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.

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.

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.

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.

A high performance CMOS sample/hold circuit is presented, which achieves the precision of 10-bit over Nyquist band in 50-MHz sampling frequency at 3.3-V supply. This circuit uses full differential circuits, bottom-plate sampling, bootstrap circuits and high performance gain-boost operational amplifier. Simulation in 0.35-μm CMOS process shows the circuit consumes 18-mW of power.

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.

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.

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.

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.

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.

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.

As a green ecological barrier in northern China， changes in the ecological environment of Hulunbuir steppe have a profound impact on both the regional ecological balance and， to some extent， the broader ecological equilibrium of the entire country. Based on the long-term MOD13Q1 vegetation index dataset and meteorological data， this study developed a dynamically adaptable vegetation cover index， gsNDVI， which is sensitive to the active vegetation season. The vegetation change trend and future development of the Hulunbuir typical steppe from 2000 to 2022 were analyzed using the Theil-Sen regression， the Mann-Kendall method， and the Hurst exponent. Additionally， partial correlation analysis was employed to investigate the impact of climate factors on vegetation change. The results show that the multi-year average gsNDVI value for the study area is 0.39， with a spatial distribution characterized by higher values in the northeast and lower values in the southwest. Overall， the mean gsNDVI value exhibits a slow growth trend， though periodic fluctuations are observed. Vegetation coverage has increased in most areas， though noticeable degradation is evident in urban areas. The partial correlation analysis results indicate that precipitation is the primary factor influencing vegetation cover change in the study area， with grasslands being the most sensitive to changes in precipitation. Furthermore， based on the combined results of trend analysis and the Hurst exponent， the vegetation trend in certain areas of Hulunbuir is expected to reverse in the future， which may pose significant challenges to ecological and environmental protection in the region.

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 integration of low earth orbit （LEO） satellite with 5G in the mobile communication system presents extensive application prospects. To ensure effective establishment of communication links between users and base stations， as well as reliable data transmission， time-frequency synchronization technology plays a crucial role. However， traditional timing and frequency synchronization algorithms face limitations when dealing with millimeter wave frequency bands， large bandwidths， high Doppler frequency shifts and change rates， and low signal-to-noise ratios in low-orbit satellite channels. These limitations result in decreased estimation accuracy. For the uplink service data channel of a 5G-based low orbit satellite communication system， a joint timing and frequency synchronization algorithm based on weighted embedded synchronization sequences is proposed to improve the accuracy of timing and frequency offset estimation. Simulation results demonstrate that the proposed timing and frequency synchronization algorithm outperforms traditional algorithms with comparable complexity in terms of synchronization performance.

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.

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.

Huanjing-1A （HJ-1A） CCD1 has four reflected solar bands in visible and near-infrared bands. The on-orbit absolute radiometric calibration frequency of HJ-1A/CCD1 is limited to the annual site calibration. Cross calibration， as a supplement means of site calibration， can achieve high-frequency on-orbit absolute radiometric calibration. In this paper， we select Terra/MODIS as the reference sensor to perform long time series cross calibration on HJ-1A/CCD1 based on Dunhuang calibration site. By limiting conditions such as the imaging angle difference （less than 20°）， the imaging time difference （less than 2 hours）， cloud cover， and imaging quality between HJ-1A/CCD1 and Terra/MODIS， a total of 147 effective cross calibration image pairs were screened out from September 2008 to December 2021. Then the 6SV v2.1 radiative transfer model was used to calculate the spectral band adjustment factor， and ultimately achieving long time series cross calibration of HJ-1A/CCD1. The results show that： 1） The cross-calibration coefficients calculated in this article are highly consistent with the officially published calibration coefficients， with an average relative difference of less than 2.25%. The calibration uncertainty is within 5.34%. 2） The long time series cross calibration results showed that after one year on-orbit operation， the gain status of HJ-1A/CCD1 was adjusted on October 20， 2009， resulting in a sudden change in the cross-calibration coefficients on the 409th day after launch. After the adjustment， the overall radiometric performance was relatively stable. 3） The radiometric performance of HJ-1A/CCD1 showed a slow and fluctuating downward trend from October 2009 to December 2021， with an annual attenuation rate of less than 3.10%. The method proposed in this paper can effectively improve the radiometric calibration frequency and accuracy， and can be used for radiometric performance monitoring over the whole life cycle of HJ-1A/CCD1.

Bayesian inference often faces challenges where the likelihood function is difficult to evaluate or lacks explicit expression， known as likelihood-free Bayesian problems， where posterior distributions can only be inferred indirectly through samples generated under specific parameters. Existing methods such as approximate Bayesian computation， synthetic likelihood， and Bayesian optimization focus on addressing these issues. This paper extends Miller et al.’s （2022） sequential neural ratio estimation method for likelihood-free Bayesian problems by transforming likelihood-to-evidence ratio estimation into a multi-class problem for efficient posterior estimation. We introduce a new calibration kernel-based ratio estimation method （CKRE）， to enhance the original method’s training efficiency and performance. The convergence of our proposed method is proven， and numerical experiments demonstrate its significant improvement in accurately estimating posterior distributions under limited sample generation conditions.

Machining feature recognition is crucial in computer-aided design （CAD） and manufacturing （CAM） as it serves as a vital link between CAD and CAM systems. Researchers have proposed two types of machining feature recognition methods： rule-based and learning-based， with the latter showing superior performance and garnering more attention. However， existing recognition methods face challenges such as insufficient utilization of geometric information， inaccurate machining feature localization， and complexity in the instance segmentation process. To address these issues， this paper proposes PT-MFR， a CAD model machining feature recognition method based on Point Transformer. It performs two tasks： semantic segmentation and instance segmentation， predicting the semantic category of machining features for each face and calculating face similarity to segment the machining feature instances. The results of both tasks are integrated to obtain the machining feature recognition results. Experimental results demonstrate that the proposed method outperforms other methods.

As the resolution of airborne synthetic aperture radar continues to improve， motion compensation has become a core link to ensure high-quality imaging. This paper conducts an in-depth analysis of the motion error of chirped pulse SAR， and proposes a Chirplet transform motion compensation algorithm based on original echo data to address the problem of non-space-variant phase error compensation of SAR. This algorithm uses Chirplet transform for time-frequency analysis to accurately characterize the phase error in the echo data， uses maximum likelihood estimation to extract the modulation frequency of the phase error， and solves the phase error for motion compensation. Compared with the PGA algorithm， this algorithm does not need to rely on strong scattering points and can achieve better image focusing performance in the presence of large phase errors. Compared with the MD subaperture algorithm， this algorithm performs frequency modulation rate estimation for each point， resulting in a more precise estimation. Finally， simulation experiments and quantitative analysis verified the effectiveness of the algorithm.