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One-Pot Process to Carborano-Coumarin via Catalytic Cascade Dehydrogenative Cross-Coupling

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Chinese Journal of Chemistry 2020年第4期38卷 383-388页

作者： Yik Ki Au hairong lyu Yangjian Quan Zuowei Xie Deportment of Chemistry and State Key Laboratory of Synthetic Chemistry The Chinese University of Hong KongShatinN.T.Hong KongChina

Summary of main observation and conclusion Ir-catalyzed cascade dehydrogenative CH/BH and BH/OH cross-coupling of carboranyl carboxylic acid with readily available benzolc acid has been achieved,leading to the facile synthesis of previously unavailable carborano-coumarin in a simple one-pot process.Two cage B-H,one aryl C--H and one 0-H bonds are activated to construct eficiently new B-C and B-0 bonds.The cascade cyclization can stop at the first B-H/C-H cross-coupling step by tuning the reaction conditions,resulting in a series of a-carboranyl benzoic acid and aryl carborane derivatives.Control experiments indicate that B-H/C-H dehydrocoupling proceeds preferentially over B-H/O-H dehydrocoupling,and both directing groups and oxidants are crucial for this reaction.An iridium(V)intermediate is proposed to be involved in the catalytic cycle.

关键词： reaction. process. coupling

基于自然语言处理与结构化算法的病历信息高精度抽取方法研究

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中国数字医学 2024年第5期19卷 40-48页

作者：王维笑费晓璐闾海荣魏岚陶焜赵明付旭赵许盼高菲任怡清华大学自动化系北京100084 首都医科大学宣武医院信息科首都医科大学宣武医院神经内科北京爱医声科技有限公司

目的:综合运用自然语言处理、结构化算法和知识图谱等技术,探索实现电子病历高精度信息抽取和结构化处理的方法。方法:通过构建命名实体识别模型、关系识别模型、同义词识别模型完成病历文本的句内信息抽取;提出了一种病历生成树算法,... 详细信息

目的:综合运用自然语言处理、结构化算法和知识图谱等技术,探索实现电子病历高精度信息抽取和结构化处理的方法。方法:通过构建命名实体识别模型、关系识别模型、同义词识别模型完成病历文本的句内信息抽取;提出了一种病历生成树算法,可以有效实现大段落病历文本分层结构的解析;同时利用知识图谱技术存储信息抽取与分层解析的构造模型,实现病历文本信息高精度抽取。结果:形成了一套融合深度学习算法与结构化解析算法的病历信息高精度抽取方法,其中实体识别模型准确率达95.74%,关系识别模型准确率达89.20%,最终生成具有清晰层次结构、可精确定位和抽取信息的结构化病历。结论:本文所探索的病历信息高精度抽取方法,将深度学习算法与结构化解析算法相融合,兼顾了病历文本的句内信息抽取与病历结构层次的解析,可以实现对病历数据的自动抽取、精准定位与高效管理,可以为临床医学研究奠定数据基础,也可以为其他疾病病历文本数据的挖掘提供方法学参考。

关键词：电子病历信息抽取自然语言处理知识图谱结构化解析

Recommendation Method for Contrastive Enhancement of Neighborhood Information

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Computers, Materials & Continua 2024年第1期78卷 453-472页

作者： hairong Wang Beijing Zhou Lisi Zhang He Ma School of Computer Science and Engineering North Minzu UniversityNingxia750021China

Knowledge graph can assist in improving recommendation performance and is widely applied in various person-alized recommendation domains.However,existing knowledge-aware recommendation methods face challenges such as weak user-item interaction supervisory signals and noise in the knowledge graph.To tackle these issues,this paper proposes a neighbor information contrast-enhanced recommendation method by adding subtle noise to construct contrast views and employing contrastive learning to strengthen supervisory signals and reduce knowledge noise.Specifically,first,this paper adopts heterogeneous propagation and knowledge-aware attention networks to obtain multi-order neighbor embedding of users and items,mining the high-order neighbor informa-tion of users and items.Next,in the neighbor information,this paper introduces weak noise following a uniform distribution to construct neighbor contrast views,effectively reducing the time overhead of view construction.This paper then performs contrastive learning between neighbor views to promote the uniformity of view information,adjusting the neighbor structure,and achieving the goal of reducing the knowledge noise in the knowledge graph.Finally,this paper introduces multi-task learning to mitigate the problem of weak supervisory signals.To validate the effectiveness of our method,experiments are conducted on theMovieLens-1M,MovieLens-20M,Book-Crossing,and Last-FM datasets.The results showthat compared to the best baselines,our method shows significant improvements in AUC and F1.

关键词： Contrastive learning knowledge graph recommendation method

Impacts of electrochemical disinfection on the viability and structure of the microbiome in secondary effluent water

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Frontiers of Environmental Science & Engineering 2024年第5期18卷 73-83页

作者： Marvin Yeung Lan Tian Yuhong Liu hairong Wang Jinying Xi Environmental Simulation and Pollution Control State Key Joint Laboratory School of EnvironmentTsinghua UniversityBeijing100084China Graduate School at Shenzhen Tsinghua UniversityShenzhen518055China

Electrochemical disinfection(ECD)is a promising disinfection technique for wastewater reclamation;however,the impacts of ECD on the microbiome in secondary effluent wastewater remain unknown.In this study,Propidium monoazide-qPCR(PMA-qPCR)and the plate count method were used to evaluate the inactivation performance,and the PMA-16S rRNA gene sequences of living cells were targeted to study the microbiome.A discrepancy was found between PMA-qPCR and the plate count method in the evaluation of cell count,with increases of 1.5 to 2.2 orders of magnitude in the disinfection rate after 150 s of disinfection.However,the cell count recovered and occasionally exceeded original levels within 3 d after disinfection.Biodiversity was suppressed after ECD,but the microbiome after 150 s disinfection retained a higher level of evenness and stability in the community with a median Shannon index(>3.7).Pathogenic bacteria remained high in relative abundance even after 150 s of 25 V disinfection,but the biofilm-forming population was effectively suppressed by ECD.The co-occurrence network revealed a centralized and fragile network as disinfection persisted,demonstrating the destabilizing effects of ECD on the microbiome.Functional pathways for cell membrane synthesis and organic compound degradation were enriched after ECD.The reaction of the microbiome after ECD was similar to other disinfection techniques in terms of community structure.

关键词： Electrochemical disinfection Secondary effluent Microbiome

Data and Model Driven Task Offloading Strategy in the Dynamic Mobile Edge Computing System

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Journal of Systems Science & Complexity 2024年第1期37卷 351-368页

作者： DONG hairong WU Wei SONG Haifeng LIU Zhen ZHANG Zixuan School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Electronic and Information Engineering BeiHang UniversityBeijing 100191China CRSC Research&Design Institute Group Co. Ltd.Beijing 100070China

Mobile Edge Computing(MEC)provides communication and computational capabilities for the industrial Internet,meeting the demands of latency-sensitive tasks.Nevertheless,traditional model-driven task offloading strategies face challenges in adapting to situations with unknown network communication status and computational capabilities.This limitation becomes notably significant in complex industrial networks of high-speed railway.Motivated by these considerations,a data and model-driven task offloading problem is proposed in this paper.A redundant communication network is designed to adapt to anomalous channel states when tasks are offloaded to edge servers.The link switching mechanism is executed by the train according to the attributes of the completed task.The task offloading optimization problem is formulated by introducing data-driven prediction of communication states into the traditional model.Furthermore,the optimal strategy is achieved by employing the informer-based prediction algorithm and the quantum particle swarm optimization method,which effectively tackle real-time optimization problems due to their low time complexity.The simulations illustrate that the data and model-driven task offloading strategy can predict the communication state in advance,thus reducing the cost of the system and improving its robustness.

关键词： Data driven model informer mobile edge computing quantum particle swarm optimization task offloading.

Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury:predictors of patient prognosis

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Neural Regeneration Research 2024年第7期19卷 1553-1558页

作者： Sihong Huang Jungong Han hairong Zheng Mengjun Li Chuxin Huang Xiaoyan Kui Jun Liu Department of Radiology The Second Xiangya HospitalCentral South UniversityChangshaHunan ProvinceChina Department of Computer Science Aberystwyth UniversityAberystwythCeredigionUK Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhenGuangdong ProvinceChina School of Computer Science and Engineering Central South UniversityChangshaHunan ProvinceChina Department of Radiology Quality Control Center of Hunan ProvinceChangshaHunan ProvinceChina Clinical Research Center for Medical Imaging of Hunan Province ChangshaHunan ProvinceChina

Patients with mild traumatic brain injury have a diverse clinical presentation,and the underlying pathophysiology remains poorly understood.Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neuro biological markers after mild traumatic brain injury.This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury.G raph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function.However,most previous mild traumatic brain injury studies using graph theory have focused on specific populations,with limited exploration of simultaneous abnormalities in structural and functional connectivity.Given that mild traumatic brain injury is the most common type of traumatic brain injury encounte red in clinical practice,further investigation of the patient characteristics and evolution of structural and functional connectivity is critical.In the present study,we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury.In this longitudinal study,we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 wee ks of injury,as well as 36 healthy controls.Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis.In the acute phase,patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network.More than 3 months of followup data revealed signs of recovery in structural and functional connectivity,as well as cognitive function,in 22 out of the 46 patients.Furthermore,better cognitive function was associated with more efficient networks.Finally,our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal ch

关键词： cognitive function cross-section follow-up functional connectivity graph theory longitudinal study mild traumatic brain injury prediction small-worldness structural connectivity subnetworks whole brain network

Unraveling the Fundamental Mechanism of Interface Conductive Network Influence on the Fast‑Charging Performance of SiO‑Based Anode for Lithium‑Ion Batteries

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Nano-Micro Letters 2024年第3期16卷 53-68页

作者： Ruirui Zhang Zhexi Xiao Zhenkang Lin Xinghao Yan Ziying He hairong Jiang Zhou Yang Xilai Jia Fei Wei Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical EngineeringTsinghua UniversityBeijing 100084People’s Republic of China School of Materials Science and Engineering University of Science and Technology BeijingBeijing 100083People’s Republic of China Beijing Key Laboratory of Chemical Power Source and Green Catalysis School of Chemistry and Chemical EngineeringBeijing Institute of TechnologyBeijing 100081People’s Republic of China Institute of Polymer Science and Engineering Department of Chemical EngineeringTsinghua UniversityBeijing 100084People’s Republic of China

Progress in the fast charging of high-capacity silicon monoxide(SiO)-based anode is currently hindered by insufficient conductivity and notable volume expansion.The construction of an interface conductive network effectively addresses the aforementioned problems;however,the impact of its quality on lithium-ion transfer and structure durability is yet to be explored.Herein,the influence of an interface conductive network on ionic transport and mechanical stability under fast charging is explored for the first time.2D modeling simulation and Cryo-transmission electron microscopy precisely reveal the mitigation of interface polarization owing to a higher fraction of conductive inorganic species formation in bilayer solid electrolyte interphase is mainly responsible for a linear decrease in ionic diffusion energy barrier.Furthermore,atomic force microscopy and Raman shift exhibit substantial stress dissipation generated by a complete conductive network,which is critical to the linear reduction of electrode residual stress.This study provides insights into the rational design of optimized interface SiO-based anodes with reinforced fast-charging performance.

关键词： Fast charging SiO anode Interface conductive network Ionic transport Mechanical stability

Novel self-assembled porous yolk-shell NiO nanospheres with excellent electrochromic performance for smart windows

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Particuology 2024年第1期84卷 72-80页

作者： Baoshun Wang Ya Huang Siming Zhao Run Li Di Gao hairong Jiang Rufan Zhang Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical EngineeringTsinghua UniversityBeijing100084China

With the rapid development of optoelectronics,electrochromic(EC)materials(ECMs)with the advan-tages of low power consumption,easy viewing,high contrast ratio,etc have attached more and more attention from the fields of smart windows,electronic billboards,emerging wearable and portable electronics,and other next-generation displays.Nickel oxide(NiO)is a promising candidate for high-performance ECMs because of its neutral-colored states and low cost.However,NiO-based ECMs still face the problem of slow switching speed due to their low electrical conductivity and small lattice spacing.Metal-organic frameworks(MOFs)are promising candidates to fabricate hollow and porous transition metal oxides(TMOs)with high ion transport efficiency,excellent specific capacitance,and electrochemical activities.In this work,porous yolk-shell NiO nanospheres(PYS-NiO NSs)were syn-thesized via a solvothermal and subsequent calcination process of Ni-MOF,which exhibited outstanding EC performance.Because the large specific surface areas and hollow porous nanostructures were conducive to ionic transport,PYS-NiO NSs exhibited a fast coloring/bleaching speed(3.6/3.9 s per one coloring/bleaching cycle)and excellent cycling stability(82%of capacity retention after 3000 cycles).These superior EC properties indicated that the PYS-NiO NSs was a promising candidate for high-performance EC devices.This work provides a new and feasible strategy for the efficient preparation of TMOs ECMs with good EC performance,especially fast switching speed.

关键词： Electrochromic Nickel oxide Metal-organic frameworks Hollow structure Smart windows

Influence of pore structure on thermal stress distribution inside coal particles during primary fragmentation

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Particuology 2024年第2期85卷 49-61页

作者： Kai Qiao Shan Zhong Siyang Tang Ke Yang hairong Yue Kui Ma Lei Song Bin Liang School of Chemical Engineering Sichuan UniversityChengdu610065China Institute of New Energy and Low-carbon Technology Chengdu610207China

Thermal stress is an important reason of coal particle primary fragmentation,during which the role of pore structure is ambiguous.Thermal stress induced fragmentation experiments were conducted with low volatile coal/char particles,and the results show that the fragmentation severity enhances with increasing porosity.Various porous thermal stress models were developed with finite element method,and the influences of the pore shape,size,position and porosity on the thermal stress were discussed.The maximum thermal stress inside particle increases with pore curvature,the pore position affects the thermal stress more significantly at the particle center and surface.The expectation of the maximum tensile thermal stress linearly increases with porosity,making the particles with higher porosity easier to fragment,contrary to the conclusion deduced from the devolatilization theory.The obtained results are valuable for the analysis of different thermal processes concerning the thermal stresses of the solid feedstocks.

关键词： Coal particle Primary fragmentation Thermal stress Pore structure Porosity