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  • Machine learning climbs the Jacob’s Ladder of optoelectronic properties

    Machine learning climbs the Jacob’s Ladder of optoelectronic properties

    We have calculated RPA spectra for all materials in the IPA database24 that have at most 8 atoms in the unit cell, i.e., a total of about 6000 spectra. The structures were originally taken from the Alexandria database of theoretically stable…

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  • Correction: Aberrant Notch-signaling promotes tumor angiogenesis in esophageal squamous-cell carcinoma

    Correction: Aberrant Notch-signaling promotes tumor angiogenesis in esophageal squamous-cell carcinoma

    Correction: Aberrant Notch-signaling promotes tumor angiogenesis in esophageal squamous-cell carcinoma

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  • Design of library intelligent lighting system based on deep learning

    Design of library intelligent lighting system based on deep learning

    Overall scheme design

    Taking into account the degree of mobility of people in the library and the different lighting needs, the university library is divided into three major areas: image detection area, infrared sensing area, and other areas. The…

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  • Major pathophysiological changes in pulmonary disease provided a molecular insight based on deep learning approach

    Major pathophysiological changes in pulmonary disease provided a molecular insight based on deep learning approach

  • Gadkowski, L. B. & Stout, J. E. Cavitary pulmonary disease. Clin. Microbiol. Rev. 21(2), 305–333 (2008).

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  • Becklake, M. R. Asbestos-related diseases…

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  • Food insecurity impacts neuroblastoma pathogenesis in murine xenograft tumor models

    Food insecurity impacts neuroblastoma pathogenesis in murine xenograft tumor models

    Cell lines

    IMR-32 cells were obtained from ATCC in March 2023. Cells were maintained in minimal essential medium, supplemented with 10% FBS, 2 mmol/L glutamine, 100 U/ml penicillin, and 100 µg/ml streptomycin, 1 mmol/L pyruvate and 0.075%…

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  • Combining knowledge distillation and neural networks to predict protein secondary structure

    Combining knowledge distillation and neural networks to predict protein secondary structure

    Evaluation metrics and parameter settings

    In this work, accuracy (Q8) and accuracy (Q3)22 are used to measure the goodness of fit of the model. The 8-state secondary structures are H, G, I, E, B, S, T, and C, and the 3-state secondary structures…

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