A parallel Euler approach for large-scale biological sequence assembly

Biological sequence assembly is an essential step for sequencing the genomes of organisms. Sequence assembly is very computing intensive especially for the large-scale sequence assembly. Parallel computing is an effective way to reduce the computing time and support the assembly for large amount of biological fragments. Euler sequence assembly algorithm is an innovative algorithm proposed recently. The advantage of this algorithm is that its computing complexity is polynomial and it provides a better solution to the notorious “repeat” problem. This paper introduces the parallelization of the Euler sequence assembly algorithm. All the Genome fragments generated by whole genome shotgun (WGS) will be assembled as a whole rather than dividing them into groups which may incurs errors due to the inaccurate group partition. The implemented system can be run on supercomputers, network of workstations or even network of PC computers. The experimental results have demonstrated the performance of our system.

Large-scale biological sequence assembly and alignment by using computing grid

Large-scale sequence assembly and alignment are fundamental parts of biological computing. However, most of the large-scale sequence assembly and alignment require intensive computing power and normally take very long time to complete. To speedup the assembly and alignment process, this paper parallelizes the Euler sequence assembly and pair-wise/multiple sequence assembly, two important sequence assembly methods, and takes advantage of Computing Grid which has a colossal computing capacity to meet the large-scale biological computing demand.

Eulerian superpath approach to correct sequencing error in shotgun assembly

This work describes an error correction method based on the Euler Superpath problem. Sequence data is mapped to an Euler Superpath dynamically by Merging Transformation. With restriction and guiding rules, data consistency is maintained and error paths are separated from correct data: Error edges are mapped to the correct ones and after substitution (of error edges with right paths), corresponding errors in the sequencing data are eliminated.

A parallel DNA fragment assembly algorithm based on eulerian superpath approach

Fragments assembly is among the core problems in the research of Genome. Although many assembly tools based on the "overlap-layout-consensus" paradigm are widely used such as in the Human Genome Project currently, they still can not resolve the "repeats problem" in the DNA sequencing. For the purpose of resolving such problem, Pevzner et al. put forward a new Euler Superpath assembly algorithm. But it needs a big and complex de Bruijin graph which consumes large amounts of memories i.e. becomes the bottleneck of the performance. We present a parallel DNA fragment assembly algorithm based on the Eularian Superpath theory and solve the bottleneck in the current assembly program. The experimental results demonstrate that our approach has a good scalability, and can be used in DNA assembly of middle and large size of eukaryote genome.

Conversion of the hot torsion test results into flow curve with multiple regimes of hardening

The method of Fields and Backofen has been commonly used to reduce the data obtained by hot torsion test into flow curves. The method, however, is most suitable for materials with monotonic strain hardening behaviour. Other methods such as Stüwe’s method, tubular specimens, differential testing and the inverse method, each suffer from similar drawbacks. It is shown in the current work that for materials with multiple regimes of hardening any method based on an assumption of constant hardening indices introduces some errors into the flow curve obtained from the hot torsion test. Therefore such methods do not enable accurate prediction of onset of recrystallisation where slow softening occurs. A new method to convert results from the hot torsion test into flow curves by taking into account the variation of constitutive parameters during deformation is presented. The method represents the torque twist data by a parametric linear least square model in which Euler and hyperbolic coefficients are used as the parameters. A closed form relationship obtained from the mathematical representation of the data is employed next for flow stress determination. Two different solution strategies, the method of normal equations and singular value decomposition, were used for parametric modelling of the data with hyperbolic basis functions. The performance of both methods is compared. Experimental data obtained by FHTTM, a flexible hot torsion test machine developed at IROST, for a C–Mn austenitic steel was used to demonstrate the method. The results were compared with those obtained using constant strain and strain rate hardening characteristics.

Detection of curved edges at subpixel accuracy using deformable models

One approach to the detection of curves at subpixel accuracy involves the reconstruction of such features from subpixel edge data points. A new technique is presented for reconstructing and segmenting curves with subpixel accuracy using deformable models. A curve is represented as a set of interconnected Hermite splines forming a snake generated from the subpixel edge information that minimizes the global energy functional integral over the set. While previous work on the minimization was mostly based on the Euler-Lagrange transformation, the authors use the finite element method to solve the energy minimization equation. The advantages of this approach over the Euler-Lagrange transformation approach are that the method is straightforward, leads to positive m-diagonal symmetric matrices, and has the ability to cope with irregular geometries such as junctions and corners. The energy functional integral solved using this method can also be used to segment the features by searching for the location of the maxima of the first derivative of the energy over the elementary curve set.

Running in a minimalist and lightweight shoe is not the same as running barefoot : a biomechanical study

Aim The purpose of this study was to determine the changes in running mechanics that occur when highly trained runners run barefoot and in a minimalist shoe, and specifically if running in a minimalist shoe replicates barefoot running.

Methods Ground reaction force data and kinematics were collected from 22 highly trained runners during overground running while barefoot and in three shod conditions (minimalist shoe, racing flat and the athlete's regular shoe). Three-dimensional net joint moments and subsequent net powers and work were computed using Newton-Euler inverse dynamics. Joint kinematic and kinetic variables were statistically compared between barefoot and shod conditions using a multivariate analysis of variance for repeated measures and standardised mean differences calculated.

Results There were significant differences between barefoot and shod conditions for kinematic and kinetic variables at the knee and ankle, with no differences between shod conditions. Barefoot running demonstrated less knee flexion during midstance, an 11% decrease in the peak internal knee extension and abduction moments and a 24% decrease in negative work done at the knee compared with shod conditions. The ankle demonstrated less dorsiflexion at initial contact, a 14% increase in peak power generation and a 19% increase in the positive work done during barefoot running compared with shod conditions.

Conclusions Barefoot running was different to all shod conditions. Barefoot running changes the amount of work done at the knee and ankle joints and this may have therapeutic and performance implications for runners.

A study on compressive anisotropy and nonassociated flow plasticity of the AZ31 Magnesium Alloy in hot rolling

Effect of anisotropy in compression is studied on hot rolling of AZ31 magnesium alloy with a three-dimensional constitutive model based on the quadratic Hill48 yield criterion and nonassociated flow rule (non-AFR). The constitutive model is characterized by compressive tests of AZ31 billets since plastic deformations of materials are mostly caused by compression during rolling processes. The characterized plasticity model is implemented into ABAQUS/Explicit as a user-defined material subroutine (VUMAT) based on semi-implicit backward Euler's method. The subroutine is employed to simulate square-bar rolling processes. The simulation results are compared with rolled specimens and those predicted by the von Mises and the Hill48 yield function under AFR. Moreover, strip rolling is also simulated for AZ31 with the Hill48 yield function under non-AFR. The strip rolling simulation demonstrates that the lateral spread generated by the non-AFR model is in good agreement with experimental data. These comparisons between simulation and experiments validate that the proposed Hill48 yield function under non-AFR provides satisfactory description of plastic deformation behavior in hot rolling for AZ31 alloys in case that the anisotropic parameters in the Hill48 yield function and the non-associated flow rule are calibrated by the compressive experimental results.

Convergence of object focused simultaneous estimation of optical flow and state dynamics

The purpose of this study is to prove the convergence of the simultaneous estimation of the optical flow and object state (SEOS) method. The SEOS method utilizes dynamic object parameter information when calculating optical flow in tracking a moving object within a video stream. Optical flow estimation for the SEOS method requires the minimization of an error function containing the object's physical parameter data. When this function is discretized, the Euler-Lagrange equations form a system of linear equations. The system is arranged such that its property matrix is positive definite symmetric, proving the convergence of the Gauss-Seidel iterative methods. The system of linear equations produced by SEOS can alternatively be resolved by Jacobi iterative schemes. The positive definite symmetric property is not sufficient for Jacobi convergence. The convergence of SEOS for a block diagonal Jacobi is proved by analysing the Euclidean norm of the Jacobi matrix. In this paper, we also investigate the use of SEOS for tracking individual objects within a video sequence. The illustrations provided show the effectiveness of SEOS for localizing objects within a video sequence and generating optical flow results.

Anisotropic hardening model based on non-associated flow rule and combined nonlinear kinematic hardening for sheet materials

 A material model for more effective analysis of plastic deformation of sheet materials is presented in this paper. The model is capable of considering the following aspects of plastic deformation behavior of sheet materials: the anisotropy in yielding stresses in different directions by using a quadratic yield function (based on Hill’s 1948 model and stress ratios), the anisotropy in work hardening by introducing non-constant flow stress hardening in different directions, the anisotropy in plastic strains in different directions by using a quadratic plastic potential function and non-associated flow rule (based on Hill’s 1948 model and plastic strain ratios, r-values), and finally some of the cyclic hardening phenomena such as Bauschinger’s effect and transient behavior for reverse loading by using a coupled nonlinear kinematic hardening (so-called Armstrong-Frederick-Chaboche model). Basic fundamentals of the plasticity of the model are presented in a general framework. Then, the model adjustment procedure is derived for the plasticity formulations. Also, a generic numerical stress integration procedure is developed based on backward-Euler method (so-called multistage return mapping algorithm). Different aspects of the model are verified for DP600 steel sheet. Results show that the new model is able to predict the sheet material behavior in both anisotropic hardening and cyclic hardening regimes more accurately. By featuring the above-mentioned facts in the presented constitutive model, it is expected that more accurate results can be obtained by implementing this model in computational simulations of sheet material forming processes. For instance, more precise results of springback prediction of the parts formed from highly anisotropic hardened materials or that of determining the forming limit diagrams is highly expected by using the developed material model.

Variant selection and intervariant crystallographic planes distribution in martensite in a Ti-6Al-4V alloy

The transformation texture was studied in a Ti-6Al-4V alloy for two microstructures produced through different phase transformation mechanisms (i.e. diffusional vs. displacive). Both microstructures revealed qualitatively similar crystallographic texture characteristics, having two main texture components with Euler angles of (90°, 90°, 0°) and (90°, 30°, 0°). However, the overall α texture strength was considerably weaker in the martensitic structure (i.e. displacive mechanism) compared with the α + β microstructure produced through slow cooling (i.e. diffusional mechanism). The intervariant boundary distribution in martensite mostly revealed five misorientations associated with the Burgers orientation relationship. The five-parameter boundary analysis also showed a very strong interface plane orientation texture, with interfaces terminated mostly on the prismatic planes {hki0}, when misorientation was ignored. The highest intervariant boundary populations belonged to the 63.26°/[10 553 ] and 60°/[112 0] misorientations, with length fractions of 0.38 and 0.3, respectively. The former was terminated on (41 3 0), and the latter was a symmetric tilt boundary, terminated on (1 011). The intervariant plane distribution in martensite was determined more by the constraints of the phase transformation than by the relative interface energies.

Continuous finite-time state feedback stabilizers for some nonlinear stochastic systems

This paper is concerned with the problem of finite-time stabilization for some nonlinear stochastic systems. Based on the stochastic Lyapunov theorem on finite-time stability that has been established by the authors in the paper, it is proven that Euler-type stochastic nonlinear systems can be finite-time stabilized via a family of continuous feedback controllers. Using the technique of adding a power integrator, a continuous, global state feedback controller is constructed to stabilize in finite time a large class of two-dimensional lower-triangular stochastic nonlinear systems. Also, for a class of three-dimensional lower-triangular stochastic nonlinear systems, a recursive design scheme of finite-time stabilization is given by developing the technique of adding a power integrator and constructing a continuous feedback controller. Finally, a simulation example is given to illustrate the theoretical results. © 2014 John Wiley & Sons, Ltd.