Epsilon negative dynamic coded THz metamaterial beamformer for digital information encryption by Eistiak Ahamed, Rasool Keshavarz, Negin Shariati

“…Achieving the desired encryption hinges on synchronizing two pivotal features: the phase difference and the epsilon shifting of the metamaterials. …”
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Ethnic Economy of Sea Mammal Hunting in Chukotsky District (Chukotka Autonomous Okrug, Russia): Activities of Territorial Neighboring Groups by Oksana P. Kolomiets

“…The article considers some features of present-day economic activity in the form of one traditional subsistence pattern characteristic of Chukotka’s indigenous peoples — sea mammal hunting. …”
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Atypical cristae in bundle sheath mitochondria in leaves of Atriplex tatarica (Chenopodiaceae s. str. / Amaranthaceae s. l.) by Fediuk O., Bilyavska N., Akimov Yu., Zolotareva O.

“…Electron microscopic analysis of leaf ultrastructure patterns of Atriplex tatarica (Chenopodiaceae s. str. / Amaranthaceae s. l.) revealed a prominent feature in mitochondria in bundle sheath cells (BSCs). …”
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Artificial intelligence analysis in cyber domain: A review by Liguo Zhao, Derong Zhu, Wasswa Shafik, S Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, Alisa Craig

“…A data set of average feature counts has been executed through a Splunk search command in 1-min intervals. …”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…LSTM networks are integrated to predict vehicle trajectories based on temporal patterns, and a combination of DenseNet and SuperPoint is utilized for robust feature extraction. …”
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Advancing sedimentation modeling in large reservoir systems: Insights from multi-scale process coupling and machine learning by Yuning Tan, Huaixiang Liu, Yongjun Lu, Zhili Wang, Wenjie Li

“…Random Forest outperformed XGBoost, Support Vector Regression, and Artificial Neural Network, demonstrating the most robust performance and the clearest feature attribution. Our climate scenario simulations revealed uneven sedimentation patterns and projected declining sedimentation rates over the next 30 years. …”
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Optimizing Sensitivity in Machine Learning Models for Pediatric Post-operative Kyphosis Prediction by Raja Ayu Mahessya, Dian Eka Putra, Rostam Ahmad Efendi, Rayendra, Rozi Meri, Riyan Ikhbal Salam, Dedi Mardianto, Ikhsan, Ismael, Arif Rizki Marsa

“…This study demonstrates the capacity of decision tree models to extract clinically meaningful patterns from small, imbalanced surgical datasets that elude conventional statistical approaches.…”
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Predicting female football outcomes by machine learning: behavioural analysis of goals as high stress events by Aratz Olaizola, Ibai Errekagorri, Elsa Fernández, Julen Castellano, John Suckling, Karmele Lopez-de-Ipina

“…We applied a comprehensive approach that integrates spatiotemporal and behavioural data during the transitional period following goals focusing on team dynamics, including chaotic and collective behavioural analysis with entropy and fractality, spatial area, movement trajectories, and locomotor patterns. Several well-established ML models and feature extraction techniques were deployed with overall good performance of greater than 70% accuracy, with some specific methodology combinations have superior performance. …”
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Improving ICESat-2 photon classification and tree height estimation using Moran's I and machine learning by Mei-Kuei Lu, Sorin Popescu, Lonesome Malambo

“…Random Forest models were developed and compared, with one model incorporating Moran's I to capture spatial patterns. …”
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Cognitive constraints and lexicogrammatical variability in ASD: from diagnostic discriminators to intervention strategies by Sumi Kato, Sumi Kato, Kazuaki Hanawa

“…To clarify which linguistic variables contribute to this differentiation, the analysis focused on identifying key syntactic features associated with ASD-specific patterns of lexicogrammatical choices.MethodsThis study used the Tag Linear Model, developed in prior work, which enables identification of specific lexicogrammatical discriminators. …”
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Generation of diverse biological forms through combinatorial interactions between tissue polarity and growth. by Richard Kennaway, Enrico Coen, Amelia Green, Andrew Bangham

“…The resulting growth depends on how specified growth patterns interact within the constraints of mechanically connected tissue. …”
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Research on Machine Vision–Based Intelligent Tracking System for Maintenance Personnel by Yinglin Ma, Hongmei Shi, Yao Wang, Baofeng Li

“…A tracking and monitoring system was developed, effectively identifying and tracking maintenance activities, demonstrating a strong practical value. …”
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Mentality in the Context of Interaction Between Social and Virtual Reality by Yulia V. Gavrilova

“…A feature of the modern world is the integration of social and virtual realities: the area of their correlation is being formed, in which the processes of human life activity take place. …”
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Graph-informed convolutional autoencoder to classify brain responses during sleep by Sahar Zakeri, Somayeh Makouei, Sebelan Danishvar

“…The accuracy of the SlS-GICA classifier is 99.92% on the significant feature set. This achievement could be considered in real-time and automatic applications to develop new therapeutic strategies for sleep-related disorders.…”
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Advances in Bract Coloration: Diversity, Pigment Synthesis, and Regulatory Mechanisms in Ornamental Plants by Xiaoyang Li, Yang Liu, Zhiquan Cai, Yiwei Zhou

“…Despite these advances, significant knowledge gaps remain in genetic inheritance patterns, epigenetic regulation, cross-pigment pathway crosstalk, and environmental modulation. …”
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An Explainable Hybrid CNN–Transformer Architecture for Visual Malware Classification by Mohammed Alshomrani, Aiiad Albeshri, Abdulaziz A. Alsulami, Badraddin Alturki

“…Visual malware classification, which transforms malware binaries into grayscale images, has emerged as a promising alternative for recognizing patterns in malicious code. This study presents a hybrid deep learning architecture that combines the local feature extraction capabilities of ConvNeXt-Tiny (a CNN-based model) with the global context modeling of the Swin Transformer. …”
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Automated multi-class MRI brain tumor classification and segmentation using deformable attention and saliency mapping by Erfan Zarenia, Amirhossein Akhlaghi Far, Khosro Rezaee

“…To improve tumor characterization, we applied data augmentation techniques to MR images and developed a hierarchical multiscale deformable attention module (MS-DAM). …”
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Graph convolutional neural networks improved target-specific scoring functions for cGAS and kRAS in virtual screening by Bo Wang, Muhammad Junaid, Wenjin Li

“…Recent studies have demonstrated that target-specific scoring functions developed using machine learning approaches can enhance the accuracy of virtual screening. …”
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Enhancing Education with Machine Learning: Predicting Student Readability Scores by Claire Bell

“…This improvement is attributed to RFST's ability to effectively identify and utilize key textual features. In comparison, the baseline RFC and GRO-optimized Random Forest (RFGR) models achieve accuracies of 0.932 and 0.935, respectively, highlighting their limitations in capturing the intricate linguistic patterns associated with readability. …”
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Clinical characteristics and epilepsy in genomic imprinting disorders: Angelman syndrome and Prader–Willi syndrome by Tzong-Shi Wang, Wen-Hsin Tsai, Li-Ping Tsai, Shi-Bing Wong

“…The distinctive gait pattern, excessive laughter, and characteristic electroencephalography features, which contain anterior-dominated, high-voltage triphasic delta waves intermixed with epileptic spikes, result in early suspicion of AS. …”
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