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3,491 results on '"Liu, Shen"'

1. Hotspots and Trends in Magnetoencephalography Research (2013-2022): A Bibliometric Analysis

Author

Liu, Shen and Zhao, Jingwen

Subjects
Computer Science - Digital Libraries
Abstract

This study aimed to utilize bibliometric methods to analyze trends in international Magnetoencephalography (MEG) research from 2013 to 2022. Due to the limited volume of domestic literature on MEG, this analysis focuses solely on the global research landscape, providing insights from the past decade as a representative sample. This study utilized bibliometric methods to explore and analyze the progress, hotspots and developmental trends in international MEG research spanning from 1995 to 2022. The results indicated a dynamic and steady growth trend in the overall number of publications in MEG. Ryusuke Kakigi emerged as the most prolific author, while Neuroimage led as the most prolific journal. Current hotspots in MEG research encompass resting state, networks, functional connectivity, phase dynamics, oscillation, and more. Future trends in MEG research are poised to advance across three key aspects: disease treatment and practical applications, experimental foundations and technical advancements, and fundamental and advanced human cognition. In the future, there should be a focus on enhancing cross-integration and utilization of MEG with other instruments to diversify research methodologies in this field

Published
2024

2. Identifying Research Hotspots and Future Development Trends in Current Psychology: A Bibliometric Analysis of the Past Decade's Publications

Author

Liu, Shen and Yang, Yan

Subjects
Computer Science - Digital Libraries, Statistics - Methodology, Statistics - Other Statistics
Abstract

By conducting a bibliometric analysis on 4,869 publications in Current Psychology from 2013 to 2022, this paper examined the annual publications and annual citations, as well as the leading institutions, countries, and keywords. CiteSpace, VOSviewer and SCImago Graphica were utilized for visualization analysis. On one hand, this paper analyzed the academic influence of Current Psychology over the past decade. On the other hand, it explored the research hotspots and future development trends within the field of international psychology. The results revealed that the three main research areas covered in the publications of Current Psychology were: the psychological well-being of young people, the negative emotions of adults, and self-awareness and management. The latest research hotspots highlighted in the journal include negative emotions, personality, and mental health. The three main development trends of Current Psychology are: 1) exploring the personality psychology of both adolescents and adults, 2) promoting the interdisciplinary research to study social psychological issues through the use of diversified research methods, and 3) emphasizing the emotional psychology of individuals and their interaction with social reality, from a people-oriented perspective.

Published
2024

6. Comparison of evaluation metrics of deep learning for imbalanced imaging data in osteoarthritis studies.

Author

Liu, Shen, Roemer, Frank, Ge, Yong, Bedrick, Edward, Li, Zong-Ming, Guermazi, Ali, Sharma, Leena, Eaton, Charles, Hochberg, Marc, Hunter, David, Nevitt, Michael, Wirth, Wolfgang, Kent Kwoh, C, and Sun, Xiaoxiao

Subjects
Bone marrow lesion, Deep learning, Imbalanced data, Osteoarthritis, Precision recall curve, Receiver operating characteristic, Humans, Deep Learning, Retrospective Studies, Benchmarking, Knee Joint, Magnetic Resonance Imaging, Osteoarthritis, Knee, Cartilage Diseases
Abstract

PURPOSE: To compare the evaluation metrics for deep learning methods that were developed using imbalanced imaging data in osteoarthritis studies. MATERIALS AND METHODS: This retrospective study utilized 2996 sagittal intermediate-weighted fat-suppressed knee MRIs with MRI Osteoarthritis Knee Score readings from 2467 participants in the Osteoarthritis Initiative study. We obtained probabilities of the presence of bone marrow lesions (BMLs) from MRIs in the testing dataset at the sub-region (15 sub-regions), compartment, and whole-knee levels based on the trained deep learning models. We compared different evaluation metrics (e.g., receiver operating characteristic (ROC) and precision-recall (PR) curves) in the testing dataset with various class ratios (presence of BMLs vs. absence of BMLs) at these three data levels to assess the models performance. RESULTS: In a subregion with an extremely high imbalance ratio, the model achieved a ROC-AUC of 0.84, a PR-AUC of 0.10, a sensitivity of 0, and a specificity of 1. CONCLUSION: The commonly used ROC curve is not sufficiently informative, especially in the case of imbalanced data. We provide the following practical suggestions based on our data analysis: 1) ROC-AUC is recommended for balanced data, 2) PR-AUC should be used for moderately imbalanced data (i.e., when the proportion of the minor class is above 5% and less than 50%), and 3) for severely imbalanced data (i.e., when the proportion of the minor class is below 5%), it is not practical to apply a deep learning model, even with the application of techniques addressing imbalanced data issues.

Published
2023

20. Multi-Augmentation for Efficient Visual Representation Learning for Self-supervised Pre-training

Author

Tran, Van-Nhiem, Huang, Chi-En, Liu, Shen-Hsuan, Yang, Kai-Lin, Ko, Timothy, and Li, Yung-Hui

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In recent years, self-supervised learning has been studied to deal with the limitation of available labeled-dataset. Among the major components of self-supervised learning, the data augmentation pipeline is one key factor in enhancing the resulting performance. However, most researchers manually designed the augmentation pipeline, and the limited collections of transformation may cause the lack of robustness of the learned feature representation. In this work, we proposed Multi-Augmentations for Self-Supervised Representation Learning (MA-SSRL), which fully searched for various augmentation policies to build the entire pipeline to improve the robustness of the learned feature representation. MA-SSRL successfully learns the invariant feature representation and presents an efficient, effective, and adaptable data augmentation pipeline for self-supervised pre-training on different distribution and domain datasets. MA-SSRL outperforms the previous state-of-the-art methods on transfer and semi-supervised benchmarks while requiring fewer training epochs.

Published
2022

22. Comparison of Patient Health Questionnaire-9, Edinburgh Postnatal Depression Scale and Hospital Anxiety and Depression – Depression subscale scores by administration mode: An individual participant data differential item functioning meta-analysis

Author

Azar, Marleine, Bhandari, Parash Mani, Chiovitti, Matthew J., He, Chen, Imran, Mahrukh, Krishnan, Ankur, Negeri, Zelalem, Neupane, Dipika, Riehm, Kira E., Yan, Xin Wei, Kloda, Lorie A., Henry, Melissa, Ismail, Zahinoor, Loiselle, Carmen G., Mitchell, Nicholas D., Al-Adawi, Samir, Alvarado, Rubén, Amtmann, Dagmar, Arroll, Bruce, Ayalon, Liat, Baradaran, Hamid R., Barnes, Jacqueline, Beck, Kevin R., Beck, Cheryl Tatano, Bernstein, Charles N., Bindt, Carola, Bombardier, Charles H., Boye, Birgitte, Büel-Drabe, Natalie, Buji, Ryna Imma, Bunevicius, Adomas, Butterworth, Peter, Can, Ceyhun, Carter, Gregory, Chagas, Marcos H., Chan, Juliana C.N., Chan, Lai Fong, Chen, Chih-Ken, Chibanda, Dixon, Chorwe-Sungani, Genesis, Clover, Kerrie, Conroy, Ronán M., Conway, Aaron, Conwell, Yeates, Correa, Humberto, Couto, Thiago Castro e, Cukor, Daniel, Daray, Federico M., de Man-van Ginkel, Janneke M., De Souza, Jennifer, Downing, Marina G., Eapen, Valsamma, Fann, Jesse R., Favez, Nicolas, Felice, Ethel, Fellmeth, Gracia, Ferentinos, Panagiotis P., Fernandes, Michelle, Field, Sally, Figueiredo, Barbara, Fischer, Felix H., Fisher, Jane R.W., Flint, Alastair J., Fujimori, Maiko, Fung, Daniel S.S., Gallagher, Pamela, Gandy, Milena, Gelaye, Bizu, Gholizadeh, Leila, Gibson, Lorna J., Goodyear-Smith, Felicity, Grassi, Luigi, Green, Eric P., Greeno, Catherine G., Hall, Brian J., Hantsoo, Liisa, Haroz, Emily E., Härter, Martin, Hegerl, Ulrich, Helle, Nadine, Hernando, Asuncion, Hides, Leanne, Hobfoll, Stevan E., Honikman, Simone, Howard, Louise M., Hyphantis, Thomas, Iglesias-González, Maria, Inagaki, Masatoshi, Jenewein, Josef, Jeon, Hong Jin, Jetté, Nathalie, Julião, Miguel, Kettunen, Pirjo A., Khamseh, Mohammad E., Kiely, Kim M., Kim, Sung-Wan, Kjærgaard, Marie, Kohlhoff, Jane, Kohrt, Brandon A., König, Hans-Helmut, Kozinszky, Zoltán, Kwan, Yunxin, Lamers, Femke, Lara, María Asunción, Leonardou, Angeliki A., Levin-Aspenson, Holly F., Liu, Shen-Ing, Löbner, Margrit, Loosman, Wim L., Lotrakul, Manote, Loureiro, Sonia R., Love, Anthony W., Löwe, Bernd, Luitel, Nagendra P., Lund, Crick, Maes, Michael, Malt, Ulrik F., Marrie, Ruth Ann, Marsh, Laura, Martínez, Pablo, Marx, Brian P., Matsuoka, Yutaka, McGuire, Anthony, Mehnert, Anja, Michopoulos, Ioannis, Sidik, Sherina Mohd, Müller-Nordhorn, Jacqueline, Muramatsu, Kumiko, Radoš, Sandra Nakić, Navarrete, Laura, Nelson, Christian J., Ng, Chong Guan, Nishi, Daisuke, O'Donnell, Meaghan L., O'Rourke, Suzanne J., Osório, Flávia L., Pabst, Alexander, Pasco, Julie A., Pawlby, Susan J., Peceliuniene, Jurate, Pence, Brian W., Persoons, Philippe, Petersen, Inge, Picardi, Angelo, Ponsford, Jennie L., Pugh, Stephanie L., Pulido, Federico, Quinn, Terence J., Quispel, Chantal, Rathod, Sujit D., Reme, Silje E., Reuter, Katrin, Riedel-Heller, Steffi G., Rooney, Alasdair G., Santos, Iná S., Saracino, Rebecca M., Schellekens, Melanie P.J., Schwarzbold, Marcelo L., Cankorur, Vesile Senturk, Shaaban, Juwita, Sharp, Deborah J., Sharpe, Louise, Shinn, Eileen H., Sidebottom, Abbey, Simard, Sébastien, Singer, Susanne, Skalkidou, Alkistis, Smith-Nielsen, Johanne, Spangenberg, Lena, Stafford, Lesley, Stein, Alan, Stewart, Robert C., Strobel, Natalie A., Su, Kuan-Pin, Sultan, Serge, Sundström-Poromaa, Inger, Sung, Sharon C., Suzuki, Keiko, Tadinac, Meri, Tan, Pei Lin Lynnette, Tandon, S. Darius, Taylor-Rowan, Martin, Teixeira, Antonio L., Tendais, Iva, Tiringer, Istvan, Töreki, Annamária, Tran, Thach D., Trevillion, Kylee, Tschorn, Mira, Turner, Alyna, Væver, Mette S., van der Feltz-Cornelis, Christina M., van Heyningen, Thandi, Vega-Dienstmaier, Johann M., Wagner, Michael, Wagner, Lynne I., Wang, Liang-Jen, Wang, Jian Li, Watson, David, Weyerer, Siegfried B., White, Jennifer, Whooley, Mary A., Wiese, Birgitt, Williams, Lana J., Winkley, Kirsty, Wynter, Karen, Yamada, Mitsuhiko, Yonkers, Kimberly A., Zeng, Qing Zhi, Zhang, Yuying, Harel, Daphna, Wu, Yin, Levis, Brooke, Fan, Suiqiong, Sun, Ying, Xu, Mingyao, Rice, Danielle B., Boruff, Jill, Markham, Sarah, Ioannidis, John P.A., Takwoingi, Yemisi, Patten, Scott B., Ziegelstein, Roy C., Cuijpers, Pim, Gilbody, Simon, Vigod, Simone, Akena, Dickens, Benedetti, Andrea, and Thombs, Brett D.

Published
2024
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28. The impact of repeated exposure on facial attractiveness: The role of cognition and emotion

Author

Han, Shangfeng, Shen, Jie, Wang, Xiujuan, Guo, Zhibin, Liu, Shen, Gan, Yetong, and Xu, Qiang

Subjects
Emotions -- Research, Emotions and cognition -- Research, Aesthetics -- Psychological aspects, Cognition -- Research, Psychological research, Face -- Psychological aspects -- Social aspects, Psychology and mental health
Abstract

Although previous studies have found that repeated exposure has an influence on the judgment of facial attractiveness, how this effect occurs remains unclear. Two experiments were conducted to explore the impact of repeated exposure on facial attractiveness and the processing mechanism. The results of Experiment 1 showed that in the case of large number of exposures, the facial attractiveness judgment for faces with high, moderate, and low attractiveness increased after repeated exposure. The increase in familiarity and liking mediated the relationship between repeated exposure and faces with high attractiveness, while the increase in liking mediated the relationship between repeated exposure and faces with low attractiveness. The results of Experiment 2 showed that in the case of small number of exposures, the facial attractiveness rating of faces with high and moderate attractiveness increased after repeated exposure. The increase in familiarity and liking mediated the relationship between repeated exposure and faces with high attractiveness, while the increase in familiarity mediated the relationship between repeated exposure and faces with moderate attractiveness. The results indicate that both the fluency of cognitive processing and change of affective attitude play an important role when people judge the facial attractiveness during repeated exposure. The present study illustrates the change rule of the evaluation of facial attractiveness, and lays a solid theoretical foundation for further investigation of the dynamic relationship between social characteristics of faces and behavioral decision-making., Author(s): Shangfeng Han [sup.1] [sup.2] , Jie Shen [sup.1] , Xiujuan Wang [sup.3] , Zhibin Guo [sup.1] , Shen Liu [sup.4] , Yetong Gan [sup.4] , Qiang Xu [sup.1] , [...]

Published
2023
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29. Belief in a just world and bullying defending behavior among adolescents: Roles of self-efficacy and responsibility

Author

Chen, Yanling, Wang, Siyao, Liu, Shen, Hong, Xinwei, Zheng, Junmeng, Jiao, Lan, and Zhang, Lin

Subjects
Psychology and mental health
Abstract

Defending behavior represents any prosocial behavior taken to assist an individual being bullied, which has received increased attention in developmental science and is an important component of anti-bullying interventions. This study aims to explore the relationship between belief in a just world (BJW) and bullying defending behavior among adolescents in the Chinese cultural context, the role of self-efficacy, responsibility, and gender. This study recruited 837 students (50.29% boys, M.sub.age = 13.6 years, SD = 0.79 years) from three junior middle schools in Zhejiang, China, using a convenience sampling method. The results show that: (1) BJW, self-efficacy, responsibility, and defending behavior are all significantly correlated; (2) BJW indirectly predicts defending behavior through the mediation of self-efficacy and responsibility, and serial mediation of self-efficacy and responsibility. (3) There are gender differences in the relationship between self-efficacy and responsibility. Compared with girls, boys' self-efficacy has a stronger predictive effect on responsibility, and they display more defending behavior. The research reveals that defending behavior can be effectively promoted by enhancing students' BJW, self-efficacy, and responsibility, providing theoretical reference and practical advice for intervention in bystander behavior in school bullying., Author(s): Yanling Chen [sup.1] , Siyao Wang [sup.1] , Shen Liu [sup.2] , Xinwei Hong [sup.1] , Junmeng Zheng [sup.1] , Lan Jiao [sup.1] , Lin Zhang [sup.1] Author Affiliations: [...]

Published
2023
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30. Recent exposure to others' confided suicidal thoughts and risk of self-harm and suicidality among adolescents

Author

Liu, Hui-Ching, Huang, Yu-Hsin, Tjung, Jin-Jin, Sun, Fang-Ju, and Liu, Shen-Ing

Subjects
Self-destructive behavior -- Risk factors -- Social aspects, Teenagers -- Social aspects -- Psychological aspects -- Health aspects, Youth -- Social aspects -- Psychological aspects -- Health aspects, Suicidal ideation -- Social aspects, Psychology and mental health
Abstract

Few studies have investigated the contagion effects of exposure to others' confided suicidal thoughts among adolescents. The aim of this study was to investigate whether recent real-world exposure to confided suicidal thoughts was associated with adolescent self-harm and suicidality within one month, and if so, to determine the related risk and protective factors. A total of 5,879 Taiwanese first-year senior high school students participated in this study and completed on-line questionnaires regarding their experience of exposure to confided suicidal thoughts, self-harm and suicidality, socio-demographic information, Patient Health Questionnaire 9-item, Multi-Dimensional Support Scale, Rosenberg Self-Esteem Scale, and alcohol and cigarette use. Of the enrolled adolescents, 3.4% had been exposed to confided suicidal thoughts (N = 200) within one month. The most common source of exposure was friends (N = 186). After controlling for a large variety of confounders, the adolescents with recent exposure to others' suicidal thoughts were four times more likely to harm themselves within one month (OR = 3.77; 95% CI: 2.26 - 6.30). The risks of suicidal ideation and suicide plans were also markedly increased (both OR = 5.15; 95% CI: 3.48 - 7.64 and 2.78 - 9.52, respectively). The risk ratios were highest if the source of exposure was from parents, and the contagion effects were dose-dependent. Support from parents and teachers could protect the adolescents from the impact of contagion. Our results suggest a contagion effect of exposure to confided suicidal thoughts among adolescents. Parents and school personnel should be aware of this and provide assistance for those in need., Author(s): Hui-Ching Liu [sup.1] , Yu-Hsin Huang [sup.1] [sup.2] , Jin-Jin Tjung [sup.3] , Fang-Ju Sun [sup.4] , Shen-Ing Liu [sup.1] [sup.2] Author Affiliations: (1) grid.413593.9, 0000 0004 0573 007X, [...]

Published
2023
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34. Sdft: A PDG-based Summarization for Efficient Dynamic Data Flow Tracking

Author

Kan, Xiao, Sun, Cong, Liu, Shen, Huang, Yongzhe, Tan, Gang, Ma, Siqi, and Zhang, Yumei

Subjects
Computer Science - Cryptography and Security
Abstract

Dynamic taint analysis (DTA) has been widely used in various security-relevant scenarios that need to track the runtime information flow of programs. Dynamic binary instrumentation (DBI) is a prevalent technique in achieving effective dynamic taint tracking on commodity hardware and systems. However, the significant performance overhead incurred by dynamic taint analysis restricts its usage in production systems. Previous efforts on mitigating the performance penalty fall into two categories, parallelizing taint tracking from program execution and abstracting the tainting logic to a higher granularity. Both approaches have only met with limited success. In this work, we propose Sdft, an efficient approach that combines the precision of DBI-based instruction-level taint tracking and the efficiency of function-level abstract taint propagation. First, we build the library function summaries automatically with reachability analysis on the program dependency graph (PDG) to specify the control- and data dependencies between the input parameters, output parameters, and global variables of the target library. Then we derive the taint rules for the target library functions and develop taint tracking for library function that is tightly integrated into the state-of-the-art DTA framework Libdft. By applying our approach to the core C library functions of glibc, we report an average of 1.58x speed up of the tracking performance compared with Libdft64. We also validate the effectiveness of the hybrid taint tracking and the ability on detecting real-world vulnerabilities.

Published
2021

38. A Dual-Attention Neural Network for Pun Location and Using Pun-Gloss Pairs for Interpretation

Author

Liu, Shen, Ma, Meirong, Yuan, Hao, Zhu, Jianchao, Wu, Yuanbin, and Lan, Man

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Pun location is to identify the punning word (usually a word or a phrase that makes the text ambiguous) in a given short text, and pun interpretation is to find out two different meanings of the punning word. Most previous studies adopt limited word senses obtained by WSD(Word Sense Disambiguation) technique or pronunciation information in isolation to address pun location. For the task of pun interpretation, related work pays attention to various WSD algorithms. In this paper, a model called DANN (Dual-Attentive Neural Network) is proposed for pun location, effectively integrates word senses and pronunciation with context information to address two kinds of pun at the same time. Furthermore, we treat pun interpretation as a classification task and construct pungloss pairs as processing data to solve this task. Experiments on the two benchmark datasets show that our proposed methods achieve new state-of-the-art results. Our source code is available in the public code repository.

Published
2021

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