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Exploring the pattern of block vitality within cities and its influencing factors is an important topic in urban vitality research, which has great significance in promoting high-quality urban development. However, existing research has paid little attention to the spatial difference characteristics of daytime and night urban vitality and the differences in their influencing factors. Using the urban area of Kunming, China, as a case study, this study explores the differences in spatial patterns of daytime and night vitality at the intra-city block scale and analyses the differences in the main influencing factors of daytime and night block vitality using spatial regression models. The study obtains the following findings: (1) daytime block vitality in Kunming’s urban district (the urban Dist. of KM) is higher than night block vitality. The First Ring Area has the highest daytime block vitality, whereas the Second Ring Area has the highest night block vitality. (2) Block vitality in the urban Dist. of KM presents a polycentric structure. (3) There are obvious differences in the factors influencing urban vitality between daytime and night, with work accessibility, functional mixing, daily consumption accessibility, floor area ratio, and average building age, having different directions of influence on daytime and night urban vitality. (4) Daytime urban vitality in the urban Dist. of KM relies on work activities, while night urban vitality relies on residential activities. The results provide a scientific basis for urban land use layout, facility construction, and higher-quality urban planning and management, thus promoting sustainable urban development.

Networked Turing patterns often manifest as groups of nodes distributed on either side of the homogeneous equilibrium, exhibiting high and low density. These pattern formations are significantly influenced by network topological characteristics, such as the average degree. However, the impact of clustering on them remains inadequately understood. Here, we investigate the relationship between clustering and networked Turing patterns using classical prey–predator models. Our findings reveal that when nodes of high and low density are completely distributed on both sides of the homogeneous equilibrium, there is a linear decay in Turing patterns as global clustering coefficients increase, given a fixed node size and average degree; otherwise, this linear decay may not always hold due to the presence of high-density nodes considered as low-density nodes. This discovery provides a qualitative assessment of how clustering coefficients impact the formation of Turing patterns and may contribute to understanding why using refuges in ecosystems could enhance the stability of prey–predator systems. The results link network topological structures with the stability of prey–predator systems, offering new insights into predicting and controlling pattern formations in real-world systems from a network perspective. [ABSTRACT FROM AUTHOR]

Arid ecosystems are known to be sensitive to climate change. The Jornada Basin in the USA, as one representative of arid land, has suffered from land degradation in recent decades. In order to disentangle the climate–vegetation feedback, we analyzed the vegetation dynamics under the effects of climate change via a mathematical model based on the reaction–diffusion mechanism. Using this model, we conducted a sensitive analysis of climate factors and concluded that the ecosystem might experience a catastrophic shift with the climatic deterioration. We considered the non-local interaction term to explain the competition among plants. Additionally, the PLR (power law range) metric was used to quantify the extent of the degradation and to compare the results of the vegetation patterns from the remote sensing data and the simulations. From the results, this model could simulate the trends of land degradation in this area. We found that the land degradation could be mainly attributed to climate changes in recent years. This approach suggests that vegetation patterns can provide hints as to whether the ecosystem is approaching desertification. These results can help with mapping vulnerable arid areas around the world through model simulation and satellite images. [ABSTRACT FROM AUTHOR]

Infectious diseases are a major threat to global health. Spatial patterns revealed by epidemic models governed by reaction–diffusion systems can serve as a potential trend indicator of disease spread; thus, they have received wide attention. To characterize important features of disease spread, there are two important factors that cannot be ignored in the reaction–diffusion systems. One is that a susceptible individual has an ability to recognize the infected ones and keep away from them. The other is that populations are usually organized as networks instead of being continuously distributed in space. Consequently, it is essential to study patterns generated by epidemic models with self- and cross-diffusion on complex networks. Here, with the help of a linear analysis method, we study Turing instability induced by cross-diffusion for a network organized SIR epidemic model and explore Turing patterns on several different networks. Furthermore, the influences of cross-diffusion and network structure on patterns are also investigated. [ABSTRACT FROM AUTHOR]

The Turing pattern is an important dynamic behavior characteristic of activator-inhibitor systems. Differentiating from traditional assumption of activator-inhibitor interactions in a spatially continuous domain, a Turing pattern in networked reaction-diffusion systems has received much attention during the past few decades. In spite of its great progress, it still fails to evaluate the precise influences of network topology on pattern formation. To this end, we try to promote the research on this important and interesting issue from the point of view of average degree-a critical topological feature of networks. We first qualitatively analyze the influence of average degree on pattern formation. Then, a quantitative relationship between pattern formation and average degree, the exponential decay of pattern formation, is proposed via nonlinear regression. The finding holds true for several activator-inhibitor systems including biology model, ecology model, and chemistry model. The significance of this study lies that the exponential decay not only quantitatively depicts the influence of average degree on pattern formation, but also provides the possibility for predicting and controlling pattern formation.

In this paper, we propose and study network epidemic models with demographics for disease transmission. We obtain the formula of the basic reproduction number R0 of infection for an SIS model with births or recruitment and death rate. We prove that if R0 ≤ 1 , infection-free equilibrium of SIS model is globally asymptotically stable; if R0 > 1 , there exists a unique endemic equilibrium which is globally asymptotically stable. It is also found that demographics has great effect on basic reproduction number R0. Furthermore, the degree distribution of population varies with time before it reaches the stationary state.

Brucellosis is one of the major infectious and contagious bacterial diseases in Hinggan League of Inner Mongolia, China. The number of newly infected human brucellosis data in this area has increased dramatically in the last 10 years. In this study, in order to explore effective control and prevention measures we propose a deterministic model to investigate the transmission dynamics of brucellosis in Hinggan League. The model describes the spread of brucellosis among sheep and from sheep to humans. The model simulations agree with newly infected human brucellosis data from 2001 to 2011, and the trend of newly infected human brucellosis cases is given. We estimate that the control reproduction number Rc is about 1.9789 for the brucellosis transmission in Hinggan League and compare the effect of existing mixed cross infection between basic ewes and other sheep or not for newly infected human brucellosis cases. Our study demonstrates that combination of prohibiting mixed feeding between basic ewes and other sheep, vaccination, detection and elimination are useful strategies in controlling human brucellosis in Hinggan League.