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Nowadays, NPS abuse are continuing to expand in terms of harm and scope, due to its cheap and easy to manufacture anywhere in the world. This study reviewed articles related to seven heavily abused NPS to analyze the structure and trends of NPS abuse. A total of 2476 articles were retrieved based on the search strategy for bibliometric analysis. A significant trend of research in recent years was the increasing number of research on synthetic opioids and designer benzodiazepines, but synthetic cannabinoid and synthetic cathinone still dominate, which were mainly concerned with the development of metabolic models and determining methods as well as their abuse characteristics and reasons. However, with the introduction of class-wide ban on synthetic cannabinoid in China and a series of enhancements in other countries, the abuse of it might decrease to some extent, but more than 20 kinds of synthetic cannabinoid beyond the scope of ban in China still reminded researchers of their potential threats. As for synthetic cathinone, an important phenomenon was some of the drugs first identified during certain period might be more widely distributed in the future. Besides, several problems such as the regulation and prevention mode of emerging NPS, development of testing technologies as well as the interpretation and identification of multiple NPS combinations were also worth paying attention to. This study could help entrants better understand the structure of NPS abuse and provided direction for future research in forensic toxicology.

Urban air mobility is an effective solution to address the current issue of ground traffic congestion in future cities. However, as the user scale continues to expand, the current civil aviation flight scheduling and control methods are becoming inadequate to meet the high-volume flight guarantee demands of future urban air transportation. In order to effectively handle and resolve potential issues in this field in the future, this paper proposes a method for planning urban air mobility route networks. The planning process is divided into two stages: construction and optimization. Methods for constructing urban air mobility route networks based on flight routes and global optimization methods based on node movement are proposed in each stage. In the construction stage, a complete construction process is designed to generate routes based on existing flight routes, in line with the trend of urban air transportation development. In the optimization stage, inspired by the ant colony algorithm, node transfer rules and information transfer rules are incorporated to design a global optimization process and algorithm for route networks. Experimental results demonstrate the effectiveness and advancement of the proposed planning method.

ObjectiveIn order to solve the problem of time cooperative path planning for unmanned marine system (UMS) in complex environments, we propose a cooperative path planning method based on a differential evolution (DE) algorithm. MethodsFirst, natural environment and enemy threat models in the air, sea and underwater are established. The objective function of path planning with multiple constraints is constructed and a strategy proposed to solve the time coordination problem under the constraints of heterogeneous platforms starting at different times and places, but arriving at the same time and place. Next, a DE algorithm is used to optimize the solution, and the influence of the number of waypoints on the success rate of the planning is studied. ResultsBased on the reasonable selection of the number of waypoints, the DE algorithm can respectively plan the path that satisfies the time cooperative constraint for the UMS and find the shortest time to reaching the target in complex environments with multiple threats and obstacles. The results also show that either excessive or inadequate numbers of waypoints will result in success rate reduction of the path planning. ConclusionsThe results of this study show that the model and constraint conditions are reasonable, and the proposed algorithm can solve the problem of time coordination in the path planning of UMS, which has great practical application value.

Combining nanomaterials and waterborne resins is an effective way to obtain high-performance waterborne coatings. This paper provides a comprehensive overview on waterborne nanocomposite coatings based on the latest research progress at home and abroad. Specifically, the characteristics of zero-dimensional (0D), one-dimensional (1D), two-dimensional (2D) and binary hybrid (0D/1D, 0D/2D, 1D/2D, 2D/2D) nanomaterials and their applications in waterborne coatings are coherently reviewed. Subsequently, various modification methods of nanomaterials, especially noncovalent modification and covalent modification, are analyzed in detail. Additionally, the enhancement mechanisms of nanomaterials enhancing the corrosion resistance of waterborne nanocomposite coatings are also discussed, including physical barrier mechanism and electrochemical mechanism. Finally, based on the above discussion, the outlooks for the future design of waterborne nanocomposite coating are presented.

Abstract In recent years, tomato mottle mosaic virus (ToMMV) has become one of the most important viral pathogens affecting solanaceous crop production in Yunnan, Hainan, and Shandong provinces of China, often causing huge yield reductions. To provide farmers and vegetable industry with reliable and easy-to-use ToMMV detection methods, we immunized BALB/c mice with purified ToMMV and obtained six hybridoma cell lines (i.e., 2D6, 9C12, 26A10, 3A4, 23A4 and 17B11) that secrete anti-ToMMV monoclonal antibodies (MAbs) through the hybridoma technology. Using these MAbs as the detection antibody, we developed three serological assays: antigen-coated-plate enzyme-linked immunosorbent assay (ACP-ELISA), dot enzyme-linked immunosorbent assay (dot-ELISA) and tissue print enzyme-linked immunosorbent assay (tissue print-ELISA) for ToMMV detection. Our test results showed that these three newly developed serological methods can be used to specifically detect ToMMV infection in plant samples, but not tobacco mosaic virus, tomato mosaic virus, cucumber green mottle mosaic virus and cucumber mosaic virus. Sensitivity analyses further showed that ACP-ELISA and dot-ELISA can be used to detect ToMMV infection in plant crude extracts diluted at 1:81,920 and 1:40,960 (weight/volume, g/mL), respectively. Surprisingly, the detection limit of the developed dot-ELISA was 26 times higher than that of traditional RT-PCR. Using field-collected plant samples, we have demonstrated that these three new serological methods are accurate and easy-to-use for large-scale detection of ToMMV in fields.

Path planning is an important part of the unmanned aerial vehicle (UAV) to realize its autonomous capabilities. Aiming at the shortcomings of the traditional ant colony algorithm-based trajectory planning method, which has slow convergence speed and easy to fall into the local optimum, a path planning method based on the improved ant colony algorithm is proposed. First, a dynamic adjusting factor is added into the heuristic function to improve the directivity of path selection and search speed. Then, the state transition strategy is improved to solve the problem of slow convergence in the initial stage and easy to fall into local optimum in the later stage. Finally, the path inflection point is smoothly optimized through the cubic B-spline curve. Simulation results show that the improved ant colony algorithm can quickly converge to the optimal path and well adapt to the flight requirements of multirotor UAV.

Multi-UAV (unmanned aerial vehicle) mission collaboration is one of the current research hotspots in automation, artificial intelligence, and other fields. The difficulty and high cost of real flight verification have led to the problem that related knowledge learning focuses on theoretical derivation and ignores technical practice. In this paper, a multi-UAV mission simulation system is designed to show the greatest advantage of its collaborative mission planning results simulated and tested in 3D scenarios. It simultaneously reflects and records changes in UAV position, velocity, status, and other state values. The simulation program can be directly applied to real flight with only a few settings. First, the general system framework is presented. Second, according to the simulation requirements, the key modules involved in the software in the loop are given. Finally, through a path planning test for two UAVs, the effect of the system is demonstrated. The results show that the simulation verification based on the system is consistent with the real flight results in terms of functional implementation. It is applicable to the teaching process of related majors and can also provide support for the realization of many complex tasks in the future.

Plum pox virus (PPV) is a causal agent of the stone fruit tree sharka disease that often causes enormous economic losses. Due to its worldwide distribution and economic importance, rapid and reliable diagnostic technologies are becoming increasingly important for successful management of sharka disease. In this study, we have produced two super-sensitive and specific anti-PPV monoclonal antibodies (i.e., MAbs 13H4 and 4A11). Using these two MAbs, we have now developed a dot enzyme-linked immunosorbent assay (dot-ELISA) and a colloidal gold immunochromatographic strip (CGICS) assay. These two technologies can be used to quickly and reliably detect PPV. The results of these sensitivity assays confirmed that the dot-ELISA and CGICS assays could detect PPV infection in apricot tree leaf crude extracts diluted up to 1:5120 and 1:6400 (w/v), respectively. Further analyses using field-collected apricot tree leaf samples showed that the detection endpoint of the dot-ELISA was ~26 times above that obtained through RT-PCR, and the CGICS was as sensitive as RT-PCR. This present study is to broaden the knowledge about detection limits of dot-ELISA and CGICS for PPV monitoring. We consider that these newly developed dot-ELISA and CGICS are particularly useful for large scale PPV surveys in fields.

Aiming at the problem of the wide range and great difficulty in the future of battlefield airspace control, based on the unique advantages of an airspace grid system in an airspace grid representation and time–space binary computing, this paper designs a pre-clustering method for mission airspace based on airspace location correlation under the condition of future large-scale air combat missions in order to realize the block control of battlefield airspace. This method reduces the whole 3D battlefield space projection to a 2D plane and regards the task airspace projection as “obstacles” in the task area; Multi-A * algorithm is used to generate the airspace clustering line surrounding the task airspace, and the airspace association clustering problem is transformed into a multiple “start point-end point” path planning problem with autonomous optimization. Through the experiment, it was found that clustering the airspace can effectively improve the management and control efficiency of large-scale battlefield airspace.

Weather radar provides regional rainfall information with a very high spatial and temporal resolution. Because the radar data suffer from errors from various sources, an accurate quantitative precipitation estimation (QPE) from a weather radar system is crucial for meteorological forecasts and hydrological applications. In the South China region, multiple weather radar networks are widely used, but the accuracy of radar QPE products remains to be analyzed and improved. Based on hourly radar QPE and rain gauge observation data, this study first analyzed the QPE error in South China and then applied the Quantile Matching (Q-matching) method to improve the radar QPE accuracy. The results show that the rainfall intensity of the radar QPE is generally larger than that determined from rain gauge observations but that it usually underestimates the intensity of the observed heavy rainfall. After the Q-matching method was applied to correct the QPE, the accuracy improved by a significant amount and was in good agreement with the rain gauge observations. Specifically, the Q-matching method was able to reduce the QPE error from 39–44%, demonstrating performance that is much better than that of the traditional climatological scaling method, which was shown to be able to reduce the QPE error from 3–15% in South China. Moreover, after the Q-matching correction, the QPE values were closer to the rainfall values that were observed from the automatic weather stations in terms of having a smaller mean absolute error and a higher correlation coefficient. Therefore, the Q-matching method can improve the QPE accuracy as well as estimate the surface precipitation better. This method provides a promising prospect for radar QPE in the study region.

Airborne-launched AUVs withstand great fluid impact force at the early stage when entering the water, which may cause damage to their structure and inner components in severe cases. Due to their large volume and mass, the major challenge involved in conducting experiments to measure the water entry impacts on real-life AUVs is the high demand for the experimental devices, finding a suitable site, and the cost of the experiments. Using a gas gun as launching device, water entry experiments using a full-size AUV model are conducted under various conditions. The axial and radial force changes that occur during the water entry process are obtained, and some accompanied phenomena such as cavitation and turnover under different water entry conditions are observed. Computational fluid dynamics (CFD) is used to simulate the water entry process of airborne-launched AUVs. The simulation results fit well with the experimental data, the latter of which show that both the water entry velocity and entry angle have a great influence on the impact load during the water entry process. These data can provide valuable reference information for AUV structure design and launch condition selection.

According to the characteristics of AUV movement, a fuzzy sliding mode controller was designed, in which fuzzy rules were adopted to estimate the switching gain to eliminate disturbance terms and reduce chattering. The six-degree-of-freedom model of AUV was simplified and longitudinal motion equations were established on the basis of previous research. The influences of first-order wave force and torque were taken into consideration. The REMUS was selected to simulate the control effects of conventional sliding mode controller and fuzzy sliding mode controller. Simulation results show that the fuzzy sliding mode controller can meet the requirements and has higher precision and stronger antijamming performances compared with conventional sliding mode controller.