Abstract:Let $\gcd(k, j)$ denote the greatest common divisor of the positive integers $k$ and $j$, $r$ be any fixed positive integer. In this paper, by using the identity of Kiuchi on $M_r(x; f)$ together with analytic method, we present asymptotic formulas of $ M_r(x;J_k)$. This complements and strengthens the corresponding result obtained by Kiuchi and Saad eddin in 2018.

Abstract:Principal component analysis is widely applied in dimensionality reduction and feature extraction，especially in tackling single high-dimensional dataset. However，traditional principal component analysis faces challenge when it comes to analyzing multiple datasets jointly. This paper introduces a novel approach named trace ratio principal component analysis，which can discover low-dimensional structure unique to the target data relative to others. Furthermore，trace ratio principal component analysis and its variants can be solved by efficient iterative algorithm. Numerical experiments show the efficiency of the method.

Abstract:In this paper, we define the weak solutions of the elliptic equation in infinite dimension and obtain their existence and uniqueness. Then, under suitable assumptions, the existence and uniqueness of solutions of the infinite dimensional wave and Schrodinger equations are obtained by the semigroup method.

Abstract:This paper introduces and analyses a full augmented mixed finite element method for the nonlinear elasticity problems with strongly imposed symmetry stress tensor. The mixed method includes the strain tensor as an auxiliary variable, which combines with the usual stress-displacement approach adopted in linear elasticity. By introducing different stability terms, we obtain an argmented mixed finite element variation formulation and a full argmented mixed finite element variation formulation. In order to obtain the well-posedness of the two schemes, we adopt different finite element spaces to approximate the variables and derive the optimal error estimate. Finally, a numerical example is presented to confirm the theoretical analysis.

Abstract:Let $H$ be a GLS-algebra and $D_{sg}({\rm{mod}}^{\mathbb{Z}} H)$ be the singularity category of finite-dimensional $\Z$-graded $H$-modules. In this paper we prove that $D_{sg}({\rm{mod}}^{\mathbb{Z}} H)$ admits a tilting object $T$, and therefore $D_{sg}({\rm{mod}}^{\mathbb{Z}} H)\simeq K^b(\proj(\End(T)^{op}))$.

Abstract:In this paper, an initial boundary value problem of Benjamin-Bona-Mahony equation is studied numerically. Firstly, the problem is discretized and linearized by extrapolating in time layer, and then extrapolated at the space level with Richardson's extrapolation idea, thus a three-layer linear difference scheme is proposed. Secondly, the existence and uniqueness of the decomposition of difference of the discrete solution are proved. Finally, the convergence and stability of the scheme are proved by combining mathematical induction and discrete functional analysis. Numerical experiments show that the accuracy of the scheme is obviously better than that of the known linear layer difference scheme.

Abstract:Directly processing the track initiation and tracking of the points recorded in the radar point recorder of the threedimensional air traffic control system will generate a large number of false alarms and a large amount of calculation. When performing target tracking, the number of candidate point sets is huge is the main reason for the large amount of calculation in the target tracking process. Based on the dynamic adaptive DBSCAN clustering algorithm and the classic Kalman filter tracking algorithm, a hybrid dynamic adaptive DBSCAN clustering tracking algorithm is proposed in this paper to reduce the number of candidate point sets. Experiments have found that the number of invalid points is reduced and the track quality is improved Computing time decreases. Through the dynamic adaptive DBSCAN clustering tracking hybrid algorithm, it can quickly track the target detected by cnac radar once and form the target track, which can detect the black flight target in time and reduce the interference to the normal flight of civil aviation aircraft to the minimum.

Abstract:RTK positioning is a realtime kinematic positioning technology based on the carrier phase measurement. By resolving data from the base station and the rover, the position data of the rover can be obtained, which is more accurate than the traditional GPS positioning. In this paper, we propose ERTK (Edge realtime Kinematic), a realtime Kinematic carrier phase differential positioning method based on Edge computing. By transferring RTK resolving task to edge equipment, there is less requirementofhardware performance in the rover, and tthe cost of each rover can be reduced. Weimplement and test this ERTK, and theexperiments have proved that the ERTK positioning can achieve the same accuracy as the traditional RTK positioning at a lower hardware cost. In addition, when using GPS+BEIDOU GNSS data to resolve and positioning, compared with the GPS+GLONASS positioning, the Fix speed is greatly improved.

Abstract:Lowlight images have problems such as low overall brightness of the image, uneven brightness, high color saturation, and image blur. To address these problems, a lowlight image enhancement algorithm fusing color model space is proposed, in which the images are processed by transforming image brightness enhancement and image color restoration to different color model spaces respectively. In the RGB color model space, the high gray levels of the image are first preprocessed and then filtered, and finally the image brightness is restored with the threecomponent enhancement function; In the HSV color model space, the image brightness is restored with the nonlinear color saturation correction function and the brightness enhancement function, and finally the processing results in the RGB and HSV color model spaces are weighted and fused. The final comparative experimental results show that the proposed method has a good effect in avoiding excessive image enhancement, color restoration and image light enhancement, and the processed images conform to the human visual characteristics.

Abstract:In view of the existing Trojan detection methods based on network flow’s anomalous behaviors, there are some problems, such as the lack of representativeness of features, the poor detection effect caused by information redundancy. A feature selection method was proposed in this paper. Firstly, in order to get sufficient feature set, features were derived from the relevant attributes by analyzing communication behavior of Trojan. Then, in order to measure the importance of feature and the correlation between features, the improved evaluation coefficient of feature importance and the joint evaluation coefficient based on correlation entropy are proposed, and a feature selection algorithm based on sequential backward selection was designed to obtain a feature subset of adaptive size. The evaluation coefficient of feature was calculated through each iteration, and the selection was done by sorting those features. In order to verify the validity, the proposed method was compared with FCBF and IG by using the naive bayes classification and the SVM classification algorithm. Compared with FCBF, the recall rate of the two classification algorithms increased by 3.76% and 1.64%, and the F1 increased by 1.04 and 0.99. Compared with IG, the recall rate increased by 6.46% and 4.96%, and the F1 increased by 3.56 and 3.18, respectively. The results of contrast experiments showed that the proposed model can effectively select the characteristics of each attribute from Trojan traffic by using the proposed feature selection algorithm, and overcome the influence of the correlation between features by using the optimized feature subset. The purpose of reducing feature dimension and improving Trojan traffic detection was achieved.

Abstract:Emoticon, as an emerging network graphic language, is widely used on the social platform due to its ability to express the sentiment and attitude of users intuitively. The current studies take emoticons as text features so that they can neither capture more finegrained correlations between emoticons, nor can they adapt to the development and change of emoticons. In order to overcome the above difficulties, we propose an emoticonimagefeature learning method based on Convolutional Auto Encoder (CAE) for microblog sentiment classification. Our model can learn image features of emoticons by CAE automatically, and such features are incorporated into the embedding representations of microblogs for sentiment classification. We verify the effectiveness of our proposed model on Chinese microblog and twitter datasets, respectively. The experimental results demonstrate that our model outperforms the stateofart methods, and the image features learned by our proposed model have stronger generalization ability even with new emoticons in crosslanguage environment.

Abstract:Since we own integrated operational amplifier, virtual short circuit and virtual open circuit and two types of integrated operational amplifier have emerged, but it has no necessary connection with the typical single-stage current series negative feedback and voltage parallel negative feedback, the two-stage voltage series negative feedback and current parallel negative feedback, and it have no detailed report. In this paper, we try to to accurate calculate i_b、u_be、A_uf according to two-way equivalent conversion of the feedback elements in the four circuits. When u_be and i_b approaching to zero at the same time is defined as virtual short and virtual break. When calculating A_uf , we should pay close attention to the two core components and ignore the secondary part of the project, and get the same result as the two types of integrated operational amplifier. In this way, not only the tedious and less used calculation of the original separation circuit is avoided, but also perfect transition from separation to integration is achieved.

Abstract:Most of the research on malware identification is based on the application program interface (API) call, but most of the current API based research does not consider the state of the device. However, the device state can directly reflect the running environment of the program, such as human operation or program automation, and it plays an important role in the analysis of application behavior. In this paper, a sensor based application behavior recognition technology is proposed. Firstly, the realtime status of the device is judged by the sensor data. Secondly, the algorithm is designed to identify the malicious application behavior using the multiple time series data generated by combining the API call time series and the first screen time series of graphical user interface (GUI). Finally, the malicious behavior analysis prototype system is designed and implemented, and it includes the functions of static piling, dynamic behavior monitoring and realtime status collection of sensors. Typical cases were selected to verify the accuracy of the proposed method, and the black box test was performed to verify the effectiveness of the malicious application identification method in this paper.

Abstract:Complex malicious activities in the Internet are jointly performed by IP address clusters. It has become an important research direction to find malicious IP clusters by processing data collected in the network. An IP blacklist association clustering algorithm (IPBACA) is proposed in the paper, in which first constructs an IPIP undirected graph, and then uses measurement statistical correlation to measure the correlation between IP blacklist and IP, and uses the given IP blacklist to find the best threshold worthy of malicious clusters, and judges its standardized residuals whether it is up to standard, it finally identifies a malicious cluster with high precision. The simulation results show, compared with ICAMO algorithm, CAIIB algorithm and DABR algorithm, the IPBACA algorithm proposed in this paper has a significant improvement in the four main performance indicators of precision, recall, F1 and normalized mutual information, and significantly improves the detection ability of malicious clusters.

Abstract:The effects of two different chirped pulses on ionization and dissociation probabilities of H2+ have been investigated theoretically. The results show that for the case of two-order chirped pulse, the ionization and dissociation probabilities of H2+ are linearly decreased as chirp parameters change from negative values to positive values. For the case of three-order chirped pulse, the ionization and dissociation probabilities of H2+ present the ‘W’ structure as chirp parameters change, and the maximum ionization and dissociation appear at the chirp parameter being 0.01.

Abstract:In view of the external magnetic field having an impact on the discharge activity of neurons, a four variable ML(Morris and Lecar) neuron model with magnetic field is discussed. The bursting type and bifurcation process are revealed by using fast/slow dynamical bifurcation analysis, and discharge behavior of the system with the change of flux feedback coefficient is studied. At the same time, taking the three coupled neuron models with ring connections as an example, by defining the synchronization criterion—correlation coefficient and the maximum synchronization difference of fast and slow variables, it is found that under the action of magnetic field, a very small coupling strength can make a system transform chaos state into periodic discharge mode, and induce the synchronous transition of neuron from unrelated to burst synchronization, then to spike synchronization. Within the appropriate dual parameter range, the system is easier to synchronize with the appropriate coupling strength. It is helpful to understand the influence of electromagnetic radiation on the collective discharge motion of neural network and its synchronization mechanism under the proper coupling connections mode.

Abstract:The molecular dynamics simulations with condensed-phase optimized molecular potentials for atomistic simulation studies (COMPASS) force field have been employed to study high energetic material CL-20. The lattice parameters and elastic constants in the pressure range of 0~10 GPa (for ε-CL-20) and 0~20 GPa (for α-, β-, and -CL-20) at room temperature, and in the temperature range of 100~500 K at room pressure are predicted. The good agreement of lattice parameters, pressure-volume relation and elastic constants of the greatest stability phase ε-CL-20 shows the accuracy of our simulations. The theoretical predictions of lattice parameters and mechanical properties of CL-20 under temperature and pressure can provide powerful guidelines for the engineering application and await further experimental confirmation.

Abstract:We study the electronic structures and optical properties of two-dimensional ZnS modified by H and F. Based on the first-principles of density functional theory (DFT), the crystal structures, stability, electronic structures and optical properties of these two-dimensional materials are calculated. The results show that the two-dimensional ZnS is a quasi-planar structure, which can transform into buckling six-membered ring structure after modification. Phonon dispersion and formation energy analysis reveal that all the chemically decorated ZnS are energetically favorable and could be synthesized. The electronic structures indicate that the two-dimensional ZnS is a direct bandgap semiconductor with energy gap of 2.625 eV. In addition, H modified ZnS will increase its energy gap and turn it into an indirect band gap semiconductor, while F modified or H-F co-modified ZnS will reduce its energy gap. The effective mass shows that the two-dimensional ZnS is a light-hole, heavy-electron type semiconductor. After H or F modification, the electron effective mass of ZnS increases significantly, but the change of electron effective mass is relatively small. Optical properties show that ZnS modified by H and F will lead to blue shift of its absorption edge, among them, the F modified and H-F co-modified (H and Zn on one side, F and S on the other) ZnS significantly enhance the absorptions of short-wavelength and middle-wavelength ultraviolet, rendering new promises in next generation high-performance electronic devices.

Abstract:The ground state structures, stabilities, electronic configurations and magnetic properties of anion gold clusters and anion Cr-doped gold clusters have been systematically investigated by density functional theory. Our results show that 〖"Au" 〗_"n+1" ^"-1" (n=1~10) clusters and AunCr-1 (n=1~6) clusters are planar configurations and AunCr-1 (n=7~10) clusters are body structures. Remarkably, the stabilities of anion gold clusters can be improved by Cr-doping. The dissociation energies and second-order difference energies results indicate that the even number of 〖"Au" 〗_"n+1" ^"-1" clusters and AunCr-1 clusters are more stable than adjacent odd clusters. The charges of the orbitals indicate that the incorporation of Cr atom makes the spd hybridization of Au atoms more complicated, and the Cr atoms are the main acceptors of the valence charge in AunCr-1 clusters. The results of orbital magnetic moment show that the electronic structure of 〖"Au" 〗_"n+1" ^"-1" clusters exhibit obvious open-closed shell structures with size increasing and the electronic structures of AunCr-1 clusters are Open shell. In this regime, the magnetic moment of 〖"Au" 〗_"n+1" ^"-1" clusters is mainly contributed by the Au5d orbitals, while the magnetic moment of AunCr-1 clusters is mainly contributed by Cr3d orbitals.

Abstract:The microstructures and hot compression behavior of Mg-4Sn-1Ce alloy were studied by optical microscopy (OM), X-ray diffraction (XRD), scanning electron microscopy (SEM) and hot simulation test. The results shown that the as-cast alloy is mainly composed of island-like “island” shaped α-Mg、Mg2Sn、Ce4Sn5 and MgSnCe phases with the strain rate range of 0.001~1 s-1 and temperature range of 250~450 ℃ hot compression. The hot deformation activation energy Q is 162.03 kJ/mol. When the hot compression temperature increases from 250 to 450 ℃, the microstructures of tested alloy evolve from (compressed grains+extruded streamlines) to recrystallized equiaxed grains.

Abstract:Heavy metal ions have a serious impact on water quality and its application, and the development of a highly selective and sensitive detection platform for heavy metal ions has great significance in the water resources protection. The surface-enhanced Raman (SERS) sol substrate was prepared by using 4-MBA to modified gold nanoparticles as a carrier, which has strong selectivity and high sensitivity to heavy metal ions such as Pb2+, Cd2+, and As3+ in aqueous solution. The experiments found that the Raman detection spectra of Pb2+, Cd2+ and As3+ by the SERS substrate have obvious shifts in vibration frequency bands and peak intensities near 1046cm-1, 1075cm-1, and 1587cm-1. An optimized enhanced substrate was obtained by optimizing the sol-substrate, which can distinguish three kinds of heavy metal ions. The detection limit for heavy metal ions can reach 0.1mg/L, and it has a linear relationship in the range of 0.5 to 100 mg/L. A standard addition verification experiment was performed on Pb2+ in real water samples. This substrate provides a fast and convenient method for heavy metal identification and detection with better enhancement effect and heavy metal quantitative analysis ability, and provides an effective means for the efficient detection of heavy metal ions in water.

Abstract:In order to research and develop the abundant resources of Jatropha curcas, the seeds of Jatropha curcas from the dry hot valley of Jinsha River in Xichang City, Sichuan Province were used as materials. The tissues for experiment were collected after soaking seeds in water to germinate. The qRTPCR results showed that the expression of Curcin and Curcin C genes in endosperm increased first and then decreased, as did the expression of Curcin C gene in cotyledons. Western Blot results showed that Curcin protein was not expressed in roots, hypocotyls, true leaves and cotyledons, Curcin C protein was also not expressed in roots and hypocotyls, but expressed in true leaves and cotyledons. Both bioinformatics software prediction and subcellular localization results showed that Curcin:GFP and CurcinC:GFP fusion proteins were localized in the cell wall. In this study, the expression patterns of two ribosome-inactivated proteins Curcin and Curcin C in Jatropha curcas were preliminarily elucidated and subcellular localization was performed.

Abstract:In order to explore the effects of All-Trans-Retinoic Acid (ATRA) on the growth of pancreatic cancer and osteosarcoma cells, this study used a larger span of ATRA concentration to treat pancreatic cancer cells PANC-1 and osteosarcoma cells U2OS and cell viability was determined by MTS viability assay. The results indicated that ATRA at a low concentration of 20~100 μmol/L could promote the growth of PANC-1 cells, on the contrary, ATRA at a high concentration of 200 μmol/L inhibited their growth. In U2OS cells, a low concentration of 10~80 μmol/L ATRA could facilitate cell growth, while a high concentration of 150~200 μmol/L ATRA showed a significant inhibitory effect on cell growth. The growth-promoting effects of low concentration ATRA could be inhibited by Bortezomib（BTZ）, while the inhibitory effects of high concentration ATRA could be enhanced by BTZ. The combination of ATRA and BTZ at low concentration reduced the expression of the apoptotic precursor protein Procaspase3, suggesting that the combination might affect the apoptotic pathway. This is the first report for the double-sided effects of different concentrations of ATRA on the growth of pancreatic cancer and osteosarcoma cells, reminding us that more attention should be paid to the impact of ATRA dosage on clinical therapy.

Abstract:In order to develop highefficiency endogenous multigene activation tools, and based on the CRISPR/Cpf1 system, which can promote the self-cleavage and release of multiple crRNAs in pre-crRNA, the TRE3G-DD-dCpf1-VPR activation system was constructed. In this system, the sitedirected mutation of the nuclease region of As/Fn/LbCpf1 to form dCpf1, and The VPR with DD-domain the tetracycline-controlled operon were introduced at the C and N terminal, respectively. The results showed that the transcription level of Oct4 gene was increased by 104 times, and the transcription levels of Myod1 and Oct4 genes can achieve different levels under the control of Dox and TMP single drugs respectively. Under the condition of adding dual drugs, Myod1 and Oct4 genes can be increased by more than 80 and 120 times respectively. It proves that the system can induce endogenous multi-gene activation quickly and efficiently by targeting DNA.

Abstract:This study aims to explore the composition and function of the microbial community of the deep strata in Jinping. The high-throughput sequencing was used to investigate the microbial diversity and the microbial populations in the deep strata of Jinping. A total of 732,477 clean tags were obtained and clustered to 1,318 effective OTUs based on 97% sequence similarity.Though there were certain differences among the microbiota of each samples. The dominant bacteria in phylum remained the same, which are Proteobacteria, Actinobacteria, Bacteroidetes and Firmicutes. PICRUSt analysis was performed to show that abundance of the functional genes higly involved in Carbohydrate metabolism, Amino acid metabolism, Energy metabolism and Metabolism of cofactors and vitamins. The research reveals that the phylogenetic diversity of the microbial communities in the deep strata of Jinping is complex, but the main microbial communities are relatively stable.