□四川日报全媒体记者 王若晔 冬季来临，温泉康养旅游迎来消费旺季。四川地热资源丰富，总量位居全国第三，截至目前，四川共调查核实地 热点近400处，是名副其实的地热大省。作为地热最常见的表现形式，温泉一般藏在哪儿？如何发现它的踪迹？在 四川，就有一群用科技破解地下热脉密码的温泉"猎手"。 近日，由西南交通大学牵头完成的《四川盆—山水热型地热资源形成机理与勘查开发研究与应用》，荣获2025年 度绿色矿山科学技术进步奖二等奖，该奖项是我国绿色矿山领域最具影响力的社会力量奖项之一。 探泉之难： 地质构造复杂且寻泉方法须升级 四川省地球物理调查研究所教授级高级工程师武斌，与温泉打了几十年交道，谈起四川温泉如数家珍。 从20世纪50年代开始，四川就启动了中深层地热能开发利用工作，武斌团队陆续发现了不少温泉，但也有不少空 手而归的时候。 "找温泉是一个复杂的技术活。"武斌说，"温泉一般出现在地质构造十分复杂的地方，地质成因和演化过程更是错 综复杂，要用到一系列关键技术手段，得会观山听雨，读懂大地的信号。" 这与四川复杂多样的地形密不可分。全省地形地貌差异显著，地热资源分布、赋存条件各不相同，进一步增加了 勘查难度。尽管四川 ...

转自：中国科学报 经历高温炙烤时，植物会"喊热"吗？遭遇病虫害时，它们是否会"呼救"？缺乏营养时，他们又是否会张 口"求援"？ 对于这些问题，相信很多人都会给出否定答案。但事实上，科研人员早已经发现，植物会和动物一样表 现出"喜怒哀乐"，而这些关键性的生理信息就藏在叶片发出的荧光信号中。 能够感知和解析这些信号的设备被称为叶绿素荧光检测仪器。它们如同一个个精通植物语言的"翻译 官"，可以让科研工作者清晰读懂植物的"心里话"，有效实现对植物光合生理信号的精准解读。 长期以来，我国在该领域的高端设备一直依赖进口，但不久前，这一局面终于被打破——江南大学教授 郭亚团队经过多年持续攻关，实现了系列高性能叶绿素荧光检测仪器的研发和量产。 "健康的植物体内，光合作用运转顺畅，叶绿素吸收的绝大部分光能都被有效利用，只有极少能量会变 成荧光'漏'出来。"郭亚说，但当植物出现干旱、病虫害等问题时，其转化效率便会降低。此时，多余 的能量会重新分配——初期，大量能量会以荧光形式散发，导致荧光信号增强，但随着植物启动强大 的"热耗散"保护机制，过剩能量将更多以热形式释放，导致荧光"泄露"比例相对降低。 "这种荧光的动态变化，正是植物 ...

Core Insights - AQR Capital Management's multi-strategy product achieved a return of 19.6% in 2025, continuing its recovery trend despite a turbulent year for the quantitative investment industry [1] - The Apex fund, with $6.8 billion in assets, reported a 3% return in December, driven primarily by stock selection strategies [1] - The Adaptive Equities Strategy, part of the market-neutral strategies, delivered a notable 24.4% return in 2025 [1] Company Performance - AQR Capital Management, co-founded by Cliff Asness and based in Greenwich, Connecticut, experienced significant asset growth in 2025, with total assets under management reaching $189 billion [1] - The asset increase in 2025 was a record high, amounting to $75 billion [1] - The company has been known for its academically supported strategies, such as equity factors, but has increasingly incorporated proprietary and machine learning technologies in recent years [1]

Group 1 - The core viewpoint of the articles highlights the significant impact of AI, particularly generative AI, on job displacement and the transformation of business models, with predictions of millions of jobs being automated by 2030 [1][2][12] - McKinsey's report indicates that by 2030, approximately 12 million jobs in the U.S. may need to be replaced due to AI automation, affecting 60%-70% of tasks, especially in white-collar jobs [1][2] - The World Economic Forum warns that AI could lead to the disappearance of 83 million jobs globally in the next five years, despite the emergence of 69 million new jobs, resulting in a net loss of 14 million jobs [1][2] Group 2 - Entrepreneurs whose businesses rely on repetitive tasks and standardized processes are most vulnerable to AI disruption, as AI excels in automating these functions [2][3][6] - Examples of vulnerable sectors include data entry outsourcing, simple customer service, and content creation that lacks originality and depth [3][4][5] - AI technologies, such as robotic process automation (RPA) and large language models (LLMs), can perform tasks like data recognition and content generation more efficiently than humans [4][5] Group 3 - Entrepreneurs providing "pseudo-demand" or "low-value" services are also at risk, as AI can eliminate inefficiencies and directly connect supply and demand, reducing the need for intermediaries [6][7] - The rise of AI-driven platforms can diminish the value of traditional middlemen, such as real estate agents and labor dispatchers, by automating information gathering and transaction facilitation [6][7] Group 4 - Despite the challenges posed by AI, there are opportunities for entrepreneurs who can leverage AI as a tool to create new business models and enhance efficiency [8][12] - Successful entrepreneurs will be those who integrate AI with industry expertise to develop innovative products or services, such as personalized education solutions or AI-assisted medical diagnostics [8][9] Group 5 - Entrepreneurs who excel in brand building, emotional connection, and community engagement are less likely to be replaced by AI, as these areas require human empathy and understanding [9][10] - The ability to foster trust and loyalty through genuine interactions and storytelling is a competitive advantage that AI cannot replicate [10][11] Group 6 - Complex interpersonal collaboration and emotional service roles, such as high-end medical care and psychological counseling, are also less susceptible to AI replacement due to their reliance on human judgment and emotional intelligence [11][12] - Entrepreneurs in these fields can thrive by providing personalized solutions and navigating uncertainties that AI cannot handle [11][12]

Core Viewpoint - The rise of AI, particularly generative AI, is significantly transforming the job market and entrepreneurial landscape, posing threats to certain types of businesses while also creating new opportunities for others [1][4][43]. Group 1: Impact of AI on Employment - According to McKinsey's 2023 report, by 2030, approximately 12 million people in the U.S. may need to change jobs due to AI automating 60%-70% of tasks, especially in white-collar jobs [2]. - The World Economic Forum warns that AI could lead to the disappearance of 83 million jobs globally in the next five years, despite the emergence of 69 million new jobs, resulting in a net loss of 14 million jobs [3]. Group 2: Vulnerable Entrepreneurial Segments - Entrepreneurs relying on repetitive labor are at high risk, as AI excels in standardizing and automating tasks such as data entry and document organization [8][9]. - Content creators lacking originality and deep insights are also vulnerable, as AI-generated content can easily surpass template-based or "rewritten" content [12][13]. - Businesses that cater to "pseudo-needs" or low-value services are threatened, as AI can streamline processes and eliminate inefficiencies, making these services redundant [17][18]. Group 3: Resilient Entrepreneurial Segments - Entrepreneurs who can integrate AI tools to create new business models are well-positioned for success, leveraging AI to enhance efficiency and decision-making [24][25]. - Those skilled in brand building and community engagement can thrive, as AI struggles to replicate human emotional connections and storytelling abilities [28][30]. - Businesses that require complex interpersonal interactions, such as high-end services and emotional support roles, are less likely to be replaced by AI due to the need for human empathy and adaptability [35][40].

Core Points - The first "Tianqiao Brain Science Institute and Science Magazine AI-Driven Science Award" winners have been announced, with a total cash prize of $50,000 awarded to three researchers [2][3] - The award aims to recognize innovative research that utilizes AI to empower scientific discoveries [2] Summary by Categories Award Winners - Dr. Zhuoran Qiao, founder scientist of Chai Discovery in San Francisco, won the grand prize of $30,000 for his research on protein folding using generative AI technology [2][3] - Two runners-up, Dr. Aditya Nair from Caltech and Stanford, and Dr. Alizée Roobaert from the Flanders Marine Institute, each received $10,000 for their respective AI solutions in neuroscience and ocean climate monitoring [2][3] Research Contributions - Dr. Qiao's work involves creating dynamic models that predict protein behavior over time and interactions with smaller molecules, providing new tools for drug discovery [2] - The runners-up focus on the integration of AI with neuroscience and innovative AI solutions for monitoring marine climate dynamics [2] Future Events - The award winners will present their research at the inaugural "Tianqiao Brain Science Institute AI-Driven Science Symposium" in San Francisco in October, alongside Nobel laureates and other leading scholars [3] - The application window for the 2025 AI-Driven Science Award will open in August [3]

Group 1 - The European Space Agency (ESA) and CERN have collaborated for 10 years, enhancing knowledge and facility sharing to maintain Europe's leadership in technological innovation [1] - The Euclid space telescope, launched in July 2023, aims to map dark matter and dark energy, expected to catalog around 8 billion galaxies by 2024 [1] - CERN provided critical technological support for the Euclid project, developing a ground science system to process raw data from the telescope [1][2] Group 2 - CERN and ESA have developed advanced technologies for Earth observation satellites, enabling environmental monitoring and weather forecasting [3] - The Edge SpAIce project, which includes CERN, aims to monitor ecosystems and track ocean plastic pollution using high-performance machine learning technology [3] Group 3 - The JUICE (Jupiter Icy Moons Explorer) mission, set to arrive at Jupiter in July 2031, will explore the planet and its moons, requiring advanced radiation protection technologies [4] - CERN has developed the VESPER testing facility to simulate Jupiter's extreme radiation environment for the JUICE mission [4] Group 4 - The LUMINA space radiation monitoring program, initiated by ESA astronaut Thomas Pesquet, uses specialized optical fibers to monitor radiation levels in the International Space Station [5] - The CELESTA satellite, launched in July 2022, focuses on studying cosmic radiation's effects on electronic devices [5] Group 5 - The collaboration between ESA and CERN supports the burgeoning space economy, facilitating the transformation of cutting-edge technologies into commercially viable space applications [6] - The Timepix technology, developed by CERN, has applications in medical imaging and radiation detection, showcasing its commercial potential [6] - Private companies like Advacam and SigmaLabs are leveraging Timepix technology for radiation monitoring systems and space radiation detectors, respectively [6][7]

Core Viewpoint - The article discusses the significance of early childhood caries (ECC) and highlights a recent study that developed a high-resolution microbial map to understand the microbial causes of caries at the single-tooth level, which can inform targeted prevention strategies [2][4][7]. Group 1 - ECC is a common issue that can lead to various health consequences, including pain, chewing difficulties, infections, and impacts on the development of permanent teeth and overall health [2]. - The study published in Cell Host & Microbe utilized machine learning to create a spatial microbial indicator (Spatial-MiC) that achieved 98% accuracy in diagnosing early caries and 93% accuracy in predicting future caries in seemingly healthy teeth [3][4]. Group 2 - The research analyzed 2,504 plaque microbiota samples from 89 preschool children over 11 months, revealing that healthy children's oral microbiota exhibited a gradient and symmetry, which was disrupted in children with caries [4]. - The findings indicate that specific microbial features related to individual teeth can guide targeted prevention strategies for ECC [4][7].