Cinética e caracterização de ramnolipídeos produzidos por Pseudomonas aeruginosa MSIC02 utilizando glicerol como fonte de carbono

Glycerol, a co-product of biodiesel production, was used as a carbon source for the kinetics studies and production of biosurfactants by P. aeruginosa MSIC02. The highest fermentative parameters (Y PX = 3.04 g g-1; Y PS = 0.189 g g-1, P B = 31.94 mg L-1 h-1 and P X = 10.5 mg L-1 h-1) were obtained at concentrations of 0.4% (w/v) NaNO3 and 2% (w/v) glycerol. The rhamnolipid exhibited 80% of emulsification on kerosene, surface tension of 32.5 mN m-1, CMC = 28.2 mg L-1, C20 (concentration of surfactant in the bulk phase that produces a reduction of 20 dyn/cm in the surface tension of the solvent) = 0.99 mg L-1, Γm (surface concentration excess) = 2.4 x 10-26 mol Å-2 and S (surface area) = 70.4 Ų molecule-1 with solutions containing 10% NaCl. A mathematical model based on logistic equation was considered to representing the process. Model parameters were estimated by non-linear regression method. This approach was able to give a good description of the process.

Mapping cancer, cardiovascular and malaria research in Brazil

This paper presents performance indicators for the Brazilian cancer, cardiovascular and malaria research areas from 1981 to 1995. The data show an increasing number of papers since 1981 and author numbers indicate a continuous growth of the scientific community and suggest an expected impact of scientific activity on biomedical education. The data also characterize cardiovascular research as a well-established area and cancer research as a faster growing consolidating field. The 1989-1994 share of Brazilian articles among world publications shows a growing trend for the cancer (1.61) and cardiovascular (1.59) areas, and a decrease for the malaria area (0.89). The burden of the three diseases on society is contrasted by the small number of consolidated Brazilian research groups, and a questionable balance of thematic activity, especially with regard to malaria. Brazilian periodicals play an important role in increasing the international visibility of science produced in the country. Cancer and cardiovascular research is strongly concentrated in the Southeastern and in Southern regions of Brazil, especially in São Paulo (at least one address from São Paulo in 64.5% of the 962 cancer articles and in 66.9% of the 2250 cardiovascular articles, the second state being Rio de Janeiro with at least one address in 14.1 and 11% of those articles, respectively). Malaria research (468 articles) is more evenly distributed across the country, following the pattern of the endemic distribution of the disease. Surveying these national indicator trends can be useful to establish policies in the decision process about health sciences, medical education and public health.

Analysis of variables that are not directly observable: influence on decision-making during the research process

The sample dimension, types of variables, format used for measurement, and construction of instruments to collect valid and reliable data must be considered during the research process. In the social and health sciences, and more specifically in nursing, data-collection instruments are usually composed of latent variables or variables that cannot be directly observed. Such facts emphasize the importance of deciding how to measure study variables (using an ordinal scale or a Likert or Likert-type scale). Psychometric scales are examples of instruments that are affected by the type of variables that comprise them, which could cause problems with measurement and statistical analysis (parametric tests versus non-parametric tests). Hence, investigators using these variables must rely on suppositions based on simulation studies or recommendations based on scientific evidence in order to make the best decisions.

INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.

Marketing in the pre-development process of agricultural machines: a reference model

The theme of the research is the development of the domain of marketing knowledge in the design of agricultural machinery. It is developed throughout the design of agricultural machinery in order to identify the corporate and customers needs and to develop strategies to satisfy these needs. The central problem of the research questions which marketing tools to apply on pre-development process of farm machinery, in order to increase the market value of the products and of the company and, consequently, generate competitive advantage to the manufacturers of agricultural machinery. As methodology, it was developed bibliographical research and multicase study of the development process of agricultural machinery developed by small, medium and large companies and the academy. As a result, a marketing reference model was elaborated for the pre-development stage of agricultural machinery, which outlines the activities, tasks, mechanisms and controls that can be used in strategic planning and in products planning of agricultural machinery manufacturers, contributing to explain the explicit knowledge in the marketing field.

Decision support system for the diagnosis of schizophrenia disorders

Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.