An Active and Soft Hydrogel Actuator to Stimulate Live Cell Clusters by Self-folding

The hydrogels are widely used in various applications, and their successful uses depend on controlling the mechanical properties. In this study, we present an advanced strategy to develop hydrogel actuator designed to stimulate live cell clusters by self-folding. The hydrogel actuator consisting of two layers with different expansion ratios were fabricated to have various curvatures in self-folding. The expansion ratio of the hydrogel tuned with the molecular weight and concentration of gel-forming polymers, and temperature-sensitive molecules in a controlled manner. As a result, the hydrogel actuator could stimulate live cell clusters by compression and tension repeatedly, in response to temperature. The cell clusters were compressed in the 0.7-fold decreases of the radius of curvature with 1.0 mm in room temperature, as compared to that of 1.4 mm in 37 degrees C. Interestingly, the vascular endothelial growth factor (VEGF) and insulin-like growth factor-binding protein-2 (IGFBP-2) in MCF-7 tumor cells exposed by mechanical stimulation was expressed more than in those without stimulation. Overall, this new strategy to prepare the active and soft hydrogel actuator would be actively used in tissue engineering, drug delivery, and micro-scale actuators

Typhoon‐induced, highly nonlinear internal solitary waves off the east coast of Korea

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94585/1/grl22467.pd

AFFINE KILLING REEB VECTOR FIELD FOR A REAL HYPERSURFACE IN THE COMPLEX QUADRIC

In this paper, first we introduce a general notion of affine Killing vector fields on the complex quadric Q^m, which is weaker than usual Killing vector field. Next, we give a complete classification of Hopf real hypersurfaces M with affine Killing Reeb vector field in the complex quadric Q^m, m ≥ 3

Temperature dependence of Mott transition in VO_2 and programmable critical temperature sensor

The temperature dependence of the Mott metal-insulator transition (MIT) is studied with a VO_2-based two-terminal device. When a constant voltage is applied to the device, an abrupt current jump is observed with temperature. With increasing applied voltages, the transition temperature of the MIT current jump decreases. We find a monoclinic and electronically correlated metal (MCM) phase between the abrupt current jump and the structural phase transition (SPT). After the transition from insulator to metal, a linear increase in current (or conductivity) is shown with temperature until the current becomes a constant maximum value above T_{SPT}=68^oC. The SPT is confirmed by micro-Raman spectroscopy measurements. Optical microscopy analysis reveals the absence of the local current path in micro scale in the VO_2 device. The current uniformly flows throughout the surface of the VO_2 film when the MIT occurs. This device can be used as a programmable critical temperature sensor.Comment: 4 pages, 3 figure

A Design Method of Distributed Algorithms via Discrete-time Blended Dynamics Theorem

We develop a discrete-time version of the blended dynamics theorem for the use of designing distributed computation algorithms. The blended dynamics theorem enables to predict the behavior of heterogeneous multi-agent systems. Therefore, once we get a blended dynamics for a particular computational task, design idea of node dynamics for individual heterogeneous agents can easily occur. In the continuous-time case, prediction by blended dynamics was enabled by high coupling gain among neighboring agents. In the discrete-time case, we propose an equivalent action, which we call multi-step coupling in this paper. Compared to the continuous-time case, the blended dynamics can have more variety depending on the coupling matrix. This benefit is demonstrated with three applications; distributed estimation of network size, distributed computation of the PageRank, and distributed computation of the degree sequence of a graph, which correspond to the coupling by doubly-stochastic, column-stochastic, and row-stochastic matrices, respectively