What is affecting the improvement of green innovation efficiency in the old industrial base: evidence from Northeast China

Green innovation is an important driving force for high-quality development and is vital for reinvigorating the old industrial bases in Northeast China. As such, this study investigates the spatial-temporal evolution characteristics and factors influencing green innovation efficiency (GIE) in Northeast China from 2005 to 2020, using the super-efficient EBM-Malmquist model, kernel density estimation, and random forest model. The results show the following. (1) The "growth effect" of technological change is the main force driving GIE improvement; the "horizontal effect" of pure technical efficiency change has started to play an important role; and the club convergence characteristics of GIE in Northeast China have started to be optimized. (2) GIE in Northeast China shows significant spatial differentiation. The urban agglomeration of Mid-southern Liaoning and Harbin-Changchun has had high values for GIE, indicating that green innovation has a cyclic cumulative effect and the spatial pattern of green innovation needs to be further optimized. (3) The random forest model is more accurate and provides more trustworthy results compared with the traditional multiple linear regression model. The results of random forest model measurement illustrate that the number of digital economy enterprises, public finance expenditure, GDP per capita, and vegetation coverage play a positive role in promoting GIE. The proportion of the non-farm population and industrial agglomeration plays a negative role in GIE. In the same period, the contribution of the number of digital economy enterprises≥0.41, public expenditure ≥0.47, GDP per capita≥0.39, and vegetation coverage≥0.36 to GIE reach maximum values and then remain unchanged.

Supported Ni Catalysts: Simple Vapor Deposition Preparation Method and Improved Catalytic Performance for Oxidative Dehydrogenation of Ethane

Developing new methods of catalyst preparation is one of the most important tasks in the field of catalysis. A simple one-tube vapor deposition (VD) is provided in this paper for preparing the supported Ni catalyst. Ni(acac)2 was used as the Ni precursor. This preparation method was successfully applied to three types of catalytic supports, that is, Al2O3 and zeolites 5A and Hβ. Varying Ni contents of less than 8 wt % can be obtained by employing different conditions. The Ni content, depending on different deposition conditions, was preliminarily explored. The catalytic performance for oxidative dehydrogenation of ethane (ODHE) was tested for the prepared Ni catalysts by the VD method. Several cases of catalytic tests showed that for the same Ni content, the VD-prepared Ni catalyst presented better performance for ODHE than the one prepared by a traditional impregnation method. Besides the improvement in catalytic performance, several advantages of our VD preparation method for catalysis are discussed.

Network pharmacology combined with experimental validation show that apigenin as the active ingredient of Campsis grandiflora flower against Parkinson's disease by inhibiting the PI3K/AKT/NF-κB pathway

The exploration of novel natural products for Parkinson's disease (PD) is a focus of current research, as there are no definitive drugs to cure or stop the disease. Campsis grandiflora (Thunb.) K. Schum (Lingxiaohua) is a traditional Chinese medicine (TCM), and the exact active constituents and putative mechanisms for treating PD are unknown. Through data mining and network pharmacology, apigenin (APi) was identified as the main active ingredient of Lingxiaohua, and key targets (TNF, AKT1, INS, TP53, CASP3, JUN, BCL2, MMP9, FOS, and HIF1A) of Lingxiaohua for the treatment of PD were discovered. The primary routes implicated were identified as PI3K/AKT, Apoptosis, TNF, and NF-κB pathways. Subsequently, therapeutic potential of APi in PD and its underlying mechanism were experimentally evaluated. APi suppressed the release of mediators of inflammation and initiation of NF-κB pathways in MES23.5 cells induced by MPP+. APi suppressed caspase-3 activity and apoptosis and elevated p-AKT levels in MES23.5 cells. Pretreatment with LY294002, a PI3K inhibitor, resulted in APi treatment blocking the activation of NF-κB pathway and expression of inflammatory factors in MES23.5 cells by activating the PI3K/AKT pathway. In conclusion, APi protects dopaminergic neurons by controlling the PI3K/AKT/NF-κB pathway, giving novel insights into the pharmacological mechanism of Lingxiaohua in treating PD.