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Large-scale research facilities (LSFs) play a crucial role in advancing fundamental scientific research and enhancing national innovation capacity. This study aims to analyze the organizational characteristics of collaboration within these facilities and their scientific impact. By collecting data on papers published between 2010 and 2023 from four typical LSFs of China, collaboration networks were constructed and compared with papers published in the same period not relying on these facilities. The results indicate that the collaboration network density of LSFs is significantly higher than that of ordinary scientific research networks, with a notably higher proportion of supporting members, reflecting a greater reliance on technical support and auxiliary work. There are also differences between different types of LSFs, with a complex non-linear relationship between the proportion of supporting members and research impact in public experimental platforms, and a significant positive linear relationship between this proportion and research impact in specialized research facilities. The effect of team size on scientific impact varies by facility type, with the number of authors having a significant effect on scientific impact in public experimental platforms and the number of institutions having a more significant positive effect on scientific impact in specialized research facilities. Additionally, the uneven distribution of degree centrality and betweenness centrality significantly affects scientific impact, but this effect varies by facility type. These findings highlight the need for differentiated and refined strategies in managing LSFs. Public experimental platforms should enhance support for core nodes and resource allocation, while specialized research facilities should focus on managing and optimizing the configuration of supporting members. This study provides empirical evidence for the management and resource allocation of LSFs, emphasizing the importance of flexible and refined management to fully harness their potential in driving scientific breakthroughs and technological innovation.

This paper aims to estimate the policy effect of the innovative city pilot policy (ICPP), on the micro-entities’ innovation collaboration. Using the patent data retrieved manually from 1270 Chinese universities and staggered establishments of innovative city pilots in various Chinese cities, we find that ICPP has positive effects on university–industry collaborations (UICs). And a number of additional checks show that the results are robust. Financial support, talent cultivation and interaction, and construction of research facilities are three plausible underlying channels. The policy effects also vary heterogeneously based on city and university characteristics. Our study contributes to the literature on the effect of place-based policies on UICs and provides new insights into improving UIC practices.

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Double Anonymous• Conference submission management system: Morressier• Number of submissions received: 150• Number of submissions sent for review: 83• Number of submissions accepted: 79• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 52.7• Average number of reviews per paper: 2.03• Total number of reviewers involved: 35• Contact person for queries:Name: Elaine JiangEmail: amds_2022@163.comAffiliation: Research Center for Stochastic Configuration Machines(SCM), China

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Double Anonymous• Conference submission management system: Morressier• Number of submissions received: 103• Number of submissions sent for review: 70• Number of submissions accepted: 63• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 61.2• Average number of reviews per paper: 2.03• Total number of reviewers involved: 28• Contact person for queries:Name: Elaine JiangEmail: ammsa2023@163.comAffiliation: Research Center for Stochastic Configuration Machines(SCM), China

Purpose Supplying off-grid facilities such as astronomical observatories with renewable energy–based systems (RES) instead of diesel generators can considerably reduce their environmental impact. However, RES require oversized capacities to counter intermittency and comply with reliability requirements, hence shifting the environmental impact from operation to construction phase. We assess whether 100% RES scenarios are favorable from an environmental point of view and discuss the trade-offs in systems with backup fossil generators versus 100% renewable ones. Methods In this comparative life cycle assessment (LCA), we study various RES supply systems to power a new telescope in the Atacama Desert, Chile. We compare six setups, including 100% RES scenarios, namely, photovoltaics (PV) with batteries and hydrogen energy storage; high-renewable scenarios, with fossil fuel power generation next to RES and storage; and a system combining PV with diesel generation. We base system sizing on a techno-economical optimization for the start of operation in 2030. Foreground data stem from life cycle inventories of RES components since 2015 and 2030 electricity mix assumptions of production countries. We assess environmental impact in the categories climate change, mineral resource depletion, and water use. Results and discussion We find that 100% RES and high-renewable scenarios result in emissions of 0.077–0.115 kg CO 2 e/kWh supplied, compared to 0.917 kg CO 2 e/kWh in the reference case with solely diesel generation. One hundred percent RES scenarios have a lower CO 2 e impact than high-renewable scenarios. However, the latter lower the mineral resource depletion and water use by about 27% compared to 100% RES scenarios. Applying hybrid energy storage systems increases the water use impact while reducing the mineral resource depletion. Conclusions None of the six energy systems we compared was clearly the best in all environmental impacts considered. Trade-offs must be taken when choosing an energy system to supply the prospective off-grid telescope in Chile. We find high-renewable systems with some fossil generation as the better option regarding power reliability, mineral resource depletion, and water use, while inducing slightly higher greenhouse gas emissions than the 100% RES scenarios. As remote research facilities and off-grid settlements today are mainly supplied by fossil fuels, we expect to motivate more multifaceted decisions for implementing larger shares of RES for these areas. To advance the LCA community in the field of energy systems, we should strive to incorporate temporal and regional realities into our life cycle inventories. To ease the path for upcoming studies, we publish this work’s inventories as detailed activity level datasets.

Preface to the Second International Conference on Space Science & Technology (ICSST 2025)With the vision of deepening international academic exchange and broadening global space cooperation, the Second International Conference on Space Science & Technology (ICSST 2025) was convened in two phases.Phase I, the Suzhou Venue (22-24 May 2025), was held in Suzhou, Jiangsu Province, China. It was sponsored by Beijing Institute of Technology, organized by the journal Space: Science & Technology, Aerospace Information Research Institute (CAS), and Soochow University, co-organized by Beijing Minospace Technology Co., Ltd, Harbin Institute of Technology Satellite Technology Co., Ltd, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, and Tsinghua University / China-Russia International Joint Research Center for Aerospace Innovation Technologies.List of Committee Member is available in this PDF.

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Double Anonymous• Conference submission management system: Morressier• Number of submissions received: 151• Number of submissions sent for review: 135• Number of submissions accepted: 119• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 78.8• Average number of reviews per paper: 1.93• Total number of reviewers involved: 39• Contact person for queries:Name: Elaine JiangEmail: amds_2022@163.comAffiliation: Research Center for Stochastic Configuration Machines(SCM), China

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Double Anonymous• Conference submission management system: Morressier• Number of submissions received: 15• Number of submissions sent for review: 15• Number of submissions accepted: 13• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 86.7• Average number of reviews per paper: 2• Total number of reviewers involved: 10• Contact person for queries:Name: Elaine JiangEmail: iceopconf@163.comAffiliation: Research Center for Stochastic Configuration Machines(SCM), China

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Double Anonymous• Conference submission management system: Morressier• Number of submissions received: 114• Number of submissions sent for review: 110• Number of submissions accepted: 101• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 88.6• Average number of reviews per paper: 2• Total number of reviewers involved: 33• Contact person for queries:Name: Elaine JiangEmail: ammsa2023@163.comAffiliation: Research Center for Stochastic Configuration Machines(SCM), China