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8. Coordinated Control of Path Tracking and Yaw Stability for Distributed Drive Electric Vehicle Based on AMPC and DYC

Author

Wu, Dongmei, Guan, Yuying, Xia, Xin, Du, Changqing, Yan, Fuwu, Li, Yang, Hua, Min, and Liu, Wei

Subjects
Computer Science - Robotics
Abstract

Maintaining both path-tracking accuracy and yaw stability of distributed drive electric vehicles (DDEVs) under various driving conditions presents a significant challenge in the field of vehicle control. To address this limitation, a coordinated control strategy that integrates adaptive model predictive control (AMPC) path-tracking control and direct yaw moment control (DYC) is proposed for DDEVs. The proposed strategy, inspired by a hierarchical framework, is coordinated by the upper layer of path-tracking control and the lower layer of direct yaw moment control. Based on the linear time-varying model predictive control (LTV MPC) algorithm, the effects of prediction horizon and weight coefficients on the path-tracking accuracy and yaw stability of the vehicle are compared and analyzed first. According to the aforementioned analysis, an AMPC path-tracking controller with variable prediction horizon and weight coefficients is designed considering the vehicle speed's variation in the upper layer. The lower layer involves DYC based on the linear quadratic regulator (LQR) technique. Specifically, the intervention rule of DYC is determined by the threshold of the yaw rate error and the phase diagram of the sideslip angle. Extensive simulation experiments are conducted to evaluate the proposed coordinated control strategy under different driving conditions. The results show that, under variable speed and low adhesion conditions, the vehicle's yaw stability and path-tracking accuracy have been improved by 21.58\% and 14.43\%, respectively, compared to AMPC. Similarly, under high speed and low adhesion conditions, the vehicle's yaw stability and path-tracking accuracy have been improved by 44.30\% and 14.25\%, respectively, compared to the coordination of LTV MPC and DYC. The results indicate that the proposed adaptive path-tracking controller is effective across different speeds.

Published
2023

9. Animal-assisted interventions in geriatric depression： a scoping review

Author

Yan Yi, Wu Dongmei, Ye Zixiang, and Zhan Weixi

Subjects
animal-assisted interventions, geriatric depression, psychological therapy, scoping review, Psychology, BF1-990, Psychiatry, RC435-571
Abstract

BackgroundGeriatric depression is a common psychiatric problem among older adults. Animal-assisted interventions （AAI） can aid in the treatment of psychiatric disorders， but their effectiveness in geriatric depression remains controversial.ObjectiveTo provide an overview of the current research on AAI in alleviating geriatric depression， in order to provide references for developing AAI programs for this population.MethodsBased on Arksey's scoping review method， a comprehensive literature search was conducted on April 16， 2023. The databases searched included China Knowledge Network， VIP， Wanfang Medical Network， China Biomedical Literature Database， Web of Science， PubMed， CINAHL， Cochrane Library and Embase. The search aimed to collect studies related to AAI and geriatric depression from the inception of each database until April 15， 2023. Two trained researchers independently screened the literature and extracted data on basic information.ResultsA total of 13 studies were included in the final review. AAI settings included nursing homes， hospitals， communities， day care centers and residences. Interventions involved touching and naming the animals， verbally interacting with the animals， playing games with the animals， communicating with the therapists and learning to care for the animals. AAI was found to improve social interaction and communication abilities， bring positive emotional experiences and enhance life satisfaction in geriatric depression. However， its effect on cognitive function improvement was inconclusive.ConclusionAAI can potentially alleviate negative mood and depressive symptoms in geriatric depression. ［Funded by National Natural Science Foundation of China （number， 82001444）］

Published
2024
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10. Futuristic Variations and Analysis in Fundus Images Corresponding to Biological Traits

Author

Hassan, Muhammad, Zhang, Hao, Ameen, Ahmed Fateh, Zeng, Home Wu, Ma, Shuye, Liang, Wen, Shang, Dingqi, Ding, Jiaming, Zhan, Ziheng, Lam, Tsz Kwan, Xu, Ming, Huang, Qiming, Wu, Dongmei, Zhang, Can Yang, You, Zhou, Ain, Awiwu, and Qin, Pei Wu

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Fundus image captures rear of an eye, and which has been studied for the diseases identification, classification, segmentation, generation, and biological traits association using handcrafted, conventional, and deep learning methods. In biological traits estimation, most of the studies have been carried out for the age prediction and gender classification with convincing results. However, the current study utilizes the cutting-edge deep learning (DL) algorithms to estimate biological traits in terms of age and gender together with associating traits to retinal visuals. For the traits association, our study embeds aging as the label information into the proposed DL model to learn knowledge about the effected regions with aging. Our proposed DL models, named FAG-Net and FGC-Net, correspondingly estimate biological traits (age and gender) and generates fundus images. FAG-Net can generate multiple variants of an input fundus image given a list of ages as conditions. Our study analyzes fundus images and their corresponding association with biological traits, and predicts of possible spreading of ocular disease on fundus images given age as condition to the generative model. Our proposed models outperform the randomly selected state of-the-art DL models., Comment: 10 pages, 4 figures, 3 tables

Published
2023

11. Trace metal-protein interactions in plasma of relevance to health and immune functioning

Author

Wu, Dongmei, Stewart, Alan J., and Powis, Simon John

Subjects
Metal-albumin interactions, Albumin, Cobalt, Zinc, Copper, Cadmium, TG2, Metal homeostasis, QP99.3A4W8
Abstract

Trace metal ions play many critical roles in biological functions in humans. Plasma proteins such as human serum albumin (HSA) are primarily responsible for the circulatory transport of metal ions and as such are relevant to health and immune functioning. To further understand the biological processes and some diseases associated with defective homeostasis of metal ions (including Co²⁺, Zn²⁺, Cd²⁺ and Cu²⁺), a deeper understanding of the properties of protein-metal ion interactions is required. On HSA, three metal-binding sites involving in binding to these metal ions are known, including sites A (His67 site), B (His9 site) and the N-terminal site (His3 site), which play different roles in binding different metal ions. Additionally, metal ion states are of clinical importance in immune system. Among these metal ions, defective homeostasis of Cu²⁺ has been proposed to be related to the development of celiac disease (CD), by regulating tissue transglutaminase (TG2) activity in extracellular environment. Thus, the aims of this project are to elucidate properties of metal ion-HSA interactions and investigate potential role for Cu²⁺ in TG2 activity regulation. Employing site-directed mutagenesis, isothermal titration calorimetry (ITC) and circular dichroism (CD), the results presented here indicate that Co²⁺ preferentially binds to HSA at site B, followed by site A and subsequentially binds to multiple weak-affinity sites. Additionally, the presence of 5 molar equivalents of palmitate can trigger structural changes and diminish Co²⁺ binding to sites A and B of HSA. An investigation of Zn²⁺ binding using mutagenesis and ITC revealed that this ion preferentially binds to site A, followed by site B, which is in firm agreement with previous data. In addition, Zn²⁺ binding to site A was dramatically reduced by addition of 5 molar equivalents of palmitate. ITC results in combination with ¹¹¹Cd-NMR spectroscopy suggest sites B and A are the two major binding sites participating in Cd²⁺ binding to HSA. Additionally, the results confirm that His9 is the indispensable histidine residue contributing to site B. Intriguingly, inspection of these data reveals that binding modes of different metal ions in different metal-binding sites (especially in site A) vary substantially. Both His67 and His247 participate in the "intact" site A in Zn²⁺ binding; however, His247 may play a less important role than His67 in Co²⁺ and Cd²⁺ binding to site A. Regarding to Cu²⁺ binding to HSA, it primarily binds to the N-terminal site and secondly binds to site A, supported by the results from ITC and EPR spectroscopy. Compellingly, the data presented here also demonstrate that Cu²⁺ is a potent inhibitor of TG2, providing an insight into deeper understanding of the development of CD. Collectively, these data provide a more comprehensive understanding of the properties of Co²⁺, Zn²⁺, Cd²⁺ and Cu²⁺ interactions with HSA and their interplay with fatty acids, contributing to more accurate insights into metal ion distribution and speciation mediated by HSA and their implications in health.

Published
2023
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12. Factors related to diabetes distress among adolescent patients with type 1 diabetes： a Meta-analysis

Author

Lu Xuanyi, Feng Lanling, and Wu Dongmei

Subjects
adolescents, type 1 diabetes, diabetes distress, meta-analysis, Psychology, BF1-990, Psychiatry, RC435-571
Abstract

BackgroundDiabetes distress is highly prevalent and has adverse impacts in adolescent patients with type 1 diabetes. However， the related factors of diabetes distress in adolescents with type 1 diabetes are not clear.ObjectiveTo identify the factors associated with diabetes distress in adolescents with type 1 diabetes using Meta-analysis， and to provide a scientific evidence for effective prevention and improvement of diabetes distress in adolescents with type 1 diabetes.MethodsOn December 1， 2022， a computerized search was conducted on databases including PubMed， Cochrane Library， Web of Science， Embase， CNKI， Wanfang Data， VIP and China Biomedical Literature Database， and studies relevant to diabetes distress in adolescents with type 1 diabetes were systematically included. Quality assessment of cross-sectional and cohort studies was carried out using criteria defined by the Agency for Healthcare Research and Quality （AHRQ） and Newcastle-Ottawa Scale （NOS）. Then the included studies were pooled in a Meta-analysis using Revman 5.3.ResultsA total of 22 studies were included， involving 6 442 adolescents with type 1 diabetes. Meta-analysis denoted that the occurrence of diabetes distress among adolescents with type 1 diabetes was correlated with age （r=0.094，95% CI： 0.042~0.145）， HbA1c （r=0.291， 95% CI： 0.248~0.335）， trait anxiety （r=0.585， 95% CI： 0.526~0.639）， depressive symptoms （r=0.635， 95% CI： 0.590~0.676）， resilience （r=-0.410， 95% CI： -0.528~-0.276） and parents' diabetes distress （r=0.462， 95% CI： 0.421~0.501）.ConclusionFactors including age， HbA1c， trait anxiety， depressive symptoms， resilience and parents' diabetes distress are correlated with diabetes distress in adolescents with type 1 diabetes. ［Funded by Sichuan Science and Technology Program （number， 24KJPX0034）］

Published
2024
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