Transit of asteroids across the 7/3 Kirkwood gap under the Yarkovsky effect

Many asteroids in the main belt are continuously pushed by Yarkovsky effect into regions of different mean motion resonances (MMRs) and then ejected out. They are considered as the principal source of near-Earth objects. We investigate in this paper the effects of the 7/3 MMR with Jupiter (J7/3 MMR) on the transportation of asteroids from Koronis and Eos families that reside respectively on the inner and outer side of the resonance. The fraction of asteroids that make successful crossing through the resonance and the escaping rate from the resonance are found to depend on the Yarkovsky drifting rate, the initial inclination and the migrating direction. The excitation of eccentricity and inclination due to the combined influence from both the resonance and Yarkovsky effect is discussed. Only the eccentricity can be pumped up considerably, and it is attributed mainly to the resonance. In the observational data, family members are also found in the resonance and on the opposite side of the resonance with respect to the corresponding family centre. The existence of these family members is explained using our results of numerical simulations. Finally, the replenishment of asteroids in the J7/3 MMR and the transportation of asteroids by it are discussed.Comment: 10 pages, 10 figures. Accepted by A&

Jointly Modeling Topics and Intents with Global Order Structure

Modeling document structure is of great importance for discourse analysis and related applications. The goal of this research is to capture the document intent structure by modeling documents as a mixture of topic words and rhetorical words. While the topics are relatively unchanged through one document, the rhetorical functions of sentences usually change following certain orders in discourse. We propose GMM-LDA, a topic modeling based Bayesian unsupervised model, to analyze the document intent structure cooperated with order information. Our model is flexible that has the ability to combine the annotations and do supervised learning. Additionally, entropic regularization can be introduced to model the significant divergence between topics and intents. We perform experiments in both unsupervised and supervised settings, results show the superiority of our model over several state-of-the-art baselines.Comment: Accepted by AAAI 201

Implementation and Study of a Novel Doubly Salient Structure Starter/Generator System

AbstractA new type of double salient starter/generator is presented, which can be used in aircraft Low Voltage Direct Current (LVDC), Variable Speed Constant Frequency (VSCF) and High Voltage Direct Current (HVDC) systems. The operational theory of the motor and generator is analyzed, and corresponding control strategies are given. An 18kW prototype has been implemented to verify the system performance. It is shown that the DSM S/G system possesses simple structure, high efficiency and flexible control. It is appropriate to be used for aircraft application

Design and fabrication of robust broadband extreme ultraviolet multilayers

The random layer thickness variations can induce a great deformation of the experimental reflection of broadband extreme ultraviolet multilayer. In order to reduce this influence of random layer thickness fluctuations, the multiobjective genetic algorithm has been improved and used in the robust design of multilayer with a broad angular bandpass. The robust multilayer with a lower sensitivity to random thickness errors have been obtained and the corresponding multilayer mirrors were fabricated. The experimental results of robust Mo/Si multilayer with a wide angular band were presented and analyzed, and the advantage of robust multilayer design was demonstrated

A generalized simplicial model and its application

Higher-order structures, consisting of more than two individuals, provide a new perspective to reveal the missed non-trivial characteristics under pairwise networks. Prior works have researched various higher-order networks, but research for evaluating the effects of higher-order structures on network functions is still scarce. In this paper, we propose a framework to quantify the effects of higher-order structures (e.g., 2-simplex) and vital functions of complex networks by comparing the original network with its simplicial model. We provide a simplicial model that can regulate the quantity of 2-simplices and simultaneously fix the degree sequence. Although the algorithm is proposed to control the quantity of 2-simplices, results indicate it can also indirectly control simplexes more than 2-order. Experiments on spreading dynamics, pinning control, network robustness, and community detection have shown that regulating the quantity of 2-simplices changes network performance significantly. In conclusion, the proposed framework is a general and effective tool for linking higher-order structures with network functions. It can be regarded as a reference object in other applications and can deepen our understanding of the correlation between micro-level network structures and global network functions

Robust approximation of chance constrained optimization with polynomial perturbation

This paper studies a robust approximation method for solving a class of chance constrained optimization problems. The constraints are assumed to be polynomial in the random vector. Under the assumption, the robust approximation of the chance constrained optimization problem can be reformulated as an optimization problem with nonnegative polynomial conic constraints. A semidefinite relaxation algorithm is proposed for solving the approximation. Its asymptotic and finite convergence are proven under some mild assumptions. In addition, we give a framework for constructing good uncertainty sets in the robust approximation. Numerical experiments are given to show the efficiency of our approach.Comment: 25 page