Microscopic Mechanism of the Helix-to-Layer Transformation in Elemental Group VI Solids

We study the conversion of bulk Se and Te, consisting of intertwined a helices, to structurally very dissimilar, atomically thin two-dimensional (2D) layers of these elements. Our ab initio calculations reveal that previously unknown and unusually stable \delta - and \eta-2D allotropes may form in an intriguing multi-step process that involves a concerted motion of many atoms at dislocation defects. We identify such a complex reaction path involving zipper-like motion of such dislocations that initiate structural changes. With low activation barriers <0.3 eV along the optimum path, the conversion process may occur at moderate temperatures. We find all one-dimensional (1D) and 2D chalcogen structures to be semiconducting.Comment: accepted by Nano Letter

Phase synchronization during the processing of taxonomic and thematic relations

Semantic relations include “taxonomic” relations based on shared features and “thematic” relations based on co-occurrence in events. The “dual-hub” account proposes that the anterior temporal lobe (ATL) is functionally specialized for taxonomic relations and the inferior parietal lobule (IPL) for thematic relations. This study examined this claim by analyzing the intra- and inter-region phase synchronization of intracranial EEG data from electrodes in the ATL, IPL, and two subregions of the semantic control network: left inferior frontal gyrus (IFG) and posterior middle temporal gyrus (pMTG). Ten participants with epilepsy completed a semantic relatedness judgment task during intracranial EEG recording and had electrodes in at least one hub and at least one semantic control region. Theta band phase synchronization was partially consistent with the dual-hub account: synchronization between the ATL and IFG/pMTG increased when processing taxonomic relations, and synchronization within the IPL and between IPL and pMTG increased when processing thematic relations

Comparative analysis of metabolome of rice seeds at three developmental stages using a recombinant inbred line population.

Plants are considered an important food and nutrition source for humans. Despite advances in plant seed metabolomics, knowledge about the genetic and molecular bases of rice seed metabolomes at different developmental stages is still limited. Here, using Zhenshan 97 (ZS97) and Minghui 63 (MH63), we performed a widely targeted metabolic profiling in seeds during grain filling, mature seeds and germinating seeds. The diversity between MH63 and ZS97 was characterized in terms of the content of metabolites and the metabolic shifting across developmental stages. Taking advantage of the ultra-high-density genetic map of a population of 210 recombinant inbred lines (RILs) derived from a cross between ZS97 and MH63, we identified 4681 putative metabolic quantitative trait loci (mQTLs) in seeds across the three stages. Further analysis of the mQTLs for the codetected metabolites across the three stages revealed that the genetic regulation of metabolite accumulation was closely related to developmental stage. Using in silico analyses, we characterized 35 candidate genes responsible for 30 structurally identified or annotated compounds, among which LOC_Os07g04970 and LOC_Os06g03990 were identified to be responsible for feruloylserotonin and l-asparagine content variation across populations, respectively. Metabolite-agronomic trait association and colocation between mQTLs and phenotypic quantitative trait loci (pQTLs) revealed the complexity of the metabolite-agronomic trait relationship and the corresponding genetic basis

OsbZIP18, a Positive Regulator of Serotonin Biosynthesis, Negatively Controls the UV-B Tolerance in Rice

Serotonin (5-hydroxytryptamine) plays an important role in many developmental processes and biotic/abiotic stress responses in plants. Although serotonin biosynthetic pathways in plants have been uncovered, knowledge of the mechanisms of serotonin accumulation is still limited, and no regulators have been identified to date. Here, we identified the basic leucine zipper transcription factor OsbZIP18 as a positive regulator of serotonin biosynthesis in rice. Overexpression of OsbZIP18 strongly induced the levels of serotonin and its early precursors (tryptophan and tryptamine), resulting in stunted growth and dark-brown phenotypes. A function analysis showed that OsbZIP18 activated serotonin biosynthesis genes (including tryptophan decarboxylase 1 (OsTDC1), tryptophan decarboxylase 3 (OsTDC3), and tryptamine 5-hydroxylase (OsT5H)) by directly binding to the ACE-containing or G-box cis-elements in their promoters. Furthermore, we demonstrated that OsbZIP18 is induced by UV-B stress, and experiments using UV-B radiation showed that transgenic plants overexpressing OsbZIP18 exhibited UV-B stress-sensitive phenotypes. Besides, exogenous serotonin significantly exacerbates UV-B stress of OsbZIP18_OE plants, suggesting that the excessive accumulation of serotonin may be responsible for the sensitivity of OsbZIP18_OE plants to UV-B stress. Overall, we identified a positive regulator of serotonin biosynthesis and demonstrated that UV-B-stress induced serotonin accumulation, partly in an OsbZIP18-dependent manner

Inversion Study of Vertical Eddy Viscosity Coefficient Based on an Internal Tidal Model with the Adjoint Method

Based on an isopycnic-coordinate internal tidal model with the adjoint method, the inversion of spatially varying vertical eddy viscosity coefficient (VEVC) is studied in two groups of numerical experiments. In Group One, the influences of independent point schemes (IPSs) exerting on parameter inversion are discussed. Results demonstrate that the VEVCs can be inverted successfully with IPSs and the model has the best performance with the optimal IPSs. Using the optimal IPSs obtained in Group One, the inversions of VEVCs on two different Gaussian bottom topographies are carried out in Group Two. In addition, performances of two optimization methods of which one is the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method and the other is a simplified gradient descent method (GDM-S) are also investigated. Results of the experiments indicate that this adjoint model is capable to invert the VEVC with spatially distribution, no matter which optimization method is taken. The L-BFGS method has a better performance in terms of the convergence rate and the inversion results. In general, the L-BFGS method is a more effective and efficient optimization method than the GDM-S