The impact of Internet access on household dietary quality:Evidence from rural China

Over the past few decades,the Internet has rapidly diffused across China.The spread of the Internet has had a profound economic and social impact on Chinese rural areas.Existing research shows that Internet access significantly impacts agricultural production and improves smallholder farmers’income.Beyond these,the Internet can affect other dimensions of social welfare.However,research about the impact of Internet access on dietary quality in rural China remains scarce.This study utilizes multi-period panel data from Fixed Observation Point in rural China from 2009 to 2015 to estimate the impact of Internet access on dietary quality and food consumption of rural households and conducts a causal analysis.Regression models with time and household fixed effects allow robust estimation while reducing potential issues of unobserved heterogeneity.The estimates show that Internet access has significantly increased rural household dietary quality(measured by the Chinese Diet Balance Index).Further research finds that Internet access has increased the consumption of animal products,such as aquatic and dairy products.We also examine the underlying mechanisms.Internet access improves dietary quality and food consumption mainly through increasing household income and food expenditure.These results encourage the promotion of Internet access as a valuable tool for nutritional improvements,especially in rural areas.

基于C#的微波器件自动校准系统的设计与实现

针对校准时,微波器件存在人工操作量大、存在读数误差等问题,本文采用C#面向对象语言,设计了一款模块化自动校准软件。该软件采用SCPI命令控制仪器;基于ACCESS数据库,实现基本信息和数据的处理存储;将图形数据转化成二进制流实现测量图形导出。同时,运用Word文档自动生成原始记录和校准证书。试验表明:该软件运行稳定、数据处理准确,满足使用要求,可实现微波器件的自动校准,提高工作效率。

Glycine-β-cyclodextrin-assisted cometabolism of phenanthrene and pyrene by Pseudomonas stutzeri DJP 1 from marine sediment

Cometabolic degradation is currently an effective and extensively way to remove high molecular weight polycyclic aromatic hydrocarbons(HMW-PAHs).Unfortunately,due to low bio-accessibility and high biotoxicity,the cometabolic degradation rate of HMW-PAHs is limited.Glycine-β-cyclodextrin(GCD)was obtained through amino modification ofβ-cyclodextrin(BCD)and added to cometabolic system of phenanthrene(PHE)and pyrene(PYR)to assist PYR biodegradation.Results show that the addition of GCD(100 mg/L)effectively improved the removal rate of PYR(20 mg/L)by 42.3%.GCD appeared to increase the bio-accessibility and reduce the biotoxicity of PHE and PYR,and then promoted the growth of Pseudomonas stutzeri DJP1 and stimulated the elevation of dehydrogenase(DHA)and catechol 12 dioxygenase(C12O)activities.The phthalate metabolic pathway was accelerated,which improved the cometabolic degradation.This study provided a new reference for the cometabolic degradation of HMW-PAHs.

Modeling and Analysis of OFDMA-NOMA-RA Protocol Considering Imperfect SIC in Multi-User Uplink WLANs

To address the problems of network congestion and spectrum resources shortage in multi-user large-scale scenarios,this paper proposes a twice random access OFDMA-NOMA-RA protocol combining the advantages of orthogonal frequency division multiple access(OFDMA)and non-orthogonal multiple access(NOMA).The idea of this protocol is that OFMDA is used to divide the entire frequency field into multiple orthogonal resource units(RUs),and NOMA is used on each RU to enable more users to access the channel and improve spectrum efficiency.Based on the protocol designed in this paper,in the case of imperfect successive interference cancellation(SIC),the probability of successful competition subchannels and the outage probability are derived for two scenarios:Users occupy the subchannel individually and users share the subchannel.Moreover,when two users share the channel,the decoding order of the users and the corresponding probabilities are considered.Then,the system throughput is obtained.To achieve better outage performance in the system,the optimal power allocation algorithm is proposed in this paper,which enables the optimal power allocation strategy to be obtained.Numerical results show that the larger the imperfect SIC coefficient,the worse the outage performance of weak users.Compared with pure OFDMA and NOMA,OFDMA-NOMA-RA always maintains an advantage when the imperfect SIC coefficient is less than a specific value.

Al-modified yolk-shell silica particle-supported NiMo catalysts for ultradeep hydrodesulfurization of dibenzothiophene and 4,6-dimethyldibenzothiophene:Efficient accessibility of active sites and suitable acidity

Yolk-shell SiO2 particles(YP)with center-radial meso-channels were fabricated through a simple and effective method.Al-containing YP-supported NiMo catalysts with different Al amounts(NiMo/AYP-x,x=Si/Al molar proportion)were prepared and dibenzothiophene(DBT)and 4,6-dimethyl-dibenzothiophene(4,6-DMDBT)were employed as the probes to evaluate the hydrodesulfurization(HDS)catalytic performance.The as-prepared AYP-x carriers and corresponding catalysts were characterized by some advanced characterizations to obtain deeper correlations between physicochemical properties and the HDS performance.The average pore sizes of series AYP-x supports are above 6.0 nm,which favors the mass transfer of organic sulfides.The cavity between the yolk and the shell is beneficial for the enrichment of S-containing compounds and the accessibility between reactants and active metals.Aluminum embedded into the silica framework could facilitate the formation of Lewis(L)and Brønsted(B)acid sites and adjust the metal-support interaction(MSI).Among all the as-synthesized catalysts,NiMo/AYP-20 catalyst shows the highest HDS activities.The improved HDS activity of NiMo/AYP-20 catalyst is attributed to the perfect combination of excellent structural properties of the yolk-shell mesoporous silica,enhanced acidity,moderate MSI,and good accessibility/dispersion of active components.

OFDMA-Based Unsourced Random Access in LEO Satellite Internet of Things

This paper investigates the low earth orbit(LEO)satellite-enabled coded compressed sensing(CCS)unsourced random access(URA)in orthogonal frequency division multiple access(OFDMA)framework,where a massive uniform planar array(UPA)is equipped on the satellite.In LEO satellite communications,unavoidable timing and frequency offsets cause phase shifts in the transmitted signals,substantially diminishing the decoding performance of current terrestrial CCS URA receiver.To cope with this issue,we expand the inner codebook with predefined timing and frequency offsets and formulate the inner decoding as a tractable compressed sensing(CS)problem.Additionally,we leverage the inherent sparsity of the UPA-equipped LEO satellite angular domain channels,thereby enabling the outer decoder to support more active devices.Furthermore,the outputs of the outer decoder are used to reduce the search space of the inner decoder,which cuts down the computational complexity and accelerates the convergence of the inner decoding.Simulation results verify the effectiveness of the proposed scheme.

基于BOPPPS模型和思维导图的Access数据库课程教学设计

阐述BOPPPS模式和思维导图开展Access数据库课程教学设计,分析BOPPPS模型和思维导图的特点,探讨Access数据库课程教学设计中的应用,包括课堂引入、课程目标、参与式学习、考试评估。

Blockchain-Enabled Privacy Protection and Access Control Scheme Towards Sensitive Digital Assets Management

With the growth of requirements for data sharing,a novel business model of digital assets trading has emerged that allows data owners to sell their data for monetary gain.In the distributed ledger of blockchain,however,the privacy of stakeholder's identity and the confidentiality of data content are threatened.Therefore,we proposed a blockchainenabled privacy-preserving and access control scheme to address the above problems.First,the multi-channel mechanism is introduced to provide the privacy protection of distributed ledger inside the channel and achieve coarse-grained access control to digital assets.Then,we use multi-authority attribute-based encryption(MAABE)algorithm to build a fine-grained access control model for data trading in a single channel and describe its instantiation in detail.Security analysis shows that the scheme has IND-CPA secure and can provide privacy protection and collusion resistance.Compared with other schemes,our solution has better performance in privacy protection and access control.The evaluation results demonstrate its effectiveness and practicability.

6G New Multiple Access Technology

As a basic technology at physical layer of mobile communications,non-orthogonal multiple access has been attracting wide attention across the academia and the industry.During the standardization of the fifth-generation(5G)of mobile communications,3GPP conducted preliminary study on non-orthogonal multiple access without reaching the consensus to standardize the technology.

Design Framework of Unsourced Multiple Access for 6G Massive IoT

In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.

Scenario Modeling-Aided AP Placement Optimization Method for Indoor Localization and Network Access

Owing to the ubiquity of wireless networks and the popularity of WiFi infrastructures,received signal strength(RSS)-based indoor localization systems have received much attention.The placement of access points(APs)significantly influences localization accuracy and network access.However,the indoor scenario and network access are not fully considered in previous AP placement optimization methods.This study proposes a practical scenario modelingaided AP placement optimization method for improving localization accuracy and network access.In order to reduce the gap between simulation-based and field measurement-based AP placement optimization methods,we introduce an indoor scenario modeling and Gaussian process-based RSS prediction method.After that,the localization and network access metrics are implemented in the multiple objective particle swarm optimization(MOPSO)solution,Pareto front criterion and virtual repulsion force are applied to determine the optimal AP placement.Finally,field experiments demonstrate the effectiveness of the proposed indoor scenario modeling method and RSS prediction model.A thorough comparison confirms the localization and network access improvement attributed to the proposed anchor placement method.

A Blockchain-Based Access Control Scheme for Reputation Value Attributes of the Internet of Things

The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.

The study of lithographic variation in resistive random access memory

Reducing the process variation is a significant concern for resistive random access memory(RRAM).Due to its ultrahigh integration density,RRAM arrays are prone to lithographic variation during the lithography process,introducing electrical variation among different RRAM devices.In this work,an optical physical verification methodology for the RRAM array is developed,and the effects of different layout parameters on important electrical characteristics are systematically investigated.The results indicate that the RRAM devices can be categorized into three clusters according to their locations and lithography environments.The read resistance is more sensitive to the locations in the array(~30%)than SET/RESET voltage(<10%).The increase in the RRAM device length and the application of the optical proximity correction technique can help to reduce the variation to less than 10%,whereas it reduces RRAM read resistance by 4×,resulting in a higher power and area consumption.As such,we provide design guidelines to minimize the electrical variation of RRAM arrays due to the lithography process.

Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access controlmechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policymanagement efficiency and difficulty in accurately describing the access control policy. To overcome theseproblems, this paper proposes a big data access control mechanism based on a two-layer permission decisionstructure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes areintroduced in the ABAC model as business constraints between entities. The proposed mechanism implementsa two-layer permission decision structure composed of the inherent attributes of access control entities and thebusiness attributes, which constitute the general permission decision algorithm based on logical calculation andthe business permission decision algorithm based on a bi-directional long short-term memory (BiLSTM) neuralnetwork, respectively. The general permission decision algorithm is used to implement accurate policy decisions,while the business permission decision algorithm implements fuzzy decisions based on the business constraints.The BiLSTM neural network is used to calculate the similarity of the business attributes to realize intelligent,adaptive, and efficient access control permission decisions. Through the two-layer permission decision structure,the complex and diverse big data access control management requirements can be satisfied by considering thesecurity and availability of resources. Experimental results show that the proposed mechanism is effective andreliable. In summary, it can efficiently support the secure sharing of big data resources.

Cluster-Based Massive Access for Massive MIMO Systems

Massive machine type communication aims to support the connection of massive devices,which is still an important scenario in 6G.In this paper,a novel cluster-based massive access method is proposed for massive multiple input multiple output systems.By exploiting the angular domain characteristics,devices are separated into multiple clusters with a learned cluster-specific dictionary,which enhances the identification of active devices.For detected active devices whose data recovery fails,power domain nonorthogonal multiple access with successive interference cancellation is employed to recover their data via re-transmission.Simulation results show that the proposed scheme and algorithm achieve improved performance on active user detection and data recovery.

Multi-aspect analysis of ureteral access sheath usage in retrograde intrarenal surgery: A RIRSearch group study

Objective:To evaluate the effect of ureteral access sheath(UAS)use and calibration change on stone-free rate and complications of retrograde intrarenal surgery(RIRS).Methods:Data from 568 patients undergoing RIRS for kidney or upper ureteral stones were retrospectively included.Firstly,patients were compared after 1:1 propensity score matching,according to UAS usage during RIRS(UAS used[+]87 and UAS non-used[−]87 patients).Then all UAS+patients(n=481)were subdivided according to UAS calibration:9.5-11.5 Fr,10-12 Fr,11-13 Fr,and 13-15 Fr.Primary outcomes of the study were the success and complications of RIRS.Results:Stone-free rate of UAS+patients(86.2%)was significantly higher than UAS−patients(70.1%)after propensity score matching(p=0.01).Stone-free rate increased with higher caliber UAS(9.5-11.5 Fr:66.7%;10-12 Fr:87.0%;11-13 Fr:90.6%;13-15 Fr:100%;p<0.001).Postoperative complications of UAS+patients(11.5%)were significantly lower than UAS−patients(27.6%)(p=0.01).Complications(8.7%)with 9.5-11.5 Fr UAS was lower than thicker UAS(17.2%)but was not statistically significant(p=0.09).UAS usage was an independent factor predicting stone-free status or peri-and post-operative complications(odds ratio[OR]3.654,95%confidence interval[CI]1.314-10.162;OR 4.443,95%CI 1.350-14.552;OR 4.107,95%CI 1.366-12.344,respectively).Conclusion:Use of UAS in RIRS may increase stone-free rates,which also increase with higher caliber UAS.UAS usage may reduce complications;however,complications seemingly increase with higher UAS calibration.

Influence of Transportation Accessibility on Urban-rural Income Disparity and Its Spatial Heterogeneity

Transportation accessibility has been treated as an important means of reducing the urban-rural income disparity.However,only a few studies have examined the effects of different types of transportation accessibility on urban-rural income disparity and their spatial heterogeneity.Based on data from 285 prefecture-level(and above)Chinese cities in 2000,2005,2010,2015,and 2020,this study uses spatial econometric models to examine how highway accessibility and railway accessibility influence the urban-rural income disparity and to identify their spatial heterogeneity.The result reveals that highway accessibility and railway accessibility have‘coreperiphery’ring-like circle structures.The urban-rural income disparity exhibits strong spatial clustering effects.Both highway accessibility and railway accessibility are negatively associated with urban-rural income disparity,and the former having a greater effect size.Moreover,there is a substitution effect between highway accessibility and railway accessibility in the whole sample.Furthermore,these associations differ in geographic regions.In the central region,highway accessibility is more important in reducing the urban-rural income disparity,but its effect is weakened with the increase of railway accessibility.In the western region,railway accessibility has a larger effect on narrowing the urban-rural income disparity,and this effect is strengthened by the increase of highway accessibility.We conclude that improving transportation accessibility is conducive to reducing the urban-rural income disparity but its effect is spatial heterogenetic.Highways and railways should be developed in a coordinated manner to promote an integrated transport network system.

Resource allocation for D2D-assisted haptic communications

Haptic communications is recognized as a promising enabler of extensive services by enabling real-time haptic control and feedback in remote environments,e.g.,teleoperation and autonomous driving.Considering the strict transmission requirements on reliability and latency,Device-to-Device(D2D)communications is introduced to assist haptic communications.In particular,the teleoperators with poor channel quality are assisted by auxiliaries,and each auxiliary and its corresponding teleoperator constitute a D2D pair.However,the haptic interaction and the scarcity of radio resources pose severe challenges to the resource allocation,especially facing the sporadic packet arrivals.First,the contentionbased access scheme is applied to achieve low-latency transmission,where the resource scheduling latency is omitted and users can directly access available resources.In this context,we derive the reliability index of D2D pairs under the contention-based access scheme,i.e.,closed-loop packet error probability.Then,the reliability performance is guaranteed by bidirectional power control,which aims to minimize the sum packet error probability of all D2D pairs.Potential game theory is introduced to solve the problem with low complexity.Accordingly,a distributed power control algorithm based on synchronous log-linear learning is proposed to converge to the optimal Nash Equilibrium.Experimental results demonstrate the superiority of the proposed learning algorithm.

A comparative study on characteristics of retracted publications across different open access levels

Purpose:Recently,global science has shown an increasing open trend,however,the characteristics of research integrity of open access(OA)publications have rarely been studied.The aim of this study is to compare the characteristics of retracted articles across different OA levels and discover whether OA level influences the characteristics of retracted articles.Design/methodology/approach:The research conducted an analysis of 6,005 retracted publications between 2001 and 2020 from the Web of Science and Retraction Watch databases.These publications were categorized based on their OA levels,including Gold OA,Green OA,and non-OA.The study explored retraction rates,time lags and reasons within these categories.Findings:The findings of this research revealed distinct patterns in retraction rates among different OA levels.Publications with Gold OA demonstrated the highest retraction rate,followed by Green OA and non-OA.A comparison of retraction reasons between Gold OA and non-OA categories indicated similar proportions,while Green OA exhibited a higher proportion due to falsification and manipulation issues,along with a lower occurrence of plagiarism and authorship issues.The retraction time lag was shortest for Gold OA,followed by non-OA,and longest for Green OA.The prolonged retraction time for Green OA could be attributed to an atypical distribution of retraction reasons.A comparative study on characteristics of retracted publications across different open access levels Research limitations:There is no exploration of a wider range of OA levels,such as Hybrid OA and Bronze OA.Practical implications:The outcomes of this study suggest the need for increased attention to research integrity within the OA publications.The occurrences offalsification,manipulation,and ethical concerns within Green OA publications warrant attention from the scientific community.Originality/value:This study contributes to the understanding of research integrity in the realm of OA publications,shedding light on retraction patterns and reasons across different OA levels.

Deep Learning Social Network Access Control Model Based on User Preferences

A deep learning access controlmodel based on user preferences is proposed to address the issue of personal privacy leakage in social networks.Firstly,socialusers andsocialdata entities are extractedfromthe social networkandused to construct homogeneous and heterogeneous graphs.Secondly,a graph neural networkmodel is designed based on user daily social behavior and daily social data to simulate the dissemination and changes of user social preferences and user personal preferences in the social network.Then,high-order neighbor nodes,hidden neighbor nodes,displayed neighbor nodes,and social data nodes are used to update user nodes to expand the depth and breadth of user preferences.Finally,a multi-layer attention network is used to classify user nodes in the homogeneous graph into two classes:allow access and deny access.The fine-grained access control problem in social networks is transformed into a node classification problem in a graph neural network.The model is validated using a dataset and compared with other methods without losing generality.The model improved accuracy by 2.18%compared to the baseline method GraphSAGE,and improved F1 score by 1.45%compared to the baseline method,verifying the effectiveness of the model.