Mobile terrestrial LiDAR data-sets in a Spatial Database Framework

Mobile Mapping Systems (MMS) have become important and regularly used platforms for the collection of physical-environment data in commercial and governmental spheres. For example, a typical MMS may collect location, imagery, video, LiDAR and air quality data from which models of the built-environment can be generated. Numerous approaches to using these data to generate models can be envisaged which can help develop detailed knowledge in the monitoring, maintanence and development of our built-environment. In this context, the efficient storing of this raw spatial data is a significant problem such that bespoke and dynamic access is possible for the generation of modeling requirements. This fundamental requirement of managing these data, where upwards of 40 gigabytes per hour of spatial-information can be collected from an MMS survey, poses significant challanges in data management alone. Existing methodologies mantain bespoke, survey oriented approaches to data management and model generation where the original MMS spatial data is not generally used or available outside these requirements. Thus, there is a need for an MMS data management framework where effective storage and access solutions can hold this information for use and analysis in any modeling context. Towards this end we detail our storage solution and the experiments where the procedures for high volume navigation and LiDAR MMS-data loading are analysed and optimised for minimum upload times and maximum access efficiency. This solution is built upon a PostgreSQL Relational Database Management System (RDBMS) with the PostGIS spatial extension and pg bulkload data loading utility

LiDAR data management pipeline; from spatial database population to web-application visualization

While the existence of very large and scalable Database Management Systems (DBMSs) is well recognized, it is the usage and extension of these technologies to managing spatial data that has seen increasing amounts of research work in recent years. A focused area of this research work involves the handling of very high resolution Light Detection and Ranging (LiDAR) data. While LiDAR has many real world applications, it is usually the purview of organizations interested in capturing and monitoring our environment where it has become pervasive. In many of these cases, it has now become the de facto minimum standard expected when a need to acquire very detailed 3D spatial data is required. However, significant challenges exist when working with these data sources, from data storage to feature extraction through to data segmentation all presenting challenges relating to the very large volumes of data that exist. In this paper, we present the complete LiDAR data pipeline as managed in our spatial database framework. This involves three distinct sections, populating the database, building a spatial hierarchy that describes the available data sources, and spatially segmenting data based on user requirements which generates a visualization of these data in a WebGL enabled web-application viewer. All work presented is in an experimental results context where we show how this approach is runtime efficient given the very large volumes of LiDAR data that are being managed

Snake energy analysis and result validation for a mobile laser scanning data-based automated road edge extraction algorithm

© 2008-2012 IEEE. The negative impact of road accidents cannot be ignored in terms of the very sizeable social and economic loss. Road infrastructure has been identified as one of the main causes of the road accidents. They are required to be recorded, located, measured, and classified in order to schedule maintenance and identify the possible risk elements of the road. Toward this, an accurate knowledge of the road edges increases the reliability and precision of extracting other road features. We have developed an automated algorithm for extracting road edges from mobile laser scanning (MLS) data based on the parametric active contour or snake model. The algorithm involves several internal and external energy parameters that need to be analyzed in order to find their optimal values. In this paper, we present a detailed analysis of the snake energy parameters involved in our road edge extraction algorithm. Their optimal values enable us to automate the process of extracting edges from MLS data for tested road sections. We present a modified external energy in our algorithm and demonstrate its utility for extracting road edges from low and nonuniform point density datasets. A novel validation approach is presented, which provides a qualitative assessment of the extracted road edges based on direct comparisons with reference road edges. This approach provides an alternative to traditional road edge validation methodologies that are based on creating buffer zones around reference road edges and then computing quality measure values for the extracted edges. We tested our road edge extraction algorithm on datasets that were acquired using multiple MLS systems along various complex road sections. The successful extraction of road edges from these datasets validates the robustness of our algorithm for use in complex route corridor environments

Optimizing hatchery practices for genetic improvement of marine bivalves

This is the final version. Available from Wiley via the DOI in this record. Aquaculture currently accounts for approximately half of all seafood produced and is the fastest growing farmed food sector globally. Marine bivalve aquaculture, the farming of oysters, mussels and clams, represents a highly sustainable component of this industry and has major potential for global expansion via increased efficiency, and numbers of, production systems. Artificial spat propagation (i.e. settled juveniles) in hatcheries and selective breeding have the potential to offer rapid and widespread gains for molluscan aquaculture industry. However, bivalves have unique life-histories, genetic and genomic characteristics, which present significant challenges to achieving such genetic improvement. Selection pressures experienced by bivalve larvae and spat in the wild contribute to drive population structure and animal fitness. Similarly, domestication selection is likely to act on hatchery-produced spat, the full implications of which have not been fully explored. In this review, we outline the key features of these taxa and production practices applied in bivalve aquaculture, which have the potential to affect the genetic and phenotypic variability of hatchery-propagated stock. Alongside, we compare artificial and natural processes experienced by bivalves to investigate the possible consequences of hatchery propagation on stock production. In addition, we identify key areas of investigation that need to be prioritized to continue to the advancement of bivalve genetic improvement via selective breeding. The growing accessibility of next-generation sequencing technology and high-powered computational capabilities facilitate the implementation of novel genomic tools in breeding programmes of aquatic species. These emerging techniques represent an exciting opportunity for sustainably expanding the bivalve aquaculture sector.Biotechnology & Biological Sciences Research Council (BBSRC)Natural Environment Research CouncilBiotechnology and Biological Sciences Research CouncilBiotechnology and Biological Sciences Research CouncilBiotechnology and Biological Sciences Research Counci

Prevalence, Nature, Severity and Risk Factors for Prescribing Errors in Hospital Inpatients : Prospective Study in 20 UK Hospitals

Funding This study was funded by the General Medical Council (GMC). The study funders had no role in the study design, in the collection, analysis, and interpretation of data, in the writing of this manuscript or in the decision to submit the article for publication. Acknowledgements The EQUIP team would like to thank the following people: Members of the Expert Reference Group (Graham Buckley, Gary Cook, Dianne Parker, Lesley Pugsley and Mike Scott); Members of the Error Validation Group (Lindsay Harper, Katy Mellor, Steven Williams, Keith Harkins, Steve McGlynn, Ray George, Tim Dornan, Penny Lewis); Tribal Consulting Ltd. (Heather Heathfield, Emma Carter) for database design; Study co-ordinators at hospitals (Linda Aldred, Deborah Armstrong, Isam Badhawi, Kathryn Ball, Neil Caldwell, Vanya Fidling, Nicholas Fong, Heather Ford, Andrea Gill, Lindsay Harper, Jean Holmes, Sally James, Christopher Poole, Sally Shaw, Heather Smith, Julie Street, Atia Rifat, David Thornton, Tracey Thornton, Jane Warren, Steven Williams), and all pharmacists at the study sites who collected data for this study.Peer reviewedPublisher PD

Contamination and exclusion in the sigma Orionis young group

We present radial velocities for 38 low-mass candidate members of the sigma Orionis young group. We have measured their radial velocities by cross-correlation of high resolution (R~6000) AF2/WYFFOS spectra of the gravity sensitive NaI doublet at 8183, 8195Angstroms. The total sample contained 117 objects of which 54 have sufficient signal-to-noise to detect NaI at an equivalent width of 3Angstroms, however we only detect NaI in 38 of these. This implies that very low-mass members of this young group display weaker NaI absorption than similarly aged objects in the Upper Scorpius OB association. We develop a technique to assess membership using radial velocities with a range of uncertainties that does not bias the selection when large uncertainties are present. The resulting membership probabilities are used to assess the issue of exclusion in photometric selections, and we find that very few members are likely to be excluded by such techniques. We also assess the level of contamination in the expected pre-main sequence region of colour-magnitude space brighter than I = 17. We find that contamination by non-members in the expected PMS region of the colour-magnitude diagram is small. We conclude that although radial velocity alone is insufficient to confirm membership, high signal-to-noise observations of the NaI doublet provide the opportunity to use the strength of NaI absorption in concert with radial velocities to asses membership down to the lowest masses, where Lithium absorption no longer distinguishes youth.Comment: 11 pages, MNRAS accepted. Online data available from: http://www.astro.ex.ac.uk/people/timn/Catalogues/service.htm

Protocol for the Smoking, Nicotine and Pregnancy (SNAP) trial: double-blind, placebo-randomised, controlled trial of nicotine replacement therapy in pregnancy

Background: Smoking in pregnancy remains a public health challenge. Nicotine replacement therapy (NRT) is effective for smoking cessation in non-pregnant people, but because women metabolise nicotine and cotinine much faster in pregnancy, it is unclear whether this will be effective for smoking cessation in pregnancy. The NHS Health Technology Assessment Programme (HTA)-funded smoking, nicotine and pregnancy ( SNAP) trial will investigate whether or not nicotine replacement therapy ( NRT) is effective, cost-effective and safe when used for smoking cessation by pregnant women. Methods/Design: Over two years, in 5 trial centres, 1050 pregnant women who are between 12 and 24 weeks pregnant will be randomised as they attend hospital for ante-natal ultrasound scans. Women will receive either nicotine or placebo transdermal patches with behavioural support. The primary outcome measure is biochemically-validated, self-reported, prolonged and total abstinence from smoking between a quit date ( defined before randomisation and set within two weeks of this) and delivery. At six months after childbirth self-reported maternal smoking status will be ascertained and two years after childbirth, self-reported maternal smoking status and the behaviour, cognitive development and respiratory symptoms of children born in the trial will be compared in both groups. Discussion: This trial is designed to ascertain whether or not standard doses of NRT ( as transdermal patches) are effective and safe when used for smoking cessation during pregnancy

Maternal psychological distress in primary care and association with child behavioural outcomes at age three

Observational studies indicate children whose mothers have poor mental health are at increased risk of socio-emotional behavioural difficulties, but it is unknown whether these outcomes vary by the mothers’ mental health recognition and treatment status. To examine this question, we analysed linked longitudinal primary care and research data from 1078 women enrolled in the Born in Bradford cohort. A latent class analysis of treatment status and self-reported distress broadly categorised women as (a) not having a common mental disorder (CMD) that persisted through pregnancy and the first 2 years after delivery (N = 756, 70.1 %), (b) treated for CMD (N = 67, 6.2 %), or (c) untreated (N = 255, 23.7 %). Compared to children of mothers without CMD, 3-year-old children with mothers classified as having untreated CMD had higher standardised factor scores on the Strengths and Difficulties Questionnaire (d = 0.32), as did children with mothers classified as having treated CMD (d = 0.27). Results were only slightly attenuated in adjusted analyses. Children of mothers with CMD may be at risk for socio-emotional and behavioural difficulties. The development of effective treatments for CMD needs to be balanced by greater attempts to identify and treat women. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00787-015-0777-2) contains supplementary material, which is available to authorized users

Genetic pest management and the background genetics of release strains

Genetic pest management (GPM) methods involve releasing modified versions of a pest species to mate with wild pests in the target area. Proposed for a wide range of applications in public health, agriculture and conservation, most progress has been made with pest insects. Offspring of the released modified insects and wild pests carry the modification—which might be transgenes, artificially introduced Wolbachia or genetic damage from radiation, for example—but they also carry a complete haploid genome from their laboratory-reared parent, as well as one from their wild parent. Unless these F1 hybrids are completely unable to reproduce, further mating will lead to introgression of DNA sequences from the release strain into the wild population. We discuss issues around strain selection and the potential consequences of such introgression. We conclude that such introgression is probably harmless in almost all circumstances, and could, in theory, provide specific additional benefits to the release programme. We outline population monitoring approaches that could be used, going forward, to determine how background genetics may affect GPM