Multi-Modal Deep Embedded Clustering (MM-DEC): A Novel Framework for Mineral Detection Using Hyperspectral Imagery by Priyanka Nair, Devesh Kumar Srivastava, Roheet Bhatnagar

“…To this end, we propose Multi-Modal Deep Embedded Clustering (MM-DEC) approach, an innovative unsupervised learning framework that integrates Convolutional Autoencoders(CAEs), Variational Autoencoders (VAEs), and Gray Level Co-occurrence Matrix (GLCM) based texture extraction that is able to exploit the spatial, spectral, and texture features of mineral in consideration We demonstrate the MM-DEC potential to identify hematite prospects in the mineralized Kiriburu area of Jharkhand, India using EO-1 Hyperion hyperspectral data. …”
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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

“…This study introduces a novel D3Net model for half-hourly EP prediction, integrating Seasonal-Trend decomposition using LOESS (STL) and Variational Mode Decomposition (VMD) with Multi-Layer Perceptron (MLP), Random Forest Regression (RFR), and Tabular Neural Network (TabNet). …”
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Improving agricultural commodity allocation and market regulation: a novel hybrid model based on dual decomposition and enhanced BiLSTM for price prediction by Lihua Zhang, Fushun Wang, Fushun Wang, Kejian Wang, Kejian Wang, Zhenxue He, Zhenxue He, Chen Chen, Chen Chen, Jiahao Liu, Jiahao Liu, Chao Wang, Chao Wang, Zhe Wang

“…This paper proposes a sustainable hybrid model SV-PSO-BiLSTM which integrates Seasonal-Trend decomposition procedure based on Loess (STL), Variational Mode Decomposition (VMD), Particle Swarm Optimization (PSO), and Bidirectional Long Short-Term Memory (BiLSTM) neural networks. …”
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Dynamic Analysis of a Fault Planetary Gear System under Nonlinear Parameter Excitation by Jianchao Han, Yinghui Liu, Lei Liang, Yang Zhao, Huibo Zhang

“…The equations of motion are derived by the Lagrangian method and solved by the numerical integration method. …”
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Gender Identification Using Multilayer Perceptron (MLP) Neural Network, Genetic Neural Network and Adaptive Neuro-Fuzzy Inference System (ANFIS) Network by Evanthia Kokkinaki

“…Additionally, the application of neural networks for gender recognition and their integration with the fuzzy C-means method is also noteworthy. …”
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Study of Thermodynamic Horizontal Structure of the Middle and Upper Atmosphere Based on Atmospheric Detection Lidar Networks by Liting Ren, Yong Yang, Linmei Liu, Xin Lin, Jinzhou Zheng, Wei Wang, Jiaming Liang, Yuan Xia, Jiqin Wang, Kaijie Ji, Zhenwei Chen, Yuqi Zhang, Xuewu Cheng, Faquan Li

“…To obtain a more reliable horizontal temperature structure, this study integrates coordinated lidar observations from Urumqi, Yuzhong, and Yangbajing with models using a three-dimensional variational (3DVAR) data assimilation method to construct a high-resolution temperature field over northwestern China. …”
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Advancing Evapotranspiration Modeling With Optimized Soil and Canopy Resistance Combinations by Jinfeng Zhao, Shikun Sun, Yali Yin, Yihe Tang, Chong Li, Yongshan Liang, Yubao Wang, Alexander Winkler, Shijie Jiang

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Artificial intelligence in vaccine research and development: an umbrella review by Rabie Adel El Arab, May Alkhunaizi, May Alkhunaizi, Yousef N. Alhashem, Alissar Al Khatib, Munirah Bubsheet, Salwa Hassanein, Salwa Hassanein

“…Moreover, bridging the gap from in silico promise to real‑world impact demands large‑scale validation studies and methods that can accommodate heterogeneous evidence, ensuring AI‑driven innovations deliver equitable global health outcomes and reinforce pandemic preparedness.…”
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Accelerated inverse design of broadband microperforated panel absorbers based on probabilistic generative model by Zhenyang Huang, Zhongpeng Li, Jinshun Hu, Yongshui Lin, Weiguo Wu, Xiaofei Cao

“…This study proposes a deterministic autoencoder-like framework that integrates response prediction and inverse design modeling, enabling highly accurate bidirectional mapping between geometric parameters and absorption spectra. …”
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Latent Profile Analysis of AI Literacy and Trust in Mathematics Teachers and Their Relations with AI Dependency and 21st-Century Skills by Tommy Tanu Wijaya, Qingchun Yu, Yiming Cao, Yahan He, Frederick K. S. Leung

“…A robust three-step latent profile analysis method was utilized to analyze the data. The research revealed five distinct profiles of AI literacy and trust among the teachers: (1) Basic AI Engagement; (2) Developing AI Literacy, Skeptical of AI; (3) Balanced AI Competence; (4) Advanced AI Integration; and (5) AI Expertise and Confidence. …”
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The Morphological Description Automation of the Optic Nerve Head Boundary in Digital Fundus Images by E. G. Tanaeva, R. G. Khafizov

“…Methods. The proposed method is based on integration algorithm of luminance samples along the diagonal. …”
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Assimilation of INSAT-3D imager retrieved aerosol optical depth for enhanced dust storm prediction using WRF-Chem model by Aman W Khan, Dilip Ganguly, Sagnik Dey, Atul Kumar Varma, Prashant Kumar

“…The Gridpoint Statistical Interpolation (GSI) three-dimensional variational (3DVAR) method was utilized for data assimilation, with simulations performed for 144 h, adjusting for uncertainties in the model’s background error covariance using different inflation factors. …”
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Fusion of three-dimensional geotechnical and geophysical data for developing digital twin of underground space by Zheng Guan, Yu Wang

“…To tackle this challenge, this study develops an innovative 3D fusion method for efficiently integrating limited geotechnical data with high-resolution geophysical data in a 3D space. …”
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Digital Technologies in Authentic Assessment in Higher Education: A Systematic Literature Review and Narrative Synthesis by Anjin Hu, Qian Liu, Ben Daniel

“…Authentic assessment is widely recognized as a valuable method that reflects real-world contexts, allowing students to apply their knowledge to practical challenges and prepare for their futures. …”
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A comparison of exogenous promoter activity at the ROSA26 locus using a ΦiC31 integrase mediated cassette exchange approach in mouse ES cells. by Chiann-mun Chen, Jon Krohn, Shoumo Bhattacharya, Benjamin Davies

“…The behavior of these exogenous promoters, when integrated at ROSA26 in both sense and antisense orientations, reveals a large variation in their levels of activity. …”
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Study of nonlinear anisotropic elliptic problems with non-local boundary conditions in weighted variable exponent Sobolev spaces by Soumia EL OMARI, Said Melliani

“…This study investigates the existence of weak solutions for nonlinear anisotropic elliptic equations characterized by non-local boundary conditions within anisotropic weighted variable exponent Sobolev spaces. By employing variational methods and compact embedding theorems tailored to anisotropic Sobolev spaces, the research focuses on understanding the impact of anisotropy, non-locality, and weighted structures on the solution behavior. …”
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Quantum-enhanced intelligent system for personalized adaptive radiotherapy dose estimation by Radhey Lal, Rajiv Kumar Singh, Dinesh Kumar Nishad, Saifullah Khalid

“…Quantum-enhanced Monte Carlo simulations, employing algorithms such as Harrow-Hassidim-Lloyd (HHL) and Variational Quantum Eigensolver (VQE), achieve computational speedups of 8–15 times compared to classical methods while maintaining high accuracy. …”
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SC-GROG followed by L+S reconstruction with multiple sparsity constraints for accelerated Golden-angle-radial DCE-MRI. by Faisal Najeeb, Kashif Amjad, Irfan Ullah, Hammad Omer

“…The GRASP (Golden-angle-radial Sparse Parallel MRI) is a contemporary method for reconstructing dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). …”
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Toward unsupervised building extraction from very high-resolution remote sensing images using SAM and CLIP by Chenxiao Zhang, Peng Yue

“…While recent work has attempted to integrate foundational models into remote sensing tasks, most approaches focus on supervised methods or fine-tuning streams. …”
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Optimizing drug design by merging generative AI with a physics-based active learning framework by Isaac Filella-Merce, Alexis Molina, Lucía Díaz, Marek Orzechowski, Yamina A. Berchiche, Yang Ming Zhu, Júlia Vilalta-Mor, Laura Malo, Ajay S. Yekkirala, Soumya Ray, Victor Guallar

“…To address these, we developed a GM workflow integrating a variational autoencoder with two nested active learning cycles. …”
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