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In this paper, two ultra-wideband monopoles in a colinear structure are presented for application in remote terrestrial communication systems. The antennas consist of a loaded monopole with a hat and an elevated loaded monopole located in the upper position. All lumped loads are modeled as linear frequency-dependent components to approximate the practical component property for achieving ultra-wideband characteristics, since the constant value property of a component is only present in a relatively narrow band. The antennas are simulated by the method of moments (MoM) with asymptotic waveform evaluation (AWE) to speed up frequency sweep across a wide bandwidth. For proper simulation with the AWE process, the parallel RLC load with linear frequency-dependent components is modeled in a corresponding impedance function. With the optimized load parameters, one antenna covers 30–750 MHz with a VSWR < 3.5 and the other one covers 800 MHz–3000 MHz with a VSWR < 2.5, which are promising results for terrestrial omnidirectional applications.

The technical condition of bridges has become a crucial issue for organizing the maintenance and repairs in bridge management systems. It is of great practical engineering significance to construct an effective model for predicting the technical condition degradation of the bridge through the use of the historical inspection data. Based on the semi-Markov random process, this paper proposes a useful deterioration prediction model for bridges in the highway network. From the historical inspection data of the prefabricated concrete box girder bridges, the degradation curves of technical condition rating are obtained. The effect of bridge length on degradation rate of the prefabricated concrete box girder bridges is analyzed. According to the Weibull distribution parameters of different condition grades, the technical state degradation models for a bridge group and an individual bridge are proposed to predict the performance of the overall bridge and superstructure of the bridge. The results show that with the increase in bridge length, the degradation rate of bridge technical condition increases. The degradation rate of the technical condition of the superstructure is faster than that of the overall bridge. The proposed semi-Markov stochastic degradation model for the bridge group can not only predict the different condition ratings of the bridges at any time, but also predict the future deterioration trend of an individual bridge under any ratings.

The requirements of 5G/6G promote progress in the miniaturization of the antenna array, which promotes the development of a closely spaced decoupling technique. However, the present techniques face the common problem of beam tilt if the spacing is close. Thus, a pattern-corrected, closely-spaced technique is proposed in this paper for the two patch antennas with the λ0/20 edge-to-edge distance of the H-plane. The corresponding structure, which is inserted at the center of the spacing, consists of a vertical wall with a single substrate and two symmetrical T-type metals, and a slot at the center is reserved to adequately accommodate the vertical wall. The vertical strip at the other end of the T-type metal is connected to the ground of the patch antenna, while the parallel strip is placed exactly above the patch substrate. After an exact analysis, a prototype was fabricated and measured, and the results showed that the measurements agreed well with those of the simulations, the decoupling coefficients in the 5.8 GHz band were below −20 dB, and the measured radiation pattern at 5.81 GHz was corrected to the broadside from 28° and the maximum realized gain was 5.30 dB.

During the last two decades, managers have been applying Building Information Modeling (BIM) to improve the quality of management as well as operation. The effectiveness of applications within a BIM environment is restrained by the limited immersive experience in virtual environments. Defined as the immersive visualization of virtual scenes, Virtual Reality (VR) is an emerging technology that can be actively explored to expand BIM to more usage. This paper highlights the need for a structured methodology for the integration of BIM/VR and gives a generic review of BIM and VR in training platforms for management in infrastructures. The rationales for fire evacuation training were formed based on the review. Then, methods of configuring BIM + VR prototypes were formulated for emergency response in highway tunnels. Furthermore, a conceptual framework integrating BIM with VR was proposed to enable the visualization of the physical context in real-time during the training. The result indicated that, extended to the training system of highway management via the “hand” of BIM, the VR solution can benefit more areas, such as the cost of fire evacuation drills in highway tunnels and the tendency of accidents to occur in the emergency response.

Genetic association studies have discovered the GTF2I-NCF1 intergenic region as a strong susceptibility locus for multiple autoimmune disorders, with the missense mutation NCF1 rs201802880 as the causal polymorphism. In this work, we aimed to perform a comprehensive meta-analysis of the association of the GTF2I-NCF1 locus with various autoimmune diseases and to provide a systemic review on potential mechanisms underlying the effect of the causal NCF1 risk variants. The frequencies of the two most extensively investigated polymorphisms within the locus, GTF2I rs117026326 and NCF1 rs201802880, vary remarkably across the world, with the highest frequencies in East Asian populations. Meta-analysis showed that the GTF2I-NCF1 locus is significantly associated with primary Sjögren’s syndrome, systemic lupus erythematosus, systemic sclerosis, and neuromyelitis optica spectrum disorder. The causal NCF1 rs201802880 polymorphism leads to an amino acid substitution of p.Arg90His in the p47phox subunit of the phagocyte NADPH oxidase. The autoimmune disease risk His90 variant results in a reduced ROS production in phagocytes. Clinical and experimental evidence shows that the hypoactive His90 variant might contribute to the development of autoimmune disorders via multiple mechanisms, including impairing the clearance of apoptotic cells, regulating the mitochondria ROS-associated formation of neutrophil extracellular traps, promoting the activation and differentiation of autoreactive T cells, and enhancing type I IFN responses. In conclusion, the identification of the association of NCF1 with autoimmune disorders demonstrates that ROS is an essential regulator of immune tolerance and autoimmunity mediated disease manifestations.

Adaptive beamforming is sensitive to steering vector (SV) and covariance matrix mismatches, especially when the signal of interest (SOI) component exists in the training sequence. In this paper, we present a low-complexity robust adaptive beamforming (RAB) method based on an interference–noise covariance matrix (INCM) reconstruction and SOI SV estimation. First, the proposed method employs the minimum mean square error criterion to construct the blocking matrix. Then, the projection matrix is obtained by projecting the blocking matrix onto the signal subspace of the sample covariance matrix (SCM). The INCM is reconstructed by replacing part of the eigenvector columns of the SCM with the corresponding eigenvectors of the projection matrix. On the other hand, the SOI SV is estimated via the iterative mismatch approximation method. The proposed method only needs to know the priori-knowledge of the array geometry and angular region where the SOI is located. The simulation results showed that the proposed method can deal with multiple types of mismatches, while taking into account both low complexity and high robustness.

As a clean and efficient energy, natural gas is the main driving force for China’s energy transformation and the realization of green energy development. Distributed natural gas combined cooling, heating and power (DNG-CCHP) is the main utilization method of distributed natural gas with many advantages. However, the economics of China’s DNG-CCHP system are poor, hindering the healthy and sustainable development of the system in China. Thus, this paper systematically analyzes the factors affecting the economics of DNG-CCHP system in China. Firstly, through the analysis of the development status and obstacles of China’s DNG-CCHP system, the economic impact factor set of DNG-CCHP systems involving 34 factors is constructed. Then, the integrated DEMTTEL-ISM method is used to construct the multi-level hierarchical structure of influencing factors, the influence mechanism of the factors on the economics of DNG-CCHP system is systematically and comprehensively analyzed, and the path of improving system economics is proposed accordingly. Finally, based on the research findings and the development of China’s DNG-CCHP, the coordinated development of DNG-CCHP and distributed renewable energy was discussed, and several policy suggestions are put forward to contribute to the integration of distributed natural gas and distributed renewable energy.

With the development and grid-connection of renewable energy sources such as wind power, there are more and more uncertainties in power systems, and large-scale wind power has brought many challenges to the security and stability the systems. These uncertainties have to be eliminated by means of upward or downward regulations of conventional generators and charging/discharging services of energy storage devices. Based on the analysis of the influence of wind power uncertainties on the day-ahead electricity market, this article proposes a robust clearing model for the day-ahead electricity market considering the wind power penetration, which can help to complete the dispatch of power system. Compared with the traditional models, the proposed model is a multi-objective model, which considers both the lowest operating cost and the least wind power curtailment of power system. Moreover, the obtained dual multipliers λ corresponding to the power balance constraints reflect the marginal cost of the power production in a certain period, that is, the locational marginal price (LMP), which can be used as the clearing prices. This robust market clearing model takes into consideration the economic and reliability of the system operation and accommodates as much renewable energy as possible. The simulation of three wind power producers was implemented on the IEEE 30-bus test system, which verified the rationality of the proposed approaches.

This paper aims to explore China’s contributions to global green energy and low-carbon (GELC) development based on the Belt and Road (B&R) Initiative. Basic situations of B&R countries reveal an urgent requirement for developing green energy. Carbon intensity is an efficient indicator reflecting the degree of GELC development, which is affected by many factors. By analyzing the spatial distribution of carbon intensities in 29 B&R countries excluding China, the spatial agglomeration and positive radiation effects are discovered, while the negative radiation effects are disappearing, indicating that the studied B&R countries lack an effective driving mechanism to promote GELC development. Besides, the spatial convergence results support significant absolute and conditional convergences in the 29 B&R countries, and a faster convergence speed when considering control variables. Therefore, B&R countries trend to converge to a steady stable carbon intensity to achieve the GELC development. Furthermore, the investment rate and openness play a driving role in pushing the decrease of carbon intensity growth rate, revealing that the B&R Initiative can promote reducing the global carbon emissions and developing global green energy. Moreover, the carbon intensity of the country will be positively affected by those of the surrounding areas, indicating that reducing carbon emission is a global governance issue requiring the participation of all countries. Finally, several policy suggestions are proposed to promote the global GELC development under B&R framework, according to the empirical findings.

During the “13th Five-Year Plan” period, green energy is the top priority for China. China has realized that natural gas, as a low-carbon energy source, fits with the nation’s energy demand and will play a critical role in the energy transition, but the actual industry development is slower than expected. By analyzing the major gas corporations around the world, the paper finds that the key factors of the sector are supply and price of the energy resource. A comprehensive analysis on domestic and foreign imported gas reveals a trend of oversupply in China in the future. Given the critical import dependence, China has introduced a series of gas price reforms since 2013, which have led to negative impacts on important gas consumption sectors including power generation. With the levelized cost of electricity (LCOE) model, we find that under the prevailing gas supply structure and price level, the economy of utility gas power generation will remain unprofitable, while combined cooling heating and power (CCHP) is only commercially feasible in coastal developed regions. If continuing, such a trend will not only bring forth disastrous consequences to gas power industry, but also damage the upstream gas industry, more importantly, impede the energy transition. We conclude the paper with policy implications on pricing mechanism reform, developing domestic unconventional gas and the R&D of gas turbine.

The influences of MgO activity and its content on the mechanical properties, drying shrinkage compensation, pore structure, and microstructure of alkali-activated fly ash–slag materials were investigated. Active MgO effectively compensated for the alkali-activated materials’ (AAMs’) drying shrinkage. The drying shrinkage increased rapidly with the increase in curing age and stabilized after 28 d. Within a certain range, the material’s drying shrinkage was inversely proportional to the content of active MgO. The higher the activity of MgO, the lower the drying shrinkage of the AAMs under the same MgO content. The drying shrinkage values of the test groups with 9% R-MgO, M-MgO, and S-MgO at 90 d were 2444 με, 2306 με, and 2156 με, respectively. In the early stage of hydration, the addition of S-MgO reduced the compressive strength. As the content of M-MgO increased, the compressive strength first increased and then decreased, reaching a maximum of 72.28 MPa at an M-MgO content of 9%. The experimental group with 9% M-MgO exhibited higher compressive and flexural strengths than those with 9% S-MgO and R-MgO, demonstrating better mechanical properties. The results of this study provide an important theoretical basis and data support for the optimal application of MgO in AAMs. MgO expansion agents have great application potential in low-carbon buildings and durable materials. Further research on their adaptability in complex environments will promote their development for engineering and provide innovative support for green buildings.

To determine slag properties and the factors influencing these properties for optimization of operating conditions in the copper flash smelting process, the composition and microstructures of the quenched smelting and converting slags have been analyzed. Thermodynamic software FactSage 8.2 has been used to investigate the effects of matte grade, SO2 partial pressure, and the Fe/SiO2 ratio on the liquidus temperature and the copper content of the smelting slag. The possibility to recover valuable metals from the smelting and converting slags through pyrometallurgical reduction by carbon is also discussed. It was found that the flash smelting slag temperature is usually higher than its liquidus temperature and the copper (1.2% Cu) is mainly present in the slag as dissolved copper. In the copper flash smelting process, the copper content in the slag can be decreased by decreasing the Fe/SiO2 ratio and temperature. In pyrometallurgical slag reduction, most Cu, Mo, and Ni can be recovered as an alloy. The conditions of recovery such as the ratio of smelting slag to converting slag, temperature, and reduction extent have been discussed.

The spatial–temporal prediction of traffic flow is very important for traffic management and planning. The most difficult challenges of traffic flow prediction are the temporal feature extraction and the spatial correlation extraction of nodes. Due to the complex spatial correlation between different roads and the dynamic trend of time patterns, traditional forecasting methods still have limitations in obtaining spatial–temporal correlation, which makes it difficult to extract more valid information. In order to improve the accuracy of the forecasting, this paper proposes a multi-scale temporal dual graph convolution network for traffic flow prediction (MD-GCN). Firstly, we propose a gated temporal convolution based on a channel attention and inception structure to extract multi-scale temporal dependence. Then, aiming at the complexity of the traffic spatial structure, we develop a dual graph convolution module including the graph sampling and aggregation submodule (GraphSAGE) and the mix-hop propagation graph convolution submodule (MGCN) to extract the local correlation and global correlation between neighbor nodes. Finally, extensive experiments are carried out on several public traffic datasets, and the experimental results show that our proposed algorithm outperforms the existing methods.