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Resumo:
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.
Resumo:
A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.
Resumo:
In this study, a wrapper approach was applied to objectively select the most important variables related to two different anaerobic digestion imbalances, acidogenic states and foaming. This feature selection method, implemented in artificial neural networks (ANN), was performed using input and output data from a fully instrumented pilot plant (1 m 3 upflow fixed bed digester). Results for acidogenic states showed that pH, volatile fatty acids, and inflow rate were the most relevant variables. Results for foaming showed that inflow rate and total organic carbon were among the relevant variables, both of which were related to the feed loading of the digester. Because there is not a complete agreement on the causes of foaming, these results highlight the role of digester feeding patterns in the development of foaming
Resumo:
Nitric oxide (NO) produced by inducible NO synthase (iNOS, NOS-2) is an important component of the macrophage-mediated immune defense toward numerous pathogens. Murine macrophages produce NO after cytokine activation, whereas, under similar conditions, human macrophages produce low levels or no NO at all. Although human macrophages can express iNOS mRNA and protein on activation, whether they possess the complete machinery necessary for NO synthesis remains controversial. To define the conditions necessary for human monocytes/macrophages to synthesize NO when expressing a functional iNOS, the human monocytic U937 cell line was engineered to synthesize this enzyme, following infection with a retroviral expression vector containing human hepatic iNOS (DFGiNOS). Northern blot and Western blot analysis confirmed the expression of iNOS in transfected U937 cells both at the RNA and protein levels. NOS enzymatic activity was demonstrated in cell lysates by the conversion of L-[3H]arginine into L-[3H]citrulline and the production of NO by intact cells was measured by nitrite and nitrate accumulation in culture supernatants. When expressing functional iNOS, U937 cells were capable of releasing high levels of NO. NO production was strictly dependent on supplementation of the culture medium with tetrahydrobiopterin (BH4) and was not modified by stimulation of the cells with different cytokines. These observations suggest that (1) human monocytic U937 cells contain all the cofactors necessary for NO synthesis, except BH4 and (2) the failure to detect NO in cytokine-stimulated untransfected U937 cells is not due to the presence of a NO-scavenging molecule within these cells nor to the destabilization of iNOS protein. DFGiNOS U937 cells represent a valuable human model to study the role of NO in immunity toward tumors and pathogens.
Resumo:
The adult hippocampus generates functional dentate granule cells (GCs) that release glutamate onto target cells in the hilus and cornus ammonis (CA)3 region, and receive glutamatergic and γ-aminobutyric acid (GABA)ergic inputs that tightly control their spiking activity. The slow and sequential development of their excitatory and inhibitory inputs makes them particularly relevant for information processing. Although they are still immature, new neurons are recruited by afferent activity and display increased excitability, enhanced activity-dependent plasticity of their input and output connections, and a high rate of synaptogenesis. Once fully mature, new GCs show all the hallmarks of neurons generated during development. In this review, we focus on how developing neurons remodel the adult dentate gyrus and discuss key aspects that illustrate the potential of neurogenesis as a mechanism for circuit plasticity and function.
Resumo:
A Fortran77 program, SSPBE, designed to solve the spherically symmetric Poisson-Boltzmann equation using cell model for ionic macromolecular aggregates or macroions is presented. The program includes an adsorption model for ions at the aggregate surface. The working algorithm solves the Poisson-Boltzmann equation in the integral representation using the Picard iteration method. Input parameters are introduced via an ASCII file, sspbe.txt. Output files yield the radial distances versus mean field potentials and average molar ion concentrations, the molar concentration of ions at the cell boundary, the self-consistent degree of ion adsorption from the surface and other related data. Ion binding to ionic, zwitterionic and reverse micelles are presented as representative examples of the applications of the SSPBE program.