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568 results on '"Xu, Xiaotong"'

1. Ranking protein-protein models with large language models and graph neural networks

Author

Xu, Xiaotong and Bonvin, Alexandre M. J. J.

Subjects
Quantitative Biology - Biomolecules, Computer Science - Artificial Intelligence
Abstract

Protein-protein interactions (PPIs) are associated with various diseases, including cancer, infections, and neurodegenerative disorders. Obtaining three-dimensional structural information on these PPIs serves as a foundation to interfere with those or to guide drug design. Various strategies can be followed to model those complexes, all typically resulting in a large number of models. A challenging step in this process is the identification of good models (near-native PPI conformations) from the large pool of generated models. To address this challenge, we previously developed DeepRank-GNN-esm, a graph-based deep learning algorithm for ranking modelled PPI structures harnessing the power of protein language models. Here, we detail the use of our software with examples. DeepRank-GNN-esm is freely available at https://github.com/haddocking/DeepRank-GNN-esm, Comment: 14 pages. Detailed protocol to use our DeepRank-GNN-esm software to analyse models of protein-protein complexes

Published
2024

2. 'It's like a rubber duck that talks back': Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Study

Author

Drosos, Ian, Sarkar, Advait, Xu, Xiaotong, Negreanu, Carina, Rintel, Sean, and Tankelevitch, Lev

Subjects
Computer Science - Human-Computer Interaction
Abstract

Generative AI tools can help users with many tasks. One such task is data analysis, which is notoriously challenging for non-expert end-users due to its expertise requirements, and where AI holds much potential, such as finding relevant data sources, proposing analysis strategies, and writing analysis code. To understand how data analysis workflows can be assisted or impaired by generative AI, we conducted a study (n=15) using Bing Chat via participatory prompting. Participatory prompting is a recently developed methodology in which users and researchers reflect together on tasks through co-engagement with generative AI. In this paper we demonstrate the value of the participatory prompting method. We found that generative AI benefits the information foraging and sensemaking loops of data analysis in specific ways, but also introduces its own barriers and challenges, arising from the difficulties of query formulation, specifying context, and verifying results., Comment: Ian Drosos, Advait Sarkar, Xiaotong Xu, Carina Negreanu, Sean Rintel, and Lev Tankelevitch. 2024. "It's like a rubber duck that talks back": Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Study. In Proceedings of the 3rd Annual Meeting of the Symposium on Human-Computer Interaction for Work (CHIWORK 2024)

Published
2024
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3. The Impact of Internal Control on the Quality of Corporate Governance from An Audit Perspective

Author

Xu, Xiaotong, Appolloni, Andrea, Series Editor, Caracciolo, Francesco, Series Editor, Ding, Zhuoqi, Series Editor, Gogas, Periklis, Series Editor, Huang, Gordon, Series Editor, Nartea, Gilbert, Series Editor, Ngo, Thanh, Series Editor, Striełkowski, Wadim, Series Editor, Cao, Feng-xia, editor, Singh, Satya Narayan, editor, Jusoh, Ahmad, editor, and Mishra, Deepanjali, editor

Published
2024
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5. Anisotropic gap structure and sign reversal symmetry in monolayer Fe(Se,Te)

Author

Li, Yu, Shen, Dingyu, Kreisel, Andreas, Chen, Cheng, Wei, Tianheng, Xu, Xiaotong, and Wang, Jian

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons
Abstract

The iron-based superconductors are an ideal platform to reveal the enigma of the unconventional superconductivity and potential topological superconductivity. Among them, the monolayer Fe(Se,Te)/SrTiO3(001), which is proposed to be topological nontrivial, shows interface-enhanced high-temperature superconductivity in the two dimensional limit. However, the experimental studies on the superconducting pairing mechanism of monolayer Fe(Se,Te) films are still limited. Here, by measuring quasiparticle interference in monolayer Fe(Se,Te)/SrTiO3(001), we report the observation of the anisotropic structure of the large superconducting gap and the sign change of the superconducting gap on different electron pockets. The results are well consistent with the 'bonding-antibonding' s+- wave pairing symmetry driven by spin fluctuations in conjunction with spin-orbit coupling. Our work is of basic significance not only for a unified superconducting formalism in the iron-based superconductors, but also for understanding of topological superconductivity in high-temperature superconductors.

Published
2022
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6. Development of immunoassay based on a specific antibody for sensitive detection of nicosulfuron in environment

Author

Gao, Qingqing, Huo, Jingqian, Chen, Lai, Yang, Dongchen, Zhang, Weihong, Jia, Bin, Xu, Xiaotong, Barnych, Bogdan, Zhang, Jinlin, and Hammock, Bruce D

Subjects
Agricultural, Veterinary and Food Sciences, Crop and Pasture Production, Environmental Sciences, Sulfonylurea Compounds, Herbicides, Soil, Pyridines, Antibodies, Nicosulfuron, Hapten synthesis, Polyclonal antibody, Environment contamination monitoring
Abstract

Nicosulfuron, one of the most widely used selective herbicides in corn field, can effectively control annual and perennial grass weeds, sedges, and some broadleaf weeds. The residual phytotoxicity of nicosulfuron in soil and water has become increasingly prominent. Therefore, an efficient method for detection of nicosulfuron was critical to ensure the sustainable and healthy development of agriculture and the ecological environment. In this paper, five nicosulfuron haptens which contained carboxyl group or aldehyde groups were designed and synthesized, and an indirect competitive immunoassay was developed for the first time. The assay showed an IC50 of 8.42 ng/mL and had negligible cross reactivities toward other sulfonylurea herbicides. In the spike and recovery studies, the recovery rate from soil samples was 95 %-104 %, and that of wheat roots was 92 %-98 %, which showed a good correlation with LC-MS analysis for nicosulfuron. The immunoassay was then used to quantify nicosulfuron concentration which could cause the obvious phytotoxic symptoms to wheat. Obvious symptoms of nicosulfuron phytotoxicity in wheat root was observed at the concentration of 0.068 ± 0.006 mg/kg (ELISA result) which was consistent with 0.072 ± 0.007 mg/kg obtained by LC-MS. The developed immunoassay method is an effective tool for environment contamination monitoring.

Published
2023

23. Development of a Rapid Gold Nanoparticle Immunochromatographic Strip Based on the Nanobody for Detecting 2,4-DichloRophenoxyacetic Acid

Author

Zhou, Hui, He, Cong, Li, Zhenfeng, Huo, Jingqian, Xue, Yu, Xu, Xiaotong, Qi, Meng, Chen, Lai, Hammock, Bruce D, and Zhang, Jinlin

Subjects
Biochemistry and Cell Biology, Biological Sciences, Bioengineering, Nanotechnology, 2, 4-Dichlorophenoxyacetic Acid, Gold, Herbicides, Limit of Detection, Metal Nanoparticles, Reproducibility of Results, gold nanoparticle immunochromatographic strip, 2, 4-Dichlorophenoxyacetic acid, nanobody, colorimetric card, 2, 4-Dichlorophenoxyacetic acid, Analytical Chemistry, Biochemistry and cell biology, Analytical chemistry
Abstract

2,4-Dichlorophenoxyacetic acid (2,4-D) is a systemic conductive herbicide widely used across the world. With the large-scale and continuous use of 2,4-D, its possible harm to the environment and non-target organisms has attracted increasing attention, and the construction of a stable rapid on-site detection method is particularly important. In order to achieve on-site rapid detection of 2,4-D, we developed a gold nanoparticle immunochromatographic strip method with the visual elimination value was 50 ng/mL, and a quantitative detection limit of 11 ng/mL based on a nanobody. By combing with the color snap, the immunochromatographic strip could quantitatively analyze the amounts of 2,4-D. Meanwhile, a colorimetric card based on the true color of the test strips was developed for the qualitative analysis of 2,4-D on-site. The samples (water, fruits and vegetables) with and without 2,4-D were detected by the immunochromatographic strips, and the results showed the accuracy and reliability. Thus, this assay is a rapid and simple on-site analytical tool to detect and quantify 2,4-D levels in environmental samples, and the analytical results can be obtained in about ten minutes. In addition, the nanobody technology used in this study provides an inexhaustible supply of a relatively stable antibodies that can be archived as a nanobody, plasmid or even its sequence.

Published
2022

34. Acceptance-Aware Multi-platform Cooperative Matching in Spatial Crowdsourcing

Author

Xu, Xiaotong, Liu, An, Liu, Guanfeng, Xu, Jiajie, Zhao, Lei, 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, Troya, Javier, editor, Medjahed, Brahim, editor, Piattini, Mario, editor, Yao, Lina, editor, Fernández, Pablo, editor, and Ruiz-Cortés, Antonio, editor

Published
2022
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38. Upgrading plan for conventional distribution networks considering virtual microgrid systems

Author

Xu, Xiaotong, Lu, Shaofeng, Xue, Fei, and Jiang, Lin

Subjects
621.3
Abstract

It is widely agreed that the integration of distributed generators (DGs) to power systems is an inevitable trend, which can help to solve many issues in conventional power systems, such as environmental pollution and load demand increasing. According to the study of European Liaison on Electricity grid Committed Towards long-term Research Activities (ELECTRA), in the future, the control center of power systems might transfer from transmission networks to distribution networks since most of DGs will be integrated to distribution networks. However, the infrastructure of conventional distribution networks (CDNs) has not enough capabilities to face challenges from DG integration. Therefore, it is necessary to make a long-term planning to construct smart distribution networks (SDNs). Although many planning strategies are already proposed for constructing SDNs, most of them are passive methods which are based on traditional control and operating mechanisms. In this thesis, an active planning framework for upgrading CDNs to SDNs is introduced by considering both current infrastructure of CDNs and future requirements of SDNs. Since conventional centralised control methods have limited capabilities to deal with huge amount of information and manage flexible structure of SDNs, virtual microgrids (VMs) are designed as basic units to realise decentralised control in this framework. Based on the idea of cyber-physical-socioeconomic system (CPSS), the structure and interaction of cyber system layer, physical system layer as well as socioeconomic system layer are considered in this framework to improve the performance of electrical networks. Since physical system layer is the most fundamental and important part in the active planning framework, and it affects the function of the other two layers, a two-phase strategy to construct the physical system layer is proposed. In the two-phase strategy, phase 1 is to partition CDNs and determine VM boundaries, and phase 2 is to determine DG allocation based on the partitioning results obtained in phase 1. In phase 1, a partitioning method considering structural characteristics of electrical networks rather than operating states is proposed. Considering specific characteristics of electrical networks, electrical coupling strength (ECS) is defined to describe electrical connection among buses. Based on the modularity in complex network theories, electrical modularity is defined to judge the performance of partitioning results. The effectiveness of this method is tested in three popular distribution networks. The partitioning method can detect VM boundaries and partitioning results are in accord with structural characteristics of distribution networks. Based on the partitioning results obtained in phase 1, phase 2 is to optimise DG allocation in electrical networks. A bi-level optimisation method is proposed, including an outer optimisation and an inner optimisation. The outer optimisation focus on long-term planning goals to realise autonomy of VMs while the inner optimisation focus on improving the ability of active energy management. Both genetic algorithm and probabilistic optimal power flow are applied to determine the type, size, location and number of DGs. The feasibility of this method is verified by applying it to PG&E 69-bus distribution network. The operation of SDNs with VMs is a very important topic since the integration of DGs will lead to bidirectional power flow and fault current variation in networks. Considering the similarity between microgrids and VMs, a hybrid control and protection scheme for microgrids is introduced, and its effectiveness is tested through Power Systems Computer Aided Design (PSCAD) simulation. Although more research is needed because SDNs are more complicated than microgrids, the hybrid scheme has great potential to be applied to VMs.

Published
2019
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