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Book ; Online: Advances in Methane Production from Coal, Shale and Other Tight Rocks

Li, Yong / Cui, Fan / Xu, Chao

2022

Keywords	Technology: general issues ; History of engineering & technology ; gel-foam ; chitosan ; acrylic acid ; coal gangue ; InSAR monitoring ; carbon capture and storage ; feasibility assessment model ; low-field NMR ; coal ; free methane ; paramagnetic mineral ; submarine channel ; submarine fan ; source-to-sink ; gas reservoirs ; South China Sea ; Yinggehai Basin ; pore structure ; shale gas ; N2 adsorption experiment ; molecular simulation ; pore connectivity ; tight sandstone ; coal measure ; southern margin of Junggar basin ; diagenetic process ; reservoir quality control ; reservoir forming ; carbonate cavern reservoir application ; pre-stack inversion ; model ; grey correlation method ; multiple linear regression ; production evaluation ; main control factor ; estimated ultimate recovery ; coalbed methane (CBM) ; prestack seismic inversion ; brittle index ; gas-bearing property ; fractures ; complex fracture net ; formation of bedding ; Fuling area
Language	English
Size	1 electronic resource (188 pages)
Publisher	MDPI - Multidisciplinary Digital Publishing Institute
Publishing place	Basel
Document type	Book ; Online
Note	English
HBZ-ID	HT030380328
ISBN	9783036560045 ; 3036560041
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Book ; Online: Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis

Li, Yong / Xu, Xing / Zhang, Lin / Qin, Yechen / Lu, Yang

2023

Keywords	Technology: general issues ; History of engineering & technology ; energy consumption optimization ; torque distribution ; energy efficiency ; motor efficiency ; four in-wheel motor drive electric vehicle ; nonlinear model predictive control ; four-wheel drive ; acceleration slip regulation ; intervention and exit mechanisms ; autonomous driving ; planning algorithm ; variable Gaussian safety field ; reinforcement learning ; policy gradient ; x-by-wire vehicle ; trajectory tracking control ; model predictive control ; hierarchical control ; distributed drive electric vehicles ; additional roll moment ; decoupling control ; load transfer rate ; electronically controlled air suspension ; solenoid valve ; extended Kalman filter bank ; fault diagnosis ; fault-tolerant control ; distributed driving electric vehicles ; polynomial path planning ; torque allocation ; obstacle avoidance path tracking ; fuzzy neural network ; particle swarm algorithm ; PID control ; active suspension ; MATLAB/Simulink simulation ; suspension ; mechatronic inerter ; bridge network ; high-order impedance ; real vehicle test ; autonomous vehicle ; path tracking control ; non-singular fast terminal sliding mode control ; model reference control ; vehicle ; fractional-order electrical network ; structure-immittance approach ; optimal design ; multi-agent coordinated control system ; active collision avoidance ; blackboard model ; real-time ; electric vehicles ; regenerative braking ; energy recovery ; genetic algorithm ; braking stability ; seat suspension ; inerter ; mechatronic system ; permanent magnet synchronous machine (PMSM) ; position sensorless compound control ; high frequency (HF) signal injection method ; I/F control ; model-based techniques ; n/a
Language	English
Size	1 electronic resource (268 pages)
Publisher	MDPI - Multidisciplinary Digital Publishing Institute
Publishing place	Basel
Document type	Book ; Online
Note	English
HBZ-ID	HT030381937
ISBN	9783036580579 ; 3036580573
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: A Dynamic Monitoring Method of Public Opinion Risk of Overseas Direct Investment-Based on Multifractal Situation Optimization.

Li, Yong

Entropy (Basel, Switzerland)

2023 Volume 25, Issue 11

Abstract: The negative public opinions and views on overseas direct investment (ODI) of a multinational enterprise (MNE) will damage the image of its brand and are likely to bring it serious economic and social losses. So, it is important for the MNE to understand ...

Abstract	The negative public opinions and views on overseas direct investment (ODI) of a multinational enterprise (MNE) will damage the image of its brand and are likely to bring it serious economic and social losses. So, it is important for the MNE to understand the formation and spread mechanism of public opinion risk (POR) in order to effectively respond to and guide the public opinion. This research proposed a multifractal-based situation optimization method to explore the POR evolution based on the media-based negative sentiment on China's ODI. The sentiment measurement is obtained by a directed crawler for gathering the text of media reports corresponding to a certain ODI event using a URL knowledge base from the GDELT Event Database. Taking the public opinion crisis of the tax evasion incident of the local arm of China's MNE in India as an example, the experiments show that this method could dynamically monitor the POR event in real-time and help MNE guide the effective control and benign evolution of public opinion of the event.
Language	English
Publishing date	2023-10-28
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2014734-X
ISSN	1099-4300 ; 1099-4300
ISSN (online)	1099-4300
ISSN	1099-4300
DOI	10.3390/e25111491
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Development and external validation of a diagnostic model for cardiometabolic-based chronic disease : results from the China health and retirement longitudinal study (CHARLS).

Li, Yong

BMC cardiovascular disorders

2023 Volume 23, Issue 1, Page(s) 417

Abstract: Background: Cardiovascular disease(CVD) is the leading cause of death in the world. Cardiometabolic-based chronic disease (CMBCD) model is presented that provides a basis for sustainable and early, evidence-based therapeutic targeting to mitigate the ... ...

Abstract	Background: Cardiovascular disease(CVD) is the leading cause of death in the world. Cardiometabolic-based chronic disease (CMBCD) model is presented that provides a basis for sustainable and early, evidence-based therapeutic targeting to mitigate the ravagest and development of CVD. CMBCD include dysglycemia, hypertension, and/or dyslipidemia progressing to downstream CVD events. Objectives: The objective of our research was to develop and externally validate a diagnostic model of CMBCD. Methods: Design: Multivariable logistic regression of a cohort for 9,463 participants aged at least 45 years were drawn from the 2018 wave of the China Health and Retirement Longitudinal Study (CHARLS). Setting: The 2018 wave of the CHARLS. Participants: Diagnostic model development: Totally 6,218 participants whose individual ID < 250,000,000,000. External validation: Totally 3,245 participants whose individual ID > 250,000,000,000. Outcomes: CMBCD . Results: CMBCD occurred in 25.5%(1,584/6,218)of individuals in the development data set and 26.2%(850 /3,245)of individuals in the validation data set. The strongest predictors of CMBCD were age, general health status, location of residential address, smoking, housework ability, pain, and exercise tolerance. We developed a diagnostic model of CMBCD. Discrimination was the ability of the diagnostic model to differentiate between people who with and without CMBCD. This measure was quantified by calculating the area under the receiver operating characteristic(ROC) curve(AUC).The AUC was 0.6199 ± 0.0083, 95% confidence interval(CI) = 0.60372 ~ 0.63612. We constructed a nomograms using the development database based on age, general health status, location of residential address, smoking, housework ability, pain, and exercise tolerance. The AUC was 0.6033 ± 0.0116, 95% CI = 0.58066 ~ 0.62603 in the validation data set. Conclusions: We developed and externally validated a diagnostic model of CMBCD. Discrimination, calibration, and decision curve analysis were satisfactory.
MeSH term(s)	Humans ; Longitudinal Studies ; Retirement ; Cardiovascular Diseases ; China/epidemiology ; Chronic Disease ; Pain
Language	English
Publishing date	2023-08-23
Publishing country	England
Document type	Journal Article
ZDB-ID	2059859-2
ISSN	1471-2261 ; 1471-2261
ISSN (online)	1471-2261
ISSN	1471-2261
DOI	10.1186/s12872-023-03418-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: [The path of translational medicine for neuroimmunological anti-inflammation and its enlightenment to acupuncture].

Li, Yong-Ming

Zhen ci yan jiu = Acupuncture research

2023 Volume 48, Issue 1, Page(s) 21–27

Abstract: Neuroimmunological anti-inflammation is one of the most successful areas of translational medicine in the past 50 years, leading directly to the success of anti-TNF biologics and vagal nerve stimulation therapy for anti-inflammation. The latter has many ... ...

Abstract	Neuroimmunological anti-inflammation is one of the most successful areas of translational medicine in the past 50 years, leading directly to the success of anti-TNF biologics and vagal nerve stimulation therapy for anti-inflammation. The latter has many similarities with traditional acupuncture therapy and further research may reveal more intertwining and enlightenment to acupuncture. This paper briefly reviews the discovery and translational process of Cachectin/TNF, anti-TNF therapy, neural inflammatory reflex arc, vagus nerve stimulation therapy, and Stimulating Peripheral Activity to Relieve Condition (SPARC) project, and also summarizes the experience and lessons learned from the path of translational medicine in this field. The two key steps in the translational process are discussed in details. The purpose is to provide reference for the development of translational medicine in acupuncture. "Minimal injury with significant healing" should be considered as the principal hypothesis to further study the biological mechanism of acupuncture and it may result in more clinical translation in the future.
MeSH term(s)	Translational Science, Biomedical ; Tumor Necrosis Factor Inhibitors ; Acupuncture Therapy ; Acupuncture ; Tumor Necrosis Factor-alpha ; Anti-Inflammatory Agents
Chemical Substances	Tumor Necrosis Factor Inhibitors ; Tumor Necrosis Factor-alpha ; Anti-Inflammatory Agents
Language	Chinese
Publishing date	2023-02-03
Publishing country	China
Document type	English Abstract ; Journal Article
ZDB-ID	1283179-7
ISSN	1000-0607
ISSN	1000-0607
DOI	10.13702/j.1000-0607.20221176
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Diagnostic Model of In-Hospital Mortality in Patients with Acute ST-Segment Elevation Myocardial Infarction Used Artificial Intelligence Methods.

Li, Yong

Cardiology research and practice

2022 Volume 2022, Page(s) 8758617

Abstract: Background: Preventing in-hospital mortality in patients with ST-segment elevation myocardial infarction (STEMI) is a crucial step.: Objectives: The objective of our research was to develop and externally validate the diagnostic model of in-hospital ... ...

Abstract	Background: Preventing in-hospital mortality in patients with ST-segment elevation myocardial infarction (STEMI) is a crucial step. Objectives: The objective of our research was to develop and externally validate the diagnostic model of in-hospital mortality in acute STEMI patients used artificial intelligence methods. Methods: We divided nonrandomly the American population with acute STEMI into a training set, a test set, and a validation set. We converted the unbalanced data into balanced data. We used artificial intelligence methods to develop and externally validate several diagnostic models. We used confusion matrix combined with the area under the receiver operating characteristic curve (AUC) to evaluate the pros and cons of the above models. Results: The strongest predictors of in-hospital mortality were age, gender, cardiogenic shock, atrial fibrillation (AF), ventricular fibrillation (VF), third degree atrioventricular block, in-hospital bleeding, underwent percutaneous coronary intervention (PCI) during hospitalization, underwent coronary artery bypass grafting (CABG) during hospitalization, hypertension history, diabetes history, and myocardial infarction history. The F2 score of logistic regression in the training set, the test set, and the validation dataset was 0.81, 0.6, and 0.59, respectively. The AUC of logistic regression in the training set, the test set, and the validation data set was 0.77, 0.78, and 0.8, respectively. The diagnostic model built by logistic regression was the best. Conclusion: The strongest predictors of in-hospital mortality were age, gender, cardiogenic shock, AF, VF, third degree atrioventricular block, in-hospital bleeding, underwent PCI during hospitalization, underwent CABG during hospitalization, hypertension history, diabetes history, and myocardial infarction history. We had used artificial intelligence methods developed and externally validated several diagnostic models of in-hospital mortality in acute STEMI patients. The diagnostic model built by logistic regression was the best. We registered this study with the registration number ChiCTR1900027129 (the WHO International Clinical Trials Registry Platform (ICTRP) on 1 November 2019).
Language	English
Publishing date	2022-05-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	2506187-2
ISSN	2090-0597 ; 2090-8016
ISSN (online)	2090-0597
ISSN	2090-8016
DOI	10.1155/2022/8758617
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Deep learning-based prediction of in-hospital mortality for sepsis

Li Yong / Liu Zhenzhou

Scientific Reports, Vol 14, Iss 1, Pp 1-

2024 Volume 8

Abstract: Abstract As a serious blood infection disease, sepsis is characterized by a high mortality risk and many complications. Accurate assessment of mortality risk of patients with sepsis can help physicians in Intensive Care Unit make optimal clinical ... ...

Abstract	Abstract As a serious blood infection disease, sepsis is characterized by a high mortality risk and many complications. Accurate assessment of mortality risk of patients with sepsis can help physicians in Intensive Care Unit make optimal clinical decisions, which in turn can effectively save patients’ lives. However, most of the current clinical models used for assessing mortality risk in sepsis patients are based on conventional indicators. Unfortunately, some of the conventional indicators have been shown to be inapplicable in the accurate clinical diagnosis nowadays. Meanwhile, traditional evaluation models only focus on a small amount of personal data, causing misdiagnosis of sepsis patients. We refine the core indicators for mortality risk assessment of sepsis from massive clinical electronic medical records with machine learning, and propose a new mortality risk assessment model, DGFSD, for sepsis patients based on deep learning. The DGFSD model can not only learn individual clinical information about unassessed patients, but also obtain information about the structure of the similarity graph between diagnosed patients and patients to be assessed. Numerous experiments have shown that the accuracy of the DGFSD model is superior to baseline methods, and can significantly improve the efficiency of clinical auxiliary diagnosis.
Keywords	Medicine ; R ; Science ; Q
Subject code	610 ; 310
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Song's Mast Cell Theory of Acupuncture.

Li, Yong Ming

Medical acupuncture

2022 Volume 34, Issue 5, Page(s) 316–324

Abstract: Professor. Jimei Song (1924-1987), from the Liaoning College of Traditional Medicine, first proposed the hypothesis that cutaneous mast cells (MCs) may be responsible for some of the phenomena associated with activation of meridians, acupoints, and De Qi ...

Abstract	Professor. Jimei Song (1924-1987), from the Liaoning College of Traditional Medicine, first proposed the hypothesis that cutaneous mast cells (MCs) may be responsible for some of the phenomena associated with activation of meridians, acupoints, and De Qi in acupuncture. This was in 1977 and she subsequently published the first investigative report on human subjects. Supported by hundreds of extensive research reports later on, now Song's Mast Cell Theory of Acupuncture is one of the leading theories in acupuncture research. As a scientist and mother, Professor Song belonged to a special generation of female professionals in China. These women were living in a very unique and challenging era. Called "half of the sky" or "bourgeoisie intellectuals," they faced unbearable difficulties in their lives and their work. The contribution of Professor Song to acupuncture is as significant as the contribution of Ms. Youyou Tu to Chinese herbal medicine. The difference is that Professor Song did not receive any award or significant recognition before she died in 1987. This review provides some background about her life, her contributions, and related publications, as well as a brief review of recent advances on MC mapping and acupuncture based on her MC theory.
Language	English
Publishing date	2022-10-17
Publishing country	United States
Document type	Journal Article
ZDB-ID	2296110-0
ISSN	1933-6594 ; 1933-6586
ISSN (online)	1933-6594
ISSN	1933-6586
DOI	10.1089/acu.2022.0035
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Diagnostic Model for In-Hospital Bleeding in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation.

Li, Yong

JMIR medical informatics

2020 Volume 8, Issue 8, Page(s) e20974

Abstract: Background: Bleeding complications in patients with acute ST-segment elevation myocardial infarction (STEMI) have been associated with increased risk of subsequent adverse consequences.: Objective: The objective of our study was to develop and ... ...

Abstract	Background: Bleeding complications in patients with acute ST-segment elevation myocardial infarction (STEMI) have been associated with increased risk of subsequent adverse consequences. Objective: The objective of our study was to develop and externally validate a diagnostic model of in-hospital bleeding. Methods: We performed multivariate logistic regression of a cohort for hospitalized patients with acute STEMI in the emergency department of a university hospital. Participants: The model development data set was obtained from 4262 hospitalized patients with acute STEMI from January 2002 to December 2013. A set of 6015 hospitalized patients with acute STEMI from January 2014 to August 2019 were used for external validation. We used logistic regression analysis to analyze the risk factors of in-hospital bleeding in the development data set. We developed a diagnostic model of in-hospital bleeding and constructed a nomogram. We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA). Results: In-hospital bleeding occurred in 112 of 4262 participants (2.6%) in the development data set. The strongest predictors of in-hospital bleeding were advanced age and high Killip classification. Logistic regression analysis showed differences between the groups with and without in-hospital bleeding in age (odds ratio [OR] 1.047, 95% CI 1.029-1.066; P<.001), Killip III (OR 3.265, 95% CI 2.008-5.31; P<.001), and Killip IV (OR 5.133, 95% CI 3.196-8.242; P<.001). We developed a diagnostic model of in-hospital bleeding. The area under the receiver operating characteristic curve (AUC) was 0.777 (SD 0.021, 95% CI 0.73576-0.81823). We constructed a nomogram based on age and Killip classification. In-hospital bleeding occurred in 117 of 6015 participants (1.9%) in the validation data set. The AUC was 0.7234 (SD 0.0252, 95% CI 0.67392-0.77289). Conclusions: We developed and externally validated a diagnostic model of in-hospital bleeding in patients with acute STEMI. The discrimination, calibration, and DCA of the model were found to be satisfactory. Trial registration: ChiCTR.org ChiCTR1900027578; http://www.chictr.org.cn/showprojen.aspx?proj=45926.
Language	English
Publishing date	2020-08-14
Publishing country	Canada
Document type	Journal Article
ZDB-ID	2798261-0
ISSN	2291-9694
ISSN	2291-9694
DOI	10.2196/20974
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Risk factors of in-hospital death in patients with acute ST elevation myocardial infarction.

Li, Yong

Internal and emergency medicine

2020 Volume 15, Issue 7, Page(s) 1335–1337

MeSH term(s)	Adult ; Aged ; Aged, 80 and over ; Cause of Death ; China/epidemiology ; Female ; Hospital Mortality ; Humans ; Middle Aged ; Risk Factors ; ST Elevation Myocardial Infarction/mortality
Language	English
Publishing date	2020-04-28
Publishing country	Italy
Document type	Letter
ZDB-ID	2454173-4
ISSN	1970-9366 ; 1828-0447
ISSN (online)	1970-9366
ISSN	1828-0447
DOI	10.1007/s11739-020-02338-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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