bluuebunny/crossref_metadata_2025_split huggingface dataset:
Axisymmetric plasma mode in disk with two-dimensional electron gas
Authors: Rodionov D A , Zagorodnev I V , Zabolotnykh A A , Volkov V A 
Published: December 2020

Abstract
A theory of resonant absorption in disk with two-dimensional electron gas has been developed when the wavelength of external radiation is comparable with the radius of the disk. We have analyzed analytically and numerically the position and the linewidth of the resonant peak, which corresponds to excitation of the axisymmetric (quadrupole) plasma mode in the disk. We have found dependence of the plasma resonance characteristics on a dimensionless retardation parameter that is equal to the product of the plasma frequency and the radius of the disk divided by the speed of light. We have shown that the linewidth is not merely the sum of collisional and radiation decay, but also contains “interference” terms.
Computer Algebra Methods in Modeling the Dynamics of Particle Beams in Accelerators
Authors: Andrianov Sergey 
Published: December 2020

Abstract
This article is devoted to the methods of numerical and symbolical methods of calculations, which are based on perturbation theory and are implemented in terms of matrix formalism. These methods were used to solve various problems of modeling and optimization in accelerator physics. The basic theoretical principles are verified using methods to neural network technologies, machine learning and others.
Shock wave and radiation at explosion of spherical HE charge inside a tube filled with xenon
Authors: Anderzhanov E K , Medvedev S P , Tereza A M , Khomik S V , Khristoforov B D 
Published: December 2020

Abstract
The operation of a powerful source of optical radiation based on explosion of spherical HE charges in metal tubes filled with xenon was investigated. The velocity and radiative characteristics of the shock wave propagating through the tube were determined. It is shown that reflective coating of pipe walls makes it possible to increase the density of the energy flux by more than an order of magnitude as well as to improve the shape of its time dependence. A three-dimensional numerical simulation of the formation and propagation of a shock wave was performed, and a simplified method for estimating the radiation intensity was proposed.
Molecular dynamics simulation of polymerization of the carbon under thermal decomposition of methane at constant volume
Authors: Kudinov A V , Gubin S A , Bogdanova Yu A 
Published: December 2020

Abstract
Thermal decomposition of methane was simulated at high temperature and pressure using the molecular dynamics method. The calculation was carried out employing ReaxFFlg potential. We show the dependence of the decomposition products on time and the results of methane polymerization at constant temperature. We also show the influence of gradual temperature decrease at the size of the polymers.
Electric probe measurements of chemical ionization behind reflected shock waves
Authors: Vlasov P A , Ryabikov O B , Smirnov V N , Mikhailov D I , Pankrat’eva I L , Polyanskii V A 
Published: December 2020

Abstract
Chemical ionization is the process of formation of charged particles as a result of energy release during the formation of chemical bonds in chemical reactions between neutral components. Chemical ionization is most often observed in the processes of hydrocarbon combustion. Measurements of ionization current in internal combustion engines are of great practical interest. Most experiments on chemical ionization were carried out in flames with obvious limitations: the composition of the mixture cannot be changed in an arbitrarily wide range of concentrations of fuel and oxidant, to investigate the pyrolysis processes, to arbitrarily change the temperature and pressure, it is impossible to dispose of the transfer processes and gradients of temperature and reactive components. Experiments in shock tubes in the reflected shock waves are free of all of the above disadvantages. In the present work, electric currents to the electrically insulated and uninsulated cylindrical probes were recorded, to which a negative (−9V) or positive (+9V) potentials were applied. In these experiments, the displacement and the total currents were recorded respectively. In the same experiments, the signals of chemiluminescent emission of electronically excited OH* radicals (λ = 308 nm) were simultaneously recorded. The main goal of the present work was to measure experimentally (1) the displacement currents on positive and negative probes, (2) the total and displacement currents on a negative cylindrical probe during acetylene pyrolysis and oxidation, and (3) to confirm correlation of the displacement currents and the signals of chemiluminescent emission of electronically excited OH* radicals.
First results and future prospects with PHELEX
Authors: Kopylov A , Orekhov I , Petukhov V 
Published: December 2020

Abstract
First results on the search for hidden-photon (HP) dark matter by multi-cathode counters are presented. The new experiment – PHELEX is described. The possibility to detect diurnal variations of the count rate from HPs in PHELEX experiment is discussed.
Top pair production at ultra-high energies
Authors: Okorokov V A 
Published: December 2020

Abstract
The top quark, the heaviest quark and, indeed, the heaviest elementary particle known today, constitutes a novel probe of the long-lived medium in quark-gluon phase which, as expected, can be produced even in light nuclei collisions at ultra-high energies. Some distinctive features are considered for particle production in the top sector in ultra-high energy domain. The antitop-top pair production is studied within the quantum chromodynamics and effective field theory approach used for calculations of total partonic cross sections. Predictions for all observables are computed at NNLO in quantum chromodynamics and at LO in effective field theory. These quantitative results can be important for both the future collider experiments at center-of-mass energy frontier and the improvement of the phenomenological models for development of the cosmic ray cascades in ultra-high energy domain. Thus the study allows the better understanding of heavy particle production and emphasizes the exciting interrelation between the high-energy physics on accelerators and ultra-high energy cosmic ray measurements.
New Markov-Chain Monte Carlo analyses for the evaluation of the antiproton background
Authors: De la Torre Luque P , Gargano F , Loparco F , Mazziotta M N , Serini D 
Published: December 2020

Abstract
Current measurements of the cosmic ray spectra have reached unprecedented accuracy thanks to the new generation of experiments, and in particular the AMS-02 mission. At the same time, significant progress has been made in the propagation models of galactic cosmic rays. Nevertheless, the current knowledge on spallation cross sections is very poor, impeding a more precise estimation of the diffusion coefficient. In this work we show a new Markov-Chain Monte Carlo algorithm able to derive the propagation parameters from the flux ratios of light secondary cosmic rays (Li, Be, B) to C and O and a new procedure able to combine the flux of these secondary cosmic rays in order to get rid of the uncertainties associated to their production cross sections. Then, we show that the antiproton spectrum inferred from this diffusion model match experimental data much better than with earlier analyses, discarding the excess of data previously explained as a possible signature of antiproton production from dark matter.
Annual variations of the 214Po, 213Po and 212Po half-life values
Authors: Alexeev E N , Gangapshev A M , Gavrilyuk Yu M , Gezhaev A M , Kazalov V V , Kuzminov V V , Panasenko S I , Petrenko O D , Ratkevich S S 
Published: December 2020

Abstract
Results of a comparative analysis of the 214Po (T
1/2 = 163.47 ± 0.03 μs), 213Po (T
1/2 = 3.705 ± 0.001 μs) and 212Po (T
1/2 = 294.09 ± 0.07 ns) half-life annular variation parameters are presented. The sinusoid curve approximated a set of 214Po τ-values obtained at BNO INR RAS has an amplitude A = (5.0 ± 1.5) ⋅ 10−4, period ω = (365 ± 8) days, and phase ϕ = (170 ± 7) days. The one obtained at the KhNU has an amplitude A = (4.9 ± 1.8) ⋅ 10−4, a period ω = (377±13) days and a phase ϕ = (77±10) days. The 213Po τ-value sine approximation has an amplitude A = (3.9 ± 1.2) ⋅ 10−4, a period ω = (370 ± 13) days and a phase ϕ = (130 ± 9) days. The 213Po τ-value set with a time duration of ~ 1700 days can be described by a sinusoidal function with an amplitude A = (3.9 ± 1.2) ⋅ 10−4, a period ω = (370 ± 13) days and a phase ϕ = (130±9) days. The 212Po one has an amplitude A = (7.5±1.6)⋅10−4, a period ω = (375±13) days and a phase ϕ = (40 ± 10) days.
Implementation of the deconvolution method for signal peak detection in read-out ASIC
Authors: Atkin E , Azarov D , Ivanov P , Normanov D , Serazetdinov A , Shumikhin V 
Published: December 2020

Abstract
An application of the deconvolution method for signal peak detection in read-out ASIC for GEM detectors is described. Instead of usage of the conventional analog or digital peak detector, deconvolution technique to define the signal maximum was studied. In this case the digital data coming from the ADC are processed by a digital filter that deconvolves according to the pre-determined transfer function of the analog channel. Such processing allows to identify the signal peak values and also to provide reasonable pileup rejection. That enables higher rates of the incoming signals and reduces the amount of lost data.
Combined with the analog channel employing 10-bit 25 MHz sampling rate ADC and 250 ns time constant 2nd-order shaper, the designed deconvolution block maintains peak detection accuracy within 9 LSBs. Time resolution of peak separation is 4 ADC sampling intervals or 100 ns.
Topological properties of Josephson current between two s- and p-wave superconducting nanowires with Majorana fermions
Authors: Suleymanli Bahruz D , Nakhmedov Enver , Naumov Petr Yu 
Published: December 2020

Abstract
Josephson current between two one-dimensional nanowires with proximity induced either s-wave or p-wave pairing and separated by a narrow dielectric barrier is calculated in the presence of Rashba spin-orbit interaction, in-plane and normal Zeeman magnetic fields. We show that Andreev retro-tunneling is realized by means of two channels. The main contribution to the Josephson current in junction of s- or p-wave superconductors is shown to give Andreev scattering in a conventional particle-hole channel, when an electron-like quasiparticle reflects to a hole-like quasiparticle with opposite spin yielding a current which depends only on the order parameters’ phase differences φ and oscillates with fractional 4π period. Nevertheless Andreev bound state energy in second anomalous particle-hole channel, corresponding to the reflection of an incident electron-like quasiparticle to a hole-like quasiparticle with the same spin orientation, survives only in the presence of the in-plane magnetic field, and oscillates with 4π period not only with φ but also with orientational angle of the in-plane magnetic field θ resulting in a magneto-Josephson effect. In the presence of Rashba spin-orbit coupling (SOC) and normal-to-plane magnetic field h, a forbidden gap is shown to open in the dependence of Andreev bound state energies on the phases φ and θ at several values of SOC strength and magnetic field, where Josephson current seems to vanish. The magnetic fields destroy also the particle-hole symmetry of the mid-gap states around Fermi level.
On perturbative unitarity in the extended MSSM Higgs sector
Authors: Dubinin M N , Fedotova E Yu 
Published: December 2020

Abstract
Higgs sector of the minimal supersymmetric standard model (MSSM) extended by dimension-six operators, which are loop contributions in the expansion of the Coleman-Weinberg type potential, is considered. The presence of such additional contributions allows the reopening of phenomenological MSSM scenarios closed in the previous analysis. In order to restrict respective MSSM parameter regions, perturbative unitarity constraints must be satisfied. We find the analytical formula for quartic and trilinear couplings for the Higgs potential extended by dimension-six operators, compare results with the loop corrected constraints at high or finite

s

with and without additional U
(6)-contributions, and show how the allowed regions in the parameter space are affected in these cases.
Measurements of the like-sign pion and kaon femtoscopic correlations at NICA energies
Authors: Nigmatkulov G , Batyuk P , Khyzhniak Y , Kodolova O , Malinina L , Mikhaylov K 
Published: December 2020

AbstractThe main goal of heavy-ion collision measurements at NICA energies(sNN=4−11GeV)is to study the properties of the quark-gluon matter at high baryon densities. Femtoscopy allows one to probe spatial and temporal characteristics of the particle-emission process at the last stage of the collision evolution - kinetic freeze-out. In this proceedings, we present estimations of like-sign pion and kaon pair femtoscopic observables for NICA energies using the UrQMD model. The dependence of the femtoscopic radii on collision energy, centrality, and pair transverse momentum are shown.
Reconstruction of γγ mass spectra in Ag+Ag collisions at 1.23 and 1.58 AGeV beam energies with ECal detector of the HADES experiment
Authors: Shabanov A , Prozorov A , Chudoba P , Galatyuk T , Guber F , Gumberidze M , Ivashkin A , Kugler A , Lalik R , Morozov S , Pechenov V , Petukhov O , Pietraszko J , Rathod N , Reshetin A , Rost A , Svoboda O , Salabura P , Tlusty P 
Published: December 2020

Abstract
HADES is a high acceptance di-electron spectrometer operating at SIS18, GSI, Germany aimed at study of hadron-proton, hadron-nucleus and nucleus-nucleus collisions at 1-4 AGeV beam energies. The new electromagnetic calorimeter (ECal) was added to the experimental setup in order to measure γ-quanta and thus extend its capabilities in study of π
0-, η-mesons, production of neutral hyperons and to improve electron-to-hadron separation for the partcles with momenta p > 300 MeV/c. The first data taking with the ECal detector was carried out in March 2019 when Ag+Ag collisions at 1.23 AGeV and 1.58 AGeV beam energies were studied. The methods of reconstruction of the γγ invariant mass spectra from these data are discussed. The analysis includes several steps: calibration of each module of the ECal detector, identification of γ-quanta, reconstruction of γγ invariant mass spectra and subtraction of combinatorial background. The obtained results show experimental capabilities of the new detector and, after efficiency corrections, will allow to normalize yields of other particles.
Prospects of non-resonant Higgs pair production at the HL-LHC and HE-LHC
Authors: Adhikary Amit , Banerjee Shankha , Barman Rahool Kumar , Bhattacherjee Biplob , Niyogi Saurabh 
Published: December 2020

Abstract
The prospects of observing the di-Higgs production in the Standard Model (SM) is explored. We choose final states based on considerable production rate and cleanliness. Standard cut-based and multivariate analyses using the Boosted Decision Tree (BDT) algorithm is performed at the high luminosity run of the 14 TeV LHC (HL-LHC) and we got a combined signal significance of ∼ 2.1. For the proposed high energy upgrade of the LHC (HE-LHC) at

s

=
27

TeV

, we do multivariate analyses using BDT algorithm, the XGBoost toolkit and Deep Neural Network (DNN), and we observe a discovery prospect with > 5σ significance for the Higgs pair production.
Production of dijets with large rapidity separation at colliders
Authors: Egorov A Yu , Kim V T 
Published: December 2020

Abstract
Production of dijets with large rapidity separation at collider energies in modified logarithm approximations is considered. The results for resummations of different types of logarithms: soft-gluon, non-global and Sudakov ones are discussed. Calculations for various dijet observables are confronted with LHC data.
Cascade single stage Detector using full convolution network
Authors: Liu Ming , Yu Zhengfa , Fu Kai , Zhou Xiangming 
Published: December 2020

Abstract
For object detection, the two-stage approach always achieves better performance than one-stage. But one-stage is more effective. The main shortcomings of one-stage approach are: class imbalance problem during the training phase and sometimes the correct object score is lower. To address those problems, we propose a novel single-shot detector, called Cascade detection. It is composed of several stages, and each stage is composed of several detection layers. The main point of our method is: we design an anchors to anchors module (A2AM), which gives one-stage approach the ability of training stage by stage. It can not only address the class imbalance problem in the training phase, but also increase the object scores and the Iou between prediction and ground truth in the inference phase. The multitask loss function enables us to train the whole network in an end-to-end way. Experiments on PASCAL VOC 2007, PASCAL VOC 2012 and MS COCO prove that our method achieves state-of-art performance detection accuracy and computation efficiency.
Improved algorithm of decision tree based on neural network
Authors: Zhang Min , Peng Hongwei , Yan Xiaoling 
Published: December 2020

Abstract
Decision trees have been applied to solve many data mining problems due to their superior learning and classification capabilities, and have achieved good results. However, for dealing with big data and complex model problems, decision trees show insufficient accuracy and overfitting. In order to solve these problems, neural network is introduced as a decision tree node, and an improved algorithm based on neural network decision tree is proposed. In the neural network decision tree, the classifier learning consists of two stages: the first stage uses a heuristic algorithm with reduced uncertainty to divide the big data, and stops the growth of the decision tree until the node dividing ability is below a certain threshold; in the second stage, the neural network is used to classify the decision-making leaf node with generalization ability. The experimental results show that compared with the traditional classification learning algorithm, the algorithm has a higher accuracy rate and it can determine the size of decision tree through structural adaptation for the classification problem of identifying big data and complex patterns.
Multi-scale Correlation Filter Tracking Algorithm Based on Feature Fusion
Authors: Ren Xiaokang , Wang Hongxiang , Wang Yongye , Li Xingzhen , Liu Xingxing 
Published: December 2020

Abstract
For the Kernel Correlation Filter (KCF) algorithm using a single feature can not fully describe the tracking target, and is susceptible to the change of the target scale, lacking the estimation of the target scale size, an improved feature fusion and multi-scale correlation filter tracking algorithm based on KCF is proposed. Firstly, in the stage of location prediction, color features and directional gradient histogram hog features are fused by feature series, and feature dimensions are added to realize target location prediction. Then the scale filter is introduced into the predicted target position to estimate the optimal target scale as the tracking result. Experimental results show that the accuracy and success rate of the improved algorithm are significantly improved compared with other classical tracking algorithms, and it can deal with scale change, occlusion, deformation and other complex situations robustly.
The improved mayfly optimization algorithm with opposition based learning rules
Authors: Gao Zheng-Ming , Zhao Juan , Li Su-Ruo , Hu Yu-Rong 
Published: December 2020

Abstract
Literal researches proved that not only the best candidates or the best historical trajectories would perform well in guiding the individuals in swarms to find the best solution, the worst and the worst historical trajectories would also work well in doing so. Such situations could be directly treated as pairs of oppositions, and satisfied the ancient Chinese Yin-Yang philosophy, where the opposition based learning (OBL) rule was directly derived from. In this paper, the improved mayfly optimization (MO) algorithm with OBL rules were proposed, simulation experiments were carried out and results showed that the improved MO algorithm with OBL rules would perform better than usual.
Automatic segmentation of low-grade glioma in MRI image based on UNet++ model
Authors: Xu Dan , Zhou Xidong , Niu Xuefen , Wang Junwei 
Published: December 2020

Abstract
Glioma is one of the common brain tumors, and the prognosis of patients with low-grade glioma is relatively good. Therefore, this paper takes the segmentation of low-grade glioma as the research direction, and proposes an automatic segmentation algorithm of low-grade glioma MRI image based on UNet++. Firstly, the sample data in the data set is normalized, and then the sample data is divided into training set, verification set and test set, and data augmentation is performed on the training set; finally, all the data in the training set is used to train the network model. In the training process, in order to alleviate the over-fitting problem of model training, we draw into the dropout after each convolution layer. In order to verify the effectiveness of the proposed model, all intracranial tumor images of patients in the test sample set are selected for segmentation, and the final average Dice coefficient can reach: 89.1%. Compared with the segmentation algorithm based on U-Net, the average Dice coefficient of this algorithm is increased by 3.89%. The experimental results show that this algorithm can achieve better automatic segmentation results for low-level glioma images, provide effective reference for doctors’ diagnosis and surgery, and alleviate the problems of low accuracy and low efficiency caused by manual annotation of images only based on personal experience of doctors.
Multi-level Qualitative Reasoning Logic
Authors: Qin Zhen , Lu Peng , Liao Yuanxiu 
Published: December 2020

Abstract
Qualitative reasoning is a very efficient method that people often use to solve problems. Recently, the literature about qualitative reasoning as a causal analysis and decision-making tool has been emerging. However, the existing qualitative reasoning methods are mainly used for the modeling of imprecise problems. There are not many studies on formalization tools of qualitative “inference”. This paper proposes a logical system for qualitative reasoning (QRL). The main research contents include: the grammar and semantic structure of QRL are given; the meaning of formula logic truth value in QRL and its assignment rules are discussed; and the reliability and completeness of QRL are proved. Compared with fuzzy logic, probability logic and other uncertain reasoning methods, the advantage of QRL method is that it can use axiomatic reasoning method, and does not need to construct membership functions and collect a large number of samples.
An improved gesture recognition algorithm for human-robot collaboration
Authors: Liu Yiqun , Wang Xiaogang , He Yang , Mu Hua , Bai Yuewei 
Published: December 2020

Abstract
In this paper, an improved gesture recognition algorithm framework based on the improved SSD algorithm and OpenPose model for solving the robot’s mobile grasping problem in human-robot environment is proposed. Improved SSD algorithm by optimizing the front network of SSD algorithm and adjusting the prediction box is designed to identify the position of the hand rapidly, and to reduce the time for the training model. Testing experiments are perfomed for recognizing the hand’s key points information and eight designed gestures are compared with the traditional algorithm. The results show that the method can greatly improve the recognition distance of the original model under the dense environment, and also enhance the robustness and accuracy of the model, and have improved the ability of long-distance human-robot collaboration to a certain extent.