arXiv subjects

Ryota Sakamoto

Publications and source records attributed to Ryota Sakamoto.

3 recordsLinked to original sources

arXiv2025

Myosin-driven advection and actin reorganization control the geometry of confined actomyosin gel

Harnessing nanoscale motor proteins to actively control material shape is a promising strategy in nanotechnology and material science. One notable system is the actomyosin network, composed of actin filaments and myosin motor proteins, providing a natural platform for constructing contractile, shape-adaptive materials. While the role of actomyosin in shaping cells has been extensively studied, the reverse question - how boundary shape affects the actomyosin system - remains poorly understood. Here, we present a microfabricated system that reveals how geometrical confinement directs the organization of actomyosin networks within microwells. By combining experimental and numerical analysis, we show that the asymmetric shape of the microwells is transferred to contracted actomyosin gels via myosin-driven actin flow. Furthermore, tuning myosin contractility and actin polymerization rate allows control over the size and shape of actomyosin gels. Our findings provide a bottom-up framework for integrating molecular motors and cytoskeletons into confined architectures to create responsive biomaterials.

cond-mat.soft↗

arXiv2021

Forecasting Health and Wellbeing for Shift Workers Using Job-role Based Deep Neural Network

Shift workers who are essential contributors to our society, face high risks of poor health and wellbeing. To help with their problems, we collected and analyzed physiological and behavioral wearable sensor data from shift working nurses and doctors, as well as their behavioral questionnaire data and their self-reported daily health and wellbeing labels, including alertness, happiness, energy, health, and stress. We found the similarities and differences between the responses of nurses and doctors. According to the differences in self-reported health and wellbeing labels between nurses and doctors, and the correlations among their labels, we proposed a job-role based multitask and multilabel deep learning model, where we modeled physiological and behavioral data for nurses and doctors simultaneously to predict participants' next day's multidimensional self-reported health and wellbeing status. Our model showed significantly better performances than baseline models and previous state-of-the-art models in the evaluations of binary/3-class classification and regression prediction tasks. We also found features related to heart rate, sleep, and work shift contributed to shift workers' health and wellbeing.

cs.LG↗

arXiv2018

Three-dimensional graphdiyne as a topological nodal-line semimetal

We study the electronic band structure of three-dimensional ABC-stacked (rhombohedral) graphdiyne, which is a new planar carbon allotrope recently fabricated. Using the first-principles calculation, we show that the system is a nodal-line semimetal, in which the conduction band and valence band cross at a closed ring in the momentum space. We derive the minimum tight-binding model and the low-energy effective Hamiltonian in a $4\times 4$ matrix form. The nodal line is protected by a non-trivial winding number, and it ensures the existence of the topological surface state in a finite-thickness slab. The Fermi surface of the doped system exhibits a peculiar, self-intersecting hourglass structure, which is quite different from the torus or pipe shape in the previously proposed nodal semimetals. Despite its simple configuration, three-dimensional graphdiyne offers unique electronic properties distinct from any other carbon allotropes.

cond-mat.mes-hall↗