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Book ; Thesis: Under stress conditions HSP70 promotes cell proliferation and inhibits cell apoptosis through the interaction with eIF4G in hepatocellular carcinoma

Wang, Meng

2020

Author's details	vorgelegt von Meng Wang
Language	English
Size	vii, 87 Blätter, Illustrationen, Diagramme, 30 cm
Publishing place	Heidelberg
Publishing country	Germany
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Dissertation, Ruprecht-Karls-Universität Heidelberg, 2020
HBZ-ID	HT020912121
Database	Catalogue ZB MED Medicine, Health

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2021 E 573	order for loan	Magazin

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Article ; Online: The Spread, Rise, and Fall of University Students’ Interconnected Internet Public Opinion in the Age of Big Data

Meng Wang

Journal of Environmental and Public Health, Vol

2022 Volume 2022

Abstract: With the interconnected network’s quick growth and widespread adoption, it has only made sense that it would serve as a hub for the dissemination of ideologies and cultural information as well as an amplifier for public opinion. The world is dualistic. ... ...

Abstract	With the interconnected network’s quick growth and widespread adoption, it has only made sense that it would serve as a hub for the dissemination of ideologies and cultural information as well as an amplifier for public opinion. The world is dualistic. The popularity of the connected network has both positive and negative effects on society. It makes people’s lives more convenient, but it also has some drawbacks. Public opinion will quickly build up on the interconnected network as network communication becomes a significant method of disseminating social information, and the number of public opinion events on the interconnected network will also rise. Accurately understanding the law of higher education students’ online public opinion to effectively direct and utilise online public opinion to carry out ideological education for students and to realise the establishment of students' good values, mental health, and behavioural norms, it is necessary to understand how to spread and rise and fall in the era of big data work. The parameter inversion model of online public opinion is established in this article based on the aforementioned issues. The parameter inversion algorithm is used to calculate the trend value of online public opinion, and the degree of fitting between the trend value of actual data and the trend value of parameter inversion is compared. The study discovered that the experiment’s fitting value is as high as 90%. The model’s prediction of the overall trend of the event development is correct, indicating that the model parameters are inverted, even though the actual public opinion data are affected by a variety of random factors, so some deviations may occur at local points. The internal law of the evolution of events that spread public opinion has been discovered, and it can be used to accurately describe the evolution and development of the public opinion dissemination process as it is driven by its internal mechanism. In the age of big data, this article analyses and summarises the rise, fall, ...
Keywords	Public aspects of medicine ; RA1-1270
Subject code	020
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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Book ; Thesis: Hemodynamic changes and remote organ injury after mesentric ischemia in rats

Wang, Meng

2017

Institution	Universität Duisburg-Essen
Author's details	vorgelegt von Meng Wang
Language	English
Size	87 Blätter, Illustrationen, Diagramme
Publishing place	Duisburg ; Essen
Publishing country	Germany
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Dissertation, Universität Duisburg-Essen, 2017
HBZ-ID	HT019417217
Database	Catalogue ZB MED Medicine, Health

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2017 E 1707	order for loan	Magazin

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Article ; Online: Applying Internet information technology combined with deep learning to tourism collaborative recommendation system.

Meng Wang

PLoS ONE, Vol 15, Iss 12, p e

2020 Volume 0240656

Abstract: Recently, more personalized travel methods have emerged in the tourism industry, such as individual travel and self-guided travel. The service models of traditional tourism limit the diversity of service options and cannot fully meet the individual needs ...

Abstract	Recently, more personalized travel methods have emerged in the tourism industry, such as individual travel and self-guided travel. The service models of traditional tourism limit the diversity of service options and cannot fully meet the individual needs of tourists anymore. The aim is to integrate sparse tourism information on the Internet, thereby providing more convenient, faster, and more personalized tourism services. Based on the shortcomings of the traditional tourism recommendation system, a deep learning-based classification processing method of tourism product information is proposed. This method uses word embedding in the data preprocessing stage. The Convolutional Neural Network (CNN) is used to process review information of users and tourism service items. The Deep Neural Network (DNN) is used to process the necessary information of users and tourism service items. Also, factorization machine technology is used to learn the interaction between the extracted features to improve the prediction model. The results show that the proposed model can maintain an excellent precision of 64.2% when generating personalized recommendation lists for users. The sensitivity and accuracy of the recommendation list are better than other algorithms. By adding DNN, the word embedding method, and the factorization machine model, the precision is improved by 30%, 33.3%, and 40%, respectively. The model accuracy is the highest with 40 hidden factors, 100 convolutions, and a 100+50 combination hidden layer. Compared with traditional methods, the proposed algorithm can provide users with personalized travel products more accurately in personalized travel recommendations. The results have enriched and developed the theory of tourism service supply chain, providing a reference for constructing a personalized tourism service system.
Keywords	Medicine ; R ; Science ; Q
Subject code	910
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Quantifying the Interaction Effects of Climatic Factors on Vegetation Growth in Southwest China

Meng Wang / Zhengfeng An

Remote Sensing, Vol 15, Iss 774, p

2023 Volume 774

Abstract: Due to the complex and variable climate structure in Southwest China (SW), the impacts of climate variables on vegetation change and the interactions between climate factors remain controversial, considering the uncertainty and complexity in the ... ...

Abstract	Due to the complex and variable climate structure in Southwest China (SW), the impacts of climate variables on vegetation change and the interactions between climate factors remain controversial, considering the uncertainty and complexity in the relationships between climate factors and vegetation in this region. In this study, the CRU TS v. 4.02 from 1982 to 2017 and the annual maximum (P 100 ), upper quarter quantile (P 75 ), median (P 50 ), lower quarter quantile (P 25 ), minimum (P 5 ), and mean (Mean) of GIMMS NDVI were utilized to reveal the main and interaction effects of significant climate variables on vegetation development at the level of SW and the core areas (CAs) of typical climate type (including T + * –P + * , T + * –P – , T + * –P + , and NSC) using the simple moving average method, a multivariate linear model, the slope method, and the Johnson–Neyman method. The obtained regression relationships between NDVI , temperature, and precipitation were verified successfully by constructing multiple linear models with interaction terms. Within the T + * –P – CA, precipitation had the main impact; meanwhile, in the SW and other CAs, the temperature had the main effect. In general, most of the significant moderating effects of temperature (precipitation) on vegetation growth predominantly increased with the increase in precipitation (temperature). Nevertheless, the significant moderating effect varied in different regions and directions. In the SW area, when the temperature/precipitation was in the range of [4.73 °C, 5.13 °C]/[730.00 mm, 753.95 mm], the impact of temperature/precipitation on NDVI had a significant positive regulating effect with respect to the precipitation/temperature. Meanwhile, in the NSC/T + * –P + * areas, when the temperature/precipitation was in the range of [15.99 °C, 16.03 °C]/[725.17 mm, 752.82 mm], the impact of temperature/precipitation on NDVI has a significant negative moderating role with respect to the precipitation/temperature. Overall, our study provides a modern ...
Keywords	interaction ; simple slope method ; Johnson—Neyman analysis ; moderator variable ; typical climate types ; Science ; Q
Subject code	333
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Three-Dimensional Resistivity and Chargeability Tomography with Expanding Gradient and Pole–Dipole Arrays in a Polymetallic Mine, China

Meng Wang / Junlu Wang / Pinrong Lin / Xiaohong Meng

Remote Sensing, Vol 16, Iss 1, p

2024 Volume 186

Abstract: Three-dimensional resistivity/chargeability tomography based on distributed data acquisition technology is likely to provide abundant information for mineral exploration. To realize true 3D tomography, establishing transmitter sources with different ... ...

Abstract	Three-dimensional resistivity/chargeability tomography based on distributed data acquisition technology is likely to provide abundant information for mineral exploration. To realize true 3D tomography, establishing transmitter sources with different injection directions and collecting vector signals at receiver points is necessary. We implemented 3D resistivity/ chargeability tomography to search for new ore bodies in the deep and peripheral areas of Huaniushan, China. A distributed data acquisition system was used to form a vector receiver array in the survey area. First, by using the expanding gradient array composed of 11 pairs of transmitter electrodes, we quickly obtained the 3D distributions of the resistivity and chargeability of the whole area. Based on the electrical structure and geological setting, a NE-striking potential area for mineral exploration was determined. Next, a pole–dipole array was employed to depict the locations and shapes of the potential ore bodies in detail. The results showed that the inversion data for the two arrays corresponded well with the known geological setting and that the ore veins controlled by boreholes were located in the low-resistivity and high-chargeability zone. These results provided data for future mineral evaluation. Further research showed that true 3D tomography has obvious advantages over quasi-3D tomography. The expanding gradient array, characterized by a good signal strength and field efficiency, was suitable for the target determination in the early exploration stage. The pole–dipole array with high spatial resolution can be used for detailed investigations. Choosing a reasonable data acquisition scheme is helpful to improve the spatial resolution and economic efficiency.
Keywords	resistivity ; induced polarization ; 3D tomography ; mining ; Science ; Q
Subject code	550
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Research on Intelligent Sports Training System for Golf Based on Body Sense Recognition

Meng Wang / Tong Zang

Computational Intelligence and Neuroscience, Vol

2022 Volume 2022

Abstract: In recent years, significant advances in the development of computer vision technology have produced many platforms and systems that combine computer technology and sports-assisted training, including intelligent systems that are integrated with golf ... ...

Abstract	In recent years, significant advances in the development of computer vision technology have produced many platforms and systems that combine computer technology and sports-assisted training, including intelligent systems that are integrated with golf training and instruction. However, the existing intelligent systems for golf-assisted teaching usually use three-dimensional depth information, which will significantly increase the cost of intelligent systems. In this paper, the extraction of golf club slope is carried out on the basis of golf sport video capture using a common monocular camera in order to match the club slope information with the professional coach swing video information. At the same time, in order to facilitate the interframe matching, the joint point information is complemented using the projection approximation point algorithm, and the segmentation of the swing video is performed using the complemented human hand joints and the fixed characteristics of the golf swing. Then, in order to solve the problem that human joints will have the same joint angle under different movements, the human limb joint angles are defined and then the swing movements in the user video frames are evaluated.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571
Subject code	796
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: Socioeconomic status and ADL disability of the older adults

Huan Liu / Meng Wang

PLoS ONE, Vol 17, Iss 2, p e

Cumulative health effects, social outcomes and impact mechanisms.

2022 Volume 0262808

Abstract: Introduction Socioeconomic status (SES) is one of the important indicators affecting individual's social participation and resource allocation, and it also plays an important role in the health shock of individuals. Faced by the trend of aging society, ... ...

Abstract	Introduction Socioeconomic status (SES) is one of the important indicators affecting individual's social participation and resource allocation, and it also plays an important role in the health shock of individuals. Faced by the trend of aging society, more and more nations across the world began to pay attention to prevent the risk of health shock of old adults. Methods Based on the data of China Health and Retirement Longitudinal Study (CHARLS) in 2013, 2015 and 2018, this study uses path analysis and ologit model to empirically estimate the effects of SES and health shock on the activities of daily living (ADL) disability of old adults. Results As a result, first, it was found that SES has significant impact on the disability of old adults. Specifically, economic conditions (income) plays dominant role. Economic status affects the risk of individual disability mainly through life security and health behavior. Secondly, SES significantly affecting health shock, with education and economic status showing remarkable impact, and there is an apparent group inequality. Furthermore, taking high education group as reference, the probability of good sight or hearing ability of the low education group was only 49.76% and 63.29% of the high education group, respectively, while the rates of no pain and severe illness were 155.50% and 54.69% of the high education group. At last, the estimation of path effect of SES on ADL disability indicates evident group inequality, with health shock plays critical mediating role. Conclusions SES is an important factor influencing residents' health shock, and health shocks like cerebral thrombosis and cerebral hemorrhage will indirectly lead to the risk of individual ADL disability. Furthermore, among the multi-dimensional indicators of SES, individual income and education are predominant factors affecting health shock and ADL disability, while occupation of pre-retirement have little impact.
Keywords	Medicine ; R ; Science ; Q
Subject code	360
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A risk‐based driver behaviour model

Yuxia Yuan / Xinwei Wang / Simeon Calvert / Riender Happee / Meng Wang

IET Intelligent Transport Systems, Vol 18, Iss 1, Pp 88-

2024 Volume 100

Abstract: Abstract Current driver behaviour models (DBMs) are primarily designed for the general driver population under specific scenarios, such as car following or lane changing. Hence DBMs capturing individual behaviour under various scenarios are lacking. This ...

Abstract	Abstract Current driver behaviour models (DBMs) are primarily designed for the general driver population under specific scenarios, such as car following or lane changing. Hence DBMs capturing individual behaviour under various scenarios are lacking. This paper presents a novel method to quantify individual perceived driving risk in the longitudinal and lateral directions using risk thresholds capturing the time headway and time to line crossing. These are integrated in a risk‐based DBM formulated under a model predictive control (MPC) framework taking into account vehicle dynamics. The DBM assumes drivers to operate as predictive controllers jointly optimising multiple criteria, including driving risk, discomfort, and travel inefficiency. Simulation results in car following and passing a slower vehicle demonstrate that the DBM predicts plausible behaviour under representative driving scenarios, and that the risk thresholds are able to reflect individual driving behaviour. Furthermore, the proposed DBM is verified using empirical driving data collected from a driving simulator, and the results show it is able to accurately generate vehicle longitudinal and lateral control matching individual human drivers. Overall, this model can capture individual risk perception behaviour and can be applied to the design and assessment of intelligent vehicle systems.
Keywords	driver behaviour model ; human factors ; path planning ; risk perception ; vehicle dynamics and control ; Transportation engineering ; TA1001-1280 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	629 ; 380
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Knowledge graph completion method based on hyperbolic representation learning and contrastive learning

Xiaodong Zhang / Meng Wang / Xiuwen Zhong / Feixu An

Egyptian Informatics Journal, Vol 24, Iss 4, Pp 100414- (2023)

2023

Abstract: Knowledge graph completion employs existing triples to deduce missing data, thereby enriching and enhancing graph completeness. Recent research has revealed that using hyperbolic representation learning in knowledge graph completion yields superior ... ...

Abstract	Knowledge graph completion employs existing triples to deduce missing data, thereby enriching and enhancing graph completeness. Recent research has revealed that using hyperbolic representation learning in knowledge graph completion yields superior expressive and generalization capabilities. However, the long-tail problem and the presence of hyperbolic metrics make it challenging to effectively learn low-frequency entities or relations, resulting in embedding space distortion and impacting the original semantic relationships. Therefore, this paper proposes a knowledge graph completion method (Att-CL) that integrates hyperbolic representation learning and contrastive learning. In this approach, knowledge is embedded into a hyperbolic space, and samples with limited hierarchical characteristics and insufficient feature information are enhanced by introducing adversarial noise. The loss function of the embedded samples is backpropagated into embedding vectors, perturbations are adjusted in the gradient direction to promote smoothness and locality, and hyperparameters are introduced for fine-tuning the adversarial strength in the construction of adversarial samples for data augmentation to enhance model robustness. To mitigate data distortion due to hyperbolic metrics, a penalty term is introduced in the contrastive loss function to control the distances of the embedding vectors from the origin, thereby reducing the impact of the metrics and further improving the model's completion ability. Experimental results on the WN18RR and FB15K-237 benchmark datasets demonstrate significant improvements in metrics such as MRR, Hits@1, and Hits@3 compared to traditional knowledge graph completion models, providing ample evidence of the model's effectiveness.
Keywords	Knowledge graph completion ; Hyperbolic representation learning ; Comparison learning ; Adversarial samples ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	004
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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