Tendon regeneration through a scaffold-free approach: development of tenogenic magnetic hASCs sheets

Tendon's regeneration is limited, demanding for cell-based strategies to fully restore their functionality upon injury. The concept of magnetic force-based TE(1), generally using magnetic nanoparticles may enable, for example, stem cell stimulation and/or remote control over TE constructs. Thus, we originally propose the development of magnetic cell sheets (magCSs) with tenogenic capability, aimed at promoting tendon's regeneration. A Tenomodulin (TNMD+) subpopulation was sorted from human adipose stem cells (hASCs), using TNMD-coated immunomagnetic beads(2) and used as cell source for the development of magCSs. Briefly, cells were labeled with iron oxide composite particles (Micromod) and cultured for 7 days in α-MEM medium with or without magnetic stimulation provided by a magnetic device (nanoTherics). CSs were retrieved from the plates using magnet attraction as contiguous sheets of cells within its own deposited ECM.

Discursos para a Independência: a Escócia e o Referendo de 2014

Dissertação de mestrado em Ciência Política

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.

A firefly dynamic penalty approach for solving engineering design problems

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

O papel da diplomacia económica na dinamização da economia: o caso de Cabo Verde

Dissertação de mestrado em Negócios Internacionais

Carbon materials as new generation of new electron shuttles for the anaerobic degradation of environmental xenobiotics

Tese de Doutoramento em Engenharia Química e Biológica

Parameter identification of the fermentative production of fructo-oligosaccharides by Aureobasidium pullulans

In this study, a mathematical model for the production of Fructo-oligosaccharides (FOS) by Aureobasidium pullulans is developed. This model contains a relatively large set of unknown parameters, and the identification problem is analyzed using simulation data, as well as experimental data. Batch experiments were not sufficiently informative to uniquely estimate all the unknown parameters, thus, additional experiments have to be achieved in fed-batch mode to supplement the missing information. © 2015 IEEE.

Acabamentos químicos em tecidos

Dissertação de mestrado em Técnicas de Caracterização e Análise Química