PALEOPROTEROZOIC TECTONICS AND EVOLUTIONARY MODEL OF THE ONEGA SYNCLINORIUM by S. Yu. Kolodyazhny, N. B. Kuznetsov, A. V. Poleshchuk, D. S. Zykov, E. A. Shalaeva

“…Consideration is being given to the Onega Paleoproterozoic structure (Onega synclinorium, OS) as a tectonotype of intraplate negative structures, which experience intermittent subsidence over a long period of time. The paper presents a model of the OS and discusses its tectonic evolution. …”
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Exploring Decentralized Warehouse Management Using Large Language Models: A Proof of Concept by Tomaž Berlec, Marko Corn, Sergej Varljen, Primož Podržaj

“…This paper presents a novel approach to decentralized warehouse management integrating Large Language Models (LLMs) into the decision-making processes of autonomous agents, which serves as a proof of concept for shared manufacturing. …”
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Physiological signal-based mental stress detection using hybrid deep learning models by Nandini Modi, Yogesh Kumar, Kapil Mehta, Neelam Chaplot

“…These spectrograms are then processed by CNN layers to extract spatial patterns, followed by MLP layers for mental stress state classification. …”
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Canopy Temperature Estimation Using Gene Expression Programming Models and Artificial Neural Networks by Mehri Saeidinia, AmirHameh Haghiabi

“…The MLP models outperformed GEP models during the training and testing processes. …”
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A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models by Hamidreza Najafi, Kimia Savoji, Marzieh Mirzaeibonehkhater, Seyed Vahid Moravvej, Roohallah Alizadehsani, Siamak Pedrammehr

“…We introduce a second GAN model with a novel loss function that significantly improves tumor detection accuracy. …”
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An adaptive deep learning approach based on InBNFus and CNNDen-GRU networks for breast cancer and maternal fetal classification using ultrasound images by Mamuna Fatima, Muhammad Attique Khan, Anwar M. Mirza, Jungpil Shin, Areej Alasiry, Mehrez Marzougui, Jaehyuk Cha, Byoungchol Chang

“…The InBnFUS network combines 5-Blocks inception-based architecture (Model 1) and 5-Blocks inverted bottleneck-based architecture (Model 2) through a depth-wise concatenation layer, while CNNDen-GRU incorporates 5-Blocks dense architecture with an integrated GRU layer. …”
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Conv1D-LSTM: Autonomous Breast Cancer Detection Using a One-Dimensional Convolutional Neural Network With Long Short-Term Memory by Mitanshi Rastogi, Meenu Vijarania, Neha Goel, Akshat Agrawal, Cresantus N. Biamba, Celestine Iwendi

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Optimizing Academic Certificate Management With Blockchain and Machine Learning: A Novel Approach Using Optimistic Rollups and Fraud Detection by Khoa Tan-Vo, Khanh Pham, Phu Huynh, Mong-Thy Nguyen Thi, Thu-Thuy Ta, Thu Nguyen, Tu-Anh Nguyen-Hoang, Ngoc-Thanh Dinh, Hong-Tri Nguyen

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Post-Ultraviolet-Curing Process Effects on Low-Velocity Impact Response of 3D Printed Polylactic Acid Parts by Tarkan Akderya

“…The impact behaviour of the specimens produced with production parameters of 200 °C printing temperature, 0.2 mm layer thickness, 50 mm/s printing speed, 100% infill rate, and 45° raster angle was compared with the raw specimens after the post-UV-curing process was applied. …”
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A Two-Stage Strategy Integrating Gaussian Processes and TD3 for Leader–Follower Coordination in Multi-Agent Systems by Xicheng Zhang, Bingchun Jiang, Fuqin Deng, Min Zhao

“…This study proposes a two-stage cooperative strategy that integrates Gaussian Processes (GPs) for modeling and a Twin Delayed Deep Deterministic Policy Gradient (TD3) for policy optimization (GPTD3), aiming to enhance adaptability and multi-objective optimization. …”
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Laser transformation hardening effect on hardening zone features and surface hardness of tool steel AISI D2 by D. Lesyk, V. Dzhemelinskyi, S. Martinez, А. Lamikiz, О. Dаnylеikо, V. Hyzhevskyi

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WTL-CNN: a news text classification method of convolutional neural network based on weighted word embedding by Weidong Zhao, Lin Zhu, Ming Wang, Xiliang Zhang, Jinming Zhang

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Reaction Gas Pressure, Temperature, and Membrane Water Content Modulate Electrochemical Process of a PEMFC: A Simulation Study by Bin Xia, Pengyan Guo, Xinjing Wei, Hehui Zong

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Research on the residual stress distribution of aircraft engine blades repaired by laser shock peening and laser cladding composite process by Cheng Xiuquan, Zhang Junhao, He Ruhao, Xiao Gangfeng, Xia Qinxiang

“…GH4169 superalloy was selected as the research material, a Swift-Voce constitutive model was constructed based on tensile testing. A full process finite element model of LSP and LC composite process, based on historical data transfer, was constructed. …”
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Study of unusable liquid propellant residues evaporation processes parameters in the tanks of launch vehicle worked-off stage in microgravity by V. I. Trushlyakov, V. A. Urbansky

“…The physical and mathematical model of the liquid evaporation process is based on the first thermodynamics law. …”
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The proteomic landscape of trophoblasts unravels calcium-dependent syncytialization processes and beta-chorionic gonadotropin (ß-hCG) production by Anna-Lena Gehl, Daniel Klawitter, Ulrich Wissenbach, Marnie Cole, Christine Wesely, Heidi Löhr, Petra Weissgerber, Adela Sota, Markus R. Meyer, Claudia Fecher-Trost

“…Methods Here, we combine human trophoblast model cell cultures, hormone assays, antibody-based detection methods and high-resolution mass spectrometry analyzes to assess changes in cellular processes during syncytialization. …”
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Assessing the suitability of the Langevin equation for analyzing measured data through downsampling by Pyei Phyo Lin, Matthias Wächter, Joachim Peinke, M Reza Rahimi Tabar

“…Such non-continuous changes pose a significant challenge for general processes and have profound implications for risk management. …”
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An Improved Deep Learning Model for Electricity Price Forecasting by Rashed Iqbal, Hazlie Mokhlis, Anis Salwa Mohd Khairuddin, Munir Azam Muhammad

“…Hence, this work proposed two-fold contributions which are (1) effective time series preprocessing module to ensure feasible time-series data is fitted in the deep learning model, and (2) an improved long short-term memory (LSTM) model by incorporating linear scaled hyperbolic tangent (LiSHT) layer in the EPF. …”
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DETAILS’ REPAIR OF CONSTRUCTION AND ROAD MACHINES: FLUCTUATIONS’ MODELLING by V. E. Ovsyannikov, V. I. Vasilyev

“…The error doesn’t exceed 20%. The developed model considers geometrical parameters of the tool (a departure, plate corners, etc.), the modes of cutting both mechanical properties of the processed material and parameters of the chip formation. …”
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Deep Learning Model for Analyzing EEG Signal Analysis by Varun Gupta, Vivek Kumar, Prince, Saurabh Singh, Young-Seok Lee, In-Ho Ra

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