On-site residence time in a driven diffusive system: violation and recovery of mean-field

We investigate simple one-dimensional driven diffusive systems with open boundaries. We are interested in the average on-site residence time defined as the time a particle spends on a given site before moving on to the next site. Using mean-field theory, we obtain an analytical expression for the on-site residence times. By comparing the analytic predictions with numerics, we demonstrate that the mean-field significantly underestimates the residence time due to the neglect of time correlations in the local density of particles. The temporal correlations are particularly long-lived near the average shock position, where the density changes abruptly from low to high. By using Domain wall theory (DWT), we obtain highly accurate estimates of the residence time for different boundary conditions. We apply our analytical approach to residence times in a totally asymmetric exclusion process (TASEP), TASEP coupled to Langmuir kinetics (TASEP + LK), and TASEP coupled to mutually interactive LK (TASEP + MILK). The high accuracy of our predictions is verified by comparing these with detailed Monte Carlo simulations

The impact of species and cell type on the nanosafety profile of iron oxide nanoparticles in neural cells

Background: While nanotechnology is advancing rapidly, nanosafety tends to lag behind since general mechanistic insights into cell-nanoparticle (NP) interactions remain rare. To tackle this issue, standardization of nanosafety assessment is imperative. In this regard, we believe that the cell type selection should not be overlooked since the applicability of cell lines could be questioned given their altered phenotype. Hence, we evaluated the impact of the cell type on in vitro nanosafety evaluations in a human and murine neuroblastoma cell line, neural progenitor cell line and in neural stem cells. Acute toxicity was evaluated for gold, silver and iron oxide (IO) NPs, and the latter were additionally subjected to a multiparametric analysis to assess sublethal effects. Results: The stem cells and murine neuroblastoma cell line respectively showed most and least acute cytotoxicity. Using high content imaging, we observed cell type-and species-specific responses to the IONPs on the level of reactive oxygen species production, calcium homeostasis, mitochondrial integrity and cell morphology, indicating that cellular homeostasis is impaired in distinct ways. Conclusions: Our data reveal cell type-specific toxicity profiles and demonstrate that a single cell line or toxicity end point will not provide sufficient information on in vitro nanosafety. We propose to identify a set of standard cell lines for screening purposes and to select cell types for detailed nanosafety studies based on the intended application and/or expected exposure

A generalised path-following solver for robust analysis of material failure

When analysing complex structures with advanced damage or material models, it is important to use a robust solution method in order to trace the full equilibrium path. In light of this, we propose a new path-following solver based on the integral of the rate of dissipation in each material point, for solving problems exhibiting large energy dissipating mechanisms. The method is a generalisation and unification of previously proposed dissipation based path-following solvers, and makes it possible to describe a wider range of dissipation mechanisms, such as large strain plasticity. Furthermore, the proposed method makes it possible to, in a straightforward way, combine the effects from multiple dissipation mechanisms in a simulation. The capabilities of the solver are demonstrated on four numerical examples, from which it can be concluded that the proposed method is both versatile and robust, and can be used in different research domains within computational structural mechanics and material science

An adaptive isogeometric shell element for the prediction of initiation and growth of multiple delaminations in curved composite structures

In order to model prominent failure modes experienced by multi-layered composites, a fine through-thickness discretisation is needed. If the structure also has large in-plane dimensions, the computational cost of the model becomes large. In light of this, we propose an adaptive isogeometric continuum shell element for the analysis of multi-layered structures. The key is a flexible and efficient method for controlling the continuity of the out-of-plane approximation, such that fine detail is only applied in areas of the structure where it is required. We demonstrate how so-called knot insertion can be utilised to automatise an adaptive refinement of the shell model at arbitrary interfaces, thereby making it possible to model multiple initiation and growth of delaminations. Furthermore, we also demonstrate that the higher-order continuity of the spline-based approximations allows for an accurate recovery of transverse stresses on the element level, even for doubly-curved laminates under general load. With this stress recovery method, critical areas of the simulated structures can be identified, and new refinements (cracks) can be introduced accordingly. In a concluding numerical example of a cantilever beam with two initial cracks, we demonstrate that the results obtained with the adaptive isogeometric shell element show good correlation with experimental data

Spiking Neurons Learning Phase Delays

Time differences between the two ears are an important cue for animals to azimuthally locate a sound source. The first binaural brainstem nucleus, in mammals the medial superior olive, is generally believed to perform the necessary computations. Its cells are sensitive to variations of interaural time differences of about 10 μs. The classical explanation of such a neuronal time-difference tuning is based on the physical concept of delay lines. Recent data, however, are inconsistent with a temporal delay and rather favor a phase delay. By means of a biophysical model we show how spike-timing-dependent synaptic learning explains precise interplay of excitation and inhibition and, hence, accounts for a physical realization of a phase delay

Physical theory for near-bed turbulent particle suspension capacity.

The inability to capture the physics of solid-particle suspension in turbulent fluids in simple formulas is holding back the application of multiphase fluid dynamics techniques to many practical problems in nature and society involving particle suspension. We present a force balance approach to particle suspension in the region near no-slip frictional boundaries of turbulent flows. The force balance parameter Γ contains gravity and buoyancy acting on the sediment and vertical turbulent fluid forces; it includes universal turbulent flow scales and material properties of the fluid and particles only. Comparison to measurements shows that Γ = 1 gives the upper limit of observed suspended particle concentrations in a broad range of flume experiments and field settings. The condition of Γ > 1 coincides with the complete suppression of coherent turbulent structures near the boundary in direct numerical simulations of sediment-laden turbulent flow. Γ thus captures the maximum amount of sediment that can be contained in suspension at the base of turbulent flow, and it can be regarded as a suspension capacity parameter. It can be applied as a simple concentration boundary condition in modelling studies of the dispersion of particulates in environmental and man-made flows