Fick's law adapted to cationic diffusion in a semi-infinite solid: application to spinel megacrystals

In alkaline lavas, the chemical zoning of megacrystals of spinel is due to the cationic exchange between the latter and the host lava. The application of Fick's law to cationic diffusion profiles allows to calculate the time these crystals have stayed in the lava. Those which are in a chemical equilibrium were in contact with the lava during 20 to 30 days, whereas megacrystals lacking this equilibrium were in contact only for 3 or 4 days. The duration of the rise of an ultrabasic nodule in the volcanic chimney was calculated by applying Stokes' law.

Quantitative Assessment of T1 Relaxation and Diffusion as a Prognostic Tool for Brain Development: A Longitudinal Preliminary Study on Preterm Babies

BACKGROUND: Despite major advances in care of premature infants, survivors exhibit mild cognitive deficits in around 40%. Beside severe intraventricular haemorrhages (IVH) and cystic periventricular leucomalacia (PVL), more subtle patterns such as grade I and II IVH, punctuate WM lesions and diffuse PVL might be linked to the cognitive deficits. Grey matter disease is also recognized to contribute to long-term cognitive impairment.¦OBJECTIVE: We intend to use novel MR techniques to study more precisely the different injury patterns. In particular MP2RAGE (magnetization prepared dual rapid echo gradient) produces high-resolution quantitative T1 relaxation maps. This contrast is known to reflect tissue anomalies such as white matter injury in general and dysmyelination in particular. We also used diffusion tensor imaging, a quantitative technique known to reflect white matter maturation and disease.¦DESIGN/METHODS: All preterm infants born under 30 weeks of GA were included. Serial 3T MR-imaging using a neonatal head-coil at DOL 3, 10 and at term equivalent age (TEA), using DTI and MP2RAGE sequences was performed. MP2RAGE generates a T1 map and allows calculating the relaxation time T1. Multiple measurements were performed for each exam in 12 defined white and grey matter ROIs.¦RESULTS: 16 patients were recruited: mean GA 27 2/7 w (191,2d SD±10,8), mean BW 999g (SD±265). 39 MRIs were realized (12 early: mean 4,83d±1,75, 13 late: mean 18,77d±8,05 and 14 at TEA: 88,91d±8,96). Measures of relaxation time T1 show a gradual and significant decrease over time (for ROI PLIC mean±SD in ms: 2100.53±102,75, 2116,5±41,55 and 1726,42±51,31 and for ROI central WM: 2302,25±79,02, 2315,02±115,02 and 1992,7±96,37 for early, late and TEA MR respectively). These trends are also observed in grey matter area, especially in thalamus. Measurements of ADC values show similar monotonous decrease over time.¦CONCLUSIONS: From these preliminary results, we conclude that quantitative MR imaging in very preterm infants is feasible. On the successive MP2RAGE and DTI sequences, we observe a gradual decrease over time in the described ROIs, representing the progressive maturation of the WM micro-structure and interestingly the same evolution is observed in the grey matter. We speculate that our study will provide normative values for T1map and ADC and might be a predictive factor for favourable or less favourable outcome.

Model selection and error estimation

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical {\sc vc} dimension, empirical {\sc vc} entropy, andmargin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

Random measurement error and regression dilution bias.

Summary points: - The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease) - Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null - Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant - Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable

Comparative testing of a miniature diffusion size classifier to assess airborne ultrafine particles under field conditions

Miniature diffusion size classifiers (miniDiSC) are novel handheld devices to measure ultrafine particles (UFP). UFP have been linked to the development of cardiovascular and pulmonary diseases; thus, detection and quantification of these particles are important for evaluating their potential health hazards. As part of the UFP exposure assessments of highwaymaintenance workers in western Switzerland, we compared a miniDiSC with a portable condensation particle counter (P-TRAK). In addition, we performed stationary measurements with a miniDiSC and a scanning mobility particle sizer (SMPS) at a site immediately adjacent to a highway. Measurements with miniDiSC and P-TRAK correlated well (correlation of r = 0.84) but average particle numbers of the miniDiSC were 30%âeuro"60% higher. This difference was significantly increased for mean particle diameters below 40 nm. The correlation between theminiDiSC and the SMPSduring stationary measurements was very high (r = 0.98) although particle numbers from the miniDiSC were 30% lower. Differences between the three devices were attributed to the different cutoff diameters for detection. Correction for this size dependent effect led to very similar results across all counters.We did not observe any significant influence of other particle characteristics. Our results suggest that the miniDiSC provides accurate particle number concentrations and geometric mean diameters at traffic-influenced sites, making it a useful tool for personal exposure assessment in such settings.

Imagerie de diffusion hépatique : facteurs prédictifs du « T2 shine-through effect » dans l'hémangiome hépatique.

Objectifs: Déterminer la fréquence et les facteurs prédictifs de l'effet T2 shine-through (T2st) dans l'hémangiome hépatique (HH). Matériels et méthodes: Entre janvier 2010 et novembre 2011, l'imagerie par résonance magnétique (IRM) du foie de 149 patients avec 400 HH a été revue rétrospectivement. Les caractéristiques lésionnelles : taille, localisation, signal et aspect en T1, T2 et diffusion, T2st, coefficient apparent de diffusion de l'HH et du foie (ADChh et ADCf) et type de rehaussement ont été évalués. Résultats: Le T2st était observé dans 53 % des HH. Sa présence était corrélée positivement avec la taille (p=0,046) et négativement avec ADChh et ADCf (p<0,0001, p=0,021). Le T2st était plus fréquent dans le lobe gauche vs droit (p=0,038), et dans les HH typiques (hypersignal T2 et rehaussement en mottes, p=0,0043). L'analyse multivariée retrouvait comme facteurs indépendants de la présence d'un T2st : ADChh et le type de rehaussement. Conclusion: Le T2st est fréquemment observé dans les HH et notamment les formes typiques. Sa présence ne remet pas en question le diagnostic dans les formes typiques.

Taking "Galton's problem" Seriously : Towards a Theory of Policy Diffusion

This article builds on the recent policy diffusion literature and attempts to overcome one of its major problems, namely the lack of a coherent theoretical framework. The literature defines policy diffusion as a process where policy choices are interdependent, and identifies several diffusion mechanisms that specify the link between the policy choices of the various actors. As these mechanisms are grounded in different theories, theoretical accounts of diffusion currently have little internal coherence. In this article we put forward an expected-utility model of policy change that is able to subsume all the diffusion mechanisms. We argue that the expected utility of a policy depends on both its effectiveness and the payoffs it yields, and we show that the various diffusion mechanisms operate by altering these two parameters. Each mechanism affects one of the two parameters, and does so in distinct ways. To account for aggregate patterns of diffusion, we embed our model in a simple threshold model of diffusion. Given the high complexity of the process that results, strong analytical conclusions on aggregate patterns cannot be drawn without more extensive analysis which is beyond the scope of this article. However, preliminary considerations indicate that a wide range of diffusion processes may exist and that convergence is only one possible outcome.

A receptor-like kinase mutant with absent endodermal diffusion barrier displays selective nutrient homeostasis defects.

The endodermis represents the main barrier to extracellular diffusion in plant roots, and it is central to current models of plant nutrient uptake. Despite this, little is known about the genes setting up this endodermal barrier. In this study, we report the identification and characterization of a strong barrier mutant, schengen3 (sgn3). We observe a surprising ability of the mutant to maintain nutrient homeostasis, but demonstrate a major defect in maintaining sufficient levels of the macronutrient potassium. We show that SGN3/GASSHO1 is a receptor-like kinase that is necessary for localizing CASPARIAN STRIP DOMAIN PROTEINS (CASPs)--major players of endodermal differentiation--into an uninterrupted, ring-like domain. SGN3 appears to localize into a broader band, embedding growing CASP microdomains. The discovery of SGN3 strongly advances our ability to interrogate mechanisms of plant nutrient homeostasis and provides a novel actor for localized microdomain formation at the endodermal plasma membrane.

Diffusion-weighted spectroscopy: a novel approach to determine macromolecule resonances in short-echo time 1H-MRS.

Quantification of short-echo time proton magnetic resonance spectroscopy results in >18 metabolite concentrations (neurochemical profile). Their quantification accuracy depends on the assessment of the contribution of macromolecule (MM) resonances, previously experimentally achieved by exploiting the several fold difference in T(1). To minimize effects of heterogeneities in metabolites T(1), the aim of the study was to assess MM signal contributions by combining inversion recovery (IR) and diffusion-weighted proton spectroscopy at high-magnetic field (14.1 T) and short echo time (= 8 msec) in the rat brain. IR combined with diffusion weighting experiments (with δ/Δ = 1.5/200 msec and b-value = 11.8 msec/μm(2)) showed that the metabolite nulled spectrum (inversion time = 740 msec) was affected by residuals attributed to creatine, inositol, taurine, choline, N-acetylaspartate as well as glutamine and glutamate. While the metabolite residuals were significantly attenuated by 50%, the MM signals were almost not affected (< 8%). The combination of metabolite-nulled IR spectra with diffusion weighting allows a specific characterization of MM resonances with minimal metabolite signal contributions and is expected to lead to a more precise quantification of the neurochemical profile.

A fully adaptive numerical approximation for a two-dimensional epidemic model with nonlinear cross-diffusion

An epidemic model is formulated by a reactionâeuro"diffusion system where the spatial pattern formation is driven by cross-diffusion. The reaction terms describe the local dynamics of susceptible and infected species, whereas the diffusion terms account for the spatial distribution dynamics. For both self-diffusion and cross-diffusion, nonlinear constitutive assumptions are suggested. To simulate the pattern formation two finite volume formulations are proposed, which employ a conservative and a non-conservative discretization, respectively. An efficient simulation is obtained by a fully adaptive multiresolution strategy. Numerical examples illustrate the impact of the cross-diffusion on the pattern formation.

Spatio-temporal Brain Dynamics Mediating Post-error Behavioral Adjustments.

Optimal behavior relies on flexible adaptation to environmental requirements, notably based on the detection of errors. The impact of error detection on subsequent behavior typically manifests as a slowing down of RTs following errors. Precisely how errors impact the processing of subsequent stimuli and in turn shape behavior remains unresolved. To address these questions, we used an auditory spatial go/no-go task where continual feedback informed participants of whether they were too slow. We contrasted auditory-evoked potentials to left-lateralized go and right no-go stimuli as a function of performance on the preceding go stimuli, generating a 2 × 2 design with "preceding performance" (fast hit [FH], slow hit [SH]) and stimulus type (go, no-go) as within-subject factors. SH trials yielded SH trials on the following trials more often than did FHs, supporting our assumption that SHs engaged effects similar to errors. Electrophysiologically, auditory-evoked potentials modulated topographically as a function of preceding performance 80-110 msec poststimulus onset and then as a function of stimulus type at 110-140 msec, indicative of changes in the underlying brain networks. Source estimations revealed a stronger activity of prefrontal regions to stimuli after successful than error trials, followed by a stronger response of parietal areas to the no-go than go stimuli. We interpret these results in terms of a shift from a fast automatic to a slow controlled form of inhibitory control induced by the detection of errors, manifesting during low-level integration of task-relevant features of subsequent stimuli, which in turn influences response speed.