Abstract
Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate, and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology that uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard - LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRa networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, using LoRaSim for different network scales. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 6% in DER, and a number of collisions 13 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 5%, 2.8%, and 2% of DER, and a number of collisions 11, 7.8 and 2.5 times smaller than equal-distribution, Tiurlikova's (SoTa), and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption similar to Tiurlikova's, and 2.8 times lower than the equal-distribution and random dynamic allocation policies. Furthermore, we approach the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.

Abstract
Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology which uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard - LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRa networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, considering realistic scenarios. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 30% in DER, and a number of collisions 17 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 10.5% and 4% of DER, and a number of collisions 13.5 and 7.5 times smaller than equal-distribution and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption 3.6 and 2.74 times lower than the equal-distribution and random dynamic allocation policies, respectively. Furthermore, we approach the practical aspects on how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.

Abstract
Laser diagnostics and treatment procedures are commonly performed for visible and near-IR wavelengths. The knowledge of the wavelength dependences for the optical properties of various biological tissues in this spectral range is useful for clinical applications. Since the optical properties of human liver have been previously known only for near-IR wavelengths, the aim is to estimate their wavelength dependences between 400 and 1000 nm. Using spectral measurements from liver samples in this range, we determine their optical properties with the inverse adding-doubling method. The obtained results indicate the presence of bile, oxyhaemoglobin and deoxyhaemoglobin in human liver. The combination of these biological components results in strong absorption for wavelengths between 400 and 600 nm, with peaks at unusual wavelengths. For wavelengths above 600 nm, the wavelength dependences for all optical properties present the typical behavior, but strong and shifted absorption observed for wavelengths below 600 nm has been previously unknown and can be useful for clinical procedures with lasers working in this range.

Abstract
This book describes the Optical Immersion Clearing method and its application to acquire information with importance for clinical practice and various fields of biomedical engineering. The method has proved to be a reliable means of increasing tissue transparency, allowing the investigator or surgeon to reach deeper tissue layers for improved imaging and laser surgery. This result is obtained by partial replacement of tissue water with an active optical clearing agent (OCA) that has a higher refractive index and is a better match for the refractive index of other tissue components. Natural tissue scattering is thereby reduced. An exponential increase in research using this method has occurred in recent years, and new applications have emerged, both in clinical practice and in some areas of biomedical engineering. Recent research has revealed that treating ex vivo tissues with solutions containing active OCAs in different concentrations produces experimental data to characterize drug delivery or to discriminate between normal and pathological tissues. The obtained drug diffusion properties are of interest for the pharmaceutical and organ preservation industry. Similar data can be estimated with particular interest for food preservation. The free water content evaluation is also of great interest since it facilitates the characterization of tissues to discriminate pathologies. An interesting new application that is presented in the book regards the creation of two optical windows in the ultraviolet spectral range through the application of the immersion method. These induced transparency windows open the possibility to diagnose and treat pathologies with ultraviolet light. This book presents photographs from the tissues we have studied and figures that represent the experimental setups used. Graphs and tables are also included to show the numerical results obtained in the sequential calculations performed.

Abstract
The optical immersion clearing technique has been successfully applied through the last 30 years in the visible to near infrared spectral range, and has proven to be a promising method to promote the application of optical technologies in clinical practice. To investigate its potential in the ultraviolet range, collimated transmittance spectra from 200 to 1000 nm were measured from colorectal muscle samples under treatment with glycerol-water solutions. The treatments created two new optical windows with transmittance efficiency peaks at 230 and 300 nm, with magnitude increasing with glycerol concentration in the treating solution. Such discovery opens the opportunity to develop clinical procedures to perform diagnosis or treatments in the ultraviolet.

Abstract
A robust method is presented for evaluating the diffusion properties of chemicals in ex vivo biological tissues. Using this method that relies only on thickness and collimated transmittance measurements, the diffusion properties of glycerol, fructose, polypropylene glycol and water in muscle tissues were evaluated. Amongst other results, the diffusion coefficient of glycerol in colorectal muscle was estimated with a value of 3.3 x 10(-7) cm(2)/s. Due to the robustness and simplicity of the method, it can be used in other fields of biomedical engineering, namely in organ cryoprotection and food industry.