Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

Accurate and efficient simulation of multiphase flow in a heterogeneous reservoir by using error estimate and control in the multiscale finite-volume framework

The multiscale finite-volume (MSFV) method is designed to reduce the computational cost of elliptic and parabolic problems with highly heterogeneous anisotropic coefficients. The reduction is achieved by splitting the original global problem into a set of local problems (with approximate local boundary conditions) coupled by a coarse global problem. It has been shown recently that the numerical errors in MSFV results can be reduced systematically with an iterative procedure that provides a conservative velocity field after any iteration step. The iterative MSFV (i-MSFV) method can be obtained with an improved (smoothed) multiscale solution to enhance the localization conditions, with a Krylov subspace method [e.g., the generalized-minimal-residual (GMRES) algorithm] preconditioned by the MSFV system, or with a combination of both. In a multiphase-flow system, a balance between accuracy and computational efficiency should be achieved by finding a minimum number of i-MSFV iterations (on pressure), which is necessary to achieve the desired accuracy in the saturation solution. In this work, we extend the i-MSFV method to sequential implicit simulation of time-dependent problems. To control the error of the coupled saturation/pressure system, we analyze the transport error caused by an approximate velocity field. We then propose an error-control strategy on the basis of the residual of the pressure equation. At the beginning of simulation, the pressure solution is iterated until a specified accuracy is achieved. To minimize the number of iterations in a multiphase-flow problem, the solution at the previous timestep is used to improve the localization assumption at the current timestep. Additional iterations are used only when the residual becomes larger than a specified threshold value. Numerical results show that only a few iterations on average are necessary to improve the MSFV results significantly, even for very challenging problems. Therefore, the proposed adaptive strategy yields efficient and accurate simulation of multiphase flow in heterogeneous porous media.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Que faire du couple local/global ? Pour une anthropologie pleinement processuelle

This article examines the uses of the local/global dichotomy in anthropology. It is argued that the use of these terms as analytical tools tends to lead to a reification of "global forces" seen as external to the local site where the ethnographic study takes place. To avoid endless debates on whether or not the "global" can be the object of ethnographic scrutiny, anthropologists should treat the local and the global as scalar properties of social systems that are generated in the course of historical processes.

Influence of local environmental olfactory cues on place learning in rats

The aim of the present study was to assess the influence of local environmental olfactory cues on place learning in rats. We developed a new experimental design allowing the comparison of the use of local olfactory and visual cues in spatial and discrimination learning. We compared the effect of both types of cues on the discrimination of a single food source in an open-field arena. The goal was either in a fixed or in a variable location, and could be indicated by local olfactory and/or visual cues. The local cues enhanced the discrimination of the goal dish, whether it was in a fixed or in a variable location. However, we did not observe any overshadowing of the spatial information by the local olfactory or visual cue. Rats relied primarily on distant visuospatial information to locate the goal, neglecting local information when it was in conflict with the spatial information.

Modeling resting-state functional networks when the cortex falls asleep: local and global changes.

The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network.

Sex biased spatial strategies relying on the integration of multimodal cues in a rat model of schizophrenia: impairment in predicting future context?

Male and female Wistar rats were treated postnatally (PND 5-16) with BSO (l-buthionine-(S,R)-sulfoximine) to provide a rat model of schizophrenia based on transient glutathione deficit. In the watermaze, BSO-treated male rats perform very efficiently in conditions where a diversity of visual information is continuously available during orientation trajectories [1]. Our hypothesis is that the treatment impairs proactive strategies anticipating future sensory information, while supporting a tight visual adjustment on memorized snapshots, i.e. compensatory reactive strategies. To test this hypothesis, BSO rats' performance was assessed in two conditions using an 8-arm radial maze task: a semi-transparent maze with no available view on the environment from maze centre [2], and a modified 2-parallel maze known to induce a neglect of the parallel pair in normal rats [3-5]. Male rats, but not females, were affected by the BSO treatment. In the semi-transparent maze, BSO males expressed a higher error rate, especially in completing the maze after an interruption. In the 2-parallel maze shape, BSO males, unlike controls, expressed no neglect of the parallel arms. This second result was in accord with a reactive strategy using accurate memory images of the contextual environment instead of a representation based on integrating relative directions. These results are coherent with a treatment-induced deficit in proactive decision strategy based on multimodal cognitive maps, compensated by accurate reactive adaptations based on the memory of local configurations. Control females did not express an efficient proactive capacity in the semi-transparent maze, neither did they show the significant neglect of the parallel arms, which might have masked the BSO induced effect. Their reduced sensitivity to BSO treatment is discussed with regard to a sex biased basal cognitive style.

First-line chemotherapy with local treatment can prevent external-beam irradiation and enucleation in low-stage intraocular retinoblastoma.

PURPOSE: To evaluate the efficacy of first-line chemotherapy (CT) in preventing external-beam radiotherapy (EBR) and/or enucleation in patients with retinoblastoma (Rbl). PATIENTS AND METHODS: Twenty-four patients with newly diagnosed unilateral or bilateral Rbl received CT associated with local treatment (LT). Two to five courses of etoposide and carboplatin were administered at 3- to 4-week intervals, depending on tumor response, and were completed each time by LT. RESULTS: Tumor response was observed in all eyes. Twenty-one of 24 patients showed a complete response (CR) that persisted at a median follow-up (FU) of 31 months (range, 4 to 41 months). Among the three patients who relapsed, two were lost to FU and one died of progressive disease. CR was achieved by CT and LT alone in 15 (71.4%) of 21 patients with less advanced disease (groups I to III). Six other patients with advanced disease (groups IV and V) experienced treatment failure and needed salvage treatment by EBR and/or enucleation. The difference between the two patient groups with regard to disease stage was statistically significant (P <.0001). EBR could be avoided in 13 (68.4%) of 19 patients, who presented with groups I to III (15 eyes) and group V (one eye) disease, whereas enucleation could be avoided in only two (40%) of five. CONCLUSION: CT combined with intensive LT is effective in patients with groups I to III Rbl, permitting the avoidance of EBR in the majority of these young children and, thus, reducing the risk of long-term sequelae. This is in contrast with the disappointing results for patients with groups IV and V Rbl, in whom EBR and/or enucleation was needed.

Adjonction d'un anesthésique local intra-articulaire lors d'arthro-TDM/IRM : utilité et avantages de la Bupivacaïne.

Objectifs: Une phase hyperalgique dans les 4 heures post-examen arthrographique est maintenant reconnue dans la littérature. Comment s'en amender ? Nous comparonsl'absence d'anesthésique à l'adjonction de deux différents anesthésiques locaux intra-articulaires(rapidocaïne/bupivacaïne) lors d'arthro-TDM/IRM. Matériels et méthodes: Après approbation du comité d'éthique, étude prospective chez 150 patients répartis aléatoirement en trois groupes : 1) sans anesthésique intra-articulaire, 2)rapidocaïne 1%, 3) bupivacaïne 0,25%. Recueil du score EVA (0-10) aux 5 temps suivants : avant injection (score de base), puis 20 minutes, 4 heures, 24 heureset 7 jours après la procédure. Résultats: Le pic douloureux maximal se trouve à 4h après la procédure (idem littérature). La douleur augmente en moyenne de 1,60 unités 4h après la procédure pour legroupe 1, de 1,22 unités pour le groupe 2 et de 0,29 unités pour le groupe 3. La différence entre les groupes 1 et 3 est statistiquement significative (p=0,002 -Tests ANOVA et de Sidak). Elle n'est pas significative entre les groupes 1 et 2 (p=0,536). La comparaison rapidocaïne et bupivacaïne est moins concluante(p=0,065). Conclusion: L'adjonction de bupivacaïne intra-articulaire devrait être réalisée lors d'examens arthrographiques, surtout afin d'améliorer le confort du patient mais aussi pourfavoriser son immobilité lors de l'acquisition des images TDM ou IRM .

Local adaptation and matching habitat choice in female barn owls with respect to melanic coloration.

Local adaptation is a major mechanism underlying the maintenance of phenotypic variation in spatially heterogeneous environments. In the barn owl (Tyto alba), dark and pale reddish-pheomelanic individuals are adapted to conditions prevailing in northern and southern Europe, respectively. Using a long-term dataset from Central Europe, we report results consistent with the hypothesis that the different pheomelanic phenotypes are adapted to specific local conditions in females, but not in males. Compared to whitish females, reddish females bred in sites surrounded by more arable fields and less forests. Colour-dependent habitat choice was apparently beneficial. First, whitish females produced more fledglings when breeding in wooded areas, whereas reddish females when breeding in sites with more arable fields. Second, cross-fostering experiments showed that female nestlings grew wings more rapidly when both their foster and biological mothers were of similar colour. The latter result suggests that mothers should particularly produce daughters in environments that best match their own coloration. Accordingly, whiter females produced fewer daughters in territories with more arable fields. In conclusion, females displaying alternative melanic phenotypes bred in habitats providing them with the highest fitness benefits. Although small in magnitude, matching habitat selection and local adaptation may help maintain variation in pheomelanin coloration in the barn owl.

Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.