Fermentation of table cream by Lactobacillus plantarum strains: effect on fungal growth,aflatoxin M1 and ochratoxin A

Aflatoxin M1 (AFM₁) and ochratoxin A (OTA) are two main mycotoxins in milk and dairy products. In the present work, the ability of four Lactobacillus strains (L. plantarum PTCC 1058, L. plantarum LP3, L. plantarum AF1 and L. plantarum LU5) to remove AFM1 and OTA in fermented cream was studied during 24 h fermentation. The antifungal activity of the mentioned lactobacilli against the defined fungi (Aspergillus flavus PTCC 5004, Aspergillus parasiticus PTCC 5018, Aspergillus nidulans PTCC 5014, Aspergillus ochraceus PTCC 5060) was also evaluated. The results showed that the cell counts of all strains were increased by 64–70% during fermentation. All Lactobacillus strains decreased the amount of AFM₁ significantly (P ≤ 0.05) in the range of 26–52%, which the highest AFM₁-reducing effect was related to L. plantarum LU5 (from 0.5 to 0.24 μg kg⁻¹). The mean OTA removal by Lactobacillus strains in fermented cream also ranged from 32 to 58%. Amongst Lactobacillus strains, the cell-free culture supernatants of L. plantarum LU5 showed the highest (inhibition zone of 26.7 ± 1.2 mm) and L. plantarum LP3 and L. plantarum PTCC 1058 the lowest antifungal activities. The fermented creams contained Lactobacillus strains exhibited the highest and lowest antifungal activities against A. ochraceus and A. parasiticus, respectively. L. plantarum LU5, with the inhibition zone of 27.6 ± 0.9 mm, was the most effective fungal inhibitor, while L. plantarum PTCC 1058 had the lowest antifungal activity.     

Role of morphology in electrochemical hydrogen storage using binary DyFeO3-ZnO nanocomposites as electrode materials

Hydrogen storage technology is one of the most challenging issues due to the increasing demand for fossil fuel replacement and the reduction of greenhouse gas emissions. In the current paper, the main aim is one-step and eco-friendly preparation of DyFeO₃-ZnO nanocomposites using Barberry fruit extract as natural precursor (with the role of both fuel and capping agent) to compare with various conventional carboxylic acids. To further examine, the effect of different parameters like calcination temperature and the type of the chelating agent was scrutinized to acquire optimum shape, structure, morphology and size of the obtained products. This is the first effort on the investigation of the hydrogen storage capacity of DyFeO₃-ZnO nanocomposites in terms of role of morphology. The electrochemical hydrogen storage capacity of obtained DyFeO₃-ZnO nanocomposites was studied mediated by chronopotentiometry charge-discharge methods in KOH medium. The synthesis of nanocomposites in the presence of chemical or natural capping agent (carboxylic acids or Barberry fruit extract) led to different morphologies which affects to the electrochemical performance. As a result, the electrode which is provided by plate-like DyFeO₃-ZnO nanocomposites performed 600.11 mAh/g discharge capacity compared with other samples. Based on the obtained results, DyFeO₃-ZnO nanocomposites can be promising compounds to improve the electrochemical performance of hydrogen storage.     

Optimisation of a combined Stirling cycle–organic Rankine cycle using a genetic algorithm

In a Stirling cycle a huge amount of energy is wasted due to the losses. This wasted energy may be utilised as a heat source for the boiler of an organic Rankine cycle (ORC). Combination of these two cycles leads to an increased cycle efficiency compared to a single Stirling cycle and the analysis and optimisation of the integrated system is carried out. Optimisation is performed using the genetic algorithm and considering three decision variables: the temperature of the cold tank of the Stirling cycle, the pressure ratio and the temperature of the ORC condenser. In optimisation, the efficiency is considered as the objective function and the highest value is achieved by adjusting the decision variables. Using this method, the efficiency of the overall combined cycle was improved in which the highest efficiency was obtained to be 41.5%.     

Effect of different levels of fat and inulin on the microbial growth and metabolites in probiotic yogurt containing nonviable bacteria

Effects of different levels of fat and inulin on bacterial cell counts, degree of proteolysis and concentrations of organic acids in the yogurt containing inactivated cells of probiotic strains Bifidobacterium animalis and Lactobacillus acidophilus were investigated. Results showed that both L. acidophilus and B. animalis grew well in the yogurt samples reaching cell counts higher than 10⁶ CFU mL^?1 at the final pH of 4.5. Inulin at the concentration of 1% had no significant effects on the production of organic acids and cell counts of L. acidophilus, but promoted the growth of B. animalis with a reduction in the degree of proteolysis. Generally, different fat levels showed significant effects on the production of organic acids and nonsignificant effects on the cell counts of probiotic bacteria and degree of proteolysis. In case of lactic acid, the ratio of L‐ (+)to D‐ (?) isomer ranged from 50/50 to 80/20 in yogurt samples.     

Polyvinylpolypyrrolidone-Supported Chlorosulfonic Acid: An Efficient Catalyst for One-Pot Synthesis of Dihydropyrimidinones and Octahydroquinazolin-2,5-diones

Polyvinylpolypyrrolidone-supported chlorosulfonic acid has been successfully applied to perform one-pot reaction of arylaldehydes, urea, ethylacetoacetate, or cyclic 1,3-diketo compounds under solvent-free condition at 70°C to provide a series of dihydropyrimidinones and octahydroquinazolin-2,5-diones in good to excellent yields. The method offers several advantages such as high yield, short reaction time, simple workup, easy preparation, and reusability of the catalyst. The [PVPP-SO₃H]⁺Cl^? catalyst was characterized via Fourier transform infrared spectroscopy (FT-IR) and thermal gravimetric analysis (TGA). Moreover, the catalyst could be recycled several times without significant loss of its catalytic activity. Clean methodologies, easy work-up procedure, high yield, and simple preparation of the catalyst are some advantages of this article.     

Antibacterial effects of chitosan coating containing Mentha aquatica L. essence against Escherichia coli,Staphylococcus aureus and Listeria monocytogenes in Iranian white cheese

The effect of a chitosan coating and Mentha aquatica L. essence on Iranian white cheese was investigated. Results showed 100% inhibition of Escherichia coli growth using 1.5% essence after 10 days. After 15 days of incubation, the Staphylococcus aureus population was reduced by 44.2%, 70.0%, and 88.5% using 0.5, 1.0 and 1.5% essence, respectively. After 15 days, Listeria monocytogenes growth was inhibited by 63.84%, 70.12%, and 85.9% using 0.5, 1.0, and 1.5% essence, respectively. Inhibition zone diameter studies also confirmed the antibacterial effects of applied coating against all the above‐mentioned bacteria in Iranian white cheese.     

An improved cluster formation process in wireless sensor network to decrease energy consumption

Wireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.

     

Performance improvement of microbial fuel cell through artificial intelligence

The current work introduces an enhancement in the performance of the microbial fuel cell through estimating the optimal set of controlling parameters. The maximization of both power density (PD) and the percentage of chemical oxygen demand (COD) removal were considered as the enhancement in the cell's performance. Three main parameters in terms of performance as well as commercialization are the system's inputs; the Pt which takes the range of 0.1‐0.5 mg/cm², the degree of sulphonation in sulfonated‐poly‐ether‐ether‐ketone that changes in the range of 20‐80%, and the rate of aeration of cathode which varies between 10 and 150 mL/min. From the experimental dataset, two robust adaptive neuro‐fuzzy inference system models based on the fuzzy logic technique have been constructed. The comparisons between the models' outputs and the experimental data showed well‐fitting in both training and testing datasets. The mean squared errors of the PD model, for testing and whole datasets, were found 2.575 and 0.909 while for the COD model it showed 19.242 and 6.791, respectively. Then, based on the two fuzzy models, a Particle Swarm Optimization algorithm has been used to determine the best parameters that maximize both of the PD and the COD removal of the cell. The optimization process was utilized for single and multi‐object optimization processes. In the single optimization, the resulting maximums of the PD and the COD removal were found 62.844 (mW/m²) and 99.99 (%), respectively. Whereas, in the multi‐object optimization, the values of 61.787 (mW/m²) and 96.21 (%) were reached as the maximums for the PD and COD, respectively. This implies that, in both cases of optimization processes, the adopted methodology can efficiently enhance the microbial fuel cell performances than the previous work.     

Failure Analysis and Remedy Procedure for Cracking of Fuel Nozzles in a Gas Turbine

A common failure in a certain type of gas turbine, observed during the first periodic inspection, is radial cracks in the tip plate of gas fuel nozzles. Here, each gas turbine has 18 nozzles. In all nozzles and in all similar units, these cracks of lengths ranging from 1 mm to a maximum of 14.5 mm are observed. As prescribed by the manufacturer, the defective part must be removed and replaced by welding and machining of a new one. But this problem is repeated and observed in the next periodic visits, and in all units. Depending on the number of nozzles in each gas turbine unit and the number of units in total, these repairs are very expensive and time-consuming. In this paper, the failure is analyzed and the causes of the cracks in the nozzles are investigated. Studies show that the main causes of nozzle failure are residual stresses caused by welding and thermal stresses caused by the start-up and shutdown processes. According to results, a solution has been proposed to release these residual and thermal stresses. After the implementation of this method in 1998, no more failure has been reported by the repair team, which proves the effectiveness of this solution. Since this paper has been prepared based on technical reports from the years between 1996 and 1998, the cited references of this paper are these technical reports.