Carbon uptake rate calculated for melt pond water samples during POLARSTERN cruise ARK-XXVII/3 (IceArc) in 2012

Net Primary Production was measured using the 14**C uptake method with minor modifications. Melt pond samples were spiked with 0.1µCi ml**-1 of 14**C labelled sodium bicarbonate (Moravek Biochemicals, Brea, USA) and distributed in 10 clear bottles (20 ml each). Subsequently they were incubated for 12 h at -1.3°C under different scalar irradiances (0-420 µmol photons m**-2 s**-1) measured with a spherical sensor (Spherical Micro Quantum Sensor US-SQS/L, Heinz Walz, Effeltrich, Germany). At the end of the incubation, samples were filtered onto 0.2 µm nitrocellulose filters and the particulate radioactive carbon uptake was determined by liquid scintillation counting using Filter count scintillation cocktail (Perkin Elmer, Waltham, USA). The carbon uptake values in the dark were subtracted from the carbon uptake values measured in the light incubations. Dissolved inorganic carbon (DIC) was measured for each sample using the flow injection system (Hall and Aller, 1992). The DIC concentration was taken into account to calculate the amount of labeled bicarbonate incorporated into the cell. Carbon fixation rates were normalized volumetrically and by chlorophyll a. Photosynthesis-irradiance curves (PI curves) were fitted using MATLAB® according to the equation proposed by Platt et al. (1980) including a photoinhibition parameter (beta) and providing the main photosynthetic parameters: maximum Chla normalized carbon fixation rate if there were no photoinhibition (Pb) and the initial slope of the saturation curve (alpha). The derived parameters: light intensity at which photosynthesis is maximal (Im), the carbon fixation rate at that maximal irradiance (Pbm) and the adaptation parameter or photoacclimation index (Ik) were calculated according to Platt et al. (1982).

Integrated net primary production during POLARSTERN cruise ARK-XXVII/3 (IceArc) in 2012

Depth-integrated in situ rates were calculated for each environment as a function of the available photosynthetically active radiation (PAR). Irradiance profiles were calculated for each environment (sea ice, melt pond, water under the ice and open water) from the daily average incoming solar shortwave irradiance measured by a pyranometer (Kipp & Zonen, Delft, Netherland) mounted on the ship. We used light attenuation coefficients of 10 m**-1 for snow, 1.5 m**-1 for sea ice (Perovich, 1996) and 0.1 m**-1 for Atlantic-influenced Arctic seawater, based on literature values and observations during the cruise. Planar irradiance was transformed to scalar irradiance according to Ehn and Mundy (2013) and Katlein et al., (2014). Water column production was integrated over the euphotic zone (1% of incoming irradiance) and sea ice production over the ice core thickness. Melt pond coverage and sea ice concentration were taken into account when calculating the total primary production per area.

Carbon uptake rate calculated for CTD water samples during POLARSTERN cruise ARK-XXVII/3 (IceArc) in 2012

Net Primary Production was measured using the 14**C uptake method with minor modifications. Seawater samples were spiked with 0.1µCi ml**-1 of 14**C labelled sodium bicarbonate (Moravek Biochemicals, Brea, USA) and distributed in 10 clear bottles (20 ml each). Subsequently they were incubated for 12 h at -1.3°C under different scalar irradiances (0-420 µmol photons m**-2 s**-1) measured with a spherical sensor (Spherical Micro Quantum Sensor US-SQS/L, Heinz Walz, Effeltrich, Germany). At the end of the incubation, samples were filtered onto 0.2 µm nitrocellulose filters and the particulate radioactive carbon uptake was determined by liquid scintillation counting using Filter count scintillation cocktail (Perkin Elmer, Waltham, USA). The carbon uptake values in the dark were subtracted from the carbon uptake values measured in the light incubations. Dissolved inorganic carbon (DIC) was measured for each sample using the flow injection system (Hall and Aller, 1992). The DIC concentration was taken into account to calculate the amount of labeled bicarbonate incorporated into the cell. Carbon fixation rates were normalized volumetrically and by chlorophyll a. Photosynthesis-irradiance curves (PI curves) were fitted using MATLAB® according to the equation proposed by Platt et al. (1980) including a photoinhibition parameter (beta) and providing the main photosynthetic parameters: maximum Chla normalized carbon fixation rate if there were no photoinhibition (Pb) and the initial slope of the saturation curve (alpha). The derived parameters: light intensity at which photosynthesis is maximal (Im), the carbon fixation rate at that maximal irradiance (Pbm) and the adaptation parameter or photoacclimation index (Ik) were calculated according to Platt et al. (1982).

Carbon uptake rate calculated for sea-ice core samples during POLARSTERN cruise ARK-XXVII/3 (IceArc) in 2012

Net Primary Production was measured using the 14**C uptake method with minor modifications. Melted sea ice samples were spiked with 0.1µCi ml**-1 of 14**C labelled sodium bicarbonate (Moravek Biochemicals, Brea, USA) and distributed in 10 clear bottles (20 ml each). Subsequently they were incubated for 12 h at -1.3°C under different scalar irradiances (0-420 µmol photons m**-2 s**-1) measured with a spherical sensor (Spherical Micro Quantum Sensor US-SQS/L, Heinz Walz, Effeltrich, Germany). At the end of the incubation, samples were filtered onto 0.2 µm nitrocellulose filters and the particulate radioactive carbon uptake was determined by liquid scintillation counting using Filter count scintillation cocktail (Perkin Elmer, Waltham, USA). The carbon uptake values in the dark were subtracted from the carbon uptake values measured in the light incubations. Dissolved inorganic carbon (DIC) was measured for each sample using the flow injection system (Hall and Aller, 1992). The DIC concentration was taken into account to calculate the amount of labeled bicarbonate incorporated into the cell. Carbon fixation rates were normalized volumetrically and by chlorophyll a. Photosynthesis-irradiance curves (PI curves) were fitted using MATLAB® according to the equation proposed by Platt et al. (1980) including a photoinhibition parameter (beta) and providing the main photosynthetic parameters: maximum Chla normalized carbon fixation rate if there were no photoinhibition (Pb) and the initial slope of the saturation curve (alpha). The derived parameters: light intensity at which photosynthesis is maximal (Im), the carbon fixation rate at that maximal irradiance (Pbm) and the adaptation parameter or photoacclimation index (Ik) were calculated according to Platt et al. (1982).

The estimation of truncation error by tau-estimation revisited

The aim of this paper was to accurately estimate the local truncation error of partial differential equations, that are numerically solved using a finite difference or finite volume approach on structured and unstructured meshes. In this work, we approximated the local truncation error using the @t-estimation procedure, which aims to compare the residuals on a sequence of grids with different spacing. First, we focused the analysis on one-dimensional scalar linear and non-linear test cases to examine the accuracy of the estimation of the truncation error for both finite difference and finite volume approaches on different grid topologies. Then, we extended the analysis to two-dimensional problems: first on linear and non-linear scalar equations and finally on the Euler equations. We demonstrated that this approach yields a highly accurate estimation of the truncation error if some conditions are fulfilled. These conditions are related to the accuracy of the restriction operators, the choice of the boundary conditions, the distortion of the grids and the magnitude of the iteration error.

Relativistic description of 3He(e,e'p)2H

The relativistic distorted-wave impulse approximation is used to describe the 3He(e, e′ p)2H process. We describe the 3He nucleus within the adiabatic hyperspherical expansion method with realistic nucleon-nucleon interactions. The overlap between the 3He and the deuteron wave functions can be accurately computed from a three-body calculation. The nucleons are described by solutions of the Dirac equation with scalar and vector (S–V) potentials. The wave function of the outgoing proton is obtained by solving the Dirac equation with a S–V optical potential fitted to elastic proton scattering data on the residual nucleus. Within this theoretical framework, we compute the cross section of the reaction and other observables like the transverse-longitudinal asymmetry, and compare them with the available experimental data measured at JLab.

The correlation between white-matter microstructure and the complexity of spontaneous brain activity: A difussion tensor imaging-MEG study

The advent of new signal processing methods, such as non-linear analysis techniques, represents a new perspective which adds further value to brain signals' analysis. Particularly, Lempel–Ziv's Complexity (LZC) has proven to be useful in exploring the complexity of the brain electromagnetic activity. However, an important problem is the lack of knowledge about the physiological determinants of these measures. Although acorrelation between complexity and connectivity has been proposed, this hypothesis was never tested in vivo. Thus, the correlation between the microstructure of the anatomic connectivity and the functional complexity of the brain needs to be inspected. In this study we analyzed the correlation between LZC and fractional anisotropy (FA), a scalar quantity derived from diffusion tensors that is particularly useful as an estimate of the functional integrity of myelinated axonal fibers, in a group of sixteen healthy adults (all female, mean age 65.56 ± 6.06 years, intervals 58–82). Our results showed a positive correlation between FA and LZC scores in regions including clusters in the splenium of the corpus callosum, cingulum, parahipocampal regions and the sagittal stratum. This study supports the notion of a positive correlation between the functional complexity of the brain and the microstructure of its anatomical connectivity. Our investigation proved that a combination of neuroanatomical and neurophysiological techniques may shed some light on the underlying physiological determinants of brain's oscillations