Search results for: Ali Mercan

Authors: Sumeyra Sevim, Gulsum Gizem Topal, Mercan Merve Tengilimoglu-Metin, Mevlude Kizil

Abstract:

Aflatoxin M1 (AFM1) is a major toxic and carcinogenic molecule in milk and milk products. Therefore, it poses a risk for public health. Probiotics can be biological agent to remove AFM1. The aim of this study is to evaluate the effect of probiotic bacteria on AFM1 detoxification in phosphate buffer saline. The PBS samples artificially contaminated with AFM1 at concentration 100 pg/ml were prepared with probiotics bacteria that including monoculture (L. plantarum, B. bifidum ATCC, B. animalis ATCC 27672) and binary culture (L. bulgaricus + S. thermophiles, B. bifidum ATCC + B. animalis ATCC 27672, L. plantarum+B. bifidum ATCC, L. plantarum+ B. animalis ATCC 27672). The samples were incubated at 37°C for 4 hours and stored for 1, 5 and 10 days. The toxin was measured by the ELISA. The highest levels of AFM1 binding ability (63.6%) in PBS were detected yoghurt starter bacteria, while L. plantarum had the lowest levels of AFM1 binding ability (35.5%) in PBS. In addition, it was found that there was significant effect of storage on AFM1 binding ability in all groups except the one including B. animalis (p < 0.05). Consequently, results demonstrate that AFM1 detoxification by probiotic bacteria has a potential application to reduce toxin concentrations in yoghurt. Moreover, probiotic strains can react with itself as synergic or antagonist.

Keywords: aflatoxin M1, ELISA, probiotics, storage

Procedia PDF Downloads 290

Authors: Cagri Mollamahmutoglu, Ali Mercan, Aykut Levent

Abstract:

Studies concerning the microstructures are becoming more important as the utilization of various micro-electro mechanical systems (MEMS) are increasing. Thus in recent years, thermal buckling and vibration analysis of microstructures have been subject to many investigations that are utilizing different numerical methods. In this study, thermal effects on mechanical response of a functionally graded (FG) Timoshenko micro-beam are presented in the framework of a mixed finite element formulation. Size effects are taken into consideration via modified couple stress theory. The mixed formulation is based on a function which in turn is derived via Gateaux Differential scientifically. After the resolution of all field equations of the beam, a potential operator is carefully constructed. Then this operator is used for the manufacturing of the functional. Usual procedures of finite element approximation are utilized for the derivation of the mixed finite element equations once the potential is obtained. Resulting finite element formulation allows usage of C₀ type simple linear shape functions and avoids shear-locking phenomena, which is a common shortcoming of the displacement-based formulations of moderately thick beams. The developed numerical scheme is used to obtain the effects of thermal loads on the static bending, free vibration and buckling of FG Timoshenko micro-beams for different power-law parameters, aspect ratios and boundary conditions. The versatility of the mixed formulation is presented over other numerical methods such as generalized differential quadrature method (GDQM). Another attractive property of the formulation is that it allows direct calculation of the contribution of micro effects on the overall mechanical response.

Keywords: micro-beam, functionally graded materials, thermal effect, mixed finite element method

Procedia PDF Downloads 99

Authors: Sumeyra Sevim, Gulsum Gizem Topal, Mercan Merve Tengilimoglu-Metin, Banu Sancak, Mevlude Kizil

Abstract:

Aflatoxin M1 (AFM1) represents mutagenic, carcinogenic, hepatotoxic and immunosuppressive properties, and shows adverse effect on human health. Recently the use of probiotics are focused on AFM1 detoxification because of the fact that probiotic strains have a binding ability to AFM1. Moreover, inulin is a prebiotic to improve the ability of probiotic bacteria. Therefore, the aim of the study is to investigate the effect of inulin on AFM1 binding ability of some probiotic bacteria. Yoghurt samples were manufactured by using skim milk powder artificially contaminated with AFM1 at concentration 100 pg/ml. Different samples were prepared for the study as: first sample consists of yoghurt starter bacteria (L. bulgaricus and S. thermophilus), the second sample consists of starter and L. plantarum, starter and B. bifidum ATCC were added to the third sample, starter and B. animalis ATCC 27672 were added to the forth sample, and the fifth sample is a binary culture consisted of starter and B. bifidum and B. animalis. Moreover, the same work groups were prepared with inulin (4%). The samples were incubated at 42°C for 4 hours, then stored for three different time interval (1,5 and 10 days). The toxin was measured by the ELISA. When inulin was added to work groups, there was significant change on AFM1 binding ability at least one sample in all groups except the one with L. plantarum (p<0.05). The highest levels of AFM1 binding ability (68.7%) in samples with inulin were found in the group which B. bifidum was added, whereas the lowest levels of AFM1 binding ability (44.4%) in samples with inulin was found in the fifth sample. The most impressive effect of inulin was found on B.bifidum. In this study, it was obtained that there was a significant effect of storage on AFM1 binding ability in the all groups with inulin except the one with L. plantarum (p<0.05). Consequently, results show that AFM1 detoxification by probiotics have a potential application to reduce toxin concentrations in yoghurt. Besides, inulin has different effects on AFM1 binding ability of each probiotic bacteria strain.

Keywords: aflatoxin M1, inulin, probiotics, storage

Procedia PDF Downloads 283

Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

Abstract:

Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

Procedia PDF Downloads 13

Authors: Cagri Mollamahmutoglu, Aykut Levent, Ali Mercan

Abstract:

Micro-beams are one of the most common components of Nano-Electromechanical Systems (NEMS) and Micro Electromechanical Systems (MEMS). For this reason, static bending, buckling, and free vibration analysis of micro-beams have been the subject of many studies. In addition, micro-beams restrained with elastic type foundations have been of particular interest. In the analysis of microstructures, closed-form solutions are proposed when available, but most of the time solutions are based on numerical methods due to the complex nature of the resulting differential equations. Thus, a robust and efficient solution method has great importance. In this study, a mixed finite element formulation is obtained for a functionally graded Timoshenko micro-beam resting on two-parameter elastic foundation. In the formulation modified couple stress theory is utilized for the micro-scale effects. The equation of motion and boundary conditions are derived according to Hamilton’s principle. A functional, derived through a scientific procedure based on Gateaux Differential, is proposed for the bending and buckling analysis which is equivalent to the governing equations and boundary conditions. Most important advantage of the formulation is that the mixed finite element formulation allows usage of C₀ type continuous shape functions. Thus shear-locking is avoided in a built-in manner. Also, element matrices are sparsely populated and can be easily calculated with closed-form integration. In this framework results concerning the effects of micro-scale length parameter, power-law parameter, aspect ratio and coefficients of partially or fully continuous elastic foundation over the static bending, buckling, and free vibration response of FG-micro-beam under various boundary conditions are presented and compared with existing literature. Performance characteristics of the presented formulation were evaluated concerning other numerical methods such as generalized differential quadrature method (GDQM). It is found that with less computational burden similar convergence characteristics were obtained. Moreover, formulation also includes a direct calculation of the micro-scale related contributions to the structural response as well.

Keywords: micro-beam, functionally graded materials, two-paramater elastic foundation, mixed finite element method

Procedia PDF Downloads 116