Refining Nodes and Edges of State Machines

State machines are hierarchical automata that are widely used to structure complex behavioural specifications. We develop two notions of refinement of state machines, node refinement and edge refinement. We compare the two notions by means of examples and argue that, by adopting simple conventions, they can be combined into one method of refinement. In the combined method, node refinement can be used to develop architectural aspects of a model and edge refinement to develop algorithmic aspects. The two notions of refinement are grounded in previous work. Event-B is used as the foundation for our refinement theory and UML-B state machine refinement influences the style of node refinement. Hence we propose a method with direct proof of state machine refinement avoiding the detour via Event-B that is needed by UML-B

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

Repetitive ocular vestibular evoked myogenic potentials in myasthenia gravis

Objective To validate the repetitive ocular vestibular evoked myogenic potentials (RoVEMP) test for diagnostic use in myasthenia gravis (MG) and to investigate its value in diagnostically challenging subgroups. Methods The RoVEMP test was performed in 92 patients with MG, 22 healthy controls, 33 patients with a neuromuscular disease other than MG (neuromuscular controls), 4 patients with Lambert-Eaton myasthenic syndrome, and 2 patients with congenital myasthenic syndrome. Results Mean decrement was significantly higher in patients with MG (28.4% +/- 32.2) than in healthy controls (3.2% +/- 13.9; p = 14.3% resulted in a sensitivity of 67% and a specificity of 82%. The sensitivity of the RoVEMP test was 80% in ocular MG and 63% in generalized MG. The RoVEMP test was positive in 6 of 7 patients with seronegative MG (SNMG) with isolated ocular weakness. Of 10 patients with SNMG with negative repetitive nerve stimulation (RNS) results, 73% had an abnormal RoVEMP test. The magnitude of decrement was correlated with the time since the last intake of pyridostigmine (B = 5.40; p = 0.019). Conclusions The RoVEMP test is a new neurophysiologic test that, in contrast to RNS and single-fiber EMG, is able to measure neuromuscular transmission of extraocular muscles, which are the most affected muscles in MG. Especially in diagnostically challenging patients with negative antibody tests, negative RNS results, and isolated ocular muscle weakness, the RoVEMP test has a clear added value in supporting the diagnosis of MG. Classification of evidence This study provides Class III evidence that RoVEMP distinguishes MG from other neuromuscular diseases

Gender differences on the semantic flanker task using transposed-letter target words

Previous research has demonstrated that men and women are differentially influenced by irrelevant distractors. Other lines of evidence have suggested that increasing the perceptual load of a task reduces distractor interference for participants generally. The present study examined these effects using a semantic version of the flanker task; participants made speeded responses to category target words that were flanked by irrelevant distractors. The response mapping between the target and flanker words was either congruent (mapped to the same motor response) or incongruent (target word mapped to a different motor response to that of the flankers). Target words were presented either normally (e.g., table: low perceptual load) or with the beginning letters transposed (e.g., atble: high perceptual load). The results revealed that women showed a larger congruency effect than men but this was not due to greater interference on incongruent trials. While men and women made faster responses to normal than to transposed target words, this was similar in magnitude. The magnitude of the flanker effect for normal and transposed target words was significantly correlated in men but not in women. These findings are consistent with the view that women may process target words to a deeper level than men and therefore may engage in more conflict monitoring then men