A gift for gratitude and cooperative behavior. Brain and cognitive effects

Recently, different psychological studies have been interested in identifying the factors that regulate the development and maintenance of long-lasting interpersonal and social relationships. Specifically, the present research explored the link between gift exchange, gratitude and cognitive effects. The behavioral performance and neural activity of 32 participants were recorded during a cooperative game to be played before and after gift exchange. Specifically, participants had to perform the task coupled with a dear friend. Half of the couples were asked to exchange a gift before the task performance; the other half was asked to exchange a gift halfway through the task performance. For hemodynamic brain responses, functional near-infrared spectroscopy was used. Results showed that an increase in cognitive performance occurred after the exchange of gifts, with improved accuracy and lower response times in task performance. Regarding hemodynamic responses, an increase in oxygenated hemoglobin was detected, especially in the dorsolateral prefrontal cortex following the gift exchange. Furthermore, it was observed that gift exchange before the beginning of the task increased the performance level. The present study provides a significant contribution to the identification of those factors that enable the increased cognitive performance based on cooperative relationships

Popularizing Electoral Politics: Change in the 2016 U.S. Presidential Race

This special issue of the European Journal of American Studies examines the popularization of electoral politics during the 2016 U.S. Presidential Election. The popularization processes include the rise of populism penetrating the U.S. political landscape; a media focus on human interest, rather than policy substance questions; personality politics and celebrity culture at the center stage of the election; and the appropriation and dissemination of popular culture discourses by social media users. The articles draw from transdisciplinary American Studies approaches to tackle a range of issues which arose during the election, from contestations of “American-ness” and competing narratives of truth—or “post-truth”—to questions of campaign finance and displays of violence, verbal and physical. The issue also takes a closer look at specific expressions of popular culture as reflected in the media, specifically in relation to the rise of nativism and the alt-right movement, the political impact of comedy on the election, and the significance of memes in the battle over image and meaning-making. The processes of popularizing electoral politics of the 2016 race had distinct consequences, not only in shaping political culture as we know it, but also in destabilizing established rules of political conduct

Collective predator evasion: Putting the criticality hypothesis to the test

According to the criticality hypothesis, collective biological systems should operate in a special parameter region, close to so-called critical points, where the collective behavior undergoes a qualitative change between different dynamical regimes. Critical systems exhibit unique properties, which may benefit collective information processing such as maximal responsiveness to external stimuli. Besides neuronal and gene-regulatory networks, recent empirical data suggests that also animal collectives may be examples of self-organized critical systems. However, open questions about self-organization mechanisms in animal groups remain: Evolutionary adaptation towards a group-level optimum (group-level selection), implicitly assumed in the "criticality hypothesis", appears in general not reasonable for fission-fusion groups composed of non-related individuals. Furthermore, previous theoretical work relies on non-spatial models, which ignore potentially important self-organization and spatial sorting effects. Using a generic, spatially-explicit model of schooling prey being attacked by a predator, we show first that schools operating at criticality perform best. However, this is not due to optimal response of the prey to the predator, as suggested by the "criticality hypothesis", but rather due to the spatial structure of the prey school at criticality. Secondly, by investigating individual-level evolution, we show that strong spatial self-sorting effects at the critical point lead to strong selection gradients, and make it an evolutionary unstable state. Our results demonstrate the decisive role of spatio-temporal phenomena in collective behavior, and that individual-level selection is in general not a viable mechanism for self-tuning of unrelated animal groups towards criticality

Models of collaboration between psychologist and family doctor: a systematic review of primary care psychology

open2noThe prevalence of psychological suffering is greater than the actual request for clinical consultation in Europe (Alonso et al., 2004). In Italy, no more than 5.5% of the population requested psychological assistance during lifetime (Miglioretti et al., 2008). There are different obstacles that prevent the access to mental health services, such as economic restrictions (Mulder et al., 2011), cultural prejudice (Kim et al., 2010), and lack of knowledge about the service providers that can answer to the patient’s psychological needs (Molinari et al., 2012). Therefore, the psychologist is often consulted as a last resort, only after everything else has failed, when problems have become severe, and thus requiring longer, more intensive, and expensive treatments. The introduction of the Primary Care Psychologist, a professional who works together with the family doctor, allows to overcome the above-mentioned problems and intercept unexpressed needs for psychological assistance. This professional role is operating in many countries since several years. In this study, current literature concerning different models of collaboration between physician and psychologist, in Europe and in Italy, was reviewed. A systematic search of Web of Science (ISI), Pubmed, Scopus, and PsychINFO was conducted using the initial search terms Primary Care Psychologist, Family Doctor, Primary Care, Collaborative Practice, and several relevant papers were identified. The review has shown the improved quality of care when mental health care is integrated into primary. Analyzing how different programs are implemented, results indicated that the more efficacious models of Primary Care Psychology are those tailored on the environment’s needs.The results of our systematic review stress the importance of the Primary Care Psychologist implementation also in Italy, to intercept unexpressed psychological needs and enhance clients’ quality of life.openFrancesca, Bianco; Enrico, BenelliBianco, Francesca; Benelli, Enric

Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach

9 páginas, 6 figuras.-- This is an Open Access article distributed under the terms of the Creative Commons Attribution LicenseMotivation: Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters. Results: In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cellsD.H., J.R.B. and J.S.R. acknowledge funding from the EU FP7 projects ‘NICHE’ (ITN Grant number 289384) and ‘BioPreDyn’ (KBBE grant number 289434). J.R.B. also acknowledges funding from the Spanish Ministerio de Economía y Competitividad (and the FEDER) through the project MultiScales (DPI2011-28112-C04-03).Peer reviewe

Multi-Quality Auto-Tuning by Contract Negotiation

A characteristic challenge of software development is the management of omnipresent change. Classically, this constant change is driven by customers changing their requirements. The wish to optimally leverage available resources opens another source of change: the software systems environment. Software is tailored to specific platforms (e.g., hardware architectures) resulting in many variants of the same software optimized for different environments. If the environment changes, a different variant is to be used, i.e., the system has to reconfigure to the variant optimized for the arisen situation. The automation of such adjustments is subject to the research community of self-adaptive systems. The basic principle is a control loop, as known from control theory. The system (and environment) is continuously monitored, the collected data is analyzed and decisions for or against a reconfiguration are computed and realized. Central problems in this field, which are addressed in this thesis, are the management of interdependencies between non-functional properties of the system, the handling of multiple criteria subject to decision making and the scalability. In this thesis, a novel approach to self-adaptive software--Multi-Quality Auto-Tuning (MQuAT)--is presented, which provides design and operation principles for software systems which automatically provide the best possible utility to the user while producing the least possible cost. For this purpose, a component model has been developed, enabling the software developer to design and implement self-optimizing software systems in a model-driven way. This component model allows for the specification of the structure as well as the behavior of the system and is capable of covering the runtime state of the system. The notion of quality contracts is utilized to cover the non-functional behavior and, especially, the dependencies between non-functional properties of the system. At runtime the component model covers the runtime state of the system. This runtime model is used in combination with the contracts to generate optimization problems in different formalisms (Integer Linear Programming (ILP), Pseudo-Boolean Optimization (PBO), Ant Colony Optimization (ACO) and Multi-Objective Integer Linear Programming (MOILP)). Standard solvers are applied to derive solutions to these problems, which represent reconfiguration decisions, if the identified configuration differs from the current. Each approach is empirically evaluated in terms of its scalability showing the feasibility of all approaches, except for ACO, the superiority of ILP over PBO and the limits of all approaches: 100 component types for ILP, 30 for PBO, 10 for ACO and 30 for 2-objective MOILP. In presence of more than two objective functions the MOILP approach is shown to be infeasible