miR-409-3p Regulates IFNG and p16 Signaling in the Human Blood of Aging-Related Hearing Loss.

Presbycusis, also referred to as age-related hearing loss (ARHL), is a multifaceted condition caused by the natural aging process affecting the auditory system. Genome-wide association studies (GWAS) in human populations can identify potential genes linked to ARHL. Despite this, our knowledge of the biochemical and molecular mechanisms behind the condition remains incomplete.

Uncertainty Estimation of the Dose Rate in Real-Time Applications Using Gaussian Process Regression.

Major standard organizations have addressed the issue of reporting uncertainties in dose rate estimations. There are, however, challenges in estimating uncertainties when the radiation environment is considered, especially in real-time dosimetry. This study reports on the implementation of Gaussian process regression based on a spectrum-to-dose conversion operator (i.

A Bayesian Approach for Remote Depth Estimation of Buried Low-Level Radioactive Waste with a NaI(Tl) Detector.

This study reports on the implementation of Bayesian inference to improve the estimation of remote-depth profiling for low-level radioactive contaminants with a low-resolution NaI(Tl) detector. In particular, we demonstrate that this approach offers results that are more reliable because it provides a mean value with a 95% credible interval by determining the probability distributions of the burial depth and activity of a radioisotope in a single measurement. To evaluate the proposed method, the simulation was compared with experimental measurements.

Multi-radioisotope identification algorithm using an artificial neural network for plastic gamma spectra.

Radioisotope identification using a plastic scintillation detector has been a challenging issue because of the poor spectral resolution and low cross-sections of these types of detectors when used for photoelectric absorption. In this paper, we propose an algorithm that identifies a single radioisotope and multiple radioisotopes from the gamma spectrum of a plastic scintillator using an artificial neural network. The spectra were simulated using Monte Carlo N-Particle Transport Code 6 to formulate the training set, and the spectra were measured by a two-inch EJ-200 to create the test set (1440 spectra in total).