Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Research and Design of a Routing Protocol in Large-Scale Wireless Sensor Networks

无线传感器网络，作为全球未来十大技术之一，集成了传感器技术、嵌入式计算技术、分布式信息处理和自组织网技术，可实时感知、采集、处理、传输网络分布区域内的各种信息数据，在军事国防、生物医疗、环境监测、抢险救灾、防恐反恐、危险区域远程控制等领域具有十分广阔的应用前景。 本文研究分析了无线传感器网络的已有路由协议，并针对大规模的无线传感器网络设计了一种树状路由协议，它根据节点地址信息来形成路由，从而简化了复杂繁冗的路由表查找和维护，节省了不必要的开销，提高了路由效率，实现了快速有效的数据传输。 为支持此路由协议本文提出了一种自适应动态地址分配算——ADAR（AdaptiveDynamicAddre...As one of the ten high technologies in the future, wireless sensor network, which is the integration of micro-sensors, embedded computing, modern network and Ad Hoc technologies, can apperceive, collect, process and transmit various information data within the region. It can be used in military defense, biomedical, environmental monitoring, disaster relief, counter-terrorism, remote control of haz...学位：工学硕士院系专业：信息科学与技术学院通信工程系_通信与信息系统学号：2332007115216

Effect of Amoxicillin dose and treatment duration on the need for antibiotic re-treatment in children with Community-Acquired Pneumonia: The CAP-IT randomized clinical trial

Importance: The optimal dose and duration of oral amoxicillin for children with community-acquired pneumonia (CAP) are unclear. Objective: To determine whether lower-dose amoxicillin is noninferior to higher dose and whether 3-day treatment is noninferior to 7 days. Design, Setting, and Participants: Multicenter, randomized, 2 × 2 factorial noninferiority trial enrolling 824 children, aged 6 months and older, with clinically diagnosed CAP, treated with amoxicillin on discharge from emergency departments and inpatient wards of 28 hospitals in the UK and 1 in Ireland between February 2017 and April 2019, with last trial visit on May 21, 2019. Interventions: Children were randomized 1:1 to receive oral amoxicillin at a lower dose (35-50 mg/kg/d; n = 410) or higher dose (70-90 mg/kg/d; n = 404), for a shorter duration (3 days; n = 413) or a longer duration (7 days; n = 401). Main Outcomes and Measures: The primary outcome was clinically indicated antibiotic re-treatment for respiratory infection within 28 days after randomization. The noninferiority margin was 8%. Secondary outcomes included severity/duration of 9 parent-reported CAP symptoms, 3 antibiotic-related adverse events, and phenotypic resistance in colonizing Streptococcus pneumoniae isolates. Results: Of 824 participants randomized into 1 of the 4 groups, 814 received at least 1 dose of trial medication (median [IQR] age, 2.5 years [1.6-2.7]; 421 [52%] males and 393 [48%] females), and the primary outcome was available for 789 (97%). For lower vs higher dose, the primary outcome occurred in 12.6% with lower dose vs 12.4% with higher dose (difference, 0.2% [1-sided 95% CI -∞ to 4.0%]), and in 12.5% with 3-day treatment vs 12.5% with 7-day treatment (difference, 0.1% [1-sided 95% CI -∞ to 3.9]). Both groups demonstrated noninferiority with no significant interaction between dose and duration (P =.63). Of the 14 prespecified secondary end points, the only significant differences were 3-day vs 7-day treatment for cough duration (median 12 days vs 10 days; hazard ratio [HR], 1.2 [95% CI, 1.0 to 1.4]; P =.04) and sleep disturbed by cough (median, 4 days vs 4 days; HR, 1.2 [95% CI, 1.0 to 1.4]; P =.03). Among the subgroup of children with severe CAP, the primary end point occurred in 17.3% of lower-dose recipients vs 13.5% of higher-dose recipients (difference, 3.8% [1-sided 95% CI, -∞ to10%]; P value for interaction =.18) and in 16.0% with 3-day treatment vs 14.8% with 7-day treatment (difference, 1.2% [1-sided 95% CI, -∞ to 7.4%]; P value for interaction =.73). Conclusions and Relevance: Among children with CAP discharged from an emergency department or hospital ward (within 48 hours), lower-dose outpatient oral amoxicillin was noninferior to higher dose, and 3-day duration was noninferior to 7 days, with regard to need for antibiotic re-treatment. However, disease severity, treatment setting, prior antibiotics received, and acceptability of the noninferiority margin require consideration when interpreting the findings. Trial Registration: ISRCTN Identifier: ISRCTN76888927

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press