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To provide real-time safety assessment for low-altitude unmanned aerial vehicle (UAV) air traffic management, and to ensure the UAVs safe operation in low-altitude airspace, a risk assessment framework is proposed. It considers the accidents probability and the accidents hazards. Firstly, accidents probability model based on the System Theoretic Process Analysis-Bayesian Network (STPA-BN) algorithm is built. Potential system hazards are effectively identified and analyzed through the STPA process. The accidents cause identified based on the STPA process is taken as the root node. The relevant failure probability table is given respectively. It constitutes the BN used to analyze the system accidents probability. This method uses a combination of qualitative and quantitative methods to calculate the accidents probability. Then, based on the UAV fall model, considering the uncertainty of the UAV operation process, the UAV fall point distribution is determined based on the Monte-Carlo method, and the impact area of the fall is calculated. Thus the system risk value is obtained. Finally, through case analysis, the validity and rationality of the proposed risk assessment framework are verified.

In order to solve the unfair individual payment costs problem in the low-altitude unmanned aerial vehicle (UAV) conflict resolution process, a multi-UAV conflict resolution algorithm based on the cooperative game concept “coalition complaint value” is proposed. Firstly, based on the low-altitude multi-UAV conflict scene characteristics, according to the “coalition complaint value” concept, the UAV conflict resolution payment matrix is established. Secondly, combined with the advantages of the artificial potential field (APF) method and the genetic algorithm (GA), a hybrid solution strategy for conflict resolution based on APF-GA is proposed. The final simulation results show that the APF-GA hybrid solution strategy has the best efficiency by combining the three evaluation indicators of calculation time, feasibility, and system efficiency. The reliability of the proposed algorithm is verified based on the Monte Carlo algorithm. The solution strategy based on the cooperative game “coalition complaint value” can improve individual fairness to a certain extent. At the same time, it can achieve the rapid planning goal with priority drones at the expense of a small amount of overall benefits.

Along with the advancement of low-altitude airspace reform, it has become a developing trend that UAV leaves the isolation airspace and gets into the fusion low-altitude airspace to perform diverse missions. A serious threat is brought to UAV in the low dynamic complex fusion airspace, so the obstacle avoidance technology has become a key process in UAV mission decision-making system, to ensure the safe operation of the UAV and to improve working efficiency. Firstly, the relevant concepts, path evaluation indexes and key technologies of UAV obstacle avoidance are described. Then, the concepts of obstacle avoidance algorithms based on optimization, potential field and machine learning are described, and the advantages and disadvantages of these algorithms are compared. Finally, the current challenges that restrict the development of UAV obstacle avoidance and the future research directions are proposed.

To determine optimal gestational weight gain (GWG) for the Chinese population. Live singleton deliveries at the largest maternal & childcare hospital in northwest China from 2010 to 2012 were analyzed retrospectively. Multivariable logistic regression analysis was conducted to determine the lowest aggregated risk of interested perinatal outcomes based on Chinese adult body mass index (BMI) categories. Eight thousand eight hundred seventy enrolled parturients were divided into 4 groups according to their prepregnancy BMI: underweight (21.31%, BMI

Additional file 1. CD44 promotes hepatocellular carcinoma progression via upregulation of YAP.

Traditional computer architecture consists of six parts: controller, arithmetic unit, memory, storage, input and output. The memory access speed is fast, but the capacity is small and data is lost when power fails. Any data that is in the storage with large capacity is not lost when computer lose power, but access speed is slow. Therefore, in traditional architecture, both memory and storage is indispensable. At present, with the birth and development of non-volatile random access memory, it provides an important premise that two kinds of memory put into one. Based on this, a new computer architecture based on dual-space memory is proposed. The new architecture is implemented by the shift latch on the hardware, so the data in terabyte storage space can be random accessed. In this paper, the working principle of this new architecture is described in detail. Finally, the advantages of the new computer architecture compared with the traditional are pointed out.

We prepare α-Fe2O3 nanosheet supported 0.38, 0.81, and 1.36 wt% Au (average particle size = 4.0 nm) nanocatalysts, and investigate their performance and mechanism for the selective catalytic oxidation of isopropanol to acetone. In the presence of 1.2 vol% isopropanol and 40 vol% O2, 1.36 wt% Au/α-Fe2O3 exhibits excellent catalytic performance, due to its moderate acidic sites and better redox properties, with acetone selectivity and yield being as high as 99% and 95% at 220 oC, respectively. In addition to acetone, little propylene, acetic acid, acetaldehyde, methyl vinyl ketone, 2-butanone, isopropyl ether, isopropyl acetate, 3-penten-2-one, isopropyl acrylate, isopropyl propionate, and 2, 4-dimethylfuran are detected. The possible reaction mechanism is proposed for the selective catalytic oxidation of isopropanol to acetone over the present catalysts. We believe the present selective catalytic oxidation method, rather than the traditional complete catalytic oxidation method, provides an alternative and economic method for VOCs emissions control.

Recently, type-II Dirac fermions characterized by strongly titled Dirac cones have been proposed. The new fermions exhibit unique physical properties different from the type-I Dirac fermions in graphene, and thus attract tremendous attentions. Up to date, all type-II fermions are only found in the heavy compounds with strong spin obit coupling. Here, we propose that both type-I and type-II Dirac fermions can exist in the graphene embedding nitrogen-molecule line defects (NMLDs). While the types of Dirac fermions are determined by the size W of graphene nanoribbons between the line defects. By comparing the two types of Dirac fermions, their different physical properties and originations are revealed directly. Remarkably, the type-I Dirac points induce one Fermi arc corresponding to edge states along the armchair direction, while the type-II Dirac points induce two Fermi arcs corresponding to two sets of edge states along the zigzag direction. These results not only expand our views on the Dirac fermions in two-dimensional structures, but also extend their applications in electronics.