A Statistical Analysis on Papers and Authors in Wuhan University Journal of Natural Sciences in 2003

The author of this article counts and analyzes the papers and authors printed in 2003 Wuhan University Journal of Natural Sciences by means of bibliometric statistical methods, of which the characteristics of papers and authors are expounded. The result shows that the ratio of reprinting of this journal has been increased and the areas where the authors come from and their organization scattered in the whole world are widened as well, which implies a better-known fame of the journal. Key words Wuhan University Journal of Natural Sciences - papers analysis - authors analysis - statistical analysis CLC number G 353.1 Biography: HU Min(1961-), famale, Associate professor, research direction; editing science and biochemistry.

Published the papers of HPLC-MS analysis—Chemical drug

Sun Guoxiang, Ding Nan, Song Yuqing, Wang Zhen, Song Liangwei. Determination of Guaiacol salicylate in Guacetisal by HPLCmethod and qualitative identification of relevant substances by HPLC-MS

Published the papers of GC-MS analysis—Chemical drug

Song Qi, Liu Hu; Gao Shu. Screening and quantitative analysis of volatile markers in the breath of patients with breast cancer Acta Universitatis Medicinalis Anhui, 2010, 45（01） ：76-79.

Published the papers of HPLC-MS analysis—Traditional Chinese medicine

Medicinal materials Ma Chenchen, Li Bailin, Ou Jie, Wang Jing, Zhao Junhong. Detection of N-acyl-homoserine lactones class signal molecules of quorum sensing secreted by bacteria using high performance liquid chromatography-mass spectrometry/ mass spectrometry

Analysis on cited times of papers published in Neural Regeneration Research

Introduction Publication Name=Neural Regeneration Research （NRR） Timespan=2008-2011. Databases=SCI-EXPANDED, SSCI, A＆HCI, CPCI-S, CPCI-SSH. Web of Science Categories： CELL BIOLOGY （938）, NEUROSCIENCE （938） Document Types： ARTICLE （922）, REVIEW （13）, EDITORIAL MATERIAL （2）, LETTER （1） Search time： 23/06/2011 A total of 938 articles published till the search time in NRR are searched, including 315 papers published in 2008, 185 in 2009, 321 in 2010, and 117 in 2011. Totally 111 papers have been cited and the total number of citations is 171. There are 76 self-citations, and 95 non-self citations, which are scattered in 85 journals. The citation situations are listed as follows.

Arc-length technique for nonlinear finite element analysis

Nonlinear solution of reinforced concrete structures, particularly complete load-deflection response, requires tracing of the equilibrium path and proper treatment of the limit and bifurcation points. In this regard, ordinary solution techniques lead to instability near the limit points and also have problems in case of snap-through and snap-back. Thus they fail to predict the complete load-displacement response. The arc-length method serves the purpose well in principle, received wide acceptance in finite element analysis, and has been used extensively. However modifications to the basic idea are vital to meet the particular needs of the analysis. This paper reviews some of the recent developments of the method in the last two decades, with particular emphasis on nonlinear finite element analysis of reinforced concrete structures.

Distance-Based Detection of Ag^(+) with Gold Nanoparticles-Coated Microfluidic Paper

In this study,we developed a microfluidic paper analysis device(μPAD)for distance-based detection of Ag^(+)in water.TheμPAD was manufactured by wax printing method on filter paper.Then,a layer of gold nanoparticles(AuNPs)was deposited and ascorbic acid was printed on the channel.In the detection,Ag^(+)was reduced by ascorbic acid and coated on the surface of the AuNPs on the channel,forming Au@Ag core/shell nanoparticles.Based on the capillary flow principle,diff erent concentrations of Ag^(+)formed diff erent distances of color ribbons.Thus,quantitative detection of Ag^(+)can be achieved by measuring the distance of the color ribbon.The detection limit of this method was as low as 1 mg·L^(-1)within 15 min and the interference of common metal ions in water can be eliminated.In conclusion,this method had successfully realized the leap from colorimetry to direct reading,realizing fast read and easy manipulation with low-cost.

Evaluation of employee profiles using a hybrid clustering and optimization model Practical study

Purpose-The purpose of this paper is to introduce an evaluation methodology for employee profiles that will provide feedback to the training decision makers.Employee profiles play a crucial role in the evaluation process to improve the training process performance.This paper focuses on the clustering of the employees based on their profiles into specific categories that represent the employees’characteristics.The employees are classified into following categories:necessary training,required training,and no training.The work may answer the question of how to spend the budget of training for the employees.This investigation presents the use of fuzzy optimization and clustering hybrid model(data mining approaches)as a fuzzy imperialistic competitive algorithm(FICA)and k-means to find the employees’categories and predict their training requirements.Design/methodology/approach-Prior research that served as an impetus for this paper is discussed.The approach is to apply evolutionary algorithms and clustering hybrid model to improve the training decision system directions.Findings-This paper focuses on how to find a good model for the evaluation of employee profiles.The paper introduces the use of artificial intelligence methods(fuzzy optimization(FICA)and clustering techniques(K-means))in management.The suggestion and the recommendations were constructed based on the clustering results that represent the employee profiles and reflect their requirements during the training courses.Finally,the paper proved the ability of fuzzy optimization technique and clustering hybrid model in predicting the employee’s training requirements.Originality/value-This paper evaluates employee profiles based on new directions and expands the implication of clustering view in solving organizational challenges(in TCT for the first time).