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Abstract
In this paper a new type of polymeric fiber optic tweezers for single cell manipulation is reported. The optical trapping of a yeast cell using a polymeric micro lens fabricated by guided photo polymerization at the fiber tip is demonstrated. The 2D trapping of the yeast cells is analyzed and maximum optical forces on the pN range are calculated. The experimental results are supported by computational simulations using a FDTD method. Moreover, new insights on the potential for simultaneous sensing and optical trapping, are presented.

Abstract
The article will present the development of the tool FEUPAutom, used at the Faculty of Engineering of the University of Porto (FEUP) in the automation engineering Technological & Scientific area. In FEUP, the pressure to deliver well trained engineers is steadily high in the last two decades, thus producing a well-known situation of massification in Higher Education Institutions, namely in engineering degrees. In the school year of 2013/14, the course where the tool was used had about 270 students, despite quite low retention rates. The article also includes a brief characterization of the engineering program, course and expected outcomes in full alignment with the ideas promoted by the EUR-ACE referential for the accreditation of engineering programs and also in strong consonance with the ideas defended by the Bologna process. The course includes lab work and a part of those uses Problem Based Learning (PBL) methodology. In the last decade, the professors of the mentioned course have tried to limit the usage of real world industrial equipments because of budget concerns, always without hindering the learning process. Adequate simulation tools were sought on the market but not found, mainly because the needs of a full blown engineer are frequently not the same as those of an early engineering student. At that point, the decision was made to develop an in-house tool, adequate for students. Industrial-grade equipment was not totally set aside, only reserved for latter stages and the actual usage strategy allowed the number of equipments to be halved. The article will go on briefly describing the FEUPAutom tool and new strategies available for lab classes and PBL. As control groups would be unethical, students' quiz data from the two last editions of the course are used to evaluate learning (self-assessed). Grading strategy and coordination with the university's LMS is also addressed. Final grades of the course and satisfaction are also discussed. The students' assessment is that the FEUPAutom tool is very useful for the learning process and easier to use than the available industrial counterpart. Continuous improvement efforts have tried to push students to adequate PBL work only possible with the tool, with some results hinting deep learning in the technical area at stake. Some final thoughts, lessons learned and future work are also present in the article.

Abstract
This paper proposes a structure driven approach to assess graph-based exercises. Given two graphs, a solution and an attempt of a student, this approach computes a mapping between the node sets of both graphs that maximizes the student's grade, as well as a description of the differences between the two graph. The proposed algorithm uses heuristics to test the most promising mappings first and prune the remaining when it is sure that a better mapping cannot be computed. The proposed algorithm is applicable to any type of document that can be parsed into its graph-inspired data model. This data model is able to accommodate diagram languages, such as UML or ER diagrams, for which this kind of assessment is typically used. However, the motivation for developing this algorithm is to combine it with other assessment models, such as the test case model used for programming language assessment. The proposed algorithm was validated with thousands of graphs with different features produced by a synthetic data generator. Several experiments were designed to analyse the impact of different features such as graph size, and amount of difference between solution and attempt.

Abstract

Abstract
This work addresses the experimental identification of mode I cohesive law of wood bonded joints. The approach combines the double cantilever beam (DCB) test with both digital image correlation (DIC) and embedded fibre Bragg grating (FBG) sensors. The spectrum geometric mean of the FBG reflected spectral response was determined, and the wavelength evolution was used to define the fracture process zone (FPZ) development phase. This evaluation allowed a consistent selection of experimental range of over which the identification procedure of mode I cohesive law is build up. Mode I crack length, Resistancecurve and cohesive law parameters are characterised and discussed. The strain energy release rate (G(I)) is determined from the P-delta curve by the compliance-based beam method (CBBM). The crack tip opening displacement (w(1)) is determined by post-processing displacements measured by DIC. The cohesive law in mode I (sigma(1)-w(1)) is then obtained by numerical differentiation of the G(1)-w(1) relationship.