Glucagon-like peptide-1 agonists in cardiovascular diseases: a bibliometric analysis from inception to 2023.

Background: In recent years, glucagon-like peptide-1 (GLP-1) agonists have garnered increasing attention for their potential cardiovascular benefits beyond glycemic control in patients with diabetes. Understanding the research landscape surrounding GLP-1 agonists and cardiovascular diseases (CVDs) is crucial for informing clinical practice and guiding future research endeavors. This bibliometric analysis aimed to comprehensively assess the scholarly output and trends in this field, shedding light on the evolving landscape of GLP-1 agonists' role in cardiovascular health.

Investigation of a surrogate measure-based safety index for predicting injury crashes at signalized intersections.

Objectives: The paper develops a machine learning-based safety index for classifying traffic conflicts that can be used to estimate the frequency of signalized intersection crashes, with a focus on the more severe ones that result in fatal and severe injury. The number of conflicts in different severity levels categorized by the safety index is used as an explanatory variable for developing statistical models for pro-actively estimating crashes.

Methods: Video-derived conflicts in different severity levels between left-turning vehicles and opposing through vehicles, a well-recognized severe injury crash typology at signalized intersections, were identified by jointly integrating the indicators of frequency and severity, using an autoencoder neural network integration method to develop anomaly scores.

Prevalence of generalized anxiety disorder among nursing students in Iran during the COVID-19 pandemic: A web-based cross-sectional study.

Background: The Coronavirus disease 2019 (COVID-19) is a public health emergency that poses anxiety symptoms to nursing students (P. Li et al., 2020).

Investigation of operation parameters on the removal efficiency of methyl orange pollutant by cellulose/zinc oxide hybrid aerogel.

In this study, Cellulose/Zinc Oxide-x (CA/ZnO-x) hybrid aerogel with various concentrations of Zn ion is synthesized through the hydrothermal method and used for organic pollutant removal. The CA/ZnO-x hybrid aerogel was characterized by XRD, UV-Visible, DRS, FTIR, FESEM, EDS, BET, LC-MS-MS analyses. In the present study, CA/ZnO-x hybrid aerogel as photocatalyst was used to investigate the influence of the photocatalytic degradation of methyl orange (MO) from an aqueous solution under UV irradiation.

Application of three dimensional porous aerogels as adsorbent for removal of heavy metal ions from water/wastewater: A review study.

Nowadays, by rapid development of economies and industries, water contamination through the heavy metal ions (toxic, non-toxic and radioactive) is a great concern and an important environmental problem. Currently, numerous techniques such as chemical precipitation, coagulation, ion-exchange, filtration, reverse osmosis, biological treatment and physical adsorption are presented by researchers for removing and recycling heavy metal ions from wastewater. Among these methods, adsorption approach is one of the most efficient techniques for the elimination of heavy metal ions from aqueous solutions.