Evolution Of Cascades Research Articles

Large-Scale Solar Wind Phenomena Affecting the Turbulent Cascade Evolution behind the Quasi-Perpendicular Bow Shock

The Earth’s magnetosphere is permanently influenced by the solar wind. When supersonic and superalfvenic plasma flow interacts with the magnetosphere, the magnetosheath region is formed, which is filled with shocked turbulent plasma. Varying SW parameters influence the mechanisms of formation of this boundary layer, including the dynamics of turbulence behind the bow shock. The effect of the solar wind on the development of turbulence in the magnetosheath was demonstrated recently based on broad statistics of spacecraft measurements. The present study considers the multipoint observations of turbulent fluctuations in the solar wind, in the dayside magnetosheath and at the flanks, to analyze the evolution of the turbulent cascade while the solar wind plasma enters the magnetosheath. Observations of the magnetosheath behind the quasi-perpendicular bow shock are analyzed to exclude the influence of the bow shock topology from consideration. Three basic types of solar wind flows are considered: slow undisturbed solar wind, compressed regions, and interplanetary manifestations of coronal mass ejections. The results show surviving Kolmogorov scaling behind the bow shock for steady solar wind flow and amplification of the compressive fluctuations at the kinetic scales at the magnetosheath flanks for the solar wind associated with compressed plasma streams. During interplanetary manifestations of the coronal mass ejection, the spectra in the dayside magnetosheath substantially deviate from those observed in the solar wind (including the absence of Kolmogorov scaling and steepening at the kinetic scales) and restore at the flanks.

Silencing RNAs expressed from W-linked PxyMasc “retrocopies” target that gene during female sex determination in Plutella xylostella

The Lepidoptera are an insect order of cultural, economic, and environmental importance, representing ∼10% of all described living species. Yet, for all but one of these species (silkmoth, Bombyx mori), the molecular genetics of how sexual fate is determined remains unknown. We investigated this in the diamondback moth (Plutella xylostella), a globally important, highly invasive, and economically damaging pest of cruciferous crops. Our previous work uncovered a regulator of male sex determination in P. xylostella-PxyMasc, a homolog of B. mori Masculinizer-which, although initially expressed in embryos of both sexes, is then reduced in female embryos, leading to female-specific splicing of doublesex. Here, through sequencing small RNA libraries generated from early embryos and sexed larval pools, we identified a variety of small silencing RNAs (predominantly Piwi-interacting RNAs [piRNAs]) complementary to PxyMasc, whose temporal expression correlated with the reduction in PxyMasc transcript observed previously in females. Analysis of these small RNAs showed that they are expressed from tandemly arranged, multicopy arrays found exclusively on the W (female-specific) chromosome, which we term "Pxyfem". Analysis of the Pxyfem sequences showed that they are partial complementary DNAs (cDNAs) of PxyMasc messenger RNA (mRNA) transcripts, likely integrated into transposable element graveyards by the noncanonical action of retrotransposons (retrocopies), and that their apparent similarity to B. mori feminizer more probably represents convergent evolution. Our study helps elucidate the sex determination cascade in this globally important pest and highlights the "shortcuts" that retrotransposition events can facilitate in the evolution of complex molecular cascades, including sex determination.

Domain Evolution of Vertebrate Blood Coagulation Cascade Proteins

Vertebrate blood coagulation is controlled by a cascade containing more than 20 proteins. The cascade proteins are found in the blood in their zymogen forms and when the cascade is triggered by tissue damage, zymogens are activated and in turn activate their downstream proteins by serine protease activity. In this study, we examined proteomes of 21 chordates, of which 18 are vertebrates, to reveal the modular evolution of the blood coagulation cascade. Additionally, two Arthropoda species were used to compare domain arrangements of the proteins belonging to the hemolymph clotting and the blood coagulation cascades. Within the vertebrate coagulation protein set, almost half of the studied proteins are shared with jawless vertebrates. Domain similarity analyses revealed that there are multiple possible evolutionary trajectories for each coagulation protein. During the evolution of higher vertebrate clades, gene and genome duplications led to the formation of other coagulation cascade proteins.

Transformer-enhanced Hawkes process with decoupling training for information cascade prediction

The ability to model the information diffusion process and predict its size is crucial to understanding information propagation mechanism and is useful for many applications such as popularity prediction and fake news detection. Recent research works have attempted to address the problem of information cascade prediction using two basic paradigms: (1) sequential methods, e.g., recurrent neural networks (RNNs), and (2) graph learning techniques to retain the topological information and enable consideration of structural relationships among diffusion participants. However, existing models consider the topological and temporal features separately, falling short of simulating their entanglement in the diffusion process. As a consequence, since the evolving directed acyclic graph (DAG) of information diffusion is intrinsically coupled with both topological and temporal dependencies, there is a loss of cross-domain information. In this paper, we propose a transformer enhanced Hawkes process (Hawkesformer), which links the hierarchical attention mechanism to Hawkes self-exciting point process for information cascade prediction. Specifically, we extend traditional Hawkes process with a topological horizon and efficiently acquire knowledge from continuous-time domain. A two-level attention architecture is used to parameterize the intensity function of Hawkesformer. At the first-level, we disentangle the primary and non-primary paths to simulate the coupled topological and temporal information for capturing the global dependencies between the nodes in a graph. At the second-level, a local pooling attentive module is proposed to embed the cascade evolution rate for modeling short-term outbreaks. Extensive experiments on two real-world datasets demonstrate the significant performance improvements of Hawkesformer over existing state-of-the-art models.

Toward a universal description of multiphase turbulence phenomena based on the vorticity transport equation

Understanding the evolution of turbulence in multiphase flows remains a challenge due to the complex inter-phase interactions at different scales. This paper attempts to enlighten the multiphase turbulence phenomenon from a new perspective by exploiting the classical concept of vorticity and its role in the evolution of the turbulent energy cascade. We start with the vorticity transport equations for two different multiphase flow formulations, which are one-fluid and two-fluid models. By extending the decaying homogeneous isotropic turbulence (HIT) problem to the multiphase flow context, we performed two highly resolved simulations of HIT in the presence of (i) a thin interface layer and (ii) homogeneously distributed solid particle. These two configurations allow for the investigation of interfacial turbulence and particulate turbulence, respectively. In addition to the analysis of the global flow characteristic in both cases, we evaluate the spectral contribution of each production/dissipation mechanism in the vorticity transport equation to the distribution of vortical energy (enstrophy) across the scales. We base our discussion on the role of the main inter-phase interaction mechanisms in vorticity transport (i.e., the surface tension for interfacial turbulence and drag force for particulate turbulence) and unveil a similar contribution from these mechanisms to the multiphase turbulence cascade. The results also explain the deviation of kinetic energy and enstrophy spectra of multiphase HIT problems from their single-phase similitudes, confirming the validity of this approach for establishing a universal description of multiphase turbulence.

Linking Transformer to Hawkes Process for Information Cascade Prediction (Student Abstract)

Information cascade is typically formalized as a process of (simplified) discrete sequence of events, and recent approaches have tackled its prediction via variants of recurrent neural networks. However, the information diffusion process is essentially an evolving directed acyclic graph (DAG) in the continuous-time domain. In this paper, we propose a transformer enhanced Hawkes process (Hawkesformer), which links the hierarchical attention mechanism with Hawkes process to model the arrival stream of discrete events continuously. A two-level attention architecture is used to parameterize the intensity function of Hawkesformer, which captures the long-term dependencies between nodes in graph and better embeds the cascade evolution rate for modeling short-term outbreaks. Experimental results demonstrate the significant improvements of Hawkesformer over the state-of-the-art.

Temporal evolution of failure avalanches of the fiber bundle model on complex networks.

We investigate how the interplay of the topology of the network of load transmitting connections and the amount of disorder of the strength of the connected elements determines the temporal evolution of failure cascades driven by the redistribution of load following local failure events. We use the fiber bundle model of materials' breakdown assigning fibers to the sites of a square lattice, which is then randomly rewired using the Watts-Strogatz technique. Gradually increasing the rewiring probability, we demonstrate that the bundle undergoes a transition from the localized to the mean field universality class of breakdown phenomena. Computer simulations revealed that both the size and the duration of failure cascades are power law distributed on all network topologies with a crossover between two regimes of different exponents. The temporal evolution of cascades is described by a parabolic profile with a right handed asymmetry, which implies that cascades start slowly, then accelerate, and eventually stop suddenly. The degree of asymmetry proved to be characteristic of the network topology gradually decreasing with increasing rewiring probability. Reducing the variance of fibers' strength, the exponents of the size and the duration distribution of cascades increase in the localized regime of the failure process, while the localized to mean field transition becomes more abrupt. The consistency of the results is supported by a scaling analysis relating the characteristic exponents of the statistics and dynamics of cascades.

Mean-field theory of social laser

In this work we suggest a novel paradigm of social laser (solaser), which can explain such Internet inspired social phenomena as echo chambers, reinforcement and growth of information cascades, enhancement of social actions under strong mass media operation. The solaser is based on a well-known in quantum physics laser model of coherent amplification of the optical field. Social networks are at the core of the solaser model; we define them by means of a network model possessing power–law degree distribution. In the solaser the network environment plays the same role as the gain medium has in a physical laser device. We consider social atoms as decision making agents (humans or even chat bots), which possess two (mental) states and occupy the nodes of a network. The solaser establishes communication between the agents as absorption and spontaneous or stimulated emission of socially actual information within echo chambers, which mimic an optical resonator of a convenient (physical) laser. We have demonstrated that social lasing represents the second order nonequilibrium phase transition, which evokes the release of coherent socially stimulated information field represented with the order parameter. The solaser implies the formation of macroscopic social polarization and results in a huge social impact, which is realized by viral information cascades occurring in the presence of population imbalance (social bias). We have shown that decision making agents follow an adiabatically time dependent mass media pump, which acts in the network community reproducing various reliable scenarios for information cascade evolution. We have also shown that in contrast to physical lasers, due to node degree peculiarities, the coupling strength of decision making agents with the network may be enhanced sqrt{langle krangle } times. It leads to a large increase of speed, at which a viral message spreads through a social media. In this case, the mass media pump supports additional reinforcement and acceleration of cascade growth. We have revealed that the solaser model in some approximations possesses clear links with familiar Ising and SIS (susceptible-infected-susceptible) models typically used for evaluating a social impact and information growth, respectively. However, the solaser paradigm can serve as a new platform for modelling temporal social events, which originate from “microscopic” (quantum-like) processes occurring in the society. Our findings open new perspectives for interdisciplinary studies of distributed intelligence agents behavior associated with information exchange and social impact.

Effect of Stress on Irradiation Responses of Highly Oriented Pyrolytic Graphite.

The effect of stress on irradiation responses of highly oriented pyrolytic graphite (HOPG) was studied by combing molecular dynamics (MD) simulation, proton irradiation, and Raman characterization. MD simulations of carbon knock-on at energies < 60 eV were used to obtain average threshold displacement energies () as a function of strain ranging from 0 to 10%. Simulations at a higher irradiation energy of 2–5 keV were used to study the effect of strain on damage cascade evolution. With increasing tensile strain, was reduced from 35 eV at 0% strain to 31 eV at 10% strain. The strain-reduced led to a higher damage peak and more surviving defects (up to 1 ps). Furthermore, high strains induced local cleavage around the cavities, as one additional mechanism of damage enhancement. Experimentally, HOPG film was folded, and the folded region with the maximum tensile stress was irradiated by a 2 MeV proton beam. Raman characterization showed significantly enhanced D to G modes in comparison to the stress-free irradiation. Based on the strain dependence of and the Kinchin–Pease model, a formula for displacement estimation under different tensile strains is proposed. The stress effects need to be considered in graphite applications in a reactor’s harsh environment where both neutron damage and stress are present.

Analysis of Cascading Failure Evolution Process of High Proportion New Energy Power System

The strong randomness of new energy, the weak anti-disturbance ability of power electronic equipment, and the interactive influence of multiple uncertainties in the source, network, and load side make the cascading failure evolution process of the high-proportion new energy power system more complicated. In order to reveal the evolution process of cascading failures, based on the defined key characteristic events, this paper divides the evolution process of cascading failures of high proportion new energy power system into the initial stage, development stage, and deterioration stage, and expounds its cascading situation in stages. Based on a DC project, cases with DC system was constructed, and the evolution process of cascading failures in high-proportion new energy power systems was simulated and analyzed.

Role of electronic energy loss on defect production and interface stability: Comparison between ceramic materials and high-entropy alloys

High-entropy alloys (HEAs) and some complex alloys exhibit desirable properties and significant structural stability in harsh environments, including possible applications in advanced reactors. Energetic ion irradiation is often used as a surrogate for neutron irradiation; however, the impact of ion electronic energy deposition and dissipation is often neglected. Moreover, differences in recoil energy spectrum and density of cascade events on damage evolution must also be considered. In many chemically complex alloys, the mean free path of electrons is reduced significantly, thus their decreased thermal conductivity and slow dissipation of localized radiation energy can have noticeable effects on displacement cascade evolution that is greatly different from metals with high thermal conductivity. In this work, nanocrystalline HEAs of Ni20Fe20Co20Cr20Cu20 and nonequiatomic (NiFeCoCr)97Cu3, both having much lower room-temperature thermal conductivity than pure Ni or Fe, are chosen as model HEAs to reveal the role that electronic energy loss during ion irradiation has in complex alloys. The response of nanocrystalline HEAs is investigated under irradiation at room temperature using MeV Ni and Au ions that have different ratios of electronic energy to damage energy, which is the energy dissipated in displacing atoms. Different from previously reported amorphization of nanocrystalline SiC, experimental results on these HEAs show that, similar to the process in nanocrystalline oxide materials, both inelastic thermal spikes via electron–phonon coupling and elastic thermal spikes via collisions among atomic nuclei contribute to the overall grain growth. The growth follows a power law dependence with the total deposited ion energy, and the derived value of the power-exponent suggests that the irradiation-induced instability at and near grain boundaries leads to local rapid atomic rearrangements and consequently grain growth. The high power-exponent value can be attributed to the sluggish diffusion and delayed defect evolution arising from the chemical complexity intrinsic to HEAs. This work calls attention to quantified fundamental understanding of radiation damage processes beyond that of simplified displacement events, especially in simulating neutron environments.

Vulnerability Analysis of Urban Rail Transit Network considering Cascading Failure Evolution

Vulnerability analysis is the premise of operational risk management and control for the large-scale and complex urban rail transit network (URTN) under the operation interruption of important stations. The temporary operation interruption of one station in an emergency may lead to the cascading failure and the paralysis of the whole URTN due to the load of other stations exceeding the limited capacity. The priority of important stations is proposed by combining its location and function in URTN. In addition, focusing on the analysis of the travel behaviour of passengers and the synergy of public transport networks, a novel cascading failure evolution model is established to simulate the cascading failure process of URTN under different attack scenarios. The vulnerability indicators are constructed to dynamically evaluate the vulnerability of URTN considering cascading failure evolution, which are different from the traditional vulnerability indicators based on complex network theory. Taking the Beijing urban rail transit network as an example, the dynamic simulation results show that the cascading failure of URTN is closely related to the temporal-spatial distribution of passenger flows and malicious attacks are more destructive than random attacks. Compared with the important stations with the largest betweenness or degree, the interrupted stations with largest intensity have a greater impact on the operational stability of URTN. Moreover, increasing the capacity coefficient of the station can reduce the vulnerability of URTN.

Simulation-based methodology to assess the lattice defects creation as energy storing process

In nuclear industry, damages caused to in-core structural materials by high-energy neutrons have been studied for years. Recently, the possibility of storing energy through the creation of defects in crystalline materials via heavy particle bombardment was investigated. To evaluate the potential of the Wigner effect as energy-storing process, a graphite-moderated Molten Salt Reactor was adopted as a test case. Neutronics simulations performed with OpenMC Monte Carlo code allowed estimating the amount of energy released during fission events, the fraction that is deposited in graphite, and the fraction that has the potential to cause radiation damages. Molecular dynamics simulations were then performed to study the evolution of cascades triggered by high-energy neutrons. As a major outcome, a more accurate estimate of the radiation damage with respect to the traditional approaches was obtained, and the fraction of the deposited neutron energy that can be stored through long-lived defects was quantified.

Plasticity in plastid redox networks: evolution of glutathione-dependent redox cascades and glutathionylation sites

BackgroundFlexibility of plant metabolism is supported by redox regulation of enzymes via posttranslational modification of cysteine residues, especially in plastids. Here, the redox states of cysteine residues are partly coupled to the thioredoxin system and partly to the glutathione pool for reduction. Moreover, several plastid enzymes involved in reactive oxygen species (ROS) scavenging and damage repair draw electrons from glutathione. In addition, cysteine residues can be post-translationally modified by forming a mixed disulfide with glutathione (S-glutathionylation), which protects thiol groups from further oxidation and can influence protein activity. However, the evolution of the plastid glutathione-dependent redox network in land plants and the conservation of cysteine residues undergoing S-glutathionylation is largely unclear.ResultsWe analysed the genomes of nine representative model species from streptophyte algae to angiosperms and found that the antioxidant enzymes and redox proteins belonging to the plastid glutathione-dependent redox network are largely conserved, except for lambda- and the closely related iota-glutathione S-transferases. Focussing on glutathione-dependent redox modifications, we screened the literature for target thiols of S-glutathionylation, and found that 151 plastid proteins have been identified as glutathionylation targets, while the exact cysteine residue is only known for 17% (26 proteins), with one or multiple sites per protein, resulting in 37 known S-glutathionylation sites for plastids. However, 38% (14) of the known sites were completely conserved in model species from green algae to flowering plants, with 22% (8) on non-catalytic cysteines. Variable conservation of the remaining sites indicates independent gains and losses of cysteines at the same position during land plant evolution.ConclusionsWe conclude that the glutathione-dependent redox network in plastids is highly conserved in streptophytes with some variability in scavenging and damage repair enzymes. Our analysis of cysteine conservation suggests that S-glutathionylation in plastids plays an important and yet under-investigated role in redox regulation and stress response.

Influence of helium on the evolution of irradiation-induced defects in tungsten: An object kinetic Monte Carlo simulation* *Project supported by the Science Challenge Project (Grant No. TZ2018002), the National Natural Science Foundation of China (Grant No. 11905135), and the National MCF Energy R&D Program of China (Grant No. 2018YFE0308103).

Understanding the evolution of irradiation-induced defects is of critical importance for the performance estimation of nuclear materials under irradiation. Hereby, we systematically investigate the influence of He on the evolution of Frenkel pairs and collision cascades in tungsten (W) via using the object kinetic Monte Carlo (OKMC) method. Our findings suggest that the presence of He has significant effect on the evolution of irradiation-induced defects. On the one hand, the presence of He can facilitate the recombination of vacancies and self-interstitial atoms (SIAs) in W. This can be attributed to the formation of immobile He-SIA complexes, which increases the annihilation probability of vacancies and SIAs. On the other hand, due to the high stability and low mobility of He-vacancy complexes, the growth of large vacancy clusters in W is kinetically suppressed by He addition. Specially, in comparison with the injection of collision cascades and He in sequential way at 1223 K, the average sizes of surviving vacancy clusters in W via simultaneous way are smaller, which is in good agreement with previous experimental observations. These results advocate that the impurity with low concentration has significant effect on the evolution of irradiation-induced defects in materials, and contributes to our understanding of W performance under irradiation.

Hydrodynamical model of QED cascade expansion in an extremely strong laser pulse

The development of a self-sustained quantum electrodynamical (QED) cascade in a single strong laser pulse is studied analytically and numerically. A hydrodynamical approach is used to construct an analytical model of cascade evolution, which includes the key features of the cascade observed in 3D QED particle-in-cell (QED-PIC) simulations, such as the magnetic field dominance in the cascade plasma and laser energy absorption. The equations of the model are derived in closed form and solved numerically. Direct comparison between the solutions of the model equations and 3D QED-PIC simulations shows that our model is able to describe the complex nonlinear process of cascade development qualitatively well. Various regimes of the interaction based on the intensity of the laser pulse are revealed in both the solutions of the model equations and the results of the QED-PIC simulations.

Defect agglomeration induces a reduction in radiation damage resistance of In-rich In x Ga1−x N

To investigate the reason for the reduction in damage resistance of In x Ga1−x N with increasing indium (In) content, we used molecular dynamics methods to simulate the threshold displacement energies, the individual recoil damage and the overlapping cascade processes in In x Ga1−x N (x = 0.3, 0.5, 0.7) during ion implantation. The average threshold displacement energy of In x Ga1−x N decreases a little (from 41.0 eV to 34.6 eV) as the In content increases (from 0.3 to 0.7) and the number of defects produced by individual cascades increases less than 30% with increasing In content (from 0.3 to 0.7), while the overlapping cascade simulations showed that with In content increasing the dynamic annealing processes in cascades were significantly suppressed. Thus, the suppression of dynamic annealing in the cascades is the main reason for the reduction of damage resistance of In x Ga1−x N by adding In content. The analysis of defect distribution during overlapping cascades showed that defects in In-rich In x Ga1−x N (x = 0.7) agglomerate more rapidly as the irradiation dose increases and are likely to form large clusters, which are harder to anneal during cascade evolution. Therefore, the suppression of dynamic annealing in In-rich In x Ga1−x N can be attributed to the rapid agglomeration of defects with the irradiation dose.

A Survey of Information Cascade Analysis

The deluge of digital information in our daily life—from user-generated content, such as microblogs and scientific papers, to online business, such as viral marketing and advertising—offers unprecedented opportunities to explore and exploit the trajectories and structures of the evolution of information cascades. Abundant research efforts, both academic and industrial, have aimed to reach a better understanding of the mechanisms driving the spread of information and quantifying the outcome of information diffusion. This article presents a comprehensive review and categorization of information popularity prediction methods, fromfeature engineering and stochastic processes, throughgraph representation, todeep learning-based approaches. Specifically, we first formally define different types of information cascades and summarize the perspectives of existing studies. We then present a taxonomy that categorizes existing works into the aforementioned three main groups as well as the main subclasses in each group, and we systematically review cutting-edge research work. Finally, we summarize the pros and cons of existing research efforts and outline the open challenges and opportunities in this field.

Primary radiation damage characteristics in displacement cascades of FeCrAl alloys

Displacement cascades in FeCrAl alloys are simulated by molecular dynamics using a recently fitted embedded atom method (EAM) potential. The threshold displacement energy of the atoms in FeCrAl is firstly computed and then the evolution of displacement cascades is quantitatively analyzed with the recoil energy ranging from 0.5keV to 15keV, and the results are compared with Fe. The influence of temperature and the direction of the primary knock-on atom (PKA) are also investigated. The results show that temperature decreases the number of surviving Frenkel pairs, but the PKA direction has very little effect on them, similar to other materials. The cluster fraction and size for interstitials increase with both irradiation temperature and PKA energy, but the increase of vacancy clusters is smaller due to their lower mobility. Compared to the case of Fe, the presence of Cr and Al in FeCrAl slightly increases the surviving FPs in FeCrAl but reduces the number of clusters formed at the annealing phase. Cr can reduce the mobility of nearby Fe and thus the surviving interstitials are mostly in the form of relatively stable Fe-Cr dumbbells. Al has little influence on surviving FPs but will restrain the formation of clusters. The proportion of Cr in clusters is largely in excess of its atomic fraction in FeCrAl, while Al takes a tiny proportion.

Molecular dynamics simulation of displacement cascades in cubic silicon carbide

We use molecular dynamics (MD) methods to study collision cascades in cubic silicon carbide (3C-SiC), which is a candidate for various applications in nuclear industries. One Tersoff potential, which can reproduce the thermal and elastic properties of 3C-SiC, was firstly connected with ZBL potential. Collison cascades were generated by primary knock-on atoms (PKAs) with damage energies ranging between 1 keV and 10 keV at 300–1800 K. It was found that the temperature weakly influences the production of defects in the temperature range (300–1800 K). However, the number of point defects increases significantly as the PKA-energy increases. Carbon defects dominate most of the defects formed in collision cascades, and the dominance becomes less significant with the increase of temperature. Some high-density interstitial point defects were observed in the evolution of the collision cascade. As the PKA-energy increases, more and more defect clusters with larger sizes can be observed. For the current PKA energy range (≤10 keV), clusters with 1–5 vacancies and with 1–4 interstitials can be found, and clusters with a larger size are rare at the end of the quenching stage. The number of these defect clusters with various sizes is temperature independent. In these defect clusters, the carbon content exceeds 50% in most conditions. In addition, the carbon ratio in interstitial clusters is usually higher than the carbon site ratio in vacancy clusters. This work not only enriches the knowledge of the the number, size distribution and compositions of point defects and their clusters induced by neutron irradiation, but also can be input for the long-term simulation methods to understand the evolution of irradiated defects in 3C-SiC. Furthermore, the defect information can be used to study the thermal and elastic properties of 3C-SiC in future work.