Enhanced adic formalism and perverse t-structures for higher Artin stacks

In this sequel of arXiv:1211.5294 and arXiv:1211.5948, we develop an adic formalism for \'etale cohomology of Artin stacks and prove several desired properties including the base change theorem. In addition, we define perverse t-structures on Artin stacks for general perversity, extending Gabber's work on schemes. Our results generalize results of Laszlo and Olsson on adic formalism and middle perversity. We continue to work in the world of $\infty$-categories in the sense of Lurie, by enhancing all the derived categories, functors, and natural transformations to the level of $\infty$-categories.Comment: 53 pages. v2: reformulatio

クロレラ熱水抽出物中のフェネチルアミンの低用量での生物活性に関する研究

京都大学0048新制・課程博士博士(農学)甲第22849号農博第2432号新制||農||1082(附属図書館)学位論文||R2||N5309(農学部図書室)京都大学大学院農学研究科応用生物科学専攻(主査)教授 佐藤 健司, 教授 澤山 茂樹, 教授 菅原 達也学位規則第4条第1項該当Doctor of Agricultural ScienceKyoto UniversityDGA

The research of smart city construction on the well-being of urban residents-analysis based on CFPS data

With the rapid progress of China's economy, improving people's happiness has become one of the main goals of China's future social development. As a populous country, China has been lagging behind in the World Happiness Index Report released by the United Nations every year. Therefore, improving people's happiness has become one of the important social issues in China. Since the 16th National Congress, China has been urbanizing rapidly and the urbanization rate is planed to reach 70% by 2050. With the rapid development of urbanization, "urban diseases" caused by uneven development and demographic problems have become obstacles to urbanization development. To solve the problem, the construction of smart cities has become a new plan to ensure the rapid development of urbanization while solving the problem of "urban diseases". Investigating the relationship and mechanism of people' happiness between smart city construction and people's happiness can help clarify the fundamental needs of smart city construction, improve people's happiness, and have certain significance for the future development direction of smart city construction. The research of this paper centers on whether smart city construction can affect the happiness of the residents and investigates through what mechanism it can affect the happiness of the residents. This paper compares the relevant literature on smart city construction and happiness, takes data from the China Family Panel Studies (CFPS), the 2012 China Smart City Development Level Assessment Report, the 2014 China Smart City Development Level Assessment Report, and the 2016 China Smart City Development Level Assessment Report, and uses the econometric method of panel data analysis to empirically test the influence degree of smart city construction on residents' happiness. The experimental results show that (1) smart city construction has a significant impact on people's happiness, and the results are positively correlated. (2) The influence degree of smart city construction on people's happiness varies across different city levels, with no significant impact in first-tier cities and more significant impact in second-tier and third-tier cities. (3) Population heterogeneity can lead to some differences in residents' happiness feeling smart city construction

RC-SSFL: Towards Robust and Communication-efficient Semi-supervised Federated Learning System

Federated Learning (FL) is an emerging decentralized artificial intelligence paradigm, which promises to train a shared global model in high-quality while protecting user data privacy. However, the current systems rely heavily on a strong assumption: all clients have a wealth of ground truth labeled data, which may not be always feasible in the real life. In this paper, we present a practical Robust, and Communication-efficient Semi-supervised FL (RC-SSFL) system design that can enable the clients to jointly learn a high-quality model that is comparable to typical FL's performance. In this setting, we assume that the client has only unlabeled data and the server has a limited amount of labeled data. Besides, we consider malicious clients can launch poisoning attacks to harm the performance of the global model. To solve this issue, RC-SSFL employs a minimax optimization-based client selection strategy to select the clients who hold high-quality updates and uses geometric median aggregation to robustly aggregate model updates. Furthermore, RC-SSFL implements a novel symmetric quantization method to greatly improve communication efficiency. Extensive case studies on two real-world datasets demonstrate that RC-SSFL can maintain the performance comparable to typical FL in the presence of poisoning attacks and reduce communication overhead by $2 \times \sim 4 \times$