Abstract

Abstract
The combination of marine origin biopolymers for tissue engineering (TE) applications is of high interest, due to their similarities with the proteins and polysaccharides present in the extracellular matrix of different human tissues. This manuscript reports on innovative collagen-chitosan-fucoidan cryogels formed by the simultaneous blending of these three marine polymers in a chemical-free crosslinking approach. The physicochemical characterization of marine biopolymers comprised FTIR, amino acid analysis, circular dichroism and SDS-PAGE, and suggested that the jellyfish collagen used in the cryogels was not denatured (preserved the triple helical structure) and had similarities with type II collagen. The chitosan presented a high deacetylation degree (90.1%) that can strongly influence the polymer physicochemical properties and biomaterial formation. By its turn, rheology, and SEM studies confirmed that these novel cryogels present interesting properties for TE purposes, such as effective blending of biopolymers without visible material segregation, mechanical stability (strong viscoelastic character), as well as adequate porosity to support cell proliferation and exchange of nutrients and waste products. Additionally,in vitrocellular assessments of all cryogel formulations revealed a non-cytotoxic behavior. The MTS test, live/dead assay and cell morphology assessment (phalloidin DAPI) showed that cryogels can provide a proper microenvironment for cell culturing, supporting cell viability and promoting cell proliferation. Overall, the obtained results suggest that the novel collagen-chitosan-fucoidan cryogels herein presented are promising scaffolds envisaging tissue engineering purposes, as both acellular biomaterials or cell-laden cryogels.

Abstract
Breast cancer imaging research has seen continuous progress throughout the years. Innovative visualization tools and easier planning techniques are being developed. Image segmentation methodologies generally have best results when applied to specific types of exams or sequences, as their features enhance and expedite those approaches. Particular methods have more purchase with the segmentation of particular structures. This is the case with diverse breast structures and the respective lesions on MRI sequences, over T1w and Dyn. The present study presents a methodology to tackle an unapproached task. We aim to facilitate the volumetric alignment of data retrieved from T1w and Dyn sequences, leveraging breast surface segmentation and registration. The proposed method revolves around Canny edge detection and mending potential holes on the surface, in order to accurately reproduce the breast shape. The contour is refined with a Level-set approach and the surfaces are aligned together using a restriction of the Iterative Closest Point (ICP) method. This could easily be applied to other paired same-time, volumetric sequences. The process seems to have promising results as average two-dimensional contour distances are at sub-voxel resolution and visual results seem well within range for the valid transference of other segmented or annotated structures. © Springer Nature Switzerland AG 2020.

Abstract
Electric vehicles (EVs) are developing due to concerns over global warming and the major role of the transportation sector in emissions. EVs can also flatten the power curve and increase the reliability of power grids when renewable energy sources are used. Despite of these benefits, EVs impose new loads on distribution networks. Simultaneous charging of EVs, especially at high penetration levels, can create new load peaks in the power curves as well as overloading transformers, shortening their service life. In actual applications, most electric cars are single-phase loads that need to be charged from household or commercial outlets. In this paper, an optimization method is presented to coordinate the dynamic charge operation of single-phase EVs in an unbalanced three-phase distribution network. In the proposed method, the main goal of charging management is to minimize the total cost, which considers both network security constraints and electric vehicle constraints. The proposed method is tested on a sample distribution network and the numerical results prove the effectiveness of the method.

Abstract
This paper models the role of electricity tariffs on the long-term adoption of photovoltaic and storage technologies as well as the consequent impact on the distribution grid. An adoption model that captures the economic rationality of tariff-driven investments and considers the stochastic nature of individual consumers' decisions is proposed. This model is then combined with a probabilistic load flow to evaluate the long-term impacts of the adoption on the voltage profiles of the distribution grid. To illustrate the methodology, different components of the electricity tariffs, including solar compensation mechanisms and time differentiation of Time-of-Use (ToU) rates, are evaluated, using a case study involving a section of a medium-voltage network with 118 nodes.

Abstract
In this paper, we present the design of an analog transmitter based on a blue LD targeting optical wireless communications, suitable for OFDM signals. The approach relies on a thorough characterization of the individual components of the module, whence a detailed circuit model is obtained to design an impedance matching circuit for improved performance, prior to fabrication. The impedance matching is based on non-uniform transmission lines and works well over a wide frequency range (100 MHz to 2 GHz). The results are experimentally validated by the transmitter response exhibiting an increased 6 dB bandwidth limit and 1 GHz bandwidth improvement. © 2020 IEEE.