Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning by ZHANG Hongrui, CAO Xin, JIANG Chao, ZU Anjun, XU Mingxiang

“…The model successfully captures nonlinear and time-varying characteristics in concrete dam deformation processes, showing high consistency with measured deformation patterns and demonstrating excellent engineering practicality. …”
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Asymmetric and transient properties of reciprocal activity of antagonists during the paw-shake response in the cat. by Jessica R Parker, Alexander N Klishko, Boris I Prilutsky, Gennady S Cymbalyuk

“…Previously, we developed a multifunctional, multistable symmetric HCO model which produced slow locomotor-like and fast paw-shake-like activity patterns. …”
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GATOR1 gene variants in focal epilepsy by Kovačević Maša, Vojvodić Nikola, Novaković Ivana

“…Loss of function of GATOR1 leads to constitutive mTORC1 activation that is linked to various malformations of cortical development (MCD), most notoriously focal cortical dysplasia (FCD), but has also been linked to epilepsy in the absence of overt MCD. …”
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Advanced smart assistance with enhancing social interaction and daily activities for visually impaired individuals using deep learning with modified seagull optimization by Sana Alazwari, Hussah Nasser AlEisa, Mohammed Rizwanullah, Radwa Marzouk

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Patient-derived organoids as a model to study tubo-ovarian carcinoma: a pathologist’s perspective by Catarina Alves-Vale, Beatriz Galvão, Ana Rita Silvestre, José Silva Pereira, Li Bei, João Paulo Fernandes, Paula Borralho, Maria Carmo-Fonseca, Noélia Custódio

“…HGSC organoids exhibited limited growth and mostly irregular structures, while preserving the p53 immunostaining pattern of the original tumour. SBT/LGSC and FT organoids maintained features of architectural complexity and faithfully recapitulated the original immunoprofile. …”
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Self-Adaptive Deep Learning Framework for Non-Intrusive Load Monitoring: Addressing Aging Appliance Challenges With Transfer Learning and Pseudo Labeling by W. A. Yasodya, S. M. L. Arampola, M. S. K. Nisakya, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara

“…Unlike traditional NILM models, this approach incorporates a unique self-adaptive feature that enables the model to automatically adapt to changing power patterns resulting from aging appliances. …”
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Applications of gene pair methods in clinical research: advancing precision medicine by Changchun Wu, Xueqin Xie, Xin Yang, Mengze Du, Hao Lin, Jian Huang

“…To bridge methodological development with practical implementation, we establish a reproducible analytical pipeline incorporating feature selection, classifier construction, and model evaluation modules using real-world benchmark datasets from pulmonary tuberculosis studies. …”
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Deep-CABPred: Deep learning model for predicting functional chlorophyll a-b binding proteins in trait-based plant ecology using hybrid embedding with semi-normalized temporal convo... by Farman Ali, Raed Alsini, Tamim Alkhalifah, Fahad Alturise, Wajdi Alghamdi, Majdi Khalid

“…Our approach leverages a combination of advanced feature embedding techniques. We extract multi-source protein information from primary sequences, employing FastText for discriminative subword-level patterns and ProtBERT (a protein large language model) for contextualized sequential features. …”
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Classification of Toraja Wood Carving Motif Images Using Convolutional Neural Network (CNN) by Nurilmiyanti Wardhani, Billy Eden William Asrul, Antonius Riman Tampang, Sitti Zuhriyah, Abdul Latief Arda

“…By understanding the meaning of each Toraja carving, both tourists and the local community can gain knowledge about Toraja culture, thereby preserving and maintaining the culture amidst modern developments. Image processing approaches, particularly the development of Convolutional Neural Networks (CNN), offer a solution for extracting information from the diverse and intricate patterns of Toraja wood carvings. …”
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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…Back-propagation Neural Network (BPNN) is an SL algorithm applied for predicting complex patterns, especially in crop yield and soil health assessments. …”
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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…In addition, the high R-squared value of 0.779234 indicates that approximately 77.92% of the variance in the observed data is explained by the model, showcasing its robustness and effectiveness in capturing the underlying patterns in temperature time series data. Overall, this study underscores the importance of VMD in preprocessing data to enhance feature representation and forecasting accuracy. …”
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Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks by Feng Han, Chongshi Gu

“…The developed DL-based model integrates an enhanced Fast-SCNN backbone for efficient feature extraction, a Lightweight Feature Pyramid Attention (LFPA) module for multi-scale context enhancement, and an Edge Attention Module (EAM) for refined boundary localization. …”
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Dynamic stroma reorganization drives blood vessel dysmorphia during glioma growth by Thomas Mathivet, Claire Bouleti, Matthias Van Woensel, Fabio Stanchi, Tina Verschuere, Li‐Kun Phng, Joost Dejaegher, Marly Balcer, Ken Matsumoto, Petya B Georgieva, Jochen Belmans, Raf Sciot, Christian Stockmann, Massimiliano Mazzone, Steven De Vleeschouwer, Holger Gerhardt

“…Abstract Glioma growth and progression are characterized by abundant development of blood vessels that are highly aberrant and poorly functional, with detrimental consequences for drug delivery efficacy. …”
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Characteristics and formation mechanism of carbon emission efficiency spatial correlation network: Perspective from Shandong Province by Li Zhang, Hongrui Wang, Beinan Guo, Xuan Liu, Caiyun Deng, Ziyang Zhao, Xin Jiang, Yiyang Li

“…Accurately characterizing the spatial correlation network features and mechanisms of carbon emission efficiency (CEE) is critical for promoting regionally coordinated development. …”
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Characteristics of phase synchronization in electrohysterography and tocodynamometry for preterm birth prediction by Jae-Hwan Kang, Young-Ju Jeon, In-Seon Lee, Junsuk Kim

“…This study suggests the critical role of EHG signals and their intricate spatiotemporal patterns in predicting preterm birth, providing insights for the development of more accurate and efficient prediction models.…”
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Explainable Artificial Intelligence for predicting the compressive strength of soil and ground granulated blast furnace slag mixtures by Ahmed Mohammed Awad Mohammed, Omayma Husain, Muyideen Abdulkareem, Nor Zurairahetty Mohd Yunus, Nadiah Jamaludin, Elamin Mutaz, Hashim Elshafie, Mosab Hamdan

“…A database of 200 samples was compiled from the literature, and six ML models—linear regression, decision trees, random forest, artificial neural networks, gradient boosting, and extreme gradient boosting were developed and evaluated. The study highlights the performance of these models and employs SHAP and LIME analysis to evaluate feature importance. …”
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Design and Analysis of Plasma-Based Reconfigurable Maxwell Fish-Eye-Lens Antennas by Jafar Bazrafshan, Fatemeh Sadeghikia, Mohamed Himdi, Ali Karami Horestani, Hajar Binti Ja'afar

“…Therefore, a key novelty of this research is the development of updated analytical design equations for MFE lenses incorporating plasma dielectrics. …”
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Exploring Applications of Convolutional Neural Networks in Analyzing Multispectral Satellite Imagery: A Systematic Review by Antonia Ivanda, Ljiljana Šerić, Maja Braović

“…Remote sensing is of great importance for analyzing and studying various phenomena occurrence and development on Earth. Today is possible to extract features specific to various fields of application with the application of modern machine learning techniques, such as Convolutional Neural Networks (CNN) on MultiSpectral Images (MSI). …”
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Ornamental Plant Growth in Different Culture Conditions and Fluoride and Chloride Removals with Constructed Wetlands by José Luis Marín-Muñiz, María E. Hernández, Sergio Zamora Castro

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Towards an interdisciplinary approach to the study of emotionality in audible speech by L.V. Velichkova, O.V. Kirshinova

“…These accent indicators disrupt the rhythmic pattern of familiar, ‘neutral’ speech and thus create a kind of restless, negative tension. …”
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