3499 research outputs found
Sort by
Genetically-Driven Enhancement of Dopaminergic Transmission Affects Moral Acceptability in Females but Not in Males: A Pilot Study
No full textMoral behavior has been a key topic of debate for philosophy and psychology for a long time. In recent years, thanks to the development of novel methodologies in cognitive sciences, the question of how we make moral choices has expanded to the study of neurobiological correlates that subtend the mental processes involved in moral behavior. For instance, in vivo brain imaging studies have shown that distinct patterns of brain neural activity, associated with emotional response and cognitive processes, are involved in moral judgment. Moreover, while it is well-known that responses to the same moral dilemmas differ across individuals, to what extent this variability may be rooted in genetics still remains to be understood. As dopamine is a key modulator of neural processes underlying executive functions, we questioned whether genetic polymorphisms associated with decision-making and dopaminergic neurotransmission modulation would contribute to the observed variability in moral judgment. To this aim, we genotyped five genetic variants of the dopaminergic pathway [rs1800955 in the dopamine receptor D4 (DRD4) gene, DRD4 48 bp variable number of tandem repeat (VNTR), solute carrier family 6 member 3 (SLC6A3) 40 bp VNTR, rs4680 in the catechol-O-methyl transferase (COMT) gene, and rs1800497 in the ankyrin repeat and kinase domain containing 1 (ANKK1) gene] in 200 subjects, who were requested to answer 56 moral dilemmas. As these variants are all located in genes belonging to the dopaminergic pathway, they were combined in multilocus genetic profiles for the association analysis. While no individual variant showed any significant effects on moral dilemma responses, the multilocus genetic profile analysis revealed a significant gender-specific influence on human moral acceptability. Specifically, those genotype combinations that improve dopaminergic signaling selectively increased moral acceptability in females, by making their responses to moral dilemmas more similar to those provided by males. As females usually give more emotionally-based answers and engage the “emotional brain” more than males, our results, though preliminary and therefore in need of replication in independent samples, suggest that this increase in dopamine availability enhances the cognitive and reduces the emotional components of moral decision-making in females, thus favoring a more rationally-driven decision process
Irreducible network backbones: unbiased graph filtering via maximum entropy
Get PDFNetworks provide an informative, yet non-redundant description of complex systems only if links represent truly dyadic relationships that cannot be directly traced back to node-specific properties such as size, importance, or coordinates in some embedding space. In any real-world network, some links may be reducible, and others irreducible, to such local properties. This dichotomy persists despite the steady increase in data availability and resolution, which actually determines an even stronger need for filtering techniques aimed at discerning essential links from non-essential ones. Here we introduce a rigorous method that, for any desired level of statistical significance, outputs the network backbone that is irreducible to the local properties of nodes, i.e. their degrees and strengths. Unlike previous approaches, our method employs an exact maximum-entropy formulation guaranteeing that the filtered network encodes only the links that cannot be inferred from local information. Extensive empirical analysis confirms that this approach uncovers essential backbones that are otherwise hidden amidst many redundant relationships and inaccessible to other methods. For instance, we retrieve the hub-and-spoke skeleton of the US airport network and many specialised patterns of international trade. Being irreducible to local transportation and economic constraints of supply and demand, these backbones single out genuinely higher-order wiring principles
Auxetic behavior and acoustic properties of microstructured piezoelectric strain sensors
No full textThe use of multifunctional composite materials adopting piezo-electric periodic cellular lattice structures with auxetic elastic behavior is a recent and promising solution in the design of piezoelectric sensors. In the present work, periodic anti-tetrachiral auxetic lattice structures, characterized by different geometries, are taken into account and the mechanical and piezoelectrical response are investigated. The equivalent piezoelectric properties are obtained adopting a first order computational homogenization approach, generalized to the case of electro-mechanical coupling, and various polarization directions are adopted. Two examples of in-plane and out-of-plane strain sensors are proposed as design concepts. Moreover, a piezo-elasto-dynamic dispersion analysis adopting the Floquet–Bloch decomposition is performed. The acoustic behavior of the periodic piezoelectric material with auxetic topology is studied and possible band gaps are detected
A nonlinear finite thickness cohesive interface element for modeling delamination in fibre-reinforced composite laminates
No full textAbstract Delamination events are major issues which notably affect the integrity of composite structures. To minimize the experimental efforts, there is an increasing demand for developing reliable numerical tools that can accurately simulate delamination initiation and propagation under mixed-mode loading conditions. The current investigation is concerned with the formulation and the finite element (FE) implementation of a new nonlinear finite thickness cohesive interface model for delamination analysis of fibre-reinforced composite laminates relying on the solid shell concept. The incorporation of geometrically nonlinear effects into the proposed interface formulation is motivated by the recent trend of producing composite structures that can experience large displacements prior to failure, as is the case of postbuckling in stiffened panels. The inelastic material behavior of the interface is modeled using two standard nonlinear decohesion laws: (i) an exponential-based, and (ii) a polynomial-based interface laws. Finally, the performance of the proposed interface element is demonstrated by means of several examples focusing on double cantilever beam (DCB) and rib-stiffened specimens. A excellent level of accuracy is achieved when comparing the numerical predictions and the available experimental data
Graph-restricted Game Approach for Investigating Human Movement Qualities
No full textA novel computational method for the analysis of expressive full-body movement qualities is introduced, which exploits concepts and tools from graph theory and game theory. The human skeletal structure is modeled as an undirected graph, where the joints are the vertices and the edge set contains both physical and non-physical links. Physical links correspond to connections between adjacent physical body joints (e.g., the forearm, which connects the elbow to the wrist). Nonphysical links act as "bridges" between parts of the body not directly connected by the skeletal structure, but sharing very similar feature values. The edge weights depend on features obtained by using Motion Capture data. Then, a mathematical game is constructed over the graph structure, where the vertices represent the players and the edges represent communication channels between them. Hence, the body movement is modeled in terms of a game built on the graph structure. Since the vertices and the edges contribute to the overall quality of the movement, the adopted game-theoretical model is of cooperative nature. A game-theoretical concept, called Shapley value, is exploited as a centrality index to estimate the contribution of each vertex to a shared goal (e.g., to the way a particular movement quality is transferred among the vertices). The proposed method is applied to a data set of Motion Capture data of subjects performing expressive movements, recorded in the framework of the H2020-ICT-2015 EU Project WhoLoDance, Project no. 688865. Preliminary results are presented
Recent Advances in Preclinical Studies and Potential Applications of Dendrimers as Drug Carriers in the Central Nervous System
No full textBackground: The brain is a well-protected organ, with a complex system of cells, proteins and transporters, that acts as a sentinel to prevent potentially harmful substances from entering the brain, stopping also active molecules administered with a therapeutic goal. Although their limited exploitation, dendrimers are currently under evaluation as drug vectors to improve pharmacological treatments, targeting active molecules across the blood-brain barrier and penetrating brain tissues.
Methods: Up to date, only three different families of dendrimers, poly(amidoamine)-, poly(propyleneimine)- and poly(L-lysine)-based, have found application as drug transporters in the Central Nervous System. Their development, functionalization and characterization are reported in the literature, with interesting preliminary outcomes in the treatment of brain disorders. Surface functionalization also affects the interaction between dendrimers and cells or tissues, with effects not only on penetration and retention, but also on the safety profile of this drug carrier.
Conclusion: This review focuses on the application of dendrimers in the field of targeted drug delivery toward the Central Nervous System, highlighting their interesting properties. Discussion will be promising and represent an important starting point for a further diffusion of dendrimers in pharmacological treatment of the Central Nervous System
AErlang at Work
No full textAErlang is an extension of the Erlang programming language which is enriched with attribute-based communication. In AErlang, the Erlang send and receive constructs are extended to permit partner selection by relying on predicates over set of attributes. AErlang avoids the limitations of the Erlang point-to-point communication making it possible to model some of the sophisticated interaction features often observed in modern systems, such as anonymity and adaptation. By using our prototype extension, we show how the extended communication pattern can capture non-trivial process interaction in a natural and intuitive way. We also sketch a modelling technique aimed at automatically verifying AErlang systems, and discuss how it can be used to check some key properties of the considered case study
Uncovering functional brain signature via random matrix theory
Get PDFThe brain is organized in a modular way, serving multiple functionalities. This multiplicity requires that both positive (e.g. excitatory, phase-coherent) and negative (e.g. inhibitory, phase-opposing) interactions take place across brain modules. Unfortunately, most methods to detect modules from time series either neglect or convert to positive any measured negative correlation. This may leave a significant part of the sign-dependent functional structure undetected. Here we present a novel method, based on random matrix theory, for the identification of sign-dependent modules in the brain. Our method filters out the joint effects of local (unit-specific) noise and global (system-wide) dependencies that empirically obfuscate such structure. The method is guaranteed to identify an optimally contrasted functional `signature', i.e. a partition into modules that are positively correlated internally and negatively correlated across. The method is purely data-driven, does not use any arbitrary threshold or network projection, and outputs only statistically significant structure. In measurements of neuronal gene expression in the biological clock of mice, the method systematically uncovers two otherwise undetectable, negatively correlated modules whose relative size and mutual interaction strength are found to depend on photoperiod. The neurons alternating between the two modules define a candidate region of functional plasticity for circadian modulation
Day-ahead scheduling and real-time Economic MPC of CHP unit in Microgrid with Smart buildings
No full textThis paper presents a model for day-ahead scheduling of the CHP heat and electric energy production for a residential Microgrid taking into account the economic factors in a liberalized electricity markets, the technical factors in the safety/quality of supply, and the consumer preferences. This day-ahead scheduling model is complemented with a real-time economic MPC model for a subsequent control with respect to the outcomes of the day-ahead scheduling. This combined scheduling and economic MPC provides a general set-up capable of overcoming several major difficulties encountered with a typical scheduling + tracking MPC set-up, e.g. the problems of connecting the economic objectives with different temporal resolution and different requirements in terms of delivery
Distributed Algorithm for Optimal Vehicle Coordination at Traffic Intersections
No full textAutomated vehicle coordination can be used to control vehicles across traffic intersections safely and efficiently. This paper proposes a novel parallelizable algorithm, which solves the coordination problem at traffic intersections under a given precedence order by using a tailored variant of the augmented Lagrangian based alternating direction inexact Newton method (ALADIN). Here, each vehicle solves its own optimal control problem and exchanges information about arrivial and departure times at the intersection with its neighbors such that collisions are avoided. We illustrate the performance of ALADIN by analyzing two scenarios, one during rush hour and one at low-traffic conditions