Abstract
In this chapter, we will describe methods based on simple measurements that allow one to acquire information of diverse nature. Regarding the characterization of optical clearing treatments and evaluation of their efficiency, we discuss a method to obtain the refractive index kinetics of the interstitial ground medium and another method to obtain the kinetics of the scattering properties of a tissue under study. The evaluation of the diffusion properties for the optical clearing agents and water involved in the fluxes between the tissue and the treating solution is also important. To obtain these properties, we describe in Sect. 6.4 a simple ex vivo method, which from collimated transmittance and thickness measurements allows one to estimate the diffusion time and the diffusion coefficient of these fluids. Such method can be used as a complementary diagnostic tool, since it allows also for discrimination between normal and pathological tissues. Also with the objective of obtaining physiological or pathological information from tissues, we describe in Sect. 6.5 the discovery of two new optical clearing windows in the ultraviolet range, which may turn possible the development of new diagnostic or treatment methodologies. © 2019, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Optical fiber sensors (OFS) based on long-period fiber gratings (LPFG) or on surface plasmon resonance (SPR) represent attractive solutions for detection systems in remote areas. An interrogation system consisting on wavelength modulation of fiber coupled distributed feedback (DFB) lasers was implemented and tested. The system uses a single photodetector to individually acquire the intensity of each DFB laser modulated by the OFS and the real transmission spectrum is reconstructed through curve fitting. Testing was accomplished by measuring the spectral features of an LPFG when changing the surrounding refractive index and errors lower than 1.8 nm in the 1530 to 1570 nm wavelength region were obtained.

Abstract
The residential sector is one of the sectors with the highest rates of electricity consumption worldwide. For years, many studies have been presented in order to minimize energy consumption at the residential level. The idea of such studies is that the residential customer (RC) is the interested party of their own consumption. Moreover, the algorithms that have been developed to predict and manage the energy consumption, also analyze the behavior of the loads, with the objective of minimizing the energy costs, with good safety, robustness, and comfort levels. In the context of the smart house (SH), one of the objectives of smart grids (SGs) is to enable the RC, with home energy management systems (HEM), to actively participate, allowing for higher reliability at different levels. In this work, a new model that simulates the behavior of an SH, considering heating, ventilation and air conditioning (HVAC) and sanitarian water heater (SWH) devices, is presented. For this purpose, the proposed model considers realistic physical parameters of the SH, together with customer comfort, in order to mitigate the RC disinterest. The proposed model considers the electric vehicle (EV), a battery-based energy storage system (ESS), a micro production unit, and different types of tariffs that the RC might choose, aiming to maximize the benefits, and temporarily shifting the proposed loads.

Abstract
A substantial amount of work is often overlooked due to the exponential rate of growth in global scientific output across all disciplines. Current approaches for addressing this issue are usually limited in scope and often restrict the possibility of obtaining multidisciplinary views in practice. To tackle this problem, researchers can now leverage an ecosystem of citizens, volunteers and crowd workers to perform complex tasks that are either difficult for humans and machines to solve alone. Motivated by the idea that human crowds and computer algorithms have complementary strengths, we present an approach where the machine will learn from crowd behavior in an iterative way. This approach is embodied in the architecture of SciCrowd, a crowd-powered human-machine hybrid system designed to improve the analysis and processing of large amounts of publication records. To validate the proposal's feasibility, a prototype was developed and an initial evaluation was conducted to measure its robustness and reliability. We conclude this paper with a set of implications for design.

Abstract

Abstract
Aim To explore the potential of a nurse health triage telephone line to advise and guide elderly users' decisions regarding the appropriate health care setting and self-care. Background Ageing is a concern in many countries and poses challenges to health care services. Triage and advice lines can play an important role for the (re)organisation of health care delivery. Discussion has been focused on the capacity of these lines to reduce inappropriate demand for acute and emergency departments. Methods Cross-sectional descriptive analysis. Results Nurses directed elders to a health care service both by downgrading their initial intentions (concurring to the most common objective) and by upgrading them (e.g., directing elders that intended to stay at home to acute and emergency care). The intention to comply with the nurse's disposition was high. Conclusions The line helped to improve the appropriateness of acute and emergency care demand and to reduce the overall demand for care by elders. There is nonetheless space for improvement given the underuse of the line by elders. Implications for Nursing Management Health telephone-based triage and advice should be promoted to increase the match between the needs of elderly patients and health resources, thus improving health equity.