Core Insights - Tsinghua University has developed an AI-driven ultra-high-throughput drug virtual screening platform called DrugCLIP, which significantly enhances the speed of new drug screening by a factor of one million and achieves full coverage of human genome-level targets [1][2] Group 1: Breakthrough in Drug Screening - The traditional drug development process faces challenges in matching small molecules to disease targets, with only 10% of potential targets currently being utilized [2] - DrugCLIP transforms the screening process by converting proteins and small molecules into computer-readable signals, allowing for automatic and precise matching without the need for gradual simulation [2][3] - DrugCLIP can perform 31 trillion matching calculations in a single day on a standard high-performance computer, completing the screening of 1 million candidate molecules in just 0.02 seconds [3] Group 2: Practical Applications and Validation - In practical applications, DrugCLIP demonstrated its accuracy by screening 1.6 million candidate molecules for depression-related targets, identifying 100 potential molecules, with 15% showing effective action on the target [4] - The platform successfully identified potential small molecules for a target related to tumors and Parkinson's disease, where no suitable small molecules had been found before, validating its broad applicability [4] Group 3: Future Prospects and Collaboration - DrugCLIP aims to collaborate with research and industry partners to accelerate the discovery of new targets and first-in-class drugs, focusing on areas such as cancer, infectious diseases, and rare diseases [5] - The platform will continue to optimize its engine performance and expand its support modalities to build a more intelligent, efficient, and inclusive global drug innovation ecosystem [5]

Core Viewpoint - The battery industry is experiencing a significant price increase in core raw materials, particularly lithium hexafluorophosphate, which has surged from 49,300 yuan per ton in July 2025 to around 170,000 yuan per ton recently, prompting companies to raise battery prices by 15% [1][2]. Group 1: Price Increase and Market Dynamics - The rapid price increase of lithium hexafluorophosphate has caught the industry off guard, driven by unexpected demand in the energy storage and electric vehicle sectors, particularly in overseas markets [2]. - Global energy storage market is expanding rapidly, with expected shipments of over 650 GWh in 2025, representing a year-on-year growth of over 80%, while China's energy storage system shipments are projected to exceed 320 GWh, growing by 88% [2]. - The price of lithium hexafluorophosphate, which constitutes 40%-50% of the cost of electrolytes, has significantly impacted downstream battery prices, creating a ripple effect throughout the supply chain [3]. Group 2: Policy Impact and Industry Response - The policy changes in February 2025 aimed at promoting high-quality development in new energy have triggered a surge in new energy storage installations, with a monthly increase of over 460% in May 2025 [3]. - Despite the demand surge, the supply side remains cautious due to high production thresholds and previous losses in the raw materials sector, leading to a consensus against blind expansion [3]. Group 3: Technological and Strategic Shifts - The current price surge is seen as a catalyst for structural optimization in battery technology, shifting the focus from quantity to quality, as companies aim to enhance energy density and cycle life [4][5]. - Leading companies are now prioritizing advanced production lines for high-density, long-life lithium iron phosphate products and larger capacity energy storage cells [4]. - The industry is transitioning from price competition to value competition, emphasizing long-term economic viability, safety, and reliability over initial pricing [5]. Group 4: Supply Chain and Global Strategy - Companies are extending upstream to secure key resources, with strategic partnerships being formed to create stable and resilient supply chains [7]. - The industry is advised to enhance its bargaining power over upstream mineral resources and adopt diversified procurement strategies to stabilize supply [7]. - Globalization is becoming crucial for absorbing advanced production capacity and improving profitability, with a shift in competition from cost and scale advantages to compliance, brand, and service systems [7]. Group 5: Future Outlook - The next 3-5 years are expected to see a mainstream evolution of battery technologies, with material price fluctuations acting as a catalyst for a more resilient development model in the battery industry [8].

在华南装光伏，制造业老板们总有个"心头患"：每年5月至10月的台风季，怕厂房顶的光伏组件被掀飞; 沿海地区盐雾弥漫，组件用几年就锈迹斑斑;夏季高温炙烤，发电量跳水还怕引发电气隐患…… "稳阵"一词在粤语中有着"稳妥、安全"之意。记者1月8日获悉，天合光能专为华南气候"量身定 制"的"至尊N型700W+系列大板型组件"用多重硬核安全屏障搭建起屋顶光伏"好稳阵"。 以福建丰大集团5.99MW屋顶光伏发电项目为例，该项目位于中印尼"两国双园"核心区，采用天合光 能"至尊N型700W+组件"，并网后在夏季台风高发期中安然无恙，经受住了多个强台风的考验，项目质 量得到了充分验证，为沿海地区光伏建设提供了极具价值的示范样本。 据悉，通过风洞测试，该组件可抵御62m/s极限风速，远超行业要求。在抗风设计上，该产品不仅增加 700W+系列组件边框与螺丝连接面的壁厚，还升级边框的结构设计，组件边框宽度增加15%，相当于给 组件装了"钢筋铁骨"。 ...

李超表示，低空经济属于新兴产业，尚处于起步期。下一步，国家发展改革委将会同有关部门和地 方，以筑牢安全责任底线为前提，按照先载货后载人、先隔离后融合、先远郊后城区的原则，严控风 险，因地制宜有序拓展低空经济应用场景，加快探索形成安全有保障、商业可持续的发展模式。 李超指出，近年来，各有关部门和地方瞄准有效需求、结合发展实际，积极探索发展低空经济应用 场景。当前，农林作业、巡检应用等场景已较为成熟，无人机应用规模不断扩大。比如，截至2025年11 月底，我国农用无人机保有量超30万架，作业面积超30亿亩次，广泛应用于植保、施肥、吊运等场景， 有效助力农业生产提质增效；电力线路无人机巡检里程超400万公里，助力电网安全运行。这些应用场 景在改善作业条件、提高生产效率等方面发挥了积极作用，可以大力推广。 低空物流、城市治理、应急救援等场景，则具备较大发展空间。例如，粤港澳大湾区加速布局低空 物流网络，飞行量快速增长，自2022年至2025年11月底，累计飞行超240万架次；浙江等多地无人机化 身"空中交警"，巡查重点道路路况、高空喊话疏导交通，助力城市交通治理；无人机在多次抗震救灾和 防汛抢险工作中发挥独特优势，有 ...

当前，光子领域的各项科技成果转化正如火如荼进行中。在前不久于上海举办的好望角科学沙龙光 子专场活动上，逾百名科学家、科技企业创始人、投资机构负责人等齐聚，共同探讨如何进一步推动光 子领域科技成果转化。与会人员认为，一套好的"算法"能让科技成果在产业化之路上"少撞南墙"。 科技日报记者 付丽丽 他们讨论的"算法"并非数学计算，而是一种对于科学的科技成果转化路径的生动比喻。 主讲嘉宾，中国科学院上海光机所所长、党委副书记张龙认为："高校院所年科研经费近万亿，但 成果转化率却不足5%。问题不在于缺乏技术，而在于科技成果转化方式不够'好用'。" 为此，张龙以杭州光学精密机械研究所为例，分享了"算法"的具体实践。其核心是构建"吸聚—孵 化—投资—转化"生态，并遵循科技成果的"选—育—嫁"逻辑。 "选"即专家"选种"，通过技术委员会、投资顾问委员会等机制确保项目"选得准"；"育"是关键环 节，通过技术研发中心、专业化投资平台和公共服务体系进行"育苗"，确保"育得良"；"嫁"则是通过专 业投资与转移转化中心"择优移栽"，确保"嫁得对"。自2019年成立以来，杭州光学精密机械研究所已引 进60余个技术团队，汇聚600余名研发 ...

记者7日从工业和信息化部获悉，工业和信息化部印发《工业互 联网和人工智能融合赋能行动方案》（以下简称《方案》），推动工 业互联网与人工智能融合赋能水平提升。 基础底座升级行动方面，支持工业企业推动工业网络控网算一体化演 进和能力升级，推进重点行业开展新型工业网络改造等。数据模型互 通行动方面，加强工业数据汇聚共享；建立全国工业数据目录，推动 多源异构工业数据联通共享等。应用模式焕新行动方面，鼓励工业企 业加快平台化设计、智能化生产、个性化定制等应用模式变革等。产 业生态融通行动方面，鼓励工业互联网企业、人工智能企业等加快打 造一批具备智能系统集成能力的解决方案等。（记者 崔爽） 《方案》部署实施4项行动，推动工业互联网和人工智能在更广范 围、更深程度、更高水平上释放融合赋能效应。 《方案》提出，到2028年，满足人工智能工业应用高通量、低时 延、高可靠通信需求的新型工业网络规模持续扩大，在原材料、装备 制造、消费品、电子信息等重点行业工业企业加快部署应用，推动不 少于5万家企业实施新型工业网络改造升级；工业数据汇聚、治理、 流通、共享体系不断完善，在20个重点行业打造一批高质量数据 集。 ...

Core Viewpoint - The "Artificial Intelligence + Manufacturing" initiative aims to deeply integrate AI technology with the manufacturing industry, enhancing innovation and application capabilities by 2027 [1] Group 1: Key Objectives - By 2027, China aims to achieve secure and reliable supply of key AI technologies, maintaining a leading position in industry scale and empowerment levels [1] - The initiative plans to promote the deep application of 3-5 general large models in manufacturing, launch 1,000 high-level industrial intelligent entities, and create 100 high-quality industrial datasets [1] - The goal includes cultivating 2-3 globally influential leading enterprises and a number of specialized small and medium-sized enterprises, while establishing a leading open-source ecosystem [1] Group 2: Major Tasks - The initiative outlines seven key tasks including innovation foundation, intelligence upgrade, product breakthroughs, entity cultivation, ecosystem expansion, safety assurance, and international cooperation [1] - Specific measures include enhancing AI computing power, supporting the development of intelligent chips, and creating high-performance algorithm models tailored for manufacturing [2] - The initiative emphasizes the need for deep integration of AI in production processes, encouraging leading enterprises to pioneer AI applications and promoting digital empowerment for SMEs [2] Group 3: Product Development - The initiative aims to drive the iteration of intelligent equipment, integrating AI technology into the development and manufacturing of major technical equipment like aircraft and ships [3] - It also focuses on upgrading smart terminals, fostering innovation in AI-enabled products such as smartphones and smart home devices, and establishing testing bases for humanoid robots [3] - Policies will support the prevention of "involution" competition in the industry, coordinate funding channels for AI-related R&D, and enhance investment in quality projects [3]

Core Viewpoint - Hangzhou Deshi Biotechnology Co., Ltd. has submitted its listing application to the Hong Kong Stock Exchange, marking a significant step in its journey towards going public after receiving regulatory approval [1][2]. Group 1: Company Overview - Deshi Biotechnology focuses on chromosome karyotype analysis, a classic method for diagnosing major diseases related to chromosomal abnormalities, which include birth defects, infertility, and hematological malignancies [1]. - The traditional karyotype analysis method relies heavily on manual operations, resulting in an average accuracy rate of only about 50% and a reporting cycle of approximately 30 days [1]. Group 2: Market Position and Innovation - The automated karyotype analysis market is dominated by international giants like Carl Zeiss and Leica, which hold over 95% of the market share [2]. - In response to the significant market demand and the lack of domestic equipment, Deshi Biotechnology has pursued an independent innovation path, developing intelligent devices and systems based on the iMedImage platform model [2]. - The company has created a highly integrated automated cell laboratory pipeline that covers four key stages of chromosome karyotype analysis: cell harvesting, slide preparation, image acquisition, and intelligent analysis, achieving full-process automation and standardization [2]. - By 2024, Deshi Biotechnology is projected to capture a market share of 30.6% in China's chromosome karyotype analysis sector, surpassing international competitors and marking a leap forward for domestic manufacturers [2].

Core Viewpoint - The release of the "Opinions on Optimizing Environmental Impact Assessment (EIA) Work for Pharmaceutical Industry Construction Projects" aims to enhance the environmental management of the pharmaceutical sector while promoting green development [1][2] Group 1: Objectives of the Opinions - The Opinions are designed to optimize the EIA process for pharmaceutical projects, particularly when changes occur post-completion, ensuring a balance between flexibility and effective management [1] - The pharmaceutical industry is recognized as a strategic sector crucial for national economy and security, characterized by high R&D demands and rapid innovation [1] Group 2: EIA Management Improvements - The Opinions clarify that changes during the operational phase of projects do not require a new EIA, streamlining the process for companies [1] - It encourages the bundling of EIA documents for similar projects within the same industrial park, which enhances management efficiency and reduces the burden on enterprises [1] Group 3: Pollution Control Measures - The Opinions impose strict requirements for environmental risk prevention related to new pollutants and various pollution control measures for air, water, soil, and solid waste [2] - Specific measures include the management of hazardous substances like dichloromethane and trichloromethane, and the treatment of antibiotic dust emissions and wastewater containing active pharmaceutical ingredients [2] - Local ecological environment departments are tasked with strengthening implementation and supervision during and after the project [2]

Core Viewpoint - The article discusses the significance of operations research in optimizing resource allocation and decision-making processes across various sectors, including the deployment of 5G base stations in China, highlighting its role as a scientific basis for effective management and modern decision-making [1][9][10]. Group 1: Definition and Origin of Operations Research - Operations research originated during World War II, evolving from a tool for specific scenarios to a universal decision-making method applicable across diverse fields [3]. - The essence of operations research is optimization, focusing on achieving the best outcomes while adhering to real-world constraints [4]. Group 2: Application Process of Operations Research - The research process in operations research follows a closed loop: identifying real-world problems, abstract modeling, computational solving, validation, and practical application [7]. - The first step involves accurately defining the problem, which is crucial for guiding subsequent research efforts [5]. Group 3: Role in National Resource Allocation - Operations research serves as a "precision navigation instrument" for national strategic decision-making, transforming complex strategic issues into computable and comparable scientific solutions [9]. - It emphasizes "quantitative optimization" and "system thinking," allowing for a comprehensive view of interrelated factors in resource allocation [10]. Group 4: Contribution to New Productive Forces - Although operations research does not directly produce technology, it fosters new academic directions and enhances efficiency in complex technical development processes [11]. - It plays a critical role in optimizing resource allocation and enhancing collaboration, which is essential for improving overall productivity [11]. Group 5: Future Trends and Challenges - The rise of new technologies like artificial intelligence and quantum computing presents both opportunities and challenges for the evolution of operations research [12][14]. - Future development will likely focus on deeper integration with AI and new computing technologies, expanding its application to complex global issues such as supply chain restructuring and carbon neutrality [15]. Group 6: Recommendations for Development - There is a need for closer integration between operations research and real-world industrial problems, emphasizing the importance of interdisciplinary collaboration and practical application [16]. - The focus should be on embedding operations research methods into national projects and public decision-making processes to create a virtuous cycle of problem-driven research and application [16].