Epidemic spreading induced by diversity of agents' mobility

In this paper, we study into the impact of the preference of an individual for public transport on the spread of infectious disease, through a quantity known as the public mobility. Our theoretical and numerical results based on a constructed model reveal that if the average public mobility of the agents is fixed, an increase in the diversity of the agents' public mobility reduces the epidemic threshold, beyond which an enhancement in the rate of infection is observed. Our findings provide an approach to improve the resistance of a society against infectious disease, while preserving the utilization rate of the public transportation system.Comment: 8 pages, 5 figure

Dynamic characteristics analysis and optimization for lateral plates of the vibration screen

To solve the problem of damage due to large dynamic stress of the lateral plates during working process of the vibration screen, it is necessary to calculate and analyze natural modes and distribution of dynamic stress of lateral plates, which is shown in results that the lateral plate structure shall be optimized. In this paper, with the total weight of the lateral plates for the banana-shaped vibration screen as the optimization objective, frequency constraints as the status variables, optimization for multi-frequency constraints is conducted based on the improved genetic algorithm. Next, a mathematical model of structure parameter optimization for the lateral plates of the vibration screen under frequency constraints is established to carry out optimization design in order to obtain a structure with smaller dynamic stress and lower weight. Sensitivity analysis is added into the improved genetic algorithm, and the optimization efficiency is increased simultaneously. The structure frequency is optimized by means of the improved genetic algorithm. Then, a modal experiment is carried out to the entire vibration screen so as to verify reliability of the finite element model, and the natural characteristics of the vibration screen before and after optimization are analyzed, and the top 6 orders natural frequency and vibration modes of the entire vibration screen are calculated, so as to indicate that optimized vibration screen is improved in terms of material saving, stiffness and stability. In addition, noise is directly related to vibration. As a result, the change of the vibration screen should be also analyzed. Noise of the vibration screen is also tested by sound array technology. Results showed that the radiated noise is reduced after optimization, and optimization in this paper is feasible

Weakly Supervised Audio Source Separation via Spectrum Energy Preserved Wasserstein Learning

Separating audio mixtures into individual instrument tracks has been a long standing challenging task. We introduce a novel weakly supervised audio source separation approach based on deep adversarial learning. Specifically, our loss function adopts the Wasserstein distance which directly measures the distribution distance between the separated sources and the real sources for each individual source. Moreover, a global regularization term is added to fulfill the spectrum energy preservation property regardless separation. Unlike state-of-the-art weakly supervised models which often involve deliberately devised constraints or careful model selection, our approach need little prior model specification on the data, and can be straightforwardly learned in an end-to-end fashion. We show that the proposed method performs competitively on public benchmark against state-of-the-art weakly supervised methods

Mono-everything: combined limits on dark matter production at colliders from multiple final states

Searches for dark matter production at particle colliders are complementary to direct-detection and indirect-detection experiments, and especially powerful for small masses, $m_\chi<100$ GeV. An important collider dark matter signature is due to the production of a pair of these invisible particles with the initial-state radiation of a standard model particle. Currently, collider searches use individual and nearly orthogonal final states to search for initial-state jets, photons or massive gauge bosons. We combine these results across final states and across experiments to give the strongest current collider-based limits in the context of effective field theories, and map these to limits on dark matter interactions with nuclei and to dark matter self-annhiliation