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  • The case against efficiency: friction in social media

    The case against efficiency: friction in social media

    Above we’ve surveyed a range of frictions studied by platforms and scientists alike, working by a wide variety of mechanisms and exhibiting effects spanning from individuals to cross-platform. Yet each of these interventions arose, in a sense,…

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  • Uncovering the molecular logic of cortical wiring between neuronal subtypes across development through ligand–receptor inference

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  • Origin of the high coercivity in FeNi inspired magnets

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  • In-vivo optical properties spectra across five body locations on ten subjects using time-domain diffuse optics

  • Sherafati, A. et al. A high-density diffuse optical tomography dataset of naturalistic viewing. Scientific Data 12, 1762 (2025).

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  • von Lühmann, A., Li, X., Gilmore, N., Boas, D. A. & Yücel, M….

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  • Advancing sports performance evaluation through T spherical fuzzy FUCA MCDM approach to real time basketball analytics

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  • Osimertinib inhibits the MYLK4-mediated phosphorylation of CDKAL1 to suppress stemness and chemoresistance in rhabdomyosarcoma

    Osimertinib inhibits the MYLK4-mediated phosphorylation of CDKAL1 to suppress stemness and chemoresistance in rhabdomyosarcoma

    Rhabdomyosarcoma (RMS) is a common pediatric soft-tissue sarcoma that often recurs or metastasizes despite aggressive multimodal therapy. Cancer stem cells (CSCs) are key contributors to these…

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  • Machine learning for individual epigenetic fingerprints as predictors of well-being in young adults

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  • Cannito, L. et al. The role of stress and cognitive absorption in predicting social network addiction. Brain Sci., 12(5). (2022).

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  • A comprehensive investigation of expired dextromethorphan HBr drug as a carbon steel corrosion inhibitor using gravimetric, electrochemical, and theoretical computational approaches

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  • Osarolube, E., Owate, I. O. & Oforka, N. C. Corrosion behaviour of mild…

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  • A data analytics-driven approach to backorder prediction using federated machine learning in industrial supply chains

  • Zhang, L. et al. How to configure the supply chain to stimulate firm innovation performance. Int. J. Prod. Econ. 277, 109384 (2024).

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  • Ntakolia, C. et al. An explainable machine learning model…

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