Stronger and Faster Degradable Biobased Poly(propylene sebacate) as Shape Memory Polymer by Incorporating Boehmite Nanoplatelets

Boehmite (BM) nanoplatelets were adopted to compound with fully biobased poly­(propylene sebacate) (PPSe) to form the shape memory composites. The PPSe/BM composites kept excellent shape memory properties as previously reported PPSe. Compared to neat PPSe, the composites possess much higher mechanical properties above the melting point and faster biodegradation rate, which was demonstrated via tensile test at elevated temperature and in vitro degradation experiments in phosphate buffer saline (PBS), respectively. The obviously improved mechanical properties at elevated temperature are attributed to the uniform dispersion of the reinforcing boehmite nanoplatelets, which was facilitated by the interfacial interaction between BM and PPSe as revealed by FTIR, XPS, and XRD results. The faster degradation is correlated to accelerated hydrolysis by basic boehmite with surface aluminols. The potential biocompatibility, as substantiated by the outstanding cell viability and cell attachment, together with the realization of transformation temperature close to body temperature makes the PPSe/BM composites suitable for the biomedical applications, such as stents, in human body

Estimating the responses of winter wheat yields to moisture variations in the past 35 years in Jiangsu Province of China

<div><p>Jiangsu is an important agricultural province in China. Winter wheat, as the second major grain crop in the province, is greatly affected by moisture variations. The objective of this study was to investigate whether there were significant trends in changes in the moisture conditions during wheat growing seasons over the past decades and how the wheat yields responded to different moisture levels by means of a popular drought index, the Standardized Precipitation Evapotranspiration Index (SPEI). The study started with a trend analysis and quantification of the moisture conditions with the Mann-Kendall test and Sen’s Slope method, respectively. Then, correlation analysis was carried out to determine the relationship between de-trended wheat yields and multi-scalar SPEI. Finally, a multivariate panel regression model was established to reveal the quantitative yield responses to moisture variations. The results showed that the moisture conditions in Jiangsu were generally at a normal level, but this century appeared slightly drier in because of the relatively high temperatures. There was a significant correlation between short time scale SPEI values and wheat yields. Among the three critical stages of wheat development, the SPEI values in the late growth stage (April-June) had a closer linkage to the yields than in the seedling stage (October-November) and the over-wintering stage (December-February). Moreover, the yield responses displayed an asymmetric characteristic, namely, moisture excess led to higher yield losses compared to moisture deficit in this region. The maximum yield increment could be obtained under the moisture level of slight drought according to the 3-month SPEI at the late growth stage, while extreme wetting resulted in the most severe yield losses. The moisture conditions in the first 15 years of the 21^st century were more favorable than in the last 20 years of the 20^th century for wheat production in Jiangsu.</p></div

The Pearson correlation coefficients between yield and growing season averaged SPEI.

<p>The Pearson correlation coefficients between yield and growing season averaged SPEI.</p

Effects of drought stress during the stages of elongation and heading on grain yield and HI.

<p>CK, MD and SD denote control, mild drought, and severe drought, respectively. Different letters indicate statistical significance among treatments at the <i>P</i>≤0.05 level.</p

Yield, yield components, total biomass, and HI as affected by various degrees of drought stress.

<p>Yield, yield components, total biomass, and HI as affected by various degrees of drought stress.</p

Monthly average temperatures of 10 sites in Jiangsu Province during the growing seasons (Oct.-Jun.) from 1979 to 2014.

<p>Monthly average temperatures of 10 sites in Jiangsu Province during the growing seasons (Oct.-Jun.) from 1979 to 2014.</p

Yield, yield components, total biomass, and HI as affected by various degrees of drought and waterlogging stress.

<p>Yield, yield components, total biomass, and HI as affected by various degrees of drought and waterlogging stress.</p

Average 1_month SPEI of 10 sites in Jiangsu Province during the growing seasons (Oct.-Jun.) from 1979 to 2014.

<p>Average 1_month SPEI of 10 sites in Jiangsu Province during the growing seasons (Oct.-Jun.) from 1979 to 2014.</p

Drought and wet levels based on SPEI values.

<p>Drought and wet levels based on SPEI values.</p

Estimation results for the panel model.

<p>Estimation results for the panel model.</p