Role of Probiotics in the Management of COVID-19: A Computational Perspective

Coronavirus disease 2019 (COVID-19) was declared a pandemic at the beginning of 2020, causing millions of deaths worldwide. Millions of vaccine doses have been administered worldwide; however, outbreaks continue. Probiotics are known to restore a stable gut microbiota by regulating innate and adaptive immunity within the gut, demonstrating the possibility that they may be used to combat COVID-19 because of several pieces of evidence suggesting that COVID-19 has an adverse impact on gut microbiota dysbiosis. Thus, probiotics and their metabolites with known antiviral properties may be used as an adjunctive treatment to combat COVID-19. Several clinical trials have revealed the efficacy of probiotics and their metabolites in treating patients with SARS-CoV-2. However, its molecular mechanism has not been unraveled. The availability of abundant data resources and computational methods has significantly changed research finding molecular insights between probiotics and COVID-19. This review highlights computational approaches involving microbiome-based approaches and ensemble-driven docking approaches, as well as a case study proving the effects of probiotic metabolites on SARS-CoV-2.

Low-dimensional heterostructures for advanced electrocatalysis: an experimental and computational perspective

The development of LD heterostructure nanomaterials represents a powerful strategy totailor the electrocatalytic function of several interfacial active sites at the subnanometer level.

Computational Perspectives on Phonological Constituency and Recursion

Whether or not phonology has recursion is often conflated with whether or not phonology has strings or trees as data structures. Taking a computational perspective from formal language theory and focusing on how phonological strings and trees are built, we disentangle these issues. We show that even considering the boundedness of words and utterances in physical realization and the lack of observable examples of potential recursive embedding of phonological constituents beyond a few layers, recursion is a natural consequence of expressing generalization in phonological grammars for strings and trees. While prosodically-conditioned phonological patterns can be represented using grammars for strings, e.g., with bracketed string representations, we show how grammars for trees provide a natural way to express these patterns and provide insight into the kinds of analyses that phonologists have proposed for them.

Artificial virtuous agents: from theory to machine implementation

Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, we critically explore the possibilities and challenges for virtue ethics from a computational perspective. Drawing on previous conceptual and technical work, we outline a version of artificial virtue based on moral functionalism, connectionist bottom–up learning, and eudaimonic reward. We then describe how core features of the outlined theory can be interpreted in terms of functionality, which in turn informs the design of components necessary for virtuous cognition. Finally, we present a comprehensive framework for the technical development of artificial virtuous agents and discuss how they can be implemented in moral environments.

Multifunctional Electrocatalysis on Single-Site Metal Catalysts: A Computational Perspective

Multifunctional electrocatalysts are vastly sought for their applications in water splitting electrolyzers, metal-air batteries, and regenerative fuel cells because of their ability to catalyze multiple reactions such as hydrogen evolution, oxygen evolution, and oxygen reduction reactions. More specifically, the application of single-atom electrocatalyst in multifunctional catalysis is a promising approach to ensure good atomic efficiency, tunability and additionally benefits simple theoretical treatment. In this review, we provide insights into the variety of single-site metal catalysts and their identification. We also summarize the recent advancements in computational modeling of multifunctional electrocatalysis on single-site catalysts. Furthermore, we explain each modeling step with open-source-based working examples of a standard computational approach.