanine-rich sequences. They are present throughout the genome, namely at telomeres, in promoter and untranslated regions of important genes. Quadruplexes are thermodynamically stable structures and once formed can be a hindrance to cellular processes like transcription, translation, replication among others. Based on these findings, it has been proposed that small molecules can be used to selectively bind and stabilise quadruplexes. In this review, we explore computational methods that can be used to study quadruplex-ligand interactions. These methods not only provide interpretation of experimental data but also generate information that cannot be accessed by experimental methods.
In drug design, often enough, no structural information on a particular receptor protein is available. However, frequently a considerable number of different ligands is known together with their measured binding affin...
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In drug design, often enough, no structural information on a particular receptor protein is available. However, frequently a considerable number of different ligands is known together with their measured binding affinities towards a receptor under consideration. In such a situation, a set of plausible relative superpositions of different ligands, hopefully approximating their putative binding geometry, is usually the method of choice for preparing data for the subsequent application of 3D methods that analyze the similarity or diversity of the ligands. Examples are 3D-QSAR studies, pharmacophore elucidation, and receptor modeling. An aggravating fact is that ligands are usually quite flexible and a rigorous analysis has to incorporate molecular flexibility. We review the past six years of scientific publishing on molecular superposition. Our focus lies on automatic procedures to be performed on arbitrary molecular structures. Methodical aspects are our main concern here. Accordingly, plain application studies with few methodical elements are omitted in this presentation. While this review cannot mention every contribution to this actively developing field, we intend to provide pointers to the recent literature providing important contributions to computational methods for the structural alignment of molecules. Finally we provide a perspective on how superposition methods can effectively be used for the purpose of virtual database screening. In our opinion it is the ultimate goal to detect analogues in structure databases of nontrivial size in order to narrow down the search space for subsequent experiments.
Since ground-coupled heat pump system (GCHPs) has been more and more widely applied, it is vital to build an accurate method for sizing borehole heat exchangers (BHEs), and the methods for determining the heat transfe...
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Since ground-coupled heat pump system (GCHPs) has been more and more widely applied, it is vital to build an accurate method for sizing borehole heat exchangers (BHEs), and the methods for determining the heat transfer between the boreholes and surrounding ground under time-varying loads in different time scales are the kernel of optimizing design of BHEs, which is helpful to obtain accurate results and significantly decrease computation time consuming. This paper summarizes computational methods for the ground thermal response of BHE under time-varying loads and thermal interaction of multiple BHEs, compares the representative design tools in terms of their performance characteristics, and analyzes the direct applications of computational methods in thermal response test (TRT) and operating performance simulation of GCHPs. Finally, some recommendations for future development of computational methods are proposed. (C) 2018 Elsevier Ltd. All rights reserved.
In this article we develop a computational method for an algorithmic process first posed by Abramovich-Aliprantis-Polyrakis in 1994 in order to check whether a finite collection of linearly independent positive vector...
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In this article we develop a computational method for an algorithmic process first posed by Abramovich-Aliprantis-Polyrakis in 1994 in order to check whether a finite collection of linearly independent positive vectors in R-m forms a lattice-subspace. Lattice-subspaces are closely related to a cost minimization problem in the theory of finance that ensures the minimum-cost insured portfolio and this connection is further investigated here. Finally, we propose a computational method in order to solve the minimization problem and to calculate the minimum-cost insured portfolio. All of the numerical work is performed using the Matlab high-level language. (c) 2006 Elsevier Inc. All rights reserved.
Ultrasound has been proposed as a means to noninvasively assess bone and, particularly, bone strength and fracture risk. Although there has been some success in this application, there is still much that is unknown re...
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Ultrasound has been proposed as a means to noninvasively assess bone and, particularly, bone strength and fracture risk. Although there has been some success in this application, there is still much that is unknown regarding the propagation of ultrasound through bone. Because strength and fracture risk are a function of both bone mineral density and architectural structure, this study was carried out to examine how architecture and density interact in ultrasound propagation. Due to the difficulties inherent in obtaining fresh bone specimens and associated architectural and density features, simulation methods were used to explore the interactions of ultrasound with bone. A sample of calcaneal trabecular bone was scanned with micro-CT and subjected to morphological image processing (erosions and dilations) operations to obtain a total of 15 three-dimensional (3-D) data sets. Fifteen two-dimensional (2-D) slices obtained from the 3-D data sets were then analyzed to evaluate their respective architectures and densities. The architecture was characterized through the fabric feature, and the density was represented in terms of the bone volume fraction. Computer simulations of ultrasonic propagation through each of the 15 2-D bone slices were carried out, and the ultrasonic velocity and mean frequency of the received waveforms were evaluated. Results demonstrate that ultrasound propagation is affected by both density and architecture, although there was not a simple linear correlation between the relative degree of structural anisotropy with the ultrasound measurements. This study elucidates further aspects of propagation of ultrasound through bone, and demonstrates as well as the power of computational methods for ultrasound research in general and tissue and bone characterization in particular. (C) 1999 World Federation for Ultrasound in Medicine & Biology.
In the wake of numerous sequenced genomes becoming available, computational methods for the reconstruction of metabolic networks have received considerable attention Here, we review recent methods and software tools u...
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In the wake of numerous sequenced genomes becoming available, computational methods for the reconstruction of metabolic networks have received considerable attention Here, we review recent methods and software tools useful along the reconstruction workflow, from sequence annotation and network assembly to model verification and testing against experimental data Reconstruction methods can be divided into three categories, depending on the magnitude of network context which is taken into account in the process of assembling the metabolic model First, each enzyme may be predicted independently by annotation transfer or machine learning methods Second, the presence of a metabolic pathway may be detected from genome and experimental evidence, often utilizing a reference pathway database. Third, the method may attempt to directly reconstruct a consistent metabolic network without relying on predefined reference pathways. Regardless of the chosen context, all methods strive to reconstruct genome-scale metabolic reconstructions. Currently a gap exists between software platforms dedicated to genome annotation and computational tools for automatically repairing network inconsistencies and validating against measurement data. We argue that to accelerate the reconstruction efforts, computational tools need to be developed that bridge the phases of the reconstruction workflow. In particular, the goal of finding consistent metabolic models suitable for computational analysis should be taken into account already in the beginning phases of reconstruction.
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