Abstract:We prove that when q is not equal to 5,9,13,17,25, and 29, there always exist solutions for the diagonal quartic equation ax^4+by^4=c over F_q.

Abstract:The multiscale asymptotic analysis and computational method for the Steklov elastic eigenvalue problems are developed in a periodically perforated domain. The first-order cell functions, the effective elastic coefficients, the homogenized elastic eigenvalue problems and the second-order cell functions are derived successively by performing the second-order two-scale(SOTS) asymptotic expansions for the eigenfunctions. The feature of the multiscale asymptotic model is that the derived homogenized eigenvalues appear in the homogenized equation instead of on the boundaries of cavities. The SOTS asymptotic expansions of the eigenvalues are also carried out, and the first- and second-order correctors for the eigenvalues are obtained by the idea of corrector equation and the error estimations of the multiscale eigenvalues are proved. Finally, a finite element algorithm is proposed based on the multiscale asymptotic expansion model. The numerical results show the effectiveness of the SOTS analysis method for predicting the Steklov elastic eigenvalues and eigenfunctions and the necessity of the second-order correctors is also demonstrated.

Abstract:Let k and n be positive integers. The Stirling numbers of the second kind is defined as the number of ways to partition a set of n elements into exactly k non-empty subsets, denoted by S(n,k). Given a prime p and a positive integer n, there exist unique integers a and m, with m≥0 and (a,p)=1, such that n=ap^m. The number m is called p-adic valuation of n, denoted by v_p(n)=m. The study of p-adic valuations of Stirling numbers of the second kind is important in number theory and algebraic topology, and full with challenging problems. In this paper, we study the p-adic valuations of the Stirling numbers of the second kind with the special form S(p^n,p2^t) when t and n are positive integers. Let p be an odd prime. We show that if n≥2 and t≥1, then v_p(S(p^n,p2^t))≥n+2-2^t. This extends the results obtained by Zhao and Qiu recently.

Abstract:We investigate the existence of multiple positive solutions for a class of first-order periodic boundary value problems. The proof of the main results is based on the theories of upper and lower solutions and Leray-Schauder degree.

Abstract:In this paper, by using Leray-Schauder’s nonlinear alternative and Leray-Schauder degree theory, we prove the existence of a two-point boundary value problem of the conformable fractional differential equation and give an example for the applicability of the main results.

Abstract:In recent years, face recognition technology as a powerful means to capture biological facial feature information and match face data in existing databases has been applied in more and more scenes with its advantages of non-contact and remote implementation. Due to the influence of illumination, posture, background environment and other factors under the natural unconstrained condition, the recognition rate of the face images captured by the devices is still insufficient in the existing face recognition model. This paper proposes a face recognition method based on fractional differential improved residual network (ResNet), by adding attention mechanism to the original network model structure. At the same time, fractional differential is used to process node functions, and convolution blocks are added to extract more face details. Finally, Arcface loss function is used to optimize the model, and iterative training is carried out in the network to complete face recognition. The experimental results show that the proposed model has better recognition performance and stronger robustness on the existing data sets such as LFW, AgeDB-30, CFP-FP.

Abstract:Aspect-based sentiment analysis aims to identify the aspects mentioned in sentences and their sentiment polarity, which is an important task in fine-grained sentiment analysis. The existing studies use sequence labeling or span-based classification methods, having their own defects such as polarity inconsistency resulted from separately tagging tokens in the former and the heterogeneous categorization in the latter where aspect-related and polarity-related labels are mixed. At the same time, the existing methods ignore the correlation between aspect-polarity pairs in sentences. In order to remedy the above defects, inspiring from the recent advancements in relation extraction, we propose to generate aspect-polarity pairs directly from a text with relation extraction technology, regarding aspect-pairs as unary relations where aspects are entities and the corresponding polarities are relations and utilize sequence decoding to capture the correlation between aspect-polar pairs. The experiments performed on three benchmark datasets demonstrate that our model outperforms the existing state-of-the-art approaches.

Abstract:Emotion recognition as a fundamental topic in computer vision has made tremendous progress, yet emotion recognition in unconstrained environments is still challenging. Existing methods mainly use face, posture, and scene information to recognize emotions, but these methods ignore the uncertainty of individuals in the context, and do not tap the emotional cues in the scene well. Aiming at the problems in existing research, a dual-branch network structure based on body and context cues is proposed. Two branches learning independently, then obtain the result of emotion classification through early fusion. For uncertainties of person in context, the body gesture attention mechanism is utilized to estimate the confidence coefficient and obtain the feature representation of body. For context branch, spatial attention mechanism and feature pyramid network are employed to fully obtain the emotional cues of different granularities in the scene. The experiment results demonstrated that the effectiveness of the proposed method in the EMOTIC dataset.

Abstract:Aiming at the problems of traffic sign detection such as large number of small targets, difficult location and low detection accuracy, a traffic sign detection algorithm based on YOLOv3 is proposed. First, the spatial pyramid pooling module is introduced into the network structure to perform the block pooling operation on three prediction feature maps with different scales, and the output of the same dimension is extracted, so as to solve the problem of information loss and scale disunity that may occur in the multi-scale prediction. In order to improve the detection accuracy of small target, the FI module is added to carry out information fusion of the three scale feature maps, and the small target information contained in the shallow large feature map is added to the deep small feature map. According to the characteristics of traffic sign dataset, the improved TIoU based on GIoU is used as the boundary box loss function to replace MSE function, which makes the boundary box regression more accurate. Finally, k-means++ algorithm is used to perform clustering analysis on the TT100K traffic sign dataset, generating new anchors with smaller size. Experimental results show that the proposed algorithm improves mAP by 11.1% compared with the original YOLOv3 algorithm, and the detection time of each image only increases by 6.6ms, which still meets the real-time detection requirements. Compared with other advanced algorithms, the proposed algorithm has better detection accuracy and detection speed.

Abstract:In order to solve the problem of monitoring the wear status of milling cutters, an improved whale algorithm is proposed to optimize the state recognition method of least squares support vector machine. Firstly, variational modal decomposition is used to process the vibration signal in the milling process, and the characteristics of the inherent modal functions obtained by decomposition is extracted; then, to tackle the problem that whale algorithm is easy to fall into local optimal solution and low convergence accuracy, a hybrid reverse learning algorithm and the nonlinear convergence factor is introduced, and benchmark functions are used to verify the effectiveness of the improved whale algorithm; finally, the improved whale algorithm optimized LSSVM model is applied to the simulation experiment of milling cutter wear status recognition. The experimental results show that, compared with particle swarm algorithm and traditional whale algorithm, the improved whale algorithm optimized LSSVM has higher recognition accuracy.

Abstract:Nowadays, network attacks are becoming more and more organized. How to effectively trace the source of threat organizations is an important part of network security defense. As the manifestation of attacking the victim"s system, threat behavior pattern is difficult to change, which is an advanced feature of the attacker. If the threat behavior patterns can be extracted effectively, the success rate and accuracy of organization traceability will be greatly improved. Therefore, this paper proposes threat behavior Technique Association Algorithm from the perspective of organizational behavior pattern. The algorithm extends the Ward connection aggregation hierarchical clustering, which can extract the threat behavior patterns of the organization by clustering the attack techniques used by the organization, and verifies the technical correlation between the threat behaviors with 95% confidence. In this paper, the threat behavior Technique Association model generated by the algorithm includes 97 types of threat behavior Technique Association clusters. Each cluster can directly see the corresponding threat behavior patterns of different organizations, which can provide strong support for organization traceability.

Abstract:A de-noising hierarchical mapping (DHM) algorithm is proposed in order to use effective deep feature selection methods in multi-dimensional clustering analysis to eliminate redundant and irrelevant features and learn the nonlinear relationship of data elements to extract the best features. In the algorithm, an acyclic neural network is first built based on the denoising autoencoder. Specifically, the fault-tolerant data are trained by hidden layer weighting and activation function to obtain the nonlinear relationship of the input data and the feature space. The features are reconstructed and the best features are selected. Secondly, the feature space is used to adjust the self-organizing feature map neural network. the minimized weighted squared Euclidean distance is calculated to find the matching winning neuron. Finally, the feature selection network and the unsupervised clustering network are combined to construct the noise reduction hierarchical map neural network. The noise reduction hierarchical map neural network is iteratively trained and the weight parameter and the deviation vector are optimized at the same time to realize an effective unsupervised clustering scheme. Experimental results on real data sets show that, compared with AESOM, DCSOM and S-SOM algorithms, the DHM algorithm has better performance in the quality and accuracy of clustering.

Abstract:The micro axial blood pump is one of the most commonly used ventricular assist devices in clinical practice. The axial flow blood pump bionic pulsation device was built to solve the problem that the constant flow assistance does not meet the characteristics of the natural heart. In addition, the long short term memory (LSTM) neural network is used to predict the beating period to improve the synchronization accuracy of the device, aim at overcoming the shortcoming of detection delay and control delay in micro axial blood pump. The root mean square error of the prediction models on the training set and test set is 8.29 and 5.33, respectively. Finally, the conclusion and error analysis are carried out, and the feasibility of the axial flow pump in the synchronous bionic pulsatility is proved.

Abstract:According to the single-fraction power pole and zero model of the Charef rational approximation of the fraction operator, two new types of non-normal scaling equations-the novel scaling equation are introduced, which are used to characterize the limit cases of the Charef rational approximation of the fraction operator. It is physically realizable. Firstly, we investigate the operational validity and performance of the rational function sequence of the novel scale equation, and compare the difference with the typical scale equation. It is found that the real solution of the rational function sequence of the novel scale equation is different from the approximate solution. This equation provides a new idea for the approximate solution of the scale equation. Then combined with the localization feature of the zero-pole subsystem, the operation oscillation period of the novel scaling equation is quantitatively analyzed. Finally, it is found that the distribution of poles and zeros in the complex plane is different from the typical scaling equation, and the singular characteristics of the novel scaling equation are found.

Abstract:The evolution prediction of network public opinion events is a key step in monitoring and management of the complicated network public opinion, as well as in preventing the sudden outbreak of public opinion crisis； however, less attention is paid on the public opinion evolution prediction, especially in the social network. In this paper, an evolution prediction model for public sentiment events on the social network is proposed, in which the sentiment value of comment texts is termed as the object of evolution prediction and the semantic similarity between sentiment words and comment texts concerning some public events is used to construct a corresponding graph structure for each period of event development, then a model for predicting the sentiment time series is constructed by combining gated recurrent unit (GRU) and graph attention network (GAT). To further verify the effectiveness of the proposed model, the text of comments on the Freud event in Twitter is selected as the dataset and the comparative experiments are conducted with the prediction model based on graph convolutional network. The experimental results show that the R2 coefficient of determination of the proposed model is 0.569, the mean absolute error (MAE), mean square error (MSE) and root mean square error (RMSE) are all smaller than those of the graph convolutional network-based prediction model, which can demonstrate the better performance of the proposed model concerning the evolution prediction of the public sentiment events under the social network environment.

Abstract:The absorption properties of Pd-doped PC6 (PdPC6) for the individual O2, CO, NO, N2O, NO2, SO2, H2S and NH3 molecules are studied by using the first-principles calculation method based on density functional theory, and the influence of gas molecule adsorption on the electronic and optical properties of PdPC6 is analyzed. The results show that Pd doping in PC6 enhances the adsorption energy of gas molecules and shows the adsorption sensitivity to the eight gas molecules. The adsorption of gas molecules causes the reconfiguration of the charge distribution of the system and hence the change of its electronic properties. PdPC6 transforms from metal to semiconductor after O2, NO, NO2 and SO2 adsorptions, while it retains metal property after the adsorptions of CO, N2O, H2S and NH3. The adsorptions of O2, CO, NO and SO2 can induce PdPC6 to produce magnetism and exhibit different spin distribution characteristics. The adsorption of gas molecules can also adjust PdPC6’s work function, and its value depends on the quantity and orientation of charge transfer. Gas adsorption can result in variation of optical absorption spectra of PdPC6. O2, NO, NO2 adsorptions make the system produce new absorption peaks at different frequencies in the low frequency region, therefore, the species of gas molecules can be identified by measuring the absorption spectrum at a specific frequency. The results provide a basis for the design and preparation of gas sensors with high sensitivity and high selectivity.

Abstract:Surface nanocrystallization can significantly improve the surface mechanical properties of metal materials and promote the thermal diffusion of atoms. This article attempts to use surface nanotechnology to improve the mechanical properties of the combination of 316L stainless steel metal substrate and Er2O3 thin film. The supersonic particle bombardment of 316L stainless steel was used to nanometerize the surface of the substrate, and then magnetron sputtering was used to deposit an erbium oxide film on the nanometerized and coarse-grained 316L stainless steel substrate and anneal at 500 ℃ and 700 ℃. The phase structure of the thin film was basically stable when annealed at 500 ℃. The erbium oxide film undergoes an obvious monoclinic to cubic phase transition when annealed at 700 ℃. Using X-ray diffraction (XRD), field emission scanning electron microscope (SEM) and friction test to evaluate the bonding properties of the film substrate. The results show that the annealed SEM image at 700 ℃ has fewer cracks and is smoother than that at 500 ℃, and it is proved that the nanometerization of the substrate will improve the bonding performance of the film substrate.

Abstract:Coherent states were first proposed by Klauder and Sudarshan in 1960. Based on this, many classical and nonclassical measures of light have been introduced. In 1971, Radcliffe proposed atomic coherent state, but the nonclassical measures based on atomic coherent state are still seldom studies. In this paper, by using the characteristics of the atomic spin coherent states, we introduce a method to measure nonclassicality and discuss some properties of this measure. For example, the invariance under the action of rotation operator and the nonclassicality of pure state. Some computational examples, such as cat state, NOON state and mixed states are given. This measure is only discussed in the spin-1 system. These results will have certain significance for exploring the measurement of quantum nonclassicality and quantum resource theory. It will also play a positive role in utilizing nonclassicality measure in the laboratories.

Abstract:In this paper, three crystal structures of ReB3, P6m2, P63/mmc, P3m1, and their structural poroperties, are calculated by using pseudopotential plane-wave method. It is found that the P6m2-ReB3 is the ground-state phase of ReB3. In particular, the elastic properties such as, elastic constants, elastic anisotropy, aggregate moduli and wave velocities of P6m2-ReB3 under high pressure are investigated systematically for the first time. The toughness and brittleness are also predicted for the P6m2-ReB3 structure. In addition, dependences of the Debye temperature, normalized volume, bulk modulus, thermal expansion coefficient, and heat capacity on pressure or temperature for the P6m2-ReB3 structure are analyzed through the quasi-harmonic Debye model.

Abstract:In order to realize the application of wettability-patterned superhydrophobic surfaces in avionics cooling, the dynamic wetting behavior and heat transfer characteristics of droplets impact on bi-phobic surface (superhydrophobic matrix with hydrophobic patterns) are analyzed. The dynamics of droplets spreading and receding phases, and the corresponding spatial distribution of the surface temperature and heat flux beneath the impact droplet, are acquired by using high speed camera and infrared camera, respectively. We analyze the discrepancies of dynamic wetting and local heat transfer during single droplet impingement onto superhydrophobic, hydrophobic and bi-phobic surfaces. Furthermore, the influences of surface temperature and impact height on droplet impact process are also analyzed. The results show that all surfaces have the same wetting behavior and similar heat transfer characteristics, surface temperature has little effect on the surface wetting behavior. Furthermore, the spreading time has nothing to do with surface temperature and impact height in spreading process. Due to the difference of wetting behavior, the heat transfer characteristics between the three surfaces are significantly different in receding process. The special wetting behavior of the bi-phobic surface makes the contact line velocity of the receding liquid film drastically change, produces some small droplets, increases the contact area in receding phase, and also has the resilience properties of superhydrophobic surface.

Abstract:In this paper, a terahertz (THz) dual tunable broadband metamaterial absorber based on bulk Dirac semi-metal (BDS) and water is proposed. Unlike the traditional single-control vibration absorber, the vibration absorber can be adjusted by temperature and Fermi level. The simulation results show that when the water temperature and Fermi level of BDS are adjusted at 15 ℃ and 30 meV, respectively, the absorption rate is greater than 90% in the frequency range of 2.97~6.11 THz. Compared with the absorber without water injection or BDS mode, the bandwidth with an absorption rate of more than 90% has been significantly improved. In addition, by adjusting the temperature of water or Fermi energy of BDS, the absorption bandwidth and intensity of the absorber can be controlled independently or jointly, without redesigning the device. We use the characteristic that the dielectric constant of water can be adjusted by temperature, as well as the characteristic that BDS can be controlled by Fermi energy, the action mechanism of the dual-control absorber is explained. In this paper, the physical mechanism of broadband absorption is studied and clarified by means of field analysis. Based on its excellent performance, our research results may have potential applications in the field of thermal detectors and terahertz imaging.

Abstract:In the face of ever-increasing food safety issues, the detection of bad additives is critical. In order to achieve the effective detection of maleic acid in food additives, we propose to use compound 1 (2,2’-diformyl-1,1’-binaphthyl) to indentify maleic acid by fluorescent. The conditions of fluorescence detection are explored in detail in detail, and the results show that the best fluorescence enhancement effect is obtained in methanol. The calculations predict the low detection limit (1.3×10-7 mol/L), which indicates that it has potential application prospect. Finally, maleic acid in starchy foods was successfully detected by using this probe.

Abstract:The choline chloride-urea deep eutectic solvent system was used to leach blast furnace dust, and then zinc was obtained by direct electrodeposition. The effects of liquid-solid ratio, leaching time, and stirring speed on the leaching rate of zinc were investigated. After the leaching experiment, the cyclic voltammetry and electrodeposition experiments were carried out, respectively. The experimental results showed that the leaching rate of zinc reaches 71% under the conditions of liquid-solid ratio of 10 mL/g, the leaching time of 30 h, the stirring speed of 300 r/min, and the temperature of 70 ℃. The cyclic voltammetry test confirmed that the reduction potential was -1.4 V. X-ray diffraction and energy spectrum analysis showed that the coating was metallic zinc with high purity. By analyzing the morphology of the coating, it was found that the zinc coating was composed of cluster grains of about 1 μm.

Abstract:This study aims to explore the potential application value of citral in the drought resistance of plants. Different concentrations of citral were used to treat Arabidopsis thaliana seedlings, and it was found that the survival rate of Arabidopsis thaliana treated with 200 μmol/L citral under subsequent drought stress was up to 80%, while that of the control group without citral treatment was only about 40%. The results of transcriptome sequencing (RNA-seq) showed that there were 230 differentially expressed genes (DEGs) between seedlings treated with and without 200 μmol/L citral. DEGs were significantly enriched in the response to stimulus and protein processing in endoplasmic reticulum, respectively, in GO term and KEGG pathway, and most of 129 up-regulated genes were related to the heat shock proteins. Four of them (AT1G07400, AT2G26150, AT4G25200, AT4G12400) were selected for RT-qPCR verification, and the gene expression level reflected by RT-qPCR was consistent with the RNA-seq data. The results of this study indicated that the drought resistance was obtained in Arabidopsis thaliana seedlings treated with 200 μmol/L citral, which may be realized by heat shock proteins to restore the physiologically active state of functional proteins that partially unfolded under subsequent drought stress conditions, thereby acquiring better tolerance and resistance to drought stress.

Abstract:In order to alleviate the contradiction between market supply and demand of Fritillaria cirrhosa, the regenerated bulbs of Fritillaria unibracteata Hsiao et K. C. Hsia var. wabuensis were produced by tissue culture technology in this study, the suitable tissue culture conditions were also explored, and the total alkaloids were determined by acid dye colorimetry. The results showed that the bulbs were sterilized with 75 % ethanol for about 10 s and 0.1 % HgCl2 for 15 min with the lowest explants contamination rate. Different types and concentrations hormones can affect the initiation and growth of explants, the concenteation range of NAA and 6-BA were controlled at 0.5~2.0 mol/L, respectively, and both can promote the growth of regenerated bulbs. The contents of total alkaloids in regenerated bulbs of Fritillariaunibracteata Hsiao et K. C. Hsia var. wabuensis were determined. Under different hormone culture conditions, there were differences in the total alkaloids of regenerated bulbs of Fritillaria unibracteata Hsiao et K. C. Hsia var. wabuensis, and the total alkaloids of more than half of the regenerated bulbs in tissue culture met the requirements of Chinese Pharmacopoeia. Therefore, tissue culture is an effective way to obtain the active ingredients of Fritillaria unibracteata Hsiao et K. C. Hsia var. wabuensis.Fritillaria unibracteata Hsiao et K. C.

Abstract:Stress refers to the ability of plants to establish protective and adaptive mechanisms under continuous exposure to environmental stimuli. As an epigenetic phenomenon, histone deacetylation plays an important role in plant adaptation. In order to explore the role of histone deacetylase in plant resistance and adaptation to high salt stress, wild-type and h2tq (HD2 four mutants) of Arabidopsis thaliana were used in this study. RNA-seq and bioinformatics methods were used to analyze the transcriptome of 10 day old seedlings before and after high salt (150 mmol/L NaCl) treatment, and the reliability of transcriptome data was verified by real-time quantitative PCR. The results showed that there were 25 differentially expressed genes in WT and hd2q, including 2 up-regulated genes and 23 down-regulated genes. After high salt treatment, there were 1407 differentially expressed genes in WT and hd2q, including 772 up-regulated genes and 635 down- regulated genes. Go and KEGG analysis showed that the control genes were mainly enriched in the extracellular region and in response to abscisic acid, while the salt treated genes were mainly enriched in the extracellular region and cell wall. Response to salt stress is a complex process involving different cross pathways. These results can provide some reference for the study of epigenetic response to salt stress.

Abstract:Actinidia chlorotic ringspot-associated virus (AcCRaV) is one of the main viruses that infect kiwifruit. For the rapid detection and monitoring of AcCRaV in kiwifruit, in this study, a reverse transcription loop-mediated isothermal amplification (RT-LAMP) combined with lateral flow dipstick (LFD) method was established, which could achieve rapid and visual detection of AcCRaV in kiwifruit. In this experiment, a set of LAMP specific primers was designed based on the conservative region of the AcCRaV coat protein gene. The optimized reaction system was reacted for 60 min under a constant temperature of 62 ℃, followed by 5 min test strip color reaction to finish the sample detection. The detection sensitivity of the RT-LAMP assay was 100 times higher than that of RT-PCR. The results of RT-LAMP detection of kiwifruit samples were consistent with those by RT-PCR detection, even more, the RT-LAMP results could be visualized through LFD test strips. In conclusion, this method can provide a time-saving and efficient diagnostic tool for detecting AcCRaV infection in kiwifruit.

Abstract:In order to explore the potential role of highly-expressed lncRNAs (HlncRNAs) in regulating the midgut development of Apis mellifera ligustica worker, the omics data obtained in the previous at 7- and 10-day-old A. m. ligustica workers’ midguts were used to screen out the HlncRNAs. RT-PCR was performed to confirm the real expression of aforementioned HlncRNAs and analysis the expression pattern of them during the developmental process of 1~21 days old workers’ midguts, and bioinformatic analyses of the regulatory function of HlncRNAs were further performed. The results suggested that the 9 HlncRNAs in the 7- and 10-day-old worker’ s midgut were the same. These HlncRNAs were expressed in 1- to 21-day-old workers’ midguts but their expression patterns were different. HlncRNAs regulated 32 upstream and downstream genes and 18 co-expressed mRNAs via cis-acting and trans-acting manner, respectively. Additionally, these HlncRNAs can target 55 miRNAs and further bind to 131 mRNAs. These results reveal the 9 HlncRNAs potentially regulated functional terms and pathways such as the stress response, sugar digestion and absorption through cis-acting, trans-acting and ceRNA network to regulate the development of A. m. ligustica worker’ s midgut.