arXiv subjects

Saptarshi Dasgupta

Publications and source records attributed to Saptarshi Dasgupta.

3 recordsLinked to original sources

arXiv2025

Emergence of Tension Chains and Active Force Patterning

Viewed under a fluorescence microscope, the actomyosin cytoskeleton presents vivid streaks of lines together with persistent oscillatory waves. Using an active hydrodynamic approach, we show how a uniform distribution of single or mixture of contractile stresslets spontaneously segregate, followed by the formation of singular structures of high contractility (tension chains) in finite time. Simultaneously, the collection of stresslets exhibit travelling waves and swapping as a consequence of nonreciprocity. In the finite geometry of the cell, the collection of active tension chains can form an active web held together by specific anchoring at the cell boundary. On the other hand, preferential wetting at the cell boundary can reinforce active segregation in a mixture of stresslets leading to stratification.

cond-mat.soft↗

arXiv2025

Segregation, Finite Time Elastic Singularities and Coarsening in Renewable Active Matter

Material renewability in active living systems, such as in cells and tissues, can drive the large-scale patterning of forces, with distinctive phenotypic consequences. This is especially significant in the cell cytoskeleton, where multiple species of myosin bound to actin, apply differential contractile stresses and undergo differential turnover, giving rise to patterned force channeling. Here we study the dynamical patterning of stresses that emerge in a hydrodynamic description of a renewable active actomyosin elastomer comprising two myosin species. Our analytical framework also holds for an actomyosin elastomer with a single myosin species. We find that a uniform active contractile elastomer spontaneously segregates into spinodal stress patterns, followed by a finite-time collapse into tension carrying singular structures that display self-similar scaling and caustics. Our numerical analysis carried out in 1D, shows that these singular structures move and merge, and gradually result in a slow coarsening dynamics. We discuss the implications of our findings to the emergence of stress fibers and the spatial patterning of actomyosin. Our study suggests, that with state-dependent turnover of crosslinkers and myosin, the in vivo cytoskeleton can navigate through the space of material parameters to achieve a variety of functional phenotypes.

cond-mat.soft↗

arXiv2024

Uncertainty-aware Active Learning of NeRF-based Object Models for Robot Manipulators using Visual and Re-orientation Actions

Manipulating unseen objects is challenging without a 3D representation, as objects generally have occluded surfaces. This requires physical interaction with objects to build their internal representations. This paper presents an approach that enables a robot to rapidly learn the complete 3D model of a given object for manipulation in unfamiliar orientations. We use an ensemble of partially constructed NeRF models to quantify model uncertainty to determine the next action (a visual or re-orientation action) by optimizing informativeness and feasibility. Further, our approach determines when and how to grasp and re-orient an object given its partial NeRF model and re-estimates the object pose to rectify misalignments introduced during the interaction. Experiments with a simulated Franka Emika Robot Manipulator operating in a tabletop environment with benchmark objects demonstrate an improvement of (i) 14% in visual reconstruction quality (PSNR), (ii) 20% in the geometric/depth reconstruction of the object surface (F-score) and (iii) 71% in the task success rate of manipulating objects a-priori unseen orientations/stable configurations in the scene; over current methods. The project page can be found here: https://actnerf.github.io.

cs.RO↗