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In this study, amorphous (Na2O)x(CaO)0.50−x(P2O5)0.50·yH2O (where x = ∼0.15 and y = ∼3) samples were prepared by a coacervate method. Thermal analysis showed that two types of water molecules were present in the coacervate structures: one type loosely bound and the other part of the phosphate structure. Structural studies using Fourier transform infrared spectroscopy (FTIR) and X-ray total diffraction revealed the samples to have very similar structures to melt-quenched glasses of comparable composition. Furthermore, no significant structural differences were observed between samples prepared using calcium nitrate as the calcium source or those prepared from calcium chloride. A sample containing ∼1 mol% Ag2O was prepared to test the hypothesis that calcium phosphate coacervate materials could be used as delivery agents for antibacterial ions. This sample exhibited significant antibacterial activity against the bacterium Psuedomonas aeruginosa. FTIR data revealed the silver-doped sample to be structurally akin to the analogous silver-free sample.

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The purpose of this research is to identify the significance of climate factors related to the significance of change of dry matter yield (DMY) of whole crop maize (WCM) by year through the exploratory data analysis. The data (124 varieties; n=993 in 7 provinces) was prepared after deletion and modification of the insufficient and repetitive data from the results (124 varieties; n=1027 in 7 provinces) of import adaptation experiment done by National Agricultural Cooperation Federation. WCM was classified into early-maturity (25 varieties, n=200), mid-maturity (40 varieties, n=409), late-maturity (27 varieties, n=234) and others (32 varieties, n=150) based on relative maturity and days to silking. For determining climate factors, 6 weather variables were generated using weather data. For detecting DMY and climate factors, SPSS21.0 was used for operating descriptive statistics and Shapiro-Wilk test. Mean DMY by year was classified into upper and lower groups, and a statistically significant difference in DMY was found between two groups (p<0.05). To find the reasons of significant difference between two groups, after statistics analysis of the climate variables, it was found that Seeding-Harvesting Accumulated Growing Degree Days (SHAGDD), Seeding-Harvesting Precipitation (SHP) and Seeding-Harvesting Hour of sunshine (SHH) were significantly different between two groups (p<0.05), whereas Seeding-Harvesting number of Days with Precipitation (SHDP) had no significant effects on DMY (p>0.05). These results indicate that the SHAGDD, SHP and SHH are related to DMY of WCM, but the comparison of R 2 among three variables (SHAGDD, SHP and SHH) couldn't be obtained which is needed to be done by regression analysis as well as the prediction model of DMY in the future study.