Abstract:In this paper, we investigate the global dynamics of a planar Filippov system with a regular-SN for general parameters not required to be sufficiently small. By analyzing the qualitative properties of the pseudo-equilibria, tangent points, equilibria at infinity as well as all kinds of periodic orbits, we obtain the global bifurcation diagram with eight bifurcation curves and give all global phase portraits in Poincare disc. Some new bifurcation phenomena which do not appear in the case of small parameters are finded.

Abstract:Suppose that the characteristic equation of the linear difference equation has a unique solution. We in this paper obtain the general solutions of the equation by using the method of variation of parameters. Under some conditions on the characteristic root, we further get the best Ulam constant of the equation by constructing a specific bounded approximate solution of the equation.

Abstract:The Cauchy problem of the Keller-Segel system with logistic source is considered. Under some conditions, we show that there exist initial data such that the smooth local-in-time solution of the system blows up in finite time, and thus the superlinear growth restrictions is insufficient to rule out the chemotactic collapse os the solution.

Abstract:In this paper, we propose an energy stable numerical scheme for the phase field crystal equation with periodic boundary condition. This scheme is based on the structure of the energy functional. A Fourier pesudo spectral approximation is applied in space as well as a third order backward differentiation scheme is applied in the temporal approximation for the equation. Meanwhile, a Douglas-Dupont type regularization term is added to ensure the modified energy stability. The unique solvability and energy stability of the scheme are established. Finally, some numerical examples are presented to confirm the robustness and accuracy of the scheme.

Abstract:In this paper, we mainly study the global existence and blowup conditions for the solutions of an inhomogeneous Choquard equation when the initial data is above the ground state"s mass-energy. Firstly, an auxiliary function is constructed by the Gagliardo-Nirenberg inequality and Virial identity, while an equivalent characterization of the initial data above the ground state"s mass-energy is obtained by using the convexity of the function. Then we get the conditions of the global existence and blowup for the Choquard equation. Finally, according to the Cauchy-Schwartz inequality and the uncertainty principle, a new sufficient condition for the existence of blow-up solutions is obtained by using the mechanical analysis of a particle moving in potential barrier field.

Abstract:The throughput can be improved by sharding in the blockchain network based on Hyperledger Fabric architecture, before sharding, it is required to pre-evaluate the failure probability of each committee, so as to obtain a more stable sharding scheme. This paper proposes a joint distribution (JD) algorithm. Firstly, for the nodes in the pre sharding scheme, random sampling is performed according to the number of committees in the pre-sharding scheme, the hypergeometric distribution of nodes in each committee is then obtained. Secondly, the probability of malicious nodes in each committee is calculated according to the hypergeometric distribution of nodes, and the joint distribution function of all committees is constructed according to these probabilities. Finally, according to the joint distribution function of all committees, the failure probability and failure years of the whole sharding scheme are calculated to realize the stability evaluation of blockchain sharding. The simulation results show that the accuracy of calculating the failure probability is verified by calculating Wilson confidence interval, which is compared with RapidChain's sharding stability analysis algorithm and Hoeffding boundary algorithm, Joint distribution (JD) algorithm can better estimate the stability of blockchain sharding.

Abstract:Software testing is one of the most time-consuming stages in the software development process. Potential errors in software can be found efficiently and in a timely manner by automatically executing a large number of test cases, which is an important technology development trend to improve the quality of large and medium-sized software development. Currently more meta-heuristic optimization algorithms have been able to automatically generate test cases, but the test efficiency is low and the overhead is large, so how to make the generated test cases cover as many goals as possible with a small number of test cases is the core technical issues in the generation of automated test cases. This paper proposes a loss function-based automatic generation algorithm for unit test cases (LFGA). During the execution of the genetic algorithm, the subsequent population distribution is changed dynamically to ensure the balance of the overall data distribution according to the path coverage of the test case population. The branch information is introduced to optimize the adaptive cross-mutation operator to automatically generate an effective test case set with as small scale and high coverage as possible. The experimental results show that, compared with the existing automatic test case generation method, the method proposed in this paper can better solve the defects of the traditional model such as initial value dependence, premature convergence, and lagging local optimization ability, and the average coverage rate of generated test cases reaches 95%, which improves search efficiency and data utilization efficiency.

Abstract:Although play an important role in the process of the robot grasping, haptics is only used to extend the state space, and the information provided by it such as position and pressure is rarely fully utilized in most reinforcement tasks. In order to solve the issues, inspired by the intrinsic reward mechanism, an intrinsic incentive method based on the “inverted T” array sensor is proposed. According to the position where the end effector of the robot touches the object, the method gives degrees of importance, and encourages the agent to achieve the goal with a more effective posture. Finally, the method was tested in the simulation environment, and the results showed that the speed of convergence of the method in the task gripping ellipsoid objects was about 20% faster than the latest benchmark method.

Abstract:Protocol clustering is a very important step in protocol reverse engineering technology. Aiming at the characteristics of binary protocols that are more transparent and satisfying a wider range of protocols, a binary protocol clustering method based on genetic and protein biological information is proposed, which can learn from the original sequence Angle to cluster protocols directly. The method firstly converts the original binary message into a quaternary gene form, uses the fast clustering method to calculate the k-seed value of the base pairwise combination to generate a distance matrix, and uses UPGMA to calculate the minimum distance spanning tree to obtain the initial cluster; A cluster of quaternary protocol messages is converted into a hexadecimal protein chain, and the sequence is obtained in a more semantic way. The clustering method based on the improved mBed algorithm is used to cluster them with high precision. Tests under pure and mixed scenarios of known and unknown protocols show that this method can achieve efficient and highaccuracy clustering of binary protocols, and has high application value.

Abstract:Aiming at the problem of human-robot interaction and anti-collision of the medical nursing manipulator in the process of trajectory tracking, a control method of the manipulator is proposed based on target region tracking and collision prediction. In this paper, according to Lyapunov function and combined with the artificial potential field, the controller to ensure the system stability is designed to achieve human-robot interaction in the target area of compliance. The collision avoidance prediction model is constructed by the distance of collision and the time of collision, and the correlation model between the radius of obstacle and the safety index of collision avoidance is established to realize the real-time change of the radius of obstacle. Experimental results show the experimental results show that the proposed method can perform target area tracking effectively and makes the human-computer interaction compliance, the obstacle avoidance process is efficient and smooth.

Abstract:In order to reduce heating waiting time of the heat-sealing knife, and concentrate energy generated by the heating tube on the contact surface of heat-sealing film, the structure of heat-sealing knife in the packaging machine is improved. First, establish the temperature field model of heat-sealing knife and verify the accuracy of model. Then, use the goal-driven optimization tool in Ansys Workbench to optimize the specific size of heat-sealing knife. Next, use the Genesis module in Ansys Workbench to perform topological analysis and optimize the structure of heat-sealing knife. On the basis of the optimization of the two, the simulation experiment was carried out by trial and error method, and the size of the heat-sealing knife was gradually adjusted. Finally, under the condition that the quality of the sealing film is guaranteed and the installation size of the heat sealing knife remains unchanged, most of the energy generated by the heating tube is concentrated on the sealing film contact surface, and the maximum temperature of the sealing film contact surface is increased from 160.25℃ to 330.11℃.According to the result, with the help of Ansys Workbench simulation software, the structure of heat-sealing knife is improved, which can achieve the purpose of reducing heating waiting time of the heat-sealing knife, and concentrate energy generated by the heating tube on the contact surface of heat-sealing film at the same time.

Abstract:Aiming at the problem that low-quality face images hinder the performance improvement of recognition systems, we propose a no reference face image quality evaluation method to evaluate the impact of different types of image degradation on the quality of face images. This method uses a cluster convolutional network structure to simulate the feature offset in the face degradation process, and face image score is calculated based on the correlation between the feature offset and the amount of image information. The genetic algorithm is used to select the network units, so that the same performance can be achieved with a smaller network scale. Using the evaluation algorithm as a tool for experiments, the impact of different image degradation types on face recognition is evaluated and studied, some useful conclusions are drawn for guiding future research on face quality. Experiments conducted on mainstream face data sets show that by filtering low-quality face images in the database, the performance of the existing face recognition system can be further improved, and the improvement of the recognition rate shows good stability. This method is low in complexity and does not require training. Compared with the latest methods such as FaceQNet, it shows obvious advantages in FNMR and EER indicators.

Abstract:As a new kind of green ionic liquid, deep eutectic solvents have many advantages such as low saturated vapor pressure, low melting point, low price, non-toxicity and degradability, and are widely used in scientific research and engineering applications. Their physical and chemical properties, such as density, viscosity and lattice structure, are the basis for developing solvents with specific functions and their applications. In this work, the density and viscosity of choline-based deep eutectic solvents at 293.15~353.15 K were calculated by molecular dynamics simulation within the framework of GAFF force field, and their average absolute deviations with experimental values in literature were 0.30% and 6.19%, respectively. At the molecular level, the radial distribution function is used to describe the structure distributions in different systems and the formation of hydrogen bonds network. It was found that the extensive hydrogen bonds network of the deep eutectic solvent system was mainly formed by the interaction of Cl atoms and H atoms on hydroxyl, and the interaction decreases with the increase of temperature, and increases with the increase of the length of the hydrogen bond donor alkyl chain. The present study will help us to further study the interaction mechanism between the composition, structure and physical properties of deep eutectic solvents.

Abstract:Aiming at the problem that large-scale field test of aerosol will cost a lot of manpower and material resources, and the harmful effects of aerosol itself are uncontrollable, in order to improve the efficiency of the test and ensure the safety and reliability of the test, in this paper CFD software is used to control the formation of aerosols and the safety and reliability of the test. The diffusion process is studied by computer simulation. Firstly, we conduct numerical simulation research on the formation process of aerosol mixture, builds physical and mathematical models to simulate the formation process of liquid aerosol, and simulate the interaction among multiple aerosol sources by adding the number of aerosol injectors. The aerosol is then continuously injected into the room-sized model, and the concentration of the dispersed aerosol is allowed to decay naturally for a period of time. The results show that when the liquid aerosol enters the environment, it diffuses in the environment and accumulates in the middle and lower parts; when the ambient pressure increases, the diffusion rate will decrease. The analysis and simulation results show that the liquid aerosol model can be used as an effective tool to reasonably analyze the effect of liquid aerosol diffusion.

Abstract:The surface weathering environment of phlogopite vermiculization was simulated under atmospheric pressure, the transformation process from phlogopite crystal layer to vermiculite crystal layer was discussed, and the effects of mixed solutions under different sodium chloride concentrations on the transformation process from phlogopite to vermiculite were studied. XRD, XRF, ICP and SEM were used to study the changes of phase, structure, chemical composition and micro morphology during the transformation. TG-DSC was used to study the changes of thermal properties of the samples before and after the transformation, and the cation exchange capacity (CEC) of the samples was measured. The results show that the transformation from phlogopite crystal layer to vermiculite crystal layer occurs after being treated with simulated environmental solution. The transformation process shows that the content of K+ in phlogopite structure is significantly reduced, sodium hydrate ion is introduced into the structure, the number of layer charges is reduced and CEC is increased. The research results have certain significance for the development and utilization of phlogopite minerals with low utilization rate in Yuli vermiculite deposit, Xinjiang.

Abstract:The effect of internuclear distance of H2+ on the single-order harmonic enhancement driven by the specific laser waveform has been studied theoretically. The results show that when the atom is driven by the specific laser waveform, the single-order harmonic enhancement can be found on the harmonic spectrum. However, when H2+ is driven by the same waveform, the single-order harmonic enhancement is related to the internuclear distance of H2+. Particularly, when H2+ is at its equilibrium position, the single-order harmonic enhancement can be found on the harmonic spectrum. When the internuclear distance of H2+ changes from 3 a.u. to 7 a.u., the single-order harmonic enhancement disappears. When the internuclear distance of H2+ is greater than 8 a.u., the single-order harmonic enhancement will reappear. Theoretical analyses show that the multichannel harmonic interference is responsible for the change of the single-order harmonic intensity.

Abstract:Fifteen known ferrocenylpyrano-fused quinolines were synthesized efficiently via three-component Povarov reaction of 4-methyl-7-aminobenzopyranone, aromatic aldehydes, and ferrocenyl acetylene in the presence of cerium trifluoromethylsulfonate (Ce(OTf)3) and scandium trifluoromethylsulfonate (Sc(OTf)3), with yields ranging from 40.0% to 66.8%. The structures of the compounds were characterized by 1H NMR, 13C NMR, and HR-MS (ESI). The antioxidant activities of the compounds were evaluated by inhibiting oxidation reaction of DNA induced by hydroxyl radical (HO·) and reductive glutathione radical (GS·), and the effects of the type, position and number of substituents on the antioxidant abilities of ferrocenylpyrano-fused quinolines were investigated. The results showed that the fifteen target compounds exhibited strong radical scavenging activities to protect DNA against oxidation induced by HO· and GS·. The absorbance percentages of thiobarbituric acid reactive substances (TBARS) of the fifteen target compounds were 36.6%~83.3% in inhibiting HO· induced oxidation of DNA, and 22.9%~67.2% in inhibiting GS· induced oxidation of DNA, respectively. The antioxidant activity could be further enhanced by introduction of electron-donating groups (such as -N(CH3)2, -OCH3, and -OH) in ferrocenylpyrano-fused quinolines structures, while antioxidant activity was reduced when electron-withdrawing group (-Cl) was introduced. The ferrocenylpyrano-fused quinolines exhibited better antioxidant performance than ferrocenyl quinolines and are potential powerful antioxidants.

Abstract:In this paper, the detailed structure of chromium coating prepared by multi-arc ion plating is shown by multi-scale characterization from about tens of microns to several angstroms. Characterized by XRD, SEM, FIB, TEM and HRTEM, the coatings show a multiple configuration including the micron-sized particles on the surface, the micron or submicron-sized droplets pinned by defect bands around, the columnar grains with stacked faults as boundaries, the ambiguous crystallites differentiated with edge and screw dislocations, the atomic distortions on the ends of these dislocations, and some disordered regions. These structures are found to affect the crystal constant, surface coarsening, and FIB-sputtered cracks by changing the coating crystallinity. In addition, the types of stacking faults and dislocations are confirmed by analyzing the HRTEM images. And finally, the effects of depositing parameters on the granular structure are also discussed.

Abstract:In order to study the taxonomy and evolution of the R2R3-MYB transcription factor family members and their possible functions under gravistimulation, this study used genome-wide identification strategy and other bioinformatics methods to analyze the related family members of Salix suchowensis in detail. The results showed that a total of 158 R2R3-MYB proteins were identified in Salix suchowensis. These members were further divided into 23 subgroups. The analysis of gene structure and motif composition showed that genes in the same subgroup usually had similar exon/intron structure and similar motif composition, which further supported the results of phylogenetic analysis. Syntenic analysis was performed to explore the evolution of the SsMYB family. 85 pairs of SsMYB genes were predicted to arise from tandem or segment duplication events, which played an important role in the expansion of the SsMYB family. In addition, RNA-seq data was used to analyze the expression pattern of SsMYB genes under gravistimulation, and 20 potential SsMYB genes were screened out which involved in negative gravitropism of the stem.

Abstract:Chlorophyll non-saponifiable matter is a by-product with a large yield in the process of producing chlorophyll from Faeces Bombycis. To further enhance the comprehensive utilization value of Faeces Bombycis, this research focuses on the chemical constituents in chlorophyll non-saponifiable matter of Faeces Bombycis. Silica gelcolumn chromatography, C18 medium pressure column chromatography, high pressure preparative column chromatography was used for separation and purification. The structures of the compounds were identified by spectroscopic data and physicochemical properties. A total of 11 compounds were isolated and identified, which were phytol(1),5-glutinen-3-ol(2), lupeol(3), stigmasterol(4), campesterol(5), β-sitosterol(6), α-tocopherol(7), γ-tocoferol(8), (2E,6E,10E,14E,18E,22E)-3, 7, 11, 15, 19, 23-hexamethyl-2, 6, 10, 14, 18, 22-tetracosahexaen-1-ol(9), 13, 14, 17, 20R)-lanosta-7, 24-diene-3-ol(10), palmitic acid(11). According to the results, the main components of the non-saponifiable matter are rich in sterols, and compounds 2, 9 and 10 were isolated from Faeces Bombycis for the first time.

Abstract:To investigate the metabolites in host root exudates that are important for the germination of Plasmodiophora brassicae resting spores, in this study, we first tested the induction ability of resting spores’ germination by root exudates from different clubroot resistant levels materials of Brassica napus, it was found that the germination rate induced by the root exudates of the susceptible materials was significantly higher than that of the resistant materials. Then, we analyzed the root exudates of two resistant and one susceptible material by non-targeted liquid chromatography-mass spectrometry metabolite profiling, non-redundant mass ions (1079 in ESI- mode and 1257 in ESI+ mode) were identified, of which 662 and 722 differential metabolites were screened in ESI- and ESI+ respectively. Some of the compounds with large differences were selected to be further verified. The results showed that Thymine, 2′-Deoxyuridine, L-isoleucine, Trigonelline, Pyridoxal 5′-phosphate, Coumarin, D-lyxose, and Amentoflavone had a significant promoting effect on the germination of resting spores and subsequently caused the development of clubroot.

Abstract:To explore the differential expression profile and potential function of piRNAs in Apis mellifera ligustica workers under Nosema ceranae stress, the differentially expressed piRNA (DEpiRNAs) in the host response to stress were screened out by using previously abtained transcriptome data from A. m. ligustica workers’ midguts at 7 days post inoculation (dpi) and 10 dpi (AmT1 and AmT2 groups) as well as corresponding un-inoculated workers’ midguts (AmCK1 and AmCK2 groups), followed by prediction and investigation of target mRNAs of DEpiRNAs with relevant software, and randomly selected DEpiRNAs were further validated by Stem-loop RT-PCR and qPCR. The results showed that 50 and 207 DEpiRNAs were screened out from AmCK1 vs AmT1 and AmCK2 vs AmT2 comparison groups, respectively; there are 10 common DEpiRNAs shared by the aforementioned two comparison groups, and the numbers of unique DEpiRNAs were 40 and 197, respectively; the consensus DEpiRNA piR-ame-1128833 can target 3021 mRNAs; Stem-loop RT-PCR result confirmed the true expression of four DEpiRNAs; RT-qPCR result verified that the expression trend of four DEpiRNAs was in accordance with that in the sequencing data. These results reveal that the expression pattern of piRNAs in the midguts of A. m. ligustica workers was altered due to N. ceranae stress. DEpiRNA potentially regulated host response to N. ceranae stress through targeting associated mRNAs.

Abstract:Objectively, housing prices are restricted by many factors and because of this, house price prediction remains a very classical and challenging problem in data analysis. In response to the redundancy of house price data, which makes it difficult to identify important features in practical scenarios, this paper proposes an innovative approach to data pre-processing and data prediction by means of double model iterative fitting. The initial data is pre-processed in terms of data meaning, data form and data relevance, then suitable models are selected for training. In traditional machine learning, Random Forest (RF) and XGBoost (XGB) are two commonly used methods. The RF model is able to accurately judge "redundant" features through its Bagging process. The XGB model, while improving prediction, is also limited by its reduced generalisation ability and cannot stably reflect the importance of features. Therefore, this paper uses the RF model to process redundant data and uses the XGB model to fit new data sets to improve the prediction results. In this paper, experiments were conducted on the Kaggle competition dataset ("House PricesAdvanced Regression Techniques") and the test results showed that the final regression accuracy R2 of the XGB regression model was 87%, while the R2 of the single RF model and the single XGB model were 79.2% and 78.7%, respectively. The experiment proves that the data prediction method can significantly improve the effect of housing price prediction. To fully reflect the model fitting effect and prediction ability, the authors change the "house price" to discrete variable which has two categories of "high" and "low", and get the Confusion Matrix with an precision of 93% and a recall of 93%.

Abstract:Trade-in is a popular marketing method in the current age, making enterprises face new challenges in market competition. This study sets up a two-period duopoly model with differentiated manufacturers considering trade-in offers. The manufacturers determine their trade-in prices and maximize their profits. The equilibrium and corresponding results are then analyzed. The results show that: (1) When the products are significantly differentiated and the depreciation coefficient is moderate, the model has a unique equilibrium and market segmentation. (2) The high-quality manufacturer benefits from his own product quality standards, and his competitiveness of not participating in the trade-in market is stronger when the depreciation coefficient is large. (3) Consumers will pay more attention to the manufacturers’ product quality market positioning, because it’s important for consumers to decide whether to participate in trade-in during the second period. Therefore, enterprises should consider external factors in advance before trade-in strategies.