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Background. In the last decades, several life science resources have structured data using the same framework and made these accessible using the same query language to facilitate interoperability. Knowledge graphs have seen increased adoption in bioinformatics due to their advantages for representing data in a generic graph format. For example, yummydata.org catalogs more than 60 knowledge graphs accessible through SPARQL, a technical query language. Although SPARQL allows powerful, expressive queries, even across physically distributed knowledge graphs, formulating such queries is a challenge for most users. Therefore, to guide users in retrieving the relevant data, many of these resources provide representative examples. These examples can also be an important source of information for machine learning, if a sufficiently large number of examples are provided and published in a common, machine-readable and standardized format across different resources. Findings. We introduce a large collection of human-written natural language questions and their corresponding SPARQL queries over federated bioinformatics knowledge graphs (KGs) collected for several years across different research groups at the SIB Swiss Institute of Bioinformatics. The collection comprises more than 1000 example questions and queries, including 65 federated queries. We propose a methodology to uniformly represent the examples with minimal metadata, based on existing standards. Furthermore, we introduce an extensive set of open-source applications, including query graph visualizations and smart query editors, easily reusable by KG maintainers who adopt the proposed methodology. Conclusions. We encourage the community to adopt and extend the proposed methodology, towards richer KG metadata and improved Semantic Web services.

Modern commercial antivirus systems increasingly rely on machine learning to keep up with the rampant inflation of new malware. However, it is well-known that machine learning models are vulnerable to adversarial examples (AEs). Previous works have shown that ML malware classifiers are fragile to the white-box adversarial attacks. However, ML models used in commercial antivirus products are usually not available to attackers and only return hard classification labels. Therefore, it is more practical to evaluate the robustness of ML models and real-world AVs in a pure black-box manner. We propose a black-box Reinforcement Learning (RL) based framework to generate AEs for PE malware classifiers and AV engines. It regards the adversarial attack problem as a multi-armed bandit problem, which finds an optimal balance between exploiting the successful patterns and exploring more varieties. Compared to other frameworks, our improvements lie in three points. 1) Limiting the exploration space by modeling the generation process as a stateless process to avoid combination explosions. 2) Due to the critical role of payload in AE generation, we design to reuse the successful payload in modeling. 3) Minimizing the changes on AE samples to correctly assign the rewards in RL learning. It also helps identify the root cause of evasions. As a result, our framework has much higher black-box evasion rates than other off-the-shelf frameworks. Results show it has over 74\%--97\% evasion rate for two state-of-the-art ML detectors and over 32\%--48\% evasion rate for commercial AVs in a pure black-box setting. We also demonstrate that the transferability of adversarial attacks among ML-based classifiers is higher than the attack transferability between purely ML-based and commercial AVs.

This concept article discusses the possibilities for identifying sedimentary-origin meteorites. The paper concerns (i) the macroscopic candidate for sedimentary meteorite in the epicenter of the 1908 Tunguska catastrophe; (ii) potential parent bodies for sedimentary meteorites; (iii) isotopic heterogeneity of unmixed silicate reservoirs on Mars; (iv) possible terrestrial loss or contamination in the noble gas signatures in new type meteorites that spent time in extreme weather conditions; (v) cosmogenic isotopes and shielding; and (vi) pseudo meteorites. We conclude that the list of candidate parent bodies for sedimentary meteorites includes, but is not limited by the Earth, Mars, Enceladus, Ganymede, Europa, and hypothetical planets that could exist between orbits of Mars and Jupiter in the past. A parent body for extraterrestrial sedimentary rocks on the Earth should be identified based on the entire body of evidence which is not limited solely by tests of oxygen and noble gas isotopes whose signatures may undergo terrestrial contamination and may exhibit significant heterogeneity within the parent bodies. Observed fall of cosmic body, evidence of hypervelocity impact complying with the criteria of impact structures, and the presence of fusion crust on the fragments should be considered as priority signs of meteoritic origin., Comment: 20 pages, 3 figures, 75 references. arXiv admin note: text overlap with arXiv:1605.01892

The article provides an open discussion and a critical feedback to the comments of Haack et al. (2015) and emphasizes a significance of the first macroscopic evidence for a candidate meteorite of a new type: planetary-origin meteorite composed of silica-rich sedimentary rock. Discussion concerns the arguments for (i) candidate parental bodies including the Earth, Mars and icy moons of Saturn and Jupiter; (ii) PGE anomaly versus glassy silicate microspherules and quartz grains anomaly in the area of the 1908 Tunguska catastrophe; (iii) isotopic heterogeneity of unmixed silicate reservoirs on Mars; (iv) possible terrestrial loss or contamination in the noble gas signatures in meteorites that spent time in the extreme weather conditions; (v) cosmogenic isotopes and shielding; and (vi) pseudo meteorites. We conclude that the list of candidate parental bodies for hypothetical sedimentary-origin meteorites includes, but is not limited by the Earth, Mars, Enceladus, Ganymede, and Europa. A parental body should be identified based on the entire body of evidence which is not limited solely by tests of oxygen and noble gas isotopes whose signatures may undergo terrestrial contamination and may exhibit significant heterogeneity within the parental bodies., Comment: 11 pages, 49 references

The aim of the study was to discover remnants of the 1908 Tunguska meteorite. Main objective of the field studies was identification of exotic rocks, furrows, and penetration funnels reported by the first eyewitnesses, residents of the area with severe forest destruction. Main methods included decoding of aerial survey photographs, systematic survey of the epicenter area of the Tunguska explosion, exploratory excavations of the objects of interest, reconstruction studies of exotic boulder by using its splinters, mineralogical and spectral analysis of specimens, experimental attempt of plasma-induced reproduction of the fusion crust on specimen. The authors present results on discovery of penetration funnel-like structures; exotic boulder (known as John's Stone)) with its shear-fractured splinters and fresh furrow in the permafrost; several splinters with glassy coatings; evidence of high-speed John's Stone deceleration in the permafrost; and clear consistency in geometry of spacial arrangements of all splinters, furrows, cleaved pebbles according to data of reconstruction studies. John's Stone is composed of highly silicified gravelite sandstone (98.5% SiO2) with grain size of 0.5 to 1.5 cm. Outer surface of several splinters showed continuous glassy coating similar to shiny fusion crust reminiscent of freshly applied enamel. Plasma-induced heating of John's Stone specimen led to its explosive disintegration; residue presented with whitish semi-transparent pumice-like grains and irregularly shaped fused particles. Overall, our data suggest that John's Stone is Tunguska meteorite candidate. Recent discoveries of sedimentary rocks, lithified gravelite sandstone, clay, and quartz on Mars provide rationale for search and identification of silica-rich Martian meteorites of sedimentary origin., Comment: Number of Pages: 19 Number of References: 27 Number of Tables: 1 Number of Figures: 5