This paper introduces DuReader, a new large-scale, open-domain Chinese machine reading comprehension (MRC) dataset, designed to address real-world MRC. DuReader has three advantages over previous MRC datasets: (1) data sources: questions and documents are based on Baidu Search and Baidu Zhidao 1 ; answers are manually generated.(2) question types: it provides rich annotations for more question types, especially yes-no and opinion questions, that leaves more opportunity for the research community. (3) scale: it contains 200K questions, 420K answers and 1M documents; it is the largest Chinese MRC dataset so far. Experiments show that human performance is well above current state-of-the-art baseline systems, leaving plenty of room for the community to make improvements. To help the community make these improvements, both DuReader 2 and baseline systems 3 have been posted online. We also organize a shared competition to encourage the exploration of more models. Since the release of the task, there are significant improvements over the baselines.
MicroRNA
(miRNA) has emerged as one of the ideal target biomarker
analytes for cancer detection because its abnormal expression is closely
related to the occurrence of many cancers. In this work, we combined
three-dimensional (3D) popcorn-like gold nanofilms as novel surface-enhanced
Raman scattering (SERS)-electrochemistry active substrates with toehold-mediated
strand displacement reactions (TSDRs) to construct a DNA molecular
machine for SERS-electrochemistry dual-mode detection of miRNA. 3D
popcorn-like spatial structures generated more active “hot
spots” and thus enhanced the sensitivity of SERS and electrochemical
signals. Besides, the TSDRs showed high sequence-dependence and high
specificity. The addition of target miRNA will trigger the molecular
machine to perform two TSDRs in the presence of signal DNA strands
modified by R6G (R6G-DNA), thus achieving an enzyme-free amplification
detection of miRNA with a low limit of detection of 0.12 fM (for the
SERS method) and 2.2 fM (for the electrochemical method). This biosensor
can also serve as a universally amplified and sensitive detection
platform for monitoring different biomarkers, such as cancer-related
DNA, messenger RNA, or miRNA molecules, with high selectivity by changing
the corresponding probe sequence.
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