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Yolk free egg substitute improves the serum phospholipid profile of mice with metabolic syndrome based on lipidomic analysis

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Food Science and Human Wellness 2024年第1期13卷 482-493页

作者： Zhihui Yu Lingyu fan Fei Tai lixin Zhang Xiaoyu Zhang Yisheng Chen College of Food Science and Engineering Shanxi Agricultural UniversityTaigu 030801China Insitute of Food Nutrition and Safety Shanxi Agricultural UniversityTaiyuan 030031China Shanxi Key Laboratory of Edible Fungi for Loess Plateau Taigu 030801China

In this study,the impacts of egg consumption on mice model of metabolic syndrome(Met S)were comparatively investigated.Mice were divided into five groups(n=8):normal diet group(ND),high-fat diet group(HFD),HFD with whole egg group(WE),HFD with free-yolk egg substitute group(YFES),and HFD with lovastatin group(Lov).Main biochemical indexes and a non-targeted lipidomic analysis were employed to insight the lipid profile changes in serum.It was revealed that WE could significantly improve serum biochemical indexes by reducing body weight,low-density lipoprotein cholesterol(LDL-C)and total cholesterol(TC),while increasing high-density lipoprotein cholesterol.YFES exhibited remarkably better performance in increasing phosphatidylglycerol and phosphatidic acids,while decreasing phosphatidylinositol than WE.A total of 50 differential lipids biomarkers tightly related to glycerophospholipids metabolism were screened out.Carnitine C18:2 and C12:1,SM(d18:0/12:0),and SM(d18:1/14:1)were significantly upregulated in YFES compared to WE.YFES reduced expression of SREBP-1c and Cpt1a,while did not affect the expression of PPAR-α.Sphingomyelin biomarkers were positively related to the TC(|r|>0.6),while PPAR-αwas negatively correlated with triglyceride and LDL-C levels.To sum up,YFES attenuated HFD-induced Met S by improving the serum phospholipids,which account for its modulation of glycerophospholipid metabolism.

关键词： Metabolic syndrome Whole egg Yolk free egg substitute Serum Lipidomics

Mechanism of high Li-ion conductivity in poly(vinylene carbonate)-poly(ethylene oxide)cross-linked network based electrolyte revealed by solid-state NMR

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Journal of Energy Chemistry 2024年第6期93卷 377-383,I0010页

作者： fan Li Tiantian Dong Yi Ji lixin Liang Kuizhi Chen Huanrui Zhang Guanglei Cui Guangjin Hou State Key Laboratory of Catalysis Dalian National Laboratory for Clean EnergyCollaborative Innovation Center of Chemistry for Energy MaterialsDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023LiaoningChina University of Chinese Academy of Sciences Beijing 100049China Qingdao Industrial Energy Storage Research Institute Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of SciencesQingdao 266101ShandongChina

Solid polymer electrolytes(SPEs)have become increasingly important in advanced lithium-ion batteries(LIBs)due to their improved safety and mechanical properties compared to organic liquid electrolytes.Cross-linked polymers have the potential to further improve the mechanical property without trading off Li-ion conductivity.In this study,focusing on a recently developed cross-linked SPE,i.e.,the one based on poly(vinylene carbonate)-poly(ethylene oxide)cross-linked network(PVCN),we used solid-state nuclear magnetic resonance(NMR)techniques to investigate the fundamental interaction between the chain segments and Li ions,as well as the lithium-ion motion.By utilizing homonuclear/heteronuclear correlation,CP(cross-polarization)kinetics,and spin-lattice relaxation experiments,etc.,we revealed the structural characteristics and their relations to lithium-ion mobilities.It is found that the network formation prevents poly(ethylene oxide)chains from crystallization,which could create sufficient space for segmental tumbling and Li-ion co nductio n.As such,the mechanical property is greatly improved with even higher Li-ion mobilities compared to the poly(vinylene carbonate)or poly(ethylene oxide)based SPE analogues.

关键词： ssNMR Lithium-ion mobility Cross-link Solid polymer electrolyte

Framework and Key Technologies of Human-machine Hybrid-augmented Intelligence System for Large-scale Power Grid Dispatching and Control

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 1-12页

作者： Shixiong fan Jianbo Guo Shicong Ma lixin Li Guozheng Wang Haotian Xu Jin Yang Zening Zhao China Electric Power Research Institute Beijing 100192China the Beijing Huairou Laboratory Beijing 101400China School of Engineering the University of GlasgowGlasgow G128QQUK

With integration of large-scale renewable energy,new controllable devices,and required reinforcement of power grids,modern power systems have typical characteristics such as uncertainty,vulnerability and openness,which makes operation and control of power grids face severe security challenges.Application of artificial intelligence(AI)technologies represented by machine learning in power grid regulation is limited by reliability,interpretability and generalization ability of complex modeling.Mode of hybrid-augmented intelligence(HAI)based on human-machine collaboration(HMC)is a pivotal direction for future development of AI technology in this field.Based on characteristics of applications in power grid regulation,this paper discusses system architecture and key technologies of human-machine hybrid-augmented intelligence(HHI)system for large-scale power grid dispatching and control(PGDC).First,theory and application scenarios of HHI are introduced and analyzed;then physical and functional architectures of HHI system and human-machine collaborative regulation process are proposed.Key technologies are discussed to achieve a thorough integration of human/machine intelligence.Finally,state-of-theart and future development of HHI in power grid regulation are summarized,aiming to efficiently improve the intelligent level of power grid regulation in a human-machine interactive and collaborative way.

关键词： Artificial intelligence human-machine collaborative control human-machine hy brid intelligence optimization and evolution power grid dispatching and control

Privacy-preserving integration of multiple institutional data for single-cell type identification with scPrivacy

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Science China(Life Sciences) 2023年第5期66卷 1183-1195页

作者： Shaoqi Chen Bin Duan Chenyu Zhu Chen Tang Shuguang Wang Yicheng Gao Shaliu Fu lixin fan Qiang Yang Qi Liu Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration(Tongji University) Ministry of EducationOrthopaedic Department of Tongji HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200092China Department of AI WeBankShenzhen 518055China Translational Medical Center for Stem Cell Therapy and Institution for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200092China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai 201210China

The rapid accumulation of large-scale single-cell RNA-seq datasets from multiple institutions presents remarkable opportunities for automatically cell annotations through integrative analyses.However,the privacy issue has existed but being ignored,since we are limited to access and utilize all the reference datasets distributed in different institutions globally due to the prohibited data transmission across institutions by data regulation laws.To this end,we present scPrivacy,which is the first and generalized automatically single-cell type identification prototype to facilitate single cell annotations in a data privacy-preserving collaboration manner.We evaluated scPrivacy on a comprehensive set of publicly available benchmark datasets for single-cell type identification to stimulate the scenario that the reference datasets are rapidly generated and distributed in multiple institutions,while they are prohibited to be integrated directly or exposed to each other due to the data privacy regulations,demonstrating its effectiveness,time efficiency and robustness for privacy-preserving integration of multiple institutional datasets in single cell annotations.

关键词： preserving integration utilize

Federated Learning with Privacy-preserving and Model IP-right-protection

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Machine Intelligence Research 2023年第1期20卷 19-37页

作者： Qiang Yang Anbu Huang lixin fan Chee Seng Chan Jian Han Lim Kam Woh Ng Ding Sheng Ong Bowen Li WeBank Shenzhen 518057China Hong Kong University of Science and Technology Hong Kong 999077China University of Malaya Kuala Lumpur 50603Malaysia University of Surrey Guildford GU27XHUK University of Aberystwyth Wales SY233DDUK Shanghai Jiao Tong University Shanghai 200240China

In the past decades,artificial intelligence(AI)has achieved unprecedented success,where statistical models become the central entity in AI.However,the centralized training and inference paradigm for building and using these models is facing more and more privacy and legal challenges.To bridge the gap between data privacy and the need for data fusion,an emerging AI paradigm feder-ated learning(FL)has emerged as an approach for solving data silos and data privacy problems.Based on secure distributed AI,feder-ated learning emphasizes data security throughout the lifecycle,which includes the following steps:data preprocessing,training,evalu-ation,and deployments.FL keeps data security by using methods,such as secure multi-party computation(MPC),differential privacy,and hardware solutions,to build and use distributed multiple-party machine-learning systems and statistical models over different data sources.Besides data privacy concerns,we argue that the concept of“model”matters,when developing and deploying federated models,they are easy to expose to various kinds of risks including plagiarism,illegal copy,and misuse.To address these issues,we introduce FedIPR,a novel ownership verification scheme,by embedding watermarks into FL models to verify the ownership of FL models and protect model intellectual property rights(IPR or IP-right for short).While security is at the core of FL,there are still many articles re-ferred to distributed machine learning with no security guarantee as“federated learning”,which are not satisfied with the FL definition supposed to be.To this end,in this paper,we reiterate the concept of federated learning and propose secure federated learning(SFL),where the ultimate goal is to build trustworthy and safe AI with strong privacy-preserving and IP-right-preserving.We provide a com-prehensive overview of existing works,including threats,attacks,and defenses in each phase of SFL from the lifecycle perspective.

关键词： Federated learning privacy-preserving machine learning security decentralized learning intellectual property protection

Conservative Treatment of Fetal Goitrous Hypothyroidism Due to Thyroglobulin Mutations:A Case Report and Literature Review

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Maternal-Fetal Medicine 2023年第3期5卷 182-186页

作者： Shiping Liu Wei Bai Ying Gao Chunyan Shi lixin fan Junya Chen Jian Shi Weije Sun Xinlin Hou Huixia Yang Department of Obstetrics and Gynecology Peking University First HospitalBeijing 100034China Department of Pediatrics Peking University First HospitalBeijing 100034China Department of Endocrinology Peking University First HospitalBeijing 100034China Department of Ultrasound Peking University First HospitalBeijing 100034China

With the advances in fetal medicine,there will be more cases of congenital hypothyroidism(CH)diagnosed in the fetal period.However,there is no consensus on the management protocol.We present a successful case of conservatively managed fetal goitrous hypothyroidism due to compound heterozygous TG mutations.Goiter was observed in a fetus at 23 weeks of gestation.Because there was no evidence of transplacental passage of antithyroid antibody and drugs,iodine overload,and iodine deficiency,the fetus was highly suspected to have CH.Considering the potential risks of amniocentesis/cordocentesis,and lack of available parenteral levothyroxine in China,the fetus was closely monitored thereafter.A male neonate was delivered vaginally without complications at 39 weeks of gestation.We verified severe hypothyroidism in the infant and immediately initiated levothyroxine therapy.His growth and mental development were normal at the age of 8 month.Whole-exome sequencing showed that the neonate had two compound heterozygous mutations in the TG gene.We also performed a literature review of the prognosis of postnatal treatment of CH due to TG mutations and the result showed that postnatal treatment of CH due to TG mutations has a favorable prognosis.However,further prospective studies are warranted to verify this conclusion.

关键词： Thyroglobulin Gene mutations Fetal hypothyroidism

基于改进自适应陷波的双馈风电场时变次同步振荡抑制策略

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中国电机工程学报 2024年第5期44卷 1836-1847,I0014页

作者：吴熙徐珊珊冯双范立新顾文东南大学电气工程学院江苏省南京市210096 江苏省智能电网技术与装备重点实验室(东南大学) 江苏省南京市210096 江苏方天电力技术有限公司江苏省南京市211102

双馈风电场经串补电容并网时,可能引发次同步控制相互作用(subsynchronous control interaction,SSCI),严重威胁系统安全稳定运行。通过在风机控制器中引入陷波器可有效阻断SSCI,然而固定参数陷波器难以适应实际系统中次同步振荡表现出... 详细信息

双馈风电场经串补电容并网时,可能引发次同步控制相互作用(subsynchronous control interaction,SSCI),严重威胁系统安全稳定运行。通过在风机控制器中引入陷波器可有效阻断SSCI,然而固定参数陷波器难以适应实际系统中次同步振荡表现出的频率大范围时变特征。为解决这一问题,该文提出一种基于改进自适应陷波(adaptive notch filter,ANF)的双馈风电场时变次同步振荡抑制策略。首先,分析ANF安装于风机转子侧变流器(rotor-side converter,RSC)不同位置时对次同步振荡分量的阻断效果,确定ANF的最佳安装位置;其次,基于紧缩技术近似投影子空间跟踪算法(projection approximation subspace tracking based on the deflation technique,PASTd)在线获取次同步振荡信息,提出总体控制架构,设计基于量测数据辨识的ANF中心频率更新策略;最终,在考虑风速、风机台数、无功出力、电网拓扑变化等多种影响因素的情况下,验证控制策略对频率时变次同步振荡的抑制效果。与现有方法相比,所提控制策略不依赖于系统的准确数学模型,且具备较强的鲁棒性和适应性。

关键词：双馈风机次同步振荡转子侧变流器安装位置自适应陷波器

CR200J型动力集中动车组气路控制箱结冰问题分析及改进

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铁道车辆 2024年第1期62卷 176-181页

作者：樊立新中国铁路乌鲁木齐局集团有限公司乌鲁木齐车辆段新疆乌鲁木齐830011

为满足广大乘客在舒适性、经济性、安全性等方面的需求,中国铁路乌鲁木齐局集团有限公司配属了时速160 km“复兴号”CR200J型动力集中动车组。冬季动力集中动车组途经高寒、暴雪、大湿度的运行区段,沿线历年极端低温为-40~-30℃,北疆的... 详细信息

为满足广大乘客在舒适性、经济性、安全性等方面的需求,中国铁路乌鲁木齐局集团有限公司配属了时速160 km“复兴号”CR200J型动力集中动车组。冬季动力集中动车组途经高寒、暴雪、大湿度的运行区段,沿线历年极端低温为-40~-30℃,北疆的精伊霍线、奎北线相对湿度为50%~80%;出现了多起动力集中动车组拖车气路控制箱结冰的问题,造成了塞拉门、集便器、空气弹簧无风等严重故障。文章从动力集中动车组运用环境、干燥器控制逻辑、供风管路、运用维修等方面进行分析,得出了冬季北疆运行线路低温、大湿度是气路控制箱结冰的外部原因,干燥器启停与空压机打风不同步、拖车供风管点取在总风缸Ⅰ之前是气路控制箱结冰的内部原因。通过优化干燥器控制逻辑、优化供风管路、调整运行交路、优化冬季排水作业、增加干燥器检查等改进措施,后续未发生气路控制箱结冰造成塞拉门、集便器、空气弹簧无风的故障,提高了乘客乘坐安全性和舒适性,确保了动力集中动车组的运营安全。

关键词：新疆动力集中动车组气路控制箱管路冻结

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语义数据标注的轻量化轨道扣件故障检测方法

振动．测试与诊断 2024年第1期44卷 52-59,196页

作者：姚德臣王琰亮杨建伟徐立新张帆北京建筑大学机电与车辆工程学院北京100044 北京建筑大学城市轨道交通车辆服役性能保障北京市重点实验室北京100044 东平湖管理局供水局陈垓闸管理所泰安271599

针对常规深度学习网络规模大、对现场设备硬件要求高且人工标注位置数据复杂费时等问题,提出了一种语义数据标注的轻量化轨道扣件故障检测方法。该方法仅对训练数据做语义标注,改进轻量化Transformer模型,嵌入梯度加权类激活映射(gradie... 详细信息

针对常规深度学习网络规模大、对现场设备硬件要求高且人工标注位置数据复杂费时等问题,提出了一种语义数据标注的轻量化轨道扣件故障检测方法。该方法仅对训练数据做语义标注,改进轻量化Transformer模型,嵌入梯度加权类激活映射(gradient-weighted class activation mapping,简称Grad-CAM)模块对模型输出的特征图权重作映射处理,可将模型对轨道扣件检测效果可视化。将获得的激活图进行二值化定位检测目标位置,实验结果表明,在真实铁路环境下,改进的轻量化轨道扣件模型的准确率为94.31%。

关键词：轨道扣件智能故障诊断深度学习轻量化网络