Applicability of Relativistic Point-Coupling Models to Neutron Star Physics

Comparing with a wide range of covariant energy density functional models based on the finite-range meson-exchange representation, the relativistic mean-field models with the zero-range contact interaction, namely the relativistic point-coupling models, are still infrequent to be utilized in establishing nuclear equation of state (EoS) and investigating neutron star properties, although comprehensive applications and achievements of them in describing many nuclear properties both in ground and exited states are mature. In this work, the EoS of neutron star matter is established constructively in the framework of the relativistic point-coupling models to study neutron star physics. Taking two selected functionals DD-PC1 and PC-PK1 as examples, nuclear symmetry energies and several neutron star properties including proton fractions, mass-radius relations, the core-crust transition density, the fraction of crustal moment of inertia and dimensionless tidal deformabilities are discussed. A suppression of pressure of neutron star matter found in the functional PC-PK1 at high densities results in the difficulty of its prediction when approaching to the maximum mass of neutron stars. In addition, the divergences between two selected functionals in describing neutron star quantities mentioned above are still large, ascribing to the less constrained behavior of these functionals at high densities. Then it is expected that the constraints on the dense matter EoS from precise and massive modern astronomical observations, such as the tidal-deformabilities taken from gravitational-wave events, would be essential to improve the parameterizing of the relativistic point-coupling models.Comment: To appear in the AIP Proceedings of the Xiamen-CUSTIPEN Workshop on the EOS of Dense Neutron-Rich Matter in the Era of Gravitational Wave Astronomy, Jan. 3-7, Xiamen, Chin

A Research of Regional Difference in R&D Activities in GUANGDONG, PR China

According to the 2008 economic census yearbook in Guangdong, it explores the reasons why the development of R&D is different in different area. According to the data, it analyses the R&D activity using factor analysis and clustering analysis, the results show that R&D activity level is directly associated with the foundation and the total quantity of R&D activities, the use efficiency of R&D expenditure as well as the output ability of R&D staff. Based on the results, the countermeasures are given. Key words: R&D activity; Regional difference; Factor analysis; Clustering analysi

Pricing European Call Currency option based on Adaptive Fuzzy Numbers with Possibilistic Mean

In this paper we use the fuzzy estimators based on confidence intervals in order to estimate the volatility of currency exchange rate having sample data. We model the uncertainty of the characteristics such as interest rates and volatility using adaptive fuzzy numbers and replace the fuzzy currency option price and the fuzzy volatility by the possibilistic mean value. Furthermore, a numerical example is presented, and we get the expected prices which depend on given degree of confidence. Key words: Currency Option; Option Pricing; Possibilistic Mean Value; Fuzzy Volatility; G-K Mode

A Fuzzy LP Approach to Option Portfolio

Abstract: Owing to the fluctuation of financial market from time to time,the volatility and stock price may occur imprecisely in the real world. Therefore, it is natural to consider the fuzzy volatility and fuzzy stock price in the financial market. Under these assumptions,the theoretical price deduced by Black–Scholes formula are will turn into the fuzzy numbers, and the derivatives, called the Greek parameters delta, gamma, of the BS model are also fuzzy numbers. An option portfolio considering these fuzzy numbers will be more accord with actual situations. In this paper, we propose a fuzzy programming model of option portfolio based a ranking criterion of fuzzy numbers, which the fuzzy option portfolio model is converted into a classical linear programming problem. Finally, a numerical example is given to illustrate the validity of the method. Key words: Ranking Criterion; Option portfolio; Fuzzy Linear Programming; Delta-Gamma Neutra

How to Build Practice Teaching System of Financial Mathematics in Local Universities

In this paper, the writer combined the experience in financial mathematics direction teaching with the results of the survey of tracking graduates, and analyzed the necessity for local colleges to carry out practical teaching in financial mathematics teaching. What’s more, the writer also proposes some suggestion in establishing practical teaching system of financial mathematics.Key words: Financial mathematics; Practical teaching; Teaching mod

The Discussion on the Mode of Undergraduate Tutorial System for Financial Mathematics Students of Local Universities

With the decreasing in the number of college students, the students quality of local university is also decreasing. This paper proposes the mode of tutor system for financial mathematics students of local universities. And it is analysis the necessity and the importance of tutor system for teaching, employment, etc. we also propose some suggestions on how to execute tutor system

The Application of Probability Method on Mathematical Analysis

This paper summarizes the applications of probabilitymethod on mathematical analysis, including a class of generalized integra1 and acquiring the sum of infinite series £ so that contact up the mathematical analysis and probability and statistics knowledge ,explain the inner contacts among different branches of mathematics in some discussions.Key words: Probability method; Mathematical analysis; Generalized integral; The sum of infinite serie

In situ structures of the segmented genome and RNA polymerase complex inside a dsRNA virus.

Viruses in the Reoviridae, like the triple-shelled human rotavirus and the single-shelled insect cytoplasmic polyhedrosis virus (CPV), all package a genome of segmented double-stranded RNAs (dsRNAs) inside the viral capsid and carry out endogenous messenger RNA synthesis through a transcriptional enzyme complex (TEC). By direct electron-counting cryoelectron microscopy and asymmetric reconstruction, we have determined the organization of the dsRNA genome inside quiescent CPV (q-CPV) and the in situ atomic structures of TEC within CPV in both quiescent and transcribing (t-CPV) states. We show that the ten segmented dsRNAs in CPV are organized with ten TECs in a specific, non-symmetric manner, with each dsRNA segment attached directly to a TEC. The TEC consists of two extensively interacting subunits: an RNA-dependent RNA polymerase (RdRP) and an NTPase VP4. We find that the bracelet domain of RdRP undergoes marked conformational change when q-CPV is converted to t-CPV, leading to formation of the RNA template entry channel and access to the polymerase active site. An amino-terminal helix from each of two subunits of the capsid shell protein (CSP) interacts with VP4 and RdRP. These findings establish the link between sensing of environmental cues by the external proteins and activation of endogenous RNA transcription by the TEC inside the virus

Joint Learning of Network Topology and Opinion Dynamics Based on Bandit Algorithms

We study joint learning of network topology and a mixed opinion dynamics, in which agents may have different update rules. Such a model captures the diversity of real individual interactions. We propose a learning algorithm based on multi-armed bandit algorithms to address the problem. The goal of the algorithm is to find each agent's update rule from several candidate rules and to learn the underlying network. At each iteration, the algorithm assumes that each agent has one of the updated rules and then modifies network estimates to reduce validation error. Numerical experiments show that the proposed algorithm improves initial estimates of the network and update rules, decreases prediction error, and performs better than other methods such as sparse linear regression and Gaussian process regression