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Aimed at those in business and professions, and with a paperback edition aimed at students, this title provides an analysis of different aspects of the modern economy. It includes sections on: Globalisation; The phoney recovery and America's imbalances; China's rise; Underachievers; The arteries of capitalism; and Economic facts and fallacies

While the higher education landscape has changed radically since the late 1980s, a consistent feature of government policy has been to widen participation to students who were disproportionately excluded previously. Post-1992 universities in particular have experienced a substantial change in their student intake, but challenges remain in ensuring the retention and success of these students. This article argues that student homelessness is a significant and an under-researched barrier to students reaching their potential. The problem is explored here, illuminated by a focus group and a series of interviews involving 16 students from one school at a London post-1992 university. The impact of homelessness was far-reaching in terms of their emotional wellbeing and ability to fully participate in university life, including pressure on time and financial resources, inability to fully focus on studies, and limited engagement with fellow students and the wider university experience.

Within the earth sciences the curation and sharing of geo-samples is crucial to supporting reproducible research, in addition to extending the use of the samples in new research, and saving costs by avoiding sample loss and duplicating sampling activities. In the Commonwealth Scientific and Industrial Research Organisation (CSIRO), researchers gather various geo-samples as part of their field studies and collaborative projects. The diversity of the samples and their unsystematic management led ambiguous sample numbers, incomplete sample descriptions, and difficulties in finding the samples and their related data. These problems are also found in universities, research institutes and government agencies, which usually curate and manage diverse samples. To address this problem, we developed an open source registration and management system to identify geo-samples unambiguously and to manage their metadata and data systematically. The system supports the linking of samples and sample collections to the real world features from where they were collected, as well as to their data and reports on the Web. This paper describes the implementation of the system including its underlying design considerations, and its applications. The system was built upon the International Geo Sample Number persistent identifier system with Semantic Web technologies. It has been implemented and tested with individual users and three sample repositories in the organization.

BackgroundAnticholinergic drugs block muscarinic receptors in the body. They are commonly prescribed for a variety of indications and their use has previously been associated with dementia and cognitive decline.
MethodsIn UK Biobank participants with linked health-care records (n=171,266, aged 40-71 at baseline), we calculated total anticholinergic drug burden according to 15 different anticholinergic scales and due to different classes of drugs. We then used linear regression to explore the associations between anticholinergic burden and various measures of cognition and structural MRI, including general intelligence, 9 separate cognitive domains, total brain volume, volumes of 68 cortical and 16 subcortical areas, and fractional anisotropy and median diffusivity of 25 white-matter tracts.
ResultsAnticholinergic burden was modestly associated with poorer cognition across most anticholinergic scales and cognitive tests (6/9 FDR-adjusted significant associations, std. betas range: -0.033, -0.006). The association was mostly driven by antibiotics (std. beta=-0.029, 95% p<0.001) and drugs to treat disorders of the nervous system (std. beta=-0.017, p<0.001). Anticholinergic burden due to the pharmacological subclass of glucose-lowering drugs (beta=-0.038, p<0.001) and the anatomical class of respiratory drugs (beta=0.016, p=0.03) was associated with total brain volume. However, anticholinergic burden was not associated with any other measure of brain macro- or microstructure (p>0.07).
DiscussionAnticholinergic burden is mildly associated with poorer cognition, but there is little evidence for an effect for measures of brain structure. Future studies might focus more broadly on polypharmacy or more narrowly on distinct drug classes, instead of using purported anticholinergic action to study the effects of drugs on cognitive ability.

We present ten simple rules that support converting a legacy vocabulary—a list of terms available in a print-based glossary or in a table not accessible using web standards—into a FAIR vocabulary. Various pathways may be followed to publish the FAIR vocabulary, but we emphasise particularly the goal of providing a globally unique resolvable identifier for each term or concept. A standard representation of the concept should be returned when the individual web identifier is resolved, using SKOS or OWL serialised in an RDF-based representation for machine-interchange and in a web-page for human consumption. Guidelines for vocabulary and term metadata are provided, as well as development and maintenance considerations. The rules are arranged as a stepwise recipe for creating a FAIR vocabulary based on the legacy vocabulary. By following these rules you can achieve the outcome of converting a legacy vocabulary into a standalone FAIR vocabulary, which can be used for unambiguous data annotation. In turn, this increases data interoperability and enables data integration. ; The contribution of SJDC was supported through a CSIRO Strategic Project for engagement with CODATA. The contribution of BM was supported through - eLTERplus, a project funded from the INFRAIA-01-2018-2019 programme of European Union's Horizon 2020 research and innovation programme under grant agreement No 871128 - OBARIS, an FFG funded project (No 887389). ; Peer Reviewed ; Postprint (published version)

Acknowledgements: We thank the LBC1936 members and project staff. Study Funding: The LBC1936 and this research are supported by Age UK (Disconnected Mind project), the UK Medical Research Council [MRC; G0701120, G1001245, MR/M013111/1, MR/R024065/1], and the University of Edinburgh. SRC, MEB, and IJD were also supported by a National Institutes of Health (NIH) research grant R01AG054628. JMW, IJD are also supported by a Wellcome Trust Strategic Award (Ref 104036/Z/14/Z). MCVH is funded by the Row Fogo Charitable Trust (grant No. BROD.FID3668413). SRC was also supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant Number 221890/Z/20/Z). Imaging and image analysis was performed at the Brain Research Imaging Centre (http://www.sbirc.ed.ac.uk/), Edinburgh, supported by the Scottish Funding Council SINAPSE Collaboration. LCAC acknowledges 4 Luciano funding from the Scottish Government's Rural and Environment Science and Analytical Services (RESAS) division. MVH is funded by the Row Fogo Charitable Trust Centre for Research into Ageing and the Brain (Ref No: AD.ROW4.35. BRO-D.FID3668413). JMW received funding from the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer's Research UK. ; Peer reviewed ; Publisher PDF

Air quality (AQ) is a very topical issue for many cities and has a direct impact on citizen health. The AQ of a large UK city is being investigated using low-cost Particulate Matter (PM) sensors, and the results obtained by these sensors have been compared with government operated AQ stations. In the first pilot deployment six AQ Internet of Things (IoT) devices have been designed and built, each with four different low-cost PM sensors, and they have been deployed at two locations within the city. These devices are equipped with LoRaWAN wireless network transceivers to test city scale Low-Power Wide Area Network (LPWAN) coverage. The study concludes that i) the physical device developed can operate at a city scale ii) some low-cost PM sensors are viable for monitoring AQ and for detecting PM trends iii) LoRaWAN is suitable for city scale sensor coverage where connectivity is an issue. Based on the findings from this first pilot project a larger LoRaWAN enabled AQ sensor network is being deployed across the city of Southampton in the UK.

This document is a manifesto and call to action produced by the DRUM (Digital Representation of Units of Measure) Task Group as part of its efforts to mobilise representatives from International Scientific Unions and Associations to engage with this fundamentally important issue. Why are Units Important? The major challenges that confront human societies are global in reach and complex in nature. They do not have simple, single-discipline, solutions. The intrinsically interdisciplinary and multidisciplinary challenges require trans-sectoral cooperation between academic, commercial and governmental agencies. For such collaboration to succeed, the essential tools for scientific exchange of information must be fit for purpose if they are to meet the challenges. Quality data is essential, and to be understandable and usable, the data must meet internationally-agreed community-endorsed conventions or standards, a key element being the clear representation of units. Although the "collaboration imperative" is recognised by the major research funders and international organisations, they often fail to appreciate all the details that are essential to enable the required cooperation. Funding to encourage collaboration, highlighting relevance, pathways to impact, and facilitating international exchanges, are all vital but these are a tower of cards if the foundations for scientific exchange of information are not up to the required challenge. Providing quality data is essential, but collaborative work will fail unless all those who need to use the data (and the associated information and knowledge) can actually understand it and this requires international, community agreements. Units of measure are a key part of such agreements. Much of the global output of data lacks clear and unambiguous definitions of the units used. While the units of measure of quantitative values might be conventional and thus unstated for the original application, they are often obscure outside the originating community or discipline. This is ...

Air Quality (AQ) is a very topical issue for many cities and has a direct impact on citizen health. The AQ of a large UK city is being investigated using low-cost Particulate Matter (PM) sensors, and the results obtained by these sensors have been compared with government operated AQ stations. In the first pilot deployment, six AQ Internet of Things (IoT) devices have been designed and built, each with four different low-cost PM sensors, and they have been deployed at two locations within the city. These devices are equipped with LoRaWAN wireless network transceivers to test city scale Low-Power Wide Area Network (LPWAN) coverage. The study concludes that (i) the physical device developed can operate at a city scale; (ii) some low-cost PM sensors are viable for monitoring AQ and for detecting PM trends; (iii) LoRaWAN is suitable for city scale sensor coverage where connectivity is an issue. Based on the findings from this first pilot project, a larger LoRaWAN enabled AQ sensor network is being deployed across the city of Southampton in the UK.

Air Quality (AQ) is a very topical issue for many cities and has a direct impact on citizen health. The AQ of a large UK city is being investigated using low-cost Particulate Matter (PM) sensors, and the results obtained by these sensors have been compared with government operated AQ stations. In the first pilot deployment, six AQ Internet of Things (IoT) devices have been designed and built, each with four different low-cost PM sensors, and they have been deployed at two locations within the city. These devices are equipped with LoRaWAN wireless network transceivers to test city scale Low-Power Wide Area Network (LPWAN) coverage. The study concludes that (i) the physical device developed can operate at a city scale; (ii) some low-cost PM sensors are viable for monitoring AQ and for detecting PM trends; (iii) LoRaWAN is suitable for city scale sensor coverage where connectivity is an issue. Based on the findings from this first pilot project, a larger LoRaWAN enabled AQ sensor network is being deployed across the city of Southampton in the UK.

This project was funded by DPUK through MRC (grant no. MR/L023784/2) and the UK Medical Research Council Award to the University of Oxford (grant no. MC_PC_17215). L.S is funded by the Virtual Brain Cloud from European comission (grant no. H2020-SC1-DTH-2018-1). C.R.B is funded by National Institutes of Health (NIH) research grant R01AG054628. S.R.C is funded by National Institutes of Health (NIH) research grant (R01AG054628), Medical Research Council (MR/R024065/1), Age UK and Economic and Social Research Council. R.E.M. was supported by Alzheimer's Research UK major project grant ARUKPG2017B-10. C.H was supported by an MRC Human Genetics Unit programme grant "Quantitative traits in health and disease" (U.MC_UU_00007/10). H.C.W received funding from Wellcome Trust. J.W is funded by TauRx pharmaceuticals Ltd and received Educational grant from Biogen paid to Alzheimer Scotland/Brain Health Scotland. G.W received GRAMPIAN UNIVERSITY HOSPITALS NHS TRUST, Scottish Government—Chief Scientist Office, ROLAND SUTTON ACADEMIC TRUST, Medical Research Scotland, Sutton Academic Trust and ROLAND SUTTON ACADEMIC TRUST. J.M.W received Wellcome Trust Strategic Award, MRC UK Dementia Research Institute and MRC project grants, Fondation Leducq, Stroke Association, British Heart Foundation, Alzheimer Society, and the European Union H2020 PHC-03-15 SVDs@Target grant (666881). D.S received MRC (MR/S010351/1), MRC (MR/W002388/1) and MRC (MR/W002566/1). A.M is supported by the Wellcome Trust (104036/Z/14/Z, 216767/Z/19/Z, 220857/Z/20/Z) and UKRI MRC (MC_PC_17209, MR/S035818/1). This work is part of a project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 847776. In addition, A.M has received grant support from The Sackler Trust, outside of the work presented. N.B received grant to institution from GSK as part of GSK/Oxford FxG initiative. A.N.H received John Black Charitable Fund-Rosetrees, H2020 funding from European Comission-Project Virtual Brain Cloud, AI for the Discovery of new therapies in Parkinson's (A2926), Rising Start Initiative—stage 2, Brain-Gut Microbiome (Call: PAR-18-296; Award ID: 1U19AG063744-01), Gut-liver-brain biochemical axis in Alzheimer's disease (5RF1AG057452-01), Virtual Brain Cloud (Call: H2020-SC1-DTH- 2018-1; Grant agreement ID: 826421). Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006) and is currently supported by the Wellcome Trust (216767/Z/19/Z). Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Edinburgh Clinical Research Facility, University of Edinburgh, Scotland and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award "STratifying Resilience and Depression Longitudinally" [STRADL] Reference 104036/Z/14/Z). We are grateful to all the families who took part; the general practitioners and the Scottish School of Primary Care for their help in recruiting them; and the whole Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, health-care assistants, and nurses. ; Peer reviewed ; Publisher PDF