Multitype satellite observation, including optical observation satellites, synthetic aperture radar (SAR) satellites, and electromagnetic satellites, has become an important direction in integrated satellite applications due to its ability to cope with various complex situations. In the multitype satellite observation scheduling problem (MTSOSP), the constraints involved in different types of satellites make the problem challenging. This article proposes a mixed-integer programming model and a generalized profit representation method in the model to effectively cope with the situation of multiple types of satellite observations. To obtain a suitable observation plan, a deep reinforcement learning-based genetic algorithm (DRL-GA) is proposed by combining the learning method and genetic algorithm. The DRL-GA adopts a solution generation method to obtain the initial population and assist with local search. In this method, a set of statistical indicators that consider resource utilization and task arrangement performance are regarded as states. By using deep neural networks to estimate the <inline-formula> <tex-math notation="LaTeX">$Q$</tex-math> </inline-formula> value of each action, this method can determine the preferred order of task scheduling. An individual update strategy and an elite strategy are used to enhance the search performance of DRL-GA. Simulation results verify that DRL-GA can effectively solve the MTSOSP and outperforms the state-of-the-art algorithms in several aspects. This work reveals the advantages of the proposed generalized model and scheduling method, which exhibit good scalability for various types of observation satellite scheduling problems.

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Premise plumbing plays an essential role in determining the final quality of drinking water consumed by customers. However, little is known about the influences of plumbing configuration on water quality changes. This study selected parallel premise plumbing in the same building with different configurations, i.e., laboratory and toilet plumbing. Water quality deteriorations induced by premise plumbing under regular and interrupted water supply were investigated. The results showed that most of the water quality parameters did not vary under regular supply, except Zn, which was significantly increased by laboratory plumbing (78.2 to 260.7 µg/l). For the bacterial community, the Chao1 index was significantly increased by both plumbing types to a similar level (52 to 104). Laboratory plumbing significantly changed the bacterial community, but toilet plumbing did not. Remarkably, water supply interruption/restoration led to serious water quality deterioration in both plumbing types but resulted in different changes. Physiochemically, discoloration was observed only in laboratory plumbing, along with sharp increases in Mn and Zn. Microbiologically, the increase in ATP was sharper in toilet plumbing than in laboratory plumbing. Some opportunistic pathogen-containing genera, e.g., Legionella spp. and Pseudomonas spp., were present in both plumbing types but only in disturbed samples. This study highlighted the esthetic, chemical, and microbiological risks associated with premise plumbing, for which system configuration plays an important role. Attention should be given to optimizing premise plumbing design for managing building water quality.

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While spintronic memories, for example, spin transfer torque magnetic random access memory (STT-MRAM), have shown huge potential for building next-generation memory due to their attractive characteristics, the relatively large write latency and deficient read mechanism preclude their further application for emerging concepts, such as in-memory-processing and neuromorphic computing. A toggle spin torque (TST) MRAM combining STT and spin orbit torque (SOT) has recently been proposed to alleviate the write issue. However, the sensing featuring a good balance between the reliability and speed has not been addressed. In this paper, we propose a self-matching complementary-reference (SMCR) sensing scheme, which provides not only a maximum sensing margin (SM) but also a high-speed read operation. Through applying it in the TST-MRAM, advantageous performance in terms of both write and read processes can be realized. To validate the functionality of our proposal, we design and evaluate an 8Kb TST-MRAM array, in which a read delay of 1 ns and a read bit error rate (BER) of 1.02 × 10-13 are achieved. Moreover, when being operated at 0.8 V supply voltage, it can reduce the read access energy by 7.5% and 20%, compared with conventional voltage sensing and dynamic reference sensing schemes, respectively. @en

Microwave heating is an encouraging heating technology for the maintenance, recycling, and deicing of asphalt pavement. To investigate the microwave heating properties of asphalt mixture, laboratory tests and numerical simulations were done and compared. Two types of Stone Mastic Asphalt (SMA) mixture samples (with basalt aggregates and steel slag aggregates) were heated using a microwave oven for different times. Numerical simulation models of microwave heating of asphalt mixture were developed with finite element software COMSOL Multiphysics. The main thermal and electromagnetic properties of asphalt mixture, served as the model input parameters, were measured through a series of laboratory tests. Both laboratory-measured and numerical simulated surface temperatures were recorded and analyzed. Results show that the replacement of basalt aggregates with steel slag aggregates can significantly increase the microwave heating efficiency of asphalt mixture. Numerical simulation results have a good correlation with laboratory test results. It is feasible to use the developed model coupling electromagnetic waves with heat transfer to simulate the microwave heating process of asphalt mixture.@en

Hairpin shaped Kelvin-Helmholtz waves are observed in tomographic PIV experiments on a micro-ramp wake. In this study, these waves are reproduced by applying BiGlobal stability theory to base flows conceived with the measurement data. The stability results converge with the number of instantaneous snapshots used for the base ow. The most unstable wavelength lies in the experimentally observed range and the flow structure closely resembles that shown in the snapshots.@en