Abstract

Abstract
The self-repair capacity of human tissue is limited, motivating the arising of tissue engineering (TE) in building temporary scaffolds that envisage the regeneration of human tissues, including articular cartilage. However, despite the large number of preclinical data available, current therapies are not yet capable of fully restoring the entire healthy structure and function on this tissue when significantly damaged. For this reason, new biomaterial approaches are needed, and the present work proposes the development and characterization of innovative polymeric membranes formed by blending marine origin polymers, in a chemical free cross-linking approach, as biomaterials for tissue regeneration. The results confirmed the production of polyelectrolyte complexes molded as membranes, with structural stability resulting from natural intermolecular interactions between the marine biopolymers collagen, chitosan and fucoidan. Furthermore, the polymeric membranes presented adequate swelling ability without compromising cohesiveness (between 300 and 600%), appropriate surface properties, revealing mechanical properties similar to native articular cartilage. From the different formulations studied, the ones performing better were the ones produced with 3 % shark collagen, 3% chitosan and 10% fucoidan, as well as with 5% jellyfish collagen, 3% shark collagen, 3% chitosan and 10% fucoidan. Overall, the novel marine polymeric membranes demonstrated to have promising chemical, and physical properties for tissue engineering approaches, namely as thin biomaterial that can be applied over the damaged articular cartilage aiming its regeneration.

Abstract
This paper proposes a multiple-lens receiver scheme to increase the misalignment tolerance of an underwater optical wireless communications link between an autonomous underwater vehicle (AUV) and a sensor plane. An accurate model of photon propagation based on the Monte Carlo simulation is presented which accounts for the lens(es) photon refraction at the sensor interface and angular misalignment between the emitter and receiver. The results show that the ideal divergence of the beam of the emitter is around 15 degrees for a 1 m transmission length, increasing to 22 degrees for a shorter distance of 0.5 m but being independent of the water turbidity. In addition, it is concluded that a seven-lense scheme is approximately three times more tolerant to offset than a single lens. A random forest machine learning algorithm is also assessed for its suitability to estimate the offset and angle of the AUV in relation to the fixed sensor, based on the power distribution of each lens, in real time. The algorithm is able to estimate the offset and angular misalignment with a mean square error of 5 mm (6 mm) and 0.157 rad (0.174 rad) for a distance between the transmitter and receiver of 1 m and 0.5 m, respectively.

Abstract
Breast cancer conservative treatment (BCCT) is a form of treatment commonly used for patients with early breast cancer. This procedure consists of removing the cancer and a small margin of surrounding tissue, while leaving the healthy tissue intact. In recent years, this procedure has become increasingly common due to identical survival rates and better cosmetic outcomes than other alternatives. Although significant research has been conducted on BCCT, there is no gold-standard for evaluating the aesthetic results of the treatment. Recent works have proposed the automatic classification of cosmetic results based on breast features extracted from digital photographs. The computation of most of these features requires the representation of the breast contour, which becomes key to the aesthetic evaluation of BCCT. State-of-the-art methods use conventional image processing tools that automatically detect breast contours based on the shortest path applied to the Sobel filter result in a 2D digital photograph of the patient. However, because the Sobel filter is a general edge detector, it treats edges indistinguishably, i.e., it detects too many edges that are not relevant to breast contour detection and too few weak breast contours. In this paper, we propose an improvement to this method that replaces the Sobel filter with a novel neural network solution to improve breast contour detection based on the shortest path. The proposed solution learns effective representations for the edges between the breasts and the torso wall. We obtain state of the art results on a dataset that was used for developing previous models. Furthermore, we tested these models on a new dataset that contains more variable photographs and show that this new approach shows better generalization capabilities as the previously developed deep models do not perform so well when faced with a different dataset for testing. The main contribution of this paper is to further improve the capabilities of models that perform the objective classification of BCCT aesthetic results automatically by improving upon the current standard technique for detecting breast contours in digital photographs. To that end, the models introduced are simple to train and test on new datasets which makes this approach easily reproducible.

Abstract

Abstract
The use of 3D animations in medical education is becoming increasingly popular. Indeed, animations are an efficient way to present complex information, reducing time spent reading textbooks. Thus, in the educational contexts, animations can help students learn more efficiently, retain and better understand information. In addition to improving the learning experience, medical education is a highly important and necessary endeavor, as it can directly affect the lives of patients. These videos can be useful in emergency care instructions and provide information about how to administer CPR to a patient or help in forensic reconstructions; a doctor might explain a medical term to a patient in a friendly way, and they can also help patients understand complex procedures. We find it important to understand if students and schools, when challenged, take a role in their community preparedness for major health problems. Projects led by schools are addressed within educational scenarios focused on STEM education and developed under a relevant public health issue through their continuous engagement in open schooling approach. By implementing an educational scenario with a focus on 3D animation, and thus potentiate the use of this technology, we intend to help raise awareness on the public health theme. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.