Estimating Oceanic Export Production based on 3D coupled physical-biogeochemical modelling

The study addresses various aspects of model-based estimating the oceanic primary production. In particular, we consider existent interpretations of the export fluxes; influence of implied conversions between modelled chlorophyll and biomass, expressed in nitrogen and/or carbon units, and, therefore, impact of decoupling the biogeochemical (N, C) cycles and chlorophyll. The export production is estimated by simulating global ocean biolgeochemical dynamics with the CN regulated model (REcoM) developed by Schartau et al. (2007) and coupled with the MITgcm. The model describes carbon (C) and nitrogen (N) fluxes between components of the ocean ecosystem. The nitrogen and carbon cycles as well as phytoplankton chlorophyll (Chl) dynamics are decoupled in accordance with the dynamic regulatory phytoplanktonic acclimation model sugested by Geider et al. (1998). Sensitivity of the primary production estimates to biological model parameters is also discussed

Drawing Binary Tanglegrams: An Experimental Evaluation

A binary tanglegram is a pair of binary trees whose leaf sets are in one-to-one correspondence; matching leaves are connected by inter-tree edges. For applications, for example in phylogenetics or software engineering, it is required that the individual trees are drawn crossing-free. A natural optimization problem, denoted tanglegram layout problem, is thus to minimize the number of crossings between inter-tree edges. The tanglegram layout problem is NP-hard and is currently considered both in application domains and theory. In this paper we present an experimental comparison of a recursive algorithm of Buchin et al., our variant of their algorithm, the algorithm hierarchy sort of Holten and van Wijk, and an integer quadratic program that yields optimal solutions.Comment: see http://www.siam.org/proceedings/alenex/2009/alx09_011_nollenburgm.pd

A study of glacial–interglacial variations of the marine stable carbon isotope record using a non-Redfield biogeochemical model

We investigate glacial–interglacial variations in the marine stable carbon-isotope record applying the marine ecosystem and biogeochemistry model RECOM, which is forced with model output from fully coupled climate simulations. Different to most other marine biogeochemistry models, RECOM does not rely on fixed stoichiomet- ric ratios of phytoplankton organic matter. Instead, the composition of phytoplankton organic matter is calculated as a response to light, temperature and nutrient supply, which allows for assessing potential stoichiometric shifts between the past and present. We consider carbon-isotopic fractionation of marine phytoplankton during photosynthesis, studying different biogenic fractionation parametrisations and their influence on model–data comparisons for the Last Glacial Maximum and the Holocene

A large-scale evaluation framework for EEG deep learning architectures

EEG is the most common signal source for noninvasive BCI applications. For such applications, the EEG signal needs to be decoded and translated into appropriate actions. A recently emerging EEG decoding approach is deep learning with Convolutional or Recurrent Neural Networks (CNNs, RNNs) with many different architectures already published. Here we present a novel framework for the large-scale evaluation of different deep-learning architectures on different EEG datasets. This framework comprises (i) a collection of EEG datasets currently including 100 examples (recording sessions) from six different classification problems, (ii) a collection of different EEG decoding algorithms, and (iii) a wrapper linking the decoders to the data as well as handling structured documentation of all settings and (hyper-) parameters and statistics, designed to ensure transparency and reproducibility. As an applications example we used our framework by comparing three publicly available CNN architectures: the Braindecode Deep4 ConvNet, Braindecode Shallow ConvNet, and two versions of EEGNet. We also show how our framework can be used to study similarities and differences in the performance of different decoding methods across tasks. We argue that the deep learning EEG framework as described here could help to tap the full potential of deep learning for BCI applications.Comment: 7 pages, 3 figures, final version accepted for presentation at IEEE SMC 2018 conferenc

Exploring glacial–interglacial variations of the marine carbon isotope record with RECOM-ciso

We explore the impact of glacial–interglacial climate variations on the marine carbon-isotope record by means of the sophisticated marine biogeochemistry model RECOM. Different to most other marine carbon cycle models, RECOM does not rely on fixed Redfield ratios for organic soft tissue. Instead, the ratios of C:N and C:Chl in phytoplankton are calculated as a response to light, temperature and nutrient supply, which allows for assessing potential shifts in marine autotroph stochiometry. Our sensitivity studies feature a recently developed model version equipped with carbon isotopes (RECOM-ciso) forced with model output from fully coupled climate simulations

Different activation energies in glucose uptake in Saccharomyces cerevisiae DFY1 suggest two transport systems

AbstractThe analysis of initial glucose uptake in Saccharomyces cerevisiae at 25°, 20°, 15° and 10°C by computer-assisted nonlinear regression analysis predicts two transport systems. The first demonstrates Michaelis–Menten kinetics and the second shows first order behaviour. The activation energies of these two systems were calculated by the Arrhenius equation at four different growth phases, namely early exponential (EE), middle exponential (ME2), late exponential (LE) and early stationary (ES) with 2% glucose in the batch medium. The activation energies calculated from the Vm values in EE, ME, LE and ES growth phases were 15.8±1.7, 13.5±1.0, 15.1±0.8 and 13.5±0.7 kcal/mol. These values are in agreement with activation energies calculated for the first mechanism, facilitated diffusion, which is the mechanism deduced from countertransport experiments. The activation energies derived for the second transport system from the first order rate constants in cells grown to EE, ME2, LE and ES were 8.0±2.1, 8.1±1.3, 9.6±3.0 and 7.5±2.6 kcal/mol. These values are still significantly higher than for free diffusion of glucose in water and lower as predicted for passage of glucose through the lipid phase. Therefore, we assume in addition to carrier-mediated facilitated diffusion the entrance of glucose into the cell through a pore