Poverty Reduction in China: Experiences and Measurement of Effects

This study employs the generalized method of moments(GMM)and panel vector autoregression(PVAR)models for a multi-factor quantitative dissection of China’s poverty reduction process across multiple stages,using provincial panel data from 2000 to 2019.According to our research,economic growth and social development are the key drivers of poverty reduction in China,but the trickle-down effect of economic growth is diminishing and marketization is having a lesser pro-poor effect.Public expenditure has failed to provide social protection and income redistribution benefits due to issues such as targeting error and elite capture.Increasing the efficiency of the poverty reduction system calls for adaptive adjustments.Finally,this study highlights China’s poverty reduction experiences and analyzes current challenges,which serve as inspiration for consolidating poverty-reduction achievements,combating relative poverty,and attaining countryside vitalization.

Are energy conservation and emission reduction policy measures effective for industrial structure restructuring and upgrading?

The use of energy conservation emission reduction policies to promote industrial restructuring and upgrading and thus facilitate energy conservation and emission reduction is one of the 10 important strategies of environmental management in China. The use of energy conservation emission reduction policies to promote industrial restructuring and upgrading and thus facilitate energy conservation and emission reduction is one of the important strategies of environmental management in China. Based on the systematic collection of 1,195 energy conservation emission reduction policies, we discuss the influence of individual measure and measure synergy of energy conservation and emission reduction policies respectively. The results show that the energy conservation and emission reduction policies have a significant effect on the overall promotion of industrial upgrading. The financial measures and guidance measures have a positive impact;the financial measures and guidance measures have significantly positive effect; however, the administrative measures, fiscal tax measures, and other economic measures do the opposite; the positive effect of the synergy of guidance measures and financial measures is greater than the negative effect of considering only the synergy of fiscal tax measures and other economic measures, and significantly greater than the negative effect of the synergy of administrative measures, fiscal tax measures, and other economic measures. We should strengthen and emphasize the use of the measure that has positive effect on industrial structure restructuring and upgrading individually and synergistically.

Decomposition analysis of carbon reduction measures and carbon emission changes in five areas in China

Based on the analysis of primary energy consumption structure in five main provinces or municipalities in China,the factors that affect carbon emissions in the five study areas are analyzed quantitatively and comparatively with the decomposition analysis method.Empirical results demonstrate that the decomposition models of carbon emissions can be defined as ＂municipality model＂ and ＂provincial model＂,and the population factor of ＂municipal model＂ plays a significant role in carbon emissions than that of ＂provincial model＂.Either positive or negative effects of energy structure can be found in five different areas.However,there is a general trend that energy structure effort is becoming more and more important.Based on the characteristics and trends of carbon emissions in different areas,the carbon reduction measures are proposed as well.

Some Implications of Theoretical Relation between RAW and RRW Measures on Risk Reduction Strategies

In using risk-informed approaches for ensuring safety of operating NPPs(nuclear power plants),risk importance measures obtained from PRAs(probabilistic risk assessments)of the plants are integral elements of consideration in many cases.In PSA models and applications associated with NPPs the risk importance of a particular feature(e.g.function,system,component,failure mode or operator action)can be,most generally,divided into two categories:importance with respect to risk increase potential and importance with respect to risk decrease potential.The representative of the first category,as used for practical purposes,is RAW(risk achievement worth).Representative of the second category,as mentioned in consideration of risk importance,is RRW(risk reduction worth).It can be shown that the two risk importance measures,RAW and RRW,are dependent on each other.The only parameter in this mutual dependency is probability of failure of the considered feature.The paper discusses the relation between RAW and RRW and some of its implications,including those on the general strategies for the reduction of risk imposed for the operation of the considered facility.Two general risk reduction strategies which are considered in the discussion are:a)risk reduction by decreasing the failure probability of the considered feature;and b)risk reduction while keeping the failure probability of the considered feature at the same level.Simple examples are provided to illustrate the differences between two strategies and point to main issues and conclusions.

Recent progress in research and design concepts for the characterization,testing,and photocatalysts for nitrogen reduction reaction

The reduction of molecular nitrogen(N_(2))to ammonia(NH_(3))under mild conditions is one of the most promising studies in the energy field due to the important role of NH_(3)in modern industry,production,and life.The photocatalytic reduction of N_(2)is expected to achieve clean and sustainable NH_(3)production by using clean solar energy.To date,the new photocatalysts for photocatalytic reduction of N_(2)to NH_(3)at room temperature and atmospheric pressure have not been fully developed.The major challenge is to achieve high light-absorption efficiency,conversion efficiency,and stability of photocatalysts.Herein,the methods for measuring produced NH_(3)are compared,and the problems related to possible NH_(3)pollution in photocatalytic systems are mentioned to provide accurate ideas for measuring photocatalytic efficiency.The recent progress of nitrogen reduction reaction(NRR)photocatalysts at ambient temperature and pressure is summarized by introducing charge transfer,migration,and separation in photocatalytic NRR,which provides a guidance for the selection of future photocatalyst.More importantly,we introduce the latest research strategies of photocatalysts in detail,which can guide the preparation and design of photocatalysts with high NRR activity.

A Novel Incremental Attribute Reduction Algorithm Based on Intuitionistic Fuzzy Partition Distance

Attribute reduction,also known as feature selection,for decision information systems is one of the most pivotal issues in machine learning and data mining.Approaches based on the rough set theory and some extensions were proved to be efficient for dealing with the problemof attribute reduction.Unfortunately,the intuitionistic fuzzy sets based methods have not received much interest,while these methods are well-known as a very powerful approach to noisy decision tables,i.e.,data tables with the low initial classification accuracy.Therefore,this paper provides a novel incremental attribute reductionmethod to dealmore effectivelywith noisy decision tables,especially for highdimensional ones.In particular,we define a new reduct and then design an original attribute reduction method based on the distance measure between two intuitionistic fuzzy partitions.It should be noted that the intuitionistic fuzzypartitiondistance iswell-knownas aneffectivemeasure todetermine important attributes.More interestingly,an incremental formula is also developed to quickly compute the intuitionistic fuzzy partition distance in case when the decision table increases in the number of objects.This formula is then applied to construct an incremental attribute reduction algorithm for handling such dynamic tables.Besides,some experiments are conducted on real datasets to show that our method is far superior to the fuzzy rough set based methods in terms of the size of reduct and the classification accuracy.

Industrial Carbon Reduction Potential Measurement and Scenario Prediction in Shaanxi Province

Promoting industrial carbon reduction is an inevitable step for achieving the Chinese carbon peak and neutrality targets.Based on the industrial energy consumption data of Shaanxi Province from 2011 to 2020,this study uses the IPCC calculation method to calculate the industrial carbon emissions in Shaanxi Province.The prediction model for industrial carbon emissions in Shaanxi Province was constructed based on the STIRPAT model from three aspects:population,economy,and technology.By setting three scenario models,the industrial carbon emissions from 2021 to 2035 and the time to achieve peak carbon neutrality were then predicted.The results show that the industry in Shaanxi Province cannot achieve a carbon peak under the baseline scenario,although it can achieve carbon peaking in 2030 under a low-carbon scenario or in 2025 under an enhanced low-carbon scenario.The predicted carbon peak values are 209.11 million t and 188.36 million t,respectively.Based on the results of this study,four policy recommendations are proposed:(1)strengthen publicity and education efforts to increase public participation in energy conservation and emission reduction;(2)promote the green transformation of industry and develop a green economy,including the active development of energy-saving and emission reduction technologies;(3)accelerate the implementation of industrial carbon reduction;and(4)promote the development and utilization of clean energy and increase efforts to adjust the energy structure.

Active control of turbulence for drag reduction based on the detection of near-wall streamwise vortices by wall information

The spatial relations between the measurable wall quantities （streamwise shear stress τwx, spanwise shear stress τwz, and pressure fluctuations Pw） and the near-wall streamwise vortices （NWSV） are investigated via direct numerical simulation （DNS） databases of fully developed turbulent channel flow at a low Reynolds number. In the stan- dard turbulent channel flow, the results show that all the wall measurable variables are closely associated with the NWSV. But after applying a stochastic interference, the relation based on τwx breaks down while the correlations based on Pw and τwz are still robust. Hence, two wall flow quantities based on Pw and τwz are proposed to detect the NWSV. As an appli- cation, two new control schemes are developed to suppress the near-wall vortical structures using the actuation of wall blowing/suction and obtain 16 % and 11% drag reduction, respectively.

Metallic spherical anechoic chamber for antenna pattern measurement

Anechoic chambers are used for indoor antenna measurements. The common method of constructing an anechoic chamber is to cover all inside walls by the electromagnetic absorbers. In this paper, a fully metallic spherical chamber structure is presented in which the propagation of the electromagnetic waves inside the chamber is controlled and they are guided to an absorber. In the proposed method, an appropriate quiet zone is obtained, and unlike ordinary anechoic chambers, the absorber usage amount is reduced greatly. The performance of the chamber is evaluated by simulation. The results show that the proposed method could provide a useful technique for the indoor antenna measurements.

Decision Bayes Criteria for Optimal Classifier Based on Probabilistic Measures

This paper addresses the high dimension sample problem in discriminate analysis under nonparametric and supervised assumptions. Since there is a kind of equivalence between the probabilistic dependence measure and the Bayes classification error probability, we propose to use an iterative algorithm to optimize the dimension reduction for classification with a probabilistic approach to achieve the Bayes classifier. The estimated probabilities of different errors encountered along the different phases of the system are realized by the Kernel estimate which is adjusted in a means of the smoothing parameter. Experiment results suggest that the proposed approach performs well.

Analysis of the factors affecting the fuel rate in the COREX process and improvement measures

Increasing production capacity and operating rate, reducing fuel rates and costs of hot metal （HM） are the urgent tasks for the COREX process. In this study ,the various factors on the fuel consumption of COREX are researched from the theoretical analysis based on the calculations of material balances and heat balances. Combined with the production performances and practices of COREX-2000 （ Saldanha, India） and COREX-3000 （ Baosteel ）, the technical measures of reducing the fuel rate are analyzed and the way forward of technical innovation is addressed and discussed with the standpoint of the COREX process improvement.

Research on Noise Reduction Approach of Raman-Based Distributed Temperature Sensor Based on Nonlinear Filter

The accuracy of temperature measurement is often reduced due to random noise in Raman-based distributed temperature sensor (RDTS). A noise reduction method based on a nonlinear filter is thus proposed in this paper. Compared with the temperature demodulation results of raw signals, the proposed method in this paper can reduce the average maximum deviation of temperature measurement results from 4.1°C to 1.2°C at 40.0°C, 50.0°C and 60.0°C. And the proposed method in this paper can improve the accuracy of temperature measurement of Raman-based distributed temperature sensor better than the commonly used wavelet transform-based method. The advantages of the proposed method in improving the accuracy of temperature measurement for Raman-based distributed temperature sensor are quantitatively reflected in the maximum deviation and root mean square error of temperature measurement results. Therefore, this paper proposes an effective and feasible method to improve the accuracy of temperature measurement results for Raman-based distributed temperature sensor.

Decreasing the error in the measurement of the ecosystem effective leaf area index of a Pinus massoniana forest

Decreasing the forest ecosystem leaf-area index error(LAIe)helps accurately estimate the growth and light energy utilization of aboveground foliage.Analyzing light transmission in forest ecosystems can effectively determine LAIe.The LAI-2200 plant canopy analyzer(PCA)is used extensively for rapid field-effective LAI(LAIe)measurements and primarily to measure forest canopy LAIe values.However,sometimes this parameter must also be measured in forests with small clearings.In this study,we used the LAI-2200 PCA to obtain one A-value and four B-values each for the canopy,herbaceous layer,and forest ecosystem LAIe.Field measurements showed that the three LAIe types were obviously different.In certain quadrats,the average herbaceous layer(Dicranopteris dichotoma Bernh.)LAIe apparently exceeded that of the Pinus massoniana forest ecosystem.The sources of this error were measuring and recording A-value readings for small canopies and underestimating the ecosystem LAIe.We obtained similar coefficients of determination for both the pre-recomputation and post-recomputation of the canopy and forest ecosystem LAIe(R^2C 0.96 and R^2C 0.99,respectively);thus,the error was decreased.Measuring field LAIe with the LAI-2200 PCA and recomputation should compensate for LAIe underestimation in complex forest ecosystems.

Disaster risk reduction in mountain areas: a research overview

This paper gives an account of the diverse dimensions of research on disaster risk reduction in mountain regions derived from an open call of the Journal of Mountain Science that brought 21 contributions.This special issue includes topics as diverse as landslide dynamics and mechanisms,landslide inventories and landslide susceptibility models,insights to landslide hazards and disasters and mitigation measures,disaster response and disaster risk reduction.The overall structure of the paper takes the form of three sections.The first part begins by laying out the significance of disaster risk reduction in mountain areas,whereas the second one looks at the research insights on disaster risk reduction in mountains provided by the contributions comprised in the special volume.The final section identifies areas for further research.

Calculation example of full cycle carbon emission of super deep foundation pit and carbon reduction measures

The determination of carbon emission from foundation pit engineering is a tough and complex project owing to its characteristics including large material consumption,short use time,difficult recycling and no operation stage.To overcome these limitations,the calculation boundary and calculation method for carbon emission of foundation pit project are defined in this paper,which is successfully applied in the carbon emission analysis of the actual engineering project,i.e.the construction of large-scale foundation pit of Kunming comprehensive transportation international hub.All the carbon emissions coresponding to four working stages including building materials production,building materials transportation,construction and demolition were calculated and anatomized.The results revealed that the content of CO_(2) released in the stage of building materials production accounts for 89.3%of the total carbon emission,which means the amount of building materials consumed in the engineering project is the crucial factor to control the carbon emission.Besides,two kinds of carbon reduction measures,i.e.optimization design of support scheme and recycling waste materials of internal support demolition,were explored by analyzing the proportion and average value of carbon emission from different sub project of the support structure.A pronounced effect of carbon reduction was achieved.Furthermore,both a fast calculation method of carbon emission factor of unit work volume and general carbon reduction measures are proposed in this paper,which could provide a reference and new viewpoint for the engineers and designers to calculate and analyze the carbon emission and to take effective carbon reduction measures.

电催化硝酸根还原制氨

在创新教育背景下,以硝酸根电催化还原制氨为反应案例,将科研成果融入到实验教学中。基于学生已掌握的实验技能和基础电化学知识,利用电化学测量技术、核磁共振波谱法、紫外分光光度法等探究催化剂电催化硝酸根还原制氨的性能。通过具体的实验操作,让学生进一步认识电催化的基本原理,掌握基础的电化学测量技术,激发学生对电化学合成的兴趣。本教学实验内容丰富,涉及多学科知识,满足多学科交叉融合发展需求,有利于学生创新发散思维的培养,符合新时代学科教育要求。

底流消能诱发泄洪闸闸墩振动问题分析和减振措施研究

底流式泄洪闸在大流量泄洪时常伴随着闸墩剧烈振动。针对泄洪闸闸墩振动问题,以某水电站为例,基于水弹性物理模型试验和原型观测,提出改善闸墩结构和优化水库调度方案的两种减振措施。物理模型试验为研究闸墩振动提供了数据支撑,而原型观测结果验证了模型试验的可靠性。结果表明:当泄流量为5400 m^(3)/s时,通过优化水库调度,采用“低孔+表孔”联合泄洪的方式,表孔的泄流量从单独泄洪时的5400 m^(3)/s转变为联合泄洪时的低孔泄流量3481 m^(3)/s+表孔泄流量1919 m^(3)/s,表孔闸墩的振动位移标准差可从182.3μm减小到51.7μm,振动削减效果为71.6%;当表孔泄流量为10030 m^(3)/s时,通过对闸墩进行加固,闸墩的振动位移标准差可由288.8μm减小到129.6μm,振动削减效果为55.1%。

基于ELM的超声多特征融合螺栓应力测量方法

针对传统超声波螺栓应力测量中存在的非线性和不适定性问题,提出一种基于极限学习机(ELM)的超声多特征融合螺栓应力测量方法。首先基于声弹性理论和散射理论,根据超声回波信号提取声时差及瑞利散射范围内多晶体材料中纵波的衰减系数等超声波特征参数。然后通过向量降维选择声时差、衰减系数和有效受力长度作为模型输入特征向量,建立了基于ELM的超声多特征融合螺栓应力测量模型。搭建螺栓轴向应力超声波测量实验平台,对不同材料和规格的螺栓进行螺栓应力的测量,并对比了使用传统的超声测量方法的测量结果,验证了传统超声检测方法的局限性。对比了ELM与其他机器学习方法包括BP、支持向量回归(SVR)的测量结果和精度。结果表明,提出的方法有效克服了传统超声测量方法的不足,能实现不同材料不同规格的螺栓应力测量,并且测量精度更高(平均相对误差为3.86%),泛化能力更好。

人工湿地温室气体排放影响因素及相关作用机制研究进展

概述了人工湿地的发展历史,分析了其温室气体排放研究现状,详细阐述了湿地类型、基质种类、进水C/N、植物种类及溶解氧浓度等对人工湿地温室气体排放的影响。在此基础上,综述了人工湿地温室气体减排的具体措施及其效果。最后,对人工湿地温室气体减排研究的发展方向进行了展望。

基于CRITIC-TOPSIS的中国区域碳减排能力评价及空间分析

气候变化是全人类的共同挑战,中国在气候治理行动中,期望在最短时间内完成碳排放强度全球最大降幅。实现碳达峰碳中和,需统筹处理好整体和局部的关系,有效评价区域碳减排能力。基于CRITIC-TOPSIS法对2015—2019年中国区域碳减排能力进行测度评价,结合GIS技术对碳减排能力空间特征开展分析。结果表明:指标权重随社会变化不断发生动态变化;碳减排能力区域差异显著,呈现明显的东部高,中西部低的现象;区域碳减排能力发展水平空间自相关性显著,其中高值聚类显著性更强,空间分布出现“俱乐部趋同”现象。最后,对目前区域碳减排能力存在的问题提出了相应的对策建议。