Infrared evidence of a Slater metal-insulator transition in NaOsO3

The magnetically driven metal-insulator transition (MIT) was predicted by Slater in the fifties. Here a long-range antiferromagnetic (AF) order can open up a gap at the Brillouin electronic band boundary regardless of the Coulomb repulsion magnitude. However, while many low-dimensional organic conductors display evidence for an AF driven MIT, in three-dimensional (3D) systems the Slater MIT still remains elusive. We employ terahertz and infrared spectroscopy to investigate the MIT in the NaOsO3 3D antiferromagnet. From the optical conductivity analysis we find evidence for a continuous opening of the energy gap, whose temperature dependence can be well described in terms of a second order phase transition. The comparison between the experimental Drude spectral weight and the one calculated through Local Density Approximation (LDA) shows that electronic correlations play a limited role in the MIT. All the experimental evidence demonstrates that NaOsO3 is the first known 3D Slater insulator.Comment: 4 figure

Mixture Transition Distribution Modelling of Multivariate Time Series of Discrete State Processes: With an Application to Modelling Flowering Synchronisation with Respect to Climate Dynamics

A new approach to assess synchronicity developed in this chapter is a novel bivariate extension of the generalised mixture transition distribution (MTDg) model (we coin this B-MTD). The aim of this chapter is to test MTDg an extended MTD with interactions model and its bivariate extension of MTD (B-MTD) to investigate synchrony of flowering of four Eucalypts species—E. leucoxylon, E. microcarpa, E. polyanthemos and E. tricarpa over a 31 year period. The mixture transition distribution (MTDg) is a method to estimate transition probabilities of high order Markov chains. Our B-MTD approach allows us the derive rules of thumb for synchrony and asynchrony between pairs of species, e.g. flowering of the four species. The latter B-MTD rules are based on transition probabilities between all possible on and off flowering states from previous to current time. We also apply MTDg modelling using lagged flowering states and climate covariates as predictors to model current flowering status (on/off) to assess synchronisation using residuals from the resultant models via our adaptation of Moran’s classic synchrony statistic. We compare these MTDg (with covariates)-based synchrony measures with our B-MTD results in addition to those from extended Kalman filter (EKF)-based residuals

Intranasal administration of NDV-HXP-S COVID19 vaccines induces robust protective mucosal and systemic immunity in mice

With the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continually changing and no end of this pandemic in sight, a next generation of vaccines preventing transmission and an equitable allocation is needed in order to reduce global disease burden. The NDV-HXP-S vaccine is based on recombinant Newcastle disease virus (NDV) stably expressing a membrane-anchored, optimized (with six proline mutations – Hexa Pro) spike protein1. Using the current influenza virus vaccine manufacturing facilities, this vaccine can be produced in embryonated eggs and thereby can meet the demands on a global scale at a low cost. Here, we report that mice vaccinated intranasally (i.n.) with different designs and regimens of our live NDV-HXP-S induced strong antibody response, displaying good systemic as well as mucosal immunity. Furthermore, the T and B cell responses in the lung were characterized via flow cytometry. It is important to emphasize, that we have been able to quickly adapt the vaccine to newly emerging variants of concern (VOC) of SARS-CoV-2. Please click Download on the upper right corner to see the full abstract

Is autoinducer-2 a universal signal for interspecies communication: a comparative genomic and phylogenetic analysis of the synthesis and signal transduction pathways

BACKGROUND: Quorum sensing is a process of bacterial cell-to-cell communication involving the production and detection of extracellular signaling molecules called autoinducers. Recently, it has been proposed that autoinducer-2 (AI-2), a furanosyl borate diester derived from the recycling of S-adenosyl-homocysteine (SAH) to homocysteine, serves as a universal signal for interspecies communication. RESULTS: In this study, 138 completed genomes were examined for the genes involved in the synthesis and detection of AI-2. Except for some symbionts and parasites, all organisms have a pathway to recycle SAH, either using a two-step enzymatic conversion by the Pfs and LuxS enzymes or a one-step conversion using SAH-hydrolase (SahH). 51 organisms including most Gamma-, Beta-, and Epsilonproteobacteria, and Firmicutes possess the Pfs-LuxS pathway, while Archaea, Eukarya, Alphaproteobacteria, Actinobacteria and Cyanobacteria prefer the SahH pathway. In all 138 organisms, only the three Vibrio strains had strong, bidirectional matches to the periplasmic AI-2 binding protein LuxP and the central signal relay protein LuxU. The initial two-component sensor kinase protein LuxQ, and the terminal response regulator luxO are found in most Proteobacteria, as well as in some Firmicutes, often in several copies. CONCLUSIONS: The genomic analysis indicates that the LuxS enzyme required for AI-2 synthesis is widespread in bacteria, while the periplasmic binding protein LuxP is only present in Vibrio strains. Thus, other organisms may either use components different from the AI-2 signal transduction system of Vibrio strains to sense the signal of AI-2, or they do not have such a quorum sensing system at all

An Unsupervised Generative Neural Approach for InSAR Phase Filtering and Coherence Estimation

Phase filtering and pixel quality (coherence) estimation is critical in producing Digital Elevation Models (DEMs) from Interferometric Synthetic Aperture Radar (InSAR) images, as it removes spatial inconsistencies (residues) and immensely improves the subsequent unwrapping. Large amount of InSAR data facilitates Wide Area Monitoring (WAM) over geographical regions. Advances in parallel computing have accelerated Convolutional Neural Networks (CNNs), giving them advantages over human performance on visual pattern recognition, which makes CNNs a good choice for WAM. Nevertheless, this research is largely unexplored. We thus propose "GenInSAR", a CNN-based generative model for joint phase filtering and coherence estimation, that directly learns the InSAR data distribution. GenInSAR's unsupervised training on satellite and simulated noisy InSAR images outperforms other five related methods in total residue reduction (over 16.5% better on average) with less over-smoothing/artefacts around branch cuts. GenInSAR's Phase, and Coherence Root-Mean-Squared-Error and Phase Cosine Error have average improvements of 0.54, 0.07, and 0.05 respectively compared to the related methods.Comment: to be published in a future issue of IEEE Geoscience and Remote Sensing Letter

Weight-Bearing Interventions to Decrease Spasticity and Improve Gait in Stroke Patients: A Case Report

The purpose of this case report was to determine the success of weight-bearing interventions on spasticity reduction and improved gait patterns in a 61 year-old-male patient recovering from a chronic left hemorrhagic CVA. The patient’s primary impairments included right upper and lower extremity spasticity, circumduction gait, weakness and decreased range of motion of right extremities. The interventions included in this patient’s treatment program included standing calf stretches, toe raises, ankle range of motion and gait training for 1 hour once a week for 4 weeks. This case report supports the application of weight-bearing through the paretic limb, which has been proven to be beneficial for reducing spasticity and increasing ROM to improve gait patterns for a patient recovering from a CVA.https://soar.usa.edu/casmfall2019/1002/thumbnail.jp