Abstract
Fourier transform infrared spectroscopy based on attenuated total reflectance sampling technique, combined with multivariate analysis methods was used to monitor the adulteration of pure sunflower oil (SO) with thermally deteriorated oil (TDO). Contrary to published research, in this work, SO was thermally deteriorated in the absence of foodstuff. SO samples were exposed to temperatures between 125 and 225°C from 6 to 24 h. Quantification of adulteration of SO with TDO, based on principal components regression (PCR), partial least squares regression (PLS-R), and linear discriminant analysis (LDA) applied to mid-infrared spectra and to their first and second derivatives is reported for the first time. Infrared frequencies associated with the biochemical differences between TDO samples deteriorated in different conditions were investigated by principal component analysis (PCA). LDA was effective in the twofold classification presence/absence of TDO in adulterated SO (with 5% V/V of less of TDO). It provided 93.7% correct classification for the calibration set and 91.3% correct classification when cross-validated. A detection limit of 1% V/V of TDO in SO was determined. Investigation of an external set of samples allowed the evaluation of the predictability of the models. The regression coefficient (R 2) for prediction was 0.95 and 0.96 and the RMSE was 2.1 and 1.9% V/V when using the PCR or PLS-R models, respectively, and the first derivative of spectra. To the best of our knowledge, no investigation of adulteration of SO with TDO based on PCR, PLS-R, and LDA has been reported so far.

Abstract

Abstract
Statistical data analysis methods are well known for their difficulty in handling large number of instances or large number of parameters. This is most noticeable in the presence of "big data", i.e., of data that are heterogeneous, and come from several sources, which makes their volume increase very rapidly. In this paper, we study popular and well-known statistical functions generally applied to data analysis, and assess their performance using our own implementation (DataIP) 1, MatLab and R. We show that DataIP outperforms MatLab and R by several orders of magnitude and that the design and implementation of these functions need to be rethought to adapt to today's data challenges.

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Abstract
The green alga Pseudokirchneriella subcapitata has been widely used in ecological risk assessment, usually based on the impact of the toxicants in the alga growth. However, the physiological causes that lead algal growth inhibition are not completely understood. This work aimed to evaluate the biochemical and structural modifications in P. subcapitata after exposure, for 72 h, to three nominal concentrations of Cd(II), Cr(VI), Cu(II) and Zn(II), corresponding approximately to 72 h-EC10 and 72 h-EC50 values and a high concentration (above 72 h-EC90 values). The incubation of algal cells with the highest concentration of Cd(II), Cr(VI) or Cu(II) resulted in a loss of membrane integrity of 16,38 and 55%, respectively. For all metals tested, an inhibition of esterase activity, in a dose-dependent manner, was observed. Reduction of chlorophyll a content, decrease of maximum quantum yield of photosystem II and modification of mitochondrial membrane potential was also verified. In conclusion, the exposure of P. subcapitata to metals resulted in a perturbation of the cell physiological status. Principal component analysis revealed that the impairment of esterase activity combined with the reduction of chlorophyll a content were related with the inhibition of growth caused by a prolonged exposure to the heavy metals.

Abstract
The goal of this project, one of the proposals of the EPS@ISEP 2014 Spring, was to develop an Aquaponics System. Over recent years Aquaponics systems have received increased attention due to its possibilities in helping reduce strain on resources within 1st and 3rd world countries. Aquaponics is the combination of Hydroponics and Aquaculture and mimics a natural environment in order to successfully apply and enhance the understanding of natural cycles within an indoor process. By using this knowledge of natural cycles it was possible to create a system with the capabilities similar to that of a natural environment with the benefits of electronic adaptions to enhance the overall efficiency of the system. The multinational team involved in its development was composed of five students, from five countries and fields of study. This paper covers their solution, involving overall design, the technology involved and the benefits it could bring to the current market. The team was able to achieve the final rendered Computer Aided Design (CAD) drawings, successfully performed all the electronic testing, and designed a solution under budget. Furthermore, the solution presented was deeply studied from the sustainability viewpoint and the team also developed a product specific marketing plan. Finally, the students involved in this project obtained new knowledge and skills.