Explore the vast range of titles available.

The Virtual Brain (TVB) is now available as open-source services on the cloud research platform EBRAINS (ebrains.eu). It offers software for constructing, simulating and analysing brain network models including the TVB simulator; magnetic resonance imaging (MRI) processing pipelines to extract structural and functional brain networks; combined simulation of large-scale brain networks with small-scale spiking networks; automatic conversion of user-specified model equations into fast simulation code; simulation-ready brain models of patients and healthy volunteers; Bayesian parameter optimization in epilepsy patient models; data and software for mouse brain simulation; and extensive educational material. TVB cloud services facilitate reproducible online collaboration and discovery of data assets, models, and software embedded in scalable and secure workflows, a precondition for research on large cohort data sets, better generalizability, and clinical translation.

The Virtual Brain (TVB) is now available as open-source cloud ecosystem on EBRAINS, a shared digital research platform for brain science. It offers services for constructing, simulating and analysing brain network models (BNMs) including the TVB network simulator; magnetic resonance imaging (MRI) processing pipelines to extract structural and functional connectomes; multiscale co-simulation of spiking and large-scale networks; a domain specific language for automatic high-performance code generation from user-specified models; simulation-ready BNMs of patients and healthy volunteers; Bayesian inference of epilepsy spread; data and code for mouse brain simulation; and extensive educational material. TVB cloud services facilitate reproducible online collaboration and discovery of data assets, models, and software embedded in scalable and secure workflows, a precondition for research on large cohort data sets, better generalizability and clinical translation.

Digital technology facilitates the manufacturing of complete dentures; however, clinical and patient-reported outcomes are underreported. This prospective, randomized, single-blind cross-over study reports the clinical and patient-related outcomes of 10 edentulous patients receiving digital dentures prepared with the Vita Vionic System and conventional dentures produced from heat-polymerized polymethylmethacrylate resin. Clinical efficiency was stated based on the Sato score for quantitative assessment of complete denture quality. Patient satisfaction was evaluated with the oral health-related quality of life questionnaire (OHIP-20). We report here that the Sato score was slightly higher in patients receiving digital versus conventional dentures with a mean of 73.2 ± 12.3 and 67.4 ± 11.8, respectively (p = 0.16). Moreover, upper and lower stability was superior in digital dentures (p = 0.03 and p = 0.10, respectively), while denture polish was better in conventional dentures (p = 0.03). Quality of life was slightly higher in patients receiving conventional compared to digital dentures with an OHIP-20 of 101.7 ± 12.0 and 95.6 ± 24.2, respectively (p = 0.33). Taken together and when considering the low power of the study, our findings suggest a trend towards better clinical efficiency of digital compared to conventional dentures, while patient satisfaction remained unaffected by the type of manufacturing.

To fulfill the Blue Economy’s promise of sustainable and just ocean use, its scientific foundation must more fully integrate the social sciences. Drawing on insights from real-world scientific networking initiatives, we identify three key contributions of the social sciences and propose a strategy to redefine the Blue Economy. This strategy anchors knowledge in societal challenges and emphasizes co-creation, the science-policy interface, knowledge integration, and the values of accountability and care.

This article is based upon work from COST Action CA22122 “Rethinking the Blue Economy: Socio-Ecological Impacts and Opportunities” (RethinkBlue), supported by COST (European Cooperation in Science and Technology). All authors acknowledge the role of the RethinkBlue COST Action in inspiring the writing of the manuscript, and thank the members of the RethinkBlue COST Action for engaging in the collective research effort. J.P. acknowledges Slovenian Research Agency (P5-0453) to support the writing of the manuscript. S.V. acknowledges the financial support from EQUALSEA (Transformative adaptation towards ocean equity) project, under the European Horizon 2020 Program, ERC Consolidator (Grant Agreement # 101002784) funded by the European Research Council, also the support of the Earth Commission and Future Earth. J.J.P.-F. acknowledges the financial support from THINKINAZUL program and the support by the Spanish Ministry of Science and Innovation, with funding from the European Union Next Generation EU (PRTR-C17.I1) and the Government of the Canary Islands. C.P.-C. received financial support from Xunta de Galicia “Axudas de apoio á etapa de formación posdoutoral” (grant ED481B-2021/095) and Xunta de Galicia “Axudas para completar á etapa de formación posdoutoral” (grant ED481D-2024/021). D.C. acknowledges the support of Croatian Science Foundation (HRZZ-UIP-2020-02-2238).