P-GELU: A Novel Activation Function to Optimize Whisper for Darija Speech Translation by Maria Labied, Abdessamad Belangour, Mouad Banane

“…Activation functions play a critical role in optimizing deep learning models, directly influencing gradient flow, convergence stability, and overall translation accuracy. …”
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Urban Functional Zone Mapping by Integrating Multi-Source Data and Spatial Relationship Characteristics by Daoyou Zhu, Xu Dang, Wenjia Shi, Yixiang Chen, Wenmei Li

“…This framework leverages the OpenStreetMap (OSM) road network to partition the study area into functional units, employs a graph model to represent urban functional nodes and their intricate spatial topological relationships, and harnesses the capabilities of Graph Convolutional Network (GCN) to fuse these multi-dimensional features through end-to-end learning for accurate urban function discrimination. …”
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Reliability and validity of the six-minute step test in assessing the functional capacity of hemodialysis patients by Carla Cristina Lima, Maria Eduarda Godoy, Débora Kellen Ferreira Fratoni, Elaine Paulin

“…Purpose Hemodialysis patients often experience functional limitations that are challenging to assess due to equipment and space constraints. …”
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Using large language models to extract plant functional traits from unstructured text by Viktor Domazetoski, Holger Kreft, Helena Bestova, Philipp Wieder, Radoslav Koynov, Alireza Zarei, Patrick Weigelt

“…Abstract Premise Functional plant ecology seeks to understand how functional traits govern species distributions, community assembly, and ecosystem functions. …”
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Enriched environment improves memory function by promoting synaptic remodeling in vascular dementia rats by Shuang Lin, Chuan-Jie Wang, Peng-Kun Yang, Bing Li, Yi Wu, Ke-Wei Yu

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Teaching Internal Medicine Residents to Critically Appraise the Role of Race in Pulmonary Function Testing by Ananya Bhatia-Lin, Nirav Bhakta, Neha Deshpande, Laura Granados, Rosemary Adamson

“…Discussion This curriculum was successful in engaging participants in critically appraising race-based interpretations of pulmonary function testing. The structure of the curriculum could be repurposed to create didactic content on other examples of race-based clinical algorithms.…”
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Reduced Functional Connectivity in Nucleus Accumbens Subregions Associates With Cognitive Changes in Alzheimer's Disease by Lefan Yu, Mengmeng Feng, Yi Shang, Zhaohai Ren, Hanqi Xing, Yue Chang, Ke Dong, Yao Xiao, Hui Dai

“…This study aimed to explore alterations in the functional connectivity (FC) of NAc subregions in AD patients and to explore their associations with neuropsychological profiles. …”
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Immunotherapy against tau fragment diminishes AD pathology, improving synaptic function and cognition by Jie Xiang, Zhengjiang Qian, Ye Xi, Yanuo Wei, Guangxing Wang, Xia Liu, Zhi-Hao Wang, Zhentao Zhang, Shengxi Wu, Keqiang Ye

“…Conclusions Targeting Tau N368 through immunotherapy alleviates tau-driven neurodegeneration, restores synaptic function, and improves accompanying Aβ pathology in AD models. …”
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Disrupted resting-state interhemispheric functional connectivity in patients with first-episode moyamoya disease by Jiajia Nie, Li Qi, Pan Wu, Chao Li, Baogen Du, Chen Chen, Shanshan Cao, Qiang Wei, Kai Wang, Ling Wei, Yanghua Tian

“…Abstract Moyamoya disease (MMD) has been reported to be associated with a wide range of structural and functional abnormalities of bilateral hemispheres. However, whether the interhemisphere functional connectivity (FC) of MMD patients is altered and its relationship with cognitive impairments still remain unclear. …”
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Applications and advances of combined fMRI-fNIRs techniques in brain functional research by Lirui Yang, Lirui Yang, Lirui Yang, Lirui Yang, Zehua Wang, Zehua Wang, Zehua Wang, Zehua Wang, Zehua Wang

“…Understanding the intricate functions of the human brain requires multimodal approaches that integrate complementary neuroimaging techniques. …”
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Exploring Math Moments: Middle-schoolers’ Phases of Problem-solving, Executive Functions in Practice, and Collaborative Problem Solving by K. Ann Renninger, Ricardo Böheim, Julien Corven, Maria Consuelo De Dios, Maeve R. Hogan, Moe Htet Kyaw, Ana G. Michels, Marina Nakayama, Pablo Torres Núñez, Helena Werneck de Souza Dias, Feven Yared

“…In addition, to further describe the students’ cognitive and behavioral engagement, we considered both the process of students' use of executive functions (EF), during problem solving, termed executive functions in practice (EFP), as well as the stage of CPS (Participation, Cooperation, and Collaboration), during phases of problem solving. …”
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Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic vulnerabilities in glioma by Elizabeth G. Fernandez, Wilson X. Mai, Kai Song, Nicholas A. Bayley, Jiyoon Kim, Henan Zhu, Marissa Pioso, Pauline Young, Cassidy L. Andrasz, Dimitri Cadet, Linda M. Liau, Gang Li, William H. Yong, Fausto J. Rodriguez, Scott J. Dixon, Andrew J. Souers, Jingyi Jessica Li, Thomas G. Graeber, Timothy F. Cloughesy, David A. Nathanson

“…Accordingly, a machine-learning approach identifies a composite molecular and functional signature that best predicts responses of diverse intracranial glioma models to standard-of-care therapies combined with ABBV-155, a clinical drug targeting intrinsic apoptosis. …”
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Functional Connectivity Changes in Primary Motor Cortex Subregions of Patients With Obstructive Sleep Apnea by Lifeng Li, Qimeng Shi, Bowen Fang, Yuting Liu, Xiang Liu, Yongqiang Shu, Yingke Deng, Yumeng Liu, Haijun Li, Junjie Zhou, Dechang Peng

“…This study examined functional connectivity (FC) changes in subregions of the primary motor cortex (M1) in patients with OSA and their association with sleep structure, cognition, and clinical features. …”
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A New Approach to Model Machine Learning by Using Complex Bipolar Intuitionistic Fuzzy Information by Naeem Jan, Rabia Maqsood, Abdul Nasir, Mohsin S. Alhilal, Amerah Alabrah, Naziha Al-Aidroos

“…Many industries are developing robust models, capable of analyzing huge and complex data by using machine learning (ML) while delivering faster and more accurate results on vast scales. …”
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The Prediction of Learned Resourcefulness of High School Students by the Relationship within Their Families by Yemliha COSKUN

“…Besides, it is inquiredwhether the learned resourcefulness level of high school students differentiateaccording to the healthiness of family functions. …”
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Image-based evaluation of single-cell mechanics using deep learning by Zhaozhao Wu, Yiting Feng, Ran Bi, Zhiqiang Liu, Yudi Niu, Yuhong Jin, Wenjing Li, Huijun Chen, Yan Shi, Yanan Du

“…Abstract Mechanical properties of cells have been proposed as potential biophysical markers for cell phenotypes and functions since they are vital for maintaining biological activities. …”
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Promising methods of prenatal diagnostics based on passive sensors and machine learning by A. A. Ivshin, V. M. Vorobyova, N. A. Malyshev

“…The following keywords in Russian and English were used for selection: "modern methods of prenatal diagnostics", "fetal monitoring", "assessment of fetus functional state", "passive sensors", "artificial intelligence", "machine learning". …”
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Bregman divergences for physically informed discrepancy measures for learning and computation in thermomechanics by Andrieux, Stéphane

“…With view on the context of convex thermomechanics, we propose tools based on the concept of Bregman divergence, a notion introduced in the 1960s and used in learning and optimization as well. This study is motivated by the need of “discrepancy measures” between physically constrained fields that are used both in traditional algorithms, analysis methods and data driven modelling or applications as well.We give also a characterization of symmetrical Bregman divergences through their generating functions which can only be quadratic forms. …”
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Neurological soft signs in comorbid learning and attention deficit hyperactivity disorders by Runa Uslu, Emine Gül Kapçi, Didem Oztop

“…Multivariate analysis of variance showed that these factors of NESS were significantly different between the clinical groups and the non-clinical group. The discriminant functional analysis also yielded significant canonical discriminant functions, correctly classifying 85% of the clinical and non-clinical groups of children. …”
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Research of the Gear Fault Diagnosis based on Improved LMD and Manifold Learning by Shen Chao, Yang Jianwei, Yao Dechen, Li Xi

“…Then,considering fuzzy entropy can be use to distinguish the complexity of the signal effectively,so the fuzzy entropy of Product functions（PF） by LMD is calculated,a high-dimensional feature vector can be obtain with product functions. …”
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