918 resultados para Orthodontic Space Closure
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This article uses census data for Berkshire to argue that large-scale counterurbanization began much earlier than is generally recognized in some parts of southern England. This was not just movement down the urban hierarchy, which as Pooley and Turnbull have demonstrated was a long-term feature of England’s settlement system, but in some cases at least amenity-driven migration to rural areas of the kind increasingly recognized as a core component of recent counterurbanization. Despite a reduction of acreage Berkshire’s rural districts saw a 54% rise in population between 1901 and 1951. The sub-regional pattern of growth is assessed to gauge whether ‘clean break’ migration to the remote west of the county (which remained effectively out of commuting range from London throughout the period) was taking place, or whether counterurbanization was confined to the more accessible eastern districts. However, whilst population did increase in both west and east, it was in fact the central districts that grew most impressively. Three case study parishes are investigated in order to gauge the nature and consequences of counterurbanization at a local level. Professional and business migrants figure prominently, seeking to preserve and promote the rural attributes of their new communities, without however cutting their ties to urban centres. It is argued that migration to rural Berkshire in the first half of the twentieth century cannot adequately be described either as a form of extended suburbanization or an anti-metropolitan ‘clean break’. Rather, early counterurbanization marks the first stage on the long road to a post-productivist countryside, in which countryside becomes detached from agriculture, there is socio-economic convergence between town and country, and the ‘rural’ increasingly becomes defined by landscape and identity rather than economic function.
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The coarse spacing of automatic rain gauges complicates near-real- time spatial analyses of precipitation. We test the possibility of improving such analyses by considering, in addition to the in situ measurements, the spatial covariance structure inferred from past observations with a denser network. To this end, a statistical reconstruction technique, reduced space optimal interpolation (RSOI), is applied over Switzerland, a region of complex topography. RSOI consists of two main parts. First, principal component analysis (PCA) is applied to obtain a reduced space representation of gridded high- resolution precipitation fields available for a multiyear calibration period in the past. Second, sparse real-time rain gauge observations are used to estimate the principal component scores and to reconstruct the precipitation field. In this way, climatological information at higher resolution than the near-real-time measurements is incorporated into the spatial analysis. PCA is found to efficiently reduce the dimensionality of the calibration fields, and RSOI is successful despite the difficulties associated with the statistical distribution of daily precipitation (skewness, dry days). Examples and a systematic evaluation show substantial added value over a simple interpolation technique that uses near-real-time observations only. The benefit is particularly strong for larger- scale precipitation and prominent topographic effects. Small-scale precipitation features are reconstructed at a skill comparable to that of the simple technique. Stratifying the reconstruction method by the types of weather type classifications yields little added skill. Apart from application in near real time, RSOI may also be valuable for enhancing instrumental precipitation analyses for the historic past when direct observations were sparse.
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To achieve CO2 emissions reductions the UK Building Regulations require developers of new residential buildings to calculate expected CO2 emissions arising from their energy consumption using a methodology such as Standard Assessment Procedure (SAP 2005) or, more recently SAP 2009. SAP encompasses all domestic heat consumption and a limited proportion of the electricity consumption. However, these calculations are rarely verified with real energy consumption and related CO2 emissions. This paper presents the results of an analysis based on weekly head demand data for more than 200 individual flats. The data is collected from recently built residential development connected to a district heating network. A methodology for separating out the domestic hot water use (DHW) and space heating demand (SH) has been developed and compares measured values to the demand calculated using SAP 2005 and 2009 methodologies. The analysis shows also the variance in DHW and SH consumption between both size of the flats and tenure (privately owned or housing association). Evaluation of the space heating consumption includes also an estimation of the heating degree day (HDD) base temperature for each block of flats and its comparison to the average base temperature calculated using the SAP 2005 methodology.
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This paper presents a numerical study of urban air-flow for a group of five buildings that is located at the University of Reading in the United Kingdom. The airflow around these buildings has been simulated by using ANSYS CFD software package. In this study, the association between certain architectural forms: a street canyon, a semi-closure, and a courtyard-like space in a low-rise building complex, and the wind environment were investigated. The analysis of CFD results has provided detailed information on the wind patterns of these urban built forms. The numerical results have been compared with the experimental measurements within the building complex. The observed characteristics of urban wind pattern with respect to the built structures are presented as a guideline. This information is needed for the design and/or performance assessments of systems such as passive and low energy design approach, a natural or hybrid ventilation, and passive cooling. Also, the knowledge of urban wind patterns allows us to develop better design options for the application of renewable energy technologies within urban environment.
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Airflow through urban environments is one of the most important factors affecting human health, outdoor and indoor thermal comfort, air quality and the energy performance of buildings. This paper presents a study on the effects of wind induced airflows through urban built form using statistical analysis. The data employed in the analysis are from the year-long simultaneous field measurements conducted at the University of Reading campus in the United Kingdom. In this study, the association between typical architectural forms and the wind environment are investigated; such forms include: a street canyon, a semi-closure, a courtyard form and a relatively open space in a low-rise building complex. Measured data captures wind speed and wind direction at six representative locations and statistical analysis identifies key factors describing the effects of built form on the resulting airflows. Factor analysis of the measured data identified meteorological and architectural layout factors as key factors. The derivation of these factors and their variation with the studied built forms are presented in detail.
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It has long been assumed that there is a distorted mapping between real and ‘perceived’ space, based on demonstrations of systematic errors in judgements of slant, curvature, direction and separation. Here, we have applied a direct test to the notion of a coherent visual space. In an immersive virtual environment, participants judged the relative distance of two squares displayed in separate intervals. On some trials, the virtual scene expanded by a factor of four between intervals although, in line with recent results, participants did not report any noticeable change in the scene. We found that there was no consistent depth ordering of objects that can explain the distance matches participants made in this environment (e.g. A > B > D yet also A < C < D) and hence no single one-to-one mapping between participants’ perceived space and any real 3D environment. Instead, factors that affect pairwise comparisons of distances dictate participants’ performance. These data contradict, more directly than previous experiments, the idea that the visual system builds and uses a coherent 3D internal representation of a scene.
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We introduce a model for a pair of nonlinear evolving networks, defined over a common set of vertices, sub ject to edgewise competition. Each network may grow new edges spontaneously or through triad closure. Both networks inhibit the other’s growth and encourage the other’s demise. These nonlinear stochastic competition equations yield to a mean field analysis resulting in a nonlinear deterministic system. There may be multiple equilibria; and bifurcations of different types are shown to occur within a reduced parameter space. This situation models competitive peer-to-peer communication networks such as BlackBerry Messenger displacing SMS; or instant messaging displacing emails.
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We propose and analyse a class of evolving network models suitable for describing a dynamic topological structure. Applications include telecommunication, on-line social behaviour and information processing in neuroscience. We model the evolving network as a discrete time Markov chain, and study a very general framework where, conditioned on the current state, edges appear or disappear independently at the next timestep. We show how to exploit symmetries in the microscopic, localized rules in order to obtain conjugate classes of random graphs that simplify analysis and calibration of a model. Further, we develop a mean field theory for describing network evolution. For a simple but realistic scenario incorporating the triadic closure effect that has been empirically observed by social scientists (friends of friends tend to become friends), the mean field theory predicts bistable dynamics, and computational results confirm this prediction. We also discuss the calibration issue for a set of real cell phone data, and find support for a stratified model, where individuals are assigned to one of two distinct groups having different within-group and across-group dynamics.
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Models of the City of London office market are extended by considering a longer time series of data, covering two cycles, and by explicit modeling of asymmetric rental response to supply and demand model. A long run structural model linking demand for office space, real rental levels and office-based employment is estimated and then rental adjustment processes are modeled using an error correction model framework. Adjustment processes are seen to be asymmetric, dependent both on the direction of the supply and demand shock and on the state of the rental market at the time of the shock. A complete system of equations is estimated: unit shocks produce oscillations but there is a return to a steady equilibrium state in the long run.
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This paper discusses concepts of value from the point of view of the user of the space and the counter view of the provider of the same. Land and property are factors of production. The value of the land flows from the use to which it is put, and that in turn, is dependent upon the demand (and supply) for the product or service that is produced/provided from that space. If there is a high demand for the product (at a fixed level of supply), the price will increase and the economic rent for the land/property will increase accordingly. This is the underlying paradigm of Ricardian rent theory where the supply of land is fixed and a single good is produced. In such a case the rent of land is wholly an economic rent. Economic theory generally distinguishes between two kinds of price, price of production or “value in use” (as determined by the labour theory of value), and market price or “value in exchange” (as determined by supply and demand). It is based on a coherent and consistent theory of value and price. Effectively the distinction is between what space is ‘worth’ to an individual and that space’s price of exchange in the market place. In a perfect market where any individual has access to the same information as all others in the market, price and worth should coincide. However in a market where access to information is not uniform, and where different uses compete for the same space, it is more likely that the two figures will diverge. This paper argues that the traditional reliance of valuers to use methods of comparison to determine “price” has led to an artificial divergence of “value in use” and “value in exchange”, but now such comparison are becoming more difficult due to the diversity of lettings in the market place, there will be a requirement to return to fundamentals and pay heed to the thought process of the user in assessing the worth of the space to be let.
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This document contains a report on the work done under the ESA/Ariadna study 06/4101 on the global optimization of space trajectories with multiple gravity assist (GA) and deep space manoeuvres (DSM). The study was performed by a joint team of scientists from the University of Reading and the University of Glasgow.
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Using the formalism of the Ruelle response theory, we study how the invariant measure of an Axiom A dynamical system changes as a result of adding noise, and describe how the stochastic perturbation can be used to explore the properties of the underlying deterministic dynamics. We first find the expression for the change in the expectation value of a general observable when a white noise forcing is introduced in the system, both in the additive and in the multiplicative case. We also show that the difference between the expectation value of the power spectrum of an observable in the stochastically perturbed case and of the same observable in the unperturbed case is equal to the variance of the noise times the square of the modulus of the linear susceptibility describing the frequency-dependent response of the system to perturbations with the same spatial patterns as the considered stochastic forcing. This provides a conceptual bridge between the change in the fluctuation properties of the system due to the presence of noise and the response of the unperturbed system to deterministic forcings. Using Kramers-Kronig theory, it is then possible to derive the real and imaginary part of the susceptibility and thus deduce the Green function of the system for any desired observable. We then extend our results to rather general patterns of random forcing, from the case of several white noise forcings, to noise terms with memory, up to the case of a space-time random field. Explicit formulas are provided for each relevant case analysed. As a general result, we find, using an argument of positive-definiteness, that the power spectrum of the stochastically perturbed system is larger at all frequencies than the power spectrum of the unperturbed system. We provide an example of application of our results by considering the spatially extended chaotic Lorenz 96 model. These results clarify the property of stochastic stability of SRB measures in Axiom A flows, provide tools for analysing stochastic parameterisations and related closure ansatz to be implemented in modelling studies, and introduce new ways to study the response of a system to external perturbations. Taking into account the chaotic hypothesis, we expect that our results have practical relevance for a more general class of system than those belonging to Axiom A.