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Laboratory and Semi-Field Evaluation on S-Methoprene Formulations Against Anopheles sinensis(Diptera:Culicidae)—Yuxi City,Yunnan Province,China

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China CDC weekly 2024年第6期6卷 105-108页

作者： wenbo hu Yijin Chen Ying Liang Tianyun Su Qiyong Liu Xuewen Li Xiaobo Liu School of Public Health Cheeloo College of MedicineShandong UniversityJinan CityShandong ProvinceChina National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases WHO Collaborating Centre for Vector Surveillance and ManagementDepartment of Vector Biology and ControlNational Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijingChina EcoZone International Riverside CityCAUSA Department of Environment and Health School of Public HealthCheeloo College of MedicineShandong UniversityJinan CityShandong ProvinceChina Department of Vector Control School of Public HealthShandong UniversityJi’nan CityShandong ProvinceChina Xinjiang Key Laboratory of Vector-borne Infectious Diseases Urumqi CityXinjiang830002

Summary What is already known about this topic?Anopheles sinensis(***)is the predominant malaria vector in *** impact of S-methoprene on the emergence process of mosquito larvae suggests its potential as a control met... 详细信息

关键词： sinensis China. predominant

数字时代的互联网使用与中老年人生活——中国老年群体数字鸿沟与数字融入调查主要数据结果分析

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人口研究 2024年第1期48卷 40-55页

作者：靳永爱胡文波冯阳中国人民大学人口与发展研究中心中国人民大学社会与人口学院

中国人口老龄化的加速推进伴随着信息化的快速发展,给人口老龄化应对带来了前所未有的机遇和挑战。从2010年到2022年,50~59岁和60岁及以上人群使用互联网的比例分别从11.1%、4.9%快速提升至73.5%、54.5%。随着互联网在中老年人中快速普... 详细信息

中国人口老龄化的加速推进伴随着信息化的快速发展,给人口老龄化应对带来了前所未有的机遇和挑战。从2010年到2022年,50~59岁和60岁及以上人群使用互联网的比例分别从11.1%、4.9%快速提升至73.5%、54.5%。随着互联网在中老年人中快速普及,迫切需要借助新的专项调查数据来探究其中的最新特征和规律。通过分析中国老年群体数字鸿沟与数字融入调查数据,研究发现,中老年上网者互联网使用的深度和广度不断拓展,但数字鸿沟依然存在;中老年上网者互联网使用时长适中,内部异质性强;中老年上网者面临网络安全风险,网络安全教育有所欠缺,网络安全素养有待提升;适度使用互联网对中老年上网者的健康老龄化和主观福祉均有积极影响。建议政府、企业、社区、家庭和老年人个体共同参与,创建老年数字友好型社会。

关键词：互联网使用中老年人生活数字时代健康老龄化

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知识引导的视觉关系检测模型

计算机应用 2024年第3期44卷 683-689页

作者：王元龙胡文博张虎山西大学计算机与信息技术学院太原030006

视觉关系检测(VRD)任务是在目标识别的基础上,进一步检测目标对象之间的关系,属于视觉理解和推理的关键技术。由于对象之间交互组合,容易造成对象间关系组合爆炸的问题,从而产生很多关联性较弱的实体对,导致后续的关系检测召回率较低。... 详细信息

视觉关系检测(VRD)任务是在目标识别的基础上,进一步检测目标对象之间的关系,属于视觉理解和推理的关键技术。由于对象之间交互组合,容易造成对象间关系组合爆炸的问题,从而产生很多关联性较弱的实体对,导致后续的关系检测召回率较低。针对上述问题,提出知识引导的视觉关系检测模型。首先构建视觉知识,对常见的视觉关系检测数据集中的实体标签和关系标签进行数据分析与统计,得到实体和关系间交互共现频率作为视觉知识;然后利用所构建的视觉知识,优化实体对的组合流程,降低关联性较弱的实体对得分,提升关联性较强的实体对得分,进而按照实体对的得分排序并删除得分较低的实体对,对于实体之间的关系也同样采用知识引导的方式优化关系得分,从而提升模型的召回率。在公开数据集视觉基因库(VG)和VRD中验证所提模型的效果:在谓词分类任务中,与现有模型PE-Net(Prototype-based Embedding Network)相比,在VG数据集上,召回率Recall@50和Recall@100分别提高了1.84和1.14个百分点;在VRD数据集上,相较于Coacher,Recall@20、Recall@50和Recall@100分别提高了0.22、0.32和0.31个百分点。

关键词：视觉关系检测实体对排序组合爆炸共现频率知识引导

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Acceptor Engineering Produces Ultrafast Nonradiative Decay in NIR-Ⅱ Aza-BODIPY Nanoparticles for Efficient Osteosarcoma Photothermal Therapy via Concurrent Apoptosis and Pyroptosis

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Research 2024年第1期2024卷 625-635页

作者： Zhenxiong Shi hua Bai Jiaxing Wu Xiaofei Miao Jia Gao Xianning Xu Yi Liu Jiamin Jiang Jiaqi Yang Jiaxin Zhang Tao Shao Bo Peng huili Ma Dan Zhu Guojing Chen wenbo hu Lin Li Wei huang Frontiers Science Center for Flexible Electronics Xi’an Institute of Flexible Electronics(IFE)and Xi’an Institute of Biomedical Materials&EngineeringNorthwestern Polytechnical UniversityXi’an 710072China Key Laboratory for Organic Electronics and Information Displays&Institute of Advanced Materials(IAM) Nanjing University of Posts&TelecommunicationsNanjing 210023China Key Laboratory of Flexible Electronics(KLOFE)and IAM Nanjing Tech UniversityNanjing 211800China Britton Chance Center for Biomedical Photonics-MoE Key Laboratory for Biomedical Photonics Wuhan National Laboratory for Optoelectronics-Advanced Biomedical Imaging FacilityHuazhong University of Science and TechnologyWuhan 430074China Department of Orthopedics Xijing HospitalThe Fourth Military Medical UniversityXi’an 710032China The Institute of Flexible Electronics(IFE Future Technologies)Xiamen UniversityXiamen 361005China

Small-molecule photothermal agents(PTAs)with intense second near-infrared(NIR-Ⅱ,1,000 to 1,700 nm)absorption and high photothermal conversion efficiencies(PCEs)are promising candidates for treating deep-seated tumors such as *** date,the development of small-molecule NIR-Ⅱ PTAs has largely relied on fabricating donor–acceptor–donor(D–A–D/D′)structures and limited success has been ***,through acceptor engineering,a donor–acceptor–acceptor(D–A–A′)-structured NIR-Ⅱ aza-boron-dipyrromethene(aza-BODIPY)PTA(SW8)was readily developed for the 1,064-nm laser-mediated phototheranostic treatment of *** the donor groups to acceptor groups produced remarkable red-shifts of absorption maximums from first near-infrared(NIR-Ⅰ)regions(~808 nm)to NIR-Ⅱ ones(~1,064 nm)for aza-BODIPYs(SW1 to SW8).Furthermore,SW8 self-assembled into nanoparticles(SW8@NPs)with intense NIR-Ⅱ absorption and an ultrahigh PCE(75%,1,064 nm).This ultrahigh PCE primarily originated from an additional nonradiative decay pathway,which showed a 100-fold enhanced decay rate compared to that shown by conventional pathways such as internal conversion and vibrational ***,SW8@NPs performed highly efficient 1,064-nm laser-mediated NIR-Ⅱ photothermal therapy of osteosarcoma via concurrent apoptosis and *** work not only illustrates a remote approach for treating deep-seated tumors with high spatiotemporal control but also provides a new strategy for building high-performance small-molecule NIR-Ⅱ PTAs.

关键词： donor BODIPY intense

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吕泗渔场经济鱼类的微塑料污染特征

大连海洋大学学报 2024年第3期39卷 490-497页

作者：胡文博张硕舒瑞霖高世科上海海洋大学海洋生物资源与管理学院上海201306 大洋渔业资源可持续开发教育部重点实验室上海201306 国家远洋渔业工程技术研究中心上海201306 农业农村部大洋渔业开发重点实验室上海201306

为研究微塑料污染对中国近海鱼类的潜在危害,以江苏省吕泗渔场经济鱼类为例,通过检测其胃中微塑料的丰度、形状、颜色、粒径和聚合物成分,分析了鱼类微塑料污染的种间差异,以及微塑料丰度与鱼类体长、体质量和所处营养位置的关系。结果... 详细信息

为研究微塑料污染对中国近海鱼类的潜在危害,以江苏省吕泗渔场经济鱼类为例,通过检测其胃中微塑料的丰度、形状、颜色、粒径和聚合物成分,分析了鱼类微塑料污染的种间差异,以及微塑料丰度与鱼类体长、体质量和所处营养位置的关系。结果表明:286尾鱼类样品体内均存在微塑料,平均丰度为(2.46±1.42)个/尾,平均粒径为(2.18±0.43)mm;微塑料主要呈蓝色纤维状,聚对苯二甲酸乙二醇酯(PET,83.9%)是主要的聚合物类型;微塑料丰度与鱼类体长、体质量和营养位置间无显著相关性(P>0.05),也未发现微塑料在鱼体内发生生物放大现象。研究表明,微塑料在调查区域中普遍存在,鱼类的体型、食性及栖息水层对其摄入微塑料的过程影响最为显著。

关键词：微塑料污染特征体型稳定同位素营养位置

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Wind power forecasting based on improved variational mode decomposition and permutation entropy

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Clean Energy 2023年第5期7卷 1032-1045页

作者： Zhijian Qu Xinxing Hou wenbo hu Rentao Yang Chao Ju State Key Laboratory of Performance Monitoring Protecting of Rail Transit Infrastructure East China Jiaotong University330013JiangxiChina College of Electrical and Automation Engineering East China Jiaotong University330013JiangxiChina

Due to the significant intermittent,stochastic and non-stationary nature of wind power generation,it is difficult to achieve the desired prediction ***,a wind power prediction method based on improved variational modal decomposition with permutation entropy is ***,based on the meteorological data of wind farms,the Spearman correlation coefficient method is used to filter the meteorological data that are strongly correlated with the wind power to establish the wind power prediction model data set;then the original wind power is decomposed using the improved variational modal decomposition technique to eliminate the noise in the data,and the decomposed wind power is reconstructed into a new subsequence by using the permutation entropy;with the meteorological data and the new subsequence as input variables,a stacking deeply integrated prediction model is developed;and finally the prediction results are obtained by optimizing the hyperparameters of the model algorithm through a genetic *** validity of the model is verified using a real data set from a wind farm in north-west *** results show that the mean absolute error,root mean square error and mean absolute percentage error are improved by at least 33.1%,56.1%and 54.2%compared with the autoregressive integrated moving average model,the support vector machine,long short-term memory,extreme gradient enhancement and convolutional neural networks and long short-term memory models,indicating that the method has higher prediction accuracy.

关键词： wind power prediction improved variational mode decomposition permutation entropy stacking deep learning

基于多新息最小二乘和多新息扩展卡尔曼滤波算法的锂电池SOC估计

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华南理工大学学报（自然科学版） 2024年第2期52卷 74-83页

作者：巫春玲付俊成徐先峰孟锦豪郑克军胡雯博长安大学能源与电气工程学院陕西西安710064 西安交通大学电气工程学院陕西西安710049

针对现有SOC(荷电状态)估计方法中电池模型参数恒定,没有考虑电池模型参数的动态变化,导致SOC的估计不够精准的问题,文中提出了一种基于电池模型参数在线辨识与SOC估计联合的算法。在二阶RC等效电路模型基础上,采用多新息最小二乘(Multi... 详细信息

针对现有SOC(荷电状态)估计方法中电池模型参数恒定,没有考虑电池模型参数的动态变化,导致SOC的估计不够精准的问题,文中提出了一种基于电池模型参数在线辨识与SOC估计联合的算法。在二阶RC等效电路模型基础上,采用多新息最小二乘(Multi Innovation Least Squares,MILS)算法对锂离子电池模型中的参数进行在线辨识,从而对电池模型进行实时修正;同时基于修正后的电池模型,采用多新息扩展卡尔曼滤波(Multi Innovation Extended Kalman Filter,MIEKF)算法对电池荷电状态进行估计。MILS算法可以解决在线参数辨识过程中的初始误差累积问题,能够实现模型参数的在线精准辨识,MIEKF算法融合了多新息理论和卡尔曼滤波理论,加入了遗忘因子以削弱历史数据并修正权重,解决了数据过饱和问题,具有较高的准确性和收敛性。实验结果表明,在对电池模型进行参数辨识时,MILS算法、RLS算法辨识的均方根误差分别为1.4、1.9 mV,MILS算法相比RLS算法的估计精度提高了26.3%;对于参数辨识后SOC的估计,MIEKF算法估计的均方根误差为0.0037,EKF算法、AEKF算法估计的均方根误差分别为0.0073、0.0052,MIEKF算法比EKF算法的估计精度提高了49.31%,比AEKF算法的估计精度提高了28.84%;并且在给定SOC初值错误的情况下,文中所提出算法在电池开始工作后30 s左右就能够收敛到真实值,是一种精度高而且鲁棒性好的有效估计方法。

关键词： SOC估计多新息参数辨识扩展卡尔曼滤波

Effect of Ni content on the wear behavior of Al-Si-Cu-Mg-Ni/SiC particles composites

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International Journal of Minerals,Metallurgy and Materials 2024年第2期31卷 374-383页

作者： Yanyu Liu Lina Jia wenbo Wang Zuheng Jin hu Zhang School of Materials Science and Engineering Beihang UniversityBeijing 100191China Ningbo Institute of Technology Beihang UniversityNingbo 315100China Qingdao Research Institute of Beihang University Qingdao 266000China Research Institute for Frontier Science Beihang UniversityBeijing 100191China

In recent years,the addition of Ni has been widely acknowledged to be capable of enhancing the mechanical properties of Al-Si ***,the effect of Ni on the wear behaviors of Al-Si alloys and Al matrix composites,particularly at elevated temperat-ures,remains an understudied *** this study,Al-Si-Cu-Mg-Ni/20wt%SiC particles(SiCp)composites with varying Ni contents were prepared by using a semisolid stir casting *** effect of Ni content on the dry sliding wear behavior of the prepared compos-ites was investigated through sliding tests at 25 and 350℃.Results indicated that theθ-Al_(2)Cu phase gradually diminished and eventually disappeared as the Ni content increased from 0wt%to 3wt%.This change was accompanied by the formation and increase inδ-Al_(3)CuNi andε-Al_(3)Ni phases in *** hardness and ultimate tensile strength of the as-cast composites improved,and the wear rates of the composites decreased from 5.29×10^(−4)to 1.94×10^(−4)mm^(3)/(N∙m)at 25℃and from 20.2×10^(−4)to 7×10^(−4)mm^(3)/(N∙m)at 350℃with the increase in Ni content from 0wt%to 2wt%.The enhancement in performance was due to the presence of strengthening network structures and additional Ni-containing phases in the ***,the wear rate of the 3Ni composite was approximately two times higher than that of the 2Ni composite due to the fracture and debonding of theε-Al_(3)Ni *** wear,delamination wear,and oxidation wear were the predominant wear mechanisms of the investigated composites at 25℃,whereas delamination wear and oxid-ation wear were dominant during sliding at 350℃.

关键词： Al matrix composite microstructure sliding test high temperature wear mechanism

熔盐法制备氮掺杂多孔石墨烯及电化学性能研究

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内蒙古科技大学学报 2024年第2期43卷 134-139页

作者：胡文博邢艳伟辛国祥刘金鑫孙伟内蒙古科技大学材料科学与工程学院内蒙古包头014010

采用熔盐法,以氧化石墨烯为原料、尿素为氮源成功制备了氮掺杂多孔石墨烯(NPG-1)材料。通过XRD、SEM、TEM、XPS、BET、CV、GCD和EIS对NPG-1进行物理性能分析和电化学性能测试。测试结果显示其具有丰富褶皱、互连网络多孔结构以及优异的... 详细信息

采用熔盐法,以氧化石墨烯为原料、尿素为氮源成功制备了氮掺杂多孔石墨烯(NPG-1)材料。通过XRD、SEM、TEM、XPS、BET、CV、GCD和EIS对NPG-1进行物理性能分析和电化学性能测试。测试结果显示其具有丰富褶皱、互连网络多孔结构以及优异的电化学性能。由于NPG-1互连网络多孔结构以及氮原子掺杂产生的赝电容,NPG-1在0.5 A/g时具有264 F/g的高比电容,经10 000次恒流充放电循环,NPG-1电容保持率达到94.9%,表明其拥有良好的循环稳定性。综上所述,这种电极材料在超级电容器领域中具有实用价值和广阔前景。

关键词：熔盐法氮掺杂多孔石墨烯超级电容器