The relation between emotional intelligence and job performance: A meta‐analysis

This meta‐analysis builds upon a previous meta‐analysis by (1) including 65 per cent more studies that have over twice the sample size to estimate the relationships between emotional intelligence (EI) and job performance; (2) using more current meta‐analytical studies for estimates of relationships among personality variables and for cognitive ability and job performance; (3) using the three‐stream approach for classifying EI research; (4) performing tests for differences among streams of EI research and their relationships with personality and cognitive intelligence; (5) using latest statistical procedures such as dominance analysis; and (6) testing for publication bias. We classified EI studies into three streams: (1) ability‐based models that use objective test items; (2) self‐report or peer‐report measures based on the four‐branch model of EI; and (3) “mixed models” of emotional competencies. The three streams have corrected correlations ranging from 0.24 to 0.30 with job performance. The three streams correlated differently with cognitive ability and with neuroticism, extraversion, openness, agreeableness, and conscientiousness. Streams 2 and 3 have the largest incremental validity beyond cognitive ability and the Five Factor Model (FFM). Dominance analysis demonstrated that all three streams of EI exhibited substantial relative importance in the presence of FFM and intelligence when predicting job performance. Publication bias had negligible influence on observed effect sizes. The results support the overall validity of EI. Copyright © 2010 John Wiley & Sons, Ltd. Note: Correction added on 22 July 2010 after first publication online on 29 June 2010. The affiliations for Ronald H. Humphrey and Thomas H. Hawver have been corrected in this version of the article.     

基于Agent的长输管道应急指挥决策系统设计

为帮助决策机构快速高效地制定长输管道事故应急救援方案和行动目标,运用Agent (真体)对长输管道应急指挥决策系统进行设计.通过划分应急指挥系统层次,分析信息融合Agent、形势评估Agent、资源规划Agent这3个关键模块,建立基于Agent的应急指挥过程模型.结合应急指挥机构和应急指挥决策系统,提出应急指挥系统...     

人工智能助力臭氧催化剂SrFexZr1-xO3的开发

将人工智能应用于催化臭氧氧化催化剂SrFe_xZr_1-xO₃的开发过程,采用共沉淀法制备了50种不同配方的催化剂,考察聚乙二醇（PEG）投加量、煅烧时间、老化时间、氨水投加量和铁掺杂量对SrFe_xZr_1-xO₃催化剂催化臭氧降解间甲酚反应活性的影响.同时,利用人工神经网络（ANN）和响应面（RSM）对催化剂合成条件与TOC去除率和间甲酚转化率的关系进行拟合,训练集中ANN的R²值分别为0.91和0.97,高于RSM的R²值0.35和0.41;在4组测试集上ANN的均方误差（MSE）分别为9.87和17.67,远小于RSM的23.89和28.87.结果表明,ANN模型对催化剂制备过程的复杂体系具有更好的拟合和泛化能力.在ANN训练好的模型中通过枚举法寻找最优合成条件为：PEG投加量为19.00%,煅烧时间为1.25 h,老化时间为26.50 h,氨水投加量为6.21 mL,铁掺杂量为3.37%,所得催化剂为SrFe_0.13Zr_0.87O₃-B.最佳反应条件下,间甲酚转化率和TOC去除率分别达到98.52%和17.21%,优于空白组的73.46%和1.86%.     

A review of recent developments in lake modelling

This paper reviews the lake models published the last five years, mainly in Ecological Modelling. The review shows that structurally dynamic modelling and coupling between hydrodynamic and ecological models are applied increasingly. A number of processes that have not been included in lake models before have been proposed. It has been shown that these additional processes in specific case studies are significant, for instance the competition between phytoplankton and macrophytes or cyanobacteria growth and growth of mussels. It is recommended to study these models for the development of models for case studies where these processes are relevant.     

风窗对井下通风系统的影响及其调节与定位优化

利用回路阻力平衡关系分析了井下风窗安装前后通风系统中各分支间风流流动关系,提出了某些分支安装风窗后,通风系统各分支的风量对此变化作出反应的分析模型,给出了度量风量和阻力反应敏感性强弱的方法;假定通风系统中某些分支同时安装风窗,在保留风窗的使用对通风系统所带来的正面作用,但要抑制其负面作用的条件下,基于尽可能使所有参与调节的分支的风阻增、减值最小化的原则,提出了指定分支实施调节的调阻调节法和优选分支实施调节的调阻调节法,并建立了相关最优调节模型及其求解方法。结果表明:两种模型可以在风窗安装之前进行解算,解算结果可预知风窗安装后通风系统各分支的风流的分布情况,并确定出相应的调控策略;优选分支调阻调节模型可以用于选择最优的风窗安装位置、数量及风窗阻力,后者可以用于确定风窗窗口面积。     

施工企业内社会资本、情绪智力与安全绩效关系研究

依据资本观、能力观等相关理论,构建了以情绪智力为中介变量的施工企业内社会资本与安全绩效关系的理论模型,并以156家施工企业为调查对象而获取的数据进行多元回归分析。研究结果表明:员工情绪智力在施工企业内社会资本的结构维度、关系维度与安全绩效之间起到完全中介作用,在认知维度与安全绩效之间起到部分中介作用。因此,施工企业应该重视企业内社会资本的积累,同时加强员工情绪智力的提升,提高安全绩效。     

人工神经网络模型在水质预警中的应用研究进展

水质预警模型是大数据时代构建环境智能决策与管理体系的关键技术.近年来,水质自动化监测能力的提升以及测管协同对环境模型的强烈需求,激发了研究人员探索新的建模方法并努力提高模型预测性能.其中,人工神经网络(Artificial Neural Network, ANN)模型发展迅速.本文综述了3大类ANN模型的发展历史和模型结构特点,梳理了ANN模型在水质数据软测量、数据异常检测和时间序列预测等方面的研究进展,归纳了一般建模流程、技术建议和常用的模型性能指标,发现ANN模型的应用依赖于监测数据质量,存在模型可解释性差、模型运行硬件资源要求较高等不足,提出未来水质预警模型的研发思路和重点,需要加快推进水环境监测技术与预警模型的协同发展和业务化应用,通过多种应用场景检验实现技术迭代,形成大数据驱动的水质在线监测-智能预警-应急管理支撑体系,助力我国环境治理能力现代化.     

微电脑烟尘采样器的使用

根据作者在仪器使用和维修过程中的一些经验,介绍TH880Ⅳ型智能烟尘平行采样仪在实际应用中遇到的问题,并提出相应的解决方法及建议。     

Forest Health,Collective Behaviors,and Management

This study compares community-based managed forests under different purposes of management, namely, state-driven conservation or community-designed utilization in two villages located in the Sopsai watershed, Nan Province, northern Thailand. The forest health under different intensity of uses is assessed in association with the collective behaviors and long-term purposes embedded in village social–cultural context. The study found no significant differences in forest succession and proportion in diameter at 1.3 m (dbh) class and height-class distribution of the forest under different use intensity. The forest for utilization also showed higher density and basal area of the local preferred species than the conservation forest. In the utilization forest, we also found a higher number of multipurpose and preferred species than in the conservation forest, which actually responded to the needs of the community in the long term to have more wood products (both firewood and timbers). The community-based forest management (CBFM) for utilization can also lead to natural regeneration and biodiversity similar to conservation forests. Through CBFM, forest resources can be managed to maintain the healthy condition under different intensities and respond to both community needs and external expectation. The findings also emphasize the importance of recognizing community needs and management objectives in watershed restoration and improving the productivity of forests under collective management.     

Ordering phenomena in quasi-one-dimensional organic conductors

Low-dimensional organic conductors could establish themselves as model systems for the investigation of the physics in reduced dimensions. In the metallic state of a one-dimensional solid, Fermi liquid theory breaks down and spin and charge degrees of freedom become separated. But the metallic phase is not stable in one dimension: as the temperature is reduced, the electronic charge and spin tend to arrange themselves in an ordered fashion due to strong correlations. The competition of the different interactions is responsible for which broken-symmetry ground state is eventually realized in a specific compound and which drives the system toward an insulating state. Here, we review the various ordering phenomena and how they can be identified by optic and magnetic measurements. While the final results might look very similar in the case of a charge density wave and a charge-ordered metal, for instance, the physical cause is completely different. When density waves form, a gap opens in the density of states at the Fermi energy due to nesting of the one-dimension Fermi surface sheets. When a one-dimensional metal becomes a charge-ordered Mott insulator, on the other hand, the short-range Coulomb repulsion localizes the charge on the lattice sites and even causes certain charge patterns. We try to point out the similarities and conceptional differences of these phenomena and give an example for each of them. Particular emphasis will be put on collective phenomena that are inherently present as soon as ordering breaks the symmetry of the system.