Field-effect transitor differential amplifier

The feasibility of using field-effect transistors in wide-band differential amplifier applications has been investigated. An analysis of bipolar transistor differential amplifiers is included which demonstrates the problem of thermal drift and low input impedance present in all low level transistor amplifiers. An investigation of a field-effect transistor shows that such a device possesses the properties of zero thermal drift at a particular bias point, extremely high input impedance, good radiation resistance, low noise, and a high power gain. It is therefore postulated that employing FET\u27s in a differential amplifier will result in a circuit having very high input impedance and low thermal drift

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

Epidemiological Risk Factors for Animal Influenza A Viruses Overcoming Species Barriers

Drivers and risk factors for Influenza A virus transmission across species barriers are poorly understood, despite the ever present threat to human and animal health potentially on a pandemic scale. Here we review the published evidence for epidemiological risk factors associated with influenza viruses transmitting between animal species and from animals to humans. A total of 39 papers were found with evidence of epidemiological risk factors for influenza virus transmission from animals to humans; 18 of which had some statistical measure associated with the transmission of a virus. Circumstantial or observational evidence of risk factors for transmission between animal species was found in 21 papers, including proximity to infected animals, ingestion of infected material and potential association with a species known to carry influenza virus. Only three publications were found which presented a statistical measure of an epidemiological risk factor for the transmission of influenza between animal species. This review has identified a significant gap in knowledge regarding epidemiological risk factors for the transmission of influenza viruses between animal species

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