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

Feasible coordination of multiple homogeneous or heterogeneous mobile vehicles with various constraints

We consider the problem of feasible coordination control for multiple homogeneous or heterogeneous mobile vehicles subject to various constraints (nonholonomic motion constraints, holonomic coordination constraints, equality/inequality constraints etc). We develop a general framework involving differential-algebraic equations and viability theory to describe and determine coordination feasibility for a coordinated motion control under heterogeneous vehicle dynamics and various constraints. A heuristic algorithm is proposed for generating feasible trajectories for each individual vehicle. We show several application examples and simulation experiments on multi-vehicle coordination under various constraints to validate the theory and the effectiveness of the proposed algorithm and control schemes

Gamma-Ray Imaging with Spatially Continuous Intensity Statistics

Novel methods for the inference of radiation intensityfunctions defined over known surfaces are proposed, intendedfor use in surveying applications with mobile spectrometers.Previous approaches, based on the maximum likelihoodexpectation maximization (ML-EM) framework with Poissonlikelihoods, are extended to better handle spatially continuousintensity statistics using ideas from Gaussian filtering. Theresulting algorithm is evaluated against a classical ML-EMmethod, and a recently proposed sparse additive point sourcelocalization (APSL) algorithm in a Monte-Carlo simulationstudy. The new generalized ASPL (GASPL) is shown tocompare favorably in terms of estimation accuracy when thetrue intensity is not well described by a set of point sources.Finally, the GASPL is used in an experiment where a detector ismounted to an unmanned aerial vehicle to estimate the intensityand location of radioactive sources placed in a meadow

Development of healthcare quality indicators for rheumatoid arthritis in Europe: the eumusc.net project.

Eumusc.net (http://www.eumusc.net) is a European project supported by the EU and European League Against Rheumatism to improve musculoskeletal care in Europe