Comparison of conventional and machine learning regression models for accurate prediction of selected optical active components - A case study: The Gulf of Izmit.

This study hypothesizes that advanced machine learning (ML) models can more accurately predict certain critical water quality parameters in marine environments compared to conventional regression techniques. We specifically evaluated the spatio-temporal distribution of Chlorophyll-a (Chl-a) and Secchi Disk Depth (SDD) in the Gulf of Izmit using in-situ measurements and Sentinel-2 satellite imagery from October 2021 and 2022. Among the models tested, the Support Vector Regression (SVR) model showed better predictive performance, achieving the lowest RMSE for SDD (1.

Investigation of organic micropollutant pollution in İzmit Bay: a comparative study of passive sampling and instantaneous sampling techniques.

In this study, we used a comprehensive array of sampling techniques to examine the pollution caused by organic micropollutants in İzmit Bay for the first time. Our methodology contains spot seawater sampling, semi-permeable membrane devices (SPMDs) passive samplers for time-weighted average (TWA), and sediment sampling for long-term pollution detection in İzmit Bay, together. Additionally, the analysis results obtained with these three sampling methods were compared in this study.

Integrated assessment of eutrophication in the southern Black Sea waters, using the Nested Environmental Status Assessment Tool.

This research deals with the land-based pressures on the southern Black Sea coast (Turkey), with the objective of assessing their eutrophication impacts. In this context, reference values of some of the eutrophication indicators were calculated, and eutrophication assessment was carried out for this area using the holistic approach NEAT (Nested Environmental Status Assessment Tool). In addition, correlations between NEAT results of coastal regions and pressure-impact analysis methods were investigated.

Lytic Activity of Various Phage Cocktails on Multidrug-Resistant Bacteria.

Purpose: A bacteriophage is a virus that infects and replicates within a bacterium following the injection of phage genome into the bacterial cytoplasm. They are seen as a possible therapy for multi-drug-resistant strains of many bacteria. The aim of this study is to evaluate the lytic activity of the Pyo, Intesti and Fersisi bacteriophage cocktails on P.

Isolation and identification of Arcobacter species from environmental and drinking water samples.

Water plays an important role in the transmission of Arcobacter spp. to animals and humans. The aim of this study was to isolate and characterize Arcobacter spp.