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2. Serious Game Analytics by Design: Feature Generation and Selection Using Game Telemetry and Game Metrics--Toward Predictive Model Construction

Author

Lu, Wenyi, Griffin, Joe, Sadler, Troy D., Laffey, James, and Goggins, Sean P.

Abstract

The construction of prediction models reflecting players' learning performance in serious games currently faces various challenges for learning analytics. In this study, we design, implement, and field test a learning analytics system for a serious game, advancing the field by explicitly showing which in-game features correspond to differences in learner performance. We then deploy and test a system that provides instructors with clear signals regarding student learning and progress in the game, which instructors could depend upon for interventions. Within the study, we examined, coded, and filtered a substantial gameplay corpus, determining expertise in the game. Mission HydroSci (MHS) is a serious game that teaches middle-school students water science. Using our logging system, designed and implemented along with game design and development, we captured around 60 in-game features from the gameplay of 373 students who completed Unit 3 of MHS in its first field test. We tested eight hypotheses during the field test and presented this paper's results to participating teachers. Our findings reveal several features with statistical significance that will be critical for creating a validated prediction model. We discuss how this work will help future research establish a framework for designing analytics systems for serious games and advancing gaming design and analytics theory.

Published
2023

3. Prophylactic donor-derived CD19 CAR-T cell infusion for preventing relapse in high-risk B-ALL after allogeneic hematopoietic stem cell transplantation

Author

Lu, Wenyi, Lyu, Hairong, Xiao, Xia, Bai, Xue, Zhang, Meng, Wang, Jiaxi, Pu, Yedi, Meng, Juanxia, Zhang, Xiaomei, Zhu, Haibo, Yuan, Ting, Wang, Bing, Jin, Xin, Cao, Xinping, Wang, Zhao, Xie, Tianle, Meng, Haotian, Stepanov, Alexey V., Gabibov, Alexander G., An, Yuxin, Sun, Rui, Zhang, Yu, Maschan, Mikhail A., Zhu, Zunmin, Zhang, Hongkai, and Zhao, Mingfeng

Published
2024
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11. Construction of GCNN-based intelligent recommendation model for answering teachers in online learning system

Author

Lu Wenyi, Wei Ting, Guo Zijun, and Ren Jianhong

Subjects
graph convolutional neural network, online learning, intelligent recommendation, Science, Electronic computers. Computer science, QA75.5-76.95
Abstract

In response to the limitations of the existing online learning system regarding the efficiency and accuracy of the question-and-answer (Q&A) teacher recommendation method, this research develops a Q&A teacher recommendation model utilizing a Graph Convolutional Neural Network. First, a time-sensitive online learning Q&A teacher recommendation model (A Time Sensitive Online Learning Q&A Teacher Recommendation Model; TSRM) is proposed to address the shortcomings that current recommendation methods ignore, i.e., the teacher’s ability to answer questions with time changes. Then, a TSRM based on Short and Long Term Interest for Answering Questions (LSTR) is proposed to address the problem that the current recommendation methods ignore, i.e., the types of questions of student users’ concerns can change. Finally, we combine the TSRM model and LSTR model to build an intelligent recommendation model for answering teachers. The conclusion is that the accuracy rate of TSRM model on the test set is 99.5%, and the recommendation success rate of LSTR model reaches 98.4%, which are better than the other two models. The above results can show that the LSTR model and TSRM model constructed by the study have high performance and can effectively perform the recommendation of answering teachers in the online learning system, thus improving the efficiency of solving students’ problem, improving students’ learning effect, and contributing to the development of university education informatization.

Published
2024
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34. Utilization of donor CLL-1 CAR-T cells for the treatment of relapsed of acute myeloid leukemia following allogeneic hematopoietic stem cell transplantation.

Author

Zhang, Meng, Zhang, Xiaomei, Wang, Jiaxi, Lu, Wenyi, Xiao, Xia, Lyu, Hairong, He, Xiaoyuan, Pu, Yedi, Meng, Juanxia, Lyu, Cuicui, Cao, Xinping, and Zhao, Mingfeng

Subjects
HEMATOPOIETIC stem cell transplantation, CYTOKINE release syndrome, ACUTE myeloid leukemia, CHIMERIC antigen receptors, PATIENTS' attitudes
Abstract

Background: Human C-type lectin-like molecule 1 (CLL-1) represents a promising therapeutic target for Chimeric antigen receptor T (CAR-T) cells therapy in the treatment of acute myeloid leukemia (AML). In this study, we aimed to evaluate the efficacy and safety profile of donor-derived CLL-1 CAR-T cells in AML patients who experienced relapsed post-transplantation. Methods: 14 AML patients who experienced relapse following allogeneic HSCT were enrolled in our clinical trial. However, 2 patients withdrew from the study due to rapid disease progression. 12 participants received donor-derived CLL-1 CAR-T cells and were categorized into 3 groups based on the dosage of infused CAR-T cells dose (Group A:0.5×106/kg, Group B:1×106/kg, Group C:1.5×106/kg). And scRNA-seq was used to reveal CLL-1 CAR-T cells dynamics in a CAR-T cells infusion products and PBMCs at the peak of expansion for patient 4. Results: CLL-1 CAR-T cells were well tolerated by all 12 patients. Cytokine Release Syndrome (CRS) was observed in all patients, with 5 patients experiencing grade ≥3. 3 patients developed cytokine release syndrome-associated encephalopathy (CRES), and 1 patient had a grade 4 severity level. All patients demonstrated a reduction in tumor burden, while 7 patients (58.33%) achieved MRD-CR and 2 patients (16.67%) reached MRD+CR. CAR-T cells expansion was detectable in all 12 patients, with the median time of peak expansion was 9 days (range: 7-11 days). In patient 4, compared to the pre-reinfusion state, CD4+ cells at the peak of expansion showed upregulation of cell killing-related genes and memory T cell-related genes (P < 0.01). Conclusions: The CLL-1 CAR-T cells therapy derived from allogeneic donors demonstrates both safety and efficacy in the management of relapsed AML following allogeneic HSCT. And adjusting the ratio of CD4+ CAR-T cells and CD8+ CAR-T cells prior to infusion may help mitigate CAR-T cell-related side effects. Clinical trial registration: https://www.chictr.org.cn/ , identifier ChiCTR2000041054. [ABSTRACT FROM AUTHOR]

Published
2025
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41. Drinking in despair: Unintended consequences of automation in China.

Author

Lu, Wenyi and Fan, Siyuan

Abstract

The side effects of technological progress on the economy have been discussed frequently, but little is known regarding its health consequences. By combining the national individual‐level panel data of alcohol drinking with the prefecture‐level robot exposure rate in China, we find that one more robot exposure rate could induce up to 2.2% points increase in the probability of problem drinking. Such a pattern of problem drinking is explained by negative emotions, which can be ascribed to job loss due to substitution, higher income vulnerability, and reduced organization participation. Further, we provide evidence that automation can incur health costs, particularly for easily substituted workers, which would exacerbate health inequality in China. This paper sheds light on the impact of automation and the social incentives of problem drinking, emphasizing the possibly heterogeneous health cost accompanied by the automation process. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Experimental research of ECW pre-ionization and assisted startup in EAST

Author

Chen, Runze, primary, Liu, Wenbin, additional, Qian, Jinping, additional, Zhang, Bin, additional, Sun, Hongjuan, additional, Luo, Zhengping, additional, Yu, Yaowei, additional, Gao, Wei, additional, Li, Miaohui, additional, Xu, Handong, additional, Wang, Mao, additional, Zuo, G Z, additional, Zhang, Ling, additional, Zhou, Ruijie, additional, Jia, Tianqi, additional, Li, Pan, additional, Wang, Wei, additional, He, Yifan, additional, Wang, Zuhao, additional, Tao, Ye, additional, Hu, Yunchan, additional, Guan, Zhongfang, additional, Lu, Wenyi, additional, Guo, YuTong, additional, and Gong, Xianzu, additional

Published
2024
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