To evaluate the feasibility of real-time temperature monitoring during an electroporation-based therapy procedure, a data-driven state-space model was developed. Agar phantoms mimicking low conductivity (LC) and high conductivity (HC) tissues were tested under the influences of high (HV) and low (LV) applied voltages. Real-time changes in impedance, measured by Fourier Analysis SpecTroscopy (FAST) along with the known tissue conductivity and applied voltages, were used to train the model. A theoretical finite element model was used for external validation of the model, producing model fits of 95.8, 88.4, 90.7, and 93.7% at 4 mm and 93.2, 58.9, 90.0, and 90.1% at 10 mm for the HV-HC, LV-LC, HV-LC, and LV-HC groups, respectively. The proposed model suggests that real-time temperature monitoring may be achieved with good accuracy through the use of real-time impedance monitoring.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9598795 | PMC |
http://dx.doi.org/10.3390/bioengineering9100499 | DOI Listing |
Sensors (Basel)
January 2025
Mechatronics Engineering Department, Yıldız Technical University, Besiktas, Istanbul 34349, Türkiye.
The accurate measurement of cooking vessel temperatures in induction hobs is crucial for ensuring optimal cooking performance and safety. To achieve this, improvements in existing measurement methods such as thermocouples, thermistors, and infrared (IR) temperature sensors are being explored. However, traditional IR sensors are sensitive to interference from the heated glass ceramic, severely affecting accuracy.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Computer Science and Engineering, Intelligent Robot Research Institute, Sun Moon University, Asan 31460, Republic of Korea.
This research work presents an integrated method leveraging Convolutional Neural Networks and Recurrent Neural Networks (CNN-RNN) to enhance the accuracy of predictive maintenance and fault detection in DC motor drives of industrial robots. We propose a new hybrid deep learning framework that combines CNNs with RNNs to improve the accuracy of fault prediction that may occur on a DC motor drive during task processing. The CNN-RNN model determines the optimal maintenance strategy based on data collected from sensors, such as air temperature, process temperature, rotational speed, and so forth.
View Article and Find Full Text PDFFoods
January 2025
School of Food and Biological Engineering, Engineering Research Center of Bio-Process of Ministry of Education, Anhui Province Laboratory of Agricultural Products Modern Processing, Hefei University of Technology, Hefei 230009, China.
Due to their lipophilicity and low content, the major sesame oleosin allergens, Ses i 4 and Ses i 5, are challenging to identify using conventional techniques. Then, a novel unlabeled electrochemical immunosensor was developed to detect the potential allergic activity of sesame oleosins. The voltammetric immunosensor was constructed using a composite of gold nanoparticles (AuNPs), polyethyleneimine (PEI), and multi-walled carbon nanotubes (MWCNTs), which was synthesized in a one-pot process and modified onto a glass carbon electrode to enhance the catalytic current of the oxygen reduction reaction.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Institute of Forestry and Pomology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100093, China.
Heat shock transcription factors (Hsfs) play an important role in response to high temperatures by binding to the promoter of the heat shock protein gene to promote its expression. As an important ornamental plant, the rose often encounters heat stress during the flowering process. However, there are few studies on the family in roses ().
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Institute of Physical Culture Sciences, University of Szczecin, 17C Narutowicza St., 70-240 Szczecin, Poland.
The transport of biological materials must protect samples from degradation and ensure courier safety. The main goal of this study was to evaluate the usefulness of a new type of container designed for the secured transport of biological material for storing samples for quantitative RNA analyses. This was achieved by analyzing changes in the expression of selected human leucocyte housekeeping genes (, , and ) using reverse transcription quantitative PCR (RT-qPCR) and digital PCR (RT-dPCR) techniques.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!