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1242. European International Centre of Excellence on Sustainable Resource Management in support of the UN Sustainable Development GoalsSnježana Miletić, Meta Dobnikar, 2025, original scientific article Abstract: The sustainable use of mineral resources essential for energy storage, power generation and the transition to climate neutrality is vital. The United Nations Economic Commission for Europe (UNECE) has set the principles and requirements on sustainable resource management needed to accomplish the 2030 Agenda for Sustainable Development and its goals. To support it, the Horizon Europe’s project abbreviated as GSEU is establishing the Geological Service for Europe, of which an integral part will be an EU International Centre of Excellence on Sustainable Resource Management (EU ICE SRM). This capacity building and knowledge centre will operate as a network of partners and experts to assist the decision-makers and key stakeholders in resource management.
Keywords: resource management, sustainable development
Published in DiRROS: 22.08.2025; Views: 353; Downloads: 90
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1243. Impact of mass transport on meniscus electrochemistry determined by time-resolved operando X-ray photoelectron spectroscopyAlenka Križan, Tove Ericson, Laura King, Qianhui Liu, Robert Temperton, Robert Dominko, Ožbej Vodeb, Dušan Strmčnik, Miran Gaberšček, Maria Hahlin, 2025, original scientific article Published in DiRROS: 22.08.2025; Views: 348; Downloads: 152
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1245. Oka-1 manifoldsAntonio Alarcón, Franc Forstnerič, 2025, original scientific article Abstract: In this paper we begin a systematic study of the class of complex manifolds which are universal targets of holomorphic maps from open Riemann surfaces. We call them Oka-1 manifolds, by analogy with Oka manifolds that are universal targets of holomorphic maps from Stein manifolds of arbitrary dimension. We prove that every complex manifold which is dominable at most points by spanning tubes of complex lines in affine spaces is an Oka-1 manifold. In particular, a manifold dominable by ${\mathbb C}^n$ at most points is an Oka-1 manifold. We provide many examples of Oka-1 manifolds among compact complex surfaces, including all Kummer surfaces and all elliptic K3 surfaces. We show that the class of Oka-1 manifolds is invariant under Oka-1 maps inducing a surjective homomorphism of fundamental groups; this includes holomorphic fibre bundles with connected Oka fibres. In another direction, we prove that every bordered Riemann surface admits a holomorphic map with dense image in any connected complex manifold. The analogous result is shown for holomorphic Legendrian immersions in an arbitrary connected complex contact manifold.
Keywords: Riemann surfaces, complex curves, Oka-1 manifolds, Oka manifolds, K3 surfaces
Published in DiRROS: 22.08.2025; Views: 224; Downloads: 115
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1246. Benchmarking sentence encoders in associating indicators with sustainable development goals and targetsAna Gjorgjevikj, Kostadin Mishev, Dimitar Trajanov, Ljupčo Kocarev, 2025, original scientific article Abstract: The United Nations’ 2030 Agenda for Sustainable Development balances the economic, environmental, and social dimension of sustainable development in 17 Sustainable Development Goals (SDGs), monitored through a well-defined set of targets and global indicators. Although essential for humanity’s future well-being, this monitoring is still challenging due to the variable quality of the statistical data of global indicators compiled at the national level and the diversity of indicators used to monitor sustainable development at the subnational level. Associating indicators other than the global ones with the SDGs/targets may help not only to expand the statistical data, but to better align the efforts toward sustainable development taken at (sub)national level. This article presents a model-agnostic framework for associating such indicators with the SDGs and targets by comparing their textual descriptions in a common representation space. While removing the dependence on the quantity and quality of the statistical data of the indicators, it provides human experts with data-driven suggestions on the complex and not always obvious associations between the indicators and the SDGs/targets. A comprehensive domain-specific benchmarking of a diverse sentence encoder portfolio was performed first, followed by fine-tuning of the best ones on a newly created dataset. Five sets of indicators used at the (sub)national level of governance (around 800 indicators in total) were used for the evaluation. Finally, the influence of 40 factors on the results was analyzed using explainable artificial intelligence (xAI) methods. The results show that 1) certain sentence encoders are better suited to solving the task than others (potentially due to their diverse pre-training datasets), 2) the fine-tuning not only improves the predictive performance over the baselines but also reduces the sensitivity to changes in indicator description length (performance drops even by up to 17% for baseline models as length increases, but remains comparable for fine-tuned models), and 3) better selected training instances have the potential to improve the performance even further (taking into account the limited fine-tuning dataset currently used and the insights from the xAI analysis). Most importantly, this article contributes to filling the existing gap in comprehensive benchmarking of AI models in solving the problem.
Keywords: representation learning
Published in DiRROS: 21.08.2025; Views: 324; Downloads: 122
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