Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

100 Hertz frame-rate switching threedimensional orbital angular momentum multiplexing holography via cross convolution

The orbital angular momentum(OAM)of light has been implemented as an information carrier in OAM holography.Holographic information can be multiplexed in theoretical unbounded OAM channels,promoting the applications of optically addressable dynamic display and high-security optical encryption.However,the frame-rate of the dynamic extraction of the information reconstruction process in OAM holography is physically determined by the switching speed of the incident OAM states,which is currently below 30 Hz limited by refreshing rate of the phase-modulation spatial light modulator(SLM).Here,based on a cross convolution with the spatial frequency of the OAM-multiplexing hologram,the spatial frequencies of an elaborately-designed amplitude distribution,namely amplitude decoding key,has been adopted for the extraction of three-dimensional holographic information encoded in a specific OAM information channel.We experimentally demonstrated a dynamic extraction frame rate of 100 Hz from an OAM multiplexing hologram with 10 information channels indicated by individual OAM values from-50 to 50.The new concept of cross convolution theorem can even provide the potential of parallel reproduction and distribution of information encoded in many OAM channels at various positions which boosts the capacity of information processing far beyond the traditional decoding methods.Thus,our results provide a holographic paradigm for high-speed 3D information processing,paving an unprecedented way to achieve the high-capacity short-range optical communication system.

Using Class Based Document Frequency to Select Features in Text Classification

Document Frequency(DF)is reported to be a simple yet quite effective measure for feature selection in text classification,which is a key step in processing big textual data collections.The calculation is based on how many documents in a collection contain a feature,which can be a word,a phrase,a n-gram,or a specially derived attribute.It is an unsupervised and class independent metric.Features of the same DF value may have quite different distribution over different categories,and thus have different discriminative power over categories.For example,in a binary classification problem,if feature A only appears in one category,but feature B,which has the same DF value as feature A,is evenly distributed in both categories.Then,feature A is obviously more effective than feature B for classification.To overcome this weakness of the original document frequency feature selection metric,we,therefore,propose a class based document frequency strategy to further refine the original DF to some extent.Extensive experiments on three text classification datasets demonstrate the effectiveness of the proposed measures.Using Class Based Document Frequency to Select

Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding

Machine learning with optical neural networks has featured unique advantages of the information processing including high speed,ultrawide bandwidths and low energy consumption because the optical dimensions(time,space,wavelength,and polarization)could be utilized to increase the degree of freedom.However,due to the lack of the capability to extract the information features in the orbital angular momentum(OAM)domain,the theoretically unlimited OAM states have never been exploited to represent the signal of the input/output nodes in the neural network model.Here,we demonstrate OAM-mediated machine learning with an all-optical convolutional neural network(CNN)based on Laguerre-Gaussian(LG)beam modes with diverse diffraction losses.The proposed CNN architecture is composed of a trainable OAM mode-dispersion impulse as a convolutional kernel for feature extraction,and deep-learning diffractive layers as a classifier.The resultant OAM mode-dispersion selectivity can be applied in information mode-feature encoding,leading to an accuracy as high as 97.2%for MNIST database through detecting the energy weighting coefficients of the encoded OAM modes,as well as a resistance to eavesdropping in point-to-point free-space transmission.Moreover,through extending the target encoded modes into multiplexed OAM states,we realize all-optical dimension reduction for anomaly detection with an accuracy of 85%.Our work provides a deep insight to the mechanism of machine learning with spatial modes basis,which can be further utilized to improve the performances of various machine-vision tasks by constructing the unsupervised learning-based auto-encoder.

Discovery of nitazoxanide-based derivatives as autophagy activators for the treatment of Alzheimer’s disease

Drug repurposing is an efficient strategy for new drug discovery.Our latest study found that nitazoxanide(NTZ),an approved anti-parasite drug,was an autophagy activator and could alleviate the symptom of Alzheimer’s disease(AD).In order to further improve the efficacy and discover new chemical entities,a series of NTZ-based derivatives were designed,synthesized,and evaluated as autophagy activator against AD.All compounds were screened by the inhibition of phosphorylation of p70S6K,which was the direct substrate of mammalian target of rapamycin(mTOR)and its phosphorylation level could reflect the mTOR-dependent autophagy level.Among these analogs,compound 22 exhibited excellent potency in promotingβ-amyloid(Aβ)clearance,inhibiting tau phosphorylation,as well as stimulating autophagy both in vitro and in vivo.What’s more,22 could effectively improve the memory and cognitive impairments in APP/PS1 transgenic AD model mice.These results demonstrated that 22 was a potential candidate for the treatment of AD.

Specific tracking of monoamine oxidase A in heart failure models by a far-red fluorescent probe with an ultra large Stokes shift

Monoamine oxidase A(MAO-A) is a prominent myocardial source of reactive oxygen species(ROS), and its expression and activity are strongly increased in failing hearts. Therefore, accurate evaluation of MAOA activity in cardiomyocytes is of great importance for understanding its biological functions and early diagnosing the progression of heart failure. However, so far, there is no report on the fluorescent diagnosis of heart failure by a specific probe for MAO-A. In this work, two far-red emissive fluorescent turn-on probes(KXS-M1 and KXS-M2) for the highly selective and sensitive detection of MAO-A were fabricated.Both probes exhibit good response to MAO-A, one of which, KXS-M2, performs better than the other one in terms of a fluorescence increment and sensitivity. Using the pioneering probe KXS-M2, specific fluorescence imaging of MAO-A in glucose-deprived H9c2 cardiac cells, zebrafish and isoprenaline-induced failing heart tissues was achieved, proving that KXS-M2 can serve as a powerful tool for the diagnosis and treatment of heart failure.