University of Rijeka

About: University of Rijeka is a education organization based out in Rijeka, Croatia. It is known for research contribution in the topics: Population & Tourism. The organization has 3471 authors who have published 7993 publications receiving 110386 citations. The organization is also known as: Rijeka University & Sveučilište u Rijeci.

Nonalcoholic Fatty Liver Disease Markers Are Associated with Insulin Resistance in Type 1 Diabetes

Abstract: Nonalcoholic fatty liver disease (NAFLD) has been associated with the insulin resistance. Aims was to explore the relationship between markers of NAFLD, namely concentrations of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALK), c-glutamyltransferase (GGT), ferritin and bilirubin and insulin resistance in type 1 diabetes. Our study included 353 patients with type 1 diabetes. Insulin sensitivity was measured with estimated glucose disposal rate calculated using theequation: eGDR = 24.31 - (12.22 9 WHR) - (3.29 9 HT) - (0.57 9 HbA1c) ; WHR = waist to hip ratio, HT = hypertension. Correlations and multiple logistic regressions analysis were performed to identify the relationships between NAFLD associated markers and eGDR, individual components of insulin resistance and risk of insulin resistance. AST, ALT, AST-to-ALT ratio, ALK and ferritin significantly correlated with insulin resistance measured by eGDR (r = -0.13, -0.14, 0.13, -0.18, and -0.24, respectively ; all P\0.05), and with individual components of insulin resistance, most notably WHR. In a multiple logistic regression model adjusted according to age, sex, duration of diabetes and BMI, increased levels of AST, ALT and ALK resulted in an increased risk for the development of insulin resistance in our subjects (OR = 1.03, 1.02, and 1.01, respectively ; all P\0.05). These findings indicate that higher levels of ALT, AST and ALK are additional markers of insulin resistance in type 1 diabetes and suggest that those subjects must be considered as potentially affected not only by a hepatic but also by a multisystemic disease through altered insulin sensitivity.

Influence of weathering processes on the shear strength of siltstones from a flysch rock mass along the northern Adriatic coast of Croatia

Abstract: Weathering processes cause significant changes in the engineering properties of rocks. Slope instability in flysch rock formations along the northern Adriatic coast of Croatia is related to the effects of weathering on the shear strength of siltstones from the flysch rock mass. Therefore, changes in geotechnical properties according to weathering grade are of immense importance in relation to instability processes. In this work, we investigated siltstones from flysch rock masses in the study area, and evaluated changes in engineering properties due to weathering. The research began with field observations and determination of the strength of different weathering grades of siltstones in the area. Mineralogical and laboratory studies were subsequently conducted, and mineral content was determined for siltstones of different weathering grades. We also performed a series of drying–wetting cycles to simulate natural conditions of the weathering process involved in the disintegration of the rock material into sand-sized and smaller particles. This weathering process resulted in disintegration of the siltstone rock mass into smaller particles that were not a unique rock block, with the soil-like material consisting of unbound particles of rock. Laboratory tests were also carried out on the soil-like material to determine the specific gravity, grain size distribution, Atterberg limits and residual shear strength for the different weathering grades of siltstones. Based on this research, we determined the changes in engineering properties for different weathering grades. Our results underscore the significant influence of the weathering process on mineral content, cation exchange capacity, liquid limit and residual shear strength, thus affecting slope stability in siltstones in flysch rock masses.

The Guidelines for Modelling the Preloading Bolts in the Structural Connection Using Finite Element Methods

Abstract: The aim of this paper is the development of the two different numerical techniques for the preloading of bolts by the finite element method using the software Abaqus Standard. Furthermore, this paper gave detailed guidelines for modelling contact, method for solving the numerical error problems such as numerical singularity error and negative eigenvalues due to rigid body motion or the problem of the extensive elongation of bolts after pretension which is occurring during the analysis. The behaviour of bolted joints depending on the two different approaches of pretension was shown on the example of an extended end-plate bolted beam-to-column connection under the monotonic loading. The behaviour of beam-to-column connection was shown in the form and moment-rotation ( - ) curves and validated by experimental test. Advantages and disadvantages of pretension techniques, as well as the speed of numerical models, were also presented in this paper.

Decision Support System to Urban Infrastructure Maintenance Management

Abstract: Life-cycle management of urban infrastructure projects is very complex process from both management and economic aspects. Focus of this research is on urban infrastructure maintenance phase of a life-cycle, especially on decision making in maintenance problems. Urban infrastructure maintenance management deals with complex decision making process. The reasons for a complexity are: lots of participants, multi- disciplinarity, huge quantity of information, limited budget, conflict goals and criteria. These facts indicate that decision making processes in urban infrastructure management undoubtedly belong to ill-defined problems. In order to cope with such complexity and to help project managers during decision making processes this research proposes an application of multicriteria methods. Multicriteria methodology proposed herein is applied on priority setting problem. It starts with goal analysis followed by definition of urban infrastructure elements and development of adequate criteria set. Evaluation of criteria importance (weights) is based on a set of experts’ opinions processed by AHP method. An assessment of maintenance conditions of urban infrastructure elements is provided trough monitoring process. The way of using proper forms and procedures for data collection is presented as well. All collected data are processed by PROMETHEE multicriteria methods. The main result of a multicriteria process is priority maintenance list for urban infrastructure elements. The methodology is tested on road infrastructure of town of Split.

Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review.

Abstract: COVID-19 is one of the greatest challenges humanity has faced recently, forcing a change in the daily lives of billions of people worldwide. Therefore, many efforts have been made by researchers across the globe in the attempt of determining the models of COVID-19 spread. The objectives of this review are to analyze some of the open-access datasets mostly used in research in the field of COVID-19 regression modeling as well as present current literature based on Artificial Intelligence (AI) methods for regression tasks, like disease spread. Moreover, we discuss the applicability of Machine Learning (ML) and Evolutionary Computing (EC) methods that have focused on regressing epidemiology curves of COVID-19, and provide an overview of the usefulness of existing models in specific areas. An electronic literature search of the various databases was conducted to develop a comprehensive review of the latest AI-based approaches for modeling the spread of COVID-19. Finally, a conclusion is drawn from the observation of reviewed papers that AI-based algorithms have a clear application in COVID-19 epidemiological spread modeling and may be a crucial tool in the combat against coming pandemics.