Search

In this work, the physical properties of Fe48Cr15Mo14C15B6Y2 alloy in liquid state at high temperature are studied. It was observed that the basic physical characteristics of the alloy, such as viscosity, electrical resistivity, and density, decrease with an increase of the temperature to 1700◦C. An abnormal increasing rate of viscosity for Fe48Cr15Mo14C15B6Y2 alloy in the temperature range from 1360 to 1550◦C was noted. The measurement of the electrical resistivity and density did not reveal any anomalies in the same temperature range. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

A lab‐scale low‐power free‐running radio frequency (RF) oscillator operating at a frequency of 27.12 ± 0.50 MHz was developed to be suitable for fundamental microbiological research topics. Calibration and validation were conducted for two common foodborne pathogens in relevant microbiological growth media, i.e., Salmonella Typhimurium and Listeria monocytogenes in Tryptic Soy Broth and Brain–Heart Infusion broth, respectively. The evolution of temperature, frequency, and power consumption was monitored during treatments, both with and without bacterial cells. The setup operated within the predefined frequency range, reaching temperatures of 71–76 °C after 15 min. The average power consumption ranged between 12 and 14 W. The presence of bacteria did not significantly influence the operational parameters. The inactivation potential of the RF setup was validated, demonstrating the absence of viable cells after 8 and 10 min of treatment, for S. Typhimurium and L. monocytogenes, respectively. In future studies, the setup can be used to conduct fundamental microbiological studies on RF inactivation. The setup can provide added value to the scientific field, since (i) no consensus has been reached on the inactivation mechanisms of RF inactivation of pathogens in foods and (ii) most commercial RF setups are unsuitable to adopt for fundamental studies. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Nanofiltration (NF) membranes, especially loose NF membranes, trigger a growing interest for the fractionation of concentrated organic matters/salt mixtures in addition to the production of pure water. This study presents an in-depth characterization of two superhydrophilic loose NF membranes (Sepro NF 6 and 2A, Ultura). The physical characterization included the determination of the molecular weight cut-off (MWCO), pore size distribution, membrane morphology, surface charge, roughness and hydrophilicity. This was combined with a chemical characterization, i.e., by Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS), to determine the intrinsic membrane properties. The chemical characterization demonstrates that both Sepro NF membranes are poly(piperazineamide) based, showing the modification chemistry for the top layer through XPS measurement. Specifically, Sepro NF 6 and NF 2A membranes were found to have a superhydrophilic surface (contact angle for Sepro NF 6: 14.3±0.9° that for Sepro NF 2A: 21.7±1.4°) with a low roughness, offering a potential advantage over conventional NF membranes in minimizing membrane fouling. Sepro NF 6 and NF 2A membranes had a mean effective pore size of 0.64±0.03nm and 0.52±0.01nm (corresponding to MWCOs of 862±80Da and 493±53Da), respectively. In terms of filtration performance, Sepro NF 6 showed a high permeability of 16.7Lm-2h-1bar-1 with 88.9% salt transmission for 0.01molL-1 NaCl solution, and a slightly lower permeability and salt transmission was obtained for Sepro NF 2A, which is desired for an effective fractionation of target organic matter/salt mixtures.

In this paper, two tuning strategies for a multi-objective predictive controller applied to a drinking water network (DWN) are proposed. A control-oriented DWN model is brie y reviewed, together with its management objectives. A comparison of methods to explore the Pareto front of the multi-objective optimisation (MOO) problem behind the predictive controller is presented with an e ective normalisation method for the model predictive control (MPC) objectives. The proposed tuning strategies, applied to a real-life case study, are compared. Finally, simulation results show that the proposed MPC tuning strategies outperform the baseline results., Peer Reviewed, Postprint (published version)

In the framework of microbiology, Individual-based Models are discrete models in which the main entities are microbes. Their use in simulations as ‘virtual experiments’ to predict the evolution of populations under specific conditions requires accurate setting of the parameters involved. We adapted and tested two optimization methods for Individual-based Model parameter estimation: the Nelder-Mead Threshold Accepting (NMTA) and the NEWUOA. These methods presented no convergence problems, and the best results in terms of time expenditure were derived with the latter., Peer Reviewed, Postprint (published version)

A previously developed growth-no growth model for Listeria monocytogenes, based on nutrient broth data and describing the influence of water activity (a(w)), pH, and acetic acid concentrations, was validated (i) for a variety of L. monocytogenes strains and (ii) in a laboratory-made, mayonnaise-based surimi salad (as an example of a mayonnaise-based salad). In these challenge tests, the influence of the inoculation level was tested as well. Also, the influence of chemical preservatives on the growth probability of L. monocytogenes in mayonnaise-based salads was determined. To evaluate the growth-no growth model performance on the validation data, four quantitative criteria are determined: concordance index, % correct predictions, % fail-dangerous, and % fail-safe. First, the growth probability of 11 L. monocytogenes strains, not used for model development, was assessed in nutrient broth under conditions within the interpolation region. Experimental results were compared with model predictions. Second, the growth-no growth model was assessed in a laboratory-made, sterile, mayonnaise-based surimi salad to identify a possible model completeness error related to the food matrix, making use of the above-mentioned validation criteria. Finally, the effect on L. monocytogenes of common chemical preservatives (sorbic and benzoic acid) at different concentrations under conditions typical of mayonnaise-based salads was determined. The study showed that the growth-no growth zone was properly predicted and consistent for all L. monocytogenes strains. A larger prediction error was observed under conditions within the transition zone between growth-no growth. However, in all cases, the classification between no growth (P = 0) and any growth (P > 0) occurred properly, which is most important for the food industry, where outgrowth needs to be prevented in all instances. The results in the sterile mayonnaise-based salad showed again that the growth-no growth zone was well predicted b

A previously developed growth-no growth model for Listeria monocytogenes, based on nutrient broth data and describing the influence of water activity (a(w)), pH, and acetic acid concentrations, was validated (i) for a variety of L. monocytogenes strains and (ii) in a laboratory-made, mayonnaise-based surimi salad (as an example of a mayonnaise-based salad). In these challenge tests, the influence of the inoculation level was tested as well. Also, the influence of chemical preservatives on the growth probability of L. monocytogenes in mayonnaise-based salads was determined. To evaluate the growth-no growth model performance on the validation data, four quantitative criteria are determined: concordance index, % correct predictions, % fail-dangerous, and % fail-safe. First, the growth probability of 11 L. monocytogenes strains, not used for model development, was assessed in nutrient broth under conditions within the interpolation region. Experimental results were compared with model predictions. Second, the growth-no growth model was assessed in a laboratory-made, sterile, mayonnaise-based surimi salad to identify a possible model completeness error related to the food matrix, making use of the above-mentioned validation criteria. Finally, the effect on L. monocytogenes of common chemical preservatives (sorbic and benzoic acid) at different concentrations under conditions typical of mayonnaise-based salads was determined. The study showed that the growth-no growth zone was properly predicted and consistent for all L. monocytogenes strains. A larger prediction error was observed under conditions within the transition zone between growth-no growth. However, in all cases, the classification between no growth (P = 0) and any growth (P > 0) occurred properly, which is most important for the food industry, where outgrowth needs to be prevented in all instances. The results in the sterile mayonnaise-based salad showed again that the growth-no growth zone was well predicted b