Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Quantitative image analysis as a tool for Yarrowia lipolytica dimorphic growth evaluation in different culture media

Yarrowia lipolytica, a yeast strain with a huge biotechnological potential, capable to produce metabolites such as γ-decalactone, citric acid, intracellular lipids and enzymes, possesses the ability to change its morphology in response to environmental conditions. In the present study, a quantitative image analysis (QIA) procedure was developed for the identification and quantification of Y. lipolytica W29 and MTLY40-2P strains dimorphic growth, cultivated in batch cultures on hydrophilic (glucose and N-acetylglucosamine (GlcNAc) and hydrophobic (olive oil and castor oil) media. The morphological characterization of yeast cells by QIA techniques revealed that hydrophobic carbon sources, namely castor oil, should be preferred for both strains growth in the yeast single cell morphotype. On the other hand, hydrophilic sugars, namely glucose and GlcNAc caused a dimorphic transition growth towards the hyphae morphotype. Experiments for γ-decalactone production with MTLY40-2P strain in two distinct morphotypes (yeast single cells and hyphae cells) were also performed. The obtained results showed the adequacy of the proposed morphology monitoring tool in relation to each morphotype on the aroma production ability. The present work allowed establishing that QIA techniques can be a valuable tool for the identification of the best culture conditions for industrial processes implementation.

Innovative methodologies for the enhancement of the flexural strengthening performance of NSM CFRP technique for RC beams

Tese de Doutoramento em Engenharia Civil

Enhancement of adhesion and promotion of osteogenic differentiation of human adipose stem cells by poled electroactive poly(vinylidene fluoride)

Poly(vinylidene fluoride) (PVDF) is a biocompatible material with excellent electroactive properties. Non-electroactive α-PVDF and electroactive β-PVDF were used to investigate the substrate polarization and polarity influence on the focal adhesion size and number as well as on human adipose stem cells (hASCs) differentiation. hASCs were cultured on different PVDF surfaces adsorbed with fibronectin and focal adhesion size and number, total adhesion area, cell size, cell aspect ratio and focal adhesion density were estimated using cells expressing EGFP-vinculin. Osteogenic differentiation was also determined using a quantitative alkaline phosphatase assay. The surface charge of the poled PVDF films (positive or negative) influenced the hydrophobicity of the samples, leading to variations in the conformation of adsorbed extracellular matrix (ECM) proteins, which ultimately modulated the stem cell adhesion on the films and induced their osteogenic differentiation.

Dissolution enhancement of active pharmaceutical ingredients by therapeutic deep eutectic systems

A therapeutic deep eutectic system (THEDES) is here defined as a deep eutectic solvent (DES) having an active pharmaceutical ingredient (API) as one of the components. In this work, THEDESs are proposed as enhanced transporters and delivery vehicles for bioactive molecules. THEDESs based on choline chloride (ChCl) or menthol conjugated with three different APIs, namely acetylsalicylic acid (AA), benzoic acid (BA) and phenylacetic acid (PA), were synthesized and characterized for thermal behaviour, structural features, dissolution rate and antibacterial activity. Differential scanning calorimetry and polarized optical microscopy showed that ChCl:PA (1:1), ChCl:AA (1:1), menthol:AA (3:1), menthol:BA (3:1), menthol:PA (2:1) and menthol:PA (3:1) were liquid at room temperature. Dissolution studies in PBS led to increased dissolution rates for the APIs when in the form of THEDES, compared to the API alone. The increase in dissolution rate was particularly noticeable for menthol-based THEDES. Antibacterial activity was assessed using both Gram-positive and Gram-negative model organisms. The results show that all the THEDESs retain the antibacterial activity of the API. Overall, our results highlight the great potential of THEDES as dissolution enhancers in the development of novel and more effective drug delivery systems.