The permeability of a pore structure is typically described by stochastic representations of its geometrical attributes (e.g. pore-size distribution, porosity, coordination number). Database-driven ...numerical solvers for large model domains can only accurately predict large-scale flow behavior when they incorporate upscaled descriptions of that structure. The upscaling is particularly challenging for rocks with multimodal porosity structures such as carbonates, where several different type of structures (e.g. micro-porosity, cavities, fractures) are interacting. It is the connectivity both within and between these fundamentally different structures that ultimately controls the porosity-permeability relationship at the larger length scales. Recent advances in machine learning techniques combined with both numerical modelling and informed structural analysis have allowed us to probe the relationship between structure and permeability much more deeply. We have used this integrated approach to tackle the challenge of upscaling multimodal and multiscale porous media. We present a novel method for upscaling multimodal porosity-permeability relationships using machine learning based multivariate structural regression. A micro-CT image of Estaillades limestone was divided into small 60
and 120
sub-volumes and permeability was computed using the Darcy-Brinkman-Stokes (DBS) model. The microporosity-porosity-permeability relationship from Menke et al. (Earth Arxiv, https://doi.org/10.31223/osf.io/ubg6p , 2019) was used to assign permeability values to the cells containing microporosity. Structural attributes (porosity, phase connectivity, volume fraction, etc.) of each sub-volume were extracted using image analysis tools and then regressed against the solved DBS permeability using an Extra-Trees regression model to derive an upscaled porosity-permeability relationship. Ten test cases of 360
voxels were then modeled using Darcy-scale flow with this machine learning predicted upscaled porosity-permeability relationship and benchmarked against full DBS simulations, a numerically upscaled Darcy flow model, and a Kozeny-Carman model. All numerical simulations were performed using GeoChemFoam, our in-house open source pore-scale simulator based on OpenFOAM. We found good agreement between the full DBS simulations and both the numerical and machine learning upscaled models, with the machine learning model being 80 times less computationally expensive. The Kozeny-Carman model was a poor predictor of upscaled permeability in all cases.
Reward-evoked dopamine transients are well established as prediction errors. However, the central tenet of temporal difference accounts-that similar transients evoked by reward-predictive cues also ...function as errors-remains untested. In the present communication we addressed this by showing that optogenetically shunting dopamine activity at the start of a reward-predicting cue prevents second-order conditioning without affecting blocking. These results indicate that cue-evoked transients function as temporal-difference prediction errors rather than reward predictions.
•Antisocial personality and psychopathy are severe personality conditions.•Inconsistencies in the characterization of these conditions plague research.•Over-reliance on scoring behavior may account ...for these failures.•These conditions account for the majority of failed treatment efforts.•Biocognitive approach provides better classification and treatment options.
Antisocial behavior is a heterogeneous construct that can be divided into subtypes, such as antisocial personality and psychopathy. The adverse consequences of antisocial behavior produce great burden for the perpetrators, victims, family members, and for society at-large. The pervasiveness of antisocial behavior highlights the importance of precisely characterizing subtypes of antisocial individuals and identifying specific factors that are etiologically related to such behaviors to inform the development of targeted treatments. The goals of the current review are (1) to briefly summarize research on the operationalization and assessment of antisocial personality and psychopathy; (2) to provide an overview of several existing treatments with the potential to influence antisocial personality and psychopathy; and (3) to present an approach that integrates and uses biological and cognitive measures as starting points to more precisely characterize and treat these individuals. A focus on integrating factors at multiple levels of analysis can uncover person-specific characteristics and highlight potential targets for treatment to alleviate the burden caused by antisocial behavior.
Induction of general anesthesia frequently induces arterial hypotension, which is often treated with a vasopressor, such as phenylephrine. As a pure α-agonist, phenylephrine is conventionally ...considered to solely induce arterial vasoconstriction and thus increase cardiac afterload but not cardiac preload. In specific circumstances, however, phenylephrine may also contribute to an increase in venous return and thus cardiac output (CO). The aim of this study is to describe the initial time course of the effects of phenylephrine on various hemodynamic variables and to evaluate the ability of advanced hemodynamic monitoring to quantify these changes through different hemodynamic variables. In 24 patients, after induction of anesthesia, during the period before surgical stimulus, phenylephrine 2 µg kg
−1
was administered when the MAP dropped below 80% of the awake state baseline value for > 3 min. The mean arterial blood pressure (MAP), heart rate (HR), end-tidal CO
2
(EtCO
2
), central venous pressure (CVP), stroke volume (SV), CO, pulse pressure variation (PPV), stroke volume variation (SVV) and systemic vascular resistance (SVR) were recorded continuously. The values at the moment before administration of phenylephrine and 5(T
5
) and 10(T
10
) min thereafter were compared. After phenylephrine, the mean(SD) MAP, SV, CO, CVP and EtCO
2
increased by 34(13) mmHg, 11(9) mL, 1.02(0.74) L min
−1
, 3(2.6) mmHg and 4.0(1.6) mmHg at T
5
respectively, while both dynamic preload variables decreased: PPV dropped from 20% at baseline to 9% at T
5
and to 13% at T
10
and SVV from 19 to 11 and 14%, respectively. Initially, the increase in MAP was perfectly aligned with the increase in SVR, until 150 s after the initial increase in MAP, when both curves started to dissociate. The dissociation of the evolution of MAP and SVR, together with the changes in PPV, CVP, EtCO
2
and CO indicate that in patients with anesthesia-induced hypotension, phenylephrine increases the CO by virtue of an increase in cardiac preload.
► We mapped indicators for biodiversity and ecosystem services across Europe. ► We compared these maps with the conservation status of protected habitats. ► Habitats in favourable conservation status ...supplied more ecosystem services. ► Habitats in favourable conservation status had higher biodiversity.
In the European Union (EU) efforts to conserve biodiversity have been consistently directed towards the protection of habitats and species through the designation of protected areas under the Habitats Directive (92/43/ECC). These biodiversity conservation efforts also have the potential to maintain or improve the supply of ecosystem services; however, this potential has been poorly explored across Europe. This paper reports on a spatial assessment of the relationships between biodiversity, ecosystem services, and conservation status of protected habitats at European scale. We mapped at 10km resolution ten spatial proxies for ecosystem service supply (four provisioning services, five regulating services and one cultural service) and three proxies for biodiversity (Mean Species Abundance, tree species diversity and the relative area of Natura 2000 sites). Indicators for biodiversity and aggregated ecosystem service supply were positively related but this relationship was influenced by the spatial trade-offs among ecosystem services, in particular between crop production and regulating ecosystem services. Using multinomial logistic regression models we demonstrated that habitats in a favourable conservation status provided more biodiversity and had a higher potential to supply, in particular, regulating and cultural ecosystem services than habitats in an unfavourable conservation status. This information is of utmost importance in identifying regions in which measures are likely to result in cost-effective progress towards both new biodiversity conservation and ecosystem services targets adopted by the Convention on Biological Diversity (CBD) and the EU Biodiversity Strategy to 2020.
Dopamine neurons are proposed to signal the reward prediction error in model-free reinforcement learning algorithms. This term represents the unpredicted or 'excess' value of the rewarding event, ...value that is then added to the intrinsic value of any antecedent cues, contexts or events. To support this proposal, proponents cite evidence that artificially-induced dopamine transients cause lasting changes in behavior. Yet these studies do not generally assess learning under conditions where an endogenous prediction error would occur. Here, to address this, we conducted three experiments where we optogenetically activated dopamine neurons while rats were learning associative relationships, both with and without reward. In each experiment, the antecedent cues failed to acquire value and instead entered into associations with the later events, whether valueless cues or valued rewards. These results show that in learning situations appropriate for the appearance of a prediction error, dopamine transients support associative, rather than model-free, learning.
Rhythmic joint coordination is ubiquitous in daily-life human activities. In order to coordinate their actions towards shared goals, individuals need to co-regulate their timing and move together at ...the collective level of behavior. Remarkably, basic forms of coordinated behavior tend to emerge spontaneously as long as two individuals are exposed to each other's rhythmic movements. The present study investigated the dynamics of spontaneous dyadic entrainment, and more specifically how they depend on the sensory modalities mediating informational coupling. By means of a novel interactive paradigm, we showed that dyadic entrainment systematically takes place during a minimalistic rhythmic task despite explicit instructions to ignore the partner. Crucially, the interaction was organized by clear dynamics in a modality-dependent fashion. Our results showed highly consistent coordination patterns in visually-mediated entrainment, whereas we observed more chaotic and more variable profiles in the auditorily-mediated counterpart. The proposed experimental paradigm yields empirical evidence for the overwhelming tendency of dyads to behave as coupled rhythmic units. In the context of our experimental design, it showed that coordination dynamics differ according to availability and nature of perceptual information. Interventions aimed at rehabilitating, teaching or training sensorimotor functions can be ultimately informed and optimized by such fundamental knowledge.
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