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Livro de bordo do 6º Retiro Doutoral em Média-Arte Digital – Ad Astra Per Aspera”, Centro Cultural Magalhães Lima, Alfama, Lisboa, 21-27 julho de 2018.

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Abstract
A. Campbell, M. Gutierrez and M. Lancelott, Operating Model Canvas, 2017, Zaltbommel, Netherlands: Van Haren Publishing, 224 pp., $41.00. ISBN: 078-0401800716.

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The wine sector requires quick and reliable methods for Vitis vinifera L. varietal identification. The number of V. vinifera varieties is estimated in about 5,000 worldwide. Single Nucleotide Polymorphisms (SNPs) represent the most basic and abundant form of genetic sequence variation, being adequate for varietal discrimination. The aim of this work was to develop DNA-based assays suitable to detect SNP variation in V. vinifera, allowing varietal discrimination. Genotyping by sequencing allowed the detection of eleven SNPs on two genes of the anthocyanin pathway, the flavanone 3-hydroxylase (F3H, EC: 1.14.11.9), and the leucoanthocyanidin dioxygenase (LDOX, EC 1.14.11.19; synonym anthocyanidin synthase, ANS) in twenty V. vinifera varieties. Three High Resolution Melting (HRM) assays were designed based on the sequencing information, discriminating five of the 20 varieties: Alicante Bouschet, Donzelinho Tinto, Merlot, Moscatel Galego and Tinta Roriz. Sanger sequencing of the HRM assay products confirmed the HRM profiles. Three probes, with different lengths and sequences, were used as bio-recognition elements in an optical biosensor platform based on a long period grating (LPG) fiber optic sensor. The label free platform detected a difference of a single SNP using genomic DNA samples. The two different platforms were successfully applied for grapevine varietal identification.

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The energy demand of the residential sector and the adjacent option for fossil fuels has negative consequences by both greenhouse gases (GHG) and other air pollutants emissions. Since home energy demand consists mainly of energy requirements for space and water heating along with the energy dedicated for appliances, different strategies that aim to stimulate an efficient use of energy need to be reinforced at all levels of human activity. In this paper, a comprehensive comparison is made between the thermostat (ON/OFF), proportional-integral-derivative (PID) and Model Predictive Control (MPC) control models of a domestic heating, ventilation and air conditioning (HVAC) system controlling the temperature of a room. A power interface that adjusts the MPC dynamic range of the output command signal into a discrete two level control signal is proposed, as a new contribution to earlier studies. The model of the house with local solar microgeneration is assumed to be located in a Portuguese city. The household of the case study is subject to the local solar irradiance, temperature and 5 Time-of-Use (Toll) electricity rates applied on an entire week of August 2016. The purpose of the optimisation is to achieve the best compromise between temperature comfort levels and energy costs and also to assess which is the best electricity ToU rate option provided by the electricity retailer for the residential sector. Also, for each electrical load of the HVAC system, the energy and cost are calculated and the results are presented by varying the different MPC weight combination in order to obtain the best possible solution and increase the quality of the model. Finally, after the best tariff and controller are determined, the impact of the solar generation is assessed.

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Text Mining and NLP techniques are a hot topic nowadays. Researchers thrive to develop new and faster algorithms to cope with larger amounts of data. Particularly, text data analysis has been increasing in interest due to the growth of social networks media. Given this, the development of new algorithms and/or the upgrade of existing ones is now a crucial task to deal with text mining problems under this new scenario. In this paper, we present an update to TextRank, a well-known implementation used to do automatic keyword extraction from text, adapted to deal with streams of text. In addition, we present results for this implementation and compare them with the batch version. Major improvements are lowest computation times for the processing of the same text data, in a streaming environment, both in sliding window and incremental setups. The speedups obtained in the experimental results are significant. Therefore the approach was considered valid and useful to the research community.