Modeling of the Magnetization and Magnetocaloric Effect in Ni2MnGa Heusler Alloy with the Effective Field Theory

Journal of Low Temperature Physics - This study modeled and investigated the magnetocaloric effect in Ni2MnGa Heusler alloy characterized by its magnetic entropy change (ΔSm) and its...     

Optical-luminescence properties of ZnO and TiO2 nanopowders obtained by pulsed laser reactive ablation

Journal of Materials Science: Materials in Electronics - The ZnO and TiO2 nanopowders have been prepared by means of the pulsed laser reactive ablation of metallic (Zn, Ti) targets. The Structural,...     

Archetypes of open-source business models

Electronic Markets - The open-source paradigm offers a plethora of opportunities for innovative business models (BMs) as the underlying codebase of the technology is accessible and extendable by...     

Irradiation with Argon Ions of Cr/4H-SiC Photodetectors

Semiconductors - The results of the effect of irradiation with Ar ions on the structural, electrophysical, and optical characteristics of ultraviolet Cr/4H-SiC photodetectors in the spectral range...     

Use of by-Product Gasoline Fractions Produced by Combining Fuel and Petrochemical Production

Chemistry and Technology of Fuels and Oils - This article considers the alternatives for treatment of the raffinate produced at a unit for the extraction of benzene-containing fractions and the...     

MHD mixed convection of a Cu–water nanofluid flow through a channel with an open trapezoidal cavity and an elliptical obstacle

In the current work, numerical simulations are achieved to study the properties and the characteristics of fluid flow and heat transfer of (Cu–water) nanofluid under the magnetohydrodynamic effects in a horizontal rectangular canal with an open trapezoidal enclosure and an elliptical obstacle. The cavity lower wall is grooved and represents the heat source while the obstacle represents a stationary cold wall. On the other hand, the rest of the walls are considered adiabatic. The governing equations for this investigation are formulated, nondimensionalized, and then solved by Galerkin finite element approach. The numerical findings were examined across a wide range of Richardson number (0.1 ≤ Ri ≤ 10), Reynolds number (1 ≤ Re ≤ 125), Hartmann number (0 ≤ Ha ≤ 100), and volume fraction of nanofluid (0 ≤ φ ≤ 0.05). The current study's findings demonstrate that the flow strength increases inversely as the Reynolds number rises, which pushes the isotherms down to the lower part of the trapezoidal cavity. The Nu_avg rises as the Ri rise, the maximum Nu_avg = 10.345 at Ri = 10, Re = 50, ϕ = 0.05, and Ha = 0; however, it reduces with increasing Hartmann number. Also, it increase by increasing ϕ, at Ri = 10, the Nu_avg increased by 8.44% when the volume fraction of nanofluid increased from (ϕ = 0–0.05).     

Animal Biomass as a Raw Material for Basic Organic Synthesis Products

Chemistry and Technology of Fuels and Oils - The review examines biomass of animal origin in terms of a potential renewable raw material for obtaining CO2-neutral fuel unaffecting the carbon...     

Assessment of technological attributes of autochthonous starter cultures in Turkish dry fermented sausage (sucuk)

The study aims to evaluate the technological properties of autochthonous strains (Lactobacillus sakei S15, Lactobacillus plantarum S24, L. plantarum S91, Pediococcus pentosaceus S128b and Staphylococcus carnosus G109) in Turkish dry fermented sausage (sucuk). After 24 h of fermentaPtion, all lactic acid bacteria strains reduced the pH to below 5.0, while the pH in the control group was above 5.3. The number of lactic acid bacteria strains reached 10⁸–10⁹ cfu g⁻¹ during fermentation. Staphylococcus carnosus G109 remained at the inoculation level of 10⁶ cfu g⁻¹ during ripening. Lactobacillus sakei S15 as mono-culture showed higher TBARS values compared to other strains. The control group had the lowest L* value and autochthonous strains caused no significant difference for a* value. According to principal component analysis results, most volatile compounds were positively correlated with the group containing only L. sakei S15.     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.