Revisiting the interest rate puzzle

This article makes a connection between Lucas` (1978) asset pricing model and the macroeconomic dynamics for some selected countries. Both the relative risk aversion and the impatience for postponing consumption by synthesizing the investor behaviour can help to understand some key macroeconomic issues across countries, such as the savings decision and the real interest rate. I find that the government consumption makes worse the so-called `equity premium-interest rate puzzle`. The first root of the quadratic function for explaining the real interest rate can produce this puzzle, but not the second root. Thus, Mehra and Prescott (1985) identified only one possible solution.

Predictors of word-level literacy amongst Grade 3 children in five diverse languages

Groups of Grade 3 children were tested on measures of word-level literacy and undertook tasks that required the ability to associate sounds with letter sequences and that involved visual, auditory and phonological-processing skills. These groups came from different language backgrounds in which the language of instruction was Arabic, Chinese, English, Hungarian or Portuguese. Similar measures were used across the groups, with tests being adapted to be appropriate for the language of the children. Findings indicated that measures of decoding and phonological-processing skills were good predictors of word reading and spelling among Arabic- and English-speaking children, but were less able to predict variability in these same early literacy skills among Chinese- and Hungarian-speaking children, and were better at predicting variability in Portuguese word reading than spelling. Results were discussed with reference to the relative transparency of the script and issues of dyslexia assessment across languages. Overall, the findings argue for the need to take account of features of the orthography used to represent a language when developing assessment procedures for a particular language and that assessment of word-level literacy skills and a phonological perspective of dyslexia may not be universally applicable across all language contexts. Copyright (C) 2008 John Wiley & Sons, Ltd.

Pricing corporate bonds in Brazil: 2000 to 2004

This paper analyzes the factors that influence the issuing price of debentures in Brazil in the period from year 2000 to 2004, applying a factor model, in which exogenous variables explain return and price behavior. The variables in this study include: rating, choice of index, maturity, country risk, basic interest rate, long-term and short-term rate spread, the stock market index, and the foreign exchange rate. Results indicate that the index variable, probability of default and bond`s maturity influence pricing and points out associations of long-term bonds with better rating issues. (C) 2008 Elsevier Inc. All rights reserved.

Refined sandwich model for the vibration of beams with embedded shear piezoelectric actuators and sensors

This work extends a previously presented refined sandwich beam finite element (FE) model to vibration analysis, including dynamic piezoelectric actuation and sensing. The mechanical model is a refinement of the classical sandwich theory (CST), for which the core is modelled with a third-order shear deformation theory (TSDT). The FE model is developed considering, through the beam length, electrically: constant voltage for piezoelectric layers and quadratic third-order variable of the electric potential in the core, while meclianically: linear axial displacement, quadratic bending rotation of the core and cubic transverse displacement of the sandwich beam. Despite the refinement of mechanical and electric behaviours of the piezoelectric core, the model leads to the same number of degrees of freedom as the previous CST one due to a two-step static condensation of the internal dof (bending rotation and core electric potential third-order variable). The results obtained with the proposed FE model are compared to available numerical, analytical and experimental ones. Results confirm that the TSDT and the induced cubic electric potential yield an extra stiffness to the sandwich beam. (C) 2007 Elsevier Ltd. All rights reserved.

Macro-Fiber Composite Actuators for Flow Control of a Variable Camber Airfoil

This research employs solid-state actuators for delay of flow separation seen in airfoils at low Reynolds numbers. The flow control technique investigated here is aimed for a variable camber airfoil that employs two active surfaces and a single four-bar (box) mechanism as the internal structure. To reduce separation, periodic excitation to the flow around the leading edge of the airfoil is induced by a total of nine piezocomposite actuated clamped-free unimorph benders distributed in the spanwise direction. An electromechanical model is employed to design an actuator capable of high deformations at the desired frequency for lift improvement at post-stall angles. The optimum spanwise distribution of excitation for increasing lift coefficient is identified experimentally in the wind tunnel. A 3D (non-uniform) excitation distribution achieved higher lift enhancement in the post-stall region with lower power consumption when compared to the 2D (uniform) excitation distribution. A lift coefficient increase of 18.4% is achieved with the identified non-uniform excitation mode at the bender resonance frequency of 125 Hz, the flow velocity of 5 m/s and at the reduced frequency of 3.78. The maximum lift (Clmax) is increased 5.2% from the baseline. The total power consumption of the flow control technique is 639 mW(RMS).

Batch distillation: Better at constant or variable reflux?

Due to its outstanding flexibility, batch distillation is still widely used in many separation processes. In the present work, a comparison between constant and variable reflux operations is studied. Firstly, a mathematical model is developed and then validated through comparison between predicted and experimental results accomplished in a lab-scale apparatus. Therefore, case studies are performed through mathematical simulations. It is noted that the most economical form of batch distillation is at constant overhead product composition, keeping the flow rate of vapor from the top of the column constant. (C) 2010 Elsevier B.V. All rights reserved.

Robust model predictive control with zone control

Model predictive control (MPC) is usually implemented as a control strategy where the system outputs are controlled within specified zones, instead of fixed set points. One strategy to implement the zone control is by means of the selection of different weights for the output error in the control cost function. A disadvantage of this approach is that closed-loop stability cannot be guaranteed, as a different linear controller may be activated at each time step. A way to implement a stable zone control is by means of the use of an infinite horizon cost in which the set point is an additional variable of the control problem. In this case, the set point is restricted to remain inside the output zone and an appropriate output slack variable is included in the optimisation problem to assure the recursive feasibility of the control optimisation problem. Following this approach, a robust MPC is developed for the case of multi-model uncertainty of open-loop stable systems. The controller is devoted to maintain the outputs within their corresponding feasible zone, while reaching the desired optimal input target. Simulation of a process of the oil re. ning industry illustrates the performance of the proposed strategy.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Pricing farm-level agricultural insurance: a Bayesian approach

This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations

The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

Stability of clavulanic acid under variable pH, ionic strength and temperature conditions. A new kinetic approach

Clavulanic acid (CA) is a beta-lactam antibiotic that alone exhibits only weak antibacterial activity, but is a potent inhibitor of beta-lactamases enzymes. For this reason it is used as a therapeutic in conjunction with penicillins and cephalosporins. However, it is a well-known fact that it is unstable not only during its production phase, but also during downstream processing. Therefore, the main objective of this study was the evaluation of CA long-term stability under different conditions of pH and temperature, in the presence of variable levels of different salts, so as to suggest the best conditions to perform its simultaneous production and recovery by two-phase polymer/salt liquid-liquid extractive fermentation. To this purpose, the CA stability was investigated at different values of pH (4.0-8.0) and temperature (20-45 degrees C), and the best conditions were met at a pH 6.0-7.2 and 20 degrees C. Its stability was also investigated at 30 degrees C in the presence of NaCl, Na(2)SO(4), CaCl(2) and MgSO(4) at concentrations of 0.1 and 0.5 M in Mcllvaine buffer (pH 6.5). All salts led to increased CA instability with respect to the buffer alone, and this effect decreased in following sequence: Na(2)SO(4) > MgSO(4) > CaCl(2) > NaCl. Kinetic and thermodynamic parameters of CA degradation were calculated adopting a new model that took into consideration the equilibrium between the active and a reversibly inactivated form of CA after long-time degradation. (C) 2009 Elsevier B.V. All rights reserved.

Allergic asthma in patients with common variable immunodeficiency

P>Background: Many patients with common variable immunodeficiency (CVID) have a clinical history suggestive of allergic respiratory disease. However, in such individuals, the prevalence of asthma and the role of atopy have not been well established. The objective of this study was to evaluate pulmonary function and identify asthma in patients with CVID. We also investigated the role of IgE as a trigger of asthma in these patients. Methods: Sixty-two patients diagnosed with CVID underwent spirometry, as well as skin prick testing and in vitro determination of serum-specific IgE levels for aeroallergens, together with bronchial provocation with histamine and allergen. Results: The most common alteration identified through spirometry was obstructive lung disease, which was observed in 29 (47.5%) of the 62 patients evaluated. Eighteen (29.0%) of the 62 patients had a clinical history suggestive of allergic asthma. By the end of the study, asthma had been diagnosed in nine (14.5%) patients and atopy had been identified in six (9.7%). In addition, allergic asthma had been diagnosed in four patients (6.5% of the sample as a whole; 22.2% of the 18 patients with a clinical history suggestive of the diagnosis). Conclusion: In this study, CVID patients testing negative for specific IgE antibodies and suspected of having allergic asthma presented a positive response to bronchial provocation tests with allergens. To our knowledge, this is the first such study. When CVID patients with a history suggestive of allergic asthma test negative on traditional tests, additional tests designed to identify allergic asthma might be conducted.

Effects of changing blood viscosity and heart rate on vena contracta width as evaluated by color Doppler flow mapping. An in vitro study with a pulsatile flow model

Background: There is only limited knowledge on how the quantification of valvular regurgitation by color Doppler is affected by changing blood viscosity. This study was designed to evaluate the effect of changing blood viscosity on the vena contracta width using an in vitro model of valvular insufficiency capable of providing ample variation in the rate and stroke volume. Methods: We constructed a pulsatile flow model filled with human blood at varying hematocrit (15%, 35%, and 55%) and corresponding blood viscosity (blood/water viscosity: 2.6, 4.8, 9.1) levels in which jets were driven through a known orifice (7 mm(2)) into a 110 mL compliant receiving chamber (compliance: 2.2 mL/mmHg) by a pulsatile pump. In addition, we used variable pump stroke volumes (5, 7.5, and 10 mL) and rates (40, 60, and 80 ppm). Vena contracta region was imaged using a 3.5 MHz transducer. Pressure and volume in the flow model were kept constant during each experimental condition, as well as ultrasound settings. Results: Blood viscosity variation in the experimental range did not induce significant changes in vena contracta dimensions. Also, vena contracta width did not change from normal to low hematocrit and viscosity levels. A very modest increase only in vena contracta dimension was observed at very high level of blood viscosity when hematocrit was set to 55% . Pump rate, in the evaluated range, did not influence vena contracta width. These results in controlled experimental settings suggest that the vena contracta is an accurate quantitative method for quantifying valvular regurgitation even when this condition is associated with anemia, a frequent finding in patients with valvular heart disease.

Bayesian analysis of skew-t multivariate null intercept measurement error model

The multivariate skew-t distribution (J Multivar Anal 79:93-113, 2001; J R Stat Soc, Ser B 65:367-389, 2003; Statistics 37:359-363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew-normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763-771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry.