Antibacterial activity and sensory properties of Heracleum persicum essential oil, nisin, and Lactobacillus acidophilus against Listeria monocytogenes in cheese

Aim: The aim of this study was to evaluate the antibacterial and chemical effect of Heracleum persicum essential oil (EO), nisin, Lactobacillus acidophilus, and their combination against Listeria monocytogenes both in vitro and in Iranian white cheese model. Materials and Methods: Chemical compositions of H. persicum EO were analyzed by gas chromatography-mass spectrometry. After production of Iranian white cheese, minimum inhibitory concentration (MIC) and minimum bactericidal concentration of EO and nisin and agar spot test of L. acidophilus against L. monocytogenes were evaluated. Results: Hexyl butanoate (25.98%), octyl isobutyrate (17.82%), methyl butyrate (14.37%), and pentyl cyclopropane (12.77%) were the main components of the EO. MIC of the EO against L. monocytogenes was 2.5 mg/mL. Combination of nisin (5.3 IU/mL) and H. persicum EO (2500 μg/mL) showed increasing effect against L. monocytogenes (fractional inhibitory concentration = 0.9), while a higher concentration of EO and nisin showed undesirable effect on the cheese flavor. Furthermore, a combination of 1012 CFU/g L. acidophilus with H. persicum EO at the concentration of 2.5 mg/mL (T12) showed acceptable sensorial and also antibacterial results in Iranian white cheese. Conclusion: Combination of H. persicum EO, L. acidophilus, and nisin can be recommended as natural preservatives and flavoring agents in cheese

Granular vortex spin-torque nano oscillator for reservoir computing

Abstract In this paper, we investigate the granularity in the free layer of the magnetic tunnel junctions (MTJ) and its potential to function as a reservoir for reservoir computing where grains act as oscillatory neurons while the device is in the vortex state. The input of the reservoir is applied in the form of a magnetic field which can pin the vortex core into different grains of the device in the magnetic vortex state. The oscillation frequency and MTJ resistance vary across different grains in a non-linear fashion making them great candidates to be served as the reservoir's outputs for classification objectives. Hence, we propose an experimentally validated area-efficient single granular vortex spin-torque nano oscillator (GV-STNO) device in which pinning sites work as random reservoirs that can emulate neuronal functions. We harness the nonlinear oscillation frequency and resistance exhibited by the vortex core granular pinning of the GV-STNO reservoir computing system to demonstrate waveform classification