The catalysts PtxTi/MCF and Pt/yTi-MCF were obtained by adding Ti element to mesocellular silica foam (MCF) support in two different ways. The catalytic activities of these catalysts for the complete oxidation of benzene, n-hexane and ethyl acetate were studied. The effects of different catalyst preparation methods, Ti addition amount and calcination temperature were investigated in detail. In addition, the structure and physicochemical properties of some of the support and catalyst were characterized by nitrogen isothermal adsorption-desorption, Raman spectrum analysis, small and wide angle XRD. The results show that, Pt8Ti/MCF has good catalytic activity and stability for the complete oxidation of benzene, n-hexane, and especially ethyl acetate. It was prepared simply by impregnating the mixture solution of platinum acetylacetone and titanium acetylacetone and then calcination, which exhibits a good application prospect in future.

This paper proposes to employ matrix weighted NURBS surfaces to fit and fair quad meshes. For a quadrilateral mesh with given or estimated unit normals at vertices, a matrix weighted NURBS surface can be constructed by choosing the mesh vertices as control points and employing normals at each vertex for computing matrix weights. Compared with traditional NURBS surfaces, matrix weighted NURBS surfaces have quasi-cylindrical accuracy. When the input data is uniformly sampled from a smooth surface, the constructed matrix weighted NURBS surface has good smoothness and fits the mesh model well; if the input grid data contain noise, a fair fitting surface that approximates the original grid well can still be obtained by resampling control vertices on current fitting surfaces and re-calculating vertex normals based on the new quad meshes iteratively.

To improve the catalytic ability of nano zero-valent iron in a Fenton like reaction system and reduce the agglomeration of nano zero-valent iron materials, the liquid phase reduction method was used to prepare biochar loaded nano zero valent iron materials (nZVI@BC). The material was characterized and the methylene blue was degraded to explore the material properties, the optimal degradation conditions and the action mechanism. The results showed that nano zero-valent iron had been successfully and evenly distributed on the surface of biochar. The prepared material was of high purity and good stability. In the degradation optimization experiment, the optimal reaction condition for degradation of 100 mg·L^-1 methylene blue solution was 25 ℃, the initial pH=3, the dosage of nZVI@BC is 30 mg·L^-1 and the dosage of H₂O₂ is 4 mmol·L^-1. Under this condition, methylene blue solution can be almost completely degraded in 10 minutes. It had found that hydroxyl radicals played a major role in the degradation process. The chromogenic functional groups first broke, followed by the destruction of the aromatic ring structure, and ultimately completed degradation. And the material had a good recycling performance. After three cycles, the removal rate of methylene blue was still above 85%. In actual printing and dyeing wastewater treatment experiments, nZVI@BC had a good wastewater treatment effect. When the dosage of H₂O₂ was 0.9 mmol·L^-1, the dosage of nZVI@BC was 60 mg·L^-1 and the pH≤ 4.5, the COD_cr decreased to below 50 mg·L^-1, up to the standards for reuse water.

In order to improve the efficiency and quality of parametric tread pattern retrieval, a novel method is proposed. Firstly, the tread pattern model in B-rep format is converted into an attribute adjacency graph, in which the edge compatibility is used for inexact matching of two attribute adjacency graphs and for the calculation of graph similarity. The geometric features reflected by the design parameters are used to define similarity of tread pattern models. Secondly, to improve query efficiency, various design parameters are used for rough space division and recursive clustering on the tread pattern database. An index structure based on the cluster tree is constructed to speed up model retrieval. Our experimental results show the superiority of the proposed method over the general model retrieval methods, both in search efficiency and quality. This demonstrates the advantage of utilizing design parameters and geometric information of the tread pattern in CAD model retrieval.

Improving the segmentation quality of 3D meshes is always an important problem to computer graphics. To handle this problem, this paper proposes a shape-aware graph attention network. The shape-aware graph attention coefficient is defined to better reflect the similarity between nodes, which not only expands the attention coefficient obtained by network learning with the help of edge features between nodes, but also introduces the attention coefficient related to the local shape information of nodes. On the other hand, the network architecture is adjusted by taking both shape features and labels of 3D mesh model as the input of graph attention network, which enables the participation of labels in network training and verification stages. Residual connection is further employed to make the network output more stable. A large number of experiments show that the proposed algorithm can obtain accurate segmentation boundaries. Compared with the existing classical segmentation algorithms on PSB dataset, the proposed algorithm improves 2% in accuracy, and achieves better Rand index. The reasonableness of the algorithm is proved by ablation experiment.

Herein, a novel one pot synthesis of chiral δ-substituent caprolactam strategy which applies 1-substituent homoallylic amine as the starting material is reported. This method combines the enzymatic dynamic kinetic resolution (DKR) and ring cross metathesis. Moreover, the configuration of caprolactam can be controlled by using lipase and protease as the DKR catalyst. The enantiomeric excess value of obtained R- and S-caprolactam can reach up to 90% and 82%, the yield can also be above 82% and 70%.

This paper discusses the effect of ex-situ ecological combined remediation (ESECR) system on the purification of phosphorus of different forms in the polluted water of Pulin Creek, a tributary of Jiulong River, and each unit of ESECR treatment system is analyzed on the correlation between different phosphorus forms and environmental factors. Results showed that the average total removal rate of TP, DTP, DP and PP of ESECR treatment system were 84.3%, 84.4%, 90.8% and 78.9% respectively, among them the DP purification effect was the best. In each unit of ESECR treatment system, when the phosphorus content in the raw water was low, the sludge-membrane symbiotic (SSM) high efficiency coagulation water purification system had good TP, DTP and DP purification effect, the average removal rate were 81.4%, 76.0% and 84.8% respectively, the average removal rate of PP was 66.7%; when the content of phosphorus in the raw water was high, the average removal rate of TP, DTP and DP of the SSM high efficiency coagulation water purification system were 37.8%, 44.6% and 45.8%, nevertheless, the purification effect of PP was significant, and the average removal rate was 93.2%. When the processed water of the SSM high efficiency coagulation water purification system with low phosphorus content, the purification effect of ecological pond Ⅱ on TP and DTP was better than that of ecological pond Ⅰ, but the results on DP was opposite. For PP, the purification effect in ecological pond Ⅱ was better than that in ecological pond Ⅰ regardless of the impact of phosphorus content. The purification effect of ecological pond Ⅲ fluctuated, the purification effect on DP is relatively significant, and the average removal rate was 94.1%. In addition to the SSM high efficiency coagulation water purification system, the form of phosphorus in the polluted water of Pulin Creek and purified water by ESECR technology was mainly PP, and the percentage of each form in total phosphorus appeared as PP>DTP>DP. Pearson correlation analysis showed that different phosphorus forms were correlated with pH, water temperature and dissolved oxygen (DO) in ESECR treatment system.

Advanced oxidative processes of persulfate (PS-AOPs) have promising applications in antibiotic wastewater treatment due to their strong oxidation capacity and good selectivity. In this study, Sargassum fusiforme was selected as a raw biomass, and ZnCl₂ carbonation-pyrolysis was adopted to prepare zinc chloride modified sheep sorrel biochar which was used as a catalyst to catalyze persulfate (PDS) to degrade the norfloxacin (NOR) in the water. The results showed that different ratios of ZnCl₂ doping would significantly affect the performance of biochar, and the catalytic efficiency of the prepared biochar was optimal when the ratio of algal powder to ZnCl₂ was 1∶1. Moreover, SEM, BET, XRD characterizations were employed to investigate the physical and chemical properties of YQZn in order to further explore the modification mechanism of ZnCl₂. The catalytic efficiency result of YQZn under different conditions showed that the biochar had the best NOR removal rate of 95.09% under the conditions of PDS concentration was 1 mmol·L^-1, modified biochar addition was 0.3 g·L^-1, pH=9 and NOR concentration was 10 mg·L^-1. \mathrm{S}{\mathrm{O}}_{\mathrm{4}}^{·-}, HO· radicals, and ¹{\mathrm{O}}_{\mathrm{2}} played a leading role in activating PDS in the system by free radical quenching. To solve the difficulties in biochar powder recovery YQZn geopolymer composite catalyst (GB) was prepared by using biochar loaded on porous geopolymer. The results showed that GB had excellent degradation activity and reuse performance, which successfully realized the loading and recycling of biochar, and thus had great potential for continuous treatment of norfloxacin in water.

V-system is a kind of complete orthogonal piecewise polynomial function system on L^{\mathrm{2}}[\mathrm{0,1}], because of the discontinuous nature of its basis functions, it has significant advantages in the expression and analysis of discontinuous signals. However, in the current V-system transformation algorithm, for a signal with a length of N, it not only needs to generate and store an N-order orthogonal matrix in advance, but also its time complexity is as high as \mathrm{{\rm O}}(N^{\mathrm{3}}). Therefore, in order to adapt to the efficient processing needs, this paper designs and implements a fast decomposition and reconstruction algorithm for V-systems from the perspective of multi-resolution analysis of V-systems. This fast algorithm does not need to store additional information, and its time complexity is only \mathrm{{\rm O}}(N^{\mathrm{2}}). The test results show that the fast algorithm proposed in this paper can meet the requirements of high-efficiency processing of large-scale data, which lays the foundation for the application of V-system in more fields.

To address the limitations of current mainstream networks, which rely solely on local neighborhoods for feature aggregation and suffering from insufficient feature extraction capabilities and information loss due to max-pooling, we propose an attention-based point cloud processing network that combines both local and global information. First, we introduce channel attention for local feature aggregation to minimize information loss. Next, we design a dynamic key point learning method to capture the remote dependency information of points and obtain global information. Finally, we develop a spatial attention fusion module to allow each point to learn the global con-textual information. Our proposed method has been benchmarked on several point cloud analysis tasks. It achieved an overall classification accuracy of 94.0% and an average classification accuracy of 91.7% on the ModelNet40 classification task. On the ScanObjectNN classification task, our method reached an overall class fication accuracy of 81.5% and an average classification accuracy of 78.1%. In the ShapeNet segmentation task, we obtained a mean intersection over union of 86.5%. The experimental results show that the proposed network has significantly improved accuracy compared to classical networks such as PointNet, PointNet++, and DGCNN in classification and segmentation tasks, and has also achieved improvement in deferent degree compared to other point cloud processing networks.

A multi-morphology design method based on conformal mapping is proposed to design triply periodic minimal surface (TPMS) microchannels with freeform boundary constraints. This method first maps the boundary of a freeform surface to a plane, allowing for channel topology design in the 2D parametric domain; Then, a Beta growth function algorithm based on loop is proposed to achieve smooth transitions of various TPMS morphological features; Finally, by mapping the designed microchannels to the 3D space constrained by the free surface, the microchannels meet the design requirements. Our results show that the microchannels constructed by this method have good adaptability to complex surface boundaries and can achieve the design goals of internal morphological features.

Overhangs are usually inevitable when fabricating a part of complex shape in 3D printing. Meanwhile, the geometric error on the side surface of an overhang (i.e. the side loss) after fabricating is often significant, which seriously affects the accuracy of the overhang as well as its container (i.e. a part). To solve the above problem, a double-level intelligent improvement approach for overhangs on side loss (i.e. process parameter optimization and geometry pre-compensation) is proposed in this paper. Firstly, a series of experiments with different values concerning the critical design parameter and process parameters are designed based on the Taguchi method. Then, a deliberate measurement method is designed to get the side loss data from the fabricated inverted 'L'-shaped parts. Secondly, two types of side loss prediction networks are respectively constructed for the two sides (that is the overhang side and the non-overhang side) of each inverted 'L'-shaped part. They are mainly designed according to the requirements of support structures on an overhang. Aided with these networks, the geometric error of both sides of an overhang on an inverted 'L'-shaped part (with various values of the critical design parameter) can be predicted accurately. Thirdly, aiming at minimizing the side losses on both sides of an overhang, a single-objective and multiple-variables nonlinear programming problem is formulated. Hereby, the corresponding optimized side losses as well as their counterpart values of key process parameters can be determined. Finally, we compensate the geometries on the two sides of an overhang based on the above-optimized side losses by conducting an inverse modification first and then fabricate the overhang adopting the above-optimized values of key process parameters. Based on fused deposition modeling, experiments were implemented on various inverted 'L'-shaped parts except the ones used in constructing prediction networks, which verified the effectiveness of the proposed approach. Meanwhile, comparative analyses with state-of-the-art works were also carried out. The results show that our method is suitable for overhangs and has great potential to significantly improve their side losses.

Artificial intelligence generated content (AIGC) has received significant attention at present. As the numerous generative models proposed, the emerging diffusion model has attracted extensive attention due to its highly interpretable mathematical properties and the ability to generate high-quality and diverse results. Nowadays, diffusion models have achieved remarkable results in the field of condition-guided image generation. This achievement promotes the development of diffusion models in other conditional tasks and has various applications in areas such as movies, games, paintings, and virtual reality. For instance, the diffusion model can generate high-resolution images in text-guided image generation tasks while ensuring the quality of the generated images. In this paper, we first introduce the definition and background of diffusion models. Then, we present a review of the development history and latest progress of conditional image generation based on diffusion models. Finally, we conclude this survey with discussions on challenges and future research directions of diffusion models.

Based on the existing results at home and abroad, this paper uses principal component analysis to combine two subjective sentiment indicators and four objective sentiment indicators into a comprehensive index that can effectively measure investor sentiment. The constructed composite sentiment index can reflect most of the information of the six original indicators, and is significantly correlated with the stock market return rate. When studying the relationship between investment sentiment fluctuation and stock market return fluctuation, vector autoregression (VAR) model is used to explore the relationship between them. Accounting for asymmetry of stock market information, exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model is used in this paper. The results show that the impact of negative and pessimistic sentiment on stock market returns is greater than that of positive and optimistic sentiment. The impact of falling earnings on investor sentiment is far greater than that of rising earnings.

Due to the increasing complexity of data form, multi-view clustering algorithms emerge one after another. The main disadvantages of existing methods include: the computational complexity of these methods is high; the final clustering involves additional processing steps; the similarity graph constructed may not be the optimal graph. In order to solve the above problems, a clustering algorithm based on sparse consensus graph decomposition is proposed. The algorithm is first tested on single-view data, and then extends from single-view data to multi-view data. The algorithm takes into account different contributions of different views to the final result by giving each view appropriate weight, at the same time, makes use of the L_{\mathrm{2,1}} norm to obtain the consensus graph with better performance, learns the non-negative representation matrix on the basis of the consensus graph, and reveals the cluster result directly after alternation iteration. Finally, an update iterative algorithm is proposed and tested on a large number of data sets to verify the effectiveness of the algorithm.

The UNet network can be used to predict the dense displacement field in the full-resolution spatial domain, and has achieved great success in the field of medical image registration. However, for three-dimensional images with large deformation, there are still shortcomings such as long running time, inability to effectively maintain the topological structure, and easily leading to the loss of spatial features. A large kernel multi-scale deformable medical image registration network based on cross-attention (LK-CAUNet) is proposed. Based on the classical UNet network, the cross-attention module is introduced to achieve efficient and multi-level semantic feature fusion. The large kernel asymmetric parallel convolution is equipped. It has the ability to learn multi-scale features and complex structures. Besides, an additional square and scaling module is added to let it have the advantages of topological conservation and transform reversibility. Using the brain MRI dataset, it is demonstrated that the proposed method has significantly improved the registration performance compared with the eighteen classical registration methods. Especially compared with the most advanced TransMorph registration method, the Dice score can be improved by 8%, and the parameter quantity is only one fifth of it.

Algebraic analysis of fuzzy logic is one of the hot issues in the field of fuzzy logic research. In this paper, Fuzzy implication algebras and its ideals problem are further studied by using the method and principle of algebra and lattice theory. Firstly, some new properties of Fuzzy implication algebras are revealed by using pseudo-complement operators. Secondly, the concepts of ideal and generating ideal are introduced in Fuzzy implication algebras, and their properties and equivalent characterizations are investigated. Finally, the lattice theory characteristics of the set consisting of all ideals in a given Fuzzy implication algebra are discussed, it is proved that the set forms a distributive continuous (algebraic) lattice with respect to the set-inclusion order, in particular, it forms a complete Heyting algebra, and then forms a Frame.

Analyzing regional differences and convergence of high-quality development of tourism is an important topic of research. In this paper, we construct an indicator system to estimate high-quality tourism development, and the dimensions include market quality upgrading, supply capacity improvement, efficiency of enterprise resource allocation, development environment enhancement, industry structure optimization, and development achievements sustainability. It adopts entropy weight-TOPSIS method to measure the high-quality development index of China tourism as well as the tourism of 30 provincial regions from 2010 to 2018, applies Dagum Gini coefficient and decomposition to measure the regional differences and resources, and uses coefficient of variation and spatial panel model to reveal the convergence. The results are as follows: (1) the level of China's tourism hight quality development is increasing gradually, but the efficiency of enterprise resource allocation, market quality upgrading and development achievements sustainability are still the main short boards. There are significant regional differences, showing a stepwise decreasing pattern from east to west; (2) the overall difference of China's tourism hight quality development is narrowing gradually, but no significant change in intra-regional differences. Although inter-regional difference shows a decline, it is still the primary source of overall difference; (3) except the central region, the tourism high-quality development exists σ convergence in China as well as in its eastern and western regions. Both absolute β convergence and conditional β convergence are found in all three regions; (4) the levels of economic basis, industrial structure, degree of marketization, and innovation ability have significant effects on the improvement of tourism high-quality development, but there is obvious regional heterogeneity. The countermeasures to narrow the regional differences in tourism high-quality development are proposed accordingly.

The rotated flux method could be used to effectively eliminate the shock instability of the approximate Riemann solver and suppress the generation of non-physical phenomenon if the equations to be solved meet the rotational invariance. For the 2D ideal magnetohydrodynamics (MHD) and shallow water magnetohydrodynamics (SWMHD) equations, the rotation-like matrix of flux function was constructed, and the corresponding rotational invariance theorem was given with proof, which was then used to deal with the governing equations applying quasi-1D method to derive the semi-discrete rotated flux scheme. Combining entropy stable flux and anti-diffusive flux by a flux limiter, a new flux that can adaptively adjust the dissipation term was obtained. Numerical experiments show that the new scheme can accurately capture the structure of solution, has high resolution, strong robustness and can be easily extended to higher dimensions.

In this paper, we first study the capacitance and energy of the capacitor when the dielectric surface inside the capacitor is charged. The results show that the capacitance and energy formula in this case are in the same form as that depicted in traditional capacitance theory, but the charge of the capacitor needs to be modified according to the charge of the dielectric surface. Then we use the capacitance theory to study the output performance of the contact-separation mode triboelectric nanogenerator (TENG). It is found that the final stable output of the contact-separation mode TENG is different from the output of the initial short time. Through theoretical deduction and numerical calculation, the electric quantity, voltage and current of contact-separation mode TENG are obtained. Finally, we analyze the charge transfer process of TENG in detail based on the theoretical calculation results. That is, when the external resistance can not be ignored, the electrode charge has a certain hysteresis effect relative to the electrode position. Our results not only generalize the capacitance theory, but also improve the working principle of TENG.