scholarly journals Source Identification of Cd and Pb in Typical Farmland Topsoil in the Southwest of China: A Case Study

2021 ◽  
Vol 13 (7) ◽  
pp. 3729
Author(s):  
Junji Zhang ◽  
Zeming Shi ◽  
Shijun Ni ◽  
Xinyu Wang ◽  
Chao Liao ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Phosphate Rock ◽  
Flow Direction ◽  
Isotope Analysis ◽  
Principal Component ◽  
Pb Isotope ◽  
Multivariate Statistical ◽  
Potential Toxic Metals ◽  
Linear Correlation Analysis

Cd and Pb in farmland topsoil are controlled by many factors. To identify the source of potential toxic metals in the farmland topsoil around Mianyuan River, the chemical analysis and multivariate statistical analysis are performed in this study. The results indicate the following: (1) The concentration of Cd and Pb in soil exceed the background value of Chinese soil elements. (2) Cd is significantly enriched in the whole region and Pb is locally enriched, both of them are more or less influenced by human activities. (3) The contents of Cd and Pb increase significantly following the flow direction of river. (4) Pb isotope analysis indicates that the main source of Pb in the soil include the air dust, coal and phosphate plant, and the contribution of them decreases successively. (5) Linear correlation analysis and principal component analysis show that the main sources of Cd in the soil are mining phosphate rock, air dust, phosphate plant and coal mining.

Application of the principal component analysis on geochemical data: a case study in the basement complex of Southern Ilesa area, Nigeria

2010 ◽  
Vol 4 (1-2) ◽  
pp. 239-247 ◽  
Author(s):  
Emmanuel A. Ariyibi ◽  
Samuel L. Folami ◽  
Bankole D. Ako ◽  
Taye R. Ajayi ◽  
Adebowale O. Adelusi
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Geochemical Data ◽  
Basement Complex

scholarly journals Penerapan Kansei Engineering dalam Perbandingan Desain Aplikasi Mobile Marketplace di Indonesia

2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Nucky Vilano ◽  
Setia Budi
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Mobile Application ◽  
Principal Component ◽  
Kansei Engineering ◽  
Multivariate Statistical ◽  
Christian University ◽  
Emotional Factors ◽  
Coefficient Corrélation ◽  
Major Factors

The company's application design is very important because it displays the company's image and to attract more users to purchase/utilize the application. This research applies Kansei Engineering Method to analyze the emotion or feelings of the user towards the design of a mobile application interface. Six Kansei Words and three specimens are utilised in this research, where Kansei words are selected from words related to user experience. The participants of this research consist of 54 students from Maranatha Christian University. Participants’ responses are studied using multivariate statistical analysis (e.g., Coefficient Correlation Analysis, Principal Component Analysis, and Factor Analysis). This study explores the emotional factors that occur in designing an application. This analysis shows that there are some major factors that greatly influence the design of a mobile application interface.

Scope and limitations of principal component analysis of high resolution LC-TOF-MS data: the analysis of the chlorogenic acid fraction in green coffee beans as a case study

2011 ◽  
Vol 3 (1) ◽  
pp. 144-155 ◽  
Author(s):  
Nikolai Kuhnert ◽  
Rakesh Jaiswal ◽  
Pinkie Eravuchira ◽  
Rasha M. El-Abassy ◽  
Bernd von der Kammer ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
High Resolution ◽  
Chlorogenic Acid ◽  
Principal Component ◽  
Green Coffee ◽  
Acid Fraction ◽  
Green Coffee Beans ◽  
Coffee Beans ◽  
Tof Ms

Wood anatomical variability in Early Permian ‘araucarioids’

IAWA Journal ◽  
2014 ◽  
Vol 35 (3) ◽  
pp. 307-331 ◽  
Author(s):  
Menno Booi ◽  
Isabel M. van Waveren ◽  
Johanna H.A. van Konijnenburg-van Cittert
Keyword(s):  
Principal Component Analysis ◽  
Wood Species ◽  
Principal Component ◽  
Statistical Analyses ◽  
Late Paleozoic ◽  
Individual Species ◽  
Early Permian ◽  
Multivariate Statistical Analyses ◽  
Multivariate Statistical ◽  
Anatomical Analysis

Although araucarioid wood is poor in diagnostic characters, well in excess of 200 Late Paleozoic species have been described. This study presents a largescale anatomical analysis of this wood type based on the fossil wood collections from the Early Permian Mengkarang Formation of Sumatra, Indonesia. Principal Component Analysis visualisation, in conjunction with uni- and multivariate statistical analyses clearly show the wood from the Mengkarang Formation to be a contiguous micromorphological unit in which no individual species can be distinguished. Pycnoxylic wood species described previously from this collection or other collections from the Mengkarang Formation fall within the larger variability described here. Based on comparison with wood from modern-day Araucariaceae, the Early Permian specimens can be differentiated from extant (but unrelated) “araucarioids” by a few (continuous) characters.

Sign in / Sign up

Export Citation Format

Share Document