38 research outputs found
An Application of Kerr Blackhole Fly-Wheel Model to Statistical Properties of QSOs/AGNs
The aim of this work is to demonstrate the properties of the magnetospheric
model around Kerr blackholes (BHs), so-called the fly-wheel (rotation driven)
model. The fly-wheel engine of the BH-accretion disk system is applied to the
statistics of QSOs/AGNs. In the model, the central BH is assumed to be formed
at and obtains nearly maximum but finite rotation energy (
extreme Kerr BH) at the formation stage. The inherently obtained rotation
energy of the Kerr BH is released through an magnetohydrodynamic process. This
model naturally leads finite lifetime of AGN activity.
Nitta et al. (1991) clarified individual evolution of Kerr BH fly-wheel
engine which is parametrized by BH mass, initial Kerr parameter, magnetic field
near the horizon and a dimension-less small parameter. We impose a statistical
model for the initial mass function (IMF) of ensemble of BHs by the
Press-Schechter formalism. By the help of additional assumptions, we can
discuss the evolution of the luminosity function and the spatial number density
of QSOs/AGNs.Comment: 12 pages, 7 figures Fig.7 has been replace
Risk factors of migraine-related brain white matter hyperintensities: an investigation of 186 patients
Brain white matter hyperintensities are more prevalent in migraine patients than in the general population, but the pathogenesis and the risk factors of these hyperintensities are not fully elucidated. The authors analyzed the routine clinical data of 186 migraine patients who were referred to the Outpatient Headache Department of the Department of Neurology, Medical School, University of Pécs, Hungary between 2007 and 2009: 58 patients with white matter hyperintensities and 128 patients without white matter hyperintensities on 3 T MRI. Significant associations between the presence of white matter hyperintensities and longer disease duration (14.4 vs. 19.9 years, p = 0.004), higher headache frequency (4.1 vs. 5.5 attacks/month, p = 0.017), hyperhomocysteinemia (incidence of hyperintensity is 9/9 = 100%, p = 0.009) and thyroid gland dysfunction (incidence of hyperintensity is 8/14 = 57.1%, p = 0.038) were found. These data support the theory that both the disease duration and the attack frequency have a key role in the formation of migraine-related brain white matter hyperintensities, but the effects of comorbid diseases may also contribute to the development of the hyperintensities
Méthode pratique de calcul de la densité spectrale de puissance de signaux codés
La connaissance de la rĂ©partition en frĂ©quence de la puissance des signaux numĂ©riques codĂ©s est un facteur important de la conception des codages binaire Ă signal. Les impĂ©ratifs peuvent ĂȘtre, par exemple, de s'affranchir de composante continue et de concentrer le maximum de puissance dans une certaine bande. L'article expose un moyen pratique, facile Ă mettre en oeuvre sur calculateur numĂ©rique, de calcul de la densitĂ© spectrale de puissance de signaux codĂ©s. La description de la procĂ©dure de codage binaire Ă signal par un graphe facilite le calcul; certaines propriĂ©tĂ©s des chaĂźnes de Markov permettent alors d'obtenir fonction d'autocorrĂ©lation et densitĂ© spectrale de puissance. En fin d'article, on rappelle comment Ă©tendre ces rĂ©sultats Ă une porteuse modulĂ©e en phase par un signal numĂ©rique
Recommended from our members
Distributed power flow loss minimization control for future grid
In this paper, a novel decentralized algorithm is proposed to minimize power flow loss in a large-scale future grid connecting with many real-time-distributed generation systems by which power flows bi-directionally. The DC-power loss at each link is defined as the product of resistance and the square of current that can be considered as a quadratic flow cost. We employ the notion of tie-sets that reduces the complexity of the power flow loss problem by dividing a power network into a set of loops that forms a linear vector space on which the power loss problem can be formulated as a convex optimization problem. As finding a solution in each tie-set enables global optimization, we realize parallel computing within a system of independent tie-sets by integrating autonomous agents. Simulation results demonstrate the minimization of the power loss on every link by iteratively optimized power flows and show the superiority against the traditional centralized optimization scheme
Distributed Real-Time Power Flow control with renewable integration
We formulate an Optimal Real-Time Power Flow (ORPF) problem that integrates renwable energy generation and energy storage. In the ORPF problem, we seek to minimize the costs of energy storage and of power generation from fossil fuel that are required to balance the loads and generation from renewable sources. We present a novel decentralized algorithm for this problem, using tie-set graph theory. Tie-set graph theory significantly reduces the complexity of the ORPF problem by dividing a power network into a set of independent loops referred to as "tie-sets." Simulation results demonstrate real-time power production responses and flow controls that lead to reliable use of battery systems and reduce the cost of using fossil fuel. © 2013 IEEE
Recommended from our members
Distributed real-time power flow control with renewable integration
We formulate an Optimal Real-Time Power Flow (ORPF) problem that integrates renwable energy generation and energy storage. In the ORPF problem, we seek to minimize the costs of energy storage and of power generation from fossil fuel that are required to balance the loads and generation from renewable sources. We present a novel decentralized algorithm for this problem, using tie-set graph theory. Tie-set graph theory significantly reduces the complexity of the ORPF problem by dividing a power network into a set of independent loops referred to as "tie-sets." Simulation results demonstrate real-time power production responses and flow controls that lead to reliable use of battery systems and reduce the cost of using fossil fuel. © 2013 IEEE