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357 results on '"Wu, Lanlan"'

1. Investigation of the effectiveness of applying ChatGPT in Dialogic Teaching Using Electroencephalography

Author

Zhang, Jiayue, Liu, Yiheng, Cai, Wenqi, Wu, Lanlan, Peng, Yali, Yu, Jingjing, Qi, Senqing, Long, Taotao, and Ge, Bao

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence, Physics - Physics Education
Abstract

In recent years, the rapid development of artificial intelligence technology, especially the emergence of large language models (LLMs) such as ChatGPT, has presented significant prospects for application in the field of education. LLMs possess the capability to interpret knowledge, answer questions, and consider context, thus providing support for dialogic teaching to students. Therefore, an examination of the capacity of LLMs to effectively fulfill instructional roles, thereby facilitating student learning akin to human educators within dialogic teaching scenarios, is an exceptionally valuable research topic. This research recruited 34 undergraduate students as participants, who were randomly divided into two groups. The experimental group engaged in dialogic teaching using ChatGPT, while the control group interacted with human teachers. Both groups learned the histogram equalization unit in the information-related course "Digital Image Processing". The research findings show comparable scores between the two groups on the retention test. However, students who engaged in dialogue with ChatGPT exhibited lower performance on the transfer test. Electroencephalography data revealed that students who interacted with ChatGPT exhibited higher levels of cognitive activity, suggesting that ChatGPT could help students establish a knowledge foundation and stimulate cognitive activity. However, its strengths on promoting students. knowledge application and creativity were insignificant. Based upon the research findings, it is evident that ChatGPT cannot fully excel in fulfilling teaching tasks in the dialogue teaching in information related courses. Combining ChatGPT with traditional human teachers might be a more ideal approach. The synergistic use of both can provide students with more comprehensive learning support, thus contributing to enhancing the quality of teaching.

Published
2024

32. Association between the C-reactive protein–albumin–lymphocyte index and metabolic syndrome: evidence from the 2003–2010 national health and nutrition examination survey.

Author

Wu, Lanlan, Han, Dunzheng, Xue, Yuting, He, Shangfei, Ma, Zhuang, Su, Shuwen, Li, Peixin, Liu, Shenrong, and Zhou, Haobin

Subjects
*HEALTH & Nutrition Examination Survey, *METABOLIC syndrome, *QUALITY of life, *CONFOUNDING variables, *ODDS ratio
Abstract

Background: Metabolic syndrome (MetS) is a global public health problem that significantly impacts human health and quality of life. The relationship between MetS and the C-reactive protein–albumin–lymphocyte (CALLY) index is uncertain. Methods: This study analyzed the data of 7,534 individuals from the National Health and Nutrition Examination Survey cycles (2003–2010 cycles). Weighted logistic regression and weighted restricted cubic spline (RCS) curve analyses were used to identify the relationships between the CALLY index and MetS, as well as its components. Results: Of the 7,534 participants, 2,086 were diagnosed with MetS. The estimated prevalence of MetS decreased with an increase in the CALLY index (P < 0.001). Multivariable logistic regression analysis showed that the odds ratio of MetS was 0.25 (95% confidence interval 0.20–0.32, P < 0.001) in the highest CALLY index quartile compared with the lowest quartile after adjusting for confounding variables. The RCS curve analysis revealed non-linear relationships between the CALLY index and MetS or its components. Conclusions: This study revealed an inverse relationship between the CALLY index and MetS risk. The CALLY index might be valuable for identifying individuals who are at a high risk of MetS. Clinical trial number: Not applicable. [ABSTRACT FROM AUTHOR]

Published
2025
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33. Exploring dipeptidyl peptidase‐IV inhibitory peptides from Tartary Buckwheat protein: A study of hydrolysis, fractionation, and molecular interactions.

Author

Wu, Weijing, Wang, Libo, Qiu, Ju, Zhuang, Ziyuan, Qin, Fei, Tan, Qianglai, Wang, Yanling, and Wu, Lanlan

Subjects
PEPTIDES, FOOD supply, BUCKWHEAT, FUNCTIONAL foods, MOLECULAR docking
Abstract

Tartary buckwheat, a protein‐rich pseudocereal with anti‐diabetic effects, has not yet been fully explored as a source of dipeptidyl peptidase‐IV (DPP‐IV) inhibitory peptides. This study aims to discover novel DPP‐IV inhibitory peptides from tartary buckwheat protein (TBP). Five hydrolysis methods were employed, with simulated gastrointestinal digestion (SGID) releasing the most active DPP‐IV inhibitory hydrolysates, showing both the highest degree of hydrolysis (22.66 ± 1.12%) and inhibition activity (41.81 ± 1.52% at 1.25 mg/mL). In addition, ultrafiltration enriched the <3 kDa fraction with the highest inhibitory rate, and further purification using reverse‐phase high‐performance liquid chromatography concentrated the DPP‐IV inhibitory peptides in the first fraction (F1). Nano liquid chromatography‐tandem mass spectrometry analysis identified 10 new peptides in F1, among which the peptide Leu‐His‐Ile‐Val‐Gly‐Pro‐Asp‐Lys (LHIVGPDK) exhibited the strongest inhibitory effect, with an IC50 value of 1.61 mM. Kinetic studies revealed that LHIVGPDK acts as a mixed‐type inhibitor, and molecular docking indicated that it inhibits DPP‐IV by forming stable complexes through five types of interactions, with hydrogen bonds playing a key role. This study underscores TBP's DPP‐IV inhibitory potential and anti‐diabetic properties, reinforcing the value of tartary buckwheat as a beneficial food for diabetes management. Practical Application: This research identified new peptides from Tartary buckwheat protein that effectively inhibit DPP‐IV, an enzyme associated with diabetes management. These findings suggest potential applications in developing functional foods to help control hypoglycemia. [ABSTRACT FROM AUTHOR]

Published
2024
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46. Enhanced PEC water splitting efficiency by type II heterojunction CdIn2S4/g-C3N4 photoanode construction.

Author

Liu, Dinghan, Liu, Jing, Wu, Lanlan, Zhou, Zhenglong, Su, Zihan, Yang, Bing, and Feng, Liangliang

Subjects
PHOTOELECTROCHEMISTRY, HETEROJUNCTIONS, SOLAR cells, DYE-sensitized solar cells, ENERGY shortages, CHARGE transfer, SONICATION
Abstract

The employment of catalysts to split water to create hydrogen is viewed as an effective solution to the energy crisis problem. In this work, type II heterojunction CdIn2S4/g-C3N4 nanocomposites with different mass ratios were successfully synthesised using a simple sonication technique. The results show that the constructed CdIn2S4/g-C3N4 heterojunctions exhibit better catalytic performance in the photoelectrocatalytic water splitting reaction, and the photocurrent density of the composite with a composite ratio of 15% reaches 0.35 mA cm−2 at 1.23 V (vs. RHE), which is a 2.33-fold enhancement relative to g-C3N4. The constructed heterojunction facilitates the photogenerated charge transfer between CdIn2S4 and g-C3N4, effectively accelerating the separation of photogenerated electrons and holes. This work provides theoretical guidance for efficient PEC water splitting technology. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Using EEG to investigate the effectiveness of applying ChatGPT

Author

Zhang, Jiayue, Liu, Yiheng, Cai, Wenqi, Wu, Lanlan, Peng, Yali, Yu, Jingjing, Qi, Senqing, Long, Taotao, Ge, Bao, Zhang, Jiayue, Liu, Yiheng, Cai, Wenqi, Wu, Lanlan, Peng, Yali, Yu, Jingjing, Qi, Senqing, Long, Taotao, and Ge, Bao

Abstract

In recent years, the rapid development of artificial intelligence technology, especially the emergence of large language models (LLMs) such as ChatGPT, has presented significant prospects for application in the field of education. LLMs possess the capability to interpret knowledge, answer questions, and consider context, thus providing support for dialogic teaching to students. Therefore, an examination of the capacity of LLMs to effectively fulfill instructional roles, thereby facilitating student learning akin to human educators within dialogic teaching scenarios, is an exceptionally valuable research topic. This research recruited 34 undergraduate students as participants, who were randomly divided into two groups. The experimental group engaged in dialogic teaching using ChatGPT, while the control group interacted with human teachers. Both groups learned the histogram equalization unit in the information-related course "Digital Image Processing". The research findings show comparable scores between the two groups on the retention test. However, students who engaged in dialogue with ChatGPT exhibited lower performance on the transfer test. Electroencephalography data revealed that students who interacted with ChatGPT exhibited higher levels of cognitive activity, suggesting that ChatGPT could help students establish a knowledge foundation and stimulate cognitive activity. However, its strengths on promoting students. knowledge application and creativity were insignificant. Based upon the research findings, it is evident that ChatGPT cannot fully excel in fulfilling teaching tasks in the dialogue teaching in information related courses. Combining ChatGPT with traditional human teachers might be a more ideal approach. The synergistic use of both can provide students with more comprehensive learning support, thus contributing to enhancing the quality of teaching.

Published
2024

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