Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis. by Jörn Diedrichsen, Nikolaus Kriegeskorte

“…Here we develop a common mathematical framework for understanding the relationship of these three methods, which share one core commonality: all three evaluate the second moment of the distribution of activity profiles, which determines the representational geometry, and thus how well any feature can be decoded from population activity. …”
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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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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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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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Using baseline MRI radiomics to predict the tumor shrinkage patterns in HR-Positive, HER2-Negative Breast Cancer by Lijia Wang, Yongchen Wang, Li Yang, Jialiang Ren, Qian Xu, Yingmin Zhai, Tao Zhou

“…IntroductionThis study aimed to develop and validate a predictive model for tumor shrinkage patterns in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer patients undergoing neoadjuvant chemotherapy (NAC).MethodsA retrospective analysis was conducted on 227 HR+/HER2- breast cancer patients with a desire for breast conservation, examining their clinicopathological characteristics, traditional MRI features, and radiomics features. …”
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A Clinical–Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma by Xiangyu Xie, Lei Chen, Kun Li, Liang Shi, Lei Zhang, Liang Zheng

“…This study aimed to develop and validate a predictive model combining clinical and radiomics features for differentiating a high-risk MP/SP in LUAD. …”
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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

“…We found that both language-motor and sensory areas generally encode production-related motoric features across modalities, indicating cooperative interactions between motor and sensory systems. …”
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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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Correlation Between Macroscopic Features of Ischemic Skin Injury and Subdermal Plexus Damage in Lipoabdominoplasty by Giuliano B. Borille, MD, Gustavo A. Pereira Filho, MSc, Mariana Zancanaro, MD, Vinicius Ribeiro, MD, Renato Giannini, MD

“…This multicentric, retrospective study included 71 patients who underwent lipoabdominoplasty and developed ischemic lesions postoperatively. The study involved 46 surgeons and 2 hyperbaric oxygen therapy centers, both of which participated by completing a questionnaire that collected information about the associated treatments and lesion features. …”
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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

“…It introduces the DR module structure for effective feature enhancement and the Detect_Shared architecture for parameter efficiency. …”
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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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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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Adaptive Robust Low-Beam Feature Point Detection Algorithm Based on Convex Hull by Qiqi Shen, Jie Wu

“…Furthermore, two application modes have been developed: one for elbow point detection and another for the simultaneous detection of multiple feature points. …”
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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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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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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

“…While many researchers have explored automated ADHD detection methods, developing accurate, rapid, and reliable approaches remains challenging.MethodsThis study proposes a graph convolutional neural network (GCN)-based ADHD detection framework utilizing multi-domain electroencephalogram (EEG) features. …”
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