Collaborative Spectrum Sensing for Illegal Drone Detection: A Deep Learning-Based Image Classification Perspective

Drones,also known as mini-unmanned aerial vehicles(UAVs),are enjoying great popularity in recent years due to their advantages of low cost,easy to pilot and small size,which also makes them hard to detect.They can provide real time situational awareness information by live videos or high definition pictures and pose serious threats to public security.In this article,we combine collaborative spectrum sensing with deep learning to effectively detect potential illegal drones with states of high uncertainty.First,we formulate the detection of potential illegal drones under illegitimate access and rogue power emission as a quaternary hypothesis test problem.Then,we propose an algorithm of image classification based on convolutional neural network which converts the cooperative spectrum sensing data at a sensing slot into one image.Furthermore,to exploit more information and improve the detection performance,we develop a trajectory classification algorithm which converts theflight process of the drones in consecutive multiple sensing slots into trajectory images.In addition,simulations are provided to verify the proposed methods’performance under various parameter configurations.

Adaptive 3D Routing Protocol for Flying Ad Hoc Networks Based on Prediction-Driven Q-Learning

The routing protocols are paramount to guarantee the Quality of Service(QoS)for Flying Ad Hoc Networks(FANETs).However,they still face several challenges owing to high mobility and dynamic topology.This paper mainly focuses on the adaptive routing protocol and proposes a Three Dimensional Q-Learning(3DQ)based routing protocol to guarantee the packet delivery ratio and improve the QoS.In 3DQ routing,we propose a Q-Learning based routing decision scheme,which contains a link-state prediction module and routing decision module.The link-state prediction module allows each Unmanned Aerial Vehicle(UAV)to predict the link-state of Neighboring UAVs(NUs),considering their Three Dimensional mobility and packet arrival.Then,UAV can produce routing decisions with the help of the routing decision module considering the link-state.We evaluate the various performance of 3DQ routing,and simulation results demonstrate that 3DQ can improve packet delivery ratio,goodput and delay of baseline protocol at most 71.36%,89.32%and 83.54%in FANETs over a variety of communication scenarios.

Characterization of a New HIV-1 Circulating Recombinant Form CRF142_BC—Yunnan,China,2015 and 2021

What is already known about this topic?Recombinant strains dominate the human immunodeficiency virus 1(HIV-1)epidemic in China.Yunnan Province was the first region in China to report HIV-1 infections in batches.The long-term HIV-1 epidemic led to the generation of various recombinant forms.Among the 47 circulating recombinant forms(CRFs)reported in China,more than 20 were first identified in Yunnan Province.What is added by this report?This study reported a previously unrecognized HIV-1 CRF(CRF142_BC)characterized by the insertion of four short subtype B fragments into the subtype C backbone.CRF142_BC was estimated to have emerged in the mid-1990s,close to the time of the emergence of most known CRF_BCs in China.What are the implications for public health practice?The discovery of new CRFs will provide a basis for HIV-1 molecular tracing and intervention research.In addition,HIV-1 recombination can alter viral biological properties.The study of HIV-1 gene variants needs to be intensified.

Carbon dioxide capture using polyethylenimine-loaded mesoporous carbons

A high efficiency sorbent for CO2 capture was developed by loading polyethylenimine （PEI） on mesoporous carbons which possessed well-developed mesoporous structures and large pore volume. The physicochemical properties of the sorbent were characterized by N2 adsorption/desorption, scanning electron microscopy （SEM）, thermal gravimetric analysis （TG） and Fourier transform infrared spectroscopy （FT-IR） techniques followed by testing for CO2 capture. Factors that affected the sorption capacity of the sorbent were studied. The sorbent exhibited extraordinary capture capacity with CO2 concentration ranging from 5% to 80%. The optimal PEI loading was determined to be 65 wt.% with a CO2 sorption capacity of 4.82 mmol-CO2/g-sorbent in 15% CO2/N2 at 75℃, owing to low mass-transfer resistance and a high utilization ratio of the amine compound （63%）. Moisture had a promoting effect on the sorption separation of CO2. In addition, the developed sorbent could be regenerated easily at 100℃, and it exhibited excellent regenerability and stability. These results indicate that this PEI-loaded mesoporous carbon sorbent should have a good potential for CO2 capture in the future.

地衣芽胞杆菌DW2中敲除氨基酸转运蛋白基因yhdG提高杆菌肽产量

杆菌肽是微生物产生的由11种氨基酸残基组成的广谱性抗生素,前体物的供应可能是限制杆菌肽高产的重要因素。文中通过支链氨基酸(异亮氨酸、亮氨酸、缬氨酸)的添加实验考察了前体物质支链氨基酸对杆菌肽高产的影响,证实了异亮氨酸(Ile)和亮氨酸(Leu)的添加可以提高杆菌肽的效价,其中Ile的添加对杆菌肽效价提高的效果较为明显。随后,文中以地衣芽胞杆菌DW2为出发菌株,分别构建了支链氨基酸转运蛋白Yhd G的缺失和强化表达菌株。发酵结果表明,转运蛋白Yhd G缺失工程菌DW2△yhd G的杆菌肽效价达到917.35 U/m L,与原始菌DW2相比提高了11%,而强化Yhd G则会使杆菌肽效价下降25%。最后通过分析胞内胞外支链氨基酸含量,发现缺失转运蛋白Yhd G能够在发酵中后期显著提高胞内支链氨基酸含量,表明氨基酸转运蛋白Yhd G在地衣芽胞杆菌DW2中可能发挥着氨基酸输出的功能。综上,文中通过缺失转运蛋白Yhd G显著提高了地衣芽胞杆菌胞内支链氨基酸的供给水平,从而提高了杆菌肽效价,为杆菌肽高产菌株的构建提供了一种新的策略。

Stochastic Bi-level Programming Model for Home Healthcare Scheduling Problems Considering the Degree of Satisfaction with Visit Time

Home health care(HHC)includes a wide range of healthcare services that are performed in customers'homes to help them recover.With the constantly increasing demand for health care,HHC policymakers are eager to address routing and scheduling problems from the perspective of optimization.In this paper,a bi-level programming model for HHC routing and scheduling problems with stochastic travel times is proposed,in which the degree of satisfaction with the visit time is simultaneously considered.The upper-level model is formulated for customer assignment with the aim of minimizing the total operating cost,and the lower-level model is formulated as a routing problem to maximize the degree of satisfaction with the visit time.Consistent with Stackelberg game decision-making,the trade-off relationship between these two objectives can be achieved spontaneously so as to reach an equilibrium state.A three-stage hybrid algorithm combining an iterated local search framework,which uses a large neighborhood search procedure as a sub-heuristic,a set-partitioning model,and a post-optimization method is developed to solve the proposed model.Numerical experiments on a set of instances including 10 to 100 customers verify the effectiveness of the proposed model and algorithm.