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...     

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...     

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.     

Feasibility of glioblastoma tissue response mapping with physiologic BOLD imaging using precise oxygen and carbon dioxide challenge

Magnetic Resonance Materials in Physics, Biology and Medicine - Innovative physiologic MRI development focuses on depiction of heterogenous vascular and metabolic features in glioblastoma. For this...     

Substrate Analysis on the Design of Wide-Band Antenna for Sub-6 GHz 5G Communication

Wireless Personal Communications - A compact triple band antenna with stacked T-shaped strips inside a rectangular ring monopole has been proposed. This novel structure with a slot in the defected...     

Development of mullite fibers and novel zirconia-toughened mullite fibers for high temperature applications

Polycrystalline mullite fibers and novel zirconia-toughened mullite (ZTM) fibers with average diameters between 9.7 and 10.3 μm containing 3, 7 and 15 wt.-% tetragonal ZrO₂ (ZTM3, ZTM7, ZTM15) in the final ceramic were prepared via dry spinning followed by continuous calcination and sintering in air. A shift in the formation of transient alumina phases and tetragonal ZrO₂ to higher temperatures with increasing amounts of ZrO₂ was observed. Concomitantly, the mullite formation temperature was lowered to 1229 °C for ZTM15 fibers. X-ray diffraction revealed formation of the desired tetragonal crystal structure of ZrO₂ directly from the amorphous precursor. Room temperature Weibull strengths of 1320, 1390 and 1740 MPa and Weibull moduli of 9.5, 7.1 and 9.0 were determined for mullite, ZTM3 and ZTM15 fibers, respectively. Average Young’s moduli ranged from 190 to 220 GPa. SEM images revealed crack-free fiber surfaces and compact microstructures independent of the amount of ZrO₂.     

Microscopic Methods for Identification of Sulfate-Reducing Bacteria from Various Habitats

This paper is devoted to microscopic methods for the identification of sulfate-reducing bacteria (SRB). In this context, it describes various habitats, morphology and techniques used for the detection and identification of this very heterogeneous group of anaerobic microorganisms. SRB are present in almost every habitat on Earth, including freshwater and marine water, soils, sediments or animals. In the oil, water and gas industries, they can cause considerable economic losses due to their hydrogen sulfide production; in periodontal lesions and the colon of humans, they can cause health complications. Although the role of these bacteria in inflammatory bowel diseases is not entirely known yet, their presence is increased in patients and produced hydrogen sulfide has a cytotoxic effect. For these reasons, methods for the detection of these microorganisms were described. Apart from selected molecular techniques, including metagenomics, fluorescence microscopy was one of the applied methods. Especially fluorescence in situ hybridization (FISH) in various modifications was described. This method enables visual identification of SRB, determining their abundance and spatial distribution in environmental biofilms and gut samples.     

A priori performance assessment of line-less mobile assembly systems

Present assembly systems are often based on rigid, line-based approaches and are hindered in their reconfiguration capability. Line-less Mobile Assembly Systems (LMAS) are a novel approach for assembly organization. They improve flexibility through mobile resources, permitting spatiotemporal freedom in scheduling and resource assignment. This paper presents a method for a priori assessment of LMAS during the early stages of the assembly system design process. The method applies a modified, extended mean value analysis to a closed queuing network representation of LMAS to estimate performance. The method is validated model analysis and comparison on two use cases indicating plausible model behavior.