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Sea buckthorn (Hippophae rhamnoides) is an ecologically significant shrub that has been effectively employed to combat desertification. Recently, its economic potential has garnered substantial scientific interest. Sea buckthorn proanthocyanidins (SBPs), which are key antioxidant bioactive compounds found in sea buckthorn, exhibit remarkable free radical scavenging capacity and multi-target biological activities, including anti-inflammatory, anti-cancer, vision protection, and cardiovascular protection effects. These attributes highlight the potential applications of SBPs in functional foods, nutritional supplements, and skincare products. This review summarizes the current state of research regarding extraction methods, structural characteristics, and associated biological activities of sea buckthorn proanthocyanidins, while also exploring future research directions to provide a reference for their further development and utilization.

Clarifying the regional transmission mechanism of COVID-19 has practical significance for effective protection. Taking 103 county-level regions of Hubei Province as an example, and taking the fastest-spreading stage of COVID-19, which lasted from 29 January 2020, to 29 February 2020, as the research period, we systematically analyzed the population migration, spatio-temporal variation pattern of COVID-19, with emphasis on the spatio-temporal differences and scale effects of related factors by using the daily sliding, time-ordered data analysis method, combined with extended geographically weighted regression (GWR). The results state that: Population migration plays a two-way role in COVID-19 variation. The emigrants’ and immigrants’ population of Wuhan city accounted for 3.70% and 73.05% of the total migrants’ population respectively; the restriction measures were not only effective in controlling the emigrants, but also effective in preventing immigrants. COVID-19 has significant spatial autocorrelation, and spatio-temporal differentiation has an effect on COVID-19. Different factors have different degrees of effect on COVID-19, and similar factors show different scale effects. Generally, the pattern of spatial differentiation is a transitional pattern of parallel bands from east to west, and also an epitaxial radiation pattern centered in the Wuhan 1 + 8 urban circle. This paper is helpful to understand the spatio-temporal evolution of COVID-19 in Hubei Province, so as to provide a reference for similar epidemic prevention.

Understanding the relationship between drought and the water use efficiency (WUE) in terrestrial ecosystems can help reduce drought risk. It remains unclear what the correlation between the cropland water use efficiency (CWUE) and drought during drought events. We aim to identify the spatiotemporal relationship between drought and the CWUE and to ensure the service capacity of cultivated land ecosystems. In this study, the cubist algorithm was used to establish a monthly integrated surface drought index (mISDI) dataset for the Huang–Huai–Hai Plain (HHHP), and the run theory was used to identify drought events. We assessed the spatio-temporal variations of drought in the HHHP during 2000–2020 and its influence on the CWUE. The research results were as follows: from the overall perspective of the HHHP, the mISDI showed a downward trend. Drought had an enhanced effect on the CWUE of the HHHP, and the enhancement of the CWUE in the eastern hilly area was more significant. The CWUE response to drought had a three-month lag period and a significant positive correlation, and it was shown that the cultivated land ecosystems in this area had strong drought resistance ability. This study provides a new framework for understanding the response of the CWUE to drought and formulating reasonable vegetation management strategies for the HHHP.

Understanding the complex variations in water use efficiency (WUE) is critical for optimizing agricultural productivity and resource management. Traditional analytical methods often fail to capture the nonlinear and multiscale variations inherent in WUE, where multifractal theory offers distinct advantages. Given its limited application in WUE studies, this paper analyzes the spatiotemporal characteristics and influencing factors of the WUE in Anhui Province from 2001 to 2022 using a multifractal, multiscale approach. The results indicated that the WUE exhibited significant interannual variation, peaking in summer, especially in August (2.4552 gC·mm−1·m−2), with the monthly average showing an inverted “V” shape. Across different spatial and temporal scales, the WUE displayed clear multifractal characteristics. Temporally, the variation in fractal features between years was not prominent, while inter-seasonal variation was most complex in August during summer. Spatially, the most distinct multifractal patterns were observed in hilly and mountainous areas, particularly in regions with brown soil distribution. Rainfall was identified as the primary natural driver influencing regional WUE changes. This study aims to promote the sustainable use of water resources while ensuring the stability of agricultural production within protected farmlands.

Urban competitiveness is an indispensable topic for urban management. The purpose of this work was to study the status quo of urban system competitiveness in any region and explore the internal factors that affect urban competitiveness. In this study, 30 indicators were selected from six dimensions: population, economic strength, infrastructure, technology and culture, open exchange, and quality of life, and a two-level evaluation index system was constructed. The entropy weight method was used to calculate the weight, and 12 prefecture-level cities in Hubei Province were taken as the evaluation object. This study found that in Hubei province, (1) science, technology, and culture are the first driving forces of urban competitiveness; (2) the impact of the quality of life on urban competitiveness is deepening and obvious, especially the impact of residents’ consumption; and (3) Wuhan, the provincial capital city, is far ahead in terms of its competition and its position is unshakable, followed by Yichang and Xiangyang. Overall, the competitiveness gap between cities in the region is gradually narrowing.

Constructing a merged concept lattice with formal concept analysis (FCA) is an important research direction in the field of integrating multi-source geo-ontologies. Extracting essential geographical properties and reducing the concept lattice are two key points of previous research. A formal integration method is proposed to address the challenges in these two areas. We first extract essential properties from multi-source geo-ontologies and use FCA to build a merged formal context. Second, the combined importance weight of each single attribute of the formal context is calculated by introducing the inclusion degree importance from rough set theory and information entropy; then a weighted formal context is built from the merged formal context. Third, a combined weighted concept lattice is established from the weighted formal context with FCA and the importance weight value of every concept is defined as the sum of weight of attributes belonging to the concept’s intent. Finally, semantic granularity of concept is defined by its importance weight; we, then gradually reduce the weighted concept lattice by setting up diminishing threshold of semantic granularity. Additionally, all of those reduced lattices are organized into a regular hierarchy structure based on the threshold of semantic granularity. A workflow is designed to demonstrate this procedure. A case study is conducted to show feasibility and validity of this method and the procedure to integrate multi-source geo-ontologies.

Land Use/Cover Change (LUCC) has gradually became an important direction in the research of global changes. LUCC is a complex system, and entropy is a measure of the degree of disorder of a system. According to land use information entropy, this paper analyzes changes in land use from the perspective of the system. Research on the entropy of LUCC structures has a certain “guiding role” for the optimization and adjustment of regional land use structure. Based on the five periods of LUCC data from the year of 1990 to 2010, this paper focuses on analyzing three types of LUCC entropies among counties in China—namely, Shannon, Renyi, and Tsallis entropies. The findings suggest that: (1) Shannon entropy can reflect the volatility of the LUCC, that Renyi and Tsallis entropies also have this function when their parameter has a positive value, and that Renyi and Tsallis entropies can reflect the extreme case of the LUCC when their parameter has a negative value.; (2) The entropy of China’s LUCC is uneven in time and space distributions, and that there is a large trend during 1990–2010, the central region generally has high entropy in space.

As digital terrain models are indispensable for visualizing and modeling geographic processes, terrain information content is useful for terrain generalization and representation. For terrain generalization, if the terrain information is considered, the generalized terrain may be of higher fidelity. In other words, the richer the terrain information at the terrain surface, the smaller the degree of terrain simplification. Terrain information content is also important for evaluating the quality of the rendered terrain, e.g., the rendered web terrain tile service in Google Maps (Google Inc., Mountain View, CA, USA). However, a unified definition and measures for terrain information content have not been established. Therefore, in this paper, a definition and measures for terrain information content from Digital Elevation Model (DEM, i.e., a digital model or 3D representation of a terrain’s surface) data are proposed and are based on the theory of map information content, remote sensing image information content and other geospatial information content. The information entropy was taken as the information measuring method for the terrain information content. Two experiments were carried out to verify the measurement methods of the terrain information content. One is the analysis of terrain information content in different geomorphic types, and the results showed that the more complex the geomorphic type, the richer the terrain information content. The other is the analysis of terrain information content with different resolutions, and the results showed that the finer the resolution, the richer the terrain information. Both experiments verified the reliability of the measurements of the terrain information content proposed in this paper.

Natural disasters occur frequently causing huge economic losses and reduced grain production. Therefore, it is important to thoroughly explore the spatial correlations between grain, disaster, and the economy. Based on inter-provincial panel data in China in 2019, this study integrates complex network and co-occurrence theory into a coupled grain–disaster–economy (GDE) multilayer network, which provides a new perspective to further explore the spatial correlation between these three systems. We identify the spatial coupled characteristics of the GDE multilayer network using three aspects: degree, centrality, and community detection. The research results show the following: (1) Provinces in the major grain-producing regions have a stronger role in allocating and controlling grain resources, and the correlation between grain and disasters in these provinces is stronger and more prone to disasters. Whereas provinces in the Beijing–Tianjin–Hebei economic zone, and the Yangtze River Delta and Pearl River Delta economic zones, such as Beijing, Tianjin, Jiangsu, Shanghai, and Zhejiang, have a high level of economic development, thereby a stronger ability to allocate economic resources. (2) The economic subsystem assumes a more important, central role compared with the grain and disaster subsystems in the formation and development of the coupled GDE multilayer network, with a stronger coordination for the co-development between the complex grain, disaster, and economy systems in the nodal provinces of the network. (3) The community modularity of the coupled GDE multilayer network is significantly higher than that of the three single-layer networks, indicating a more reasonable community division after coupling the three subsystems. The identification of the spatial characteristics of GDE using multilayer network analysis offers a new perspective on taking various measures to improve the joint sustainable development of grain, disaster, and the economy in different regions of China according to local conditions.

As complex systems, the spatial structure of urban systems can be analyzed by entropy theory. This paper first calculates the interaction force between cities based on the gravity model, the spatial relationship matrix between cities is constructed using the method of network modeling, and the spatial network modeling of urban system can be calculated. Secondly, the Efficiency Entropy (EE), Quality Entropy (QE), and System Entropy (SE) of urban system network are calculated and analyzed by information entropy. Finally, taking the Huaihe River Basin (HRB) as a case study, model verification and empirical analysis are performed. It is found that the spatio–temporal pattern of the urban system network structure in the basin is uneven: in space, the urban system network in the HRB presents a layer-by-layer spatial distribution centered on the core city of Xuzhou; meanwhile, the overall urban system network in the basin presents an orderly development trend. This study has certain theoretical and practical value for the planning of urban and urban systems and the coordinated development of regions.