Abstract
This paper describes an energy management system that is being developed in the AnyPLACE project to support new energy services, like demand response, in residential buildings. In the project end-user interfaces are designed and implemented to allow the input of preferences regarding the flexible use of shiftable and thermal appliances. Monitoring and self-learning algorithm are used to allow additional information to be collected and an automation platform is available for the management and control of appliances. An energy management algorithm is presented that processes end-user preferences and devices characteristics to produce an optimal dispatch considering demand response incentives. Results show the successful implementation of an optimized energy scheduling.

Abstract
Software developers have always found it difficult to adopt Field-Programmable Gate Arrays (FPGAs) as computing platforms. Recent advances in HLS tools aim to ease the mapping of computations to FPGAs by abstracting the hardware design effort via a standard OpenCL interface and execution model. However, OpenCL is a low-level programming language and requires that developers master the target architecture in order to achieve efficient results. Thus, efforts addressing the generation of OpenCL from high-level languages are of paramount importance to increase design productivity and to help software developers. Existing approaches bridge this by translating MATLAB/Octave code into C, or similar languages, in order to improve performance by efficiently compiling for the target hardware. One example is the MATISSE source-to-source compiler, which translates MATLAB code into standard-compliant C and/or OpenCL code. In this paper, we analyse the viability of combining both flows so that sections of MATLAB code can be translated to specialized hardware with a small amount of effort, and test a few code optimizations and their effect on performance. We present preliminary results relative to execution times, and resource and power consumption, for two OpenCL kernels generated by MATISSE, and manual optimizations of each kernel based on different coding techniques.

Abstract
We present DIGItal sTeps (DIGIT), a system for assisting in the creation of footstep sounds in a post-production foley context—a practice that recreates all diegetic sounds for a moving image. The novelty behind DIGIT is the use of the acoustic (haptic) response of a gesture on a tangible interface as means for navigating and retrieving similar matches from a large database of annotated footstep sounds. While capturing the tactile expressiveness of the traditional sound foley practice in the exploration of physical objects, DIGIT streamlines the workflow of the audio post production environment for film or games by reducing its costly and time-consuming requirements. © 2018, Springer Nature Switzerland AG.

Abstract
Heart rate variability (HRV) analysis has been used as a quantitative marker of the autonomous nervous system activity to measure mental stress. Wearable sensors have been emerging as a solution to collect HRV data for stress assessment in a real context, however such studies raise additional requirements. The wearable system must be minimally obtrusive to allow the subjects to perform their tasks without interference, and inconspicuous to avoid the anxiety associated with wearing medical devices in public. The purpose of this study was to quantify the accuracy trade-off in the use of a chest band heart rate sensor that is less intrusive and less costly than a wearable electrocardiogram (ECG). The HRV metrics extracted from a chest band heart rate monitor, Zephyr HxM (TM) (Zph (TM)), were compared with those extracted from an ECG certified medical device, Vital Jacket (TM) (VJ (TM)). The two systems were worn simultaneously. under laboratory conditions by a population of 14 young and healthy subjects, aged 20 to 26 years, under the stress induced by the Trier Social Stress Test (TSST) procedure. The results showed a mean difference between RR intervals of 9 ms; a. root-mean square error. (RMSE) of less than 8% and. a Pearson's correlation higher than 0.946, considering all TSST phases. In the HRV analysis, the average of all normal intervals (AVNN) showed errors less than 2% between the two systems with a correlation higher than 0.99 for all TSST phases. We thus conclude that the used chest band sensor represents an alternative to the current wearable medical devices to monitor RR intervals, and could be used for mental stress monitoring similar to the TSST protocol.

Abstract
Background and Objectives: In spite of the existence of a multitude of techniques that allow the estimation of stress from physiological indexes, its fine-grained assessment is still a challenge for biomedical engineering. The short-term assessment of stress condition overcomes the limits to stress characterization with long blocks of time and allows to evaluate the behaviour change in real-world settings and also the stress level dynamics. The aim of the present study was to evaluate time and frequency domain and nonlinear heart rate variability (HRV) metrics for stress level assessment using a short-time window. Methods: The electrocardiogram (ECG) signal from 14 volunteers was monitored using the Vital Jacketml while they performed the Trier Social Stress Test (TSST) which is a standardized stress-inducing protocol. Window lengths from 220 s to 50 s for HRV analysis were tested in order to evaluate which metrics could be used to monitor stress levels in an almost continuous way. Results: A sub-set of HRV metrics (AVNN, rMSSD, SDNN and pNN20) showed consistent differences between stress and non-stress phases, and showed to be reliable parameters for the assessment of stress levels in short-term analysis. Conclusions: The AVNN metric, using 50 s of window length analysis, showed that it is the most reliable metric to recognize stress level across the four phases of TSST and allows a fine-grained analysis of stress effect as an index of psychological stress and provides an insight into the reaction of the autonomic nervous system to stress.

Abstract
AbstractMicroorganisms evolved adaptive responses that enable them to survive stressful challenges in ever changing environments by adjusting metabolism through the modulation of gene expression, protein levels and activity, and flow of metabolites. More frequent challenges allow natural selection ampler opportunities to select from a larger number of phenotypes that are compatible with survival. Understanding the causal relationships between physiological and metabolic requirements that are needed for cellular stress adaptation and gene expression changes that are used by organisms to achieve those requirements may have a significant impact in our ability to interpret and/or guide evolution.Here, we study those causal relationships during heat shock adaptation in the yeastSaccharomyces cerevisiae. We do so by combining dozens of independent experiments measuring whole genome gene expression changes during stress response with a nonlinear simplified kinetic model of central metabolism.This combination is used to create a quantitative, multidimensional, genotype-to-phenotype mapping of the metabolic and physiological requirements that enable cell survival to the feasible changes in gene expression that modulate metabolism to achieve those requirements. Our results clearly show that the feasible changes in gene expression that enable survival to heat shock are specific for this stress. In addition, they suggest that genetic programs for adaptive responses to desiccation/rehydration and to pH shifts might be selected by physiological requirements that are qualitatively similar, but quantitatively different to those for heat shock adaptation. In contrast, adaptive responses to other types of stress do not appear to be constrained by the same qualitative physiological requirements. Our model also explains at the mechanistic level how evolution might find different sets of changes in gene expression that lead to metabolic adaptations that are equivalent in meeting physiological requirements for survival. Finally, our results also suggest that physiological requirements for heat shock adaptation might be similar between unicellular ascomycetes that live in similar environments. Our analysis is likely to be scalable to other adaptive response and might inform efforts in developing biotechnological applications to manipulate cells for medical, biotechnological, or synthetic biology purposes.