Evolution and Structure of Elementary Physical Particles

This paper is presented in two parts. The first part provides a glimpse of the long-awaited unified theory, which explains the parallel activation of different levels of the universe: intellectual (humans), psychological (animals), biological (vegetation), physical (matter), and cosmological (energies) levels, whereas in the conventional approach, the physical and cosmological levels are grouped into the same category. This paper explains the evolution and structure of elementary physical particles (EPPs) based on the evolution and structure of elementary biological particles (cells). The second part of the paper explains the structure and ingredients of the PPE, which are responsible for the creation of the following four fields, as suggested by the author: visibility, forcibility (magnetism), the fullness field, and the hollowness field. All these fields comprise different unknown cosmological substances. These cosmological fields are present in all physical entities and are responsible for all kinds of physical activations. Finally, the paper explains the evolution of electromagnetic waves, electromagnetic fields, gravitation, and repulsion (repulsive gravitation). The theory is consistent with all previously conducted experiments and systematically unfolds several mysteries, thereby demonstrating the validity of the proposed theory.

Dynamic reactive power planning method for CSP-PV hybrid power generation system

Aiming at the faults of some weak nodes in the concentrated solar power-photovoltaic(CSP-PV)hybrid power generation system,it is impossible to restore the transient voltage only relying on the reactive power regulation capability of the system itself.We propose a dynamic reactive power planning method suitable for CSP-PV hybrid power generation system.The method determines the installation node of the dynamic reactive power compensation device and its compensation capacity based on the reactive power adjustment capability of the system itself.The critical fault node is determined by the transient voltage stability recovery index,and the weak node of the system is initially determined.Based on this,the sensitivity index is used to determine the installation node of the dynamic reactive power compensation device.Dynamic reactive power planning optimization model is established with the lowest investment cost of dynamic reactive power compensation device and the improvement of system transient voltage stability.Furthermore,the component of the reactive power compensation node is optimized by particle swarm optimization based on differential evolution(DE-PSO).The simulation results of the example system show that compared with the dynamic position compensation device installation location optimization method,the proposed method can improve the transient voltage stability of the system under the same reactive power compensation cost.

Solar-stellar astrophysics and dark matter

In this review, we recall how stars contribute to the search for dark matter and the specific role of the Sun. We describe a more complete picture of the solar interior that emerges from neutrino detections, gravity and acoustic mode measurements of the Solar and Heliospheric Observatory （SOHO） satellite, becoming a reference for the most common stars in the Universe. The Sun is a unique star in that we can observe directly the effect of dark matter. The absence of a signature related to Weakly Interacting Massive Particles （WIMPs） in its core disfavors a WIMP mass range below 12 GeV. We give arguments to continue this search on the Sun and other promising cases. We also examine another dark matter candidate, the sterile neutrino, and infer the limitations of the classical structural equations. Open questions on the young Sun, when planets formed, and on its present internal dynamics are finally dis- cussed. Future directions are proposed for the next decade： a better description of the solar core, a generalization to stars coming from seismic missions and a better under- standing of the dynamics of our galaxy which are all crucial keys for understanding dark matter.

PREAPARATION OF CATIONIC LATEXES OF POLY(STYRENE-CO-BUTYL ACRYLATE) AND THEIR PROPERTIES EVOLUTION IN LATEX DILUTION

Cationic latexes were prepared through emulsion copolymerization of styrene （St） and butyl acrylate （BA） with a cationic surfactant, cetyl trimethyl ammonium bromide （CTAB）. Latex properties, including particle size, size distribution, （ potential, surface tension and monomer conversion, were determined for latexes prepared with different CTAB amounts. Evolution of these properties during emulsion polymerization was followed in order to understand the mechanism of the particles formation. Results showed that both particle size and 6＂ potential were function of polymerization time and latex solids. Parallel emulsion polymerizations with cationic, anionic charged initiator and charge-free initiators were also carried out, the latex properties were determined at different polymerization time. All these results were attentively interpreted based on the mechanisms of emulsion polymerization, surfactant adsorption and latex particle stabilization.

Application of complete ensemble intrinsic time-scale decomposition and least-square SVM optimized using hybrid DE and PSO to fault diagnosis of diesel engines

Targeting the mode-mixing problem of intrinsic time-scale decomposition （ITD） and the parameter optimization problem of least-square support vector machine （LSSVM）, we propose a novel approach based on complete ensemble intrinsic time-scale decomposition （CEITD） and LSSVM optimized by the hybrid differential evolution and particle swarm optimization （HDEPSO） algorithm for the identification of the fault in a diesel engine. The approach consists mainly of three stages. First, to solve the mode-mixing problem of ITD, a novel CEITD method is proposed. Then the CEITD method is used to decompose the nonstationary vibration signal into a set of stationary proper rotation components （PRCs） and a residual signal. Second, three typical types of time-frequency features, namely singular values, PRCs energy and energy entropy, and AR model parameters, are extracted from the first several PRCs and used as the fault feature vectors. Finally, a HDEPSO algorithm is proposed for the parameter optimization of LSSVM, and the fault diagnosis results can be obtained by inputting the fault feature vectors into the HDEPSO-LSSVM classifier. Simulation and experimental results demonstrate that the proposed fault diagnosis approach can overcome the mode-mixing problem of ITD and accurately identify the fault patterns of diesel engines.