Electrospun silk-elastin-like fiber mats for tissue engineering applications

Protein-based polymers are present in a wide variety of organisms fulfilling structural and mechanical roles. Advances in protein engineering and recombinant DNA technology allow the design and production of recombinant protein-based polymers (rPBPs) with an absolute control of its composition. Although the application of recombinant proteins as biomaterials is still an emerging technology, the possibilities are limitless and far superior to natural or synthetic materials, as the complexity of the structural design can be fully customized. In this work, we report the electrospinning of two new genetically engineered silk-elastin-like proteins (SELPs) consisting of alternate silk- and elastin-like blocks. Electrospinning was performed with formic acid and aqueous solutions at different concentrations without addition of further agents. The size and morphology of the electrospun structures was characterized by scanning electron microscopy showing to be dependent of concentration and solvent used. Treatment with air saturated with methanol was employed to stabilize the structure and promote water insolubility through a time-dependent conversion of random coils into β-sheets (FTIR). The resultant methanol-treated electrospun mats were characterized for swelling degree (570-720%), water vapour transmission rate (1083 g/m2/day) and mechanical properties (modulus of elasticity of ~126 MPa). Furthermore, the methanol-treated SELP fiber mats showed no cytotoxicity and were able to support adhesion and proliferation of normal human skin fibroblasts. Adhesion was characterized by a filopodia-mediated mechanism. These results demonstrate that SELP fiber mats can provide promising solutions for the development of novel biomaterials suitable for tissue engineering applications.

One-sided Radial-Fundamental Matrix Estimation

For modern consumer cameras often approximate calibration data is available, making applications such as 3D reconstruction or photo registration easier as compared to the pure uncalibrated setting. In this paper we address the setting with calibrateduncalibrated image pairs: for one image intrinsic parameters are assumed to be known, whereas the second view has unknown distortion and calibration parameters. This situation arises e.g. when one would like to register archive imagery to recently taken photos. A commonly adopted strategy for determining epipolar geometry is based on feature matching and minimal solvers inside a RANSAC framework. However, only very few existing solutions apply to the calibrated-uncalibrated setting. We propose a simple and numerically stable two-step scheme to first estimate radial distortion parameters and subsequently the focal length using novel solvers. We demonstrate the performance on synthetic and real datasets.

Automation & control remote laboratory: evaluating a cooperative methodology

This paper presents a study carried out in order to evaluate the students' perception in the development and use of remote Control and Automation education kits developed by two Universities. Three projects, based on real world environments, were implemented, being local and remotely operated. Students implemented the kits using the theoretical and practical knowledge, being the teachers a catalyst in the learning process. When kits were operational, end-user students got acquainted to the kits in the course curricula units. It is the author's believe that successful results were achieved not only in the learning progress on the Automation and Control fields (hard skills) but also on the development of the students soft skills, leading to encouraging and rewarding goals, motivating their future decisions and promoting synergies in their work. The design of learning experimental kits by students, under teacher supervision, for future use in course curricula by enduser students is an advantageous and rewarding experience.