A Yarn Quality Prediction Method Based on M-ESTIMATOR Robust Broad Learning System With Tightly Cascaded Feature Layers by Baowei Zhang, Zhilin Guo, Yonghua Wang

Subjects: “…Broad learning system…”
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Rapid prediction of key residues for foldability by machine learning model enables the design of highly functional libraries with hyperstable constrained peptide scaffolds. by Fei Cai, Yuehua Wei, Daniel Kirchhofer, Andrew Chang, Yingnan Zhang

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Pilot evaluation of a socio-emotional learning program on executive functions in elementary school students: a cluster-randomized controlled trial by Rita Antunes, Rita Antunes, Tânia Carneiro, Luciana Joaquim, Luciana Joaquim, Margarida Matos, Joana Alexandre, Marisa G. Filipe

Subjects: “…social and emotional learning program…”
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Flood Classification and Improved Loss Function by Combining Deep Learning Models to Improve Water Level Prediction in a Small Mountain Watershed by Rukai Wang, Ximin Yuan, Fuchang Tian, Minghui Liu, Xiujie Wang, Xiaobin Li, Minrui Wu

“…We employ STGCN and GWN models with the spatiotemporal attention mechanism. Enhanced loss functions further refine flood prediction accuracy. …”
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A deep machine learning model development for the biomarkers of the anatomical and functional anti-VEGF therapy outcome detection on retinal OCT images by B.E. Malyugin, S.N. Sakhnov, L.E. Axenova, K.D. Axenov, E.V. Kozina, V.V. Vronskaya, V.V. Myasnikova

“…Predictors of this anatomical outcome, as well as predictors of functional outcome or final visual acuity, can be assessed using optical coherence tomography (OCT). …”
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The relationship between parent’s mental health and professional functioning and students’ e-learning burnout and well-being during the COVID-19 pandemic by Katarzyna Tomaszek, Agnieszka Muchacka-Cymerman

“…Student burnout from distance learning did not significantly correlate with work flow and online job burnout of parents. …”
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Effects of repetitive transcranial magnetic stimulation on learning and memory cognitive function in rats with vascular cognitive impairment and its neural induction mechanism by Jiati Wang, Huan Gao

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Deep Learning Strategy for UAV-Based Multi-Class Damage Detection on Railway Bridges Using U-Net with Different Loss Functions by Yong-Hyoun Na, Doo-Kie Kim

“…To enable multi-class segmentation, the U-Net model was trained using three different loss functions: Cross-Entropy Loss, Focal Loss, and Intersection over Union (IoU) Loss. …”
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Fine-grained building function recognition with street-view images and GIS map data via geometry-aware semi-supervised learning by Weijia Li, Jinhua Yu, Dairong Chen, Yi Lin, Runmin Dong, Xiang Zhang, Conghui He, Haohuan Fu

Subjects: “…Building function…”
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Machine learning analysis of kinematic movement features during functional tasks to discriminate chronic neck pain patients from asymptomatic controls by Filippo Moggioli, Óscar Rodríguez-López, Elena Bocos-Corredor, Constantino Antonio García, Sonia Liébana, Tomás Pérez-Fernández, Cristina Sánchez, Susan Armijo-Olivo, José Angel Santos-Paz, Aitor Martín-Pintado-Zugasti

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Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms by Saadiallakh Normatov, Pavel V. Nesterov, Timur A. Aliev, Alexandra A. Timralieva, Alexander S. Novikov, Ekaterina V. Skorb

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A bespoke water T–maze apparatus and protocol: an optimized, reliable, and repeatable method for screening learning, memory, and executive functioning in laboratory mice by Jeremy Davidson Bailoo, Susan E. Bergeson, Igor Ponomarev, Joshua O. Willms, Brent R. Kisby, Gail A. Cornwall, Clinton C. MacDonald, J. Josh Lawrence, J. Josh Lawrence, Vadivel Ganapathy, Sathish Sivaprakasam, Praneetha Panthagani, Scott Trasti, Justin A. Varholick, Michael Findlater, Amrika Deonarine

“…Given the robust performance observed across spatial acquisition (learning and memory) as well as during reversal learning (executive function), we further reduced (by 43%) the overall distance and time that the animal must swim in order to find the escape platform in a bespoke standalone Water T-Maze (WTM). …”
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Virally mediated expression of a biologically active peptide to restrain the nuclear functions of ERK1/2 attenuates learning extinction but not acquisition by Bar Izkovich, Adonis Yiannakas, Sapir Ne’eman, Sailendrakumar Kolatt Chandran, Kobi Rosenblum, Efrat Edry

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Evaluating the Effect of Thermal Treatment on Phenolic Compounds in Functional Flours Using Vis–NIR–SWIR Spectroscopy: A Machine Learning Approach by Achilleas Panagiotis Zalidis, Nikolaos Tsakiridis, George Zalidis, Ioannis Mourtzinos, Konstantinos Gkatzionis

“…This study explores the thermal stability of phenolic compounds in various functional flours using visible, near and shortwave-infrared (Vis–NIR–SWIR) spectroscopy (350–2500 nm), integrated with machine learning (ML) algorithms. …”
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Machine Learning-Assisted High-Throughput Screening for Electrocatalytic Hydrogen Evolution Reaction by Guohao Yin, Haiyan Zhu, Shanlin Chen, Tingting Li, Chou Wu, Shaobo Jia, Jianxiao Shang, Zhequn Ren, Tianhao Ding, Yawei Li

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Uncovering biologically relevant Autism subtypes using advanced machine learning techniques by Christopher "Gabby" Vento, Joseph Cubells, Larry Young, Elissar Andari

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Hyperparameter optimisation in deep learning from ensemble methods: applications to proton structure by Juan Cruz-Martinez, Aron Jansen, Gijs van Oord, Tanjona R Rabemananjara, Carlos M R Rocha, Juan Rojo, Roy Stegeman

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Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

Subjects: “…Reinforcement learning…”
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Estimation of Cation Exchange Capacity for Low-Activity Clay Soil Fractions Using Experimental Data from South China by Jun Zhu, Zhong-Xiu Sun

Subjects: “…pedotransfer function…”
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Screening tools for subjective cognitive decline and mild cognitive impairment based on task-state prefrontal functional connectivity: a functional near-infrared spectroscopy study by Zhengping Pu, Hongna Huang, Man Li, Hongyan Li, Xiaoyan Shen, Lizhao Du, Qingfeng Wu, Xiaomei Fang, Xiang Meng, Qin Ni, Guorong Li, Donghong Cui

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