Radiogenic heat production drives Cambrian–Ordovician metamorphism of the Curnamona Province, south-central Australia: Insights from petrochronology and thermal modelling

Multi-mineral petrochronology can effectively track changes in the thermochemical environment experienced by rocks during metamorphism. We demonstrate this concept using garnet–chlorite schists from the Walter-Outalpa Shear Zone of the southern Curnamona Province, South Australia, which reveal a cryptic and protracted (c. 39 Myr) record of high thermal gradient metamorphism. Petrochronological data including in situ monazite U–Pb and garnet Lu–Hf and Sm–Nd dating suggest elevated geotherms were persistent between at least c. 519–480 Ma, throughout the duration of garnet growth. Additional in situ xenotime U–Pb dating implies that partial garnet breakdown occurred between c. 480–440 Ma, likely induced by fluid-rock interaction or exhumation. Although metamorphism temporally overlaps with the timing of the regional Delamerian Orogeny (c. 520–480 Ma), the thermal mechanism to sustain elevated temperatures has remained enigmatic. One-dimensional thermal models are used to appraise the role of radiogenic heat production in driving the observed high thermal gradient metamorphism. The models reveal that with only modest crustal thickening during orogenesis, the endogenous radiogenic heat production hosted within the basement rocks could plausibly provide the thermal impetus for metamorphism

Residential mobility and childhood leukemia.

AimsStudies of environmental exposures and childhood leukemia studies do not usually account for residential mobility. Yet, in addition to being a potential risk factor, mobility can induce selection bias, confounding, or measurement error in such studies. Using data collected for California Powerline Study (CAPS), we attempt to disentangle the effect of mobility.MethodsWe analyzed data from a population-based case-control study of childhood leukemia using cases who were born in California and diagnosed between 1988 and 2008 and birth certificate controls. We used stratified logistic regression, case-only analysis, and propensity-score adjustments to assess predictors of residential mobility between birth and diagnosis, and account for potential confounding due to residential mobility.ResultsChildren who moved tended to be older, lived in housing other than single-family homes, had younger mothers and fewer siblings, and were of lower socioeconomic status. Odds ratios for leukemia among non-movers living <50 meters (m) from a 200+ kilovolt line (OR: 1.62; 95% CI: 0.72-3.65) and for calculated fields ≥ 0.4 microTesla (OR: 1.71; 95% CI: 0.65-4.52) were slightly higher than previously reported overall results. Adjustments for propensity scores based on all variables predictive of mobility, including dwelling type, increased odds ratios for leukemia to 2.61 (95% CI: 1.76-3.86) for living < 50 m from a 200 + kilovolt line and to 1.98 (1.11-3.52) for calculated fields. Individual or propensity-score adjustments for all variables, except dwelling type, did not materially change the estimates of power line exposures on childhood leukemia.ConclusionThe residential mobility of childhood leukemia cases varied by several sociodemographic characteristics, but not by the distance to the nearest power line or calculated magnetic fields. Mobility appears to be an unlikely explanation for the associations observed between power lines exposure and childhood leukemia

Driving next generation manufacturing through advanced metals characterisation capability

Understanding the effects of manufacturing methods upon materials has driven constant innovation for over 300 years. While our ability to fabricate metallurgical wonders extends into the annals of history our ability to understand the scientific principles where process meets material has been pivotal to improving our capabilities. In this letter we briefly consider this history, comment upon the current state-of-the-art and, most importantly, propose new technologies for future industrial application which have been devised and exploited by the authors. It is hoped that this letter will allow other researchers to engage in this topic and facilitate the emergence of new processcompatible technologies which do not require destructive evaluation. This is particularly timely given the ability to manipulate microstructures with increasing dexterity. This is perhaps best illustrated in additive manufacturing [1] but is also a key consideration when process planning for machining [2], grinding [3] and forming [4]

Dynamic Clustering of Histogram Data Based on Adaptive Squared Wasserstein Distances

This paper deals with clustering methods based on adaptive distances for histogram data using a dynamic clustering algorithm. Histogram data describes individuals in terms of empirical distributions. These kind of data can be considered as complex descriptions of phenomena observed on complex objects: images, groups of individuals, spatial or temporal variant data, results of queries, environmental data, and so on. The Wasserstein distance is used to compare two histograms. The Wasserstein distance between histograms is constituted by two components: the first based on the means, and the second, to internal dispersions (standard deviation, skewness, kurtosis, and so on) of the histograms. To cluster sets of histogram data, we propose to use Dynamic Clustering Algorithm, (based on adaptive squared Wasserstein distances) that is a k-means-like algorithm for clustering a set of individuals into $K$ classes that are apriori fixed. The main aim of this research is to provide a tool for clustering histograms, emphasizing the different contributions of the histogram variables, and their components, to the definition of the clusters. We demonstrate that this can be achieved using adaptive distances. Two kind of adaptive distances are considered: the first takes into account the variability of each component of each descriptor for the whole set of individuals; the second takes into account the variability of each component of each descriptor in each cluster. We furnish interpretative tools of the obtained partition based on an extension of the classical measures (indexes) to the use of adaptive distances in the clustering criterion function. Applications on synthetic and real-world data corroborate the proposed procedure

Vapour-liquid coexistence in many-body dissipative particle dynamics

Many-body dissipative particle dynamics is constructed to exhibit vapour-liquid coexistence, with a sharp interface, and a vapour phase of vanishingly small density. In this form, the model is an unusual example of a soft-sphere liquid with a potential energy built out of local-density dependent one-particle self energies. The application to fluid mechanics problems involving free surfaces is illustrated by simulation of a pendant drop.Comment: 8 pages, 6 figures, revtex

Glide and Superclimb of Dislocations in Solid 4^4He

Glide and climb of quantum dislocations under finite external stress, variation of chemical potential and bias (geometrical slanting) in Peierls potential are studied by Monte Carlo simulations of the effective string model. We treat on unified ground quantum effects at finite temperatures $T$. Climb at low $T$ is assisted by superflow along dislocation core -- {\it superclimb}. Above some critical stress avalanche-type creation of kinks is found. It is characterized by hysteretic behavior at low $T$. At finite biases gliding dislocation remains rough even at lowest $T$ -- the behavior opposite to non-slanted dislocations. In contrast to glide, superclimb is characterized by quantum smooth state at low temperatures even for finite bias. In some intermediate $T$-range giant values of the compressibility as well as non-Luttinger type behavior of the core superfluid are observed.Comment: Updated version submitted to JLTP as QFS2010 proceedings; 11 pages, 6 figure

The community ecology perspective of omics data

The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (ɑ-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (β-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of ɑ- and β-diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data. Video Abstract

Magnetic phases of skyrmion-hosting GaV4S8−ySey (y = 0, 2, 4, 8) probed with muon spectroscopy

We present the results of a muon-spin spectroscopy investigation of GaV4S8−ySey with y = 0, 2, 4, and 8. Zero-field measurements suggest that GaV4Se8 and GaV4S8 have distinct magnetic ground states, with the latter material showing an anomalous temperature dependence of the local magnetic field. It is not possible to evolve the magnetic state continuously between these two systems, with the intermediate y = 2 and 4 materials showing glassy magnetic behavior at low temperature. The skyrmion lattice (SkL) phase is evident in the y = 0 and 8 materials through an enhanced response of the muon-spin relaxation to the emergent dynamics that accompany the SkL. For our polycrystalline samples of GaV4Se8, this enhanced dynamic response is confined to a smaller region of the magnetic field-temperature phase diagram than the previous reports of the SkL in single crystals

Classification of a supersolid: Trial wavefunctions, Symmetry breakings and Excitation spectra

A state of matter is characterized by its symmetry breaking and elementary excitations. A supersolid is a state which breaks both translational symmetry and internal $U(1)$ symmetry. Here, we review some past and recent works in phenomenological Ginsburg-Landau theories, ground state trial wavefunctions and microscopic numerical calculations. We also write down a new effective supersolid Hamiltonian on a lattice. The eigenstates of the Hamiltonian contains both the ground state wavefunction and all the excited states (supersolidon) wavefunctions. We contrast various kinds of supersolids in both continuous systems and on lattices, both condensed matter and cold atom systems. We provide additional new insights in studying their order parameters, symmetry breaking patterns, the excitation spectra and detection methods.Comment: REVTEX4, 19 pages, 3 figure

Defects and glassy dynamics in solid He-4: Perspectives and current status

We review the anomalous behavior of solid He-4 at low temperatures with particular attention to the role of structural defects present in solid. The discussion centers around the possible role of two level systems and structural glassy components for inducing the observed anomalies. We propose that the origin of glassy behavior is due to the dynamics of defects like dislocations formed in He-4. Within the developed framework of glassy components in a solid, we give a summary of the results and predictions for the effects that cover the mechanical, thermodynamic, viscoelastic, and electro-elastic contributions of the glassy response of solid He-4. Our proposed glass model for solid He-4 has several implications: (1) The anomalous properties of He-4 can be accounted for by allowing defects to freeze out at lowest temperatures. The dynamics of solid He-4 is governed by glasslike (glassy) relaxation processes and the distribution of relaxation times varies significantly between different torsional oscillator, shear modulus, and dielectric function experiments. (2) Any defect freeze-out will be accompanied by thermodynamic signatures consistent with entropy contributions from defects. It follows that such entropy contribution is much smaller than the required superfluid fraction, yet it is sufficient to account for excess entropy at lowest temperatures. (3) We predict a Cole-Cole type relation between the real and imaginary part of the response functions for rotational and planar shear that is occurring due to the dynamics of defects. Similar results apply for other response functions. (4) Using the framework of glassy dynamics, we predict low-frequency yet to be measured electro-elastic features in defect rich He-4 crystals. These predictions allow one to directly test the ideas and very presence of glassy contributions in He-4.Comment: 33 pages, 13 figure