Flow-induced crystallisation of polymers from aqueous solution

Synthetic polymers are thoroughly embedded in the modern society and their consumption grows annually. Efficient routes to their production and processing have never been more important. In this respect, silk protein fibrillation is superior to conventional polymer processing, not only by achieving outstanding physical properties of materials, such as high tensile strength and toughness, but also improved process energy efficiency. Natural silk solidifies in response to flow of the liquid using conformation-dependent intermolecular interactions to desolvate (denature) protein chains. This mechanism is reproduced here by an aqueous poly(ethylene oxide) (PEO) solution, which solidifies at ambient conditions when subjected to flow. The transition requires that an energy threshold is exceeded by the flow conditions, which disrupts a protective hydration shell around polymer molecules, releasing them from a metastable state into the thermodynamically favoured crystalline state. This mechanism requires vastly lower energy inputs and demonstrates an alternative route for polymer processing

Mapping arctic tundra vegetation communities using field spectroscopy and multispectral satellite data in North Alaska, USA

The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ~1 m chamber flux) and those encompassing multiple vegetation communities (e.g., ~300 m eddy covariance measurements). The objectives of this study were: (1) to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2) to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450-510 nm, 630-690 nm and 705-745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450-510 nm and 630-690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (~70%) resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m) to patch level (<500 m) using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given thespatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments

The Off-diagonal Goldberger-Treiman Relation and Its Discrepancy

We study the off-diagonal Goldberger-Treiman relation (ODGTR) and its discrepancy (ODGTD) in the N, Delta, pi sector through O(p^2) using heavy baryon chiral perturbation theory. To this order, the ODGTD and axial vector N to Delta transition radius are determined solely by low energy constants. Loop corrections appear at O(p^4). For low-energy constants of natural size, the ODGTD would represent a ~ 2% correction to the ODGTR. We discuss the implications of the ODGTR and ODGTD for lattice and quark model calculations of the transition form factors and for parity-violating electroexcitation of the Delta.Comment: 11 pages, 1 eps figur

νd→μ−Δ++n\nu d \to \mu^- \Delta^{++} n Reaction and Axial Vector N−ΔN-\Delta Coupling

The reaction $\nu d \to \mu^- \Delta^{++} n$ is studied in the region of low $q^2$ to investigate the effect of deuteron structure and width of the $\Delta$ resonance on the differential cross section. The results are used to extract the axial vector $N-\Delta$ coupling $C^{A}_5$ from the experimental data on this reaction. The possibility to determine this coupling from electroweak interaction experiments with high intensity electron accelerators is discussed.Comment: 14 pages, REVTEX, 5 figure

Low-Prandtl-number B\'enard-Marangoni convection in a vertical magnetic field

The effect of a homogeneous magnetic field on surface-tension-driven B\'{e}nard convection is studied by means of direct numerical simulations. The flow is computed in a rectangular domain with periodic horizontal boundary conditions and the free-slip condition on the bottom wall using a pseudospectral Fourier-Chebyshev discretization. Deformations of the free surface are neglected. Two- and three-dimensional flows are computed for either vanishing or small Prandtl number, which are typical of liquid metals. The main focus of the paper is on a qualitative comparison of the flow states with the non-magnetic case, and on the effects associated with the possible near-cancellation of the nonlinear and pressure terms in the momentum equations for two-dimensional rolls. In the three-dimensional case, the transition from a stationary hexagonal pattern at the onset of convection to three-dimensional time-dependent convection is explored by a series of simulations at zero Prandtl number.Comment: 26 pages, 9 figure

The stochastic gravitational wave background from turbulence and magnetic fields generated by a first-order phase transition

We analytically derive the spectrum of gravitational waves due to magneto-hydrodynamical turbulence generated by bubble collisions in a first-order phase transition. In contrast to previous studies, we take into account the fact that turbulence and magnetic fields act as sources of gravitational waves for many Hubble times after the phase transition is completed. This modifies the gravitational wave spectrum at large scales. We also model the initial stirring phase preceding the Kolmogorov cascade, while earlier works assume that the Kolmogorov spectrum sets in instantaneously. The continuity in time of the source is relevant for a correct determination of the peak position of the gravitational wave spectrum. We discuss how the results depend on assumptions about the unequal-time correlation of the source and motivate a realistic choice for it. Our treatment gives a similar peak frequency as previous analyses but the amplitude of the signal is reduced due to the use of a more realistic power spectrum for the magneto-hydrodynamical turbulence. For a strongly first-order electroweak phase transition, the signal is observable with the space interferometer LISA.Comment: 46 pages, 17 figures. Replaced with revised version accepted for publication in JCA

Association of Prenatal Maternal Depression and Anxiety Symptoms with Infant White Matter Microstructure

Importance: Maternal depression and anxiety can have deleterious and lifelong consequences on child development. However, many aspects of the association of early brain development with maternal symptoms remain unclear. Understanding the timing of potential neurobiological alterations holds inherent value for the development and evaluation of future therapies and interventions. Objective: To examine the association between exposure to prenatal maternal depression and anxiety symptoms and offspring white matter microstructure at 1 month of age. Design, Setting, and Participants: This cohort study of 101 mother-infant dyads used a composite of depression and anxiety symptoms measured in mothers during the third trimester of pregnancy and measures of white matter microstructure characterized in the mothers' 1-month offspring using diffusion tensor imaging and neurite orientation dispersion and density imaging performed from October 1, 2014, to November 30, 2016. Magnetic resonance imaging was performed at an academic research facility during natural, nonsedated sleep. Main Outcomes and Measures: Brain mapping algorithms and statistical models were used to evaluate the association between maternal depression and anxiety and 1-month infant white matter microstructure as measured by diffusion tensor imaging and neurite orientation dispersion and density imaging findings. Results: In the 101 mother-infant dyads (mean [SD] age of mothers, 33.22 [3.99] years; mean age of infants at magnetic resonance imaging, 33.07 days [range, 18-50 days]; 92 white mothers [91.1%]; 53 male infants [52.5%]), lower 1-month white matter microstructure (decreased neurite density and increased mean, radial, and axial diffusivity) was associated in right frontal white matter microstructure with higher prenatal maternal symptoms of depression and anxiety. Significant sex × symptom interactions with measures of white matter microstructure were also observed, suggesting that white matter development may be differentially sensitive to maternal depression and anxiety symptoms in males and females during the prenatal period. Conclusions and Relevance: These data highlight the importance of the prenatal period to early brain development and suggest that the underlying white matter microstructure is associated with the continuum of prenatal maternal depression and anxiety symptoms

Perturbative and nonperturbative contributions to the strange quark asymmetry in the nucleon

There are two mechanisms for the generation of an asymmetry between the strange and anti-strange quark distributions in the nucleon: nonperturbative contributions originating from nucleons fluctuating into virtual baryon-meson pairs such as $\Lambda K$ and $\Sigma K$, and perturbative contributions arising from gluons splitting into strange and anti-strange quark pairs. While the nonperturbative contributions are dominant in the large-$x$ region, the perturbative contributions are more significant in the small-$x$ region. We calculate this asymmetry taking into account both nonperturbative and perturbative contributions, thus giving a more accurate evaluation of this asymmetry over the whole domain of $x$. We find that the perturbative contributions are generally a few times larger in magnitude than the nonperturbative contributions, which suggests that the best region to detect this asymmetry experimentally is in the region $0.02 < x < 0.03$. We find that the asymmetry may have more than one node, which is an effect that should be taken into account, e.g. for parameterizations of the strange and anti-strange quark distributions used in global analysis of parton distributions.Comment: 14 pages, 4 figures, figures comparing theoretical calculations with NNPDF global analysis added, accepted for publication in EPJ