Perception of affects from non-facial expressions of the robot Nabaztag

International audienceSocial robots using language and affective expressions can encourage and improve human-robot interaction. Body move-ments, postures, orientations, colors, and sounds can be used as either the primary method of expres-sion or to provide affective expression redundancy1. This study aimed at investigating how the elderly and the young perceive affects from expressions of Nabaztag, a non anthropomorphic robot with only non facial expression

A statistical learning strategy for closed-loop control of fluid flows

This work discusses a closed-loop control strategy for complex systems utilizing scarce and streaming data. A discrete embedding space is first built using hash functions applied to the sensor measurements from which a Markov process model is derived, approximating the complex system’s dynamics. A control strategy is then learned using reinforcement learning once rewards relevant with respect to the control objective are identified. This method is designed for experimental configurations, requiring no computations nor prior knowledge of the system, and enjoys intrinsic robustness. It is illustrated on two systems: the control of the transitions of a Lorenz’63 dynamical system, and the control of the drag of a cylinder flow. The method is shown to perform well

Temporal-spatial profiling of pedunculopontine galanin-cholinergic neurons in the lactacystin rat model of Parkinson’s disease

Parkinson’s disease (PD) is conventionally seen as resulting from single-system neurodegeneration affecting nigrostriatal dopaminergic neurons. However, accumulating evidence indicates a multi-system degeneration and neurotransmitter deficiencies, including cholinergic neurons which degenerate in a brainstem nucleus, the pedunculopontine nucleus (PPN), resulting in motor- and cognitive impairments. The neuropeptide galanin can inhibit cholinergic transmission, whilst being upregulated in degenerating brain regions associated with cognitive decline. Here we determined the temporal-spatial profile of progressive expression of endogenous galanin within degenerating cholinergic neurons, across the rostro-caudal axis of the PPN, by utilising the lactacystin-induced rat model of PD. First, we show progressive neuronal death affecting nigral dopaminergic and PPN cholinergic neurons, reflecting that seen in PD patients, to facilitate use of this model for assessing the therapeutic potential of bioactive peptides. Next, stereological analyses of the lesioned brain hemisphere found that the number of PPN cholinergic neurons expressing galanin increased by 11%, compared to sham-lesioned controls, increasing by a further 5% as the neurodegenerative process evolved. Galanin upregulation within cholinergic PPN neurons was most prevalent closest to the intra-nigral lesion site, suggesting that galanin upregulation in such neurons adapt intrinsically to neurodegeneration, to possibly neuroprotect. This is the first report on the extent and pattern of galanin expression in cholinergic neurons across distinct PPN subregions in both the intact rat CNS and lactacystin lesioned rats. The findings pave the way for future work to target galanin signaling in the PPN, to determine the extent to which upregulated galanin expression could offer a viable treatment strategy for ameliorating PD symptoms associated with cholinergic degeneration

Applying Bayesian model averaging for uncertainty estimation of input data in energy modelling

Background Energy scenarios that are used for policy advice have ecological and social impact on society. Policy measures that are based on modelling exercises may lead to far reaching financial and ecological consequences. The purpose of this study is to raise awareness that energy modelling results are accompanied with uncertainties that should be addressed explicitly. Methods With view to existing approaches of uncertainty assessment in energy economics and climate science, relevant requirements for an uncertainty assessment are defined. An uncertainty assessment should be explicit, independent of the assessor’s expertise, applicable to different models, including subjective quantitative and statistical quantitative aspects, intuitively understandable and be reproducible. Bayesian model averaging for input variables of energy models is discussed as method that satisfies these requirements. A definition of uncertainty based on posterior model probabilities of input variables to energy models is presented. Results The main findings are that (1) expert elicitation as predominant assessment method does not satisfy all requirements, (2) Bayesian model averaging for input variable modelling meets the requirements and allows evaluating a vast amount of potentially relevant influences on input variables and (3) posterior model probabilities of input variable models can be translated in uncertainty associated with the input variable. Conclusions An uncertainty assessment of energy scenarios is relevant if policy measures are (partially) based on modelling exercises. Potential implications of these findings include that energy scenarios could be associated with uncertainty that is presently neither assessed explicitly nor communicated adequately

The potential of metering roundabouts: influence in transportation externalities

Roundabouts are increasingly being used on busy arterial streets for traffic calming purposes. However, if one roundabout leg is near a distribution hub, e.g. parking areas of shopping centers, the entry traffic volumes will be particularly high in peak hours. This paper investigated a partial-metering based strategy to reduce traffic-related costs in a corridor. Specifically, the resulting traffic performance, energy, environmental and exposure impacts associated with access roundabouts were studied in an urban commercial area, namely: a) to characterize corridor operations in terms of link-specific travel time, fuel consumption, carbon dioxide and nitrogen oxides emissions, and noise costs; b) to propose an optimization model to minimize above outputs; and c) to demonstrate the model applicability under different traffic demand and directional splits combinations. Traffic, noise and vehicle dynamics data were collected from a corridor with roundabouts and signalized intersections near a commercial area of Guimarães, Portugal. Microscopic traffic and emission modeling platforms were used to model traffic operations and estimate pollutant emissions, respectively. Traffic noise was estimated with a semi-dynamical model. Link-based cost functions were developed based on the integrated modeling structure. Lastly, a Sequential quadratic programming type approach was applied to find optimal timing settings. The benefit of the partial-metering system, in terms of costs, could be up to 13% with observed traffic volumes. The efficiency of the proposed system increased as entering traffic at the metered approaches increased (~7% less costs). The findings let one to quantify metering benefits near shopping areas

Coupling of ORL1 (NOP) receptor to G proteins differs in the nucleus accumbens of anxious and non anxious mice.

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