Calculation of Shear-Bearing Capacity of Aluminum Alloy-Concrete Composite Beam by Chenghua Li, Ziliang Lu

“…An improved shear capacity formula was derived based on the tension–compression bar model and the superposition method. The proposed formula achieved an average ratio of 1.018 to finite element results, with a standard deviation of 0.151, and the proposed formula was validated against 22 FEA models, demonstrating excellent agreement with numerical results and confirming its reliability for practical engineering applications. …”
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Coupled estimation of internal tides and turbulent motions via statistical modal decomposition by I. Maingonnat, G. Tissot, N. Lahaye

“…The method is presented and tested in an idealised framework based on the rotating-shallow-water model, where we provide a physical interpretation for the decomposition method based on theoretical considerations. …”
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Epileptic Seizure Detection in Neonatal EEG Using a Multi-Band Graph Neural Network Model by Lihan Tang, Menglian Zhao

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Offline reinforcement learning combining generalized advantage estimation and modality decomposition interaction by Kaixin Jin, Lifang Wang, Xiwen Wang, Wei Guo, Qiang Han, Xiaoqing Yu

“…Abstract Transformers show great potential in offline reinforcement learning via trajectory sequence modeling for action prediction. However, existing Transformer-based methods face limitations, such as ineffective trajectory stitching and the neglect of deep interactions within and between multimodal information in trajectories. …”
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Decomposition Residual Odor Volatiles in Soil from a West Texas Environment by Jennifer Raymer, Jorge Ulises Rojas-Guevara, Paola Alexandra Prada-Tiedemann

“…After removal, the headspace of soil samples, taken from under the cadaver decomposition island (CDI), were analyzed once per week for a period of 4 weeks using solid phase micro extraction- gas chromatography/mass spectrometry (SPME-GC/MS) as the instrumental analysis method. …”
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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

“…In this study, we develop a systematic methodology with multivariate models and machine learning algorithms to (i) model complex patterns of relationships or multi-phenotypic differences between the thermal environment and thermoregulatory, hormonal, biochemical, hematological and productive responses; and (ii) identify potential associations among biological relationships that may underlie shared and specific phenotypic patterns of adaptive responses. …”
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Bayesian Robust Tensor Decomposition Based on MCMC Algorithm for Traffic Data Completion by Longsheng Huang, Yu Zhu, Hanzeng Shao, Lei Tang, Yun Zhu, Gaohang Yu

“…In this paper, a Bayesian robust tensor decomposition method (MBRTF) based on the Markov chain Monte Carlo (MCMC) algorithm is proposed. …”
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Simple Fermionic backflow states via a systematically improvable tensor decomposition by Massimo Bortone, Yannic Rath, George H. Booth

“…This ansatz naturally encodes many-electron correlations without the ordering dependence of other tensor decompositions. We benchmark its performance against standard models, demonstrating improved accuracy over comparable methods in Fermi-Hubbard and molecular systems and competitive results with state-of-the-art density matrix renormalization group (DMRG) in ab initio 2D hydrogenic lattices. …”
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Measuring the credit gap: a forecast combination approach by N. Kundan Kishor, Nam Nguyen

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Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis by Ben Gabrielson, Hanlu Yang, Trung Vu, Vince Calhoun, Tulay Adali

“…Generalizations of matrix decompositions to multidimensional arrays, called tensor decompositions, are simple yet powerful methods for analyzing datasets in the form of tensors. …”
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Preparation characterization and non-isothermal decomposition kinetics of different carbon nitride sheets by M. Elshafie, S.A. Younis, P. Serp, E.A.M. Gad

“…The energy of activation Ea and the frequency factor A. Decomposition pathway were investigated using four mathematical methods and 35 mechanisms (g(α)) models. …”
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Socioeconomic inequalities in cervical cancer screening practices in Vietnam: a decomposition analysis by Thi Bich-Van Nguyen, Kim-Duy Vu, Lam Tung Ngoc Cu, Minh Hai Nguyen Ngoc, Hoang-Dung Ho

“…The study utilised decomposition analysis to unravel the contributions of various determinants to socioeconomic disparities in screening uptake, employing Poisson regression with robust variance models to explore the association between socioeconomic status, quantified through Wealth Index quintiles, and screening practices. …”
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An improved deep learning approach for speech enhancement by Malek Miled, Mohamed Anouar Ben Messaoud

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Single X-ray Projection Material Decomposition using a Mesh Projector by Fleur Linsen, Domenico Iuso, Jan Sijbers

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Fuzzy Galaxies or Cirrus? Decomposition of Galactic Cirrus in Deep Wide-field Images by Qing Liu, Roberto Abraham, Peter G. Martin, William P. Bowman, Pieter van Dokkum, Shany Danieli, Ekta Patel, Steven R. Janssens, Zili Shen, Seery Chen, Ananthan Karunakaran, Michael A. Keim, Deborah Lokhorst, Imad Pasha, Douglas L. Welch

“…In this paper, we present a technique for the photometric characterization of Galactic cirrus based on (1) extraction of its filamentary or patchy morphology and (2) incorporation of color constraints obtained from Planck thermal dust models. Our decomposition method is illustrated using a ~10 deg ^2 imaging data set obtained by the Dragonfly Telephoto Array, and its performance is explored using various metrics that characterize the flatness of the sky background. …”
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A Mechanical Fault Diagnosis Method for On-Load Tap Changers Based on GOA-Optimized FMD and Transformer by Ruifeng Wei, Zhenjiang Chen, Qingbo Wang, Yongsheng Duan, Hui Wang, Feiming Jiang, Daoyuan Liu, Xiaolong Wang

“…To achieve this, a novel hybrid method is proposed that integrates the Gazelle Optimization Algorithm (GOA), Feature Mode Decomposition (FMD), and a Transformer-based classification model. …”
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Enhanced bearing health indicator extraction using slope adaptive signal decomposition for predictive maintenance by Dev Bhanushali, Pooja Kamat, Harsh Dhiman

“…This study introduces the Slope Adaptive Signal Decomposition (SASD) algorithm, a novel method for extracting enhanced intrinsic machine health indicators from vibration data. …”
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Crashworthiness and optimization for foam-filled multi-layer composite lattice structures by Jiye Chen, Wangwang He, Hai Fang, Yong Zhuang, Zhixiong Zhang, Yufeng Zhao

“…Foam materials have been widely used to fill composite lattice structures to improve energy absorption and mechanical properties. …”
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Machine learning methods for predicting human-adaptive influenza A virus reassortment based on intersegment constraint by Dan-Dan Zeng, Dan-Dan Zeng, Yu-Rong Cai, Sen Zhang, Fang Yan, Tao Jiang, Jing Li

“…IntroductionIt is not clear about mechanisms underlining the inter-segment reassortment of Influenza A viruses (IAVs).We analyzed the viral nucleotide composition (NC) in coding sequences,examined the intersegment NC correlation, and predicted the IAV reassortment using machine learning (ML) approaches based on viral NC features.MethodsUnsupervised ML methods were used to examine the NC difference between human-adapted and zoonotic IAVs. …”
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Corrosion resistance prediction of high-entropy alloys: framework and knowledge graph-driven method integrating composition, processing, and crystal structure by Guangxuan Song, Dongmei Fu, Yongjie Lin, Lingwei Ma, Dawei Zhang

“…Abstract The prediction of corrosion resistance in High-entropy alloys (HEAs) faces challenges due to previous machine learning methods not fully capturing the interdependencies between composition, processing, and crystal structure. …”
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