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Cited Key Resources
Stakeholder Type
1Quantum Revolution& Advanced AI2HumanAugmentation3Eco-Regeneration& Geo-Engineering4Science& Diplomacy1. ANTICIPATIONPOTENTIALAdvancedArtificial IntelligenceQuantumTechnologiesBrain-inspiredComputingBiologicalComputingCognitiveEnhancementHuman Applications of Genetic EngineeringRadical HealthExtensionConsciousnessAugmentation DecarbonisationWorldSimulationFuture FoodSystemsSpaceResourcesOceanStewardshipComplex Systems forSocial EnhancementScience-basedDiplomacyInnovationsin EducationSustainableEconomicsCollaborativeScience Diplomacy
1Quantum Revolution& Advanced AI2HumanAugmentation3Eco-Regeneration& Geo-Engineering4Science& Diplomacy1. ANTICIPATIONPOTENTIALAdvancedArtificial IntelligenceQuantumTechnologiesBrain-inspiredComputingBiologicalComputingCognitiveEnhancementHuman Applications of Genetic EngineeringRadical HealthExtensionConsciousnessAugmentation DecarbonisationWorldSimulationFuture FoodSystemsSpaceResourcesOceanStewardshipComplex Systems forSocial EnhancementScience-basedDiplomacyInnovationsin EducationSustainableEconomicsCollaborativeScience Diplomacy


Cited Key Resources

Each of the 18 scientific emerging topics described in the science breakthrough radar presents a carefully vetted overview by lead scientists of the current state-of-the-art in a given field and what could be important science breakthroughs in 5, 10 or 25 years. The descriptions of the emerging topics and related subfields draw upon evidence from key resources and publications from the scientific literature. This section provides a list of cited resources, organised by emerging topic and related sub-fields.
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Key Resources By Topic:

1Kaiming He et al., Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification, 2015 IEEE International Conference on Computer Vision (ICCV), 2015, p.1026.https://doi/10.1109/ICCV.2015.1232Oriol Vinyals et al., StarCraft II: A New Challenge for Reinforcement Learning, arXiv:1708.04782 [cs], 2017. Staff, Waymo self-driving vehicles cover 20 million miles on public roads, Reuters, 2020. Weinberg, Philosophers On GPT-3 (updated with replies by GPT-3), Daily Nous, 2020. Intelligence and Life in 2030, 2016 Report | One Hundred Year Study on Artificial Intelligence (AI100), 2016. Selman, Yolanda Gil, A 20-Year Community Roadmap for Artificial Intelligence Research in the US, arXiv:1908.02624 [cs], 2019. of AI Report 2020, 2020. Zillner et al., Strategic Research, Innovation and Deployment Agenda: AI, Data and Robotics Partnership, 2020. New Generation of Artificial Intelligence Development Plan, The Foundation for Law and International Affairs, 2017.

1.1.1Deeper Machine Learning

10Kenji Kawaguchi, Leslie Pack Kaelbling, Yoshua Bengio, Generalization in Deep Learning, arXiv:1710.05468 [cs, stat], 2020. Sotala, Defining Human Values for Value Learners, AAAI-16 AI, Society and Ethics workshop, 2016, p.10. R. Hoffman et al., Metrics for Explainable AI: Challenges and Prospects, arXiv:1812.04608 [cs], 2019.

1.1.2Human-centred AI

13Mark O. Riedl, Human-Centered Artificial Intelligence and Machine Learning, arXiv:1901.11184 [cs], 2019. Kragic et al., Interactive, Collaborative Robots: Challenges and Opportunities, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018, p.18.

1.1.3Next-level AI

15Yaqing Wang et al., Generalizing from a Few Examples: A Survey on Few-shot Learning, ACM Computing Surveys, Vol. 53, 2020, p.10301. d’Avila Garcez et al., Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning, arXiv:1905.06088 [cs], 2019. Marcus, Deep Learning: A Critical Appraisal, arXiv:1801.00631 [cs, stat], 2018.

1.1.4Interdisciplinary AI

18Hsin-Yuan Huang et al., Power of data in quantum machine learning, Nature Communications, Vol. 12, 2021, p.2631. Biamonte et al., Quantum machine learning, Nature, Vol. 549, 2017, p.195.https://doi.org10.1038/nature2347420Amira Abbas et al., The Power of Quantum Neural Networks, Nature Computational Science, Vol. 1, 2021, p.403.
1European Quantum Flagship, Strategic Research Agenda, 2020. Office for Science, Quantum Technologies: Blackett Review, 2016. Science and Technology Council, National Strategic Overview for Quantum Information Science, 2018., OIDA Quantum Photonics Roadmap: Every Photon Counts, OIDA Reports, Vol. 3, 2020.

1.2.1Quantum Communication

5Juan Yin et al., Entanglement-Based Secure Quantum Cryptography over 1,120 Kilometres, Nature, Vol. 582, 2020, p.501. Chen et al., An Integrated Space-to-Ground Quantum Communication Network over 4,600 Kilometres, Nature, Vol. 589, 2021, p.214. Chen et al., Twin-Field Quantum Key Distribution over a 511 Km Optical Fibre Linking Two Distant Metropolitan Areas, Nature Photonics, Vol. 15, 2021, p.570. Acín et al., Device-Independent Security of Quantum Cryptography against Collective Attacks, Physical Review Letters, Vol. 98, 2007, p.230501.

1.2.2Quantum Computing

9Frank Arute et al., Quantum Supremacy Using a Programmable Superconducting Processor, Nature, Vol. 574, 2019, p.505. Choi, Amir Fruchtman, Technical Roadmap for Fault-Tolerant Quantum Computing, Networked Quantum Information Technologies, 2016.

1.2.3Quantum Sensing and Imaging

11S. Pirandola et al., Advances in Photonic Quantum Sensing, Nature Photonics, Vol. 12, 2018, p.724. M. Boss et al., Quantum Sensing with Arbitrary Frequency Resolution, Science, Vol. 356, 2017, p.837.

1.2.4Quantum Foundations

13Adriana Marais et al., The Future of Quantum Biology, Journal of The Royal Society Interface, Vol. 15, 2018, p.20180640. Petruccione, Betony Adams, Quantum Effects in the Brain: A Review, AVS Quantum Science, Vol. 2, 2020, p.22901. Campaioli et al., Enhancing the Charging Power of Quantum Batteries, Physical Review Letters, Vol. 118, 2017, p.150601. Adams, Do Quantum Effects Play a Role in Consciousness?, Physics World, 2021. Li et al., Nuclear Spin Attenuates the Anesthetic Potency of Xenon Isotopes in Mice: Implications for the Mechanisms of Anesthesia and Consciousness, Anesthesiology, Vol. 129, 2018, p.271. A. Sechzer et al., Aberrant Parenting and Delayed Offspring Development in Rats Exposed to Lithium, Biological Psychiatry, Vol. 21, 1986, p.1258.
1Dennis Christensen et al., 2021 Roadmap on Neuromorphic Computing and Engineering, arXiv:2105.05956 [cond-mat], 2021, accessed 11th May 2021. Furber, Large-scale neuromorphic computing systems, Journal of Neural Engineering, Vol. 13, 2016, p.51001, accessed 31st Jul 2016. D Schuman et al., A Survey of Neuromorphic Computing and Neural Networks in Hardware, arXiv:1705.06963 [cs], 2017, accessed 18th May 2017. D. Kendall, Suhas Kumar, The building blocks of a brain-inspired computer, Applied Physics Reviews, Vol. 7, 2020, p.11305, accessed 29th Feb 2020.

1.3.1Neural Network Architectures

5Oliver Rhodes et al., Real-time cortical simulation on neuromorphic hardware, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 378, 2020, p.20190160, accessed 6th Feb 2020. Ning et al., A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses, Frontiers in Neuroscience, Vol. 9, 2015, accessed 31st Dec 2014.

1.3.2Neuromorphic Systems

7Mantas Mikaitis et al., Neuromodulated Synaptic Plasticity on the SpiNNaker Neuromorphic System, Frontiers in Neuroscience, Vol. 12, 2018, accessed 31st Dec 2017. N. Tait et al., Neuromorphic photonic networks using silicon photonic weight banks, Scientific Reports, Vol. 7, 2017, p.7430, accessed 6th Aug 2017. Xu et al., 11 TOPS photonic convolutional accelerator for optical neural networks, Nature, Vol. 589, 2021, p.44, accessed 31st Dec 2020. Davies et al., Loihi: A Neuromorphic Manycore Processor with On-Chip Learning, IEEE Micro, Vol. 38, 2018, p.82, accessed 31st Dec 2017. Akopyan et al., TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 34, 2015, p.1537, accessed 30th Sep 2015.

1.3.3Neural Network Algorithms

12Thomas Bohnstingl et al., Neuromorphic Hardware Learns to Learn, Frontiers in Neuroscience, Vol. 13, 2019, accessed 31st Dec 2018. Zhang et al., A system hierarchy for brain-inspired computing, Nature, Vol. 586, 2020, p.378, accessed 30th Sep 2020.

1.3.4Neuromorphic Benchmarking

14Mike Davies, Benchmarks for progress in neuromorphic computing, Nature Machine Intelligence, Vol. 1, 2019, p.386, accessed 31st Aug 2019. Keyword Spotting Efficiency on Neuromorphic Hardware, Proceedings of the 7th Annual Neuro-inspired Computational Elements Workshop, 2019, p.1, accessed 25th Mar 2019.
1Neil Dalchau et al., Computing with biological switches and clocks, Natural Computing, 2018, accessed 3rd Jun 2018. Grozinger et al., Pathways to cellular supremacy in biocomputing, Nature Communications, Vol. 10, 2019, p.5250, accessed 19th Nov 2019. Purcell, Timothy K. Lu, Synthetic analog and digital circuits for cellular computation and memory, Current Opinion in Biotechnology, Cell and Pathway Engineering, Vol. 29, 2014, p.146, accessed 30th Sep 2014. A.N. Brophy, Christopher A. Voigt, Principles of genetic circuit design, Nature Methods, Vol. 11, 2014, p.508, accessed 30th Apr 2014.


5Hyojin Kim, Daniel Bojar, Martin Fusseneger, A CRISPR/Cas9-based central processing unit to program complex logic computation in human cells, Proceedings of the National Academy of Sciences, Vol. 116, 2019, p.7214, accessed 8th Apr 2019. Goñi-Moreno, Pablo I. Nikel, High-Performance Biocomputing in Synthetic Biology–Integrated Transcriptional and Metabolic Circuits, Frontiers in Bioengineering and Biotechnology, Vol. 7, 2019, accessed 31st Dec 2018.

1.4.2Bio-computational Logic and Strategies

7Lewis Grozinger et al., Pathways to cellular supremacy in biocomputing, Nature Communications, Vol. 10, 2019, p.5250, accessed 19th Nov 2019. V. Nicolau et al., Parallel computation with molecular-motor-propelled agents in nanofabricated networks, Proceedings of the National Academy of Sciences, Vol. 113, 2016, p.2591, accessed 7th Mar 2016. Macia et al., Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia, PLOS Computational Biology, Vol. 12, 2016, p.1004685, accessed 31st Jan 2016.

1.4.3Programmable Bio-synthesis

10Airbus, Airbus and Koniku Inc. embark on disruptive biotechnology solutions for aviation security operations, Airbus, 2020. Courbet et al., Detection of pathological biomarkers in human clinical samples via amplifying genetic switches and logic gates, Science Translational Medicine, Vol. 7, 2015, p.28983, accessed 26th May 2015.

1.4.4Novel Bio-computing Paradigms

12Lewis Grozinger et al., Pathways to cellular supremacy in biocomputing, Nature Communications, Vol. 10, 2019, p.5250, accessed 19th Nov 2019. Selberg, Marcella Gomez, Marco Rolandi, The Potential for Convergence between Synthetic Biology and Bioelectronics, Cell Systems, Vol. 7, 2018, p.231, accessed 25th Sep 2018.
1Caterina Cinel, Davide Valeriani, Riccardo Poli, Neurotechnologies for Human Cognitive Augmentation: Current State of the Art and Future Prospects, Frontiers in Human Neuroscience. S. Leoutsakos et al., Deep Brain Stimulation Targeting the Fornix for Mild Alzheimer Dementia (the ADvance Trial): A Two Year Follow-up Including Results of Delayed Activation, Journal of Alzheimer’s Disease: JAD, Vol. 64, 2018, p.597. R. Willett et al., High-Performance Brain-to-Text Communication via Handwriting, Nature, Vol. 593, 2021, p.249. Society, iHuman: Blurring lines between man and machine, The Royal Society, 2019.

2.1.1Brain Monitoring

5Alexander J. Casson, Wearable EEG and Beyond, Biomedical Engineering Letters, Vol. 9, 2019, p.53. J. Jun et al., Fully Integrated Silicon Probes for High-Density Recording of Neural Activity, Nature, Vol. 551, 2017, p.232. Waldert, Invasive vs. Non-Invasive Neuronal Signals for Brain-Machine Interfaces: Will One Prevail?, Frontiers in Neuroscience, Vol. 10, 2016.

2.1.2Neuromodulation Delivery Systems

8Rafael Polanía, Michael A. Nitsche, Christian C. Ruff, Studying and Modifying Brain Function with Non-Invasive Brain Stimulation, Nature Neuroscience, Vol. 21, 2018, p.174. Antonenko et al., TDCS-Induced Episodic Memory Enhancement and Its Association with Functional Network Coupling in Older Adults, Scientific Reports, Vol. 9, 2019, p.2273. Chen et al., Near-Infrared Deep Brain Stimulation via Upconversion Nanoparticle–Mediated Optogenetics, Science, Vol. 359, 2018, p.679. Velisar et al., Dual Threshold Neural Closed Loop Deep Brain Stimulation in Parkinson Disease Patients, Brain Stimulation, Vol. 12, 2019, p.868.

2.1.3Hybrid Cognition

12Sara Reardon, AI-Controlled Brain Implants for Mood Disorders Tested in People, Nature, Vol. 551, 2017, p.549. Nishimoto et al., Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies, Current Biology, Vol. 21, 2011, p.1641. Horikawa et al., Neural Decoding of Visual Imagery During Sleep, Science, Vol. 340, 2013, p.42. Yu et al., Can FMRI Discriminate between Deception and False Memory? A Meta-Analytic Comparison between Deception and False Memory Studies, Neuroscience & Biobehavioral Reviews, Vol. 104, 2019, p.43. Abe et al., Neural Correlates of True Memory, False Memory, and Deception, Cerebral Cortex, Vol. 18, 2008, p.2811.

2.1.4Memory Modification

17Itzhak Fried, Emily A. Mankin, Modulation of Human Memory by Deep Brain Stimulation of the Entorhinal-Hippocampal Circuitry, Neuron, Vol. 106, 2020, p.218. Suthana et al., Memory Enhancement and Deep-Brain Stimulation of the Entorhinal Area, New England Journal of Medicine, Vol. 366, 2012, p.502. K. Chen et al., Artificially Enhancing and Suppressing Hippocampus-Mediated Memories, Current Biology, Vol. 29, 2019, p.1885. Liu et al., Optogenetic Stimulation of a Hippocampal Engram Activates Fear Memory Recall, Nature, Vol. 484, 2012, p.381. Naufel et al., DARPA Investment in Peripheral Nerve Interfaces for Prosthetics, Prescriptions, and Plasticity, Journal of Neuroscience Methods, Vol. 332, 2020, p.108539.
1Steven M. Weisberg, Daniel Badgio, Anjan Chatterjee, A CRISPR New World: Attitudes in the Public toward Innovations in Human Genetic Modification, Frontiers in Public Health, Vol. 5, 2017. Academy of Medicine, National Academy of Sciences and the Royal Society et al., Heritable Human Genome Editing, National Academies Press, 2020. Cavaliere, The Ethics of Human Genome Editing, WHO, 2019, p.19. Saha et al., The NIH Somatic Cell Genome Editing program, Nature, Vol. 592, 2021, p.195., Human genome editing: recommendations, WHO, 2021.

2.2.1Gene-based Diagnostics and Prevention

6Ji Chen et al., The trans-ancestral genomic architecture of glycemic traits, Nature Genetics, Vol. 53, 2021, p.840. Naeem et al., Latest Developed Strategies to Minimize the Off-Target Effects in CRISPR-Cas-Mediated Genome Editing, Cells, Vol. 9, 2020, p.1608.

2.2.2Gene Therapies and Enhancement

8Jacqueline Martin-Laffon, Marcel Kuntz, Agnès E. Ricroch, Worldwide CRISPR patent landscape shows strong geographical biases, Nature Biotechnology, Vol. 37, 2019, p.613. A. Stadtmauer et al., CRISPR-engineered T cells in patients with refractory cancer, Science, Vol. 367, 2020. Gaj, Charles A. Gersbach, Carlos F. Barbas, ZFN, TALEN, and CRISPR/Cas-based methods for genome engineering, Trends in Biotechnology, Vol. 31, 2013, p.397.

2.2.3Novel Bioengineering Approaches

11Krzysztof Krawczyk et al., Electrogenetic cellular insulin release for real-time glycemic control in type 1 diabetic mice, Science, Vol. 368, 2020, p.993. Mochida et al., Statistical and Machine Learning Approaches to Predict Gene Regulatory Networks From Transcriptome Datasets, Frontiers in Plant Science, Vol. 9, 2018.

2.2.4Synthetic Organisms

1Carlos López-Otín et al., The Hallmarks of Aging, Cell, Vol. 153, 2013, p.1194. Kennedy et al., Geroscience: linking aging to chronic disease, Cell, Vol. 159, 2014, p.709. Tchkonia, James Kirkland, Senolytic drugs: from discovery to translation, Journal of Internal Medicine, Vol. 288, 2020, p.518. Barzilai et al., Metformin as a Tool to Target Aging, Cell Metabolism, Vol. 23, 2016, p.1060.

2.3.1Age-related Diagnostics and Prevention

5Aleksandr Zenin et al., Identification of 12 Genetic Loci Associated with Human Healthspan, Communications Biology, Vol. 2, 2019, p.1. Ahadi et al., Personal aging markers and ageotypes revealed by deep longitudinal profiling, Nature Medicine, Vol. 26, 2020, p.83. Xia et al., Molecular and Phenotypic Biomarkers of Aging, F1000Research, Vol. 6, 2017, p.860. Jylhävä, Nancy L. Pedersen, Sara Hägg, Biological Age Predictors, EBioMedicine, Vol. 21, 2017, p.29. Zhavoronkov et al., Artificial Intelligence for Aging and Longevity Research: Recent Advances and Perspectives, Ageing Research Reviews, Vol. 49, 2019, p.49. Sundaram et al., Predicting the Clinical Impact of Human Mutation with Deep Neural Networks, Nature Genetics, Vol. 50, 2018, p.1161.

2.3.2Fundamental Geroscience

11Geroscience: The Intersection of Basic Aging Biology, Chronic Disease, and Health, NIH. Partridge, Teresa Niccoli, Ageing as a Risk Factor for Disease, Current Biology , Vol. 22, 2012, p.741. V. Pyrkov et al., Longitudinal Analysis of Blood Markers Reveals Progressive Loss of Resilience and Predicts Human Lifespan Limit, Nature Communications , Vol. 12, 2021, p.2765.

2.3.3Slowing Biological Ageing

14TAME - Targeting Aging with Metformin, American Federation for Aging Research. Tchkonia, J. L. Kirkland, Senolytic Drugs: From Discovery to Translation, Journal of Internal Medicine, Vol. 288, 2020, p.518.

2.3.4Reversing Ageing

16Kara N. Fitzgerald et al., Potential Reversal of Epigenetic Age Using a Diet and Lifestyle Intervention: A Pilot Randomized Clinical Trial, Aging, Vol. 13, 2021, p.9419. Lu et al., Reprogramming to Recover Youthful Epigenetic Information and Restore Vision, Nature, Vol. 588, 2020, p.124. Davidsohn et al., A Single Combination Gene Therapy Treats Multiple Age-Related Diseases, Proceedings of the National Academy of Sciences, Vol. 116, 2019, p.23505. W. Koblan et al., In vivo base editing rescues Hutchinson–Gilford progeria syndrome in mice, Nature, Vol. 589, 2021, p.608.
1Matthias Michel et al., Opportunities and Challenges for a Maturing Science of Consciousness, Nature Human Behaviour, Vol. 3, 2019, p.104. Koch, Giulio Tononi, Consciousness: Here, There and Everywhere?, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 370, 2015, p.20140167. Dresler et al., Hacking the Brain: Dimensions of Cognitive Enhancement, ACS Chemical Neuroscience, Vol. 10, 2019, p.1137.

2.4.1Cognitive Capacity Enhancement

4Lea Winerman, Smarter than Ever?, American Psychological Association Monitor, Vol. 44, 2013, p.30. Tsai, Andrii Rudenko, Epigenetic Modifications in the Nervous System and Their Impact upon Cognitive Impairments, Neuropharmacology: Neuroepigenetic Disorders, Vol. 80, 2014, p.70. Bertrand, Learning Empathy Through Virtual Reality: Multiple Strategies for Training Empathy-Related Abilities Using Body Ownership Illusions in Embodied Virtual Reality, Frontiers in Robotics and AI, Vol. 5, 2018. Krokos, Catherine Plaisant, Amitabh Varshney, Virtual Memory Palaces: Immersion Aids Recal, Virtual Reality, Vol. 23, 2019, p.1.

2.4.2Consciousness Assessment

8Jacobo Diego Sitt et al., Large Scale Screening of Neural Signatures of Consciousness in Patients in a Vegetative or Minimally Conscious State, Brain, Vol. 137, 2014, p.2258. Casarotto et al., Stratification of Unresponsive Patients by an Independently Validated Index of Brain Complexity, Annals of Neurology, Vol. 80, 2016, p.718. G. Casali et al., A Theoretically Based Index of Consciousness Independent of Sensory Processing and Behavior, Science Translational Medicine, Vol. 5, 2013, p.198105. Thibaut et al., TDCS in Patients with Disorders of Consciousness: Sham-Controlled Randomized Double-Blind Study, Neurology, Vol. 82, 2014, p.1112. Chang, Spontaneous expression of mirror self-recognition in monkeys after learning precise visual-proprioceptive association for mirror images, Proceedings of the National Academy of Sciences, Vol. 114, 2017, p.3258. H. Porter III, A Methodology for the Assessment of AI Consciousness, Lecture Notes in Computer Science (Springer, 2016), p.305. Kohda et al., If a Fish Can Pass the Mark Test, What Are the Implications for Consciousness and Self-Awareness Testing in Animals?, PLOS Biology , Vol. 17, 2019, p.3000021. Bayne, Anil K. Seth, Marcello Massimini, From Complexity to Consciousness, Trends in Neurosciences, Vol. 43, 2020, p.546.

2.4.3Brain-Machine Interfaces

16Maryam M. Shanechi, Brain–Machine Interfaces from Motor to Mood, Nature Neuroscience, Vol. 22, 2019, p.1554.

2.4.4Sense-expanding Technologies

17Dasha Nelidova et al., Restoring light sensitivity using tunable near-infrared sensors, Science, Vol. 368, 2020, p.1108. Hameed et al., A novel human-machine interface using subdermal magnetic implants, IEEE 9th International Conference on Cybernetic Intelligent Systems, 2010, p.1. Eagleman, Scott D. Novich, Using space and time to encode vibrotactile information: toward an estimate of the skin’s achievable throughput, Experimental Brain Research, Vol. 233, 2015, p.2777.
1Damon Matthews, Kasia Tokarska, Refining the Remaining 1.5C ‘Carbon Budget’,, 192021. Damon Matthews et al., An Integrated Approach to Quantifying Uncertainties in the Remaining Carbon Budget, Communications Earth & Environment, Vol. 2, 2021, p.1. Luderer et al., Environmental Co-Benefits and Adverse Side-Effects of Alternative Power Sector Decarbonization Strategies, Nature Communications, Vol. 10, 2019, p.5229. Batteries, IRENA, 2019. of Solar Voltaic, IRENA, 2019. Emissions Technologies and Reliable Sequestration: A Research Agenda, Engineering National Academies of Sciences, 2018.

3.1.1Negative Emission Technologies

7Jeff Tollefson, IPCC Says Limiting Global Warming to 1.5 °C Will Require Drastic Action, Nature, Vol. 562, 2018, p.172. #GenerationRestoration: Ecosystem Restoration for People, Nature and Climate, UNEP, 2021. Carbon Dioxide, Global CCS Institute. Tollefson, Sucking Carbon Dioxide from Air Is Cheaper than Scientists Thought, Nature, Vol. 558, 2018, p.173.

3.1.2Energy Transition

11EIA Projects Nearly 50% Increase in World Energy Usage by 2050, Led by Growth in Asia, US Energy Information Administration (EIA), 2419. Hydrogen: A Guide to Policy Making, IRENA, 2020. O’Neill, Giant Turbines Poised to Claim Offshore Wind, Engineering, 42021. Pure Hydrogen by Repurposing Existing Gas Infrastructure: Overview of existing studies and reflections on the conditions for repurposing, European Union Agency for the Cooperation of Energy Regulators, 2021. Dreyfus, A. Berka, Decentralisation and Inclusivity in the Energy Sector: Preconditions, Impacts and Avenues for Further Research, Renewable and Sustainable Energy Reviews, Vol. 138, 2021, p.110663.

3.1.3Advanced Materials

16Li-Chiang Lin et al., In Silico Screening of Carbon-Capture Materials, Nature Materials, Vol. 11, 2012, p.633. G. Boyd et al., Data-Driven Design of Metal–Organic Frameworks for Wet Flue Gas CO2 Capture, Nature, Vol. 576, 2019, p.253. J. de Pablo et al., New Frontiers for the Materials Genome Initiative, NPJ Computational Materials, Vol. 5, 2019, p.1.

3.1.4Energy Storage

19M. A. Abdelkareem, A. G. Olabi, Energy Storage Systems towards 2050, Energy, Vol. 219, 2021, p.119634.
1Oran R. Young et al., The Globalization of Socio-Ecological Systems: An Agenda for Scientific Research, Global Environmental Change, Vol. 16, 2006, p.304. Davies et al., Simulating Social-Ecological Systems: The Island Digital Ecosystem Avatars (IDEA) Consortium, Gigascience, Vol. 5, 2016, p.14. Hoßbach, Martin Enders, Dimensions of Digital Twin Applications - A Literature Review, AMCIS 2019 Proceedings, 2019.

3.2.1Physical Models

4Destination Earth: Shaping Europe’s Digital Future. Voosen, Europe Is Building a “Digital Twin” of Earth to Revolutionize Climate Forecasts, Science, 44105. H. Pierce et al., Credit Data Generators for Data Reuse, Nature, Vol. 570, 2019, p.30.

3.2.2Ecological Models

7Petr Baldrian, The Known and the Unknown in Soil Microbial Ecology, FEMS Microbiology Ecology, Vol. 95, 2019. Cressey, Tropical paradise inspires virtual ecology lab, Vol. 517, 2015, p.255. Mirtl et al., Genesis, Goals and Achievements of Long-Term Ecological Research at the Global Scale: A Critical Review of ILTER and Future Directions, Science of The Total Environment , Vol. 626, 2018, p.1439.

3.2.3Socio-economic Models

10United Nations Department of Economic and Social Affairs, 68% of the World Population Projected to Live in Urban Areas by 2050, Says UN, 43236.

3.2.4Integration and Coupling

11Virtual Singapore. Lemus et al., The 4-Site Pacific Transect Collaborative (4-Site), Marine Technology Society Journal, Vol. 55, 2021, p.134.
1P.R. Shukla et al., Chapter 5 : Food Security — Special Report on Climate Change and Land, IPCC, 2019. Food Systems for People, our Planet and Prosperity, 2020. secretariat, Global Assessment Report on Biodiversity and Ecosystem Services, IPBES, 43602. Mooney et al., A Long Food Movement: Transforming Food Systems by 2045, IPES Food Panel, 2021.

3.3.1Ecosystem-level Genetic Modification

5Leah Shaffer, Inner Workings: RNA-Based Pesticides Aim to Get around Resistance Problems, Proceedings of the National Academy of Sciences, Vol. 117, 2020, p.32823. Callaway, CRISPR Plants Now Subject to Tough GM Laws in European Union, Nature , Vol. 560, 2018, p.16. E. Hoffman, Revisions to USDA Biotechnology Regulations: The SECURE Rule, Proceedings of the National Academy of Sciences, Vol. 118, 2021. Torti et al., Transient Reprogramming of Crop Plants for Agronomic Performance, Nature Plants, Vol. 7, 2021, p.159.

3.3.2Alternative Proteins

9Zafer Bashi et al., The Market for Alternative Protein: Pea Protein, Cultured Meat, and More, McKinsey, 43693. C. Onwezen et al., A Systematic Review on Consumer Acceptance of Alternative Proteins: Pulses, Algae, Insects, Plant-Based Meat Alternatives, and Cultured Meat, Appetite, Vol. 159, 2021, p.105058. Treich, Cultured Meat: Promises and Challenges, Environmental and Resource Economics, Vol. 79, 2021, p.33.

3.3.3Resilient Farming

12Achim Walter et al., Smart Farming Is Key to Developing Sustainable Agriculture, Proceedings of the National Academy of Sciences, Vol. 114, 2017, p.6148. García et al., A Systematic Literature Review on the Use of Machine Learning in Precision Livestock Farming, Computers and Electronics in Agriculture, Vol. 179, 2020, p.105826. Leippert et al., The Potential of Agroecology to Build Climate-Resilient Livelihoods and Food Systems , Food and Agriculture Organization of the United Nations, 2020.

3.3.4Personalised Nutrition

15V. Saroja Voruganti, Nutritional Genomics of Cardiovascular Disease, Current Genetic Medicine Reports, Vol. 6, 2018, p.98. M. Ordovas et al., Personalised Nutrition and Health, BMJ, Vol. 361, 2018. R. Sempionatto et al., Wearable and Mobile Sensors for Personalized Nutrition, ACS Sensors, Vol. 6, 2021, p.1745.
1Gil Denis, Towards Disruptions in Earth Observation? New Earth Observation Systems and Markets Evolution: Possible Scenarios and Impacts, Acta Astronautica, Vol. 137, 2017, p.415. J. Muelhaupt et al., Space Traffic Management in the New Space Era, Journal of Space Safety Engineering, Space Traffic Management and Space Situational Awareness, Vol. 6, 2019, p.80. Sudmanns et al., Big Earth Data: Disruptive Changes in Earth Observation Data Management and Analysis?, International Journal of Digital Earth, Vol. 13, 2020, p.832. Resource Exploration and Utilization Act of 2015. Initiative. - European Space Resources Innovation Centre.https://www.esric.lu7Linda J. Tacconi et al., Voyage 2050 Final recommendations from the Voyage 2050 Senior Committee, ESA, 2021. Science and Astrobiology Decadal Survey 2023–2032, National Academies. Publishes Artemis Plan to Land First Woman, Next Man on Moon, NASA, 2120. Jones, China Outlines Space Plans to 2025, Space News, 302021. Paper on China’s Space Activities Published, China Daily, 2816. Nations Office for Outer Space Affairs, Space Economy Initiative 2020 Outcome Report, 2021.

3.4.1Earth Orbit

13Outer Space Objects Index. Space Objects Index. Space Objects Index. Donovan, Eric Rosenbaum, China Plans a Solar Power Play in Space That NASA Abandoned Decades Ago, CNBC, 172019. Voices on 2030 – The Future of Space, KPMG, 2020, p.92. Sentinel Expansion Missions, ESA. Needham, Plans for First Chinese Solar Power Station in Space Revealed, The Sydney Morning Herald, 152019. debris: Analysis and Prediction, ESA. Kessler, BG Cour-Palais, Collision Frequency of Artificial Satellites: The Creation of a Debris Belt, Journal of Geophysical Research, Vol. 83, 1978, p.2637.doi:10.1029/JA083iA06p02637

3.4.2The Moon

22Joey Roulette, NASA’s new space suits are delayed, making a 2024 Moon landing ‘not feasible’’, The Verge, 102021. power and the ITER project, European Commission, 2021. Jones, The Recent Large Reduction in Space Launch Cost, 48th International Conference on Environmental Systems, 2018. Sheetz, Elon Musk’s SpaceX beats Bezos’ Blue Origin in NASA contest to build astronaut lunar lander, CNBC, 162021. Artemis, NASA. DRAFT OF THE POST-2020 GLOBAL BIODIVERSITY FRAMEWORK, UN Convention on Biological Diversity. FH Thompson, Jowitt, Simon M., Gavin M. Mudd, Future availability of non-renewable metal resources and the influence of environmental, social, and governance conflicts on metal production., Communications Earth & Environment, Vol. 1, 2020, p.1. Bardi, Rolf Jakobi, Hiroshan Hettiarachchi, Mineral Resource Depletion: A Coming Age of Stockpiling?, Biophysical Economics and Resource Quality, Vol. 1, 2016. T. Metzger, Jacob Smith, John E. Lane, Phenomenology of Soil Erosion Due to Rocket Exhaust on the Moon and the Mauna Kea Lunar Test Site, Journal of Geophysical Research: Planets , Vol. 116, 2011. T Metzger et al., Cratering and Blowing Soil by Rocket Engines During Lunar Landings, International Conference on Case Histories in Geotechnical Engineering, Vol. 1, 2008. 32Is There an Atmosphere on the Moon?, NASA, 2013.

3.4.3Asteroid Belt

33T. E. Graedel et al., On the materials basis of modern society, Proceedings of the National Academy of Sciences, Vol. 112, 2013, p.6295. Research Council, Minerals, Critical Minerals, and the U.S. Economy, National Academies Press, 2008.35Matthias Willbold, Tim Elliott, Stephen Moorbath, The tungsten isotopic composition of the Earth’s mantle before the terminal bombardment, Nature, Vol. 477, 2011, p.195. Brophy et al., Asteroid retrieval feasibility, IEEE Aerospace Conference, 2012. Glester, Asteroid Trillionaires, Physics World, 112018. Lim, The World Is Running Out of Elements, and Researchers Are Looking in Unlikely Places for Replacements, Discover, 1620. Foust, Deep Space Industries Acquired by Bradford Space, Space News, 219. Foust, Asteroid Mining Company Planetary Resources Acquired by Blockchain Firm, Space News, 3118. Osterloff, How an asteroid ended the age of the dinosaurs, Natural History Museum. Kawaguchi et al., DNA Damage and Survival Time Course of Deinococcal Cell Pellets During 3 Years of Exposure to Outer Space, Frontiers in Microbiology, Vol. 11, 2020, p.2050.ín K. Ragnarsdóttir, Rare metals getting rarer, Nature Geoscience, Vol. 1, 2008, p.720. Elvis, Prospecting asteroid resources, Asteroids (Springer), 2013, p.81. A. Curtis et al., Use of swarm intelligence in spacecraft constellations for the resource exploration of the asteroid belt, Proceedings of the Third International Workshop on Satellite Constellations and Formation Flying, 2003, p.24. Panel on Planetary Protection, COSPAR policy on planetary protection, Space Resources Today, Vol. 208, 2020.


47Elizabeth Howell, A brief history of Mars missions,, 821. UAE. Brown, SpaceX Mars city: What Musk's ‘free planet’ declaration really means,, 32021. Wall, SpaceX's 1st crewed Mars mission could launch as early as 2024, Elon Musk says,, 22021. Weitering, Elon Musk says SpaceX's 1st Starship trip to Mars could fly in 4 years,, 172020. S. F. Portree, Mars in 1995! (1980-1981),, 82012. plans for first manned mission to Mars in 2033,, 242021.
1Center for Science Diplomacy, American Association for the Advancement of Science. Blasiak et al., Evolving Perspectives of Stewardship in the Seafood Industry, Frontiers in Marine Science, Vol. 8, 2021, p.676. Union Science Diplomacy Alliance, European Union. Blasiak et al., The Ocean Genome: Conservation and the Fair, Equitable and Sustainable Use of Marine Genetic Resources, High Level Panel for a Sustainable Ocean Economy. Stone, Timothy Legrand, Science Diplomacy and Transnational Governance Impact, British Politics, Vol. 13, 2018, p.392. A. Levin et al., Global Observing Needs in the Deep Ocean, Frontiers in Marine Science, Vol. 6, 2019, p.241. Rabone et al., Access to Marine Genetic Resources (MGR): Raising Awareness of Best-Practice Through a New Agreement for Biodiversity Beyond National Jurisdiction (BBNJ), Frontiers in Marine Science, Vol. 6, 2019, p.520.

3.5.1Harnessing Ocean Biodiversity

8R. Blasiak et al., The Ocean Genome and Future Prospects for Conservation and Equity, Nature Sustainability , Vol. 3, 2020, p.588. C. Leal et al., Fifty Years of Capacity Building in the Search for New Marine Natural Products, Proceedings of the National Academy of Sciences, Vol. 117, 2020, p.24165. R. Vieira, Fernando Morgado, Marine Bioprospecting to Improve Knowledge of the Biological Sciences and Industrial Processes, Affordable and Clean Energy (Springer), 2020.

3.5.2Transition Ecosystems

11Romain Hugonnet et al., Accelerated Global Glacier Mass Loss in the Early Twenty-First Century, Nature, Vol. 592, 2021, p.726. Watts, World Will Lose 10% of Glacier Ice Even If It Hits Climate Targets, Guardian, 292021. Furhan, Adaptation, Production, and Biotechnological Potential of Cold-Adapted Proteases from Psychrophiles and Psychrotrophs: Recent Overview, Journal of Genetic Engineering and Biotechnology, Vol. 18, 2020, p.36.

3.5.3Repairing the Ocean

14Reniel B. Cabral et al., A Global Network of Marine Protected Areas for Food, Proceedings of the National Academy of Sciences, Vol. 117, 2020, p.28134. Hoegh-Guldberg et al., The Ocean as a Solution to Climate Change: Five Opportunities for Action,, 2019. Al Busaidi, 5 Ways to Net a Sustainable Future for Aquaculture, World Economic Forum, 202018. P. Hughes et al., Global Warming and Recurrent Mass Bleaching of Corals, Nature , Vol. 543, 2017, p.373. Kleinhaus, Science, Diplomacy, and the Red Sea’s Unique Coral Reef: It’s Time for Action, Frontiers in Marine Science, Vol. 7, 2020. González-Rivero et al., Monitoring of Coral Reefs Using Artificial Intelligence: A Feasible and Cost-Effective Approach, Remote Sensing, Vol. 12, 2020, p.489. Boström-Einarsson et al., Coral Restoration – A Systematic Review of Current Methods, Successes, Failures and Future Directions, PLOS ONE, Vol. 15, 2020, p.226631.

3.5.4Improved Ocean Observation

21GEBCO Seabed 2030 Project’. Miao, Shuo Pang, Dapeng Jiang, Development of an Inexpensive Decentralized Autonomous Aquatic Craft Swarm System for Ocean Exploration, Journal of Marine Science and Application, Vol. 18, 2019, p.343. Choi, Mahdi Jadaliha, Environmental Monitoring Using Autonomous Aquatic Robots: Sampling Algorithms and Experiments, IEEE Transactions on Control Systems Technology, Vol. 21, 2013, p.899.
1Joseph E Stiglitz, Crises, Contagion, and the Need for a New Paradigm, 2012. Helbing, Globally Networked Risks and How to Respond, Nature, Vol. 497, 2013, p.51. S. Rogoff, Carmen M. Reinhart, From Financial Crash to Debt Crisis, American Economic Review, Vol. 5, 2011, p.1676. Commission Directorate General for Research and Innovation, alues for the Future: The Role of Ethics in European and Global Governance, 2021.

4.1.1Computational Social Science

5David M. J. Lazer et al., Computational Social Science: Obstacles and Opportunities, Science, Vol. 369, 2020, p.1060.

4.1.2Digital Democracy

6Beth Simone Noveck, Five Hacks for Digital Democracy, Nature, Vol. 544, 2017, p.287.

4.1.3Collective Intelligence

7Dirk Helbing, Richard P. Mann, Optimal Incentives for Collective Intelligence, Proceedings of the National Academy of Sciences, Vol. 114, 2017, p.5077. Williams Woolley, Ishani Aggarwal, Thomas W. Malone, Collective Intelligence and Group Performance, Current Directions in Psychological Science, Vol. 24, 2015, p.420.

4.1.4Design for Values

9Nynke Tromp and Paul Hekkert, Designing for Society: Products and Services for a Better World, 2019.10European Commission Directorate General for Research and Innovation, alues for the Future: The Role of Ethics in European and Global Governance, 2021., IEEE 7000-2021 - IEEE Approved Draft Model Process for Addressing Ethical Concerns During System Design’, 2021.
1M. L Cummings et al., Artificial Intelligence and International Affairs: Disruption Anticipated, 2018. Corneliu Bjola, Diplomacy in the Age of Artificial Intelligence, ETHZ, 82019. Unver, Computational Diplomacy: Foreign Policy Communication in the Age of Algorithms and Automation, SSRN Scholarly Paper, 2017. Meier, Michael Ambühl, Negotiation Engineering: Why Quantitative Thinking Can Also Be Useful in Negotiations, Swiss Pharma, Vol. 43, 2021, p.37. Sabater-Mir, Isaac Pinyol, Computational Trust and Reputation Models for Open Multi-Agent Systems: A Review’, Artificial Intelligence Review, Vol. 40, 2013, p.1.

4.2.1Computational Diplomacy

6Global Diplomacy Index, Global Diplomacy Index, Lowy Institute, 2019.

4.2.2Negotiation Engineering

7Michael Ambühl, Tobias W. Langenegger, Negotiation Engineering: A Quantitative Problem-Solving Approach to Negotiation, Group Decision and Negotiation, Vol. 27, 2018, p.9. Ambühl, Negotiation Engineering: Why Quantitative Thinking Can Also Be Useful in Negotiations, Swiss Pharma, Vol. 43, 2021, p.37.

4.2.3Predictive Peacekeeping

9Philip A. Schrodt, James Yonamine, Benjamin E. Bagozzi, Data-Based Computational Approaches to Forecasting Political Violence, Handbook of Computational Approaches to Counterterrorism (Springer), 2013. Karlsrud, Allard Duursma, Predictive Peacekeeping: Strengthening Predictive Analysis in UN Peace Operations, Stability: International Journal of Security and Development , Vol. 8, 2019, p.1. Lagi, Karla Z. Bertrand, Yaneer Bar-Yam, The Food Crises and Political Instability in North Africa and the Middle East, SSRN Scholarly Paper, 2011. Karlsrud, Peacekeeping 4.0: Harnessing the Potential of Big Data, Social Media, and Cyber Technologies, Cyberspace and International Relations: Theory, Prospects and Challenges (Springer), 2014.

4.2.4Trust and Co-operation Modelling

13Alexander Peysakhovich, Adam Lerer, Maintaining Cooperation in Complex Social Dilemmas Using Deep Reinforcement Learning, ArXiv:1707.01068 [Cs], 22018. Pinyol, Computational Trust and Reputation Models for Open Multi-Agent Systems: A Review’, Artificial Intelligence Review, Vol. 40, 2013, p.1.
1Maya Escueta et al., Education Technology: An Evidence-Based Review, National Bureau of Economic Research, 2017. Serdyukov, Innovation in Education: What Works, What Doesn’t, and What to Do about It?, Journal of Research in Innovative Teaching & Learning , Vol. 10, 2017, p.4. Kreimeia, EdTech Hub.

4.3.1Learning Analytics

8Kenneth R. Koedinger et al., Using Data-Driven Discovery of Better Student Models to Improve Student Learning, Lecture Notes in Computer Science (Springer), 2013, p.421. Vance Paredes et al., Educational Data Mining and Learning Analytics for Improving Online Learning Environments, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 64, 2020, p.500. Hwang et al., A Fuzzy Expert System-Based Adaptive Learning Approach to Improving Students’ Learning Performances by Considering Affective and Cognitive Factors, Computers and Education: Artificial Intelligence, Vol. 1, 2020, p.100003.

4.3.2Educational Sensing

4Amy Ogan, Reframing Classroom Sensing: Promise and Peril, Interactions, Vol. 26, 2019, p.26. Petrosino, Mitchell J. Nathan, Expert Blind Spot Among Preservice Teachers, American Educational Research Journal , Vol. 40, 2003, p.905. Lu et al., A Framework for Learning Analytics Using Commodity Wearable Devices, Sensors, Vol. 17, 2017, p.1382. Shaun Baker et al., Off-Task Behavior in the Cognitive Tutor Classroom: When Students “Game the System”, CHI ’04: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2004, p.383.

4.3.3Out-of-school Learning

11Khe Foon Hew, Min Lan, Examining Learning Engagement in MOOCs: A Self-Determination Theoretical Perspective Using Mixed Method, International Journal of Educational Technology in Higher Education, Vol. 17, 2020, p.7. Economic Forum, A Global Standard for Lifelong Learning and Worker Engagement to Support Advanced Manufacturing, VOCED Plus, 2019. Escobari, Ian Seyal, Michael J. Meaney, Realism about Reskilling, Brookings, 2019., Understanding the Social Outcomes of Learning, OECD, 2007.

4.3.4Neuroscientific Aspects of Learning

15Nastasya Honoré et al., Training Inhibition and Social Cognition in the Classrooms, Frontiers in Psychology, Vol. 11, 2020, p.1974. S. Ling, Adele Diamond, Conclusions about Interventions, Programs, and Approaches for Improving Executive Functions That Appear Justified and Those That, despite Much Hype, Do Not, Developmental Cognitive Neuroscience, Vol. 18, 2016, p.34. A. Simonsmeier et al., Electrical Brain Stimulation (TES) Improves Learning More than Performance: A Meta-Analysis, Neuroscience & Biobehavioral Reviews, Vol. 84, 2018, p.171. Klinge et al., Methylphenidate Enhances Implicit Learning in Healthy Adults, Journal of Psychopharmacology, Vol. 32, 2018, p.70.
1Johannes Buggle, Paula Cacault, Jean-Pierre Danthine, Bending the Line: Moving Towards a Circular Economy, Enterprise for Society Center, 2021. Nations Department of Economic and Social Affairs, Global Sustainable Development Report 2019, 2019. Polasky et al., Role of economics in analyzing the environment and sustainable development, Proceedings of the National Academy of Sciences, Vol. 116, 2019, p.5233. New Circular Economy Action Plan For a Cleaner and More Competitive Europe, European Commission, 2020. circular economy policy goals: enabling the transition to scale, Ellen Macarthur Foundation, 2021. Pathways for Inclusive Growth: From Paralysis to Preparation, Pathways Commission, 2018, p.1.

4.4.1Managing Climate Externalities

7Susan Martin, Climate Change, Migration, and Governance, Global Governance: A Review of Multilateralism and International Organizations, Vol. 16, 2010, p.397. Hino, Christopher B. Field, Katharine J. Mach, Managed retreat as a response to natural hazard risk, Nature Climate Change, Vol. 7, 2017, p.364. K. Sovacool, Björn-Ola Linnér, Michael E. Goodsite, The political economy of climate adaptation, Nature Climate Change, Vol. 5, 2015, p.616.

4.4.2Automation and Work

10Johannes Buggle, Paula Cacault, Jean-Pierre Danthine, Automation Technologies and the Future of Work: Policies for Inclusive Growth, Enterprise for Society Center, 2021. Manyika et al., Jobs lost, jobs gained: workforce transitions in a time of automation | VOCEDplus, the international tertiary education and research database, McKinsey Global Institute, 2017. Restrepo, Daron Acemoglu, Automation and New Tasks: How Technology Displaces and Reinstates Labor, Journal of Economic Perspectives, Vol. 33, 2019, p.3. Bogenschneider, Ryan Abbott, Should Robots Pay Taxes? Tax Policy in the Age of Automation, Harvard Law and Policy Review, Vol. 12, 2018.

4.4.3Bootstrapping Circular Economies

14Yong Geng, Joseph Sarkis, Raimund Bleischwitz, How to globalize the circular economy, Nature, Vol. 565, 2019, p.153. the circular economy: Accelerating the scale-up across global supply chains, World Economic Forum.

4.4.4Sustainable Global Trade

16Mohsin Raza, Pim Martens, Is Globalisation Sustainable?, Sustainability, Vol. 2, 2010, p.280. J. V. Vermeulen, Self-Governance for Sustainable Global Supply Chains: Can it Deliver the Impacts Needed?, Business Strategy and the Environment, Vol. 24, 2015, p.73. Beatriz Lopes de Sousa Jabbour et al., Sustainability of supply chains in the wake of the coronavirus (COVID-19/SARS-CoV-2) pandemic: lessons and trends, Modern Supply Chain Research and Applications, Vol. 2, 2020, p.117. Nandi et al., Redesigning Supply Chains using Blockchain-Enabled Circular Economy and COVID-19 Experiences, Sustainable Production and Consumption, Vol. 27, 2021, p.10.
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4.5.1Multistakeholder Technology Diplomacy

6Daniel Gehrt, Does Science Diplomacy Work in Highly Competitive Technology Areas? An Analysis of the EU’s S&T Cooperation with China in the Field of Solar Photovoltaics, Science and Diplomacy, 232019. Feijóo et al., Harnessing Artificial Intelligence (AI) to Increase Wellbeing for All: The Case for a New Technology Diplomacy, Telecommunications Policy, Artificial intelligence, economy and society, Vol. 44, 2020, p.101988.

4.5.2Integrating Non-State Actors

8Michele Acuto, Mika Morissette, Agis Tsouros, City Diplomacy: Towards More Strategic Networking? Learning with WHO Healthy Cities, Global Policy, Vol. 8, 2017, p.14. Klynge, Mikael Ekman, Nikolaj Juncher Waedegaard, Diplomacy in the Digital Age: Lessons from Denmark’s TechPlomacy Initiative, The Hague Journal of Diplomacy, Vol. 15, 2020, p.185. Roig, Jia Liang Sun-Wang, Juan-Luis Manfredi-Sánchez, Barcelona’s Science Diplomacy: Towards an Ecosystem-Driven Internationalization Strategy, Humanities and Social Sciences Communications, Vol. 7, 2020, p.1.

4.5.3Diplomacy for Big Science

11Jovan Kurbalija, Katharina E. Höne, Accelerating Basic Science in an Intergovernmental Framework: Learning from CERN’s Science Diplomacy, Global Policy, Vol. 9, 2018, p.67. Åberg, The Ways and Means of ITER: Reciprocity and Compromise in Fusion Science Diplomacy, History and Technology, Vol. 37, 2021, p.106.

4.5.4Managing the Global Commons

13Cassandra M. Brooks et al., Reaching Consensus for Conserving the Global Commons: The Case of the Ross Sea, Antarctica, Conservation Letters , Vol. 13, 2020, p.12676. Harden-Davies, The next Wave of Science Diplomacy: Marine Biodiversity beyond National Jurisdiction, ICES Journal of Marine Science, Vol. 75, 2018, p.426. Arthur Berkman et al., The Arctic Science Agreement Propels Science Diplomacy, Science, Vol. 358, 2017, p.596. Steer, Global Commons, Cosmic Commons: Implications of Military and Security Uses of Outer Space, Georgetown Journal of International Affairs, Vol. 18, 2017, p.9.