Western diet(rich in highly refined sugar and fat)can induce a range of metabolic dysfunctions in animals and humans,including neuroinflammation and cognitive function decline.Neuroinflammation and cognitive impairmen...Western diet(rich in highly refined sugar and fat)can induce a range of metabolic dysfunctions in animals and humans,including neuroinflammation and cognitive function decline.Neuroinflammation and cognitive impairment,two critical pathological characteristics of Alzheimer’s disease,have been closely associated with microbial alteration via the gut-brain axis.Thus,the present study aimed to investigate the influence of 2-O-β-D-glucopyranosyl-L-ascorbic acid(AA-2βG)isolated from the fruits of Lycium barbarum on preventing the high-fructose diet(HFrD)induced neuroinflammation in mice.It was found that AA-2βG prevented HFr D-induced cognitive deficits.AA-2βG also predominantly enhanced the gut barrier integrity,decreased lipopolysaccharide entry into the circulation,which subsequently countered the activation of glial cells and neuroinflammatory response.These beneficial effects were transmissible by horizontal fecal microbiome transplantation,transferring from AA-2βG fed mice to HFr D fed mice.Additionally,AA-2βG exerted neuroprotective effects involving the enrichment of Lactobacillus and Akkermansia,potentially beneficial intestinal bacteria.The present study provided the evidence that AA-2βG could improve indices of cognition and neuroinflammmation via modulating gut dybiosis and preventing leaky gut.As a potential functional food ingredient,AA-2βG may be applied to attenuate neuroinflammation associated with Western-style diets.展开更多
The work in this article focuses on developing and improving the performance of new leaky-wave antenna configurations that can be adapted for use in radar systems. The study focused on the W-band, where we demonstrate...The work in this article focuses on developing and improving the performance of new leaky-wave antenna configurations that can be adapted for use in radar systems. The study focused on the W-band, where we demonstrated the possibility of modifying resonant frequencies and reducing the number of patches required. The antenna was designed using HFSS, based on the finite element method. It we designed enabled us to observe the influence of the number of patches on the radiation pattern, and also to achieve low levels of minor’s lobes. and good directivity at the operating frequency. These patches are arranged in the shape of an inverted T. The interest of this study is to meet the requirements of radar antennas dedicated to detection.展开更多
The communication system of high-speed trains in railway tunnels needs to be built with leaky cables fixed on the tunnel wall with special fixtures.To ensure safety,checking the regular leaky cable fixture is necessar...The communication system of high-speed trains in railway tunnels needs to be built with leaky cables fixed on the tunnel wall with special fixtures.To ensure safety,checking the regular leaky cable fixture is necessary to elimi-nate the potential danger.At present,the existing fixture detection algorithms are difficult to take into account detection accuracy and speed at the same time.The faulty fixture is also insufficient and difficult to obtain,seriously affecting the model detection effect.To solve these problems,an innovative detection method is proposed in this paper.Firstly,we presented the Res-Net and Wasserstein-Deep Convolution GAN(RW-DCGAN)to implement data augmentation,which can enable the faulty fixture to export more high-quality and irregular images.Secondly,we proposed the Ghost SENet-YOLOv5(GS-YOLOv5)to enhance the expression of fixture feature,and further improve the detection accuracy and speed.Finally,we adopted the model compression strategy to prune redundant channels,and visualized training details with Grad-CAM to verify the reliability of our model.Experimental results show that the algorithm model is 69.06%smaller than the original YOLOv5 model,with 70.07%fewer parameters,2.1%higher accuracy and 14.82 fps faster speed,meeting the needs of tunnel fixture detection.展开更多
基金the financial support from the Key Research and Development Program of Ningxia Hui Autonomous Region of China(2021BEF02008)the National Natural Science Foundation of China(32272330)the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘Western diet(rich in highly refined sugar and fat)can induce a range of metabolic dysfunctions in animals and humans,including neuroinflammation and cognitive function decline.Neuroinflammation and cognitive impairment,two critical pathological characteristics of Alzheimer’s disease,have been closely associated with microbial alteration via the gut-brain axis.Thus,the present study aimed to investigate the influence of 2-O-β-D-glucopyranosyl-L-ascorbic acid(AA-2βG)isolated from the fruits of Lycium barbarum on preventing the high-fructose diet(HFrD)induced neuroinflammation in mice.It was found that AA-2βG prevented HFr D-induced cognitive deficits.AA-2βG also predominantly enhanced the gut barrier integrity,decreased lipopolysaccharide entry into the circulation,which subsequently countered the activation of glial cells and neuroinflammatory response.These beneficial effects were transmissible by horizontal fecal microbiome transplantation,transferring from AA-2βG fed mice to HFr D fed mice.Additionally,AA-2βG exerted neuroprotective effects involving the enrichment of Lactobacillus and Akkermansia,potentially beneficial intestinal bacteria.The present study provided the evidence that AA-2βG could improve indices of cognition and neuroinflammmation via modulating gut dybiosis and preventing leaky gut.As a potential functional food ingredient,AA-2βG may be applied to attenuate neuroinflammation associated with Western-style diets.
文摘The work in this article focuses on developing and improving the performance of new leaky-wave antenna configurations that can be adapted for use in radar systems. The study focused on the W-band, where we demonstrated the possibility of modifying resonant frequencies and reducing the number of patches required. The antenna was designed using HFSS, based on the finite element method. It we designed enabled us to observe the influence of the number of patches on the radiation pattern, and also to achieve low levels of minor’s lobes. and good directivity at the operating frequency. These patches are arranged in the shape of an inverted T. The interest of this study is to meet the requirements of radar antennas dedicated to detection.
基金supported by the National Natural Science Foundation of China(No.61702347,No.62027801)Natural Science Foundation of Hebei Province(No.F2022210007,No.F2017210161)+2 种基金Science and Technology Project of Hebei Education Department(No.ZD2022100,No.QN2017132)Central Guidance on Local Science and Technology Development Fund(No.226Z0501G)National innovation and Entrepreneurship training program for college students(No.202110107024).
文摘The communication system of high-speed trains in railway tunnels needs to be built with leaky cables fixed on the tunnel wall with special fixtures.To ensure safety,checking the regular leaky cable fixture is necessary to elimi-nate the potential danger.At present,the existing fixture detection algorithms are difficult to take into account detection accuracy and speed at the same time.The faulty fixture is also insufficient and difficult to obtain,seriously affecting the model detection effect.To solve these problems,an innovative detection method is proposed in this paper.Firstly,we presented the Res-Net and Wasserstein-Deep Convolution GAN(RW-DCGAN)to implement data augmentation,which can enable the faulty fixture to export more high-quality and irregular images.Secondly,we proposed the Ghost SENet-YOLOv5(GS-YOLOv5)to enhance the expression of fixture feature,and further improve the detection accuracy and speed.Finally,we adopted the model compression strategy to prune redundant channels,and visualized training details with Grad-CAM to verify the reliability of our model.Experimental results show that the algorithm model is 69.06%smaller than the original YOLOv5 model,with 70.07%fewer parameters,2.1%higher accuracy and 14.82 fps faster speed,meeting the needs of tunnel fixture detection.
