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71.
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73.
Influence of Fe-Content on Visible Light Photoactivity of Bi-Pyrochlores
Matjaž Valant, Benčina Metka, 2017, objavljeni povzetek znanstvenega prispevka na konferenci (vabljeno predavanje)

Ključne besede: piroklori, fotokatalizatorji, rekombinacija
Objavljeno: 20.07.2017; Ogledov: 488; Prenosov: 0
.pdf Polno besedilo (1,35 MB)

74.
75.
Host cell sorting machinery facilitates human papillomavirus trafficking
Martina Bergant Marušič, predavanje na tuji univerzi

Ključne besede: human papillomaviruses, trafficking, sorting nexins
Objavljeno: 20.07.2017; Ogledov: 458; Prenosov: 0
.pdf Polno besedilo (139,61 KB)

76.
HAIR CORTISOL LEVEL IN THE GOLDEN JACKAL (CANIS AUREUS MOREOTICUS I. GEOFFROY SAINT HILAIRE, 1835) IN RELATION TO THE SAMPLE CONSERVATION, SEX AND ECOLOGICAL CHARACTERISTICS.
Stefano Filacorda, Veronica Maran, Tanja Peric, Stefano Pesaro, Marta Montillo, 2017, objavljeni povzetek znanstvenega prispevka na konferenci

Opis: Hair cortisol analysis is a complementary method for monitoring HPA axis activity, capturing systemic cortisol exposure over longer periods of time. We have tested the hair cortisol concentration on 16 specimens of Golden jackal (Canis aureus moreoticus): 5 from frozen animals, 10 from stuffed animals and 1 taken from injured animal during recovery in an Animal Care Center; the samples came from Italy (Friuli Venezia Giulia and Veneto Region) and Croatia (Istria and Dalmatian region). We have studied the hair cortisol concentration by RIA method in respect to conservation method, sex and areas of origin, with non parametric tests and mixed model. The hair cortisol concentration (values expressed in pg/mg) from the frozen animals (mean=3.38 SD=3.13, n=5) was not different in respect to the stuffed samples (mean=2.81 SD=2.72, n=9), also the sex has not showed any statistical effect (males mean=1.96 SD=0.63 n=9; females mean=4.56 SD=3.99 n=6). The hair cortisol concentration in respect to the sites of origin of samples, dispersal and core areas was not different (dispersal areas: mean=1.56 SD=0.77 n=5, core areas: mean=3.72 SD=3.14 n=10). The use of mixed model to detect the effect of areas (core and dispersal areas) and interaction between sex and areas has showed the presence of significative higher hair concentrations of cortisol in core areas for the females (mean=6.27 SD=3.84 n=4)in respect to the males (mean=2.02 SD=0.52 n=6). The concentration of hair cortisol of sick and injured animal recovered in the Animal Care Center was higher (> of 12 pg/mg) in respect to the other samples. Hair sample can be used to develop a clearer understanding of the interrelationship of health and physiology, mobility and social behaviour.
Ključne besede: hair, Canis aureus, cortisol
Objavljeno: 19.07.2017; Ogledov: 563; Prenosov: 0
.pdf Polno besedilo (1,91 MB)

77.
Something other than wh-words survives sluicing in Slovenian. What else?
Petra Mišmaš, Franc Marušič, Vesna Plesničar, Tina Šuligoj, 2017, objavljeni povzetek znanstvenega prispevka na konferenci

Ključne besede: sluicing, discourse particles, left periphery, Slovenian, syntax
Objavljeno: 19.07.2017; Ogledov: 237; Prenosov: 0
.pdf Polno besedilo (236,20 KB)

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79.
ECOLOGY OF WILD WINE YEASTS AND THEIR ENOLOGICAL POTENTIAL
Gabrijel Cernigoi, 2017, diplomsko delo

Opis: The aim of the study was to investigate and select indigenous yeasts Saccharomyces cerevisiae and non-conventional yeasts that were isolated during this and previous studies, and than evaluate them for wine production by performing micro-scale vinification experiment
Ključne besede: Saccharomyces, non-conventional yeasts, wine, fermentations
Objavljeno: 17.07.2017; Ogledov: 360; Prenosov: 30
.pdf Polno besedilo (1,09 MB)

80.
Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms
Johannes Fuernkranz, Nada Lavrač, Dragan Gamberger, 2010, samostojni znanstveni sestavek ali poglavje v monografski publikaciji

Opis: Features are the main rule building blocks for rule learning algorithms. They can be simple tests for attribute values or complex logical terms representing available domain knowledge. In contrast to common practice in classification rule learning, we argue that separation of the feature construction and rule construction processes has theoretical and practical justification. Explicit usage of features enables a unifying framework of both propositional and relational rule learning and we present and analyze procedures for feature construction in both types of domains. It is demonstrated that the presented procedure for constructing a set of simple features has the property that the resulting set enables construction of complete and consistent rules whenever it is possible, and that the set does not include obviously irrelevant features. Additionally, the concept of feature relevancy is important for the effectiveness of rule learning. It this work, we illustrate the concept in the coverage space and prove that the relative relevancy has the quality-preserving property in respect to the resulting rules. Moreover, we show that the transformation from the attribute to the feature space enables a novel, theoretically justified way of handling unknown attribute values. The same approach enables that estimated imprecision of continuous attributes can be taken into account, resulting in construction of robust features in respect to this imprecision.
Ključne besede: Machine learning, Feature construction, Rule learning, Unknown attribute values
Objavljeno: 14.07.2017; Ogledov: 272; Prenosov: 0
.pdf Polno besedilo (365,76 KB)

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