Volume holographic illuminator for Airy light-sheet microscopy.

Airy light sheets combined with the deconvolution approach can provide multiple benefits, including large field of view (FOV), thin optical sectioning, and high axial resolution. The efficient design of an Airy light-sheet fluorescence microscope requires a compact illumination system. Here, we show that an Airy light sheet can be conveniently implemented in microscopy using a volume holographic grating (VHG). To verify the FOV and the axial resolution of the proposed VHG-based Airy light-sheet fluorescence microscope, ex-vivo fluorescently labeled Caenorhabditis elegans (C. elegans) embryos were imaged, and the Richardson-Lucy deconvolution method was used to improve the image contrast. Optimized parameters for deconvolution were compared with different methods. The experimental results show that the FOV and the axial resolution were 196 µm and 3 µm, respectively. The proposed method of using a compact VHG to replace the common spatial light modulator provides a direct solution to construct a compact light-sheet fluorescence microscope.

Intelligent Phase Contrast Meta-Microscope System.

Phase contrast imaging techniques enable the visualization of disparities in the refractive index among various materials. However, these techniques usually come with a cost: the need for bulky, inflexible, and complicated configurations. Here, we propose and experimentally demonstrate an ultracompact meta-microscope, a novel imaging platform designed to accomplish both optical and digital phase contrast imaging. The optical phase contrast imaging system is composed of a pair of metalenses and an intermediate spiral phase metasurface located at the Fourier plane. The performance of the system in generating edge-enhanced images is validated by imaging a variety of human cells, including lung cell lines BEAS-2B, CLY1, and H1299 and other types. Additionally, we integrate the ResNet deep learning model into the meta-microscope to transform bright-field images into edge-enhanced images with high contrast accuracy. This technology promises to aid in the development of innovative miniature optical systems for biomedical and clinical applications.

Reducing side effects of hiding sensitive itemsets in privacy preserving data mining.

Data mining is traditionally adopted to retrieve and analyze knowledge from large amounts of data. Private or confidential data may be sanitized or suppressed before it is shared or published in public. Privacy preserving data mining (PPDM) has thus become an important issue in recent years. The most general way of PPDM is to sanitize the database to hide the sensitive information. In this paper, a novel hiding-missing-artificial utility (HMAU) algorithm is proposed to hide sensitive itemsets through transaction deletion. The transaction with the maximal ratio of sensitive to nonsensitive one is thus selected to be entirely deleted. Three side effects of hiding failures, missing itemsets, and artificial itemsets are considered to evaluate whether the transactions are required to be deleted for hiding sensitive itemsets. Three weights are also assigned as the importance to three factors, which can be set according to the requirement of users. Experiments are then conducted to show the performance of the proposed algorithm in execution time, number of deleted transactions, and number of side effects.