Coordinating multi-site construction projects using federated clouds

The requirements imposed by AEC (Architecture/Engineering/Construction) projects with regard to data storage and execution, on-demand data sharing and complexity on building simulations have led to utilising novel computing techniques. In detail, these requirements refer to storing the large amounts of data that the AEC industry generates — from building schematics to associated data derived from different contractors that are involved at various stages of the building lifecycle; or running simulations on building models (such as energy efficiency, environmental impact & occupancy simulations). Creating such a computing infrastructure to support operations deriving from various AEC projects can be challenging due to the complexity of workflows, distributed nature of the data and diversity of roles, profiles and location of the users. Federated clouds have provided the means to create a distributed environment that can support multiple individuals and organisations to work collaboratively. In this study we present how multi-site construction projects can be coordinated by the use of federated clouds where the interacting parties are represented by AEC industry organisations. We show how coordination can support (a) data sharing and interoperability using a multi-vendor Cloud environment and (b) process interoperability based on various stakeholders involved in the AEC project lifecycle. We develop a framework that facilitates project coordination with associated “issue status” implications and validate our outcome in a real construction project

SAR-Based Vibration Estimation Using the Discrete Fractional Fourier Transform

A vibration estimation method for synthetic aperture radar (SAR) is presented based on a novel application of the discrete fractional Fourier transform (DFRFT). Small vibrations of ground targets introduce phase modulation in the SAR returned signals. With standard preprocessing of the returned signals, followed by the application of the DFRFT, the time-varying accelerations, frequencies, and displacements associated with vibrating objects can be extracted by successively estimating the quasi-instantaneous chirp rate in the phase-modulated signal in each subaperture. The performance of the proposed method is investigated quantitatively, and the measurable vibration frequencies and displacements are determined. Simulation results show that the proposed method can successfully estimate a two-component vibration at practical signal-to-noise levels. Two airborne experiments were also conducted using the Lynx SAR system in conjunction with vibrating ground test targets. The experiments demonstrated the correct estimation of a 1-Hz vibration with an amplitude of 1.5 cm and a 5-Hz vibration with an amplitude of 1.5 mm

Ancient Maya wetland fields revealed under tropical forest canopy from laser scanning and multiproxy evidence

Understanding agricultural subsistence is vital for understanding past complex societies. Lidar data are indicating widespread ancient Maya infrastructure. Wetland agriculture was crucial to ancient cultures, but no previous study coupled lidar with multiproxy evidence to demonstrate the extent and uses of Maya wetland fields. We conducted a lidar survey around wetlands that multiple use proxies established were ancient Maya polycultural systems. Lidar indicated the Birds of Paradise (BOP) wetland field complex was five times larger than we had previously mapped and identified an even larger wetland agroecosystem. We ground-verified the BOP fields through excavations and dating, creating a study to couple these multiproxy data with lidar, thereby demonstrating widespread ancient Maya wetland agroecosystems.We report on a large area of ancient Maya wetland field systems in Belize, Central America, based on airborne lidar survey coupled with multiple proxies and radiocarbon dates that reveal ancient field uses and chronology. The lidar survey indicated four main areas of wetland complexes, including the Birds of Paradise wetland field complex that is five times larger than earlier remote and ground survey had indicated, and revealed a previously unknown wetland field complex that is even larger. The field systems date mainly to the Maya Late and Terminal Classic (∼1,400–1,000 y ago), but with evidence from as early as the Late Preclassic (∼1,800 y ago) and as late as the Early Postclassic (∼900 y ago). Previous study showed that these were polycultural systems that grew typical ancient Maya crops including maize, arrowroot, squash, avocado, and other fruits and harvested fauna. The wetland fields were active at a time of population expansion, landscape alteration, and droughts and could have been adaptations to all of these major shifts in Maya civilization. These wetland-farming systems add to the evidence for early and extensive human impacts on the global tropics. Broader evidence suggests a wide distribution of wetland agroecosystems across the Maya Lowlands and Americas, and we hypothesize the increase of atmospheric carbon dioxide and methane from burning, preparing, and maintaining these field systems contributed to the Early Anthropocene.Office of the VP for Researc

Baseline projections for Latin America: base-year assumptions, key drivers and greenhouse emissions

This paper provides an overview of the base-year assumptions and baseline projections for the set of models participating in the LAMP and CLIMACAP projects. We present the range in baseline projections for Latin America, and identify key differences between model projections including how these projections compare to historic trends. We find relatively large differences across models in base year assumptions related to population, GDP, energy and CO2 emissions due to the use of different data sources, but also conclude that this does not influence the range of projections. We find that population and GDP projections across models span a broad range, comparable to the range represented by the set of Shared Socioeconomic Pathways (SSPs). Kaya-factor decomposition indicates that the set of baseline scenarios mirrors trends experienced over the past decades. Emissions in Latin America are projected to rise as a result of GDP and population growth and a minor shift in the energy mix toward fossil fuels. Most scenarios assume a somewhat higher GDP growth than historically observed and continued decline of population growth. Minor changes in energy intensity or energy mix are projected over the next few decades

Citizen science reveals widespread negative effects of roads on amphibian distributions

Landscape structure is important for shaping the abundance and distribution of amphibians, but prior studies of landscape effects have been species or ecosystem-specific. Using a large-scale, citizen science-generated database, we examined the effects of habitat composition, road disturbance, and habitat split (i.e. the isolation of wetland from forest by intervening land use) on the distribution and richness of frogs and toads in the eastern and central United States. Undergraduates from nine biology and environmental science courses collated occupancy data and characterized landscape structure at 1617 sampling locations from the North American Amphibian Monitoring Program. Our analysis revealed that anuran species richness and individual species distributions were consistently constrained by both road density and traffic volume. In contrast, developed land around wetlands had small, or even positive effects on anuran species richness and distributions after controlling for road effects. Effects of upland habitat composition varied among species, and habitat split had only weak effects on species richness or individual species distributions. Mechanisms underlying road effects on amphibians involve direct mortality, behavioral barriers to movement, and reduction in the quality of roadside habitats. Our results suggest that the negative effects of roads on amphibians occur across broad geographic regions, affecting even common species, and they underscore the importance of developing effective strategies to mitigate the impacts of roads on amphibian populations

Network FOuNTAIN a CDBB network: For ONTologies and information maNagement in digital built Britain. Final report.

Network FOuNTAIN is the Network For ONTologies And Information maNagement in Digital Built Britain. The Network is supported by the Centre for Digital Built Britain. The vision of the Network is for all stakeholders in Digital Built Britain (DBB) to be able to meet their information needs. With the establishment of concepts such as Building Information Modelling (BIM) and Common Data Environments (CDE), built environment design, construction and operation are becoming increasingly information-intensive. The Network undertook five workshop activities between July and December 2018. This report summarises the proceedings of these workshops, and in particular establishes future capabilities needed to realise the vision of DBB

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis

BACKGROUND: Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. METHODS: We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. RESULTS: We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region. INTERPRETATION: Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission