On the convergence rate and optimization of a numerical method with splitting of boundary conditions for the stokes system in a spherical layer in the axisymmetric case: Modification for thick layers

The convergence rate of a fast-converging second-order accurate iterative method with splitting of boundary conditions constructed by the authors for solving an axisymmetric Dirichlet boundary value problem for the Stokes system in a spherical gap is studied numerically. For R/r exceeding about 30, where r and R are the radii of the inner and outer boundary spheres, it is established that the convergence rate of the method is lower (and considerably lower for large R/r) than the convergence rate of its differential version. For this reason, a really simpler, more slowly converging modification of the original method is constructed on the differential level and a finite-element implementation of this modification is built. Numerical experiments have revealed that this modification has the same convergence rate as its differential counterpart for R/r of up to 5 × 10³. When the multigrid method is used to solve the split and auxiliary boundary value problems arising at iterations, the modification is more efficient than the original method starting from R/r ～ 30 and is considerably more efficient for large values of R/r. It is also established that the convergence rates of both methods depend little on the stretching coefficient η of circularly rectangular mesh cells in a range of η that is well sufficient for effective use of the multigrid method for arbitrary values of R/r smaller than ～ 5 × 10³.     

Stability of Markovian structure observed in high frequency foreign exchange data

Contrary to the common sense in economics and financial engineering, price fluctuations at very fine level of motion exhibit various evidences against the efficient market hypothesis. We attempt to investigate this issue by studying extensive amount of foreign currency exchange data for over five years at the finest level of resolution. We specifically focus on the proposed stability in binomial conditional probabilities originally found in much smaller examples of financial time series. In order to handle very large data, we have written an efficient program in C that automatically generates those conditional probabilities. It is found that the stability is maintained for extremely large time duration that covers almost the entire period. Based on the length of conditions for which the conditional probabilities are distinguishable each other, we identify the length of memory being less than 3 movements.     

Inviscid,laminar and turbulent opposed flows

This paper attempts to reproduce numerically previous experimental findings with opposed flows and extends their range to quantify the effects of upstream pipes and nozzles with inviscid, laminar and turbulent flows. The choice of conservation equations, boundary conditions, algorithms for their solution, the degree of grid dependence, numerical diffusion and the validity of numerical approximations are justified with supporting calculations where necessary. The results of all calculations on the stagnation plane show maximum strain rates close to the annular exit from the nozzles and pipes for lower separations and it can be expected that corresponding reacting flows will tend to extinguish in this region with the extinction moving towards the axis. With laminar flows, the maximum strain rate increased with Reynolds number and the maximum values were generally greater than with inviscid flows and smaller than with turbulent flows. With large separations, the strain rates varied less and this explains some results with reacting flows where the extinction appeared to begin on the axis. The turbulent‐flow calculations allowed comparison of three common variants of a two‐equation first‐moment closure. They provided reasonable and useful indications of strain rates but none correctly represented the rms of velocity fluctuations on the axis and close to the stagnation plane. As expected, those designed to deal with this problem produced results in better agreement with experiment but were still imperfect. Copyright © 2004 John Wiley & Sons, Ltd.     

A general Hsu-Robbins-Erdős Type estimate of tail probabilities of sums of independent identically distributed random variables

Periodica Mathematica Hungarica - Let X 1,X 2,... be a sequence of independent and identically distributed random variables, and put % MATHTYPE!MTEF!2!1!+-%...     

Estimates for the Rapid Decay of Concentration Functions of n-Fold Convolutions

We estimate the concentration functions of n-fold convolutions of one-dimensional probability measures. The Kolmogorov–Rogozin inequality implies that for nondegenerate distributions these functions decrease at least as O(n ^–1/2). On the other hand, Esseen⁽³⁾ has shown that this rate is o(n ^–1/2) iff the distribution has an infinite second moment. This statement was sharpened by Morozova.⁽⁹⁾ Theorem 1 of this paper provides an improvement of Morozova's result. Moreover, we present more general estimates which imply the rates o(n ^–1/2).     

Convexity Bias in the Pricing of Eurodollar Swaps

The traditional use of LIBOR futures prices to obtain surrogates for the Eurodollar forward rates is proved to yield a systematic bias in the pricing of Eurodollar swaps when one assumes that the yield curve is well described by the Heath-Jarrow-Morton model. The resulting theoretical inequality is consistent with the empirical observations of Burghardt and Hoskins (1995), and it provide a theoretical basis for price anomalies that are suggested by more recent empirical data.     

二水草酸锌脱水的热分解动力学研究

提出一种多升温速率-等温法确定机理函数g(α)的新方法;并用迭代的等转化率法求出较为可靠的活化能Ea;在Ea和g(α)的基础上计算出指前因子A.用该法对二水草酸锌（ZnC2O4•2H2O）脱水反应的热分解动力学三因子进行了求算,得出Ea为87.22 kJ•mol－1, A为4.2120×108～7.2328×108 s－1;以及随机成核和随后生长型机理函数Am（Avrami-Erofeer）,其积分形式g(α)=[－ln(1－α)] 1/m和微分形式f(α)=m(1－α)•[－ln(1－α)](1－1/m),调节因子m=1.85～2.00.     

用~(13)C NMR弛豫研究星形聚苯乙烯在溶液中的分子运动(Ⅱ)

对不同支化度和不同支链链长的20％(W/V)星形聚苯乙烯溶液测定了~(13)C NMR弛豫参数,用1g-x~2分布、Cole-Cole分布和构象跳跃模型对主链的分子运动进行了分析讨论,并对芳环侧基的内旋转运动也进行了分析,求出了活化能和跳跃速率。结果表明,轻度化学交联对相关时间分布有一定影响,对链段运动的势垒没有明显影响。支链链长对~(13)C NMR弛豫的影响和对线形聚合物的影响是类似的。     

Thermal analysis study of Bi<Subscript>2</Subscript>Sr<Subscript>2</Subscript>Ca<Subscript>2</Subscript>Cu<Subscript>3-x</Subscript>Er<Subscript>x</Subscript>O<Subscript>10+δ</Subscript> glass-ceramic system

Summary We have fabricated glasses in the Bi-2223 HT_c superconductor system with Bi₂Sr₂Ca₂Cu_3-xEr_xO_{10+ δ} nominal composition, where x=0.5 and 1.0, by the glass-ceramic technique. Using an analysis developed for non-isothermal crystallization studies, information on some aspects of crystallization temperature and thermal properties has been obtained. The crystallization studies were made using DTA with several uniform rates. The calculations of crystallization activation energies, E_a, and the Avrami parameters, n, were made based on the non-isothermal kinetic theory of Kissinger and the Ozawa’s equations. The DTA data of the samples showed that the first crystallization temperature, T_x1, increases and the second crystallization temperature, T_x2, decreases by increasing the Er concentration. This suggests that the Er substitution had significant effect on the glassification of the BSCCO material due to change on the surface nucleation and increased ionic activities at high temperature region. The activation energy for crystallization, E_a, of the samples was also showed an increase at high Er concentration case. However, the Avrami parameter, n, decreased from 2.5 to 1.7 for x=0.5 and 1.0 samples, respectively. This suggests that the growth mechanism is diffusion-controlled and three-dimensional parabolic growth takes place near the first crystallization temperature. The oxidization rates and the activation barrier for oxygen out-diffusion process, E, was calculated using the TG data. It was found that the total mass gain in the x=0.5 sample is comparably smaller than that of the x=1.0 sample. This shows that the oxygen absorption of the x=1.0 sample is faster than the x=0.5 sample, leading to increase in the oxidization rate in the x=1.0 material.     

Neural Networks for Financial Time Series Forecasting

Financial and economic time series forecasting has never been an easy task due to its sensibility to political, economic and social factors. For this reason, people who invest in financial markets and currency exchange are usually looking for robust models that can ensure them to maximize their profile and minimize their losses as much as possible. Fortunately, recently, various studies have speculated that a special type of Artificial Neural Networks (ANNs) called Recurrent Neural Networks (RNNs) could improve the predictive accuracy of the behavior of the financial data over time. This paper aims to forecast: (i) the closing price of eight stock market indexes; and (ii) the closing price of six currency exchange rates related to the USD, using the RNNs model and its variants: the Long Short-Term Memory (LSTM) and the Gated Recurrent Unit (GRU). The results show that the GRU gives the overall best results, especially for the univariate out-of-sample forecasting for the currency exchange rates and multivariate out-of-sample forecasting for the stock market indexes.