Modelling of the spread of a potential invasive pest,the Siberian moth (Dendrolimus sibiricus) in Europe

Background： The Siberian moth （Dendrolimus sibiricus） （SM） defoliates several tree species from the genera Larix, Piceo and Abies in northern Asia, east of the Urals. The SM is a potential invasive forest pest in Europe because Europe has several suitable host species and climatic conditions of central and northern Europe are favourable for the SM. Methods： This study developed a grid-based spatio-temporal model for simulating the spread of the SM in case it enters Europe from Russia via border stations. The spread rate was modeled as a function of the spatial distribution of host species, climatic suitability of different locations for the SM, human population density, transportation of moth-carrying material, and flying of moths from tree to tree. Results and conclusions： The simulations showed that the SM is most likely to spread in the forests of northeast Belarus, the Baltic countries, and southern and central Finland. Climatic conditions affected the occurrence of the SM more than human population density and the coverage of suitable host species.

Attention-Based and Time Series Models for Short-Term Forecasting of COVID-19 Spread

The growing number of COVID-19 cases puts pressure on healthcare services and public institutions worldwide.The pandemic has brought much uncertainty to the global economy and the situation in general.Forecasting methods and modeling techniques are important tools for governments to manage critical situations caused by pandemics,which have negative impact on public health.The main purpose of this study is to obtain short-term forecasts of disease epidemiology that could be useful for policymakers and public institutions to make necessary short-term decisions.To evaluate the effectiveness of the proposed attention-based method combining certain data mining algorithms and the classical ARIMA model for short-term forecasts,data on the spread of the COVID-19 virus in Lithuania is used,the forecasts of epidemic dynamics were examined,and the results were presented in the study.Nevertheless,the approach presented might be applied to any country and other pandemic situations.The COVID-19 outbreak started at different times in different countries,hence some countries have a longer history of the disease with more historical data than others.The paper proposes a novel approach to data registration and machine learning-based analysis using data from attention-based countries for forecast validation to predict trends of the spread of COVID-19 and assess risks.

Modeling the spread of hot-rolled Ni-based alloy plates

The width spread of Ni-based alloy plates in the rolling process is studied. An equation for describing therolling spread of Ni-based alloy plate is proposed based on production data and the Bachtinow equation, which cannot fully account for the compositional variability of Ni-based alloys. To address this, a new coefficient for alloying is added to the equation based on production data. By adding alloying coefficients, it is possible to improve the prediction accuracy for the rolling spread of Ni-based alloy plates and thus better control the width of the rolling spread of different steel grades.

The Mathematical Model of Short-Term Forest Fire Spread

In this paper, we establish a mathematical model of the forest fire spread process based on a partial differential equation. We describe the distribution of time field and velocity field in the whole two-dimensional space by vector field theory. And we obtain a continuous algorithm to predict the dynamic behavior of forest fire spread in a short time. We use the algorithm to interpolate the fire boundary by cubic non-uniform rational B-spline closed curve. The fire boundary curve at any time can be simulated by solving the Eikonal equation. The model is tested in theory and in practice. The results show that the model has good accuracy and stability, and it’s compatible with most of the existing models, such as the elliptic model and the cellular automata model.

An Overview on Opinion Spreading Model

Research on opinion spreading has received more and more attention in recent years. This paper focus on make a summary of opinion evolution researches, we first review some classical opinion models, and then introduce the existing result of improvement models from the aspect of opinion space, model parameter, social network and so on. The current study’s limitation and further research are also prospected at the end. By in-depth understand the opinion spreading mechanism so as to guide and control the public opinions, which is very useful and meaningful.

Simulation modelling of potato virus Y spread in relation to initial inoculum and vector activity

Potato virus Y(PVY)is a non-persistent virus that is transmitted by many aphid species and causes significant damage to potato production.We constructed a spatially-explicit model simulating PVY spread in a potato field and used it to investigate possible effects of transmission efficiency,initial inoculum levels,vector behavior,vector abundance,and timing of peak vector activity on PVY incidence at the end of a simulated growing season.Lower PVY incidence in planted seed resulted in lower virus infection at the end of the season.However,when populations of efficient PVY vectors were high,significant PVY spread occurred even when initial virus inoculum was low.Non-colonizing aphids were more important for PVY spread compared to colonizing aphids,particularly at high densities.An early-season peak in the numbers of noncolonizing aphids resulted in the highest number of infected plants in the end of the season,while mid-and late-season peaks caused relatively little virus spread.Our results highlight the importance of integrating different techniques to prevent the number of PVY-infected plants from exceeding economically acceptable levels instead of trying to control aphids within potato fields.Such management plans should be implemented very early in a growing season.

Temperature-Dependent Newtonian Rheology in Advection-Convection Geodynamical Model for Plate Spreading in Eastern Volcanic Zone, Iceland

Geodynamic process as advection-convection of the Mid-Atlantic Ocean Ridge (MAR), that is exposed on land in Iceland is investigated. Advection is considered for the plate spreading velocity. Geodetic GPS data during 2000-2010 is used to estimate plate spreading velocity along a profile in the Eastern Volcanic Zone (EVZ), Iceland striking N102。E, approximately parallel to the NUVEL-1A spreading direction between the Eurasian and North American plates. To predict subsurface mass flow patterns, temperature-dependent Newtonian rheology is considered in the finite-element models (FEM). All models are considered 2-D with steady-state, incompressible rheology whose viscosity depends on the subsurface temperature distribution. The thickness of lithosphere along the profile in the EVZ is identified by 700。C isotherm and 1022 Pa s iso-viscosity, those reach 50 ± 3 km depth at distance of 100 km from rift axis. Geodetic observation and model prediction results show the ~90% of spreading is accommodated within ~45 km of the rift axis in each direction. Model predicts ~8.5 mm.yr-1 subsidence at the surface of rift center when magmatic plumbing is inactive. The rift center (the highest magmatic influx is ~11 mm.yr-1) in model shifts ~10 - 20 km west to generate observed style surface deformation. The spreading velocity, isotherm and depth of isotherm are the driving forces resulting in the surface deformation. These three parameters have more or less equal weight. However, as the center of deformation in the EVZ shifts and most of the subsidence takes place in the volcanic system that is currently the active which is the located of plate axis.

Utilization of Oil Properties to Develop a Spreading Rate Regression Model for Nigerian Crude Oil

The target of this study is to develop a spreading rate regression model capable of predicting rate of spread of Nigerian crude oil spills on water. The major factors responsible for spreading rate of crude oil on water were considered, namely surface tension, viscosity, and specific gravity/American Petroleum Institute degree (0API), all at specified temperature values. The surface tension, viscosity and density parameters were interactively measured under controlled factorial analysis. The spreading rate of each crude oil was determined by artificially spilling them on laboratory calm/stagnant water in a rectangular tank and their averages were also computed. These averages were used to develop a regression model equation for spreading rate. The model developed indicated that an average spreading rate was 3.3528 cm/s at 37.5°C and the predictive regression model is evaluated with the interactions of specific gravity, viscosity and surface tension. It is convenient to state that the model will predict the spread rate of crude oils which possess imputed physicochemical properties having pour point averaged 15.5°C on calm seawater.

Steady-State Analysis of SECIR Rumor Spreading Model in Complex Networks

In this paper, the SECIR rumor spreading model is formulated and analyzed, in which the social education level and the counterattack mechanism are taken into consideration. The results show that improving education level and increasing the ratio of counter are effective in reducing the risk of rumor propagation and enhancing the resistance to rumor propagation.

Modelling the spread of sexually transmitted diseases on scale-free networks

In this paper a new model for the spread of sexually transmitted diseases （STDs） is presented. The dynamic behaviors of the model on a heterogenons scale-free （SF） network are considered, where the absence of a threshold on the SF network is demonstrated, and the stability of the disease-free equilibrium is obtained. Three immunization strategies, uniform immunization, proportional immunization and targeted immunization, are applied in this model. Analytical and simulated results are given to show that the proportional immunization strategy in the model is effective on SF networks.

Modified Ceiling Bounce Model for Computing Path Loss and Delay Spread in Indoor Optical Wireless Systems

This paper proposes modifications to the tradional Ceiling Bounce Model and uses it to characterize diffuse indoor optical wireless channel by analyzing the effect of transceiver position on signal propagation properties. The modified approach uses a combination of the tradional ceiling bounce method and a statistical approach. The effects of different transmitter-receiver separations and height of the ceiling on path loss and delay spread are studied in detail.

Mathematical Modeling of Crown Forest Fire Spread

Mathematical model of forest fire was based on an analysis of known experimental data and using concept and methods from reactive media mechanics. In this paper the assignment and theoretical investigations of the problems of crown forest fire spread in windy condition were carried out. In this context, a study—mathematical modeling—of the conditions of forest fire spreading that would make it possible to obtain a detailed picture of the change in the temperature and component concentration fields with time, and determine as well as the limiting condition of fire propagation in forest with fire break.

A review of numerical modeling research on the marine oil spill

Recently, as the oceanic activities are more and more frequently carried out, marine oil spill accidents bring to enormous harm to the economy and society in China, especially in the Offshore China. Marine oil spill is one kind of serious disasters which severely damages the marine environment. Aiming at the improvement of the emergency response system and response ability for the oil spill, the relative technologies on oil spill response are developed. This paper briefly introduces the developments and achievements of the oil spill numerical models, including the oil spill spreading model, the oil spill transport model, the oil particle model as well as the oil spill weathering model, which provide the theoretic criterions for the future work on the oil spill predicting and response.

Spread-F的经度效应

从三维地理坐标系出发建立模型 ,考虑了地磁倾角和偏角的影响 ,研究Spread F现象的全球分布特点 ,是对以前的研究从赤道地区向中、低纬度地区的推广。从该三维模型中可以看到地磁场的大小和位型的影响 (包括磁倾角和磁偏角的效应 )。由于地磁位型的不同 ,发生率的分布并不具有经度对称性 ,即使在磁赤道附近也如此。在某些特殊的经度和纬度地区 ,会达到发生率的峰值。

A cellular automata model of epidemics of a heterogeneous susceptibility

In this paper we present a model with spatial heterogeneity based on cellular automata （CA）. In the model we consider the relevant heterogeneity of host （susceptible） mixing and the natural birth rate. We divide the susceptible population into three groups according to the immunity of each individual based on the classical susceptible-infectedremoved （SIR） epidemic models, and consider the spread of an infectious disease transmitted by direct contact among humans and vectors that have not an incubation period to become infectious. We test the local stability and instability of the disease-free equilibrium by the spectrum radii of Jacobian. The simulation shows that the structure of the nearest neighbour size of the cell （or the degree of the scale-free networks） plays a very important role in the spread properties of infectious disease. The positive equilibrium of the infections versus the neighbour size follows the third power law if an endemic equilibrium point exists. Finally, we analyse the feature of the infection waves for the homogeneity and heterogeneous cases respectively.

Dynamic properties of epidemic spreading on finite size complex networks

The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS （susceptibleinfected-susceptible） model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.

Virus spreading in wireless sensor networks with a medium access control mechanism

In this paper, an extended version of standard susceptible-infected （SI） model is proposed to consider the influence of a medium access control mechanism on virus spreading in wireless sensor networks. Theoretical analysis shows that the medium access control mechanism obviously reduces the density of infected nodes in the networks, which has been ignored in previous studies. It is also found that by increasing the network node density or node communication radius greatly increases the number of infected nodes. The theoretical results are confirmed by numerical simulations.

Epidemic spreading on networks with vaccination

In this paper, a new susceptible-infected-susceptible （SIS） model on complex networks with imperfect vaccination is proposed. Two types of epidemic spreading patterns （the recovered individuals have or have not immunity） on scale-free networks are discussed. Both theoretical and numerical analyses are presented. The epidemic thresholds related to the vaccination rate, the vaccination-invalid rate and the vaccination success rate on scale-free networks are demonstrated, showing different results from the reported observations. This reveals that whether or not the epidemic can spread over a network under vaccination control is determined not only by the network structure but also by the medicine＇s effective duration. Moreover, for a given infective rate, the proportion of individuals to vaccinate can be calculated theoretically for the case that the recovered nodes have immunity. Finally, simulated results are presented to show how to control the disease prevalence.

Epidemic Propagation: An Automaton Model as the Continuous SIR Model

The use of the SIR model to predict the time evolution of an epidemic is very frequent and has spatial information about its propagation which may be very useful to contrast its spread. In this paper we take a particular cellular automaton model that well reproduces the time evolution of the disease given by the SIR model;setting the automaton is generally an annoying problem because we need to run a lot of simulations, compare them to the solution of the SIR model and, finally, decide the parameters to use. In order to make this procedure easier, we will show a fast method that, in input, requires the parameters of the SIR continuous model that we want to reproduce, whereas, in output, it yields the parameters to use in the cellular automaton model. The problem of computing the most suitable parameters for the reticular model is reduced to the problem of finding the roots of a polynomial Equation.

Numerical analyses of pile performance in laterally spreading frozen ground crust overlying liquefiable soils

Lateral spread of frozen ground crust over liquefied soil has caused extensive bridge foundation damage in the past winter earthquakes.A shake table experiment was conducted to investigate the performance of a model pile in this scenario and revealed unique pile failure mechanisms.The modelling results provided valuable data for validating numerical models.This paper presents analyses and results of this experiment using two numerical modeling approaches： solid-fluid coupled finite element（FE） modeling and the beam-on-nonlinear-Winkler-foundation（BNWF） method.A FE model was constructed based on the experiment configuration and subjected to earthquake loading.Soil and pile response results were presented and compared with experimental results to validate this model.The BNWF method was used to predict the pile response and failure mechanism.A p-y curve was presented for modelling the frozen ground crust with the free-field displacement from the experiment as loading.Pile responses were presented and compared with those of the experiment and FE model.It was concluded that the coupled FE model was effective in predicting formation of three plastic hinges at ground surface,ground crust-liquefiable soil interface and within the medium dense sand layer,while the BNWF method was only able to predict the latter two.