On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Object oriented simulation of hybrid renewable energy systems focused on supervisor control

EFTA 2009

Making object-oriented databases more knowledgeable (From ADAM to ABEL)

Tesis leida en la Universidad de Aberdeen. 178 p.

Mugilid Fish Are Sentinels of Exposure to Endocrine Disrupting Compounds in Coastal and Estuarine Environments

Effects on fish reproduction can result from a variety of toxicity mechanisms first operating at the molecular level. Notably, the presence in the environment of some compounds termed endocrine disrupting chemicals (EDCs) can cause adverse effects on reproduction by interfering with the endocrine system. In some cases, exposure to EDCs leads to the animal feminization and male fish may develop oocytes in testis (intersex condition). Mugilid fish are well suited sentinel organisms to study the effects of reproductive EDCs in the monitoring of estuarine/marine environments. Up-regulation of aromatases and vitellogenins in males and juveniles and the presence of intersex individuals have been described in a wide array of mullet species worldwide. There is a need to develop new molecular markers to identify early feminization responses and intersex condition in fish populations, studying mechanisms that regulate gonad differentiation under exposure to xenoestrogens. Interestingly, an electrophoresis of gonad RNA, shows a strong expression of 5S rRNA in oocytes, indicating the potential of 5S rRNA and its regulating proteins to become useful molecular makers of oocyte presence in testis. Therefore, the use of these oocyte markers to sex and identify intersex mullets could constitute powerful molecular biomarkers to assess xenoestrogenicity in field conditions.

Analysis of multivariate stochastic signals sampled by on-line particle analyzers: Application to the quantitative assessment of occupational exposure to NOAA in multisource industrial scenarios (MSIS)

In multisource industrial scenarios (MSIS) coexist NOAA generating activities with other productive sources of airborne particles, such as parallel processes of manufacturing or electrical and diesel machinery. A distinctive characteristic of MSIS is the spatially complex distribution of aerosol sources, as well as their potential differences in dynamics, due to the feasibility of multi-task configuration at a given time. Thus, the background signal is expected to challenge the aerosol analyzers at a probably wide range of concentrations and size distributions, depending of the multisource configuration at a given time. Monitoring and prediction by using statistical analysis of time series captured by on-line particle analyzers in industrial scenarios, have been proven to be feasible in predicting PNC evolution provided a given quality of net signals (difference between signal at source and background). However the analysis and modelling of non-consistent time series, influenced by low levels of SNR (Signal-Noise Ratio) could build a misleading basis for decision making. In this context, this work explores the use of stochastic models based on ARIMA methodology to monitor and predict exposure values (PNC). The study was carried out in a MSIS where an case study focused on the manufacture of perforated tablets of nano-TiO2 by cold pressing was performed

Occupational exposure to nano-TiO2 in the life cycle steps of new depollutant mortars used in construction

The present work is focused on the measurement of workers exposure to nano-TiO2 in the life cycle steps of depollutant mortars. It has been done in the framework of the SCAFFOLD project, which aims at the management of potential risks arising from the use of manufactured nanomaterials in construction. Main findings can be summarized as follows: (1) The occupational exposure to nano-TiO2 is below 0.3 mg/m(3) for all measured scenarios. The highest concentrations were measured during the cleaning task (in the nano-TiO2 manufacturing process) and during the application (spraying) of depollutant coatings on a wall. (2) It was found a high release of particles above the background in several tasks as expected due to the nature of the activities performed. The maximum concentration was measured during drilling and during adding powder materials (mean total particle concentration up to 5.591E+04 particles/cm(3) and 5.69E+04 particles/cm(3)). However, considering data on total particle concentration released, no striking differences have been observed when tasks have been performed using conventional materials in the sector (control) and when using materials doped with nano-objects.