To realize cross-wedge rolling of shaft parts without a stub bar in a short process,an axial closed-open-type cross-wedge rolling technique was proposed.Based on the strain characteristics in the rolling,evaluation in...To realize cross-wedge rolling of shaft parts without a stub bar in a short process,an axial closed-open-type cross-wedge rolling technique was proposed.Based on the strain characteristics in the rolling,evaluation indices of deformation uniformity were provided,and the DEFORM-3D software was adopted to conduct numerical simulations of the rolling process.The metal flow and strain distribution in all stages of the rolling process were analyzed.It is shown that the strain value of the rolled piece close to the end is relatively high while the overall strain distribution is uniform in the rolling process.When the percentage reduction in area is smaller,the fluctuation range of the equivalent strain will be lower and the overall uniformity of the rolled piece will be better.A variable angle wedge was implemented to make metal flow inward and eliminate concavity.Finally,rolling experiment was performed,which indicate that the shape of the rolled piece obtained is consistent with the simulation results.Concavity value in the rolling is decreased by 92%as compared to conventional open rolling.The research results lay a theoretical basis for realizing closed-open-type cross-wedge rolling without a stub bar.展开更多
In this feasibility study, we investigate the viability of using Liquefied Natural Gas （LNG） fuel in an open type Ro-Ro passenger ferry and the associated potential challenges with regard to the vessel safety system...In this feasibility study, we investigate the viability of using Liquefied Natural Gas （LNG） fuel in an open type Ro-Ro passenger ferry and the associated potential challenges with regard to the vessel safety systems. We recommend an appropriate methodology for converting existing ships to run on LNG fuel, discuss all the necessary modifications to the ship’s safety systems, and also evaluate the relevant ship evacuation procedures. We outline the basic requirements with which the ship already complies for each safety system and analyze the additional restrictions that must be taken into consideration for the use of LNG fuel. Appropriate actions are recommended. Furthermore, we carry out a hazard identification study. Overall, we clearly demonstrate the technical feasibility of the investigated scenario. Minimal modifications to the ship’s safety systems are required to comply with existing safety rules for this specific type of ship.展开更多
Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model...Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model integrating Deep Residual Network(ResNet)and Support Vector Machine(SVM)for both≥C-class(C,M,and X classes)and≥M-class(M and X classes)flares.We collected samples of magnetograms from May 1,2010 to September 13,2018 from Space-weather Helioseismic and Magnetic Imager(HMI)Active Region Patches and then used a cross-validation method to obtain seven independent data sets.We then utilized five metrics to evaluate our fusion model,based on intermediate-output extracted by ResNet and SVM using the Gaussian kernel function.Our results show that the primary metric true skill statistics(TSS)achieves a value of 0.708±0.027 for≥C-class prediction,and of 0.758±0.042 for≥M-class prediction;these values indicate that our approach performs significantly better than those of previous studies.The metrics of our fusion model’s performance on the seven datasets indicate that the model is quite stable and robust,suggesting that fusion models that integrate an excellent baseline network with SVM can achieve improved performance in solar flare prediction.Besides,we also discuss the performance impact of architectural innovation in our fusion model.展开更多
In this study we review the occurrence of different types (A, B, C, M, and X classes) of solar flares during different solar cycle phases from 1996 to 2019 covering the solar cycles 23 and 24. During this period, a to...In this study we review the occurrence of different types (A, B, C, M, and X classes) of solar flares during different solar cycle phases from 1996 to 2019 covering the solar cycles 23 and 24. During this period, a total of 19,126 solar flares were observed regardless the class: 3548 flares in solar cycle 23 (SC23) and 15,668 flares in solar cycle 24 (SC24). Our findings show that the cycle 23 has observed the highest occurrences of M-class and X-class flares, whereas cycle 24 has pointed out a predominance of B-class and C-class flares throughout its different phases. The results indicate that the cycle 23 was magnetically more intense than cycle 24, leading to more powerful solar flares and more frequent geomagnetic storms, capable of generating significant electromagnetic emissions that can affect satellites and GPS signals. The decrease in intense solar flares during cycle 24 compared to cycle 23 reflects an evolution in solar activity patterns over time.展开更多
The detection of stellar flares is crucial to understanding dynamic processes at the stellar surface and their potential impact on surrounding exoplanetary systems.Extensive time series data acquired by the Transiting...The detection of stellar flares is crucial to understanding dynamic processes at the stellar surface and their potential impact on surrounding exoplanetary systems.Extensive time series data acquired by the Transiting Exoplanet Survey Satellite(TESS)offer valuable opportunities for large-scale flare studies.A variety of methods is currently employed for flare detection,with machine learning(ML)approaches demonstrating strong potential for automated classification tasks,particularly for the analysis of astronomical time series.This review provides an overview of the methods used to detect stellar flares in TESS data and evaluates their performance and effectiveness.It includes our assessment of both traditional detection techniques and more recent methods,such as ML algorithms,highlighting their strengths and limitations.By addressing current challenges and identifying promising approaches,this manuscript aims to support further studies and promote the development of stellar flare research.展开更多
Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causin...Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.展开更多
The caption of Figure 5 should be:Wind/WAVES type II burst starting around 14 MHz(∼12:05 UT,2017 September 6)and continuing down to∼100 kHz(09:00 UT,2017 September 7).The end time is marked by the short vertical lin...The caption of Figure 5 should be:Wind/WAVES type II burst starting around 14 MHz(∼12:05 UT,2017 September 6)and continuing down to∼100 kHz(09:00 UT,2017 September 7).The end time is marked by the short vertical line with its length indicating the bandwidth(70-130 kHz).The horizontal error bars signify the end time uncertainty.The vertical dashed line marks the SGRE end(06:28 UT,September 7);the horizontal dashed line represents the gamma-ray background.The shock arrival time at 1 au is labeled“SH”(Gopalswamy et al.2018).展开更多
目的比较采用毛囊单位钻取术(follicular unit excision,FUE)喇叭口针和锐针钻取毛囊的临床效果。方法回顾性分析自2024年10月至2025年5月,南方医科大学南方医院进行毛发移植49例患者的临床资料。采用FUE喇叭口针钻取毛囊的患者25例,采...目的比较采用毛囊单位钻取术(follicular unit excision,FUE)喇叭口针和锐针钻取毛囊的临床效果。方法回顾性分析自2024年10月至2025年5月,南方医科大学南方医院进行毛发移植49例患者的临床资料。采用FUE喇叭口针钻取毛囊的患者25例,采用FUE锐针钻取毛囊患者24例。通过查询每例患者供区毛囊钻取情况(包括毛囊钻取时间、毛囊钻取总量及毛囊离断率等)、随访期间供区恢复和并发症情况等,综合分析采用FUE喇叭口针和FUE锐针钻取毛囊的临床效果。结果FUE喇叭口针和FUE锐针组患者中,毛囊的平均钻取总量分别为(5380±237)根毛囊和(5540±204)根毛囊,平均钻取时间分别为(89±23)min和(93±28)min,差异均无统计学意义(P>0.05);平均离断率分别为(4.37±0.31)%和(7.02±0.39)%,差异有统计学意义(P<0.05)。FUE喇叭口针组和FUE锐针组患者供区术后恢复时间均为(3±1)d,并发症发生率差异无统计学意义(P>0.05),术后两组间毛发生长情况无明显差异。结论FUE喇叭口针钻取毛囊具有离断率较低的特点,能够减少毛囊损伤,值得临床推广。展开更多
太阳耀斑是太阳大气中最强烈的爆发现象,能够释放大量能量并产生各种波长的电磁辐射.研究太阳耀斑对于理解太阳活动、空间天气预报以及保护地球空间环境至关重要.本数据集基于夸父一号(ASO-S)卫星搭载的全日面成像仪(Solar Disk Imager,...太阳耀斑是太阳大气中最强烈的爆发现象,能够释放大量能量并产生各种波长的电磁辐射.研究太阳耀斑对于理解太阳活动、空间天气预报以及保护地球空间环境至关重要.本数据集基于夸父一号(ASO-S)卫星搭载的全日面成像仪(Solar Disk Imager, SDI)在莱曼阿尔法波段(121.6±7.5) nm采集的全日面图像数据,通过一套自主研发的太阳耀斑自动识别与关键参数提取算法,系统记录了2024年莱曼阿尔法太阳耀斑事件.该算法可有效避免宇宙线、粒子暴等事件的干扰,能够对不同强度级别的耀斑进行识别,并能对日面上同时发生的多个耀斑进行分别识别与追踪.本数据集收录了耀斑的起止时间、持续时间、发生位置、显著性等关键参数,包含耀斑识别过程记录文档、耀斑事件列表、耀斑峰值时刻快视图像和耀斑区域电影动画等数据.该数据集可为太阳物理学研究、空间天气预报以及相关领域提供重要的科学数据支持.展开更多
The accurate release of a large amount FSH and LH caused by flare-up can be used not only for controlled ovary hyperstimulation for poor responders,but also for ovulation induction of PCOS patients as well as to preve...The accurate release of a large amount FSH and LH caused by flare-up can be used not only for controlled ovary hyperstimulation for poor responders,but also for ovulation induction of PCOS patients as well as to prevent multiple follicles development,multiple gestation and ovary hyperstimulation.Details should be paid attention to while adopting the flare-up protocol,in order to take it’s advantages and avoid disadvantages.展开更多
基金The authors gratefully acknowledge the support of K.C.Wong Education Foundation.Hong Kong,the National Natural Science Foundation of China(Grant Number 51975301)the Natural Science Foundation of Zhejiang(Grant Number LZI7EO5OOO1).
文摘To realize cross-wedge rolling of shaft parts without a stub bar in a short process,an axial closed-open-type cross-wedge rolling technique was proposed.Based on the strain characteristics in the rolling,evaluation indices of deformation uniformity were provided,and the DEFORM-3D software was adopted to conduct numerical simulations of the rolling process.The metal flow and strain distribution in all stages of the rolling process were analyzed.It is shown that the strain value of the rolled piece close to the end is relatively high while the overall strain distribution is uniform in the rolling process.When the percentage reduction in area is smaller,the fluctuation range of the equivalent strain will be lower and the overall uniformity of the rolled piece will be better.A variable angle wedge was implemented to make metal flow inward and eliminate concavity.Finally,rolling experiment was performed,which indicate that the shape of the rolled piece obtained is consistent with the simulation results.Concavity value in the rolling is decreased by 92%as compared to conventional open rolling.The research results lay a theoretical basis for realizing closed-open-type cross-wedge rolling without a stub bar.
基金conducted within the framework of the project LNG-COMSHIP,Greek General Secretariat of Research and Technology Code:12CHN400,and was funded by the European Regional Development Fund(ERDF) and National Resources
文摘In this feasibility study, we investigate the viability of using Liquefied Natural Gas （LNG） fuel in an open type Ro-Ro passenger ferry and the associated potential challenges with regard to the vessel safety systems. We recommend an appropriate methodology for converting existing ships to run on LNG fuel, discuss all the necessary modifications to the ship’s safety systems, and also evaluate the relevant ship evacuation procedures. We outline the basic requirements with which the ship already complies for each safety system and analyze the additional restrictions that must be taken into consideration for the use of LNG fuel. Appropriate actions are recommended. Furthermore, we carry out a hazard identification study. Overall, we clearly demonstrate the technical feasibility of the investigated scenario. Minimal modifications to the ship’s safety systems are required to comply with existing safety rules for this specific type of ship.
基金supported by the National Key R&D Program of China (Grant No.2022YFF0503700)the National Natural Science Foundation of China (42074196, 41925018)
文摘Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model integrating Deep Residual Network(ResNet)and Support Vector Machine(SVM)for both≥C-class(C,M,and X classes)and≥M-class(M and X classes)flares.We collected samples of magnetograms from May 1,2010 to September 13,2018 from Space-weather Helioseismic and Magnetic Imager(HMI)Active Region Patches and then used a cross-validation method to obtain seven independent data sets.We then utilized five metrics to evaluate our fusion model,based on intermediate-output extracted by ResNet and SVM using the Gaussian kernel function.Our results show that the primary metric true skill statistics(TSS)achieves a value of 0.708±0.027 for≥C-class prediction,and of 0.758±0.042 for≥M-class prediction;these values indicate that our approach performs significantly better than those of previous studies.The metrics of our fusion model’s performance on the seven datasets indicate that the model is quite stable and robust,suggesting that fusion models that integrate an excellent baseline network with SVM can achieve improved performance in solar flare prediction.Besides,we also discuss the performance impact of architectural innovation in our fusion model.
文摘In this study we review the occurrence of different types (A, B, C, M, and X classes) of solar flares during different solar cycle phases from 1996 to 2019 covering the solar cycles 23 and 24. During this period, a total of 19,126 solar flares were observed regardless the class: 3548 flares in solar cycle 23 (SC23) and 15,668 flares in solar cycle 24 (SC24). Our findings show that the cycle 23 has observed the highest occurrences of M-class and X-class flares, whereas cycle 24 has pointed out a predominance of B-class and C-class flares throughout its different phases. The results indicate that the cycle 23 was magnetically more intense than cycle 24, leading to more powerful solar flares and more frequent geomagnetic storms, capable of generating significant electromagnetic emissions that can affect satellites and GPS signals. The decrease in intense solar flares during cycle 24 compared to cycle 23 reflects an evolution in solar activity patterns over time.
基金supported by the National Natural Science Foundation of China(12473104 and U2031144).
文摘The detection of stellar flares is crucial to understanding dynamic processes at the stellar surface and their potential impact on surrounding exoplanetary systems.Extensive time series data acquired by the Transiting Exoplanet Survey Satellite(TESS)offer valuable opportunities for large-scale flare studies.A variety of methods is currently employed for flare detection,with machine learning(ML)approaches demonstrating strong potential for automated classification tasks,particularly for the analysis of astronomical time series.This review provides an overview of the methods used to detect stellar flares in TESS data and evaluates their performance and effectiveness.It includes our assessment of both traditional detection techniques and more recent methods,such as ML algorithms,highlighting their strengths and limitations.By addressing current challenges and identifying promising approaches,this manuscript aims to support further studies and promote the development of stellar flare research.
基金partially supported by the National Key R&D Program of China (2022YFE0133700)the National Natural Science Foundation of China(12273007)+4 种基金the Guizhou Provincial Excellent Young Science and Technology Talent Program (YQK[2023]006)the National SKA Program of China (2020SKA0110300)the National Natural Science Foundation of China(11963003)the Guizhou Provincial Basic Research Program (Natural Science)(ZK[2022]143)the Cultivation project of Guizhou University ([2020]76).
文摘Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.
文摘The caption of Figure 5 should be:Wind/WAVES type II burst starting around 14 MHz(∼12:05 UT,2017 September 6)and continuing down to∼100 kHz(09:00 UT,2017 September 7).The end time is marked by the short vertical line with its length indicating the bandwidth(70-130 kHz).The horizontal error bars signify the end time uncertainty.The vertical dashed line marks the SGRE end(06:28 UT,September 7);the horizontal dashed line represents the gamma-ray background.The shock arrival time at 1 au is labeled“SH”(Gopalswamy et al.2018).
文摘目的比较采用毛囊单位钻取术(follicular unit excision,FUE)喇叭口针和锐针钻取毛囊的临床效果。方法回顾性分析自2024年10月至2025年5月,南方医科大学南方医院进行毛发移植49例患者的临床资料。采用FUE喇叭口针钻取毛囊的患者25例,采用FUE锐针钻取毛囊患者24例。通过查询每例患者供区毛囊钻取情况(包括毛囊钻取时间、毛囊钻取总量及毛囊离断率等)、随访期间供区恢复和并发症情况等,综合分析采用FUE喇叭口针和FUE锐针钻取毛囊的临床效果。结果FUE喇叭口针和FUE锐针组患者中,毛囊的平均钻取总量分别为(5380±237)根毛囊和(5540±204)根毛囊,平均钻取时间分别为(89±23)min和(93±28)min,差异均无统计学意义(P>0.05);平均离断率分别为(4.37±0.31)%和(7.02±0.39)%,差异有统计学意义(P<0.05)。FUE喇叭口针组和FUE锐针组患者供区术后恢复时间均为(3±1)d,并发症发生率差异无统计学意义(P>0.05),术后两组间毛发生长情况无明显差异。结论FUE喇叭口针钻取毛囊具有离断率较低的特点,能够减少毛囊损伤,值得临床推广。
文摘太阳耀斑是太阳大气中最强烈的爆发现象,能够释放大量能量并产生各种波长的电磁辐射.研究太阳耀斑对于理解太阳活动、空间天气预报以及保护地球空间环境至关重要.本数据集基于夸父一号(ASO-S)卫星搭载的全日面成像仪(Solar Disk Imager, SDI)在莱曼阿尔法波段(121.6±7.5) nm采集的全日面图像数据,通过一套自主研发的太阳耀斑自动识别与关键参数提取算法,系统记录了2024年莱曼阿尔法太阳耀斑事件.该算法可有效避免宇宙线、粒子暴等事件的干扰,能够对不同强度级别的耀斑进行识别,并能对日面上同时发生的多个耀斑进行分别识别与追踪.本数据集收录了耀斑的起止时间、持续时间、发生位置、显著性等关键参数,包含耀斑识别过程记录文档、耀斑事件列表、耀斑峰值时刻快视图像和耀斑区域电影动画等数据.该数据集可为太阳物理学研究、空间天气预报以及相关领域提供重要的科学数据支持.
文摘The accurate release of a large amount FSH and LH caused by flare-up can be used not only for controlled ovary hyperstimulation for poor responders,but also for ovulation induction of PCOS patients as well as to prevent multiple follicles development,multiple gestation and ovary hyperstimulation.Details should be paid attention to while adopting the flare-up protocol,in order to take it’s advantages and avoid disadvantages.
