Neural networks for small scale ORC optimization

This study concerns a thermodynamic and technical optimization of a small scale Organic Rankine Cycle system for waste heat recovery applications. An Artificial Neural Network (ANN) has been used to develop a thermodynamic model to be used for the maximization of the production of power while keeping the size of the heat exchangers and hence the cost of the plant at its minimum. R1234yf has been selected as the working fluid. The results show that the use of ANN is promising in solving complex nonlinear optimization problems that arise in the field of thermodynamics

Parallel decomposition methods for linearly constrained problems subject to simple bound with application to the SVMs training

We consider the convex quadratic linearly constrained problem with bounded variables and with huge and dense Hessian matrix that arises in many applications such as the training problem of bias support vector machines. We propose a decomposition algorithmic scheme suitable to parallel implementations and we prove global convergence under suitable conditions. Focusing on support vector machines training, we outline how these assumptions can be satisfied in practice and we suggest various specific implementations. Extensions of the theoretical results to general linearly constrained problem are provided. We included numerical results on support vector machines with the aim of showing the viability and the effectiveness of the proposed scheme

Bonobos Protect and Console Friends and Kin

Post-conflict third-party affiliation has been reported to have different functional meanings, one of them being consolation. Here, we tested the main hypotheses that have been put forth to explain the presence of this phenomenon at a functional level in the bonobo: Self-Protection Hypothesis, Victim-Protection Hypothesis, Relationship-Repair or Substitute for Reconciliation Hypothesis, and Consolation Hypothesis. By analyzing the data collected over 10 years, we investigated what factors affected the distribution of both spontaneous third party affiliation (initiated by the bystander) and solicited third party affiliation (initiated by the victim). We considered factors related to the individual features (sex, rank, age) of victim and bystander, their relationship quality (kinship, affiliation), and the effect that third party affiliation had on the victim (such as protection against further attacks and anxiety reduction). Both spontaneous and solicited third party affiliation reduced the probability of further aggression by group members on the victim (Victim-Protection Hypothesis supported). Yet, only spontaneous affiliation reduced victim anxiety (measured via self-scratching), thus suggesting that the spontaneous gesture - more than the protection itself - works in calming the distressed subject. The victim may perceive the motivational autonomy of the bystander, who does not require an invitation to provide post-conflict affiliative contact. Moreover, spontaneous - but not solicited - third party affiliation was affected by the bond between consoler and victim, being the relationship between consoler and aggressor irrelevant to the phenomenon distribution (Consolation Hypothesis supported). Spontaneous affiliation followed the empathic gradient described for humans, being mostly offered to kin, then friends, then acquaintances. Overall, our findings do not only indicate the consolatory function of spontaneous third-party affiliation but they also suggest that consolation in the bonobo may be an empathy-based phenomenon

A fast branch-and-bound algorithm for non-convex quadratic integer optimization subject to linear constraints using ellipsoidal relaxations

We propose two exact approaches for non-convex quadratic integer minimization subject to linear constraints where lower bounds are computed by considering ellipsoidal relaxations of the feasible set. In the first approach, we intersect the ellipsoids with the feasible linear subspace. In the second approach we penalize exactly the linear constraints. We investigate the connection between both approaches theoretically. Experimental results show that the penalty approach significantly outperforms CPLEX on problems with small or medium size variable domains. © 2015 Elsevier B.V. All rights reserved

In Play We Trust. Rapid Facial Mimicry Predicts the Duration of Playful Interactions in Geladas

The primate play-face is homologous to the human facial display accompanying laughter. Through facial mimicry, the playface evokes in the perceiver a similar positive emotional state. This sensorimotor and emotional sharing can be adaptive, as it allows individuals to fine-tune their own motor sequences accordingly thus increasing cooperation in play. It has been recently demonstrated that, not only humans and apes, but also geladas are able to mimic others\u27 facial expressions. Here, we describe two forms of facial mimicry in Theropithecus gelada: rapid (RFM, within 1.0 s) and delayed (DFM, within 5.0 s). Play interactions characterized by the presence of RFM were longer than those with DFM thus suggesting that RFM is a good indicator of the quality of communicative exchanges and behavioral coordination. These findings agree with the proposal of a mirror mechanism operating during perception and imitation of facial expressions. In an evolutionary perspective, our findings suggest that RFM not only was already present in the common ancestor of cercopitecoids and hominoids, but also that there is a relationship between RFM and length and quality of playful interactions

Yawn contagion in humans and bonobos: emotional affinity matters more than species.

In humans and apes, yawn contagion echoes emotional contagion, the basal layer of empathy. Hence, yawn contagion is a unique tool to compare empathy across species. If humans are the most empathic animal species, they should show the highest empathic response also at the level of emotional contagion. We gathered data on yawn contagion in humans (Homo sapiens) and bonobos (Pan paniscus) by applying the same observational paradigm and identical operational definitions .W eselected a naturalistic approach because experimental management practices can produce different psychological and behavioural biases in the two species, and differential attention to artificia lstimuli .Withi nspecies ,yaw ncontagio nwa shighes tbetween strongly bonded subjects. Between species, sensitivity to others\u27 yawns was higher in humans than in bonobos when involving kin and friends but was similar when considering weakly-bonded subjects. Thus, emotional contagion is not always high- est in humans. The cognitive components concur in empowering emotional affinity between individuals. Yet, when they are not in play, humans climb down from the empathic podium to return to the "understory", which our species shares with apes

Different yawns, different functions? Testing social hypotheses on spontaneous yawning in Theropithecus gelada

Here, we tested hypotheses about the potential functions of yawning based on its intensity and social contexts. Due to their spectrum intensity of yawns (covered teeth/YW1; uncovered teeth/YW2; uncovered gums/YW3), geladas are a good model species for this purpose. We suggest that yawns of different intensity can bear different information according to the performer, the context and the behavioural pattern temporally associated to the yawn event. YW3, mainly performed by high ranking males during periods of high social tension, was frequently associated with an auditory component and often accompanied by scratching (a measure of anxiety). YW1 and YW2, preferentially performed by females, were frequently associated to lip smacking, an affiliative display. In conclusion, even though a clear-cut functional distinction of geladas\u27 yawn intensity is difficult, YW1 and YW2 seem to be more linked to affiliative social interactions; whereas, YW3 seems to be more linked to agonistic and tension situations

Water Masers in the Andromeda Galaxy: The First Step Toward Proper Motion

We have detected and confirmed five water maser complexes in the Andromeda Galaxy (M31) using the Green Bank Telescope. These masers will provide the high brightness temperature point sources needed for proper motion studies of M31, enabling measurement of its full three-dimensional velocity vector and its geometric distance via proper rotation. The motion of M31 is the keystone of Local Group dynamics and a gateway to the dark matter profiles of galaxies in general. Our survey for water masers selected 206 luminous compact 24 micron-emitting regions in M31 and was sensitive enough to detect any maser useful for ~10 microarcsecond per year astrometry. The newly discovered masers span the isotropic luminosity range 0.3-1.9 x 10^-3 L(Sun) in single spectral components and are analogous to luminous Galactic masers. The masers are distributed around the molecular ring, including locations close to the major and minor axes, which is nearly ideal for proper motion studies. We find no correlation between 24 micron luminosity and water maser luminosity, suggesting that while water masers arise in star-forming regions, the nonlinear amplification pathways and beamed nature of the water masers means that they are not predictable based on IR luminosity alone. This suggests that there are additional bright masers to be found in M31. We predict that the geometric distance and systemic proper motion of M31 can be measured in 2-3 years with current facilities. A "moving cluster" observation of diverging masers as M31 approaches the Galaxy may be possible in the long term.Comment: 6 pages, 3 figures, 2 tables, accepted by ApJ Letter

Gait learning for soft microrobots controlled by light fields

Soft microrobots based on photoresponsive materials and controlled by light fields can generate a variety of different gaits. This inherent flexibility can be exploited to maximize their locomotion performance in a given environment and used to adapt them to changing conditions. Albeit, because of the lack of accurate locomotion models, and given the intrinsic variability among microrobots, analytical control design is not possible. Common data-driven approaches, on the other hand, require running prohibitive numbers of experiments and lead to very sample-specific results. Here we propose a probabilistic learning approach for light-controlled soft microrobots based on Bayesian Optimization (BO) and Gaussian Processes (GPs). The proposed approach results in a learning scheme that is data-efficient, enabling gait optimization with a limited experimental budget, and robust against differences among microrobot samples. These features are obtained by designing the learning scheme through the comparison of different GP priors and BO settings on a semi-synthetic data set. The developed learning scheme is validated in microrobot experiments, resulting in a 115% improvement in a microrobot's locomotion performance with an experimental budget of only 20 tests. These encouraging results lead the way toward self-adaptive microrobotic systems based on light-controlled soft microrobots and probabilistic learning control.Comment: 8 pages, 7 figures, to appear in the proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems 201