In this paper， we study the Cauchy problem for the 4-th order nonlinear equation {\partial }_{t}h+{\partial }_x^{\mathrm{4}}h+{\partial }_x^{\mathrm{2}}\left({\left|{\partial }_{x}h\right|}^{\alpha }\right)=\mathrm{0} in one dimension for the initial data h_{\mathrm{0}} where \alpha \ge \mathrm{5} and \alpha \in \mathbb{R}. Making use of some subtle estimates of the corresponding linear equation and the nonlinear term， Littlewood-Paley theory， two-norm method， and contraction mapping principle， we obtain the local well-posedness result in nonhomogeneous Besov spaces.

We use pairwise fusion penalty regularization method， based on Tobit regression model， to perform subgroup analysis on left-censored data with heterogeneity， simultaneously estimating regression parameters and identifying subgroups. By introducing a set of new parameters， the original optimization problem is transformed into a multivariate optimization problem with equality constraints only that can be solved by alternating direction method of multipliers. Moreover， the multivariate function related to the loss in each iteration is transformed into a group of quadratic surrogate functions of single variable by generalized coordinate descent algorithm. We prove that the proposed algorithm is convergent， and establish the large sample properties of the obtained parameter estimators. Simulation studies and real data analysis show that the proposed method has good performance.

Vapor compression refrigeration can operate electronic devices at lower temperatures even under harsh conditions， but it faces critical challenges in miniaturization and oil-free operation. This paper presents a detailed analysis and optimization of the excitation coils of the linear compressor using finite element analysis. The optimization allows the coil to be more compactly integrated with the outer stator core， further reducing the compressor's volume. A bobbinless coil was developed to increase the slot fill factor， resulting in a more compact structure. Simulation comparisons demonstrate effective enhancements in motor output capacity and efficiency. A prototype was constructed， featuring a linear motor with an outer diameter of 61 mm and a length of 36 mm. The measured electromagnetic force coefficient is 20.73 N·A^-1， which is very close to the simulation result of 21.34 N·A^-1. Voltage regulation experiments were also conducted under oil-free conditions， confirming that the device can maintain its performance while achieving miniaturization and oil-free operation.

Based on the PIC-drift-diffusion hybrid model， a two-dimensional cylindrical-coordinate hybrid model computational procedure suitable for EUV-induced plasma has been developed， which fully takes into account the characteristics of EUV-induced plasma， and adopts the PIC method to track the motion process of ions， and adopts the drift-diffusion model to deal with electrons rapidly entering the quasi-equilibrium state. Based on this hybrid model， the long-time dynamic evolution of multi-pulse EUV-induced H plasma is simulated. The results show that the hybrid model can accurately describe the dynamical behavior of the plasma， and also significantly improve the computational efficiency and expand the time scale. The plasma evolution shows a certain cumulative effect， with the increase of the number of EUV pulses， the average density of the H plasma gradually rises， the average kinetic energy of the electrons gradually decreases， and the flux of H ions reaching the wall gradually increases， all of these parameters tend to stabilize after the number of pulses reaches a certain value. In addition， the pressure of the background gas has a significant effect on the multi-pulse cumulative effect， and the plasma parameters require more pulses to reach a steady state as the background gas pressure increases.

This paper conducts a direct numerical simulation of the convective heat transfer of cold water in a Taylor-Couette system with a high-temperature and rotating inner cylinder， aiming to elucidate the flow features and heat transfer characteristics under different density inversion parameters. For this purpose， multiple density inversion parameters were selected to study the evolution of flow states from natural convection to turbulence. By examining the hydrodynamic and thermal behaviors of cold water across various parameter variations， this paper reveals the diversity of flow regimes and the tight association between heat transfer characteristics and flow features. With the increase in Reynolds number， the flow undergoes two transitions. The initial transition is from a buoyancy-dominated regime to a spiral vortex flow. Pronounced density inversion effects intensify the axial flow’s suppression of radial heat transfer， manifesting a minimal value of heat transfer near {\Theta }_{\mathrm{m}}=\mathrm{0.5}. The subsequent transition occurs within the rotation-dominated regime， where the flow progresses from wavy vortex flow to wavy turbulent vortex， accompanied by the emergence of Görtler vortices and an increase in smaller-scale structures at elevated Reynolds numbers， thus enhancing heat transfer capability. The mechanisms behind flow regime transitions are explored from the perspective of the combined effects of density inversion， centrifugal force， and buoyancy. The results suggest that a marked density inversion effect weakens the buoyancy effect and strengthens the sensitivity to the centrifugal force， leading to an earlier onset of centrifugal-dominated flow at a lower Reynolds number.

We measured the relative abundance of antibiotic resistance genes （ARGs） related to the treatment of brucellosis by quantitative real-time polymerase chain reaction （PCR）， characterized the bacterial composition by 16S rRNA gene sequencing， and analysed the relationships between ARGs and bacteria by network analyses in multiple environmental media samples （rainwater， topsoil and PM_2.5） collected in the summers from 2019 to 2021. The three environmental media of Hulunbuir Grassland were contaminated with some degree of ARGs with the highest ARG abundance in the topsoil. Significant relationships were observed between ARGs and bacteria， thereby promoting the spread of antibiotic resistance. Extensive distribution of ARG carrying bacteria in atmospheric particles， rainwater， and soil may also increase potential ARG exposure risks. These findings are valuable in understanding the ARG pollution levels and distribution characteristics in three environmental media， which can aid to design and implement policies to curb ARGs in local areas.

Based on the current situation and price data of forest land and mineral resources in Yunfu City of Guangdong Province， in 2010， 2015，and 2020， using geostatistical analysis techniques， dynamic index， and accounting models for economic value and ecological value， this paper explores the spatial-temporal differentiation of the value of regional advantageous natural resources assets， and reveals the dynamic changes of the physical quantity and value of forest land and mineral resources assets in Yunfu City. The results show that： in terms of the physical quantity of assets， the forest land and mineral resources in Yunfu City decreased by 1 622.89 and 16.69 hm² respectively from 2010 to 2015， and increased by 45 877.86 and 485.69 hm² respectively from 2015 to 2020； in terms of asset value， the value of forest land resources assets （including economic value and ecological value ） increased by 6.164 billion yuan from 2010 to 2015， and the value of mineral resources assets decreased by 272 million yuan. The amount of asset value of forest land resources （including economic value and ecological value） decreased by a total of 1.67 billion yuan from 2015 to 2020， and the amount of asset value of mineral resources increased by a total of 7.956 billion yuan， and the amount of asset value of forest land and mineral resources in Yunfu City experienced more significant changes from 2015 to 2020， and the amount of increase in their physical quantity was higher than the amount of change from 2010 to 2015， and was also higher than the overall amount of change from 2010 to 2020. The value of advantageous natural resource assets in Yunfu City is characterized by obvious spatial and temporal heterogeneity， and factors such as the level of regional economic development and policy regulation have a more significant impact on the amount of natural resource asset value.

Taking Northeast China as an example， utilizing methods such as agglomeration of newborn enterprise， kernel density estimation， and negative binomial regression model， this study analyzes the evolutionary characteristics and influencing factors of the spatial layout of wood processing enterprises under the background of the implementation of a typical ecologically-oriented environmental regulation policy — Natural Forest Protection Project （NFPP）. The results show that： 1） Under the context of natural forest conservation， wood processing enterprises have agglomerated in the densely populated urban belts of the central inland regions. There is a distinct tendency for them to cluster near provincial capital cities and their surrounding areas. In Harbin-Dalian urban agglomerations and areas along the Qiqihar-Harbin-Suifenhe railroad， new wood-processing enterprises are distributed in a particularly pronounced manner. 2） Diverse sub-industries of new wood processing enterprises exhibit varying spatial distribution characteristics and influencing factors. In comparison， industries such as sawn timber and engineered wood products， which are relatively lower-end in the wood processing sector， are more sensitive to changes in traditional economic geographic factors. As a result， their spatial layouts undergo more pronounced changes. 3）The influencing factors of new wood processing enterprise distribution are significantly different at various stages. With the implementation of NFPP， the dependence of the spatial layout of new wood processing enterprises on soft environments has increased， such as knowledge spillover， environmental regulation intensity， and marketization. The rigid constraints of traditional economic geographical factors have weakened， such as resource endowment and location conditions.

The eastern sandy land of Qinghai Lake is one of the most severely affected areas by wind-blown sand activities on the Qinghai-Xizang Plateau， threatening the stability of the regional ecosystem. This study analyzes different types and restoration ages of artificial plant communities to investigate the effects of vegetation restoration on suppressing aeolian activities. The results show that vegetation restoration reduces wind speed and decreases aeolian activity. The “Artemisia desertorum-Hippophae rhamnoides community” on fixed sandy land and the “Artemisia desertorum-Salix cheilophila community” on semi-fixed sandy land were more effective in reducing wind speed compared to shifting sands. Additionally， the structure and diversity of plant communities played a crucial role in wind erosion control， with increased species and functional diversity enhancing ecological functions. The study also found that artificial community restoration improved soil particle size distribution， increasing the content of fine and silt particles， thereby enhancing soil resistance to wind erosion. In summary， artificial vegetation restoration significantly improves ecological functions and mitigates aeolian activities， providing theoretical and practical guidance for ecological restoration in cold sandy areas.

The palm-leaf manuscript is a treasure of human civilization， which is the scripture written or engraved on the processed leaves of palm trees. Originating in ancient India， it was gradually introduced into China in the historical period， and reached a period of great prosperity in the Tang Dynasty. Chinese ancestors had a clear understanding of the materials used to make the palm-leaf manuscript. According to our study， the “Doro” （多罗） tree in ancient books should be talipot（Corypha umbraculifera）， while the “Beiduo” （贝多） tree should be palmyra（Borassus flabellifer）. The word “Beiduo”， which appeared many times in Chinese classical poetry， has become a synonym of Buddhist classics. Material evidence of ancient palm-leaf manuscript has been unearthed in many places in Xinjiang， among which Powell’s manuscript as well as Spitzer’s manuscript unearthed in Kuqa were of great significance， with the latter being considered to be the earliest physical evidence of palm-leaf manuscript all over the world. In addition， ancient palm-leaf manuscripts were also unearthed in the Mogao Caves in Dunhuang， which was also of great importance. To date， palm-leaf manuscripts are mainly preserved in Xizang， as well as Xishuangbanna in Yunnan Province， where they have been well organized and protected.​ The characters on the palm-leaf manuscripts were carved and written， respectively， which should be adapted to their preservation conditions.

Large earthquakes can trigger earthquakes directly or delayed at long distances， and in order to explore the triggering mechanism， it is necessary to gain a deeper understanding of the dynamic stress characteristics of strong teleseismic surface waves and their dynamic Coulomb stress change on long-distance fault surfaces. Four-component borehole strainmeters are capable of directly observing the stress tensor in the rock surrounding a borehole and are uniquely suited to study dynamic stress Coulomb stress changes. In this paper， we analyze the 100 Hz seismic strain waveforms recorded at 4 four-component borehole strain stations， namely， Youyu， Yingxian， Yangqu， and Huairen， in northern Shanxi Province， from the 20240123T020904 M_S7.1 earthquake in Wushi County， Xinjiang， China. P-， S-， and surface wave phases were identified， the dynamic Coulomb stress changes in the Kouquan fault zone for teleseismic earthquakes in dry-and water-saturated rock states were calculated comparatively， and the relationship between the epicenter distance and the maximum stress amplitude was estimated from the strain magnitude. The results show that the maximum amplitude of the body stress produced by the teleseismic earthquake in northern Shanxi is 0.96 kPa， and the maximum amplitude of the maximum shear stress is 1.37 kPa； the dynamic Coulomb stress change of the Kouquan fault （strike N35°E， dip 50°， normal fault） by the teleseismic earthquake has a peak value of 1.6 and 1.9 kPa when the medium is dry-and water-saturated rock， respectively， which is below the dynamic stress triggering thresholds， indicating that there is no obvious triggering relationship between the Shanxi Zuoyun M_S3.0 and Wushi M_S7.1 earthquakes that occurred in this fault zone. The ideas and methods in this paper provide a basis for research on the possible triggering effects of larger teleseismic earthquakes in the future.

As an important technique for the fine interpretation of the polarimetric synthetic aperture radar targets， the model-based polarimetric decomposition is dedicated to additively expanding the complex target scatterings over the canonical models of surface scattering， double-bounce scattering， and volume scattering. However， model-based decompositions suffer from negative powers and insufficient utilization of polarimetric information. The complete model-based decomposition （CMD） and its improvement solve these problems， but cause the so-called zero-power degradation. This is because CMD can not always extract a surface component and a double-bounce component from the remaining matrix after the removal of the volume scattering， and zero scattering power is then inevitable. CMD is reinforced in this paper. We find that the extraction of the surface and double-bounce components in CMD is essentially a sub-dichotomy of the canonical Huynen dichotomy that prefers volume scattering. By adaptively upgrading it with the other two sub-dichotomies of the canonical Huynen dichotomy that prefer surface scattering and dihedral scattering， respectively， the reinforced CMD can always decompose the surface and double-bounce components without degradation，and the problem of zero power is thus effectively solved. Qualitative and quantitative comparisons on measured polarimetric SAR datasets are presented to demonstrate the good performance of the proposed method.

In addressing the issue of inadequate precision in surface deformation estimation using the PSInSAR technique with small datasets， this study proposes a dual-weighted low-rank tensor decomposition algorithm for denoising the observed data of temporal interferometric phases. This algorithm enhances the applicability of tensor decomposition in the context of small dataset PSInSAR technology， particularly in larger urban areas. This article utilizes a dataset comprising 29 TerraSAR images from the Tianjin region and extracts a subset of 6 to 11 images as a small dataset for validating the proposed algorithm. The combined approach of dual-weighted tensor decomposition and PSInSAR is employed for ground subsidence estimation. Experimental results demonstrate a significant improvement in the quality of surface deformation estimation using the proposed algorithm for small dataset PSInSAR technology. In the region exhibiting detailed deformation under the condition of 11 images， the error in deformation rate estimation is reduced by approximately 82% compared to the results obtained using the original low-rank tensor decomposition algorithm with the same number of SAR images.

To address the issue of low defect recognition accuracy due to the scarcity of insulator defect samples in power inspection， we propose a recognition method that combines a fine-tuning training strategy with a cosine similarity softmax （CSM） classifier. This method applies a few-shot learning based on metric learning to the task of insulator defect classification. The approach consists of two main steps： first， pre-training the neural network on a large dataset； and second， using the fine-tuning training strategy and CSM classifier to optimize the model， integrating meta-learning and metric learning to transfer the relevant knowledge acquired during the pre-training and meta-learning phases to the domain of insulator defect image classification. Ablation experiments demonstrate that incorporating the fine-tuning training strategy increases recall by more than 0.66% and precision by more than 0.70%. Adding the CSM further improves recall by more than 0.50% and precision by more than 0.53%. Compared to other mainstream few-shot learning methods， our method shows improvements in recall and precision of over 0.67% and 0.62%， respectively. Experimental results indicate that the proposed method exhibits high performance in terms of accuracy， robustness， and generalization capability， confirming its effectiveness in the task of insulator defect image classification for power inspection.