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• Optical and acoustic modes can be independently designed in this hybrid waveguide. • Small-signal Stokes gain of 0.7 dB is observed. • The hybrid waveguide has efficient selectivity for the excited acoustic modes. On-chip stimulated Brillouin scattering (SBS) has attracted extensive attention by introducing acousto-optic coupling interactions in all-optical signal processing systems. In this article, we demonstrate stimulated intermodal Brillouin scattering (SIMBS) through a hybrid photonic-phononic silicon waveguide on the silicon-on-insulator (SOI) platform. The designed photonic-phononic waveguide can independently control the optical and acoustic fields by introducing the ridge waveguide as a line defect into the honeycomb lattice phononic crystal slab. Small-signal Stokes gain of 0.7 dB is achieved in a 1-cm long straight waveguide device with an on-chip pump power of 42.5 mW. Positive net Brillouin amplification is also expected by effectively reducing the linear loss. Our proposed device offers a potential approach to implementing Brillouin amplifiers, nonreciprocal devices, and signal processing in planar photonic integrated circuits. [ABSTRACT FROM AUTHOR]

• A high-precision real-time distributed optical fiber temperature and strain sensing system is achieved and demonstrated. • A nonlinear interpolation deep neural network (NIDNN) is proposed to interpolate and denoise for BGS. • A convolutional neural network based on depthwise separable convolution (BFSECNN) is proposed to shorten the BFS extraction. • The sweep time after using NIDNN is 1/6 of the hardware sweep time of 1-MHz interval for the 28.5-km long distributed Brillouin optical fiber sensor. • The BFSECNN extraction time is 3.7 s for 71,168 BGSs, 77 times faster than the Lorentzian curve fitting. Distributed Brillouin optical fiber sensors can detect temperature and strain over long distances in standard single-mode fibers from the measurement of their Brillouin gain spectrum (BGS). However, the performance of these sensors is restricted by parameters such as the frequency scanning interval, average times of data acquisition, and Brillouin frequency shift (BFS) extraction time. Therefore, achieving high-precision real-time monitoring is challenging. In this study, we introduce a nonlinear interpolation deep neural network (NIDNN) to interpolate and denoise the BGS. Additionally, we propose a BFS extraction convolutional neural network (BFSECNN) based on depthwise separable convolution (DSC) to shorten the BFS extraction and training time. Both the simulation and experimental results show that the NIDNN and BFSECNN contributed to higher accuracy in BFS extraction and shorter data processing time. The sweep time of the distributed Brillouin optical fiber sensor with a 28.5-km length after using the NIDNN is 1/6 of the hardware sweep time of the 1-MHz interval, and the BFSECNN extraction time is 3.7 s. Moreover, combining the NIDNN with the BFSECNN reduced the BFS uncertainty by 5.3 MHz at the end of the optical fiber. Used individually or together, the proposed NIDNN and BFSECNN could improve the performance of existing distributed Brillouin optical fiber sensors without any hardware modifications. [ABSTRACT FROM AUTHOR]

Improving the efficiency and productivity of the water supply sector is related to the mitigation of a country's water resources crisis and the governance of the water ecological environment. This paper employs a sequential data envelopment analysis (DEA) approach to examine the comparative efficiency of China's urban water industry by using the country-level data from 1998 to 2017, and then attempts to make a cross-country comparison of the technology gap in the urban water industry between China and major OECD countries. The results show that China's urban water sector performance is improving despite falling short of urban water development in the major OECD. The gap between the performance of China's urban water sector and that of major OECD countries is narrowing. Efficiency improvement has become the main driver of productivity growth of urban water sector in both China and the major OECD countries. Besides, the reduction of capital deepening in the water industry and the easing of water stress could improve the water industry's performance in efficiency. While increased foreign direct investment instead reduces the water industry's efficiency, increased R&D expenditure can improve efficiency, but both are not statistically significant. These findings indicate that compared to major OECD countries, China's urban water industry should strengthen the reform change as soon as possible from asset-heavy to asset-light operation and service, and then improve the water conservation system. [ABSTRACT FROM AUTHOR]

• A high SNR distributed optical fiber sensing system is achieved. • There is a corresponding relationship between the sensing distance and the optimal Raman pump power. • Both simulation and experiment analyze the probe light power and the system SNR distribution. • A BOTDR system assisted by first-order co-direction Raman pumping with window function is proposed. • The mathematical model of the window function is designed. Raman amplification can extend the sensing distance of distributed Brillouin optical fiber sensor, and there is a corresponding relationship between the optimal Raman pump, the sensing distance, and the lanched probe power. We propose a scheme of co-directional Raman pumping Brillouin optical time-domain reflectometer (BOTDR) with window functions to make a better tradeoff between sensing distance and signal-to-noise ratio (SNR). The mathematical model of window functions is designed based on the relationship between the sensing distance and Raman pump power. Both simulations and experiments analyze the distributions of Brillouin scattering power, which are detected under the fixed Raman pump and processed by the window functions. We then obtain the Brillouin frequency shift (BFS) distribution curve by Lorentzian curve fitting. The experimental results show that the system SNR is increased by 3.3 dB at the near-end of the 78.8 km long sensing fiber. Moreover, the accuracy of temperature and strain at the far-end is enhanced by 2.75 °C and 389 με by using window functions, respectively. [ABSTRACT FROM AUTHOR]