安心卡引导的尊严照护干预联合SHARE模式在肿瘤患者安宁疗护中的应用

目的:探讨和分析安心卡引导的尊严照护干预联合SHARE模式在肿瘤患者安宁疗护中的应用,为临床提供参考。方法:选取2022年1—12月郑州市第三人民医院收治的68例肿瘤患者作为研究对象。对照组(34例)采取传统的照护方法和告知模式,试验组(34例)采取安心卡引导的尊严照护方法和SHARE告知模式,比较两组患者的自尊水平、死亡态度、焦虑情绪、睡眠质量状况。结果:干预后,两组患者的自尊水平测定分数均增高,试验组的自尊水平测定分数显著高于对照组,差异有统计学意义(t=4.218,P<0.05);干预后,试验组的害怕、回避死亡态度得分显著低于对照组,自然接受、接近接受死亡态度得分显著高于对照组,差异有统计学意义(t=10.119、3.222、17.142、6.278,P<0.05);干预后,两组患者的焦虑情绪得分均降低,试验组焦虑情绪得分显著低于对照组,差异有统计学意义(t=18.739,P<0.05);干预后,两组患者的睡眠质量得分均降低,试验组睡眠质量得分显著低于对照组,差异有统计学意义(t=10.746,P<0.05);干预后,两组患者的疼痛程度得分均降低,干预后试验组疼痛程度得分显著低于对照组,差异有统计学意义(t=9.685,P<0.05)。结论:安心卡引导的尊严照护干预联合SHARE模式在肿瘤患者安宁疗护中,有利于肿瘤患者疾病治疗和身心健康发展,可供临床参考。

非暴力沟通联合think-pair-share模式培训在普外科护士在职培训中的应用研究

目的:探讨非暴力沟通联合think-pair-share(TPS)模式培训在普外科护士在职培训中的应用效果。方法:2020年10月至2021年10月选取本院普外科的4个护理单元,通过随机抽签法分为试验组和对照组,试验组参加非暴力沟通联合TPS模式培训,对照组参与常规非暴力沟通培训。对比两组护士临床沟通能力、患者满意度以及教学满意度的差异。结果:试验组护士临床沟通能力、患者满意度、教学满意度调查结果均优于对照组(P<0.001)。结论:非暴力沟通联合TPS模式培训在普外科护士在职培训中能提高普外科护士的护患沟通能力,提升其岗位胜任力。

长三角城市群经济韧性测度与分析——基于Shift-Share的经济韧性分解

以长三角城市群27个城市为研究对象,测度2008—2010年抵抗期和2010—2019年恢复期城市群经济韧性水平,并进一步运用Shift-Share分解方法探索长三角城市群经济韧性内在影响机制。研究显示:抵抗期和恢复期中长三角城市群经济韧性均值分别为0.309和0.301,均强于全国层面经济韧性水平;Shift-Share分解后发现竞争力分量对各城市经济韧性水平提升起到决定性作用,抵抗期阶段主要由第二、三产业共同作用影响经济韧性水平;恢复期阶段则以第二产业竞争力为主导力量,同时以第三产业竞争力作为辅助力量。通过实证探究长三角城市群经济一体化发展的规律和特点,为增强中国经济韧性提出相关建议,助力中国经济高质量发展。

Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

BC-PC-Share:Blockchain-Based Patient-Centric Data Sharing Scheme for PHRs in Cloud Computing

Sharing of personal health records(PHR)in cloud computing is an essential functionality in the healthcare system.However,how to securely,efficiently and flexibly share PHRs data of the patient in a multi-receiver setting has not been well addressed.For instance,since the trust domain of the cloud server is not identical to the data owner or data user,the semi-trust cloud service provider may intentionally destroy or tamper shared PHRs data of user or only transform partial ciphertext of the shared PHRs or even return wrong computation results to save its storage and computation resource,to pursue maximum economic interest or other malicious purposes.Thus,the PHRs data storing or sharing via the cloud server should be performed with consistency and integrity verification.Fortunately,the emergence of blockchain technology provides new ideas and prospects for ensuring the consistency and integrity of shared PHRs data.To this end,in this work,we leverage the consortiumblockchain technology to enhance the trustworthiness of each participant and propose a blockchain-based patient-centric data sharing scheme for PHRs in cloud computing(BC-PC-Share).Different from the state-of-art schemes,our proposal can achieve the following desired properties:(1)Realizing patient-centric PHRs sharing with a public verification function,i.e.,which can ensure that the returned shared data is consistent with the requested shared data and the integrity of the shared data is not compromised.(2)Supporting scalable and fine-grained access control and sharing of PHRs data with multiple domain users,such as hospitals,medical research institutes,and medical insurance companies.(3)Achieving efficient user decryption by leveraging the transformation key technique and efficient user revocation by introducing time-controlled access.The security analysis and simulation experiment demonstrate that the proposed BC-PC-Share scheme is a feasible and promising solution for PHRs data sharing via consortium blockchain.

Low-Cost Federated Broad Learning for Privacy-Preserved Knowledge Sharing in the RIS-Aided Internet of Vehicles

High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility environment.In order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL)framework that integrates broad learning(BL)into federated learning(FL).In FBL,we design a broad fully connected model(BFCM)as a local model for training client data.To enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS)configuration optimization framework for FBL.The problem is decoupled into two convex subproblems.Aiming to improve the resource scheduling efficiency in FBL,a double Davidon–Fletcher–Powell(DDFP)algorithm is presented to solve the time slot allocation and RIS configuration problem.Based on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL)in FBL to compensate clients for their costs.The simulation results show that the proposed FBL framework achieves better performance than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV.

A Blind Batch Encryption and Public Ledger-Based Protocol for Sharing Sensitive Data

For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.

A New Double Layer Multi-Secret Sharing Scheme

Cryptography is deemed to be the optimum strategy to secure the data privacy in which the data is encoded ahead of time before sharing it.Visual Secret Sharing(VSS)is an encryption method in which the secret message is split into at least two trivial images called’shares’to cover it.However,such message are always targeted by hackers or dishonest members who attempt to decrypt the message.This can be avoided by not uncovering the secret message without the universal share when it is presented and is typically taken care of,by the trusted party.Hence,in this paper,an optimal and secure double-layered secret image sharing scheme is proposed.The proposed share creation process contains two layers such as threshold-based secret sharing in the first layer and universal share based secret sharing in the second layer.In first layer,Genetic Algorithm(GA)is applied to find the optimal threshold value based on the randomness of the created shares.Then,in the second layer,a novel design of universal share-based secret share creation method is proposed.Finally,Opposition Whale Optimization Algorithm(OWOA)-based optimal key was generated for rectange block cipher to secure each share.This helped in producing high quality reconstruction images.The researcher achieved average experimental outcomes in terms of PSNR and MSE values equal to 55.154225 and 0.79365625 respectively.The average PSNRwas less(49.134475)and average MSE was high(1)in case of existing methods.

A General Framework for Intelligent IoT Data Acquisition and Sharing in an Untrusted Environment Based on Blockchain

Traditional Io T systems suffer from high equipment management costs and difficulty in trustworthy data sharing caused by centralization.Blockchain provides a feasible research direction to solve these problems. The main challenge at this stage is to integrate the blockchain from the resourceconstrained Io T devices and ensure the data of Io T system is credible. We provide a general framework for intelligent Io T data acquisition and sharing in an untrusted environment based on the blockchain, where gateways become Oracles. A distributed Oracle network based on Byzantine Fault Tolerant algorithm is used to provide trusted data for the blockchain to make intelligent Io T data trustworthy. An aggregation contract is deployed to collect data from various Oracle and share the credible data to all on-chain users. We also propose a gateway data aggregation scheme based on the REST API event publishing/subscribing mechanism which uses SQL to achieve flexible data aggregation. The experimental results show that the proposed scheme can alleviate the problem of limited performance of Io T equipment, make data reliable, and meet the diverse data needs on the chain.

A Framework Based on the DAO and NFT in Blockchain for Electronic Document Sharing

In the information age,electronic documents(e-documents)have become a popular alternative to paper documents due to their lower costs,higher dissemination rates,and ease of knowledge sharing.However,digital copyright infringements occur frequently due to the ease of copying,which not only infringes on the rights of creators but also weakens their creative enthusiasm.Therefore,it is crucial to establish an e-document sharing system that enforces copyright protection.However,the existing centralized system has outstanding vulnerabilities,and the plagiarism detection algorithm used cannot fully detect the context,semantics,style,and other factors of the text.Digital watermark technology is only used as a means of infringement tracing.This paper proposes a decentralized framework for e-document sharing based on decentralized autonomous organization(DAO)and non-fungible token(NFT)in blockchain.The use of blockchain as a distributed credit base resolves the vulnerabilities inherent in traditional centralized systems.The e-document evaluation and plagiarism detection mechanisms based on the DAO model effectively address challenges in comprehensive text information checks,thereby promoting the enhancement of e-document quality.The mechanism for protecting and circulating e-document copyrights using NFT technology ensures effective safeguarding of users’e-document copyrights and facilitates e-document sharing.Moreover,recognizing the security issues within the DAO governance mechanism,we introduce an innovative optimization solution.Through experimentation,we validate the enhanced security of the optimized governance mechanism,reducing manipulation risks by up to 51%.Additionally,by utilizing evolutionary game analysis to deduce the equilibrium strategies of the framework,we discovered that adjusting the reward and penalty parameters of the incentive mechanism motivates creators to generate superior quality and unique e-documents,while evaluators are more likely to engage in assessments.

Prevalence and Factors Associated with Sharing of Human Immunodeficiency Seropositivity Status among Serodiscordant Couples in the City of Parakou (Benin)

Introduction: In serodiscordant couples, sharing serostatus is a crucial step in the HIV risk management process. The aim of this study was to determine the prevalence and factors associated with serostatus sharing among HIV serodiscordant couples in the city of Parakou. Setting and methods: This study was carried out in the city of Parakou, capital of northern Benin. It was a descriptive, analytical cross-sectional study with non-probability sampling for convenience. Socio-demographic data, as well as data on antecedents, behaviours, social and marital life, were collected using a questionnaire gave to the participants. Clinical and therapeutic data were collected from patients’ medical records and follow-up charts. Data were analyzed and processed using R 4.3.1 software. The significance level was set at 5%, and logistic regression was used to identify potential predictors of shared serostatus among serodiscordant couples in the city of Parakou in 2022. Results: A total of 299 participants in long-term serodiscordant relationships were included in our study. The average age of the subjects was 37.55 ± 10.25 years. Women were the infected partner in 80.27% of cases. The most common level of education was secondary (33.45%). Most respondents (230 subjects, 76.92%) were married. The average duration of the couple’s relationship was 121.68 months ± 96.32. The most frequent screening circumstances were: Prevention of mother-to-child transmission (PMTCT) (50.84%) and hospital screening (26.09%). The infected partner shared his or her serostatus with his or her spouse in 47.83% of cases. Potential predictors of serostatus sharing within the couple were: marital status (p Conclusion: The sharing of serostatus within serodiscordant couples needs to be managed in a way that takes into account the social and marital characteristics of the couple.

FADSF:A Data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage terminal.The data of ICV(intelligent connected vehicles)is the key to organically maximizing their efficiency.However,in the context of increasingly strict global data security supervision and compliance,numerous problems,including complex types of connected vehicle data,poor data collaboration between the IT(information technology)domain and OT(operation technology)domain,different data format standards,lack of shared trust sources,difficulty in ensuring the quality of shared data,lack of data control rights,as well as difficulty in defining data ownership,make vehicle data sharing face a lot of problems,and data islands are widespread.This study proposes FADSF(Fuzzy Anonymous Data Share Frame),an automobile data sharing scheme based on blockchain.The data holder publishes the shared data information and forms the corresponding label storage on the blockchain.The data demander browses the data directory information to select and purchase data assets and verify them.The data demander selects and purchases data assets and verifies them by browsing the data directory information.Meanwhile,this paper designs a data structure Data Discrimination Bloom Filter(DDBF),making complaints about illegal data.When the number of data complaints reaches the threshold,the audit traceability contract is triggered to punish the illegal data publisher,aiming to improve the data quality and maintain a good data sharing ecology.In this paper,based on Ethereum,the above scheme is tested to demonstrate its feasibility,efficiency and security.

Improvement and security analysis of multi-ring discrete modulation continuous variable quantum secret sharing scheme

In order to avoid the complexity of Gaussian modulation and the problem that the traditional point-to-point communication DM-CVQKD protocol cannot meet the demand for multi-user key sharing at the same time, we propose a multi-ring discrete modulation continuous variable quantum key sharing scheme(MR-DM-CVQSS). In this paper, we primarily compare single-ring and multi-ring M-symbol amplitude and phase-shift keying modulations. We analyze their asymptotic key rates against collective attacks and consider the security key rates under finite-size effects. Leveraging the characteristics of discrete modulation, we improve the quantum secret sharing scheme. Non-dealer participants only require simple phase shifters to complete quantum secret sharing. We also provide the general design of the MR-DM-CVQSS protocol.We conduct a comprehensive analysis of the improved protocol's performance, confirming that the enhancement through multi-ring M-PSK allows for longer-distance quantum key distribution. Additionally, it reduces the deployment complexity of the system, thereby increasing the practical value.

A verifiable essential secret image sharing scheme based on HLRs(VESIS-(t,s,k,n))

In traditional secret image sharing schemes,a secret image is shared among shareholders who have the same position.But if the shareholders have two different positions,essential and non‐essential,it is necessary to use essential secret image sharing schemes.In this article,a verifiable essential secret image sharing scheme based on HLRs is proposed.Shareholder's share consists of two parts.The first part is produced by the shareholders,which prevents the fraud of dealers.The second part is a shadow image that is produced by using HLRs and the first part of share.The verification of the first part of the shares is done for the first time by using multilinear and bilinear maps.Also,for verifying shadow images,Bloom Filters are used for the first time.The proposed scheme is more efficient than similar schemes,and for the first part of the shares,has formal security.

Cryptanalysis of efficient semi-quantum secret sharing protocol using single particles

In paper[Chin.Phys.B 32070308(2023)],Xing et al.proposed a semi-quantum secret sharing protocol by using single particles.We study the security of the proposed protocol and find that it is not secure,that is,the three dishonest agents,Bob,Charlie and Emily can collude to obtain Alice's secret without the help of David.

Blockchain-Based MCS Detection Framework of Abnormal Spectrum Usage for Satellite Spectrum Sharing Scenario

In this paper, the problem of abnormal spectrum usage between satellite spectrum sharing systems is investigated to support multi-satellite spectrum coexistence. Given the cost of monitoring, the mobility of low-orbit satellites, and the directional nature of their signals, traditional monitoring methods are no longer suitable, especially in the case of multiple power level. Mobile crowdsensing(MCS), as a new technology, can make full use of idle resources to complete a variety of perceptual tasks. However, traditional MCS heavily relies on a centralized server and is vulnerable to single point of failure attacks. Therefore, we replace the original centralized server with a blockchain-based distributed service provider to enable its security. Therefore, in this work, we propose a blockchain-based MCS framework, in which we explain in detail how this framework can achieve abnormal frequency behavior monitoring in an inter-satellite spectrum sharing system. Then, under certain false alarm probability, we propose an abnormal spectrum detection algorithm based on mixed hypothesis test to maximize detection probability in single power level and multiple power level scenarios, respectively. Finally, a Bad out of Good(BooG) detector is proposed to ease the computational pressure on the blockchain nodes. Simulation results show the effectiveness of the proposed framework.

Blockchain-Based Key Management Scheme Using Rational Secret Sharing

Traditional blockchain key management schemes store private keys in the same location,which can easily lead to security issues such as a single point of failure.Therefore,decentralized threshold key management schemes have become a research focus for blockchain private key protection.The security of private keys for blockchain user wallet is highly related to user identity authentication and digital asset security.The threshold blockchain private key management schemes based on verifiable secret sharing have made some progress,but these schemes do not consider participants’self-interested behavior,and require trusted nodes to keep private key fragments,resulting in a narrow application scope and low deployment efficiency,which cannot meet the needs of personal wallet private key escrow and recovery in public blockchains.We design a private key management scheme based on rational secret sharing that considers the self-interest of participants in secret sharing protocols,and constrains the behavior of rational participants through reasonable mechanism design,making it more suitable in distributed scenarios such as the public blockchain.The proposed scheme achieves the escrow and recovery of personal wallet private keys without the participation of trusted nodes,and simulate its implementation on smart contracts.Compared to other existing threshold wallet solutions and keymanagement schemes based on password-protected secret sharing(PPSS),the proposed scheme has a wide range of applications,verifiable private key recovery,low communication overhead,higher computational efficiency when users perform one-time multi-key escrow,no need for trusted nodes,and personal rational constraints and anti-collusion attack capabilities.

Blockchain-Enabled Federated Learning for Privacy-Preserving Non-IID Data Sharing in Industrial Internet

Sharing data while protecting privacy in the industrial Internet is a significant challenge.Traditional machine learning methods require a combination of all data for training;however,this approach can be limited by data availability and privacy concerns.Federated learning(FL)has gained considerable attention because it allows for decentralized training on multiple local datasets.However,the training data collected by data providers are often non-independent and identically distributed(non-IID),resulting in poor FL performance.This paper proposes a privacy-preserving approach for sharing non-IID data in the industrial Internet using an FL approach based on blockchain technology.To overcome the problem of non-IID data leading to poor training accuracy,we propose dynamically updating the local model based on the divergence of the global and local models.This approach can significantly improve the accuracy of FL training when there is relatively large dispersion.In addition,we design a dynamic gradient clipping algorithm to alleviate the influence of noise on the model accuracy to reduce potential privacy leakage caused by sharing model parameters.Finally,we evaluate the performance of the proposed scheme using commonly used open-source image datasets.The simulation results demonstrate that our method can significantly enhance the accuracy while protecting privacy and maintaining efficiency,thereby providing a new solution to data-sharing and privacy-protection challenges in the industrial Internet.

Verifiable quantum secret sharing scheme based on orthogonal product states

In the domain of quantum cryptography,the implementation of quantum secret sharing stands as a pivotal element.In this paper,we propose a novel verifiable quantum secret sharing protocol using the d-dimensional product state and Lagrange interpolation techniques.This protocol is initiated by the dealer Alice,who initially prepares a quantum product state,selected from a predefined set of orthogonal product states within the C~d■C~d framework.Subsequently,the participants execute unitary operations on this product state to recover the underlying secret.Furthermore,we subject the protocol to a rigorous security analysis,considering both eavesdropping attacks and potential dishonesty from the participants.Finally,we conduct a comparative analysis of our protocol against existing schemes.Our scheme exhibits economies of scale by exclusively employing quantum product states,thereby realizing significant cost-efficiency advantages.In terms of access structure,we adopt a(t, n)-threshold architecture,a strategic choice that augments the protocol's practicality and suitability for diverse applications.Furthermore,our protocol includes a rigorous integrity verification mechanism to ensure the honesty and reliability of the participants throughout the execution of the protocol.

A Shared Natural Neighbors Based-Hierarchical Clustering Algorithm for Discovering Arbitrary-Shaped Clusters

In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering results.While various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared neighbors,most neighbor relationships can only handle single structural relationships,and the identification accuracy is low for datasets with multiple structures.In life,people’s first instinct for complex things is to divide them into multiple parts to complete.Partitioning the dataset into more sub-graphs is a good idea approach to identifying complex structures.Taking inspiration from this,we propose a novel neighbor method:Shared Natural Neighbors(SNaN).To demonstrate the superiority of this neighbor method,we propose a shared natural neighbors-based hierarchical clustering algorithm for discovering arbitrary-shaped clusters(HC-SNaN).Our algorithm excels in identifying both spherical clusters and manifold clusters.Tested on synthetic datasets and real-world datasets,HC-SNaN demonstrates significant advantages over existing clustering algorithms,particularly when dealing with datasets containing arbitrary shapes.