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It has been very significant to visualize time series big data. In the paper we shall discuss a new analysis method called "statistical shape analysis" or "geometry driven statistics" on time series statistical data in economics. In the paper, we analyse the agriculture, value added and industry, value added (percentage of GDP) changes from 2000 to 2010 in Asia. We handle the data as a set of landmarks on a two-dimensional image to see the deformation using the principal components. The point of the analysis method is the principal components of the given formation which are eigenvectors of its bending energy matrix. The local deformation can be expressed as the set of non-Affine transformations. The transformations give us information about the local differences between in 2000 and in 2010. Because the non-Affine transformation can be decomposed into a set of partial warps, we present the partial warps visually. The statistical shape analysis is widely used in biology but, in economics, no application can be found. In the paper, we investigate its potential to analyse the economic data.

By simulating the electron paramagnetic resonance (EPR) and optical spectra on the basis of the 120x120 complete energy matrix, this paper determines the local lattice structure parameters R(1) and R(2) for MCl:V(2+) (M=Na, K, Rb) systems at 77 K, 195 K and RT (room temperature 295 K or 302 K), respectively. The theoretical results indicate that there exists a compressed distortion in MCl:V(2+) systems. Meanwhile, it finds that the structure parameters R(1), R(2) and vertical bar Delta R vertical bar (= R(1) - R(2)) increase with the rising temperature. Subsequently, from the analysis it concludes that the relation of EPR parameter D vs. Delta R is approximately linear. Finally, the effects of orbital reduction factor k on the g factors for the three systems have been discussed.

The increase in renewable sources in the energy matrix of the countries is an effort to reduce dependency on crude oil and the environmental impacts associated with its use. In order to help overcome the lack of widely accepted quality standards for fuel ethanol and to guarantee its competitiveness in the international trade market, the NMIs have been working to develop certified reference materials for bio-fuels and measurement methods. Inorganic impurities such as Cu, Na and Fe may be present in the fuel ethanol and their presence is associated with corrosion and the formation of oxide deposits in some engine parts. The key comparison CCQM-K100 was carried out under the auspices of the Inorganic Analysis Working Group (IAWG) and the coordination of the National Institute of Metrology, Quality and Technology (INMETRO). The objective of this key comparison was to compare the measurement capabilities of the participants for the determination of Cu in fuel ethanol. Ten NMIs participated in this exercise and most of them used the isotopic dilution method for determining the amount of Cu. The median was chosen as key comparison reference value (KCRV). The assigned KCRV for the Cu content was 0.3589 ?g/g with a combined standard uncertainty of 0.0014 ?g/g. In general, there is a good agreement among the participants' results. Main text. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).