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Institution

University of Zagreb

EducationZagreb, Grad Zagreb, Croatia
About: University of Zagreb is a education organization based out in Zagreb, Grad Zagreb, Croatia. It is known for research contribution in the topics: Population & European union. The organization has 21769 authors who have published 50267 publications receiving 783239 citations. The organization is also known as: Zagreb University & Sveučilište u Zagrebu.


Papers
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Journal ArticleDOI
01 Dec 2018-Energy
TL;DR: It is quantified how benefits exceed costs by a safe margin with the benefits of systems integration being the most important.

373 citations

Journal ArticleDOI
TL;DR: It is found that, depending on specific growth protocols, the spatial extension of the high-mobility electron gas can be varied from hundreds of micrometres into SrTiO(3) to a few nanometres next to the LaAlO( 3)/SrTiO (3) interface.
Abstract: At the interface between complex insulating oxides, novel phases with interesting properties may occur, such as the metallic state reported in the LaAlO(3)/SrTiO(3) system . Although this state has been predicted and reported to be confined at the interface, some studies indicate a much broader spatial extension, thereby questioning its origin. Here, we provide for the first time a direct determination of the carrier density profile of this system through resistance profile mappings collected in cross-section LaAlO(3)/SrTiO(3) samples with a conducting-tip atomic force microscope (CT-AFM). We find that, depending on specific growth protocols, the spatial extension of the high-mobility electron gas can be varied from hundreds of micrometres into SrTiO(3) to a few nanometres next to the LaAlO(3)/SrTiO(3) interface. Our results emphasize the potential of CT-AFM as a novel tool to characterize complex oxide interfaces and provide us with a definitive and conclusive way to reconcile the body of experimental data in this system.

371 citations

Journal ArticleDOI
TL;DR: A systematic review of published evidence related to the safety and health effects of the administration of formula supplemented with probiotics and/or prebiotics compared with unsupplemented formulae is presented in this article.
Abstract: Infant formulae are increasingly supplemented with probiotics, prebiotics, or synbiotics despite uncertainties regarding their efficacy. The present article, developed by the Committee on Nutrition of the European Society for Paediatric Gastroenterology, Hepatology, and Nutrition, systematically reviews published evidence related to the safety and health effects of the administration of formulae supplemented with probiotics and/or prebiotics compared with unsupplemented formulae. Studies in which probiotics/prebiotics were not administered during the manufacturing process, but thereafter, for example in capsules, the contents of which were supplemented to infant formula or feeds, were excluded.On the basis of this review, available scientific data suggest that the administration of currently evaluated probiotic- and/or prebiotic-supplemented formula to healthy infants does not raise safety concerns with regard to growth and adverse effects. The safety and clinical effects of 1 product should not be extrapolated to other products. At present, there is insufficient data to recommend the routine use of probiotic- and/or prebiotic-supplemented formulae. The Committee considers that the supplementation of formula with probiotics and/or prebiotics is an important field of research. There is a need in this field for well-designed and carefully conducted randomised controlled trials, with relevant inclusion/exclusion criteria and adequate sample sizes. These studies should use validated clinical outcome measures to assess the effects of probiotic and/or prebiotic supplementation of formulae. Such trials should also define the optimal doses and intake durations, as well as provide more information about the long-term safety of probiotics and/or prebiotics. Because most of the trials were company funded, independent trials, preferentially financed jointly by national/governmental/European Union bodies and other international organisations, would be desirable.

370 citations

Journal ArticleDOI
TL;DR: In this article, the authors generalize the result of Baker and Davenport and prove that the Diophantine pair {1, 3, 8, d} cannot be extended to infinitely many Diophantus quadruples.
Abstract: The Greek mathematician Diophantus of Alexandria noted that the rational numbers 1 16 , 33 16 , 17 4 and 105 16 have the following property: the product of any two of them increased by 1 is a square of a rational number (see [4]). The first set of four positive integers with the above property was found by Fermat, and it was {1, 3, 8, 120}. A set of positive integers {a1, a2, . . . , am} is said to have the property of Diophantus if aiaj +1 is a perfect square for all 1 ≤ i < j ≤ m. Such a set is called a Diophantine m-tuple (or P1-set of size m). In 1969, Baker and Davenport [2] proved that if d is a positive integer such that {1, 3, 8, d} is a Diophantine quadruple, then d has to be 120. The same result was proved by Kanagasabapathy and Ponnudurai [9], Sansone [12] and Grinstead [7]. This result implies that the Diophantine triple {1, 3, 8} cannot be extended to a Diophantine quintuple. In the present paper we generalize the result of Baker and Davenport and prove that the Diophantine pair {1, 3} can be extended to infinitely many Diophantine quadruples, but it cannot be extended to a Diophantine quintuple.

368 citations

Journal ArticleDOI
TL;DR: Two important improvements to the SVR based load forecasting method are introduced, i.e., procedure for generation of model inputs and subsequent model input selection using feature selection algorithms and the use of the particle swarm global optimization based technique for the optimization of SVR hyper-parameters reduces the operator interaction.
Abstract: This paper presents a generic strategy for short-term load forecasting (STLF) based on the support vector regression machines (SVR). Two important improvements to the SVR based load forecasting method are introduced, i.e., procedure for generation of model inputs and subsequent model input selection using feature selection algorithms. One of the objectives of the proposed strategy is to reduce the operator interaction in the model-building procedure. The proposed use of feature selection algorithms for automatic model input selection and the use of the particle swarm global optimization based technique for the optimization of SVR hyper-parameters reduces the operator interaction. To confirm the effectiveness of the proposed modeling strategy, the model has been trained and tested on two publicly available and well-known load forecasting data sets and compared to the state-of-the-art STLF algorithms yielding improved accuracy.

367 citations


Authors

Showing all 22096 results

NameH-indexPapersCitations
Harry Campbell150897115457
Joseph R. Ecker14838194860
Igor Rudan142658103659
Nikola Godinovic1381469100018
Ivica Puljak134143697548
Damir Lelas133135493354
Željko Ivezić12934484365
Piotr Ponikowski120762131682
Marin Soljacic11776451444
Ivan Dikic10735952088
Ozren Polasek10243652674
Mordechai Segev9972940073
Srdan Verstovsek96104538936
Segev BenZvi9548232127
Mirko Planinic9446731957
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023119
2022529
20213,277
20203,360
20193,176
20183,042