基于词汇吸引与排斥模型的共现词提取

:共现词提取在信息挖掘和自然语言处理中有着十分重要的地位。而传统的共现词提取方法仅仅局 限在单一的一种统计量上,其结果十分不精确,需要人工再进行整理。本文提出了一种基于词汇吸引与排斥 模型的共现词提取算法,并通过将多种常用统计量进行组合,改进了算法的效果。在开放测试环境下,所提取 的共现词其用户感兴趣度为60187 %。将该算法应用于基于Web 的共现词检索系统,在速度和共现词的提取 精度上均取得了比较好的效果。福建省自然科学基金资助项目(A0310009) ;福建省重点科技资助项目(2001J005

Pyrethroids as Promising Marine Antifoulants: Laboratory and Field Studies

【英文摘要】Due to the regulations and bans regarding the use of traditional toxic chemicals against marine fouling organisms and the practical impediments to the commercialization of natural product antifoulants, there is an urgent need for compounds that are antifouling-active, environmentally friendly, and have a potential for commercial application. In this study, a series of common, commercially available pyrethroid products, which are generally used as environmentally safe insecticides, was evaluated for antifouling activity in the laboratory using an anti-settlement test with cyprids of the barnacle Balanus albicostatus and also in a field experiment. Laboratory assay showed that all eleven pyrethroids (namely, rich d-trans-allethrin, Es-biothrin, rich d-prallethrin, S-prallethrin, tetramethrin, rich d-tetramethrin, phenothrin, cyphenothrin, permethrin, cypermethrin, and high active cypermethrin) were able to inhibit barnacle settlement (EC50 range of 0.0316 to 87.00 μg/ml) without significant toxicity. Analysis of structure–activity relationships suggested that the cyano group at the α-carbon position had a significant influence on the expression of antifouling activity in pyrethroids. In the field, the antifouling activity of pyrethroids was further confirmed, with the most potent pyrethroids being cypermethrin and high active cypermethrin, which displayed efficiency comparable with that of tributyltin. In summary, our investigation indicated that these pyrethroids have a great and practical commercial potential as antifouling agents

植物查尔酮合成酶超基因家族的分子进化

查尔酮合成酶(CHS)超基因家族又称为植物类型III聚酮合酶超基因家族,其编码酶通过催化和合成一系列结构多样及生理活性各异的次生代谢物,在植物生长发育和适应环境的过程中扮演着重要角色。为全面了解CHS超基因家族在植物中的进化规律,重建其进化历史,该研究利用14种具有全基因组数据的代表植物,通过生物信息学手段,深入挖掘和分析了不同植物类群基因组中查尔酮合成酶超基因家族的成员构成,推测了其可能的扩增机制和功能分歧,并探讨了该超基因家族在植物中的总体进化趋势。结果共识别144条具有表达信息的同源序列,它们全部来自9种陆生植物的基因组,藻类植物基因组中没有发现相关序列。系统发育和进化分析表明,CHS超基因家族的起源古老,它们可能为适应复杂的生态环境而出现在早期的陆生植物中,之后在长期的进化过程中不断发生谱系的特异扩张和拷贝丢失,最后通过功能分歧的形式在不同植物类群中被分别固定。此外,进化检验也显示,尽管CHS超基因家族内部发生了多样的遗传改变,但整个超基因家族仍处于强烈的纯化选择之下,并且个体基因中也无任何单氨基酸位点受到正向选择的影响

Calibrated Parameters of Likelihood Ratio Test Based on Probability Integral Translation

提出有关列联表面貌的预测和似然比检验的预测误差推理方法,用于单向有序列联表和小样本的预测.其目的是提供预测准确度和高效的分析工具,以及更普遍的预测检验能力.仿真实验显示,该方法可以用于通常的小样本.若似然比检验所得到的P值结论与单向有序列联表的面貌不一致时,应依据基于概率积分变换的0.074校准参数修正P值误差,使P值结论与单向有序列联表的面貌一致.我们将似然比检验的预测误差推理方法应用到胃病的分析,得到证型的胃痛严重度参数与列联表面貌的预测一致的结果.We develop procedures for inference about the predictions of contingency table profile and the prediction errors of likelihood ratio test,when there is a contingency table where one factor as ordinal variable and with small sample sizes.The aim is to provide tools for analysis of predictive accuracy and efficiency,and,more generally,of predictive ability.Simulations indicate that the procedures can work well in samples of size typically available.If P-value conclusions of likelihood ratio test do not consistent with profile predictions of contingency table,we should revise P-value error of 0.074 calibration parameters based on probability integral translation,make P-value conclusion consistent with profile predictions of contingency table with one factor as ordinal variable.国家自然科学基金(60803078

Rules Mining Research on the Eye Features Computation in the Spirit Diagnosing of TCM

中医客观化中有一个很重要的问题是根据量化的人体特征推导出人体的状态.提出了一种用于中医察目望神客观化中从眼部特征推导出人体“神“的状态的规则挖掘方法.首先给出了视频采集方法,接着使用类-属性依赖最大化方法(CAIM)对眼部特征数据进行离散化形成规则挖掘中的属性区间,然后使用云模型进行关联规则挖掘得到大量候选规则,再对3种互补的规则裁剪方法进行修改和组合用于候选规则的整理,并形成最终的规则集合.利用交叉验证法检验规则挖掘的效果,得到了93%的平均精确度,达到了很好的效果.Quantitative features reflecting the human body′s appearance are very helpful in diagnosing human′s health state in Traditional Chinese Medicine(TCM).This paper presents a novel application of eye features computation in the Spirit diagnosing,for which rules describing "the Spirit" state are mined by the quantitative features regarding the human eyes.With videos capturing the eye condition during a short time,a set of eye features are extracted.On the basis of it,attribute intervals of the eye feature space are generated by the CAIM.Then,a various of candidate rules are mined by the association rule mining based on the Cloud model.Finally,three complementary rule-pruning methods are modified and combined to trim the boring candidate rules.The cross validation test for mined rules reaches the average accuracy of 93%,which shows the good performance of the proposed method.国家自然科学基金项目(60672018);深圳市科技计划基础研究项目(JC200903180630A