In this paper, all the forests, woodlands and trees in the administrative area of Zhaoling Township in Chuzhou City of Huai'an City were collected and analyzed. The total area of the administrative area is 4852 hectares, the forest coverage rate is 22.07%, and the forest greening rate is 26.13%. This index has exceeded 20% of the forest coverage rate of the well - off society. Tree species is particularly serious. In the forest system (pure forest), the area of pure forest of poplar is accounted for 99.9% of the whole forest area. In the four tree systems, the number of poplar trees accounted for 80% of the total number of trees in the whole tree, and the total amount of poplar trees accounted for 98%. The poplar pure forest age group structure disorders, the unit area is low. The ratio of total area of poplar pure forest in Zhongling and young forests was 92.9%, and the ratio of total area of poplar pure forest and mature forest was 7.1%. The ratio of mature forest and the ratio of mature forest was 0.7%, and the proportion of each group was obviously abnormal.

This study employs a transfer matrix, dynamic degree, stability index, and the PLUS model to analyze the spatiotemporal changes in forest land and their driving factors in Yibin City from 2000 to 2022. The results reveal the following: (1) The land use in Yibin City is predominantly characterized by cultivated land and forest land (accounting for over 95% of the total area). The area of cultivated land initially increased and then decreased, while forest land continued to decline and construction land expanded significantly. The rate of forest land loss has slowed (with the dynamic degree decreasing from −0.62% to −0.04%), and ecosystem stability has improved (the F-value increased from 2.27 to 2.9). The conversion of cultivated land to forest land is the primary driver of forest recovery, whereas the conversion of forest land to cultivated land is the main cause of reduction; (2) cultivated land is concentrated in the central and northeastern regions, while forest land is distributed in the western and southern mountainous areas. Construction land is predominantly located in urban areas and along transportation routes. Areas of forest land reduction are mainly found in the central and southern regions with rapid economic development, while areas of forest land increase are concentrated in high-altitude zones or key ecological protection areas. Stable forest land is distributed in the western and southern ecological conservation zones; (3) changes in forest land are primarily influenced by annual precipitation, elevation, and distance to rivers. Road accessibility and GDP have significant impacts, while slope, annual average temperature, and population density exert moderate influences. Distance to railways, aspect, and soil type have relatively minor effects. The findings of this study provide a scientific basis for the sustainable management of forest resources and ecological conservation in Yibin City.

The present research is on the propagation of Rayleigh waves in a homogenous thermoelastic solid half-space by considering the compact form of six different theories of thermoelasticity. The medium is subjected to an insulated boundary surface that is free from normal stress, tangential stress, and a temperature gradient normal to the surface. After developing a mathematical model, a dispersion equation is obtained with irrational terms. To apply the algebraic method, this equation must be converted into a rational polynomial equation. From this, only those roots are filtered out, which has satisfied both of the above equations for the propagation of waves decaying with depth. With the help of these roots, different characteristics are computed numerically, like phase velocity, attenuation coefficient, and path of particles. Various particular cases are compared graphically by using phase velocity and attenuation coefficient. The elliptic path of surface particles in Rayleigh wave propagation is also presented for the different theories using physical constants of copper material for different depths and thermal conductivity.

Hybrid nanofluids have several potential applications in various industries, including electronics cooling, automotive cooling systems, aerospace engineering, and biomedical applications. The primary goal of the study is to provide more information about the characteristics of a steady and incompressible stream of a hybrid nanofluid flowing over a thin, inclined needle. This fluid consists of two types of nanoparticles: non-magnetic nanoparticles (aluminium oxide) and magnetic nanoparticles (ferrous oxide). The base fluid for this nanofluid is a mixture of water and ethylene glycol in a 50:50 ratio. The effects of inclined magnetic fields and joule heating on the hybrid nanofluid flow are considered. The Runge-Kutta fourth-order method is used to numerically solve the partial differential equations and governing equations, which are then converted into ordinary differential equations using similarity transformations. Natural convection refers to the fluid flow that arises due to buoyancy forces caused by temperature differences in a fluid. In the context of an inclined needle, the shape and orientation of the needle have significantly affected the flow patterns and heat transfer characteristics of the nanofluid. These analyses protest that raising the magnetic parameter results in an increase in the hybrid nanofluid thermal profile under slip circumstances. Utilizing the potential of hybrid nanofluids in a variety of technical applications, such as energy systems, biomedicine, and thermal management, requires an understanding of and ability to manipulate these effects.

To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.