Evaluating the strength properties of high-performance concrete in the form of ensemble and hybrid models using deep learning techniques by Zhe Wang, Tao Sun, Yan Sun, Na Liu

“…Abstract In the behavior of concrete, factors such as particle types, water content, aggregates, additives, and binders significantly influence its Compressive Strength (CS) properties. …”
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A New High-Performance Photovoltaic Emulator Suitable for Simulating and Validating Maximum Power Point Tracking Controllers by Ambe Harrison, Njimboh Henry Alombah

“…Currently, researchers face several challenges in testing MPPT algorithms due to the unpredictable nature of solar PV power generation. …”
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Turbidity Estimation by Machine Learning Modelling and Remote Sensing Techniques Applied to a Water Treatment Plant by Víctor Gauto, Enid Utges, Elsa Hervot, Maria Daniela Tenev, Alejandro Farías

“…Global feature importance and partial dependencies profile techniques identified the most influential spectral bands. …”
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Computational fluid dynamic and machine learning modeling of nanofluid flow for determination of temperature distribution and models comparison by Farag M. A. Altalbawy, Ahmad Alkhayyat, Ramdevsinh Jhala, Anupam Yadav, T. Ramachandran, Aman Shankhyan, A. Karthikeyan, Dhirendra Nath Thatoi, Vladimir Vladimirovich Sinitsin

“…The case study is fluid flow of nanofluid through a pipe and the nanofluid contains CuO particles. To enhance model efficacy, the Political Optimizer (PO) algorithm was utilized for fine-tuning purposes. …”
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Quantum DeepONet: Neural operators accelerated by quantum computing by Pengpeng Xiao, Muqing Zheng, Anran Jiao, Xiu Yang, Lu Lu

“…In the realm of computational science and engineering, constructing models that reflect real-world phenomena requires solving partial differential equations (PDEs) with different conditions. …”
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YOLOv8-POS: a lightweight model for coal-rock image recognition by Yanqin Zhao, Wenyu Wang

“…The methodology introduces a C2f-PConv module, which ingeniously combines the strengths of C2f and partial convolution (PConv) to selectively process channels. …”
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The siRNA Non-seed Region and Its Target Sequences Are Auxiliary Determinants of Off-Target Effects. by Piotr J Kamola, Yuko Nakano, Tomoko Takahashi, Paul A Wilson, Kumiko Ui-Tei

“…However, the siRNA guide strand may bind unintended off-target transcripts via partial sequence complementarity by a mechanism closely mirroring micro RNA (miRNA) silencing. …”
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Energy‐based PINNs for solving coupled field problems: Concepts and application to the multi‐objective optimal design of an induction heater by Marco Baldan, Paolo Di Barba

“…Abstract Physics‐informed neural networks (PINNs) are neural networks (NNs) that directly encode model equations, like Partial Differential Equations (PDEs), in the network itself. …”
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THEMIS: A Parameter Estimation Framework for the Event Horizon Telescope by Avery E. Broderick, Roman Gold, Mansour Karami, Jorge A. Preciado-López, Paul Tiede, Hung-Yi Pu, Kazunori Akiyama, Antxon Alberdi, Walter Alef, Keiichi Asada, Rebecca Azulay, Anne-Kathrin Baczko, Mislav Baloković, John Barrett, Dan Bintley, Lindy Blackburn, Wilfred Boland, Katherine L. Bouman, Geoffrey C. Bower, Michael Bremer, Christiaan D. Brinkerink, Roger Brissenden, Silke Britzen, Dominique Broguiere, Thomas Bronzwaer, Do-Young Byun, John E. Carlstrom, Andrew Chael, Shami Chatterjee, Koushik Chatterjee, Ming-Tang Chen, Yongjun Chen, Ilje Cho, John E. Conway, James M. Cordes, Geoffrey B. Crew, Yuzhu Cui, Jordy Davelaar, Mariafelicia De Laurentis, Roger Deane, Jessica Dempsey, Gregory Desvignes, Sheperd S. Doeleman, Ralph P. Eatough, Heino Falcke, Vincent L. Fish, Ed Fomalont, Raquel Fraga-Encinas, Per Friberg, Christian M. Fromm, Peter Galison, Charles F. Gammie, Roberto García, Olivier Gentaz, Boris Georgiev, Ciriaco Goddi, José L. Gómez, Minfeng Gu, Mark Gurwell, Kazuhiro Hada, Michael H. Hecht, Ronald Hesper, Luis C. Ho, Paul Ho, Mareki Honma, Chih-Wei L. Huang, Lei Huang, David H. Hughes, Makoto Inoue, Sara Issaoun, David J. James, Michael Janssen, Britton Jeter, Wu Jiang, Alejandra Jiménez-Rosales, Michael D. Johnson, Svetlana Jorstad, Taehyun Jung, Ramesh Karuppusamy, Tomohisa Kawashima, Garrett K. Keating, Mark Kettenis, Jae-Young Kim, Jongsoo Kim, Motoki Kino, Jun Yi Koay, Patrick M. Koch, Shoko Koyama, Michael Kramer, Carsten Kramer, Thomas P. Krichbaum, Cheng-Yu Kuo, Sang-Sung Lee, Yan-Rong Li, Zhiyuan Li, Michael Lindqvist, Rocco Lico, Kuo Liu, Elisabetta Liuzzo, Wen-Ping Lo, Andrei P. Lobanov, Laurent Loinard, Colin Lonsdale, Ru-Sen Lu, Nicholas R. MacDonald, Jirong Mao, Alan P. Marscher, Iván Martí-Vidal, Satoki Matsushita, Lynn D. Matthews, Karl M. Menten, Yosuke Mizuno, Izumi Mizuno, James M. Moran, Kotaro Moriyama, Monika Moscibrodzka, Cornelia Müller, Hiroshi Nagai, Neil M. Nagar, Masanori Nakamura, Ramesh Narayan, Gopal Narayanan, Iniyan Natarajan, Roberto Neri, Chunchong Ni, Aristeidis Noutsos, Hiroki Okino, Héctor Olivares, Gisela N. Ortiz-León, Tomoaki Oyama, Daniel C. M. Palumbo, Jongho Park, Ue-Li Pen, Dominic W. Pesce, Vincent Piétu, Richard Plambeck, Aleksandar PopStefanija, Oliver Porth, Ben Prather, Venkatessh Ramakrishnan, Ramprasad Rao, Mark G. Rawlings, Alexander W. Raymond, Luciano Rezzolla, Bart Ripperda, Freek Roelofs, Alan Rogers, Eduardo Ros, Mel Rose, Helge Rottmann, Chet Ruszczyk, Benjamin R. Ryan, Kazi L. J. Rygl, Salvador Sánchez, David Sánchez-Arguelles, Mahito Sasada, Tuomas Savolainen, F. Peter Schloerb, Karl-Friedrich Schuster, Lijing Shao, Zhiqiang Shen, Des Small, Bong Won Sohn, Jason SooHoo, Fumie Tazaki, Remo P. J. Tilanus, Michael Titus, Kenji Toma, Pablo Torne, Efthalia Traianou, Sascha Trippe, Shuichiro Tsuda, Ilse van Bemmel, Huib Jan van Langevelde, Daniel R. van Rossum, Jan Wagner, John Wardle, Jonathan Weintroub, Norbert Wex, Robert Wharton, Maciek Wielgus, George N. Wong, Qingwen Wu, Doosoo Yoon, André Young, Ken Young, Ziri Younsi, Feng Yuan, Ye-Fei Yuan, J. Anton Zensus, Guangyao Zhao, Shan-Shan Zhao, Ziyan Zhu, The Event Horizon Telescope Collaboration

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Fixed Point Results for a Class of Monotone Nonexpansive Type Mappings in Hyperbolic Spaces by Rameshwar Pandey, Rajendra Pant, Ahmed Al-Rawashdeh

“…We consider a wider class of nonexpansive type mappings and present some fixed point results for this class of mapping in partially hyperbolic spaces. Indeed, first we obtain some existence results for this class of mappings. …”
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Retrieving Inland Water Quality Parameters via Satellite Remote Sensing: Sensor Evaluation, Atmospheric Correction, and Machine Learning Approaches by Mohsen Ansari, Anders Knudby, Meisam Amani, Michael Sawada

“…Second, the strengths and weaknesses of atmospheric correction algorithms used over inland waters are examined. The results show that no atmospheric correction algorithm performed consistently across all conditions. …”
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The linear electromagnetic gyrokinetic global simulation by using the numerical Lie-transform code by Guodong Zhang, Jinxiang You, Zihao Wang, Tiannan Wu, Yuefeng Qiu, Lu Wang, Shaojie Wang

“…The development of electromagnetic gyrokinetic codes usually faces challenges including physical model, numerical instabilities as well as corresponding algorithms and accuracy; one of the typical challenges is the well-known cancellation problem. …”
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Monotone Data Visualization Using Rational Trigonometric Spline Interpolation by Farheen Ibraheem, Maria Hussain, Malik Zawwar Hussain

“…The rational cubic function has four parameters in each subinterval, while the rational bicubic partially blended function has eight parameters in each rectangular patch. …”
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Joint Caching and Computation in UAV-Assisted Vehicle Networks via Multi-Agent Deep Reinforcement Learning by Yuhua Wu, Yuchao Huang, Ziyou Wang, Changming Xu

“…We precisely model the problem as a Decentralized Partially Observable Markov Decision Process (Dec-POMDP) and adopt the Multi-Agent Proximal Policy Optimization (MAPPO) algorithm, which follows the Centralized Training Decentralized Execution (CTDE) paradigm. …”
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Typification of Projects for the Transition to Cloud Services by A. G. Voronova

“…For the first time, a method of self-preparation of a company for the implementation of cloud solutions is proposed. The algorithm systematizes the cloud migration processes. …”
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A comprehensive systematic review of intrusion detection systems: emerging techniques, challenges, and future research directions by Arjun Kumar Bose Arnob, Rajarshi Roy Chowdhury, Nusrat Alam Chaiti, Sudipta Saha, Ajoy Roy

“…This research also highlights the success of models such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Explainable AI (XAI) in improving detection accuracy as well as computational efficiency and interoperability. …”
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Inventory Model for Instantaneously Deteriorating Items with Multiple Trade Facilities, Stock- and Price-Dependent Demand, and Full Backlogging by Rabeya Sarker, Md. Sharif Uddin, Md Abu Helal, Aminur Rahman Khan, Ali AlArjani, El-Awady Attia

“…This paper formulates six inventory models for products with instantaneous deterioration, focusing on the impacts of full and partial advance payment structures. The demand function depends on both price and stock levels and accounts for shortages through full backlogging. …”
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Optimal Allocation of Gas Supply Reliability in Natural Gas Pipeline System Based on Exterior Penalty Function Method by Yueqi LIU, Lei HOU, Shuaishuai TANG, Huai SU, Xingtao LI

“…Optimal allocation of gas supply reliability is an important part of gas supply reliability of natural gas pipeline system.In order to study the optimal allocation scheme of gas supply reliability with the lowest cost,a cost function model based on the gas supply capacity of the pipeline system was constructed.To address the limitation of traditional intelligent optimization algorithms (e.g.,Particle Swarm Optimization) that overlook constraints during iterative updates,this research proposed a novel Exterior Penalty Function Method for optimizing gas supply reliability.This method transformed constraints in the allocation model into penalty function terms,established a revised objective function,and converted the constrained allocation problem into an unconstrained extremum problem.Applying this method to a practical pipeline system,optimal gas supply reliability allocation values were derived.The results demonstrate that the Exterior Penalty Function Method significantly reduces computational time without compromising accuracy.The allocation outcomes exhibit robust convergence and align with engineering practicality.By clarifying the optimized allocation values of unit gas supply reliability and comparing them with the current reliability,the weak units in the gas supply system can be identified,providing a scientific basis for improving the gas supply reliability of pipeline systems.…”
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Secrecy-Constrained UAV-Mounted RIS-Assisted ISAC Networks: Position Optimization and Power Beamforming by Weichao Yang, Yajing Wang, Dawei Wang, Yixin He, Li Li

“…To address this non-convex, multivariate, and coupled problem, we decompose it into three subproblems, which are solved iteratively using particle swarm optimization (PSO), semi-definite relaxation (SDR), majorization–minimization (MM), and alternating direction method of multipliers (ADMM) algorithms. …”
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Real-Time Acoustic Holography for Target Pattern Acoustic Field Reconstruction With Iterative Unsupervised Learning by Minjie Ma, Xuewei Wang, Yang Li, Jia Wang

“…The ability to reconstruct acoustic field is essential for applications such as particle manipulation, medical therapy, and ultrasonic imaging. …”
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