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Open access to research data is increasingly important for accelerating research. Grant authorities therefore request detailed plans for how data is managed in the projects they finance. We have recently developed such a plan for the EU−H2020 BIG-MAP project-a cross-disciplinary project targeting disruptive battery-material discoveries. Essential for reaching the goal is extensive sharing of research data across scales, disciplines and stakeholders, not limited to BIG-MAP and the European BATTERY 2030+ initiative but within the entire battery community. The key challenges faced in developing the data management plan for such a large and complex project were to generate an overview of the enormous amount of data that will be produced, to build an understanding of the data flow within the project and to agree on a roadmap for making all data FAIR (findable, accessible, interoperable, reusable). This paper describes the process we followed and how we structured the plan.

Introduction: An accurate and timely diagnosis for Alzheimer’s disease (AD) is important, both for care and research. The current diagnostic criteria allow the use of CSF biomarkers to provide pathophysiological support for the diagnosis of AD. How these criteria should be operationalized by clinicians is unclear. Tools that guide in selecting patients in which CSF biomarkers have clinical utility are needed. We evaluated computerized decision support to select patients for CSF biomarker determination. Methods: We included 535 subjects (139 controls, 286 Alzheimer’s disease dementia, 82 frontotemporal dementia and 28 vascular dementia) from three clinical cohorts. Positive (AD like) and negative (normal) CSF biomarker profiles were simulated to estimate whether knowledge of CSF biomarkers would impact (confidence in) diagnosis. We applied these simulated CSF values and combined them with demographic, neuropsychology and MRI data to initiate CSF testing (computerized decision support approach). We compared proportion of CSF measurements and patients diagnosed with sufficient confidence (probability of correct class ≥0.80) based on an algorithm with scenarios without CSF (only neuropsychology, MRI and APOE), CSF according to the appropriate use criteria (AUC) and CSF for all patients. Results: The computerized decision support approach recommended CSF testing in 140 (26%) patients, which yielded a diagnosis with sufficient confidence in 379 (71%) of all patients. This approach was more efficient than CSF in none (0% CSF, 308 (58%) diagnosed), CSF selected based on AUC (295 (55%) CSF, 350 (65%) diagnosed) or CSF in all (100% CSF, 348 (65%) diagnosed). Conclusions: We used a computerized decision support with simulated CSF results in controls and patients with different types of dementia. This approach can support clinicians in making a balanced decision in ordering additional biomarker testing. Computer-supported prediction restricts CSF testing to only 26% of cases, without compromising diagnostic accuracy.

Background and aims: Cerebral white matter hyperintensities (WMH) have been suggested to contribute to progression in Alzheimer's disease (AD). Quantification of WMH in patients can be performed both manually, where WMH is categorized according to the Fazekas scale, and automatically using software which calculates WMH based on a FLAIR MRI sequence. The aim of this study was to investigate to which extent the WMH-burden affects progression in a mixed population of clinical AD and prodromal AD. Furthermore, we assessed whether manual rating and automatic segmentation of WMH provide equal information on progression. Methods: Patients with clinical diagnosis of AD and MCI patients suspected of having early AD were included. Evaluation of progression was performed by an experienced clinician at a 12-month follow-up visit. Manual evaluation (Fazekas scale) of WMH was performed by an experienced neuroradiologist and automatic segmentation was performed as previously described (Koikkalainen et al, 2016, Neuroimage). Patients were examined for the association between WMH-burden at baseline and progression in disease after 12 months and stratified by diagnosis of AD without CVD and AD with CVD. Results: There was no significant difference between WMH-burden and progression status in either AD without CVD (p=0.122) or AD with CVD (p=0.159). However, there was a trend for a higher WMH-burden in progressed vs. stable patients diagnosed with AD with CVD. Conclusion: WMH-burden seems to have an impact on progression in AD only when present in large amounts. We are currently investigating the prognostic value of manual and automatic WMH-burden measurements. Background and aims: According to international criteria, amyloid-biomarkers are diagnostic elements for Alzheimer's disease (AD). Controversies about their accuracy for early and differential diagnosis may be explained by distinct pathological processes or by between-center variability in amyloid-markers. We pretended to compare the agreement between amyloid CSF-biomarkers, [11C]-Pittsburgh Compound Positron Emission Tomography (PIB-PET) and Florbetapir (18F) and the accuracy of these biomarkers for AD diagnosis. Methods: 96 patients with at least two amyloid markers were included. The clinical course was considered the diagnostic gold standard. We used locally established cutoffs of amyloid CSF-AD biomarkers-Aβ42

29th European Photovoltaic Solar Energy Conference and Exhibition; 3994-3999, During the past four years, national experts from 11 institutions around the world have worked together within Subtask 3 – High penetration solutions for central PV generation scenarios – in order to identify best practice scenarios for a technically and economically improved grid integration of PV focusing on aspects at a power system level. The study, in order to envision the future PV penetration into a power system in the scope of transmission system level, reviewed the impacts of PV Penetration, the countermeasures for system operation and augmentation planning, and market design including the impact of other variable renewable generation. The study also reviewed the state-of-art methodology of power system operation planning and augmentation planning.

This study examines the reactive power ancillary services of solar inverters which are connected to low voltage (LV) distribution networks by giving attention to the grid voltage support service and grid losses. Two typical reference LV distribution network models as suburban and farm are introduced from the literature in order to evaluate contribution of two static droop strategies cosφ(P) and Q(U) on the grid voltage. Photovoltaic (PV) hosting capacities of the suburban and farm networks are estimated and the most predominant limitations of connecting more solar inverters are emphasized for each network type. Regarding the overloading of MV/LV distribution transformers, overloading of lines and the grid overvoltage limitations, new local grid voltage support methods (cosφ(P,U) and Q(U,P)) are also proposed. Resulting maximum allowable penetration levels with different reactive power methods are presented by load flow simulation.

25th European Photovoltaic Solar Energy Conference and Exhibition / 5th World Conference on Photovoltaic Energy Conversion, 6-10 September 2010, Valencia, Spain; 4971-4975, This paper presents the approach and objectives of the new IEA-PVPS1 [1] Task 14 on “High Penetration PV in Electricity Grids” which aims at reducing the technical barriers to achieving high PV penetration levels and thus promoting the use of grid connected PV as an important source in electric power systems. Task 14 will focus on working with utilities, industry, and other stakeholders to develop the technologies and methods enabling the widespread deployment of distributed PV technologies into the electricity grids. Using the highly accepted dissemination tools of IEA PVPS easy access to the main findings of the work is expected to mitigate concerns of high penetration PV to the benefit of a large number of countries.

Polarforschung