bluuebunny/crossref_metadata_2025_split huggingface dataset:
Energy interval 2S-1S in muonic ions of lithium, beryllium and boron
Authors: Dorokhov A E , Faustov R N , Martynenko A P , Martynenko F A 
Published: December 2020

Abstract
Within the framework of the quasipotential method in quantum electrodynamics, the energy interval (2S – 1S) in muonic ions of lithium, beryllium and boron is calculated. Corrections of order α
3 – α
6, which are determined by relativistic effects, effects of vacuum polarization, nuclear structure and recoil, as well as combined corrections, including the above, are taken into account. Nuclear structure effects are expressed in terms of the nuclear charge radius in the case of one-photon interaction and the electromagnetic form factors of nuclei in the case of two-photon interaction. The obtained numerical values for the (2S – 1S) energy interval can be used for comparison with future experimental data and for a more accurate determination of the nuclear charge radii.
Vector mesons spectrum in a medium with a chiral imbalance induced by the vacuum of fermions
Authors: Kovalenko V , Andrianov A , Andrianov V 
Published: December 2020

Abstract
The properties of the light vector mesons in the presence of local parity breaking medium with a chiral imbalance are considered in the vector-meson dominance model. Applying the finite lowest-order radiatively induced local effective Lagrangian, initially developed for the QED, for the vector ρ and ω mesons, we obtained the mass spectrum as a function of momentum and chiral chemical potential μ5. We showed that in addition to the Chern–Simons term, splitting the transverse polarisations of the mesons, there is another radiatively induced contribution that becomes important at momentum and μ
5 around a few hundred MeV.
Shear viscosity of nucleons and pions in heavy-ion collisions at energies of NICA
Authors: Zabrodin E , Teslyk M , Vitiuk O , Bravina L 
Published: December 2020

Abstract
The shear viscosity is calculated microscopically via the Green-Kubo relation for the series of snapshots in the central region in an ongoing relativistic collision simulated via the UrQMD framework for various bombarding energies in the anticipated NICA experiments. In previous works the shear viscosity was calculated as function of temperature, while the chemical potential of baryon charge was kept constant. In present work we extract, in various time windows, the average energy density, the net baryon density and the small though nonzero net strangeness density. By fitting these parameters to statistical model, one can get temperature and both chemical potentials of baryon charge and strangeness. Simultaneously, these parameters are used as input to simulations in a box, again within the UrQMD transport model. The autocorrelations in time of the energy stress tensor are extracted, and subsequently via the Green-Kubo identities the shear viscosity coefficient of that equilibrium hadronic system is obtained. Then we calculate partial viscosity both for nucleons and pions for five collision energies from Elab
= 5 to 40 AGeV. It appears that substantial part of the contribution to total shear viscosity of the system comes out from pion-nucleon and other correlators.
Influence of quark content and collision geometry on proton production in heavy ion collisions
Authors: Larionova D , Berdnikov A , Berdnikov Ya , Kotov D , Mitrankov Iu 
Published: December 2020

Abstract
Proton production have been preivously measured in PHENIX experiment in Au+Au collisions at

s

N
N

=
200

GeV

. It was obtained that protons yields are enhanced over all mesons yields. This phenomenon was called “baryon puzzle”. This paper presents mesurements of protons in asymmetric Cu+Au collisions at

s

N
N

=
200

GeV

in order to investigate influence of collision geometry. Results in Cu+Au and Au+Au systems were found to be in agreement at similar number of participants, which might indicate that proton production in heavy-ion collision scales with the average size of the nuclear overlap region and do not depends on the details of its shape. ln order to investigate influence of quark content on production of protons consisting of three quarks comparison with φ, π
0 -mesons (quark-antiquark pairs) was provided in Cu+Au collisions at the collision energy of 200 GeV. Such information can improve our understanding of quark-gluon plasma and recombination model.
12 years of HYDJET++ generator: history and the latest results
Authors: Belyaev A V , Bravina L V , Chernyshov A S , Eyyubova G Kh , Korotkikh V L , Lokhtin I P , Malinina L V , Petrushanko S V , Snigirev A M , Zabrodin E E 
Published: December 2020

Abstract
It has been dozen years since HYDJET++ Monte-Carlo event generator for the simulation of relativistic heavy ion collisions was developed. Now the generator is widely used for the simulation of nucleus-nucleus interactions from NICA to LHC energies. The model calculations on soft and hard probes of quark-gluon plasma (including collective flow, different kinds of particle correlations, jets, D and B mesons etc.) agree well with the experimental data. In this paper the selected main results and the very new ones are presented.
Reconstruction of moments of particle distributions with Identity Method at MPD
Authors: Altsybeev Igor , Petrov Vitaliy 
Published: December 2020

Abstract
Precise determination of the moments of multiplicity distributions of identified particles could be challenging due to the misidentification in detectors. The so-called Identity Method allows one to solve this problem. In this contribution, performance of the Identity Method was tested on the A – A events simulated in the conditions of the MPD experiment at NICA. With this method, moments within a single kinematic window as well as coefficients of forward-backward pseudorapidity correlations are extracted.
Stopping of protons in pA collisions at SPS and NICA energies in analytical hydrodynamic model and in SMASH event generator
Authors: Ermakova V , Sandul V , Feofilov G 
Published: December 2020

Abstract
Our study is motivated by the first experimental results on pion production and stopping obtained in pA collisions in E910 experiment at BNL. The effect of stopping is the deceleration of an incident high energy proton traversing the target nucleus. It appears due to the energy losses relevant to the production of secondary particles in the inelastic interactions with nucleons.
A hydrodynamic effective model of stopping is proposed that is based on the consideration of the nuclear matter as a liquid and by the introduction of an effective stopping force acting on a fast-moving proton. With this force, we obtain a differential equation that describes the relativistic motion of a proton in a nucleus. Calculations in the framework of this analytical model are performed for the correlation between the mean multiplicity of charged pions and a number of binary collisions.
Resolving Black Hole Information Paradox: Revisited
Authors: Kashi B 
Published: December 2020

Abstract
Blackhole remnants are one of the most exotic remnants in our universe, leaving behind several unsolved paradoxes. Resolving the black hole information paradox, in particular, can direct us to numerous engrossing discoveries and provide a decent understanding of the unsolved conventional theories. We readdress the notions underlying the paradox explicitly, beginning from the basic principles. Various theories, explanations, conclusions, their advantages and disadvantages in several works of literature regarding the information paradox and black hole entropy are discussed. Recent developments in the interpretation of the black hole information paradox are reviewed. A congenital solution to this contradiction involves the transition of classical physics to quantum physics. At the centre of the black hole, the space-time theory by Einstein’s general theory of relativity fails. The research suggests that the solution obtained from considering the principles of quantum gravity is quite plausible. This approach also gives a decent explanation towards the recondite hypothesis of tunnelling of black holes to white holes and the interior geometries of white holes.
Δϕ distributions between final state particles as a criterion of the pile-up background mismodeling and its impact on Z(vv)γ process
Authors: Pyatiizbyantseva D , Soldatov E Yu 
Published: December 2020

Abstract
In the case of the pile-up background (background from the neighboring interactions inside the bunch crossing) for Z(vv)γ process at the Large Hadron Collider (LHC) experiments, its accurate calculation is very challenging. If the impact of the pile-up background is negligible, as it is expected in the case of Z(vv)γ process selection, some global uncertainty from this source can be used. This report studies the pile-up background and shows that it is expected to have a completely different shape for Δϕ distributions between final state particles in comparison to the signal and other background processes. Thus, the absence of Δϕ-mismodeling in the analysis proves that the pile-up background is indeed negligible.
Application of Authentication and Secret-key Distribution Mechanism of Challenge-response in Micro-service Security Supervision and Authentication Interaction
Authors: Chunlei Chang , Liang Bai , Kai Yun , Kai Li 
Published: December 2020

Abstract
The aims are to ensure the safety of communication among micro-service system modules, protect the trust of inter-servant-module, and improve the communicating efficiency. The authentication and secret-key distribution mechanism of challenge-response are introduced to improve the scheme for secure communication, supervision, and forewarning of data, and the effect is then tested. The modules of authentication and secret-key distribution and the data security communication are built according to the characteristic of challenge-response. These modules orient micro-service secure communication protocol. Besides, supervision and forewarning scheme is improved by running the log. Next, the security and efficiency of communication encryption and the function of supervision and management are tested. The results indicate that the scheme proposed can ensure the confidentiality and integrity of the communication process, and the log analysis module designed can promote and guarantee the daily operation and maintenance of administrators. Such progress has important reference value for applying authentication and secret-key distribution mechanism of challenge-response in micro-service security supervision and authentication interaction.
Brief Analysis of perfecting the law of maintaining computer network security
Authors: Huang Mei , Gu Liangjun 
Published: December 2020

Abstract
Since the 21st century, computer network technology has developed rapidly, and now all industries are inseparable from the application of computer network technology. However, due to the complexity and virtuality of computer network itself, it is easy to cause some network security problems. In addition, due to the rapid development of computer network, some laws related to computer network security have not been updated and improved in time, and the application of laws to maintain computer network security is also facing some great difficulties. Therefore, it is necessary to strengthen the establishment and improvement of laws and regulations on computer network security and build a peaceful, safe, open, cooperative and orderly cyberspace.
Application of Computer Accounting System in Internal Control of Enterprise Accounting
Authors: Lan Yulin , Tang Yueting 
Published: December 2020

Abstract
In the process of rapid development of computer technology, to promote the effective application of corporate accounting internal control in computers, accounting information system software can be constructed. The use of computer accounting information system software can improve the efficiency and level of corporate internal accounting control. The system software can not only improve the corporate financial management system, but also protect the accounting information system of the calculation class. When carrying out the internal control of the computer accounting information system, we need to strengthen computer hardware and software protection, and correctly face the security threats that exist in the computer for accounting control. In addition, we also need to take effective measures to improve the application level of corporate internal control on computers.
Reducts in single valued neutrosophic ß-covering approximation spaces
Authors: Mao Lingling 
Published: December 2020

Abstract
The problem of reducts is an interesting issue in all rough set models. In this paper, we propose the concept of the reduct in a single valued neutrosophic β-covering approximation space (SVN-β-CAS). Moreover, reducts in SVN-β-CASs are investigated while adding and removing some objects of the universe, respectively. Firstly, the notion of the reduct in a SVN-β-CAS is presented. It can be seen as the generalization of the reduct in covering and fuzzy β-covering approximation spaces. Then, two new SVN-β-CASs are presented while adding and removing some objects of the original universe. Finally, some properties of reducts of SVN β-coverings are investigated while adding and removing some objects, respectively.
The Research And Application Of Intelligence Evaluation System In colleges and universities
Authors: Qu Feng Lin , Chen Lin , Jiang YongChen 
Published: December 2020

Abstract
Teaching quality is the lifeline and core competitiveness of the survival and development of higher vocational colleges. Student evaluation plays an important role in the monitoring of teaching quality. Based on the analysis of the existing teaching evaluation system and its results, this paper proposes a multi-dimensional teaching evaluation information system based on quantitative teaching evaluation index system and intelligent analysis function. The system has been tested and run by a university, and its feasibility and effectiveness have been verified. It provides a reference scheme for other universities to build a multi-dimensional evaluation system based on the characteristics of the subject.
BSMM: A Broadcast Storm Mitigation Model Based On Distributed Data Clusters and Hybrid Network Architecture in Vehicular Named Data Network
Authors: Fan Na , Li Chen , Zhang Tianyang , Duan Zongtao , Wang Qinglong , Zhu Yishui 
Published: December 2020

Abstract
Vehicle networks play a key role in intelligent traffic field. Named Data Networks (NDN) which has characteristics of interest packet driving and content caching is suitable for Vehicle networks. After the technology of NDN is used in vehicle networks, Vehicular Named-data Network (VNDN) is constructed. However, the efficiency of communication is affected by the high-speed movement of vehicles and the changing topology of VNDN. In VNDN, vehicles broadcast interest packets to retrieve required data. It is easier to rise broadcast storm because of the broadcast behaviour. In order to deal with this problem, we firstly propose a hierarchical hybrid network architecture which is consisting of vehicle network and infrastructure network. Secondly, we propose a concept of distributed data named cluster based on the hybrid network architecture. Based on the above, a novel broadcast storm mitigation strategy (BSMS) which includes a real-time route update algorithm and a hierarchical routing request algorithm is proposed to relieve the broadcast storm. At the same time, the proposed model based on distributed data named clusters provides a real-time update data request interface for vehicles. The simulation results show that the proposed model BSMM is able to resist the broadcast storm and improve the efficiency of communication among vehicles in VNDN.
Activity recommendations based on heterogeneous social networks
Authors: Qi Xiaoying , Yu Wen 
Published: December 2020

Abstract
EBSN (event-based Social Network) is a Heterogeneous Network, namely, H-EBSN (Heterogeneous event-based Social Network), which contains both online interactive information and offline interactive information. How to effectively use the interaction between online and offline to recommend activities is one of the hot issues at present. The following work has been done for the activity recommendation of H-EBSN:
(1) Construct H-EBSN, extract all link-roads and obtain user interest through link-roads’ characteristics.
(2) Analyze H-EBSN meta path, take the path number of extracted link-roads as feature vector, establish user interest model, and use generalized regression neural network to solve the model.
(3) The training set was constructed by using the movie-watching activity data set, and the generalized regression neural network was used to solve the model. Experiments show that the activity recommendation method based on H-EBSN proposed in this paper has a good recommendation effect.
Target recognition algorithm based on improved depth separable convolution
Authors: Shi Jun , Liu Yunqing , Liu Quanyang , Zhang Qiong , Fei Yan 
Published: December 2020

Abstract
Realizing accurate target recognition in the fields of drones, vehicle-mounted systems, robots, etc. has increasingly become a hot research direction for researchers. Aiming at the problem of using deep learning algorithms to identify targets on mobile devices with limited size, the network model has a large number of parameters resulting in a large calculation cost, a complicated recognition process, and a large number of iterations resulting in a long recognition time. This paper proposes an improved deep separable convolution algorithm, which consists of deep convolution and point-by-point convolution, which is based on convolution kernels for step-by-step filtering and combination. After deep convolution, batchnorm is added, and the activation function uses a linear function. Add batchnorm and nonlinear activation function ReLU after 1×1 convolution to ensure the accuracy of target detection. This algorithm reduces the amount of parameters while ensuring recognition accuracy, reduces the amount of recognition calculations, and reduces the weight of the network model. It provides a network foundation for implementing image recognition on devices with limited size.
Artificial Intelligence in Agriculture
Authors: Zha Jiali 
Published: December 2020

Abstract
The application of AI in agriculture has been widely considered as one of the most viable solutions to address food inadequacy and to adapt to the need of a growing population. This review provides an overview of AI’s application in agronomic areas and progress in research labs. The review first presents two fields that AI can potentially play an important role in, which are soil management and weed management, and then Internet of Things (IoT) a technology that shows great potential in future usage is mentioned. Three challenges that need to be addressed in order for AI-based technology to be popularized in markets are uneven distribution of mechanization, the ability of algorithms to process large sets of data accurately and quickly, and the security and privacy of data, as well as the devices. Agricultural robots targeted at diverse aspects in agricultural industry have been developed and improved greatly in the past years, and although pointing out the hardship of applying machines and algorithms tested in experimental environment to real environments, the review highlights an already prosperous development and a promising prospect of application.
Study on the Application of CALL in College Oral English Language Teaching
Authors: Dang Ruihong 
Published: December 2020

Abstract
For a long time, Computer-aided language Leaching(CALL) system has been widely used in College English teaching practice. With the deepening of education informatization reform, how to use CALL to improve college oral English teaching has become a hot research topic. Therefore, this paper analyzes the characteristics of the application of CALL in oral English teaching, and puts forward some improving strategies and optimizing measures under the background of education informatization, aiming to enhance the role of CALL system in oral English teaching, so as to improve the teaching effect and teaching quality of college oral English
Research on the Innovation of Artificial Intelligence Training Mode for New Engineering Majors in Higher Vocational Colleges
Authors: Li Gan 
Published: December 2020

Abstract
The “new” of the new economy is mainly reflected in two aspects. First, information technology (including cloud computing, big data, Internet of things, artificial intelligence and other technologies) is widely used in social material production and spiritual and cultural fields. The new form of social culture and material production has the characteristics of high efficiency, changeability and cross field. Second, the wide application of new materials and bioengineering technology will greatly change the relationship between man and nature (including the material characteristics of human beings), and make the living state and living space of human beings have essential changes different from those of any previous era. With the prosperity of China’s industrial manufacturing industry, the industrial chain of artificial intelligence is developing rapidly. The purpose of AI interface research is to realize human-computer communication. Therefore, scholars must make efforts from both theoretical and practical aspects to solve the functional problems of computer’s understanding and translation of words and languages, and self-expression. [1] Due to the research and application of intelligent interface technology, the development of computer technology has been greatly promoted, and the operation speed and human-computer communication have been greatly improved.
Detection and Analysis of Credit Card Application Fraud Using Machine Learning Algorithms
Authors: Han Yaodong , Yao Shun , Wen Tie , Tian Zhenyu , Wang Changyu , Gu Zheyuan 
Published: December 2020

Abstract
Fraud is a widespread problem in the financial industry with devastating effects. It is essential to prevent and reduce fraud effectively. Traditional approaches, such as expert system, suffers from the incapability to handle complex problems and tremendous amount of data, while the recent development of various machine learning techniques brings new solutions. With many research works focusing on tackle frauds of credit card transaction or insurance, only few mentioned the identity fraud of credit card application. This article presents a few machine learning models to detect such fraud. We firstly explore and clean up the data. Then 331 expert variables are created with professional consult and selected to 30 to reduce dimensionality of our data. Multiple models, such as logistic regression and decision trees, are built and fit on the training set. Finally, we found that the random forest model performs the best in terms of fraud detection rate, achieving 54% in out-of-time test. The obtained model can be applied in anti-fraud monitoring systems, or a similar model development process can be performed in related business areas to detect fraud and reduce the occurrence of such behaviors.
Research on COVID-19 Global Forecast based on SIR Model-ML regression
Authors: Wei He , Qingtao Zeng , Likun Lu , Yeli Li 
Published: December 2020

Abstract
Under the background of the global COVID-19 pandemic, the global COVID-19 epidemic spread was modeled and analyzed, and its future trend was predicted. The dataset covers 163 countries and almost 2 full months from 2020, which is enough data to get some clues about the pandemic. The epidemic situation was predicted by the fusion of SIR model and ML regression, and the results showed that the model analysis was basically consistent with the real performance of the epidemic development. Finally, the development stage and trend of the epidemic situation are evaluated to provide a basis for the government to formulate relevant epidemic prevention policies.