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868 results on '"Yu, Weihua"'

1. A MEMS-based terahertz broadband beam steering technique

Author

Yu, Weihua, Peng, Hong, Li, Mingze, Li, Haolin, Xue, Yuan, and Xie, Huikai

Subjects
Physics - Optics, Electrical Engineering and Systems Science - Signal Processing
Abstract

A multi-level tunable reflection array wide-angle beam scanning method is proposed to address the limited bandwidth and small scanning angle issues of current terahertz beam scanning technology. In this method, a focusing lens and its array are used to achieve terahertz wave spatial beam control, and MEMS mirrors and their arrays are used to achieve wide-angle beam scanning. The 1~3 order terahertz MEMS beam scanning system designed based on this method can extend the mechanical scanning angle of MEMS mirrors by 2~6 times, when tested and verified using an electromagnetic MEMS mirror with a 7mm optical aperture and a scanning angle of 15{\deg} and a D-band terahertz signal source. The experiment shows that the operating bandwidth of the first-order terahertz MEMS beam scanning system is better than 40GHz, the continuous beam scanning angle is about 30{\deg}, the continuous beam scanning cycle response time is about 1.1ms, and the antenna gain is better than 15dBi at 160GHz. This method has been validated for its large bandwidth and scalable scanning angle, and has potential application prospects in terahertz dynamic communication, detection radar, scanning imaging, and other fields.

Published
2024

37. A UAV Aerial Image Target Detection Algorithm Based on YOLOv7 Improved Model.

Author

Qin, Jie, Yu, Weihua, Feng, Xiaoxi, Meng, Zuqiang, and Tan, Chaohong

Subjects
OBJECT recognition (Computer vision), FEATURE extraction, ALGORITHMS
Abstract

To address the challenges of multi-scale objects, dense distributions, occlusions, and numerous small targets in UAV image detection, we present CMS-YOLOv7, a real-time target detection method based on an enhanced YOLOv7 model. Firstly, the detection layer P2 for small targets was added to YOLOv7 to enhance the detection ability of small and medium-sized targets, and the deep detection head P5 was taken out to mitigate the influence of excessive downsampling on small target images. The anchor frame was calculated by the K-means++ method. Using the concept of Inner-IoU, the Inner-MPDIoU loss function was constructed to control the range of the auxiliary border and improve detection performance. Furthermore, the CARAFE module was introduced to replace traditional upsampling methods, offering improved integration of semantic information during the image upsampling process and enhancing feature mapping accuracy. Simultaneously, during the feature extraction stage, a non-strided convolutional SPD-Conv module was constructed using space-to-depth techniques. This module replaced certain convolutional operations to minimize the loss of fine-grained information and improve the model's ability to extract features from small targets. Experiments on the UAV aerial photo dataset VisDrone2019 demonstrated that compared with the baseline YOLOv7 object detection algorithm, CMS-YOLOv7 achieved an improvement of 3.5% mAP@0.5, 3.0% mAP@0.5:0.95, and the number of parameters decreased by 18.54 M. The ability of small target detection was significantly enhanced. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Phocaeicola vulgatus alleviates diet-induced metabolic dysfunction-associated steatotic liver disease progression by downregulating histone acetylation level via 3-HPAA

Author

Jin, Shengxi, primary, Chen, Peng, additional, Yang, Jing, additional, Li, Duguang, additional, Liu, Xiaolong, additional, Zhang, Yiyin, additional, Xia, Qiming, additional, Li, Yiling, additional, Chen, Guoqiao, additional, Li, Yixuan, additional, Tong, Yifan, additional, Yu, Weihua, additional, Fan, Xiaoxiao, additional, and Lin, Hui, additional

Published
2024
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41. A Fully Automated Mini-Mental State Examination Assessment Model Using Computer Algorithms for Cognitive Screening

Author

Chen, Lihua, primary, Zhang, Meiwei, additional, Yu, Weihua, additional, Yu, Juan, additional, Cui, Qiushi, additional, Chen, Chenxi, additional, Liu, Junjin, additional, Huang, Lihong, additional, Liu, Jiarui, additional, Yu, Wuhan, additional, Li, Wenjie, additional, Zhang, Wenbo, additional, Yan, Mengyu, additional, Wu, Jiani, additional, Wang, Xiaoqin, additional, Song, Jiaqi, additional, Zhong, Fuxing, additional, Liu, Xintong, additional, Wang, Xianglin, additional, Li, Chengxing, additional, Tan, Yuantao, additional, Sun, Jiangshan, additional, Li, Wenyuan, additional, and Lü, Yang, additional

Published
2024
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49. SIRT4 promotes neuronal apoptosis in models of Alzheimer's disease via the STAT2–SIRT4–mTOR pathway.

Author

Xing, Dianxia, Zhang, Wenjin, Cui, Wei, Yao, Xiuya, Xiao, Yaping, Chen, Lihua, Yuan, Shiyun, Duan, Yanyan, Yu, Weihua, Pan, Pengfei, and Lü, Yang

Subjects
ALZHEIMER'S disease, TRANSCRIPTION factors, APOPTOSIS, WESTERN immunoblotting, POLYMERASE chain reaction
Abstract

Alzheimer's disease (AD) is the leading cause of dementia and presents a considerable disease burden. Its pathology involves substantial neuronal loss, primarily attributed to neuronal apoptosis. Although sirtuin 4 (SIRT4) has been implicated in regulating apoptosis in various diseases, the role of SIRT4 in AD pathology remains unclear. The study used APP/PS1 mice as an animal model of AD and amyloid-β (Aβ)1-42-treated HT-22 cells as an AD cell model. SIRT4 expression was determined by quantitative real-time polymerase chain reaction, Western blot, and immunofluorescence. A Sirt4 knockdown model was established by intracranial injection of lentivirus-packaged sh-SIRT4 and cellular lentivirus transfection. Immunohistochemistry and flow cytometry were used to examine Aβ deposition in mice and apoptosis, respectively. Protein expression was assessed by Western blot analysis. The UCSC and JASPAR databases were used to predict upstream transcription factors of Sirt4. Subsequently, the binding of transcription factors to Sirt4 was analyzed using a dual-luciferase assay and chromatin immunoprecipitation. SIRT4 expression was upregulated in both APP/PS1 mice and Aβ-treated HT-22 cells compared with their respective control groups. Sirt4 knockdown in animal and cellular models of AD resulted in reduced apoptosis, decreased Aβ deposition, and amelioration of learning and memory impairments in mice. Mechanistically, SIRT4 modulates apoptosis via the mTOR pathway and is negatively regulated by the transcription factor signal transducer and activator of transcription 2 (STAT2). Our study findings suggest that targeting the STAT2-SIRT4-mTOR axis may offer a new treatment approach for AD. NEW & NOTEWORTHY: The study reveals that in Alzheimer's disease models, SIRT4 expression increases, contributing to neuronal apoptosis and amyloid-β deposition. Reducing SIRT4 lessens apoptosis and amyloid-β accumulation, improving memory in mice. This process involves the mTOR pathway, regulated by STAT2 transcription factor. These findings suggest targeting the STAT2-SIRT4-mTOR axis as a potential Alzheimer's treatment strategy. [ABSTRACT FROM AUTHOR]

Published
2024
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