Abstract:The paper discusses the impact of natural sciences such as artificial intelligence technology to Jurimetrics, computational law (or computational jurisprudence) and cognitive law (or cognitive jurisprudence) from the perspective of technological development and interdisciplinary. It first proposes the theory and definition of cognitive law, including its research scope, studying meanings and academic discipline, and teases out the relationships among Jurimetrics, computational law and cognitive law. To reduce the subjectivity and provide the objective reference for the vague expression in legal system, some quantitative methods, computational intelligence and cognitive intelligence are applied to legal system successively. However, legal information is open textured and semantic vagueness, and it is difficult to express all kinds of tacit knowledge, process knowledge and fuzzy knowledge by computer symbol system. Cognitive intelligence stresses to improve the ability of intelligent systems to understand data, express knowledge, reason logically and learn by themselves. Following the footsteps of technology, it will be the inevitable trend stepping from Jurimetrics and computational law to cognitive law. Cognitive law improves the understanding of legal rules and analysis of legal behavior, and enhances the interpretability of intelligent judgments by utilizing cognitive intelligence. As the sub-branch of cognitive social science, cognitive law will improve traditional legal theories, promote the deeply integration of the Common law system and the civil law system, and is expected to be a new interdisciplinary subject.

Abstract:In this paper, we propose a model for the recommendation of applicable law articles. As an application, the judgment documents data sets of fraud and divorce dispute are selected from the criminal and civil cases. Based on transfer learning, the legal word vectors are trained from the pre-trained general word vectors by using the FastText model. Then, the text is classified according to the well trained vectors. The simulation results show that for both the fraud and the divorce dispute, after the transfer learning, the applicable law can be recommended comprehensively and accurately for the case discription text, especially for the targeted regulations and judicial interpretations. With the continuous improvement of the transfer learning mode, our model is expected to be further applied to the evidence pushing and sentencing prediction.

Abstract:As a class of simple mathematical models, the model of tossing an unbiased coin independently has extensive applications in many fields. The length of the longest head run has been long explored by many scholars. Up to now, there is still a lot of results on the extension of this problem and their applications. In this paper, we study the length of the longest consecutive switches and present several limit theorems.

Abstract:In this paper, by using the dynamical bifurcation theory of non-linear evolution equations, we consider an antiviral drug therapy model with Neumann boundary condition, explore the dynamical bifurcation and its practical significance. Numerical stimulation shows the effectiveness of the model.

Abstract:This paper aims at the obstacle avoidance problem for swarm in a multi-obstacle environment. Based on the improved Cucker-Smale swarm motion model and limit-cycle obstacle avoidance algorithm, we propose a new CS flocking model. In this model, we improve the multi-obstacle merging method, introduce the well-directed movement rules. The simulation results show that in the entire swarm obstacle avoidance process, the number of collision individuals and obstacle avoidance time of the algorithm are improved compared with the traditional limit cycle obstacle avoidance method.

Abstract:In this paper, we study the singularity and global regularity of a class of degenerate parabolic systems with time-dependent coefficients and Neumann boundary condition. By using the comparison principle of weak solution and some differential inequalities, we give the conditions for the global existence and blow-up of the solution.

Abstract:We investigate the long-time dynamical behavior of coupled suspension bridge equations with nonlocal weak damping terms. Firstly, we establish the well-posedness of the solutions based on the monotone operator theory. Secondly, the dissipation of solution semigroups {S(t)} is obtained. Then the asymptotic smoothness of solution semigroups {S(t)} is verified by using the energy reconstruction method. Fianlly the existence of global attractors for the coupled suspension bridge equations with nonlocal weak damping terms is proved.

Abstract:Lane linedetection at night based on machine vision and image processing has always beena research problem in this field, even with the recent deep learning methods, the detection accuracy can only reach to about 50%. To this end, a new algorithm is proposed in this paper. According to the characteristics of the lane line and the speed of the vehicle, multiple images in a video are fused into one detected image; the effective lane line detection area is identified in the region merging by using the characteristics of the image; after the valid detection region is cut into as a new image, the algorithm based on Frag and Hessian matrix is used to smooth and enhance the image; in order to extract the feature points of lane line, a lane line feature point algorithm is proposed based on a new Fractional differential template, then according to the possible position of lane line in the image, the feature points are detected from four directions. After the candidate points are detected, the candidate lane lines are obtained by recursive Hough line transformation. In order to determine the final lane lines,the angle of one lane line should be between 25° and 65°, while the angle of the other lane line should be between 115° and 155°, otherwise, the Hough line transform is continuedby reducing the threshold of the number of lines until two lane lines areobtained. Through testing hundreds of night lane images, the detection accuracy of the new algorithm can reach to 70% compared with deep learning methods and traditional image segmentation algorithms.

Abstract:The session based recommendation is a subtask of recommendation system, which addresses the recommendation problem about anonymous users. Although the existing methods with the graph neural network for recommendation have achieved good results, which are insufficient to capture more accurate potential information in user’s sessions. To solve the above problem, a novel recommendation model, session based Graph Convolutional Recurrent Neural Networks (GCRNN) is proposed in this paper to capture more potential information in user’s sessions and enhance the recommendation effects. In the proposed model, the graph convolutional neural network layer is used to capture structural information in the user graphs, as well the recurrent neural network layer is utilized to obtain the temporal information and the dependency relationship between sessions to acquire more affluent and accurate potential information in sessions. We conducted extensive experiments on two public datasets, and the results show that GCRNN is superior to the state of the art methods in the sessionbased recommendation.

Abstract:This work proposes a hybrid genetic algorithm based on timetable and A* algorithm to solve the scheduling problem of multiautomatic guided vehicle (AGV) distribution in the flexible workshop, and the optimization goal of the algorithm is to minimize the total time for the AGV to transport the workpieces from the rough library to the finished product warehouse. Two schemes are proposed to solve the collision problem in AGV path planning and the problem of position occupation while the AGV is waiting at the position of machine. The machine and AGV scheduling is integrated in the divided task unit. Then the chromosome coding method based on the task unit is designed. The population initialization scheme, the cross and mutation operator and the elite retention strategy are improved. In the decoding operation, according to the schedule information, the A* algorithm and conflict resolution are used to plan out the best path without collisions and occupation conflicts in each task unit. Finally, the feasibility and effectiveness of the algorithm are verified by the numerical examples.

Abstract:The state detection parameters of gas turbine gas-path components are extremely nonlinear and their fault characteristics are difficult to be extracted,using traditional KPCA for fault detection is difficult to scientifically value nuclear parameters, thus reducing the accuracy of fault detection.To solve this problem, this paper proposes a fault detection algorithm for kernel principal component analysis based on optimized hybrid kernel(DE-KPCA).Firstly, the dynamic weight hybrid kernel function is established, and the global and local mappings are optimized by adjusting the weight ratio of the kernel function. With the sample detection accuracy as the optimization target, the mixed core parameters were optimized successively.Finally, a principal component abnormal state detection method based on optimized hybrid kernel function is constructed to realize on-line detection of gas turbine gas-path faults.In this paper, the fault simulation of turbojet turbojet engine is verified, which proves that this method can realize the scientific value of nuclear parameters and is more accurate and practical for gas turbine gas-path fault detection than traditional KPCA detection.

Abstract:The bandwidth of an automated guided vehicle in industrial environments should meet the requirements of visual navigation, monitoring and control signal transmission simultaneously. Providing image signals in real time while not consuming too much bandwidth has become the key to the transmission of automated guided vehicle in industrial environments. The images used for navigation monitoring should be of high quality in the horizontal field of view. However, the acquisition of the view in the horizontal field is difficult because the road surface is uneven during the moving of vehicles, and the excessive bandwidth occupation of view acquisition will affect the navigation, monitoring and control signal transmission of the automated guided vehicle. Therefore, transmitting image data in real time under lowbandwidth conditions is the focus of automated guided vehicle image transmission research. The image used for navigation monitoring should be of high quality in the horizontal field of view. In order to balance image quality against bandwidth consumption, this paper proposes an image compression algorithm based on the H.264/AVC algorithm. The proposed algorithm uses a gesture sensor to obtain the horizontal field of view as the region of interest, and adopts different compression rates for the region of interest and the region of no interest in the video frame, respectively. Compared to the H.264/AVC algorithm, this method can achieve a higher compression rate while ensuring the image quality, and is more friendly to the network bandwidth.

Abstract:In order to reduce the loss caused by the attack of ransomware, this paper proposed a framework (AntiRansomware System, ARS) based on the family characteristics and the traditional malicious code detection technology. Specifically, a method is proposed to detect ransomware based on file behavior statistics. It uses the minifilter to collect the file behavior information of benign and ransomware as train set, and uses a variety of supervised classification algorithms to train classifier for runtime detection. Then, the copyonwrite technology is utilized to dynamically backup modified files in the program at runtime, and the detection results are used to determine whether to restore files. Finally, a prototype system is developed and tested. The results show that, under the premise of ensuring the security of the data file, the ARS framework can effectively prevent the ransomware attack and reduce the harm of ransomware.

Abstract:Based on the theory of fractional calculus and the fact that actual capacitance and actual inductance are fractional in nature. Firstly，based on the establishment of a fractionalorder mathematical model of the Boost converter, a fractionalorder predictive current control is proposed, and a predictive controller is designed. Secondly, based on the investigation of the inductor current waveform of the fractional boost circuit, an integerorder predictive current control of the fractional boost circuit is proposed. Finally, a fractionalorder inductance approximation circuit was obtained based on the fractional reactance chain and the Oustaloup fractionalorder approximation algorithm. The designed controller was simulated and verified using Matlab software. The results show that the fractionalorder prediction current control has the smallest overshoot and the shortest transition time, especially the performance on antiload disturbance is better. Although the performance of integerorder predictive current control is lower than that of fractionalorder predictive control, it also has better control performance，the simulation results verify the feasibility and effectiveness of the proposed control method as well.

Abstract:Boundary samples of different categories staggered on the boundary in the datasets of named entity recognition research, which affects the performance of named entity recognition model. A method based on local adversarial training and BiLSTMCRF model is proposed to solve the problem above. The method selects hard examples which contain a lot of boundary samples to crafting adversarial samples. The process is based on the characteristics of boundary samples that are easily perturbed to leave from the correct category, and then get adversarial samples from the target attack step according to the confusion matrix error probability distribution. Finally, the datasets mixing with the original data and the adversarial is used to adversarial training to enhance the model’s recognition ability. In order to verify the superiority of this method, global/local adversarial training based on nontarget attack method and local adversarial training based on target attack are designed as comparative experiments. Experimental results show that the method proposed improves the quality of adversarial samples while retaining the advantages of adversarial training. The F1 scores on the three datasets of JNLPBA, MalwareTextDB, and Drugbank are increased by 1.34%, 6.03%, and 3.65% respectively.

Abstract:Analyze the characteristics of B-type fractal-pyramid fractance approximation circuit, which has only negative half-order operational performance. According to scalingextension theory, a fractance approximation circuit with arbitrary real-order calculus operator is obtained——a scaling fractal-pyramid fractance approximation circuit, which then can be described by anirregular double scaling equation. The operational performance and approximation performance of this fractance approximation circuit is analyzed. The typical numerical solution algorithmsare used to analyze the frequency-domain characteristics and operational characteristics, the effects of different initial impedance values on the pole-zero distributions and frequency-domain curves are compared. By combining the operational characteristic curves and thedifferent values of scalingfeature parameters, the optimization principle of the scaling fractalpyramid fractance approximation circuit is theoretically analyzed and a specific optimization method is given. The approximation performance before and after the optimization of the scaling fractal-pyramid fractance approximation circuit is comparatively analyzed, and the operational oscillation phenomenon isquantitatively analyze.The actual circuit design scheme of the scaling fractal-pyramid fractance approximation circuit is introduced and an example is given. Resistors,capacitors, and active devices are used to generalize the operational order of this fractance from-1<μ<0 to 0<|μ|<2. Scalingfractal-pyramid fractance approximation circuit and its optimized circuit provide new ideas for the construction and application of fractance.

Abstract:The electronic structure, magnetic properties and optical properties of the O, Mn single doped and Mn-O co-doped MoS2 monolayer systems are calculated based on the first-principles spin-polarization density functional theory. For Mn and Mn-O doped, the MoS2 monolayer system evolve from a completely symmetric band structures in spin-up and spin-down channels to a half-metal (HM) ferromagnet with completely (100%) spin polarization. their magnetic moments are 1 μB and 1.08 μB, mainly concentrated on the doped Mn atoms. while the spin-down channel remains semiconducting character but with a smaller spin-down gap of 1.613 and 0.396 eV due to appearance of the impurity bands. Meanwhile, in the low energy region (0~2.5 eV), it’s dielectric constant, refractive index and absorption coefficient are significantly enhanced compared with the undoped and O-doped MoS2 system, red shift phenomenon appear after Mn-O co-doped.

Abstract:The intensity of harmonic cutoff region of H2+ and D2+ driven by different laser conditions has been studied theoretically. The results show that for the lower laser intensity case, the harmonic yield of H2+ is higher than that of D2+ when the shorter pulse duration is used. As the pulse duration increases, the harmonic yield of D2+ will be enhanced and higher than that of H2+. For the higher laser intensity case, when the shorter pulse duration is used, the intensity difference of harmonic yield is decreased, though the harmonic yield of H2+ is still higher than that of D2+. When the longer pulse duration is used, the harmonic yield of D2+ is much higher than that of H2+. Theoretical analyses show that the different harmonic yields of H2+ and D2+ is attributed to different time scales of nuclear motion.

Abstract:A self-consistent two-dimensional fluid plasma model coupled with Maxwell's equation at medium pressure is established, and a series of kinetic reaction equations of molecular ions are also added. We demonstrate the changes of electron density, temperature, electric field module, skin depth and other parameters in the excitation process at medium pressure. The dominated reason for the spatial distribution of molecular ions is analyzed. In addition, compared with the atmospheric pressure microwave plasma, it is found that the gas temperature of the medium pressure microwave plasma is lower and the damage to the glass tube is smaller. It can be applied to the treatment of various exhaust gases, the synthesis of nanoparticles and the preparation of thin films, which is easy to achieve large-scale, and has a good application prospect.

Abstract:This paper mainly focuses on the problem that is difficult to determine the geometric shape change of embedded crack propagation in pressure vessels. The stress intensity factor of crack front is obtained by using the methods of Newman and Raju, and the relationships between depth and length changes of different cracks are obtained by combining with Paris formula. Meanwhile, by discretizing the elliptical crack tip into multiple points with equal distances and using the Simpson quadrature method, the geometric change relationships of the embedded cracks of pressure vessels with different materials are obtained under cyclic loading. The results show that under the action of tensile force, the fatigue growth of buried cracks tends to expand in the direction of the optimal expansion path. The larger the initial crack aspect ratio and the exponent m gives rise to the faster the speed of convergence to the optimal propagation path, namely, the faster tendency to form an approximate circle.

Abstract:The turbulent boundary layer with injection and suction is of fundamental interest for the analytical research in the field of transpiration or film cooling, which has an important theoretical significance. The momentum boundary layer is divided into the viscous sublayer and turbulent core zone for steady turbulent flows on a porous flat plate, and the velocity distributions in the two zones are approximated by the cubic polynomial and 1/5 power functions, respectively. An integral method is used to recast the momentum equations into the integro-differential equation groups, and the analytical solutions of velocity boundary layers through the permeable surfaces are obtained by employing the fourth-order Runge-Kutta method. Following the foregoing analytical results, the profile of skin friction factor on the wall is also obtained. It is showed that the proposed analytical solutions have a satisfactory agreement with the existing experimental measurements carried out respectively by Whitten and Blackwell, and also with the empirical formula of Kays.

Abstract:The properties of the sheath directly affect the quality of microwave plasma applied to industry and other fields. Aiming at the difficulty in studying the time-varying spatial distribution and electric field distribution, the finite element method was used to establish a microwave-argon plasma three-dimensional model coupled with Maxwell's equation at medium pressure to analyze the spatiotemporal characteristics of the sheath and give its two-dimensional equivalent model. Based on the analysis of the parameters of plasma, the formation process of the sheath and the change trend of its thickness were presented. The time-space transient characteristics of the plasma electric field and the microwave electric field were compared respectively. The results show that in time, due to the different diffusion speed and stress direction of electrons and ions the thickness of the sheath increases gradually, and eventually forms a steady state sheath; In space, the sheath exists near all the discharge tube walls adjacent to the plasma. The electric field intensity of the sheath layer is always greater than that of the bulk plasma region, and the direction of the electric field always points to the tube wall, which has a damping effect on the microwave electric field. In addition, it is proved by quantitative analysis that the thickness of sheath decreases with the increase of pressure.

Abstract:All-inorganic perovskites, such as CsPbX3 (X = Cl, Br, I), are gaining increasing attention due to their outstanding optoelectronic properties, especially their higher thermal stability comparing with organic-inorganic hybrid perovskites. However, CsPbX3-based photodetector demonstrated a relatively low responsivity due to the low carrier mobility of perovskite films. In this work, we synthesize CsPbBr3 quantum dots and construct a hybrid graphene-CsPbBr3 quantum dots photodetector with a responsivity of 3.5×104 A W-1, by introducing graphene as a transport layer. The unprecedented performance is attributed to the effective charge transfer and photogating effect, high mobility of graphene and prolonged carrier lifetime.

Abstract:Based on the FLIC simulation platform, we have performed a numerical simulation study on a 7 MW biomass layer fired hot air boiler in Northeast China. The simulation results show that the biomass layer can be roughly divided into three stages, the water evaporation section (0~0.5 m), the volatile emission combustion section (0.5~2.1 m) and the fixed carbon combustion section (1.0~2.8 m). The volatile content of this fuel is relatively high, the thickness of the bed after its precipitation is significantly reduced, and the primary air temperature is too low, resulting in a low fixed carbon burnout rate, so the primary air temperature can be appropriately increased. According to the characteristics of the fuel in different combustion stages, the air can be supplied on demand. For example, 80% to 90% of the total volume can be provided during the volatiles escape combustion stage, and 10% to 20% of the total air can be provided during the fixed carbon combustion stage. This improves the fuel combustion efficiency, and can optimize the structure of the arch angle and the furnace arch coverage length according to the flue gas temperature, and enhance the ignition and burnout of the furnace arch. According to the simulation results, it is proposed to optimize the primary air and the air supply scheme to make the combustion more adequate.

Abstract:In order to explore the biological function of bHLH transcription factors in Brassica napus L., two full-length cDNA sequences of bHLH122 transcription factor genes were cloned from Brassica napus L. by homologous cloning method and named BnbHLH122-1 (GenBank accession number: MT795160) and BnbHLH122-2 (GenBank accession number: MT795161) respectively. Bioinformatics analysis showed that both BnbHLH122 proteins were unstable hydrophilicity proteins with the bHLH conserved domain, which were closely related to the predicted bHLH122 proteins in Brassica rapa and Brassica oleracea, respectively. The results of subcellular localization and transcriptional activation verification showed that both BnbHLH122 proteins were located in the nucleus and had transcriptional activation activity. Then the qRT-PCR results showed that the BnbHLH122-1 gene is mainly expressed in the roots at the flowering stage, and the BnbHLH122-2 gene is mainly expressed in the roots at the seeding stage and flowers at the flowering stage. Besides, the expression of BnbHLH122 genes was significantly affected by the stresses of high temperature, low temperature, drought, salt, osmosis, Sclerotinia sclerotiorum and the hormone treatments of ABA, SA and MeJA, indicating that BnbHLH122 genes may play important roles in regulation in the progress of maintaining normal growth and development and resisting stresses in Brassica napus L..

Abstract:The rare plant Camellia luteoflora Y. K. Li has shrunk in the natural distribution area and is at risk of extinction. In order to analyze the potentially suitable distribution area of C.luteoflora under the current climate and environmental conditions, Maximum Entropy Model (MaxEnt) and Geographic Information System (ArcGIS) were used to predict the suitable distribution areas of C.luteoflora and to explore the dominant environmental factors. The results show that Luzhou, Yibin, Zunyi, Zhaotong, Kunming, Jiangjin and Qijiang of Chongqing are the highly suitable areas for C.luteoflora (fitness index>0.54), and the junction of Guizhou, Sichuan and Chongqing is its core distribution area. The results of the jackknife test showed that the main environmental factors affecting the distribution area of C.luteoflora included the average temperature of the hottest quarter (bio 10), the precipitation of the hottest quarter (bio 18) and the precipitation of the coldest quarter (bio 19), with a cumulative contribution rate of 90.8%. The results of statistical analysis of environmental factors in the suitable area show that the highest temperature in the hottest month is 22.5~27.5 ℃, the average temperature in the hottest season is 11.1~18 ℃, the precipitation in the wettest month is 290~500 mm, the precipitation in the hottest season is 4.4~6.6 mm, the precipitation in the coldest season is 16.7~24.8 mm, the altitude is 450~1 000 m, the slope direction is in the range of -40°~190°, and the slope is between 20°~64°, which is the most suitable niche parameter for C.luteoflora. In addition to the three reported natural distribution areas, the prediction results show that there may still be undiscovered growth areas of C.luteoflora, and field surveys are needed.

Abstract:To investigate the possible mechanism of Ganoderma lucidum inhibiting tumor，the H22 tumorbearing mice were treated with triterpenoids, polysaccharides and their mixture separately. The tumor weight and volume were measured, and the proportion of Treg cells in tumor tissues was detected by flow cytometry. The expression level of CCL22、CCR4 and FOXP3 were detected by RT-PCR. Immunohistochemical staining was used to detect the expression level of FOXP3 protein, ELISA was used to detect the cytokine content of IL-10, TGF-β1 and IL-2. The results showed the tumor inhibition rate in the mixture group(47.8%) was significantly higher than that in the triterpenoid group (21.4%) and the polysaccharide group (30.8%) . The proportion of Treg cells of the mixture group (1.93%) in the tumor microenvironment was significantly lower than that in the triterpenoid group (3.04%) and polysaccharide group (2.18%). The levels of FOXP3, IL-10, TGF-β1 and related mRNA were significantly reduced in Ganoderma lucidum groups. Meanwhile, the IL2 level was increased in Ganoderma lucidum groups. Therefore, Ganoderma lucidum can inhibit Treg cell function by reducing the infiltration of Treg cells into tumor tissue and inhibiting cytokine secretion in the mouse tumor microenvironment. Meanwhile, Ganoderma lucidum can increase the level of IL-2 in the tumor microenvironment to promote an antitumor immune response. Besides, the combination of triterpenoids and polysaccharides may have a synergistic effect.

Abstract:The plant hormone abscisic acid (ABA) plays an important role in the response of plants to abiotic and biotic stresses for survival and reproduction. In this study, the TDNA mutants of carks as parents to construct double mutant to detect the function of CARKs in the ABA signaling pathway. Seed germination and cotyledon greening rate were analyzed in plants before and after ABA treatment. The results revealed that, compared with wild type, CARKs single mutant and double mutants had a higher germination rate. The cotyledon greening rates of double mutants also showed similar results. These results indicated that CARKs play a positive regulatory role in the ABAmediated germination and seedling growth in Arabidopsis. And the members of the CARK family showed redundant roles in ABA signaling.