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钠-葡萄糖耦联转运体2抑制剂对代谢综合征相关代谢紊乱的作用研究进展

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浙江大学学报（医学版） 2024年第3期53卷 382-389页

作者：徐纯想蔡晓霞邱星宇赵亮浙江大学医学院附属儿童医院肾内科国家儿童健康与疾病临床医学研究中心浙江杭州310052 红河卫生职业学院基础医学院云南红河661199 浙江大学医学院基础医学院生理学系浙江杭州310058 浙江省新生儿疾病(诊治)重点实验室浙江杭州310052

代谢综合征是一组复杂的代谢紊乱症候群,其全球发病率不断升高,严重威胁人类的健康,但临床上尚无特效药。钠-葡萄糖耦联转运体2(SGLT2)抑制剂是一种新型口服降糖药物,它不仅可以通过抑制肾脏近曲小管上皮细胞对葡萄糖的重吸收促进尿糖... 详细信息

代谢综合征是一组复杂的代谢紊乱症候群,其全球发病率不断升高,严重威胁人类的健康,但临床上尚无特效药。钠-葡萄糖耦联转运体2(SGLT2)抑制剂是一种新型口服降糖药物,它不仅可以通过抑制肾脏近曲小管上皮细胞对葡萄糖的重吸收促进尿糖排泄这种非胰岛素依赖方式降低血糖,还可以通过改善胰岛β细胞功能、降低炎症反应、抑制氧化应激来降低血糖。此外,SGLT2抑制剂还可以通过渗透性利尿、增加脂肪代谢以减轻体重;通过抑制交感神经系统过度激活、改善血管功能等作用降低血压;通过增加三酰甘油降解进而改善血脂;通过促进肾脏及肠道尿酸排泄和减少尿酸合成来降低血尿酸。本文就SGLT2抑制剂对代谢综合征相关代谢紊乱的改善作用及其相关调控机制进行综述。

关键词：钠-葡萄糖耦联转运体2抑制剂代谢综合征糖尿病体重减轻高血压血脂异常高尿酸血症综述

Cy-CNN: cylinder convolution based rotation-invariant neural network for point cloud registration

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Science China(Information Sciences) 2023年第5期66卷 73-87页

作者： Hengwang ZHAO Zhidong liang Yuesheng HE chunxiang WANG Ming YANG Department of Automation Shanghai Jiao Tong University Research Institute of Robotics Shanghai Jiao Tong University

Point cloud registration is a challenging problem in the condition of large initial misalignments and noises. A major problem encountered in the registration algorithms is the definition of correspondence between two point clouds. Point clouds contain rich geometric information and the same geometric structure implies the same feature even if they are in diferent poses, which motivates us to seek a rotation-invariant feature representation for calculating the correspondence. This work proposes a rotation-invariant neural network for point cloud registration. To acquire rotation-invariant features, we firstly propose a rotationinvariant point cloud representation(RIPR) at the input level. Instead of using the original coordinates,we propose to use point pair features(PPF) and the transformed coordinates in the local reference frame(LRF) to represent a point. Then, we design a new convolution operator named Cylinder-Conv which utilizes the symmetry of cylinder-shaped voxels and the hierarchical geometry information of the surface of3D shapes. By specifying the cylinder-shaped structures and directions, Cylinder-Conv can better capture the local neighborhood geometry of each point and maintain rotation-invariance. Finally, we combine RIPR and Cylinder-Conv to extract normalized rotation-invariant features to generate the correspondence and perform a diferentiable singular value decomposition(SVD) step to estimate the rigid transformation. The proposed network presents state-of-the-art performance on point cloud registration. Experiments show that our method is robust to initial misalignments and noises.

关键词： deep learning point cloud registration rotation invariant computer vision

城乡融合视角下全面推进辽宁乡村振兴的路径选择

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沈阳工业大学学报（社会科学版） 2024年第3期17卷 251-264页

作者：徐春祥梁姝娜王子君潍坊科技学院经济管理学院山东潍坊262700 沈阳理工大学科技处辽宁沈阳110159

城乡融合发展是全面推进辽宁乡村振兴的必由之路,是促进全省农业农村现代化、实现共同富裕的重要突破口,是新时代缩小城乡发展差距、破解全省“城乡发展不均衡、农业农村发展不充分”这一社会矛盾的必然选择,是高质量实施辽宁全面振兴... 详细信息

城乡融合发展是全面推进辽宁乡村振兴的必由之路,是促进全省农业农村现代化、实现共同富裕的重要突破口,是新时代缩小城乡发展差距、破解全省“城乡发展不均衡、农业农村发展不充分”这一社会矛盾的必然选择,是高质量实施辽宁全面振兴新突破三年行动方案的重要抓手。梳理我国城乡关系发展脉络,提出城乡融合基本内涵;从农村人居环境、农业转移人口市民化进程、城乡发展差距、城乡基本公共服务均等化、农村土地制度改革、农民精神风貌等方面展现辽宁城乡融合发展成效;从城乡均衡发展、农村基础设施改善和人居环境质量提升、城乡居民收入及消费支出差距、医患矛盾、要素市场化改革、农业与其他产业之间效率差距、城乡融合区域差异、“三农”政策宣介效果等方面指出当前制约辽宁城乡融合发展的因素;从城乡发展理念、新型城乡关系、农村人居环境质量提升、乡村产业发展模式、农村土地改革、乡村区域发展差异、要素市场化改革、县域经济、“三农”政策解读等方面提出加快城乡融合发展、全面推进辽宁乡村振兴的路径,旨为实现经济高质量发展提供理论基础。

关键词：城乡融合城乡差距乡村振兴县域经济

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Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

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Advances in Atmospheric Sciences 2023年第2期40卷 235-250页

作者： Jianguo LIU Zong-liang YANG Binghao JIA Longhuan WANG Ping WANG Zhenghui XIE chunxiang SHI School of Mathematics and Computational Science and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan ProvinceHuaihua UniversityHuaihuaHunan 418008China Department of Geological Sciences The John A.and Katherine G.Jackson School of GeosciencesUniversity of Texas at AustinAustinTexas 78712-1722USA State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China National Meteorological Information Center China Meteorological AdministrationBeijing 100081China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were conducted.Six simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against observations.The results show that the meteorological forcing is the most important factor governing output.Beyond that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the LSM.The Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight basins.It increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD simulations.This study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

关键词： hydrological simulations land surface model meteorological forcing land surface parameters uncertainty

基于MODIS和CLDAS的综合干旱监测模型研究

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南京信息工程大学学报 2024年第3期16卷 394-404页

作者：邢雅洁沈润平黄安奇梁宇靖王云宇谢昭颖师春香孙帅南京信息工程大学地理科学学院南京210044 国家气象信息中心北京100081

传统的干旱监测指数主要考虑单一影响因子,往往无法全面综合反映干旱状况.基于MODIS数据和CLDAS数据,选取多个影响因子和能够直接反映干旱程度的干旱指数作为自变量,以综合气象干旱指数(CI)为因变量,通过梯度提升机(GBM)机器学习算法建... 详细信息

传统的干旱监测指数主要考虑单一影响因子,往往无法全面综合反映干旱状况.基于MODIS数据和CLDAS数据,选取多个影响因子和能够直接反映干旱程度的干旱指数作为自变量,以综合气象干旱指数(CI)为因变量,通过梯度提升机(GBM)机器学习算法建立日尺度综合干旱监测模型,并以2015—2018年华北地区干旱为例进行了研究.结果表明模型监测结果与站点CI计算值具有显著的相关性,训练集和测试集决定系数分别达到0.945和0.655,均方根误差(RMSE)分别为0.033和0.082,综合干旱监测模型具有较高的精度.且模型监测与CI监测各月等级一致率均在65%以上,并与标准化降水蒸散指数(SPEI)和土壤相对湿度(RSM)相关系数分别为0.68和0.60,能较好地反映气象干旱和农业干旱状况.典型干旱情况监测表明,综合干旱监测模型综合考虑多种干旱影响因素,能较准确地识别出干旱的发生,表征综合干旱发生状况.

关键词： CLDAS 综合干旱监测梯度提升机 MODIS

Mechanical Properties of Lime-Fly Ash-Sulphate Aluminum Cement Stabilized Loess

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Journal of Renewable Materials 2020年第10期8卷 1357-1373页

作者： liang Jia chunxiang Li Jian Guo College of Civil Engineering Lanzhou University of TechnologyLanzhou730050China

Lime-fly ash stabilized loess has a poor early strength,which results in a later traffic opening time when it is used as road-base materials.Consideration of the significant early strength characteristics of sulphate aluminum cement(SAC),it is always added into the lime-fly ash mixtures to improve the early strength of stabilized loess.However,there is a scarcity of research on the mechanical behavior of lime-fly ash-SAC stabilized loess and there is a lack of quantitative evaluation of loess stabilized with binder materials.This research explored the effects of the amount of binder materials,curing time and porosity on the unconfined compressive strength(UCS),splitting tensile strength(STS),cohesion(c)and friction angle(φ)of lime-fly ash-SAC stabilized loess by a series of unconfined compressive tests(UCT)and splitting tensile tests(STT).The results indicate that an increase in curing time and a decrease in porosity lead to a continuous increase in the UCS and STS for lime-fly ash-SAC stabilized loess.The addition of SAC has a prominent enhancement in the early strength of lime-fly ash-SAC stabilized loess.When the curing time,porosity,and binder content were constant,the UCS and STS increase with increasing SAC content;For a stabilized loess with 30%binder content and 5%SAC content after 1 day of curing,the UCS was greater than 0.7 MPa,which meets the requirement of opening traffic,so lime-fly ash-SAC stabilized loess could be used as an excellent maintenance material for road-base;In accordance with the analysis of testing data,empirical relationships between the UCS and STS of lime-fly-SAC stabilized loess and key effect factors(binder materials content,curing time and porosity)were developed,which can provide references for reasonably selecting the amount of binder materials,compaction degree and curing period to meet the required strength of practical engineering.Finally,based on the Mohr-Coulomb theory and the above empirical relationships,a simpler method for calculating the c andφof stabilized loess was

关键词： Loess sulphate aluminum cement unconfined compressive strength splitting tensile strength

Fusion of In-Situ Soil Moisture and Land Surface Model Estimates Using Localized Ensemble Optimum Interpolation over China

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Journal of Meteorological Research 2020年第6期34卷 1335-1346页

作者： Lipeng JIANG chunxiang SHI Shuai SUN Xiao liang School of Geographic Sciences Nanjing University of Information Science&TechnologyNanjing 210044 National Meteorological Information Center China Meteorological AdministrationBeijing 100081

Land data assimilation(DA)is an effective method to provide high-quality spatially and temporally continuous soil moisture datasets that are crucial in weather,climate,hydrological,and agricultural research.However,most existing land DA applications have used remote sensing observations,and are based on one-dimensional(1 D)analysis,which cannot be directly employed to reasonably assimilate the recently expanded in-situ soil moisture observations in China.In this paper,a two-dimensional(2 D)localized ensemble-based optimum interpolation(En OI)scheme for assimilating in-situ soil moisture observations from over 2200 stations into land surface models(LSMs)is introduced.This scheme uses historical LSM simulations as ensemble samples to provide soil moisture background error covariance,allowing the in-situ observation information to be propagated to surrounding pixels.It is also computationally efficient because no additional ensemble simulations are needed.A set of ensemble sampling and localization length scale sensitivity experiments are performed.The En OI performs best for in-situ soil moisture fusion over China with an ensemble sampling of hourly soil moisture from the previous 7 days and a localization length scale of 100 km.Following the evaluation,simulations for in-situ soil moisture fusion are also performed from May 2016 to September 2016.The En OI analysis is notably better than that without in-situ observation fusion,as the wet bias of 0.02 m3 m-3 is removed,the root-mean-square error(RMSE)is reduced by about 37%,and the correlation coefficient is increased by about 25%.Independent evaluation shows that the En OI analysis performs considerably better than that without fusion in terms of bias,and marginally better in terms of RMSE and correlation.

关键词： soil moisture fusion land surface model(LSM) ensemble optimum interpolation localization

Fusing Geometrical and Visual Information via Superpoints for the Semantic Segmentation of 3D Road Scenes

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Tsinghua Science and Technology 2020年第4期25卷 498-507页

作者： Liuyuan Deng Ming Yang Zhidong liang Yuesheng He chunxiang Wang the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China the Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China the Research Institute of Robotics Shanghai Jiao Tong UniversityShanghai 200240China

This paper addresses the problem of the semantic segmentation of large-scale 3D road scenes by incorporating the complementary advantages of point clouds and images.To make full use of geometrical and visual information,this paper extracts 3D geometric features from a point cloud using a deep neural network for 3D semantic segmentation and extracts 2D visual features from images using a Convolutional Neural Network(CNN)for 2D semantic segmentation.In order to bridge the features of the two modalities,this paper uses superpoints as an intermediate representation to connect the 2D features with the 3D features.A superpoint-based pooling method is proposed to fuse the features from the two different modalities for joint learning.To evaluate the approach,the paper generates 3D scenes from the Virtual KITTI dataset.The results of the experiments demonstrate that the proposed approach is capable of segmenting large-scale 3D road scenes based on the compact and semantically homogeneous superpoints,and that it achieves considerable improvements over the 2D image and 3D point cloud semantic segmentation methods.

关键词： scene understanding point cloud semantic segmentation multi-modal information fusion deep learning

Improving Land Surface Hydrological Simulations in China Using CLDAS Meteorological Forcing Data

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Journal of Meteorological Research 2019年第6期33卷 1194-1206页

作者： Jianguo LIU chunxiang SHI Shuai SUN Jingjing liang Zong-liang YANG School of Mathematics and Computational Science and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan ProvinceHuaihua UniversityHuaihua 418008China National Meteorological Information Center China Meteorological AdministrationBeijing 100081China Key Laboratory of Regional Climate–Environment Research for Temperate East Asia Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Department of Geological Sciences The John A.and Katherine G.Jackson School of GeosciencesThe University of Texas at AustinAustinTX 78712USA

The accuracy of land surface hydrological simulations using an offline land surface model(LSM)depends largely on the quality of the atmospheric forcing data.In this study,Global Land Data Assimilation System(GLDAS)forcing data and the newly developed China Meteorological Administration Land Data Assimilation System(CLDAS)forcing data are used to drive the Noah LSM with multiple parameterizations(Noah-MP)and to explore how the newly developed CLDAS forcing data improve land surface hydrological simulations over China's Mainland.The monthly soil moisture(SM)and evapotranspiration(ET)simulations are then compared and evaluated against observations.The results show that the Noah-MP driven by the CLDAS forcing data(referred to as CLDASNoah-MP)significantly improves the simulations in most cases over China's Mainland and its eight river basins.CLDASNoahMP increases the correlation coefficient(R)values from 0.451 to 0.534 for the SM simulations at a depth range of 0–10 cm in China's Mainland,especially in the eastern monsoon area such as the Huang–Huai–Hai Plain,the southern Yangtze River basin,and the Zhujiang River basin.Moreover,the root-mean-square error is reduced from 0.078 to0.068 m3 m-3 for the SM simulations,and from 12.9 to 11.4 mm month-1 for the ET simulations over China's Mainland,especially in the southern Yangtze River basin and Zhujiang River basin.This study demonstrates that,by merging more in situ and remote sensing observations in regional atmospheric forcing data,offline LSM simulations can better simulate regional-scale land surface hydrological processes.

关键词： hydrological simulations Noah-MP atmospheric forcing China Meteorological Administration Land Data Assimilation System(CLDAS) Global Land Data Assimilation System(GLDAS)