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    19299 research outputs found

    劉涵玥氏の研究発表印象記

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    departmental bulletin pape

    郭栩峰氏の研究発表印象記

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    Die Strafbarkeit von durch Vorteilsgewährung bedingten sexuellen Handlungen

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    大橋眞弓先生に贈る言葉

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    Improving Molecular Design with Direct Inverse Analysis of QSAR/QSPR Model

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    Recent advances in machine learning have significantly impacted molecular design, notably the molecular generation method combining the chemical variational autoencoder (VAE) with Gaussian mixture regression (GMR). In this method, a mathematical model is constructed with X as the latent variable of the molecule and Y as the target properties and activities.Through direct inverse analysis of this model, it is possible to generate molecules with the desired target properties. However, this approach outputs many strings that do not follow the simplified molecular input line entry system grammar and generates unrealistic chemical structures in which the properties and activity do not satisfy the target values. In this study, we focus on hierarchical VAE using molecular graphs to address these issues. We confirm that the combination of hierarchical VAE and GMR does not generate invalid outputs and returns molecules that simultaneously satisfy multiple target values. Moreover, we use this method to identify several molecules that are predicted to exhibit activity against drug targets.journal articl

    Correlations between the constituent molecules,crystal structures,and dielectric constants in organic crystals

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    Organic crystals are crystals composed of molecules of organic compounds. Materials made from organic crystals are used in devices, such as capacitors and ferroelectric memories. It is desirable to develop new materials with improved physical properties such as the dielectric constant (DC). However, the relationship between the constituent molecule (CM), crystal structure (CS), and DC of the organic crystals is not clearly understood. In this study, we investigated the relationship between CM, CS, and DC with existing data and machine learning. Using regression analysis, we could construct machine learning models between CM and DC, between CS and DC, and between CM and CS, and could predict DC from CM, DC from CS, and CS from CM using the constructed models.journal articl

    Preface to the Special Issue on Philosophy of Reiner Schürmann

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    Enlightenment in Dogen’s Early Thought -Are there any other behaviors besides zazen that lead to enlightenment?-

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    Why Must the Relationship between States be Federal? -Considerations on the Second Definitive Article in Kant’s Perpetual Peace:A Philosophical Sketch-

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    David Dyzenhausʼs Legal Philosophy -On the Puzzle of Wicked Legal Systems-

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