The Relationship Between Market Structure and Market Performance in Real Estate Based on Market Concentration Rate and Principal Component Analysis

Author(s):  
Hong Zhang ◽  
Nan Guo
Energies ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 213
Author(s):  
Chao Cui ◽  
Suoliang Chang ◽  
Yanbin Yao ◽  
Lutong Cao

Coal macrolithotypes control the reservoir heterogeneity, which plays a significant role in the exploration and development of coalbed methane. Traditional methods for coal macrolithotype evaluation often rely on core observation, but these techniques are non-economical and insufficient. The geophysical logging data are easily available for coalbed methane exploration; thus, it is necessary to find a relationship between core observation results and wireline logging data, and then to provide a new method to quantify coal macrolithotypes of a whole coal seam. In this study, we propose a L-Index model by combing the multiple geophysical logging data with principal component analysis, and we use the L-Index model to quantitatively evaluate the vertical and regional distributions of the macrolithotypes of No. 3 coal seam in Zhengzhuang field, southern Qinshui basin. Moreover, we also proposed a S-Index model to quantitatively evaluate the general brightness of a whole coal seam: the increase of the S-Index from 1 to 3.7, indicates decreasing brightness, i.e., from bright coal to dull coal. Finally, we discussed the relationship between S-Index and the hydro-fracturing effect. It was found that the coal seam with low S-Index values can easily form long extending fractures during hydraulic fracturing. Therefore, the lower S-Index values indicate much more favorable gas production potential in the Zhengzhuang field. This study provides a new methodology to evaluate coal macrolithotypes by using geophysical logging data.


2018 ◽  
Vol 10 (2) ◽  
pp. 312 ◽  
Author(s):  
Ana-Maria Săndică ◽  
Monica Dudian ◽  
Aurelia Ştefănescu

EU countries to measure human development incorporating the ambient PM2.5 concentration effect. Using a principal component analysis, we extract the information for 2010 and 2015 using the Real GDP/capita, the life expectancy at birth, tertiary educational attainment, ambient PM2.5 concentration, and the death rate due to exposure to ambient PM2.5 concentration for 29 European countries. This paper has two main results: it gives an overview about the relationship between human development and ambient PM2.5 concentration, and second, it provides a new quantitative measure, PHDI, which reshapes the concept of human development and the exposure to ambient PM2.5 concentration. Using rating classes, we defined thresholds for both HDI and PHDI values to group the countries in four categories. When comparing the migration matrix from 2010 to 2015 for HDI values, some countries improved the development indicator (Romania, Poland, Malta, Estonia, Cyprus), while no downgrades were observed. When comparing the transition matrix using the newly developed indicator, PHDI, the upgrades observed were for Denmark and Estonia, while some countries like Spain and Italy moved to a lower rating class due to ambient PM2.5 concentration.


1974 ◽  
Vol 52 (8) ◽  
pp. 1947-1972
Author(s):  
K. A. Kershaw

The relationship of the sedge meadows lying between raised-beach ridges at the Pen Island site in NW Ontario is described using principal-component analysis. Three major trends are detected following moss hummock formation, depth of water table, and pH. The data also show a progressive sequence from the young meadows with few hummocks and high pH to the older meadows where marked hummock formation has occurred and where the overall pH is lower. Six noda have subsequently been extracted as the central plant associations characteristic of the area.


Author(s):  
Kosuke Shimizu ◽  
Tetsuya Matsukawa ◽  
Risa Kanematsu ◽  
Kimihisa Itoh ◽  
Shinya Kanzaki ◽  
...  

Abstract Headspace solid-phase microextraction combined with GC/MS (HS-SPME-GC/MS) is one of the strongest tools for comprehensive analysis of volatile compounds and has been used to analyze aromatic components of mango and investigate its varietal characteristics. In this study, profiling of aroma compounds in 17 mango cultivars, grown in the same green house to exclude the effect of environmental factors, was conducted and the patterns were subjected to principal component analysis (PCA) to identify the relationship between the aroma components and cultivars. Fifty-nine different volatile constituents were detected from the blends of these 17 mango cultivars. The cultivars were divided into four clusters using PCA based on the volatile components determined in the study. Aiko was found to mainly contain δ-3-carene and showed a composition more similar to its pollen parent, Irwin, than to its seed parent, Chiin Hwang No. 1.


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