微型发光二极管（Micro-LED）具有较好的稳定性，是当前高亮显示应用的最佳选择，其具有高对比度、低响应时间、宽工作温区、低能耗和广视角等优势，成为当前产业界和学术界比较看好的新型显示技术。综述了Micro-LED新型显示技术的原理，对比其与现有技术的性能，从材料、器件、集成和成本良率等几个角度探讨了Micro-LED新型显示技术的关键技术挑战。未来3~5年内，Micro-LED显示技术仍然会在材料、器件、集成等技术方面存在技术创新和重大突破的关键机会，该技术支撑着未来显示产业的发展，也是中国科技创新引领全球的一次重要科技革命。建议鼓励创新，营造良好的科技创新环境，通过产学研合作解决当前Micro-LED新型显示技术的关键问题。同时发挥市场和社会资本的作用，引导产业遵循技术发展和商业发展规律。Micro-LED显示产业尽管仍面临技术挑战，但增强现实等近眼显示设备的推出，可能彻底革新现有的显示产品形态，Micro-LED显示产业市场将可能迎来爆发式增长。

量子点以其高色纯度、高效率、可调光谱、广泛的光谱覆盖范围，以及低成本的溶液加工等诸多优点，成为新兴的显示领域材料。然而，无论是以光致发光为主的显示技术，还是发光二极管（QLEDs）显示技术，都面临着一些挑战，如器件寿命低、蓝光效率低、镉基量子点毒性、图案化困难等。总结了量子点的物理特性、量子点的种类、发光机制及在显示领域的研究进展，介绍了镉基量子点QLEDs的研究进展，报道了最新三基色QLEDs的发光亮度、效率和器件寿命。总结了量子点图案化技术，分析了不同技术的优势和劣势。为进一步提高量子点在显示领域的应用，科研人员需要不断开拓和创新，攻克量子点的应用难题，实现自发光量子点显示。

清洁能源转型是一项应对全球气候变化，牵动全球供应链的工程，而关键矿产则是实现净零碳排放目标和发展清洁能源技术不可缺少的物质基础。在沙特试图摆脱对石油经济依赖的前提下，如何保障能源转型过程中所亟需的关键矿产供给、快速发展清洁能源产业是沙特调整经济结构多元化、实现“2030愿景”的重点。当前，中国“一带一路”倡议与沙特“2030愿景”目标高度契合，双方在清洁能源领域合作可以充分实现资源禀赋互补、技术经验共享、产业市场互通。因此，应在社会、供应链等多维度下梳理和分析中沙两国在清洁能源领域的合作基础与发展潜力，在双方的利益视角下提出合作建议，推动沙特能源转型、促进沙特“2030愿景”实现的同时，进一步释放双方资源共享、技术创新、市场开拓等潜力，推进中国与沙特周边地区建立合作伙伴关系，构建“一带一路”中国国际合作发展新格局。

介绍了锂离子电池基本构造、工作原理及回收现状。详细阐述了当前研究中正极材料的主流回收方法，综述了废锂离子电池回收技术的研究进展，其中包括回收工艺发展、回收产品、对环境负担的影响，以及电池退役后的选择，如二次利用、直接再生修复电极材料、湿法或火法冶金回收材料等。从电池材料回收率，循环利用再生体系，电解液、隔膜和负极材料等综合回收方面对现有废旧锂离子电池回收处理与再利用技术提出了改进意见。

本着分门别类、本刊推荐、专家遴选、宁缺毋滥、叙述事实的原则，从国内外重要科技期刊和科技新闻媒体所报道的中国科技成果中，按科学、技术、工程3个类别，由《科技导报》编辑部遴选、推荐候选条目，经《科技导报》编委、审稿人等专家通信评选，推选出2024年中国重大科学、技术和工程进展30项。（1）中国重大科学10项进展分别为：发现迄今全球最早的多细胞真核生物化石；发现新型钙-氧气电池；“拉索”发现高能宇宙线起源关键证据；破解叶绿体基因“转录机器”构造；解密细胞自组织漩涡的机理；实验上首次发现引力子模；提出应用青蒿素类衍生物治疗多囊卵巢综合征的新策略；发现异体通用型CAR-T治疗自身免疫疾病新疗法；发现高丰度绿色元素催化生产低碳烯烃新机制；揭秘月背土壤成分与年代。（2）中国重大技术10项进展分别为：解码抗癌药物紫杉醇的生物合成途径；开发具Pb容量的3D纳米级光盘存储器；研制出大规模智能光计算芯片太极；利用国产型扫描探针显微镜首次“看到”冰表面的原子结构；基于原语表示的类脑互补视觉感知芯片“天眸芯”研制成功；实现以RNA为媒介的基因精准写入；构建超越经典计算机的量子模拟器；研制具有原子尺度局域化光场的奇点介电纳米激光；高性能有机热电材料研究取得重要进展；借助AI破解催化领域重大科学难题。（3）中国重大工程10项进展分别为：中国南极第5站秦岭站建成开站；亚洲第一深水导管架“海基二号”出港；嫦娥六号实现世界首次月球背面采样返回；国家重大工程深中通道正式通车试运营；我国刷新水冷磁体世界纪录；我国首艘大洋钻探船“梦想”号正式入列；我国自主研制世界首台低能量强流高电荷态重离子研究装通过验收；世界最大吨位新型“海上浮式生产储油船”交付离港；全球最大压缩空气储能电站开工；世界最长高速公路隧道天山胜利隧道顺利贯通。

This paper provides a comprehensive review of the development, current status and future prospects of Tokamak-type nuclear fusion devices in the world. First, it expounds the advantages of fusion energy compared with other energy sources, such as its high safety, abundant fuel reserves, high energy density, no greenhouse gas emissions like carbon dioxide and environmental friendliness. Subsequently, it focuses on reviewing the historical development of the Tokamak, from the concept's inception in the 1950s to the current construction of the International Thermonuclear Experimental Reactor (ITER). It highlights the renowned tokamak devices that have made significant influential achievements and critical technological breakthroughs in the world, such as those that have validated the scientific feasibility of controlled nuclear fusion, achieved the highest fusion energy gain (Q), set world records for plasma triple products, reached the highest plasma temperatures, or revealed important physical phenomena, mechanisms, and new or advanced operation modes. Next, the paper also examines the critical scientific and technological challenges yet to be resolved for Tokamak fusion reactors, such as fuel cycles, tritium self - sufficiency, and materials issues. Finally, it offers perspectives on the future development direction of Tokamak fusion reactors and the commercialization prospects of fusion energy. This review aims to serve as a reference for the field of nuclear fusion research.

This article focuses on amorphous matters and reviews recent advances in amorphous materials and physics. More recently, more than 30% of the lunar soil collected by China's Chang'e-5 mission was found to be glassy, further confirming the widespread existence of amorphous matter in the universe. Topological order and inhomogeneity may be hidden behind the seemingly chaotic structure of amorphous materials, so amorphous matters have strange genetic, sensitive and relaxation behaviors, and show a series of excellent physical and chemical properties, such as extreme stability, super-plasticity, super mechanical behavior and excellent soft magnetic properties. The new generation of Zr-based and Fe-based amorphous alloys developed based on order regulation and high flux technology are successfully applied to core components such as folding mobile phone hinges and new energy vehicle motors, indicating that amorphous matters have irreplaceable application advantages. The future development of amorphous matters should focus on introducing a new paradigm of material research, attaching importance to the importance of process innovation, promoting the cross-integration of multi-disciplinary fields, giving full play to the advantages of advanced characterization technology and large scientific devices, and creating a whole-chain innovation model for production, university and research, so as to actively promote the rapid development of amorphous materials and physics, and expand the application of amorphous matters in high-tech fields. Make the future of mankind a better place.

人工智能的飞速发展给生物学研究带来了深远影响，其中，AlphaFold2在蛋白质结构预测领域引发了革命性的突破。评估了AlphaFold2对G蛋白偶联受体（GPCR），结构预测的可靠性，凭借其对蛋白质三维结构的高度准确预测。然而，在实际应用中，AlphaFold2的预测结果并非在所有场景下都足够精确。以GPCR为例，这类重要的药物靶点参与了广泛的生理过程，其结构研究对理解功能机制和药物开发具有重要意义。结果表明，尽管AlphaFold2能够准确捕捉GPCR整体骨架的主要特征，但其预测模型在胞外域与跨膜域的组装、配体结合口袋的形状，以及信号传导界面的构象等方面，与实验解析的高分辨率结构存在显著差异。这些差异限制了AlphaFold2模型在GPCR功能研究和基于结构的药物设计中的应用能力。因此，尽管AlphaFold2为结构预测提供了强大的工具，但其在特定场景下的局限性表明，AI结构预测作为一种辅助工具，尚不能完全取代实验结构生物学，需要联合使用以辅助药理学研究和药物设计。

智能建造数字化平台作为建筑行业数字化转型的关键支撑，在建筑信息模型（BIM）、云计算和大数据等核心技术的驱动下实现了突破性发展。从相关研究总体特征、相关研究现状和平台案例分析3个维度对2010—2023年的相关研究进行分析。研究发现，BIM技术通过三维可视化建模和全生命周期数据管理构建了平台的基础框架；云计算技术凭借其弹性计算资源和分布式处理能力为平台提供了强大的技术支撑；大数据技术则通过实时数据分析和智能决策优化了工程管理流程。以北京城市副中心项目为例，该平台创新性地采用“环状”数字集成交付模式，整合区块链数据确权技术，实现了政府投资项目设计-施工-运维全过程的数字化协同管理，有效解决了传统工程管理中的“三超”问题。然而当前研究仍存在明显局限，比如应用场景主要集中于单体项目层面，缺乏行业级系统整合；技术标准体系尚未统一，制约了数据互联互通；人工智能等新兴技术的融合应用研究相对不足。未来发展方向应着重于构建产业级集成平台，推动规模化应用；建立统一的技术标准和数据接口规范；深化人工智能、数字孪生等创新技术与传统建造技术的融合应用；探索数据资产交易机制，促进数据要素市场化。

重点分析了固态储氢、有机液态储氢、甲醇储氢和氨储氢等多种新型储运氢技术特点、发展现状、经济成本及关键技术瓶颈，探讨了其未来发展方向，并横向对比了不同氢储运技术的经济性水平与应用前景。当前，固态储氢技术已在部分领域实现示范应用，但其大规模产业化仍面临高成本和高能耗等挑战。有机液态储氢技术虽然操作便捷，但受限于脱氢温度高、释氢速率低及对贵金属催化剂的依赖。绿色甲醇和绿氨储氢技术在能耗、安全性和经济性方面仍存在一定制约。不同储运技术各具优势与局限，需要综合考虑氢储运量、运输距离、安全性、碳排放及具体应用场景，以确定最优的技术路径和应用方案。

水处理、能源转化和生物医药等领域对高效分离膜的需求日益迫切。无论是海水淡化、电池隔膜，还是人工离子通道，核心都依赖于纳米孔膜对特定离子的精准筛选。科学界长期以来将这种选择性理解为几何作用：水合离子被紧紧包裹在水分子外衣之中，能否通过孔道主要取决于“身体尺寸”与孔径是否匹配。然而，随着纳米孔尺度越来越小，这一解释逐渐显得不足，因为实际观测到的选择性规律往往无法用几何大小简单说明。

2025年2月24日，国际数学界迎来一项里程碑式突破：34岁的中国数学家王虹与加拿大不列颠哥伦比亚大学教授约书亚·扎尔（Joshua Zahl）合作，在预印本平台arXiv提交了一篇长达127页的论文，称证明了三维挂谷猜想（Kakeya Conjecture）。这一成果被菲尔兹奖得主陶哲轩评价为“几何测度论领域的惊人进展”，并引发全球数学界震动。若通过同行评审，该成果将填补几何测度论领域百年空白，并为调和分析、数论等学科提供新工具。

Envisioning the strategic demands for building a modernized powerful nation in 2040 and motivated by the integrated development of new materials, new productive forces, and emerging industries, this manuscript comprehensively analyzes the common requirements of national strategies, relevant policies, and action outlines regarding frontier-disruptive core technologies and critical material development. Based on the advancement and innovation of Materials Genome Engineering's core technologies setting a crucial foundation for key innovations in AI data infrastructure, foundational material models, R&D of new materials, and industrial applications, AI will further accelerate the development of high-throughput intelligent computing software/tools, drive paradigm shifts from high-throughput experimentation to autonomous experimentation, propel the evolution of material AI agents, construct data resource nodes/platforms with standardized specifications, advance new productivity and novel material industries, as well as foster educational paradigm transformation and next-generation talent cultivation. The convergence of Materials Genome Engineering and intelligent science is fundamentally reshaping the underlying logic of material science, technology, and education through a trinity model consisted of ''theoretical reconstruction, technological empowerment, and industrial traction''. This integration represents not merely disciplinary upgrading, but a systematic transformation encompassing scientific paradigms, industrial ecosystems, and talent development models. It will cultivate interdisciplinary professionals crucial for strategic fields such as advanced materials, emerging industries, and future-oriented sectors.

探讨了大语言模型（LLMs）是否能够通过语言任务的预训练而产生情感智能，并从心理学的角度提出了测试大语言模型的情感智能水平的方法，以及情感智能大模型在心理学的应用。从情感智能的定义出发，回顾了大语言模型的发展历程，总结出目前LLMs相关研究主要集中于提升模型在自然语言处理任务中的性能，而忽视了模型的情感智能，即感知、理解、使用和管理情绪的能力。尽管LLMs在处理语言任务方面表现出色，但在理解和生成情感文本方面仍存在局限性，因此，提出对大模型的情感智能水平进行全面评估的必要性。从心理学角度出发，总结了LLMs情感智能评估相关的工作，倡议心理学把大语言模型作为新的研究对象，重点关注大模型的情感道德问题。从情感认知科学的角度，论述大语言模型作为一种工具，对新时代的情绪心理学研究的重要价值。

2025年8月26日，江门中微子实验（JUNO）成功完成2万t液体闪烁体灌注，并正式运行取数。经过10余年准备和建设，JUNO成为国际上首个运行的超大规模和超高精度中微子专用大科学装置。

矿产资源的开发和利用是维系现代社会经济发展和人类活动的重要基础。然而，近百年来各类矿产资源的开采和加工产生了大量尾矿矿渣，严重威胁着生态环境和人类社会的可持续发展。如何实现尾矿区的生态重建成为实现可持续矿业的关键。在分析传统尾矿生态修复技术不足的基础上，提出基于土壤发生学原理的尾矿生态修复新策略，即尾矿成土生态工程。具体而言，本策略将尾矿视为成土母质矿物，通过系统性生态工程手段加速成土过程，并逐步将其改造成具有多孔物理结构和化学缓冲特性，能够承载生态功能的稳定类土基质，从而实现对尾矿区的生态重建。尾矿成土生态工程需综合考虑尾矿的特性、本地微生物和植物物种资源及气候条件，因地制宜设计技术路线，构建成套技术体系。最后，基于现有研究进展，提出了尾矿成土的关键基础科学问题和技术应用前景。

简要回顾2024年原子核物理科技发展的前沿与热点，放射性核束物理，相对论重离子碰撞物理，中低能与高能的交叉、无中微子双贝塔衰变、超精细结构、核钟、核物质状态方程与核天体物理等交叉学科及核医学等方向，其中有涉及理论的拓展也有实验的突破，这些原子核物理学的发展不断地推动我们对物质基本构成和宇宙演化的深入理解。

2025年1月20日，中国全超导托卡马克核聚变实验装置（EAST）在合肥实现1亿℃，持续1066 s高约束模等离子体运行，打破了此前该装置403 s的世界纪录。这一成果由中国科学院合肥物质科学研究院等离子体物理研究所团队完成，标志着中国聚变能源研究从基础科学向工程实践迈出重大一步。

实现技术发展与安全的平衡，是当前全球人工智能治理必须直面的重大现实问题。目前全球人工智能治理最具代表性的是，欧盟以伦理先行为导向的“硬法治”模式和美国以技术先行为导向的“软规则”模式。从治理思想、治理主体、治理体系和治理策略系统分析了2种模式的区别，并基于此提出了优化我国人工智能治理路径的政策启示：在治理思想上，应坚持伦理治理和鼓励创新并重；在治理机制上，建立分级分类风险治理机制，实行精细化监管；在治理体系上，构建多层次全方位的人工智能治理体系；在治理主体上，注重发挥企业和行业自治力量；在治理合作机制上，积极参与多边治理交流合作，提高中国在人工智能全球治理的影响力和话语权。

2023年是著名博物学家阿尔弗雷德·拉塞尔·华莱士诞辰200周年、逝世110周年，纪念他的最佳方式是总结和弘扬其精神遗产。以文本细读和个案研究为主要研究方法，在简要回顾华莱士的重要自然科学成就的基础上，着重阐述他为追求真理而无畏艰险的牺牲精神、坚持实地调查的方法论态度、勇于挑战权威的理论创新精神。博物学家华莱士是一位将科学要求与伦理要求相统一，具有高度社会责任感的空想社会主义者，他留给后人的最宝贵的精神财富正是其科学精神与人文关怀。

Deep-sea exploration is a key technology for developing marine resources, studying the evolution of the Earth, and protecting the Earth's ecosystem. This paper reviews the main progress of deep-sea exploration technology in the past seven years (2019–2025), including the fields of submersibles, sensors, communication, energy, etc., and looks ahead to the development trends in the next 5~10 years. Firstly, the importance and challenges of deep-sea exploration are introduced. Then, the current status of technologies in various aspects such as deep-sea submersibles, sensors and observations, sampling and analysis, communication and navigation, energy, as well as big data and artificial intelligence are described in detail. The analysis shows that intelligentization, long endurance, and in-situ experimental technologies will become the core directions, but the adaptability to high-pressure environments, energy supply, and data transmission remain the main bottlenecks. Subsequently, the future development trends such as intelligentization and autonomy, long endurance and energy innovation, and the cost revolution are discussed. It is expected that this paper will play a certain guiding role in promoting the sustainable development of deep-sea exploration technology.

阐述了因DeepSeek横空出世引发的关于AI发展路径的思考。首先解释了为什么DeepSeek会引起全球性的科技震撼，接着讨论了“规模法则”（Scaling Law）是否已遇到天花板、发展“通用人工智能”（AGI）应选择什么道路、发展人工智能应该追求高算力还是高算效（高能效）、“开源”为什么有这么大的威力等问题。最后对中国在人工智能领域的实力提升和如何实现人工智能自立自强提出建议。

深入探讨了大科学装置在推动人类知识创新进程中的核心作用，特别聚焦于稳态强磁场实验装置（SHMFF）这一实例，剖析了其在达成科学目标、驱动知识创新、促进产业升级、加强国际合作与交流以及吸引高端人才等多个维度上的显著贡献。SHMFF通过构建高场磁体集群，为物理、化学、材料、生物学等多学科前沿研究提供先进实验条件，支撑用户取得系列高水平成果。其衍生技术广泛应用于高端装备制造、药物研发等领域，有效促进区域经济发展。同时，SHMFF坚持开放共享理念，通过国际合作在生物、材料等领域取得多项突破，促进知识共享。SHMFF的成功实践验证了大科学装置对知识创新的推动作用，也为中国优化大科学装置布局、提升设施先进性提供了重要参考。未来，持续建设和完善大科学装置体系，将成为推动知识创新和科技进步的重要战略支撑。

江泽涵是中国著名数学家、数学教育家，中国拓扑学派开创者。学术研究方面，深耕于拓扑学领域，带领团队取得国际瞩目的成果，竭力促进国内数学研究的发展；数学教育方面，重视数学基础教育改革，强调数学竞赛的人才选拔功能和数学史的教育价值，对基础教育产生了积极深远的影响；行政管理方面，积极整顿学风，深入系务改革，大力推动了北大数学系的蓬勃兴盛。通过回顾江泽涵的学术人生和数学贡献，缅怀其留下的教育思想和崇高精神。

《地外原位资源利用差距评估报告》是国际空间探索协调组（ISECG）定期更新的关于全球太空探索任务的汇总文件，旨在推动全球太空探索与原位资源利用（ISRU）的可持续性。首先，基于ISRU的总体目标与关键结构分解，总结了目前针对ISRU技术、试验测试设备以及星壤模拟物3方面开展的评估工作，并进行归类比较。其次，通过重点解析此报告的ISRU差距评估内容，依次对各参与国当前在原位资源勘查、原位资源采集和预处理、生产消耗品的资源加工、生产建造和制造原料的资源加工、月面原位建造、地外空间制造6大关键领域的技术研究重心与优势展开具体的分析。最后，提出了基于解析此报告对ISRU技术的多学科融合研究、高保真极端环境模拟平台建设以及结合深空探测需求推进高水平ISRU任务实施的展望。

2025年3月5日，美国计算机学会（ACM）宣布，将2024年图灵奖（Turing Award）授予美国马萨诸塞大学教授Andrew G.Barto与加拿大阿尔伯塔大学教授Richard S.Sutton，以表彰他们对强化学习理论框架方面的开创性贡献。图灵奖被誉为“计算界诺贝尔奖”，由谷歌公司提供百万美元奖金支持。谷歌高级副总裁Jeff Dean强调，这一贡献直接实现了图灵“机器经验学习”的构想，其算法已成为自动驾驶、芯片设计等领域的技术支柱。

夜幕降临时，几位科学家正乘坐中国载人深海潜水器“奋斗者”号向深渊进发。随着潜水器逐渐下潜，在深不可测的黑暗中，上海交通大学极端环境微生物学家赵维殳瞥见了散发着绿、黄、橙3色荧光的发光生物。抵达万米海底后，研究人员打开探照灯，一片“深邃神秘的蓝色”随即映入眼帘，到处漂浮着形形色色的浮游生物。Weishu Zhao回忆道，“那一刻，我幡然领悟，（深海）一定是一个超乎人类想象的奇特世界”

Biological carbon fixation is crucial to the Earth's carbon cycle and is one of the effective ways to transform CO₂ and manage carbon emissions. Chemoautotrophs, with their unique metabolic strategies and environmental adaptability, play an important role in this process. They are able to convert CO₂ into valuable organic products, solving the problem of limited CO₂ utilization. However, the carbon fixation potential of chemoautotrophs in controlled systems has not been fully explored. This review illustrates the possible challenges of stable culture of chemoautotrophic bacteria in bioreactor. Based on this, a series of physical, chemical and biological methods are proposed to regulate the carbon metabolism of chemoautotrophic bacteria and improve their carbon fixation efficiency. Further, the application prospects of chemoautotrophic carbon fixation in controlled systems are expected, including improving the primary productivity of natural ecosystems, reducing carbon emissions in specific sites, and producing high−value microbial by−products. This review highlights the advantages and challenges of these applications, providing important insights into carbon capture, fixation and conversion by chemoautotrophs.

海洋具有广阔的空间和较为理想的风力条件，相比陆上风电，海上风电能够获取更为稳定和强劲的风能资源，从而提高发电效率和输出功率。在分析中国海上风电发展现状的基础上，结合中国发展海上风电存在海洋资源法律体系不完备、海洋规划体系待深化、海洋综合管理机制不健全、海上风电产业政策支持力度不够等问题，借鉴国外发展海上风电的经验，从完善海洋资源开发利用管理立法、加强海洋空间规划体系保障、健全海洋资源开发利用管理机制、完善海上风电产业链发展政策等方面提出中国发展海上风电的对策建议，可以为中国海上风电产业的未来发展提供参考和借鉴。

分析了激光无线能量传输（laser wireless power transmission，LWPT）技术的基本原理、发展背景及未来应用。该技术基于受激辐射原理，将电能转化为激光能量，经过大气或真空介质传输后，最终由激光电池将光能高效转换为电能，具备高方向性、高能量密度、远距离传输等优势。在低空产业领域，LWPT可为无人机、飞行汽车等提供持续能源补给，显著提升续航能力与作业效率；在商业航天领域，其可为卫星、空间站及深空探测器构建灵活的能量传输网络，支撑长期太空任务。展望未来，LWPT技术与激光通信、卫星遥感定位等技术结合，可实现能源与信息的协同传输，构建交通–信息–能源三网融合的智能化蓝图，推动交通系统向高效化、自动化迈进。这一目标的实现，需依托多行业深度合作与持续技术创新，并同步推进跨领域协同研发及标准规范制定。通过推动该技术的发展，有望催生能源传输领域的革命性变革，为现代社会的发展提供坚实的支撑。

个人基因信息在基因技术中的应用存在隐私泄露、基因歧视等伦理风险。对于基因信息应用伦理风险的治理，机构内设伦理委员会审查模式难以保证审查公正性、既有的匿名化标准不足以肩负保护公民个人基因信息的重任、反基因歧视法律法规亟待完善、增强型基因编辑规制不足。通过研究中国基因信息保护的制度现状，确定了基因信息技术伦理治理的基本立场，提出了基因信息应用伦理风险治理的优化路径，具体包括严格基因信息应用的伦理审查机制、确立基因信息的合理使用标准、完善反基因歧视法律法规、完善非法植入基因编辑、克隆胚胎罪。

新一代信息技术作为智能互联技术体系的关键要素，重构了智能制造价值链，为智能制造质量管理提供了新范式。结合中国智能制造发展实际情况，分析了新一代信息技术背景下智能制造质量管理的新趋势与新需求。概述了质量4.0的基本理论，拓展了质量4.0中价值链的含义，并通过内部价值链、产业价值链与相关方价值链3个维度构建了基于质量4.0的智能制造全价值链质量管理模式，以促进质量4.0理论与方法在智能制造质量管理实践中落地。

The impact of global warming and how to deal with it are topics of widespread concern across various sectors of society. This paper focuses on the impacts of global climate change on dryland. Over the past fifty years, the temperature has risen at the rate of 0.32℃ /decade, and climate warming has enhanced the evaporation capacity and consequently expanded the world's arid regions by approximately 2.61×10⁶ km². The frequency and severity of droughts has also increased, with an average of 251 meteorological droughts occurring in 34 major river basins. The drought heatwave compound events and flash droughts are becoming more common. The duration of heat waves has extended from 8 to 12 days on average. With climate warming, the water availability has decreased with increased water uncertainty. Concurrently, greenhouse gas emissions increased and carbon sequestration reduced. Desertification has aggravated, and poverty?stricken area has expanded. In light of these challenges, it is recommended to vigorously advocate carbon emission reduction strategies to curb the pace of climate warming, strengthen international cooperation, formulate a global action plan to mitigate the continuous expansion of arid areas, build a cooperation mechanism to address climate change in terms of policy, management, education, science and technology, finance and other aspects, and solve the "double dilemma" of desertification and poverty in multiple ways.

图像压缩感知是一种能够在低采样率下实现高效信号采样与重构的技术，但在实现高质量图像重构时，面临局部与全局特征难以有效融合的问题。为此，提出一种结合Transformer与卷积神经网络（convolutional neural networks，CNN）优点的图像压缩感知重构框架（transformer-CNN mixture transformer，TCMformer）。该框架充分利用CNN的局部建模能力和Transformer的全局特征捕捉能力；设计了一种特征融合模块（TCM Block），有效桥接局部与全局特征，从而提升特征表示效率；同时，为降低模型复杂度并控制计算成本，框架采用基于窗口的Transformer结构，通过分块实现高效的全局建模。此外，引入渐进式重建策略，利用多尺度特征图逐步优化重建质量。实验结果表明，TCMformer在峰值信噪比、结构相似性和视觉效果上相较于主流的压缩感知重构算法表现更优，为实现高质量的图像重建提供了一种有效的解决方案。

It is the obligation of the parties to the Convention on Biological Diversity to update and revise the National Biodiversity Strategies and Action Plans (NBSAPs). COP15 decision required all parties to revise or update NBSAPs in alignment with the Kunming−Montreal Global Biodiversity Framework including national targets communicated in a standardized format. China's strategic position in biodiversity conservation has been continuously rising. In January 2024, the China's Biodiversity Conservation Strategy and Action Plan (2023−2030) was officially released. This article reviews the main considerations and elements changed in the update and revision of the NBSAP, and introduces the main contents of the NBSAP, including four priority areas: mainstreaming biodiversity, responding to the threat of biodiversity loss, sustainable utilization and benefit sharing of biodiversity, and modernization of biodiversity governance capacity. Topical issues and newly added priority actions have been analyzed and interpreted. This article also summaries the main implications and practical significance of the NBSAP. A Chinese solution for promoting the implementation of the Kunming−Montreal Global Biodiversity Framework was submitted. NBSAP was connected with domestic policies in the field of biodiversity, guiding local levels to carry out conservation practices, and providing a reference for analyzing and responding to new focuses and new issues in future biodiversity conservation work.

The accurate and efficient extraction of building from remote sensing images is fundamental for applications such as fine urban management, high−precision mapping, and land resource investigation. It is essential to investigate how to leverage image features for intelligent interpretation. This study introduces a global self−attention network with edge−enhancement (E−GSANet) for remote sensing building extraction. The network integrate the edge enhancement module into the encoder backbone, providing the network with a priori knowledge about boundaries, and then establish long−distance dependency relationships between features using the global self−attention feature expression module, enabling the fusion of salient features with edge−enhanced features. A stepwise up−sampling decoding module is designed to fusing the shallow features with rich spatial detail information and the deep features with high−order semantic information to obtain accurate extraction results of buildings. The comparison experiments between E−GSANet and the current mainstream methods is conducted based on two open−source remote sensing building datasets. The quantitative analysis and qualitative demonstrations prove that E−GSANet achieves optimal results across all evaluation metrics, yielding more complete building extractions, precise edges, and higher accuracy. Additionally, network structure ablation experiments and analysis demonstrate the effectiveness of each module.

Drug discovery, as the core driving force of the modern pharmaceutical industry, faces the difficulty of the traditional model's "high investment, long cycle, and low output, " urgently requiring breakthroughs to address increasingly complex health demands. The rapid development of artificial intelligence (AI) technology has brought revolutionary changes to drug discovery, significantly enhancing efficiency and success rates in areas such as protein structure prediction, protein design, antibody drug design, and small molecule drug development. This article focuses on the domestic and international progress of AI in these key domains, providing an in-depth analysis of AI breakthrough in protein structure prediction and its potential applications in target discovery and virtual screening. It explores the closed-loop model of AI-driven protein design, from structure prediction to functional innovation, and examines AI's role in antibody sequence optimization, affinity maturation, and novel antibody design. Additionally, it reviews the latest achievements of AI in small molecule drug target identification, virtual screening, and ADMET optimization. The article also highlights challenges in AI applications, including data quality, model interpretability, and experimental validation, while envisioning future directions such as multimodal data integration, dynamic behavior prediction, and automated platforms. By comprehensively analyzing the current state and challenges of AI-enabled drug discovery, this article aims to offer scientific perspectives and insights to accelerate new drug creation and enhance human health and well-being. It seeks to provide readers with a thorough and insightful view of technological issues in AI-empowered drug discovery, stimulate thinking about future directions, and promote the more effective application of AI technologies in this field, ultimately benefiting human health through an accelerated drug development process.

在量子信息技术与信息通信技术融合背景下，面向提升信息通信安全性和便携性的迫切需求，采用了理论分析和实际应用案例结合的方式，探讨了量子保密通信与5G融合的探索实践，展示了量子保密通信在5G网络中的融合策略与应用成效。量子保密通信正携手5G在承载网络、网络切片等基础设施层面探索融合，同时催生出量子加密通话、量子加密对讲等融合创新应用。展望了量子保密通信与5G融合的未来发展：随着量子保密通信和5G在基础设施、应用场景等方面不断深度融合，将共同构筑高速泛在、自主可控的数字基础设施，为数字经济的蓬勃发展提供坚实而强大的安全保障，有力推动产业数字化转型升级，助力数字经济持续发展。

党的二十大报告强调了弘扬科学家精神对于科技创新的重要意义。从实证角度阐释科学家精神在杰出科学家身上的生成理路有助于探寻科技创新人才的应然成长路径。基于对国家最高科学技术奖获得者报道材料的语义网络分析，发现几种重要的身份是科学家展现科学家精神的中介因素；基于扎根理论的分析进一步构建了科学家精神的理论模型。根据研究结论得出的启示有：必须重视对科技创新人才的身份塑造、实行科学精神6个内涵的一体教育和重构科学家精神中创新和育人的蕴涵。此外，面向科技创新人才的爱国主义教育必须重视体悟，要帮助科技创新人才树立终身学习的理念，国家和社会要充分肯定科技创新人才家人的贡献。

The dual pressures of urbanization and climate change are intensifying the urban heat island effect, carbon emissions, and air pollution, posing significant challenges to environmental sustainability and urban livability. As the demand for multiobjective coordinated management of urban ecological environments continues to increase, integrating heat, carbon, and pollution into a unified framework for comprehensive assessment has become a key direction for future urban planning and policy−making. This article systematically compares and analyzes the consistency between global development agendas and the goals of reducing urban heat, carbon, and pollution, highlighting the significant potential and advantages of new−generation information technologies in intelligent optimization and coordinated scheduling, data fusion and analysis, real−time monitoring and feedback, and decision support and simulation. From the new perspective of urban spatial form, it comprehensively reviews the specific content, challenges, and future issues in conducting multi−scale, multi−dimensional "heat−carbon−pollution" multi−objective coordinated reduction planning. It provides innovative solutions for multi−objective coordinated management and sustainable development of "heat−carbon−pollution" in Chinese cities.