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A disposable tartrazine sensor fabricated with a synchronously activated nanocomposite comprising gadolinium molybdate nanoflowers anchored on functionalized carbon nanofibers

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New Journal of Chemistry 2023年第6期48卷 2660-2672页

作者： Jayapaul, Abishek Sakthivel, Rajalakshmi Lin, Yu-Chien Dhawan, Udesh Liu, Xinke Wen, Hsiao-Wei Chung, Ren-Jei No. 1 Section 3 Zhongxiao E. Rd. Taipei10608 Taiwan Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow GlasgowG116EW United Kingdom College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Department of Food Science and Biotechnology National Chung Hsing University Taichung402202 Taiwan Food and Animal Product Safety Inspection Center National Chung Hsing University Taichung402202 Taiwan Taipei10608 Taiwan

Tartrazine (TRZ) is a synthetic food dye considered noxious to human health and a toxic environmental contaminant owing to the presence of a harmful azo group (-N 00000000 00000000 00000000 00000000 11111111 00000000 11111111 00000000 00000000 00000000 N-) in its chemical structure. The global necessity to prevent food contamination has led scientific researchers to develop disposable sensing platforms. This study aims to integrate nanotechnology with electrochemistry to fabricate a disposable screen-printed carbon electrode (SPCE) with a nanocomposite composed of gadolinium molybdate (Gd2MoO6) nanoflowers decorated on an enmeshed matrix of acid-functionalized carbon nanofibers (f-CNF). The hierarchal arrangement of distinct components in the nanocomposite is promoted by synergism through the formation of a hybrid heterojunction. This heterojunction in the electrode modifier activates the electrode to sense TRZ with a remarkable limit of detection (0.8 nmol L−1) and quantification (2 nmol L−1) over a broad linear range of 0.025 μM to 216.45 μM. Furthermore, the functional sensing ability of the proposed sensor was analyzed in various commercial food products. © 2024 The Royal Society of Chemistry.

关键词： Nanocomposites

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Design and Analysis of Two Efficient Socialist Millionaires’ Protocols for Privacy Protection 1

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7th International Conference on Smart Computing and Communication, SmartCom 2022

作者： Liu, Xin Liu, Xiaomeng Tu, Xiaofen Xiong, Neal School of Information Engineering Inner Mongolia University of Science and Technology Inner Mongolia Baotou014010 China National Engineering Research Center for E-Learning Central China Normal University Wuhan430079 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States

ISBN: (数字)9783031281242

ISBN: (纸本)9783031281235

Yao's Millionaires’ problem has led to the emergence of secure multi-party computation. As an important tool for privacy protection in cryptography, secure multi-party computation has attracted more and more scholars to study it. The socialist millionaires’ problem is the basic module of the secure multiparty computing protocol. Designing secure and efficient solutions for the socialist millionaires’ problem can be effectively applied to the secret ballot, electronic auction, and so on. Based on the vector encoding method, the Paillier encryption scheme, and the Goldwasser-Micali encryption scheme, two efficient socialist millionaires’ protocols are proposed and the protocols are analyzed. The correctness analysis, security proof, performance analysis, and experimental simulation show that the efficiency of the two protocols is superior to the existing schemes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cryptography

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Perovskite Nanocrystal Based Plastic Optical Fiber Amplifier via Two-Photon Excitation

Perovskite Nanocrystal Based Plastic Optical Fiber Amplifier...

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IEEE Photonics Conference (IPC)

作者： Yue Wang Chun Hong Kang Partha Maity Tien Khee Ng Omar F. Mohammed Boon S. Ooi Photonics Laboratory Electrical and Computer Engineering Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Advanced Membranes and Porous Materials Center Division of Physical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

A plastic optical fiber amplifier coated with CsPbBr3 nanocrystals and pumped by an 800-nm Ti:Sapphire laser exhibited two-photon-excited amplified spontaneous emission with a 7.4-mJ/cm 2 threshold and >10-dB opti... 详细信息

ISBN: (数字)9798350361957

ISBN: (纸本)9798350361964

关键词： Optical fiber amplifiers Plastic optical fiber Nanocrystals Stimulated emission Optical pumping Ultrafast optics Optical amplifiers Gain Pump lasers Fiber lasers

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Functionally graded structure of a nitride-strengthened Mg_(2)Si-based hybrid composite

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Journal of Magnesium and Alloys 2024年第3期12卷 1239-1256页

作者： Jeongho Yang Woongbeom Heogh Hogi Ju Sukhyun Kang Tae-Sik Jang Hyun-Do Jung Mohammad Jahazi Seung Chul Han Seong Je Park Hyoung Seop Kim Susmita Bose Amit Bandyopadhyay Martin Byung-Guk Jun Young Won Kim Dae-kyeom Kim Rigoberto CAdvincula Clodualdo Aranas Jr Sang Hoon Kim School of Mechanical Engineering Pusan National UniversityBusan 46241Republic of Korea Department of Mechanical Design Engineering Hanyang UniversitySeoul 04763Republic of Korea Process Research 3 Team LG Display Co.Ltd.PajuGyeonggi-do 10845Republic of Korea Department of Materials Science and Engineering Chosun UniversityGwangju 61452Republic of Korea Institute of Well-Aging Medicare&Chosun University LAMP Center Chosun UniversityGwangju 61452Republic of Korea Division of Materials Science and Engineering Hanyang UniversitySeoul 04763Republic of Korea Department of Mechanical Engineering École de Technologie SupérieureMontrealQuebec H3C 1K3Canada Material&Component Convergence R&D Center Korea Construction Equipment Technology InstituteGunsanJeollabuk-do 54002Republic of Korea School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Graduate Institute of Ferrous&Eco Materials Technology Pohang University of Science and TechnologyPohangGyeongsangbuk-do 37673Republic of Korea Advanced Institute for Materials Research Tohoku UniversitySendai 980-8577Japan Institute for Convergence Research and Education in Advanced Technology Yonsei UniversitySeoul 03722Republic of Korea School of Mechanical and Materials Engineering Washington State UniversityPullmanWashington 99164USA School of Mechanical Engineering Purdue UniversityWest LafayetteIndiana 47907USA Research Institute of Advanced Manufacturing Technology Korea Institute of Industrial TechnologyIncheon 21999Republic of Korea Department of Macromolecular Science and Engineering Case Western Reserve UniversityClevelandOhio 44106USA Department of Chemical and Biomolecular Engineering and Joint Institute for Advanced Materials University of TennesseeKnoxvilleTennessee 37996USA Center for Nanophase Materials and Sciences Oak Ridge National LaboratoryOak RidgeTennessee 37830USA Department of Mechanical Engineering University of New BrunswickFrederictonNew Brunswick E3B 5A3Cana

The ex-situ incorporation of the secondary SiC reinforcement,along with the in-situ incorporation of the tertiary and quaternary Mg_(3)N_(2) and Si_(3)N_(4) phases,in the primary matrix of Mg_(2)Si is employed in order to provide ultimate wear resistance based on the laser-irradiation-induced inclusion of N_(2) gas during laser powder bed *** is substantialized based on both the thermal diffusion-and chemical reactionbased metallurgy of the Mg_(2)Si–SiC/nitride hybrid *** study also proposes a functional platform for systematically modulating a functionally graded structure and modeling build-direction-dependent architectonics during additive *** strategy enables the development of a compositional gradient from the center to the edge of each melt pool of the Mg_(2)Si–SiC/nitride hybrid ***,the coefficient of friction of the hybrid composite exhibits a 309.3%decrease to–1.67 compared to–0.54 for the conventional nonreinforced Mg_(2)Si structure,while the tensile strength exhibits a 171.3%increase to 831.5 MPa compared to 485.3 MPa for the conventional *** outstanding mechanical behavior is due to the(1)the complementary and synergistic reinforcement effects of the SiC and nitride compounds,each of which possesses an intrinsically high hardness,and(2)the strong adhesion of these compounds to the Mg_(2)Si matrix despite their small sizes and low concentrations.

关键词： Laser powder bed fusion Mg_(2)Si-SiC/nitride hybrid composite Both the thermal diffusion-and chemical reaction-based metallurgy Functionally graded structure Compositional gradient Wear resistance.

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Enhancing electrochemical performance and stabilizing zinc anode in mild acidic electrolyte using combined additive

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Materials science for Energy Technologies 2023年第1期6卷 178-191页

作者： Motlagh, Shiva Rezaei Khezri, Ramin Mohamad, Ahmad Azmin Pornprasertsuk, Rojana Kidkhunthod, Pinit Nguyen, Mai Thanh Yonezawa, Tetsu Kheawhom, Soorathep Department of Chemical Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand School of Materials and Mineral Resources Engineering Universiti Sains Malaysia Nibong Tebal Pulau Pinang 14300 Malaysia Department of Materials Science Faculty of Science Chulalongkorn University Bangkok10330 Thailand Center of Excellence on Advanced Materials for Energy Storage Chulalongkorn University Bangkok10330 Thailand Center of Excellence in Petrochemical and Materials Technology Chulalongkorn University Bangkok10330 Thailand Department of Materials Science and Bioengineering Nagaoka University of Technology Niigata940-2188 Japan Synchrotron Light Research Institute 111 University Avenue Muang District Nakhon Ratchasima30000 Thailand Division of Materials Science and Engineering Faculty of Engineering Hokkaido University Hokkaido060-8628 Japan Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand

Rechargeable zinc-based batteries having aqueous electrolytes are renowned as promising alternatives for large scale energy storage systems (ESSs). However, in mild acidic electrolytes, zinc anodes pose several issues that have yet to be overcome. For tackling the major difficulties of zinc anodes, electrolyte engineering is the most practical and cost-effective strategy. Notwithstanding the broad variety of mechanisms associated with different electrolyte additives, the function of a single additive is straightforward. Finding combined additives with broader functionalities and greater efficacy is crucial. In this work, the combination of ionic liquid (IL) 1-butyl-1-methylpyrrolidinium dicyanamide ([BMPY][DCN]) and ethylene glycol (EG) as additives in an aqueous electrolyte 3 M ZnSO4 proves to be an effective strategy for simultaneously enhancing both zinc dissolution and deposition. IL significantly enhances zinc (Zn) dissolution and deposition while EG plays an important role in suppressing hydrogen evolution reaction (HER)and corrosion. Thus, 13.50 % improvement in capacity is achieved by the mixed additive EG + IL/ZnSO4 compared with the 3 M ZnSO4 electrolyte. In the Zn//Zn symmetrical system at 2 mA cm−2, the mixed additive greatly augments the cyclability of zinc, reaching over 400 h while maintaining excellent coulombic efficiency (CE). In-situ XAS and FT-EXAFS analyses confirm the high activities of both zinc oxidation/reduction in the mixed additive electrolyte. Results demonstrate that EG + IL/ZnSO4 can be applied to increase the cyclability of aqueous zinc-based batteries while sustaining high performance. © 2022

关键词： Ethylene glycol

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不可逆分析法研究受磁偶极子影响的Ree-Eyring纳米流体流动多相催化作用

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Journal of Central South University 2023年第7期30卷 2324-2339页

作者： Seemab BASHIR Muhammad RAMZAN Seifedine KADRY C Ahamed SALEEL Department of Mathematics Air UniversityIslamabad44000Pakistan Department of Computer Science Bahria UniversityIslamabad44000Pakistan Department of Mathematics and Computer Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Mechanical Engineering College of EngineeringKing Khalid UniversityAsir-Abha61421Saudi Arabia

Ree-Eyring流体是一种非牛顿流体,具有屈服应力和剪切稀化的特点,比如乳剂、浆体和聚合物溶液。根据Ree-Eyring流体的特性,通过考虑不均匀的产热/吸收效应和黏性耗散效应,以及分析传热现象来研究磁偶极子作用下表面拉伸纳米流体的流动... 详细信息

Ree-Eyring流体是一种非牛顿流体,具有屈服应力和剪切稀化的特点,比如乳剂、浆体和聚合物溶液。根据Ree-Eyring流体的特性,通过考虑不均匀的产热/吸收效应和黏性耗散效应,以及分析传热现象来研究磁偶极子作用下表面拉伸纳米流体的流动行为。所建立模型考虑了对流条件下边界表面的熵产生,将偏微分方程组(PDEs)充分变换转换为耦合常微分方程组(ODEs),采用MATLAB bvp4c法进行数值计算,并以图表形式显示计算结果。结果表明,随着Brinkman数的变化,不可逆性产生率激增。此外,当热泳参数最小化时,边界附近的温度降低,而在远离边界处温度上升。表面催化参数减弱了溶质的分布,模型得到了验证。

关键词： Ree-Eyring纳米流体磁偶极子多相催化熵产生

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6D Pose Estimation and Correction for Fully Occluded 3D Model X-Ray Source Using Deeplabv3 Utilizing Mobilenetv2 Backbone and Dense Fusion Algorithm

6D Pose Estimation and Correction for Fully Occluded 3D Mode...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Rogelio, Jayson P. Dadios, Elmer Jose P. Bandala, Argel Naguib, Raouf Vicerra, Ryan Rhay Sybingco, Edwin Lim, Laurence Gan Metals Industry Research and Development Center De La Salle University Department of Science and Technology Philippines De La Salle University College of Manufacturing and Management Manila Philippines De La Salle University College of Electronics and Communications Engineering Manila Philippines Liverpool Hope University Mathematics Computer Science and Engineering Liverpool United Kingdom De La Salle University College of Mechanical Engineering Manila Philippines

ISBN: (纸本)9798350364910

Recent advancements in computer vision, notably in 6D pose estimation with methods like DeepLabv3 and Dense Fusion, show promising results. However, a substantial research gap exists in addressing the limitations of these methods in occluded scenarios, which in need further research to enhance their effectiveness and adaptability in situations involving hidden or partially obscured objects. This study introduces a novel approach employing 6D object pose estimation and pose correction by integrating DeepLabV3 and modified dense fusion. The study exhibits enhanced accuracy in pose estimation and correction for occluded 3D object model x-ray source. Evaluation metrics, including intersection-over-union and mean average, demonstrate high accuracy percentages for detecting the body (98.91%), handle (96.57%), and aperture (89.54%). The mean IoU for each part of the 3D model portable X-ray source ranges from 65.69% to 76.42%. Pose estimation accuracy, assessed through the Average Distance Difference (ADD) metric, indicates superior performance for static pose estimation closer to the camera. Dynamic pose estimation exhibits higher average ADD metrics in scenes with total occlusion. The robustness metric reveals lower lost tracking counts in scenes without occlusion, emphasizing the algorithm's challenges in fully occluded scenarios. © 2024 IEEE.

关键词： X ray apparatus

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Statistical Data Mining with Slime Mould Optimization for Intelligent Rainfall Classification

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computer Systems science & engineering 2023年第10期47卷 919-935页

作者： Ramya Nemani G.Jose Moses Fayadh Alenezi K.Vijaya Kumar Seifedine Kadry Jungeun Kim Keejun Han Department of Mathematics Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science and Engineering University Institute of Engineering and Technology(UIET)Guru Nanak UniversityHyderabadIndia Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia Department of Computer Science and Engineering GITAM School of TechnologyVishakhapatnam CampusGITAM(Deemed to be a University)VishakhapatnamIndia Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea Division of Computer Engineering Hansung UniversitySeoul02876Korea

Statistics are most crucial than ever due to the accessibility of huge counts of data from several domains such as finance,medicine,science,engineering,and so *** data mining(SDM)is an interdisciplinary domain that examines huge existing databases to discover patterns and connections from the *** varies in classical statistics on the size of datasets and on the detail that the data could not primarily be gathered based on some experimental strategy but conversely for other ***,this paper introduces an effective statistical Data Mining for Intelligent Rainfall Prediction using Slime Mould Optimization with Deep Learning(SDMIRPSMODL)*** the presented SDMIRP-SMODL model,the feature subset selection process is performed by the SMO algorithm,which in turn minimizes the computation *** rainfall *** neural network with long short-term memory(CNN-LSTM)technique is *** last,this study involves the pelican optimization algorithm(POA)as a hyperparameter *** experimental evaluation of the SDMIRP-SMODL approach is tested utilizing a rainfall dataset comprising 23682 samples in the negative class and 1865 samples in the positive *** comparative outcomes reported the supremacy of the SDMIRP-SMODL model compared to existing techniques.

关键词： Statistical data mining predictive models deep learning rainfall prediction parameter tuning

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Learning Discriminative Feature Representations via Metric Learning for Early Operation of Wind Turbine Anomaly Detection Systems

Learning Discriminative Feature Representations via Metric L...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Taiki Inoue Jun Ogata Makoto Iida Tetsuji Ogawa Department of Communications and Computer Engineering Waseda University Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology (AIST) Research Center for Advanced Science and Technology The University of Tokyo

To achieve robust wind turbine anomaly detection, we attempted to incorporate metric learning into the process of learning discriminative feature representations. In the context of anomaly detection based on inlier modeling, where anomalies are identified as inputs deviating from the normal state distribution, the key to building a high-performance and robust system, even with limited training data, lies in eliminating the influence of environmental differences from the inputs and obtaining a compact normal state distribution. To address this, we designed a deep neural network-based feature extractor to mitigate the impact of environmental changes. Additionally, we integrated metric learning into its learning process to obtain a more compact distribution by embedding inputs with similar properties close to one another. We validated the effectiveness of the developed network as a feature extractor for constructing a normal model with limited data through experimental comparisons using vibration data collected from sensors. Specifically, we utilized MobileNet as a discriminative feature extractor to identify 37 wind turbines. By introducing metric learning based on t-SNE into its training process, we achieved a notable 50 % improvement in the AUC. Remarkably, this significant improvement was accomplished using only a small amount of data, approximately 13 minutes, obtained from the monitored turbine.

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Four-dimensional conserved topological charge vectors in plasmonic quasicrystals

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science (New York, N.Y.) 2025年第6734期387卷 644-648页

作者： Tsesses, Shai Dreher, Pascal Janoschka, David Neuhaus, Alexander Cohen, Kobi Meiler, Tim C. Bucher, Tomer Sapir, Shay Frank, Bettina Davis, Timothy J. Meyer Zu Heringdorf, Frank Giessen, Harald Bartal, Guy rew and Erna Viterbi Department of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa Israel Department of Physics MIT-Harvard Center for Ultracold Atoms and Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge MA United States Faculty of Physics and Center for Nanointegration University of Duisburg-Essen Duisburg-Essen (CENIDE) Duisburg Germany 4th Physics Institute Research Center SCoPE Integrated Quantum Science and Technology Center University of Stuttgart Stuttgart Germany Centre for Disruptive Photonic Technologies and School of Physical and Mathematical Sciences Nanyang Technological University Singapore Faculty of Mathematics and Computer Science Weitzmann Institute of Science Rehovot Israel School of Physics University of Melbourne Parkville VIC Australia

According to Noether's theorem, symmetries in a physical system are intertwined with conserved quantities. These symmetries often determine the system topology, which is made ever more complex with increased dimensionality. Quasicrystals have neither translational nor global rotational symmetry, yet they intrinsically inhabit a higher-dimensional space in which symmetry resurfaces. Here, we discovered topological charge vectors in four dimensions (4D) that govern the real-space topology of 2D quasicrystals and reveal their inherent conservation laws. We demonstrate control over the topology in pentagonal plasmonic quasilattices, mapped by both phase-resolved and time-domain near-field microscopy, showing that their temporal evolution continuously tunes the 2D projections of their distinct 4D topologies. Our work provides a route to experimentally probe the thermodynamic properties of quasicrystals and topological physics in 4D and above.

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