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1. Efficient and Accurate Prompt Optimization: the Benefit of Memory in Exemplar-Guided Reflection

Author

Yan, Cilin, Wang, Jingyun, Zhang, Lin, Zhao, Ruihui, Wu, Xiaopu, Xiong, Kai, Liu, Qingsong, Kang, Guoliang, and Kang, Yangyang

Subjects
Computer Science - Computation and Language
Abstract

Automatic prompt engineering aims to enhance the generation quality of large language models (LLMs). Recent works utilize feedbacks generated from erroneous cases to guide the prompt optimization. During inference, they may further retrieve several semantically-related exemplars and concatenate them to the optimized prompts to improve the performance. However, those works only utilize the feedback at the current step, ignoring historical and unseleccted feedbacks which are potentially beneficial. Moreover, the selection of exemplars only considers the general semantic relationship and may not be optimal in terms of task performance and matching with the optimized prompt. In this work, we propose an Exemplar-Guided Reflection with Memory mechanism (ERM) to realize more efficient and accurate prompt optimization. Specifically, we design an exemplar-guided reflection mechanism where the feedback generation is additionally guided by the generated exemplars. We further build two kinds of memory to fully utilize the historical feedback information and support more effective exemplar retrieval. Empirical evaluations show our method surpasses previous state-of-the-arts with less optimization steps, i.e., improving F1 score by 10.1 on LIAR dataset, and reducing half of the optimization steps on ProTeGi.

Published
2024

2. ReCLIP++: Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation

Author

Wang, Jingyun and Kang, Guoliang

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Recent works utilize CLIP to perform the challenging unsupervised semantic segmentation task where only images without annotations are available. However, we observe that when adopting CLIP to such a pixel-level understanding task, unexpected bias (including class-preference bias and space-preference bias) occurs. Previous works don't explicitly model the bias, which largely constrains the segmentation performance. In this paper, we propose to explicitly model and rectify the bias existing in CLIP to facilitate the unsupervised semantic segmentation task. Specifically, we design a learnable ''Reference'' prompt to encode class-preference bias and a projection of the positional embedding in vision transformer to encode space-preference bias respectively. To avoid interference, two kinds of biases are firstly independently encoded into the Reference feature and the positional feature. Via a matrix multiplication between two features, a bias logit map is generated to explicitly represent two kinds of biases. Then we rectify the logits of CLIP via a simple element-wise subtraction. To make the rectified results smoother and more contextual, we design a mask decoder which takes the feature of CLIP and rectified logits as input and outputs a rectified segmentation mask with the help of Gumbel-Softmax operation. To make the bias modeling and rectification process meaningful and effective, a contrastive loss based on masked visual features and the text features of different classes is imposed. To further improve the segmentation, we distill the knowledge from the rectified CLIP to the advanced segmentation architecture via minimizing our designed mask-guided, feature-guided and text-guided loss terms. Extensive experiments on various benchmarks demonstrate that ReCLIP++ performs favorably against previous SOTAs. The implementation is available at: https://github.com/dogehhh/ReCLIP., Comment: Extended version of our CVPR 24 paper

Published
2024

5. Monosodium Urate Crystal‐Induced Pyroptotic Cell Death in Neutrophil and Macrophage Facilitates the Pathological Progress of Gout

Author

Chen, Chen, Wang, Jingyun, Guo, Yiyang, Li, Min, Yang, Kaijun, Liu, Yang, Ge, Dan, Liu, Yong, Xue, Changying, Xia, Tian, and Sun, Bingbing

Subjects
Biochemistry and Cell Biology, Biological Sciences, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Dimethyl fumarate, Gout, Macrophage, Monosodium urate crystals, Neutrophil, Neutrophil extracellular traps, Pyroptosis, Nanoscience & Nanotechnology
Abstract

Monosodium urate (MSU) crystal deposition in joints can lead to the infiltration of neutrophils and macrophages, and their activation plays a critical role in the pathological progress of gout. However, the role of MSU crystal physicochemical properties in inducing cell death in neutrophil and macrophage is still unclear. In this study, MSU crystals of different sizes are synthesized to explore the role of pyroptosis in gout. It is demonstrated that MSU crystals induce size-dependent pyroptotic cell death in bone marrow-derived neutrophils (BMNs) and bone marrow-derived macrophages (BMDMs) by triggering NLRP3 inflammasome-dependent caspase-1 activation and subsequent formation of N-GSDMD. Furthermore, it is demonstrated that the size of MSU crystal also determines the formation of neutrophil extracellular traps (NETs) and aggregated neutrophil extracellular traps (aggNETs), which are promoted by the addition of interleukin-1β (IL-1β). Based on these mechanistic understandings, it is shown that N-GSDMD oligomerization inhibitor, dimethyl fumarate (DMF), inhibits MSU crystal-induced pyroptosis in BMNs and J774A.1 cells, and it further alleviates the acute inflammatory response in MSU crystals-induced gout mice model. This study elucidates that MSU crystal-induced pyroptosis in neutrophil and macrophage is critical for the pathological progress of gout, and provides a new therapeutic approach for the treatment of gout.

Published
2023

7. Developing an Ontology of Multiple Programming Languages from the Perspective of Computational Thinking Education

Author

International Association for Development of the Information Society (IADIS), Nongkhai, Lalita Na, Wang, Jingyun, and Mendori, Takahiko

Abstract

This paper proposes the design of an ontology of multiple programming languages and give three examples to show the methodology. Our ontology aims to summarize the core of computational thinking logic by elaborating the concepts of three object-oriented programming languages in the industry: Python, Java, and C#. Therefore, the construction of the ontology lies not only on these three programming languages but also on their common concepts. This kind of ontology design facilitates the ontology extension and merging when concepts of other programming languages are added in the future. This ontology could be used to not only provide a guideline for any research work focusing on computational thinking education but also describe the common concept of visual programming tools and existing programming languages. Based on this ontology, an adaptive tutoring system intended to provide learners with personalized programming exercises, is under development.

Published
2022

8. A Method of NSA Wireless Network Quality Evaluation Based on the Associated MR of MN and SN

Author

Zheng, Yuting, Song, Chuntao, Li, Yi, Jin, Yuchao, Xu, Lexi, Zhu, Xiaomeng, Wang, Jingyun, Xiao, Tian, Cheng, Xinzhou, 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, Tan, Kay Chen, Series Editor, Wang, Yue, editor, Zou, Jiaqi, editor, Xu, Lexi, editor, Ling, Zhilei, editor, and Cheng, Xinzhou, editor

Published
2024
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9. Research on URLLC Network Energy Efficiency Algorithm Based on Reliability

Author

Li, Yi, Jin, Yuchao, Zheng, Yuting, Zhu, Xiaomeng, Wang, Jingyun, Xu, Lexi, Cheng, Xinzhou, Xiao, Tian, Cao, Lijuan, 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, Tan, Kay Chen, Series Editor, Wang, Yue, editor, Zou, Jiaqi, editor, Xu, Lexi, editor, Ling, Zhilei, editor, and Cheng, Xinzhou, editor

Published
2024
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10. Multi-scenario Integrated Algorithm for User Perception Based on 5G Management Data

Author

Jin, Yuchao, Li, Yi, Li, Deyi, Wang, Jingyun, Zheng, Yuting, Xu, Lexi, Cheng, Xinzhou, Zhu, Xiaomeng, Jia, Yuwei, 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, Tan, Kay Chen, Series Editor, Wang, Yue, editor, Zou, Jiaqi, editor, Xu, Lexi, editor, Ling, Zhilei, editor, and Cheng, Xinzhou, editor

Published
2024
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11. Research on Alarm Cleaning and Outlier Detection Algorithms of Network Data Analysis

Author

Wang, Jingyun, Li, Deyi, Jin, Yuchao, Han, Yuhui, Li, Yi, Xu, Lexi, Cheng, Xinzhou, Zhou, Shiyu, Zheng, Yuting, 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, Tan, Kay Chen, Series Editor, Wang, Yue, editor, Zou, Jiaqi, editor, Xu, Lexi, editor, Ling, Zhilei, editor, and Cheng, Xinzhou, editor

Published
2024
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12. A Method of Alarm Correlation and Root Cause Analysis in 5G Core Network

Author

Zhou, Shiyu, Liu, Xiqing, Cheng, Xinzhou, Zhao, Zhenqiao, Wang, Jingyun, Xiao, Tian, 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, Tan, Kay Chen, Series Editor, Wang, Yue, editor, Zou, Jiaqi, editor, Xu, Lexi, editor, Ling, Zhilei, editor, and Cheng, Xinzhou, editor

Published
2024
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13. Purification and Identification of Novel Antioxidant Peptides from Sheep Hemoglobin Hydrolysate and Their Protective Effect on H2O2-Induced Oxidative Injury in Caco-2 Cells

Author

MA Zehao, GENG Yukun, WANG Jingyun, LU Shiling, CAO Doudou, LIU Xingyu

Subjects
sheep hemoglobin, antioxidant peptide, purification, identification, caco-2 cells, cytoprotection, Food processing and manufacture, TP368-456
Abstract

In this study, antioxidant peptides derived from sheep hemoglobin were prepared from fresh sheep blood. Sephadex G-25 chromatography, DEAE Sephadex A-50 chromatography, reverse phase high performance liquid chromatography (RP-HPLC) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) were used to separate, purify, and identify peptides from the hydrolysate of sheep hemoglobin. The antioxidant activity of the obtained peptides was evaluated by their free radical scavenging capacity, stability against simulated gastrointestinal digestion and protective effect on H2O2-induced oxidative injury in Caco-2 cells. The results indicated that three novel antioxidant peptides, Ala-Tyr-Glu-Val-Asp (AYEVD), Phe-His-Thr-Met-Glu (FHTME) and Ser-Phe-Met-Tyr-Glu-Lys (SFMYEK), were purified and identified from the hydrolysate, with molecular masses of 595.60, 663.74 and 803.92 Da, respectively. Among them, AYEVD had the strongest scavenging capacity to scavenge 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical, and AYEVD showed stronger antioxidant activity after simulated gastrointestinal digestion. In addition, AYEVD inhibited H2O2-induced oxidative injury in Caco-2 cells, significantly reduced the accumulation of reactive oxygen species (ROS), suppressed early cell apoptosis and the formation of malondialdehyde (MDA), and increased the activity of intracellular antioxidant enzymes. Therefore, this study could provide a theoretical basis for the application of novel antioxidant peptides from sheep hemoglobin in functional foods.

Published
2024
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21. Development and Evaluation of a Visualization System to Support Meaningful E-Book Learning

Author

Wang, Jingyun, Shimada, Atsushi, Oi, Misato, Ogata, Hiroaki, and Tabata, Yoshiyuki

Abstract

This study presents an ontology-based visualization support system for e-book learners which promotes both meaningful receptive learning and meaningful discovery learning. To examine the system effectiveness, two learning modes are used: (a) reception comparison mode, where at the outset learners are shown complete versions of expert-generated topic maps; and (b) "cache-cache comparison mode," where at the first stage of learning all information concerning relations is concealed, and at the second stage learners are encouraged to actively create those relations before comparing the learner-generated and expert-generated relations. The 50 control group participants studied in reception comparison mode while the 146 experimental group participants studied in cache-cache comparison mode. Differences in learning perception and achievement between the two groups are examined, as is the effect of learner expertise level on learning mode effectiveness. Although the control group reported significantly more pressure and less satisfaction than the experimental group, no significant learning achievement differences were found between the two groups. However, in cache-cache comparison mode, the performance of learners with low prior knowledge increased more than that of learners with high prior knowledge; on the other hand, for learners with high prior knowledge, no significant effect of learning mode on learning achievement was found.

Published
2023
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25. Glue-Assisted Grinding Exfoliation of Large-Size 2D Materials for Insulating Thermal Conduction and Large-Current-Density Hydrogen Evolution

Author

Yang, Liusi, Wang, Dashuai, Liu, Minsu, Liu, Heming, Tan, Junyang, Zhou, Heyuan, Wang, Zhongyue, Yu, Qiangmin, Wang, Jingyun, Lin, Junhao, Zou, Xiaolong, Qiu, Ling, Cheng, Hui-Ming, and Liu, Bilu

Subjects
Physics - Applied Physics, Condensed Matter - Materials Science
Abstract

Two-dimensional (2D) materials have many promising applications, but their scalable production remains challenging. Herein, we develop a glue-assisted grinding exfoliation (GAGE) method in which the adhesive polymer acts as a glue to massively produce 2D materials with large lateral sizes, high quality, and high yield. Density functional theory simulation shows that the exfoliation mechanism involves the competition between the binding energy of selected polymers and the 2D materials which is larger than the exfoliation energy of the layered materials. Taking h-BN as an example, the GAGE produces 2D h-BN with an average lateral size of 2.18 {\mu}m and thickness of 3.91 nm. The method is also extended to produce various other 2D materials, including graphene, MoS2, Bi2O2Se, vermiculite, and montmorillonite. Two representative applications of thus-produced 2D materials have been demonstrated, including h-BN/polymer composites for insulating thermal conduction and MoS2 electrocatalysts for large-current-density hydrogen evolution, indicating the great potential of massively produced 2D materials., Comment: 23 pages, 5 figures

Published
2021

30. BETTER: An Automatic feedBack systEm for supporTing emoTional spEech tRaining

Author

Wynn, Adam, Wang, Jingyun, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wang, Ning, editor, Rebolledo-Mendez, Genaro, editor, Matsuda, Noboru, editor, Santos, Olga C., editor, and Dimitrova, Vania, editor

Published
2023
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31. Risk factors for mental health symptoms during the COVID-19 pandemic in ophthalmic personnel and students in USA (& Canada): a cross-sectional survey study.

Author

Pang, Yi, Li, Meng, Robbs, Connor, Wang, Jingyun, Jain, Samiksha, Ticho, Ben, Green, Katherine, and Suh, Donny

Subjects
Anxiety, COVID-19, Depression, Mental health, Ophthalmologist, Optometrist, Stress, Anxiety, COVID-19, Cross-Sectional Studies, Depression, Female, Health Personnel, Humans, Mental Health, Pandemics, Risk Factors, SARS-CoV-2, Students, United States
Abstract

BACKGROUND: The COVID-19 pandemic poses mental health challenges to frontline healthcare workers. Eye care professionals may be especially susceptible to mental health problems due to high-risk exposures to patients. Yet, no prior research has studied mental health issues among eye care professionals during the COVID-19 pandemic. OBJECTIVE: The purpose of this study was to identify risk factors for mental health problems during the COVID-19 pandemic among eye care professionals. METHODS: We conducted a cross-sectional survey study among eye care professionals and students in the United States and Canada from June 23 to July 8, 2020 during the COVID-19 pandemic. A total of 8505 eye care professionals and students received email invitations to the survey and 2134 participated. We measured mental health outcomes including symptoms of depression, anxiety, and stress using validated scales, as well as potential risk factors including demographic characteristics, state-level COVID-19 case counts, participants patient interactions, childcare responsibilities, and pre-pandemic stress levels. Linear multiple regression and logistic regression analyses were used to determine relationships between risk factors and mental health outcomes. RESULTS: We found that 38.4% of eyecare professional participants in the survey met screening threshold as probable cases of anxiety, depression, or both during the COVID-19 pandemic. Controlling for self-reported pre-pandemic stress level and state COVID-19 case daily cases, significant risk factors for depression, anxiety, and psychological stress during the COVID-19 pandemic included: being female, younger age, and being Black or Asian. Interestingly, we found two somewhat surprising protective factors against depression symptoms: more frequent interactions with patients and having a greater proportion of childcare responsibilities at home. CONCLUSIONS: This study showed a high prevalence of mental health problems and revealed disparities in mental health among eye care personnel and students: Female, younger, Black, and Asian populations are particularly vulnerable to mental health issues. These results indicate that it is critical to identify mental health issues more effectively and develop interventions among this population to address this significant and growing public health issue. The strategies and policies should be reflective of the demographic disparities in this vulnerable population.

Published
2021

47. An AI-Based Feedback Visualisation System for Speech Training

Author

Wynn, Adam T., Wang, Jingyun, Umezawa, Kaoru, Cristea, Alexandra I., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Rodrigo, Maria Mercedes, editor, Matsuda, Noburu, editor, Cristea, Alexandra I., editor, and Dimitrova, Vania, editor

Published
2022
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