Search

The construction of new towns is one of the main measures to evacuate urban populations and promote regional coordination and urban–rural integration in China. Mining the spatio-temporal pattern of new town hot spots based on multivariate data and analyzing the influencing factors of new town construction hot spots can provide a strategic basis for new town construction, but few researchers have extracted and analyzed the influencing factors of new town internal hot spots and their classification. In order to define the key points of Wuhan's new town construction and promote the construction of new cities in an orderly and efficient manner, this paper first constructs a space-time cube based on the luminous remote sensing data from 2010 to 2019, extracts hot spots and emerging hot spots in Wuhan New City, selects 14 influencing factor indicators such as population density, and uses bivariate Moran's index to analyze the influencing factors of hot spots, indicating that the number of bus stops and vegetation coverage rate are the most significant. Secondly, the disorderly multivariate logistic regression model is used to analyze the influencing factors of emerging hot spots. The results show that population density, vegetation coverage, road density, distance to water bodies, and distance to train stations are the most significant factors. Finally, based on the analysis results, some relevant suggestions for the construction of Wuhan New City are proposed, providing theoretical support for the planning and policy guidance of new cities, and offering reference for the construction of new towns in other cities, promoting the construction of high-quality cities. [ABSTRACT FROM AUTHOR]

In this work, the input–output finite-time stability (IO-FTS) of a class of continuous-time switched systems characterized by uncertainties and subjected to external disturbances is studied under asynchronous switching by means of the sliding mode control (SMC) method. The IO-FTS poses a finite-time constraint problem, which involves addressing two main issues: firstly, ensuring that the state trajectory of the switched system reaches the given sliding mode surface within the specified time, and secondly, achieving IO-FTS for the closed-loop switched system during asynchronous switching. To address these issues, we apply a partitioning strategy and construct asynchronous sliding mode controllers with adjustable parameters to ensure the reachability of the system's state trajectory within a finite time. Subsequently, we employ a multiple Lyapunov function (MLF) approach to provide sufficient conditions that ensure IO-FTS during the whole phase [ 0 , T ] for the resulting switched system. Additionally, we analyze the asynchronous characteristics concerning the reachability phase of the designed sliding surface, considering the system's switching properties. Finally, we demonstrate the efficacy of the proposed approach with a numerical example. [ABSTRACT FROM AUTHOR]

Governmental attention towards the high-quality development of the Yellow River basin has brought new development opportunities for the hotel industry. This study aims to reveal the spatial-temporal evolution patterns and influencing factors of hotels in the Yellow River Basin from 2012 to 2022, based on economic, social, and physical geographic data of 190,000 hotels in the Yellow River flowing. With the help of a GIS technology system, the spatial-temporal evolution patterns of all hotels, star hotels, and ordinary hotels were explored, respectively. Then, the significant influencing factors of these patterns were revealed by using geographic detector and Person correlation analysis. The following conclusions were drawn: (1) the overall scale of the hotel industry in the Yellow River Basin expanded year by year, achieving rapid growth from 2016, and fluctuating around 2020 due to the impact of the novel coronavirus epidemic; the overall spatial distribution had significant regional differences, showing the structural characteristics of "southeast more, northwest less"; (2) there was a great difference in the degree of spatial autocorrelation agglomeration among prefecture-level cities, and the degree of agglomeration of both the hotel industry as a whole and general hotels decreased year by year, showing a random distribution in 2022; star hotels were always distributed randomly. Additionally, a strong synergistic correlation was shown between the number of ordinary hotels and the number of star hotels in local space; (3) overall, the development of the hotel industry was significantly affected by seven factors: structural force, macro force, ecological force, internal power, consumption power, intermediary power, and external power. There were differences in the forces acting on different types of hotels, which gives a pattern recognition in-depth. [ABSTRACT FROM AUTHOR]

Ganoderma triterpenes (GTs) are the major secondary metabolites of Ganoderma lucidum, a traditional Chinese medicine, popularly used for complementary cancer therapy. GTs are lanostane-tetracyclic triterpenes. They have been reported to possess anti-tumor, anti-inflammation, antioxidant, antimicrobial and blood fat reducing effects. To date, 316 GTs have been found and their similar chemical structures have proved difficult to elucidate. This paper compiles 316 naturally occurring triterpenes from Ganoderma based on the literature published through January 2013 along with their structures, physiological activities and 13C-NMR spectral data.