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Accurately measuring the current is crucial for assessing the operational status of the line. The tunnel transmission approach presents challenges due to its intricate line layout in limited space. Utilizing non-contact current measurement offers a superior alternative. To suppress the potential magnetic interference in the transmission tunnel, a novel M-shaped magnetic shielding design for current measurement is proposed. The structure is used to measure current in triangularly arranged conductors where magnetic interference exists at random position. First, a one-dimensional and two-dimensional sensor system based on a triangular arrangement of conductors are used to analyze the magnetic field. Then, the structure of the magnetic shielding is derived. The relationship between the geometrical parameters of shielding structure and the position of the sensors with mean shielding uncertainty (MSU) is discussed by finite element analysis (FEA) method. At current of 2000 A in the conductors, the lowest MSU for the M-shape shielding structure (0.19%) is significantly lower than the lowest MSU for the C-shape shielding (1.63%). Moreover, the M-shaped shielding fits better with the geometry of conductors. In addition, thickness of the shielding structure, position of shielding structure and position of sensors are optimized based on the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The FEA method is used to simulate magnetic field interference acting on a three-phase AC current with an amplitude of 2000A. The two-dimensional sensor system with shielding structure can reduce the root mean square error (RMSE) of current to be measured from 14.42% to 3.79%.

Previous reinforcement learning (RL) methods suffer significant performance degradation or collapse when deployed to the real world due to the huge sim-real gap. This article proposes a hybrid offline-and-online meta-RL (HOMRL) algorithm that leverages prior task experience to learn and adapt to new pantograph active control tasks in real-world applications. The policy learning process consists of three phases: offline meta-policy pretraining, online adaptation, and fine-tuning. First, we construct an offline meta-RL approach that learns from the massive and heterogeneous static training datasets, eliminating online interaction's high cost and hazard. Second, we combine context-based meta-RL with online fine-tuning to generalize to challenging tasks, while high safety and success rates are critical in railway applications. Finally, the proposed environment-sensitive task encoder (TE) and well-trained agent can adapt to new tasks quickly and efficiently, even in unseen tasks and nonstationary environments. If the new task is similar to the prior data, the contextual meta-learner adapts immediately. If it is too different, it gradually adapts through fine-tuning.

Organic aerosols (OA) constitute an important fraction of fine particulate matter (PM2.5) air pollution, yet accurate and efficient OA modeling within chemical transport models (CTM) remains a challenge. Volatility basis set (VBS) schemes for OA have demonstrated improved performance in simulating OA, particularly for primary organic aerosol (POA), but their computational complexity impedes application to advanced modeling tasks, such as detailed source apportionment. Conversely, simpler “two-product” schemes are efficient and compatible with source apportionment techniques but many of them tend to overestimate POA by treating it as non-volatile. Either VBS or 2-product schemes can perform well for secondary organic aerosol (SOA) depending upon the data and assumptions used to model SOA formation from precursors. In this study, we update the Comprehensive Air Quality Model with extensions (CAMx) “SOAP” 2-product modeling framework by (1) treating POA as semivolatile using an efficient scheme, (2) adding SOA formation from semivolatile organic compounds (SVOCs), and (3) adopting SOA yields derived from the widely-used Community Multiscale Air Quality (CMAQ) AERO7 scheme. The first update allows temperature-dependent partial evaporation of POA to SVOC, which is subsequently oxidized in the gas phase. For the latter two updates, SOA yields are updated to emulate the AERO7 scheme based on an offline conceptual model. We implemented these changes within the existing SOAP2 scheme of CAMx to create a new scheme called “SOAP3”. A series of CTM simulations were conducted with the SOAP3 scheme to simulate OA and its components in China during July and November 2018. Results were validated against surface observations and compared to the SOAP2 and AERO7 schemes. Compared to SOAP2, SOAP3 substantially reduced POA proportions (by 10–24%) and increased SOA concentrations (by 45–193%) for selected regions. SOAP3 performs more like the AERO7 scheme than SOAP2 in terms of the simulated OA components and improved accuracy compared to observations. Uncertainties and limitations of the current SOAP3 scheme are also discussed. Our study demonstrates a feasible and readily implemented methodology for improving two-product OA modeling, which is currently employed in many CTMs.

In high-speed railways, the pantograph-catenary system (PCS) is a critical subsystem of the train power supply system. In particular, when the double-PCS (DPCS) is in operation, the passing of the leading pantograph (LP) causes the contact force of the trailing pantograph (TP) to fluctuate violently, affecting the power collection quality of the electric multiple units (EMUs). The actively controlled pantograph is the most promising technique for reducing the pantograph-catenary contact force (PCCF) fluctuation and improving the current collection quality. Based on the Nash equilibrium framework, this study proposes a multiagent reinforcement learning (MARL) algorithm for active pantograph control called cooperative proximity policy optimization (Coo-PPO). In the algorithm implementation, the heterogeneous agents play a unique role in a cooperative environment guided by the global value function. Then, a novel reward propagation channel is proposed to reveal implicit associations between agents. Furthermore, a curriculum learning approach is adopted to strike a balance between reward maximization and rational movement patterns. An existing MARL algorithm and a traditional control strategy are compared in the same scenario to validate the proposed control strategy’s performance. The experimental results show that the Coo-PPO algorithm obtains more rewards, significantly suppresses the fluctuation in PCCF (up to 41.55%), and dramatically decreases the TP’s offline rate (up to 10.77%). This study adopts MARL technology for the first time to address the coordinated control of double pantographs in DPCS.

Active pantograph control is the most promising technique for reducing contact force (CF) fluctuation and improving the train’s current collection quality. Existing solutions, however, suffer from two significant limitations: 1) they are incapable of dealing with the various pantograph types, catenary line operating conditions, changing operating speeds, and contingencies well and 2) it is challenging to implement in practical systems due to the lack of rapid adaptability to a new pantograph-catenary system (PCS) operating conditions and environmental disturbances. In this work, we alleviate these problems by developing a revolutionary context-based deep meta-reinforcement learning (CB-DMRL) algorithm. The proposed CB-DMRL algorithm combines Bayesian optimization (BO) with deep reinforcement learning (DRL), allowing the general agent to adapt to new tasks quickly and efficiently. We evaluated the CB-DMRL algorithm’s performance on a proven PCS model. The experimental results demonstrate that meta-training DRL policies with latent space swiftly adapt to new operating conditions and unknown perturbations. The meta-agent adapts quickly after two iterations with a high reward, which require only ten spans, approximately equal to 0.5 km of PCS interaction data. Compared with state-of-the-art DRL algorithms and traditional solutions, the proposed method can promptly traverse scenario changes and reduce CF fluctuations, resulting in an excellent performance.

We developed a new copper foil sample treated with (2-(Methylthio)pyrimidin-4-yl)methanamine (MET) for 2h, which can remarkably improve anti-corrosion performance and peel strength. First-principles calculations confirmed that the S-Cu and N-Cu bonds were both formed on the Cu (1 1 1) surface for MET, which contributes to the improved stability of the coating. In contrast, only the S-Cu bond was found for 2-(Methylsulfanyl)pyrimidin-4-amine (AMI). [Display omitted] • A new copper foil sample treated with (2-(Methylthio)pyrimidin-4-yl)methanamine for 2 h (MET/Cu-2 h) was developed, which can remarkably improve anti-corrosion performance and peel strength. • The surface of copper foil treated with MET for 2 h is flat enough to transmit high-speed and high-frequency signals. • First-principles calculations confirmed that not only the methymercapto-(CH 3 S-) in MET could react with copper, but also the nitrogen in the methylamino group could form Cu–N bonds, which contributes to the improved stability of the coating. In this experiment, two similar molecules with bifunctional groups have been characterized to prove the advantages of dual-anchor molecular coating in the interfacial modification of the copper foil. The physicochemical properties of the modified copper foils have been studied. The obtained results indicate that the anti-corrosion performance and peeling strength were significantly improved for the copper foil treated with (2-(Methylthio)pyrimidin-4-yl)methanamine (MET), whose bonding information was analyzed via the density functional theory calculation. It was found that the S-Cu and N-Cu bonds were both formed on the Cu (1 1 1) surface for MET coating, and the adsorption of the double anchor points improves the stability of the interface. The peeling test exhibits the function of MET coating as the adhesion promotor between low-surface profile copper and resin for high-speed signal transmission. [ABSTRACT FROM AUTHOR]

Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the “air pollution complex” was first proposed by Professor Xiaoyan TANG in 1997. For papers published in 2021 on air pollution (only papers included in the Web of Science Core Collection database were considered), more than 24 000 papers were authored or co-authored by scientists working in China. In this paper, we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years, including studies on (1) sources and emission inventories, (2) atmospheric chemical processes, (3) interactions of air pollution with meteorology, weather and climate, (4) interactions between the biosphere and atmosphere, and (5) data assimilation. The intention was not to provide a complete review of all progress made in the last few years, but rather to serve as a starting point for learning more about atmospheric chemistry research in China. The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established, provided robust scientific support to highly successful air pollution control policies in China, and created great opportunities in education, training, and career development for many graduate students and young scientists. This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances, whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China, to hopefully be addressed over the next few decades.

Catenary components, such as the messenger wire base (MWB) and rotary double ear (RDE), are important connection components in railway power supply systems. They may exhibit crack or break defects, which can be monitored using a recent advanced anomaly detection model called student–teacher feature pyramid matching (STPM), with advantages in accuracy and speed. However, the STPM has several problems with MWB and RDE crack detection: 1) crack defects are not obvious in the low-light catenary images due to inadequate illumination, which may lead to difficulties in detecting dark cracks; 2) target knowledge is not used during knowledge distilling, which weakens the generalization ability of the detection model; and 3) complex surface conditions of the components can cause detection errors, but it lacks a further correction step. This article proposes a novel crack detection method called enhanced coarse-to-fine (ECF)-STPM to address these issues. First, an image enhancement method, self-calibrated illumination (SCI) learning, is introduced to improve image quality. It can make the features of dark cracks more obvious and easier to extract. Second, a novel coarse-to-fine model is constructed for crack recognition. In the coarse stage, a new teacher network that introduces the target component classification task rather than the original general object classification task is proposed. In the correction stage, a binary classification convolutional neural net (CNN) based on data augmentation is built to correct the error labels of crack segments predicted by the coarse stage. In experiments, this article evaluates the effect of each proposed module independently and the overall performance of the whole model on a real-life catenary component dataset. The test results show that the proposed ECF-STPM method effectively detects MWB and RDE cracks in catenary systems.

Acid mine drainage (AMD) has a low pH and a high concentration of sulfates and heavy metals and its untreated discharge contributes to environmental pollution. Traditional bio-oxidation is less effective in removing Fe3+and few studies have reported passive treatment using biological oxidation. Here, based on the biofilm formation on the surface of an elastic filler by iron-oxidizing bacteria, we proposed a novel treatment system for AMD involving a combination of bio-oxidation and addition of carbonate rocks prior to the neutralization phase. The results showed that the Fe2+oxidation efficiency and total iron (TFe) removal efficiency reached 40.18–55.00% and 5.86–17.39% (during Fe2+oxidation without carbonate rocks) as well as 39.09–52.64% and 25.09–47.33% (during Fe2+oxidation with carbonate rocks), respectively. The corresponding values for the control group (single carbonate neutralization) were 24.22–34.73% and 12.31–30.14%, respectively. The X-ray diffractometry and scanning electron microscopy results showed that carbonate rock addition in the oxidation section regulated the acidic environment and provided favorable conditions for schwertmannite formation. Additionally, schwertmannite provided ideal attachment conditions for bacteria. High-throughput sequencing revealed that Acidithiobacillusand Leptospirillumdominated the biological oxidation stage, accounting for more than 75% of bacteria. This demonstrated that Acidithiobacillusand Leptospirillumcould co-exist in passive processing systems as the dominating flora. The results can be used as a basic data reference for the development of a process and method for the combined treatment of AMD by biological oxidation and carbonate rock neutralization.

The pantograph-catenary system (PCS) is the essential power supply system in the high-speed railway, but its coupling performance is influenced significantly by the rapidly increasing train speed. The actively controlled pantograph is one of the promising technologies to suppress the fluctuation of the pantograph-catenary contact force (PCCF). In this paper, we propose a novel pantograph control strategy based on deep reinforcement learning (DRL) to overcome the complex time-varying characteristic of PCS, which distorts the system identification of the classical control methods. First, a non-linear pantograph-catenary system model is established based on the finite element and multi-body dynamics theory as the simulation environment in DRL. Then, the state space, action space, and reward in DRL are redesigned to train the agent, which is suitable for PCS. Finally, the effectiveness and robustness of our proposed method are verified under various working conditions and parameter disturbances. The experiment results show that our control strategy can reduce the PCCF fluctuation up to 40% and reject parametric perturbation while achieving state-of-the-art performance on the benchmarks.

Although there is a general consensus about the importance of providing access to combinatorial information in specialized dictionaries and term banks, few terminological resources actually record collocations. More importantly, since most terminological resources are concept-based, their structures are not adapted to the description of this linguistic phenomenon. This paper presents a methodology and descriptive model designed to include Chinese collocations in a multilingual  resource which focuses on environment terminology. The methodology is corpusbased and the descriptive model (based on Explanatory and Combinatorial Lexicology (Mel’?uk et al., 1995)) aims to account for the lexico-semantic properties of collocations. We first comment on the characteristics of Chinese collocations that need to be taken into consideration and that can differ from collocations in other languages. Then, we describe the DiCoEnviro, a multilingual terminological resource on the environment, and the methodology devised to compile it. We then focus on collocations and explain how some parts of the methodology for their collection and lexicographical description need to be adapted to Chinese.

Binders play an important role in the safety of plastic bonded explosives (PBX). For the performance improvement of HMX-based explosive, the impact safety for the explosive using thermoplastic polyurethane (Estane5703) as binder, was investigated by comparing with that using fluorine rubber (F2604). By experiments performed with a self-designed impact test device to measure critical ignition velocity, it was found that the critical ignition velocity (277.36 m/s) of Estane5703-containing explosive was 9.3% higher than that of F2604-containing explosive. By analyzing the particle size distribution and morphological characteristics of the impacted powder, it could also be inferred that Estane5703 binder had better bond behavior than F2604. Beside, combustion characteristics of impacted powder were compared in a closed combustion vessel. The results indicated that the maximum combustion pressure (Pmax) of the Estane5703-containing impacted explosive powder was 56.5% lower than that of F2604-containing impacted explosive powder. The combustion duration of the Estane5703-containing impacted powder was 24.1% longer than that of F2604-containing powder, suggesting that the combustion of the former was milder. Therefore, it can be concluded that the Estane5703-containing explosive has better impact safety than the F2604-containing explosive due to the higher bond strength of Estane5703.

Environmental contextPhytoremediation requires an understanding of bioconcentration and translocation processes that determine behaviour and fate of potentially toxic elements. We studied the distribution of antimony and arsenic in terrestrial and aquatic soil-plant systems in an antimony ore zone. We found that the common climbing plant Kudzu (Pueraria lobata) is suitable for phyto-stabilisation of antimony-bearing tailings, while tiger grass (Thysanolaena maxima) was able to extract antimony and arsenic from contaminated soils. AbstractAntimony (Sb) pollution is a major environmental issue in China. Many historical abandoned tailings have released high concentrations of Sb and its associated element arsenic (As) to surrounding environments. This has prompted the need to understand accumulation and translocation processes that determine the behaviour and fate of Sb and As in contaminated soil–plant systems and to identify suitable plant species for phytoremediation. Here we investigate distribution of Sb and As in terrestrial and aquatic dominant plant species and associated soils, all of which are naturally found in an Sb ore concentration area in south-west China. Total Sb and As concentrations were measured by inductively coupled plasma mass spectrometry (ICP-MS). The percentage of soluble Sb and As in the total concentrations were determined; the results showed that the basic soil environment facilitates the release of Sb and As from contaminated soils, and that Sb has higher mobility than As. Bioconcentration factor (BCF) and translocation factor (TF) were used for evaluating the ability of plants to accumulate and transport Sb and As, respectively. The results indicated that all selected plant species have the potential to tolerate high concentrations of Sb and As. Consequently, this study suggested that Pueraria lobata (PL) can be used as the preferred species for phytostabilisation of abandoned Sb-bearing tailings, given that PL has well-developed roots and lush leaf tissues and the ability to translocate Sb from roots to aboveground parts. Thysanolaena maxima (TM) is suitable for phyto-extraction of Sb and As in contaminated soils.

As a kind of high-efficiency explosive with compound destructive capability, the energy output law of thermobaric explosives has been receiving great attention. In order to investigate the effects of main components on the explosive characteristics of thermobaric explosives, various high explosives and oxidants were selected to formulate five different types of thermobaric explosive. Then they were tested in both open space and closed space respectively. Pressure measurement system, high-speed camera, infrared thermal imager and multispectral temperature measurement system were used for pressure, temperature and fireball recording. The effects of different components on the explosive characteristics of thermobaric explosive were analyzed. The results showed that in open space, the overpressure is dominated by the high explosives content in the formulation. The addition of the oxidants will decrease the explosion overpressure but will increase the duration and overall brightness of the fireball. While in closed space, the quasi-static pressure formed after the explosion is positively correlated with the temperature and gas production. In addition, it was found that the differences in shell constraints can also alter the afterburning reaction of thermobaric explosives, thus affecting their energy output characteristics. PVC shell constraint obviously increases the overpressure and makes the fireball burn more violently.

ABSTRACTWe collected tailings samples to assess and analyze the concentrations of heavy metals, pollution levels, and the risks posed by heavy metals in the tailings of the Zuoxiguo antimony mine to ecological and human health. The samples were selected by employing the serpentine sampling method, which were treated heavy-metal digestion method. Cu, Cr, Cd, and Pb were determined via inductively coupled plasma mass spectrometry, As and Sb were identified through atomic fluorescence, the average concentration of heavy metals in the tailings is: Sb (5902.77 mg/kg)>As (412.53 mg/kg)>Zn (155.42 mg/kg)>Cr (143.32 mg/kg)>Cu (92.68 mg/kg)>Pb (48.49 mg/kg)>Cd (3.29 mg/kg). The average Nemerow pollution index (NPI) was 553.06, indicating a high level of pollution. The average integrated ecological risk index (RI) result was 5395.94, indicating a serious threat to the study area’s ecology. The Non-carcinogenic health-risk index (HQ) suggested that all heavy metals posed a higher risk to children than to adults under different modes of exposure, with oral intake of Sb and As posing a non-carcinogenic risk to both adults and children, For adults, HQingvalue of Sb and As are 22.07 and 2.13, respectively; for child, HQingvalue of Sb and As are 178 and 16.29, which are exceeding limitation of 1. Dermal exposure posing a non-carcinogenic risk to child, for child, HQdermvalue of Sb and As are 14.96 and 3.32, which are also exceeding limitation of 1. The findings suggest that Sb and As pose serious threats to both the ecological environment and human health and that the local government should focus on Sb and As management for regions.

The field observations imply that the long‐range transport of carbon dioxide (CO2) emitted by biomass burning (BB) in Southeast Asia might impact the atmospheric CO2in South China, while the transboundary path and the contributions of long‐range transport on atmospheric CO2concentrations in South China remain poorly understood. In this study, a regional air quality model system (RAQMS) was developed by incorporating the atmospheric process of CO2to investigate the impacts of BB in Southeast Asia on tropospheric CO2concentration over South China in spring during 2009–2018. CO2emissions from BB in Southeast Asia in spring varied greatly from 2009 to 2018, and high monthly mean emissions were concentrated in the west of Myanmar, the border between Myanmar, Thailand and Laos, the north of Laos, and Cambodia, with the maximum reaching 1.0 g m−2hr−1. Higher monthly mean concentrations of near surface CO2and tropospheric CO2produced by BB were mainly distributed in the source regions of Southeast Asia and South China. The monthly mean tropospheric CO2concentrations produced by BB in Southeast Asia were higher in March 2010, 2014, and 2015, which were obviously related to the interannual variation of BB emission, and affected by the atmospheric circulation as well. The contribution of BB emission in Southeast Asia to the net change of tropospheric CO2concentration in South China presented a belt distribution from the southwest to the northeast, with a domain average of 5.7%–38.6% over South China in March 2009–2018. Biomass burning (BB) frequently occurs in spring in Southeast Asia, releasing large amounts of carbon dioxide (CO2) and influencing ecosystem gross primary productivity, which are helpful to warm the Earth. Previous studies mainly pay attention to the impacts of transboundary BB pollutants on air quality in South China, while researches involved with the transboundary CO2from BB in Southeast Asia and its impacts on atmospheric CO2are very limited. This study investigates and quantifies the impacts of BB in Southeast Asia on tropospheric CO2concentration over South China in spring during 2009–2018 through model development and simulation. Several sensitivity experiments are conducted to test the impact of emissions from different inventories on the simulation results and to identify the primary affecting factor for the transboundary CO2mass from Southeast Asia to China, for example, BB emission amount and meteorological condition. This study provides valuable insights into the transboundary process of the CO2from BB in Southeast Asia and the contribution of BB emissions and transmissions to tropospheric CO2concentration over South China, which could be of great significance in carbon accounting and climate change researches. Impacts of biomass burning in Southeast Asia on tropospheric CO2concentration over South China during 2009–2018 are investigatedThe transboundary CO2from biomass burning significantly increases the atmospheric CO2concentration in South China in springBiomass burning emission amount is the primary factor affecting the mass of transported CO2to South China Impacts of biomass burning in Southeast Asia on tropospheric CO2concentration over South China during 2009–2018 are investigated The transboundary CO2from biomass burning significantly increases the atmospheric CO2concentration in South China in spring Biomass burning emission amount is the primary factor affecting the mass of transported CO2to South China

Experiments were conducted to simultaneously remove NO and SO2from simulated exhaust gas by cyclic scrubbing and online supplementing pH-buffered NaClO2solutions in a bench-scale reactor. The effects of key operating parameters on pollutant removal performance had been investigated. The results suggested that an extremely high oxidant utilization rate could be obtained when the oxidant supplementing molar rate approached the oxidant consumption molar rate. Though co-existing SO2in flue gas would consume a certain amount of the oxidant during the absorption process, the intermediate products of SO32–ions generated from SO2hydrolysis might be in favor of NO2absorption to some extent. The introduction of ethanol in scrubbing solution could enhance NOxremoval performance largely, which was possibly because of its inhibition effect on SO32–oxidation. The reaction mechanism and reaction products in scrubbing solutions were also discussed roughly through theoretical calculations and ion chromatography analysis.

Oblique Bracing Wire (OBW) is an important device of catenary support components (CSCs), which supports the lower steady arm and the registration tube to keep the overhead line high and the pull-out value within the specified range. OBW fault can cause unstable train operation or safety hazards to trains and passengers. With the development of deep learning, it has been tried to achieve the precise location and fault detection of the CSCs to ensure the stable operation of the train. In this article, three deep learning frameworks called Faster RCNN ResNet101, SSD (Single shot multi-box detector) and YOLOv2(You only look once) are used to achieve location for Bracing wire hook and Messenger wire base respectively. Through the comparison of the location effects of the three frameworks on CSCs, the Faster RCNN ResNet101 is chosen as the framework for location. Then curvature detection algorithm is used for loose default of OBW. The experiment results show that the proposed fault detection method has high diagnostic rate and universality.

The development of fluorine-free MXene based composites for electrochemical energy storage and conversion devices is considered to be a promising approach. Herein, we used Lewis acid Fe (III) to etch Ti3AlC2successfully to prepare MXene with in-situ loaded Fe2O3nanoparticles. The three-dimensional porous aerogels co-doped with S and N were synthesized by the redox self-assembly reaction of MXene and graphene oxide in the hydrothermal condition containing thiourea. XPS results show that S and N heteroatoms can enhance the hydrophilicity and pseudo-capacitance of the composites by changing the electronic structure of adjacent C atoms and forming S-C/N-C bonds. The specific capacitance of the optimized Fe3+-Ti3C2Tx/S,N-rGO-2 is 220.7 F g−1at 1 A g−1, and the capacitance retention rate is above 80 % after 5000 cycles at a current density of 6 A g−1. The all-solid-state symmetric supercapacitor with Fe3+-Ti3C2Tx/S,N-rGO-2 as electrode materials, and PVA-KOH as electrolyte can work normally in extreme environments of 60 and −20 °C, respectively. This work provides a viable route for the fluorine-free preparation of MXene and its electrochemical application.

The interaction between the catenary and pantograph is one of the most crucial factors that determine the train operation in high-speed railway. The bad state of catenary is able to directly influence the power supply safety of traction power system. In this paper, four aspects on the catenary research of high-speed railway are reviewed in detail, namely the solution methods for catenary equilibrium state, the dynamic modeling methods of catenary, non-contact detection methods of catenary, and the static and dynamic evaluation methods of catenary. In addition, their recent advances are described. For the low solution accuracy of the initial equilibrium state of catenary, the structure finding method with multi-objective constraint and nonlinear finite element procedure are introduced to solve the problem. For the catenary’s dynamic modeling, considering the influence of environmental wind on the catenary, environmental wind simulations and wind tunnel tests are used to obtain the aerodynamic coefficients and build the wind field along the catenary for analysis of its wind vibration characteristics. In order to improve the detection accuracy of non-contact detection for the catenary, the deep learning theory and real-time detection algorithms should be adopted in the future. In view of the lack of dynamic assessment method for the catenary, the modern spectrum evaluation, time–frequency analysis, big data technology and their combinations will be the important means for future catenary evaluation.

The stability of arsenic (As) and antimony (Sb) was best under neutral condition (7 or so).Antimony (Sb) stability is affected by maintenance days and adding amount.The morphology and composition of the tailing changed obviously at 28 days.The pH of acidic tailings was adjusted by applying alkaline amendments.Realizing waste recycling and waste treatment, controlling the migration and transformation process of Sb and As.

Nanodiamonds (NDs) prepared by the explosion method possess very large surface energies, resulting in serious agglomerates, limiting their further application. Herein, we employed the strong shearing action of hydroxyl ion (OH–) to induce the hydrolysis of esters between the ND primary particles, generating the carboxyl and hydroxyl groups, breaking hard agglomeration of NDs, and successfully constructed electrical double layers on the surface of NDs via deprotonation of surface oxygen-containing groups induced by the strong shearing action of hydroxyl ion (OH–), leading to a significant increase of zeta potential absolute value (−54.2 mV), achieving the long-term stable (200 days) monodispersion of NDs (m-NDs). The as-obtained m-NDs, as efficient nanofillers, were added into the waterborne epoxy (WEP) to produce a composite coating of m-NDs/WEP, displaying a considerable improvement in anticorrosion performance. The results of electrochemical impedance spectroscopy show that the |Z|f= 0.01 Hzof m-NDs/WEP is nearly 3 orders of magnitude higher than that of pure WEP after 168 h of immersion. The excellent anticorrosion performance of m-NDs/WEP can be ascribed to the excellent compatibility, electrical insulation property, and physical barrier behavior of m-NDs, inhibiting the infiltration of corrosive medium. The molecular dynamics simulation reveals that m-NDs have good barrier properties against a corrosive medium.

ABSTRACTGuanine nucleotide-binding (G) proteins, namely, phosphate-binding (P) loop GTPases, play a critical role in life processes among different species. Based on the structural characteristics, G proteins can be divided into heterotrimeric G proteins, small G proteins and multiple unique unconventional G proteins. The highly conserved unconventional G protein YchF is composed of a core G domain, an inserted coiled-coil domain, and a TGS domain from the N-terminus to the C-terminus. In this review, we compared the structural characteristics of the G domain in rice OsYchF1 with those of Rattus norvegicusheterotrimeric G protein α-subunit and human small G protein Ras-related G protein C and analyzed the binding modes of these G proteins with GTP or ATP by performing molecular dynamics simulations. In summary, it will provide new insights into the enormous diversity of biological function of G proteins.

The practical applications of enzymes are usually hampered by their fragile nature, poor reusability, and high costs. Enzyme immobilization has been considered to be a powerful solution to these problems. Metal-organic frameworks (MOFs) are an emerging class of porous materials that have unique features such as high surface area, tunable porosity, diverse architectures, and relatively high stability. These properties make them an ideal platform for enzyme immobilization. Laccases are versatile oxidases capable of oxidizing various organic compounds due to their broad substrate specificity. Integration of laccases with MOFs enables the generation of novel laccase-MOFs biocomposites with improved stability and activity as well as excellent recyclability. In recent years, a large number of laccase-MOFs biocomposites have been synthesized for promising applications in bioremediation, biosensing, and organic synthesis. This review summarizes recent advances in general strategies for preparing laccase-MOFs biocomposites, such as physical adsorption, covalent attachment and in situ encapsulation. It further discusses the catalytic performance of laccase-MOFs biohybrids including stability, reusability and catalytic activity. Then the potential applications of MOFs-immobilized laccases are introduced with special emphasis on biodegradation of numerous environmental pollutants. Finally, the current challenges and future prospects for the development and application of laccase-MOFs biocatalysts are also discussed.

A closed-form displacement response of track subjected to loads moving at variable speeds is proposed in this paper. The structure of the track is modeled as a Timoshenko beam of infinite length that is periodically supported by double-layer spring-damping elements. The frequency-domain displacement response of the track is simplified into the mathematical form of a summation rather than an integral. The transfer function for the track is expressed in the form of a transfer matrix. Various kinds of moving loads, such as single and series moving forces, masses and double-layer mass systems, are considered in calculations. For the verification of the theory, the displacement response of a simply supported beam subjected to masses moving at variable speeds is calculated and compared with reports in the literature on the same case. The obtained results indicate that the influence of the loads moving at variable speeds on the displacement response of the track cannot be ignored, and the displacement response of the track increases slightly with acceleration of the moving loads. Also, larger oscillations are generated by the interaction of the moving mass and the track.

Titanium aircraft component has been considering difficult-to-cut not only for the poor machinability of material itself but also for the complexity of its structure which generally consists of thin-ribs, thin-webs, corners, pockets, etc. Structural features are therefore as important as material properties for the selection of cutting tools when machining titanium aircraft components. In this paper, a new method of cutting performance evaluation of end mills was proposed for the machining process of titanium aircraft components. A test benchmark with typical difficult-to-cut features extracted from aircraft components was first designed as well as its machining process. In order to comprehensively evaluate the cutting performance, fuzzy comprehensive evaluation (FCE) models which considered the tool wear, material removal rate, surface roughness and dimension error were developed for rough and finish end milling respectively. Finally, experiments of milling the benchmark were carried out, and then the FCE models were applied to evaluate the cutting performance of end mills. The results show that the method is suitable and effective to evaluate cutting performance of end mills for titanium aircraft components.

To delineate the groundwater flow system in a basin, the groundwater age was estimated by analyzing chlorofluorocarbons (CFC-11, CFC-12 and CFC-113) in a typical headwater wetland in Ichikawa, Japan. Feasibility of groundwater dating by CFCs was assessed comprehensively based on the concentrations of NO3−, SO42−, Fe2+and dissolved CH4in the groundwater, because the CFCs would be degraded under the reduction condition available in a wetland. It was found that the CFC-11 apparent age was much older than that estimated by other CFC species. It showed that CFC-12 and CFC-113 were suitable tracers for groundwater dating because of their stability in the wetland environment. Furthermore, the mixture of groundwater with different age was discussed by CFC-12 and CFC-113 based on the binary mixing model and piston-flow model. As a result, the apparent age of groundwater in the study area is in the range of 38–48 years.

Abstract: Based on simulated major aerosol concentrations (e.g., sulfate, nitrate, ammonium, organic carbon, black carbon, and sea salt) over East Asia during the year 2005 by using the Multi-scale Air Quality modeling system (RAMS-CMAQ), the aerosol optical depth (AOD) was calculated by the reconstruction mass-extinction method and then analyzed to explore its characteristics in temporal-spatial distributions. For evaluating the model performances, simulated AOD values were compared against observations at stations of the Aerosol Robotic Network (AERONET) and the Chinese Sun Hazemeter Network (CSHNET). The comparison shows that the model can well reproduce observed temporal and spatial features of AOD, especially in natural environment. However, the simulated AOD values are underestimated over urban and suburban regions with dense human activities. Analysis of simulation results indicates that AOD varies significantly in time and space, and generally, AOD values are lower in summer and higher in winter. Excluding the contribution from soil dust aerosols, high AOD values (over 0.8) are found over the Sichuan Basin, South China, and Central China in several months, while low values (less than 0.2) are over northern and western areas of East Asia and southern sea regions. Analysis also shows that aerosols such as sulfate, nitrate, and ammonium are main contributors to AOD in East Asia, and their contributions are over 80% in most high AOD areas, while black carbon aerosols play an important role in northern China where dense human activities exist, especially in the winter time.

Troposphärische Chemie- und Aerosolprozesse sind kürzlich in das Regionale Integrierte Umweltmodell-System RIEMS eingebaut worden, um den direkten Strahlungsantrieb (DRE) durch Aerosol über Ostasien, wo starkes Bevölkerungs- und Wirtschaftswachstum stattfindet, zu berechnen. Es wurden fünf Aerosol-Komponenten (Sulfate, schwarzer Kohlenstoff, organischer Kohlenstoff, Staub und Seesalz) in RIEMS eingefügt, wobei die Gasphasenchemie durch den CB-IV-Mechanismus beschrieben wird. Die Monate März, Juli, Oktober und Dezember 2006 werden als für die vier Jahreszeiten Ostasiens typische Zeiträume untersucht. Die modellierten Monatsmittel der aerosol-optischen Dicke (AOD) stimmen generell mit MISR-Daten überein, obwohl das Modell zu einer Unterschätzung in einigen Gebieten neigt. Die AOD-Verteilung war durch hohe Werte in Ostchina und den Wüsten Westchinas gekennzeichnet, wobei die Winterwerte die niedrigsten waren. Der direkte Strahlungsantrieb zeigt jahreszeitliche Variationen mit einem Maximum im März und einem Minimum im Winter am Boden gegenüber einem Maximum im Juli und einem Minimum im Winter am Oberrand der Atmosphäre (TOA). Die leichte Erwärmung am Atmosphärenoberrand im März unter all-sky-Bedingungen ist sowohl auf absorbierendes Aerosol als auch auf den Erwärmungseffekt durch Wolken zurückzuführen. Gemittelt über das ostasiatische Untersuchungsgebiet und alle vier Jahreszeiten liegt der direkte Strahlungsantrieb zwischen -6,2 W m-2 am Boden und -0,2 W m-2 am Atmosphärenoberrand.

A convenient method for methane (CH4) direct conversion to methanol (CH3OH) is of great significance to use methane-rich resources, especially clathrates and stranded shale gas resources located in remote regions. Theoretically, the activation of CH4and the selectivity to the CH3OH product are challenging due to the extreme stability of CH4and relatively high reactivity of CH3OH. The state-of-the-art ‘methane reforming - methanol synthesis’ process adopts a two-step strategy to avoid the further reaction of CH3OH under the harsh conditions required for CH4activation. In the electrochemical field, researchers are trying to develop conversion pathways under mild conditions. They have found suitable catalysts to activate the C–H bonds in methane with the help of external charge and have designed the electrode reactions to continuously generate certain active oxygen species. These active oxygen species attack the activated methane and convert it to CH3OH, with the benefit of avoiding over-oxidation of CH3OH, and thus obtain a high conversion efficiency of CH4to CH3OH. This mini-review focuses on the advantages and challenges of electrochemical conversion of CH4to CH3OH, especially the strategies for supplying electro-generated active oxygen species in-situto react with the activated methane.

Maintenance of catenary system is a crucial task for the safe operation of high-speed railway systems. Catenary system malfunction could interrupt railway service and threaten public safety. This article presents a computer vision algorithm that is developed to automatically detect the defective rod-insulators in a catenary system to ensure reliable power transmission. Two key challenges in building such a robust inspection system are addressed in this work, the detection of the insulators in the catenary image and the detection of possible defects. A two-step insulator detection method is implemented to detect insulators with different inclination angles in the image. The sub-images containing cantilevers and rods are first extracted from the catenary image. Then, the insulators are detected in the sub-image using deformable part models. A local intensity period estimation algorithm is designed specifically for insulator defect detection. Experimental results show that the proposed method is able to automatically and reliably detect insulator defects including the breakage of the ceramic discs and the foreign objects clamped between two ceramic discs. The performance of this visual inspection method meets the strict requirements for catenary system maintenance.