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To solve the contradiction between limited spectrum resources and increasing communication demand, this paper proposes a wireless resource allocation scheme based on the Deep Q Network (DQN) to allocate radio resources in a downlink multi-user cognitive radio (CR) network with slicing. Secondary users (SUs) are multiplexed using non-orthogonal multiple access (NOMA). The SUs use the hybrid spectrum access mode to improve the spectral efficiency (SE). Considering the demand for multiple services, the enhanced mobile broadband (eMBB) slice and ultrareliable low-latency communication (URLLC) slice were established. The proposed scheme can maximize the SE while ensuring Quality of Service (QoS) for the users. This study established a mapping relationship between resource allocation and the DQN algorithm in the CR-NOMA network. According to the signal-to-interference-plus-noise ratio (SINR) of the primary users (PUs), the proposed scheme can output the optimal channel selection and power allocation. The simulation results reveal that the proposed scheme can converge faster and obtain higher rewards compared with the Q-Learning scheme. Additionally, the proposed scheme has better SE than both the overlay and underlay only modes.

Heterogeneous base station deployment enables to provide high capacity and wide area coverage. Network slicing makes it possible to allocate wireless resource for heterogeneous services on demand. These two promising technologies contribute to the unprecedented service in 5G. We establish a multiservice heterogeneous network model, which aims to raise the transmission rate under the delay constraints for active control terminals, and optimize the energy efficiency for passive network terminals. A policy-gradient-based deep reinforcement learning algorithm is proposed to make decisions on user association and power control in the continuous action space. Simulation results indicate the good convergence of the algorithm, and higher reward is obtained compared with other baselines.

Two different D-A type zine-based-COFs synthesized from 2,4,6-trihydroxy-benzene-1,3,5-tricarbaldehyde and triazine or heptazine were combined with ZnIn2S4(ZIS) and S vacancies were in-situ introduced in ZIS, successfully constructing two Z-scheme composite photocatalysts (CMa/VS-ZIS and CHt/VS-ZIS) for photocatalytic CO2reduction. The orderly donor-acceptor structure within the COF in the composite photocatalysts enhances intramolecular charge transfer and separation through push-pull electronic interactions. The COF/ZIS heterojunction effectively promotes the separation of photogenerated charge carriers, and the S vacancies further facilitate electron transfer from COF and ZIS, inhibiting charge recombination while serving as active sites to promote the conversion of CO2to CO. Both composite photocatalysts show significantly improved photocatalytic CO2reduction activity and selectivity compared to ZIS and the respective COFs. Compared to the triazine acceptor, the larger conjugated heptazine acceptor is more conducive to transferring photogenerated electrons from donor to acceptor within the COF. The synergistic effect of D-A charge difference and S vacancies more effectively enhances the separation efficiency of photogenerated carriers. CHt/VS-ZIS exhibited higher efficiency for CO2reduction to CO than CMa/VS-ZIS. This study provides a strategy for designing and synthesizing COF/ZIS heterojunction photocatalysts for photocatalytic CO2reduction.

The cognitive network has become a promising method to solve the spectrum resources shortage problem. Especially for the optimization of network slicing resources in the cognitive radio access network (RAN), we are interested in the profit of the mobile virtual network operator (MVNO) and the utility of secondary users (SUs). In cognitive RAN, we aim to find the optimal scheme for the MVNO to efficiently allocate slice resources to SUs. Since the MVNO and SUs are selfish and the game between the MVNO and SUs is difficult to reach equilibrium, we consider modeling this scheme as a Stackelberg game. Leveraging mathematical programming with equilibrium constraints (MPEC) and Karush-Kuhn-Tucker (KKT) conditions, we can obtain a single-level optimization problem, and then prove that the problem is a convex optimization problem. The simulation results show that the proposed method is superior to the noncooperative game. While guaranteeing the Quality of Service (QoS) of primary users (PUs) and SUs, the proposed method can balance the profit of the MVNO and the utility of SUs.

ABSTRACTA new process has been developed for inclusion removal. This process involves the creation and dispersion of fine bubbles in molten steel by calcium carbonate powder injection through the nozzles of the up-snorkel in RH (Ruhstahl Hausen Process) degasser. The plant trials have been carried out in ANSTEEL and the ruling factors have been analysed. The results indicate that this novel technique is beneficial to separate the small non-metallic inclusion removal from the molten steel. Compared with the conventional inclusion removal technology, the number of the oxide inclusions can be decreased to a lower level and the inclusion becomes finer. Using this novel technology, the total oxygen in the as-cast slab can approach 6 ppm.

A new process has been developed for inclusion removal. This process involves the creation and dispersion of fine bubbles in molten steel by calcium carbonate powder injection through the nozzles of the up-snorkel in RH (Ruhstahl Hausen Process) degasser. The plant trials have been carried out in ANSTEEL and the ruling factors have been analysed. The results indicate that this novel technique is beneficial to separate the small non-metallic inclusion removal from the molten steel. Compared with the conventional inclusion removal technology, the number of the oxide inclusions can be decreased to a lower level and the inclusion becomes finer. Using this novel technology, the total oxygen in the as-cast slab can approach 6 ppm.

Highly time-resolved measurements of water soluble ions, organic and elemental carbon concentrations in the particle diameter size range Dp< 2.5 μm (PM2.5) were performed at a downwind urban site in Nanjing in the western part of the Yangtze River Delta (YRD) in eastern China during the 2014 Youth Olympic Games (YOG). In this study, we discuss the impacts of emission control in Nanjing and the surrounding areas during the YOG and regional/long-range transport on PM2.5pollution in Nanjing. The average concentrations of NO3−, SO42−, NH4+were 12.1 ± 9.9, 16.5 ± 9.2, 9.0 ± 5.4 μg m−3during the YOG, and increased 34.3%, 53.7%, 43.9% after the YOG, respectively. The control of construction or on-road soil dust and control of industry led to the decrease of Ca2+concentration by 55% and SO2concentration by 46%. However, SO42−concentrations remained at relatively high levels, suggesting a significant impact of regional pollution to secondary fine particles in Nanjing. Strong correlations between OC and EC were observed during and after the YOG. A higher percentage (41%) of secondary organic carbon in Nanjing during the YOG periods was consistent with high potential photochemistry and low contributions from coal combustion. Lagrangian dispersion modelling results proved that the city clusters along the Nanjing and Shanghai axis were the major source region for high PM2.5pollution in upwind Nanjing. This work shows that short-term strict control measures could improve the air quality, especially that affected by the primary pollutants; however, regional collaborative control strategy across administrative borders in the YRD is needed for a substantial improvement of air quality.