Pattern dynamics and bifurcation in delayed SIR network with diffusion network

The spread of infectious diseases often presents the emergent properties,which leads to more dificulties in prevention and treatment.In this paper,the SIR model with both delay and network is investigated to show the emergent properties of the infectious diseases'spread.The stability of the SIR model with a delay and two delay is analyzed to illustrate the effect of delay on the periodic outbreak of the epidemic.Then the stability conditions of Hopf bifurcation are derived by using central manifold to obtain the direction of bifurcation,which is vital for the generation of emergent behavior.Also,numerical simulation shows that the connection probability can affect the types of the spatio-temporal patterns,further induces the emergent properties.Finally,the emergent properties of COVID-19 are explained by the above results.

Progress of Pattern Dynamics in Plasma Waves

This paper is concerned with the pattern dynamics of the generalized nonlinear Schrodinger equations(NSEs)relatedwith various nonlinear physical problems in plasmas.Our theoretical and numerical results show that the higher-order nonlinear effects,acting as a Hamiltonian perturbation,break down the NSE integrability and lead to chaotic behaviors.Correspondingly,coherent structures are destroyed and replaced by complex patterns.Homoclinic orbit crossings in the phase space and stochastic partition of energy in Fourier modes show typical characteristics of the stochastic motion.Our investigations show that nonlinear phenomena,such as wave turbulence and laser filamentation,are associated with the homoclinic chaos.In particular,we found that the unstable manifolds W(u)possessing the hyperbolic fixed point correspond to an initial phase θ=45° and 225° ,and the stable manifolds W(s)correspond toθ=135° and 315° .

Dynamic evolution patterns of the degree of ground resistivity anisotropy and the sets mogenic process

Following a new train of thinking, this paper has explored first the potential information in the ground resistivitydata observed by the existing geoelectric observation system, investigated and proposed a new dimensionlessgeoelectric precursor factor, the degree of ground resistivity anisotropy, S, and studied the characteristics of dynamic evolution pattern of S during the seismogenic process. The results show that, during the seismogenic process, the degree of ground resistivity anisotropy (S) displays h process of 'normal' → 'abnormal strengthening(amplitude, range)' → 'abnormal weakening'→ 'earthquake occurrence'→ 'normal'. The earthquake wouldoccur at the time when the S value has entered the late stage of strengthening and turns to weaken and in the gradient belt on the margin ofS anomaly region. The dynamic evolution pattern ofS reflects the changes of the tectonicstress field during the seismogenic process. Therefore, it would be possible to trace the process of earthquake generation and occurrence from the dynamic evolution pattern ofS so as to service eaJ'thquake prediction.

Research on dynamics patterns and parameter characters of crustal deformation field before and after strong earthquake

Based on the dynamic monitoring data of crustal deformation, the parameter evolution for the dynamics pattern and fractal dimension of crustal deformation field and the integral activity level of many faults etc. before and after the Tangshan (1976) and Lijiang (1996) strong earthquakes and others are studied by using the method of pattern dynamics. It is exposed that two time space characters, the ordered dimension drop of the deformation field and the accelerated motion of multi fault before an earthquake, are probably caused by the deformation localization and fault softening after the seismogenic process enters the nonlinear stage. They could be an important seismic precursor if they occurred repeatedly before strong earthquakes.

A Study on the Prediction Method of Strong Earthquakes Based on Dynamic Seismicity Patterns with Dynamic Implications

Seismic gap method is one of the effective earthquake prediction methods using seismicity patterns. However, this method has some limitations and uncertainty when using it singly in predicting earthquakes. This paper puts forward the prediction method using the dynamic seismicity pattern with dynamic implications. This method considers the formation and evolution of the seismic gap on the basis of plate movement and structural characteristics. Through analysis of 26 cases of earthquakes of MS≥5.0 occurring in East China and South China, this paper obtains the relationship between the main shock with seismic gap and active fault's location, as well as the relationship between the seismic gap and location and strike of active faults. Meanwhile, this paper provides a dynamic explanation of the differences in the formation and evolution patterns of the seismic gap between the two regions, thus providing the physical basis for and reducing the uncertainty of predicting earthquakes using the seismic gap method.

Nanoindentation Models of Monolayer Graphene and Graphyne under Point Load Pattern Studied by Molecular Dynamics

Molecular dynamics simulations are performed to study the nanoindentation models of monolayer suspended graphene and graphyne. Fullerenes are selected as indenters. Our results show that Young＇s modulus of monolayer-thick graphyne is almost half of that of graphene, which is estimated to be 0.50 TPa. The mechanical properties of graphene and graphyne are different in the presence of strain. A pre-tension has an important effect on the mechanical properties of a membrane. Both the pre-tension and Young＇s modulus plots demonstrate index behavior. The toughness of graphyne is stronger than that of graphene due to Young＇s modulus magnitude. Young＇s moduli of graphene and graphyne are almost independent of the size ratio of indenter to membrane.

Analysis of dynamic of two-phase flow in small channel based on phase space reconstruction combined with data reduction sub-frequency band wavelet

A new method of nonlinear analysis is established by combining phase space reconstruction and data reduction sub-frequency band wavelet. This method is applied to two types of chaotic dynamic systems(Lorenz and Rssler) to examine the anti-noise ability for complex systems. Results show that the nonlinear dynamic system analysis method resists noise and reveals the internal dynamics of a weak signal from noise pollution. On this basis, the vertical upward gas–liquid two-phase flow in a 2 mm × 0.81 mm small rectangular channel is investigated. The frequency and energy distributions of the main oscillation mode are revealed by analyzing the time–frequency spectra of the pressure signals of different flow patterns. The positive power spectral density of singular-value frequency entropy and the damping ratio are extracted to characterize the evolution of flow patterns and achieve accurate recognition of different vertical upward gas–liquid flow patterns(bubbly flow:100%, slug flow: 92%, churn flow: 96%, annular flow: 100%). The proposed analysis method will enrich the dynamics theory of multi-phase flow in small channel.

Geometrically-Compatible Dislocation Pattern and Modeling of Crystal Plasticity in Body-Centered Cubic(BCC)Crystal at Micron Scale Dedicated to Professor Karl Stark Pister for his 95th birthday

The microstructure of crystal defects,e.g.,dislocation patterns,are not arbitrary,and it is possible that some of them may be related to the microstructure of crystals itself,i.e.,the lattice structure.We call those dislocation patterns or substructures that are related to the corresponding crystal microstructure as the Geometrically Compatible Dislocation Patterns(GCDP).Based on this notion,we have developed a Multiscale Crystal Defect Dynamics(MCDD)to model crystal plasticity without or with minimum empiricism.In this work,we employ the multiscale dislocation pattern dynamics,i.e.,MCDD,to simulate crystal plasticity in body-centered cubic(BCC)single crystals,mainlyα-phase Tantalum(α-Ta)single crystals.The main novelties of the work are:(1)We have successfully simulated crystal plasticity at micron scale without any empirical parameter inputs;(2)We have successfully employed MCDD to perform direct numerical simulation of inelastic hysteresis of the BCC crystal;(3)We have used MCDD crystal plasticity model to demonstrate the size-effect of crystal plasticity and(4)We have captured cross-slip which may lead to size-effect.

Dynamical pattern recognition for univariate time series and its application to an axial compressor

In this paper, a learning and recognition approach is proposed for univariate time series composed of output measurements of general nonlinear dynamical systems. Firstly, a class of dynamical systems in the canonical form is derived to describe the univariate time series by introducing coordinate transformation. An observer-based deterministic learning technique is then adopted to achieve dynamical modeling of the associated transformed systems of the training univariate time series, and the modeling results in the form of radial basis function network (RBFN) models are stored in a pattern library. Subsequently, multiple observer-based dynamical estimators containing the RBFN models in the pattern library are constructed for a test univariate time series, and a recognition decision scheme is proposed by the derived recognition indicator. On this basis, more concise recognition conditions are provided, which is beneficial for verifying the recognition results. Finally, simulation studies on the Rossler system and aero-engine stall warning verify the effectiveness of the proposed approach.

Formation Dynamics and Quantitative Prediction of Hydrocarbons of the Superpressure System in the Dongying Sag

Based on the theory of formation dynamics of oil/gas pools, the Dongying sag can be divided into three dynamic systems regarding the accumulation of oil and gas： the superpressure closed system, the semi-closed system and the normal pressure open system. Based on the analysis of genesis of superpressure in the superpressure closed system and the rule of hydrocarbon expulsion, it is found that hydrocarbon generation is related to superpressure, which is the main driving factor of hydrocarbon migration. Micro fractures formed by superpressure are the main channels for hydrocarbon migration. There are three dynamic patterns for hydrocarbon expulsion： free water drainage, hydrocarbon accumulation and drainage through micro fissures. In the superpressure closed system, the oil-driving-water process and oil/gas accumulation were completed in lithologic traps by way of such two dynamic patterns as episodic evolution of superpressure systems and episodic pressure release of faults. The oil-bearing capacity of lithologic traps is intimately related to reservoir-forming dynamic force. Quantitative evaluation of dynamic conditions for pool formation can effectively predict the oil-bearing capability of traps.

Multiphase convolutional dense network for the classification of focal liver lesions on dynamic contrast-enhanced computed tomography

BACKGROUND The accurate classification of focal liver lesions(FLLs)is essential to properly guide treatment options and predict prognosis.Dynamic contrast-enhanced computed tomography(DCE-CT)is still the cornerstone in the exact classification of FLLs due to its noninvasive nature,high scanning speed,and high-density resolution.Since their recent development,convolutional neural network-based deep learning techniques has been recognized to have high potential for image recognition tasks.AIM To develop and evaluate an automated multiphase convolutional dense network(MP-CDN)to classify FLLs on multiphase CT.METHODS A total of 517 FLLs scanned on a 320-detector CT scanner using a four-phase DCECT imaging protocol(including precontrast phase,arterial phase,portal venous phase,and delayed phase)from 2012 to 2017 were retrospectively enrolled.FLLs were classified into four categories:Category A,hepatocellular carcinoma(HCC);category B,liver metastases;category C,benign non-inflammatory FLLs including hemangiomas,focal nodular hyperplasias and adenomas;and category D,hepatic abscesses.Each category was split into a training set and test set in an approximate 8:2 ratio.An MP-CDN classifier with a sequential input of the fourphase CT images was developed to automatically classify FLLs.The classification performance of the model was evaluated on the test set;the accuracy and specificity were calculated from the confusion matrix,and the area under the receiver operating characteristic curve(AUC)was calculated from the SoftMax probability outputted from the last layer of the MP-CDN.RESULTS A total of 410 FLLs were used for training and 107 FLLs were used for testing.The mean classification accuracy of the test set was 81.3%(87/107).The accuracy/specificity of distinguishing each category from the others were 0.916/0.964,0.925/0.905,0.860/0.918,and 0.925/0.963 for HCC,metastases,benign non-inflammatory FLLs,and abscesses on the test set,respectively.The AUC(95%confidence interval)for differentiating each category from the others was 0.92(0.837-0.992),0.99(0.967-1.00),0.88(0.795-0.955)and 0.96(0.914-0.996)for HCC,metastases,benign non-inflammatory FLLs,and abscesses on the test set,respectively.CONCLUSION MP-CDN accurately classified FLLs detected on four-phase CT as HCC,metastases,benign non-inflammatory FLLs and hepatic abscesses and may assist radiologists in identifying the different types of FLLs.

AUTOMATIC ORDER-DETERMINATION OF TRANSIENT IN--PLANE DISPLACEMENT MOIRE PATTERNS

This paper presents a fringe-carrier method that eliminates sign ambiguity of transient moire fringes which can be used to automatically determine the relative orders. A fringe carrier is preset in the static state of the specimen and the dynamic in-plane displacements are recorded as the modulation to the frequency of the carrier fringes when the specimen is loaded by impact. According to a modulating criterion developed from the modulation degree, the fringes of the transient moire patterns keep monotonical in orders so that they can be automatically encoded in grey levels by a digital image system. The moire orders purely caused by dynamic loadings are evaluated by subtracting the grey-value of the unmodulated carrier image from that of the modulated carrier images encoded by their orders. With the subtracted moire orders the strain components can be obtained, and, correspondingly, the histograms of dynamic displacement moire images are shown with order variation by image-difference.

Can small-scale altitudinal gradients predict spatial and temporal patterns in tropical forests?

In tropical montane forests,compositional and structural changes are commonly driven by broad-scale altitudinal variation.Here,given the lack of knowledge on small-scale vegetation changes and temporal dynamics,we address the effects of small-scale variations in soil and altitude on tree community structure,temporal dynamics and phylogenetic diversity in a semi-deciduous tropical forest of the Atlantic Forest Domain,southeastern Brazil.In 2010 and 2015 we sampled thirty plots of 400 m^(2),set up along an altitudinal gradient between 1000 and 1500 m a.s.I..In each plot,we collected soil samples for chemical and textural analyses.We fitted linear models to test the effects of altitude and soil on community dynamics and phylogenetic parameters.Altitude and soil explained the spatial variation in number of individuals and phylogenetic diversity metrics.From lower to higher altitudes,we found decreasing fertility,increasing tree density and decreasing phylogenetic diversity.Altitude significantly influenced the increases in total biomass(from 240.9 to 255.4 t ha^(-1))and individual biomass(from 0.15 to 0.17 t)recorded in the interval.And while community temporal dynamics had rates of 1.96%for mortality,1.02%for recruitment,1.61%for biomass loss and 2.81%for biomass gain,none of them were explained by altitude or soil.Temporal species substitution averaged0.1 in the interval.Altogether,these results suggest that the small-scale variations in altitude and soil likely determine the conditions and resources that drive community assembly and structure,which are expressed by spatial variations along the altitudinal gradient.At the same time,temporal patterns were not influenced by altitude-related environmental variation,resulting in a similar dynamic behaviour across the gradient,suggesting that broad-scale factors may play a more important role than local ones.

Decomposition dynamic of higher plant pigments by HPLC analysis

The fate of the litter of dominant vegetation(willows and reeds) is one of the aspects studied in the frame of the project “Onderzoek Milieu Effecten Sigmaplan”. One of the questions to be considered is how long the litter stays within the estuary. In this paper, the time the leaf litter(Salix triandra and Phragmites australis) stayed in the Schelde estuary was studied by using plant pigment as biomarkers with HPLC application. After analyzing the original data from the incubation experiment described by Dubuison and Geers(1999), the decomposition dynamics patterns of pigments were analyzed and described, and these decomposition dynamics patterns were used as calibration patterns. By using Spearman Rank Order Correlation, the calibration patterns of the pigments which were significant(p<0.05) were grouped. In this way, several groups of the calibration patterns of pigment decomposition were achieved. The presence or absence of these groups of pigments (whether they can be detected or not from HPLC) was shown to be useful in determining the time the litter has stayed in the water. Combining data of DW and POC, more precise timing can be obtained.

Hollow hexagonal pattern with surface discharges in a？dielectric barrier discharge

The hollow hexagonal pattern involved in surface discharges is firstly investigated in a？dielectric barrier discharge system. The spatiotemporal structures of the pattern are studied using an intensified charge-coupled device and photomultiplier. Instantaneous images taken by an intensified charge-coupled device and optical correlation measurements show that the surface discharges are induced by volume discharges. The optical signals indicate that the discharge filaments constituting the hexagonal frame discharge randomly at the first current pulse or the second pulse, once？or twice. There is no？interleaving of several sub-lattices, which indicates that the ‘memory＇ effect is no longer in force due to surface discharges. By using the emission spectrum method, both the molecule vibration temperature？and electron density of the surface discharges are larger than that of the volume discharges.

Application Strategy of Dynamic Management Mode in Municipal Road Survey and Design Management

With the continuous improvement of urbanization level,the construction of municipal roads has received more attention.The rational application of dynamic management mode to the survey and design management of municipal roads is conducive to improve the survey and design management level of municipal roads and further realizing the optimization of the construction effect of municipal roads.In this paper,the various factors which are affecting the management of municipal road survey and design as well the principles of municipal road design were discussed.Further,the recommendation of the application strategy of dynamic management mode in municipal road survey and design management was proposed in this paper.

Self-erasable dynamic surface patterns via controllable elastic modulus boosting multi-encoded and tamper-proof information storage

Dynamic surface patterns(DSPs)have attracted significant interest in anti-counterfeiting,enabling information to be stored,encrypted and decrypted in response to external stimuli.However,creating dynamic surface patterns,capable of controlling wrinkling time and independently modulating different information in both wrinkled and fluorescent states,remains a tremendous challenge.These limit DSPs to further enhance tamper-proofing capacity and extend the information storage density.Here,a rationally designed patterning strategy based on controllable elastic modulus was demonstrated to fabricate self-erasable dynamic surface patterns(S-DSPs)that increase information storage density.These novel S-DSPs strategically integrated amino co-oligomers(ACOs)with the 9-anthracenemethanol(9-AM)as skin layers,designing a bilayer multi-encoding system which could carry several different types of information with wrinkled and fluorescent patterns.The ACOs with relatively low molecular weight can endow the elastic modulus of skin layers with a wide range of regulation.As a result,the difference between the compressive strain and the critical wrinkle strain in the bilayer system would be precisely modulated by photo-dimerization to form quick-response(minimum<1 min)and self-erasable(3 min–8 days)wrinkled patterns for S-DSPs.Meanwhile,the fluorescence pattern could be independently erased and reprogrammed without affecting the change in the wrinkle pattern under modulus-controlled conditions.Moreover,controllable self-erasure in S-DSPs significantly develops tamper-proof capabilities in a supply chain.This original strategy could provide a new approach to the tamper-proof,high-density,and multi-encoded information storage in the product security or inkless printing.

POSITIVITY-PRESERVING LOCAL DISCONTINUOUS GALERKIN METHOD FOR PATTERN FORMATION DYNAMICAL MODEL IN POLYMERIZING ACTIN FLOCKS

In this paper,we apply local discontinuous Galerkin(LDG)methods for pattern formation dynamical model in polymerizing actin focks.There are two main dificulties in designing effective numerical solvers.First of all,the density function is non-negative,and zero is an unstable equilibrium solution.Therefore,negative density values may yield blow-up solutions.To obtain positive numerical approximations,we apply the positivitypreserving(PP)techniques.Secondly,the model may contain stif source.The most commonly used time integration for the PP technique is the strong-stability-preserving Runge-Kutta method.However,for problems with stiff source,such time discretizations may require strictly limited time step sizes,leading to large computational cost.Moreover,the stiff source any trigger spurious filament polarization,leading to wrong numerical approximations on coarse meshes.In this paper,we combine the PP LDG methods with the semi-implicit Runge-Kutta methods.Numerical experiments demonstrate that the proposed method can yield accurate numerical approximations with relatively large time steps.

A New Elastoplastic 3D Sand Production Model for Fractured Gas Fields

Reservoirs characterized by high temperature,high-pressure,medium high cementation strength,low porosity,and low permeability,in general,are not affected by sand production issues.Since 2009,however,it is known that cases exists where sand is present and may represent a significant technical problem(e.g.,the the Dina II condensate gas field).In the present study,the main factors affecting sand production in this type of reservoir are considered(mechanical properties,stress fields,production system,completion method and gas flow pattern changes during the production process).On this basis,a new liquid-solid coupled porous elasto-plastic 3D sand production model is introduced and validated through comparison with effective sand production data.The related prediction errors are found to be within 15%,which represents the necessary prerequisite for the utilization of such a model for the elaboration of sand prevention measures.

On the physical model of earthquake precursor fields and the mechanism of precursors＇timespace distribution（Ⅲ）──anomalies of seismicity and crustal deformation and their mechanisms when a strong earthquake is in prep

By studying the seismicity pattern before 37 earthquakes with M≥6. 0 in North China and the pattern of crustal deformation in the Capital Area from 1954 to 1992, some abnormal characteristics of these patterns before strong earthquakes have been extracted. A comparison has been made between the anomalies of these two kinds of Patterns. From the results we can know the following. ① Before a strong earthquake, the seismicity will strengthen and the crustal deformation rate will increase. ② Several years before a strong earthquake, there will be seismic gaps and deformation gaps around the epicenter of the quake. ③ The dynamic parameters of patterns all show a decrease in information dimension. This means that the crustal deformation has become more and more localized with time and it gives an important indication showing that a strong earthquake is in preparation. At the end of the paper, the physical mechanisms of the abnormal patterns of seismicity and crustal deformationhave been explained in a unified way in terms of the earthquake-generating model of a inhomogeneous strongbody in inhmogeneous media.