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In this study, we synthesized novel gold-carbon dots (GCDs) with unique properties by microwave-assisted method. The characterization of high-resolution transmission electron microscope (HRTEM), XRD, high-angle annular dark field scanning transmission electron microscope (HAADF-STEM), and energy dispersive spectrometer demonstrates that GCDs are composed of carbon and Au. Tiny Au clusters are dispersed in a 2 nm-size carbon skeleton, which integrates the properties of typical CDs and gold nanoclusters (AuNCs), displaying fascinating peroxidase-like activity and single excitation/dual emission. Dual emission of the GCDs exhibits different fluorescent response to the target species and enables the GCDs to be exploited for sensing and bioimaging. The highly photostable and biocompatible GCDs were applied to dual fluorescent imaging for breast cancer cells and normal rat osteoblast cells under a single excitation. Moreover, ratiometric fluorescence imaging was used to monitor Fe(3+) level in normal rat osteoblast cells.

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This paper proposes a synthetic aperture radar (SAR) automatic target recognition (ATR) method via hierarchical fusion of two classification schemes, i.e., convolutional neural networks (CNN) and attributed scattering center (ASC) matching. CNN can work with notably high effectiveness under the standard operating condition (SOC). However, it can hardly cope with various extended operating conditions (EOCs), which are not covered by the training samples. In contrast, the ASC matching can handle many EOCs related to the local variations of the target by building a one-to-one correspondence between two ASC sets. Therefore, it is promising that both effectiveness and efficiency of the ATR method can be improved by combining the merits of the two classification schemes. The test sample is first classified by CNN. A reliability level calculated based on the outputs from CNN. Once there is a notably reliable decision, the whole recognition process terminates. Otherwise, the test sample will be further identified by ASC matching. To evaluate the performance of the proposed method, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset under SOC and various EOCs. The results demonstrate the superior effectiveness and robustness of the proposed method compared with several state-of-the-art SAR ATR methods.

AgBiS2 nanodots as an NIR light-excited photosensitizer produce a PDT effect, which is reported for the first time.

A single-molecule electrochemiluminescence bioassay is developed here which allows imaging and direct quantification of single biomolecules. Imaging single biomolecules is realized by localizing the electrochemiluminescence events of the labeled molecules. Such an imaging system allows mapping the spatial distribution of biomolecules with electrochemiluminescence and contains quantitative single-molecule insights. We further quantify biomolecules by spatiotemporally merging the repeated reactions at one molecule site and then counting the clustered molecules. The proposed single-molecule electrochemiluminescence bioassay is used to detect carcinoembryonic antigen, showing a limit of detection of 67 attomole concentration which is 10 000 times better than conventional electrochemiluminescence bioassays. This spatial resolution and sensitivity enable single-molecule electrochemiluminescence bioassay a new toolbox for both specific bioimaging and ultrasensitive quantitative analysis.