Joint Allocation of Wireless Resource and Computing Capability in MEC-Enabled Vehicular Network

In MEC-enabled vehicular network with limited wireless resource and computation resource,stringent delay and high reliability requirements are challenging issues.In order to reduce the total delay in the network as well as ensure the reliability of Vehicular UE(VUE),a Joint Allocation of Wireless resource and MEC Computing resource(JAWC)algorithm is proposed.The JAWC algorithm includes two steps:V2X links clustering and MEC computation resource scheduling.In the V2X links clustering,a Spectral Radius based Interference Cancellation scheme(SR-IC)is proposed to obtain the optimal resource allocation matrix.By converting the calculation of SINR into the calculation of matrix maximum row sum,the accumulated interference of VUE can be constrained and the the SINR calculation complexity can be effectively reduced.In the MEC computation resource scheduling,by transforming the original optimization problem into a convex problem,the optimal task offloading proportion of VUE and MEC computation resource allocation can be obtained.The simulation further demonstrates that the JAWC algorithm can significantly reduce the total delay as well as ensure the communication reliability of VUE in the MEC-enabled vehicular network.

Amylopectin from Glutinous Rice as a Sustainable Binder for High-Performance Silicon Anodes

Silicon(Si)has been investigated as a promising anode material because of its high theoretical capacity(4200 m Ah g^(-1)).However,silicon anode suffers from huge volume changes during repeated charge–discharge cycles.In this work,inspired by a remarkable success of the glutinous rice mortar in the Great Wall with ca.2000-year history,amylopectin(AP),the key ingredient responsible for the strong bonding force,is extracted from glutinous rice and utilized as a flexible,aqueous,and resilient binder to address the most challenging drastic volume-expansion and pulverization issues of silicon anode.Additionally,the removal of toxic N-methyl-2-pyrrolidone(NMP)organic solvent makes the electrode fabrication process environmentally friendly and healthy.The as-prepared Si-AP electrode with 60 wt%of Si can uphold a high discharge capacity of 1517.9 m Ah g^(-1)at a rate of 0.1 C after 100 cycles.The cycling stability of the Si-AP has been remarkably improved in comparison with both traditional polyvinylidene fluoride(PVDF)and aqueous carboxymethylcellulose(CMC)binders.Moreover,when the content of silicon in the Si-AP electrode increases to 70 wt%,a high discharge capacity of 1463.1 m Ah g^(-1)can still be obtained after 50 cycles at 0.1°C.These preliminary results suggest that the sustainably available and environmentally benign amylopectin binders could be a promising choice for the construction of highly stable silicon anodes.

An Early Warning Model of Telecommunication Network Fraud Based on User Portrait

With the frequent occurrence of telecommunications and networkfraud crimes in recent years, new frauds have emerged one after another whichhas caused huge losses to the people. However, due to the lack of an effectivepreventive mechanism, the police are often in a passive position. Usingtechnologies such as web crawlers, feature engineering, deep learning, andartificial intelligence, this paper proposes a user portrait fraudwarning schemebased on Weibo public data. First, we perform preliminary screening andcleaning based on the keyword “defrauded” to obtain valid fraudulent userIdentity Documents (IDs). The basic information and account information ofthese users is user-labeled to achieve the purpose of distinguishing the typesof fraud. Secondly, through feature engineering technologies such as avatarrecognition, Artificial Intelligence (AI) sentiment analysis, data screening,and follower blogger type analysis, these pictures and texts will be abstractedinto user preferences and personality characteristics which integrate multidimensionalinformation to build user portraits. Third, deep neural networktraining is performed on the cube. 80% percent of the data is predicted basedon the N-way K-shot problem and used to train the model, and the remaining20% is used for model accuracy evaluation. Experiments have shown thatFew-short learning has higher accuracy compared with Long Short TermMemory (LSTM), Recurrent Neural Networks (RNN) and ConvolutionalNeural Network (CNN). On this basis, this paper develops a WeChat smallprogram for early warning of telecommunications network fraud based onuser portraits. When the user enters some personal information on the frontend, the back-end database can perform correlation analysis by itself, so as tomatch the most likely fraud types and give relevant early warning information.The fraud warning model is highly scaleable. The data of other Applications(APPs) can be extended to further improve the efficiency of anti-fraud whichhas extremely high public welfare value.

The Biological Significance of Multi-copy Regions and Their Impact on Variant Discovery

Identification of genetic variants via high-throughput sequencing(HTS)technologies has been essential for both fundamental and clinical studies.However,to what extent the genome sequence composition affects variant calling remains unclear.In this study,we identified 63,897 multi-copy sequences(MCSs)with a minimum length of 300 bp,each of which occurs at least twice in the human genome.The 151,749 genomic loci(multi-copy regions,or MCRs)harboring these MCSs account for 1.98% of the genome and are distributed unevenly across chromosomes.MCRs containing the same MCS tend to be located on the same chromosome.Gene Ontology(GO)analyses revealed that 3800 genes whose UTRs or exons overlap with MCRs are enriched for Golgirelated cellular component terms and various enzymatic activities in the GO biological function category.MCRs are also enriched for loci that are sensitive to neocarzinostatin-induced double-strand breaks.Moreover,genetic variants discovered by genome-wide association studies and recorded in dbSNP are significantly underrepresented in MCRs.Using simulated HTS datasets,we show that false variant discovery rates are significantly higher in MCRs than in other genomic regions.These results suggest that extra caution must be taken when identifying genetic variants in the MCRs via HTS technologies.

Incidence of Eczema in Early Infancy and the Prenatal Risk Factors—Guangzhou,Guangdong,China,2018–2019

What is already known on this topic?Eczema is a common allergic disease in children,which seriously affects the quality of life of children and their families.What is added by this report?The results showed that the incidence of very-earlyonset eczema was 12.4%.Primiparity was associated with a higher risk of eczema[risk ratio(95%confidence interval):1.23(1.06–1.42)].What are the implications for public health practice?Very-early-onset eczema is common.Given its adverse impact on children’s health and life quality,this previously neglected public health issue needs to be prioritized.In addition,maternal parity could serve as an indicator in risk assessment and prediction for infant eczema.