Numerical simulation of Stephan blowing impacts on thermally laminated 3D flow of MHD trihybrid nanofluid with Soret and Dufour effects by Noureddine Elboughdiri, Munawar Abbas, Hamdi Ayed, Abir Mouldi, Nahid Fatima, Dilsora Abduvalieva, Mohamed Said, Ibrahim Mahariq, Ahmed S. Hendy, Ahmed M. Galal

“…The heat transfer rate is increased by 21.87 % for the ternary hybrid nanofluid, 16.56 % for the hybrid nanofluid, and 11.25 % for the mono nanofluid when the nanoparticles volume fraction is increased from 0.01 to 0.04.…”
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Retinopathy Disease Detection and Classification Using a Coordinate Attention Module-Based Convolutional Neural Network with Leaky Rectified Linear Unit by Pravin Balaso Chopade, Prabhakar N. Kota, Bhagvat D. Jadhav, Pravin Marotrao Ghate, Shriram Sadashiv Kulkarni

“…Model yang dicadangkan mencapai keputusan yang lebih baik pada dataset MESSIDOR berdasarkan metrik ketepatan, ketepatan, panggilan semula, kekhususan, skor f1, dan nilai Kawasan di Bawah Lengkung (AUC) iaitu sekitar 99.72%, 99.46%, 99.25%, 99.61%, 99.37% dan 99.14%, masing-masing, membuktikan keunggulannya berbanding kaedah sedia ada, Capsule Network dan Hybrid Adaptive DL berasaskan DR (HADL-DR). …”
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Critical review of multimorbidity outcome measures suitable for low-income and middle-income country settings: perspectives from the Global Alliance for Chronic Diseases (GACD) res... by Najma Siddiqi, Meena Daivadanam, J Jaime Miranda, Trishul Siddharthan, John R Hurst, Rajesh Vedanthan, Gary Parker, Gina Agarwal, Shabbar Jaffar, Naomi Levitt, Niels H Chavannes, Pallab K Maulik, Patricio Lopez-Jaramillo, Kamran Siddiqi, Muralidhar M Kulkarni, Gillian Sandra Gould, Job F M van Boven, Kirsten Bobrow, M O Owolabi, Joan B Soriano, Erick Wan-Chun Huang, Shahirose Sadrudin Premji, Lijing Yan, Ricardo Araya, F Xavier Gómez-Olivé, Bruce J Kirenga, Rianne M J J van der Kleij, Laura Loli-Dano, Shane Norris, Josefien van Olmen, Antigona C Trofor

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Tools to improve discharge equity: Protocol for the pilot TIDE trial by Kirsten Austad, Cecilia Thai, Alegna Zavatti, Nhi Nguyen, Diana Bautista-Hurtado, Patrick Kenney, Noelia Lugo, Joo H. Lee, Howard Lanney, Ziming Xuan, Erika G. Cordova-Ramos, Mari-Lynn Drainoni, Brian Jack

“…Methods: We present the protocol for a type I hybrid implementation-effectiveness pilot randomized trial. …”
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Convolutional neural networks for sea surface data assimilation in operational ocean models: test case in the Gulf of Mexico by O. Zavala-Romero, O. Zavala-Romero, A. Bozec, E. P. Chassignet, J. R. Miranda, J. R. Miranda

“…This work explores the application of convolutional neural networks (CNNs) in data assimilation within the context of the HYbrid Coordinate Ocean Model (HYCOM) in the Gulf of Mexico. …”
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Manifestaciones neurológicas asociadas a la vacuna contra COVID-19 by R. Alonso Castillo, J.C. Martínez Castrillo

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Seroconversion and dynamics of IgG anti-SARS-CoV-2 antibodies during the pandemic: A two-month observation cohort study on the population of Sleman in Indonesia. by Jajah Fachiroh, Septi Kurnia Lestari, Dewi Kartikawati Paramita, Bagas Suryo Bintoro, Fatwa Sari Tetra Dewi, Lutfan Lazuardi, Cici Permata Rusadi, Erti Nur Sagenah, Eggi Arguni

“…This evidence suggested for hybrid immunity, on which infection and vaccine simultaneously contributes to anti-RBD-SARS-CoV-2 IgG seroconversion.…”
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Fhl1, a new spatially specific protein, regulates vein graft neointimal hyperplasia by Chaoqun Wang, Jiantao Chen, Zicong Feng, Bohao Jian, Suiqing Huang, Kangni Feng, Haoliang Liu, Zhuoming Zhou, Ziyin Ye, Jing Lu, Mengya Liang, Zhongkai Wu

“…Spatial transcriptomics profiles and morphological observations demonstrated that a newly generated cell population outside the grafted vein with hybrid phenotype between SMCs and fibroblasts contributes to neointimal formation.…”
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Neurological manifestations associated with COVID-19 vaccine by R. Alonso Castillo, J.C. Martínez Castrillo

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State Estimation in Power Systems Under Random Data Attack Using Correlation Matching, Semidefinite Relaxation, and Truncated Eigenvalue Decomposition by Bamrung Tausiesakul, Krissada Asavaskulkiet, Chuttchaval Jeraputra, Ittiphong Leevongwat, Thamvarit Singhavilai, Supun Tiptipakorn

“…This work considers a state estimation problem in modern power systems from the perspective of smart grids. Due to the use of digital technology, smart grids often encounter malicious data that is deliberately injected to attack their grid operations. …”
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Multi-Timescale Battery-Charging Optimization for Electric Heavy-Duty Truck Battery-Swapping Stations, Considering Source–Load–Storage Uncertainty by Peijun Shi, Guojian Ni, Rifeng Jin, Haibo Wang, Jinsong Wang, Zhongwei Sun, Guizhi Qiu

“…First, a model incorporating uncertainties in renewable energy output, time-of-use pricing, and grid load fluctuations is developed for the battery-swapping station. …”
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Life cycle greenhouse gas emissions of hydrogen imported by maritime transportation: A South Korean case study by Gyuna Kwak, Juha Lee, Yujin Jung, Wonjae Choi

“…The study demonstrates that the grid electricity emissions in hydrogen-producing countries have a stronger impact than the transportation distance. …”
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Research on pipeline-type power frequency electromagnetic heating system and multi-layer winding based power regulation method by Feng Zhou, Longyun Liu, Zixuan Wang, Xin Tong, Yanping Liu

“…The study results suggest that energy output can be managed as needed, reducing the impact of loading and unloading on the local power grid and equipment, demonstrating strong practicality. …”
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Stability and Convergence of Nuclear Detonations in White Dwarf Collisions by Peter Anninos, David Cruz-Lopez, Brighten Jiang, Emanuel Gordis

“…Within these bounds, we find that grid resolutions of 5 km or better are necessary for uncertainties in total released energy and iron-group products to drop below 10%. …”
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Technology for Improving Distribution Network Disaster-Prevention Capabilities for Intercurrent Natural Disasters Areas Under Extreme Weather： Review and Prospect by CHEN Bin, LIAO Jinlin

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Peningkatan Kinerja Protokol PEGASIS Dengan Pembagian Area Dan Pembentukan Chain Secara Adaptif by Muhammad Riko Anshori Prasetya, Waskhito Wibisono

“…VCLUS-PEGASIS memodifikasi area PEGASIS dengan membaginya menjadi beberapa grid secara vertikal. Selain itu, chain dalam satu grid akan diubah apabila terjadi transmisi yang panjang antara satu node dengan node tetangganya yang masih dalam satu area menggunakan algoritma K-Means. …”
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Using Flow 3D Simulation, Multiple Nonlinear Regression Approach, and Artificial Neural Network Approach Approaches to Study the Behavior of Vertical Drop Structures by Shaikhli Hasan Al, Mohammed Sarah Hashim, Al-Khafaji Zainab

“…Various turbulence models and grid configurations were assessed. The numerical results, achieved with a grid size of 20,000 nodes, a downstream channel length of 2 meters, the standard k-ε turbulence model, and a standard wall function, exhibited excellent agreement with theoretical equations. …”
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Numerical and Experimental-Based Framework for Fuel Cell System Fatigue Analysis in Frequency Domain by Zhe Liu, Mingjie Wang, Pengbo Guo, Dawei Gao, Yunkai Gao

“…First, a finite element model of the fuel cell system was created in accordance with established standards, followed by grid convergence analysis and grid quality correction to enhance model accuracy. …”
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Application of Improved Deep Learning Method in Intelligent Power System by HuiJie Liu, Yang Liu, ChengWen Xu

“…In view of the inaccurate short-term power load prediction in the power system, where the smart grid cannot effectively coordinate the production, transportation, and distribution of electric energy, the authors propose the application of improved deep learning methods in intelligent power systems. …”
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Machine-Learning-Driven Identification of Electrical Phases in Low-Sampling-Rate Consumer Data by Dilan C. Hangawatta, Ameen Gargoom, Abbas Z. Kouzani

“…Accurate electrical phase identification (PI) is essential for efficient grid management, yet existing research predominantly focuses on high-frequency smart meter data, not adequately addressing phase identification with low sampling rates using energy consumption data. …”
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