Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production ...Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.展开更多
随着分布式能源的发展,传统用户具备发电能力而成为产消者(production and consumption users,PCU)的趋势愈演愈烈,该文主要研究了同一微能网下大量产消者的协同运行问题。电价不确定性和产消者响应给微能网协同不同利益主体的PCU之间...随着分布式能源的发展,传统用户具备发电能力而成为产消者(production and consumption users,PCU)的趋势愈演愈烈,该文主要研究了同一微能网下大量产消者的协同运行问题。电价不确定性和产消者响应给微能网协同不同利益主体的PCU之间的调度带来困难。在此背景下提出考虑产消者响应与电价不确定性的微能网与产消者混合博弈优化策略。首先,构建产消者响应模型和电价不确定性模型,引入效用函数来描述PCU的满意程度,采用鲁棒优化和机会约束方法描述电价的不确定性与新能源出力的不确定性。其次,构建混合博弈模型,即上层微能网运营商(integrated energy operator,IEO)与下层PCU之间的主从博弈模型和下层PCU联盟之间的合作博弈模型。上层IEO作为主从博弈的领导者以运行成本最小化为目标,通过为产消者制定电价、热价引导产消者的用能需求;下层产消者作为跟随者,以效益最大为目标通过合作方式对IEO的决策进行产消者响应。PCU之间的合作博弈以纳什议价的方式进行,将PCU模型等效为联盟收益最大化和合作分配两个子问题。基于KKT条件利用Big-M法和Mc Cormick包络法将双层问题转换为单层混合整数线性规划问题求解主从博弈,结合交替方向乘子法(alternating direction multiplier method,ADMM)求解下层合作博弈。结果表明,该文所提策略有效协调了微能网与PCU的调度并保证了PCU合作联盟的公平性。展开更多
The epidemiology of HIV-1 varies in different areas of the world, and it is possible that this complexity may leave unique footprints in the viral genome. Thus, we attempted to find significant patterns in global HIV-...The epidemiology of HIV-1 varies in different areas of the world, and it is possible that this complexity may leave unique footprints in the viral genome. Thus, we attempted to find significant patterns in global HIV-1 genome sequences. By applying the rule inference algorithm RIPPER (Repeated Incremental Pruning to Produce Error Reduction) to multiple sequence alignments of Env sequences from four classes of compiled datasets, we generated four sets of signature patterns. We found that these patterns were able to distinguish southeastern Asian from non- southeastern Asian sequences with 97.5% accuracy, Chinese from non-Chinese sequences with 98.3% accuracy, African from non-African sequences with 88.4% accuracy, and southern African from non-southern African sequences with 91.2% accuracy. These patterns showed different associations with subtypes and with amino acid positions. In addition, some signature patterns were characteristic of the geographic area from which the sample was taken. Amino acid features corresponding to the phylogenetic clustering of HIV-1 sequences were consistent with some of the deduced patterns. Using a combination of patterns inferred from subtypes B, C, and all subtypes chimeric with CRF01_AE worldwide, we found that signature patterns of subtype C were extremely common in some sampled countries (for example, Zambia in southern Africa), which may hint at the origin of this HIV-1 subtype and the need to pay special attention to this area of Africa. Signature patterns of subtype B sequences were associated with different countries. Even more, there are distinct patterns at single position 21 with glycine, leucine and isoleucine corresponding to subtype C, B and all possible recombination forms chimeric with CRF01_AE, which also indicate distinct geographic features. Our method widens the scope of inference of signature from geographic, genetic, and genomic viewpoints. These findings may provide a valuable reference for epidemiological research or vaccine design.展开更多
基金the Special Project of the National Science Foundation of China(NSFC)“Open Development of China’s Trade and Investment:Basic Patterns,Overall Effects,and the Dual Circulations Paradigm”(Grant No.72141309)NSFC General Project“GVC Restructuring Effect of Emergent Public Health Incidents:Based on the General Equilibrium Model Approach of the Production Networks Structure”(Grant No.72073142)+1 种基金NSFC General Project“China’s Industrialization Towards Mid-and High-End Value Chains:Theoretical Implications,Measurement and Analysis”(Grant No.71873142)the Youth project of The National Social Science Fund of China“Research on the green and low-carbon development path and policy optimization of China’s foreign trade under the goal of‘dual carbon’”(Grant No.22CJY019).
文摘Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.
文摘随着分布式能源的发展,传统用户具备发电能力而成为产消者(production and consumption users,PCU)的趋势愈演愈烈,该文主要研究了同一微能网下大量产消者的协同运行问题。电价不确定性和产消者响应给微能网协同不同利益主体的PCU之间的调度带来困难。在此背景下提出考虑产消者响应与电价不确定性的微能网与产消者混合博弈优化策略。首先,构建产消者响应模型和电价不确定性模型,引入效用函数来描述PCU的满意程度,采用鲁棒优化和机会约束方法描述电价的不确定性与新能源出力的不确定性。其次,构建混合博弈模型,即上层微能网运营商(integrated energy operator,IEO)与下层PCU之间的主从博弈模型和下层PCU联盟之间的合作博弈模型。上层IEO作为主从博弈的领导者以运行成本最小化为目标,通过为产消者制定电价、热价引导产消者的用能需求;下层产消者作为跟随者,以效益最大为目标通过合作方式对IEO的决策进行产消者响应。PCU之间的合作博弈以纳什议价的方式进行,将PCU模型等效为联盟收益最大化和合作分配两个子问题。基于KKT条件利用Big-M法和Mc Cormick包络法将双层问题转换为单层混合整数线性规划问题求解主从博弈,结合交替方向乘子法(alternating direction multiplier method,ADMM)求解下层合作博弈。结果表明,该文所提策略有效协调了微能网与PCU的调度并保证了PCU合作联盟的公平性。
基金the funding by the Chinese Key National Science and Technology Program in the 12th Five-Year Period, grant 2012ZX10001006-002
文摘The epidemiology of HIV-1 varies in different areas of the world, and it is possible that this complexity may leave unique footprints in the viral genome. Thus, we attempted to find significant patterns in global HIV-1 genome sequences. By applying the rule inference algorithm RIPPER (Repeated Incremental Pruning to Produce Error Reduction) to multiple sequence alignments of Env sequences from four classes of compiled datasets, we generated four sets of signature patterns. We found that these patterns were able to distinguish southeastern Asian from non- southeastern Asian sequences with 97.5% accuracy, Chinese from non-Chinese sequences with 98.3% accuracy, African from non-African sequences with 88.4% accuracy, and southern African from non-southern African sequences with 91.2% accuracy. These patterns showed different associations with subtypes and with amino acid positions. In addition, some signature patterns were characteristic of the geographic area from which the sample was taken. Amino acid features corresponding to the phylogenetic clustering of HIV-1 sequences were consistent with some of the deduced patterns. Using a combination of patterns inferred from subtypes B, C, and all subtypes chimeric with CRF01_AE worldwide, we found that signature patterns of subtype C were extremely common in some sampled countries (for example, Zambia in southern Africa), which may hint at the origin of this HIV-1 subtype and the need to pay special attention to this area of Africa. Signature patterns of subtype B sequences were associated with different countries. Even more, there are distinct patterns at single position 21 with glycine, leucine and isoleucine corresponding to subtype C, B and all possible recombination forms chimeric with CRF01_AE, which also indicate distinct geographic features. Our method widens the scope of inference of signature from geographic, genetic, and genomic viewpoints. These findings may provide a valuable reference for epidemiological research or vaccine design.
