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Abstract To thrive in extreme conditions, organisms have evolved a diverse arsenal of adaptations that confer resilience. These species, their traits, and the mechanisms underlying them comprise a valuable resource that can be mined for numerous conceptual insights and applied objectives. One of the most dramatic adaptations to water limitation is desiccation tolerance. Understanding the mechanisms underlying desiccation tolerance has important potential implications for medicine, biotechnology, agriculture, and conservation. However, progress has been hindered by a lack of standardization across sub-disciplines, complicating the integration of data and slowing the translation of basic discoveries into practical applications. Here, we synthesize current knowledge on desiccation tolerance across evolutionary, ecological, physiological, and cellular scales to provide a roadmap for advancing desiccation tolerance research. We also address critical gaps and technical roadblocks, highlighting the need for standardized experimental practices, improved taxonomic sampling, and the development of new tools for studying biology in a dry state. We hope that this perspective can serve as a roadmap to accelerating research breakthroughs and unlocking the potential of desiccation tolerance to address global challenges related to climate change, food security, and health.

Anion exchange membrane water electrolyser showing the chemical structure of hydroxyl-conductive 2D hBN-based anion exchange membrane (AEM). The developed AEMs exhibit high hydroxyl conductivity, superior mechanical and electrochemical stability.

The Arctic climate system is in great distress, warming faster than the rest of the world and transforming more rapidly than previously anticipated. Sustained and harmonized multidisciplinary observations at key locations are needed to fill knowledge gaps and evaluate the ongoing climate change impacts on the complex Arctic marine system. For more than a decade, the Distributed Biological Observatory (DBO) has functioned as a “detection array” for ecosystem changes and trends in the Pacific sector of the Arctic Ocean. This long-term collaborative initiative builds on active involvement of scientists conducting in situ observations within marine disciplines to systematically document how the arctic marine ecosystem is transforming with environmental change. The DBO concept is currently being expanded into other sectors of the Arctic, including Davis Strait and Baffin Bay, the Atlantic Arctic gateway area, and the East Siberian Sea. Through increased collaboration and joint practices, findings from these regional areas can leverage to pan-Arctic perspectives and improve our understanding of the entire Arctic Ocean. Common practices are now being developed, including key phenomena and relevant indicators to study. Also, we strive towards harmonized routines for sampling, analysis and data sharing to increase the comparability across both disciplines and regions, and to improve the usability of our in-situ observations also for the modelling and remote sensing scopes. An ambition is, moreover, to expand from today's predominantly open-sea coverage towards coastal regions, to the benefit of both local communities and researchers. The process of establishing a pan-Arctic DBO network is to a large part facilitated by the EU Horizon project Arctic PASSION (2022-2025). Here, we present the latest developments and shared priorities, as well as our vision of how to incorporate our efforts into other parallel processes aiming to strengthen the pan-Arctic observing system towards, during and beyond the upcoming IPY.

The European Union's goal of achieving climate neutrality by 2050, outlined in the European Green Deal, is supported by numerous studies providing insights into pathways and emission reduction strategies in the energy sectors. However, model comparisons of such pathways are less common due to the complex nature of climate and energy modelling. Our study brings together integrated assessment models and energy system models under a common framework to develop EU policy scenarios: a Current Trends scenario reflecting existing policies and trends and a Climate Neutrality scenario aligned with the EU's emission reduction target. Both scenarios project reduced final energy consumption by 2050, driven by increased electrification and decreased fossil fuel usage. Electricity consumption increases driven by electrification despite the improved efficiency of electrified technologies. Models align on a shift toward renewables but diverge in technology and fuel choices, reflecting various approaches to reach net-zero energy systems. Furthermore, trade-offs between energy demand and supply mitigation strategies, as well as between renewable energy, e-fuels, and CCS technologies are identified. Considering these model variations, our study highlights the importance of consistent model comparison to offer reliable recommendations to policymakers and stakeholders. We conclude that model diversity is a valuable asset when used sensibly. ISSN:0360-5442 ISSN:1873-6785 Energy, 319

The thesis explores the emerging concept twin transitions (digitalization and decarbonization). It examines how digital innovation interacts with sustainability transitions by focusing on the case of the processing sector, which includes industries such as steel and chemicals. The thesis introduces two conceptual frameworks: (1) the Digital Meta-Regime, which captures the overarching influence of digital technologies across industries; and (2) Digital Innovation Systems, which provides a lens for analyzing how digital innovation operates within specific industries. Central to the research is the idea that while digital technologies like artificial intelligence (AI), digital twins, and advanced analytics hold transformative potential, their actual impact on sustainability is complex and contingent. A case study on AI in the steel industry illustrates this duality. Through an inventory analysis of 140 AI tools and 12 interviews with key actors, we demonstrate how AI facilitates operational efficiencies but tends to reinforce existing fossil-based paths rather than promoting novel low-carbon innovations. This reveals tensions where digital technology risks perpetuating unsustainable practices unless explicitly aligned with sustainability goals. However, the analysis also shows the wide-ranging applications that AI can enable within the steel industry like predicting process parameters; optimizing operations, scheduling, and electrical energy; and forecasting product demand, quality, and site emissions. Further qualitative analysis on the digital innovation system of the Dutch processing industry using 28 semi-structured interviews reveals key innovation resources, systemic problems, system-building activities, and higher-order mechanisms at play. For instance, various socio-technical barriers are faced by organizations involved with digital innovation, ranging from misaligned incentives, decision-making hurdles, and skills gaps to infrastructure, scaling, and partnership challenges, highlighting the challenges of integrating new technologies in industrial contexts. Understanding such digital innovation dynamics helped construct a policy framework for steering digital technologies towards sustainable applications, addressing shared barriers, and embedding better directionality. We argued for balancing critical perspectives with the enabling nature of digitalization, emphasizing the need for nuanced, context-specific policies to drive sustainability and prevent misuse of twin transition narratives by incumbents. To do so, we provide a heuristic tool to assist policymakers and industry actors in navigating twin transitions. The thesis provides theoretical contributions to the literature on technological innovation systems through the development and implementation of a resource-based perspective which provide new insights, beyond the traditional structure-function view. We demonstrate that variable accessibility and applicability are a quality of all technological systems, however, focusing on accessibility and applicability helps reveal unique characteristics within the innovation systems of pervasive or multi-purpose technologies. Additionally, the thesis provides groundwork on the co-dynamics of digital and sustainable innovation, the (ongoing) role of digitalization in shaping incumbent and niche socio-technical configurations, and how systems-thinking can inform twin transition policy. An important methodological contribution is made in combining and balancing technological (or techno-economic) and socio-institutional approaches for studying digital or other socio-technical systems. Further contributions and future work are discussed in relation to institutional logics, deep transitions, and mission-oriented innovation policy. Overall, this thesis provides important structure and guidance for thinking about digitalization in the context of sustainability.

The authors regret that the link to the supplementary documention was inadvertedly not included in the paper. The link to the supplementary documention is now included in this corrigendum. The authors would like to apologise for any inconvenience caused.

OBJECTIVE: There is a growing correlation between the rise in infectious diseases and climate change; however, little is known about the interactions and mixed effects of climate factors on infectious diseases. METHOD: We conducted a retrospective longitudinal study spanning 108 consecutive months from 2014 to 2022 in Can Tho, Vietnam to identify common infectious diseases (excluding tuberculosis, HIV, and COVID-19) and their associations with climate change and determine which common diseases presented concurrently with the COVID-19 period using multivariate linear regression, receiver operating characteristic (ROC) curve analysis, Bayesian kernel machine regression (BKMR) and orthogonal partial least squares discriminant analysis. RESULT: The five infectious diseases with the highest average incidence rates per 100,000 people were diarrhea; hand, foot, and mouth disease (HFMD); dengue fever; viral hepatitis; and influenza. Positive associations with humidity were observed for dengue fever and HFMD. Temperature was positively associated with malaria. Negative associations were found between humidity and both chickenpox and tetanus. Diarrhea (AUC = 0.79; 95 % CL = 0.70–0.87) and dengue fever (AUC = 0.74; 95 % CL = 0.62–0.83) emerged as the most influential diseases both before and during the COVID-19 period. In our BKMR analysis, we found a significant association between the combined influence of temperature and humidity and the occurrence of dengue fever and HFMD, especially when all climate factors were at or above their 60th percentile relative to their values at the 50th percentile. Temperature emerged as the primary driver associated with the occurrence of infectious diseases. CONCLUSION: These findings underscore the importance of implementing robust surveillance, prevention, and control measures by public health authorities in Can Tho. Initiatives like vaccination campaigns, vector control programs, public education on hygiene practices, and strengthening healthcare infrastructure are crucial for mitigating the spread of infectious diseases and safeguarding public health in the region.