Formation Mechanism of Poor Settlements in Lanzhou City

Clarifying the formation mechanism of poor settlements is the " pathological" basis for urban regeneration and poverty governance.On the basis of scientific determination of 155 poor settlements in Lanzhou City,this paper classified their types and analyzed the characteristics of their quantity distribution and density distribution. From the perspective of spatial and social interaction,and combined the internal factors and external factors,this paper put forward the formation mechanism of poor settlements,namely,superposition of unit society collapse and physical environment degradation,interaction between differentiation of residents' income and reform of housing institution,interweaving between urban discontinuous planning and jumping construction,coupling between passive urbanization and active urbanization,and derivation of lagged economic development and unique regional culture.

Rotating Stomata Measurement Based on Anchor-Free Object Detection and Stomata Conductance Calculation

Stomata play an essential role in regulating water and carbon dioxide levels in plant leaves,which is important for photosynthesis.Previous deep learning-based plant stomata detection methods are based on horizontal detection.The detection anchor boxes of deep learning model are horizontal,while the angle of stomata is randomized,so it is not possible to calculate stomata traits directly from the detection anchor boxes.Additional processing of image(e.g.,rotating image)is required before detecting stomata and calculating stomata traits.This paper proposes a novel approach,named DeepRSD(deep learning-based rotating stomata detection),for detecting rotating stomata and calculating stomata basic traits at the same time.Simultaneously,the stomata conductance loss function is introduced in the DeepRSD model training,which improves the efficiency of stomata detection and conductance calculation.The experimental results demonstrate that the DeepRSD model reaches 94.3%recognition accuracy for stomata of maize leaf.The proposed method can help researchers conduct large-scale studies on stomata morphology,structure,and stomata conductance models.

Dynamics of a stochastic rabies epidemic model with Markovian switching

In this paper,we analyze a stochastic rabies epidemic model which is perturbed by both white noise and telegraph noise.First,we prove the existence of the unique global positive solution.Second,by constructing an appropriate Lyapunov function,we establish a sufficient condition for the existence of a unique ergodic stationary distribution of the positive solutions to the model.Then we establish sufficient conditions for the extinction of diseases.Finally,numerical simulations are introduced to illustrate our theoretical results.

Modeling a stochastic avian influenza model under regime switching and with human-to-human transmission

In this paper,we investigate the stochastic avian influenza model with human-to-human transmission,which is disturbed by both white and telegraph noises.First,we show that the solution of the stochastic system is positive and global.Furthermore,by using stochastic Lyapunov functions,we establish sufficient conditions for the existence of a unique ergodic stationary distribution.Then we obtain the conditions for extinction.Finally,numerical simulations are employed to demonstrate the analytical results.