Previsão da Classificação da qualidade dos efluentes da indústria petrolífera com recurso a sistemas inteligentes

O presente trabalho realizou-se na Refinaria de Sines e teve como principal objectivo a utilização de ferramentas oriundas da Área Científica da Inteligência Artificial no desenvolvimento de modelos de previsão da classificação da Água Residual Industrial de acordo com a Legislação em vigor, com vista à minimização dos impactes ambientais e das tarifas aplicadas pela Concessionária (Águas de Santo André) à Refinaria. Actualmente a avaliação da qualidade do efluente é realizada através de métodos analíticos após colheita de uma amostra do efluente final. Esta abordagem é muito restritiva já que não permite actuar sobre o efluente em questão pois apenas pode evitar que, no futuro, uma mistura semelhante volte a ser refinada. Devido a estas limitações, o desenvolvimento de modelos de previsão baseados em Data Mining mostrou ser uma alternativa para uma questão pró-activa da qualidade dos efluentes que pode contribuir decisivamente para o cumprimento das metas definidas pela Empresa. No decurso do trabalho, foram desenvolvidos dois modelos de previsão da qualidade do efluente industrial com desempenhos muito semelhantes. Um deles utiliza a composição das misturas processadas e o outro, utiliza informações relativas ao crude predominante na mistura. ABSTRACT; This study has taken place at the Sines Refinery and its main objective is the use of Artificial Intelligence tools for the development of predictive models to classify industrial residual waters according with the Portuguese Law, based on the characteristics of the mixtures of crude oil that arrive into the Refinery to be processed, to minimize the Environmental impacts and the application of taxes. Currently, the evaluation of the quality of effluent is performed by analytical methods after harvesting a sample of the final effluent. This approach is very restrictive since it does not act on the intended effluent; it can only avoid that in the future a similar mixture is refined. Duet these limitations, the development of forecasting models based on Data Mining has proved to be an alternative on the important issue which is the quality of effluent, which may contribute to the achievement of targets set by the Company. During this study, two models were developed to predict the quality of industrial effluents with very similar performances. One uses the composition of processed mixtures and the other uses information regarding the predominant oil in the mixture.

Recent Developments in Wine Tartaric Stabilization

Tartrate precipitation is still a relevant subject in Enology, being one of the most common problems of wine physical-chemical instability. Potassium bitartrate and calcium tartrate precipitations are undesirable phenomena which can occur in bottled wines, especially when these are stored at low temperatures. The occurrence of tartrate salt crystals (potassium hydrogen tartrate – KHT and calcium tartrate – CaT) in bottles has severe consequences in the final aspect of the wine and therefore on the consumer’s acceptance, making tartrate wine stabilization virtually mandatory before bottling. Currently, several solutions to prevent this haze are available: subtractive methods including the conventional cold treatments that promote the cristalization of KHT, removal of potassium and calcium ions either by electrodialysis or ion exchange resins; and additive methods such as the addition of carboxymethylcellulose, mannoproteins or metatartaric acid. For monitoring the KHT stability, several analytical methods have been developed based on conductivity evaluation, namely the mini-contact test and the saturation temperature measurements (TS). These methods will also be revisited, aiming to raise awareness of their utility as tools in quality control of wines. This review addresses tartrate precipitation subject and the most recent preventive solutions available, pointing out the advantages and drawbacks of each one, and its impact on the final characteristics of the wine.

Quantification of free auxins in semi-hardwood plant cuttings and microshoots by dispersive liquid–liquid microextraction/microwave derivatization and GC/MS analysis

Several studies have suggested that differences in the natural rooting ability of plant cuttings could be attributed to differences in endogenous auxin levels. Hence, during rooting experiments, it is important to be able to routinely monitor the evolution of endogenous levels of plant hormones. This work reports the development of a new method for the quantification of free auxins in auxin-treated Olea europaea (L.) explants, using dispersive liquid–liquid microextraction (DLLME) and microwave assisted derivatization (MAD) followed by gas chromatography/mass spectrometry (GC/MS) analysis. Linear ranges of 0.5–500 ng mL 1 and 1–500 mg mL 1 were used for the quantification of indole-3-acetic acid (IAA) and indole-3-butyric acid (IBA), respectively. Determined by serial dilutions, the limits of detection (LOD) and quantification (LOQ) were 0.05 ng mL 1 and 0.25 ng mL 1, respectively for both compounds. When using the calibration curve for determination, the LOQ corresponded to 0.5 ng mL 1 (IAA) and 0.5 mg mL 1 (IBA). The proposed method proved to be substantially faster than other alternatives, and allowed free auxin quantification in real samples of semi-hardwood cuttings and microshoots of two olive cultivars. The concentrations found in the analyzed samples are in the range of 0.131–0.342 mg g 1 (IAA) and 20–264 mg g 1 (IBA).

José de Escovar at the Chapel of the Souls: Technical and Material Study of a 1603 Panel Painting

This article reports the preliminary results of a technical and material study carried out on a 17th century panel painting located at the Chapel of the Souls in the main church of Vila Nova da Baronia (30 km away from Evora city, in southern Portugal). This painting is attributed to Jose the Escovar, a painter that worked for Evora Archiepiscopate between 1583 and 1622. Jose the Escovar is known by his mural paintings all across the Alentejo region. This is the first time that a panel painting made by this artist was studied. Analytical methods used included in situ technical photography (visible (Vis), raking light (RAK), infrared (IR), and ultraviolet (UV)), optical microscopy of cross sections, scanning electron microscopy with energy dispersive X-ray spectrometry (SEM-EDS), micro Raman spectroscopy, and micro Fourier transform infrared spectroscopy (m-FT-IR). The goal was to ascertain the techniques and colored materials used by Escovar on this painting so that the data can be used in future comparisons with others works attributed to this painter based on stylistic aspects.

God is in the detail. Gold, silver and polychromy

The visible polychromy of a wooden sculpture representing St. John the Evangelist, from Museu Nacional de Arte Antiga, Lisbon (Portugal) presents several techniques that complement each other on the creation of a sumptuous estofado. This case-study allowed the survey on gilding, silvering and polychromy practices, and observations on their execution are briefly reported and documented with results from a multi-analytical approach. Examination included digital photomicrography and the observation of micro-samples cross-sections, while material identification resorted to several analytical methods that included scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDS) and X-ray diffraction (XRD).