Abstract
Nowadays, Magnetic Resonance Imaging is widely accepted and is becoming an increasingly useful imaging technique. For its functioning, in magnetic resonance equipments there are three main sources of electromagnetic fields: static magnetic fields, time-varying gradient fields and radiofrequencies fields. All of these fields have effects both on patients and workers. The main effect of radiofrequencies fields is heat deposition on human body, which causes tissue heating. There are international guidelines that establish occupational limits for its exposure. A good knowledge of radiofrequencies implications and its safety aspects is vital for better practices in magnetic resonance imaging.

Abstract
In this work we present a simple and low cost setup that allows obtaining the light spectra and measuring the wavelength of its features. It is based on a cheap transmission diffraction grating, an ordinary digital camera and using Tracker software to increase measuring accuracy. This equipment can easily be found in most schools. The experimental setup is easy to implement (the typical setup for a pocket spectroscope) replacing the eye with the camera. The calibration is done using a light source with a well-known spectrum. The acquired images are analyzed with Tracker (freeware software frequently used for motion studies). With this system, we have analyzed several light sources. As an example, the analysis of the spectra obtained with compact fluorescent lamp allowed to recognize the spectrum of mercury in the lamp, as expected. This spectral analysis is therefore useful in schools, among other topics, to enable the recognition of chemical elements through spectroscopy, and to alert students to the different spectra of illuminating light sources used in houses and public places.

Abstract
This paper presents the performance analysis of a new geometry sensing configuration for refractive index, based on surface plasmon resonance (SPR) in photonic crystal fiber (PCF) D-type optical fiber with a thin gold layer, using the finite element method (FEM). The configuration is analyzed in terms of the loss. The results are compared with a conventional SPR D-type and with a PCF D-type optical fiber sensor for refractive index measurement. The simulation results show an improvement of the sensitivity and resolution (3.70x10(3)nm/RIU and 2.72x10(-5)RIU, respectively, when considering an accurately spectral variation detection of 0.1nm).

Abstract
This paper presents the performance analysis of a sensing configuration of refractive index, based on surface plasmon resonance (SPR) in microstructured D-type optical fiber with a thin gold layer, using the finite-element method. The configuration is analyzed in terms of the loss and distribution Poynting vector. The results are compared with a conventional SPR D-type optical fiber sensor for refractive index measurement. The simulation results show an improvement of the sensitivity and resolution (10 x 10(3) nm/RIU and 9.8 x 10(-6) RIU, respectively, when considering an accurately spectral variation detection of 0.1 nm).

Abstract
A new sensing system for the detection of thermal deterioration of extra virgin olive oil based on long period fibre grating is reported. It is demonstrated the feasibility of long period fibre grating sensor for the analysis of high refractive index edible oils. The detection principle is the wavelength dependence of the attenuation bands of a TiO2-coated long period fibre grating on the changes in the refractive index of the medium surrounding the cladding surface of the optical fibre. The quality of the sensor was tested by measuring the wavelength shift of the attenuation bands in response to thermal deterioration of an edible oil (extra virgin olive oil) with refractive index higher than the fibre cladding. Absorption spectroscopy has allowed the effects of thermal deterioration to be detected, for example, in the decreasing of the absorption band at 677 nm, attributed to chlorophyll A. A detection limit of about 5 min at 180 A degrees C and of about 2 min at 225 A degrees C was observed for the sensing system. The proposed sensing system could lead to the realisation of a biochemical sensor for the food industry. The change in refractive index of extra virgin olive oil as a function of heating time and temperature was systematically measured for the first time.

Abstract
A methodology based on Fourier transform infrared spectroscopy with attenuated total reflectance sampling technique, combined with multivariate analysis, was developed to monitor adulteration of extra virgin olive oil (EVOO) with peanut oil (PEO). Principal components regression (PCR), partial least squares regression (PLS-R), and linear discriminant analysis (LDA) allowed quantification of percentage of adulteration based on spectral data of 192 samples. Wavenumbers associated with the biochemical differences among several types of edible oils were investigated by principal component analysis. Two sets of frequencies were selected in order to establish a robust regression model. Set A consisted on the frequency regions from 600 to 1,800 cm-1 and from 2,750 to 3,050 cm-1. Set B comprised 17 discrete peak absorbance frequencies for which the communality value was higher than 0.6. Analysis of an external set of 25 samples allowed the validation and evaluation of the predictability of the models. When using a specific set of discrete peak absorbance frequencies, the R 2 coefficients for the prediction were 0.960 and 0.977, and the root mean square error (RMSE) were 1.49 and 1.05% V/V when using the PCR or PLS-R models, respectively. LDA was successful in the binary classification presence/absence of PEO in adulterated EVOO (with 5% V/V of less of PEO). LDA provided 92.3% correct classification for the calibration set and 88.3% correct classification when cross-validated. The lowest detectable concentration of PEO in EVOO was the lowest adulteration level studied, 0.5% V/V.