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作者： Zhilei Zhang Yichen Zhang Shuting Gong Shouyong Tang rongchao Cheng Zheng Yang Han ren Hong Yang CNPC Engineering Technology R&D Company Limited Zhejiang Oilfield Company Natural gas Exploration & Development Department

As an important slurry material for water-based drilling fluids, montmorillonite has been widely used in oil drilling because of its excellent properties such as expansibility, dispersion and suspension, slurry making, cation exchange and adsorption. However, at a certain temperature and pressure, montmorillonite will transform into illite, chlorite and other minerals, changing the properties of drilling fluids. In order to systematically summarize and sort out the current research status of montmorillonite transformation, this study focused on the research progress of montmorillonite transformation into other minerals under different temperature and pressure conditions, and summarized the transformation mechanism of montmorillonite. The montmorillonite is transformed into illite by adding K+ in the interlayer spacing and removing Si by adding Al to tetrahedron structure. The conversion of montmorillonite to chlorite by adding Fe, Mg ions into the octahedron, and Si in the tetrahedron is replaced by Al. The precipitated brucite layer is connected with the upper and lower layers.

关键词： red research progress of clay transformation in drilling fluids

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Machine Learning with deep Learning Approach for Cyber Security Threats Prevention Model

Machine Learning with Deep Learning Approach for Cyber Secur...

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2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Jagan, S. Pokhariyal, rajesh Mahajan, Kirti deepika, Ch L N Sudha, P. deva dutta, Abhradita Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Bharati Vidyapeeth Deemed University Institute of Management & Entrepreneurship Development Department of Information Technology Pune411030 India Department : SOCC Kluniversity 522 502 India St. Martins Engineering College Department of Computer Science and Engineering Telangana Secunderabad India New Horizon College of Engineering Department of Mechanical Engineering Bangalore560103 India

ISBN: (纸本)9798350319200

The need for effective cybersecurity solutions has never been greater than in today's world of constant digitalization and interconnection. This study explores the use of deep learning to the creation of a model for preventing cyber security threats using machine learning. The model is meant to successfully identify and prevent cyber-attacks by analysing network traffic and system behaviour using a convolutional neural network (CNN) linked with variationalautoencoders (VAEs). This study's findings illustrate the model's competency in threat recognition with a high degree of accuracy, precision, and recall. Actively monitoring and evaluating network data, providing automatic threat identification and response, further demonstrates its usefulness when used in the real world. This work sets the path for future developments in quantum-resistant encryption, adversarial machine learning studies, deep learning architectures, autonomous cybersecurity systems, explainable AI, and global threat intelligence cooperation. These new approaches have great potential for paving the way towards a more secure and resilient cyber future. © 2023 IEEE.

关键词： Convolutional Neural Network (CNN) deep Learning Machine Learning Network Traffic Analysis Quantum-resistant Cryptography real-time Monitoring Threat Prevention Variational Autoencoders (VAEs)

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Exploring the Potential of deep Learning in Parkinson's disease drug discovery

Exploring the Potential of Deep Learning in Parkinson's Dise...

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Advances in Computing research on Science Engineering and technology (ACrOSET), International Conference on

作者： ravula Arun Kumar M. Ponnrajakumari M ravi Kumar A. Nirisha raja Chandrasekaran Tejashree Tejpal Moharekar Department of CSE Vardhaman College of Engineering Telanagana India Department of ECE Velammal Engineering College Chennai India Department of CSE KL University Vijayawada India Department. of CSIT MLR Institute of Technology Telangana India Department of ECE Sagunthala R&D Institute of Science and Technology Chennai India Yashwantrao Chavan School of Rural Development Shivaji University Kolhapur India

ISBN: (数字)9798350388800

ISBN: (纸本)9798350388817

Complex and complex neurological illnesses like Parkinson's disease (Pd) are difficult to investigate. This publication introduces “Neural Pathway Profiling for Parkinson's disease drug discovery.” It leverages cutting-edge deep learning. GCNs explain molecular interactions, LSTMs examine temporal sequences, and VAEs learn by forming new patterns. Our research uses genes, proteins, and clinical data to explain how Parkinson's disease's various components interact in complex ways. LSTMs illustrate how clinical data is connected to time, GCNs reveal how molecules interact in biological networks, and VAEs discover hidden chemical structures for generative learning. The blended design reveals key brain connections and Parkinson's disease therapeutic targets.

关键词： drugs deep learning Heating systems Ethics Accuracy Sensitivity Parkinson's disease Computational modeling Neural pathways drug discovery

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Initial Study on Applicability of Thermal Imaging for Microplastics Identification in Aquatic Medium

SSRN

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SSrN 2023年

作者： Manikandan, E. Pravin, Sheena Christabel Kiruthika, V. Gopikashree, S. Chandan, Sai Gokul H.T. Karthigeyan, K.A. Shoba, S. Centre for Innovation and Product Development Vellore Institute of Technology Chennai Campus Chennai India School of Electronics Engineering Vellore Institute of Technology Chennai Campus Chennai India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Centre for Advanced Data Science Vellore Institute of Technology Chennai Campus Chennai India

Owing to plastic's durability, plastic waste management is challenging. The current issue is that millions of tonnes of plastic end up in the ocean, possibly resulting in microplastic pollution and becoming the most prevalent underwater contaminant. Efficient identification of microplastic pollution is a scientific challenge because as the size of the particles decreases, it becomes more difficult to recognize and detect them. In this work, we demonstrate a deep learning-based approach for microplastics identification. The dataset is acquired using the thermal imaging technique. data collection is followed by a data pre-processing step and finally, a classification step. The reported best accuracy, 97.42%, is achieved using the CNN model. The proposed approach allows for the deployment of increasingly diversified models as deep-learning models are still progressing. © 2023, The Authors. All rights reserved.

关键词： data handling

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Effect of Surface Activation on the Corrosion resistance of a MAO/Ni-P Composite Coating on LZ91 Magnesium Alloy

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Journal of the Taiwan Institute of Chemical Engineers 2023年第1期147卷

作者： Chen, Chi-An Lee, Jeou-Long Jian, Shun-Yi Lee, Chia-Yu Ger, Ming-der Combination Medical Device Technology Division Medical Devices R&D Service Department Metal Industries Research & Development Centre Kaohsiung802 Taiwan Department of Chemical and Materials Engineering Lung Hwa University of Science and Technology Taoyuan330 Taiwan Department of Material Engineering Ming Chi University of Technology New Taipei City Taiwan Center for Plasma and Thin Film Technologies Ming Chi University of Technology New Taipei Taiwan Graduate School of Defense Science Chung Cheng Institute of Technology National Defense University Taoyuan Taiwan Department of Chemical & Materials Engineering Chung Cheng Institute of Technology National Defense University Taoyuan Taiwan System Engineering and Technology Program National Chiao Tung University Hsin-Chu Taiwan

Background: LZ91 Magnesium alloy with a dual-phase structure has improved mechanical properties and a low density of about 1.48 g/cm3 but their limited resistance to corrosion limits their application. Therefore, it is a great challenge to increase the stability of LZ91 alloys under corrosive factors and environments. Methods: This study uses micro-arc oxidation (MAO) and an electroless nickel-phosphorus (Ni-P) plated composite film to increase the corrosion resistance of LZ91 magnesium alloy. Before electroless Ni-P plating, the MAO layers are activated by palladium catalysts at different pH values to produce composite coatings. SEM, EdS and Image J are used to determine the surface properties and elemental composition of the samples. The corrosion resistance is measured using a potentiodynamic polarization test and electrochemical impedance spectroscopy (EIS) in 3.5 wt.% NaCl solution. Findings: The results show that the MAO coating is activated by an acid catalyst and the surface is obviously corroded. The electroless Ni-P plating grows into the MAO coating and the substrate corrodes. Therefore, corrosive medium (chloride ion) easily enter to the substrate and pitting corrosion occurred. On the contrary, activation by a neutral catalyst (pH=7) maintains the original structure of the MAO coating and provides a good bonding interface for the Ni-P coating. Form the potentiodynamic analysis can be finds that the corrosion potential for the neutral catalyst treated sample is -0.35V and the corrosion current density value is 1.77×10−6 A/cm2, so the corrosion characteristic become better than the acid catalyst treated samples. In terms of the long-term resistance after 48 h, EIS analysis shows that the resistance value remains at about 7.6×104 Ω•cm2. A composite coating that is compact and with excellent resistance to corrosion resistance is produced, which provides better protection for LZ91 magnesium alloys. © 2023 Taiwan Institute of Chemical Engineers

关键词： Corrosion resistance

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A Sample-driven Selection Framework: Towards Graph Contrastive Networks with reinforcement Learning 24

A Sample-driven Selection Framework: Towards Graph Contrasti...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Zheng, Xiangping Hao, Xiuxin Wu, Bo Bao, Xigang Zhang, Xuan Li, Wei Liang, Xun College of Computer Science and Technology Harbin Engineering University Heilongjiang Harbin China Modeling and Emulation in E-Government National Engineering Laboratory Heilongjiang Harbin China Qingdao Innovation and Development Base of Harbin Engineering University Shandong Qindao China R&d and External Relations Department Xiangjiang Laboratory Hunan Changsha China School of Artificial Intelligence and Advanced Computing Hunan University of Technology and Business Hunan Changsha China Changsha Artificial Intelligence Social Laboratory Hunan Changsha China School of Information Renmin University of China Beijing China Guanghua School of Management Peking University Beijing China Harvest Fund Management Co. Ltd. Beijing China

ISBN: (纸本)9798400706868

Graph Contrastive Learning (GCL) aims to address the issue of label scarcity by leveraging graph structures to propagate labels from a limited set of labeled data to a broader range of unlabeled data. However, recent GCL methods often rely on uniform negative sample selection schemes, such as random sampling, which results in suboptimal performance. To tackle this challenge, we present GraphSaSe, a tailored approach specifically designed for graph contrastive learning. Our method introduces an innovative reinforcement learning strategy that translates the divergence between positive pairs into a reinforcement reward mechanism. This mechanism generates selection probabilities to dynamically guide the selection of negative samples during training. We explore the impact of negative sample selection at different stages in graph contrastive learning and analyze how the discount factor affects the reward mechanism in reinforcement learning. These studies enhance the overall performance of the model. Comprehensive experimentation across diverse real-world datasets validates the effectiveness of our algorithm, positioning it favorably against contemporary state-of-the-art methodologies. © 2024 ACM.

关键词： Contrastive Learning

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MoS2-coupled coniferous ZnO for photocatalytic degradation of dyes

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Journal of the Taiwan Institute of Chemical Engineers 2023年 142卷

作者： Kao, Li-Heng Chuang, Kao-Shu Catherine, Hepsiba Niruba Huang, Jui-Hsiung Hsu, Hsiang-Jhih Shen, Yu-Chin Hu, Chechia Department of Chemical and Materials Engineering National Kaohsiung University of Science and Technology Kaohsiung807 Taiwan Department of Green Material Technology Green Technology Research Institute CPC Corporation Kaohsiung City811 Taiwan Department of Chemical Engineering National Taiwan University of Science and Technology Daan Dist. Taipei City106 Taiwan R&D center for Membrane Technology Chung Yuan Christian University Chungli Dist. Taoyuan City320 Taiwan

Background: The modification of ZnO through structural engineering and coupling with different 2d materials as a photocatalyst has received considerable attention. Few studies have reported the coupling of 2d material, MoS2, with ZnO for photocatalysis. However, no study has been conducted on MoS2-coupled coniferous T-shaped ZnO and its photocatalytic performance to the best of our knowledge. Methods: In this study, the flame transport synthesis technique was employed for the preparation of coniferous T-shaped ZnO (T-ZnO). The as-prepared coniferous-like T-ZnO was coupled with MoS2 by hydrothermal treatment at 200 °C for 18 h and used for the photocatalytic dye removal. Significant findings: After coupling with MoS2, T-ZnO and spherical O-shape (O-ZnO) exhibited improved photocatalytic activities for the removal of dyes (methyl blue (MB) and rhodamine B (rhB)). Thanks to the heterojunction formation between MoS2 and ZnO, the electron transfer could be facilitated, evidenced by the small Tafel slope with a value of approximately 95.6 mv dec‒1. Moreover, the MoS2@T-ZnO sample could be recycled for photocatalytic MB removal at least 5 times. Our results suggested that the coupling of MoS2 over structural-engineered ZnO could be an alternative approach to further improving the photocatalytic activity of ZnO. © 2022

关键词： II-VI semiconductors

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Comparative study of surface contaminated layer on titanium aluminum alloy and titanium alloy investment castings 21st

Comparative study of surface contaminated layer on titanium ...

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21st Chinese materials Conference, CMC 2020

作者： Feng, Zhihua ding, Xianfei Feng, Xin Nan, Hai Zhang, Aibin Beijing Baimtec Material Co. Ltd. Beijing100094 China Cast Titanium Alloy R&D Center AECC Beijing Institute of Aeronautical Materials Beijing100095 China Beijing Engineering Research Center of Advanced Titanium Alloy Precision Forming Technology Beijing100094 China

ISBN: (纸本)9783035717389

A comparative study of the surface contaminated layer formed by chemical reaction between ceramic-mold and titanium aluminum alloy castings or titanium alloy castings were carried out. The morphology, thickness and hardness of the surface contaminated layer were characterized by means of metalloscopy and microhardness measurement. The results show that surface contaminated layers formed between Ti-Al alloy castings and ceramic-mold, also formed between Ti alloy castings and ceramic-mold. The surface contaminated layers of Ti-Al alloy castings were continuous and compact, their thickness was about 0~90 μm. The surface contaminated layers of titanium alloy castings were not even, their thickness was 0~900 μm. Titanium alloy is more liable to react with the ceramic-mold than the Ti-Al alloy. © 2021 Trans Tech Publications Ltd, Switzerland.

关键词： Titanium alloys

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Academic-Industrial Collaborations: Merging Paths to Thrive

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OrGANIC LETTErS 2024年第14期26卷 2669-2671页

作者： Bao, Hongli Bravo-Altamirano, Karla Buchan, Zachary Cabrera, Pablo J. ryan, Sarah J. roth, Joshua J. Sartillo-Piscil, Fernando Sawai, Yasuhiro Tambar, Uttam K. Zarate, Cayetana Key Laboratory of Coal to Ethylene Glycol and Its Related Technology State Key Laboratory of Structural Chemistry Center for Excellence in Molecular Synthesis Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fuzhou 350002 P. R. China Pfizer Worldwide Research and Development Medicine Eastern Point Road Groton Connecticut 06340 United States Discovery Chemistry Small Molecule Discovery and Development Corteva Agrisciences 9330 Zionsville Road Indianapolis Indiana 46268 United States Chemical Research & DevelopmentPfizer Worldwide Research & Development Eastern Point Road Groton Connecticut 06340 United States Nufarm Limited Pipe Road Laverton North VIC 3026 Australia Centro de Investigación de la Facultad de Ciencias Químicas Benemérita Universidad Autónoma de Puebla (BUAP) 14 Sur Esq. San Claudio Col. San Manuel 72570 Puebla México Synthetic Molecule Process Development Pharmaceutical Sciences Takeda Pharmaceutical Company Limited 26-1 Muraoka-Higashi 2-chome Fujisawa Kanagawa 251-8555 Japan Department of Biochemistry The University of Texas Southwestern Medical Center 5323 Harry Hines Boulevard Dallas Texas 75390-9038 United States Johnson & Johnson Innovative Medicine Chemical Process R&D Cilag AG Hochstrasse 201 8200 Schaffhausen Switzerland

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dual-Polarized Microstrip Antenna with Cross Grid Structure radiating Towards the Edge of the Substrate in the d-Band

Dual-Polarized Microstrip Antenna with Cross Grid Structure ...

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European Conference on Antennas and Propagation, EuCAP

作者： ryosuke Hasaba Ken Takahashi Tomoki Abe Tomohiro Murata Yoichi Nakagawa Koji Takinami Hiroshi Taneda Takashi Tomura Issei Watanabe Engineering Division Panasonic Industry Co. Ltd. Yokohama Japan Development Center Panasonic System Networks R&D Lab. Co Kanazawa Japan Research & Development Div. Shinko Electric Industries Co. Ltd. Nagano Japan Department of Electrical and Electronic Engineering Institute of Science Tokyo Tokyo Japan Advanced ICT Research Institute National Institute of Information and Communications Technology Tokyo Japan

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This paper proposes a dual-polarized antenna for d-band applications, which radiates in the substrate end direction. The antenna's radiating elements and ground are formed using vias, via lands, and copper foil. The radiating element features a cross-grid design, which combines both cross and grid shapes. This allows for the adjustment of the resonant frequency for each polarization, even under manufacturing rule constraints. The characteristics and operation of a singleelement antenna were demonstrated through simulations. Subsequently, the gain of an 8-element array was compared between measured and calculated values, demonstrating the effectiveness of the proposed antenna.

关键词： Antenna measurements Shape resonant frequency Microstrip antennas directive antennas Gain measurement Manufacturing Microstrip Substrates Antenna arrays

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