993 research outputs found
Exact arithmetic as a tool for convergence assessment of the IRM-CG method
Using exact computer arithmetic, it is possible to determine the (exact)
solution of a numerical model without rounding error. For such purposes, a
corresponding system of equations should be exactly defined, either directly or
by rationalisation of numerically given input data. In the latter case there is
an initial round off error, but this does not propagate during the solution
process. If this system is first exactly solved, then by the floating-point
arithmetic, convergence of the numerical method is easily followed. As one
example, IRM-CG, a special case of the more general Iterated Ritz method and
interesting replacement for a standard or preconditioned CG, is verified.
Further, because the computer demands and execution time grow enourmously with
the number of unknowns using this strategy, the possibilities for larger
systems are also provided.Comment: 12 page
An overview of Forward Dynamics Algorithms and their use in Open Source Dynamics Engines
Simulation of real-world dynamics is of major importance in testing and verifying developed industrial concepts and solutions, developing and verifying potential control paradigms, scientific research, learning and training tools, or the entertainment industry as a basis for a game engine. The module of the 3D virtual simulator that achieves simulation of the real-world behaviour such as rigid and elastic body dynamics, particle dynamics, fluid dynamics, electrodynamics, magnetism, etc., is often referred to as a dynamics engine or physics engine. The core of the rigid body dynamics (physics) engine is the solution to the forward dynamics problem, which is defined as finding a rigid body's path, velocity, and acceleration for a given input actuating torque and external forces. The past few decades saw a considerable amount of research in robot dynamics modelling, and there are many methods for robot dynamic model development available in the literature. The most commonly used algorithms for solving robot forward dynamics problem are the Composite-Rigid-Body Algorithm (CRBA) [1] and the Articulated-Body Algorithm (ABA) [2]. CRBA and ABA are reduced coordinate methods where known constraints, such as joints, are embedded in the formulation of the equations of motion. Besides reduced coordinate methods, there are maximal coordinate methods using Lagrange multipliers [3-4] to enforce constraints using constraint reaction forces
Self-organising management of Grid environments
This paper presents basic concepts, architectural principles and algorithms for efficient resource and security management in cluster computing environments and the Grid. The work presented in this paper is funded by BTExacT and the EPSRC project SO-GRM (GR/S21939)
MicroRNA-222 regulates muscle alternative splicing through Rbm24 during differentiation of skeletal muscle cells
A number of microRNAs have been shown to regulate skeletal muscle development and differentiation. MicroRNA-222 is downregulated during myogenic differentiation and its overexpression leads to alteration of muscle differentiation process and specialized structures. By using RNA-induced silencing complex (RISC) pulldown followed by RNA sequencing, combined with in silico microRNA target prediction, we have identified two new targets of microRNA-222 involved in the regulation of myogenic differentiation, Ahnak and Rbm24. Specifically, the RNA-binding protein Rbm24 is a major regulator of muscle-specific alternative splicing and its downregulation by microRNA-222 results in defective exon inclusion impairing the production of muscle-specific isoforms of Coro6, Fxr1 and NACA transcripts. Reconstitution of normal levels of Rbm24 in cells overexpressing microRNA-222 rescues muscle-specific splicing. In conclusion, we have identified a new function of microRNA-222 leading to alteration of myogenic differentiation at the level of alternative splicing, and we provide evidence that this effect is mediated by Rbm24 protei
Effect of gut active carbohydrates on plasma IgG concentrations in piglets and calves
Improving immune status in neonates is crucial to health and production. Gut active carbohydrates (GAC) have been associated with increasing immunoglobin levels and immonucompetence development in mammals. The objective of the following studies was to evaluate whether GAC (mannan-oligosaccharides) applied orally to progeny immediately following parturition, improved blood plasma immunoglobulin (Ig) type G concentrations in piglets and calves. Three trials were conducted comparing control groups with those receiving GAC orally. The first two trials used piglets that were monitored for blood IgG at 2 days of age and for changes in body weight (BW), and the third trial monitored calf IgG from birth to 21 days of age. Piglets in the experimental group received 0.75 g GAC in 10 ml saline at birth and 24 h of age. The calf trial compared the control group against calves that received 22.5 g GAC mixed into 4.5 l of colostrum (to give 5 g/l) in the first 24 h after parturition. Blood serum samples were taken at 2 days post partum in piglets, and at several time points from 6 h to 21 days of age in calves, and were analysed for IgG levels by radial immunodiffusion. In the first piglet trial, significantly higher levels (32%) of IgG were observed for piglets fed GAC (P < 0.001), and in the second, IgG concentration was elevated by 23% (P < 0.01) and BW increased by 9% (P = 0.023) with GAC supplementation. Significant improvements for calves were recorded at all time points in those fed GAC (P < 0.05), with an increase in serum IgG observed after the first day, which was maintained throughout the sampling period, resulting in a difference of 39% at the end of the trial (21 d). These findings form a basis for further studies, which are required to investigate possible modes of action involved in enhancing blood immunoglobulin concentrations in young animals, and the longer-term effects this may have on the development of the immune respons
Saturated VSD model of a six-phase induction machine
In this paper, a saturated model of an asymmetrical six-phase induction machine is presented. The model is based on the vector space decomposition approach, and it includes main and leakage flux saturation, as well as the mutual coupling between orthogonal planes, while using the Gamma equivalent circuit approach. The accuracy of the proposed model in unbalanced operating modes that are characteristic for multiphase machines, such as post-fault and power sharing operation, makes it advantageous compared to existing models. The model is developed assuming that the machine operates in asymmetrical conditions and that, therefore, there is fundamental frequency excitation in both planes. The inter-plane coupling effect is examined using finite element analysis and an experimental procedure for its quantification is developed. The model is verified by comparison with the experimental results obtained from a prototype asymmetrical six-phase induction machine, and its advantages compared to existing models are emphasized
Lattice dynamics of FeSb2
The lattice dynamics of FeSb2 is investigated by the first-principles DFT
calculations and Raman spectroscopy. All Raman and infra-red active phonon
modes are properly assigned. The calculated and measured phonon energies are in
good agreement except for the B3g symmetry mode. We have observed strong mixing
of the Ag symmetry modes, with the intensity exchange in the temperature range
between 210 K and 260 K. The Ag modes repulsion increases by doping FeSb2 with
Co. There are no signatures of the electron-phonon interaction for these modes
Introduction of holstein-friesian genes into the Black-pied population
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