We show that the self-part of the Van Hove function-the correlation function describing the dynamics of a single molecule-of water can be determined through a high-resolution inelastic x-ray scattering experiment. The measurement of inelastic x-ray scattering up to 10Å^-1 makes it possible to convert the inelastic x-ray scattering spectra into the Van Hove function, and its self-part is extracted from the short-range correlations. The diffusivity estimated from the short-range dynamics of water molecules is different from the long-range diffusivity measured by other methods. This approach using the experimentally determined self-part of the Van Hove function will be useful to the study of the local dynamics of atoms and molecules in liquids.Here we report on compression experiments of colloidal pillars in which the evolution of a shear band can be followed at the particle level during deformation. Quasistatic deformation results in dilation and anisotropic changes in coordination in a localized band of material. Additionally, a transition from solid- to liquidlike mechanical response accompanies the structural change in the band, as evidenced by saturation of the packing fraction at the glass transition point, a diminishing ability to host anelastic strains, and a rapid decay in the long-range strain correlations. Overall, our results suggest that shear banding quantitatively resembles a localized, driven glass transition.We investigate analytically and numerically the existence and dynamical stability of different localized modes in a two-dimensional photonic lattice comprising a square plaquette inscribed in the dodecagon lattices. The eigenvalue spectrum of the underlying linear lattice is characterized by a net formed of one flat band and four dispersive bands. By tailoring the intersite coupling coefficient ratio, opening of gaps between two pairs of neighboring dispersive bands can be induced, while the fully degenerate flat band characterized by compact eigenmodes stays nested between two inner dispersive bands. The nonlinearity destabilizes the compact modes and gives rise to unique families of localized modes in the newly opened gaps, as well as in the semi-infinite gaps. The governing mechanism of mode localization in that case is the light energy self-trapping effect. We have shown the stability of a few families of nonlinear modes in gaps. The suggested lattice model may serve for probing various artificial flat-band systems such as ultracold atoms in optical lattices, periodic electronic networks, and polariton condensates.We use queueing theory to develop a general framework for analyzing search processes with stochastic resetting, under the additional assumption that following absorption by a target, the particle (searcher) delivers a packet of resources to the target and the search process restarts at the reset point x_r. This leads to a sequence of search-and-capture events, whereby resources accumulate in the target under the combined effects of resource supply and degradation. Combining the theory of G/M/∞ queues with a renewal method for analyzing resetting processes, we derive general expressions for the mean and variance of the number of resource packets within the target at steady state. These expressions apply to both exponential and nonexponential resetting protocols and take into account delays arising from various factors such as finite return times, refractory periods, and delays due to the loading or unloading of resources. In the case of exponential resetting, we show how the resource statistics can be expressed in terms of the MFPTs T_r(x_r) and T_r+γ(x_r), where r is the resetting rate and γ is the degradation rate. This allows us to derive various general results concerning the dependence of the mean and variance on the parameters r,γ. Our results are illustrated using several specific examples. Finally, we show how fluctuations can be reduced either by allowing the delivery of multiple packets that degrade independently or by having multiple independent searchers.This Rapid Communication reports on the observation of an interesting phenomenon the shape, especially the length, of a microwave plasma jet (MPJ) can be clearly influenced by simply placing a conductor near the plasma source, particularly when the nearby conductor is in contact with the external conductor of the coaxial microwave plasma generator, accompanied by a significant change in microwave reflection power from the terminal. To further investigate this discovery, the relationships between the length of the plume and some important factors, such as the conductivity and length of the nearby conductor, microwave input power, and gas flow velocity, are analyzed, and we find nonlinear rules of influence of these factors on the jet. Measurements of the electric potential around the jet reveal the nonuniform and non-neutral charge distribution inside the visible plasma plume, which plays a vital role in uncovering the mechanism underlying this phenomenon. The results are helpful for providing a deeper understanding of microwave plasma jet characteristics. More importantly, it provides guidelines to control the MPJ using simple structures.We provide a general framework to model the growth of networks consisting of different coupled layers. Our aim is to estimate the impact of one such layer on the dynamics of the others. As an application, we study a scientometric network, where one layer consists of publications as nodes and citations as links, whereas the second layer represents the authors. This allows us to address the question of how characteristics of authors, such as their number of publications or number of previous coauthors, impacts the citation dynamics of a new publication. To test different hypotheses about this impact, our model combines citation constituents and social constituents in different ways.  https://www.selleckchem.com/products/pmsf-phenylmethylsulfonyl-fluoride.html  We then evaluate their performance in reproducing the citation dynamics in nine different physics journals. For this, we develop a general method for statistical parameter estimation and model selection that is applicable to growing multilayer networks. It takes both the parameter errors and the model complexity into account and is computationally efficient and scalable to large networks.