Rhenium-Based Electrocatalysts for Water Splitting.

Due to the contamination and global warming problems, it is necessary to search for alternative environmentally friendly energy sources. In this area, hydrogen is a promising alternative. Hydrogen is even more promising, when it is obtained through water electrolysis operated with renewable energy sources.

Nonequilibrium thermodynamics of the asymmetric Sherrington-Kirkpatrick model.

Most natural systems operate far from equilibrium, displaying time-asymmetric, irreversible dynamics characterized by a positive entropy production while exchanging energy and matter with the environment. Although stochastic thermodynamics underpins the irreversible dynamics of small systems, the nonequilibrium thermodynamics of larger, more complex systems remains unexplored. Here, we investigate the asymmetric Sherrington-Kirkpatrick model with synchronous and asynchronous updates as a prototypical example of large-scale nonequilibrium processes.

Recurrent, nonequilibrium systems and the Markov blanket assumption.

Markov blankets - statistical independences between system and environment - have become popular to describe the boundaries of living systems under Bayesian views of cognition. The intuition behind Markov blankets originates from considering acyclic, atemporal networks. In contrast, living systems display recurrent, nonequilibrium interactions that generate pervasive couplings between system and environment, making Markov blankets highly unusual and restricted to particular cases.

How particular is the physics of the free energy principle?

The free energy principle (FEP) states that any dynamical system can be interpreted as performing Bayesian inference upon its surrounding environment. Although, in theory, the FEP applies to a wide variety of systems, there has been almost no direct exploration or demonstration of the principle in concrete systems. In this work, we examine in depth the assumptions required to derive the FEP in the simplest possible set of systems - weakly-coupled non-equilibrium linear stochastic systems.

A unifying framework for mean-field theories of asymmetric kinetic Ising systems.

Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods have been proposed for their analysis, each based on unique assumptions about the system's temporal evolution. This disparity of approaches makes it challenging to systematically advance mean-field methods beyond previous contributions.

Critical integration in neural and cognitive systems: Beyond power-law scaling as the hallmark of soft assembly.

Inspired by models of self-organized criticality, a family of measures quantifies long-range correlations in neural and behavioral activity in the form of self-similar (e.g., power-law scaled) patterns across a range of scales.

Integrated information in the thermodynamic limit.

The capacity to integrate information is a prominent feature of biological, neural, and cognitive processes. Integrated Information Theory (IIT) provides mathematical tools for quantifying the level of integration in a system, but its computational cost generally precludes applications beyond relatively small models. In consequence, it is not yet well understood how integration scales up with the size of a system or with different temporal scales of activity, nor how a system maintains integration as it interacts with its environment.

Exploring Criticality as a Generic Adaptive Mechanism.

The activity of many biological and cognitive systems is not poised deep within a specific regime of activity. Instead, they operate near points of critical behavior located at the boundary between different phases. Certain authors link some of the properties of criticality with the ability of living systems to generate autonomous or intrinsically generated behavior.

Adaptation to criticality through organizational invariance in embodied agents.

Many biological and cognitive systems do not operate deep within one or other regime of activity. Instead, they are poised at critical points located at phase transitions in their parameter space. The pervasiveness of criticality suggests that there may be general principles inducing this behaviour, yet there is no well-founded theory for understanding how criticality is generated at a wide span of levels and contexts.

Extended Neural Metastability in an Embodied Model of Sensorimotor Coupling.

The hypothesis that brain organization is based on mechanisms of metastable synchronization in neural assemblies has been popularized during the last decades of neuroscientific research. Nevertheless, the role of body and environment for understanding the functioning of metastable assemblies is frequently dismissed. The main goal of this paper is to investigate the contribution of sensorimotor coupling to neural and behavioral metastability using a minimal computational model of plastic neural ensembles embedded in a robotic agent in a behavioral preference task.

Self-organized criticality, plasticity and sensorimotor coupling. Explorations with a neurorobotic model in a behavioural preference task.

During the last two decades, analysis of 1/ƒ noise in cognitive science has led to a considerable progress in the way we understand the organization of our mental life. However, there is still a lack of specific models providing explanations of how 1/ƒ noise is generated in coupled brain-body-environment systems, since existing models and experiments typically target either externally observable behaviour or isolated neuronal systems but do not address the interplay between neuronal mechanisms and sensorimotor dynamics. We present a conceptual model of a minimal neurorobotic agent solving a behavioural task that makes it possible to relate mechanistic (neurodynamic) and behavioural levels of description.

Quantifying long-range correlations and 1/f patterns in a minimal experiment of social interaction.

In recent years, researchers in social cognition have found the "perceptual crossing paradigm" to be both a theoretical and practical advance toward meeting particular challenges. This paradigm has been used to analyze the type of interactive processes that emerge in minimal interactions and it has allowed progress toward understanding of the principles of social cognition processes. In this paper, we analyze whether some critical aspects of these interactions could not have been observed by previous studies.

Pedometers to enhance physical activity in COPD: a randomised controlled trial.

Physical inactivity is a cardinal feature of chronic obstructive pulmonary disease (COPD), and is associated with increased morbidity and mortality. Pedometers, which have been used in healthy populations, might also increase physical activity in patients with COPD. COPD patients taking part in a 3-month individualised programme to promote an increase in their daily physical activity were randomised to either a standard programme of physical activity encouragement alone, or a pedometer-based programme.

Intermittent animal behavior: the adjustment-deployment dilemma.

Intermittency is ubiquitous in animal behavior. We depict a coordination problem that is part of the more general structure of intermittent adaptation: the adjustment-deployment dilemma. It captures the intricate compromise between the time spent in adjusting a response and the time used to deploy it: The adjustment process improves fitness with time, but during deployment fitness of the solution decays as environmental conditions change.

The situated HKB model: how sensorimotor spatial coupling can alter oscillatory brain dynamics.

Despite the increase of both dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the Haken-Kelso-Bunz (HKB) model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose "brain" is modeled by the HKB equation.

Control of triglyceride storage by a WD40/TPR-domain protein.

Obesity is a metabolic disorder related to improper control of energy uptake and expenditure, which results in excessive accumulation of body fat. Initial insights into the genetic pathways that regulate energy metabolism have been provided by a discrete number of obesity-related genes that have been identified in mammals. Here, we report the identification of the adipose (adp) gene, the mutation of which causes obesity in Drosophila.