{"title":"Book review: <i>Crosswinds: Nehru, Zhou and the Anglo-American Competition over China</i> by Vijay Gokhale","authors":"Ravi Ranjan Kumar","doi":"10.1177/0920203x251318173a","DOIUrl":"https://doi.org/10.1177/0920203x251318173a","url":null,"abstract":"","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"39 1","pages":"128-129"},"PeriodicalIF":0.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://journals.sagepub.com/doi/pdf/10.1177/0920203X251318173a","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147908469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"基于网络药理学及体外实验探究中草药组方协同调节皮肤老化的作用机制","authors":"春波 冯","doi":"10.61369/cdcst.7983","DOIUrl":"https://doi.org/10.61369/cdcst.7983","url":null,"abstract":"人体皮肤结构和稳态平衡被破坏的主要原因有真皮层细胞外基质蛋白降解、DNA损伤和氧化应激等因素。本文采用有皮肤抗衰老性能报道的中草药(Traditional Chinese Medicine ,TCM),探索其不同组合的组方,包括人参、黄精、桂花、昙花和莲,基于网络药理学预测不同TCM组方的潜在功效靶点和抗衰老机制,比较了不同组方在皮肤中的生物活性组间区别,探究了不同组方中草药的抗衰老效果。通过体外实验多维度验证不同组方在相同浓度下的协同作用。结果显示,五味中草药组方比人参、黄精、昙花三味组方以及单味人参,具有在胶原蛋白促生、SA-&beta;-半乳糖苷酶降低、&gamma;H2AX诱导的DNA损伤降低等方面更强的抗皮肤衰老效果。","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"1 2","pages":"1-1"},"PeriodicalIF":0.0,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147886333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An STP look at logical blocking of finite state machines: formulation, detection, and search","authors":"Yongyi Yan, Penglei Hao, Jumei Yue, Haitao Li, Jun-E Feng","doi":"10.1007/s11432-022-4124-7","DOIUrl":"https://doi.org/10.1007/s11432-022-4124-7","url":null,"abstract":"<p>The logical blocking of finite state machines (FSMs) is examined at the three levels of formulation, detection, and search from an STP viewpoint (semi-tensor product of matrices). The research idea regards an FSM as a logical system. The realizing method treats the event sequence exciting an FSM as the input signal of a logical system and treats the current states of an FSM as the states of a logical system. Based on a recently developed bilinear dynamic model of FSMs, a difference equation-like model is first proposed to describe the logical blocking. By defining a loop structure of FSMs and using the difference equation-like model, a criterion is built by which whether a given FSM is blocking can be easily judged. If it is, several algorithms are designed to find all the logical blocking of the FSM. Further, these results are extended to apply to the case of nondeterministic FSMs and, thus, to networks of FSMs. The proposed STP approach may provide a new angle for considering the problems of FSMs, and the presented results may strengthen the links between systems governed by human-designed rules and systems governed by natural laws.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"192 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"State and parameter identification of linearized water wave equation via adjoint method","authors":"Yang Yu, Cheng-Zhong Xu, Hai-Long Pei, Jinpeng Yu","doi":"10.1007/s11432-023-4094-4","DOIUrl":"https://doi.org/10.1007/s11432-023-4094-4","url":null,"abstract":"<p>In this paper, we focus on the state and parameter identification problem of a hydrodynamical system. This system is modeled as a linearized water wave equation (LWWE), a hyperbolic state-space model coupled with a Laplace equation. We assume that the wave elevation at two distinct points is the only measurement of water waves. We show that the state and water depth can be reconstructed from this point measurement records. The identification problem is recast as an optimization problem over an infinite-dimensional space. We propose the adjoint method-based identification algorithm to generate an estimated state and water depth. We then performed a numerical simulation to show the effectiveness of our designed algorithm by comparing it with existing studies.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"3 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiang Luo, Chen Zhang, Chenbo Geng, Yanzhi Yi, Jiahui Hu, Renwei Zhang, Zhen Zhang, Gianpietro Consolaro, Fan Yang, Tun Lu, Ning Gu, Li Shang
{"title":"TSCompiler: efficient compilation framework for dynamic-shape models","authors":"Xiang Luo, Chen Zhang, Chenbo Geng, Yanzhi Yi, Jiahui Hu, Renwei Zhang, Zhen Zhang, Gianpietro Consolaro, Fan Yang, Tun Lu, Ning Gu, Li Shang","doi":"10.1007/s11432-024-4071-6","DOIUrl":"https://doi.org/10.1007/s11432-024-4071-6","url":null,"abstract":"<p>Today’s deep learning models face an increasing demand to handle dynamic shape tensors and computation whose shape information remains unknown at compile time and varies in a nearly infinite range at runtime. This shape dynamism brings tremendous challenges for existing compilation pipelines designed for static models which optimize tensor programs relying on exact shape values. This paper presents TSCompiler, an end-to-end compilation framework for dynamic shape models. TSCompiler first proposes a symbolic shape propagation algorithm to recover symbolic shape information at compile time to enable subsequent optimizations. TSCompiler then partitions the shape-annotated computation graph into multiple subgraphs and fine-tunes the backbone operators from the subgraph within a hardware-aligned search space to find a collection of high-performance schedules. TSCompiler can propagate the explored backbone schedule to other fusion groups within the same subgraph to generate a set of parameterized tensor programs for fused cases based on dependence analysis. At runtime, TSCompiler utilizes an occupancy-targeted cost model to select from pre-compiled tensor programs for varied tensor shapes. Extensive evaluations show that TSCompiler can achieve state-of-the-art speedups for dynamic shape models. For example, we can improve kernel efficiency by up to 3.97× on NVIDIA RTX3090, and 10.30 × on NVIDIA A100 and achieve up to five orders of magnitude speedups on end-to-end latency.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"39 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"NeurDB: an AI-powered autonomous data system","authors":"Beng Chin Ooi, Shaofeng Cai, Gang Chen, Yanyan Shen, Kian-Lee Tan, Yuncheng Wu, Xiaokui Xiao, Naili Xing, Cong Yue, Lingze Zeng, Meihui Zhang, Zhanhao Zhao","doi":"10.1007/s11432-024-4125-9","DOIUrl":"https://doi.org/10.1007/s11432-024-4125-9","url":null,"abstract":"<p>In the wake of rapid advancements in artificial intelligence (AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB (AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and self-driving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"6 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}