Ensemble Behavior Research Articles

Dynamic modeling of the tight junction pore pathway.

Claudins define paracellular permeability to small molecules by forming ion-selective pores within the tight junction. We recently demonstrated that claudin-2 channels are gated and open and close on a submillisecond timescale. To determine if and how the ensemble behavior of this unique class of entirely extracellular gated ion channels could define global epithelial barrier function, we have developed an in silico model of local claudin-2 behavior. This model considers the complex anastomosing ultrastructure of tight junction strands and can be scaled to show that local behavior defines global epithelial barrier function of epithelial monolayers expressing different levels of claudin-2. This is the first mathematical model to describe global epithelial barrier function in terms of the dynamic behavior of single tight junction channels and establishes a framework to consider gating kinetics as a means to regulate barrier function.

A continuum theory of edge dislocations

Continuum theory of dislocation aims to describe the behavior of large ensembles of dislocations. This task is far from completion, and, most likely, does not have a “universal solution”, which is applicable to any dislocation ensemble. In this regards it is important to have guiding lines set by benchmark cases, where the transition from a discrete set of dislocations to a continuum description is made rigorously. Two such cases have been considered recently: equilibrium of dislocation walls and screw dislocations in beams. In this paper one more case is studied, equilibrium of a large set of 2D edge dislocations placed randomly in a 2D bounded region. The major characteristic of interest is energy of dislocation ensemble, because it determines the structure of continuum equations. The homogenized energy functional is obtained for the periodic dislocation ensembles with a random contents of the periodic cell. Parameters of the periodic structure can change slowly on distances of order of the size of periodic cells. The energy functional is obtained by the variational-asymptotic method. Equilibrium positions are local minima of energy. It is confirmed the earlier assertion that energy density of the system is the sum of elastic energy of averaged elastic strains and microstructure energy, which is elastic energy of the neutralized dislocation system, i.e. the dislocation system placed in a constant dislocation density field making the averaged dislocation density zero.The computation of energy is reduced to solution of a variational cell problem. This problem is solved analytically. The solution is used to investigate stability of simple dislocation arrays, i.e. arrays with one dislocation in the periodic cell.The relations obtained yield two outcomes: First, there is a state parameter of the system, dislocation polarization; averaged stresses affect only dislocation polarization and cannot change other characteristics of the system. Second, the structure of dislocation phase space is strikingly simple. Dislocation phase space is split in a family of subspaces corresponding to constant values of dislocation polarizations; in each equipolarization subspace there are many local minima of energy; for zero external stresses the system is stuck in a local minimum of energy; for non-zero slowly changing external stress, dislocation polarization evolves, while the system moves over local energy minima of equipolarization subspaces. Such a simple picture of dislocation dynamics is due to the presence of two time scales, slow evolution of dislocation polarization and fast motion of the system over local minima of energy. The existence of two time scales is justified for a neutral system of edge dislocations.

Neuromorphic device architectures with global connectivity through electrolyte gating

Information processing in the brain takes place in a network of neurons that are connected with each other by an immense number of synapses. At the same time, neurons are immersed in a common electrochemical environment, and global parameters such as concentrations of various hormones regulate the overall network function. This computational paradigm of global regulation, also known as homeoplasticity, has important implications in the overall behaviour of large neural ensembles and is barely addressed in neuromorphic device architectures. Here, we demonstrate the global control of an array of organic devices based on poly(3,4ethylenedioxythiophene):poly(styrene sulf) that are immersed in an electrolyte, a behaviour that resembles homeoplasticity phenomena of the neural environment. We use this effect to produce behaviour that is reminiscent of the coupling between local activity and global oscillations in the biological neural networks. We further show that the electrolyte establishes complex connections between individual devices, and leverage these connections to implement coincidence detection. These results demonstrate that electrolyte gating offers significant advantages for the realization of networks of neuromorphic devices of higher complexity and with minimal hardwired connectivity.

Memory-induced diffusive-superdiffusive transition: Ensemble and time-averaged observables.

The ensemble properties and time-averaged observables of a memory-induced diffusive-superdiffusive transition are studied. The model consists in a random walker whose transitions in a given direction depend on a weighted linear combination of the number of both right and left previous transitions. The diffusion process is nonstationary, and its probability develops the phenomenon of aging. Depending on the characteristic memory parameters, the ensemble behavior may be normal, superdiffusive, or ballistic. In contrast, the time-averaged mean squared displacement is equal to that of a normal undriven random walk, which renders the process nonergodic. In addition, and similarly to Lévy walks [Godec and Metzler, Phys. Rev. Lett. 110, 020603 (2013)PRLTAO0031-900710.1103/PhysRevLett.110.020603], for trajectories of finite duration the time-averaged displacement apparently become random with properties that depend on the measurement time and also on the memory properties. These features are related to the nonstationary power-law decay of the transition probabilities to their stationary values. Time-averaged response to a bias is also calculated. In contrast with Lévy walks [Froemberg and Barkai, Phys. Rev. E 87, 030104(R) (2013)PLEEE81539-375510.1103/PhysRevE.87.030104], the response always vanishes asymptotically.

Evaluation of Transfer Wicking Behavior of Fibrous Material Ensembles Used by Wildland Firefighters

Moisture is widely recognized as one of the most important factors that influencing thermal comfort and thermal protective performance of firefighters. In this study, it was aimed to investigate the effect of liquid moisture on the transfer wicking behavior from the wet underwear fabric to the dry outerwear layer within two-layer fabric assemblies, which is typically used by wildland firefighters. The obtained results indicated that the transfer wicking behavior between the entire two-layer clothing systems selected is not very obvious. Results indicated that the transfer wicking ratio was low 5 percent of water content initially held in wet fabric. The greater amount of liquid water initially held in two-layer fabric assemblies, the greater the amount of water transferred. The effect of moisture level on air permeability of bi-layer fabric constructions associated with thermo-physiological comfort properties was also investigated. Results show that the air permeability of multilayer fabrics decreased with an increase of moisture content. Compared to having no water, the air permeability reduced to 50 percent when the water content reached up to 70%. The perception gained from this work could serve as technical basis for further development of high-performance firefighter protective clothing.

Random Subclasses Ensembles by Using 1-Nearest Neighbor Framework

A classifier ensemble is a combination of diverse and accurate classifiers. Generally, a classifier ensemble performs better than any single classifier in the ensemble. Naive Bayes classifiers are simple but popular classifiers for many applications. As it is difficult to create diverse naive Bayes classifiers, naive Bayes ensembles are not very successful. In this paper, we propose Random Subclasses (RS) ensembles for Naive Bayes classifiers. In the proposed method, new subclasses for each class are created by using 1-Nearest Neighbor (1-NN) framework that uses randomly selected points from the training data. A classifier considers each subclass as a class of its own. As the method to create subclasses is random, diverse datasets are generated. Each classifier in an ensemble learns on one dataset from the pool of diverse datasets. Diverse training datasets ensure diverse classifiers in the ensemble. New subclasses create easy to learn decision boundaries that in turn create accurate naive Bayes classifiers. We developed two variants of RS, in the first variant RS(2), two subclasses per class were created whereas in the second variant RS(4), four subclasses per class were created. We studied the performance of these methods against other popular ensemble methods by using naive Bayes as the base classifier. RS(4) outperformed other popular ensemble methods. A detailed study was carried out to understand the behavior of RS ensembles.

Manifestation of particle morphology on the mechanical behaviour of granular ensembles

This paper presents the effect of particle morphology (grain shape) on the mechanical response of granular materials. Two model systems with extreme differences in morphology were selected (spherical glass ballotini and angular sand) for this experimental programme. A series of hollow cylinder torsion tests were conducted in this programme under monotonic drained conditions on specimens reconstituted to the same relative density. Tests were conducted under different intermediate principal stress ratio (b) on both the model materials. The glass ballotini shows increased dilation at the outset of the test, however, at large strains, the particle rearrangement in the sand and the increased interlocking leads to higher strength at the critical state. The effect of individual particle morphology is manifested in both the increased friction angle and a larger sized failure locus in stress space with increase in angularity. The stresses developed in these two model materials are also accompanied by intriguing volume change behaviour. The glass ballotini despite a lower strength presents a predominantly dilative response immaterial of the ` b' value, while the angular sand shows increased strength at large strains, while showing a contractive response. These results allow incorporation of particle morphology effects at the ensemble level in plasticity based constitutive models.

Scaling laws of passive-scalar diffusion in the interstellar medium

Passive scalar mixing (metals, molecules, etc.) in the turbulent interstellar medium (ISM) is critical for abundance patterns of stars and clusters, galaxy and star formation, and cooling from the circumgalactic medium. However, the fundamental scaling laws remain poorly understood in the highly supersonic, magnetized, shearing regime relevant for the ISM. We therefore study the full scaling laws governing passive-scalar transport in idealized simulations of supersonic turbulence. Using simple phenomenological arguments for the variation of diffusivity with scale based on Richardson diffusion, we propose a simple fractional diffusion equation to describe the turbulent advection of an initial passive scalar distribution. These predictions agree well with the measurements from simulations, and vary with turbulent Mach number in the expected manner, remaining valid even in the presence of a large-scale shear flow (e.g. rotation in a galactic disk). The evolution of the scalar distribution is not the same as obtained using simple, constant "effective diffusivity" as in Smagorinsky models, because the scale-dependence of turbulent transport means an initially Gaussian distribution quickly develops highly non-Gaussian tails. We also emphasize that these are mean scalings that only apply to ensemble behaviors (assuming many different, random scalar injection sites): individual Lagrangian "patches" remain coherent (poorly-mixed) and simply advect for a large number of turbulent flow-crossing times.

Modeling Cargo Transport by Pairs of Kinesin-1 and -3 Motors

Intracellular cargo transport frequently involves multiple motor types, either having opposite directionality or having the same directionality but different speeds. Although significant progress has been made in characterizing kinesin motors at the single-molecule level, predicting their ensemble behavior requires tight coupling between experiments and modeling to uncover the underlying motor behavior. To understand how diverse kinesins attached to the same cargo coordinate their movement, we analyzed the transport properties of complexes of kinesin-1 and kinesin-3 motors attached to protein scaffolds in vitro (Norris et al.

Cytoplasmic RNA-Protein Particles Exhibit Non-Gaussian Subdiffusive Behavior

The cellular cytoplasm is a complex, heterogeneous environment (both spatially and temporally) that exhibits viscoelastic behavior. To further develop our quantitative insight into cellular transport, we analyze data sets of mRNA molecules fluorescently labeled with MS2-GFP tracked in real time in live Escherichia coli and Saccharomyces cerevisiae cells. As shown previously, these RNA-protein particles exhibit subdiffusive behavior that is viscoelastic in its origin. Examining the ensemble of particle displacements reveals a Laplace distribution at all observed timescales rather than the Gaussian distribution predicted by the central limit theorem. This ensemble non-Gaussian behavior is caused by a combination of an exponential distribution in the time-averaged diffusivities and non-Gaussian behavior of individual trajectories. We show that the non-Gaussian behavior is a consequence of significant heterogeneity between trajectories and dynamic heterogeneity along single trajectories. Informed by theory and simulation, our work provides an in-depth analysis of the complex diffusive behavior of RNA-protein particles in live cells.

Progressive freezing of interacting spins in isolated finite magnetic ensembles

Self-organization of magnetic nanoparticles into secondary nanostructures provides an innovative way for designing functional nanomaterials with novel properties, different from the constituent primary nanoparticles as well as their bulk counterparts. Collective magnetic properties of such complex closed packing of magnetic nanoparticles makes them more appealing than the individual magnetic nanoparticles in many technological applications. This work reports the collective magnetic behaviour of magnetic ensembles comprising of single domain Fe3O4 nanoparticles. The present work reveals that the ensemble formation is based on the re-orientation and attachment of the nanoparticles in an iso-oriented fashion at the mesoscale regime. Comprehensive dc magnetic measurements show the prevalence of strong interparticle interactions in the ensembles. Due to the close range organization of primary Fe3O4 nanoparticles in the ensemble, the spins of the individual nanoparticles interact through dipolar interactions as realized from remnant magnetization measurements. Signature of super spin glass like behaviour in the ensembles is observed in the memory studies carried out in field cooled conditions. Progressive freezing of spins in the ensembles is corroborated from the Vogel–Fulcher fit of the susceptibility data. Dynamic scaling of relaxation reasserted slow spin dynamics substantiating cluster spin glass like behaviour in the ensembles.

Spatiotemporal order and emergent edge currents in active spinner materials

Collections of interacting, self-propelled particles have been extensively studied as minimal models of many living and synthetic systems from bird flocks to active colloids. However, the influence of active rotations in the absence of self-propulsion (i.e., spinning without walking) remains less explored. Here, we numerically and theoretically investigate the behavior of ensembles of self-spinning dimers. We find that geometric frustration of dimer rotation by interactions yields spatiotemporal order and active melting with no equilibrium counterparts. At low density, the spinning dimers self-assemble into a triangular lattice with their orientations phase-locked into spatially periodic phases. The phase-locked patterns form dynamical analogs of the ground states of various spin models, transitioning from the three-state Potts antiferromagnet at low densities to the striped herringbone phase of planar quadrupoles at higher densities. As the density is raised further, the competition between active rotations and interactions leads to melting of the active spinner crystal. Emergent edge currents, whose direction is set by the chirality of the active spinning, arise as a nonequilibrium signature of the transition to the active spinner liquid and vanish when the system eventually undergoes kinetic arrest at very high densities. Our findings may be realized in systems ranging from liquid crystal and colloidal experiments to tabletop realizations using macroscopic chiral grains.

Control of Asymmetric Scattering Behavior of Plasmonic Nanoparticle Ensembles

A transparent or translucent film shows the same color for both front and back sides in general. However, different colors can be shown by the aid of strong plasmonic scattering of metal nanoparticles. Here we propose a design strategy of films exhibiting asymmetric scattering behavior. Typically two different types of nanoparticles are embedded in a SiO2 thin film that is coated on a TiO2 thin film. One of the particle types is selectively excited for the front incidence, and the other type for the back incidence, by tuning the electric field distribution inside the SiO2 film. We experimentally prepared two different samples that scatter light of different colors from the front and the back sides by using Au nanorods and Ag nanospheres.

Ensemble X-ray variability of active galactic nuclei

Most investigations of the X-ray variability of active galactic nuclei (AGN) have been concentrated on the detailed analyses of individual, nearby sources. A relatively small number of studies have treated the ensemble behaviour of the more general AGN population in wider regions of the luminosity-redshift plane. We want to determine the ensemble variability properties of a rich AGN sample, called Multi-Epoch XMM Serendipitous AGN Sample (MEXSAS), extracted from the fifth release of the XMM-Newton Serendipitous Source Catalogue (XMMSSC-DR5), with redshift between 0.1 and 5, and X-ray luminosities in the 0.5-4.5 keV band between 10^42 and 10^47 erg/s. We urge caution on the use of the normalised excess variance (NXS), noting that it may lead to underestimate variability if used improperly. We use the structure function (SF), updating our previous analysis for a smaller sample. We propose a correction to the NXS variability estimator, accounting for the light curve duration in the rest frame on the basis of the knowledge of the variability behaviour gained by SF studies. We find an ensemble increase of the X-ray variability with the rest-frame time lag tau, given by tau^0.12. We confirm an inverse dependence on the X-ray luminosity, approximately as L_X^-0.19. We analyse the SF in different X-ray bands, finding a dependence of the variability on the frequency as nu^-0.15, corresponding to a softer when brighter trend. In turn, this dependence allows us to parametrically correct the variability estimated in observer-frame bands to that in the rest frame, resulting in a moderate shift upwards (V-correction). Ensemble X-ray variability of AGNs is best described by the structure function. An improper use of the normalised excess variance may lead to an underestimate of the intrinsic variability, so that appropriate corrections to the data or the models must be applied to prevent these effects.

Tuning Viral Capsid Nanoparticle Stability with Symmetrical Morphogenesis.

Virus-like particles (VLPs) provide engineering platforms for the design and implementation of protein-based nanostructures. These capsids are comprised of protein subunits whose precise arrangement and mutual interactions determine their stability, responsiveness to destabilizing environments, and ability to undergo morphological transitions. The precise interplay between subunit contacts and the overall stability of the bulk capsid population remains poorly resolved. Approaching this relationship requires a combination of techniques capable of accessing nanoscale properties, such as the mechanics of individual capsids, and bulk biochemical procedures capable of interrogating the stability of the VLP ensemble. To establish such connection, a VLP system is required where the subunit interactions can be manipulated in a controlled fashion. The P22 VLP is a promising platform for the design of nanomaterials and understanding how nanomanipulation of the particle affects bulk behavior. By contrasting single-particle atomic force microscopy and bulk chemical perturbations, we have related symmetry-specific anisotropic mechanical properties to the bulk ensemble behavior of the VLPs. Our results show that the expulsion of pentons at the vertices of the VLP induces a concomitant chemical and mechanical destabilization of the capsid and implicates the capsid edges as the points of mechanical fracture. Subsequent binding of a decoration protein at these critical edge regions restores both chemical and mechanical stability. The agreement between our single molecule and bulk techniques suggests that the same structural determinants govern both destabilizing and restorative mechanisms, unveiling a phenomenological coupling between the chemical and mechanical behavior of self-assembled cages and laying a framework for the analysis and manipulation of other VLPs and symmetric self-assembled structures.

First-order phase transitions in the real microcanonical ensemble

We present a simulation and data analysis technique to investigate first-order phase transitions and the associated transition barriers. The simulation technique is based on the real microcanonical ensemble where the sum of kinetic and potential energy is kept constant. The method is tested for the droplet condensation-evaporation transition in a Lennard-Jones system with up to 2048 particles at fixed density, using simple Metropolis-like sampling combined with a replica-exchange scheme. Our investigation of the microcanonical ensemble properties reveals that the associated transition barrier is significantly lower than in the canonical counterpart. Along the line of investigating the microcanonical ensemble behavior, we develop a framework for general ensemble evaluations. This framework is based on a clear separation between system-related and ensemble-related properties, which can be exploited to specifically tailor artificial ensembles suitable for first-order phase transitions.

Single-Channel Recording of Ligand-Gated Ion Channels.

Single-channel recordings reveal the microscopic properties of individual ligand-gated ion channels. Such recordings contain much more information than measurements of ensemble behavior and can yield structural and functional information about the receptors that participate in fast synaptic transmission in the brain. With a little care, a standard patch-clamp electrophysiology setup can be adapted for single-channel recording in a matter of hours. Thenceforth, it is a realistic aim to record single-molecule activity with microsecond resolution from arbitrary cell types, including cell lines and neurons.

Increased Titin Compliance Reduced Length-Dependent Contraction and Slowed Cross-Bridge Kinetics in Skinned Myocardial Strips from Rbm (20ΔRRM) Mice.

Titin is a giant protein spanning from the Z-disk to the M-band of the cardiac sarcomere. In the I-band titin acts as a molecular spring, contributing to passive mechanical characteristics of the myocardium throughout a heartbeat. RNA Binding Motif Protein 20 (RBM20) is required for normal titin splicing, and its absence or altered function leads to greater expression of a very large, more compliant N2BA titin isoform in Rbm20 homozygous mice (Rbm20ΔRRM) compared to wild-type mice (WT) that almost exclusively express the stiffer N2B titin isoform. Prior studies using Rbm20ΔRRM animals have shown that increased titin compliance compromises muscle ultrastructure and attenuates the Frank-Starling relationship. Although previous computational simulations of muscle contraction suggested that increasing compliance of the sarcomere slows the rate of tension development and prolongs cross-bridge attachment, none of the reported effects of Rbm20ΔRRM on myocardial function have been attributed to changes in cross-bridge cycling kinetics. To test the relationship between increased sarcomere compliance and cross-bridge kinetics, we used stochastic length-perturbation analysis in Ca2+-activated, skinned papillary muscle strips from Rbm20ΔRRM and WT mice. We found increasing titin compliance depressed maximal tension, decreased Ca2+-sensitivity of the tension-pCa relationship, and slowed myosin detachment rate in myocardium from Rbm20ΔRRM vs. WT mice. As sarcomere length increased from 1.9 to 2.2 μm, length-dependent activation of contraction was eliminated in the Rbm20ΔRRM myocardium, even though myosin MgADP release rate decreased ~20% to prolong strong cross-bridge binding at longer sarcomere length. These data suggest that increasing N2BA expression may alter cardiac performance in a length-dependent manner, showing greater deficits in tension production and slower cross-bridge kinetics at longer sarcomere length. This study also supports the idea that passive mechanical characteristics of the myocardium influence ensemble cross-bridge behavior and maintenance of tension generation throughout the sarcomere.

Synthetic Micro/Nanomotors and Pumps: Fabrication and Applications

Synthetic active systems capable of autonomous motion or driving fluid flow are of great current interest owing to their potential applications in nanomachinery, cargo capture and delivery, reversible assemblies, and chemical/biochemical sensing. Designing self-powered micro/nanomotors and understanding their propulsion mechanisms and ensemble behavior are now areas of great interest in low-Reynolds-number mechanics. In this article, we classify prototypes of existing small-scale motors on the basis of the materials used in synthesis and fabrication, with the aim of understanding the importance of material selection in designing functional motors for futuristic applications.

Non-equilibrium dynamics of magnetically anisotropic particles under oscillating fields.

In this article, we demonstrate how magnetic anisotropy of colloidal particles can give rise to unusual dynamics and controllable rearrangements under time-dependent fields. As an example, we study spherical particles with a radially off-centered net magnetic moment in an oscillating field. Based on complementary data from a numerical simulation of spheres with shifted dipole and experimental observations from particles with hemispherical ferromagnetic coating, it is explained on a two particle basis how this magnetic anisotropy causes nontrivial rotational motion and magnetic reorientation. We further present the behavior of larger ensembles of coated particles. It illustrates the potential for controlled reconfiguration based on the presented two-particle dynamics.