Abstract
A methodology based on Fourier transform infrared (FTIR) spectroscopy, combined with multivariate analysis methods, was applied in order to monitor extra virgin olive oils produced from three distinct cultivars on different maturation stages. For the first time, this kind of methodology is used for the simultaneous discrimination of the maturation stage, and different cultivars. Principal component analysis and discriminant analysis were utilised to create a model for the discrimination of olive oil samples. Partial least squares regression was employed to design calibration models for the determination of chemical parameters. The performance of these models was based on the multiple coefficient of determination (R-2), the root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV). The prediction models for the chemical parameters resulted in a R-2 ranged from 0.93 to 0.99, a RMSEC ranged from 1% to 4% and a RMSECV from 2% to 5%. It has been shown that this kind of approach allows to distinguish the different cultivars, and to clearly discern the different maturation stages, in each one of these distinct cultivars. Furthermore, the results demonstrated that FTIR spectroscopy in tandem with chemometric techniques allows the creation of viable and accurate models, suitable for correlating the data collected by FTIR spectroscopy, with the chemical composition of the EVOOs, obtained by standard methods.

Abstract
Extra virgin olive oils produced from three cultivars on different maturation stages were characterized using Raman spectroscopy. Chemometric methods (principal component analysis, discriminant analysis, principal component regression and partial least squares regression) applied to Raman spectral data were utilized to evaluate and quantify the statistical differences between cultivars and their ripening process. The models for predicting the peroxide value and free acidity of olive oils showed good calibration and prediction values and presented high coefficients of determination ( > 0.933). Both the R-2, and the correlation equations between the measured chemical parameters, and the values predicted by each approach are presented; these comprehend both PCR and PLS, used to assess SNV normalized Raman data, as well as first and second derivative of the spectra. This study demonstrates that a combination of Raman spectroscopy with multivariate analysis methods can be useful to predict rapidly olive oil chemical characteristics during the maturation process.

Abstract
We investigated the reductive intramolecular cyclization of bromopropargyl ethers derivatives, catalyzed by electrogenerated (1,4,8,11-tetramethyl-1,4,8,11-tetraaza-cyclotetradecane)nickel(I), [Ni(tmc)]+ as the catalysts in N,N,N-trimethyl-N-(2- hydroxyethyl)ammonium bis(trifluoromethylsulfonyl)imide,[N1112(OH)][NTf2] and 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, [C2mim][NTf2] by cyclic voltammetry and controlled-potential electrolysis. The results show that the reaction leads to the formation of the expected cyclic compounds, which are important intermediates in the synthesis of natural products with possible biological activities. © The Electrochemical Society.

Abstract
Childhood lead poisoning remains a significant public health issue, especially in the United States, where the most common source of exposure is lead-based paint (LBP). X-Ray Fluorescence (XRF) analysis is still the most widely used method for detecting LBP in the field. Although portable XRF instrumentation based on excitation from a 57Co radioisotope has been used for more than 30 years, there have been few reports documenting its performance. Here we describe a study that was conducted by the New York State Department of Health's Wadsworth Center laboratory in response to concerns raised by field users of the RMD LPA-1 XRF analyzer (Protec Instrument Corp.) working across the state. The performance issues were investigated for ten field units: five reported as problematic based on user feedback, and 5 that were not. Accuracy was assessed against NIST SRM 2579 lead in paint, which was developed specifically for use with portable XRF analyzers. On average, the absolute bias found was within ±20% at the threshold value for LBP (1.0 mg cm-2) based on the NIST SRM 2579 data. Calibration blocks provided with each analyzer for quality assurance monitoring were evaluated using a different XRF analyzer (Niton XLT 3t 700s GOLDD) operated in painted products mode (µg cm-2). However, when the Niton XRF analyzer was checked against NIST SRM 2579, it was found to have a negative bias. That negative bias was easily corrected using a "calibration" curve with a quadratic fit to the data. NIST-corrected data obtained for the calibration blocks showed assigned values were within the manufacturer's stated tolerance range, albeit with a consistent positive bias. The root cause for 3 of the 5 problematic devices was likely incorrect positioning of the device. A low bias for a fourth device was likely caused by a deteriorated calibration block, and the fifth device, while just within the manufacturer's technical specifications, was the only one confirmed with a low bias. Increased operator training may resolve some of the issues reported in the field; on-going competency assessments may be warranted for this hand-held technology. © 2014 The Royal Society of Chemistry.

Abstract
Fiber Bragg grating sensors were attached to the surface of a rechargeable lithium battery in order to monitor its thermal and strain fluctuations through charge and different discharge C rates. During the discharge process above 1C, it were observed, a temperature and strain fluctuations of a 4.12 +/- 0.67 degrees C and 24.64 +/- 6.02 mu epsilon, respectively. In the regular charge process, a temperature and strain variation of 1.03 +/- 0.67 degrees C and 15.86 +/- 6.02 mu epsilon, were detected.

Abstract