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Removal of hydrophobic volatile organic compounds with sodium hypochlorite and surfactant in a co-current rotating packed bed

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Journal of Environmental Sciences 2018年第2期30卷 190-196页

作者： Wenhui Li Haidi Liu Shuangde Li Weiman Li Yunfa Chen Jiajia Gao Yaqun Cao State Key Laboratory of Multi-phase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Healthy &Intelligent Kitchen System Integration Zhejiang Ningbo 315336 China University of Chinese Academy of Sciences Beijing 100049 China

A co-current flow rotating packed bed was applied to remove volatile organic compounds（VOCs） by sodium hypochlorite（Na Cl O） and surfactant（sodium dodecyl benzene sulfonate,SDBS） from air stream. Xylene was used as a model VOC herein. The effect of p H,concentration of Na Cl O and SDBS solution, liquid flow rate, gas flow rate and rotational speed on xylene removal efficiency and overall mass transfer coefficient（KGa） were discussed. Then, a correlation for KGa of the co-current rotating packed bed was proposed by fitting the experimental data of KGa and independent variables of liquid/gas ratio,rotational speed, p H, Na Cl O concentration and treatment time, which was in good agreement with the experimental data（the deviation ≤ ± 30%）.

关键词： Co-current flow rotating packed bed VOCs Removal efficiency Overall mass transfer coefficient

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Review of seru production

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Frontiers of engineering Management 2019年第2期6卷 183-192页

作者： Yang YU Jiafu TANG State Key Laboratory of Synthetic Automation for Process Industries Department of Intelligent Systems Engineering Northeastern University Shenyang 110819 China College of Management Science and Engineering Dongbei University of Finance and Economics Dalian 116023 China

Seru production is regarded as a new production mode and derived from the production site of Japanese electronics industry. This production mode is proposed to overcome the low flexibility of the assembly line. Seru production has been successfully implemented in Japanese electronics industry, such as Canon and Sony. Benefits from Seru production include rapid response, good flexibility, and high productivity. Seru production has received extensive attention in academic research and production practice. This study reviews the background, characteristics, types, and operation of seru production. The advantages and applicable scenes of seru production are summarized from the perspective of business practice. We compare seru production and famous production modes, i.e., assembly line, cellular manufacturing, and Toyota Production System. The literature on seru production is surveyed and classified. Furthermore, future research directions are provided.

关键词： seru production production mode flexibility literature review

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Machine learning for modelling unstructured grid data in computational physics: a review

arXiv

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arXiv 2025年

作者： Cheng, Sibo Bocquet, Marc Ding, Weiping Finn, Tobias Sebastian Fu, Rui Fu, Jinlong Guo, Yike Johnson, Eleda Li, Siyi Liu, Che Moro, Eric Newton Pan, Jie Piggott, Matthew Quilodran, Cesar Sharma, Prakhar Wang, Kun Xiao, Dunhui Xue, Xiao Zeng, Yong Zhang, Mingrui Zhou, Hao Zhu, Kewei Arcucci, Rossella CEREA ENPC EDF R&D Institut Polytechnique de Paris Île-de-France France School of Artificial Intelligence and Computer Science Nantong University Jiangsu Nantong226019 China School of Mathematical Sciences Key Laboratory of Intelligent Computing and Applications Tongji University Shanghai200092 China School of Engineering and Materials Science Faculty of Science and Engineering Queen Mary University of London LondonE1 4NS United Kingdom Zienkiewicz Centre for Modelling Data and AI Faculty of Science and Engineering Swansea University SwanseaSA1 8EN United Kingdom Department of Computer Science and Engineering Hong Kong university of science and technology Hong Kong Department of Earth Science & Engineering Imperial College London LondonSW7 2AZ United Kingdom Tianjin Key Laboratory of Imaging and Sensing Microelectronics Technology School of Microelectronics Tianjin University Tianjin300072 China Centre for Health Informatics Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Department of Community Health Sciences Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Undaunted Grantham Institute for Climate Change and the Environment Imperial College London LondonSW7 2AZ United Kingdom Culham Campus AbingdonOX14 3DB United Kingdom Centre for Computational Science Department of Chemistry University College London LondonWC1E 6BT United Kingdom Concordia Institute for Information Systems Engineering Concordia University MontrealQCH3G 1M8 Canada School of Mechanical Medical and Process Engineering Faculty of Engineering Queensland University of Technology BrisbaneQLD Australia Department of Chemical Engineering University College London LondonWC1E 6BT United Kingdom

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper provides a comprehensive review of advanced ML methodologies designed to handle unstructured grid data in high-dimensional dynamical systems. Key approaches discussed include graph neural networks, transformer models with spatial attention mechanisms, interpolation-integrated ML methods, and meshless techniques such as physics-informed neural networks. These methodologies have proven effective across diverse fields, including fluid dynamics and environmental simulations. This review is intended as a guidebook for computational scientists seeking to apply ML approaches to unstructured grid data in their domains, as well as for ML researchers looking to address challenges in computational physics. It places special focus on how ML methods can overcome the inherent limitations of traditional numerical techniques and, conversely, how insights from computational physics can inform ML development. To support benchmarking, this review also provides a summary of open-access datasets of unstructured grid data in computational physics. Finally, emerging directions such as generative models with unstructured data, reinforcement learning for mesh generation, and hybrid physics-data-driven paradigms are discussed to inspire future advancements in this evolving field. © 2025, CC BY-NC-SA.

关键词： Mesh generation

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Investigation of mechanical behavior of Ag/Cu bilayer using nanoindentation test

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AIP Conference Proceedings 2024年第1期3241卷

作者： Rachid Herbazi Hassane Mes-adi Meryem Taoufiki Amine El Harfouf Khalid Amechnoue Adil Chahboun Intelligent Systems and Applications Laboratory (LSIA) EMSI Tangier Morocco Laboratory of Process Engineering Computer Science and Mathematics National School of Applied Sciences of Khouribga Sultan Moulay Slimane University Beni-Mellal Morocco Sustainable Development Laboratory Faculty of Science and Technology of Beni-Mellal Sultan Moulay Slimane University Beni-Mellal Morocco Multidisciplinary Laboratory of Research and Innovation (LaMRI) Energy Materials Atomic and Information Fusion (EMAFI) Team Polydisciplinary Faculty of Khouribga Sultan Moulay Slimane University Beni-Mellal Morocco. ERMIA National School of Applied Sciences Abdelmalek Essaadi University Tangier Morocco. ERCMN Faculty of Sciences and Technology Abdelmalek Essaadi University Tangier Morocco.

In this paper, we employed molecular dynamics (MD) simulations to model the nanoindentation process, aiming to explore the mechanical characteristics of a silver (Ag) coating film on a copper (Cu) substrate. Three distinct bilayer configurations were selected, namely Ag (100)/Cu (111), Ag (110)/Cu (111), and Ag (111)/Cu (111), with the purpose of examining the impact of heterogeneous interfaces on deformation behaviors during nanoindentation. The results demonstrate that the Ag (111)/Cu (111) bilayer exhibits a higher force during the nanoindentation process when compared to the Ag (100)/Cu (111) and Ag (110)/Cu (111) bilayers. This suggests that interfaces with a smaller mismatch in the specified crystal plane between Ag and Cu are proven to be harder. To studied the correlation between indentation velocity and the interface, we considered various values of indentation velocities ranging from 120 m/s to 200 m/s, conducting indentations on the Ag (111)/Cu (111) bilayer. The findings indicate that variations in indentation velocity significantly impact the mechanical properties of Ag (111)/Cu (111) bilayers. Both force and hardness values exhibit a significant increase as indentation velocity rises, implying that the strength of Ag/Cu bilayers is more pronounced at higher indentation velocities. These observed trends were attributed to defect and dislocation formation at the interface, as confirmed through dislocation extraction analysis (DXA).

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Size-induced axial segregation of binary mixtures in rotating drum of different lengths

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Chemical engineering Science 2025年 316卷

作者： Jielong He Yuelei Wang Liuyimei Yang Jin Xu Qijun Zheng Sida Liu Zongyan Zhou Jiangxi Provincial Key Laboratory of Particle Technology Jiangxi University of Science and Technology Nanchang 330013 China Research Centre for Intelligent Mineral Processing & Metallurgy International Institute for Innovation Jiangxi University of Science and Technology Nanchang 330013 China Ganjiang Innovation Academy Chinese Academy of Sciences Ganzhou 341000 China Centre for Simulation and Modelling of Particulate Systems Monash-Southeast University Joint Research Institute Suzhou 215123 China ARC Research Hub for Smart Process Design and Control Department of Chemical and Biological Engineering Monash University Melbourne VIC 3800 Australia

This study investigates the size-induced axial segregation of binary mixtures in rotating drums, particularly focusing on the effect of drum length. The results indicate that long drums require more time to achieve stable segregation and form more segregation bands. The core region under the free bed surface remains predominantly filled with small particles, indicating that radial segregation occurs simultaneously with the axial segregation. The angle of repose of large particle bands is consistently greater than that of small particle bands, which drives the migration of large particles. Short drums are more sensitive to changes in rotational speed, while long drums with moderate rotational speed promote the formation of segregation bands. The width of small particle bands shows an increasing–decreasing-stabilizing trend with the drum length increasing. An analysis of particle velocities reveals that the characteristics of segregation bands are closely related to the relative velocity difference between large and small particles.

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Point Tracking in Surgery–The 2024 Surgical Tattoos in Infrared (STIR) Challenge

arXiv

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arXiv 2025年

作者： Schmidt, Adam Karaoglu, Mert Asim Sinha, Soham Jang, Mingang Ha, Ho-Gun Jung, Kyungmin Gu, Kyeongmo Ullah, Ihsan Lee, Hyunki Šerých, Jonáš Neoral, Michal Matas, Jiří Zhou, Rulin He, Wenlong Wang, An Ren, Hongliang Silva, Bruno Queirós, Sandro Lima, Estêvão Vilaça, João L. Kikuchi, Shunsuke Kouno, Atsushi Matsuzaki, Hiroki Li, Tongtong Chen, Yulu Li, Ling Ma, Xiang Li, Xiaojian Zeinoddin, Mona Sheikh Wang, Xu Tandogdu, Zafer Shaw, Greg Mazomenos, Evangelos Stoyanov, Danail Chen, Yuxin Wu, Zijian Ladikos, Alexander DiMaio, Simon Salcudean, Septimiu E. Mohareri, Omid Intuitive Surgical Inc. Sunnyvale United States ImFusion GmbH Munich Germany Technical University of Munich Munich Germany NVIDIA Santa Clara United States Korea Republic of CMP Visual Recognition Group Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic Shenzhen Research Institute China The Chinese University of Hong Kong China Shenzhen University China School of Medicine University of Minho Braga Portugal ICVS/3B’s - PT Government Associate Laboratory Braga Guimarães Portugal 2Ai –School of Technology IPCA Barcelos Portugal LASI – Associate Laboratory of Intelligent Systems Guimarães Portugal Jmees Inc Japan United States School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei China Hawkes Institute University College London London United Kingdom Dept of Urology University College London Hospitals United Kingdom University of British Columbia Canada

Understanding tissue motion in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-based scanning, and subtask autonomy. Labeled data are essential to enabling algorithms in these downstream tasks since they allow us to quantify and train algorithms. This paper introduces a point tracking challenge to address this, wherein participants can submit their algorithms for quantification. The submitted algorithms are evaluated using a dataset named surgical tattoos in infrared (STIR), with the challenge aptly named the STIR Challenge 2024. The STIR Challenge 2024 comprises two quantitative components: accuracy and efficiency. The accuracy component tests the accuracy of algorithms on in vivo and ex vivo sequences. The efficiency component tests the latency of algorithm inference. The challenge was conducted as a part of MICCAI EndoVis 2024. In this challenge, we had 8 total teams, with 4 teams submitting before and 4 submitting after challenge day. This paper details the STIR Challenge 2024, which serves to move the field towards more accurate and efficient algorithms for spatial understanding in surgery. In this paper we summarize the design, submissions, and results from the challenge. The challenge dataset is available here: https://***/records/14803158, and the code for baseline models and metric calculation is available here: https://***/athaddius/STIRMetrics Copyright © 2025, The Authors. All rights reserved.

关键词： Endoscopy

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Atomically Precise Nanometer-Sized Pt Catalysts with an Additional Photothermy Functionality

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Angewandte Chemie 2024年第25期136卷

作者： Runguo Wang Dr. Dong Chen Dr. Liang Fang Dr. Wentao Fan Dr. Qing You Guoqing Bian Yue Zhou Dr. Wanmiao Gu Dr. Chengming Wang Dr. Licheng Bai Prof. Dr. Jin Li Prof. Dr. Haiteng Deng Dr. Lingwen Liao Prof. Dr. Jun Yang Prof. Dr. Zhikun Wu Key Laboratory of Materials Physics Anhui Key Laboratory of Nanomaterials and Nanotechnology CAS Center for Excellence in Nanoscience Institute of Solid State Physics HFIPS Chinese Academy of Sciences Hefei 230031 China Key Laboratory of Precision and Intelligent Chemistry University of Science and Technology of China Hefei 230026 P. R. China Institute of Physical Science and Information Technology Anhui University Hefei 230601 P.R. China State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 P. R. China Instruments' Center for Physical Science University of Science and Technology of China Hefei 230026 P. R. China Shenzhen Engineering Center for the Fabrication of Two-Dimensional Atomic Crystals Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 P. R. China Tsinghua University-Peking University Joint Center for Life Sciences School of Life Sciences Tsinghua University Beijing 100084 P.R.China MOE Key Laboratory of Bioinformatics School of Life Sciences Tsinghua University Beijing 100084 P.R.China

Atomically precise ~1-nm Pt nanoparticles (nanoclusters, NCs) with ambient stability are important in fundamental research and exhibit diverse practical applications (catalysis, biomedicine, etc.). However, synthesizing such materials is challenging. Herein, by employing the mixture ligand protecting strategy, we successfully synthesized the largest organic-ligand-protected (~1-nm) Pt 23 NCs precisely characterized with mass spectrometry and single-crystal X-ray diffraction analyses. Interestingly, natural population analysis and Bader charge calculation indicate an alternate, varying charge -layer distribution in the sandwich-like Pt 23 NC kernel. Pt 23 NCs can catalyze the oxygen reduction reaction under acidic conditions without requiring calcination and other treatments, and the resulting specific and mass activities without further treatment are sevenfold and eightfold higher than those observed for commercial Pt/C catalysts, respectively. Density functional theory and d -band center calculations interpret the high activity. Furthermore, Pt 23 NCs exhibit a photothermal conversion efficiency of 68.4 % under 532-nm laser irradiation and can be used at least for six cycles, thus demonstrating great potential for practical applications.

关键词： Pt nanocluster atomically precise ambient stability ORR photothermy

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Titelbild: Atomically Precise Nanometer-Sized Pt Catalysts with an Additional Photothermy Functionality (Angew. Chem. 25/2024)

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Angewandte Chemie 2024年第25期136卷

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Cover Picture: Atomically Precise Nanometer-Sized Pt Catalysts with an Additional Photothermy Functionality (Angew. Chem. Int. Ed. 25/2024)

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Angewandte Chemie International Edition 2024年第25期63卷

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Time Series Forecasting of New Cases and New Deaths Rate for COVID-19 using Deep Learning Methods

arXiv

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arXiv 2021年

作者： Ayoobi, Nooshin Sharifrazi, Danial Alizadehsani, Roohallah Shoeibi, Afshin Gorriz, Juan M. Moosaei, Hossein Khosravi, Abbas Nahavandi, Saeid Chofreh, Abdoulmohammad Gholamzadeh Goni, Feybi Ariani Klemeš, Jiří Jaromír Mosavi, Amir Department of Mathematics Savitribai Phule Pune University Pune411007 India Department of Computer Engineering School of Technical and Engineering Shiraz Branch Islamic Azad University Shiraz Iran Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3216 Australia Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran Faculty of Electrical and Computer Engineering Biomedical Data Acquisition Lab K. N. Toosi University of Technology Tehran Iran Department of Signal Theory Networking and Communications Universidad de Granada Spain Department of Mathematics Faculty of Science University of Bojnord Iran Sustainable Process Integration Laboratory - SPIL NETME Centre Faculty of Mechanical Engineering Brno University of Technology - VUT Brno Technická 2896/2 Brno616 69 Czech Republic Department of Management Faculty of Business and Management Brno University of Technology VUT Brno Kolejní 2906/4 Brno612 00 Czech Republic Faculty of Civil Engineering Technische Universität Dresden Dresden01069 Germany John von Neumann Faculty of Informatics Obuda University Budapest1034 Hungary School of Economics and Business Norwegian University of Life Sciences 1430 Norway

The first known case of Coronavirus disease 2019 (COVID-19) was identified in December 2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and costs to many countries. Predicting the number of new cases and deaths during this period can be a useful step in predicting the costs and facilities required in the future. The purpose of this study is to predict new cases and deaths rate one, three and seven-day ahead during the next 100 days. The motivation for predicting every n days (instead of just every day) is the investigation of the possibility of computational cost reduction and still achieving reasonable performance. Such a scenario may be encountered real-time forecasting of time series. Six different deep learning methods are examined on the data adopted from the WHO website. Three methods are LSTM, Convolutional LSTM, and GRU. The bidirectional extension is then considered for each method to forecast the rate of new cases and new deaths in Australia and Iran countries. This study is novel as it carries out a comprehensive evaluation of the aforementioned three deep learning methods and their bidirectional extensions to perform prediction on COVID-19 new cases and new death rate time series. To the best of our knowledge, this is the first time that Bi-GRU and Bi-Conv-LSTM models are used for prediction on COVID-19 new cases and new deaths time series. The evaluation of the methods is presented in the form of graphs and Friedman statistical test. The results show that the bidirectional models have lower errors than other models. Several error evaluation metrics are presented to compare all models, and finally, the superiority of bidirectional methods is determined. This research could be useful for organizations working against COVID-19 and determining their long-term plans. Copyright © 2021, The Authors. All rights reserved.

关键词： Coronavirus

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