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Book ; Online: Recent Advances in Swarm Intelligence Algorithms and Their Applications

Dong, Jian

2023

Keywords	Information technology industries ; Computer science ; preference incorporation ; ant colony optimisation ; grey wolf optimisation ; interval outranking ; multi-criteria decision analysis ; swarm intelligence algorithms ; piecewise linearization ; optimization ; parameter tuning ; approximation ; experimental comparison ; graph convolutional network ; relation extraction ; machine learning ; natural language processing ; metaheuristic algorithms ; Whale Optimization Algorithm ; HBA ; radial distribution systems ; power loss ; sensitivity analysis ; DG optimal allocation ; voltage deviation ; capacitor banks ; electricity market ; optimal bidding ; Harris Hawk Optimization ; multi layered neural network ; bi-level optimization ; strategic bidding ; ground-penetrating radar (GPR) ; cavity morphology recognition ; few-shot learning (FSL) ; deep learning (DL) ; relation network (RelationNet) ; unmanned aerial vehicle swarm ; antenna array ; near-field beamforming ; array element position error compensation ; spatial area division ; economic load dispatch ; pigeon-inspired optimizer ; oppositional-based learning ; swarm intelligence algorithm ; oppositional-based pigeon-inspired optimizer ; tunicate swarm algorithm ; chaotic mapping ; Lévy flight strategy ; benchmark test functions ; engineering design problems ; meta-heuristic ; large-scale agents ; attack and defense ; multi-population mean-field game ; high-dimensional solution space ; neural networks ; bat algorithm ; hybrid strategy ; energy harvesting ; NOMA ; cognitive relay network ; multimodal optimization ; multiple optima ; partition-based random search ; niching ; global optimization problems ; moth-flame optimization ; premature convergence ; population diversity ; grey wolf optimization ; swarm intelligence ; real world application ; spiking neural P system ; AEC system ; LMS ; neuromorphic architecture ; FPGA ; Harris hawks optimization ; elite opposition-based learning ; Sobol sequence ; nonlinear weight ; Gaussian walk learning ; particle swarm optimization algorithm ; dynamic vibration absorber ; Maxwell-type ; inerter ; negative stiffness ; chaotic-based PPE algorithm ; meta-heuristic algorithm ; chaotic maps ; Mahjong ; differential evolution ; deficiency number ; combinatorial optimization ; reinforcement learning ; multi-agent reinforcement learning ; self play ; population play ; n/a
Language	English
Size	1 electronic resource (494 pages)
Publisher	MDPI - Multidisciplinary Digital Publishing Institute
Publishing place	Basel
Document type	Book ; Online
Note	English
HBZ-ID	HT030381792
ISBN	9783036582559 ; 303658255X
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Robust Data-Driven Iterative Learning Control for Linear-Time-Invariant and Hammerstein-Wiener Systems.

Dong, Jianfei

IEEE transactions on cybernetics

2023 Volume 53, Issue 2, Page(s) 1144–1157

Abstract: Iterative learning control (ILC) relies on a finite-time interval output predictor to determine the output trajectory in each trial. Robust ILCs intend to model the uncertainties in the predictor and to guarantee the convergence of the learning process ... ...

Abstract	Iterative learning control (ILC) relies on a finite-time interval output predictor to determine the output trajectory in each trial. Robust ILCs intend to model the uncertainties in the predictor and to guarantee the convergence of the learning process subject to such model errors. Despite the vast literature in ILCs, parameterizing the uncertainties with the stochastic errors in the predictor parameters identified from system I/O data and thus robustifying the ILC have not yet been targeted. This work is devoted to solving such problems in a data-driven fashion. The main contributions are two-fold. First, a data-driven ILC method is developed for LTI systems. The relationship is established between the errors in the predictor matrix and the stochastic disturbances to the system. Its robust monotonic convergence (RMC) is then linked with the closed-loop learning gain matrix that contains the predictor uncertainties and is analyzed based on a closed-form expectation of this gain matrix multiplied with its own transpose, that is, in a mean-square sense (MS-RMC). Second, the data-driven ILC and MS-RMC analysis are extended to nonlinear Hammerstein-Wiener (H-W) systems. The advantages of the proposed methods are finally verified via extensive simulations in terms of their convergence and uncorrelated tracking performance with the stochastic parametric uncertainties.
Language	English
Publishing date	2023-01-13
Publishing country	United States
Document type	Journal Article
ISSN	2168-2275
ISSN (online)	2168-2275
DOI	10.1109/TCYB.2021.3105745
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Analysis of Emotional Stress of Teachers in Japanese Teaching Process Based on EEG Signal Analysis.

Dong, Jie

Occupational therapy international

2022 Volume 2022, Page(s) 2593338

Abstract: The construction direction of Japanese teaching evaluation system based on hybrid teaching mode is to give full feedback to teaching process, diversify evaluation subjects and evaluation methods, and obtain comprehensive and objective evaluation results. ...

Abstract	The construction direction of Japanese teaching evaluation system based on hybrid teaching mode is to give full feedback to teaching process, diversify evaluation subjects and evaluation methods, and obtain comprehensive and objective evaluation results. Compared with most similar studies, more EEG data of teachers' emotional stress relief and healthy people in Japanese teaching process were collected, and a large number of features were extracted. An experiment of teachers' emotional stress relief recognition in Japanese teaching process based on EEG signal was designed. The feature selection algorithm was used to screen the EEG feature combinations of teachers' emotional stress relief and healthy subjects, and the classification experiment was carried out to verify the difference. Finally, this paper uses the feature selection algorithm of tree model and the random forest model classifier to establish the recognition model of teachers' emotional stress discharge in Japanese teaching process based on EEG signals and achieves the effect of more accurate recognition of teachers' emotional stress discharge in Japanese teaching process. First, the connotation, value, and influencing factors of teachers' emotion management ability are logically integrated and systematically expounded. Second, based on emotional psychology, emotional intelligence theory, psychotherapy theory, and management theory, teachers' emotional management ability is constructed according to the three-dimensional structure theory of intelligence and information processing theory. It is constructed from three dimensions: object dimension (teachers themselves, students, and students), content dimension (positive and negative emotions), and operational dimension (emotional perception, emotional understanding, emotional expression, and emotional regulation).
MeSH term(s)	Electroencephalography ; Humans ; Japan ; Occupational Therapy ; Psychological Distress ; School Teachers/psychology
Language	English
Publishing date	2022-06-29
Publishing country	England
Document type	Journal Article
ZDB-ID	2095334-3
ISSN	1557-0703 ; 0966-7903
ISSN (online)	1557-0703
ISSN	0966-7903
DOI	10.1155/2022/2593338
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: What Risk Factors to Cause Long COVID and Its Impact on Patient Survival Outcomes when Combined with the Effect from Organ Transplantation in the Acute COVID

Dong, Jianghu

2023

Abstract: Coronavirus disease 2019 in solid organ transplant (SOT) patients is associated with more severe outcomes than non-immunosuppressed hosts. However, exactly which risk factors cause Long COVID in acute COVID cases remains unknown. More importantly, the ... ...

Abstract	Coronavirus disease 2019 in solid organ transplant (SOT) patients is associated with more severe outcomes than non-immunosuppressed hosts. However, exactly which risk factors cause Long COVID in acute COVID cases remains unknown. More importantly, the impact of Long COVID on patient survival remains understudied, especially when examined alongside the effect of SOT. All patients have been identified with acute COVID in the National COVID Collaborative Cohort registry. We compared patient demographics in Long COVID vs. those without Long COVID based on descriptive statistics. Multivariable logistics regressions were used to determine the factors related to the likelihood of developing Long COVID from a case of acute COVID. Multi-variables Cox regression was used to determine the time-to-event outcome of patient survival with Long COVID. This study reviewed data from a cohort of 6,416,500 acute COVID patients. Of that group, 31,744 patients developed Long COVID from ICD diagnosis. The mean (q1, q3) age was 39 (22, 57) years old, and 55% of patients were female. From this cohort, a total of 31,744 (1%) developed Long COVID and 43,565 (1%) had SOT, with a total of 698 SOT patients identified with Long COVID. Mean age of those with Long COVID was 52 (39, 64) years old and 64% of patients were female. Most of the SOT patients were kidney transplant recipients. From the Cox regression analysis of patient survival, there were many significant factors related to patient survival, with elderly SOT patients having a much higher hazard ratio of 27.8 (26.3, 29.4). This study has identified the important risk factors that are more likely to cause Long COVID in an acute COVID cohort. We investigated hazard ratios of patient survival based on multivariable Cox models, which found that Long COVID had a more direct impact on survival in elderly patients and those with SOT.
Keywords	Statistics - Applications
Subject code	616 ; 610
Publishing date	2023-05-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Human bone marrow-resident and blood-circulating memory T lymphocytes.

Dong, J

Zeitschrift fur Rheumatologie

2018 Volume 77, Issue 5, Page(s) 409–411

Title translation	Gedächtnis-T-Lymphozyten im menschlichen Knochenmark und Blutkreislauf.
MeSH term(s)	Bone Marrow ; Bone Marrow Cells ; Humans ; Immunologic Memory ; T-Lymphocytes
Language	English
Publishing date	2018-05-18
Publishing country	Germany
Document type	Journal Article
ZDB-ID	124985-x
ISSN	1435-1250 ; 0340-1855 ; 0301-6382
ISSN (online)	1435-1250
ISSN	0340-1855 ; 0301-6382
DOI	10.1007/s00393-018-0485-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Uh III Zs.128: Show issues

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Article: LncRNAs: the missing link to senescence nuclear architecture.

Han, Jing-Dong J

Trends in biochemical sciences

2023 Volume 48, Issue 7, Page(s) 618–628

Abstract: During cellular senescence and organismal aging, cells display various molecular and morphological changes. Although many aging-related long noncoding RNAs (lncRNAs) are highly associated with senescence-associated secretory phenotype, the roles of ... ...

Abstract	During cellular senescence and organismal aging, cells display various molecular and morphological changes. Although many aging-related long noncoding RNAs (lncRNAs) are highly associated with senescence-associated secretory phenotype, the roles of lncRNAs in senescence-associated nuclear architecture and morphological changes are just starting to emerge. Here I review lncRNAs associated with nuclear structure establishment and maintenance, their aging-related changes, and then focus on the pervasive, yet underappreciated, role of RNA double-strand DNA triplexes for lncRNAs to recognize targeted genomic regions, making lncRNAs the nexus between DNA and proteins to regulate nuclear structural changes. Finally, I discuss the future of deciphering direct links of lncRNA changes to various nuclear morphology changes assisted by artificial intelligence and genetic perturbations.
MeSH term(s)	RNA, Long Noncoding/genetics ; RNA, Long Noncoding/metabolism ; Artificial Intelligence ; Cell Nucleus/metabolism ; DNA/genetics ; Cellular Senescence/genetics
Chemical Substances	RNA, Long Noncoding ; DNA (9007-49-2)
Language	English
Publishing date	2023-04-15
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	194216-5
ISSN	1362-4326 ; 0968-0004 ; 0376-5067
ISSN (online)	1362-4326
ISSN	0968-0004 ; 0376-5067
DOI	10.1016/j.tibs.2023.03.007
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Zs.A 1207: Show issues

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Article ; Online: The ticking of aging clocks.

Han, Jing-Dong J

Trends in endocrinology and metabolism: TEM

2023 Volume 35, Issue 1, Page(s) 11–22

Abstract: Computational models that measure biological age and aging rate regardless of chronological age are called aging clocks. The underlying counting mechanisms of the intrinsic timers of these clocks are still unclear. Molecular mediators and determinants of ...

Abstract	Computational models that measure biological age and aging rate regardless of chronological age are called aging clocks. The underlying counting mechanisms of the intrinsic timers of these clocks are still unclear. Molecular mediators and determinants of aging rate point to the key roles of DNA damage, epigenetic drift, and inflammation. Persistent DNA damage leads to cellular senescence and the senescence-associated secretory phenotype (SASP), which induces cytotoxic immune cell infiltration; this further induces DNA damage through reactive oxygen and nitrogen species (RONS). I discuss the possibility that DNA damage (or the response to it, including epigenetic changes) is the fundamental counting unit of cell cycles and cellular senescence, that ultimately accounts for cell composition changes and functional decline in tissues, as well as the key intervention points.
MeSH term(s)	Humans ; Aging/genetics ; Cellular Senescence/genetics ; DNA Damage/genetics ; Reactive Oxygen Species
Chemical Substances	Reactive Oxygen Species
Language	English
Publishing date	2023-10-23
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	1042384-9
ISSN	1879-3061 ; 1043-2760
ISSN (online)	1879-3061
ISSN	1043-2760
DOI	10.1016/j.tem.2023.09.007
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 2999: Show issues

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Article ; Online: Intelligent medicine, the wings of global health.

Dong, Jiahong

Intelligent medicine

2021 Volume 1, Issue 1, Page(s) 1–2

Language	English
Publishing date	2021-06-12
Publishing country	China
Document type	Editorial
ISSN	2667-1026
ISSN (online)	2667-1026
DOI	10.1016/j.imed.2021.06.001
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Effects of Comprehensive Noise Reduction Management Combined with Reality Therapy on Anxiety and Depression in Hospitalised Patients with Breast Cancer.

Dong, Jie / Guo, Juan

Noise & health

2024 Volume 25, Issue 119, Page(s) 211–219

Abstract: Objective: This study was conducted to explore the effects of comprehensive noise reduction management combined with reality therapy on anxiety and depression in hospitalised patients with breast cancer.: Methods: The medical records of 166 ... ...

Abstract	Objective: This study was conducted to explore the effects of comprehensive noise reduction management combined with reality therapy on anxiety and depression in hospitalised patients with breast cancer. Methods: The medical records of 166 inpatients with breast cancer in Tongji Hospital affiliated with Tongji Medical College of Huazhong University of Science and Technology from March 2020 to March 2022 were retrospectively analysed. According to different intervention methods, these patients were divided into group A (n = 58, receiving conventional intervention), group B (n = 55, receiving conventional intervention combined with reality therapy) and group C (n = 53, receiving conventional intervention combined with comprehensive noise reduction management and reality therapy intervention). Patients' anxiety and depression, quality of life and satisfaction degree in the three groups were compared. Results: Before the intervention, the scores of the Hospital Anxiety and Depression Scale (HADS) and Short-From-36 Health Survey (SF-36) scale did not significantly differ amongst the three groups (P > 0.05). After the intervention, we observed a difference in the pairwise comparison of HADS scores amongst the three groups, in which group C had the lowest score and group A had the highest HADS score (P < 0.001). We also noted a difference in the pairwise comparison of SF-36 scores amongst the three groups, in which group C had the highest SF-36 score and group A had the lowest SF-36 score (P < 0.001). The pairwise comparison of satisfaction revealed a difference amongst the three groups, in which group C had the highest satisfaction (92.45%, 94.34% and 94.34%), and group A had the lowest satisfaction (74.14%, 74.14% and 75.86%; P < 0.05). Conclusion: Comprehensive noise reduction management combined with reality therapy can effectively relieve the negative emotions of inpatients with breast cancer, as well as improve their survival state of patients. It is suggested that it be included in the clinical intervention system for breast cancer.
MeSH term(s)	Humans ; Female ; Breast Neoplasms/complications ; Breast Neoplasms/therapy ; Breast Neoplasms/psychology ; Depression/etiology ; Depression/therapy ; Depression/psychology ; Quality of Life ; Reality Therapy ; Retrospective Studies ; Anxiety/etiology ; Anxiety/therapy ; Anxiety/psychology
Language	English
Publishing date	2024-02-12
Publishing country	India
Document type	Journal Article
ZDB-ID	1482372-x
ISSN	1998-4030 ; 1463-1741
ISSN (online)	1998-4030
ISSN	1463-1741
DOI	10.4103/nah.nah_37_23
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Article ; Online: MAEF-Net: MLP Attention for Feature Enhancement in U-Net based Medical Image Segmentation Networks.

Zhang, Yunchu / Dong, Jianfei

IEEE journal of biomedical and health informatics

2024 Volume 28, Issue 2, Page(s) 846–857

Abstract: Medical image segmentation plays an important role in diagnosis. Since the introduction of U-Net, numerous advancements have been implemented to enhance its performance and expand its applicability. The advent of Transformers in computer vision has led ... ...

Abstract	Medical image segmentation plays an important role in diagnosis. Since the introduction of U-Net, numerous advancements have been implemented to enhance its performance and expand its applicability. The advent of Transformers in computer vision has led to the integration of self-attention mechanisms into U-Net, resulting in significant breakthroughs. However, the inherent complexity of Transformers renders these networks computationally demanding and parameter-heavy. Recent studies have demonstrated that multilayer perceptrons (MLPs), with their simpler architecture, can achieve comparable performance to Transformers in natural language processing and computer vision tasks. Building upon these findings, we have enhanced the previously proposed "Enhanced-Feature-Four-Fold-Net" (EF
MeSH term(s)	Humans ; Electric Power Supplies ; Natural Language Processing ; Neural Networks, Computer ; Image Processing, Computer-Assisted
Language	English
Publishing date	2024-02-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	2695320-1
ISSN	2168-2208 ; 2168-2194
ISSN (online)	2168-2208
ISSN	2168-2194
DOI	10.1109/JBHI.2023.3332908
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