Probing signatures of bounce inflation with current observations

The aim of this paper is to probe the features of the bouncing cosmology with the current observational data. Basing on bounce inflation model, with high derivative term, we propose a general parametrization of primordial power spectrum which includes the typical bouncing parameters, such as bouncing time-scale, and energy scale. By applying Markov Chain Monto Carlo analysis with current data combination of Planck 2015, BAO and JLA, we report the posterior probability distributions of the parameters. We find that, bouncing models can well explain CMB observations, especially the deficit and oscillation on large scale in TT power spectrum.Comment: 17 pages, 8 figure

Self-organization and phase transition in financial markets with multiple choices

Market confidence is essential for successful investing. By incorporating multi-market into the evolutionary minority game, we investigate the effects of investor beliefs on the evolution of collective behaviors and asset prices. When there exists another investment opportunity, market confidence, including overconfidence and under-confidence, is not always good or bad for investment. The roles of market confidence is closely related to market impact. For low market impact, overconfidence in a particular asset makes an investor become insensitive to losses and a delayed strategy adjustment leads to a decline in wealth, and thereafter, one's runaway from the market. For high market impact, under-confidence in a particular asset makes an investor over-sensitive to losses and one's too frequent strategy adjustment leads to a large fluctuation in asset prices, and thereafter, a decrease in the number of agents. At an intermediate market impact, the phase transition occurs. No matter what the market impact is, an equilibrium between different markets exists, which is reflected in the occurrence of similar price fluctuations in different markets. A theoretical analysis indicates that such an equilibrium results from the coupled effects of strategy updating and shift in investment. The runaway of the agents trading a specific asset will lead to a decline in the asset price volatility and such a decline will be inhibited by the clustering of the strategies. A uniform strategy distribution will lead to a large fluctuation in asset prices and such a fluctuation will be suppressed by the decrease in the number of agents in the market. A functional relationship between the price fluctuations and the numbers of agents is found

The research of particle sieving under a creative mode of vibration

In order to improve screening performance, a creative vibrating screen with a new mode coupling of translation and swing was proposed which inspired by the manner of manual sieving. A mechanical model of the new motion was established. The discrete element method (DEM) was used to study the particulate systems with the complex particle size distribution considering interactions between particles. This paper simulated the screening process with the new compound trace to calculate screening efficiency in different vibration parameters. Vibration parameters mainly encompass swing angle, swing frequency, translation frequency, translation direction angle, and amplitude. The functional relationships between screening efficiency and vibration parameters were presented based on 3D-DEM simulations. The results show that each vibration parameter has an optimum value in simulations. The relationships and optimal parameters offer insights to vibrating screen design, manufacture and installation. Compared to single translation or swing trace, screening efficiency were improved. The laboratory-scale vibrating screen with transformation parameters was created for validating the screening principle from the simulation data

Multifractal Modelling of Aircraft Echoes from Low-resolution Radars Based on Structural Functions

As a kind of complex targets, the nonrigid vibration and attitude change of an aircraft as well as the rotation of its rotating parts will induce complex nonlinear modulation on its echo from low-resolution radars. If one performs the multifractal analysis of measures on an aircraft echo, it may offer a fine description of the dynamic characteristics which induce the echo structure. On basis of introducing multifractal theory based on structural functions, the paper models real recorded aircraft echo data from a low-resolution radar by using the random walk process and the incremental process respectively, and investigates the application of echo multifractal characteristics in aircraft target classification with low-resolution radars. The analysis shows that aircraft echoes from low-resolution radars have clear multifractal characteristics, and one should take an aircraft echo series as a random walk process to perform the multifractal analysis. The experimental results validate the classification method based on multifractal signatures.Defence Science Journal, 2013, 63(5), pp.515-520, DOI:http://dx.doi.org/10.14429/dsj.63.377

The study on magnetism and solid coupling vibration and its electromagnetic force characteristics in stator system of electrical machine

The air-gap electromagnetic force is not the unique excitation which excites magnetism and solid coupling vibration on stator system of asynchronous machine. Besides, there should be a ponderomotive force as an internal electromagnetic excitation in stator core. Therefore, the magnetism and solid coupling vibration equation with both of the forces was obtained for the electromagnetically excited vibration on stator system of electrical machine. Based on Maxwell equations and the electromagnetic constitutive relation, the expressions of the electromagnetic field and force were derived by solving the eddy equation and the boundary conditions. With numerical calculation, the influences of geometric parameters on the electromagnetic field and forces were analyzed. The electromagnetic excitations of magnetism and solid coupling vibration on stator system were improved by the analysis of ponderomotive force in the stator core. Furthermore, the conclusions provide a theoretical basis for the electromagnetic design of asynchronous machine

A generalized public goods game with coupling of individual ability and project benefit

Facing a heavy task, any single person can only make a limited contribution and team cooperation is needed. As one enjoys the benefit of the public goods, the potential benefits of the project are not always maximized and may be partly wasted. By incorporating individual ability and project benefit into the original public goods game, we study the coupling effect of the four parameters, the upper limit of individual contribution, the upper limit of individual benefit, the needed project cost and the upper limit of project benefit on the evolution of cooperation. Coevolving with the individual-level group size preferences, an increase in the upper limit of individual benefit promotes cooperation while an increase in the upper limit of individual contribution inhibits cooperation. The coupling of the upper limit of individual contribution and the needed project cost determines the critical point of the upper limit of project benefit, where the equilibrium frequency of cooperators reaches its highest level. Above the critical point, an increase in the upper limit of project benefit inhibits cooperation. The evolution of cooperation is closely related to the preferred group-size distribution. A functional relation between the frequency of cooperators and the dominant group size is found

Multi-Constraint Molecular Generation using Sparsely Labelled Training Data for Localized High-Concentration Electrolyte Diluent Screening

Recently, machine learning methods have been used to propose molecules with desired properties, which is especially useful for exploring large chemical spaces efficiently. However, these methods rely on fully labelled training data, and are not practical in situations where molecules with multiple property constraints are required. There is often insufficient training data for all those properties from publicly available databases, especially when ab-initio simulation or experimental property data is also desired for training the conditional molecular generative model. In this work, we show how to modify a semi-supervised variational auto-encoder (SSVAE) model which only works with fully labelled and fully unlabelled molecular property training data into the ConGen model, which also works on training data that have sparsely populated labels. We evaluate ConGen's performance in generating molecules with multiple constraints when trained on a dataset combined from multiple publicly available molecule property databases, and demonstrate an example application of building the virtual chemical space for potential Lithium-ion battery localized high-concentration electrolyte (LHCE) diluents