A Variational Pan-Sharpening With Local Gradient Constraints

2019 ◽  
Author(s):  
Xueyang Fu ◽  
Zihuang Lin ◽  
Yue Huang ◽  
Xinghao Ding
Keyword(s):  
Gradient Constraints ◽  
Local Gradient

Electromechanical fields in a hollow piezoelectric cylinder under non-uniform load: flexoelectric effect

2021 ◽  
pp. 108128652110207
Author(s):  
Olha Hrytsyna
Keyword(s):  
Analytical Solutions ◽  
Point Group ◽  
The Body ◽  
Small Scale ◽  
Gradient Theory ◽  
Local Mass ◽  
Wide Range ◽  
Mass Displacement ◽  
Local Mass Displacement ◽  
Local Gradient

The relations of a local gradient non-ferromagnetic electroelastic continuum are used to solve the problem of an axisymmetrical loaded hollow cylinder. Analytical solutions are obtained for tetragonal piezoelectric materials of point group 4 mm for two cases of external loads applied to the body surfaces. Namely, the hollow pressurized cylinder and a cylinder subjected to an electrical voltage V across its thickness are considered. The derived solutions demonstrate that the non-uniform electric load causes a mechanical deformation of piezoelectric body, and vice versa, the inhomogeneous radial pressure of the cylinder induces its polarization. Such a result is obtained due to coupling between the electromechanical fields and a local mass displacement being considered. In the local gradient theory, the local mass displacement is associated with the changes to a material’s microstructure. The classical theory does not consider the effect of material microstructure on the behavior of solid bodies and is incapable of explaining the mentioned phenomena. It is also shown that the local gradient theory describes the size-dependent properties of piezoelectric nanocylinders. Analytical solutions to the formulated boundary-value problems can be used in conjunction with experimental data to estimate some higher-order material constants of the local gradient piezoelectricity. The obtained results may be useful for a wide range of appliances that utilize small-scale piezoelectric elements as constituting blocks.

scholarly journals A counter gradient of Activin A and follistatin instructs the timing of hair cell differentiation in the murine cochlea

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Meenakshi Prajapati-DiNubila ◽  
Ana Benito-Gonzalez ◽  
Erin Jennifer Golden ◽  
Shuran Zhang ◽  
Angelika Doetzlhofer
Keyword(s):  
Cell Differentiation ◽  
Hair Cell ◽  
Hair Cells ◽  
Activin A ◽  
Sensory Epithelium ◽  
Outer Hair Cells ◽  
Longitudinal Gradient ◽  
Hair Cell Differentiation ◽  
Local Gradient ◽  
Molecular Signals

The mammalian auditory sensory epithelium has one of the most stereotyped cellular patterns known in vertebrates. Mechano-sensory hair cells are arranged in precise rows, with one row of inner and three rows of outer hair cells spanning the length of the spiral-shaped sensory epithelium. Aiding such precise cellular patterning, differentiation of the auditory sensory epithelium is precisely timed and follows a steep longitudinal gradient. The molecular signals that promote auditory sensory differentiation and instruct its graded pattern are largely unknown. Here, we identify Activin A and its antagonist follistatin as key regulators of hair cell differentiation and show, using mouse genetic approaches, that a local gradient of Activin A signaling within the auditory sensory epithelium times the longitudinal gradient of hair cell differentiation. Furthermore, we provide evidence that Activin-type signaling regulates a radial gradient of terminal mitosis within the auditory sensory epithelium, which constitutes a novel mechanism for limiting the number of inner hair cells being produced.

scholarly journals Inverse design of grating couplers using the policy gradient method from reinforcement learning

Nanophotonics ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Sean Hooten ◽  
Raymond G. Beausoleil ◽  
Thomas Van Vaerenbergh
Keyword(s):  
Neural Network ◽  
Reinforcement Learning ◽  
Gradient Method ◽  
Photonic Devices ◽  
Inverse Design ◽  
Grating Couplers ◽  
Electromagnetic Devices ◽  
Policy Gradient ◽  
Gradient Based ◽  
Local Gradient

Abstract We present a proof-of-concept technique for the inverse design of electromagnetic devices motivated by the policy gradient method in reinforcement learning, named PHORCED (PHotonic Optimization using REINFORCE Criteria for Enhanced Design). This technique uses a probabilistic generative neural network interfaced with an electromagnetic solver to assist in the design of photonic devices, such as grating couplers. We show that PHORCED obtains better performing grating coupler designs than local gradient-based inverse design via the adjoint method, while potentially providing faster convergence over competing state-of-the-art generative methods. As a further example of the benefits of this method, we implement transfer learning with PHORCED, demonstrating that a neural network trained to optimize 8° grating couplers can then be re-trained on grating couplers with alternate scattering angles while requiring >10× fewer simulations than control cases.

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