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Showing 901 - 920 results of 1,810 for search '((( resources OR resources) detection functions ) OR ( source detection functions ))', query time: 0.18s Refine Results
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    Glucose Sensing in Saliva by Jacopo Giaretta, Riccardo Zulli, Theja Prabhakar, Ronil J. Rath, Sina Naficy, Sara Spilimbergo, Paul S. Weiss, Syamak Farajikhah, Fariba Dehghani

    Published 2024-11-01
    “…Abstract Glucose plays critical roles in many human body functions, above all as a source of energy. Abnormal levels of glucose are correlated to different diseases, importantly including diabetes. …”
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  4. 904

    The transcription factor Ste12 mediates the regulatory role of the Tmk1 MAP kinase in mycoparasitism and vegetative hyphal fusion in the filamentous fungus Trichoderma atroviride. by Sabine Gruber, Susanne Zeilinger

    Published 2014-01-01
    “…An essential step in this mycoparasitic fungus-fungus interaction is the detection of the fungal host followed by activation of molecular weapons in the mycoparasite by host-derived signals. …”
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  5. 905

    Genome-Wide Scan for Copy Number Variations in Chinese Merino Sheep Based on Ovine High-Density 600K SNP Arrays by Yuezhen Tian, Jing An, Xinning Zhang, Jiang Di, Junmin He, Ayinuer Yasen, Yanpin Ma, Gaohaer Sailikehan, Xixia Huang, Kechuan Tian

    Published 2024-10-01
    “…To generate a comprehensive CNVR map of the ovine genome, we conducted genome-wide CNV detection using genotyping data from 285 fine wool sheep. …”
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    A novel approach to field data augmentation with remote sensing and machine learning in rangelands by Hailey E. Schmidt, Javier Osorio Leyton, Efrain Noa Yarasca, Sorin C. Popescu, Justinn J. Jones, Justin P. Wied, Xinyuan Wu

    Published 2025-12-01
    “…However, these ecosystems are increasingly threatened by woody plant encroachment (WPE), which impacts forage availability, habitat quality, and other ecosystem functions. Despite advances in remote sensing and machine learning (ML) for monitoring and managing WPE, a significant gap persists in providing effective, scalable, and high-quality training data to support early detection efforts. …”
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  8. 908

    Estimating fish stock biomass using a Bayesian state-space model: accounting for catchability change due to technological progress by Makoto Nishimoto, Yoshinori Aoki, Naoto Matsubara, Paul Hamer, Yuichi Tsuda

    Published 2024-12-01
    “…This model allows for the flexible integration of the timing and functional form of the uptake of technological innovations that are assumed to influence catchability. …”
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    Soil pollution and remediation: emerging challenges and innovations by Hao Chen, Bin Gao, Yuncong Li

    Published 2025-04-01
    “…These pollutants pose severe risks to environmental health and agricultural productivity by altering soil functionality and contaminant mobility. This perspective summarizes innovative monitoring and remediation technologies, including advanced sensors and bioremediation strategies, that enable real-time detection and effective management of soil pollutants. …”
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  13. 913

    Research on lightweight weed recognition algorithm based on improved YOLOv8 by Zhang Chao, Liu Bin, Li Kun

    Published 2025-01-01
    “…Different scale features are used to improve the performance of target detection. Finally, the MPDIoU loss function is replaced to enhance the convergence and stability of the model. …”
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  14. 914

    Survey on Backdoor Attacks on Deep Learning: Current Trends, Categorization, Applications, Research Challenges, and Future Prospects by Muhammad Abdullah Hanif, Nandish Chattopadhyay, Bassem Ouni, Muhammad Shafique

    Published 2025-01-01
    “…Such attacks are usually referred to as Trojan or backdoor attacks and are very stealthy and hard to detect. In this paper, we highlight the complete attack surface that can be exploited to inject hidden malicious functionality (backdoors) in machine learning models. …”
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    Learning Transferable Convolutional Proxy by SMI-Based Matching Technique by Wei Jin, Nan Jia

    Published 2020-01-01
    “…The classification responses are also smoothened by manifolds of both the source domain and proxy space. By minimizing an objective function of SMI, classification error, and manifold regularization, we learn the convolutional networks of both source and target domains. …”
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    Diagnostic potential of the B9D2 gene in colorectal cancer based on whole blood gene expression data and machine learning by Zhaorui Wang, Yongcheng Fu, Haozhe Zhang, Na Liu, Ningjing Lei

    Published 2025-08-01
    “…The B9D2 gene, which is essential for ciliary function, has been rarely explored in CRC. This study is the first to investigate the diagnostic potential of B9D2 in CRC, using bioinformatics and machine learning to uncover its novel role in early detection, with implications for clinical translation. …”
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    LIFE CYCLE ASSESSMENT IN HEALTHCARE SYSTEM OPTIMIZATION. INTRODUCTION by V. Sarancha, K. Vitale, S. Oreskovic, V. Sulyma

    Published 2015-03-01
    “…Various factors and parameters that may influence effectiveness of different sectors in healthcare system are detected. Performance optimization of detected parameters could lead to better system functioning, higher patient safety, economic sustainability and reduce resources consumption.…”
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