Scaling and balancing carbon dioxide fluxes in a heterogeneous tundra ecosystem of the Lena River Delta

The current assessments of the carbon turnover in the Arctic tundra are subject to large uncertainties. This problem can (inter alia) be ascribed to both the general shortage of flux data from the vast and sparsely inhabited Arctic region, as well as the typically high spatiotemporal variability of carbon fluxes in tundra ecosystems. Addressing these challenges, carbon dioxide fluxes on an active flood plain situated in the Siberian Lena River Delta were studied during two growing seasons with the eddy covariance method. The footprint exhibited a heterogeneous surface, which generated mixed flux signals that could be partitioned in such a way that both respiratory loss and photosynthetic gain were obtained for each of two vegetation classes. This downscaling of the observed fluxes revealed a differing seasonality in the net uptake of bushes (−0.89 µmol m−2 s−1) and sedges (−0.38 µmol mm−2 s−1) in 2014. That discrepancy, which was concealed in the net signal, resulted from a comparatively warm spring in conjunction with an early snowmelt and a varying canopy structure. Thus, the representativeness of footprints may adversely be affected in response to prolonged unusual weather conditions. In 2015, when air temperatures on average corresponded to climatological means, both vegetation-class-specific flux rates were of similar magnitude (−0.69 µmol m−2 s−1). A comprehensive set of measures (e.g. phenocam) corroborated the reliability of the partitioned fluxes and hence confirmed the utility of flux decomposition for enhanced flux data analysis. This scrutiny encompassed insights into both the phenological dynamic of individual vegetation classes and their respective functional flux to flux driver relationships with the aid of ecophysiologically interpretable parameters. For comparison with other sites, the decomposed fluxes were employed in a vegetation class area-weighted upscaling that was based on a classified high-resolution orthomosaic of the flood plain. In this way, robust budgets that take the heterogeneous surface characteristics into account were estimated. In relation to the average sink strength of various Arctic flux sites, the flood plain constitutes a distinctly stronger carbon dioxide sink. Roughly 42 % of this net uptake, however, was on average offset by methane emissions lowering the sink strength for greenhouse gases. With growing concern about rising greenhouse gas emissions in high-latitude regions, providing robust carbon budgets from tundra ecosystems is critical in view of accelerating permafrost thaw, which can impact the global climate for centuries

Effect of dopants on thermal stability and self-diffusion in iron nitride thin films

We studied the effect of dopants (Al, Ti, Zr) on the thermal stability of iron nitride thin films prepared using a dc magnetron sputtering technique. Structure and magnetic characterization of deposited samples reveal that the thermal stability together with soft magnetic properties of iron nitride thin films get significantly improved with doping. To understand the observed results, detailed Fe and N self-diffusion measurements were performed. It was observed that N self-diffusion gets suppressed with Al doping whereas Ti or Zr doping results in somewhat faster N diffusion. On the other hand Fe self-diffusion seems to get suppressed with any dopant of which heat of nitride formation is significantly smaller than that of iron nitride. Importantly, it was observed that N self-diffusion plays only a trivial role, as compared to Fe self-diffusion, in affecting the thermal stability of iron nitride thin films. Based on the obtained results effect of dopants on self-diffusion process is discussed.Comment: 10 pages, 9 fig

Seasonal progression of active-layer thickness dependent on microrelief

Introduction Active-layer thickness is a major factor for all physical and biological processes in permafrost soils. It is closely related to the fluxes of energy, water and carbon between permafrost landscapes and the atmosphere. Active-layer thickness is mainly driven by air temperature, but also influenced by snow cover, summer rainfall, soil properties and vegetation characteristics (Nelson et al., 1998). The typical polygonal tundra of the Lena Delta is characterised by a pronounced microrelief, which causes a high small-scale heterogeneity of soil and vegetation properties. Consequently, also the active-layer thickness varies substantially across small lateral distances of decimetres to metres. In order to up-scale results of process studies to the landscape scale, a quantification of the heterogeneity of active-layer thickness is of great interest

Spin-polarized electron transport in ferromagnet/semiconductor heterostructures: Unification of ballistic and diffusive transport

A theory of spin-polarized electron transport in ferromagnet/semiconductor heterostructures, based on a unified semiclassical description of ballistic and diffusive transport in semiconductor structures, is developed. The aim is to provide a framework for studying the interplay of spin relaxation and transport mechanism in spintronic devices. A key element of the unified description of transport inside a (nondegenerate) semiconductor is the thermoballistic current consisting of electrons which move ballistically in the electric field arising from internal and external electrostatic potentials, and which are thermalized at randomly distributed equilibration points. The ballistic component in the unified description gives rise to discontinuities in the chemical potential at the boundaries of the semiconductor, which are related to the Sharvin interface conductance. By allowing spin relaxation to occur during the ballistic motion between the equilibration points, a thermoballistic spin-polarized current and density are constructed in terms of a spin transport function. An integral equation for this function is derived for arbitrary values of the momentum and spin relaxation lengths. For field-driven transport in a homogeneous semiconductor, the integral equation can be converted into a second-order differential equation that generalizes the standard spin drift-diffusion equation. The spin polarization in ferromagnet/semiconductor heterostructures is obtained by invoking continuity of the current spin polarization and matching the spin-resolved chemical potentials on the ferromagnet sides of the interfaces. Allowance is made for spin-selective interface resistances. Examples are considered which illustrate the effects of transport mechanism and electric field.Comment: 23 pages, 8 figures, REVTEX 4; minor corrections introduced; to appear in Phys. Rev.

Generalized Drude model: Unification of ballistic and diffusive electron transport

For electron transport in parallel-plane semiconducting structures, a model is developed that unifies ballistic and diffusive transport and thus generalizes the Drude model. The unified model is valid for arbitrary magnitude of the mean free path and arbitrary shape of the conduction band edge profile. Universal formulas are obtained for the current-voltage characteristic in the nondegenerate case and for the zero-bias conductance in the degenerate case, which describe in a transparent manner the interplay of ballistic and diffusive transport. The semiclassical approach is adopted, but quantum corrections allowing for tunneling are included. Examples are considered, in particular the case of chains of grains in polycrystalline or microcrystalline semiconductors with grain size comparable to, or smaller than, the mean free path. Substantial deviations of the results of the unified model from those of the ballistic thermionic-emission model and of the drift-diffusion model are found. The formulation of the model is one-dimensional, but it is argued that its results should not differ substantially from those of a fully three-dimensional treatment.Comment: 14 pages, 5 figures, REVTEX file, to appear in J. Phys.: Condens. Matte

Elucidating the structural composition of a Fe-N-C catalyst by nuclear and electron resonance techniques

Fe–N–C catalysts are very promising materials for fuel cells and metal–air batteries. This work gives fundamental insights into the structural composition of an Fe–N–C catalyst and highlights the importance of an in‐depth characterization. By nuclear‐ and electron‐resonance techniques, we are able to show that even after mild pyrolysis and acid leaching, the catalyst contains considerable fractions of α‐iron and, surprisingly, iron oxide. Our work makes it questionable to what extent FeN4 sites can be present in Fe–N–C catalysts prepared by pyrolysis at 900 °C and above. The simulation of the iron partial density of phonon states enables the identification of three FeN4 species in our catalyst, one of them comprising a sixfold coordination with end‐on bonded oxygen as one of the axial ligands

Dependence of interface conductivity on relevant physical parameters in polarized Fermi mixtures

We consider a mass-asymmetric polarized Fermi system in the presence of Hartree-Fock (HF) potentials. We concentrate on the BCS regime with various interaction strengths and numerically obtain the allowed values of the chemical and HF potentials, as well as the mass ratio. The functional dependence of the heat conductivity of the N-SF interface on relevant physical parameters, namely the temperature, the mass ratio, and the interaction strength, is obtained. In particular, we show that the interface conductivity starts to drop with decreasing temperature at the temperature, $T_{\text{m}}$, where the mean kinetic energy of the particles is just sufficient to overcome the SF gap. We obtain $T_{\text{m}}$ as a function of the mass ratio and the interaction strength. The variation of the heat conductivity, at fixed temperature, with the HF potentials and the imbalance chemical potential is also obtained. Finally, because the range of relevant temperatures increases for larger values of the mass ratio, we consider the $^6\text{Li}$-$^{40}\text{K}$ mixture separately by taking the temperature dependence of the pair potential into account.Comment: To appear in Physica C (2012

The novel mu-opioid antagonist, GSK1521498, reduces ethanol consumption in C57BL/6J mice.

RATIONALE Using the drinking-in-the-dark (DID) model, we compared the effects of a novel mu-opioid receptor antagonist, GSK1521498, with naltrexone, a licensed treatment of alcohol dependence, on ethanol consumption in mice. OBJECTIVE We test the ability of GSK1521498 to reduce alcohol consumption and compare its intrinsic efficacy to that of naltrexone by comparing the two drugs at doses matched for equivalent receptor occupancy. METHODS Thirty-six C57BL/6J mice were tested in a DID procedure. In 2-day cycles, animals experienced one baseline, injection-free session, and one test session when they received two injections, one of test drug and one placebo. All animals received GSK1521498 (0, 0.1, 1 and 3 mg/kg, i.p., 30 min pre-treatment) and naltrexone (0, 0.1, 1 and 3 mg/kg, s.c. 10 min pre-treatment) in a cross-over design. Receptor occupancies following the same doses were determined ex vivo in separate groups by autoradiography, using [3H]DAMGO. Binding in the region of interest was measured integrally by computer-assisted microdensitometry and corrected for non-specific binding. RESULTS Both GSK1521498 and naltrexone dose-dependently decreased ethanol consumption. When drug doses were matched for 70-75 % receptor occupancy, GSK1521498 3 mg/kg, i.p., caused a 2.5-fold greater reduction in alcohol consumption than naltrexone 0.1 mg/kg, s.c. Both GSK1521498 and naltrexone significantly reduced sucrose consumption at a dose of 1 mg/kg but not 0.1 mg/kg. In a test of conditioned taste aversion, GSK1521498 (3 mg/kg) reduced sucrose consumption 24 h following exposure to a conditioning injection. CONCLUSIONS Both opioid receptor antagonists reduced alcohol consumption but GK1521498 has higher intrinsic efficacy than naltrexone

Synthesis and Optimization of Reversible Circuits - A Survey

Reversible logic circuits have been historically motivated by theoretical research in low-power electronics as well as practical improvement of bit-manipulation transforms in cryptography and computer graphics. Recently, reversible circuits have attracted interest as components of quantum algorithms, as well as in photonic and nano-computing technologies where some switching devices offer no signal gain. Research in generating reversible logic distinguishes between circuit synthesis, post-synthesis optimization, and technology mapping. In this survey, we review algorithmic paradigms --- search-based, cycle-based, transformation-based, and BDD-based --- as well as specific algorithms for reversible synthesis, both exact and heuristic. We conclude the survey by outlining key open challenges in synthesis of reversible and quantum logic, as well as most common misconceptions.Comment: 34 pages, 15 figures, 2 table