Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

ANTIFUNGAL ACTIVITY OF SILVER NANOPARTICLES OBTAINED BY GREEN SYNTHESIS

Silver nanoparticles (AgNPs) are metal structures at the nanoscale. AgNPs have exhibited antimicrobial activities against fungi and bacteria; however synthesis of AgNPs can generate toxic waste during the reaction process. Accordingly, new routes using non-toxic compounds have been researched. The proposal of the present study was to synthesize AgNPs using ribose as a reducing agent and sodium dodecyl sulfate (SDS) as a stabilizer. The antifungal activity of these particles against C. albicans and C. tropicalis was also evaluated. Stable nanoparticles 12.5 ± 4.9 nm (mean ± SD) in size were obtained, which showed high activity against Candida spp. and could represent an alternative for fungal infection treatment.

Insights into cell wall synthesis and cell division in Staphylococcus aureus

Dissertation presented to obtain the Ph.D degree in Biology

Quantum dots: synthesis, functionalization and bioconjugation for biological applications

Dissertation presented to obtain the Ph.D degree in Engineering Sciences and Technology

Candida albicans PROTEIN PROFILE CHANGES IN RESPONSE TO THE BUTANOLIC EXTRACT OF Sapindus saponariaL.

Candida albicans is an opportunistic human pathogen that is capable of causing superficial and systemic infections in immunocompromised patients. Extracts of Sapindus saponaria have been used as antimicrobial agents against various organisms. In the present study, we used a combination of two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) to identify the changes in protein abundance of C. albicans after exposure to the minimal inhibitory concentration (MIC) and sub-minimal inhibitory concentration (sub-MIC) of the butanolic extract (BUTE) of S. saponaria and also to fluconazole. A total of six different proteins with greater than 1.5 fold induction or repression relative to the untreated control cells were identified among the three treatments. In general, proteins/enzymes involved with the glycolysis (GPM1, ENO1, FBA1), amino acid metabolism (ILV5, PDC11) and protein synthesis (ASC1) pathways were detected. In conclusion, our findings reveal antifungal-induced changes in protein abundance of C. albicans. By using the previously identified components of the BUTE of S. saponaria(e.g., saponins and sesquiterpene oligoglycosides), it will be possible to compare the behavior of compounds with unknown mechanisms of action, and this knowledge will help to focus the subsequent biochemical work aimed at defining the effects of these compounds.