Vicious and Virtuous Cycles and the Role of External Non-government Actors in Community Forestry in Oaxaca and Michoacán, Mexico

Community forestry offers potential for socioeconomic benefits while maintaining ecosystem services. In Mexico, government and donor efforts to develop this sector focus on issues within forest communities. Often overlooked are effects of external non-government actors (NGOs and foresters) as links or barriers between communities and funding, capacity building, and technical support. To analyze the role of these actors, I analyze household survey and interview data from 11 communities with varying levels of vertical integration of forestry production in states with divergent records of community forestry, Oaxaca and Michoacán. Results suggest that strong community governance is necessary but not sufficient for vertical integration, and strong interactions with non-government actors are critical. These actors, operating within the existing framework of government regulations, have a range of incentives for engaging communities. Availability of these actors motivated by concern for community capacity instead of timber income may be a determinant of community forestry development

The Mitochondrial Ca(2+) Uniporter: Structure, Function, and Pharmacology.

Mitochondrial Ca(2+) uptake is crucial for an array of cellular functions while an imbalance can elicit cell death. In this chapter, we briefly reviewed the various modes of mitochondrial Ca(2+) uptake and our current understanding of mitochondrial Ca(2+) homeostasis in regards to cell physiology and pathophysiology. Further, this chapter focuses on the molecular identities, intracellular regulators as well as the pharmacology of mitochondrial Ca(2+) uniporter complex

Short Term Synaptic Depression Imposes a Frequency Dependent Filter on Synaptic Information Transfer

Depletion of synaptic neurotransmitter vesicles induces a form of short term depression in synapses throughout the nervous system. This plasticity affects how synapses filter presynaptic spike trains. The filtering properties of short term depression are often studied using a deterministic synapse model that predicts the mean synaptic response to a presynaptic spike train, but ignores variability introduced by the probabilistic nature of vesicle release and stochasticity in synaptic recovery time. We show that this additional variability has important consequences for the synaptic filtering of presynaptic information. In particular, a synapse model with stochastic vesicle dynamics suppresses information encoded at lower frequencies more than information encoded at higher frequencies, while a model that ignores this stochasticity transfers information encoded at any frequency equally well. This distinction between the two models persists even when large numbers of synaptic contacts are considered. Our study provides strong evidence that the stochastic nature neurotransmitter vesicle dynamics must be considered when analyzing the information flow across a synapse

From Spiking Neuron Models to Linear-Nonlinear Models

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates

Eupraxia, a step toward a plasma-wakefield based accelerator with high beam quality

The EuPRAXIA project aims at designing the world's first accelerator based on advanced plasma-wakefield techniques to deliver 5 GeV electron beams that simultaneously have high charge, low emittance and low energy spread, which are required for applications by future user communities. Meeting this challenging objective will only be possible through dedicated effort. Many injection/acceleration schemes and techniques have been explored by means of thorough simulations in more than ten European research institutes. This enables selection of the most appropriate methods for solving each particular problem. The specific challenge of generating, extracting and transporting high charge beams, while maintaining the high quality needed for user applications, are being tackled using innovative approaches. This article highlights preliminary results obtained by the EuPRAXIA collaboration, which also exhibit the required laser and plasma parameters

How Noisy Adaptation of Neurons Shapes Interspike Interval Histograms and Correlations

Channel noise is the dominant intrinsic noise source of neurons causing variability in the timing of action potentials and interspike intervals (ISI). Slow adaptation currents are observed in many cells and strongly shape response properties of neurons. These currents are mediated by finite populations of ionic channels and may thus carry a substantial noise component. Here we study the effect of such adaptation noise on the ISI statistics of an integrate-and-fire model neuron by means of analytical techniques and extensive numerical simulations. We contrast this stochastic adaptation with the commonly studied case of a fast fluctuating current noise and a deterministic adaptation current (corresponding to an infinite population of adaptation channels). We derive analytical approximations for the ISI density and ISI serial correlation coefficient for both cases. For fast fluctuations and deterministic adaptation, the ISI density is well approximated by an inverse Gaussian (IG) and the ISI correlations are negative. In marked contrast, for stochastic adaptation, the density is more peaked and has a heavier tail than an IG density and the serial correlations are positive. A numerical study of the mixed case where both fast fluctuations and adaptation channel noise are present reveals a smooth transition between the analytically tractable limiting cases. Our conclusions are furthermore supported by numerical simulations of a biophysically more realistic Hodgkin-Huxley type model. Our results could be used to infer the dominant source of noise in neurons from their ISI statistics

Emission of volatile halogenated compounds, speciation and localization of bromine and iodine in the brown algal genome model Ectocarpus siliculosus

This study explores key features of bromine and iodine metabolism in the filamentous brown alga and genomics model Ectocarpus siliculosus. Both elements are accumulated in Ectocarpus, albeit at much lower concentration factors (2-3 orders of magnitude for iodine, and < 1 order of magnitude for bromine) than e.g. in the kelp Laminaria digitata. Iodide competitively reduces the accumulation of bromide. Both iodide and bromide are accumulated in the cell wall (apoplast) of Ectocarpus, with minor amounts of bromine also detectable in the cytosol. Ectocarpus emits a range of volatile halogenated compounds, the most prominent of which by far is methyl iodide. Interestingly, biosynthesis of this compound cannot be accounted for by vanadium haloperoxidase since the latter have not been found to catalyze direct halogenation of an unactivated methyl group or hydrocarbon so a methyl halide transferase-type production mechanism is proposed

Status of the Horizon 2020 EuPRAXIA conceptual design study

The Horizon 2020 project EuPRAXIA (European Plasma Research Accelerator with eXcellence In Applications) is producing a conceptual design report for a highly compact and cost-effective European facility with multi-GeV electron beams accelerated using plasmas. EuPRAXIA will be set up as a distributed Open Innovation platform with two construction sites, one with a focus on beam-driven plasma acceleration (PWFA) and another site with a focus on laser-driven plasma acceleration (LWFA). User areas at both sites will provide access to free-electron laser pilot experiments, positron generation and acceleration, compact radiation sources, and test beams for high-energy physics detector development. Support centres in four different countries will complement the pan-European implementation of this infrastructure

CONTROL OF MHD STABILITY IN DIII-D ADVANCED TOKAMAK DISCHARGES

OAK-B135 Advanced tokamak research in DIII-D seeks to optimize the tokamak approach for fusion energy production, leading to a compact, steady state power source. High power density implies operation at high toroidal beta, {beta}{sub T}=&lt;p&gt;2{micro}{sub 0}/B{sub T}{sup 2}, since fusion power density increases roughly as the square of the plasma pressure. Steady-state operation with low recirculating power for current drive implies operation at high poloidal beta, {beta}{sub P} = &lt;p&gt;2{micro}{sub 0}/&lt;B{sub P}&gt;{sup 2}, in order to maximize the fraction of self-generated bootstrap current. Together, these lead to a requirement of operation at high normalized beta, {beta}{sub N} = {beta}{sub T}(aB/I), since {beta}{sub P}{beta}{sub T} {approx} 25[(1+{kappa}{sup 2})/2] ({beta}{sub N}/100){sup 2}. Plasmas with high normalized beta are likely to operate near one or more stability limits, so control of MHD stability in such plasmas is crucial