874 resultados para correlation-based feature selection


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This article investigates the expression patterns of 160 genes that are expressed during early mouse development. The cDNAs were isolated from 7.5 d postcoitum (dpc) encloderm, a region that comprises visceral encloderm (VE), definitive encloderm, and the node-tissues that are required for the initial steps of axial specification and tissue patterning in the mouse. To avoid examining the same gene more than once, and to exclude potentially ubiquitously expressed housekeeping genes, cDNA sequence was derived from 1978 clones of the Endoderm library. These yielded 1440 distinct cDNAs, of which 123 proved to be novel in the mouse. In situ hybridization analysis was carried out on 160 of the cDNAs, and of these, 29 (18%) proved to have restricted expression patterns.

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Understanding and predicting the distribution of organisms in heterogeneous environments lies at the heart of ecology, and the theory of density-dependent habitat selection (DDHS) provides ecologists with an inferential framework linking evolution and population dynamics. Current theory does not allow for temporal variation in habitat quality, a serious limitation when confronted with real ecological systems. We develop both a stochastic equivalent of the ideal free distribution to study how spatial patterns of habitat use depend on the magnitude and spatial correlation of environmental stochasticity and also a stochastic habitat selection rule. The emerging patterns are confronted with deterministic predictions based on isodar analysis, an established empirical approach to the analysis of habitat selection patterns. Our simulations highlight some consistent patterns of habitat use, indicating that it is possible to make inferences about the habitat selection process based on observed patterns of habitat use. However, isodar analysis gives results that are contingent on the magnitude and spatial correlation of environmental stochasticity. Hence, DDHS is better revealed by a measure of habitat selectivity than by empirical isodars. The detection of DDHS is but a small component of isodar theory, which remains an important conceptual framework for linking evolutionary strategies in behavior and population dynamics.

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This article examines whether UK portfolio returns are time varying so that expected returns follow an AR(1) process as proposed by Conrad and Kaul for the USA. It explores this hypothesis for four portfolios that have been formed on the basis of market capitalization. The portfolio returns are modelled using a kalman filter signal extraction model in which the unobservable expected return is the state variable and is allowed to evolve as a stationary first order autoregressive process. It finds that this model is a good representation of returns and can account for most of the autocorrelation present in observed portfolio returns. This study concludes that UK portfolio returns are time varying and the nature of the time variation appears to introduce a substantial amount of autocorrelation to portfolio returns. Like Conrad and Kaul if finds a link between the extent to which portfolio returns are time varying and the size of firms within a portfolio but not the monotonic one found for the USA.

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A novel biosensing system based on a micromachined rectangular silicon membrane is proposed and investigated in this paper. A distributive sensing scheme is designed to monitor the dynamics of the sensing structure. An artificial neural network is used to process the measured data and to identify cell presence and density. Without specifying any particular bio-application, the investigation is mainly concentrated on the performance testing of this kind of biosensor as a general biosensing platform. The biosensing experiments on the microfabricated membranes involve seeding different cell densities onto the sensing surface of membrane, and measuring the corresponding dynamics information of each tested silicon membrane in the form of a series of frequency response functions (FRFs). All of those experiments are carried out in cell culture medium to simulate a practical working environment. The EA.hy 926 endothelial cell lines are chosen in this paper for the bio-experiments. The EA.hy 926 endothelial cell lines represent a particular class of biological particles that have irregular shapes, non-uniform density and uncertain growth behaviour, which are difficult to monitor using the traditional biosensors. The final predicted results reveal that the methodology of a neural-network based algorithm to perform the feature identification of cells from distributive sensory measurement has great potential in biosensing applications.

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A study of conveying practice demonstrates that belt conveyors provide a versatile and. much-used method of transporting bulk materials, but a review of belting manufacturers' design procedures shows that belt design and selection rules are often based on experience with all-cotton belts no longer in common use, and are net completely relevant to modern synthetic constructions. In particular, provision of the property "load support", which was not critical with cotton belts, is shown to determine the outcome of most belt selection exercises and lead to gross over specification of other design properties in many cases. The results of an original experimental investigation into this property, carried out to determine the belt and conveyor parameters that affect it, how the major role that belt stiffness plays in its provision; the basis for a belt stiffness test relevant to service conditions is given. A proposal for a more rational method of specifying load support data results from the work, but correlation of the test results with service performance is necessary before the absolute toad support capability required from a belt for given working conditions can be quantified. A study to attain this correlation is the major proposal for future work resulting from the present investigation, but a full review of the literature on conveyor design and a study of present practice within the belting industry demonstrate other, less critical, factors that could profitably be investigated. It is suggested that the most suitable method of studying these would be a rational data collection system to provide information on various facets of belt service behaviour; a basis for such a system is proposed. In addition to the work above, proposals for simplifying the present belt selection methods are made and a strain transducer suitable for use in future experimental investigations is developed.

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Nearest feature line-based subspace analysis is first proposed in this paper. Compared with conventional methods, the newly proposed one brings better generalization performance and incremental analysis. The projection point and feature line distance are expressed as a function of a subspace, which is obtained by minimizing the mean square feature line distance. Moreover, by adopting stochastic approximation rule to minimize the objective function in a gradient manner, the new method can be performed in an incremental mode, which makes it working well upon future data. Experimental results on the FERET face database and the UCI satellite image database demonstrate the effectiveness.

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An array of different structural probes has been used to define the effect of adding Zn and Ti to a sodium-calcium phosphate glass. X-ray absorption spectroscopy at the Zn K-edge suggests that the Zn atoms occupy mixed (4- and 6-fold) sites within the glass matrix. X-ray diffraction reveals a feature at 2.03 angstrom that develops with the addition of Zn and Ti and is consistent with Zn-O and Ti-O near-neighbour distances. Neutron diffraction is used to resolve two distinct P-O distances and highlights the decrease in P center dot center dot center dot P coordination number from 2.0 to 1.7 as the Ti metal concentration rises, which is attributed to the O/P fraction moving away from the metaphosphate value of 3.0 to 3.1 with the addition of Ti. Other correlations, such as those associated with CaO(x) and NaO(x) polyhedra, remain largely unaffected. These results suggest that the network forming P center dot center dot center dot P correlation is most disrupted, with the disorder parameter rising from 0.07 to 0.10 angstrom with the additional modifiers. Zn appears to be introduced into the network as a direct replacement for Ca and causes no structural variation over the composition range studied.

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This article examines whether UK portfolio returns are time varying so that expected returns follow an AR(1) process as proposed by Conrad and Kaul for the USA. It explores this hypothesis for four portfolios that have been formed on the basis of market capitalization. The portfolio returns are modelled using a kalman filter signal extraction model in which the unobservable expected return is the state variable and is allowed to evolve as a stationary first order autoregressive process. It finds that this model is a good representation of returns and can account for most of the autocorrelation present in observed portfolio returns. This study concludes that UK portfolio returns are time varying and the nature of the time variation appears to introduce a substantial amount of autocorrelation to portfolio returns. Like Conrad and Kaul if finds a link between the extent to which portfolio returns are time varying and the size of firms within a portfolio but not the monotonic one found for the USA. © 2004 Taylor and Francis Ltd.