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The main objective of this paper is to handle the trajectory tracking control for a class of three-wheel mobile robot by using a novel adaptive robust control. The mobile robot consists of nonholonomic constraints and uncertainties. The uncertainties include initial condition offset, mass, and moment of inertia of the system, which are time-varying and bounded (unknown). The control force in analytical form is obtained by UK theory, and the adaptive robust control is formulated to handle the uncertainties. For estimating the unknown bounds of uncertainties, the leakage-type adaptive law is designed, which can automatically adjust its own value according to the trajectory tracking errors. Then we verify the uniform boundedness and uniform ultimate boundedness of the proposed control by Lyapunov method. Finally, numerical simulations are conducted to show the trajectory tracking effectiveness of the designed control method. [ABSTRACT FROM AUTHOR]

• A novel model of loop metro service driven by stochastic demand of general distribution. • A Markov decision process for optimal schedule with circulation of limited rolling stock. • An actor-critic deep reinforcement learning framework with an off-policy training algorithm. • A case study demonstrating the efficiency and robustness of the proposed control system. This paper presents a novel actor-critic deep reinforcement learning approach for metro train scheduling with circulation of limited rolling stock. The scheduling problem is modeled as a Markov decision process driven by stochastic passenger demand. As in most dynamic optimization problems, the complexity of the scheduling process grows exponentially with the amount of states, decisions, and uncertainties involved. This study aims to address this 'curses of dimensionality' issue by adopting an actor-critic deep reinforcement learning solution framework. The framework simplifies the evaluation and searching process for potential optimal solutions by parameterizing the original state and decision spaces with the use of artificial neural networks. A deep deterministic policy gradient algorithm is developed for training the artificial neural networks via simulated system transitions before the actor-critic agent can be applied for online schedule control. The proposed approach is tested with a real-world scenario configured with data collected from the Victoria Line of London Underground, UK. Experiment results illustrate the advantages of the proposed method over a range of established meta-heuristics in terms of computing time, system efficiency, and robustness under different stochastic environments. This study innovates urban transit operations with state-of-the-art computer science and dynamic optimization techniques. [ABSTRACT FROM AUTHOR]

This paper analyses aggregate time-series data to estimate the direct rebound effect in UK road freight over the period 1970–2014. We investigate 25 different model specifications, conduct a comprehensive set of diagnostic tests to evaluate the robustness of these specifications and estimate the rebound effect using three different elasticities. Using the mean of the statistically significant estimates from these specifications, we estimate a direct rebound effect of 61% - which is larger than previous estimates in the literature and almost twice as large as the consensus estimate of direct rebound effects in road passenger transport. Using the mean of the estimates from our most robust models, we estimate a slightly lower direct rebound effect of 49%. Our estimates are fairly consistent between different model specifications and different metrics, although individual estimates range from 21% to 137%. We also find that an increasing proportion of UK road freight is being undertaken by foreign registered vehicles, and that increases in the vehicle weight limits have encouraged more freight activity. We highlight the significant limitations imposed by the use of aggregate time series data and recommend that further studies in this area employ data from vehicle use surveys. [ABSTRACT FROM AUTHOR]

Previous research has demonstrated a significant relationship between the geographical distance from a voter to a candidate and the likelihood of the voter choosing that candidate. However, models of this relationship may be mis- or under-specified, by not taking into account voters' perceptions of distance or not controlling for other possible factors related to a candidate's ‘localness’ which may influence vote choice. Using a two-wave panel survey carried out during the 2015 UK General Election, this article tests a more fully specified alternative-specific multinomial probit model of candidate-voter distance. We show that, although the effect size is smaller than in previous tests, candidate-voter distance mattered in the 2015 General Election, an effect that is robust to controls not only for party support and incumbency, as previous research had demonstrated, but also to measures of voter information, candidate presence and marginality. We also find that contiguity mattered: candidates living in non-neighbouring constituencies have a lower likelihood of vote than those living in neighbouring constituencies or in the constituency itself. [ABSTRACT FROM AUTHOR]

Summary Floods pose multi-dimensional hazards to critical infrastructure and society and these hazards may increase under climate change. While flood conditions are dependent on catchment type and soil conditions, seasonal precipitation extremes also play an important role. The extreme precipitation events driving flood occurrence may arrive non-uniformly in time. In addition, their seasonal and inter-annual patterns may also cause sequences of several events and enhance likely flood responses. Spatial and temporal patterns of extreme daily precipitation occurrence are characterized across the UK. Extreme and very heavy daily precipitation is not uniformly distributed throughout the year, but exhibits spatial differences, arising from the relative proximity to the North Atlantic Ocean or North Sea. Periods of weeks or months are identified during which extreme daily precipitation occurrences are most likely to occur, with some regions of the UK displaying multimodal seasonality. A Generalized Additive Model is employed to simulate extreme daily precipitation occurrences over the UK from 1901 to 2010 and to allow robust statistical testing of temporal changes in the seasonal distribution. Simulations show that seasonality has the strongest correlation with intra-annual variations in extreme event occurrence, while Sea Surface Temperature (SST) and Mean Sea Level Pressure (MSLP) have the strongest correlation with inter-annual variations. The north and west of the UK are dominated by MSLP in the mid-North Atlantic and the south and east are dominated by local SST. All regions now have a higher likelihood of autumnal extreme daily precipitation than earlier in the twentieth century. This equates to extreme daily precipitation occurring earlier in the autumn in the north and west, and later in the autumn in the south and east. The change in timing is accompanied by increases in the probability of extreme daily precipitation occurrences during the autumn, and in the number of days with a very high probability of an extreme event. These results indicate a higher probability of several extreme occurrences in succession and a potential increase in flooding. [ABSTRACT FROM AUTHOR]

• A gasifier design was compared with two reaction rate models. • A standard laboratory gasifier test-bed is proposed and built using a flexible design strategy. • An Arduino based robust instrumentation and control system was successfully demonstrated. • A novel seed-propagated hybrid Miscanthus gasification trials were successful. • New opportunities for growing Miscanthus variety in harsher environments, for energy crops. Biomass gasification remains an attractive option to impact climate chaos; however, the technology presents challenges in tolerance to feedstock variability and tar production, which can limit the overall process efficiency, gasifier performance, durability and downstream syngas utilisation. The primary objectives of this study were to compare two gasifier design approaches using different reaction kinetics, based on multiple or singular oxidation and gasification reactions, and build and test a novel, flexible, laboratory-scale downdraft gasifier to convert pellets from UK hybrid Miscanthus into syngas, whilst deploying inexpensive instrumentation methods. The experimental gasification parameters studied were carbon conversion efficiency, gas yield, cold gas efficiency and gas heating values. The performance study shows that the system achieved good average temperature (842–866 °C) in the reduction zones for equivalence ratios between 0.25 and 0.35. The optimum values for carbon conversion efficiency, cold gas efficiency, heating values (HHV) of product gas and gas yield were 74%, 32%, 4.17 MJ/m3 and 1.32 m3/kg (biomass) , respectively. The reported performance parameters for the new seed-propagated hybrid Miscanthus in the present study were comparable to those from conventional Miscanthus pellet gasification in downdraft gasifiers but these new hybrid varieties offer advantages in productivity over broader climatic regions compared to conventional varieties. [ABSTRACT FROM AUTHOR]

The article discusses the use of "First of a Kind" and "Nth of a kind" (FOAK-NOAK) concept in the construction of nuclear power station and its robustness. Topics include the benefits of using the FOAK-NOAK concept in reducing the cost and time of manufacture, the modelling studies of nuclear systems in Great Britain which rely on an assued FOAK improvement model, and the need to use reality check to complete the examination of FOAK-NOAK based on public domain information.

Abstract: We present a 10-stage reconstruction of the evolution in ice-flow patterns of the last British Ice Sheet from build-up to demise derived from geomorphological evidence. 100 flowsets identified in the subglacial bedform record (drumlins, mega-scale glacial lineations, and ribbed moraine) are combined with ancillary evidence (erratic-transport paths, absolute dates and a semi-independently reconstructed retreat pattern) to define flow patterns, ice divides and ice-sheet margins during build-up, maximum glaciation and retreat. Overprinting and cross-cutting of landform assemblages are used to define the relative chronology of flow patterns and a tentative absolute chronology is presented based on a collation of available dates for ice advance and retreat. The ice-flow configuration of the last British Ice Sheet was not static. Some ice divides were remarkably stable, persisting through multiple stages of the ice-sheet evolution, whereas others were transient features existing for a short time and/or shifting in position 10s km. The 10 reconstructed stages of ice-sheet geometry capture two main modes of operation; first as an integrated ice sheet with a broadly N–S orientated ice divide, and second as a multi-domed ice sheet orientated parallel with the shelf edge. A thick integrated ice sheet developed as ice expanded out of source areas in Scotland to envelop southerly ice caps in northern England and Wales, and connect with the Irish Ice Sheet to the west and the Scandinavian Ice Sheet across the North Sea. Following break-up of ice over the North Sea, ice streaming probably drove mass loss and ice-sheet thinning to create a more complex divide structure, where ice-flow patterns were largely controlled by the form of the underlying topography. Ice surface lowering occurred before separation of, and retreat to, multiple ice centres centred over high ground. We consider this 10-stage reconstruction of the evolution in ice-sheet configuration to be the simplest palaeo-glaciological interpretation of the flowsets identified from the geomorphological record and their relative timing. This empirically-based reconstruction of flow-pattern geometry provides a framework for more detailed local and regional studies and numerical modelling to provide robust explanations of the observed changes in ice-sheet structure in terms of climate and glacial dynamics. As a minimum, numerical model outputs should be able to reproduce the identified flowset patterns in space and satisfy their chronological order. [Copyright &y& Elsevier]

Global GHG emissions continue to rise, with nearly a quarter of it due to trade that is not currently captured within global climate policy. In the context of current trade patterns and limited global cooperation on climate change, the feasibility of consumption-based emissions accounting to contribute to a more comprehensive (national) policy framework in the UK is investigated. Consumption-based emissions results for the UK from a range of models are presented, their technical robustness is assessed, and their potential application in national climate policy is examined using examples of policies designed to reduce carbon leakage and to address high levels of consumption. It is shown that there is a need to include consumption-based emissions as a complementary indicator to the current approach of measuring territorial emissions. Methods are shown to be robust enough to measure progress on climate change and develop and inform mitigation policy. Finally, some suggestions are made for future policy-oriented research in the area of consumption-based accounting that will facilitate its application to policy. Policy relevance Emissions embodied in trade are rapidly increasing and there is thus a growing gap between production emissions and the emissions associated with consumption. This is a growing concern due to the absence of a global cap and significant variation in country-level mitigation ambitions. Robust measurements of consumption-based emissions are possible and provide new insights into policy options. This includes trade-related policy (e.g. border carbon adjustments) and domestic policies (e.g. resource efficiency strategies). As climate policy targets deepen, there is a need for a broad range of policy options in addition to production and technological solutions. Consumption-based emissions are complementary to production-based emissions inventories, which are still the most accurate estimate for aggregated emissions at the global level. However, without consumption-based approaches, territorial emissions alone will not provide a complete picture of progress in regional and national emissions reduction. [ABSTRACT FROM PUBLISHER]

Abstract: The authors review recent scholarly and policy initiatives in respect of media pluralism and argue that contradictions between policy objectives, in analytical approaches and deficiencies in some established methodologies mean that robust conclusions have been hard to secure. They argue that concerns about diminishing pluralism are likely to grow in consequence of changes in a dominant legacy media funding model as advertising revenues move online. Examining UK data, they argue that a contemporary focus of concern, growing concentration in privately owned media, is overshadowed by the striking dominance of the publicly owned BBC and suggest established analytical methodologies used to analyse market power may offer a valuable analogy in the definition and measurement of pluralism issues. They consider possible alternatives to regulation as means of enhancing pluralism and propose the use of subsidised entry. [Copyright &y& Elsevier]

Abstract: Curriculum tracking creates incentives in the years before its start, and we should therefore expect test scores to be higher during those years. I find robust evidence for incentive effects of tracking in the UK based on the UK comprehensive school reform. Results from the Swedish comprehensive school reform are inconclusive. Internationally, I find a large and widening test score gap between early and late tracking countries. Incentive effects of tracking show how early age scores can be endogenous with respect to later-age policies, and add to a growing literature on incentives in education. [Copyright &y& Elsevier]

Abstract: An energy system model, UK MARKAL, is combined with decomposition analysis and sensitivity analysis to derive mitigation costs and emissions reduction potentials in the UK transport sector. The paper tests the robustness of a marginal abatement cost curve for the year 2030 for two parameters: path dependency and discount rate. Path dependency is found to be a significant, yet not substantial, influencing factor on the shape and the structure of the marginal abatement cost curve. Doubling the technology-specific hurdle rates shows that abatement costs increase significantly. The results suggest that policy makers should be aware of the underlying carbon tax pathway and whether results are based on society’s view or a private perspective. [Copyright &y& Elsevier]

Concerns about the social sustainability of emerging technologies are identified as a motivation behind recent interest in public engagement as a mode of formal technology assessment, nanoscale science and technology (NST) being a key example. Two rival understandings of engagement as a contribution to social sustainability, namely 'restoring trust' and 'building robustness' are identified. These different approaches are analysed as strategic responses to the politics of uncertainty in technological societies, each reflecting different assumptions about how to domesticate an intrinsically uncertain future. Government-sponsored experiments with upstream engagement around NST in the UK were surrounded by rhetoric concerning the need to build robustness into how nanotechnologies develop. It is argued, however, that assumptions held by policy and business actors about the strategic value of narratives of restoring trust, together with deeply embedded assumptions about how technological innovation creates the future, tended to place obstacles in the way of turning this aspiration into reality. [ABSTRACT FROM AUTHOR]

Efficient, practical and accurate estimates of population parameters are a necessary basis for effective conservation action to meet biodiversity targets. The brown hare is representative of many European farmland species: historically widespread and abundant but having undergone rapid declines as a result of agricultural intensification. As a priority species in the UK Biodiversity Action Plan, it has national targets for population increase that are part of wider national environmental indicators. Previous research has indicated that brown hare declines have been greatest in pastural landscapes and that gains might be made by focussing conservation effort there. We therefore used hares in pastural landscapes to examine how basic changes in survey methodology can affect the precision of population density estimates and related these to national targets for biodiversity conservation in the UK. Line transects for hares carried out at night resulted in higher numbers of detections, had better-fitting detection functions and provided more robust density estimates with lower effort than those during the day, due primarily to the increased probability of detection of hares at night and the nature of hare responses to the observer. Hare spring densities varied widely within a single region, with a pooled mean of 20.6 hares km-2, significantly higher than the reported national average of hares in pastures of 3.3 hares km-2. The high number of encounters allowed us to resolve hare densities at site, season and year scales. We demonstrate how survey conduct can impact on data quantity and quality with implications for setting and monitoring biodiversity targets. Our case study of the brown hare provides evidence that for wildlife species with low detectability, large scale volunteer-based monitoring programmes, either species specific or generalist, might be more successfully and efficiently carried out by a small number of trained personnel able to employ methods that maximise detectability. [ABSTRACT FROM AUTHOR]

Summary: This study introduces new approaches to improve the statistical robustness of techniques for quantifying the fractal scaling of groundwater levels, and uses these techniques to investigate scaling of groundwater levels from a consolidated permeable carbonate aquifer. Six groundwater level time series and an associated river stage time series from the unconfined Chalk aquifer (a dual-porosity, fractured limestone aquifer) in the Pang–Lambourn catchment, UK, have been analysed. Surrogate data of time series with known scaling properties have been used to estimate the probability distribution of the spectral and geometric scaling exponents determined by detrended fluctuation analysis (DFA) and power spectral density (PSD) respectively; robust regression techniques have been used to improve estimates of the scaling exponents; and robust non-parametric techniques have been used to correlate scaling exponents with features of the boreholes and catchments. Strong statistical support has been found for temporal scaling of groundwater levels over a wide range of time scales, however, bootstrap estimates of the scaling exponents indicate a much larger range of exponents than found by previous studies, suggesting that the uncertainty in existing estimates of scaling exponents may be too small. There is robust evidence that geometrical scaling properties at each borehole can be related to the depth of the observation boreholes and distance of those boreholes from the river in the catchment, but no such correlations were found for the spectral scaling exponents. The results build on the body of evidence that groundwater levels, as with many hydrogeological phenomena, may be well modelled with mathematical concepts from statistical mechanics that do not attempt to capture every detail of these highly heterogeneous and complex systems. [ABSTRACT FROM AUTHOR]

Rationale, aims and objectives Learning is recognized to be at the heart of the quality improvement process in the National Health Service (NHS). However, the challenge will be how to ensure that learning becomes embedded within the NHS culture. The aim of this study is to identify a robust feedback process and format in which practices could receive data on their responses to a Learning Practice Inventory (a diagnostic instrument designed to identify a practice’s capacity for collective learning and change). Method Five practices volunteered to test the instrument, and it was distributed to all members of the primary care team. A process was worked through to identify different formats for presenting scores within and between practices. The preferred method of data presentation was sought, and an evaluation gathered information on the preferred form of feedback, the usefulness of the data, the clarity of the questions and the level of interest in receiving further information. Results Eighty-five staff from five practices completed the questionnaire, and 61 individuals completed the evaluation forms. In most cases, there was a spread of scores by staff within practices and across the scale of 1–10. Medians were clustered at the learning practice end for all five practices. However, despite this skew, there were sometimes quite large differences between practices in their median scores. Conclusion Our study suggests that a robust feedback process on collective capacity for learning and change can be identified that is useful and feasible. A key implication is that some form of educational support is required, and this work will take place as part of an ongoing programme of research by the authors. [ABSTRACT FROM AUTHOR]

In 2002, the commercial digital terrestrial television service in the United Kingdom had a technological revival Since its first broadcast in 1998, there have been a number of reception issues concerning Digital Video Broadcasting - Terrestrial (DVB-T). As a result, the modulation method has changed in order to maximize the coverage and minimize errors. The consequence of changing the modulation method to a more robust system is that the overall throughput must suffer. Therefore, a trade-off between throughput and robustness must be made. This paper will detail the results of experiments performed to ascertain the justification of changing the modulation method in a DVB-T compliant system from 64-QAM to 16- QAM when transmitted at Radio Frequencies (RF) when subjected to multipath with long path delays as is normal in a Single Frequency Network (SFN). [ABSTRACT FROM AUTHOR]

• Representative pathways can be sought to characterise a larger pathway ensemble. • Clustering performance is sensitive to the distribution of pathways. • K-means is the most robust approach for pathway grouping. • Hierarchical clustering might perform better if pathway distribution is irregular. • Sectoral standardisation can reveal the trade-offs between metrics in each sector. Long-term decarbonisation pathways to achieve ambitious low-carbon targets involve a range of uncertainties. Different energy system modelling approaches can be used to systematically evaluate the influence of the uncertainties, but this often leads to an unmanageable number of pathways. Summarising the large ensemble through a more limited number of representative pathways, to inform stakeholders, can be challenging. This study thus explores how to identify representative decarbonisation pathways using clustering algorithms, which can assist in grouping similar data points in uncategorised datasets, such as pathway ensembles. However, the suitability of clustering algorithms for pathway characterisation has not been investigated to date. Hence, k-means, hierarchical clustering, Gaussian mixture model, spectral clustering, and density-based clustering are adopted for comparisons. An illustrative pathway ensemble for the United Kingdom is applied to evaluate their performance based on cluster validity indices. Three metric transformations, including power, standardisation and sectoral standardisation, are also applied to create three additional sets of pathways for testing. The k-means algorithm is found to outperform others consistently, although hierarchical clustering might also be applicable if the distribution of pathway proximity is uneven. The results also highlight the utility of the approach in revealing distinctive trade-offs between technologies among the identified representative pathways. For instance, the electrification of heating can be replaced by district heating in the residential sector. The described, novel approach can be applied to characterise other sets of pathways, with greater technological details generated by any energy system models, to reveal insights for long-term decarbonisation. [ABSTRACT FROM AUTHOR]

Large terrain datasets provide the foundation for much of the work carried out by the British Geological Survey (BGS) in developing various environmental data products for a wide range of users. With high resolution data being more readily available today than ever before, it is vital that [1] a given dataset is kept up-to-date and [2] any uncertainty associated with the dataset is effectively accounted for and communicated. We present the workflow implemented by the BGS to maintain elevation datasets as well as the process undertaken to account for the uncertainties associated with derivative products, both as a result of the input elevation data and the methods and approaches available to calculate the various metrics. We also present a range of approaches that have been investigated and implemented to enable effective processing and delivery of these large datasets.For the management of our most recently acquired terrain dataset of Great Britain, we have developed a complete workflow which maintains full version control of all original data provided whilst enabling the seamless integration of updates as they become available. This provides the basis for the key area of development: accounting for the uncertainty associated with the derivatives based on these terrain data. This is of vital importance for the BGS as where products are developed – e.g. BGS GeoSure which was developed to enable the identification of areas subject to specific geohazards – we ensure that they reliable, repeatable and robust. Uncertainty surface calculations for each derivative (e.g. slope, aspect, curvature) are based on a Monte Carlo approach. The overall process enables the assessment of both the differences between the various methods available for a given derivative calculation and the potential uncertainty that may be introduced by the input terrain data. The uncertainty associated with each derivative provides a standalone dataset which can then be used within the larger product development cycle. The provision of robust measures of uncertainty are key when developing and delivering geospatial data products and yet this information can remain hard to acquire, especially with regard to its spatial distribution. This is ever more important where a given product or dataset is promoted based on measures of improved accuracy and granularity. The approach that has been developed and will be presented has improved the transparency and reliability of the input layers that we use throughout our product development life cycle. [ABSTRACT FROM AUTHOR]