A blockchain-based audit approach for encrypted data in federated learning

The development of data-driven artificial intelligence technology has given birth to a variety of big data applications. Data has become an essential factor to improve these applications. Federated learning, a privacy-preserving machine learning method, is proposed to leverage data from different data owners. It is typically used in conjunction with cryptographic methods, in which data owners train the global model by sharing encrypted model updates. However, data encryption makes it difficult to identify the quality of these model updates. Malicious data owners may launch attacks such as data poisoning and free-riding. To defend against such attacks, it is necessary to find an approach to audit encrypted model updates. In this paper, we propose a blockchain-based audit approach for encrypted gradients. It uses a behavior chain to record the encrypted gradients from data owners, and an audit chain to evaluate the gradients’ quality. Specifically, we propose a privacy-preserving homomorphic noise mechanism in which the noise of each gradient sums to zero after aggregation, ensuring the availability of aggregated gradient. In addition, we design a joint audit algorithm that can locate malicious data owners without decrypting individual gradients. Through security analysis and experimental evaluation, we demonstrate that our approach can defend against malicious gradient attacks in federated learning.     

四氢姜黄素经PI3K/Akt信号通路对人血小板活化和聚集的调控作用

目的：探讨姜黄素的主要肠道代谢物四氢姜黄素（tetrahydrocurcumin，THC）对血小板活化和聚集的影响及其可能的分子机制。方法：在体外实验中，用不同浓度的THC（0、0.5、1、10 μmol/L）提前与健康人纯化血小板共同孵育40 min，然后加入凝血酶激活血小板2 min，用流式细胞术测定血小板表面CD62P和CD63的表达量，用酶联免疫吸附法测定血小板释放血小板因子-4（platelet factor-4，PF4）和趋化因子配体-5（chemokine ligand 5，CCL5）水平，用血小板聚集仪检测血小板释放ATP水平和血小板最大聚集率，用Western blot蛋白免疫印迹法检测血小板磷酸肌醇-3-激酶（phosphoinositide 3-kinase，PI3K）和Akt蛋白的磷酸化水平。结果：与模型组（血小板悬液中加入0.05%二甲基亚砜）相比，THC能抑制凝血酶诱导的血小板表面CD62P和CD63的表达，抑制PF4、CCL5和ATP的释放，降低血小板最大聚集率，下调PI3K和Akt蛋白的磷酸化水平，且呈浓度依赖效应，其中10 μmol/L的浓度下作用效果显著（P＜0.01、P＜0.001）。PI3K的特异性激动剂740 Y-P可部分逆转THC对PF4和CCL5释放和血小板聚集的抑制作用（P＜0.05、P＜0.01）。结论：THC具有显著抑制血小板活化和聚集的作用，其机制可能是THC可下调PI3K/Akt介导的信号通路。     

AQP3 Increases Intercellular Cohesion in NSCLC A549 Cell Spheroids through Exploratory Cell Protrusions

Tumor cell aggregation is critical for cell survival following the loss of extracellular matrix attachment and dissemination. However, the underlying mechanotransduction of clustering solitary tumor cells is poorly understood, especially in non-small cell lung cancers (NSCLC). Here, we examined whether cell surface protrusions played an important role in facilitating the physical contact between floating cells detached from a substrate. We employed poly-2-hydroxyethyl methacrylate-based 3D culture methods to mimic in vivo tumor cell cluster formation. The suprastructural analysis of human NSCLC A549 cell spheroids showed that finger-like protrusions clung together via the actin cytoskeleton. Time-lapse holotomography demonstrated that the finger-like protrusions of free-floating cells in 3D culture displayed exploratory coalescence. Global gene expression analysis demonstrated that the genes in the organic hydroxyl transport were particularly enriched in the A549 cell spheroids. Particularly, the knockdown of the water channel aquaporin 3 gene (AQP3) impaired multicellular aggregate formation in 3D culture through the rearrangement of the actomyosin cytoskeleton. Moreover, the cells with reduced levels of AQP3 decreased their transmigration. Overall, these data indicate that cell detachment-upregulated AQP3 contributes to cell surface protrusions through actomyosin cytoskeleton remodeling, causing the aggressive aggregation of free-floating cells dependent on the property of the substratum and collective metastasis.     

电商平台产品共同购买网络的影响因素研究

共同购买网络的推荐系统应用越加广泛，仅基于网络内生结构变量研究其共同购买链接的经济意义已有局限，故加入网络口碑这一外生变量，进行更全面的分析。采用了社会网络方法中指数随机图模型进行建模，主要围绕产品销售量、产品入度、差评率和评论数4个方面因素，探究其对共同购买网络中共同购买链接形成的影响。结果显示，销售量、产品入度和评论数对共同购买链接形成的影响呈正比关系，而差评率则会显著地降低产品共同购买的几率。该指数随机图构建出的共同购买网络为在线电商平台管理网络口碑和推荐系统优化设计提供有益参考。     

Luminescent Solar Concentrators Based on Aggregation Induced Emission

A promising path to cost-effective photovoltaic (PV) systems is sunlight concentration. Over classical non-imaging geometrical concentrators, luminescent solar concentrators (LSCs) possess several advantages: low cost and weight, elevated theoretical concentration factors and aptitude to efficiently working with diffuse light without tracking or cooling equipment. Although considerable progress has been made, current LSC-PV systems attain low power conversion efficiencies due to critical processes that hinder their ability to deliver light to PV cells including fluorescence quenching due to dye aggregation. To overcome this issue, fluorophores with aggregation induced emission (AIEgens) have been proposed thanks to their high Stokes shift and quantum yield in the solid state. In this review, the current state of knowledge concerning the preparation of LSCs based on AIEgens is summarized with special reference on the strategy adopted aimed at increasing the absorption bandwidth while maximizing the solar collection.     

机翼极限环颤振的CFD/CSD全隐式紧耦合方法

针对轴承振动实时状态监控的需要，从符号动力学角度提出了符号聚合近似与Lempel-ziv复杂度（SAX-LZC）融合的振动监控参数。首先，以Logistic映射和Duffing方程为对象，从理论角度验证了SAX-LZC对动力学结构表征的准确性，并验证了该指标的抗噪能力和计算效率；其次，将SAX-LZC指标与信息熵、样本熵、多分段Lempel-ziv复杂度等动力学参数性能进行了综合对比；最后，从实验角度对轴承早期微弱异常进行了监测，并对轴承典型故障进行了特征提取。理论研究结果表明，SAX-LZC具有动力学结构表征准确、抗噪能力好、计算高效简洁等优点，克服了常规动力学参数工程应用能力弱的问题。实验研究结果表明，SAX-LZC对早期微弱异常有准确的监测，对不同种类故障具有较好的区分度，弥补了时域和频域对轴承微弱故障表征能力不足的缺陷，是一种轴承振动实时状态监控与故障特征提取的有效参数。     

“电网一张图”时空信息管理系统

文章首先总结了电力企业信息管理系统的现状,提出了多源信息管理系统融合集成的邦联、子集和完全融合3种方式,分析了3种方式的优缺点,以建设企业"互联网搜索"型数字引擎为目标,提出了融合基于本体的图数据库建模,多维关联与路径因果分析,和人机共生互动可视化决策于一体的企业信息管理系统技术发展趋势;在系统分析目前正在快速发展的图数据库技术与传统关系数据库之间的本质区别基础上,总结原创的电力图计算平台技术的特点;在此基础上讨论"电网一张图"在建设能源互联网时空信息管理平台数据关联索引图中的核心作用,提出了支持能源互联网建设的"电网一张图"时空信息管理系统的技术架构与特点,最后总结"电网一张图"时空信息管理系统在提高电网安全运行水平、提升客户服务水平、增强清洁能源消纳水平、改善经营绩效水平、以及为综合能源服务和建设能源生态等提供数据服务方面的广阔应用场景。     

Emergency decision support modeling for COVID-19 based on spherical fuzzy information

Significant emergency measures should be taken until an emergency event occurs. It is understood that the emergency is characterized by limited time and information, harmfulness and uncertainty, and decision-makers are always critically bound by uncertainty and risk. This paper introduces many novel approaches to addressing the emergency situation of COVID-19 under spherical fuzzy environment. Fundamentally, the paper includes six main sections to achieve appropriate and accurate measures to address the situation of emergency decision-making. As the spherical fuzzy set (FS) is a generalized framework of fuzzy structure to handle more uncertainty and ambiguity in decision-making problems (DMPs). First, we discuss basic algebraic operational laws (AOLs) under spherical FS. In addition, elaborate on the deficiency of existing AOLs and present three cases to address the validity of the proposed novel AOLs under spherical fuzzy settings. Second, we present a list of Einstein aggregation operators (AgOp) based on the Einstein norm to aggregate uncertain information in DMPs. Thirdly, we are introducing two techniques to demonstrate the unknown weight of the criteria. Fourthly, we develop extended TOPSIS and Gray relational analysis approaches based on AgOp with unknown weight information of the criteria. In fifth, we design three algorithms to address the uncertainty and ambiguity information in emergency DMPs. Finally, the numerical case study of the novel carnivorous (COVID-19) situation is provided as an application for emergency decision-making based on the proposed three algorithms. Results explore the effectiveness of our proposed methodologies and provide accurate emergency measures to address the global uncertainty of COVID-19.     

Distributed allocation and dynamic reassignment of channels in UAV networks for wireless coverage

Providing wireless coverage to users using Unmanned Aerial Vehicles (UAVs) encounters two major challenges: deployment and channel allocation. To this end, solutions to both issues are proposed in this paper. An overloaded UAV attempts to acquire more channels by performing channel bonding/aggregation followed by requesting its chosen peers to move closer for load sharing. The proposed channel reallocation schemes minimize interference caused by channel reassignments, or change in network topology. The simulation results show that when employing these schemes, more data is served with reduced discontinuous service time and efficient usage of limited battery power.     

基于k-shell的复杂网络最短路径近似算法

复杂网络最短路径经典算法的处理效率较低，不适用于大规模复杂网络，而现有近似算法通用性有限，且计算准确率不理想，不能满足规模日益扩大的复杂网络中的最短路径计算需求。针对于此，提出基于[k]-shell的复杂网络最短路径近似算法。算法利用节点的[k]-shell值进行网络划分并引导搜索路径，利用超点聚合处理[k]-shell子网来降低路径搜索中节点和连边的规模，通过在路径搜索过程使用双向搜索树方法提高算法的计算效率和准确率。实验结果表明，算法通用性较好，在现实与仿真大规模复杂网络中均具有较高的计算效率和准确率。