The steady state in noncollinear magnetic multilayers

There are at least two different putative steady state solutions for current across noncollinear magnetic multilayers; one has a discontinuity in the spin current at the interface the other is continuous. We compare the resistance of the two and find the solution with the continuous spin currents is lower. By using the entropic principle we can state that this solution is a better estimate of the resistance for a noncollinear magneticComment: 14 pages, 4 figures,Submitted to Physical Review

Different steady states for spin currents in noncollinear multilayers

We find there are at least two different steady states for transport across noncollinear magnetic multilayers. In the conventional one there is a discontinuity in the spin current across the interfaces which has been identified as the source of current induced magnetic reversal; in the one advocated herein the spin torque arises from the spin accumulation transverse to the magnetization of a magnetic layer. These two states have quite different attributes which should be discerned by current experiments.Comment: 8 pages, no figure. Accepted for publication in Journal of Physics: Condensed Matte

Electrical Resistivity of a Thin Metallic Film

The electrical resistivity of a pure sample of a thin metallic film is found to depend on the boundary conditions. This conclusion is supported by a free-electron model calculation and confirmed by an ab initio relativistic Korringa-Kohn-Rostoker computation. The low-temperature resistivity is found to be zero for a free-standing film (reflecting boundary conditions) but nonzero when the film is sandwiched between two semi-infinite samples of the same material (outgoing boundary conditions). In the latter case, this resistivity scales inversely with the number of monolayers and is due to the background diffusive scattering by a finite lattice.Comment: 20 pages. To be published in Physical Review B, December 15, 199

Quantifying gross vs. net agricultural land use change in Great Britain using the Integrated Administration and Control System

Land use change has impacts upon many natural processes, and is one of the key measures of anthropogenic disturbance on ecosystems. Agricultural land covers 70% of Great Britain's (GB) land surface and annually undergoes disturbance and change through farming practices such as crop rotation, ploughing and the planting and subsequent logging of forestry. It is important to quantify how much of GB's agricultural land undergoes such changes and what those changes are at an annual temporal resolution. Integrated Administration and Control System (IACS) data give annual snapshots of agricultural land use at the field level, allowing for high resolution spatiotemporal land use change studies at the national scale. Crucially, not only do the data allow for simple net change studies (total area change of a land use, in a specific areal unit) but also for gross change calculations (summation of all changes to and from a land use), meaning that both gains and losses to and from each land use category can be defined. In this study we analysed IACS data for GB from 2005 to 2013, and quantified gross change for over 90% of the agricultural area in GB for the first time. It was found that gross change totalled 63,500 km2 in GB compared to 20,600 km2 of net change, i.e. the real year-on-year change is, on average, three times larger than net change. This detailed information on nature of land use change allows for increased accuracy in modelling the impact of land use change on ecosystem processes and is directly applicable across EU member states, where collection of such survey data is a requirement. The modelled carbon flux associated with gross land use change was at times >100 Gg C y−1 larger than that based on net land use change for some land use transitions

Completing the FACE of elevated CO₂ research

We appraise the present geographical extent and inherent knowledge limits, following two decades of research on elevated CO2 responses in plant communities, and ask whether such research has answered the key question in quantifying the limits of compensatory CO2 uptake in the major biomes. Our synthesis of all ecosystem-scale (between 10 m2 and 3000 m2 total experimental plot area) elevated CO2 (eCO2) experiments in natural ecosystems conducted worldwide since 1987 (n = 151) demonstrates that the locations of these eCO2 experiments have been spatially biased, targeting primarily the temperate ecosystems of northern America and Europe. We consider the consequences, suggesting fundamentally that this limits the capacity of the research to understand how the world's major plant communities will respond to eCO2. Most notably, our synthesis shows that this research lacks understanding of impacts on tropical forests and boreal regions, which are potentially the most significant biomes for C sink and storage activity, respectively. Using a meta-analysis of the available data across all biomes, we show equivocal increases in net primary productivity (NPP) from eCO2 studies, suggesting that global validation is needed, especially in the most important biomes for C processing. Further, our meta-analysis identifies that few research programs have addressed eCO2 effects on below-ground C storage, such that at the global scale, no overall responses are discernable. Given the disparity highlighted in the distribution of eCO2 experiments globally, we suggest opportunities for newly-industrialized or developing nations to become involved in further research, particularly as these countries host some of the most important regions for tropical or sub-tropical forest systems. Modeling approaches that thus far have attempted to understand the biological response to eCO2 are constrained with respect to collective predictions, suggesting that further work is needed, which will link models to in situ eCO2 experiments, in order to understand how the world's most important regions for terrestrial C uptake and storage will respond to a future eCO2 atmosphere

Mapping soil moisture across the UK: assimilating cosmic-ray neutron sensors, remotely-sensed indices, rainfall radar and catchment water balance data in a Bayesian hierarchical model

Soil moisture is important in many hydrological and ecological processes. However, data sets which are currently available have issues with accuracy and resolution. To translate remotely-sensed data to an absolute measure of soil moisture requires mapped estimates of soil hydrological properties and estimates of vegetation properties, and this introduces considerable uncertainty. We present an alternative methodology for producing daily maps of soil moisture over the UK at 2-km resolution ("SMUK"). The method is based on a simple empirical model, calibrated with five years of daily data from cosmic-ray neutron sensors at ~40 sites across the country. The model is driven by precipitation, humidity, a remotely-sensed "soil water index" satellite product, and soil porosity. The model explains around 70 % of the variance in the daily observations. The spatial variation in the parameter describing the soil water retention (and thereby the response to precipitation) was estimated using daily water balance data from ~1200 catchments with good coverage across the country. The model parameters were estimated by Bayesian calibration using a Markov chain Monte Carlo method, so as to characterise the posterior uncertainty in the parameters and predictions. We found that the simple model could emulate the behaviour of a more complex process-based model. Given the high resolution of the inputs in time and space, the model can predict the very detailed variation in soil moisture which arises from the sporadic nature of precipitation events, including the small-scale and short-term variations associated with orographic and convective rainfall. Predictions over the period 2016 to 2023 demonstrated realistic patterns following the passage of weather fronts and prolonged droughts. The model has negligible computation time, and inputs and predictions are updated daily, lagging approximately one week behind real time

Severity scoring of manganese health effects for categorical regression

Characterizing the U-shaped exposure response relationship for manganese (Mn) is necessary for estimating the risk of adverse health from Mn toxicity due to excess or deficiency. Categorical regression has emerged as a powerful tool for exposure-response analysis because of its ability to synthesize relevant information across multiple studies and species into a single integrated analysis of all relevant data. This paper documents the development of a database on Mn toxicity designed to support the application of categorical regression techniques. Specifically, we describe (i) the conduct of a systematic search of the literature on Mn toxicity to gather data appropriate for dose-response assessment; (ii) the establishment of inclusion/exclusion criteria for data to be included in the categorical regression modeling database; (iii) the development of a categorical severity scoring matrix for Mn health effects to permit the inclusion of diverse health outcomes in a single categorical regression analysis using the severity score as the outcome variable; and (iv) the convening of an international expert panel to both review the severity scoring matrix and assign severity scores to health outcomes observed in studies (including case reports, epidemiological investigations, and in vivo experimental studies) selected for inclusion in the categorical regression database. Exposure information including route, concentration, duration, health endpoint(s), and characteristics of the exposed population was abstracted from included studies and stored in a computerized manganese database (MnDB), providing a comprehensive repository of exposure-response information with the ability to support categorical regression modeling of oral exposure data

Spin Hall Effect induced by resonant scattering on impurities in metals

The Spin Hall Effect (SHE) is a promising way for transforming charge currents into spin currents in spintronic devices. Large values of the Spin Hall Angle, the characteristic parameter of the yield of this transformation, have been recently found in noble metals doped with nonmagnetic impurities. We show that this can be explained by resonant scattering off impurity states split by the spin-orbit interaction. We apply our calculation to the interpretation of experiments on copper doped with 5d impurities and we describe the conditions to obtain the largest effects

Influenza A Virus Lacking the NS1 Gene Replicates in Interferon-Deficient Systems

AbstractThe NS1 protein is the only nonstructural protein encoded by influenza A virus. It has been proposed that the NS1 performs several regulatory functions during the viral replication cycle, including the regulation of synthesis, transport, splicing, and translation of mRNAs. Through the use of reverse genetics, a viable transfectant influenza A virus (delNS1) which lacks the NS1 gene has been generated. Our results indicate that the NS1 of influenza A virus is an auxiliary (virulence) factor which plays a crucial role in inhibiting interferon-mediated antiviral responses of the host