4K-DMDNet:diffraction model-driven network for 4K computer-generated holography

Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography(CGH).Current data-driven deep learning algorithms face the challenge that the labeled training datasets limit the training performance and generalization.The model-driven deep learning introduces the diffraction model into the neural network.It eliminates the need for the labeled training dataset and has been extensively applied to hologram generation.However,the existing model-driven deep learning algorithms face the problem of insufficient constraints.In this study,we propose a model-driven neural network capable of high-fidelity 4K computer-generated hologram generation,called 4K Diffraction Model-driven Network(4K-DMDNet).The constraint of the reconstructed images in the frequency domain is strengthened.And a network structure that combines the residual method and sub-pixel convolution method is built,which effectively enhances the fitting ability of the network for inverse problems.The generalization of the 4K-DMDNet is demonstrated with binary,grayscale and 3D images.High-quality full-color optical reconstructions of the 4K holograms have been achieved at the wavelengths of 450 nm,520 nm,and 638 nm.

Photoreduction of CO_(2) in the presence of CH_(4) over g-C_(3)N_(4) modified with TiO_(2) nanoparticles at room temperature

CO_(2)reduction under simulated sunlight over photocatalysts has become an attractive researcher area recently.In this work,carbon nitride compounds modified by TiO_(2)nanoparticles(TNPs)have been used for the photoreduction of CO_(2)in the presence of CH_(4)at room temperature.Briefly,a series of noble-metal-free TNP-graphitic-carbon nitride(g-C_(3)N_(4),also abbreviated CN)photocatalysts with different TNPs loadings and calcination temperatures have been synthesized by a wet-chemical method.The characterization results of XRD,FTIR,SEM,TEM,BET,XPS,CO_(2)Adsorption,UV-vis,and PL demonstrate that the BET surface area and CO_(2)adsorption capacity have been improved after the calcination.Besides,the g-C_(3)N_(4)has been successfully coupled with the TNPs and a heterojunction has formed at their interface.These characters contribute to increase the photocatalytic activity of TNPs-CN toward reducing CO_(2)in the presence of CH_(4),and its'performance is better than bare g-C_(3)N_(4),Titania(P_(25))-CN,MgO-CN,or Cu_(2)O-CN.Orthogonal experiments are then carried out to investigate the sensitivity factors and optimum conditions.The sensitivity results show that the reaction pressure makes little difference on the photocatalysis results,which verifies the photoinduced CO_(2)-CH_(4)reaction has a tiny change in gas volume.In addition,under the optimum conditions,the turnover frequency(TOF)of CO after 4 h reaction can reach 9.98μmol g-cat.^(-1)h^(-1),and traces of ethane and ethylene have been detected during the reactions.In addition,surface acetate and carbonaceous deposit are found on the(20)TNPs-CN/450 surface after continuous 24 h irradiation under the optimum conditions,which resulting in the inactivation of the catalyst.Finally,possible reaction mechanisms have been proposed based on the results.

Single-shot lensless imaging with fresnel zone aperture and incoherent illumination

Lensless imaging eliminates the need for geometric isomorphism between a scene and an image while allowing the construction of compact,lightweight imaging systems.However,a challenging inverse problem remains due to the low reconstructed signal-to-noise ratio.Current implementations require multiple masks or multiple shots to denoise the reconstruction.We propose single-shot lensless imaging with a Fresnel zone aperture and incoherent illumination.By using the Fresnel zone aperture to encode the incoherent rays in wavefront-like form,the captured pattern has the same form as the inline hologram.Since conventional backpropagation reconstruction is troubled by the twin-image problem,we show that the compressive sensing algorithm is effective in removing this twin-image artifact due to the sparsity in natural scenes.The reconstruction with a significantly improved signal-to-noise ratio from a single-shot image promotes a camera architecture that is flat and reliable in its structure and free of the need for strict calibration.

Quantitative phase imaging through an ultra-thin lensless fiber endoscope

Quantitative phase imaging(QPI)is a label-free technique providing both morphology and quantitative biophysical information in biomedicine.However,applying such a powerful technique to in vivo pathological diagnosis remains challenging.Multi-core fiber bundles(MCFs)enable ultra-thin probes for in vivo imaging,but current MCF imaging techniques are limited to amplitude imaging modalities.We demonstrate a computational lensless microendoscope that uses an ultra-thin bare MCF to perform quantitative phase imaging with microscale lateral resolution and nanoscale axial sensitivity of the optical path length.The incident complex light field at the measurement side is precisely reconstructed from the far-field speckle pattern at the detection side,enabling digital refocusing in a multi-layer sample without any mechanical movement.The accuracy of the quantitative phase reconstruction is validated by imaging the phase target and hydrogel beads through the MCF.With the proposed imaging modality,three-dimensional imaging of human cancer cells is achieved through the ultra-thin fiber endoscope,promising widespread clinical applications.

Fabrication of a Flexible Electric Skin Using a Bionic Cell and Study of Its Sensing Ability

Imitating the structure and function of the Pacinian corpuscle in the human body,a Bionic Cell(BC)with a liquid core was designed and made with polyvinylidene fluoride(PVDF),and an Electronic Skin(ES)sensor was successfully obtained by embedding the BCs into silicone rubber.The passive sensing ability of the ES for surface vibration pressure was measured.The results showed that the ES could detect waveform,frequency,amplitude and other parameters of the surface,and it exhibited not only a high sensitivity of 0.46563 fc/Pa,but also a large pressure measurement range of 0.6 Pa–6014 Pa.A falling real object impact experiment was carried out,and the results indicated that the ES output charge was linearly related to the falling height of the object and logarithmically related to the mass of the object.Then,a crawling insect experiment and human pulse experiment were performed to study the perception ability of the ES to irregular pressure.Due to its special structure,simple fabrication process,and high sensitivity wide measurement range,the ES fabricated in this paper is expected to be used as robot skin with tactile perception ability in the near future.

A Text Correlation Algorithm for Stock Market News Event Extraction

To extract effective information in massive financial news,this paper proposes amethod to calculate the correlation between text and text set by extracting structured events in the stockmarket news text,and provides more detailed and interpretable information.First,the structured event triplet was extracted from the text set,and the trained word vector was used to represent the event triplet as an event vector.Event vectors were clustered,the cosine distances were calculated for the cluster centers,and the correlation between the text sets was determined by matching.Finally,the event triplets with the highest correlation between the text sets were selected to provide explanation information for the calculation results.Experimental results show that this method effectively measures the correlation between text and text set.