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Article ; Online: Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model

Gaining Han / Zongsheng Wu / Wei Zhang / Wei Wang

Computational Intelligence and Neuroscience, Vol

2022 Volume 2022

Abstract: The interactive motion planning between unmanned vehicles and pedestrians in urban road environments is the key to realizing the autonomous motion of unmanned vehicles in hybrid traffic scenarios. The problem of human-vehicle interaction motion planning ... ...

Abstract	The interactive motion planning between unmanned vehicles and pedestrians in urban road environments is the key to realizing the autonomous motion of unmanned vehicles in hybrid traffic scenarios. The problem of human-vehicle interaction motion planning modeling at complex intersections is studied for an unmanned vehicle in this article. First, the motion planning of pedestrians and the unmanned vehicles is established according to the social force model and the behavioral dynamics model. Then, the autonomous vehicle is added to the crowd, and the human-vehicle interaction force is established. The virtual force is added to the social force model and the behavioral dynamics model, respectively, and the improved social force model and the behavioral dynamics model are used for the motion planning of pedestrians and unmanned vehicles. In this way, the established model solves the problems of simple pedestrian interaction motion planning in the social force model and single-body motion planning in the behavioral dynamics and thus provides a strong support for multibody motion planning. Finally, through the interactive motion planning trajectory of pedestrians and unmanned vehicles in different scenes, the vehicle and pedestrian motion planning trajectory can effectively avoid overlapping or crossing, so as to avoid the collision, which verifies the effectiveness and feasibility of the proposed model.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571
Subject code	629
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model.

Han, Gaining / Wu, Zongsheng / Zhang, Wei / Wang, Wei

Computational intelligence and neuroscience

2022 Volume 2022, Page(s) 3154532

Abstract	The interactive motion planning between unmanned vehicles and pedestrians in urban road environments is the key to realizing the autonomous motion of unmanned vehicles in hybrid traffic scenarios. The problem of human-vehicle interaction motion planning modeling at complex intersections is studied for an unmanned vehicle in this article. First, the motion planning of pedestrians and the unmanned vehicles is established according to the social force model and the behavioral dynamics model. Then, the autonomous vehicle is added to the crowd, and the human-vehicle interaction force is established. The virtual force is added to the social force model and the behavioral dynamics model, respectively, and the improved social force model and the behavioral dynamics model are used for the motion planning of pedestrians and unmanned vehicles. In this way, the established model solves the problems of simple pedestrian interaction motion planning in the social force model and single-body motion planning in the behavioral dynamics and thus provides a strong support for multibody motion planning. Finally, through the interactive motion planning trajectory of pedestrians and unmanned vehicles in different scenes, the vehicle and pedestrian motion planning trajectory can effectively avoid overlapping or crossing, so as to avoid the collision, which verifies the effectiveness and feasibility of the proposed model.
MeSH term(s)	Humans ; Accidents, Traffic/prevention & control ; Safety ; Pedestrians ; Walking
Language	English
Publishing date	2022-10-28
Publishing country	United States
Document type	Journal Article
ZDB-ID	2388208-6
ISSN	1687-5273 ; 1687-5273
ISSN (online)	1687-5273
ISSN	1687-5273
DOI	10.1155/2022/3154532
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Article ; Online: Knowledge graph analysis and visualization of AI technology applied in COVID-19

Wu, Zongsheng / Xue, Ru / Shao, Meiyun

Environ Sci Pollut Res. 2022 Apr., v. 29, no. 18 p.26396-26408

2022

Abstract: With the global outbreak of coronavirus disease (COVID-19) all over the world, artificial intelligence (AI) technology is widely used in COVID-19 and has become a hot topic. In recent 2 years, the application of AI technology in COVID-19 has developed ... ...

Abstract	With the global outbreak of coronavirus disease (COVID-19) all over the world, artificial intelligence (AI) technology is widely used in COVID-19 and has become a hot topic. In recent 2 years, the application of AI technology in COVID-19 has developed rapidly, and more than 100 relevant papers are published every month. In this paper, we combined with the bibliometric and visual knowledge map analysis, used the WOS database as the sample data source, and applied VOSviewer and CiteSpace analysis tools to carry out multi-dimensional statistical analysis and visual analysis about 1903 pieces of literature of recent 2 years (by the end of July this year). The data is analyzed by several terms with the main annual article and citation count, major publication sources, institutions and countries, their contribution and collaboration, etc. Since last year, the research on the COVID-19 has sharply increased; especially the corresponding research fields combined with the AI technology are expanding, such as medicine, management, economics, and informatics. The China and USA are the most prolific countries in AI applied in COVID-19, which have made a significant contribution to AI applied in COVID-19, as the high-level international collaboration of countries and institutions is increasing and more impactful. Moreover, we widely studied the issues: detection, surveillance, risk prediction, therapeutic research, virus modeling, and analysis of COVID-19. Finally, we put forward perspective challenges and limits to the application of AI in the COVID-19 for researchers and practitioners to facilitate future research on AI applied in COVID-19.
Keywords	COVID-19 infection ; artificial intelligence ; databases ; economics ; medicine ; monitoring ; prediction ; risk ; statistical analysis ; therapeutics ; viruses ; China
Language	English
Dates of publication	2022-04
Size	p. 26396-26408.
Publishing place	Springer Berlin Heidelberg
Document type	Article ; Online
ZDB-ID	1178791-0
ISSN	1614-7499 ; 0944-1344
ISSN (online)	1614-7499
ISSN	0944-1344
DOI	10.1007/s11356-021-17800-z
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Enhancement of anaerobic digestion from food waste via inert substances based on metagenomic analysis: Oxidative phosphorylation and metabolism.

Jiang, Xiupeng / Li, Zongsheng / Lin, Kunsen / Zhao, Youcai / Su, Lianghu / Wu, Tong / Zhou, Tao

Environmental research

2023 Volume 246, Page(s) 118033

Abstract: The application of anaerobic digestion (AD) in the treatment of food waste (FW) has become widespread. However, the presence of inert substances, such as bones, ceramics, and shells, within FW introduces a degree of uncertainty into the AD process. To ... ...

Abstract	The application of anaerobic digestion (AD) in the treatment of food waste (FW) has become widespread. However, the presence of inert substances, such as bones, ceramics, and shells, within FW introduces a degree of uncertainty into the AD process. To clarify this intricate issue, this study conducted an in-depth investigation into the influence of inert substances on AD. The results revealed that when inert substances were present at a concentration of 0.08 g/g VSS, methane productivity in the AD process was significantly augmented by 86%. Subsequent investigations suggested that this positive effect was primarily evident in various biochemical processes, including solubilization, hydrolysis acidification, methanogenesis, and the accumulation of extracellular polymeric substances. Metagenomic analysis showed that inert substances enhance the relative abundance of hydrolytic bacteria and have a pronounced impact on the relative abundance of hydrogenotrophic methanogens (Methanosarcina) and acetotrophic methanogens (Methanobacterium). Additionally, inert substances significantly increased the relative abundance of functional genes in oxidative phosphorylation, a pivotal pathway for ATP synthesis. Furthermore, inert substances had a substantial effect on the functional genes related to the metabolic pathways associated with methanogenesis (both hydrogenotrophic and acetotrophic). This comprehensive study shed light on the substantial impact of inert substances on the AD of food waste, contributing to an enhanced understanding of the underlying mechanisms of anaerobic fermentation.
MeSH term(s)	Anaerobiosis ; Food Loss and Waste ; Bioreactors ; Oxidative Phosphorylation ; Food ; Refuse Disposal ; Methane ; Sewage/microbiology
Chemical Substances	Food Loss and Waste ; Methane (OP0UW79H66) ; Sewage
Language	English
Publishing date	2023-12-28
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2023.118033
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Article ; Online: A Cyclical Non-Linear Inertia-Weighted Teaching–Learning-Based Optimization Algorithm

Zongsheng Wu / Ru Xue

Algorithms, Vol 12, Iss 5, p

2019 Volume 94

Abstract: After the teaching−learning-based optimization (TLBO) algorithm was proposed, many improved algorithms have been presented in recent years, which simulate the teaching−learning phenomenon of a classroom to effectively solve global optimization problems. ... ...

Abstract	After the teaching−learning-based optimization (TLBO) algorithm was proposed, many improved algorithms have been presented in recent years, which simulate the teaching−learning phenomenon of a classroom to effectively solve global optimization problems. In this paper, a cyclical non-linear inertia-weighted teaching−learning-based optimization (CNIWTLBO) algorithm is presented. This algorithm introduces a cyclical non-linear inertia weighted factor into the basic TLBO to control the memory rate of learners, and uses a non-linear mutation factor to control the learner’s mutation randomly during the learning process. In order to prove the significant performance of the proposed algorithm, it is tested on some classical benchmark functions and the comparison results are provided against the basic TLBO, some variants of TLBO and some other well-known optimization algorithms. The experimental results show that the proposed algorithm has better global search ability and higher search accuracy than the basic TLBO, some variants of TLBO and some other algorithms as well, and can escape from the local minimum easily, while keeping a faster convergence rate.
Keywords	optimization ; teaching–learning-based optimization (TLBO) ; global optimization ; swarm intelligent optimization ; Industrial engineering. Management engineering ; T55.4-60.8 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	006
Language	English
Publishing date	2019-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Knowledge graph analysis and visualization of AI technology applied in COVID-19.

Wu, Zongsheng / Xue, Ru / Shao, Meiyun

Environmental science and pollution research international

2021 Volume 29, Issue 18, Page(s) 26396–26408

Abstract	With the global outbreak of coronavirus disease (COVID-19) all over the world, artificial intelligence (AI) technology is widely used in COVID-19 and has become a hot topic. In recent 2 years, the application of AI technology in COVID-19 has developed rapidly, and more than 100 relevant papers are published every month. In this paper, we combined with the bibliometric and visual knowledge map analysis, used the WOS database as the sample data source, and applied VOSviewer and CiteSpace analysis tools to carry out multi-dimensional statistical analysis and visual analysis about 1903 pieces of literature of recent 2 years (by the end of July this year). The data is analyzed by several terms with the main annual article and citation count, major publication sources, institutions and countries, their contribution and collaboration, etc. Since last year, the research on the COVID-19 has sharply increased; especially the corresponding research fields combined with the AI technology are expanding, such as medicine, management, economics, and informatics. The China and USA are the most prolific countries in AI applied in COVID-19, which have made a significant contribution to AI applied in COVID-19, as the high-level international collaboration of countries and institutions is increasing and more impactful. Moreover, we widely studied the issues: detection, surveillance, risk prediction, therapeutic research, virus modeling, and analysis of COVID-19. Finally, we put forward perspective challenges and limits to the application of AI in the COVID-19 for researchers and practitioners to facilitate future research on AI applied in COVID-19.
MeSH term(s)	Artificial Intelligence ; COVID-19 ; Humans ; Pattern Recognition, Automated ; SARS-CoV-2 ; Technology
Language	English
Publishing date	2021-12-02
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1178791-0
ISSN	1614-7499 ; 0944-1344
ISSN (online)	1614-7499
ISSN	0944-1344
DOI	10.1007/s11356-021-17800-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: CIRP increases Foxp3

Wu, Zongsheng / Liu, Xu / Huang, Wei / Chen, Jing / Li, Songli / Chao, Jie / Xie, Jianfeng / Liu, Ling / Yang, Yi / Wu, Xiaojing / Qiu, Haibo

International immunopharmacology

2024 Volume 132, Page(s) 111924

Abstract: Background: T helper (Th) cell imbalances have been associated with the pathophysiology of sepsis, including the Th1/Th2 and Th17/T regulatory cells (Treg) paradigms. Cold-inducible RNA-binding protein (CIRP), a novel damage-associated molecular pattern ...

Abstract	Background: T helper (Th) cell imbalances have been associated with the pathophysiology of sepsis, including the Th1/Th2 and Th17/T regulatory cells (Treg) paradigms. Cold-inducible RNA-binding protein (CIRP), a novel damage-associated molecular pattern (DAMP) was reported that could induce T cell activation, and skew CD4 Methods: A prospective exploratory study including patients with sepsis was conducted. Blood samples were collected from patients on days 0, 3 and 7 on admission. The serum CIRP and peripheral blood Treg/Th17 percentage was determined by ELISA and flow cytometry. CD4 Results: A total of 19 patients with sepsis finally completed the study. Serum CIRP levels remained high in the majority of patients up to 1 week after admittance was closely associated with high Treg/Th17 ratio of peripheral blood and poor outcome. A univariate logistic analysis demonstrated that higher CIRP concentration at Day 7 is an independent risk factor for Treg/Th17 ratio increasing. CIRP promotes Treg development and suppresses Th17 differentiation was found both in vivo and in vitro. Pretreated with C23 not only alleviated the majority of negative effect of CIRP on Th17 differentiation, but also inhibited Treg differentiation, to some extent. Tlr4 deficiency could abolish almost all downstream effects of rmCIRP. Furthermore, IL-2 is proved a key downstream molecules of the effect CIRP, which also could amplify the activated CD4 Conclusions: Persistent high circulating CIRP level may lead to Treg/Th17 ratio elevated through TLR4 and subsequent active IL-2 signaling which contribute to immunosuppression during late phases of sepsis.
Language	English
Publishing date	2024-03-25
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2043785-7
ISSN	1878-1705 ; 1567-5769
ISSN (online)	1878-1705
ISSN	1567-5769
DOI	10.1016/j.intimp.2024.111924
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Correction: Overexpressing TGF-β1 in mesenchymal stem cells attenuates organ dysfunction during CLP-induced septic mice by reducing macrophage-driven.

Liu, Feng / Xie, Jianfeng / Zhang, Xiwen / Wu, Zongsheng / Zhang, Shi / Xue, Ming / Chen, Jianxiao / Yang, Yi / Qiu, Haibo

Stem cell research & therapy

2022 Volume 13, Issue 1, Page(s) 362

Language	English
Publishing date	2022-07-27
Publishing country	England
Document type	Published Erratum
ZDB-ID	2548671-8
ISSN	1757-6512 ; 1757-6512
ISSN (online)	1757-6512
ISSN	1757-6512
DOI	10.1186/s13287-022-03078-6
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Article ; Online: Correction

Feng Liu / Jianfeng Xie / Xiwen Zhang / Zongsheng Wu / Shi Zhang / Ming Xue / Jianxiao Chen / Yi Yang / Haibo Qiu

Stem Cell Research & Therapy, Vol 13, Iss 1, Pp 1-

Overexpressing TGF-β1 in mesenchymal stem cells attenuates organ dysfunction during CLP-induced septic mice by reducing macrophage-driven

2022 Volume 2

Keywords	Medicine (General) ; R5-920 ; Biochemistry ; QD415-436
Language	English
Publishing date	2022-07-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Study on space diversity and influencing factors of Tunpu settlement in central Guizhou Province of China

Hongyi Ge / Zhitai Wang / Yu Bao / Zongsheng Huang / Xintong Chen / Bin Wu / Yunwei Qiao

Heritage Science, Vol 10, Iss 1, Pp 1-

2022 Volume 18

Abstract: Abstract The Tunpu settlements are the historical product of the co-evolution development of the unique geographical and cultural environment of Guizhou and the military defense policies of Ming Dynasty (1368–1644 AD), which created products such as the ... ...

Abstract	Abstract The Tunpu settlements are the historical product of the co-evolution development of the unique geographical and cultural environment of Guizhou and the military defense policies of Ming Dynasty (1368–1644 AD), which created products such as the station troops and station farms. In this study, taking 10 Tunpu settlements in central Guizhou as the research objects, the space diversity of the Tunpu settlement and its influencing factors were analyzed based on the theory and calculation method of plant community species diversity. The results showed that: (1) On the whole, the space α-diversities of the military Tunpu settlements and the commercial Tunpu settlements were relatively high, with strong spatial similarity, while the residential Tunpu settlements had a lower degree of space α-diversity and significant difference. The space α-diversity of different types of the Tunpu settlement presents a variety of changes from the core protected areas to coordinated control areas. (2) There was a significant correlation between the spatial network and spatial morphological indicators and space β-diversity among the Tunpu settlement, and the stepwise regression showed that spatial morphological indicators had a strong explanatory power for the space β-diversity among the Tunpu settlements. (3) The space diversities of the Tunpu settlements were affected by the multiple synergies of natural environment, policy support, social-economic factors and cultural customs. Among them, policy factors and cultural factors were the dominant factors in the space diversity characteristics of the Tunpu settlements. By analyzing the space diversity law and its driving factors of the Tunpu settlements, this study could provide an important scientific basis for the protection planning and management of traditional settlements.
Keywords	Space diversity ; Key factors ; Tunpu settlement ; Central Guizhou ; Fine Arts ; N ; Analytical chemistry ; QD71-142
Subject code	930
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	SpringerOpen
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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