Abstract:We in this paper characterize the boundedness and compactness of a class of Toeplitz operator on the Bloch-type space. In addition, we also give a characterization for the functions in terms of fractional derivative.

Abstract:In this paper, we study the existence of positive solutions for a class of fourth-order nonlinear difference equation boundary value problems, and construct the Green’s function for the associated linear problem and then obtain its properties. The proof of the main result is based on the Leray-Schauder fixed point theorem.

Abstract:In this article, based on Kronecker-Weber theorem we explicitly give a conductor formula for the Abelian number fields in terms of the ramification indices. Particularly, the conductor of a quadratic number field can be easily deduced from this formula.

Abstract:Schur proved the irreducible of a class of polynomials over Q, which is re-proved by Coleman by using the method of p-adic Newton polygon. In this paper, also by using the tool of p-adic Newton polygon, and applying the local-global principle, we prove the irreducible of a class of generalized Schur-type polynomials over Q.

Abstract:Prestack reverse time migration is a popular method for imaging underground structures in seismic exploration. Its imaging condition requires to gather data from the source wavefield and receiver wavefield samultaneously, which means that we have to store all source wavefield data at all times of the forward simulation and huge storage demand. The source wavefield reconstruction technologies can be used to solve this problem at the cost of introducing additional computational complexity. In this paper we introduce the POD finite element method and apply it to the reconstruction of viscous source wavefield, here the proper orthogonal decomposition (POD) method is used to reduce the storage demand by decreasing the dimensionality of data while keeping high enough accuracy. Numerical examples show that, compared with the traditional finite element methods, the POD finite element method can save more computer memory and speed up the reconstruction.

Abstract:In this paper, we propose a two-level differece scheme with six-order spatial accuracy for the initial boundary value problem of KdV equation with homogeneous boundary condition. In this scheme, the Crank-Nicolson difference scheme with second-order theoretical accuracy in time layer and the discretization of space layer is performed by extrapolating difference combination with six-order accuracy. This scheme can simulate two conservation properties of the original problem reasonably. Then the convergence and stability of the scheme are proved by using the energy method. Finally, numerical examples verify the performance of the scheme.

Abstract:Existing image super-resolution reconstruction methods take less into account the noise information contained in real low-resolution images, which will affect the quality of image reconstruction. Inspired by the real image denoising algorithm, this paper introduces a noise distribution collection network to collect noise distribution information of low-resolution images, and adopts a model design of Generative Adversarial Network to improve the reconstruction quality of noisy images. The noise distribution information will be input to the super-resolution reconstruction network and the discriminant network respectively. During the reconstruction process, the noise is removed during while ensuring the recovery of useful high-frequency information, because the ability of the discriminant network has an important impact on the performance of the entire model, the U-Net network is selected to obtain better gradient information feedback. Comparison with the classical image super-resolution reconstruction methods and ablation experiments,the resluts show that the proposed model obtains better performance in the noisy low-resolution image reconstruction task after using the noise collection network and the U-Net discriminant network.

Abstract:Accurately identifying the key nodes in the network is one of the important research topics in complex networks. Most of the existing key node identification methods are based on the centrality measurement method by the network structure, which has low identification accuracy and limited scope of application. A key node identification method, based on Graph Convolutional Network (GCN), is proposed in this paper, which considers not only the node attributes, but also the network structure and neighbor node structure. Multidimensional features are extracted first from the network legend data to construct feature vectors and then the node feature vector is input to the GCN layer for learning. Finally, the minimum loss is calculated with the regression loss function, and the key nodes are identified. In this paper, SIR (Susceptible Infected Removed) is choosed as the evaluation method in the propagation dynamics simulation experiment and Pinning Control experiment, the proposed method is verified on different types of real networks, the results show that the GCNbased method proposed in this paper outperforms other methods in terms of scope of application and accuracy.

Abstract:Blind face restoration is the process of restoring a high-quality image from a low-quality image (e.g., blurred, noisy, or compressed image). Since the degradation type and degradation parameters of the low-quality image are unknown, blind face restoration is a highly ill-posed problem that heavily relies on various facial prior such as facial components and facial landmarks during the restoration process. However, these facial priors are typically extracted or estimated from low-quality images, which may be inaccurate, directly affecting the final restoration performance. The current mainstream methods mostly use ConNets for feature extraction and do not consider long-distance features, resulting in a lack of continuous consistency in the final results.The authors propose an improved StyleGAN model named SwinStyleGAN, which uses Swin Transformer to extract long-distance features and gradually generates images through an improved StyleGAN synthesis network.Addtionally, the authors design a Spatial Attention Transformation (SAT) module to reassign pixel weights of each stage feature to further constrain the generator. Experiments show that the proposed SwinStyleGAN in this paper has better blind face restoration performance.

Abstract:Public opinion prediction is one of the key solutions to improve the ability to guide public opinion in emergencies. However, most of the existing public opinion prediction work focuses on the trend indicator or sentiment polarity of events ,while little attention paid to the prediction of hot words and topics in specific events. In this paper, a temporal evolving graph convolutional network for public opinion prediction in emergencies is proposed, in which the hot words associated with specific events are taken as the object of public opinion prediction. Our approach combines evolving graph convolutional network with gated recurrent unit: the former is used to learn the dynamic spatial correlation between words and the latter is used to capture the temporal changes of words, the hot words of an emergency in the next time period is then predicted through full connection layer output. To validate the proposed method, we selected discussion texts related to two emergencies on Weibo as the dataset, and conducted comparative experiments with two existing hot word prediction methods. The results show that our method achieved higher precision, recall, and F1-score in both emergencies, with precision of 51.21% and 50.98%, recall of 50.17% and 48.15%, and F1-scores of 50.68% and 49.52%, respectively. These results demonstrate that our proposed method is effective inpredicting public opinion during emergencies

Abstract:Significant progress has been made in the research of log anomaly detection. However, two challenges still exist in reality. Firstly, log data is often stored on different servers, creating "data islands", the number of abnormal samples in the log data of a single company or organization is insufficient and the abnormal patterns are relatively limited, it is a challenge to train a detection model with high accuracy through these data. Integrating log data from different sources can improve the model''s performance but may result in log data leakage during transmission; Secondly,the log data of different application system types varies in log structure and syntax, and simple integration for training models is ineffective. To address these issues, this paper proposes a log anomaly detection training framework called LogFTL based on federated transfer learning, which uses federated learning algorithm based on matching average. On the premise of ensuring the privacy and security of the client''s data, LogFTL aggregates the model parameters of the client on the server side to form a global model which is then distributed to the client side. Using the client''s local data, the LogFTL framework migrates and learns to optimize the client’s local model and the detection effect of local log data is improved.The experiment resluts show that the LogFTL framework proposed in this paper outperforms traditional log anomaly detection methods in federated learning scenarios, and demonstrate the transfer learning effectiveness of LogFTL.

Abstract:Network covert timing channel is a highly concealed method of information leakage. As the main communication method of APT attack, it poses a great threat to network security. The current detection methods for covert channel are insufficient generality, have high false detection rate, and manual extraction of features is time-consuming. This paper proposes a detection method based on grayscale image transformation. This method normalizes the inter-arrival time sequence of packets, and converts them into pixel values, and then converts into a grayscale image, thereby transforming a problem of one-dimensional sequence classification into a problem of two-dimensional image classification. The authors use the Convolutional Neural Networks to automatically acquire image features, and use the Convolutional Block Attention Module to optimize the feature adaptively from two dimensions of space and channel. The authors train the network with the data set composed of legitimate traffic and covert channel traffic, and the obtained binary classifier can be used to judge whether the detected traffic is covert timing channel traffic. Finally, the proposed approach is compared with the four existing detection methods. The experimental results show that the proposed method has higher precision and recall rate, and the proposed model has better generality and lower false detection rate.

Abstract:Grey-box fuzzing technology has been proved to be an efficient and practical vulnerability mining technology. It is widely used in the field of vulnerability mining, and many high-risk vulnerabilities are found through grey-box fuzzing. American Fuzzy Lop(AFL) is a classic representative of grey-box fuzzing and many subsequent grey-box fuzzing are improved on the basis of AFL according to different conditions but AFL still faces certain issues.AFL uses random numbers to represent instrumentation points when performing instrumentation on target program, the random numbers of the two instrumentation points are used to perform the XOR operation in the testing process, and the result is used to represent an edge.This method can lead to HASH collision problems when performing edge statistics, which decreases the probability of discovering new edges and affects AFL''s vulnerability mining efficiency, especially for larger code sizes..In this paper, by improving the way of assembly-level instrumentation, the basic block-sensitive instrumentation is changed to branchsensitive instrumentation, so that the control flow graph of the program is changed into a binary tree form, and non-random numbers are used to mark each instrumentation point, which is relatively well solved the problem of HASH collision. Experiments show that the propsosed method is effective, and since the improvement is transparent to the upper layer, it can be applied to various AFL-based grey-box fuzzing tools, thereby improving the efficiency of the fuzzing test.

Abstract:As the core component of aero-engine, the blade plays a key role in its safety and reliability. The dimension and shape accuracy of the blade profile have always been strictly required in the process of blade machining and measuring. Thus, in this paper we propose a method for reconstructing the three-dimensional profile based on line-laser scanning. First, based on the developed four-axis blade measurement device, the rapid scanning and data acquisition of the blade profile are realized by combining the linear encoder and the line laser sensor. Then, a registration method based on the geometric features of the blade datum plane is further proposed to align the multi-view scanning data of blade profile, and the high precision reconstruction of the blade profile are achieved accordingly. Finally, a typical blade is taken as the experimental object for profile reconstruction experiment, and the profile reconstruction data is compared with the CMM measurement results from the same blade. The results show that the average deviation of cross-sections in blade profile is less than 0.040 mm and the standard deviation is less than 0.028mm. This demonstrates the accuracy and feasibility of the proposed method.

Abstract:In this work, the electrochemical dissolution behavior of electron beam melting (EBM)-formed TC4 samples and conventionally forged TC4 in 3.5 wt% NaCl solution was investigated using an electrochemical workstation. The results show that the non-equilibrium microstructure of the EBM formed TC4 samples makes them exhibit different corrosion resistance compared to the conventionally forged TC4. the corrosion resistance of the EBM formed TC4 samples differs in different planes compared to the forged TC4, with the EBM horizontal plane being larger than the forged one, but the EBM vertical plane being smaller than the forged one. the anisotropy of the corrosion properties appearing in the vertical plane of the EBM formed TC4 samples is mainly caused by the β-columnar grain. In the process of corrosion, pitting preferentially occurs at α grain boundaries because of the higher grain boundary energy and the formation of porous passivation layers. This work is helpful to enrich the study of corrosion energy of TC4 alloy prepared by additive manufacturing in the field of aerospace titanium alloys.

Abstract:Molecular dynamics simulations based on the self-consistent charge density-functional tight-binding (SCC-DFTB) method is used to study the oxidation mechanism of three models (defect-free, atomic-defect and pore-defect) of carbon-based ablative materials under high temperature. It is found that the reaction products at high temperature are mainly CO and CO2. The production process of CO mainly comes from decomposition of C-C bond in epoxy group. The formation of CO2 is relatively complex, mainly from fragmentation of small molecular clusters (C2O2, C3O1, C4O1). It is found that C-C bond is the main way of graphite oxidation reaction, and C-O bond is the controlling factor of CO and CO2 generation rate. In addition, the temperature, defects and holes of the system have important effects on the oxidation mechanism of graphite. By analyzing the oxidation reaction rate, the calculated activation energies of the three model oxidation reactions are 7.56, 2.4 and 1.6 kcal/mol, respectively. The model with atomic defects and holes corresponds to a low activation energy and a high oxidation reaction rate, while the case without defects associates with the lowest oxidation reaction rate due to the highest activation energy.

Abstract:Curzerene is a natural product of terpene furans isolated from the curcuma rhizomes, which has various biological activities such as anti-inflammation, anti-cancer and anti-leishmaniasis. In this paper, commercially available (+)-verbenone (6) was utilized as chiral starting material to synthesize Curzerene in 5 steps with 34% total yield. A key ketone compound 4 was first obtained through a known three-step reaction. Then ketone 4 and 1,1-dimethoxyacetone underwent TiCl4-Et3N-mediated cyclization reaction to afford natural products isogermafurenolid (2) and its isomer 8-epi-isogermafurenolid (2′) in 56% and 20% yield, respectively. Finally, the target Curzerene was synthesized from 2 and 2′ with 82% yield by a one-pot reaction of DIBAL-H reduction and subsequent acid promoted dehydration.

Abstract:Cuboid anatase TiO2 nanocrystals with co-exposed [111]-/{101} facets were synthesized by one-pot method under mild hydrothermal conditions (120~180 ?C) using layered titanate H1.07Ti1.73O4 as precursor and different amounts of HF as morphology-controlling agent. The crystal structure, morphology, microstructure, surface area, electronic states, optical properties and charge migration behavior of xHF-T180 (x = 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 mL) anatase TiO2 nanocrystals were characterized, and their photocatalytic degradation of MB was evaluated. The results show that, compared with CM-TiO2 and other xHF-T180 anatase TiO2 nanocrystals, 2.5HF-T180 shows the highest k value (0.0165 min-1), which is 18.33, 1.99, 1.31, 1.46, 1.16, 1.27 and 1.34 times that of Blank (0.0009 min-1), CM-TiO2 (0.0083 min-1), 0.5HF-T180 (0.0126 min-1), 1.0HF-T180 (0.0113 min-1), 1.5HF-T180 (0.0142 min-1), 2.0HF-T180 (0.0130 min-1), and 3.0HF-T180 (0.0123 min-1), respectively. The highest photocatalytic activity of 2.5HF-T180 can be attributed to the synergistic effect of its smallest particle size, largest specific surface area, weakest fluorescent intensity and smallest electrical resistance. This study provides a new idea for the synthesis of anatase-type TiO2 nanocrystals with high photocatalytic performance for the treatment of organic dye wastewater.

Abstract:In order to explore the post-translational modification of Arabidopsis abscisic acid (ABA) receptor, this study constructed overexpressing CARK5 and kinase-dead CARK5m (CARK5N250A) in the wild type and T-DNA mutant cark5 plants by genetic and physiological assays, to analyze the functions of CARK5 in ABA signaling. The results showed that CARK5 can promote ABA-mediated inhibition of seed germination, seedling cotyledon and primary root elongation, but the overexpression kinase-inactive CARK5m (CARK5N250A) has a similar phenotype to the mutant cark5. In addition, overexpressing CARK5 enhanced plant drought resistance and ABA-marked gene RAB18 expression. Taken together, these data suggest that CARK5 positively regulates the ABA signaling pathway by phosphorylation of ABA receptors.

Abstract:To explore the impact of pyrite slag heap on surrounding farmland, 61 soil samples were systematically collected from a pyrite slag heap and surrounding agricultural land in Southern Sichuan Province, and the contents of heavy metals (Cr, Ni, Cu, Zn, Cd, Pb, As, Hg) were determined, and the pollution levels and characteristics of the spatial distribution of eight heavy metals were analyzed. The sources of heavy metals were identified by correlation and principal component analysis, and the risk level of soil pollution was evaluated by a comprehensive ecological risk index and geoaccumulation index. In the soil, the results showed that the contents of Cr, Cu and Cd of the study area exceeded the corresponding national standards, and the contents of Cr, Cd, Pb, and As were significantly higher than the background values, which were 1.56, 1.40, 1.45 and 2.89 times of the background values, respectively. The spatial distribution of Ni, Cu and Zn content was relatively uniform, while the spatial distribution of the other five heavy metals was relatively concentrated. The farmland soil around the mining area was at a medium ecological risk level (150

Abstract:In order to improve the understanding of the energy and nutrient limitation of soil microorganisms in the alpine region of western Sichuan, the soils at different altitudes (2969 m, 3280 m, 3697 m and 3992 m) in the alpine region of western Sichuan were used as the research object. By measuring soil physicochemical properties and extracellular enzyme activities, the distribution law of soil enzyme activity and enzyme stoichiometry along the altitude and its influencing factors were discussed. The results showed that: (1) The activities of β-1,4-glucosidase (BG), Cellobiohydrolase (CBH), β-1,4-N-acetylglucosaminidase (NAG), Leucine aminopeptidase (LAP) and Acid phosphatases (AP) showed a distribution pattern of first decreasing and then increasing with the increase of altitude. Specifically, the activities of carbon and phosphorus acquisition enzymes were the highest at 3992 m, and the lowest at 3280 m. The highest nitrogenacquisition enzyme activity was at 2969 m, and the lowest was at 3697 m. (2) Soil microorganisms at 3280 m were relatively limited by N and P, while those at the other three altitudes were relatively limited by C and P. (3) Soil ammonium nitrogen (NH+4-N), total nitrogen (TN), soil total carbon (TC), and soil nutrient stoichiometry were the key factors driving the changes in soil enzyme activities and their stoichiometry along the altitude. According to the results, the characteristics of soil enzyme activities in this study area were related to the availability of environmental resources.

Abstract:In order to avoid the leakage expression of the Tet-on inducible expression system and to achieve easy, stable and efficient expression of exogenous gene when induced at a specific time, this study planned to add the destabilizing domain FK506-binding protein, regulated by the stable ligand Shield-1, to the N-terminal of the target gene to control its background expression at the protein level. To verify the performance of this system, the fluorescent protein TdTomato was used as the reporter gene in this study. The results of flow analysis showed that the leakage expression in the optimized system was reduced about 7 times compared with the original one at the protein level. This system was applied to the in vitro odontogenic induction system based on mouse embryonic stem cells. Under the synergistic effect of the inducible factor Dox and the stable ligand Shield-1, the induced overexpression of tooth development-related transcription factor Hand2 could improve the completion of odontogenic induction.