With the global pandemic of infectious diseases, the demand for accurate nucleic acid detection is daily increasing. The traditional threshold-based algorithms are adopted as the mainstream for processing the images of digital polymerase chain reaction (dPCR) now, but they are facing huge challenges on complex problems such as irregular noise, uneven illumination, and the lack of data. So, this paper proposed a novel few-shot learning method based on our improved YOLOv3 model with fast processing speed and high accuracy to deal with complicated situations. Besides, to reduce the requirement of the large training dataset and annotation time of deep neural networks, we proposed the Random Background Transfer Method (RBTM) and Source Traceability Annotation Method (STAM) as the data augmentation and annotation method separately, which exploit the prior knowledge of the data and successfully realized the few-shot learning. Bases on the domain knowledge of dPCR images, our method could effectively augment images and reduce the labeling time by 70% while retaining the visually prominent features and improves the detection accuracy from 63.96% of the traditional threshold-based algorithm to as high as 98.98%. With the optimal processing speed and accuracy, our method is the state-of-art strategy for the detection of dPCR images now.

Phase diagrams reflect the possible kinetic routes and guide various applications such as the designed assembly and synthesis of functional materials. Two-dimensional (2D) materials have been a focus of ongoing research due to their wide applications; therefore, researchers are highly motivated to discover the general principles that control the assembly of such materials. In this study, we map the 2D phase diagrams of short- and long-range attractive colloids at single-particle resolution by video microscopy. Phase boundaries, including (meta)critical or triple points and corresponding real-space configurations, are precisely specified. Profiles of 2D phase diagrams with attractive interactions resemble their 3D counterparts. For short-range systems, by measuring the deepest achievable supercooled states on the phase diagram, a “crater” structure surrounding the metastable fluid-fluid critical point indicates an enhanced nucleation rate within the crater and further suggests a local minimum of the free-energy barrier for crystallization in this area. During a dense fluid-mediated two-step crystallization process, we observe that multiple crystallites could form within a single dense fluid cluster, partly due to its highly amorphous shape. This highly amorphous shape is found for all observed well-developed dense fluid clusters. It is a supplement to the multistep nucleation process. For long-range systems, equilibrium vapor-liquid coexistence is observed, which paves the way for the exploration of critical behaviors. Rigidity percolation of crystallites, and bulk fluid-solid coexistence which provide clear evidence of a possible first-order transition for 2D melting, are observed for both systems. Our experiments reveal the general features of phase behaviors shared by 2D attractive systems including graphene, protein membranes, and adsorbed nanocrystals.

Networks and gels are soft elastic solids of tremendous technological importance that consist of cross-linked polymers whose structure and connectivity at the molecular level are fundamentally nonuniform. Pre-failure local mechanical responses are not understood at the level of individual crosslinks, despite the enormous attention given to their macroscopic mechanical responses and to developing optical probes to detect their loci of mechanical failure. Here, introducing the extensophore concept to measure nondestructive forces using an optical probe with continuous force readout proportional to deformation, we show that the crosslinks in an elastic polymer network extend, fluctuate, and deform with a wide range of molecular individuality. Requiring little specialized equipment, this foundational single-molecule phosphorescence approach, applied here to polymer science and engineering, can be useful to a broad science and engineering community.