ASAD: A Meta Learning-Based Auto-Selective Approach and Tool for Anomaly Detection by Nadia Rashid, Rashid Mehmood, Fahad Alqurashi, Saad Alqahtany, Juan M. Corchado

“…It is trained using 139 datasets built upon 60 base datasets from 11 diverse domains (finance, healthcare, network security) and 80 ML and DL models composed of 22 base anomaly detection algorithms. It uses meta-features and correlation functions to evaluate 300 features. …”
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Nanoparticle-Enhanced Acoustic Wave Biosensor Detection of <i>Pseudomonas aeruginosa</i> in Food by Sandro Spagnolo, Katharina Davoudian, Brian De La Franier, Robert Kocsis, Tibor Hianik, Michael Thompson

“…To improve the sensitivity of the sensor, gold nanoparticles (AuNPs) were functionalized with the same aptamer for <i>P. aeruginosa</i> and flowed through the sensor following bacteria, reducing the extrapolated LOD to 68 CFU mL⁻¹ in PBS and 46 CFU mL⁻¹ in milk. …”
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Enhanced neurological anomaly detection in MRI images using deep convolutional neural networks by Ahmed Mateen Buttar, Zubair Shaheen, Abdu H. Gumaei, Mogeeb A. A. Mosleh, Mogeeb A. A. Mosleh, Indrajeet Gupta, Samah M. Alzanin, Muhammad Azeem Akbar

“…Our approach incorporates key preprocessing techniques, such as reducing noise and normalizing image intensity in MRI scans, alongside an optimized model architecture. …”
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Yttrium nitrate activates the oxidative stress-mediated NF-κB pathway to induce testicular inflammatory response and reduce sperm quality in mice by Si-Fan Zhang, Na Li, Dong-Li Liu, Yong-Hong Li, Yi Yang, Yao Ma, Yu-Qing Wang, Yue Ma, Zhao-jin Luan

“…The results revealed that YN exposure reduced sperm motility, increased sperm apoptosis, disrupted testicular tissue structure and function in mice. …”
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Human Neural Stem Cells Reduce Hypoxia-Ischemic Neurological Impairment Through the Regulation of Inflammatory M1/M2 Microglias in Rats by Ding YB, Zhao Y, Chen BY, Wang Q, Wang ZY, Luan Z, Yi B

“…Furthermore, Hematoxylin-eosin (HE) staining and neurological function was assessed at 12 weeks post-implantation.Results: After implantation, hNSCs survived for a duration of 12 weeks. …”
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GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…It also focuses on hard samples to reduce the impact of easily misclassified samples, thereby enhancing the model&#x2019;s performance in complex fire detection. …”
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YOLOLS: A Lightweight and High-Precision Power Insulator Defect Detection Network for Real-Time Edge Deployment by Qinglong Wang, Zhengyu Hu, Entuo Li, Guyu Wu, Wengang Yang, Yunjian Hu, Wen Peng, Jie Sun

“…To further optimize performance, a lightweight shared-convolution detection head significantly reduces parameter count and computational cost without compromising detection accuracy. …”
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Full-waveform Small-footprint LiDAR Multi-target Echo Waveform Lightweight Detection by Spatio-temporal Coupling Models by Zhen XIAO, Yanfeng GU, Yanze JIANG, Xian LI

“…The proposed method eliminates redundant computations caused by indiscriminate processing of single-target echoes, significantly reducing waveform decomposition iterations. The technical contributions include constructing a spatiotemporal coupling echo signal model that captures the spatiotemporal characteristics of echo transmission, implementing model-driven lightweight waveform parameter estimation through double Gaussian function superposition fitting, and introducing an adaptive correlation discrimination method based on a signal-to-noise ratio approach. …”
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YOLO-SRMX: A Lightweight Model for Real-Time Object Detection on Unmanned Aerial Vehicles by Shimin Weng, Han Wang, Jiashu Wang, Changming Xu, Ende Zhang

“…Finally, the Wise-IoU loss function is adopted to replace the traditional bounding box loss. …”
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Macrophage Membrane Coated Manganese Dioxide Nanoparticles Loaded with Rapamycin Alleviate Intestinal Ischemia-Reperfusion Injury by Reducing Oxidative Stress and Enhancing Autopha... by Sheng R, Wang W, Zeng W, Li B, Yu H, Li X, Liang Y, Wang Y, Liao Y, Liu D

“…The biocompatibility and safety of Ma@(MnO₂+RAPA) were confirmed through histological analysis and biochemical detection in mice.Conclusion: Our results demonstrated that Ma@(MnO₂+RAPA) alleviated intestinal I/R injury by reducing oxidative stress, promoting autophagy, and inhibiting inflammation. …”
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The results of the cross-sectional study of platelet aggregative function in children with hemorrhagic syndrome by Olga B. Gordeeva, Albina V. Dobrotok, Mariia V. Volkova, Natalia L. Aleshenko, Vladimir S. Kargin, Irine Dzharkava, Nadezhda F. Zhdanovskaia

“…Hyperaggregation with ASPI test was detected in 18% of cases (n = 9).Conclusion. The analyzed results of laboratory tests of platelet aggregation function, hypoaggregation with inducers was observed in more than half of the children, hyperaggregation was observed was present in almost half of the patients.…”
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Increasing Lignification in Translucent Disorder Aril of Mangosteen Related to the ROS Defensive Function by Chalermchai Wongs-Aree, Patchayapon Siripirom, Apinya Satitpongchai, Kitti Bodhipadma, Sompoch Noichinda

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Explainable Siamese Neural Networks for Detection of High Fall Risk Older Adults in the Community Based on Gait Analysis by Christos Kokkotis, Kyriakos Apostolidis, Dimitrios Menychtas, Ioannis Kansizoglou, Evangeli Karampina, Maria Karageorgopoulou, Athanasios Gkrekidis, Serafeim Moustakidis, Evangelos Karakasis, Erasmia Giannakou, Maria Michalopoulou, Georgios Ch Sirakoulis, Nikolaos Aggelousis

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Functional Verification of Extended Kalman Filter on FPGA for Railway Wheelset Parameters Estimation by Khakoo Mal, Tayab Din Memon, Imtiaz Hussain Kalwar, Allah Rakhio Junejo, Majid Hussain Memon, Tarique Rafique Memon, Sufyan Ali Memon, Bhawani Shankar Chowdhry

“…The industry 4.0 is greatly benefit from the promising functional verification and area-performance analysis on small commercial FPGA devices to detect and identify the faults in the early stages as part of predictive maintenance that saves time, money, and reduce accidents caused by railway derailments. …”
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Detection method of small size defects on pipeline weld surface based on improved YOLOv7. by Xiangqian Xu, Wenting Hou, Xing Li

“…The experimental results show that the defect detection mAP@0.5 based on the improved YOLOv7 algorithm can reach 72.2%, which is 11% higher than that of YOLOv7, and the model calculation amount and parameter amount are reduced by 75.6% and 60.3%, respectively. …”
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Apprehending the Effect of Internet of Things (IoT) Enables Big Data Processing through Multinetwork in Supporting High-Quality Food Products to Reduce Breast Cancer by Surendra Kumar Shukla, B. Muthu Kumar, Divyanshu Sinha, Varsha Nemade, Shynar Mussiraliyeva, R. Sugumar, Rituraj Jain

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Research on Improved Bridge Surface Disease Detection Algorithm Based on YOLOv7-Tiny-DBB by Haichao An, Ying Fan, Zhuobin Jiao, Meiqin Liu

“…In response to the diverse target types, variable morphological characteristics, and the prevalence of small sample targets that are prone to missed detections in the bridge surface disease identification, this paper proposes an improved algorithm for detecting bridge surface diseases based on YOLOv7-Tiny-DBB. …”
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Improved model MASW YOLO for small target detection in UAV images based on YOLOv8 by Xianghe Meng, Fei Yuan, Dexiang Zhang

“…The use of flexible non-maximum suppression Soft-NMS is chosen to replace the non-maximum suppression NMS to improve the model’s detection of occlusion and dense targets. The loss function of the model is optimised through the implementation of Wise-IoU, which serves as a replacement for the loss function of the baseline model, thereby enhancing the accuracy of bounding box regression, especially perform better when the target deformation or scale change is large. …”
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Malware Detection and Classification in Android Application Using Simhash-Based Feature Extraction and Machine Learning by Wafaa Al-Kahla, Eyad Taqieddin, Ahmed S. Shatnawi, Rami Al-Ouran

“…Our results showed that using Random Forest as a classifier, SHA-512 the hash function and 2-WORD tokenization led to high accuracy with reduced time and memory requirements for training, validating, and testing. …”
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Star-YOLO: A Lightweight Real-Time Wheat Grain Detection Model for Embedded Deployment by Zhihang Qu, Xiao Liang, Sicheng Liang, Xiumei Guo

“…To this end, this paper introduces Star-YOLO, a lightweight wheat grain detection model built upon YOLOv11n. The model employs StarNet to refine the C3k2 structure, reducing computational complexity without compromising detection accuracy, and integrates the MBConv module into the detection head to boost feature extraction while further minimizing computational load. …”
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