The detection of alcohol intoxication using electrooculography signals from smart glasses and machine learning techniques by Rafał J. Doniec, Natalia Piaseczna, Konrad Duraj, Szymon Sieciński, Muhammad Tausif Irshad, Ilona Karpiel, Mirella Urzeniczok, Xinyu Huang, Artur Piet, Muhammad Adeel Nisar, Marcin Grzegorzek

“…The Bagged Trees achieved the highest accuracy of 79%. The most important features to detect simulated alcohol intoxication were the blink rate and the velocity of the saccade, a rapid simultaneous movement of both eyes in the same direction. …”
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Ultrasound molecular imaging of M2 macrophages for early detection of chronic rejection in heart transplantation by Jia Xu, Cheng Deng, Tang Gao, Mengrong He, Wenpei Fu, Xin Zhang, Yin Bai, Jiani Qiu, Rui Wang, Yihan Chen, Qiaofeng Jin, Li Zhang, Qing Lv, Mingxing Xie, Wenqian Wu

“…The primary pathological features of CR encompass cardiac allograft vasculopathy and myocardial fibrosis. …”
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Experimental Study of Trajectory Features for the Recognition of Low-Flying Low-Speed Radar Targets Using Passive Coherent Radar Systems by V. L. Dao, A. A. Konovalov, M. H. Le

“…Specific features of the trajectory of small aerial targets of each type were investigated. …”
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Clinical and genetic features of a family with multinodular goiter harboring a DICER1 c.2035 A >G variant by Man-Li Guo, Xu Hu, Hong Zhu, Ling-Guang Luo, Shao-Gang Ma

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Development of a double-antigen sandwich ELISA for rapid and accurate detection of antibodies against Capripoxvirus by Wanying Wang, Zhengwang Shi, Juncong Luo, Huancheng Liao, Lu Feng, Yuqian Zhu, Yongyu Lin, Xintai Shi, Fan Zhang, Tao Xi, Jie Chen, Hong Tian, Haixue Zheng

“…The performances of the DAgS-ELISA were highly consistent with the commercial kit in testing 150 clinical serum samples, which were very similar (kappa value = 0.759). Moreover, the analysis of antibody dynamics revealed that the results exhibited higher sensitivity in early detection of total antibodies compared with the commercial kit. …”
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Curvature-Based Change Detection in Road Segmentation: Ascending Hierarchical Clustering vs. K-Means by David Jaurès Fotsa-Mbogne, Addie Bernice Nguensie-Wakponou, Jean Michel Nlong, Marcellin Atemkeng, Maurice Tchuente

“…Our goal is to segment roads into homogeneous sub-sections that can subsequently be labeled based on the level or type of irregularity. Using an analysis of variance (ANOVA) statistical test, we demonstrate that curvature features are effective for classification, with a Fisher value of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>14.28</mn></mrow></semantics></math></inline-formula> and a <i>p</i>-value of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>9.77</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>7</mn></mrow></msup></mrow></semantics></math></inline-formula>. …”
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Relationship between clinical features and distant metastases in rectal cancer predicted based on a nomogram: a retrospective cohort study by Qiong Jia, Guoli Li, Min Zhang, Mingyue Guo

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Evaluating the impact of anti-CGRP monoclonal antibodies on retinal features in migraine patients: a retrospective optical coherence tomography study by Massimo Cesareo, Alessio Martucci, Roberta Bovenzi, Marco Lombardo, Francesca Pistoia, Vittoria Carla D’Agostino, Alessandro Stefani, Carlo Nucci, Nicola Biagio Mercuri, Maria Albanese

“…Several studies have investigated the retinal vasculature features in individuals with migraine, but there have been conflicting results. …”
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State-of-Health Estimation of Lithium-Ion Batteries Based on Electrochemical Impedance Spectroscopy Features and Fusion Interpretable Deep Learning Framework by Bohan Shao, Jun Zhong, Jie Tian, Yan Li, Xiyu Chen, Weilin Dou, Qiangqiang Liao, Chunyan Lai, Taolin Lu, Jingying Xie

“…The multi-head attention mechanism is the core of this framework, enabling the model to perform weighted analysis of input features. This enables the model to provide a more transparent decision-making process, assisting in the discovery and interpretation of key features within battery SOH estimation. …”
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pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis. by Theodoros Giannakopoulos

“…Here we present the theoretical background behind the wide range of the implemented methodologies, along with evaluation metrics for some of the methods. pyAudioAnalysis has been already used in several audio analysis research applications: smart-home functionalities through audio event detection, speech emotion recognition, depression classification based on audio-visual features, music segmentation, multimodal content-based movie recommendation and health applications (e.g. monitoring eating habits). …”
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Neural signatures of depression: classifying drug-naïve MDD patients with time- and frequency-domain EEG features during emotional processing by Bernis Sütçübaşı, Tuğçe Ballı, Barış Metin, Emine Elif Tülay

“…Combined analysis of the band power features exhibited high accuracy for both positive and negative stimuli (92.86% each). …”
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Epidemiological and clinical features of acute respiratory infections occurring in St. Petersburg during the 2017–2018 and 2018–2019 epidemic seasons by D. A. Guzhov, E. A. Elpaeva, M. A. Egorova, V. A. Eder, I. L. Baranovskaya, S. A. Klotchenko, I. I. Tokin, A. V. Vasin

“…Pathogen types were determined by polymerase chain reaction (PCR). Data analysis was carried out using mathematical statistics methods using the Statistica 10 software package (StatSoft Inc.).Results: in this study, we examined the epidemiological and clinical features of acute respiratory infections in St. …”
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Smartphone-Based SPAD Value Estimation for Jujube Leaves Using Machine Learning: A Study on RGB Feature Extraction and Hybrid Modeling by Qi Wang, Ziyan Shi, Kaiyao Hou, Ning Yan, Cuiyun Wu, Xu Li

“…The RGB images were preprocessed and their color features were extracted using Python and OpenCV. Through correlation analysis, 21 color features highly correlated with chlorophyll content were selected and downscaled with principal component analysis. …”
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Clinical features of anti-SAE1 antibody-positive myositis and interstitial lung disease: a multicenter, retrospective study in Taiwan by Chao-Yang Hsiao, Chao-Yang Hsiao, Shu-Chi Tseng, Chung-Yuan Hsu, Li-Chung Chiu, Li-Jen Su, Tien-Ming Chan

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Epidemiological and clinical features of acute respiratory infections occurring in St. Petersburg during the 2017–2018 and 2018–2019 epidemic seasons by D. A. Guzhov, E. A. Elpaeva, M. A. Egorova, V. A. Eder, I. L. Baranovskya, S. A. Klotchenko, I. I. Tokin, A. V. Vasin

“…Pathogen types were determined by polymerase chain reaction (PCR). Data analysis was carried out using mathematical statistics methods using the Statistica 10 software package (StatSoft Inc.).Results: in this study, we examined the epidemiological and clinical features of acute respiratory infections in St. …”
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Enhanced skin cancer diagnosis: a deep feature extraction-based framework for the multi-classification of skin cancer utilizing dermoscopy images by Hadeel Alharbi, Gabriel Avelino Sampedro, Roben A. Juanatas, Se-jung Lim

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Practical Malware Analysis by D. A. Elizarov, A. V. Katkov

“…The main task is to analyze malware to assess threats and timely detection and take action.Method. For analysis, you should use an isolated environment with a customized environment and software.Result. …”
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Evaluating the Performance of a Fake News Model on A Domain-Specific and Heterogeneous Dataset to Improve Detection by Georgina Obuandike, Emmy Danny Ajik, Faith Oluwatosin Echobu

“…These findings suggest that dynamic and robust fake news detection systems should integrate both heterogeneous datasets and domain-specific features to enhance effectiveness. …”
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DTNLS: 3D Point Cloud Segmentation Based on 2D Image and 3D Point Cloud Double Texture Feature by Zhiguang Liu, Xiaoxiao Yan, Jiahui Zhao, Yong Shi, Fei Yu, Jian Zhao

“…The DTNLS method first uses the color texture feature of the image to segment the pixels and then obtains the clustering center and segmentation boundary outline. 3D LiDAR point cloud texture segmentation takes the clustering center obtained above as the diffusion source, diffuses outwards along the ring LiDAR line, finds the LiDAR point cloud texture boundary features near the image segmentation boundary contour, and finally realizes 3D point cloud segmentation. …”
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Feature Extraction and Attribute Recognition of Aerosol Particles from In Situ Light-Scattering Measurements Based on EMD-ICA Combined LSTM Model by Heng Zhao, Yanyan Zhang, Dengxin Hua, Jiamin Fang, Jie Zhang, Zewen Yang

“…Therefore, we propose a feature extraction and attribute recognition method from in situ light-scattering measurements based on Bayesian Optimization, wavelet scattering transform, and long short-term memory neural network (BO-WST-LSTM), with empirical mode decomposition (EMD) and independent component analysis (ICA) algorithm for signal preprocessing. …”
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