925 resultados para Wave-function Approach


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This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

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The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis-Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models-a fixed effects model and a random effects model-are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed. (c) 2004 Elsevier B.V. All rights reserved.

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We discuss recent progress towards the establishment of important structure-property-function relationships in eumelanins-key functional bio-macromolecular systems responsible for photoprotection and immune response in humans, and implicated in the development of melanoma skin cancer. We focus on the link between eumelanin's secondary structure and optical properties such as broad band UV-visible absorption and strong non-radiative relaxation; both key features of the photo-protective function. We emphasise the insights gained through a holistic approach combining optical spectroscopy with first principles quantum chemical calculations, and advance the hypothesis that the robust functionality characteristic of eumelanin is related to extreme chemical and structural disorder at the secondary level. This inherent disorder is a low cost natural resource, and it is interesting to speculate as to whether it may play a role in other functional bio-macromolecular systems.

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Tropical deforestation is the major contemporary threat to global biodiversity, because a diminishing extent of tropical forests supports the majority of the Earth's biodiversity. Forest clearing is often spatially concentrated in regions where human land use pressures, either planned or unplanned, increase the likelihood of deforestation. However, it is not a random process, but often moves in waves originating from settled areas. We investigate the spatial dynamics of land cover change in a tropical deforestation hotspot in the Colombian Amazon. We apply a forest cover zoning approach which permitted: calculation of colonization speed; comparative spatial analysis of patterns of deforestation and regeneration; analysis of spatial patterns of mature and recently regenerated forests; and the identification of local-level hotspots experiencing the fastest deforestation or regeneration. The colonization frontline moved at an average of 0.84 km yr(-1) from 1989 to 2002, resulting in the clearing of 3400 ha yr(-1) of forests beyond the 90% forest cover line. The dynamics of forest clearing varied across the colonization front according to the amount of forest in the landscape, but was spatially concentrated in well-defined 'local hotspots' of deforestation and forest regeneration. Behind the deforestation front, the transformed landscape mosaic is composed of cropping and grazing lands interspersed with mature forest fragments and patches of recently regenerated forests. We discuss the implications of the patterns of forest loss and fragmentation for biodiversity conservation within a framework of dynamic conservation planning.

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The effects of dredging on the benthic communities in the Noosa River, a subtropical estuary in SE Queensland, Australia, were examined using a 'Beyond BACF experimental design. Changes in the numbers and types of animals and characteristics of the sediments in response to dredging in the coarse sandy sediments near the mouth of the estuary were compared with those occurring naturally in two control regions. Samples were collected twice before and twice after the dredging operations, at multiple spatial scales, ranging from metres to kilometres. Significant effects from the dredging were detected on the abundance of some polychaetes and bivalves and two measures of diversity (numbers of polychaete families and total taxonomic richness). In addition, the dredging caused a significant increase in the diversity of sediment particle sizes found in the dredged region compared with elsewhere. Community composition in the dredged region was more similar to that in the control regions after dredging than before. Changes in the characteristics of the sedimentary environment as a result of the dredging appeared to lead to the benthic communities of the dredged region becoming more similar to those elsewhere in the estuary, so dredging in this system may have led to the loss or reduction in area of a specific type of habitat in the estuary with implications for overall patterns of biodiversity and ecosystem function. (c) 2006 Elsevier B.V. All rights reserved.

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Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

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Consider a haploid population and, within its genome, a gene whose presence is vital for the survival of any individual. Each copy of this gene is subject to mutations which destroy its function. Suppose one member of the population somehow acquires a duplicate copy of the gene, where the duplicate is fully linked to the original gene's locus. Preservation is said to occur if eventually the entire population consists of individuals descended from this one which initially carried the duplicate. The system is modelled by a finite state-space Markov process which in turn is approximated by a diffusion process, whence an explicit expression for the probability of preservation is derived. The event of preservation can be compared to the fixation of a selectively neutral gene variant initially present in a single individual, the probability of which is the reciprocal of the population size. For very weak mutation, this and the probability of preservation are equal, while as mutation becomes stronger, the preservation probability tends to double this reciprocal. This is in excellent agreement with simulation studies.

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Exercise brachial blood pressure ( BP) predicts mortality, but because of wave reflection, central ( ascending aortic) pressure differs from brachial pressure. Exercise central BP may be clinically important, and a noninvasive means to derive it would be useful. The purpose of this study was to test the validity of a noninvasive technique to derive exercise central BP. Ascending aortic pressure waveforms were recorded using a micromanometer-tipped 6F Millar catheter in 30 patients (56 +/- 9 years; 21 men) undergoing diagnostic coronary angiography. Simultaneous recordings of the derived central pressure waveform were acquired using servocontrolled radial tonometry at rest and during supine cycling. Pulse wave analysis of the direct and derived pressure signals was performed offline (SphygmoCor 7.01). From rest to exercise, mean arterial pressure and heart rate were increased by 20 +/- 10 mm Hg and 15 +/- 7 bpm, respectively, and central systolic BP ranged from 77 to 229 mm Hg. There was good agreement and high correlation between invasive and noninvasive techniques with a mean difference (+/- SD) for central systolic BP of -1.3 +/- 3.2 mm Hg at rest and -4.7 +/- 3.3 mm Hg at peak exercise ( for both r=0.995; P < 0.001). Conversely, systolic BP was significantly higher peripherally than centrally at rest (155 +/- 33 versus 138 +/- 32mm Hg; mean difference, -16.3 +/- 9.4mm Hg) and during exercise (180 +/- 34 versus 164 +/- 33 mm Hg; mean difference, -15.5 +/- 10.4 mm Hg; for both P < 0.001). True myocardial afterload is not reliably estimated by peripheral systolic BP. Radial tonometry and pulse wave analysis is an accurate technique for the noninvasive determination of central BP at rest and during exercise.

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Efficient insulin action requires spatial and temporal coordination of signaling cascades. The prototypical insulin receptor substrate, IRS-1 plays a central role in insulin signaling. By subcellular fractionation IRS-1 is enriched in a particulate fraction, termed the high speed pellet (HSP), and its redistribution from this fraction is associated with signal attenuation and insulin resistance. Anecdotal evidence suggests the cytoskeleton may underpin the localization of IRS-1 to the HSP. In the present study we have taken a systematic approach to examine whether the cytoskeleton contributes to the subcellular fractionation properties and function of IRS-1. By standard microscopy or immunoprecipitation we were unable to detect evidence to support a specific interaction between IRS-1 and the major cytoskeletal components actin (microfilaments), vimentin (intermediate filaments), and tubulin (microtubules) in 3T3-L1 adipocytes or in CHO.IR.IRS-1 cells. Pharmacological disruption of microfilaments and microtubules, individually or in combination, was without effect on the subcellular distribution of IRS-1 or insulin-stimulated tyrosine phosphorylation in either cell type. Phosphorylation of Akt was modestly reduced (20-35%) in 3T3-L1 adipocytes but not in CHO.IR.IRS-1 cells. In cells lacking intermediate filaments (Vim(-/-)) IRS-1 expression, distribution and insulin-stimulated phosphorylation appeared normal. Even after depolymerisation of microfilaments and microtubules, insulin-stimulated phosphorylation of IRS-1 and Akt were maintained in Vim-/- cells. Taken together these data indicate that the characteristic subcellular fractionation properties and function of IRS-1 are unlikely to be mediated by cytoskeletal networks and that proximal insulin signaling does not require an intact cytoskeleton. (c) 2006 Elsevier Ltd. All rights reserved.

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Working memory is an essential component of wide-ranging cognitive functions. It is a complex genetic trait probably influenced by numerous genes that individually have only a small influence. These genes may have an amplified influence on phenotypes closer to the gene action. In this study, event-related potential (ERP) phenotypes recorded during a working-memory task were collected from 656 adolescents from 299 families for whom genotypes were available. Univariate linkage analyses using the MERLIN variance-components method were conducted on slow wave phenotypes recorded at multiple sites while participants were required to remember the location of a target. Suggestive linkage (LOD > 2.2) was found on chromosomes 4, 5, 6, 10, 17, and 20. After correcting for multiple testing, suggestive linkage remained on chromosome 10. Empirical thresholds were computed for the most promising phenotypes. Those on chromosome 10 remained suggestive. A number of genes reported to regulate neural differentiation and function (i.e. NRP1, ANK3, and CHAT) were found under these linkage peaks and may influence the levels of neural activity occurring in individuals participating in a spatial working-memory task.

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An extended refraction-diffraction equation [Massel, S.R., 1993. Extended refraction-diffraction equation for surface waves. Coastal Eng. 19, 97-126] has been applied to predict wave transformation and breaking as well as wave-induced set-up on two-dimensional reef profiles of various shapes. A free empirical coefficient alpha in a formula for the average rate of energy dissipation [epsilon(b)] = (alpha rho g omega/8 pi)(root gh/C)(H-3/h) in the modified periodic bore model was found to be a function of the dimensionless parameter F-c0 = (g(1.25)H(0)(0.5)T(2.5))/h(r)(1.75), proposed by Gourlay [Gourlayl M.R., 1994. Wave transformation on a coral reef. Coastal Eng. 23, 17-42]. The applicability of the developed model has been demonstrated for reefs of various shapes subjected to various incident wave conditions. Assuming proposed relationships of the coefficient alpha and F-c0, the model provides results on wave height attenuation and set-up elevation which compare well with experimental data. (C) 2000 Elsevier Science B.V. All rights reserved.

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The texture segmentation techniques are diversified by the existence of several approaches. In this paper, we propose fuzzy features for the segmentation of texture image. For this purpose, a membership function is constructed to represent the effect of the neighboring pixels on the current pixel in a window. Using these membership function values, we find a feature by weighted average method for the current pixel. This is repeated for all pixels in the window treating each time one pixel as the current pixel. Using these fuzzy based features, we derive three descriptors such as maximum, entropy, and energy for each window. To segment the texture image, the modified mountain clustering that is unsupervised and fuzzy c-means clustering have been used. The performance of the proposed features is compared with that of fractal features.

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A framework is a reusable design that requires software components to function. To instantiate a framework, a software engineer must provide the software components required by the framework. To do this effectively, the framework-component interfaces must be specified so the software engineer knows what assumptions the framework makes about the components, and so the components can be verified against these assumptions. This paper presents an approach to specifying software frameworks. The approach involves the specification of the framework’s syntax, semantics, and the interfaces between the framework and its components. The approach is demonstrated with a simple case study.

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New experimental data are presented on the dynamics of a transient wave group breaking on a beach. The transient group is tracked during shoaling and wave breaking, together with the long waves forced during those processes. High spatial sampling enables novel resolution of the evolution of the wave envelope during breaking and the correlation between the envelope and the long waves. The data show a strong dynamic long wave setup in front of the group in shallow water. The amplitude of the dynamic setup is likely to be a function of beach slope, and larger on steeper beaches.

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This paper reports preliminary progress on a principled approach to modelling nonstationary phenomena using neural networks. We are concerned with both parameter and model order complexity estimation. The basic methodology assumes a Bayesian foundation. However to allow the construction of pragmatic models, successive approximations have to be made to permit computational tractibility. The lowest order corresponds to the (Extended) Kalman filter approach to parameter estimation which has already been applied to neural networks. We illustrate some of the deficiencies of the existing approaches and discuss our preliminary generalisations, by considering the application to nonstationary time series.