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.

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.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

Does using stepwise variable selection to build sequential path analysis models make sense?

Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.

Test procedure for variable rate fertilizer on coffee

The objective was to develop and test a procedure for applying variable rates of fertilizers and evaluate yield response in coffee (Coffea arabica L.) with regard to the application of phosphorus and potassium. The work was conducted during the 2004 season in a 6.4 ha field located in central Sao Paulo state. Two treatments were applied with alternating strips of fixed and variable rates during the whole season: one following the fertilizing procedures recommended locally, and the other based on a grid soil sampling. A prototype pneumatic fertilizer applicator was used, carrying two conveyor belts, one for each row. Harvesting was done with a commercial harvester equipped with a customized volumetric yield monitor, separating the two treatments. Data were analyzed based on geostatistics, correlations and regressions. The procedure showed to be feasible and effective. The area that received fertilizer applications at a variable rate showed a 34% yield increase compared to the area that received a fixed rate. The variable rate fertilizer resulted in a savings of 23% in phosphate fertilizer and a 13% increase in potassium fertilizer, when compared to fixed rate fertilizer. Yield in 2005, the year after the variable rate treatments, still presented residual effect from treatments carried out during the previous cycle.

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.

Quantification of chlorpheniramine maleate enantiomers by ultraviolet spectroscopy and chemometric methods

Chlorpheniramine maleate (CLOR) enantiomers were quantified by ultraviolet spectroscopy and partial least squares regression. The CLOR enantiomers were prepared as inclusion complexes with beta-cyclodextrin and 1-butanol with mole fractions in the range from 50 to 100%. For the multivariate calibration the outliers were detected and excluded and variable selection was performed by interval partial least squares and a genetic algorithm. Figures of merit showed results for accuracy of 3.63 and 2.83% (S)-CLOR for root mean square errors of calibration and prediction, respectively. The ellipse confidence region included the point for the intercept and the slope of 1 and 0, respectively. Precision and analytical sensitivity were 0.57 and 0.50% (S)-CLOR, respectively. The sensitivity, selectivity, adjustment, and signal-to-noise ratio were also determined. The model was validated by a paired t test with the results obtained by high-performance liquid chromatography proposed by the European pharmacopoeia and circular dichroism spectroscopy. The results showed there was no significant difference between the methods at the 95% confidence level, indicating that the proposed method can be used as an alternative to standard procedures for chiral analysis.

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.

The economic determinants of the Brazilian nominal term structure of interest rates

The purpose of this study is to identify the effects of monetary policy and macroeconomic shocks on the dynamics of the Brazilian term structure of interest rates. We estimate a near-VAR model under the identification scheme proposed by Christiano et al. (1996, 1999). The results resemble those of the US economy: monetary policy shocks that flatten the term structure of interest rates. We find that monetary policy shocks in Brazil explain a significantly larger share of the dynamics of the term structure than in the USA. Finally, we analyse the importance of standard macroeconomic variables (e. g. GDP, inflation and measure of country risk) to the dynamics of the term structure in Brazil.

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.

Variable Demand and Profitability in Service Companies: a case study in the information technology sector

Managing a variable demand scenario is particularly challenging on services organizations because services companies usually have a major part of fixed costs. The article studies how a services organization manages its demand variability and its relation with the organization`s profitability. Moreover, the study searched for alternatives used to reduce the demand variability`s impact on the profitability of the company. The research was based on a case study with a Brazilian services provider on information technology business. The study suggests that alternatives like using outsourced employees to cover demand peaks may bring benefits only on short term, reducing the profitability of the company on long term: Some options are revealed, like the internationalization of employees and the investment on developing its own workforce.

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.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Impact of Atypical Retardation Patterns on Detection of Glaucoma Progression using the GDx with Variable Corneal Compensation

PURPOSE: To evaluate the impact of atypical retardation patterns (ARP) on detection of progressive retinal nerve fiber layer (RNFL) loss using scanning laser polarimetry with variable corneal compensation (VCC). DESIGN: Observational cohort study. METHODS: The study included 377 eyes of 221 patients with a median follow-up of 4.0 years. Images were obtained annually with the GDx VCC (Carl Zeiss Med, itec Inc, Dublin, California, USA), along with optic disc stereophotographs and standard automated perimetry (SAP) visual fields. Progression was determined by the Guided Progression Analysis software for SAP and by masked assessment of stereophotographs by expert graders. The typical scan score (TSS) was used to quantify the presence of ARPs on GDx VCC images. Random coefficients models were used to evaluate the relationship between ARP and RNFL thickness measurements over time. RESULTS: Thirty-eight eyes (10%) showed progression over time on visual fields, stereophotographs, or both. Changes in TSS scores from baseline were significantly associated with changes in RNFL thickness measurements in both progressing and nonprogressing eyes. Each I unit increase in TSS score was associated with a 0.19-mu m decrease in RNFL thickness measurement (P < .001) over time. CONCLUSIONS: ARPs had a significant effect on detection of progressive RNFL loss with the GDx VCC. Eyes with large amounts of atypical patterns, great fluctuations on these patterns over time, or both may show changes in measurements that can appear falsely as glaucomatous progression or can mask true changes in the RNFL. (Am J Ophthalmol 2009;148:155-163. (C) 2009 by Elsevier Inc. All rights reserved.)

Brain Structural Variability due to Aging and Gender in Cognitively Healthy Elders: Results from the Sao Paulo Ageing and Health Study

BACKGROUND AND PURPOSE: Several morphometric MR imaging studies have investigated age- and sex-related cerebral volume changes in healthy human brains, most often by using samples spanning several decades of life and linear correlation methods. This study aimed to map the normal pattern of regional age-related volumetric reductions specifically in the elderly population. MATERIALS AND METHODS: One hundred thirty-two eligible individuals (67-75 years of age) were selected from a community-based sample recruited for the Sao Paulo Ageing and Health (SPAH) study, and a cross-sectional MR imaging investigation was performed concurrently with the second SPAH wave. We used voxel-based morphometry (VBM) to conduct a voxelwise search for significant linear correlations between gray matter (GM) volumes and age. In addition, region-of-interest masks were used to investigate whether the relationship between regional GM (rGM) volumes and age would be best predicted by a nonlinear model. RESULTS: VBM and region-of-interest analyses revealed selective foci of accelerated rGM loss exclusively in men, involving the temporal neocortex, prefrontal cortex, and medial temporal region. The only structure in which GM volumetric changes were best predicted by a nonlinear model was the left parahippocampal gyrus. CONCLUSIONS: The variable patterns of age-related GM loss across separate neocortical and temporolimbic regions highlight the complexity of degenerative processes that affect the healthy human brain across the life span. The detection of age-related Ill GM decrease in men supports the view that atrophy in such regions should be seen as compatible with normal aging.