Core Insights - A research team led by researcher Han Wenbiao from the Shanghai Astronomical Observatory has discovered that binary black holes may not be "lonely wanderers," but could be influenced by a third dense celestial body during merger events, providing new clues to the formation of binary black holes [1][2] Group 1: Research Findings - The research results were published on August 1 in the international journal "Astrophysical Journal Letters" [1] - Since the first detection of gravitational waves in 2015, over 100 gravitational wave events have been detected, most of which originate from binary black hole mergers, offering critical data for understanding the physical processes involved [1] - The research team previously proposed a model where a supermassive black hole and a binary black hole form a "trio," with the binary black hole being influenced by the supermassive black hole's gravity, leading to a gradual decrease in their orbital distance and the emission of gravitational waves [1] Group 2: Specific Event Analysis - The team focused on the gravitational wave event GW190814, which features two black holes with a mass difference of nearly 10 times, suggesting they may have once formed a "trio" with a supermassive black hole [2] - The presence of a third dense body near the binary black holes could create a line-of-sight acceleration, altering the frequency of gravitational waves through the Doppler effect, leaving a unique "signature" in the signals [2] - The analysis of multiple high signal-to-noise ratio binary black hole events strongly supports the existence of line-of-sight acceleration in the GW190814 event, marking the first clear indication of a third dense body in a binary black hole merger [2]

Core Insights - The research team from the Victoria Museum in Australia has created a global distribution and evolutionary relationship map of the sea snake tail, revealing that marine life connections in the deep sea are more intricate than previously thought [1][2] - The study, published in the latest issue of Nature, indicates that the sea snake tail, an ancient polychaete that has existed for 480 million years, can be found from shallow waters to depths exceeding 3,500 meters [1] - The analysis of 2,699 specimens from 48 natural history museums, collected during 332 scientific expeditions, has uncovered the migration mysteries of this deep-sea animal [1] Research Findings - Sea snake tails, which lack fins and wings, can migrate across oceans via deep-sea currents, with their larvae's extended survival in cold water being crucial for this "free ride" [1] - The study provides a new perspective on marine evolution, suggesting that the deep sea is not an isolated environment but rather a "biological highway" with extensive connectivity [1] - Notably, temperate deep-sea communities exhibit remarkable global interconnections, such as the close evolutionary ties between species in southern Australian waters and their "distant relatives" in the North Atlantic [1] Environmental Implications - The research highlights that deep-sea ecosystems are not entirely homogeneous; while species are dispersing, environmental changes and geological events continue to shape unique biodiversity patterns [1] - The findings underscore the importance of protecting deep-sea life in the face of threats from deep-sea mining and climate change [1][2]

Group 1 - The National Healthcare Security Administration (NHSA) is promoting the application of artificial intelligence and big data in the healthcare insurance sector, transitioning from traditional methods to intelligent and precise fund supervision [1][2] - The healthcare insurance data encompasses 1.33 billion insured individuals, 50 million employers, 1.14 million hospitals and pharmacies, 17,900 medical supply companies, and 376,000 medical products, supporting an annual revenue and expenditure of approximately 3 trillion yuan and 10 billion medical service transactions [1] - The 2025 National Smart Healthcare Insurance Competition will adopt an open model without specific tracks, focusing on various fields such as healthcare, innovative drug development, financial insurance, and academic research [2] Group 2 - Participants in the competition will have access to real patient data regarding medical treatment, settlement, fund operation, and drug usage, which will enhance the feasibility and practicality of their proposals [2] - The competition marks the first attempt to integrate healthcare insurance data with data from other industries, facilitating interconnectivity and collaboration among healthcare institutions, research institutes, universities, and corporate R&D centers [2] - The Shanghai government will provide a secure and compliant local healthcare insurance data verification environment and computational resources for projects aiming for local implementation [3]

Core Insights - Harvard University researchers have developed a new optical device called "metasurface" that can perform complex quantum operations on a single plane, addressing scalability issues in photon quantum information processing [1][2] - The metasurface integrates multiple traditional optical component functions, potentially revolutionizing quantum computing and quantum communication at room temperature [1][2] Group 1: Metasurface Technology - The metasurface is a nanometer-thick optical element with micro-nano structures smaller than the wavelength of light, allowing precise control over light's phase and polarization [2] - This technology condenses complex quantum optical systems into a miniaturized platform, significantly enhancing system stability and interference resistance [2] Group 2: Design and Production - The research team utilized graph theory to model multi-photon interference paths, translating these abstract graphs into actual nanoscale structures on the metasurface [2] - This method closely links metasurface design with quantum optical states, providing a systematic approach for constructing specific quantum state devices [2] - The integrated design of the device greatly reduces optical loss, which is crucial for maintaining quantum information integrity [2] - The device can be mass-produced using existing semiconductor manufacturing processes, indicating potential for low-cost and replicable production models [2] Group 3: Broader Applications - The potential applications of this technology extend beyond quantum computing, with prospects for advancements in quantum sensing and fundamental research, offering new tools akin to "chip laboratories" [2]

Core Insights - Zhejiang University has launched a new generation of neuromorphic brain-like computer named "Wukong," which is the first in the world to exceed 2 billion neurons based on dedicated neuromorphic chips [1][2] - "Wukong" features over 2 billion spiking neurons and more than 100 billion synapses, closely resembling the scale of a macaque brain, with a typical operating power consumption of approximately 2000 watts [1] - The previous largest neuromorphic brain-like computer was Intel's Hala Point system, which had a neuron scale of 1.15 billion [1] Group 1 - "Wukong" is equipped with 960 self-developed Darwin 3rd generation brain-like computing chips, organized into 15 blade-type neuromorphic brain-like servers [1] - Each chip supports over 2.35 million spiking neurons and hundreds of millions of synapses, along with a dedicated instruction set for brain-like computing and an online learning mechanism [1][2] Group 2 - The research team has developed the Darwin brain-like operating system alongside "Wukong," which can run intelligent applications such as DeepSeek brain-like models for logical reasoning, content generation, and mathematical problem-solving [2] - "Wukong" offers a new computational paradigm with its large scale, high parallelism, and low power consumption, providing a computational foundation for artificial intelligence development and serving as a simulation tool for neuroscientists [2]

谷歌同时在arXiv预印本平台上传了一篇尚未经同行评审的论文。文中称，该模型在准确性和数据密度 方面均优于同类AI模型，同时能显著降低计算时间和能耗。 谷歌表示，谷歌"地球引擎"平台此前已托管了农业、森林砍伐、天气等主题的独立数据集，AlphaEarth 将这些数据集整合在一起，生成统一产品，便于科学家进行探索。 （文章来源：科技日报） 据英国《自然》网站7月31日消息，谷歌发布了一款"AlphaEarth"人工智能（AI）模型，其如同"虚拟卫 星"，能够整合海量的异构观测数据（包括卫星图像、雷达数据等），追踪地球陆地和浅海区域的变 化。该模型获得了科研人员高度评价，但他们也呼吁谷歌提供更多测试细节，并提醒相关研究人员，仍 需自行验证该工具生成的地图数据。 谷歌称，这款模型可在"任何地点、任何时间"进行地理绘图。卫星获取的只有颜色、云层等单一属性信 息，而AlphaEarth会将这些信息处理成名为"嵌入向量"的数字表示，从而能使研究人员轻松检索出树 种、建筑物、地下水等特征。研究人员可以利用该模型寻找清洁能源项目的最佳选址，研究气候变化对 生态系统的影响，监测森林砍伐等。处理后的数据被封装为一个个边长10米的 ...

伦德伯格展望，在不远的将来，医生或许能在患者的"数字孪生"上预演治疗方案，更快速、更经济、更 安全的个性化诊疗将成为现实。 细胞是孕育生命的微小单元。细胞内部及其与外部之间物质、能量和信号的传递与交换，构建出人类生 长、发育、衰老与疾病的生命图谱。解读细胞的奥秘，便是破译生命的密码。随着人工智能（AI）技 术的突飞猛进，一种全新的研究范式——AI虚拟细胞（AIVC）逐渐崭露头角。 AIVC就是利用AI模拟细胞行为，探索生命机制的过程。据英国《自然》网站报道，全球科研团队正掀 起一场AIVC研发浪潮，谷歌旗下"深度思维"等机构纷纷投身其中。这项技术有望重塑多个生物与医学 领域，从基因调控到药物开发，为探索生命机制、修复损伤、治疗疾病打开新的窗口。《细胞》杂志则 报道称，AIVC有可能彻底改变科学过程，助力科学家在生物医学研究、个性化医学、药物发现、细胞 工程和可编程生物学等方面取得重大突破。 最值得期待的科技突破之一 令人振奋的是，AIVC能让研究人员在计算机虚拟环境中替代传统的活体实验。斯坦福大学教授斯蒂芬· 奎克教授认为，未来的生物学研究可能90%依靠计算模拟，而非依赖实验室操作。虽然模拟精度仍取决 于数据 ...

铁是地球上开采量最大的金属，空气更是取之不尽的免费资源。铁空气电池堪称结合了自然界最经济的 两种元素。更值得一提的是，电池采用的水基电解质不仅成本低廉，还大幅降低了起火风险。 这些铁空气电池被安置在标准的12米集装箱内，1集装箱可储存数兆瓦时的电量。目前，美国马萨诸塞 州的Form能源公司也正在推进类似项目，计划率先在新英格兰及中西部地区部署该技术。 这款创新电池借助生锈和祛锈过程来储存和释放能量：利用电能将氧化铁（铁锈）还原为金属铁，实现 能量储存；金属铁与空气中的氧气反应重新生成铁锈，从而释放出储存能量。整个过程犹如赋予铁 器"呼吸"的能力，让生锈过程变得可逆可控。 目前的并网电池大都是磷酸铁锂电池，但其通常仅能维持4—6小时供电且成本高昂。铁空气电池展现出 显著优势：其储能时长突破100小时，制造材料均为廉价易得的常见物质。 据英国《新科学家》杂志网站7月31日报道，荷兰初创企业Ore Energy研发的铁空气电池可持续储能100 小时以上，已于近日成功接入荷兰代尔夫特理工大学电网系统，成为全球首个并网运行的铁空气电池。 这项技术突破不仅为可再生能源替代化石燃料提供了新路径，更有望显著提升电力系统的稳定 ...

Core Insights - The research team at Kunming University of Science and Technology has made significant breakthroughs in the intersection of "Artificial Intelligence + Materials" by proposing a "Continuous Transfer" machine learning framework, addressing the technical bottleneck of multi-performance prediction of materials with small datasets [1][2] - The framework allows for the efficient development of new functional materials, demonstrating the universality of transfer learning in optimizing multiple material properties [2] Group 1: Research Achievements - The team successfully constructed a "Continuous Transfer" learning strategy that first trains a high-precision base model using extensive formation energy data, followed by sequential predictions of key material properties such as stability, bandgap, and bulk modulus [1] - In a shear modulus prediction task with only 51 data points, the team utilized a bulk modulus model as a "stepping stone" for secondary transfer, significantly enhancing prediction reliability in small datasets [1] Group 2: Material Discovery - Using the framework, the research team rapidly screened over 18,000 candidate materials, identifying 54 inorganic double perovskite coating materials with high stability and excellent ductility [2] - Among these, cesium copper hexafluoroiridate exhibited outstanding performance, with a bandgap suitable for photovoltaic applications and a high ductility indicated by the ratio of shear modulus to bulk modulus [2] Group 3: Implications for the Industry - This research not only provides a candidate material library for fields such as perovskite solar cells and photocatalysis but also offers a scalable computational tool to address the challenges of data scarcity in material development [2] - The advancements in material informatics signify a crucial step in solving the "few data, many tasks" dilemma in material research, providing an efficient computational paradigm for multi-performance optimization [2]

Core Insights - The 27th Annual Conference of the China Association for Science and Technology (CAST) was held in Beijing from July 1 to 31, focusing on "Tracing Technological Frontiers to Support Innovative Development" [1] - The conference attracted over 7,000 participants, including more than 110 academicians, with 57% of attendees being young scientists under 40 years old [1] - A total of over 990 high-level academic reports were presented during the conference [1] Group 1 - One highlight of the conference was the deep involvement and leadership of young scientists in frontier discussions [2] - The conference fostered an atmosphere of equal communication, allowing young scholars to directly question academicians and experts, which is beneficial for breaking cognitive biases and enhancing problem understanding [4] - The design of forums encouraged embracing uncertainty in research and promoted non-consensus viewpoints, creating a more inclusive and open academic environment [4] Group 2 - Participants engaged in discussions on cutting-edge topics such as "Sim2Real challenges" and "multimodal perception fusion" in the "Embodied Intelligent Robots" forum, inspiring new research directions [3] - The "Key Technologies for Commercialization of Controlled Nuclear Fusion" forum attracted diverse participants from academia, industry, and technology sectors, facilitating in-depth discussions on uncertain topics related to nuclear fusion [4] - The conference emphasized the importance of fostering divergent thinking and academic innovation through collaborative discussions among participants of varying expertise and age [4]