鼻咽癌筛查成本效果的初步分析

目的:评价鼻咽癌新筛查方案的成本和效果。方法:在鼻咽癌高发区中山市进行鼻咽癌筛查,统计癌检出率、早诊率、人均筛查成本、发现早期病例平均费用和早期发现成本系数等指标。结果:共筛查16 712人,确诊鼻咽癌25例,检出率149.59/10万,早诊率76.0%,治疗率100.0%。筛查成本41.56元/人,发现病例费用27 779.82元,发现早期病例费用36 552.40元,按我国人均GDP计算,早期发现成本系数(EDCI)为1.71,按中山市人均GDP计算,EDCI为0.65。结论:相对常见恶性肿瘤鼻咽癌筛查成本较高,但在高发区筛查可以显著提高早诊率,并降低治疗费用

血液病患者中庚型肝炎病毒检测及感染情况研究

目的:了解武汉地区血液病患者中庚型肝炎病毒(HGV)的感染情况,探讨HGV的传播途径。方法:采用酶联免疫吸附试验(ELISA)及逆转录聚合酶链反应(RT-PCR)方法测定各型血液病患者血清中的抗HGV和HGV RNA。结果:51例血液病患者中血清抗HGV阳性6例,占11.8％(5/61),HGV RNA均阴性。6例抗GHV阳性患者中急粒2例,占25%(2/8),慢粒1例,占50%(1/2),再障2例,占50％(2/4),粒细胞缺乏症1例,占100%(1/1)。6例抗HGV阳性患者均有受血史,占18.7%(6/32),显著多于无受血史者。6例抗HGV阳性患者有1例ALT升高,且发生在化疗结束后,与抗HGV阴性患者无显著性差异。结论:血液病患者中存在HGV感染,输血是其主要传播途径,且与受血次数呈正相关。HGV病毒血症时间短,为自限性,致病力弱,不单独引起肝损害,也不加重化疗所致的肝损害

Research of a New Adaptive Clustering Algorithm on High Dimensional Data

聚类有效性是用来评估在不同输入条件下的聚类算法性能的处理过程.高维数据空间的稀疏性和“维灾“问题使得传统有效性指标失去作用.提出新的可用于高维数据集的有效性指标,并结合启发式递减算法,提出一种高维数据的自适应聚类算法,用于确定高维数据集的最佳聚类数目.实验结果表明:提出的聚类算法有较好的性能.Cluster validation is the process of evaluating performance of clustering algorithms under varying input conditions.The sparsity and the problem of the curse of dimensionality of high-dimensional data,make the most of the traditional clustering algorithm loose action in high-dimensional space.New clustering validation indices for high-dimensional data sets were proposed,and combined with the heuristic decreasing algorithm,we also offered an adaptive clustering algorithm for automatically determining the optimum number of clusters in high dimensional data.The experiment shows that the algorithm can get a better result.集美大学科研基金资助项目(F05026;ZB2005002

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies