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.

Future changes in precipitation and water availability over the Tibetan Plateau projected by CMIP6 models constrained by climate sensitivity

Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.

Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling

Spring consecutive rainfall events(CREs) are key triggers of geological hazards in the Three Gorges Reservoir area(TGR), China. However, previous projections of CREs based on the direct outputs of global climate models(GCMs) are subject to considerable uncertainties, largely caused by their coarse resolution. This study applies a triple-nested WRF(Weather Research and Forecasting) model dynamical downscaling, driven by a GCM, MIROC6(Model for Interdisciplinary Research on Climate, version 6), to improve the historical simulation and reduce the uncertainties in the future projection of CREs in the TGR. Results indicate that WRF has better performances in reproducing the observed rainfall in terms of the daily probability distribution, monthly evolution and duration of rainfall events, demonstrating the ability of WRF in simulating CREs. Thus, the triple-nested WRF is applied to project the future changes of CREs under the middle-of-the-road and fossil-fueled development scenarios. It is indicated that light and moderate rainfall and the duration of continuous rainfall spells will decrease in the TGR, leading to a decrease in the frequency of CREs. Meanwhile, the duration, rainfall amount, and intensity of CREs is projected to regional increase in the central-west TGR. These results are inconsistent with the raw projection of MIROC6. Observational diagnosis implies that CREs are mainly contributed by the vertical moisture advection. Such a synoptic contribution is captured well by WRF, which is not the case in MIROC6,indicating larger uncertainties in the CREs projected by MIROC6.

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.

人工智能背景下Materials Project数据库在计算材料学课程教学中的应用

该文探讨了在人工智能背景下,Materials Project数据库在计算材料学课程教学中的应用和影响。Materials Project数据库是一个集成了AI和大数据技术的开放获取的材料库,能为学生提供海量的材料晶体结构和物性数据,使教学内容更为丰富,让学生能通过亲自操作获取和分析数据,深入理解微观结构与物性之间的关系。这一新兴的教学模式不仅提升了学生的科研能力和创新思维能力,还有助于培养具备计算材料专业知识和多学科交叉的复合型人才。总体来说,人工智能时代下,大数据的引入为计算材料学课程带来新的活力,并对未来教育改革和实践产生了积极影响。

Transcriptional regulation in the development and dysfunction of neocortical projection neurons

Glutamatergic projection neurons generate sophisticated excitatory circuits to integrate and transmit information among different cortical areas,and between the neocortex and other regions of the brain and spinal cord.Appropriate development of cortical projection neurons is regulated by certain essential events such as neural fate determination,proliferation,specification,differentiation,migration,survival,axonogenesis,and synaptogenesis.These processes are precisely regulated in a tempo-spatial manner by intrinsic factors,extrinsic signals,and neural activities.The generation of correct subtypes and precise connections of projection neurons is imperative not only to support the basic cortical functions(such as sensory information integration,motor coordination,and cognition)but also to prevent the onset and progression of neurodevelopmental disorders(such as intellectual disability,autism spectrum disorders,anxiety,and depression).This review mainly focuses on the recent progress of transcriptional regulations on the development and diversity of neocortical projection neurons and the clinical relevance of the failure of transcriptional modulations.

Cascading multi-segment rupture process of the 2023 Turkish earthquake doublet on a complex fault system revealed by teleseismic P wave back projection method

In this study,the vertical components of broadband teleseismic P wave data recorded by China Earthquake Network are used to image the rupture processes of the February 6th,2023 Turkish earthquake doublet via back projection analysis.Data in two frequency bands(0.5-2 Hz and 1-3 Hz)are used in the imaging processes.The results show that the rupture of the first event extends about 200 km to the northeast and about 150 km to the southwest,lasting~90 s in total.The southwestern rupture is triggered by the northeastern rupture,demonstrating a sequential bidirectional unilateral rupture pattern.The rupture of the second event extends approximately 80 km in both northeast and west directions,lasting~35 s in total and demonstrates a typical bilateral rupture feature.The cascading ruptures on both sides also reflect the occurrence of selective rupture behaviors on bifurcated faults.In addition,we observe super-shear ruptures on certain fault sections with relatively straight fault structures and sparse aftershocks.

Recent Ventures in Interdisciplinary Arctic Research:The ARCPATH Project

This paper celebrates Professor Yongqi GAO's significant achievement in the field of interdisciplinary studies within the context of his final research project Arctic Climate Predictions: Pathways to Resilient Sustainable Societies-ARCPATH(https://www.svs.is/en/projects/finished-projects/arcpath). The disciplines represented in the project are related to climatology, anthropology, marine biology, economics, and the broad spectrum of social-ecological studies. Team members were drawn from the Nordic countries, Russia, China, the United States, and Canada. The project was transdisciplinary as well as interdisciplinary as it included collaboration with local knowledge holders. ARCPATH made significant contributions to Arctic research through an improved understanding of the mechanisms that drive climate variability in the Arctic. In tandem with this research, a combination of historical investigations and social, economic, and marine biological fieldwork was carried out for the project study areas of Iceland, Greenland, Norway, and the surrounding seas, with a focus on the joint use of ocean and sea-ice data as well as social-ecological drivers. ARCPATH was able to provide an improved framework for predicting the near-term variation of Arctic climate on spatial scales relevant to society, as well as evaluating possible related changes in socioeconomic realms. In summary, through the integration of information from several different disciplines and research approaches, ARCPATH served to create new and valuable knowledge on crucial issues, thus providing new pathways to action for Arctic communities.

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.

Diagnosis of indirectly driven double shell targets with point-projection hard x-ray radiography

We present an application of short-pulse laser-generated hard x rays for the diagnosis of indirectly driven double shell targets. Coneinserted double shell targets were imploded through an indirect drive approach on the upgraded SG-II laser facility. Then, based on thepoint-projection hard x-ray radiography technique, time-resolved radiography of the double shell targets, including that of their near-peakcompression, were obtained. The backlighter source was created by the interactions of a high-intensity short pulsed laser with a metalmicrowire target. Images of the target near peak compression were obtained with an Au microwire. In addition, radiation hydrodynamicsimulations were performed, and the target evolution obtained agrees well with the experimental results. Using the radiographic images, arealdensities of the targets were evaluated.

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.

Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

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.