Search

Your search keyword '"Wang, Xuhui"' showing total 1,717 results
Start Over Author "Wang, Xuhui"
1,717 results on '"Wang, Xuhui"'

2. Identifying Influential nodes in Brain Networks via Self-Supervised Graph-Transformer

Author

Kang, Yanqing, Zhu, Di, Zhang, Haiyang, Shi, Enze, Yu, Sigang, Wu, Jinru, Wang, Xuhui, Liu, Xuan, Chen, Geng, Jiang, Xi, Zhang, Tuo, and Zhang, Shu

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Artificial Intelligence
Abstract

Studying influential nodes (I-nodes) in brain networks is of great significance in the field of brain imaging. Most existing studies consider brain connectivity hubs as I-nodes. However, this approach relies heavily on prior knowledge from graph theory, which may overlook the intrinsic characteristics of the brain network, especially when its architecture is not fully understood. In contrast, self-supervised deep learning can learn meaningful representations directly from the data. This approach enables the exploration of I-nodes for brain networks, which is also lacking in current studies. This paper proposes a Self-Supervised Graph Reconstruction framework based on Graph-Transformer (SSGR-GT) to identify I-nodes, which has three main characteristics. First, as a self-supervised model, SSGR-GT extracts the importance of brain nodes to the reconstruction. Second, SSGR-GT uses Graph-Transformer, which is well-suited for extracting features from brain graphs, combining both local and global characteristics. Third, multimodal analysis of I-nodes uses graph-based fusion technology, combining functional and structural brain information. The I-nodes we obtained are distributed in critical areas such as the superior frontal lobe, lateral parietal lobe, and lateral occipital lobe, with a total of 56 identified across different experiments. These I-nodes are involved in more brain networks than other regions, have longer fiber connections, and occupy more central positions in structural connectivity. They also exhibit strong connectivity and high node efficiency in both functional and structural networks. Furthermore, there is a significant overlap between the I-nodes and both the structural and functional rich-club. These findings enhance our understanding of the I-nodes within the brain network, and provide new insights for future research in further understanding the brain working mechanisms.

Published
2024

4. Seasonal CO2 amplitude in northern high latitudes

Author

Liu, Zhihua, Rogers, Brendan M., Keppel-Aleks, Gretchen, Helbig, Manuel, Ballantyne, Ashley P., Kimball, John S., Chatterjee, Abhishek, Foster, Adrianna, Kaushik, Aleya, Virkkala, Anna-Maria, Burrell, Arden L., Schwalm, Christopher, Sweeney, Colm, Schuur, Edward A. G., Dean, Jacqueline, Watts, Jennifer D., Kim, Jinhyuk E., Wang, Jonathan A., Hu, Lei, Welp, Lisa, Berner, Logan T., Mauritz, Marguerite, Mack, Michelle, Parazoo, Nicholas C., Madani, Nima, Keeling, Ralph, Commane, Roisin, Goetz, Scott, Piao, Shilong, Natali, Susan M., Wang, Wenjuan, Buermann, Wolfgang, Walker, Xanthe, Lin, Xin, Wang, Xuhui, Jin, Yuming, Yu, Kailiang, and Zhang, Yangjian

Published
2024
Full Text
View/download PDF

8. Large Language Models for Robotics: Opportunities, Challenges, and Perspectives

Author

Wang, Jiaqi, Wu, Zihao, Li, Yiwei, Jiang, Hanqi, Shu, Peng, Shi, Enze, Hu, Huawen, Ma, Chong, Liu, Yiheng, Wang, Xuhui, Yao, Yincheng, Liu, Xuan, Zhao, Huaqin, Liu, Zhengliang, Dai, Haixing, Zhao, Lin, Ge, Bao, Li, Xiang, Liu, Tianming, and Zhang, Shu

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

Large language models (LLMs) have undergone significant expansion and have been increasingly integrated across various domains. Notably, in the realm of robot task planning, LLMs harness their advanced reasoning and language comprehension capabilities to formulate precise and efficient action plans based on natural language instructions. However, for embodied tasks, where robots interact with complex environments, text-only LLMs often face challenges due to a lack of compatibility with robotic visual perception. This study provides a comprehensive overview of the emerging integration of LLMs and multimodal LLMs into various robotic tasks. Additionally, we propose a framework that utilizes multimodal GPT-4V to enhance embodied task planning through the combination of natural language instructions and robot visual perceptions. Our results, based on diverse datasets, indicate that GPT-4V effectively enhances robot performance in embodied tasks. This extensive survey and evaluation of LLMs and multimodal LLMs across a variety of robotic tasks enriches the understanding of LLM-centric embodied intelligence and provides forward-looking insights toward bridging the gap in Human-Robot-Environment interaction.

Published
2024

22. Structure, physical properties, and magnetically tunable topological phases in topological semimetal EuCuBi

Author

Wang, Xuhui, Li, Boxuan, Zhou, Liqin, Chen, Long, Wang, Yulong, Yang, Yaling, Zhou, Ying, Liao, Ke, Weng, Hongming, and Wang, Gang

Subjects
Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons
Abstract

A single material achieving multiple topological phases can provide potential application for topological spintronics, whereas the candidate materials are very limited. Here, we report the structure, physical properties, and possible emergence of multiple topological phases in the newly discovered, air-stable EuCuBi single crystal. EuCuBi crystallizes in a hexagonal space group P63/mmc (No. 194) in ZrBeSi-type structure with an antiferromagnetic (AFM) ground state below TN = 11.2 K. There is a competition between AFM and ferromagnetic (FM) interactions below TN revealed by electrical resistivity and magnetic susceptibility measurements. With the increasing magnetic field, EuCuBi evolves from the AFM ground state with a small amount of FM component, going through two possible metamagnetic phases, finally reaches the field-induced FM phase. Based on the first-principles calculations, we demonstrate that the Dirac, Weyl, and possible mirror Chern insulator can be achieved in EuCuBi by tuning the temperature and applying magnetic field, making EuCuBi a promising candidate for exploring multiple topological phases., Comment: 16 pages,8 figures

Published
2023
Full Text
View/download PDF

23. Clinical features of and influencing factors of obsessive-compulsive personality disorder in patients with obsessive-compulsive disorder

Author

Jiang Wenjing, Wang Xuhui, Xu Zhihan, Zhang Xuedi, Wang Zhongqi, Zhou Ping, and Liu Na

Subjects
obsessive-compulsive personality disorder, obsessive-compulsive disorder, clinical features, influencing factors, Psychology, BF1-990, Psychiatry, RC435-571
Abstract

BackgroundObsessive-compulsive personality disorder and obsessive-compulsive disorder （OCD） are common psychological disorders with similar clinical symptoms， but the differences between the two need further clarification.ObjectiveTo explore the clinical features of and influencing factors of obsessive-compulsive personality disorder in patients with OCD， so as to provide references for further relevant clinical diagnosis and treatment.MethodsA total of 195 patients with OCD were selected as the research subjects， who received treatment at the outpatient and inpatient departments of the Affiliated Brain Hospital of Nanjing Medical University from July 2022 to December 2023 and met the diagnostic criteria for OCD in the International Classification of Diseases， tenth edition （ICD-10）. Evaluation was conducted by using the Yale-Brown Obsessive Compulsive Scale （Y-BOCS）， Personality Diagnostic Questionnaire-4+ （PDQ-4+）， Obsessive-Compulsive Inventory-Revised （OCI-R）， Beck Depression Inventory （BDI）， Beck Anxiety Inventory （BAI） and Sheehan Disability Scale （SDS）. In accordance with the score of Obsessive-Compulsive Personality Disorder Scale in PDQ-4+， patients were divided into the OCD group with obsessive-compulsive personality disorder （n=58） and the OCD group without obsessive-compulsive personality disorder （n=137）. Pearson correlation analysis and Spearman correlation analysis were adopted to examine the correlation between clinical features and the score of the Obsessive-Compulsive Personality Disorder Scale. Multiple linear regression analysis was used to explore the influencing factors of OCD patients with obsessive-compulsive personality disorder.ResultsStatistically significant differences were observed between OCD patients with and without obsessive-compulsive personality disorder in the age， family history of mental illness， time without treatment， hoarding and ranking dimension scores in OCI-R， OCI-R total score， score of Obsessive-Compulsive Personality Disorder Scale in PDQ-4， and BDI score （P≤0.05）. OCD patients with obsessive-compulsive personality disorder in the time without treatment， OCI-R total score， hoarding and ranking dimension scores in OCI-R and BDI score are all positively correlated with the score of the Obsessive-Compulsive Personality Disorder Scale （r=0.120， 0.526， 0.364， 0.492， 0.414， P

Published
2024
Full Text
View/download PDF

24. Multimodal Machine Translation with Fusion of Generated Visual Information

Author

Yuan, Jiaqi, Shi, Xiayang, Niu, Yue, Niu, Yufeng, Wang, Xuhui, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Zhang, Yonghong, editor, Qi, Lianyong, editor, Liu, Qi, editor, Yin, Guangqiang, editor, and Liu, Xiaodong, editor

Published
2024
Full Text
View/download PDF

25. Global variations in critical drought thresholds that impact vegetation

Author

Li, Xiangyi, Piao, Shilong, Huntingford, Chris, Peñuelas, Josep, Yang, Hui, Xu, Hao, Chen, Anping, Friedlingstein, Pierre, Keenan, Trevor F, Sitch, Stephen, Wang, Xuhui, Zscheischler, Jakob, and Mahecha, Miguel D

Subjects
Biological Sciences, Ecology, Engineering, Environmental Sciences, Geomatic Engineering, Climate Action, Life on Land, drought threshold, inflection points, vegetation response, soil moisture, drought impacts, Crop and Pasture Production
Abstract

Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001-2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

Published
2023

27. An Empirical Investigation of Leadership and Human Resources Capacities as Key Actors in the Implementation of Smart Education

Author

Wang, Xuhui, Wilson, Jonela, and Li, Wenjing

Abstract

Due to the novelty of the smart education phenomenon, a quantitative investigation of the variables that will influence the implementation of 'smart education' was needed. Therefore, based on a probability simple random survey of 349 Grenadian employees from tertiary institutions in the education industry, the influence of leadership and human resource capacities on smart education were investigated. Results produced from SPSS analysis software and Smart PLS revealed that leadership and human resources capacities have sufficient confidence to have a significant influence on smart education, producing a positive association with 'smart education.' However, this relationship is positively moderated by additional investments, such as infrastructural innovation. These findings enrich the current literature on smart education (SE) by increasing knowledge of the phenomenon through the lenses of the Actor-Network Theory and Technology Adoption Model. Accordingly, policymakers should bear these findings in mind when developing holistic strategies to guide SE's successful enactment.

Published
2021

Catalog

Books, media, physical & digital resources
See catalog results