An exact solution of spherical mean-field plus orbit-dependent non-separable pairing model with two non-degenerate j-orbits

An exact solution of nuclear spherical mean-field plus orbit-dependent non-separable pairing model with two non-degenerate j-orbits is presented. The extended one-variable Heine-Stieltjes polynomials associated to the Bethe ansatz equations of the solution are determined, of which the sets of the zeros give the solution of the model, and can be determined relatively easily. A comparison of the solution to that of the standard pairing interaction with constant interaction strength among pairs in any orbit is made. It is shown that the overlaps of eigenstates of the model with those of the standard pairing model are always large, especially for the ground and the first excited state. However, the quantum phase crossover in the non-separable pairing model cannot be accounted for by the standard pairing interaction.Comment: 5 pages, 1 figure, LaTe

Phylogenetic Molecular Ecological Network of Soil Microbial Communities in Response to Elevated CO2

Understanding the interactions among different species and their responses to environmental changes, such as elevated atmospheric concentrations of CO2, is a central goal in ecology but is poorly understood in microbial ecology. Here we describe a novel random matrix theory (RMT)-based conceptual framework to discern phylogenetic molecular ecological networks using metagenomic sequencing data of 16S rRNA genes from grassland soil microbial communities, which were sampled from a long-term free-air CO2 enrichment experimental facility at the Cedar Creek Ecosystem Science Reserve in Minnesota. Our experimental results demonstrated that an RMT-based network approach is very useful in delineating phylogenetic molecular ecological networks of microbial communities based on high-throughput metagenomic sequencing data. The structure of the identified networks under ambient and elevated CO2 levels was substantially different in terms of overall network topology, network composition, node overlap, module preservation, module-based higher-order organization, topological roles of individual nodes, and network hubs, suggesting that the network interactions among different phylogenetic groups/populations were markedly changed. Also, the changes in network structure were significantly correlated with soil carbon and nitrogen contents, indicating the potential importance of network interactions in ecosystem functioning. In addition, based on network topology, microbial populations potentially most important to community structure and ecosystem functioning can be discerned. The novel approach described in this study is important not only for research on biodiversity, microbial ecology, and systems microbiology but also for microbial community studies in human health, global change, and environmental management

Pure Monte Carlo Counterfactual Regret Minimization

Counterfactual Regret Minimization (CFR) and its variants are the best algorithms so far for solving large-scale incomplete information games. Building upon CFR, this paper proposes a new algorithm named Pure CFR (PCFR) for achieving better performance. PCFR can be seen as a combination of CFR and Fictitious Play (FP), inheriting the concept of counterfactual regret (value) from CFR, and using the best response strategy instead of the regret matching strategy for the next iteration. Our theoretical proof that PCFR can achieve Blackwell approachability enables PCFR's ability to combine with any CFR variant including Monte Carlo CFR (MCCFR). The resultant Pure MCCFR (PMCCFR) can significantly reduce time and space complexity. Particularly, the convergence speed of PMCCFR is at least three times more than that of MCCFR. In addition, since PMCCFR does not pass through the path of strictly dominated strategies, we developed a new warm-start algorithm inspired by the strictly dominated strategies elimination method. Consequently, the PMCCFR with new warm start algorithm can converge by two orders of magnitude faster than the CFR+ algorithm

The tricarboxylic acid cycle in Shewanella oneidensis is independent of Fur and RyhB control

Background: It is well established in E. coli and Vibrio cholerae that strains harboring mutations in the ferric uptake regulator gene (fur) are unable to utilize tricarboxylic acid (TCA) compounds, due to the down-regulation of key TCA cycle enzymes, such as AcnA and SdhABCD. This down-regulation is mediated by a Fur-regulated small regulatory RNA named RyhB. It is unclear in the gamma proteobacterium S. oneidensis whether TCA is also regulated by Fur and RyhB. Results: In the present study, we showed that a fur deletion mutant of S. oneidensis could utilize TCA compounds. Consistently, expression of the TCA cycle genes acnA and sdhA was not down-regulated in the mutant. To explore this observation further, we identified a ryhB gene in Shewanella species and experimentally demonstrated the gene expression. Further experiments suggested that RyhB was up-regulated in fur mutant, but that AcnA and SdhA were not controlled by RyhB. Conclusions: These cumulative results delineate an important difference of the Fur-RyhB regulatory cycle between S. oneidensis and other gamma-proteobacteria. This work represents a step forward for understanding the unique regulation in S. oneidensis

Zonal Soil Type Determines Soil Microbial Responses to Maize Cropping and Fertilization.

Soil types heavily influence ecological dynamics. It remains controversial to what extent soil types shape microbial responses to land management changes, largely due to lack of in-depth comparison across various soil types. Here, we collected samples from three major zonal soil types spanning from cold temperate to subtropical climate zones. We examined bacterial and fungal community structures, as well as microbial functional genes. Different soil types had distinct microbial biomass levels and community compositions. Five years of maize cropping (growing corn or maize) changed the bacterial community composition of the Ultisol soil type and the fungal composition of the Mollisol soil type but had little effect on the microbial composition of the Inceptisol soil type. Meanwhile, 5 years of fertilization resulted in soil acidification. Microbial compositions of the Mollisol and Ultisol, but not the Inceptisol, were changed and correlated (P < 0.05) with soil pH. These results demonstrated the critical role of soil type in determining microbial responses to land management changes. We also found that soil nitrification potentials correlated with the total abundance of nitrifiers and that soil heterotrophic respiration correlated with the total abundance of carbon degradation genes, suggesting that changes in microbial community structure had altered ecosystem processes. IMPORTANCE Microbial communities are essential drivers of soil functional processes such as nitrification and heterotrophic respiration. Although there is initial evidence revealing the importance of soil type in shaping microbial communities, there has been no in-depth, comprehensive survey to robustly establish it as a major determinant of microbial community composition, functional gene structure, or ecosystem functioning. We examined bacterial and fungal community structures using Illumina sequencing, microbial functional genes using GeoChip, microbial biomass using phospholipid fatty acid analysis, as well as functional processes of soil nitrification potential and CO2 efflux. We demonstrated the critical role of soil type in determining microbial responses to land use changes at the continental level. Our findings underscore the inherent difficulty in generalizing ecosystem responses across landscapes and suggest that assessments of community feedback must take soil types into consideration. Author Video: An author video summary of this article is available