Fostering learner autonomy through explicit metacognitive strategy instruction: A study in the Omani EFL context by Surya S. Vellanki, Zahid K. Khan, Saadat Mond

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Business Process Reengineering based on Information Economics by syifa annastasia, Sinung Suakanto, Muharman Lubis

“…This study aims to address that gap by redesigning the recruitment and selection process using an information economics approach evaluating the value of information to drive better decision making and resource allocation. …”
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SP-GEM: Spatial Pattern-Aware Graph Embedding for Matching Multisource Road Networks by Chenghao Zheng, Yunfei Qiu, Jian Yang, Bianying Zhang, Zeyuan Li, Zhangxiang Lin, Xianglin Zhang, Yang Hou, Li Fang

“…However, weighting spatial information on the node feature alone fails to give full play to the expressive power of GNNs. …”
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Assessing the potential impact of grasshopper outbreaks on Patagonian wetlands through mathematical modelling by Laura Soledad Serrano, Ana Laura Pietrantuono, María Fabiana Laguna, Mariana Weigandt, María Emilia Amadio, Valeria Fernández-Arhex

“…We employed this information to develop a spatially explicit stochastic model based on individuals. …”
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Discriminator-free adversarial domain adaptation with information balance by Hui Jiang, Di Wu, Xing Wei, Wenhao Jiang, Xiongbo Qing

“…This approach ensures an explicit domain alignment and category distinction, thus enabling DBDA to fully leverage the predicted discriminative information for an effective feature alignment. …”
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Is cardiovascular risk profiling from UK Biobank retinal images using explicit deep learning estimates of traditional risk factors equivalent to actual risk measurements? A prospec... by Kohji Nishida, Ryo Kawasaki, Yiming Qian, Liangzhi Li, Yuta Nakashima, Hajime Nagahara

“…Objective Despite extensive exploration of potential biomarkers of cardiovascular diseases (CVDs) derived from retinal images, it remains unclear how retinal images contribute to CVD risk profiling and how the results can inform lifestyle modifications. Therefore, we aimed to determine the performance of cardiovascular risk prediction model from retinal images via explicitly estimating 10 traditional CVD risk factors and compared with the model based on actual risk measurements.Design A prospective cohort study design.Setting The UK Biobank (UKBB), a prospective cohort study, following the health conditions including CVD outcomes of adults recruited between 2006 and 2010.Participants A subset of data from the UKBB which contains 52 297 entries with retinal images and 5-year cumulative incidence of major adverse cardiovascular events (MACE) was used. …”
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Aggregating Contextual Information for Multi-Criteria Online Music Recommendations by Jieqi Liu

“…This paper introduces CAMCMusic, a novel context-aware multi-criteria music recommendation system designed to address these limitations without relying on user-specific attributes, music features, or explicit user ratings. CAMCMusic integrates contextual information into a multi-criteria decision-making framework to align music genre recommendations with the user’s contextual situation for generating Top-N music recommendations. …”
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Modeling and Quantifying Interaction of Information and Capacity in Public Transport Disruptions by Mahsa Rahimi Siegrist, Francesco Corman

“…We formalize the agent-based assignment problem in capacitated transit networks for disrupted situations, where some information is available about the disruption. We extend a microsimulation environment to quantify precisely the impact and the number of agents directly and indirectly affected by the disruption, respectively, those passengers who cannot perform their trip because of disrupted services (directly affected passengers), and those passengers whose services are not disrupted but experience additional crowding effects (indirectly affected passengers). …”
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Enhancing implicit sentiment analysis via knowledge enhancement and context information by Yanying Mao, Qun Liu, Yu Zhang

“…The experiments on two implicit sentiment analysis datasets and two explicit sentiment analysis datasets prove that our model can achieve better performances in text sentiment analysis by fully utilizing external commonsense knowledge and context information.…”
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SICGNN: structurally informed convolutional graph neural networks for protein classification by YongHyun Lee, Eunchan Kim, Jiwoong Choi, Changhyun Lee

“…By explicitly including information of the entire graph topology, the proposed model can utilize both local neighborhood and global structural information. …”
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Phylogenetically informed predictions outperform predictive equations in real and simulated data by Jacob D. Gardner, Joanna Baker, Chris Venditti, Chris L. Organ

“…Abstract Inferring unknown trait values is ubiquitous across biological sciences—whether for reconstructing the past, imputing missing values for further analysis, or understanding evolution. Models explicitly incorporating shared ancestry amongst species with both known and unknown values (phylogenetically informed prediction) provide accurate reconstructions. …”
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Physics‐Informed Deep Learning for Forward and Inverse Modeling of Inplane Crustal Deformation by Tomohisa Okazaki, Kazuro Hirahara, Takeo Ito, Masayuki Kano, Naonori Ueda

“…Furthermore, PINNs yielded stable inversion results without explicit regularization terms, implying that solving the governing equations with PINNs implicitly imposes regularization based on the physical requirements. …”
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Nash Equilibrium of Stochastic Partial Differential Game with Partial Information via Malliavin Calculus by Gaofeng Zong

“…All the system coefficients and the objective performance functionals are assumed to be random. We find an explicit strong solution of the linear stochastic partial differential equation with a generalized probabilistic representation for this solution with the benefit of Kunita’s stochastic flow theory. …”
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Maximizing information obtained from standardized fire tests using a Bayesian framework by Balša Jovanović, Ruben Van Coile, Edwin Reynders, Geert Lombaert, Robby Caspeele

“…Current practice is mostly focused on prescriptive design approaches where the performance of the structure in case of fire is assessed based on its performance in standardized fire tests. …”
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Neighborhood Information Aggregation and Multi-View Feature Extraction-Based Contrastive Graph Clustering by Liulong Yao, Jinrong Cui, Yazi Xie, Chengli Sun

“…While these strategies perform well on image data, they often tend to lead to semantic drift when used on graph-structured data, thus limiting the performance of the model. …”
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Relocation of hospital facilities: guidelines for resilient performance by Natália Maciel Tocchetto, Tarcisio Abreu Saurin, Helena Barreto dos Santos

“…Conclusions The guidelines consist of new prescriptive knowledge, explicitly connected to the resilience perspective. …”
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Spatially-informed interpolation for reconstructing lake area time series using semantic neighborhood correlation by Chen Liu

“…By explicitly modeling the inherent hydrological and climatic coherence among neighboring lakes, SNCI provides robust, accurate, and scalable interpolations even in the presence of extensive temporal data losses. …”
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Synchronization-Based Guaranteed-Performance Formation Design for Swarm Systems by Hongtao Dang, Yichen Du, Lingyun Kong, Hui Yao, Jianxiang Xi

“…Firstly, a new formation protocol is presented, where the weights of connected edges are adaptively regulated and the performance constraint is imposed. Then, on the basis of the Riccati inequality, sufficient conditions for synchronization-based guaranteed-performance formation are proposed, and an explicit expression of the guaranteed-performance cost is shown, where it is fully distributed to design gain matrices of the formation protocol in the sense that it is independent of global information of swarm systems. …”
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High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning by Yalan Song, Tadd Bindas, Chaopeng Shen, Haoyu Ji, Wouter J. M. Knoben, Leo Lonzarich, Martyn P. Clark, Jiangtao Liu, Katie vanWerkhoven, Sam Lamont, Matthew Denno, Ming Pan, Yuan Yang, Jeremy Rapp, Mukesh Kumar, Farshid Rahmani, Cyril Thébault, Richard Adkins, James Halgren, Trupesh Patel, Arpita Patel, Kamlesh Arun Sawadekar, Kathryn Lawson

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Information‐Theoretic Scores for Bayesian Model Selection and Similarity Analysis: Concept and Application to a Groundwater Problem by Maria Fernanda Morales Oreamuno, Sergey Oladyshkin, Wolfgang Nowak

“…Exploring the connection between Bayesian inference and information theory, we explicitly link BME and ELPD together with RE and IE to highlight the information flow in BMS and BMJ analyses. …”
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