Hongru Shi

Lanzhou University of Technology

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Jiejie Huang

Nantong University

Tingting Sun

China Mobile (China)

Gang Yao

University of Electronic Science and Technology of China

Changyue Hou

University of Electronic Science and Technology of China

Sisi Jiang

University of Electronic Science and Technology of China

Jinyan Ouyang

Lanzhou University of Technology

Hechun Li

University of Electronic Science and Technology of China

Dezhong Yao

University of Electronic Science and Technology of China

Shutao Zhang

Lanzhou University of Technology

Aimin Zhou

Northeast Agricultural University

Cooperative Institutions

University of Electronic Science and Technology of China

Chinese Academy of Medical Sciences & Peking Union Medical College

Lanzhou University of Technology

Zhengzhou University

Nantong University

Hefei University of Technology

Beihang University

North Sichuan Medical University

Affiliated Hospital of North Sichuan Medical College

Wuhan Institute of Technology

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Atypical Hierarchical Connectivity Revealed by Stepwise Functional Connectivity in Aging

Bioengineering (2023)

Hechun Li Hongru Shi Sisi Jiang Changyue Hou Hanxi Wu

Hierarchical functional structure plays a crucial role in brain function. We aimed to investigate how aging affects hierarchical functional structure and to evaluate the relationship between such effects and molecular, microvascular, and cognitive features. We used resting-state functional magnetic resonance imaging (fMRI) data from 95 older adults (66.94 ± 7.23 years) and 44 younger adults (21.8 ± 2.53 years) and employed an innovative graph-theory-based analysis (stepwise functional connectivity (SFC)) to reveal the effects of aging on hierarchical functional structure in the brain. In the older group, an SFC pattern converged on the primary sensory-motor network (PSN) rather than the default mode network (DMN). Moreover, SFC decreased in the DMN and increased in the PSN at longer link-steps in aging, indicating a reconfiguration of brain hub systems during aging. Subsequent correlation analyses were performed between SFC values and molecular, microvascular features, and behavioral performance. Altered SFC patterns were associated with dopamine and serotonin, suggesting that altered hierarchical functional structure in aging is linked to the molecular fundament with dopamine and serotonin. Furthermore, increased SFC in the PSN, decreased SFC in the DMN, and accelerated convergence rate were all linked to poorer microvascular features and lower executive function. Finally, a mediation analysis among SFC features, microvascular features, and behavioral performance indicated that the microvascular state may influence executive function through SFC features, highlighting the interactive effects of SFC features and microvascular state on cognition.

10.3390/bioengineering10101166

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MD-TransUNet: An Image Segmentation Network for Car Front Face Design

Applied Sciences (2024)

Jinyan Ouyang Hongru Shi Jianning Su Shutao Zhang Aimin Zhou

To enhance the segmentation accuracy of car front face elements such as headlights and grilles for car front face design, and to improve the superiority and efficiency of solutions in automotive partial modification design, this paper introduces MD-TransUNet, a semantic segmentation network based on the TransUNet model. MD-TransUNet integrates multi-scale attention gates and dynamic-channel graph convolution networks to enhance image restoration across various design drawings. To improve accuracy and detail retention in segmenting automotive front face elements, dynamic-channel graph convolution networks model global channel relationships between contextual sequences, thereby enhancing the Transformer’s channel encoding capabilities. Additionally, a multi-scale attention-based decoder structure is employed to restore feature map dimensions, mitigating the loss of detail in the local feature encoding by the Transformer. Experimental results demonstrate that the MSAG module significantly enhances the model’s ability to capture details, while the DCGCN module improves the segmentation accuracy of the shapes and edges of headlights and grilles. The MD-TransUNet model outperforms existing models on the automotive front face dataset, achieving mF-score, mIoU, and OA metrics of 95.81%, 92.08%, and 98.86%, respectively. Consequently, the MD-TransUNet model increases the precision of automotive front face element segmentation and achieves a more advanced and efficient approach to partial modification design.

10.3390/app14198688

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Analysis of Frequency Regulation Capability of Doubly Fed Induction Generator and Supercapacitor Energy Storage Based on Dynamic Power Flow

Energies (2023)

Tingting Sun Hongru Shi Lei Ren Jiejie Huang

The grid-integrated doubly fed induction generator (DFIG) is required to participate in the frequency regulation of the power system. The supercapacitor energy storage (SES) is capable of enhancing the frequency regulation capability of the DFIG in a coupled manner. The SES is connected to the DC capacitor of the DFIG and provides active power response through the droop control. The dynamic power flow (DPF) model is established to quantify the frequency response of the power system when the DFIG-SES system participates in the frequency regulation. The integration of the SES affects the internal power flow distribution of the DFIG; thus, the detailed model of the DFIG is incorporated into the DPF analysis. Considering the different response speeds of the synchronous generator (SG), the SES, and the DFIG to the frequency regulation, the first-order inertia delay in the governor control of the SG is included in the DPF model. The impact of the delay time constant on the continued operation time of the SES is analyzed. With the same deloading percentage, the output power of the DFIG is adjusted based on a variable droop coefficient scheme to fully utilize its active power reserve. The feasibility and effectiveness of the DFIG-SES scheme to participate in the frequency regulation are analyzed based on the DPF and verified through numerical analysis.

Frequency grid

10.3390/en16207059

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Application of controllable resistive-type fault current limiter to low-voltage ride-through of DFIG

2022 7th International Conference on Power and Renewable Energy (ICPRE) (2023)

Tingting Sun Hongru Shi Jiejie Huang

The resistive-type fault current limiter (FCL) may be applied to assist the low-voltage ride-through (LVRT) of the doubly-fed induction generator (DFIG). Considering the various fault scenarios, FCL with the fixed resistance may not provide flexible response to the different depths of terminal voltage drop. The controllable resistive-type fault current limiter (CRTFCL) is capable to adjust its resistance value to guarantee the satisfactory LVRT effect under different voltage drop depths. In this paper, the CRTFCL is applied to the LVRT of the DFIG. The different control targets of the DFIG during the LVRT, i.e., stator voltage control and active power output control, are selected and realized through the control to the resistance of the CRTFCL. The impact of the parameter setting of the CRTFCL resistance control on the LVRT effect is investigated. The numerical analysis is carried out with the different levels of the voltage drop. The control scheme to the CRTFCL resistance is simulated to show its feasibility and effectiveness to improve the LVRT effect of the DFIG.

Voltage drop

Fault current limiter

Resistive touchscreen

Limiter

10.1109/icpre59655.2023.10353667

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