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Abstract: Accurate and efficient evaluation of steel properties is crucial for modern manufacturing. This study presents a novel approach that combines spark imaging and deep learning to predict carbon content in steel. By capturing and analyzing sparks generated during grinding, the method offers a fast and cost-effective alternative to conventional testing. Using convolutional neural networks (CNNs), the proposed models demonstrate high reliability and adaptability across different steel types. Among the tested architectures, MobileNet-v2 achieved the best performance, balancing accuracy and computational efficiency. The findings highlight the potential of machine vision and artificial intelligence in non-destructive steel analysis, providing rapid and precise insights for industrial applications.
Keywords: carbon content prediction, convolutional neural networks, deep learning, machine vision, spark imaging, steel analysis
Published in DKUM: 03.11.2025; Views: 0; Downloads: 5
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Abstract: Semi-natural grasslands are some of the most species-rich habitats in Europe and provide important ecosystem services such as biodiversity conservation, carbon sequestration and soil fertility maintenance. This study investigates how different intensities of grassland management affect the composition of functional groups and soil chemical properties. Five grassland management systems were analyzed: Cut3—three cuts per year; LGI—low grazing intensity; CG—combined cutting and grazing; Cut4—four cuts per year; and HGI—high grazing intensity. The functional groups assessed were grasses, legumes and forbs, while soil samples from three depths (0–10, 10–20 and 20–30 cm) were analyzed for their chemical properties (soil organic carbon—SOC; soil total nitrogen—STN; inorganic soil carbon—SIC; soil organic matter—SOM; potassium oxide—K2O; phosphorus pentoxide—P2O5; C/N ratio; and pH) and physical properties (volumetric soil water content—VWC; bulk density—BD; and porosity—POR). The results showed that less intensive systems had a higher proportion of legumes, while species diversity, as measured via the Shannon index, was the highest in the Cut4 system. The CG system tended to have the highest SOC and STN at a 0–10 cm depth, with a similar trend observed for SOCstock at a 0–30 cm depth. The Cut4, HGI and CG systems also had an increased STNstock. Both grazing systems had the highest P2O5 content. A tendency towards a higher BD was observed in the top 10 cm of soil in the more intensive systems. Choosing a management strategy that is tailored to local climate and site conditions is crucial for maintaining grassland stability, enhancing carbon sequestration and promoting long-term sustainability in the context of climate change.
Keywords: grassland biodiversity, management intensity, composition of functional groups, soil chemical and physical properties, carbon and nitrogen storage, soil C:N ratio, sustainability
Published in DKUM: 13.10.2025; Views: 0; Downloads: 8
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Abstract: Track-etched polyethylene terephthalate (TE-PET) membranes, characterized by their well-defined cylindrical pores and narrow pore size distribution, offer advantages in filtration applications but demonstrate a gradual decrease of water flux over time. In this work, we evaluate the performance of track-etched polyethylene terephthalate (TE-PET) membranes as microfilters in low-pressure cross-flow and dead-end filtration systems. Membranes with pore sizes between 0.2 and 2.5 μm and porosities of 0.2–20% were tested at different low pressures (0.02–10 bar). Monitoring water flux over time exhibited a significant reduction. This behaviour is attributed to polymer swelling within the pore walls due to the formation of a sol-gel film. Notably, this swelling is enhanced under dynamic flow conditions, with larger pores exhibiting more rapid and pronounced flux decline. When filtering organic solvents, the flux drop is less pronounced and depends on their viscosity and polarity. Surface characterization by atomic force microscopy further confirmed morphological changes in TE-PET support after water filtration. Additional contributing factors, such as fouling and compaction, are also discussed.
Keywords: track-etched support, polyethylene terephthalate, water filtration, swelling, sol-gel film, carbon nanomembrane
Published in DKUM: 13.06.2025; Views: 0; Downloads: 5
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Abstract: The preconditioning and modification of the supporting electrode surface is an essential step in every biosensor architecture. In particular, when using screen-printed carbon electrodes (SPEs) as inexpensive and convenient disposable sensor substrates, their somewhat lower electrochemical (surface) reproducibility might represent a complex hurdle. Herein, we investigated the effect of selected preconditioning strategies, such as cyclic voltammetric pretreatment, in H2SO4 and H2O2 and plasma pretreatment with a positive and negative glow discharge, which all improved the electrochemical stability of the unmodified SPEs. Furthermore, we studied the influence of preconditioning strategies on the adsorption kinetics of the two most commonly used building blocks for biosensor preparation, i.e., bovine serum albumin (BSA) and protein A. We observed an advantageous effect of all the examined preconditioning strategies for the modification of SPEs with protein A, being the most effective the negative glow discharge. On the other hand, BSA exhibited a more complex adsorption behavior, with the negative glow discharge as the only generally beneficial preconditioning strategy providing the highest electrochemical stability. Protein A revealed a more substantial impact on the electrochemical signal attenuation than BSA considering their same concentrations in the modification solutions. For both BSA and protein A, we showed that the concentrations of 5 and 10 µg mL−1 already suffice for an electrochemically satisfactorily stable electrode surface after 60 min of incubation time, except for BSA at the positive-plasma-treated electrode.
Keywords: screen-printed carbon electrode, SPE, electrochemical biosensor, adsorption, bovine serum albumin, protein A, glow discharge
Published in DKUM: 15.05.2025; Views: 0; Downloads: 2
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Abstract: In this research, a new approach to enzyme inactivation in flour was presented by supercritical technology, considered a sustainable technology with lower energy consumption compared to other technologies that use ultra-high temperature processing. Total protein concentration and the activity of enzymes α-amylase, lipase, peroxidase, polyphenol oxidase, and protease were determined in flour pre-treated with scCO2. During the study, it was observed that the activity of enzymes such as lipase and polyphenol oxidase, was significantly reduced under certain conditions of scCO2 treatment, while the enzymes α-amylase and protease show better stability. In particular, polyphenol oxidase was effectively inactivated below the 60% of preserved activity at 200 bar and 3 h, whereas α-amylase under the same conditions retained its activity. Additionally, the moisture content of the scCO2-treated spelt flour was reduced by 5%, and the fat content was reduced by 58%, while the quality of scCO2-treated flour was maintained. In this regard, the sustainable scCO2 process could be a valuable tool for controlling the enzymatic activity of spelt flour since the use of scCO2 technology has a positive effect on the quality of flour, which was verified by the baking performance of spelt flour with the baked spelt bread as an indicator of quality.
Keywords: food treatment, spelt flour, proteins, supercritical carbon dioxide, enzyme inactivation, defatted flour, carbon dioxide solubility
Published in DKUM: 17.04.2025; Views: 0; Downloads: 4
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