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

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

Evaluation of corrosion and scaling potentials of oilfield waters in an offshore producing facility, Niger Delta

Abstract In this study, water samples from Miocene reservoirs, offshore Niger Delta, and seawater samples used for water injection were investigated in an attempt to examine the chemistry, evaluate the corrosion behaviour of steel, iron, and aluminium in different aqua media, and evaluate the scaling potentials of the oilfield produced waters (OFPW). Chemical analyses of the waters were determined; corrosion rate measurements were carried out by the weight loss method at room temperature while corrosion kinetics was carried out using conventional methods. Langelier saturation index (LSI), Ryznar stability index (RSI), Larson–Skold index (L–S), Puckorius scaling index (PSI), and aggressiveness index (AI) were evaluated for assessing the corrosiveness and scaling potential of the formation waters, using water quality data. The magnitude of corrosion of these metals was studied for an exposure period of 42 days. Chemical analysis revealed that the waters are slightly alkaline and generally classified as hard, saline water of the Na-Cl type based on its total dissolved solids (TDS). Produced water pH values range from 7.32 to 8.38. Results showed the likelihood of some of the water to form mild to severe scales based on the corrosivity indices, while the seawater samples are classified as ‘non-aggressive’ and ‘aggressive’. Steel has the highest corrosion rate with a value of 3.84 × 10−3 mg cm−2 h−1 compared to aluminium with the lowest rate of 0.37 × 10−3 mg cm−2 h−1. In most cases, the rate of corrosion of the metals followed the first-order rate constant in some of the samples, and the second-order in others within the first seven days. It was observed that the rate of corrosion follows this order: steel &amp;gt; iron &amp;gt; aluminium. The potential heavy and intolerable corrosion associated with the use of these seawater samples as injection waters is a potential risk that must be handled by adequate treatment.</jats:p

CHARACTERISTIC DISTRIBUTION AND SOURCE APPORTIONMENT OF SOME HEAVY METALS ON STREET DUST OF IKORODU AREA OF LAGOS STATE, SOUTHWESTERN, NIGERIA.

This research reports the characteristic distribution and source apportionment of some heavy metals in dust ofIkorodu area of Lagos State. The dust samples were collected randomly four times a month at ten different locationsin Ikorodu area. Dust samples were obtained by sweeping surface dust into plastic waste packer using plastic brushand transferred into pre-labeled polythene bags. The samples were filtered through 75 μm stainless steel sieve,weighed, digested with appropriate amount of HNO3 and H2O for 2 h. The concentrations of heavy metals wereanalyzed using Atomic Absorption Spectrophotometer (AAS). Results showed that the percentage contribution ofeach heavy metal at Ikorodu area were: Zn 79.4, Pb 14.8, Cu 0.9, Ni 4.9 and Cd 0.01. The most abundant heavymetal was Zn 2869.70 mg/kg while the least was Cd 0.69 mg/kg. The most polluted site wasResidential Area 1 (993.674 mg/kg) while the least polluted was Industrial Area 3 (81.397 mg/kg). The major roads(38.1%) had the highest concentration of heavy metal pollution while the agricultural area (5.7%) had the leastpollution. The sequence and distribution follow the pattern: Zn &gt; Pb &gt; Ni &gt; Cu &gt; Cd. The Principal ComponentAnalysis PCA showed that the major sources of heavy metals in Ikorodu dust are anthropogenic. Pearsoncorrelation analysis also showed that there was strong positive correlation (0.887) between the heavy metals. Theconcentrations of Heavy metals Zn, Pb, Ni, Cu exceeded the recommended limits of the Federal Ministry ofEnvironment (FME), European communities (EC) and United Nations Environmental Programme (UNEP)permissible levels for dust suggesting that the study area is pollute