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A comparison of atmospheric CO_2 concentration GOSAT-based observations and model simulations

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Science China Earth Sciences 2014年第1期57卷 1393-1402页

作者： LEI LiPing GUAN XianHua zeng zhaocheng ZHANG Bing RU Fei BU Ran Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital EarthChinese Academy of Sciences

Satellite observations of atmospheric CO2 are able to truly capture the variation of global and regional CO2 *** model simulations based on atmospheric transport models can also assess variations of atmospheric CO2 concentrations in a continuous space and time,which is one of approaches for qualitatively and quantitatively studying the atmospheric transport mechanism and spatio-temporal variation of atmospheric CO2 in a global *** observations and model simulations of CO2 offer us two different approaches to understand the atmospheric ***,the difference between them has not been comprehensively compared and assessed for revealing the global and regional features of atmospheric *** this study,we compared and assessed the spatio-temporal variation of atmospheric CO2 using two datasets of the column-averaged dry air mole fractions of atmospheric CO2(XCO2)in a year from June 2009 to May 2010,respectively from GOSAT retrievals(***)and from Goddard Earth Observing System-Chemistry(GEOS-Chem),which is a global 3-D chemistry transport *** addition to the global comparison,we further compared and analyzed the difference of CO2 between the China land region and the United States(US)land region from two datasets,and demonstrated the reasonability and uncertainty of satellite observations and model *** results show that the XCO2 retrieved from GOSAT is globally lower than GEOS-Chem model simulation by 2 ppm on average,which is close to the validation conclusion for GOSAT by ground *** difference of XCO2 between the two datasets,however,changes with the different *** China land region,the difference is large,from 0.6 to 5.6 ppm,whereas it is 1.6 to 3.7 ppm in the global land region and 1.4 to 2.7 ppm in the US land *** goodness of fit test between the two datasets is 0.81 in the US land region,which is higher than that in the global land region(0.67)and China land region(0.68).The analysis results f

关键词： GOSAT GEOS-Chem atmospheric CO2 concentration inconsistency regional comparison

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沙尘气溶胶散射效应对大气二氧化碳卫星遥感反演误差的影响分析

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遥感学报 2024年第10期28卷 2582-2599页

作者：华健聪曾招城北京大学地球与空间科学学院遥感与地理信息系统研究所北京100871

二氧化碳(CO_(2))是一种重要的温室气体,利用卫星遥感可实现全球大气CO_(2)的持续大范围监测,对于制定减排策略应对全球气候变暖具有重要意义。大气中的气溶胶散射效应是制约卫星高精度CO_(2)反演的主要因素。现有研究表明,在地表反照... 详细信息

二氧化碳(CO_(2))是一种重要的温室气体,利用卫星遥感可实现全球大气CO_(2)的持续大范围监测,对于制定减排策略应对全球气候变暖具有重要意义。大气中的气溶胶散射效应是制约卫星高精度CO_(2)反演的主要因素。现有研究表明,在地表反照率较高的地区,例如沙漠地区,卫星反演的CO_(2)大气柱平均干燥空气混合比(XCO_(2))比真实值普遍偏高,偏差程度可达到满足实际应用需求所允许误差的50%。然而目前学界对此还缺乏足够的理解和定量分析。围绕这一难点问题,本文应用精准的大气辐射传输模型和基于最优化估计的XCO_(2)全物理反演算法,分析和量化沙漠地区沙尘气溶胶散射效应所导致的XCO_(2)反演误差。本研究从气溶胶的3个重要特征变量出发,包括气溶胶光学厚度(AOD)、气溶胶层高(ALH)和单次散射反照率(SSA),解析沙尘气溶胶散射效应导致XCO_(2)卫星反演结果偏差的物理机制。研究结果表明卫星反演算法中低估沙尘气溶胶的AOD、低估ALH或高估SSA是沙漠地区XCO_(2)出现高估的可能原因。具体表现为:(1)在反演算法不考虑气溶胶的情况下,若实际AOD大于1.0,将导致XCO_(2)反演结果高估超过1%;(2)当AOD低估0.3至0.5时,XCO_(2)的反演结果将高估0.15%至1.28%;(3)当ALH低估超过0.6 km时,XCO_(2)将高估超过1%;(4)在高估单次散射反照率(SSA)的情况下,XCO_(2)反演结果偏高,但高估不超过0.15%。由本文的模拟实验可知,精准的气溶胶信息对于实现高精度的XCO_(2)反演极为关键。本文还探究了沙漠地区可能发生的“临界反照率”效应对反演结果的影响,并指出此效应可能是高亮地表中CO_(2)探测卫星无法同时量化气溶胶信息的根源。本文提出,为了解决这一难题,实际反演中需要综合气溶胶探测仪器的观测数据对气溶胶信息进行进一步约束以提高XCO_(2)的反演精度。本文结论可为未来卫星反演算法的改进提供参考依据。

关键词：沙尘气溶胶二氧化碳卫星遥感反演算法散射效应辐射传输模型

大气CO_2浓度时空变化卫星遥感监测的应用潜力分析

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遥感学报 2015年第1期19卷 34-45页

作者：布然雷莉萍郭丽洁刘达曾招城中国科学院遥感与数字地球研究所数字地球重点实验室北京100094 西安科技大学陕西西安710054 中国科学院大学北京100049 香港中文大学太空与地球信息科学研究所中国香港999077

GOSAT卫星观测反演大气CO2浓度精度已经提高到了1—2 ppm,而卫星数据能否准确地揭示全球和区域大气CO2浓度变化特征还缺乏充分的评价与分析。本文针对已经连续运行观测3年的GOSAT卫星,收集了来自美国NASA-OCO团队(ACOS)和日本环境研究所... 详细信息

GOSAT卫星观测反演大气CO2浓度精度已经提高到了1—2 ppm,而卫星数据能否准确地揭示全球和区域大气CO2浓度变化特征还缺乏充分的评价与分析。本文针对已经连续运行观测3年的GOSAT卫星,收集了来自美国NASA-OCO团队(ACOS)和日本环境研究所GOSAT团队(NIES)基于各自算法反演的两套大气CO2柱浓度数据,描述并分析了全球大气CO2时空变化特征。分析结果表明,从XCO2反演的绝对值结果来看ACOS总体上比NIES的高出约2 ppm左右,但从时空的相对变化上它们揭示了相近的大气CO2浓度时空变化特征。两套数据显示出全球平均大气CO2浓度在2010年—2012年的3年期间年增量分别为1.8 ppm和2.0 ppm;季节变化幅度,北半球最大4—6 ppm,南半球最大约2 ppm,这与地面观测结果基本一致。进一步将EDGAR 4.2人为排放总量格网化数据与GOSAT卫星观测反演的CO2浓度进行相关统计分析,结果指出两套数据对人为排放量有着微弱的响应。本文结果指出目前GOSAT卫星观测反演的XCO2可以检测出全球和区域大气CO2浓度的年变化、季节变化和区域空间变化的特征;GOSAT卫星10.5 km空间分辨率的观测虽难于检测出点源的浓度变化,但从区域上对人为排放的累积效应的监测显示了一定的应用潜力。

关键词： GOSAT 大气CO2浓度时空变化人为排放

不同卫星反演的大气CO_2浓度差异时空特征分析

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中国科学院大学学报（中英文） 2019年第3期36卷 331-337页

作者：吴长江雷莉萍曾招城中国科学院遥感与数字地球研究所数字地球重点实验室北京100094 中国科学院大学资源与环境学院北京100049 美国加州理工学院地质与行星科学系

定量化分析不同遥感观测卫星所反演的大气CO_2浓度之间的差异,对于利用卫星遥感数据准确揭示全球大气CO_2浓度的时空变化特征具有重要的参考价值。利用CarbonTracker模型模拟的大气CO_2廓线数据对SCIAMACHY、GOSAT和OCO-2卫星反演的大气... 详细信息

定量化分析不同遥感观测卫星所反演的大气CO_2浓度之间的差异,对于利用卫星遥感数据准确揭示全球大气CO_2浓度的时空变化特征具有重要的参考价值。利用CarbonTracker模型模拟的大气CO_2廓线数据对SCIAMACHY、GOSAT和OCO-2卫星反演的大气CO_2柱浓度数据进行校正,并通过计算卫星校正前后的差值分析不同卫星观测平台对大气廓线的响应差异。同时比较分析不同时空尺度的各卫星观测所刻画的大气CO_2柱浓度变化的差异。实验结果表明,SCIAMACHY的差值明显大于其他2颗卫星,且在低纬度和高纬度区域分别显示(-0.25±0.15)×10^(-6)和(-0.38±0.25)×10^(-6)的浓度差异。消除这些差异后,3颗卫星的CO_2柱浓度观测数据显示相似的季节变化、年变化特征以及相似的空间分布规律。研究结果表明,模型模拟数据可用来整合这3颗卫星由于观测仪器响应和时空尺度不同所引起的大气CO_2柱浓度数据间的差异。

关键词：大气CO2浓度 SCIAMACHY GOSAT OCO-2 模型模拟

Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

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Neural Regeneration Research 2025年第1期20卷 159-173页

作者： Man Han Deyang zeng Wei Tan Xingxing Chen Shuyuan Bai Qiong Wu Yushan Chen Zhen Wei Yufei Mei Yan zeng Brain Science and Advanced Technology Institute Wuhan University of Science and TechnologyWuhanHubei ProvinceChina Geriatric Hospital Affiliated to Wuhan University of Science and Technology WuhanHubei ProvinceChina School of Public Health Wuhan University of Science and TechnologyWuhanHubei ProvinceChina

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral *** studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and *** how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress *** this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of *** focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine *** determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic ***,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

关键词： amygdala chronic mild stress chronic social defeat stress corticolimbic system depression hippocampus medial prefrontal cortex nucleus accumbens social stress models ventral tegmental area

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深度学习赋能波束管理:现状、挑战与机遇

中山大学学报（自然科学版）（中英文） 2025年第1期64卷 40-50页

作者：王昭诚马可清华大学电子工程系北京100084

随着载波频率的不断提高和大规模天线阵列的广泛部署,基于模拟移相器的波束赋形成为下一代无线通信的标志性技术之一。此时,波束管理被用于获取和维护基站和用户端具有最大接收功率的最优波束对,以保障可靠的无线通信服务。传统波束管... 详细信息

随着载波频率的不断提高和大规模天线阵列的广泛部署,基于模拟移相器的波束赋形成为下一代无线通信的标志性技术之一。此时,波束管理被用于获取和维护基站和用户端具有最大接收功率的最优波束对,以保障可靠的无线通信服务。传统波束管理方法往往依赖于海量搜索。同时,传统数学模型无法全面的、准确刻画非线性的波束的内在关联和高维无线环境特征,因而难以取得令人满意的波束增益性能。近年来,得益于深度学习强大的自适应拟合能力,深度学习赋能波束管理得到了国内外广泛关注。本文总结了深度学习赋能波束管理的研究进展,并展望了未来的研究方向。首先,阐述了深度学习应用于波束管理的典型场景和潜在优势;随后,从空/时/频域切入,讨论当前深度学习赋能波束管理的主要研究路线和代表性工作;最后,面向更大规模的无线网络、更多元的波束管理功能和更鲁棒的深度学习模型,阐述未来的研究挑战与机遇。

关键词：深度学习波束管理空域时域频域

Glucocorticoid receptor signaling in the brain and its involvement in cognitive function

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Neural Regeneration Research 2025年第9期20卷 2520-2537页

作者： Chonglin Su Taiqi Huang Meiyu Zhang Yanyu Zhang Yan zeng Xingxing Chen Brain Science and Advanced Technology Institute Hubei Province Key Laboratory of Occupational Hazard Identification and ControlSchool of MedicineWuhan University of Science and TechnologyWuhanHubei ProvinceChina

The hypothalamic-pituitary-adrenal axis regulates the secretion of glucoco rticoids in response to environmental *** the brain,a nuclear receptor transcription fa ctor,the glucocorticoid recepto r,is an important component of the hypothalamicpituitary-a d renal axis's negative feedback loop and plays a key role in regulating cognitive equilibrium and *** glucoco rticoid receptor influences cognitive processes,including glutamate neurotransmission,calcium signaling,and the activation of brain-derived neurotrophic factor-mediated pathways,through a combination of genomic and non-genomic *** interactions within the central nervous system can alter the expression and activity of the glucocorticoid receptor,there by affecting the hypothalamic-pituitary-a d renal axis and stress-related cognitive *** appropriate level of glucocorticoid receptor expression can improve cognitive function,while excessive glucocorticoid receptors or long-term exposure to glucoco rticoids may lead to cognitive *** with cognitive impairment-associated diseases,such as Alzheimer's disease,aging,depression,Parkinson's disease,Huntington's disease,stroke,and addiction,often present with dysregulation of the hypothalamic-pituitary-adrenal axis and glucocorticoid receptor *** review provides a comprehensive overview of the functions of the glucoco rticoid receptor in the hypothalamic-pituitary-a d renal axis and cognitive *** emphasizes that appropriate glucocorticoid receptor signaling fa cilitates learning and memory,while its dysregulation can lead to cognitive *** provides clues about how glucocorticoid receptor signaling can be targeted to ove rcome cognitive disability-related disorders.

关键词： brain-derived neurotrophic factor calcium signaling glucocorticoid receptor glucocorticoid glutamate transmission hypothalamic-pituitary-adrenal axis long-term potentiation neurocognitive disorders neuroplasticity stress

人为排放所引起大气CO_2浓度变化的卫星遥感观测评估

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科学通报 2017年第25期62卷 2941-2950页

作者：雷莉萍钟惠贺忠华蔡博峰杨绍源吴长江曾招城刘良云张兵中国科学院遥感与数字地球研究所数字地球重点实验室北京100094 中国科学院大学资源与环境学院北京100049 中国环境保护部环境规划院气候变化与环境政策研究中心北京100012 Division of Geological and Planetary Sciences California Institute of Technology

人为排放是引起大气CO_2浓度升高的主要原因,由大气CO_2卫星遥感观测获取全球和区域大气CO_2浓度的变化已被认为是评估区域人为排放的有效手段之一.为了深入定量分析区域人为碳排放对大气CO_2浓度变化的贡献,本研究利用由温室气体观测卫... 详细信息

人为排放是引起大气CO_2浓度升高的主要原因,由大气CO_2卫星遥感观测获取全球和区域大气CO_2浓度的变化已被认为是评估区域人为排放的有效手段之一.为了深入定量分析区域人为碳排放对大气CO_2浓度变化的贡献,本研究利用由温室气体观测卫星(GOSAT)获取的近5年(2010~2014年)大气CO_2柱浓度数据,以同纬度带高人为排放区域的中国京津冀和美国东部城市密集区为研究对象区,结合位温气象数据和人为碳排放清单数据圈定出对比背景区,通过分析比较人为排放区与背景区的CO_2浓度差值,评估人为排放对大气CO_2浓度增量变化的影响.分析结果显示,近5年中国京津冀和美国东部城市密集区的大气CO_2浓度比背景区分别显示平均1.8和2.0 ppm的升高;且冬季均高于其他季节,分别为2.4±0.6和2.8±0.8 ppm.进一步分析月变化特征时发现中国京津冀地区2014年11月亚太经合组织会议(APEC)期间大气CO_2浓度异常低于前期3.2 ppm,反映了会议期间政府实施的减排控制效果.论文研究结果表明CO_2卫星观测能够从区域大气CO_2浓度的变化定量评估人为排放的影响,作为有效手段之一辅助于区域人为排放控制效果的评估.

关键词：人为排放大气CO2浓度温室气体观测卫星(GOSAT) 区域对比

Advances in genotypic antimicrobialresistance testing: a comprehensive review

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Science China Life Sciences 2025年第01期 130-143页

作者： Boheng Duan Xianjun zeng Junping Peng Huan Kui College of Nanchang University Department of Imaging The Second Affiliated Hospital of Nanchang University NHC Key Laboratory of Systems Biology of Pathogens National Institute of Pathogen BiologyChinese Academy of Medical Sciences & Peking Union Medical College Key Laboratory of Respiratory Disease Pathogenomics Chinese Academy of Medical Sciences & Peking Union Medical College Key Laboratory of Pathogen Infection Prevention and Control (Ministry of Education) State Key Laboratory of Respiratory Health and MultimorbidityNational Institute of Pathogen BiologyChinese Academy of Medical Sciences & Peking Union Medical College

Antimicrobial resistance(AMR) represents a substantial threat to global public health, complicating the treatment of common infections and leading to prolonged illness and escalated healthcare expenses. To effectively combat AMR, timely and accurate detection is crucial for AMR surveillance and individual-based therapy. Phenotypic antibiotic resistance testing(AST) has long been considered the gold standard in clinical applications, serving as the foundation for clinical AMR diagnosis and optimized therapy. It has significantly contributed to ensuring patients′ health and the development of novel antimicrobials. Despite advancements in automated culture-based AST technologies,inherent limitations impede the widespread use of phenotypic AST in AMR surveillance. Genotypic AST technologies offer a promising alternative option, exhibiting advantages of rapidity, high sensitivity, and specificity. With the continuous advancement and expanding applications of genotypic AST technologies, such as microfluidics, mass spectrometry, and high-resolution melting curve analysis, new vigor has been injected into the development and clinical implementation of genotypic AST technologies. In this narrative review, we discuss the principles, applications, and advancements of emerging genotypic AST methods in clinical settings. The comprehensive review aims to highlight the significant scientific potential of emerging genotypic AST technologies in clinical AMR diagnosis, providing insights to enhance existing methods and explore novel approaches.

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