Brazilian exchange rate complexity: Financial crisis effects

With the financial market globalization, foreign investments became vital for the economies, mainly in emerging countries. In the last decades, Brazilian exchange rates appeared as a good indicator to measure either investors' confidence or risk aversion. Here, some events of global or national financial crisis are analyzed, trying to understand how they influenced the "dollar-real" rate evolution. The theoretical tool to be used is the Lopez-Mancini-Calbet (LMC) complexity measure that, applied to real exchange rate data, has shown good fitness between critical events and measured patterns. (C) 2011 Elsevier B.V. All rights reserved.

Mutual Information Rate and Bounds for It

The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two time series (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators.

Age-Related Maximum Heart Rate Among Ischemic and Nonischemic Heart Failure Patients Receiving beta-Blockade Therapy

Background: Equations to predict maximum heart rate (HRmax) in heart failure (HF) patients receiving beta-adrenergic blocking (BB) agents do not consider the cause of HF. We determined equations to predict HRmax in patients with ischemic and nonischemic HF receiving BB therapy. Methods and Results: Using treadmill cardiopulmonary exercise testing, we studied HF patients receiving BB therapy being considered for transplantation from 1999 to 2010. Exclusions were pacemaker and/or implantable defibrillator, left ventricle ejection fraction (LVEF) >50%, peak respiratory exchange ratio (RER) <1.00, and Chagas disease. We used linear regression equations to predict HRmax based on age in ischemic and nonischemic patients. We analyzed 278 patients, aged 47 +/- 10 years, with ischemic (n = 75) and nonischemic (n = 203) HF. LVEF was 30.8 +/- 9.4% and 28.6 +/- 8.2% (P = .04), peak VO2 16.9 +/- 4.7 and 16.9 +/- 5.2 mL kg(-1) min(-1) (P = NS), and the HRmax 130.8 +/- 23.3 and 125.3 +/- 25.3 beats/min (P = .051) in ischemic and nonischemic patients, respectively. We devised the equation HRmax = 168 - 0.76 x age (R-2 = 0.095; P = .007) for ischemic HF patients, but there was no significant relationship between age and HRmax in nonischemic HF patients (R-2 = 0.006; P = NS). Conclusions: Our study suggests that equations to estimate HRmax should consider the cause of HF. (J Cardiac Fail 2012;18:831-836)