目的量化关于心脏手术体外循环目标导向灌注(GDP)相关学术论文的基本信息,探索关于GDP研究领域的研究热点、趋势及最具有影响力的论文,为研究人员及临床工作者提供参考。方法利用科学网(Web of Science)检索GDP相关文献,使用R语言数据包...目的量化关于心脏手术体外循环目标导向灌注(GDP)相关学术论文的基本信息,探索关于GDP研究领域的研究热点、趋势及最具有影响力的论文,为研究人员及临床工作者提供参考。方法利用科学网(Web of Science)检索GDP相关文献,使用R语言数据包Bibliometrix对文献的发表年代、期刊来源及期刊所属国家、高频关键词的分布情况进行统计分析,并进行聚类分析,得到该GDP研究领域关注热点。结果筛选出GDP相关文献116篇,获得该领域研究热度趋势、来源期刊分布、各国研究热度等数据资料。高频关键词共计15个,通过对高频关键词进行聚类分析,得到3个主要研究热点方向。关于GDP研究领域的热点有氧供指数、氧耗监测、组织灌注监测等。结论GDP研究热点主要为GDP研究内容和技术、对象、临床结局。基于文献计量学的研究方法,本研究提供较为全面的关于GDP研究领域发展的分析总结,未来该领域的氧供与氧耗监测与调控仍可能是热门研究方向。展开更多
原始采集的医学图像普遍存在对比度不足、细节模糊以及噪声干扰等质量问题,使得现有医学图像分割技术的精度很难达到新的突破。针对医学图像数据增强技术进行研究,在不明显改变图像外观的前提下,通过添加特定的像素补偿和进行细微的图...原始采集的医学图像普遍存在对比度不足、细节模糊以及噪声干扰等质量问题,使得现有医学图像分割技术的精度很难达到新的突破。针对医学图像数据增强技术进行研究,在不明显改变图像外观的前提下,通过添加特定的像素补偿和进行细微的图像调整来改善原始图像质量问题,从而提高图像分割准确率。首先,设计引入了一个新的优化器模块,以产生一个连续分布的空间作为迁移的目标域,该优化器模块接受数据集的标签作为输入,并将离散的标签数据映射到连续分布的医学图像中;其次,提出了一个基于对抗生成网络的EnGAN模型,并将优化器模块产生的迁移目标域用来指导对抗网络的目标生成,从而将改善的医学图像质量知识植入模型中实现图像增强。基于COVID-19数据集,实验中使用U-Net、U-Net+ResNet34、U-Net+Attn Res U-Net等卷积神经网络作为骨干网络,Dice系数和交并比分别达到了73.5%和69.3%、75.1%和70.5%,以及75.2%和70.3%。实验的结果表明,提出的医学图像质量增强技术在最大限度保留原始特征的条件下,有效地提高了分割的准确率,为后续的医学图像处理研究提供了一个更为稳健和高效的解决方案。展开更多
目的利用文献计量学方法分析量化小儿心脏术后急性肾损伤(CS-AKI)的研究现状、热点及前沿,为临床工作者和相关研究人员提供参考。方法利用Web of Science检索2005~2024年间小儿CS-AKI相关文献,利用R语言数据包Bibliometrix对文献发表年...目的利用文献计量学方法分析量化小儿心脏术后急性肾损伤(CS-AKI)的研究现状、热点及前沿,为临床工作者和相关研究人员提供参考。方法利用Web of Science检索2005~2024年间小儿CS-AKI相关文献,利用R语言数据包Bibliometrix对文献发表年代、期刊、作者及关键词等进行可视化分析。结果筛选出小儿CS-AKI相关文献558篇,发文量呈逐年上升趋势。发文量前三的期刊为Pediatric Critical Care Medicine、Pediatric Nephrology、Pediatric Cardiology。全球小儿CS-AKI的作者中,Devarajan P、Goldstein SL、Zappitelli M为重要核心作者,且美国生产力最高。高频关键词为小儿CS-AKI的危险因素、病因及发病机制、预后、预测因子及防治措施。结论小儿CS-AKI近年来逐渐被重视,研究热点主要为CS-AKI的危险因素与预后、病因与发病机制及防治措施。未来该领域的预测指标与保护措施仍可能是热门研究方向。展开更多
By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-grow...By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.展开更多
The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking th...The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking the Shuipingzi 1#landslide that occurred in the Baihetan Reservoir area of the Jinsha River in China as an engineering example,this study established a large-scale physical model(with dimensions of 30 m×29 m×3.5 m at a scale of 1:150)and conducted scaled experiments on 3D landslide-induced impulse waves.During the process in which a sliding mass displaced and compressed a body of water to generate waves,the maximum initial wave amplitude was found to be positively correlated with the sliding velocity and the volume of the landslide.With the increase in the water depth,the wave amplitude initially increased and then decreased.The duration of pressure exertion by the sliding mass at its maximum velocity directly correlated with an elevated wave amplitude.Based on the theories of low-amplitude waves and energy conservation,while considering the energy conversion efficiency,a predictive model for the initial wave amplitude was derived.This model could fit and validate the functions of wavelength and wave velocity.The accuracy of the initial wave amplitude was verified using physical experiment data,with a prediction accuracy for the maximum initial wave amplitude reaching 90%.The conversion efficiency(η)directly determined the accuracy of the estimation formula.Under clear conditions for landslide-induced impulse wave generation,estimating the value ofηthrough analogy cases was feasible.This study has derived the landslide-induced impulse waves amplitude prediction formula from the standpoints of wave theory and energy conservation,with greater consideration given to the intrinsic characteristics in the formation process of landslide-induced impulse waves,thereby enhancing the applicability and extensibility of the formula.This can facilitate the development of empirical estimation methods for landslide-induced impulse waves toward universality.展开更多
文摘目的量化关于心脏手术体外循环目标导向灌注(GDP)相关学术论文的基本信息,探索关于GDP研究领域的研究热点、趋势及最具有影响力的论文,为研究人员及临床工作者提供参考。方法利用科学网(Web of Science)检索GDP相关文献,使用R语言数据包Bibliometrix对文献的发表年代、期刊来源及期刊所属国家、高频关键词的分布情况进行统计分析,并进行聚类分析,得到该GDP研究领域关注热点。结果筛选出GDP相关文献116篇,获得该领域研究热度趋势、来源期刊分布、各国研究热度等数据资料。高频关键词共计15个,通过对高频关键词进行聚类分析,得到3个主要研究热点方向。关于GDP研究领域的热点有氧供指数、氧耗监测、组织灌注监测等。结论GDP研究热点主要为GDP研究内容和技术、对象、临床结局。基于文献计量学的研究方法,本研究提供较为全面的关于GDP研究领域发展的分析总结,未来该领域的氧供与氧耗监测与调控仍可能是热门研究方向。
文摘原始采集的医学图像普遍存在对比度不足、细节模糊以及噪声干扰等质量问题,使得现有医学图像分割技术的精度很难达到新的突破。针对医学图像数据增强技术进行研究,在不明显改变图像外观的前提下,通过添加特定的像素补偿和进行细微的图像调整来改善原始图像质量问题,从而提高图像分割准确率。首先,设计引入了一个新的优化器模块,以产生一个连续分布的空间作为迁移的目标域,该优化器模块接受数据集的标签作为输入,并将离散的标签数据映射到连续分布的医学图像中;其次,提出了一个基于对抗生成网络的EnGAN模型,并将优化器模块产生的迁移目标域用来指导对抗网络的目标生成,从而将改善的医学图像质量知识植入模型中实现图像增强。基于COVID-19数据集,实验中使用U-Net、U-Net+ResNet34、U-Net+Attn Res U-Net等卷积神经网络作为骨干网络,Dice系数和交并比分别达到了73.5%和69.3%、75.1%和70.5%,以及75.2%和70.3%。实验的结果表明,提出的医学图像质量增强技术在最大限度保留原始特征的条件下,有效地提高了分割的准确率,为后续的医学图像处理研究提供了一个更为稳健和高效的解决方案。
基金supported in part by the National Natural Science Foundation of China under Grant 62171465,62072303,62272223,U22A2031。
文摘By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.
基金The authors would like thank LI Renjiang and HU Bin from the China Three Gorges Corporation for providing many valuable suggestions for the establishment of the physical models.This work was supported by the National Natural Science Foundation of China(No.U23A2045)the China Three Gorges Corporation(YM(BHT)/(22)022)the Scientific Research Project of Chongqing Municipal Bureau of Planning and Natural Resources(Evaluation and Reinforcement Technology of Surge Disaster Caused by High and Steep Dangerous Rocks in Chongqing Reservoir Area of the Three Gorges Project,KJ-2023046).
文摘The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking the Shuipingzi 1#landslide that occurred in the Baihetan Reservoir area of the Jinsha River in China as an engineering example,this study established a large-scale physical model(with dimensions of 30 m×29 m×3.5 m at a scale of 1:150)and conducted scaled experiments on 3D landslide-induced impulse waves.During the process in which a sliding mass displaced and compressed a body of water to generate waves,the maximum initial wave amplitude was found to be positively correlated with the sliding velocity and the volume of the landslide.With the increase in the water depth,the wave amplitude initially increased and then decreased.The duration of pressure exertion by the sliding mass at its maximum velocity directly correlated with an elevated wave amplitude.Based on the theories of low-amplitude waves and energy conservation,while considering the energy conversion efficiency,a predictive model for the initial wave amplitude was derived.This model could fit and validate the functions of wavelength and wave velocity.The accuracy of the initial wave amplitude was verified using physical experiment data,with a prediction accuracy for the maximum initial wave amplitude reaching 90%.The conversion efficiency(η)directly determined the accuracy of the estimation formula.Under clear conditions for landslide-induced impulse wave generation,estimating the value ofηthrough analogy cases was feasible.This study has derived the landslide-induced impulse waves amplitude prediction formula from the standpoints of wave theory and energy conservation,with greater consideration given to the intrinsic characteristics in the formation process of landslide-induced impulse waves,thereby enhancing the applicability and extensibility of the formula.This can facilitate the development of empirical estimation methods for landslide-induced impulse waves toward universality.
