Computational and Mathematical Modelling of the EGF Receptor System

This chapter gives an overview of computational and mathematical modelling of the EGF receptor system. It begins with a survey of motivations for producing such models, then describes the main approaches that are taken to carrying out such modelling, viz. differential equations and individual-based modelling. Finally, a number of projects that applying modelling and simulation techniques to various aspects of the EGF receptor system are described

A xandarellid artiopodan from Morocco – a middle Cambrian link between soft-bodied euarthropod communities in North Africa and South China

NB. A corrigendum [correction] for this article was published online on 09 May 2017; this has been attached to this article as an additional file. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ © The Author(s) 2017. The attached file is the published version of the article

Estimating fine-root production by tree species and understorey functional groups in two contrasting peatland forests

Background and aims Estimation of root-mediated carbon fluxes in forested peatlands is needed for understanding ecosystem functioning and supporting greenhouse gas inventories. Here, we aim to determine the optimal methodology for utilizing ingrowth cores in estimating annual fine-root production (FRP) and its vertical distribution in trees, shrubs and herbs. Methods We used 3-year data obtained with modified ingrowth core method and tested two calculation methods: 'ingrowth-dividing' and `ingrowth-subtracting'. Results The ingrowth-dividing method combined with a 2-year incubation of ingrowth cores can be used for the 'best estimate' of FRP. The FRP in the nutrient-rich fen forest (561 g m(-2)) was more than twice that in the nutrient-poor bog forest (244 g m(-2)). Most FRP occurred in the top 20-cm layer (76-82 %). Tree FRP accounted for 71 % of total FRP in the bog and 94 % in the fen forests, respectively, following the aboveground vegetation patterns; however, in fen forest the proportions of spruce and birch in FRP were higher than their proportions in stand basal area. Conclusions Our methodology may be used to study peatland FRP patterns more widely and will reduce the volume of labour-intensive work, but will benefit from verification with other methods, as is the case in all in situ FRP studies.Peer reviewe

Does the age of fine root carbon indicate the age of fine roots in boreal forests?

To test the reliability of the radiocarbon method for determining root age, we analyzed fine roots (originating from the years 1985 to 1993) from ingrowth cores with known maximum root age (1 to 6 years old). For this purpose, three Scots pine (Pinus sylvestris L.) stands were selected from boreal forests in Finland. We analyzed root 14C age by the radiocarbon method and compared it with the above-mentioned known maximum fine root age. In general, ages determined by the two methods (root 14C age and ingrowth core root maximum age) were in agreement with each other for roots of small diameter (<0.5mm). By contrast, in most of the samples of fine roots of larger diameter (1.5-2mm), the 14C age of root samples of 1987-89 exceeded the ingrowth core root maximum age by 1-10 years. This shows that these roots had received a large amount of older stored carbon from unknown sources in addition to atmospheric CO2 directly from photosynthesis. We conclude that the 14C signature of fine roots, especially those of larger diameter, may not always be indicative of root age, and that further studies are needed concerning the extent of possible root uptake of older carbon and its residence time in roots. Keywords: fine root age, Pinus sylvestris, radiocarbon, root carbon, ingrowth cores, tree ringPeer reviewe

Pattern Recognition in a Bimodal Aquifer Using the Normal-Score Ensemble Kalman Filter

The ensemble Kalman filter (EnKF) is now widely used in diverse disciplines to estimate model parameters and update model states by integrating observed data. The EnKF is known to perform optimally only for multi-Gaussian distributed states and parameters. A new approach, the normal-score EnKF (NS-EnKF), has been recently proposed to handle complex aquifers with non-Gaussian distributed parameters. In this work, we aim at investigating the capacity of the NS-EnKF to identify patterns in the spatial distribution of the model parameters (hydraulic conductivities) by assimilating dynamic observations in the absence of direct measurements of the parameters themselves. In some situations, hydraulic conductivity measurements (hard data) may not be available, which requires the estimation of conductivities from indirect observations, such as piezometric heads. We show how the NS-EnKF is capable of retrieving the bimodal nature of a synthetic aquifer solely from piezometric head data. By comparison with a more standard implementation of the EnKF, the NS-EnKF gives better results with regard to histogram preservation, uncertainty assessment, and transport predictions. © 2011 International Association for Mathematical Geosciences.The authors gratefully acknowledge the financial support by the Spanish Ministry of Science and Innovation through project CGL2011-23295. The first author appreciates the financial aid from China Scholarship Council (CSC No. [2007]3020).Zhou, H.; Li, L.; Hendricks Franssen, H.; Gómez-Hernández, JJ. (2012). Pattern Recognition in a Bimodal Aquifer Using the Normal-Score Ensemble Kalman Filter. Mathematical Geosciences. 44(2):169-185. https://doi.org/10.1007/s11004-011-9372-3S169185442Arulampalam MS, Maskell S, Gordon N, Clapp T (2002) A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans Signal Process 50(2):174–188Bertino L, Evensen G, Wackernagel H (2003) Sequential data assimilation techniques in oceanography. Int Stat Rev 71(2):223–241Burgers G, Jan van Leeuwen P, Evensen G (1998) Analysis scheme in the ensemble Kalman filter. Mon Weather Rev 126(6):1719–1724Carrera J, Neuman SP (1986b) Estimation of aquifer parameters under transient and steady state conditions: 2. Uniqueness, stability, and solution algorithms. Water Resour Res 22(2):211–227Chen Y, Zhang D (2006) Data assimilation for transient flow in geologic formations via ensemble Kalman filter. Adv Water Resour 29:1107–1122Delhomme JP (1979) Spatial variability and uncertainty in groundwater flow parameters: a geostatistical approach. Water Resour Res 15(2):269–280Evensen G (1994) Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J Geophys Res 99(C5):10143–10162Evensen G (2007) Data assimilation: the ensemble Kalman filter. Springer, Berlin, 279 ppFernàndez-Garcia D, Illangasekare T, Rajaram H (2005) Differences in the scale dependence of dispersivity and retardation factors estimated from forced-gradient and uniform flow tracer tests in three-dimensional physically and chemically heterogeneous porous media. Water Resour Res 41(3):W03012Gómez-Hernández JJ, Journel AG (1993) Joint sequential simulation of multi-Gaussian fields. In: Soares A (ed) Geostatistics Tróia ’92, vol 1. Kluwer Academic, Dordrecht, pp 85–94Gómez-Hernández JJ, Wen XH (1998) To be or not to be multi-Gaussian? A reflection on stochastic hydrogeology. Adv Water Resour 21(1):47–61Gu Y, Oliver DS (2006) The ensemble Kalman filter for continuous updating of reservoir simulation models. J Energy Resour Technol 128:79–87Harbaugh AW, Banta ER, Hill MC, McDonald MG (2000) MODFLOW-2000, the U.S. geological survey modular ground-water model—user guide to modularization concepts and the ground-water flow process. Tech rep. Open-File Report 00-92, U.S. Department of the Interior, U.S. Geological Survey. Reston, Virginia, 121 ppHendricks Franssen HJ, Kinzelbach W (2008) Real-time groundwater flow modeling with the Ensemble Kalman Filter: joint estimation for states and parameters and the filter inbreeding problem. Water Resour Res 44:W09408Hendricks Franssen HJ, Kinzelbach W (2009) Ensemble Kalman filtering versus sequential self-calibration for inverse modelling of dynamic groundwater flow systems. J Hydrol 365(3–4):261–274Houtekamer PL, Mitchell HL (2001) A sequential ensemble Kalman filter for atmospheric data assimilation. Mon Weather Rev 129:123–137Journel AG, Deutsch CV (1993) Entropy and spatial disorder. Math Geol 25(3):329–355Li L, Zhou H, Gómez-Hernández JJ (2011a) A comparative study of three-dimensional hydraulic conductivity upscaling at the macrodispersion experiment (MADE) site, Columbus air force base, Mississippi (USA). J Hydrol 404(3–4):278–293Li L, Zhou H, Gómez-Hernández JJ (2011b) Transport upscaling using multi-rate mass transfer in three-dimensional highly heterogeneous porous media. Adv Water Resour 34(4):478–489Moradkhani H, Sorooshian S, Gupta HV, Houser PR (2005) Dual state-parameter estimation of hydrological models using ensemble Kalman filter. Adv Water Resour 28:135–147Naevdal G, Johnsen L, Aanonsen S, Vefring E (Mar. 2005) Reservoir monitoring and continuous model updating using ensemble Kalman filter. SPE J 10(1):66–74Pardo-Igúzquiza E, Dowd PA (2003) CONNEC3D: a computer program for connectivity analysis of 3D random set models. Comput Geosci 29:775–785Schöniger A, Nowak W, Hendricks Franssen HJ (2011) Parameter estimation by ensemble Kalman filters with transformed data: approach and application to hydraulic tomography. Water Resour Res (submitted)Simon E, Bertino L (2009) Application of the Gaussian anamorphosis to assimilation in a 3-D coupled physical-ecosystem model of the North Atlantic with the EnKF: a twin experiment. Ocean Sci 5:495–510Stauffer D, Aharony A (1994) Introduction to percolation theory. Taylor and Francis, London. 181 ppStrébelle S 2000. Sequential simulation drawing structures from training images. PhD thesis, Stanford University. 187 ppStrebelle S (2002) Conditional simulation of complex geological structures using multiple-point statistics. Math Geol 34(1):1–21Wen X, Chen W (2006) Real-time reservoir model updating using ensemble Kalman filter: the confirming approach. SPE J 11(4):431–442Wen X, Chen W (2007) Some practical issues on real time reservoir updating using ensemble Kalman filter. SPE J 12(2):156–166Zhou H, Gómez-Hernández JJ, Hendricks Franssen H-J, Li L (2011) An approach to handling non-gaussianity of parameters and state variables in ensemble Kalman filtering. Adv Water Resour 34(7):844–864Zinn B, Harvey C (2003) When good statistical models of aquifer heterogeneity go bad: a comparison of flow, dispersion, and mass transfer in connected and multivariate Gaussian hydraulic conductivity fields. Water Resour Res 39(3):105

Fine-root turnover rates of European forests revisited: an analysis of data from sequential coring and ingrowth cores

Background and Aims Forest trees directly contribute to carbon cycling in forest soils through the turnover of their fine roots. In this study we aimed to calculate root turnover rates of common European forest tree species and to compare them with most frequently published values. Methods We compiled available European data and applied various turnover rate calculation methods to the resulting database. We used Decision Matrix and Maximum-Minimum formula as suggested in the literature. Results Mean turnover rates obtained by the combination of sequential coring and Decision Matrix were 0.86 yr−1 for Fagus sylvatica and 0.88 yr−1 for Picea abies when maximum biomass data were used for the calculation, and 1.11 yr−1 for both species when mean biomass data were used. Using mean biomass rather than maximum resulted in about 30 % higher values of root turnover. Using the Decision Matrix to calculate turnover rate doubled the rates when compared to the Maximum-Minimum formula. The Decision Matrix, however, makes use of more input information than the Maximum-Minimum formula. Conclusions We propose that calculations using the Decision Matrix with mean biomass give the most reliable estimates of root turnover rates in European forests and should preferentially be used in models and C reporting

Modern Clinical Research on LSD

All modern clinical studies using the classic hallucinogen lysergic acid diethylamide (LSD) in healthy subjects or patients in the last 25 years are reviewed herein. There were five recent studies in healthy participants and one in patients. In a controlled setting, LSD acutely induced bliss, audiovisual synesthesia, altered meaning of perceptions, derealization, depersonalization, and mystical experiences. These subjective effects of LSD were mediated by the 5-HT2A receptor. LSD increased feelings of closeness to others, openness, trust, and suggestibility. LSD impaired the recognition of sad and fearful faces, reduced left amygdala reactivity to fearful faces, and enhanced emotional empathy. LSD increased the emotional response to music and the meaning of music. LSD acutely produced deficits in sensorimotor gating, similar to observations in schizophrenia. LSD had weak autonomic stimulant effects and elevated plasma cortisol, prolactin, and oxytocin levels. Resting-state functional magnetic resonance studies showed that LSD acutely reduced the integrity of functional brain networks and increased connectivity between networks that normally are more dissociated. LSD increased functional thalamocortical connectivity and functional connectivity of the primary visual cortex with other brain areas. The latter effect was correlated with subjective hallucinations. LSD acutely induced global increases in brain entropy that were associated with greater trait openness 14 days later. In patients with anxiety associated with life-threatening disease, anxiety was reduced for 2 months after two doses of LSD. In medical settings, no complications of LSD administration were observed. These data should contribute to further investigations of the therapeutic potential of LSD in psychiatry

Training, Match and Non-Rugby Activities in Elite Male Youth Rugby Union Players in England

Rugby union is a late specialisation sport. As a consequence, youth players may still be engaged in other activities and sports throughout the year as they transition to rugby specialisation. Limited research exists quantifying rugby union training and matches as well as engagement in other activities and sports. Therefore, the aim of this study was to quantify and compare rugby union training, matches and other activities of elite youth U15 and U16 rugby union players at different stages of the season

Efferent Control of the Electrical and Mechanical Properties of Hair Cells in the Bullfrog's Sacculus

Background: Hair cells in the auditory, vestibular, and lateral-line systems respond to mechanical stimulation and transmit information to afferent nerve fibers. The sensitivity of mechanoelectrical transduction is modulated by the efferent pathway, whose activity usually reduces the responsiveness of hair cells. The basis of this effect remains unknown. Methodology and Principal Findings: We employed immunocytological, electrophysiological, and micromechanical approaches to characterize the anatomy of efferent innervation and the effect of efferent activity on the electrical and mechanical properties of hair cells in the bullfrog’s sacculus. We found that efferent fibers form extensive synaptic terminals on all macular and extramacular hair cells. Macular hair cells expressing the Ca 2+-buffering protein calretinin contain half as many synaptic ribbons and are innervated by twice as many efferent terminals as calretinin-negative hair cells. Efferent activity elicits inhibitory postsynaptic potentials in hair cells and thus inhibits their electrical resonance. In hair cells that exhibit spiking activity, efferent stimulation suppresses the generation of action potentials. Finally, efferent activity triggers a displacement of the hair bundle’s resting position. Conclusions and Significance: The hair cells of the bullfrog’s sacculus receive a rich efferent innervation with the heaviest projection to calretinin-containing cells. Stimulation of efferent axons desensitizes the hair cells and suppresses their spiking activity. Although efferent activation influences mechanoelectrical transduction, the mechanical effects on hair bundles ar