Data-Driven Optimal Dispatch of Integrated Energy in Zero-Carbon Building System Considering Occupant Comfort and Uncertainty by Kui Hua, Qingshan Xu, Shujuan Li, Lele Fang

“…Numerical results demonstrate that the total energy cost can be reduced by 18.87% in summer and 27.22% in winter when relaxing the occupant comfort constraints, and comparative analysis shows that the proposed approach can achieve a balance between conservativeness and computational complexity.…”
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Data-driven design of topologically optimized auxetic metamaterials for tailored stress–strain and Poisson’s ratio-strain behaviors by Yueyou Tang, Anfu Zhang, Qi Zhou, Mu He, Liang Xia

“…Conventional topology optimization methods often struggle to achieve simultaneous customization of stress–strain and Poisson’s ratio–strain curves in auxetic metamaterials, due to the complexity of nonlinear analysis, multi-objective coupling, and high computational costs. …”
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Data of vegetation structure metrics retrieved from airborne laser scanning surveys for European demonstration sitesZenodo by W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

“…It supports landscape-scale habitat analysis and contributes to the standardization of vegetation metrics from ALS data for site-specific ecological monitoring (e.g., Natura 2000). …”
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Study on the Natural Ventilation Model of a Single-Span Plastic Greenhouse in a High-Altitude Area by Youyu Li, Shumei Zhao, Anguo Dai, Jingfu Zhang, Zilong Fan, Tao Ding

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Integration of Satellite, Models and Ground Sensors for City-scale Air Quality Monitoring through the Open Data Cube by A. Moazzam, D. Oxoli, J. R. Cedeno Jimenez, M. A. Brovelli

“…The Open Data Cube system facilitates data access, processing, and analysis by structuring multi-source air quality information into a unified data endpoint. …”
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SentemQC - A novel and cost-efficient method for quality assurance and quality control of high-resolution frequency sensor data in fresh waters [version 2; peer review: 1 approved,... by Sofie Gyritia Madsen van't Veen, Joachim Audet, Eti Ester Levi, Brian Kronvang, Søren Erik Larsen, Erik Jeppesen, Esben Astrup Kristensen, Anders Nielsen, Thomas Alexander Davidson, Jane Rosenstand Laugesen, Peter Mejlhede Andersen

“…As a result, the method can mark not only individual outliers but also clusters of anomalies. Our analysis shows that the method is robust for detecting anomalies in HF sensor data from multiple water quality sensors measuring nitrate, turbidity, oxygen, and pH. …”
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AI-Driven Optimization of Multilayer Thin-Film Structures for Advanced Optical Applications by Emad Alkhazraji, Sani Mukhtar, Haitham Khaled, Jaime Viegas

“…Beyond fast prediction, we analyze the physical influence of each design parameter using Principal Component Analysis (PCA), Global Sensitivity Analysis, and SHapley Additive exPlanations (SHAP). …”
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Investigating the Ability to Mask Dental Discoloration by CAD/CAM Bleach Shade Ceramics in Different Thicknesses by Shervin Reybod, Fariba Ezoji, Ghazaleh Ahmadizenouz, Behnaz Esmaeili

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A novel appliance-based secure data aggregation scheme for bill generation and demand management in smart grids by Yihui Dong, Jian Shen, Sai Ji, Rongxin Qi, Shuai Liu

“…The fog nodes (FNs) in our scheme are responsible for the calculation of aggregation with its powerful computing and storage capabilities. The security analysis shows that our scheme satisfies IND-CPA and multiple security goals. …”
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SentemQC - A novel and cost-efficient method for quality assurance and quality control of high-resolution frequency sensor data in fresh waters [version 1; peer review: 1 approved,... by Sofie Gyritia Madsen van't Veen, Joachim Audet, Eti Ester Levi, Brian Kronvang, Søren Erik Larsen, Erik Jeppesen, Esben Astrup Kristensen, Anders Nielsen, Thomas Alexander Davidson, Jane Rosenstand Laugesen, Peter Mejlhede Andersen

“…As a result, the method can mark not only individual outliers but also clusters of anomalies. Our analysis shows that the method is robust for detecting anomalies in HF sensor data from multiple water quality sensors measuring nitrate, turbidity, oxygen, and pH. …”
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Adaptive Grid Generation by Solving One-Dimensional Diffusion Equation Using Physics-Informed Neural Networks by Olzhas Turar, Maksat Mustafin, Darkhan Akhmed-Zaki

“…In this work, the construction of adaptive one-dimensional computational grids is considered using a numerical method and physics-informed neural networks (PINNs). …”
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Optimizing Commercial-Scale Storage for Chinese Cabbage (<i>Brassica rapa</i> L. ssp. <i>Pekinensis</i>): Integrating Morphological Classification, Respiratory Heat Effects, and Co... by Sung Gi Min, Timilehin Martins Oyinloye, Young Bae Chung, Won Byong Yoon

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Real-time force/position control of soft growing robots: A data-driven model predictive approach by Kalibala Abdonoor, Nada Ayman A., Ishii Hiroyuki, El-Hussieny Haitham

“…In this article, we present a data-driven dynamic model for a pressure-driven everting vine robot, utilizing a deep neural network (DNN)-based discrete-time dynamic model. …”
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Plasma sphingolipids mediate the association between gut microbiome composition and type 2 diabetes risk in the HELIUS cohort: a case-cohort study by Femke Rutters, Max Nieuwdorp, Mirthe Muilwijk, Irene van Valkengoed, Bert-Jan van den Born, Henrike Galenkamp, Joline W J Beulens, Martin F Overbeek, Mark Davids

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Petri graph neural networks advance learning higher order multimodal complex interactions in graph structured data by Alma Ademovic Tahirovic, David Angeli, Adnan Tahirovic, Goran Strbac

“…Abstract Graphs are widely used to model interconnected systems, offering powerful tools for data representation and problem-solving. However, their reliance on pairwise, single-type, and static connections limits their expressive capacity. …”
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A hybrid deep learning framework for short-term load forecasting with improved data cleansing and preprocessing techniques by Muhammad Sajid Iqbal, Muhammad Adnan, Salah Eldeen Gasim Mohamed, Muhammad Tariq

“…Notably, the proposed approach achieves a remarkable MSE of 0.0058 for load forecasting and 0.0033 for generation forecasting. Comparative analysis with state-of-the-art (SOTA) techniques in terms of accuracy and computational cost underscores the superior accuracy of the proposed framework in forecasting both generation and demand. …”
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Inferring the Density and Membership of Stellar Streams with Flexible Models: The GD-1 Stream in Gaia Data Release 3 by Kiyan Tavangar, Adrian M. Price-Whelan

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Data driven fuel consumption prediction model for green aviation using radial basis function neural network by Yuandi Zhao, Zhongyi Wang, Xiaohui Wang, Ye Song, Yuzhe Han

“…The model provides a lightweight and computationally efficient solution for high-dimensional, nonlinear flight data, ensuring accuracy with lower computational burdens. …”
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BSDR: A Data-Efficient Deep Learning-Based Hyperspectral Band Selection Algorithm Using Discrete Relaxation by Mohammad Rahman, Shyh Wei Teng, Manzur Murshed, Manoranjan Paul, David Brennan

“…Hyperspectral band selection algorithms are crucial for processing high-dimensional data, which enables dimensionality reduction, improves data analysis, and enhances computational efficiency. …”
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Normal weight obesity in adolescents: patterns and associated factors by Maria Kaczmarek

“…Body composition was assessed via bioelectrical impedance analysis. …”
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