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
The ability to detect pathological changes early and in a non-invasive way represents important advantages in the medical field. Diagnosis should become less intrusive, more accurate and less expensive in order to implement in the clinical routine. Infrared thermography has the advantages of being non-invasive, fast, reliable, capable of producing multiple recordings in short intervals, and absolutely safe for patients and clinicians. Thermographic image (TI) came to be an extensively studied technique to quantify sensitive changes in skin temperature in relation to certain diseases: early in the pathological process (lesions, inflammation and infection) the circulation fluxes are altered and, consequently, the tissues’ temperature is reflected in thermography pattern, before structural or functional changes can be observed. This technique proved to be able to give relevant clinical information, such as breast cancer, foot disease in diabetes, rheumatoid arthritis and sports injuries. Monitoring the temperature profile of a patient will allow understanding the physiological evolution of some diseases or monitoring the pharmacologic therapy effect. However, the high cost of this technology and the small number of commercial solutions do not allow a general implementation in the clinical environmental. The future direction is the combination of this technique with the other images techniques in order to add clinical information for a more reliable diagnostic.

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.

Abstract
We describe an online method to estimate the wavefront outer scale profile, L0(h), for very large and future extremely large telescopes. The stratified information on this parameter impacts the estimation of the main turbulence parameters [turbulence strength, Cn2(h); Fried's parameter, r0; isoplanatic angle, ?0; and coherence time, t0) and determines the performance of wide-field adaptive optics (AO) systems. This technique estimates L0(h) using data from the AO loop available at the facility instruments by constructing the cross-correlation functions of the slopes between two or more wavefront sensors, which are later fitted to a linear combination of the simulated theoretical layers having different altitudes and outer scale values. We analyse some limitations found in the estimation process: (i) its insensitivity to large values of L0(h) as the telescope becomes blind to outer scales larger than its diameter; (ii) the maximum number of observable layers given the limited number of independent inputs that the cross-correlation functions provide and (iii) the minimum length of data required for a satisfactory convergence of the turbulence parameters without breaking the assumption of statistical stationarity of the turbulence. The method is applied to the Gemini South multiconjugate AO system that comprises five wavefront sensors and two deformable mirrors. Statistics of L0(h) at Cerro Pachón from data acquired during 3 yr of campaigns show interesting resemblance to other independent results in the literature. A final analysis suggests that the impact of error sources will be substantially reduced in instruments of the next generation of giant telescopes.

Abstract
Enhancement and wise archiving of astronomical images require an accurate estimate of the observational Point Spread Function (PSF). Although modelling of the telescope and its optics is a well-understood problem, PSF reconstruction becomes challenging when the observations include adaptive optics (AO) correction. The approach presented in this paper consists in feeding an end-to-end (E2E) simulation of the telescope, the instrument and its environment with the characterized disturbances from the telemetry and AO loop data, in order to produce the estimated PSFs. This method benefits from the developments made in the last years with respect to the estimation of external disturbances during AO correction, such as turbulence profile and its dynamics as well as sensor noise and vibrations characteristics. In particular, characterization of the turbulence profile in terms of strength, C2n (h), and outer scale, L0(h), is considered with an example on on-sky recorded AO telemetry from the GALACSI AO system. Once identified, the internal and external parameters of the observing conditions are used as inputs to carry out E2E simulations of the optical propagation and estimate the PSF. The method can be regarded as a "brute force" approach, as it is highly intensive in computer power; particularly for the ELTs. However, its ability to integrate complex combination of effects from all disturbances and not relying on analytical approximations for the aliasing or fitting errors makes the approach worth of a deeper study. E2E simulations have been used before in PSF reconstruction, but limited to a theoretical modelling of the system. Here, the development of the E2E simulation part is an ongoing work. A simplified AO system similar to the GALACSI WFM is currently simulated to obtain the PSF estimates and illustrate how such approach allows to account for the anisoplanatic effects and for the inuence of the outer scale values.