3 research outputs found
Non-Autoregressive Math Word Problem Solver with Unified Tree Structure
Existing MWP solvers employ sequence or binary tree to present the solution
expression and decode it from given problem description. However, such
structures fail to handle the variants that can be derived via mathematical
manipulation, e.g., and can both be
possible valid solutions for a same problem but formulated as different
expression sequences or trees. The multiple solution variants depicting
different possible solving procedures for the same input problem would raise
two issues: 1) making it hard for the model to learn the mapping function
between the input and output spaces effectively, and 2) wrongly indicating
\textit{wrong} when evaluating a valid expression variant. To address these
issues, we introduce a unified tree structure to present a solution expression,
where the elements are permutable and identical for all the expression
variants. We propose a novel non-autoregressive solver, named \textit{MWP-NAS},
to parse the problem and deduce the solution expression based on the unified
tree. For evaluating the possible expression variants, we design a path-based
metric to evaluate the partial accuracy of expressions of a unified tree. The
results from extensive experiments conducted on Math23K and MAWPS demonstrate
the effectiveness of our proposed MWP-NAS. The codes and checkpoints are
available at: \url{https://github.com/mengqunhan/MWP-NAS}.Comment: Accepted at EMNLP202
Dual Recognition Strategy for Specific and Sensitive Detection of Bacteria Using Aptamer-Coated Magnetic Beads and Antibiotic-Capped Gold Nanoclusters
Food poisoning and infectious diseases
caused by pathogenic bacteria
such as Staphylococcus aureus (SA) are serious public health concerns. A method
of specific, sensitive, and rapid detection of such bacteria is essential
and important. This study presents a strategy that combines aptamer
and antibiotic-based dual recognition units with magnetic enrichment
and fluorescent detection to achieve specific and sensitive quantification
of SA in authentic specimens and in
the presence of much higher concentrations of other bacteria. Aptamer-coated
magnetic beads (Apt-MB) were employed for specific capture of SA. Vancomycin-stabilized fluorescent gold nanoclusters
(AuNCs@Van) were prepared by a simple one-step process and used for
sensitive quantification of SA in the
range of 32–10<sup>8</sup> cfu/mL with the detection limit
of 16 cfu/mL via a fluorescence intensity measurement. And using this
strategy, about 70 cfu/mL of <i>SA</i> in complex samples
(containing 3 × 10<sup>8</sup> cfu/mL of other different contaminated
bacteria) could be successfully detected. In comparison to prior studies,
the developed strategy here not only simplifies the preparation procedure
of the fluorescent probes (AuNCs@Van) to a great extent but also could
sensitively quantify SA in the presence
of much higher concentrations of other bacteria directly with good
accuracy. Moreover, the aptamer and antibiotic used in this strategy
are much less expensive and widely available compared to common-used
antibodies, making it cost-effective. This general aptamer- and antibiotic-based
dual recognition strategy, combined with magnetic enrichment and fluorescent
detection of trace bacteria, shows great potential application in
monitoring bacterial food contamination and infectious diseases