bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detecting the relativistic bispectrum in 21cm intensity maps
Authors: Jolicoeur Sheean , Maartens Roy , De Weerd Eline M. , Umeh Obinna , Clarkson Chris , Camera Stefano 
Published: June 2021

Abstract
We investigate the detectability of leading-order relativistic effects in the bispectrum of future 21cm intensity mapping surveys. The relativistic signal arises from Doppler and other line-of-sight effects in redshift space. In the power spectrum of a single tracer, these effects are suppressed by a factor
ℋ2/k2. By contrast, in the bispectrum the relativistic signal couples to short-scale modes, leading to
an imaginary contribution that scales as
ℋ/k, thus increasing the possibility of detection.
Previous work has shown that this relativistic signal is detectable in a Stage IV Hα galaxy survey.
We show that the signal is also detectable by next-generation 21cm intensity maps, but typically with a lower signal-to-noise, due to foreground and telescope beam effects.
A study of beam ion and deuterium–deuterium fusion-born triton transports due to energetic particle-driven magnetohydrodynamic instability in the large helical device deuterium plasmas
Authors: Ogawa K. , Isobe M. , Nuga H. , Kamio S. , Fujiwara Y. , Kobayashi M.I. , Sangaroon S. , Takada E. , Seki R. , Yamaguchi H. , Murakami S. , Jo J. , Osakabe M. 
Published: June 2021

Abstract
Understanding energetic particle transport due to magnetohydrodynamic instabilities excited by energetic particles is essential to apprehend alpha particle confinement in a fusion burning plasma. In the large helical device (LHD), beam ion and deuterium–deuterium fusion-born triton transport due to resistive interchange mode destabilized by helically-trapped energetic ions (EIC) are studied employing comprehensive neutron diagnostics, such as the neutron flux monitor and a newly developed scintillating fiber detector characterized by high detection efficiency. Beam ion transport due to EIC is studied in deuterium plasmas with full deuterium or hydrogen/deuterium beam injections. The total neutron emission rate (S
n) measurement indicates that EIC induces about a 6% loss of passing transit beam ions and a 60% loss of helically-trapped ions. The loss rate of helically-trapped ions, which drive EIC, is larger than the loss rate of passing transit beam ions. Furthermore, the drop of S
n increasing linearly with the EIC amplitude shows that barely confined beam ions existing near the confinement-loss boundary are lost due to EIC. In full deuterium conditions, a study of deuterium–deuterium fusion-born triton transport due to EIC is performed by time-resolved measurement of total secondary deuterium–tritium neutron emission rate (S
n_DT). Drop of S
n_DT increases substantially with EIC amplitude to the third power and reaches up to 30%. The relation shows that not only tritons confined in confined-loss boundary, but also tritons confined in the inner region of a plasma, are substantially transported.
Based on “MOOC + SPOC” customized regional primary and secondary school teachers’ information technology application ability training strategy
Authors: Jiqiong Yang , Yue Qian 
Published: June 2021

Abstract
According to the research status of information technology application ability of regional primary and secondary school teachers, aiming at the subjective factors of regional primary and secondary school teachers, such as weak foundation, less free time, conflict between training time and working time, and the lack of close combination of existing training content and teaching practice, single training method and outdated content, can not meet the different needs of different teachers and other objective factors, put forward the “MOOC + SPOC” based on the regional primary and secondary school teachers’ information technology application ability training design, in order to use the fragment time to complete the preliminary knowledge learning and then through the flip classroom mixed mode to complete the knowledge internalization, effective training is realized through the path of evaluation and feedback to promote ability improvement.
‘Anomalies’ Visualized by Ten Years Tracking of Ph.D. Recruitment Data on JREC-IN in Japan
Authors: Hirayama Kota , Umemura Kazuo 
Published: June 2021

Abstract
We have accumulated retrieval data of PhD job recruitments using the JREC-IN website, which is the public jobs database in Japan. We focused on retrieval for natural science and engineering fields with five typical keywords such as ‘Chemistry’ and ‘Biology/Life science’. To continue the retrieval for ten years, a simple keyword search was demonstrated, although a more detailed analysis might be available for short-term searches. Our data revealed several anomalies. First, the ratios of non-permanent positions against permanent positions in ‘biology/life science’ fields and ’chemistry’ fields were much higher (195% and 153%) than other fields such as ‘physics’. Biologists and chemists may easily find non-permanent positions, but it is not easy to find a permanent position. Second, a clear anomaly of recruitments according to seasons in one year was observed based on the ten years’ historical data. Because the fiscal year in Japan starts in April, the number of recruitments of permanent positions was maximised in August in all fields. Then, the peak of recruitments of non-permanent positions appeared in November through February. Our work provided fundamental knowledge to understand and solve the PhD job problem in the natural science and engineering fields in Japan.
Application of the intra cluster, characteristic of k-means clustering method in English score analysis in Colleges
Authors: Wang Qin 
Published: June 2021

Abstract
As an important data mining method, clustering algorithm can find valuable information hidden in data objects through unsupervised classification method. It is widely used in data analysis, image segmentation, feature learning and other fields. It is one of the common methods in traditional machine learning algorithm. K-means clustering algorithm is a partition-based algorithm in clustering analysis, which is efficient and accurate, easy to implement, and is generally implemented in machine learning and other fields. In this paper, based on the characteristics of K-means clustering method, the scores of each part of 30 college students' English scores are used as the input data, and the cluster center is used as the influencing factor to participate in the clustering process. The clustering effect is evaluated under the average distance of the characteristics within the cluster after several iterations.
Refined range analysis of early warning and pre-control based on multi-element spatiotemporal clustering
Authors: Tu Min 
Published: June 2021

Abstract
There are three parts in public security big data analysis when early warning and pre-control oriented: refined analysis scope, visualization of temporal and spatial characteristics of analysis scope, and subspace emergency analysis model for early warning and controlling. These three parts are interrelated, and complete the early warning and pre-control analysis of emergency iteratively. The exploration method of refined analysis range is analysed in the paper, which is based on the calculation and comparison of multi-element spatiotemporal clustering results. This research adopts a grid division strategy to convert heterogeneous data into a normalized space-time grid, in order to improve the versatility of the framework. And the estimation of grid records without observed values using kernel density estimation method. The added clustering ensemble is to improve the stability of clustering results. It can avoid the influence of uncertain factors on the clustering results, as well as improving the real-time performance of clustering algorithm, by the optimization of clustering ensemble parameters, and the clustering ensemble deployed on Hadoop platform.
An optimal algorithm analysis of signal transitive random signal without noise feedback
Authors: Xiao Xiaonan 
Published: June 2021

Abstract
This article used the way of stochastic processes statistics to raise and study a kind of optimization of signal transitive stochasic system without noise feedback, and it did the optimum operation to permit coding function of the signal and solved the measuring question of the optimum coding and decoding of the signal. It could contributs an ideal way of mathematical.
Classification and analysis of literary works based on distribution weighted term frequency-inverse document frequency
Authors: Dai Wei 
Published: June 2021

Abstract
Term Frequency-Inverse Document Frequency (TF-IDF) is a commonly used data mining weighting technology for information retrieval. It can evaluate the importance of a word to a text and is widely used in Internet search engines. In order to improve the text analysis ability of different text types, a variety of weighting algorithms of TF-IDF have been developed. For the word analysis of literary works of various genres, this paper adopts Distribution Weighted Term Frequency-Inverse Document Frequency (TF-IDF-DW), which takes the distribution of feature items within and between classes into account, and can get better screening results. In the text classification part, via the comprehensive weight value obtained by TF-IDF-DW, and the classification results are obtained by class center vector algorithm and Bayesian algorithm. Finally, the classification performance of TF-IDF-DW algorithm is evaluated by comparison with the traditional TF-IDF method.
Application of panel data-generalized method of moments on the impact of urban output
Authors: Cong Dibei , Xia Gang , Xiang Wenjing 
Published: June 2021

Abstract
This article summarized the mechanism of the impact of real estate tax on city output path, on the basis of selecting the Chinese provincial panel data from 2005 to 2019, by using the PD - GMM method. The real estate tax was taken as the core explanation variable, and was added a lot of control variables to establish the impact of real estate tax on city output 7 panel data models. We estimated and analyzed the robustness through Eviews software. Research results showed that: (1) from the national level, the real estate industry tax would have a significant effect on urban output, and there is a "U" shaped relationship between the output and the real estate tax and cities. At the beginning of the urban development, the city real estate tax inhibited output, when the urban economy was in the period of high quality development. The real estate tax on urban output result, had obvious function. (2) At the regional level, the real estate tax in the eastern region had a negative inhibitory effect on the urban revenue, while the real estate tax in the western region had a significant promoting effect on the urban revenue, and the influence degree was shown as the eastern>western>middle. (3) The more real estate investment and human capital are tilted to the west, the more favorable the development of the western region, while the impact on the eastern and central regions was not significant.
Research on thermal imaging fault detection system based on weibull distributed electrical system
Authors: Pang Jiamao , Yu Zhimin , Chen Xiangguang 
Published: June 2021

Abstract
A fault prediction analysis is performed In order to use infrared thermal imaging technology to detect electrical system faults, based on Weibull distribution technology. First, the principle is explained, the key technologies and factors of infrared thermal imaging and the electrical fault monitoring system are analyzed, and the available technologies are summarized. The detection process and analysis research are established with the help of on-site inspection and analysis results for power system fault analysis and research. The research shows that the method is effective for fault detection and trend analysis, and provides a reference for power fault detection and prediction analysis.
Research on the influence of radius test based on hydraulic fracturing measures
Authors: Ma Shuyin 
Published: June 2021

Abstract
By analyzing the mechanism of hydraulic fracturing, and the special geological conditions of a certain mine, the relevant parameters of hydraulic fracturing and increasing permeability suitable for the mine are determined through on-site fracturing pump tests. After two sets of hydraulic fracturing tests in the test areas, and compared with the original drainage parameters, the average coal seam gas drainage concentration increased by an average of 3.55, 3.65 times, and the scalar drainage increased by 3.6, 3.1 times. The average water content of coal seams increased by 1.43 times and 1.65 times. Finally, after comprehensive analysis of the borehole gas drainage concentration, gas drainage scalar and coal seam water content measured in test area 1 and test area 2, it is concluded that the influence radius of fracturing and permeability is 25~30m. It provides an effective reference for the layout of hydraulic fracturing boreholes and increasing the effect of gas drainage.
Research on brand value based on analytic hierarchy process and fuzzy comprehensive evaluation
Authors: Chen Wei , Bu Xiaona 
Published: June 2021

Abstract
Based on the continuous deepening of brand strategy concepts in recent years, improving brand value has become a top priority. This article uses Xingtai wild jujube as an example to use the analytic hierarchy process to evaluate the brand value of Xingtai wild jujube from four aspects: product quality, brand support, product leadership, product profitability, and its subordinates 10 indicators; and use the fuzzy comprehensive evaluation method to calculate the evaluation score of Xingtai wild jujube, draw conclusions and make suggestions for the future development of Xingtai wild jujube.
Research on radar behavior recognition method under the condition of electronic jamming
Authors: Chu Zhenyong , Xiao Nan , Liang Jun 
Published: June 2021

Abstract
In the course of ECM, the attacker needs to grasp the working state of the target radar by identifying its behaviors, so as to adopt the best attack strategy. Based on the correlation characteristics between nodes of the networked combat system, the proposed method processes the electromagnetic radiation parameters of the target radar and its cooperative radar, uses the support vector machine multi-classifier algorithm to identify the target radar's behaviors, and determines the influence of jamming on the radar's working states. The simulation results show that the proposed method has higher accuracy than the traditional method which only considers the target radar radiation parameters, and the selection of kernel function and electromagnetic radiation parameters are closely related to the accuracy of behavior recognition.
Research on the causes of regional differences in urban residential land incremental value based on shapley value decomposition framework
Authors: Wu Zhenhua , Yu Qinping , Wang Yabei , Bai Qinguo 
Published: June 2021

Abstract
This paper studied the formation mechanism of the differences of land incremental value among various regions by using the Shapley value decomposition framework. It was the first time to introduce inequality indexes to measure the differences in land incremental value in various regions, then a semi-logarithmic regression equation were constructed to determine the influencing factors, and finally the contribution of each factor was measured through the Shapley value decomposition model. The results indicated that: the regional inherent differences between cities and the differences in the residential land price per land area have a stable and strong impact on the differences in urban residential land value increment; the differences in completion value of residential buildings have a certain contribution on the expansion of regional differences in urban residential land incremental value, but they fluctuate greatly; the contribution of the differences of housing investment demand to the differences of urban residential land incremental value has gradually increased.
Risk of spillovers between the Chinese and international crude oil futures’ markets: A dynamic Copula-CoES approach
Authors: Cao Jie , Lei Lianghai , Zhang Rong , Lei Qiran 
Published: June 2021

Abstract
To overcome the limitations of conditional value-at-risk (CoVaR), the upside conditional expected shortfall (CoES) is proposed and used as a measure of the extreme risk spillover effect between the Chinese and international crude oil futures markets. Then, the calculation formula of the upside CoES is given under the semiparametric dynamic Copula model, which does not need to set the specific evolution equation of the Copula parameters. The empirical results show that there is a strong positive correlation between Chinese and international crude oil futures, and the correlation gradually increases when oil prices rise. There is a significant two-way risk spillover effect for both of them, and the average risk spillover intensity between Chinese crude oil futures (INE) and West Texas intermediate crude oil futures (WTI) is the highest. Moreover, INE is not always the recipient of the price fluctuation risk. In particular, INE has played the role of risk spillover most of the time after 2019. This study provides new ideas for the measurement of risk spillovers.
Quality evaluation system based on 3D-indicators-perspective model
Authors: Wang Yanan , Wang Han 
Published: June 2021

Abstract
The quality evaluation system is based on the perspective of owners, which integrates various resources effectively and reasonably, and evaluates the results after arrangement, reflecting the satisfaction of owners to the results of resource utilization. This paper constructs a quality evaluation system from three dimensions of profitability, security and growth. The monthly transaction data from January 2010 to December 2018 and data from 2010 to 2018 are selected as data research samples. The conclusion is that good quality needs good profitability, safety and growth. The paper also puts forward some countermeasures and suggestions for sample companies with low quality score, in order to provide effective reference.
Research on real-time simulation modeling of hybrid electric vehicle power system
Authors: Miao Zheng , Zhang Ying 
Published: June 2021

Abstract
This article conducts simulation research on the power plant of hybrid electric vehicles. Through the strategy and logic control of the power system, the stable operation of the engine in the economic area is realized. The engine model can express the relationship between performance and operating point more clearly, and can better meet the real-time response requirements of the system. This paper establishes Simulink-Amesim joint simulation model and conducts simulation analysis. The results show that the curve of engine torque changing with speed basically conforms to the engine principle.
Establishment and analysis of quality art-evaluation model based on BP neural network
Authors: Cui Guoling 
Published: June 2021

Abstract
BP is a multi-layer feedforward neural network trained by error back propagation algorithm, which is designed to mimic the structure of biological neurons. The system could solve the problem of hidden layer connection weight learning in multi-layer neural network. Based on the influence degree of investment on art education in primary and secondary schools, four input layer neurons including the number of investment fields, the type of investment fields, the popularity rate and the utilization rate were selected to build a neural network model. The average relative error between the statistical value and the predicted value was 0.15%, which could prove that the model had a high prediction accuracy and can be applied in evaluating on primary and secondary school arts education.
BPS monopoles and dyons in generalized BPS Lagrangian method
Authors: Atmaja A N 
Published: June 2021

Abstract
We generalize BPS Lagrangian method and rederive BPS equations for monopoles and dyons from the Lagrangian of SU(2) Maxwell-Higgs model in four dimensional spacetime. We show that in the BPS Lagrangian method the Gausss’s law constraint does not necessary to be imposed beforehand. We find that the BPS Lagrangian has non-boundary terms which in turn gives us some constraint equations. These constraint equations can be reduced by taking the standard BPS equations for Monopoles and Dyons, which turns out to be the Gausss’s law constraint in the BPS limit.
Searching for a modification of a conformally flat metric in the five-dimensional braneworld model that localizes scalar and vector fields
Authors: Rohman Muhammad Taufiqur , Triyanta  
Published: June 2021

Abstract
A modification of the Randall-Sundrum metric model in the form of conformally flat metric was proposed some years ago. The proposed model shows better localization properties than the original Randall-Sundrum model. However, this new model still does not meet the expectation that all fundamental fields can be localized for one type of warp factor, e.g. for a decreasing warp factor. In this research we propose to add a factor f(r) in the extra coordinate part of the above modified Randall-Sundrum metric and derive conditions for localization for scalar and vector fields. r is the extra coordinate. We then look for some functions f(r) that fulfill the localization conditions for both scalar and vector fields. Examples of the function f(r) under investigation are e
Ar, e
−Ar−Br
2
, e
−A/r
, Ar, Ar + Br
2, and sinh(Ar). We found the expected function, that is e Ar
, which might be used as a further discussion in fields localization.
Density functional theory of Ni-doped (10, 0) single-walled carbon nanotubes for C 2H 2 and C 2H 4 sensing
Authors: Yusfi M , Jonuarti R , Wungu T D K , Suprijadi  
Published: June 2021

Abstract
The adsorption of C 2H 2 and C 2H 4 gas molecules on Ni-doped singe-wall carbon nanotubes (Ni-SWCNT (10,0)) was investigated using Density functional theory (DFT). To discover the highest interaction energy, three Ni-SWCNT configurations that are bridge, hollow, and top position of Ni on SWCNT were calculated. The Ni on the bridge configuration was the most stable configuration based on binding energy and Ni-C bond length analysis. With the addition of Ni to SWCNT, the energy gap energy of SWCNT becomes narrower from 0.879 eV to 0.289 eV. The C 2H 4 adsorption energy was acquired stronger than C 2H 2, which results in a smaller energy gap. Also, the geometry change of the gases/Ni-SWCNT was investigated in this research.