Forecasting medical waste in Istanbul using a novel nonlinear grey Bernoulli model optimized by firefly algorithm.

Waste management has gained global importance, aligning with the escalating impact of the COVID-19 pandemic and the associated concerns regarding medical waste, which poses threats to public health and environmental sustainability. In Istanbul, medical waste is considered a significant concern due to the rising volume of this waste, along with challenges in collection, incineration and storage. At this juncture, precise estimation of the waste volume is crucial for resource planning and allocation.

A micromorphological study of some Prunella L. (Lamiaceae) taxa and its taxonomic implications.

Pollen morphology and nutlet structures of some Prunella L. taxa were examined in detail by light microscopy (LM) and scanning electron (SEM) microscopy. Pollen grains of Prunella vary in size from small to large (Polar axis (P) = 22.

Quantitative Metrics in Mass-Gathering Studies: A Comprehensive Systematic Review.

Introduction: Mass gatherings are events where many people come together at a specific location for a specific purpose, such as concerts, sports events, or religious gatherings, within a certain period of time. In mass-gathering studies, many rates and ratios are used to assess the demand for medical resources. Understanding such metrics is crucial for effective planning and intervention efforts.

Bioaccessibility and antioxidant capacity of kefir-based smoothies fortified with kale and spinach after in vitro gastrointestinal digestion.

The kefir-based smoothies with kale and spinach were designed as a ready-to-drink and innovative functional snack. Microbiological, physicochemical, as well as pre- and postgastrointestinal total antioxidant capacity (TAC; CUPRAC, DPPH, and FRAP) analyses were conducted. It was determined that the kefir-based smoothies with vegetables had higher ash, carbohydrate, and dietary fiber values.

Prediction of amputation risk of patients with diabetic foot using classification algorithms: A clinical study from a tertiary center.

Diabetic foot ulcers can have vital consequences, such as amputation for patients. The primary purpose of this study is to predict the amputation risk of diabetic foot patients using machine-learning classification algorithms. In this research, 407 patients treated with the diagnosis of diabetic foot between January 2009-September 2019 in Istanbul University Faculty of Medicine in the Department of Undersea and Hyperbaric Medicine were retrospectively evaluated.