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Abstract Urban agglomeration system resilience involves multiple subsystems that are interconnected and interactive, and exploring the relationships among subsystems can elucidate and increase urban agglomeration resilience. This study constructed a social-economic-built environment resilience model and proposed a social-economic-built environment resilience index system. Using the entropy weight method, the coupling coordination degree (CCD) model, GeoDetector, spatial autocorrelation analysis and the autoregressive integrated moving average model (ARIMA) model, the resilience development level of the Beijing‒Tianjin‒Hebei (BTH) region from 2000 to 2020 was evaluated, the main influencing factors for the spatiotemporal differentiation pattern were identified, and the development levels in 2030 and 2050 were predicted. The results show that (1) high-resilience and high-CCD regions are concentrated in the region of Beijing and Tianjin in the centre, and low-value regions are concentrated in the districts and counties in the west and south; (2) economic elements, especially the economic aggregate status of a region as a whole, are the main factors contributing to the differences in resilience levels between regions, but their influence gradually decreases; and (3) the gap between the CCDs of Beijing, Tianjin and cities in Hebei increased from 2000 to 2020, but this gap is expected to narrow by 2030 and 2050. On this basis, five categories of future development guidelines for cities in the BTH region are proposed.

Waterlogging is one of the world's most dangerous climatic hazards, seriously limiting the safety and sustainable development of cities. Analysis of the factors influencing urban waterlogging and disaster risk assessment are of great importance for the prevention and control of waterlogging. The study constructs a framework for assessing Urban Waterlogging Risk (UWR) from four dimensions: natural condition, social capital, infrastructure and built environment, emphasizing the need to understand and address the vulnerabilities and risks faced by cities in terms of waterlogging. On this basis, the MaxEnt model is used to rank the contribution rate of the indicators and identify positive and negative correlations, as well as to assess the risk of waterlogging and identify waterlogging-prone areas, taking Tianjin Downtown as the research object. The results show that: (1) MaxEnt model has strong applicability for waterlogging risk assessment. (2) The elements with the highest impact on urban waterlogging are population density, impervious surface, precipitation, etc., and prove that the regional waterlogging risk increases with the increase of population, building density, and impervious surface. (3) The high-risk area of waterlogging in Tianjin Downtown is concentrated in the central part of the city, which is characterized by a high degree of development and construction and a dense population; the low-risk area is mainly the area with a low degree of construction at the edge of the city, as well as the area with a large green area or water bodies. In this study, a comprehensive framework for assessing UWR was developed, key factors affecting the spatial distribution of UWR were identified, and the MaxEnt model was used to perform the risk assessment with a high degree of accuracy. The study results can provide a theoretical reference for the urban disaster warning and land use optimization.

The concept of urban resilience focuses on understanding the process and mechanisms of disaster occurrence, providing innovative approaches to address stormwater flooding. However, existing studies primarily concentrate on enhancing overall system resilience, with limited research examining the temporal progression from stormwater disturbance to flood generation. To fill this gap, this study categorizes the development process of stormwater flooding into three periods: disturbance resistance (DR), adjustment and adaptation (AA), and rapid recovery (RR). Using the SWMM (Storm Water Management Model) software, 27 representative parcels in the Beijing-Tianjin-Hebei region of China were simulated. By sequentially considering single-indicator control variables, resilience indicators that significantly impact the three periods were identified through the construction of a stormwater flooding resilience indicator library. Subsequently, resilience models for each disaster phase were constructed using the BP (Back Propagation) neural network, and genetic algorithms were employed to optimize the models and determine the optimal values of resilience indicators for each period. Finally, the research findings were summarized into a resilience design method for the built environment to address stormwater flooding, accompanied by a guide for improving stormwater flooding resilience.The study reveals the following key findings: (1) the influence of physical and spatial elements in the built environment on stormwater flooding formation varies across different stages of the disaster process; (2) distinct resilience indicators operate at different times and in different ways throughout the entire stormwater flooding resilience process; (3) enhancing stormwater flooding resilience in the built environment does not necessarily require setting specific threshold values for each influencing indicator; instead, an optimal single value emerges when multiple indicators interact. Moreover, when multiple indicators interact, an optimal combination module with the best value for a single indicator exists. This study investigates the complete cycle from storm disturbance to flood disaster formation, offering both solutions for cities to mitigate storm flood disasters and advancing theoretical research on urban storm flood resilience while fostering interdisciplinary integration.

Abstract Background Yigan mingmu oral liquid (YGMM) is a herbal medicine based on a famous Chinese herbal formula that has been used for sore eyes for more than 400 years. Eye health is closely associated with the liver based on TCM. This study aimed to investigate the hepatoprotective effect of YGMM against acute liver injury induced by alcohol in rats. Methods Experimental rats were administered with silymarin and YGMM through the gastric gavage during the entire experiment. Starting from the 11th day, the rats were administered orally with 14 ml/kg Red Star Erguotou Liquor, a popular brand, at 4 h after the dose of silymarin (100 mg/kg) and YGMM (1, 2.5 and 5 ml/kg in low, middle and high dosage group, respectively) once a day for 4 weeks except for the rats in the normal group. Biochemical parameters, including ALT, AST, TB, TG, T-SOD, GSH, and MDA were detected to evaluate the protective effect of YGMM. Pathological changes were observed through histopathological examination. Results Treatment with YGMM exhibited a significant protective effect by reversing the biochemical parameters (ALT, AST, TB, TG, and GSH) and histopathological changes. Histopathological examination by Oil Red O Staining Solution showed that lipid droplets were significantly reduced in the silymarin and YGMM groups (p

Phytochemical investigation of the n-BuOH-soluble fraction of the EtOH extract of the herbaceous stems of Ephedra sinica, which is known as Ephedrae Herba in Traditional Chinese Medicine, led to the isolation and identification of 12 A-type proanthocyanidins, containing five dimers, two trimers and five tetramers [i.e., (+)-epigallocatechin-(2α→O→7,4α→8)-(-)-catechin, named ephedrannin D1, a dimer; epigallocatechin-(2α→O→7,4α→8)-epigallocatechin-(4α→8)-catechin (ephedrannin Tr1), a trimer; and epigallocatechin-(2α→O→7,4α→8)-epigallocatechin-(4α→8)-epigallocatechin-(2α→O→7,4α→8)-gallocatechin, named ephedrannin Te1, a tetramer). Tetramers composed of gallocatechin are reported for the first time in Ephedraceae. Catechin, epicatechin, gallocatechin, epigallocatechin and four known dimers were also isolated. The structures were elucidated by extensive spectroscopic analysis. The absolute configurations of the 4α linkages, which were confirmed by NOESY and CD experiments, are the outstanding characteristic of most of these isolated A-type proanthocyanidins. The antimicrobial activities of these compounds were tested by measuring the minimum inhibitory concentrations (MIC) against bacteria (both Gram positive and Gram negative) and fungi, and were found to be in the range of 0.00515–1.38 mM. Compounds 6, 8, 10 and 11 exhibited moderate antimicrobial activities against Canidia albicans.