979 resultados para B-Functions
Resumo:
Data from six studies with male broilers fed diets covering a wide range of energy and protein were used in the current two analyses. In the first analysis, five models, specifically re-parameterized for analysing energy balance data, were evaluated for their ability to determine metabolizable energy intake at maintenance and efficiency of utilization of metabolizable energy intake for producing gain. In addition to the straight line, two types of functional form were used. They were forms describing (i) diminishing returns behaviour (monomolecular and rectangular hyperbola) and (ii) sigmoidal behaviour with a fixed point of inflection (Gompertz and logistic). These models determined metabolizable energy requirement for maintenance to be in the range 437-573 kJ/kg of body weight/day depending on the model. The values determined for average net energy requirement for body weight gain varied from 7(.)9 to 11(.)2 kJ/g of body weight. These values show good agreement with previous studies. In the second analysis, three types of function were assessed as candidates for describing the relationship between body weight and cumulative metabolizable energy intake. The functions used were: (a) monomolecular (diminishing returns behaviour), (b) Gompertz (smooth sigmoidal behaviour with a fixed point of inflection) and (c) Lopez, France and Richards (diminishing returns and sigmoidal behaviour with a variable point of inflection). The results of this analysis demonstrated that equations capable of mimicking the law of diminishing returns describe accurately the relationship between body weight and cumulative metabolizable energy intake in broilers.
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Landscape narrative, combining landscape and narrative, has been employed to create storytelling layouts and interpretive information in some famous botanic gardens. In order to assess the educational effectiveness of using "landscape narrative" in landscape design, the Heng-Chun Tropical Botanical Garden in Taiwan was chosen as research target for an empirical study. Based on cognitive theory and the affective responses of environmental psychology, computer simulations and video recordings were used to create five themed display areas with landscape narrative elements. Two groups of pupils watched simulated films. The pupils were then given an evaluation test and questionnaire, to determine the effectiveness of the landscape narrative. When the content was well associated and matched with the narrative landscape, the comprehension and retention of content was increased significantly. The results also indicated that visual preference of narrative landscape scenes was increased. This empirical study can be regarded as a successful model of integrating landscape narrative and interpretation practice that can be applied to the design of new theme displays in botanic gardens to improve both the effectiveness of interpretation plans and the visual preference of visitors. (c) 2008 Elsevier B.V. All rights reserved.
Resumo:
The capacity of the surface glycoproteins of enveloped viruses to mediate virus/cell binding and membrane fusion requires a proper thiol/disulfide balance. Chemical manipulation of their redox state using reducing agents or free sulfhydryl reagents affects virus/cell interaction. Conversely, natural thiol/disulfide rearrangements often occur during the cell interaction to trigger fusogenicity, hence the virus entry. We examined the relationship between the redox state of the 20 cysteine residues of the SARS-CoV (severe acute respiratory syndrome coronavirus) Spike glycoprotein S1 subdomain and its functional properties. Mature S1 exhibited similar to 4 unpaired cysteines, and chemically reduced S1 displaying up to similar to 6 additional unpaired cysteines still bound ACE2 and enabled fusion. In addition, virus/cell membrane fusion occurred in the presence of sulfhydryl-blocking reagents and oxidoreductase inhibitors. Thus, in contrast to various viruses including HIV (human immunodeficiency virus) examined in parallel, the functions of the SARS-CoV Spike glycoprotein exhibit a significant and surprising independence of redox state, which may contribute to the wide host range of the virus. These data suggest clues for molecularly engineering vaccine immunogens.
Resumo:
A novel trinuclear nickel(II) complex, [Ni-3(L)(2)(H2O)(2)](ClO4)(2), where L is a bridging unsymmetrical tetradentate ligand, involving o-phenylenediamine, diacetyl monoxime and acetylacetone (H2L = 4-[2-(3-hydroxy-1-methyl-but-2-enylideneamino)-phenylimino]-pentan-2- one oxime) has been synthesized and characterized structurally. In the complex, an octahedral Ni( II) centre is held in the middle by two square planar units with the aid of oxime and ketonic bridges. (c) 2007 Elsevier B. V. All rights reserved.
Resumo:
Time correlation functions yield profound information about the dynamics of a physical system and hence are frequently calculated in computer simulations. For systems whose dynamics span a wide range of time, currently used methods require significant computer time and memory. In this paper, we discuss the multiple-tau correlator method for the efficient calculation of accurate time correlation functions on the fly during computer simulations. The multiple-tau correlator is efficacious in terms of computational requirements and can be tuned to the desired level of accuracy. Further, we derive estimates for the error arising from the use of the multiple-tau correlator and extend it for use in the calculation of mean-square particle displacements and dynamic structure factors. The method described here, in hardware implementation, is routinely used in light scattering experiments but has not yet found widespread use in computer simulations.
Resumo:
Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.
Resumo:
This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.
Resumo:
Biomass allocation to above- and belowground compartments in trees is thought to be affected by growth conditions. To assess the strength of such influences, we sampled six Norway spruce forest stands growing at higher altitudes. Within these stands, we randomly selected a total of 77 Norway spruce trees and measured volume and biomass of stem, above- and belowground stump and all roots over 0.5 cm diameter. A comparison of our observations with models parameterised for lower altitudes shows that models developed for specific conditions may be applicable to other locations. Using our observations, we developed biomass functions (BF) and biomass conversion and expansion factors (BCEF) linking belowground biomass to stem parameters. While both BF and BCEF are accurate in belowground biomass predictions, using BCEF appears more promising as such factors can be readily used with existing forest inventory data to obtain estimates of belowground biomass stock. As an example, we show how BF and BCEF developed for individual trees can be used to estimate belowground biomass at the stand level. In combination with existing aboveground models, our observations can be used to quantify total standing biomass of high altitude Norway spruce stands.
Resumo:
Roots, stems, branches and needles of 160 Norway spruce trees younger than 10 years were sampled in seven forest stands in central Slovakia in order to establish their biomassfunctions (BFs) and biomassexpansionfactors (BEFs). We tested three models for each biomass pool based on the stem base diameter, tree height and the two parameters combined. BEF values decreased for all spruce components with increasing height and diameter, which was most evident in very young trees under 1 m in height. In older trees, the values of BEFs did tend to stabilise at the height of 3–4 m. We subsequently used the BEFs to calculate dry biomass of the stands based on average stem base diameter and tree height. Total stand biomass grew with increasing age of the stands from about 1.0 Mg ha−1 at 1.5 years to 44.3 Mg ha−1 at 9.5 years. The proportion of stem and branch biomass was found to increase with age, while that of needles was fairly constant and the proportion of root biomass did decrease as the stands grew older.
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Snaclecs are small non-enzymatic proteins present in viper venoms reported to modulate haemostasis of victims through effects on platelets, vascular endothelial and smooth muscle cells. In this study, we have isolated and functionally characterised a snaclec which we named rhinocetin from the venom of West African gaboon viper, Bitis gabonica rhinoceros. Rhinocetin was shown to comprise α and β chains with the molecular masses of 13.5 and 13kDa respectively. Sequence and immunoblot analysis of rhinocetin confirmed this to be a novel snaclec. Rhinocetin inhibited collagen-stimulated activation of human platelets in dose dependent manner, but displayed no inhibitory effects on glycoprotein VI (collagen receptor) selective agonist, CRP-XL-, ADP- or thrombin-induced platelet activation. Rhinocetin antagonised the binding of monoclonal antibodies against the α2 subunit of integrin α2β1 to platelets and coimmunoprecipitation analysis confirmed integrin α2β1 as a target for this venom protein. Rhinocetin inhibited a range of collagen induced platelet functions such as fibrinogen binding, calcium mobilisation, granule secretion, aggregation and thrombus formation. It also inhibited integrin α2β1 dependent functions of human endothelial cells. Together, our data suggest rhinocetin to be a modulator of integrin α2β1 function and thus may provide valuable insights into the role of this integrin in physiological and pathophysiological scenarios including haemostasis, thrombosis and envenomation.
Resumo:
Sigma B (σB) is an alternative sigma factor that controls the transcriptional response to stress in Listeria monocytogenes and is also known to play a role in the virulence of this human pathogen. In the present study we investigated the impact of a sigB deletion on the proteome of L. monocytogenes grown in a chemically defined medium both in the presence and in the absence of osmotic stress (0.5 M NaCl). Two new phenotypes associated with the sigB deletion were identified using this medium. (i) Unexpectedly, the strain with the ΔsigB deletion was found to grow faster than the parent strain in the growth medium, but only when 0.5 M NaCl was present. This phenomenon was independent of the carbon source provided in the medium. (ii) The ΔsigB mutant was found to have unusual Gram staining properties compared to the parent, suggesting that σB contributes to the maintenance of an intact cell wall. A proteomic analysis was performed by two-dimensional gel electrophoresis, using cells growing in the exponential and stationary phases. Overall, 11 proteins were found to be differentially expressed in the wild type and the ΔsigB mutant; 10 of these proteins were expressed at lower levels in the mutant, and 1 was overexpressed in the mutant. All 11 proteins were identified by tandem mass spectrometry, and putative functions were assigned based on homology to proteins from other bacteria. Five proteins had putative functions related to carbon utilization (Lmo0539, Lmo0783, Lmo0913, Lmo1830, and Lmo2696), while three proteins were similar to proteins whose functions are unknown but that are known to be stress inducible (Lmo0796, Lmo2391, and Lmo2748). To gain further insight into the role of σB in L. monocytogenes, we deleted the genes encoding four of the proteins, lmo0796, lmo0913, lmo2391, and lmo2748. Phenotypic characterization of the mutants revealed that Lmo2748 plays a role in osmotolerance, while Lmo0796, Lmo0913, and Lmo2391 were all implicated in acid stress tolerance to various degrees. Invasion assays performed with Caco-2 cells indicated that none of the four genes was required for mammalian cell invasion. Microscopic analysis suggested that loss of Lmo2748 might contribute to the cell wall defect observed in the ΔsigB mutant. Overall, this study highlighted two new phenotypes associated with the loss of σB. It also demonstrated clear roles for σB in both osmotic and low-pH stress tolerance and identified specific components of the σB regulon that contribute to the responses observed.
Resumo:
We consider in this paper the solvability of linear integral equations on the real line, in operator form (λ−K)φ=ψ, where and K is an integral operator. We impose conditions on the kernel, k, of K which ensure that K is bounded as an operator on . Let Xa denote the weighted space as |s|→∞}. Our first result is that if, additionally, |k(s,t)|⩽κ(s−t), with and κ(s)=O(|s|−b) as |s|→∞, for some b>1, then the spectrum of K is the same on Xa as on X, for 01. As an example where kernels of this latter form occur we discuss a boundary integral equation formulation of an impedance boundary value problem for the Helmholtz equation in a half-plane.
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Communication signal processing applications often involve complex-valued (CV) functional representations for signals and systems. CV artificial neural networks have been studied theoretically and applied widely in nonlinear signal and data processing [1–11]. Note that most artificial neural networks cannot be automatically extended from the real-valued (RV) domain to the CV domain because the resulting model would in general violate Cauchy-Riemann conditions, and this means that the training algorithms become unusable. A number of analytic functions were introduced for the fully CV multilayer perceptrons (MLP) [4]. A fully CV radial basis function (RBF) nework was introduced in [8] for regression and classification applications. Alternatively, the problem can be avoided by using two RV artificial neural networks, one processing the real part and the other processing the imaginary part of the CV signal/system. A even more challenging problem is the inverse of a CV
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We compare a number of models of post War US output growth in terms of the degree and pattern of non-linearity they impart to the conditional mean, where we condition on either the previous period's growth rate, or the previous two periods' growth rates. The conditional means are estimated non-parametrically using a nearest-neighbour technique on data simulated from the models. In this way, we condense the complex, dynamic, responses that may be present in to graphical displays of the implied conditional mean.