Research progress on intestinal microbiota regulating cognitive function through the gut-brain axis.

The intestinal microbiota community is a fundamental component of the human body and plays a significant regulatory role in maintaining overall health and in the management disease states.The intestinal microbiota-gut-brain axis represents a vital connection in the cognitive regulation of the central nervous system by the intestinal microbiota.The impact of intestinal microbiota on cognitive function is hypothesized to manifest through both the nervous system and circulatory system. Imbalances in intestinal microbiota during the perioperative period could potentially contribute to perioperative neurocognitive dysfunction. This article concentrates on a review of existing literature to explore the potential influence of intestinal microbiota on brain and cognitive functions via the nervous and circulatory systems.Additionally, it summarizes recent findings on the impact of perioperative intestinal dysbacteriosis on perioperative neurocognitive dysfunction and suggests novel approaches for prevention and treatment of this condition.

65,536-ary orbital angular momentum-shift keying free-space optical communication based on few-shot learning.

In an orbital angular momentum-shift keying free-space optical (OAM-SK FSO) communication system, precisely recognizing OAM superposed modes at the receiver site is crucial to improve the communication capacity. While deep learning (DL) provides an effective method for OAM demodulation, with the increase of OAM modes, the dimension explosion of OAM superstates results in unacceptable costs on training the DL model. Here, we demonstrate a few-shot-learning-based demodulator to achieve a 65,536-ary OAM-SK FSO communication system. By learning from only 256 classes of samples, the remaining 65,280 unseen classes can be predicted with an accuracy of more than 94%, which saves a large number of resources on data preparation and model training. Based on this demodulator, we first realize the single transmission of a color pixel and the single transmission of two gray scale pixels on the application of colorful-image-transmission in free space with an average error rate less than 0.023%. This work may provide a new, to the best of our knowledge, approach for big data capacity in optical communication systems.

Meta-learning-based optical vector beam high-fidelity communication under high scattering.

While spatial structured light based free space optical communication provides high-bandwidth communication with broad application prospect, severe signal distortion caused by optical scattering from ambient microparticles in the atmosphere can lead to data degradation. A deep-learning-based adaptive demodulator has been demonstrated to resolve the information encoded in the severely distorted channel, but the high generalization ability for different scattering always requires prohibitive costs on data preparation and reiterative training. Here, we demonstrate a meta-learning-based auto-encoder demodulator, which learns from prior theoretical knowledge, and then training with only three realistic samples per class can rectify and recognize transmission distortion. By employing such a demodulator to hybrid vector beams, high fidelity communication can be established, and data costs are reduced when faced with different scattering channels. In a proof-of-principle experiment, an image with 256 gray values is transmitted under severe scattering with an error ratio of less than 0.05%. Our work opens the door to high-fidelity optical communication in random media environments.

Measuring Stokes parameters by means of unitary operations.

We propose an improved scheme to measure the Stokes polarization parameters by making the to-be-measured state evolve unitarily. An optical setup able to implement the scheme is presented theoretically and experimentally. Theoretical results indicate that at least two unitary operators should be employed to determine the Stokes parameters of light with arbitrary degrees of polarization. Compared with the results acquired by a commercial polarimeter, the proposed scheme is used to obtain the Stokes parameters of 13 representative states with degrees of polarization r=1 and r=0.5, experimentally. The fidelity between the two states gained by the above methods is in the range of 0.9802±0.0046 to 1.0000±0.0000.

Implementation of High Time Delay Accuracy of Ultrasonic Phased Array Based on Interpolation CIC Filter.

In order to improve the accuracy of ultrasonic phased array focusing time delay, analyzing the original interpolation Cascade-Integrator-Comb (CIC) filter, an 8× interpolation CIC filter parallel algorithm was proposed, so that interpolation and multichannel decomposition can simultaneously process. Moreover, we summarized the general formula of arbitrary multiple interpolation CIC filter parallel algorithm and established an ultrasonic phased array focusing time delay system based on 8× interpolation CIC filter parallel algorithm. Improving the algorithmic structure, 12.5% of addition and 29.2% of multiplication was reduced, meanwhile the speed of computation is still very fast. Considering the existing problems of the CIC filter, we compensated the CIC filter; the compensated CIC filter's pass band is flatter, the transition band becomes steep, and the stop band attenuation increases. Finally, we verified the feasibility of this algorithm on Field Programming Gate Array (FPGA). In the case of system clock is 125 MHz, after 8× interpolation filtering and decomposition, time delay accuracy of the defect echo becomes 1 ns. Simulation and experimental results both show that the algorithm we proposed has strong feasibility. Because of the fast calculation, small computational amount and high resolution, this algorithm is especially suitable for applications with high time delay accuracy and fast detection.