Novel dynamic anti-collusion ciphertext policy attribute-based encryption scheme in 5G D2D environment

To share data securely with secure attribute revocation,anti-collusion,and dynamic user management in the 5G device-to-device(D2D)environment,a novel dynamic anti-collusion ciphertext policy attribute-based encryption(NDA-CP-ABE)scheme in the 5G D2D environment is proposed.On the basis of the ciphertext policy attribute-based encryption algorithm,fine-grained access control and secure attribute revocation are realized,and the confidentiality of data is guaranteed.A polynomial function is adopted in the ciphertext generation phase to realize dynamic user management.A random number is used to prevent a collusion attack among the legitimate user equipment(UE),revoked UE,and external network attackers.Finally,on the basis of the Diffie-Hellman problem,the NDA-CP-ABE scheme is formally proved,and the simulation performances are compared with those of similar schemes.The results show that data can be securely shared through a D2D channel with secure attribute revocation,anti-collusion,and dynamic user management.Moreover,compared with similar schemes,the NDA-CP-ABE scheme has higher efficiency in encryption,decryption,and storage.

Coronavirus disease 2019 epidemic prediction in Shanghai under the “dynamic zero-COVID policy”using time-dependent SEAIQR model

It’s urgently needed to assess the COVID-19 epidemic under the“dynamic zero-COVID policy”in China,which provides a scientific basis for evaluating the effectiveness of this strategy in COVID-19 control.Here,we developed a time-dependent susceptible-exposed-asymptomatic-infected-quarantined-remov ed(SEAIQR)model with stage-specific interventions based on recent Shanghai epidemic data,considering a large number of asymptomatic infectious,the changing parameters,and control procedures.The data collected from March 1st,2022 to April 15th,2022 were used to fit the model,and the data of subsequent 7 days and 14 days were used to evaluate the model performance of forecasting.We then calculated the effective regeneration number(Rt)and analyzed the sensitivity of different measures scenarios.Asymptomatic infectious accounts for the vast majority of the outbreaks in Shanghai,and Pudong is the district with the most positive cases.The peak of newly confirmed cases and newly asymptomatic infectious predicted by the SEAIQR model would appear on April 13th,2022,with 1963 and 28,502 cases,respectively,and zero community transmission may be achieved in early to mid-May.The prediction errors for newly confirmed cases were considered to be reasonable,and newly asymptomatic infectious were considered to be good between April 16th to 22nd and reasonable between April 16th to 29th.The final ranges of cumulative confirmed cases and cumulative asymptomatic infectious predicted in this round of the epidemic were 26,477~47,749 and 402,254~730,176,respectively.At the beginning of the outbreak,Rt was 6.69.Since the implementation of comprehensive control,Rt showed a gradual downward trend,dropping to below 1.0 on April 15th,2022.With the early implementation of control measures and the improvement of quarantine rate,recovery rate,and immunity threshold,the peak number of infections will continue to decrease,whereas the earlier the control is implemented,the earlier the turning point of the epidemic will arrive.The proposed time-dependent SEAIQR dynamic model fits and forecasts the epidemic well,which can provide a reference for decision making of the“dynamic zero-COVID policy”.

SDN-Based Data Offloading for 5G Mobile Networks

The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applications and terminals with improved multi- media. Wi-Fi is an essential approach to alleviating mobile data traffic load on a cellular network because it provides extra capacity and improves overall performance. In this paper, we propose an integrated LTE/Wi-Fi architecture with software-defined networking （SDN） abstraction in mobile baekhaul and enhanced components that facilitate the move towards next-generation 5G mo- bile networks. Our proposed architecture enables programmable offloading policies that take into account real-time network conditions as well as the status of devices and applications. This mechanism improves overall network performance by deriving real- time policies and steering traffic between cellular and Wi-Fi networks more efficiently.

The spatiotemporal analysis of SARS-CoV-2 transmission in China since the termination of the dynamic zero-COVID policy

China's dynamic zero-COVID policy has effectively curbed the spread of SARS-CoV-2,while inadvertently creating immunity gaps within its population.Subsequent surges in COVID-19 cases linked to various SARS-CoV-2 lineages post-policy termination necessitate a thorough investigation into the epidemiological landscape.This study addresses this issue by analyzing a comprehensive dataset of 39,456 high-quality genomes collected nationwide over an 11-month period since policy termination.Through lineage assignment,phylogenetic analysis,pandemic pattern comparison,phylodynamic reconstruction,and recombination detection,we found that China's postepidemic period could be divided into three stages,along with dynamic changes in dominant lineages.Geographical clustering of similar lineages implies the importance of cross-border cooperation among neighboring regions.Compared to the USA,UK,and Japan,China exhibits unique trajectories of lineage epidemics,characterized by initial lagging followed by subsequent advancement,indicating the potential influence of diverse prevention and control policies on lineage epidemic patterns.Hong Kong,Shanghai,and Hubei emerge as pivotal nodes in the nationwide spread,marking a shift in the transmission center from east to central regions of China.Although China hasn't experienced significant variant emergence,the detection and validation of the novel recombination event,XCN lineage,underscore the ongoing virus evolution.Overall,this study systematically analyzes the spatiotemporal transmission of SARS-CoV-2 virus in China since the termination of the dynamic zeroCOVID policy,offering valuable insights for regional surveillance and evidence-based public health policymaking.

Clinical practice of rapid antigen tests for SARS-CoV-2 Omicron variant:A single-center study in China

Responding to the fast-spreading SARS-CoV-2 Omicron variant, to improve screening efficiency, rapid antigen tests(RATs) were first added as a supplementary detection method in China in mid-March, 2022. What and how big a role RATs should play need to be supported by clinical data. Here, RAT performance and relevant factors in comparison with nucleic acid amplification tests(NAATs) were assessed in Omicron-infected inpatients. From the NAAT results, nasopharyngeal swabs(NPs) performed better than oropharyngeal swabs(OPs). RATs tested on NAAT positive NPs performed better than those with OP-positive samples. The RAT positivity rate was strongly associated with high levels of N and OFR1ab genes, especially in NPs where patients also had significantly longer hospital stays and shorter days from symptom onset to RAT testing. Self-performed RATs had a detection accuracy that was comparable to professionally performed RATs when the subjects were well guided. The antigen negative rate of the studied patients was 100% at discharge. These findings suggest that, in addition to a supplementary detection role, RATs can be an important strategy for evaluating the disease progression of Omicron-infected inpatients. This study provides important clinical data to support better rules regarding RATs under China’s COVID-19 prevention and control policy.

Regional inequality, spatial spillover effects, and the factors influencing city-level energy-related carbon emissions in China

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.

A Prediction Framework for Turning Period Structures in COVID-19 Epidemic and Its Application to Practical Emergency Risk Management

The aim of this paper is first to establish a general prediction framework for turning(period)term structures in COVID-19 epidemic related to the implementation of emergency risk management in the practice,which allows us to conduct the reliable estimation for the peak period based on the new concept of“Turning Period”(instead of the traditional one with the focus on“Turning Point”)for infectious disease spreading such as the COVID-19 epidemic appeared early in year 2020.By a fact that emergency risk management is necessarily to implement emergency plans quickly,the identification of the Turning Period is a key element to emergency planning as it needs to provide a time line for effective actions and solutions to combat a pandemic by reducing as much unexpected risk as soon as possible.As applications,the paper also discusses how this“Turning Term(Period)Structure”is used to predict the peak phase for COVID-19 epidemic in Wuhan from January/2020 to early March/2020.Our study shows that the predication framework established in this paper is capable to provide the trajectory of COVID-19 cases dynamics for a few weeks starting from Feb.10/2020 to early March/2020,from which we successfully predicted that the turning period of COVID-19 epidemic in Wuhan would arrive within one week after Feb.14/2020,as verified by the true observation in the practice.The method established in this paper for the prediction of“Turning Term(Period)Structures”by applying COVID-19 epidemic in China happened early 2020 seems timely and accurate,providing adequate time for the government,hospitals,essential industry sectors and services to meet peak demands and to prepare aftermath planning,and associated criteria for the Turning Term Structure of COVID-19 epidemic is expected to be a useful and powerful tool to implement the so-called“dynamic zero-COVID-19 policy”ongoing basis in the practice.