27 resultados para Longitudinal Growth Modelling


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Arrays of nickel and gold nanorods have been grown on glass and silicon substrates using porous alumina templates of less than 500 nm thickness. A method is demonstrated for varying the diameter of the nanorods whilst keeping the spacing constant. Optical extinction spectra for the gold nanorods show two distinct maxima associated with the transverse and longitudinal axes of the rods. Adding small quantities of oxygen to the aluminium before anodization is found to improve the sharpness of the extinction peaks. The spectral position of the longitudinal peak is shown to be sensitive to the nanorod diameter for constant length and spacing. For the nickel nanorods it is shown that the magnetic properties are governed by both interactions between the wires and shape anisotropy.

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Signal transduction pathways describe the dynamics of cellular response to input signalling molecules at receptors on the cell membrane. The Mitogen-Activated Protein Kinase (MAPK) cascade is one of such pathways that are involved in many important cellular processes including cell growth and proliferation. This paper describes a black-box model of this pathway created using an advanced two-stage identification algorithm. Identification allows us to capture the unique features and dynamics of the pathway and also opens up the possibility of regulatory control design. In the approach described, an optimal model is obtained by performing model subset selection in two stages, where the terms are first determined by a forward selection method and then modified using a backward selection model refinement. The simulation results demonstrate that the model selected using the two-stage algorithm performs better than with the forward selection method alone.

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Aim: Species loss has increased significantly over the last 1000 years and is ultimately attributed to the direct and indirect consequences of increased human population growth across the planet. A growing number of species are becoming endangered and require human intervention to prevent their local extirpation or complete extinction. Management strategies aimed at mitigating a species loss can benefit greatly from empirical approaches that indicate the rate of decline of a species providing objective information on the need for immediate conservation actions, e.g. captive breeding; however, this is rarely employed. The current study used a novel method to examine the distributional trends of a model endangered species, the freshwater pearl mussel, Margaritifera margaritifera (L.).
Location: United Kingdom and Republic of Ireland.
Methods: Using species presence data within 10-km grid squares since records began three-parameter logistic regression curves were fitted to extrapolate an estimated date of regional extinction.
Results: This study has shown that freshwater pearl mussel distribution has contracted since known historical records and outlier populations were lost first. Within the United Kingdom and Republic of Ireland, distribution loss has been greatest in Scotland, Northern Ireland, Wales and England, respectively, with the Republic of Ireland containing the highest relative proportion of M. margaritifera distribution, in 1998.
Main conclusions: This study provides empirical evidence that this species could become extinct throughout countries within the United Kingdom within 170 years under the current trends and emphasizes that regionally specific management strategies need to be implemented to prevent extirpation of this species.

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The design of medical devices could be very much improved if robust tools were available for computational simulation of tissue response to the presence of the implant. Such tools require algorithms to simulate the response of tissues to mechanical and chemical stimuli. Available methodologies include those based on the principle of mechanical homeostasis, those which use continuum models to simulate biological constituents, and the cell-centred approach, which models cells as autonomous agents. In the latter approach, cell behaviour is governed by rules based on the state of the local environment around the cell; and informed by experiment. Tissue growth and differentiation requires simulating many of these cells together. In this paper, the methodology and applications of cell-centred techniques-with particular application to mechanobiology-are reviewed, and a cell-centred model of tissue formation in the lumen of an artery in response to the deployment of a stent is presented. The method is capable of capturing some of the most important aspects of restenosis, including nonlinear lesion growth with time. The approach taken in this paper provides a framework for simulating restenosis; the next step will be to couple it with more patient-specific geometries and quantitative parameter data.

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The use of joint modelling approaches is becoming increasingly popular when an association exists between survival and longitudinal processes. Widely recognized for their gain in efficiency, joint models also offer a reduction in bias compared with naïve methods. With the increasing popularity comes a constantly expanding literature on joint modelling approaches. The aim of this paper is to give an overview of recent literature relating to joint models, in particular those that focus on the time-to-event survival process. A discussion is provided on the range of survival submodels that have been implemented in a joint modelling framework. A particular focus is given to the recent advancements in software used to build these models. Illustrated through the use of two different real-life data examples that focus on the survival of end-stage renal disease patients, the use of the JM and joineR packages within R are demonstrated. The possible future direction for this field of research is also discussed. © 2013 International Statistical Institute.

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Two models that can predict the voltage-dependent scattering from liquid crystal (LC)-based reflectarray cells are presented. The validity of both numerical techniques is demonstrated using measured results in the frequency range 94-110 GHz. The most rigorous approach models, for each voltage, the inhomogeneous and anisotropic permittivity of the LC as a stratified media in the direction of the biasing field. This accounts for the different tilt angles of the LC molecules inside the cell calculated from the solution of the elastic problem. The other model is based on an effective homogeneous permittivity tensor that corresponds to the average tilt angle along the longitudinal direction for each biasing voltage. In this model, convergence problems associated with the longitudinal inhomogeneity are avoided, and the computation efficiency is improved. Both models provide a correspondence between the reflection coefficient (losses and phase-shift) of the LC-based reflectarray cell and the value of biasing voltage, which can be used to design beam scanning reflectarrays. The accuracy and the efficiency of both models are also analyzed and discussed.

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The momentum term has long been used in machine learning algorithms, especially back-propagation, to improve their speed of convergence. In this paper, we derive an expression to prove the O(1/k2) convergence rate of the online gradient method, with momentum type updates, when the individual gradients are constrained by a growth condition. We then apply these type of updates to video background modelling by using it in the update equations of the Region-based Mixture of Gaussians algorithm. Extensive evaluations are performed on both simulated data, as well as challenging real world scenarios with dynamic backgrounds, to show that these regularised updates help the mixtures converge faster than the conventional approach and consequently improve the algorithm’s performance.

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Building Information Modelling (BIM) is growing in pace, not only in design and construction stages, but also in the analysis of facilities throughout their life cycle. With this continued growth and utilisation of BIM processes, comes the possibility to adopt such procedures, to accurately measure the energy efficiency of buildings, to accurately estimate their energy usage. To this end, the aim of this research is to investigate if the introduction of BIM Energy Performance Assessment in the form of software analysis, provides accurate results, when compared with actual energy consumption recorded. Through selective sampling, three domestic case studies are scrutinised, with baseline figures taken from existing energy providers, the results scrutinised and compared with calculations provided from two separate BIM energy analysis software packages. Of the numerous software packages available, criterion sampling is used to select two of the most prominent platforms available on the market today. The two packages selected for scrutiny are Integrated Environmental Solutions - Virtual Environment (IES-VE) and Green Building Studio (GBS). The results indicate that IES-VE estimated the energy use in region of ±8% in two out of three case studies while GBS estimated usage approximately ±5%. The findings indicate that the introduction of BIM energy performance assessment, using proprietary software analysis, is a viable alternative to manual calculations of building energy use, mainly due to the accuracy and speed of assessing, even the most complex models. Given the surge in accurate and detailed BIM models and the importance placed on the continued monitoring and control of buildings energy use within today’s environmentally conscious society, this provides an alternative means by which to accurately assess a buildings energy usage, in a quick and cost effective manner.

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Rhizosphere processes play a key role in nutrient cycling in terrestrial ecosystems. Plant rhizodeposits supply low-molecular weight carbon substrates to the soil microbial community, resulting in elevated levels of activity surrounding the root. Mechanistic compartmental models that aim to model carbon flux through the rhizosphere have been reviewed and areas of future research necessary to better calibrate model parameters have been identified. Incorporating the effect of variation in bacterial biomass physiology on carbon flux presents a considerable challenge to experimentalists and modellers alike due to the difficulties associated with differentiating dead from dormant cells. A number of molecular techniques that may help to distinguish between metabolic states of bacterial cells are presented. The calibration of growth, death and maintenance parameters in rhizosphere models is also discussed. A simple model of rhizosphere carbon flow has been constructed and a sensitivity analysis was carried out on the model to highlight which parameters were most influential when simulating carbon flux. It was observed that the parameters that most heavily influenced long-term carbon compartmentalisation in the rhizosphere were exudation rate and biomass yield. It was concluded that future efforts to simulate carbon flow in the rhizosphere should aim to increase ecological realism in model structure.

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The shallow water kelp Laminaria digitata, abundant in coastal zones of the North Atlantic, is exposed to a range of hydrodynamic environments that makes it ideal for assessing the role of water motion on their growth rate. Here we quantify the growth of L. digitata, as a factor of blade and stipe elongation, at sites adjacent to Strangford Lough, Northern Ireland under different hydrodynamic conditions over a one year period. A modelling approach was used to numerically determine both the temporal and spatial variability of the hydrodynamic environment. Ambient seawater nutrient concentrations, temperature and irradiance were measured as well as the internal nutrient status of the L. digitata populations. Kelp populations growing in the greatest and lowest water motion showed the lowest growth rates. Differences observed in growth rate could not be attributed to seawater nutrient availability, temperature or light. The internal nutrient status also suggested no influence on the observed differences in growth rate. Therefore if there are minimal differences in light, temperature and nutrients between sites, then populations of L. digitata exposed to different water motions are likely to exhibit different growth rates. It is suggested that the growth rate differences observed were a function of water motion with the possibility that, in response to the hydrodynamic forces experienced by the algal cells, L. digitata kelps in the high energy environments were putting more energy into strengthening cell walls rather than blade elongation

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Objective
Scant evidence is available on the discordance between loneliness and social isolation among older adults. We aimed to investigate this discordance and any health implications that it may have.

Method
Using nationally representative datasets from ageing cohorts in Ireland (TILDA) and England (ELSA), we created a metric of discordance between loneliness and social isolation, to which we refer as Social Asymmetry. This metric was the categorised difference between standardised scores on a scale of loneliness and a scale of social isolation, giving categories of: Concordantly Lonely and Isolated, Discordant: Robust to Loneliness, or Discordant: Susceptible to Loneliness. We used regression and multilevel modelling to identify potential relationships between Social Asymmetry and cognitive outcomes.

Results
Social Asymmetry predicted cognitive outcomes cross-sectionally and at a two-year follow-up, such that Discordant: Robust to Loneliness individuals were superior performers, but we failed to find evidence for Social Asymmetry as a predictor of cognitive trajectory over time.

Conclusions
We present a new metric and preliminary evidence of a relationship with clinical outcomes. Further research validating this metric in different populations, and evaluating its relationship with other outcomes, is warranted.

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The predictive capability of high fidelity finite element modelling, to accurately capture damage and crush behaviour of composite structures, relies on the acquisition of accurate material properties, some of which have necessitated the development of novel approaches. This paper details the measurement of interlaminar and intralaminar fracture toughness, the non-linear shear behaviour of carbon fibre (AS4)/thermoplastic Polyetherketoneketone (PEKK) composite laminates and the utilisation of these properties for the accurate computational modelling of crush. Double-cantilever-beam (DCB), four-point end-notched flexure (4ENF) and Mixed-mode bending (MMB) test configurations were used to determine the initiation and propagation fracture toughness in mode I, mode II and mixed-mode loading, respectively. Compact Tension (CT) and Compact Compression (CC) test samples were employed to determine the intralaminar longitudinal tensile and compressive fracture toughness. V-notched rail shear tests were used to measure the highly non-linear shear behaviour, associated with thermoplastic composites, and fracture toughness. Corresponding numerical models of these tests were developed for verification and yielded good correlation with the experimental response. This also confirmed the accuracy of the measured values which were then employed as input material parameters for modelling the crush behaviour of a corrugated test specimen.