Experimental Investigations of Elastic Tail Propulsion at Low Reynolds Number

A simple way to generate propulsion at low Reynolds number is to periodically oscillate a passive flexible filament. Here we present a macroscopic experimental investigation of such a propulsive mechanism. A robotic swimmer is constructed and both tail shape and propulsive force are measured. Filament characteristics and the actuation are varied and resulting data are quantitatively compared with existing linear and nonlinear theories

A two-dimensional model of low-Reynolds number swimming beneath a free surface

Biological organisms swimming at low Reynolds number are often influenced by the presence of rigid boundaries and soft interfaces. In this paper we present an analysis of locomotion near a free surface with surface tension. Using a simplified two-dimensional singularity model, and combining a complex variable approach with conformal mapping techniques, we demonstrate that the deformation of a free surface can be harnessed to produce steady locomotion parallel to the interface. The crucial physical ingredient lies in the nonlinear hydrodynamic coupling between the disturbance flow created by the swimmer and the free boundary problem at the fluid surface

Soft swimming: Exploiting deformable interfaces for low-Reynolds number locomotion

Reciprocal movement cannot be used for locomotion at low-Reynolds number in an infinite fluid or near a rigid surface. Here we show that this limitation is relaxed for a body performing reciprocal motions near a deformable interface. Using physical arguments and scaling relationships, we show that the nonlinearities arising from reciprocal flow-induced interfacial deformation rectify the periodic motion of the swimmer, leading to locomotion. Such a strategy can be used to move toward, away from, and parallel to any deformable interface as long as the length scales involved are smaller than intrinsic scales, which we identify. A macro-scale experiment of flapping motion near a free surface illustrates this new result

Nonpolar resistance switching of metal/binary-transition-metal oxides/metal sandwiches: homogeneous/inhomogeneous transition of current distribution

Exotic features of a metal/oxide/metal (MOM) sandwich, which will be the basis for a drastically innovative nonvolatile memory device, is brought to light from a physical point of view. Here the insulator is one of the ubiquitous and classic binary-transition-metal oxides (TMO), such as Fe2O3, NiO, and CoO. The sandwich exhibits a resistance that reversibly switches between two states: one is a highly resistive off-state and the other is a conductive on-state. Several distinct features were universally observed in these binary TMO sandwiches: namely, nonpolar switching, non-volatile threshold switching, and current--voltage duality. From the systematic sample-size dependence of the resistance in on- and off-states, we conclude that the resistance switching is due to the homogeneous/inhomogeneous transition of the current distribution at the interface.Comment: 7 pages, 5 figures, REVTeX4, submitted to Phys. Rev. B (Feb. 23, 2007). If you can't download a PDF file of this manscript, an alternative one can be found on the author's website: http://staff.aist.go.jp/i.inoue

Data-driven control of COVID-19 in buildings: a reinforcement-learning approach

In addition to its public health crisis, COVID-19 pandemic has led to the shutdown and closure of workplaces with an estimated total cost of more than $16 trillion. Given the long hours an average person spends in buildings and indoor environments, this research article proposes data-driven control strategies to design optimal indoor airflow to minimize the exposure of occupants to viral pathogens in built environments. A general control framework is put forward for designing an optimal velocity field and proximal policy optimization, a reinforcement learning algorithm is employed to solve the control problem in a data-driven fashion. The same framework is used for optimal placement of disinfectants to neutralize the viral pathogens as an alternative to the airflow design when the latter is practically infeasible or hard to implement. We show, via simulation experiments, that the control agent learns the optimal policy in both scenarios within a reasonable time. The proposed data-driven control framework in this study will have significant societal and economic benefits by setting the foundation for an improved methodology in designing case-specific infection control guidelines that can be realized by affordable ventilation devices and disinfectants

Inhibition of Casein Kinase 2 Modulates XBP1-GRP78 Arm of Unfolded Protein Responses in Cultured Glial Cells

Stress signals cause abnormal proteins to accumulate in the endoplasmic reticulum (ER). Such stress is known as ER stress, which has been suggested to be involved in neurodegenerative diseases, diabetes, obesity and cancer. ER stress activates the unfolded protein response (UPR) to reduce levels of abnormal proteins by inducing the production of chaperon proteins such as GRP78, and to attenuate translation through the phosphorylation of eIF2α. However, excessive stress leads to apoptosis by generating transcription factors such as CHOP. Casein kinase 2 (CK2) is a serine/threonine kinase involved in regulating neoplasia, cell survival and viral infections. In the present study, we investigated a possible linkage between CK2 and ER stress using mouse primary cultured glial cells. 4,5,6,7-tetrabromobenzotriazole (TBB), a CK2-specific inhibitor, attenuated ER stress-induced XBP-1 splicing and subsequent induction of GRP78 expression, but was ineffective against ER stress-induced eIF2α phosphorylation and CHOP expression. Similar results were obtained when endogenous CK2 expression was knocked-down by siRNA. Immunohistochemical analysis suggested that CK2 was present at the ER. These results indicate CK2 to be linked with UPR and to resist ER stress by activating the XBP-1-GRP78 arm of UPR

Fingerprinting Soft Materials: A Framework for Characterizing Nonlinear Viscoelasticity

We introduce a comprehensive scheme to physically quantify both viscous and elastic rheological nonlinearities simultaneously, using an imposed large amplitude oscillatory shear (LAOS) strain. The new framework naturally lends a physical interpretation to commonly reported Fourier coefficients of the nonlinear stress response. Additionally, we address the ambiguities inherent in the standard definitions of viscoelastic moduli when extended into the nonlinear regime, and define new measures which reveal behavior that is obscured by conventional techniques.Comment: 10 pages, 3 figures, full-page double-space preprint forma