Clemaps: Multiple Alignment Of Protein Structures Based On Conformational Letters

CLEMAPS is a tool for multiple alignment of protein structures. It distinguishes itself from other existing algorithms for multiple structure alignment by the use of conformational letters, which are discretized states of 3D segmental structural states. A letter corresponds to a cluster of combinations of three angles formed by C-alpha pseudobonds of four contiguous residues. A substitution matrix called CLESUM is available to measure the similarity between any two such letters. The input 3D structures are first converted to sequences of conformational letters. Each string of a fixed length is then taken as the center seed to search other sequences for neighbors of the seed, which are strings similar to the seed. A seed and its neighbors form a center-star, which corresponds to a fragment set of local structural similarity shared by many proteins. The detection of center-stars using CLESUM is extremely efficient. Local similarity is a necessary, but insufficient, condition for structural alignment. Once center-stars are found, the spatial consistency between any two stars are examined to find consistent star duads using atomic coordinates. Consistent duads are later joined to create a core for multiple alignment, which is further polished to produce the final alignment. The utility of CLEMAPS is tested on various protein structure ensembles.

Fast Discrimination of Commerical Corn Varieties Based on Near Infrared Spectra

The existing methods for the discrimination of varieties of commodity corn seed are unable to process batch data and speed up identification, and very time consuming and costly. The present paper developed a new approach to the fast discrimination of varieties of commodity corn by means of near infrared spectral data. Firstly, the experiment obtained spectral data of 37 varieties of commodity corn seed with the Fourier transform near infrared spectrometer in the wavenurnber range from 4 000 to 12 000 cm (1). Secondly, the original data were pretreated using statistics method of normalization in order to eliminate noise and improve the efficiency of models. Thirdly, a new way based on sample standard deviation was used to select the characteristic spectral regions, and it can search very different wavenumbers among all wavenumbers and reduce the amount of data in part. Fourthly, principal component analysis (PCA) was used to compress spectral data into several variables, and the cumulate reliabilities of the first ten components were more than 99.98%. Finally, according to the first ten components, recognition models were established based on BPR. For every 25 samples in each variety, 15 samples were randomly selected as the training set. The remaining 10 samples of the same variety were used as the first testing set, and all the 900 samples of the other varieties were used as the second testing set. Calculation results showed that the average correctness recognition rate of the 37 varieties of corn seed was 94.3%. Testing results indicate that the discrimination method had higher precision than the discrimination of various kinds of commodity corn seed. In short, it is feasible to discriminate various varieties of commodity corn seed based on near infrared spectroscopy and BPR.

A meso elastoplastic constitutive model for polycrystalline metals based on equivalent slip systems with latent hardening

A meso material model for polycrystalline metals is proposed, in which the tiny slip systems distributing randomly between crystal slices in micro-grains or on grain boundaries are replaced by macro equivalent slip systems determined by the work-conjugate principle. The elastoplastic constitutive equation of this model is formulated for the active hardening, latent hardening and Bauschinger effect to predict macro elastoplastic stress-strain responses of polycrystalline metals under complex loading conditions. The influence of the material property parameters on size and shape of the subsequent yield surfaces is numerically investigated to demonstrate the fundamental features of the proposed material model. The derived constitutive equation is proved accurate and efficient in numerical analysis. Compared with the self-consistent theories with crystal grains as their basic components, the present theory is much simpler in mathematical treatment.

A Method Based on Digital Image Analysis for Measuring the Strain Field of Deformed Sheet

对薄板成形应变场传统的测量方法进行了研究,指出了其不足和误差的来源,提出了数字图像分析法测量薄板成形中的应变场,对测量原理、新的测量方法对传统方法的改进,以及如何降低误差进行了介绍,指出数字图像分析法的前景,提出了改进意见。

Burst Detection in Turbulent Channel Flows Based on Large Eddy Simulation Databases

Reliable turbulent channel flow databases at several Reynolds numbers have been established by large eddy simulation (LES), with two of them validated by comparing with typical direct numerical simulation (DNS) results. Furthermore, the statistics, such as velocity profile, turbulent intensities and shear stress, were obtained as well as the temporal and spatial structure of turbulent bursts. Based on the LES databases available, the conditional sampling methods are used to detect the structures of burst events. A method to deterimine the grouping parameter from the probability distribution function (pdf) curve of the time separation between ejection events is proposed to avoid the errors in detected results. And thus, the dependence of average burst period on thresholds is considerably weakened. Meanwhile, the average burst-to-bed area ratios are detected. It is found that the Reynolds number exhibits little effect on the burst period and burst-to-bed area ratio.

Parameters Inversion of Fluid-Saturated Porous Media Based on Neural Networks

The multi-layers feedforward neural network is used for inversion of material constants of fluid-saturated porous media. The direct analysis of fluid-saturated porous media is carried out with the boundary element method. The dynamic displacement responses obtained from direct analysis for prescribed material parameters constitute the sample sets training neural network. By virtue of the effective L-M training algorithm and the Tikhonov regularization method as well as the GCV method for an appropriate selection of regularization parameter, the inverse mapping from dynamic displacement responses to material constants is performed. Numerical examples demonstrate the validity of the neural network method.

Formation of Fivefold Deformation Twins in Nanocrystalline Face-Centered-Cubic Copper Based on Molecular Dynamics Simulations

Fivefold deformation twins were reported recently to be observed in the experiment of the nanocrystalline face-centered-cubic metals and alloys. However, they were not predicted previously based on the molecular dynamics (MD) simulations and the reason was thought to be a uniaxial tension considered in the simulations. In the present investigation, through introducing pretwins in grain regions, using the MD simulations, the authors predict out the fivefold deformation twins in the grain regions of the nanocrystal grain cell, which undergoes a uniaxial tension. It is shown in their simulation results that series of Shockley partial dislocations emitted from grain boundaries provide sequential twining mechanism, which results in fivefold deformation twins. (c) 2006 American Institute of Physics.

Intensity Distribution Design for Laser-Induced Thermal Loading Based on Numerical Simulation

To accomplish laser-induced thermal loading simulation tests for pistons,the Gaussian beam was modulated into multi-circular beam with specific intensity distribution.A reverse method was proposed to design the intensity distribution for the laser-induced thermal loading based on finite element(FE) analysis.Firstly,the FE model is improved by alternating parameters of boundary conditions and thermal-physical properties of piston material in a reasonable range,therefore it can simulate the experimental resul...

A Nanomechanical Device Based on Light-Driven Proton Pumps

In this paper, a hybrid device based on a microcantilever interfaced with bacteriorhodopsin (bR) is constructed. The microcantilever, on which the highly oriented bR film is self-assembled, undergoes controllable and reversible bending when the light-driven proton pump protein, bR, on the microcantilever surface is activated by visible light. Several control experiments are carried out to preclude the influence of heat and photothermal effects. It is shown that the nanomechanical motion is induced by the resulting gradient of protons, which are transported from the KCl solution on the cytoplasmic side of the bR film towards the extracellular side of the bR film. Along with a simple physical interpretation, the microfabricated cantilever interfaced with the organized molecular film of bR can simulate the natural machinery in converting solar energy to mechanical energy.

An analysis of collective damage for short fatigue cracks based on equilibrium of crack numerical density

Collective damage of short fatigue cracks was analyzed in the light of equilibrium of crack numerical density. With the estimation of crack growth rate and crack nucleation rate, the solution of the equilibrium equation was studied to reveal the distinct feature of saturation distribution for crack numerical density. The critical time that characterized the transition of short and long-crack regimes was estimated, in which the influences of grain size and grain-boundary obstacle effect were investigated. Furthermore, the total number of cracks and the first order of damage moment were discussed.

A Label-Free Multisensing Immunosensor Based on Imaging Ellipsometry

An immunosensor based on imaging ellipsometry and its potential applications was demonstrated in this paper. It has been proven a fast, reliable, and convenient method to quantify the thickness distribution of protein layers or detect protein concentration in solution. Combined with a protein chip, the immunosensor was able to detect multiple analytes simultaneously without any labeling. Preliminary results demonstrated how this immunosensor could be used to monitor several independent biospecific binding processes in real-time and in situ conditions.

The Mach reflection of a detonation based on soot track measurements

This paper presents a series of soot tracks formed by gaseous detonation waves diffracting around wedges with different wedge angles. These cellular structure patterns describe the Mach-reflection processes of a detonation and reveal some unique characteristics. They can be used to analyze the relationship between the trajectory angle of the triple point, wedge angle, and initial pressure in Mach reflection. Compared to the Mach-reflected one-dimensional shock wave in nonreactive air, all these unique characteristics for a Mach-reflected detonation should be attributed to the transverse-wave structure of the detonation front; meanwhile, the precursor shock wave and transverse wave influence the Mach-reflected detonation, respectively. The experimental results support the recently published numerical simulation of this complex phenomenon.

Reliable Validation Based on Optical Flow Visualization for CFD Simulations

A reliable validation based on the optical flow visualization for numerical simulations of complex flowfields is addressed in this paper. Several test cases, including two-dimensional, axisymmetric and three-dimensional flowfields, were presented to demonstrate the effectiveness of the validation and gain credibility of numerical solutions of complex flowfields. In the validation, images of these flowfields were constructed from numerical results based on the principle of the optical flow visualization, and compared directly with experimental interferograms. Because both experimental and numerical results are of identical physical representation, the agreement between them can be evaluated effectively by examining flow structures as well as checking discrepancies in density. The study shows that the reliable validation can be achieved by using the direct comparison between numerical and experiment results without any loss of accuracy in either of them.

Size Effects in Micro-bending Deformation of MEMS Devices Based on the Discrete Dislocation Theory

In the present research, the discrete dislocation theory is used to analyze the size effect phenomena for the MEMS devices undergoing micro-bending load. A consistent result with the experimental one in literature is obtained. In order to check the effectiveness to use the discrete dislocation theory in predicting the size effect, both the basic version theory and the updated one are adopted simultaneously. The normalized stress-strain relations of the material are obtained for different plate thickness or for different obstacle density. The prediction results are compared with experimental results.

Asymptotic analysis based on K-S constitutive law for a rubber wedge compressed by a line load at its tip

In the present paper, a rubber wedge compressed by a line load at its tip is asymptotically analyzed using a special constitutive law proposed by Knowles and Sternberg (K-S elastic law) [J. Elasticity 3 (1973) 67]. The method of dividing sectors proposed by Gao [Theoret. Appl. Fract, Mech. 14 (1990) 219] is used. Domain near the wedge tip can be divided into one expanding sector and two narrowing sectors. Asymptotic equations of the strain-stress field near the wedge tip are derived and solved numerically. The deformation pattern near a wedge tip is completely revealed. A special case. i.e. a half space compressed by a line load is solved while the wedge angle is pi.