Research on seismic activity and seismic structural characteristics of the Shandong region by Linhai Lu, Zhenghao Liu, Hanwen Zhang, Chaojun Wu, Jiecheng Sun, Xianfeng Ma, Dingyi Zhou, Han Han, Haojin Zhang, Rui Li

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Grammatical Deviations in the Lesson Plans Among Bachelor of Secondary Education (BSED) English Students by Deo J. Galvez, Marie L. Celesio

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Integrated Geospatial Characterization of Geomorphological and Structural Features in Parts of Enugu, Southeastern Nigeria: Implications for Regional Geology and Land Use by Nkiru Nwokeabia Charity, Ifeanyi Odoh Benard, Arinzechukwu Odinye, Callista Igwebudu Nwanneka, Peter Ezealaji Ifeanyi

“…This comprehensive analysis integrates multiple geospatial and geomorphological features to offer a holistic understanding of land use dynamics and development constraints in Enugu Local Government Areas (LGAs), providing a basis for informed decision-making in regional planning.…”
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Clinicopathologic characteristics and predictive nomogram of skip lymph node metastasis in gastric cancer by Xinwei Zhang, Yuwei Du, Yuegang Li, Chi Xue, Zhi Zhu

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Improved cloud tracking method tolerant to streaky features: application to Venusian cloud images by Yusuke Nara, Takeshi Imamura

“…Abstract An improved cloud tracking method applicable to cloud images dominated by streaky features was developed and applied to Venusian ultraviolet images. …”
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Development of social vocalizations in mice. by Jasmine M S Grimsley, Jessica J M Monaghan, Jeffrey J Wenstrup

“…This study examined patterns in the development of pup isolation vocalizations, and compared these to adult vocalizations. …”
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Development of Professional Competencies in IT-specialists by Anatolii V. Karpov, Aleksandr A. Karpov, Sergei O. Prisyazhnyuk

“…Background. The disclosure of patterns of formation and development of basic competencies of specialists is an essential condition for optimizing the process of professional training and improving the effectiveness of information-related activity in general. …”
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Sex differences in features of atherosclerotic plaques as revealed by various imaging techniques: historical review by Dalya Laban, Alice Kattan, Lamia Ait-Abdellah, Hema Krishna, Hema Krishna, Elizabeth Le Master, Irena Levitan

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Application Framework and Optimal Features for UAV-Based Earthquake-Induced Structural Displacement Monitoring by Ruipu Ji, Shokrullah Sorosh, Eric Lo, Tanner J. Norton, John W. Driscoll, Falko Kuester, Andre R. Barbosa, Barbara G. Simpson, Tara C. Hutchinson

“…A feature point tracking-based algorithm for square checkerboard patterns and a Hough Transform-based algorithm for concentric circular patterns are developed to ensure reliable detection and tracking of image features. …”
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Neural representation of sensorimotor features in language-motor areas during auditory and visual perception by Yuanyi Zheng, Jianfeng Zhang, Yang Yang, Min Xu

“…These findings underscore the dual encoding capacities of language-motor areas, revealing both shared and distinct neural representation patterns across modalities, which may be linked to innate sensory-motor mechanisms and modality-specific processing demands. …”
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Early Prediction of Battery Lifetime Using Centered Isotonic Regression with Quantile-Transformed Features by Muhammad Arslan Khan, Yixing Wang, Benben Jiang

“…The rapid development of lithium-ion (Li-ion) batteries has raised requirements for cycle life prediction to ensure safety and reliability. …”
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Citrus Disease Detection Based on Dilated Reparam Feature Enhancement and Shared Parameter Head by Xu Guo, Xingmeng Wang, Wenhao Zhu, Simon X. Yang, Lepeng Song, Ping Li, Qinzheng Li

“…Current models struggle with accuracy and efficiency due to diverse leaf lesion patterns and complex orchard environments. This study presents YOLOv8n-DE, an improved lightweight YOLOv8-based model for enhanced citrus disease detection. …”
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Adaptive Robust Low-Beam Feature Point Detection Algorithm Based on Convex Hull by Qiqi Shen, Jie Wu

“…It is designed to be applicable to the detection of feature points in “two-segment,” “three-segment,” and “five-segment” low-beam light patterns. …”
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New Appliance Signatures for NILM Based on Mono-Fractal Features and Multi-Fractal Formalism by Anam Mughees, Muhammad Kamran, Neelam Mughees, Abdullah Mughees, Krzysztof Ejsmont

“…This research aims to bridge this gap by developing feature extraction and classification techniques specifically for low-power NILM. …”
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Features of Learning Strategies, Barriers and Motivation of Chinese Students in Russian-Speaking Environment and in China by Natalya S. Brem, Elena M. Dubrovskaya

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Sensitivity Study of Feature Vectors Formed on the Basis of Multiple Scale Transformations of Processed Images by D. V. Vasilieva

“…A concept of image construction for the purposes of feature vector formation was developed.Conclusion. …”
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The interplay between angiogenesis-associated genes and molecular, clinical, and immune features in bladder cancer by Xiaoxiao Guo, Jingxin Yang, Rui Cao, Gangyue Hao

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A Unified Approach to Voice Classification: Leveraging Spectrograms, Mel Spectrograms, and Statistical Features by Muhammad Talha, Huma Ghafoor, Seung Yeob Nam

“…This study presents a multi-input neural network architecture for voice classification that integrates two parallel convolutional neural networks (CNNs) for spectrogram and Mel spectrogram images, along with a fully connected dense network for six handpicked numerical statistical features from time domain signal. The outputs from these branches are flattened and merged, enabling the model to learn complementary patterns from both visual and numerical modalities. …”
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Features of the Reinforcement–Soil Interfacial Effect in Fiber-Reinforced Soil Based on Pullout Tests by Dingkan Xiao, Jun Zhang, Wei Xu, Jiang Wang, Nianyuan Qiu, Juan Wu, Huiyan Ling, Bo Qu, Zhihua Yao

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ADHD detection from EEG signals using GCN based on multi-domain features by Ling Li, Xueyang Guo, Zihan Yang, Yanping Zhao, Xu Liu, Junxian Yang, Yanyan Chen, Xinxian Peng, Lina Han

“…Finally, a GCN model integrates these time-frequency features with topological patterns from the connectivity matrix for ADHD classification.ResultsEvaluated on two EEG datasets, the proposed method achieved average accuracies of 97.29% and 96.67%, outperforming comparative models (XGBoost, LightGBM, AdaBoost, random forest). …”
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