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Lung cancer is one of the most harmful malignant tumors to human health. The accurate judgment of the pathological type of lung cancer is vital for treatment. Traditionally, the pathological type of lung cancer requires a histopathological examination to determine, which is invasive and time consuming. In this work, a novel residual neural network is proposed to identify the pathological type of lung cancer via CT images. Due to the low amount of CT images in practice, we explored a medical-to-medical transfer learning strategy. Specifically, a residual neural network is pre-trained on public medical images dataset luna16, and then fine-tuned on our intellectual property lung cancer dataset collected in Shandong Provincial Hospital. Data experiments show that our method achieves 85.71% accuracy in identifying pathological types of lung cancer from CT images and outperforming other models trained with 2054 labels. Our method performs better than AlexNet, VGG16 and DenseNet, which provides an efficient, non-invasive detection tool for pathological diagnosis.

Mn2+ doping effectively realizes white light emission in three-dimensional lead halide perovskite nanocrystals. Meanwhile, research on Mn-doped two-dimensional layered perovskite single crystal is limited. We report centimeter-scale Mn-doped PEA2PbBr4 (C6H5CH2CH2NH3+ and PEA+) single crystals prepared by a slow evaporation method. Mn2+ dopants mainly act as substitutional doping and exhibit paramagnetic properties in the crystal at low doping density, while interstitial doping of Mn2+ prevails and induces antiferromagnetic characteristics at high doping density. Mn:PEA2PbBr4 single crystals exhibit dual-band chromacity-tunable blue-orange photoluminescence originating from excitons and Mn2+ emission. The negative temperature quenching effect is achieved by Mn-doping defects for the temperature-dependent exciton photoluminescence. Upon testing in the low-pressure vacuum chamber, the Mn2+ peak of the single crystal shows a dramatic shift from 610 to 690 nm. These results indicate that Mn:PEA2PbBr4 single crystal can serve as a potential and promising luminescent device material that achieves color tunable properties by regulating the systematic changes in the intensity ratio of exciton emission and Mn2+ emission, which will be very helpful for exploring the application of perovskite in magneto-optical devices in the future. [ABSTRACT FROM AUTHOR]

In order to detect and identify fire accidents accurately and efficiently, an intelligent fire identification system based on neural network algorithm is designed, which can overcome the shortcomings of single information, complex wiring, poor adaptability, etc. The characteristic extraction of sensors is adopted in the information layer to solve the problems in multi-sensor fusion. The fire data are transmitted to the main controller through LoRa wireless module and fused by back propagation neural network, which is self-learning and adaptive. The output of neural network and fuzzy inference with other factors are used for decision criteria to improve the identification accuracy. The common combustibles and various interference sources are selected for fire tests. The result shows that the detection accuracy is up to 100% and the false alarm rate is lower than 0.1%, meanwhile, the system has the advantages of fast response and high detection efficiency. [ABSTRACT FROM AUTHOR]

A proposed ultra-high slew rate current recycling folded cascode operational transconductance amplifier (OTA) working in the subthreshold region is presented. By employing adaptive biasing and the proposed positive-feedback nonlinear current mirror techniques, it not only forces the charge or discharge path to enter the strong inversion region during slewing, but also provides an ultra-high output current, leading to a significant boost in the slew rate. The simulation results of the two OTAs designed in SMIC 0.18 μ m CMOS process demonstrate that the slew rate of our proposed OTA is enhanced 387 times than that of the conventional counterpart with the same power. [ABSTRACT FROM AUTHOR]