Knowledge Base Completion: Baselines Strike Back

Many papers have been published on the knowledge base completion task in the past few years. Most of these introduce novel architectures for relation learning that are evaluated on standard datasets such as FB15k and WN18. This paper shows that the accuracy of almost all models published on the FB15k can be outperformed by an appropriately tuned baseline - our reimplementation of the DistMult model. Our findings cast doubt on the claim that the performance improvements of recent models are due to architectural changes as opposed to hyper-parameter tuning or different training objectives. This should prompt future research to re-consider how the performance of models is evaluated and reported

Text Understanding with the Attention Sum Reader Network

Several large cloze-style context-question-answer datasets have been introduced recently: the CNN and Daily Mail news data and the Children's Book Test. Thanks to the size of these datasets, the associated text comprehension task is well suited for deep-learning techniques that currently seem to outperform all alternative approaches. We present a new, simple model that uses attention to directly pick the answer from the context as opposed to computing the answer using a blended representation of words in the document as is usual in similar models. This makes the model particularly suitable for question-answering problems where the answer is a single word from the document. Ensemble of our models sets new state of the art on all evaluated datasets.Comment: Presented at ACL 201

Reading Companion: The Technical and Social Design of an Automated Reading Tutor

This paper describes IBM’s automatic reading tutor system, the Reading Companion. The reading tutor aims to improve the literacy skills of beginning readers, both children and adults, and help adults who are non-native speakers of English to learn the language. We describe Reading Companion’s architecture, which allows a large, globally distributed reading companion community to create and share new reading material. We also report substantial accuracy improvements in recognizing children’s speech gained by training the recognizer on the IBM Kidspeak corpus, a newly developed corpus of children’s speech

Molecular basis of tRNA recognition by the Elongator complex

The highly conserved Elongator complex modifies transfer RNAs (tRNAs) in their wobble base position, thereby regulating protein synthesis and ensuring proteome stability. The precise mechanisms of tRNA recognition and its modification reaction remain elusive. Here, we show cryo–electron microscopy structures of the catalytic subcomplex of Elongator and its tRNA-bound state at resolutions of 3.3 and 4.4 Å. The structures resolve details of the catalytic site, including the substrate tRNA, the iron-sulfur cluster, and a SAM molecule, which are all validated by mutational analyses in vitro and in vivo. tRNA binding induces conformational rearrangements, which precisely position the targeted anticodon base in the active site. Our results provide the molecular basis for substrate recognition of Elongator, essential to understand its cellular function and role in neurodegenerative diseases and cancer

CSF-Biomarkers in Olympic Boxing: Diagnosis and Effects of Repetitive Head Trauma

Background Sports-related head trauma is common but still there is no established laboratory test used in the diagnostics of minimal or mild traumatic brain injuries. Further the effects of recurrent head trauma on brain injury markers are unknown. The purpose of this study was to investigate the relationship between Olympic (amateur) boxing and cerebrospinal fluid (CSF) brain injury biomarkers. Methods The study was designed as a prospective cohort study. Thirty Olympic boxers with a minimum of 45 bouts and 25 non-boxing matched controls were included in the study. CSF samples were collected by lumbar puncture 1–6 days after a bout and after a rest period for at least 14 days. The controls were tested once. Biomarkers for acute and chronic brain injury were analysed. Results NFL (mean ± SD, 532±553 vs 135±51 ng/L p = 0.001), GFAP (496±238 vs 247±147 ng/L p<0.001), T-tau (58±26 vs 49±21 ng/L p<0.025) and S-100B (0.76±0.29 vs 0.60±0.23 ng/L p = 0.03) concentrations were significantly increased after boxing compared to controls. NFL (402±434 ng/L p = 0.004) and GFAP (369±113 ng/L p = 0.001) concentrations remained elevated after the rest period. Conclusion Increased CSF levels of T-tau, NFL, GFAP, and S-100B in >80% of the boxers demonstrate that both the acute and the cumulative effect of head trauma in Olympic boxing may induce CSF biomarker changes that suggest minor central nervous injuries. The lack of normalization of NFL and GFAP after the rest period in a subgroup of boxers may indicate ongoing degeneration. The recurrent head trauma in boxing may be associated with increased risk of chronic traumatic brain injury

The Bean Channel: Java distributed event model

Available from STL Prague, CZ / NTK - National Technical LibrarySIGLECZCzech Republi