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A Wind Tunnel Experimental Study on the Wake Characteristics of a Horizontal Axis Wind Turbine

Journal of Thermal Science 2025年第1期34卷 145-158页

作者： GUO Xingduo li Yinran li Rennian MA Yulong wei Kui College of Energy and Power Engineering Lanzhou University of Technology Key Laboratory of Fluid Machinery and Systems Gansu Provincial Technology Centre for Wind Turbines

The characteristics of wind turbine wakes are influenced by multiple factors,including the atmospheric boundary layer(ABL) wind and wind turbine operating conditions(e.g.,tip speed ratio and yaw angle).In this study,two types of ABL winds with different velocity gradients and turbulence intensities are generated in a wind tunnel through configurations of spires,baffles,and various numbers of roughness elements.A wind turbine with a rotor diameter of 0.8 m and a hub height of 0.6 m is tested under varying tip speed ratios,yaw angles,and ABL wind *** results indicate that the streamwise velocity deficit in the near-wake region becomes more pronounced with an increase in the tip speed ratio,while the far-wake velocity deficit remains largely unaffected by changes in the tip speed *** the yaw angle increases,the wake deflection becomes more prominent and the wake narrows;the offset of the wake center at various downstream positions grows linearly,reaching a maximum value of approximately half the rotor ***,the turbulence level and influence range in the wake region are reduced when the turbine is *** ABL wind conditions,high turbulence intensity in the incoming flow accelerates wake recovery,and the Reynolds stress at different lateral positions tends to become consistent with increasing longitudinal ***,turbulence has a significant impact on the meandering characteristics of the wind turbine wake,with greater fluctuations in the wake center observed under higher turbulence ***,this study provides insights that could inform the optimal operation of wind farms.

关键词： horizontal axis wind turbine turbulence wind tunnel experiment wind turbine wake

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Sequence-activated chemiluminescence probes: programmable illumination for high-contrast in vivo sensing and imaging

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Science China Chemistry 2025年第1期68卷 26-34页

作者： Yutao Zhang Juan li wei-Hong Zhu Zhiqian Guo Shanghai Key Laboratory of Functional Materials Chemistry Joint International Research Laboratory of Precision Chemistry and Molecular Engineering Institute of Fine Chemicals School of Chemistry and Molecular Engineering East China University of Science and Technology State Key Laboratory of Bioreactor Engineering Shanghai Frontier Science Research Base of Optogenetic Techniques for Cell MetabolismEast China University of Science & Technology

Sequence-activated chemiluminescence(CL) technique offers a unique approach to detecting specific biomolecules or cellular events with high sensitivity and spatial resolution. The fundamental principle behind sequence-activated CL probes involves tailoring highly-controllable CL signals in response to specific sequences or events of interest, thus enabling high-contrast signals under complex physiological conditions. This sequential activation could be triggered by enzymes, reactive oxygen species(ROS), biothiols or changes in the microenvironment. These unique sequence-activated CL probes bestow several advantages, including minimal background, deep-tissue penetration, and the ability of non-invasive or minimally invasive detection. The sequence-activated CL techniques represent a significant advancement in molecular imaging and diagnostics. In this mini-review, we focus on the latest developments in sequential CL probes, addressing the technical challenges and discussing the future trajectory by harnessing CL signaling and molecular recognition.

关键词： chemiluminescnece sequence-activation in-vivo bioimaging cyclic peroxide

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Research on Stock Price Prediction Method Based on the GAN-LSTM-Attention Model

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Computers, Materials & Continua 2025年第1期82卷 609-625页

作者： Peng li Yanrui wei lili Yin College of Computer Science and Technology Harbin University of Science and TechnologyHarbin150006China

Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and *** paper introduces a generative adversarial network model that incorporates an attention mechanism(GAN-LSTM-Attention)to improve the accuracy of stock price ***,the generator of this model combines the long and Short-Term Memory Network(LSTM),the Attention Mechanism and,the Fully-Connected Layer,focusing on generating the predicted stock *** discriminator combines the Convolutional Neural Network(CNN)and the Fully-Connected Layer to discriminate between real stock prices and generated stock ***,to evaluate the practical application ability and generalization ability of the GAN-LSTM-Attention model,four representative stocks in the United States of America(USA)stock market,namely,Standard&Poor’s 500 Index stock,Apple Incorporatedstock,AdvancedMicroDevices Incorporatedstock,and Google Incorporated stock were selected for prediction experiments,and the prediction performance was comprehensively evaluated by using the three evaluation metrics,namely,mean absolute error(MAE),root mean square error(RMSE),and coefficient of determination(R2).Finally,the specific effects of the attention mechanism,convolutional layer,and fully-connected layer on the prediction performance of the model are systematically analyzed through ablation *** results of experiment show that the GAN-LSTM-Attention model exhibits excellent performance and robustness in stock price prediction.

关键词： Stock price prediction generative adversarial network attention mechanism time-series prediction

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Si-C Foam Porous-Medium Combustion Power-Generation System for low-Calorific-Value Biomass Syngas

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Journal of Thermal Science 2025年第1期34卷 206-222页

作者： YANG Jianwen CHEN wei CAO Bingwei liU Xinhui li Hang College of Mechanical and Aerospace Engineering Jilin University School of Mechanical and Vehicle Engineering Changchun University

Syngas produced from the gasification of organic feedstocks from biomass is one of the clean and sustainable sources of *** advantages of simple access and renewability of biomass energy can meet the energy needs of temporary power *** study presents a biomass power-generation system for vehicular *** biomass and a free-piston Stirling engine generator（FPSEG） as the primary material and prime mover,respectively,biomass energy is converted into electricity by combusting the syngas to heat the *** and key parameter design for biomass gasification and thermoelectric conversion systems within a power generation system were performed.A porous medium area was constructed using Si-C foam ceramics to obtain an energy-conversion experimental *** effects of bed height,porosity,porous-region diameter,and air-intake conditions on the power-generation performance were investigated,and optimisations were performed for the thermoelectric conversion *** rate of increase during FPSEG power generation first increased and then decreased with increasing bed height,peaking at a bed height of 40 *** increasing porous-region diameter accelerated FPSEG power generation,whereas porosity changes in the porous media did not significantly affect the rate of change during FPSEG power *** increasing air intake,the rate of increase during power generation first increased and then *** maximum change rate and the highest thermoelectric conversion efficiency of the power-generation system occurred at 9.5 m3/h and 6.5 m3/h（～45.1%）air intakes,*** the thermal inertia and combustion structure of the thermoelectric conversion system significantly increased the power-generation rate of the system,with 1.8 W/s being observed at a 9.7 m3/h air intake.

关键词： biomass combined heat and power (CHP) gasification porous media combustion power generation

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Quantum public-key crypto via EPR pairs

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 58-63页

作者： Xiang-Qun Fu Hong-wei li Jian-Hong Shi Tan li Wan-Su Bao Henan Key Laboratory of Quantum Information and Cryptography Information Engineering University Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China

With the development of quantum computing technology, quantum public-key cryptography is gradually becoming an alternative to the existing classical public-key cryptography. This paper designs a quantum trapdoor one-way function via EPR pairs and quantum measurements. Based on this, a new quantum public-key cryptosystem is presented, which offers forward security,and can resist the chosen-plaintext attack and chosen-ciphertext attack. Compared with the existing quantum public-key cryptos,eavesdropping can be automatically detected in this new quantum public-key cryptosystem under a necessary condition, which is also detailed in the paper.

关键词： quantum public-key crypto trapdoor one-way function EPR pairs

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Domain generalization with semi-supervised learning for people-centric activity recognition

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Science China(Information Sciences) 2025年第1期68卷 171-188页

作者： Jing liU wei ZHU Di li Xing HU liang SONG Academy for Engineering & Technology Fudan University Shanghai East-bund Research Institute on Networking Systems of AI School of Optoelectronic Information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Aerodynamic Optimization and Flow Mechanism for a Compressor Cascade at low Reynolds Number

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Journal of Thermal Science 2025年第1期34卷 92-109页

作者： li lin ZHANG Jianshe CHEN Caiyan TAN wei ZHANG Yanfeng Key Laboratory of light-Duty Gas-Turbine Institute of Engineering ThermophysicsChinese Academy of Sciences University of Chinese Academy of Sciences National Key Laboratory of Science and Technology on Advanced light-duty Gas-turbine

low-Reynolds-number effect is an important factor affecting the performance of compressors and other main components of high-altitude long-endurance unmanned aerial *** improve the flow condition and reduce flow loss under the condition of high altitude and low Reynolds number(Re),this paper proposes an optimization process based on a surrogate model,which combines the class-shape transformation method(CST),the Latin hypercube sampling(LHS) method,the light gradient-boosting machine algorithm(lightGBM),and a genetic algorithm(GA) to optimize a high-subsonic compressor *** surrogate model is verified to be accurate and can be used in the optimization *** accuracy of the GA is higher than the other algorithms under common test *** optimization results are verified by numerical simulation,and the flow differences before and after optimization are compared,especially the flow within the boundary *** changing the blade shape,the optimization process adjusts the loading distribution to delay the transition of the optimized blade on the suction surface,which changes the turbulent reattachment in the laminar separation bubble(LSB) into laminar ***,the mixing loss induced by the turbulent reattachment of the LSB and the wake loss of turbulent separation at the trailing edge are significantly reduced,and the performance of the compressor profile is finally *** addition,turbulent separation of the optimized profile is delayed reducing the range of the wake region on the suction *** this optimization process,the reduction of total pressure loss coefficient at Re of 2.5×10～5,3.5×10～5,and 4.5×10～5 are 16.32%,20.76%,and 22.16%,respectively.

关键词： Reynolds number

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Clinical characteristics of patients with congenital long QT syndrome and bigenic mutations

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Chinese Medical Journal 2014年第8期127卷 1482-1486页

作者： Juang Jyh-Ming Jimmy Chen Ching-Yu Yeh Huei-Ming Chiu wei-Yih Yu Chih-Chieh liu Yen-Bin Tsai Chia-Ti lo li-wei Yeh Shih-Fan Sherri Lai ling-Ping Cardiovascular Center and Division of Cardiology Department of Internal Medicine Department of Anesthesiology Department of Environmental and Occupational Medicine Division of Endocrinology and Metabolism Department of Internal Medicine Taiwan University Hospital and Taiwan University College of Medicine Taipei Taiwan China

Background Congenital long QT syndrome （LQTS） is an ion channelopathy associated with genetic mutations. It is well known that most LQTS patients （91%） have a single mutation. The purpose of this study was to investigate the clinical characteristics of congenital LQTS patients with bigenic mutations in Taiwan, China. Methods Congenital LQTS patients were recruited consecutively at Taiwan University Hospital in Taiwan from 2003 to 2009. The diagnosis of LQTS was defined by an LQTS Schwartz score greater than 4. Mutation screening in KCNQ1, KCNH2, KCNE1, and SCN5A was performed using direct sequencing. Results Three of 16 LQTS patients （18.7%） were identified with bigenic mutations. One patient had missense mutations in KCNQ1 and KCNH2, the second in KCNQ1 and KCNE1, and the third in KCNH2 and SCN5A. The mean age at onset of LQTS for patients with bigenic mutations was （17±3） years, and all of these patients were female. Two of them experienced seizure and one presented with syncope, although one of them had a family history of syncope. The mean QTc interval was （515＋17） ms, similar to those with single mutation or SNPs （（536~74） ms, P=-0.63）. Compared to those LQTS patients with single mutation or SNPs, a significantly higher percentage of LQTS patients with bigenic mutations presented with seizure and were younger at onset of the first index event （P=0.03 and 0.001, respectively）, but lower percentage of them presented with sudden cardiac death （P=0.03）. Conclusions Although the percentage of bigenic mutations in LQTS is less than 10% in Caucasian populations, we identified 3 of 16 LQTS patients （18.7%, 95% confidence interval： 0.04-0.46） with bigenic mutations in Taiwan. However, the sevedtv of their clinical presentations was not hioher than those patients with sinele mutation or SNPs.

关键词： long QTsyndrome genetic mutation Taiwan Chinese

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A Rapid Adaptation Approach for Dynamic Air‑Writing Recognition Using Wearable Wristbands with Self‑Supervised Contrastive Learning

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Nano-Micro Letters 2025年第2期17卷 417-431页

作者： Yunjian Guo Kunpeng li wei Yue Nam‑Young Kim Yang li Guozhen Shen Jong‑Chul Lee Department of Electronic Convergence Engineering Kwangwoon UniversitySeoul 01897South Korea Radio Frequency Integrated Circuit(RFIC)Bio Centre Kwangwoon UniversitySeoul 01897South Korea Department of Electronic Engineering Kwangwoon UniversitySeoul 01897South Korea School of Microelectronics Shandong UniversityJinan 250101People’s Republic of China State Key Laboratory of Integrated Chips and Systems Fudan UniversityShanghai 200433People’s Republic of China School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081People’s Republic of China

Wearable wristband systems leverage deep learning to revolutionize hand gesture recognition in daily *** existing approaches that often focus on static gestures and require extensive labeled data,the proposed wearable wristband with selfsupervised contrastive learning excels at dynamic motion tracking and adapts rapidly across multiple *** features a four-channel sensing array composed of an ionic hydrogel with hierarchical microcone structures and ultrathin flexible electrodes,resulting in high-sensitivity capacitance *** wireless transmission from a Wi-Fi module,the proposed algorithm learns latent features from the unlabeled signals of random wrist ***,only few-shot labeled data are sufficient for fine-tuning the model,enabling rapid adaptation to various *** system achieves a high accuracy of 94.9%in different scenarios,including the prediction of eight-direction commands,and air-writing of all numbers and *** proposed method facilitates smooth transitions between multiple tasks without the need for modifying the structure or undergoing extensive task-specific *** utility has been further extended to enhance human–machine interaction over digital platforms,such as game controls,calculators,and three-language login systems,offering users a natural and intuitive way of communication.

关键词： Wearable wristband Self-supervised contrastive learning Dynamic gesture Air-writing Human-machine interaction

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Precise gradient separation of nanoparticles using reduced graphene oxide-polyoxomolybdate membranes

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Science China Chemistry 2025年第1期68卷 209-216页

作者： Yixin Yang Wanlei Zhao Ruoxuan Zheng Hongqiang li wei Chen Yu-Fei Song State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical Technology Quzhou Institute for Innovation in Resource Chemical Engineering

The purification and size sieving of nanoparticles （NPs） represents a significant scientific ***,the r GO-polyoxometalates (POMs=PMo12,Mo132and Mo368) membranes were fabricated successfully via a simple and scalable POMsassisted in-situ photoreduction *** the mass ratio of r GO to PMo12was 1:30,the resultant r GO-PMo12membranes with highly ordered and uniform nanochannels of 1.0 nm can be obtained,which showed an accurate carbon quantum dots（CQDs） separation with a cut-off size approximately 1.0 *** increase of the size of the interlayered POMs from PMo12（1.0 nm）,{Mo132}（2.9 nm） to{Mo368}（3.8 nm）,the resultant r GO-PMo12,r GO-Mo132and r GO-Mo368exhibited precise gradient separation of CQDs and Au nanoparticles by size exclusion *** results pave a promising way to construct new twodimensional （2D） membranes for highly efficient size-selective separation.

关键词： reduced graphene oxide polyoxometalates membranes gradient separation nanoparticles

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