Simulating microbial degradation of organic matter in a simple porous system using the 3-D diffusion-based model MOSAIC

This paper deals with the simulation of microbial degradation of organic matter in soil within the pore space at a microscopic scale. Pore space was analysed with micro-computed tomography and described using a sphere network coming from a geometrical modelling algorithm. The biological model was improved regarding previous work in order to include the transformation of dissolved organic compounds and diffusion processes. We tested our model using experimental results of a simple substrate decomposition experiment (fructose) within a simple medium (sand) in the presence of different bacterial strains. Separate incubations were carried out in microcosms using five different bacterial communities at two different water potentials of −10 and −100 cm of water. We calibrated the biological parameters by means of experimental data obtained at high water content, and we tested the model without changing any parameters at low water content. Same as for the experimental data, our simulation results showed that the decrease in water content caused a decrease of mineralization rate. The model was able to simulate the decrease of connectivity between substrate and microorganism due the decrease of water content

Distances and classification of amino acids for different protein secondary structures

Window profiles of amino acids in protein sequences are taken as a description of the amino acid environment. The relative entropy or Kullback-Leibler distance derived from profiles is used as a measure of dissimilarity for comparison of amino acids and secondary structure conformations. Distance matrices of amino acid pairs at different conformations are obtained, which display a non-negligible dependence of amino acid similarity on conformations. Based on the conformation specific distances clustering analysis for amino acids is conducted.Comment: 15 pages, 8 figure

A variational approach for retrieving ice cloud properties from infrared measurements: application in the context of two IIR validation campaigns

Cirrus are cloud types that are recognized to have a strong impact on the Earth-atmosphere radiation balance. This impact is however still poorly understood, due to the difficulties in describing the large variability of their properties in global climate models. Consequently, numerous airborne and space borne missions have been dedicated to their study in the last decades. The satellite constellation A-Train has proven to be particularly helpful to study cirrus on global scale due to such instruments as the Infrared Imaging Radiometer (IIR), which shows great sensitivity to the radiative and microphysical properties of these clouds. This study presents an algorithm that uses thermal infrared measurements to retrieve the optical thickness of cirrus and the effective size of their ice crystals. This algorithm is based on an optimal estimation scheme, which possesses the advantage of attributing precise uncertainties to the retrieved parameters. Two IIR airborne validation campaigns have been chosen as case studies. It is observed that optical thicknesses could be accurately retrieved but that large uncertainties may occur on the effective diameters. Strong agreements have been found between the products of our algorithm when separately applied to the measurements of IIR and of the airborne radiometer CLIMAT-AV, which comforts the results of previous validations of IIR level-1 measurements. Comparisons with in situ observations and with operational products of IIR also show confidence in our results. However, we have found that the quality of our retrievals can be strongly impacted by uncertainties related to the choice of a pristine crystal model and by poor constraints on the properties of possible liquid cloud layers underneath cirrus. Simultaneous retrievals of liquid clouds radiative and microphysical properties or the use of different ice crystal models should therefore be considered to improve the quality of the results

Shear coordinate description of the quantised versal unfolding of D_4 singularity

In this paper by using Teichmuller theory of a sphere with four holes/orbifold points, we obtain a system of flat coordinates on the general affine cubic surface having a D_4 singularity at the origin. We show that the Goldman bracket on the geodesic functions on the four-holed/orbifold sphere coincides with the Etingof-Ginzburg Poisson bracket on the affine D_4 cubic. We prove that this bracket is the image under the Riemann-Hilbert map of the Poisson Lie bracket on the direct sum of three copies of sl_2. We realise the action of the mapping class group by the action of the braid group on the geodesic functions . This action coincides with the procedure of analytic continuation of solutions of the sixth Painlev\'e equation. Finally, we produce the explicit quantisation of the Goldman bracket on the geodesic functions on the four-holed/orbifold sphere and of the braid group action.Comment: 14 pages, 2 picture

Fluctuation theorems for harmonic oscillators

We study experimentally the thermal fluctuations of energy input and dissipation in a harmonic oscillator driven out of equilibrium, and search for Fluctuation Relations. We study transient evolution from the equilibrium state, together with non equilibrium steady states. Fluctuations Relations are obtained experimentally for both the work and the heat, for the stationary and transient evolutions. A Stationary State Fluctuation Theorem is verified for the two time prescriptions of the torque. But a Transient Fluctuation Theorem is satisfied for the work given to the system but not for the heat dissipated by the system in the case of linear forcing. Experimental observations on the statistical and dynamical properties of the fluctuation of the angle, we derive analytical expressions for the probability density function of the work and the heat. We obtain for the first time an analytic expression of the probability density function of the heat. Agreement between experiments and our modeling is excellent

Chronic Stress and Ovarian Function in Female Childhood Cancer Survivors

Objectives: To explore the relationships among perceived stress, biomarkers of hypothalamic–pituitary–adrenal (HPA) activity, gonadotropin levels, and anti-Müllerian hormone (AMH) in female childhood cancer survivors (CCSs). Sample & Setting: 24 female CCSs from the Royal Hospital for Sick Children in Edinburgh, Scotland, were included in the study. Methods & Variables: Perceived stress was measured using the Perceived Stress Scale. HPA activity was measured using salivary cortisol and hair cortisol. Ovarian function was measured using serum gonadotropin levels and serum AMH levels. Latent growth curve modeling was used to determine diurnal cortisol slope and intercept. Bayesian structural equation modeling was used to explore the relationship among perceived stress, biomarkers of HPA activity, and ovarian function. Results: The authors found an inverse association between perceived stress and ovarian function and a positive association between biomarkers of HPA activity and ovarian function. Implications for Nursing: Further research is needed to understand factors contributing to risk for post-treatment reproductive dysfunction in female CCSs