997 resultados para Mixture function


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Since European settlement, there has been a dramatic increase in the density, cover and distribution of woody plants in former grassland and open woodland. There is a widespread belief that shrub encroachment is synonymous with declines in ecosystem functions, and often it is associated with landscape degradation or desertification. Indeed, this decline in ecosystem functioning is considered to be driven largely by the presence of the shrubs themselves. This prevailing paradigm has been the basis for an extensive program of shrub removal, based on the view that it is necessary to reinstate the original open woodland or grassland structure from which shrublands are thought to have been derived. We review existing scientific evidence, particularly focussed on eastern Australia, to question the notion that shrub encroachment leads to declines in ecosystem functions. We then summarise this scientific evidence into two conceptual models aimed at optimising landscape management to maximise the services provided by shrub-encroached areas. The first model seeks to reconcile the apparent conflicts between the patch- and landscape-level effects of shrubs. The second model identifies the ecosystem services derived from different stages of shrub encroachment. We also examined six ecosystem services provided by shrublands (biodiversity, soil C, hydrology, nutrient provision, grass growth and soil fertility) by using published and unpublished data. We demonstrated the following: (1) shrub effects on ecosystems are strongly scale-, species- and environment-dependent and, therefore, no standardised management should be applied to every case; (2) overgrazing dampens the generally positive effect of shrubs, leading to the misleading relationship between encroachment and degradation; (3) woody encroachment per se does not hinder any of the functions or services described above, rather it enhances many of them; (4) no single shrub-encroachment state (including grasslands without shrubs) will maximise all services; rather, the provision of ecosystem goods and services by shrublands requires a mixture of different states; and (5) there has been little rigorous assessment of the long-term effectiveness of removal and no evidence that this improves land condition in most cases. Our review provides the basis for an improved, scientifically based understanding and management of shrublands, so as to balance the competing goals of providing functional habitats, maintaining soil processes and sustaining pastoral livelihoods.

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Membranes are essential for the integrity and function of the cell. The collective property of the lipid bilayer is critical in providing an optimal functioning environment for membrane proteins. The simple yet well-characterized bacterium Escherichia coli serves an ideal model system to study the function of specific lipids since its lipid content can be easily manipulated. The most abundant lipid in E. coli membrane is phosphatidylethanolamine (PE, 70-80%). A PE-lacking E. coli mutant displays a complex mixture of deficient phenotypes, suggesting a profound role for PE in different aspects of cell function. A novel role of PE as a topological and functional determinant for membrane proteins has been established using lactose permease (LacY) as a model protein. PE is found to be required for energy-dependent uphill transport process of LacY. In PE-lacking membranes, LacY undergoes a dramatic conformational change, and the first half of the protein adopts an inverted topology with respect to the bilayer plane. ^ The work reported here was initiated to understand the molecular properties of lipids that enable their function as topological and functional determinants for membrane proteins. A glycolipid, monoglucosyldiacylglycerol (MGlcDAG) which shares physicochemical similarities with PE, was introduced to PE-lacking E. coli membranes. The introduction of MGlcDAG suppresses many of the PE-deficient phenotypes, and in particular supports the function and native topology of LacY. ^ The lipid-sensitive topogenic signals encoded in the amino acid sequence of LacY were also identified. Native LacY adopts an inverted topology when synthesized without PE, but mutation of specific acidic residues in the cytoplasmic extra-membrane domains can prevent this inversion and supports a native topological organization of LacY in PE-lacking membranes. These results suggest that it is the interplay between the collective charge properties of the lipid bilayer and extra-membrane loops of protein that determines the final orientation of transmembrane domains. By comparing the similarities as well as differences between these two lipids, we established how specific physical and chemical properties of lipids influence various cell functions and elucidated the molecular basis for the novel role of lipids in determining membrane protein topology. ^

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The vestibules of adult guinea pigs were lesioned with gentamicin and then treated with perilymphatic infusion of either of two growth factor mixtures (i.e., GF I or GF II). GF I contained transforming growth factor α (TGFα), insulin-like growth factor type one (IGF-1), and retinoic acid (RA), whereas GF II contained those three factors and brain-derived neurotrophic factor. Treatment with GF I significantly enhanced vestibular hair cell renewal in ototoxin-damaged utricles and the maturation of stereociliary bundle morphology. The addition of brain-derived neurotrophic factor to the GF II infusion mixture resulted in the return of type 1 vestibular hair cells in ototoxin-damaged cristae, and improved vestibular function. These results suggest that growth factor therapy may be an effective treatment for balance disorders that are the result of hair cell dysfunction and/or loss.

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A one-step method for the conversion of isopropyl protected guaiacols to the corresponding acetates is reported. Treating 6-substituted isopropyl protected guaiacols with trimethylsilyl trifluoromethanesulfonate in a mixture of acetic anhydride and acetonitrile affords 6-substituted guaiacol acetates in yields ranging from 35% to 99%. (C) 2003 Elsevier Ltd. All rights reserved.

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Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

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Minimization of a sum-of-squares or cross-entropy error function leads to network outputs which approximate the conditional averages of the target data, conditioned on the input vector. For classifications problems, with a suitably chosen target coding scheme, these averages represent the posterior probabilities of class membership, and so can be regarded as optimal. For problems involving the prediction of continuous variables, however, the conditional averages provide only a very limited description of the properties of the target variables. This is particularly true for problems in which the mapping to be learned is multi-valued, as often arises in the solution of inverse problems, since the average of several correct target values is not necessarily itself a correct value. In order to obtain a complete description of the data, for the purposes of predicting the outputs corresponding to new input vectors, we must model the conditional probability distribution of the target data, again conditioned on the input vector. In this paper we introduce a new class of network models obtained by combining a conventional neural network with a mixture density model. The complete system is called a Mixture Density Network, and can in principle represent arbitrary conditional probability distributions in the same way that a conventional neural network can represent arbitrary functions. We demonstrate the effectiveness of Mixture Density Networks using both a toy problem and a problem involving robot inverse kinematics.

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Mixture Density Networks (MDNs) are a well-established method for modelling the conditional probability density which is useful for complex multi-valued functions where regression methods (such as MLPs) fail. In this paper we extend earlier research of a regularisation method for a special case of MDNs to the general case using evidence based regularisation and we show how the Hessian of the MDN error function can be evaluated using R-propagation. The method is tested on two data sets and compared with early stopping.

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Training Mixture Density Network (MDN) configurations within the NETLAB framework takes time due to the nature of the computation of the error function and the gradient of the error function. By optimising the computation of these functions, so that gradient information is computed in parameter space, training time is decreased by at least a factor of sixty for the example given. Decreased training time increases the spectrum of problems to which MDNs can be practically applied making the MDN framework an attractive method to the applied problem solver.

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People readily perceive smooth luminance variations as being due to the shading produced by undulations of a 3-D surface (shape-from-shading). In doing so, the visual system must simultaneously estimate the shape of the surface and the nature of the illumination. Remarkably, shape-from-shading operates even when both these properties are unknown and neither can be estimated directly from the image. In such circumstances humans are thought to adopt a default illumination model. A widely held view is that the default illuminant is a point source located above the observer's head. However, some have argued instead that the default illuminant is a diffuse source. We now present evidence that humans may adopt a flexible illumination model that includes both diffuse and point source elements. Our model estimates a direction for the point source and then weights the contribution of this source according to a bias function. For most people the preferred illuminant direction is overhead with a strong diffuse component.

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The aim of this paper is to establish some mixture distributions that arise in stochastic processes. Some basic functions associated with the probability mass function of the mixture distributions, such as k-th moments, characteristic function and factorial moments are computed. Further we obtain a three-term recurrence relation for each established mixture distribution.

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Understanding how aquatic species grow is fundamental in fisheries because stock assessment often relies on growth dependent statistical models. Length-frequency-based methods become important when more applicable data for growth model estimation are either not available or very expensive. In this article, we develop a new framework for growth estimation from length-frequency data using a generalized von Bertalanffy growth model (VBGM) framework that allows for time-dependent covariates to be incorporated. A finite mixture of normal distributions is used to model the length-frequency cohorts of each month with the means constrained to follow a VBGM. The variances of the finite mixture components are constrained to be a function of mean length, reducing the number of parameters and allowing for an estimate of the variance at any length. To optimize the likelihood, we use a minorization–maximization (MM) algorithm with a Nelder–Mead sub-step. This work was motivated by the decline in catches of the blue swimmer crab (BSC) (Portunus armatus) off the east coast of Queensland, Australia. We test the method with a simulation study and then apply it to the BSC fishery data.

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The aim was to evaluate the relationship between orofacial function, dentofacial morphology, and bite force in young subjects. Three hundred and sixteen subjects were divided according to dentition stage (early, intermediate, and late mixed and permanent dentition). Orofacial function was screened using the Nordic Orofacial Test-Screening (NOT-S). Orthodontic treatment need, bite force, lateral and frontal craniofacial dimensions and presence of sleep bruxism were also assessed. The results were submitted to descriptive statistics, normality and correlation tests, analysis of variance, and multiple linear regression to test the relationship between NOT-S scores and the studied independent variables. The variance of NOT-S scores between groups was not significant. The evaluation of the variables that significantly contributed to NOT-S scores variation showed that age and presence of bruxism related to higher NOT-S total scores, while the increase in overbite measurement and presence of closed lip posture related to lower scores. Bite force did not show a significant relationship with scores of orofacial dysfunction. No significant correlations between craniofacial dimensions and NOT-S scores were observed. Age and sleep bruxism were related to higher NOT-S scores, while the increase in overbite measurement and closed lip posture contributed to lower scores of orofacial dysfunction.

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In this study, we investigated the effect of low density lipoprotein receptor (LDLr) deficiency on gap junctional connexin 36 (Cx36) islet content and on the functional and growth response of pancreatic beta-cells in C57BL/6 mice fed a high-fat (HF) diet. After 60 days on regular or HF diet, the metabolic state and morphometric islet parameters of wild-type (WT) and LDLr-/- mice were assessed. HF diet-fed WT animals became obese and hypercholesterolaemic as well as hyperglycaemic, hyperinsulinaemic, glucose intolerant and insulin resistant, characterizing them as prediabetic. Also they showed a significant decrease in beta-cell secretory response to glucose. Overall, LDLr-/- mice displayed greater susceptibility to HF diet as judged by their marked cholesterolaemia, intolerance to glucose and pronounced decrease in glucose-stimulated insulin secretion. HF diet induced similarly in WT and LDLr-/- mice, a significant decrease in Cx36 beta-cell content as revealed by immunoblotting. Prediabetic WT mice displayed marked increase in beta-cell mass mainly due to beta-cell hypertrophy/replication. Nevertheless, HF diet-fed LDLr-/- mice showed no significant changes in beta-cell mass, but lower islet-duct association (neogenesis) and higher beta-cell apoptosis index were seen as compared to controls. The higher metabolic susceptibility to HF diet of LDLr-/- mice may be explained by a deficiency in insulin secretory response to glucose associated with lack of compensatory beta-cell expansion.

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This study aimed to evaluate long-term atrophy in contralateral hippocampal volume after surgery for unilateral MTLE, as well as the cognitive outcome for patients submitted to either selective transsylvian amygdalohippocampectomy (SelAH) or anterior temporal lobe resection (ATL). We performed a longitudinal study of 47 patients with MRI signs of unilateral hippocampal sclerosis (23 patients with right-sided hippocampal sclerosis) who underwent surgical treatment for MTLE. They underwent preoperative/postoperative high-resolution MRI as well as neuropsychological assessment for memory and estimated IQ. To investigate possible changes in the contralateral hippocampus of patients, we included 28 controls who underwent two MRIs at long-term intervals. The volumetry using preoperative MRI showed significant hippocampal atrophy ipsilateral to the side of surgery when compared with controls (p<0.0001) but no differences in contralateral hippocampal volumes. The mean postoperative follow-up was 8.7 years (± 2.5 SD; median=8.0). Our patients were classified as Engel I (80%), Engel II (18.2%), and Engel III (1.8%). We observed a small but significant reduction in the contralateral hippocampus of patients but no volume changes in controls. Most of the patients presented small declines in both estimated IQ and memory, which were more pronounced in patients with left TLE and in those with persistent seizures. Different surgical approaches did not impose differences in seizure control or in cognitive outcome. We observed small declines in cognitive scores with most of these patients, which were worse in patients with left-sided resection and in those who continued to suffer from postoperative seizures. We also demonstrated that manual volumetry can reveal a reduction in volume in the contralateral hippocampus, although this change was mild and could not be detected by visual analysis. These new findings suggest that dynamic processes continue to act after the removal of the hippocampus, and further studies with larger groups may help in understanding the underlying mechanisms.

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In Brazil, the consumption of extra-virgin olive oil (EVOO) is increasing annually, but there are no experimental studies concerning the phenolic compound contents of commercial EVOO. The aim of this work was to optimise the separation of 17 phenolic compounds already detected in EVOO. A Doehlert matrix experimental design was used, evaluating the effects of pH and electrolyte concentration. Resolution, runtime and migration time relative standard deviation values were evaluated. Derringer's desirability function was used to simultaneously optimise all 37 responses. The 17 peaks were separated in 19min using a fused-silica capillary (50μm internal diameter, 72cm of effective length) with an extended light path and 101.3mmolL(-1) of boric acid electrolyte (pH 9.15, 30kV). The method was validated and applied to 15 EVOO samples found in Brazilian supermarkets.