Antioxidant extraction process for Andean Oca by a photodiode array detector using response surface methodology

Application of Experimental Design techniques has proven to be essential in various research fields, due to its statistical capability of processing the effect of interactions among independent variables, known as factors, in a system’s response. Advantages of this methodology can be summarized in more resource and time efficient experimentations while providing more accurate results. This research emphasizes the quantification of 4 antioxidants extraction, at two different concentration, prepared according to an experimental procedure and measured by a Photodiode Array Detector. Experimental planning was made following a Central Composite Design, which is a type of DoE that allows to consider the quadratic component in Response Surfaces, a component that includes pure curvature studies on the model produced. This work was executed with the intention of analyzing responses, peak areas obtained from chromatograms plotted by the Detector’s system, and comprehending if the factors considered – acquired from an extensive literary review – produced the expected effect in response. Completion of this work will allow to take conclusions regarding what factors should be considered for the optimization studies of antioxidants extraction in a Oca (Oxalis tuberosa) matrix.

Fabrication and characterization of transparent conductive oxide surface sensors for electrocorticography – TrECoG

Understanding how the brain works has been one of the greatest goals of mankind. This desire fuels the scientific community to pursue novel techniques able to acquire the complex information produced by the brain at any given moment. The Electrocorticography (ECoG) is one of those techniques. By placing conductive electrodes over the dura, or directly over the cortex, and measuring the electric potential variation, one can acquire information regarding the activation of those areas. In this work, transparent ECoGs, (TrECoGs) are fabricated through thin film deposition of the Transparent Conductive Oxides (TCOs) Indium-Zinc-Oxide (IZO) and Gallium-Zinc-Oxide (GZO). Five distinct devices have been fabricated via shadow masking and photolithography. The data acquired and presented in this work validates the TrECoGs fabricated as efficient devices for recording brain activity. The best results were obtained for the GZO- based TrECoG, which presented an average impedance of 36 kΩ at 1 kHz for 500 μm diameter electrodes, a transmittance close to 90% for the visible spectrum and a clear capability to detect brain signal variations. The IZO based devices also presented high transmittance levels (90%), but with higher impedances, which ranged from 40 kΩ to 100 kΩ.

Novel antibiotic-loaded orthopaedic bone cements: insights on drug release profiles and biocompatibility

Acrylic bone cement (BC) is widely used as an anchor of artificial joints. Bacterial infection due to biofilm formation and inflammation are common and difficult to treat problems associated with commercial available BC formulations. Research on novel BC compositions is urgently needed. The main objective of this thesis was to develop a new biocompatible antibiotic-loaded BC with improved release profile. To achieve that aim several additives were incorporated, as an antibiotic (levofloxacin) to combat bacterial growth, an anti-inflammatory drug (diclofenac) to decrease the inflammatory process and two well-known and broadly used biopolymers, alginate and chitosan in order to increase matrix porosity, and in this way to intensify the amount of released drug. Novel BC formulations were tested in order to find the most suitable one that had potential to proceed to clinical application. Numerous tests were conducted as: a) evaluation of drug release profiles in different biomimetic media, b) mechanical and surface studies, c) microbiological activity testing against Staphylococcus aureus and d) in vitro biocompatibility assays (fibroblasts and osteoblasts). In general, the addition of biopolymers increased drug release, didn’t compromised BC mechanical properties and increased BC hydrophilicity. Microbiological testing revealed that Lev[BC]Chi was the only matrix that reduced significantly biofilm formation. On the contrary, alginate and diclofenac loading into BC seemed to increase biofilm growth. Biocompatibility studies showed some decrease in cell viability, in particularly on osteoblasts, mainly due to the high amounts of released drugs. In conclusion, the present work has shown that the matrix with more potential to proceed in further investigations was Lev[BC]Chi. Other conditions (namely additives and drugs concentrations) should be evaluated with the other tested BC matrices before being discharged.

Plasma nitriding of AA2011 alloy and surface characterization by NDT techniques

Al-Cu alloys are widely used in the aerospace and automotive industries due to their high specific strength in some tempered conditions. However, due to poor corrosion and wear resistance, they are often anodized and/or painted. Plasma nitriding has been proposed as an alternative, though the developments in this technique are still in a recent stage for Al alloys. Electrical characterization techniques are well implemented NDTs in the industry because of good accuracy associated with lower cost, compared to other methods. Some, like eddy currents and 4-point probe techniques, are often used in coating inspection. The objective of this study was to perform Al nitriding at low temperatures to minimize the tempering initial condition damage and to assess the feasibility of eddy currents technique as a method for evaluating surface properties. The work developed can be divided in two stages. The first one was the process tuning, done at the Shibaura Institute of Technology, in Tokyo; and the second was the electrical characterization done in Faculdade de Ciências e Tecnologia, UNL. Low temperature nitriding of AA2011 alloy specimens was successfully achieved. Electrical conductivity results show that lift-off measurements by eddy currents testing can be related to surface properties.

Machine diagnosis based on artificial immune systems

Nowadays, many of the manufactory and industrial system has a diagnosis system on top of it, responsible for ensuring the lifetime of the system itself. It achieves this by performing both diagnosis and error recovery procedures in real production time, on each of the individual parts of the system. There are many paradigms currently being used for diagnosis. However, they still fail to answer all the requirements imposed by the enterprises making it necessary for a different approach to take place. This happens mostly on the error recovery paradigms since the great diversity that is nowadays present in the industrial environment makes it highly unlikely for every single error to be fixed under a real time, no production stop, perspective. This work proposes a still relatively unknown paradigm to manufactory. The Artificial Immune Systems (AIS), which relies on bio-inspired algorithms, comes as a valid alternative to the ones currently being used. The proposed work is a multi-agent architecture that establishes the Artificial Immune Systems, based on bio-inspired algorithms. The main goal of this architecture is to solve for a resolution to the error currently detected by the system. The proposed architecture was tested using two different simulation environment, each meant to prove different points of views, using different tests. These tests will determine if, as the research suggests, this paradigm is a promising alternative for the industrial environment. It will also define what should be done to improve the current architecture and if it should be applied in a decentralised system.

Predicting market movement with Artificial Neural Networks

This paper presents an application of an Artificial Neural Network (ANN) to the prediction of stock market direction in the US. Using a multilayer perceptron neural network and a backpropagation algorithm for the training process, the model aims at learning the hidden patterns in the daily movement of the S&P500 to correctly identify if the market will be in a Trend Following or Mean Reversion behavior. The ANN is able to produce a successful investment strategy which outperforms the buy and hold strategy, but presents instability in its overall results which compromises its practical application in real life investment decisions.

Using artificial neural networks to generate trading signals for crude oil, copper and gold futures

In this thesis, a feed-forward, back-propagating Artificial Neural Network using the gradient descent algorithm is developed to forecast the directional movement of daily returns for WTI, gold and copper futures. Out-of-sample back-test results vary, with some predictive abilities for copper futures but none for either WTI or gold. The best statistically significant hit rate achieved was 57% for copper with an absolute return Sharpe Ratio of 1.25 and a benchmarked Information Ratio of 2.11.

The perfect paint in modern art conservation: a comparative study of 21st century vinyl emulsions

Contemporary painting places, and will continue to place, several questions about its meaning, its chemical nature, its durability and the best way to preserve it. This research aims at putting together comprehensive data on vinyl based paints, including their components, their properties, their aging behavior and their response to selected cleaning products. In this project degradation mechanisms of vinyl binders and formulations used in the 20th and 21st century were studied. Stability over time of selected vinyl polymers was assessed through natural indoor and artificially aging. The objective was to enhance knowledge and understanding of vinyl emulsion formulations and their performance over time. Overall conservation state of pictorial layers namely, adhesion, cohesion and discoloration of selected case studies from the Portuguese artist Julião Sarmento (b.1948) was correlated with the observed molecular level changes studied in laboratory experiments. Sarmento’s paintings were chosen due to conservation concerns (discoloration) on some of his works from the 90’s. Besides, research was carried out to start increasing the knowledge of what can be expected of PVAc based paints in terms of response to conservation treatments namely, surface cleaning. Artificial aging showed that the most recent formulations which are based on a poly(vinyl acetate), poly(vinyl chloride) and polyethylene terpolymer are less stable when compared to some homopolymer formulations. From the four pigments studied, titanium dioxide rutile and a carbon based black proved to be stabilizers for both types of polymer. The mixture lithopone plus calcium carbonate has showed to have a photocatalytic effect on the binders. The studied paintings showed to be in an overall good state of conservation except for the paintings created in the 90’s with white glue and a mixture of white lithoponeand calcium carbonate. Discoloration of this white paint seems to be irreversible and ongoing and is still a major concern. The disapearance of the plasticizer was the only change detected. The current works created by Sarmento are expected to be more stable as they were painted using the rutile titanium dioxide. Immersion/cleaning tests showed that vinyl based paints can be susceptible to water and organic solvents like ethanol as some evidences point to the removal/diffusion of additives from the paint. The observations made point to the need to further proceed in this research field.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.