Influence of Climate and Socio-Economic Factors on the Spatio-Temporal Variability of Soil Organic Matter: A Case Study of Central Heilongjiang Province, China

For the scientific management of farmland, it is significant to understand the spatio-temporal variability of soil organic matter and to study the influences of related factors. Using geostatistical theory, GIS spatial analysis, trend analysis and a Geographically Weighted Regression （GWR） model, this study analyzed the response of soil organic matter to climate and socio-economic factors in central Heilongjiang Province during the past 25 years. Second soil survey data of China for 1979-1985, 2005 field sampling data, climate observations and socio-economic data for 1980-2005 were analyzed. First, soil organic matter in 2005 was spatially interpolated using the Co-Kriging method along with auxiliary data sets of soil type and pH. The spatio-temporal variability was then studied by comparison with the 1980s second soil census data. Next, the temporal trends in climate and socio-economic factors over the past 25 years were investigated. Finally, we examined the variation of the response of soil organic matter to climate and socio-economic factors using the GWR model spatially and temporally. The model showed that 53.82% area of the organic matter content remained constant and 29.39% has decreased during the past 25 years. The impact of precipitation on organic matter content is mainly negative, with increasing absolute values of the regression coefficient. The absolute value of regression coefficient of annual average temperature has decreased, and more areas are now under its negative effects. In addition, the areas of positive regression coefficient of annual sunshine hours have northward shifted, with the increasing absolute value of positive coefficient and decreasing absolute value of negative coefficient. The areas of positive regression coefficient of mechanized farming as a socio-economic factor have westward shifted, with the increasing absolute value of negative coefficient and decreasing absolute value of positive coefficient. The area of regions with the positive regression coefficient of irrigation has expanded. The regions with positive regression coefficient of fertilizer use have shrinked. The positive regression coefficient of mulch film consumption has significantly increased. The regression coefficient of pesticide consumption was mainly positive in the west of the study area, while it was negative to the east. Generally, GWR model is capable to investigate the influence of both climatic and socio-economic factors, avoided the insufficiency of other research based on the single perspective of climatic or socio-economic factors. Therefore, we can conclude that GWR model could provide methodological support for global change research and serve as basic reference for cultivated land quality improvement and agricultural decision making.

冷却工艺对A995-5A双相不锈钢厚大铸件裂纹缺陷的影响

双相不锈钢A995-5A厚大铸钢件正常冷却状态下,冷却速度缓慢,在冷却过程中极易产生大量的σ脆性相,因此铸件裂纹倾向严重,易导致铸件报废。为了减少或杜绝裂纹缺陷的产生,可在铸件凝固后进行高温清砂,快速冷却,使铸件冷却过程中快速通过产生σ相组织的温度区间,减少σ相的产生。实际生产中,采用浇注铸件凝固后就进行高温打箱,对铸件强制风冷或喷雾风冷,可以有效消除裂纹缺陷。

利拉鲁肽单药治疗新诊超重或肥胖2型糖尿病的效果及安全性评价

目的探究利拉鲁肽单药治疗新诊超重或肥胖2型糖尿病的效果及安全性。方法选取62例超重或肥胖2型糖尿病作为研究对象,按照病例单双号分为对照组和实验组,各31例。实验组给予利拉鲁肽治疗,对照组给予二甲双胍治疗,比较两组的治疗效果、血脂、血糖、体质量指数(BMI)以及不良反应发生率。结果实验组患者的治疗有效率为96.77%,高于对照组的77.42%,差异有统计学意义(P<0.05);实验组患者血脂、血糖、BMI指标均显著优于对照组,差异有统计学意义(P<0.05);实验组患者不良反应发生率为3.22%,低于对照组的19.35%,差异有统计学意义(P<0.05)。结论采用利拉鲁肽治疗超重或肥胖2型糖尿病患者,可提高患者的临床效果,改善血脂、血糖、BMI指数,减少不良反应的发生,值得临床推广。

基于土地利用的中国城镇化SD模型与模拟

中国正处在快速推进的城镇化进程中,耕地与林地、牧草地和水域等生态用地将如何变化,以及建设用地是否仍将快速增长?这不仅是国家宏观政策制定者关心的问题,也是广大学者和普通民众面临的具体问题。通过构建基于土地利用的中国城镇化系统动力学(System dynamics,SD)模型,尝试对上述问题作出分析。研究结果表明:(1)本文构建的模型是有效的,具备可靠性和稳定性。(2)若要保持国家耕地保有量不少于18.25亿亩,到2050年需补充83.17万~412.67万hm^(2)耕地资源。(3)到2050年,如果中国城镇化水平达到78%左右,建设用地总量将达到4007.29万~4214.25万hm^(2),较2020年净增加了155.87万~342.88万hm^(2)。(4)2020—2050年生态用地数量表现为先增加后减少,其中,林地显著增加,牧草地减少,水域略有增加。研究成果可为全国国土空间规划多方案模拟、评估和决策提供科学服务。