Classical force field parameters for two high-affinity ligands of FKBP12

FKBP12 is an important target in the treatment of transplant rejection and is also a promising target for cancer and neurodegenerative diseases. We determined for two ligands of nanomolar affinity the set of parameters in the CHARMM force field. The fitting procedure was based on reproducing the quantum chemistry data (distances, angles, and energies). Since the dynamical behavior of such ligands strongly depends on the dihedral angles, care was taken to derive the corresponding parameters. Moreover, since each of the central core region of these two ligands is similar to other known ligands or drugs of other proteins, part at least of these parameters could also be useful for these other ligands.     

Optimization of parameters of nonbonded interactions in a spectroscopically determined force field

A procedure is given by which parameters of nonbonded interactions in a molecular mechanics energy function can be optimized for maximum compatibility with ab initio force fields and structures. The method is based on a previously derived transformation of ab initio valence parameters to the molecular mechanics formalism. Explicit analytical expressions for the derivatives of the molecular mechanics force constants and reference geometry parameters with respect to the parameters of the nonbonded interactions are derived. The form of the goodness-of-fit function is discussed. A first application to a set of alanine dipeptides is described.     

Interactive graphical optimization of potential energy function parameters in the consistent force field

The performance of a molecular mechanics force field depends on the form of its potential energy function as well as on their parametrization. In the consistent force field (CFF), the fundamentally empirical nature of potential energy functions is recognized by their refinement through optimization which is an integral part of the CFF concept. A graphical interface to the optimization algorithm has been developed with the dual purposes of compressing large amounts of numerical data into one intuitive comprehensible picture of the residue functions and giving the user interactive control of the optimization process. The principles of force field optimization are outlined, with emphasis on the design and realization of the graphical interface.     

A neural network approach for approximate force response analyses of a bridge population

In this paper, artificial neural networks (ANNs) are used to develop an efficient method for rapid and approximate force response analyses of a bridge population. The single-span reinforced concrete T-beam bridge population in Pennsylvania State is taken as a particular case study. First, a statistical analysis is conducted to examine implicit and explicit dependencies between various geometrical and structural parameters of the bridges, and the governing bridge parameters are identified along with their ranges of variation within the population. Then, a set of sample bridges are randomly generated using different combinations of the governing parameters within their predefined ranges of variation. An exact finite element analysis is implemented for each sample bridge, and the maximum moment and shear responses in beams are obtained at critical locations under various combinations of standard truck loads. An ANN is implemented to learn the relationship between the bridge parameters (inputs) and responses (outputs) based on the sample set and to make predictions for other bridges that are not present in the set. The performances of a variety of different ANN architectures are tested, and their prediction capabilities are measured and compared.     

Continuous force field analysis for generalized gradient vector flow field

We propose a modification of the generalized gradient vector flow field techniques based on a continuous force field analysis. At every iteration the generalized gradient vector flow method obtains a new, improved vector field. However, the numerical procedure always employs the original image to calculate the gradients used in the source term. The basic idea developed in this paper is to use the resulting vector field to obtain an improved edge map and use it to calculate a new gradient based source term. The improved edge map is evaluated by new continuous force field analysis techniques inspired by a preceding discrete version. The approach leads to a better convergence and better segmentation accuracy as compared to several conventional gradient vector flow type methods.     

基于拓扑子集的势场原子类型的派定

对于除了标准氨基酸、核酸残基以外的一般分子,派定分子中原子的原子类型,确定原子类型在不同分子势场之间的转换,这些工作一般是由人工来完成。本文从分子拓扑学的角度解析了分子势场的原子类型(atom type)定义,以基于分子拓扑子集取代原子类型定义的分子片断为途径,实现势场原子类型的计算机自动派定。该方法易于编程,并能满足用户调整原子类型的意愿。     

基于近似最小距离场的二维图像骨架提取方法

提出了基于近似最小距离场提取二值图像的8-连通骨架的算法。该算法对图像中的每个像素根据其与边界的相对距离进行整数编码,形成近似最小距离场,将该距离场中的几何邻接的、具有局部最大值的像素形成聚类,对聚类进行细化,用最短路径将不同的细化后的聚类连接起来。该算法简单,将其在实验数据集上进行实验,结果证明算法具有很高的效率。     

Determination of back-pressure profile for forward extrusion using sequential approximate optimization

This paper proposes a method for determining optimal back-pressure profile in forging of aluminum alloy using a sequential approximate optimization (SAO). In forging, it is important to improve the mold filling for the product quality. In addition, it is preferable to produce a product with a minimum forming energy. To achieve these objectives simultaneously, a forging method with back-pressure profile is proposed. Here, the back-pressure profile implies that the back-pressure varies through the stroke. In this paper, a multi-objective optimization (MOO) problem is formulated. To improve the mold filling, an unfilled area is taken as the first objective function. Furthermore, a forming energy during the forging is taken as the second objective function. Numerical simulation in the forging is so expensive that the SAO using the radial basis function (RBF) network is adopted, and the pareto-frontier is identified with a small number of simulation runs. Based on the numerical result, the experiments are also conducted. It can be found from these results that, the back-pressure profile approach is valid for improving the mold filling as well as the forming energy.     

The approximate reanalysis method for topology optimization under harmonic force excitations with multiple frequencies

In mode acceleration method for topology optimization related harmonic response with multiple frequencies, most of the computation effort is invested in the solution of the eigen-problem. This paper is focused on reduction of the computational effort in repeated solution of the eigen-problem involved in mode acceleration method. The block combined approximation with shifting method is adopted for eigen-problem reanalysis, which simultaneously calculates some eigenpairs of modified structures. The triangular factorizations of shifted stiffness matrices generated within a certain number of design iterations are utilized to calculate the modes. For improving computational efficiency, Basic Linear Algebra Subprograms (BLAS) are utilized. The reanalysis method is based on matrix-matrix operations with Level-3 BLAS and can provide very fast development of approximate solutions of high quality for frequencies and associated mode shapes of the modified structure. Numerical examples are given to demonstrate the efficiency of the proposed topology optimization procedure and the accuracy of the approximate solutions.     

外激励参数未知系统的同步控制及其参数识别

考虑外激励的振幅和频率未知的混沌系统.把系统未知参数扩张成系统的新的状态量,构造新的驱动系统.用参数自适应控制方法构造一个响应系统,使之与驱动系统的结构相同.基于级联系统的稳定性理论,通过两个步骤来设计控制器和参数自适应律,使得驱动—响应系统能够达到完全同步.当驱动—响应系统达到完全同步时,就可以识别出系统的未知参数振...     

High-aspect-ratio microstructure filling by centrifugal force field modeling

This paper addresses the influence of centrifugal force and surface tension on the fluid filling processes in high-aspect-ratio microstructures. The microstructure was treated as a porous media. Numerical solutions are obtained for different parameters that governing the fluid filling flow phenomena. It was found that at certain high rotation speed of the filling system, efficient filling can be attained regardless surface is hydrophobic or hydrophilic. The pressure distribution during the filling process is also addressed. It is found that pressure variations along the filling length were almost in linear fashion from inlet pressure to the capillary pressure for both complete and incomplete filling.This work was supported by the National Science Council (series no. NSC91-2218-E-005-001) of Taiwan. The National Synchrotron Radiation Research Center (NSRRC) provided synchrotron radiation for fabricating high-aspect-ratio PMMA molds is acknowledged.     

Simplified AutoDock force field for hydrated binding sites

A set of high quality structures of protein-ligand complexes with experimentally determined binding affinities has been extracted from the Protein Data Bank and used to test and recalibrate AutoDock force field. Since for some binding sites water molecules are crucial for bridging the receptor-ligand interactions, they have to be included in the analysis. To simplify the process of incorporating water molecules into the binding sites and make it less ambiguous, new simple water model was created. After recalibration of the force field on the new dataset much better correlation between the computed and experimentally determined binding affinities was achieved and the quality of pose prediction improved even more.     

Adaptive fuzzy force control of manipulators with unknown environment parameters

This article proposes an adaptive fuzzy control scheme for explicit force control of a robot manipulator in contact with an environment whose parameters are unknown and vary considerably. The scheme consists of three main components: a reference force model describing the desired behavior of the force control system, a fuzzy force controller that determines the adjustment to the position control loop, and a fuzzy learning and adaptation mechanism that modifies the fuzzy force controller according to the difference between the actual and desired force responses. The modification is performed by shifting and contracting/expanding the membership functions of the fuzzy sets associated with the consequent rules of the fuzzy force controller. It is demonstrated, through simulations of a two-link manipulator and a 6-DOF industrial robot, that the scheme is capable force tracking despite wide parameter variations, such as when the environment stiffness changes by several orders of magnitude. © 1997 John Wiley & Sons, Inc.     

Multi-objective optimization of volume shrinkage and clamping force for plastic injection molding via sequential approximate optimization

Process parameters in plastic injection molding (PIM), such as the packing pressure, the mold temperature, the melt temperature, and so on, are generally determined by a trial-and error method through the experiments. Computer-aided engineering (CAE) in the PIM is an alternative approach to determine the optimal process parameters. In cap-type plastic product, large volume shrinkage makes the clamping difficult. Furthermore, small clamping force leads to high productivity as well as cost reduction. Both volume shrinkage and clamping force should then be minimized simultaneously, and a multi-objective design optimization is formulated. Inappropriate process parameters easily lead to short shot that the melt plastic is not fully filled into cavity. In this paper, short shot is handled as the design constraint. Numerical simulation of the PIM is so expensive that the response surface approach is valid. In particular, a sequential approximate optimization (SAO) that the response surface is repeatedly constructed and optimized with some new sampling points is recognized as one of the most powerful tools available. In this paper, the radial basis function (RBF) network is adopted for the SAO, and the pareto-frontier is identified with a small number of simulation runs. Numerical result shows that the pareto-frontier is well identified with a small number of simulation runs.     

On the equivalence of approximate stationary axially symmetric solutions of the Einstein field equations

We study stationary axially symmetric solutions of the Einstein vacuum field equations that can be used to describe the gravitational field of astrophysical compact objects in the limiting case of slow rotation and slight deformation. We derive explicitly the exterior Sedrakyan–Chubaryan approximate solution, and express it in an analytical form, which makes it practical in the context of astrophysical applications. In the limiting case of vanishing angular momentum, the solution reduces to the well-known Schwarzschild solution in vacuum. We demonstrate that the new solution is equivalent to the exterior Hartle–Thorne solution. We establish mathematical equivalence between the Sedrakyan–Chubaryan, Fock–Abdildin and Hartle–Thorne formalisms.     

Lorentz force based magnetic field sensor with optical readout

A miniaturized sensor capable for measuring high magnetic flux densities is presented. The magnetic flux density is converted into a movement of a micro machined U-shaped cantilever, which bears a thin film lead. The cantilever movement is accomplished by the Lorentz force acting on the electrical current. The cantilever poses as a deflecting mirror in an optical readout system. The ratio of the intensity of the light reflected by the front side of the cantilever to the intensity of the incident light is analyzed. The optical conversion principle was proven experimentally. It is well described by an optical near field model. To overcome measurement problems caused by the deformation due to mechanically prestressed cantilevers, an ac excitation was used for sensor characterization. A measurement range of the current–flux density product of 2.2 mA T was achieved by evaluating the peak light intensity. Beyond this limit more sophisticated signal analysis has to be applied. Depending on the rest position, a magnetic flux density of about 10 mT can be resolved with a current of 10 mA. The target of an upper limit of 50 T can be achieved by reducing the electrical current.     

On the estimation of Markov random field parameters

We examine the histogram method for estimating the parameters associated with a Markov random field. This method relies on the estimation of the local interaction sums from histogram data. We derive an estimator for these quantities that is optimal in a well-defined sense. Furthermore, we show that the final step of the histogram method, the solution of a least-squares problem, can be done substantially faster than one might expect if no equation culling is used. We also examine the use of weighted least-squares and see that this seems to lead to better estimates even with small amounts of data