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Considering water quality is an essential requirement in terms of environmental planning and management. To protect and manage water resources effectively, it is necessary to develop an analytical decision-support system. In this study, a systematic approach was suggested to evaluate the lake water quality. The methodology includes the prediction of the values in different locations of the lakes from experimental data through inverse distance weighting (IDW) method, creation of maps by using Geographic Information System (GIS) integrated with analytic hierarchy process (AHP) from multi-criteria decision analysis (MCDA), reclassification into five class, combining the time-related spatial data into a single map to predict the whole lake water quality from the data of sampling points, and finally overlapping the final maps with topography/geology and land use. The proposed approach was verified and presented as case study for Meke and Acigol Lakes in Konya/Turkey which were affected by human and natural factors although they have ecological, hydromorphological, and socio-economic importance. In the proposed approach, categorizing water quality parameters as "hardness and minerals," "substrates and nutrients," "solids content," "metals," and "oil-grease" groups was helpful for AHP with the determined group weights of 0.484, 0.310, 0.029, and 0.046, respectively. Assigning weights within each group and then assigning weights between groups resulted in creating accurate final map. The proposed approach is flexible and applicable to any lake water quality data; even with a limited number of data, the whole lake water quality maps could be created for assessment.
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http://dx.doi.org/10.1007/s11356-024-32184-6 | DOI Listing |
Driven by eutrophication and global warming, the occurrence and frequency of harmful cyanobacteria blooms (CyanoHABs) are increasing worldwide, posing a serious threat to human health and biodiversity. Early warning enables precautional control measures of CyanoHABs within water bodies and in water works, and it becomes operational with high frequency in situ data (HFISD) of water quality and forecasting models by machine learning (ML). However, the acceptance of early warning systems by end-users relies significantly on the interpretability and generalizability of underlying models, and their operability.
View Article and Find Full Text PDFPLoS Negl Trop Dis
September 2025
Department of Clinical Science, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Background: Salmonella enterica encompasses over 2,600 serovars, including several commonly associated with severe infection in humans. Salmonella is a major cause of sepsis in Africa; however, diagnosis requires clinical microbiology facilities. Environmental surveillance has the potential to play a role in Salmonella surveillance.
View Article and Find Full Text PDFProbiotics Antimicrob Proteins
September 2025
Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247 667, India.
Ethnic fermented foods represent a significant repository for discovering novel probiotic entities. These fermented foods, entrenched in indigenous practices, have conserved a distinct microbiota through generations. Exploration of these fermented foods could yield microbial consortia capable of transforming human health.
View Article and Find Full Text PDFBiol Trace Elem Res
September 2025
Department of Environmental Sciences, Faculty of Biological Sciences, Kohat University of Science and Technology Kohat, Khyber Pakhtunkhwa, 26000, Pakistan.
The aim of the study was to evaluate the toxic metals (TMs) pollution, bioaccumulation and its potential health risk via consumption of different vegetables irrigated by different water sources released from industrial estates of Khyber Pakhtunkhwa. Water (fresh and waste), soil and vegetables samples were collected in triplicates and acid digested. Digestion of samples were followed by evaporation and filtration and then assessed for TMs via atomic absorption spectrophotometer.
View Article and Find Full Text PDFJ Investig Med
September 2025
Department of Physiology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Aims: To compare the effect of magnesium and potassium on insulin resistance and blood sugar levels among insomniac patients with diabetes mellitus.
Methods: A randomized controlled study was conducted on 320 subjects enrolled in placebo (T1), Magnesium (T2), Potassium (T3) and Magnesium + Potassium (T4) treatment groups. Pre- and post-trial blood sugar and insulin levels were analyzed through blood.