Spreading Process Research Articles

Hyper-cores promote localization and efficient seeding in higher-order processes

Going beyond networks, to include higher-order interactions of arbitrary sizes, is a major step to better describe complex systems. In the resulting hypergraph representation, tools to identify structures and central nodes are scarce. We consider the decomposition of a hypergraph in hyper-cores, subsets of nodes connected by at least a certain number of hyperedges of at least a certain size. We show that this provides a fingerprint for data described by hypergraphs and suggests a novel notion of centrality, the hypercoreness. We assess the role of hyper-cores and nodes with large hypercoreness in higher-order dynamical processes: such nodes have large spreading power and spreading processes are localized in central hyper-cores. Additionally, in the emergence of social conventions very few committed individuals with high hypercoreness can rapidly overturn a majority convention. Our work opens multiple research avenues, from comparing empirical data to model validation and study of temporally varying hypergraphs.

Understanding and leveraging phenotypic plasticity during metastasis formation

Cancer metastasis is the process of detrimental systemic spread and the primary cause of cancer-related fatalities. Successful metastasis formation requires tumor cells to be proliferative and invasive; however, cells cannot be effective at both tasks simultaneously. Tumor cells compensate for this trade-off by changing their phenotype during metastasis formation through phenotypic plasticity. Given the changing selection pressures and competitive interactions that tumor cells face, it is poorly understood how plasticity shapes the process of metastasis formation. Here, we develop an ecology-inspired mathematical model with phenotypic plasticity and resource competition between phenotypes to address this knowledge gap. We find that phenotypically plastic tumor cell populations attain a stable phenotype equilibrium that maintains tumor cell heterogeneity. Considering treatment types inspired by chemo- and immunotherapy, we highlight that plasticity can protect tumors against interventions. Turning this strength into a weakness, we corroborate current clinical practices to use plasticity as a target for adjuvant therapy. We present a parsimonious view of tumor plasticity-driven metastasis that is quantitative and experimentally testable, and thus potentially improving the mechanistic understanding of metastasis at the cell population level, and its treatment consequences.

Compound Droplet Impact on a Thin Hydrophobic Cylinder.

The impact of compound droplets on solid surfaces is a ubiquitous phenomenon that pervades both the natural and technological fields. A comprehensive understanding of the dynamics of the droplet impact on solid surfaces is therefore of paramount importance for a broad range of applications. In this study, we investigate the impact of a water-in-oil compound droplet on a thin hydrophobic cylindrical surface, with regard to the Weber number and cylinder dimensions. Owing to the prewetting effect of the oil, the droplet completely engulfs the cylinder during impact. The ensuing breakups of oil and water engender various unique impact outcomes, which are depicted via a phase map. The phase boundaries are described by analyzing the gravitational and drag forces exerted by the cylinder. A threshold value of the Weber number is found beyond which its effect on the azimuthal spreading process becomes less obvious. The distinctive axial spreading processes of oil and water are illustrated through high-speed imaging from both front and side perspectives, revealing that droplet oscillation is critically influenced by the Weber number. Our work elucidates the impact dynamics of compound droplets on curved surfaces, providing pivotal insights into related thermal management, droplet printing, and coating fabrication applications.

Prediction of an epidemic spread based on the adaptive genetic algorithm

In recent years, coronavirus disease 2019 (COVID-19) has plagued the world, causing huge losses to the lives and property of people worldwide. How to simulate the spread of an epidemic with a reasonable mathematical model and then use it to analyze and to predict its development trend has attracted the attention of scholars from different fields. Based on the susceptible–infected–recovered (SIR) propagation model, this work proposes the susceptible–exposed–infected–recovered–dead (SEIRD) model by introducing a specific medium having many changes such as the self-healing rate, lethality rate, and re-positive rate, considering the possibility of virus propagation through objects. Finally, this work simulates and analyzes the propagation process of nodes in different states within this model, and compares the model prediction results optimized by the adaptive genetic algorithm with the real data. The experimental results show that the susceptible–exposed–infected–recovered–dead model can effectively reflect the real epidemic spreading process and provide theoretical support for the relevant prevention and control departments.

An experimental investigation into the fire behaviors and smoke characteristics of continuous spill fires in road tunnels

Continuous fuel spill fires are a common accident scenario which needs to be considered for the safe operation of tunnels, given the potential threat posed to trapped persons. In this paper, a series of continuous spill fire experiments on a concrete surface were studied using a 1/8 reduced-scale tunnel model. Gasoline was used as the discharge fuel and the discharge rate varied from 1.5 to 5.2 ml/s. The burning area, steady regression rate, smoke front arrival time, and ceiling temperature were analyzed. The results show that the burning area spreads slowly following an initial rapid spill stage, with the spread process following a pattern of exponential decay. The steady regression rate is found to be approximately 63% of that of pool fires for the same burning area. At the same heat release rate, the smoke front moves faster for spill fires than pool fires because of the larger burning area, and a correlation is built to predict the smoke front arrival time. Finally, a ceiling temperature rise prediction model is developed which considers the spread and burning processes of the fire. The results are of practical importance in the quantitative risk assessment of liquid fuel fire accidents in tunnels, and their implications for personnel evacuation.

Wetting Behavior of CO2 Droplets on Smooth Solid Surface: Molecular Simulation Perspective

The wettability of droplets on solid surfaces is important for accurately revealing the microscopic mechanisms of gas condensation nucleation and droplet growth. During the contact condensation of CO2 gas on the heat exchanger surface in the pressurized liquefied natural gas technology, the wettability of CO2 droplets on the heat exchanger surface directly affects the heat transfer thermal resistance of the heat exchanger, which then affects the heat transfer efficiency of methane and ethane in the heat exchanger. Therefore, molecular dynamics simulations were used to study the spreading process and wetting patterns of nanoscale CO2 droplets on different energy surfaces. The results show that as the potential well depth ε of the wall atoms increases, the intensity of the solid-liquid interaction increases and the corresponding surface energy increases accordingly, showing different droplet spreading rates and wetting characteristics. Unlike the interfacial characteristics of macroscopic droplets, there are significant fluctuations at the gas-liquid interface of droplets on the molecular scale, but microdroplets can still form a specific contact angle after spreading on different energy surfaces in a statistical sense, and this contact angle decreases with increasing intensity of solid-liquid interaction. The low-energy surface at potential well depths ε less than 266 J·mol-1 exhibits a CO2-phobicity, and the surface becomes CO2-philic as the potential well depth continues to increase. The trend of the contact angle of CO2 droplets affected by temperature is the same as that of the center-of-mass height, which characterizes the spreading morphology of CO2 droplets. As the temperature increases, the contact angle decreases due to the further spreading and wetting of droplets on different energy surfaces. As the CO2-philicity of the surface gets higher, the contact angle decreases to a greater extent.

WFNet: A hierarchical convolutional neural network for wildfire spread prediction

Pattern analysis in wildfire spread behaviors is crucial for rescue actions and disaster reduction. Deep learning methods have the potential to model the wildfire spread despite problems such as continuous time prediction and multimodal environmental encoding. Therefore, we present a novel hierarchical convolutional neural network (CNN) denoted as WFNet to model the spread pattern of wildfires. The core of WFNet is defining the spread spatiotemporal distribution field (SSDF) to describe the process of wildfire spread, enabling global optimization and end-to-end prediction. Then, a hierarchical State-Condition mechanism is implemented to progressively and efficiently encode high-order features pertaining to multimodal elements. The experimental results demonstrate that WFNet has a competitive performance to existing models in computation time and model accuracy. More interestingly, WFNet shows excellent robustness when input fire state is in an uncertain moment, enabling investigators to quickly backward the ignition from the fire perimeter.

Experimental study of coal spontaneous combustion high-temperature region spreading characteristics

To solve the difficult problem of determining the change law of key point temperature and gas during the motion of high temperature area inside the coal mine seam, this study used the simulation platform of coal spontaneous combustion (CSC) development to investigate the temperature, gas concentration, functional group migration, and change rule of key points with layers in the holistic process of high-temperature region (HTR) spreading of Wen-Zhuang coalmine in Shanxi province, China. The analysis involved the dynamic change rule among temperature, oxygen consumption rate, CO, and C2H4. Finally, with the gray correlation method, the changes of the dominant functional groups released by CO and C2H4 were explored, which revealed the transport rule between the functional groups and the regional spreading in the HTR spreading process. The results show that the temperature of coal body and the rate of oxygen consumption gradually decreased with the deepening of coal layers. Among them, as the coal seam burns, the coal body will appear to “collapse”, along with the phenomenon of “re-ignition”; at the combustion point temperature of each coal layer, the activity of the oxygen-containing functional group was the largest, the activity of hydroxyl group was the smallest, and the activity of aliphatic and aromatic hydrocarbons was similar. Among them, the hydroxyl group, aromatic hydrocarbon, and oxygen-containing functional group had the same trend changing with the deepening of the layers, exhibiting a trend of first decreasing after increasing and later decreasing, and positively correlated with the ignition temperature of each layer. The trend of aliphatic hydrocarbon was opposite to the trend of other functional groups and negatively correlated with the ignition temperature of each layer. The research results of this paper can be used for disaster prevention in the HTR of mine fires, and parameters, such as indicator gases, functional groups and temperature, can be used to determine and deter the migration trend of mine fires, providing a theoretical basis for the prevention and control of high-temperature diffusion of coal spontaneous combustion.

Research on the spreading of Jing Xiao Chan Bao

Jing Xiao Chan Bao(, Tested Treasures in Obstetrics) written by Zan Yin is the earliest extant book of obstetrics and gynecology in China. It was dispersed after written and reappeard by the late Qing Dynasty. Although widely quoted in later medical books, its spread process is not clear yet. In this paper, we reviewed the process of the book's written and the catalogue of historical records, and analyze the type and scope of articles quoted from this book by the Song, Yuan, and Ming dynasties. It can be speculated that the book was lost in the late Song Dynasty and doctors in Yuan and Ming Dynasties have not seen the handed-down masterpiece.

Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis

Psychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown. To test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads. This case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023. Coordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated and empirical spatial patterns of GMV alterations were used to quantify model performance. Of 534 included individuals, 354 (66.3%) were men, and the mean (SD) age was 28.4 (7.4) years. In both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately estimated by coordinated deformation models constrained by structural, rather than functional, network architecture (r range, >0.46 to <0.57; P < .01). The same model also robustly estimated longitudinal volume changes related to illness (r ≥ 0.52; P < .001) and antipsychotic exposure (r ≥ 0.50; P < .004). Network diffusion modeling consistently identified, across all 4 data sets, the anterior hippocampus as a putative epicenter of pathological spread in psychosis. Epicenters of longitudinal GMV loss were apparent in posterior cortex early in the illness and shifted to the prefrontal cortex with illness progression. These findings highlight a central role for white matter fibers as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicenter of early brain pathology from which dysfunction may spread to affect connected areas.

Sooting behavior on a spreading flame over PMMA rods under different oxygen concentrations

The flame spread process over the surface of a solid combustible material is highly influenced by the radiative feedback from the flame, and the conditions under which the process takes place. Soot particles generated during the burn are a big contributor to flame radiation and can play a critical role in the radiative exchange between the flame and the solid. Thus, increased knowledge of the soot production processes involved in the spread of a flame can further promote the understanding of growth and development of fires. The main purpose of this work is to study the effect of oxygen concentration on the sooting behavior of cylindrical samples of polymethyl-methacrylate (PMMA) in an opposed flow configuration. Measured data shows that during downward/opposed flame spread the mass burning rate and soot volume fractions increase with higher oxygen concentrations. The data presented is correlated using a scaling analysis that provides correlations for the maximum soot volume fraction, and the maximum integrated soot volume fraction as a function of the oxygen concentration using similar residence times to establish comparable conditions. The data shows the correlations introduced here provide useful information of the sooting behavior of spreading flames in environments of varied oxygen concentrations that could be used to guide potential fire safety applications.

Early wetting and interfacial behavior of Sn-based solder on copper substrates with different roughness

Purpose This paper aims to investigate the effect of solder composition and roughness on early wetting behavior and interfacial reaction under atmospheric conditions. Design/methodology/approach High-speed photography is used to observe the early wetting and spreading process of the solder on the substrate in real time. The morphology of intermetallic compounds (IMCs) was observed by scanning electron microscopy, and the composition of IMCs micro bumps was determined by energy dispersive spectroscopy. Findings With a roughness range of 0.320–0.539 µm, the solder is distributed in an elliptical trilinear pattern along the grinding direction. With a roughness range of 0.029–0.031 µm, the solder spreads in the direction of grinding and perpendicular, forming a perfect circle (except in the case of Sn63Pb37 solder). The effect of three types of solder on early wettability is Sn63Pb37 &gt; Sn96.5Ag3Cu0.5 &gt; Sn. The wetting behavior is consistent with the Rn∼t model. The rapid spreading stage (Stage I) is controlled by the interfacial reaction with n1 values between 2.4 and 4. The slow spreading stage (stage II) is controlled by diffusion with n2 values between 4 and 6.7. The size of Cu6Sn5 formed on a rough substrate is greater than that produced on a smooth substrate. Originality/value Investigating the effect of solder composition and roughness on early wettability. This will provide a powerful guide in the field of soft brazing.

In-situ observation of powder spreading in powder bed fusion metal additive manufacturing process using particle image velocimetry

Providing a dense powder bed is necessary to ensure the rationality of the final product prepared by powder bed fusion-based additive manufacturing under broad building parameters. In this study, the powder spreading mechanism was elucidated using particle image velocimetry and discrete element simulations. The particle flow regimes in the spreading process were identified based on the particle displacement: alignment, rotation, and deposition. The alignment regime was dominant in gas-atomized stainless steel 304 powder piles, whereas the rotation regime was dominant in plasma rotating electrode processed stainless steel 304 powder piles. A high-fidelity spreading simulation model was developed to clarify the critical factors resulting in the different flow regimes of different stainless steel 304 powders. The dominant rotational regime of the plasma rotating electrode processed powder was substituted for alignment by increasing the cohesive force. The particle supply in the spreading process was further suppressed by increasing the cohesive force, owing to the formation of a strong force arch and agglomeration. The high cohesive force in the gas-atomized powder was mainly attributed to the electrostatic force caused by the thick oxide film. Therefore, it was proven that the oxide film thickness is a key factor in determining the powder spreading mechanism and powder bed quality in the powder bed fusion additive manufacturing process.

Influence Minimization With Conformity-Aware Competitions

Negative information (such as rumors that prevail) may produce tremendous damage in society incredibly quickly. One practical way to control negative information is to add positive information into the spread mechanism, which enjoys both effectiveness and cost-economic counterbalance. This article presents a novel conformity-aware competitive independent cascade model to simulate the spread process of two items (e.g., truth and rumor). Two advanced algorithms named the rumor-aware betweenness first (RBF) and conformity-aware demand degree (CDD) are proposed to solve the corresponding influence minimization problem. Extensive experiments conducted on seven synthetic/real-world networks have demonstrated that first, the proposed CDD or RBF algorithm outperforms other state-of-the-art methods in terms of rumor containment and efficiency in running speed; second, the time delay of rumor detection is entitled to be concerned about and costly measures are necessary if rumors have diffused chronically; and third, authoritative truth information plays a critical role in competing with rumors, relying on truth seeds will generate negative feedback when their credibility ratio is less than a specific threshold.

A fractional-order tuberculosis model with efficient and cost-effective optimal control interventions

This study is concerned with applying fractional calculus in modelling tuberculosis (TB) transmission dynamics. A new six-dimensional fractional-order mathematical model in the sense of the Caputo derivative operator is formulated to capture memory effects in the spread process of tuberculosis. Some key features such as vaccination, forces of TB infection, and exogenous re-infection by two actively infectious classes are considered. Banach fixed point theory is employed to prove the existence and uniqueness of a solution for the fractional-order model. Equilibrium points and effective reproduction number of the model are determined. Analysis reveals that the model exhibits backward bifurcation where stable TB-free and TB-present equilibrium points co-exist when the effective reproduction number is below unity. Some sensitive parameters of the model are identified to help design intervention measures against the disease. Hence, four time-dependent controls, namely advocacy effort against infection and re-infection, vaccination control, prophylaxis against latent infection, and treatment control, are considered to form a fractional-order optimal control model. The controls are characterized using Pontryagin’s maximum principle. Efficiency and cost-effectiveness assessments are conducted to quantify the most efficient and cost-effective intervention plan to minimize TB spread in the population. Behaviours of the fractional-order TB model at varying values of the order of the Caputo derivative are extensively explored to show memory effects in the transmission dynamics of the disease.

Fast Spread in Controlled Evolutionary Dynamics

We study a controlled evolutionary dynamics that models the spread of a novel state in a network where the exogenous control aims to quickly spread the novel state. We estimate the performance of the system by analytically establishing upper and lower bounds on the expected time needed for the novel state to replace the original one. Such bounds are expressed as functions of the control policy adopted and of the network structure, and establish fundamental limitations on the system's performance. Leveraging these results, we classify network structures depending on the possibility of achieving a fast spread of the novel state (i.e., complete replacement in a time growing logarithmically with the network size) using simple open-loop control policies. Finally, we propose a feedback control policy that using little knowledge of the network and of the system's evolution at a macroscopic level allows for a substantial speed up of the spreading process, guaranteeing fast spread on topologies where simple open-loop control policies are not sufficient. Examples and simulations corroborate our findings.

The fate of mitochondria during platelet activation

AbstractBlood platelets undergo several successive motor-driven reorganizations of the cytoskeleton when they are recruited to an injured part of a vessel. These reorganizations take place during the platelet activation phase, the spreading process on the injured vessel or between fibrin fibers of the forming clot, and during clot retraction. All these steps require a lot of energy, especially the retraction of the clot when platelets develop strong forces similar to those of muscle cells. Platelets can produce energy through glycolysis and mitochondrial respiration. However, although resting platelets have only 5 to 8 individual mitochondria, they produce adenosine triphosphate predominantly via oxidative phosphorylation. Activated, spread platelets show an increase in size compared with resting platelets, and the question arises as to where the few mitochondria are located in these larger platelets. Using expansion microscopy, we show that the number of mitochondria per platelet is increased in spread platelets. Live imaging and focused ion beam–scanning electron microscopy suggest that a mitochondrial fission event takes place during platelet activation. Fission is Drp1 dependent because Drp1-deficient platelets have fused mitochondria. In nucleated cells, mitochondrial fission is associated with a shift to a glycolytic phenotype, and using clot retraction assays, we show that platelets have a more glycolytic energy production during clot retraction and that Drp1-deficient platelets show a defect in clot retraction.

Drivers of the dynamics of the spread of cholera in the Democratic Republic of the Congo, 2000-2018: An eco-epidemiological study.

The dynamics of the spread of cholera epidemics in the Democratic Republic of the Congo (DRC), from east to west and within western DRC, have been extensively studied. However, the drivers of these spread processes remain unclear. We therefore sought to better understand the factors associated with these spread dynamics and their potential underlying mechanisms. In this eco-epidemiological study, we focused on the spread processes of cholera epidemics originating from the shores of Lake Kivu, involving the areas bordering Lake Kivu, the areas surrounding the lake areas, and the areas out of endemic eastern DRC (eastern and western non-endemic provinces). Over the period 2000-2018, we collected data on suspected cholera cases, and a set of several variables including types of conflicts, the number of internally displaced persons (IDPs), population density, transportation network density, and accessibility indicators. Using multivariate ordinal logistic regression models, we identified factors associated with the spread of cholera outside the endemic eastern DRC. We performed multivariate Vector Auto Regressive models to analyze potential underlying mechanisms involving the factors associated with these spread dynamics. Finally, we classified the affected health zones using hierarchical ascendant classification based on principal component analysis (PCA). The increase in the number of suspected cholera cases, the exacerbation of conflict events, and the number of IDPs in eastern endemic areas were associated with an increased risk of cholera spreading outside the endemic eastern provinces. We found that the increase in suspected cholera cases was influenced by the increase in battles at lag of 4 weeks, which were influenced by the violence against civilians with a 1-week lag. The violent conflict events influenced the increase in the number of IDPs 4 to 6 weeks later. Other influences and uni- or bidirectional causal links were observed between violent and non-violent conflicts, and between conflicts and IDPs. Hierarchical clustering on PCA identified three categories of affected health zones: densely populated urban areas with few but large and longer epidemics; moderately and accessible areas with more but small epidemics; less populated and less accessible areas with more and larger epidemics. Our findings argue for monitoring conflict dynamics to predict the risk of geographic expansion of cholera in the DRC. They also suggest areas where interventions should be appropriately focused to build their resilience to the disease.

Visualisation of [11C]CO2 storage in coal with positron emission tomography imaging

Positron Emission Tomography (PET) imaging has demonstrated its capability in providing real-time visualisation of fluids flow in geological materials. However, it has not been used for the study of CO2 injection and storage in coal for the application of CO2 geo-sequestration. To observe the processes directly, [11C]CO2 is the most optimal radiotracer, which is rarely used due to its short half-life (20.4 min) and handling safety issues as a gaseous tracer. In this work, a novel laboratory protocol is developed to use gaseous [11C]CO2 as the radiolabelled tracer to visualise and quantify dynamic processes of gas spreading, adsorption, diffusion, and advection flow in coal under in-situ conditions. The experimental setup integrates core flooding setup with PET scanning. Coal samples are pre-treated to mimic different injection conditions, including coal seam gas reservoirs in early production stage, gas depleted stage and CO2 storage stage. Due to high temporal resolution of PET imaging, time-lapse CO2 gas concentration map of each test is acquired by converting the PET intensity values to gas concentrations. Impacting factors on storage capacity and efficiency are also studied, including permeability, gas adsorption, gas exchange, and initial storage conditions. This work introduces a new laboratory protocol and analysing framework to quantify sub-core scale multiphysics CO2 flow in coal, which provides a foundation for future across-scale theoretical and experimental study of multiphase and multicomponent flow behaviours in coal for the application of CO2 geo-sequestration.

离心圆盘式有机肥撒施机改进设计与仿真分析

Aiming at the poor efficiency in crushing a handful of caking organic fertilizers spraying from the traditional disc spreader, an improved disc spreader equipped with spike-tooth crushing unit was designed with the introduction of its structural composition and working principle. Also simulation experiments were carried out based on the discrete element method according to the solutions made before and after the structural improvement. Firstly, a granular organic fertilizer model was established based on the EDEM and a caking organic fertilizer bonding model was built based on the HMB (Hertz-Mindlin with bonding) contact model. Then two organic fertilizer spreading models corresponding to the solutions were respectively established, based on which simulation experiments were repeated three times on the spreading process. The analysis on the particle velocity vector diagram revealed the interaction relationship between organic fertilizers with the toothed shaft, external wall and disk, verifying the crushing mechanism of crushing unit. By calculating the total number of the bonds generated and broken in the spreading process in both of the spreading models, the average broken rate of bonds in the spreading process was separately 58.87% and 98.05% based on each solution, revealing that the improved solution outperformed the traditional solution in terms of the efficiency in crushing the caking organic fertilizers. This research will be a reference in designing the critical components or improving the overall performance of disc spreader.