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

The design and optimization of a power supply for a one-meter electromagnetic railgun

A naval electromagnetic railgun would be a considerable asset against a littoral environment. By accelerating projectiles to 3 km/s, a naval railgun would be capable of reaching 300-400 nautical miles. Problems such as rail erosion, energy storage and fire control prevent the railgun from becoming a weapon to date. At the Naval Postgraduate School, the Physics Department continues to investigate and develop concepts to overcome these challenges. As part of the methodology, previous students built a one-meter railgun system for experimentation. The existing 1.6 mF power supply is insufficient to fire this railgun effectively. To design a sufficient power supply a MATLAB code was created to simulate a generated current pulse and to predict the subsequent railgun performance. Interrelated factors such as railgun geometry, muzzle velocity, current density and contact surface area were taken into consideration. Also, tradeoffs in capacitance, projectile mass and residual current were weighed against one another to achieve desired railgun performances. From numerous simulations, this study determined that the one-meter railgun with a 21.5 mF power supply could fire a 0.158-kg projectile at a velocity of 1 km/s, and leave a residual current of only 4% of the initial energy once the projectile exits the rails. v.http://archive.org/details/thedesignndoptim109451155US Navy (USN) autho

4. TITLE AND SUBTITLE: Title (Mix case letters) The Design and Optimization of a Power Supply for a One-meter Electromagnetic

Approved for public release; distribution is unlimited. E REPORT DOCUMENTATION PAG Form Approved OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washingto

Reduced HIV/AIDS diagnosis rates and increased AIDS mortality due to late diagnosis in Brazil during the COVID-19 pandemic

Abstract The COVID-19 pandemic has severely affected global health, leading to the suspension of numerous routine healthcare services and posing challenges in efforts to control other diseases, such as HIV/AIDS. This study aimed to assess the impact of the COVID-19 pandemic on HIV/AIDS diagnoses and mortality rates in Brazil during 2020 and 2021. The percentage change was calculated to determine whether there was an increase or decrease in HIV/AIDS diagnoses and mortality, considering the average numbers from the last 5 years. Additionally, a Joinpoint regression model and an interrupted time series analysis were applied to assess time trends before and after the onset of the pandemic. Lastly, choropleth maps were prepared. We observed a reduction of 22.4% (2020) and 9.8% (2021) in the diagnosis of HIV/AIDS in Brazil. Conversely, there was a significant increase in the percentage change of late diagnosis of AIDS deaths in 2020 (6.9%) and 2021 (13.9%), with some states showing an increase of over 87%. Decreasing time trends in the diagnosis of HIV/AIDS were identified before the pandemic in Brazil, especially in the Southeast and South regions, and then time trends stabilized after including the pandemic years. Along with the dissemination of COVID-19, there was a reduction in the diagnosis of HIV/AIDS and an increase in late diagnosis AIDS deaths, signaling a serious impact of the pandemic on HIV/AIDS control strategies in Brazil. Therefore, we highlight the need for continuous efforts to control both diseases, that is, maintaining regular health services even in crisis situations

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