A Method for Extracting Features of the Intrinsic Mode Function’s Energy Arrangement Entropy in the Shaft Frequency Electric Field of Vessels by Xiaoguang Ma, Zhaolong Sun, Runxiang Jiang, Xinquan Yue, Qi Liu

“…To address the challenge of detecting low-frequency electric field signals from vessels in complex marine environments, a vessel shaft frequency electric field feature extraction method based on intrinsic mode function energy arrangement entropy values is proposed, building upon a scaled model. …”
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Development and validation of microwave-assisted extraction for phenolic compound profiling in diverse oyster mushrooms (Pleurotus spp.) sourced from various geographical regions by M Umar Harun, Miguel Palma, Widiastuti Setyaningsih

“…Seven phenolic compounds—p-coumaric acid, t-cinnamic acid, p-hydroxybenzaldehyde, p-hydroxybenzoic acid, quercetin-3-glucoside, gallic acid, and vanillic acid—were effectively extracted and quantified using ultra-performance liquid chromatography with photodiode array detection. Application of this method across oyster mushroom samples from different geographical sources revealed significant variation in phenolic compound concentrations, with Pleurotus pulmonarius exhibiting the highest level of gallic acid at 433.90 ± 7.77 μg g−1 (DM) and Pleurotus ostreatus var. …”
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Morphological and functional characteristics of Trichinella sp. larvae in bears and badgers in the Kirov Region by O. B. Zhdanova, I. I. Okulova, A. V. Uspensky, L. A. Napisanova

“…For postmortem diagnosis of trichinellosis in the obtained bears and badgers, we can use trichinelloscopy and peptolysis methods which are aimed at detecting infection sources and preventing zoonosis in humans.…”
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National occupational safety and health systems: Exploring the underlying networks for future sustainable development by Gaia Vitrano, Guido J.L. Micheli

“…These findings provide valuable insights into how these functions are carried out differently across countries, detecting potential shareable best practices and improvement directions for the future sustainability of national OSH systems.…”
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Cascaded Directional Coupler-Based Triplexer Working on Spectroscopically Relevant Wavelengths for Multiple Gas Detection by Ajmal Thottoli, Gabriele Biagi, Artem S. Vorobev, Antonella D’Orazio, Giovanni Magno, Liam O’Faolain

“…The triplexer’s functions focus on enhancing the coupling efficiency and selectivity, while facilitating the on-chip integration of diode lasers. …”
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Harnessing Deep Learning With AlexNet for Tomato Leaf Disease Detection in the Indian Himalayan Terrain by Ruchika Sharma, Sameena Naaz, Pankaj Vaidya

“…Agriculture is essential for living in the Indian Himalayan region (IHR), as it functions as the main occupation and source of income. …”
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A diagnosis method based on graph neural networks embedded with multirelationships of intrinsic mode functions for multiple mechanical faults by Bin Wang, Manyi Wang, Yadong Xu, Liangkuan Wang, Shiyu Chen, Xuanshi Chen

“…Additionally, a graph-level based fault diagnosis network model is designed to enhance feature learning capabilities for graph samples and enable flexible application across diverse signal sources and devices. Experimental validation with datasets including independent vibration signals for gear fault detection, mixed vibration signals for concurrent gear and bearing faults, and pressure signals for hydraulic cylinder leakage characterization demonstrates the model's adaptability and superior diagnostic accuracy across various types of signals and mechanical systems.…”
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CSW-YOLO: A traffic sign small target detection algorithm based on YOLOv8. by Qian Shen, Yi Li, YuXiang Zhang, Lei Zhang, ShiHao Liu, Jinhua Wu

“…The model achieves precision on par with existing mainstream algorithms, while being simpler, significantly reducing computational requirements, and being more suitable for small target detection tasks. The source code and test results of the models used in this study are available at https://github.com/lyzzzzyy/CSW-YOLO.git.…”
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VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes by Yunxiang Liu, Yuqing Shi

“…Accurate detection of vulnerable road users (VRUs) is critical for enhancing traffic safety and advancing autonomous driving systems. …”
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Asynchronous bearing only tracking management approach in distributed multi-function integrated sensors by ZHANG Wei, YANG Qiu, LI Hao

“…The distributed multi-function system requires only one integrated sensor to switch to electronic support measure (ESM) mode within each tracking cycle to update the angle measurement information of target radiation source, while the other integrated sensors still work in the original planned mode and task. …”
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Brain tumor detection through image fusion using whale optimization and edge preserving filter by Bhattiprolu Nagasirisha, Venkatesh Munagala, Ramakrishna Reddy Eamani, Mocherla Venkata Srikanth, Asileti Suneel Kumar, Varre Venkata Kanaka Durga Prasad

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Acoustic Emission as a Method for Analyzing Changes and Detecting Damage in Composite Materials During Loading by Katarzyna PANASIUK, Krzysztof DUDZIK, Grzegorz HAJDUKIEWICZ

“…The signal obtained from the sensor was then further processed and used to draw up diagrams of the AE hits, amplitude, root mean square of the AE source signal (RMS) and duration in the function of time. …”
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SILVERRUSH. XIV. Lyα Luminosity Functions and Angular Correlation Functions from 20,000 Lyα Emitters at z ∼ 2.2–7.3 from up to 24 deg2 HSC-SSP and CHORUS Surveys: Linking the Postr... by Hiroya Umeda, Masami Ouchi, Satoshi Kikuta, Yuichi Harikane, Yoshiaki Ono, Takatoshi Shibuya, Akio K. Inoue, Kazuhiro Shimasaku, Yongming Liang, Akinori Matsumoto, Shun Saito, Haruka Kusakabe, Yuta Kageura, Minami Nakane

“…We present luminosity functions (LFs) and angular correlation functions (ACFs) derived from 18,960 Ly α emitters (LAEs) at z  = 2.2−7.3 over a wide survey area of ≲24 deg ^2 that are identified in the narrowband data of the HSC-SSP and CHORUS surveys. …”
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LMGD: Log-Metric Combined Microservice Anomaly Detection Through Graph-Based Deep Learning by Xu Liu, Yuewen Liu, Miaomiao Wei, Peng Xu

“…Therefore, there is an urgent need for fast and accurate anomaly detection capabilities. However, the existing microservice anomaly detection methods do not pay attention to the multi-source data of the microservice system and thus have low accuracy. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
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Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Machine Learning (ML)-based Intrusion Detection Systems (IDS) are integral to securing modern IoT networks but often suffer from a lack of transparency, functioning as “black boxes” with opaque decision-making processes. …”
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Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

“…The Industrial Internet of Things (IIoT) faces significant cybersecurity threats due to its ever-changing network structures, diverse data sources, and inherent uncertainties, making robust intrusion detection crucial. …”
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Detection of Greenhouse and Typical Rural Buildings with Efficient Weighted YOLOv8 in Hebei Province, China by Bingkun Wang, Zhiyuan Liu, Jiangbo Xi, Siyan Gao, Ming Cong, Haixing Shang

“…However, in rural and mountainous areas, the resolution and accessibility of remote sensing satellite images from a single source are poor, making it difficult to detect greenhouses and rural buildings effectively and automatically. …”
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Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring by Kaitlin J. Palmer, Sam Tabbutt, Douglas Gillespie, Jesse Turner, Paul King, Dominic Tollit, Jessica Thompson, Jason Wood

“…Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. …”
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SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI by Ami Tsuchida, Martin Goubet, Philippe Boutinaud, Iana Astafeva, Victor Nozais, Pierre-Yves Hervé, Thomas Tourdias, Stéphanie Debette, Marc Joliot

“…An increasing number of automated CMB detection methods being proposed are based on supervised deep learning (DL). …”
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