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1,011 results on '"Liang, Xiaolong"'

1. Field Knowledge as a Dual to Distributed Knowledge: A Characterization by Weighted Modal Logic

Author

Liang, Xiaolong and Wáng, Yì N.

Subjects
Computer Science - Logic in Computer Science, Mathematics - Logic
Abstract

The study of group knowledge concepts such as mutual, common, and distributed knowledge is well established within the discipline of epistemic logic. In this work, we incorporate epistemic abilities of agents to refine the formal definition of distributed knowledge and introduce a formal characterization of field knowledge. We propose that field knowledge serves as a dual to distributed knowledge. Our approach utilizes epistemic logics with various group knowledge constructs, interpreted through weighted models. We delve into the eight logics that stem from these considerations, explore their relative expressivity and develop sound and complete axiomatic systems.

Published
2024

4. Epistemic Logic over Similarity Graphs: Common, Distributed and Mutual Knowledge

Author

Liang, Xiaolong and Wáng, Yì N.

Subjects
Computer Science - Logic in Computer Science, Computer Science - Computational Complexity, Mathematics - Logic
Abstract

In this paper, we delve into the study of epistemic logics, interpreted through similarity models based on weighted graphs. We explore eight languages that extend the traditional epistemic language by incorporating modalities of common, distributed, and mutual knowledge. The concept of individual knowledge is redefined under these similarity models. It is no longer just a matter of personal knowledge, but is now enriched and understood as knowledge under the individual's epistemic ability. Common knowledge is presented as higher-order knowledge that is universally known to any degree, a definition that aligns with existing literature. We reframe distributed knowledge as a form of knowledge acquired by collectively leveraging the abilities of a group of agents. In contrast, mutual knowledge is defined as the knowledge obtained through the shared abilities of a group. We then focus on the resulting logics, examining their relative expressivity, semantic correspondence to the classical epistemic logic, proof systems and the computational complexity associated with the model checking problem and the satisfiability/validity problem. This paper offers significant insights into the logical analysis and understanding of these enriched forms of knowledge, contributing to the broader discourse on epistemic logic.

Published
2023

10. Correlation of interferon-induced gene IFIT1 with immune infiltration and prognosis in ovarian cancer

Author

WANG Ruiwei, LI Fengjie, and LIANG Xiaolong

Subjects
ovarian cancer, ifit1, bioinformatic analysis, immune infiltration, neutrophils, Medicine (General), R5-920
Abstract

Objective To analyze the correlation of interferon-induced protein with tetratricopeptide repeats 1 (IFIT1) with immune infiltration and prognosis of ovarian cancer (OC). Methods GEO database was employed to select the tumor immune related genes, and Kaplan-Meier and Prognoscan databases were used to identify the genes significantly associated with OC prognosis. The differential expression of IFIT1 between OC tissue and normal tissue were confirmed with GEPIA, Human Protein Atlas, and Timer databases. The expression level of IFIT1 in OC tissues with different grades and stages were analyzed in the UALCAN database. In addition, based on David database, GO enrichment analysis was used to analyze the interacting genes and proteins of IFIT1 in the String and Genemania databases. Timer and Tisidb databases verified the correlation between IFIT1 and immune cells mutually. Finally, after IFIT1 knockdown xenograft model was constructed based on lentiviral vector of IFIT1 shRNA, the tumor growth was observed in the transplanted nude mice, and infiltration of neutrophils was observed with immunohistochemical assay. Results FIT1, a tumor immune gene, selected from the GEO database, Kaplan-Meier and Prognoscan databases, was negatively correlated with the OC prognosis. GEPIA, Human Protein Atlas, Timer database, and UALCAN database indicated that the expression level of IFIT1 was significantly higher in the OC tissues than the normal ovarian tissues, and had no obvious correlation with tumor stage and grade. Analysis in String, Genemania, and David database found the interaction genes and proteins of IFIT1 were enriched in activation of 2'-5' oligonucleotide synthase, virus defense, and innate immunity, and other processes. The Timer database presented that IFIT1 was positively correlated with the infiltration of CD8+T cells, B cells, dendritic cells, neutrophils, and macrophage in OC, with neutrophils having the most significant correlation. Tisidb and GSCA also confirmed the positive correlation between IFIT1 and neutrophil infiltration in OC (P < 0.05). RT-qPCR and Western blotting confirmed that IFIT1 knockdown resulted in suppressed tumor growth in OC cells xenograft nude mice (P < 0.05) and reduced neutrophil infiltration in the xenograft tissues. Conclusion IFIT1 may influence the malignant progression of OC by promoting neutrophil infiltration.

Published
2024
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31. An EBV-related CD4 TCR immunotherapy inhibits tumor growth in an [HLA-DP5.sup.+] nasopharyngeal cancer mouse model

Author

Wang, Chenwei, Chen, Jiewen, Li, Jingyao, Xu, Zhihong, Huang, Lihong, Zhao, Qian, Chen, Lei, Liang, Xiaolong, Hu, Hai, Li, Gang, Xiong, Chengjie, Wu, Bin, You, Hua, Du, Danyi, Wang, Xiaoling, Li, Hongle, Wang, Zibing, and Chen, Lin

Subjects
T cells -- Growth, Nasopharyngeal cancer -- Drug therapy, Mass spectrometry -- Health aspects -- Analysis, Immunotherapy -- Analysis -- Health aspects, Antigens -- Growth, Cancer -- Care and treatment -- Drug therapy, Peptides -- Analysis -- Health aspects -- Growth, Company growth, Health care industry
Abstract

Adoptive transfer of T cell receptor-engineered T cells (TCR-T) is a promising strategy for immunotherapy against solid tumors. However, the potential of [CD4.sup.+] T cells in mediating tumor regression has been neglected. Nasopharyngeal cancer is consistently associated with EBV. Here, to evaluate the therapeutic potential of CD4 TCR-T in nasopharyngeal cancer, we screened for CD4 TCRs recognizing EBV nuclear antigen 1 (EBNA1) presented by HLA-DP5. Using mass spectrometry, we identified [EBNA1.sub.567-581], a peptide naturally processed and presented by HLA-DP5. We isolated TCR135, a CD4 TCR with high functional avidity, that can function in both [CD4.sup.+] and [CD8.sup.+] T cells and recognizes HLA-DP5-restricted [EBNA1.sub.567-581]. TCR135-transduced T cells functioned in two ways: directly killing [HLA-DP5.sup.+][EBNA1.sup.+] tumor cells after recognizing EBNA1 presented by tumor cells and indirectly killing HLA-DP5-negative tumor cells after recognizing EBNA1 presented by antigen- presenting cells. TCR135-transduced T cells preferentially infiltrated into the tumor microenvironment and significantly inhibited tumor growth in xenograft nasopharyngeal tumor models. Additionally, we found that 62% of nasopharyngeal cancer patients showed 50%-100% expression of HLA-DP on tumor cells, indicating that nasopharyngeal cancer is well suited for CD4 TCR-T therapy. These findings suggest that TCR135 may provide a new strategy for EBV-related nasopharyngeal cancer immunotherapy in [HLA-DP5.sup.+] patients., Introduction Recent advances in immunotherapy have shown promising results in the treatment of solid tumors. Adoptive transfer of T cell receptor- engineered (TCR-engineered) T cells (TCR-T) is a promising approach [...]

Published
2024
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48. Adversarial Defense by Suppressing High-frequency Components

Author

Zhang, Zhendong, Jung, Cheolkon, and Liang, Xiaolong

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Recent works show that deep neural networks trained on image classification dataset bias towards textures. Those models are easily fooled by applying small high-frequency perturbations to clean images. In this paper, we learn robust image classification models by removing high-frequency components. Specifically, we develop a differentiable high-frequency suppression module based on discrete Fourier transform (DFT). Combining with adversarial training, we won the 5th place in the IJCAI-2019 Alibaba Adversarial AI Challenge. Our code is available online., Comment: 3 pages. This paper is a technical report of the 5th place solution in the IJCAI-2019 Alibaba Adversarial AI Challenge. This paper has been accepted by the corresponding workshop

Published
2019

50. The third Intensive Care Bundle with Blood Pressure Reduction in Acute Cerebral Haemorrhage Trial (INTERACT3): an international, stepped wedge cluster randomised controlled trial

Author

Robinson, Thompson, Miranda, J. Jaime, Anderson, Craig S., You, Chao, Song, Lili, Parry-Jones, Adrian, Sprigg, Nikola, Durrans, Sophie, Harris, Caroline, Bamford, Ann, Smith, Olivia, Herbert, Robert, Chen, Christopher, Whiteley, William, Hu, Rong, Billot, Laurent, Li, Qiang, Mysore, Jayanthi, Hu, Xin, Zhang, Yao, Liu, Feifeng, Sakamoto, Yuki, You, Shoujiang, Han, Qiao, Crutzen, Bernard, Li, Yunke, Cheung, Emily, Jan, Stephen, Liu, Hueiming, Ouyang, Menglu, Sun, Lingli, Chu, Honglin, Anjum, Anila, Gonzalez Mc Cawley, Francisca, Del Rio, Alejandra, Rimoli, Bruna, Cerantola, Rodrigo, Jeevarajah, Thanushanthan, Kannangara, Madhushani, Joseph, Andrene, Nanayakkara, Chamath, Chen, Xiaoying, Malavera, Alejandra, Zhang, Chunmiao, Yang, Zhao, Li, Brook, Meng, Zhuo, Liu, Leibo, Ning, Yi, Dong, Le, Armenis, Manuela, Lim, Joyce, Monaghan, Helen, Ma, Lu, Li, Xi, Luo, Rui, Cheng, Guojuan, Dong, Yilin, Liu, Ziqin, Wang, Shuihong, Zhang, Ying, Cheng, Jipeng, Shi, Hui, Li, Wenjing, Mou, Langming, Yi, Ping, Chen, Chen, Chen, Xue, 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Fuhua, Zhang, Xueguang, Xu, Jianguo, Zhang, Mingsen, Wang, Bin, Ma, Yiming, Jiang, Donglin, Zhou, Jun, Liu, Cong, Nie, Wenhong, Li, Mingguo, Tian, Tao, Li, Yong, He, Mingfang, Tu, Xiaolong, Wu, Zhengjun, Liu, Hong, Zhong, Dongsheng, Jiang, Rongcai, Sun, Jian, Tian, Ye, Wei, Yingsheng, An, Shuo, Wei, Pingbo, Luo, Le, Lin, Bin, Liu, Gang, Wen, Yan, Cai, Qiang, Chen, Qianxue, Lei, Pan, Li, Zhiyang, Zhang, Meifang, He, Jiaquan, Chen, Yan, Liu, Jun, Liu, Xinghai, Li, Junyan, Chen, Min, Wang, Jing, Zhou, Bingzhi, Ye, Baichun, Zhang, Jiancheng, Zhang, Manyuan, Pan, Xuming, Yu, Xiaoxiang, Xu, Jian, Xiao, Qingbao, Wang, Yuefei, Tao, Liang, Shi, Lin, Zheng, Niandong, You, Guoliang, Lei, Bo, Chen, Shu, Wu, Honggang, Hu, Jin, Zhao, Jianlan, Yu, Jian, Yuan, Qiang, Du, Zhuoying, Tang, Xielin, Li, Qianke, Liu, Shenghua, Yang, Feilong, Xiao, Kui, Luo, Chao, Wang, Guang, Che, Xudong, Teng, Zhipeng, Wan, Wenwu, Li, Jun, Liu, Yu, Fan, Mingbo, Zhang, Tao, Cai, Lun, Ma, Yuan, Ma, Zhifeng, Li, Bin, He, Linlin, Li, Jinghui, Zhang, Weibing, Zhang, Shuxin, Zhang, Hongzhen, Dai, Yingguang, Lei, Jun, Mao, Lei, Huang, Yiyang, Zhou, Zhi, Chen, Ping, Chen, Fang, Wei, Pan, Li, Tiangui, Chen, Honglin, Zeng, Mengfei, Mou, Kejie, Xue, Jun, Jiang, Yong, Tang, Xiaoping, Chen, Tao, Zhang, Yalan, Xu, Yanbing, Gu, Yuchen, Chen, Lei, Zhao, Yujun, Yang, Bin, Kuai, Peng, Wang, Xi, Yang, Yuwang, Hu, Xueling, Zhang, Huitian, Yang, Yintao, Wang, Weifeng, Zhang, Junyi, Cheng, Wei, Zhang, Xiaoxue, Ma, Xiaowen, He, Qin, Zhang, Li, Gao, Rong, Liu, Huixiang, Ye, Jingwei, Xu, Ping, Wu, Xin, Yuan, Yuan, Zou, Peng, Zhang, Zhen, Cheng, Jiyong, Zhou, Zhangming, Zeng, Yijun, Liang, Zhang, Du, Deming, Yu, Shui, Cao, Yongjun, Xu, Jiaping, Huang, Zhichao, Chen, Dongqin, Xiao, Wenfeng, Zhu, Li, Yuan, Miao, Wang, Yuhai, Shi, Dongliang, Hu, Xu, Xiang, Dingchao, Shi, Like, Wang, Hongqin, Yang, Liu, Miao, Wang, Hu, Yiyi, Zhao, Yuchun, Hu, Xi, Zhou, Weiduo, Sun, Chao, Tang, Dong, Yao, Kun, You, Jin, Chen, Shishi, Yao, Jianmin, Li, Huanmei, Liu, Jinmei, Bai, Ailin, Yi, Yong, Deng, Qingshan, Luo, Peng, Wang, Han, Jiang, Jingcheng, Yang, Qingwei, He, Shunpo, Wang, Jun, Chen, Yu, He, Hua, Deng, Yuyang, Cao, Zhikai, Yi, Xuxia, Luo, Jinbiao, Luo, Shuang, Gong, Min, Liu, Li, Gao, Xuejun, Liu, Jia, Wu, Li'e, Zhang, Jia, Sun, Hongying, Li, Xinhui, Jia, Lu, Wu, Jianbing, Zhang, Jie, Zhang, Huajun, Du, Chunfu, Li, Shun, Yang, Xiaobin, He, Jie, Liao, Lei, Zhou, Gezhi, Dong, Wentao, Chen, Yunxiang, Lin, Xiaofeng, Shui, Xujian, Zhang, Peng, Zhao, Yuan, Yang, Hongli, Zhao, Wenbin, Zhang, Xiaoyi, Chen, Jincao, Wu, Qian, Dai, Xuan, Tang, Baogui, Wang, Yinjuan, Liu, Tao, Zhang, Haixia, Duan, Faliang, Luo, Ming, Jiao, Qingfang, Lei, Guoliang, Wang, Dong, Song, Chunwang, Tan, Haopeng, Ye, Feng, Qin, Xinghu, Liang, Xiaolong, Liu, Junling, Yang, Lang, Yang, Jie, Lin, Yapeng, Yang, Qian, Ma, Xuntai, Qi, Yinkuang, Pan, Baogen, Jiang, Caixia, Ye, Zhanying, Dong, Ce, Yue, Xiongfei, Yang, Xiaopeng, Maimaitiyiming, Tuoheti, 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Karunathilake, Kanchana, Gayan, Isuru, Wijenayake, Kaminda, Gunasekara, Hasitha, Vidyarathne, Jagath, Keshavaraj, Ajantha, Janarthanan, Kanagasabapathy, Gerald Jeevathasan, Arhivalaky, Sivamainthan, Sivaram, John Priyanth, Mathyamuthan, John Priyanth, Abirami, Rajendiran, Thambippillai, Alwis, Sanjeewa, Gunasekare, Nushara, Liyanarachchi, Vasundara, Dissanayake, Athula, Uluwattage, Wimalasiri Mewa, Ratnayake, Gimhani, Rajinee, Charika, Jayawardana, Sakura, Peiris, Janaka, Wicramasinghe, Ranjith, Fernando, Chamila, Abbas, Jessie, Withanage, Nethmini, Bandara, Makaranda, Mai, Duy Ton, Nguyen, Van Chi, Dao, Viet Phuong, Vuong, Xuan Trung, Nguyen, Tien Dung, Dinh, Trung Hieu, Phan, Ha Quan, Bui, Quoc Viet, Phung, Dinh Tho, Pham, Quang Tho, Pham, Dinh Dai, Do, Duc Thuan, Dang, Phuc Duc, Dang, Minh Duc, Nguyen, Dang Hai, Nguyen, Thi Phuong Nga, Nguyen, Quoc Huy, Pham, Quoc Dai, Chau, Quoc Vinh, Tai, Vinh Thy Van, Le, Tran Vinh, Le, Cong Tri, Tran, Ha Mai Khuong, Nguyen, Huu Khanh, Ngyen, Hoang Minh Thao, Vo, Duc Chien, Nguyen, Thai My Phuong, Tran, Trung Thanh, Vo, Thi Hanh Vi, Cao, Hao Nhien, Nguyen, Ba Thang, Le, Thi Ngoc Suong, La, Thien Duc, Pham, Chi Duc, Thai, Huy, Muñoz-Venturelli, Paula, de Silva, Asita, Thang, Nguyen Huy, Wahab, Kolawole W, Pandian, Jeyaraj D, Pontes-Neto, Octavio M, Shi, Haiping, Wang, Xia, Zhao, Yang, Li, Hao, Liu, Yi, Jiang, Yan, Wu, Bo, Liu, Ming, and Anderson, Craig S

Published
2023
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