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Integrating real‐time electrical gas sensing and highly identifiable surface‐enhanced Raman spectroscopy (SERS) for volatile organic compounds (VOCs) monitoring holds significant potential for safeguarding public health and safety. However, this technique remains in the proof‐of‐concept stage because the performance and reproducibility of devices fall short of meeting the practical application requirements. This work addresses this challenge by employing vortex engineering on a bifunctional dual‐layer array of Ni‐doped SnO2 (Ni‐SnO2) bowl‐coated on Ni‐SnO2/Au/SiO2 and developing highly reproducible device fabrication. In the dual‐layer array, vortices generated in upper Ni‐SnO2 bowls slow down the VOC flow and direct its delivery to gaps between lower Ni‐SnO2/Au/SiO2 units that are critical to SERS and electrical sensing. Experimental results show that the vortex effect in the array enables a low limit of detection of 10 ppb with a response and recovery in seconds. The excellent practicality of the array has been demonstrated through a ca. 100 hours of quantitative dual‐monitoring of styrene in a spacious environment (~60 m3) with a 5‐meter distance between the leakage source and the array. This work advances dual‐monitoring sensors for practical applications and offers insights for designing gas‐sensing materials and devices. [ABSTRACT FROM AUTHOR]

Foxtail millet is a traditional minor crop in China, known for its strong resistance to stress, tolerance to barren lands, and wide adaptation. Phosphorus is an essential element for crop growth and development, and the appropriate application of phosphorus can enhance crop yield and quality. However, the optimal phosphorus fertilization levels for the growth of foxtail millet have yet to be determined. This study aims to explore the effects of different phosphorus application levels (T1, T2, T3, and T4), on phosphorus accumulation and use efficiency and crop yield and quality in the foxtail millet cultivars 'B376' and 'B27', which have different phosphorus efficiencies. Additionally, we investigated the effects of phosphorus accumulation and use efficiency on the heading and filling stages of these cultivars. The results show that the total phosphorus content and accumulation levels in the 'B376' and 'B27' cultivars vary at different developmental stages and in different plant parts. Furthermore, crop yield and quality in both cultivars vary in response to the different phosphorus application levels. In terms of yield, the phosphorus-tolerant variety 'B376' reaches its highest at T2, while the phosphorus-sensitive variety 'B27' achieves its maximum yield at T3. For quality, 'B376' exhibits the highest moisture and crude fat content under T4, and the highest protein and the lowest amylose content under T3. On the other hand, 'B27' achieves its highest moisture content under T4, its highest crude fat and protein levels under T3, and its lowest amylose content under T2. Therefore, the response to different phosphorus application levels differs between the two cultivars with different phosphorus use efficiencies. Moreover, under different phosphorus fertilization levels, the average crop yield, moisture, fat, and amylose content averages of the phosphorus-tolerant 'B376' cultivar are 16.1%, 1.2%, 7.0%, and 4.1% higher than those of the phosphorus-sensitive 'B27' cultivar. Additionally, phosphorus use efficiency is positively correlated with the moisture and crude fat contents of foxtail millet. In conclusion, the phosphorus-tolerant cultivar demonstrates superior phosphorus accumulation, absorption, and utilization capacities compared to the phosphorus-sensitive cultivar. These results suggest that in the phosphorus-tolerant 'B376', optimal phosphorus fertilization levels enhance the development of roots, stems, and leaves at the T2 (P45) level, and promote the accumulation of moisture and crude fat in foxtail millet grains, thereby improving their taste and quality. Our findings provide a theoretical basis for phosphorus fertilizer utilization in foxtail millet cultivation and will help determine the optimal fertilization levels for foxtail millet growth. [ABSTRACT FROM AUTHOR]

In order to improve the optimization effect of the fruit fly optimization algorithm（FOA） on support vector machine（SVM） parameters, the evolution strategy of FOA was improved, and the duoble group coevolution fruit fly optimization algorithm（DGCFOA） was proposed in this paper. The DGCFOA was used to optimize the parameters of SVM and then used to gearbox fault diagnosis. Diagnosis results show that DGCFOA algorithm can obtained better SVM parameters when compared with FOA, it significantly improved fault diagnosis accuracy of gearbox. In addition, the diagnosis results also show that DGCFOA has higher diagnostic accuracy and more obvious advantages when compared with some other methods.