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中国高质量就业水平的时空分异及影响因素分析

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西北人口 2025年第1期46卷 87-101页

作者：司小飞河南师范大学社会事业学院河南新乡453007 河南师范大学河南省新时代文明实践研究中心河南新乡453007

高质量就业反映了劳动者与生产资料结合的状况,不仅关系到劳动者的权益保护,影响经济发展和社会稳定,甚至还会影响共同富裕的实现。文章基于2011~2022年中国31个省(自治区、直辖市)的面板数据,利用熵权topsis、莫兰指数、Dagum基尼系数... 详细信息

高质量就业反映了劳动者与生产资料结合的状况,不仅关系到劳动者的权益保护,影响经济发展和社会稳定,甚至还会影响共同富裕的实现。文章基于2011~2022年中国31个省(自治区、直辖市)的面板数据,利用熵权topsis、莫兰指数、Dagum基尼系数法、空间计量模型对中国高质量就业水平的时空分异及影响因素进行分析,研究发现:1.中国高质量就业的总体水平在2021年之前一直处于上升趋势,而到2021年之后则出现下降趋势,且总体水平不高;2.高质量就业水平的各个维度发展不协调,社会保障与劳动报酬的维度发展相对滞后;3.中国高质量就业水平的总体差异进一步扩大,区域间差异是造成总体差距不断扩大的主要原因;4.中国高质量就业水平存在显著的空间溢出效应,经济增长、人口增长、贸易开放、产业结构和人力资本对本省和邻省高质量就业均具有显著的正向影响,而外商投资对本省高质量就业具有显著的负向影响,政府干预对邻省高质量就业具有抑制作用。针对该结论,从发挥政策资源的优势,提升高质量就业的总体水平、补齐区域发展短板,缩小区域间高质量就业水平的差距、补齐社会保障和劳动报酬的短板,推动高质量就业各维度的协调发展、发挥高质量就业的正向空间溢出效应,推进高质量就业水平的均衡发展4个方面提升中国高质量就业水平。

关键词：高质量就业时空分异影响因素

Peri-centrosomal localization of small interfering RNAs in C. elegans

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Science China Life Sciences 2025年

作者： Qile Jin Xuezhu Feng Minjie Hong Ke Wang Xiangyang Chen Jiewei Cheng Yan Kuang Xiaoyue si Mingjing Xu Xinya Huang Shouhong Guang Chengming Zhu Department of Obstetrics and Gynecology The First Affiliated Hospital of USTC The USTC RNA Institute Hefei National Research Center for Physical Sciences at the Microscale School of Life Sciences Division of Life Sciences and Medicine Biomedical Sciences and Health Laboratory of Anhui Province University of Science and Technology of China School of Basic Medicine Anhui Medical University

The centrosome is the microtubule-organizing center and a crucial part of cell division. Centrosomal RNAs(cnRNAs) have been reported to enable precise spatiotemporal control of gene expression during cell division in many species. Whether and how cnRNAs exist in C. elegans are unclear. Here, using the nuclear RNAi Argonaute protein NRDE-3 as a reporter, we observed potential peri-centrosome localized small interfering(si)RNAs in C. elegans. NRDE-3 was previously shown to associate with pre-mRNAs and pre-rRNAs via a process involving the presence of complementary siRNAs. We generated a GFP-NRDE-3 knock-in transgene through CRISPR/Cas9 technology and observed that NRDE-3 formed peri-centrosomal foci neighboring the tubulin protein TBB-2, other centriole proteins and pericentriolar material(PCM)components in C. elegans embryos. The peri-centrosomal accumulation of NRDE-3 depends on RNA-dependent RNA polymerase(RdRP)-synthesized 22G siRNAs and the PAZ domain of NRDE-3, which is essential for siRNA binding. Mutation of eri-1, ergo-1, or drh-3 significantly increased the percentage of pericentrosome-enriched NRDE-3. At the metaphase of the cell cycle, NRDE-3 was enriched in both the peri-centrosomal region and the spindle. Moreover, the integrity of centriole proteins and pericentriolar material(PCM) components is also required for the peri-centrosomal accumulation of NRDE-3. Therefore, we concluded that siRNAs could accumulate in the pericentrosomal region in C. elegans and suggested that the peri-centrosomal region may also be a platform for RNAi-mediated gene regulation.

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超级电容器(NixCo1-x)0.85Se纳米球状正极材料的制备及性能研究

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化学工业与工程 2025年第1期42卷 69-77页

作者：张卫国陈光耀王宏智姚素薇天津大学化工学院天津体育学院

采用溶剂热法制备了镍钴双金属硒化物(NixCo1-x)0.85Se电极材料，利用XRD、SEM、TEM以及XPS测试材料的微观形貌和元素组成，通过三电极体系测试电极材料的电化学性能。(NixCo1-x)0.85Se呈现纳米球状结构，直径在200～500 nm之间。通过... 详细信息

采用溶剂热法制备了镍钴双金属硒化物(NixCo1-x)0.85Se电极材料，利用XRD、SEM、TEM以及XPS测试材料的微观形貌和元素组成，通过三电极体系测试电极材料的电化学性能。(NixCo1-x)0.85Se呈现纳米球状结构，直径在200～500 nm之间。通过调节实验条件，合成了Ni/Co比例不同的材料，其中(Ni0.50Co0.50)0.85Se具有最大比电容值(2 900 F·g-1,1 A·g-1)。(Ni0.50Co0.50)0.85Se与活性炭组装成混合超级电容器，循环稳定性较好(1 A·g-1电流密度下2 500次充放电循环后，电容保持率83.21%),表明镍钴硒化物在超级电容器领域具有较高的应用价值。

关键词：镍钴硒化物混合超级电容器纳米球状材料

Research on Short-Term Electric Load Forecasting Using IWOA CNN-BiLSTM-TPA Model

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印刷与数字媒体技术研究 2025年第1期 179-187页

作者： MEI Tong-da si Zhan-jun ZHANG Ying-xue College of Artificial Intelligence Tianjin University of Science and TechnologyTianjin 300457China

Load forecasting is of great significance to the development of new power *** the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and *** places higher demands on the prediction and analysis of power *** order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was ***,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data ***,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the *** allowed the model to differentiate the importance of load sequences at different time *** the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the *** this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.

关键词： Whale Optimization Algorithm Convolutional Neural Network Long Short-Term Memory Temporal Pattern Attention Power load forecasting

Construction of axial and point chirality through Ni-catalyzed sila-cycloaddition reaction via desymmetrization and (dynamic) kinetic resolution

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Science China Chemistry 2025年

作者： Hua-Jie Zhu Ming-Hao Shen Jia-Wei si Wei-Ke Zhu Xiao-Jun Fang Fei Ye Jian Cao Zheng Xu Li-Wen Xu Key Laboratory of Organosilicon Chemistry and Material Technology of Ministry of Education and Key Laboratory of Organosilicon Material Technology of Zhejiang Province College of Material Chemistry and Chemical Engineering Hangzhou Normal University State Key Laboratory for Oxo Synthesis and Selective Oxidation Suzhou Research Institute Lanzhou Institute of Chemical PhysicsChinese Academy of Sciences

Recent developments in chirality chemistry have revealed remarkable instances of atropisomers featuring multiple chiral elements. Despite significant progress in the synthesis and application of atropisomers, developing a synthetic protocol for the simultaneous introduction of axial and point chirality is still a fascinating challenge. In this context, we present a convenient and versatile method for synthesizing novel atropisomers with axial and point chirality. This approach, based on a new reaction mechanism with nickel-controlled si–C bond activation, facilitates the controllable migratory insertion of aldehydes into the Ni–C bond. We utilize multidimensional strategies of desymmetrization, kinetic resolution and dynamic kinetic resolution to complete enantioselective nickel-catalyzed ring expansion of benzosilacyclobutenes with aldehydes. The design of multidimensional kinetic resolution, desymmetrization, and dynamic resolution, features a straightforward catalytic system, mild reaction conditions, and broad functional group tolerances. Various axially chiral biaryl oxasilacycles bearing carbon-or siliconstereogenic centers are obtained with excellent diastereo-and enantio-selectivities(up to >20:1 dr and >99.9% ee) through the use of a chiral Ni complex with a large cavity-type 1,1,4,4-tetra-aryl-2,3-O-isopropylidene-L-threitol(TADDOL)-derived phosphoramidite ligand.

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Homologous CoS2 interface with directed electron transfer and strong chloridion repulsion for efficient seawater oxidation

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Science China Chemistry 2025年

作者： Yuan Tian Jiang-Bo Chen Jie Ying Ge Tian Yu-Xuan Xiao Yi Lu si-Ming Wu Wei Geng Ling Shen Xiao-Yu Yang State Key Laboratory of Advanced Technology for Materials Synthesis and Processing and School of Materials Science and Engineering and Shenzhen Research Institute & Laoshan Laboratory Wuhan University of Technology School of Chemical Engineering and Technology Sun Yat-Sen University National Energy Key Laboratory for New Hydrogen-Ammonia Energy Technologies Foshan Xianhu Laboratory

Seawater electrolysis is a highly promising method to produce high energy density hydrogen,especially in dry areas that have scarce freshwater ***,application of seawater electrolysis is confronted by two major problems associated with catalysts employed for the anodic oxygen evolution reaction （OER） including the competitive hypochlorite evolution reaction（HCER） and strong chloridion （Cl–） triggered *** studies aimed at overcoming these problems,a facile method has been developed to synthesize a homologous CoS2heterojunction as an OER *** to a difference in work functions at the interface and increased electron density,this material has directed electron transfer and strong chloridion repulsion properties,*** have shown that CoS2achieves low overpotentials of 289 and 322 mV at 10 mA cm-2current density in respective alkaline （1 M KOH） and alkaline simulated seawater ***,the outstanding stability of CoS2is reflected in a negligible decline in activity during promotion of the OER for 100 *** of density functional theory calculations reveal that the homologous CoS2heterojunction promotes directed electron transport for optimizing adsorption/desorption of reactive species and heightens the Cl-adsorption energy for strongly repulsing Cl-,phenomena that enhance OER performance in alkaline simulated seawater.

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无创血流储备分数的历史和现状及发展趋势

中国医药 2025年第1期20卷 133-137页

作者：王点翟光耀首都医科大学潞河临床医学院首都医科大学附属北京潞河医院心血管病中心北京101149

人工智能通过冠状动脉CT血管造影(CCTA)数据,计算出冠状动脉的CT血管造影血流储备分数(CT-FFR)。这种能力通过机器学习不断提升和改进,可以用于自动检测和评估冠状动脉狭窄,识别斑块成分以及预测病变的进展,还可以显著提高诊断的准确性... 详细信息

人工智能通过冠状动脉CT血管造影(CCTA)数据,计算出冠状动脉的CT血管造影血流储备分数(CT-FFR)。这种能力通过机器学习不断提升和改进,可以用于自动检测和评估冠状动脉狭窄,识别斑块成分以及预测病变的进展,还可以显著提高诊断的准确性和效率。人工智能在CCTA中的应用也面临着一些挑战和问题,包括算法的泛化能力、数据的标准化和隐私保护等。为了进一步提高CT-FFR技术在临床中的实用性和效率,需要对这些挑战进行深入研究,并开发出更加优化的解决方案。

关键词：冠状动脉狭窄冠状动脉CT血管造影血流储备分数 CT血管造影血流储备分数人工智能

针对缺失实验室指标多约束表征学习的卵巢癌鉴别方法

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南方医科大学学报 2025年第1期45卷 170-178页

作者：卢梓涵黄方俊蔡光瑶刘继红甄鑫南方医科大学生物医学工程学院广东广州510515 中山大学肿瘤防治中心妇科//华南肿瘤学国家重点实验室//肿瘤医学省部共建协同创新中心广东广州510145 广东省人民医院广东广州510080

目的探索基于多约束表征学习分类模型在面对缺失实验室指标的情况下鉴别卵巢癌的鉴别能力和应用价值。方法收集了2344例患者(393例卵巢癌和1951例对照)的缺失实验室指标表格型数据,使用本研究提出的基于判别学习和互信息以及特征投影重... 详细信息

目的探索基于多约束表征学习分类模型在面对缺失实验室指标的情况下鉴别卵巢癌的鉴别能力和应用价值。方法收集了2344例患者(393例卵巢癌和1951例对照)的缺失实验室指标表格型数据,使用本研究提出的基于判别学习和互信息以及特征投影重要性得分一致性及缺失位置估算的表征学习分类模型对缺失的卵巢癌实验室指标特征进行投影到潜在空间得到分类模型。对提出的约束项进行消融实验,通过准确率、ROC曲线下面积(AUC)、敏感度、特异性说明约束项的可行性和有效项。采用交叉验证方法和准确率、AUC、敏感度、特异性评价该分类模型的鉴别性能。将本研究与其他用于缺失数据的插补方法进行对缺失数据处理后鉴别分类能力的对比。结果消融实验结果显示约束项之间有很好的相容性,每项约束项都有较好的鲁棒性。交叉验证结果显示,本研究提出的基于多约束表征学习分类模型在面对缺失实验室指标的情况下对卵巢癌的鉴别中的AUC、准确率、敏感度、特异性分别为0.915、0.888、0.774、0.910,其中AUC和敏感度优于其它缺失数据插补方法。结论基于多约束表征学习模型在缺失实验室指标鉴别卵巢癌的应用中具有优秀的鉴别能力和较高的应用价值。与其他缺失插补方法相比,本研究提出的多约束表征学习模型在针对卵巢癌缺失实验室指标的鉴别分类任务中具有较大的优势。

关键词：缺失数据多约束表征学习模型判别分析特征投影重要性得分一致性缺失位置估算互信息卵巢癌

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水环境中口罩源“塑料际”微生物生态

环境科学 2025年第2期46卷 1193-1202页

作者：彭思伟张广毅焦园园郑州大学水利与交通学院郑州450001 郑州大学地下工程研究院郑州450001

因疫情及其它呼吸道疾病影响,医用口罩常态化使用增加,其废弃物进入环境中风险增大且产生的微塑料可能会对水生态系统产生影响.通过对口罩进入水环境的模拟实验,探究口罩不同层微生物群落多样性、功能、组装机制和相互作用.结果表明,各... 详细信息

因疫情及其它呼吸道疾病影响,医用口罩常态化使用增加,其废弃物进入环境中风险增大且产生的微塑料可能会对水生态系统产生影响.通过对口罩进入水环境的模拟实验,探究口罩不同层微生物群落多样性、功能、组装机制和相互作用.结果表明,各层口罩源“塑料际”有独特的微生物群落,且随时间增加,丰富度逐渐提高.口罩源“塑料际”微生物功能也随时间显著变化,且与致病微生物、光营养、有机物降解和C、N、S元素循环有关.口罩源“塑料际”微生物群落组装机制研究结果表明,随机性过程更为重要(NST>0.5),但随时间增加,确定性过程的作用逐渐提高.共生网络结果表明,不同层口罩源“塑料际”微生物都有较高的模块数和模块化程度,且随着定植时间增加,微生物群落复杂性逐渐降低.口罩源“塑料际”有着独特的生态过程,该研究有助于对口罩源“塑料际”生态效应和微生物定植过程的理解.

关键词：口罩塑料际微生物组装机制生态学