Mixture design and multivariate image analysis to monitor the colour of strawberry yoghurt purée

Food colour is a commercial added value, since it represents the first appealing factor for consumers. In this context, this study was aimed at evaluating the effect of strawberry yoghurt purée (SYP) formulation on the corresponding colour and on its variation over time, which is mainly due to degradation and browning phenomena. To this aim, a combined approach was used that included mixture design and multivariate analysis of RGB images. Strawberry purée, sugar, lemon juice and two types of thickener were mixed in different proportions by I-optimal mixture design to obtain 44 SYP formulations. The samples were subjected to light and temperature stress conditions for five weeks; during this time the RGB images of the samples were acquired using a flatbed scanner, along with the images of the corresponding control samples. The dimensionality of the acquired images was reduced by two different approaches: i) the conversion of images into signals, namely colourgrams, which can be seen as the colour fingerprint of the imaged samples, and ii) the calculation of the median values of various colour-related parameters. The colourgrams dataset was then subjected to exploratory data analysis using Principal Component Analysis, while the median values of colour-related parameters were analysed using Response Surface Methodology and Partial Least Squares-Discriminant Analysis. The aim of data analysis was both to find the best colour parameters to describe colour variability over time, and to investigate the cause-effect relationship between mixture proportions and colour response. The results highlighted that, among the considered colour parameters, relative green (i.e., the ratio of green to lightness) and red could be used to monitor colour changes. Colour variation due to stress conditions was more pronounced for samples with a high percentage of strawberry purée, and the type of thickener also affected the colour degradation kinetics

Noise reduction in muon tomography for detecting high density objects

The muon tomography technique, based on multiple Coulomb scattering of cosmic ray muons, has been proposed as a tool to detect the presence of high density objects inside closed volumes. In this paper a new and innovative method is presented to handle the density fluctuations (noise) of reconstructed images, a well known problem of this technique. The effectiveness of our method is evaluated using experimental data obtained with a muon tomography prototype located at the Legnaro National Laboratories (LNL) of the Istituto Nazionale di Fisica Nucleare (INFN). The results reported in this paper, obtained with real cosmic ray data, show that with appropriate image filtering and muon momentum classification, the muon tomography technique can detect high density materials, such as lead, albeit surrounded by light or medium density material, in short times. A comparison with algorithms published in literature is also presented

Precision measurements of Linear Scattering Density using Muon Tomography

We demonstrate that muon tomography can be used to precisely measure the properties of various materials. The materials which have been considered have been extracted from an experimental blast furnace, including carbon (coke) and iron oxides, for which measurements of the linear scattering density relative to the mass density have been performed with an absolute precision of 10%. We report the procedures that are used in order to obtain such precision, and a discussion is presented to address the expected performance of the technique when applied to heavier materials. The results we obtain do not depend on the specific type of material considered and therefore they can be extended to any application.Comment: 16 pages, 4 figure

Multi-target prediction of wheat flour quality parameters with near infrared spectroscopy

Near Infrared (NIR) spectroscopy is an analytical technology widely used for the non-destructive characterisation of organic samples, considering both qualitative and quantitative attributes. In the present study, the combination of Multi-target (MT) prediction approaches and Machine Learning algorithms has been evaluated as an effective strategy to improve prediction performances of NIR data from wheat flour samples. Three different Multi-target approaches have been tested: Multi-target Regressor Stacking (MTRS), Ensemble of Regressor Chains (ERC) and Deep Structure for Tracking Asynchronous Regressor Stack (DSTARS). Each one of these techniques has been tested with different regression methods: Support Vector Machine (SVM), Random Forest (RF) and Linear Regression (LR), on a dataset composed of NIR spectra of bread wheat flours for the prediction of quality-related parameters. By combining all MT techniques and predictors, we obtained an improvement up to 7% in predictive performance, compared with the corresponding Single-target (ST) approaches. The results support the potential advantage of MT techniques over ST techniques for analysing NIR spectra

Enhanced catecholamine transporter binding in the locus coeruleus of patients with early Parkinson disease

<p>Abstract</p> <p>Background</p> <p>Studies in animals suggest that the noradrenergic system arising from the locus coeruleus (LC) and dopaminergic pathways mutually influence each other. Little is known however, about the functional state of the LC in patients with Parkinson disease (PD).</p> <p>Methods</p> <p>We retrospectively reviewed clinical and imaging data of 94 subjects with PD at an early clinical stage (Hoehn and Yahr stage 1-2) who underwent single photon computed tomography imaging with FP-CIT ([¹²³I] N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl) tropane). FP-CIT binding values from the patients were compared with 15 healthy subjects: using both a voxel-based whole brain analysis and a volume of interest analysis of <it>a priori </it>defined brain regions.</p> <p>Results</p> <p>Average FP-CIT binding in the putamen and caudate nucleus was significantly reduced in PD subjects (43% and 57% on average, respectively; p < 0.001). In contrast, subjects with PD showed an increased binding in the LC (166% on average; p < 0.001) in both analyses. LC-binding correlated negatively with striatal FP-CIT binding values (caudate: contralateral, ρ = -0.28, p < 0.01 and ipsilateral ρ = -0.26, p < 0.01; putamen: contralateral, ρ = -0.29, p < 0.01 and ipsilateral ρ = -0.29, p < 0.01).</p> <p>Conclusions</p> <p>These findings are consistent with an up-regulation of noradrenaline reuptake in the LC area of patients with early stage PD, compatible with enhanced noradrenaline release, and a compensating activity for degeneration of dopaminergic nigrostriatal projections.</p

Correlation energy in the He atom by Fulde's local approach

In the framework of calculations of electronic correlation energies some considerations are made on Fulde's Linearized Local Approach with emphasis on the comparison with the usual C.I. techniques. The particular rules proposed by Fulde in terms of the second quantization formalism to eliminate single excitation effects are analyzed and the equivalent C.I. wavefunction is derived. Subsequently one presents the results of some computations of the correlation energy in the ground state of the He atom within the Local Approach and with a S.T.O. basis and one compares these results to the corresponding calculations performed by Fulde with a G.T.O. basis. Our results are slightly better than Fulde's because we have tried to optimize the « regions » and we have also frequently considered density-density correlations between different regions. The effectiveness of the Local Approach is confirmed provided that an optimized, or at least reasonable, choice of the « regions » is performed.Dans le cadre du calcul des énergies de corrélation des électrons, nous présentons des considérations sur l'approche locale linéarisée (LLA) de Fulde, et nous étudions en détail comment elle se compare aux techniques d'interactions de configuration (IC). Nous analysons les règles particulières que Fulde impose aux opérateurs de fermions pour éliminer les contributions des excitations simples et nous calculons la fonction d'onde équivalente à l'approche IC. Nous présentons ensuite les résultats de quelques calculs de l'énergie de corrélation dans l'état fondamental de l'atome d'hélium, obtenus dans cette approche locale et dans une base d'orbitales de type Slater, et nous les comparons aux résultats correspondants obtenus par Fulde dans une base d'orbitales de type gaussien. Nos résultats sont un peu meilleurs que ceux de Fulde parce que nous avons essayé d'optimiser les « regions » et nous avons aussi souvent pris en compte les corrélations entre les densités de régions différentes. On peut conclure que cette approche locale est une technique très efficace pour les calculs des énergies de corrélation pourvu que les « régions » soient bien optimisées