The aggregation index (AI) is a classical ecology calculation method, which has been widely used for measuring the aggregation level of spatial patterns within a landscape scale in landscape ecological studies. Howeve...The aggregation index (AI) is a classical ecology calculation method, which has been widely used for measuring the aggregation level of spatial patterns within a landscape scale in landscape ecological studies. However, it has certain limitions. For instance, identical results can be obtained by AI even when the shape and number of landscape patches are totally different in two landscape units. Furthermore, the value of AI approaches to 1 if the landscape patch is large enough. To solve these problems, a logical limitation of the original AI equation was revised firstly. Secondly, an improved AI-J was developed based on the awareness of the effects of spatial distribution characteristics of patches and changing spatial scale on AI operation. Finally, the accuracy of AI and AI-J results were evaluated through a case study of city green patches in Chengdu, P. R. China. The results show that the calculated result of AI-J is more precise than that of AI and AI-J can be used to compare a certain landscape class under different spatial scales.展开更多
The author [Pakkar, M.S. (2014) Using Data Envelopment Analysis and Analytic Hierarchy Process to Construct Composite Indicators. Journal of Applied Operational Research, 6(3), 174-187.] recently proposed a multiplica...The author [Pakkar, M.S. (2014) Using Data Envelopment Analysis and Analytic Hierarchy Process to Construct Composite Indicators. Journal of Applied Operational Research, 6(3), 174-187.] recently proposed a multiplicative approach using Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP) to reflect the priority weights of indicators in constructing composite indicators (CIs). Nonetheless, this approach is limited to the situations with a single level hierarchy which might not satisfy the needs of a multiple level hierarchy. Therefore, the current paper extends this approach to the situations in which the indicators of similar characteristics can be grouped into sub-categories and further linked into categories to form a three-level hierarchical structure. An illustrative example of road safety performance for a set of European countries highlights the usefulness of the proposed “extended approach”.展开更多
Colloform pyrite is a special form of nano-micro polycrystalline aggregation growth, for which a suitable term is ＂aggregates of nano-micro crystals＂. This kind of colloform texture is observed in various geological...Colloform pyrite is a special form of nano-micro polycrystalline aggregation growth, for which a suitable term is ＂aggregates of nano-micro crystals＂. This kind of colloform texture is observed in various geological bodies, such as ancient sedimentary rocks, modern marine and lake sediments, various types of ore deposits, and modern seafloor hydrothermal vents. This paper summarizes the latest developments and research into the definition, formation mechanisms, and environmental indications of colloform pyrite. There appears to be three main formation mechanisms of colloform pyrite： pseudomorphic replacement; biogenic precipitation; and inorganic precipitation. The morphology, particle size, trace element content and preferential growth orientations of coUoform pyrite microcrystals can be important indicators for sedimentary environments, hydrothermal activity, and ore-forming processes. We suggest that the microscopic features of nano-micro crystals in colloform pyrite and their aggregation growth patterns need further investigation. The relationships between formation mechanisms of colioform pyrite, organic activity and depositional environments require further exploration. To reveal the nature of nano-micro grain aggregation growth in colloform pyrite and analyse its growth environment and evolutionary history, it is supposed to apply nanoscientific and nanotechnological methods, further integrate consideration of macroscopic geological backgrounds and microscopic mineral growth phenomena, combine high-resolution imaging systems and in situ quantitative microanalysis methods and constitute a mergence of earth science, thermodynamics and kinetics, life science, material science, and chemistry in the study.展开更多
基金Funded by the National 11th Five-Year Technology Based PlanTopic of China (No. 2006BAJ05A13)
文摘The aggregation index (AI) is a classical ecology calculation method, which has been widely used for measuring the aggregation level of spatial patterns within a landscape scale in landscape ecological studies. However, it has certain limitions. For instance, identical results can be obtained by AI even when the shape and number of landscape patches are totally different in two landscape units. Furthermore, the value of AI approaches to 1 if the landscape patch is large enough. To solve these problems, a logical limitation of the original AI equation was revised firstly. Secondly, an improved AI-J was developed based on the awareness of the effects of spatial distribution characteristics of patches and changing spatial scale on AI operation. Finally, the accuracy of AI and AI-J results were evaluated through a case study of city green patches in Chengdu, P. R. China. The results show that the calculated result of AI-J is more precise than that of AI and AI-J can be used to compare a certain landscape class under different spatial scales.
文摘The author [Pakkar, M.S. (2014) Using Data Envelopment Analysis and Analytic Hierarchy Process to Construct Composite Indicators. Journal of Applied Operational Research, 6(3), 174-187.] recently proposed a multiplicative approach using Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP) to reflect the priority weights of indicators in constructing composite indicators (CIs). Nonetheless, this approach is limited to the situations with a single level hierarchy which might not satisfy the needs of a multiple level hierarchy. Therefore, the current paper extends this approach to the situations in which the indicators of similar characteristics can be grouped into sub-categories and further linked into categories to form a three-level hierarchical structure. An illustrative example of road safety performance for a set of European countries highlights the usefulness of the proposed “extended approach”.
基金funded by the National Natural Science Foundation of China(41272062)the Fundamental Research Funds for the Northeastern University(N150106001)+1 种基金the Open Foundation Of State Key Laboratory Of Ore Deposit Geochemistry(Institute Of Geochemistry,Chinese Academy Of Sciences,Guiyang)(201308)the Open Foundation Of Key Laboratory Of Mineralogy and Metallogeny in Guangzhou Institute of Geochemistry,Chinese Academy of Sciences(KLMM20150101)
文摘Colloform pyrite is a special form of nano-micro polycrystalline aggregation growth, for which a suitable term is ＂aggregates of nano-micro crystals＂. This kind of colloform texture is observed in various geological bodies, such as ancient sedimentary rocks, modern marine and lake sediments, various types of ore deposits, and modern seafloor hydrothermal vents. This paper summarizes the latest developments and research into the definition, formation mechanisms, and environmental indications of colloform pyrite. There appears to be three main formation mechanisms of colloform pyrite： pseudomorphic replacement; biogenic precipitation; and inorganic precipitation. The morphology, particle size, trace element content and preferential growth orientations of coUoform pyrite microcrystals can be important indicators for sedimentary environments, hydrothermal activity, and ore-forming processes. We suggest that the microscopic features of nano-micro crystals in colloform pyrite and their aggregation growth patterns need further investigation. The relationships between formation mechanisms of colioform pyrite, organic activity and depositional environments require further exploration. To reveal the nature of nano-micro grain aggregation growth in colloform pyrite and analyse its growth environment and evolutionary history, it is supposed to apply nanoscientific and nanotechnological methods, further integrate consideration of macroscopic geological backgrounds and microscopic mineral growth phenomena, combine high-resolution imaging systems and in situ quantitative microanalysis methods and constitute a mergence of earth science, thermodynamics and kinetics, life science, material science, and chemistry in the study.
