针对印染废水难以处理而对环境造成污染问题,以活性黑染料为目标污染物,制备了一种ZIF-8/MCM-48新型复合吸附材料,并采用X射线衍射(X-ray Diffraction,XRD)、扫描电镜(Scanning Electron Microscopy,SEM)、N_(2)的吸脱附曲线对其形貌、...针对印染废水难以处理而对环境造成污染问题,以活性黑染料为目标污染物,制备了一种ZIF-8/MCM-48新型复合吸附材料,并采用X射线衍射(X-ray Diffraction,XRD)、扫描电镜(Scanning Electron Microscopy,SEM)、N_(2)的吸脱附曲线对其形貌、结构、组成进行表征,研究了其对活性黑染料废水的吸附性能,并通过调整ZIF-8/MCM-48复合物比例、活性黑染料废水浓度、染料废水pH值及吸附时间,来确定最大吸附量和最佳吸附条件。结果表明,ZIF-8/MCM-48复合吸附剂的投加量为0.4 g/L、废水pH值为6、吸附时间为50 min时,0.15 g/L活性黑染料废水的脱色率达到了最高,为58.7%。最后对吸附过程进行了动力学分析,发现其符合二级动力学方程。展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
目的探究微型染色体维持蛋白3(minichromosome maintenance protein 3,MCM3)在乳腺癌及其亚型三阴型乳腺癌组织(triple-negative breast cancer,TNBC)中的表达和预后价值。方法通过免疫组化EnVision两步法检测乳腺癌及非癌乳腺组织中MCM...目的探究微型染色体维持蛋白3(minichromosome maintenance protein 3,MCM3)在乳腺癌及其亚型三阴型乳腺癌组织(triple-negative breast cancer,TNBC)中的表达和预后价值。方法通过免疫组化EnVision两步法检测乳腺癌及非癌乳腺组织中MCM3蛋白的表达水平。通过整合全球多中心乳腺癌基因芯片及测序数据,计算不同分子病理亚型乳腺癌与非癌乳腺组织中MCM3 mRNA表达的标准化均数差(standardized mean difference,SMD)及其综合受试者工作特征曲线(summary receiver operating characteristic curve,sROC)下面积,并对比TNBC与非TNBC组中MCM3的表达差异。同时绘制Kaplan-Meier曲线分析MCM3 mRNA在乳腺癌及TNBC中的预后预测价值。结果乳腺癌中MCM3蛋白和mRNA表达均显著高于非癌乳腺对照。4个分子病理亚型(Luminal A型、Luminal B型、HER2过表达型、TNBC)乳腺癌组织MCM3 mRNA水平也均高于非癌对照组织。预后评估显示,高表达MCM3可成为预测乳腺癌不良无远处转移生存期和无复发生存期的独立因素,在TNBC中,MCM3的高表达在此为保护因素。结论MCM3表达增高可能在乳腺癌的发生发展中具有一定的促进作用,该作用在TNBC中更为显著。展开更多
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
