Front Face Fluorescence Spectroscopy Combined with PLS-DA Allows to Monitor Chemical Changes of Edible Vegetable Oils during Storage at 60 °C

In this work, front-face fluorescence spectroscopy coupled with chemometric tools are used for the monitoring of rapeseed, sunflower, extra virgin olive, and linseed oil. The oil samples are heated at 60 °C for up to 15 days. The fluorescence excitation spectra are scanned in the range of 270–420 nm and 250–310 nm after emission wavelength set at 450 and 330 nm, respectively. The primary and secondary lipid oxidation products are also determined on the same oil samples. By applying partial least square discriminant analysis (PLS-DA) to each spectral collection obtained after emission set at 450 and 330 nm, clear discrimination of edible oil samples according to their botanical types, and sometimes aging, is obtained. Practical Applications: This study shows that oxidation of rapeseed, sunflower, extra virgin olive, and linseed oil monitored different trends due to their difference in composition. The presented results demonstrated the capability of the front-face fluorescence spectroscopy to differentiate four vegetable oils contained in capped and uncapped flasks indicating the evolution of primary and secondary indicators of oxidation during the storage period. The technology can be exploited at the industrial level for monitoring in a non-destructive manner the level of oxidation of edible oil.     

Extensive malignant schwannoma of the sciatic nerve. Contribution of imaging techniques

The authors reports a case of malignant schwannoma of sciatic nerve. Clinically, this tumor was manifested by a progressive tumefaction of the leg, and moderate pain, without functional signs. The origin of the sciatic nerve has been suspected by computed tomography, because its location, the vascular contacts, and the lesion's extension. Biopsy leads to confirm the nerve tumor, and precised the histologic type: malignant schwannoma. Local, regional and general extension did not premise treatment.     

A Distributed Artificial Network Solving Complex and Multiple Causal Associations

Causal reasoning (known also as abduction) is a hard task that cognitive agents perform reliably and quickly. A particular class of causal reasoning that raises several difficulties is the cancellation class. Cancellation occurs when a set of causes (hypotheses) cancel each other's explanation with respect to a given effect (observation). For example, a cloudy sky may suggest a rainy weather; whereas a shiny sky may suggest the absence of rain. In the current paper, we extend a recent neural model to handle cancellation interactions. We conduct a sensitivity analysis of this proposal on ad hoc problems put at extreme cases. Finally, we test the model on a large database and propose objective criteria to quantitatively evaluate its performance. Simulation results are very satisfactory and should encourage research.     

Development of a rapid method based on front face fluorescence spectroscopy for the monitoring of egg freshness: 1—evolution of thick and thin egg albumens

In this preliminary study, the intrinsic fluorescence of thick and thin egg albumens was evaluated as a possible rapid method for the monitoring of egg freshness. The fluorescence emission spectra of tryptophan residues (excitation: 290 nm; emission: 305–430 nm) of proteins and fluorescent Maillard reaction products (excitation: 360; emission: 380–580 nm) were recorded directly on thick and thin albumen samples within 2–3, 4, 5, 9, 10, 12, 16, 18, 23, 25 and 29 days of storage. Principal component analysis (PCA) and factorial discriminant analysis (FDA) were applied to the spectra data sets. Considering tryptophan fluorescence spectra recorded on thick egg albumen, correct classification was observed for 62.8 and 54.3% for the calibration and the validation sets, respectively. Better classification was obtained from thin egg albumen since 67.3 and 69.1% of samples were correctly classified. Considering fluorescent Maillard reaction products, the similarity map determined by the principal components (PCs) 1 and 2 showed a discrimination of eggs as a function of their storage time on both thick and thin albumens. The percentage of samples correctly classified into four groups by the FDA was 97.4 and 91.4% for the calibration and validation thick albumen samples, respectively. It was concluded that fluorescent Maillard reaction products could be considered as fingerprints that may allow the discrimination between fresh and aged eggs.     

A three-dimensional statistical framework for performance measurement of robotic systems

A three-dimensional statistical evaluation framework for performance measurement of robotic systems has been developed. A specific experimental setup has been designed, implemented, and evaluated for different robot characteristics (velocities and target location) and for a specific task. A statistical analysis method to evaluate performance is demonstrated. Results indicate the significance of this methodology since the capabilities and performance of a particular robot depend on actual operating conditions.