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This deliverable relates to the work carried out under task T8.3, “Research Impact Services”. The task’s focus is on the development of pilots with selected National funding agencies and infrastructure initiatives in order to serve them with the OpenAIRE research impact suite of services. A major service that OpenAIRE provides is the linking of research results to funding. Aside from importing the links from the repositories and journals, OpenAIRE designs, develops and enhances mining algorithms that identify and extract funding information from the text of scientific publications. With the help of NOADs we have initiated bi-lateral, often informal, collaborations with national funding agencies to facilitate mining extraction on their data. This is an on-going activity throughout the duration of the project. Currently the national funding agencies that we are working with are: FCT (Portugal), ARC (Australia), NHMRC (Australia), NSF & NIH (USA), SFI (Ireland), “Ministry of Science Education and Sport” & "Croatian Science Foundation” (Croatia), NWO (Netherlands), and DFG (Germany). This deliverable describes the nature of the data of the identified National funding agencies, as well as their export technologies, and provides the specification of the general-purpose OpenAIRE services required to support research impact measurements.

Introduction: Vaccines and drugs for the treatment and prevention of COVID-19 require robust evidence generated from clinical trials before they can be used. Decisions on how to apply non-pharmaceutical interventions such as quarantine, self-isolation, social distancing and travel restrictions should also be based on evidence. There are some experiential and mathematical modelling data for these interventions, but there is a lack of data on the social, ethical and behavioural aspects of these interventions in the literature. Therefore, our study aims to produce evidence to inform (non-pharmaceutical) interventions such as communications, quarantine, self-isolation, social distancing, travel restrictions and other public health measures for the COVID-19 pandemic. Methods: The study will be conducted in the United Kingdom, Italy, Malaysia, Slovenia and Thailand. We propose to conduct 600-1000 quantitative surveys and 25-35 qualitative interviews per country. Data collection will follow the following four themes: (1) Quarantine and self-isolation (2) social distancing and travel restrictions (3) wellbeing and mental health (4) information, misinformation and rumours. In light of limitations of travel and holding in-person meetings, we will primarily use online/remote methods for collecting data. Study participants will be adults who have provided informed consent from different demographic, socio-economic and risk groups. Discussion: At the time of the inception of the study, United Kingdom, Italy, Malaysia, Slovenia and Thailand have initiated strict public health measures and varying degrees of "lockdowns" to curb the pandemic. These public health measures will change in the coming weeks and months depending on the number of cases of COVID-19 in the respective countries. The data generated from our study could inform these strategies in real time.

Introduction: The Age-Well observational, cross-sectional study investigates the affective and cognitive mechanisms of meditation expertise with behavioral, neuroimaging, sleep, and biological measures sensitive to aging and Alzheimer's disease (AD). Methods: Thirty cognitively unimpaired individuals aged 65 years or older with at least 10,000 hours of practice in mindfulness meditation (MM) and loving-kindness and compassion meditation (LKCM) are selected. The outcomes are the neuroimaging brain correlates of MM and LKCM and the assessments of long-term meditation practices on behavioral, neural, and biological measures as compared to nonmeditator older controls from the Age-Well randomized controlled trial. Results: Recruitment and data collection began in late 2016 and will be completed by late 2019. Discussion: Results are expected to foster the understanding of the effects of meditation expertise on aging and of the mechanisms of action underlying the meditation intervention in the Age-Well randomized controlled trial. These finding will contribute to the design of meditation-based prevention randomized controlled trials for the aged population and to the exploration of the possible long-time developmental trajectory of meditation training. © 2018 The Authors

IntroductionInertial measurement units (IMUs) positioned on various body locations allow detailed gait analysis even under unconstrained conditions. From a medical perspective, the assessment of vulnerable populations is of particular relevance, especially in the daily-life environment. Gait analysis algorithms need thorough validation, as many chronic diseases show specific and even unique gait patterns. The aim of this study was therefore to validate an acceleration-based step detection algorithm for patients with Parkinson’s disease (PD) and older adults in both a lab-based and home-like environment.MethodsIn this prospective observational study, data were captured from a single 6-degrees of freedom IMU (APDM) (3DOF accelerometer and 3DOF gyroscope) worn on the lower back. Detection of heel strike (HS) and toe off (TO) on a treadmill was validated against an optoelectronic system (Vicon) (11 PD patients and 12 older adults). A second independent validation study in the home-like environment was performed against video observation (20 PD patients and 12 older adults) and included step counting during turning and non-turning, defined with a previously published algorithm.ResultsA continuous wavelet transform (cwt)-based algorithm was developed for step detection with very high agreement with the optoelectronic system. HS detection in PD patients/older adults, respectively, reached 99/99% accuracy. Similar results were obtained for TO (99/100%). In HS detection, Bland–Altman plots showed a mean difference of 0.002 s [95% confidence interval (CI) −0.09 to 0.10] between the algorithm and the optoelectronic system. The Bland–Altman plot for TO detection showed mean differences of 0.00 s (95% CI −0.12 to 0.12). In the home-like assessment, the algorithm for detection of occurrence of steps during turning reached 90% (PD patients)/90% (older adults) sensitivity, 83/88% specificity, and 88/89% accuracy. The detection of steps during non-turning phases reached 91/91% sensitivity, 90/90% specificity, and 91/91% accuracy.ConclusionThis cwt-based algorithm for step detection measured at the lower back is in high agreement with the optoelectronic system in both PD patients and older adults. This approach and algorithm thus could provide a valuable tool for future research on home-based gait analysis in these vulnerable cohorts.

The marine silicon cycle is intrinsically linked with carbon cycling in the oceans via biological production of silica by a wide range of organisms. The stable silicon isotopic composition (denoted by δ30Si) of siliceous microfossils extracted from sediment cores can be used as an archive of past oceanic silicon cycling. However, the silicon isotopic composition of biogenic silica has only been measured in diatoms, sponges and radiolarians, and isotopic fractionation relative to seawater is entirely unknown for many other silicifiers. Furthermore, the biochemical pathways and mechanisms that determine isotopic fractionation during biosilicification remain poorly understood. Here, we present the first measurements of the silicon isotopic fractionation during biosilicification by loricate choanoflagellates, a group of protists closely related to animals. We cultured two species of choanoflagellates, Diaphanoeca grandis and Stephanoeca diplocostata, which showed consistently greater isotopic fractionation (approximately −5 ‰ to −7 ‰) than cultured diatoms (−0.5 ‰ to −2.1 ‰). Instead, choanoflagellate silicon isotopic fractionation appears to be more similar to sponges grown under similar dissolved silica concentrations. Our results highlight that there is a taxonomic component to silicon isotope fractionation during biosilicification, possibly via a shared or related biochemical transport pathway. These findings have implications for the use of biogenic silica δ30Si produced by different silicifiers as proxies for past oceanic change.

On 7-8\ud th\ud November 2016, 60 people with an interest in the\ud ‘\ud Trials\ud within Cohorts\ud ’\ud (TwiCs) approach for randomised controlled trial design\ud met in London. The purpose of this 2\ud nd\ud TwiCs international symposium\ud was to share perspectives and experiences on ethical aspects of the\ud TwiCs design, discuss how TwiCs relate to the current ethical frame-\ud work, provide a forum in which to discuss and debate ethical issues\ud and identify future directions for conceptual and empirical research.\ud The symposium was supported by the Wellcome Trust and the NIHR\ud CLAHRC Yorkshire and Humber and organised by members of the\ud TwiCs network led by Clare Relton and attended by people from the\ud UK, the Netherlands, Norway, Canada and USA. The two-day sympo-\ud sium enabled an international group to meet and share experiences\ud of the TwiCs design (also known as the\ud ‘\ud cohort multiple RCT design\ud ’\ud ),\ud and to discuss plans for future research. Over the two days, invited\ud plenary talks were interspersed by discussions, posters and mini pre-\ud sentations from bioethicists, triallists and health research regulators.\ud Key findings of the symposium were: (1) It is possible to make a\ud compelling case to ethics committees that TwiCs designs are ap-\ud propriate and ethical; (2) The importance of wider considerations\ud around the ethics of inefficient trial designs; and (3) some questions\ud about the ethical requirements for content and timing of informed\ud consent for a study using the TwiCs design need to be decided on\ud a case-by-case basis.