Spatiotemporal Assessment of SO₂, SO₄and AOD from over MENA Domain from 2006-2016 Using Multiple Satellite and Reanalysis MERRA-2 Data

The sulfur pollutants are the source of a sizeable portion of the air pollution. In this work, the recent spatiotemporal distribution and trend of the mass concentration of two of the critical sulfur pollutants, SO2 and SO4, in addition to the aerosol optical properties (AOD) were analyzed over the region of the Middle East and North Africa (MENA) from satellite and Modern Era-Retrospective Analysis for Research and Applications version 2 (MERRA-2) reanalysis data. The SO2 and SO4 data used in these analyses are obtained from (MERRA-2) with a resolution of 0.5° × 0.625° throughout a period of 10 years (2005-2015). On the other hand, the temporal trend and spatial distribution of AOD were identified from four different satellite data. 1) moderate-resolution imaging spectroradiometer (MODIS) Level 3 AOD data at 550 nm wavelengths from Collection 6 algorithm (combined dark target and deep blue algorithms) are used for 10 years temporal analysis (2006-2015). 2) Multi-angle imaging spectroradiometer (MISR) with 0.5 deg spatial resolution for the same 10 years (2006-2015). 3) Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) with 0.5 deg for the period (2005-2010). 4) Ozone Monitoring Instrument (OMI) AOD at 500 nm wavelength with resolution 1 degree. This study presents more resent 10 years of Spatiotemporal of SO2, SO4 and AOD over MENA domain.

新疆地区ERA5和MERRA-2大气可降水量精度分析

大气再分析资料提供的大气可降水量(PWV)产品在天气变化和气候研究中扮演着极为重要的角色。新疆地区存在地形起伏大、气候复杂和实测高分辨率PWV产品缺乏等特点,大气再分析资料提供的PWV产品可作为有力补充。以新疆地区2018年11个GNSS站数据反演得到的PWV(GNSS-PWV)信息作为参考值,评估ERA5和MERRA-2提供PWV产品在新疆地区的精度,并分析两种再分析资料PWV的偏差(Bias)和均方根差(RMSE)的时空变化特性及其日变化。结果表明:以GNSS-PWV为参考值,ERA5和MERRA-2在新疆地区的PWV年均Bias分别为-0.97和-1.20 mm,年均RMSE分别为1.81和2.11 mm,两种再分析资料PWV均具有较高精度,其中ERA5 PWV精度略高于MERRA-2 PWV;两种再分析资料的PWV精度都有明显的季节性变化,总体表现为夏季精度低,冬季精度高;在PWV日变化分布上,两种再分析资料与GNSS-PWV展现出较高的一致性,能较好地反映新疆地区PWV的日变化特性。

A phenology-based vegetation index for improving ratoon rice mapping using harmonized Landsat and Sentinel-2 data

Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.

Evaluation of surface temperature and pressure derived from MERRA-2 and ERA5 reanalysis datasets and their applications in hourly GNSS precipitable water vapor retrieval over China

Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range Weather Forecasts(ECMWF) have released their latest reanalysis product: the modern-era retrospective analysis for research and applications, version 2(MERRA-2) and the fifthgeneration ECMWF reanalysis(ERA5), respectively. Based on the reanalysis data, we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed. The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy. The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K, with the root mean square error(RMSE) of 0.95 hPa and 2.04 K, respectively. The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K, with the RMSE of 1.08 h Pa and 2.66 K, respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2. The two reanalysis data show negative biases in most regions of China, with the highest to lowest accuracy in the following order: the south,north, northwest, and Tibet Plateau. Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV) and ERA5(GNSS ERA5 PWV) with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations, it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV. These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data, indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China.

A systematic study of Erzhu Erchen decoction against damp-heat internalized type 2 diabetes based on data mining and experimental verification

Background:Erzhu Erchen decoction(EZECD),which is based on Erchen decoction and enhanced with Atractylodes lancea and Atractylodes macrocephala,is widely used for the treatment of dampness and heat(The clinical manifestations of Western medicine include thirst,inability to drink more,diarrhea,yellow urine,red tongue,et al.)internalized disease.Nevertheless,the mechanism of EZECD on damp-heat internalized Type 2 diabetes(T2D)remains unknown.We employed data mining,pharmacology databases and experimental verification to study how EZECD treats damp-heat internalized T2D.Methods:The main compounds or genes of EZECD and damp-heat internalized T2D were obtained from the pharmacology databases.Succeeding,the overlapped targets of EZECD and damp-heat internalized T2D were performed by the Gene Ontology,kyoto encyclopedia of genes and genomes analysis.And the compound-disease targets-pathway network were constructed to obtain the hub compound.Moreover,the hub genes and core related pathways were mined with weighted gene co-expression network analysis based on Gene Expression Omnibus database,the capability of hub compound and genes was valid in AutoDock 1.5.7.Furthermore,and violin plot and gene set enrichment analysis were performed to explore the role of hub genes in damp-heat internalized T2D.Finally,the interactions of hub compound and genes were explored using Comparative Toxicogenomics Database and quantitative polymerase chain reaction.Results:First,herb-compounds-genes-disease network illustrated that the hub compound of EZECD for damp-heat internalized T2D could be quercetin.Consistently,the hub genes were CASP8,CCL2,and AHR according to weighted gene co-expression network analysis.Molecular docking showed that quercetin could bind with the hub genes.Further,gene set enrichment analysis and Gene Ontology represented that CASP8,or CCL2,is negatively involved in insulin secretion response to the TNF or lipopolysaccharide process,and AHR or CCL2 positively regulated lipid and atherosclerosis,and/or including NOD-like receptor signaling pathway,and TNF signaling pathway.Ultimately,the quantitative polymerase chain reaction and western blotting analysis showed that quercetin could down-regulated the mRNA and protein experssion of CASP8,CCL2,and AHR.It was consistent with the results in Comparative Toxicogenomics Database databases.Conclusion:These results demonstrated quercetin could inhibit the expression of CASP8,CCL2,AHR in damp-heat internalized T2D,which improves insulin secretion and inhibits lipid and atherosclerosis,as well as/or including NOD-like receptor signaling pathway,and TNF signaling pathway,suggesting that EZECD may be more effective to treat damp-heat internalized T2D.

基于改进遗传算法的2型糖尿病中医药有效处方推荐方法研究

目的改进遗传算法创新推荐度模型,以2型糖尿病(T2DM)电子病历数据为基础进行核心处方挖掘及有效处方推荐。方法基于真实世界电子病历数据,构建T2DM患者有效处方集及不同证型原始处方集数据库;对遗传算法进行改进,优化适应度函数的构建,使提取出的核心有效处方朝着有效处方集的方向进化;基于核心有效处方与原始处方集的相似度关系,创新推荐度模型,通过遍历不同证型原始处方集进行处方推荐度挖掘。结果共使用有效诊疗标准的处方17712条,提取的核心有效处方中包含中药37种;最终挖掘出满足“推荐度≥85%”的处方26条,最大推荐度为97.26%。结论研究改进遗传算法提高了对中药处方集的特征提取和全局搜索能力,并通过提出新的推荐度模型进行临床处方决策推荐,提高了电子病历数据的利用率。

Structural Setting of the South-West Cameroon Using Satellite Potential Field Derived from SGG-UGM-2 Gravity Data

This study aims to improve knowledge of the structure of southwest Cameroon based on the analysis and interpretation of gravity data derived from the SGG-UGM-2 model. A residual anomaly map was first calculated from the Bouguer anomaly map, which is strongly affected by a regional gradient. The residual anomaly map generated provides information on the variation in subsurface density, but does not provide sufficient information, hence the interest in using filtering with the aim of highlighting the structures affecting the area of south-west Cameroon. Three interpretation methods were used: vertical gradient, horizontal gradient coupled with upward continuation and Euler deconvolution. The application of these treatments enabled us to map a large number of gravimetric lineaments materializing density discontinuities. These lineaments are organized along main preferential directions: NW-SE, NNE-SSW, ENE-WSW and secondary directions: NNW-SSE, NE-SW, NS and E-W. Euler solutions indicate depths of up to 7337 m. Thanks to the results of this research, significant information has been acquired, contributing to a deeper understanding of the structural composition of the study area. The resulting structural map vividly illustrates the major tectonic events that shaped the geological framework of the study area. It also serves as a guide for prospecting subsurface resources (water and hydrocarbons). .

基于机械过冷的双温蒸发CO_(2)数据中心冷却供热系统性能

为实现数据中心绿色高效制冷,并提高能源综合利用率,提出了集成机械过冷和双温蒸发技术的CO_(2)数据中心冷却供热系统(DMS-DE)。建立了系统热力学和碳排放特性分析模型,并与基本CO_(2)系统(Base)和单温蒸发机械过冷CO_(2)系统(DMS-SE)进行对比分析。结果表明:DMS-DE存在最大COP(性能系数)、最优过冷度和排气压力。采用机械过冷技术和双温蒸发技术可显著提升系统COP和效率。与Base和DMS-SE相比,COP分别提高14.1%和9.0%,效率分别提高13.24%和4.31%。DMS-DE的生命周期碳排放相对Base和DMS-SE分别降低16.1%和9.3%。

改良PI-RADS评分联合血清AGR2、sTim-3水平对前列腺癌的诊断价值

目的探究改良前列腺影像报告和数据系统(PI-RADS)评分联合血清前梯度蛋白2(AGR2)、可溶性T细胞免疫球蛋白黏蛋白分子3(sTim-3)水平对前列腺癌(PCa)的诊断价值。方法选取2022年6月至2023年6月长江大学附属黄冈市中心医院进行前列腺穿刺活检的125例患者作为研究对象,根据病理结果将PCa患者归为恶性组(n=74),将前列腺良性肿瘤患者归为良性组(n=51)。比较两组血清中AGR2、sTim-3水平,采用多因素Logistic回归分析PCa的影响因素,绘制受试者工作特征(ROC)曲线分析血清AGR2、sTim-3水平对PCa的诊断价值。结果与良性组比较,恶性组PI-RADS评分、前列腺特异性抗原密度(PSAD)及血清AGR2、sTim-3水平显著升高(P<0.05);AGR2、sTim-3、PI-RADS评分均为患者发病的影响因素(P<0.05);PI-RADS评分及血清AGR2、sTim-3水平诊断PCa的曲线下面积(AUC)分别为0.855、0.899、0.851,三者联合诊断的AUC为0.957,三者联合诊断优于各自单独诊断(P<0.05),三者联合诊断的灵敏度为93.24%,特异度为86.27%。结论PCa患者PI-RADS评分及血清AGR2、sTim-3水平均上升,且均为PCa的影响因素,三者联合对PCa具有较高的诊断价值。

基于手机平台的Data Matrix 2维条码识别

传统的条码图像采集和识别是通过工业扫描枪。近年来,随着移动增值业务和3G技术的发展,2维条码在手机设备的应用中得到飞速发展。以Data Matrix为例,研究了基于嵌入式手机设备的2维条码识别技术。首先根据Data Matrix条码的特点,给出了一种基于链码跟踪和线段检测的快速Data Matrix检测算法。接着分析了条码信号经过点扩展函数卷积后的降质模型,并利用维纳滤波对条码信号进行反模糊滤波。最后,针对透视畸变的现象,设计了一种适合于嵌入式手机设备的快速反透视算法。实验结果表明,提出的识别算法具有优秀的性能,显著提高了条码的识别率,满足了实际使用的要求。

中国区域CALIPSO和MERRA-2气溶胶三维参数对比验证

气溶胶是目前大气污染重要的贡献源之一,影响着全球辐射平衡和气候变化。当前主被动遥感卫星(如MODIS和CALIPSO)获取全球气溶胶信息时间分辨率较低,而全球再分析数据MERRA-2提供了高时间分辨率的三维气溶胶分布信息,但是MERRA-2气溶胶产品的质量仍然有待验证。针对上述问题,通过对MERRA-2和CALIPSO的三维消光系数廓线进行交叉对比,验证了MERRA-2在中国中东部(特别是重人为污染区域)的数据精度。实验结果表明,MERRA-2和CALIPSO的消光系数整体具有较好相关性(0.79),其中二者在秋季相关性最高(0.82),夏季和冬季次之(0.81和0.80),春季相关性最低(0.77)。随着高度的不断增加,大气更为洁净,MERRA-2和CALIPSO之间相关系数从0.78降为0.52,标准差从0.0280降为0.0014。上述结果表明,MERRA-2在重污染情况下能提供更为准确的气溶胶三维分布信息,同时MERRA-2和CALIPSO消光系数的一致性受气溶胶类型的影响不大。

基于OCO-2卫星数据的中国CO_(2)浓度时空变化特征

大气CO_(2)浓度增加引起的全球变暖问题是国内外学者关注的热点议题,但对CO_(2)的监测一直存在较多的不确定性。利用2015—2022年OCO-2卫星观测的CO_(2)柱浓度混合比数据(XCO_(2)),基于克里金插值和标准差椭圆等方法,分析了中国CO_(2)浓度时空分布与变化特征,有以下3个结论。1)基于OCO-2卫星数据的XCO_(2)数据集精度较高,与地面监测站(瓦里关站、鹿林站)观测结果的均方根误差仅为1.75 ppm和1.58 ppm,相关系数分别为0.91和0.96。2)年际上,2015—2022年中国年均XCO_(2)由399.52 ppm增至417.64 ppm,年均增速为2.56 ppm/a,高于过去10年全球CO_(2)浓度平均增速(2.06 ppm/a),但在2019年之后XCO_(2)增速呈下降趋势。季节上,XCO_(2)具有明显的季节变化特征,春季XCO_(2)最高,夏季最低。3)空间分布上,XCO_(2)表现出东部高,西部、东北地区低的空间分布特征。XCO_(2)浓度高值区域集中在京津冀和长三角等城市群。中国东北、西南地区XCO_(2)增速较快,高于华东、华南等经济发达地区。

面向碳卫星数据的高时空分辨率XCO_(2)浓度估算的研究

基于碳卫星的遥感是一种正在发展的大范围高精度CO_(2)监测方法,但当监测对象为我国长三角区域这种大空间尺度时,碳卫星数据会存在时空稀疏性的问题。本文提出了一种新的模型ST-SAN(space time soft attention network),旨在提高碳卫星数据的高时空分辨率XCO_(2)(大气CO_(2))浓度估算精度。本文将2016—2020年的多源数据(包括人类活动数据、气象数据和植被数据)与碳卫星数据结合,生成空间分辨率为0.05°的无间隙XCO_(2)日浓度数据集。通过ST-SAN模型对这些数据进行训练和预测。实验结果表明,重建后的XCO_(2)数据集与OCO-2卫星数据和地面站点数据具有高度一致性,验证了本方法在高时空分辨率XCO_(2)浓度估算中的有效性。

早发型2型糖尿病患者子女颈动脉全息血管硬度及影响因素分析

目的评估早发型2型糖尿病患者子女颈动脉弹性功能,并分析影响其弹性的因素。资料与方法前瞻性分析2020年10月—2021年8月河南省人民医院2型糖尿病患者子女63例,根据其父母糖尿病发病年龄(<40岁为早发型,≥40岁为晚发型)分为父母早发糖尿病子女组(早发组,32例)和父母晚发糖尿病子女组(晚发组,31例)。同期选择32例年龄、性别及体重指数相匹配的健康志愿者作为对照组。应用全息血管内-中膜厚度测量和全息血管硬度分析技术测量受试者颈总动脉内-中膜厚度、血管壁位移、血管收缩期管径、硬度指数和脉搏波传导速度,比较上述参数的组间差异。结果早发组颈动脉内-中膜厚度、脉搏波传导速度、硬度指数高于晚发组及对照组(t=0.054~1.228,P均<0.05),血管壁位移低于晚发组及对照组(t=0.048、0.109,P<0.05)。结论2型糖尿病患者子女颈动脉僵硬度明显高于正常对照组,且早发组的颈动脉弹性下降较晚发组更明显。

中国区域ERA5和MERRA-2再分析资料计算T_(m)的精度分析

以中国区域89个探空站2017年资料为参考值,对ERA5和MERRA-2再分析资料积分计算的T_(m)的精度进行评估,并分析2种资料计算的T_(m)的bias和RMSE的时空变化特性。结果表明:1)以探空站资料为参考值,ERA5和MERRA-2再分析资料计算的T_(m)的年均bias分别为0.41K和0.10K,年均RMSE分别为1.26K和1.34K。2)2种资料计算的T_(m)的bias和RMSE具有相似的时空变化特性,时间上总体表现为夏季精度高、冬季精度稍低,但ERA5再分析资料计算的T_(m)的bias在全年均表现为正值,而MERRA-2再分析资料计算的T_(m)的bias在夏季表现为负值,其余时间表现为正值;在空间上,2种资料计算的T_(m)的bias和RMSE在高程上无明显变化特性,但在纬度上RMSE均表现出随纬度增加而逐渐变大的趋势,总体保持在2.5K以内。

广西地区MERRA-2加权平均温度模型

针对广西地区南接热带海洋、西临云贵高原、地形起伏较大等特点,通过分析广西2014—2016年的MERRA-2再分析资料格网点高度处的加权平均温度(T_(m))及格网点垂直方向温度递减率(K)的时序变化特征,建立了每个格网点高度处的加权平均温度模型和温度递减率模型,进而建立了广西地区MERRA-2加权平均温度模型(GXT_(m))。以2017年探空站资料计算得到的T_(m)作为参考值,对其进行精度检验,并与Bevis模型、中国东部模型、广西气象参数模型以及GPT2w-1和GPT2w-5模型进行比较。结果表明:GXT_(m)模型的平均偏差(Bias)和均方根误差(RMSE)分别为0.26和2.51 K,GXT_(m)模型的精度(RMSE)较Bevis模型、中国东部模型、GPT2w-1模型和GPT2w-5模型分别提高了32%、34%、17%和46%,与广西气象参数模型精度相当。

桂林地区一次暴雨过程ERA5/MERRA-2资料计算PWV的精度分析

为了评估再分析资料在特定地区和特定天气条件下反演大气水汽(precipitable water vapor, PWV)的性能,利用2015—2017年桂林探空站观测数据建立桂林地区大气加权平均温度模型,并用该模型计算出的连续运行参考站(continuously operating reference stations, CORS)大气水汽(CORS-PWV)为参考值,与ERA5和MERRA-2这2种再分析资料提取的PWV作比较。结果表明:新建立的桂林地区大气加权平均温度模型的精度比Bevis模型提高了8.4%,比广西模型提高了13.4%,比中国东部模型提高了17.4%;在暴雨过程中,以2017年年积日为178~183 CORS站反演的PWV为参考值,ERA5提取PWV的平均bias和RMSE分别为1.55 mm和3.38 mm,而MERRA-2提取PWV则表现出较大的平均bias和RMSE,分别为4.60 mm和6.18 mm,并且ERA5提取的PWV与CORS站反演的PWV具有更好的一致性,与地面实际降水情况相符。

Comparisons of OCO-2 satellite derived XCO_(2)with in situ and modeled data over global ocean

Atmospheric CO_(2)is one of key parameters to estimate air-sea CO_(2)flux.The Orbiting Carbon Observatory-2(OCO-2)satellite has observed the column-averaged dry-air mole fractions of global atmospheric carbon dioxide(XCO_(2))since 2014.In this study,the OCO-2 XCO_(2)products were compared between in-situ data from the Total Carbon Column Network(TCCON)and Global Monitoring Division(GMD),and modeling data from CarbonTracker2019 over global ocean and land.Results showed that the OCO-2 XCO_(2)data are consistent with the TCCON and GMD in situ XCO_(2)data,with mean absolute biases of 0.25×10^(-6)and 0.67×10^(-6),respectively.Moreover,the OCO-2 XCO_(2)data are also consistent with the CarbonTracker2019 modeling XCO_(2)data,with mean absolute biases of 0.78×10^(-6)over ocean and 1.02×10^(-6)over land.The results indicated the high accuracy of the OCO-2 XCO_(2)product over global ocean which could be applied to estimate the air-sea CO_(2)flux.

Comparison and Analysis of CO_2 Emissions Data for China

This paper reviews the CO2emissions data for China provided by various international organizations and databases(namely IEA,BP,EDGAR/PBL/JRC,CDIAC,EIA and CAIT)and compares them with China’s official data and estimation.The difference among these data is due to different scopes,methods and underlying data,and particularly the difference in fossil fuel consumption.Compared with data from other databases,IEA and CAIT data have the best comparability with China’s official data.The paper recommends that China enhance its coal statistics,raise the frequency of official data publication and improve the inventory completeness.

How signaling and search costs affect information asymmetry in P2P lending:the economics of big data

In the past decade,online Peer-to-Peer(P2P)lending platforms have transformed the lending industry,which has been historically dominated by commercial banks.Information technology breakthroughs such as big data-based financial technologies(Fintech)have been identified as important disruptive driving forces for this paradigm shift.In this paper,we take an information economics perspective to investigate how big data affects the transformation of the lending industry.By identifying how signaling and search costs are reduced by big data analytics for credit risk management of P2P lending,we discuss how information asymmetry is reduced in the big data era.Rooted in the lending business,we propose a theory on the economics of big data and outline a number of research opportunities and challenging issues.