Shedding light on El Farol

We mathematize El Farol bar problem and transform it into a workable model. In general, the average convergence to optimality at the collective level is trivial and does not even require any intelligence on the side of agents. Secondly, specializing to a particular ensemble of continuous strategies yields a model similar to the Minority Game. Statistical physics of disordered systems allows us to derive a complete understanding of the complex behavior of this model, on the basis of its phase diagram.Comment: 8 pages, 5 figure

Experimental and numerical research activity on a packed bed TES system

This paper presents the results of experimental and numerical research activities on a packed bed sensible thermal energy storage (TES) system. The TES consists of a cylindrical steel tank filled with small alumina beads and crossed by air used as the heat transfer fluid. Experimental tests were carried out hile varying some operating parameters such as the mass flow rate, the inlet–outlet temperature thresholds and the aspect ratio (length over diameter). Numerical simulations were carried out using a one-dimensional model, specifically developed in the Matlab-Simulink environment and a 2D axisymmetric model based on the ANSYS-Fluent platform. Both models are based on a two-equation transient approach to calculate fluid and solid phase temperatures. Thermodynamic properties were considered to be temperature-dependent and, in the Computational Fluid Dynamics (CFD) model, variable porosity of the bed in the radial direction, thermal losses and the effective conductivity of the alumina beads were also considered. The simulation results of both models were compared to the experimental ones, showing good agreement. The one-dimensional model has the advantage of predicting the axial temperature distribution with a very low computational cost, but it does not allow calculation of the correct energy stored when the temperature distribution is strongly influenced by the wall. To overcome this problem a 2D CFD model was used in this work

STZ-diabetic rat heart maintains developed tension amplitude by increasing sarcomere length and crossbridge density

New Findings: What is the central question of this study? In the papillary muscle from type I diabetic rats, does diabetes-associated altered ventricular function result from changes of acto-myosin interactions and are these modifications attributable to a possible sarcomere rearrangement? What is the main finding and its importance? For the first time, we showed that type-I diabetes altered sarcomeric ultrastructure, as seen by transmission electron microscopy, consistent with physiological parameters. The diabetic condition induced slower timing parameters, which is compatible with a diastolic dysfunction. At the sarcomeric level, augmented β-myosin heavy chain content and increased sarcomere length and crossbridges' number preserve myocardial stroke and could concur to maintain the ejection fraction. Abstract: We investigated whether diabetes-associated altered ventricular function, in a type I diabetes animal model, results from a modification of acto-myosin interactions, through the in vitro recording of left papillary muscle mechanical parameters and examination of sarcomere morphology by transmission electron microscopy (TEM). Experiments were performed on streptozotocin-induced diabetic and age-matched control female Wistar rats. Mechanical isometric and isotonic indexes and timing parameters were determined. Using Huxley's equations, we calculated mechanics, kinetics and energetics of myosin crossbridges. Sarcomere length and A-band length were measured on TEM images. Type I and III collagen and β-myosin heavy chain (MHC) expression were determined by immunoblotting. No variation in resting and developed tension or maximum extent of shortening was evident between groups, but diabetic rats showed lower maximum shortening velocity and prolonged timing parameters. Compared to controls, diabetics also displayed a higher number of crossbridges with lower unitary force. Moreover, no change in type I and III collagen was associated to diabetes, but pathological rats showed a two-fold enhancement of β-MHC content and longer sarcomeres and A-band, detected by ultrastructural morphometry. Overall, these data address whether a preserved systolic function accompanied by an altered diastolic phase results from a recruitment of super-relaxed myosin heads or the phosphorylation of the regulatory light chain site in myosin. Although the early signs of diabetic cardiomyopathy were well expressed, the striking finding of our study was that, in diabetics, sarcomere modification may be a possible compensatory mechanism that preserves systolic function

Multi-Agent Complex Systems and Many-Body Physics

Multi-agent complex systems comprising populations of decision-making particles, have many potential applications across the biological, informational and social sciences. We show that the time-averaged dynamics in such systems bear a striking resemblance to conventional many-body physics. For the specific example of the Minority Game, this analogy enables us to obtain analytic expressions which are in excellent agreement with numerical simulations.Comment: Accepted for publication in Europhysics Letter

Detection of Solar Coronal Mass Ejections from Raw Images with Deep Convolutional Neural Networks

Coronal Mass Ejections (CMEs) are massive releases of plasma from the solar corona. When the charged material is ejected towards the Earth, it can cause geomagnetic storms and severely damage electronic equipment and power grids. Early detection of CMEs is therefore crucial for damage containment. In this paper, we study detection of CMEs from sequential images of the solar corona acquired by a satellite. A low-complexity deep neural network is trained to process the raw images, ideally directly on the satellite, in order to provide early alerts

The aggression and behavioral abnormalities associated with monoamine oxidase A deficiency are rescued by acute inhibition of serotonin reuptake

The termination of serotonin (5-hydroxytryptamine, 5-HT) neurotransmission is regulated by its uptake by the 5-HT transporter (5-HTT), as well as its degradation by monoamine oxidase (MAO)-A. MAO-A deficiency results in a wide set of behavioral alterations, including perseverative behaviors and social deficits. These anomalies are likely related to 5-HTergic homeostatic imbalances; however, the role of 5-HTT in these abnormalities remains unclear. To ascertain the role of 5-HTT in the behavioral anomalies associated to MAO-A deficiency, we tested the behavioral effects of its blocker fluoxetine on perseverative, social and aggressive behaviors in transgenic animals with hypomorphic or null-allele MAO-A mutations. Acute treatment with 5-HTT blocker fluoxetine (10 mg/kg, i.p.) reduced aggressive behavior in MAO-A knockout (KO) mice and social deficits in hypomorphic MAO-ANeo mice. Furthermore, this treatment also reduced perseverative responses (including marble burying and water mist-induced grooming) in both MAO-A mutant genotypes. Both MAO-A mutant lines displayed significant reductions in 5-HTT expression across the prefrontal cortex, amygdala and striatum, as quantified by immunohistochemical detection; however, the down-regulation of 5-HTT in MAO-ANeo mice was more pervasive and widespread than in their KO counterparts, possibly indicating a greater ability of the hypomorphic line to enact compensatory mechanisms with respect to 5-HT homeostasis. Collectively, these findings suggest that the behavioral deficits associated with low MAO-A activity may reflect developmental alterations of 5-HTT within 5-HTergic neurons. Furthermore, the translational implications of our results highlight 5-HT reuptake inhibition as an interesting approach for the control of aggressive outbursts in MAO-A deficient individuals

Towards Autopoietic Computing

A key challenge in modern computing is to develop systems that address complex, dynamic problems in a scalable and efficient way, because the increasing complexity of software makes designing and maintaining efficient and flexible systems increasingly difficult. Biological systems are thought to possess robust, scalable processing paradigms that can automatically manage complex, dynamic problem spaces, possessing several properties that may be useful in computer systems. The biological properties of self-organisation, self-replication, self-management, and scalability are addressed in an interesting way by autopoiesis, a descriptive theory of the cell founded on the concept of a system's circular organisation to define its boundary with its environment. In this paper, therefore, we review the main concepts of autopoiesis and then discuss how they could be related to fundamental concepts and theories of computation. The paper is conceptual in nature and the emphasis is on the review of other people's work in this area as part of a longer-term strategy to develop a formal theory of autopoietic computing.Comment: 10 Pages, 3 figure

The Heliospheric Space Weather Center: A novel space weather service

The Heliospheric Space Weather Center project is the result of the synergy between the Aerospace Logistics Technology Engineering Company (ALTEC S.p.A.) and the INAF-Astrophysical Observatory of Torino, both located in Turin, Italy. The main goal of this project is to provide space weather medium and short-term forecast, by combining remote-sensing and in situ open data with novel data analysis technologies, giving to scientists the possibility of designing, implementing, and validating space-weather algorithms using extensive data sets

Deep-Manager: a versatile tool for optimal feature selection in live-cell imaging analysis

One of the major problems in bioimaging, often highly underestimated, is whether features extracted for a discrimination or regression task will remain valid for a broader set of similar experiments or in the presence of unpredictable perturbations during the image acquisition process. Such an issue is even more important when it is addressed in the context of deep learning features due to the lack of a priori known relationship between the black-box descriptors (deep features) and the phenotypic properties of the biological entities under study. In this regard, the widespread use of descriptors, such as those coming from pre-trained Convolutional Neural Networks (CNNs), is hindered by the fact that they are devoid of apparent physical meaning and strongly subjected to unspecific biases, i.e., features that do not depend on the cell phenotypes, but rather on acquisition artifacts, such as brightness or texture changes, focus shifts, autofluorescence or photobleaching. The proposed Deep-Manager software platform offers the possibility to efficiently select those features having lower sensitivity to unspecific disturbances and, at the same time, a high discriminating power. Deep-Manager can be used in the context of both handcrafted and deep features. The unprecedented performances of the method are proven using five different case studies, ranging from selecting handcrafted green fluorescence protein intensity features in chemotherapy-related breast cancer cell death investigation to addressing problems related to the context of Deep Transfer Learning. Deep-Manager, freely available at https://github.com/BEEuniroma2/Deep-Manager, is suitable for use in many fields of bioimaging and is conceived to be constantly upgraded with novel image acquisition perturbations and modalities

Enhanced endocannabinoid-mediated modulation of rostromedial tegmental nucleus drive onto dopamine neurons in sardinian alcohol-preferring rats

The progressive predominance of rewarding effects of addictive drugs over their aversive properties likely contributes to the transition from drug use to drug dependence. By inhibiting the activity of DA neurons in the VTA, GABA projections from the rostromedial tegmental nucleus (RMTg) are well suited to shift the balance between drug-induced reward and aversion. Since cannabinoids suppress RMTg inputs to DA cells and CB1 receptors affect alcohol intake in rodents, we hypothesized that the endocannabinoid system, by modulating this pathway, might contribute to alcohol preference. Here we found that RMTg afferents onto VTA DA neurons express CB1 receptors and display a 2-arachidonoylglycerol (2-AG)-dependent form of short-term plasticity, that is, depolarization-induced suppression of inhibition (DSI). Next, we compared rodents with innate opposite alcohol preference, the Sardinian alcohol-preferring (sP) and alcohol-nonpreferring (sNP) rats. We found that DA cells from alcohol-naive sP rats displayed a decreased probability of GABA release and a larger DSI. This difference was due to the rate of 2-AG degradation. In vivo, we found a reduced RMTg-induced inhibition of putative DA neurons in sP rats that negatively correlated with an increased firing. Finally, alcohol failed to enhance RMTg spontaneous activity and to prolong RMTg-induced silencing of putative DA neurons in sP rats. Our results indicate functional modifications of RMTg projections to DA neurons that might impact the reward/aversion balance of alcohol attributes, which may contribute to the innate preference observed in sP rats and to their elevated alcohol intak