ABSTRACT
The territory of the Republic of Serbia is vulnerable to various natural disasters, among which forest fires stand out. In relation with climate changes, the number of forest fires in Serbia has been increasing from year to year. Protected natural areas are especially endangered by wildfires. For Nature Park Golija, as the second largest in Serbia, with an area of 75,183 ha, and with MaB Reserve Golija-Studenica on part of its territory (53,804 ha), more attention should be paid in terms of forest fire mitigation. GIS and multi-criteria decision analysis are indispensable when it comes to spatial analysis for the purpose of natural disaster risk management. Index-based and fuzzy AHP methods were used, together with TOPSIS method for forest fire susceptibility zonation. Very high and high forest fire susceptibility zone were recorded on 26.85% (Forest Fire Susceptibility Index) and 25.75% (fuzzy AHP). The additional support for forest fire prevention is realized through an additional Internet of Thing (IoT)-based sensor network that enables the continuous collection of local meteorological and environmental data, which enables low-cost and reliable real-time fire risk assessment and detection and the improved long-term and short-term forest fire susceptibility assessment. Obtained results can be applied for adequate forest fire risk management, improvement of the monitoring, and early warning systems in the Republic of Serbia, but are also important for relevant authorities at national, regional, and local level, which will be able to coordinate and intervene in a case of emergency events.
Subject(s)
Fires , Wildfires , Forests , Geographic Information Systems , Humans , SerbiaABSTRACT
BACKGROUND/AIM: Beside arterial hypertension as the most important factor of a myocardial hypertension development, very important risk factors are obesity, hypercholesterolemia, insulin resistance, etc. The aim of the study was to examine the influence of metabolic syndrome (MetS) on left ventricular hypertrophy in patients with arterial hypertension. METHODS: We checked medical records for 138 patients with arterial hypertension, and compared them with the control group of 44 normotensive subjects. The patients with arterial hypertension were divided into two groups considering the presence of MetS: with MetS (59 patients), and without MetS (79 patients). We defined MetS as presence of three (or more) within five criteria: central obesity (> 102 cm male, > 88 cm female), raised triglycerides (> 1.7 mmol/L, or drug treatment for elevated triglycerides), reduced high density lipoprotein (HDL) cholesterol (< 1.03 mmol/L male, < 1.3 mmol/L female), raised blood pressure (> 130 mmHg systolic, > 90mmHg diastolic), raised fasting glucose (> 6.11 mmol/L, or drug treatment for elevated glucose level). In each group routine laboratory, echocardiography and 24-hour ambulatory blood pressure monitoring were performed. RESULTS: We found statisticaly significant higher left ventricular mass in both subgroups hypertensive patients in comparison with the control group (p < 0.05). We did not find statistically significant difference (227.31 +/- 63.44 vs 219 +/- 59.5, p > 0.05) in left ventricular mass between these two groups of patients. In the patients with arterial hypertension and MetS we found hypertrophy more frequently than in the subgroup without MetS (43/57 vs 34/69, p < 0.001). CONCLUSION: Our results suggest that associated cardiometabolic risks increase the prevalence of myocardial hypertrophy, but do not influence left ventricular mass.