Simultaneous extraction and analysis of preservatives and artificial sweeteners in juices by salting out liquid-liquid extraction method prior to ultra-high performance liquid chromatography

A novel and fast salting out liquid-liquid extraction method was developed for simultaneous determination of food additives with different polarities in juices. Chromatographic separation was achieved in less than 6 min using Acquity UPLC BEH C 18 (100 mm × 2.1 mm d.i. × 1.7 µm) column with ammonium acetate with 0.01% of trifluoroacetic acid as eluent A and acetonitrile as eluent B at a flow rate of 0.2 mL min-1. The main factors affecting the extraction efficiency were optimized. The method was validated applying accuracy profile based on total error. The extraction recoveries ranged from 84.97 to 122%. Relative standard deviation ranged from 1.24 to 7.99% for intraday assay and from 1.69 to 9.16% for intermediate precision. The limits of detection for five food additives were from 0.3 to 1.42 µg mL-1. The method was successfully applied to 47 samples of juices from nine brands

Optimization and design of an aircraft’s morphing wing-tip demonstrator for drag reduction at low speed, Part I – Aerodynamic optimization using genetic, bee colony and gradient descent algorithms

In this paper, an ‘in-house’ genetic algorithm is described and applied to an optimization problem for improving the aerodynamic performances of an aircraft wing tip through upper surface morphing. The algorithm’s performances were studied from the convergence point of view, in accordance with design conditions. The algorithm was compared to two other optimization methods, namely the artificial bee colony and a gradient method, for two optimization objectives, and the results of the optimizations with each of the three methods were plotted on response surfaces obtained with the Monte Carlo method, to show that they were situated in the global optimum region. The optimization results for 16 wind tunnel test cases and 2 objective functions were presented. The 16 cases used for the optimizations were included in the experimental test plan for the morphing wing-tip demonstrator, and the results obtained using the displacements given by the optimizations were evaluated

Indice de primarité et différenciation génétique des populations caprines de la steppe (Arabia) et du désert (Mekatia) d'Algérie

International audienc

Hydromagnetic soret convection in a shallow porous enclosure with a shear stress applied on the free upper surface

Paper presented at the 5th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, South Africa, 1-4 July, 2007.The fluid flow induced by combined effects of thermal gradient, thermal diffusion, magnetic field and an external shear stress in a horizontal porous layer, subject to uniform heat flux along its long horizontal walls is studied analytically and numerically. The shear stress is applied on the top horizontal free surface while the bottom one is assumed to be rigid. The problem formulation is based on the Brinkman model with the Boussinesq approximation. The governing parameters are the thermal Rayleigh number, RT , the Lewis number, Le, the separation parameter, ϕ, the Darcy number, Da, the Hartmann number Ha, the dimensionless shear stress, τ and the aspect ratio of the enclosure, Ar. The analytical solution is derived on the basis of the parallel flow approximation and validated numerically using a finite difference method. The critical Rayleigh numbers for the onset of stationary, subcritical and oscillatory convection are determined explicitly as functions of the governing parameters for infinite layers in the absence of the external shear stress. The effect of the main governing parameters on the fluid flow and heat and mass transfer characteristics is discussed.cs201

Correspondence - Characterization of the effective performance of a high-frequency annular-array-based imaging system using anechoic-pipe phantoms

A resolution integral (RI) method based on anechoic-pipe, tissue-mimicking phantoms was used to compare the detection capabilities of high-frequency imaging systems based on a single-element transducer, a state-of-the-art, 256-element linear array or a 5-element annular array. All transducers had a central frequency of 40 MHz with similar conventionally measured axial and lateral resolutions (about 50 and 85 μm, respectively). Using the RI metric, the annular array achieved the highest performance (RI = 60), followed by the linear array (47) and the single-element transducer (24). Results showed that the RI metric could be used to efficiently quantify the effective transducer performance and compare the image quality of different systems

Numerical and experimental transition results evaluation for a morphing wing and aileron system

A new wing-tip concept with morphing upper surface and interchangeable conventional and morphing ailerons was designed, manufactured, bench and wind tunnel tested. The development of this wing tip model was performed in the frame of an international CRIAQ project, and the purpose was to demonstrate the wing upper surface and aileron morphing capabilities in improving the wing tip aerodynamic performances. During numerical optimization with ‘in-house’ genetic algorithm software, and during wind tunnel experimental tests, it was demonstrated that the air flow laminarity over the wing skin was promoted, and the laminar flow was extended with up to 9% of the chord. Drag coefficient reduction of up to 9% was obtained when the morphing aileron was introduced

Verticalization of bacterial biofilms

Biofilms are communities of bacteria adhered to surfaces. Recently, biofilms of rod-shaped bacteria were observed at single-cell resolution and shown to develop from a disordered, two-dimensional layer of founder cells into a three-dimensional structure with a vertically-aligned core. Here, we elucidate the physical mechanism underpinning this transition using a combination of agent-based and continuum modeling. We find that verticalization proceeds through a series of localized mechanical instabilities on the cellular scale. For short cells, these instabilities are primarily triggered by cell division, whereas long cells are more likely to be peeled off the surface by nearby vertical cells, creating an "inverse domino effect". The interplay between cell growth and cell verticalization gives rise to an exotic mechanical state in which the effective surface pressure becomes constant throughout the growing core of the biofilm surface layer. This dynamical isobaricity determines the expansion speed of a biofilm cluster and thereby governs how cells access the third dimension. In particular, theory predicts that a longer average cell length yields more rapidly expanding, flatter biofilms. We experimentally show that such changes in biofilm development occur by exploiting chemicals that modulate cell length.Comment: Main text 10 pages, 4 figures; Supplementary Information 35 pages, 15 figure

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps

© 2017 The Author(s). This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic

On Random Subspace Optimization-Based Hybrid Computing Models Predicting the California Bearing Ratio of Soils

The California Bearing Ratio (CBR) is an important index for evaluating the bearing capacity of pavement subgrade materials. In this research, random subspace optimization-based hybrid computing models were trained and developed for the prediction of the CBR of soil. Three models were developed, namely reduced error pruning trees (REPTs), random subsurface-based REPT (RSS-REPT), and RSS-based extra tree (RSS-ET). An experimental database was compiled from a total of 214 soil samples, which were classified according to AASHTO M 145, and included 26 samples of A-2-6 (clayey gravel and sand soil), 3 samples of A-4 (silty soil), 89 samples of A-6 (clayey soil), and 96 samples of A-7-6 (clayey soil). All CBR tests were performed in soaked conditions. The input parameters of the models included the particle size distribution, gravel content (G), coarse sand content (CS), fine sand content (FS), silt clay content (SC), organic content (O), liquid limit (LL), plastic limit (PL), plasticity index (PI), optimum moisture content (OMC), and maximum dry density (MDD). The accuracy of the developed models was assessed using numerous performance indexes, such as the coefficient of determination, relative error, MAE, and RMSE. The results show that the highest prediction accuracy was obtained using the RSS-based extra tree optimization technique

Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks

There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID-19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID-19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID-19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype