Evaluation of the New Dynamic Global Vegetation Model in CAS-ESM

In the past several decades, dynamic global vegetation models（DGVMs） have been the most widely used and appropriate tool at the global scale to investigate vegetation-climate interactions. At the Institute of Atmospheric Physics, a new version of DGVM（IAP-DGVM） has been developed and coupled to the Common Land Model（CoLM） within the framework of the Chinese Academy of Sciences＇ Earth System Model（CAS-ESM）. This work reports the performance of IAP-DGVM through comparisons with that of the default DGVM of CoLM（CoLM-DGVM） and observations. With respect to CoLMDGVM, IAP-DGVM simulated fewer tropical trees, more ＂needleleaf evergreen boreal tree＂ and ＂broadleaf deciduous boreal shrub＂, and a better representation of grasses. These contributed to a more realistic vegetation distribution in IAP-DGVM,including spatial patterns, total areas, and compositions. Moreover, IAP-DGVM also produced more accurate carbon fluxes than CoLM-DGVM when compared with observational estimates. Gross primary productivity and net primary production in IAP-DGVM were in better agreement with observations than those of CoLM-DGVM, and the tropical pattern of fire carbon emissions in IAP-DGVM was much more consistent with the observation than that in CoLM-DGVM. The leaf area index simulated by IAP-DGVM was closer to the observation than that of CoLM-DGVM; however, both simulated values about twice as large as in the observation. This evaluation provides valuable information for the application of CAS-ESM, as well as for other model communities in terms of a comparative benchmark.

Dynamic Analysis and Dimensional Synthesis of Easy-to-Protect Large-Load Robot for Extracting Fermented Grains

To improve the operation situation of difficulty and low efficiency in the extraction of fermented grains(FG),a high-load and large-workspace reclaiming robot for ceramic cylinder fermentation is designed,and a reclaiming effector is designed according to the operating characteristics.Firstly,the kinematics and singularity of the mechanism are analyzed.A multi-domain polar coordinate search method is proposed to obtain the workspace and the volume of the mechanism.Secondly,the dynamic modeling is completed and the example simulation is carried out.Thirdly,the motion-force transmission index of the mechanism is established.And based on the global transmissibility and the good-transmission workspace,the dimensional synthesis of the driving mechanism is completed by using the performance atlas-based method.Finally,aiming at the regular workspace size,stiffness and loading capacity,the Pareto optimal solution set of the executive mechanism dimension is obtained by using the multi-objective particle swarm optimization(MOPSO)algorithm.This paper can provide a theoretical basis for the optimal design and control of FG reclaiming robot.

Modeling dynamic assessment of ecosystem services based on remote sensing technology:A sampling of the Gansu grassland ecosystem

The ecosystem is important because it is the life sustaining system for human survival.Three ecosystem characteristics are:regional particularities,ecosystem complexity and conventional cultural particularities.This paper develops a remote sensing based dynamic model to assess grassland ecosystem service values involving multidisciplinary knowledge.The ecological value of grassland ecosystems is focused on using a remote sensing technique in the model,and setting up the framework for a dynamic assessing model.The grassland ecological services condition and value in 1985 is used as the benchmark.The dynamic model has two adjusting indicators:biomass and price index.The biomass is simulated using the CASA(Carnegie-Ames-Stanford Approach) model.The price index was obtained from statistics data published by the statistical bureau.Results show that the grassland ecosystem value in Gansu Province was 28.36 billion Chinese Yuan in 1985,140.37 billion in 1999 and 130.86 billion in 2002.

U-model Enhanced Dynamic Control of a Heavy Oil Pyrolysis/Cracking Furnace

This paper proposes a case study in the control of a heavy oil pyrolysis/cracking furnace with a newly extended U-model based pole placement controller(U-PPC). The major work of the paper includes: 1) establishing a control oriented nonlinear dynamic model with Naphtha cracking and thermal dynamics; 2) analysing a U-model(i.e., control oriented prototype) representation of various popular process model sets; 3)designing the new U-PPC to enhance the control performance in pole placement and stabilisation; 4) taking computational bench tests to demonstrate the control system design and performance with a user-friendly step by step procedure.

Evaluating innovation ecosystem resiliency using agent-based modeling and systems dynamics

Evaluating the resilience of the innovation ecosystem to maintain its performance,in the sense of resistance to disruption and recovery after it,has recently received more attention.Several studies have been conducted to model different ecosystems and evaluate their resilience.However,modeling the innovation ecosystem from a holistic perspective and performing a quantitative assessment of its resilience have received less attention.This paper models the innovation ecosystem holistically and evaluates its resilience index using a quantitative approach through five main steps.In the first step,a case study related to the innovation ecosystem of Iran's Ministry of Energy,called the Power Innovation Ecosystem,is modeled by combining system dynamics and agent-based modeling.Upon validating the model in the second step,the disruption of the loss of experts is investigated in the third step,and all possible actions to recover each actor are analyzed.In the fourth step,the performance of the ecosystem is simulated before and after the disruption using the data gathered in the previous steps.Finally,resilience is calculated in two different ways in the fifth step.Several improvement solutions are also suggested when considering that the resilience index of the innovation ecosystem is at a medium level.This research may assist policymakers in observing the resilience level of the innovation ecosystem based on the proposed model.By applying strategic changes to this model,they can determine the effects of their policies and make the most appropriate decisions to increase the resilience of the innovation ecosystem.

Vehicle Dynamic State Estimation： State of the Art Schemes and Perspectives

Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developments in the estimation of vehicle dynamic states. The definitions used in vehicle dynamic state estimation are first introduced, and alternative estimation structures are presented. Then, the sensor configuration schemes used to estimate vehicle velocity, sideslip angle, yaw rate and roll angle are presented. The vehicle models used for vehicle dynamic state estimation are further summarized, and representative estimation approaches are discussed. Future concerns and perspectives for vehicle dynamic state estimation are also discussed.

我国环境规制效率的区域差异及变化轨迹——基于30个省份的面板数据

“十四五”时期是深入打好污染防治攻坚战、实现生态环境质量改善由量变到质变的关键时期,提升环境规制效率是推进生态文明建设的必然选择。论文基于2009—2020年30个省份的面板数据,采用基于非期望产出的超效率SBM模型和Malmquist指数模型以及加权求和法,对环境规制静态、动态和综合效率分别进行了测度,并利用核密度估计、变异系数和基尼系数法,探究我国东部、中部、西部和东北部四大区域环境规制效率的区域差异和动态变化轨迹。研究结果表明:我国省际环境规制效率差距较大,四大区域呈现非均衡特征;环境规制效率较高的省份主要分布在东部地区,西部地区的环境规制效率提升空间和潜力最大,中部和东北地区的环境规制效率上升趋势较弱。

钢坯定重动态智能调控技术探讨

近年来,随着棒材生产多线切分常态化,高速棒材生产技术及钢坯免加热直接轧制技术日益成熟,并得到广泛应用。在棒材生产过程中,许多企业实现了钢坯快速输送并直接轧制,生产效率大大提高。但是,轧钢生产线要求连铸工序对钢坯进行定重控制,采用跨单位电话通知方式进行人工调整,响应速度慢、稳定性差,难以满足快节奏的生产模式,导致轧后通尺量大,严重制约成材率指标的提高。因此,从连铸到轧钢工序系统考虑,通过建立数学模型,运用在线检测、信息计算技术,实现生产过程的动态调整,达到无人干预并自动控制的目的,为生产线实现高效智能制造提供切实可行的技术控制方法。

基于混频动态因子模型的数字经济状态指数构建与预测研究——以杭州市为例

我国数字经济规模不断扩大,在经济发展、税收、就业等方面发挥着越来越重要的作用。为及时了解数字经济发展现状、对数字经济发展趋势做出预判,有必要构建刻画数字经济发展状态的数字经济状态指数。本文提出运用混频动态因子模型,从不同频度的数据中提取因子构建月度数字经济状态指数的方法,并运用杭州市季度数字经济产业增加值和月度数字经济产业营业收入数据进行实证分析,构建了杭州市月度数字经济状态指数。实证结果表明,所构建的月度数字经济状态指数能很好地刻画数字经济发展状态,且可以为预测季度数字经济状态指数提供有用信息,从而为政府决策提供理论支持。

开放经济动态随机一般均衡模型下最优货币政策和货币状况指数研究——基于1992—2022年中国数据的理论和实证分析

本文构建开放经济下的新凯恩斯动态随机一般均衡模型,模拟显示在外部冲击下,利率、汇率和最终目标高度相关。以理论模型为基础对最优货币政策进行探究,发现其政策权重受消费者、生产者和中央银行的行为等模型参数的影响。进一步构建货币状况指数(MCI),其权重不仅取决于商品市场、货币市场和利率平价参数等的变化,还依赖于最优货币政策参数的变化。根据1992—2022年数据进行实证研究发现,最优货币政策参数为1.1823,意味着我国央行的货币政策是逆周期操作的,且赋予经济增长以更大的权重;估计出MCI的权重为0.7867,意味着实际利率上升1%相当于实际汇率下降0.79%,实际利率变动的影响弱于实际汇率。最后本文研究表明货币状况指数可以作为宏观经济目标变动的先行指标。

数字经济对高校科技成果转化效率的影响

党的二十大报告强调了发展数字经济和促进科技成果转化的重要性。对于科技成果产出的重要场所高校而言,数字经济发展能否提高其科技成果转化效率成为亟待探究的问题。研究首先在理论上论述了数字经济发展对高校科技成果转化效率的影响机理,然后使用动态面板模型对这一机理进行检验。研究发现,数字经济发展能显著提高高校科技成果转化效率;在东部,优质高校数量越多、高新技术企业越密集的地区,数字经济对高校科技成果转化效率的促进作用越大。鉴于此,建议加强数字经济基础设施投入力度,支持中西部地区数字经济发展;搭建高校科技成果交流的数字化平台,加快培养数字经济等新兴专业紧缺人才;培育优质高新技术企业,利用数字技术构建高校—市场—政府协同创新联盟。

基于结构方程模型的广州市相对贫困空间分异及动力机制研究

我国农村脱贫攻坚取得全面胜利,相对贫困问题将是未来贫困研究的关键。文章以广州市为例,通过多源综合数据分析相对贫困分布规律和空间聚集特征,并结合结构方程模型探讨相对贫困空间分异的动力机制。研究表明:(1)广州市相对贫困呈现“高—低—高”的圈层分布特征;(2)根据结构方程模型路径分析结果,基础设施、人力资本、经济活力、自然环境等因素对广州市相对贫困空间分异形成了多重路径的影响关系;(3)结合地理区位和城乡差异划分内城衰落型、城乡融合型和乡村滞后型3种贫困模式,并针对不同贫困空间类型提出差异化的贫困治理建议,以期为后扶贫时代城乡相对贫困的精细化治理提供理论基础。

中国工业低碳全要素生产率的测算及分解——基于动态EBM-MI指数模型

采用动态EBM-MI指数模型测度2000—2015年中国33个工业行业的低碳全要素生产率,并将低碳全要素生产率分解为规模效率变动(SEC)、动态进步(DPC)、纯技术进步(TPC)、纯技术效率变动(PTEC)以及环境效率变动(EC)五项。研究结果表明:1.中国工业低碳全要素生产率的年均增长率为4.3%,其历年指数大都围绕1波动。在五个分解项中,技术进步对低碳全要素生产率增长发挥的作用最大。2.绝大多数工业行业的低碳全要素生产率是增长的,且增速具有较为明显的行业异质性,技术密集型、清洁型工业的增速明显高于其他行业,污染密集型工业的增速最为缓慢。

The effectiveness of different wear indicators in quantifying wear on railway wheels of freight wagons

Railway infrastructure relies on the dynamic interaction between wheels and rails;thus,assessing wheel wear is a critical aspect of maintenance and safety.This paper focuses on the wheel-rail wear indicator T-gamma(Tγ).Amidst its use,it becomes apparent that Tγ,while valuable,fails to provide a comprehensive reflection of the actual material removal and actual contact format,which means that using only Tγas a target for optimization of profiles is not ideal.In this work,three different freight wagons are evaluated:a meter-gauge and a broad-gauge heavy haul vehicles from South American railways,and a standard-gauge freight vehicle operated in Europe,with different axle loads and dissimilar new wheel/rail profiles.These vehicles are subjected to comprehensive multibody simulations on various tracks.The simulations aimed to elucidate the intricate relationship between different wear indicators:Tγ,wear index,material removal,and maximum wear depth,under diverse curves,non-compensated lateral accelerations(A_(nc)),and speeds.Some findings showed a correlation of 0.96 between Tγand wear depth and 0.82 between wear index and material removed for the outer wheel.From the results,the Tγis better than the wear index to be used when analyzing wear depth while the wear index is more suited to foresee the material lost.The results also show the low influence of A_(nc)on wear index and Tγ.By considering these factors together,the study aims to improve the understanding of wheel-rail wear by selecting the best wear analysis approaches based on the effectiveness of each parameter.

Modeling the dynamic performance of transportation infrastructure using panel data model in state-space specifications

In this study,different modeling approaches used in panel data for performance forecast of transportation infrastructure are firstly reviewed,and the panel data models(PDMs)are highlighted for longitudinal data sets.The state-space specification of PDMs are proposed as a framework to formulate dynamic performance models for transportation facilities and panel data sets are used for estimation.The models could simultaneously capture the heterogeneity and update forecast through inspections.PDMs are applied to tackle the cross-section heterogeneity of longitudinal data,and PDMs in state-space forms are used to achieve the goal of updating performance forecast with new coming data.To illustrate the methodology,three classes of dynamic PDMs are presented in four examples to compare with two classes of static PDMs for a group of composite pavement sections in an airport in east China.Estimation results obtained by ordinary least square(OLS)estimator and system generalized method of moments(SGMM)are compared for two dynamic instances.The results show that the average root mean square errors of dynamic specifications are all significantly lower than those of static counterparts as prediction continues over time.There is no significant difference of prediction accuracy between state-space model and curve shifting model over a short time.In addition,SGMM does not obtain higher prediction accuracy than OLS in this case.Finally,it is recommended to specify the inspection intervals as several constants with integer multiples.

太忻一体化经济区土地利用变化及驱动力分析

分析研究区的土地利用变化及其驱动力,能够为开展土地开发与管理提供科学依据.以太忻一体化经济区为研究区,基于1990年、2000年、2010年、2020年4期Landsat影像数据,运用动态度、PLUS模型等方法,探究了1990年—2020年土地利用的时空变化状况及其主要影响因子.结果表明:草地、林地、耕地是主要用地景观;建设用地景观面积持续增加,其他土地利用类型的景观面积均呈波动变化;土地利用景观变化速率差异明显,建设用地的变化速率最大,建设用地和林地动态度呈正向变化;经济区土地利用景观变化的主要驱动力是社会经济因素.

基于GRA的强夯指标影响因素分析及预估模型建立

为消除强夯法施工控制指标影响因素权重判定过程中,因人为主观因素产生的误差,文中提出以夯击沉降量、有效加固深度及夯击间距作为目标,选取诸如土体参数、夯锤形态及施工工艺等因素作为行为因子,以灰色关联理论建立其间的相互联系,分析各影响因素的关联度。在此基础之上,以多元回归分析为手段,建立控制指标力学-经验模型。结果表明,对于夯击沉降量、有效加固深度及夯击间距而言,需以夯击能、土体重度及夯锤底面积作为主要控制因素;建立的力学-经验模型具有较高的精度,R2均在0.9以上,可为强夯施工初期各项施工工艺、土体参数、施工设备的选择提供理论参照。

基于互联网+动态模型的粮食综合评价体系

论文将互联网平台与粮食系统跨界融合,构建了基于互联网+动态模型的粮食综合评价指标体系。该体系借助Hadoop进行大数据处理来源于联合国开发署网站的数据集,对可持续性、公平性、效率、盈利能力四个一级指标分别用不同算法进行评价;利用层次分析法计算综合评价得分;对一级指标的影响因素分别建立线性回归模型并判断显著性;通过动态模型建立常微分方程模型dx/dt=-k(x-A)并求特解,以改进和预测该体系更改回归模型变量的目标值后何时能实现。用该评价体系对中国和澳大利亚的粮食体系评估与结果可视化。结果表明,该优化后的评价体系能通过指标发展趋势分析出决定粮食安全的主要因素,得出总体评价且避免了总体水平掩盖个别指标的状况,且能利用互联网的特性动态更新数据集与模型结果。

不同卧位机械通气病毒性肺炎预后状况及影响因素和预测模型构建

目的探究不同卧位机械通气病毒性肺炎患者预后及影响因素,并构建预测模型,为改善病毒性肺炎患者预后提供参考。方法选取2020年1月—2023年5月收治的363例行机械通气病毒性肺炎患者,统计不同卧位机械通气病毒性肺炎患者预后状况,据28 d预后情况分为预后不良和预后良好组,分析预后不良的影响因素,构建预后不良的Nomogram预测模型,并采用受试者工作特征(ROC)曲线、决策曲线分析(DCA)、临床影响曲线(CIC)行外部验证。结果行俯卧位机械通气病毒性肺炎患者28 d预后不良率为17.19%(33/192),预后良好率为82.81%(159/192);行仰卧位机械通气病毒性肺炎患者28 d预后不良率为28.65%(49/171),预后良好率为71.35%(122/171)。多因素Logistic回归分析结果显示,病原学情况、机械通气体位、机械通气时间、氧合指数、动态肺顺应性、并发急性呼吸窘迫综合征、淋巴细胞计数、淀粉样蛋白A均是机械通气病毒性肺炎患者预后不良的独立影响因素(P<0.01)。基于多因素Logistic回归分析所得的独立影响因素绘制机械通气病毒性肺炎患者预后不良的Nomogram预测模型,ROC曲线分析显示,该模型曲线下面积为0.903(95%CI:0.868,0.938),DCA曲线显示该模型具有较好的临床净获益,CIC曲线显示该预测模型可在阈值概率范围内有效区分机械通气病毒性肺炎预后不良高危患者。结论病毒性肺炎患者行俯卧位机械通气预后要好于仰卧位机械通气,机械通气病毒性肺炎患者预后不良受病原学情况、机械通气体位、机械通气时间、氧合指数、动态肺顺应性、并发急性呼吸窘迫综合征、淋巴细胞计数、淀粉样蛋白A影响,基于上述因素构建预测模型具有较高预测效能,临床效用良好。

基于动态CRITIC赋权的中国金融压力指数构建与金融风险识别

合理测度和准确识别金融市场风险,对于稳定经济、有效防范金融风险意义重大。依据中国金融市场特征,本文采用动态CRITIC法计算权重并建立金融压力指数测度模型,通过非参数统计核密度法和B-N数据分解法对金融压力指数的分布和金融风险状态进行估计与识别,采用马尔科夫区制转换模型检验高低风险转换概率,并与基于确定项进行识别的结果进行对比分析。研究表明:基于动态CRITIC赋权的金融压力指数更能反映金融市场的极端值和金融风险,随机冲击是影响我国金融压力指数的重要因素,两种金融风险识别方法均可识别金融风险状态且各有优势,研究中可以互为补充。今后应建立更加完善的风险测度指标体系,进一步完善监管制度,加强对金融风险的宏观审慎管理和防范。