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  1. 481
  2. 482
  3. 483

    Optimization of Protein Extraction from Sunflower Meal Using Taguchi Design and Regression Modeling for Human Nutrition Applications by Anca Becze, Marin Senila, Lacrimioara Senila, Lucian Dordai, Oana Cadar, Vanda Liliana Fuss-Babalau, Marius Roman, Levente Levei, Paul Uiuiu, Mihai Octavian Naghiu

    Published 2025-07-01
    “…Safety analyses confirmed the absence of detectable aflatoxins and very low PAH levels. These results support the use of sunflower protein concentrate as a sustainable, nutritionally valuable, and safe ingredient for functional food applications. …”
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    Article
  4. 484

    Venturing Into the Unknown: The Importance of Variable Selection When Modelling Alien Species Under Non‐Analogue Climatic Conditions by Tom Vorstenbosch, Franz Essl, Bernd Lenzner, Johannes Wessely, Stefan Dullinger

    Published 2024-10-01
    “…Here, we tested the assumption that this aspect of model design is a major source of uncertainty, especially when projections are made to non‐analogue climates. …”
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    Article
  5. 485

    Research on Underwater Target Detection Technology Based on SMV-YOLOv11n by Dongcheng Liao, Yijun Shen, Jinyu Ou, Yanlian Du

    Published 2025-01-01
    “…High-precision underwater object detection is a crucial component for improving the efficiency of marine resource development. …”
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    Article
  6. 486

    Multi-Person Fall Detection Using Data Assimilation Method With Kalman Filter by Jinmo Yang, Ye Jin Jin, R. Young Chul Kim

    Published 2025-01-01
    “…Fall detection is an essential technology for ensuring the safety of elderly individuals, as falling accidents are critical and can cause significant functional damage in old age. …”
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    Article
  7. 487

    Walkability Evaluation of Historical and Cultural Districts Based on Multi-Source Data: A Case Study of the Former Russian Concession in Hankou by Haoran She, Jing Sun, Yuchen Zeng, Wenyu Tu, Guang Ao, Wei Shang

    Published 2025-05-01
    “…Key issues such as low spatial quality and functional disorder were identified, and targeted optimization strategies are proposed. …”
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    Article
  8. 488

    Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification by Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam, Mohammed Arfat Raihan Chowdhury, Md. Shamim Anower, Md. Masud Rana, Md. Shafiul Alam, Mahmudul Hasan, Md. Shohanur Islam Sobuj, Md. Babul Islam, Veerpratap Meena, Francesco Benedetto

    Published 2024-01-01
    “…Electric vehicles (EVs) are commonly recognized as environmentally friendly modes of transportation. They function by converting electrical energy into mechanical energy using different types of motors, which aligns with the sustainable principles embraced by smart cities. …”
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  9. 489

    A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection. by George Nicholson, Mattias Rantalainen, Jia V Li, Anthony D Maher, Daniel Malmodin, Kourosh R Ahmadi, Johan H Faber, Amy Barrett, Josine L Min, N William Rayner, Henrik Toft, Maria Krestyaninova, Juris Viksna, Sudeshna Guha Neogi, Marc-Emmanuel Dumas, Ugis Sarkans, MolPAGE Consortium, Peter Donnelly, Thomas Illig, Jerzy Adamski, Karsten Suhre, Maxine Allen, Krina T Zondervan, Tim D Spector, Jeremy K Nicholson, John C Lindon, Dorrit Baunsgaard, Elaine Holmes, Mark I McCarthy, Chris C Holmes

    Published 2011-09-01
    “…Two of the three hit regions lie within haplotype blocks (at 2p13.1 and 10q24.2) that carry the genetic signature of strong, recent, positive selection in European populations. Genes NAT8 and PYROXD2, both with relatively uncharacterized functional roles, are good candidates for mediating the corresponding mQTL associations. …”
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  10. 490

    Metal and metal oxide nanomaterials for heavy metal remediation: novel approaches for selective, regenerative, and scalable water treatment by David B. Olawade, David B. Olawade, David B. Olawade, Ojima Z. Wada, Bamise I. Egbewole, Oluwaseun Fapohunda, Abimbola O. Ige, Sunday Oluwadamilola Usman, Olawale Ajisafe

    Published 2024-10-01
    “…The review identifies several promising nanomaterials, such as graphene oxide, carbon nanotubes, and metal-organic frameworks, which exhibit high surface areas, tunable surface chemistries, and excellent adsorption capacities. Surface functionalization with specific functional groups (e.g., carboxyl, amino, thiol) significantly enhances the selectivity for target heavy metal ions. …”
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  11. 491

    Object detection with afordable robustness for UAV aerial imagery: model and providing method by Viacheslav Moskalenko, Artem Korobov, Yuriy Moskalenko

    Published 2024-08-01
    “…The model and method for ensuring the robustness of resource-constrained neural network systems for object detection in aerial video surveillance. …”
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  12. 492

    Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends by Camelia Adela Maican, Cristina Floriana Pană, Daniela Maria Pătrașcu-Pană, Virginia Maria Rădulescu

    Published 2025-06-01
    “…Key findings are summarized in a comparative matrix, highlighting trends, gaps, and inconsistencies across publication sources. This review identifies critical research gaps—including the underuse of hybrid models, lack of benchmark datasets, and limited integration between detection and control layers—and offers concrete recommendations for future research. …”
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  13. 493
  14. 494

    3L-YOLO: A Lightweight Low-Light Object Detection Algorithm by Zhenqi Han, Zhen Yue, Lizhuang Liu

    Published 2024-12-01
    “…Existing methods often use image enhancement to improve detection, which results in a large amount of computational resource consumption. …”
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  15. 495

    Automatic detection of foreign object intrusion along railway tracks based on MACENet. by Xichun Chen, Yu Tian, Ming Li, Bin Lv, Shuo Zhang, Zixian Qu, Jianqing Wu, Shiya Cheng

    Published 2025-01-01
    “…Ensuring high accuracy and efficiency in foreign object intrusion detection along railway lines is critical for guaranteeing railway operational safety under limited resource conditions. …”
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  16. 496

    Rice disease detection method based on multi-scale dynamic feature fusion by Qian Fan, Runhao Chen, Bin Li

    Published 2025-05-01
    “…These optimizations enable efficient deployment on resource-constrained mobile devices, making the model highly suitable for real-time disease detection in practical agricultural scenarios where hardware limitations are critical. …”
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    Article
  17. 497

    Automatic detection of floating instream large wood in videos using deep learning by J. Aarnink, J. Aarnink, T. Beucler, T. Beucler, M. Vuaridel, V. Ruiz-Villanueva, V. Ruiz-Villanueva

    Published 2025-02-01
    “…Therefore, the findings of this paper could be used when designing a custom wood detection network. With the growing availability of flood-related videos featuring wood uploaded to the internet, this methodology facilitates the quantification of wood transport across a wide variety of data sources.…”
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  18. 498

    Real time wire rope detection method based on Rockchip RK3588 by Mengpeng Qian, Yong Wang, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Ming Chen, Hailong Wu, Zuchao Zhang

    Published 2025-08-01
    “…To enhance non-destructive wire rope inspection, a Mini-YOLO model was developed by integrating MobileNetV3, the Coordinate Attention (CA) mechanism, and a novel loss function, Inner-IoU, into the YOLOv8 framework. This paper’s innovation lies not in creating algorithmic components from scratch, but in their synergistic integration and targeted optimization to solve the specific challenges of real-time defect detection on resource-constrained edge devices. …”
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  19. 499

    An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

    Published 2025-04-01
    “…IntroductionIn the aviation field, drone search and rescue is a highly urgent task involving small target detection. In such a resource-constrained scenario, there are challenges of low accuracy and high computational requirements.MethodsThis paper proposes IYFVMNet, an improved lightweight detection network based on YOLOv8. …”
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  20. 500

    SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

    Published 2024-12-01
    “…Finally, the Inner-IoU optimization loss function is applied to accelerate model convergence and enhance detection accuracy.ResultsTesting results indicate that SGSNet performs exceptionally well across key metrics, achieving 98.83% precision, 99.45% recall, 99.14% F1 score, 99.50% mAP@0.5, and a loss value of 0.3534. …”
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