题目：Does large-scale research infrastructure affect regional knowledge innovation, and how? A case study of the National Supercomputing Center in China

作者：Yang, H., Liu, L. & Wang, G.

来源：Humanit Soc Sci Commun 11, 338(2024)

摘要：Large-scale research infrastructures (LSRIs) are widely acknowledged as a crucial instrument for venturing into the uncharted territories of science and technology, as well as contributing to the well-being of society. However, only a limited number of literature have scrutinized the impact of LSRIs, founded upon a causal inference framework. Moreover, the function of LSRIs in the advancement of innovation at the regional level remains inadequately identified. Drawing on the resource-based view, this study develops a conceptual framework that links the scientific effect of LSRIs to innovation resources in order to assess their impact on knowledge innovation (KI). Taking China’s National Supercomputing Center (NSC) as a case, three major mechanism hypotheses are proposed for the impact of NSC on KI, including basic effect, network effect, and technology effect. Using panel data from 283 cities in China from 2000 to 2020, we employ a spatial difference-in-differences estimation model to examine the impact of NSC on KI. The research finds that: (1) The construction of NSC stimulates KI in local and surrounding areas. (2) The main mechanisms by which NSC promotes KI include the increase in fiscal investment and talents in science, the improvement of digital infrastructure, as well as the enhancement of urban network centrality and innovation efficiency. (3) Geographical proximity, cooperation proximity, and digitization proximity constitute the main channels of policy spillover. (4) NSC has not shown significant promotion of regional innovation convergence, and its radiation influence needs further improvement. (5) The knowledge innovation effects of NSCs manifest heterogeneity based on the distinct knowledge orientation and innovation environment, with this impact being notably pronounced in application innovation-oriented cities such as Shenzhen. The results of this study reveal the positive yet limited impact of NSC on KI and provide a reference for other economies in the areas of LSRIs, digital infrastructure, and the formulation of place-based innovation policy.

题目：AlphaPept: a modern and open framework for MS-based proteomics

作者：Strauss, M.T., Bludau, I., Zeng, WF. et al.

来源：Nat Commun 15, 2168(2024)

摘要：In common with other omics technologies, mass spectrometry (MS)-based proteomics produces ever-increasing amounts of raw data, making efficient analysis a principal challenge. A plethora of different computational tools can process the MS data to derive peptide and protein identification and quantification. However, during the last years there has been dramatic progress in computer science, including collaboration tools that have transformed research and industry. To leverage these advances, we develop AlphaPept, a Python-based open-source framework for efficient processing of large high-resolution MS data sets. Numba for just-in-time compilation on CPU and GPU achieves hundred-fold speed improvements. AlphaPept uses the Python scientific stack of highly optimized packages, reducing the code base to domain-specific tasks while accessing the latest advances. We provide an easy on-ramp for community contributions through the concept of literate programming, implemented in Jupyter Notebooks. Large datasets can rapidly be processed as shown by the analysis of hundreds of proteomes in minutes per file, many-fold faster than acquisition. AlphaPept can be used to build automated processing pipelines with web-serving functionality and compatibility with downstream analysis tools. It provides easy access via one-click installation, a modular Python library for advanced users, and via an open GitHub repository for developers.

题目：国家高性能计算环境运行状态诊断系统

作者：赵一宁、肖海力

来源：数据与计算发展前沿, 2024, 6(1): 57-67.

摘要：本文介绍了一种在大规模分布式运行环境中建立运行状态诊断系统的方法。为保障高性能计算环境的稳定运行，分析日志等环境数据是一种获取环境状态侧写和发现异常的重要途经。然而分析结果通常是文本和数字，对运维人员来讲缺乏直观印象，不利于快速理解。我们建设了国家高性能计算环境运行状态诊断系统，它是一种对于目标计算环境的运行状态进行量化和可视化评判的系统，通过对于目标环境的信息收集、整理，进行不同角度的分项分析。各分析结果被集成为统一的环境运行状态分值，并采用可视化方法将其立体地表现出来，以便相关运维人员能够直观地获取环境信息和快速定位问题。整个环节绝大部分处理分析工作是由程序自动完成，环境运行状态诊断系统极大减少了人工操作量，为运维工作起到有效的支撑作用。

题目：从知识困境到认知陷阱：生成式技术驱动型信息生态系统安全问题研究

作者：白云、李白杨、毛进、李纲

来源：信息资源管理学报, 2024, 14(1): 13-21.

摘要：生成式技术驱动型信息生态系统以生成式人工智能技术为核心，对整个信息环境中的知识传递与共享、认知流动与扩散过程发挥支撑和推动作用。然而，这种创新型的信息生态系统也伴随着知识安全和认知安全问题的出现。本文从知识环境和认知环境两个层面入手，对生成式技术驱动型信息生态系统的特点、优势与风险进行深入剖析，探索如何在符合人类价值观和社会伦理的前提下，充分发挥生成式人工智能的潜力，推动构建高效、安全、可持续发展的生成式技术驱动型信息生态系统。

题目：SDGs科研工作台架构设计与实现

作者：陈灿、朴英超

来源：数据与计算发展前沿, 2024, 6(1): 94-101.

摘要：地球大数据平台为可持续发展目标研究提供了计算资源和数据资源的支持，但各学科研究人员对于资源的占用不均衡，且对资源的使用率也不高。本文致力于解决地球大数据平台中资源使用的问题，更好地服务科研人员开展SDGs研究。本文采用云原生技术构建了一个面向可持续发展研究的一站式科研工作环境，为研究人员提供在线获取和处理数据、训练和使用模型、构建和部署应用软件等服务。极大地减轻了科研人员搭建科研软件栈的工作负担，提高了对占用资源的使用率，同时依托云原生的自动扩缩容能力，实现了资源的均衡使用。通过云原生架构构建的科研工作台，实现了云服务从研发、测试、部署、版本更新到使用的一体化应用生态，有效地支持了面向数据驱动的SDGs研究新范式。

题目：数智赋能信息资源管理新路径: 指令工程的概念、内涵和发展

作者：陆伟、汪磊、程齐凯、刘家伟、黄永

来源：图书情报知识, 2024, 41(1): 6-11.

摘要：新一轮科技革命和产业变革方兴未艾，大数据、人工智能等系列数智技术对信息资源管理学科产生了深远影响。在大模型背景下，指令工程通过高质量、体系化、流程化的指令设计引导模型生成结果，是高效发挥大模型能力的重要途径，可以用于解决学科相关重要问题。本文首先介绍了指令工程的概念，然后详细梳理了指令的构成要素、设计模式以及指令工程的特点和意义，并探讨了指令工程赋能信息资源管理的建设路径。未来，指令工程的研究和发展还需要关注通用及领域指令工程建设、指令工程标准化、知识产权保护、安全性和体系化测试评估等问题，以期能够在各行业复杂的应用场景中更好地发挥指令的效能。