Spreading Phenomena Research Articles

RETRACTED ARTICLE: Investigating the effects of drought on the environment in northwestern province of Iran, Ardabil, using combined indices, Iran

Drought is a spreading phenomenon, and it has caused a lot of damages in different parts of the country in recent years. Therefore, we evaluated and monitored the drought and its indicators in this study. We used rainfall and temperature data [in a period 26 years (1993–2018)] from five synoptic stations of Ardabil province obtained from the Meteorological Organization, and then, the droughts of this province were investigated using the four indices of CZI, SPI, ZSI and MCZI in DIP software. The results showed that very severity droughts at 12-month scale occurred lower than the 6-month scale, and, the medium droughts were more than severe and very severe droughts in the 5 stations. The severity of the drought was more at the 12-month scale than the 6-month scale in the TOPSIS model, but the VIKOR model showed more severe drought at 6-month scale than the 12-month scale. Therefore, we can prevent the critical consequences of the drought and probable problems in different parts such as meteorology, agriculture, and water basins with precise and efficient schedules for the stations that are more exposed to drought.

Spreading speed in a farmers and hunter-gatherers model arising from Neolithic transition in Europe

We study spreading phenomena in a two-component reaction-diffusion system, modeling the Neolithic transition from hunter-gatherer societies to agricultural societies in Europe. When farmer populations were introduced into the region inhabited by hunter-gatherer populations, farmer populations spread as an expanding wave through Europe. The speed of the wave is observed to tend to be a constant. We analytically compute the spreading velocity of the model, and characterize the longtime behavior of solutions of the model. Without comparison principle, we introduce a new technique that can locate the spreading front in reaction-diffusion systems.

Benchmark of a new multi-ion-species collision operator for [formula omitted] Monte Carlo neoclassical simulation

A numerical method to implement a linearized Coulomb collision operator in the two-weight δf Monte Carlo method for multi-ion-species neoclassical transport simulation is developed. The conservation properties and the self-adjoint property of the operator in the collisions between two particle species with different temperatures are verified. The linearized operator in a δf Monte Carlo code is benchmarked with other two kinetic simulations, a δf continuum gyrokinetic code with the same linearized collision operator and a full-f PIC code with Nanbu collision operator. The benchmark simulations of the equilibration process of plasma flow and temperature fluctuation among several particle species show very good agreement between δf Monte Carlo code and the other two codes. An error in the H-theorem in the two-weight δf Monte Carlo method is found, which is caused by the weight spreading phenomenon inherent in the two-weight δf method. It is demonstrated that the weight averaging method serves to restoring the H-theorem without causing side effect.

A Phenomenon Study on Spreading and Evaporating Process of Droplet on DBD Actuator for Wind Turbine Anti-icing

This paper reports on the phenomenon of the unique spreading and evaporation process of water droplets on the surface of a dielectric barrier discharge (DBD) actuator. High-speed photography was used to capture the droplet spreading dynamics, and the temperature field evolution was characterized by infrared imaging. On the DBD actuator, the maximum spreading diameters of the droplets are shown to be increased by ∼95%, and the contact angles decrease from 58º to 13º, indicating that the DBD plasma significantly increases the hydrophilicity of the actuator surfaces. It is also revealed that the evaporation time induced by the DBD plasma is 6.54 times faster than that of an electric heater. It is argued that coupled effects of the hydrophilicity caused by plasma and the heat flux in the streamers bridging the electrodes and the droplets should be the crucial points of plasma evaporation physics of impinging water droplets, which are especially meaningful in anti-icing applications.

Microwave absorbing structure using periodic pattern coated fabric

In this study, a microwave absorbing structure consisting of a periodic pattern coated glass fabric (PPCF) and a glass-fiber/epoxy composite as the spacer is presented using a practical approach for application in aircraft. To fabricate a PPCF, a carbon-based conducting material bar coating device was used. To test the performance of the PPCF, an X-band (8.2–12.4 GHz) microwave absorbing structure was fabricated using an autoclave and measured using a free-space measurement system. The return loss of the fabricated PPCF microwave absorbing structure was −27 dB at the resonance frequency, and the measurement result was well matched with the simulation result. Since the pattern was implemented on an uneven surface, the performance stability of the distribution of sheet resistance on the surface, pattern spreading phenomena, and waviness of patterns was verified using a simulation method. The simulation result showed good performance stability. To verify the mechanical properties, an interlaminar shear strength (ILSS) test was performed. Since the pattern on the glass fabric can act in a similar way to a defect, there is a high probability of mechanical property degradation. However, the ILSS test results of the PPCF specimen was comparable with a pure glass-fiber/epoxy composite.

Influence of Polarization on the Morphological Changes of Nickel in Fuel Electrodes of Solid Oxide Cells

In this work, morphological changes that patterned nickel films undergo during operations under both solid oxide fuel cell and solid oxide electrolysis modes are investigated using patterned nickel film electrodes. Based on ex situ scanning electron microscope observations, it is found that local morphological changes of nickel at active three-phase-boundaries are influenced by polarization during operations. Under fuel cell mode,the phenomenon of discontinuous nickel spreading caused by the co-effect of enhanced nickel wettability on yttria-stabilized zirconia and nickel coarsening is responsible for the complex morphological changes of patterned nickel film. Under electrolysis mode, the delamination of nickel from the yttria-stabilized zirconia is observed, which is attributed to the weakened nickel wettability on yttria-stabilized zirconia. The phenomena observed during different operations are explained by correlating the nickel wettability on yttria-stabilized zirconia to the level of adsorbed oxygen on the nickel surface, as inferred from the changes in both nickel surface tension and work of adhesion at the nickel-yttria-stabilized zirconia interface.

Suppressing artificial equilibrium states caused by spurious currents in droplet spreading simulations with dynamic contact angle model

Accurate methods for numerical simulation of dynamic wetting and spreading phenomena are a valuable tool to support the advancement of related technological processes such as inkjet-printing. Here, it is demonstrated that numerical methods employing dynamic contact angle models are prone to artificial equilibrium states caused by spurious (parasitic) currents. The capability of different approaches in reducing spurious currents for sessile and spreading droplets with low equilibrium contact angle is evaluated. To minimise the influence of spurious currents on dynamic contact angle models, a smoothing step in the evaluation of the contact line velocity is introduced in this paper. The benefit and performance of this new approach is demonstrated by algebraic volume-of-fluid simulations of spreading and receding droplets with the Kistler dynamic contact angle model.

Potential-Driven Model for Influence Maximization in Social Networks

The adoption of a new technology, the spreading of ideologies, the transmission of contagions, are examples of spreading phenomena that can be modelled at two distinct levels of resolution, a macroscopic and a microscopic level.In the present work, we consider the network at the microscopic level and represent its nodes as a system of interacting particles and propose a novel, physics-inspired approach. This approach assumes that nodes interact via `forces' that derive from the `potential' that each node creates at the location of the other nodes, leading to a potential gradient that indicates the `natural' direction of diffusion through the network. A set of influencers in the network, is determined from strategically selected nodes based on the value of their net potential. We use synthetic networks of various sizes and compare the influence spread resulting from a seed set determined from the potential-based model and alternate approaches, including the greedy algorithm of Kempe et al. Our findings indicate that this approach achieves comparable results to those of the greedy algorithm without the prohibitive computational cost, and consistently outperforms the other approaches by a large margin. We then apply our methodology to information spreading related to the Twitter Higgs Boson user dataset. The results are analyzed in the context of influence maximization, and we provide insights into the general application of this technique for information dissemination.

2D ZIF-derived ZnO nanosheets—an example for improving semiconductor metal oxide detector performance in gas chromatography through material design strategy

Semiconductor metal oxide (SMO)-based GC detector was investigated by rational design of 2D materials used as detector sensing film, which was verified to be a feasible way to overcome tailing and peak spreading phenomena usually existed in SMOs-based GC detector. Specifically, 2D flake-like ZnO chosen as an example was successfully synthesized by employing 2D ZIF-8 as template, and then acted as detector in portable gas chromatograph. The properties of detector were evaluated via detection of alcohols and other oxygen-containing VOCs. The results exhibited good linear dependence between peak heights and concentrations of target gases with a short response and recovery time (several seconds) and a high sensitivity, low detection limit (ppb level), together with prominent selectivity for oxygen-containing VOCs than hydrocarbons. Moreover, tailing and peak spreading phenomena mentioned above were hardly observed due to a smaller diffusion barrier for 2D material as compared to 3D counter parts. It is concluded that 2D materials-based portable GC detectors indeed possess great potential in practical application in the future.

Quantifying echo chamber effects in information spreading over political communication networks

Echo chambers in online social networks, in which users prefer to interact only with ideologically-aligned peers, are believed to facilitate misinformation spreading and contribute to radicalize political discourse. In this paper, we gauge the effects of echo chambers in information spreading phenomena over political communication networks. Mining 12 million Twitter messages, we reconstruct a network in which users interchange opinions related to the impeachment of the former Brazilian President Dilma Rousseff. We define a continuous political leaning parameter, independent of the network’s structure, that allows to quantify the presence of echo chambers in the strongly connected component of the network. These are reflected in two well-separated communities of similar sizes with opposite views of the impeachment process. By means of simple spreading models, we show that the capability of users in propagating the content they produce, measured by the associated spreading capacity, strongly depends on their attitude. Users expressing pro-impeachment leanings are capable to transmit information, on average, to a larger audience than users expressing anti-impeachment leanings. Furthermore, the users’ spreading capacity is correlated to the diversity, in terms of political position, of the audience reached. Our method can be exploited to identify the presence of echo chambers and their effects across different contexts and shed light upon the mechanisms allowing to break echo chambers.

Latent geometry and dynamics of proximity networks.

Proximity networks are time-varying graphs representing the closeness among humans moving in a physical space. Their properties have been extensively studied in the past decade as they critically affect the behavior of spreading phenomena and the performance of routing algorithms. Yet the mechanisms responsible for their observed characteristics remain elusive. Here we show that many of the observed properties of proximity networks emerge naturally and simultaneously in a simple latent space network model, called dynamic-S^{1}. The dynamic-S^{1} does not model node mobility directly but captures the connectivity in each snapshot-each snapshot in the model is a realization of the S^{1} model of traditional complex networks, which is isomorphic to hyperbolic geometric graphs. By forgoing the motion component the model facilitates mathematical analysis, allowing us to prove the contact, intercontact, and weight distributions. We show that these distributions are power laws in the thermodynamic limit with exponents lying within the ranges observed in real systems. Interestingly, we find that network temperature plays a central role in network dynamics, dictating the exponents of these distributions, the time-aggregated agent degrees, and the formation of unique and recurrent components. Further, we show that paradigmatic epidemic and rumor-spreading processes perform similarly in real and modeled networks. The dynamic-S^{1} or extensions of it may apply to other types of time-varying networks and constitute the basis of maximum likelihood estimation methods that infer the node coordinates and their evolution in the latent spaces of real systems.

How The Social Interactions in Communities affect the Fear of Crime

AbstractFear of crime (FoC) refers to the subjective risk assessment of being a crime victim and the magnitude of its consequences. FoC emerges as a social construct, which is highly dependent on various psychological, cultural, and social factors. Mathematical models for the emergence and diffusion of information related to FoC relies on sequential and random interactions among persons. However, these interactions seem to be simultaneous and conditioned to members of particular social groups. Recent evidence suggests that in other spreading phenomena, the topology of the underlying network that supports individual communication may influence the community member's opinions. This paper studies how the FoC changes with preferential interaction between persons defined by a network with community structure. These particular networks are typical of many unequal societies. The results indicate that even if these supporting structures allow efficient communication, in the case of FoC propagation, this particular structure may promote an isolation effect of the FoC for the different communities. This isolation effect is higher for communities with low susceptibility to crime. Therefore, groups with low susceptibility to crime have higher feelings of security than groups with high susceptibility to crime when considering interactions in communities.

Free boundary problem for a reaction-diffusion equation with positive bistable nonlinearity

This paper deals with a free boundary problem for a reaction-diffusion equation in a one-dimensional interval whose boundary consists of a fixed end-point and a moving one. We put homogeneous Dirichlet condition at the fixed boundary, while we assume that the dynamics of the moving boundary is governed by the Stefan condition. Such free boundary problems have been studied by a lot of researchers. We will take a nonlinear reaction term of positive bistable type which exhibits interesting properties of solutions such as multiple spreading phenomena. In fact, it will be proved that large-time behaviors of solutions can be classified into three types; vanishing, small spreading and big spreading. Some sufficient conditions for these behaviors are also shown. Moreover, for two types of spreading, we will give sharp estimates of spreading speed of each free boundary and asymptotic profiles of each solution.

Network inference from the timing of events in coupled dynamical systems.

Spreading phenomena like opinion formation or disease propagation often follow the links of some underlying network structure. While the effects of network topology on spreading efficiency have already been vastly studied, we here address the inverse problem of whether we can infer an unknown network structure from the timing of events observed at different nodes. For this purpose, we numerically investigate two types of event-based stochastic processes. On the one hand, a generic model of event propagation on networks is considered where the nodes exhibit two types of eventlike activity: spontaneous events reflecting mutually independent Poisson processes and triggered events that occur with a certain probability whenever one of the neighboring nodes exhibits any of these two kinds of events. On the other hand, we study a variant of the well-known SIRS model from epidemiology and record only the timings of state switching events of individual nodes, irrespective of the specific states involved. Based on simulations of both models on different prototypical network architectures, we study the pairwise statistical similarity between the sequences of event timings at all nodes by means of event synchronization and event coincidence analysis (ECA). By taking strong mutual similarities of event sequences (functional connectivity) as proxies for actual physical links (structural connectivity), we demonstrate that both approaches can lead to reasonable prediction accuracy. In general, sparser networks can be reconstructed more accurately than denser ones, especially in the case of larger networks. In such cases, ECA is shown to commonly exhibit the better reconstruction accuracy.

Spreading in a cone for the Fisher-KPP equation

In this paper we consider the spreading phenomena in the Fisher-KPP equation in a high dimensional cone with Dirichlet boundary condition. We show that any solution starting from a nonnegative and compact supported initial data spreads and converges to the unique positive steady state. Moreover, the asymptotic spreading speeds of the front in all directions pointing to the opening are c0 (which is the minimal speed of the traveling wave solutions of the 1-dimensional Fisher-KPP equation). Surprisingly, they do not depend on the shape of the cone, the propagating directions and the boundary condition.

Spreading speeds for multidimensional reaction–diffusion systems of the prey–predator type

We investigate spreading properties of solutions of a large class of two-component reaction–diffusion systems, including prey–predator systems as a special case. By spreading properties we mean the long time behaviour of solution fronts that start from localized (i.e. compactly supported) initial data. Though there are results in the literature on the existence of travelling waves for such systems, very little has been known—at least theoretically—about the spreading phenomena exhibited by solutions with compactly supported initial data. The main difficulty comes from the fact that the comparison principle does not hold for such systems. Furthermore, the techniques that are known for travelling waves such as fixed point theorems and phase portrait analysis do not apply to spreading fronts. In this paper, we first prove that spreading occurs with definite spreading speeds. Intriguingly, two separate fronts of different speeds may appear in one solution—one for the prey and the other for the predator—in some situations.

Impact of temporal connectivity patterns on epidemic process

To provide a comprehensive view for dynamics of and on many real-world temporal networks, we investigate the interplay of temporal connectivity patterns and spreading phenomena, in terms of the susceptible-infected-removed (SIR) model on the modified activity-driven temporal network (ADTN) with memory. In particular, we focus on how the epidemic threshold of the SIR model is affected by the heterogeneity of nodal activities and the memory strength in temporal and static regimes, respectively. While strong ties (memory) between nodes inhibit the spread of epidemic to be localized, the heterogeneity of nodal activities enhances it to be globalized initially. Since the epidemic threshold of the SIR model is very sensitive to the degree distribution of nodes in static networks, we test the SIR model on the modified ADTNs with the possible set of the activity exponents and the memory exponents that generates the same degree distributions in temporal networks. We also discuss the role of spatiotemporal scaling properties of the largest cluster and the maximum degree in the epidemic threshold. It is observed that the presence of highly active nodes enables to trigger the initial spread of epidemic in a short period of time, but it also limits its final spread to the entire network. This implies that there is the trade-off between the spreading time of epidemic and its outbreak size. Finally, we suggest the phase diagram of the SIR model on ADTNs and the optimal condition for the spread of epidemic under the circumstances.

CENTRAL NERVOUS SYSTEM ANTIGEN’S EPITOPES SELECTION, WHICH TAKE PART IN MULTIPLE SCLEROSIS PATIENTS AUTOIMMUNE REACTIONS, AS A WAY OF A SPECIFIC TOLEROGENITY CREATION

To determine the central nervous system (CNS) peptide epitopes that take part in multiple sclerosis (MS) immune response, and taking into consideration the literature, we selected CNS peptides that most likely participated in MS immune response: MBP1 (83-99), MBP2 (111-129), MBP3 (146-170), PLP, and MOG. We estimated the specific activation of serum T-cells by the level of detected cytokines in 6 MS patients: 3 - with relapsing-remitting MS (RRMS), 2 - primary progressive MS (PPMS), 1 - secondary progressive MS (SPMS). As a result we revealed that all selected peptides took part in MS immunopathogenesis: in all patients MBP1 and PLP were involved; MBP2, MBP3, and MOG - in 5 of 6 patients. In response to CNS peptides T-cells most actively produced INFg, in a less degree - IL10 and IL4. In 5 of 6 cases we found negative correlation between levels of INFg and IL10. Cytokine levels did not differ between RRMS, PPMS and SPMS. Our results confirm the immunological phenomenon of epitope spreading that affects the efficacy of MS treatment, including immunological tolerance restoration.

Wetting kinetics and spreading phenomena of the precursor film and bulk liquid in the AgCuTi/TC4 system

The reactive wetting of AgCuTi filler metal over a TC4 substrate was conducted using real-time in situ hot stage microscopy. In addition to the commonly observed bulk liquid, a rapidly spreading precursor film was observed. Both the precursor film and bulk liquid were studied and characterized. The wetting kinetics of the bulk liquid within the main spreading stage was predominantly controlled by chemical reactions, in which Ag-based solid solutions (Ag(s,s)), Ti-based solid solutions (Ti(s,s)) and intermetallic compounds (Ti2Cu) were formed within the central domain. The high temperature phase transition of α-Ti to β-Ti induced by the diffusion of Ag into the TC4 substrate was also observed at the edge domain. In the mid-to late-stage spreading process, a thin precursor film, with an extremely rapid spreading speed, appeared at the front of the triple line. According to compositional analysis, the precursor film was predominantly composed of Ag and exhibited similar spreading characteristics to pure Ag on TC4. The formation mechanism of the precursor film can be explained by the mechanism of rapid adsorption followed by the film overflow; based on this mechanism, a physical model was proposed.

In-situ investigation of the impact of spreading on matrix-fracture interactions during three-phase flow in fractured porous media

This paper presents the results of a detailed experimental study performed to examine fluid flow in a water-wet fractured sandstone rock. Using high-resolution X-ray micro computed tomography technique, we systematically investigate the pore-scale displacement mechanisms and governing interactions between the matrix and fracture during gas injection. We perform two sets of flow experiments using brine/Soltrol 170 (spreading oil)/nitrogen and brine/decalin (nonspreading oil)/nitrogen fluid systems to probe the possible beneficial role of spreading phenomena in transferring oil from the matrix to the fracture during gas injection. Gas injection after primary oil drainage was used to generate a wide range of oil saturations and pore fluid arrangements with both fluid systems. Direct visualization of the pore fluid occupancies at different oil saturations in the medium reveals the significant role that the spreading oil layers play in maintaining the hydraulic conductivity of the oil phase between the matrix and the fracture. This mainly takes place at low remaining oil saturations under the spreading condition where layer drainage, in the presence of stable and connected spreading oil layers, is the dominant displacement mechanism. In the case of high remaining oil saturations, it is observed that the oil movement is primarily governed by piston-like displacements as well as the ability of the gas phase to access the pore elements adjacent to the fracture. Under the nonspreading condition, oil cannot maintain its connectivity due to the absence of the spreading layers, leading to higher residual oil saturations in the matrix and lower ultimate oil recovery.