Laboratory study of slope stability of granular media remains a challenge for modeling, understanding, and predicting natural hazards, such as avalanches and landslides, precursory signs of which are controlled by numerous physical parameters. The present work focuses on the impact of the humidity, in the range of 40-90%, on the stability of monodisperse dense packings of spherical beads. The beads are in a transparent box that is slowly and continuously tilted and allows simultaneous top and lateral optical measurements of global displacements of grains at the surface, defined as precursors. Humidity increases the cohesion between the grains. By performing successive avalanches that destabilize deeper granular layers, we assess the role of the exposure time to the high humidity rates in the diffusion process to reach the hygroscopic equilibrium inside the packing. We highlight an increase of the stability and first precursor angles, associated to a constant angle increment between two consecutive precursors, with a dependency with both the diameter (0.2,0.5, and 0.75 mm) and the material (glass and polystyrene) of the grains.Coulomb plasmas crystallize in a number of physical systems, such as dusty plasmas, neutron star crusts, and white dwarf cores. The crystal structure of the one-component and binary plasma has received significant attention in the literature, though the less studied multicomponent plasma may be most relevant for many physical systems which contain a large range of particle charges. We report on molecular dynamics simulations of multicomponent plasmas near the melting temperature with mixtures taken to be realistic x-ray burst ash compositions. We quantify the structure of the crystal with the bond order parameters and radial distribution function. Consistent with past work, low charge particles form interstitial defects and we argue that they are in a quasiliquid state within the lattice. The lattice shows screening effects which preserves long-range order despite the large variance in particle charges, which may impact transport properties relevant to astrophysics.We introduce a minimal hydrodynamic model of polarization, migration, and deformation of a biological cell confined between two parallel surfaces. In our model, the cell is driven out of equilibrium by an active cytsokeleton force that acts on the membrane. The cell cytoplasm, described as a viscous droplet in the Darcy flow regime, contains a diffusive solute that actively transduces the applied cytoskeleton force. While fairly simple and analytically tractable, this quasi-two-dimensional model predicts a range of compelling dynamic behaviours. A linear stability analysis of the system reveals that solute activity first destabilizes a global polarization-translation mode, prompting cell motility through spontaneous symmetry breaking. At higher activity, the system crosses a series of Hopf bifurcations leading to coupled oscillations of droplet shape and solute concentration profiles. At the nonlinear level, we find traveling-wave solutions associated with unique polarized shapes that resemble experimental observations. Altogether, this model offers an analytical paradigm of active deformable systems in which viscous hydrodynamics are coupled to diffusive force transducers.This corrects the article DOI 10.1103/PhysRevE.99.052116.A theoretically highly efficient mechanism, operating at high laser intensities and powers, is identified for spectral transferring huge laser energies to shorter ultraviolet and x-ray wavelengths. With megajoule laser energies currently available at near-optical wavelengths, this transfer would, in theory, enable megajoule x-ray lasers, a huge advance over the millijoules x-ray pulses produced now. In fact, enabling even kilojoule x-ray lasers would still be a fantastic advance, and a more likely achievable one, considering practical experimental inefficiencies.This corrects the article DOI 10.1103/PhysRevE.99.063203.Resilience describes a system’s ability to adjust its activity to retain the basic functionality when errors or failures occur in components (nodes) of the network. Due to the complexity of a system’s structure, different components in the system exhibit diversity in the ability to affect the resilience of the system, bringing us a great challenge to protect the system from collapse. A fundamental problem is therefore to propose a physically insightful centrality index, with which to quantify the resilience contribution of a node in any systems effectively. However, existing centrality indexes are not suitable for the problem because they only consider the network structure of the system and ignore the impact of underlying dynamic characteristics. To break the limits, we derive a new centrality index resilience centrality from the 1D dynamic equation of systems, with which we can quantify the ability of nodes to affect the resilience of the system accurately. Resilience centrality unveils the long-sought relations between the ability of nodes in a system’s resilience and network structure of the system the capacity is mainly determined by the degree and weighted nearest-neighbor degree of the node, in which weighted nearest-neighbor degree plays a prominent role. Further, we demonstrate that weighted nearest-neighbor degree has a positive impact on resilience centrality, while the effect of the degree depends on a specific parameter, average weighted degree β_eff, in the 1D dynamic equation. To test the performance of our approach, we construct four real networks from data, which corresponds to two complex systems with entirely different dynamic characteristics. The simulation results demonstrate the effectiveness of our resilience centrality, providing us theoretical insights into the protection of complex systems from collapse.We show that the Olami-Feder-Christensen model exhibits an effective ergodicity breaking transition as the noise is varied. Above the critical noise, the system is effectively ergodic because the time-averaged stress on each site converges to the global spatial average. In contrast, below the critical noise, the stress on individual sites becomes trapped in different limit cycles, and the system is not ergodic. To characterize this transition, we use ideas from the study of dynamical systems and compute recurrence plots and the recurrence rate. The order parameter is identified as the recurrence rate averaged over all sites and exhibits a jump at the critical noise. We also use ideas from percolation theory and analyze the clusters of failed sites to find numerical evidence that the transition, when approached from above, can be characterized by exponents that are consistent with hyperscaling.We propose a kinetic gelation model of polymer growth with two monomeric types that have distinct functionalities (reaction sites), and can polymerize using different reaction types. The heterotypic aggregation of two monomer types is modeled using a moment generating function approach by tracking the temporal evolution of a closed system of moment equations up until gelation. We investigate several scenarios of polymerization with two distinct monomers that differ in the types of reactions that can occur. We determine numerical and analytical conditions for finite time blow-up (the emergence of an oligomer of infinite size) that depend on initial conditions, reaction rates, and number of reaction sites per monomer.Simulations are widely used to study nucleation in first order phase transitions due to the fact that they have access to the relevant length and time scales. However, simulations face the problem that nucleation is an activated process. Therefore, rare event simulation techniques are needed to promote the formation of the critical nucleus. The Seeding method, where the simulations are started with the nucleus already formed, has proven quite useful in efficiently providing estimates of the nucleation rate for a wide range of orders of magnitude. So far, Seeding has been employed in the NPT ensemble, where the nucleus either grows or redissolves. Thus, several trajectories have to be run in order to find the thermodynamic conditions that make the seeded nucleus critical. Moreover, the nucleus lifetime is short and the statistics for obtaining its properties is consequently poor. To deal with these shortcomings we extend the Seeding method to the NVT ensemble. We focus on the problem of bubble nucleation in a metastable Lennard Jones fluid. We show that, in the NVT ensemble, it is possible to equilibrate and stabilise critical bubbles for a long time. The nucleation rate inferred from NVT-Seeding is fully consistent with that coming from NPT-Seeding. The former is quite suitable to obtain the nucleation rate along isotherms, whereas the latter is preferable if the dependence of the rate with temperature at constant pressure is required. Care should be taken with finite size effects when using NVT-Seeding. Further work is required to extend NVT seeding to other sorts of phase transitions.A Hamiltonian-based model of many harmonically interacting massive particles that are subject to linear friction and coupled to heat baths at different temperatures is used to study the dynamic approach to equilibrium and nonequilibrium stationary states. An equilibrium system is here defined as a system whose stationary distribution equals the Boltzmann distribution, the relation of this definition to the conditions of detailed balance and vanishing probability current is discussed both for underdamped as well as for overdamped systems. Based on the exactly calculated dynamic approach to the stationary distribution, the functional that governs this approach, which is called the free entropy S_free(t), is constructed. For the stationary distribution S_free(t) becomes maximal and its time derivative, the free entropy production S[over ̇]_free(t), is minimal and vanishes. Thus, S_free(t) characterizes equilibrium as well as nonequilibrium stationary distributions by their extremal and stability propertirature of the heat bath it is coupled to. Active particle models can be described in the same general framework, which thereby allows us to characterize their entropy production not only in the stationary state but also in the approach to the stationary nonequilibrium state. Finally, the connection to nonequilibrium thermodynamics formulations that include the reservoir entropy production is discussed.The geomagnetic field’s dipole undergoes polarity reversals in irregular time intervals. Particularly long periods without reversals (of the order of 10^7 yr), called superchrons, have occurred at least three times in the Phanerozoic (since 541 million years ago). We provide observational evidence for high non-Gaussianity in the vicinity of a transition to and from a geomagnetic superchron, consisting of a sharp increase in high-order moments (skewness and kurtosis) of the dipole’s distribution. Such an increase in the moments is a universal feature of crisis-induced intermittency in low-dimensional dynamical systems undergoing global bifurcations. This implies a temporal variation of the underlying parameters of the physical system. Through a low-dimensional system that models the geomagnetic reversals, we show that the increase in the high-order moments during transitions to geomagnetic superchrons is caused by the progressive destruction of global periodic orbits exhibiting both polarities as the system approaches a merging bifurcation.