bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diffusion MRI tractography for neurosurgery: the basics, current state, technical reliability and challenges
Authors: Yang Joseph Yuan-Mou , Yeh Chun-Hung , Poupon Cyril , Calamante Fernando 
Published: June 2021

Abstract
Diffusion magnetic resonance imaging (dMRI) tractography is currently the only imaging technique that allows for non-invasive delineation and visualisation of white matter (WM) tracts in vivo, prompting rapid advances in related fields of brain MRI research in recent years. One of its major clinical applications is for pre-surgical planning and intraoperative image guidance in neurosurgery, where knowledge about the location of WM tracts nearby the surgical target can be helpful to guide surgical resection and optimise post-surgical outcomes. Surgical injuries to these WM tracts can lead to permanent neurological and functional deficits, making the accuracy of tractography reconstructions paramount. The quality of dMRI tractography is influenced by many modifiable factors, ranging from MRI data acquisition through to the post-processing of tractography output, with the potential of error propagation based on decisions made at each and subsequent processing steps. Research over the last 25 years has significantly improved the anatomical accuracy of tractography. An updated review about tractography methodology in the context of neurosurgery is now timely given the thriving research activities in dMRI, to ensure more appropriate applications in the clinical neurosurgical realm. This article aims to review the dMRI physics, and tractography methodologies, highlighting recent advances to provide the key concepts of tractography-informed neurosurgery, with a focus on the general considerations, the current state of practice, technical challenges, potential advances, and future demands to this field.
Thoughts on Online Teaching of Employment Guidance Course for Civil Aviation Majors under the COVID-19 Epidemic--Based on the teaching practice of college students enrolled in 2018 in the Civil Aviation Management Institute of China
Authors: Ma Jing , Sun Liang , Zhang Tao 
Published: June 2021

Abstract
The employment situation in civil aviation has become more severe this year due to the adverse effects of the COVID-19 epidemic. The online teaching of employment guidance courses can promote high-quality employment for graduates, but also poses new challenges for teachers and students. For college students enrolled in 2018 majoring in civil aviation, the teachers in the Civil Aviation Management Institute of China accomplished the employment guidance course, adopting a teaching method combining online teaching with offline guidance, and applying the Deming cycle to continuously improve the course quality. To facilitate better employment of civil aviation graduates under the epidemic, this paper suggests that it is necessary to establish an employment guidance and service system, improve the comprehensive quality of graduates, promote cooperation and mutual assistance between schools and employers, and guide graduates to start their businesses or further study rationally.
Research on the Quality Evaluation for Training of Undergraduate Majoring in Logistics Management and Engineering Based on Improved TOPSIS Method
Authors: Nie Tongtong 
Published: June 2021

Abstract
In view of the Training Quality of Undergraduate Majoring in Logistics Management and Engineering, an improved TOPSIS method based on combinatorial weight is proposed to evaluate the training quality of undergraduate majoring in logistics management and engineering. Firstly, the paper studies and analyses the related literatures of training quality of undergraduate majoring in logistics management and engineering, and puts forward a set of evaluation of training quality indicator system for the undergraduate majoring in logistics management and engineering. Secondly, the objective weight and subjective weight of each indicator are determined by using the variable coefficient method based on mixed data and the improved AHP method based on triangular fuzzy number, and on this basis, the combined weight of each indicator is calculated by using the maximum method of comprehensive evaluation value. After that, the improved TOPSIS method is used to rank the training quality for undergraduate majoring in logistics management and engineering.
The effect of algorithm parameters on the number of iterations of the dual fat boundary method
Authors: Liu Kui , Hu Zhendong 
Published: June 2021

Abstract
The Dual Fat Boundary Method (DFBM) is an improvement of the Fat Boundary Method (FBM), which is proposed to solve elasticity problems defined on a perforated domain. The DFBM does not need an analytical solution in the holes, so it is suitable for any reasonable hole shapes and Dirichlet boundary conditions on the holes. However, as an iteration method, the relationship between iteration times and algorithmic parameters has not been studied. Here we give a numerical study by taking the perforated infinite plate problem as an example. It reveals that the relaxation parameters for two local domains should be equal to obtain the fastest convergence. Furthermore, the number of iterations for DFBM is smaller than FBM in the larger range of relaxation parameters despite of the decreasing range of convergence.
Impact of government subsidies on green supply chain operation under different power structures
Authors: Liu Liu , Zhang Hua 
Published: June 2021

Abstract
Government subsidies play an important role in the operations of a green supply chain. However, the effectiveness of these subsidies under different power structures has rarely been examined. In this paper, we investigate a two-echelon green supply chain with a manufacturer who obtains government subsidies to develop and produce green products and a retailer who sells to consumers. We examine the impact of government subsidies on green product innovation, supply chain profits, and social welfare by focusing on five power structure models: centralized decision (C), manufacturer-Stackelberg (MS), retailer-Stackelberg (RS), vertical Nash (NL), and vertical Nash with bargaining mechanism (NB) models. The results show that government subsidies have a positive impact on the energy-saving level of green products, firms’ financial performance, and supply chain profits. We also find that the NB model is the optimal power structure of decentralized decision scenarios in terms of green product innovation, supply chain profits, and social welfare. Our findings indicate that if supply chain members have equal power and bargaining mechanisms the effectiveness of government subsidies will be enhanced. This study provides new theoretical insights for green supply chain research by revealing the interplay between the power structure of the green supply chain and government subsidies.
Extraction and analysis of spatial divergence features of residence space
Authors: Sun Lishuang , Wu Xinyu , Xie Zhiwei , Wu Yifan 
Published: June 2021

Abstract
Reasonable planning of urban residential spaces is important for urban development. This article used the population spatial distribution data and house price data to extract and analyze the characteristics of urban residential space differentiation in Shenyang and Wuhan. The results showed that: (1) There was a phenomenon of residential space differentiation in Shenyang and Wuhan. Compared with Shenyang, the phenomenon of residential space differentiation in Wuhan was more serious;(2) The proportion of people living in low, medium and high housing price areas in Shenyang and Wuhan showed the primary form of olive structure. Research conclusions: Combined with the data of population spatial distribution and house price, the study of urban social space was conducive to building a fair, just and harmonious urban social space, which was valuable not only in theory but also in practice.
Spectral data processing based on maximum noise fraction
Authors: Guo Wentai , Ge Liangquan , Li Fei , Hu Chuanhao 
Published: June 2021

Abstract
The processing of gamma spectrum measurement data has always been an important step in data interpretation of the survey area. It includes the correction of radioactivity interference caused by non-measuring targets, the correction of effects caused by different heights or topography in the survey environment, the smoothness and denoising of the measurement spectrum, etc. The accuracy of each step will affect the final data resources. The interpretation of the materials results in inaccurate regional radioactivity assessment. Maximum noise separation transformation is a similar method to principal component transformation, which is used to reduce dimensionality and noise of data. This paper takes the noise reduction process of gamma spectrum data processing as the research direction, uses SPSS data processing software, combines with MATLAB to denoise the data, and uses the maximum noise separation transformation as the denoising method, applies it to denoise the spectral data, and uses the principal component analysis method and the maximum noise fraction method to denoise the same set of data separately. After analysis, it is concluded that the maximum noise fraction method is superior to principal component analysis when there is a large noise variance for a set of data.
Quantitative analysis of resident consumption structure in Sichuan Province
Authors: Zou Yonghong , Zhou Jun 
Published: June 2021

Abstract
Based on the data of residents' income and consumption from Sichuan Statistical Yearbook and China Statistical Yearbook from 2014 to 2018, this paper makes a descriptive analysis on the current situation of residents' consumption in Sichuan Province from three aspects: income expenditure comparison, Engel coefficient and the proportion of each consumption spending. Based on the income and consumption data of urban and rural residents in Sichuan Province, the consumption structure of urban and rural residents in Sichuan Province is analysed from two aspects of marginal propensity to consume and income elasticity of demand by using the results of ELES model. At last, the paper puts forward relevant suggestions from four aspects: exploring ways to increase residents' income, reducing residents' housing cost, strengthening infrastructure construction and improving rural medical insurance coverage.
Data study on influence of high altitude on dynamic performance of supercharged diesel engine
Authors: Dong Jihao , Cao Wen 
Published: June 2021

Abstract
In this paper, the dynamic performance of turbocharged diesel engine is studied comprehensively and systematically by using a high altitude diesel engine simulation test-bed to simulate different altitudes. The influence of altitude change on the dynamic performance of turbocharged diesel engine is analyzed, which provides an important basis for further improving and enhancing the performance of turbocharged diesel engine at high altitude.
Numerical study on penetration mode of steel with prefabricated double cracks
Authors: Zhou Weidong , Sun Ye 
Published: June 2021

Abstract
When a flat steel with double cracks fails, the stress fields between different cracks will interact. The area between the cracks, that is, the steel bridge area, will be penetrated. This paper embeds the strain strength criterion into the discrete element numerical simulation method, and uses the block discrete element software UDEC to simulate the crack propagation and penetration in the steel bridge region of the prefabricated double-crack flat steel sample. Numerical simulation results show that there are four basic penetration modes in the double-crack steel sample during compression: (1) Discontinuous mode, which is characterized by no penetration between cracks, and the two pre-crack tip wing cracks independently expand; (2) Shear penetration mode, which is characterized by shear cracks penetrating the steel bridge. The principal stress field and shear stress field are concentrated in the steel bridge area, but the shear stress plays a leading role in penetration; (3) Tensile penetration mode, its characteristics: In order to penetrate the steel bridge with tensile cracks, the principal stress field is highly concentrated accumulated and nucleated in the area of the steel bridge, and the steel bridge penetration is instantaneous; The process occurs after the peak intensity.
Theoretical study on limited slip principle of differential
Authors: Dong Jihao , Sun Ye 
Published: June 2021

Abstract
As one of the important assemblies of off-road vehicles, the anti-skid performance of differential is closely related to the passability of the whole vehicle. Based on the analysis of the power distribution characteristics of ordinary bevel gear differential, this paper studies the anti-slip principle of variable transmission ratio differential theoretically through mechanical analysis and working process analysis. The variation of adhesion coefficient between tire and pavement is analyzed, and the reasonable value of locking coefficient is obtained.
Research on the marine human resource development based on VAR model
Authors: Zhu Wanqing , Xiao Jianhua 
Published: June 2021

Abstract
This paper selects the data of China's marine human resources data from 1996 to 2016, and uses the VAR model to conduct an empirical analysis. Research shows that marine human resource development can promote the development of marine system, but mainly contributing to the marine scientific research investment, while the contribution of marine education investment is relatively small, resulting in insufficient supply of marine talents and affecting the positive development. Therefore, in order to promote the construction of a maritime power, corresponding suggestions are put forward.
Application of improved adaboost iteration in small sample for prediction of oral performance
Authors: Guan Hongmei 
Published: June 2021

Abstract
Adaboost as a kind of iterative algorithm, is a kind of important integrated learning technology, can be randomly surmised with slightly higher prediction accuracy than usingweak learning enhancement study for high prediction precision of apparatus, it’s is very difficult in strongly constructing learning, it provides an effective new way of thinking and new methods for the design of the learning algorithm. As a kind of algorithm framework, Boosting can be applied to almost all the popular machine learning algorithm to further improve forecasting precision of the original algorithm, and its application is very extensive and has a great influence. Based on Adaboost, 90 students’ oral English at a university as weak classifier samples, via the iterative calculation, get a high reliability of strong classifier, and it’s concluded that the prediction result with student can evaluate the prediction accuracy of the algorithm for results compared with the actual results.
Construction of evolutionary game model between actors and governance system in forest operation
Authors: Wang Guangju , Xie Renshan , Zhang Beibei , Yang Jianzhou 
Published: June 2021

Abstract
With the continuous development of evolutionary game theory, evolutionary game is widely used in various fields of society. This paper constructs the evolutionary game model of actors and governance system in forest resource operation and management, and analyzes the stability strategy of each break-even point of the game system. The results suggest that: (1) When the parameters meet the conditions C
5 > pC
4 + C
2
R + C
3 < pC
4, the evolutionary stability strategy of the game system is of (no protection, no regulation), which may lead to the continuous deterioration of forest resources; (2) When the parameters meet the conditions C
5 < pC
4 + C
2
R + C
3 > pC
4
C
5 < C
2, the evolutionary stability strategy of the game system is of (no protection, regulation), which is to strengthen the supervision mechanism and improve the consciousness of actors to protect forest resources; (3) When the conditions are satisfied C
5 < pC
4 + C
2
R + C
3 < pC
4, there is no evolutionary stability strategy in the game system.
Implementation of digital constant fraction timing based on field programmable gate array
Authors: Ding Wenwan , Hu Chuanhao , Cao Yang , Li Xuegang , Yue Tao , Zhao Kunling , Zhang Song , Zhang Wenbing , Gu Yi 
Published: June 2021

Abstract
Compared with analog circuits, FPGA(Field Programmable Gate Array) had the advantages of redevelopment and low cost. Compared with MCU, FPGA used hardware description language to construct the circuit, which had the advantages of simple structure and fast parallel operation speed. In this paper, the simulation of digital Constant Fraction Timing can be realized based on FPGA, and the feasibility and accuracy of the design can be proved by using the simulation waveform of Modelsim and the waveform can be captured by signaltap. Modelsim can verify the correctness of the timing between modules, and signaltap can verify the actual running effect of the program on the board.
Application of regression neural network and MIV algorithm in visual communication design
Authors: Zhu Wen 
Published: June 2021

Abstract
Regression neural network algorithm can continuously learn the characteristics of training samples, and it has good data tolerance, robustness and generalization ability, and has been widely used in all kinds of nonlinear regression problems. In this paper, a multi-input and single output neural network regression model is constructed. Through the weight training of a large number of experimental sample data characteristics, the nonlinear regression mapping relationship of multi parameter input is established, so as to realize the accurate prediction of the basic situation of cultural and creative enterprises, then to analyze the influence of cultural and creative enterprises on the visual communication design course. The result of the correlation coefficient of the two is 0.79. The average relative errors between the predicted results and the actual results are 9.167% and 9.63%, respectively, both of which are less than 12%. It shows that the regression neural network model constructed in this paper can accurately analyse and predict the data, and the error between the predicted value and the target output value of the network model meets the actual requirements. So it has good prediction accuracy and generalization performance.
Application of slack variable-optimized SVM on piano teaching reform
Authors: Li Tianjiao 
Published: June 2021

Abstract
The data mining task of the classification algorithm is mainly to classify the data and classify them into each known category. As a classification algorithm, SVM has many unique advantages in solving small sample, nonlinear and high-dimensional pattern recognition. Based on the advantages of the SVM algorithm, this paper optimizes the slack variables, establishes a teaching quality evaluation model, and takes 500 subjects of the questionnaire survey as data samples by comparing with a variety of classification methods to evluate, and the results show that the accuracy of the SVM model is 92.70%, which proves the effectiveness of the research model.
Hybrid binary quantization and BP network on action mechanism
Authors: Jiang Chenhui , Shangguan Zhiyang , He Huan , Zhang Jinglou , Ping Jing , Li Naiwei 
Published: June 2021

Abstract
BP neural network is a kind of artificial neural network, which is mainly used in function approximation, model recognition, classification and data compression. In the case of limited analysis ability of traditional research methods, BP neural network can overcome the problems of nonlinear relationship. In this paper, the improved BP neural network was used to predict the properties. The data processing of the properties, tastes and was carried out by binary quantization. The prediction results’ correct rate was 87.5%.
Research on the Development Strategy of TC/CP Based on MSE-CM-BP Neural Network
Authors: Yang Zihan 
Published: June 2021

Abstract
As a science dedicated to simulating human learning by computer, machine learning has the ability to improve itself through empirical learning in dealing with interdisciplinary data statistics and approximation. Among them, BP neural network has stable and good nonlinear optimization processing ability, and it can deal with complex big data from a statistical perspective in strategy development. Therefore, this paper collects the data of income and rural development and its related influencing factors from 2010 to 2019, establishes a BP neural network with mean square error as the convergence measure of the results, and evaluates the application effect of BP neural network with the development strategy and creative products. The relative error of the results is less than 12%, and the correlation coefficient between influencing factors and results is not less than 0.8547.
Density functional study on the interaction of Graphene-supported Nickel cluster with CO2 molecule
Authors: Pradana M R , Maulana A L , Prasetyo Y , Saputro A G , Agusta M K , Ginting L Y , Dipojono H K 
Published: June 2021

Abstract
We try to use small size Ni cluster supported on graphitic material as an alternative for CO 2 hydrogenation catalyst. As an initial step, we study the ability of the supported Ni 4 cluster to interact with CO 2 molecule by means of density functional theory-based calculations. We find that strong CO2 adsorption can only be formed on top of the Ni 4 cluster site. Due to the strong Ni 4-CO 2 interaction, the CO 2 molecule is always adsorbed with a bidentate adsorption configuration on the Ni 4 cluster. The graphene surface and Ni 4-graphene interface cannot accommodate CO 2 chemisorption due to the weak graphene-CO 2 interaction.
Using particle effective density to determine SMPS-based aerosol mass concentration: application to airborne carbon and titanium nanoparticles
Authors: Bau Sébastien , Oury Benoît , Matera Virginie , Simon Xavier 
Published: June 2021

Abstract
To avoid multiple instruments to be deployed in field measurement campaigns based on airborne nanoparticles characterization, this study aims at investigating the capability of a Scanning Mobility Particle Sizer (SMPS) to provide accurate data relative to the mass concentration. Two series of test nanoaerosols were produced using a spark-discharge generator equipped with carbon or titanium electrodes (modal number diameters between ~ 50 and ~ 170 nm). The mass concentration was monitored by means of a personal AM520 photometer operated in parallel with the SMPS and closed-face cassette sampling for further off-line analysis: gravimetric analysis, and chemical analysis (thermo-optical analysis for carbon, ICP-OES for titanium). For each operating condition, the average number size distribution stemming from the SMPS was converted into mass size distribution accounting for particle effective density and integrated over the whole range of particle diameters to determine the corresponding mass concentration. Results highlight correlations (R2 ~ 0.9) between SMPS-based and chemical analysis or gravimetric mass concentrations below 1 mg/m3, with relative discrepancies lower than ~ 15% and ~ 25%, respectively. The AM520 photometric response remains dependent on particle physical and light scattering properties, which differ with the test dust used for factory calibration.