Design and analysis of a fiber Bragg grating-based foot pressure assessment system.

This research presents a comprehensive study focused on the design, implementation, and analysis of an innovative fiber Bragg grating (FBG) based foot pressure assessment system. FBG sensors strategically placed on the great toe, metatarsal 1, metatarsal 2, and heel provided distinct peak resonant wavelengths, strains, and pressures during experimental cycles. Participant 1 exhibited peak resonant wavelength of 1537.745 nm for great toe, 1537.792 nm for metatarsal 1, 1537.812 nm for metatarsal 2, and 1537.824 nm for heel. Participant 2 showcased distinct graphical representations with peak resonant wavelengths ranging from 1537.903 to 1537.917 nm. In a fracture patient condition, the FBG-based system monitored weight-bearing capacity, integrated with real-time X-ray imaging for dynamic insights of rehabilitation as distinct approach. The strains and pressures at each position exhibited notable variations along with the sensitivity of 1.31µÎµ obtained across all positions, underscoring the FBG-based system's reliability in capturing subtle foot pressure.

Bibliometric research analysis of molecularly imprinted polymers (MIPs): evidence and research activity dynamics.

The escalating issue of water pollution has become a worldwide issue that has captured the attention of numerous scientists. Molecularly imprinted polymers (MIPs) have emerged as adaptable materials with exceptional attributes, including easy synthesis, low cost, remarkable durability, long life, and accessibility. These attributes have motivated researchers to develop novel materials based on MIPs to tackle hazardous contaminants in environmental matrices. The purpose of this paper was to conduct a bibliometric analysis on MIPs' publications, in order to shed light on the developments and focus points of the field. The selected publications were obtained from Scopus database and subjected to a filtering process, resulting in 11,131 relevant publications. The analysis revealed that the leading publication source (journal) is Biosensors and Bioelectronics; the mostly employed keywords are solid-phase extraction, electrochemical sensor, and molecular recognition; and the top contributing countries are China, Iran, and the USA. The Latent Dirichlet Allocation (LDA) algorithm was used for extracting thematic axes from the textual content of the publications. The results of the LDA model showcase that the topic of synthesis and performance of MIPs for environmental applications can be considered as the most dominant topic with a share value of 72.71%. From the analysis, it can be concluded that MIPs are a cross-disciplinary research field.

Low-Dose Chest CT Protocols for Imaging COVID-19 Pneumonia: Technique Parameters and Radiation Dose.

Chest computed tomography (CT) plays a vital role in the early diagnosis, treatment, and follow-up of COVID-19 pneumonia during the pandemic. However, this raises concerns about excessive exposure to ionizing radiation. This study aimed to survey radiation doses in low-dose chest CT (LDCT) and ultra-low-dose chest CT (ULD) protocols used for imaging COVID-19 pneumonia relative to standard CT (STD) protocols so that the best possible practice and dose reduction techniques could be recommended. A total of 564 articles were identified by searching major scientific databases, including ISI Web of Science, Scopus, and PubMed. After evaluating the content and applying the inclusion criteria to technical factors and radiation dose metrics relevant to the LDCT protocols used for imaging COVID-19 patients, data from ten articles were extracted and analyzed. Technique factors that affect the application of LDCT and ULD are discussed, including tube current (mA), peak tube voltage (kVp), pitch factor, and iterative reconstruction (IR) algorithms. The CTDIvol values for the STD, LDCT, and ULD chest CT protocols ranged from 2.79-13.2 mGy, 0.90-4.40 mGy, and 0.20-0.28 mGy, respectively. The effective dose (ED) values for STD, LDCT, and ULD chest CT protocols ranged from 1.66-6.60 mSv, 0.50-0.80 mGy, and 0.39-0.64 mSv, respectively. Compared with the standard (STD), LDCT reduced the dose reduction by a factor of 2-4, whereas ULD reduced the dose reduction by a factor of 8-13. These dose reductions were achieved by applying scan parameters and techniques such as iterative reconstructions, ultra-long pitches, and fast spectral shaping with a tin filter. Using LDCT, the cumulative radiation dose of serial CT examinations during the acute period of COVID-19 may have been inferior or equivalent to that of conventional CT.

Refined Automatic Brain Tumor Classification Using Hybrid Convolutional Neural Networks for MRI Scans.

Refined hybrid convolutional neural networks are proposed in this work for classifying brain tumor classes based on MRI scans. A dataset of 2880 T1-weighted contrast-enhanced MRI brain scans are used. The dataset contains three main classes of brain tumors: gliomas, meningiomas, and pituitary tumors, as well as a class of no tumors. Firstly, two pre-trained, fine-tuned convolutional neural networks, GoogleNet and AlexNet, were used for classification process, with validation and classification accuracy being 91.5% and 90.21%, respectively. Then, to improving the performance of the fine-tuning AlexNet, two hybrid networks (AlexNet-SVM and AlexNet-KNN) were applied. These hybrid networks achieved 96.9% and 98.6% validation and accuracy, respectively. Thus, the hybrid network AlexNet-KNN was shown to be able to apply the classification process of the present data with high accuracy. After exporting these networks, a selected dataset was employed for testing process, yielding accuracies of 88%, 85%, 95%, and 97% for the fine-tuned GoogleNet, the fine-tuned AlexNet, AlexNet-SVM, and AlexNet-KNN, respectively. The proposed system would help for automatic detection and classification of the brain tumor from the MRI scans and safe the time for the clinical diagnosis.

Photoneutrons and Gamma Capture Dose Rates at the Maze Entrance of Varian TrueBeam and Elekta Versa HD Medical Linear Accelerators.

Herein, we evaluated the neutron and gamma capture dose equivalent rates at the maze entrance of Varian TrueBeam and Elekta Versa HD™ medical linear accelerators (linacs) using experimental measurements as well as empirical calculations. Dose rates were measured using calibrated neutron and gamma area survey meters placed side-by-side at the measurement point of interest. Measurements were performed at a source-to-detector distance of 100 cm, with a 10 × 10 cm2 field size therapeutic X-ray beam, and a 30 × 30 × 15 cm3 solid water patient equivalent phantom, with a linac operating at 15, 10 MV, and 10 MV flattened filter-free (FFF). Dose rates were also measured at different points at the centerline along the maze towards the maze entrance. The measured dose equivalent rates at the maze entrance were comparable to those reported in the literature. The dose rates along the maze decreased exponentially towards the maze entrance and were significant for short maze lengths. The evaluated empirical methods for estimating neutron dose rates at the maze entrance of a linac proposed by Kersey, the modified Kersey method and Falcão method, agree by a factor of two from the experimental measurements. The results revealed vital radiation protection considerations owing to neutron contamination in external beam therapy.