Abstract
To overcome the high light-scattering problem that occurs in biological tissues, we present in this chapter the different clearing methods known today. Most of these methods have benefits and downsides, depending on the application for which they are used. The optical immersion method is introduced as a better, reliable, and reversible way to turn tissues clear. The major benefits and advantages of this method such as its reversibility, the lack of side effects, and application in large wavelength range will be presented. A description of the molecular diffusion of optical clearing agents is given to explain the reduction in the refractive index mismatch that natural tissues have. © 2019, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The advent of small and low-cost Unmanned Aerial Vehicles (UAVs) is paving the way to use swarms of UAVs to perform missions such as aerial video monitoring and infrastructure inspection. Within a swarm, UAVs communicate by means of a Flying Multi-hop Network (FMN), which due to its dynamics induces frequent changes of network topology and quality of the links. Recently, UAVs have also been used to provide Internet access and enhance the capacity of existing networks in Temporary Events. This brings up additional routing challenges not yet addressed, in order to provide always-on and high capacity paths able to meet the Quality of Service expected by the users. This paper presents RedeFINE, a centralized routing solution for FMNs that selects high-capacity paths between UAVs and avoids communications disruptions, by defining in advance the forwarding tables and the instants they shall be updated in the UAVs; this represents a major step forward with respect to traditional routing protocols. The performance evaluation of RedeFINE shows promising results, especially regarding Throughput and Packet Delivery Ratio, when compared with state of the art routing solutions.

Abstract
Developing robust and universal methods for unsupervised segmentation of moving objects in video sequences has proved to be a hard and challenging task that has attracted the attention of many researchers over the last decades. State-of-the-art methods are, in general, computationally heavy preventing their use in real-time applications. This research addresses this problem by proposing a robust and computationally efficient method, coined BMOG, that significantly boosts the performance of a widely used method based on a Mixture of Gaussians. The proposed solution explores a novel classification mechanism that combines color space discrimination capabilities with hysteresis and a dynamic learning rate for background model update. The complexity of BMOG is kept low, proving its suitability for real-time applications. BMOG was objectively evaluated using the ChangeDetection.net 2014 benchmark. An exhaustive set of experiments was conducted, and a detailed analysis of the results, using two complementary types of metrics, revealed that BMOG achieves an excellent compromise in performance versus complexity.

Abstract
The performance of Resonant Tunnelling Diode (RTD) oscillators with an optical window is evaluated experimentally, in the transmission of advanced modulation formats using electrical and optical modulation, for the first time. Additionally, the impact of phase noise in the transmission performance is also assessed.

Abstract
The high permittivity of InP substrates has been a limiting factor for the bandwidth and efficiency of antennas fabricated in this material. In this manuscript we propose an elliptical monopole, monolithically fabricated in InP, fed by a CPW line. The suggested topology was simulated using HFSS finite element method. Input reflection coefficient measurements were performed on the monopole to validate the proposed antenna. Simulated and measured -10 dB bandwidths of 27 and 24 GHz were obtained, respectively. The peak simulated efficiency and realized gain were 95.37% and 4.6 dBi.

Abstract
Technological advances are pushing into the mass market innovative wearable devices featuring increasing processing and sensing capacity, non-intrusiveness and ubiquitous use. Sensors built-in those devices, enable acquiring different types of data and by taking advantage of the available processing power, it is possible to run intelligent applications that process the sensed data to offer added -value to the user in multiple domains. Although not new to the modern society, it is unquestionable that the present exercise boom is rapidly spreading across all age groups. However, in a great majority of cases, people perform their physical activity on their own, either due to time or budget constraints and may easily get discouraged if they do not see results or perform exercises inadequately. This paper presents an application, running on a wearable device, aiming at operating as a personal trainer that validates a set of proposed exercises in a sports' session. The developed solution uses inertial sensors of an Android Wear smartwatch and, based on a set of pattern recognition algorithms, detects the rate of success in the execution of a planned workout. The fact that all processing can be executed on the device is a differentiator factor to other existing solutions.