广西龙滩库区移民小学一起乙型流感爆发流行特征分析
CHINESE COMMUNITY DOCTORS（2012）
Abstract
目的:分析2012年2月广西边远山区库区内移民区小学一起乙型流感爆发流行特征,为制定类似学校防治措施提供参考.方法:收集该小学患病学生资料,描述和分析流行病学、病原学、临床表现及防治措施等相关资料.结果:该小学连同学前班学生354人,年龄5～13岁,均未进行流感疫苗接种.出现1例以发热、咳嗽、头痛为主要症状的病例后,随后2天增加到38例,最后发现53例,发病率14.97%,病例分布各年级,并以内宿生为主75.47%,由于各年龄组学生混合居住,因此,患病学生无年级发病规律现象.取样实验室检测证实为乙型流行性感冒病毒.经及时采取患病学生隔离治疗及对师生卫生防治知识宣传等措施后,疫情得到有效控制.结论:对边远山区学校师生除应加强卫生防治知识宣传教育外,还应积极开展流感疫苗接种.
More求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined