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Determination of the Pile Drivability Using Random Forest Optimized by Particle Swarm Optimization and Bayesian Optimizer

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 871-892页

作者： Shengdong Cheng Juncheng gao Hongning qi State Key Laboratory of Eco-Hydraulics in Northwest Arid Region Xi’an University of TechnologyXi’an710048China School of Resources and Safety Engineering Central South UniversityChangsha410083China

Driven piles are used in many geological environments as a practical and convenient structural ***,the determination of the drivability of piles is actually of great importance in complex geotechnical *** methods of predicting pile drivability often rely on simplified physicalmodels or empirical formulas,whichmay lack accuracy or applicability in complex geological ***,this study presents a practical machine learning approach,namely a Random Forest(RF)optimized by Bayesian Optimization(BO)and Particle Swarm Optimization(PSO),which not only enhances prediction accuracy but also better adapts to varying geological environments to predict the drivability parameters of piles(i.e.,maximumcompressive stress,maximum tensile stress,and blow per foot).In addition,support vector regression,extreme gradient boosting,k nearest neighbor,and decision tree are also used and applied for comparison *** order to train and test these models,among the 4072 datasets collected with 17model inputs,3258 datasets were randomly selected for training,and the remaining 814 datasets were used for model ***,the results of these models were compared and evaluated using two performance indices,i.e.,the root mean square error(RMSE)and the coefficient of determination(R2).The results indicate that the optimized RF model achieved lower RMSE than other prediction models in predicting the three parameters,specifically 0.044,0.438,and 0.146;and higher R2 values than other implemented techniques,specifically 0.966,0.884,and *** addition,the sensitivity and uncertainty of the optimized RF model were analyzed using Sobol sensitivity analysis and Monte Carlo(MC)*** can be concluded that the optimized RF model could be used to predict the performance of the pile,and it may provide a useful reference for solving some problems under similar engineering conditions.

关键词： Random forest regression model pile drivability Bayesian optimization particle swarm optimization

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Effect of FeSi additive in dual-chamber sample cup on thermal analysis characteristic values and vermiculating rate of compacted graphite iron

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China Foundry 2024年第1期21卷 91-100页

作者： De-quan Shi Ze-yu Liu gui-li gao Yi-cheng Feng School of Materials and Chemistry University of Shanghai for Science and TechnologyShanghai 200093China School of Materials Science and Chemical Engineering Harbin University of Science&TechnologyHarbin 150040China School of Mechanical and Energy Engineering Shanghai Technical Institute of Electronics and InformationShanghai 201411China

Thermal analysis plays a key role in the online inspection of molten iron *** solidification process of molten iron can be reflected by thermal analysis curves,and silicon is one of important elements affecting the solidification of molten *** this study,FeSi75 was added in one chamber of the dual-chamber sample cup,and the influences of FeSi75 additive on the characteristic values of thermal analysis curves and vermiculating rate were *** results show that with the increase of FeSi75,the start temperature of austenite formation TALfirstly decreases and then increases,but the start temperature of eutectic growth TSEF,the lowest eutectic temperature TEU,temperature at maximum eutectic reaction rate TEM,and highest eutectic temperature TERkeep always an *** temperature at final solidification point TEShas little *** FeSi75 additive has different influences on the vermiculating rate of molten iron with different vermiculation,and the vermiculating rate increases for lower vermiculation molten iron while decreases for higher *** to the thermal analysis curves obtained by a dual-chamber sample cup with 0.30wt.%FeSi75 additive in one chamber,the vermiculating rate of molten iron can be evaluated by comparing the characteristic values of these *** time differenceΔtERcorresponding to the highest eutectic temperature TERhas a closer relationship with the vermiculating rate,and a parabolic regression curve between the time differenceΔtERand vermiculating rateηhas been obtained within the range of 65%to 95%,which is suitable for the qualified melt.

关键词： FeSi75 additive characteristic value vermiculating rate thermal analysis compacted graphite iron

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All laser direct writing process for temperature sensor based on graphene and silver

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Frontiers of Optoelectronics 2024年第1期17卷 45-55页

作者： qi Li Ruijie Bai Lianbo Guo Yang gao Shanghai Key Laboratory of Intelligent Sensing and Detection Technology School of Mechanical and Power EngineeringEast China University of Science and TechnologyShanghai 200237China North Automatic Control Technology Institute Taiyuan 030006China Wuhan National Laboratory for Optoelectronics Huazhong University of Science&TechnologyWuhan 430074China

A highly sensitive temperature sensing array is prepared by all laser direct writing(LDW)method,using laser induced silver(LIS)as electrodes and laser induced graphene(LIG)as temperature sensing layer.A finite element analysis(FEA)photothermal model incorporating a phase transition mechanism is developed to investigate the relationship between laser parameters and LIG properties,providing guidance for laser processing parameters selection with laser power of 1–5 W and laser scanning speed(greater than 50 mm/s).The deviation of simulation and experimental data for widths and thickness of LIG are less than 5%and 9%,*** electrical properties and temperature responsiveness of LIG are also *** changing the laser process parameters,the thickness of the LIG ablation grooves can be in the range of 30–120μm and the resistivity of LIG can be regulated within the range of 0.031–67.2Ω・*** percentage temperature coefficient of resistance(TCR)is calculated as−0.58%/°***,the FEA photothermal model is studied through experiments and simulations data regarding LIS,and the average deviation between experiment and simulation is less than 5%.The LIS sensing samples have a thickness of about 14μm,an electrical resistivity of 0.0001–100Ω・m is insensitive to temperature and pressure ***,for a LIS-LIG based temperature sensing array,a correction factor is introduced to compensate for the LIG temperature sensing being disturbed by pressure stimuli,the temperature measurement difference is decreased from 11.2 to 2.6°C,indicating good accuracy for temperature measurement.

关键词： Laser direct writing Temperature sensor Finite element analysis Laser induced graphene Laser induced silver

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Hybrid pedestrian positioning system using wearable inertial sensors and ultrasonic ranging

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Defence Technology（防务技术） 2024年第3期33卷 327-338页

作者： Lin qi Yu Liu Chuanshun gao Tao Feng Yue Yu School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Department of Land Surveying and Geo-Informatics The Hong Kong Polytechnic UniversityHong Kong 999077China

Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,*** performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration *** paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint *** addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial ***,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall *** results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.

关键词： Pedestrian positioning system Wearable inertial sensors Ultrasonic ranging Deep-learning Data and model dual-driven

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Novel medium entropy perovskite oxide Sr(FeCoNiMo)_(1/4)O_(3−δ)for zinc-air battery cathode

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Journal of Energy Chemistry 2024年第9期96卷 669-678页

作者： Kaixin Li Juntao gao Xu Han qi Shao Zhe Lü School of Physics Harbin Institute of TechnologyHarbin 150001HeilongjiangChina Heilongjiang Provincial Key Laboratory of Advanced Quantum Functional Materials and Sensor Components Harbin 150001HeilongjiangChina

It is widely recognized that the development of ZABs is impeded by the kinetic bottleneck of oxygen evolution reaction(OER)and oxygen reduction reaction(ORR).The application of conformational entropy strategy to oxides often involves introducing multiple elements with different properties,thereby providing outstanding bifunctional catalytic activity for OER/***,the possible underlying catalytic pathways and potential interactions between various components are still poorly *** paper presents an excellent medium-entropy perovskite oxide,Sr(FeCoNiMo)_(1/4)O_(3−δ)(lower overpotential of 301 mV at 10 mA cm^(−2)).Zinc-air batteries employing it as a cathode catalyst demonstrate excellent round-trip efficiency(62%).By combining theoretical calculation with experiments,we aim to establish the link between the electronic structure of perovskite oxides with different elemental compositions and their OER *** reveals that the conformational entropy strategy can simultaneously shift the O 2p-band center and metal d-band center of perovskite oxide towards the vicinity of the Fermi energy level,thereby triggering a more favorable lattice oxygen-participated mechanism(LOM)during the OER *** outcomes of this work provide crucial insights into the role of conformational entropy strategies in oxygen catalysis and offer potential avenues for constructing efficient and stable electrocatalysts.

关键词： Sr(FeCoNiMo)_(1/4)O_(3−δ) Bifunctional catalyst Medium entropy LOM Rechargeable zinc-air batteries

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Role of polarization evolution in the hysteresis effect of Pb-based antiferroelecrtics

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Chinese Chemical Letters 2024年第4期35卷 516-519页

作者： Botao gao He qi Hui Liu Jun Chen Beijing Advanced Innovation Center for Materials Genome Engineering Department of Physical ChemistryUniversity of Science and Technology BeijingBeijing 100083China Shanghai Institute of Ceramics Chinese Academy of SciencesShanghai 201899China Hainan University Haikou 570228China

The electric field-induced irreversible domain wall motion results in a ferroelectric(FE) hysteresis. In antiferroelectrics(AFEs), the irreversible phase transition is the main reason for the hysteresis effects, which plays an important role in energy storage performance. Compared to the well-demonstrated FE hysteresis,the structural mechanism of the hysteresis in AFE is not well understood. In this work, the underlying correlation between structure and the hysteresis effect is unveiled in Pb(Zr,Sn,Ti)O_(3) AFE system by using in-situ electrical biasing synchrotron X-ray diffraction. It is found that the AFE with a canting dipole configuration, which shows a continuous polarization rotation under the electric field, tends to have a small hysteresis effect. It presents a negligible phase transition, a small axis ratio, and electric field-induced lattice changing, small domain switching. All these features together lead to a slim hysteresis loop and a high energy storage efficiency. These results offer a deep insight into the structure-hysteresis relationship of AFEs and are helpful for the design of energy storage material.

关键词： Antiferroelectric Hysteresis effect Structure refinement Perovskite In situ synchrotron radiation

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Status of biomarker development for frontotemporal dementia and amyotrophic lateral sclerosis

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Neural Regeneration Research 2024年第10期19卷 2117-2118页

作者： Yue Yang qi Cheng Jianqun gao Woojin Scott Kim Brain and Mind Centre&School of Medical Sciences The University of SydneySydneyNSWAustralia Department of Neurology and Neurophysiology Liverpool HospitalSydneyNSWAustralia Stroke and Neurology Research Group Ingham Institute for Applied Medical ResearchSydneyNSWAustralia Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation ShanghaiChina Clinical Research Center for Anesthesiology and Perioperative Medicine ShanghaiChina Translational Research Institute of Brain and Brain-Like Intelligence Shanghai Fourth People’s HospitalSchool of MedicineTongji UniversityShanghaiChina

Frontotemporal dementia(FTD) and amyotrophic lateral sclerosis(ALS) are neurodegenerative diseases that belong to the same disease spectrum,with overlapping of genetic and pathological *** mutations in TARDBP,C9ORF72,... 详细信息

关键词： amyotrophic sclerosis diseases

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A nonlinear wake model of a wind turbine considering the yaw wake steering

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Journal of Oceanology and Limnology 2024年第3期42卷 715-727页

作者： Yunzhou LI Zhiteng gao Shoutu LI Suiping qi Xiaoyu TANG College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073China Multi-function Towing Tank School of Naval ArchitectureOcean and Civil EngineeringShanghai Jiao Tong UniversityShanghai 200240China School of Energy and Power Engineering Lanzhou University of TechnologyLanzhou 730050China Institute of Oceanographic Instrumentation Qilu University of Technology(Shandong Academy of Sciences)Qingdao 266061China State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Laoshan Laboratory Qingdao 266237China

Duo to fluctuations in atmospheric turbulence and yaw control strategies,wind turbines are often in a yaw *** predict the far wake velocity field of wind turbines quickly and accurately,a wake velocity model was derived based on the method of momentum conservation considering the wake steering of the wind turbine under yaw *** consider the shear effect of the vertical incoming wind direction,a two-dimensional Gaussian distribution function was introduced to model the velocity loss at different axial positions in the far wake region based on the assumption of nonlinear wake *** work also developed a“prediction-correction”method to solve the wake velocity field,and the accuracy of the model results was verified in wake experiments on the Garrad Hassan wind ***,a 33-kW two-blade horizontal axis wind turbine was simulated using this method,and the results were compared with the classical wake model under the same parameters and the computational fluid dynamics(CFD)simulation *** results show that the nonlinear wake model well reflected the influence of incoming flow shear and yaw wake steering in the wake velocity ***,computation of the wake flow for the Horns Rev offshore wind farm with 80 wind turbines showed an error within 8%compared to the experimental *** established wake model is less computationally intensive than other methods,has a faster calculation speed,and can be used for engineering calculations of the wake velocity in the far wakefield of wind turbines.

关键词： far wake wake model wake steering wind shear wind farm

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Bionic immunoactivator copresenting autophagy promoting and costimulatory molecules for synergistic cancer immunotherapy

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Nano Research 2024年第3期17卷 1710-1724页

作者： Yiwei Peng Yiliang Yang Zhenzhen Yang Datong gao Jiajia Li qi Sun Yitian Du Meng Lin Xianrong qi Beijing Key Laboratory of Molecular Pharmaceutics and New Drug Delivery System School of Pharmaceutical SciencesPeking UniversityBeijing 100191China

Immunotherapy has great promise in improving malignant tumor ***,the efficacy of existing strategies is often limited by the immunosuppressive ***,we demonstrate an in situ bionic immunoactivator,PLT-Bec1/DTA-1,with possessed natural advantages of platelets for tumor recruitment and activation,on which DTA-1(CD357 monoclonal antibody)and Bec1 were tethered as combined immune ***-Bec1/DTA-1,as a self-triggered release repository,can deliver the pre-tethered Bec1 and DTA-1 deeply through the secretion of platelet microparticles(PMPs),thereby cooperate tacitly and exhibit superiority in immune activation of dendritic cells(DCs)and T cells via autophagy inducibility,coupled with glucocorticoid-induced tumor necrosis factor receptor(GITR)-triggered T_(Reg) suppression,remodeled the immunosuppressive network of tumor ***-Bec1/DTA-1 promoted antigen presentation and T cell proliferation,and alleviated the low activity state of bone marrow-derived dendritic cells(BMDCs)in tumor suppressive ***-Bec1/DTA-1 inhibited tumor recurrence(5-and 13-fold lower of control group in tumor volume)and CD8^(+)T/T_(Reg) ratio(6.3-and 8.8-fold *** group)in mouse tumor model after intravenous or subcutaneous ***,PLT-Bec1/DTA-1 prevented tumor colonization in lung through in situ immune activation,and was slightly superior to the combined of Bec1 and *** findings highlight the promise of delivering immunostimulatory payloads via bionic carriers,eliciting automatic in situ activation of effector immune cells in tumor microenvironment for tumor *** these results provide promising prospects into the application of immunoactivator in improving cancer synergistic immunotherapy to overcome the bottlenecks in clinic.

关键词： in situ bionic immunoactivator autophagy glucocorticoid-induced tumor necrosis factor receptor(GITR)agonist platelets and platelet microparticles cancer immunotherapy

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Efficient and robust CNN-LSTM prediction of flame temperature aided light field online tomography

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Science China(Technological Sciences) 2024年第1期67卷 271-284页

作者： NIU ZhiTian qi Hong SUN AnTai REN YaTao HE MingJian gao BaoHai School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China Key Laboratory of Aerospace Thermophysics Ministry of Industry and Information TechnologyHarbin 150001China

Light field tomography,an optical combustion diagnostic technology,has recently attracted extensive attention due to its easy implementation and ***,the conventional iterative methods are high data throughput,low efficiency and time-consuming,and the existing machine learning models use the radiation spectrum information of the flame to realize the parameter field measurement at the current *** is still an offline measurement and cannot realize the online prediction of the instantaneous structure of the actual turbulent combustion *** this work,a novel online prediction model of flame temperature instantaneous structure based on deep convolutional neural network and long short-term memory(CNN-LSTM)is *** method uses the characteristics of local perception,shared weight,and pooling of CNN to extract the threedimensional(3D)features of flame temperature and outgoing radiation ***,the LSTM is used to comprehensively utilize the ten historical time series information of high dynamic combustion flame to accurately predict 3D temperature at three future moments.A chaotic time-series dataset based on the flame radiation forward model is built to train and validate the performance of the proposed CNN-LSTM *** is proven that the CNN-LSTM prediction model can successfully learn the evolution pattern of combustion flame and make accurate predictions.

关键词： temperature prediction convolutional neural network long short-term memory light field imaging online tomography

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