聚焦PEP新教材Start to read板块教学,针对传统阅读启蒙课存在的思维培养不足、教学活动单一等问题,提出“问题·活动·评价”三位一体的教学新范式。通过构建层级化问题体系引导思维进阶,设计梯度式活动促进语篇理解,实施全程...聚焦PEP新教材Start to read板块教学,针对传统阅读启蒙课存在的思维培养不足、教学活动单一等问题,提出“问题·活动·评价”三位一体的教学新范式。通过构建层级化问题体系引导思维进阶,设计梯度式活动促进语篇理解,实施全程化评价保障学习效果。研究表明,该范式能有效提升学生阅读兴趣与综合语言能力,为小学英语阅读启蒙教学提供可复制、可推广的创新路径。展开更多
High-precision magnetic field measurements are crucial for understanding Earth’s internal structure,space environment,and dynamic geomagnetic variations.Data from the Fluxgate Magnetometer (FGM) on the Macao Science ...High-precision magnetic field measurements are crucial for understanding Earth’s internal structure,space environment,and dynamic geomagnetic variations.Data from the Fluxgate Magnetometer (FGM) on the Macao Science Satellite-1A (MSS-1A),added to data from other space-based magnetometers,should increase significantly the ability of scientists to observe changes in Earth’s magnetic field over time and space.Additionally,the MSS-1A’s FGM is intended to help identify magnetic disturbances affecting the spacecraft itself.This report focuses on the in-flight calibration of the MSS-1 FGM.A scalar calibration,independent of geomagnetic field models,was performed to correct offsets,sensitivities,and misalignment angles of the FGM.Using seven months of data,we find that the in-flight calibration parameters show good stability.We determined Euler angles describing the rotational relationship between the FGM and the Advanced Stellar Compass (ASC) coordinate system using two approaches:calibration with the CHAOS-7 geomagnetic field model,and simultaneous estimation of Euler angles and Gaussian spherical harmonic coefficients through self-consistent modeling.The accuracy of Euler angles describing the rotation was better than 18 arcsec.The calibrated FGM data exhibit good agreement with the calibrated data of the Vector Field Magnetometer (VFM),which is the primary vector magnetometer of the satellite.These calibration efforts have significantly improved the accuracy of the FGM measurements,which are now providing reliable data for geomagnetic field studies that promise to advance our understanding of the Earth’s magnetic environment.展开更多
BACKGROUND:In-flight medical emergencies(IMEs)present significant challenges to healthcare professionals,particularly those with limited training or experience in managing such situations.The objective of this study w...BACKGROUND:In-flight medical emergencies(IMEs)present significant challenges to healthcare professionals,particularly those with limited training or experience in managing such situations.The objective of this study was to evaluate the level of knowledge,attitudes,and behaviors of licensed doctors in Saudi Arabia concerning IMEs,and to identify the demographic factors influencing their preparedness.METHODS:A cross-sectional study was conducted with a sample of 383 licensed physicians across five regions of Saudi Arabia.Participants completed a self-administered questionnaire assessing demographics,knowledge of IMEs,attitudes towards providing assistance,and previous experience with in-flight emergencies.Data were analyzed using SPSS 26,with statistical significance set at P<0.05.RESULTS:The results revealed a predominantly young(75.8% aged 25-34 years)and male(69.6%)participant pool.While 76.6% of respondents recognized the impact of cabin pressure on oxygen,only 45.4% correctly identified air travel risks for asthmatic patients.Although 66.8% felt confident assisting in IMEs,20.9% cited medicolegal concerns.Moreover,area of working within Saudi Arabia(P=0.020),year of experience(P=0.041),prior experience with IMEs(P=0.021),and IMEs training(P<0.001)had a significant association with levels of knowledge.CONCLUSION:The study highlights a critical need for enhanced training programs with a focus on the management of IMEs among healthcare practitioners in Saudi Arabia.展开更多
In the realm of all-electric aircraft research,the integration of cathode-open proton exchange membrane fuel cells(PEMFC)with lithiumbatteries as a hybrid power source for small to medium-sized unmanned aerial vehicle...In the realm of all-electric aircraft research,the integration of cathode-open proton exchange membrane fuel cells(PEMFC)with lithiumbatteries as a hybrid power source for small to medium-sized unmanned aerial vehicles(UAVs)has garnered significant attention.The PEMFC,serving as the primary energy supply,markedly extends the UAV’s operational endurance.However,due to payload limitations and spatial constraints in the airframe layout of UAVs,the stack requires customized adaptation.Moreover,the implementation of auxiliary systems to facilitate cold starts of the PEMFC under low-temperature conditions is not feasible.Relying solely on thermal insulation measures also proves inadequate to address the challenges posed by complex low-temperature startup scenarios.To overcomethis,our study leverages the UAV’s lithium battery to heat the cathode inlet airflow,aiding the cathode-open PEMFC cold start process.To validate the feasibility of the proposed air-assisted heating strategy during the conceptual design phase,this study develops a transient,non-isothermal 3Dcathode-open PEMF Cunitmodel incorporating cathode air-assisted heating and gas-ice phase change.The model’s accuracy was verified against experimental cold-start data from a stack composed of identical single cells.This computational framework enables quantitative analysis of temperature fields and ice fraction distributions across domains under varying air-assisted heating powers during cold starts.Building upon this model,the study further investigates the improvement in cold start performance by heating the cathode intake air with varying power levels.The results demonstrate that the fuel cell achieves self-startup at temperatures as low as−13℃ under a constant current density of 100mA/cm^(2) without air-assisted heating.At an ambient temperature of−20℃,a successful start-up can be achieved with a heating power of 0.45 W/cm^(2).The temperature variation overtime during the cold start process can be represented by a sum of two exponential functions.The air-assisted heating scheme proposed in this study has significantly improved the cold start performance of fuel cells in low-temperature environments.Additionally,it provides critical reference data and validation support for component selection and feasibility assessment of hybrid power systems.展开更多
引言小学英语阅读教学是落实英语学科核心素养的必经之路,而科普绘本阅读又是阅读的重中之重。本文通过对多维阅读科普绘本It Started with a plant的教学案例分析,详细探讨了人工智能赋能小学英语绘本教学的应用策略和实际成效。人工...引言小学英语阅读教学是落实英语学科核心素养的必经之路,而科普绘本阅读又是阅读的重中之重。本文通过对多维阅读科普绘本It Started with a plant的教学案例分析,详细探讨了人工智能赋能小学英语绘本教学的应用策略和实际成效。人工智能的引入,极大地增强了课堂的互动性和趣味性,使学生更深入地理解食物链的逻辑,激发了学习英语的兴趣。人工智能不仅能够为孩子们提供个性化学习体验,还能够极大地提高教学效率和质量。展开更多
This paper investigates the start-up and shutdown phases of a five-bladed closed-impeller centrifugal pump through experimental analysis,capturing the temporal evolution of its hydraulic performances.The study also pr...This paper investigates the start-up and shutdown phases of a five-bladed closed-impeller centrifugal pump through experimental analysis,capturing the temporal evolution of its hydraulic performances.The study also predicts the transient characteristics of the pump under non-rated operating conditions to assess the accuracy of various machine learning methods in forecasting its instantaneous performance.Results indicate that the pump’s transient behavior in power-frequency mode markedly differs from that in frequency-conversion mode.Specifically,the power-frequency mode achieves steady-state values faster and exhibits smaller fluctuations before stabilization compared to the other mode.During the start-up phase,as the steady-state flow rate increases,inlet and outlet pressures and head also rise,while torque and shaft power decrease,with rotational speed remaining largely unchanged.Conversely,during the shutdown phase,no significant changes were observed in torque,shaft power,or rotational speed.Six machine learning models,including Gaussian Process Regression(GPR),Decision Tree Regression(DTR),and Deep Learning Networks(DLN),demonstrated high accuracy in predicting the hydraulic performance of the centrifugal pump during the start-up and shutdown phases in both power-frequency and frequency-conversion conditions.The findings provide a theoretical foundation for improved prediction of pump hydraulic performance.For instance,when predicting head and flow rate during power-frequency start-up,GPR achieved absolute and relative errors of 0.54 m(7.84%)and 0.21 m3/h(13.57%),respectively,while the Feedforward Neural Network(FNN)reported errors of 0.98 m(8.24%)and 0.10 m3/h(16.71%).By contrast,the Support Vector Machine Regression(SVMR)and Generalized Additive Model(GAM)generally yielded less satisfactory prediction accuracy compared to the other methods.展开更多
The ductile-to-brittle transition temperature(DBTT)of high strength steels can be optimized by tailoring microstructure and crystallographic orientation characteristics,where the start cooling temperature plays a key ...The ductile-to-brittle transition temperature(DBTT)of high strength steels can be optimized by tailoring microstructure and crystallographic orientation characteristics,where the start cooling temperature plays a key role.In this work,X70 steels with different start cooling temperatures were prepared through thermo-mechanical control process.The quasi-polygonal ferrite(QF),granular bainite(GB),bainitic ferrite(BF)and martensite-austenite constituents were formed at the start cooling temperatures of 780℃(C1),740℃(C2)and 700℃(C3).As start cooling temperature decreased,the amount of GB decreased,the microstructure of QF and BF increased.Microstructure characteristics of the three samples,such as high-angle grain boundaries(HAGBs),MA constituents and crystallographic orientation,also varied with the start cooling temperatures.C2 sample had the lowest DBTT value(−86℃)for its highest fraction of HAGBs,highest content of<110>oriented grains and lowest content of<001>oriented grains parallel to TD.The high density of{332}<113>and low density of rotated cube{001}<110>textures also contributed to the best impact toughness of C2 sample.In addition,a modified model was used in this paper to quantitatively predict the approximate DBTT value of steels.展开更多
文摘聚焦PEP新教材Start to read板块教学,针对传统阅读启蒙课存在的思维培养不足、教学活动单一等问题,提出“问题·活动·评价”三位一体的教学新范式。通过构建层级化问题体系引导思维进阶,设计梯度式活动促进语篇理解,实施全程化评价保障学习效果。研究表明,该范式能有效提升学生阅读兴趣与综合语言能力,为小学英语阅读启蒙教学提供可复制、可推广的创新路径。
文摘High-precision magnetic field measurements are crucial for understanding Earth’s internal structure,space environment,and dynamic geomagnetic variations.Data from the Fluxgate Magnetometer (FGM) on the Macao Science Satellite-1A (MSS-1A),added to data from other space-based magnetometers,should increase significantly the ability of scientists to observe changes in Earth’s magnetic field over time and space.Additionally,the MSS-1A’s FGM is intended to help identify magnetic disturbances affecting the spacecraft itself.This report focuses on the in-flight calibration of the MSS-1 FGM.A scalar calibration,independent of geomagnetic field models,was performed to correct offsets,sensitivities,and misalignment angles of the FGM.Using seven months of data,we find that the in-flight calibration parameters show good stability.We determined Euler angles describing the rotational relationship between the FGM and the Advanced Stellar Compass (ASC) coordinate system using two approaches:calibration with the CHAOS-7 geomagnetic field model,and simultaneous estimation of Euler angles and Gaussian spherical harmonic coefficients through self-consistent modeling.The accuracy of Euler angles describing the rotation was better than 18 arcsec.The calibrated FGM data exhibit good agreement with the calibrated data of the Vector Field Magnetometer (VFM),which is the primary vector magnetometer of the satellite.These calibration efforts have significantly improved the accuracy of the FGM measurements,which are now providing reliable data for geomagnetic field studies that promise to advance our understanding of the Earth’s magnetic environment.
基金approved by the Regional Research Ethics Committee,Qassim Province,Saudi Arabia.Number(607-45-12634).
文摘BACKGROUND:In-flight medical emergencies(IMEs)present significant challenges to healthcare professionals,particularly those with limited training or experience in managing such situations.The objective of this study was to evaluate the level of knowledge,attitudes,and behaviors of licensed doctors in Saudi Arabia concerning IMEs,and to identify the demographic factors influencing their preparedness.METHODS:A cross-sectional study was conducted with a sample of 383 licensed physicians across five regions of Saudi Arabia.Participants completed a self-administered questionnaire assessing demographics,knowledge of IMEs,attitudes towards providing assistance,and previous experience with in-flight emergencies.Data were analyzed using SPSS 26,with statistical significance set at P<0.05.RESULTS:The results revealed a predominantly young(75.8% aged 25-34 years)and male(69.6%)participant pool.While 76.6% of respondents recognized the impact of cabin pressure on oxygen,only 45.4% correctly identified air travel risks for asthmatic patients.Although 66.8% felt confident assisting in IMEs,20.9% cited medicolegal concerns.Moreover,area of working within Saudi Arabia(P=0.020),year of experience(P=0.041),prior experience with IMEs(P=0.021),and IMEs training(P<0.001)had a significant association with levels of knowledge.CONCLUSION:The study highlights a critical need for enhanced training programs with a focus on the management of IMEs among healthcare practitioners in Saudi Arabia.
基金funded by Zhejiang Province Spearhead and Leading Goose Research and Development Key Program,grant number 2023C01239.
文摘In the realm of all-electric aircraft research,the integration of cathode-open proton exchange membrane fuel cells(PEMFC)with lithiumbatteries as a hybrid power source for small to medium-sized unmanned aerial vehicles(UAVs)has garnered significant attention.The PEMFC,serving as the primary energy supply,markedly extends the UAV’s operational endurance.However,due to payload limitations and spatial constraints in the airframe layout of UAVs,the stack requires customized adaptation.Moreover,the implementation of auxiliary systems to facilitate cold starts of the PEMFC under low-temperature conditions is not feasible.Relying solely on thermal insulation measures also proves inadequate to address the challenges posed by complex low-temperature startup scenarios.To overcomethis,our study leverages the UAV’s lithium battery to heat the cathode inlet airflow,aiding the cathode-open PEMFC cold start process.To validate the feasibility of the proposed air-assisted heating strategy during the conceptual design phase,this study develops a transient,non-isothermal 3Dcathode-open PEMF Cunitmodel incorporating cathode air-assisted heating and gas-ice phase change.The model’s accuracy was verified against experimental cold-start data from a stack composed of identical single cells.This computational framework enables quantitative analysis of temperature fields and ice fraction distributions across domains under varying air-assisted heating powers during cold starts.Building upon this model,the study further investigates the improvement in cold start performance by heating the cathode intake air with varying power levels.The results demonstrate that the fuel cell achieves self-startup at temperatures as low as−13℃ under a constant current density of 100mA/cm^(2) without air-assisted heating.At an ambient temperature of−20℃,a successful start-up can be achieved with a heating power of 0.45 W/cm^(2).The temperature variation overtime during the cold start process can be represented by a sum of two exponential functions.The air-assisted heating scheme proposed in this study has significantly improved the cold start performance of fuel cells in low-temperature environments.Additionally,it provides critical reference data and validation support for component selection and feasibility assessment of hybrid power systems.
文摘引言小学英语阅读教学是落实英语学科核心素养的必经之路,而科普绘本阅读又是阅读的重中之重。本文通过对多维阅读科普绘本It Started with a plant的教学案例分析,详细探讨了人工智能赋能小学英语绘本教学的应用策略和实际成效。人工智能的引入,极大地增强了课堂的互动性和趣味性,使学生更深入地理解食物链的逻辑,激发了学习英语的兴趣。人工智能不仅能够为孩子们提供个性化学习体验,还能够极大地提高教学效率和质量。
基金financially supported by Science and Technology Project of Quzhou(Grant Nos.2023K256,2023NC08)Research Grants Program of Department of Education of Zhejiang Province(No.Y202455709)+1 种基金Zhejiang Provincial Natural Science Foundation of China(Grant No.LZY21E050001)University-Enterprise Cooperation Program for Visiting Engineers in Higher Education Institutions in Zhejiang Province(No.FG2020215).
文摘This paper investigates the start-up and shutdown phases of a five-bladed closed-impeller centrifugal pump through experimental analysis,capturing the temporal evolution of its hydraulic performances.The study also predicts the transient characteristics of the pump under non-rated operating conditions to assess the accuracy of various machine learning methods in forecasting its instantaneous performance.Results indicate that the pump’s transient behavior in power-frequency mode markedly differs from that in frequency-conversion mode.Specifically,the power-frequency mode achieves steady-state values faster and exhibits smaller fluctuations before stabilization compared to the other mode.During the start-up phase,as the steady-state flow rate increases,inlet and outlet pressures and head also rise,while torque and shaft power decrease,with rotational speed remaining largely unchanged.Conversely,during the shutdown phase,no significant changes were observed in torque,shaft power,or rotational speed.Six machine learning models,including Gaussian Process Regression(GPR),Decision Tree Regression(DTR),and Deep Learning Networks(DLN),demonstrated high accuracy in predicting the hydraulic performance of the centrifugal pump during the start-up and shutdown phases in both power-frequency and frequency-conversion conditions.The findings provide a theoretical foundation for improved prediction of pump hydraulic performance.For instance,when predicting head and flow rate during power-frequency start-up,GPR achieved absolute and relative errors of 0.54 m(7.84%)and 0.21 m3/h(13.57%),respectively,while the Feedforward Neural Network(FNN)reported errors of 0.98 m(8.24%)and 0.10 m3/h(16.71%).By contrast,the Support Vector Machine Regression(SVMR)and Generalized Additive Model(GAM)generally yielded less satisfactory prediction accuracy compared to the other methods.
基金Project(2018XK2301) supported by the Change-Zhu-Tan National Independent Innavation Demonstration Zone Special Program,China。
文摘The ductile-to-brittle transition temperature(DBTT)of high strength steels can be optimized by tailoring microstructure and crystallographic orientation characteristics,where the start cooling temperature plays a key role.In this work,X70 steels with different start cooling temperatures were prepared through thermo-mechanical control process.The quasi-polygonal ferrite(QF),granular bainite(GB),bainitic ferrite(BF)and martensite-austenite constituents were formed at the start cooling temperatures of 780℃(C1),740℃(C2)and 700℃(C3).As start cooling temperature decreased,the amount of GB decreased,the microstructure of QF and BF increased.Microstructure characteristics of the three samples,such as high-angle grain boundaries(HAGBs),MA constituents and crystallographic orientation,also varied with the start cooling temperatures.C2 sample had the lowest DBTT value(−86℃)for its highest fraction of HAGBs,highest content of<110>oriented grains and lowest content of<001>oriented grains parallel to TD.The high density of{332}<113>and low density of rotated cube{001}<110>textures also contributed to the best impact toughness of C2 sample.In addition,a modified model was used in this paper to quantitatively predict the approximate DBTT value of steels.
