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Solution of the Poisson-Boltzmann Equation for a Cylindrical Particle with a Limited Length: Functional Theoretical Approach

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Chemical Research in Chinese Universities 2005年第5期21卷 592-596页

作者： WANG Zheng-wu GU Ming-yan zhang ge-xin YI Xi-zhang School of Chemical and Material Engineering Southern Yangtze University Wuxi 214036 P. R. China Institute of Theoretical Chemistry Shandong University Jinan 250100 P. R. China

With the help of the method of separation of variables and the Debye-Hüchel approximation, the Poisson-Boltzmann equation that describes the distribution of the potential in the electrical double layer of a cylindrical particle with a limited length has been firstly solved under a very low potential condition. Then with the help of the functional analysis theory this equation has been further analytically solved under general potential conditions and consequently, the corresponding surface charge densities have been obtained. Both the potential and the surface charge densities cointide with those results obtained from the Debye-Hüchel approximation when the very low potential of zeψ〈〈kT is introduced.

关键词： Cylindrical particle Electrical double layer Poisson-Boltzmann equation Surface charge density,Functional analysis theory

Metal-organic-framework-derived copper-based catalyst for multicomponent C-S coupling reaction

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Chinese Journal of Chemical Engineering 2024年第6期70卷 1-8页

作者： Lixin Chen Hui zhang Linxi Hou xin ge Key Laboratory of Synthetic and Biological Colloids Ministry of EducationSchool of Chemical and Material EngineeringJiangnan UniversityWuxi 214122China Department of Materials-Oriented Chemical Engineering School of Chemical EngineeringFuzhou UniversityFuzhou 350116China Qingyuan Innovation Laboratory Quanzhou 362801China

Copper-based metal-organic frameworks(Cu-MOFs)are a promising multiphase catalyst for catalyzing C-S coupling reactions by virtue of their diverse structures and ***,the unpleasant odor and instability of the organosulfur,as well as the mass-transfer resistance that exists in multiphase catalysis,have often limited the catalytic application of Cu-MOFs in C-S coupling *** this paper,a Cu-MOFs catalyst modified by cetyltrimethylammonium bromide(CTAB)was designed to enhance mass transfer by increasing the adsorption of organic substrates using the long alkanes of ***,elemental sulfur was used to replace organosulfur to achieve a highly efficient and atom-economical multicomponent C-S coupling reaction.

关键词： Design Copper-based metal-organic frameworks (Cu-MOFs) Adsorption C-S coupling reaction Multiphase reaction

资本要素市场分割、金融脆弱性与经济高质量发展的互动关系

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湖南财政经济学院学报 2024年第4期40卷 66-77页

作者：李程韩明月张馨戈魏仝飞天津工业大学经济与管理学院天津300387

对资本要素市场分割、金融脆弱性和高质量发展指数进行测度,发现资本要素市场分割指数呈现波动中下降的趋势,金融脆弱性呈现波动中上升趋势,经济高质量发展指数呈现上升的趋势,并使用VAR模型研究三者的关系,研究表明:资本要素市场分割... 详细信息

对资本要素市场分割、金融脆弱性和高质量发展指数进行测度,发现资本要素市场分割指数呈现波动中下降的趋势,金融脆弱性呈现波动中上升趋势,经济高质量发展指数呈现上升的趋势,并使用VAR模型研究三者的关系,研究表明:资本要素市场分割对经济发展质量具有负向影响,并提高了金融脆弱性;金融脆弱性对资本要素市场分割具有非线性作用,高质量发展降低了资本要素市场分割;经济高质量发展和金融脆弱性具有互相促进的作用。由此,结论反映出,经济高质量发展过程中,应该注意促进要素市场统一建设,并将金融风险控制在一定的范围内。

关键词：资本要素市场分割金融脆弱性经济高质量发展 VAR模型

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表皮生长因子受体在非小细胞肺癌中的表达及与患者临床特征的关系

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癌症进展 2024年第12期22卷 1357-1359,1379页

作者：李俏然赵信喜张新阁刘向阳驻马店市中心医院病理科河南驻马店463000

目的探讨表皮生长因子受体(EGFR)在非小细胞肺癌(NSCLC)中的表达及与患者临床特征的关系。方法收集95例NSCLC患者的NSCLC组织和癌旁正常组织,采用免疫组化法检测各组织中EGFR表达情况,比较不同临床特征NSCLC患者NSCLC组织中的EGFR表达... 详细信息

目的探讨表皮生长因子受体(EGFR)在非小细胞肺癌(NSCLC)中的表达及与患者临床特征的关系。方法收集95例NSCLC患者的NSCLC组织和癌旁正常组织,采用免疫组化法检测各组织中EGFR表达情况,比较不同临床特征NSCLC患者NSCLC组织中的EGFR表达情况。结果NSCLC组织中EGFR阳性表达率明显高于癌旁正常组织,差异有统计学意义(P﹤0.01)。有淋巴结转移和预后差NSCLC患者NSCLC组织中EGFR阳性表达率分别高于无淋巴结转移和预后良好患者,差异均有统计学意义(P﹤0.05)。结论EGFR在NSCLC患者中高表达,EGFR检测可用于诊断NSCLC,并预测预后,与患者淋巴结转移密切相关。

关键词：表皮生长因子受体非小细胞肺癌免疫组化法预后淋巴结转移

Comparison of tailpipe carbonyls and volatile organic compounds emissions from in-use gasoline/CNG bi-fuel vehicles

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Journal of Environmental Sciences 2024年第1期135卷 619-629页

作者： Jiachen Li Yunshan ge xin Wang Mengzhu zhang Haohao Wang School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

Ground-level ozone contamination has been globally an urban air quality issue,particularly for China,which has recently made significant progress in purifying its *** exhaust emissions from motor vehicles,predominantly carbonyls and volatile organic compounds(VOCs),are among the leading contributors to ozone *** this chassislevel study,the unregulated emissions from five China-5 certified gasoline/CNG bi-fuel taxis,along with their ozone forming potential(OFP),were *** is found that carbonyls and VOCs were mainly emitted during the starting phase no matter the engine was cold or *** to gasoline,CNG fueling reduced VOCs emissions on a large scale,especially in the starting phase,but had elevated *** a fleet average,CNG fueling derived 15%and 46%less OFP than gasoline in cold-and hot-start tests,*** contributed to over 90%of the total OFP of the *** terms of alleviating ground-level ozone contamination,CNG is a feasible alternative to gasoline on light-duty vehicles.

关键词： CNG Gasoline Carbonyls VOCs OFP

Studies on the Cloud Points of Nonionic Surfactants with QSPR

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Chemical Research in Chinese Universities 2007年第6期23卷 715-719页

作者： CHEN Mei-ling WANG Zheng-wu zhang ge-xin GU Jin CUN Zhe TAO Fu-ming School of Chemistry and Materials Engineering Southern Yangtze University Wuxi 214122 P. R. China Department of Food Science ＆ Technology School of Agriculture and Biology Shanghai Jiaotong University Shanghai 201101 P. R. China Department of Chemistry and Biochemistry California State University Fullerton CA 92834 USA

With quantum chemical parameters, topological indexes, and physical chemistry parameters as descriptors, a quantitative structure-property relationship（QSPR） has been found for the cloud points of four series of nonionic surfactants（ a total of 65 surfactants）. The best-regressed model includes six descriptors, and the correlation coefficient of multiple determination is as high as 0. 962.

关键词： Nonionic surfactants Cloud point Quantitative structure-property relationship

Cross-Project Software Defect Prediction Based on SMOTE and Deep Canonical Correlation Analysis

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Computers, Materials & Continua 2024年第2期78卷 1687-1711页

作者： xin Fan Shuqing zhang Kaisheng Wu Wei Zheng Yu ge School of Software Nanchang Hangkong UniversityNanchang330063China Software Testing and Evaluation Center Nanchang Hangkong UniversityNanchang330063China

Cross-Project Defect Prediction(CPDP)is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target ***,existing CPDP methods only consider linear correlations between features(indicators)of the source and target *** models are not capable of evaluating non-linear correlations between features when they exist,for example,when there are differences in data distributions between the source and target *** a result,the performance of such CPDP models is *** this paper,this paper proposes a novel CPDP method based on Synthetic Minority Oversampling Technique(SMOTE)and Deep Canonical Correlation Analysis(DCCA),referred to as *** Correlation Analysis(CCA)is employed to address the issue of non-linear correlations between features of the source and target projects.S-DCCA extends CCA by incorporating the MlpNet model for feature extraction from the *** redundant features are then eliminated by maximizing the correlated feature subset using the CCA loss ***,cross-project defect prediction is achieved through the application of the SMOTE data sampling *** Under Curve(AUC)and F1 scores(F1)are used as evaluation *** paper conducted experiments on 27 projects from four public datasets to validate the proposed *** results demonstrate that,on average,our method outperforms all baseline approaches by at least 1.2%in AUC and 5.5%in F1 *** indicates that the proposed method exhibits favorable performance characteristics.

关键词： Cross-project defect prediction deep canonical correlation analysis feature similarity

High-temperature wetting behavior between slag and refractory

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Journal of Iron and Steel Research International 2024年第6期31卷 1304-1319页

作者： Yong-xin Wang Ya-ge Li Ya-bo Gao Zhong Huang Hai-jun zhang The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and TechnologyWuhan 430081HubeiChina

Slag corrosion is one of the main factors of the damage of refractory,and its primary manifestations involve the melting of refractory in slag and the slag penetration into refractory,both of which are highly related to the wetting behavior between slag and *** high-temperature wettability could be characterized by parameters including the surface tension,adhesion work,and spreading coefficient of the slag on refractory surface,and it could be suppressed by altering the slag/refractory interface,thus resulting in an improved anti-corrosion *** this,the key knowledges of the slag corrosion,theory of wetting behavior and test of high-temperature contact angle were firstly ***,the major factors influencing the high-temperature slag wetting behavior were discussed based on the aspects of slag composition,refractory composition,and surface ***,the future research direction was proposed in this field.

关键词： High-temperature wetting Refractory Slag corrosion Surface tension

Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 51-65页

作者： Yonghua Song ge Chen Hongcai zhang State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China School of Electrical and Computer Engineering Purdue UniversityWest LafayetteIN 47907 USA

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks(ADNs)to facilitate integration of distributed renewable *** to unavailability of network topology and line impedance in many distribution networks,physical model-based methods may not be applicable to their *** tackle this challenge,some studies have proposed constraint learning,which replicates physical models by training a neural network to evaluate feasibility of a decision(i.e.,whether a decision satisfies all critical constraints or not).To ensure accuracy of this trained neural network,training set should contain sufficient feasible and infeasible ***,since ADNs are mostly operated in a normal status,only very few historical samples are ***,the historical dataset is highly imbalanced,which poses a significant obstacle to neural network *** address this issue,we propose an enhanced constraint learning ***,it leverages constraint learning to train a neural network as surrogate of ADN's ***,it introduces Synthetic Minority Oversampling Technique to generate infeasible samples to mitigate imbalance of historical *** incorporating historical and synthetic samples into the training set,we can significantly improve accuracy of neural ***,we establish a trust region to constrain and thereafter enhance reliability of the *** confirm the benefits of the proposed method in achieving desirable optimality and feasibility while maintaining low computational complexity.

关键词： Deep learning demand response distribution networks imbalanced data optimal power flow