Bayesian variable selection with graphical structure learning: Applications in integrative genomics. by Suprateek Kundu, Yichen Cheng, Minsuk Shin, Ganiraju Manyam, Bani K Mallick, Veerabhadran Baladandayuthapani

“…We propose a novel multi-scale Bayesian approach that combines integrative graphical structure learning from multiple sources of data with a variable selection framework-to determine the key genomic drivers of cancer progression. …”
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A hybrid model for refining gross primary productivity estimation by integrating multiple environmental factors by Zhilong Li, Ziti Jiao, Zheyou Tan, Chenxia Wang, Jing Guo, Sizhe Chen, Ge Gao, Fangwen Yang, Xin Dong

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Structural Equation Modeling and Genome-Wide Selection for Multiple Traits to Enhance Arabica Coffee Breeding Programs by Matheus Massariol Suela, Camila Ferreira Azevedo, Ana Carolina Campana Nascimento, Eveline Teixeira Caixeta Moura, Antônio Carlos Baião de Oliveira, Gota Morota, Moysés Nascimento

“…Recognizing the interrelationship among variables becomes critical in genetic breeding programs, where the goal is often to optimize selection for multiple traits. …”
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Development of a river dissolved oxygen prediction model integrating spatial effects and multiple deep learning algorithm by Yubo Zhao, Mo Chen

“…In this model, the DO series is first decomposed into multiple sub-series via VMD, and each sub-series is individually trained and predicted using the FECAM-WTConv-Transformer structure; the final output is obtained by aggregating the predictions. …”
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Characterizing Wake Behavior of Adaptive Aerodynamic Structures Using Reduced-Order Models by Kyan Sadeghilari, Aditya Atre, John Hall

“…Alongside that, the Materials and Methods section shows different modeling environments and their possible integration into FLORIS. …”
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Integrating multiple “omics” analysis for plant metabolites and their functions by ZHOU Guoyan, HU Wangxiong, XU Jianhong, XUE Qingzhong

“…Glucosinolate (GSL) metabolic pathways provide a useful model system for the research of genome structure of the quantitative characters, while the genome-wide association studies (GWAS) fast become the preferred method for analyzing complex quantitative traits. …”
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Adaptive Integrated Navigation Algorithm Based on Interactive Filter by Bin Zhao, Chunlei Gao, Hui Xia, Jinxia Han, Ying Zhu

“…To address the diverse requirements of accuracy and robustness in integrated navigation for unmanned aerial vehicles, an interactive robust filter algorithm that integrates the interactive multiple model concept and leverages the complementary applicability of the strong tracking filter and the smooth variable structure filter is proposed. …”
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Depth-specific soil moisture estimation in vegetated corn fields using a canopy-informed model: A fusion of RGB-thermal drone data and machine learning by Milad Vahidi, Sanaz Shafian, William Hunter Frame

“…Sophisticated regression models such as Gradient Boosting Machines (GBM), Least Absolute Shrinkage and Selection Operator (Lasso), and Support Vector Machines (SVM) were employed to analyze the effects of spectral indices, land surface temperature (LST), and structural canopy variables on soil moisture estimation accuracy. …”
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Multi-Information-Assisted Joint Detection and Tracking of Ground Moving Target for Airborne Radar by Ran Liu, Xiangqian Li, Jinping Sun, Tao Shan

“…Additionally, we innovatively propose an improved Variable Structure Interacting Multiple Model (VS-IMM) filter that leverages road network constraints and detector outputs for tracking, featuring an enhanced model probability calculation to significantly reduce computational time. …”
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Transformer-Based Models for Probabilistic Time Series Forecasting with Explanatory Variables by Ricardo Caetano, José Manuel Oliveira, Patrícia Ramos

“…This study assesses how incorporating these variables enhances forecast accuracy, addressing a research gap in the comprehensive evaluation of explanatory variables within multiple Transformer-based models. …”
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“Quo Vadis urban areas?”: (Re)thinking the future of urban areas using interpretive structural modeling by Beatriz C. S. Caboz, Fernando A. F. Ferreira, Neuza C. M. Q. F. Ferreira, Ronald W. Spahr, Mark A. Sunderman, Margarida R. Santos

“…The main purpose of this study is to propose a process-oriented methodology that integrates cognitive mapping, interpretive structural modeling (ISM) and a matrice d’impacts croisés multiplication appliquée à un classement (MICMAC) analysis to evaluate and prioritize key determinants of urban development. …”
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MR-EILLS: an invariance-based Mendelian randomization method integrating multiple heterogeneous GWAS summary datasets by Lei Hou, Hao Chen, Xiao-Hua Zhou

“…The MR-EILLS model works in both univariate and multivariate scenarios and allows for invalid instrumental variables that violate the exchangeability and exclusion restriction assumptions. …”
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An integrated mutation-based immunoinformatic approach incorporating variability in epitopes: a study based on HIV subtype C by Saurav Kumar Mishra, Neeraj Kumar, Md. Harun Or Rashid, Md. Harun Or Rashid, Sharifa Sultana, Turki M. Dawoud, Mohammed Bourhia, John J. Georrge

“…The vaccine’s structure was modeled and examined to validate its structural quality, and a high population coverage was also found. …”
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Implementation of fatigue model for unidirectional laminate based on finite element analysis: theory and practice by D. Carrella-Payan, B. Magneville, M. Hack, C. Lequesne, T. Naito, Y. Urushiyama, W. Yamazaki, T. Yokozeki, W. Van Paepegem

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Implementation of fatigue model for unidirectional laminate based on finite element analysis: theory and practice by D. Carrella-Payan, B. Magneville, M. Hack, C. Lequesne, T. Naito, Y. Urushiyama, W. Yamazaki, T. Yokozeki, W. Van Paepegem

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Model-based design of a mechanically intelligent shape-morphing structure by Qianyi Chen, Dingena Schott, Jovana Jovanova

“…In conclusion, utilizing multiple smart materials within the model-based design framework offers an efficient approach for developing mechanically intelligent structure capable of complex deformations and variable stiffness, thereby providing support for underwater or offshore engineering applications.…”
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Parallelizing process model integration for model predictive control through oracle design and analysis for a Grover’s algorithm-inspired optimization strategy by Kip Nieman, Helen Durand, Saahil Patel, Daniel Koch, Paul M. Alsing

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Spatial and Spectral Structure-Aware Mamba Network for Hyperspectral Image Classification by Jie Zhang, Ming Sun, Sheng Chang

“…Moreover, the lack of neighborhood spectral information utilization fails to mitigate the impact of spatial variability on classification performance. To address these limitations, we propose a novel model, Dual-Aware Discriminative Fusion Mamba (DADFMamba), which is simultaneously aware of spatial-spectral structures and adaptively integrates discriminative features. …”
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Integrating multi-omics with neuroimaging and behavior: A preliminary model of dysfunction in football athletes by Sumra Bari, Nicole L. Vike, Khrystyna Stetsiv, Alexa Walter, Sharlene Newman, Keisuke Kawata, Jeffrey J. Bazarian, Linda Papa, Eric A. Nauman, Thomas M. Talavage, Semyon Slobounov, Hans C. Breiter

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A comprehensive review on the integration of artificial intelligence in friction stir welding for monitoring, modelling, and process optimization by Mostafa Akbari, Ezatollah Hassanzadeh, Yaghuob Dadgar Asl, Amirhossein Moghanian

“…AI techniques are primarily employed for modeling, monitoring, optimization, and management of complex systems influenced by multiple parameters within industrial processes. …”
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