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.

Determinants and public policy implications of academic-industry knowledge transfer in life sciences: a review and a conceptual framework

Abstract: There is a considerable interest of scholars in benefits and challenges arising from involvement of academic researchers and their institutions in knowledge transfer activities with the business sector. The emerging questions have resulted in a number of studies, yielding rich but mixed findings. The purpose of this paper is to systematically review this body of investigative work, with a particular emphasis on life sciences. Based on the systematic analysis and synthesis of 135 articles published between 1980 and 2014, we discuss the most interesting findings for each of the six identified principal academic-industry research topics: involvement predictors and motivators, role of incentives, institutional performance determinants, knowledge transfer institutionalization, relationship with scientific output and impact on open science. Whereas many studies reach consensus regarding the particular personal and contextual predictors of researchers’ knowledge transfer involvement, we also find substantial evidence that depending on empirical setting, variables such as scientific productivity and institutional technology transfer support policies can act both as enablers and inhibitors in the process. We find no straightforward evidence regarding the role of the size, age and structure of technology transfer offices in the knowledge transfer performance of academic institutions. We also show that most studies agree that engagement in knowledge transfer activities does not negatively affect the researchers’ scientific output. Yet, it is less clear to what extent university-industry interactions can be detrimental for the norms of open science. We draw several policy implications for academic settings and emphasize interesting avenues for further research in this field.

Turbogenerator Steam Turbine Variation in Developed Power: Analysis of Exergy Efficiency and Exergy Destruction Change

Abstract: Developed power variation of turbogenerator (TG) steam turbine, which operates at the conventional LNG carrier, allows insight into the change in turbine exergy efficiency and exergy destruction during the increase in turbine power. Measurements of required operating parameters were performed in eight different TG steam turbine operating points during exploitation. Turbine exergy efficiency increases from turbine power of 500 kW up to 2700 kW, and maximum exergy efficiency was obtained at 70.13% of maximum turbine developed power (at 2700 kW) in each operating point. From turbine developed power of 2700 kW until the maximum power of 3850 kW, exergy efficiency decreases. Obtained change in TG turbine exergy efficiency is caused by an uneven intensity of increase in turbine developed power and steam mass flow through the turbine. TG steam turbine exergy destruction change is directly proportional to turbine load and to steam mass flow through the turbine—higher steam mass flow results in a higher turbine load which leads to the higher exergy destruction and vice versa. The higher share of turbine developed power and the lower share of turbine exergy destruction in the TG turbine exergy power inlet lead to higher turbine exergy efficiencies. At each observed operating point, turbine exergy efficiency in exploitation is lower when compared to the maximum obtained one for 8.39% to 12.03%.

Stochastic Model of Financial Markets Reproducing Scaling and Memory in Volatility Return Intervals

Abstract: We investigate the volatility return intervals in the NYSE and FOREX markets. We explain previous empirical findings using a model based on the interacting agent hypothesis instead of the widely-used efficient market hypothesis. We derive macroscopic equations based on the microscopic herding interactions of agents and find that they are able to reproduce various stylized facts of different markets and different assets with the same set of model parameters. We show that the power-law properties and the scaling of return intervals and other financial variables have a similar origin and could be a result of a general class of non-linear stochastic differential equations derived from a master equation of an agent system that is coupled by herding interactions. Specifically, we find that this approach enables us to recover the volatility return interval statistics as well as volatility probability and spectral densities for the NYSE and FOREX markets, for different assets, and for different time-scales. We find also that the historical S&P500 monthly series exhibits the same volatility return interval properties recovered by our proposed model. Our statistical results suggest that human herding is so strong that it persists even when other evolving fluctuations perturbate the financial system.

Earthquake in the time of COVID-19: The story from Croatia (CroVID-20).

Abstract: www.jogh.org • doi: 10.7189/jogh.10.010349 1 June 2020 • Vol. 10 No. 1 • 010349 On the hundredth day since the WHO was notified of the first cases of “pneumonia with unknown cause” in China, the COVID-19 pandemic, caused by SARS-CoV-2, has spread throughout the world to 195 countries with over 1.5 million cases and more than 85 000 deaths [1]. In early January, when we had just learned that a newly discovered disease was spreading in faraway China, only a few thought it would soon be coming to Croatia. Nevertheless, by February, when the epidemic was rapidly spreading in northern Italy, it was already quite likely that it would not bypass Croatia, and on 25 February 2020 the first case of COVID-19 was registered in our country [2].

Lipid Classes and Fatty Acid Composition of Diplodus vulgaris and Conger conger Originating from the Adriatic Sea

Abstract: Lipid classes and fatty acid composition of polar (phosphatidylethanolamine, phosphatidylcholine, phosphatidylinositol, phosphatidylserine) and neutral (triglycerides) lipid fractions of common two-banded seabream (Diplodus vulgaris, L.) and sea eel (Conger conger, L.) originating from the Adriatic Sea (the [ibenik basin) were determined. Total lipid content in C. conger (3.7 ± 0.2 %) was almost three times higher than in D. vulgaris (1.3 ± 0.2 %). Polar lipids in D. vulgaris were almost twice as high (28.1 ± 4.2 %) as in C. conger (15.5 ± 0.2 %). Neutral lipids were present in higher proportions (71.9 ± 4.2 %) in D. vulgaris and (84.5 ± 0.2 %) in C. conger. The fatty acid composition of triglycerides was much more complex than those of polar lipid fractions. There were 25 identified fatty acids in Diplodus vulgaris and 23 identified fatty acids in Conger conger muscle tissue samples. Palmitic (16:0, 20.3–63.9 %), stearic (18:0, 5.5–58.7 %) and oleic (18:1 n-9c, 3.8–23.1 %) acid were the most abundant fatty acids in both analysed fish species, but their amounts differed significantly. Appreciable quantities of docosahexaenoic acid (DHA 22:6 n-3, 0.5–15.4 %), eicosapentaenoic acid (EPA 20:5 n-3, 1.2–5.3 %), arachidonic acid (20:4 n-6, 0.7–7.8 %) and tetracosaeonic acid (24:1 n-9, 0.7–4.8 %) were also found. EPA + DHA values were much higher in the Conger conger lipid fractions in comparison with Diplodus vulgaris lipid fractions, except for phosphatidylethanolamine. Our study points out that both fish species contain appreciable levels of n-3 polyunsaturated fatty acids and would therefore be suitable for highly unsaturated low-fat diets.