Combined x-ray diffraction, electrical resistivity, and ab initio study of (TMTTF)_{2}PF_{6} under pressure: Implications for the unified phase diagram by Miho Itoi, Kazuyoshi Yoshimi, Hanming Ma, Takahiro Misawa, Takao Tsumuraya, Dilip Bhoi, Tokutaro Komatsu, Hatsumi Mori, Yoshiya Uwatoko, Hitoshi Seo

“…(ii) The degree of dimerization in the intrachain transfer integrals, as the result of the decrease in structural dimerization together with the change in the intermolecular configuration, almost disappears above 4 GPa; the interchain transfer integrals also show characteristic variations under pressure. …”
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A Novel Open Circuit Fault Diagnosis for a Modular Multilevel Converter with Modal Time-Frequency Diagram and FFT-CNN-BIGRU Attention by Ziyuan Zhai, Ning Wang, Siran Lu, Bo Zhou, Lei Guo

“…To solve this problem, an intelligent diagnosis method is proposed to integrate the modal time–frequency diagram and FFT-CNN-BiGRU-Attention. …”
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A State-Supervised Model and Novel Anomaly Index for Gas Turbines Blade Fault Detection Under Multi-Operating Conditions by Yuan Xiao, Kun Feng, Dongyan Miao, Peng Zhang, Jiaxin Yang

“…First, a State-Supervised Variational Autoencoder (SS-VAE) model is introduced, which integrates the learning process of turbine operational states into the VAE bypass, enabling it to capture variations in vibration signal data across different operating conditions. …”
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KEDM: Knowledge-Embedded Diffusion Model for Infrared Image Destriping by Lingxiao Li, Xin Wang, Dan Huang, Yunan He, Zhuqiang Zhong, Qingling Xia

“…To address challenges such as incomplete stripe removal, potential loss of image details and textures, and the generation of artificial artifacts during destriping, we propose a novel stripe removal method based on a knowledge-embedded diffusion model (KEDM). …”
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Extended Minimal Atomicity through Nondifferentiability: A Mathematical-Physical Approach by Gabriel Gavriluţ, Alina Gavriluţ, Maricel Agop

“…In the one-dimensional stationary case of the fractal Schrödinger type geodesics, a special symmetry induced by the homographic group in Barbilian’s form “makes possible the synchronicity” of all entities of a given physical system. The integral and differential properties of this group under the restriction of defining a parallelism of directions in Levi-Civita’s sense impose correspondences with the “dynamics” of the hyperbolic plane so that harmonic mappings between the ordinary flat space and the hyperbolic one generate (by means of a variational principle) a priori probabilities in Jaynes’ sense. …”
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Deep Learning to Estimate Model Biases in an Operational NWP Assimilation System by Patrick Laloyaux, Thorsten Kurth, Peter Dominik Dueben, David Hall

“…The different strengths and weaknesses of both deep learning and weak constraint 4D‐Var are discussed, highlighting the potential for each method to learn model biases effectively and adaptively.…”
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Application of an improved LSTM model based on FECA and CEEMDAN VMD decomposition in water quality prediction by Jie Long, Chong Lu, Yiming Lei, Zhong Yuan Chen, Yihan Wang

“…Abstract To address the limitations of existing water quality prediction models in handling non-stationary data and capturing multi-scale features, this study proposes a hybrid model integrating Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Variational Mode Decomposition (VMD), Long Short-Term Memory Network (LSTM), and Frequency-Enhanced Channel Attention (FECA). …”
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BlindFG: Learning Contextual Fishing Trajectories for Unreported Fishing Gear Classification by Changha Lee, Chan-Hyun Youn

“…Experimental evaluations demonstrate that our method significantly enhances the prediction of vessel trajectories and the accurate classification of AIS-off fishing practices worldwide.…”
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A Numerical Approach to Calculate the Radiation Efficiency of Baffled Planar Structures Using the Far Field by Mario A. GONZÁLEZ-MONTENEGRO, Roberto JORDAN, Arcanjo LENZI, Jorge P. ARENAS

“…On the other hand, few works exist in which the calculation is done in the far field from near field data by the use of radiation matrices, possibly because the numerical integration becomes complicated and expensive due to large variations of directivity of the source. …”
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Optimal Control Strategy and Evaluation Framework for Frequency Response of Combined Wind–Storage Systems by Jie Hao, Huiping Zheng, Xueting Cheng, Yuxiang Li, Liming Bo, Juan Wei

“…The increasing integration of wind turbines into the power grid has reduced the system frequency stability, necessitating the integration of energy storage systems in primary frequency regulation. …”
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Multi-Step Natural Gas Load Forecasting Incorporating Data Complexity Analysis with Finite Features by Ning Tian, Bilin Shao, Huibin Zeng, Meng Ren, Wei Zhao, Xue Zhao, Shuqiang Wu

“…This study aims to bring innovative ideas to load forecasting by integrating complex features into the decomposition forecasting framework.…”
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Study of the mechanical properties of double line pipelines under silty sandstone and pipeline coupling by Cun-dong Xu, Wen-hao Han, Jin-xi Xia, Jun-kun Nie, Jun Cao, Zhi-hang Wang

“…A numerical simulation method is adopted to establish a three-dimensional finite element model integrating a “double-line pipeline-artificial fill-foundation” to study the influence of different single-layer filling thicknesses and internal water pressures on the mechanical properties of the double-line pipeline. …”
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Transformations of Optimal Control Problems by A. Tsirlin

“…The paper considers such transformations of variational and optimal control problems (by a change of phase variables) that help to get the solution. …”
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A Multi-Criteria Decision-Making Framework for Evaluating Emerging Digital Technologies in Supply Chain Optimization by Nabil M. AbdelAziz, Dina Mohamed, Hasnaa Soliman

“…A sensitivity analysis confirmed the robustness of these rankings against weight variations, while comparative validation using alternative MCDM methods (e.g., CODAS,COPRAS, EDAS, and SPOTIS) further supports the reliability of the findings. …”
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Transient Voltage Unit Protection Based on Fault Information Fusion by Zhenwei Guo, Ruiqiang Zhao, Haojie Li, Yongyan Jiang

“…Transient voltage high-frequency instantaneous amplitudes are obtained and integrated using the Variational Mode Decomposition Hilbert Transform (VMD-HT) to increase the stability of high-frequency fault signal detection. …”
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STAGE framework: A stock dynamic anomaly detection and trend prediction model based on graph attention network and sparse spatiotemporal convolutional network. by Ming Shi, Roznim Mohamad Rasli, Shir Li Wang

“…This paper proposes the STAGE framework, which integrates the Graph Attention Network (GAT), Variational Autoencoder (VAE), and Sparse Spatiotemporal Convolutional Network (STCN), to enhance the accuracy of stock prediction and the robustness of anomaly data detection. …”
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Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

“…Specifically, the proposed model comprises three key components: (i) a mutual information-based feature selection method to identify the most significant input variables influencing energy consumption; (ii) a variational mode decomposition (VMD) approach to decompose the original energy consumption signal into intrinsic mode functions (IMFs), capturing relevant trends and eliminating noise; and (iii) a long short-term memory (LSTM) neural network to perform time-series forecasting of the target energy consumption values. …”
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A Novel Technique for Predicting the Thermal Behavior of Stratospheric Balloon by Yunpeng Ma, Jun Huang, Mingxu Yi

“…This paper is devoted to introduce a novel method of the operational matrix of integration for Legendre wavelets in order to predict the thermal behavior of stratospheric balloons on float at high altitude in the stratosphere. …”
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Ultra-wideband unidirectional pseudospin-polarized waveguide with dual boundary conditions by Haddi Ahmadi, Kazem Zafari, Mohammad Pasdari-Kia, Nasrin Razmjooei, Kamalodin Arik, Zahra Ahmadi, Mahdi Nooshyar, Hamid Nezamdoost, Hamed Saghaei, Farzaneh Sadat Ghoreishi, Homayoon Oraizi

“…To achieve precise performance predictions, we employ a rigorous variational method to calculate the surface impedance of the metasurfaces, enhancing the accuracy of analytical and numerical results. …”
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The potential of observing atmospheric rivers with Global Navigation Satellite System (GNSS) radio occultation by B. Rahimi, U. Foelsche, U. Foelsche

“…The retrieval of water vapor from GNSS-RO data requires background information, which is usually incorporated by the one-dimensional variational method (1D-Var) that combines observations and background in an optimal manner. …”
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