中新网上海12月21日电 (记者 陈静)冥想已成为国际上广泛使用的情绪调节方式。记者21日获悉，随着 脑科学、心理学、AI情绪计算与数字药物体系持续融合，冥想进入"可量化、可评估、可处方、可沉 浸"的智能实践阶段。 AI数智冥想系统定位亦从"单一产品"升级为"数字心理干预链路"：从App的入门引导，到AR的沉浸训 练，再到微厅的深度观测，实现训练连续性、反馈结构化与个体差异可量化补偿，弥补了传统冥想"难 测、难证、难坚持"的不足。其背后集成了脑科学、人工智能、心理学、音乐治疗与数字药物等方法， 是跨学科协同的技术落点。 华东师范大学药学院院长李洪林表示，数智冥想不是单点成果，而是跨学科协同的体现，这不仅是一次 成果展示，而是构建体系，旨在让冥想从"小众修行"转向"常态能力"，让数字药物从单点产品进入制度 体系，让健康人群与疾病人群受益，而不是局限于医疗场景。学院将以药物科学、智能科学、心理科学 等学科为支点，推动未来药学人才、未来干预技术和未来健康场景的融合。下一步，研发团队将围 绕"可提示、可反馈、可干预"原则，构建针对青少年情绪支持、老年睡眠与认知调节、注意力受损群体 等场景的临床验证体系，加速原创成果从 ...

党的十八大以来，"广西生态优势金不换"这一重要论断的提出，既彰显了广西作为南方生态屏障的战略 价值，也对美丽广西建设提出了更高要求。广西高校思政课开展生态文明教育，既是贯彻国家战略的政 治要求，也是新时代高校思政教育内涵式发展需要。当前广西高校思政课生态文明教育面临教学方式偏 传统、内容浅表化、理论与实践脱节等困境。为此，需要整合跨学科资源形成"理论-实践"教学链，开 发本土案例素材，创新数字化教学手段，构建特色化教学路径，实现从知识传授到价值引领的转变。 一、重构课程内容，建立跨学科协同机制 在思政课程中强化生态文明教育，精准嵌入专题内容与议题设计。例如，"概论"课中增设生态文明专题 时，可采用"法律条文+本土案例+技术模拟"的立体教学模式，结合《生物多样性保护法》《自然保护区 条例》及《广西壮族自治区森林和野生动物类型自然保护区管理条例》等法律规章的制度保障，通过卫 星遥感图像量化呈现广西弄岗国家级自然保护区的物种保护成效，搭配喀斯特地貌虚拟仿真实验，动态 演示石漠化治理前后的植被覆盖、岩石裸露率等核心生态指标变化。这种"法律-案例-技术"的三维联 动，能使"绿水青山就是金山银山"的理论具象化，增强理论阐 ...

Core Viewpoint - The article discusses a breakthrough in converting CO2 into high-value C3-C4 diols through a synergistic electrochemical and AI-assisted biosynthesis system, highlighting its significance for green chemistry and carbon neutrality [2][3][4]. Group 1: Research Breakthroughs - A novel carbon-negative emission system has been developed, integrating electrochemical and biocatalytic processes to efficiently convert CO2 into 1,3-propanediol (1,3-PDO) and 1,3-butanediol (1,3-BDO) [4][15]. - The electrochemical module utilizes a CuZn alloy catalyst, achieving an ethanol production rate of 1200 μmol h⁻¹ cm⁻² at an amperometric current density of -1100 mA cm⁻², with a Faradaic efficiency of 35% [6][15]. - The biocatalytic module employs engineered DERA enzymes to extend C–C bonds, significantly enhancing the synthesis efficiency of 1,3-PDO to a record yield of 1.8 g L⁻¹ h⁻¹ [10][15]. Group 2: Technological Innovations - A biomimetic J-T membrane has been developed to address ethanol permeation issues, achieving less than 1% ethanol crossover while maintaining high OH⁻ conductivity [7][15]. - AI-assisted enzyme engineering has led to a 2.5-fold increase in catalytic efficiency for the DERA enzyme, facilitating faster synthesis of target diols [10][15]. - Molecular dynamics simulations revealed that mutations introduced new hydrogen bonding networks, enhancing substrate affinity and catalytic efficiency [11][15]. Group 3: Performance Metrics - The integrated system achieved a production rate of 1.8 g L⁻¹ h⁻¹ for 1,3-PDO and 1.0 g L⁻¹ h⁻¹ for 1,3-BDO, with a carbon atom utilization rate of approximately 80% [15]. - All carbon atoms in the products were confirmed to originate from CO2, showcasing the system's efficiency compared to existing electro-biological hybrid systems, which typically yield less than 0.05 g L⁻¹ h⁻¹ [15][18]. - The research demonstrates significant advancements in catalyst design, membrane separation, and enzyme engineering, emphasizing the potential of interdisciplinary collaboration in green synthesis [16].

Core Viewpoint - Major scientific infrastructure is crucial for supporting original innovation and achieving high-level technological self-reliance in the context of intensified global technological competition [1][4]. Group 1: Development and Current Status - China's major scientific infrastructure has developed into a world-class system through national planning and a phased approach, with facilities like the Shanghai Synchrotron Radiation Facility and the Spallation Neutron Source leading internationally [2][3]. - The current trend is towards systematization, digitalization, and internationalization, integrating technologies like 5G and AI to enhance operational efficiency and facilitate global scientific collaboration [2][3]. Group 2: Strategic Importance - Major scientific infrastructure plays a core role in basic research and industrial applications, providing essential support for fields such as quantum materials and AI training, thereby enhancing the innovation chain from research to application [3][4]. - It serves as a key link in optimizing resource allocation for regional coordinated development, fostering innovation ecosystems across different regions of China [3][4]. Group 3: Challenges and Structural Issues - Despite advancements, China's major scientific infrastructure faces structural challenges, including a tendency to prioritize construction over research and issues with resource allocation and collaboration [6][7]. - There is a need for a systematic approach to overcome these challenges and fully activate the strategic potential of major scientific infrastructure [6][7]. Group 4: Future Directions and Recommendations - To achieve the goal of becoming a technological powerhouse by 2035, major scientific infrastructure must transition from scale expansion to quality enhancement, focusing on strategic areas like quantum technology and deep space exploration [7][8]. - Recommendations include strengthening top-level design, enhancing collaborative mechanisms, innovating funding models, and restructuring talent cultivation systems to better support the infrastructure's capabilities [7][8].