967 resultados para mixture of distribution hypothesis


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This article models the interactions between safety and quality control and stage of distribution in the food marketing complex

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Metabolic syndrome is a set of disorders that increases the risk of developing cardiovascular disease. The gut microbiota is altered toward a less beneficial composition in overweight adults and this change can be accompanied by inflammation. Prebiotics such as galactooligosaccharides can positively modify the gut microbiota and immune system; some may also reduce blood lipids. We assessed the effect of a galactooligosaccharide mixture [Bi2 muno (B-GOS)] on markers of metabolic syndrome, gut microbiota, and immune function in 45 overweight adults with $3 risk factors associated with metabolic syndrome in a double-blind, randomized, placebo (maltodextrin)-controlled, crossover study (with a 4-wk wash-out period between interventions). Whole blood, saliva, feces, and anthropometric measurements were taken at the beginning, wk 6, and end of each 12-wk intervention period. Predominant groups of fecal bacteria were quantified and full blood count, markers of inflammation and lipid metabolism, insulin, and glucose were measured. B-GOS increased the number of fecal bifidobacteria at the expense of less desirable groups of bacteria. Increases in fecal secretory IgA and decreases in fecal calprotectin, plasma C-reactive protein, insulin, total cholesterol (TC), TG, and the TC:HDL cholesterol ratio were also observed. Administration of B-GOS to overweight adults resulted in positive effects on the composition of the gut microbiota, the immune response, and insulin, TC, and TG concentrations. B-GOSmay be a useful candidate for the enhancement of gastrointestinal health, immune function, and the reduction of metabolic syndrome risk factors in overweight adults.

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This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) model, which is designed based on the minimum bit error rate (MBER) criterion, in the system setting of the intersymbol interference channel plus a co-channel interference. Our proposed algorithm is referred to as the on-line mixture of Gaussians estimator aided MBER (OMG-MBER) equalizer. Specifically, a mixture of Gaussians based probability density function (PDF) estimator is used to model the PDF of the decision variable, for which a novel on-line PDF update algorithm is derived to track the incoming data. With the aid of this novel on-line mixture of Gaussians based sample-by-sample updated PDF estimator, our adaptive nonlinear equalizer is capable of updating its equalizer’s parameters sample by sample to aim directly at minimizing the RBF nonlinear equalizer’s achievable bit error rate (BER). The proposed OMG-MBER equalizer significantly outperforms the existing on-line nonlinear MBER equalizer, known as the least bit error rate equalizer, in terms of both the convergence speed and the achievable BER, as is confirmed in our simulation study

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A fortified food that was rich in protein, vitamins and iron made of chickpea, bovine lung and corn was developed with the aim of controlling iron-deficiency anaemia in children from poorer areas. It was tested in Teresina, State of Piaui, Northeastern Brazil, on a population with high anaemia prevalence. Two local daycare units with similar characteristics were selected and the children at one of them received a 30 g pack three times a week, representing a total iron daily intake of 6.96 mg. The other daycare unit was followed as a control. The capillary haemoglobin concentration was determined for the children at both daycare units, at the beginning of the study and after a two-month intervention period. The mean haemoglobin concentration in the test group at the beginning of the intervention was 11.8 g/dL, which increased to 13.1 g/dL at the end of the intervention. In the control group these figures remained practically constant (11.6-11.8 g/dL). These represented a dramatic and significant drop in anaemia prevalence, from 61.5% to 11.5% in the test group, and an insignificant reduction (63.1-57.7%) in the control group. The acceptance of the fortified snack was excellent and no undesirable effects were observed. (C) 2007 Published by Elsevier Ltd.

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Much recent research has focused on the use of species distribution models to explore the influence(s) of environment (predominantly climate) on species’ distributions. A weakness of this approach is that it typically does not consider effects of biotic interactions, including competition, on species’ distributions.
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Here we identify and quantify the contribution of environmental factors relative to biotic factors (interspecific competition) to the distribution and abundance of three large, wide-ranging herbivores, the antilopine wallaroo (Macropus antilopinus), common wallaroo (Macropus robustus) and eastern grey kangaroo (Macropus giganteus), across an extensive zone of sympatry in tropical northern Australia.
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To assess the importance of competition relative to habitat features, we constructed models of abundance for each species incorporating habitat only and habitat + the abundance of the other species, and compared their respective likelihoods using Akaike's information criterion. We further assessed the importance of variables predicting abundance across models for each species.
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The best-supported models of antilopine wallaroo and eastern grey kangaroo abundance included both habitat and the abundance of the other species, providing evidence of interspecific competition. Contrastingly, models of common wallaroo abundance were largely influenced by climate and not the abundance of other species. The abundance of antilopine wallaroos was most influenced by water availability, eastern grey kangaroo abundance and the frequency of late season fires. The abundance of eastern grey kangaroos was most influenced by aspects of climate, antilopine wallaroo abundance and a measure of cattle abundance.
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Our study demonstrates that where census and habitat data are available, it is possible to reveal species’ interactions (and measure their relative strength and direction) between large, mobile and/or widely-distributed species for which competition is difficult to demonstrate experimentally. This allows discrimination of the influences of environmental factors and species interactions on species’ distributions, and should therefore improve the predictive power of species distribution models.

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Finite Element (FE) model updating has been attracting research attentions in structural engineering fields for over 20 years. Its immense importance to the design, construction and maintenance of civil and mechanical structures has been highly recognised. However, many sources of uncertainties may affect the updating results. These uncertainties may be caused by FE modelling errors, measurement noises, signal processing techniques, and so on. Therefore, research efforts on model updating have been focusing on tackling with uncertainties for a long time. Recently, a new type of evolutionary algorithms has been developed to address uncertainty problems, known as Estimation of Distribution Algorithms (EDAs). EDAs are evolutionary algorithms based on estimation and sampling from probabilistic models and able to overcome some of the drawbacks exhibited by traditional genetic algorithms (GAs). In this paper, a numerical steel simple beam is constructed in commercial software ANSYS. The various damage scenarios are simulated and EDAs are employed to identify damages via FE model updating process. The results show that the performances of EDAs for model updating are efficient and reliable.

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This paper proposes an effective VAR planning based on reactive power margin for the enhancement of dynamic voltage stability in distribution networks with distributed wind generation. The analysis is carried over a distribution test system representative of the Kumamoto area in Japan. The detailed mathematical modeling of the system is also presented. Firstly, this paper provides simulation results showing the effects of composite load on voltage dynamics in the distribution network through an accurate time-domain analysis. Then, a cost-effective combination of shunt capacitor bank and distribution static synchronous compensator (D-STATCOM) is selected to ensure fast voltage recovery after a sudden disturbance. The analysis shows that the proposed approach can reduce the size of compensating devices, which in turn, reduces the cost. It also reduces power loss of the system.

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This paper presents potential barriers to integrate the squirrel cage induction generator (SCIG) and doubly fed induction generator (DFIG) type wind turbine in distribution networks. The analysis is carried out over a 16 bus distribution test system. Both static and dynamic analyses are performed to see the impact of two different generators on the distribution system. The simulation results show that both SCIG and DFIG type wind turbines have significant impact on the static voltage stability, power loss, and dynamic behavior of the system, which should be taken into account to improve systems performance before integrating wind generation in existing distribution networks.

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In this paper, simulation results showing the effect of lower and higher penetration of distributed wind generation on the voltage profile in distribution systems have been presented. The analysis is carried out over two distribution test systems. The detailed mathematical modeling of the system is also presented. It also investigates the small-signal stability of distribution systems using eigenvalue approach. The analyses show that voltage variation problems occur in different nodes of the distribution networks with an increase of penetration level. However, proper selection of dispersion level can improve the voltage profile of the distribution systems

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This paper presents a novel control design for D-STATCOM to ensure grid code-compatible performance of distributed wind generators. The approach considered in this paper is to find the smallest upper bound on the H norm of the uncertain system and to design an optimal linear quadratic Gaussian (LQG) controller based on this bound. The change in the model due to variations of induction motor (IM) load compositions in the composite load is considered as an uncertain term in the design algorithm. The performance of the designed controller is demonstrated on a distribution test system representative of the Kumamoto area in Japan. It is found that the proposed controller enhances voltage stability of the distribution system under varying operating conditions