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长三角地区工业细分行业碳效率评价及其影响因素分析

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全球能源互联网 2024年第1期7卷 101-113页

作者：卢峰徐俊甘超李若男赵晓丽国网浙江省电力有限公司湖州供电公司浙江省湖州市313000 中国人寿保险股份有限公司湖南省分公司湖南省长沙市410011 中国石油大学(北京)经济管理学院北京市昌平区102249

由浙江、江苏、安徽和上海组成的长三角地区是国内经济发展高地,同时也是高碳排放区域。研究长三角地区细分行业碳效率特征及其影响因素,不仅对这一地区实现低碳发展目标具有重要意义,也对全国其他地区未来低碳发展具有较为重要的指导... 详细信息

由浙江、江苏、安徽和上海组成的长三角地区是国内经济发展高地,同时也是高碳排放区域。研究长三角地区细分行业碳效率特征及其影响因素,不仅对这一地区实现低碳发展目标具有重要意义,也对全国其他地区未来低碳发展具有较为重要的指导意义。利用固定效应随机前沿模型对2014至2019年三省一市37个行业进行了碳效率测算,并对各地区工业碳效率动态变化进行了分析;然后,基于随机前沿模型方法对碳效率影响因素进行了探究;最后,应用不同生产函数形式和去极端值的方式验证了本模型的稳健性。研究结果表明,长三角地区三省一市的高碳效率行业存在明显差异,且主要受行业专业化程度以及环境规制强度的影响,国有资产占比对碳效率的影响在安徽省显著。此外,提高专业化程度是持续推动碳效率水平提高的关键性因素,环境规制能快速推动部分行业提高碳效率,但是无法推动地区工业碳效率的长期进步。

关键词：长三角地区碳效率工业细分行业固定效应随机前沿模型

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DPABINet:脑网络和图论分析工具箱

Science Bulletin 2024年第11期69卷 1628-1631页

作者：严超赣王鑫迪鲁彬邓昭宇高青林 CAS Key Laboratory of Behavioral Science Institute of PsychologyBeijing 100101China Department of Psychology University of Chinese Academy of SciencesBeijing 100101China International Big-Data Center for Depression Research Institute of PsychologyChinese Academy of SciencesBeijing 100101China Magnetic Resonance Imaging Research Center Institute of PsychologyChinese Academy of SciencesBeijing 100101China McGill Centre for Integrative Neuroscience Montreal Neurological InstituteMcGill UniversityMontréal H3A 2B4Canada

The human brain, a marvel of intricate connections, functions as a complex network comprising structurally and functionally integrated regions. This network orchestrates a multitude of complex patterns through high-le... 详细信息

关键词：图论分析脑网络工具箱

大洋钻探过程钻速在线区间预测方法——以微型钻探船室内模拟实验为例

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钻探工程 2024年第5期51卷 45-52页

作者：张琦甘超曹卫华中国地质大学(武汉)自动化学院湖北武汉430074 复杂系统先进控制与智能自动化湖北省重点实验室湖北武汉430074 地球探测智能化技术教育部工程研究中心湖北武汉430074

大洋钻探是从事海洋能源资源勘探开发和地壳构造演化研究的主要手段,常面临复杂海况扰动大、海底地层不确定性强等问题。本文提出一种大洋钻探过程钻速在线区间预测方法,以微型钻探船室内模拟实验为例开展方法的验证工作,为工程化应用... 详细信息

大洋钻探是从事海洋能源资源勘探开发和地壳构造演化研究的主要手段,常面临复杂海况扰动大、海底地层不确定性强等问题。本文提出一种大洋钻探过程钻速在线区间预测方法,以微型钻探船室内模拟实验为例开展方法的验证工作,为工程化应用奠定重要基础。首先,运用数据重采样、数据时深匹配、数据滤波等方法对多源大洋钻探数据进行预处理。其次,引入极限学习机、粒子群优化等方法建立钻速点预测模型。再者,利用非参数估计方法构造置信区间,建立钻速区间预测模型,并开展钻速区间预测。最后,通过滑动窗口方法在线更新区间预测模型参数,实现模型的在线学习和优化。微型钻探船室内模拟实验的对比结果验证了所提方法具有很强的钻速预测能力和鲁棒性,为大洋钻探过程钻速优化控制提供了新的工程解决方案。

关键词：大洋钻探过程钻速区间预测室内模拟实验在线学习误差分析

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众脑之力:通过开放神经影像数据和大规模协作催化神经精神疾病的创新发现

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Science Bulletin 2024年第10期69卷 1536-1555页

作者：鲁彬陈骁 Francisco Xavier Castellanos Paul M.Thompson 左西年臧玉峰严超赣 CAS Key Laboratory of Behavioral Science Institute of PsychologyBeijing 100101China Department of Psychology University of Chinese Academy of SciencesBeijing 100101China Department of Child and Adolescent Psychiatry NYU Grossman School of MedicineNew York 10016USA d Nathan Kline Institute for Psychiatric Research Orangeburg 10962USA Imaging Genetics Center Mark&Mary Stevens Institute for Neuroimaging&InformaticsKeck School of MedicineUniversity of Southern CaliforniaLos Angeles 90033USA Developmental Population Neuroscience Research Center IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijing 100875China National Basic Science Data Center Beijing 100190China Centre for Cognition and Brain Disorders The Affiliated Hospital of Hangzhou Normal UniversityHangzhou 310004China Institute of Psychological Science Hangzhou Normal UniversityHangzhou 310030China Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairment Hangzhou 311121China International Big-Data Center for Depression Research Institute of PsychologyChinese Academy of SciencesBeijing 100101China Magnetic Resonance Imaging Research Center Institute of PsychologyChinese Academy of SciencesBeijing 100101China

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric *** pooling images from various cohorts,statistical power has increased,enabling the detection of subtle abnormalities and robust associations,and fostering new research *** collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted ***-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric *** also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric ***,challenges such as data harmonization across different sites,privacy protection,and effective data sharing must be *** proper governance and open science practices,we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis,treatment selection,and outcome prediction,contributing to optimal brain health.

关键词： Magnetic resonance imaging Neuropsychiatric disorders Big data Open science Artificial intelligence

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2型糖尿病肾脏病与TMAO的相关性研究

中国临床药理学与治疗学 2024年第6期29卷 661-670页

作者：王梦珂甘超袁玥邹婧怡王珍李淑云吕海宏兰州大学第一临床医学院甘肃兰州730000 兰州大学第一医院检验科甘肃兰州730000 兰州大学第一医院内分泌科甘肃兰州730000

目的:探讨氧化三甲胺(trimethylamine-N-oxide,TMAO)与2型糖尿病肾脏病(diabetic kid-neydisease,DKD)的相关性,为2型糖尿病肾脏病的临床早期诊断提供新的思路。方法:选取2023年1月至2023年5月兰州大学第一医院内分泌科住院的2型糖尿病... 详细信息

目的:探讨氧化三甲胺(trimethylamine-N-oxide,TMAO)与2型糖尿病肾脏病(diabetic kid-neydisease,DKD)的相关性,为2型糖尿病肾脏病的临床早期诊断提供新的思路。方法:选取2023年1月至2023年5月兰州大学第一医院内分泌科住院的2型糖尿病患者246例,将其分为糖尿病肾脏病组(DKD组)及非糖尿病肾脏病组(NDKD组),根据尿白蛋白/肌酐比(UACR)分为A1、A2、A3亚组,根据肾小球滤过率(eGFR)分为G1、G2、G3、G4-5亚组,并依据肾脏病改善全球预后组织(KDIGO)指南进行糖尿病肾脏病进展风险评估(低、中、高或极高风险)。收集患者的临床资料,通过酶联免疫法检测血TMAO水平,通过SPSS25.0软件进行统计学分析。结果:T2DM患者TMAO水平与UACR呈正相关(r=0.515,P<0.001),与eGFR呈负相关(r=-0.409,P<0.001)。高水平TMAO是DKD的独立危险因素,TMAO预测DKD最佳切点为5.37µmol/L,曲线下面积为0.745,特异性为58.3%,敏感性为83.8%。结论:TMAO与DKD发生发展密切相关,其对DKD具有一定的临床预测价值,TMAO可能成为糖尿病肾脏病早期诊断及治疗的潜在靶点。

关键词：氧化三甲胺 2型糖尿病糖尿病肾病肠道菌群代谢产物尿微量白蛋白

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Altered cerebral activities and functional connectivity in depression:a systematic review of fMRI studies

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Quantitative Biology 2022年第4期10卷 366-380页

作者： Xue-Ying Li Xiao Chen chao-gan Yan CAS Key Laboratory of Behavioral Science Institute of PsychologyBeijing 100101China Sino-Danish College University of Chinese Academy of SciencesBeijing 101400China Sino-Danish Center for Education and Research Beijing 101400China CFIN and PET Center Aarhus UniversityNørrebrogade 448000 AarhusDenmark Magnetic Resonance Imaging Research Center Institute of PsychologyChinese Academy of SciencesBeijing 100101China International Big-Data Center for Depression Research Chinese Academy of SciencesBeijing 100101China Department of Psychology University of Chinese Academy of SciencesBeijing 100049China

Background:As one of the leading causes of global disability,major depressive disorder(MDD)places a noticeable burden on individuals and *** the great expectation on finding accurate biomarkers and effective treatment targets of MDD,studies in applying functional magnetic resonance imaging(fMRI)are still faced with challenges,including the representational ambiguity,small sample size,low statistical power,relatively high false positive rates,***,reviewing studies with solid methodology may help achieve a consensus on the pathology of ***:In this systematic review,we screened fMRI studies on MDD through strict criteria to focus on reliable studies with sufficient sample size,adequate control of head motion,and a proper multiple comparison control ***:We found consistent evidence regarding the dysfunction within and among the default mode network(DMN),the frontoparietal network(FPN),and other brain ***,controversy remains,probably due to the heterogeneity of participants and data processing ***:Future studies are recommended to apply a comprehensive set of neuro-behavioral measurements,consider the heterogeneity of MDD patients and other potentially confounding factors,apply surface-based neuroscientific network fMRI approaches,and advance research transparency and open science by applying state-ofthe-art pipelines along with open data sharing.

关键词： depression resting-state fMRI task-based fMRI default mode network frontoparietal network

DPABISurf:data processing&analysis for brain imaging on surface

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Science Bulletin 2021年第24期66卷 2453-2455页

作者： chao-gan Yan Xin-Di Wang Bin Lu CAS Key Laboratory of Behavioral Science Institute of PsychologyBeijing 100101China Department of Psychology University of Chinese Academy of SciencesBeijing 100101China International Big-Data Center for Depression Research Institute of PsychologyChinese Academy of SciencesBeijing 100101China Magnetic Resonance Imaging Research Center Institute of PsychologyChinese Academy of SciencesBeijing 100101China McGill Centre for Integrative Neuroscience Montreal Neurological InstituteMcGill UniversityMontréal H3A 2B4Canada Beijing Intelligent Brain Cloud Inc.Beijing 100036China

Functional magnetic resonance imaging(fMRI)is a prevalent technology in brain research of cognition,emotion,development,and brain *** traditional fMRI analysis is based on volume-based preprocessing pipelines and algorithms,which means that the brain MRI data is to be registered to a 3-dimensional(3D)coordinate[1].However,the relatively low spatial resolution of fMRI may lead to partial-volume-effect(e.g.,a 3D region may contain signals from grey matter,white matter and even cerebrospinal fluid).Given the human brain function is organized in a brain surface mesh manner,therefore,a growing number of studies conducted surface-based preprocessing pipelines and ***-based methods reconstructed the brain grey matter into 2-dimensional cortical surface which better represent the curving structure of the ***-based method is superior to volume-based method on brain registration,signal–noise ratio and reproducibility of algorithms[2].Specifically,the traditional volume-based approach was reported with a spatial localization that is only 35%of the best surface-based method[2].

关键词：脑影像 coordinate registered

Concordance among indices of intrinsic brain function： Insights from inter-individual variation and temporal dynamics

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Science Bulletin 2017年第23期62卷 1572-1584页

作者： chao-gan Yan Zhen Yang Stanley J. Colcombe Xi-Nian Zuo Michael P. Milham CAS Key Laboratory of Behavioral Science Institute of Psychology Beijing 100101 China Departrnent of Psychology University of Chinese Academy of Sciences Beijing 100101 China Magnetic Resonance Imaging Research Center Institute of Psychology Chinese Academy of Sciences Beijing 100101 China center for Lifespan Innovation of Mind and Brain Institute of Psychology Chinese Academy of Sciences Beijing China Nathan Kline Institute for Psychiatric Research Orangeburg NY 10962 USA Department of Child and Adolescent Psychiatry NYU Langone Medical Center School of Medicine New York NY 10016 USA Center for Neuromodulation in Depression and Stress Department of Psychiatry Perelman School of Medidne University of Pennsylvania Philadelphia PA 19104 USA Child Mind Institute New York NY 10022 USA

Various resting-state fMRI(R-fMRI) measures have been developed to characterize intrinsic brain activity. While each of these measures has gained a growing presence in the literature, questions remain regarding the common and unique aspects these indices capture. The present work provided a comprehensive examination of inter-individual variation and intra-individual temporal variation for commonly used measures, including fractional amplitude of low frequency fluctuations, regional homogeneity,voxel-mirrored homotopic connectivity, network centrality and global signal correlation. Regardless of whether examining intra-individual or inter-individual variation, we found that these definitionally distinct R-fMRI indices tend to exhibit a relatively high degree of covariation, which doesn't exist in phase randomized surrogate data. As a measure of intrinsic brain function, concordance for R-fMRI indices was negatively correlated with age across individuals(i.e., concordance among functional indices decreased with age). To understand the functional significance of concordance, we noted that higher concordance was generally associated with higher strengths of R-fMRI indices, regardless of whether looking through the lens of inter-individual(i.e., high vs. low concordance participants) or intra-individual(i.e., high *** concordance states identified via temporal dynamic analyses) differences. We also noted a linear increase in functional concordance together with the R-fMRI indices through the scan, which may suggest a decrease in arousal. The current study demonstrated an enriched picture regarding the relationship among the R-fMRI indices, as well as provided new insights in examining dynamic states within and between individuals.

关键词： Resting-state fMRI Intrinsic brain activity Concordance Temporal dynamics Inter-individual variation

基于Apriori算法的飞机冲偏出跑道诱因挖掘

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计算机仿真 2024年第2期41卷 44-50页

作者：赵赶超雷晶晶刘志强张林中国民用航空飞行学院四川广汉618307

为加强民航客机飞行运行全过程的安全管理,减少飞机起降阶段冲偏出跑道事件发生的概率,对冲偏出跑道事件中的诱发因素进行定性和定量分析,根据事故事件特点,建立起降阶段飞机冲偏出跑道事件诱因分析体系,对不同类型的事件进行布尔离散化... 详细信息

为加强民航客机飞行运行全过程的安全管理,减少飞机起降阶段冲偏出跑道事件发生的概率,对冲偏出跑道事件中的诱发因素进行定性和定量分析,根据事故事件特点,建立起降阶段飞机冲偏出跑道事件诱因分析体系,对不同类型的事件进行布尔离散化,采用Apriori算法对飞机冲偏出跑道数据集开展关联分析,挖掘出不同诱发因素之间的关联规则。以国内某航空公司波音737机队在2001-2021年间冲偏出跑道数据进行分类和识别;运用Apriori算法建立数据挖掘仿真模型;使用MATLAB编程迭代计算,找到飞机冲偏出跑道诱因中有强关联的因素,并保留其数据。结果表明,当飞机故障时,有28.77%的概率会出现飞行员操作有误;当道面积雪时,有23.64%的概率会出现违反标准操作程序;当飞行程序设计不合理时,有22.84%的概率会出现飞行员判断有误;当飞机故障时,有20.65%的概率会出现飞行员控制有误;当跑道道面湿滑时,有20.12%的概率会出现飞行员控制有误。

关键词：冲偏出跑道数据挖掘关联规则