A multicolour SOR method for the finite-element method

In this paper we present several algorithms to reorder unknowns in a finite-element mesh so that we can use the multicolour SOR method to solve the corresponding linear system on a pipelined computer or on a parallel computer. We also discuss the assembling process by reordering elements with our algorithms. Numerical tests on a pipelined computer indicate the efficiency of the multicolour SOR method.     

BILED／BILD组合回路的光学逻辑运算

利用激光二极管或发光二极管混合双稳态回路(BILD/BILED)的组合,得到了光学多稳态,光学异或逻辑门和光学R-S触发器.这种光电子学的逻辑回路与大规模集成技术完全相容,因此有希望应用于光学信息处理,光通信和光计算.     

One-step assembly of carbamoyl substituted annulated 1,4-oxazepines

We present a convenient synthesis of heterocyclic scaffolds using a novel modification of four-component Ugi condensation. Two complementary variants of this useful synthetic strategy provide an efficient one-step assembly of four novel pharmaceutically relevant (hetero)aryl-fused 1,4-oxazepines with different substituents’ profile.     

High throughput N-modular redundancy for error correction design of memristive stateful logic

Memristive stateful logic is one of the most promising candidates to implement an in-memory computing system that computes within the storage unit. It can eliminate the costs for the data movement in the traditional von Neumann system. However, the instability in the memristors is inevitable due to the limitation of the current fabrication technology, which incurs a great challenge for the reliability of the memristive stateful logic. In this paper, the implication of device instability on the reliability of the logic event is simulated. The mathematical relationship between logic reliability and redundancy has been deduced. By combining the mathematical relationship with the vector-matrix multiplication in a memristive crossbar array, the logic error correction scheme with high throughput has been proposed. Moreover, a universal design paradigm has been put forward for complex logic. And the circuit schematic and the flow of the scheme have been raised. Finally, a 1-bit full adder (FA) based on the NOR logic and NOT logic is simulated and the mathematical evaluation is performed. It demonstrates the scheme can improve the reliability of the logic significantly. And compared with other four error corrections, the scheme which can be suitable for all kinds of R-R logics and V-R logics has the best universality and throughput. Compared with the other two approaches which also need additional complementary metal-oxide semiconductor (CMOS) circuits, it needs fewer transistors and cycles for the error correction.     

建筑风压数值模拟的几种并行化策略

针对四个处理机的Ｔｒａｎｓｐｕｔｅｒ并行计算机系统，建立了建筑风压数值模拟问题基于ＳＩＭ－ＰＬＥＣ算法的几种并行化策略：分区并行策略、方程并行策略和双重并行策略。对各种策略的计算流程、数据通讯及并行效率等进行了分析和比较，并通过实例计算作了验证。     

Flow and heat transfer in a moving fluid over a moving flat surface

In this paper, a numerical analysis of the momentum and heat transfer of an incompressible fluid past a parallel moving sheet based on composite reference velocity U is carried out. A single set of equations has been formulated for both momentum and thermal boundary layer problems containing the following parameters: r the ratio of the free stream velocity to the composite reference velocity, σ (Prandtl number) the ratio of the momentum diffusivity of the fluid to its thermal diffusivity, and E _c (E _ck ) (Eckert number). The present study has been carried out in the domain 0 ≤ r ≤ 1. It is found that the direction of the wall shear changes in such an interval and an increase of the parameter r yields an increase in temperature.      

防护林带：湍流的数学模型与计算机模拟

虽然防护林用于减小风速、控制热量和水汽传递及污染物扩散、 改善气候与环境、增加作物产量等已经有几百年了, 但直到近几十年, 人们才开始系统地研究防护林空气动力学的遮蔽机制.在本综述中,我 们考察了绕防护林带的流动与湍流控制机制,最新的模型与数值模拟 研究情况;通过数值模拟与实验数据的比较,来了解防护林带结构与防 风效果之间的关系;讨论数值分析如何及为什么能够得到所需要的结果. 本文将从多孔隙防护林带流动基本方程组的推导开始,讨论数值模型及 模拟过程,对附体与分离流动进行预测;分析了遮蔽机制与动量交换;对 风向、防护林密度、宽度和三维性对流动与湍流的影响作了系统的论 述.还对热流和土壤水分蒸发的新模型及数值模拟作了简述.最后,我们 对网络工作站、群和高性能分布式并行计算机及其对防护林带模型预 报能力的提高作了讨论.     

Prediction and simulation of wear response of Linz–Donawitz (LD) slag filled glass–epoxy composites using neural computation

This article reports on the implementation of a soft computing technique based on artificial neural networks (ANNs) in analyzing the wear performance of a new class of hybrid composites filled with Linz–Donawitz slag (LDS). LDS is a major solid waste generated in huge quantities during steel making. It comes from slag formers such as burned lime/dolomite and from oxidizing of silica, iron etc. while refining the iron into steel in the LD furnace. In this work, hybrid composites consisting of short glass fiber (SGF) reinforced epoxy filled with different LDS content (0, 7.5, 15 and 22.5 wt%) are prepared by simple hand lay‐up technique. Solid particle erosion trials, as per ASTM G 76 test standards, are conducted on the composite samples following a well‐planned experimental schedule based on Taguchi design of experiments. Significant process parameters predominantly influencing the rate of erosion are identified. The study reveals that the LDS content is the most significant among various factors influencing the wear rate of these composites. Further, a model based on ANN for the prediction of erosion performance of these composites is implemented. The ANN prediction profiles for the characteristic wear properties exhibit very good agreement with the measured results demonstrating that a well‐trained network has been created. The simulated results explaining the effect of significant process variables on the wear rate indicate that the trained neural network possesses enough generalization capability of predicting wear rate even beyond the experimental range. Copyright © 2014 John Wiley & Sons, Ltd.     

Enhanced conformational sampling method for proteins based on the TaBoo SeArch algorithm: Application to the folding of a mini‐protein,chignolin

The conformational samplings are indispensible for obtaining reliable canonical ensembles, which provide statistical averages of physical quantities such as free energies. However, the samplings of vast conformational space of biomacromolecules by conventional molecular dynamics (MD) simulations might be insufficient, due to their inadequate accessible time‐scales for investigating biological functions. Therefore, the development of methodologies for enhancing the conformational sampling of biomacromolecules still remains as a challenging issue in computational biology. To tackle this problem, we newly propose an efficient conformational search method, which is referred as TaBoo SeArch (TBSA) algorithm. In TBSA, an inverse energy histogram is used to select seeds for the conformational resampling so that states with high frequencies are inhibited, while states with low frequencies are efficiently sampled to explore the unvisited conformational space. As a demonstration, TBSA was applied to the folding of a mini‐protein, chignolin, and automatically sampled the native structure (C_α root mean square deviation < 1.0 Å) with nanosecond order computational costs started from a completely extended structure, although a long‐time 1‐µs normal MD simulation failed to sample the native structure. Furthermore, a multiscale free energy landscape method based on the conformational sampling of TBSA were quantitatively evaluated through free energy calculations with both implicit and explicit solvent models, which enable us to find several metastable states on the folding landscape. © 2015 Wiley Periodicals, Inc.     

“Parallel factor analysis of multi-excitation ultraviolet resonance Raman spectra for protein secondary structure determination”

Protein secondary structural analysis is important for understanding the relationship between protein structure and function, or more importantly how changes in structure relate to loss of function. The structurally sensitive protein vibrational modes (amide I, II, III and S) in deep-ultraviolet resonance Raman (DUVRR) spectra resulting from the backbone C–O and N–H vibrations make DUVRR a potentially powerful tool for studying secondary structure changes. Experimental studies reveal that the position and intensity of the four amide modes in DUVRR spectra of proteins are largely correlated with the varying fractions of α-helix, β-sheet and disordered structural content of proteins. Employing multivariate calibration methods and DUVRR spectra of globular proteins with varying structural compositions, the secondary structure of a protein with unknown structure can be predicted. A disadvantage of multivariate calibration methods is the requirement of known concentration or spectral profiles. Second-order curve resolution methods, such as parallel factor analysis (PARAFAC), do not have such a requirement due to the “second-order advantage.” An exceptional feature of DUVRR spectroscopy is that DUVRR spectra are linearly dependent on both excitation wavelength and secondary structure composition. Thus, higher order data can be created by combining protein DUVRR spectra of several proteins collected at multiple excitation wavelengths to give multi-excitation ultraviolet resonance Raman data (ME-UVRR). PARAFAC has been used to analyze ME-UVRR data of nine proteins to resolve the pure spectral, excitation and compositional profiles. A three factor model with non-negativity constraints produced three unique factors that were correlated with the relative abundance of helical, β-sheet and poly-proline II dihedral angles. This is the first empirical evidence that the typically resolved “disordered” spectrum represents the better defined poly-proline II type structure.