Defect engineering is recognized as an effective route to obtain highly active photocatalytic materials.However,the current understanding of defects is mainly limited to isolated atomic vacancy defects,ignoring the ex...Defect engineering is recognized as an effective route to obtain highly active photocatalytic materials.However,the current understanding of defects is mainly limited to isolated atomic vacancy defects,ignoring the exploration of the functions of multivariate defects formed by the deletion of several adjacent atoms in photocatalytic system.Here,we prepared SnS2 nanostructures with the same morphology but different dominant defects,and by testing their photocatalytic performance,it was found that the multivariate defects can significantly improve the photocatalytic performance than isolated S vacancies.Combining experiments and theoretical calculations,we confirmed that the promotion of multivariate defects,especially“S-Sn-S”vacancy associates,on the photocatalytic performance is reflected in many aspects,such as the regulation of the energy band structure,the improvement of the charge separation efficiency,and the promotion of the adsorption and activation of guest molecules.SnS2 with“S-Sn-S”vacancy associates exhibits excellent photocatalytic water purification ability.Under the induction of“S-Sn-S”vacancy associates,phenol was thoroughly photocatalytically decomposed,further confirming its excellent functionality.This work not only provides new insights into identifying advantage defects in the catalyst structure,but also offers new ideas for constructing highly active photocatalysts based on defect engineering.展开更多
Soil erosion has long been a problem in the Ethiopian highlands in general and Dembecha district in particular. The objective of this study was to identify factors influencing adoption of soil and water conservation p...Soil erosion has long been a problem in the Ethiopian highlands in general and Dembecha district in particular. The objective of this study was to identify factors influencing adoption of soil and water conservation practices. Both quantitative and qualitative data were collected from primary and sec-ondary sources. The primary data were collected from respondent samples and key informants through interview and personal observation. The secondary data were collected from sources such as books, journals, statistical reports and official documents. A multistage sampling technique was applied to select sample households. Sample sizes of 150 households were selected using simple random sampling. Both descriptive statistics and a multivariate probit econometric model were employed to analyze the data. The model results revealed that the likelihood of decisions to adopt soil bund, stone bund, check dam and strip cropping were 74, 56, 29 and 56%respectively. The joint probability of adopting the selected soil and water conservation practices was 14.2%. The model results also confirmed that age, sex, education level, household size, livestock holding, land size, access to credit, access to extension service and training were significant factors that affected the adoption of soil and water conservation practices in the study area. Based on our findings, the study suggests that the government and stakeholders should focus on strengthening the provision of formal and non-formal training and facilitate an effective extension service.展开更多
Accelerated degradation test(ADT)has become an efficient approach to assess the reliability of degradation products within limited time and budget.Some products have more than one degradation process that is responsib...Accelerated degradation test(ADT)has become an efficient approach to assess the reliability of degradation products within limited time and budget.Some products have more than one degradation process that is responsible for failure of product,which introduces some problems of modeling accelerated degradation data and estimating unknown parameters.In order to solve the problems,a practical method of inferring reliability with multivariate accelerated degradation data is proposed in this paper.Stochastic processes are used to fit accelerated degradation data,and then margin reliability functions are derived from the degradation models.Unlike the traditional assumption that the degradation increments of multivariate degradation processes at the same observing time are mutually dependent,the margin reliabilities at the same time are considered to be dependent,which is applicable to the situation that multivariate degradation data is not simultaneously observed.Copula functions are used to describe the dependency between marginal reliabilities,and the two situations that copula parameter is independent of accelerated stress or dependent on accelerated stress are both considered.In the case study,the bivariate accelerated degradation data of O-ring rubber is used to demonstrate our proposed method.The research results indicate that the proposed method provides a practical and feasible approach to reliability inference with multivariate accelerated degradation data.展开更多
基金supported by Joint Funds of the National Natural Science Foundation of China(Nos.U20A20302 and 21701125)China Postdoctoral Science Foundation(Nos.2021T140512 and 2020M680869)+3 种基金Natural Science Foundation of Tianjin(No.20JCQNJC00950)Natural Science Foundation of Hebei Province(No.B2021202001)Key R&D projects in Hebei Province(No.20373701D)Overseas High-level Talents Introduction Plan Foundation of Hebei Province(No.E2019050012).
文摘Defect engineering is recognized as an effective route to obtain highly active photocatalytic materials.However,the current understanding of defects is mainly limited to isolated atomic vacancy defects,ignoring the exploration of the functions of multivariate defects formed by the deletion of several adjacent atoms in photocatalytic system.Here,we prepared SnS2 nanostructures with the same morphology but different dominant defects,and by testing their photocatalytic performance,it was found that the multivariate defects can significantly improve the photocatalytic performance than isolated S vacancies.Combining experiments and theoretical calculations,we confirmed that the promotion of multivariate defects,especially“S-Sn-S”vacancy associates,on the photocatalytic performance is reflected in many aspects,such as the regulation of the energy band structure,the improvement of the charge separation efficiency,and the promotion of the adsorption and activation of guest molecules.SnS2 with“S-Sn-S”vacancy associates exhibits excellent photocatalytic water purification ability.Under the induction of“S-Sn-S”vacancy associates,phenol was thoroughly photocatalytically decomposed,further confirming its excellent functionality.This work not only provides new insights into identifying advantage defects in the catalyst structure,but also offers new ideas for constructing highly active photocatalysts based on defect engineering.
文摘Soil erosion has long been a problem in the Ethiopian highlands in general and Dembecha district in particular. The objective of this study was to identify factors influencing adoption of soil and water conservation practices. Both quantitative and qualitative data were collected from primary and sec-ondary sources. The primary data were collected from respondent samples and key informants through interview and personal observation. The secondary data were collected from sources such as books, journals, statistical reports and official documents. A multistage sampling technique was applied to select sample households. Sample sizes of 150 households were selected using simple random sampling. Both descriptive statistics and a multivariate probit econometric model were employed to analyze the data. The model results revealed that the likelihood of decisions to adopt soil bund, stone bund, check dam and strip cropping were 74, 56, 29 and 56%respectively. The joint probability of adopting the selected soil and water conservation practices was 14.2%. The model results also confirmed that age, sex, education level, household size, livestock holding, land size, access to credit, access to extension service and training were significant factors that affected the adoption of soil and water conservation practices in the study area. Based on our findings, the study suggests that the government and stakeholders should focus on strengthening the provision of formal and non-formal training and facilitate an effective extension service.
基金the National Natural Science Foundation of China(Nos.51605487 and 51975580)。
文摘Accelerated degradation test(ADT)has become an efficient approach to assess the reliability of degradation products within limited time and budget.Some products have more than one degradation process that is responsible for failure of product,which introduces some problems of modeling accelerated degradation data and estimating unknown parameters.In order to solve the problems,a practical method of inferring reliability with multivariate accelerated degradation data is proposed in this paper.Stochastic processes are used to fit accelerated degradation data,and then margin reliability functions are derived from the degradation models.Unlike the traditional assumption that the degradation increments of multivariate degradation processes at the same observing time are mutually dependent,the margin reliabilities at the same time are considered to be dependent,which is applicable to the situation that multivariate degradation data is not simultaneously observed.Copula functions are used to describe the dependency between marginal reliabilities,and the two situations that copula parameter is independent of accelerated stress or dependent on accelerated stress are both considered.In the case study,the bivariate accelerated degradation data of O-ring rubber is used to demonstrate our proposed method.The research results indicate that the proposed method provides a practical and feasible approach to reliability inference with multivariate accelerated degradation data.
文摘工作在复杂环境下的多元退化设备面临失效数据少、多源信息融合准确度低和监督学习数据不平衡等问题,对此本文提出一种基于时间序列生成对抗网络(Time-series Generative Adversarial Networks,TimeGAN)与单分类支持向量机(One-Class Support Vector Machine,OCSVM)组合模型的小子样数据增广方法.方法引入了TimeGAN模型拟合真实数据时间序列相关性,从而生成新的多元退化设备数据.本文提出了一种基于最大均值差异改进方法的可信度判据,避免强相关特征对生成数据质量评价的影响,通过使用T-分布随机邻近嵌入(T-distributed Stochastic Neighbor Embedding,T-SNE)和全局最大均值差异(Global Maximum Mean Discrepancy,GMMD)的组合方法,定性定量地评价生成数据的质量水平.基于训练后的OCSVM模型,对生成数据进行异常检测与剔除,进一步提高生成数据的质量.以航空发动机数据集C-MAPSS为例进行方法验证分析,通过与其他数据增强模型对比验证了所提方法的可行性和有效性.
文摘滚动轴承性能退化评估是预诊断的提前和基础,对在役滚动轴承实施在线状态监测和性能退化评估具有重要意义。针对概率相似度量评估方法存在模型复杂、容易过早饱和等现象,提出一种基于自回归时序(autoregressive model,简称AR)模型和多元状态估计(multivariate state estimation technique,简称MSET)的滚动轴承性能在线评估方法,其中AR模型用于提取轴承振动信号的状态特征,MSET模型用于重构AR模型系数。首先,提取正常运行状态下振动信号的AR模型系数构建MSET模型的历史记忆矩阵;其次,将待测信号的AR系数作为观测向量输入MSET模型中得到重构后的估计向量;最后,由原始AR系数和重构AR系数分别构造自回归模型,并各自完成对待测信号的时序建模,将两自回归模型所得残差序列的均方根值之差作为性能劣化程度指标。离散实验数据和全寿命疲劳实验数据分析结果表明,该方法能够有效检测早期故障,且具有与轴承故障发展趋势一致性更好等优点。
