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  3. 17443

    Participatory approaches and Social Network Analysis to analyse the emergence of collective action for rural development: a case study in the Spanish Pyrenees by M. Teston, E. Sturaro, E. Muñoz-Ulecia, A. Tenza-Peral, S. Raniolo, E. Pisani, C. Pachoud, M. Ramanzin, D. Martín-Collado

    Published 2024-12-01
    “…The trust network was analysed using the Louvain’s algorithm to identify potential internal communities and the exponential random graph model (ERGM) to infer the shaping effects of actors’ attributes on the network’s structure. …”
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  4. 17444
  5. 17445

    Primary pediatric stroke center in the multidisciplinary pediatric hospital. New reality in pediatrics by E. E. Petryaykina, I. I. O. Shcherderkina

    Published 2020-03-01
    “…There were improved: the diagnostics of cerebrovascular pathology and its algorithm, modern reperfusion methods of treatment (thrombolysis, thromboextraction) were introduced into practice, outpatient observation. …”
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    Article
  6. 17446

    A KeyBERT-Enhanced Pipeline for Electronic Information Curriculum Knowledge Graphs: Design, Evaluation, and Ontology Alignment by Guanghe Zhuang, Xiang Lu

    Published 2025-07-01
    “…This paper proposes a KeyBERT-based method for constructing a knowledge graph of the electronic information curriculum system, aiming to enhance the structured representation and relational analysis of educational content. Electronic Information Engineering curricula encompass diverse and rapidly evolving topics; however, existing knowledge graphs often overlook multi-word concepts and more nuanced semantic relationships. …”
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    CAFiKS: Communication-Aware Federated IDS With Knowledge Sharing for Secure IoT Connectivity by Ogobuchi Daniel Okey, Demostenes Zegarra Rodriguez, Frederico Gadelha Guimaraes, Joao Henrique Kleinschmidt

    Published 2025-01-01
    “…In many cases, deep neural networks (DNNs) serve as the backbone algorithm in federated processes. However, their computational demands make them impractical for deployment in Internet of Things (IoT) environments, which are characterised by resource-constrained devices; hence, the need for lightweight and adaptable solutions. …”
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  12. 17452

    Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis. by Roland F Schwarz, Charlotte K Y Ng, Susanna L Cooke, Scott Newman, Jillian Temple, Anna M Piskorz, Davina Gale, Karen Sayal, Muhammed Murtaza, Peter J Baldwin, Nitzan Rosenfeld, Helena M Earl, Evis Sala, Mercedes Jimenez-Linan, Christine A Parkinson, Florian Markowetz, James D Brenton

    Published 2015-02-01
    “…<h4>Conclusions</h4>This study demonstrates that quantitative measures of intra-tumour heterogeneity may have predictive value for survival after chemotherapy treatment in HGSOC. …”
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  13. 17453

    Prognostic role of hemostasis-regulating genetic factors and their interaction with conventional risk factors at the early stages of coronary heart disease development by E. Yu. Andreenko, L. M. Samokhodskaya, A. V. Balatskyi, P. I. Makarevich, S. A. Boytsov

    Published 1970-01-01
    “…In participants with HCH, the PLA2/PLA2 genotype of GPIIIa was linked to increased MI risk for CHD patients (p=0,01; OR=6,0). Conclusion. The algorithm for predicting the genetic CHD risk may incorporate the assessment of the genetic polymorphism of GPIa (C807T), GPIIIa (PLA1/PLA2), factor XIII (V34L), and factor VII (R353Q). …”
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  14. 17454

    The role of artificial intelligence in managing hospitalized patients with mental illness: a scoping review by Md Samiun, Moustaq Karim Khan Rony, Sumaiya Yeasmin, Mia Md Tofayel Gonee Manik, Anupom Debnath, Mustakim Bin Aziz, Afia Fairooz Tasnim, Sadia Islam Nilima

    Published 2025-07-01
    “…Despite these advancements, challenges were noted, such as algorithmic biases due to non-diverse training data, privacy and security risks for sensitive patient information, and clinician resistance stemming from concerns about autonomy and ethical implications of AI-supported clinical decisions. …”
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  15. 17455

    Analysis of the Strength Development, CO<sub>2</sub> Emissions, and Optimized Low-Carbon Design of Fly-Ash-Enhanced Composite Concrete by Bo Yang, Yu Dong, Xiao-Yong Wang

    Published 2025-02-01
    “…Similarly, reducing the W/(C + FA) ratio from 0.50 to 0.30 also lowers the CO<sub>2</sub> emissions per unit of strength. Finally, a genetic algorithm was employed for the optimization of the low-carbon design. …”
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  16. 17456

    COMPREHENSIVE THERAPY OF ENDO-PERIODONTAL LESIONS: MOVING STEP BY STEP TOWARDS COMPLETE FUNCTIONAL REHABILITATION OF PATIENTS WITH COMBINED PATHOLOGY by Yu.O. Kinash, L.V. Kinash

    Published 2024-10-01
    “…The coefficient of concordance demonstrates the importance of the therapy we conducted with the possibility of predicting its outcomes, mathematically confirming and equating the data with index analysis. …”
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    Integrating GIS and remote sensing for soil attributes mapping in degraded pastures of the Brazilian Cerrado by Rômullo Oliveira Louzada, Ivan Bergier, Édson Luis Bolfe, Jayme Garcia Arnal Barbedo

    Published 2025-06-01
    “…This study integrates active and passive remote sensing data with Machine Learning (ML) methods to predict the physicochemical properties of degraded sandy soils in the Brazilian Cerrado. …”
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    The impact of SRRM2-AS1 in ovarian cancer: a comprehensive analysis based on pan-cancer and in vitro validation by Jiaojiao Lu, Xia Zheng, Xu Li

    Published 2025-06-01
    “…Immune cell infiltrations were assessed with the single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm, while subcellular localization was predicted using the lncATLAS database. …”
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    Machine learning-driven identification of critical gene programs and key transcription factors in migraine by Lei Zhang, Yujie Li, Yunhao Xu, Wei Wang, Guangyu Guo

    Published 2025-01-01
    “…Random forest analysis predicted ARID3A as the top transcription factor regulating gene program 1, suggesting its potential role in modulating calcium-related genes involved in migraine. …”
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  20. 17460

    Phenotypic Trait Acquisition Method for Tomato Plants Based on RGB-D SLAM by Penggang Wang, Yuejun He, Jiguang Zhang, Jiandong Liu, Ran Chen, Xiang Zhuang

    Published 2025-07-01
    “…The relative errors when predicting the plant height, canopy width, and volume are 3.86%, 14.34%, and 27.14%, respectively, while the errors concerning the fruit count and fruit volume are 14.36% and 14.25%. …”
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