The electrical and dielectric properties of liquids can be used for sensing. Specific applications, e.g., the continuous in-line monitoring of blood conductivity as a measure of the sodium concentration during dialysis treatment, require contactless measuring methods to avoid any contamination of the medium. The differential transformer is one promising approach for such applications, since its principle is based on a contactless, magnetically induced conductivity measurement. The objective of this work is to investigate the impact of the geometric parameters of the sample or medium under test on the sensitivity and the noise of the differential transformer to derive design rules for an optimized setup. By fundamental investigations, an equation for the field penetration depth of a differential transformer is derived. Furthermore, it is found that increasing height and radius of the medium is accompanied by an enhancement in sensitivity and precision.
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http://dx.doi.org/10.3390/s21072365 | DOI Listing |
Heliyon
January 2025
Department of Mechanical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Background: The development of heat transfer devices used for heat conversion and recovery in several industrial and residential applications has long focused on improving heat transfer between two parallel plates. Numerous articles have examined the relevance of enhancing thermal performance for the system's performance and economics. Heat transport is improved by increasing the Reynolds number as the turbulent effects grow.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore.
Long-gauge fiber optic sensors have proven to be valuable tools for structural health monitoring, especially in reinforced concrete (RC) beam structures. While their application in this area has been well-documented, their use in RC columns remains relatively unexplored. This suggests a promising avenue for further research and development.
View Article and Find Full Text PDFNPJ Syst Biol Appl
January 2025
gRED Computational Sciences, Genentech Inc, South San Francisco, CA, USA.
Understanding transcriptional heterogeneity in cancer cells and its implication for treatment response is critical to identify how resistance occurs and may be targeted. Such heterogeneity can be captured by in vitro studies through clonal barcoding methods. We present TraCSED (Transformer-based modeling of Clonal Selection and Expression Dynamics), a dynamic deep learning approach for modeling clonal selection.
View Article and Find Full Text PDFEye (Lond)
January 2025
Department of Surgical Sciences, University of Turin, Turin, Italy.
Purpose: This study aims to develop a deep-learning-based software capable of detecting and differentiating microaneurysms (MAs) as hyporeflective or hyperreflective on structural optical coherence tomography (OCT) images in patients with non-proliferative diabetic retinopathy (NPDR).
Methods: A retrospective cohort of 249 patients (498 eyes) diagnosed with NPDR was analysed. Structural OCT scans were obtained using the Heidelberg Spectralis HRA + OCT device.
bioRxiv
December 2024
Department of Cell Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Metabolic differences between males and females have been well documented across many species. However, the molecular basis of these differences and how they impact tolerance to nutrient deprivation is still under investigation. In this work, we use to demonstrate that sex-specific differences in fat tissue metabolism are driven, in part, by dimorphic expression of the Integrated Stress Response (ISR) transcription factor, ATF4.
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