bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pulp Stones: Diagnostic Significance in Early Diagnosis and Radiographic Correlation with Ischemic Heart Diseases
Authors: S. Nachiappan , Chandran Ajay , B. Swathika , S. Ganesan , A. Mahaprasad , Muddebihal Farahnaz , Nayyar Abhishek Singh 
Published: June 2021

Abstract
Context and Aim Sufficient evidence exists in the literature which indicates that patients with ischemic heart diseases (IHDs) show higher degree of pulp calcifications. The present study was, therefore, planned to estimate the prevalence of pulp stones in patients diagnosed with/or undergoing treatment for IHDs.
Materials and Methods The present study, which consisted of 300 subjects within the age range of 25 to 65 years, was divided into two groups: study group comprising 150 patients (113 males and 37 females) and 150 age- and sex-matched healthy controls. Pulp stones were imaged using bitewing radiographs and paralleling technique under standard conditions.
Statistical Analysis Used Statistical analysis was done using IBM SPSS Statistics for Windows version 21 (IBM Corp, Armonk, USA), while independent t-test and Chi-square test were done to check the prevalence of pulp stones in the study and control groups, based on gender-, arch-, region- and side-wise distribution. p < 0.05 was considered statistically significant.
Results The patients with IHDs exhibited 100% prevalence of pulp stones and the difference was found to be statistically significant, although there was a significant difference in the mean number of pulp stones observed in the study and control groups, with the study group revealing 2217 pulp stones as against 639 pulp stones observed in the control group (p < 0.001). Furthermore, maxillary arch and posterior teeth were predominantly affected in both the groups, although the difference was not found to be statistically significant.
Conclusions The findings of the present study suggested a positive correlation between pulp stones and IHDs, highlighting the significance of dental radiographic examination, which may have a possibility for an early detection of IHDs.
Shadows and rings of the Kehagias-Sfetsos black hole surrounded by thin disk accretion
Authors: Li Guo-Ping , He Ke-Jian 
Published: June 2021

Abstract
In this paper, under the illumination of thin disk accretion, we have employed the ray-tracing method to carefully investigate shadows and rings of the Kehagias-Sfetsos(KS) black hole in deformed Hořava-Lifshitz(HL) gravity.
The results show that the event horizon r+, the radius r_p and impact parameter bp of photon sphere are all decreased with the increase of the HL parameter ω, but the effective potential increases. And, it also turns out that the trajectories of light rays emitted from the north pole direction are defined as the direct emission, lensing ring and photon ring of KS black hole, on the basis of orbits n = ϕ/2π.
As black hole surrounded by thin disk accretion, we show that the corresponding transfer functions have their values increased with the parameter ω. More importantly, we also find that the direct emissions always dominate the total observed intensity, while lensing rings as a thin ring make a very small contribution and photon ring as a extremely narrow ring make a negligible contribution, for all three toy-model functions. In view of this, the results finally imply that shadows and rings as the observational appearance of KS black hole exhibit some obvious interesting features, which might be regarded as an effective way to distinguish black holes in HL gravity from the Schwarzschild black hole.
Teaching Pupils to Design Comparative Experiments with Web-Based Inquiry Unit During COVID-19 Pandemic: A Pilot Study
Authors: Chao Qing , Lu Tong , Zhao Xiaoyu , Peng Qingqing , Zhao Guoqing 
Published: June 2021

Abstract
The COVID-19 pandemic caused many students away from the classroom. Its affecting region was so large and the inquiry learning had to move to online from offline. Although many studies had investigated the effectiveness of web-based inquiry learning, few of them conducted that under the pandemic. The pandemic took many new characters into education, such as the demand for the Internet. Hence, we conducted the pre-posttest quasi-experiment to investigate the effectiveness of online science inquiry during the pandemic. Under the instruction of teachers online, 30 fifth-grade students (19 males and 11 females) in a Chinese city completed a web-based inquiry learning program in the Web-based Inquiry Science Environment (WISE) platform. The experimental design ability test (EDAT) was conducted before and after web-based inquiry learning as the pre-test and post-test. The students’ attitude to web-based inquiry learning was also measured. The results showed, different from the studies before, the students’ score on experimental design ability decreased after web-based inquiry learning, especially in Asking Questions and Making Hypotheses subscales of EDAT significantly. No significant gender difference was detected. The students showed not a high attitude toward web-based inquiry learning. The possible factors causing that results and implications were discussed.
Multi-UAV cooperative Route planning based on decision variables and improved genetic algorithm
Authors: Zhang Jie , Li Ningzhou , Zhang Danyu , Wei Xiaojuan , Zhang Xiaojuan 
Published: June 2021

Abstract
In order to reduce the threat cost of multi-UAV coordination, improve the effective flight time and the mission success rate, a path planning model was designed for the effectiveness and real-time performance of multi-UAV track coordination. In this paper, based on the path planning model under the condition of non-interference, the model of minimum cost flight path of multi-UAV based on time synergy is given, and a time-sequence-space coordination model is proposed to meet the requirements of electronic jamming, mission confusion and radar illumination. The decision variables of range and threat are introduced into the collaborative function of track cost, and by adjusting the cost functions and collaborative variables in real time, the path planning model was optimized for unmanned support aircraft in coordination with multiple unmanned aircraft mission, at the same time, the genetic algorithm is improved by combining the adaptive crossover rate and mutation rate, and the optimization of track collaborative solution process is realized. Finally, the effectiveness of track coordination model of multi-UAV based on decision variables and improved genetic algorithm is verified by semi-physical simulation.
Research on HR management based on RNN expectation theory
Authors: Fang Yayue 
Published: June 2021

Abstract
RNN convolutional neural network is an important part of deep learning algorithm. Compared with fully connected neural network, the biggest difference is that the hidden units are not independent of each other. Not only the hidden layer neurons are irrelated to each other, but also the state of the current hidden layer cells is affected by the historical input data. This feature enables it to extract the temporal relationship of temporal data structure. One of the current outputs of one sequence is also related to the previous output. The specific expression is that the network will memorize the information before and apply it to the calculation of current output, the nodes between hidden layers are no longer connected but connected. Moreover, the input of hidden layer includes not only the output of input layer but also the output of hidden layer at the last time. RNN neural network is widely used in natural language processing (NLP): machine translation, speech recognition, image description generation, text similarity calculation. The DAFDC-RNN model in this paper is verified by the financial and real estate industry data from 2019 to 2020, which shows that the model has excellent stability and sensitivity. Compared with CNN model, it increases by 34.3% and 24.9%. The advantages of data processing as follow: it can process a large number of time series data, the processing capacity of data set is large, it can process 1000 + data, and it has more data base for time series prediction. The disadvantage as follow: Compared with CNN model, the working time of CNN model is increased by 48%, but the model has strong stability and adaptability. Taking the data from 2019 to 2020 as the input of DAFDC-RNN time series forecasting model, the salary forecast of real estate and financial industry in 2021 is obtained. Based on this data, the industry expectation of Finance and real estate industry under human resource management under expectation theory is reduced.
Effect of Chinese industrial structure upgrading on household consumption structure: evidence from CHIP data
Authors: Wang Liping , Huang Lu 
Published: June 2021

Abstract
Based on the data of Chinese Household Income Project (CHIP) and 117 cities in 2007 and 2013, this paper analyzed the effect of industrial structure upgrading on household consumption structure by using the ordinary least square method and quantile regression method. The following conclusions were drawn. Firstly, the upgrading of industrial structure can significantly promote the upgrading of household consumption structure. Secondly, compared with the low-level consumption structure households, the industrial structure upgrading has a stronger impact on households with high-level consumption structure. With the increase of quantile level, the influence of industrial structure upgrading on the upgrading of residents' consumption structure can gradually increase. Therefore, the government should actively promote the supply-side reform and the upgrading of industrial structure, which would be conducive to the upgrading of consumption structure.
Research on master data recognition of TCM based on analytic hierarchy process
Authors: Sang Yuhui , Tian Shuanggui 
Published: June 2021

Abstract
With the rapid development of information technology in the field of medical and health, the requirement for information sharing was higher and higher. TCM plays an irreplaceable role in promoting health development. The information of TCM was represented by the construction, application and data sharing of information system, and faced complicated problems. Data environment, standardized data management requirements and data standards were very important. In the field of TCM, the main line was about "TCM information integration standardization, TCM standards into information", while the main data was taken as the basis of data standardization. This paper through the investigation and summary of the existing information system and data items, according to theoretical research of main data recognition by scholars, discussed the main data identification method by using analytic hierarchy process, and extracted the main data, so as to improve quality of data management and optimize data management environment.
Efficiency optimization strategy of LLC resonant converter based on Hybrid PWM and PFM digital control mode
Authors: Xun Hehui , Shen Hanxin , Chen Wenxiang 
Published: June 2021

Abstract
There is a problem that the overall efficiency of LLC resonant converter decreases due to large switching loss under light load, in order to solve it, an efficiency optimization strategy based on hybrid PWM and PFM digital control mode was proposed to improve the efficiency of LLC Resonant Converter in the full load range. In order to adapt to different loads, Boost LLC converter circuit topology was proposed. The former Boost circuit was controlled by pulse width modulation (PWM), and the latter LLC was controlled by pulse frequency modulation (PFM). Pulse width modulation (PWM) control of the front Boost circuit can improve the bus voltage of the rear LLC circuit and adapt to different loads. Under the pulse frequency modulation (PFM), the efficiency of the rear LLC resonant converter under light load can be further improved by adjusting the resonant frequency. The experimental results showed that the proposed digital control efficiency optimization method could enable the Boost LLC converter to achieve high efficiency in the whole load range, and the overall conversion efficiency was not less than 94%.
Study on open operation and compactness based on constructing rough set L-f topological space
Authors: Zhong Mantian 
Published: June 2021

Abstract
How to construct topological space in rough set and study its topological space open operation and compactness was presented. The rough set topological space was constructed by using the equivalence class and the rough set L – f topological space was constructed by using mapping, which is first established. To obtain the essential attributes of the constructed rough set L – f topological space, the following five techniques were used: the opening operation of the L – f topological space can be defined by using the inductive method, and it was proved that the L – f topological space by using deductive reasoning which satisfied the β – open operation, the correctness and open coverage of the topological space can be defined by using the set, and it was proved that the L – f topological space was β – correctness by using deductive reasoning at the same time. Furthermore, it was verified that the constructed rough set L – f topological space by using data was very effective. The theoretical results had important significance in the promote study the topological space of rough set.
Study on gamma spectrum wavelet noise reduction based on scintillation detector
Authors: Yu Yingchi , Ge Liangquan , Li Fei , Hu Chuanhao 
Published: June 2021

Abstract
Wavelet transform is a time-scale signal analysis method, which holds the characteristics of the same window size, arbitrary shape change and multi-resolution analysis. Most applications of wavelet transform need to be based on signal decomposition and reconstruction, that is, through the combination of low-pass and high-pass filters to achieve frequency division, the signal is decomposed into signal detail components and large-scale approximate components. In the measurement process of the original energy spectrum data, the denoting process plays a role in reducing the incidence of statistical fluctuations to a certain extent, which is of profound significance to improve the data accuracy. In this paper, wavelet transform is used as the theoretical basis to denoise the actual energy spectrum, at the same time based on the MATLAB platform, simulation of signal with noise, using the different parameters on the signal processing. Firstly, the signal-to-noise ratio (SNR) of the hard and soft thresholds to the signal processing under the same conditions was compared, and then the change of the SNR was observed when the number of decomposition layers was changed under the wavelet basis of db3 (soft threshold). The experimental results show that: 1) under the same conditions, the soft threshold method has higher SNR than hard threshold; 2) The number of decomposition layers and the elimination moment affect the signal-to-noise ratio and smoothness of the processed signal respectively, and when the number of decomposition layers is 7-8 layers, the signal-to-noise ratio is about 29, the signal processing effect is the best. This study has shown that Wavelet method is an effective way to process energy spectrum.
Analyzing agricultural ecological efficiency in Weihai City based on the SBM, STIRPAT and SLM models
Authors: Zhang Xiang , Zheng Xungang 
Published: June 2021

Abstract
The essay is to study the development of ecological agriculture in Weihai city. The super slack-based measurement (SBM) model was adopted to measure the agricultural ecological efficiency of Weihai City’s seven districts and counties from 2008 to 2018. Based on the stochastic impacts obtained by conducting a regression on the STIRPAT model, the spatial lag model (SLM) was applied to empirically analyze the factors influencing agricultural ecological efficiency and the corresponding mechanisms. Our findings indicate that, in their direct effects, the population density, proportion of the primary industry, urbanization rate, agricultural mechanization rate, and agricultural development scale were significantly positive. Meanwhile, the rural labor transfer, agricultural output value per capita, and industrialization rate were significantly negative, and the planting structure was not significant. Under the spatial spillover effects, the rural labor transfer and agricultural output value per capita were significantly positive. The proportion of the primary industry and agricultural development scale were significantly negative, while the population density, urbanization rate, industrialization rate, agricultural mechanization rate, and planting structure were less significant. The suggestions put forward are to increase the level of scale, promote research and development, and adjust the industrial structure. The innovation and contribution of this paper lies in the application of the STIRPAT and SLM models to study the issue of agricultural ecological efficiency.
AGV vehicle differential drive model
Authors: Yao Yi , Sun Ye 
Published: June 2021

Abstract
Based on the establishment and analysis of the position model and forward kinematics model of the AGV vehicle, this paper derives the motion trajectory and related motion parameters of the fixed standard wheel and the manipulated standard wheel, and analyzes the motion of the AGV vehicle based on the specific motion parameters, to obtain the constraint sum of the motion and rolling and sliding of the differential AGV vehicle, and the relationship between the wheel speed of the AGV vehicle.
Colliding bodies algorithm with adaptive parameter adjustment strategy
Authors: Yu Chun , Liu Hui , Liu Bing , Li Yong , Fan Jian 
Published: June 2021

Abstract
Colliding Bodies Optimization (CBO) is a new meta-heuristic algorithm that uses collisions between objects to move to a better position so that the solution tends to be an optimal solution. Aiming at the shortcomings of CBO algorithm's poor optimization accuracy and prone to evolutionary stagnation in the later stage of iterations, this paper proposes a new Colliding Bodies Optimization algorithm with adaptive adjustment strategy. Firstly, a set of initial solutions of colliding bodies are generated by the good-point set strategy to improve the stability of the algorithm solution. Secondly, we adjust the linear strategy of the control parameters to a nonlinear strategy and combine it with the fitness value to form an adaptive parameter adjustment strategy. Finally, in order to make the algorithm escape from the local optimal, a mutation operation is performed on the position of the object. In order to test the effectiveness of the proposed algorithm, experiments were conducted on 23 benchmark functions with it and the comparison algorithm. The experimental results show that the performance of the proposed algorithm is better than other experimental algorithms.
Numerical simulation research on crack propagation of plane steel
Authors: Zhou Weidong , Sun Ye 
Published: June 2021

AbstractThere are still two deficiencies in the study of crack propagation in plane steel. One is that there are few studies on the theory of crack cracking and the cracking criterion from the strain field at the crack tip; the other is that there are few studies using the block discrete element method to explore the crack propagation. In view of the above two points, this paper proposes a strain strength criterion to explain the extension of tensile cracks and shear cracks in steel. This strain strength criterion assumes: (1) Tensile cracks grow along the direction of the maximum principal strain. When the principal strainγreaches a critical value, the tensile cracks begin to grow; (2) Shear cracks grow in the direction of the most dangerous stress state. When the Mohr circle exceeds the Mohr Coulomb failure line, the shear crack starts to expand. In addition, this paper applies the strain strength criterion to the block discrete element method to simulate the macro-mechanical response characteristics of steel under load and the propagation and evolution process of cracks. It is shown (1) the stress-strain curve appears elastic, stagnant, fluctuating, and falling back, etc. The basic law, and (2) the characteristics of stable and unstable growth of cracks during the whole loading process.
Evaluation and empirical analysis of the influence of disciplinary competition on innovation practice ability
Authors: Liu Zhang , Zhao Yiheng , Fang Guiying , Huang Yong 
Published: June 2021

Abstract
Mathematical modelling is an embodiment of the application of mathematics in various fields. Exploring the effect of mathematical modeling on the innovative practical ability of college students is conducive to college students’ understanding of mathematical modeling competitions and colleges’ education on mathematical modeling courses. It can also stimulate the confidence of students majoring in mathematics in their majors. On the basis of clarifying the theoretical basis and basic principles of the evaluation of innovative practical ability, this paper combines the characteristics of current college students to construct a college student’s innovation that includes 5 first-level indicators and 15 second-level indicators. Practice system. By the Delphi method and improved analytic hierarchy process we can determine the index weights and the weighted average model of fuzzy mathematics to analyze the collected evaluation membership matrix. We also obtain the membership matrix of the impact of mathematical modeling on the innovative practical ability of college students. Using the principle of maximum membership to get the degree of influence

V
3
*

=
0.3941

, the research results show that the mathematical modeling competition can improve the innovative and practical ability of college students.
Application of hybrid model of big data and BP network on strategy prediction
Authors: Qin Tengteng 
Published: June 2021

Abstract
Big data refers to the data set that cannot be captured, managed and processed by conventional software tools within a certain period of time. It is a massive, high growth rate and diversified information asset that needs new processing mode to have stronger decision-making power, insight and process optimization ability. BP neural network can be applied to the prediction of models and the study of the relationship between different models. Therefore, the combination of big data technology and BP neural network can deal with large and complex nonlinear structural problems from a statistical point of view, and with high stability and accuracy. This paper collects a cloud computing revenue from 2015 to 2019, and analyzes the impact of strategy mode value by using the combination of big data and BP neural network. The conclusion is that the correlation coefficient is 0.99762, which proves that big data combined with BP neural network can make accurate and effective decision prediction.