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There is increasing evidence of different subtypes of individuals with mild cognitive impairment (MCI). An important line of research is whether neuropsychologically-defined subtypes have distinct patterns of neurodegeneration and cerebrospinal fluid (CSF) biomarker composition. In our study, we demonstrated that MCI participants of the ADNI database (N = 640) can be discriminated into 3 coherent neuropsychological subgroups. Our clustering approach revealed amnestic MCI, mixed MCI, and cluster-derived normal subgroups. Furthermore, classification modeling revealed that specific predictive features can be used to differentiate amnestic and mixed MCI from cognitively normal (CN) controls: CSF Aβ 1 42 concentration for the former and CSF Aβ 1–42 concentration, tau concentration as well as grey matter atrophy (especially in the temporal and occipital lobes) for the latter. In contrast, participants from the cluster-derived normal subgroup exhibited an identical profile to CN controls in terms of cognitive performance, brain structure, and CSF biomarker levels. Our comprehensive data analytics strategy provides further evidence that multimodal neuropsychological subtyping is both clinically and neurobiologically meaningful. [ABSTRACT FROM AUTHOR]

Empirically based literature suggests that avoidance/approach motivation arising from color–meaning associations assume a key mediational role in the color effect during psychological functioning. Even if several studies investigated color–meaning associations through different methodological approaches, no study investigated specific color–meaning associations (1) through continuous measures (2) for both positive and negative meanings. In addition, color effects are not unequivocal, and interindividual variability issues are still underexplored. The present study is based on the application of visual analog scales to assess continuous measures of specific color–meaning associations related to both negative and positive meanings that could rely on avoidance/approach motivation. The data analyses compared the distribution of the color–meaning association scores rated by participants (N = 152) on visual analog scales. The results showed strong associations between red color and items that could be related to avoidance motivation. Conversely, green color association scores showed distinct and specific associations that could be related to approach motivation. The results also revealed that blue color could exhibit a similar pattern for some meaning association scores compared with green color, as well as orange compared with red association scores. In addition, the results suggest that color preferences may influence color effects, especially regarding color-related approach motivation. The present study provides new insights about the color effect on psychological functioning and a novel approach to investigate the mediational processes such as avoidance/approach motivation that considers interindividual differences along a continuum. [ABSTRACT FROM AUTHOR]

Global climate models, like any in silico numerical experiments, are affected by different types of bias. Uncertainty quantification remains a challenge in any climate detection and attribution analysis. A fundamental methodological question is to determine which statistical summaries, while bringing relevant signals, can be robust with respect to multimodel errors. In this paper, we propose a simple statistical framework that significantly improves signal detection in climate attribution studies. We show that the complex bias correction step can be entirely bypassed for models for which bias between the simulated and unobserved counterfactual worlds is the same as between the simulated and unobserved factual worlds. To illustrate our approach, we infer emergence times in precipitation from the CMIP5 and CMIP6 archives. The detected anthropogenic signal in yearly maxima of daily precipitation clearly emerges at the beginning of the twenty-first century. In addition, no CMIP model seems to outperform the others and a weighted linear combination of all improves the estimation of emergence times. Significance Statement: We show that the bias in multimodel global climate simulations can be efficiently handled when the appropriate metric is chosen. This metric leads to an easy-to-implement statistical procedure based on a checkable assumption. This allows us to demonstrate that optimal convex combinations of CMIP outputs can improve the signal strength in finding emergence times. Our data analysis procedure is applied to yearly maximum of precipitation from CMIP5 and CMIP6 databases. The attribution of the anthropogenic forcing clearly emerges in extreme precipitation at the beginning of the twenty-first century. [ABSTRACT FROM AUTHOR]

Background: Soft palate defects created during oral cancer surgery may prevent complete palatal closure and trigger palatopharyngeal insufficiency. One current treatment employs a rigid obturator prosthesis; an extension of acrylic resin at the level of the hard palate ensures surface contact with the remaining musculature. Unfortunately, airflow escape often causes hypernasality, compromises speech intelligibility, and creates swallowing problems (including leakage of food and fluid into the nasal airway). We plan to test a new removable denture featuring a thick dental dam that serves as a membrane obturator. The principal objective of the clinical trial is a comparison of speech handicap levels after 1 month in patients with acquired velar insufficiencies who wear either the new device or a conventional, rigid obturator. The secondary objectives are between-device comparisons of the swallowing handicaps and the health-related qualities of life.Methods: The VELOMEMBRANE trial is a superiority, open-labeled, two-way, random crossover clinical trial. Adult patients exhibiting velar or palatovelar substance loss after tumor excision and who are indicated for rigid obturator-mediated prosthetic rehabilitation will be recruited in two teaching hospitals in France. Fourteen participants will be randomly allocated to wear both prostheses for 1-month periods in either order. The new membrane obturator is a removable resin prosthesis incorporating a rigid extension that holds a dental dam to restore the soft palate. The primary outcome will be the extent of phonation-related disability (the overall score on the Voice Handicap Index [VHI]). The secondary outcomes will be the Deglutition Handicap Index and health-related quality of life scores of the European Organization for Research and Treatment of Cancer (EORTC).Discussion: High-quality evidence will be provided to document the utility of a new medical device that may greatly improve the management and quality of life of patients with acquired velar insufficiency.Trial Registration: ClinicalTrials.gov NCT04009811 . Registered on 4 July 2019. [ABSTRACT FROM AUTHOR]

Modulation instability is one of the most ubiquitous phenomena in physics. Here we investigate the phase-sensitive properties of modulation instability with harmonic seeding in passive fiber resonators. Theoretical investigations based on the Lugiato−Lefever equation with time dependent pump and a three-wave truncation show that the dynamics of the system is sensitive to the relative phase between input signal, idler, and pump waves. The modulation instability gain can even vanish for a peculiar value of the initial relative phase. An advanced multi-heterodyne measurement technique had been developed to record the real time evolution, round-trip to round-trip, of the power and phase of the output cavity field to confirm these theoretical predictions. Modulation instability refers to the sensitivity of dispersive, weakly nonlinear systems to small perturbations and may be used as a source of optical gain. Here, the phase-sensitive properties of modulation instability with harmonic seeding in passive fiber resonators are investigated in theory and experiments. [ABSTRACT FROM AUTHOR]

Indigenous post-secondary students face cumbersome barriers to educational attainment. This article explores those barriers and presents findings from a survey of Indigenous students conducted at Algoma University in Sault St. Marie, Ontario, Canada. For First Nations' students surveyed in 2016 (n = 36), funding was identified as a major barrier and, considering that nearly half of students had dependents, finding affordable housing and childcare was a significant challenge. The transition to an urban area from living on-reserve is also difficult for many students. The Anishinaabe Initiatives Division at Algoma University hosted culturally affirming events for Indigenous students. We found this to be an effective tool universities can use to bolster student resilience and foster a sense of belonging. We also propose that funding on university campuses must increase to support Indigenous students' educational attainment goals. [ABSTRACT FROM AUTHOR]

The field of statistics has become one of the mathematical foundations in forecast evaluation studies, especially with regard to computing scoring rules. The classical paradigm of scoring rules is to discriminate between two different forecasts by comparing them with observations. The probability distribution of the observed record is assumed to be perfect as a verification benchmark. In practice, however, observations are almost always tainted by errors and uncertainties. These may be due to homogenization problems, instrumental deficiencies, the need for indirect reconstructions from other sources (e.g., radar data), model errors in gridded products like reanalysis, or any other data-recording issues. If the yardstick used to compare forecasts is imprecise, one can wonder whether such types of errors may or may not have a strong influence on decisions based on classical scoring rules. We propose a new scoring rule scheme in the context of models that incorporate errors of the verification data. We rely on existing scoring rules and incorporate uncertainty and error of the verification data through a hidden variable and the conditional expectation of scores when they are viewed as a random variable. The proposed scoring framework is applied to standard setups, mainly an additive Gaussian noise model and a multiplicative Gamma noise model. These classical examples provide known and tractable conditional distributions and, consequently, allow us to interpret explicit expressions of our score. By considering scores to be random variables, one can access the entire range of their distribution. In particular, we illustrate that the commonly used mean score can be a misleading representative of the distribution when the latter is highly skewed or has heavy tails. In a simulation study, through the power of a statistical test, we demonstrate the ability of the newly proposed score to better discriminate between forecasts when verification data are subject to uncertainty compared with the scores used in practice. We apply the benefit of accounting for the uncertainty of the verification data in the scoring procedure on a dataset of surface wind speed from measurements and numerical model outputs. Finally, we open some discussions on the use of this proposed scoring framework for non-explicit conditional distributions. [ABSTRACT FROM AUTHOR]

The classical theory of modulation instability (MI) attributed to Bespalov-Talanov in optics and Benjamin-Feir for water waves is just a linear approximation of nonlinear effects and has limitations that have been corrected using the exact weakly nonlinear theory of wave propagation. We report results of experiments in both optics and hydrodynamics, which are in excellent agreement with nonlinear theory. These observations clearly demonstrate that MI has a wider band of unstable frequencies than predicted by the linear stability analysis. The range of areas where the nonlinear theory of MI can be applied is actually much larger than considered here. [ABSTRACT FROM AUTHOR]

Estimating the likelihood of compound climate extremes such as concurrent drought and heatwaves or compound precipitation and wind speed extremes is important for assessing climate risks. Typically, simulations from climate models are used to assess future risks, but it is largely unknown how well the current generation of models represents compound extremes. Here, we introduce a new metric that measures whether the tails of bivariate distributions show a similar dependence structure across different datasets. We analyse compound precipitation and wind extremes in reanalysis data and different high-resolution simulations for central Europe. A state-of-the-art reanalysis dataset (ERA5) is compared to simulations with a weather model (Weather Research and Forecasting – WRF) either driven by observation-based boundary conditions or a global circulation model (Community Earth System Model – CESM) under present-day and future conditions with strong greenhouse gas forcing (Representative Concentration Pathway 8.5 – RCP8.5). Over the historical period, the high-resolution WRF simulations capture precipitation and wind extremes as well as their response to orographic effects more realistically than ERA5. Thus, WRF simulations driven by observation-based boundary conditions are used as a benchmark for evaluating the dependence structure of wind and precipitation extremes. Overall, boundary conditions in WRF appear to be the key factor in explaining differences in the dependence behaviour between strong wind and heavy precipitation between simulations. In comparison, external forcings (RCP8.5) are of second order. Our approach offers new methodological tools to evaluate climate model simulations with respect to compound extremes. [ABSTRACT FROM AUTHOR]

Estimating the likelihood of compound climate extremes such as concurrent drought and heatwaves or compound precipitation and wind speed extremes is important for assessing climate risks. Typically, simulations from climate models are used to assess future risks, but it is largely unknown how well the current generation of models represents compound extremes. Here, we introduce a new metric that measures whether the tails of bivariate distributions show a similar dependence structure across different datasets. We analyse compound precipitation and wind extremes in reanalysis data and different high-resolution simulations for central Europe. A state-of-the-art reanalysis dataset (ERA5) is compared to simulations with a weather model (WRF) either driven by observation-based boundary conditions or a global circulation model (CESM) under present-day and future conditions with strong greenhouse gas forcing (RCP8.5). Over the historical period, the high-resolution WRF simulations capture precipitation and wind extremes and there response to orographic effects more realistically than ERA5. Thus, WRF simulations driven by observation-based boundary conditions are used as a benchmark for evaluating the dependence structure of wind and precipitation extremes. Overall, boundary conditions in WRF appear to be the key factor in explaining differences in the dependence behaviour between strong wind and heavy rainfall between simulations. In comparison, external forcings (RCP8.5) are of second order. Our approach offers new methodological tools to evaluate climate model simulations with respect to compound extremes. [ABSTRACT FROM AUTHOR]

Oral chemotherapies pediatrics are manufactured from injectable specialties in a controlled-atmosphere area. Packaged in Luer-Lock syringes, the transition to an ENFit™ connector became crucial to enable administration in surveyed patients. In parallel, a study was carried out to optimize and secure patient care by setting up a retrocession circuit.To introduce the ENFit™ range of devices into the manufacturing process for oral or enteral chemotherapy syringes. Secondly, establish a retrocession circuit, validate its economic relevance and implement and evaluate efforts to promote proper use.ENFit™ meeting the specifications were sourced and then evaluated. Research was conducted on the legislative framework governing the retrocession of masterful preparations made from injectable specialties. A 2021 retrospective economic study enabled the assessment of the financial balance generated by a potential retrocession circuit. Meetings to promote the good use of medication were conducted. Satisfaction questionnaires were created for caregivers and medical staff in the pediatric department.All ENFit™ ranges have been referenced within the Fresenius laboratory. Retrocession has been set up in accordance with legislation. The economic study highlighted a potential revenue of EUR 69,900 in 2021. Three good-use booklets and a dosage plan were created to promote good use. Ten families and 12 caregivers responded to the questionnaire, with satisfaction rates of 81.1% and 71.9%, respectively.ENFit™ devices has enabled oral and enteral administration of chemotherapy. The retrocession circuit includes all the good-use elements required for optimal patient care. The results of the satisfaction survey are positive, certain areas for improvement have been identified. [ABSTRACT FROM AUTHOR]

Multiple changes in Earth’s climate system have been observed over the past decades. Determining how likely each of these changes is to have been caused by human influence is important for decision making with regard to mitigation and adaptation policy. Here we describe an approach for deriving the probability that anthropogenic forcings have caused a given observed change. The proposed approach is anchored into causal counterfactual theory (Pearl 2009), which was introduced recently, and in fact partly used already, in the context of extreme weather event attribution (EA). We argue that these concepts are also relevant to, and can be straightforwardly extended to, the context of detection and attribution of long-term trends associated with climate change (D&A). For this purpose, and in agreement with the principle of fingerprinting applied in the conventional D&A framework, a trajectory of change is converted into an event occurrence defined by maximizing the causal evidence associated to the forcing under scrutiny. Other key assumptions used in the conventional D&A framework, in particular those related to numerical model error, can also be adapted conveniently to this approach. Our proposal thus allows us to bridge the conventional framework with the standard causal theory, in an attempt to improve the quantification of causal probabilities. An illustration suggests that our approach is prone to yield a significantly higher estimate of the probability that anthropogenic forcings have caused the observed temperature change, thus supporting more assertive causal claims. [ABSTRACT FROM AUTHOR]

Intracerebral hemorrhage (ICH) is the most severe form of stroke. Catheter-delivered thrombolysis with recombinant tissue-type plasminogen activator (rtPA) for the drainage of ICH is currently under evaluation in a phase III clinical trial (MISTIE III). However, in a pig model of ICH, in situ fibrinolysis with rtPA was reported to increase peri-lesional edema by promoting N-methyl-D-aspartate (NMDA)-dependent excitotoxicity. In the present study, we engineered a nonneurotoxic tPA variant, OptPA, and investigated its safety and efficacy for in situ fibrinolysis in a rat model of ICH. Magnetic resonance imaging analyses of hematoma and edema volumes, behavioral tasks and histological analyses were performed to measure the effects of treatments. In vitro, OptPA was equally fibrinolytic as rtPA without promoting NMDA-dependent neurotoxicity. In vivo, in situ fibrinolysis using OptPA reduced hematoma volume, like rtPA, but it also reduced the evolution of peri-hematomal neuronal death and subsequent edema progression. Overall, this preclinical study demonstrates beneficial effects of OptPA compared to rtPA for the drainage of ICH. [ABSTRACT FROM AUTHOR]

Both climate and statistical models play an essential role in the process of demonstrating that the distribution of some atmospheric variable has changed over time and in establishing the most likely causes for the detected change. One statistical difficulty in the research field of detection and attribution resides in defining events that can be easily compared and accurately inferred from reasonable sample sizes. As many impacts studies focus on extreme events, the inference of small probabilities and the computation of their associated uncertainties quickly become challenging. In the particular context of event attribution, the authors address the question of how to compare records between the counterfactual "world as it might have been" without anthropogenic forcings and the factual "world that is." Records are often the most important events in terms of impact and get much media attention. The authors will show how to efficiently estimate the ratio of two small probabilities of records. The inferential gain is particularly substantial when a simple hypothesis-testing procedure is implemented. The theoretical justification of such a proposed scheme can be found in extreme value theory. To illustrate this study's approach, classical indicators in event attribution studies, like the risk ratio or the fraction of attributable risk, are modified and tailored to handle records. The authors illustrate the advantages of their method through theoretical results, simulation studies, temperature records in Paris, and outputs from a numerical climate model. [ABSTRACT FROM AUTHOR]

The selenium enrichment in groundwater may be caused by the contact with sedimentary formations. In many French regions, geogenic sedimentary sources of Se were identified as responsible of the Se concentrations exceeding the European limit in many wells designated to produce drinking water. This study focuses on the black argillaceous infillings of the Hydrogeological Experimental Site of Poitiers (HESP) and aims to better understand the Se release mechanisms at the interface between these infillings and aqueous media using batch experiments with variable pH and contact time. The Se behavior as function of pH was similar in the ultrapure water and in the HESP water and can be discriminated in three main domains. For very acidic domain the speciation of the released Se, that can be associated to the dissolution of some mineral phases, was majorly unidentified. For 2 < pH < 7.5, Se is mainly released as oxyanions which can be associated to interfacial processes. For basic pH, the maximal quantity of Se was released as oxyanions and unidentified species and is accompanied with the Fe and organic carbon mobilization. The kinetic data showed that the HESP water enhance the Se mobilization as function of time. The kinetic release of Se can be modeled as the release of three main fractions that cannot be directly correlated to the Se speciation: an immediate fraction followed by the release of two fractions corresponding to the pseudo first order kinetic. These results coupled with some in-situ data confirm the diversity and the complexity of the release mechanisms of Se that is not associated with a specific carrier phase but disseminated within the sedimentary matrix. [ABSTRACT FROM AUTHOR]

The continuous ranked probability score (CRPS) is a much used measure of performance for probabilistic forecasts of a scalar observation. It is a quadratic measure of the difference between the forecast cumulative distribution function (CDF) and the empirical CDF of the observation. Analytic formulations of the CRPS can be derived for most classical parametric distributions, and be used to assess the efficiency of different CRPS estimators. When the true forecast CDF is not fully known, but represented as an ensemble of values, the CRPS is estimated with some error. Thus, using the CRPS to compare parametric probabilistic forecasts with ensemble forecasts may be misleading due to the unknown error of the estimated CRPS for the ensemble. With simulated data, the impact of the type of the verified ensemble (a random sample or a set of quantiles) on the CRPS estimation is studied. Based on these simulations, recommendations are issued to choose the most accurate CRPS estimator according to the type of ensemble. The interest of these recommendations is illustrated with real ensemble weather forecasts. Also, relationships between several estimators of the CRPS are demonstrated and used to explain the differences of accuracy between the estimators. [ABSTRACT FROM AUTHOR]

The analysis of multiple extreme values aims to describe the stochastic behaviour of observations in the joint upper tail of a distribution function. For instance, being able to simulate multivariate extreme events is convenient for end users who need a large number of random replications of extremes as input of a given complex system to test its sensitivity. The simulation of multivariate extremes is often based on the assumption that the dependence structure, the so-called extremal dependence function, is described by a specific parametric model. We propose a simulation method for sampling bivariate extremes, under the assumption that the extremal dependence function is semi-parametric. This yields a flexible tool that can be broadly applied in real-data analyses. With the aim of estimating the probability of belonging to some extreme sets, our methodology is examined via simulation and illustrated by an analysis of strong wind gusts in France. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The selenium (Se) content and the associated release mechanisms in both surface and groundwater have become a major concern worldwide over the past 30 years. Within the Hydrogeological Experimental Site of Poitiers (HESP), a large range of aqueous Se concentrations (from non-detectable to more than 30 ppb) is observed in a limited area (about 10 ha), where water flows are highly characterized. This site thus consists of an interesting spot to better understand the release mechanisms of selenium into groundwater. The present study consists of an identification and a characterization of the lithological sources of Se within the HESP. Total rock analyses applied to core samples from different depths and wells demonstrated that selenium is concentrated in argillaceous sediments enriched with organic matter, pyrite and uranium that fulfill a part of the karst cavities developed within the Bajocian host rocks. Mineralogical and petrographic investigations highlighted the heterogeneity of these filling materials and showed the presence of successive deposits under different climatic conditions. Extensive characterizations dated the selected Se-rich samples from the Upper Cretaceous and converged to demonstrate the external and continental origin of the studied filling materials and their transformation after deposition under reduced conditions. Only indirect correlations allow considering an agreement between the Se history and the very mature organic matter identified in the argillaceous samples. This association will be further favored to determine the mechanisms releasing selenium into groundwater. [ABSTRACT FROM AUTHOR]

In this paper, thefoldingmethodology developed in the context of univariate Extreme Value Theory (EVT) by Youet al.is extended to a multivariate framework. Under the usual EVT assumption of regularly varying tails, our multivariate folding allows for the estimation of the spectral probability measure. A new weakly consistent estimator based on the classical empirical estimator is proposed. Its behaviour is illustrated through simulations and an actuarial application relative to reinsurance pricing in the case of an insurance data-set. [ABSTRACT FROM AUTHOR]

Accurate stochastic simulations of hourly precipitation are needed for impact studies at local spatial scales. Statistically, hourly precipitation data represent a difficult challenge. They are non-negative, skewed, heavy tailed, contain a lot of zeros (dry hours) and they have complex temporal structures (e.g., long persistence of dry episodes). Inspired by frailty-contagion approaches used in finance and insurance, we propose a multi-site precipitation simulator that, given appropriate regional atmospheric variables, can simultaneously handle dry events and heavy rainfall periods. One advantage of our model is its conceptual simplicity in its dynamical structure. In particular, the temporal variability is represented by a common factor based on a few classical atmospheric covariates like temperatures, pressures and others. Our inference approach is tested on simulated data and applied on measurements made in the northern part of French Brittany. [ABSTRACT FROM AUTHOR]

Arsenic (As) is one of the main toxic elements of geogenic origin that impact groundwater quality and human health worldwide. In some groundwater wells of the Sologne region (Val de Loire, France), drilled in a confined aquifer, As concentrations exceed the European drinking water standard (10 μg L−1). The monitoring of one of these drinking water wells showed As concentrations in the range 20–25 μg L−1. The presence of dissolved iron (Fe), low oxygen concentration and traces of ammonium indicated reducing conditions. The δ34S SO4 was anticorrelated with sulphate concentration. Drilling allowed to collect detrital material corresponding to a Miocene floodplain and crevasse splay with preserved plant debris. The level that contained the highest total As concentration was a silty-sandy clay containing 26.9 mg kg−1 As. The influence of alternating redox conditions on the behaviour of As was studied by incubating this material with site groundwater, in biotic or inhibited bacterial activities conditions, without synthetic organic nutrient supply, in presence of H 2 during the reducing periods. The development of both AsV-reducing and AsIII-oxidising microorganisms in biotic conditions was evidenced. At the end of the reducing periods, total As concentration strongly increased in biotic conditions. The microflora influenced As speciation, released Fe and consumed nitrate and sulphate in the water phase. Microbial communities observed in groundwater samples strongly differed from those obtained at the end of the incubation experiment, this result being potentially related to influence of the sediment compartment and to different physico-chemical conditions. However, both included major Operating Taxonomic Units (OTU) potentially involved in Fe and S biogeocycles. Methanogens emerged in the incubated sediment presenting the highest solubilised As and Fe. Results support the hypothesis of in-situ As mobilisation and speciation mediated by active biogeochemical processes. [Display omitted] • Arsenic of sedimentary origin influences quality of a French groundwater. • Temporal variations of As- and S- cycles bio-indicators are observed on site. • Incubations of core material show biologically related As solubilisation. • Incubated core slurries and groundwater present distinct bacterial communities. • As concentration and speciation is driven by bacterial activities. [ABSTRACT FROM AUTHOR]

In geosciences, data assimilation (DA) addresses the reconstruction of a hidden dynamical process given some observation data. DA is at the core of operational systems such as weather forecasting, operational oceanography and climate studies. Beyond the reconstruction of the mean or most likely state, the inference of the state posterior distribution remains a key challenge, that is, quantify uncertainties as well as to inform intrinsical stochastic variabilities. Indeed, DA schemes, such as variational DA and Kalman methods, can have difficulty in dealing with complex non‐linear processes. A growing literature investigates the cross‐fertilization of DA and machine learning. This study proposes an end‐to‐end neural scheme based on a variational Bayes inference formulation to jointly address DA and uncertainty quantification. It combines an Evidence Lower BOund variational cost to a trainable gradient‐based solver to infer the state posterior probability distribution function given observation data. The inference of the posterior and the trainable solver are learnt jointly. We demonstrate the relevance of the proposed scheme for a Gaussian parameterization of the posterior and different case‐study experiments, including Lorenz 63 dynamics and river flow measurements. A benchmark with respect to state‐of‐the‐art schemes is provided. Plain Language Summary: The spatiotemporal reconstruction of a dynamical process from some observation data is at the core of a wide range of applications in geosciences. This is particularly true for weather forecasting, operational oceanography and climate studies. However, the reconstruction of a given dynamic and the prediction of future states must take into account the uncertainties that affect the system. Thus, the available observation measurements are only provided with a limited accuracy. Besides, the encoded physical equations that model the evolution of the system do not capture the full complexity of the real system. Finally, the numerical approximation generates a non‐negligible error. For these reasons, it seems relevant to calculate a probability distribution of the state system rather than the most probable state. Using recent advances in machine learning techniques for inverse problems, we propose an algorithm that jointly learns a parametric distribution of the state, the dynamics governing the evolution of the parameters, and a solver. Experiments conducted on synthetic reference data sets, as well as on data sets describing environmental systems, validate our approach. Key Points: We propose a neural approach to jointly solve data assimilation and uncertainty quantification problems using a variational Bayes formulationOur end‐to‐end neural architecture implements a learnable gradient‐based solver for a Evidence Lower BOund criterionStudies conducted on Lorenz 63 dynamics and on river discharge from the Danube river network highlight the potential of our approach [ABSTRACT FROM AUTHOR]

In this paper, we describe and study a class of linear shrinkage estimators of the covariance matrix that is well-suited for high dimensional matrices, has a rather wide domain of applicability, and is rooted into the Gaussian conjugate framework of Chen (1979). We propose here a new look at this framework. The linear shrinkage estimator is thereby obtained as the posterior mean of the covariance, using a Bayesian Gaussian model with conjugate inverse Wishart prior, and deriving the shrinkage intensity and target matrix by marginal likelihood maximization. We introduce some extensions to the seminal approach by deriving a closed-form expression of the marginal likelihood as well as computationally light schemes for its maximization. Further, these developments are implemented in a variety of situations and include a simulation-based performance comparison with a recent, widely used class of linear shrinkage estimators. The Gaussian conjugate estimators are found to outperform these estimators in every tested situation where the latter are available and to be more widely and directly applicable. [ABSTRACT FROM AUTHOR]

Abstract: The vertebrate ectoderm gives rise to organs that produce mineralized or keratinized substances, including teeth, hair, and claws. Most of these ectodermal derivatives grow continuously throughout the animal׳s life and have active pools of adult stem cells that generate all the necessary cell types. These organs provide powerful systems for understanding the mechanisms that enable stem cells to regenerate or renew ectodermally derived tissues, and remarkable progress in our understanding of these systems has been made in recent years using mouse models. We briefly compare what is known about stem cells and their niches in incisors, hair follicles, and claws, and we examine expression of Gli1 as a potential example of a shared stem cell marker. We summarize some of the features, structures, and functions of the stem cell niches in these ectodermal derivatives; definition of the basic elements of the stem cell niches in these organs will provide guiding principles for identification and characterization of the niche in similar systems. [Copyright &y& Elsevier]

Polychlorinated biphenyls (PCBs) are environmental contaminants that persist in environment and human tissues. Perinatal exposure to these endocrine disruptors causes cognitive deficits and learning disabilities in children. These effects may involve their ability to interfere with thyroid hormone (TH) action. We tested the hypothesis that developmental exposure to PCBs can concomitantly alter TH levels and TH-regulated events during cerebral cortex development: progenitor proliferation, cell cycle exit and neuron migration. Pregnant rats exposed to the commercial PCB mixture Aroclor 1254 ended gestation with reduced total and free serum thyroxine levels. Exposure to Aroclor 1254 increased cell cycle exit of the neuronal progenitors and delayed radial neuronal migration in the fetal cortex. Progenitor cell proliferation, cell death and differentiation rate were not altered by prenatal exposure to PCBs. Given that PCBs remain ubiquitous, though diminishing, contaminants in human systems, it is important that we further understand their deleterious effects in the brain. [ABSTRACT FROM AUTHOR]

The article focuses on reading of symptoms through different conditions. Topics discussed include unconscious determination of a person enjoyed by him when experiencing symptoms, illustration given by the author Stendhal in his novel "Lucien Leuwen" related to symptoms and desires; and woman acting as a symptom for a man.

One of the main objectives of statistical climatology is to extract relevant information hidden in complex spatial-temporal climatological datasets. To identify spatial patterns, most well-known statistical techniques are based on the concept of intra- and intercluster variances (like the k-means algorithm or EOFs). As analyzing quantitative extremes like heavy rainfall has become more and more prevalent for climatologists and hydrologists during these last decades, finding spatial patterns with methods based on deviations from the mean (i.e., variances) may not be the most appropriate strategy in this context of studying such extremes. For practitioners, simple and fast clustering tools tailored for extremes have been lacking. A possible avenue to bridging this methodological gap resides in taking advantage of multivariate extreme value theory, a well-developed research field in probability, and to adapt it to the context of spatial clustering. In this paper, a novel algorithm based on this plan is proposed and studied. The approach is compared and discussed with respect to the classical k-means algorithm throughout the analysis of weekly maxima of hourly precipitation recorded in France (fall season, 92 stations, 1993-2011). [ABSTRACT FROM AUTHOR]

Abstract: Neuroimaging data support the idea that schizophrenia is a brain disorder with altered brain structure and function. New resting-state functional connectivity techniques allow us to highlight synchronization of large-scale networks, such as the default-mode network (DMN) and salience network (SN). A large body of work suggests that disruption of these networks could give rise to specific schizophrenia symptoms. We examined the intra-network connectivity strength and gray matter content (GMC) of DMN and SN in 26 schizophrenia patients using resting-state functional magnetic resonance imaging and voxel-based morphometry. Resting-state data were analyzed with independent component analysis and dual-regression techniques. We reported reduced functional connectivity within both DMN and SN in patients with schizophrenia. Concerning the DMN, patients showed weaker connectivity in a cluster located in the right paracingulate cortex. Moreover, patients showed decreased GMC in this cluster. With regard to the SN, patients showed reduced connectivity in the left and right striatum. Decreased connectivity in the paracingulate cortex was correlated with difficulties in abstract thinking. The connectivity decrease in the left striatum was correlated with delusion and depression scores. Correlation between the connectivity of DMN frontal regions and difficulties in abstract thinking emphasizes the link between negative symptoms and the likely alteration of the frontal medial cortex in schizophrenia. Correlation between the connectivity of SN striatal regions and delusions supports the aberrant salience hypothesis. This work provides new insights into dysfunctional brain organization in schizophrenia and its contribution to specific schizophrenia symptoms. [Copyright &y& Elsevier]

PA nanocomposites are prepared from clays organophilized with a phosphonium and an ammonium salt, and sodium montmorillonite is used as reference. The analysis of mechanical and micromechanical properties of the composites reveal that several micromechanical deformation processes occur in the PA/MMT composites. The matrix cavitates at relatively small stress. Processes related to non-exfoliated clay structural units are initiated at larger stresses. Sound is emitted mainly by the fracture of particles, but debonding may also occur. The plastic deformation of the matrix dominates at larger stresses and deformations. The various local deformations are independent of each other and composite properties are not determined by silicate related processes but by the deformation of the matrix. [ABSTRACT FROM AUTHOR]

Summary: Insomnia disorder has been associated with poor executive functioning. Functional imaging studies of executive functioning in insomnia are scarce and inconclusive. Because the Attentional Network Test relies on well‐defined cortical networks and sensitively distinguishes different aspects of executive function, it might reveal brain functional alterations in relatively small samples of patients. The current pilot study assessed functional connectivity during the Attentional Network Test performed using magnetic resonance imaging in 12 participants with insomnia and 13 self‐defined good sleepers. ANCOVAs were used to evaluate group differences in performance and functional connectivity in the regions of interest representing the attentional networks (i.e. alerting, orienting and executive control) at p < 0.05, uncorrected. During the orienting part, participants with insomnia showed weaker connectivity of the precentral gyrus with the superior parietal lobe (false discovery rate‐corrected), while they showed stronger connectivity between premotor and visual regions. Individual differences in connectivity between premotor and visual regions correlated inversely with reaction time. Reaction times suggested more efficient executive control in participants with insomnia compared with good sleepers. During the executive control part, participants with insomnia showed stronger connectivity of thalamic parts of the arousal circuit with the middle frontal and the occipital gyri. Conversely, connectivity between the inferior and superior frontal gyri was weaker. Participants with insomnia seem to recruit more cortical resources in visuo‐motor regions to orient attention than good sleepers do, and seem to have enhanced executive control that relates to stronger connectivity of arousal‐related thalamic areas. This latter result should be treated with caution and requires confirmation. [ABSTRACT FROM AUTHOR]

Background Only a small proportion of alcoholic patients develop advanced liver disease, suggesting that factors other than alcohol intake may influence alcoholic liver disease ( ALD) progression. We have shown that body mass index ( BMI) is an independent risk factor for fibrosis in alcohol-induced liver disease and that adipose tissue inflammation is correlated with liver lesions in alcoholic patients. The aim of this study was to determine whether visceral adipose tissue, as assessed by abdominal height measurement, affected individual susceptibility to fibrosis in alcoholic patients. Methods We included 127 consecutive alcoholic patients with abnormal liver test findings for whom liver histology data were available. Abdominal height was measured with a Holtain- Kahn abdominal caliper. We carried out univariate comparisons followed by multivariate regression analysis, to investigate the relationship between abdominal height and fibrosis score. Results Abdominal height ( p < 0.005), waist circumference ( p < 0.05), fasting blood glucose concentration ( p < 0.05), serum triglyceride concentration ( p < 0.05), serum bilirubin ( p < 0.005), and BMI ( p = 0.05) were higher, whereas high-density lipoprotein ( HDL) cholesterol level ( p < 0.01) was lower in the 72 patients with significant (F2-F4) fibrosis than in the 55 patients with F0-F1 fibrosis. In multivariate regression analysis, only abdominal height (β = 7.2, p < 0.002) was independently and positively correlated with fibrosis score, which was also negatively correlated with HDL cholesterol level (β = −1.04, p < 0.05). Conclusions We provide the first demonstration that abdominal height may be a predictor of significant fibrosis in patients with ALD. Our findings support a role for visceral fat accumulation, independent of BMI and of metabolic syndrome criteria, in the onset of alcoholic liver damage. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To compare complication rates and short-term outcomes of laparoscopic sacrocolpopexy among obese and non-obese women. Methods: A retrospective multicenter study of 39 obese women and 111 non-obese women was conducted. Obesity was defined as a body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters) above 30. Operative parameters (length of operation, associated procedures, complication rate, and length of hospitalization) and short-term (2months) objective and subjective results were evaluated. Results: The median BMI in the obese group was 30.5 (interquartile range [IQR] 30–32) versus 23 (IQR 21–25) in the non-obese group (P <0.0001). Short-term anatomic results (postoperative stage of prolapse) were comparable in the obese and non-obese groups: stage 0–1, 87.1% versus 91.6% (P =0.60); stage 2, 10.2% versus 5.5% (P =0.60); stage 3–4, 2.5% versus 2.5% (P =0.60). Complication rates were also similar in the obese and non-obese groups: bladder injury, 2.5% versus 5.4% (P =0.77); laparoconversion, 5.1% versus 4.5% (P =0.77). Rates of reoperation (excluding women with de novo urinary stress incontinence) were 12.8% in the obese group and 8.1% in the non-obese group (P =0.58). Conclusion: Laparoscopic sacrocolpopexy has similar complication rates and short-term outcomes among both obese and non-obese women. [Copyright &y& Elsevier]

In multiple change-point analysis, inferring the number of change points is often achieved by minimizing a selection criterion that trades off data fidelity with complexity. We address the open problem of defining a selection criterion adapted to the context of multiple change-point analysis. Our approach is inspired by the Schwarz seminal formulation of the Bayesian information criterion (BIC): similarly, we introduce priors—here describing the occurrence of change points—and we use the Laplace approximation to derive a closed-form expression of the criterion. Differently from this previous work, we take advantage of the a priori information introduced, instead of asymptotically eliminating the dependence on priors. Results obtained on simulated series show a substantial gain in performance versus recent alternative criteria used in multiple change-point analysis. Results also show that the a priori information introduced in our criterion on the regularity of interevent times is the main driver of this substantial performance gain. Methods are motivated by and demonstrated on a meteorological application involving the homogenization of a temperature series. [ABSTRACT FROM AUTHOR]

Abstract: During conscious rest, the mind switches into a state of wandering. Although this rich inner experience occupies a large portion of the time spent awake, how it relates to brain activity has not been well explored. Here, we report the results of a behavioral and functional magnetic resonance imaging (fMRI) study of the continuous resting state in 307 healthy participants. The analysis focused on the relationship between the nature of inner experience and the temporal correlations computed between the low-frequency blood oxygen level-dependent (BOLD) fluctuations (0.01–0.1Hz) of five large-scale modules. The subjects'' self-reported time spontaneously spent on visual mental imagery and/or inner language was used as the behavioral variable. Decreased temporal correlations between modules were revealed when subjects reported more time spent thinking in mental images and inner language. These changes segregated the three modules supporting inner-oriented activities from those associated with sensory-related and externally guided activities. Among the brain areas associated with inner-oriented processing, the module including the lateral parietal and frontal regions (commonly described as being engaged in the manipulation and maintenance of internal information) was implicated in the majority of these effects. The preponderance of segregation appears to be the signature of the spontaneous sequence of thoughts during rest that are not constrained by logic, causality, or even a rigorous temporal organization. In other words, though goal-directed tasks have been demonstrated to rely on specific regional integration, mind wandering can be characterized by widespread modular segregation. Overall, the present study provides evidence that modulation of spontaneous low-frequency fluctuations in the brain is at least partially explained by spontaneous conscious cognition while at rest. [Copyright &y& Elsevier]

Abstract: In climatology and hydrology, univariate Extreme Value Theory has become a powerful tool to model the distribution of extreme events. The Generalized Pareto Distribution (GPD) is routinely applied to model excesses in space or time by letting the two GPD parameters depend on appropriate covariates. Two possible pitfalls of this strategy are the modeling and the interpretation of the scale and shape GPD parameters estimates which are often and incorrectly viewed as independent variables. In this note we first recall a statistical technique that makes the GPD estimates less correlated within a Maximum Likelihood (ML) estimation approach. In a second step we propose novel reparametrizations for two method-of-moments particularly popular in hydrology: the Probability Weighted Moment (PWM) method and its generalized version (GPWM). Finally these three inference methods (ML, PWM and GPWM) are compared and discussed with respect to the issue of correlations. [Copyright &y& Elsevier]

Sex steroids and thyroid hormones play a key role in the development of the central nervous system. The critical role of these hormonal systems may explain the sensitivity of the hypothalamus, the cerebral cortex, and the hippocampus to endocrine-disrupting chemicals (EDC). This review examines the evidence for endocrine disruption of glial-neuronal functions in the hypothalamus, hippocampus, and cerebral cortex. Focus was placed on two well-studied EDC, the insecticide dichlorodiphenyltrichloroethane (DDT) and polychlorinated biphenyls (PCB). DDT is involved in neuroendocrine disruption of the reproductive axis, whereas polychlorinated biphenyls (PCB) interact with both the thyroid hormone- and sex steroid-dependent systems and disturb the neuroendocrine control of reproduction and development of hippocampus and cortex. These results highlight the impact of EDC on the developing nervous system and the need for more research in this area. [ABSTRACT FROM AUTHOR]

Spontaneous brain activity was mapped with functional MRI (fMRI) in a sample of 180 subjects while in a conscious resting-state condition. With the use of independent component analysis (ICA) of each individual fMRI signal and classification of the ICA-defined components across subjects, a set of 23 resting-state networks (RNs) was identified. Functional connectivity between each pair of RNs was assessed using temporal correlation analyses in the 0.01- to 0.1-Hz frequency band, and the corresponding set of correlation coefficients was used to obtain a hierarchical clustering of the 23 RNs. At the highest hierarchical level, we found two anticorrelated systems in charge of intrinsic and extrinsic processing, respectively. At a lower level, the intrinsic system appears to be partitioned in three modules that subserve generation of spontaneous thoughts (M1a; default mode), inner maintenance and manipulation of information (M1b), and cognitive control and switching activity (M1c), respectively. The extrinsic system was found to be made of two distinct modules: one including primary somatosensory and auditory areas and the dorsal attentional network (M2a) and the other encompassing the visual areas (M2b). Functional connectivity analyses revealed that M1b played a central role in the functioning of the intrinsic system, whereas M1c seems to mediate exchange of information between the intrinsic and extrinsic systems. [ABSTRACT FROM AUTHOR]

Abstract: The use of organo-montmorillonite as nanofiller for the preparation of polymer nanocomposites still attracts a lot of attention both on experimental and industrial scale. In order to enlarge the range of organo-montmorillonites available for this application, supercritical carbon dioxide (scCO2) was used as a medium for the organomodification process. This environmentally friendly solvent showed a great potential to obtain ready-to-use organo-montmorillonite powders. Intercalation with high degrees of exchange was obtained when the surfactants (alkyl ammonium, phosphonium, and imidazolium salts) were in the liquid state at the reaction temperature. The addition of a small quantity of co-solvent enabled the intercalation of solid surfactants, such as those bearing hydroxyl or carboxyl groups. Basal spacings of montmorillonite modified in scCO2 corresponded to those measured for organo-montmorillonite prepared in the wet process. A detailed investigation of the reaction conditions was finally performed in order to up-scale the process. [Copyright &y& Elsevier]

Abstract: Polyamide-6 nanocomposites were prepared from a new phosphonium organoclay obtained at pilot scale in supercritical carbon dioxide (scCO2) and a commercially available ammonium modified-silicate. The composites were homogenised by twin-screw extrusion, then specimens for testing were prepared by injection moulding. The clay content of the composites was varied from 0 to 7 vol.% in 7 steps. The clays were characterised in detail; they differed in their surface coverage and gallery structure, while their particle size was similar and their surface energy differed only slightly. X-ray diffraction, electronic microscopy and rheology were used for the characterisation of composite structure. Different gallery structure of the clays led to dissimilar extent of exfoliation. The phosphonium organoclay exfoliated better in PA than the silicate treated with the ammonium salt in spite of its smaller surface coverage. The nanocomposites showed the usual complex structure: besides individual platelets and intercalated stacks, large particles were also present and the development of a silicate network could be shown at large clay contents. Quantitative determination of the extent of reinforcement revealed two determining factors: contact surface and strength of interaction. The first increases with exfoliation, but the latter decreases as an effect of organophilisation. The extent of exfoliation was also estimated quantitatively, and the calculation confirmed the results of qualitative evaluation showing larger extent of exfoliation for the scCO2-prepared phosphonium clay. [ABSTRACT FROM AUTHOR]

Background & Aims: Adipose tissue is an important source of cytokines. Excess weight is an independent risk factor for steatosis, acute alcoholic hepatitis (AAH), and cirrhosis in patients with alcoholic liver disease (ALD). In this study, we investigated the role of adipose tissue in human ALD. Patients and methods: Fifty patients with ALD underwent liver and abdominal subcutaneous adipose tissue biopsies and supplied blood samples for the investigation of cytokine gene expression and secretion, as well as liver histology. Results: The levels of TNF-α and IL-10 in adipose tissue were higher in patients with AAH. IL-10 level in adipose tissue was also correlated with fibrosis score. TNF-α gene expression in adipose tissue was correlated with Maddrey score, blood C-reactive protein (CRP) concentration and liver IL-6 concentration. IL-6 production levels in the liver were higher in patients with AAH and correlated with AAH score, liver histological lesions, liver TNF-α concentration, Maddrey score, and blood CRP concentration. Plasma concentrations of soluble forms of TNF-receptor were correlated with inflammatory lesions in the liver, Maddrey score and fibrosis score. Conclusion: In patients with ALD, inflammation occurs not only in the liver, but also in the adipose tissue. Adipose tissue inflammation is correlated with the severity of pathological features in the liver. Our findings may account for the harmful interactions between body mass index, AAH, fibrosis, and cirrhosis in alcoholic patients. [Copyright &y& Elsevier]

In this paper the author explains how, besides her psychoanalytic experience, the practise of baby-observation following Mrs Bick's method allowed her to construct her technique in therapies of parents-baby relationship. After a short description of this method, the author details every aspect of the observation and her application in the therapies. Some clinical vignettes are included. [ABSTRACT FROM AUTHOR]

Abstract: Eukaryotic/archaeal translation initiation factor 2 (e/aIF2) is a heterotrimeric GTPase that plays a key role in selection of the correct start codon on messenger RNA. This review integrates structural and functional data to discuss the involvement of the three subunits in initiator tRNA binding. A possible role of the peripheral subunits in modulating the guanine nucleotide cycle on the core subunit is also addressed. [Copyright &y& Elsevier]

Background: Bearing in mind the mechanisms involved in nonalcoholic fatty liver disease, this study aims to verify whether metabolic syndrome or its various individual components are independent predictive factors for steatosis ≥10% in alcoholic patients. Methods: This study included 281 consecutive alcoholic patients with abnormal liver tests and either normal liver histology or steatosis <10% ( n = 119) or steatosis ≥10% ( n = 162). Logistic regression analysis was used to study the relationship between metabolic syndrome components and various risk factors and the presence of steatosis ≥10%. We assessed apolipoprotein A1 (ApoA-1) levels, a major protein component of plasma high-density lipoprotein (HDL), rather than HDL-cholesterol levels. Results: Plasma ApoA-1 levels ( p < 0.01), body mass index (BMI) ( p < 0.01), and waist circumference ( p < 0.05) were significantly higher in patients with steatosis ≥10% than in patients with normal liver histology or steatosis <10%. A higher percentage of patients with steatosis ≥10% had high blood pressure ( p = 0.003) than patients with normal liver histology or steatosis <10%. In the logistic regression, ApoA-1 [odds ratio (OR) = 1.57 (1.10–2.22)], BMI [OR = 1.10 (1.01–1.23)], and high blood pressure [OR = 1.84 (1.10–3.06)] were positively and independently correlated with the presence of steatosis ≥10%. In the multivariate regression high blood pressure was independently and positively correlated with steatosis score ( r = 0.55 ± 0.26; p < 0.05). On the other hand, when the presence of high blood pressure was the dependent variable, the presence of steatosis ≥10% positively and independently correlated with it [OR = 1.82 (1.05–3.15)]. Conclusion: In alcoholic patients without fibrosis, ApoA-1, BMI, and high blood pressure on the next morning after the admission were predictive of steatosis ≥10%. High blood pressure was the only metabolic syndrome component associated with the presence of alcoholic steatosis ≥10% and was not correlated with other metabolic syndrome components. These findings suggest that steatosis mechanisms are different in alcoholic and nonalcoholic fatty liver. [ABSTRACT FROM AUTHOR]

Abstract: In this study, the preparation of organoclays via a new process using supercritical carbon dioxide is described. This method turns out to be very efficient with various surfactants, in particular nonwater-soluble alkylphosphonium salts. The influence of the surfactant as well as of the clay nature on the thermal stability of the organoclay is evaluated by thermogravimetric analysis. Phosphonium-based montmorillonites are up to 90°C more stable than ammonium-based montmorillonites. Moreover, the use of hectorite adds another 40°C of thermal stability to the phosphonium-modified clays. These organomodified clays have been melt-blended with polyamide 6 and morphology as well as fire properties of the nanocomposites are discussed, in terms of influence of the stability of organoclays. For the first time, comparison of nanocomposites based on clay organomodified by ammonium and phosphonium salts of the very same structure is reported. [Copyright &y& Elsevier]

Abstract: A solid CoII complex with l-proline as ligand was synthesized and fully characterized using spectroscopic studies, magnetic data, and DFT calculations. Dioxygen scavenging properties were investigated by UV/Vis spectroscopy and oxymetry techniques. The Co-proline system presented very interesting properties in matter of oxygen absorption capacity both in solution and incorporated in a polymer matrix. [Copyright &y& Elsevier]