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The Qinghai-Tibet Plateau (QTP) has undergone substantial warming, resulting in extensive permafrost degradation and a pronounced increase in landslide frequency. However, the causal link between climate warming and permafrost landslide occurrences remains poorly understood. A comprehensive inventory of permafrost landslides along the Qinghai-Tibet Engineering Corridor (QTEC) from 2016 to 2022 was compiled through remote sensing and field verification, along with an analysis of landslide triggering factors based on data from 5 weather stations, 4 active layer thickness observation sites, and 3 precipitation stations. From 2000 to 2020, the mean annual air temperature (MAAT) showed an increase of 0.5°C per decade, while precipitation remained relatively stable. A notable peak occurred in 2016, with MAAT and mean annual surface ground temperature rising sharply by 0.59°C and 0.41°C, respectively, from the previous year. In the same year, active layer thickness across observation sites increased by an average of 18.5 cm, exceeding the average thickening rate. This substantial deepening of the active layer suggests that a portion of the underlying permafrost, potentially ice-rich near the permafrost table, thawed during the warm season. Laboratory experiments further reveal a three-stage reduction in soil strength as temperatures approach 0°C, with the most pronounced decline at −1°C. Interpretation of landslide data shows that landslide frequency in 2016 significantly increased, reaching approximately 1.3 times the historical total. This suggests that a thawed interlayer forming at the active layer-permafrost interface plays a dominant role in landslide initiation. The thawed layer acts as a weak zone, enabling the downward movement of the overlying active layer and contributing to slope instability. These findings provide robust evidence linking temperature rise to permafrost-related landslides, offering new insights into the mechanisms of temperature-induced slope instability in high-altitude regions. [ABSTRACT FROM AUTHOR]

Ocean circulation plays an important role in the formation and occurrence of extreme climate events. The study shows that the periodic variation of ocean circulation under strong wind stress is closely related to climate oscillation. Ocean circulation is a nonlinear dynamic system, which shows complex nonlinear characteristics, so the essence behind ocean circulation has not been clearly explained. Therefore, the response and evolution of the circulation system to wind stress are studied based on the bifurcation and catastrophe theories in nonlinear dynamics. First, the quasi-geostrophic gyre equation and the normalized gravity model are introduced and developed to study ocean circulation driven by wind stress, and solved using the Galerkin method. Then, the bifurcation and catastrophe behaviors of the system governed by the low-order ocean circulation model during the change in wind stress intensity and the coexistence of multiple equilibria in the circulation system are studied in detail. The results show that saddle and unstable nodes appear in the system after a cusp catastrophe. With the change in model parameters, the unstable node becomes the unstable focus, and then the subcritical Hopf bifurcation occurs. The system forms a bistable interval when the system undergoes a catastrophe twice, and the system shows hysteresis. In addition, multiple equilibrium states are coexisting in the circulating system, and the unstable equilibrium state always changes into a stable equilibrium state through vortex movement. Therefore, there is a route for the system to induce short-term climate oscillation, that is, in the multi-stable equilibrium state of the system, the vortex oscillates after being subject to small disturbances, and then triggers climate oscillation. [ABSTRACT FROM AUTHOR]

Feed-forward effect strongly modulates collective behavior of a multiple-layer neuron network and usually facilitates synchronization as signals are propagated to deep layers. However, a full synchronization of neuron system corresponds to functional disorder. In this work, we focus on a network containing two layers as the simplest model for multiple layers to investigate pattern selection during interaction between two layers. We first confirm that the chimera state emerges in layer 1 and it also induces chimera in layer 2 when the feed-forward effect is strong enough. A cluster is discovered as a transient state which separates full synchronization and chimera state and occupy a narrow region. Second, both feed-forward and back-forward effects are considered and we discover chimera states in both layers 1 and 2 under the same parameter for a large range of parameters selection. Finally, we introduce adaptive dynamics into inter-layer rather than intra-layer couplings. Under this circumstance, chimera state can still be induced and coupling matrix will be self-organized under suitable phase parameter to guarantee chimera formation. Indeed, chimera, cluster and synchronization can propagate from one layer to another in a regular multiple network for a corresponding parameter selection. More importantly, adaptive coupling is proved to control pattern selection of neuron firing in a network and this plays a key role in encoding scheme. [ABSTRACT FROM AUTHOR]

Generation of high spatial and temporal resolution LAI (leaf area index) products is challenging because higher spatial resolution remotely sensed data usually have coarse temporal resolutions and vice versa. In this study, a novel method that combining Kriging interpolation and Cressman interpolation was proposed to generate high spatial and temporal resolution LAI products by fusing Moderate Resolution Imaging SpectroRadiometer (MODIS) characterized by coarse spatial resolution and high temporal resolution and Gaofen-1 (GF-1) with fine spatial resolution and coarse temporal resolution. This method was applied to the Huangpu district of Guangzhou, Guangdong, China. The results showed that compared to field observation, the predicted values of LAI had an acceptable accuracy of 73.12%. Using Moran's I index and Kolmogorov-Smirnov tests, it was found that the MODIS data were spatially auto-correlated and characterized by normal distributions. Scaling down the 1 km× 1 km spatial resolution MODIS products to a spatial resolution of 30 m×30 m using point-Kriging resulted in a precision of 79.38% compared to the results at the same spatial resolution derived from an 8 m×8 m spatial resolution GF-1 image by scaling up using block-Kriging. Moreover, the regression models that accounts for the relationship between NDVI (Normalized Difference Vegetation Index) and LAI based on MODIS data obtained the determination coefficients ranging from 0.833 to 0.870. Finally, the data fusion and interpolation of MODIS and GF-1 data using Cressman method generated high spatial and temporal resolution LAI maps, which showed reasonably spatial and temporal variability. The results imply that the proposed method is a powerful tool to create high spatial and temporal resolution LAI products. [ABSTRACT FROM AUTHOR]

Objective: To establish a SEIR epidemic dynamics model that can be used to evaluate the COVID-19 epidemic, and to predict and evaluate the COVID-19 epidemic in Hubei province using the proposed model., Methods: COVID-19 SEIR transmission dynamics model was established, which took transmission ability in latent period and tracking quarantine interventions into consideration. Based on the epidemic data of Hubei province from January 23, 2020 to February 24, 2020, the parameters of the newly established modified SEIR model were fitted. By using Euler integral algorithm to solve the modified SEIR dynamics model, the epidemic situation in Hubei province was analyzed, and the impact of prevention and control measures such as quarantine and centralized treatment on the epidemic development was discussed., Results: The theoretical estimation of the epidemic situation by the modified SEIR epidemic dynamics model is in good agreement with the actual situation in Hubei province. Theoretical analysis showed that prevention and control quarantine and medical follow-up quarantine played an important inhibitory effect on the outbreak of the epidemic.The centralized treatment played a key role in the rapid decline in the number of infected people. In addition, it is suggested that individuals should improve their prevention awareness and take strict self-protection measures to curb the increase in infected people., Conclusions: The modified SEIR model is reliable in the evaluation of COVID-19 epidemic in Hubei province, which provides a theoretical reference for the decision-making of epidemic interventions.

Nonlinear waves produced in an incompressible boundary layer driven by a travelling wave are investigated, with damping considered as well. As one of the typical nonlinear waves, the spike-like wave is governed by the driven-damped Benjamin-Ono equation. The wave field enters a completely irregular state beyond a critical time, increasing the amplitude of the driving wave continuously. On the other hand, the number of spikes of solitary waves increases through multiplication of the wave pattern. The wave energy grows in a sequence of sharp steps, and hysteresis loops are found in the system. The wave energy jumps to different levels with multiplication of the wave, which is described by winding number bifurcation of phase trajectories. Also, the phenomenon of multiplication and hysteresis steps is found when varying the speed of driving wave as well. Moreover, the nature of the change of wave pattern and its energy is the stability loss of the wave caused by saddle-node bifurcation.