Serbian and Canadian water quality index of Danube river in Serbia in 2010

This paper aims to assess water quality of Danube River in Serbia for 2010. Two methodologies were applied for this purpose: Serbian Water Quality Index (SWQI) and Canadian Water Quality Index (CWQI). WQI value is dimensionless, single number ranging from 0 to 100 (best quality) derived from numerous physical, chemical, biological and microbiological parameters. SWQI was mainly good and very good. This methodology includes parameters for assessment of organic loading, but does not involve parameters of heavy metals concentration. For that purpose CWQI was used. Besides overall, CWQI was calculated for following uses: aquatic habitat, drinking, recreation, irrigation and livestock. Overall CWQI was marginal and fair, which was equivalent with poor and good SWQI. CWQI methodology showed increased concentration of copper in all cases which affected overall water quality and aquatic habitat while increased turbidity in many cases had negative influence on drinking water. Differences between SWQI and CWQI resulted from different methodology: different methods of calculation and parameters. In order to get more comparable results it is necessary to develop unique WQI methodology. [Projekat Ministarstva nauke Republike Srbije, br. 47007

Geoecological determinants of the protection and revitalization of water.

Основни циљ рада је утврђивање међузависности геоеколошких детерминанти, као и могућности примене одговарајућих мера заштите и ревитализације текућих вода у функцији одрживог развоја АП Војводине. Примењена је специфична методологија, на основу које је анализиран квалитет воде са више аспеката и за различиту употребу. Предложен је геоеколошки модел као резултат анализе геоеколошких детерминанти, који се може даље разрађивати и користити за процену постојећег стања одрживог развоја АП Војводине. Геоеколошке детерминанте су анализиране са аспекта климе, хидрологије, рељефа, земљишта, живог света и социо-економске компоненте. Потврђен је њихов позитиван и негативан утицај на одрживи развој испитиваног подручја, као и њихова комплексност и међузависност. Повезаност геоеколошких детерминанти огледа се у честој смени суша и поплава (поред водећих климатских, на ове појаве утичу геолошке, геоморфолошке и педолошке детерминанте), деградацији земљишта (утицај геолошких и геоморфолошких карактеристика), као и загађењу вода (осим доминантног антропогеног фактора, присутни су и климатски, геоморфолошки и педолошки утицаји). Предложени геоеколошки модел, који је састављен на основу ових детерминанти и њиховoг утицаја на одрживи развој се састоји из следећих компоненти: степен суше (на основу Индекса аномалија падавина, енг. Rainfall Anomaly Index – RAI), пољопривредно земљиште угрожено поплавама, укупан квалитет воде (на основу Српског индекса квалитета воде – SWQI и Canadian Water Quality Index – CWQI), квалитет воде за потребе пољопривреде (на основу Agri-food Water Quality Index – AFWQI), квалитет земљишта (на основу Soil Quality Index – SoQI), индекс биодиверзитета (на основу...The main aim of the study is to define the geoecological determinants interdependence as well as possibility of relevant measures implementation for protection and revitalization of water courses in the terms of sustainable development of AP Vojvodina. Specific methodology, applied in the study was used for water quality analyses from many aspects and for different purposes. Geoecological model was recommended as the result of geoecological determinants analyses, which could be further elaborated and used for assessment of current sustainable development state of AP Vojvodina. Geoecological determinants were analized from the aspects of climate, hydrology, relief, soil, living organisms and social–economic components. It was confirmed their positive and negative impact on sustainable development of studied area, as well as their complexity and interdependence. Correlation of geoecological determinants reflects in the frequent exchanges of droughts and floods (besides leading climate, these events are impacted by geological, geomorphological and pedological determinants), soil degradation (impact of geological and geomorphological chacarcteristics), as well as water pollution (besides dominant anthropogenic factor, climate, geomorphology and pedology also have influence). Recommended geoecological model, which is constructed on the basis of these determinants and their influence on the sustainable development consists from the following components: drought grade (based on Rainfall Anomaly Index – RAI), agricultural land threatened by floods, overall water quality (based on Serbian Water Quality Index – SWQI and Canadian Water Quality Index – CWQI), water quality for agricultural use (based on..

CUBE ONLINE ANALYTICAL MODEL (COLAM) IN THE RIVER SHIPPING LOGISTIC FORECASTING

In this paper authors developed Cube Online Analytical Model (COLAM) which should anticipate various restrictions and hazards in river transport system. The aim is to construct a theoretical model which will predict certain delays in transport time caused by topographic and hydrographic constraints, natural hazards (such as ice, floods and droughts), economic and political constraints (tariff barriers between the countries, operating costs, terminal costs and sanctions, the threat of war, etc.) and different technical accidents. COLAM integrates hydroinformatic and hydrologic base of knowledge with real time and gives possibility to provide information for economic queries with different hierarchy of time. COLAM is methodological and practical instrument for this challenge. It integrates hydroinformatic and hydrologic base of knowledge with real time. The model in each concrete case is created to receive information about possible changing of navigation periods on the base of multi-dimension all of three groups of risks (natural hazards, social and technical hazards) as also their combinations

Sustainable Tourism Development and Ramsar Sites in Serbia: Exploring Residents’ Attitudes and Water Quality Assessment in the Vlasina Protected Area

This study aims to present the potential for sustainable tourism development on Vlasina Lake, which is, along with its surroundings, declared as a Ramsar site, Natural Asset of Exceptional Importance, IBA, IPA, PBA and Emerald area. A survey conducted among the residents indicated that they expressed positive attitudes towards sustainable tourism development, even though a small percentage of them are employed in tourism. Considering the lake as the most valuable part of this area, this study emphasized water quality assessment as the necessary condition for sustainable tourism development. Water quality indices (SWQI, CWQI and WPI) were used for water quality assessment for the period 2013–2022. Based on SWQI, Vlasina Lake has a good to excellent water quality and, according to WPI, has clean water suitable for tourism and recreation. The CWQI for overall water quality ranged from marginal to good. It is the highest for recreation, but it is based on only one parameter (pH), which is the limitation of this methodology. Based on field research, survey, water quality assessment and previous studies, it is concluded that this area has favorable conditions for developing various types of tourism, which could contribute to the future development of this undeveloped and unpopulated area.This article belongs to the Special Issue Sustainable Tourism and Use of Natural Resources - Contemporary Practices and Management Challenges

High intensity interval training protects the heart during increased metabolic demand in patients with type 2 diabetes: a randomised controlled trial

AimThe present study assessed the effect of high intensity interval training on cardiac function during prolonged submaximal exercise in patients with type 2 diabetes.MethodsTwenty-six patients with type 2 diabetes were randomized to a 12 week of high intensity interval training (3 sessions/week) or standard care control group. All patients underwent prolonged (i.e. 60min) submaximal cardiopulmonary exercise testing (at 50% of previously assess maximal functional capacity) with non-invasive gas-exchange and haemodynamic measurements including cardiac output and stroke volume before and after the intervention.ResultsAt baseline (prior to intervention) there was no significant difference between the intervention and control group in peak exercise oxygen consumption (20.36.1 vs. 21.75.5ml/kg/min, p=0.21), and peak exercise heart rate (156.3 +/- 15.0 vs. 153.8 +/- 12.5 beats/min, p=0.28). During follow-up assessment both groups utilized similar amount of oxygen during prolonged submaximal exercise (15.0 +/- 2.4 vs. 15.2 +/- 2.2ml/min/kg, p=0.71). However, cardiac function i.e. cardiac output during submaximal exercise decreased significantly by 21% in exercise group (16.2 +/- 2.7-12.8 +/- 3.6L/min, p=0.03), but not in the control group (15.7 +/- 4.9-16.3 +/- 4.1L/min, p=0.12). Reduction in exercise cardiac output observed in the exercise group was due to a significant decrease in stroke volume by 13% (p=0.03) and heart rate by 9% (p=0.04).Conclusion Following high intensity interval training patients with type 2 diabetes demonstrate reduced cardiac output during prolonged submaximal cardiopulmonary exercise testing. Ability of patients to maintain prolonged increased metabolic demand but with reduced cardiac output suggests cardiac protective role of high intensity interval training in type 2 diabetes.Trial registration ISRCTN78698481. Registered 23 January 2013, retrospectively registered

A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy

Background: Machine learning (ML) and artificial intelligence are emerging as important components of precision medicine that enhance diagnosis and risk stratification. Risk stratification tools for hypertrophic cardiomyopathy (HCM) exist, but they are based on traditional statistical methods. The aim was to develop a novel machine learning risk stratification tool for the prediction of 5-year risk in HCM. The goal was to determine if its predictive accuracy is higher than the accuracy of the state-of-the-art tools. Method: Data from a total of 2302 patients were used. The data were comprised of demographic characteristics, genetic data, clinical investigations, medications, and disease-related events. Four classification models were applied to model the risk level, and their decisions were explained using the SHAP (SHapley Additive exPlanations) method. Unwanted cardiac events were defined as sustained ventricular tachycardia occurrence (VT), heart failure (HF), ICD activation, sudden cardiac death (SCD), cardiac death, and all-cause death. Results: The proposed machine learning approach outperformed the similar existing risk-stratification models for SCD, cardiac death, and all-cause death risk-stratification: it achieved higher AUC by 17%, 9%, and 1%, respectively. The boosted trees achieved the best performing AUC of 0.82. The resulting model most accurately predicts VT, HF, and ICD with AUCs of 0.90, 0.88, and 0.87, respectively. Conclusions: The proposed risk-stratification model demonstrates high accuracy in predicting events in patients with hypertrophic cardiomyopathy. The use of a machine-learning risk stratification model may improve patient management, clinical practice, and outcomes in general

Geoecological determinants of the protection and revitalization of water.

Основни циљ рада је утврђивање међузависности геоеколошких детерминанти, као и могућности примене одговарајућих мера заштите и ревитализације текућих вода у функцији одрживог развоја АП Војводине. Примењена је специфична методологија, на основу које је анализиран квалитет воде са више аспеката и за различиту употребу. Предложен је геоеколошки модел као резултат анализе геоеколошких детерминанти, који се може даље разрађивати и користити за процену постојећег стања одрживог развоја АП Војводине. Геоеколошке детерминанте су анализиране са аспекта климе, хидрологије, рељефа, земљишта, живог света и социо-економске компоненте. Потврђен је њихов позитиван и негативан утицај на одрживи развој испитиваног подручја, као и њихова комплексност и међузависност. Повезаност геоеколошких детерминанти огледа се у честој смени суша и поплава (поред водећих климатских, на ове појаве утичу геолошке, геоморфолошке и педолошке детерминанте), деградацији земљишта (утицај геолошких и геоморфолошких карактеристика), као и загађењу вода (осим доминантног антропогеног фактора, присутни су и климатски, геоморфолошки и педолошки утицаји). Предложени геоеколошки модел, који је састављен на основу ових детерминанти и њиховoг утицаја на одрживи развој се састоји из следећих компоненти: степен суше (на основу Индекса аномалија падавина, енг. Rainfall Anomaly Index – RAI), пољопривредно земљиште угрожено поплавама, укупан квалитет воде (на основу Српског индекса квалитета воде – SWQI и Canadian Water Quality Index – CWQI), квалитет воде за потребе пољопривреде (на основу Agri-food Water Quality Index – AFWQI), квалитет земљишта (на основу Soil Quality Index – SoQI), индекс биодиверзитета (на основу...The main aim of the study is to define the geoecological determinants interdependence as well as possibility of relevant measures implementation for protection and revitalization of water courses in the terms of sustainable development of AP Vojvodina. Specific methodology, applied in the study was used for water quality analyses from many aspects and for different purposes. Geoecological model was recommended as the result of geoecological determinants analyses, which could be further elaborated and used for assessment of current sustainable development state of AP Vojvodina. Geoecological determinants were analized from the aspects of climate, hydrology, relief, soil, living organisms and social–economic components. It was confirmed their positive and negative impact on sustainable development of studied area, as well as their complexity and interdependence. Correlation of geoecological determinants reflects in the frequent exchanges of droughts and floods (besides leading climate, these events are impacted by geological, geomorphological and pedological determinants), soil degradation (impact of geological and geomorphological chacarcteristics), as well as water pollution (besides dominant anthropogenic factor, climate, geomorphology and pedology also have influence). Recommended geoecological model, which is constructed on the basis of these determinants and their influence on the sustainable development consists from the following components: drought grade (based on Rainfall Anomaly Index – RAI), agricultural land threatened by floods, overall water quality (based on Serbian Water Quality Index – SWQI and Canadian Water Quality Index – CWQI), water quality for agricultural use (based on..

Estimate of clinical outcomes from the patient perspective is important for clinical decision making

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Hurricane genesis modelling based on the relationship between solar activity and hurricanes

The work examines the potential causative link between the flow of charged particles that are coming from the Sun and hurricanes. For establishing eventual link, the method of correlation analysis is applied, but with the phase shift of 0–5 days. There are nine parameters which are observed as an input, and daily values of the hurricane phenomenon are observed as an output in the period May–October 1999–2013. The results that have been obtained are considerably weak, leading to the need of applying the method of nonlinear analysis. The R/S analysis was conducted to determine the degree of randomness for time series of input and output parameters. The calculated Hurst index of variables X4–X9 is persistent (0.71–0.96). That allows us to conclude that the dynamics of these time series is heavily dependent on the same factors or on each other. Unlike the previous index, we have concluded that the behavior of high-energy protons (X1–X3) and the number of hurricane time series are completely stochastic. The problem of finding hidden dependencies in large databases refers to problems of data mining. The Sugeno function of zero order was selected as a method of output fuzzy system. Bearing in mind the available equipment, the models had to be shortened to the phase shift of 0–3 days. The “brute-force attack” method was used to find the most significant factors from all data. Within the experiments, six input factors were calculated which became the basis for building the final ANFIS models. These models can predict 22–26 % of the hurricanes