ERIRMS Evaluation of the Reliability of IoT-Aided Remote Monitoring Systems of Low-Voltage Overhead Transmission Lines.

Researchers have studied instances of power line technical failures, the significant rise in the energy loss index in the line connecting the distribution transformer and consumer meters, and the inability to control unauthorized line connections. New, innovative, and scientific approaches are required to address these issues while enhancing the reliability and efficiency of electricity supply. This study evaluates the reliability of Internet of Things (IoT)-aided remote monitoring systems specifically designed for a low-voltage overhead transmission line.

Identification of Exhaled Metabolites Correlated with Respiratory Function and Clinical Features in Adult Patients with Cystic Fibrosis by Real-Time Proton Mass Spectrometry.

Cystic fibrosis (CF) is a hereditary disease characterized by the progression of respiratory disorders, especially in adult patients. The purpose of the study was to identify volatile organic compounds (VOCs) as predictors of respiratory dysfunction, chronic respiratory infections of , , , and VOCs associated with severe genotype and highly effective modulator treatment (HEMT). Exhaled breath samples from 102 adults with CF were analyzed using PTR-TOF-MS, obtained during a forced expiratory maneuver and normal quiet breathing.

The Blood Plasma Lipidomic Profile in Atherosclerosis of the Brachiocephalic Arteries.

According to the World Health Organization, ischemic stroke is the second leading cause of death in the world. Frequently, it is caused by brachiocephalic artery (BCA) atherosclerosis. Timely detection of atherosclerosis and its unstable course can allow for a timely response to potentially dangerous changes and reduce the risk of vascular complications.

Exhaled breath analysis in adult patients with cystic fibrosis by real-time proton mass spectrometry.

Background: Proton-transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is a promising tool for a rapid online determination of exhaled volatile organic compounds (eVOCs) profiles in patients with cystic fibrosis (CF).

Objective: To detect VOC breath signatures specific to adult patients with CF compared with controls using PTR-TOF-MS.

Methods: 102 CF patients (54 M/48, mean age 25.

Diabetic Retinopathy Diagnosis based on Convolutional Neural Network in the Russian Population: A Multicenter Prospective Study.

Background: Diabetic retinopathy is the most common complication of diabetes mellitus and is one of the leading causes of vision impairment globally, which is also relevant for the Russian Federation.

Objective: To evaluate the diagnostic efficiency of a convolutional neural network trained for the detection of diabetic retinopathy and estimation of its severity in fundus images of the Russian population.

Methods: In this cross-sectional multicenter study, the training data set was obtained from an open source and relabeled by a group of independent retina specialists; the sample size was 60,000 eyes.