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Clinical value of precise rehabilitation nursing in management of cerebral infarction

World Journal of Clinical Cases 2024年第1期12卷 24-31页

作者： Ya-Na Xu xiu-Zhen Wang Xiao-Rong zhang Department of Neurology Wuhan Fourth HospitalWuhan 430030Hubei ProvinceChina Department of Neurosurgery The First People's Hospital of Jiangxia DistrictWuhan City(Union Jiangnan Hospital of Huazhong University of Science and Technology)Wuhan 430200Hubei ProvinceChina

BACKGROUND Cerebral infarction,previously referred to as cerebral infarction or ischemic stroke,refers to the localized brain tissue experiencing ischemic necrosis or softening due to disorders in brain blood supply,ischemia,and *** precision rehabilitation nursing model for chronic disease management is a continuous,fixed,orderly,and efficient nursing model aimed at standardizing the clinical nursing process,reducing the wastage of medical resources,and improving the quality of medical *** To analyze the value of a precise rehabilitation nursing model for chronic disease management in patients with cerebral *** Patients(n=124)admitted to our hospital with cerebral infarction between November 2019 and November 2021 were enrolled as the study *** random number table method was used to divide them into a conventional nursing intervention group(n=61)and a model nursing intervention group(n=63).Changes in the nursing index for the two groups were compared after conventional nursing intervention and precise rehabilitation intervention nursing for chronic disease *** Compared with the conventional intervention group,the model intervention group had a shorter time to clinical symptom relief(P<0.05),lower Hamilton Anxiety Scale and Hamilton Depression Scale scores,a lower incidence of total complications(P<0.05),a higher disease knowledge mastery rate,higher safety and quality,and a higher overall nursing satisfaction rate(P<0.05).CONCLUSION The precision rehabilitation nursing model for chronic disease management improves the clinical symptoms of patients with cerebral infarction,reducing the incidence of total complications and improving the clinical outcome of patients,and is worthy of application in clinical practice.

关键词： Precise rehabilitation nursing model for chronic disease management Cerebral infarction Knowledge of disease Safety and quality

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Collaborative robust dispatch of electricity and carbon under carbon allowance trading market

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Global Energy Interconnection 2024年第4期7卷 391-401页

作者： Songyu Wu Xiaoyan Qi Xiang Li Xuanyu Liu Bolin Tong Feiyu zhang zhong zhang Electric Power Research Institute of State Grid Liaoning Electric Power Co. Shenyang 110006P.R.China School of Electrical Engineering Dalian University of TechnologyDalian 116024P.R.China

The launch of the carbon-allowance trading market has changed the cost structure of the power *** is an asynchronous coupling mechanism between the carbon-allowance-trading market and the day-ahead power-system *** this study,a data-driven model of the uncertainty in the annual carbon price was ***,a collaborative,robust dispatch model was constructed considering the annual uncertainty of the carbon price and the daily uncertainty of renewable-energy *** model is solved using the column-and-constraint generation *** operation and cost model of a carbon-capture power plant(CCPP)that couples the carbon market and the economic operation of the power system is also *** critical,profitable conditions for the economic operation of the CCPP were *** studies demonstrated that the proposed low-carbon,robust dispatch model reduced carbon emissions by 2.67%compared with the traditional,economic,dispatch *** total fuel cost of generation decreases with decreasing,conservative,carbon-price-uncertainty levels,while total carbon emissions continue to *** the carbon-quota coefficient decreases,the system dispatch tends to increase low-carbon unit *** study can provide important guidance for carbon-market design and the low-carbon-dispatch selection strategies.

关键词： Asynchronous coupling mechanism Collaborative robust optimization Carbon price uncertainty Carbon capture power plant Low carbon dispatch

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QBIoT:A Quantum Blockchain Framework for IoT with an Improved Proof-of-Authority Consensus Algorithm and a Public-Key Quantum Signature

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Computers, Materials & Continua 2024年第7期80卷 1727-1751页

作者： Ang Liu Qing zhang Shengwei Xu Huamin Feng xiu-bo Chen Wen Liu Network and Information Management Division Beijing Electronic Science and Technology InstituteBeijing100070China Department of Cyberspace Security Beijing Electronic Science and Technology InstituteBeijing100070China Information Security Institute Beijing Electronic Science and Technology InstituteBeijing100070China General Office Beijing Electronic Science and Technology InstituteBeijing100070China Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China

The Internet of Things(IoT)is a network system that connects physical devices through the Internet,allowing them to ***,IoT has become an integral part of our lives,offering convenience and smart ***,the growing number of IoT devices has brought about a corresponding increase in cybersecurity threats,such as device vulnerabilities,data privacy concerns,and network *** blockchain technology with IoT has proven to be a promising approach to enhance IoT ***,the emergence of quantum computing poses a significant challenge to the security of traditional classical cryptography used in blockchain,potentially exposing it to quantum *** support the growth of the IoT industry,mitigate quantum threats,and safeguard IoT data,this study proposes a robust blockchain solution for IoT that incorporates both classical and post-quantum security ***,we present the Quantum-Enhanced Blockchain Architecture for IoT(QBIoT)to ensure secure data sharing and integrity ***,we propose an improved Proof of Authority consensus algorithm called“Proof of Authority with Random Election”(PoARE),implemented within QBIoT for leader selection and new block ***,we develop a publickey quantum signature protocol for transaction verification in the ***,a comprehensive security analysis of QBIoT demonstrates its resilience against cyber threats from both classical and quantum *** summary,this research introduces an innovative quantum-enhanced blockchain solution to address quantum security concernswithin the realmof *** proposedQBIoT framework contributes to the ongoing development of quantum blockchain technology and offers valuable insights for future research on IoT security.

关键词： IoT quantum blockchain public-key quantum signature quantum hash function

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A reverse particle grading strategy for design and fabrication of porous SiC ceramic supports with improved strength

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Journal of Advanced Ceramics 2024年第7期13卷 1011-1022页

作者： Zheng Liang Han zhang Yichuan Li Wenkang zhang Jian Zhou Qilin Gu Zhaoxiang zhong Weihong Xing State Key Laboratory of Materials-Oriented Chemical Engineering National Engineering Research Center for Special Separation MembraneNanjing Tech UniversityNanjing 211816China Nanjing Membrane Application Institute Co. Ltd.Nanjing 210009China

Porous ceramics usually require high mechanical strength and maximized porosity simultaneously,while for conventional particle grading strategies,it is highly challenging to meet both *** this end,a reverse particle grading strategy was developed based on the linear packing model by unusually introducing coarse particles(d_(50)=16μm)into a fine particle(d50=5μm)*** the extrusion and sintering process,tubular porous SiC ceramic supports with improved mechanical strength were successfully *** effects of coarse particles on the rheological properties of the ceramic paste and the macroscopic properties and microstructure of the SiC supports were systematically *** an increase in the content of coarse SiC particles to 30 wt%,the pressure generated during extrusion decreased from 5.5±0.2 to 1.3±0.1 ***,the bending strength of the tubular supports increased from 36.6±5.6 to 49.1±4.5 MPa when 20 wt%coarse powder was *** notably improved mechanical strength was attributed to the distribution of coarse particles that prolonged the route of crack ***,the optimized tubular supports had an average pore size of 1.2±0.1μm,an open porosity of 45.1%±1.6%,and a water permeability of 7163±150 L/(m^(2)·h·bar)as well as good alkali and acid corrosion ***,the strategy was proven to be feasible for the scale-up fabrication of 19-channel SiC tubular porous ceramic supports.

关键词： porous SiC ceramic tubular ceramic support reverse particle grading reaction bonding chemical stability

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The superiority of nonconjugated structures in fluorescence:through-space ***-bond charge transfer

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Science China Chemistry 2024年第9期67卷 3121-3130页

作者： Weihao Tu Zuping Xiong Lei Wang Jianyu zhang Jing Zhi Sun Haoke zhang Ben zhong Tang MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and EngineeringZhejiang UniversityHangzhou 310058China Zhejiang-Israel Joint Laboratory of Self-Assembling Functional Materials ZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang UniversityHangzhou 311215China Centre of Healthcare Materials Shaoxing InstituteZhejiang UniversityShaoxing 312000China Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and ReconstructionThe Hong Kong University of Science and TechnologyHong Kong 999077China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhen(CUHK-Shenzhen)Guangzhou 518172China

Constructing charge transfer(CT)state by introducing donor(D)and acceptor(A)is an efficient strategy to regulate the photophysical properties of luminescent *** CT-type luminophores are built onπ-conjugated fused-ring structures,which always show hybrid CT/locally excited(LE)states and luminescence quenching effect in the aggregate *** this work,eight conjugated biphenyl(BP)and nonconjugated diphenylmethane(DPM)derivatives with different donors and acceptors are synthesized to investigate the CT *** photophysical characterization and theoretical calculation demonstrate that the through-space CT(TSCT)in nonconjugated DA-DPM exhibit superior photophysical performance than the conjugated DA-BP with through-bond CT(TBCT),the main manifestations are as follows:(1)TSCT luminophores produce longer maximum emission wavelength(λ_(em))than the corresponding TBCT *** example,the longest λ_(em)of DMA-CN-DPM(DMA,dimethylamino)is 621 nm but the corresponding λ_(em)of DMA-CN-BP is only 480 nm.(2)TSCT-based DA-DPM demonstrates more sensitive responsiveness to environmental stimuli such as temperature and polarity.(3)Complete separation of the the highest occupied molecular orbital(HOMO)and the lowest unoccupied molecular orbital(LUMO)distribution exists in all kinds of conformation of DA-DPM,which was hard to realize in conjugated DA-BP.

关键词： through-space charge transfer through-space conjugation clusteroluminescence diphenylmethane

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Method for the multi-view estimation of fish mass using a two-stage neural network with edge-sensitive module

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International Journal of Agricultural and Biological Engineering 2024年第3期17卷 222-229页

作者： Zeyu Jiao Yingjie Cai Qi zhang Zhenyu zhong Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent ManufacturingGuangdong Academy of SciencesGuangzhou 510070China Department of Electronic Engineering The Chinese University of Hong KongHong Kong 999077China College of Economics and Management Northwest A&F UniversityYangling 712100ShaanxiChina

The estimation of fish mass is one of the most basic and important tasks in *** the mass of fish at different growth stages is of great significance for feeding,monitoring the health status of fish,and making breeding plans to increase *** existing estimation methods for fish mass often stay in the 2D plane,and it is difficult to obtain the 3D information on fish,which will lead to the *** solve this problem,a multi-view method was proposed to obtain the 3D information of fish and predict the mass of fish through a two-stage neural network with an edge-sensitive *** the first stage,the side-and downward-view images of the fish and some 3D information,such as side area,top area,length,deflection angle,and pitch angle,were captured to estimate the size of the fish through two vertically placed *** the area of the fish at different views was estimated accurately through the pre-trained image segmentation neural network with an edgesensitive *** the second stage,a fully connected neural network was constructed to regress the fish mass based on the 3D information obtained in the previous *** experimental results indicate that the proposed method can accurately estimate the fish mass and outperform the existing estimation methods.

关键词： fish mass multi-view estimation two-stage neural network edge-sensitive module image segmentation

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Investigating Periodic Dependencies to Improve Short-Term Load Forecasting

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Energy Engineering 2024年第3期121卷 789-806页

作者： Jialin Yu Xiaodi zhang Qi zhong Jian Feng State Grid Zhejiang Jiaxing Electric Power Co. Ltd.Jiaxing314000China State Grid Zhejiang Electric Power Co. Ltd.Hangzhou310000China

With a further increase in energy flexibility for customers,short-term load forecasting is essential to provide benchmarks for economic dispatch and real-time alerts in power *** electrical load series exhibit periodic patterns and share high associations with metrological ***,current studies have merely focused on point-wise models and failed to sufficiently investigate the periodic patterns of load series,which hinders the further improvement of short-term load forecasting ***,this paper improved Autoformer to extract the periodic patterns of load series and learn a representative feature from deep decomposition and *** addition,a novel multi-factor attention mechanism was proposed to handle multi-source metrological and numerical weather prediction data and thus correct the forecasted electrical *** paper also compared the proposed model with various competitive *** the experimental results reveal,the proposed model outperforms the benchmark models and maintains stability on various types of load consumers.

关键词： Load forecasting transformer attention mechanism power grid

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Unbalanced private set intersection with linear communication complexity

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Science China(Information Sciences) 2024年第3期67卷 79-93页

作者： Quanyu ZHAO Bingbing JIANG Yuan zhang Heng WANG Yunlong MAO Sheng zhong Department of Computer Science and Technology Nanjing University Purple Mountain Lab

The private set intersection(PSI) protocol allows two parties holding a set of integers to compute the intersection of their sets without revealing any additional information to each other. The unbalanced PSI schemes consider a specific setting where a client holds a small set of the size n and a server holds a much larger set of the size m(n ■ m). The communication overhead of state-of-the-art balanced PSI schemes is O(m + n) and the unbalanced PSI schemes are O(nlogm). In this paper, we propose a novel secure unbalanced PSI protocol based on a hash proof system. The communication complexity of our protocol grows only linearly with the size of the small set. In other words, our protocol achieves communication overhead of O(n). We test the performance on a personal computer(PC) machine with a local area network(LAN)setting for the network. The experimental results demonstrate that the client only takes 2.01 s of online computation, 4.27 MB of round trip communication to intersect 1600 pieces of 32-bit integers with 220pieces of 32-bit integers with the security parameter λ = 512. Our protocol is efficient and can be applied to resource-constrained devices, such as cell phones.

关键词： unbalanced private set intersection Hash proof system linear communication complexity small set resource-constrained devices

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Predictability of the 7·20 extreme rainstorm in Zhengzhou in stochastic kinetic-energy backscatter ensembles

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Science China Earth Sciences 2024年第7期67卷 2226-2241页

作者： Min YANG Peilong YU Lifeng zhang Xiaobing PAN Quanjia zhong Yunying LI College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073China Key Laboratory of High Impact Weather(Special) China Meteorological AdministrationChangsha 410073China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjing 210044China Department of Ocean Science Hong Kong University of Science and TechnologyHong Kong 999077China

The scale-dependent predictability of the devastating 7·20 extreme rainstorm in Zhengzhou,China in 2021 was investigated via ensemble experiments,which were perturbed on different scales using the stochastic kinetic-energy backscatter(SKEB)scheme in the WRF model,with the innermost domain having a 3-km grid *** daily rainfall(RAIN24h)and the cloudburst during 1600-1700 LST(RAIN1h)were *** demonstrated that with larger perturbation scales,the ensemble spread for the rainfall maximum widens and rainfall forecasts become closer to the *** ensembles with mesoscale or convective-scale perturbations,RAIN1h loses predictability at scales smaller than 20 km and RAIN24h is predictable for all *** in ensembles with synoptic-scale perturbations,the largest scale of predictability loss extends to 60 km for both RAIN1h and ***,the average positional error in forecasting the heaviest rainfall for RAIN24h(RAIN1h)was 400 km(50-60)*** southerly low-level jet near Zhengzhou was assumed to be directly responsible for the forecast uncertainty of *** rapid intensification in low-level cyclonic vorticity,mid-level divergence,and upward motion concomitant with the jet dynamically facilitated the *** analysis of the divergent,rotational and vertical kinetic spectra and the corresponding error spectra showed that the error kinetic energy at smaller scales grows faster than that at larger scales and saturates more quickly in all ***-scale perturbations not only boost larger-scale error growth but are also conducive to error growth at all scales through a downscale cascade,which indicates that improving the accuracy of larger-scale flow forecast may discernibly contributes to the forecast of cloudburst intensity and position.

关键词： Stochastic kinetic-energy backscatter(SKEB) Extreme rainfall Ensemble forecast Predictability

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A residual denoising and multiscale attention-based weighted domain adaptation network for tunnel boring machine main bearing fault diagnosis

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Science China(Technological Sciences) 2024年第8期67卷 2594-2618页

作者： zhong Tao QIN ChengJin SHI Gang zhang ZhiNan TAO JianFeng LIU ChengLiang State Key Laboratory of Mechanical System and Vibration School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

As a critical component of a tunnel boring machine(TBM),the precise condition monitoring and fault analysis of the main bearing is essential to guarantee the safety and efficiency of the TBM cutter ***,under conditions of strong noise and complex working environments,traditional signal decomposition and machine learning methods struggle to extract weak fault features and achieve high fault classification *** address these issues,we propose a novel residual denoising and multiscale attention-based weighted domain adaptation network(RDMA-WDAN)for TBM main bearing fault *** approach skillfully designs a deep feature extractor incorporating residual denoising and multiscale attention modules,achieving better domain adaptation despite significant domain *** residual denoising component utilizes a convolutional block to extract noise features,removing them via residual ***,the multiscale attention module uses a 4-branch convolution and 3 pooling strategy-based channel–spatial attention mechanism to extract multiscale features,concentrating on deep fault *** training,a weighting mechanism is introduced to prioritize domain samples with clear fault *** optimizes the deep feature extractor to obtain common features,enhancing domain adaptation.A low-speed and heavy-loaded bearing testbed was built,and fault data sets were established to validate the proposed *** experiments show that in noise domain adaptation tasks,proposed the RDMA–WDAN significantly improves target domain classification accuracy by 42.544%,23.088%,43.133%,16.344%,5.022%,and 9.233%over dense connection network(DenseNet),squeeze–excitation residual network(SE-ResNet),antinoise multiscale convolutional neural network(ANMSCNN),multiscale attention module-based convolutional neural network(MSAMCNN),domain adaptation network,and hybrid weighted domain adaptation(HWDA).In combined noise and working condition domain a

关键词： tunnel boring machine(TBM) main bearing fault diagnosis domain adaptation antinoise cross working RDMA-WDAN

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