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.     

The influence of low- and high-linear energy transfers on some physical properties of poly(methyl-methacrylate) samples

Clear poly(methyl-methacrylate)—PMMA—dosimeter is widely used in food irradiations. Positron annihilation lifetime spectroscopy (PALS) is one of the unique tools used for studying free-volumes and open-volume type defects in solid media. The Vicker's microhardness measurements offer a simple and nondestructive tool for investigating the mechanical behavior of polymer materials. PALS as well as microhardness measurements were carried out for PMMA samples, irradiated with low- and high-linear energy transfers (LET). The low-LET irradiations were provided at lethal doses of gamma radiations for vegetative bacteria. Such irradiations showed a chain scission in the PMMA samples. High-LET irradiations showed behavior different from the low-LET ones. The observed behavior depends on the alpha particle fluence. The microhardness testing was carried out for virgin and irradiated PMMA samples at high-LET. A negative correlation was found between PALS measurements and microhardness results. The optical characteristics and structural studies for the virgin and irradiated PMMA samples were in agreement with the PALS and microhardness measurements. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Full-duplex overlay cognitive wireless powered communication network using RF energy harvesting

In this paper, a novel full-duplex overlay cognitive wireless powered communication network (FD-OCWPCN) is proposed where a full-duplex (FD) hybrid-access point (H-AP) supports the full access of all battery-free secondary users (SUs). The H-AP broadcasts wireless power to empower the nearby SUs in the downlink (DL) phase while decoding the information transmitted uplink (UL) phase by the SUs, simultaneously. To overcome the self-interference (SI) phenomenon in FD-OCWPCN, the problem of maximizing the system sum-throughput with optimal UL-DL transmission/reception time and H-AP’s transmit power allocation is considered. This problem is non-convex under perfect/imperfect SI cancelation (SIC), so we employ the active interference temperature control and the gradient projection techniques to effectively reduce it into a convex problem. Closed-form expressions for the perfect/imperfect SIC cases are also derived. To assess the performance of the FD-OCWPCN, a comparison with a half-duplex OCWPCN (HD-OCWPCN) is provided. The achievable average sum-throughput for different FD/HD-OCWPCN is compared in the context of the average and peak transmit power at the H-AP, the number of SUs, path loss exponent and fairness metric. The simulation results depict the superiority of the FD-OCWPCN over the HD-OCWPCN for the perfect SIC and the effective imperfect SIC.

     

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.

     

Co-doping effects of (Al,Ti, Mg) on the microstructure and electrical behavior of ZnO-based ceramics

Co-doped ZnO-based ceramics using Al, Ti, and Mg ions in different ratios were synthesized with the objective to investigate the doping effects on the crystalline features, microstructure and the electrical behavior. For Al and Ti doping, a coexistence of crystalline phases was shown with a major wurtzite ZnO structure and secondary spinel phases (ZnAl₂O₄, Zn₂TiO₄, or Zn_aTi_bAl_cO_d), while Mg doping did not alter significantly the structural features of the wurtzite ZnO phase. The electrical behavior induced by Al, Ti, and Mg co-doping in different ratios was investigated using Raman, electron paramagnetic resonance (EPR) and ²⁷Al and ⁶⁷Zn solid-state nuclear magnetic resonance (NMR). Al doping induces a high electrical conductivity compared to other doping elements. In particular, shallow donors from Zn_i-Al_Zn defect structures are inferred from the characteristic NMR signal at about 185 ppm; that is, quite far from the usual oxygen coordinated Al. The Knight shift effect emanating from a highly conducting Al-doped ZnO ceramics was considered as the origin of this observation. Oppositely, as Ti doping leads to the formation of secondary spinel phases, EPR analysis shows a high concentration of Ti³⁺ ions which limit the electrical conductivity. The correlation between the structural features at the local order, the involved defects and the electrical behavior as function of the doping process are discussed.     

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.     

No-chatter model-free sliding mode control for synchronization of chaotic fractional-order systems with application in image encryption

Multimedia Tools and Applications - Synchronization of different Chaotic dynamical systems is one of the main issues in engineering which has a lot of applications in applied sciences like secure...