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

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

Chinese herbal injections in combination with radiotherapy for advanced pancreatic cancer: A systematic review and network meta-analysis.

Advanced pancreatic cancer (APC) is a fatal disease with limited treatment options. This study aims to evaluate the effectiveness and safety of different Chinese herbal injections (CHIs) as adjuvants for radiotherapy (RT) in APC and compare their treatment potentials using network meta-analysis. We systematically searched three English and four Chinese databases for randomized controlled trials (RCTs) from inception to July 25, 2023. The primary outcome was the objective response rate (ORR). Secondary outcomes included Karnofsky performance status (KPS) score, overall survival (OS), and adverse events (AEs). The treatment potentials of different CHIs were ranked using the surface under the cumulative ranking curve (SUCRA). The Cochrane RoB 2 tool and CINeMA were used for quality assessment and evidence grading. Eighteen RCTs involving 1199 patients were included. Five CHIs were evaluated. Compound Kushen injection (CKI) combined with RT significantly improved ORR compared to RT alone (RR 1.49, 95 % CrI 1.21-1.86). Kanglaite (KLT) plus RT (RR 1.58, 95 % CrI 1.20-2.16) and CKI plus RT (RR 1.49, 95 % CrI 1.16-1.95) were associated with improved KPS score compared to radiation monotherapy, with KLT+RT being the highest rank (SUCRA 72.28 %). Regarding AEs, CKI plus RT was the most favorable in reducing the incidence of leukopenia (SUCRA 90.37 %) and nausea/vomiting (SUCRA 85.79 %). CKI may be the optimal choice of CHIs to combine with RT for APC as it may improve clinical response, quality of life, and reduce AEs. High-quality trials are necessary to establish a robust body of evidence. PROSPERO, CRD42023396828. [Abstract copyright: © 2023 Korea Institute of Oriental Medicine. Published by Elsevier B.V.