Search

The development of satellite sensors and interferometry synthetic aperture radar (InSAR) technology has enabled the exploitation of their benefits for long-term structural health monitoring (SHM). However, some restrictions cause this process to provide a small number of images leading to the problem of small data for SAR-based SHM. Conversely, the major challenge of the long-term monitoring of civil structures pertains to variations in their inherent properties by environmental and/or operational variability. This article aims to propose new hybrid unsupervised learning methods for addressing these challenges. The methods in this work contain three main parts: (i) data augmentation by the Markov Chain Monte Carlo algorithm, (ii) feature normalization, and (iii) decision making via Mahalanobis-squared distance. The first method presented in this work develops an artificial neural network-based feature normalization by proposing an iterative hyperparameter selection of hidden neurons of the network. The second method is a novel unsupervised teacher-student learning by combining an undercomplete deep neural network and an overcomplete single-layer neural network. A small set of long-term displacement samples extracted from a few SAR images of TerraSAR-X is applied to validate the proposed methods. The results show that the methods can effectively deal with the major challenges in the SAR-based SHM applications.

Despite the several sources of inaccuracy, commercial microwave links (CML) have been recently exploited to estimate the average rainfall intensity along the radio path from signal attenuation. Validating these measurements against "ground truth" from conventional rainfall sensors, as rain gauges, is a challenging issue due to the different spatial sampling involved. Here, we assess the performance of a network of CML as opportunistic rainfall sensors in a challenging mountainous environment located in Northern Italy. The benchmark dataset was provided by an operational network of rain gauges and by three disdrometers. Moreover, disdrometer data were used to establish an accurate relationship between path attenuation and rainfall intensity. A new method was developed for assessing CML: time series of rainfall occurrence and rainfall depth, representative of CML radio path, were derived from the nearby rain gauges and disdrometers and compared with the same quantities gathered from the CML. It turns out that, over the very short integration times considered (10 min), CML perform well in detecting rainfall, whereas quantitative rainfall estimates may have large discrepancies.

An anisotropic colloidal shape in combination with an externally tunable interaction potential results in a plethora of self-assembled structures with potential applications toward the fabrication of smart materials. Here we present our investigation on the influence of an external magnetic field on the self-assembly of hematite-silica core-shell prolate colloids for two aspect ratios ρ = 2.9 and 3.69. Our study shows a rather counterintuitive but interesting phenomenon, where prolate colloids self-assemble into oblate liquid crystalline (LC) phases. With increasing concentration, particles with smaller ρ reveal a sequence of LC phases involving para-nematic, nematic, smectic, and oriented glass phases. The occurrence of a smectic phase for colloidal ellipsoids has been neither predicted nor reported before. Quantitative shape analysis of the particles together with extensive computer simulations indicate that in addition to ρ, a subtle deviation from the ideal ellipsoidal shape dictates the formation of this unusual sequence of field-induced structures. Particles with ρ = 2.9 exhibit a hybrid shape containing features from both spherocylinders and ellipsoids, which make their self-assembly behavior richer than that observed for either of the "pure" shapes. The shape of the particles with higher ρ matches closely with the ideal ellipsoids, as a result their phase behavior follows the one expected for a "pure" ellipsoidal shape. Using anisotropic building blocks and external fields, our study demonstrates the ramifications of the subtle changes in the particle shape on the field-directed self-assembled structures with externally tunable properties.

Double-stranded DNA (dsDNA) fragments exhibit noncovalent attractive interactions between their tips. It is still unclear how DNA liquid crystal self-assembly is affected by such blunt-end attractions. It is demonstrated that stiff dsDNA fragments with moderate aspect ratio can specifically self-assemble in concentrated aqueous solutions into different types of smectic mesophases on the basis of selectively screening of blunt-end DNA stacking interactions. To this end, this type of attractions are engineered at the molecular level by constructing DNA duplexes where the attractions between one or both ends are screened by short hairpin caps. All-DNA bilayer and monolayer smectic-A type of phases, as well as a columnar phase, can be stabilized by controlling attractions strength. The results imply that the so far elusive smectic-A in DNA rod-like liquid crystals is a thermodynamically stable phase. The existence of the bilayer smectic phase is confirmed by Monte-Carlo simulations of hard cylinders decorated with one attractive terminal site. This work demonstrates that DNA blunt-ends behave as well-defined monovalent attractive patches whose strength and position can be potentially precisely tuned, highlighting unique opportunities concerning the stabilization of nonconventional DNA-based lyotropic liquid crystal phases assembled by all-DNA patchy particles with arbitrary geometry and composition., (© 2021 The Authors. Small published by Wiley-VCH GmbH.)

Biological liquid crystals, originating from the self-assembly of biological filamentous colloids, such as cellulose and amyloid fibrils, show a complex lyotropic behaviour that is extremely difficult to predict and characterize. Here we analyse the liquid crystalline phases of amyloid fibrils, and sulfated and carboxylated cellulose nanocrystals and measure their Frank-Oseen elastic constants K1, K2 and K3 by four different approaches. The first two approaches are based on the benchmark of the predictions of: (i) a scaling form and (ii) a variational form of the Frank-Oseen energy functional with the experimental critical volumes at order-order liquid crystalline transitions of the tactoids. The third and the fourth methods imply: (iii) the direct scaling equations of elastic constants and (iv) a molecular theory predicting the elastic constants from the experimentally accessible contour length distributions of the filamentous colloids. These three biological systems exhibit diverse liquid crystalline behaviour, governed by the distinct elastic constants characterizing each colloid. Differences and similarities among the three systems are highlighted and interpreted based on the present analysis, providing a general framework to study dispersed liquid crystalline systems.

Liquid-crystalline phases in all-DNA systems have been extensively studied in the past and although nematic, cholesteric and columnar mesophases have been observed, the smectic phase remained elusive. Recently, it has been found evidence of a smectic-A ordering in an all-DNA system, where the constituent particles, which are gapped DNA duplexes, resemble chain-sticks. It has been argued that in the smectic-A phase these DNA chain-sticks should be folded as a means to suppress aggregate polydispersity and excluded volume. Nevertheless, if initial crystalline configurations are prepared in silico with gapped DNA duplexes either fully unfolded or fully folded by carrying out computer simulations one can end up with two different phases having at the same concentration and temperature the majority of gapped DNA duplexes either folded or unfolded. This result suggests that these two phases have a small free energy difference, since no transition is observed from one to the other within the simulation time span. In the present manuscript, we assess which of these two phases is thermodynamically stable through a suitable protocol based on thermodynamic integration. Our method is rather general and it can be used to discriminate stable states from metastable ones of comparable free energy.

Amyloid fibrils offer the possibility of controlling their contour length, aspect ratio, and length distribution, without affecting other structural parameters. Here we show that a fine control in the contour length distribution of β-lactoglobulin amyloid fibrils, achieved by mechanical shear stresses of different levels, translates into the organization of tactoids of different shapes and morphologies. While longer fibrils lead to highly elongated nematic tactoids in an isotropic continuous matrix, only sufficiently shortened amyloid fibrils lead to cholesteric droplets. The progressive decrease in amyloid fibrils length leads to a linear decrease of the anchoring strength and homogeneous tactoid → bipolar tactoid → cholesteric droplet transitions. Upon fibrils length increase, we first find experimentally and predict theoretically a decrease of the cholesteric pitch, before full disappearance of the cholesteric phase. The latter is understood to arise from the decrease of the energy barrier separating cholesteric and nematic phases over thermal energy for progressively longer, semiflexible fibrils.

Anisotropic interactions can bring about the formation, through self-assembly, of semi-flexible chains, which in turn can give rise to nematic phases for suitable temperatures and concentrations. A minimalist model constituted of hard cylinders decorated with attractive sites has been already extensively studied numerically. Simulation data shows that a theoretical approach recently proposed is able to properly capture the physical properties of these self-assembly-driven liquid crystals. Here, we investigated a simpler model constituted of bifunctional Kern-Frenkel hard spheres which does not possess steric anisotropy but which can undergo a istropic-nematic transition as a result of their self-assembly into semi-flexible chains. For this model we compare an accurate numerical estimate of isotropic-nematic phase boundaries with theoretical predictions. The theoretical treatment, originally proposed for cylinder-like particles, has been greatly simplified and its predictions are in good agreement with numerical results. Finally, we also assess a crucial, and not obvious, hypothesis used in the theory, i.e. the ability of the Onsager trial function to properly model particle orientation in the presence of aggregation, that has not been properly checked yet.

Maximum annual daily precipitation is a fundamental hydrologic variable that does not attain asymptotic conditions. Thus the classical extreme value theory (i.e., the Fisher-Tippett's theorem) does not apply and the recurrent use of the Generalized Extreme Value distribution (GEV) to estimate precipitation quantiles for structural-design purposes could be inappropriate. In order to address this issue, we first determine the exact distribution of maximum annual daily precipitation starting from a Markov chain and in a closed analytical form under the hypothesis of stochastic independence. As a second step, we formulate a superstatistics conjecture of daily precipitation, meaning that we assume that the parameters of this exact distribution vary from a year to another according to probability distributions, which is supported by empirical evidence. We test this conjecture using the world GHCN database to perform a worldwide assessment of this superstatistical distribution of daily precipitation extremes. The performances of the superstatistical distribution and the GEV are tested against data using the Kolmogorov-Smirnov statistic. By considering the issue of model's extrapolation, that is, the evaluation of the estimated model against data not used in calibration, we show that the superstatistical distribution provides more robust estimations than the GEV, which tends to underestimate (7-13%) the quantile associated to the largest cumulative frequency. The superstatistical distribution, on the other hand, tends to overestimate (10-14%) this quantile, which is a safer option for hydraulic design. The parameters of the proposed superstatistical distribution are made available for all 20,561 worldwide sites considered in this work.

Autocatalysis, i.e., the speeding up of a reaction through the very same molecule which is produced, is common in chemistry, biophysics, and material science. Rate-equation-based approaches are often used to model the time dependence of products, but the key physical mechanisms behind the reaction cannot be properly recognized. Here, we develop a patchy particle model inspired by a bicomponent reactive mixture and endowed with adjustable autocatalytic ability. Such a coarse-grained model captures all general features of an autocatalytic aggregation process that takes place under controlled and realistic conditions, including crowded environments. Simulation reveals that a full understanding of the kinetics involves an unexpected effect that eludes the chemistry of the reaction, and which is crucially related to the presence of an activation barrier. The resulting analytical description can be exported to real systems, as confirmed by experimental data on epoxy-amine polymerizations, solving a long-standing issue in their mechanistic description.

The hard cylinder model decorated with attractive patches proved to be very useful recently in studying physical properties of several colloidal systems. Phase diagram, elastic constants and cholesteric properties obtained from computer simulations based on a simple hard cylinder model have been all successfully and quantitatively compared to experimental results. Key to these simulations is an efficient algorithm to check the overlap between hard cylinders. Here, we propose two algorithms to check the hard cylinder overlap and we assess their efficiency through a comparison with an existing method available in the literature and with the well-established algorithm for simulating hard spherocylinders. In addition, we discuss a couple of optimizations for performing computer simulations of patchy anisotropic particles and we estimate the speed-up which they can provide in the case of patchy hard cylinders.

One of the ultimate goals of climate studies is to provide projections of future scenarios: for this purpose, sophisticated models are conceived, involving lots of parameters calibrated via observed data. The outputs of such models are used to investigate the impacts on related phenomena such as floods, droughts, etc. To evaluate the performance of such models, statistics like moments/quantiles are used, and comparisons with historical data are carried out. However, this may not be enough: correct estimates of some moments/quantiles do not imply that the probability distributions of observed and simulated data match. In this work, a distributional multivariate approach is outlined, also accounting for the fact that climate variables are often dependent. Suitable statistical tests are described, providing a non-parametric assessment exploiting the Copula Theory. These procedures allow to understand (i) whether the models are able to reproduce the distributional features of the observations, and (ii) how the models perform (e.g., in terms of future climate projections and changes). The proposed methodological approach is appropriate also in contexts different from climate studies, to evaluate the performance of any model of interest: methods to check a model per se are sketched out, investigating whether its outcomes are (statistically) consistent.

Many natural and industrial processes rely on constrained transport, such as proteins moving through cells, particles confined in nanocomposite materials or gels, individuals in highly dense collectives and vehicular traffic conditions. These are examples of motion through crowded environments, in which the host matrix may retain some glass-like dynamics. Here we investigate constrained transport in a colloidal model system, in which dilute small spheres move in a slowly rearranging, glassy matrix of large spheres. Using confocal differential dynamic microscopy and simulations, here we discover a critical size asymmetry, at which anomalous collective transport of the small particles appears, manifested as a logarithmic decay of the density autocorrelation functions. We demonstrate that the matrix mobility is central for the observed anomalous behaviour. These results, crucially depending on size-induced dynamic asymmetry, are of relevance for a wide range of phenomena ranging from glassy systems to cell biology.

In this paper we introduce a fully flexible coarse-grained model of immunoglobulin G (IgG) antibodies parametrized directly on cryo-EM data and simulate the binding dynamics of many IgGs to antigens adsorbed on a surface at increasing densities. Moreover, we work out a theoretical model that allows to explain all the features observed in the simulations. Our combined computational and theoretical framework is in excellent agreement with surface-plasmon resonance data and allows us to establish a number of important results. (i) Internal flexibility is key to maximize bivalent binding, flexible IgGs being able to explore the surface with their second arm in search for an available hapten. This is made clear by the strongly reduced ability to bind with both arms displayed by artificial IgGs designed to rigidly keep a prescribed shape. (ii) The large size of IgGs is instrumental to keep neighboring molecules at a certain distance (surface repulsion), which essentially makes antigens within reach of the second Fab always unoccupied on average. (iii) One needs to account independently for the thermodynamic and geometric factors that regulate the binding equilibrium. The key geometrical parameters, besides excluded-volume repulsion, describe the screening of free haptens by neighboring bound antibodies. We prove that the thermodynamic parameters govern the low-antigen-concentration regime, while the surface screening and repulsion only affect the binding at high hapten densities. Importantly, we prove that screening effects are concealed in relative measures, such as the fraction of bivalently bound antibodies. Overall, our model provides a valuable, accurate theoretical paradigm beyond existing frameworks to interpret experimental profiles of antibodies binding to multi-valent surfaces of different sorts in many contexts.

Unveiling the subtle rules that control the buildup of macroscopic chirality starting from chiral molecular elements is a challenge for theory and computations. In this context, a remarkable phenomenon is the formation of helically twisted nematic (cholesteric) phases, with pitch in the micrometer range, driven by self-assembly of relatively small chiral species into supramolecular semiflexible polymers. We have developed a theoretical framework to connect the cholesteric organization to the shape and chirality of the constituents, described with molecular detail, in this kind of system. The theory has been tested against new accurate measurements for solutions of short DNA duplexes. We show that the cholesteric organization is determined by steric repulsion between duplexes, and we identify distinctive features of linear self-assembly in the temperature and concentration dependence of the pitch.

The globular protein γB-crystallin exhibits a complex phase behavior, where liquid-liquid phase separation characterized by a critical volume fraction ϕc = 0.154 and a critical temperature Tc = 291.8 K coexists with dynamical arrest on all length scales at volume fractions around ϕ ≈ 0.3-0.35, and an arrest line that extends well into the unstable region below the spinodal. However, although the static properties such as the osmotic compressibility and the static correlation length are in quantitative agreement with predictions for binary liquid mixtures, this is not the case for the dynamics of concentration fluctuations described by the dynamic structure factor S(q,t). Using a combination of dynamic light scattering and neutron spin echo measurements, we demonstrate that the competition between critical slowing down and dynamical arrest results in a much more complex wave vector dependence of S(q,t) than previously anticipated.

We put forward a theoretical framework to calculate pair distribution functions in the nematic liquid crystals formed by sphere-cylinders that self-assemble in linear chain structures. For a nematically ordered system, one can distinguish between the spatial correlations in the plane perpendicular to the crystalline axis, and in the direction parallel to the latter. Following this separation, we show that the RDFs in the parallel case can be described using a superposition of a chain model and Onsager distribution, whereas the RDFs in the perpendicular case turn out to be that of the soft disks. Based on this concept, we show how the spatial correlations in the system are influenced by the nematic order parameter. We conclude that even if the nematic ordering is high in the system, the imperfection of the crystal is strongly reflected in the pair distributions.

We present a general approach based on nonequilibrium thermodynamics for bridging the gap between a well-defined microscopic model and the macroscopic rheology of particle-stabilised interfaces. Our approach is illustrated by starting with a microscopic model of hard ellipsoids confined to a planar surface, which is intended to simply represent a particle-stabilised fluid-fluid interface. More complex microscopic models can be readily handled using the methods outlined in this paper. From the aforementioned microscopic starting point, we obtain the macroscopic, constitutive equations using a combination of systematic coarse-graining, computer experiments and Hamiltonian dynamics. Exemplary numerical solutions of the constitutive equations are given for a variety of experimentally relevant flow situations to explore the rheological behaviour of our model. In particular, we calculate the shear and dilatational moduli of the interface over a wide range of surface coverages, ranging from the dilute isotropic regime, to the concentrated nematic regime.

Short cylinder-like DNA duplexes, comprising 6 to 20 base pairs, self-assemble into semi-flexible chains, due to coaxial stacking interactions between their blunt ends. The mutual alignment of these chains gives rise to macroscopically orientationally ordered liquid crystal phases. Interestingly, experiments show that the isotropic-nematic phase boundary is sequence-dependent. We perform all-atom simulations of several sequences to gain insights into the structural properties of the duplex and correlate the resulting geometric properties with the observed location of the isotropic-nematic phase boundary. We identify in the duplex bending the key parameter for explaining the sequence dependence, suggesting that DNA duplexes can be assimilated to bent-core mesogens. We also develop a coarse-grained model for the different DNA duplexes to evaluate in detail how bending affects the persistence length and excluded volume of the aggregates. This information is fed into a recently developed formalism to predict the isotropic-nematic phase boundary for bent-core mesogens. The theoretical results agree with the experimental observations.

Hard helices can be regarded as a paradigmatic elementary model for a number of natural and synthetic soft matter systems, all featuring the helix as their basic structural unit, from natural polynucleotides and polypeptides to synthetic helical polymers, and from bacterial flagella to colloidal helices. Here we present an extensive investigation of the phase diagram of hard helices using a variety of methods. Isobaric Monte Carlo numerical simulations are used to trace the phase diagram; on going from the low-density isotropic to the high-density compact phases a rich polymorphism is observed, exhibiting a special chiral screw-like nematic phase and a number of chiral and/or polar smectic phases. We present full characterization of the latter, showing that they have unconventional features, ascribable to the helical shape of the constituent particles. Equal area construction is used to locate the isotropic-to-nematic phase transition, and the results are compared with those stemming from an Onsager-like theory. Density functional theory is also used to study the nematic-to-screw-nematic phase transition; within the simplifying assumption of perfectly parallel helices, we compare different levels of approximation, that is second- and third-virial expansions and a Parsons-Lee correction.

Rangelands provide the main forage resource for livestock in many parts of the world, but maintaining long-term productivity and providing sufficient income for the rancher remains a challenge. One key issue is to maintain the rangeland in conditions where the rancher has the greatest possibility to adapt his/her management choices to a highly fluctuating and uncertain environment. In this study, we address management robustness and adaptability, which increase the resilience of a rangeland. After reviewing how the concept of resilience evolved in parallel to modelling views on rangelands, we present a dynamic model of rangelands to which we applied the mathematical framework of viability theory to quantify the management adaptability of the system in a stochastic environment. This quantification is based on an index that combines the robustness of the system to rainfall variability and the ability of the rancher to adjust his/her management through time. We evaluated the adaptability for four possible scenarios combining two rainfall regimes (high or low) with two herding strategies (grazers only or mixed herd). Results show that pure grazing is viable only for high-rainfall regimes, and that the use of mixed-feeder herds increases the adaptability of the management. The management is the most adaptive with mixed herds and in rangelands composed of an intermediate density of trees and grasses. In such situations, grass provides high quantities of biomass and woody plants ensure robustness to droughts. Beyond the implications for management, our results illustrate the relevance of viability theory for addressing the issue of robustness and adaptability in non-equilibrium environments.

The anisotropy of attractive interactions between particles can favor, through a self-assembly process, the formation of linear semi-flexible chains. In the appropriate temperatures and concentration ranges, the growing aspect ratio of the aggregates can induce formation of a nematic phase, as recently experimentally observed in several biologically relevant systems. We present here a numerical study of the isotropic-nematic phase boundary for a model of bifunctional polymerizing hard cylinders, to provide an accurate benchmark for recent theoretical approaches and to assess their ability to capture the coupling between self-assembly and orientational ordering. The comparison indicates the importance of properly modeling excluded volume and orientational entropy and provides a quantitative confirmation of some theoretical predictions.

Moist savannas and tropical forests share the same climatic conditions and occur side by side. Experimental evidences show that the tree cover of these ecosystems exhibits a bimodal frequency distribution. This is considered as a proof of savanna-forest bistability, predicted by dynamic vegetation models based on non-linear differential equations. Here, we propose a change of perspective about the bimodality of tree cover distribution. We show, using a simple matrix model of tree dynamics, how the bimodality of tree cover can emerge from the switching between two linear dynamics of trees, one in presence and one in absence of fire, with a feedback between fire and trees. As consequence, we find that the transitions between moist savannas and tropical forests, if sharp, are not necessarily catastrophic.

In the real world, diffusion-limited reactions in chemistry and biology mostly occur in crowded environments, such as macromolecular complex formation in the cell. Despite the paramount importance of such phenomena, theoretical approaches still mainly rely on the Smoluchowski theory, only valid in the infinite dilution limit. In this paper we introduce a novel theoretical framework to describe the encounter rate and the stationary density profiles for encounters between an immobilized target and a fluid of interacting spherical particles, valid in the local density approximation. A comparison with numerical simulations performed for a fluid of hard spheres and square well attractive hard spheres confirms the accuracy of our treatment.

The co-existence of trees and grasses in savannas in general can be the result of processes involving competition for resources (e.g. water and nutrients) or differential response to disturbances such as fire, animals and human activities; or a combination of both broad mechanisms. In moist savannas, the tree-grass coexistence is mainly attributed to of disturbances, while in dry savannas, limiting resources are considered the principal mechanism of co-existence. Virtually all theoretical explorations of tree-grass dynamics in dry savannas consider only competition for soil water. Here we investigate whether coexistence could result from a balanced competition for two resources, namely soil water and mineral nitrogen. We introduce a simple dynamical resource-competition model for trees and grasses. We consider two alternative hypotheses: (1) trees are the superior competitors for nitrogen while grasses are superior competitors for water, and (2) vice-versa. We study the model properties under the two hypotheses and test each hypothesis against data from 132 dry savannas in Africa using Kendall's test of independence. We find that Hypothesis 1 gets much more support than Hypothesis 2, and more support than the null hypothesis that neither is operative. We further consider gradients of rainfall and nitrogen availability and find that the Hypothesis 1 model reproduces the observed patterns in nature. We do not consider our results to definitively show that tree-grass coexistence in dry savannas is due to balanced competition for water and nitrogen, but show that this mechanism is a possibility, which cannot be a priori excluded and should thus be considered along with the more traditional explanations., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

We investigate numerically pseudo-first-order irreversible bimolecular reactions of the type A + B → B between hard spheres undergoing event-driven Brownian dynamics. We study the encounter rate and the survival probability of A particles as functions of the packing fraction ϕ in the trapping (a single particle diffusing among static non-overlapping traps) and target (many traps diffusing in the presence of a single static target particle) settings, as well as in the case of diffusing traps and particles (full mobility). We show that, since inertial effects are accounted for in our simulation protocol, the standard Smoluchowski theory of coagulation of non-interacting colloids is recovered only at times greater than a characteristic time Δt, marking the transition from the under-damped to the over-damped regime. We show that the survival probability S(t) decays exponentially during this first stage, with a rate 1/τ0 is proportional to φ. Furthermore, we work out a simple analytical expression that is able to capture to an excellent extent the numerical results for t < Δt at low and intermediate densities. Moreover, we demonstrate that the time constant of the asymptotic exponential decay of S(t) for diffusing traps and particles is k(S)(-1), where kS = 4π(DA + DB)Rρ is the Smoluchowski rate. Detailed analyses of the effective decay exponent β = d [log(-logS(t))]/d (logt) and of the steady-state encounter rate reveal that the full mobility and trapping problem are characterized by very similar kinetics, rather different from the target problem. Our results do not allow one to ascertain whether the prediction S(t) is proportional to exp(-at(3/2)) (a = const.) as t → ∞ for the trapping problem in 3D is indeed recovered. In fact, at high density, S(t) is dominated by short encounter times, which makes it exceedingly hard to record the events corresponding to the exploration of large, trap-free regions. As a consequence, at high densities the steady-state rate simply tends to 1/τ0. Finally, we work out an analytical formula for the rate that shows a remarkable agreement with the numerics up φ = 0.4.

The universal scaling between the average slow relaxation/transport and the average picosecond rattling motion inside the cage of the first neighbors has been evidenced in a variety of numerical simulations and experiments. Here, we first show that the scaling does not need information concerning the arbitrarily-defined glass transition region and relies on a single characteristic length scale a(2)(1/2) which is determined even far from that region. This prompts the definition of a novel reduced rattling amplitude (1/2) which has been investigated by extensive molecular-dynamics simulations addressing the slow relaxation, the diffusivity, and the fast cage-dynamics of both components of an atomic binary mixture. States with different potential, density, and temperature are considered. It is found that if two states exhibit coinciding incoherent van Hove function on the picosecond timescale, the coincidence is observed at long times too, including the large-distance exponential decay--a signature of heterogeneous dynamics--observed when the relaxation is slow. A major result of the present study is that the correlation plot between the diffusivity of the two components of the binary mixtures and their respective reduced rattling amplitude collapse on the same master curve. This holds true also for the structural relaxation of the two components and the unique master curve coincides with the one of the average scaling. It is shown that the breakdown of the Stokes-Einstein law exhibited by the distinct atomic species of the mixture and the monomers of a chain in a polymer melt is predicted at the same reduced rattling amplitude. Finally, we evidence that the well-known temperature/density thermodynamic scaling of the transport and the relaxation of the mixture is still valid on the picosecond timescale of the rattling motion inside the cage. This provides a link between the fast dynamics and the thermodynamic scaling of the slow dynamics.

The tree-grass co-existence in savannas involves multiple and sometimes connected biogeophysical conditions. The savanna domain, its boundaries, and transitions (gradual or abrupt) to other vegetation types (i.e., grassland or forest) are fundamental for the management of ecosystems and for preserving the biodiversity in present conditions and in future changing scenarios. Here we investigate the savanna domain within grazers-fire and browsers-fire parameter planes through a simple ecohydrological model of tree-grass-soil water dynamics. Stability maps allow to identify savanna domains and to show the behavior of vegetation under increasing pressure of grazing and browsing. Stability maps shed light on the causes behind possible vegetation abrupt transitions (e.g., forest collapse and bush encroachment). An application to 15 African savannas sites is presented and discussed with the support of a local sensitivity analysis of the model's parameters., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Recently, a simple scaling argument was introduced that allows us to map, with some precautions, Brownian and Monte Carlo dynamics for spherical particles. Here, we extend the scaling to study systems that have orientational degrees of freedom and carefully asses its validity over a wide region of temperature and density. Our work allows us to devise a Brownian Monte Carlo algorithm that produces, to a good approximation, physically meaningful trajectories with a minimum programming effort, although at the expense of some sampling efficiency., (© 2011 American Institute of Physics)

In the diffusion model of chemical reactions, the encounter (reaction) rate between reactant particles is governed by the Smoluchowski equation, which is a diffusion equation in a field of forces. We consider crowded environments where the particles diffuse through a "liquid" of like particles. Assuming that the liquid-like short-range structure around the reactant gives rise to an effective (osmotic) barrier leads us to map a complicated many-body problem to a one-dimensional problem. This allows us to describe theoretically such complex systems that are encountered in many applications where crowding, intermolecular interactions, and flow are simultaneously present. A particularly important effect is discovered which is due to the interplay between shear and crowding. This effect is responsible for unexpected peaks in the reactivity at low flow intensity which may explain, among other things, the bizarre colloidal stability behavior of concentrated protein suspensions.

The mechanisms permitting the co-existence of tree and grass in savannas have been a source of contention for many years. The two main classes of explanations involve either competition for resources, or differential sensitivity to disturbances. Published models focus principally on one or the other of these mechanisms. Here we introduce a simple ecohydrologic model of savanna vegetation involving both competition for water, and differential sensitivity of trees and grasses to fire disturbances. We show how the co-existence of trees and grasses in savannas can be simultaneously controlled by rainfall and fire, and how the relative importance of the two factors distinguishes between dry and moist savannas. The stability map allows to predict the changes in vegetation structure along gradients of rainfall and fire disturbances realistically, and to clarify the distinction between climate- and disturbance-dependent ecosystems., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Hard spheres interacting through a square well potential were simulated by using two different methods: Brownian cluster dynamics (BCD) and event driven Brownian dynamics (EDBD). The structure of the equilibrium states obtained by both methods was compared and found to be almost identical. Self-diffusion coefficients (D) were determined as a function of the interaction strength. The same values were found by using BCD or EDBD. Contrary to EDBD, BCD allows one to study the effect of bond rigidity and hydrodynamic interaction within the clusters. When the bonds are flexible, the effect of attraction on D is relatively weak compared to systems with rigid bonds. D increases first with increasing attraction strength, and then decreases for stronger interaction. Introducing intracluster hydrodynamic interaction weakly increases D for a given interaction strength. Introducing bond rigidity causes a strong decrease in D which no longer shows a maximum as function of the attraction strength.

We report event-driven molecular dynamics simulations of the irreversible gelation of hard ellipsoids of revolution containing several associating groups, characterizing how the cluster size distribution evolves as a function of the extent of reaction, both below and above the gel point. We find that over a very large interval of values of the extent of reaction, parameter-free mean-field predictions are extremely accurate, providing evidence that in this model the Ginzburg zone near the gel point, where non-mean field effects are important, is very limited. We also find that the Flory's hypothesis for the post-gelation regime properly describes the connectivity of the clusters even if the long-time limit of the extent of reaction does not reach the fully reacted state. This study shows that irreversibly aggregating asymmetric hard-core patchy particles may provide a close realization of the mean-field model, for which available theoretical predictions may help control the structure and the connectivity of the gel state. Besides chemical gels, the model is relevant to network-forming soft materials like systems with bioselective interactions, functionalized molecules and patchy colloids.

We report a numerical investigation of the viscoelastic behavior in models for steric repulsive and short-ranged attractive colloidal suspensions, along different paths in the attraction strength vs packing fraction plane. More specifically, we study the behavior of the viscosity (and its frequency dependence) on approaching the repulsive glass, the attractive glass, and in the reentrant region where viscosity shows a nonmonotonic behavior on increasing attraction strength. On approaching the glass lines, the increase of the viscosity is consistent with a power-law divergence with the same exponent and critical packing fraction previously obtained for the divergence of the density fluctuations. Based on mode-coupling calculations, we associate the increase of the viscosity with specific contributions from different length scales. We also show that the results are independent of the microscopic dynamics by comparing Newtonian and Brownian simulations for the same model. Finally, we evaluate the Stokes-Einstein relation approaching both glass transitions, finding a clear breakdown which is particularly strong for the case of the attractive glass.

We study the dynamics of monodisperse hard ellipsoids via a new event-driven molecular dynamics algorithm as a function of volume fraction phi and aspect ratio X0. We evaluate the translational D(trans) and the rotational D(rot) diffusion coefficients and the associated isodiffusivity lines in the phi-X0 plane. We observe a decoupling of the translational and rotational dynamics which generates an almost perpendicular crossing of the D(trans) and D(rot) isodiffusivity lines. While the self-intermediate scattering function exhibits stretched relaxation, i.e., glassy dynamics, only for large phi and X(0) approximately 1, the second order orientational correlator C2(t) shows stretching only for large and small X0 values. We discuss these findings in the context of a possible prenematic order driven glass transition.

Brownian dynamics algorithms integrate Langevin equations numerically and allow to probe long time scales in simulations. A common requirement for such algorithms is that interactions in the system should vary little during an integration time step; therefore, computational efficiency worsens as the interactions become steeper. In the extreme case of hard-body interactions, standard numerical integrators become ill defined. Several approximate schemes have been invented to handle such cases, but little emphasis has been placed on testing the correctness of the integration scheme. Starting from the two-body Smoluchowski equation, the authors discuss a general method for the overdamped Brownian dynamics of hard spheres, recently developed by one of the authors. They test the accuracy of the algorithm and demonstrate its convergence for a number of analytically tractable test cases.

The authors report Brownian dynamics simulation of the out-of-equilibrium dynamics (aging) in a colloidal suspension composed of rigid charged disks, one possible model for Laponite, a synthetic clay deeply investigated in the last few years by means of various experimental techniques. At variance with previous numerical investigations, mainly focusing on static structure and equilibrium dynamics, the authors explore the out-of-equilibrium aging dynamics. They analyze the wave vector and waiting time dependence of the dynamics, focusing on the single-particle and collective density fluctuations (intermediate scattering functions), the mean-squared displacement, and the rotational dynamics. Their findings confirm the complexity of the out-of-equilibrium dynamical behavior of this class of colloidal suspensions and suggest that an arrested disordered state driven by a repulsive Yukawa potential, i.e., a Wigner glass, can be observed in this model.

We report extensive Monte Carlo and event-driven molecular dynamics simulations of the fluid and liquid phase of a primitive model for silica recently introduced by Ford et al. [J. Chem. Phys. 121, 8415 (2004)]. We evaluate the isodiffusivity lines in the temperature-density plane to provide an indication of the shape of the glass transition line. Except for large densities, arrest is driven by the onset of the tetrahedral bonding pattern and the resulting dynamics is strong in Angell's classification scheme [J. Non-Cryst. Solids 131-133, 13 (1991)]. We compare structural and dynamic properties with corresponding results of two recently studied primitive models of network forming liquids-a primitive model for water and an angular-constraint-free model of four-coordinated particles-to pin down the role of the geometric constraints associated with bonding. Eventually we discuss the similarities between "glass" formation in network forming liquids and "gel" formation in colloidal dispersions of patchy particles.

We report extensive Monte Carlo and event-driven molecular dynamics simulations of a liquid composed of particles interacting via hard-sphere interactions complemented by four tetrahedrally coordinated short-range attractive ("sticky") spots, a model introduced several years ago by Kolafa and Nezbeda (Kolafa, J.; Nezbeda, I. Mol. Phys. 1987, 87, 161). To access the dynamic properties of the model, we introduce and implement a new event-driven molecular dynamics algorithm suited to study the evolution of hard bodies interacting, beside the repulsive hard-core, with a short-ranged interpatch square well potential. We evaluate the thermodynamic properties of the model in deep supercooled states, where the bond network is fully developed, providing evidence of density anomalies. Different from models of spherically symmetric interacting particles, the liquid can be supercooled without encountering the gas-liquid spinodal in a wide region of packing fractions phi. Around an optimal phi, a stable fully connected tetrahedral network of bonds develops. By analyzing the dynamics of the model we find evidence of anomalous behavior: around the optimal packing, dynamics accelerate on both increasing and decreasing phi. We locate the shape of the isodiffusivity lines in the (phi - T) plane and establish the shape of the dynamic arrest line in the phase diagram of the model. Results are discussed in connection with colloidal dispersions of sticky particles and gel-forming proteins and their ability to form dynamically arrested states.

We perform event-driven molecular dynamics simulations of a system composed by uniaxial hard ellipsoids for different values of the aspect ratio and packing fraction. We compare the molecular orientational-dependent structure factors previously calculated within the Percus-Yevick approximation with the numerical results. The agreement between theoretical and numerical results is rather satisfactory. We also show that, for specific orientational quantities, the molecular structure factors are sensitive to the particle shape and can be used to distinguish prolate from oblate ellipsoids. A first order theoretical expansion around the spherical shape and a geometrical analysis of the configurations confirms and explains such an observation.

We numerically study the dependence of the dynamics on the range of interaction Delta for the short-range square well potential. We find that, for small Delta, dynamics scale exactly in the same way as thermodynamics, both for Newtonian and Brownian microscopic dynamics. For interaction ranges from a few percent down to the Baxter limit, the relative location of the attractive-glass line and the liquid-gas line does not depend on Delta. This proves that, in this class of potentials, disordered arrested states (gels) can be generated only as a result of a kinetically arrested phase separation.

Generation of equilibrium configurations is the major obstacle for numerical investigation of the slow dynamics in supercooled liquid states. The parallel tempering (PT) technique, originally proposed for the numerical equilibration of discrete spin-glass model configurations, has recently been applied in the study of supercooled structural glasses. We present an investigation of the ability of parallel tempering to properly sample the liquid configuration space at different temperatures, by mapping the PT dynamics into the dynamics of the closest local potential energy minima (inherent structures). Comparing the PT equilibration process with the standard molecular dynamics equilibration process we find that the PT does not increase the speed of equilibration of the (slow) configurational degrees of freedom.

The transport and relaxation properties of a molecular supercooled liquid on an isobar are studied by molecular dynamics. The molecule is a rigid heteronuclear biatomic system. The diffusivity is fitted over four orders of magnitude by the power law D proportional to (T-T(c))(gamma(D)), with gamma(D)=1.93+/-0.02 and T(c)=0.458+/-0.002. The self-part of the intermediate scattering function F(s)(k(max),t) exhibits a steplike behavior at the lowest temperatures. On cooling, the increase of the related relaxation time tau(alpha) tracks the diffusivity, i.e., tau(alpha) proportional to (k(2)(max)D)(-1). At the lowest temperatures, fractions of highly mobile and trapped molecules are also evidenced. Translational jumps are also evidenced. The duration of the jumps exhibits a distribution. The distribution of the waiting times before a jump takes place, psi(t), is exponential at higher temperatures. At lower temperatures a power-law divergence is evidenced at short times, psi(t) proportional to t(xi-1) with 0

The rotational dynamics of a supercooled model liquid of rigid A-B dumbbells interacting via a Lennard-Jones potential is investigated along one single isobar. The time-temperature superposition principle, one key prediction of mode-coupling theory (MCT), was studied for the orientational correlation functions C(l). In agreement with previous studies we found that the scaling of C(l) in a narrow region at long times is better at high-l values. However, on a wider time interval the scaling works fairly better at low-l values. Consistently, we observed the remarkable temperature dependence of the rotational correlation time tau(1) as a power law in T-T(c) over more than three orders of magnitude and the increasing deviations from that law on increasing l (T(c) is the MCT critical temperature). For 0.7

RF current delivery may cause acute and chronic dysfunction of previously implanted pacemakers. The aim of this study was to assess prospectively the effects of RF energy on Thera I and Kappa pacemakers in 70 consecutive patients (mean age 70 +/- 11 years, mean left ventricular ejection fraction 48 +/- 15%) who underwent RF ablation of the AV junction for antiarrhythmic drug refractory atrial fibrillation (permanent in 42 patients, paroxysmal in 28). These pacing systems incorporate protection elements to avoid electromagnetic interference. The pacemakers (Thera DR 7960 I in 20 patients, Thera SR 8960 I in 30, Kappa DR 600-601 in 8, Kappa SR 700-701 in 12) were implanted prior to RF ablation in a single session procedure and were transiently programmed to VVI mode at a rate of 30 beats/min. Capsure SP and Z unibipolar leads were used. During RF application there was continuous monitoring of three ECG leads, endocavitary electrograms, and event markers. Complete AV block was achieved in all cases after 3.6 +/- 2.9 RF pulses and 100 +/- 75 seconds of RF energy delivery. The mean time of pacemaker implantation and RF ablation was 60 +/- 20 minutes. Transient or permanent pacemaker dysfunction including under/oversensing, reversion to a "noise-mode" pacing, pacing inhibition, reprogramming, or recycling were not observed. Leads impedance, sensing, and pacing thresholds remained in the normal range in the acute and long-term phase (average follow-up 18 +/- 12 months). In conclusion, Thera I and Kappa pacemakers exhibit excellent protection against interference produced by RF current. The functional integrity of the pacemakers and Capsure leads was observed in the acute and chronic phases. Thus, the implantation of these pacing systems prior to RF ablation of the AV junction can be recommended.