Risk analysis of Portfolio is studied ,by comparing Copula functions and the traditional VaR methods,mixing copula is made. By backtesting ,the empirical research shows that mixing Copula method makes better VaR model .

The redox property of palladium nanoparticles (NPs) is pivotal to CeO₂ supported Pd catalysts in oxidation reactions and is closely related to the structure of Pd-CeO₂ interface. Herein, we report that low-temperature CO oxidation activity of Pd/CeO₂ highly depends on the shape and crystal plane of CeO₂ supports. Pd/CeO₂ catalysts with CeO₂ nanoocthedrons (NOCs) and nanocubes (NCs) as supports were prepared by colloidal-deposition method. Results show that Pd/CeO₂ NOCs with ceria {111} facets enclosed exhibited much higher catalytic activity than Pd/CeO₂NCs with ceria {100} facets exposed. DFT calculations revealed that the redox property of surface Pd species may play important roles in determining the reducibility and activity of catalysts. The PdO_x to Pd cycle is more facile on Pd₄@CeO₂(111) than on Pd₄@CeO₂(100), which is dictated by the Pd-ceria interaction in the end. Our results show that the redox property of surface Pd is pivotal to the reducibility and activity of Pd/ceria catalysts, which could be tuned by manipulation of the Pd-CeO₂ interaction via tuning the exposed facets of ceria support.

This review aims to guide the future development of related research in the field of learning path planning through the analysis of the current research status of learning path planning. Specifically, this review first introduces the definition of learning path planning and the commonly used parameters in learning path planning methods; then, it classifies in detail according to the algorithms used to generate learning path planning and summarizes the advantages and disadvantages of various learning path planning methods. In addition, the data set and evaluation method used by the learning path planning method is introduced. Finally, the challenges faced by the learning path planning method are summarized and the future development trend is predicted.

GH3 genes belong to a primary auxin-response gene family. The 10 promoter sequences of Arabidopsis GH3 genes were analyzed using bioinformatics method. The results show that the transcription start site of these genes is generally 65~145bp away from the start codon, and the TATA boxes are located in the (-24)-(-40)bp. MDB and MatInspector analyses show that most upstream regions of these GH3 genes contain the cis-elements required for tissue and organ-specific expression responding to phytohormones and external environment, indicating that the expressions of GH3 genes are strictly controlled by multi-factors. Gene chip data show that AuxREs is very important for GH3 genes in response to IAA treatment,but it is not the unique cis-element for auxin response.

This paper overviews the significance, advances and future direction in the glycobiology field. Special emphasis is given to cell cell adhesion which is mediated by the interaction between carbohydrates and carbohydrates binding proteins (CBP). The roles of carbohydrates in the folding of nascent polypeptides, immune system, and cellular signal transductions are also reviewed. The scope also covers carbohydrates in infections, carbohydrates in diseases,and chemical synthesis/structural analysis of carbohydrates. Finally,the features and future directions of glycobiological research are pointed out by the author.

Poly (vinyl alcohol) (PVA) and its derivatives,the excellent water-soluble polymers,have attracted more and more attention,as they show the usability in many processes,as well as possess the promise of degradation in the presence of some specific microbials.In the present paper,the recent advances in the biodegradation of PVA and its derivatives,including the mechanism,influential factors,evaluation method and degradation environment etc,have been reviewed.Moreover,the latest development of PVA-based blendsPcomposites and their biodegradation is also introduced in the present article.

Light field is a representation of full four-dimensional radiance of all rays with spatial and angular information in free space, and capture of light field data enables many new development potentials for computational imaging. The historical development of light field photography is summarized, and typical light field photography devices are categorized in view of capture methods for 4D light field. Based on the principles of light field camera, computational imaging theorem, refocusing theory, synthetic aperture refocusing algorithm, and light field microscopic technology are emphatically described. Finally, the promising application perspectives and existing critical issues of light field imaging are discussed.

The micron-grade PMMA microspheres with narrow size distribution were prepared by dispersion polymerization. The mechanism of the dispersion polymerization was discussed. The factors influencing both the size and size distribution of the microspheres including initial concentrations of the initiator, monomer, stabilizer, the polarity of the medium and the reaction conditions were studied. The results indicated that the size and size distribution of microspheres both increased with initial concentrations of initiator and monomer. Increasing the amount of the stabilizer resulted in decreasing size and narrowing size distribution of microspheres. Other factors such as the polarity of medium and the reaction temperature had great influences too. By controlling these factors, the desired-size monodisperse microspheres could be obtained.

Textual document clustering is one of the effective approaches to establish a classification instance of huge textual document set. Clustering Validation or Quality Evaluation techniques can be used to assess the efficiency and effective of a clustering algorithm. This paper presents the quality evaluation criterions from outer and inner. Based on these criterions we take three typical textual document clustering algorithms for assessment with experiments. The comparison results show that STC(Suffix Tree Clustering) algorithm is better than k-Means and Ant-Based clustering algorithms. The better performance of STC algorithm comes from that it takes accounts the linguistic property when processing the documents. Ant-Based clustering algorithm’s performance variation is affected by the input variables. It is necessary to adopt linguistic properties to improve the Ant-Based text clustering’s performance.

Responsive to dehydration (RD) is a class of genes that regulates dehydration in plants. They are functionally tolerant to plant dehydration, some of which are responsive to abiotic stresses such as low temperature and high salinity. However, they belong to different families, respectively, and have discrepancy in the structure and function. In this paper, the structural composition, conserved motif, regulatory mechanism, and the function in response to biotic and abiotic stress were summarized in different RDs, as well as the different cis-acting elements in the promoter region played a role in response to abiotic stress so as to provide relevant basis for future researches on RD.

Gram-Schmidt algorithm is one of the fundamental methods in linear algebra, which is mainly used to compute QR decomposition. The classical and modified Gram-Schmidt are both based on level 1 or level 2 BLAS operations which have low cache reuse. In this paper, a new block Gram-Schmidt algorithm is proposed. The new algorithm ensures the orthogonality of resulting matrix Q is close to machine precision and improves performance because of using level 3 BLAS. Numerical experiments confirm the favorable numerical stability of the new algorithm and its effectiveness on modern computers.

DBSCAN is a classic density-based clustering algorithm. It can automatically determine the number of clusters and treat clusters of arbitrary shapes. In the clustering process of DBSCAN, two parameters, Eps and minPts,have to be specified by uses. In this paper an adaptive algorithm named SA-DBSCAN was introduced to determine the two parameters automatically via analysis of the statistical characteristics of the dataset, which enabled clustering process of DBSCAN fully automated. Experimental results indicate that SA-DBSCAN can select appropriate parameters and gain a rather high validity of clustering.

A design of high resolution camera system based on DALSA’ s CCD evaluation kit EKxxxx was presented. It was composed of a pulse pattern generator (SAA8103), a vertical line driver (TDA9991), four analog-to-digital interfaces (TDA9965) and a system controller (P89LV51RD2). Camera link with medium configuration was adopted to transfer digital images. The software for controlling and debugging the camera was developed. To correct the non-uniformity of 4 outputs, a method based on two-point correction was described. The system can acquire ultra high resolution pictures at a high frame rate thus it is suitable for aero photography.

In recent years, the heavy metal pollution incidents in China were frequently reported. However, studies on pollution, sources, and control strategies of atmospheric heavy metals in China are rare. We summarize the research results reported in recent years. The features of pollution level, seasonal variation, regional differences, size distribution of the atmospheric heavy metal elements including Pb, V, As, Mn, Ni, Cr, and Cd in China are analyzed. The main sources, current control status, and control technologies of atmospheric heavy metals are discussed. Comprehensive suggestions for China's heavy metal pollution control are put forward based on the summarization of the progress and experience of the atmospheric heavy metal pollution control in other countries and regions.

Gallium nitride is a novel kind of semiconductor,whose direct band gap is 3139eV at the room temperature. It has been proved to be a promising material for electronic and photoelectric devices. A good many of its growth methods have been discovered, and some of them had been implemented in production practice with monitoring systems. Some comparisons were made between different methods. The structure-performance dependence of GaN itself, GaN-based family and multinitrides have been summarized. The main fields of GaN-based material were presented. GaN-based material is being considered to be the excellent candidate of electronic device potentially used in high temperature,high-power and worst environment surroundings.

Uranium dioxide is a kind of steady nuclear fuel that has the characteristic of high melting point and steady property. The thermal conductivity of uranium dioxide can directly influence the temperature distribution of nuclear fuel and the max temperature of the center of nuclear fuel. The experimental results and expression of thermal conductivity have been compared in the paper. The deviation between the experiment results has decreased. The non-equilibrium molecular dynamics simulation results are in good agreement with the experiment results in medium temperature region. In low temperature region, it is necessary to add the quantum correction to the kinetic energy computation of phonon. In high temperature region, it is needed to use the accurate potential model and build up the electron gas energy transport model and photon radiation energy transport to study the thermal conductivity well and truly for the nuclear reactor safety design and uranium dioxide engineering application.

Cyclopentenones are important synthetic building blocks and as motifs appear in bioactive molecules and natural products. We applied density functional theory (DFT) calculations to gain insight into the modular strategy involved in the palladium-catalyzed synthesis of cyclopentenone from α,β-unsaturated acid chlorides and alkynes in the presence of hydrosilane. The study unveils that the transformation proceeds via the sequence:the disassembly of α,β-unsaturated acid chloride into vinyl, carbonyl, and Cl fragments with the palladium catalyst; carbon monoxide release; coupling of alkyne with vinyl group; carbon monoxide re-coordination and migratory insertion to form another C-C bond with alkyne, ring-closure via C=C bond insertion, transmetalation with hydrosilane, C, H-reductive elimination to release the product. Different from the mechanism proposed by the experimentalists, the CO group is involved in the reaction via separate liberation and re-coordination in the solvent cage, rather than persistent coordination with palladium. The transmetalation for H/Cl exchange takes place at the late stage and is a bottleneck of the transformation, instead of at early disassembly stage.

In this paper, we present a new method based on self-modification mechanism to protect softwares against illegal acts of hacking. The key idea is to converse key codes into data in the original program so as to make programs harder to analyze correctly. Then, we translate data to executable codes by enabling the virtual memory page which stores the hidden code to be executable at run-time. Our experiments demonstrate that the method is practical and efficient.

Activated alumina (AA) is widely used for defluoridation. Batch experiments were carried out to investigate the influence of Cl^- (1000 mg·L^-1) and HCO₃^- (2000 mg·L^-1) on adsorption kinetics of F^- (10 mg·L^-1) on AA in coalbed methane co-produced water (CBMW). The results show that in the presence of Cl^- the adsorption rate and the equilibrium absorption capacity increase, but in the presence of HCO₃^- both the quantities decrease. These effects should be considered when one treats CBMW.

Calmodulin, the predominant calcium receptor, is one of the best-characterized calcium sensors in eukaryotes which regulates diverse cellular functions by modulating the activity of a variety of enzymes and proteins. Research workers have evidences suggesting Ca2+ and calmodulin are involved in various environment stimulation reaction. By differential screen, we isolated a positive clone in the T.caerulescens cDNA library induced in response to Cd2+. The result of cDNA sequence analysis showed that the positive clone shared more than 92 % homologies for nucleotide sequences with CaM2 gene from Arabidopsis thanliana, named TcCaM2. The TcCaM2 gene consists of 447 nucleotides and encodes 149 amino acids, and it shares more than 83 % homologies for nucleotide sequences and 95 % for encoding amino acid sequences as compared with those of calmodulin genes of other plants. A yeast-expressed plasmid with TcCaM2 was constructed and transferred into heavy metal sensitive yeast mutant cells. Further study about the growth patterns of TcCaM2 -expressed yeast indicated that over expression of TcCaM2 improved Co2+、Ni2+ resistance and increased Cd2+ hypersensitivity in the yeast cells. As an important role in the T.caerulescens’s response to heavy metal, TcCaM2 can work as a significant gene tool in the phytoremediation of heavy metal pollution.

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.

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 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.

Super-resolution technology has become an important tool for reconstructing high-resolution datasets and supplementing the shortage of high-resolution images with its characteristics of flexibility and low cost. Compared with natural images， remote sensing images of real scenes are complex and specific， which make super-resolution tasks more difficult. Meanwhile， for remote sensing images， traditional deep learning models can improve the resolution， but there is still a great deficiency of improvement for the details and textures of the ground objects. Therefore， based on the generative adversarial network model， this paper fuses channel-space attention to enhance the feature learning capability of the network and use an artifact suppression strategy to distinguish smooth regions from detail-rich regions， so that the network can focus more on detail-rich regions and suppress the generation of artifacts. Extensive experiments on GaoFen satellite data show that the quantitative metrics and visual quality of the method proposed in this paper are better than those of the current mainstream methods.

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.

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.

This article takes 567 national level (168) and provincial level (511) traditional villages in Shandong Province as subjects of investigation. Firstly, a spatial econometric model is used to analyze the spatial distribution characteristics of traditional villages in Shandong Province. Secondly, the Delphi method and SPSS factor analysis method are used to screen and analyze the evaluation indicators. A total of 28 indicators including village cultural resources, village ecological and natural resources, institutional management, tourism infrastructure, and village economic vitality are obtained. Finally, the AHP entropy weight method is used to combine weights to score the selected indicators. A scoring table for tourism development potential of traditional villages in Shandong Province is constructed, and a multi-objective linear weighted function model is used for scoring. The results showed that: 1) The overall spatial distribution of traditional villages in Shandong Province is uneven, mostly distributed in mountainous areas or underdeveloped areas of cities with relatively uneven development and underdeveloped infrastructure; 2) Among various indicators, the cultural resources (0.331 2) and institutional management (0.144 0) of the village play an important role, followed by tourism infrastructure (0.143 7), village ecological and natural resources (0.143 4), and village economic vitality (0.097 7); 3) The evaluation results show that there are 135 key traditional villages (S≥7.9) in Shandong Province, accounting for only 23.81% of the total number of traditional villages in Shandong Province; there are 295 traditional villages (6.2<S<7.9), accounting for 52.03% of the total number of traditional villages in Shandong Province; there are 137 traditional villages with a focus on protection (S≤6.2), accounting for 24.16% of the total number of traditional villages in Shandong Province; 4) Based on the characteristics of various traditional villages, corresponding development strategies are proposed in this paper.

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.

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.

Regime shifts and their underlying mechanisms in ecosystems are a critical issue in ecological research， with profound implications for predicting ecological risks under global change. This review systematically synthesizes the theoretical advances in alternative stable state （ASS） of ecosystem multi-stability， focusing on three key dimensions： micro-macro process coupling， mechanisms of threshold response， and the role of regulatory nodes in ecosystem resilience. By integrating methodologies such as ASS theory， potential landscape modeling， and bifurcation analysis， we highlight how climate change and anthropogenic activities are driving critical ecosystems （e.g.， coral reefs， Amazon rainforest， Arctic permafrost） toward tipping points， while hysteresis effects and irreversible potentials exacerbate recovery challenges. Emerging approaches combining network theory and energy （carbon） flux analysis offer novel insights for cross-scale early warning， yet bridging micro-scale mechanisms with macro-scale patterns remains a critical challenge. This review provides a theoretical framework for ecological threshold management and underscores the urgent need for interdisciplinary approaches to address planetary-scale regime shift risks.

The coordinated development of regional economy-resource-environment system (ERE) is a crucial aspect of achieving the sustainable development goals. Taking Binzhou City in Shandong Province, a typical city in the Yellow River Delta, as an example, this paper constructs a coupling coordination degree model and examines the coupled and coordinated development of its ERE system from 2000 to 2020. Furthermore, a system dynamics (SD) model of Binzhou City’s ERE is constructed based on 71 indicators, through which causal feedback relationships and flows among subsystems are illustrated. Four scenarios are set for simulation as follows: current trend continuing mode, secondary industry leading mode, resource and environment prioritizing mode, and system coordinated mode. The results show that: 1) Over the past 20 years, the level of coupled and coordinated development in Binzhou City has been increasing year by year, and the type of coupled and coordinated development has gradually transitioned from an unbalanced state to a well-coordinated state, but there is still instability in the ERE; 2) Through SD parameter calculation and multi-scenario simulation analysis of Binzhou City’s ERE, it is pointed out that continuing the current development model cannot achieve high-quality sustainable development in Binzhou City. Therefore, a coordinated and stable development model, which takes economic, resource, and environmental benefits into account, is suggested as the relatively optimal solution for Binzhou City to achieve sustainable development in the long run.

The identification of paleo-cropping layers is an essential part of the study of the origins of agriculture and the exploration of ancient human land use. It is a challenge that archaeologists and palaeoenvironmentalists are facing together. The existing methods of identifying ancient cultivation layers are costly and limited, and there is an urgent need to develop new, simple, convenient, and reliable methods to identify ancient cultivation layers. Farming without irrigation, using plows to turn the land, once occurred in Beijing’s Dongling Mountain and continued for at least 300 years before retiring. There are also natural meadows and broadleaf forests in the area with no tillage history. In this study, four types of soil profiles, namely natural meadow, natural broadleaf forest, abandoned farming meadow, and abandoned farming broadleaf forest, were compared in terms of their soluble salt content, pH, magnetic susceptibility, and color characteristics in order to establish a method for identifying ancient cultivation layers. It was found that the soluble salt content in the abandoned farming soil profile was significantly lower than that in the natural profile, and the coefficient of variation was also significantly lower than that in the natural profile. The soluble salt content and its coefficient of variation can be used to identify ancient tillage layers without irrigation. Soil magnetic susceptibility and pH also have potential value in identifying ancient cultivation layers, and further in-depth studies are needed.

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.

The potential of light detection and ranging (LiDAR) technology in the application of individual tree segmentation and parameter estimation in desert Haloxylon ammodendron forests has not been explored. This study uses UAV LiDAR data to extract canopy height models (CHM) at spatial resolutions of 0.1, 0.25, 0.5, and 1 m on different interpolation methods, and applies the CHM seed point segmentation algorithm to segment individual trees in three types of Haloxylon ammodendron plots with different growth conditions. This study evaluates the impact of spatial resolution and growth conditions on segmentation accuracy, and verifies the extraction accuracy of tree height and crown width with field measurement data. The results show that the inverse distance weighting interpolation has a higher segmentation accuracy in this study. Spatial resolution is a key factor affecting the results of individual tree segmentation, with the best segmentation results obtained at a resolution of 0.25 m.Class III plots had the highest segmentation accuracy, which was 27% higher than that of Class II plots and 44% higher than that of Class I sample plots. The overlapping crowns of Haloxylon ammodendron in plot I make it difficult to distinguish the crown boundaries, while the independent crowns in plot III make it easier to achieve accurate segmentation. The R² of the tree height fitting model for all three types of plots is around 0.80, with RMSE less than 0.31 m. The R² of the canopy extraction fit for the Class I and II plots is around 0.70, with a slightly higher RMSE error, and the branches in a half dead state of Haloxylon ammodendron in plot III affect the extraction accuracy of crown width. This study demonstrates that LiDAR data has great potential for individual tree segmentation in desert Haloxylon ammodendron forests, which can provide data support for desert forests carbon sink estimation in Xinjiang.

This paper addresses the research challenges in unmanned aerial vehicle communication networks, including significant interference among multiple users, high complexity of dynamic models, and the difficulty in designing real-time optimal control strategies. For the first time, the multi-antenna technology is introduced into the quadcopter unmanned aerial vehicle (UAV) communication network, proposing a complex communication network model under the 3D multi-user multiple-input single-output scenario. This model takes into account the small-scale variations of UAV attitudes and their impact on channel quality. Additionally, the space division multiple access technology is employed to effectively mitigate inter-user interference model predictive control. In this context, an online UAV attitude control and resource allocation strategy based on model predictive control(MPC) algorithm is designed. By iteratively solving the open-loop control problem with a rolling window of limited time duration, the average spectral efficiency of the UAV communication system is maximized. Simulation results demonstrate that the proposed coupled communication model significantly improves system gains, and the control strategy efficiently optimizes UAV flight trajectories and allocates communication resources in dynamic environments.

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.

The use of excavated soil from highway construction sites to produce foamed polymeric soil， employed as a thermal insulation layer for seasonally frozen subgrades， not only achieves comprehensive resource utilization but also mitigates frost damage to the subgrades. Based on the excavated soil along the Urumqi Ring Expressway， combined with cement and foam， the foamed polymeric soil with porous insulation properties was developed. The influences of wet density， soil admixture， and water-cement ratio on the thermal conductivity， unconfined compressive strength， and stiffness of foamed polymeric soil were systematically investigated， establishing an intrinsic connection between pore structure and macroscopic performance. The research findings indicate that when the density of foamed polymeric soil increases from 600 kg/m³ to 1 200 kg/m³， its thermal conductivity approximately doubles， strength increases by about 3.95 times， and modulus increases by approximately 10.5 times. Compared to traditional subgrade soil， the thermal conductivity of foamed polymeric soil is significantly reduced by 52%-96.4%. Further analysis of the pore structure reveals that as the pore size of foamed polymeric soil within a unit volume decreases， the proportion of the skeleton increases correspondingly， while the volume of air pores decreases. This microstructural change manifests as improved thermal insulation performance （i.e.， reduced thermal conductivity） and significant enhancement in mechanical properties （including strength and stiffness） at the macroscopic level. Foamed polymeric soil not only demonstrates better thermal insulation performance but also exhibits strong mechanical characteristics， providing a suitable solution for the thermal insulation layer of seasonally frozen subgrades.

Multitemporal polarimetric synthetic aperture radar (SAR) provides abundant polarimetric scattering information, which is of great value to the long-term monitoring of various crop lands. To make full use of the time correlation and polarimetric information of multitemporal polarimetric SAR, this paper proposed a multitemporal polarimetric SAR crop classification method, which is based on the complete polarimetric covariance matrix. The method can maintain the complex matrix structure of covariance matrix and realize the independent representation of time dimension in tensor space, so that it can be applied to both full- and compact-polarimetric SAR. The method adopted the object-level classification strategy. Firstly, the superpixel segmentation of multitemporal SAR data was achieved by the simple linear iterative clustering (SLIC) method. Then, the covariance matrices of multitemporal SAR were expressed as tensors, and the multilinear principal component analysis (MPCA) method was used to reduce the feature dimension. Finally, the crop classification is achieved by decision tree. In this research, four multitemporal RADARSAT-2 Fine Quad SAR images covered Wuqing District，Tianjin, were used for the crop classification experiments. Compared with methods proposed in other references, the method proposed in this paper achieved the highest overall classification accuracy. Besides, the proposed method was applied to the π/4 mode and the CTLR mode compact-polarimetric SAR to discuss the capability of different kinds of polarimetric SAR in crop classification. Compared with the full-polarimetric SAR, the compact-polarimetric SAR could achieve comparable classification accuracies, but the full-polarimetric SAR performed better at the classes with small sample size, such as rice and lotus.

Single image super-resolution （SISR） can improve the resolution of remote sensing images （RSIs）， thereby improving the application value of data. At present， the number of pixels of RSIs generally reaches hundreds of millions， and it is usually necessary to divide the image into patches when performing SISR. However， there is a lack of relevant research on how to effectively determine the patch size and whether different sizes affect the results. In this paper， taking a large-scale high-resolution RSIs as the experiment data， 3 typical SISR models are selected， 9 groups of SR experiments under different patch sizes are carried out， and the super-resolution （SR） results for the whole of the large-scaled RSI are analyzed comprehensively both qualitatively and quantitatively. The results show that： 1） Cutting of the patches results in stitching seams at the stitching place. In particular， when the patch size is small， a large number of stitching seams show a block effect and the inconsistency is more obvious. 2） With the increase of the patch size， the SR accuracy of the three models is improved， and the overall computational efficiency is also improved. When the test patches are larger than the training patches， the elapsed time and accuracy stabilize. 3） The feasibility and accuracy of the whole RSI input are closely related to the model. The ESPCN model has the best accuracy when inputting the whole RSI， the RDBPN model may cause the accuracy to decrease due to the non-square matrix of the RSI， and the HSENET model has high requirements for computing power and cannot calculate the whole RSI. In conclusion， this paper provides an experimental basis for the selection of patch size for RSI SR engineering applications.

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.