A novel adaptive mechanical-wetting lens for visible and near infrared imaging

We demonstrate an adaptive mechanical-wetting lens with a concentric reservoir to reduce image aberrations and overcome the gravity effect. This lens adopts liquid pressure to change the interface between two immiscible liquids which, in turn, changes the focal length of the resultant liquid lens. Good optical performance, high resolution, and a wide dynamic range of both positive and negative optical power are achieved. Since no PDMS is employed, such lenses can extend their working range to infrared region by choosing proper liquids

Liquid-based infrared optical switch

We report an infrared (IR) optical switch using a position-shifting glycerol droplet. The droplet is surrounded by density-matched oil. In the voltage-on state, the droplet shifts in one direction. Upon removing the voltage, the droplet returns to its original position with the aid of interfacial tensions. Due to the strong absorption of glycerol at 1.55 mu m, our IR optical switch shows similar to 95:1 contrast ratio and similar to 200 ms response time. Such a device is promising for fiber optical switch and various IR optical attenuators

Equity pledge of controlling shareholders, property right structure and enterprise innovation efficiency: evidence from Chinese firms

The innovation efficiency of an enterprise is subject to the behavior of the innovation subject, while the equity pledge behavior of the controlling shareholder not only brings convenience for innovation investment and financing, but also brings risks which has an impact on the innovation output of the enterprise. In this paper, we investigate how equity pledge of controlling shareholders affect the enterprise innovation efficiency using the data of China’s A-share listed companies from 2014 to 2020, and examine the effect of property right structure on the relationship between them from the two dimensions of equity nature and equity concentration. We find that equity pledge of controlling shareholders are signifcantly negatively related to innovation efficiency, meaning that equity pledge inhibits the innovation behavior of enterprises and reduces the innovation efficiency. We further provide evidence to show that the impediment effect of equity pledge of controlling shareholder on enterprise innovation efficiency is more pronounced in non-state-owned enterprises and decentralized equity enterprises. Moreover, our analysis shows that different equity concentration levels have different effects in the process of equity pledge affecting enterprise innovation efficiency and the effect of concentrated equity enterprises is lower than that of decentralized enterprises

Switchable focus using a polymeric lenticular microlens array and a polarization rotator

We demonstrate a flat polymeric lenticular microlens array using a mixture of rod-like diacrylate monomer and positive dielectric anisotropy nematic liquid crystal (LC). To create gradient refractive index profile in one microlens, we generate fringing fields from a planar top electrode and two striped bottom electrodes. After UV stabilization, the film is optically anisotropic and can stand alone. We then laminate this film on a 90 degrees twisted-nematic LC cell, which works as a dynamic polarization rotator. The static polymeric lenticular lens exhibits focusing effect only to the extraordinary ray, but no optical effect to the ordinary ray. Such an integrated lens system offers several advantages, such as low voltage, fast response time, and temperature insensitivity, and can be used for switchable 2D/3D displays

Data Augmentation for Environmental Sound Classification Using Diffusion Probabilistic Model with Top-k Selection Discriminator

Despite consistent advancement in powerful deep learning techniques in recent years, large amounts of training data are still necessary for the models to avoid overfitting. Synthetic datasets using generative adversarial networks (GAN) have recently been generated to overcome this problem. Nevertheless, despite advancements, GAN-based methods are usually hard to train or fail to generate high-quality data samples. In this paper, we propose an environmental sound classification augmentation technique based on the diffusion probabilistic model with DPM-Solver$++$ for fast sampling. In addition, to ensure the quality of the generated spectrograms, we train a top-k selection discriminator on the dataset. According to the experiment results, the synthesized spectrograms have similar features to the original dataset and can significantly increase the classification accuracy of different state-of-the-art models compared with traditional data augmentation techniques. The public code is available on https://github.com/JNAIC/DPMs-for-Audio-Data-Augmentation