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Abstract Stereoselective reactions have played a vital role in the emergence of life, evolution, human biology, and medicine. However, for a long time, most industrial and academic efforts followed a trial-and-error approach for asymmetric synthesis in stereoselective reactions. In addition, most previous studies have been qualitatively focused on the influence of steric and electronic effects on stereoselective reactions. Therefore, quantitatively understanding the stereoselectivity of a given chemical reaction is extremely difficult. As proof of principle, this paper develops a novel composite machine learning method for quantitatively predicting the enantioselectivity representing the degree to which one enantiomer is preferentially produced from the reactions. Specifically, machine learning methods that are widely used in data analytics, including Random Forest, Support Vector Regression, and LASSO, are utilized. In addition, the Bayesian optimization and permutation importance tests are provided for an in-depth understanding of reactions and accurate prediction. Finally, the proposed composite method approximates the key features of the available reactions by using Gaussian mixture models, which provide suitable machine learning methods for new reactions. The case studies using the real stereoselective reactions show that the proposed method is effective and provides a solid foundation for further application to other chemical reactions. 

Blockchain is the technology used by developers of cryptocurrencies, like Bitcoin, to enable exchange of financial “coins” between participants in the absence of a trusted third party to ensure the transaction, such as is typically done by governments. Blockchain has evolved to become a generic approach to store and process data in a highly decentralized and secure way. In this article, we review blockchain concepts and use cases, and discuss the challenges in using them from a governmental viewpoint. We begin with reviewing the categories of blockchains, the underlying mechanisms, and why blockchains can achieve their security goals. We then review existing known governmental use cases by regions. To show both technical and deployment details of blockchain adoption, we study a few representative use cases in the domains of healthcare and energy infrastructures. Finally, the review of both technical details and use cases helps us summarize the adoption and technical challenges of blockchains.