bluuebunny/crossref_metadata_2025_split huggingface dataset:
ODEA: Orbital Dynamics in a complex Evolving Architecture
Authors: Rodet L. , Beust H. , Bonnefoy M. , De Rosa R. J. , Kalas P. , Lagrange A.-M. 
Published: October 2019

Context. Mixed-variable symplectic integrators are widely used in orbital dynamics. However, they have been developed for Solar system-type architectures, and can not handle evolving hierarchy, in particular in systems with two or more stellar components. Such configuration may have occurred in the history of HD 106906, a tight pair of F-type stars surrounded by a debris disk and a planetary-mass companion on a wide orbit.
Aims. We present the new algorithm ODEA, based on the symplectic algorithm Swift HJS, that can model any system (binary,...) with unstable architecture. We study the peculiar system HD 106906 as a testcase for the code.
Methods. We define and compute a criterion based on acceleration ratios to indicate when the initial hierarchy is not relevant anymore. A new hierarchy is then computed. The code is applied to study the two recently evidenced fly-bys that occurred on system HD 106906, to determine if they could account for the wide orbit of the planet. Thousands of simulations have been performed to account for the uncertainty on the perturbers coordinates and velocities.
Results. The algorithm is able to handle any change of hierarchy, temporary or not. We used it to fully model HD 106906 encounters. The simulations confirm that the fly-bys could have stabilized the planet orbit, and show that it can account for the planet probable misalignment with respect to the disk plane as well as the disk morphology. However, that requires a small distance at closest approach (≲0.05 pc), and this configuration is not guaranteed.
Conclusions. ODEA is a very good choice for the study of non-Solar type architecture. It can now adapt to an evolving hierarchy, and is thus suitable to study capture of planets and dust. Further observations of the perturbers, in particular their radial velocity, are required to conclude on the effects of the fly-by on system HD 106906.
Optimization of surface flux transport models for the solar polar magnetic field
Authors: Petrovay K. , Talafha M. 
Published: October 2019

Context. The choice of free parameters in surface flux transport (SFT) models describing the evolution of the large-scale poloidal magnetic field of the Sun is critical for the correct reproduction of the polar magnetic flux built up during a solar cycle, which is known to be a good predictor of the amplitude of the upcoming cycle.
Aims. For an informed choice of parameters it is important to understand the effects of and interplay among the various parameters and to optimize the models for the polar magnetic field.
Methods. Here we present the results of a large-scale systematic study of the parameter space in an SFT model where the source term representing the net effect of tilted flux emergence was chosen to represent a typical, average solar cycle as described by observations.
Results. Comparing the results with observational constraints on the spatiotemporal variation of the polar magnetic field, as seen in magnetograms for the last four solar cycles, we mark allowed and excluded regions in the 3D parameter space defined by the flow amplitude u0, the magnetic diffusivity η and the decay time scale τ, for three different assumed meridional flow profiles.
Conclusions. Without a significant decay term in the SFT equation (i.e., for τ >  10 yr) the global dipole moment reverses too late in the cycle for all flow profiles and parameters, providing independent supporting evidence for the need of a decay term, even in the case of identical cycles. An allowed domain is found to exist for τ values in the 5–10 yr range for all flow profiles considered. Generally higher values of η (500–800 km2 s−1) are preferred though some solutions with lower η are still allowed.
Shape model and spin-state analysis of PHA contact binary (85990) 1999 JV6 from combined radar and optical observations
Authors: Rożek A. , Lowry S. C. , Nolan M. C. , Taylor P. A. , Benner L. A. M. , Fitzsimmons A. , Zegmott T. J. , Weissman P. R. , Green S. F. , Rozitis B. , Snodgrass C. , Smythe W. D. , Hicks M. D. , Howell E. S. , Virkki A. K. , Aponte-Hernandez B. , Rivera-Valentín E. G. , Rodriguez-Ford L. A. , Zambrano-Marin L. F. , Brozović M. , Naidu S. P. , Giorgini J. D. , Snedeker L. G. , Jao J. S. , Ghigo F. D. 
Published: October 2019

Context.The potentially hazardous asteroid (85990) 1999 JV6 has been a target of previously published thermal-infrared observations and optical photometry. It has been identified as a promising candidate for possible Yarkovsky-O’Keefe-Radzievskii-Paddack (YORP) effect detection.Aims.The YORP effect is a small thermal-radiation torque considered to be a key factor in spin-state evolution of small Solar System bodies. In order to detect YORP on 1999 JV6 we developed a detailed shape model and analysed the spin-state using both optical and radar observations.Methods.For 1999 JV6, we collected optical photometry between 2007 and 2016. Additionally, we obtained radar echo-power spectra and imaging observations with Arecibo and Goldstone planetary radar facilities in 2015, 2016, and 2017. We combined our data with published optical photometry to develop a robust physical model.Results.We determine that the rotation pole resides at negative latitudes in an area with a 5° radius close to the south ecliptic pole. The refined sidereal rotation period is 6.536787 ± 0.000007 h. The radar images are best reproduced with a bilobed shape model. Both lobes of 1999 JV6 can be represented as oblate ellipsoids with a smaller, more spherical component resting at the end of a larger, more elongated component. While contact binaries appear to be abundant in the near-Earth population, there are only a few published shape models for asteroids in this particular configuration. By combining the radar-derived shape model with optical light curves we determine a constant-period solution that fits all available data well. Using light-curve data alone we determine an upper limit for YORP of 8.5 × 10−8rad day−2.Conclusions.The bifurcated shape of 1999 JV6 might be a result of two ellipsoidal components gently merging with each other, or a deformation of a rubble pile with a weak-tensile-strength core due to spin-up. The physical model of 1999 JV6 presented here will enable future studies of contact binary asteroid formation and evolution.
Brain-Nutrients: Hirnstoffwechsel und Mikronährstoffe
Authors: Gröber Uwe , Kisters Klaus 
Published: October 2019

ZusammenfassungFür die optimale Entwicklung und Funktion des Gehirns sowie die Neuroprotektion ist eine ausreichende Versorgung mit Vitamin D, EPA, DHA, Eisen, B-Vitaminen, antioxidativen Vitaminen und Carotinoiden notwendig. Die Ernährung von Kindern und Jugendlichen weicht häufig von den Empfehlungen ab, sodass sie oft mit den genannten Mikronährstoffen unterversorgt sind. Eine Ernährungsumstellung und ggf. die Supplementierung von Nährstoffen ist im Hinblick auf die kognitive Leistungsfähigkeit und die Gesunderhaltung des Gehirns empfehlenswert. Erfolg verspricht nur die regelmäßige und konsequente Einnahme über einen ausreichend langen Zeitraum.
Spectrum of flows on discrete pair of contours
Authors: Tatashev Alexander G. , Yashina Marina V. 
Published: October 2019

Abstract
We consider a deterministic discrete dynamical system, which is a contour network of Buslaev type. This system contains two contours. The ith contour contains Ni
cells, i = 1, 2. There is a cluster of particles on each contour moving in accordance with given rules. The clusters contain 1 ≤ M
1 < N
1 and 1 ≤ M
2 < N
2 particles respectively. There is no more than one particle in each cell at any time. There is a common point (node) of the contours. Particles cannot cross the node simultaneously. A set of repeating system states is called a spectral cycle. Average velocities of clusters correspond to spectral cycles. The set of spectral cycles and values of the average velocities have been found.
Research on variable probability assignment technique of genetic algorithm for WTA of ground target attacking
Authors: Fu Guangyuan , Wang Chao , Zhang Daqiao , Wang Ranhui , Zhang Shujuan , Tan Fei 
Published: October 2019

Abstract
The targets and the use of weapons are complicated on attacking ground target, Besides, the weapon-target assignment (WTA) research is extremely difficult and lacking. For a timely and rational WTA scheme can not only help to seize fleeting war opportunities, but also optimize the use of weapon resources to maximize the battlefield benefits with minimum costs, this article builds a mathematical model and uses genetic algorithm (GA) to find the optimal WTA result. But the algorithm is difficult to prepare better initial population because of the random assignment of variables which results in undesirable optimization results. To overcome the challenge in initializing GA, this article puts forward a variable probability assignment technique. This technique first uses feasible solutions to determine the probability distribution of the variable values, then, uses probability assignment mode to replace the stochastic uniform assignment mode to initialize variables, and produces the initial population individual close to the optimal individual with certainty. The simulation calculation shows that the improved GA can effectively solve the WTA problem of the large scale ground targets attacking with better performance.
Regional analysis on model validation with different metrics
Authors: Wu Danqing 
Published: October 2019

Abstract
Compared with the global analysis, the regional analysis can offer more comprehensive and more detail information with an input variable fixed in an interval. Existing validation metrics mostly focus on the global discrepancy between the observations and the computer models. To further measure the difference in detail, the concept of regional validation was proposed in this work. To make regional validation specific and easily understandable, two existing validation metrics-the area metric and the G metric were applied. The contribution to whole validation (CWV) metric was proposed to depict the relationship between the proposed regional validation and the initial whole scale validation. At last, an example was employed to demonstrate the rationality and necessity of the regional validation.
Numerical methods for the time fractional diffusion equation
Authors: Guo Chong , Zhao Fengqun 
Published: October 2019

Abstract
In this paper, a differential analog of the Caputo fractional derivative called the L2 − 1σ formula is considered. The time semi-discrete scheme of the time fractional diffusion equation is obtained by using the L2 − 1σ formula to discretize the time derivative. The Sinc-Collocation method and the Sinc-Galerkin method are used to discretize the spatial derivatives, and the numerical schemes of the time fractional diffusion equation are constructed. Finally, the validity of the numerical schemes of this paper is verified by numerical example.
The study on supply and demand of water resources in Alar city based on the system dynamics model
Authors: Liu Xijuan , Liu Yun 
Published: October 2019

Abstract
According to the status of water resources shortage in Alar, this paper establishes a system dynamics (SD) model for the water resources carrying capacity (WRCC) and analyzes the balance between water resources supply and demand. Three cases are designed to simulate the level of WRCC from 2010 to 2030. The total water demand and secondary product output value are chosen as the evaluation indices to study the WRCC in Alar. The results show that the carrying capacity of water resources in Alar cannot meet the demand of social economic development in recent years, and case 3 could effectively alleviate water scarcity. Based on the results, in order to guarantee sustainable utilization of water resources and social economy development, it is necessary to increase water saving policies and increase the introduction amount of surface water in the future.
Research on the optimization of logistics vehicle routing under multimode transportation strategy based on ant colony algorithm
Authors: Qi Haining , Liu Yanqiu , Xu Shida 
Published: October 2019

Abstract
The transformation of multiple transport tools which the multimode transportation process involves, and the split transportation brought by the third-party logistics makes the problem more complicated. At present, a large amount of research on the multimode transportation problem remains at the decision-making level, lacking quantitative comparative analysis of vehicle path combinatorial optimization problem. The common genetic algorithm adopts the method of generating an initial solution randomly, which will lead to a large number of infeasible solutions in the population and reduce the solving speed. In view of the above problems, this paper proposes using ant colony algorithm to solve the multimode transportation problem. The solution of ant colony algorithm is generated according to the pheromone concentration and the state transfer probability of nodes, so the feasibility of spatial connection is ensured in the generation stage of solution. The concept of virtual node is introduced to reduce the difficulty coefficient of the problem. Finally, an example is given to prove the validity of the proposed model and algorithm.
Complex networks derived from time series and its application in EEG-based emotion assessment with convolutional neural networks
Authors: Zhang Zelin , Xu Jinyu 
Published: October 2019

Abstract
Construction the complex network paradigm, it is evidenced a new tool for exploring the dynamic mechanism hiding in the time series data which is a trajectory of complex system. This method has been applied in various domains gradually, such as physics, engineering, medicine and economics. In this paper, a new method for network paradigm transforming based on separating with the isoprobability is proposed, then it is applied in EEG signal analysis. The measures of transformed networks from 62-electrods ESI NeuroScan platform were used to construct EEG map. A three-layer convolutional neural network with 15 input channels were built so as to implement EEG-based emotion assessment. By nine fold cross validation, the structure of the convolutional neural network is improved. The simulation shows that our approach is better than differential entropy features based method.
Study on electromagnetic dynamic tunability of composite structure based on plasma periodic structure loading frequency selective surface
Authors: Luo Qian , Hou Zhongyu 
Published: October 2019

Abstract
The plasma periodic structure has dynamic reconstruction characteristics having important practical significance in electromagnetic engineering applications. In this paper, a composite electromagnetic structure consisting of plasmas which are periodically arranged and frequency selective surface is proposed and researched. Based on the periodically arranged plasma columns, the frequency selective surface is introduced to study whether a photon-like effect will occur on EM waves propagation in the composite structure even a stronger dynamic tuning ability. The reflectivity between 1~2GHz and 8~12GHz was tested in a microwave dark room to study the influence of periodic plasma and frequency selective surface on incident electromagnetic waves with the free space method. A commercial electromagnetic software also was used to calculate the electric field at different frequency points, and study the mechanism of its interaction with electromagnetic waves.
Raman spectroscopic analysis of paddy rice infected by three pests and diseases common in Northeast Asia
Authors: Yue Xin , Tan Yong , Fan Wenzhong , Song Shaozhong , Ji Hongyu , Li Bingbing 
Published: October 2019

Abstract
Pests and diseases seriously affect the yield and economic benefits of growing rice, and the key to inhibiting rice’s pathogenesis is to find early identification of rice infection. The characteristic Raman spectrum of healthy leaves, and leaves infected with rice blast, paddy rice bakanae and infected by Chilo suppressalis (Walker) were tested by TriVista555CRS laser Raman spectrometer (900cm−1–1700cm−1). At the same integration time, compared with healthy plants, the Raman peak of infected plants not only changed significantly, but also the signal intensity decreased. The results show that there are clear Raman peaks at the three characteristic wavenumbers of 1002.87cm−1, 1156.5cm−1 and 1522.36cm−1. Especially in the leaves of rice blast, it was found that the degree of fungal infection affects the peak width at half height of the characteristic peak. The research shows that Raman spectroscopy provides an effective method for the early detection of rice pests and diseases which may have economic benefits.
Exact multiple inverses of the quadratic planar map
Authors: Huang Yu-Kun 
Published: October 2019

Abstract
We developed a method for exactly determining the multiple inverses of quadratic planar maps. The quadratic planar map was transformed through an affine transformation into its conjugate domain, where all inverses can be exactly determined, and transform the inverses back. We showed that for all quadratic planar maps with non-vanishing critical curves, except for two exceptional cases of the map with a degenerate critical curve, there exists at least one available transformation. For both exceptional cases and for those maps with vanishing critical curves, the inverses are determinable without any transformation. This result can be applied to the calculation of stable manifolds of the quadratic planar map. It may help us further understand the dynamics, the basins of attraction, and the bifurcations associated with the quadratic planar map under iteration.
Is Lagrangian weight crucial in the direct forcing immersed boundary method?
Authors: Zhou Kun , Ding Zhou , Sun Ke 
Published: October 2019

Abstract
Particle resolved direct numerical simulation (PR-DNS) is one of the most powerful research tools for particle laden flows. Among a few most popular PR-DNS methods, the direct forcing immersed boundary method (DF-IBM) has obtained great success and has been adopted in various simulations of rigid particulate flows. Within DF-IBM, Eulerian and Lagrangian frameworks are used to depict the continuum and dispersed phases, respectively. Interpolation between the two frameworks is accomplished through a discrete delta function. It is generally believed that a Lagrangian weight attached to each Lagrangian marker, which is distributed on a particle’s surface, needs to be carefully chosen. To be more specific, the Lagrangian weight is supposed to match the local Eulerian cell. The matching requirement is not trivial for non-uniform Eulerian mesh or irregular shaped particles. There are various methods developed to calculate the Lagrangian weight. Here, the Lagrangian weights in a few testing cases have been calculated following two intuitively “straightforward” methods. It turns out there are substantial discrepancies in the Lagrangian weights obtained from different methods. However, further numerical examples demonstrate that such discrepancies have negligible effects on the flow dynamics. So a natural question is raised: Is Lagrangian weight crucial in the direct forcing immersed boundary method? A negative answer to this question is suggested. More detailed analysis is provided in a forthcoming paper.
Research on XGboost academic forecasting and analysis modelling
Authors: Hu Ting , Song Ting 
Published: October 2019

Abstract
The analysis and evaluation of student achievement is an important part of teaching work and an important part of school routine management. Scientifically analysing and evaluating students’ academic achievements can not only enable teachers to accurately grasp the students’ learning status, but also enable students to understand their own learning situation, and also provide necessary analysis for teaching management and improving teaching. In order to evaluate students’ learning situation comprehensively, objectively and reasonably, this paper uses XGBoost algorithm to classify and evaluate students’ performance based on statistical analysis of basic data, and establishes a performance evaluation model. For the curriculum relevance, the student’ s performance data is statistically compiled according to the statistical knowledge. The subjective and objective structural entropy weight method is used to classify the characteristic importance results, and finally the relevant courses of the completed courses are obtained. For the results of the unfinished course using the completed course results, the XGBoost method is used to predict each student’ s grades.
An efficient EM algorithm for the mixture of negative binomial models
Authors: Huang Chunmao , Liu Xingwang , Yao Tianyuan , Wang Xiaoqiang 
Published: October 2019

AbstractOverdispersion is a widespread phenomenon in most count data sets. The negative binomial distribution is commonly adopted to fit over-dispersed count data. On the other hand, the mixture model always plays an important role in unsupervised classification. However, when estimating the parameters in the mixture of negative binomial models, the typical generalized Expectation Maximization (EM) algorithm which involves additional iterative procedures in M-step increases computational time. Hence, there remains a need for an efficient algorithm that can speed up the procedure of parameter estimation. For this purpose, here we develop a novel EM algorithm that successfully avoids the typical numerical solution in M-step for the mixture of negative binomial models. We extend further this EM algorithm to the zero-inflated negative binomial model. In the simulation studies, we focus on the runtimes and the classification performance of our proposed algorithm implemented in the mixture of negative binomial model. We found that our proposed EM algorithm can reduce the runtime of maximum likelihood estimation effectively, while achieving the similar classification performance in comparison with the typical EM algorithm. The mixture of negative binomial model and the proposed EM algorithm finally illustrates their good performance of fitting the real earthquake count data.
Volatility spillover and co-movement among Chinese shipping sector stock index, oil futures price, ocean freight charge and exchange rate
Authors: Zhao Zitong , Tansuchat Roengchai 
Published: October 2019

Abstract
This study aims to analyze the co-movement and volatility spillover among four stock markets consist of Chinese shipping sector stock index, oil futures, shipping freight and currency market. We estimate dependence among these four markets using the multivariate copula model. Then we use the VAR model and impulse response function to investigate the volatility spillover among them. The empirical results show that the Gaussian copula is the most appropriate dependence mode as the AIC and BIC of this copula are the lowest when compared to other candidate copula models. The dependence correlation coefficients show a weak volatility dependence among these four markets. In addition, the results of the VAR suggest a spillover effect from shipping stock and oil to freight market.