3,734 research outputs found

    Northern range extension of the powerful owl Ninox strenua

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    Transition in housing design and thermal comfort in rural Tanzania

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    This study evaluates the performance of three low-income passive housing designs at providing thermal comfort for their inhabitants in temperate tropical rural Tanzania. Severe climatic conditions in these upland regions include large daily oscillations in air temperature (14°C-36°C) and high levels of solar radiation, causing overheating which affects inhabitant health and wellbeing. Inadequate shelter in these difficult climatic conditions is a widespread problem with 71% of Tanzanians living in rural areas, of which 28% of are below the national poverty line. Over the last 10 years an increasing number of houses are using modern building materials (brick or concrete walls and iron roof) rather than traditional vernacular design (mud-pole walls and thatch roof). Three designs were chosen to describe this transition. The performances of the three houses were simulated across a study year using IES and then compared against five chosen criteria to assess thermal comfort. Detailed analyses of critical times of day and specific areas of the building envelope were used to identify critical areas of design. The traditional house overheated significantly less often with smaller diurnal indoor temperature swings than the modern houses (due to its higher roof insulation and wall thermal mass). It also experienced uncomfortably low temperatures least often but maintained higher temperatures for longer during hot evenings. The modern houses outperformed the traditional house in ventilation gains with constant heat rejection throughout the day and night. The traditional house’s open structure resulted in high daytime ventilation gains and night-time heat rejection. Consideration of the position and internal gains of each room was found to be an important design factor. Across the study year the traditional design provided greater thermal comfort. However, as durability and social pressures are important factors in the choice of building materials, the design of modern materials that can mimic and improve on traditional material performance is critical to improving the health of inhabitants

    Transformation and fate of microphytobenthos carbon in subtropical, intertidal sediments: potential for long-term carbon retention revealed by <sup>13</sup>C-labeling

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    Microphytobenthos (MPB) are ubiquitous in coastal sediments, but the fate of their production (carbon biomass) is poorly defined. The processing and fate of MPB-derived carbon in subtropical intertidal sediments was investigated through in situ labeling with <sup>13</sup>C-bicarbonate. Of the added <sup>13</sup>C, 100% was fixed within ~ 4 h, suggesting that MPB productivity was limited by inorganic carbon availability. Although there was rapid transfer of <sup>13</sup>C to bacteria (within 12 h), a relatively small fraction of <sup>13</sup>C was transferred to heterotrophs (up to 12.5% of total fixed <sup>13</sup>C into bacteria and 0.01% into foraminifera). MPB was the major reservoir for <sup>13</sup>C throughout the study, suggesting that production of extracellular polymeric substances was limited and/or MPB recycled <sup>13</sup>C. This retention of <sup>13</sup>C was reflected in remarkably slow estimated turnover times for the MPB community (66–100 d). Over 31 d, ~ 70% of the <sup>13</sup>C was lost from sediments. This was primarily via resuspension (~ 55%), enhanced by elevated freshwater flow following rainfall. A further ~ 13% was lost via fluxes of dissolved inorganic carbon during inundation. However, <sup>13</sup>C losses via dissolved organic carbon fluxes from inundated sediments (0.5%) and carbon dioxide fluxes from exposed sediments (<0.1%) were minimal. The retention of ~ 30% of the carbon fixed by MPB within one tidal exposure after > 30 d, despite high resuspension, demonstrates the potentially substantial longer term retention of MPB-derived carbon in unvegetated sediments and suggests that MPB may contribute to carbon burial ("blue carbon")

    Development and application of a catchment scale pesticide fate and transport model for use in drinking water risk assessment

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    This paper describes the development and application of IMPT (Integrated Model for Pesticide Transport), a parameter-efficient tool for predicting diffuse-source pesticide concentrations in surface waters used for drinking water supply. The model was applied to a small UK headwater catchment with high frequency (8 h) pesticide monitoring data and to five larger catchments (479–1653 km2) with sampling approximately every 14 days. Model performance was good for predictions of both flow (Nash Sutcliffe Efficiency generally > 0.59 and PBIAS < 10%) and pesticide concentrations, although low sampling frequency in the larger catchments is likely to mask the true episodic nature of exposure. The computational efficiency of the model, along with the fact that most of its parameters can be derived from existing national soil property data mean that it can be used to rapidly predict pesticide exposure in multiple surface water resources to support operational and strategic risk assessments

    Protocol for a process-oriented qualitative evaluation of the Waltham Forest and East London Collaborative (WELC) integrated care pioneer programme using the Researcher-in-Residence model

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    INTRODUCTION: The integration of health and social care in England is widely accepted as the answer to fragmentation, financial concerns and system inefficiencies, in the context of growing and ageing populations with increasingly complex needs. Despite an expanding body of literature, there is little evidence yet to suggest that integrated care can achieve the benefits that its advocates claim for it. Researchers have often adopted rationalist and technocratic approaches to evaluation, treating integration as an intervention rather than a process. Results have usually been of limited use to practitioners responsible for health and social care integration. There is, therefore, a need to broaden the evidence base, exploring not only what works but also how integrated care can most successfully be implemented and delivered. For this reason, we are carrying out a formative evaluation of the Waltham Forest and East London Collaborative (WELC) integrated care pioneer programme. Our expectation is that this will add value to the literature by focusing on the processes by which the vision and objectives of integrated care are translated through phases of development, implementation and delivery from a central to a local perspective, and from a strategic to an operational perspective. METHODS AND ANALYSIS: The qualitative and process-oriented evaluation uses an innovative participative approach-the Researcher-in-Residence model. The evaluation is underpinned by a critical ontology, an interpretive epistemology and a critical discourse analysis methodology. Data will be generated using interviews, observations and documentary gathering. ETHICS AND DISSEMINATION: Emerging findings will be interpreted and disseminated collaboratively with stakeholders, to enable the research to influence and optimise the effective implementation of integrated care across WELC. Presentations and publications will ensure that learning is shared as widely as possible. The study has received ethical approval from University College London's Research Ethics Committee and has all appropriate NHS governance clearances

    The Use of Remote Sensing Techniques for Monitoring and Characterization of Slope Instability

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Understanding changes in slope geometry and knowledge of underlying engineering properties of the rock mass are essential for the safe design of man-made slopes and to reduce the significant risks associated with slope failure. Recent advances in the geomatics industry have provided the capability to obtain accurate, fully geo-referenced three-dimensional datasets that can be subsequently interrogated to provide engineering-based solutions for monitoring of deformation processes, rock mass characterization and additional insight into any underlying failure mechanisms. Importantly, data can also be used to spatially locate and map geological features and provide displacement or deformation rate information relating to movement of critical sections or regions of a slope. This paper explores the benefits that can be obtained by incorporating different remote sensing techniques and conventional measurement devices to provide a comprehensive database required for development of an effective slope monitoring and risk management program. The integration of different techniques, such as high accuracy discrete point measurement at critical locations, which can be used to complement larger scale less dense three-dimensional survey will be explored. Case studies using a combination of aerial and terrestrial laser scanning, unmanned aerial vehicle and hand-held scanning devices will demonstrate their ability to provide spatial data for informing decision making processes and ensuring compliance with Regulations

    A combined field/remote sensing approach for characterizing landslide risk in coastal areas

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Understanding the key factors controlling slope failure mechanisms in coastal areas is the first and most important step for analyzing, reconstructing and predicting the scale, location and extent of future instability in rocky coastlines. Different failure mechanisms may be possible depending on the influence of the engineering properties of the rock mass (including the fracture network), the persistence and type of discontinuity and the relative aspect or orientation of the coastline. Using a section of the North Coast of Cornwall, UK, as an example we present a multi-disciplinary approach for characterizing landslide risk associated with coastal instabilities in a blocky rock mass. Remotely captured terrestrial and aerial LiDAR and photogrammetric data was interrogated using Geographic Information System (GIS) techniques to provide a framework for subsequent analysis, interpretation and validation. The remote sensing mapping data was used to define the rock mass discontinuity network of the area and to differentiate between major and minor geological structures controlling the evolution of the North Coast of Cornwall. Kinematic instability maps generated from aerial LiDAR data using GIS techniques and results from structural and engineering geological surveys are presented. With this method, it was possible to highlight the types of kinematic failure mechanism that may generate coastal landslides and highlight areas that are more susceptible to instability or increased risk of future instability. Multi-temporal aerial LiDAR data and orthophotos were also studied using GIS techniques to locate recent landslide failures, validate the results obtained from the kinematic instability maps through site observations and provide improved understanding of the factors controlling the coastal geomorphology. The approach adopted is not only useful for academic research, but also for local authorities and consultancy's when assessing the likely risks of coastal instability

    Bringing Lunar LiDAR Back Down to Earth: Mapping Our Industrial Heritage through Deep Transfer Learning

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    This is the final version. Available on open access from MDPI via the DOI in this recordThis article presents a novel deep learning method for semi-automated detection of historic mining pits using aerial LiDAR data. The recent emergence of national scale remotely sensed datasets has created the potential to greatly increase the rate of analysis and recording of cultural heritage sites. However, the time and resources required to process these datasets in traditional desktop surveys presents a near insurmountable challenge. The use of artificial intelligence to carry out preliminary processing of vast areas could enable experts to prioritize their prospection focus; however, success so far has been hindered by the lack of large training datasets in this field. This study develops an innovative transfer learning approach, utilizing a deep convolutional neural network initially trained on Lunar LiDAR datasets and reapplied here in an archaeological context. Recall rates of 80% and 83% were obtained on the 0.5 m and 0.25 m resolution datasets respectively, with false positive rates maintained below 20%. These results are state of the art and demonstrate that this model is an efficient, effective tool for semi-automated object detection for this type of archaeological objects. Further tests indicated strong potential for detection of other types of archaeological objects when trained accordingly
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