Browsing by Author "Sharma, A."
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- Some of the metrics are blocked by yourconsent settingsClinical performance of WaveletTM morphology discrimination algorithm in a worldwide single-chamber ICD population(Lippincott Williams & Wilkins, 2004)
;Klein, G. J. ;Manolis, A. S. ;Viskin, S. ;Tang, A. ;Inbar, S. ;Unterberg-Buchwald, Christine ;Sharma, A. ;Rooney, E. A. ;Gillberg, Jeffrey M. ;Schaaf, K. ;Becker, D.Benditt, D. G. - Some of the metrics are blocked by yourconsent settingsElastic response of filamentous networks with compliant crosslinks(2013)
;Sharma, A. ;Sheinman, M. ;Heidemann, K. M.MacKintosh, Frederick C.Experiments have shown that elasticity of disordered filamentous networks with compliant crosslinks is very different from networks with rigid crosslinks. Here, we model and analyze filamentous networks as a collection of randomly oriented rigid filaments connected to each other by flexible crosslinks that are modeled as wormlike chains. For relatively large extensions we allow for enthalpic stretching of crosslink backbones. We show that for sufficiently high crosslink density, the network linear elastic response is affine on the scale of the filaments' length. The nonlinear regime can become highly nonaffine and is characterized by a divergence of the elastic modulus at finite strain. In contrast to the prior predictions, we do not find an asymptotic regime in which the differential elastic modulus scales linearly with the stress, although an approximate linear dependence can be seen in a transition from entropic to enthalpic regimes. We discuss our results in light of recent experiments. - Some of the metrics are blocked by yourconsent settingsInherently unstable networks collapse to a critical point(Amer Physical Soc, 2015)
;Sheinman, M. ;Sharma, A. ;Alvarado, J. ;Koenderink, G. H.MacKintosh, Frederick C.Nonequilibrium systems that are driven or drive themselves towards a critical point have been studied for almost three decades. Here we present a minimalist example of such a system, motivated by experiments on collapsing active elastic networks. Our model of an unstable elastic network exhibits a collapse towards a critical point from any macroscopically connected initial configuration. Taking into account steric interactions within the network, the model qualitatively and quantitatively reproduces results of the experiments on collapsing active gels. - Some of the metrics are blocked by yourconsent settingsNon-equilibrium steady state transitions in a model actin cortex(Wiley-blackwell, 2016)
;Tan, T. ;Garb, M. Malik ;Abu-Shah, E. ;Li, J. ;Sharma, A. ;McKintosh, F. ;Keren, K. ;Fakhri, NiktaSchmidt, C. - Some of the metrics are blocked by yourconsent settingsSheinman, Sharma, and MacKintosh Reply:(Amer Physical Soc, 2016)
;Sheinman, M. ;Sharma, A.MacKintosh, Frederick C. - Some of the metrics are blocked by yourconsent settingsStrain-controlled criticality governs the nonlinear mechanics of fibre networks(Nature Publishing Group, 2016)
;Sharma, A. ;Licup, A. J. ;Jansen, K. A. ;Rens, R. ;Sheinman, M. ;Koenderink, G. H.MacKintosh, F. C.Disordered fibrous networks are ubiquitous in nature as major structural components of living cells and tissues. The mechanical stability of networks generally depends on the degree of connectivity: only when the average number of connections between nodes exceeds the isostatic threshold are networks stable(1). On increasing the connectivity through this point, such networks undergo a mechanical phase transition from a floppy to a rigid phase. However, even sub-isostatic networks become rigid when subjected to sufficiently large deformations. To study this strain-controlled transition, we perform a combination of computational modelling of fibre networks and experiments on networks of type I collagen fibres, which are crucial for the integrity of biological tissues. We show theoretically that the development of rigidity is characterized by a strain-controlled continuous phase transition with signatures of criticality. Our experiments demonstrate mechanical properties consistent with our model, including the predicted critical exponents. We show that the nonlinear mechanics of collagen networks can be quantitatively captured by the predictions of scaling theory for the strain-controlled critical behaviour over a wide range of network concentrations and strains up to failure of the material. - Some of the metrics are blocked by yourconsent settings