Suchergebnisse

The term "social licence" has been used to describe which uses and users of health data the public supports - and under what conditions. From November 2022 to January 2023, Health Data Research Network Canada was funded by the Public Health Agency of Canada to explore whether there was consensus among experienced public and patient advisors on: (i) uses of health data that all members supported or opposed and (ii) what constitutes an essential requirement for a health data use or user to be within social licence.
The project was conducted in English and French in collaboration with the Interdisciplinary Research Group in Health Informatics (GRIIS) at the University of Sherbrooke. It involved 20 public/patient advisor "participants" and an additional 13 public/patient advisors who served as peer-reviewers, all of whom had prior experience working in a health-related field and/or with health data. The process followed inclusive design principles in that it captured views held by the majority and minority of participants, including views expressed by only one or two participants.
After two 2-hour facilitated sessions, participants agreed that it is within social licence for health data to be used (i) by healthcare practitioners to improve patient care, (ii) by governments and administrators to improve the health system, and (iii) by university-based researchers to understand disease and well-being. There was consensus opposition to (i) an individual or organisation selling someone else's identified health data and (ii) health data being used for a purpose that has no public or societal benefit. There was no consensus about what constitutes an essential requirement for a use or users of health data to be with social licence. The results of the process have been published in a non-peer-reviewed report co-authored with participants.
This paper has been co-authored with a subset of the participants and peer-reviewers to present a high-level summary of the findings, methodological details, and templates to enable other groups to adapt the process to their own settings. It also presents the results of an anonymous evaluation of the process using the Public and Patient Engagement Evaluation Tool (PPEET), which were mostly positive and identified some areas for improvement.

Observing nearby galaxies with submillimeter telescopes on the ground has two major challenges. First, the brightness is significantly reduced at long submillimeter wavelengths compared to the brightness at the peak of the dust emission. Second, it is necessary to use a high-pass spatial filter to remove atmospheric noise on large angular scales, which has the unwelcome side effect of also removing the galaxy's large-scale structure. We have developed a technique for producing high-resolution submillimeter images of galaxies of large angular size by using the telescope on the ground to determine the small-scale structure (the large Fourier components) and a space telescope (Herschel or Planck) to determine the large-scale structure (the small Fourier components). Using this technique, we are carrying out the HARP and SCUBA-2 High Resolution Terahertz Andromeda Galaxy Survey (HASHTAG), an international Large Program on the James Clerk Maxwell Telescope, with one aim being to produce the first high-fidelity high-resolution submillimeter images of Andromeda. In this paper, we describe the survey, the method we have developed for combining the space-based and ground-based data, and we present the first HASHTAG images of Andromeda at 450 and 850 mu m. We also have created a method to predict the CO(J = 3-2) line flux across M31, which contaminates the 850 mu m band. We find that while normally the contamination is below our sensitivity limit, it can be significant (up to 28%) in a few of the brightest regions of the 10 kpc ring. We therefore also provide images with the predicted line emission removed. ; National Key R&D Program of China 2017YFA0402700 UK Research & Innovation (UKRI) Science & Technology Facilities Council (STFC) Canada Foundation for Innovation CGIAR European Regional Development Fund (ERDF) via the Welsh Government UK Research & Innovation (UKRI) Science & Technology Facilities Council (STFC) ST/K000926/1 European Research Council (ERC) European Commission ERC-2014-CoG-647939 National Research Foundation 2018R1D1A1B07048314 National Natural Science Foundation of China (NSFC) 12073002 11721303 11991052 STFC consolidated grant "Astrophysics at Oxford" ST/H002456/1 ST/K00106X/1 UK Research & Innovation (UKRI) Science & Technology Facilities Council (STFC) ST/S00033X/1 National Natural Science Foundation of China (NSFC) 11873086 U1631237 11873028 Yunnan Province of China 2017HC018 Chinese Academy of Sciences National Basic Research Program of China 2017YFA0402704 2016YFA0400702 National Natural Science Foundation of China (NSFC) 11861131007 12033004 Chinese Academy of Sciences Key Research Program of Frontier Sciences QYZDJ-SSW-SLH008 National Commission for Scientific and Technological Research of Chile (CONICYT) through a CAS-CONICYT Joint Postdoctoral Fellowship Academia Sinica - Taiwan AS-IA-106-M03 Ministry of Science and Technology, Taiwan MOST107-2119-M-001-031-MY3 European Research Council (ERC) European Commission SNDUST ERC-2015-AdG-694520 National Key Research and Development Program of China 2017YFA0402703 National Science Centre, Poland through the POLONEZ 2015/19/P/ST9/04010 SONATA BIS grant 2018/30/E/ST9/00208 Natural Sciences and Engineering Research Council of Canada (NSERC) CGIAR Canada Research Chairs European Research Council (ERC) 694343 ; Versión publicada - versión final del editor