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Table of Content

      
    20 November 2013
    Volume 48 Issue 11
    Articles
    The cytotoxic effects of cadmium on barfin flounder ovary cells and its mechanism study
    XU Xiao-hui, FAN Ting-jun*, JING Yi, JIANG Guo-jian, YANG Xiu-xia, GE Yuan
    J4. 2013, 48(11):  1-6. 
    Abstract ( 320 )   PDF (2198KB) ( 681 )   Save
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    To investigate the cytotoxicity and its underlying mechanisms of cadmium chloride (CdCl2) to barfin flounder ovary (BFO) cells, in vitro cultured BFO cells were treated with CdCl2 at different concentrations and investigated toxicologically and cytologically in this study. Cytotoxicity results showed that the BFO cells were very sensitive to CdCl2, and their cell growth were inhibited in a concentration dependent manner by CdCl2 at a concentration above 10μmol/L. CdCl2 at a concentration above 40μmol/L could reduce the activities of superoxide dismutase (SOD) and glutathione peroxidase (GSTPx), and elevate the content of melondialdehyde (MDA) in BFO cells significantly. Mechanism results showed that typical morphological changes similar to those of apoptotic cells were found in BFO cells after treated with CdCl2 at a concentration above 40μmol/L. Obvious elevation of plasma membrane permeability in AO/EB double fluorescent staining and comet tails in single cell gel electrophoresis were both found in CdCl2 treated BFO cells. And the apoptotic ratio of BFO cells, the length and fluorescent intensity of comet tails from BFO cells were increased with the concentration of CdCl2. In conclusion, CdCl2 has significant cytotoxicity to BFO cells which was achieved by inducing cell apoptosis, which has laid a solid foundation for studies of the cytotoxicity and toxic mechanisms of cadmium and the other heavy metals.

    Studies on roots characteristics and correlations between the aerial and underground parts of Populus clones
    ZHAO Jian-cheng1, CAO Bang-hua1*, WU Li-yun2, ZHAO Pei1, HOU Rui1, NIU Qing-lin1
    J4. 2013, 48(11):  7-13. 
    Abstract ( 349 )   PDF (2187KB) ( 432 )   Save
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    A field experiment was conducted to investigate the roots characteristics and the correlations between the aboveground and underground parts of 20 Populus clones. The results showed that their root systems are mainly concentrated in 0~50cm soil layer, the root system is given priority to with horizontal root, vertical root basic disappearance, adventitious roots of small Angle, with the ground close to the level.Zhongzhu 1, NL 351, T 26 and zhongzhu 6 had larger total length of adventitious roots and zhongzhu 1, zhongzhu 6, NL 351 and I 107 adventitious roots in the total quantity is more which the ground diameter under 2cm accounted for 60%~80% of total number of adventitious roots. The growth indexes between the aerial and underground parts, exists significant correlation relationship, such as height, crown diameter, root weight and root length. The root/shoot ratio ranged from 0.23 to 0.45. The root length per unit shoot weight differences is bigger, the biggest for T26, the smallest for zhonghe 1. The root absorption efficiency was significantly negative correlated with the root/shoot ratio and the root length per unit shoot weigh, known as root redundancy. By cluster analysis, 20 Populus clones were divided into 3 groups and 6 categories at similarity coefficient 1.3. The results may provide a theoretical basis for further breeding improved clones of poplar and management.

    Gene cloning and polymorphism analysis of major histocompatibility
    complex(MHC) class IA gene from Oreochromis niloticus
    LI Tong-ming, ZHOU Fen-na, CUI Zhi-feng, JI Xiang-shan, WANG Hui*
    J4. 2013, 48(11):  14-22. 
    Abstract ( 338 )   PDF (3195KB) ( 385 )   Save
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    In this study, The PCR products by rapid amplification of cDNA ends polymerase chain reaction(RACE PCR) and touchdown PCR from the tilapia MHC class IA gene 3’ end were spliced and sequenced. The two 957bp cDNA sequences were newly obtained and named orni DAA*0101 and orni DAA*0102, respectively. They encode two newly discovered subtypes of the alleles from tilapia MHC class IA gene. Both of the two cDNA fragments contain a 666bp CDS region which consists of: a partial peptidebinding region, an immunoglobulin like region, a transmembrane region, a cytoplasmic region and with a 291bp 3’ UTR region. Homologous comparison shows that the cDNA sequences have two transition sites in 388bp and 426bp, but the amino acid sequences have only one single amino acid changed in the 130th site: the differences between Glutamic and Lysine. It is the first time to discover an amino acid variation in the relatively conservative IGC domain. The information newly obtained has an important value to reveal the relationship between high disease 20130419resistance and polymorphism of tilapia MHC class IA gene.

    Optimization the extraction process of effective compositions
    from Cortex Juglandis Mandshuricae
    FANG Wei1, WANG Yi-nan2, CAI Xiao-yan1, CAO Zhi-jia1, CHEN Hong-sheng1, ZHANG Yong-li1*
    J4. 2013, 48(11):  23-26. 
    Abstract ( 272 )   PDF (1019KB) ( 379 )   Save
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     To optimize the extraction process of effective compositions from Cortex Juglandis Mandshuricae. Cortex Juglandis Mandshuricae were extracted with ethanol,concentrated with ethyl acetate and chloroform and eluted gradiently on silica gel to get 3 kinds of flavonoids compounds. Orthogonal experiments were used to examine the best extraction process.  The best extraction process is to use 75% ethanol with 8 times the weight of Cortex Juglandis Mandshuricae scoured grist to reflux extract 3 times with 1.5h each time.The products identified by nuclear magnetic resonance methods. Myricetin, naringenin and hesperitin are the main contents of the Cortex Juglandis Mandshuricae, and the ethanol refluxing extraction process is feasible.

    Measurement study of cloud computing: a survey
    LIU Yang, QIN Feng-lin, GE Lian-sheng
    J4. 2013, 48(11):  27-35. 
    Abstract ( 403 )   PDF (925KB) ( 400 )   Save
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    The significant meaning of the measurement study of cloud computing for the application and development of cloud computing was highlighted, and then a comprehensive survey of the recent research advances in the monitoring system architecture and measurement technology was provided. The architecture and implementation of the typical monitoring systems for cloud computing were introduced and compared. Moreover, the categorization and comparison of the various approaches for the performance measurement of cloud computing were detailed analyzed, and then the research works in traffic measurement, topology measurement and reliability measurement were summarized. Finally, the future possible research directions in the measurement study of cloud computing were prospected.

    Design and implementation of a multi-path inter-domain
    routing simulator based on Click and NS2
    GUO Xiao-dong, JIAO Liang, QIU Yi-hong, GE Lian-sheng
    J4. 2013, 48(11):  36-43. 
    Abstract ( 444 )   PDF (1934KB) ( 448 )   Save
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    To meet the requirements for the simulation and performance evaluation of multi path inter domain routing protocols, a Click and NS2 based dedicated multi path inter domain routing simulator, named MIRS, is designed and implemented. MIRS is built by embedding the Click modular software router into the NS2 simulator. The source code with MIRS may run under a simulator as well as on existent actual systems with minor modifications, thereby efficiently shortening the period of experiment and evaluation. Moreover, MIRS can improve the accuracy of simulations by accurately describing the traffic forwarding behavior of multi path routers.  Simulation was conducted with a network topology as well as the real network topology of Shandong University respectively. The results not only indicate that multi path routing has a greater advantage in improving network performance than singlepath routing, but also show that MIRS is a useful and effective tool for evaluating multipath routing protocols.

    An overview of graph indexing technology
    LIU Ya-hui1, 2, LIU Chun-yang3*, ZHANG Tie-ying1, CHENG Xue-qi1
    J4. 2013, 48(11):  44-52. 
    Abstract ( 434 )   PDF (1187KB) ( 495 )   Save
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    Graph is a general data structure for modeling in varies of fields. With the development of information and network technology, it is widely applied for representing relationship between entities. In this way, most valuable information is hidden in entities. So as to mine the hidden information in graph, related researches on this topic are becoming popular. The key to solve the problem is how to efficiently search on graph. In the graph database, there are two kinds of graph data sets: Single Graph and Graphs. However, it is time consuming in searching either Single Graph or Graphs. Thus, graph indexing is proposed to be a promising way to minimize the search space on graph in order to speed up graph search algorithms. This paper categorizes graph search into subgraph search and supergraph search.They are subdivided into smaller categories in terms of selected graph structure in building graph indexing. Meanwhile, the paper describes graph indexing building methods and detailed explanation on typical graph indexing. It compares kinds of graph indexing and analyzes their specific applications. At last, it discusses the development trend of graph indexing.

    Chinese spam microblog filtering based on the fusion of
    multi-angle features
    YU Ran 1,2, LIU Chun-yang3*, JIN Xiao-long 1, WANG Yuan-zhuo 1, CHENG Xue-qi 1
    J4. 2013, 48(11):  53-58. 
    Abstract ( 566 )   PDF (1090KB) ( 536 )   Save
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    As microblog contains valuable information, data analysis on microblog such as topic detection has become a research hotspot. Due to the high flexibility of microblog′s content and form, noisy data is a big challenge for microblog analysis. Therefore, no effective method has been developed for nonpublic topic Chinese spam microblog filtering until now. To fill this gap, a new method was proposed to fuse multi-angle features extracted from both the content and structure of microblog. The fused features were then employed for filtering spam microblog with classifiers. Experiments on real data demonstrate that the fusion of multi-angle features can effectively improve the performance of spam filtering.

    Research on themes recommendation in microblogging
    scenario based on neighbor-user profile
    ZHENG Jian-xing, ZHANG Bo-feng*, YUE Xiao-dong, CHENG Ze-yu
    J4. 2013, 48(11):  59-65. 
    Abstract ( 480 )   PDF (1621KB) ( 418 )   Save
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    In micro-blogging social network, micro-blog content is short text and covered less themes. In addition, themes in network changed fast and user′s interests updated frequently. Existing user profile can′t accurately depict various interests of user. Group of users with high awareness can form neighbor set of user, whose topic interests can comprehensively reflect diverse interests of target user. A neighbor-user profile implementing algorithm was proposed by building neighbor theme interest set of ontology user profile and calculating update of neighbor theme interest degree of ontology user profile in terms of neighbor set of target user. Experiments show that the accuracy of micro-blogging themes recommendation based on neighbor-user profile performs better than that of traditional individual user profile in the micro-blogging social network platform.

    Store review spam detection based on quantitative sentiment
    PENG Qing-xi, QIAN Tie-yun
    J4. 2013, 48(11):  66-72. 
    Abstract ( 385 )   PDF (1260KB) ( 399 )   Save
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    A novel concept of quantitative sentiment was proposed, which means the sentiment score of the review. The sentiment score is  derived from the natural language text of the review. To calculate the quantitative sentiment, the dependency relationships between sentiment words are  discussed. A quantitative sentiment algorithm of the sentiment sentence is  presented. Furthermore, the relationship between quantitative sentiment and spam reviews is  discussed. A series of prediction rules are  established through intuitive observation. In the end, the store reviews are  analyzed by establishing a time series with quantitative sentiment as indicator. The spam reviews are  detected efficiently. Experimental results show that the proposed method  has good detection result and outperform existing methods in detecting sore review spam.

    The method of latent friend recommendation based on the trust relations
    HUANG Liang, DU Yong-ping
    J4. 2013, 48(11):  73-79. 
    Abstract ( 370 )   PDF (2088KB) ( 411 )   Save
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    E-commerce has greatly changed people′s daily activity and consumption behavior. Mining the potential platform friends effectively has become an important demand for services in the e-commerce. We present an approach for the friend recommendation by the consideration of user interest factors and trust factors. The mixed trust network is designed and built and it contains the authority value and the trust information between the users. In order to achieve personalized friend recommendation, the trust evaluation value and the similarity value based on the interest are combined to measure the association between the users. The experiment on the Epinions dataset is carried  and the  precision, recall and F-value are used as the evaluation metric. Compared to other system of precision 10%~15% and recall 10%~20%,  the best performance of precision 22.47% and recall 21.15%. The results show that the proposed method effectively improves the recommended performance.

    A temporal-aware model for search engine
    ZHANG Nai-zhou1, CAO Wei 2, CHEN Ke-rui 1, LI Shi-jun3
    J4. 2013, 48(11):  80-86. 
    Abstract ( 336 )   PDF (1793KB) ( 503 )   Save
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    Many of web pages have freshness and nowadays many users’ queries are closely related to this freshness. For current search engines, however, there are still some problems in handling many queries with time property. A new temporal aware search engine model was presented, which introduces the user query understanding, index structure and page ranking algorithm based on the temporal aware processing into architecture of search engine. This model aims at overcome the shortcoming of the traditional keywordbased search engine in dealing with the time based queries. Extensive experiments are carried out in a real Web environment, and the experimental results show the effectiveness of the model.

    Multi-source data fusion based on the expand vector space model
    CHEN Ke-rui, PAN Jun
    J4. 2013, 48(11):  87-92. 
    Abstract ( 490 )   PDF (860KB) ( 533 )   Save
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    The expansion of ontology resource is one of the key for the whole natural language processing. Since the information obtained traditionally from single data source could not reflect the overall picture and the coverage rate doesn’t reach targeted one, the construction of an integrated data management platform would be required to store and organize data sources by classification. The AVP data platform was  proposed firstly. In the process of data construction on AVP platform, the most important issue is to integrate multi-source data, in other words, to perform semantic role labeling on web data coming from different sources, to identify ambiguous entries, and to eventually merge into data warehouses which use sense as the basic unit. An automated method of semantic role matching has been suggested, and it would solve the problem of semantic role matching resulted from multi-source data fusion. The basic idea is to use attribute-values of entries as the feature template, and then apply expand vector space model to identity ambiguity for entries while assisted by the cooccurrence probability of attribute values. Through the massive experimental contrast, the system mentioned above performed very well in all respects. The theory and algorithm proposed in this paper could solve the problem of semantic role matching existed in multi-source data fusion effectively.

    The multi-scale retinex algorithm for image enhancement based on
    sub-band weighting fusion
    FANG Zhi-jun, LIU Xin-yun, WU Shi-qian, ZHENG Wen-juan
    J4. 2013, 48(11):  93-98. 
    Abstract ( 403 )   PDF (2436KB) ( 532 )   Save
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    The Retinex model refers to human perception of lightness and color. The multi-scale Retinex(MSR) algorithm, which is high dynamic range, color constancy and high color fidelity, is widely used in low-light image enhancement. A novel multi-scale retinex method based on sub-band weighting fusion for image enhancement was proposed. First, hybrid intensity transfer function was used to have retinex outputs in different scales. Then the retinex outputs were decomposed into non-overlapping spectral sub-bands. Image enhancement was processed in each sub-band. Final, the resulted image was fused by weighting every point of each Retinex outputs. The experimental results show that the proposed algorithm effectively enhances the contrast of original image and achieve a visual-pleasing and colorvivid outputs.

    A space-time-efficient multi-category text categorization algorithm
    LIU Wu-ying, YI Mian-zhu, ZHANG Xing
    J4. 2013, 48(11):  99-104. 
    Abstract ( 303 )   PDF (1024KB) ( 372 )   Save
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    Low space-time complexity is always the expected performance of multi-category text categorization algorithms. The investigation of token frequency distribution in the set of news documents validates that the token frequency distribution obeys the ubiquitous power law. According to the distribution property of power law, a novel data structure of multi-category token frequency index is designed and based on which a multi-category text categorization algorithm with low space-time complexity is propose. The experimental results on the TanCorp data set show that the proposed algorithm is space-time-efficient in the application of multi-category news document categorization.

    Mean model based IBCF algorithm
    QI Li-li, SUN Jing-yu*, CHEN Jun-jie
    J4. 2013, 48(11):  105-110. 
    Abstract ( 6204 )   PDF (1451KB) ( 580 )   Save
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    The item-based collaborative filtering algorithm (IBCF),a recommendation algorithm with high precision,simple and easy to use in actual system, is widely used in the field of recommendation systems. But it meets a higher computational time complexity for similar calculation because of the long length of item vector. In this paper, a sampled approach firstly is suggested to represent an item vector called mean model item vector representation through analyzing theory of IBCF algorithm, to solve the problem of the long length of item vector and cut down the computational time. Experiments using Movie Lens datasets show that the algorithm is very efficient to cut down the computational time on the premise of accuracy. Furthermore, some right sampling methods can be used to optimize the calculation method of similarity in order to meet practical application requirement.