In this work, Bi₂O_3-x with surface oxygen vacancies was prepared through the NaBH₄ reduction of Bi₂O₃. After that, carbon quantum dots (CQDs) were deposited onto the surface of the Bi₂O_3-x to obtain a series of the CQDs/Bi₂O_3-x composites. The HRTEM and XPS characterizations of the CQDs/Bi₂O_3-x composites suggest that the thickness of surface oxygen vacancies could be adjusted by changing the concentration of NaBH₄ solution, and the intimate contact between CQDs and the Bi₂O_3-x is achieved. Acid orange 7 (AO7) was adopted as the target reactant for investigating the photocatalytic degradation activities of the CQDs/Bi₂O_3-x composites under simulated sunlight and NIR light irradiation. It is found that the photocatalytic activities of the samples are closely related to the concentration of NaBH₄ and content of CQDs. The Bi₂O_3-x samples exhibit enhanced simulated-sunlight-driven photocatalytic activity compared with Bi₂O₃. Specifically, the optimal degradation efficiency of AO7 is achieved over the 3R-Bi₂O_3-x (concentration of NaBH₄: 3 mmol/L), which is 1.38 times higher than the degradation AO7 efficiency over Bi₂O₃. After the decoration of the 3R-Bi₂O_3-x surface with CQDs, the simulated-sunlight-driven photocatalytic activity of the CQDs/Bi₂O_3-x composite could be further enhanced. Among the samples, the 15C/3R-Bi₂O_3-x sample reveals the highest photocatalytic activity, leading to an AO7 degradation percentage of ~97% after 60 min irradiation. Different from Bi₂O₃ and the 3R-Bi₂O_3-x, the 15C/3R-Bi₂O_3-x sample also exhibits near-infrared (NIR)-light-driven photocatalytic degradation activity. In addition, the intrinsic photocatalytic activity of CQDs/Bi₂O_3-x composite was further confirmed by the degradation of phenol under simulated sunlight and NIR light irradiation. The photocurrent response and electrochemical impedance spectroscopy (EIS) measurements confirm the efficient migration and separation of photogenerated charges in the CQDs/Bi₂O_3-x samples. The •OH and h⁺ are proved to be the main reactive species in the simulated sunlight and NIR light photocatalytic processes over the CQDs/Bi₂O_3-x composites. According to the above experiments, the photocatalytic degradation mechanisms of the CQDs/Bi₂O_3-x composites under simulated sunlight and NIR light illumination were proposed.

Location-based services are now playing an integral role in the development of emerging industries, such as the Internet of Things, artificial intelligence and smart cities. Although GPS, Beidou and other satellite positioning technologies are becoming more and more mature, they still have certain limitations. In order to meet the needs of high-precision positioning, wireless positioning is proposed as a supplementary technology to satellite positioning, in which the Received Signal Strength Indication (RSSI) is one of the most popular positioning methods. In this paper, the application scenarios, evaluation methods and related localization methods of wireless positioning based on RSSI are studied. Secondly, the relevant optimization methods are analyzed and compared from different angles, and the methods of RSSI data acquisition are described. Finally, the existing problems and future development trends in RSSI positioning methods are expounded, which has certain reference significance for further research on RSSI localization.

Peak detection is a crucial preprocessing step in the analysis of various spectral signals. The method based on the continuous wavelet transform is more practical and popular, and has better detection accuracy and reliability by identifying peaks across scales in the wavelet space and implicitly removing noise as well as the baseline. However, there are inevitably overlapping peaks in the measured spectra, and the formed composite ridges affect peak detection accuracy. Most peak detection methods have limited applicability to overlapping peaks. A weighted continuous wavelet transform (WCWT) peak detection algorithm is proposed to improve the adaptive ability of the peak detection method. This method yields more obvious spectral peak characteristics in low-scale regions. Composite ridges can be successfully truncated by setting a noise threshold based on the standard deviation of the spectral signal. In addition, the maximum value in the ridges was compressed and shifted to a smaller scale, which could determine the peaks more accurately. The method was applied to the peak detection of simulated spectra, Romanian database of Raman spectra, and real liquid electrode glow discharge spectra. The results show that the proposed method exhibits good peak detection performance.

Traditional rainfall data collection mainly relies on rain buckets and meteorological data. It rarely considers the impact of sensor faults on measurement accuracy. To solve this problem, a two-layer genetic algorithm–backpropagation (GA-BP) model is proposed. The algorithm focuses on multi-source data identification and fusion. Rainfall data from a sensor array are first used. The GA optimizes the weights and thresholds of the BP neural network. It determines the optimal population and minimizes fitness values. This process builds a GA-BP model for recognizing sensor faults. A second GA-BP network is then created based on fault data. This model achieves data fusion output. The two-layer GA-BP algorithm is compared with a single BP neural network and actual expected values to test its performance. The results show that the two-layer GA-BP algorithm reduces data fusion runtime by 2.37 s compared to the single-layer BP model. For faults such as lost signals, high-value bias, and low-value bias, recognition accuracies improve by 26.09%, 18.18%, and 7.15%, respectively. The mean squared error is 3.49 mm lower than that of the single-layer BP model. The fusion output waveform is also smoother with less fluctuation. These results confirm that the two-layer GA-BP model improves system robustness and generalization.