Epidemic modelling by ripple-spreading network and genetic algorithm

Mathematical analysis and modelling is central to infectious disease epidemiology. This paper, inspired by the natural ripple-spreading phenomenon, proposes a novel ripple-spreading network model for the study of infectious disease transmission. The new epidemic model naturally has good potential for capturing many spatial and temporal features observed in the outbreak of plagues. In particular, using a stochastic ripple-spreading process simulates the effect of random contacts and movements of individuals on the probability of infection well, which is usually a challenging issue in epidemic modeling. Some ripple-spreading related parameters such as threshold and amplifying factor of nodes are ideal to describe the importance of individuals’ physical fitness and immunity. The new model is rich in parameters to incorporate many real factors such as public health service and policies, and it is highly flexible to modifications. A genetic algorithm is used to tune the parameters of the model by referring to historic data of an epidemic. The well-tuned model can then be used for analyzing and forecasting purposes. The effectiveness of the proposed method is illustrated by simulation results

Finite-Time Synchronizing Fractional-Order Chaotic Volta System with Nonidentical Orders

We investigate synchronizing fractional-order Volta chaotic systems with nonidentical orders in finite time. Firstly, the fractional chaotic system with the same structure and different orders is changed to the chaotic systems with identical orders and different structure according to the property of fractional differentiation. Secondly, based on the lemmas of fractional calculus, a controller is designed according to the changed fractional chaotic system to synchronize fractional chaotic with nonidentical order in finite time. Numerical simulations are performed to demonstrate the effectiveness of the method

Finite-Time Synchronizing Fractional-Order Chaotic Volta System with Nonidentical Orders

We investigate synchronizing fractional-order Volta chaotic systems with nonidentical orders in finite time. Firstly, the fractional chaotic system with the same structure and different orders is changed to the chaotic systems with identical orders and different structure according to the property of fractional differentiation. Secondly, based on the lemmas of fractional calculus, a controller is designed according to the changed fractional chaotic system to synchronize fractional chaotic with nonidentical order in finite time. Numerical simulations are performed to demonstrate the effectiveness of the method

Synchronization of fractional chaotic complex networks with delays

summary:The synchronization of fractional-order complex networks with delay is investigated in this paper. By constructing a novel Lyapunov-Krasovskii function $V$ and taking integer derivative instead of fractional derivative of the function, a sufficient criterion is obtained in the form of linear matrix inequalities to realize synchronizing complex dynamical networks. Finally, a numerical example is shown to illustrate the feasibility and effectiveness of the proposed method

Understanding the phenomenological and intrinsic blazar sequence using a simple scaling model

The blazar sequence, including negative correlations between radiative luminosity $L_{\rm rad}$ and synchrotron peak frequency $\nu$, and between Compton dominance $Y$ and $\nu$, is widely adopted as a phenomenological description of spectral energy distributions (SEDs) of blazars, although its underlying cause is hotly debated. In particular, these correlations turn positive after correcting Doppler boosting effect. In this work, we revisit the phenomenological and intrinsic blazar sequence with three samples, which are historical sample (SEDs are built with historical data), quasi-simultaneous sample (SEDs are built with quasi-simultaneous data) and Doppler factor corrected sample (a sample with available Doppler factors), selected from literature. We find that phenomenological blazar sequence holds in historical sample, but does not exist in quasi-simultaneous sample, and intrinsic correlation between $L_{\rm rad}$ and $\nu$ becomes positive in Doppler factor corrected sample. We also analyze if the blazar sequence still exists in subclasses of blazars, i.e., flat-spectrum radio quasars and BL Lacertae objects, with different values of $Y$. To interpret these correlations, we apply a simple scaling model, in which physical parameters of the dissipation region are connected to the location of the dissipation region. We find that the model generated results are highly sensitive to the chosen ranges and distributions of physical parameters. Therefore, we suggest that even though the simple scaling model can reproduce the blazar sequence under specific conditions that have been fine-tuned, such results may not have universal applicability. Further consideration of a more realistic emission model is expected.Comment: Accepted for publication in MNRAS (14 pages, 6 figures, 3 tables

Observation of orbital ordering and origin of the nematic order in FeSe

To elucidate the origin of nematic order in FeSe, we performed field-dependent 77Se-NMR measurements on single crystals of FeSe. We observed orbital ordering from the splitting of the NMR spectra and Knight shift and a suppression of it with magnetic field B0 up to 16 T applied parallel to the Fe-planes. There is a significant change in the distribution and magnitude of the internal magnetic field across the orbital ordering temperature Torb while stripe-type antiferromagnetism is absent. Giant antiferromagnetic (AFM) spin fluctuations measured by the NMR spin-lattice relaxation are gradually developed starting at ~ 40 K, which is far below the nematic ordering temperature Tnem. These results demonstrate that orbital ordering is the origin of the nematic order, and the AFM spin fluctuation is the driving mechanism of superconductivity in FeSe under the presence of the nematic order.Comment: 6 pages, 4 figure