182 resultados para integrated nested Laplace approximation


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Purpose: Private social and environmental reporting (SER) has grown considerably in recent years, consistent with a rise in institutional investor engagement and dialogue with investee companies. We interpret the emergence of integrated private reporting through the lens of institutional logics. We frame the emergence of integrated private reporting as a merging of two hitherto separate and possibly rival institutional logics. Methodology/Approach: We interviewed 19 companies listed on the FTSE100 and 20 UK institutional investors. The interviews were semi-structured and analysed in an interpretive fashion. Findings and Implications: We provide evidence to suggest that private SER is beginning to merge with private financial reporting and that, as a result integrated private reporting is emerging. This trend is mirroring the international trend in public reporting toward an integrated approach. Specifically, we find that specialist social responsible investment managers are starting to attend private financial reporting meetings whilst mainstream fund managers are starting to attend private meetings on environmental, social and governance (ESG) issues. Further, senior company directors are becoming increasingly conversant with ESG issues. We interpret our findings as two possible scenarios: (i) there is a genuine hybridisation occurring in UK institutional investment such that integrated private reporting is emerging, or; (ii) the financial logic is absorbing and effectively neutralising the responsible investment logic. Originality: This is the first research investigating the evolution of private integrated reporting.

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An efficient data based-modeling algorithm for nonlinear system identification is introduced for radial basis function (RBF) neural networks with the aim of maximizing generalization capability based on the concept of leave-one-out (LOO) cross validation. Each of the RBF kernels has its own kernel width parameter and the basic idea is to optimize the multiple pairs of regularization parameters and kernel widths, each of which is associated with a kernel, one at a time within the orthogonal forward regression (OFR) procedure. Thus, each OFR step consists of one model term selection based on the LOO mean square error (LOOMSE), followed by the optimization of the associated kernel width and regularization parameter, also based on the LOOMSE. Since like our previous state-of-the-art local regularization assisted orthogonal least squares (LROLS) algorithm, the same LOOMSE is adopted for model selection, our proposed new OFR algorithm is also capable of producing a very sparse RBF model with excellent generalization performance. Unlike our previous LROLS algorithm which requires an additional iterative loop to optimize the regularization parameters as well as an additional procedure to optimize the kernel width, the proposed new OFR algorithm optimizes both the kernel widths and regularization parameters within the single OFR procedure, and consequently the required computational complexity is dramatically reduced. Nonlinear system identification examples are included to demonstrate the effectiveness of this new approach in comparison to the well-known approaches of support vector machine and least absolute shrinkage and selection operator as well as the LROLS algorithm.

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IntFOLD is an independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance. The only required input to the server is an amino acid sequence for the target protein. Here we describe major performance and user interface updates to the server, which comprises an integrated pipeline of methods for: tertiary structure prediction, global and local 3D model quality assessment, disorder prediction, structural domain prediction, function prediction and modelling of protein-ligand interactions. The server has been independently validated during numerous CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiments, as well as being continuously evaluated by the CAMEO (Continuous Automated Model Evaluation) project. The IntFOLD server is available at: http://www.reading.ac.uk/bioinf/IntFOLD/

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The Monte Carlo Independent Column Approximation (McICA) is a flexible method for representing subgrid-scale cloud inhomogeneity in radiative transfer schemes. It does, however, introduce conditional random errors but these have been shown to have little effect on climate simulations, where spatial and temporal scales of interest are large enough for effects of noise to be averaged out. This article considers the effect of McICA noise on a numerical weather prediction (NWP) model, where the time and spatial scales of interest are much closer to those at which the errors manifest themselves; this, as we show, means that noise is more significant. We suggest methods for efficiently reducing the magnitude of McICA noise and test these methods in a global NWP version of the UK Met Office Unified Model (MetUM). The resultant errors are put into context by comparison with errors due to the widely used assumption of maximum-random-overlap of plane-parallel homogeneous cloud. For a simple implementation of the McICA scheme, forecasts of near-surface temperature are found to be worse than those obtained using the plane-parallel, maximum-random-overlap representation of clouds. However, by applying the methods suggested in this article, we can reduce noise enough to give forecasts of near-surface temperature that are an improvement on the plane-parallel maximum-random-overlap forecasts. We conclude that the McICA scheme can be used to improve the representation of clouds in NWP models, with the provision that the associated noise is sufficiently small.

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A sequential extraction method was utilized to analyze seven forms of P in an integrated vertical-flow constructed wetland (IVFCW) containing earthworms and different substrates. The aluminum-bound P (Al-P) content was found to be lower, and the occluded P (Oc-P) content was higher in the IVFCW. The addition of earthworms into the influent chamber of IVFCW increased the exchange P (Ex-P), iron-bound P (Fe-P), calcium bound P (Ca-P), Oc-P, detritus-bound (De-P) and organic P (Org-P) content in the influent chamber, and also enhanced P content uptake by wetland plants. A significantly positive correlation between P content of above-ground wetland plants and the Ex-P, Fe-P, Oc-P and Org-P content in the rhizosphere was found (P < 0.05), which indicated that the Ex-P, Fe-P, Oc-P and Org-P could be bio-available P. The Ex-P, Fe-P, De-P, Oc-P and Ca-P content of the influent chamber was higher where the substrate contained a mixture of Qing sand and river sand rather than only river sand. Also the IVFCW with earthworms and both Qing sand and river sand had a higher removal efficiency of P, which was related to higher P content uptake by wetland plants and P retained in IVFCW. These findings suggest that addition of earthworms in IVFCW increases the bioavailable P content, resulting in enhanced P content uptake by wetland plants.

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In this paper an equation is derived for the mean backscatter cross section of an ensemble of snowflakes at centimeter and millimeter wavelengths. It uses the Rayleigh–Gans approximation, which has previously been found to be applicable at these wavelengths due to the low density of snow aggregates. Although the internal structure of an individual snowflake is random and unpredictable, the authors find from simulations of the aggregation process that their structure is “self-similar” and can be described by a power law. This enables an analytic expression to be derived for the backscatter cross section of an ensemble of particles as a function of their maximum dimension in the direction of propagation of the radiation, the volume of ice they contain, a variable describing their mean shape, and two variables describing the shape of the power spectrum. The exponent of the power law is found to be −. In the case of 1-cm snowflakes observed by a 3.2-mm-wavelength radar, the backscatter is 40–100 times larger than that of a homogeneous ice–air spheroid with the same mass, size, and aspect ratio.

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Current approaches for the reduction of carbon emissions in buildings are often predicated on the integration of renewable technologies into building projects. Building integrated photovoltaics (BIPV) is one of these technologies and brings its own set of challenges and problems with a resulting mutual articulation of this technology and the building. A Social Construction of Technology (SCOT) approach explores how negotiations between informal groups of project actors with shared interests shape the ongoing specification of both BIPV and the building. Six main groups with different interests were found to be involved in the introduction of BIPV (Cost Watchers, Design Aesthetes, Green Guardians, Design Optimizers, Generation Maximizers and Users). Their involvement around three sets of issues (design changes from lack of familiarity with the technology, misunderstandings from unfamiliar interdependencies of trades and the effects of standard firm procedure) is followed. Findings underline how BIPV requires a level of integration that typically spans different work packages and how standard contractual structures inhibit the smooth incorporation of BIPV. Successful implementation is marked by ongoing (re-)design of both the building and the technology as informal fluid groups of project actors with shared interests address the succession of problems which arise in the process of implementation.

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Innovative, low carbon technologies are already available for use in the construction of buildings, but the impact of their specification on construction projects is unclear. This exploratory research identifies issues which arise following the specification of BIPV in non-residential construction projects. Rather than treating the inclusion of a new technology as a technical problem, the research explores the issue from a socio-technical perspective to understand the accommodations which the project team makes and their effect on the building and the technology. The paper is part of a larger research project which uses a Social Construction of Technology Approach (SCOT) to explore the accommodations made to working practices and design when Building Integrated PhotoVoltaic (BIPV) technology is introduced. The approach explores how the requirements of the technology from different groups of actors (Relevant Social Groups or RSG's) give rise to problems and create solutions. As such it rejects the notion of a rational linear view of innovation diffusion; instead it suggests that the variety and composition of the Relevant Social Groups set the agenda for problem solving and solutions as the project progresses. The research explores the experiences of three people who have extensive histories of involvement with BIPV in construction, looks at how SCOT can inform our understanding of the issues involved and identifies themes and issues in the specification of BIPV on construction projects. A key finding concerns the alignment of inflection points at which interviewees have found themselves changing from one RSG to another as new problems and solutions are identified. The points at which they change RSG often occurred at points which mirror conventional construction categories (in terms of project specification, tender, design and construction).

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Applying geophysical techniques to detect and map the physical extent of individual unmarked graves proves difficult in many cases. The success of individual geophysical techniques for detecting unmarked graves may be due to a poor understanding of the nature of the graves themselves, the context in which they lie in, and temporal changes to the burial state. Given the unpredictability of these variables, it is surprising that grave prospection is often undertaken using only a single method. This paper presents a multi-methodological survey strategy for detecting unmarked burials and utilises an analytical approach for visualising and evaluating survey results.

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We compare measurements of integrated water vapour (IWV) over a subarctic site (Kiruna, Northern Sweden) from five different sensors and retrieval methods: Radiosondes, Global Positioning System (GPS), ground-based Fourier-transform infrared (FTIR) spectrometer, ground-based microwave radiometer, and satellite-based microwave radiometer (AMSU-B). Additionally, we compare also to ERA-Interim model reanalysis data. GPS-based IWV data have the highest temporal coverage and resolution and are chosen as reference data set. All datasets agree reasonably well, but the ground-based microwave instrument only if the data are cloud-filtered. We also address two issues that are general for such intercomparison studies, the impact of different lower altitude limits for the IWV integration, and the impact of representativeness error. We develop methods for correcting for the former, and estimating the random error contribution of the latter. A literature survey reveals that reported systematic differences between different techniques are study-dependent and show no overall consistent pattern. Further improving the absolute accuracy of IWV measurements and providing climate-quality time series therefore remain challenging problems.

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Complex products such as manufacturing equipment have always needed maintenance and repair services. Increasingly, leading manufacturers are integrating products and services to generate increased revenues and achieve customer satisfaction. Designing integrated products and services requires a different approach to new product development and a clear understanding of how customers perceive the value they obtain from actual usage of products and services—so-called value-in-use. However, there is a lack of research on integrated products and services and how they impact customer satisfaction. An exploratory study was undertaken to understand customers’ views on integrated products and services and the value-in-use derived from such offerings. As value-in-use and its impacts are complicated concepts, a technique from psychology—Repertory Grid Technique—was used to gather data in 33 interviews. The interviews allowed a deep understanding of customer views on integrated products and services to be obtained, and a systematic analysis identified the key attributes of value-in-use. In order to probe further, the data were then analyzed using Honey’s procedure, which identified the impact of the attributes of value-in-use on customer satisfaction. Two key attributes—relational dynamic and access—were found to have the most influence on customer satisfaction. This paper contributes to the innovation field by identifying customer needs for integrated products and services and how these impact customer satisfaction. These are key points and need to be fully considered by managers during new product and service development. Similarly, the paper identifies a number of important areas for further research.

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In this work, we prove a weak Noether-type Theorem for a class of variational problems that admit broken extremals. We use this result to prove discrete Noether-type conservation laws for a conforming finite element discretisation of a model elliptic problem. In addition, we study how well the finite element scheme satisfies the continuous conservation laws arising from the application of Noether’s first theorem (1918). We summarise extensive numerical tests, illustrating the conservation of the discrete Noether law using the p-Laplacian as an example and derive a geometric-based adaptive algorithm where an appropriate Noether quantity is the goal functional.