Fluorescence spectroscopy coupled with factorial discriminant analysis technique to identify sheep milk from different feeding systems

Rapid measurements of milk properties and discrimination of milk origin are necessary techniques for quality control of milk products. The present study was undertaken to evaluate the potential of using front face fluorescence spectroscopy (FFFS) and synchronous fluorescence spectroscopy (SFS) for monitoring the quality of forty-five ewe’s milk samples originating from different feeding systems. Physico-chemical analyses and fluorescence spectra were conducted on samples during lactation periods (the first 11 weeks). The principal component analysis (PCA) separately applied to the physico-chemical and fluorescence spectral data showed only small discrimination between milk samples based on lactation periods and diet compositions. Similar results were obtained by separately applying factorial discriminant analysis (FDA) on each technique. In a second step, concatenation technique were applied to FFF spectra acquired after excitation set at 250, 290, 380 nm and emission set at 410 nm. Results obtained showed a good discrimination among milk samples with regard to feeding systems given to the ewes throughout the lactation periods. In addition, a better discrimination was observed with FFFS than with SFS.     

A comparison and joint use of mid infrared and fluorescence spectroscopic methods for differentiating between manufacturing processes and sampling zones of ripened soft cheeses

Ten traditional M1 (n = 5) and M2 (n = 5) soft cheeses produced from raw milk, and five other stabilised M3 (n = 5) cheeses manufactured from pasteurised milk, were studied using mid infrared (MIR) and front face fluorescence (FFFS) spectroscopies. MIR (3000–900 cm⁻¹), tryptophan (excitation: 290 nm, emission: 305-450 nm), 400-640 emission spectra (excitation: 380 nm) and vitamin A (excitation: 280–350 nm, emission: 410 nm) spectra were recorded at two sampling zones (external (E) and central (C)) of the investigated cheeses. When the factorial discriminant analysis (FDA) was applied to the MIR spectra, the classification was not satisfactory. With tryptophan fluorescence spectra, correct classification of 94.4 and 69.4% was observed for the calibration and validation spectra, respectively. Better classification was obtained using vitamin A fluorescence spectra, since 91.8 and 80.6% of the calibration and validation spectra, respectively, were correctly classified. When the first five principal components (PCs) of the PCA extracted from each data set were pooled into a single matrix and analysed by FDA, the classification was considerably improved, obtaining a percentage of correct classification of 100 and 91.7% for the calibration and validation samples, respectively. It was concluded that concatenation of the physico-chemical and spectroscopic data sets is an efficient technique for the identification of soft cheese varieties.     

Monitoring the Egg Freshness During Storage Under Modified Atmosphere by Fluorescence Spectroscopy

A total of 207 intact brown-shelled eggs of the same flock (29 weeks of age) belonging to two treatment groups were stored in daylight at 12.2 °C and 87% relative humidity (RH): (1) 108 eggs and (2) 99 other eggs were kept in an atmosphere containing 2 and 4.6% of CO₂, respectively. The 18 remaining eggs have also been analysed directly when they were available in our laboratory to check the degree of freshness (aged of 1 day or less). Eggs of the two groups were analysed after 6, 8, 12, 15, 20, 22, 26, 29, 33, 40, 47 and 55 days of storage using front face fluorescence spectroscopy. The emission fluorescence spectra of aromatic amino acids and nucleic acids (AAA+NA; excitation, 250 nm; emission, 280–450 nm), fluorescent Maillard reaction products (excitation, 360 nm; emission, 380–580 nm) and the excitation spectra of vitamin A (emission, 410 nm; excitation, 270–350 nm) were scanned on thick albumen and egg yolk. For each treatment, the principal component analysis applied on the vitamin A fluorescence spectra allowed a good discrimination of eggs according to both their storage time and conditions, while more overlapping between egg samples was observed when the other intrinsic probes were investigated. These results showed that vitamin A fluorescence spectra could be considered as a good indicator of egg freshness kept only in 2% of CO₂.     

Local commute-time guided MDS for 3D non-rigid object retrieval

In this paper, we propose a 3D non-rigid shape retrieval method based on canonical shape analysis. Our main idea is to transform the problem of non-rigid shape retrieval into a rigid shape retrieval problem via the well-known multidimensional scaling (MDS) approach and random walk on graphs. We first segment the non-rigid shape into local partitions based on its salient features. Then, we calculate a local MDS problem for each partition, where the local commute time distance is used as weighting function in order to preserve local shape details. Finally, we aggregate the set of local MDS problems as a global constrained problem. The constraint is formulated using the biharmonic function between local salient features. In contrast to MDS method, the proposed local MDS is computationally efficient, parameters free and gives isometry-invariant forms with minimum features distortion. Due to these advantageous properties, the proposed method achieved good retrieval accuracy on non-rigid shape benchmark datasets.     

Impact of Temperature Cycling and Isothermal Storage on the Quality of Acidic and Neutral Shelf-Stable Dairy Desserts Packaged in Flexible Pouches

The aims of the present study were, first, to identify the quality changes occurring in sterilized vanilla and strawberry pudding during storage at 20 °C; second, to understand the effect of storage temperature on aging; and, third, to determine if temperature could be used as an accelerating factor for shelf life or stability studies. Shelf-stable pudding was produced industrially and packaged in flexible pouches. Different ingredients were used to produce strawberry and vanilla pudding, and the resulting pH was 4.1 and 6.5, respectively. Pudding pouches were kept for 7 days at 20 °C and stored for up to 112 days at ??18, 4, 20, and 30 °C, or cycled repeatedly between ??18 and 20 °C, 4 and 20 °C, and 30 and 20 °C with a frequency of two cycles per week. Color, pH, apparent viscosity, flow behavior, and fluorescence spectra measurements were conducted up to 112 days of storage. The most relevant indicators to monitor quality changes in vanilla pudding were η, pH, b*, and tryptophan emission spectra, and in strawberry pudding, a*, b*, and riboflavin, tryptophan, and vitamin A emission spectra. Indeed, the temperature of 30 °C was identified as the most suitable accelerating factor for accelerated aging tests regarding changes in pH, color, riboflavin, and tryptophan fluorescence spectra of pudding, while cycles of 4/20 °C and isothermal storage at 4 °C were the most appropriate tests to accelerate changes in apparent viscosity of pudding.     

Application of synchronous fluorescence spectroscopy for the determination of some chemical parameters in PDO French blue cheeses

The present study was aimed at investigating the potential of using synchronous fluorescence spectroscopy (SFS) coupled with multivariate statistical analyses for the determination of some chemical parameters (pH, fat, dry matter, protein and soluble nitrogen) of French blue-veined cheeses belonging to four brands (FA-Fourme d’Ambert, FM-Fourme de Montbrison, BA-Bleu d’Auvergne and BC-Bleu des Causses). Three partial least square regression models with leave-one-out cross-validation technique were considered in the present study. The first one including the “Fourme cheeses” (FA and FM), the second one including the “Blue cheeses” (BA and BC) and the last one including the 4 Blue-veined cheeses (FA, FM, BA and BC). The models qualities were investigated principally by the R ² (coefficient of determination) and the RPD (ratio of standard deviation to root-mean-square error of cross-validation) factors. The results showed that SFS succeeded to predict ash and protein in Blue (ash: R ² = 0.90, RPD = 3.17; protein R ² = 0.80, RPD = 2.24) or Fourme cheeses (ash: R ² = 0.81, RPD = 2.29; protein R ² = 0.81, RPD = 2.26) when considered individually, while SFS failed to predict all the physicochemical parameters when the two groups were analyzed jointly.     

On Conducting Simultaneous Versus Sequential Engineering Activities in Risky R&D

We consider development projects in which the activities can be classified in two types: uncertainty resolving R&D efforts that accumulate in the form of knowledge to eventually give rise to a discovery; and routine technical investments which aim at improving the profitability of the project once the discovery has been made. The advantage of initiating routine preparatory activities prior to the achievement of a technological breakthrough in such projects, sometimes termed as 'concurrent engineering', is analyzed within a suitable dynamic optimization framework. The optimal double expenditure policy is compared with the conservative delayed investment policy, under which all the routine engineering activities are delayed until the risky R&D efforts culminate in a breakthrough. A criterion for the optimality of the latter policy is developed on the basis of the probability distribution of the discovery date. The application of the criterion is illustrated for a variety of specifications regarding the uncertainty associated with the R&D process. We find that simultaneous investment is the optimal policy for a large class of probability distributions. However, if the conditional probability of immediate discovery is always below some critical value, it is optimal to delay the preparatory activities until the discovery.     

Molecular Docking and Biophysical Studies for Antiproliferative Assessment of Synthetic Pyrazolo-Pyrimidinones Tethered with Hydrazide-Hydrazones

Chemotherapy represents the most applied approach to cancer treatment. Owing to the frequent onset of chemoresistance and tumor relapses, there is an urgent need to discover novel and more effective anticancer drugs. In the search for therapeutic alternatives to treat the cancer disease, a series of hybrid pyrazolo[3,4-d]pyrimidin-4(5H)-ones tethered with hydrazide-hydrazones, 5a–h, was synthesized from condensation reaction of pyrazolopyrimidinone-hydrazide 4 with a series of arylaldehydes in ethanol, in acid catalysis. In vitro assessment of antiproliferative effects against MCF-7 breast cancer cells, unveiled that 5a, 5e, 5g, and 5h were the most effective compounds of the series and exerted their cytotoxic activity through apoptosis induction and G0/G1 phase cell-cycle arrest. To explore their mechanism at a molecular level, 5a, 5e, 5g, and 5h were evaluated for their binding interactions with two well-known anticancer targets, namely the epidermal growth factor receptor (EGFR) and the G-quadruplex DNA structures. Molecular docking simulations highlighted high binding affinity of 5a, 5e, 5g, and 5h towards EGFR. Circular dichroism (CD) experiments suggested 5a as a stabilizer agent of the G-quadruplex from the Kirsten ras (KRAS) oncogene promoter. In the light of these findings, we propose the pyrazolo-pyrimidinone scaffold bearing a hydrazide-hydrazone moiety as a lead skeleton for designing novel anticancer compounds.     

A learning process of the matching identification problem

Recently, Mehrez and Steinberg (1995) described and studied the matching identification problem (MIP). The MIP is a form of knowledge acquisition problem from the field of artificial intelligence. For instance, an expert system infers knowledge from a set of examples. But how do you most quickly acquire the examples that knowledge is inferred from? The MIP is a special case of this problem. Although an optimal algorithm was not found by Mehrez and Steinberg, they described two general types of heuristics. We describe in this paper an optimal algorithm for the case of K=2, and an improved heuristic for general K, which identifies a chosen subset with 6% fewer inquiries on average when N=15, K=3. The heuristic improves relative to the Type I heuristic as N increases, K held constant. The improved heuristic is concerned with the symbols yet unclassified as being in the chosen subset or not in the chosen subset. By inquiring subsets with all unclassified symbols, we most quickly "span" the set of unclassified numbers. Closed form equations are developed for the expected number of inquiries required and the variance of the number of inquiries required for the optimal algorithm. Computational studies are provided for Mehrez and Steinberg's Type I heuristics, the K=2 optimal algorithm, and the spanning heuristic.