On the system of rational difference equations x(n) = A+(1)over-bar y(n-p), y(n) = A+(gamma(n-1))over-bar x(n-r)y(n-5)

In this paper, we study the behavior of the positive solutions of the system of two difference equations [GRAPHICS] where p >= 1, r >= 1, s >= 1, A >= 0, and x(1-r), x(2-r),..., x(0), y(1-max) {p.s},..., y(0) are positive real numbers. (c) 2005 Elsevier Inc. All rights reserved.

X-13arima-seats com R: um estudo de caso para a produção industrial brasileira

Esse artigo apresenta o uso do programa de ajuste sazonal X-13ARIMA-SEATS desenvolvido e mantido por US Census Bureau. O programa é mundialmente utilizado por órgãos de estatística e, em alguns lugares, ainda em sua versão anterior. O ajuste sazonal é implementado no software R e aplicado na série temporal do índice de produção industrial geral do Brasil. As ferramentas disponíveis pelo programa permitiram aprimorar o ajuste automático e diagnosticá-lo de forma adequada. Apresenta-se também uma rotina para executar o ajuste sazonal em mais de uma série simultaneamente, uma vez que, geralmente, as instituições que realizam tal procedimento, não o fazem para apenas uma série temporal.

Vacuum effects on massive spinor fields: S-1 x R-3 topology

The aim of this work was to investigate the role played by an external field on the Casimir energy density for massive fermions under S-1 x R-3 topology. Both twisted- and untwisted-spin connections are considered and the calculation in a closed form is performed using an alternative approach based on the combination of the analytic regularization method and the Euler-Maclaurin summation formula. It is shown that no mass scale appears in the final result and, therefore, Casimir effect arises only from the boundary conditions and vacuum fluctuations induced by the coupling with the external field.

Crystallization and preliminary X-ray crystallographic studies of Protac (R), a commercial protein C activator isolated from Agkistrodon contortrix contortrix venom

The protein C pathway plays an important role in the control and regulation of the blood coagulation cascade and prevents the propagation of the clotting process on the endothelium surface. In physiological systems, protein C activation is catalyzed by thrombin, which requires thrombomodulin as a cofactor. The protein C activator from Agkistrodon contortrix contortrix acts directly on the zymogen of protein C converting it into the active form, independently of thrombomodulin. Suitable crystals of the protein C activator from Agkistrodon contortrix contortrix were obtained from a solution containing 2 M ammonium sulfate as the precipitant and these crystals diffracted to 1.95 angstrom resolution at a synchrotron beamline. The crystalline array belongs to the monoclinic space group C2 with unit cell dimensions a=80.4, b = 63.3 and c = 48.2 angstrom, alpha = gamma = 90.0 degrees and beta = 90.8 degrees. (C) 2005 Elsevier B.V. All rights reserved.

Boundary of the rauzy fractal sets in R x C generated by P(x)=x(4)-x(3)-x(2)-x-1

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spinning Hopf solitons on S-3 x R

We consider a field theory with target space being the two dimensional sphere S-2 and defined on the space-time S-3 x R. The Lagrangean is the square of the pull-back of the area form on S-2. It is invariant under the conformal group SO(4, 2) and the infinite dimensional group of area preserving diffeomorphisms of S-2. We construct an infinite number of exact soliton solutions with non-trivial Hopf topological charges. The solutions spin with a frequency which is bounded above by a quantity proportional to the inverse of the radius of S-3. The construction of the solutions is made possible by an ansatz which explores the conformal symmetry and a U(1) subgroup of the area preserving diffeomorphism group.

Economic design of (X)over-bar and R charts under Weibull shock models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Joint (X)over-bar and R charts with variable sample sizes and sampling intervals

Recent studies have shown that the (X) over bar chart with variable sampling intervals (VSI) and/or with variable sample sizes (VSS) detects process shifts faster than the traditional (X) over bar chart. This article extends these studies for processes that are monitored by both the (X) over bar and R charts. A Markov chain model is used to determine the properties of the joint (X) over bar and R charts with variable sample sizes and sampling intervals (VSSI). The VSSI scheme improves the joint (X) over bar and R control chart performance in terms of the speed with which shifts in the process mean and/or variance are detected.

Joint conomic design of (x)over-bar and R charts under Weibull shock models

This paper deals with the joint economic design of (x) over bar and R charts when the occurrence times of assignable causes follow Weibull distributions with increasing failure rates. The variable quality characteristic is assumed to be normally distributed and the process is subject to two independent assignable causes (such as tool wear-out, overheating, or vibration). One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. A cost model is developed and a non-uniform sampling interval scheme is adopted. A two-step search procedure is employed to determine the optimum design parameters. Finally, a sensitivity analysis of the model is conducted, and the cost savings associated with the use of non-uniform sampling intervals instead of constant sampling intervals are evaluated.

Joint (X)over-bar and R charts with two-stage samplings

When joint (X) over bar and R charts are in use, samples of fixed size are regularly taken from the process, and their means and ranges are plotted on the (X) over bar and R charts, respectively. In this article, joint (X) over bar and R charts have been used for monitoring continuous production processes. The sampling is performed, in two stages. During the first stage, one item of the sample is inspected and, depending on the result, the sampling is interrupted if the process is found to be in control; otherwise, it goes on to the second stage, where the remaining sample items are inspected. The two-stage sampling procedure speeds up the detection of process disturbances. The proposed joint (X) over bar and R charts are easier to administer and are more efficient than the joint (X) over bar and R charts with variable sample size where the quality characteristic of interest can be evaluated either by attribute or variable. Copyright (C) 2004 John Wiley Sons, Ltd.

Joint X̄ and R Charts with Variable Sample Sizes and Sampling Intervals

Recent studies have shown that the X̄ chart with variable sampling intervals (VSI) and/or with variable sample sizes (VSS) detects process shifts faster than the traditional X̄ chart. This article extends these studies for processes that are monitored by both the X̄ and R charts. A Markov chain model is used to determine the properties of the joint X and R charts with variable sample sizes and sampling intervals (VSSI). The VSSI scheme improves the joint X̄ and R control chart performance in terms of the speed with which shifts in the process mean and/or variance are detected.

Joint conomic design of x̄ and R charts under Weibull shock models

This paper deals with the joint economic design of x̄ and R charts when the occurrence times of assignable causes follow Weibull distributions with increasing failure rates. The variable quality characteristic is assumed to be normally distributed and the process is subject to two independent assignable causes (such as tool wear-out, overheating, or vibration). One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. A cost model is developed and a non-uniform sampling interval scheme is adopted. A two-step search procedure is employed to determine the optimum design parameters. Finally, a sensitivity analysis of the model is conducted, and the cost savings associated with the use of non-uniform sampling intervals instead of constant sampling intervals are evaluated.