Search

Your search keyword '"Li Baopeng"' showing total 11 results
Start Over Author "Li Baopeng" Search Limiters Peer Reviewed
11 results on '"Li Baopeng"'

4. Effects of Acupuncture at Neiguan in Neural Activity of Related Brain Regions: A Resting-State fMRI Study in Anxiety

Author

Li,Chunlin, Wang,Yuangeng, Li,Baopeng, and Su,Shanshan

Subjects
Neuropsychiatric Disease and Treatment
Abstract

Chunlin Li,1 Yuangeng Wang,2 Baopeng Li,3 Shanshan Su4 1Department of Encephalopathy, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, People’s Republic of China; 2First College of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, People’s Republic of China; 3Department of Radiology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, People’s Republic of China; 4Department of Nephrology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, People’s Republic of ChinaCorrespondence: Chunlin Li, Department of Encephalopathy, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No. 16369 Jingshi Road, Jinan, People’s Republic of China, Tel +86 137 91118881, Email 37673261@qq.comBackground: Acupuncture of PC6 points has the effects of calming, tranquilizing, regulating qi, and relieving pain and has been clinically found to alleviate anxiety disorders. To explore the mechanism of improvement at the Neiguan point acupuncture in anxiety patients, we used fMRI to observe the changes in brain function in patients with immediate anxiety before and after acupuncture at the Neiguan point.Subjects and Methods: The experiment followed the principle of randomized, single-blind design. Twenty-four anxiety volunteers (14 males and 10 females, 20– 35 years old) were divided randomly into two groups: a group of acupuncture at Neiguan and a group of acupuncture at non-acupoint. Functional magnetic resonance imaging (fMRI) was applied to measure brain activity pre- and post-acupuncture. The amplitude of low-frequency fluctuations (ALFF) and seed-based functional connectivity (FC) was used to analyze the activity and network of brain regions. Statistical analysis was done using SPSS 21.0 and REST 1.8 software.Results: ALFF results revealed that post-acupuncture at Neiguan increased the activity of the left parahippocampal gyrus, fusiform gyrus, and right superior temporal gyrus and decreased the activity of the right middle frontal gyrus, right precuneus, and cuneus. Post-acupuncture at non-acupoint led to a significant ALFF increase in the thalamus and middle frontal gyrus. The ALFF in the left middle frontal gyrus was decreased. Functional connectivity in several anterior default mode network (DMN) regions and vermis cerebelli at left parahippocampal/fusiform gyri was increased, and connectivity in bilateral superior temporal gyri was decreased. FC with posterior DMN regions decreased at the right middle frontal gyrus, right precuneus, and cuneus.Conclusion: Our study elucidates that acupuncture at Neiguan modulates anxiety by activating or deactivating these brain anxiety-related regions and provides potential explanations for the application of PC6 acupuncture in mental diseases.Keywords: PC6 acupuncture, mental disease, functional magnetic resonance imaging, functional connectivity

Published
2022
Full Text
View/download PDF

5. Wavefront Reconstruction Using Two-Frame Random Interferometry Based on Swin-Unet.

Author

Shu, Xindong, Li, Baopeng, and Ma, Zhen

Subjects
INTERFEROMETRY, VIBRATION (Mechanics), PIEZOELECTRIC ceramics, PHASE-shifting interferometry, PIEZOELECTRIC transducers, COST control, WAVEFRONTS (Optics)
Abstract

Due to its high precision, phase-shifting interferometry (PSI) is a commonly used optical component detection method in interferometers. However, traditional PSI, which is susceptible to environmental factors, is costly, with piezoelectric ceramic transducer (PZT) being a major contributor to the high cost of interferometers. In contrast, two-frame random interferometry does not require precise multiple phase shifts, which only needs one random phase shift, reducing control costs and time requirements, as well as mitigating the impact of environmental factors (mechanical vibrations and air turbulence) when acquiring multiple interferograms. A novel method for wavefront reconstruction using two-frame random interferometry based on Swin-Unet is proposed. Besides, improvements have been made on the basis of the established algorithm to develop a new wavefront reconstruction method named Phase U-Net plus (PUN+). According to training the Swin-Unet and PUN+ with a large amount of simulated data generated by physical models, both of the methods accurately compute the wrapped phase from two frames of interferograms with an unknown phase step (except for multiples of π). The superior performance of both methods is effectively showcased by reconstructing phases from both simulated and real interferograms, in comprehensive comparisons with several classical algorithms. The proposed Swin-Unet outperforms PUN+ in reconstructing the wrapped phase and unwrapped phase. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

8. Phase retrieval based on difference map and deep neural networks.

Author

Li, Baopeng, Ersoy, Okan K., Ma, Caiwen, Pan, Zhibin, Wen, Wansha, Song, Zongxi, and Gao, Wei

Subjects
*ALGORITHMS
Abstract

Phase retrieval occurs in many research areas. There are some classical phase retrieval methods such as hybrid input-output (HIO) and difference map (DM). However, phase retrieval results are sensitive to noise, and the reconstructed images always include artefacts. In this paper, we use the DM algorithm together with DNN to get better phase retrieval results. We train one deep neural network using amplitude images and phase images, respectively. First, using DM, we get initial reconstructed amplitude and phase results. Then, using DNN improves both amplitude and phase results. Finally, using the DM algorithm again improves the DNN results further. The numerical experimental results show that using DM gives better results than HIO, and using DNN improves phase information better than just using DNN to train for amplitude information alone. Compared with only using DNN improves amplitude methods, our method using DM plus DNN plus DM yields a better reconstruction performance for both amplitude and phase. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

10. Optimization design of PWM rectifier system based on ant colony algorithm.

Author

Du Ning, Bai Baodong, Chen Dezhi, Li Baopeng, and Wang Jiayin

Abstract

By introducing ant colony algorithm, a novel optimization method is obtained to design PWM rectifier systems based on voltage oriented vector control strategies in this paper. This method was model-free, without user interaction and faster convergent rate than genetic algorithm. Optimization process on the whole of all the PI parameters will obtain a global optimal solution. State of controllable rectification and energy feedback was simulated before and after the optimization by using SimPowerSystems toolbox under Matlab environment. Results show that effectiveness and feasibility of the method has practical significance in engineering system to optimize PI parameters. [ABSTRACT FROM PUBLISHER]

Published
2013
Full Text
View/download PDF

11. Research on speed estimation method of induction motor based on improved fuzzy Kalman filtering.

Author

Chen Dezhi, Bai Baodong, Du Ning, Li Baopeng, and Wang Jiayin

Abstract

An improved fuzzy Kalman filtering speed estimation scheme was proposed by means of measuring stator side voltage and current value based on vector control state equation of induction motor. The designed fuzzy adaptive controller conducted recursive online correction of measurement noise covariance matrix by monitoring the ratio of theory residuals and actual residuals to make it approach real noise level gradually, allowing the filter to perform optimal estimation to improve estimation accuracy of EKF. Meanwhile, co-simulation scheme based on MATLAB and Ansoft was proposed in order to improve simulation accuracy. Field-circuit coupling problems of induction motor under the action of vector control were solved and the parameter optimization accuracy was improved dramatically. The simulation and experimental results show that this algorithm has a strong ability to inhibit the random measurement noise. It is able to estimate motor speed accurately, and has superior static and dynamic characteristics. [ABSTRACT FROM PUBLISHER]

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results