高州市某农村小学乙型流感聚集性疫情调查分析

目的 分析2012年高州市某农村小学聚集性乙型流行性感冒疫情发生的原因及传染来源,为防治流行性感冒提供科学依据.方法 利用流行性感冒的个案调查表、实验室检测结果、现场卫生学资料进行流行病学分析.结果 本次聚集性疫情的发生始于2012年2月18日,首发病例的传染来源不明,最后1例病例发病时间为2月21日,暴露人口263人,发病9例,罹患率为3.4％,无死亡病例.发病年龄分布在13～14岁年龄组,无性别差异,由于首发病例为住宿生,住宿生发病率远高于走读生.采集9例病例血清标本,6例乙型流行性感冒病毒核酸检测阳性.结论 这是一起乙型流行性感冒的聚集性疫情,传播途径为空气飞沫传播;早发现、早报告、早隔离和接种流行性感冒疫苗是控制流行性感冒疫情最为关键的措施.     

“十一五”期间我国中医外科学研究热点分析

以中国学术文献网络出版总库2006-2010年间的329篇中医外科文献为分析对象,基于文献聚类及高频关键词的社会网络分析方法,对文献主题及相关主题词进行系统分析,揭示"十一五"期间中医外科在教学、临床等方面的研究热点与主题分布。     

针刺对脑功能性网络连接的影响

目的:通过研究脑功能性网络的连接特性探讨针刺对脑部的作用。方法:首先设计了针刺足三里采集脑电(EEG)信号的实验;然后采用相干估计法分析9位志愿者(6位男性,3位女性)针刺前、针刺中和针刺后各阶段EEG信号的同步特性并建立相应的脑同步性矩阵和脑功能性网络。结果:通过针刺中、针刺后与针刺前的状态相比观察到,针刺足三里会显著提高EEG信号的δ频段和γ频段的同步性。通过对脑功能性网络的节点度分析发现,针刺足三里会增加脑部区域的度;进一步分析发现针刺会大量增加δ频段内脑部远端区域间长距离连接的数目,从而增强脑功能性网络的聚类系数,降低其平均路径长度。结论:针刺足三里能够协调脑部不同区域间的电活动,具有提高脑部远端区域间信息交流的效果,并且这种效果是对脑部有益的。     

Clustering and switching processes in semantic verbal fluency in the course of Alzheimer's disease subjects: results from the PAQUID longitudinal study

Reduced semantic fluency performances have been reported in the preclinical phase of Alzheimer's disease (AD). To investigate the cognitive processes underlying this early deficit, this study analyzed the verbal production of predemented subjects for the animals category with the qualitative parameters related to clustering (i.e. the ability to generate words belonging to semantic subcategories of animals) and switching (i.e. the ability to shift from one subcategory to another) proposed by Troyer. This qualitative analysis was applied to the PAQUID (Personnes Agées QUID) cohort, a 17-year longitudinal population-based study. The performances on the animal verbal fluency task of 51 incident cases of possible and probable AD were analyzed at the onset of dementia, 2 years and 5 years before dementia onset. Each case was matched for age, sex and education to two control subjects leading to a sample of 153 subjects. The mean cluster size and the raw number of switches were compared in the two samples. The results revealed a significantly lower switching index in the future AD subjects than in the elderly controls including 5 years before dementia incidence. A significant decline in this parameter was evidenced all along the prodromal phase until the clinical diagnosis of dementia. In contrast, the mean cluster size could not discriminate the two groups. Therefore the results support the hypothesis that impaired shifting abilities - rather than semantic memory storage degradation - could explain the early decline in semantic fluency performance occurring in the predementia phase of AD.     

ICP: A novel approach to predict prognosis of prostate cancer with inner-class clustering of gene expression data

Prostate cancer has heterogeneous characteristics. For that reason, even if tumors appear histologically similar to each other, there are many cases in which they are actually different, based on their gene expression levels. A single tumor may have multiple expression levels with both high-risk cancer genes and low-risk cancer genes. We can produce more useful models for stratifying prostate cancers into high-risk cancer and low-risk cancer categories by considering the range in each class through inner-class clustering. In this paper, we attempt to classify cancers into high-risk (aggressive) prostate cancer and low-risk (non-aggressive) prostate cancer using ICP (Inner-class Clustering and Prediction). Our model classified more efficiently than the models of the algorithms used for comparison. After discovering a number of genes linked to prostate cancer from the gene pairs used in our classification, we discovered that the proposed method can be used to find new unknown genes and gene pairs which distinguish between high-risk cancer and low-risk cancer.     

How language can help discrimination in the Neural Modelling Fields framework

The relationship between thought and language and, in particular, the issue of whether and how language influences thought is still a matter of fierce debate. Here we consider a discrimination task scenario to study language acquisition in which an agent receives linguistic input from an external teacher, in addition to sensory stimuli from the objects that exemplify the overlapping categories that make up the environment. Sensory and linguistic input signals are fused using the Neural Modelling Fields (NMF) categorization algorithm. We find that the agent with language is capable of differentiating object features that it could not distinguish without language. In this sense, the linguistic stimuli prompt the agent to redefine and refine the discrimination capacity of its sensory channels.     

气相色谱数据的聚类分析法评价中药厚朴的质量

本文对中药厚朴进行气相色谱分析,根据样品组分的相对含量,用样品的多指标点绘法,对这些样品进行聚类分析,为评价其真伪及质量的优劣进行了初步的尝试,获得了一定结果。     

分类指标等价模糊聚类法及应用

本文给出了分类指标等价模糊聚类法的数学方法和应用实例。此法简便,能客观和真实的反映被分类对象所固有的特性,并具直观性,避免了许多聚类方法的主观性。在实际应用中聚类合理     

Segmentation of retinal blood vessels using a novel clustering algorithm (RACAL) with a partial supervision strategy

In this paper, segmentation of blood vessels from colour retinal images using a novel clustering algorithm with a partial supervision strategy is proposed. The proposed clustering algorithm, which is a RAdius based Clustering ALgorithm (RACAL), uses a distance based principle to map the distributions of the data by utilising the premise that clusters are determined by a distance parameter, without having to specify the number of clusters. Additionally, the proposed clustering algorithm is enhanced with a partial supervision strategy and it is demonstrated that it is able to segment blood vessels of small diameters and low contrasts. Results are compared with those from the KNN classifier and show that the proposed RACAL performs better than the KNN in case of abnormal images as it succeeds in segmenting small and low contrast blood vessels, while it achieves comparable results for normal images. For automation process, RACAL can be used as a classifier and results show that it performs better than the KNN classifier in both normal and abnormal images.     

基于关联规则与熵聚类的清热类中成药组方规律研究

目的:探讨常用清热类中成药组方规律。方法:收录《新编国家中成药》中清热类中成药处方,采用关联规则Apriori算法和复杂系统熵聚类等方法,确定处方中药物的使用频次及药物之间的关联规则等。结果:高频次药物包括甘草、黄芩、冰片、金银花、大黄、连翘等;高频次药物组合包括"甘草、黄芩""甘草、桔梗""连翘、金银花"等;置信度较高的关联规则包括"牛黄->冰片""桔梗->甘草""朱砂->冰片""栀子->黄芩"等。结论:处方用药中除常见的清热类中药外,尚包括具有清热作用的部分开窍药、安神药、泻下药及其他类药物。