Global and Hemispherical Interannual Variation of Total Column Ozone from TOMS and OMI Data

Daily Total Column Ozone (TCO) measurements compiled from Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instruments (OMI) were used to analyze the global and hemispherical TCO interannual variations. Two periods of TCO measurements were analyzed separately covering full years. For the 1978-1994 period, the TCO showed a global decade decrease rate of 13.45 DU (about -4.3%). For the Northern Hemisphere(NH) the decade decrease rate was of 12.96 DU (-4.0%), while in the Southern Hemisphere (SH) was of 13.57 DU (-4.5%). These decreases in ozone trends, using the totality of TOMS and OMI satellite measurements, are greater than those reported in literature. The 1998-2014 period global TCO decade decrease rate was of 1.56 DU, corresponding 0.94 DU and 0.138 DU for the NH and SH, respectively. The global TCO variations must show a double annual periodicity, the first one with maxima in March due to the Northern Hemisphere (NH) and the second one during September due to the Southern Hemisphere (SH). However, the maxima due to SH TCO interannual variations have gradually vanished. A disturbance in the SH TCO interannual variations has appeared since 1980;graphically the periodicity brakes down and transforms to a double peak from 1985 and on. This effect can be attributed to the hemispheric impact of the ozone hole at the South Pole. Between October 1, 2004 and December 14, 2005 TOMS and OMI have recorded this disturbance unequivocally. We conclude that the disturbance in SH TCO has an irreversible character.

Image reconstruction for cone-beam computed tomography using total p-variation plus Kullback-Leibler data divergence

Accurate reconstruction from a reduced data set is highly essential for computed tomography in fast and/or low dose imaging applications. Conventional total variation（TV）-based algorithms apply the L1 norm-based penalties, which are not as efficient as Lp（0〈p〈1） quasi-norm-based penalties. TV with a p-th power-based norm can serve as a feasible alternative of the conventional TV, which is referred to as total p-variation（TpV）. This paper proposes a TpV-based reconstruction model and develops an efficient algorithm. The total p-variation and Kullback-Leibler（KL） data divergence, which has better noise suppression capability compared with the often-used quadratic term, are combined to build the reconstruction model. The proposed algorithm is derived by the alternating direction method（ADM） which offers a stable, efficient, and easily coded implementation. We apply the proposed method in the reconstructions from very few views of projections（7 views evenly acquired within 180°）. The images reconstructed by the new method show clearer edges and higher numerical accuracy than the conventional TV method. Both the simulations and real CT data experiments indicate that the proposed method may be promising for practical applications.

A new edge recognition technology based on the normalized vertical derivative of the total horizontal derivative for potential field data

边察觉和改进技术通常在用潜在的域数据认出地质的身体的边被使用。我们在场一种新边识别技术基于有边察觉和改进技术的功能的全部的水平衍生物的规范的垂直衍生物。首先，我们计算潜在地的数据的全部的水平衍生物(THDR ) 然后计算 n 顺序 THDR 的垂直衍生物(VDRn ) 。为 n 顺序垂直衍生物，全部的水平衍生物(PTHDR ) 的山峰价值用比 0 大的阀值价值被获得。这 PTHDR 能被用于边察觉。第二， PTHDR 价值被全部的水平衍生物划分并且由最大的价值使正常化。最后，我们使用了数字模型的不同类型验证新边识别技术的有效性和可靠性。

A data-derived soft-sensor method for monitoring effluent total phosphorus

The effluent total phosphorus(ETP) is an important parameter to evaluate the performance of wastewater treatment process(WWTP). In this study, a novel method, using a data-derived soft-sensor method, is proposed to obtain the reliable values of ETP online. First, a partial least square(PLS) method is introduced to select the related secondary variables of ETP based on the experimental data. Second, a radial basis function neural network(RBFNN) is developed to identify the relationship between the related secondary variables and ETP. This RBFNN easily optimizes the model parameters to improve the generalization ability of the soft-sensor. Finally, a monitoring system, based on the above PLS and RBFNN, named PLS-RBFNN-based soft-sensor system, is developed and tested in a real WWTP. Experimental results show that the proposed monitoring system can obtain the values of ETP online and own better predicting performance than some existing methods.

Agricultural Total Factor Productivity and Income Gap between Urban and Rural Residents--An Empirical Study Based on Provincial Panel Data

Taking the relevant data of 27 provinces in China during 2013 and 2017 as samples,this paper firstly measured the agricultural total factor productivity( TFP) using Malmquist index method. Then,it built the panel data model,and empirically tested the impacts of agricultural TFP on the income gap between urban and rural residents. The results show that the improvement in agricultural TFP can promote the narrowing of the income gap between urban and rural residents,and the factors such as urbanization level and industrial structure also have significant impacts on the income gap between urban and rural residents. On the basis of these,it came up with recommendations,including increasing agricultural human capital investment and establishing agricultural production research institutions.

Accuracy Assessment and Guidelines for Manual Traffic Counts from Pre-Recorded Video Data

Traffic count is the fundamental data source for transportation planning, management, design, and effectiveness evaluation. Recording traffic flow and counting from the recorded videos are increasingly used due to convenience, high accuracy, and cost-effectiveness. Manual counting from pre-recorded video footage can be prone to inconsistencies and errors, leading to inaccurate counts. Besides, there are no standard guidelines for collecting video data and conducting manual counts from the recorded videos. This paper aims to comprehensively assess the accuracy of manual counts from pre-recorded videos and introduces guidelines for efficiently collecting video data and conducting manual counts by trained individuals. The accuracy assessment of the manual counts was conducted based on repeated counts, and the guidelines were provided from the experience of conducting a traffic survey on forty strip mall access points in Baton Rouge, Louisiana, USA. The percentage of total error, classification error, and interval error were found to be 1.05 percent, 1.08 percent, and 1.29 percent, respectively. Besides, the percent root mean square errors (RMSE) were found to be 1.13 percent, 1.21 percent, and 1.48 percent, respectively. Guidelines were provided for selecting survey sites, instruments and timeframe, fieldwork, and manual counts for an efficient traffic data collection survey.

数据要素与新质生产力:基于企业全要素生产率视角

新质生产力以全要素生产率提升为标志、核心是创新,数据要素对于提升创新水平与全要素生产率具有重要意义。本文将国家级大数据综合试验区试点作为一次准自然实验,基于我国2009—2021年制造业和服务业上市公司面板数据,利用双重差分模型识别数据要素影响企业全要素生产率的因果效应与作用机制。研究发现:数据要素显著提升了企业全要素生产率,且对服务业企业全要素生产率的影响大于制造业企业;经过一系列稳健性检验后上述结论依然成立。机制分析结果表明,数据要素主要通过数字化变革和创新对企业全要素生产率产生间接影响。调节效应表明,产业融合与数据要素会共同发挥作用、提升企业全要素生产率,且在中、高产业融合区域的作用效果没有显著差异,在低产业融合区域的效果不显著。

东北三省耕地利用格局变化对粮食全要素生产率的影响

耕地是粮食生产最基本的要素,当前粮食需求扩大与粮食生产区域性不足矛盾突出,寻求更合理的耕地利用格局来实现粮食全要素生产率的提升具有重要意义。本研究基于土地利用/土地覆被变化(LUCC)遥感监测数据,应用GIS软件提取东北三省2000、2005、2010、2015年耕地利用格局相关数据,同时运用数据包络分析模型估算了2000、2005、2010年和2015年东北三省区域和市域粮食全要素生产率。在耕地利用格局变化分析和粮食全要素生产率测算的基础上,从耕地利用格局变化的角度选取指标构建面板数据模型,定量分析其对粮食全要素生产率的影响。结果表明:东北三省市域粮食全要素生产率4个时期均值分别为0.81、0.78、0.82和0.83,粮食全要素生产率空间分布从最初的相对均匀到局部集聚;耕地转出率和耕地斑块破碎度与粮食全要素生产率呈负相关关系,耕地面积比例、耕地转入率和耕地斑块聚合度与粮食全要素生产率呈正相关关系;东北三省粮食全要素生产率提高主要源于耕地面积增加、林地和未利用地向耕地的转入以及耕地在流域的聚合,粮食全要素生产率的降低主要源于耕地转入减少和建设用地对耕地的嵌入式占用。研究表明,严格规划耕地利用格局、持续开展土地整理、提高耕地聚合度,可在保证耕地有效数量的同时,提高耕地利用格局的集聚性和合理性,促进粮食全要素生产率的提升。

对抗性话语的底层概念及研究方法

国际地缘政治场域中错综复杂的矛盾与利益冲突已投射、产生一种新的频繁显现的话语方式——对抗性话语。本文从梳理哲学中的“矛盾”概念开始,然后系统讨论对抗性话语的界定特征及实证研究方法。研究揭示,毛泽东论述的对抗性矛盾是现今对抗性话语最重要和最直接的哲学概念基础,而维特根斯坦的语言游戏论可为对抗性话语研究提供分析工具。文章继而从话语动因、目标受众、话语方式与策略、评价标准等向度讨论话语对抗双方的攻防、博弈和较量特征。方法论上,本文主张采用基于语料库与人工智能技术相结合的路径,强调数据整体解释性与局部语境下意义识解的协同要义。

长江经济带粮食生态全要素生产率的时空特征

在资源环境约束趋紧、确保粮食安全底线多重压力下,厘清长江经济带粮食生态全要素生产率对深入推进长江大保护至关重要。基于2011—2020年长江经济带110个地级市数据,对粮食生产环节的碳排放、面源污染和生态价值进行测算,构建非期望产出框架下的投入产出体系,运用超效率Slacks-Based Measure模型和全局Malmquist-Luenberger指数考察长江经济带粮食生态全要素生产率的时空动态特征。研究发现:1)2012—2020年间长江经济带粮食生态全要素生产率总体呈增长态势,年均增长0.98%,且其增长主要源于技术进步而非技术效率提升所致。2)从时空特征看,2012—2020年长江经济带各地级市的粮食生态全要素生产率改善趋势明显,粮食综合技术效率变化的空间格局变化趋势无明显规律。3)在研究期内上游地区的粮食生态全要素生产率平均最高,然后依次是中游地区、下游地区。3个区域的粮食生态全要素生产率都处于递增状态。因此,在建设农业强国的征程中,要高度重视农业技术进步并不断提升粮食生产技术效率,以此来稳定提升长江经济带粮食生态全要素生产率,同时要根据区域禀赋差异设计针对性提升策略。

Assessment of International GNSS Service Global Ionosphere Map products over China region based on measurements from the Crustal Movement Observation Network of China

The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.

大数据发展如何影响企业全要素生产率?——基于内外部双重视角的分析

加快数字经济与实体经济深度融合是实现经济高质量发展的必然要求,探索大数据发展影响企业全要素生产率背后的机制和规律具有重要意义。以国家级大数据综合试验区设立为准自然实验,利用多期双重差分模型检验大数据发展对企业全要素生产率的影响、潜在机制及作用异质性,主要发现如下:大数据发展能有效提升企业全要素生产率,该结论在经过安慰剂检验、倾向得分匹配、替换被解释变量等一系列稳健性检验后依然成立;大数据发展能通过在企业内部优化人力资本结构和提升内部控制质量、从企业外部降低企业金融错配程度和环境不确定性,进而提升企业全要素生产率;异质性分析表明,大数据发展对高融资约束度、高管理层持股比例的企业以及非国有企业全要素生产率提升效应更加明显,与此同时,大数据发展仅提升了成熟期和衰退期企业的全要素生产率而对成长期企业影响不显著。本研究为推动企业进行更加广泛深入的数字化变革、运用大数据技术赋能高质量发展提供了新的思路。

眼底血管病变与脑小血管病及认知功能的相关性研究

目的探究脑小血管病(CSVD)总负担与眼底血管病变的相关性及眼底血管病变对CSVD相关认知功能障碍的评价意义。方法连续纳入2021年5月至2022年8月在北京朝阳医院神经内科病房查体的健康受试者290例,根据CSVD总负担评分进行分组,分为0分组129例,1分组51例,2分组42例,3分组44例,4分组24例。受试者完成头部MRI检查、眼底荧光造影及认知功能评估,并对CSVD总负担和眼底血管病变进行评价。比较不同CSVD总负担评分组间一般临床资料、化验指标、眼底血管情况及认知功能的差异。用Spearman相关性分析及线性相关分析探究眼底血管病变与CSVD总负担及认知功能的相关性。结果不同CSVD总负担组年龄、受教育年限、脑梗死/TIA、总胆固醇、低密度脂蛋白胆固醇、肌酐、蒙特利尔认知评估量表评分、简易智能状态检查量表评分、连线试验、数字符号转换试验、Stroop色词干扰试验、语言流畅性测试、视网膜中央动脉等效值(CRAE)、视网膜中央静脉等效值(CRVE)、动静脉比值(AVR)、Scheie分级、深部白质高信号、脑室旁白质高信号、基底节区扩大的血管周围间隙、腔隙、脑微出血等比较,差异有统计学意义(P<0.05,P<0.01)。Spearman相关性分析显示,CSVD总负担与CRAE、AVR呈负相关(r=-0.655,P=0.000;r=-0.679,P=0.000),与CRVE、Scheie分级呈正相关(r=0.560,P=0.000;r=0.685,P=0.000)。多因素线性分析显示,校正相关危险因素后CRAE、CRVE、AVR、Scheie分级与CSVD总负担显著相关(P<0.01),且与认知功能障碍存在相关性。结论眼底血管病变与CSVD总负担增加密切相关,可作为探究CSVD相关认知功能障碍的有效指标。

基于小样本数据驱动模型的硅片线切割质量预测

在单晶硅加工中,硅片多线切割质量检测耗时和检测成本高造成硅片质量检测难。因此,提出一种基于生成对抗网络(WGAN-GP)数据处理与自注意力残差网络(SeResNet)的硅片质量预测方法。分析多线切割的机制,确定影响硅片质量的工艺参数,建立数据样本,使用WGAN-GP对样本数据进行数据增强。在此基础上,建立基于SeResNet的硅片总体厚度偏差预测模型。以硅片的多线切割加工过程监控数据为模型验证数据,对构建的硅片总体厚度偏差预测模型进行验证。实验结果表明:该模型具有良好泛化性和高准确率,有效解决了小样本数据下的预测难题,实现了平均相对误差小于10%的硅片总体厚度偏差预测,所以基于数据驱动的硅片质量预测来代替硅片加工中的质量检测具有重要的现实意义。

太行肉牛育种指数构成分析

对应太行肉牛育种实践,综合分析太行肉牛新品种选育的目标性状以及各性状在总性能指数构成中的权重。太行肉牛新品种选育的总性能指数由体型结构、适应性、生长发育、繁殖力、泌乳力及牛肉指数等六大目标性状构成,权重分别为16%、18%、25%、25%、6%和10%。同时描述了各目标性状的具体度量与数据采集方法。以期业界同仁共同探讨、批评指正,合力推进太行肉牛的育种进程。

建筑全生命周期碳排放——内涵、计算和减量

The life-cycle assessment method,which originates from general products and services,has gradually come to be applied to investigations of the life-cycle carbon emissions(LCCE)of buildings.A literature review was conducted to clarify LCCE implications,calculations,and reductions in the context of buildings.A total of 826 global building carbon emission calculation cases were obtained from 161 studies based on the framework of the building life-cycle stage division stipulated by ISO 21930 and the basic principles of the emission factor(EF)approach.The carbon emission calculation methods and results are discussed herein,based on the modules of production,construction,use,end-of-life,and supplementary benefits.According to the hotspot distribution of a building’s carbon emissions,carbon reduction strategies are classified into six groups for technical content and benefits analysis,including reducing the activity data pertaining to building materials and energy,reducing the carbon EFs of the building materials and energy,and exploiting the advantages of supplementary benefits.The research gaps and challenges in current building LCCE studies are summarized in terms of research goals and ideas,calculation methods,basic parameters,and carbon reduction strategies;development suggestions are also proposed.

基于DEA方法的京津冀奶业效率研究

为了探究影响京津冀地区奶业效率的关键因素,分析三地奶业的发展方向,促使京津冀形成优势互补、共同发展的新发展格局,本研究采用数据包络分析法,基于2017-2022年的京津冀地区以及其他奶业强省的统计数据,对京津冀地区以及其他奶业强省的奶业效率进行了测算对比,并进一步运用DEA-Malmquist模型,对京津冀地区奶业的时序特征以及空间特征进行分析,探究近六年京津冀地区奶业的发展状况。研究表明:北京奶业综合效率、技术效率以及规模效率均达到有效,资源利用率达到了最优状态;天津奶业要素投入利用不充分,增加要素的投入将会增加该地区的奶业效率;河北省奶业规模大,技术效率低,通过提高技术进步与成母牛单产将会增加该地区的奶业效率。尽管京津冀地区的规模效率较低,但在技术进步的推动下,全要素生产率逐年上升。说明京津冀地区应发展适度的规模奶牛养殖,逐渐形成奶牛养殖产业集群,提升其规模效率,并在提升成母牛单产和促进消费的作用下,逐渐提升京津冀奶业效率。

数字经济对全要素生产率的影响研究——来自国家级大数据综合试验区的证据

基于国家级大数据综合试验区的准自然实验,运用2014—2019年280个地级市的面板数据,采用多期双重差分法实证检验数字经济对全要素生产率的影响。研究结果表明:数字经济显著提升了全要素生产率,这一结论在经过多种稳健性检验后仍然成立;中介效应检验表明,数字经济通过提高资源配置效率和促进技术创新来提升全要素生产率;异质性分析表明,数字经济对低资源禀赋城市、低数字经济发展水平城市以及智慧城市的全要素生产率具有促进作用,抑制高资源禀赋、高数字经济城市的全要素生产率,而对非智慧城市的作用则不明显。因此,应基于大数据综合试验区深度挖掘数字经济的直接作用与间接作用,同时采取差异化发展战略,培育壮大全要素生产率增长新动能。

基于DEA-Malmquist指数的长江经济带中医类医疗机构卫生资源配置效率评价

目的评估2017—2021年长江经济带中医类医疗机构的卫生资源配置效率,为科学配置中医类卫生资源提供参考依据。方法选取2018—2022年《中国卫生健康统计年鉴》中的数据作为样本,分析中医类医疗机构卫生资源的投入和产出指标。采用数据包络分析(DEA)法的BCC模型,对2021年中医类医疗机构的卫生资源配置效率进行静态分析。采用Malmquist指数模型,对2017—2021中医类医疗机构的卫生资源配置效率进行动态分析。结果2017—2021年长江经济带中医类医疗机构的投入指标(机构数、床位数及卫生技术人员数)和出院人次呈逐年下降趋势,诊疗人次呈逐年增加趋势。2021年长江经济带中医类医疗机构卫生资源综合效率总均值为0.856,有3个省市的卫生资源配置达到DEA强有效,8个省市的卫生资源配置为非DEA有效,存在投入冗余和产出不足的情况。2017—2021年长江经济带11个省市中医类医疗机构的全要素生产率指数总均值为0.863,其中10个省市的全要素生产率指数均<1。2017—2021年长江经济带中医类医疗机构全要素生产率指数呈先上升后下降再回升的总体趋势,技术效率、纯技术效率和规模效率的指数变化模式均为先增后减。结论2021年长江经济带中医类医疗机构的卫生资源配置效率亟须提升,其中规模效率是其主要制约因素,且各区域间的配置效率存在差异。因此,建议合理控制中医类医疗机构的规模,创新其管理模式,科学地制定区域规划,从而实现卫生资源配置的优化。

大数据试验区建设助推经济绿色发展的机制与实现路径

数字经济是推动经济结构转型、实现经济绿色发展的全新动能.综合运用EBM模型、双重差分模型等,以国家级大数据综合试验区设立为准自然实验,基于中国271个地级及以上城市面板数据,实证检验了大数据试验区建设对经济绿色发展的影响.研究结果表明:(1)大数据试验区的建设显著促进了经济绿色发展,经过一系列稳健性检验后依旧显著;(2)机制检验发现,地区创新水平与产业协同集聚在主回归中发挥中介效应;(3)异质性分析表明,大数据试验区建设对经济绿色发展的助推作用在地理区位、人力资本水平、城镇化水平不同的地区影响效果不同.通过分析得出了大数据试验区建设助推经济绿色发展的作用机制,提出了完善西部地区数字基础设施的建设、加大科研资金投入等对策建议,以期对当前研究有一定借鉴意义.