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High-throughput and label-free protein nanopore-based sensors are extensively used in DNA sequencing, single-protein analysis, molecular sensing and chemical catalysis with single channel recording. These technologies show great potential for identifying various harmful substances linked to public health by addressing the limitations of current portability and the speed of existing techniques. In this review, we provide an overview of the fundamental principles of nanopore sensing, with a focus on chemical modification and genetic engineering strategies aimed at enhancing the detection sensitivity and identification accuracy of protein nanopores. The engineered protein nanopores enable direct sensing, while the introduction of aptamers and substrates enables indirect sensing, translating the physical structure and chemical properties of analytes into readable signals. These scientific discoveries and engineering efforts have provided new prospects for detecting and monitoring trace hazardous substances. [ABSTRACT FROM AUTHOR]

The construction of heterostructures was considered to be an excellent strategy to achieve efficient charge separation and enhanced photocatalytic activity. Herein, the two-dimensional spherical In2S3 anchored onto the porous carbon nitride surface by a facile self-assembly process benefiting from the special structural design, and the composite material is endowed with a large specific surface area and more active sites. And the novel S-type heterojunction structure can not only greatly improve the problem of carrier recombination but also maintain a high redox potential, thus further enhancing the performance of photocatalysts. Results showed that the best total photocatalytic degradation and remarkable photocatalytic activity effect of CBZ reaches 98.3% after 120 min could be obtained at the g-C3N4/In2S3 under near room temperature and pressure and without using any sacrificial agents or promoters. The composite catalyst still exhibited excellent stability after five cycles. This work will provide the deep understanding of constructing interface engineering modulation, providing enlightenment for the design of high-performance photocatalysts. [ABSTRACT FROM AUTHOR]

Community integrated energy system coupled with renewable energy generation provides an effective solution to improve economy and reduce carbon emissions. This paper establishes a two‐stage multi‐objective optimal scheduling model for community integrated energy system. During the day‐ahead scheduling stage, a comprehensive customer dissatisfaction model based on Kano model is established, and the model takes total operating cost, comprehensive customer dissatisfaction, and carbon emissions as multi‐objectives. The Non‐dominate Sorting Genetic Algorithmic‐II (NSGA‐II) and the CRITIC‐TOPSIS evaluation model are used to develop a day‐ahead scheduling scheme. On the premise of ensuring customer dissatisfaction, the intra‐day scheduling stage evens out the uncertainty of wind power and photovoltaic power through rolling optimization and improves the reliability of system operation. Simulation results show that the proposed model reduces the total operating cost and carbon emissions by 8.1% and 12.8%, respectively, which validates the effectiveness of the proposed model. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]