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SSRN 2023年

作者： Deng, Jiawei Liu, Jiabin Li, Wenhao Geng, Xiaokang Xie, Jiaping Jeong, Sang Young Huang, Bin Zhou, Dan Wu, Feiyan Woo, Han Young Chen, Lie Nanchang University Nanchang330031 China Department of Materials Science Fudan University Songhu Road Shanghai200438 China School of Metallurgical and Chemical Engineering Jiangxi University of Science and Technology 156 Ke Jia Road Ganzhou341000 China School of Materials Science and Engineering Tianjin Key Laboratory of Molecular Optoelectronic Science Tianjin University Tianjin300072 China Key Laboratory of Jiangxi Province for Persistent Pollutants Control and Resources Recycle Nanchang Hangkong University Nanchang330063 China Department of Chemistry College of Science Korea University 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of

Developing high-performance active layer with excellent comprehensive performance is very crucial for the commercialization of organic solar cells (OSCs). Here, we demonstrate the multi-function of ferroelectric polymer polyvinylidene fluoride (PVDF) in improving the device comprehensive performance including device efficiency, stability, green-solvent large-area printing and mechanical property. Addition of PVDF not only enhances the build-in field to promote charge kinetics, but also develops robust network through strong interaction and chain entanglement between polymer donor and PVDF. Importantly, such robust network effectively protects the active layer from excessive flushing/swelling between D/A component to optimize layer-by-layer (LBL) deposition, induce a favorable vertical phase distribution and prolong the film-forming process, consequently facilitating green-solvent blade-coating printing, improving device efficiency and stability, and enhancing device mechanical flexibility. Due to the multiple advantages of PVDF, the PM6/BTP-eC9 obtains an excellent efficiency of 18.35% for BTP-eC9-based LBL devices. By blade-coating printing with green solvent, one of the highest efficiencies of 16.40% is achieved for large-area (1.21 cm2) binary device. Particularly, toughness is used to comprehensively evaluate mechanical property of OSCs, showing significant improvement with simultaneously enhanced fracture strength and tensile strain, and enabling small molecule-based system even have comparable mechanical flexibility and comprehensive performance to the all-polymer system. © 2023, The Authors. All rights reserved.

关键词： Tensile strain

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A survey of prototype and experiment for UAV communications

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science China(Information sciences) 2021年第4期64卷 5-25页

作者： Qingheng SONG Yong ZENG Jie XU Shi JIN College of Electrical and Information Engineeing Huaihua University Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province National Mobile Communications Research Laboratory Southeast University Future Network of Intelligence Institute (FNii) and School of Science and Engineering The Chinese University of Hong Kong (Shenzhen)

Unmanned aerial vehicle(UAV) communications have attracted significant attention from both academia and industry. To facilitate the large-scale usage of UAVs for various applications in practice,we provide a comprehensive survey on the prototype and experiment for UAV communications. To this end, we first provide an overview on the general architecture of the prototype and experiment for UAV communications, and then present experimental verification for air-to-ground channel models and UAV energy consumption models. Next, we discuss measurement experiments on two promising paradigms of UAV communications, namely cellular-connected UAVs and UAV-enabled aerial communication platforms. For the former, we focus on the feasibility study and address the interference mitigation issue. For UAV-enabled aerial communication platforms, we present three scenarios, namely UAV-enabled aerial base stations, UAVenabled aerial relays and UAV-enabled aerial data collection/dissemination. Finally, we point out some promising future directions for prototype and experimental measurements of UAV communications.

关键词： UAV communications prototype development channel model energy efficiency UAV-enabled communications platforms cellular-connected UAVs

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A Simplified Variant for Graph Convolutional Network Based Knowledge Graph Completion Model

A Simplified Variant for Graph Convolutional Network Based K...

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IEEE International Conference on Data science in Cyberspace (DSC)

作者： Yashen Wang Qiang Li Yi Zhang Xuecheng Zhang Zhuoya Ju Jian Sun National Engineering Laboratory for Risk Perception and Prevention (RPP) Key Laboratory of Cognition and Intelligence Technology (CIT) China Academy of Electronics and Information Technology Artificial Intelligence Institute of CETC Beijing China The State Key Laboratory for Management and Control of Complex Systems Scientific and Technological Innovation Center of ARI Institute of Automation Chinese Academy of Sciences Beijing China CETC Academy of Electronics and Information Technology Group Co. Ltd. Beijing China Khoury College of Computer Science Northeastern University U.S.A Scientific and Technological Innovation Center of ARI Beijing China Qi An Xin Technology Group Inc. Beijing China

Knowledge graphs (KGs) serve as useful resources for various applications including machine learning, data mining, and artificial intelligence. Knowledge Graph Completion (KGC) aims at reasoning over known (observed) facts and infer the missing (unobserved) relationships, to improve KG's coverage. Many recent works have laid stress on leveraging Graph Convolutional Networks (GCNs) for KGC task, which obtain good representation learning ability for graph-structured data, and have achieved satisfactory results. However, GCN-based researches continue to improve these lines of models by introducing an increasingly complex feature space. Especially, the hyper-parameter space of conventional GCN-based KGC model is too huge, resulting in low computational efficiency and excessive storage pressure. To overcome this problem, this paper investigates a simplified and generic variant for GCN-based KGC model, and shows that simple changes in the architecture of the underlying architecture (with a Subtraction Operator and an Addition Operator), can compte with state-of-the-art GCN-based models. Therefore, this paper proposes a easy-to-accomplish plug-in unit, which could be loaded into any current GCN-based KGC architectures, and help them maximize the maintenance of native model's original performance while significantly reducing parameter scale.

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Deglycosylation of shrimp tropomyosin modulates allergic reactions via immuoregulation and intestinal microbiota

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International journal of biological macromolecules 2025年第Pt 3期318卷 145258页

作者： Fan Sun Ziye Zhang Lichun Liu Fatih Özogul Zhenxing Li Hong Lin State Key Laboratory of Marine Food Processing & Safety Control College of Food Science and Engineering Ocean University of China Qingdao 266404 China. State Key Laboratory of Marine Food Processing & Safety Control College of Food Science and Engineering Ocean University of China Qingdao 266404 China. Electronic address: zhangziye@***. Department of Seafood Processing Technology Faculty of Fisheries Cukurova University Adana Turkey.

As reported, the glycans of tropomyosin (TM) affected its allergenicity. This work elucidates the regulatory role of glycans in Penaeus chinensis tropomyosin (Pen c 1) allergenicity via deglycosylation treatment. As the results, Pen c 1 is a glycoprotein with 2.625 % carbohydrate content, containing N-glycans and O-glycans. Compared with the native Pen c 1, deglycosylation treatment significantly reduced the carbohydrate content of de-N-glycosylated Pen c 1 (Pen c 1-DNG), de-O-glycosylated Pen c 1 (Pen c 1-DOG) and de-N&O-glycosylated Pen c 1 (Pen c 1-DNOG), promoted the IgG/IgE-binding capacity of deglycosylated Pen c 1, increased mast cell degranulation and allergic mediator secreation via exposing the previous hidden epitopes by glycans. Additionally, deglycosylated Pen c 1 exhibited elevated anaphylactic scores and serum allergic biomarkers in BALB/c mice, aggravated pulmonary inflammation in lung tissues, increased spleen index and Th2 cytokine secretion with unaffected Th1 responses. Moreover, deglycosylation of Pen c 1 increased the Firmicutes/Bacteroidota ratio and reduced Muribaculaceae abundance in intestinal microbiota. These findings demonstrated that removal of glycan from Pen c 1 could strengthen allergic reactions via modulating immune response and intestinal microbiota. This investigation could provide novel insights into regulating the glycan-dependent allergenicity of shrimp tropomyosin allergens via immuoregulation and intestinal microbiota.

关键词： Allergenicity Deglycosylation Tropomyosin

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Multifunctional Carbon Aerogel Granules Designed for Column Reactor for Efficient Treatment of Shale Gas Flowback and Produced Water

SSRN

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SSRN 2022年

作者： Liu, Yuanhui An, Ni Tian, Lun Yang, Ping Wang, Wei Liu, Baicang MOE Key Laboratory of Deep Earth Science and Engineering China State Key Laboratory of Hydraulics and Mountain River Engineering College of Architecture and Environment Sichuan University Sichuan Chengdu610065 China School of Chemical Engineering Sichuan University Sichuan Chengdu610065 China Yibin Institute of Industrial Technology Sichuan University Yibin Park Sichuan Yibin644000 China

Shale gas flowback and produced water (SGFPW) greatly hinders sustainable shale gas development and can cause severe environmental threats without proper treatment. Aerogel is an advanced adsorption material for treating SGFPW with complex components;nevertheless, there is little investigation on the aerogel adsorbent designed for SGFPW treatment on-site. Herein, we report a facile and green method for preparing carbon aerogel granules (CAGs) with porous biochar aerogel (PBA) incorporated on physically cross-linked chitosan matrix for high-performance treatment of SGFPW. CAGs exhibit good elasticity with Young’s modulus of 49 kPa for practical use and ultra-high water adsorption ratio of 1936.7% for fast liquid-phase mass transfer of pollutants from SGFPW to CAGs. CAGs show high removal rates for various organic pollutants in SGFPW, including ≥ 36.6% of dissolved organic carbon (DOC), ≥ 72.2% of UV254, and ≥ 92.2% of total fluorescent organic compounds within 60 min. Meanwhile, CAGs allow steady adsorption of heavy metals such as Zn (18.8–21.7%), Co (20.1–23.7%), Cu (18.4–29.8%), Pb (32.5–62.1%), and Al (54.8–58.1%) in SGFPW. The adsorption of dissolved organic pollutants in SGFPW by CAGs is mainly based on their π-π electron-donor-acceptor (EDA) interaction with the PBA carbon skeleton, while the adsorption of heavy metals based on their complexation with the N and O atoms of PBA. CAGs are suitable for the fixed bed to treat SGFPW, which displays good binary functions of filtration and adsorption, showing high potential for treating SGFPW on-site. © 2022, The Authors. All rights reserved.

关键词： Adsorption

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Causal Invariant Hierarchical Molecular Representation for Out-of-distribution Molecular Property Prediction

Causal Invariant Hierarchical Molecular Representation for O...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xinlong Wen Yifei Guo Shuoying Wei Wenhan Long Lida Zhu Rongbo Zhu Huazhong Agricultural University Wuhan China College of Informatics Huazhong Agricultural University Wuhan China Shenzhen Institute of Nutrition and Health Huazhong Agricultural University Shenzhen China Shenzhen Branch Guangdong Laboratory for Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of Agriculture and Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China Engineering Research Center of Intelligent Technology for Agriculture Ministry of Education Wuhan China Huazhong University of Science and Technology Wuhan China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Molecular representation learning is widely used in the field of drug discovery, due to its ability to accurately capture the complex features of compounds in high-dimensional space. However, existing molecular representation learning models are prone to be influenced by spurious parts during distribution shifts (also known as out-of-distribution, or OOD), which results in models mistakenly treating these spurious parts as crucial features of molecules, thereby limiting the generalization capability of the models. To tackle this issue, a novel invariant molecular representation learning model, called Causal Invariant Hierarchical Molecular Representation Graph Neural Networks (CHiMoGNN), is proposed for OOD molecular property prediction. In CHiMoGNN, a Feature Enhancement (FE) module is designed to leverage the multi-level molecular parts to enhance the expression of invariant features, thereby enhancing the model’s capability to capture key molecular information. In addition, a Cartesian Product based Environmental Impact (EI) module is adopted to generate counterfactual samples with environmental diversity. Consequently, these samples are utilized to train a classifier that maintains consistent performance across various environments. Extensive experiments on seven real-world datasets demonstrate that CHiMoGNN outperforms 9 state-of-the-art models, achieving a 5.73% increase in average ROC-AUC, and the results also show that CHiMoGNN can effectively maintain generalization in various distribution shifts. Code and datasets are available at https://***/Chertuion/CHiMoGNN.

关键词： Representation learning Limiting Codes Predictive models Feature extraction Iron Graph neural networks Drug discovery Data mining Compounds

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Quantification of two-site kinetic transport parameters of polystyrene nanoplastics in porous media

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Chemosphere 2023年第1期338卷 139506页

作者： Wu, Yuheng Cheng, Zhou Wu, Ming Hao, Yanru Lu, Guoping Mo, Cehui Li, Qusheng Wu, Jianfeng Wu, Jichun Hu, Bill X. Guangdong Provincial Research Center for Environment Pollution Control and Remediation Materials College of Life Science and Technology Jinan University Guangzhou510632 China Guangdong Provincial Academy of Environmental Science Guangzhou510045 China Key Laboratory of Surficial Geochemistry Ministry of Education Department of Hydrosciences School of Earth Sciences and Engineering Nanjing University Nanjing210023 China Guangdong Yixin Ecological Technology Co. Ltd Guangzhou510055 China Guangdong Key Laboratory of Environmental Pollution and Health School of Environment Jinan University Guangzhou510632 China School of Water Conservancy and Environment University of Jinan Jinan250022 China

In this study, a combination of column experiments, interface chemistry theory and transport model with two-site kinetics was used to systematically investigate the effect of pH on the transport of polystyrene nanoparticles (PSNPs) in porous media. The porous media containing quartz sand (QS) and three kinds of clay minerals (CMs)-kaolinite (KL), illite (IL) and montmorillonite (MT), was used in column experiments to simulate the porous media in the soil-groundwater systems. Experimental results showed that the inhibitory effect of CMs on the transport of PSNPs is weakened as pH increases. The two-dimensional (2D) surface of the DLVO interaction energy (2D-pH-DLVO) was built to calculate the interactions between PSNPs and CMs under different conditions of pH. Results suggested the inflection point of PSNP-QS, PSNP-KL, PSNP-IL and PSNP-MT are 2.42, 3.30, 2.84 and 3.69, respectively. Most importantly, there was a significant correlation between the two-site kinetic parameters related to PSNPs transport and the DLVO energy barrier (DB). The contributions of the interactions of PSNPs-PSNPs and PSNPs-minerals were determined for PSNPs transport in porous media. The critical values of pH related to the migration ability of PSNPs in porous media could be determined by a combination of column experiments, 2D-pH-DLVO and PSNPs transport model. The critical values of pH were 2.95–3.01, 3.22–3.51, 2.98–3.02, 3.31–3.33 for the migration ability of PSNPs in QS, QS + KL, QS + IL and QS + MT porous media, respectively. The stronger migration ability of PSNPs under high pH conditions is attributed to the enhanced deprotonation of the media surface and increased negative surface charge, which increases the electrostatic repulsion between PSNPs and porous media (QS, CMs). Moreover, the agglomeration of PSNPs usually is weaker and the average particle size of agglomerates is smaller under the condition of high pH, thus leading to the stronger migration ability of PSNPs under high pH c

关键词： Kinetics

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Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

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arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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一种改进的纯组分物性预测机器学习模型（英文）

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engineering 2024年第8期 61-73页

作者：曹欣羽贡铭 Anjan Tula 陈曦 Rafiqul Gani Venkat Venkatasubramanian State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Department of Physics Bard College at Simon's Rock PSE for SPEED Company Sustainable Energy and Environment Thrust The Hong Kong University of Science and Technology (Guangzhou) Department of Applied Sustainability Széchenyi István University Complex Resilient Intelligent Systems Laboratory Department of Chemical Engineering Columbia University

Information on the physicochemical properties of chemical species is an important prerequisite when performing tasks such as process design and product design. However, the lack of extensive data and high experimental costs hinder the development of prediction techniques for these properties. Moreover,accuracy and predictive capabilities still limit the scope and applicability of most property estimation methods. This paper proposes a new Gaussian process-based modeling framework that aims to manage a discrete and high-dimensional input space related to molecular structure representation with the group-contribution approach. A warping function is used to map discrete input into a continuous domain in order to adjust the correlation between different compounds. Prior selection techniques, including prior elicitation and prior predictive checking, are also applied during the building procedure to provide the model with more information from previous research findings. The framework is assessed using datasets of varying sizes for 20 pure component properties. For 18 out of the 20 pure component properties,the new models are found to give improved accuracy and predictive power in comparison with other published models, with and without machine learning.

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Eco−Friendly Recycling of Silicon−Rich Lye: Synthesis of Hierarchically Structured Calcium Silicate Hydrate and its Application for Phosphorus Removal

SSRN

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SSRN 2022年

作者： Qi, Fang Zhu, Ganyu Zhang, Yimin Li, Huiquan Li, Shaopeng Yang, Chennian Zhang, Jianbo College of Resources and Environmental Engineering State Environmental Protection Key Laboratory of Mineral Metallurgical Resources Utilization and Pollution Control Wuhan University of Science and Technology Hubei Province Wuhan430081 China Key Laboratory of Green Process and Engineering National Engineering Research Center of Green Recycling for Strategic Metal Resources Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China School of Chemical Engineering University of Chinese Academy of Sciences Beijing100049 China

Silicon−rich lye (SRL), a byproduct generated from pre−treatment of coal−based solid waste (CSW), was considered as a preponderant silicon source to prepare hierarchically nanostructured calcium silicate hydrate (C−S−H). Through the novel mild−causticization synthesis strategy, C−S−H was prepared under optimal caustic process conditions at time of 3 h, temperature of 80°C, Ca/Si of 1.25:1, and active CaO to obtain a conversion rate of Si up to 97.33% during the high−value utilization of SRL. The synthesized C−S−H possesses abundant mesoporous structure and massive exchangeable active sites, whose formation in C−S−H is advanced through an appropriate elevation regulation of caustic temperature and time. The adsorption capacity up to 119.27 mg/g for C−S−H presents outstanding removal performance toward phosphorus in the industrial wastewater than massive other previous reports. The removal mechanism of phosphorus can be identified as the surface chemisorption and formation of calcium phosphate co−precipitation. This study can provide considerable and potential guidance to the coordinated disposal between industrial solid wastes and wastewater purification. © 2022, The Authors. All rights reserved.

关键词： Phosphorus

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