Tsetse Genetics: Contributions to Biology, Systematics, and Control of Tsetse Flies

Tsetse flies (Diptera: Glossinidae) constitute a small, ancient taxon of exclusively hematophagous insects that reproduce slowly and viviparously. Because tsetse flies are the only vectors of pathogenic African trypanosomes, they are a potent and constant threat to humans and livestock over much of sub-Saharan Africa. Despite their low fecundity, tsetse flies demonstrate great resilience, which makes population suppression expensive, transient, and beyond the capacities of private and public sectors to accomplish, except over small areas. Nevertheless, control measures that include genetic methods are under consideration at national and supranational levels. There is a pressing need for sufficient laboratory cultures of tsetse flies and financial support to carry out genetic research. Here we review tsetse genetics from organismal and population points of view and identify some research needs

Effects of rain shelter or simulated rain during grain filling and maturation on subsequent wheat grain quality in the UK

The effects of simulated additional rain (ear wetting, 25 mm) or of rain shelter imposed at different periods after anthesis on grain quality at maturity and the dynamics of grain filling and desiccation were investigated in UK field-grown crops of wheat (Triticum aestivum L., cvar Tybalt) in 2011 and in 2012 when June–August rainfall was 255.0 and 214.6 mm, respectively, and above the decadal mean (157.4 mm). Grain filling and desiccation were quantified well by broken-stick regressions and Gompertz curves, respectively. Rain shelter for 56 (2011) or 70 d (2012) after anthesis, and to a lesser extent during late maturation only, resulted in more rapid desiccation and hence progress to harvest maturity whereas ear wetting had negligible effects, even when applied four times. Grain-filling duration was also affected as above in 2011, but with no significant effect in 2012. In both years, there were strong positive associations between final grain dry weight and duration of filling. The treatments affected all grain quality traits in 2011: nitrogen (N) and sulphur (S) concentrations, N:S ratio, sodium dodecyl sulphate (SDS) sedimentation volume, Hagberg Falling Number (HFN), and the incidence of blackpoint. Only N concentration and blackpoint were affected significantly by treatments in 2012. Rain shelter throughout grain filling reduced N concentration, whereas rain shelter reduced the incidence of blackpoint and ear wetting increased it. In 2011, rain shelter throughout reduced S concentration, increased N:S ratio and reduced SDS. Treatment effects on HFN were not consistent within or between years. Nevertheless, a comparison between the extreme treatment means in 2012 indicated damage from late rain combined with ear wetting resulted in a reduction of c. 0.7 s in HFN/mm August rainfall, whilst that between samples taken immediately after ear wetting at harvest maturity or 7 d later suggested recovery from damage to HFN upon re-drying in planta. Hence, the incidence of blackpoint was the only grain quality trait affected consistently by the diverse treatments. The remaining aspects of grain quality were comparatively resilient to rain incident upon developing and maturing ears of cvar Tybalt. No consistent temporal patterns of sensitivity to shelter or ear wetting were detected for any aspect of grain quality

Topological Defects and the Spin Glass Phase of Cuprates

We propose that the spin glass phase of cuprates is due to the proliferation of topological defects of a spiral distortion of the antiferromagnet order. Our theory explains straightforwardly the simultaneous existence of short range incommensurate magnetic correlations and complete a-b symmetry breaking in this phase. We show via a renormalization group calculation that the collinear O(3)/O(2) symmetry is unstable towards the formation of local non-collinear correlations. A critical disorder strength is identified beyond which topological defects proliferate already at zero temperature.Comment: 7 pages, 2 figures. Final version with some changes and one replaced figur

Magnetic susceptibility of a CuO2 plane in the La2CuO4 system: I. RPA treatment of the Dzyaloshinskii-Moriya Interactions

Motivated by recent experiments on undoped La2CuO4, which found pronounced temperature-dependent anisotropies in the low-field magnetic susceptibility, we have investigated a two-dimensional square lattice of S=1/2 spins that interact via Heisenberg exchange plus the symmetric and anti-symmetric Dzyaloshinskii-Moriya anisotropies. We describe the transition to a state with long-ranged order, and find the spin-wave excitations, with a mean-field theory, linear spin-wave analysis, and using Tyablikov's RPA decoupling scheme. We find the different components of the susceptibility within all of these approximations, both below and above the N'eel temperature, and obtain evidence of strong quantum fluctuations and spin-wave interactions in a broad temperature region near the transition.Comment: 20 pages, 2 column format, 22 figure

The use of a coaxial gun for plasma propulsion Final report

Plasma propulsion by coaxial gu

Unifying the Phase Diagrams of the Magnetic and Transport Properties of La_(2-x)Sr_xCuO_4, 0 < x < 0.05

An extensive experimental and theoretical effort has led to a largely complete mapping of the magnetic phase diagram of La_(2-x)Sr_xCuO_4, and a microscopic model of the spin textures produced in the x < 0.05 regime has been shown to be in agreement with this phase diagram. Here we use this same model to derive a theory of the impurity-dominated, low temperature transport. Then, we present an analysis of previously published data for two samples: x = 0.002 data from Chen et. al., and x = 0.04 data from Keimer et. al. We show that the transport mechanisms in the two systems are the same, even though they are on opposite sides of the observed insulator-to-metal transition. Our model of impurity effects on the impurity band conduction, variable-range hopping conduction, and coulomb gap conduction, is similar to that used to describe doped semiconductors. However, for La_(2-x)Sr_xCuO_4 we find that in addition to impurity-generated disorder effects, strong correlations are important and must be treated on a equal level with disorder. On the basis of this work we propose a phase diagram that is consistent with available magnetic and transport experiments, and which connects the undoped parent compound with the lowest x value for which La_(2-x)Sr_xCuO_4 is found to be superconducting, x about 0.06.Comment: 7 pages revtex with one .ps figur

Sr impurity effects on the magnetic correlations of LaSrCuO

We examine the low-temperature magnetic properties of moderately doped LaSrCuO paying particular attention to the spin-glass (SG) phase and the C-IC transition as they are affected by Sr impurity disorder. New measurements of the low-temperature susceptibility in the SG phase show an increase of an anomalously small Curie constant with doping. This behaviour is explained in terms of our theoretical work that finds small clusters of AFM correlated regions separated by disordered domain walls. The domain walls lead to a percolating sequence of paths connecting the impurities. We predict that for this spin morphology the Curie constant should scale as $1/(2 \xi(x,T=0)^2)$, a result that is quantitatively in agreement with experiment. Also, we find that the magnetic correlations in the ground states in the SG phase are commensurate, and that this behaviour should persist at higher temperatures where the holes should move along the domain walls. However, our results show that incommensurate correlations develop continuously around 5 % doping, consistent with recent measurements by Yamada.Comment: 30 pages, revtex, 8 .ps format figures (2 meant to be in colour), to be published in Physical Review B

MetabR: an R script for linear model analysis of quantitative metabolomic data

Background Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings Here we present a simple menu-driven program, “MetabR”, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA) to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org

MetabR: an R script for linear model analysis of quantitative metabolomic data

Background Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings Here we present a simple menu-driven program, “MetabR”, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA) to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/ webcite

Chiral Plaquette Polaron Theory of Cuprate Superconductivity

Ab-initio density functional calculations on explicitly doped La(2-x)Sr(x)CuO4 find doping creates localized holes in out-of-plane orbitals. A model for superconductivity is developed based on the assumption that doping leads to the formation of holes on a four-site Cu plaquette composed of the out-of-plane A1 orbitals apical O pz, planar Cu dz2, and planar O psigma. This is in contrast to the assumption of hole doping into planar Cu dx2-y2 and O psigma orbitals as in the t-J model. Interaction of holes with the d9 spin background leads to chiral polarons with either a clockwise or anti-clockwise charge current. When the polaron plaquettes percolate through the crystal at x~0.05 for LaSrCuO, a Cu dx2-y2 and planar O psigma band is formed. Spin exchange Coulomb repulsion with chiral polarons leads to D-wave superconductivity. The equivalent of the Debye energy in phonon superconductivity is the maximum energy separation between a chiral polaron and its time-reversed partner. An additive skew-scattering contribution to the Hall effect is induced by chiral polarons and leads to a temperature dependent Hall effect that fits the measured values for LaSrCuO. The integrated imaginary susceptibility satisfies omega/T scaling due to chirality and spin-flip scattering of polarons along with a uniform distribution of polaron energy splittings. The derived functional form is compatible with experiments. The static spin structure factor is computed and is incommensurate with a separation distance from (pi,pi) given by ~(2pi)x. Coulomb scattering of the x2-y2 band with polarons leads to linear resistivity. Coupling of the x2-y2 band to the undoped Cu d9 spins leads to the ARPES pseudogap and its doping and temperature dependence.Comment: 32 pages, 17 figure