Journal of Northeastern University(Natural Science)

Information Fusion Based Abnormal Condition Levels Recognition of Smelting in Fused Magnesium Furnace

LI Hong-ru， WANG Yi-wen， DENG Jing-chuan

2020, 41 (2): 153-157. DOI: 10.12068/j.issn.1005-3026.2020.02.001

Abstract ( 729 )

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A method of recognizing abnormal condition levels during heating and melting process of fused magnesium furnace utilizing multi-source information fusion is proposed. Current， image and sound signal features are extracted to be serialized and normalized under the premise of analyzing abnormal condition degrees during heating and melting process. Different features are selected according to the characteristics of various anomalies. The models for recognizing mild semi-melting and severe overheating conditions based on support vector machine， for moderate and severe semi-melting conditions based on rule reasoning， and for mild and moderate overheating conditions based on decision tree support vector machine， are established， respectively. The simulation results show that the proposed method can effectively recognize the abnormal condition levels of semi-melting and overheating conditions.

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Modelling of Gene Regulatory Networks by Parent Node Screening-Based Bayesian Method

QU Lu-xuan， GUO Shang-hui， WANG Zhi-qiong， XIN Jun-chang

2020, 41 (2): 158-162. DOI: 10.12068/j.issn.1005-3026.2020.02.002

Abstract ( 651 )

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Among the methods for modeling gene regulation networks， Bayesian network model can intuitively express the regulatory relationship between genes. However， due to the high complexity of Bayesian network model in the structure learning， the efficiency of the gene regulation networks modeling is low and the scale of the reconstructed network is limited. Therefore， this paper proposed a method which is called the parent node screening-based Bayesian network(PS-BN). The PS-BN method combines the correlation model with Bayesian network model. Under the premise of making full use of the search strategy of structure learning in Bayesian network model， the parent node screening method is used to remove some redundant nodes， thus reducing the search space. The experimental results show that compared with the Bayesian network model， the PS-BN method greatly improves the efficiency of modeling gene regulatory networks while improving the accuracy.

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Improved Coral Reef Algorithm

KONG Zhi， LI Shi-cheng， ZHAO Jie

2020, 41 (2): 163-169. DOI: 10.12068/j.issn.1005-3026.2020.02.003

Abstract ( 700 )

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The coral reef algorithm has the disadvantages of being easy to fall into local optimum and low precision. In view of the shortcomings of coral reef algorithm， this paper proposes an improved coral reef algorithm. By referring to particle swarm optimization， Gaussian mutation and simulated annealing algorithm， this algorithm improves the broadcast spawning， asexual reproduction and setting(replacement)mechanisms of coral reef algorithm， which greatly improves the optimization precision of the algorithm and can jump out of the local optimum. In the simulation experiment， the improved coral reef algorithm is respectively compared with ten algorithms such as basic coral reef algorithm and particle swarm algorithm in high-dimensional and low-dimensional test functions. The experimental results show that the improved coral reef algorithm has better convergence rate and accuracy than other algorithms， which can still be maintained in the high-dimensional test functions.

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Modified Grasshopper Optimization Algorithm and Applications in Optimal Dispatch of Electric Vehicle Battery Swapping Station

WANG Sheng-sheng， ZHANG Wei， DONG Ru-yi， LI Wen-hui

2020, 41 (2): 170-175. DOI: 10.12068/j.issn.1005-3026.2020.02.004

Abstract ( 631 )

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The dispatch of electric vehicle battery swapping station is usually optimized by swarm intelligence algorithms. However， the existing algorithms are easily trapped in local optimum and premature convergence. Thus， an improved grasshopper optimization algorithm(IGOA)is proposed to achieve optimal dispatch. In the IGOA， the boundary bounce strategy is adopted to improve the efficiency; the sine/cosine algorithm is introduced to enhance the global searching ability; the Lévy flight is applied to perturb the particles randomly to keep the algorithm from being trapped in local optimum; the nonlinear operation is used to accelerate the convergence rate at the later stage of the algorithm. The simulation results show that the IGOA outperforms GOA and several other swarm intelligence algorithms as to the optimal dispatch of electric vehicle battery swapping station.

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Algorithm for Structure Design of RBF Neural Network Based on Parameter Optimization

ZHAI Ying-ying， ZUO Li， ZHANG En-de

2020, 41 (2): 176-182. DOI: 10.12068/j.issn.1005-3026.2020.02.005

Abstract ( 904 )

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An algorithm based on parameter optimization(KV-RBF)is proposed for optimizing RBF(radial basis function) neural network structure. Firstly， the K-means++ algorithm， which makes the clustering algorithm more accurate， is improved to find an appropriate initial center for the hidden layer node of RBF neural network. Then， considering the influence of data distribution and scaling factor selection， the width of neuron basis function in the hidden layer is calculated by variance measurement. Finally， the network parameters are modified to improve the nonlinear approximation ability of the network. The experimental results show that the proposed RBF neural network based on parameter optimization has good approximation effect and generalization ability.

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Retinal Vessel Segmentation Algorithm Based on Orientation Scores and Frangi Filter

SHE Li-huang， GUO Yi-rong， ZHANG Shi

2020, 41 (2): 182-187. DOI: 10.12068/j.issn.1005-3026.2020.02.006

Abstract ( 929 )

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This paper proposes an algorithm based on orientation scores combined with Frangi filter to fix the difficulties caused by bifurcation and crossings of retinal vessels. The Frangi filter， which is constructed by Hessian matrix and suitable for filtering the linear object， is used to enhance the contrast of the blood vessels.The anisotropy and orthogonality of the cake wavelet in the orientation scores are used to filter the blood vessels in multiple angles and directions， which is beneficial to the processing of details and the complete segmentation of the retinal vascular network. The comparison of the method proposed with other existing methods shows that the algorithm is better than other algorithms in processing the bifurcation and crossings， and the measurements of accuracy， sensitivity and specificity are superior to existing algorithms.

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A Comparative Study of Aortic Pressure Wave Reconstructed from Different Peripheral Arterial Pressure Waves

XU Li-sheng， SONG Dai-yuan， LIU Wen-yan， WANG Yu-fan

2020, 41 (2): 188-192. DOI: 10.12068/j.issn.1005-3026.2020.02.007

Abstract ( 584 )

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Central aortic pressure wave(CAPW)can be reconstructed by different peripheral artery pressure waves(PAPW)non-invasively using blind system identification technology， but the selection of peripheral arteries remains a serious problem. In this paper， an aortic pressure wave reconstruction algorithm based on subspace method has been used. Radial pressure waves and dorsal pedal artery pressure waves are collected for reconstruction. The aortic pressure wave is reconstructed dynamically through four different combinations， and the results are assessed by dynamic time warping.The optimal combination of peripheral arterial waves is also determined.The results show that any combination of the dorsal and radial arteries pressure wave has no significant effect on the reconstruction of aortic pressure wave(P>0.5). However，the reconstruction cannot be achieved by only using the radial pressure waves or the dorsal pedal pressure waves.

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Breast Cancer Related LVI Status Prediction Based on Active Contour Model and Radiomics

FENG Bao， LI Chang-lin， LI Zhi， LIU Zhuang-sheng

2020, 41 (2): 193-199. DOI: 10.12068/j.issn.1005-3026.2020.02.008

Abstract ( 884 )

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To predict preoperative lymphovascular invasion(LVI)status of breast cancer patients， a computer-aided analysis method which combines an active contour model and radiomics is proposed. First， the image from dynamic contrast enhanced magnetic resonance imaging(DCE-MRI)of breast cancer is segmented by an active contour model(ACM)based on post probability and fuzzy velocity function. By constructing the region term of the active contour model based on post probability in the wavelet domain and the edge stop term of the active contour model by using the fuzzy velocity function， the accuracy of breast cancer lesion segmentation can be improved. Second， the image features such as morphology， grayscale and texture are extracted. Finally， a model for predicting LVI status is developed by the random forest classifier and its predictive ability is verified by experimental results.

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Effect of Crucible Material on Inclusions in 55SiCr Spring Steel

LI Yang， CHEN Chang-yong， QIN Guo-qing， JIANG Zhou-hua

2020, 41 (2): 200-207. DOI: 10.12068/j.issn.1005-3026.2020.02.009

Abstract ( 588 )

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The effects of MgO and MgO-CaO refractories on inclusions in 55SiCr spring steel were studied in a MoSi₂ furnace. The results indicate that both MgO and MgO-CaO crucibles can adjust the composition of the steel within the aiming range. Moreover， compared with MgO crucible， MgO-CaO crucible is more effective in purifying the molten steel， in which the contents of P， S，［Al］_s and T.O in 55SiCr spring steel smelted by MgO-CaO crucible are reduced to 56×10^-6， 10×10^-6， ≤5×10^-6 and 4×10^-6， respectively. The average diameter of inclusions in steel decreases from 1.376μm to 1.222μm， and the ratio of the inclusions with the size <2μm increased from 79% to 89%. This is mainly because the MgO-CaO crucible has not only the functions of dephosphorization， desulfurization and deoxidization， but also CaO reacts with Al₂O₃ inclusions in steel to form hybrid inclusions with lower melting point， which is easier to float and remove， so that the molten steel is further purified.

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Experimental Study on Welding of Q345B/HG785D Steel Plates in Crane Frame

QI Peng-yuan， LIU Jia-qi， WANG Gang， LIU Xiang-hua

2020, 41 (2): 208-212. DOI: 10.12068/j.issn.1005-3026.2020.02.010

Abstract ( 737 )

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Taking butt welding of dissimilar steel plates of Q345B and HG785D as the object， we studied the welding defects， mechanical properties and microstructures of the welded joint by metal active gas(MAG)arc welding under different heat input conditions. It is found that the strength of the welded joint can be improved effectively by reducing welding current in butt welding of dissimilar steel ends. When the joint is preheated before welding and slowly cool down after welding， the quenched hard area in the microstructure is reduced and the toughness of heat affected zone(HAZ)is increased. Under the heat input conditions of 140-200A welding current， 22-24V welding voltage and 28cm/min welding speed， the mechanical and bending properties of the welded joint can be optimized by the process of preheating and post-heat welding. The optimized welding process can inhibit the weld cracking effectively in crane frame.

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Experimental Study on Granulation of Blast Furnace Slag by Gas Quenching

KANG Yue， LIU Chao， ZHANG Yu-zhu， JIANG Mao-fa

2020, 41 (2): 212-216. DOI: 10.12068/j.issn.1005-3026.2020.02.011

Abstract ( 668 )

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To effectively utilize waste heat from blast furnace slag(BFS)and increase the additional value of slag， the BFS is granulated using the dry treatment(gas quenching) method. The effects of basicity and nozzle pressure on bead formation rate， mean diameter and particle size distribution of slag beads are studied. The results show that with the increases of basicity， the bead formation rate firstly increases up to the highest rate at the basicity of 1.2 and then decreases. The mean diameter firstly decreases and then increases with the basicity， especially， when the basicity is over 1.2. With the nozzle pressure increasing， the bead formation rate firstly increases， followed by a drop and then raise again. The bead formation rate reaches the highest value at the pressure of 0.2MPa. The mean diameter of the slag beads decreases gradually and the decreasing tendency slows down when the pressure is larger than 0.3MPa. The particle size distribution of slag beads mainly ranges in 1~2.5mm， satisfying the Gaussian distribution basically.

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Dynamic Reliability Analysis of Torque Shaft in Cutting Part of Coal Mining Machines

YANG Zhou， JIANG Chao， ZHANG Yi-min， JIANG Hong-meng

2020, 41 (2): 217-222. DOI: 10.12068/j.issn.1005-3026.2020.02.012

Abstract ( 572 )

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The Workbench software was used to establish a parametric finite element model of the torque shaft. Through modal analysis and comparison with the transfer matrix method， the first six orders of natural frequency and corresponding limit speed were obtained to verify the rationality of the structure and speed design. The harmonic response analysis illustrated that resonance invalidation should consider the first natural frequency. In addition， the response surface design and Latin superpower square sampling methods were used to realize the sampling analysis of the structure and material parameters. The BP neural network technology was used to fit the functions of first order natural frequency， solving the reliability sensitivity of each random parameter. The first order second moment and Monte-Carlo simulation were used to calculate the reliability at a specific speed and to find out the biggest influencing factor on the dynamic reliability， thus laying a foundation for the robust optimization design of shaft.

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Reliability Analysis Based on Active Learning for Complex Mechanical Structure

CAO Ru-nan， SUN Zhi-li， ZHANG Yi-bo， WANG Jian

2020, 41 (2): 223-228. DOI: 10.12068/j.issn.1005-3026.2020.02.013

Abstract ( 600 )

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In order to advance the efficiency for analyzing the reliability of complex mechanical structure， a new adaptive learning method(AK-MCS-K)， which combines adaptive learning function VF with k-means clustering， is proposed. The AK-MCS-K method balances the precision of failure probability estimation and computational efficiency. It can realize parallel computation， that is， several samples can be simulated simultaneously at every iteration on a few computers. When evaluating the reliability of complex structures with time-consuming and implicit function， reducing iterations can effectively save time and improve computational efficiency. Compared with others， the AK-MCS-K method can reduce the number of iterations significantly with higher computational efficiency under the condition of satisfying the precision. Finally， the new method is used for analyzing the reliability of the motion accuracy of a simplified model of a rigid-flexible coupling artillery coordinator.

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A Reliability Analysis Method Based on Relative Error Estimation of Failure Probability

ZHANG Yi-bo， SUN Zhi-li， YAN Yu-tao， WANG Jian

2020, 41 (2): 229-234. DOI: 10.12068/j.issn.1005-3026.2020.02.014

Abstract ( 662 )

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To analyze the reliability of complex mechanical structures more efficiently， an innovative adaptive analysis method is proposed based on the Kriging model and the relative error estimation of failure probability. The range of the number of actual failure samples in the region where the signs of samples are uncertain is derived using the normal distribution that approximates to the Poisson binomial distribution. The lower limit of the range is redefined by introducing a scale factor to ensure that the number of actual failure samples can accurately fall within the range. Then， a more accurate estimation of relative error of failure probability is provided. The adaptive design of experiments is implemented by the learning function U. Two examples are employed to verify the accuracy， generality and efficiency of the presented relative error estimation of failure probability and the adaptive analysis method. The results indicate that the as-introduced approach can not only accurately estimate the relative error of failure probability， but also significantly decrease the calls to performance function.

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Damage Location of Fiber-Reinforced Composites Based on Lumped Mass Approach

LI Hui， XU Zhong-hao， WANG Dong-sheng， ZU Xu-dong

2020, 41 (2): 234-240. DOI: 10.12068/j.issn.1005-3026.2020.02.015

Abstract ( 533 )

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A method for locating the damage of fiber-reinforced composites(FRCs) is studied， which is named as the ‘exponential approximation-lumped mass approach’. Firstly， a lumped mass model is established for a FRCs beam structure. Then， the stiffness matrix of the undamaged beam is obtained by theoretical calculation， and the residual force vector of the beam with damage is determined as the key locating index based on the measured natural frequencies and the regularized modal shape data. Furthermore， a criterion is proposed for approximating the position of damage， so that a set of standard procedures for the damage locating can be determined. Finally， a T300 carbon fiber/resin composite beam with different fiber breakage damages is studied as a case and it is found that the as-proposed damage locating approach can effectively identify the damage positions of the composite beam.

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Blank Holder Force Prediction of Tailor Welded Blank Based on Neural Network Optimized by Genetic Algorithm

ZHANG Hua-wei， ZHENG Xiao-tao

2020, 41 (2): 241-245. DOI: 10.12068/j.issn.1005-3026.2020.02.016

Abstract ( 581 )

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Numerical simulation and neural network technology were used for the blank holder force(BHF) prediction of tailor welded blank(TWB) box part in deep drawing. The influence of BHF loading type on the formability of TWB box part was analyzed by numerical simulation， and a preferable BHF loading type was obtained. Then BP neural network model suitable for BHF prediction was developed. At last， the neural network model was optimized by the genetic algorithm. The elitism strategy was introduced into the course of gene selection， and finally an ideal BHF curve was obtained by the neural network model optimized by the genetic algorithm， which can predict BHF value varying in deep drawing process and can lay the technical foundation for intelligent stamping.

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Grinding Mechanism and Surface Roughness of FeCoNiCrMo High-Entropy Alloy

WEN Xue-long， YU Xing-chen， GONG Ya-dong， MENG Fan-tao

2020, 41 (2): 246-251. DOI: 10.12068/j.issn.1005-3026.2020.02.017

Abstract ( 731 )

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The surface grinding experiment of FeCoNiCrMo high-entropy alloy was conducted to analyze the grinding mechanism and influence of grinding parameters on the surface roughness and morphology of the alloy. The surface morphology of the specimens ground with different grinding wheels and the surface roughness of the specimens under dry and wet grinding conditions were investigated. The experiment results show that grinding FeCoNiCrMo follows the removal mechanism of plastic material. As the grinding speed increases and the feed rate and grinding depth decrease， the surface roughness of the specimens decreases and their surface morphology is smoother. The surface roughness of the specimens ground with the resin bond grinding wheel is lower and their surface morphology is better， compared with the ones ground with the electroplated grinding wheel. The surface roughness is significantly lower and the surface quality is better under the condition of wet grinding than that under the condition of dry grinding.

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Research on Grinding Process Performance of 2.5D C_f/SiC

QU Shuo-shuo， GONG Ya-dong， YANG Yu-ying， SHE Yue-bin

2020, 41 (2): 252-257. DOI: 10.12068/j.issn.1005-3026.2020.02.018

Abstract ( 558 )

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To study the grinding process performance of 2.5D C_f/SiC composites， single factor tests were designed and executed. The results show that grinding depth， wheel speed and feed speed have prominent influence on the processing performance evaluation parameters， including surface topography， surface roughness and grinding force. It also implies that the grinding depth is the maximal influence factor， while feed speed is the minimal one. Due to difference of supporting effects of the warp fiber and weft fiber， the defect forms on the machined surface are different. The mainly surface defects of 2.5D C_f/SiC contain interfacial debonding， crack， fiber outcrop and pullout. In addition， different grinding chips would be produced with different grinding parameters and fiber orientations. According to the experimental results， the grinding mechanism of 2.5D C_f/SiC was researched in detail， which supplies significantly technical support for investigation on the grinding theory of 2.5D C_f/SiC.

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Multi-objective Scheduling Algorithm for Mixed-Model Assembly Line Considering Energy Consumption

ZHOU Bing-hai， FEI Qian-ran

2020, 41 (2): 258-264. DOI: 10.12068/j.issn.1005-3026.2020.02.019

Abstract ( 550 )

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To improve the energy efficiency of parts feeding in mixed-model assembly line， mobile robots with “transfer” strategy and line-integrated supermarkets are considered， and parts feeding models with recharge situation are introduced. Combined with the energy consumption characteristics of robots， mathematical programming formulations are given with the aim to minimize the robots group scale and total energy consumption. On this basis， a modified multi-objective discrete differential evolutionary algorithm with variable neighborhood strategy is developed， where a nearest-neighbor heuristics constructs the initial solution and a variable neighborhood strategy as a local search procedure improves the quality of solutions generated. Finally， the feasibility and effectiveness of the as-proposed algorithm is validated by simulation results.

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Simulated Remediation for Cr(Ⅵ) Pollution with Sucrose-Modified Nanoscale Zero Valent Iron

CUI Jian， WANG En-de， ZHOU Rui， WANG Chang-qi

2020, 41 (2): 265-269. DOI: 10.12068/j.issn.1005-3026.2020.02.020

Abstract ( 521 )

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In order to observe whether an in-situ reactive zone is formed and study the remediation efficiency for high concentration of Cr(Ⅵ) pollution， the in-situ reactive zone of modified nanosale zero valent iron was created in a two-dimensional simulation trough. The results of simulated experiments showed that a large amount of sucrose-modified nano-iron slurry is injected to form an effective reaction zone in the Cr(Ⅵ) pollution halo. The recovery efficiency of the reaction zone for high concentration of Cr(Ⅵ) is the best in the first 30 minutes， and the Cr(Ⅵ) removing efficiency is 91%. The removal rate remains at 60% stably after 4 hours to 187 hours of the reaction， with a large area of effective repair area formed. The Cr(Ⅵ) in the reaction zone is reduced by Cr(Ⅲ)， and the formed Cr(Ⅲ) may naturally form a precipitate in a neutral or alkaline environment.

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Effects of LMWOAs of Iris Pseudacorus L. Rhizosphere on Ammonia Nitrogen Adsorption of Soil

LI Hai-bo， ZHAO Xiao-ming， LI Ying-hua， CHEN Xi

2020, 41 (2): 269-274. DOI: 10.12068/j.issn.1005-3026.2020.02.021

Abstract ( 578 )

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Low molecular weight organic acid(LMWOA) of rhizosphere is a kind of active allelochemical， which has such important ecological functions as promoting the migration， transformation and accumulation of pollutants. The GC-MS technology was applied to analyze the composition characteristics and relative content of the rhizosphere metabolites of Iris Pseudacorus L.. The simulation experiments were carried out to reveal the thermo-dynamic effects of the LMWOA on the soil adsorption of ammonia nitrogen. The results showed that different types of LMWOAs could promote the adsorption of ammonia nitrogen， but the degree of action is different. The adsorption kinetics of ammonia nitrogen of soil matches the Elovich equation and the double constant equation， and the isothermal adsorption complies with the characteristics of the Langmuir and Freundlich equations. Its bond energy constant K_L is significantly correlated with the organic acid dissociation constant pKa， and the mechanism of LMWOA regulation of soil adsorption of ammonia nitrogen is mainly the activation of organic matters.

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Process Mineralogical Characteristics and Ore Value of Typical Vanadium Titanium Magnetite in China

YU Hong-dong， WANG Li-na， QU Jing-kui， QI Tao

2020, 41 (2): 275-281. DOI: 10.12068/j.issn.1005-3026.2020.02.022

Abstract ( 1385 )

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The process mineralogy of vanadium-titanium magnetite from Panzhihua， Chengde and Chaoyang is studied， and the value of the ore is calculated according to the spot price of iron concentrate， titanium concentrate and the theoretical mineral processing index. The results show that the grade of magnetic iron is 13.26%， 12.84% and 1.15%， the grade of TiO₂ is 10.98%， 4.53% and 2.02%， and the grade of V₂O₅ is 0.22%， 0.23% and 0.055%， respectively， in vanadium- titanomagnetite from Panzhihua， Chengde and Chaoyang. The mineral contents and mineral compositions of titanomagnetite and ilmenite in vanadium-titanomagnetite of different mineral areas are significantly different. The grade of iron is 59.21%， 66.46% and 55.74%， the grade of TiO₂ is 12.35%， 4.87% and 16.42%， and the grade of V₂O₅ is 0.928%， 1.142% and 2.07%， respectively， in iron concentrates from Panzhihua， Chengde and Chaoyang. Panzhihua ore has the highest value， followed by Chengde， while Chaoyang ore is the lowest.

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Evolution Law of Elastic Modulus of Sandstone with Double Fissures Under Cyclic Loading

WANG Shu-hong， WANG Zi-he， WANG Kai-yi， ZHUANG Xian-peng

2020, 41 (2): 282-286. DOI: 10.12068/j.issn.1005-3026.2020.02.023

Abstract ( 602 )

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According to the uniaxial cyclic loading and unloading test results of sandstone with precast fissures， the effects of fracture geometric parameters on elastic modulus of specimens were investigated. Using PFC^2D code， the relationship between crack development status and elastic modulus of specimens was analyzed. The research results show that: with the increase of cycle numbers， the elastic modulus of most specimens shows a strengthening phenomenon， and the first loading/unloading cycle has the most significant strengthening effect on the elastic modulus， which is related to the internal meso-structure; while the elastic modulus of a few specimens shows a weakening phenomenon; and combining with the PFC^2D code simulation， the weakening phenomenon is closely related to the crack development status.

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Fire Characteristics of Thermal Insulation Material XPS Under Ventilation Environment

SHANG Rong-xue， ZOU Bin， ZHANG Pei-hong， HAO Yu-jun

2020, 41 (2): 287-293. DOI: 10.12068/j.issn.1005-3026.2020.02.024

Abstract ( 651 )

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The fire behavior， ignition characteristics and smoke characteristics of XPS(extruded polystyrene) were studied experimentally with various distances and locations of the fire source under the mechanical ventilation velocities of 0， 0.6 and 1.2m/s. The experimental results showed that the flame spreading speed on the surface of XPS gradually increased and coking appeared earlier with the increase of wind speed. The XPS ignition time were nearly linearly related to the fire source distances under the same ventilation velocity and fire source location. The maximum ignition distance of XPS decreased from 0.2 m to 0.15 m with the increase of ventilation velocity from 0.6m/s to 1.2m/s when the fire source was perpendicular to the wall. In addition， the maximum temperature of smoke and the minimum variation of the concentrations of oxygen， carbon dioxide， and carbon monoxide were obtained when the ventilation velocity reached to 0.6m/s. Therefore， the XPS burning rate increased first and then decreased with the growth of ventilation velocity. When the ventilation velocity was low， the increase of oxygen concentration promoted the XPS combustion. The thermal inhibitory influence of new air on the XPS combustion was enhanced significantly with the further increase of the ventilation velocity， thus the XPS combustion rate reduced.

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Optimization Decision for Retailer-Dominant Pre-sale Supply Chain Financing

SUN Jing-ze， ZHUANG Xin-tian

2020, 41 (2): 294-299. DOI: 10.12068/j.issn.1005-3026.2020.02.025

Abstract ( 539 )

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Focusing on the phenomenon that retailers often face the shortage of capital in the supply chain， the optimization decision for retailer-dominant pre-sale supply chain financing was studied， based on the two typical financing modes of commercial loan and commercial buyback. Firstly， a model of three-level supply chain composed of a supplier， a dominant retailer and a bank was established. Secondly， the optimization decision and the optimal profit of supply chain members under the two modes were obtained. Finally， through numerical example calculation， the advantages and disadvantages of the two financing modes were compared from the perspective of banks， suppliers and retailers to gain corresponding managerial insights， which may provide scientific support for the optimization decision of supply chain members.

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Empirical Study on the Relationship and Influence Channel Between Stock Liquidity and Stock Price Crash Risk

HOU Yu-ting， JIN Xiu

2020, 41 (2): 300-304. DOI: 10.12068/j.issn.1005-3026.2020.02.026

Abstract ( 615 )

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Based on Governance Theory and Short-termism theory， the fixed effect model was adopted to analyze the panel data of A-share non-financial listed companies from 2007 to 2016， study the relationship between stock liquidity and stock price crash risk， and further analyze the channel of stock liquidity affecting stock price crash risk. The results show that stock liquidity has a significantly positive correlation with crash risk， and proved that stock liquidity affects crash risk through the short-term institutional investor channel. The conclusions may provide valuable references for investors， listed companies and market regulators to understand stock price crash risk from a micro perspective.

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