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The aquatic environment in aquaculture serves as the foundation for the survival and growth of aquatic animals, while a high-quality water environment is a necessary condition for promoting efficient and healthy aquaculture development. To effectively guide early warnings and the regulation of water quality in aquaculture, this study proposes a predictive model based on a dual-channel and dual-attention mechanism, namely, the DAM-ResNet-LSTM model. This model encompasses two parallel feature extraction channels: a residual network (ResNet) and long short-term memory (LSTM), with dual-attention mechanisms integrated into each channel to enhance the model's feature representation capabilities. Then, the proposed model is trained, validated, and tested using water quality and meteorological parameter data collected by an offshore farm environmental monitoring system. The results demonstrate that the proposed dual-channel structure and dual-attention mechanism can significantly improve the predictive performance of the model. The prediction accuracy for pH, dissolved oxygen (DO), and salinity (SAL) (with Nash coefficients of 0.9361, 0.9396, and 0.9342, respectively) is higher than that for chemical oxygen demand (COD), ammonia nitrogen (NH3-N), nitrite (NO2−), and active phosphate (AP) (with Nash coefficients of 0.8578, 0.8542, 0.8372, and 0.8294, respectively). Compared to the single-channel model DA-ResNet (ResNet integrated with the proposed dual-attention mechanism), the Nash coefficients for predicting pH, DO, SAL, COD, NH3-N, NO2−, and AP increase by 12.76%, 12.58%, 11.68%, 18.350%, 19.32%, 16%, and 14.99%, respectively. Compared to the single-channel DA-LSTM model (LSTM integrated with the proposed dual-attention mechanism), the corresponding increases in Nash coefficients are 9.15%, 9.93%, 9.11%, 10.91%, 10.11%, 10.39%, and 10.2%, respectively. Compared to the ResNet-LSTM (ResNet and LSTM in parallel) model without the attention mechanism, the improvements in Nash coefficients are 1.91%, 2.4%, 0.74%, 3.41%, 2.71%, 3.55%, and 4.13%, respectively. The predictive performance of the model fulfills the practical requirements for accurate forecasting of water quality in nearshore aquaculture. [ABSTRACT FROM AUTHOR]

In phase‐shifting interferometric measurement system, using wavelength‐tuned phase‐shifting technology to measure optical surface can improve vibration errors. However, the wavelength‐tuned phase‐shifting interferometry is greatly challenged by nonlinear distortion between wavelength‐tuned light intensity and voltage modulation, which has a certain impact on phase calculation accuracy. To address this issue, an adaptive light intensity‐aided interferometric measurement scheme is proposed in this study. To improve the adjustment time of voltage response, an improved fuzzy single‐neuron adaptive proportional differential integral constant amplitude control algorithm is built. By exploiting the online detection and feedback control of light intensity, the stable output of light intensity is integrated into phase‐shifting measurement system. Experiment results verify that the improvement of light intensity fluctuation range, root mean square, and peak‐to‐valley measurement repeatability can be achieved with the proposed scheme. [ABSTRACT FROM AUTHOR]

Sensitive and stable triethylamine (TEA) gas sensors are desirable for environmental and human safety. However, the high operating temperature of the metal-oxide-based gas sensors poses a limitation on their wide applications. Herein, we fabricate an exceptional TEA gas sensor based on the core–shell heterostructure comprising crystalline CuO and amorphous In2O3/ZnO (CuInZnO) via a facile electrodeposition method. Remarkably, the optimum gas sensor (CuInZnO-3) exhibits an outstanding gas response (∼25) toward a 10 ppm TEA at room temperature. Moreover, CuInZnO-3 shows excellent selectivity, linear response, and stability. The superior sensing performance can be mainly ascribed to the unique core–shell nanorod heterostructure with a high specific surface area, allowing the formation of p–n junctions. The amorphous nature of the In2O3/ZnO shell also enriches the active oxygen on the surface and enhances gas adsorption. [ABSTRACT FROM AUTHOR]

We propose a strategy to etch dopants to construct Mo2C with more unsaturated coordination of Mo atoms and lattice distortion for enhanced catalytic activity. It is more effective than doping and etching pure Mo2C and provides a novel strategy for the preparation of catalysts with high catalytic activity. [ABSTRACT FROM AUTHOR]

The electrochemical corrosion behavior of X70 pipeline steel in a simulated solution of Qinzhou's strongly acidic latosol within a range of temperature from 30 °C to 70 °C was studied by electrochemical impedance spectroscopy, polarization curve measurement, immersion weight loss method, and X-ray diffraction. The effect of temperature on corrosion resistance of X70 pipeline steel was discussed. The results showed that as the temperature rose, the polarization resistance of X70 pipeline steel in the simulated solution decreased, the corrosion potential shifted negatively, and the corrosion current density increased, indicating that the corrosion rate of X70 pipeline steel increased and its corrosion resistance became worse. The dissolution of Fe occurred at the anode, while hydrogen evolution and oxygen depolarization occurred at the cathode. The phase constitution of the corrosion product on the surface of X70 pipeline steel was affected by variation of temperature. The corrosion products were the same at 30 °C and 40 °C, but different at 50, 60, and 70 °C, comprising γ-FeO(OH), Fe(OH)3, Fe3O4, α-FeO(OH), and Fe2O3. The film of corrosion product became looser with the increasing of temperature, and the corrosion of X70 pipeline steel became more and more serious. [ABSTRACT FROM AUTHOR]