From Images to Connections: Can DQN with GNNs learn the Strategic Game of Hex?

The gameplay of strategic board games such as chess, Go and Hex is often characterized by combinatorial, relational structures -- capturing distinct interactions and non-local patterns -- and not just images. Nonetheless, most common self-play reinforcement learning (RL) approaches simply approximate policy and value functions using convolutional neural networks (CNN). A key feature of CNNs is their relational inductive bias towards locality and translational invariance. In contrast, graph neural networks (GNN) can encode more complicated and distinct relational structures. Hence, we investigate the crucial question: Can GNNs, with their ability to encode complex connections, replace CNNs in self-play reinforcement learning? To this end, we do a comparison with Hex -- an abstract yet strategically rich board game -- serving as our experimental platform. Our findings reveal that GNNs excel at dealing with long range dependency situations in game states and are less prone to overfitting, but also showing a reduced proficiency in discerning local patterns. This suggests a potential paradigm shift, signaling the use of game-specific structures to reshape self-play reinforcement learning

Synergism of microwaves and ultrasound for advanced biorefineries

AbstractConventional energy sources are limited and non-renewable and their consumption contributes to greenhouse gas emissions. The world is in need of advanced biorefineries to meet ever growing energy demands associated with population growth and economic development. An advanced biorefinery should use renewable and sustainable (both in quality and quantity) feedstock that gives rise to higher energy gains with minimum non-renewable energy and resource consumption. Development of advanced biorefineries is currently encircled by two major issues. The first issue is to ensure adequate biofuel feedstock supplies while the second issue is to develop resource-efficient technologies for the feedstock conversion to maximize energy and economic and environmental benefits. While microalgae, microbial derived oils, and agricultural biomass and other energy crops show great potential for meeting current energy demands in a sustainable manner, process intensification and associated synergism can improve the resource utilization efficiency. Synergism of process intensification tools is important to increase energy efficiency, reduce chemical utilization and associated environmental impacts, and finally process economics. Among the many process intensification methods, this commentary provides a perspective on the essential role of MWs and US and their synergy in biofuel production. Individual, sequential, and simultaneous applications of MWs and US irradiations can be utilized for process intensification of various biofuels production and selective recovery of high value bioproducts. Process related barriers, namely mass and heat transfer limitations, can be eliminated by this synergism while improving the reaction efficiency and overall process economics significantly. In this article, a brief review focused on recent developments in MW and US mediated process intensification for biofuel synthesis and associated issues in their synergism followed by a discussion on current challenges and future prospective is presented

An Eye for Landscapes - Rapid Aerial Mapping with Handheld Sensors

This portable system offers fast deployment with no recalibration and maps both vertical and horizontal features while maintaning optimal flight parameters. The geo-referenced image and 3D point-cloud data can be processed into digital terrain models, digital surface models, and automatically derived 3D city models

UniPathway: a resource for the exploration and annotation of metabolic pathways

UniPathway (http://www.unipathway.org) is a fully manually curated resource for the representation and annotation of metabolic pathways. UniPathway provides explicit representations of enzyme-catalyzed and spontaneous chemical reactions, as well as a hierarchical representation of metabolic pathways. This hierarchy uses linear subpathways as the basic building block for the assembly of larger and more complex pathways, including species-specific pathway variants. All of the pathway data in UniPathway has been extensively cross-linked to existing pathway resources such as KEGG and MetaCyc, as well as sequence resources such as the UniProt KnowledgeBase (UniProtKB), for which UniPathway provides a controlled vocabulary for pathway annotation. We introduce here the basic concepts underlying the UniPathway resource, with the aim of allowing users to fully exploit the information provided by UniPathwa

Environmental shaping of codon usage and functional adaptation across microbial communities.

Microbial communities represent the largest portion of the Earth's biomass. Metagenomics projects use high-throughput sequencing to survey these communities and shed light on genetic capabilities that enable microbes to inhabit every corner of the biosphere. Metagenome studies are generally based on (i) classifying and ranking functions of identified genes; and (ii) estimating the phyletic distribution of constituent microbial species. To understand microbial communities at the systems level, it is necessary to extend these studies beyond the species' boundaries and capture higher levels of metabolic complexity. We evaluated 11 metagenome samples and demonstrated that microbes inhabiting the same ecological niche share common preferences for synonymous codons, regardless of their phylogeny. By exploring concepts of translational optimization through codon usage adaptation, we demonstrated that community-wide bias in codon usage can be used as a prediction tool for lifestyle-specific genes across the entire microbial community, effectively considering microbial communities as meta-genomes. These findings set up a 'functional metagenomics' platform for the identification of genes relevant for adaptations of entire microbial communities to environments. Our results provide valuable arguments in defining the concept of microbial species through the context of their interactions within the community